Miracle-dz/UniFAR-FTUs huggingface dataset:
Can You Be Hit by Your Partner and Be Intensely in Love?

This study examines, in a multilevel context, the influence of intensity of love at an individual level on couples’ mean reports of psychological and physical aggression in a sample of 2,988 adult couples of both sexes from the Region of Madrid. The percentages of intimate partner aggression considering the highest report of aggression in the couple were around 60% of psychological aggression and 15% of physical aggression. Multilevel models confirm that individuals who were less intensely in love reported a higher level of psychological aggression. Concerning physical aggression, men who declared they were less intensely in love reported a higher level of physical aggression by their partners, but this pattern was not found in the women. Therefore, psychological aggression plays a more relevant role in the intensity of love than physical aggression.
Modelling Inhalational Anaesthetics Using Bayesian Feature Selection and QSAR Modelling Methods

The development of robust and predictive QSAR models is highly dependent on the use of molecular descriptors that contain information relevant to the property being modelled. Selection of these relevant features from a large pool of possibilities is difficult to achieve effectively. Modern Bayesian methods provide substantial advantages over conventional feature selection methods for feature selection and QSAR modelling. We illustrate the importance of descriptor choice and the beneficial properties of Bayesian methods to select context‐dependent relevant descriptors and build robust QSAR models, using data on anaesthetics. Our results show the effectiveness of Bayesian feature selection methods in choosing the best descriptors when these are mixed with less informative descriptors. They also demonstrate the efficacy of the Abraham descriptors and identify deficiencies in ParaSurf descriptors for modelling anaesthetic action.
The Mengovirus Leader Protein Suppresses Alpha/Beta Interferon Production by Inhibition of the Iron/Ferritin-Mediated Activation of NF-κB

ABSTRACT In our studies on the biological function of the mengovirus leader protein, we identified a casein kinase II (CK-2) phosphorylation site in the protein. Here we report that the mengovirus leader protein can be phosphorylated by CK-2 in vitro. Expression of a recombinant leader protein in which the consensus CK-2 sequence around threonine 47 was disturbed resulted in a mutant protein that could no longer be phosphorylated. The CK-2 consensus sequence was modified by site-directed mutagenesis and subsequently introduced into a mengovirus cDNA clone to investigate the effect of the phosphorylation of the leader protein on virus replication and on the host cell response. Modifications by which the CK-2 consensus sequence was disturbed resulted in mutant viruses with reduced growth kinetics. We demonstrated that the integrity of the CK-2 phosphorylation site of the mengovirus leader protein was specifically related to the suppression of NF-κB activation and subsequent suppression of alpha/beta interferon production in infected cells. We also found that the integrity of the CK-2 phosphorylation site of the leader protein coincided with an increase of ferritin expression in the infected cell. These data indicate that the leader protein suppresses the iron-mediated activation of NF-κB and thereby inhibits alpha/beta interferon expression in the infected cell.
Inertial particle transport from peat moss vortex rings

We present a numerical analysis of how vortex rings from Sphagnum moss disperse their spores. Comparisons of the results of our CFD model with data measured from high-speed video reveal that the pressure inside the capsules is only 2 atm, which is significantly less than has been reported in the literature. We show that vortex rings produced by these pressures do not optimize the impulse to the fluid as is seen in other biological systems. We also present an analysis of the efficiency with which vortex rings from Sphagnum transport spores to heights where they can be carried by wind currents. Spore trajectories determined from a modified Maxey-Riley equation form a dynamical system for which we find the Lagrangian coherent structures (LCS), which define regions where spores are entrained in the vortex bubble. By analyzing the dependence of the LCS on capsule pressure, we will assess the efficiency with which vortex rings from Sphagnum transport spores.
The Impact of Public Expenditure on Economic Growth of Kosovo

