Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimental investigation on the erosion behavior in high-current vacuum arcs and resulting microparticles dynamics

Microparticles are an inevitable component of vacuum arcs. This paper focused on the dynamics of microparticle and erosion behavior in high-current vacuum arcs. The arc was sustained with AC 110 Hz between two butt CuCr alloy contacts with a diameter of 10 mm. An in situ microparticle diagnostic system suitable for vacuum arcs was developed. Three sources of microparticles were observed and the corresponding motion characteristics were obtained by our method. The influence of current and Cr content on erosion characteristics was investigated. The results indicate that the increase of Cr content contributes to inhibiting production of microparticles when the current is small. CuCr30 has the best effect of suppressing microparticle production among the three tested alloy materials under large current. The work of this paper helps with the understanding of microparticle behavior in high-current vacuum arcs and may provide a path for the design of a vacuum electrode.
Towards the understanding at the molecular level of the structured-water absorption and fluorescence spectra: a fingerprint of π-stacked water

An intriguing absorption peak around ∼270 nm (4.59 eV) has been recurrently recorded in aqueous solutions of salts, sugars, amino acids, in the free-solute zone (exclusion zone) adjacent to various hydrophilic surfaces, as well as a transient in the conversion process of ice to water. The corresponding associated fluorescence has been observed in the interval 480–490 nm (2.58–2.53 eV). The spectroscopic features have been related to the presence of structured water but its nature remains incompletely understood. On the basis of high-level ab initio computations, the main absorption feature of structured water is assigned to the presence of two π-stacked ground-state water molecules, preferably non-hydrogen bonded, at relatively short intermolecular distances (around 2 Å). The lowest singlet excited state is characterised by an equilibrium distance of around 2 Å with a vertical absorption transition predicted at 4.5 eV. The excited π-stacked dimer has a large binding energy (∼1 eV). Therefore, near-ultraviolet light may favour the formation of structured water. Two relaxed side-hydrated π-stacked water molecules (a relaxed tetramer) constitute the smallest unique excimer-type fluorescent moiety consistent with the available experimental data.
Adversarial Attacks Technology in Deep Learning Models

Deep learning related to computer vision, speech recognition, and language processing has been developing rapidly over recent years. The applications of these models, however, have underlying risks. Recent studies have shown that small perturbation from adversarial examples could result in false interpretation of the neural network examples and false judgment. Therefore, understanding adversarial example technologies is essential for promoting the safety and robustness of neural network models. This paper summarizes current adversarial example technologies in different applications, discusses the current prospects and challenges, and envision potential future developments in related fields.
Analysis of Subgrade Vibration and Dynamic Stress of Heavy Haul Railway with High Embankment based on ZL-TNTLM Program

Aiming at the high embankment section of heavy-load Railway, a finite element model of dynamic response of subgrade structure under train load is established, and ZL-TNTLM program is used to apply load excitation. The results show that the dynamic stress on the top of the roadbed is a single peak curve under heavy train load, and the peak value of the vertical acceleration vibration changes obviously under heavy train load, and presents a periodic change With the increase of the train speed, the dynamic pressure stress of the track bed and the foundation bed does not increase obviously with the increase of the train speed, but fluctuates and changes slowly; the dynamic stress and the vertical acceleration in the roadbed attenuate non-linearly along the depth direction The attenuation of acceleration is greater than dynamic stress along the direction of subgrade depth. The results are of theoretical and engineering significance for revealing the dynamic stress and vertical acceleration mechanism of heavy-haul railway subgrade under the change of high-speed train speed.
DeltaFS: A Scalable No-Ground-Truth Filesystem For Massively-Parallel Computing

High-Performance Computing (HPC) is known for its use of massive concurrency. But it can be challenging for a parallel filesystem's control plane to utilize cores when every client process must globally synchronize and serialize its metadata mutations with those of other clients. We present DeltaFS, a new paradigm for distributed file system metadata. DeltaFS allows jobs to self-commit their namespace changes to logs, avoiding the cost of global synchronization. Followup jobs selectively merge logs produced by previous jobs as needed, a prin-ciple we term No Ground Truth which allows for efficient data sharing. By avoiding unnecessary synchronization of metadata operations, DeltaFS improves metadata operation throughput up to 98× leveraging parallelism on the nodes where job processes run. This speedup grows as job size increases. DeltaFS enables efficient inter-job communication, reducing overall workflow runtime by significantly improving client metadata operation latency up to 49× and resource usage up to 52×.
The Effects of Hatha Yoga and Specific Balance Exercises in Older Adults Living in Nursing Homes

