bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of drilling fluid flow in the annulus of drill string through computational fluid dynamics
Authors: Joshi Nishant , Khapre Akhilesh , Keshav Amit , Poonia Anil Kumar 
Published: June 2021

Abstract
During an oil and gas well drilling the drilling fluids are pumped through the drill string to cool and lubricate the drill bit. This also serves the purpose of bringing the rock cutting back to surface and serves various other purposes also like pressure control and maintain well bore stability. As the well is drilled the casing are lowed from the well from caving in. This results in a situation where there is an annular flow of drilling fluid where the inner pipe is rotating while the outer pipe is stationary. The understanding of fluid dynamics of such situation is extremely important and detailed investigations are required. Though experimental investigation will reflect the actual behavior but with the advancement is the numerical techniques such experimentation can be avoided with the application of computational fluid dynamics. Therefore, the present study employs the homogeneous model to simulate a single-phase fluid flow and predict pressure loss variation in eccentric vertical annuli as a function of varying drilling parameters: fluid velocity, inner pipe rotation speed
Supply-chain two-warehouse inventory model for deteriorating items on exponential time function with shortage and partial backlogging in inflationary environment
Authors: Rizwanullah Mohd , Verma Sachin Kumar , Junnaidi Maqsood Hussain 
Published: June 2021

AbstractIn this paper, we have developed two-warehouse problem of supply chain system for deteriorating items, where demand is taken as the function of stock with the exponent function of time. The Practical situation of shortage also include due to the shortage of inventory occur so frequently in daily life in the inventory problem of supply chain system. Backlogging case of shortage is also taken into consideration to make the model more concerned with real life situation. Role of inflation cannot be avoided, so we have included an inflation factor in our model too. A sensitivity analysis is given by the suitable example. To justify our result graph between various parameters is also shown in analysis part. Keywords: term, term, term.
Space optimized design of a flywheel for punching press
Authors: Mendhe M K , Jachak S R , Kamble P D , Sangotra D I , Kakde A 
Published: June 2021

Abstract
Flywheel is a mechanical device which acts as a saving bank account where one can deposit extra money and withdraws whenever required likewise flywheel also store the energy when the demand is less and deliver it when the demand is high. It is mounted in between driver and the follower. It act as a energy store. This paper is focused on the use of mathematical modeling of flywheel and space optimized design for punching press. Flywheel has to be designed for a punch which has to make 20 holes/minute in a plate of thickness 12 mm with constrained of space. 1200mm is the limiting value of diameter of flywheel. The flywheel design is based on the space limitations. The various parameters and stresses induced are determined. At the end it is seen that diameter of the flywheel is less than the permissible value therefore design is safe and optimized for available space.
Comparison of effectiveness of models for solvingfuzzy assignment problem
Authors: Thakre TA , Chaudhari O K , RajshriGupta  
Published: June 2021

Abstract
The task of assigning particular task to a particular person can be solved using assignment problem. If the problem is considered under fuzzy environment, then uncertainty can be minimized which is usually involved in human complex problem. There are various modelsfor solving fuzzy assignment problem. In this paper, the triangular fuzzy assignment problem is formulated. It is then solved by the fuzzy Hungarian method, Hungarian and direct method. The results are obtained and comparison of optimal solution among these methods is done for the effectiveness of the method. The method is illustrated by numerical example based on real life data.
Vision system check for authentication of quality of industry automation for detection of system parts using raspberry pi
Authors: Sorte Swati , Patil Wani , Joshi Sonali , Ghutke Payal 
Published: June 2021

Abstract
Typical tasks of vision systems are included in Recognition area of work – object recognition, identification, detection, content-based image retrieval, pose estimation, optical character recognition (OCR), 2-D encoding and decoding, shape recognition technology, facial recognition and many more. The process followed in order to attain these tasks generally follows the same pattern. First step is image acquisition using various types of cameras according to the requirements (light-sensitive cameras, range sensors, ultrasonic cameras and many more) and acquiring pixel intensities corresponding to light intensity or other measures. Followed by preprocessing in order to reduce noise, increase contrast, resample or scaling using filters, histogram equalization, re-sampling algorithms.
A survey on the techniques to find elementary feasible solutions for fuzzy transportation problems
Authors: Gupta Rajshri , Chaudhari O K , Thakre T A 
Published: June 2021

Abstract
To obtain an optimum solution for the fuzzy transportation problem, there is requisite to find an elementary feasible solution. In this paper, a survey is presented on the current methods to get feasible solutions for the fuzzy transportation problems. The methods are also showed with a mathematical example for fuzzy data and a comparative study is also presented.
Analysis of AI techniques for healthcare data with implementation of a classification model using support vector machine
Authors: Jaiswal P G , Gaikwad M , Gaikwad N 
Published: June 2021