The aim of the paper is to identify the impact of public expenditure on economic growth of Kosovo over the period 2000-2016. The structure of the econometric model is built by two economic theories, Wagner and Keynesian, where these two economic concepts support the results of the paper, that public expenditure and economic growth have a positive relation, but public expenditure does not have a direct impact on economic growth, but can have a stimulate effect on the economic growth process. The results of the econometric model showed that none of the public expenditure categories in Kosovo had any impact on economic growth of Kosovo over the period 2000-2016. The general conclusion is that public expenditure in Kosovo has been characterized by an unproductive public expedition, for the period 2000-2016, the effect of public expenditure on economic growth has not had the necessary and reasonable impact on achieving the economic target in Kosovo. The findings of the paper can be used by Kosovo's own government to orient the fiscal policies in Kosovo. The study seeks to contribute to the provision of an effective public expenditure structure in Kosovo, with particular emphasis on the best categorization of their impact on Kosovo's economic growth.
Concurrent mobility load balancing in LTE self-organized networks

Mobility load balancing (MLB) is an important use case in the long term evolution (LTE) self-optimized networks (SON). To combat the potential Ping-Pong load transfer and low convergence issues, we propose a concurrent MLB (CLB) scheme to solve out the asymmetry traffic distribution among multiple cells and the potential hidden-cell problem. CLB is implemented among multiple source and target cells, which can be regarded as a load redistribution game among them. Here, source cells are referred to as the sellers since they have excess load, and target cells as the buyers since they can absorb more load from the sellers. However, the gaming implementation complexity of such CLB is very high and the overhead is too heavy due to onetime trigger of CLB always involving multiple cells. Also, this situation is further challenged by the large-scale deployment of multiple cells in a specific region. Therefore, we further propose an irregular CLB (termed as ICLB) scheme, which overcomes the shortage of CLB of all associated cells who taking part. For ICLB, we denote the cell selection mechanism in detail. Simulation results show that both CLB and ICLB algorithms can overcome Ping-Pong load balancing problem. Meanwhile, the load distribution is more balancing than that of conventional MLB, and the performance of average blocking probability and the number of unsatisfied users are improved significantly.
Multiclass Core Vector Machine with smaller core sets

Traditional methods for solving multi-class problems, well-known as multi-SVMs, always combine certain decomposed binary-SVMs' results to formulate the final decision function. The prevalent methods are ‘one vs. one’ and ‘one vs. all’, which are based on a voting scheme among the binary classifiers to derive the winning class. However, they do not scale well with the data size and class number. Core Vector Machine (CVM) is a promising technique for scaling up a binary-SVM to handle large data sets with the greedy-expansion strategy, where the kernels are required to be normalized to ensure the equivalence between the kernel-induced spaces of SVM and Minimum Enclosing Ball (MEB). The idea proposed by CVM can also be utilized to formulate multi-SVM to MEB, by which we propose an approximate MEB algorithm with smaller core sets to handle multi-SVM. The experimental results on synthetic and benchmark data sets demonstrate the competitive performances of the method we proposed both on training time and training accuracy.
CUSHAW3: Sensitive and Accurate Base-Space and Color-Space Short-Read Alignment with Hybrid Seeding

The majority of next-generation sequencing short-reads can be properly aligned by leading aligners at high speed. However, the alignment quality can still be further improved, since usually not all reads can be correctly aligned to large genomes, such as the human genome, even for simulated data. Moreover, even slight improvements in this area are important but challenging, and usually require significantly more computational endeavor. In this paper, we present CUSHAW3, an open-source parallelized, sensitive and accurate short-read aligner for both base-space and color-space sequences. In this aligner, we have investigated a hybrid seeding approach to improve alignment quality, which incorporates three different seed types, i.e. maximal exact match seeds, exact-match k-mer seeds and variable-length seeds, into the alignment pipeline. Furthermore, three techniques: weighted seed-pairing heuristic, paired-end alignment pair ranking and read mate rescuing have been conceived to facilitate accurate paired-end alignment. For base-space alignment, we have compared CUSHAW3 to Novoalign, CUSHAW2, BWA-MEM, Bowtie2 and GEM, by aligning both simulated and real reads to the human genome. The results show that CUSHAW3 consistently outperforms CUSHAW2, BWA-MEM, Bowtie2 and GEM in terms of single-end and paired-end alignment. Furthermore, our aligner has demonstrated better paired-end alignment performance than Novoalign for short-reads with high error rates. For color-space alignment, CUSHAW3 is consistently one of the best aligners compared to SHRiMP2 and BFAST. The source code of CUSHAW3 and all simulated data are available at http://cushaw3.sourceforge. net.
Up-regulation of Connective Tissue Growth Factor in Hyperoxia-Induced Lung Fibrosis

