bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Vibration Fault Diagnosis Technology of Steam Turbine Unit in Power Plant Based on Wavelet Theory
Authors: Sun Yu , Han Xuhui 
Published: January 2021

Abstract
Aiming at the frequency spectrum characteristics of the vibration of steam turbine generator sets, a fault diagnosis method of steam turbine rotor vibration based on wavelet packet transform is proposed, which can better reflect the spectral components and energy contained in vibration signals than general wavelet transform. Experimental analysis shows that the fault feature extraction method based on wavelet packet analysis and signal energy decomposition can obtain the fault status of steam turbine rotor vibration; according to the frequency spectrum characteristics of different faults, different faults can be identified, so as to perform steam turbine rotor vibration fault diagnosis. This method is more effective than the fault feature extraction method based on Fourier transform and is suitable for mechanical fault diagnosis.
A multi-energy complementary virtual power plant operation optimization model for distributed energy aggregation is considered
Authors: Qu Xiaoyun , Xiong Xiong , Ji Yu , Zhang Ying , Gong Chuanzheng , Liu Hang 
Published: January 2021

Abstract
In this paper, a stochastic scheduling optimization model of virtual power plant (VPP) is established to maximize the net operating income of VPP considering the loss of uncertain risks. Firstly, the model of conventional scheduling optimization of virtual power plant is presented. Then, the risk conditional value (CVaR) theory is introduced to quantify the operational risk level of VPP, and the constraint conditions containing random variables are converted by the confidence method to establish the risk avoidance scheduling optimization model of VPP. Finally, an improved IIEEE30 node system is used as a simulation system to verify the validity and applicability of the proposed model.
Study on SrNb-Oxide Cathode Material for Low-temperature Solid Oxide Fuel Cell
Authors: Zheng Dan , He Qiong , Gao Ji , Wang Baoyuan 
Published: January 2021

Abstract
In this paper, a novel semiconductor-ionic SrNb oxide (SNO)-Ce0.8Sm0.2O2-δ(SDC) composite has been prepared, characterized and developed as a membrane, which is sandwiched between two layers of Ni-foam coated with Ni0.8Co0.15Al0.05LiO2-δ(NCAL) to construct single layer fuel cell (SLFC, the branch of solid oxide fuel cell). Such a device presented an open circuit voltage (OCV) of 1.03V and maximum power density of 630 mW/cm2 at 550 °C when the mass ratio of SNO to SDC is 1:9. The feasible study of solid oxide in fuel cells will provide experimental and theoretical support for the development of SLFC technology.
Optimization of EDM Electrode by Direct Metal Laser Sintering (DMLS) method for SS316L Material
Authors: Shashank S , Pinto Thomas , Ramachandra C G , Raghavendra M J 
Published: January 2021

Abstract
EDM is one of the methods used in processing. It is a process in which the eroded material starts from the piece with the aid of a series of sparks to obtain the desired shape. It is useful for processing hard metals. The work done by several researchers helps in producing EDM electrodes through SLS, as a different method to conventional processing techniques, and to assess the action of electrodes produced with the technique. Due to this reason, experimental research is carried by SLS out on electrodes made from brass, copper alloy and nickel alloy of bronze and nickel, and steel alloy disintegration of a solid substance. EDM recital is evaluated in terms of material deposition (Vw), which represents the volume of extract from the piece per unit of time (cubic meters per second) and correlative magnitude wear (θ), which shows the relationship between the rate of electrode wear and the rate of material withdrawn. A comparative study between the electrodes produced by SLS and the electrodes made in a conventional manner with respect to SS316L material is made.
Fracture Toughness Measurement of Aluminium and Steel Inserted Aluminium Using Numerical Method
Authors: Kumar Mohan , Londhe Neelakantha V 
Published: January 2021

