Miracle-dz/UniFAR-FTUs huggingface dataset:
Intermittent and rhythmic exposure to melatonin in primary cultured adipocytes enhances the insulin and dexamethasone effects on leptin expression

Abstract: Considering the cyclic characteristic of production and secretion of pineal melatonin, it is reasonable to assume that this oscillation might be important in determining the variety of its circadian and seasonal effects. To simulate this physiological condition in vitro, isolated adipocytes were exposed to melatonin in a circadian‐like pattern by adding the hormone to the incubating medium during 12 hr (mimicking the night), followed by an equal period without melatonin (mimicking the day). This intermittent procedure was interrupted when three cycles with melatonin were fulfilled (60‐hr incubation). Here, we report the effects of melatonin (1 nM) added intermittently or continuously to the incubating medium alone or in combination with insulin (5 nM) and/or dexamethasone (7 nM) on leptin release and expression by rat adipocytes. After acute 12‐hr incubation neither melatonin nor insulin alone affected leptin expression, but together they increased it by 105%. Dexamethasone increased leptin mRNA content and release (70%) but this effect was not enhanced by melatonin. Nevertheless, after 60 hr under intermittent melatonin, we observed a synergism between melatonin and dexamethasone. This interaction promoted an increment (75% compared with dexamethasone alone) in leptin release and expression. Our results suggest that circadian‐like exposure to melatonin potentiates the dexamethasone action and is important to the effects promoted by insulin on leptin expression. Based on an in vitro approach, this work helps to clarify the physiological relevance and the repercussions of the in vivo circadian pattern of melatonin secretion.
High Air Humidity Causes Atmospheric Water Absorption via Assimilating Branches in the Deep-Rooted Tree Haloxylon ammodendron in an Arid Desert Region of Northwest China

Atmospheric water is one of the main water resources for plants in arid ecosystems. However, whether deep-rooted, tomentum-less desert trees can absorb atmospheric water via aerial organs and transport the water into their bodies remains poorly understood. In the present study, a woody, deep-rooted, tomentum-less plant, Haloxylon ammodendron (C.A. Mey.) Bunge, was selected as the experimental object to investigate the preconditions for and consequences of foliar water uptake. Plant water status, gas exchange, and 18O isotopic signatures of the plant were investigated following a typical rainfall pulse and a high-humidity exposure experiment. The results showed that a high content of atmospheric water was the prerequisite for foliar water uptake by H. ammodendron in the arid desert region. After atmospheric water was absorbed via the assimilating branches, which perform the function of leaves due to leaf degeneration, the plant transported the water to the secondary branches and trunk stems, but not to the taproot xylem or the soil, based on the 18O isotopic signatures of the specimen. Foliar water uptake altered the plant water status and gas exchange-related traits, i.e., water potential, stomatal conductance, transpiration rate, and instantaneous water use efficiency. Our results suggest that atmospheric water might be a subsidiary water resource for sustaining the survival and growth of deep-rooted plants in arid desert regions. These findings contribute to the knowledge of plant water physiology and restoration of desert plants in the arid regions of the planet.
Measuring Change Over Time: A Systematic Review of Evaluative Measures of Cognitive Functioning in Traumatic Brain Injury

Objectives: The purpose of evaluative instruments is to measure the magnitude of change in a construct of interest over time. The measurement properties of these instruments, as they relate to the instrument's ability to fulfill its purpose, determine the degree of certainty with which the results yielded can be viewed. This work systematically reviews all instruments that have been used to evaluate cognitive functioning in persons with traumatic brain injury (TBI), and critically assesses their evaluative measurement properties: construct validity, test-retest reliability, and responsiveness. Data Sources: MEDLINE, Central, EMBASE, Scopus, PsycINFO were searched from inception to December 2016 to identify longitudinal studies focused on cognitive evaluation of persons with TBI, from which instruments used for measuring cognitive functioning were abstracted. MEDLINE, instrument manuals, and citations of articles identified in the primary search were then screened for studies on measurement properties of instruments utilized at least twice within the longitudinal studies. Study Selection: All English-language, peer-reviewed studies of longitudinal design that measured cognition in adults with a TBI diagnosis over any period of time, identified in the primary search, were used to identify instruments. A secondary search was carried out to identify all studies that assessed the evaluative measurement properties of the instruments abstracted in the primary search. Data Extraction: Data on psychometric properties, cognitive domains covered and clinical utility were extracted for all instruments. Results: In total, 38 longitudinal studies from the primary search, utilizing 15 instruments, met inclusion and quality criteria. Following review of studies identified in the secondary search, it was determined that none of the instruments utilized had been assessed for all the relevant measurement properties in the TBI population. The most frequently assessed property was construct validity. Conclusions: There is insufficient evidence for the validity and reliability of instruments measuring cognitive functioning, longitudinally, in persons with TBI. Several instruments with well-defined construct validity in TBI samples warrant further assessment for test-retest reliability and responsiveness. Registration Number: www.crd. york.ac. uk/PROSPERO/, identifier CRD42017055309.
A Comparative Analysis of Deep Learning Approaches for Network Intrusion Detection Systems (N-IDSs): Deep Learning for N-IDSs

