Miracle-dz/UniFAR-FTUs huggingface dataset:
Single Intersection Traffic Light Control by Multi-agent Reinforcement Learning

Deep reinforcement learning is a data-driven method, which is very promising for alleviating traffic congestion through intelligent control of traffic lights. In this paper, the traffic signal of an intersection is divided into four independent phases and then controlled by deep Q-network (DQN) models respectively. Models can receive observations from their own angle of view, i.e., north-south straight, north-south left turn, east-west straight, east-west left turn, instead of extracting features from the whole scene. We suppose that it is beneficial for learning better policy if agents could sense the environment more precisely. DQN models are jointly trained under the revised QMIX framework to promote coordination capability. For decentralized execution, traffic lights of the phase with the highest Q-value will turn green. The experiments are done under SUMO, the results demonstrate that our method obtains higher reward and lower delay compared to controlling the holistic cycle by using a single DQN model.
Individualized epidemic spreading models predict epilepsy surgery outcomes: a pseudo-prospective study

Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients, but up to 50% of patients continue to have seizures one year after the resection. In order to aid presurgical planning and predict postsurgical outcome in a patient-by-patient basis, we developed a framework of individualized computational models that combine epidemic spreading with patient-specific connectivity and epileptogeneity maps: the Epidemic Spreading Seizure and Epilepsy Surgery framework (ESSES). The ESSES parameters were fitted in a retrospective study (N=15) to reproduce invasive electroencephalography (iEEG)-recorded seizures. ESSES could not only reproduce the iEEG-recorded seizures, but significantly better so for patients with good (seizure-free, SF) than bad (non-seizure-free, NSF) outcome (area under the curve AUC=0.73). Once the model parameters were set in the retrospective study, ESSES can be applied also to patients without iEEG data. We illustrate here the clinical applicability of ESSES with a pseudo-prospective study (N=34) with a blind setting (to the resection strategy and surgical outcome) that emulated the presurgical conditions. ESSES could predict the chances of good outcome after any resection by finding patient-specific optimal resection strategies, which we found to be smaller for SF than NSF patients, suggesting an intrinsic difference in the network organization or presurgical evaluation results of NSF patients. The actual surgical plan also overlapped more with the optimal resection, and had a larger effect in decreasing modeled seizure propagation, for SF patients than for NSF patients. Overall, ESSES could correctly predict 75% of NSF and 80.8% of SF cases pseudo-prospectively. Our results show that individualised computational models may inform surgical planning by suggesting optimal resections and providing information on the likelihood of a good outcome after a proposed resection. This is the first time that such a model is validated on a fully independent cohort without the need for iEEG recordings.
LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype

The accurate classification of lymphoma subtypes using hematoxylin and eosin (H&E)-stained tissue is complicated by the wide range of morphological features these cancers can exhibit. We present LymphoML - an interpretable machine learning method that identifies morphologic features that correlate with lymphoma subtypes. Our method applies steps to process H&E-stained tissue microarray cores, segment nuclei and cells, compute features encompassing morphology, texture, and architecture, and train gradient-boosted models to make diagnostic predictions. LymphoML's interpretable models, developed on a limited volume of H&E-stained tissue, achieve non-inferior diagnostic accuracy to pathologists using whole-slide images and outperform black box deep-learning on a dataset of 670 cases from Guatemala spanning 8 lymphoma subtypes. Using SHapley Additive exPlanation (SHAP) analysis, we assess the impact of each feature on model prediction and find that nuclear shape features are most discriminative for DLBCL (F1-score: 78.7%) and classical Hodgkin lymphoma (F1-score: 74.5%). Finally, we provide the first demonstration that a model combining features from H&E-stained tissue with features from a standardized panel of 6 immunostains results in a similar diagnostic accuracy (85.3%) to a 46-stain panel (86.1%).
Numerical calculations of two-cell and single-cell Taylor flows

Numerical solutions of the Navier-Stokes equations for steady axisymmetric flow in the Taylor experiment are presented. In the cases considered the annulus is so short that only one or two Taylor cells are present. The results are compared with a recent theoretical and experimental study by Benjamin & Mullin (1981). The qualitative picture of the flows possible proposed by Benjamin & Mullin is confirmed by the calculations, and the quantitative agreement with their experimental results is quite satisfactory.
The impact of the COVID-19 pandemic on the mental health of families dealing with attention-deficit hyperactivity disorder

