Miracle-dz/UniFAR-FTUs huggingface dataset:
Plasma Concentrations and Dietary Intakes of Choline and Betaine in Association With Atrial Fibrillation Risk: Results From 3 Prospective Cohorts With Different Health Profiles

Background Although choline metabolism has been associated with atherosclerotic heart disease, less research attention has been paid to the associations of choline and its oxidative metabolite betaine with cardiac arrhythmias. Methods and Results We evaluated associations of plasma concentrations and dietary intakes of choline and betaine with long‐term atrial fibrillation (AF) risk in a community‐based cohort, HUSK ([the Hordaland Health Study] n=6949), and validated the findings in 2 patient cohorts: the Western Norway Coronary Angiography Cohort (n=4164) and the NORVIT (Norwegian B‐Vitamin) Trial (n=3733). Information on AF was obtained from the CVDNOR (Cardiovascular Disease in Norway) project. In HUSK, WECAC (Western Norway Coronary Angiography Cohort), and NORVIT, 552, 411, and 663 AF cases were identified during a median follow‐up time of 10.9, 7.3, and, 8.7 years, respectively. Plasma concentrations of choline and betaine were significantly positively associated with later AF risk after multivariable adjustments in HUSK. Such associations were independently replicated in the 2 external prospective patient cohorts. The pooled hazard ratio was 1.13 (95% confidence interval 1.08‐1.19, P<0.001) and 1.16 (95% confidence interval 1.10‐1.22, P<0.001) per SD increment for log‐transformed choline and betaine, respectively. Moreover, dietary intake of choline was marginally associated with AF risk (pooled hazard ratio 1.29, 95% confidence interval 1.01‐1.66, fifth versus first quintile), whereas no significant association was observed between dietary betaine and AF risk. Conclusions Our findings indicate that plasma concentrations as well as dietary intake of choline, but not betaine, are associated with subsequent risk of AF, suggesting a potential role of choline metabolism in the pathogenesis of AF. Clinical Trial Registration URL: https://www.clinicaltrials. gov.Unique identifier: NCT00671346.
HIV Protease-Generated Casp8p41, When Bound and Inactivated by Bcl2, Is Degraded by the Proteasome

ABSTRACT HIV protease is known to cause cell death, which is dependent upon cleavage of procaspase 8. HIV protease cleavage of procaspase 8 generates Casp8p41, which directly binds Bak with nanomolar affinity, causing Bak activation and consequent cell death. Casp8p41 can also bind Bcl2 with nanomolar affinity, in which case cell death is averted. Central memory CD4 T cells express high levels of Bcl2, possibly explaining why those cells do not die when they reactivate HIV. Here, we determine that the Casp8p41-Bcl2 complex is polyubiquitinated and degraded by the proteasome. Ixazomib, a proteasome inhibitor in clinical use, blocks this pathway, increasing the abundance of Casp8p41 and causing more cells to die in a Casp8p41-dependent manner. IMPORTANCE The Casp8p41 pathway of cell death is unique to HIV-infected cells yet is blocked by Bcl2. Once bound by Bcl2, Casp8p41 is polyubiquitinated and degraded by the proteasome. Proteasome inhibition blocks degradation of Casp8p41, increasing Casp8p41 levels and causing more HIV-infected cells to die.
Scene Classification Based on a Deep Random-Scale Stretched Convolutional Neural Network