We tested the effects of Hatha Yoga and specific balance exercises on balance function and fear of falling in older adults living in nursing homes. Twenty-six older adults underwent either Hatha Yoga or simple balance exercises practice. Before, during, and after completing the two programmes, the performance-oriented mobility assessment tool and the Italian version of the falls efficacy scale international were administered to assess participants’ balance function and fear of falling. Hatha Yoga practice yielded significant differences in balance function and fear of falling associated with low falls risk and reduced fear of falling. Specific balance exercises practice yielded significant differences only on balance function but with reduced performance-oriented mobility assessment tool scores associated with a greater falls risk. Accordingly, to improve the quality of life of older adults living in nursing homes, the practice of Hatha Yoga should be encouraged.
GENETIC ANALYSIS OF WET GLUTEN CONTENT IN GRAIN IN DIALLEL CROSS OF DURUM WHEAT

In the period 2014-2016, a diallel cross design was performed and harvested without the reciprocal crosses. The study includes five modern durum wheat varieties: Victoria (BG), Deni (BG), Superdur (AT), Progress (BG), Predel (BG). Parents and hybrids were sown by block method with three replications in the experimental field of the Field Crops Institute in Chirpan, Bulgaria. The trait studied was wet gluten content in grain. The results of the technological analysis were statistically processed by Hayman Jinks methods. Both the additive and dominant parameters have influenced the inheritance of the studied character. The dominant parameters are higher and they have a greater role in inheritance. To increase the wet gluten content, recessive genes are accumulated in the genotype. Heritability coefficients indicate that efficient genotype selection is possible by phenotype, but it should start in the later segregated generations. The graphical analysis points out that the trait is under the control of an additive-dominant genetic system with manifestations of epistasis. In all cases the epistasis is of a complementary type with involved overdominance.
Image-to-Recipe Translation using Multi-model Architecture

5Assistant Professor, Department of Computer Science and Engineering, Sir M. Visvesvaraya Institute of Technology, VTU, Bengaluru, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Food photography has become a very popular trend in this era. Social media sites are flooded with images of food every day. Many people will not be able to figure out what dish it is, and it will be extremely difficult to determine it accurately. There are many diet-conscious people who also face the same problem. So, there was a need for a system that provides the details of any dish. Hence, we will use image processing to process an input image, classification methods and convolutional neural networks to implement a system that will be able to classify and label the unique ingredients in the picture, and finally, give the recipe of a dish. As the largest freely accessible collection of recipe data, Recipe1M offers the opportunity to train high-capacity models on aligned, multimodal data. Furthermore, we demonstrate that regularization by introducing a high-level classification technique improves retrieval overall performance to rival that of humans and also empowers semantic vector math.
Essentials OF CLOUD COMPUTING

*,1Department of CSE, ABES Institute of Technology, Ghaziabad (U.P.), India. -----------------------------------------------------------------------------***--------------------------------------------------------------------------------Theoretical Cloud processing is on request as it offers dynamic adaptable asset distribution for reliable and positive administrations in pay-as-you-use way, to Cloud administration clients. For facilitating and conveying administrations over web it has developed as new worldview. Distributed computing pulls in entrepreneurs as it benefits ventures when there is ascend in administration request and disposes of the need of provisioning plan of proprietors. Distributed computing gives gigantic chances to IT industry. This paper is utilized to survey the distributed computing idea, their attributes, design, administration models, arrangement models and difficulties.
Some Limitations of the Degree Day System as Used in Viticulture in California

The average and range in dates of budbreak, bloom, and fruit maturity of five grape cultivars grown in five different climatic regions of California were determined over a period of two to six years. For each cultivar and climatic region, a comparison of the variation in the average number of degree days and duration (in days) for three developmental periods (budbreak to bloom, bloom to fruit maturity (20°Brix), and budbreak to fruit maturity) was made. No statistically significant difference was observed between the two procedures. Determining the number of degree days by digitizing the area under the thermograph curves for five different locations gave degree day values for the period 1 April to 31 October that ranged 6% to 22% lower than the traditional method of mathematically averaging the maximum and minimum temperature per day. For a given cultivar, there were wide differences in the number of degree days required for the developmental periods between the five locations. Possible reasons for these differences are discussed.
Modelling and Simulation of PV Array for Maximum Load Demand at J.C.O.E.T and Grid Interconnection

1-6Student, Dept. of Electrical Engineering, J.C. O.E. T, MS, India ---------------------------------------------------------------------***---------------------------------------------------------------------Abstract This paper presents the modelling and simulation of PV array for maximum load demand at JCOET and grid interconnection. The simulations are carried out for 100 KW PV system using Maximum Power Point Tracking (MPPT) algorithm for capturing the maximum possible power under varying solar irradiance and temperature conditions on MATLAB/Simulink platform. The generated power will be utilized by J.C. O.E. T. & extra power will be transferred to the Grid. The MPPT algorithm (Incremental Conductance) is incorporated in the control strategies employed in the DC-DC boost converter connected between the PV array and the inverter. The simulation results of output power for varying solar irradiance and temperature conditions have been proposed.
Ensemble Learning Technique for Cloud Classification

