Miracle-dz/UniFAR-FTUs huggingface dataset:
A method for primary proton spectrum measurement at Eo >= 10 PeV with SPHERE-2 telescope

A new method for selecting a certain part of the proton-induced events from the bulk of the primary nuclei events is presented. The method uses the shape of EAS Cherenkov light lateral distribution (CLLD) and is based on a few hundreds of artificial events by 10-30 PeV protons and helium nuclei simulated with CORSIKA/QGSJET-I/QGSJETII code. Distribution of the proton CLLD steepness parameter has a long tail which is absent in helium distribution. The tail contains about 10% of the proton sample which could be distinguished from other nuclei events. The method was adapted to the geometry and conditions of SPHERE-2 telescope and proved to be capable of proton event selection.
Modelling and model predictive control for a bicycle-rider system

ABSTRACT This study proposes a bicycle-rider control model based on model predictive control (MPC). First, a bicycle-rider model with leaning motion of the rider’s upper body is developed. The initial simulation data of the bicycle rider are then used to identify the linear model of the system in state-space form for MPC design. Control characteristics of the proposed controller are assessed by simulating the roll-angle tracking control. In this riding task, the MPC uses steering and leaning torques as the control inputs to control the bicycle along a reference roll angle. The simulation results in different cases have demonstrated the applicability and performance of the MPC for bicycle-rider modelling.
Comparative Analysis of Medium Term Load Forecasting using Genetic Algorithm and Particle Swarm Optimization

The forecasting of electrical energy provides the required information about future conditions of the network to the system engineers and helps to predict essential improving actions such as putting power plants at their maximum production, electricity purchasing, switching etc. It is essential for the booking of fuel supply and maintenance activities and making arrangements for utility power exchange. With the ongoing advancement of new numerical, mining and man-made reasoning devices, it is potentially feasible to enhance the result.
Spatially Connected Artificial Neural Network

: A spatially connected artificial neural network (ANN) is proposed. The ANN parameters are tuned using particle swarm optimization. Architecture of the ANN is determined by proximity of node inputs to node outputs. The inputs and outputs of nodes have assigned locations in space during training. During inference, the nodes may retain locations of inputs and outputs or only retain information about connectivity and weights.
Energy performance optimization in buildings: A review on semantic interoperability, fault detection, and predictive control

The building sector accounts for about 30% of the global final energy consumption. Most of the consumed energy originates from fossil fuels. The operation of buildings is known to suffer from various deficiencies, degrading their energy performance. An untapped potential lies, therefore, in the optimization of building operation to significantly reduce CO2 emissions and to increase the cost effectiveness and user comfort. Over the past 40 years, extensive research has been carried out to investigate and develop methods for building performance optimization based on measured data from building services, such as heating, ventilation, air conditioning, and lighting systems. The ongoing digitalization trend in the building sector offers the opportunity to easily access large amounts of high-quality measurement data and semantic building information as digital descriptions. This facilitates the development and implementation of automated routines for the continuous supervision and optimization of building operation, including reliable fault detection and diagnosis and model-predictive control. This review article is focused on three major research topics in the field of energy-efficient buildings, namely, semantic interoperability between heterogeneous and complex systems, methods for fault detection and diagnosis, and model-predictive control.
Defect Detection of Mechanical Design Products Using Deep Neural Network

In industrial production, defect detection is one of the key methods to control the quality of mechanical design products. Although defect detection algorithms based on traditional machine learning can greatly improve detection efficiency, manual feature extraction is required and the design process is complicated. With the rapid development of CNN, major breakthroughs have been made in computer vision. Therefore, building a surface defect detection algorithm for mechanical design products based on DCNNs plays a very important role in improving industrial production efficiency. This paper studies the surface defect detection algorithm of mechanical products based on deep convolutional neural network, focusing on solving two types of problems: defect recognition and defect segmentation. Aiming at the problem of defect recognition, this paper studies a defect recognition algorithm based on fully convolutional block detection. This algorithm introduces the idea of block detection into the ResNet fully convolutional neural network. While realizing the local discrimination mechanism, it overcomes the shortcomings of the traditional block detection receptive field. Compared with the original ResNet image classification algorithm, this algorithm has stronger generalization ability and detection ability of small defects. Aiming at the problem of defect segmentation, this paper studies a defect segmentation algorithm based on improved Deeplabv3+.
Design Considerations And ManagementTechniques For Enhancing Software QualityOf Real-time Systems

