Miracle-dz/UniFAR-FTUs huggingface dataset:
A Procedure for Collecting Mental Workload Data During an Experiment That Is Comparable to IMPRINT Workload Data

Abstract : U.S. Army Research Laboratory (ARL) analysts use the Improved Performance Research Integration Tool (IMPRINT) to predict the mental workload and performance of Soldiers operating the Future Combat System (FCS) manned ground vehicles. IMPRINT is a human-performance-modeling tool that analysts use to build models representing Soldiers interacting with equipment to accomplish a mission. The models contain tasks, task sequences, task times, and workload estimates that allow the software to calculate estimates of mental workload and mission performance. One of the key outputs from the IMPRINT models is the combination of tasks likely to contribute to high Soldier workload. Evaluators of FCS equipment can include the potentially high workload task combinations into their evaluations to be sure that they evaluate the tasks mostly like to contribute to mental overload. The U.S. Army Aberdeen Test Center (ATC) is one of the groups responsible for testing and evaluating FCS equipment and concepts. They must identify any issues that might degrade mission performance, including Soldier mental overload. To ensure that the ATC evaluations include tasks relevant to Soldier mental workload they can include high workload task combinations identified by IMPRINT into their test plans. However, to be compatible with IMPRINT, they must evaluate workload by a methodology compatible with the IMPRINT technique. This report outlines the methodology ATC and ARL developed within the Automated Communications Analysis of Situation Awareness /IMPRINT/Joint Warfighter Test and Training Capability test conducted in May 2008.
Novel technical and privacy-preserving technology for artificial intelligence in ophthalmology

Purpose of review The application of artificial intelligence (AI) in medicine and ophthalmology has experienced exponential breakthroughs in recent years in diagnosis, prognosis, and aiding clinical decision-making. The use of digital data has also heralded the need for privacy-preserving technology to protect patient confidentiality and to guard against threats such as adversarial attacks. Hence, this review aims to outline novel AI-based systems for ophthalmology use, privacy-preserving measures, potential challenges, and future directions of each. Recent findings Several key AI algorithms used to improve disease detection and outcomes include: Data-driven, imagedriven, natural language processing (NLP)-driven, genomics-driven, and multimodality algorithms. However, deep learning systems are susceptible to adversarial attacks, and use of data for training models is associated with privacy concerns. Several data protection methods address these concerns in the form of blockchain technology, federated learning, and generative adversarial networks. Summary AI-applications have vast potential to meet many eyecare needs, consequently reducing burden on scarce healthcare resources. A pertinent challenge would be to maintain data privacy and confidentiality while supporting AI endeavors, where data protection methods would need to rapidly evolve with AI technology needs. Ultimately, for AI to succeed in medicine and ophthalmology, a balance would need to be found between innovation and privacy.
Impact of Patient Education via WeChat on Bowel Preparation for Colonoscopy

Supplemental digital content is available in the text. The aim of this study was to evaluate the impact of education via WeChat on the quality of bowel preparation in patients undergoing colonoscopy through a meta-analysis of randomized controlled trials. Randomized controlled trials of bowel preparation education provided via WeChat for patients undergoing colonoscopy were screened from databases such as PubMed, Web of Science, Cochrane Library, and Embase. Papers published from the date of database construction to May 1, 2021, were extracted, and a meta-analysis was performed using Review Manager software. A total of four randomized controlled trials were included in the meta-analysis. The results showed that for patients undergoing colonoscopy, education via WeChat significantly improves the quality of bowel preparation for colonoscopy, reduces the insertion time, and increases the adenoma detection rate and the patient's compliance and willingness to repeat bowel preparation. In conclusion, education via WeChat before colonoscopy can significantly improve the quality of bowel preparation.
COMPARISON OF CO2 EMISSIONS DUE TO BUILDING CONSTRUCTION BETWEEN JAPAN AND U.S.

