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results for Manufacturing for Georgia
Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation61
Mapping the economic potential in Manu-
facturing: results for Moldova
Results of the economic mapping for Moldova are
shown in Table 2.12. In total, 5 manufacturing in-
dustries have been identified as having a current
strength and only one manufacturing industry has
been identified as having an emerging strength
(these industries are highlighted in the two col-
umns with an ‘X’ in a green-coloured cell).Industries with current strength include Pro-
cessing/preserving of fish, etc. (102); Manufacture
of textiles (13); Manufacture of wearing apparel
(14); Manufacture of leather and related products
(15); and Furniture (310). Industries with emerg-
ing strength include Manufacture of chemicals
and chemical products (20).
Employ-
mentTurnoverEmploy-
ment &
turnoverEmploy-
mentTurnoverEmploy-
ment &
turnover
Current Current Current Emerging Emerging Emerging
7 10 5 1 7 1
101 Processing/preserving of meat X
102 Processing/preserving of fish, etc. X X X
103 Processing/preserving of fruit, vegetables X
104 Vegetable and animal oils and fats X X
106Grain mill products, starches and starch
products X
13 Manufacture of textiles X X X
14 Manufacture of wearing apparel X X X
15Manufacture of leather and related
productsX X X
16Manufacture of wood and of products
of wood and cork, except furniture;
manufacture of articles of straw and
plaiting materials X
19Manufacture of coke and refined
petroleum products X
20Manufacture of chemicals and chemical
products X X X
22Manufacture of rubber and plastic
products X
25Manufacture of fabricated metal
products, except machinery and
equipment X
26Manufacture of computer, electronic and
optical products X
27 Manufacture of electrical equipment X
28Manufacture of machinery and equipment
n.e.c. X
29Manufacture of motor vehicles, trailers
and semi-trailersX
310 Furniture X X X
n.e.c. = not elsewhere classifiedTable 2.12. Economic mapping results for Manufacturing for Moldova
62
Part 2 Analysis of economic and innovation potential
Mapping the economic potential in Manu-
facturing – results for Ukraine
Results of the economic mapping for Ukraine are
shown in Table 2.13. In total, 5 manufacturing
industries have been identified as having a cur-
rent strength and 4 manufacturing industries have
been identified as having an emerging strength
(these industries are highlighted in the two col-
umns with an ‘X’ in a green-coloured cell).
Industries with current strength include Vege-
table and animal oils and fats (104); Manufacture of basic metals (24); Manufacture of | [
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] | [] |
of
exportsEmerging
strength% share
of
exports
18 60.9% 26 47.9%
0 Food and live animals
001 Live animals other than animals of division 03 X 1.8%
056 Vegetables, roots and tubers, prepared or preserved, n.e.s. X 0.2%
058Fruit, preserved, and fruit preparations (excluding fruit
juices) X 0.4%
075 Spices X 0.3% X 0.3%
098 Edible products and preparations, n.e.s. X 0.2%
1 Beverages and tobacco
111 Non-alcoholic beverages, n.e.s. X 4.4% X 4.4%
112 Alcoholic beverages X 9.0% X 9.0%
2 Crude materials, inedible, except fuels
283Copper ores and concentrates; copper mattes; cement
copperX 11.4% X 11.4%
288 Non-ferrous base metal waste and scrap, n.e.s. X 1.3%
289Ores and concentrates of precious metals; waste, scrap and
sweepings of precious metals (other than of gold) X 0.3%
3 Mineral fuels, lubricants and related materials
333Petroleum oils and oils obtained from bituminous minerals,
crude X 1.3%
334Petroleum oils and oils obtained from bituminous minerals
(other than crude); preparations, n.e.s., containing by weight
70% or more of petroleum oils or of oils obtained from
bituminous minerals, these oils being the basic constituents
of the preparations; waste oils X 0.6%
351 Electric current X 0.8%Table 2.18. Goods export specialisation for Georgia
70
Part 2 Analysis of economic and innovation potential
SITC Goods nameCurrent
strength% share
of
exportsEmerging
strength% share
of
exports
18 60.9% 26 47.9%
4 Animal and vegetable oils, fats and waxes
411 Animal oils and fats X 0.2%
5 Chemicals and related products, n.e.s.
522 Inorganic chemical elements, oxides and halogen salts X 0.3% X 0.3%
523 Salts and peroxysalts, of inorganic acids and metals X 0.6%
541Medicinal and pharmaceutical products, other than
medicaments of group 542X 0.4%
542 Medicaments (including veterinary medicaments) X 4.1% X 4.1%
553Perfumery, cosmetic or toilet preparations (excluding
soaps)X 0.6% X 0.6%
6 Manufactured goods classified chiefly by material
625Rubber tyres, interchangeable tyre treads, tyre flaps and
inner tubes for wheels of all kindsX 0.8% X 0.8%
671Pig-iron, spiegeleisen, sponge iron, iron or steel granules
and powders and ferro-alloysX 9.5% X 9.5%
672Ingots and other primary forms, of iron or steel; semi-
finished products of iron or steel X 1.0%
679Tubes, pipes and hollow profiles, and tube or pipe fittings,
of iron or steel X 0.4%
684 Aluminium X 0.3%
699 Manufactures of base metal, n.e.s. X 0.2%
7 Machinery and transport equipment
723Civil engineering and contractors' plant and equipment;
parts thereofX 0.3% X 0.3%
778 Electrical | [
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" \n",
"333Petroleum",
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"bituminous",
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",",
"\n",
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" ",
"X",
"1.3",
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"(",
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" ",
"X",
"0.8%Table",
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"Goods",
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"specialisation",
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"Georgia",
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"70",
"\n ",
"Part",
"2",
"Analysis",
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"economic",
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"innovation",
"potential",
"\n",
"SITC",
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"\n",
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"\n",
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"\n",
"strength%",
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"\n",
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"18",
"60.9",
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"411",
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"X",
"0.2",
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" \n",
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"n.e.s",
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"0.3",
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"X",
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"4.1",
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"553Perfumery",
",",
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"(",
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"0.6",
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"X",
"0.6",
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"6",
"Manufactured",
"goods",
"classified",
"chiefly",
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"material",
" \n",
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"interchangeable",
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"flaps",
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"\n",
"inner",
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"1.0",
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"hollow",
"profiles",
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"fittings",
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" ",
"X",
"0.4",
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"684",
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"X",
"0.3",
"%",
"\n",
"699",
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"base",
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",",
"n.e.s",
".",
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"X",
"0.2",
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"723Civil",
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"contractors",
"'",
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";",
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"parts",
"thereofX",
"0.3",
"%",
"X",
"0.3",
"%",
"\n",
"778",
"Electrical"
] | [] |
patents.
Azerbaijan has the following two: for the ‘Oil and
Gas Production and Transportation’ cluster, the
S&T domains Chemistry and chemical engineer-
ing, Energy and Nanotechnology and materials
could be aligned with the E&I domain Manufac-
ture of coke and refined petroleum products. For
the ‘Chemical Products’ cluster, the S&T domains
Chemistry and chemical engineering and Nano-
technology and materials could again be matched
with the E&I domains. In this case, further con-
cordances could be also found with the Agrifood
and Biotechnology S&T domains. For all S&T do-
mains except for Agrifood, the concordances were
produced by both patents and publications.
Georgia has two concordances: for the ‘Food
Processing and Manufacturing’ cluster, the Agri-
food S&T domain could be aligned with the man-
ufacturing of food and beverages E&I domains
through both patents and publications. For the
‘Metalworking Technology’ cluster, the Nano-
technology and materials S&T domain could be
matched with the Manufacture of fabricated met-
al products E&I domain.
Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation251
Moldova has four concordances: for the econom-
ic cluster ‘Food Processing & Manufacturing’, the
Agrifood S&T domain could be matched with the
corresponding food and beverage manufactur-
ing E&I domains. The concordance was triggered
by both patents and publications. For the ‘Wood
Products’ cluster, a concordance was obtained be-
tween the respective E&I domain and the Chem-
istry and chemical engineering. For the cluster
‘Chemical Products’, a concordance between the
E&I domain Manufacture of chemicals and chem-
ical products and the Biotechnology, Chemistry
and chemical engineering and Nanotechnology
and materials S&T domains could be found. In all
cases, the concordance is produced by both pat-
ent and publications and seems to be satisfactory.
For the cluster ‘Communications Equipment and
Services’, a reasonable concordance between the
Telecommunications E&I domain and the ICT and
computer science S&T domain could be identified.
The concordance is, in this case, produced by pub-
lications only.
Ukraine, having the largest number of S&T re-
cords, has the following five concordances: in the
cluster ‘Food Processing and Manufacturing’, the
S&T domain Agrifood could be aligned with the
Manufacture of food products E&I domain. The
concordance was produced by both publications
and patents. In the ‘Metalworking Technology’
cluster, a concordance could be produced between
the Nanotechnology and materials S&T domain
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Grünthal, G., Thieken, A. H., Schwarz, J., Radtke, K. S., Smolka,
A., and Merz, B.: Comparative risk assessment for the city of
Cologne-storms, floods, earthquake, Nat. Hazards, 38, 21–44,
2006.
Haasnoot, M., Kwakkel, J. H., Walker, W. E., and ter Maat, J.: Dy-
namic adaptive policy pathways: A method for crafting robust
decisions for a deeply uncertain world, Global Environ. Change,
23, 485–498, https://doi.org/10.1016/j.gloenvcha.2012.12.006,
2013.
Hak, T., van Rhee, H., and Suurmond, R.: How to interpret results
of meta-analysis, SSRN, https://doi.org/10.2139/ssrn.3241367,
2016.
Han, J., Wu, S., and Wang, H.: Preliminary study on geo-
logical hazard chains, Earth Science Frontiers, 14, 11–20,
https://doi.org/10.1016/S1872-5791(08)60001-9, 2007.
Hansjürgens, B. and Antes, R.: Economics and management of cli-
mate change: risks, mitigation and adaptation, Springer, Berlin,
Heidelberg, https://doi.org/10.1007/978-3-540-77658-5, 2008.