Background The COVID-19 pandemic uprooted regular routines forcing many children to learn from home, requiring many adults to work from home, and cutting families off from support outside the home. Public health restrictions associated with the pandemic caused widespread psychological distress including depression and anxiety, increased fear, panic, and stress. These trends are particularly concerning for families raising neuroatypical children such as those with Attention-Deficit Hyperactivity Disorder (ADHD), as these children are already more likely than their typically developing peers to experience comorbid mental health issues, and to experience greater distress when required to stay indoors. Families with children who have ADHD are also at greater risk for experiencing heightened familial stress due to the challenges associated with managing ADHD behavioural symptoms, greater parental discord and divorce, and greater financial difficulties compared to other families. The current study engaged families comprised of at least one child diagnosed with ADHD to elucidate 1) the unique ways that the COVID-19 pandemic affected their mental health and 2) the specific barriers these families faced to maintaining optimal mental wellbeing. Methods and findings A total of 33 participants (15 parent-child dyads) engaged in virtual interviews. Content analysis revealed that the most frequently identified mental health effects for families were increased child anxiety and disconnectedness, as well as deteriorating parental mental health. The most frequently identified barriers to maintaining optimal mental wellbeing were lack of routine, lack of social interaction and social supports, and uncertainty and fear. Conclusions Findings underscore areas of need during times of large-scale social isolation, specifically for families with children who have ADHD. This work contributes to a growing body of research aimed at creating safeguards to support mental wellbeing for vulnerable families during times of crisis.
X-ray imaging and diffraction from surface phonons on GaAs

Surface acoustic waves (SAWs) are excited on the GaAs (001) surface by using interdigital transducers, designed for frequencies of up to 900 MHz. The emitted phonons with wavelengths down to 3.5 μm are visualized and characterized by combined x-ray diffraction techniques. Using stroboscopic topography, the SAW emission of a parallel and a focusing transducer geometry are imaged. High-resolution x-ray diffraction profiles show up to 12 phonon-induced satellite reflections besides the GaAs (004) reflection, with a width of 9 arcsec each. The diffraction pattern is simulated numerically, applying the kinematical scattering theory to a model crystal. From fits to measured diffraction profiles at different excitation voltages, the SAW amplitudes were calculated and found to be in the sub-nm range.
Preventing contrast-induced acute kidney injury with probucol and hydration in patients with coronary heart disease: A systematic review and meta-analysis of randomized controlled trials

Background: Preventing contrast-induced acute kidney injury (CI-AKI) is critical because of its association with poor clinical outcomes, including extended hospital stays and increased mortality. The effects of probucol on preventing CI-AKI have been controversial. Therefore, this systematic review and meta-analysis evaluated the influence of probucol combined with hydration on the CI-AKI risk in patients with coronary heart disease undergoing coronary angiography (CAG) or percutaneous coronary intervention (PCI). Methods: We retrieved data from the following databases from their inception to May 29, 2022: PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, Chinese Biomedical Literature Database (Sinomed), Wanfang Database, and Chinese Scientific Journal Database. The methodological quality of the trials was assessed following the Cochrane Handbook guidelines, and Review Manager 5.3 and Stata 14.0 software were used for the data analysis. Results: We included 14 trials comprising 3306 patients in the analysis. All included trials reported the CI-AKI incidence rate (the primary outcome). Probucol with hydration significantly reduced the CI-AKI incidence compared to hydration alone (odds ratio [OR]: 0.33, 95% confidence interval [CI]: 0.25–0.44, P < .001). Subgroup analyses were performed based on the contrast medium type (iso-osmolality vs low-osmolality contrast medium [LOCM]) and volume (less than or more than 200 mL); the effects of probucol with hydration versus hydration-only on CI-AKI were comparable within each subgroup. Additionally, the serum creatinine (Scr) concentration 24 hours, 48 hours, and 72 hours and the estimated glomerular filtration rate (eGFR) 72 hours after contrast exposure were better in the probucol with hydration group than the hydration-only group. Finally, major clinical adverse events and adverse drug reactions were comparable between the probucol with hydration and hydration-only groups. Conclusion: Probucol with hydration decreases the CI-AKI incidence compared to hydration only in patients with coronary heart disease undergoing CAG or PCI. However, more high-quality, large-sample, multicenter randomized trials are needed to confirm this conclusion.
The global convergence of spectral RMIL conjugate gradient method for unconstrained optimization with applications to robotic model and image recovery

In 2012, Rivaie et al. introduced RMIL conjugate gradient (CG) method which is globally convergent under the exact line search. Later, Dai (2016) pointed out abnormality in the convergence result and thus, imposed certain restricted RMIL CG parameter as a remedy. In this paper, we suggest an efficient RMIL spectral CG method. The remarkable feature of this method is that, the convergence result is free from additional condition usually imposed on RMIL. Subsequently, the search direction is sufficiently descent independent of any line search technique. Thus, numerical experiments on some set of benchmark problems indicate that the method is promising and efficient. Furthermore, the efficiency of the proposed method is demonstrated on applications arising from arm robotic model and image restoration problems.
In the quest for effective factors of satisfaction with life: Insights from intra-couple interaction and financial management variables

