Miracle-dz/UniFAR-FTUs huggingface dataset:
Are Skeletal Muscle Changes during Prolonged Space Flights Similar to Those Experienced by Frail and Sarcopenic Older Adults?

Microgravity exposure causes several physiological and psychosocial alterations that challenge astronauts’ health during space flight. Notably, many of these changes are mostly related to physical inactivity influencing different functional systems and organ biology, in particular the musculoskeletal system, dramatically resulting in aging-like phenotypes, such as those occurring in older persons on Earth. In this sense, sarcopenia, a syndrome characterized by the loss in muscle mass and strength due to skeletal muscle unloading, is undoubtedly one of the most critical aging-like adverse effects of microgravity and a prevalent problem in the geriatric population, still awaiting effective countermeasures. Therefore, there is an urgent demand to identify clinically relevant biological markers and to underline molecular mechanisms behind these effects that are still poorly understood. From this perspective, a lesson from Geroscience may help tailor interventions to counteract the adverse effects of microgravity. For instance, decades of studies in the field have demonstrated that in the older people, the clinical picture of sarcopenia remarkably overlaps (from a clinical and biological point of view) with that of frailty, primarily when referred to the physical function domain. Based on this premise, here we provide a deeper understanding of the biological mechanisms of sarcopenia and frailty, which in aging are often considered together, and how these converge with those observed in astronauts after space flight.
Properties of Encroachments and the Associated Roadway and Roadside Environment in the Second Strategic Highway Research Program

An encroachment is defined as a vehicle departing the lanes of the traveled way and entering the roadside or median. Encroachments have been previously characterized by Hutchinson and Kennedy and by Cooper, in studies conducted in 1964 and 1978, respectively. Both studies are more than 40 years old, and both roadways and vehicles have changed significantly since data collection ended, presenting the need for an updated encroachment study. This study identified and characterized encroachment events in the Second Strategic Highway Research Program Naturalistic Driving Study (SHRP 2 NDS). Then, we compared the statistical distributions of roadway and roadside environmental factors weighted by their occurrence in SHRP 2 NDS normal driving and during these encroachment events. This weighting represented the typical infrastructure SHRP 2 vehicles encountered, as opposed to the infrastructure installed. Segments of roadway encountered more frequently or encroachment areas represented more frequently were weighted more heavily. A total of 863,280 SHRP 2 trips containing normal driving and road-departure events were selected from the SHRP 2 dataset which included 215,993 h of driving. A total of 278,415 departure events were found. Encroachment events were similar to normal driving in roadway grade, shoulder width, and lane width. Encroachment events occurred more frequently on roadway sections with depressed medians, one or two lanes in the travel direction, smaller horizontal curve radii, or rumble strips present.
Developing A Dynamic Testbed: Designing for Trust in Complex Human Agent Teams

There has been a great deal of research examining trust in human-agent teaming. However, the majority of this research has focused on a human-agent dyad with low-interdependency and limited time to study the trajectory of trust. As human-agent teams (HATs) increase in agent capabilities, team size, and heterogeneity, there is a need to enable research paradigms to understand the nuances of trust dynamics in HATs. To support this, we propose that research testbeds should contain four principal dimensions. First, agents in testbeds should be enabled to enact varying levels of autonomy, especially at the highest level. Second, the testbed must support performance of a task that requires true interdependence between the human(s) and the agent(s). Third, the testbed should be able to integrate multiple agents, with varying capabilities and roles, which differ from each other and that of the human. Fourth, testbed scenarios must be long enough to allow sufficient time for (a) trust to be established, (b) trust events (e.g., violation and repair) to be injected multiple times, and (c) the impacts of the events to unfold.
RepKV: A Replicated Key-Value Store to Boost Multiple Indices for Key-Value Separation

Primary and secondary indices are demanded in real-world applications. Recent works show that key-value(KV) separation is efficient to improve queries of multiple secondary indices in LSM-based KV stores. It stores the value in a separate value log and only stores keys and the value address in primary and secondary indices. However, this share-value scheme on multiple indices results in suboptimal efficiency: (1) queries on secondary indices and range queries on all indices cannot fully exploit the bandwidth of SSD devices simultaneously (2) the put operation is inefficient to update secondary indices.To address the above inefficiency, we propose RepKV, a replicated KV store aiming to boost operations of multiple in-dices. Firstly, RepKV uses a primary-backup replication scheme. Each replication stores the same KV pairs but adopts different organizations to exploit the benefit of SSD devices. Secondly, RepKV proposes a lightweight replication scheme to mitigate the extra KV pairs synchronized in replications. Thirdly, RepKV uses a parallel parsing policy to boost the put operation. Experimental results show that RepKV can improve the query performance on secondary indices by up to 22.24%, the range query performance of all indices by up to 31.38%, and the put performance by up to 13.8%. Besides, RepKV can reduce the I/O amplification of replication by up to 3.05x via the lightweight replication scheme.
Genotype × Environment Interaction Influence Secondary Metabolite in Cowpea Infested by Flower Bud Thrips

