bluuebunny/crossref_metadata_2025_split huggingface dataset:
SMEs Perception towards Adoption of Measurement System Analysis Strategy: A Case Study in Pump Manufacturing Industry
Authors: Varun Kumar T. , Ramya G. , Kowsalya P. , Shanmuga Priya B. , Tharani P. 
Published: October 2020

Abstract
Every industry from large scale to small scale is nowadays seeking for their continuous improvement. It is necessary to compare the performance of the measurement processes with the standard systems. In a typical scenario, one of the two processes represents an attempt to improve the other process, and one must determine if the attempt has been successful. Since repeatability and reproducibility (R&R) studies are often used to determine the adequacy of each measurement process separately, it is suitable to compare the results of these studies to determine if there is any difference in the variability of the two processes. In this paper, we consider R&R studies with two factors of parts and operators. We consider situations where the operator factor can be either random or fixed. Each operator makes repeated measurements on each part in a sample of process output and the different operators are used for each measurement process and the parts used for measurements are the same. A ratio commonly used to determine the adequacy of a single measurement process is used to compare the variability of the two measurement processes. Two statistical tests a result for differences in their ratio depends on their confidence intervals are proposed and compared using computer simulation. Finally, our study enables delegates to assess the performance of new and existing measurement systems.
A review on Friction Stir Welding in Aluminium Alloys
Authors: Stephen Leon J , Bharathiraja G , Jayakumar V 
Published: October 2020

Abstract
Joining of aluminium alloys is always a challenging task due to its easily oxidising property in its molten stage. Although its application is huge in the building of aerospace structure, 2XXX and 7XXX series alloys are categorised as non-weldable aluminium alloys. Recent development in the application of friction stir welding process in the joining of these non-weldable alloys simplified the fabrication processes. In this review article, significance of friction stir welding comparing with other solid state metal joining process is addressed. Recent developments and application of this relatively new metal joining process in various industries are also discussed. Particular emphasis has been given to the mechanism responsible for the formation of this solid state joining technique. Apart from this, major process parameters that influence the formation of weld and weld defects caused by the improper selection of process parameters are also explained in detail.
Influence of Boron Carbide Addition on Particle Size of Copper Zinc Alloys Synthesized by Powder Metallurgy
Authors: Rajeshkumar L. , Suriyanarayanan R. , Shree Hari K. , Venkatesh Babu S. , Bhuvaneswari V. , Jithin Karunan M.P. 
Published: October 2020

Abstract
Material systems with the combination of metals and non-metals forming an alloy systems has numerous advantages when compared with the monolithic materials. Synthesizing such materials systems can easily be done by many solid state processing methods. Copper Zinc (Cu-Zn) forms a ductile material system finding its applications in various conductive and tribological applications. Nano composites finds lot more applications due to the high specific area occupied by the particles. Focus of the current project is on the study of influence of Boron Carbide (B4C) powders addition into the Cu-Zn matrix while synthesizing them through high energy ball milling. B4C powders are added to the matrix at 10 % by volume. Particle size of the powder are determined by Scherer and Williamson-Hall synthesis methods after characterizing the milled powders by X-Ray diffraction (XRD). As the B4C powders are brittle, maximum volume fraction of these powders are expected to influence particle size of Cu-Zn alloy powders. Powder morphology is analysed by scanning electron microscopy (SEM). Influence of B4C powder particles upon grain size of Cu-Zn alloy powder blends was very minimum due to the tendency of particles to get saturated with respect to particle size after repeated milling.
A Review on Submerged Friction Stir Welding of Light Weight Alloys
Authors: Sucharitha M. , Ravi Sankar B. , Umamaheswarrao P. 
Published: October 2020