Automatic cloud classification is one of the important areas of remote sensing for metrological applications. Machine learning and deep learning techniques have been used for automatic classification of the cloud type. Several pretrained models are developed using convolutional neural network (CNN), which is part of deep learning. The classification performance of pretrained networks can be further improved using ensemble methods. Ensemble learning can perform better than single learner. In this paper, we proposed two different ensemble learning techniques: ensemble of CNN and ensemble of classifier. In first approach, CNN ensemble is performed, where the features extracted by two or more CNN are combined together using single classifier. The second method is to ensemble the predictions of different classifiers produced by a single or multiple CNN. The accuracy of cloud classification of the proposed methods has improved compared to without ensemble of pretrained networks.
Optimization of microwave-assisted extraction and the effect of microencapsulation on mangosteen (Garcinia mangostana L.) rind extract

Abstract The effects of optimization of microwave-assisted extraction (MAE) and microencapsulation on the total xanthone content (TXC), total phenolic content (TPC), and antioxidant activity of mangosteen rind extract were studied. Response surface methodology (RSM) was employed with Box-Behnken design to generate fifteen optimization responses by incorporating three independent variables, namely soaking time, solvent-to-feed (S/F) ratio and extraction time. The highest extraction yield (19.43%) was obtained in the third response. TXC and TPC results fitted well, with high R-squared values (0.83-0.91), into the generated models, but not the antioxidant activity data. The interactive effects of S/F ratio and extraction time significantly increased the yields of TXC (46.62 mg α-mangostin/g crude extract) and TPC (46.30 mg gallic acid equivalent/g crude extract), but longer soaking time showed adverse effect. All the results obtained from the optimized models were validated using experimental data which showed desirability index of 0.88. The optimized parameters of MAE were established as 20:1 S/F ratio and 9 min extraction time, without soaking process. Despite the intact morphology of microcapsules observed, spray drying microencapsulation only preserved TXC partially (63.54%) but denatured more than 85% of TPC. Future investigation on the microencapsulation of mangosteen rind extract is required.
Simulation of Brain Nervous System Based on Complex Networks

The aim of the paper is to simulate the brain nervous system based on complex networks. Complex networks provides a new view for brain network, and the brain nervous system can be abstracted to a network. In this paper we delineate the simulation process to brain nervous system by complex network and computer algorithm. By the logical definition, we can abstract the node and edge to set up the brain nervous system networks with the different algorithms. The simulation results imply that it is feasible to simulate brain nervous system network based on complex networks with brain anatomical and functional architectures. © 2014 Elixir All rights reserved ARTIC LE INF O Article h istory: Received: 6 February 2014; Received in revised form: 15 March 2014; Accepted: 23 March 2014;
Creating Intelligent Agents in Game Using Reinforcement Learning

1Student, Dept. of CSE, Galgotias College of Engineering & Technology, UP, India 2Student, Dept. of CSE, Galgotias College of Engineering & Technology, UP, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Creating AI agents that act in complex and believable methods in computer games and digital conditions is a tough project. Shaping has functioned admirably in the development of neural systems for AI agents management in generally truthful platforms inclusive of the N.E. R.O(Nothing ever remains obscure) video game, but could be work concentrated. Another arrangement, coevolution, vows to set up molding naturally, yet it is hard to control. In spite of the fact that these two methodologies have been utilized independently before, they're well matched on a basic level. This research indicates how system learning algorithms determined creative solutions and surprising new techniques that could transfer to the real world.The significant measure of multifaceted nature and variety on this planet developed because of coevolution and opposition among individuals, directed by herbal determination. At the point when a brand new effective technique or change rises, it modifies the certain assignment conveyance neighbouring retailers need to clear up also, making another weight for adjustment. These transformative firearms races form inevitable auto-curriculars wherein facing sellers constantly creates supplementary commitments to each other. In different words, having AI models compete in an unsupervised manner may additionally be a miles better manner to develop beneficial and robust competencies than letting them toddle around on their own, racking up an abstract wide variety like percentage of environment explored or the like.
Animation, Theory of Mind and Humanoid Robots: Creating a Social Robot Video Task

Abstract Theory of Mind (ToM)—a social cognitive ability commonly underdeveloped in individuals with autism—is necessary to attribute mental states to oneself and others. Research into robot-assisted interventions to improve ToM ability in children with autism has become increasingly popular. However, no appropriate task currently exists to measure the degree of efficacy of robot-assisted interventions targeting ToM ability. The authors demonstrate how animation techniques and principles can be leveraged to develop and produce videos of humanoid robots interacting, which could selectively measure ToM.
Peppermint (Mentha piperita L.) Essential Oil in Systemic and Oral Health

