Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of capacity and operational scheduling for grid-tied microgrid using pumped-storage hydroelectricity and photovoltaic

This paper deals with the optimization of capacity and operation scheduling for a grid-tied microgrid system. Photovoltaic power system is used as renewable energy source and pumped-storage hydroelectricity is used as energy storage. The physical models of the photovoltaic system and pumped-storage hydroelectricity are developed. The objective function is formulated based on capital and operational costs of individual systems. The constraints for the optimization are defined considering the model of systems, operational limitations, and performance requirements. The capacity and the operation scheduling of the photovoltaic and pumped-storage hydroelectricity are optimized based on the solar insolation data and average load demand tied to the microgrid. The performances required are high renewable energy penetration and low curtailed renewable energy. The optimization problem is solved using the mixed integer linear problem (MILP). With the proposed scheme, the renewable energy penetration ratio achieves 50%, which is acceptable. Moreover, the curtailed renewable energy ratio of 1.22% is obtained, which is very low. Both achievements, the acceptable renewable energy penetration ratio and the low curtailed renewable energy ratio, are the key outcomes of this research.
Thermomechanical analysis of an aircraft tire in cornering using coupled ale and lagrangian formulations

The thermomechanical behavior of an aircraft tire is predicted, using experimental devices, a model based on finite element software and an appropriate method of expressing the heat generated by skid in terms of the local friction coefficient, depending on the temperature. In the thermomechanical model, a steady state mechanical analysis is combined with a transient thermal problem. This combined approach is based on three main computing steps: the deformation step, the dissipation step and the thermal step. The deformation step calculates the stress and the velocity fields, which are used as inputs in the dissipation step to calculate the heat generated due to friction. The internal dissipation is assumed to be negligible. Finally, the thermal step yields new thermal maps based on the heat flux computed in the dissipation step. The coupling is established by updating the friction coefficient in the first two steps.
The design of broadband highly efficient gallium nitride RFPAs used in back-off mode

A requirement for multiple linear RF power amplifiers (RFPA) covering the frequency range 1.5 - 2.8GHz has led to the development of an approach for designing a broadband, linear and highly efficient RFPA operating in output back-off mode (OBO). In addition a 1st pass design flow using NI Microwave Office is described as well as a measurement technique of the input and output impedances of the matching networks prior to RFPA `turn-on'. The effectiveness of this approach is demonstrated using a commercially available discrete 10W GaN on SiC packaged HEMT using a 0.25um process (Triquint T2G6000528) and a 20mil RO4350B PCB dielectric. The fabricated RFPA achieved a peak power of >+40dBm and a peak drain efficiency of >54% over its operating bandwidth. In back off-mode the RFPA achieved an un-corrected linearity of 30dBc and drain efficiency ≥34% when driven with a COFDM 2.5MHz, 9.5dB PAPR modulated signal in the 2.0 - 2.5GHz band.
Mean square stabilization of multi-input systems over stochastic multiplicative channels

This paper deals with the mean square stabilization problem for multi-input networked systems via single packet or multiple packets transmission, where the unreliability of input channels is modeled by a multiplicative white noise. For the single packet case, the critical value (lower bound) of mean square capacity for ensuring mean square stabilization is given by adopting the bisection technique. For the m-parallel multiple packets transmission strategy, a necessary and sufficient condition on overall mean square capacity for mean square stabilization in terms of the Mahler measure or topological entropy of the plant is presented, under the assumption that the given network resource can be allocated among all the input channels. Applications in erasure-type channel and channel with stochastic sector-bounded uncertainty are provided to demonstrate the results.
Moral courage in nursing: A concept analysis

Background: Nursing as an ethical practice requires courage to be moral, taking tough stands for what is right, and living by one’s moral values. Nurses need moral courage in all areas and at all levels of nursing. Along with new interest in virtue ethics in healthcare, interest in moral courage as a virtue and a valued element of human morality has increased. Nevertheless, what the concept of moral courage means in nursing contexts remains ambiguous. Objective: This article is an analysis of the concept of moral courage in nursing. Design: Rodgers’ evolutionary method of concept analysis provided the framework to conduct the analysis. Data sources: The literature search was carried out in September 2015 in six databases: PubMed, CINAHL, Scopus, Web of Science, PsycINFO, and The Philosopher’s Index. The following key words were used: “moral” OR “ethical” AND “courage” OR “strength” AND “nurs*” with no time limit. After applying inclusion and exclusion criteria, 31 studies were included in the final analysis. Ethical considerations: This study was conducted according to good scientific guidelines. Results: Seven core attributes of moral courage were identified: true presence, moral integrity, responsibility, honesty, advocacy, commitment and perseverance, and personal risk. Antecedents were ethical sensitivity, conscience, and experience. Consequences included personal and professional development and empowerment. Discussion and conclusion: This preliminary clarification warrants further exploring through theoretical and philosophical literature, expert opinions, and empirical research to gain validity and reliability for its application in nursing practice.
Scene-Adaptive Vehicle Detection Algorithm Based on a Composite Deep Structure

