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9514_51 | Studies of recurrent febrile seizures have shown that seizures resulted in impaired learning and memory but also disrupted signaling that normally results in activation of cAMP response element binding factor (CREB), a transcription factor. For rats tested in the inhibitory avoidance learning paradigm, normally an activation of CREB occurs by phosphorylation at Ser133. This activation is impaired following recurrent febrile seizures. A seizure-induced modification of a signaling cascade upstream of CREB is suggested by this. Adult rats with infant febrile seizures were treated with Rolipram, a specific phosphodiesterase type IV inhibitor (PDE4 inhibitor), which resultes in the activation of protein kinase A (PKA) and is known to activate CREB by the mitogen-activated protein kinase (MAPK) pathway. Rolipram treatment reversed the learning deficits in rats that had experienced recurrent febrile seizures. |
9514_52 | Optical monitoring
Recording the activity of a single neuron at any given time at many locations in the dendritic tree has been accomplished using voltage-sensitive dyes with optical monitoring. Signals are rapid but also small, and measurements from single cells require intense illumination. As the dyes are very phototoxic, the cells usually die after only a few action potentials. However, measurements from both somatic and dendritic patch recordings show that the peak membrane potential deflection during a paroxysmal depolarizing shift (PDS) is 10mV greater in the apical trunk (supragranular location) than the soma. This is consistent with the anatomy of neocortical networks because the most powerful reciprocal layer connections are in supragranular layers 2 and 3. This may resolve the conflicting information suggesting that the activity spreads primarily at the supragranular layers or at the large layer 5 neurons. |
9514_53 | Conventional studies with electron microscopy or Golgi stains portrayed dendrites as stable structures. However, time-lapsed photography and two-photon microscopy have revealed dendrites as living, constantly changing tissues which are motile on a rapid time scale. |
9514_54 | Electroencephalogram |
9514_55 | Electroencephalogram (EEG) scalp signals are summed EPSPs and IPSPs of nerve cells. EEG can only measure the potentials of cells arranged in organized layers and whose apical dendrites are oriented perpendicularly to the surface of the cortex (as they are in pyramidal cells). The potential measured by the EEG is the difference between the basal and apical parts of the active neurons that are oriented in such a way. The EPSPs that converge on the pyramidal neurons through direct afferent fibers ending in the upper part of the apical dendrites cause a flow of charged ions (a current) between points at different potentials within and outside neurons. The positive ions then enter the cell following concentration and electrical charge gradient and propagate to the rest of the neuron. EPSPs from the distal apical dendrites create a current starting from the apical part nearest to the synapse (where the magnitude is greater) toward the cell body because the resistance to this flow is less. |
9514_56 | The current perpendicular (or radial) to the apical dendrite is accompanied by a magnetic field that propagates orthogonally (or tangentially) to the current along the extracellular side of the cell membrane. This set of ionic and electrical functional alterations thus generates the fields of electromagnetic potentials or electromagnetic dipoles. These can be defined also as single equivalent dipoles. |
9514_57 | References
Cerebrum
Neurohistology |
9515_0 | The Burrows–Wheeler transform (BWT, also called block-sorting compression) rearranges a character string into runs of similar characters. This is useful for compression, since it tends to be easy to compress a string that has runs of repeated characters by techniques such as move-to-front transform and run-length encoding. More importantly, the transformation is reversible, without needing to store any additional data except the position of the first original character. The BWT is thus a "free" method of improving the efficiency of text compression algorithms, costing only some extra computation. The Burrows–Wheeler transform is an algorithm used to prepare data for use with data compression techniques such as bzip2. It was invented by Michael Burrows and David Wheeler in 1994 while Burrows was working at DEC Systems Research Center in Palo Alto, California. It is based on a previously unpublished transformation discovered by Wheeler in 1983. The algorithm can be implemented |
9515_1 | efficiently using a suffix array thus reaching linear time complexity. |
9515_2 | Description
When a character string is transformed by the BWT, the transformation permutes the order of the characters. If the original string had several substrings that occurred often, then the transformed string will have several places where a single character is repeated multiple times in a row.
For example:
The output is easier to compress because it has many repeated characters.
In this example the transformed string contains six runs of identical characters:
XX,
SS,
PP,
..,
II,
and
III, which together make 13 out of the 44 characters.
Example
The transform is done by sorting all the circular shifts of a text in lexicographic order and by extracting the last column and the index of the original string in the set of sorted permutations of S. |
9515_3 | Given an input string S = ^BANANA| (step 1 in the table below), rotate it N times (step 2), where N = 8 is the length of the S string considering also the symbol ^ representing the start of the string and the red | character representing the 'EOF' pointer; these rotations, or circular shifts, are then sorted lexicographically (step 3). The output of the encoding phase is the last column L = BNN^AA|A after step 3, and the index (0-based) I of the row containing the original string S, in this case I = 7.
The following pseudocode gives a simple (though inefficient) way to calculate the BWT and its inverse. It assumes that the input string s contains a special character 'EOF' which is the last character and occurs nowhere else in the text.
function BWT (string s)
create a table, where the rows are all possible rotations of s
sort rows alphabetically
return (last column of the table) |
9515_4 | function inverseBWT (string s)
create empty table
repeat length(s) times
// first insert creates first column
insert s as a column of table before first column of the table
sort rows of the table alphabetically
return (row that ends with the 'EOF' character) |
9515_5 | Explanation
To understand why this creates more-easily-compressible data, consider transforming a long English text frequently containing the word "the". Sorting the rotations of this text will group rotations starting with "he " together, and the last character of that rotation (which is also the character before the "he ") will usually be "t", so the result of the transform would contain a number of "t" characters along with the perhaps less-common exceptions (such as if it contains "ache ") mixed in. So it can be seen that the success of this transform depends upon one value having a high probability of occurring before a sequence, so that in general it needs fairly long samples (a few kilobytes at least) of appropriate data (such as text).
