Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of vitamin D deficiency in Korean patients with acute respiratory distress syndrome

Background/Aims Vitamin D modulates innate and adaptive immune responses, and vitamin D deficiency is associated with increased mortality in hospitalized patients with pneumonia. We evaluated the prevalence of vitamin D deficiency in Korean patients with acute respiratory distress syndrome (ARDS) and its effect on the clinical outcomes of ARDS. Methods We retrospectively analyzed the data of 108 patients who had a measured serum level of 25-hydroxy vitamin D3 (25(OH)D3) at the time of diagnosis with ARDS. The clinical outcomes were evaluated based on 25(OH)D3 levels of 20 ng/mL and stratified by quartiles of 25(OH)D3 levels. Results The mean age of patients was 59.4 years old; 77 (71.3%) were male. Vitamin D deficiency was found in 103 patients (95.4%). The mean 25(OH)D3 level was 8.3 ± 7.0 ng/mL. Neither in-hospital mortality (40.0% vs. 68.0%) nor 6-month mortality (40.0% vs. 71.8%) significantly differed between groups. There were no significant differences in 25(OH)D3 level between survivors (8.1 ± 7.6 ng/mL) and non-survivors (8.5 ± 6.8 ng/mL, p = 0.765). There were no trends toward a difference in mortality among quartiles of 25(OH)D3 levels. However, 25(OH)D3 levels were inversely related with length of hospital stay and intensive care unit stay among in-hospital survivors. Conclusions Vitamin D deficiency was prevalent in Korean patients with ARDS. However, levels of vitamin D were not associated with mortality. A large, prospective study is needed to evaluate the effects of vitamin D deficiency on clinical outcomes of ARDS.
Relating Process Models and Event Logs - 21 Conformance Propositions

Process mining sheds new light on the relationship between process models and real-life processes. Process discovery can be used to learn process models from event logs. Conformance checking can be used to confront a descriptive or normative model with the actual behavior observed. Quantifying the relationship between process models and event logs is notoriously difﬁcult. Existing approaches seem to make ad-hoc choices, leading to results that are not easy to interpret. To address these problems, we present 21 conformance propositions . These describe expected or desired properties of conformance measures. These cover notions such as recall (also called ﬁtness), precision , and generalization . These propositions are put into a broader frame of Log-to-Log (L2L), Model-to-Model (M2M), and Log-to-Model (L2M) comparisons. Moreover, it is argued that conformance measures need to consider the likelihood of traces. Real-life event logs are incomplete showing only sample behavior. Moreover, observed traces tend to follow a Pareto distribution. Yet, mainstream process mining approaches stick to a “binary view” on process models (observed traces are ﬁtting or not). This is hindering progress. The goal is to trigger a discussion by clearly formulating the challenges and requirements (rather than proposing new measures or techniques).
Socio-emotional ability, temperament and coping strategies associated with different use of Internet in Internet addiction.

OBJECTIVE The aim of the present study was to compare socio-emotional patterns, temperamental traits, and coping strategies, between a group of Internet addiction (IA) patients and a control group. PATIENTS AND METHODS Twenty-five IA patients and twenty-six healthy matched subjects were tested on IA, temperament, coping strategies, alexithymia and attachment dimensions. Participants reported their prevalent Internet use (online pornography, social networks, online games). RESULTS The IA patients using Internet for gaming online showed a greater attitude to novelty seeking and a lower tendency to use socio-emotional support and self-distraction compared to patients using Internet for social networking. Moreover, they showed a lower level of acceptance than patients using Internet for pornography. In the control group, the participants using Internet for online gaming showed higher levels of IA, emotional impairments and social alienation compared to social-networks and pornography users. CONCLUSIONS Findings showed a higher psychological impairment in gaming online users compared to social networking and online pornography users.
Circadian Rhythms of Urinary Cortisol Levels Vary Between Individuals in Wild Male Chimpanzees: A Reaction Norm Approach

