bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimental evaluation of diesel engine operating with A TERNARY BLEND (BIODIESEL-DIESEL-ETHANOL)
Authors: Vishnoi Pradeep Kumar , Gautam Puneet Singh , Maheshwari Peeyush , Samant Tarun Singh , Gupta V. K. 
Published: August 2021

Abstract
The present investigation aims to study the future potential fuel of a non-edible tamanu oil (calophyllum inophyllum). The raw oil of tamanu oil was converted into biodiesel in two-step esterification process and different test fuel blends with biodiesel were prepared with conventional diesel and ethanol as an additive to evaluate its effect on engine characteristics such as BP, BTE, and BSFC, EGT and smoke density on a 4.4 kW rated power, single-cylinder four-stroke of constant rpm C.I. engineat different loads (25%, 50%, 75%, and 100% of rated power). The fuel blends were prepared with biodiesel in the ratio of 40%,100% coded as B40 and B100 respectively along with diesel fuel and ethanol as an additive in the fixed ratio of 10%, 15%, and 20%. It was found that B40E20D40 showed a reduction in smoke density and BSFC of 14.28% and 5.9% respectively, 18.3% increase in BTE and 3.73% reduction in exhaust gas temperature at full load whereas B100 showed a maximum reduction in smoke density of 15.97% with 4.53% increase in BSFC and a marginal increase in EGT of 0.53%. B40E20D40 gave a better performance in a diesel engine from the perspective of minimum BSFC, lower exhaust gas temperature and higher BTE among all other blends.
Experimental analysis and theoretical validation of C.I. engine performance and combustion parameters using zero-dimensional mathematical model fuelled with biodiesel and diesel blends
Authors: Gautam• Puneet Singh , Vishnoi Pradeep Kumar , Maheshwari Peeyush , Samant Tarun Singh , Gupta V. K. 
Published: August 2021

Abstract
The present work aims to analyze the experimental and numerical investigation on performance such as brake power (BP), brake specific fuel consumption (BSFC), brake thermal efficiency (BTE), and combustion parameters (in-cylinder pressure, heat release rate) on a 4.4 kW single-cylinder four-stroke C.I. engine running on biodiesel extracted from tamanu oil and diesel. A two-zone, zero-dimensional mathematical model was developed by using thermodynamic laws and cylinder volume, Wiebie’s co-relation, in-cylinder pressure, heat transfer model, engine friction model was developed to validate the above engine performance parameters and analyze the combustion parameters comprising of in-cylinder pressure, in-cylinder temperature, net heat release rate at different loads with single varying-parameter i.e. equivalence ratio while other parameters engine speed, compression ratio, injection timing were kept constant. It was found that the theoretical results were in good agreement with the experimental results for straight diesel and its blends with biodiesel.
Finite element simulation of residual stresses in welded steel butt joints and their experimental verification and mitigation
Authors: Eswara V , Jaggannadha Rao D V N J , Seetharama Rao Y 
Published: August 2021

Abstract
The localized, intense, and moving heat source existing in welded fabrication results in residual stresses and distortion. Residual stresses remain inside the material even after the external forces or thermal gradients are removed after welding. Residual stresses decrease fatigue life of the welded joint leading to premature failures and associated distortion cause problems in fitment during assembly. Estimation of residual stresses before actual fabrication is essential for elimination or mitigation after fabrication. In this work, finite element thermomechanical analyses are carried out to estimate the levels of residual stresses of thin welded similar butt joints of 1018 steel and SS 304 steel. The numerically obtained results of the joints are compared with experimental results of identical joint geometry, welding conditions, and material properties existing in the literature. The comparison of numerically obtained thermal histories with those from experiments yielded good agreements. Longitudinal residual stresses are found to be dominant and comparison of these longitudinal stresses with experimental data also found to be in good agreements. Further, the levels of residual stresses are computed with three different preheat temperatures (600°C, 700°C and 800°C) to study the effect of preheating temperature in the mitigation of residual stresses. It has been found that the peak value of longitudinal stress decreased considerably with preheat temperature. Increasing preheat temperature has a marginal reduction in the peak value of longitudinal stress.
Application of thermal spraying process in advancement of welding Technology
Authors: Husain Syed Qaisar , Sharma Divyansu , Singh Vikash , Varshney Gagan , Bhati Girendra , Singh Sudesh , Raja Avinash Ravi 
Published: August 2021