The remarkable thing about the BWT is not that it generates a more easily encoded output—an ordinary sort would do that—but that it does this reversibly, allowing the original document to be re-generated from the last column data. |
9515_6 | The inverse can be understood this way. Take the final table in the BWT algorithm, and erase all but the last column. Given only this information, you can easily reconstruct the first column. The last column tells you all the characters in the text, so just sort these characters alphabetically to get the first column. Then, the last and first columns (of each row) together give you all pairs of successive characters in the document, where pairs are taken cyclically so that the last and first character form a pair. Sorting the list of pairs gives the first and second columns. Continuing in this manner, you can reconstruct the entire list. Then, the row with the "end of file" character at the end is the original text. Reversing the example above is done like this: |
9515_7 | Optimization
A number of optimizations can make these algorithms run more efficiently without changing the output. There is no need to represent the table in either the encoder or decoder. In the encoder, each row of the table can be represented by a single pointer into the strings, and the sort performed using the indices. In the decoder, there is also no need to store the table, and in fact no sort is needed at all. In time proportional to the alphabet size and string length, the decoded string may be generated one character at a time from right to left. A "character" in the algorithm can be a byte, or a bit, or any other convenient size.
One may also make the observation that mathematically, the encoded string can be computed as a simple modification of the suffix array, and suffix arrays can be computed with linear time and memory. The BWT can be defined with regards to the suffix array SA of text T as (1-based indexing): |
9515_8 | There is no need to have an actual 'EOF' character. Instead, a pointer can be used that remembers where in a string the 'EOF' would be if it existed. In this approach, the output of the BWT must include both the transformed string, and the final value of the pointer. The inverse transform then shrinks it back down to the original size: it is given a string and a pointer, and returns just a string.
A complete description of the algorithms can be found in Burrows and Wheeler's paper, or in a number of online sources. The algorithms vary somewhat by whether EOF is used, and in which direction the sorting was done. In fact, the original formulation did not use an EOF marker. |
9515_9 | Bijective variant
Since any rotation of the input string will lead to the same transformed string, the BWT cannot be inverted without adding an EOF marker to the end of the input or doing something equivalent, making it possible to distinguish the input string from all its rotations. Increasing the size of the alphabet (by appending the EOF character) makes later compression steps awkward.
There is a bijective version of the transform, by which the transformed string uniquely identifies the original, and the two have the same length and contain exactly the same characters, just in a different order. |
9515_10 | The bijective transform is computed by factoring the input into a non-increasing sequence of Lyndon words; such a factorization exists and is unique by the Chen–Fox–Lyndon theorem, and may be found in linear time. The algorithm sorts the rotations of all the words; as in the Burrows–Wheeler transform, this produces a sorted sequence of n strings. The transformed string is then obtained by picking the final character of each string in this sorted list. The one important caveat here is that strings of different lengths are not ordered in the usual way; the two strings are repeated forever, and the infinite repeats are sorted. For example, "ORO" precedes "OR" because "OROORO..." precedes "OROROR...". |
9515_11 | For example, the text "^BANANA|" is transformed into "ANNBAA^|" through these steps (the red | character indicates the EOF pointer) in the original string. The EOF character is unneeded in the bijective transform, so it is dropped during the transform and re-added to its proper place in the file.
The string is broken into Lyndon words so the words in the sequence are decreasing using the comparison method above. (Note that we're sorting '^' as succeeding other characters.) "^BANANA" becomes (^) (B) (AN) (AN) (A). |
9515_12 | Up until the last step, the process is identical to the inverse Burrows-Wheeler process, but here it will not necessarily give rotations of a single sequence; it instead gives rotations of Lyndon words (which will start to repeat as the process is continued). Here, we can see (repetitions of) four distinct Lyndon words: (A), (AN) (twice), (B), and (^). (NANA... doesn't represent a distinct word, as it is a cycle of ANAN....)
At this point, these words are sorted into reverse order: (^), (B), (AN), (AN), (A). These are then concatenated to get
^BANANA |
9515_13 | The Burrows-Wheeler transform can indeed be viewed as a special case of this bijective transform; instead of the traditional introduction of a new letter from outside our alphabet to denote the end of the string, we can introduce a new letter that compares as preceding all existing letters that is put at the beginning of the string. The whole string is now a Lyndon word, and running it through the bijective process will therefore result in a transformed result that, when inverted, gives back the Lyndon word, with no need for reassembling at the end.
Relatedly, the transformed text will only differ from the result of BWT by one character per Lyndon word; for example, if the input is decomposed into six Lyndon words, the output will only differ in six characters.
For example, applying the bijective transform gives:
The bijective transform includes eight runs of identical
characters. These runs are, in order: XX,
II,
XX,
PP,
..,
EE,
..,
and
IIII. |
9515_14 | In total, 18 characters are used in these runs.
Dynamic Burrows–Wheeler transform
When a text is edited, its Burrows–Wheeler transform will change. Salson et al. propose an algorithm that deduces the Burrows–Wheeler transform of an edited text from that of the original text, doing a limited number of local reorderings in the original Burrows–Wheeler transform, which can be faster than constructing the Burrows–Wheeler transform of the edited text directly.
Sample implementation
This Python implementation sacrifices speed for simplicity: the program is short, but takes more than the linear time that would be desired in a practical implementation. It essentially does what the pseudocode section does.
Using the STX/ETX control codes to mark the start and end of the text, and using s[i:] + s[:i] to construct the ith rotation of s, the forward transform takes the last character of each of the sorted rows: |
9515_15 | def bwt(s: str) -> str:
"""Apply Burrows–Wheeler transform to input string."""
assert "\002" not in s and "\003" not in s, "Input string cannot contain STX and ETX characters"
s = "\002" + s + "\003" # Add start and end of text marker
table = sorted(s[i:] + s[:i] for i in range(len(s))) # Table of rotations of string
last_column = [row[-1:] for row in table] # Last characters of each row
return "".join(last_column) # Convert list of characters into string
The inverse transform repeatedly inserts r as the left column of the table and sorts the table. After the whole table is built, it returns the row that ends with ETX, minus the STX and ETX. |
9515_16 | def ibwt(r: str) -> str:
"""Apply inverse Burrows–Wheeler transform."""