With the large number of high-resolution images now being acquired, high spatial resolution (HSR) remote sensing imagery scene classification has drawn great attention but is still a challenging task due to the complex arrangements of the ground objects in HSR imagery, which leads to the semantic gap between low-level features and high-level semantic concepts. As a feature representation method for automatically learning essential features from image data, convolutional neural networks (CNNs) have been introduced for HSR remote sensing image scene classification due to their excellent performance in natural image classification. However, some scene classes of remote sensing images are object-centered, i.e., the scene class of an image is decided by the objects it contains. Although previous methods based on CNNs have achieved comparatively high classification accuracies compared with the traditional methods with handcrafted features, they do not consider the scale variation of the objects in the scenes. This makes it difficult to directly utilize CNNs on those remote sensing images belonging to object-centered classes to extract features that are robust to scale variation, leading to wrongly classified scene images. To solve this problem, scene classification based on a deep random-scale stretched convolutional neural network (SRSCNN) for HSR remote sensing imagery is proposed in this paper. In the proposed method, patches with a random scale are cropped from the image and stretched to the specified scale as the input to train the CNN. This forces the CNN to extract features that are robust to the scale variation. Furthermore, to further improve the performance of the CNN, a robust scene classification strategy is adopted, i.e., multi-perspective fusion. The experimental results obtained using three datasets—the UC Merced dataset, the Google dataset of SIRI-WHU, and the Wuhan IKONOS dataset—confirm that the proposed method performs better than the traditional scene classification methods.
THE CULTURAL TRANSMISSION OF FAITH Why innate intuitions are necessary, but insufficient, to explain religious belief

The cognitive science of religion integrates insights from diverse scientific disciplines to explain how people acquire, represent and transmit religious concepts. This perspective has led to a fruitful research program on the naturalistic origins of religion. However, it has thus far not directly addressed a key component of religion: faith or committed belief. The present review proposes a framework that integrates standard approaches from the cognitive science of religion with established models of cultural evolution and cultural learning. According to this synthetic approach, innate cognitive content biases explain how people mentally represent gods, and cultural evolutionary models explain why people come to believe and commit to the particular supernatural beliefs that they do. This synthesis offers a more complete picture of the origins and cultural persistence of religious belief.
PDZ Domain-Mediated Interactions of G Protein-Coupled Receptors with Postsynaptic Density Protein 95: Quantitative Characterization of Interactions

G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome. Their signaling is regulated by scaffold proteins containing PDZ domains, but although these interactions are important for GPCR function, they are still poorly understood. We here present a quantitative characterization of the kinetics and affinity of interactions between GPCRs and one of the best characterized PDZ scaffold proteins, postsynaptic density protein 95 (PSD-95), using fluorescence polarization (FP) and surface plasmon resonance (SPR). By comparing these in vitro findings with colocalization of the full-length proteins in cells and with previous studies, we suggest that the range of relevant interactions might extend to interactions with K i = 450 µM in the in vitro assays. Within this range, we identify novel PSD-95 interactions with the chemokine receptor CXCR2, the neuropeptide Y receptor Y2, and four of the somatostatin receptors (SSTRs). The interaction with SSTR1 was further investigated in mouse hippocampal neurons, where we found a clear colocalization between the endogenously expressed proteins, indicating a potential for further investigation of the role of this interaction. The approach can easily be transferred to other receptors and scaffold proteins and this could help accelerate the discovery and quantitative characterization of GPCR–PDZ interactions.
Microglia and Beyond: Innate Immune Cells As Regulators of Brain Development and Behavioral Function

Innate immune cells play a well-documented role in the etiology and disease course of many brain-based conditions, including multiple sclerosis, Alzheimer’s disease, traumatic brain and spinal cord injury, and brain cancers. In contrast, it is only recently becoming clear that innate immune cells, primarily brain resident macrophages called microglia, are also key regulators of brain development. This review summarizes the current state of knowledge regarding microglia in brain development, with particular emphasis on how microglia during development are distinct from microglia later in life. We also summarize the effects of early life perturbations on microglia function in the developing brain, the role that biological sex plays in microglia function, and the potential role that microglia may play in developmental brain disorders. Finally, given how new the field of developmental neuroimmunology is, we highlight what has yet to be learned about how innate immune cells shape the development of brain and behavior.
Emission factors of atmospheric and climatic pollutants from crop residues burning

