Miracle-dz/UniFAR-FTUs huggingface dataset:
Circadian Rhythmicity of Diazinon Susceptibility, Detoxifying Enzymes, and Energy Reserves in Aphis gossypii (Hemiptera: Aphididae)

Abstract The daily susceptibility rhythm of the cotton aphid, Aphis gossypii Glover, to diazinon and the corresponding changes in the activity of three xenobiotic detoxifying enzymes—cytochrome P450 monooxygenases (P450), glutathione S-transferases (GSTs), and esterases—were investigated. Bioassays were conducted to estimate the median lethal doses (LD50) of diazinon at six different zeitgeber times (ZT0, 4, 8, 12, 16, and 20) under constant light (LL) and lighting conditions of 16 h of light and 8 h of darkness (LD). The results showed that the highest susceptibility occurred at the onset of night (ZT16) and 4 h before this time point (ZT12) under the LD condition. The endogenous rhythmicity of susceptibility was ensured, as the highest susceptibility occurred at the same time under the LL condition. The circadian changes in susceptibility to diazinon were almost coincident with changes in esterase and GSTs activity, but not in P450 activity. We also found rhythmic changes in energy components of whole-body aphids, with similar patterns of circadian changes of proteins, lipids, and soluble carbohydrates, but not glycogen, under LL and LD conditions. These photoperiod conditions (LD and LL) showed different fluctuation in trends of energy resources and of course, different quantities. Our study represents the first report of circadian control of insecticide susceptibility in aphids and provides insights into more efficient control of these pests by unveiling the times of day during which aphids are more susceptible to insecticides with attention to endogenous physiological phenomena.
Soft Langmuir–Blodgett Technique for Hard Nanomaterials

Materials and their assemblies of dimensions down to a few nanometers have attracted considerable scientific interest in physical, chemical, and biological sciences because of unique properties not available in their bulk counterparts. The Langmuir–Blodgett (LB) technique allows rigid nanomaterials to be aligned in particular structures through a flexible assembly process at liquid interfaces. In this review, we summarize the development of assembly of hard nanomaterials using soft LB techniques. An initial summary of the basic features of nanomaterials will include dimension‐related effects, synthesis, characterization, and analysis, and will be followed by examples of LB assemblies of nanomaterials described according to their morphology: nanoparticles, nanorods, nanowires, nanotubes, and nanosheets. Some of the nanomaterials have been fabricated in orientation‐controlled morphologies, and have been incorporated into prototype devices for gas sensing and photocurrent transport. In the final part of this review, the challenges remaining for LB techniques of hard nanomaterials will be overviewed, and will include a comparison with the widely‐used LB technique involving soft materials.
Down‐regulating Myoferlin inhibits the vasculogenic mimicry of melanoma via decreasing MMP‐2 and inducing mesenchymal‐to‐epithelial transition

Vasculogenic mimicry (VM) constitutes a novel approach for tumour blood supply and contributes to tumour metastasis and poor prognosis in patients with melanoma. Myoferlin (MYOF), a type II membrane protein involved in membrane regeneration and repair, is elevated in several malignant tumours, especially in advanced melanomas. This study aims to investigate the role and mechanism of MYOF in the regulation of VM. VM structures were found in 14 of 52 tested melanoma samples, and high MYOF expression correlated with VM structures. According to Kaplan–Meier survival curves, VM channels and elevated MYOF expression both correlated with poor prognosis in melanoma patients. Down‐regulation of MYOF by siRNA severely impaired the capability of A375 cells to form VM structures in vitro. Further studies demonstrated MYOF knockdown inhibited cell migration and invasion, which is required for VM formation, via decreasing MMP‐2 expression as evidenced by Western blotting, RT‐RCP and ELISA results. SB‐3CT, a specific inhibitor of MMP‐2, showed similar inhibiting effects with siMYOF, further supporting that MYOF down‐regulation inhibits MMP‐2 expression to affect VM formation. Moreover, MYOF knockdown suppress VM formation by A375 cells by inducing mesenchymal‐to‐epithelial transition (MET). After down‐regulating MYOF, focal adhesions were enlarged and A375 cells developed into a clear epithelial morphology. Such cells acquired the expression of E‐cadherin at adherens junctions along with a loss of mesenchymal markers, such as Vimentin and Twist1. In conclusion, MYOF plays an important role in VM and knockdown of MYOF suppresses VM formation via decreasing MMP‐2 and inducing MET in A375 melanoma cells.
Mathematical foundations of the GraphBLAS