Abstract
Artificial intelligence (AI) is imposed to impersonate human cognitive functions. AI Techniques are most popular across healthcare. The motive behind implementing an AI system is to make the system more fast and efficient. Now, AI can assist medical physician for fast and accurate diagnosis of diseases. When the time of deployment of the AI system will come then, systems need to be ‘trained’ for a huge amount of data will be generated from different clinical performance data. Now a day’s data is available in a structured, unstructured and, semi-structured format. For supporting, retrieving results and knowledge from this data, its analysis using different AI techniques are available. This includes machine learning methods for structured data and unsupervised learning for unstructured data which is useful for retrieving features when the outcome for some subjects is missing. In this paper different conventional machine learning techniques used in healthcare, domains is analyzed using different data types. Also, a comparison of different methods used in Artificial intelligence fiction in the healthcare domain is explored. A flow from clinical data creation, through NLP data enhancement and Machine learning data analysis for making clinical diagnosis decisions and its predictions are discussed and implementation using a support vector machine (SVM) on the healthcare dataset consisting of the patient questionnaire isdone.
Quadruple fixed point result in m-metric space
Authors: Gandhi Manjusha. P , Aserkarand Anushri A , Bajpai Kavita B 
Published: June 2021

Abstract
The Banach Contraction theorem is the basis of the theory of fixed points. Many scholars have been working in different directions on the Banach Theorem. Further theorems on coupled, tripled and quadruple fixed points are established. A quadruple fixed point result was developed in this paper for partial order M-metric space using a monotone property. This theorem is the extension and alteration of literary outcomes. An illustration to verify the outcome has been given.
Mathematics Subject Classification: 46T99, 54H25, 47H10, 54E50
Application of hybrid Taguchi-Grey relational analysis (HTGRA) multi-optimization technique to minimize surface roughness and tool wear in turning AISI4340 steel
Authors: Kamble Prashant D , Waghmare Atul C , Askhedkar Ramesh D , Sahare Shilpa B , Singh Brij R 
Published: June 2021

Abstract
In this paper, an attempt is made to optimize the turning process by minimizing Surface Roughness and Tool Wear. The independent l factors used are Environmental Condition, Feed Rate, Depth of Cut, Nose Radius and Tool Types. The dependant factors are Surface Roughness and Tool Wear. Experimentations are conducted on CNC Spinner Lathe machine. AISI 4340 steel is selected as workpiece material. Three different types of Cutting tool are considered for the study. Grey Relational Analysis and Taguchi Philosophy together are used to optimize the process. As per the Taguchi method L27, Orthogonal Array (OA) is finalized for the experimentation. For the computation of the response table and ANOVA table, the Taguchi based data Analysis is used. The Variance Analysis (ANOVA) and S/N ratio (SRN) are employed to find the contribution and ranking of contribution parameters to optimize multiple output parameters.
A nine-point sampling point scheme for twenty node brick element
Authors: Johnson Shyjo , Sivakumar S , Nagarajan D 
Published: June 2021

Abstract
A new sampling point scheme with nine evaluation points were introduced in this research study for twenty noded brick elements. The new sampling points were located inside the brick element at the corners and center point of the 20 node brick element. This integration scheme can be assumed to be an imitation of Gaussian integration scheme. Standard benchmark problems were chosen from the different research works and compared with our proposed scheme. Finally, the proposed integration scheme achieves good results for twenty node brick element on different performance parameters of finite element analysis.
An intelligent system for transforming natural language queries into SQL and its execution
Authors: Kale Swati , Gahse Vinay , Mahatkar Piyush , Ratnaparkhi Ruhit , Dhawale Nakul , Totade Tanay 
Published: June 2021

Abstract
In today’s world information storing and retrieval plays an important role. Database systems play a key role in the new commercial system for information storage. For accessing the data from database, a person who is not having the knowledge of SQL may find themselves handicapped while dealing with the database. This presents a significant limitation in a developing country such as India, because even today, a very large majority of the population does not have the technical knowledge of how to deal with database systems.
In such a case, Natural language processing (NLP) assumes a significant job. NLP is getting perhaps the most dynamic strategies utilized in Human-PC Interaction. It is a part of AI which is utilized for Information Retrieval, Machine interpretation, and Language Analysis. This paper, proposes a system which allows the user to query the database in a compatible mode language, through a convenient Graphical User Interface which results in the data required by the user.
A comparative study of elzaki and laplace transforms to solve ordinary differential equations of first and second order
Authors: Mitra Ankita 
Published: June 2021

Abstract
- Real life problems which can be formulated in differential equations can be solved by different integral transform. In here, we will discuss some formulas and properties of two transform namely Elzaki transform and Laplace transform and will be used to solve the same set of Differential equation and will be compared with each other.
SDG implications of water-energy system transitions in India, for NDC, 2 °C, and well below 2 °C scenarios
Authors: Vishwanathan Saritha Sudharmma , Garg Amit , Tiwari Vineet , Kapshe Manmohan , Nag Tirthankar 
Published: June 2021