Nat. Hazards Earth Syst. Sci., 25, 287–304, 2025 https://doi.org/10.5194/nhess-25-287-2025T.-E. Antofie et al.: Spatial identification of regions exposed to multi-hazards at pan-European level 303
IPCC: Managing the risks of extreme events and disasters to ad-
vance climate change adaptation. A special report of work-
ing groups I and II of the intergovernmental panel on climate
change, Cambridge University Press, Cambridge, ISBN 978-1-
107-02506-6, 2012.
ISO: ISO 3166-1 – Codes for the representation of names of coun-
tries and their subdivisions – Part 1: Country codes, International
Organization for Standardization, Geneva, Switzerland, https://
www.iso.org/obp/ui/en/#iso:std:iso:3166:-1:ed-4:v1:en (last ac-
cess: 17 January 2025), 2020.
Jelinski, D. E. and Wu, J.: The modifiable areal unit problem and
implications for landscape ecology, Landscape Ecol., 11, 129–
140, 1996.
Kappes, M. S., Keiler, M., and Glade, T.: From single- to multi-
hazard risk analyses: a concept addressing emerging challenges,
in: Mountain Risks: Bringing Science to Society, edited by:
Malet, J. P., Glade, T., and Casagli, N., CERG Editions, Stras-
bourg, France, 351–356, ISBN 2-9518317-1-5, 2010.
Kappes, M. S., Frigerio, S., and Malet, J. P.: Multi-hazard expo-
sure analyses with multirisk – a platform for user-friendly anal-
ysis, 12th Congress INTERPRAEVENT, April 2012, Grenoble,
France, 487–495, 2012a.
Kappes, M. S., Gruber, K., Frigerio, S., Bell, R., Keiler, M.,
and Glade, T.: The multirisk platform: the technical con-
cept and application of a regional scale multihazard ex-
posure analysis tool, Geomorphology, 151–152, 139–155,
https://doi.org/10.1016/j.geomorph.2012.01.024, 2012b.
Kappes, M. S., Keiler, M., von Elverfeldt, K., and Glade, T.: Chal-
lenges of analyzing multi-hazard risk: a review, Nat. Hazards, 64,
1925–1958, 2012c.
Koks, E. E., Rozenberg, J., Zorn, C., Tariverdi, M., V ousdoukas,
M., Fraser, S. A., Hall, J. W., and Hallegatte, S.: A global multi-
hazard risk analysis of road and railway infrastructure assets,
Nat. Commun., 10, 2677, https://doi.org/10.1038/s41467-019-
10442-3, 2019. | [
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minimize the
MAUP effect, recommended practices focus on using smaller
areal unit (e.g. LAUs rather than provinces or countries) for
data aggregation (Kwan, 2012). This reduces the potential
errors in spatial pattern distortion without entirely removing
them.
2.1.2 Input hazard and exposure data
The exposure data are built on the relationship between haz-
ard (i) and assets (ii): exposure or assets at risk Df(assets,
hazard). We overlay spatial information about residential
built-up areas and population with data describing hazard ar-
eas in order to define the assets exposed to single hazards.
We then aggregate the exposure at the level of LAUs. We
identify statistically significant hotspots of asset exposure to
single hazards through the application of two distinct expo-
sure aggregation methods:
–based on absolute values, the sum of the exposed asset;
–based on relative values, as ratios or share of the expo-
sure from the total assets in LAUs.
For the exposure to earthquakes, due to the continuous
spatial extent of the hazard area, we depict the relative ag-
gregation schema using the density (or share of the exposure
compared to the total area of the LAUs). The relative aggre-
gation schema intends to address risk management strategies
based on cost-efficient measures, while the absolute schema
supports risk management strategies that prioritize the most
affected areas and people.
(i) Hazard layers. The hazard layers considered in this study
represent areal extension rather than intensity. We use not a
probabilistic assessment but rather a deterministic approach,
selecting hazards with average temporal (frequency of oc-
currence) and spatial probability (susceptibility). The hazard
datasets used here and their characteristics are presented in
Table 1. The motivations for their selection along with their
usage in disaster risk assessments are detailed in the sections
dedicated to individual hazards in the Supplement (Sect. S1
– “Hazard layers and their definitions”).
(ii) Asset layers. As asset layers, we use the residential built-
up areas from the European Settlement Map (ESM) (Flor-
https://doi.org/10.5194/nhess-25-287-2025 Nat. Hazards Earth Syst. Sci., 25, 287–304, 2025290 T.-E. Antofie et al.: Spatial identification of regions exposed to multi-hazards at pan-European level
Figure 1. Different steps of the methodological approach developed in this study.
Figure 2. Local administrative unit areas (km2): spatial distribution (a)and mean LAU area per country (b). The abbreviations for countries
shown in the figures follow the ISO 3166-1 alpha-2 standard (ISO, 2020).
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defence R&I – that will
be undersupplied without common action and funding. Finally, for Member States to converge more closely in their
policies – be it the Single Market or more generally in the policies described in this report such as climate, innova -
tion, defence, space and education – both regulation and incentives will be required. Incentives will also require
common funding. However, if the strategy is not fully implemented and productivity growth does not pick up, a
broader issuance of public debt may be needed to make the funding of the transitions a more realistic proposition.
The issuance of common safe assets to fund joint investment projects could follow existing templates –
however, it would have to be accompanied by all the safeguards that such a fundamental step would entail .
The use of a common safe asset has a well-established precedent in the funding of the NGEU. The present circum -
stances are equally serious, even if less dramatic. But issuing such assets on a more systematic basis would require
a stronger set of fiscal rules which ensure that an increase in common debt is matched by a more sustainable path
of national debt. In this way, all EU Member States could contribute to such an asset without prejudging the sustain -
ability of their public debt. Issuance would also have to remain mission and project-specific.
MOBILISING PRIVATE AND PUBLIC FINANCE AT SCALE
To unlock private capital, the EU must build a genuine Capital Markets Union (CMU) supported by a stronger
pension system . As a key pillar of the CMU, the European Securities and Markets Authority (ESMA) should transi -
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similar to the US Securities and Exchange Commission. An essential step to transform ESMA into such an agency is
modify its governance and decision-making processes along similar lines as those of the ECB Governing Council,
detaching them as much as possible from the national interests of EU Member States. Harmonising insolvency
frameworks will also be critical to remove fragmentation created by differing creditor hierarchies, while the EU should
continue to eliminate taxation obstacles to cross-border investing. These measures would in turn make it easier to
foster centralisation in clearing and settlement. Ultimately, the EU should aim to create a single central counter -
party platform (CCP) and a | [
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and cork
181_Printing and service activities related to printing
19_Coke and refined petroleum products
210_Pharmaceuticals, medicinal chemicals, etc.
23_Other non-metallic mineral products
25_Fabricated metal products
27_Electrical equipment
29_Motor vehicles, trailers and semi-trailers
310_Furniture
33_Repair and installation of machinery and equipmentMethodology
The methodology used to analyse INDSTAT data
is slightly different to that presented in Section
2.1 as data are less recent and the total number
of analysed industries is much smaller. Aggregate
industry-level data have been used to identify two
types of industries:
■industries with a current strength, includ-
ing specialised industries with critical mass,
where the degree of specialisation and rela-
tive size for both the number of employees
and turnover are above predefined thresholds;
■industries with an emerging strength, in-
cluding emerging industries with increasing
degrees of specialisation, where the change
in the degree of specialisation for both the
number of employees and turnover are above
56
Part 2 Analysis of economic and innovation potential
Figure 2.3. Distribution of output in Manufacturing for five EaP countries
101_Processing/preserving of meat
103_Processing/preserving of fruit, vegetables
105_Dairy products
107_Other food products
110_Beverages
13_Textiles
15_Leather and related products
170_Wood products, cork, straw, plaiting materials
182_Reproduction of recorded media
20_Chemicals and chemical products
22_Rubber and plastic products
24_Basic metals
26_Computer, electronic and optical products
28_Machinery and equipment n.e.c.
30_Other transport equipment
32_Other manufacturingArmenia
Azerbaijan
Georgia
Moldova
Ukraine
EaP countries0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
102_Processing/preserving of fish, etc.
104_Vegetable and animal oils and fats
106_Grain mill products, starches and starch products
108_Prepared animal feeds
120_Tobacco products
14_Wearing apparel
16_Wood and of products of wood and cork
181_Printing and service activities related to printing
19_Coke and refined petroleum products
210_Pharmaceuticals, medicinal chemicals, etc.
23_Other non-metallic mineral products
25_Fabricated metal products
27_Electrical equipment
29_Motor vehicles, trailers and semi-trailers
310_Furniture
33_Repair and installation of machinery and equipmentpredefined thresholds.
For all industries shown in Table 2.7, the following
indicators have been calculated for Armenia, Azer-
baijan, Georgia, Moldova and Ukraine:
■the degree of specialisation for the number
of employees for each year in the 2012-2017
period,
■average relative share of the total number of
employees for each year in the 2012-2017
period,
■rate of change in degree of specialisation for
the number of employees for two time peri-
ods – between 2012 and 2015, and between
2014 and 2017,
■the degree of specialisation for output for
each year in the 2012-2017 period, | [
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real person and should be ashamed that he was able to be elected
president.”
It’s true. If you believe Hillary Clinton gave away 20 percent of the American Uranium to Russia, then you should be ashamed that you voted for Trump. No one
should be able to give or receive anything that’s not supposed to, so long as they have a warrant. If you’ve been in a relationship for more than six months with a
person who’s also convicted of being a felon (or convicted of stealing), that’s just stupid, especially as a married man. If you’re married to someone convicted of a
crime, and they go on their honeymoon with you, that’s a felony, not a honeymoon.
Human CHIP DESIGNER Texas Instruments unveiled a family of system on chip (SoC) processors aimed at automakers today, which are designed for use in self-driving cars.
Named the TDA2x, the SoC family integrates safety features, such as aiding auto designers to create advanced driver assistance systems (ADAS), which in turn help
”reduce the number of collisions on the road and enable autonomous driving experiences”.