The GraphBLAS standard (GraphBlas.org) is being developed to bring the potential of matrix-based graph algorithms to the broadest possible audience. Mathematically, the GraphBLAS defines a core set of matrix-based graph operations that can be used to implement a wide class of graph algorithms in a wide range of programming environments. This paper provides an introduction to the mathematics of the GraphBLAS. Graphs represent connections between vertices with edges. Matrices can represent a wide range of graphs using adjacency matrices or incidence matrices. Adjacency matrices are often easier to analyze while incidence matrices are often better for representing data. Fortunately, the two are easily connected by matrix multiplication. A key feature of matrix mathematics is that a very small number of matrix operations can be used to manipulate a very wide range of graphs. This composability of a small number of operations is the foundation of the GraphBLAS. A standard such as the GraphBLAS can only be effective if it has low performance overhead. Performance measurements of prototype GraphBLAS implementations indicate that the overhead is low.
Family caregivers' level of mastery predicts survival of patients with glioblastoma: A preliminary report

Glioblastoma multiforme (GBM) is associated with a poor prognosis, and patients rely heavily on family caregivers for physical and emotional support. The capability and mental health of family caregivers may influence their ability to provide care and affect patient outcomes. The objective of the current study was to investigate whether caregivers' anxiety, depressive symptoms, burden, and mastery influenced survival in a sample of patients newly diagnosed with GBM.
EFFECTS OF HIGH-INTENSITY TRAINING WITH ONE VERSUS THREE CHANGES OF DIRECTION ON YOUTH FEMALE BASKETBALL PLAYERS’ PERFORMANCE

To compare the effects of high-intensity interval training (HIT) with one versus three changes of direction (COD) on young (age, 17.2±1.1 years) female basketball players’ performance, six weeks of regular basketball training (control period) was followed by six weeks of high-intensity training added to regular training , two times per week, with a random allocation of athletes to either HIT with one (HIT-COD1; n=6) or three COD (HIT-COD3; n=6). Before and after the control and HIT-COD training periods athletes performed repeated-sprint ability test (RSA), modified agility T-test (MAT), V-cut, triple standing dominant (TS-D) and nondominant (TS-ND) jump, TS-D and TS-ND with COD tests, and 30-15 Intermittent Fitness Test (30-15IFT). With the exception of a substantial improvement in V-cut in both groups, no substantial changes occurred during the control period. Both HIT-COD training programs improved V-cut, although only HIT-COD3 substantially improved RSA mean time (RSAm), MAT and the final speed reached in 30-15IFT (VIFT). The between-group comparison revealed greater improvements in RSAm and VIFT in HIT-COD3 than in HITCOD1. In conclusion, supplementation of basketball training with HIT-COD drills adds improvements to young female basketball player’s performance, especially when 3 COD are incorporated into HIT.Key words: team sport, agility, fitness, women, maturation, explosive strength
Software Defined Architecture for VANET: A Testbed Implementation with Wireless Access Management