Recently, due to the advance and impressive results of deep learning techniques in the fields of image recognition, natural language processing and speech recognition for various long-standing artificial intelligence (AI) tasks, there has been a great interest in applying towards security tasks too. This article focuses on applying these deep taxonomy techniques to network intrusion detection system (N-IDS) with the aim to enhance the performance in classifying the network connections as either good or bad. To substantiate this to NIDS, this article models network traffic as a time series data, specifically transmission control protocol / internet protocol (TCP/IP) packets in a predefined time-window with a supervised deep learning methods such as recurrent neural network (RNN), identity matrix of initialized values typically termed as identity recurrent neural network (IRNN), long short-term memory (LSTM), clock-work RNN (CWRNN) and gated recurrent unit (GRU), utilizing connection records of KDDCup-99 challenge data set. The main interest is given to evaluate the performance of RNN over newly introduced method such as LSTM and IRNN to alleviate the vanishing and exploding gradient problem in memorizing the long-term dependencies. The efficient network architecture for all deep models is chosen based on comparing the performance of various network topologies and network parameters. The experiments of such chosen efficient configurations of deep models were run up to 1,000 epochs by varying learning-rates between 0.01-05. The observed results of IRNN are relatively close to the performance of LSTM on KDDCup-99 NIDS data set. In addition to KDDCup-99, the effectiveness of deep model architectures are evaluated on refined version of KDDCup-99: NSL-KDD and most recent one, UNSW-NB15 NIDS datasets.
Dipeptidyl Peptidase-4 Inhibitors for the Potential Treatment of Brain Disorders; A Mini-Review With Special Focus on Linagliptin and Stroke

Cerebral stroke is a leading cause of death and persistent disability of elderly in the world. Although stroke prevention by targeting several risk factors such as diabetes and hypertension has decreased the stroke incidence, the total number of strokes is increasing due to the population aging and new preventive therapies are needed. Moreover, post-stroke acute pharmacological strategies aimed to reduce stroke-induced brain injury have failed in clinical trials despite being effective in animal models. Finally, approximately 30% of surviving stroke patients do not recover from stroke and remain permanently dependent on supportive care in activities of daily living. Therefore, strategies to improve stroke recovery in the post-acute phase are highly needed. Linagliptin is a dipeptidyl peptidase-4 inhibitor which is clinically approved to reduce hyperglycemia in type 2 diabetes. The regulation of glycemia by dipeptidyl peptidase-4 inhibition is mainly achieved by preventing endogenous glucagon-like peptide-1 (GLP-1) degradation. Interestingly, linagliptin has also shown glycaemia-independent beneficial effects in animal models of stroke, Parkinson's disease and Alzheimer's disease. In some case the preclinical data have been supported with some clinical data. Although potentially very interesting for the development of new strategies against stroke and neurodegenerative disorders, the mode of action of linagliptin in the brain is still largely unknown and seems to occur in a GLP-1R-independent manner. The purpose of this mini-review is to summarize and discuss the recent experimental and clinical work regarding the effects of linagliptin in the central nervous system, with special emphasis on acute neuroprotection, stroke prevention and post-stroke recovery. We also highlight the main questions in this research field that need to be addressed in clinical perspective.
Benjamin–Ono soliton dynamics in a slowly varying potential

The Benjamin Ono equation with a slowly varying potential is with , , and , and H denotes the Hilbert transform. The soliton profile is Qa,c(x) = cQ(c(x − a)), where and , c > 0 are parameters. For initial condition u0(x) to (pBO) close in to Q0,1(x), we show that the solution to (pBO) remains close in to Qa(t),c(t)(x) and specify the parameter dynamics on an O(h−1) time scale.
Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories

Data-driven approaches to scientific research have generated new types of repositories that provide scientists the means necessary to store, share and re-use big data-sets generated at various stages of the research process. As the number and heterogeneity of research data repositories increase, it becomes critical for scientists to solve data quality problems associated to the data-sets stored in these repositories. To date, several authors have been focused on the data quality issues associated to the data-sets stored in the repositories, yet there is little knowledge about the quality problems of the metadata used to describe these data-sets. Metadata is important for the long-term sustainability of research data repositories and data re-use. The aim of the research reported in this paper was to identify the data quality problems associated with the metadata used in the Dryad data repository. The paper concludes with some recommendations for improving the quality of metadata in research data repositories.
Chiral superconductivity in the alternate stacking compound 4Hb-TaS2