Existing machine-learning-based vehicle detection algorithms for intelligent vehicles have an obvious disadvantage in that the detection effect decreases dramatically when the distribution of training samples and the scene target samples do not match. To address this issue, a scene-adaptive vehicle detection algorithm based on a composite deep structure is proposed in this paper. Inspired by the Bagging (Bootstrap aggregating) mechanism, multiple relatively independent source samples are first used to build multiple classifiers and then voting is used to generate target training samples with confidence scores. The automatic feature extraction ability of deep convolutional neural network is then used to perform source-target scene feature similarity calculations with a deep auto-encoder in order to design a composite deep-structure-based scene-adaptive classifier and its training method. Experiments on the KITTI data set and a data set captured by our group demonstrate that the proposed method performs better than existing machine-learning-based vehicle detection methods. In addition, compared with existing scene-adaptive object detection methods, our method improves the detection rate by an average of approximately 3%.
A bias fault estimation of actuators and sensors by optimization with ℓ0 norm constraint

This paper proposes a bias fault estimation method by a single observer, which is based on the compress sensing. Fault-tolerant control of systems becomes increasingly important to keep safety of systems. The bias fault estimation is one of the most important technologies in fault-tolerant control theory, especially for passive fault-tolerant servo systems. For the bias fault estimation problem, the disturbance observer approach has been proposed. However, this approach cannot be applied to the estimation of all faults at both actuators and sensors by a single observer. In this paper, a bias fault estimation method based on the compress sensing is proposed. Under the assumption that only one device fault occurs at a time, the bias fault estimation method by a single observer can be formulated as an optimization problem with l0 norm constraint. This paper gives a numerical example to demonstrate the effectiveness of the proposed estimation method.
Applying Cooperative Machine Learning to Speed Up the Annotation of Social Signals in Large Multi-modal Corpora

Scientific disciplines, such as Behavioural Psychology, Anthropology and recently Social Signal Processing are concerned with the systematic exploration of human behaviour. A typical work-flow includes the manual annotation (also called coding) of social signals in multi-modal corpora of considerable size. For the involved annotators this defines an exhausting and time-consuming task. In the article at hand we present a novel method and also provide the tools to speed up the coding procedure. To this end, we suggest and evaluate the use of Cooperative Machine Learning (CML) techniques to reduce manual labelling efforts by combining the power of computational capabilities and human intelligence. The proposed CML strategy starts with a small number of labelled instances and concentrates on predicting local parts first. Afterwards, a session-independent classification model is created to finish the remaining parts of the database. Confidence values are computed to guide the manual inspection and correction of the predictions. To bring the proposed approach into application we introduce NOVA - an open-source tool for collaborative and machine-aided annotations. In particular, it gives labellers immediate access to CML strategies and directly provides visual feedback on the results. Our experiments show that the proposed method has the potential to significantly reduce human labelling efforts.
What Do Software Developers Need to Know to Build Secure Energy-Efficient Android Applications?

Green computing is a growing trend in computing, pursuing the goal of helping software developers to be more aware and produce energy-efficient software. This is especially relevant for battery-powered mobile applications, where a minimal energy consumption is desired to both mitigate the greenhouse effect and extend the battery lifetime. In this paper, we analyze the energy consumption and execution time of cryptographic primitives in Android devices. Our ultimate goal is to help Android application developers, especially those who are not experts in security, to choose the most energy-efficient cryptographic algorithms considering different security providers and security transformations. Information to make a tradeoff between energy and time consumption is also provided, being especially useful when the differences in energy consumption of different alternatives are not so significant. We have conducted our experiments with an energy profiling tool based on the PowerTutor application, which has been adapted to automate the energy profiling. Our results show that this type of power consumption studies is necessary, because selecting the most energy-efficient configuration depends on many factors, and some of the choices are not obvious to developers.
Identification of a Large Family of Slam-Dependent Surface Lipoproteins in Gram-Negative Bacteria