ABSTRACT Biomass burning is a common agricultural practice, because it allows elimination of postharvesting residues; nevertheless, it involves an inefficient combustion process that generates atmospheric pollutants emission, which has implications on health and climate change. This work focuses on the estimation of emission factors (EFs) of PM2.5, PM10, organic carbon (OC), elemental carbon (EC), carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) of residues from burning alfalfa, barley, beans, cotton, maize, rice, sorghum, and wheat in Mexico. Chemical characteristics of the residues were determined to establish their relationship with EFs, as well as with the modified combustion efficiency (MCE). Essays were carried out in an open combustion chamber with isokinetic sampling, following modified EPA 201-A method. EFs did not present statistical differences among different varieties of the same crop, but were statistically different among different crops, showing that generic values of EFs for all the agricultural residues can introduce significant uncertainties when used for climatic and atmospheric pollutant inventories. EFs of PM2.5 ranged from 1.19 to 11.30 g kg−1, and of PM10 from 1.77 to 21.56 g kg−1. EFs of EC correlated with lignin content, whereas EFs of OC correlated inversely with carbon content. EFs of EC and OC in PM2.5 ranged from 0.15 to 0.41 g kg−1 and from 0.33 to 5.29 g kg−1, respectively, and in PM10, from 0.17 to 0.43 g kg−1 and from 0.54 to 11.06 g kg−1. CO2 represented the largest gaseous emissions volume with 1053.35–1850.82 g kg−1, whereas the lowest was CH4 with 1.61–5.59 g kg−1. CO ranged from 28.85 to 155.71 g kg−1, correlating inversely with carbon content and MCE. EFs were used to calculate emissions from eight agricultural residues burning in the country during 2016, to know the potential mitigation of climatic and atmospheric pollutants, provided this practice was banned. Implications: The emission factors of particles, short-lived climatic pollutants, and atmospheric pollutants from the crop residues burning of eight agricultural wastes crops, determined in this study using a standardized method, provides better knowledge of the emissions of those species in Latin America and other developing countries, and can be used as inputs in air quality models and climatic studies. The EFs will allow the development of more accurate inventories of aerosols and gaseous pollutants, which will lead to the design of effective mitigation strategies and planning processes for sustainable agriculture.
Testing the Granger Noncausality Hypothesis in Stationary Nonlinear Models of Unknown Functional Form

In this article, we propose a general method for testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form. These tests are based on a Taylor expansion of the nonlinear model around a given point in the sample space. We study the performance of our tests by a Monte Carlo experiment and compare these to the most widely used linear test. Our tests appear to be well-sized and have reasonably good power properties.
Please Call Again: Correcting Nonresponse Bias in Treatment Effect Models

Abstract We propose a novel selectivity correction procedure to deal with survey attrition in treatment effect models, at the crossroads of the Heckit model and the bounding approach of Lee (2009). As a substitute for the instrument needed in sample selectivity correction models, we use information on the number of prior calls made to each individual before obtaining a response to the survey. We obtain sharp bounds to the average treatment effect on the common support of responding individuals. Because the number of prior calls brings information, we can obtain tighter bounds than in other nonparametric methods.
Altered phosphorylation pattern of simian virus 40 T antigen expressed in insect cells by using a baculovirus vector

The phosphorylation pattern of simian virus 40 (SV40) large tumor (T) antigen purified from insect cells infected with a recombinant baculovirus was compared with that reported previously for T antigen from SV40-infected monkey cells. The specific activity of metabolic phosphate labeling of baculovirus T antigen was reduced, and the phosphopeptide map of the baculovirus protein, while qualitatively similar to that of lytic T, revealed several quantitative differences. The most striking difference was the prominence in the baculovirus map of peptides containing phosphothreonine 124. These peptides are known to arise from other phosphopeptides upon dephosphorylation of neighboring serines, suggesting that baculovirus T may be underphosphorylated at these serines and perhaps other sites. Functional assays used to further investigate the phosphorylation state of the baculovirus protein included SV40 DNA binding after enzymatic dephosphorylation with alkaline phosphatase and after phosphorylation by a murine homolog of cdc2 protein kinase. The results imply that baculovirus T antigen is underphosphorylated, in particular at those serine residues whose phosphorylation is responsible for down regulation of DNA-binding activity at site II in the core origin of DNA replication. In contrast, no evidence for a functionally significant underphosphorylation at threonine 124 could be found.
Exploring the mediating role of innovation in the effect of the knowledge management process on performance

