Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive science as a source of forward and inverse models of human decisions for robotics and control

Those designing autonomous systems that interact with humans will invariably face questions about how humans think and make decisions. Fortunately, computational cognitive science offers insight into human decision-making using tools that will be familiar to those with backgrounds in optimization and control (e.g., probability theory, statistical machine learning, and reinforcement learning). Here, we review some of this work, focusing on how cognitive science can provide forward models of human decision-making and inverse models of how humans think about others’ decision-making. We highlight relevant recent developments, including approaches that synthesize black box and theory-driven modeling, accounts that recast heuristics and biases as forms of bounded optimality, and models that characterize human theory of mind and communication in decision-theoretic terms. In doing so, we aim to provide readers with a glimpse of the range of frameworks, methodologies, and actionable insights that lie at the intersection of cognitive science and control research. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
Single‐Junction Organic Photovoltaic Cell with 19% Efficiency

Improving power conversion efficiency (PCE) is important for broadening the applications of organic photovoltaic (OPV) cells. Here, a maximum PCE of 19.0% (certified value of 18.7%) is achieved in single‐junction OPV cells by combining material design with a ternary blending strategy. An active layer comprising a new wide‐bandgap polymer donor named PBQx‐TF and a new low‐bandgap non‐fullerene acceptor (NFA) named eC9‐2Cl is rationally designed. With optimized light utilization, the resulting binary cell exhibits a good PCE of 17.7%. An NFA F‐BTA3 is then added to the active layer as a third component to simultaneously improve the photovoltaic parameters. The improved light unitization, cascaded energy level alignment, and enhanced intermolecular packing result in open‐circuit voltage of 0.879 V, short‐circuit current density of 26.7 mA cm−2, and fill factor of 0.809. This study demonstrates that further improvement of PCEs of high‐performance OPV cells requires fine tuning of the electronic structures and morphologies of the active layers.
Impact of the dog population and household environment for the maintenance of natural foci of Leishmania infantum transmission to human and animal hosts in endemic areas for visceral leishmaniasis in Sao Paulo state, Brazil

When it comes to visceral leishmaniasis (VL) in Brazil, one of the main targets of public health policies of surveillance is the control of domestic canine reservoirs of Leishmania infantum. This paper aims to evaluate the effect of the dog population and household environment for the maintenance of natural foci in the transmission to human and animal hosts in an endemic city for VL, Bauru, in Brazil. We collected 6,578 blood samples of dogs living in 3,916 households from Nov.2019 to Mar.2020 and applied geospatial models to predict the disease risk based on the canine population. We used Kernel density estimation, cluster analysis, geostatistics, and Generalized Additive Models (GAM). To validate our models, we used cross-validation and created a receiver operating characteristic (ROC) curve. We found an overall canine VL (CVL) seroprevalence of 5.6% for the sampled dogs, while for the households, the positivity rate was 8.7%. Odds ratios (OR) for CVL increased progressively according to the number of canines for >2 dogs (OR 2.70); households that already had CVL in the past increased the chances for CVL currently (OR 2.73); and the cases of CVL increase the chances for human VL cases (OR 1.16). Our models were statistically significant and demonstrated a spatial association between canine and human disease cases, mainly in VL foci that remain endemic. Although the Kernel density ratio map had the best performance (AUC = 82), all the models showed high risk in the city’s northwest area. Canine population dynamics must be considered in public policies, and geospatial methods may help target priority areas and planning VL surveillance in low and middle-income countries.
Informing Autonomous Deception Systems with Cyber Expert Performance Data

The performance of artificial intelligence (AI) algorithms in practice depends on the realism and correctness of the data, models, and feedback (labels or rewards) provided to the algorithm. This paper discusses methods for improving the realism and ecological validity of AI used for autonomous cyber defense by exploring the potential to use Inverse Reinforcement Learning (IRL) to gain insight into attacker actions, utilities of those actions, and ultimately decision points which cyber deception could thwart. The Tularosa study, as one example, provides experimental data of real-world techniques and tools commonly used by attackers, from which core data vectors can be leveraged to inform an autonomous cyber defense system.
Estimating disorder and its adverse effects in semiconductor Majorana nanowires