Software quality is a primary concern for both software development organizations and software user, especially in the area of a real-time software system . In this paper, we propose a software design methodology based on function decomposition and implementation considerations to obtain a reliable software in our real-time switching system. We suggest some specific metrics to be used for finding error-prone modules, whose metrics are the obtainable attributes from the characteristics of function structure and the function scenario sequence chart during design phase. By earlier identifying and ranking of error prone functions according to their error proneness based on our model, their software quality can be considerably improved. In addition, a control mechanism for effectively managing software change considering function error proneness during overall system life cycle is briefly presented.
Role for NK Cells Inflammatory Response Reveals a Critical A Fatal Cytokine-Induced Systemic

The mechanism of cytokine-induced shock remains poorly understood. The combination of IL-2 and IL-12 has synergistic antitumor activity in vivo, yet has been associated with signiﬁcant toxicity. We examined the effects of IL-2 plus IL-12 in a murine model and found that the daily, simultaneous administration of IL-2 and IL-12 resulted in shock and 100% mortality within 4 to 12 days depending on the strain employed. Mice treated with IL-2 plus IL-12 exhibited NK cell apoptosis, pulmonary edema, degenerative lesions of the gastrointestinal tract, and elevated serum levels of proinﬂammatory cytokines and acute phase reac-tants. The actions of TNF- a , IFN- g , macrophage-inﬂammatory protein-1 a , IL-1, IL-1-converting enzyme, Fas, perforin, inducible nitric oxide synthase, and STAT1 did not contribute to the observed toxicity, nor did B or T cells. However, toxicity and death from treatment with IL-2 plus IL-12 could be completely abrogated by elimination of NK cells. These results suggest that the fatal systemic inﬂammatory response induced by this cytokine treatment is critically dependent upon NK cells, but does not appear to be mediated by the known effector molecules of this cellular compartment. These data may provide insight into the pathogenesis of cytokine-induced shock in humans. The Journal of Immunology, 1999, 162: 4943–4951.
Garlic is one of the Most Popular Herbal Remedies

Introduction: Hyperlipidemia, either primary or secondary causes atherogenetic abnormalities leading to coronary artery disease, cardiac arrest and arrhythmias. Herbal therapy for prevention or cure of Hyperlipidemia is replacing allopathic medicine due to their bioequivalence and good compliance features. This study was conducted to compare hypolipidemic effects of Garlic and Nigella sativa. Place of Study: Study was conducted at Jinnah Hospital Lahore from July 2013 to December 2013. Seventy-five hyperlipidemic patients were enrolled after being written consent, which was approved by Ethics committee of the hospital. Grouping: They were divided in three equal groups comprising 25 patients in each group. Group-A was treated by Nigella Sativa, Group-B was advised to take Garlic 10 grams twice daily for two months. Group-C was on placebo. Results: After two months therapy it was observed by statistical analysis that Nigella sativa decreased total cholesterol 12.4mg/dl, triglycerides 16.7mg/ dl, and LDL cholesterol 27.3mg/dl. HDL rise was 5.2mg/dl. Garlic decreased total cholesterol 17.9mg/dl, triglycerides 19.9mg/dl and LDL cholesterol 14.8mg/ dl. HDL cholesterol rise was 8.0mg/dl. Conclusion: It was concluded from this study that there is little difference between hypolipidemic effects of two important and famous herbal medicines ie, Nigella sativa and Garlic.
The Effect of Providing Peer Information on Retirement Savings Decisions

Behavior genetics is the study of the relationship between genetic variation and psychological traits. Turkheimer (2000) proposed “Three Laws of Behavior Genetics” based on empirical regularities observed in studies of twins and other kinships. On the basis of molecular studies that have measured DNA variation directly, we propose a Fourth Law of Behavior Genetics: “A typical human behavioral trait is associated with very many genetic variants, each of which accounts for a very small percentage of the behavioral variability. ” This law explains several consistent patterns in the results of gene discovery studies, including the failure of candidate gene studies to robustly replicate, the need for genome-wide association studies (and why such studies have a much stronger replication record), and the crucial importance of extremely large samples in these endeavors. We review the evidence in favor of the Fourth Law and discuss its implications for the design and interpretation of gene-behavior research.
A wide range of cultivated legume species act as alternative hosts for the pea aschochyta blight fungus, Didymella pinodes