The aim of this study is to characterize energy consumption and CO2 emission due to building construction in Japan by comparing U.S. We have compared from the view point of cost, energy consumption and CO2 emission per unit floor area of new building construction between Japan and U.S. The results are as follows.1) Total cost of building materials per unit floor area of new building construction in Japan is about 1.6 times larger compared to that in U.S.2) New building construction in U.S. tends to use fewer amounts of structural building materials than Japan. 3) Embodied energy of structural building materials in Japan is less than or comparable to that in U.S.
A statistical modelling approach for source attribution meta‐analysis of sporadic infection with foodborne pathogens

Numerous source attribution studies for foodborne pathogens based on epidemiological and microbiological methods are available. These studies provide empirical data for modelling frameworks that synthetize the quantitative evidence at our disposal and reduce reliance on expert elicitations. Here, we develop a statistical model within a Bayesian estimation framework to integrate attribution estimates from expert elicitations with estimates from microbial subtyping and case‐control studies for sporadic infections with four major bacterial zoonotic pathogens in the Netherlands (Campylobacter, Salmonella, Shiga toxin‐producing E. coli [STEC] O157 and Listeria). For each pathogen, we pooled the published fractions of human cases attributable to each animal reservoir from the microbial subtyping studies, accounting for the uncertainty arising from the different typing methods, attribution models, and year(s) of data collection. We then combined the population attributable fractions (PAFs) from the case‐control studies according to five transmission pathways (domestic food, environment, direct animal contact, human–human transmission and travel) and 11 groups within the foodborne pathway (beef/lamb, pork, poultry meat, eggs, dairy, fish/shellfish, fruit/vegetables, beverages, grains, composite foods and food handlers/vermin). The attribution estimates were biologically plausible, allowing the human cases to be attributed in several ways according to reservoirs, transmission pathways and food groups. All pathogens were predominantly foodborne, with Campylobacter being mostly attributable to the chicken reservoir, Salmonella to pigs (albeit closely followed by layers), and Listeria and STEC O157 to cattle. Food‐wise, the attributions reflected those at the reservoir level in terms of ranking. We provided a modelling solution to reach consensus attribution estimates reflecting the empirical evidence in the literature that is particularly useful for policy‐making and is extensible to other pathogens and domains.
Rutin increases alpha‐tubulin acetylation via histone deacetylase 6 inhibition

Microtubules are dynamic cytoskeletal filaments composed of alpha‐ (α) and beta (β)‐tubulin proteins. α‐tubulin proteins are posttranslationally acetylated, and loss of acetylation is associated with axonal transport defects, a common alteration contributing to the pathomechanisms of several neurodegenerative diseases. Restoring α‐tubulin acetylation by pharmacological inhibition of HDAC6, a primary α‐tubulin deacetylase, can rescue impaired transport. Therefore, HDAC6 is considered a promising therapeutic target for neurodegenerative diseases, but currently, there is no clinically approved inhibitor for this purpose. In this study, using drug repurposing strategy, we aimed to identify compounds possessing HDAC6 inhibition activity and inducing α‐tubulin acetylation. We systematically analyzed the FDA‐approved library by utilizing virtual screening and consensus scoring approaches. Inhibition activities of promising compounds were tested using in vitro assays. Motor neuron‐like NSC34 cells were treated with the candidate compounds, and α‐tubulin acetylation levels were determined by Western blot. Our results demonstrated that rutin, a natural flavonoid, inhibits cellular HDAC6 activity without inducing any toxicity, and it significantly increases α‐tubulin acetylation level in motor neuron‐like cells.
COVID-19–induced acute kidney injury in critically ill patients: epidemiology, risk factors, and outcome

