Miracle-dz/UniFAR-FTUs huggingface dataset:
A retrospective cohort study of perioperative prognostic factors associated with intra-abdominal sepsis

Context: Intra-abdominal sepsis following laparotomy for acute abdomen remains still a challenging condition. The understanding of various perioperative risk factors by anesthesiologists are crucial in optimum management these patients. Aims: The objective of this study is to assess the perioperative risk factors, which predicts the outcome of treatment. Settings and Design: This retrospective observational study of 603 patients who underwent Laparotomies between March 2012 and March 2015 at our University Medical College. Of 603 patients, 52 consecutive patients with intra-abdomen sepsis who underwent surgical procedures and admitted in Intensive Care Unit (ICU) were selected and analyzed for prognostic risk factors in relation to severity of the disease. Subjects and Methods: 52 consecutive patients who developed intra-abdominal sepsis following laparotomy was allocated one of two groups; Group Sepsis, patients with peritonitis without systemic hypotension (mean arterial pressure [MAP] >60 mm of Hg); and Group septic shock, patients with peritonitis with systemic hypotension (mean arterial pressure [MAP] <60 mm of Hg) and patients were analyzed for prognostic risk factors Statistical Analysis Used: Categorical variables were analyzed by using Fisher's exact (two-tail) test and continuous variable were analyzed by using Mann–Whitney (two-tail) U-test. Results: Out of 603 patients who underwent laparotomy 52 patients developed an intra-abdominal septic complication. Of these 52 cases studied 28 patients developed septic shock and required a longer duration of admission in ICU and more inotropic support. Preoperative albumin and hematocrit level were significantly low in septic shock patients as compared to the patients with sepsis without systemic hypotension. PaCO2: FiO2was also significantly low in these patients. Conclusions: Preoperative low hematocrit, low albumin level, and delay in laparotomy more than 72 h were also associated with adverse outcome in the patients with intra-abdominal sepsis. Clinicians should maintain equipoise on this topic pending prospective randomized clinical trials.
Interpretable Neural Predictions with Differentiable Binary Variables

The success of neural networks comes hand in hand with a desire for more interpretability. We focus on text classifiers and make them more interpretable by having them provide a justification–a rationale–for their predictions. We approach this problem by jointly training two neural network models: a latent model that selects a rationale (i.e. a short and informative part of the input text), and a classifier that learns from the words in the rationale alone. Previous work proposed to assign binary latent masks to input positions and to promote short selections via sparsity-inducing penalties such as L0 regularisation. We propose a latent model that mixes discrete and continuous behaviour allowing at the same time for binary selections and gradient-based training without REINFORCE. In our formulation, we can tractably compute the expected value of penalties such as L0, which allows us to directly optimise the model towards a pre-specified text selection rate. We show that our approach is competitive with previous work on rationale extraction, and explore further uses in attention mechanisms.
An open‐source system for vision‐based micro‐aerial vehicle mapping, planning, and flight in cluttered environments

We present an open‐source system for Micro‐Aerial Vehicle (MAV) autonomous navigation from vision‐based sensing. Our system focuses on dense mapping, safe local planning, and global trajectory generation, especially when using narrow field‐of‐view sensors in very cluttered environments. In addition, details about other necessary parts of the system and special considerations for applications in real‐world scenarios are presented. We focus our experiments on evaluating global planning, path smoothing, and local planning methods on real maps made on MAVs in realistic search‐and‐rescue and industrial inspection scenarios. We also perform thousands of simulations in cluttered synthetic environments, and finally validate the complete system in real‐world experiments.
Optimization of electrospinning parameters for polyacrylonitrile-MgO nanofibers applied in air filtration

ABSTRACT The present study aimed to optimize the electrospinning parameters for polyacrylonitrile (PAN) nanofibers containing MgO nanoparticle to obtain the appropriate fiber diameter and mat porosity to be applied in air filtration. Optimization of applied voltage, solution concentration, and spinning distance was performed using response surface methodology. In total, 15 trials were done according to the prepared study design. Fiber diameter and porosity were measured using scanning electron microscopic (SEM) image analysis. For air filtration testing, the nanofiber mat was produced based on the suggested optimum conditions for electrospinning. According to the results, the lower solution concentration favored the thinner fiber. The larger diameter gave a higher porosity. At a given spinning distance, there was a negative correlation between fiber diameter and applied voltage. Moreover, there were curvilinear relationships between porosity and both spinning distance and applied voltage at any concentration. It was also concluded that the developed filter medium could be comparable to the high-efficiency particulate air (HEPA) filter in terms of collection efficiency and pressure drop. The empirical models presented in this study can provide an orientation to the subsequent experiments to form uniform and continuous nanoﬁbers for future application in air purification. Implications: High-efficiency filtration is becoming more important, due to decreasing trends air quality. Effective filter media are increasingly needed in industries applying clean-air technologies, and the necessity for developing the high-performance air filters has been more and more felt. Nanofibrous filter media that are mostly fabricated via electrospinning technique have attracted considerable attention in the last decade. The present study aimed to develop the electrospun PAN-containing MgO nanoparticle (using the special functionalities such as absorption and adsorption characteristics, antibacterial functionality, and as a pore-forming agent) filter medium through experimental investigations for application in high-performance air filters.
MiR-424 is over-expressed and attenuates ischemia-reperfusion kidney injury via p53 and death receptor 6 pathway.