Investigating the repeatability of trait variation between individuals, that is the amount of individual variation in relation to overall phenotypic variation, indicates an upper level of heritability and reveals whether a given trait may be subject to selection. Labile traits are characterized by high levels of flexibility and consequently low trait repeatability is expected. Indeed, research examining glucocorticoid levels in various non-mammal species found low repeatability scores. However, mammals may be different in this respect as (i) differential maternal care early in life has the potential to prime hypothalamic-pituitary-adrenal axis functioning and (ii) allelic variation affecting hypothalamic-pituitary-adrenal axis functioning has been reported. Individuals often differ from each other in average and/or plastic labile trait expression, two aspects that can be described using a reaction norm approach. Both consistent and flexible reaction norm expression has been argued to serve adaptive purposes, depending on the stability and predictability of environmental conditions. Here we investigated both trait and reaction norm repeatability of urinary cortisol levels in wild adult male chimpanzees. To capture the expression of the circadian urinary cortisol rhythm of individual males over time, urine samples were collected throughout the day. In total data of 30 males collected over a period of 8 years were included in the dataset. No male was sampled over the whole 8-year period however. We found minor levels of trait repeatability but considerable reaction norm repeatability. This implies a minor role of genetic or priming factors on cortisol excretion, but reveals that males differ consistently in average urinary cortisol levels and the shape of the circadian urinary cortisol rhythm. Relating these results to fitness parameters will provide answers to questions on the adaptive value of reaction norm repeatability of this labile hormonal trait in the future.
Protein−Protein Interfaces Probed by Methyl Labeling and Proton‐Detected Solid‐State NMR Spectroscopy

Abstract Proton detection and fast magic‐angle spinning have advanced biological solid‐state NMR, allowing for the backbone assignment of complex protein assemblies with high sensitivity and resolution. However, so far no method has been proposed to detect intermolecular interfaces in these assemblies by proton detection. Herein, we introduce a concept based on methyl labeling that allows for the assignment of these moieties and for the study of protein−protein interfaces at atomic resolution.
Actionable Metabolic Pathways in Heart Failure and Cancer—Lessons From Cancer Cell Metabolism

Recent advances in cancer cell metabolism provide unprecedented opportunities for a new understanding of heart metabolism and may offer new approaches for the treatment of heart failure. Key questions driving the cancer field to understand how tumor cells reprogram metabolism and to benefit tumorigenesis are also applicable to the heart. Recent experimental and conceptual advances in cancer cell metabolism provide the cardiovascular field with the unique opportunity to target metabolism. This review compares cancer cell metabolism and cardiac metabolism with an emphasis on strategies of cellular adaptation, and how to exploit metabolic changes for therapeutic benefit.
An Efficient Kernel Transformation Architecture for Binary- and Ternary-Weight Neural Network Inference

While deep convolutional neural networks (CNNs) have emerged as the driving force of a wide range of domains, their computationally and memory intensive natures hinder the further deployment in mobile and embedded applications. Recently, CNNs with low-precision parameters have attracted much research attention. Among them, multiplier-free binary- and ternary-weight CNNs are reported to be of comparable recognition accuracy with full-precision networks, and have been employed to improve the hardware efficiency. However, even with the weights constrained to binary and ternary values, large-scale CNNs still require billions of operations in a single forward propagation pass.In this paper, we introduce a novel approach to maximally eliminate redundancy in binary- and ternary-weight CNN inference, improving both the performance and energy efficiency. The initial kernels are transformed into much fewer and sparser ones, and the output feature maps are rebuilt from the immediate results. Overall, the number of total operations in convolution is reduced. To find an efficient transformation solution for each already trained network, we propose a searching algorithm, which iteratively matches and eliminates the overlap in a set of kernels. We design a specific hardware architecture to optimize the implementation of kernel transformation. Specialized dataflow and scheduling method are proposed. Tested on SVHN, AlexNet, and VGG-16, our architecture removes 43.4%–79.9% operations, and speeds up the inference by 1.48–3.01 times.
Distributed Trade-Based Edge Device Management in Multi-Gateway IoT