Pulmonary oxygen toxicity plays an important role in the lung injury process that leads to the development of bronchopulmonary dysplasia. Connective tissue growth factor (CTGF) is a fibroblast mitogen and promoter of collagen deposition. We investigated the effects of postnatal hyperoxia on lung collagen and CTGF expression in rats. Rat pups were exposed to 7 d of >95% O2 and a further 3 wk of 60% O2. CTGF mRNA and protein expression increased after hyperoxia treatment, and the values were significantly higher in hyperoxia-exposed rats on postnatal d 7 and 14. Lung collagen levels increased as rats aged, and the values were comparable between room air-exposed and hyperoxia-exposed rats on postnatal d 7 and 14 and were significantly higher in hyperoxia-exposed rats on postnatal d 21 and 28. Increases in CTGF mRNA and protein expressions preceded the onset of increased lung collagen. These data demonstrate that CTGF is up-regulated at time points preceding the fibrotic phase of the lung injury adding credence to the hypothesis that CTGF seems to be involved in the pathogenesis of hyperoxia-induced lung fibrosis and an anti-CTGF strategy might attenuate hyperoxia-induced lung fibrosis.
Essays on Non-Gaussian Time Series Analysis

This thesis is a compilation of essays on the extension of financial econometric techniques to various fields of financial and non-financial risk management—namely, longevity risk, disaster risk and food security risk. First, longevity risk is quantified by proposing a mortality forecasting methodology based on a modified survival function and nonparametric residual-based bootstrapping. The parameters of the survival function are estimated through time and are modelled with a time series model structure. The estimated model is used to generate forecasts of parameter values and life expectancy. Confidence intervals are generated by residual-based bootstrapping through an autoregressive sieve based on the estimated model. The methodology is applied to life tables of male and female subjects from the United States, Australia and Japan, and compared with the Lee–Carter model in terms of forecasting life expectancy. From the results for the three countries, the proposed survival function has better long-term forecasting performance than does the Lee–Carter model. Second, a proposed methodology for estimating disaster risk is devised using bootstrapped multivariate extreme value theory methods. A disaster risk measure called storm-at-risk is created. The risk measure can be estimated through semiparametric and nonparametric approaches and is applied to weather extremes data generated by typhoons that enter the western North Pacific basin. Robustness checks on the performance of the approaches are conducted. The semiparametric approach performs better than the nonparametric approach in longer periods, but not in smaller periods. Third, food security risk is quantified by proposing risk measures for hierarchical agricultural time series data, which are generated for national and sub-national levels. The risk measures are created by a combination of forecast reconciliation methods for hierarchical time series data and residual-based bootstrapping methods. The methodology is applied to Philippine rice production time series data that are collected from the regions and are aggregated to the macro-regional and national levels.
The End of an Architectural Era for Analytical Databases