BACKGROUND Ischemic reperfusion injury of kidney is major cause for renal failure, however the involved pathogenesis remains unclear creating an void for its effective treatment. Here we studied involvement of microRNA-424 in renal injury. METHODS For the study, p53 or HIF-1α mice were used, ischemic renal injury was induced using clamping of renal pedicles bilateraly. Proximal kidney tubular cells were used for in vitro studies. Hoechst 33342 analysis was done for apoptosis. Blood urea nitrogen (BUN) and serum creatinine was done for renal function, Hematoxylin-eosin tissue damage and Terminal transferase-dUTP nick-end labeling assay for apoptosis. RT-PCR was done for miRNA and ChIP assay to identify the binding of p53 to miR-424. TargetScan and miRanda data base were scanned to find targets of miR-424. Protein expression was done by western blot analysis. RESULTS We discovered that, miR-424 was over-expressed in ischemic renal injury mice and in hypoxia exposed renal cells. In cells, miR-424 suppressed the expression levels of death receptor 6 (DR6) and halted the apoptosis mediated by hypoxia. Blocking of miR-424 halted the inhibition of DR6 and caused apoptosis and activation of caspase. In mice, miR-424 mimic inhibited expression of DR6 and attenuated ischemic renal injury. We established that, up-regulation of miR-424 in ischemic reperfusion injury was p53 dependent, also inhibition of p53 caused repression of miR-424 levels in hypoxia induced cells in vitro. The p53 knockout mice showed attenuation in levels of miR-424 confirming role of p53 behind up-regulation of miR-424 in vivo. CONCLUSION The study confirmed p53/miR-424/DR6 as a protective cascade during ischemic-reperfusion injury.
Statistical limit laws for hyperbolic groups

Using techniques from ergodic theory and symbolic dynamics, we derive statistical limit laws for real valued functions on hyperbolic groups. In particular, our results apply to convex cocompact group actions on $\text{CAT}(-1)$ spaces, and provide a precise statistical comparison between word length and displacement. After generalising our methods to the multidimensional setting, we prove that the abelianisation map satisfies a non-degenerate multidimensional central limit theorem. We also obtain local limit theorems for group homomorphisms.
A 4 Gb/s 3-bit Parallel Transmitter With the Crosstalk-Induced Jitter Compensation Using TX Data Timing Control

By using the data timing control at the transmitter (TX), the crosstalk-induced jitter (CIJ) is compensated for in the 3-bit parallel data transmission through the coupled microstrip lines on printed circuit board (PCB). The difference in propagation velocity with the signal modes (odd, static, even) is compensated for by sending data earlier or later at TX according to the signal modes, so that the signals of different modes arrive at receiver at the same time. The proposed TX was implemented by using a 0.18 mum CMOS process. The measurement shows that the proposed TX reduces the RX jitters by about 30 ps (more than 50% of the added jitter due to CIJ and ISI) at the data rates from 2.6 Gb/s to 4.0 Gb/s. The proposed scheme can be applied to more than three parallel microstrip lines.
Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance

We present Zeno, a technique to make distributed machine learning, particularly Stochastic Gradient Descent (SGD), tolerant to an arbitrary number of faulty workers. Zeno generalizes previous results that assumed a majority of non-faulty nodes; we need assume only one non-faulty worker. Our key idea is to suspect workers that are potentially defective. Since this is likely to lead to false positives, we use a ranking-based preference mechanism. We prove the convergence of SGD for non-convex problems under these scenarios. Experimental results show that Zeno outperforms existing approaches.
A survey of molecular cores in M 17 SWex

A survey of molecular cores covering the infrared dark cloud known as the M 17 southwest extension (M 17 SWex) has been carried out with the 45 m Nobeyama Radio Telescope. Based on the N2H+ (J = 1–0) data obtained, we have identified 46 individual cores whose masses are in the range from 43 to $3026\, {M}_{\odot }$. We examined the relationship between the physical parameters of the cores and those of young stellar objects (YSOs) associated with the cores found in the literature. The comparison of the virial mass and the core mass indicates that most of the cores can be gravitationally stable if we assume a large external pressure. Among the 46 cores, we found four massive cores with YSOs. They have large masses of $\gtrsim 1000\, M_{\odot }$ and line widths of $\gtrsim 2.5\:$km s−1 which are similar to those of clumps forming high-mass stars. However, previous studies have shown that there is no active massive star formation in this region. Recent measurements of near-infrared polarization imply that the magnetic field around M 17 SWex is likely to be strong enough to support the cores against self-gravity. We therefore suggest that the magnetic field may prevent the cores from collapsing, causing the low level of massive star formation in M 17 SWex.
The Mass–Activity Relationships in M and K Dwarfs. I. Stellar Parameters of Our Sample of M and K Dwarfs