Abstract
The aim of the current work is to test the possibility of improvement of fracture properties of a shaft fabricated by press fitting a rod inside a tube and explore the effect of interface on the crack propagation. Measurement of Mode II fracture toughness is considered for this purpose. In this study numerical method developed by Yong Li and Viola based on Kienzler and Herrmann’s method by conducting a simple shear test on round bar specimen is adopted. Round bar specimens with a circumferential notch are subjected to shear test. Three specimens are prepared using Al6061T6 alloy tube inserted with rod of three different materials A6061T6 alloy, commercial pure Copper, and AISI1045 steel. Also a plain rod of Al6061T6 alloy is tested under shear to compare the results. Shear tests are conducted on Universal Testing Machine and fracture toughness values are calculated using modified Kienzler and Herrmann’s equations. The results indicated an improvement of 18% in the fracture toughness values in the case of A6061T6 alloy rod inserted A6061T6 alloy tube compared to the fracture toughness of plain A6061T6 alloy rod. And when steel rod is inserted inside the A6061T6 alloy tube an improvement of 33.33% in the fracture toughness.
Impact of Alumina Particulates Addition on Hardness and Wear Behaviour of 2014 Al Metal Matrix Composites by Vortex Method
Authors: Bharath V , Auradi V , Nagaral Madeva , Dayanand Samuel , Boppana Satish Babu 
Published: January 2021

Abstract
In this study, 2014 Al matrix alloy reinforced with a 9 wt% of alumina (20 μm) particulates composites by novel two stage melt stirring (stir casting) practice used to synthesize, describe and analyze wear behaviour. Adding up of reinforcement was kept at 0 and 9wt%. For each wt. % preheated (i.e., 250°C) alumina particles were introduced in to the molten 2014Al alloy in steps of two by creating a vortex to overcome the clustering effects. Produced composite was examined by SEM analysis in support of exploring the microstructures and chemical components. Additionally characterization of wear studies of cast 2014Al matrix alloy and 2014Al-Al2O3 particulate composites were analyzed. After the assessment, it had been seen that there is an improvement in the hardness of the composites prepared and this is due to the incorporation of Al2O3 particulates in 2014Al alloy matrix meanwhile. Additionally, the wear rate of all composites prepared diminishes with increase in sliding distance while the wear rate of the composites prepared enhances with increase in load. By using Scanning Electron Microscope (SEM) the diverse wear mechanism for different test states of various compositions were examined.
Investigation on the Microstructure and Mechanical Properties of Aluminum 7075 Reinforced With Different Weight Percentage of Tungsten Carbide and Cobalt Metal Matrix Hybrid Composites
Authors: Guruchannabasavaiah N G , Auradi Virupaxi , Nandeeshaiah B M , Boppana Satish Babu , Nishanth B N 
Published: January 2021

Abstract
In this paper an effort has made to develop and characterize Al7075 alloy reinforced with Tungsten carbide (WC) & Cobalt (Co). For uniform grain size and homogeneity of the reinforcements with matrix, Cermets (WC-Co) of grain size 50 microns were prepared with the help of ball milling operation. An experiment was conducted to evaluate the microstructure; mechanical properties like hardness test & tensile test as per the standards for different weight percentages of Cermets like 3, 6 and 9wt. %. Micrographs were studied to know the micro structure of the composite material and the result showed the, randomly dispersed reinforcement particles & fine interdendritic precipitates were seen. A comparative study was conducted for the microstructure and mechanical properties by using Cermets with varied weight percentages reinforced with Al7075 matrix. Mechanical properties results reveal that there is a considerable improvement in tensile strength and hardness as the percentage of Cermet increased from 3 to 9wt. %.
Structural Analysis of A Two-Wheeler Disc Brake
Authors: Bhat Adarsh , Pal Bhaskar , Dandotiya Devendra 
Published: January 2021

Abstract
Automotive brakes have come a long way, from drum brakes being widely used for a long time until disc brakes came along and began slowly wiping out the usage of drum brakes. This is primarily due to the number of advantages that the disc-pad setup brings - better stopping distance being one of the most important aspects of any braking system. Apart from this, key advantages of disc brakes over drum brakes include better heat dissipation, fade resistance, self-adjusting ability, compact packaging and so on. Although drum brakes too have certain advantages over disc brakes with lesser cost of manufacturing being one of them, the pure superiority of disc brakes outweighs the few benefits of the drum brakes and this has also reflected in the market. However, there is always scope for improvement when it comes to the structural and thermal characteristics of the brake disc. Researches have been carried out to discover better suited materials and brake disc designs to improve the overall structural and thermal characteristics and reduce uneven wear, squealing etc. The aim of this research is to analyze a new design and material combination based on earlier researches to decrease the deformation and provide a base for improving thermal characteristics.
The effect of Zinc Oxide on Operation of Compression Ignition Engine with EGR fueled with Waste Cooking Oil Biodiesel
Authors: Lobo Ashley , Ramesh D K , Chowdhury Dwaipayan Roy 
Published: January 2021