The Internet-of-Things (IoT) envisions an infrastructure of ubiquitous networked smart devices offering advanced monitoring and control services. The current art in IoT architectures utilizes gateways to enable application-specific connectivity to IoT devices. In typical configurations, IoT gateways are shared among several IoT edge devices. Given the limited available bandwidth and processing capabilities of an IoT gateway, the service quality (SQ) of connected IoT edge devices must be adjusted over time not only to fulfill the needs of individual IoT device users but also to tolerate the SQ needs of the other IoT edge devices sharing the same gateway. However, having multiple gateways introduces an interdependent problem, the binding, i.e., which IoT device shall connect to which gateway. In this article, we jointly address the binding and allocation problems of IoT edge devices in a multigateway system under the constraints of available bandwidth, processing power, and battery lifetime. We propose a distributed trade-based mechanism in which after an initial setup, gateways negotiate and trade the IoT edge devices to increase the overall SQ. We evaluate the efficiency of the proposed approach with a case study and through extensive experimentation over different IoT system configurations regarding the number and type of the employed IoT edge devices. Experiments show that our solution improves the overall SQ by up to 56% compared to an unsupervised system. Our solution also achieves up to 24.6% improvement on overall SQ compared to the state-of-the-art SQ management scheme, while they both meet the battery lifetime constraints of the IoT devices.
On Secrecy Outage Probability and Average Secrecy Rate of Large-Scale Cellular Networks

We investigate the secrecy performance in large-scale cellular networks, where both Base Stations (BSs) and eavesdroppers follow independent and different homogeneous Poisson point processes (PPPs). Based on the distances between the BS and user, the intended user selects the nearest BS as serving BS to transmit the confidential information. We first derive closed-formed expressions of secrecy outage probability and average secrecy rate of a single-antenna system for both noncooperative and cooperative eavesdroppers scenarios. Then, to further improve the secrecy performance through additional spatial degrees of freedom, the above analyses generalize to the multiantenna scenario, where BSs employ the transmit antenna selection (TAS) scheme. Finally, the results show the small-scale fading has a considerable effect on the secrecy performance in certain density of eavesdroppers and small path loss exponent environment, and when the interference caused by BS is considered, the secrecy performance will be reduced. Moreover, the gap of secrecy performance between noncooperative and cooperative eavesdroppers cases is nearly invariable as the number of antennas increases.
OFTL: Ordering-aware FTL for Maximizing Performance of the Journaling File System

Journaling of ext4 file system employs two FLUSH commands to make their data durable, even though the FLUSH is more expensive than the ordinary write operations. In this paper, to halve the number of FLUSH commands, we propose an efficient FTL, called OFTL, that completely ensures the write order of the journal data blocks in storage-level. For performance comparison, we implemented our OFTL on Jasmine OpenSSD and measured its performance with three different workloads. Our experimental results show that OFTL outperforms the up-to-date FTLs on the existing journaling modes by up to 1.97 times.
Assessing Soft-Tissue Shrinkage Estimates in Museum Specimens Imaged With Diffusible Iodine-Based Contrast-Enhanced Computed Tomography (diceCT)

Abstract The increased accessibility of soft-tissue data through diffusible iodine-based contrast-enhanced computed tomography (diceCT) enables comparative biologists to increase the taxonomic breadth of their studies with museum specimens. However, it is still unclear how soft-tissue measurements from preserved specimens reflect values from freshly collected specimens and whether diceCT preparation may affect these measurements. Here, we document and evaluate the accuracy of diceCT in museum specimens based on the soft-tissue reconstructions of brains and eyes of five bats. Based on proxies, both brains and eyes were roughly 60% of the estimated original sizes when first imaged. However, these structures did not further shrink significantly over a 4-week staining interval, and 1 week in 2.5% iodine-based solution yielded sufficient contrast for differentiating among soft-tissues. Compared to six “fresh” bat specimens imaged shortly after field collection (not fixed in ethanol), the museum specimens had significantly lower relative volumes of the eyes and brains. Variation in field preparation techniques and conditions, and long-term storage in ethanol may be the primary causes of shrinkage in museum specimens rather than diceCT staining methodology. Identifying reliable tissue-specific correction factors to adjust for the shrinkage now documented in museum specimens requires future work with larger samples.
The histidine triad nucleotide‐binding protein 2 (HINT‐2) positively regulates hepatocellular energy metabolism

