This article appraises cultural understanding and controversies regarding hikikomori (prolonged social withdrawal), with reference to research over the past 20 years. Initially viewed as a uniquely Japanese phenomenon, hikikomori is now recognised globally, prompting a re-evaluation of its cultural, psychological and socioeconomic demographics. A revision in lifestyle after the COVID-19 pandemic and ongoing technological advancements – particularly the rise of social media, gaming and the internet – have paradoxically both exacerbated isolation and provided new forms of social interaction for young adults who confine themselves at home. This phenomenon underlines the complex interplay between putative individual psychopathology, neurodiversity and broader societal shifts across the globe.

Prior to the No Surprises Act (NSA), numerous states passed laws protecting patients from surprise medical bills from out-of-network (OON) hospital-based physicians supporting elective treatment in in-network hospitals. Even in non-emergency situations, patients have little ability to choose physicians such as anaesthesiologists, pathologists or radiologists. Using a comprehensive, multi-payer claims database, we estimated the effect of these laws on hospital-based physician reimbursement, charges, network participation and potential surprise billing episodes. Overall, the state laws were associated with a reduction in anaesthesiology prices and charges, but an increase in pathology and radiology prices. The price effects for each state exhibit substantial heterogeneity. California and New Jersey experienced increases in network participation by anaesthesiologists and pathologists and reductions in potential surprise billing episodes, but, overall, we find little evidence of changes in network participation across all of the states implementing surprise billing laws. Our results suggest that the effects of the NSA may vary across states.

High prevalence of long COVID symptoms has emerged as a significant public health concern. This study investigated the associations between three doses of COVID-19 vaccines and the presence of any and ≥3 types of long COVID symptoms among people with a history of SARS-CoV-2 infection in Hong Kong, China. This is a secondary analysis of a cross-sectional online survey among Hong Kong adult residents conducted between June and August 2022. This analysis was based on a sub-sample of 1,542 participants with confirmed SARS-CoV-2 infection during the fifth wave of COVID-19 outbreak in Hong Kong (December 2021 to April 2022). Among the participants, 40.9% and 16.1% self-reported having any and ≥3 types of long COVID symptoms, respectively. After adjusting for significant variables related to sociodemographic characteristics, health conditions and lifestyles, and SARS-CoV-2 infection, receiving at least three doses of COVID-19 vaccines was associated with lower odds of reporting any long COVID symptoms comparing to receiving two doses (adjusted odds ratio [AOR]: 0.69, 95% CI: 0.54, 0.87, P = .002). Three doses of inactivated and mRNA vaccines had similar protective effects against long COVID symptoms. It is important to strengthen the coverage of COVID-19 vaccination booster doses, even in the post-pandemic era.

Systematic review and meta-analysis were conducted to provide comprehensive information on the prevalence of amphistome infections in domestic ruminants in sub-Saharan Africa. A systematic search of peer-reviewed articles published between 2002 and 2023 was conducted. Prevalence estimates and meta-analysis were based on 76 peer-reviewed articles which met the inclusion criteria. Of the 55,122 domestic ruminants screened, 12,858 were infected, and the overall pooled prevalence was 22% (95% confidence interval [CI], 10-37). The highest prevalence was recorded in southern Africa 25% (95% CI, 0-62), and central Africa 16% (95% CI, 0-61) the lowest. Cattle were the most frequently sampled hosts (76.56%, n = 42,202) and sheep (8.78%, n = 4838) the lowest, and cattle recorded the highest pooled prevalence of 28% (95% CI, 12-47), and goats the lowest at 5% (95% CI, 0-14). Prevalence rate was the high in males 32% (95% CI, 21-44), adult ruminants 37% (95% CI, 15-62) and animals with poor body condition 47% (95% CI, 34-60), and during the wet season 36% (95% CI, 0-94). The highest pooled prevalence was recorded at postmortem 23% (95% CI, 8-43) compared to coprology 20% (95% CI, 6-39) studies. The meta-regression model demonstrated that the body condition score, host, and period, and the interactions of different factors significantly influenced the prevalence. The lowest prevalence rate was noted for the period between 2013 and 2023. This is the first systematic review and meta-analysis in sub-Saharan Africa that provides a comprehensive review of the prevalence of amphistome infections in domestic ruminants in the past 20 years.

Social impact has been widely discussed by the engineering community, but studies show that there is currently little systematic consideration of the social impact of products in both academia and in industry beyond social impacts on health and safety. While Failure Mode and Effect Analysis (FMEA) is useful for evaluating health and safety risks, new developments are needed to create an FMEA-style evaluation that can be applied to a wide range of social impacts for engineered products. The authors describe necessary modifications to traditional FMEA that transform it into a tool for social impact analysis. The modification of FMEA involves the introduction of positive and negative impacts, the inclusion of discrete and continuous impacts, the consideration of various stakeholder types, and the inclusion of uncertainty in place of detectability. This modified FMEA is referred to in this paper as Social Impact Effects Analysis (SIEA). The paper describes how SIEA is performed and articulates the potential benefits of SIEA.