Abstract
India needs to address the immediate concerns of water supply and demand, due to its increasing population, rapid urbanization, and growing industrialization. Additionally, the changing climate will influence water resources, which will subsequently impact the overall sectoral end-use demand patterns. In this study, we have integrated a water module with the existing bottom-up, techno-economic Asia–Pacific Integrated Model/End-use energy system model for India to estimate the future water demand in major end-use sectors under business-as-usual (BAU), nationally determined contribution (NDC), and low-carbon futures (2 °C and ‘well below 2 °C’) up to 2050. We also simulate the effects of water constraints on major sectors under different climate-change regimes. Our results show that water-intensive end-use sectors, specifically agriculture and power, will face major impacts under water-constrained scenarios. Over the period between 2020 and 2050, policy measures taken under the NDC scenario can cumulatively save up to 14
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3.7% of the 2000 annual water demand or 2.5% of the 2015 annual water demand.
billion cubic metres (bcm) of water, while low-carbon scenarios can save 20–21 bcm of water between 2020 and 2050, compared with BAU. In a water-constrained future, NDC and low-carbon futures can save 28–30 bcm of water. There is a need to increase the current water supply by 200–400 bcm. The marginal cost of installing dry cooling systems in the power sector is considerably higher than the cost and benefits of installing micro-irrigation systems with solar PV. Integrated policy coherence is required to achieve sustainable development goals, e.g., NDC and Paris Agreement goals, in both water and energy sectors. Concurrently, regulatory and economic instruments will play an essential role in improving resource-use efficiency at a systemic level, to reduce the overall water demand.
Lifestyle Interventions Reduce the Need for Guideline-Directed Antihypertensive Medication
Authors: Hinderliter Alan L , Smith Patrick , Sherwood Andrew , Blumenthal James 
Published: June 2021

Abstract

Background
The 2017 ACC-AHA Hypertension Guideline recommends initiation of antihypertensive drug therapy based on blood pressure (BP) and an assessment of global cardiovascular disease (CVD) risk, but intensive lifestyle modification may lower BP to below recommended thresholds for treatment in some patients.

Methods
We examined the effects of lifestyle modification on calculated CVD risk and on the indications for BP-lowering medications in individuals with untreated hypertension. Participants included 144 adults with BP 130–160/80–99 mm Hg who were randomized to 16 weeks of DASH (Dietary Approaches to Stop Hypertension) diet plus behavioral weight management (DASH + WM), DASH diet alone (DASH), or Usual Care.

Results
The mean age of the study cohort was 52.0 years; the average baseline BP was 138 ± 9/86 ± 6 mm Hg. The 10-year CVD risk, as calculated by the Pooled Cohort Equations, was 5.7%. The adjusted 10-year risk fell to 4.4% in the DASH + WM group and to 5.0% in the DASH arm, but was not significantly changed (5.7%) in the Usual Care controls. The percentages of participants with guideline-based indications for antihypertensive drugs fell from 51% to 18% in the DASH + WM group and from 48% to 22% in the DASH group; and did not change significantly (49% to 44%) in the Usual Care group (P = 0.010 for the active intervention groups vs. Usual Care; P = 0.042 for DASH + WM vs. DASH).

Conclusions
These data demonstrate that in men and women with mildly elevated BP, lifestyle interventions can lower the calculated CVD risk and dramatically decrease the number of individuals for whom guideline-directed antihypertensive medication is indicated.
Can Self-Regulation be Transferred to Second/Foreign Language Learning and Teaching? Current Status, Controversies, and Future Directions
Authors: Teng Lin Sophie , Zhang Lawrence Jun 
Published: June 2021

Abstract
Recognized as an essential component of 21st century skills, self-regulation, also as a robust and vibrant theory, has been extensively researched in the field of education psychology for many decades. However, it is an area of research whose theoretical principles that drive the research work have not been sufficiently applied to the field of second language acquisition (SLA), applied linguistics, or foreign language education. Inspired by the heated discussion on self-regulation and language learning strategies in recent years (Rose et al. 2018; Griffiths 2020), this brief article presents a critical review of how self-regulation has been applied to second/foreign language learning and teaching in the past 15 years. By taking stock of conceptual and methodological issues, we highlight the state-of-the-art research and propose key foci for future studies. We conclude that self-regulation principles, measurements, and practices have a solid ground for enriching second/foreign language learning and teaching, and thus offer a complex and broad range of research possibilities.
Wavelet-Gaussian process regression model for forecasting daily solar radiation in the Saharan climate
Authors: Ferkous Khaled , Chellali Farouk , Kouzou Abdalah , Bekkar Belgacem 
Published: June 2021