Abstract
Friction stir welding gained wide acceptance in many industries owing to its capability of joining lightweight materials, the subsequent development to Friction stir welding (FSW) was to submerge workpiece in liquids during welding termed as submerged friction stir welding (SFSW) resulted in improving mechanical properties. However, joint efficiency was much dependent on the process parameters. Hence, the present work aimed to consolidate the research works available in underwater friction stir welding (UFSW) primarily focusing on effect of process parameters on weld joint.
CuO-nano based Biodegradable Refrigeration Oil in R134a Refrigeration Systems for Energy Conservation and Green Environment
Authors: Vithya P. , Sriram G. , Arumugam S. , Aditya Chaitanya M.D.V. , Surya Deepak G. , Sriram Kumar K. , Jayaram Chandra P. 
Published: October 2020

Abstract
The present study experimentally investigated the reliability and performance of a vapour compression refrigeration system with CuO nano based biodegradable refrigeration oil. The pentaerythritol ester biodegradable refrigeration oil (PE) is blended with synthetic refrigeration oil (ISO 68 grade-POE oil) in the fraction of 50% by volume. Nanolubricant was synthesized on the basis of the concept of the nanofliuds, which was prepared by mixing CuO nanoparticles with pentaerythritol ester based biodegradable refrigeration oil blend (PE50). The concentration of nano CuO ranges in the order of 0.1% to 0.3% by weight with particle size of 40 nm to prepare CuO nano biodegradable refrigeration oil. An experimental test rig is designed and fabricated indigenously to carry out the investigations. The results indicated that CuO nano-based biodegradable refrigeration oil works normally and safely in the system. The compressor power consumption was reduced by 5.02% with the use of 0.3% CuO nano biodegradable refrigeration oil. The PE50 with 0.3% CuO nano has a considerable rise in coefficient of performance (COP) of about 45%. Hence CuO nano-based biodegradable refrigeration oil in refrigeration system considerably reduces the energy consumption and increases the COP of the refrigeration system.
Review on Thermal analysis of Polymer Matrix Composites
Authors: Venkatakoteswararao G. , Vinayagamoorthy R. 
Published: October 2020

AbstractNatural fibers are widely used for reinforcement in composite materials and well tried to be effectively exchange fibre strengthened chemical compound composites to some extent in applications like domestic, automotive and lower finish region elements. A few explores have been investigated in last decades to research the conduct of natural fiber composites. The natural fibre strengthened composites are atmosphere friendly, have high strength to weight quantitative relation like artificial optical fiber strengthened composites. Deferential scanning calorimetry (DSC) and Thermogravimetric analysis (TGA) were used to evaluate the thermal properties. TGA is used to measure temperature change and mass loss of samples and DSC enables the measurement of glass transition temperature. This article presents an extensive study on the thermal properties of polymeric composites; the examination on polymeric composites is consistently in the phase of improving the properties.
Effect of Nano Particles on Tribological Behavior of Reciprocating Air Compressor Oil Using Fourball Tribometer: An Experimental Investigation
Authors: Chenga Reddy P. , Arumugam S. 
Published: October 2020

Abstract
This paper presents an experimental investigation of tribological properties of pentaerythritol ester (PE) as biolubricant with the addition of nanoparticles i.e. copper oxide (CuO). The nano particle was added with pentaerythritol ester by wt.% as 0.1, 0.3 and 0.5%. The experimental work was conducted on a fourball tribometer under various conditions such as applied load of 40 kg, speed of 1200 rpm, experimental duration of 1 hr and a temperature of 75°C under the standard of ASTM 4172. The 0.3% PE based nanoparticle lubricant shows the low coefficient of friction (COF), frictional torque (FT) and wear scar diameter (WSD) as compared to other nano based lubricants and with base oil. The tested worn surface was examined with SEM analysis and results are reported that the 0.3% nanoparticle lubricant shows the smoother and low surface roughness.
Eco Friendly Machining Processes for Sustainability - Review
Authors: Rajmohan T. , Kalyan Chakravarthy V.V. , Nandakumar A. , Satish Kumar S.D. 
Published: October 2020

