bluuebunny/crossref_metadata_2025_split huggingface dataset:
Solution of Multi-response Optimization: Case Study in turning of AISI D2 Steel using Fuzzy TOPSIS Integrated Taguchi Approach
Authors: Kumari Soni , Sonia Pankaj 
Published: May 2021

Abstract
The present work aims to access the consequence of turning parameter e.g., spindle speed (N), depth of cut (D) and feed rate (f) on several execution indices viz. surface roughness and material removal rate in the machining of AISI D2 steel by means of PVD coated carbide tool. Experimentation trials were carried in accordance to the L9 orthogonal array. In addition, attempts were made to turn the multiple responses got into single responses utilizing TOPSIS. In this study, Decision-Makers’ (DMs’) subjective opinion (in regards of response weight) which were expressed in language-based terminologies has been transformed into fuzzy numbers. Fuzzy representation of multiple-judgments have been aggregated and finally defuzzified to obtain crisp weight. Response data thus obtained from machining experiments along with crisp weight of the responses have been utilized in TOPSIS. At last, for determining the combination of optimal parameters, Taguchi has been implemented.
Influence of Lauric acid on mechanical properties of Portland cement
Authors: Sharma Neha , Verma Mohit , Sharma Prashant 
Published: May 2021

Abstract
In this research we focused on use of lauric acid as an admixture in cement. The main aim of this research is to scrutinize the outcomes of LA on different properties of cement i.e. normal consistency, setting time, compressive strength and the capillary absorption. As large amount of energy has been consumed during the grinding process of clinker therefore many researchers and investigators used fatty acids as a grinding aid to reduce this energy consumption. Herein, effect of LA as an admixture has been reported. Different proportion of LA i.e. 0.25%, 0.50%, 0.75%, 1.0%, 1.25%, 1.5%, 1.75%, 2.0% of dry weight of cement has been used as an admixture to know the properties of Portland cement. To test the compressive strength of Portland cement, total of 96 cubical specimens were prepared and tested for compression strength in UTM under curing stage of three, seven and twenty-eight days. Examined results showed that LA when used in appropriate amount extends the initial and final setting time of ordinary Portland cement. We noticed the decreasement in capillary absorption as amount of LA escalates. We have accomplished in upgrading the mechanical performance of cement, including the capillary absorption, the compressive strength and reducing the amount of mixing water used while modifying the setting time according to use requirements.
Effect of hydrophobic agent in cement and concrete : A Review
Authors: Sharma Neha , Sharma Prashant 
Published: May 2021

Abstract
Hydrophobic agents have been used in cement and concrete to reduce water penetration in concrete since many years. Hydrophobic agents are the materials that are employed in cement for enhancing the contact angle between the water and the concrete surface. Fatty acids and their fractions have been introduced in the cement as either phase change materials or as an admixture to minimize water ingress into concrete. Many alkenes, oils, fats, and greasy substances come under the category of hydrophobic molecule. Due to reduction in water permeability, hydrophobic agent enhances the durability and aesthetic appearance of the concrete. Since the mid-20th century, hydrophobic concrete found much popularity in building and construction. Hydrophobic are non-polar and lipophilic substances exhibits high contact angle thereby minimizes the rate of detrimental reactions. This article presents an overview of the work that has been carried out on the application of hydrophobic agents in cement mortar and concrete.
Trends and Patterns of Sustainable Technology: A Bibliometric Analysis of Economies
Authors: Singh Trilok Pratap , Khandelwal Utkal 
Published: May 2021

Abstract
Engineering creates efficient products, systems, and structures. However, suppose the products, procedures, or facilities are not easy to find the most efficient solutions to current issues. In that case, engineering efficiency is risky because the wrong thing could be engineered successfully and potentially worsens. The question is how sustainable technology (ST) can contribute. Statistical information was collected from the repository of Elsevier Scopus. The research request consisted of all publications with the terms ‘sustainable technology’ in their name, description, and keywords. The study was conducted from January 2010 to June 2019. The subject is under pressure; numerous joint publications are available; articles by various writers from European and Asian countries dominate the number of papers, with Finland and India as the leading economies.
An Overview on Biomaterials and Its Applications in Medical Science
Authors: Bharadwaj Alok 
Published: May 2021