Abstract
In the contemporary world, with the incubation of advanced technologies and tremendous outbursts of research works, simplification of large cumbersome tasks with assets to saving time and money is perhaps one of the most crucial aspects in the current scenario. This paper focuses primarily on advancing welding technology using thermal spraying as the major tool for improving the cost, labor and time associated with some of the common welding processes. The analysis has been carried out on mild steel plates having the thickness of 3 mm & 4 mm thick. This has indeed provided multi-faceted benefits such as weldability of similar and dissimilar metals keeping in mind the quality of welded joint, cost of operation and minimizing time for achieving optimum results etc. The study has also compared different welding processes to that of thermal spraying for achieving the same results based on well-defined parameters, as discussed in further sections. Ultimately, now with thermal spraying a plethora of processes can be accompanied such as coating, cladding etc, in addition to welding technology as well.
Optimization of FDM 3D printing process parameters using Taguchi technique
Authors: Sharma Kuldeep , Kumar Kapil , Singh Kumar Rishi , Rawat M S 
Published: August 2021

Abstract
Fused deposition modelling (FDM) is a fast growing and low-cost 3D printing technology in order to comply most prominent demands of today’s industries in terms of capability to fabricate complex parts along with high flexibility in design. The dimensional accuracy, is an urgent need of final parts printed by FDM process, that is primarily influenced by the process parameters. Optimizing the process parameters which significantly influence the dimensional accuracy is the primary goal of this study in order to achieve the ultimate final part quality. This experimental study investigates the effect of different process parameters viz. layer height, raster angle, nozzle temperature and surrounding pressure on thickness of the final part for Poly Lactic Acid (PLA) filament. Experiments, based on Taguchi’s L9 orthogonal array, were performed and subsequently experimental data have been analysed by ANOVA. It has been observed that the layer height is the most significant factor in order to achieve the dimensional accuracy.
Estimation of temperature during TIG welding of titanium
Authors: Raja Avinash Ravi , Dixit Anuj , Jain Ayush , Husain Syed Qaisar , Varshney Gagan , Singh Sudesh 
Published: August 2021

Abstract
In this experimentation work, the welding of titanium (commercially pure of grade 2) has been performed. The technique used to perform the welding is Tungsten Inert Gas Welding. Several experimentations have been performed to get the preferred welding. On which further studies have been done. Temperature has been measured during the welding process to get the estimation.
Modelling and Analysis of SUV Chassis
Authors: Manikandan H , Cyril S 
Published: August 2021

Abstract
Truck chassis is like a skeleton of the vehicle. The chassis undergoes various stresses and deformation, when the vehicle is in motion. The present work aims at deriving the static and dynamic characteristics of the chassis, by modelling the chassis and carrying out meshing and then subjecting it to static and dynamic analysis as well as modal analysis. Various materials were chosen for doing the Finite Element Analysis. Modal analysis is done by attuning the selective material properties and the predicted natural frequencies and mode shapes were validated against experimental results. The final results were incorporated in the model to optimise the chassis with respect to strength, vibration and weight.
Substrate material selection and design optimization of patch antenna
Authors: Dubey Anil Kumar 
Published: August 2021

Abstract

In this paper parametric analysis of different substrate materials used for microstrip patch antenna are analyzed based on its physical properties, also parametric calculation performed for selection of substrate working at operating frequency of 5.8 GHz. Proposed microstrip patch antenna was optimized by varying its design structure from rectangular patch to E-shaped structure. Method of moment based electromagnetic simulator IE3D was used for parametric calculation and optimization of proposed patch antenna design.
A review on superhydrophobic materials and coating techniques
Authors: Mishra Vipul Kumar , Saini R , Kumar N 
Published: August 2021

