Miracle-dz/UniFAR-FTUs huggingface dataset:
Radiative and thermodynamic responses to aerosol extinction profiles during the pre-monsoon month over South Asia

Abstract. Aerosol radiative effects and thermodynamic responses over South Asia are examined with the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) for March 2012. Model results of aerosol optical depths (AODs) and extinction profiles are analyzed and compared to satellite retrievals and two ground-based lidars located in northern India. The WRF-Chem model is found to heavily underestimate the AOD during the simulated pre-monsoon month and about 83 % of the model's low bias is due to aerosol extinctions below ∼ 2 km. Doubling the calculated aerosol extinctions below 850 hPa generates much better agreement with the observed AOD and extinction profiles averaged over South Asia. To separate the effect of absorption and scattering properties, two runs were conducted: in one run (Case I), the calculated scattering and absorption coefficients were increased proportionally, while in the second run (Case II) only the calculated aerosol scattering coefficient was increased. With the same AOD and extinction profiles, the two runs produce significantly different radiative effects over land and oceans. On the regional mean basis, Case I generates 48 % more heating in the atmosphere and 21 % more dimming at the surface than Case II. Case I also produces stronger cooling responses over the land from the longwave radiation adjustment and boundary layer mixing. These rapid adjustments offset the stronger radiative heating in Case I and lead to an overall lower-troposphere cooling up to −0.7 K day−1, which is smaller than that in Case II. Over the ocean, direct radiative effects dominate the heating rate changes in the lower atmosphere lacking such surface and lower atmosphere adjustments due to fixed sea surface temperature, and the strongest atmospheric warming is obtained in Case I. Consequently, atmospheric dynamics (boundary layer heights and meridional circulation) and thermodynamic processes (water vapor and cloudiness) are shown to respond differently between Case I and Case II, underlining the importance of determining the exact portion of scattering or absorbing aerosols that lead to the underestimation of aerosol optical depth in the model. In addition, the model results suggest that both the direct radiative effect and rapid thermodynamic responses need to be quantified for understanding aerosol radiative impacts.
Convolutional Neural Network based Medical Imaging Segmentation : Recent Progress and Challenges

A key research topic in Medical Image Analysis is image segmentation. Traditionally such task is solved by hand-engineered features based methods, which could be highly dataset related. Convolutional Neural Network (CNN) has shown great success in many areas, especially in the area of computer vision. Different from the hand-engineered feature based classification, Convolutional Neural Network uses selflearned features from data for classification. Recently, some progress has been made in the area of Convolutional Neural Network based image segmentation, which cast light on the area of medical imaging. This survey gives a brief introduction on Convolutional Neural Network based medical image segmentation. Three categories of methods are discussed are discussed: CNN based method, Encoder-Decoder based method and Generative Adversarial Network based method. For each category, first a brief introduction is given followed by a timeline of model evolving then some recent progress on medical imaging is introduced. Besides some technical details, we also introduce some available public packages for a fast development and some public data sources.
Motor Imagery and Motor Coordination in Autism Spectrum Disorders: Similarities and Differences

Autism spectrum disorders (ASD) are composed by a variety of developmental deficits, such as problems in verbal communication and repetitive behaviours. Together with these social deficits, the recent literature has reported difficulties in motor coordination during the everyday life of children and adolescents with ASD. These motor deficits could be linked to a possible alteration of motor simulation processes in ASD but just a few studies attempted to directly compare motor imagery tasks and actual motor coordination within these disorders and specifically using the same task. In a recent study, the relationship between explicit motor imagery and motor execution has been investigated within the same experimental paradigm. The authors employed a spatial bimanual task called “circles-lines” task where participants are asked to draw with one hand (i.e., baseline), either hands (i.e., bimanual task) or try to imagine the movements with one hand while simultaneously draw with the other (i.e., imagery task). This task is a prototype of a complex bimanual skill and shows how these two processes can be studied together within the same paradigm. In particular, results of the study highlighted how motor imagery and motor coordination only partially follow the same path of development in ASD. Indeed, ASD participants showed much lower results in the motor imagery task in comparison to the performance in actual bimanual task, which was similar to the typically developed controls. In conclusion, the data show that motor imagery and actual coordination, even though interrelated processes which share similar brain areas, can be dissociated in ASD where development of spatial coordination consolidates earlier than motor imagery
Characteristics of Patients With Opioid Use Disorder Associated With Performing Overdose Reversals in the Community: An Opioid Treatment Program Analysis