AbstractBiomaterials have been used tremendously in medical science over last many decades. In human body a number of body tissues like teeth, ligament, bones tendons and others have been successfully replaced by these biomaterials. In present scenario the various applications of these biomaterials are still awaited. The most important challenge in using these biomaterials is immune rejection because in current situation the lifetime implants and bone replacement must required biocompatibility along with the biological and mechanical characteristics of the biomaterial used. Till now a number of biomaterials have been discovered and due to their biocompatibility and biodegradability, these are biomaterials are employed significantly in biotherapy and medical science. On the basis of the source, these biomaterials can be grouped into two categories namely natural or synthetic polymers, henceforth they have paid much consideration.An ideal biomaterial must have the following characteristics like they fulfill the various chemical and physical requirements along with the mechanical vigor and biocompatibility e.g. stainless steel, zirconia, alumina, Co-Cr alloys, polythene (high molecular weight), poly methyl methacrylate etc. In present scenario, considerable efforts has been done in improving the utility of artificial joints, but now the current focus has been committed for reducing the wear and to amplify the duration of implants or prosthesis inside the human body. In the present review an efforts has been made to provide awareness and importance of these biomaterials in the medical science along with fulfilling all the challenges.
Early Diagnosis of Breast Cancer Prediction using Random Forest Classifier
Authors: Anisha P R , Kishor Kumar Reddy C , Apoorva K , Meghana Mangipudi C 
Published: May 2021

Abstract
Breast Cancer is one of the most dreadful diseases and is a potential cause of death in women. Late prediction of Breast Cancer may greatly reduce survival chances, and as a solution to that the automatic disease detection system aids the medical field to diagnose and analyze, which offers rapid response, reliability, effectiveness as well as decrease the risk of death. In this paper, we explain how breast cancer can be predicted using a Machine Learning Technique named Random Forest Classifier. This classifier structures the data into numerous trees and obtains a final result i.e., whether a person is at risk of having breast cancer or not. This model has an accuracy of 98%.
Deep learning based non-linear regression for Stock Prediction
Authors: Agrawal Subhash Chand 
Published: May 2021

Abstract
Stock market prediction is an activity to estimate the future value of a stock. The accurate prediction of particular share’s future price can lead to significant profit margins for an investor. The efficient market hypothesis states that prices of the stock depend on the available information and price changes, do not consider any hidden information. Therefore, prediction of stock plays a significant role to influence the investor’s decisions. It also acts a recommend system for investment related decision in stock market for short term investors and financial suffering system for long term shareholders. In this paper, we propose a stock market prediction system using machine learning algorithms. This paper first explores a few machine learning algorithms for estimating stock value and then proposes a solution that can predict the future stock value with higher accuracy. In this paper, we propose a deep learning based non-linear regression method to predict the stock price. The experiments are performed on two publically available datasets : Tesla Stock Price and New York Stock Exchange which consist of stock data from 2010 to 2020. The analysis of experimentation reveals that the proposed method performed better than existing machine learning based approaches.
A Social Application of Artificial Intelligence & IoT for Water Conservation
Authors: Rathor Sandeep , Kumari Shalini 
Published: May 2021

Abstract
Water is an essential resource for all life on earth. As time advances, water is becoming scarcer. Water is a renewable resource and if not managed, in the coming time, it will become a non-renewable resource. Therefore, it is necessary to handle the management of water smartly. So, artificial intelligence technology can be utilized to change conventional water and wastewater into instrumented, interconnected, and intelligent systems. This paper proposes a low cost and affordable smart & intelligent water conservation system. The objective of the paper is to make a smart water conservation system for the society with the help of the artificial intelligence and IoT. Artificial intelligence using IoT provides accurate automatic task and up-to-date information that enables information and systematic decision. Implementation results show that, how have we made water conservation systems smart by using artificial intelligence and various sensors and microcontrollers.
Descriptive Naming & Summarization of large text using Topic Model-A Survey
Authors: Tripathi Saumya 
Published: May 2021