Secondary metabolites are among the major contributors of host-plant resistance. Cowpea produces secondary metabolites that are known to enhance resistance to insect pests including flower bud thrips. However, environmental conditions tend to affect the production of secondary metabolites, thereby affecting the response of the host plants to insect pest. The objective of this study was to determine the effect of the genotype × environment interaction on the production of secondary metabolites and flower bud thrips resistance in cowpea. Six cowpea genotypes were evaluated for flower bud thrips damage and the contents of flavonoids, antioxidants, phenolics, proteins, lignin, tannins and reducing sugars in four environments with varying temperatures and rainfall patterns. The data collected were subjected to the analysis of variance and genotype and genotype × environment (GGE) analysis. Flower thrips damage, and the contents of flavonoids, antioxidants, lignin, tannins and reducing sugars varied significantly (p < 0.001) among genotypes. Genotype Sanzi produced high levels of antioxidants, while TVU-9820 led in phenolic concentrations respectively. Metabolite contents were significantly (p < 0.001) different among environments, with the long rain season of field experiments led to increased production of flavonoids, proteins, lignin and tannins. A resistant genotype, TVU-3804, produced relatively stable contents of flavonoids, antioxidants, phenolics, proteins and reducing sugars across environments. In this study, the environment influenced the concentration of the metabolites, which in turn affected the cowpea’s resistance to flower bud thrips.
Identification of muscle determinant for different gait speeds by proper orthogonal decomposition

In this investigation, we explore the use of the proper orthogonal decomposition (POD) on electromyography (EMG) of the leg muscles, with the objective of elucidating the muscles behavior for each gait speeds. Four different gait speeds were used in the study: slow, comfortable, fast and fastest walking. The electromyographic data used in this study were recorded from 12 bilateral lower limb muscles: tensor fascia latae (TFL), semitendinosus (ST), vastus medialis (VM), rectus femoris (RF), tibialis anterior (TA) and medial gastrocnemius (MG). Results indicate that the primary muscles for these gait speeds were bilateral TFL which act alternately to accept weight bearing on each leg. The same muscles also show another dominant function when working simultaneously in pelvic stabilization. In addition, we found that when the speed of walking increases, the number of muscle determinants for gait has been added. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
The Aging Heart: A Molecular and Clinical Challenge

Aging is associated with an increasing burden of morbidity, especially for cardiovascular diseases (CVDs). General cardiovascular risk factors, ischemic heart diseases, heart failure, arrhythmias, and cardiomyopathies present a significant prevalence in older people, and are characterized by peculiar clinical manifestations that have distinct features compared with the same conditions in a younger population. Remarkably, the aging heart phenotype in both healthy individuals and patients with CVD reflects modifications at the cellular level. An improvement in the knowledge of the physiological and pathological molecular mechanisms underlying cardiac aging could improve clinical management of older patients and offer new therapeutic targets.
Introducing materials informatics to dielectrics design

It has become increasingly common to use machine learning techniques for discovering and designing novel materials. Big data enables machine learning techniques to make accurate predictions. However, experimental data are not abundant especially in the case of dielectric properties. In addition, the properties of polymers depend not only on the structure of monomers but also on the length of polymers, morphology, additives, and so on which further complicates the problem. Here, we review our latest research outcomes that are related to computational and data-driven dielectric materials design. First, we show how we were able to accurately predict the dielectric properties of gases using a small data set and further discover new molecules that can potentially outperform existing SF6 alternative gases. Then we show that by proper feature engineering it is possible to predict the thermal and electrical properties of polymer/inorganic filler composites. The main findings are as follows: (1) in line with our intuition, in general, accurate prediction of dielectric properties is difficult compared to the prediction of thermal or mechanical properties, (2) the process condition has an especially great impact on the electric properties of polymers, (3) with the knowledge of the underlying physics affecting the macroscopic properties, one can predict the dielectric properties of various materials with reasonable accuracy, (4) machine learning helps us understand the factors that control the dielectric properties, and (5) it can also be used to guide experiments or to provide testing standards.
Arbuscular Mycorrhiza Symbiosis as a Factor of Asteraceae Species Invasion