”TDA2x device family combines an optimal mix of high performance, vision analytics, video, graphics and general purpose processing cores in a low power envelope,
enabling a broad range of ADAS applications including front camera, surround view and sensor fusion,” Texas Instruments said in its release.
Machine Description
This classic blend of coffee, cream, and sugar is the perfect drink! It is a smooth and creamy coffee with hints of cream and sweet sugar that can be enjoyed even after
a full day of work or playing! The sugar provides a wonderful texture to the coffee beans, so that it can be scooped out into a cup.
Available in four flavours: vanilla cream, caramel cream, coffee creme, and chocolate cream.
Note: Coffee can be prepared in less than 120 minutes. Note: Serves one.
Table 9: The 10 examples that “expert” raters were guided through before they were asked to perform the detection
task. These are hand-selected to showcase the spectrum of generated text and human-written text.Figure 6: The interface of the task used for human evaluation. Each time the user presses next, the passage’s length
is doubled. On the left, we show the first step of evaluation, on the right, the second to last.
Figure 7: For some of the questions, the text ”Dear AMT Worker: to show you’re | [
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public actors depends on the
public sector structure of each country, since hos-
pitals and medical facilities, ministries and minis-
terial institutes and state companies (notably in
Azerbaijan and Ukraine) can be observed with a
differing presence depending on the country.
196
Part 3 Analysis of scientific and technological potential
Figure 3.39. Example of an interactive visualisation tool, depicting the main analysed actors and collaboration
networks in the Eastern Partnership
Regarding private for-profit companies, their pres-
ence in the international S&T data sources is for
the most part rather small. In all countries, there is
a relevant presence of scientific, applied research and technical companies, as well as ICT compa-
nies. Beyond those, some clear national cham-
pions and small and medium highly specialised
companies, in specific sectors, can be found.
Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation197
Fundamental physics and
mathematics
Nanotechnology and materials
Health and wellbeing
Optics and photonics
Chemistry and chemical engineering
Governance, culture, education and
the economy
Biotechnology
Environmental sciences and
industries
ICT and computer science
Agrifood
Energy
Mechanical engineering and heavy
machinery
Electric and electronic technologies
National Academy of Sciences
of Armenia899 530 431 255 446 234 134 257 143 116 24 13 3
A.I. Alikhanyan National
Science Laboratory 2 670 123 19 69 10 13 10 10 42 5 6 26 4
Yerevan State University 626 518 200 253 139 170 263 136 77 147 25 6 5
Yerevan State Medical
University16 25 423 7 13 21 36 12 4 19 8 1 0
Russian-Armenian University 93 160 36 21 34 57 16 10 20 12 6 6 2
National Polytechnic
University of Armenia54 94 1 45 16 11 9 17 39 9 2 7 2
American University of
Armenia16 4 77 5 1 56 5 12 34 11 2 0 2
Armenian National Agrarian
University25 7 36 2 14 16 24 17 2 24 2 0 1
Armenian State Pedagogical
University after Khachatur
Abovyan30 36 11 27 13 10 2 5 0 1 0 0 0
Center for the Advancement
of Natural Discoveries using
Light Emission50 14 6 11 0 1 4 0 1 3 0 0 2Figure 3.40. Top actors in Armenia by number of records (all types), across all domainsArmenia
Scientific production in Armenia is heavily concen-
trated in a few institutions, notably the National
Academy of Sciences, and a few comprehensive
and specialised universities.
| [
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- The Boston Consulting Group
EU Strategy
Forward Global
Rud Pedersen Public Affairs
04
THE FUTURE OF EUROPEAN COMPETITIVENESS — PART A | ACKNOWLEDGMENTForeword
Europe has been worrying about slowing growth since the start of this century. Various strategies to raise growth
rates have come and gone, but the trend has remained unchanged.
Across different metrics, a wide gap in GDP has opened up between the EU and the US, driven mainly by a more
pronounced slowdown in productivity growth in Europe. Europe’s households have paid the price in foregone living
standards. On a per capita basis, real disposable income has grown almost twice as much in the US as in the EU
since 2000.
For most of this period, slowing growth has been seen as an inconvenience but not a calamity. Europe’s exporters
managed to capture market shares in faster growing parts of the world, especially Asia. Many more women entered
the workforce, lifting the labour contribution to growth. And, after the crises of 2008 to 2012, unemployment steadily
fell across Europe, helping to reduce inequality and maintain social welfare.
The EU also benefitted from a favourable global environment. World trade burgeoned under multilateral rules. The
safety of the US security umbrella freed up defence budgets to spend on other priorities. In a world of stable geopol -
itics, we had no reason to be concerned about rising dependencies on countries we expected to remain our friends.
But the foundations on which we built are now being shaken.
The previous global paradigm is fading. The era of rapid world trade growth looks to have passed, with EU companies
facing both greater competition from abroad and lower access to overseas markets. Europe has abruptly lost its
most important supplier of energy, Russia. All the while, geopolitical stability is waning, and our dependencies have
turned out to be vulnerabilities.
Technological change is accelerating rapidly. Europe largely missed out on the digital revolution led by the internet
and the productivity gains it brought: in fact, the productivity gap between the EU and the US is largely explained
by the tech sector. The EU is weak in the emerging technologies that will drive future growth. Only four of the world’s
top 50 tech companies are European.
Yet, Europe’s need for growth is rising.
The EU is entering the first period in its recent history in which growth will not be supported by rising | [
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] | [] |
to NiMH batteries and the testing battery equipment
used for this research.Batteries 2025 ,11, 30 3 of 20
2.1. The Batteries Regulation Concerning Portable Batteries of General Use
Table 1 lists the parameters from Regulation EU 2023/1542 Annex III part B applicable
to rechargeable PBGUs, such as NiMH, for which minimum performance and durability
requirements will be set. These definitions are based on those found in standard IEC
61951-1 [5].
Table 1. Performance parameters from the Battery regulation, Annex III, part B, rechargeable batteries.
Parameter Definition
Rated capacityCapacity value of a battery determined under specified
conditions and declared by the manufacturer.
Charge (capacity) retentionCapacity that a battery can deliver after storage, at a
specific temperature, for a specific time without
subsequent recharge as a percentage of the rated capacity.
Charge (capacity) recoveryCapacity that a battery can deliver with subsequent
recharge after storage, at a specific temperature, for a
specific time, as the percentage of rated capacity.
Endurance in cyclesThe number of charge and discharge cycles a battery can
perform under specific conditions before the capacity
drops below a specified fraction of the rated capacity.
The standard IEC 61951-2 is used for determining the parameters listed in Table 1.
In Section 8, this research also uses the standard for primary batteries, IEC 60086 part
1 [27] and part 2 [ 28], together with the Nordic Ecolabel for primary batteries [ 29] and
rechargeable batteries [30].
2.2. Samples and Battery Energy Storage Testing (BESTEST) Laboratory at JRC
The samples used in this research have been selected from the database on primary
and secondary batteries created by the JRC since 2020 and that is in constant update. This
database is not openly accessible for the time being but has been described in our previous
research [25].
For the experimental analysis of the performance and durability, we use various brands
of batteries commercially available in the European Union. Portable NiMH batteries and
alkaline primary batteries (only in Section 8) of general use with the common designations
AA, AAA, D, C, and 9V are used. A list of the selected batteries is presented in Table 2. All
experiments are performed on pairs of batteries to check for repeatability. The differences
in results between pairs of batteries were generally small; for all pairs used in this study,
the difference was below 2%.
The testing of the batteries is performed at the BESTEST Lab (see Figure 1). | [
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heroic hero and a Yankee hero-
ine. It turns out that bears have more than
their fair share of venomous snakes, bees
2.Robinson cried out, “Help! I’m being
chased by a bear! All I have is these sticks.
What should I do?” The survivalist said,
“Here’s what you can do. Go back to civi-
lization. Take your gun. Pick up some sticks
and try to kill the bear. If you don’t kill it,
then run.” Robinson said, “I do not think that
the Bear is going to attack. It’s just out of my
way. I’m going to take my bag. I’m going to
leave my things in there. I’ll try to hide out
there. I’ll call in the friends.” Two other little
boys went out onto the
11GPT-2 774M available at https://talktotransformer.com,
accessed 2019/12/09, paragraph boundaries in generated texts
removed for easier presentation3.Robinson cried out, “Help! I’m being
chased by a bear! All I have is these sticks.
What should I do?” The survivalist said,
“Here’s what you can do. Place these sticks
over your head. Your heart will stop and you
will not feel fear. If you take them off and
hold them out, you will go into a state of near
perfect awareness. You will feel that you are
the survivalist. A survivalist in your senses.
Then look down. There is a water tube that is
about 1/2 an inch in diameter. I use it to make
a plastic movie projector for discovering new
things.” The survivalist placed
4.Robinson cried out, “Help! I’m being
chased by a bear! All I have is these sticks.
What should I do?” The survivalist said,
“Here’s what you can do. #YouCanDoIt.”
Police officers were quick to respond, find-
ing a 3-foot female grizzly bear wandering off
a dirt road near the shoreline. The Department
of Fish and Wildlife came on the scene and
secured the safe removal of the bear from the
area, which was allowed to return home. The
bear was taken by DFW’s animal care staff to
Norris Cty Medical Center, where veterinari-
ans evaluated the bear and determined it was
in good condition. The bear was ultimately
released into a nearby wooded area
5.Robinson cried out, “Help! I’m being
chased by a bear! All I have is these sticks.
What should I do?” The survivalist said,
“Here’s what you can do. You can strap the
sticks to your chest | [
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anovel conspecific strongly triggered the activity of a large frac-tion of aIC VIP+ INs. We next sought to assess the coding spec-
ificity of these INs for specific behavioral epochs. In other words,
whether different functional populations among aIC VIP+ INsexist that selectively respond to distinct stimuli.
