which is used to describe a third component of thinking processes, particularly preverbal, and it denotes the concept that the world is activated by some generalized "energy" that links together causally all objects and events ; it is presumably revealed by a person's lack of curiosity about causal connections, as though they were self-evident. Aside from the rather frequent use of such key words, having strong connotations for this reviewer far away from what the author is aiming to denote, the book is written in a lucid and stimulating style that makes reading it an invigorating intellectual exercise. It is a book that is likely to have somewhat limited attraction to the full-time clinician, especially one treating adult patients. And child psychiatrists and psychologists, if reasonably well read, will most likely be familiar with the majority of references from which this author has synthesized his material. On the other hand, the scholarly and refreshing con¬ ceptual approaches of the author will appeal to psychologists, philosophers, linguists, and psychiatrists with a research bent and anyone else who wants to be provoked to do some thinking on the problems of language, language development, and the psychology of cognition. Louis A. GOTTSCHALK, M.D. Plans and the Structure of Behavior. By George A Miller, Eugene gALANTER, and Karl H. Pribram. Price, $5.00. Pp. 226. Henry Holt & Co., Inc., New York 17, 1960. This is an important book for psychiatrists and behavioral scientists, since it presents a clear, concise study of the application of cybernetics, information and computer theory to the problem of analyzing behavior. The authors have been actively engaged in behavioral research in different areas\p=m-\Millerin information and communication, Galanter in experimental psychology, and Pribram in neurophysiology. The book resulted from a series of discussions which they engaged in during a year they spent together at the Center for Advanced Study in the Behavioral Sciences, Palo Alto, Calif. Their original intent was to write a diary, as it were, of the development of their ideas and, fortunately, enough of this remains to make the book clear, easy to read, and interesting. It is also fortunate, however, that in the final writing a variety of studies comparing the "behavior" of computing machines with human "cognitive behavior" have been reviewed and summarized. The result is one of the best presentations of the present status of the brain-computer problem. The authors, however, do not discuss certain aspects of this problem, such as the difference between the brain and its vast number of parallel channels, but few operations, and the modern high-speed computer with its few channels and vast numbers of operations. This omission is consistent with their interest, since it would introduce the question of mechanisms rather than the problem of the structure of behavior as it is observed in everyday life in the clinic and in experiments on learning, conditioning, etc. Similarly, they do not discuss the qualitative differences between mechanisms of memory in the computer and those in the brain. In the former, a "memory"\p=m-\ i.e., stored information\p=m-\isidentified, metaphorically speaking, by an address, whereas no such mechanism is known in the brain (personal communication, Dr. Julian Bigelow). With few exceptions, however, the data, concepts, and theories presented are handled with elegant precision, as illustrated by the discussion of Sherrington's concepts of the "Reflex" and the "Synapse," Kurt Lewin's ideas of "tension states," and the numerous references to the work of Newell, Shaw, and Simon on computers and logic. There are, nevertheless, areas with

https://link.springer.com/content/pdf/10.1057%2Fjors.1968.86.pdf

Plans and the Structure of Behavior

Decades of research have repeatedly shown that people perform poorly at estimating and understanding conditional probabilities that are inherent in Bayesian reasoning problems. Yet in the medical domain, both physicians and patients make daily, life-critical judgments based on conditional probability. Although there have been a number of attempts to develop more effective ways to facilitate Bayesian reasoning, reports of these findings tend to be inconsistent and sometimes even contradictory. For instance, the reported accuracies for individuals being able to correctly estimate conditional probability range from 6% to 62%. In this work, we show that problem representation can significantly affect accuracies. By controlling the amount of information presented to the user, we demonstrate how text and visualization designs can increase overall accuracies to as high as 77%. Additionally, we found that for users with high spatial ability, our designs can further improve their accuracies to as high as 100%. By and large, our findings provide explanations for the inconsistent reports on accuracy in Bayesian reasoning tasks and show a significant improvement over existing methods. We believe that these findings can have immediate impact on risk communication in health-related fields.

/pdf/improving-bayesian-reasoning-the-effects-of-phrasing-21jmphbkcj.pdf

Improving Bayesian Reasoning: The Effects of Phrasing, Visualization, and Spatial Ability

Despite notable scientific and medical advances, broader political, socioeconomic and behavioural factors continue to undercut the response to the COVID-19 pandemic1,2. Here we convened, as part of this Delphi study, a diverse, multidisciplinary panel of 386 academic, health, non-governmental organization, government and other experts in COVID-19 response from 112 countries and territories to recommend specific actions to end this persistent global threat to public health. The panel developed a set of 41 consensus statements and 57 recommendations to governments, health systems, industry and other key stakeholders across six domains: communication; health systems; vaccination; prevention; treatment and care; and inequities. In the wake of nearly three years of fragmented global and national responses, it is instructive to note that three of the highest-ranked recommendations call for the adoption of whole-of-society and whole-of-government approaches1, while maintaining proven prevention measures using a vaccines-plus approach2 that employs a range of public health and financial support measures to complement vaccination. Other recommendations with at least 99% combined agreement advise governments and other stakeholders to improve communication, rebuild public trust and engage communities3 in the management of pandemic responses. The findings of the study, which have been further endorsed by 184 organizations globally, include points of unanimous agreement, as well as six recommendations with >5% disagreement, that provide health and social policy actions to address inadequacies in the pandemic response and help to bring this public health threat to an end. 

