Miracle-dz/UniFAR-FTUs huggingface dataset:
THE EFFECTS SOYMILK FREMENTED WITH BIFIDOBACTERIUM LACTIS AND CONTAINING OMEGA-3 ON HAEMATOLOGICAL, OXIDATIVE STRESS, ANTI-OXIDANT AND INFLAMMATORY PARAMETERS IN TYPE 2 DIABETIC RATS

Background : Type 2 diabetes is a major metabolic disorder. This study was aimed to evaluate the effect of probiotic soymilk fermented with Bifidobacterium lactis and containing omega-3 on hematologic, oxidative stress, anti-oxidant and inflammatory parameters in type 2 diabetic rats. Methods : In this experimental manipulation study 65 rats were divided into five groups. Type 2 diabetes was induced by a single injection of streptozotocin and nicotinamide. Normal control (NC) and diabetic control (DC) rats received 1 mL/day of distilled water, and three groups of diabetic rats were administered 1 mL/day of soymilk (SM), fermented soymilk (FSM) and fermented soymilk fortified with omega-3 (FSM+omega-3) products by oral gavage for 28 days. Hematologic, oxidative stress, anti-oxidant and inflammatory parameters were measured at the end of experiment. Results : At the end of experiment, in all treated diabetic rats compared with the DC group, red blood cell (RBC), hemoglobin (Hb), hematocrit and superoxide dismutase (SOD) concentrations increased significantly (p<0.05), and malondialdehyde (MDA) concentrations reduced significantly (p<0.05). The reduction of MDA and increasing in Hb, RBC, hematocrit and SOD concentrations in the FSM+omega-3 group was more than two other groups. In the FSM+omega-3 group, high sensitivity C-reactive protein (hs-CRP) concentrations compared with the DC and FSM groups were significantly lower (p<0.05). Conclusion : The experiments suggest that combining soymilk, probiotics and omega-3 may be beneficial for the reducing oxidative-stress in type 2 diabetes.
SnuRHAC: A Runtime for Heterogeneous Accelerator Clusters with CUDA Unified Memory

This paper proposes a framework called SnuRHAC, which provides an illusion of a single GPU for the multiple GPUs in a cluster. Under SnuRHAC, a CUDA program designed to use a single GPU can utilize multiple GPUs in a cluster without any source code modification. SnuRHAC automatically distributes workload to multiple GPUs in a cluster and manages data across the nodes. To manage data efficiently, SnuRHAC extends CUDA Unified Memory and exploits its page fault mechanism. We also propose two prefetching techniques to fully exploit UM and to maximize performance. Static prefetching allows SnuRHAC to prefetch data by statically analyzing CUDA kernels. Dynamic prefetching complements static prefetching. SnuRHAC enforces an application to run on a single GPU if it is not suitable for multiple GPUs. We evaluate the performance of SnuRHAC using 18 benchmark applications from various sources. The evaluation result shows that while SnuRHAC significantly improves ease-of-programming, it shows scalable performance for the cluster environment depending on the application characteristics.
Towards Exploiting CPU Elasticity via Efficient Thread Oversubscription

Elasticity is an essential feature of cloud computing, which allows users to dynamically add or remove resources in response to workload changes. However, building applications that truly exploit elasticity is non-trivial. Traditional applications need to be modified to efficiently utilize variable resources. This paper explores thread oversubscription, i.e., provisioning more threads than the available cores, to exploit CPU elasticity in the cloud. While maintaining sufficient concurrency allows applications to utilize additional CPUs when more are made available, it is widely believed that thread oversubscription introduces prohibitive overheads due to excessive context switches, loss of locality, and contention on shared resources. In this paper, we conduct a comprehensive study of the overhead of thread oversubscription. We find that 1) the direct cost of context switching (i.e., 1-2 μs on modern processors) does not cause noticeable performance slow down to most applications; 2) oversubscription can be both constructive and destructive to the performance of CPU caches and TLB. We identify two previously under-studied issues that are responsible for drastic slowdowns in many applications under oversubscription. First, the existing thread sleep and wakeup process in the OS kernel is inefficient in handling oversubscribed threads. Second, pervasive busy-waiting operations in program code can waste CPU and starve critical threads. To this end, we devise two OS mechanisms, virtual blocking and busy-waiting detection, to enable efficient thread oversubscription without requiring program code changes. Experimental results show that our approaches can achieve an efficiency close to that in under-subscribed scenarios while preserving the capability to expand to many more CPUs. The performance gain is up to 77% for blocking- and 19x for busy-waiting-based applications compared to the vanilla Linux.
MPI-CorrBench: Towards an MPI Correctness Benchmark Suite