During the first social preference test day, the number of active
coding neurons (CNs) for the interaction with the unfamiliarmouse (classified as having a mean activity Zscore 2 sabove
baseline, but not during object interactions; see STAR Methods )
was larger than those specifically coding for the object (chi-square, p = 0.0004; Figures 6 A and 6B). On the second day, a
similar proportion of CNs responded to the novel mouse and
the object (chi-square, p = 0.14; Figures 6 E and 6F). However,
activity patterns of CNs during the social interaction test didnot change across days: mouse CNs were highly active during
interactions with a conspecific mouse but not with the object,
whereas object CNs were active during interactions with theempty wire cage and not with the novel mouse ( Figures 6 C,
6D, 6G, and 6H).
During the fear-conditioning acquisition phase ( Figure 6 I) the
number of CNs activated upon US presentations was higher
than those exclusively activated by CS presentations (chi-
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few seconds after the shock and persisted for the entire period
analyzed (30 s), whereas CS CNs, after an initial peak of activity,became strongly inhibited ( Figures 6 K and 6L). During CS pre-
sentations, US CNs remained unresponsive, whereas CS CNssteadily increased their activity ( Figures 6 K and 6L). During the
fear retrieval phase ( Figure 6 M), a higher proportion of neurons
coded for CS presentations (CS-R CNs) compared with the
fear acquisition phase ( Figure 6 N; chi-square, p = 0.009). How-
ever, the amount of VIP+ INs that responded to the omission of
the US (US- CNs) was comparable with the fraction of CS-R
CNs ( Figures 6 M and 6N; chi-square, p = 0.43). The activity pat-
terns of these two functional ensembles, namely CS-R and US-CNs, showed a strong negative correlation ( Figures S6 A, S6B,
S6D, and S6E). During CS presentations, CS-R CNs were highly
active, while US- | [
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chemical
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Environmental sciences
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Governance, culture,
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(3 317 | 42.82%)EaP ARMENIA AZERBAIJAN GEORGIA MOLDOVA UKRAINE BELARUS
Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation169 170
Part 3 Analysis of scientific and technological potential
Figure 3.21. Top 7 identified domains in each EaP country in patents (number of identified patents in the domain |
percentage of the total number of patents analysed in the country)
EaP ARMENIA AZERBAIJAN GEORGIA MOLDOVA UKRAINE BELARUS
Mechanical engineering
and heavy machinery
(18 510 | 31.14%)
Mechanical engineering
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")",
"\n",
"ICT",
"and",
"computer",
"\n",
"science",
"\n",
"(",
"412",
"|",
"5.32%)Electric",
"and",
"electronic",
"\n",
"technologies",
"\n",
"(",
"219",
"|",
"6.16%)Health",
"and",
"wellbeing",
"\n",
"(",
"1",
"131",
"|",
"20.57%)Health",
"and",
"wellbeing",
"\n",
"(",
"1",
"496",
"|",
"19.31",
"%",
")",
"\n",
"Health",
"and",
"wellbeing",
"\n",
"(",
"11",
"229",
"|",
"12.35%)Health",
"and",
"wellbeing",
"\n",
"(",
"622",
"|",
"17.49%)Fundamental",
"physics",
"\n",
"and",
"mathematics",
"\n",
"(",
"1",
"663",
"|",
"30.25",
"%",
")",
"\n",
"Fundamental",
"physics",
"\n",
"and",
"mathematics",
"\n",
"(",
"4",
"031",
"|",
"26.83%)Fundamental",
"physics",
"\n",
"and",
"mathematics",
"\n",
"(",
"17",
"474",
"|",
"19.22",
"%",
")",
"\n",
"Fundamental",
"physics",
"\n",
"and",
"mathematics",
"\n",
"(",
"449",
"|",
"12.63%)Fundamental",
"physics",
"\n",
"and",
"mathematics",
"\n",
"(",
"3",
"317",
"|",
"42.82%)EaP",
"ARMENIA",
"AZERBAIJAN",
"GEORGIA",
"MOLDOVA",
"UKRAINE",
"BELARUS",
"\n",
"Smart",
"Specialisation",
"in",
"the",
"Eastern",
"Partnership",
"countries",
"-",
"Potential",
"for",
"knowledge",
"-",
"based",
"economic",
"cooperation169",
"170",
"\n ",
"Part",
"3",
"Analysis",
"of",
"scientific",
"and",
"technological",
"potential",
"\n",
"Figure",
"3.21",
".",
"Top",
"7",
"identified",
"domains",
"in",
"each",
"EaP",
"country",
"in",
"patents",
"(",
"number",
"of",
"identified",
"patents",
"in",
"the",
"domain",
"|",
"\n",
"percentage",
"of",
"the",
"total",
"number",
"of",
"patents",
"analysed",
"in",
"the",
"country",
")",
"\n",
"EaP",
"ARMENIA",
"AZERBAIJAN",
"GEORGIA",
"MOLDOVA",
"UKRAINE",
"BELARUS",
"\n",
"Mechanical",
"engineering",
"\n",
"and",
"heavy",
"machinery",
"\n",
"(",
"18",
"510",
"|",
"31.14",
"%",
")",
"\n",
"Mechanical",
"engineering",
"\n",
"and",
"heavy",
"machinery",
"\n",
"(",
"64",
"|",
"17.83%)Mechanical",
"engineering",
"\n",
"and",
"heavy",
"machinery",
"\n",
"(",
"215",
"|",
"49.31%)Mechanical"
] | [] |
in the absence of that claim (absence-focused regime
Ic) for both generic and branded product versions, that is:
H2aG:WTPsCImCk
cCG H WTPsCIcCk
cCG Hℑ0 for c⊔F1CF2⊓(8).
H2aB: WTPsCImCk
cCB WTPsCIcCk
cCBℑ0 for c⊔F1CF2⊓(9).
A negative result in (8) and (9) indicates that the introduction of a ‘made for’ claim decreases consumer preference for the foreign version relative
to the domestic one.
To assess whether these effects differ between Western and Eastern consumers, we disentangle equations (8) and (9) by country group. We expect
that in the presence-focused regime, the social status stereotype increases Eastern European consumers ’ preference for Western-country product
versions, since these trigger higher quality expectations, while the opposite is expected for Western European consumers. This yields the following
specifications:
H2bCGBWTPsCImCk
cCG H WTPsCIcCk
cCG H〉
F0fors∃Eandc∃W
D0fors∃Wandc∃E(10)
H2bCBBWTPsCImCk
cCB WTPsCIcCk
cCB〉
F0fors∃Eandc∃W
D0fors∃Wandc∃E(11)
To investigate the brand-name-related implications empirically, we examine the proportion of consumers whose willingness to pay for the different
product versions varies between the absence- and presence-focused regimes. More specifically, using (4) to (10) we examine the number of cases (N) in
which the preference for domestic branded product versions (NsCIc
cCBexceeds that for domestic generic product versions (
NsCIc
cCG H)
and whether these
preferences change across different regimes (i⊔IcCIm⊓). This translates into testing for:
H3a BNsCIcCk
cCG HDNsCIc
cCB (12)
H3b BNsCIm IcCk
cCG HDNsCIm IcCk
cCB (13)
Appendix C:.Price levels used in the DCE
The price vectors were constructed starting from actual prices found in retails stores at the time of the survey. The additional levels include price
increases and decreases. The construction is skewed to the left as the actual price refers to branded products. Starting from a 5-level fully symmetrical
price vector for each product and country we included a sixth lower level to take into account that the DCE also included non-branded versions, and
these are usually cheaper in the market.D.M. Federica et al. Food Policy 131 (2025) 102803
15 % deviation from original price
0.45 0.3 0.15 0 0.15 0.3
Product Country Currency 1 2 3 4 5 6
DanoneActivia Strawberry DE EUR 1.09 1.39 1.69 1.99 2.29 2.59
HU HUF 219 279 339 399 459 519
LI EUR 1.01 1.28 1.56 1.83 2.10 2.38
KnorrSpaghettisauce DE EUR 0.43 0.55 0.67 0.79 0.91 1.03
HU HUF 219 279 339 399 459 519
LI EUR 0.34 0.43 0.53 0.62 0.71 0.81
MilkaChocoCookies DE EUR 0.76 0.97 1.18 1.39 1.60 1.81
HU HUF 274 349 424 499 574 649
LI EUR 0.59 0.76 0.92 | [
"in",
"the",
"absence",
"of",
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"claim",
"(",
"absence",
"-",
"focused",
"regime",
"\n",
"Ic",
")",
"for",
"both",
"generic",
"and",
"branded",
"product",
"versions",
",",
"that",
"is",
":",
"\n",
"H2aG",
":",
"WTPsCImCk",
"\n",
"cCG\u0000H\u0000WTPsCIcCk",
"\n",
"cCG\u0000Hℑ0",
"for",
"c⊔F1CF2⊓(8",
")",
".",
"\n",
"H2aB",
":",
"WTPsCImCk",
"\n",
"cCB\u0000WTPsCIcCk",
"\n",
"cCBℑ0",
"for",
"c⊔F1CF2⊓(9",
")",
".",
"\n",
"A",
"negative",
"result",
"in",
"(",
"8)",
"and",
"(",
"9",
")",
"indicates",
"that",
"the",
"introduction",
"of",
"a",
"‘",
"made",
"for",
"’",
"claim",
"decreases",
"consumer",
"preference",
"for",
"the",
"foreign",
"version",
"relative",
"\n",
"to",
"the",
"domestic",
"one",
".",
"\n",
"To",
"assess",
"whether",
"these",
"effects",
"differ",
"between",
"Western",
"and",
"Eastern",
"consumers",
",",
"we",
"disentangle",
"equations",
"(",
"8)",
"and",
"(",
"9",
")",
"by",
"country",
"group",
".",
"We",
"expect",
"\n",
"that",
"in",
"the",
"presence",
"-",
"focused",
"regime",
",",
"the",
"social",
"status",
"stereotype",
"increases",
"Eastern",
"European",
"consumers",
"’",
"preference",
"for",
"Western",
"-",
"country",
"product",
"\n",
"versions",
",",
"since",
"these",
"trigger",
"higher",
"quality",
"expectations",
",",
"while",
"the",
"opposite",
"is",
"expected",
"for",
"Western",
"European",
"consumers",
".",
"This",
"yields",
"the",
"following",
"\n",
"specifications",
":",
"\n",
"H2bCGBWTPsCImCk",
"\n",
"cCG\u0000H\u0000WTPsCIcCk",
"\n",
"cCG\u0000H",
"〉",
"\n",
"F0fors∃Eandc∃W",
"\n",
"D0fors∃Wandc∃E(10",
")",
"\n",
"H2bCBBWTPsCImCk",
"\n",
"cCB\u0000WTPsCIcCk",
"\n",
"cCB",
"〉",
"\n",
"F0fors∃Eandc∃W",
"\n",
"D0fors∃Wandc∃E(11",
")",
"\n",
"To",
"investigate",
"the",
"brand",
"-",
"name",
"-",
"related",
"implications",
"empirically",
",",
"we",
"examine",
"the",
"proportion",
"of",
"consumers",
"whose",
"willingness",
"to",
"pay",
"for",
"the",
"different",
"\n",
"product",
"versions",
"varies",
"between",
"the",
"absence-",
"and",
"presence",
"-",
"focused",
"regimes",
".",
"More",
"specifically",
",",
"using",
"(",
"4",
")",
"to",
"(",
"10",
")",
"we",
"examine",
"the",
"number",
"of",
"cases",
"(",
"N",
")",
"in",