The histidine triad nucleotide‐binding protein 2 (HINT‐2) is a mitochondrial adenosine phosphor‐amidase expressed in hepatocytes. The phenotype of Hint2 knockout (Hint2−/−) mice includes progressive hepatic steatosis and lysine hyperacetylation of mitochondrial proteins, which are features of respiratory chain malfunctions. We postulated that the absence of HINT‐2 induces a defect in mitochondria bioenergetics. Isolated Hint2−/− hepatocytes produced less ATP and generated a lower mitochondrial membrane potential than did Hint2+/+ hepatocytes. In extracellular flux analyses with glucose, the basal, ATP‐linked, and maximum oxygen consumption rates (OCRs) were decreased in Hint2−/− hepatocytes and in HepG2 cells lacking HINT‐2. Conversely, in HINT‐2 overexpressing SNU‐449 and HepG2 cells, the basal, ATP‐linked, and maximum OCRs were increased. Similarly, with palmitate, basal and maximum OCRs were decreased in Hint2−/− hepatocytes, but they were increased in HINT‐2 overexpressing HepG2 cells. When assayed with radiolabeled substrate, palmitate oxidation was reduced by 25% in Hint2−/− mitochondria. In respirometry assays, complex I‐ and II‐driven, coupled and uncoupled respirations and complex IV KCN‐sensitive respiration were reduced in Hint2−/− mitochondria. Furthermore, HINT‐2 associated with cardiolipin and glucose‐regulated protein 75 kDa. Our study shows decreased electron transfer and oxidative phosphorylation capacity in the absence of HINT‐2. The bioenergetics deficit accumulated over time in hepatocytes lacking HINT‐2 likely leads to the secondary outcome of steatosis. —Rajasekaran, R. , Felser, A. , Nuoffer, J.‐M. , Dufour, J.‐F. , St‐Pierre, M. V. The histidine triad nucleotide‐binding protein 2 (HINT‐2) positively regulates hepatocellular energy metabolism. FASEB J. 32, 5143–5161 (2018). www.fasebj. org
High Speed Kernelized Correlation Filters without Boundary Effect

Recently, correlation filter based trackers (CF trackers) have attracted much attention in vision community because of their top performance in both location and speed. However, the boundary effect imposed by the periodic assumption for the efficient optimization seriously limits their location accuracy. Although there existed many modern works to relax the boundary effect of CF trackers, they all are not able to eliminate the boundary effect thoroughly as well as exploit the kernel trick to improve their location accuracy, and their speeds are reduced greatly. Either relaxing the boundary effect or being able to exploit kernel trick to improve the accuracy, and either relaxing the boundary effect or keeping CF trackers running at high speed have been two dilemmas in the society of visual tracking. To solve these problems, in this paper, we propose a high speed kernel correlation filter without the boundary effect (nBEKCF). Unlike all current CF trackers which exploited real and virtual image patches to train their regression functions, we construct a set of non-orthogonal bases with a group of circulant basic samples and utilize a function defined in Hilbert space and a set of densely sampled, totally real patches to regress a Gaussian goal. This way, the boundary effect is eliminated thoroughly in theory and the kernel trick can be employed naturally. To ensure nBEKCF runs at high speed, we present two efficient algorithms, ACSII and CCIM, to significantly accelerate the evaluation of kernel matrix without employing FFT. By exploiting the circulant structure of basic samples, the efficiency of CCIM in evaluating correlation exceeds that of FFT remarkably. Preliminary experimental results on two public datasets, OTB2013 and OTB2015, show that, without bells and whistles, nBEKCF outperforms representative trackers with hand-crafted features, in the meanwhile, runs at 70 fps on average.
Identification of a novel, dominant dwarfing gene (Ddw4) and its effect on morphological traits of rye