Abstract
Green manufacturing is a style for industrialized that minimizes dissipate and contamination. The pollution prevention resolves in manufacturing industries to expand and execute various environmentally-friendly strategies. The main purpose of green machining is to hold up future generations by attaining sustainability. Cutting fluids are discoloured with metal particles and foulness products which reduce the efficiency of cutting fluids. To minimize the unpleasant environmental effects coupled with the use of cutting fluids, the harmful components from their formulations have to be eliminated or reduced to the acceptable level. In addition, mineral based cutting fluids are going to be replaced with vegetable based cutting fluids since they are environmentally friendly. The present review primarily determined on examining different aspects of machining process from an environmental sensitivity. This paper presents the environmental green machining such as dry machining, machining with minimum quantity lubricant, Cryogenic machining, hot machining, vegetable oil-based cutting fluids and nano filled cutting fluids. The Performance of Eco-friendly machining are discussed in terms of cutting forces, tool flank wear, cutting temperatures and surface finish are also discussed.
Biomass porous carbon-based composite for high performance supercapacitor
Authors: Wang Huilin , Wen Jie 
Published: October 2020

AbstractBiomass porous carbons with abundant pore structure, surface functional groups, and excellent electrical conductivity, are widely used for electrode materials. In this work, biomass carbon with 3D mesh structure was loaded with metal sulfide to synthesize porous carbon-based ultrathin Ni3S2layered nanosheet structure supercapacitor composite material electrode. C/Ni3S2-16 showed 600 F g−1of high specific capacitance with 20 A g−1current density. After 5,000 charge and discharge cycles, 88.8% of the maximum (imital) specific capacitance was maintained at 10 A g−1. The assembled C/Ni3S2-16//C asymmetric supercapacitor achieved an energy density of up to 35.7 Wh Kg−1, which was remained at 27.9 Wh Kg−1with a high power density at 1500 W kg−1. Developed pore structure of biomass porous carbon provide sufficient space for the electrolyte in and out of the electrode, therefore the potentially high electrochemical activity and energy density of the transition metal sulfide were fully exhibited.
The mortality rate of Parkinson’s disease and related comorbidities: a nationwide population-based matched cohort study in Korea
Authors: Yoon Seo Yeon , Shin Jaeyong , Kim Yong Wook , Chang Jee Suk , Won Kim Hye 
Published: October 2020

Abstract

Background
previous studies on mortality of Parkinson’s disease (PD) enrolled a relatively small number of participants and were conducted in western countries. The objective of this study was to evaluate mortality rate of PD using a large nationwide cohort in Korea and to evaluate effects comorbidities have on mortality in PD.

Methods
the nationwide population-based cohort study was conducted using the Korean National Health Insurance Service—National Sample Cohort data. Patients with a primary diagnosis of PD were selected from the database. A matched cohort without PD was enrolled through randomly matching patients by sex, age, year of diagnosis, residential area and income level to the PD group with a ratio of 1:9. The Cox proportional hazard model was used to assess mortality risk between the two cohorts. A logistic regression analysis was used to identify mortality risk factors in PD cohort.

Results
in total, 25,620 patients were enrolled. The Cox proportional regression model had an adjusted hazard ratio of 2.479 [95% confidence interval (CI), 2.272-2.704] for mortality in PD cohort. Comorbidities, such as ischaemic stroke [odds ratios (OR) = 2.314, 95% CI, 1.895-2.824], haemorrhagic stroke (OR = 2.281, 95% CI, 1.466-3.550) and chronic obstructive pulmonary disease (OR = 1.307, 95% CI, 1.048-1.630) were associated with increased mortality, whereas dyslipidemia (OR = 0.285, 95% CI, 0.227-0.358) was negatively correlated with mortality.