Ascochyta blight, caused by the polyphagous fungus Didymella pinodes , is one of the most economically damaging diseases of pea. Susceptibility/resistance of several legume species to several D. pinodes isolates from pea was assessed under controlled environmental conditions to test the hypothesis that D. pinodes was host-speciﬁc. Forty-three cultivars of ﬁve legume species (pea, common vetch, clover, alfalfa and faba bean) typically grown in temperate climates were screened with four pea-infecting isolates from France, and one pea-infecting isolate from Australia. Seven days after inoculation, disease incidence and necrosis were measured on foliar organs to estimate aggressiveness of the isolates. Cultivars of each legume species displayed differential resistance/susceptibility to each isolate as indicated by signiﬁcant cultivar 9 isolate interactions in ANOVA . Faba bean, common vetch, alfalfa and clover cultivars were consistently less susceptible than pea cultivars regardless of the inoculated isolate. The behaviour of D. pinodes isolates also indicated various patterns of disease development according to the legume species and the cultivars. Genetic distance between the ﬁve legume species was not correlated with overall differences in susceptibility, indicating that D. pinodes is not specialized to pea and shows a wide host range among legume species. Disease risk assessment in the pea crop should therefore consider the vicinity of cultivated and wild legume species that may serve as alternative hosts for D. pinodes . signiﬁcant. Variation in resistance among cultivars within each host species was estimated using a single D. pinodes isolate, Dp 1. Finally, association between disease severity and disease incidence on foliar organs was tested by Pearson correlation analy- sis.
Isotypes 2 Function of Some Secretory Phospholipase A Enhancement of Mast Cell Survival: A Novel

This study tested the hypothesis that certain secretory phospholipase A 2 (sPLA 2 ) isotypes act in a cytokine-like fashion through cell surface receptors to inﬂuence mast cell survival. Initial experiments revealed that sPLA 2 activity and sPLA 2 receptor expression are increased, and mast cells lost their capacity to maintain membrane asymmetry upon cytokine depletion. Groups IB and III, but not group IIA PLA 2 , prevented the loss of membrane asymmetry. Similarly, group IB prevented nucleosomal DNA fragmentation in mast cells. Providing putative products of sPLA 2 hydrolysis to cytokine-depleted mast cells did not inﬂuence survival. Furthermore, catalytic inactivation of sPLA 2 did not alter its capacity to prevent apoptosis. Inhibition of protein synthesis using cycloheximide or actinomycin reversed the antiapoptotic effect of sPLA 2 . Additionally, both wild-type and catalytically inactive group IB PLA 2 induced IL-3 synthesis in mast cells. However, adding IL-3-neutralizing Ab did not change Annexin V FITC binding and only partially inhibited thymidine incorporation in sPLA 2 -supplemented mast cells. In contrast, IL-3-neutralizing Ab inhibited both Annexin V FITC binding and thymidine incorporation in mast cells maintained with IL-3. sPLA 2 enhanced phosphoinositide 3 (cid:1) -kinase activity, and a speciﬁc inhibitor of phosphoinositide 3 (cid:1) -kinase reversed the antiapoptotic effects of sPLA 2 . Likewise, sPLA 2 increased the degradation of I- (cid:1) B (cid:2) , and speciﬁc inhibitors of nuclear factor (cid:1) activation (NF- (cid:1) B) reversed the antiapoptotic effects of sPLA 2 . Together, these experiments reveal that certain isotypes of sPLA 2 enhance the survival of mast cells in a cytokine-like fashion by activating antiapoptotic signaling pathways independent of IL-3 and probably via sPLA 2 receptors rather than sPLA 2 catalytic products. The Journal of Immunology, 2001, 167: 4161–4171.
GENETIC ANALYSIS TO IDENTIFY SUITABLE PARENTS FOR DEVOLEPMENT AND RELASE OF NEW TOMATO HYBRIDS COMBINATIONS

A study was conducted on a 7x 7 diallel set of tomato excluding reciprocals to identify desired parents and its cross combinations which appears high productivity and high quality under conditions in Egypt as well as to gather information on genetic behavior of some traits . The results revealed that both general and specific combining abilities were highly significant for all studied traits . therefore, both additive and non additive gene action were important in the expression of these traits . The magnitudes of additive genetic variances were larger than those of the non – additive variances for plant height ,number of branches / plant ,average fruit weight and TSS % . However ,for other traits ,the dominance gene effects play the major role in the inheritance of these traits. Degree of dominance (Ơ 2 D/ Ơ 2 A) 1/2 revealing the importance of partial dominance and that the additive effects played the major role in the inheritance of the plant height ,number of branches / plant ,average fruit weight, fruit shape index and TSS %. Whereas revealing the importance of over dominance in the genetic control of other traits . In addition both broad and narrow sense heritability values were high for all studied traits ,indicating that all traits were highly heritable . Heterosis over mid parents or better parents was present in most of crosses for the studied traits. LHT24 and CLN2498D were good combiner for vegetative traits. Peto 86 was the best combiner for number fruits/ plant and total yield/plant . Marglobe is consider good combiner for average fruit weight and fruit shape index . Advantage 2 was best combiner for TSS. LHT24 breeding after further evaluation.
Identi cation of the Active Constituents and Signi cant Pathways of Bushen Huoxue Decoction for the Treatment of Recurrent Spontaneous Abortion Based on Network Pharmacology