Shortening rye stems to improve lodging resistance is among the major tasks awaiting breeders of this cereal. The most straightforward way to achieve this goal is the implementation of a dominant dwarfing gene into high yielding cultivars. The choice of dominant dwarfing genes in rye is limited to Ddw1 and Ddw3 loci, which are well characterized with respect to map position and tightly linked molecular markers on the long arms of chromosomes 5RL and 1RL, respectively. This paper reports on the identification and preliminary characterization of a novel dominant dwarfing gene, Ddw4, from line S44. This was mapped within the centromeric region of chromosome 3R. The Ddw4 gene is sensitive to exogenous gibberellin. Its introduction into the rye populational cultivar Dańkowskie Amber decreased plant height by c. 54% without any negative effects on spike length and number of kernels per spike. Further genetic studies are needed to determine the perspectives for application of the newly detected dwarfing gene into breeding programs for short-stem rye.
Molecular determination of claudin-15 organization and channel selectivity

Tight junctions are macromolecular structures that traverse the space between adjacent cells in epithelia and endothelia. Members of the claudin family are known to determine tight junction permeability in a charge- and size-selective manner. Here, we use molecular dynamics simulations to build and refine an atomic model of claudin-15 channels and study its transport properties. Our simulations indicate that claudin-15 forms well-defined channels for ions and molecules and otherwise “seals” the paracellular space through hydrophobic interactions. Ionic currents, calculated from simulation trajectories of wild-type as well as mutant channels, reflect in vitro measurements. The simulations suggest that the selectivity filter is formed by a cage of four aspartic acid residues (D55), contributed by four claudin-15 molecules, which creates a negative electrostatic potential to favor cation flux over anion flux. Charge reversal or charge ablation mutations of D55 significantly reduce cation permeability in silico and in vitro, whereas mutations of other negatively charged pore amino acid residues have a significantly smaller impact on channel permeability and selectivity. The simulations also indicate that water and small ions can pass through the channel, but larger cations, such as tetramethylammonium, do not traverse the pore. Thus, our model provides an atomic view of claudin channels, their transport function, and a potential three-dimensional organization of its selectivity filter.
The Make-or-Buy Decision in the Croatian Shipbuilding Industry: A Transaction Cost Economics Approach

The Make-or-Buy Decision in the Croatian Shipbuilding Industry: A Transaction Cost Economics Approach This paper examines the make-or-buy decision in the Croatian shipbuilding industry using a Transaction Cost Economics Approach. In other words, shipyards' decision to ‘make’ a component or to ‘buy’ it from market firms is analysed in relation to certain characteristics of the transactions in order to assess whether this decision is made in accordance with the theory's predictions. The empirical investigation, which is based on a sample of 167 observations, suggests that transaction cost hypotheses are only partially confirmed. Namely, while physical asset specificity and complexity are likely to increase the probability that a transaction will be internalised, temporal asset specificity and frequency seem not to affect significantly the integration decision. However, as the analysis leaves much of the variance in the patterns of vertical integration unexplained, the finding presented in this study should be seen as tentative. The inclusion of the remaining shipyards in the analysis as well as of new and more variables in the model are likely to improve the reliability of the results.
An Efficient Bayesian Yield Estimation Method for High Dimensional and High Sigma SRAM Circuits

With increasing dimension of variation space and computational intensive circuit simulation, accurate and fast yield estimation of realistic SRAM chip remains a significant and complicated challenge. In this paper, du Experiment results show that the proposed method has an almost constant time complexity as the dimension increases, and gains 6× speedup over the state-of-the- art method in the 485D cases.
Extensive Evaluation of Programming Models and ISAs Impact on Multicore So Error Reliability

To take advantage of the performance enhancements provided by multicore processors, new instruction set architectures (ISAs) and parallel programming libraries have been investigated across multiple industrial segments. This paper investigates the impact of parallelization libraries and distinct ISAs on the soft error reliability of two multicore ARM processor models (i.e., Cortex-A9 and Cortex-A72), running Linux Kernel and benchmarks with up to 87 billion instructions. An extensive soft error evaluation with more than 1.2 million simulation hours, considering ARMv7 and ARMv8 ISAs and the NAS Parallel Benchmark (NPB) suite is presented.