Chiral superconductivity in 4Hb-TaS2 was discovered using muon spin rotation. Van der Waals materials offer unprecedented control of electronic properties via stacking of different types of two-dimensional materials. A fascinating frontier, largely unexplored, is the stacking of strongly correlated phases of matter. We study 4Hb-TaS2, which naturally realizes an alternating stacking of 1T-TaS2 and 1H-TaS2 structures. The former is a well-known Mott insulator, which has recently been proposed to host a gapless spin-liquid ground state. The latter is a superconductor known to also host a competing charge density wave state. This raises the question of how these two components affect each other when stacked together. We find a superconductor with a Tc of 2.7 Kelvin and anomalous properties, of which the most notable one is a signature of time-reversal symmetry breaking, abruptly appearing at the superconducting transition. This observation is consistent with a chiral superconducting state.
Hiding in Plain Sight: A Longitudinal Study of Combosquatting Abuse

Domain squatting is a common adversarial practice where attackers register domain names that are purposefully similar to popular domains. In this work, we study a specific type of domain squatting called "combosquatting," in which attackers register domains that combine a popular trademark with one or more phrases (e.g., betterfacebook[.]com, youtube-live[.]com). We perform the first large-scale, empirical study of combosquatting by analyzing more than 468 billion DNS records - collected from passive and active DNS data sources over almost six years. We find that almost 60% of abusive combosquatting domains live for more than 1,000 days, and even worse, we observe increased activity associated with combosquatting year over year. Moreover, we show that combosquatting is used to perform a spectrum of different types of abuse including phishing, social engineering, affiliate abuse, trademark abuse, and even advanced persistent threats. Our results suggest that combosquatting is a real problem that requires increased scrutiny by the security community.
Iconic Interfaces For Kids on the Internet

Use of the Internet, in particular searching the Internet, is becoming an essential part of school education at all levels. In particular, in the UK it is part of the National Curriculum, which must be taught to all children at state schools. However, for the youngest children text-based searches are difficult or impossible to use as the children are only starting to read and write fluently. For such children visual and iconic interfaces are essential. However, the metaphors and icons that are appropriate for adults are not necessarily easy for children to recognise and understand. This paper describes some of the issues that arose during the design of an iconic search tool aimed at children aged 5—6.
Sources of Pathogenic Nucleic Acids in Systemic Lupus Erythematosus

A hallmark of systemic lupus erythematosus (SLE), and several related autoimmune diseases, is the presence of autoantibodies against nucleic acids and nucleic acid-binding proteins, as well as elevated type I interferons (IFNs), which appear to be instrumental in disease pathogenesis. Here we discuss the sources and proposed mechanisms by which a range of cellular RNA and DNA species can become pathogenic and trigger the nucleic acid sensors that drive type I interferon production. Potentially SLE-promoting DNA may originate from pieces of chromatin, from mitochondria, or from reverse-transcribed cellular RNA, while pathogenic RNA may arise from mis-localized, mis-processed, ancient retroviral, or transposable element-derived transcripts. These nucleic acids may leak out from dying cells to be internalized and reacted to by immune cells or they may be generated and remain to be sensed intracellularly in immune or non-immune cells. The presence of aberrant DNA or RNA is normally counteracted by effective counter-mechanisms, the loss of which result in a serious type I IFN-driven disease called Aicardi-Goutières Syndrome. However, in SLE it remains unclear which mechanisms are most critical in precipitating disease: aberrant RNA or DNA, overly sensitive sensor mechanisms, or faulty counter-acting defenses. We propose that the clinical heterogeneity of SLE may be reflected, in part, by heterogeneity in which pathogenic nucleic acid molecules are present and which sensors and pathways they trigger in individual patients. Elucidation of these events may result in the recognition of distinct “endotypes” of SLE, each with its distinct therapeutic choices.
Parallel optimized pearson correlation condition (PO-PCC) for robust cosmetic makeup facial recognition