Toward ITS, academia and industry aim to utilize all possible radio access technologies in order to support reliable services and applications in VANETs. Thus, the inclusion of already deployed Wi-Fi networks in VANET topology is a crucial step for the next generation vehicular networks. However, the VANET topology also requires preservation of the features already offered by DSRC and the core cellular network. As a result, the coexistence of multiple different access technologies results in high complexity in terms of the control and management of the network infrastructure. To this end, software defined networking provides a promising opportunity to simplify the management and control of clumsy network infrastructures by decoupling the data and control planes in order to provide elasticity for current networks. In this article, we propose an architectural model that exploits this opportunity in order to enhance VANET with Wi-Fi access capability. Moreover, we offer a novel software defined VANET architecture that consists of soft OpenFlow switches with Wi-Fi capabilities as both roadside units and vehicles. In particular, we first investigate existing test tools and environments for software defined wireless networks and also supply a novel testbed architecture in order to provide a feasible test environment for evaluating the proposed architecture. Additionally, we propose a Wireless Access Management (WAM) protocol that provides wireless host management and basic flow admission with respect to the available bandwidth to validate the capability of the offered architecture. The observation results of the deployed testbed prove the conformity of the offered 802.11 architecture to the VANET.
Nanoparticles-induced apoptosis of human airway epithelium is mediated by proNGF/p75NTR signaling

ABSTRACT Environmental and occupational exposures to respirable ultrafine fractions of particulate matter (PM) have been implicated in the initiation and exacerbation of lung diseases. However, the precise mechanisms underlying production of cell damage and death attributed to nanoparticles (NP) on human airway epithelium are not fully understood. This study examined the role of neurotrophic pathways in NP-induced airway toxicity. Size and agglomeration of TiO2 nanoparticles (TiO2-NP) and fine (TiO2-FP) particles were measured by dynamic light scattering. Expression and signaling of key neurotrophic factors and receptors were assessed by real-time polymerase chain reaction, flow cytometry, immunostaining, and Western blot in various respiratory epithelial cells after exposure to TiO2-NP or TiO2-FP. Particle-induced cell death was measured by flow cytometry after annexin V/propidium iodide staining. The role of neurotrophin-dependent apoptotic pathways was analyzed with specific blocking antibodies or siRNAs. Exposure of human epithelial cells to TiO2-NP enhanced interleukin (IL)-1α synthesis, as well as nerve growth factor (NGF) gene expression and protein levels, specifically the precursor form (proNGF). TiO2-NP exposure also increased expression of p75NRF receptor genes. These neurotropic factor and receptor responses were stimulated by IL-1α and abolished by its specific receptor antagonist (IL-1-ra). TiO2-NP also increased JNK phosphorylation and apoptosis, which was prevented by anti-p75NRF or NGFsiRNA. Data demonstrated that TiO2-NP exerted adverse effects in the respiratory tract by inducing unbalanced overexpression of immature neurotrophins, which led to apoptotic death of epithelial cells signaled through the death receptor p75NTR. This may result in airway inflammation and hyperreactivity after exposure to TiO2-NP.
GECS: Graph Embedding Using Connection Subgraphs

This paper studies the problem of learning large-scale graph representations (a.k.a. embeddings). Such representations encode the relations among distinct nodes on the continuous feature space. The learned representations generalize over various tasks, such as node classification, link prediction, and recommendation. Learning nodes representations aims to map proximate nodes close to one another in the low-dimension vector space. Thus, embedding algorithms pursue to preserve local and global network structure by identifying nodes neighborhood notions. However, the means proposed methods have been employed in order to identify nodes neighborhoods fail to precisely capture network structure. In this paper, we propose a novel scalable graph embedding algorithmic framework called GECS, which aims to learn graph representations using connection subgraphs, where analogy with electrical circuits has been employed. The connection subgraphs are created to address the proximity among each two non-adjacent nodes, which are abundant in real-world networks, by maximizing the amount of flow between them. Although a subgraph captures proximity between two non-adjacent nodes, the formation of the subgraph addresses the direct connections with immediate neighbors as well. Therefore, our algorithm better preserves the local and global structure of a network. Further, despite the fact that non-adjacent nodes are numerous in real-world networks, our algorithm can scale to large-scale graphs, because we do not deal with the graph as a whole, instead, with much more smaller extracted subgraphs. Since our algorithm is not yet empirically examined, we here introduce a potential solution that can better learn graph representations comparing to existing embedding methods accompanied by rational reasoning
Cross-Layer Design for Video Replication Strategy over Multihop Wireless Networks