Traditional enterprise warehouse solutions center around an analytical database system that is monolithic and inflexible: data needs to be extracted, transformed, and loaded into the rigid relational form before analysis. It takes years of sophisticated planning to provision and deploy a warehouse; adding new hardware resources to an existing warehouse is an equally lengthy and daunting task. Additionally, modern data analysis employs statistical methods that go well beyond the typical roll-up and drill-down capabilities provided by warehouse systems. Although it is possible to implement such methods using a combination of SQL and UDFs, query engines in relational databases are ill-suited for these. The Hadoop ecosystem introduces a suite of tools for data analytics that overcome some of the problems of traditional solutions. These systems, however, forgo years of warehouse research. Memory is significantly underutilized in Hadoop clusters, and execution engine is naive compared with its relational counterparts. It is time to rethink the design of data warehouse systems and take the best from both worlds. The new generation of warehouse systems should be modular, high performance, fault-tolerant, easy to provision, and designed to support both SQL query processing and machine learning applications. This paper references the Shark system developed at Berkeley as an initial attempt.
GPU based parallel cooperative Particle Swarm Optimization using C-CUDA: A case study

The applications requiring massive computations may get benefit from the Graphics Processing Units (GPUs) with Compute Unified Device Architecture (CUDA) by reducing the execution time. Since the introduction of CUDA, applications from different areas have been benefited. Evolutionary algorithms are one such potential area where CUDA implementation proves to be beneficial not only in terms of the speedups obtained but also the improvement in convergence time. In this paper we present a detailed study of parallel implementation of one of the existing variants of Particle Swarm Optimization which is Cooperative Particle Swarm Optimization (CPSO). We also present a comparative study on CPSO implemented in C and C-CUDA. The algorithm was tested on a set of standard benchmark optimization functions. In this process, some interesting results related to the speedup and improvements in the time in convergence were obtained. The differences in randomizing procedures used in CUDA seem to contribute towards the diversity in population leading to better solution in contrast with the serial implementation. It also provides motivation for further research on neural network architecture and weight optimization using CUDA implementation. The results obtained in this paper therefore re-emphasize the utility of CUDA based implementation for complex and computationally intensive applications.
A Real‐Time Assessment of Factors Influencing Medication Events

Abstract: Reducing medical error is critical to improving the safety and quality of healthcare. Physician stress, fatigue, and excessive workload are performance‐shaping factors (PSFs) that may influence medical events (actual administration errors and near misses), but direct relationships between these factors and patient safety have not been clearly defined. This study assessed the real‐time influence of emotional stress, workload, and sleep deprivation on self‐reported medication events by physicians in academic hospitals. During an 18‐month study period, 185 physician participants working at four university‐affiliated teaching hospitals reported medication events using a confidential reporting application on handheld computers. Emotional stress scores, perceived workload, patient case volume, clinical experience, total sleep, and demographic variables were also captured via the handheld computers. Medication event reports (n = 11) were then correlated with these demographic and PSFs. Medication events were associated with 36.1% higher perceived workload (p < .05), 38.6% higher inpatient caseloads (p < .01), and 55.9% higher emotional stress scores (p < .01). There was a trend for reported events to also be associated with less sleep (p = .10). These results confirm the effect of factors influencing medication events, and support attention to both provider and hospital environmental characteristics for improving patient safety.
Experimenting with system and Libc call interception attacks on ARM-based Linux kernel

Linux is one of the highly portable operating systems for embedded systems such as tablet PC. Recently it has been used for a smartphone operating system based on ARM processor. In ×86-based Linux, system call and standard library interception attacks using a Loadable Kernel Module (LKM) have been reported. Those attacks are usually used so that the attacker sets up a backdoor or makes a rootkit with root privilege. In this paper, we report that those attacks also are available in an ARM-based Linux which is popularly adopted for smartphone OS including Android. We also implement those attacks on Maemo platform on Nokia N900, show their empirical results, and then discuss some countermeasures thereof.
GLTSCR2/PICT-1, a Putative Tumor Suppressor Gene Product, Induces the Nucleolar Targeting of the Kaposi's Sarcoma-Associated Herpesvirus KS-Bcl-2 Protein