We use the available transport measurements in the literature to develop a dataset for the likely amount of disorder in semiconductor (InAs and InSb) materials which are used in fabricating the superconductor-semiconductor nanowire samples in the experimental search for Majorana zero modes. Using the estimated disorder in direct Majorana simulations, we conclude that the current level of disorder in semiconductor Majorana nanowires is at least an order of magnitude higher than that necessary for the emergence of topological Majorana zero modes. In agreement with existing results, we find that our estimated disorder leads to the occasional emergence of trivial zero modes, which can be post-selected and then further fine-tuned by varying system parameters (e.g., tunnel barrier), leading to trivial zero-bias conductance peaks in tunneling spectroscopy with ∼ 2e/h magnitude. Most calculated tunnel spectra in these disordered systems, however, manifest essentially no significant features, which is also consistent with the current experimental status, where zero-bias peaks are found only occasionally in some samples under careful fine-tuning.
Depressive symptoms among frontline and non-frontline healthcare providers in response to the COVID-19 pandemic in Kelantan, Malaysia: A cross sectional study

Background Healthcare providers are vulnerable in the fight against COVID-19 and may experience significant psychological and mental health consequences. This study aimed to compare the levels of depressive symptoms among frontline and non-frontline healthcare providers in response to the COVID-19 pandemic. Methods A comparative cross-sectional study was conducted in two government hospitals managing COVID-19-related cases in Kelantan, Malaysia from May to July 2020 to identify and compared depressive symptoms levels of frontline and non-frontline healthcare providers. Convenient sampling was applied in the selection of eligible participants and those diagnosed as having any psychiatric illnesses were excluded. The self-administered questionnaires for the Malay versions of the Hospital Anxiety and Depression Scale to measure depressive symptoms score and the Medical Outcome Study Social Support Survey to measure social support score as an important confounder. A descriptive analysis, independent t-test and ANCOVA were performed using SPSS version 26. Results A total of 306 respondents from healthcare providers were recruited which 160 were frontline healthcare providers and 146 were non-frontline healthcare providers. The level of depressive symptoms (HADS score >8) was 27.5% for the frontline healthcare providers and 37.7% for the non-frontline healthcare providers. The mean depressive symptoms score for the non-frontline healthcare providers was 0.75 points higher than that of the frontline healthcare providers after adjusting for gender, duration of employment and social support. Conclusion Non-frontline healthcare providers are also experiencing psychological distress during the COVID-19 pandemic even though they do not have direct contact with COVID-19 patients.
Classification of Distinct Patterns of Ischemic Cholangiopathy Following DCD Liver Transplantation: Distinct Clinical Courses and Long-term Outcomes From a Multicenter Cohort

Background. As the number of donation after circulatory death (DCD) liver transplants (LTs) performed in the United States continues to increase annually, there has been interest by policy makers to develop a more robust exception point safety net for patients who develop ischemic cholangiopathy (IC) following DCD LT. As such, there is a need for better understanding of the clinical course and long-term outcomes in patients who develop IC, as well as determining if IC can be classified into distinct categories with distinctly different clinical outcomes. Methods. All DCD LT performed at Mayo Clinic Florida, Mayo Clinic Arizona, and Mayo Clinic Rochester from January 1999 to March 2020 were included (N = 770). Outcomes were compared between 4 distinct radiologic patterns of IC: diffuse necrosis, multifocal progressive, confluence dominant, and minor form. Results. In total, 88 (11.4%) patients developed IC, of which 42 (5.5%) were listed for retransplantation of liver (ReLT). Patients with diffuse necrosis and multifocal progressive patterns suffered from frequent hospital admissions for cholangitis in the first year following DCD LT (median 3 and 2), were largely stent dependent (100% and 85.7%), and almost universally required ReLT. Patients with confluence dominant disease were managed with multiple stents and frequently recovered, ultimately becoming stent free without need for ReLT. Patients with the minor form IC did well with limited need for stent placement or repeat procedures and did not require ReLT. Graft survival was different between the 4 distinct IC patterns (P < 0.001). Conclusions. The present analysis provides a detailed analysis on the natural history and clinical course of IC. Patients developing IC can be classified into 4 distinct patterns with distinct clinical courses.
B-Cell Compartmental Features and Molecular Basis for Therapy in Autoimmune Disease