In this paper, we propose a cross-layer optimization approach for replication of video streaming over multihop wireless network by jointly taking into account application, network, MAC, and physical layers. Specifically, we design a middleware replication strategy layer with a stack profile, in which parameters across the hops and all considered layers are exchanged for optimal video replication. The simulation results demonstrate that our method improves the replication strategy performance in terms of user-perceived video quality. In turn, it satisfies the heterogeneous receive bandwidth constraint of users for efficiently using the network bandwidth compared to other optimal replication strategies without cross-layer approach.
An indirect closed circuit respiration chamber suitable for fowl.

Abstract The indirect closed circuit calorimeter, constructed of Perspex, can hold a single fowl of up to 3 kg. or six chickens from 10 to 24 days of age. Heat production is measured over a period of 24 hr. A decrease in pressure within the chamber occurs through absorption of expired CO2 in a KOH solution. A solenoid valve is activated and O2 flows into the chamber from a cylinder holding 200 1. of O2 which is weighed at the start and finish of a 24 hr. determination of heat production. Samples of chamber air are withdrawn at the start and finish of each determination and heat production is calculated from the quantitative recovery of carbonate and from the loss of weight of the O2 cylinder, after first correcting for any changes in the composition of the chamber air that occur during the 24 hr. period of measurement. Three chickens (each weighing about 1 kg.) taken from a group of 10 cross-bred cockerels, were placed one in each of three calorimeters and given a commercial cereal-based diet. The remaining 7 cockerels were killed to give initial values of body composition of the 3 experimental fowl. Heat productions were measured over a period of 12–18 days; the 3 fowl were then killed and body composition determined. Heat production of the cockerels, estimated from gaseous exchange was, on average, within 1% of values derived from the carbon and nitrogen balances. Fasting heat productions of the 3 fowl were 71, 72 and 71 kcal. /kg.3/4/day and net availability (%) of metabolizable energy of the diet was 70, 70 and 61 respectively. Composition of weight gain of two of the cockerels agreed with values estimated from carbon and nitrogen balance, but for the third cockerel nitrogen retention was much higher when estimated from nitrogen balance than from carcass analysis.
Food restriction affects maternal investment but not neonate phenotypes in a viviparous lizard

Food availability significantly affects an animal's energy metabolism, and thus its phenotype, survival, and reproduction. Maternal and offspring responses to food conditions are critical for understanding population dynamics and life-history evolution of a species. In this study, we conducted food manipulation experiments in field enclosures to identify the effect of food restriction on female reproductive traits and postpartum body condition, as well as on hatchling phenotypes, in a lacertid viviparous lizard from the Inner Mongolian desert steppe of China. Females under low-food availability treatment (LFT) had poorer immune function and body condition compared with those under high-food availability treatment (HFT). The food availability treatments significantly affected the litter size and litter mass of the females, but not their gestation period in captivity or brood success, or the body size, sprint speed, and sex ratio of the neonates. Females from the LFT group had smaller litter sizes and, therefore, lower litter mass than those from the HFT group. These results suggest that female racerunners facing food restriction lay fewer offspring with unchanged body size and locomotor performance, and incur a cost in the form of poor postpartum body condition and immune function. The flexibility of maternal responses to variable food availability represents an important life strategy that could enhance the resistance of lizards to unpredictable environmental change.
Drug–drug interactions involving antidepressants: focus on desvenlafaxine