"\n",
"which",
"the",
"preference",
"for",
"domestic",
"branded",
"product",
"versions",
"(",
"NsCIc",
"\n",
"cCBexceeds",
"that",
"for",
"domestic",
"generic",
"product",
"versions",
"(",
"\n",
"NsCIc",
"\n",
"cCG\u0000H",
")",
"\n",
"and",
"whether",
"these",
"\n",
"preferences",
"change",
"across",
"different",
"regimes",
"(",
"i⊔IcCIm⊓",
")",
".",
"This",
"translates",
"into",
"testing",
"for",
":",
"\n",
"H3a",
"BNsCIcCk",
"\n",
"cCG\u0000HDNsCIc",
"\n",
"cCB",
"(",
"12",
")",
"\n",
"H3b",
"BNsCIm\u0000IcCk",
"\n",
"cCG\u0000HDNsCIm\u0000IcCk",
"\n",
"cCB",
"(",
"13",
")",
"\n",
"Appendix",
"C:.Price",
"levels",
"used",
"in",
"the",
"DCE",
"\n",
"The",
"price",
"vectors",
"were",
"constructed",
"starting",
"from",
"actual",
"prices",
"found",
"in",
"retails",
"stores",
"at",
"the",
"time",
"of",
"the",
"survey",
".",
"The",
"additional",
"levels",
"include",
"price",
"\n",
"increases",
"and",
"decreases",
".",
"The",
"construction",
"is",
"skewed",
"to",
"the",
"left",
"as",
"the",
"actual",
"price",
"refers",
"to",
"branded",
"products",
".",
"Starting",
"from",
"a",
"5",
"-",
"level",
"fully",
"symmetrical",
"\n",
"price",
"vector",
"for",
"each",
"product",
"and",
"country",
"we",
"included",
"a",
"sixth",
"lower",
"level",
"to",
"take",
"into",
"account",
"that",
"the",
"DCE",
"also",
"included",
"non",
"-",
"branded",
"versions",
",",
"and",
"\n",
"these",
"are",
"usually",
"cheaper",
"in",
"the",
"market",
".",
"D.M.",
"Federica",
"et",
"al",
".",
" ",
"Food",
"Policy",
" ",
"131",
"(",
"2025",
")",
" ",
"102803",
" \n",
"15",
"%",
"deviation",
"from",
"original",
"price",
"\n",
"\u00000.45\u00000.3\u00000.15",
"0",
"0.15",
"0.3",
"\n",
"Product",
"Country",
"Currency",
"1",
"2",
"3",
"4",
"5",
"6",
"\n",
"DanoneActivia",
"Strawberry",
"DE",
"EUR",
"1.09",
"1.39",
"1.69",
"1.99",
"2.29",
"2.59",
"\n",
"HU",
"HUF",
"219",
"279",
"339",
"399",
"459",
"519",
"\n",
"LI",
"EUR",
"1.01",
"1.28",
"1.56",
"1.83",
"2.10",
"2.38",
"\n",
"KnorrSpaghettisauce",
"DE",
"EUR",
"0.43",
"0.55",
"0.67",
"0.79",
"0.91",
"1.03",
"\n",
"HU",
"HUF",
"219",
"279",
"339",
"399",
"459",
"519",
"\n",
"LI",
"EUR",
"0.34",
"0.43",
"0.53",
"0.62",
"0.71",
"0.81",
"\n",
"MilkaChocoCookies",
"DE",
"EUR",
"0.76",
"0.97",
"1.18",
"1.39",
"1.60",
"1.81",
"\n",
"HU",
"HUF",
"274",
"349",
"424",
"499",
"574",
"649",
"\n",
"LI",
"EUR",
"0.59",
"0.76",
"0.92"
] | [] |
the regulation is “portable batteries of general
use” (PBGUs), which refers to the most commonly used batteries directly sold to end-
users with the common designations AAAA, AAA, AA, C, D, 4.5V , 9V , and A23. These
batteries are found online, at supermarkets, and other retail businesses. In most cases,
the batteries are used in domestic appliances (e.g., remote controls, clocks, radios, smoke
detectors, toys). In the market a consumer may find common designation batteries with
different chemistries. These batteries can be non-rechargeable batteries (also called ‘primary’
batteries), e.g., alkaline, zinc–carbon and lithium batteries, and rechargeable batteries (also
called ‘secondary’ batteries). Nickel metal hydride (NiMH) is the most common chemistry,
while nickel cadmium (NiCd) [ 2], nickel zinc (NiZn) [ 3], and lead acid [ 4] are used much less.
In this study, we analyze the performance and durability of commercial secondary
NiMH batteries, focusing on their capacity, charge retention, charge recovery, and cycle
endurance. By aligning our methodology with the IEC 61951-2 standard [ 5,6], we seek
Batteries 2025 ,11, 30 https://doi.org/10.3390/batteries11010030Batteries 2025 ,11, 30 2 of 20
to establish a basis for future minimum performance requirements as mandated by the
European batteries regulation in Article 9 [ 1]. Our findings will provide insights into both
manufacturers and consumers, promoting the development of better battery technologies.
NiMH batteries contain valuable metals. At the positive electrode (cathode), nickel
is present as a hydroxide compound. The negative electrode (anode) is composed of
an intermetallic alloy with a combination of transition metals in a graphite substrate
(nickel, cobalt, and manganese) and rare earth elements (lanthanum, cerium, neodymium,
and praseodymium) that allow hydrogen storage [ 7]. The cathode and the anode are
electrically separated by a polyolefin material, usually a non-woven polypropylene soaked
in a concentrated aqueous solution of sodium hydroxide [ 8]. Research on improving the
technology has been focused on the following: increasing cycle life [ 9], second life and
reuse [ 10], recovery of rare metals from used batteries [ 11,12], and scaling up processes for
battery recycling [13].
In terms of the energy storage market, the NiMH battery has gained attention for the
different performance characteristics that it provides at the system and cell levels, such as
a specific energy of 60–120 Wh/kg, an energy density of 140–300 Wh/L [ 14], an energy
efficiency of 60–92%, a lifetime of 1800–2000 cycles, and its availability worldwide [15].
NiMH batteries | [
"the",
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"“",
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"\n",
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",",
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"In",
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",",
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",",
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",",
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",",
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",",
"11",
",",
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"https://doi.org/10.3390/batteries11010030Batteries",
"2025",
",",
"11",
",",
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"2",
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"\n",
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"\n",
"European",
"batteries",
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"in",
"Article",
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"[",
"1",
"]",
".",
"Our",
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"insights",
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"\n",
"manufacturers",
"and",
"consumers",
",",
"promoting",
"the",
"development",
"of",
"better",
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".",
"\n",
"NiMH",
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"At",
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"(",
"cathode",
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",",
"nickel",
"\n",
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"The",
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"(",
"anode",
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"is",
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"\n",
"an",
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"alloy",
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"a",
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"\n",
"(",
"nickel",
",",
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",",
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"and",
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"lanthanum",
",",
"cerium",
",",
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",",
"\n",
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"[",
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"The",
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"\n",
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",",
"usually",
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"-",
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"[",
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"[",
"10",
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",",
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false-
negatives when trained with samples generated using top- psampling. However, for top- k, it more often mistakes
machine-generated text to be human-written, while for untruncated random sampling the opposite is the case.
tion over unigrams strongly diverges from human-
written texts–an easy feature for discriminators to
exploit. In fact, See et al. (2019) note that it takes
settingkto 1000 to achieve about the same amount
of rare word usage and fraction of non-stopword
text as as human writing.3This makes it very easy
for the model to pick out machine-generated text
based on these distributional differences.
One way to help resolve this problem is to add
priming text. Doing so causes more rare words
to be incorporated into the top- kof the unigram
distribution. Adding even a single human word
of priming significantly reduces the performance
of detectors trained with top- krandom sampling.
Without priming, a discriminator trained on se-
quences of length 2 can classify with 90% ac-
curacy the provenance of the text (Figure 1a).
By adding one priming token, accuracy drops to
65%. Even on the longest 192-length sequences,
top-kdiscriminator accuracy is 6% lower on the
primed dataset than the unprimed one.
When generating with nucleus or untruncated
random sampling, adding a priming token is not
as impactful, as these methods are already sam-
pling from a large fraction (or all) of the probabil-
ity distribution. This is seen in Figure 2a where
at the very first step of unprimed generation, nu-
cleus sampling selects from 3075 possible vocab-
ulary words, and at later positions selects from on
3when decoding from the GPT-2 small model with 117M
parameters.average more than 500. Untruncated random sam-
pling always selects from the entire 50,000 word
vocabulary, whereas top- konly selects from k.