The aim of the study was to investigate the factors affecting life satisfaction with reference to particular reports from both partners in the relationship. The study was conducted within a group of 500 heterosexual couples. The accuracy of the actor-partner interdependence models (APIM) which offer in-depth insights into the dyadic relationships between female and male partners were estimated. The results of the chi-square test enabled us to reject the hypothesis of actor indistinguishability, therefore the model proposing distinguishability with respect to gender was explored further. The results suggest that women’s credit management behavior patterns predict changes in her assessment of well-being. Moreover, the financial behavior patterns of women have an impact on the assessment of well-being as reported by their male partners. Moreover, shared goals and values turned out to be significant with regard to the assessment of quality of life for both women and men. The obtained results provide an insight into the difficulties experienced within relationships and indicate the importance of the roles assumed in various areas of financial management.
Associations between vitamin E status and bone mineral density in children and adolescents aged 8–19 years: Evidence based on NHANES 2005–2006, 2017–2018

Introduction Bone mineral density (BMD) in adolescence is a crucial determinant in osteoporosis and fragility fractures in older age. Vitamin E is the most abundant lipid-soluble antioxidant present in the blood. However, the association of vitamin E status with BMD in children and adolescents remains unclear. Methods We first measured the association of vitamin E status (serum α- and γ tocopherol) with BMD in children and adolescents with the National Health and Nutrition Examination Survey (NHANES). Multiple linear regression models were performed to evaluate their relationship after adjusting for a large range of covariates. Stratified analyses and interaction tests were used to explore their effects on different genders, ages, and races/ethnicities. Results 13,606 children and adolescents from NHANES (2005–2006, 2017–2018) were included in our analysis. Compared with the lowest α-tocopherol quartile, individuals in the highest α-tocopherol quartile are likelier to be Non-Hispanic White and have a higher value of poverty income ratio (PIR). They have a lower value of serum phosphorus and lumbar spine BMD. Every 1umol/L increase in serum α- and γ- tocopherol, the lumbar spine BMD decreased by -0.0016 and -0.0068 g/cm2. Compared with the lowest quartile serum α- and γ- tocopherol concentration, individuals in the highest quartile have a -0.0223 and -0.0329 g/cm2 lower mean BMD, respectively. Interaction effects suggest that the negative effect is more prominent among female youth, individuals aged 8–13 years, non-Hispanic whites, Mexican Americans, and non-Hispanic blacks. Conclusions Our study indicates serum α- and γ-tocopherol are negatively correlated with lumbar BMD. Age, gender, and race may have a modifying effect on this relationship. Our study has an important clinical implication. A higher vitamin E status for children and adolescents could not improve BMD, even decrease BMD. More prospective research with stronger evidence is needed to verify our findings and their underlying mechanisms.
Alterations in the coagulation markers did not show differences with the severity of COVID‐19 in Peruvian patients: A cross‐sectional single‐center study

COVID‐19 is a pandemic disease that can lead to altered lung function, systemic inflammatory events, and altered coagulation. During severe stages of the disease, changes in coagulation homeostasis increase, leading to thrombosis, and increased risk of death. In this cross‐sectional study, we aimed to assess coagulation markers by COVID‐19 severity in Peruvian adults.
Gridless Method for Euler Equations and Distributing Point Technique

An explicit gridless method for solving Euler equations is presented. Only clouds of points instead of grids are distributed over the computational domain and the spatial derivatives of the Euler equations are estimated using a least-square curve fit on local clouds of points. This paper gives a discrete form for Euler equations based on gridless method,and five steps for Runge-Kutta are adopted for time-marching. In addition, this paper describes a convenient technique for distributing points and selecting points to constitute "clouds of points". Numerical results are obtained for the flows over NACA0012 and RAE2822 airfoils.
Impact of COVID-19 on Patients with Diabetes Standard of Care in the Jazan Region, Saudi Arabia

Background: COVID-19 patients with DM have increased mortality and severity of the disease. Although telemedicine helps to minimize the impact of COVID-19 on the DM standard of care, it is increasingly evident that COVID-19 has a significant impact on DM standards of care, especially in areas where telemedicine is not available. Objective: The study aimed to assess the impact of COVID-19 on patients with diabetes standard of care in the Jazan region, Saudi Arabia. Methods: A cross-sectional study using an online pretested questionnaire targeted adult diabetic patients living in the Jazan region between December 2021 to March 2022. The participants were selected through a random sampling method. They completed self-administered questionnaires that included demographic variables. Results: A total of 258 study subjects participated in this study. In comparison to DM standards of care before and during COVID-19, there was no clinically significant difference in medication compliance, blood glucose checking, or experiencing blood glucose extrusion. However, with the spread of the corona pandemic and the closure of clinics, the percentage of those who have difficulty controlling blood sugar levels has increased to 22%, despite the availability of telemedicine. Conclusion: DM standards of care have not been affected and were not statistically significant, which could be explained by the rapid adoption of telemedicine during the lockdown. However, as corona spread participants had difficulty controlling blood sugar levels. This indicates that governmental multidisciplinary work limits the COVID-19 impact; however, further work is still needed to ensure that DM care is not compromised.
Differences in the predicted nasoseptal flap length among races: A propensity score matching analysis