table = [""] * len(r) # Make empty table
for i in range(len(r)):
table = sorted(r[i] + table[i] for i in range(len(r))) # Add a column of r
s = [row for row in table if row.endswith("\003")][0] # Find the correct row (ending in ETX)
return s.rstrip("\003").strip("\002") # Get rid of start and end markers
Following implementation notes from Manzini, it is equivalent to use a simple null character suffix instead. The sorting should be done in colexicographic order (string read right-to-left), i.e. in Python. (The above control codes actually fail to satisfy EOF being the last character; the two codes are actually the first. The rotation holds nevertheless.) |
9515_17 | BWT Applications
As a lossless compression algorithm the Burrows-Wheeler Transform offers the important quality that its encoding is reversible and hence the original data may be recovered from the resulting compression. The lossless quality of Burrows Algorithm has provided for different algorithms with different purposes in mind. To name a few, Burrows Wheeler Transform is used in algorithms for sequence alignment, image compression, data compression, etc. The following is a compilation of some uses given to the Burrows-Wheeler Transform. |
9515_18 | BWT for Sequence Alignment
The advent of next-generation sequencing (NGS) techniques at the end of the 2000s decade has led to another application of the Burrows–Wheeler transformation. In NGS, DNA is fragmented into small pieces, of which the first few bases are sequenced, yielding several millions of "reads", each 30 to 500 base pairs ("DNA characters") long. In many experiments, e.g., in ChIP-Seq, the task is now to align these reads to a reference genome, i.e., to the known, nearly complete sequence of the organism in question (which may be up to several billion base pairs long). A number of alignment programs, specialized for this task, were published, which initially relied on hashing (e.g., Eland, SOAP, or Maq). In an effort to reduce the memory requirement for sequence alignment, several alignment programs were developed (Bowtie, BWA, and SOAP2) that use the Burrows–Wheeler transform. |
9515_19 | BWT for Image Compression |
9515_20 | The Burrows-Wheeler Transformation has proved to be fundamental for image compression applications. For example, Showed a compression pipeline based on the application of the Burrows-Wheeler Transformation followed by Inversion, Run-Length, and Arithmetic encoders. The pipeline developed in this case is known as Burrows-Wheeler Transform with an Inversion Encoder (BWIC). The results shown by BWIC are shown to outperform the compression performance of well-known and widely used algorithms like Lossless_JPEG and JPEG_2000. BWIC is shown to outperform Lossless_JPEG and JPEG_2000 in terms of final compression size of radiography medical images on the order of 5.1% and 4.1% respectively. The improvements are achieved by combining BWIC and a pre-BWIC scan of the image in a vertical snake order fashion. More recently, additional works like that of have shown the implementation of the Burrows-Wheeler Transform in conjunction with the known Move-to-front transform(MTF) achieve near |
9515_21 | lossless compression of images. |
9515_22 | BWT for Compression of Genomic Databases
Cox et al. presented a genomic compression scheme that uses BWT as the algorithm applied during the first stage of compression of several genomic datasets including the human genomic information. Their work proposed that BWT compression could be enhanced by including a second stage compression mechanism called same-as-previous encoding ("SAP"), which makes use of the fact that suffixes of two or more prefix letters could be equal. With the compression mechanism BWT-SAP, Cox et al. showed that in the genomic database ERA015743, 135.5 GB in size, the compression scheme BWT-SAP compresses the ERA015743 dataset by around 94%, to 8.2 GB. |
9515_23 | BWT for Sequence Prediction
BWT has also been proved to be useful on sequence prediction which is a common area of study in machine learning and Natural Language Processing. In particular, Ktistakis et al. proposed a sequence prediction scheme called SuBSeq that exploits the lossless compression of data of the Burrows-Wheeler Transform. SuBSeq exploits BWT by extracting the FM-index and then performing a series of operations called backwardSearch, forwardSearch, neighbourExpansion, and getConsequents in order to search for predictions given a suffix. The predictions are then classified based on a weight and put into an array from which the element with the highest weight is given as the prediction from the SuBSeq algorithm. SuBSeq has been show to outperform state of the art algorithms for sequence prediction both in terms of training time and accuracy.
References |
9515_24 | External links
Article by Mark Nelson on the BWT
A Bijective String-Sorting Transform, by Gil and Scott
Yuta's openbwt-v1.5.zip contains source code for various BWT routines including BWTS for bijective version
On Bijective Variants of the Burrows–Wheeler Transform, by Kufleitner
Blog post and project page for an open-source compression program and library based on the Burrows–Wheeler algorithm
MIT open courseware lecture on BWT (Foundations of Computational and Systems Biology)
League Table Sort (LTS) or The Weighting algorithm to BWT by Abderrahim Hechachena (claims to be faster, but correctness is not proven)
Lossless compression algorithms
Transforms
Articles with example pseudocode
Articles with example Python (programming language) code
Articles with example R code |
9516_0 | The rhetoric of health and medicine (or medical rhetoric) is an academic discipline concerning language and symbols in health and medicine. Rhetoric most commonly refers to the persuasive element in human interactions and is often best studied in the specific situations in which it occurs. As a subfield of rhetoric, medical rhetoric specifically analyzes and evaluates the structure, delivery, and intention of communications messages in medicine- and health-related contexts. Primary topics of focus includes patient-physician communication, health literacy, language that constructs disease knowledge, and pharmaceutical advertising (including both direct-to-consumer and direct-to-physician advertising). The general research areas are described below. Medical rhetoric is a more focused subfield of the rhetoric of science. |
9516_1 | Practitioners from the medical rhetoric field hail from a variety of disciplines, including English studies, communication studies, and health humanities. Through methods such as content analysis, survey methodology, and usability testing, researchers in this sphere recognize the importance of communication to successful healthcare.
Several communication journals, including Communication Design Quarterly, Journal of Business and Technical Communication, Technical Communication Quarterly, and Present Tense, have published special issues on themes related to medical rhetoric. The majority of research in the field is indexed in the academic database EBSCO Communication & Mass Media Complete. In 2013, scholars in the field also began a biennial symposium, Discourses of Health and Medicine.
History of the field |
9516_2 | The rhetoric of health and medicine is tied to the emergence of rhetoric of science in the early 1970s and 1980s. Contemporary theorists such as Kenneth Burke, Michel Foucault, Thomas Kuhn, Bruno Latour, and Steve Woolgar laid the theoretical groundwork for this early interest in the persuasive dimensions of scientific language. In the 1980s the field shifted when rhetorical critics like Martha Solomon and Charles Anderson began analyzing texts on biomedicine. Solomon analyzed the rhetoric used in medical reports during the Tuskegee Syphilis Project, while Anderson examined the writings of surgeon Richard Selzer to comment on the rhetoric of surgery. |
9516_3 | In the 1990s, the rhetoric of health and medicine emerged more clearly as a field distinct from rhetoric of science. Rhetorical scholar Celeste Condit raised questions about the historical and rhetorical dimensions of issues like abortion and genetics in works such as 1990's Decoding Abortion Rhetoric: Communicating Social Change and 1999's The Meanings of the Gene: Public Debates about Heredity. In these seminal works, Condit focused on what she called "rhetorical formations," or the multiple simultaneous discourses that surrounded each rhetorical object. |
9516_4 | The field also saw the rise of discussion on disability studies and illness narratives during the 1990s, which initiated the beginning of a Special Interest Group on disability studies at the annual Conference on College Composition and Communication (CCCC), headed by Brenda Jo Brueggemann. The initiation of this group then inspired a Medical Rhetoric Special Interest Group, headed by Barbara Heifferon, which has continued to meet annually to present day.