AbstractForecasting solar radiation is fundamental to several domains related to renewable energy where several methods have been used to predict daily solar radiation, such as artificial intelligence and hybrid models. Recently, the Gaussian process regression (GPR) algorithm has been used successfully in remote sensing and Earth sciences. In this paper, a wavelet-coupled Gaussian process regression (W–GPR) model was proposed to predict the daily solar radiation received on a horizontal surface in Ghardaia (Algeria). For this purpose, 3 years of data (2013–15) have been used in model training while the data of 2016 were used to validate the model. In this work, different types of mother wavelets and different combinations of input data were evaluated based on the minimum air temperature, relative humidity and extraterrestrial solar radiation on a horizontal surface. The results demonstrated the effectiveness of the new hybrid W–GPR model compared with the classical GPR model in terms of root mean square error (RMSE), relative root mean square error (rRMSE), mean absolute error (MAE) and determination coefficient (R2).
Dissociable Components of Information Encoding in Human Perception
Authors: Vidaurre Diego , Cichy Radoslaw M , Woolrich Mark W 
Published: June 2021

Abstract
Brain decoding can predict visual perception from non-invasive electrophysiological data by combining information across multiple channels. However, decoding methods typically conflate the composite and distributed neural processes underlying perception that are together present in the signal, making it unclear what specific aspects of the neural computations involved in perception are reflected in this type of macroscale data. Using MEG data recorded while participants viewed a large number of naturalistic images, we analytically decomposed the brain signal into its oscillatory and non-oscillatory components, and used this decomposition to show that there are at least three dissociable stimulus-specific aspects to the brain data: a slow, non-oscillatory component, reflecting the temporally stable aspect of the stimulus representation; a global phase shift of the oscillation, reflecting the overall speed of processing of specific stimuli; and differential patterns of phase across channels, likely reflecting stimulus-specific computations. Further, we show that common cognitive interpretations of decoding analysis, in particular about how representations generalize across time, can benefit from acknowledging the multicomponent nature of the signal in the study of perception.
Improved Auditory Function Caused by Music Versus Foreign Language Training at School Age: Is There a Difference?
Authors: Tervaniemi Mari , Putkinen Vesa , Nie Peixin , Wang Cuicui , Du Bin , Lu Jing , Li Shuting , Cowley Benjamin Ultan , Tammi Tuisku , Tao Sha 
Published: June 2021

Abstract
In adults, music and speech share many neurocognitive functions, but how do they interact in a developing brain? We compared the effects of music and foreign language training on auditory neurocognition in Chinese children aged 8–11 years. We delivered group-based training programs in music and foreign language using a randomized controlled trial. A passive control group was also included. Before and after these year-long extracurricular programs, auditory event-related potentials were recorded (n = 123 and 85 before and after the program, respectively). Through these recordings, we probed early auditory predictive brain processes.
To our surprise, the language program facilitated the children’s early auditory predictive brain processes significantly more than did the music program. This facilitation was most evident in pitch encoding when the experimental paradigm was musically relevant. When these processes were probed by a paradigm more focused on basic sound features, we found early predictive pitch encoding to be facilitated by music training.
Thus, a foreign language program is able to foster auditory and music neurocognition, at least in tonal language speakers, in a manner comparable to that by a music program. Our results support the tight coupling of musical and linguistic brain functions also in the developing brain.
Case report of a very late dual coronary stent thrombosis in a patient with coronavirus disease 2019
Authors: Hauguel-Moreau Marie , Lannou Simon , Bergez Léa , Mansencal Nicolas 
Published: June 2021

Abstract

Background
Coronavirus disease 2019 (COVID-19) is associated with hypercoagulability and a high rate of thrombosis. Few cases of coronary stent thrombosis associated with COVID-19 have been reported.

Case summary
In this report, we describe the case of a 65-year-old man with a history of coronary artery disease (CAD) who was admitted following an out-of-hospital cardiac arrest related to an ST-segment elevation myocardial infarction revealing a very late dual coronary stent thrombosis of the left anterior descending and posterior descending arteries. Ten days prior to admission, he was diagnosed with COVID-19 pneumonia and treated with dexamethasone, which led to rapid clinical improvement. After resuscitation, coronary angiography revealed an acute thrombotic occlusion in the two previous drug-eluting stents (implanted in 2010 and 2018), with a high thrombus burden. He was successfully treated by percutaneous coronary intervention. The patient did not present any further complications during his hospital stay and was transferred to a cardiac rehabilitation centre.

Discussion
Dual stent thrombosis is an exceptional event highlighting the high procoagulant state promoted by coronavirus 19. This case suggests that strengthening of antithrombotic therapy in CAD patients presenting with COVID-19 should be discussed.