Objectives We compared the lengths of a nasoseptal flap (NSF) and skull base according to race, age, and sex. Methods We performed paranasal sinus computed tomography in 19,961 adult patients between 2003 and 2022. The race of the patients was East Asian (n = 71), Caucasian (n = 71), or Middle Eastern (n = 71). The expected lengths of the NSF and anterior skull base defect were measured and analyzed according to race, age, and sex. Results Compared with Caucasians and Middle Easterners, East Asians had a shorter NSF length (p < 0.001) and lower ratio of the expected NSF length to the expected defect length (p < 0.001). There was no difference in the values among age groups. The expected NSF length was longer, and the ratio of the expected NSF length to the expected defect length was higher, in males than females (p < 0.001 for both). Conclusions East Asians and females had a shorter NSF length and lower ratio of expected NSF to surgical defect lengths after anterior skull base reconstruction compared with the other races and with males, respectively. Anatomical differences should be considered when long NSF lengths are required, such as for anterior skull base reconstruction.
The pathogenesis hypothesis and research progress of CLIPPERS: A literature review

Chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids (CLIPPERS) is still a rare autoimmune disease in the world. In recent years, there are more and more reports about the clinical manifestations of CLIPPERS, but the specific etiology and pathogenesis are not clear. In this paper, by collating the literature reported in recent years, in the reported effective treatment cases, we found the current hypothesis about the pathogenesis of CLIPPERS. Three pathogenesis hypotheses: organ-specific autoimmunity; virus infection affects autoimmunity; and helper T lymphocyte 17 mediates autoimmunity. Although it is hypothetical, it is expected to further clarify the pathogenesis, evolution characteristics, and treatment of CLIPPERS, so as to provide a reference for further understanding of the disease. In the future, more observations and studies are needed to further verify the feasibility of the hypothesis. This article expands on atypical clinical manifestations and summarizes treatment options. Hope to provide a reference for clinical diagnosis and treatment of CLIPPERS.
Psychological factors affecting potential users’ intention to use autonomous vehicles

As a currently emerging technology and an emerging intelligent mode of transport, autonomous vehicles (AVs) with lots of potential advantages need attention in terms of acceptability of their users. This research incorporates three psychological factors of perceived trust, perceived value, and perceived enjoyment into the technology acceptance model, and explores the influence of these factors on the potential use intention of AVs users. In this study, the questionnaire data from 232 participants were analysed, and the structural equation model test study model was adopted, and nine hypotheses proposed in this study were verified. The results show that perceived enjoyment, perceived trust, perceived usefulness, and attitude have a direct positive impact on users’ usage intentions. Perceived value, perceived usefulness, and perceived ease of use have a direct positive impact on user attitudes. In addition, perceived ease of use has also been shown to directly affect perceived usefulness. This study constructs and demonstrates a model of autonomous vehicle acceptance. This model can be used for user acceptance research of unmanned vehicles. The research expands the theory of technology acceptance model and its applicable fields, and enriches the theory of user research on unmanned vehicles. This study provides predictors of AVs acceptance for AVs designers, automakers, automotive policy makers, and related practitioners. Help them make actionable autonomous vehicle-related decisions to promote high-acceptance autonomous vehicle design and user intent for autonomous vehicles.
Contextualizing gender disparities in online teaching evaluations for professors

Student evaluation of teaching (SET) is widely used to assess teaching effectiveness in higher education and can significantly influence professors’ career outcomes. Although earlier evidence suggests SET may suffer from biases due to the gender of professors, there is a lack of large-scale examination to understand how and why gender disparities occur in SET. This study aims to address this gap in SET by analyzing approximately 9 million SET reviews from RateMyProfessors.com under the theoretical frameworks of role congruity theory and shifting standards theory. Our multiple linear regression analysis of the SET numerical ratings confirms that women professors are generally rated lower than men in many fields. Using the Dunning log-likelihood test, we show that words used in student comments vary by the gender of professors. We then use BERTopic to extract the most frequent topics from one- and five-star reviews. Our regression analysis based on the topics reveals that the probabilities of specific topics appearing in SET comments are significantly associated with professors’ genders, which aligns with gender role expectations. Furtherly, sentiment analysis indicates that women professors’ comments are more positively or negatively polarized than men’s across most extracted topics, suggesting students’ evaluative standards are subject to professors’ gender. These findings contextualize the gender gap in SET ratings and caution the usage of SET in related decision-making to avoid potential systematic biases towards women professors.