Abstract
Nanoparticles are being used increasingly along with second and third generation biofuels. One major advantage of nanoparticles is its surface to volume ratio and also the number of active surfaces it possess which make it ideal for application as a catalyst in a chemical reaction or in biodiesel’s case an additive. Zinc Oxide (ZnO) has been employed in the current experimentation as an additive because it improves the properties such as the flash and fire point of the fuel in which it is blended in. Also, ZnO disperses well in fluid and provides advanced theoretical density along with not getting clogged in the fuel pump. In the present work Biodiesel derived from Waste cooking oil-Waste cooking oil methyl ester (WCOME) has been used along with ZnO nanoparticle and the amount of ZnO used is 80 ppm. The engine is also fitted with hot Exhaust Gas Recirculation system in order to decrease the Nitrogen Oxides (NOx) emission. Combustion properties such as Heat Release Rate and P-θ diagram have been thoroughly studied. The performance parameters like Brake Specific Fuel Consumption and Break Thermal Efficiency are also calculated and plotted on graphs for evaluation. Exhaust gases from the engine are measured and the results have been plotted on graphs for comparison. The properties of exhaust gases considered are % of Carbon Monoxide, Nitrogen oxides, Unburnt Hydrocarbons & Smoke Opacity. From the results it was revealed that all 3 parameters: Performance, Combustion & Emissions of the engine was improved by using ZnO as additive.
Mathematical Modeling of Boundary Stress State of Orthotropic Material
Authors: Holovata Sofia , Sokolovskyy Yaroslav , Pobereyko Bohdan , Holovatyy Andriy 
Published: January 2021

Abstract
In the paper, the mathematical model for determination of stress and deformation fields inside and at the elastic region boundary of deformation of orthotropic materials under the biaxial loadings is developed. Within the proposed model, a mathematical model for determination of the material transition boundary from elastic into non-elastic deformation region is developed and a system of nonlinear equations for calculation of the values of its parameters is obtained. By using the continuous method of solution continuation with respect to the best parameter and Runge-Kutta method, the demarcation curves of absolutely elastic and non-elastic deformation regions for the pine tree are constructed. The analysis of the obtained curves is carried out and on its base it is shown that the proposed model, in contrast to the known mechanical theories of strength, makes possible to determine and substantiate the ultimate stress states of materials whose asymmetry coefficients of the boundaries of proportionality in some anisotropy directions are greater, and in others less than one.
The Golden Ratio Regularities of Decayed Oscillations
Authors: Kosobutskyy P , Jaworski N , Farmaha I , Marikutsa U , Iwaniec M 
Published: January 2021

Abstract
This paper develops the method for linear oscillator decayed oscillations amplitude division into two unequal parts by so called golden proportion. It is shown that the relaxation time of the area under the envelope of the oscillations amplitudes and the amplitudes themselves coincide, which indicates that the decay time at the golden ratio plays the same role as the relaxation time. This simplifies the algorithm for optimization of oscillatory systems by objective function.
Nocturnal foraging lifts time constraints in winter for migratory geese but hardly speeds up fueling
Authors: Lameris Thomas K , Dokter Adriaan M , van der Jeugd Henk P , Bouten Willem , Koster Jasper , Sand Stefan H H , Westerduin Coen , Nolet Bart A 
Published: January 2021