Empirical correlations between stellar parameters such as rotation or radius and magnetic activity diagnostics require estimates of the effective temperatures and the stellar radii. The aim of this study is to propose simple methods that can be applied to large samples of stars in order to derive estimates of the stellar parameters. Good empirical correlations between red/infrared colors (e.g., (R – I)C) and effective temperatures have been well established for a long time. The more recent (R – I)C color–Teff correlation using the data of Mann et al. (hereafter M15) and Boyajian et al. (hereafter B12) shows that this color can be applied as a temperature estimate for large samples of stars. We find that the mean scatter in Teff relative to the (R – I)C–Teff relationship of B12 and M15 data is only ±3σ = 44.6 K for K dwarfs and ±3σ = 39.4 K for M dwarfs. These figures are small and show that the (R – I)C color can be used as a first-guess effective temperature estimator for K and M dwarfs. We derive effective temperatures for about 1910 K and M dwarfs using the calibration of (R – I)C color–Teff from B12 and M15 data. We also compiled Teff and metallicity measurements available in the literature using the VizieR database. We determine Teff for 441 stars with previously unknown effective temperatures. We also identified 21 new spectroscopic binaries and one triple system from our high-resolution spectra.
Design of digital robust controller for PWM power amplifier and bumpless mode switching

In this paper a multi-stage switching type digital controller is proposed for spreading capacitance load range more and improving transient characteristics for inductance load. In the previous proposed controller, the configuration of the controller is the same to all loads. At inductive load, there is a possibility that the transient characteristics may become bad and the specification may not be satisfied. Therefore, a load current is estimated at inductive load, and the controller which also uses load current for feedback is configured. A inductance is estimated and a controller is switched to this controller bumplessly. In order to extend the range of capacitance load, a controller is increased from two stage to three stage, and these are switched to each other bumplessly. A DSP is implemented to this digital controller. It is demonstrated from experiments that the multi-stage switching type digital controller is realizable and the given specifications are satisfied.
Randomized Study of the Effect of Vitamin D and Omega-3 Fatty Acids Cosupplementation as Adjuvant Chemotherapy on Inflammation and Nutritional Status in Colorectal Cancer Patients

Abstract This study aimed to evaluate the effects of vitamin D3 and omega-3 fatty acids cosupplementation on inflammation and nutritional status in colorectal cancer patients. In this clinical trial, 81 colorectal cancer patients were randomly assigned into four groups: (1) control group: receiving a vitamin D3 placebo weekly + omega-3 fatty acid placebo capsules daily; (2) omega-3 fatty acid group: receiving 2 omega-3 fatty acid capsules (each capsule containing 330 mg of omega-3 fatty acids) daily + a vitamin D3 placebo weekly; (3) vitamin D group: receiving a 50,000 IU vitamin D3 soft gel weekly + 2 omega-3 fatty acid placebo capsules daily; (4) cosupplementation group: receiving a 50,000 IU vitamin D3 soft gel weekly + 2 omega-3 fatty acids capsules daily for 8 weeks. Before and after the intervention, height, weight, fat-free mass (FFM), serum levels of 25(OH)D, tumor necrosis factor alpha (TNF-α), and interleukin 6 (IL-6), C-reactive protein (CRP), and albumin, were measured. After 8 weeks of intervention, patients who received combined vitamin D3 and omega-3 fatty acids supplements compared with omega-3, vitamin D3, and placebo groups had significantly decreased CRP and TNF-α. In addition, serum level of IL-6 was decreased significantly in omega-3, vitamin D3, and cosupplementation groups compared with baseline. Regarding nutritional status, weight, BMI, and FFM% were increased significantly in vitamin D3, omega-3, and cosupplementation groups at the end of the intervention. Vitamin D3 plus omega-3 fatty acids cosupplementation in colorectal cancer patients has beneficial impacts on inflammation and nutritional status.
Obesity is associated with activated and insulin resistant immune cells

Obesity and type 2 diabetes mellitus are characterized by insulin resistance and ‘low‐grade inflammation’; however, the pathophysiological link is poorly understood. To determine the relative contribution of obesity and insulin resistance to systemic ‘inflammation’, this study comprehensively characterized circulating immune cells in different grades of obesity.
SAWNet: A Spatially Aware Deep Neural Network for 3D Point Cloud Processing