Objective: The primary outcome of this study is to identify characteristics of study participants in a large opioid treatment program (OTP) for opioid use disorder (OUD) who used take-home naloxone to perform 1 or more opioid overdose (OD) reversal(s) in the community. Methods: This 6-month prospective cohort study provided take-home naloxone and opioid OD education for 287 study participants with OUD. Characteristics associated with use of the take-home naloxone were determined from among 16 variables using multivariable logistic regression. Results: The study participants who had greater odds of using the take-home naloxone to perform OD reversals, compared to those who did not use the take-home naloxone, (a) received emergency room care themselves for OD (OR = 4.89, 95% CI 1.54–15.52, P = 0.007), (b) previously witnessed someone else OD (OR = 5.67, 95% CI 1.24–25.87, P = 0.025), (c) tested positive for 2 or more illicit substances at their 6-month urine analysis (OR = 5.26, 95% CI 1.58–17.54, P = 0.007) or were missing their 6-month urine analysis (OR = 3.46, 95% CI 1.42–8.43, P = 0.006). In addition, they had greater odds of being (d) less than 30 years old (OR = 2.80, 95% CI 1.02–7.66, P = 0.045), and (e) Hispanic (OR = 3.98, 95% CI 1.41–11.21, P = 0.009). Conclusions: This study prospectively identified several characteristics of patients enrolled in an OTP with increased odds of using take-home naloxone in their social networks. Future harm reduction efforts may benefit by using targeted characteristics to identify those most likely to use naloxone in their communities.
A Wealth of Sub-Consensus Deterministic Objects

The consensus hierarchy classifies shared an object according to its consensus number, which is the maximum number of processes that can solve consensus wait-free using the object. The question of whether this hierarchy is precise enough to fully characterize the synchronization power of deterministic shared objects was open until 2016, when Afek et al. showed that there is an infinite hierarchy of deterministic objects, each weaker than the next, which is strictly between i and i + 1-processors consensus, for i ≥ 2. For i = 1, the question whether there exist a deterministic object whose power is strictly between read-write and 2-processors consensus, remained open. We resolve the question positively by exhibiting an infinite hierarchy of simple deterministic objects which are equivalent to set-consensus tasks, and thus are stronger than read-write registers, but they cannot implement consensus for two processes. Still our paper leaves a gap with open questions. 2012 ACM Subject Classification Theory of computation → Distributed computing models
TIVAN: tissue-specific cis-eQTL single nucleotide variant annotation and prediction

SUMMARY Predicting genetic regulatory variants, most of which locate in non-coding genomic regions, still remain a challenge in genetic research. Among all non-coding regulatory variants, cis-eQTL single nucleotide variants (SNVs) are of particular interest for their crucial role in regulating gene expression. Since different gene expression patterns are believed to contribute to the etiologies of different phenotypes, it is desirable to characterize the impact of cis-eQTL SNVs in a context-specific manner. Though computational methods for predicting the potential of variants being pathogenic or deleterious are well-established, methods for annotating and predicting cis-eQTL SNVs are under-developed. Here, we present TIVAN (TIssue-specific Variant ANnotation and prediction), an ensemble method of decision trees, to predict tissue-specific cis-eQTL SNVs. TIVAN is trained based on a comprehensive collection of features, including genome-wide genomic and epigenomic profiling data. As a result, TIVAN has been shown to accurately discriminate cis-eQTL SNVs from non-eQTL SNVs and perform favorably to other methods by obtaining higher five-fold cross-validation AUC values (CV-AUC) and Leave-One-Chromosome-Out predicted AUC values (LOCO-AUC) across 44 different tissues belonging to 27 different tissue classes. Finally, TIVAN consistently maintains top performance on an independent testing dataset, which includes 7 tissues in 11 studies. AVAILABILITY AND IMPLEMENTATION TIVAN software is available at https://github.com/lichen-lab/TIVAN. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
The Effect of Training in the Preparatory and Competitive Periods on Trunk Rotational Power in Canoeists, Ice-Hockey Players, and Tennis Players