The Message Passing Interface (MPI) is the de-facto standard for distributed memory computing in high-performance computing (HPC). To aid developers write correct MPI programs, different tools have been proposed, e.g., Intel Trace Analyzer and Collector (ITAC), MUST, Parcoach and MPI-Checker. Unfortunately, the effectiveness of these tools is hard to compare, as they have not been evaluated on a common set of applications. More importantly, well-known and widespread benchmarks, which tend to be well-tested and error free, were used for their evaluation. To enable a structured comparison and improve the coverage and reliability of available MPI correctness tools, we propose MPI-CorrBench as a common test harness. MPI-CorrBench enables a structured comparison of the different tools available w.r. t. various types of errors. In our evaluation, we use MPI-CorrBench to provide a well-defined set of error-cases to MUST, ITAC, Parcoach and MPI-Checker. In particular, we find that ITAC and MUST complement each other in many cases. In general, MUST works better for detecting type errors while ITAC is better in detecting errors in non-blocking operations. Although the most-used functions of MPI are well supported, MPI-CorrBench shows that for one sided communication, the error detection capability of all evaluated tools needs improvement. Moreover, our experiments reveal a MPI standard violation in the MPICH test suite as well as several cases of discouraged use of MPI functionality.
A randomized controlled trial to isolate the effects of fasting and energy restriction on weight loss and metabolic health in lean adults

Daily energy restriction more effectively reduces body fat content than alternate-day fasting, with no evidence of fasting-specific health benefits. Not so fast Intermittent fasting is increasingly popular, but whether fasting itself offers specific nutritional benefits in lean individuals compared to traditional daily calorie restriction is unknown. In a small clinical trial of healthy individuals, Templeman et al. found that alternate-day fasting without energy restriction was ineffective at reducing body mass. Even with net energy intake restricted to that of daily dieters, alternate-day fasting less effectively reduced body fat content and offered no additional short-term improvements in metabolic or cardiovascular health compared to daily energy restriction. Intermittent fasting may impart metabolic benefits independent of energy balance by initiating fasting-mediated mechanisms. This randomized controlled trial examined 24-hour fasting with 150% energy intake on alternate days for 3 weeks in lean, healthy individuals (0:150; n = 12). Control groups involved a matched degree of energy restriction applied continuously without fasting (75% energy intake daily; 75:75; n = 12) or a matched pattern of fasting without net energy restriction (200% energy intake on alternate days; 0:200; n = 12). Primary outcomes were body composition, components of energy balance, and postprandial metabolism. Daily energy restriction (75:75) reduced body mass (−1.91 ± 0.99 kilograms) almost entirely due to fat loss (−1.75 ± 0.79 kilograms). Restricting energy intake via fasting (0:150) also decreased body mass (−1.60 ± 1.06 kilograms; P = 0.46 versus 75:75) but with attenuated reductions in body fat (−0.74 ± 1.32 kilograms; P = 0.01 versus 75:75), whereas fasting without energy restriction (0:200) did not significantly reduce either body mass (−0.52 ± 1.09 kilograms; P ≤ 0.04 versus 75:75 and 0:150) or fat mass (−0.12 ± 0.68 kilograms; P ≤ 0.05 versus 75:75 and 0:150). Postprandial indices of cardiometabolic health and gut hormones, along with the expression of key genes in subcutaneous adipose tissue, were not statistically different between groups (P > 0.05). Alternate-day fasting less effectively reduces body fat mass than a matched degree of daily energy restriction and without evidence of fasting-specific effects on metabolic regulation or cardiovascular health.
Perception, Attitude and Support of Society Towards Drug Abuse: Do Gender, Age and Education Matter?