Deep neural networks have established themselves as the state-of-the-art methodology in almost all computer vision tasks to date. But their application to processing data lying on non-Euclidean domains is still a very active area of research. One such area is the analysis of point cloud data which poses a challenge due to its lack of order. Many recent techniques have been proposed, spearheaded by the PointNet architecture. These techniques use either global or local information from the point clouds to extract a latent representation for the points, which is then used for the task at hand (classification/segmentation). In our work, we introduce a neural network layer that combines both global and local information to produce better embeddings of these points. We enhance our architecture with residual connections, to pass information between the layers, which also makes the network easier to train. We achieve state-of-the-art results on the ModelNet40 dataset with our architecture, and our results are also highly competitive with the state-of-the-art on the ShapeNet part segmentation dataset and the indoor scene segmentation dataset. We plan to open source our pre-trained models on github to encourage the research community to test our networks on their data, or simply use them for benchmarking purposes.
X-ray spectra of the Fe-L complex

The Hitomi results for the Perseus cluster have shown that accurate atomic models are essential to the success of X-ray spectroscopic missions and just as important as the store of knowledge on instrumental calibration and astrophysical modeling. Preparing the models requires a multifaceted approach, including theoretical calculations, laboratory measurements, and calibration using real observations. In a previous paper, we presented a calculation of the electron impact cross sections on the transitions forming the Fe-L complex. In the present work, we systematically tested the calculation against cross-sections of ions measured in an electron beam ion trap experiment. A two-dimensional analysis in the electron beam energies and X-ray photon energies was utilized to disentangle radiative channels following dielectronic recombination, direct electron-impact excitation, and resonant excitation processes in the experimental data. The data calibrated through laboratory measurements were further fed into a global modeling of the Chandra grating spectrum of Capella. We investigated and compared the fit quality, as well as the sensitivity of the derived physical parameters to the underlying atomic data and the astrophysical plasma modeling. We further list the potential areas of disagreement between the observations and the present calculations, which, in turn, calls for renewed efforts with regard to theoretical calculations and targeted laboratory measurements.
Kin interactions and changing social structure during a population outbreak of feral house mice

Populations of feral house mice (Mus domesticus L.) in Australia undergo multiannual fluctuations in density, and these outbreaks may be partly driven by some change in behavioural self‐regulation. In other vertebrate populations with multiannual fluctuations, changes in kin structure have been proposed as a causal mechanism for changes in spacing behaviour, which consequently result in density fluctuations. We tested the predictions of two alternative conceptual models based on kin selection in a population of house mice during such an outbreak. Both published models ( Charnov & Finerty 1980 ; Lambin & Krebs 1991 ) propose that the level of relatedness between interacting individuals affects their behavioural response and that this changes with population density, though the nature of this relationship differs between the two models. Neither of the models was consistent with all observed changes in relatedness between interacting female mice; however, our results suggested that changes in kin structure still have potential for explaining why mouse outbreaks begin. Therefore, we have developed a variant of one of these conceptual models suggesting that the maintenance of female kin groups through the preceding winter significantly improves recruitment during the subsequent breeding season, and is therefore necessary for mouse outbreaks. We provide six testable predictions to falsify this hypothesis.
Exercise-based treatments for substance use disorders: evidence, theory, and practicality

Abstract Background: Epidemiological studies reveal that individuals who report risky substance use are generally less likely to meet physical activity guidelines (with the exception of certain population segments, such as adolescents and athletes). A growing body of evidence suggests that individuals with substance use disorders (SUDs) are interested in exercising and that they may derive benefits from regular exercise, in terms of both general health/fitness and SUD recovery. Objectives: The aims of this paper were to: (i) summarize the research examining the effects of exercise-based treatments for SUDs; (ii) discuss the theoretical mechanisms and practical reasons for investigating this topic; (iii) identify the outstanding relevant research questions that warrant further inquiry; and (iv) describe potential implications for practice. Methods: The following databases were searched for peer-reviewed original and review papers on the topic of substance use and exercise: PubMed Central, MEDLINE, EMBASE, PsycINFO, and CINAHL Plus. Reference lists of these publications were subsequently searched for any missed but relevant manuscripts. Identified papers were reviewed and summarized by both authors. Results: The limited research conducted suggests that exercise may be an effective adjunctive treatment for SUDs. In contrast to the scarce intervention trials to date, a relative abundance of literature on the theoretical and practical reasons supporting the investigation of this topic has been published. Conclusions: Definitive conclusions are difficult to draw due to diverse study protocols and low adherence to exercise programs, among other problems. Despite the currently limited and inconsistent evidence, numerous theoretical and practical reasons support exercise-based treatments for SUDs, including psychological, behavioral, neurobiological, nearly universal safety profile, and overall positive health effects.