/pdf/a-multinational-delphi-consensus-to-end-the-covid-19-public-3techjk7.pdf

A multinational Delphi consensus to end the COVID-19 public health threat

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths and substantial morbidity worldwide. Intense scientific effort to understand the biology of SARS-CoV-2 has resulted in daunting numbers of genomic sequences. We witnessed evolutionary events that could mostly be inferred indirectly before, such as the emergence of variants with distinct phenotypes, for example transmissibility, severity and immune evasion. This Review explores the mechanisms that generate genetic variation in SARS-CoV-2, underlying the within-host and population-level processes that underpin these events. We examine the selective forces that likely drove the evolution of higher transmissibility and, in some cases, higher severity during the first year of the pandemic and the role of antigenic evolution during the second and third years, together with the implications of immune escape and reinfections, and the increasing evidence for and potential relevance of recombination. In order to understand how major lineages, such as variants of concern (VOCs), are generated, we contrast the evidence for the chronic infection model underlying the emergence of VOCs with the possibility of an animal reservoir playing a role in SARS-CoV-2 evolution, and conclude that the former is more likely. We evaluate uncertainties and outline scenarios for the possible future evolutionary trajectories of SARS-CoV-2. In this Review, Markov, Katzourakis and colleagues explore the evolution of SARS-CoV-2 at different scales, the phases of the COVID-19 pandemic, factors that drive the evolution of the virus, theories for the emergence of epidemiologically important variants and potential future evolutionary scenarios and their likely health repercussions. 

/pdf/the-evolution-of-sars-cov-2-1ifd7o7m.pdf

The evolution of SARS-CoV-2

In medicine, genetics, criminology and various other areas, Venn and Euler diagrams are used to visualize data set relations and their cardinalities. The data sets are represented by closed curves and the data set relationships are depicted by the overlaps between these curves. Both the sets and their intersections are easily visible as the closed curves are preattentively processed and form common regions that have a strong perceptual grouping effect. Besides set relations such as intersection, containment and disjointness, the cardinality of the sets and their intersections can also be depicted in the same diagram (referred to as area-proportional) through the size of the curves and their overlaps. Size is a preattentive feature and so similarities, differences and trends are easily identified. Thus, such diagrams facilitate data analysis and reasoning about the sets. However, drawing these diagrams manually is difficult, often impossible, and current automatic drawing methods do not always produce appropriate diagrams.

This dissertation presents novel automatic drawing methods for different types of Euler diagrams and a user study of how such diagrams can help probabilistic judgement. The main drawing algorithms are: eulerForce, which uses a force-directed approach to lay out Euler diagrams; eulerAPE, which draws area-proportional Venn diagrams with ellipses. The user study evaluated the effectiveness of area- proportional Euler diagrams, glyph representations, Euler diagrams with glyphs and text+visualization formats for Bayesian reasoning, and a method eulerGlyphs was devised to automatically and accurately draw the assessed visualizations for any Bayesian problem. Additionally, analytic algorithms that instantaneously compute the overlapping areas of three general intersecting ellipses are provided, together with an evaluation of the effectiveness of ellipses in drawing accurate area-proportional Venn diagrams for 3-set data and the characteristics of the data that can be depicted accurately with ellipses.

Visualizing set relations and cardinalities using Venn and Euler diagrams

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases1-3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission. 

/pdf/wastewater-sequencing-reveals-early-cryptic-sars-cov-2-146hej2j.pdf

Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission

..................................................................................................................................... 2 Approval .................................................................................................................................... 3 Acknowledgements .................................................................................................................... 4 Table of contents ........................................................................................................................ 5 List of Tables .............................................................................................................................. 8 List of Figures ............................................................................................................................ 9 Chapter 1. Research Problems, Objectives and Significance .................................................. 10 Chapter 2. Literature review .................................................................................................... 14 Performance of Conditional Probability Problems .............................................................. 14 Different verbal formats for conditional probability problems ........................................ 15 Conditional probability reasoning and other forms of reasoning .................................... 17 Use of visuals in conditional probability problem solving .................................................. 19 Problems with Venn and Euler diagrams ......................................................................... 20 Relevant Cognitive Theories ................................................................................................ 21 Baddeley and Hitch’s model of working memory ........................................................... 21 Dual-coding theory .......................................................................................................... 22 Mental models .................................................................................................................. 23 Graph comprehension theory ........................................................................................... 24 Cognitive load theory ....................................................................................................... 26 Working memory and short-term memory capacity ........................................................ 27 Relational complexity ...................................................................................................... 31 Cognitive load theory and relational complexity in HCI Research ................................. 33 Synthesis and key findings................................................................................................... 34 Chapter 3. Hypothesis Development ....................................................................................... 36 How Visuals Can Improve Performance .............................................................................. 37 Hypotheses ........................................................................................................................... 38 Hypothesis 1..................................................................................................................... 40 Hypothesis 2..................................................................................................................... 41 Hypothesis 3..................................................................................................................... 41 Hypothesis 4..................................................................................................................... 42 Chapter 4. Method ................................................................................................................... 43 Participants ........................................................................................................................... 43 Experiment design ............................................................................................................... 44 Treatments ............................................................................................................................ 45

https://via.library.depaul.edu/cgi/viewcontent.cgi?article=1002&context=cdm_etd

Vincent J Kellen

Papers

Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission

The Effects of Diagrams and Relational Complexity on User Performance in Conditional Probability Problems in a Non-Learning Context