This article highlights the support, attitude and perception of the general public towards drug abuse so that appropriate policies can be framed for the prevention of drug abuse among youth. The study aims to understand the relationship among variables influencing behaviour change with respect to drug abuse. Questionnaire from 1,159 respondents was administered comprising of 39 items exploring Perception, Attitude, Support pertaining to illicit drugs. Positive or negative attitude towards drug abuse is evolved out of the perception of problems associated with drug abuse and the support provided to dissuade drug-abusing behaviour, and relationship among these variables was tested using SEM-Path analysis. The perception of problems related to drug addiction significantly influences the attitude towards drug addiction. The perceived nature of the support structure augments the influence further (partial mediation). The augmenting effect of the support structure can be seen among gender, age and education. Moderator effects of age, gender and education were studied by estimating multi-group path coefficients. This article is useful to local government as they may take some of the findings of this article for framing policy related to educating youth related to drugs, creating a campaign regarding the harm of drug abuse and involving those volunteers in drug assistance programmes that are more supportive of drug addicts. This article is helpful for society to make them understand that their positive attitude and support towards drug abuse will give a second chance to drug addicts to leave drugs and live a normal life again.
REVENIA-KORINOS: ONE OF THE EARLIEST NEOLITHIC SETTLEMENTS IN NORTH GREECE AS EVIDENCED BY RADIOCARBON DATING

ABSTRACT Radiocarbon (14C) dating was applied to the Neolithic open-air, flat-extended settlement at Revenia-Korinos in Pieria, North Greece. The samples came from the earlier habitation period of the settlement, characterized by more than 100 pits that vary significantly in shape and dimensions, some of them being identified as subterranean or semi-subterranean pit dwellings. It is suggested that the fills of the pits were the result of secondary, structured refuse deposition, except for pits that preserve their habitational use, according to stratigraphic data. The 14C results confirm that Revenia is among the earliest Neolithic settlements in North Greece and the Aegean in general. The initial phase of habitation is dated at around 6600/6550 BC comparable only to two other EN sites in North Greece. Habitation intensified at around 6460/6430 BC, accompanied by a shift in pottery style. This phase lasts until 6200/6100 BC when the pit habitation mode is followed by above-ground, rectangular post-framed structures. The dates of the human burials from Revenia also identify them as among the earliest Neolithic burials in Greece. Finally, the radiocarbon dates proved very useful for sequencing the chronological use of the pits and the excavated area in general.
Age-related increases in reaction time result from slower preparation, not delayed initiation

Recent work indicates that healthy younger adults can prepare accurate responses faster than their voluntary reaction times indicate, leaving a seemingly unnecessary delay of 80-100ms before responding. Here we examined how the preparation of movements, initiation of movements, and the delay between them are affected by ageing. Participants made planar reaching movements in two conditions. The ‘Free Reaction Time’ condition assessed the voluntary reaction times with which participants responded to the appearance of a stimulus. The ‘Forced Reaction Time’ condition assessed the minimum time actually needed to prepare accurate movements by controlling the time allowed for movement preparation. The time taken to both initiate movements in the Free Reaction Time and to prepare movements in the Forced Response condition increased with age. Notably, the time required to prepare accurate movements was significantly shorter than participants’ self-selected initiation times; however, the delay between movement preparation and initiation remained consistent across the lifespan (~90ms). These results indicate that the slower reaction times of healthy older adults are not due to an increased hesitancy to respond, but can instead be attributed to changes in their ability to process stimuli and prepare movements accordingly, consistent with age-related changes in brain structure and function.
High resolution dynamic mapping of the C. elegans intestinal brush border