Background and Objectives To assess the molecular landscape of B-cell subpopulations across different compartments in patients with neuromyelitis optica spectrum disorder (NMOSD). Methods We performed B-cell transcriptomic profiles via single-cell RNA sequencing across CSF, blood, and bone marrow in patients with NMOSD. Results Across the tissue types tested, 4 major subpopulations of B cells with distinct signatures were identified: naive B cells, memory B cells, age-associated B cells, and antibody-secreting cells (ASCs). NMOSD B cells show proinflammatory activity and increased expression of chemokine receptor genes (CXCR3 and CXCR4). Circulating B cells display an increase of antigen presentation markers (CD40 and CD83), as well as activation signatures (FOS, CD69, and JUN). In contrast, the bone marrow B-cell population contains a large ASC fraction with increased oxidative and metabolic activity reflected by COX genes and ATP synthase genes. Typically, NMOSD B cells become hyperresponsive to type I interferon, which facilitates B-cell maturation and anti–aquaporin-4 autoantibody production. The pool of ASCs in blood and CSF were significantly elevated in NMOSD. Both CD19− and CD19+ ASCs could be ablated by tocilizumab, but not rituximab treatment in NMOSD. Discussion B cells are compartmentally fine tuned toward autoreactivity in NMOSD and become hyperreactive to type I interferon. Inhibition of type I interferon pathway may provide a new therapeutic avenue for NMOSD.
Do Current X-Ray Observations Capture Most of the Black-hole Accretion at High Redshifts?

The cosmic black hole accretion density (BHAD) is critical for our understanding of the formation and evolution of supermassive black holes (BHs). However, at high redshifts (z > 3), X-ray observations report BHADs significantly (∼10 times) lower than those predicted by cosmological simulations. It is therefore paramount to constrain the high-z BHAD using independent methods other than direct X-ray detections. The recently established relation between star formation rate and BH accretion rate among bulge-dominated galaxies provides such a chance, as it enables an estimate of the BHAD from the star formation histories (SFHs) of lower-redshift objects. Using the CANDELS Lyα Emission At Reionization (CLEAR) survey, we model the SFHs for a sample of 108 bulge-dominated galaxies at z = 0.7–1.5, and further estimate the BHAD contributed by their high-z progenitors. The predicted BHAD at z ≈ 4–5 is consistent with the simulation-predicted values, but higher than the X-ray measurements (by ≈3–10 times at z = 4–5). Our result suggests that the current X-ray surveys could be missing many heavily obscured Compton-thick active galactic nuclei (AGNs) at high redshifts. However, this BHAD estimation assumes that the high-z progenitors of our z = 0.7–1.5 sample remain bulge-dominated where star formation is correlated with BH cold-gas accretion. Alternatively, our prediction could signify a stark decline in the fraction of bulges in high-z galaxies (with an associated drop in BH accretion). JWST and Origins will resolve the discrepancy between our predicted BHAD and the X-ray results by constraining Compton-thick AGN and bulge evolution at high redshifts.
An Unsupervised Method for Building Sentence Simplification Corpora in Multiple Languages

The availability of parallel sentence simplification (SS) is scarce for neural SS modelings. We propose an unsupervised method to build SS corpora from large-scale bilingual translation corpora, alleviating the need for SS supervised corpora. Our method is motivated by the following two findings: neural machine translation model usually tends to generate more high-frequency tokens and the difference of text complexity levels exists between the source and target language of a translation corpus. By taking the pair of the source sentences of translation corpus and the translations of their references in a bridge language, we can construct large-scale pseudo parallel SS data. Then, we keep these sentence pairs with a higher complexity difference as SS sentence pairs. The building SS corpora with an unsupervised approach can satisfy the expectations that the aligned sentences preserve the same meanings and have difference in text complexity levels. Experimental results show that SS methods trained by our corpora achieve the state-of-the-art results and significantly outperform the results on English benchmark WikiLarge.
Family help received by Mexican older adults across socioeconomic strata: changes over a critical decade

