On the dependability and feasibility of layperson ratings of divergent thinking

A new system for subjective rating of responses to divergent thinking tasks was tested using raters recruited from Amazon Mechanical Turk. The rationale for the study was to determine if such raters could provide reliable (aka generalizable) ratings from the perspective of generalizability theory. To promote reliability across the Alternative Uses and Consequence task prompts often used by researchers as measures of Divergent Thinking, two parallel scales were developed to facilitate feasibility and validity of ratings performed by laypeople. Generalizability and dependability studies were conducted separately for two scoring systems: the average-rating system and the snapshot system. Results showed that it is difficult to achieve adequate reliability using the snapshot system, while good reliability can be achieved on both task families using the average-rating system and a specific number of items and raters. Additionally, the construct validity of the average-rating system is generally good, with less validity for certain Consequences items. Recommendations for researchers wishing to adopt the new scales are discussed, along with broader issues of generalizability of subjective creativity ratings. © 2018 Hass, Rivera and Silvia

Traumatized to Death: The Cumulative Effects of Serial Parole Denials

Content warning: discussion of suicide. If you are thinking about suicide, please call the National Suicide Prevention Lifeline at 800-273-TALK (8255)

Student + Design + Competition: Decoding the Competition Culture

It is believed that young1 or undiscovered designers bring fresher and innovative ideas to the table of architectural competitions. For many aspiring and unrecognized young designers, a design competition is an opportunity to win public contracts and recognition through good, innovative design. Bjarke Ingels, Zaha Hadid, Alvar Aalto, Henry Hobson Richardson, Daniel Libeskind, Renzo Piano and Richard Rogers are all examples of well-known architects who gained recognition by entering and winning an architectural design competition, and thus catapulting their careers into the limelight. The idea of competition is a very intriguing one. Competition brings forth passion, excitement, visionary ideas and the ambition to succeed. As an architecture student, it is very inspiring to discover the story of Maya Lin, who was a mere twenty-year-old undergraduate student at Yale University when her design for the Vietnam Veteran’s Memorial triumphed over 1,420 other entries. More impressive than winning the competition as a student was that Maya Lin’s design was actually constructed. Maya Lin’s story encourages young designers to compete side-by-side with prestigious architects. Yet some architects regard young designers with a lack of respect. They equate not having the architecture license as having inadequate 1 For this investigation, the author will identify the term “young designer” as an undergraduate or graduate student studying at a university or college, an individual under forty years of age, or a newly established firm with less than five years of experience. In addition, the term “designer” replaces the identity of an “architect” as an individual cannot be given the title architect unless he or she is licensed

Forelimb kinematics during swimming in the pig-nosed turtle, Carettochelys insculpta, compared with other turtle taxa: rowing versus flapping, convergenceversus intermediacy

Animals that swim using appendages do so by way of rowing and/or flapping motions. Often considered discrete categories, rowing and flapping are more appropriately regarded as points along a continuum. The pig-nosed turtle, Carettochelys insculpta, is unusual in that it is the only freshwater turtle to have limbs modified into flippers and swim via synchronous forelimb motions that resemble dorsoventral flapping, traits that evolved independently from their presence in sea turtles. We used high-speed videography to quantify forelimb kinematics in C. insculpta and a closely related, highly aquatic rower (Apalone ferox). Comparisons of our new data with those previously collected for a generalized freshwater rower (Trachemys scripta) and a flapping sea turtle (Caretta caretta) allow us to: (1) more precisely quantify and characterize the range of limb motions used by flappers versus rowers, and (2) assess whether the synchronous forelimb motions of C. insculpta can be classified as flapping (i.e. whether they exhibit forelimb kinematics and angles of attack more similar to closely related rowing species or more distantly related flapping sea turtles). We found that the forelimb kinematics of previously recognized rowers (T. scripta and A. ferox) were most similar to each other, but that those of C. insculpta were more similar to rowers than to flapping C. caretta. Nevertheless, of the three freshwater species, C. insculpta was most similar to flapping C. caretta. ‘Flapping’ in C. insculpta is achieved through humeral kinematics very different from those in C. caretta, with C. insculpta exhibiting significantly more anteroposterior humeral motion and protraction, and significantly less dorsoventral humeral motion and depression. Based on several intermediate kinematic parameters and angle of attack data, C. insculpta may in fact represent a synchronous rower or hybrid rower-flapper, suggesting that traditional views of C. insculpta as a flapper should be revised

