Miracle-dz/UniFAR-FTUs huggingface dataset:
Gender modulates development of the metabolic syndrome phenotype in fructose-fed rats

We analyzed the effects of a fructose-rich diet (FRD) to test the assumption that the expression of metabolic syndrome phenotype is different in male and female rats. Two-way ANOVA revealed a significant effect of FRD on feeding behavior and carbohydrate/lipid metabolism. The increased caloric intake in FRD rats of both sexes was followed by a cluster of gender-specific changes typical for the metabolic syndrome. Female rats were characterized by decreased glycemia, increased triglycerides, enlarged visceral adipose tissue and increased absolute mass of liver, without changes in systolic blood pressure and insulin sensitivity. In contrast, male rats developed less disturbances in physical and biochemical characteristics, but blood pressure and insulin sensitivity were impaired by FRD. The results emphasize the detrimental effects of fructose consumption on cardiovascular risk and insulin action in males, whereas females are affected by other metabolic disturbances. These results support the idea of gender-dependent differences in the expression of the metabolic syndrome phenotype. [Projekat Ministarstva nauke Republike Srbije, br. 41009]
LCAP - A Lightweight CAN Authentication Protocol for Securing In-Vehicle Networks

—The design of in-vehicle communication networks has been always concerned with reliability and safety. There was no much attention paid to the security of such networks. This is because there was no clear evidence if the security of such networks could be compromised. However, recent experiments have shown the consequences of compromising in-vehicle networks. Those experiments relied on vulnerabilities that exist in such networks. Some of those vulnerabilities arise from the used communication standards themselves. Therefore, it became necessary to ﬁnd ways of introducing security to the used standards. In this paper, a lightweight message source authentication protocol for Controller Area Network (CAN) [1] is proposed and fully implemented. The main advantage of the protocol is that it can be practically deployed in vehicles manufactured nowadays with minimum overhead. The protocol does not require any hardware modiﬁcations to be done in the CAN network. Also, it does not add much overhead to the embedded software of the ECUs. Moreover, it tends to avoid any modiﬁcations from being done to the existing CAN message sets that are being exchanged between ECUs.
Inhibition of Viviparous Sprouting on Melon Seeds Using High Level of Potassium Fertilization or Abscisic Acid Application

The present experiments were undertaken in order to clarify the effects of a high potassium fertilization level on the occurrence of viviparous sprouting in melon fruit. Melon (Cucumis melo L. group) plants of two susceptible lines and one resistant line to viviparous sprouting were used at two different potassium concentrations. A high potassium fertilization level (12.0 mmol·L) resulted in a marked decrease of the occurrence of viviparous sprouting in the susceptible lines, and in the increase of the endogenous ABA content. No significant differences were observed in the seed number per fruit, the seed weight, and the percentage of seed germination at a high level of potassium fertilization. Further experiments were conducted in order to analyze the effects of exogenous ABA treatment at a low potassium fertilization level (1.5 mmol·L) on the occurrence of viviparous sprouting in melon fruit. At 25 days after pollination, ABA solution at different concentrations was sprayed on the fruits of the susceptible melon line grown at two different potassium fertilization levels. Even at a low potassium fertilization level, exogenous ABA application inhibited the occurrence of viviparous sprouting and increased ABA contents both in juice samples around the placenta and in the seeds. ABA treatment, however, led to a significant decrease in the seed number per fruit and in the percentage of seed germination, as a result of a marked increase in the ABA content and potassium absorption.
Sovereign Debt Crisis, Fiscal Consolidation, and Active Central Bankers in a Monetary Union

Abstract This paper examines the impact of exogenous shocks on sovereign debts in an incomplete monetary union. We assume that financial stability is a public good that sovereign debt shocks can undermine in fragile (peripheral) members. Our model shows that, unlike the common misconception, active monetary policies do not induce the peripheral government to relax its fiscal constraints; on the contrary, these policies tend to incentivize fiscal discipline by reducing the cost of balance consolidation. Active monetary policies, in fact, partially reallocate the stabilization costs from the periphery to the core of the union, preserving the common good and facilitating fiscal discipline in the periphery.
Innovative Options Data Signal for Trading with Technical Indicators and VIX optimized by a GA