The advent of generative artificial intelligence (AI) models holds potential for aiding teachers in the generation of pedagogical materials. However, numerous knowledge gaps concerning the behavior of these models obfuscate the generation of research-informed guidance for their effective usage. Here, we assess trends in prompt specificity, variability, and weaknesses in foreign language teacher lesson plans generated by zero-shot prompting in ChatGPT. Iterating a series of prompts that increased in complexity, we found that output lesson plans were generally high quality, though additional context and specificity to a prompt did not guarantee a concomitant increase in quality. Additionally, we observed extreme cases of variability in outputs generated by the same prompt. In many cases, this variability reflected a conflict between outdated (e.g. reciting scripted dialogues) and more current research-based pedagogical practices (e.g. a focus on communication). These results suggest that the training of generative AI models on classic texts concerning pedagogical practices may bias generated content toward teaching practices that have been long refuted by research. Collectively, our results offer immediate translational implications for practicing and training foreign language teachers on the use of AI tools. More broadly, these findings highlight trends in generative AI output that have implications for the development of pedagogical materials across a diversity of content areas.

Many population biology, ecology, and evolution experiments rely on the accuracy of the classification of individuals and the estimation of size population. The visual classification of vinegar flies, Drosophila melanogaster (Diptera: Drosophilidae), morphs is a laborious task usually performed by bench workers. Because of the size of the flies and the degree of precision needed to distinguish the morphological features on which the classification is based, the work is performed using a dissecting microscope. Here, we describe a method to automate the counting and identification of two types of vinegar flies, white and wild individuals. Our method is based on the image-recognition artificial intelligence (AI) tool, FlydAI (FlyDetector AI), which proved to correctly classify the flies when high-quality images were used, with a success rate of up to 100% in samples containing up to 200 individuals. This is a significant improvement with respect to preexisting approaches in terms of accuracy and specificity of the morphs detected. Although this tool is exclusively trained to routine lab tasks involving wild and white D. melanogaster, the AI can be easily trained to recognise different vinegar fly mutants and other types of insects of similar size, and its potential in other areas still needs to be explored.

Exopsychology is a sub-discipline of psychology concerned with how humans contemplateextraterrestrials as well as forming hypothesis about how these beings may think, feel and behave. While researching the former is undoubtedly a subject for empirical science, aspects of the latter remain uncertain. Given the contemporary scientific insight, it may still be possible to identify a set of cornerstones and eventually create a space of possible configurations of the extraterrestrial mind. Here, we identify three basic compatibility requirements: first, any form of life must navigate internal and external (environmental) demands and thus actively ensure the compatibility of its current state with the same demands. Second, any advanced cognitive development and the emergence of remotely detectable technosignatures require not only the relevant capabilities for manipulation but also compatibility with a permissive environment. Lastly, requirements also concern the compatibility of extraterrestrial thinking and behaviour with our search method. In its most basic understanding, search for extraterrestrial intelligence (SETI) searches for something done by somebody. However, the meaning of this simple formula and the psychological theory behind it is underdeveloped. Hence, psychological aid is needed to assist SETI in its effort to reveal whether galactic information indicates the presence of a mere object or activity of an identified subject with whom humans may establish contact. The fact that people believe in and search for extraterrestrials emphasizes that psychology should pay attention to this domain of phenomena. Hence, different imaginations of the extraterrestrial, ranging from benign to cruel, from superior to equally developed, are briefly discussed regarding their emergence and function as coping and motivating mechanisms for the uncertain search.

Migrant labor exploitation is widespread in developed countries, which host growing populations of undocumented migrants. While denouncing by migrants is essential to prosecute exploitative employers, an undocumented community actively hiding from the state is unlikely to whistleblow. I consider an intervention providing migrant farmworkers in Italy information and incentives to report on their racketeers. I leverage the staggered rollout of the intervention to study its effects in a difference-in-differences framework. The intervention empowered migrants to whistleblow, increased the prosecution of criminal organizations responsible for racketeering migrants, and raised awareness among natives, who became more favorable toward immigration and parties supporting it. These findings highlight the conditions under which undocumented migrants can take political action for their socioeconomic advancement. Unlike other integration policies which have been shown to backlash, highlighting migrants’ vulnerability to exploitation might foster solidarity and more liberal immigration attitudes among natives.

In this paper, we establish a definitive result which almost completely closes the problem of bounded elementary generation for Chevalley groups of rank $\ge 2$ over arbitrary Dedekind rings R of arithmetic type, with uniform bounds. Namely, we show that for every reduced irreducible root system $\Phi $ of rank $\ge 2$, there exists a universal bound $L=L(\Phi )$ such that the simply connected Chevalley groups $G(\Phi ,R)$ have elementary width $\le L$ for all Dedekind rings of arithmetic type R.

A classical problem, due to Gerencsér and Gyárfás from 1967, asks how large a monochromatic connected component can we guarantee in any r-edge colouring of $K_n$? We consider how big a connected component we can guarantee in any r-edge colouring of $K_n$ if we allow ourselves to use up to s colours. This is actually an instance of a more general question of Bollobás from about 20 years ago which asks for a k-connected subgraph in the same setting. We complete the picture in terms of the approximate behaviour of the answer by determining it up to a logarithmic term, provided n is large enough. We obtain more precise results for certain regimes which solve a problem of Liu, Morris and Prince from 2007, as well as disprove a conjecture they pose in a strong form.

We also consider a generalisation in a similar direction of a question first considered by Erdős and Rényi in 1956, who considered given n and m, what is the smallest number of m-cliques which can cover all edges of $K_n$? This problem is essentially equivalent to the question of what is the minimum number of vertices that are certain to be incident to at least one edge of some colour in any r-edge colouring of $K_n$. We consider what happens if we allow ourselves to use up to s colours. We obtain a more complete understanding of the answer to this question for large n, in particular, determining it up to a constant factor for all $1\le s \le r$, as well as obtaining much more precise results for various ranges including the correct asymptotics for essentially the whole range.