ABSTRACT Objective. To identify how patterns of family economic support help alleviate the cumulative effects of inequality, with focus on the financial support that children give their elderly parents. Methods. This paper uses data from two cross-sections, 2001 and 2012, of the Mexican Health and Aging Study for the 50 years and older population. Analysis includes descriptive statistics to estimate differences in economic support based on family and individual characteristics; and a multinomial probit regression model, in each cross-section, to analyze the amount of money received for economic help and the associated characteristics. Results. Economic help received was significantly reduced, both in proportion, from 20% to 10% between 2001 and 2012, and in the amount received, with differences by income quintile. In 2001, 14.9% of those in the lowest quintile (Q1) would move to Q4–Q5 with children’s help; in 2012, this was 9.1%. The adjusted probability of receiving any amount of money from children decreased from 0.511 in 2001 to 0.340 in 2012. Conclusions. In Mexico, economic inequality in the 50 years and older population remains a constant. Economic help received from children varied by income quintile and plays an important role for those in the lowest income groups. More research is needed to understand the patterns of intergenerational exchanges as these cohorts of older adults continue to age and as future cohorts are entering old age with more pronounced changes than the current cohorts experienced over this critical decade.
Diverse Sample Generation: Pushing the Limit of Data-free Quantization

—Recently, generative data-free quantization emerges as a practical approach that compresses the neural network to low bit-width without access to real data. It generates data to quantize the network by utilizing the batch normalization (BN) statistics of its full-precision counterpart. However, our study shows that in practice, the synthetic data completely constrained by BN statistics suffers severe homogenization at distribution and sample level, which causes serious accuracy degradation of the quantized network. This paper presents a generic D iverse S ample G eneration (DSG) scheme for the generative data-free post-training quantization and quantization-aware training, to mitigate the detrimental homogenization. In our DSG, we ﬁrst slack the statistics alignment for features in the BN layer to relax the distribution constraint. Then we strengthen the loss impact of the speciﬁc BN layer for different samples and inhibit the correlation among samples in the generation process, to diversify samples from the statistical and spatial perspective, respectively. Extensive experiments show that for large-scale image classiﬁcation tasks, our DSG can consistently outperform existing data-free quantization methods on various neural architectures, especially under ultra-low bit-width (e.g., 22% gain under W4A4 setting). Moreover, data diversifying caused by our DSG brings a general gain in various quantization methods, demonstrating diversity is an important property of high-quality synthetic data for data-free quantization.
Toward an Understanding of SEI Formation and Lithium Plating on Copper in Anode-Free Batteries

“Anode-free” batteries present a significant advantage due to their substantially higher energy density and ease of assembly in a dry air atmosphere. However, issues involving lithium dendrite growth and low cycling Coulombic efficiencies during operation remain to be solved. Solid electrolyte interphase (SEI) formation on Cu and its effect on Li plating are studied here to understand the interplay between the Cu current collector surface chemistry and plated Li morphology. A native interphase layer (N-SEI) on the Cu current collector was observed with solid-state nuclear magnetic resonance spectroscopy (ssNMR) and electrochemical impedance spectroscopy (EIS). Cyclic voltammetry (CV) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) studies showed that the nature of the N-SEI is affected by the copper interface composition. An X-ray photoelectron spectroscopy (XPS) study identified a relationship between the applied voltage and SEI composition. In addition to the typical SEI components, the SEI contains copper oxides (CuxO) and their reduction reaction products. Parasitic electrochemical reactions were observed via in situ NMR measurements of Li plating efficiency. Scanning electron microscopy (SEM) studies revealed a correlation between the morphology of the plated Li and the SEI homogeneity, current density, and rest time in the electrolyte before plating. Via ToF-SIMS, we found that the preferential plating of Li on Cu is governed by the distribution of ionically conducting rather than electronic conducting compounds. The results together suggest strategies for mitigating dendrite formation by current collector pretreatment and controlled SEI formation during the first battery charge.
A multi-messenger view of cosmic dawn: Conquering the final frontier