In the early 21st century, scholars began to pay increasing attention to various topics in the rhetoric of health and medicine. J. Blake Scott's 2003 book Risky Rhetoric: AIDS and the Cultural Practices of HIV Testing used Michel Foucault's theory of examination, which defines rhetoric as a form of disciplinary power, to examine the cultural condition that influence HIV testing. He reported that the rhetoric used in public policy and various propaganda led to the stigmatization and discrimination of people with HIV/AIDS. |
9516_5 | In 2005, Judy Segal's Health and the Rhetoric of Medicine gained recognition for highlighting the persuasive elements in diagnoses, health policies, illness experiences, and illness narratives. She also addressed direct-to-consumer advertising of prescription drugs, the role of health information in creating the "worried well," and problems of trust and expertise in doctor-patient relationships.
In 2010, Lisa Keränen's Scientific Characters: Rhetoric, Politics, and Trust in Breast Cancer Research addressed issues of research viability and relationships among scientists, patients, and advocates. Kimberly Emmons’ work on the rhetoric surrounding depression, Black Dogs and Blue Words: Depression and Gender in the Age of Self-Care, was published the same year.
Research areas
Rhetoric of pharmaceutical and science commercialization |
9516_6 | The rhetoric of pharmaceutical and science commercialization is the study of the persuasive language and symbols that the pharmaceutical industry and biotechnology companies use to communicate and influence consumers, physicians, regulatory agencies, and other stakeholders in the commercialization of biotechnology. Scholars have found that the language used to define, describe, and regulate pharmaceuticals influences the understanding and perception of the drugs among both the general public and experts. Information about pharmaceutical products is highly regulated and filtered through many channels as it moves from scientist to consumer. Despite the regulations on pharmaceutical advertising, pharmaceutical companies use carefully crafted direct-to-consumer advertising to rhetorically influence the patient-physician dialogue to drive consumption of specific pharmaceutical drugs. Furthermore, pharmaceutical companies mislead physicians and scientists through deceptive rhetorical |
9516_7 | strategies in technical documentation (which both package inserts directed towards physicians and medical journal articles directed towards scientists). In a recent study, a pharmaceutical company disguised negative performance in one group of subjects by selectively merging data between different patient groups in clinical trials and carefully crafting supporting statements. This study shows that scientific data and knowledge is secondary to rhetorical messages supporting commercialization, and that human health is secondary to company profit. Notably, technical information is subject to obfuscation and distortion so that the message communicated outside of a commercial organization aligns with the primary goal of selling a product. Studying and trying to improve the rhetorical processes involved in pharmaceutical information as it moves through the chain of dissemination is a key concern of rhetorical scholarship on this topic. |
9516_8 | Rhetoric of mental health |
9516_9 | The rhetoric of mental health considers how language functions in the production of knowledge on topics such as mental and psychological disorders, chemical imbalances in the brain, and variations on what are considered normal mental faculties. The $100 million Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative, introduced by the Obama administration in 2013, is testament to the emerging importance of brain science and mental health in medical science and public policy debate. Neurorhetoric, the study of how language is used in the creation, distribution, and reception of science about the brain, has recently become an important topic in medical rhetoric and composition studies, as well as in popular science publications targeted at non-scientists. Information and texts relevant to the rhetoric of mental health include psychotropic pharmaceutical regulations, their production, prescription, advertising, and consumption, and scientific and popular |
9516_10 | discussions about major depressive disorder, bipolar disorder, obsessive-compulsive disorder, schizophrenia, autism, and other mental disorders. The Diagnostic and Statistical Manual of Mental Disorders (DSM, now in its 5th edition) is a central text for the study of the mental health profession. |
9516_11 | Patient narrative |
9516_12 | Patient narrative is the clinical story of a person's past and present medical history documented by a medical clinician. The patient narrative can also be referred to as the medical history, the History and Physical (H & P), or the clinical narrative. The H&P includes a Subject, Objective, Assessment, and Plan (SOAP note), which summarizes the patient's narrative or history of medical illness, objectively reports the patient's clinical data and lab results, assesses diagnoses and prognoses, and often recommends how to address the patient's clinical situation. As part of the American Recovery and Reinvestment Act of 2009, the government enacted the Health Information Technology for Economic and Clinical Health (HITECH) Act, which mandates that health providers transition from handwritten (typed) patient narratives to electronic patient narratives in forms such as the electronic medical record (EMR) or the electronic health record (EHR). The EMR and EHR are of interest to communication |
9516_13 | scholars because they economize the words and space of the traditional patient narrative into a structured system of navigation screens and checkboxes. |
9516_14 | Rhetorics of alternative medicine
The rhetoric of alternative medicine differs from traditional medical rhetoric in its emphasis on the persuasive aspects of language related to holistic or other nonstandard approaches. Some of these alternative medical practices include acupuncture, massage therapy, and chiropractic care. Scholars further explore alternative medical practitioners’ claims that they take a holistic approach to medical treatment, assessing a person's body, mind, and spirit, rather than just treating a disease.
Patient-physician communication |
9516_15 | Starting with references to medical care in ancient Greece, Plato's “Dialogues”, expressed that physician-patient communication should not include any “lively interactions” between the physician and patient. In the Age of Enlightenment, Dr. John Gregory began to emphasize patient-physician communication by introducing the idea of preventative care for “gentleman of a liberal education.” Few found his suggestive style of care useful, and the view that “physicians must assume sole responsibility for protecting the ignorant public from its folly” lived on for some time. As late as the 1980s, the American Medical Association still had not incorporated regulations into their Code of Ethics that required physicians to incorporate patient opinion into the decision-making process. It was not until 1996 when the Health Insurance Portability and Accountability Act (HIPAA) was created to protect patient rights and privacy. This law was intended to assure patients that their wishes would be |
9516_16 | considered in treatment decision-making. |
9516_17 | Professional opportunities
For students who take a more applied approach to health and medical rhetoric, there are an increasing number of employment opportunities in industry, government, and nonprofit organizations. Such opportunities fall into two broadly defined categories: service and advocacy.