ABSTRACT The aim of this study is to explore the mediating role of innovation components in the relationship between knowledge management processes and performance. The research questions were investigated through questionnaires with top-level managers of a firm operating in the Turkish telecommunication industry. The results of the study indicated that knowledge management processes affect all innovation components. In addition to the direct effects of the knowledge management process on firm performance, marketing, product and process innovation are mediators in the relationship between the knowledge management process and performance. Finally, this research sheds light on how firms can manage their knowledge to gain a competitive advantage based on innovation.
Ground Deformations around the Toktogul Reservoir, Kyrgyzstan, from Envisat ASAR and Sentinel-1 Data - A Case Study about the Impact of Atmospheric Corrections on InSAR Time Series

We present ground deformations in response to water level variations at the Toktogul Reservoir, located in Kyrgyzstan, Central Asia. Ground deformations were measured by Envisat Advanced Synthetic Aperture Radar (ASAR) and Sentinel-1 Differential Interferometric Synthetic Aperture Radar (DInSAR) imagery covering the time periods 2004–2009 and 2014–2016, respectively. The net reservoir water level, as measured by satellite radar altimetry, decreased approximately 60 m (∼13.5 km3) from 2004–2009, whereas, for 2014–2016, the net water level increased by approximately 51 m (∼11.2 km3). The individual Small BAseline Subset (SBAS) interferograms were heavily influenced by atmospheric effects that needed to be minimized prior to the time-series analysis. We tested several approaches including corrections based on global numerical weather model data, such as the European Centre for Medium-Range Weather Forecasts (ECMWF) operational forecast data, the ERA-5 reanalysis, and the ERA-Interim reanalysis, as well as phase-based methods, such as calculating a simple linear dependency on the elevation or the more sophisticated power–law approach. Our findings suggest that, for the high-mountain Toktogul area, the power–law correction performs the best. Envisat descending time series for the period of water recession reveal mean line-of-sight (LOS) uplift rates of 7.8 mm/year on the northern shore of the Toktogul Reservoir close to the Toktogul city area. For the same area, Sentinel-1 ascending and descending time series consistently show a subsidence behaviour due to the replenishing of the water reservoir, which includes intra-annual LOS variations on the order of 30 mm. A decomposition of the LOS deformation rates of both Sentinel-1 orbits revealed mean vertical subsidence rates of 25 mm/year for the common time period of March 2015–November 2016, which is in very good agreement with the results derived from elastic modelling based on the TEA12 Earth model.
Reduced state representation in delayed-state SLAM

This paper introduces an approach that reduces the size of the state and maximizes the sparsity of the information matrix in exactly sparse delayed-state SLAM. We propose constant time procedures to measure the distance between a given pair of poses, the mutual information gain for a given candidate link, and the joint marginals required for both measures. Using these measures, we can readily identify non redundant poses and highly informative links and use only those to augment and to update the state, respectively. The result is a delayed-state SLAM system that reduces both the use of memory and the execution time and that delays filter inconsistency by reducing the number of linearization introduced when adding new loop closure links. We evaluate the advantage of the proposed approach using simulations and data sets collected with real robots.
Convergence of multivariate belief propagation, with applications to cuckoo hashing and load balancing