How Can Transformer Models Shape Future Healthcare: A Qualitative Study

Transformer models have been successfully applied to various natural language processing and machine translation tasks in recent years, e.g. automatic language understanding. With the advent of more efficient and reliable models (e.g. GPT-3), there is a growing potential for automating time-consuming tasks that could be of particular benefit in healthcare to improve clinical outcomes. This paper aims at summarizing potential use cases of transformer models for future healthcare applications. Precisely, we conducted a survey asking experts on their ideas and reflections for future use cases. We received 28 responses, analyzed using an adapted thematic analysis. Overall, 8 use case categories were identified including documentation and clinical coding, workflow and healthcare services, decision support, knowledge management, interaction support, patient education, health management, and public health monitoring. Future research should consider developing and testing the application of transformer models for such use cases

Potential of Large Language Models in Health Care: Delphi Study

Background: A large language model (LLM) is a machine learning model inferred from text data that captures subtle patterns of language use in context. Modern LLMs are based on neural network architectures that incorporate transformer methods. They allow the model to relate words together through attention to multiple words in a text sequence. LLMs have been shown to be highly effective for a range of tasks in natural language processing (NLP), including classification and information extraction tasks and generative applications. Objective: The aim of this adapted Delphi study was to collect researchers’ opinions on how LLMs might influence health care and on the strengths, weaknesses, opportunities, and threats of LLM use in health care. Methods: We invited researchers in the fields of health informatics, nursing informatics, and medical NLP to share their opinions on LLM use in health care. We started the first round with open questions based on our strengths, weaknesses, opportunities, and threats framework. In the second and third round, the participants scored these items. Results: The first, second, and third rounds had 28, 23, and 21 participants, respectively. Almost all participants (26/28, 93% in round 1 and 20/21, 95% in round 3) were affiliated with academic institutions. Agreement was reached on 103 items related to use cases, benefits, risks, reliability, adoption aspects, and the future of LLMs in health care. Participants offered several use cases, including supporting clinical tasks, documentation tasks, and medical research and education, and agreed that LLM-based systems will act as health assistants for patient education. The agreed-upon benefits included increased efficiency in data handling and extraction, improved automation of processes, improved quality of health care services and overall health outcomes, provision of personalized care, accelerated diagnosis and treatment processes, and improved interaction between patients and health care professionals. In total, 5 risks to health care in general were identified: cybersecurity breaches, the potential for patient misinformation, ethical concerns, the likelihood of biased decision-making, and the risk associated with inaccurate communication. Overconfidence in LLM-based systems was recognized as a risk to the medical profession. The 6 agreed-upon privacy risks included the use of unregulated cloud services that compromise data security, exposure of sensitive patient data, breaches of confidentiality, fraudulent use of information, vulnerabilities in data storage and communication, and inappropriate access or use of patient data. Conclusions: Future research related to LLMs should not only focus on testing their possibilities for NLP-related tasks but also consider the workflows the models could contribute to and the requirements regarding quality, integration, and regulations needed for successful implementation in practice