Service |
9516_18 | Service is a situation in which a communication expert helps a healthcare professional be more effective in his or her communication efforts. This might mean the communicator is paid to assist with a task like grant writing, editing, or authoring a medical document. Medical transcriptionists, represented by the Association for Healthcare Documentation Integrity (AHDI), provide another form of professional communication in medical discourse. The AHDI is the world's largest nonprofit organization representing individuals and organizations in healthcare documentation. By ensuring documentation's accuracy, privacy, and security, the organization aims to protect public health, increase patient safety, and improve quality of care for healthcare consumers. Other professional medical writing associations include the American Medical Writers Association (AMWA) and the International Academy of Nursing Editors (INANE). |
9516_19 | Sometimes these medical authors are considered “ghostwriters,” or paid writers who write a communicative piece but are not formally acknowledged as a text's author. Karen L. Wooley says that professional writers must adhere to ethical guidelines that ghostwriters may not be expected to follow. While authors control their content when working with a professional medical writer, Wooley says that ghostwriters may try to take control of the content away from the author and hide certain facts, such as where a project's funding comes from. Researchers such as Elliott Moffatt are concerned that medical ghostwriting, especially in the context of pharmaceutical research, is dangerous to public health. Possible dangers can include misrepresenting the data and subtly influencing the way clinicians and patients perceive the data.
Advocacy |
9516_20 | Advocacy in medical rhetoric is a situation in which the communicator addresses a health-related topic, empowering the citizens of a community to understand how that issue impacts them. This type of health communication enables the public to understand a health issue more thoroughly, providing them with the tools necessary to challenge or change existing power structures within their own communities. Advocacy is often associated with risk communication, the process of explaining natural disasters, human-made hazards, and behavioral practices to the public in a way they can understand. Theorists such as Don Nutbeam propose a need for advocacy and say that health literacy, or people's ability to access and make decisions with health information, is an important part of empowerment. Nick Pidgeon and Baruch Fischhoff say that communicating complex medical or health information to the public is difficult because past scientists failed to base their communication on solid principles and |
9516_21 | evidence. Based on these past failures, Pidgeon and Fischhoff argue for a simpler and trustworthier model of science communication. In response to this issue, Jeffrey T. Grabill and W. Michele Simmons propose that technical communicators can provide advocacy because they have both good writing skills and an ability to understand and convey information to patients. |
9516_22 | Rhetorical concepts
Rhetoric, like any field of study, is made up of constituent parts. These parts are often referred to as either rhetorical concepts or rhetorical principles. Rhetorical concepts can be seen as tools of the trade that allow rhetoricians to effectively communicate in a way that is most likely to persuade readers and audiences of the messages and meanings intended by the rhetorician. Rhetorical concepts are an important part of what makes an argument persuasive, and all effective arguments inherently contain them. Rhetorical concepts help rhetoricians convey information that would otherwise be unascertainable by the audience, which is especially important for topics that carry heavy implications, such as the complications that often follow complex medical and health needs.
Figures of Speech |
9516_23 | Figures of speech are a type of figurative language that often convey specialized meaning not based on the literal meaning of the words that make up the figure. Often providing emphasis, freshness of expression, or clarity, they can be used to explain complex, unknown topics to readers and audiences in a way that makes them easier for the reader to understand.
Metaphor and analogy |
9516_24 | Metaphor and analogy are important in scientific communication because they make new ideas understandable to both expert and nonexpert audiences. Disease, for example, which is difficult to comprehend on both large and microbiological scales, is often communicated through metaphor and analogy. When a public health campaign “wages war” on cancer, or a microbiologist describes a virus as “attacking” a cell, these forceful words create a war-like metaphor for understanding the way disease works. Notable work in this area has been done by Judy Segal, who chronicled the impact of five biomedical metaphors in her book Health and the Rhetoric of Medicine, including ‘‘medicine is war,’’ ‘‘the body is a machine,’’ ‘‘diagnosis is health,’’ ‘‘medicine is a business,’’ and ‘‘the person is genes, ’’ all of which have had academic, cultural, and social impacts on the way medicine is practiced and understood. Monika Cwiarka has also questioned the use of laboratory mice in behavior-based studies, |
9516_25 | asking whether certain behaviors observed in mice can be considered analogous to those observed in humans. Another important recent study is Gronnvoll and Landau's research to determine how the public uses metaphor to understand genetic science. |
9516_26 | Hyperbole |
9516_27 | Hyperbole is a figure of speech more often used by a patient when speaking with a doctor than by doctors communicating with their patients. Where some figures of speech can help to lend meaning or understanding to medical and scientific communication, hyperbole often obscures the truth by exaggerating it, which can have detrimental and even deadly results. Headaches, for example, can occasionally be described by patients as feeling as if their “head’s going to explode.” This type of communication can make it difficult for doctors to understand the true gravity of a symptom, which may lead to misdiagnosis. Furthermore, doctors and scientists need to be especially aware of the negative implications that hyperbole can have in medical discourses. As Joseph Loscalzo points out in his article Clinical Trials in Cardiovascular Medicine in an Era of Marginal Benefit, Bias, and Hyperbole, the use of hyperbole by investigators during medical trials can “often prejudice the trialist in favor of |
9516_28 | a positive result.” When investigators provide trialists with bias, whether intentionally or unintentionally, the data that is collected may be skewed in the direction of the bias provided by the investigator. |
9516_29 | Stasis |
9516_30 | Consider a hypothetical conversation between two parties about health care reform. One party may wish to argue the moral necessity of health care reform while the other party wishes to argue that health care reform is economically infeasible. Until both parties agree on the issue at hand (whether it be the economic or moral considerations of health care reform), resolution of the argument cannot take place. Once the parties have agreed on the issue at hand, they have achieved rhetorical stasis. The idea of first agreeing to the issue at hand is central to any discussion between rational people. One example of how stasis can apply to health and medical rhetoric is provided in a recent article by Christa Teston and Scott Graham. These researchers applied the rhetorical concept of stasis to medical discourse by reviewing the FDA discussion on Avastin as a treatment for metastatic breast cancer. They concluded that the absence of stasis resulted in miscommunication between the |
9516_31 | interested parties. The FDA could have achieved stasis, these authors conclude, by first reaching consensus on the following questions: What counts as clinical benefit? What kinds of evidence would be deemed meaningful? |
9516_32 | Rhetorical Appeals
The rhetorical appeals, often referred to as modes of persuasion or ethical strategies, are a set of rhetorical concepts used to persuade audiences. Initially introduced by Aristotle in On Rhetoric, the appeals focus on three ways to persuade your audience: by appealing to the character of the speaker (ethos), the emotions of the audience (pathos), or the logic/truth of the argument itself (logos).