Background The kidney represents a potential target for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Clinical data about acute kidney injury (AKI) during SARS-CoV-2 infection are lacking. We aimed to investigate the proportion, risk factors, and prognosis of AKI in critical patients affected with SARS-CoV-2. Methods A case/control study was conducted in two intensive care units of a tertiary teaching hospital. Results Among 109 patients, 75 were male (69%) with median age at 64 years and 48 (44%) developed AKI within 4 days (interquartile range [IQR], 1–9). Of them, 11 (23%), 9 (19%), and 28 (58%) were classified as stage 1, 2, and 3, respectively. AKI patients were older and presented more sepsis, acute respiratory distress syndrome, and rhabdomyolysis; higher initial urea and creatinine; more marked inflammatory syndrome and hematological disorders; and required more mechanical ventilation and vasopressors. An elevated D-dimers level (odds ratio [OR], 12.83; 95% confidence interval [CI], 1.9–85) was an independent factor of AKI. Sepsis was near to significance (OR, 5.22; 95% CI, 0.94–28; P=0.058). AKI was independently related to mortality (OR, 6.8; 95% CI, 1.49–105) and significantly reduced the survival (14.7 days; IQR, 12-17 vs. 19.9 days; IQR, 17-22.7; P=0.011) in AKI and no AKI group respectively. Hypoxemia with the ratio of the arterial partial pressure of oxygen and the inspiratory concentration of oxygen <70, and vasopressors were identified as mortality factors. Conclusions AKI occurred in almost half the studied patients and significantly worsened their prognosis. A high D-dimers level and sepsis contributed significantly to its development.
Rediscovery of Michajlovia turdi (Digenea: Brachylaimoidea) from Japan

ABSTRACT Michajlovia turdi (Yamaguti, 1939) (Digenea: Brachylaimoidea) has been found from the Japanese thrush, Turdus cardis Temminck, 1831, in Hokkaido, the northernmost island of Japan. This is a rediscovery of M. turdi in Japan after approximately 80 years from the original description of the species as Leucochloridium turdi Yamaguti, 1939. Here we redescribe the morphology of M. turdi and generate DNA barcodes for the species by sequencing nuclear ribosomal RNA (18S and 28S) and mitochondrial cytochrome c oxidase subunit I (COI) genes. Our molecular phylogenetic analysis was not effective at determining the taxonomic rank of Michajlovia in Brachylaimoidea, and consequently the genus remains as incertae sedis.
Absence of Connexin 43 results in smaller retinas and arrested, depolarized retinal progenitor cells in human retinal organoids.

The development of the vertebrate retina relies on complex regulatory mechanisms to achieve its characteristic layered morphology containing multiple neuronal cell types. While connexin 43 (CX43) is not expressed by mature retinal neurons mutations in its gene GJA1 are associated with microphthalmia and low vision in patients. To delineate how lack of CX43 affects retinal development, GJA1 was disrupted in human induced pluripotent stem cells (hiPSCs) (GJA1-/-) using CRISPR/Cas9 editing, and these were subsequently differentiated into retinal organoids. GJA1-/- hiPSCs do not display defects in self-renewal and pluripotency, but the resulting organoids are smaller with a thinner neural retina and decreased abundance of many retinal cell types. CX43-deficient organoids express lower levels of the neural marker PAX6 and the retinal progenitor cell (RPC) markers PAX6, SIX3, and SIX6. Conversely, expression of the early neuroectoderm markers SOX1 and SOX2 remains high in GJA1-/- organoids throughout their development. Lack of CX43 results in an increased population of CHX10-positive RPCs that are smaller, disorganized, do not become polarized, and possess a limited ability to commit to retinal fate specification. Our data indicate that lack of CX43 causes a developmental arrest in RPCs that subsequently leads to pan-retinal defects and stunted ocular growth.
Research progress of BK virus and systemic lupus erythematosus

Background: Systemic lupus erythematosus (SLE) is an autoimmune disease in which patients are often infected by viruses due to deficient immunity or immunosuppressant use. BK virus (BKV)mainly affects the kidney and can also cause multiple organ involvement throughout the body, which is similar to SLE. BKV is mostly a latent infection in vivo. The incidence of virus reactivation is higher in SLE patients. Reactivation of BKV can induce the production of autoantibodies, thereby promoting the occurrence and development of SLE. Purpose: Aim of this article is to review the prevalence and pathegenesis of BKV infection in SLE patients. Method: The literature search was conducted using four different databases including PubMed, Cochrane Library, Scopus and Web of Science. Results: BK virus is higher infection and reactivation in SLE patients. The "hapten carrier" mechanism may lead to the production of autoantibodies. Some immunosuppressive drugs, like leflumide and hydroxychloroquine, may show a protective effect. Conclusions: BKV infection plays a role in the occurrence and development of SLE, and its significance deserves further exploration.
The Adaptive Olfactory Measure of Threshold (ArOMa-T): a rapid test of olfactory function