This study evaluates changes in trunk rotational power at different weights and velocities after the preparatory and competitive periods in ice-hockey players, tennis players, and canoeists. The subjects performed trunk rotations to each side with a barbell of different weights placed on the shoulders (6, 10, 12, 16, 20, 22, and 26 kg) prior to and after 6 weeks of the preparatory period and 6 weeks of the competitive period. The results showed that mean power produced in the acceleration phase of trunk rotations increased significantly at weights from 10 to 26 kg or 6 to 26 kg after the preparatory and competitive periods in tennis players. The values obtained during trunk rotations with weights ≥12 kg also increased significantly after the preparatory period in ice-hockey players, whereas there were no significant changes after the competitive period. Similarly, the mean power during trunk rotations with weights ≥10 kg increased significantly only after the preparatory period in canoeists. Similar changes were observed for the peak power. These findings demonstrate that changes in trunk rotational power reflect the specificity of their training programs. This information may provide a basis for designing exercises focused on improvements of power produced during trunk rotations under loading conditions.
Nonlinear association structures in flexible Bayesian additive joint models

Joint models of longitudinal and survival data have become an important tool for modeling associations between longitudinal biomarkers and event processes. The association between marker and log hazard is assumed to be linear in existing shared random effects models, with this assumption usually remaining unchecked. We present an extended framework of flexible additive joint models that allows the estimation of nonlinear covariate specific associations by making use of Bayesian P‐splines. Our joint models are estimated in a Bayesian framework using structured additive predictors for all model components, allowing for great flexibility in the specification of smooth nonlinear, time‐varying, and random effects terms for longitudinal submodel, survival submodel, and their association. The ability to capture truly linear and nonlinear associations is assessed in simulations and illustrated on the widely studied biomedical data on the rare fatal liver disease primary biliary cirrhosis. All methods are implemented in the R package bamlss to facilitate the application of this flexible joint model in practice.
Automatic correction of short-duration artefacts in single-channel EEG recording: a group-sparse signal denoising algorithm

A new algorithm for correcting short-duration artefacts in single-channel EEG recording is proposed here. A short-duration artefact has the characteristics of a group-sparse (GS) signal, i.e. a sparse signal in which its non-zero entries tend to concentrate in groups. Therefore, the problem of extracting a short-duration artefact from a recorded EEG data is formulated in the proposed algorithm as a denoising optimisation problem in which a penalty term is utilised to encourage the group sparsity of the estimated artefact. A quadratic penalty term is utilised in the proposed algorithm, and, hence, a closed-form solution is obtained in each iteration of the algorithm. In addition, a technique for automatic selection of the regularisation parameter, which controls the trade-off between the sparsity of the estimated artefact and its closeness to the measured EEG data, is also proposed. Simulation results on real and simulated EEG data show that the proposed algorithm can be successfully utilised to correct different kinds of short-duration artefacts in both single-channel and multichannel recordings. In addition, the proposed algorithm is also shown to produce significantly improved results compared to existing techniques used for performing similar tasks.
The Opioid Epidemic and the Role of the Occupational Health Nurse

The opioid epidemic is a national public health crisis. It began with the misuse of commonly used prescription opioid pain relievers and has led to the increased use of heroin and illicit fentanyl. Large-scale initiatives have begun on the federal and state level and place an emphasis on improved opioid prescribing, which have important implications for the workplace. Treatment of work injury may initiate the use of prescription opioids and result in misuse and possible overdose. Prescription drug abuse affects all aspects of society so potentially any workplace could be affected. A multifaceted approach is needed to reduce opioid morbidity and mortality and the occupational health nurse should be actively involved. The intent of this article is to provide an overview of the epidemic and its impact on health, the challenges for the workplace, and recommended strategies for the occupational health nurse to impact the problem.
Supplemental Nutrition Assistance Program participation and racial/ethnic disparities in food and beverage purchases