Meihe LI Capital Medical University A liated Beijing Hospital of Traditional Chinese Medicine: Beijing Hospital of Traditional Chinese Medicine Jinping WU 521 hospital of norinco group Minchao KANG Xi'an jiaotong University health science center Ying XU xi'an jiaotong university second a liated hospital Xin XU capital medical university of Beijing traditional Chinese Medicine hospital Huimin DANG (  wbb.23@163.com ) Xi'an Jiaotong University Second A liated Hospital
Energy Efficient 2-Tiers Weighted in-Sensor Data Cleaning

— Managing efficiently the battery and power consumption became a major challenge in sensor networks. Data transmission is very costly in terms of energy which leads to think of a data cleaning technique in order to reduce the size of packets sent to the sink. However, the quality of the information should be preserved during the in-network transmission. This paper introduces a tree-based bi-level periodic data cleaning approach implemented on the source node and the aggregator levels. Our contribution in this paper is two folds. First we look on a periodic basis at each data measured and periodically clean it while taking into consideration the number of occurrences of the measures captured which we shall call weight. A data cleaning is performed between groups of nodes on the level of the aggregator which, contains lists of measures along with their weights. This algorithm will not tolerate the effect of the information that each data measurement provides by preserving the weight of each measure. The experimental results show the effectiveness of this technique in terms of energy efficiency and quality of the information by focusing on a periodical data cleaning while taking into consideration the weight of the data captured.
Reliability Evaluation of Erasure Coded Systems under Rebuild Bandwidth Constraints

—Modern storage systems employ erasure coding redundancy and recovering schemes to ensure high data reliability at high storage efﬁciency. The widely used replication scheme belongs to this broad class of erasure coding schemes. The effectiveness of these schemes has been evaluated based on the Mean Time to Data Loss ( MTTDL ) and the Expected Annual Fraction of Data Loss ( EAFDL ) metrics. To improve the reliability of data storage systems, certain data placement and rebuild schemes reduce the rebuild times by recovering data in parallel from the storage devices. It is often assumed that there is sufﬁcient network bandwidth to transfer the data required by the rebuild process at full speed. In large-scale data storage systems, however, the network bandwidth is constrained. This article obtains MTTDL and EAFDL of erasure coded systems analytically for arbitrary rebuild time distributions and for the symmetric, clustered, and declustered data placement schemes under network rebuild bandwidth constraints. The resulting reliability degradation is assessed and the results obtained establish that the declustered placement scheme offers superior reliability in terms of both metrics. Efﬁcient codeword conﬁgurations that achieve high reliability in the presence of network rebuild bandwidth constraints are identiﬁed.
Design and Comparison of Two Multilevel Converters for Flicker Compensation

Abstract The paper is concerned with the design of multilevel converters for compensating the flicker on the medium-voltage distribution networks. Two topologies of converters are considered, namely the Diode Clamped MultiLevel Converter (DCMLC) and the Cascade H-bridge MultiLevel Converter (CMLC). By analytical procedure, the current ratings for the semiconductor devices of the converters are determined, and their passive elements are sized up. The main outcome of the study is that the two topologies substantially require the same overall rating for the semiconductor devices, with the exception of the clamping diodes in the DCMLC-based topology. As a counterpart, the latter topology needs a lower overall capacitance.
Open Research ’It’s the ﬁrst scientiﬁc evidence’: Men’s experience of pregnancy conﬁrmation - some ﬁndings from a longitudinal ethnographic study of transition to fatherhood

Background and aims In contrast to women's experiences of motherhood, there has been comparatively little research investigating men's experience of the transition to fatherhood and how changing cultural perspectives contribute to the contemporary experience of fathering. This paper draws on the findings of a larger ethnographic study of men’s transition to fatherhood in the United Kingdom (UK) and discusses men's experiences of pregnancy confirmation. Methods
Impact of vehicle automation and electric propulsion on production costs for mobility services worldwide

Automated driving technology along with electric propulsion are widely expected to fundamentally change our transport systems. They may not only allow a more productive use of travel time, but will likely trigger completely new business models in the mobility market. A key determinant of the future prospects of both existing and new mobility services will be their production costs. Hence, in this research the production costs of various transport modes both today and in an automated-electric future are analyzed. To account for different local contexts, the study is conducted for 17 cities across the globe. The results indicate that high-income countries will benefit the most from vehicle automation, while only smaller changes can be expected in lower-income countries. This is due to the different relative contribution of labor cost to the total cost of current taxi and bus operations. In a likely final state, transportation costs will be largely decoupled from a country’s income level, which will favor productivity in higher-income locations.