Abstract

Due to the plethora of documents containing large scale of text that are available on web it sometimes gets difficult to go through each document to get the clear picture of what the text is depicting. In this paper, we are analyzing several techniques to evaluate Topic Model. A Topic Model is a very popular approach for representing and smoothing the content of documents. Here we will focus on uncovering the thematic structure of a corpus of document that will help in document classification and for compact document topic representation. We have gone through some of the famous topic model such as-Latent Semantic Indexing (LSI),Probabilistic Latent Semantic Indexing (PLSI),Latent Dirichlet Allocation (LDA),Pachinko Allocation Model (PAM) where we encounter few issues such as Topic models are not proper for some SNS such as micro blogging and supervise learning techniques are designed for one-labeled corpus-i. e. they are limiting the document to a single label.
A theoretical investigation of a controlled hybrid mechanical/capillary pumped loop
Authors: Levêque Marie , Dutour Sébastien , Miscevic Marc , Lavieille Pascal , Bertin Yves , Mari Raphaël 
Published: May 2021

Abstract
A series hybrid mechanical/CPL system is a way to improve the performance characteristics over a plain CPL system, as demonstrated by Schweickart et al [1]. However, few hybrid loops actually operate because the control of the system remains difficult. An investigation of a controlled hybrid CPL is proposed based on a dynamic model, consisting of the coupling of a CPL model and a mechanical pump whose speed is controlled by a PID. We first theoretically determined the controller parameters versus the CPL characteristics in order to optimize the command for a given CPL. In a second part, some simulations of two different architectures were performed and analyzed. These results have confirmed that the hybrid system is very attractive to greatly improve the CPL performance.
Loop heat pipe dynamics modeling and analysis
Authors: Buz Vasily , Goncharov Konstantin 
Published: May 2021

Abstract
The report presents mathematical model and computational analysis of dynamic processes in the loop heat pipe, as well as some ways of regulating its work. This is considered a one-dimensional unsteady model of the loop. For each element of loop the model contains the energy equation for flow of fluid and to the walls, and the equation of conservation of momentum of the working fluid. The joint solution of a system of such equations for all elements of the loop allows to calculate the temperature distribution and pressure contour at any point in time. The calculations showed that under certain conditions in the loop heat pipe can be auto-oscillations of different nature. Analysed methods of eliminating these auto-oscillations. One way to regulate the loop heat pipe is the use of a control valve on the additional bypass line. The analysis showed that this method can significantly improve the quality of temperature control and reduce energy consumption by regulation or do without energy consumption. Presents a model of the dynamics of loop heat pipe gives physically reasonable results of calculations and is consistent with the results of the tests.
A Dual stopband two-sided frequency selective surface for mobile shielding applications
Authors: Mayouf A T , Sayidmarie K H , Ali Y E Mohammed 
Published: May 2021

Abstract
A two-sided frequency selective surface (FSS) is proposed to shield two bands of the mobile frequencies (EGSM-900 and DCS-1800). The FSS consists of an array of square concentric-rings cells printed on both sides of the substrate to offer better shielding of the two mobile frequencies. The CST Microwave suit is used for the simulations. The equivalent circuit model for the two-sided FSS is analysed and the transmission frequency in terms of the two stop frequencies is estimated. The obtained shielding is better than 40 dB across the two bands. The proposed FSS can be used to reduce mobile radiation or to isolate halls from nearby mobile base stations. The bandwidth of the FSS cell can be increased by using ring pairs of unequal sizes on the two sides of the substrate.
Characterization and selective deposition of carbon nanotubes from carbon nanoparticles mixture using mild acid treatment and electrokinetic manipulation
Authors: Abdulhameed Abdullah , Mohtar Mohd Nazim , Hamidon Mohd Nizar , Mansor Ishak , Halin Izhal Abdul 
Published: May 2021