In this thesis it is proposed the use of options data, organized in an innovative form, in a mechanism made by an investment simulator led by technical and VIX indicators using trailing stoplosses and optimized by a genetic algorithm with the objective of discover a rule that can be applied in the options market, then some tests were made in the SP500 Index options market for results comparing and analyzing. Daily options data from 2011 to 2017 on the SP500 index were used for train with a rolling window and a return of investment of 325% was achieved in test in a time period of 1200 days.
Investor sentiment and the cross-section of Japanese stock returns

This paper examines sentiment as an augmentation to the Fama and French threefactor model. International tests of empirical asset pricing models show that only three pricing factors are relevant, but perhaps not sufficient, in modelling the cross-section of Japanese stock returns. We find that that sentiment can help explain the cross-section of Japanese stock returns and is able to remove excess returns when added to the three-factor model. We also observe asymmetric effects of sentiment on stocks in the cross-section of size. Small stocks and large stocks are more affected by sentiment. This paper demonstrates that the addition of a factor capturing sentiment should be considered when modelling Japanese stock returns.
Comparative analysis of supervised machine learning algorithms for heart disease detection

This paper describes the most prominent algorithms of Supervised Machine Learning (SML), their characteristics, and comparatives in the way of treating data. The Heart Disease dataset obtained from Kaggle was used to determine and test its highest percentage of accuracy. To achieve the objective, Python sklearn libraries were used to implement the selected algorithms, evaluate and determine which algorithm is the one that obtains the best results, applying decision tree algorithms achieved the best prediction results.
Effect of Platinum Precursor Type on Activity of Pt/CeO2 catalyst in C3H8 and CO Oxidation

Noble metal precursor type has been found to affect the strong metal-support interaction and catalytic activity. Here, the effect of platinum precursor type of Pt/CeO2 catalyst on the catalytic activity of C3H8 and CO oxidation was investigated in this work. The catalytic activity measurements show that the chlorine-free Pt/CeO2(Pt(NO3)2) catalyst with Pt(NO3)2 precursor showed better catalytic activity than the chlorine-free Pt/CeO2((EA)2Pt(OH)6) catalyst with (EA)2Pt(OH)6 precursor; moreover, the activity of chlorine-free Pt/CeO2 catalysts were obviously superior than that of the chlorinated Pt/CeO2(H2PtCl6) catalyst with platinum precursor of H2PtCl6, which because of the presence of chloride ions resulting from H2PtCl6 precursor increased the formation of surface Ce-O-Cl species and diminished the promoter effect of ceria support. The H2-temperature programmed reduction results indicate that, the Pt(NO3)2 precursor exhibited stronger metal-support interaction with CeO2 support than the (EA)2Pt(OH)6 precursor, and hence the Pt/CeO2(Pt(NO3)2) showed lower reduction temperature and better catalytic behaviors than the Pt/CeO2((EA)2Pt(OH)6) catalyst.
CATEGORIZING DECISION MAKING UNITS BASED ON MULTI-LEVEL FRONTIERS IN DATA ENVELOPMENT ANALYSIS

This study comments on the data envelopment analysis (DEA) approach which was presented to grade countries/territories by Yang et al. (2016) [Yang, G. -l. , Ahlgren, P., Yang, L. , Rousseau, R. , & Ding, J. (2016). Using multi-level frontiers in DEA models to grade countries/territories. Journal of Informetrics, 10, 238–253]. We show the fundamental problem of their approach and propose a DEA approach to tackle this problem.
Running head: PHYSIOLOGICAL THREAT AND NUMBER PROCESSING Physiological threat responses influence number processing