Psychiatric and physical conditions often coexist, and there is robust evidence that associates the frequency of depression with single and multiple physical conditions. More than half of patients with depression may have at least one chronic physical condition. Therefore, antidepressants are often used in cotherapy with other medications for the management of both psychiatric and chronic physical illnesses. The risk of drug–drug interactions (DDIs) is augmented by complex polypharmacy regimens and extended periods of treatment required, of which possible outcomes range from tolerability issues to lack of efficacy and serious adverse events. Optimal patient outcomes may be achieved through drug selection with minimal potential for DDIs. Desvenlafaxine is a serotonin–norepinephrine reuptake inhibitor approved for the treatment of adults with major depressive disorder. Pharmacokinetic studies of desvenlafaxine have shown a simple metabolic profile unique among antidepressants. This review examines the DDI profiles of antidepressants, particularly desvenlafaxine, in relation to drugs of different therapeutic areas. The summary and comparison of information available is meant to help clinicians in making informed decisions when using desvenlafaxine in patients with depression and comorbid chronic conditions.
Bmc Infectious Diseases

Gene expression profiling of human alveolar macrophages infected by B. anthracis spores demonstrates TNF-α and NF-κb are key components of the innate immune response to the pathogen Abstract Background: Bacillus anthracis, the etiologic agent of anthrax, has recently been used as an agent of bioterrorism. The innate immune system initially appears to contain the pathogen at the site of entry. Because the human alveolar macrophage (HAM) plays a key role in lung innate immune responses, studying the HAM response to B. anthracis is important in understanding the pathogenesis of the pulmonary form of this disease.
Deep Temporal Clustering : Fully Unsupervised Learning of Time-Domain Features

Unsupervised learning of time series data, also known as temporal clustering, is a challenging problem in machine learning. Here we propose a novel algorithm, Deep Temporal Clustering (DTC), to naturally integrate dimensionality reduction and temporal clustering into a single end-to-end learning framework, fully unsupervised. The algorithm utilizes an autoencoder for temporal dimensionality reduction and a novel temporal clustering layer for cluster assignment. Then it jointly optimizes the clustering objective and the dimensionality reduction objec tive. Based on requirement and application, the temporal clustering layer can be customized with any temporal similarity metric. Several similarity metrics and state-of-the-art algorithms are considered and compared. To gain insight into temporal features that the network has learned for its clustering, we apply a visualization method that generates a region of interest heatmap for the time series. The viability of the algorithm is demonstrated using time series data from diverse domains, ranging from earthquakes to spacecraft sensor data. In each case, we show that the proposed algorithm outperforms traditional methods. The superior performance is attributed to the fully integrated temporal dimensionality reduction and clustering criterion.
A new approach for regularization of inverse problems in images processing

Optical flow motion estimation from two images is limited by the aperture problem. A method to deal with this problem is to use regularization techniques. Usually, one adds a regularization term with appriopriate weighting parameter to the optical flow cost funtion. Here, we suggest a new approach to regularization for optical flow motion estimation. In this approach, all the regularization informations are used in the definition of an appropriate norm for the cost function via a trust function to be defined, one does not ever need weighting parameter. A simple derivation of such a trust function from images is proposed and a comparison with usual approaches is presented. These results show the superiority of such approach over usual ones.
Molecular interaction studies of the volumetric behaviour of binary liquid mixtures containing alcohols

An attempt has been made to relate the volumetric effects involved in the binary mixtures of normal and branched alcohols and various components (aromatics, halo and nitroaromatics and haloaliphatics) with the molecular in- teractions of unlike molecules. This review is a condensation of research ac- tivities developed in recent years as results of a better understanding of volu- metric behaviour and a stronger insight into the complex structure of those mixtures. The influence of important contributions of a physical, chemical and geometrical nature that change excess molar volume, V E (positive, sigmoidal, negative) is considered and explained in detail. It appears that the balance between these contributions is quite sensitive to the behaviour of the alcohol molecules in contact with the chosen compounds.