The epoch of Cosmic Dawn, when the first stars and galaxies were born, is widely considered as the final frontier of observational cosmology today. Mapping the period between Cosmic Dawn and the present-day provides access to more than 90% of the baryonic (normal) matter in the universe, and unlocks several thousand times more Fourier modes of information than available in today’s cosmological surveys. We review the progress in modeling baryonic gas observations as tracers of the cosmological large-scale structure from Cosmic Dawn to the present day. We illustrate how the description of dark matter haloes can be extended to describe baryonic gas abundances and clustering. This innovative approach allows us to fully utilize our current knowledge of astrophysics to constrain cosmological parameters from future observations. Combined with the information content of multi-messenger probes, this will also elucidate the properties of the first supermassive black holes at Cosmic Dawn. We present a host of fascinating implications for constraining physics beyond the [Formula: see text]CDM model, including tests of the theories of inflation and the cosmological principle, the effects of nonstandard dark matter, and possible deviations from Einstein’s general relativity on the largest scales.
Coffee and tea consumption and mortality from all causes, cardiovascular disease and cancer: a pooled analysis of prospective studies from the Asia Cohort Consortium.

BACKGROUND Accumulating evidence suggests that consuming coffee may lower the risk of death, but evidence regarding tea consumption in Asians is limited. We examined the association between coffee and tea consumption and mortality in Asian populations. METHODS We used data from 12 prospective cohort studies including 248 050 men and 280 454 women from the Asia Cohort Consortium conducted in China, Japan, Korea and Singapore. We estimated the study-specific association of coffee, green tea and black tea consumption with mortality using Cox proportional-hazards regression models and the pooled study-specific hazard ratios (HRs) using a random-effects model. RESULTS In total, 94 744 deaths were identified during the follow-up, which ranged from an average of 6.5 to 22.7 years. Compared with coffee non-drinkers, men and women who drank at least five cups of coffee per day had a 24% [95% confidence interval (CI) 17%, 29%] and a 28% (95% CI 19%, 37%) lower risk of all-cause mortality, respectively. Similarly, we found inverse associations for coffee consumption with cardiovascular disease (CVD)-specific and cancer-specific mortality among both men and women. Green tea consumption was associated with lower risk of mortality from all causes, CVD and other causes but not from cancer. The association of drinking green tea with CVD-specific mortality was particularly strong, with HRs (95% CIs) of 0.79 (0.68, 0.91) for men and 0.78 (0.68, 0.90) for women who drank at least five cups per day of green tea compared with non-drinkers. The association between black tea consumption and mortality was weak, with no clear trends noted across the categories of consumption. CONCLUSIONS In Asian populations, coffee consumption is associated with a lower risk of death overall and with lower risks of death from CVD and cancer. Green tea consumption is associated with lower risks of death from all causes and CVD.
Improvements in the Pharmacological Profile of Diazepam by KRM-II-81, an Imidazodiazepine Positive Allosteric Modulator of 2/3-Containing GABAA Receptors: Preclinical Data Predict Enhanced Efficacy for Epilepsy, Chronic Pain, Anxiety, and Depression

Improvements in the Pharmacological Profile of Diazepam by KRM-II-81, an Imidazodiazepine Positive Allosteric Modulator of 2/3-Containing GABAA Receptors: Preclinical Data Predict Enhanced Efficacy for Epilepsy, Chronic Pain, Anxiety, and Depression. Pharmaceutical Sciences And Biomedical Analysis Journal. 2019; 2(1):117. Improvements in the Pharmacological Profile of Diazepam by KRM-II-81, an Imidazodiazepine Positive Allosteric Modulator of  2/3-Containing GABAA Receptors: Preclinical Data Predict Enhanced Efficacy for Epilepsy, Chronic Pain, Anxiety, and Depression