Abstract
Particle manipulation is often required in the fabrication of microelectronic devices such as transistors and sensors. In this work, we succeeded in depositing aligned carbon nanotubes (CNTs) from an oxidized conglomerates carbon mixture using a simple low power procedure consisting of mild acid treatment and frequency-dependent dielectrophoretic (DEP) force. The treatment improved the dispersity and solubility of CNTs due to the functional groups introduced on their surface. The DEP force was generated with an AC signal of 1 MHz and 7.07 Vrms to attract the CNTs to a transparent electrode gap of 50 μm. Treatment quality was confirmed and characterized by Raman spectroscopy, Fourier-transform infrared spectroscopy (FTIR), energy dispersive x-ray analysis (EDX) and high-resolution transmission electron microscopy (HRTEM). Ultraviolet-visible spectroscopy (UV-vis) and dynamic light scattering (DLS) were used to analyze the dispersity and solubility of carbon particles and their size distribution in different solvents. The morphology of the deposited CNTs and amorphous carbon were observed by optical microscope and field-emission scanning electron microscope (FESEM). The procedure used in this work is cost-effective, scalable and essential for future assembly. Furthermore, the transparency of the system makes it suitable for real-time observation, transparent sensors, and the ability to integrate it into microfluidic channels.
Microstructure and mechanical properties of superelastic NiTi fiber reinforced NiTi/(Al3Ti+Al3Ni) metal-intermetallic laminated (SFR-MIL) composites
Authors: Kang Fuwei , Zhang Ximeng , Zhang Fahong , Wang Enhao , Cao Yang , Jiang Wei , Wang Liping , Han Yuqiang , Lin Chunfa 
Published: May 2021

Abstract
In this work, a novel superelastic NiTi fiber reinforced NiTi/(Al3Ti+Al3Ni) metal-intermetallic laminated (SFR-MIL) composites was fabricated via vacuum hot pressing method. In order to accurately determine the reaction products of the fabrication process, the microstructure and phase constituents were analyzed and determined using scanning electron microscopy (SEM), energy dispersive spectroscope (EDS) and x-ray diffraction (XRD). Results showed that Al3Ti and Al3Ni were formed during fabrication process. In addition, the quasi-static tensile testing results indicated the average UTS and failure strain of SFR-MIL composite are 377.0 MPa and 15.4%, respectively. The compressive tests of SFR-MIL composites manifested that the average peak compressive strength of this class of materials with load perpendicular to layers is 1114.3 MPa, equivalent to or higher than that of some other laminated composites. Then, the fracture mechanisms are discussed, and the results showed that the reaction band is the possible crack initiation due to the stress concentration, and the major fracture mechanisms are intergranular and transgranular fracture modes.
Civil society, NGOs, and refugees
Authors: Loescher Gil 
Published: May 2021

Abstract
This chapter focuses on the role of civil society, non-governmental organizations (NGOs), and refugee-led initiatives in protecting and assisting refugees and other forced migrants. A number of civil society actors were involved with the drafting of the 1951 Refugee Convention. Moreover, it was a civil society movement that persuaded states to declare the UN’s World Refugee Year 60 years ago. Both refugees and humanitarian actors now face a multitude of new security challenges, such as the changing nature of conflict and the worldwide spread of terrorism. As a consequence, it has become extremely dangerous for aid workers to carry out their humanitarian work.
Temperature effects on forest understorey plants in hedgerows: a combined warming and transplant experiment
Authors: Vanneste Thomas , Van Den Berge Sanne , Brunet Jörg , Hedwall Per-Ola , Verheyen Kris , De Frenne Pieter 
Published: May 2021