The intestinal brush border is made of an array of microvilli that increases the membrane surface area for nutrient processing, absorption, and host defence. Studies on mammalian cultured epithelial cells uncovered some of the molecular players and physical constrains required to establish this apical specialized membrane. However, the building and maintenance of a brush border in vivo has not been investigated in detail yet. Here, we combined super-resolution imaging, transmission electron microscopy and genome editing in the developing nematode C. elegans to build a high-resolution and dynamic localization map of known and new markers of the brush border. Notably, we show that microvilli components are dynamically enriched at the apical membrane during microvilli outgrowth and maturation but become highly stable once microvilli are built. This new mapping tool will be instrumental to understand the molecular processes of microvilli growth and maintenance in vivo as well as the effect of genetic perturbations, notably in the context of disorders affecting brush border integrity.
Bacteriophage T4 Vaccine Platform for Next-Generation Influenza Vaccine Development

Developing influenza vaccines that protect against a broad range of viruses is a public health priority, and several conserved viral proteins or domains have been identified as promising targets for such vaccine development. However, none of the targets is immunogenic, and vaccine platforms that can incorporate multiple antigens with enhanced immunogenicity are desperately needed. In this study, we provided proof-of-concept for the development of next-generation influenza vaccine using T4 phage virus-like particle (VLP) platform. With extracellular domain of influenza matrix protein 2 (M2e) as a readout, we showed that more than 1,280 M2e molecules can be assembled on a 120×90 nanometer phage capsid to form T4-M2e VLPs, which are highly immunogenic and induced complete protection against influenza virus challenge without any addition adjuvant. Potentially, additional conserved antigens or molecular adjuvants could be incorporated into the T4-M2e VLPs to customize influenza vaccines to address different issues. All the components of T4 VLP vaccines can be mass-produced in E. coli in a short time, therefore, providing a rapid approach to deal with the potential influenza pandemic.
Early functional connectivity in the developing sensorimotor network that is independent of sensory experience

Neonatal sensory experience shapes development of neural pathways carrying sensory information to the cortex. These pathways link to wider functional networks that coordinate activity of separate cortical regions, but it remains unknown when these broader networks emerge or how their maturation is influenced by sensory experience. By imaging activity across the cortex in neonatal mice, we have found unexpectedly early emergence of coordinated activity within a sensorimotor network that includes whisker-related somatosensory cortex and motor cortex. This network is spontaneously active but is not engaged by sensory stimulation, even though whisker deflection reliably drives cortical activity within barrel cortex. Acute silencing of the sensory periphery ablated spontaneous activity that was restricted to barrel cortex but spared this early sensorimotor network coactivity, suggesting that it is driven from elsewhere. Furthermore, perturbing sensory experience by whisker trimming did not impact emergence or early maturation of spontaneous activity in the sensorimotor network. As such, functional sensorimotor cortical networks develop early and, in contrast to development of ascending sensory pathways, their initial maturation is independent of sensory experience.
An approach to models for the design of upflow anaerobic filters

In this paper, a novel categorization system of anaerobic reactors is created to frame novel upflow anaerobic filter (UAF) reactor separated into two stages (UAF-2SS) and three separated stages (UAF-3SS). Three models for the performance of UAF-2SS and UAF-3SS reactors are proposed: (1) Modified model of the Monod’s Equation for estimating the substrate utilization rate (SUR) whose kinetic coefficient explains intracellular processes, (2) Model for biochemical transformation of substrate based on the Monod’s Equation and the Velz’s Law where the kinetic coefficient is associated to extra and intracellular processes and (3) Coupled model for transport and biochemical transformation processes integrated by two components depending on extracellular processes (adsorption and hydrolysis) and intracellular processes (fermentation/anaerobic oxidation, acidogenesis and methanogenesis). The highest degree of explanation of the proposed kinetic models for performance of UAF-2SS and UAF-3SS in the substrate removal is achieved through the coupled model.
Deep learning prediction of mild cognitive impairment conversion to Alzheimer’s disease at 3 years after diagnosis using longitudinal and whole-brain 3D MRI