Conclusion
over the 10 year follow-up period, the PD cohort’s mortality rate was 2.5 times higher than the comparison cohort. Understanding the effects that comorbidities have on morality in PD would be useful for predicting mortality in patients with PD.
Optimized combination methods for exploring and verifying disease-resistant transcription factors in melon
Authors: Wang Zhicheng , Luan Yushi , Zhou Xiaoxu , Cui Jun , Luan Feishi , Meng Jun 
Published: October 2020

Abstract
A large amount of omics data and number of bioinformatics tools has been produced. However, the methods for further exploring omics data are simple, in particular, to mine key regulatory genes, which are a priority concern in biological systems, and most of the specific functions are still unknown. First, raw data of two genotypes of melon (susceptible and resistant) were obtained by transcriptome analysis. Second, 391 transcription factors (TFs) were identified from the plant transcription factor database and cucurbit genomics database. Then, functional enrichment analysis indicated that these genes were mainly annotated in the process of transcription regulation. Third, 243 and 230 module-specific TFs were screened by weighted gene coexpression network analysis and short time series expression miner, respectively. Several TF genes, such as WRKYs and bHLHs, were regarded as key regulatory genes according to the values of significantly different modules. The coexpression network showed that these TF genes were significant correlated with resistance (R) genes, such as DRP2, RGA3, DRP1 and NB-ARC. Fourth, cis-acting element analysis illustrated that these R genes may bind to WRKY and bHLH. Finally, the expression of WRKY genes was verified by quantitative reverse transcription PCR (RT-qPCR). Phylogenetic analysis was carried out to further confirm that these TFs may play a critical role in Curcurbitaceae disease resistance. This study provides a new optimized combination strategy to explore the functions of TFs in a wide spectrum of biological processes. This strategy may also effectively predict potential relationships in the interactions of essential genes.
COVID-19—Lessons Learned and Questions Remaining
Authors: Fang Ferric C , Benson Constance A , del Rio Carlos , Edwards Kathryn M , Fowler Vance G , Fredricks David N , Limaye Ajit P , Murray Barbara E , Naggie Susanna , Pappas Peter G , Patel Robin , Paterson David L , Pegues David A , Petri William A , Schooley Robert T 
Published: October 2020

AbstractIn this article, the editors of Clinical Infectious Diseases review some of the most important lessons they have learned about the epidemiology, clinical features, diagnosis, treatment and prevention of SARS-CoV-2 infection and identify essential questions about COVID-19 that remain to be answered.
A new water-soluble bacterial NADH: fumarate oxidoreductase
Authors: Bertsova Yulia V , Oleynikov Ilya P , Bogachev Alexander V 
Published: October 2020

ABSTRACTThe cytoplasmic fumarate reductase of Klebsiella pneumoniae (FRD) is a monomeric protein which contains three prosthetic groups: noncovalently bound FMN and FAD plus a covalently bound FMN. In the present work, NADH is revealed to be an inherent electron donor for this enzyme. We found that the fumarate reductase activity of FRD significantly exceeds its NADH dehydrogenase activity. During the catalysis of NADH:fumarate oxidoreductase reaction, FRD turnover is limited by a very low rate (∼10/s) of electron transfer between the noncovalently and covalently bound FMN moieties. Induction of FRD synthesis in K. pneumoniae cells was observed only under anaerobic conditions in the presence of fumarate or malate. Enzymes with the FRD-like domain architecture are widely distributed among various bacteria and apparently comprise a new type of water-soluble NADH:fumarate oxidoreductases.
Phase-velocity inversion from data-based diffraction kernels: seismic Michelson interferometer
Authors: Chmiel Małgorzata , Roux Philippe , Wathelet Marc , Bardainne Thomas 
Published: October 2020

SUMMARY
We propose a new surface wave tomography approach that benefits from densely sampled active-source arrays and brings together elements from active-source seismic-wave interferometry, full waveform inversion and dense-array processing. In analogy with optical interferometry, seismic Michelson interferometer (SMI) uses seismic interference patterns given by the data-based diffraction kernels in an iterative inversion scheme to image a medium. SMI requires no traveltime measurements and no spatial regularization, and it accounts for bent rays. Furthermore, the method does not need computation of complex synthetic models, as it works as a data-driven inversion technique that makes it computationally very fast. In an automatic way, it provides high-resolution phase-velocity maps and their error estimation. SMI can complete traditional surface wave tomography studies, as its use can be easily extended from land active seismic data to the virtual source gathers of ambient-noise-based studies with dense arrays.
A semblance measure for model comparison
Authors: Commer Michael 
Published: October 2020