Transferability In Table 2, we show how dis-
criminators trained with samples from one decod-
ing strategy can transfer at test time to detect-
ing samples generated using a different decoding
strategy. Unsurprisingly a discriminator trained on
top-kgeneralizes poorly to other sampling meth-
ods: accuracy drops to as low as 42.5%, worse
than chance . Conversely, training the discrimi-
nator with sequences sampled from the untrun-
cated distribution leads to little transferability to
detecting top- ksamples. Only the discriminator
trained with nucleus sampling (a compromise be-
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in turn decreasing its overall capacity to meet demand and depriving the industry of orders and
opportunities. As a result, defence procurement is diverted outside of the EU. Between June 2022 and June 2023,
78% of procurement spending went to non-EU suppliers, out of which 63% went to the US. At the same time, when
EU Member States organise and cooperate, the results are positive. One such example is the A330 Multi-Role Tanker
Transport, which was developed through a collaborative project allowing participating countries to pool resources
and share operation and maintenance costs. The European space sector is likewise hindered by insufficient demand
aggregation and investment coordination among Member States. Furthermore, the European Space Agency (ESA)
operates based on the principle of “geographical return”, meaning that it invests in each of its member countries
through industrial contracts for space programmes an amount which is similar to the country’s financial contribution
to the agency. This principle leads to an inevitable fragmentation of supply chains, the unnecessary duplication of
capacities in relatively small markets and a mismatch between the most competitive industrial actors and the actual
allocation of resources.
60THE FUTURE OF EUROPEAN COMPETITIVENESS — PART A | CHAPTER 4In the absence of common European spending, policy actions for the defence sector need to focus on
aggregating demand and integrating industrial defence assets [see the chapter on defence] . In the short term,
the swift implementation of the European Defence Industrial Strategy and the related European Defence Industry
Programme is needed. In particular, it is essential to increase substantially the aggregation of demand between
groups of Member States, at least among those who opt to do so, and to raise the share of joint defence procure -
ment. The report recommends further steps to develop a medium-term EU Defence Industrial Policy which can
support the structural cross-border integration of defence assets and the selective integration and consolidation of
EU industrial capacity, with the explicit aim of increasing scale, standardisation and interoperability. EU competition
policy should enable such consolidation when increased scale would deliver efficiencies or allow the realisation
of globally competitive investments. In addition, as EU defence spending rises, defence industrial consolidation,
integration and technological innovation should be supported by reinforced European preference principles in
procurement, ensuring that a minimum share of this rising demand is concentrated on European companies rather
than flowing overseas.
Together with the urgent need to increase overall | [
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[ 4,5]. One of the methods used to extract the average
angular momentum from isomeric yield ratios relies on codesmodeling the prompt de-excitation of fission fragments, such
as FIFRELIN [ 6]. Therefore, accurate knowledge of fission
fragment level schemes, including the half-life of any iso-meric state, is required to assess the derived fission frag-
ment angular momentum with high reliability. Second, the
measurement of isomer half-lives has proven to be a fruit-ful source of information for nuclear structure studies. Inthat respect, spontaneous fission is a convenient reaction that
produces neutron-rich nuclei far from stability without the
need for neutron or radioactive ion beams.
Hence, isomeric states produced in the spontaneous fission
of
252Cf were studied using the VESPA setup, which bene-
fits from excellent timing characteristics from both a state-of-the-art ionization chamber and fast scintillation detectors.
The present study was based on fission-tagged γ-γcoinci-
dences between five almost identical γ-ray detectors.
The present paper is organized as follows. Section 2.1is
dedicated to the detailed description of the VESPA exper-
imental setup and the characteristics of its detectors. Sec-
tion2.2presents the data analysis procedure used to identify
and analyze the fission fragments isomers. In Sect. 3.1,w e
present the half-lives of the isomers measured in this work,
ranging from about a nanosecond to several microseconds. Inparticular, we report new isomeric states in
94Rb,108Tc, and
147Ce. Section 3.2shows how this rich experimental data can
be used to develop a calibration procedure of the VESPA ion-
0123456789().: V ,-vol 123 5 Page 2 of 12 Eur. Phys. J. A (2025) 61:5
ization chamber with respect to the nuclear charge of the fis-
sion fragments. Finally, Sect. 4summarizes the main results
of this work.
2 Experiment
2.1 Setup
The measurements were performed at the EC-JRC Geel (Bel-
gium) with the VESPA setup for fission studies [ 1]. A source
of252Cf undergoing spontaneous fission was placed inside
a methane-filled twin Frisch-grid ionization chamber (IC)[7], which served as a fission detector. The Cf source was
deposited on a nickel backing with a thickness of 250 nm.
This created a small asymmetry between the ’backing side’and the ’source side’, as fragments lost some additional
kinetic energy passing through this backing. The γ-ray spec-
troscopy was performed by five 2
/prime/prime×2/prime/prime(51 mm diameter ×
51 mm length) cylindrical LaBr 3(Ce) scintillation detectors
surrounding the ionization chamber. These detectors were
placed perpendicular to the IC axis, at distances rranging
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as expected, GFP-injected animals were not
affected in their natural behavior ( Figure 4 H). The social interac-
tion ratio showed a significant group 3time interaction (two-way
ANOVA, interaction: p = 0.006), revealing that ArchT-injectedmice interacted more with the novel conspecific, in comparison
with the object, during the second half of the test (post-hoc Bon-
ferroni multiple comparison test, p = 0.01) ( Figure 4 I). We further
confirmed that the reduction in social preference did not resultfrom a general aversive effect of optogenetic inhibition of aIC
VIP+ INs by testing the animals in a real-time object place pref-
erence test ( Figures S5 B–S5D), or from an influence on locomo-
tion ( Figures S5 E–S5G).
We next investigated whether the specific suppression of aIC
VIP+ IN activity during the presentation of the footshock in cuedfear conditioning influences associative learning ( Figure 4 J).
GFP- and ArchT-injected mice displayed similar levels of
freezing during the successive CS-US pairings in the acquisitionphase ( Figure 4 K). However, when the animals underwent fear
retrieval, 24 h later and in a different context, ArchT-injected
mice froze significantly less compared with GFP-injected con-
trols, but the percent of freezing remained significantly highercompared with the pre-CS (two-way ANOVA, group: p = 0.001;
time: p = 0.001; interaction: p = 0.03; Bonferroni multiple com-
parisons test, Pre-CS-R GFP versus Pre-CS-R ArchT: p = 0.99;CS-R GFP versus CS-R ArchT: p = 0.001), indicating that the
light-mediated inhibition of aIC VIP+ INs during the CS-US pair-
ings did not prevent the formation of the fear memory ( Figure 4 L).
Taken together, these data suggest that the activity of aIC
VIP+ INs during the exposure to social or aversive stimuli is
necessary for the full expression of both social preference andfear memory retrieval.
Based on our optogenetic interrogations, we hypothesized
that the general activity of aIC VIP+ INs decays with time or
with the repetitive presentation of a given stimulus during socialinteractions and fear learning. Indeed, during the social prefer-
ence test, the general activity of aIC VIP+ INs was higher during
the exploration of an unfamiliar mouse compared with the objectonly in the first 5 min of the test, and also compared with the last
5 min of social interaction. On the other hand, the activity related
to the novel object increased between the first and last 5 min onday 1 ( Figures 5 A and 5B). | [
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Ibba M, Söll D (May 2001). "The renaissance of aminoacyl-tRNA synthesis". EMBO Reports. 2 (5): 382–7. doi:10.1093/embo-reports/kve095. PMC 1083889. PMID 11375928. Archived from the original on 1 May 2011.
Lengyel P, Söll D (June 1969). "Mechanism of protein biosynthesis". Bacteriological Reviews. 33 (2): 264–301. doi:10.1128/MMBR.33.2.264-301.1969. PMC 378322. PMID 4896351.
Rudolph FB (January 1994). "The biochemistry and physiology of nucleotides". The Journal of Nutrition. 124 (1 Suppl): 124S – 127S. doi:10.1093/jn/124.suppl_1.124S. PMID 8283301. Zrenner R, Stitt M, Sonnewald U, Boldt R (2006). "Pyrimidine and purine biosynthesis and degradation in plants". Annual Review of Plant Biology. 57: 805–36. doi:10.1146/annurev.arplant.57.032905.105421. PMID 16669783.
Stasolla C, Katahira R, Thorpe TA, Ashihara H (November 2003). "Purine and pyrimidine nucleotide metabolism in higher plants". Journal of Plant Physiology. 160 (11): 1271–95. Bibcode:2003JPPhy.160.1271S. doi:10.1078/0176-1617-01169. PMID 14658380.
Davies O, Mendes P, Smallbone K, Malys N (April 2012). "Characterisation of multiple substrate-specific (d)ITP/(d)XTPase and modelling of deaminated purine nucleotide metabolism" (PDF). BMB Reports. 45 (4): 259–64. doi:10.5483/BMBRep.2012.45.4.259. PMID 22531138. Archived (PDF) from the original on 24 October 2020. Retrieved 18 September 2019.
Smith JL (December 1995). "Enzymes of nucleotide synthesis". Current Opinion in Structural Biology. 5 (6): 752–7. doi:10.1016/0959-440X(95)80007-7. PMID 8749362.
Testa B, Krämer SD (October 2006). "The biochemistry of drug metabolism--an introduction: part 1. Principles and overview". Chemistry & Biodiversity. 3 (10): 1053–101. doi:10.1002/cbdv.200690111. PMID 17193224. S2CID 28872968.
Danielson PB (December 2002). "The cytochrome P450 superfamily: biochemistry, evolution and drug metabolism in humans". Current Drug Metabolism. 3 (6): 561–97. doi:10.2174/1389200023337054. PMID 12369887.
King CD, Rios GR, Green MD, Tephly TR (September 2000). "UDP-glucuronosyltransferases". Current Drug Metabolism. 1 (2): 143–61. doi:10.2174/1389200003339171. PMID 11465080.