Purpose: Many widely-used psychophysical tests of olfaction have limitations that can create barriers to adoption outside research settings. For example, tests that measure the ability to identify odors may confound sensory performance with memory recall, verbal ability, and past experience with the odor. Conversely, threshold-based tests typically avoid these issues, but are labor intensive. Additionally, many commercially available olfactory tests are slow and may require a trained administrator, making them impractical for use in a short wellness visit or other broad clinical assessment. Methods: We tested the performance of the Adaptive Olfactory Measure of Threshold (ArOMa-T) -- a novel odor detection threshold test that employs an adaptive Bayesian algorithm paired with a disposable odor-delivery card -- in a non-clinical sample of individuals (n=534) at the 2021 Twins Day Festival in Twinsburg, OH. Results: Participants successfully completed the test in under 3 min with a false alarm rate of 9.6% and a test-retest reliability of 0.61. Odor detection thresholds differed by sex (~3.2-fold) and between the youngest and oldest age groups (~8.7-fold), consistent with prior work. In an exploratory analysis, we failed to observe evidence of detection threshold differences between participants who reported a history of COVID-19 and matched controls who did not. We also found evidence for broad-sense heritability of odor detection thresholds. Conclusion: Together, these data indicate the ArOMa-T can determine odor detection thresholds. The ArOMa-T may be particularly valuable in clinical or field settings where rapid and portable assessment of olfactory function is needed.
Integrated single-cell RNA sequencing analysis reveals alterations of ageing human lung endothelium heterogeneity in idiopathic pulmonary fibrosis

Increasing age is the main risk factor for chronic lung diseases (CLD) including idiopathic pulmonary fibrosis (IPF). Halting or reversing progression of IPF remains an unmet clinical need due to limited knowledge of underlying mechanisms. In particular, the contribution of the endothelium to ageing in human lung under physiological conditions and in IPF remains insufficiently understood. In this study, we analysed heterogeneity of endothelium in physiologically ageing human lung and its alterations in IPF. We conducted a comprehensive in silico analysis of scRNAseq profiles of human lung tissues from older healthy donors and age-matched IPF patients (n=9 for each group) by integrating datasets from two independent cohorts. We generated a single-cell map of the ageing human lung and identified 17 subpopulations of ageing endothelium (12 for blood and 5 for lymphatic vessels, including 4 'de-differentiated'), with distinct transcriptional profiles, specific gene expression signatures and percentage contributions, revealing previously underappreciated extent of heterogeneity. In IPF lung, the balance of different endothelial sub-types was significantly altered both in terms of cell numbers and gene expression patterns, identifying disease-relevant subpopulations and transcriptional changes associated with specific signalling pathways and cellular processes. These findings reveal a previously unrecognised phenomenon of ageing human lung endothelium re-programming towards an 'IPF endothelium' state, suggesting potential avenues for therapeutic management or biomarker discovery for diagnostics or prognostics of IPF. Our study creates a conceptual framework for appreciating the heterogeneity of ageing endothelium and its alterations in CLDs and diseases associated with fibrosis in other organs, including lymphoedema and cancer.
Full title: Derivation and external validation of clinical prediction rules identifying children at risk of linear growth faltering (stunting) presenting for diarrheal care Short title: Clinical prediction rules for growth faltering after diarrhea

Affiliations: 1. Division of Infectious Diseases, University of Utah School of Medicine, Salt Lake City, UT, USA 2. Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA 3. Department of Global Health, Global Center for Integrated Health of Women, Adolescents and Children (Global WACh), University of Washington, Seattle, WA, USA 4. International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh 5. Department of Emergency Medicine, Warren Alpert Medical School of Brown University, Providence, RI, USA 6. Department of Pediatrics and Environmental and Global Health, Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA 7. Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, VA, USA 8. Department of Pediatrics, Center for Vaccine Development, University of Maryland School of Medicine, Baltimore, MD, USA
Space Oddity? A Statistical Formulation of Conjunction Assessment