Makeup changes or the application of cosmetics constitute one of the challenges for the improvement of the recognition precision of human faces because makeup has a direct impact on facial features, such as shape, tone, and texture. Thus, this research investigates the possibility of integrating a statistical model using Pearson Correlation (PC) to enhance the facial recognition accuracy. PC is generally used to determine the relationship between the training and testing images while leveraging the key advantage of fast computing. Considering the relationship of factors other than the features, i.e., changes in shape, size, color, or appearance, leads to a robustness of the cosmetic images. To further improve the accuracy and reduce the complexity of the approach, a technique using channel selection and the Optimum Index Factor (OIF), including Histogram Equalization (HE), is also considered. In addition, to enable real-time (online) applications, this research applies parallelism to reduce the computational time in the pre-processing and feature extraction stages, especially for parallel matrix manipulation, without affecting the recognition rate. The performance improvement is confirmed by extensive evaluations using three cosmetic datasets compared to classic facial recognitions, namely, principal component analysis and local binary pattern (by factors of 6.98 and 1.4, respectively), including their parallel enhancements (i.e., by factors of 31,194.02 and 1577.88, respectively) while maintaining high recognition precision.
Intraspecific Root Trait Variability Along Environmental Gradients Affects Salt Marsh Resistance to Lateral Erosion

Recent studies in salt marshes have demonstrated the role of plant roots in sediment stabilisation, and hence the importance of marshes in providing coastal protection. However, the relative role of root traits and environmental factors in controlling sediment stability, and how intraspecific variability of root traits vary within and among marshes, remain poorly understood. In this study, we investigated which root trait(s) drive sediment stability (resistance to lateral erosion) in two marsh species with an important role in coastal protection (Spartina anglica and Atriplex portulacoides) and how the environment affects the expression of these traits. We sampled three marshes along salinity gradients in each of two estuaries in Wales (UK), establishing replicate plots in the respective dominant zones of each species. In all plots we sampled abiotic variables (sand, redox potential, pH, salinity) and root traits (root density, specific root density, root volume, root length density); in a subset of these plots (three per species in each marsh/species/marsh) we extracted soil-plant cores and assessed their erosion resistance in a flume. Sediment stability was enhanced by increases in root density and reductions in sand content. Abiotic variables affected root density in different ways depending on species: in S. anglica, redox was the only significant factor, with a positive, linear effect on root density; in A. portulacoides, redox had a non-linear (U-shaped) effect on root density, while sand had a negative effect. Collectively, these results show that i) intraspecific variability in root density can influence sediment stability in salt marshes, and ii) sediment properties not only influence sediment stability directly, but also indirectly via root density. These results shed light on spatial variability in the stability of salt marshes to lateral erosion and suggest that root density should be incorporated into coastal vegetation monitoring programs as an easy-to-measure root trait that links the environment to sediment stability and hence to the function and services provided by marshes.
Thermal Components in Gamma-Ray Bursts. I. How Do They Affect Nonthermal Spectral Parameters?

The spectral components of the prompt emission of gamma-ray bursts (GRBs) mainly consist of two possible origins: synchrotron (nonthermal) and photosphere (thermal). The typical spectral properties of GRBs can be modeled by a dominant nonthermal component (a Band-like function or cutoff power law), while some of them have an additional thermal component (a Planck-like function). In this paper, we investigate the effects of thermal components on the nonthermal spectral parameters. We focus on eight Fermi Gamma-ray Burst Monitor bursts of which the spectra deviate from a Band-only function, and the thermal components are significant. We sort them into thermal-subdominant Group I (e.g., GRB 110721A) and thermal-dominant Group II (e.g., GRB 090902B). Several interesting results are found assuming the spectral component is totally attributed to the nonthermal component: (i) the low-energy photon index α becomes harder; (ii) the peak energy Ec is significantly smaller and lies between the peak temperature of blackbody component and the peak energy of the cutoff power law + blackbody (CPL+BB) model; (iii) total flux F is generally the same; (iv) the changes (Δα and ΔEc) are positively correlated with the ratio between the thermal flux and total flux; and (v) parameter relations (F–α, F–Ec, and Ec–α) also changed prominently. The GRBs in both groups show the same results. Our analysis indicates that the thermal component is important, and it significantly affects the spectral parameters and the consequential physical interpretations.
Transport timescales and tracer properties in the extratropical UTLS

Abstract. A comprehensive evaluation of seasonal backward trajectories initialized in the northern hemisphere lowermost stratosphere (LMS) has been performed to investigate the factors that determine the temporal and spatial structure of troposphere-to-stratosphere-transport (TST) and it's impact on the LMS. In particular we explain the fundamental role of the transit time since last TST (tTST) for the chemical composition of the LMS. According to our results the structure of the LMS can be characterized by a layer with tTST Carbon monoxide (CO) mirrors this structure of tTST due to it's finite lifetime on the order of three months. Water vapour isopleths, on the other hand, do not uniquely indicate TST and are independent of tTST, but are determined by the Lagrangian Cold Point (LCP) of air parcels. Most of the backward trajectories from the LMS experienced their LCP in the tropics and sub-tropics, and TST often occurs 20 days after trajectories have encountered their LCP. Therefore, ExTL properties deduced from CO and H2O provide totally different informations on transport and particular TST for the LMS.