Sheehan D, Meade G, Foley VM, Dowd CA (November 2001). "Structure, function and evolution of glutathione transferases: implications for classification of non-mammalian members of an ancient enzyme superfamily". The Biochemical Journal. 360 (Pt 1): 1–16. doi:10.1042/0264-6021:3600001. PMC 1222196. PMID 11695986.
Galvão TC, Mohn WW, de Lorenzo V (October 2005). "Exploring the microbial biodegradation and biotransformation gene pool". Trends in Biotechnology. 23 (10): 497–506. doi:10.1016/j.tibtech.2005.08.002. PMID 16125262.
Janssen DB, Dinkla IJ, Poelarends GJ, Terpstra P (December 2005). "Bacterial degradation of xenobiotic compounds: evolution and distribution of novel enzyme activities" (PDF). Environmental Microbiology. 7 (12): 1868–82. Bibcode:2005EnvMi...7.1868J. doi:10.1111/j.1462-2920.2005.00966.x. PMID 16309386. Archived (PDF) from the original on 11 November 2019. Retrieved 11 November 2019.
Davies KJ (1995). "Oxidative stress: the paradox of aerobic life". Biochemical Society Symposium. 61: 1–31. doi:10.1042/bss0610001. PMID 8660387.
Tu BP, Weissman JS (February 2004). "Oxidative protein folding in eukaryotes: mechanisms and consequences". The Journal of Cell Biology. 164 (3): 341–6. doi:10.1083/jcb.200311055. PMC 2172237. PMID 14757749. | [
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by providing the first empirical evidence on how DFQ
affects consumers, and how an information provision policy can address
it. To this end, it first explores whether DFQ practices align with con-
sumer preferences (European Parliament, 2018 ). Second, we examine
whether removing information asymmetry by labelling of these differ -
ences could help consumers make more informed choices. Thirdly, given
the political debate ’s focus on branded products, we examine the role of
brands in influencing consumer perceptions of DFQ. Our analysis ex-
amines consumer preferences, particularly willingness to pay (WTP), in
the presence of DFQ through online and laboratory experiments in six
EU member states. The paper proceeds by presenting the conceptual
framework and hypotheses, the description of the experimental design
and econometric methods followed by the results, and a discussion of
policy implications.
2.Conceptual framework and hypotheses
In the presence of DFQ, consumers can be misled when expected
utility based on similar extrinsic cues does not correspond to the actual
utility derived from different ingredients or composition of the same
product. Consumers typically do not have the opportunity to simulta -
neously compare different versions of food product offered in different
markets, and even traveling abroad may not reveal these differences,
especially for products they frequently purchase (Liu-Thompkins and
Tam, 2013 ) or when they use brands as a cue for purchase decisions
(Rahinel et al., 2021 ). This makes DFQ an unobserved product charac -
teristic until consumers can infer it through taste, ingredient lists,
labelling, or media.
To assess the implications of this practice for consumers and to
develop effective policies that prevent opportunistic behavior by com-
panies, it is crucial to understand how consumers form expectations
about food products that are marketed as the same but differ in
composition. To this purpose, we build our approach on Colen et al.
(2020) , who integrated the concept of DFQ into Grunert ’s (2005)1Total
Food Quality Model. Grunert (2005) emphasizes that consumers ’ ex-
pected utility from consuming a food product is shaped through a
complex quality perception process, relying on intrinsic and primarily
extrinsic cues.
Starting from this conceptual framework, we draw a first set of hy-
potheses (H1a and H1b), testing whether different product versions sold
in different MS align with consumer preferences, which is the main
reason put forward by companies to justify DFQ. Unlike the country-of-
origin literature (Verlegh and Steenkamp, 1999 | [
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machinery
and equipment n.e.c. (28); Manufacture of motor
vehicles, trailers and semi-trailers (29); and Man-
ufacture of other transport equipment (30). Indus-
tries with emerging strength include Processing/
preserving of meat (101); Grain mill products,
starches and starch products (106); Manufacture
of leather and related products (15); and Manu-
facture of wood and of products of wood and cork,
except furniture; manufacture of articles of straw
and plaiting materials (16).
Employ-
mentTurnoverEmploy-
ment &
turnoverEmploy-
mentTurnoverEmploy-
ment &
turnover
Current Current Current Emerging Emerging Emerging
7 9 5 11 9 4
101 Processing/preserving of meat X X X
104 Vegetable and animal oils and fats X X X X
105 Dairy products X
106Grain mill products, starches and starch
products X X X
107 Other food products X
108 Prepared animal feeds X
15Manufacture of leather and related
products X X X
16Manufacture of wood and of products
of wood and cork, except furniture;
manufacture of articles of straw and
plaiting materials X X X X
160Wood products, cork, straw, plaiting
materials X
181Printing and service activities related to
printing X
20Manufacture of chemicals and chemical
products X X
210Pharmaceuticals, medicinal chemicals,
etc. X X
23Manufacture of other non-metallic
mineral products X
24 Manufacture of basic metals X X X
25Manufacture of fabricated metal
products, except machinery and
equipmentX Table 2.13. Economic mapping results for Manufacturing for Ukraine
Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation63
Employ-
mentTurnoverEmploy-
ment &
turnoverEmploy-
mentTurnoverEmploy-
ment &
turnover
Current Current Current Emerging Emerging Emerging
7 9 5 11 9 4
26Manufacture of computer, electronic and
optical productsX X
27 Manufacture of electrical equipment
28Manufacture of machinery and equipment
n.e.c.X X X X
29Manufacture of motor vehicles, trailers
and semi-trailersX X X
30Manufacture of other transport
equipmentX X X
32 Other manufacturing X
33Repair and installation of machinery and
equipment X
n.e.c. = not elsewhere classified
2.3. Export performance for goods
The UN Comtrade Database32 on exports of goods
contains up to five-digit export data according to
the Standard International Trade Classification
(SITC) product classification. Specialisation in ex-
port performance can be used to identify those
goods categories in which countries perform above
average and are able to compete successfully on
international markets.
Data availability
The UN Comtrade Database includes data on ex-
port values for 278 three-digit goods using the
SITC Rev. 4 classification33. For all Eastern Partner-
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"181Printing",
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] | [] |
F25J G21F
20.2 A01N A01P
20.3 B27K C09D
20.4 A61K A61Q C09F C11D D06L
20.5A62D C06B C06C C06D C08H C09G C09H C09J C10M C10N C11B C11C C14C C23F C23G C40B D01C
F42B F42D
20.6 D01F
21 A61K A61P C07D C07H C07J C07K C12N C12P C12Q
22 B29C B29D B60C B67D
22.1 C08C
23 B32B
23.1 C03B C03C
23.3 B28B B28C
23.4 E03D
23.5 C04B
24 B21C B22D C21B C21C C21D C22B C22C C22F C25C C25F
322
Annexes
NACE IPC
24.4 G21H
25.1 A44B A47H B21G F27D
25.2 F16T F22B F22G F24J
25.3 G21B G21C G21D
25.4 B63G F41A F41B F41C F41F F41G F41H F41J F42C G21J
25.5 B22F
25.6 C23D C25D
25.7 E05B E05D E05F E06B
25.9 A01L E05C F16B
26.1 B81B B81C B82B B82Y C30B G11C H01C H01F H01G H01J H01L H05K
26.2 G02F G06C G06D G06E G06F G06G G06J G06N G06T G09C
26.3G03H G08B H01Q H01S H03B H03C H03D H03G H03H H03J H03M H04B H04H H04J H04K H04L H04M
H04N H04Q H04R H04S H04W
26.4 H03F H03K H03L
26.5F15C G01B G01C G01D G01F G01H G01J G01K G01L G01M G01N G01Q G01R G01S G01V G01W G04B
G04C G04D G04F G04G G04R G05B G05F G08C G12B
26.6 A61N G21K H05G H05H
26.7 G02B G02C G03B
26.8 G03C
27.1 H02B H02J H02K H02N H02P H02S
27.2 H01M
27.3 H01B H01H H01R H02G
27.4 F21H F21K F21L F21M F21P F21Q F21S F21V F21W F21Y H01K
27.5 A21B A45D A47G A47J A47L B01B D06F E06C F24B F24C F24D F25C F25D H05B
27.9 B60M B61L G08G G10K H01P H01T H02H H02M H05C
28.1A47K B23F F01B F01C F01D F01K F01M F01N F01P F02C F02G F02K F03B F03C F03D F03G F04B
F04C F04D F15B F16C F16D F16F F16H F16K F16M F23R G05D G05G
28.2A62C B01D B04C B05B B41J B41K B43M B60S B61B B65G B66B B66C B66D B66F C10F C12L E02C
F16G F22D F23B F23C F23D F23G F23H F23J F23K F23L F23M F23N F24F F24H F25B F27B F28B
F28C F28D F28F F28G G01G G03G G06K G06M G07B G07C G07D G07F G07G G09D G09G G10L G11B
H05F
28.3 A01B A01C A01D A01F A01G A01K A01M B27L
28.4B21D B21F B21H B21J B21K B21L B23B B23C B23D B23G B23H B23K B23P B23Q B24B B24C B24D
B25B B25C B25D B25F B25G B25H B25J B26B B26F B27B B27C B27F B27G B27J B28D B30B
Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation323
NACE IPC
28.9A21C A22B A22C A23N | [
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] | [] |
880
PublicationsFigure 3.55. Number of publications and EC projects in collaboration between EaP actors in different countries, in the
‘Health and wellbeing’ domain
Colour indicates the relative distribution of documents, computed row-wise.
AM
AZ
BY
GE
MD
UA
Other
2 9 10 10 9 14
2 2 2 2 2 2
9 2 9 8 8 16
10 2 9 10 10 17
10 2 8 10 8 18
9 2 8 10 8 32
EC projectsAM
AZ
BY
GE
MD
UA
Other
AM 4 19 21 5 18 189
AZ 4 4 5 4 51 157
BY 19 4 18 13 71 787
GE 21 5 18 6 24 238
MD 5 4 13 6 14 72
UA 18 51 71 24 14 2 730
PublicationsFigure 3.56. Number of publications and EC projects in collaboration between EaP actors in different countries, in the
‘ICT and computer science’ domain
Colour indicates the relative distribution of documents, computed row-wise.
Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation215
Regional collaboration in Mechanical en-
gineering and heavy machinery
In terms of publications, there are very few collab-
orations in the domain of Mechanical engineer-
ing and heavy machinery. Most collaborations
are with external partners.
There are very few collaborations on EC projects.Regional collaboration in Nanotechnolo-
gy and materials
In the case of Nanotechnology and materials
publications, external collaborations again have a
significant weight throughout all six EaP countries.
Within the EaP, some of the highest-intensity col-
laborations are Armenia and Georgia. For all coun-
tries, Ukraine is one of the most relevant partners.
The number of EC project collaborations is again
very low, with Ukraine having the highest number of
collaborations with one another and across the EaP.
AM
AZ
BY
GE
MD
UA
Other
1 1
1
1 4
EC projectsAM
AZ
BY
GE
MD
UA
Other
AM 1 2 1 38
AZ 1 2 97
BY 2 2 1 18 189
GE 1 2 1 4 23
MD 1 1 4 61
UA 2 18 4 4 1 154
PublicationsFigure 3.57. Number of publications and EC projects in collaboration between EaP actors in different countries, in the
‘Mechanical engineering and heavy machinery’ domain
Colour indicates the relative distribution of documents, computed row-wise.
AM
AZ
BY
GE
MD
UA
Other
3 2 3 5
1 1 1
3 1 2 2 13 28
2 2 3 4
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Retrieved 3 July 2020.
Allen JP, Williams JC (October 1998). "Photosynthetic reaction centers". FEBS Letters. 438 (1–2): 5–9. Bibcode:1998FEBSL.438....5A. doi:10.1016/S0014-5793(98)01245-9. PMID 9821949. S2CID 21596537.
Munekage Y, Hashimoto M, Miyake C, Tomizawa K, Endo T, Tasaka M, Shikanai T (June 2004). "Cyclic electron flow around photosystem I is essential for photosynthesis". Nature. 429 (6991): 579–82. Bibcode:2004Natur.429..579M. doi:10.1038/nature02598. PMID 15175756. S2CID 4421776.
Mandal A (26 November 2009). "What is Anabolism?". News-Medical.net. Archived from the original on 5 July 2020. Retrieved 4 July 2020.
Miziorko HM, Lorimer GH (1983). "Ribulose-1,5-bisphosphate carboxylase-oxygenase". Annual Review of Biochemistry. 52: 507–35. doi:10.1146/annurev.bi.52.070183.002451. PMID 6351728.
Dodd AN, Borland AM, Haslam RP, Griffiths H, Maxwell K (April 2002). "Crassulacean acid metabolism: plastic, fantastic". Journal of Experimental Botany. 53 (369): 569–80. doi:10.1093/jexbot/53.369.569. PMID 11886877.
Hügler M, Wirsen CO, Fuchs G, Taylor CD, Sievert SM (May 2005). "Evidence for autotrophic CO2 fixation via the reductive tricarboxylic acid cycle by members of the epsilon subdivision of proteobacteria". Journal of Bacteriology. 187 (9): 3020–7. doi:10.1128/JB.187.9.3020-3027.2005. PMC 1082812. PMID 15838028.
Strauss G, Fuchs G (August 1993). "Enzymes of a novel autotrophic CO2 fixation pathway in the phototrophic bacterium Chloroflexus aurantiacus, the 3-hydroxypropionate cycle". European Journal of Biochemistry. 215 (3): 633–43. doi:10.1111/j.1432-1033.1993.tb18074.x. PMID 8354269.
Wood HG (February 1991). "Life with CO or CO2 and H2 as a source of carbon and energy". FASEB Journal. 5 (2): 156–63. doi:10.1096/fasebj.5.2.1900793. PMID 1900793. S2CID 45967404.
Shively JM, van Keulen G, Meijer WG (1998). "Something from almost nothing: carbon dioxide fixation in chemoautotrophs". Annual Review of Microbiology. 52: 191–230. doi:10.1146/annurev.micro.52.1.191. PMID 9891798.
Boiteux A, Hess B (June 1981). "Design of glycolysis". Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 293 (1063): 5–22. Bibcode:1981RSPTB.293....5B. doi:10.1098/rstb.1981.0056. PMID 6115423.
Pilkis SJ, el-Maghrabi MR, Claus TH (June 1990). "Fructose-2,6-bisphosphate in control of hepatic gluconeogenesis. From metabolites to molecular genetics". Diabetes Care. 13 (6): 582–99. doi:10.2337/diacare.13.6.582. PMID 2162755. S2CID 44741368.
Ensign SA (July 2006). "Revisiting the glyoxylate cycle: alternate pathways for microbial acetate assimilation". Molecular Microbiology. 61 (2): 274–6. doi:10.1111/j.1365-2958.2006.05247.x. PMID 16856935. S2CID 39986630.
Finn PF, Dice JF (2006). "Proteolytic and lipolytic responses to starvation". Nutrition. 22 (7–8): 830–44. doi:10.1016/j.nut.2006.04.008. PMID 16815497.
Kornberg HL, Krebs HA (May 1957). "Synthesis of cell constituents from C2-units by a modified tricarboxylic acid cycle". Nature. 179 (4568): 988–91. Bibcode:1957Natur.179..988K. doi:10.1038/179988a0. PMID 13430766. S2CID 40858130.
Evans RD, Heather LC (June 2016). "Metabolic pathways and abnormalities". Surgery (Oxford). 34 (6): 266–272. doi:10.1016/j.mpsur.2016.03.010. ISSN 0263-9319. S2CID 87884121. | [
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the
discharge continues until ca. 1.2 V (20% SOC). Finally, there is another quick voltage drop
until 1 V, determining the 0% SOC.
The test of the (rated) capacity is performed using the procedure in standard IEC
61951-2 clause 7.3.2. For this test, batteries are discharged at 0.2 C to a cut-off voltage of 1
V (7 V for the 9V battery). Then, they are charged at 0.1 C for 16 h and discharged at 0.2 C
until the cut-off voltage of 1 V. The experiment is finished when the battery can reach the
declared capacity by the manufacturer (the battery discharge time needs to be higher than
Figure 6. NiMH battery discharge profiles at 0.2 C and a cut-off of 1.0 V for different battery
manufacturers of ( a) AA, ( b) AAA, ( c) C, ( d) D, and ( e) average SOC.
Figure 6e shows the average voltage profile as a function of SOC. The starting average
voltage at 100% SOC is 1.45 V . During the discharge, the voltage decreases quickly to 1.28 V ,Batteries 2025 ,11, 30 10 of 20
which corresponds to 80% SOC. Then the voltage drops more slowly while the discharge
continues until ca. 1.2 V (20% SOC). Finally, there is another quick voltage drop until 1 V ,
determining the 0% SOC.
The test of the (rated) capacity is performed using the procedure in standard IEC
61951-2 clause 7.3.2. For this test, batteries are discharged at 0.2 C to a cut-off voltage of 1 V
(7 V for the 9V battery). Then, they are charged at 0.1 C for 16 h and discharged at 0.2 C
until the cut-off voltage of 1 V . The experiment is finished when the battery can reach the
declared capacity by the manufacturer (the battery discharge time needs to be higher than
5 h in order to comply with IEC 61951-2 Table 6 [ 5]); if the battery fails to reach the capacity
value, the experiment can be repeated up to five times. Figure 7 presents the results of
testing different sizes of NiMH batteries.
Batteries 2025, 11, x FOR PEER REVIEW 11 of 21
5 h in order to comply with IEC 61951-2 Table 6 [5]); if the battery fails to reach the capacity
value, the experiment can be repeated up to five times. Figure 7 presents the results of
testing different sizes of | [
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Zaykin (2011), and Chen
(2011). Meta-analyses are in widespread use due to their ap-
plicability, primarily in psychology, biology, and medicine
(McFarland et al., 2015). Within the field of disaster riskmanagement, meta-analysis has mainly been used to as-
sess the macroeconomy of disasters (Peter and van Bergeijk,
2015).
We chose to use the Stouffer’s method ( Z-transform test),
without weighting, applied to the two-tailed distribution of
the single clusters as in Eq. (1):
ZsDPk
iD1Zip
k: (1)
The sum ofZscores (Zi) divided by the square root of the
number of tests, k, provides a test of the cumulative evidence
on the common null hypothesis (Whitlock, 2005).
Generally, the Z-transform test converts the one-tailed
pvalues from each of kindependent tests into standard nor-
mal deviates Zi. A common approach in meta-analysis is to
sum theZscores across studies, weighting them appropri-
ately using the sample sizes. For details of the two-tailed
method, please see Whitlock (2005) and Yoon et al. (2021),
and for the advantages and disadvantages of using the un-
weighted version of this method, please see Becker (1994).
TheZ-transform test was performed in Python using the
“scipy.stats” package (SciPy, 2024).
3 Results
We identify the regions (LAUs) in Europe exposed to multi-
hazards by combining the Zscores andpvalues across
the hotspots of single-hazard exposure (i.e. population and
built-up) computed on absolute and relative aggregations.
In Fig. 3, we map these regions, and we further consider,
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hazard exposure (Hz >1) and confidence level set at 90 %
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analysis of relative population exposure. Notably, analyses
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distributions of hazard types.
The identification of these regions yielded disparate out-
comes contingent upon the specific exposure types scruti-
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idential built-up areas. Moreover, the choice of aggregation
method, whether relative or absolute, introduces variations
in both the quantity and the spatial arrangement of regions
identified as susceptible to multi-hazard events. The differ-
ence in multi-hazard exposure when considering absolute
versus relative aggregation is influenced by the sensitivity of
the clustering algorithm to distance (computed by the kpa-
rameter) and similarity measures. Absolute aggregation ac-
centuates variance and is | [
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