Abstract
Since the recent year, we have seen the interest in scientist to mimic the natural behaviour, and they tried to mimic the nature’s property of superhydrophobicity artificially and very far they also get succeeded. This superhydrophobic property is very useful in many aspects of life as well as in industries as they have an extensive property to overcame wear, corrosion, biofouling etc. There are different ways to fabricate these coatings, some are chemical and some are physical. In this review paper, we have discussed the theoretical background of superhydrophobicity and discussed the need for a surface to become superhydrophobic like surface energy and roughness and also different ways of fabrication in which some are simple and cost-effective and some are very useful for industries. Also, there are different examples of materials that can show superhydrophobic properties.
Characterization of electric discharge machining of titanium alloy utilizing MEIOT technique for orthopedic implants
Authors: Prabhakar B S Manoj , R Ranjith , S Venkatesan 
Published: August 2021

Abstract
In this research work, medical grade titanium alloy Ti4Al6V was electric discharge machined with an objective of attaining mirror finish for orthopedic implants. Experiments were conducted by varying tool materials, discharge current, pulse on time and pulse off time whereas the responses chronicled are material removal rate, electrode wear rate and surface roughness. The aluminium (A), copper (C) and aluminium alloy reinforced with graphite particles of various weight percentage (5-A1,10-A2,15-A3) were used as tool materials. The composites were fabricated using stir casting technique. The findings showed that the titanium alloy machined with A1 composite tool offers the highest MRR, the C tool has the lowest EWR, and the A2 composite tool results in good surface finish. The surface of specimens produced using A1 tool exhibits poor surface quality owing to the eczema surface. Specimens machined with the C tool have a remelted layer, pockmarks, and an uneven fusion structure, which were not present in specimens machined with the A2 tool. MOORA-ELECTRE Integrated Optimization Technique (MEIOT) was applied to select the best parametric combination and the best electrode material.
Pectate lyase action in vivo and fruit softening. A commentary on: ‘Fruit softening: evidence for pectate lyase action in vivo in date (Phoenix dactylifera) and rosaceous fruit cell walls’
Authors: Seymour Graham B 
Published: August 2021

This article comments on:
Thurayya Z. S. Al Hinai, Robert A. M. Vreeburg, C. Logan Mackay, Lorna Murray, Ian H. Sadler and Stephen C. Fry. Fruit softening: evidence for pectate lyase action in vivo in date (Phoenix dactylifera) and rosaceous fruit cell walls, Annals of Botany, Volume 128, Issue 5, 8 October 2021, Pages 511–526, https://doi.org/10.1093/aob/mcab072
cblaster: a remote search tool for rapid identification and visualization of homologous gene clusters
Authors: Gilchrist Cameron L M , Booth Thomas J , van Wersch Bram , van Grieken Liana , Medema Marnix H , Chooi Yit-Heng 
Published: August 2021

Abstract

Motivation
Genes involved in coordinated biological pathways, including metabolism, drug resistance and virulence, are often collocalized as gene clusters. Identifying homologous gene clusters aids in the study of their function and evolution, however, existing tools are limited to searching local sequence databases. Tools for remotely searching public databases are necessary to keep pace with the rapid growth of online genomic data.

Results
Here, we present cblaster, a Python-based tool to rapidly detect collocated genes in local and remote databases. cblaster is easy to use, offering both a command line and a user-friendly graphical user interface. It generates outputs that enable intuitive visualizations of large datasets and can be readily incorporated into larger bioinformatic pipelines. cblaster is a significant update to the comparative genomics toolbox.

Availability and implementation
cblaster source code and documentation is freely available from GitHub under the MIT license (github.com/gamcil/cblaster).