Ethos |
9516_33 | Ethos is an appeal to the authority or credibility of the presenter and is especially important in health and medicine communication. As Sarah Bigi explains in her article The Persuasive Role of Ethos in doctor-patient Interactions, “physicians are expected to inform, advise and persuade patients regarding their health problems.” In order to successfully persuade their patients, doctors need to rely on the rhetorical appeals, and the appeal that patients seem to care about the most is the ethos of the doctor. If a doctor does not seem credible, then a patient is unlikely to follow their instructions or diagnosis, which can lead to further health complications down the line.
Pathos
Pathos is an appeal to the audience's emotions. The speaker may use pathos in a multitude of ways; however, in terms of the rhetoric of health and medicine, two particular emotions stand out: fear and hope. |
9516_34 | When doctors appeal to fear it is not done so lightly. Doctors have to decide if instilling fear in their patient is the right tactic for persuading their patients to agree with the physician's treatment plan. For instance, if a patient has diabetes and is likely to lose a toe or foot if they do not change the way they treat their condition, it is up to the doctor to decide when to stop telling their patient that “changing your habits will give you a better life” and to start telling their patient that “if you don’t stop your current habits, you’re going to lose a foot.”
When doctors appeal to hope, the doctor tries to persuade the patient through describing a scenario of a positive future that's only possible by the patient following the doctor's orders. In some cases, Cognitive Behavioral Therapy, the act of presenting this positive emotional state can actually create a positive result in itself.
Logos |
9516_35 | Logos is logical appeal or the simulation of it. It is normally used to describe facts and figures that support the speaker's claims or thesis. It is important to health and medicine communications because patients want to know which treatments work best, and they want the scientific data to prove it. Having an appeal to logic also enhances ethos because information makes the speaker look knowledgeable and prepared to his or her audience. However, the data can be confusing and thus confuse the audience. So, the doctor has to make sure to leverage the appeals to best persuade their patients. Doctors must decide how many facts and figures are appropriate to persuade an audience of the factual basis of the argument while portraying themselves as a credible speaker and playing to the right emotional state of their patient---all to get the patient to follow the doctor's orders. |
9516_36 | Research methodology
Rhetoricians of health and medicine conduct research primarily through qualitative methods, although quantitative methods are also occasionally employed. Scholars in the field apply these techniques to understand how and for what reasons health and medical communication is accomplished.
Content analysis
Through content analysis, scholars strive to answer the questions first formulated by political scientist Harold Lasswell as they apply to health and medicine texts: “Who says what, to whom, why, to what extent and with what effect?" For example, researchers might study the content of pharmaceutical advertisements on television to determine their appeals to potential consumers. Others might examine the communication of health information via new media such as Twitter and Facebook. Rhetoricians have increasingly turned to computers to facilitate quantitative content analysis as they gather massive data collections from Internet sources. |
9516_37 | Survey research
Researchers in the field are also concerned with the effectiveness of health and medical communications. Audience surveys are often used to determine if a target audience understands a given set of health or medical instructions. The results help researchers adjust these instructions and assist audiences in achieving functional health literacy. Other surveys gauge the public's attitudes and knowledge regarding important medical topics such as mental health. This sort of research identifies gaps for public health agencies to address in their communications. |
9516_38 | Usability testing
Creators of health and medical communications often test their work with a subset of their target audience before its wider release. This practice is particularly important when content creators are not themselves part of their target audience, as is often the case for communications that address vulnerable communities such as senior citizens or immigrants with English as a second language. Usability research can include techniques such as “think aloud” testing, in which potential users talk the researcher through their navigation of a given computer program or text. Evaluations by experts in other fields, such as design or user experience, are also employed.
References
External links
American Medical Writers’ Association (AMWA)
Society for Technical Communication (STC)
Council for Programs in Technical and Scientific Communication (CPTSC)
Association of Teachers of Technical Writing (ATTW)
Rhetoric Society of America (RSA)
Rhetoric
Medicine in society |
9517_0 | The 2000 Pacific hurricane season was an above-average Pacific hurricane season, although most of the storms were weak and short-lived. There were few notable storms this year. Tropical storms Miriam, Norman, and Rosa all made landfall in Mexico with minimal impact. Hurricane Daniel briefly threatened the U.S. state of Hawaii while weakening. Hurricane Carlotta was the strongest storm of the year and the second-strongest June hurricane in recorded history. Carlotta killed 18 people when it sank a freighter. Overall, the season was significantly more active than the previous season, with 19 tropical storms. In addition, six hurricanes developed. Furthermore, there were total of two major hurricanes (Category 3 or greater on the Saffir–Simpson hurricane wind scale). |
9517_1 | The season officially started on May 15 in the Eastern Pacific, and on June 1 in the Central Pacific; they both ended on November 30, 2000. These dates conventionally delimit the period of each year when most tropical cyclones form in the Pacific basin. However, the formation of tropical cyclones is possible at any time of the year; despite this, there were no off-season tropical cyclones this year. Seasonal activity began on May 22, when Hurricane Aletta formed off the southwest coast of Mexico. Two storms formed in June, though the season slowly became active in July when three named storms developed, including Hurricane Daniel, which was the second-strongest storm of the season. August was the most active month of the year, with six named storms forming, including hurricanes Gilma and Hector. September was a relatively quiet month with two storms, one of which was Hurricane Lane. Two storms developed in October including Tropical Storm Olivia, while the final named storm, Tropical |
9517_2 | Storm Rosa, formed in November. |
9517_3 | Seasonal summary
The accumulated cyclone energy index for the 2000 Pacific hurricane season, is 95.35 units. Broadly speaking, ACE is a measure of the power of a tropical or subtropical storm multiplied by the length of time it existed. It is only calculated for full advisories on specific tropical and subtropical systems reaching or exceeding wind speeds of .