Being able to process numbers – such as solving a math task or roughly comparing product prices – is a key competency. Yet, previous research suggests that negative affective responses, such as math anxiety or experienced threat towards numbers, reduce performance. However, such research mainly relied on self-report measures. The present research sought to go one step further by investigating how physiological responses indicative of threat predict math performance. Individuals’ physiological responses while solving a task reflect whether they evaluate the task as exceeding or matching their personal resources (i.e., respond to the task as a threat vs. challenge), and these responses in turn predict subsequent performance. We thus assumed that the more individuals exhibit a threat (rather than challenge) physiological response to a numerical task, the worse they would perform on this task. Results of an experiment with cardiovascular indicators of threat vs. challenge (i.e., measuring the efficiency of blood transportation) supported this assumption. The findings thereby contribute to an understanding of how threat responses to numerical tasks can hinder performance and provide first indications how such performance decrements might be mitigated. (181 words)
Single image HDR reconstruction using a CNN with masked features and perceptual loss

Digital cameras can only capture a limited range of real-world scenes' luminance, producing images with saturated pixels. Existing single image high dynamic range (HDR) reconstruction methods attempt to expand the range of luminance, but are not able to hallucinate plausible textures, producing results with artifacts in the saturated areas. In this paper, we present a novel learning-based approach to reconstruct an HDR image by recovering the saturated pixels of an input LDR image in a visually pleasing way. Previous deep learning-based methods apply the same convolutional filters on wellexposed and saturated pixels, creating ambiguity during training and leading to checkerboard and halo artifacts. To overcome this problem, we propose a feature masking mechanism that reduces the contribution of the features from the saturated areas. Moreover, we adapt the VGG-based perceptual loss function to our application to be able to synthesize visually pleasing textures. Since the number of HDR images for training is limited, we propose to train our system in two stages. Specifically, we first train our system on a large number of images for image inpainting task and then fine-tune it on HDR reconstruction. Since most of the HDR examples contain smooth regions that are simple to reconstruct, we propose a sampling strategy to select challenging training patches during the HDR fine-tuning stage. We demonstrate through experimental results that our approach can reconstruct visually pleasing HDR results, better than the current state of the art on a wide range of scenes.
Robotic Unicycle Intelligent Robust Control Pt I: Soft Computational Intelligence Toolkit

1. Dubna State University, Institute of system analysis and management, Dubna, Moscow, 141980, Russia 2. INESYS LLC (EFKO GROUP), Ovchinnikovskaya naberezhnaya 20, Bld 1, Business Centre “Central City Tower”, Moscow, 115035, Russia 3. NUST MISIS IYS Lab, Leninskiy prospekt 4, Moscow, 119049, Russia 4. Dept. of Mechanical and Intelligent Control Eng., University of Electro-Communications, 1-5-1 Chofu, Chofugaoka, 182 Tokyo, Japan
Public Attitudes Towards the Role of the State and the Private Provision of Training: Evidence from the Swiss Apprenticeship System

Existing empirical research shows that a substantive fraction of Swiss training firms is willing to incur considerable net training costs. One potential explanation for such behavior is that firms act in accordance with the norms and expectations they are faced with in the local labor market they are operating in. In the research described in this paper we ask whether the norm towards the private, rather than the public, provision of public goods influences the probability that a firm is willing to offer apprenticeship positions. In line with our hypothesis, we find that the training incidence is higher in communities which are characterized by a stronger norm towards the private, rather than the public, provision of public goods, which we measure using local results from several national-level votes which explicitly dealt with the proper role of the state in the context of the apprenticeship system. This finding turns out to be robust to a series of robustness checks as well as to an instrumental-variable strategy that tackles the issue of potential endogeneity of public attitudes. JEL classification: D22; D63; H41; I22; J24
NUMERICAL ANALYSIS OF FUEL MIXING PHYSICS IN GAS TURBINE COMBUSTOR