Supplementary information
Supplementary data are available at Bioinformatics Advances online.
MERIDA: a novel Boolean logic-based integer linear program for personalized cancer therapy
Authors: Lenhof Kerstin , Gerstner Nico , Kehl Tim , Eckhart Lea , Schneider Lara , Lenhof Hans-Peter 
Published: August 2021

AbstractMotivationA major goal of personalized medicine in oncology is the optimization of treatment strategies given measurements of the genetic and molecular profiles of cancer cells. To further our knowledge on drug sensitivity, machine learning techniques are commonly applied to cancer cell line panels.ResultsWe present a novel integer linear programming formulation, called MEthod for Rule Identification with multi-omics DAta (MERIDA), for predicting the drug sensitivity of cancer cells. The method represents a modified version of the LOBICO method and yields easily interpretable models amenable to a Boolean logic-based interpretation. Since the proposed altered logical rules lead to an enormous acceleration of the running times of MERIDA compared to LOBICO, we cannot only consider larger input feature sets integrated from genetic and molecular omics data but also build more comprehensive models that mirror the complexity of cancer initiation and progression. Moreover, we enable the inclusion of a priori knowledge that can either stem from biomarker databases or can also be newly acquired knowledge gathered iteratively by previous runs of MERIDA. Our results show that this approach does not only lead to an improved predictive performance but also identifies a variety of putative sensitivity and resistance biomarkers. We also compare our approach to state-of-the-art machine learning methods and demonstrate the superior performance of our method. Hence, MERIDA has great potential to deepen our understanding of the molecular mechanisms causing drug sensitivity or resistance.Availability and implementationThe corresponding code is available on github (https://github.com/unisb-bioinf/MERIDA.git).Supplementary informationSupplementary data are available at Bioinformatics online.
NetControl4BioMed: a web-based platform for controllability analysis of protein–protein interaction networks
Authors: Popescu Victor-Bogdan , Sánchez-Martín José Ángel , Schacherer Daniela , Safadoust Sadra , Majidi Negin , Andronescu Andrei , Nedea Alexandru , Ion Diana , Mititelu Eduard , Czeizler Eugen , Petre Ion 
Published: August 2021

Abstract

Motivation
There is an increasing amount of data coming from genome-wide studies identifying disease-specific survivability-essential proteins and host factors critical to a cell becoming infected. Targeting such proteins has a strong potential for targeted, precision therapies. Typically however, too few of them are drug targetable. An alternative approach is to influence them through drug targetable proteins upstream of them. Structural target network controllability is a suitable solution to this problem. It aims to discover suitable source nodes (e.g. drug targetable proteins) in a directed interaction network that can control (through a suitable set of input functions) a desired set of targets.

Results
We introduce NetControl4BioMed, a free open-source web-based application that allows users to generate or upload directed protein–protein interaction networks and to perform target structural network controllability analyses on them. The analyses can be customized to focus the search on drug targetable source nodes, thus providing drug therapeutic suggestions. The application integrates protein data from HGNC, Ensemble, UniProt, NCBI and InnateDB, directed interaction data from InnateDB, Omnipath and SIGNOR, cell-line data from COLT and DepMap, and drug–target data from DrugBank.

Availabilityand implementation
The application and data are available online at https://netcontrol.combio.org/. The source code is available at https://github.com/Vilksar/NetControl4BioMed under an MIT license.
Individualized response to semantic versus phonological aphasia therapies in stroke
Authors: Kristinsson Sigfus , Basilakos Alexandra , Elm Jordan , Spell Leigh Ann , Bonilha Leonardo , Rorden Chris , den Ouden Dirk B , Cassarly Christy , Sen Souvik , Hillis Argye , Hickok Gregory , Fridriksson Julius 
Published: August 2021