Abstract Objective The current study aimed to (i) describe racial/ethnic disparities in household food and beverage purchases among participants and non-participants in the Supplemental Nutrition Assistance Program (SNAP) and (ii) examine longitudinal associations between SNAP participation and purchases by race/ethnicity. Design To describe disparities, we estimated sociodemographic-adjusted mean purchases of seven unhealthy food and beverage groups (e.g. junk food, sugar-sweetened beverages) and four nutrients (e.g. sugar, Na) among white, black and Hispanic SNAP-participating and non-participating households. To examine longitudinal associations, we used multivariable linear regression with household fixed effects. Setting USA, 2010–2014. Subjects Food and beverage purchases among low-income (≤250 % federal poverty line) US households (n 30 403) participating in the Nielsen Homescan Panel. Results Among non-participants, there were significant black–white disparities (i.e. differences favouring white households) in households’ adjusted mean purchases of processed meat, sweeteners, sugar-sweetened beverages, energy and Na. These disparities persisted among SNAP participants. In contrast, the only significant Hispanic–white disparity among non-participants was for Na purchases; this disparity was reduced in magnitude and no longer significant among SNAP-participating households. Additionally, Hispanic households purchased less energy from junk foods than white households, regardless of SNAP status. In longitudinal models accounting for household fixed effects, SNAP participation was associated with increased energy purchased among black households. No other significant longitudinal associations between SNAP and purchase outcomes were observed. Conclusions SNAP may not be meeting its potential to improve food and beverage purchases or reduce disparities. Research is needed to identify strategies for ensuring nutritious purchases across all racial/ethnic groups.
Multiplication of the SNCA locus exacerbates neuronal nuclear aging

Abstract Human‐induced Pluripotent Stem Cell (hiPSC)‐derived models have advanced the study of neurodegenerative diseases, including Parkinson's disease (PD). While age is the strongest risk factor for these disorders, hiPSC‐derived models represent rejuvenated neurons. We developed hiPSC‐derived Aged dopaminergic and cholinergic neurons to model PD and related synucleinopathies. Our new method induces aging through a `semi‐natural’ process, by passaging multiple times at the Neural Precursor Cell stage, prior to final differentiation. Characterization of isogenic hiPSC‐derived neurons using heterochromatin and nuclear envelope markers, as well as DNA damage and global DNA methylation, validated our age‐inducing method. Next, we compared neurons derived from a patient with SNCA‐triplication (SNCA‐Tri) and a Control. The SNCA‐Tri neurons displayed exacerbated nuclear aging, showing advanced aging signatures already at the Juvenile stage. Noteworthy, the Aged SNCA‐Tri neurons showed more &agr;‐synuclein aggregates per cell versus the Juvenile. We suggest a link between the effects of aging and SNCA overexpression on neuronal nuclear architecture.
Topical haemostatic powder as a novel endoscopic therapy for severe colonic diverticular bleeding

Although most diverticular bleeding resolve spontaneously, up to 30% can bleed torrentially, necessitating angioembolization, endoscopic or surgical intervention. Non‐contact endoscopic therapies, such as topical haemostatic powders, do not require precise targeting and are attractive because identification of specific culprit diverticulum is difficult. While their use in non‐variceal upper gastrointestinal bleeding is well established, its role in lower gastrointestinal bleeding remains unclear. We used topical Hemospray in a novel setting of severe diverticular bleeding, evaluating its efficacy in achieving haemostasis, reducing re‐bleeding and the need for re‐intervention.
SPIO-loaded nanostructured lipid carriers as liver-targeted molecular T2-weighted MRI contrast agent.