The surfaces of many Gram-negative bacteria are decorated with soluble proteins anchored to the outer membrane via an acylated N-terminus; these proteins are referred to as surface lipoproteins or SLPs. In Neisseria meningitidis, SLPs such as transferrin-binding protein B (TbpB) and factor-H binding protein (fHbp) are essential for host colonization and infection because of their essential roles in iron acquisition and immune evasion, respectively. Recently, we identified a family of outer membrane proteins called Slam (Surface lipoprotein assembly modulator) that are essential for surface display of neisserial SLPs. In the present study, we performed a bioinformatics analysis to identify 832 Slam related sequences in 638 Gram-negative bacterial species. The list included several known human pathogens, many of which were not previously reported to possess SLPs. Hypothesizing that genes encoding SLP substrates of Slams may be present in the same gene cluster as the Slam genes, we manually curated neighboring genes for 353 putative Slam homologs. From our analysis, we found that 185 (~52%) of the 353 putative Slam homologs are located adjacent to genes that encode a protein with an N-terminal lipobox motif. This list included genes encoding previously reported SLPs in Haemophilus influenzae and Moraxella catarrhalis, for which we were able to show that the neighboring Slams are necessary and sufficient to display these lipoproteins on the surface of Escherichia coli. To further verify the authenticity of the list of predicted SLPs, we tested the surface display of one such Slam-adjacent protein from Pasteurella multocida, a zoonotic pathogen. A robust Slam-dependent display of the P. multocida protein was observed in the E. coli translocation assay indicating that the protein is a Slam-dependent SLP. Based on multiple sequence alignments and domain annotations, we found that an eight-stranded beta-barrel domain is common to all the predicted Slam-dependent SLPs. These findings suggest that SLPs with a TbpB-like fold are found widely in Proteobacteria where they exist with their interaction partner Slam. In the future, SLPs found in pathogenic bacteria can be investigated for their role in virulence and may also serve as candidates for vaccine development.
3D visualisation of pore structures in cement-based materials by LSCM

The visualisation and representation of three-dimensional (3D) pore morphologies in cement-based materials are of significant interest for understanding the relationship between pore structures and durability. In this study, laser scanning confocal microscopy (LSCM) was used to observe a series of two-dimensional (2D) cross-sectional images. Thresholding was used as the image segmentation technique to group the image pixels by checking the pixel intensities against a set of thresholds. 3D models of the pore structures and the matrix were reconstructed by grey-level interpolation, which transformed the 2D cross-sectional images into 3D models. The experimental results show that the 3D complex morphologic characters of pore structures and the matrix can be accurately visualised with the image segmentation technique and grey-level interpolation.
In vitro Effects of the Specific Mitochondrial TSPO Ligand Ro5 4864 in Cultured Human Osteoblasts

Abstract The 18 kDa mitochondrial translocator protein (TSPO) ligands (10 µM), e. g. , protoporphyrin IX, PK 11195 and FGIN-1-27, have different effects on metabolism and protein expression in human osteoblasts. In this study, we investigated the archetypical TSPO specific ligand Ro5-4864 (10 µM) effect in primary osteoblasts in culture aiming to further understand the TSPO role in these mature metabolically active cells. We found that following exposure to Ro5-4864, cellular [18F]-FDG incorporation and ATP content were reduced by 48% (p<0.001) and 44% (p<0.001), respectively. The mitochondrial membrane potential (ΔΨm) increased by 50% (p<0.01), mRNA synthesis of TSPO and voltage dependent anion channel (VDAC1) decreased both by 70%, the TSPO and VDAC1 protein expression decreased by 80% and 68%, respectively (p<0.001). Ro5 4864 caused a decrease in the proportion of cells in the G1 phase (by 20%, p<0.05), shifting the cell cycle to the S and G2/M phases. Furthermore, 63% decrease in hexokinase 2 protein expression (p<0.001) was found. However, we found no significant effects on hexokinase 2 mRNA expression (by RT-PCR). We also did not see significant changes in mitochondrial mass (MitoTracker Green assay), apoptosis rate (TUNEL assay), overall cell death (LDH assay), cellular proliferation (BrdU assay), cell maturation (cellular alkaline phosphatase assay), and the number of cells in the culture. Therefore, an overall effect of Ro5-4864 exhorts is via pathways related to the mitochondrial activity, which is only partly like PK 11195, but not to the other TSPO ligands.
Mining Suspicious Tax Evasion Groups in Big Data

There is evidence that an increasing number of enterprises plot together to evade tax in an unperceived way. At the same time, the taxation information related data is a classic kind of big data. These issues challenge the effectiveness of traditional data mining-based tax evasion detection methods. To address this problem, we first investigate the classic tax evasion cases, and employ a graph-based method to characterize their property that describes two suspicious relationship trails with a same antecedent node behind an Interest-Affiliated Transaction (IAT). Next, we propose a Colored Network-Based Model (CNBM) for characterizing economic behaviors, social relationships, and the IATs between taxpayers, and generating a Taxpayer Interest Interacted Network (TPIIN). To accomplish the tax evasion detection task by discovering suspicious groups in a TPIIN, methods for building a patterns tree and matching component patterns are introduced and the completeness of the methods based on graph theory is presented. Then, we describe an experiment based on real data and a simulated network. The experimental results show that our proposed method greatly improves the efficiency of tax evasion detection, as well as provides a clear explanation of the tax evasion behaviors of taxpayer groups.
The effect of dissolved impurities on the mechanical properties of ice crystals