Invasive weeds of the Asteraceae family are widespread in the world. Arbuscular mycorrhiza (AM) is one of the main factors contributing to the successful distribution of these species that is most clearly manifested in the subfamily Asteroideae. The benefits of plant-AMF symbiosis are most significant under unfavorable biotic and abiotic conditions. The specificity of the relationship between arbuscular mycorrhizal fungi (AMF) communities and plants and is determined at the presymbiotic stage. The AMF colonization level is higher in invasive species than in native ones, but AMF communities associated with Asteraceae invasive species are less diverse. AMF communities of Asteraceae invaders often include fewer common species (e.g., species belonging to Diversisporales). Invaders also reduce native AMF species richness in new areas. Arbuscular mycorrhizal fungi can form mycorrhizal networks that allow the redistribution of nutrients in plant communities. The most significant influence of AMF associated with invasive Asteraceae plants is seen in the formation of soil and rhizosphere microbiota, including the suppression of beneficial soil bacteria and fungi. This review could be useful in the development of practical recommendations for the use of AMF-based fertilizers.
An Approach for Systems-Level Understanding of Prostate Cancer from High-Throughput Data Integration to Pathway Modeling and Simulation

To understand complex diseases, high-throughput data are generated at large and multiple levels. However, extracting meaningful information from large datasets for comprehensive understanding of cell phenotypes and disease pathophysiology remains a major challenge. Despite tremendous advances in understanding molecular mechanisms of cancer and its progression, current knowledge appears discrete and fragmented. In order to render this wealth of data more integrated and thus informative, we have developed a GECIP toolbox to investigate the crosstalk and the responsible genes’/proteins’ connectivity of enriched pathways from gene expression data. To implement this toolbox, we used mainly gene expression datasets of prostate cancer, and the three datasets were GSE17951, GSE8218, and GSE1431. The raw samples were processed for normalization, prediction of differentially expressed genes, and the prediction of enriched pathways for the differentially expressed genes. The enriched pathways have been processed for crosstalk degree calculations for which number connections per gene, the frequency of genes in the pathways, sharing frequency, and the connectivity have been used. For network prediction, protein–protein interaction network database FunCoup2.0 was used, and cytoscape software was used for the network visualization. In our results, we found that there were enriched pathways 27, 45, and 22 for GSE17951, GSE8218, and GSE1431, respectively, and 11 pathways in common between all of them. From the crosstalk results, we observe that focal adhesion and PI3K pathways, both experimentally proven central for cellular output upon perturbation of numerous individual/distinct signaling pathways, displayed highest crosstalk degree. Moreover, we also observe that there were more critical pathways which appear to be highly significant, and these pathways are HIF1a, hippo, AMPK, and Ras. In terms of the pathways’ components, GSK3B, YWHAE, HIF1A, ATP1A3, and PRKCA are shared between the aforementioned pathways and have higher connectivity with the pathways and the other pathway components. Finally, we conclude that the focal adhesion and PI3K pathways are the most critical pathways, and since for many other pathways, high-rank enrichment did not translate to high crosstalk degree, the global impact of one pathway on others appears distinct from enrichment.
The Arylamidine T-2307 as a Novel Treatment for the Prevention and Eradication of Candida tropicalis Biofilms

Candida tropicalis is an emerging pathogen with a high mortality rate due to its virulence factors, including biofilm formation, that has important repercussions on the public health system. The ability of C. tropicalis to form biofilms, which are potentially more resistant to antifungal drugs and the consequent increasing antimicrobial resistance, highlights an urgent need for the development of novel antifungal. The present study analyzed the antibiofilm capacity of the arylamidine T-2307 on two strains of Candida tropicalis. Antimicrobial activity and time-killing assays were performed to evaluate the anticandidal effects of T-2307, the antibiofilm ability on biomass inhibition and eradication was evaluated by the crystal violet (CV) method. Furthermore, in Galleria mellonella infected larvae an increased survival after pre—and post- treatment with T-2307 was observed. The MTT test was used to determine the viability of immortalized human prostate epithelial cells (PNT1A) after exposure to different concentrations of T-2307. Levels of interleukin IL-4, IL-8, IL-10 were quantified after Candida infection of PNT1A cells and treatment. Active doses of T-2307 did not affect the viability of PNT1A cells, and drug concentrations of 0.005 or 0.01 µg mL−1 inhibited the secretion of inflammatory cytokines. Taken together, these results provide new information on T-2307, indicating this drug as a new and promising alternative therapeutic option for the treatment of Candida infections.
A portable fNIRS system with eight channels