Abstract
Attempts to personalize aphasia treatment to the extent where it is possible to reliably predict individual response to a particular treatment have yielded inconclusive results. The current study aimed to (i) compare the effects of phonologically versus semantically focussed naming treatment and (ii) examine biographical and neuropsychological baseline factors predictive of response to each treatment. One hundred and four individuals with chronic post-stroke aphasia underwent 3 weeks of phonologically focussed treatment and 3 weeks of semantically focussed treatment in an unblinded cross-over design. A linear mixed-effects model was used to compare the effects of treatment type on proportional change in correct naming across groups. Correlational analysis and stepwise regression models were used to examine biographical and neuropsychological predictors of response to phonological and semantic treatment across all participants. Last, chi-square tests were used to explore the association between treatment response and phonological and semantic deficit profiles. Semantically focussed treatment was found to be more effective at the group-level, independently of treatment order (P = 0.041). Overall, milder speech and language impairment predicted good response to semantic treatment (r range: 0.256–0.373) across neuropsychological tasks. The Western Aphasia Battery-Revised Spontaneous Speech score emerged as the strongest predictor of semantic treatment response (R2 = 0.188). Severity of stroke symptoms emerged as the strongest predictor of phonological treatment response (R2 = 0.103). Participants who showed a good response to semantic treatment were more likely to present with fluent speech compared to poor responders (P = 0.005), whereas participants who showed a good response to phonological treatment were more likely to present with apraxia of speech (P = 0.020). These results suggest that semantic treatment may be more beneficial to the improvement of naming performance in aphasia than phonological treatment, at the group-level. In terms of personalized predictors, participants with relatively mild impairments and fluent speech responded better to semantic treatment, while phonological treatment benefitted participants with more severe impairments and apraxia of speech.
Neural Basis of Somatosensory Spatial and Temporal Discrimination in Humans: The Role of Sensory Detection
Authors: Huang Cheng-Wei , Lin Chin-Hsien , Lin Yi-Hsuan , Tsai Hsin-Yun , Tseng Ming-Tsung 
Published: August 2021

Abstract
While detecting somatic stimuli from the external environment, an accurate determination of their spatial and temporal properties is essential for human behavior. Whether and how detection relates to human capacity for somatosensory spatial discrimination (SD) and temporal discrimination (TD) remains unclear. Here, participants underwent functional magnetic resonance imaging scanning when simply detecting vibrotactile stimuli of the leg, judging their location (SD), or deciding their number in time (TD). By conceptualizing tactile discrimination as consisting of detection and determination processes, we found that tactile detection elicited activation specifically involved in SD within the right inferior and superior parietal lobules, 2 regions previously implicated in the control of spatial attention. These 2 regions remained activated in the determination process, during which functional connectivity between these 2 regions predicted individual SD ability. In contrast, tactile detection produced little activation specifically related to TD. Participants’ TD ability was implemented in brain regions implicated in coding temporal structures of somatic stimuli (primary somatosensory cortex) and time estimation (anterior cingulate, pre-supplementary motor area, and putamen). Together, our findings indicate a close link between somatosensory detection and SD (but not TD) at the neural level, which aids in explaining why we can promptly respond toward detected somatic stimuli.
mRNA-Decapping Associated DcpS Enzyme Controls Critical Steps of Neuronal Development
Authors: Salamon Iva , Palsule Geeta , Luo Xiaobing , Roque Alfonso , Tucai Shawn , Khosla Ishan , Volk Nicole , Liu Wendy , Cui Huijuan , Pozzo Valentina Dal , Zalamea Petronio , Jiao Xinfu , D’Arcangelo Gabriella , Hart Ronald P , Rasin Mladen-Roko , Kiledjian Megerditch 
Published: August 2021

Abstract
Homozygous mutations in the gene encoding the scavenger mRNA-decapping enzyme, DcpS, have been shown to underlie developmental delay and intellectual disability. Intellectual disability is associated with both abnormal neocortical development and mRNA metabolism. However, the role of DcpS and its scavenger decapping activity in neuronal development is unknown. Here, we show that human neurons derived from patients with a DcpS mutation have compromised differentiation and neurite outgrowth. Moreover, in the developing mouse neocortex, DcpS is required for the radial migration, polarity, neurite outgrowth, and identity of developing glutamatergic neurons. Collectively, these findings demonstrate that the scavenger mRNA decapping activity contributes to multiple pivotal roles in neural development and further corroborate that mRNA metabolism and neocortical pathologies are associated with intellectual disability.