Abstract
Climate warming advances the optimal timing of breeding for many animals. For migrants to start breeding earlier, a concurrent advancement of migration is required, including premigratory fueling of energy reserves. We investigate whether barnacle geese are time constrained during premigratory fueling and whether there is potential to advance or shorten the fueling period to allow an earlier migratory departure. We equipped barnacle geese with GPS trackers and accelerometers to remotely record birds’ behavior, from which we calculated time budgets. We examined how time spent foraging was affected by the available time (during daylight and moonlit nights) and thermoregulation costs. We used an energetic model to assess onset and rates of fueling and whether geese can further advance fueling by extending foraging time. We show that, during winter, when facing higher thermoregulation costs, geese consistently foraged at night, especially during moonlit nights, in order to balance their energy budgets. In spring, birds made use of the increasing day length and gained body stores by foraging longer during the day, but birds stopped foraging extensively during the night. Our model indicates that, by continuing nighttime foraging throughout spring, geese may have some leeway to advance and increase fueling rate, potentially reaching departure body mass 4 days earlier. In light of rapid climatic changes on the breeding grounds, whether this advancement can be realized and whether it will be sufficient to prevent phenological mismatches remains to be determined.
DeepCNV: a deep learning approach for authenticating copy number variations
Authors: Glessner Joseph T , Hou Xiurui , Zhong Cheng , Zhang Jie , Khan Munir , Brand Fabian , Krawitz Peter , Sleiman Patrick M A , Hakonarson Hakon , Wei Zhi 
Published: January 2021

Abstract
Copy number variations (CNVs) are an important class of variations contributing to the pathogenesis of many disease phenotypes. Detecting CNVs from genomic data remains difficult, and the most currently applied methods suffer from an unacceptably high false positive rate. A common practice is to have human experts manually review original CNV calls for filtering false positives before further downstream analysis or experimental validation. Here, we propose DeepCNV, a deep learning-based tool, intended to replace human experts when validating CNV calls, focusing on the calls made by one of the most accurate CNV callers, PennCNV. The sophistication of the deep neural network algorithm is enriched with over 10 000 expert-scored samples that are split into training and testing sets. Variant confidence, especially for CNVs, is a main roadblock impeding the progress of linking CNVs with the disease. We show that DeepCNV adds to the confidence of the CNV calls with an optimal area under the receiver operating characteristic curve of 0.909, exceeding other machine learning methods. The superiority of DeepCNV was also benchmarked and confirmed using an experimental wet-lab validation dataset. We conclude that the improvement obtained by DeepCNV results in significantly fewer false positive results and failures to replicate the CNV association results.
Accuracy or novelty: what can we gain from target-specific machine-learning-based scoring functions in virtual screening?
Authors: Shen Chao , Weng Gaoqi , Zhang Xujun , Leung Elaine Lai-Han , Yao Xiaojun , Pang Jinping , Chai Xin , Li Dan , Wang Ercheng , Cao Dongsheng , Hou Tingjun 
Published: January 2021

AbstractMachine-learning (ML)-based scoring functions (MLSFs) have gradually emerged as a promising alternative for protein–ligand binding affinity prediction and structure-based virtual screening. However, clouds of doubts have still been raised against the benefits of this novel type of scoring functions (SFs). In this study, to benchmark the performance of target-specific MLSFs on a relatively unbiased dataset, the MLSFs trained from three representative protein–ligand interaction representations were assessed on the LIT-PCBA dataset, and the classical Glide SP SF and three types of ligand-based quantitative structure-activity relationship (QSAR) models were also utilized for comparison. Two major aspects in virtual screening campaigns, including prediction accuracy and hit novelty, were systematically explored. The calculation results illustrate that the tested target-specific MLSFs yielded generally superior performance over the classical Glide SP SF, but they could hardly outperform the 2D fingerprint-based QSAR models. Although substantial improvements could be achieved by integrating multiple types of protein–ligand interaction features, the MLSFs were still not sufficient to exceed MACCS-based QSAR models. In terms of the correlations between the hit ranks or the structures of the top-ranked hits, the MLSFs developed by different featurization strategies would have the ability to identify quite different hits. Nevertheless, it seems that target-specific MLSFs do not have the intrinsic attributes of a traditional SF and may not be a substitute for classical SFs. In contrast, MLSFs can be regarded as a new derivative of ligand-based QSAR models. It is expected that our study may provide valuable guidance for the assessment and further development of target-specific MLSFs.
Exploring TEAD2 as a drug target for therapeutic intervention of cancer: A multi-computational case study
Authors: Pal Rajesh , Kumar Amit , Misra Gauri 
Published: January 2021