HIV-1 Vpr Causes Synaptodendritic Damage in Neurons

HIV weakens the immune system by infecting and destroying T-cells, leaving the body vulnerable to infection and the development of AIDS. Conventional treatments for HIV, such as combined anti-rectroviral therapy (cART), fail to prevent the development of HIV-associated neurocognitive disorder (HAND). Neurological dysfunction has been directly related to the invasion of HIV in the central nervous system (CNS). HIV produces neurotoxic proteins, such as the Viral Protein R (Vpr), which contribute to HAND. Astrocytes are the most abundant cells in the brain and an important HIV target. We hypothesize that astrocytes expressing Vpr will cause neuronal damage in our co-culture system. Primary astrocytes were transfected with Vpr plasmid or control (pEGFP or mock) using electroporation. Astrocytes were then co-cultured with cortical neurons. At 48 and 72 hours we collected the primary astrocytes to confirm the Vpr expression via western blot analysis. We then measured structural damage in the neurons using immunofluorescence for cytoskeletal (MAP2, f-actin) and synaptic (synaptophysin) damage. Preliminary results showed strong staining of filamentous actin and MAP2 with weak detection of synaptophysin. The positive control for neurotoxicity (2.8µM acrylamide) showed substantial damage to the cellular structure. Results for Vpr expression are pending. After confirming that the immunofluorescence assays are working with our controls, we expect to detect any synaptodendritic damage in the neurons caused by Vpr in our upcoming experiments

Aquatic turning performance of painted turtles (Chrysemys picta) and functional consequences of a rigid body design

The ability to capture prey and avoid predation in aquatic habitats depends strongly on the ability to perform unsteady maneuvers (e.g. turns), which itself depends strongly on body flexibility. Two previous studies of turning performance in rigid-bodied taxa have found either high maneuverability or high agility, but not both. However, examinations of aquatic turning performance in rigid-bodied animals have had limited taxonomic scope and, as such, the effects of many body shapes and designs on aquatic maneuverability and agility have yet to be examined. Turtles represent the oldest extant lineage of rigid-bodied vertebrates and the only aquatic rigid-bodied tetrapods. We evaluated the aquatic turning performance of painted turtles, Chrysemys picta (Schneider, 1783) using the minimum length-specific radius of the turning path (R/L) and the average turning rate (ωavg) as measures of maneuverability and agility, respectively. We filmed turtles conducting forward and backward turns in an aquatic arena. Each type of turn was executed using a different pattern of limb movements. During forward turns, turtles consistently protracted the inboard forelimb and held it stationary into the flow, while continuing to move the outboard forelimb and both hindlimbs as in rectilinear swimming. The limb movements of backward turns were more complex than those of forward turns, but involved near simultaneous retraction and protraction of contralateral fore- and hindlimbs, respectively. Forward turns had a minimum R/L of 0.0018 (the second single lowest value reported from any animal) and a maximum ωavg of 247.1°. Values of R/L for backward turns (0.0091-0.0950 L) were much less variable than that of forward turns (0.0018-1.0442 L). The maneuverability of turtles is similar to that recorded previously for rigidbodied boxfish. However, several morphological features of turtles (e.g. shell morphology and limb position) appear to increase agility relative to the body design of boxfish

The Self-Pollination of Amur Honeysuckle

Amur honeysuckle (Lonicera maackii) poses a dire threat to the health of forests throughout the eastern United States. While self-pollination has been identified as an important trait of invasive plant species, this trait is understudied, and Amur honeysuckle is anecdotally described as lacking this characteristic. To examine the ability of Amur honeysuckle to self-pollinate, we selected 171 individual shrubs distributed across 9 sites. We compared the number of berries, seeds per berry, and seed germination rates of self- and cross-pollinated flowers by pairing branches covered with pollination bags prior to flower emergence with uncovered branches on the same individual shrub. Out of 171 individuals, 48 produced self-pollinated berries within pollination bags (28%), with 48% of bagged branches exhibiting necrosis due to increased temperature and humidity. Self-pollinated berries produced 1.5 ± 1.4 ( mean ± 1 SD) seeds per berry, whereas cross-pollinated berries produced 3.3 ± 1.5 seeds per berry. In a germination trial, 47.3% of self-pollinated seeds have germinated compared to 41.7% of crosspollinated seeds. This study has shown that Amur honeysuckle can self-pollinate and set viable seed, providing the species with an important mechanism to increase population abundance during early stages of invasion