This paper is motivated by two applications, namely i) generalizations of cuckoo hashing, a computationally simple approach to assigning keys to objects, and ii) load balancing in content distribution networks, where one is interested in determining the impact of content replication on performance. These two problems admit a common abstraction: in both scenarios, performance is characterized by the maximum weight of a generalization of a matching in a bipartite graph, featuring node and edge capacities. Our main result is a law of large numbers characterizing the asymptotic maximum weight matching in the limit of large bipartite random graphs, when the graphs admit a local weak limit that is a tree. This result specializes to the two application scenarios, yielding new results in both contexts. In contrast with previous results, the key novelty is the ability to handle edge capacities with arbitrary integer values. An analysis of belief propagation algorithms (BP) with multivariate belief vectors underlies the proof. In particular, we show convergence of the corresponding BP by exploiting monotonicity of the belief vectors with respect to the so-called upshifted likelihood ratio stochastic order. This auxiliary result can be of independent interest, providing a new set of structural conditions which ensure convergence of BP.
Understanding Keystroke Dynamics for Smartphone Users Authentication and Keystroke Dynamics on Smartphones Built-In Motion Sensors

Personal Identification Numbers (PINs) and pattern drawing have been used as common authentication methods especially on smartphones. Such methods, however, are very vulnerable to the shoulder surfing attack. Thus, keystroke dynamics that authenticate legitimate users based on their typing manner have been studied for years. However, many of the studies have focused on PC keyboard keystrokes. More studies on mobile and smartphones keystroke dynamics are warranted; as smartphones make progress in both hardware and software, features from smartphones have been diversified. In this paper, using various features including keystroke data such as time interval and motion data such as accelerometers and rotation values, we evaluate features with motion data and without motion data. We also compare 5 formulas for motion data, respectively. We also demonstrate that opposite gender match between a legitimate user and impostors has influence on authenticating by our experiment results.
Anticoagulation therapy in patients with non-valvular atrial fibrillation hospitalized in the Department of Medicine in the NOACs era

Background The treatment of atrial fibrillation (AF) includes anticoagulation (AC) therapy to prevent systemic emboli. Until recently, warfarin was the main AC agent, while in recent years, the new oral anticoagulants (NOACs) are increasingly being used. Aim The aim of our study was to characterize the AC treatment policy of AF patients at the department of medicine in the NOACs era. Methods and Design An observational study of consecutive hospitalized patients with non-valvular AF for a period of 3 months in Beilinson hospital (January to March 2017). Demographic characteristics, clinical data and AC therapeutic approach were compared to those from the pre-NOACs era, based on a previous study. Results A total of 335 patients were hospitalized with either new (21%) or prior (79%) non-valvular AF. An increase in AC therapy among patients with prior and new AF was observed compared to the pre-NOACs era (76% vs. 59%; P < 0.001 and 68% vs. 49%; P < 0.001, respectively). Totally, 76% of all patients were discharged with AC therapy compared to 55% in the pre-NOACs era. As in the pre-NOACs era, prior AC therapy was the main predictor for the prescription of AC therapy during hospitalization and discharge (OR = 13, 95% CI; 7-25, P = 0.0001). Conclusion There is a significant increase in the AC therapy prescription, mainly NOACs, in hospitalized non-valvular AF patients. This increase could be explained by the difficulties in warfarin treatment and the benefits of NOACs. Nevertheless, a large observational study is required to prove these findings.
A Compact High-Performance Patch Antenna Array for 60-GHz Applications

In this letter, a compact and high-performance patch antenna array is developed for 60-GHz applications. The method to enhance both the gain and the frequency bandwidth of the antenna array simultaneously by using a parallel-series feed network together with the differential feeding technique is studied thoroughly. The tested antenna array achieves operation bandwidth ( ) from 55 to 68 GHz, which covers worldwide 60-GHz unlicensed band of 57-66 GHz, with peak gain of 12.8-15.6 dBi. The measured -3-dB beamwidths at 61.5 GHz are around ±13° in E-plane and ±15° in H-plane, respectively. The designed high-gain antenna array has a compact size of only 20 ×14 mm2 excluding the connector footprint for test.