AbstractBackground and AimsHedgerows have been shown to improve forest connectivity, leading to an increased probability of species tracking the shifting bioclimatic envelopes. However, it is still unknown how species in hedgerows respond to temperature changes, and whether effects differ compared with those in nearby forests. We aimed to elucidate how ongoing changes in the climate system will affect the efficiency of hedgerows in supporting forest plant persistence and migration in agricultural landscapes.MethodsHere we report results from the first warming experiment in hedgerows. We combined reciprocal transplantation of plants along an 860-km latitudinal transect with experimental warming to assess the effects of temperature on vegetative growth and reproduction of two common forest herbs (Anemone nemorosa and Geum urbanum) in hedgerows versus forests.Key ResultsBoth species grew taller and produced more biomass in forests than in hedgerows, most likely due to higher competition with ruderals and graminoids in hedgerows. Adult plant performance of both species generally benefitted from experimental warming, despite lower survival of A. nemorosa in heated plots. Transplantation affected the species differently: A. nemorosa plants grew taller, produced more biomass and showed higher survival when transplanted at their home site, indicating local adaptation, while individuals of G. urbanum showed greater height, biomass, reproductive output and survival when transplanted northwards, likely owing to the higher light availability associated with increasing photoperiod during the growing season.ConclusionsThese findings demonstrate that some forest herbs can show phenotypic plasticity to warming temperatures, potentially increasing their ability to benefit from hedgerows as ecological corridors. Our study thus provides novel insights into the impacts of climate change on understorey plant community dynamics in hedgerows, and how rising temperature can influence the efficiency of these corridors to assist forest species’ persistence and colonization within and beyond their current distribution range.
Acid or base? How do plants regulate the ecology of their phylloplane?
Authors: Gilbert Kadeem J , Renner Tanya 
Published: May 2021

AbstractPlants interface with and modify the external environment across their surfaces, and in so doing, can control or mitigate the impacts of abiotic stresses and also mediate their interactions with other organisms. Botanically, it is known that plant roots have a multi-faceted ability to modify rhizosphere conditions like pH, a factor with a large effect on a plant’s biotic interactions with microbes. But plants can also modify pH levels on the surfaces of their leaves. Plants can neutralize acid rain inputs in a period of hours, and either acidify or alkalinize the pH of neutral water droplets in minutes. The pH of the phylloplane—that is, the outermost surface of the leaf—varies across species, from incredibly acidic (carnivorous plants: as low as pH 1) to exceptionally alkaline (species in the plant family, Malvaceae, up to pH 11). However, most species mildly acidify droplets on the phylloplane by 1.5 orders of magnitude in pH. Just as rhizosphere pH helps shape the plant microbiome and is known to influence belowground interactions, so too can phylloplane pH influence aboveground interactions in plant canopies. In this review, we discuss phylloplane pH regulation from the physiological, molecular, evolutionary, and ecological perspectives and address knowledge gaps and identify future research directions.
Effects of three-dimensional soil heterogeneity and species composition on plant biomass and biomass allocation of grass-mixtures
Authors: Liu Yongjie , Li Guoe , Wang Mingxia , Yan Wenjing , Hou Fujiang 
Published: May 2021

Abstract
Soil heterogeneity significantly affects plant dynamics such as plant growth and biomass. Most studies developed soil heterogeneity in two dimensions, i.e. either horizontally or vertically. However, soil heterogeneity in natural ecosystems varies both horizontally and vertically, i.e. in three dimensions. Previous studies on plant biomass and biomass allocation rarely considered the joint effects of soil heterogeneity and species composition. Thus, to investigate such joint effects on plant biomass and biomass allocation, a controlled experiment was conducted, where three levels of soil heterogeneity and seven types of species compositions were applied. Such soil heterogeneity was developed by filling nutrient-rich and nutrient-poor substrates in an alternative pattern in pots with different patch sizes (small, medium or large), and species compositions was achieved by applying three plant species (i.e. Festuca elata, Bromus inermis, Elymus breviaristatus) in all possible combinations (growing either in monoculture or in mixtures). Results showed that patch size significantly impacted plant biomass and biomass allocation, which differed among plant species. Specially, at the pot scale, with increasing patch size, shoot biomass decreased, while root biomass and R:S ratio increased, and total biomass tended to show a unimodal pattern, where the medium patch supported higher total biomass. Moreover, at the substrate scale, more shoot biomass and total biomass were found in nutrient-rich substrate. Furthermore, at the community scale, two of the three target plant species growing in monoculture had more shoot biomass than those growing together with other species. Thus, our results indicate soil heterogeneity significantly affected plant biomass and biomass allocation, which differ among plant species, though more research is needed on the generalization on biomass allocation. We propose that soil heterogeneity should be considered more explicitly in studies with more species in long-term experiments.