Background Superparamagnetic iron oxide (SPIO) acts as a negative contrast agent in magnetic resonance imaging (MRI), and is widely used in clinical applications, including the diagnosis of hepatic diseases. Hepatocyte-targeted magnetic resonance contrast agents (MRCAs) can provide useful information for evaluating hepatic diseases. We prepared targeted magnetic nanostructured lipid carriers (MNLCs) to enhance the hepatocytes targeting efficiency. Methods In vitro characterizations of MNLCs were determined by transmission electron microscopy (TEM). The cytotoxicity assay of the MNLCs was measured by methyl tetrazolium (MTT) method. The uptaken study was measured by confocal microscopy, flow cytometry and MRI in vitro. The enhanced liver-targeting efficiency of MNLCs was measured by fluorescence imaging and MRI in vivo. Results Gal-NLC-SPIO was prepared successfully. The cytotoxicity assay of the MNLCs demonstrated that the MNLC had relatively low cytotoxicity and high biocompatibility for LO2 cells. More importantly, we confirmed that Gal-NLC-SPIO had greater uptake by LO2 cells than Gal-NLC-SPIO/PEG and free Gal in vitro. A liver distribution study of MNLCs in normal mice demonstrated that the fluorescent signal values to livers of the Gal-NLC-SPIO were signiﬁcantly stronger than those of NLC-SPIO and Gal-NLC-SPIO/PEG. The liver targeting efficiency of Gal-NLC-SPIO was confirmed both in vitro and in vivo. Conclusions We successfully developed liver-targeting MNLCs, which showed accurate hepatocytes targeting, and thus have the potential to be a new MRI contrast agent to help the diagnosis of liver diseases.
Experimental Dissection of the Lytic Replication Cycles of Herpes Simplex Viruses in vitro

Herpes simplex viruses type 1 and type 2 (HSV-1 and HSV-2) produce lifelong infections and are highly prevalent in the human population. Both viruses elicit numerous clinical manifestations and produce mild-to-severe diseases that affect the skin, eyes, and brain, among others. Despite the existence of numerous antivirals against HSV, such as acyclovir and acyclovir-related analogs, virus variants that are resistant to these compounds can be isolated from immunosuppressed individuals. For such isolates, second-line drugs can be used, yet they frequently produce adverse side effects. Furthermore, topical antivirals for treating cutaneous HSV infections usually display poor to moderate efficacy. Hence, better or novel anti-HSV antivirals are needed and details on their mechanisms of action would be insightful for improving their efficacy and identifying specific molecular targets. Here, we review and dissect the lytic replication cycles of herpes simplex viruses, discussing key steps involved in cell infection and the processes that yield new virions. Additionally, we review and discuss rapid, easy-to-perform and simple experimental approaches for studying key steps involved in HSV replication to facilitate the identification of the mechanisms of action of anti-HSV compounds.
Level crossing speech sampling and its sparsity promoting reconstruction using an iterative method with adaptive thresholding

The authors propose asynchronous level crossing (LC) A/D converters for low redundancy voice sampling. They propose to utilise the family of iterative methods with adaptive thresholding (IMAT) for reconstructing voice from non-uniform LC and adaptive LC (ALC) samples thereby promoting sparsity. The authors modify the basic IMAT algorithm and propose the iterative method with adaptive thresholding for level crossing (IMATLC) algorithm for improved reconstruction performance. To this end, the authors analytically derive the basic IMAT algorithm by applying the gradient descent and gradient projection optimisation techniques to the problem of square error minimisation subjected to sparsity. The simulation results indicate that the proposed IMATLC reconstruction method outperforms the conventional reconstruction method based on low-pass signal assumption by 6.56 dBs in terms of reconstruction signal-to-noise ratio (SNR) for LC sampling. In this scenario, IMATLC outperforms orthogonal matching pursuit, least absolute shrinkage and selection operator and smoothed L0 sparsity promoting algorithms by average amounts of 12.13, 10.31, and 10.28 dBs, respectively. Finally, the authors compare the performance of the proposed LC/ALC-based A/Ds with the conventional uniform sampling-based A/Ds and their random sampling-based counterparts both in terms of perceptual evaluation of speech quality and reconstruction SNR.