Combustion physics is a vital challenge for the gas turbine designers. The requirement of reduced emission is in global demand by combustor manufacturers of both aeronautical application and power generation. Due to challenges of cost involved in combustor testing and measurement, it is imperative for a designer to use numerical simulation technique to get insight of the complex physics and ensure better design to meet low emission requirements. Here, attempt is made to investigate the effect of suitability of the numerical models for design analysis on achieving better fuel mixing efficiency on a scaled down model of gas turbine combustor.
Rat liver mitochondrial carnitine palmitoyltransferase-I, hepatic carnitine, and malonyl-CoA: Effect of starvation

Abstract Hepatic mitochondrial fatty acid oxidation and ketogenesis increase during starvation. Carnitine palmitoyltransferase I (CPT-I) catalyses the rate-controlling step in the overall pathway and retains its control over β-oxidation under fed, starved and diabetic conditions. To determine the factors contributing to the reported several-fold increase in fatty acid oxidation in perfused livers, we measured the Vmax and Km values for palmitoyl-CoA and carnitine, the Ki (and IC50) values for malonyl-CoA in isolated liver mitochondria as well as the hepatic malonyl-CoA and carnitine contents in control and 48 h starved rats. Since CPT-I is localized in the mitochondrial outer membrane and in contact sites, the kinetic properties of CPT-I also was determined in these submitochondrial structures. After 48 h starvation, there is: (a) a significant increase in Ki and decrease in hepatic malonyl-CoA content; (b) a decreased Km for palmitoyl-CoA; and (c) increased catalytic activity (Vmax) and CPT-I protein abundance that is significantly greater in contact sites compared with outer membranes. Based on these changes the estimated increase in mitochondrial fatty acid oxidation is significantly less than that observed in perfused liver. This suggests that CPT-I is regulated in vivo by additional mechanism(s) lost during mitochondrial isolation or/and that mitochondrial oxidation of peroxisomal β-oxidation products contribute to the increased ketogenesis by bypassing CPT-I. Furthermore, the greater increase in CPT-I protein in contact sites as compared to outer membranes emphasizes the significance of contact sites in hepatic fatty acid oxidation.
Evaluation of cyanobacteria biomass derived from upgrade of phycocyanin fluorescence estimation

The number of harmful cyanobacterial blooms has increased significantly at the global level in recent years. One of the characteristics of cyanobacteria that gives them advantage over other phytoplankton organisms are auxiliary photosyntheticpigments, such as phycocyanin. This fluorescent pigment emits light at a different wavelength as chlorophyll and can therefore be used for detection of cyanobacteria in situ. In this study we used submersible phycocyanin fluorescence sensors and compare their voltage output to concentration of extracted phycocyanin, cell counts and biovolume. The relation was linear in all three cases; however, the variability of regression line slopes between different cyanobacteria strains was high in the case of PC extract concentration and cell count. The highest uniformity in the linear fits was between fluorescence signal and biovolume therefore making it the best candidate for fluorescence sensor voltage output conversion. In the context of this work we also compared different methods for PC extraction. Modifying the equations by subtracting the absorption at 750 nm almost entirely reduces the false PC concentration estimation due to sample turbidity.
Process analytical technology tools for process control of roller compaction in solid pharmaceuticals manufacturing

Abstract This article presents an overview of using process analytical technology in monitoring the roller compaction process. In the past two decades, near-infrared spectroscopy, near-infrared spectroscopy coupled with chemical imaging, microwave resonance technology, thermal effusivity and various particle imaging techniques have been used for developing at-, off-, on- and in-line models for predicting critical quality attributes of ribbons and subsequent granules and tablets. The common goal of all these methods is improved process understanding and process control, and thus improved production of high-quality products. This article reviews the work of several researchers in this field, comparing and critically evaluating their achievements.
Presenting a Conceptual Model of Adopting Micro-Blogging in Learning