SUMMARYAlgorithmic and computational advances have made it possible that geophysical survey and earth model design can be aided by many systematic trial inverse-modelling runs with synthetic data. Such may, for example, come up in machine-learning approaches. Automated image appraisal pertaining to such applications will involve common statistical tests for goodness-of-data fit as a primary evaluation method. However, solution non-uniqueness may render multiple images equivalent in terms of their data fit, requiring secondary categorizers. A logical choice for classifying synthetic-imaging results quantifies the goodness of model fit where a known reference model replaces the observational input. The task of model intercomparison in terms of measuring the resemblance to the reference model poses challenges to common distance-based metrics like root mean square error and mean absolute error. First, distance-based metrics can introduce spurious contributions when smooth models with fuzzy target contours are to be compared against a sharp reference. Second, large differences due to parameter-estimation overshoots can dominate distance metrics. The remedy proposed here is referred to as semblance and is based on the idea of logistic functions, where a binary-dependent variable adds non-zero or zero accumulation terms for the, respectively, passing or failing of preset target thresholds. This classifying approach is amenable to an objective where model feature recognition is primary. Numerical comparisons to distance-based metrics provide evidence for the advantages of the semblance in view of this objective. Geophysical imaging in conjunction with machine-learning is seen as a benefitting upcoming application area.
Experimental test of the cooling rate effect on blocking temperatures in stepwise thermal demagnetization
Authors: Berndt Thomas A , Chang Liao , Paterson Greig A , Cao Changqian 
Published: October 2020

SUMMARYUpon cooling, most rocks acquire a thermoremanent magnetization (TRM); the cooling rate at which this happens not only affects palaeointensity estimates, but also their unblocking temperatures in stepwise thermal demagnetization experiments, which is important, for example, to estimate volcanic emplacement temperatures. Traditional single-domain (SD) theory of magnetic remanence relates relaxation times to blocking temperatures— the blocking temperature is the temperature at which the relaxation time becomes shorter than the experimental timescale—and therefore strictly only applies to remanence acquisition mechanisms at constant temperatures (i.e. viscous remanent magnetizations, VRMs). A theoretical framework to relate (constant) blocking temperatures to (time-varying) cooling rates exists, but this theory has very limited experimental verification—partly due to the difficulty of accurately knowing the cooling rates of geological materials. Here we present an experimental test of this ‘cooling rate effect on blocking temperatures’ through a series of demagnetization experiments of laboratory-induced TRMs with controlled cooling rates. The tested cooling rates span about 1 order of magnitude and are made possible through (1) extremely accurate demagnetization experiments using a low-temperature magnetic properties measurement system (MPMS) and (2) the use of a ‘1-step-only’ stepwise thermal demagnetization protocol where the relaxation process is measured over time. In this way the relaxation time corresponding to the blocking temperature is measured, which can be done to much higher accuracy than measuring the blocking temperature directly as done in traditional stepwise thermal demagnetization experiments. Our experiments confirm that the cooling rate relationship holds to high accuracy for ideal magnetic recorders, as shown for a synthetic weakly interacting SD magnetoferritin sample. A SD-dominated low-Ti titanomagnetite Tiva Canyon Tuff sample, however, showed that natural samples are unlikely to be sufficiently ‘ideal’ to meet the theoretical predictions to high accuracy—the experimental data agrees only approximately with the theoretical predictions, which may potentially affect blocking temperature estimates in stepwise thermal demagnetization experiments. Moreover, we find a strongly enhanced cooling rate effect on palaeointensities for even marginally non-ideal samples (up to 43 per cent increase in pTRM for a halving of the cooling rate).