The season officially started on May 15, 2000 in the eastern Pacific, and on June 1, 2000 in the central Pacific, and lasted until November 30, 2000. These dates conventionally delimit the period of each year when most tropical cyclones form in the northeastern Pacific Ocean. This season had an above average number of storms. However, it had a below-average number of hurricanes and major hurricanes. There were also two tropical depressions that did not reach storm strength. In the central Pacific, two tropical storms formed. The first storm formed on May 22 and the last storm dissipated on November 8.
Systems |
9517_4 | Hurricane Aletta |
9517_5 | A tropical wave crossed Central America and entered the Gulf of Tehuantepec on May 20. Deep convection developed near the center of the disturbance, and the system became the first tropical depression of the season on May 22 while located south of Acapulco, Mexico. A mid-level ridge forced a west-northwest track away from the Mexican coast. It intensified into Tropical Storm Aletta early on May 23 while located south of Zihuatanejo, Mexico, becoming the first May tropical storm in four years. As it turned westward, it continued a slow intensification trend, before strengthening more quickly due to decreased wind shear. On May 24, Aletta attained hurricane status, and shortly thereafter reached peak winds of ; this made it a Category 2 on the Saffir–Simpson scale. After maintaining peak winds for about 18 hours, Aletta began a weakening trend due to increasing wind shear. At around the same time, a trough eroded the ridge that was steering the movement of Aletta, causing the hurricane |
9517_6 | to remain almost stationary for the next two days. The lack of motion resulted in upwelling which imparted additional weakening, and Aletta dropped to tropical storm status on May 27. It quickly deteriorated that day, and on May 28 the system dissipated well south of Cabo San Lucas after it began a slow north drift. The remnants lingered in the same area for the next several days. |
9517_7 | Hurricane Aletta was the second-strongest May hurricane by pressure, as well as the fourth strongest May hurricane by winds.
Tropical Storm Bud |
9517_8 | The tropical wave that eventually became Tropical Storm Bud was first identified off the coast of Africa on May 22. It moved across the Atlantic Ocean and Caribbean, then into the eastern Pacific Ocean on June 6 with little development. The tropical wave remained disorganized until June 11 when a broad low-pressure area developed southwest of Acapulco, Mexico. The wave was only intensifying slowly, and on June 13, it became strong enough to be designated as a tropical depression. It quickly strengthened to tropical storm intensity six hours later, and moved to the northwest. It was forecast to strengthen to a strong tropical storm with winds reaching , but the storm only reached a peak intensity of early on June 14. Bud turned to the north-northwest, and slowly weakened from June 15 onwards, due to increasing vertical wind shear and cooler ocean water temperatures. The storm's forward speed decreased and began to meander, as the ridge to the north of Bud weakened and a trough |
9517_9 | developed over the western United States. It drifted erratically while located just north of Socorro Island, and was downgraded to a tropical depression on June 16. By the next day, the depression degenerated into an area of low pressure, which persisted until June 19. |
9517_10 | Bud passed near Socorro Island on June 15, with estimated one-minute winds of , and caused large waves along the western coast of Mexico. However, no reports of damage or casualties were received.
Hurricane Carlotta |
9517_11 | A tropical wave left the coast of Africa on June 3. It entered the East Pacific on June 12 and spawned a weak low four days later. It remained disorganized until developing a concentration of deep convection on June 18, and the low became Tropical Depression Three-E by 18:00 UTC that day. It strengthened into Tropical Storm Carlotta six hours later. Moving generally westward at about 11 knots (13 mph), Carlotta developed a ragged banding eye surrounded by deep convection late on June 19, and became a hurricane at 6:00 UTC on the 20th. Carlotta began to rapidly intensify shortly after becoming a hurricane, with its winds increasing by 80 mph in just 24 hours, and it reached peak intensity at 6:00 UTC on the 21st with 155 mph (250 km/h) winds. Shortly thereafter, Carlotta turned to the west-northwest, slowing slightly, around the edge of a mid-tropospheric ridge over Mexico. It quickly weakened during this time, down to 100 knots (115 mph) by 00:00 UTC on June 22. Oscillating eye |
9517_12 | definition that day caused Carlotta to fluctuate in intensity until it resumed weakening on June 23, falling to tropical storm status on June 24 as it moved more quickly towards cooler waters. Diminishing convection caused Carlotta to weaken to tropical depression intensity by 00:00 UTC on June 25, and it dissipated six hours later. A remnant swirl of low clouds persisted for several days afterward. |
9517_13 | Though it never made landfall, Carlotta killed 18 people when it sank the Lithuanian freighter M/V Linkuva. Carlotta is also the third-most intense June tropical cyclone in the east Pacific; only Ava of 1973 and Celia of 2010 were stronger.
Tropical Depression Four-E |
9517_14 | Tropical Depression Four-E formed from the same tropical wave that spawned Tropical Depression Two in the Atlantic Ocean. The tropical wave crossed Central America between June 30 and July 1, continuing to move westward into the Pacific Ocean. The wave became more organized on July 6 and the National Hurricane Center started issuing advisories on the newly developed tropical depression later that day. The NHC initiallu predicted that the depression would reach tropical storm intensity, as there was a lack of vertical wind shear around the system and sea surface temperatures were warm enough for intensification to occur. The depression lacked any deep convection, however, and it began weakening On July 7. The depression entered an area of stronger wind shear and dissipated that day.
Tropical Storm Upana |
9517_15 | A tropical wave organized into Tropical Depression One-C on July 20 while located southeast of the Hawaiian Islands. It strengthened slowly and moved nearly due west, before reaching storm strength later on July 20. The storm was named Upana, which is Hawaiian for "Urban". Despite a favorable environment, Upana strengthened little, reaching a peak intensity on July 21 with winds of . The storm had no deep convection in its circulation on July 22, and was downgraded to a tropical depression in the afternoon. Late on July 23, deep convection flared up, briefly strengthening the system again, but failed to re-gain tropical storm status, as it remained poorly organized. It dissipated on July 24, despite a low-shear environment favorable for development. Upana's remnants continued moving to the west, where JMA classified its remnants as a tropical depression while it was still east of the International Date Line on July 27. It crossed the into the West Pacific shortly afterward. The |
9517_16 | remnants were re-designated as Tropical Depression 12W by the JTWC, and later re-strengthened into a tropical storm and was named Chanchu. Chanchu moved north, and had dissipated by July 30. |
9517_17 | Upana is the first storm in the Central Pacific Hurricane Center's area of responsibility to be named in July, and the first tropical storm to develop in the region since Tropical Storm Paka in the 1997 season.