Abundant study on the hemodynamic response of a brain have brought quite a few advances in technologies of measuring it. The most benefitted is the functional near infrared spectroscope (fNIRS). A variety of devices have been developed for different applications. Because portable fNIRS systems were more competent to measure responses either of special subjects or in natural environment, several kinds of portable fNIRS systems have been reported. However, they all required a computer for receiving data. The extra computer increases the cost of a fNIRS system. What’s more noticeable is the space required to locate the computer even for a portable system. It will discount the portability of the fNIRS system. So we designed a self-contained eight channel fNIRS system, which does not demand a computer to receive data and display data in a monitor. Instead, the system is centered by an ARM core CPU, which takes charge in organizing data and saving data, and then displays data on a touch screen. The system has also been validated by experiments on phantoms and on subjects in tasks.
Ordering kinetics of body-centered-cubic morphology in diblock copolymer solutions at low temperatures

The ordering kinetics of a body-centered cubic (bcc) mesophase in squalane solutions of poly(styrene-b-ethylene-alt-propylene) (SEP) at low temperatures was studied using rheological and small-angle x-ray scattering methods. At temperatures more than 110 °C below the order-to-disorder transition temperature (TODT), the evolution of the storage modulus, G′, and the absolute value of the complex modulus, |G*|, was found to be describable by the Avrami equation, assuming a “series” mechanical model for the combination of a soft initial phase and a growing hard phase. The ordering half time, t0.5, of the SEP/squalane solutions decreased with temperature from 50 to 120 °C and increased with concentration from 5 to 10 wt %, indicating the diffusion-controlled nature of the ordering process in these micellar systems at low temperatures. The temperature dependence of t0.5 followed the Arrhenius relationship with the activation energy showing negligible concentration dependence. Furthermore, the elastic modulus of.
Scheduling Information-Guided Efficient High-Level Synthesis Design Space Exploration

High-level synthesis (HLS) transforms designs specified by high-level programming language into RTL designs. In order to get the optimal designs, many design space exploration (DSE) methods are proposed. However, most of them consider the HLS tool as a black box, ignoring crucial information from the synthesis process, particularly the scheduling step. In this work, we propose to extract some useful information from scheduling to guide the DSE and develop a genetic algorithm (GA)-based DSE method based on our in-house HLS tool. The experimental results show that our method can obtain more Pareto-optimal points than the counterpart without using the scheduling information. It also outperforms a traditional GA-based HLS DSE method by using only a quarter of the total run time. For a large benchmark, our method finds 95.7% Pareto-optimal designs by visiting only 0.18% total promising design points.
Investigating Changes in pH and Soluble Solids Content of Potato during the Storage by Electronic Nose and Vis/NIR Spectroscopy

Potato is an important agricultural product, ranked as the fourth most common product in the human diet. Potato can be consumed in various forms. As customers expect safe and high-quality products, precise and rapid determination of the quality and composition of potatoes is of crucial significance. The quality of potatoes may alter during the storage period due to various phenomena. Soluble solids content (SSC) and pH are among the quality parameters experiencing alteration during the storage process. This study is thus aimed to assess the variations in SSC and pH during the storage of potatoes using an electronic nose and Vis/NIR spectroscopic techniques with the help of prediction models including partial least squares (PLS), multiple linear regression (MLR), principal component regression (PCR), support vector regression (SVR) and an artificial neural network (ANN). The variations in the SSC and pH are ascending and significant. The results also indicate that the SVR model in the electronic nose has the highest prediction accuracy for the SSC and pH (81, and 92%, respectively). The artificial neural network also managed to predict the SSC and pH at accuracies of 83 and 94%, respectively. SVR method shows the lowest accuracy in Vis/NIR spectroscopy while the PLS model exhibits the best performance in the prediction of the SSC and pH with respective precision of 89 and 93% through the median filter method. The accuracy of the ANN was 85 and 90% in the prediction of the SSC and pH, respectively.
Towards Human-Automation Teamwork in Shared En-Route Air Traffic Control: Task Analysis

In the quest for more efficient air traffic management, a common approach is to allocate an increasing amount of functionality to higher levels of automation, with a supervisory role for humans. This potentially leads to forthcoming issues such as skill degradation and out-of-the-loop phenomenon. If the traffic in an airspace is instead shared between a human operator and an automated system, with specific flights fully delegated to automation, operators can maintain their skills and stay actively involved in controlling the rest of the traffic. This does, however, lead to new forms of mixed conflicts, where two flights are controlled by different agents. A smart flight allocation strategy, starting with the delegation of basic flights requiring little monitoring or cognitive effort, is expected to improve combined human-automation performance. In this paper, we present flowcharts to model en-route air traffic controller cognitive think and action processes in two core tasks: conflict detection and resolution. We qualitatively describe the impact of delegating flights to automation and the associated introduction of mixed conflicts. Once empirically validated and quantified in follow-up research, these models can be used to design flight allocation strategies for future human-automation teams.