Mohmmadhiwa Abdekhoda Associate Professor, Department of Medical Library and Information Sciences, School of Health Management and Medical Informatics, Tabriz University of Medical Sciences. Iranian Center of Excellence in Health Management (ICEHM), School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran. ORCID: 0000-0002-1797-8916. E-mail: hiwaabdekhoda@gmail.com
Improving Parsing Performance for Arabic PP Attachment Ambiguity

Prepositional phrase attachment ambiguity is a pervasive problem in natural language parsing. Whereas attachment ambiguity in English has been the subject of rigorous studies, and signiﬁcant progress has been made, other languages have not beneﬁted from the same attention. We analyze attachment ambiguity in Arabic by ﬁrst developing a comprehensive evaluation metric. Next, the performance of two publicly-distributed Arabic parsers is compared using stock conﬁgurations. Finally, we use linguistic analysis to ﬁnd new features that improve both attachment ambiguity and overall parsing performance. The best feature set achieves 80.14% F1, a 1.47% improvement over the baseline. Most importantly, our approach yields a 7.7% F1 improvement in Arabic construct NP attachment contexts.
Glucose concentration does not affect degradation of a protein that aberrantly engages the endoplasmic reticulum translocon

Description Approximately one third of eukaryotic proteins enter the endoplasmic reticulum (ER) en route to their subcellular or extracellular destinations Many of these proteins use the Sec61p translocon complex to cross the ER membrane (Aviram 2017). Proteins that persistently engage the translocon prevent other proteins from reaching the ER Thus, cells have evolved multiple quality control mechanisms to degrade proteins that aberrantly occupy this channel In ER-associated degradation of translocon-associated proteins (ERAD-T), such polypeptides are targeted for destruction by homologs of the ER-resident RING (really interesting new gene) domain ubiquitin ligase Hrd1p. Deg1*-Sec62 is an engineered model translocon-associated substrate for Hrd1p in yeast (Figure 1A). Analogously, in mammalian cells, the Hrd1p homolog gp78 promotes turnover of the low-density lipoprotein (LDL) component apolipoprotein B, which stalls in the translocon if it is unable to associate with LDL lipid molecules (Fisher et al. 2011). We recently discovered that degradation of Deg1*-Sec62 is impaired by ER stress (the accumulation of misfolded or unfolded proteins in the ER). Deg1*-Sec62 is strongly stabilized by treatment with dithiothreitol (DTT; which reduces disulfide bonds) or tunicamycin (which prevents N-linked glycosylation). By contrast, however, Deg1*-Sec62 degradation is unaffected by perturbation of ER membrane lipid composition (i.e. inositol limitation) or treatments expected to broadly perturb
Editorial

Evolutionary robotics (Cliff et al. 1993; Nolfi and Floreano, 2000) is the study and application of autonomous robots developed through a self-organizational method based on artificial evolution. This approach stresses the importance of the study of systems that: (1) have a body and are situated in a physical environment, and (2) autonomously develop their own skills in close interaction with the environment. Over the last ten years, or more, Evolutionary Robotics has attracted the interest of a large community of researchers with different research interests and backgrounds, ranging from AI and robotics, to biology and cognitive science, to the study of social behavior. Continuous progress in evolutionary robotics has led to a substantial maturation of the field and a clearer understanding of its potential and of its current limitations. The contributions of this special issue cover many of the most interesting research directions currently investigated in the field. For other important topics, not covered or only partially covered in this special issue, the reader might consult: co-evolution of morphology and control (Pollack et al., 2001; Bongard & Pfeifer, 2003), evolution and learning (Nolfi & Floreano, 1999; Floreano & Urzelai, 2001; Tuci et al., 2003), integration of sensory-motor information over time (Nolfi and Marocco, 2001; Nolfi, 2002; Ziemke & Thieme, 2002; Beer, 2003), homeostasis (Di Paolo, 2000), evolution of collective behaviors (Baldassarre et al., 2003, 2004; Quinn et al., 2003), emergence of communication and language (Quinn, 2001; Marocco et al., 2003).