Tropical Depression Five-E
The origins of Tropical Depression Five-E were first identified on July 8 when a tropical wave moved off the west African coast. It entered the eastern Pacific Ocean on July 16 after tracking over the Caribbean Sea. The wave developed to a tropical depression on July 22. Lacking significant deep convection and moving over cold waters, Five-E never intensified further to a tropical storm. The depression dissipated late on July 23, just one day after it formed.
Hurricane Daniel |
9517_18 | A tropical wave departed the western African coast on July 8. The wave crossed the Atlantic and Central America uneventfully. However, on July 23, while in the East Pacific, the wave's weather became well-organized, and it developed into a tropical depression that day. After reaching tropical storm intensity, the system was named Daniel, and it became a hurricane the next day. Rapid intensification brought Daniel to its peak as a Category 3 hurricane on July 25. Afterwards, the storm fluctuated in intensity until it weakened to a tropical storm on July 30. Daniel slowed, turned northwestward, and passed 120 nautical miles north of Hawaii the next day. Accelerating, Daniel weakened to a tropical depression on August 3 and dissipated two days later. |
9517_19 | No casualties or damaged was reported in association with Hurricane Daniel, despite the system's passing close enough to Hawaii to require tropical storm warnings. It still produced heavy surf conditions along the northern shores of the Hawaiian Islands. Daniel was the first tropical cyclone to be a significant threat to Hawaii since 1994.
Tropical Storm Emilia |
9517_20 | On July 11, a tropical wave moved off the African coast, and moved to the Lesser Antilles one week later. It passed over Central America near Panama on July 22 without any increase in organization. On July 25, the wave began to show curved banding, showing that it had become better organized. It intensified to a tropical depression on July 26 while located south southwest of Manzanillo, Mexico, designated as Tropical Depression Seven-E. The depression was upgraded to Tropical Storm Emilia later that day while moving northwest, steered by a mid-level ridge to its north. During this time, Emilia was forecast to strengthen to a hurricane within two days, due to the system moving over warm waters. However, late on July 27, the storm began to accelerate, meaning that it will move into cooler waters sooner than firstly anticipated, therefore, only allowing the storm to intensify within a few hours before weakening. Emilia moved near Socorro Island and its intensity peaked with wind speeds |
9517_21 | of , with an eyewall beginning to form. A few hours later, the storm moved into cooler waters and drier air, and Emilia's deep convection dissipated, weakening the storm. Late on July 28 deep convection redeveloped near the storm's center, but wind shear prevented Emilia from strengthening. It turned to the west and weakened below tropical storm intensity on July 29, as the deep convection in the storm diminished again. It shortly dissipated while located several hundred miles west south-west of Cabo San Lucas, Mexico. |
9517_22 | Tropical Storm Fabio |
9517_23 | A tropical wave moved off the west coast of Africa on July 19, and entered into the Pacific on July 27. Minimal development occurred in the west-northwestward moving wave until August 1. It was then that the tropical wave began developing a low-level circulation and convective organization was seen to the south of Manzanillo, Colima, Mexico. The system continued to become better organized, and was classified as Tropical Depression Eight-E, which was centered about west-southwest of Manzanillo on August 3 at 1200 UTC. The depression initially moved west-northwestward about , and later slowed and turned westward on August 4. As the depression had curved westward, it had intensified enough to be upgraded to Tropical Storm Fabio. Despite the presence of wind shear, Fabio continued to strengthen and reach a peak intensity of later that day. Fabio turned toward west-southwest while weakening on August 5. Fabio weakened back to a tropical depression on August 6 and dissipated two days |
9517_24 | later about west-southwest of Cabo San Lucas, Mexico. The remnant swirl of low clouds persisted for several more days, eventually undergoing a Fujiwhara interaction with the remains of Hurricane Gilma. |
9517_25 | Hurricane Gilma
Gilma's precursor was a tropical wave that moved off the African coast on July 20 or 21. The wave entered the East Pacific on August 2, and the formation of a well-defined center led to the formation of a depression on August 5, 250 nautical miles south of Manzanillo, Mexico. The system strengthened into a tropical storm at 12:00 UTC that day, at which point it became known as Gilma. Gilma gradually intensified and became a hurricane on August 8 at 6:00 UTC. Gilma reached peak intensity six hours later and moved over cooler waters. Gilma steadily weakened thereafter, and became a tropical depression again at 00:00 UTC on August 10. The cyclone lost any significant convection at 18:00 UTC on the same day, and dissipated six hours later.
Hurricane Hector |
9517_26 | In the middle of August, two tropical storms developed off the Mexican coastline. Hector, the first, became a tropical depression at 18:00 UTC on August 10, and developed banding features late the next day and strengthened into a tropical storm. Hector moved generally westward under the influence of a strong ridge, developed a central dense overcast and a ragged eye, and became a hurricane on August 14. Hector reached peak intensity 12 hours later. Hector then weakened and dissipated over colder water southwest of Baja California. The remnants of Hector passed over the Hawaiian Islands several days later, producing heavy rain over most of the island chain.
Tropical Storm Ileana |
9517_27 | A tropical wave emerged from the African coast on the first day of August. The wave crossed Central America and southern Mexico into the Eastern Pacific, and on August 13, a 12:21 UTC QuikSCAT scan revealed a low-level circulation, and it was designated as a tropical depression. Early the next day, the depression strengthened into a 40 mph tropical storm named Ileana. Tropical Storm Ileana paralleled the Mexican coast and reached peak intensity as a high-end tropical storm early on August 15 with 70 mph winds. The storm maintained this intensity for 18 hours before passing just south of the Baja California Peninsula, turning west, and weakening to a tropical depression late on August 16. It dissipated early the next day, but the remnant low-level circulation persisted until August 20.
Tropical Storm Wene |
9517_28 | A tropical disturbance developed in the Western Pacific Ocean along the eastern periphery of the monsoon trough in mid-August. Located at 33° north, it steadily organized, and became Tropical Depression Sixteen-W on August 15 while located to the northwest of Honolulu, Hawaii. It moved eastward along the west–east-oriented surface pressure trough, and crossed the International Date Line later on August 15. Abnormally warm sea surface temperatures allowed the system to intensify despite its unusually high latitude, and it became Tropical Storm Wene on August 16. It quickly attained a peak intensity of , but weakened due to colder sea surface temperatures and wind shear. Wene continued to weaken, and dissipated when the storm merged with an extratropical cyclone. |
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