Background While there is no cure for Alzheimer’s disease (AD), early diagnosis and accurate prognosis of AD may enable or encourage lifestyle changes, neurocognitive enrichment, and interventions to slow the rate of cognitive decline. The goal of our study was to develop and evaluate a novel deep learning algorithm to predict mild cognitive impairment (MCI) to AD conversion at three years after diagnosis using longitudinal and whole-brain 3D MRI. Methods This retrospective study consisted of 320 normal cognition (NC), 554 MCI, and 237 AD patients. Longitudinal data include T1-weighted 3D MRI obtained at initial presentation with diagnosis of MCI and at 12-month follow up. Whole-brain 3D MRI volumes were used without a priori segmentation of regional structural volumes or cortical thicknesses. MRIs of the AD and NC cohort were used to train a deep learning classification model to obtain weights to be applied via transfer learning for prediction of MCI patient conversion to AD at three years post-diagnosis. Two (zero-shot and fine tuning) transfer learning methods were evaluated. Three different convolutional neural network (CNN) architectures (sequential, residual bottleneck, and wide residual) were compared. Data were split into 75% and 25% for training and testing, respectively, with 4-fold cross validation. Prediction accuracy was evaluated using balanced accuracy. Heatmaps were generated. Results The sequential convolutional approach yielded slightly better performance than the residual-based architecture, the zero-shot transfer learning approach yielded better performance than fine tuning, and CNN using longitudinal data performed better than CNN using a single timepoint MRI in predicting MCI conversion to AD. The best CNN model for predicting MCI conversion to AD at three years after diagnosis yielded a balanced accuracy of 0.793. Heatmaps of the prediction model showed regions most relevant to the network including the lateral ventricles, periventricular white matter and cortical gray matter. Conclusions This is the first convolutional neural network model using longitudinal and whole-brain 3D MRIs without extracting regional brain volumes or cortical thicknesses to predict future MCI to AD conversion at 3 years after diagnosis. This approach could lead to early prediction of patients who are likely to progress to AD and thus may lead to better management of the disease.
CFD analysis of biomass steam gasification in fluidized bed gasifier: A parametric study by the assessment of drying stage

ABSTRACT In this study, CFD analysis was performed based on a comprehensive pyrolysis chemical reaction model to simulate the gasification process of biomass in a fluidized bed gasifier using almond shells as the biomass feedstock. A novel multi-phase CFD model consisting of 33 chemical reactions that cover all of the drying stages, detailed primary and secondary pyrolysis stages, as well as gasification stage, was adopted for the first time. Gasification temperature and steam-to-biomass ratio were selected as the main parameters and their effects on produced gas composition, lower heating value, char yield, tar content, and tar components were evaluated. The obtained results of the base case agreed to a reasonable extent with the results of the previous experimental works. According to the results, an increase in gasification temperature enhanced the mole fractions of H2 and CO. Therefore, it was recommended to use higher temperatures and steam-to-biomass ratio for production purposes of H2 and CO. The lower heating value decreased by a factor of 14.7% and 1.86% for increased values of gasification temperature and steam-to-biomass ratio, respectively. It was also observed that CH4 mole fraction has a strong effect on the lower heating value of the produced gas. Furthermore, char yield was found to have a declined trend with increasing gasification temperature; however, the reverse was valid with increasing steam-to-biomass ratio.
Elastic Origin of the Unsymmetrical Thermal Hysteresis in Spin Crossover Materials: Evidence of Symmetry Breaking

The jungle of experimental behaviors of spin-crossover materials contains a tremendous number of unexpected behaviors, among which, the unsymmetrical hysteresis loops having different shapes on heating and cooling, that we often encounter in literature. Excluding an extra effect of crystallographic phase transitions, we study here these phenomena from the point of view of elastic modeling and we demonstrate that a simple model accounting for the bond lengths misfits between the high-spin and low-spin states is sufficient to describe the situation of unsymmetrical hysteresis showing plateaus at the transition only on cooling or on heating branches. The idea behind this effect relates to the existence of a discriminant elastic frustration in the lattice, which expresses only along the high-spin to low-spin transition or in the opposite side. The obtained two-step transitions showed characteristics of self-organization of the spin states under the form of stripes, which we explain as an emergence process of antagonist directional elastic interactions inside the lattice. The analysis of the spin state transformation inside the plateau on cooling in terms of two sublattices demonstrated that the elastic-driven self-organization of the spin states is accompanied with a symmetry breaking.