Satellite conjunctions involving ‘near misses’ of space objects are becoming increasingly likely. One approach to risk analysis for them involves the computation of the collision probability, but this has been regarded as having some counter-intuitive properties and its interpretation has been debated. This paper formulates an approach to satellite conjunction based on a simple statistical model and discusses inference on the miss distance between the two objects, both when the relative velocity can be taken as known and when its uncertainty must be taken into account. It is pointed out that the usual collision probability estimate can be badly biased, but that highly accurate inference on the miss distance is possible. The ideas are illustrated with case studies and Monte Carlo results that show its excellent performance.
Building and curating conversational corpora for diversity-aware language science and technology

We present an analysis pipeline and best practice guidelines for building and curating corpora of everyday conversation in diverse languages. Surveying language documentation corpora and other resources that cover 67 languages and varieties from 28 phyla, we describe the compilation and curation process, specify minimal properties of a unified format for interactional data, and develop methods for quality control that take into account turn-taking and timing. Two case studies show the broad utility of conversational data for (i) charting human interactional infrastructure and (ii) tracing challenges and opportunities for current ASR solutions. Linguistically diverse conversational corpora can provide new insights for the language sciences and stronger empirical foundations for language technology.
Transition to Linearity of Wide Neural Networks is an Emerging Property of Assembling Weak Models

Wide neural networks with linear output layer have been shown to be near-linear, and to have near-constant neural tangent kernel (NTK), in a region containing the optimization path of gradient descent. These findings seem counter-intuitive since in general neural networks are highly complex models. Why does a linear structure emerge when the networks become wide? In this work, we provide a new perspective on this"transition to linearity"by considering a neural network as an assembly model recursively built from a set of sub-models corresponding to individual neurons. In this view, we show that the linearity of wide neural networks is, in fact, an emerging property of assembling a large number of diverse"weak"sub-models, none of which dominate the assembly.
An Accurate Unsupervised Method for Joint Entity Alignment and Dangling Entity Detection

Knowledge graph integration typically suffers from the widely existing dangling entities that cannot find alignment cross knowledge graphs (KGs). The dangling entity set is unavailable in most real-world scenarios, and manually mining the entity pairs that consist of entities with the same meaning is labor-consuming. In this paper, we propose a novel accurate Unsupervised method for joint Entity alignment (EA) and Dangling entity detection (DED), called UED. The UED mines the literal semantic information to generate pseudo entity pairs and globally guided alignment information for EA and then utilizes the EA results to assist the DED. We construct a medical cross-lingual knowledge graph dataset, MedED, providing data for both the EA and DED tasks. Extensive experiments demonstrate that in the EA task, UED achieves EA results comparable to those of state-of-the-art supervised EA baselines and outperforms the current state-of-the-art EA methods by combining supervised EA data. For the DED task, UED obtains high-quality results without supervision.
Noise and fluctuations can undermine the efficiency of Majority Rule in Group Evaluation problems

Crowdsourcing is a mechanism by means of which groups of people are able to execute a task by sharing ideas, efforts and resources. Thanks to the online technologies, crowdsourcing has become in the last decade an even more utilized process in different and diverse fields. An instance of such process is the so-called "label aggregation problem": in practice, it is the evaluation of an item by groups of agents, where each agent gives its own judgment of it. Starting from the individual evaluations of their members, how can the groups give their global assessment? In this work, by means of a game-theoretical, evolutionary approach, we show that in most cases the majority rule (the group evaluation is the evaluation of the majority of its members) is still the best way to get a reliable group evaluation, even when the agents are not the best experts of the topic at stake; on the other hand, we also show that noise (i.e., fortuitous errors, misunderstanding, or every possible source of non-deterministic outcomes) can undermine the efficiency of the procedure in non-trivial situations. Therefore, in order to make the process as reliable as possible, the presence of noise and its effects should be carefully taken into account.