ABSTRACT KS-Bcl-2, encoded by Kaposi's sarcoma-associated herpesvirus (KSHV), is a structural and functional homologue of the Bcl-2 family of apoptosis regulators. Like several other Bcl-2 family members, KS-Bcl-2 protects cells from apoptosis and autophagy. Using a yeast two-hybrid screen and coimmunoprecipitation assays, we identified a novel KS-Bcl-2-interacting protein, referred to as protein interacting with carboxyl terminus 1 (PICT-1), encoded by a candidate tumor suppressor gene, GLTSCR2. Confocal laser scanning microscopy revealed nucleolar localization of PICT-1, whereas KS-Bcl-2 was located mostly at the mitochondrial membranes with a small fraction in the nucleoli. Ectopic expression of PICT-1 resulted in a large increase in the nucleolar fraction of KS-Bcl-2, and only a minor fraction remained in the cytoplasm. Furthermore, knockdown of endogenous PICT-1 abolished the nucleolar localization of KS-Bcl-2. However, ectopically expressed PICT-1 did not alter the cellular distribution of human Bcl-2. Subsequent analysis mapped the crucial amino acid sequences of both KS-Bcl-2 and PICT-1 required for their interaction and for KS-Bcl-2 targeting to the nucleolus. Functional studies suggest a correlation between nucleolar targeting of KS-Bcl-2 by PICT-1 and reduction of the antiapoptotic activity of KS-Bcl-2. Thus, these studies demonstrate a cellular mechanism to sequester KS-Bcl-2 from the mitochondria and to downregulate its virally encoded antiapoptotic activity. Additional characterization of the interaction of KS-Bcl-2 and PICT-1 is likely to shed light on the functions of both proteins.
Efficient Cre/loxP Site-Specific Recombination in a HepG2 Human Liver Cell Line

A worldwide shortage of donor livers is a limiting factor of the clinical application of hepatocyte transplantation (HTX). To resolve this issue, we focused on a reversible immortalization system that allows temporary expansion of primary hepatocyte populations by transfer of an oncogene that can be subsequently excised. As a preliminary test toward this goal, we examined the efficacy of Cre/loxP site-specific recombination in a transformed human liver cell line, HepG2. The present study utilized retroviral transfer of a prototypical immortalizing gene, simian virus 40 large T antigen (SV40Tag), flanked by a pair of loxP recombination targets and adenovirus-mediated Cre/loxP recombination. Here we report that complete elimination of the retroviral transferred oncogene was achieved by site-specific recombination using a replication-deficient recombinant adenovirus vector producing Cre recombinase (Ad-Cre).
Relevance of corruption on the effect of public health expenditure and taxation on economic growth

ABSTRACT We investigate whether corruption distorts the positive effect of public health expenditure and taxation on growth through panel data analysis of 75 developing countries for the period from 1995 to 2014. The findings indicate that, although both public health expenditure and taxation can increase economic growth, in countries with more corrupt governments this effect is reduced.
The Role of P-glycoprotein in the Blood-Brain Barrier

The blood-brain barrier is composed of specialized endothelial cells that prevent various substances from entering the brain. P-glycoprotein is an important component of this barrier and is present in high concentration on the apical surface of these endothelial cells. It is an ATP-dependent transport protein thought to be involved in extruding a variety of structurally unrelated compounds and preventing their accumulation within the brain. It is known that P-glycoprotein impedes the entry of various drugs that are used in the treatment of central nervous system diseases. Understanding the structure and the function of P-glycoprotein will lead to the development of specific and selective P-glycoprotein inhibitors. Combined use of these inhibitors along with therapeutic agents could treat central nervous system diseases and result in improved clinical efficacy.
Path Research on Ideological and Political Education for Poverty-Stricken College Students Based on Psychological Analysis

Due to economic poverty and particularity of the self-development consciousness of college poverty-stricken students, which tends to cause negative change of psychological aspects, and affect their normal adaptation and self development. Therefore, this article proposes that when offering effective solutions to their economic difficulties and establishing aid work mechanism for poverty-stricken students, we should accurately analyze their psychological characteristics and provide psychological adjustment to them. At the same time, the method of ideological and political education is introduced into the method by specific psychological methods, such as problem centered, positive psychology and psychological contract, to explore the effective paths of ideological and political education for poverty-stricken students.