Abstract The results obtained from experiments on the mechanical properties of single crystals of ice doped with several impurities are presented. At −70°C, small amounts of dissolved hydrogen flouride (HF) have a pronounced softening effect, ammonia (NH3) produces a slight hardening, and ammonium fluoride (NH4F) has no apparent effect. These results are discussed in terms of Glen's (1968) theory of dislocation movement in ice crystals and a possible explanation of the results is offered.
Meso/Macroporous Carbon Monoliths from Polymeric Foams

The authors present a novel route for the preparation of monolithic carbons with a meso/macroporous structure by templating mesostructured silica monoliths prepared by using macroporous polystyrene foams as structure scaffolds. The carbon skeletal of these materials shows a well-developed and well-structured porosity made up of mesopores and a very large surface area and a high pore volume.
Candidate SNP of CACNA2D1 Gene Associated with Clinical Mastitis and Production Traits in Sahiwal (Bos taurus indicus) and Karan Fries (Bos taurus taurus × Bos taurus indicus)

ABSTRACT The present study was conducted to identify polymorphisms in CACNA2D1 gene and their association with clinical mastitis and production traits. Exon 18 and its flanking regions were screened for the presence of SNPs. Statistical analysis was performed to identify association of period of birth, breed, and genotype with mastitis incidence on randomly selected 103 Sahiwal and 102 Karan Fries cattle. PCR-RFLP analysis revealed that g.38819398G > A mutation in exon 18 (269 bp amplicon) of CACNA2D1 gene resolved into AA, AG, and GG genotypes in Sahiwal and Karan Fries cattle. Wald chi-square analysis revealed that the period of birth, breed, and genotype were significantly associated with mastitis incidence. GG genotyped cattle were found to be less susceptible to mastitis. Least square analysis revealed that GG and AG genotype animals of G38819398A SNP of CACNA2D1 gene in Sahiwal as well as in Karan Fries cattle were associated with higher average milk yields during 1st, 2nd, and 3rd lactations (P < 0.01). These observations and their differential association with the incidence of mastitis and production traits can be utilized as an aid to selection for simultaneous improvement of both antagonistic traits; however, validation of results on large number of animals is warranted.
The p300 and CBP Transcriptional Coactivators Are Required for β-Cell and α-Cell Proliferation

p300 (EP300) and CBP (CREBBP) are transcriptional coactivators with histone acetyltransferase activity. Various β-cell transcription factors can recruit p300/CBP, and thus the coactivators could be important for β-cell function and health in vivo. We hypothesized that p300/CBP contribute to the development and proper function of pancreatic islets. To test this, we bred and studied mice lacking p300/CBP in their islets. Mice lacking either p300 or CBP in islets developed glucose intolerance attributable to impaired insulin secretion, together with reduced α- and β-cell area and islet insulin content. These phenotypes were exacerbated in mice with only a single copy of p300 or CBP expressed in islets. Removing p300 in pancreatic endocrine progenitors impaired proliferation of neonatal α- and β-cells. Mice lacking all four copies of p300/CBP in pancreatic endocrine progenitors failed to establish α- and β-cell mass postnatally. Transcriptomic analyses revealed significant overlaps between p300/CBP-downregulated genes and genes downregulated in Hnf1α-null islets and Nkx2.2-null islets, among others. Furthermore, p300/CBP are important for the acetylation of H3K27 at loci downregulated in Hnf1α-null islets. We conclude that p300 and CBP are limiting cofactors for islet development, and hence for postnatal glucose homeostasis, with some functional redundancy.
Constrained Orientation Control of a Spherical Parallel Manipulator via Online Convex Optimization

This paper introduces a new framework for the closed-loop orientation control of spherical parallel manipulators (SPMs) based on the online solution of a convex optimization problem. The aim of solving a constrained optimization problem is to define a reference position for the SPM that remains as close as possible to the ideal reference (i.e., the one for which the top mobile platform has the desired orientation), at the same time keeping the SPM within the set of configurations in which collisions between links and singular configurations are avoided (the so-called feasible workspace). The proposed approach relies on a recently introduced method for obtaining unique inverse kinematics for SPMs and a newly proposed method for generating an approximation of the feasible workspace suitable for fast online optimization. The proposed control scheme is experimentally tested on an Agile Wrist SPM prototype, confirming the performance expected from the theoretical formulation.