Abstract
Transcriptional enhanced associate domain (TEAD) is a family of transcription factors that plays a significant role during embryonic developmental processes, and its dysregulation is responsible for tumour progression. TEAD is considered as druggable targets in various diseases, namely cancer, cardiovascular diseases and neurodegenerative disorders.
Previous structural studies revealed the importance of the central hydrophobic pocket of TEAD as a potential target for small-molecule inhibitors and demonstrated flufenamic acid (FLU) (a COX-2 enzyme inhibitor) to bind and inhibit TEAD2 functions. However, to date, no drug candidates that bind specifically to TEAD2 with high selectivity and efficacy have been developed or proposed.
Within this framework, we present here a case study where we have identified potential TEAD2 inhibitor candidates by integrating multiple computational approaches. Among the candidates, the top two ranked compounds ZINC95969481 (LG1) which is a fused pyrazole derivative and ZINC05203789 (LG2), a fluorene derivative resulted in much favourable binding energy scores than the reference ligand, FLU. The drug likeliness of the best compounds was also evaluated in silico to ensure the bioavailability of these compounds particularly LG1 as compared to FLU thus providing a strong rationale for their development as leads against TEAD. Molecular dynamics simulations results highlighted the role of key residues contributing to favourable interactions in TEAD2-LG1 complex with much favourable interaction and binding free energy values with respect to the reference compound. Altogether, this study provides a starting platform to be more exploited by future experimental research towards the development of inhibitors against TEAD, a persuasive strategy for therapeutic intervention in cancer treatment.
Nebulosa recovers single-cell gene expression signals by kernel density estimation
Authors: Alquicira-Hernandez Jose , Powell Joseph E 
Published: January 2021

Abstract

Summary
Data sparsity in single-cell experiments prevents an accurate assessment of gene expression when visualized in a low-dimensional space. Here, we introduce Nebulosa, an R package that uses weighted kernel density estimation to recover signals lost through drop-out or low expression.

Availability and implementation
Nebulosa can be easily installed from www.github.com/powellgenomicslab/Nebulosa.

Supplementary information
Supplementary data are available at Bioinformatics online.
Chronology of Practice: Chinese Practice in Public International Law in 2019*
Authors: Wu Xiaohui 
Published: January 2021

Abstract
This Survey covers materials reflecting Chinese practice in 2019 relating to: treaties, agreements and other documents signed or ratified by the People’s Republic of China; national legislation; statements made by Chinese representatives at the meetings of the UN and other international organizations, international conferences, and those made by the Foreign Ministry spokespersons, with respect to various branches of international law; and judicial decisions, in particular on the applicability and application of international conventions, by Chinese courts.
Phage Origin of Mitochondrion-Localized Family A DNA Polymerases in Kinetoplastids and Diplonemids
Authors: Harada Ryo , Inagaki Yuji 
Published: January 2021

Abstract
Mitochondria retain their own genomes as other bacterial endosymbiont-derived organelles. Nevertheless, no protein for DNA replication and repair is encoded in any mitochondrial genomes (mtDNAs) assessed to date, suggesting that the nucleus primarily governs the maintenance of mtDNA. As the proteins of diverse evolutionary origins occupy a large proportion of the current mitochondrial proteomes, we anticipate finding the same evolutionary trend in the nucleus-encoded machinery for mtDNA maintenance. Indeed, none of the DNA polymerases (DNAPs) in the mitochondrial endosymbiont, a putative α-proteobacterium, seemingly had been inherited by their descendants (mitochondria), as none of the known types of mitochondrion-localized DNAP showed a specific affinity to the α-proteobacterial DNAPs. Nevertheless, we currently have no concrete idea of how and when the known types of mitochondrion-localized DNAPs emerged. We here explored the origins of mitochondrion-localized DNAPs after the improvement of the samplings of DNAPs from bacteria and phages/viruses. Past studies have revealed that a set of mitochondrion-localized DNAPs in kinetoplastids and diplonemids, namely PolIB, PolIC, PolID, PolI-Perk1/2, and PolI-dipl (henceforth designated collectively as “PolIBCD+”) have emerged from a single DNAP. In this study, we recovered an intimate connection between PolIBCD+ and the DNAPs found in a particular group of phages. Thus, the common ancestor of kinetoplastids and diplonemids most likely converted a laterally acquired phage DNAP into a mitochondrion-localized DNAP that was ancestral to PolIBCD+. The phage origin of PolIBCD+ hints at a potentially large contribution of proteins acquired via nonvertical processes to the machinery for mtDNA maintenance in kinetoplastids and diplonemids.