There are indications that ingested peppermint oil can interact with certain prescription medications that are metabolized by the hepatic system, these include cyclosporin and Cytochrome P450 1A2 as well as some anti-depressants, the anti-psychotic drug haloperidol, anti-nausea drugs, the beta-blocker propranolol and hypertensives and angina drugs. There do not appear to be any problems of interactions with medications associated with drinking mint tea or with topical use of peppermint oil.
Distribution of Dye in Elms after Trunk or Root Injection

Acid fuchsin dye, when injected under 1.1 kg/cm2 pressure through hollow, tapered spiles that had been driven into 1.5 cm diameter holes drilled 4 cm deep into elm tree trunks, came up in all the xylem vessel layers intersected by the holes except in the current year's layer of the xylem. When the same dye was injected into comparable trees through the severed ends of roots, however, nearly all of it came up in the xylem vessel layer of the current year. This result may help to account for variable success in controlling Dutch elm disease by trunk injection of fungicides.
Genetic Algorithm Based Hybrid PID Fuzzy Speed Controller in FOCIM

In this paper induction motor speed controlling using FOC with genetic algorithm tuned hybrid PID plus fuzzy controller is discussed. Tuning of PID plus fuzzy speed controller by GA improves static and dynamic performance of FOCIM. Nonlinear induction motor modeling is modeled as linear model for optimization of controller gains. Matlab/Simulink based simulations are carried out with different cases to check efficiency of proposed controller. These results are compared with conventional trial and error method to check improvement in peak overshoot and response time. © 2016 Elixir All rights reserved. Elixir Elec. Engg. 93 (2016) 39737-39743 Electrical Engineering Available online at www.elixirpublishers. com (Elixir International Journal) Veena Kumari Adil and Sanjay Kumar Singhai/ Elixir Elec. Engg. 93 (2016) 39737-39743 39738 Krause‟s model is most popular model of induction motor detailed in [13]. DQ equivalent circuit of induction motor is shown in Fig. 1. Induction motor modeling equations in flux linkage form are given in equation 1-5 as (1)
Water uptake kinetics in soaking of grass pea

Grass pea (Lathyrus sativus L.) belongs to Leguminosae botanical family, also called Fabaceae or Papilionaceae (Yadav & Bejiga, 2006). This family has three subfamilies, including Papilionoideae, to which the seed legumes belong. It represents the most economically important group of flowering plants in the human and animal diet (Doyle & Luckow, 2003). From the 187 of the genus Lathyrus, grass pea is the only used as food and is of great economic importance in India, Bangladesh, Pakistan, Nepal and Ethiopia (Campbell, 1997). It is also grown in Central, South and Eastern Europe, West Asia and North Africa. It is a crop that withstands poor soil and extreme environmental conditions, such as drought and flooding. As a result, besides being an essential source of proteins in poor regions, it also has a potential of use in wealthier regions due to the worldwide trend of increasing consumption of vegetable proteins and climate change resulting in changing agricultural conditions. However, care should be taken on an exclusive dependence on grass pea for protein intake, which is undesirable due to the presence of the toxin β-ODAP that is active when a complement of sulphur containing amino acids is not supplied in the diet (Ngudi et al., 2012).
Analysis of Open Source Node.js Vulnerability Scanners

1Student, Department of Computer Science and Engineering, R.V. College of Engineering, Bengaluru, Karnataka, India 2MTS 1, Enterprise Solutions, PayPal Bangalore, Karnataka, India 3Assistant Professor, Department of Computer Science and Engineering, R.V. College of Engineering, Bengaluru, Karnataka, India 4Associate Professor, Department of Computer Science and Engineering, R.V. College of Engineering, Bengaluru, Karnataka, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Today, web developers don’t write the entire code from scratch, rather they rely on many open source components. The widespread use means developers don’t have an in-depth knowledge of how the code exactly works. Often these components are not kept up to date with the latest release and patches. These unmaintained versions add to the security threats. One way of keeping a track of such dependencies is to continuously monitor them with scanning tools. Out of the few open source tools available, Retire.js and Snyk are among the top. Retire.js, is recommended by OWASP (Open Web Application Security Project) for scanning node and JavaScript vulnerabilities. Snyk on the other hand is more feature rich than most other tools and has an extensive vulnerability database. Both these tools come with CLI (command line interface) integration, which provides a benchmark standard for comparison. This paper reviews the tools for both feature-based comparisons (based on existing features) as well as result-based comparisons (based on scanning result). Feature-based comparisons will focus on parameters like user-friendliness, vulnerability database, extent of scanning and features of command line interface of two tools. Result-based comparison will directly compare the result of scans and the vulnerability database of two tools.