bluuebunny/crossref_metadata_2025 huggingface dataset:
The Technical Impacts of the Carbon Tax in China
Authors: Chen Shuyang
Published: September 2021

Despite the significant impacts of technology on the socioeconomic effects of climate policies, many previous researchers neglected the induced technical impacts and thus resulted in biased evaluations of climate policies. Hence, it is important that the induced technology should be endogenized in the policy evaluation framework. In this paper, I attempt to use a Computable General Equilibrium (CGE) model to quantify the technical impacts of the Chinese carbon tax. The technical impacts are denoted by the induced technological change (ITC), which is a function of the energy-use efficiency (EUE), energy-production efficiency (EPE), and nonenergy-production efficiency (ENE). The carbon tax will increase the energy cost share because the of the internalisation of the abatement costs. This paper empirically shows that the carbon tax will decrease the energy cost share and production efficiency but increase the energy use and nonenergy production efficiency. Overall, the carbon tax will promote the technological development, compared to the baseline scenario. In addition to the policy effects of the tax, the ITC will decrease the energy use and production efficiency but increase the nonenergy production efficiency. The ITC will increase the RGDP, decrease the household welfare, and increase the average social cost of carbon (ASCC). To summarise, despite that the carbon tax will decrease the welfare at the country and household level, the ITC of the carbon tax will increase the welfare at the country level but decrease the welfare at the household level. Under the ITC impacts, the emission abatement will become costlier.
Effectivity of Camellia sinensis Extract with Nanochitosan to Fibroblast Amounts of Wistar Rats Gingival Wound Healing Process
Authors: Bramanti Indra , Uningojati Annisa Hidaratri , Asriyani Dilla , Tabtila Urfa , Muin Fathul , Kausara Bramanti Nadya
Published: September 2021

Green tea (Camellia sinensis) has high level of flavonoids which are proven to have anti-inflammatory activity. Effect of flavonoids can be enhanced by nano-chitosan capsulation as drug carrier. Chitosan is polysaccharide derived from crustacean shells that mostly used as matrix of various drugs and plant extracts. The aim of this study was to determine the effectivity of flavonoids in green tea extract in nanochitosan capsulation towards the number of fibroblasts on proliferative phase of gingival wound healing process. Green tea was extracted, encapsulated with nano-chitosan and then made into gel. Gingiva labial of 24 male white 3-month-old Wistar rats were wounded by punch biopsy (2 mm diameter), then were treated two times a day, and were divided randomly into four groups of topical gel applications: green tea extract gel encapsulated nano-chitosan, green tea extract gel, base gel as negative control, and NSAIDs gel as positive control, starting at 0 day until 7th day. At 5th and 7th day, three rats from each group were decapitated and the mandibular gingiva was taken in order to make histology slides with hematoxylin eosin staining. Under microscope, the number of fibroblasts were examined. The data were analysed using ANOVA test with 95% confidence level. The results showed that the number of fibroblasts on proliferative phase was significantly higher than control negative (p < 0.05) and has no significant differences (p > 0.05) with control positive. In conclusion, topical application of green tea extract gel encapsulated nano-chitosan was effective to accelerate rats gingival wound healing process by increasing the fibroblasts.
Skeletal Class II Malocclusion Treatment with Combined Twin Block and Lip Bumper Appliances: A Case Report
Authors: Lubis Hilda Fitria , Harahap Nurhayati , Sari Ananda Permata
Published: September 2021

Functional appliances have been used over a century in clinical orthodontic treatments for skeletal Class II malocclusion patients. Its popularity is attributed to its high patient adaptability and ability to produce rapid treatment changes. The twin block and lip bumper can be combined depending on the patient’s cases. The purpose of therapy with twin block is effective in mandibular growth deficiencies to induce supplementary lengthening of mandibular by stimulating increased growth at the condylar cartilage. The patient was a ten-year-old male patient with skeletal Class II malocclusion. He had a convex facial profile, SNA (sella, nasion, A point) angle of 77.5°, SNB (sella, nasion, B point) angle of 73.0°, ANB (A point, nasion, B point) angle of 4.5°, overjet of 6.5 mm, overbite of 11/41 = 5.0 mm, 21/31 = 4.5 mm, abnormal upper labial frenulum, crossbite in the second left premolar of maxilla, crowded anterior teeth of mandibular, deficiency of mandibular growth, lower lip sucking habit, anterior teeth of maxilla with diastema and proclination. Orthodontic treatment for patient is a combination of twin block and lip bumper appliances. After seven months, frenectomy is used to eliminate and correct the spacing in the frenulum. After 10 months, the patient’s skeletal and profile had improved to skeletal Class I malocclusion, SNA angle of 78.0°, SNB angle of 75.0°, ANB angle of 3.0°, overbite and overjet of 4.0 mm, and the lower lip sucking habit had stopped. Twin block and lip bumper appliances are particularly good alternative treatment in managing selected cases of skeletal Class II malocclusion.
Assessing Measurement Invariance of Achievement Emotions Questionnaire for Teachers in Prospective Teacher Sample
Authors: KİLMEN Sevilay
Published: September 2021

The purpose of the current study is to determine whether the Achievement Emotions Questionnaire for Teachers (AEQT) is a psychometrically sound instrument to measure prospective teachers' teaching-related emotions. The three-factor model of the AEQT was confirmed in a prospective teacher sample. Also, reliability results showed that the AEQT is a reliable measurement tool. Measurement invariance results revealed that configural, metric, and scalar invariance were provided across gender. These findings support the use of the AEQT when examining differences based on achievement emotions across gender. For teacher training programs, only configural invariance was provided. Although configural invariance suggests that the three-factor structure of the AEQT is the same across the teacher training programs, the lack of metric invariance indicates that the relationship between the items and the underlying latent variable the AEQT factors is not the same across these groups. The observed variables are not related to the latent variable equivalently across teacher training programs. This result does not allow the comparison of path coefficients and covariances between observed and latent variables across teacher training programs. Also, the lack of scalar invariance indicates that different teacher training programs may interpret some items differently and prevent a comparison of averages between these groups.
Investigation of a Middle School Preservice Teacher’s Knowledge of Content and Students
Authors: ERSARI Ebru
Published: September 2021

The purpose of this study was to explicate one preservice middle grades mathematics teacher’s Knowledge of Content and Students (KCS) in the context of multiple solution strategies. This study’s purpose is to underline the importance of preservice teachers’ KCS and provide possible investigative methods for evaluating preservice teachers’ KCS. Specifically, the research inquiry guiding this study focused on how a middle school preservice mathematics teacher displays KCS when engaging with tasks about pattern recognition and linear functions in the context of multiple solution strategies. The data consisted of three videotaped semi-structured interviews with the preservice mathematics teacher as well as the written work she produced during the interviews. This study explicated one preservice mathematic teacher’s performance regarding two important themes of KCS: generating multiple possible solution strategies of middle school students and explaining multiple student solution strategies. In terms of generating multiple solution strategies of middle school students, the study found that the preservice mathematics teacher provided the same solution strategies that she employed when she solved the problems by herself. Regarding explaining multiple student solution strategies, this study revealed that the preservice teacher did not explicate how typical middle school students reason. The preservice teacher had limitations when explaining the possible procedures that students might have used to solve problems when given the final student solutions. With regard to the teacher’s abilities to recognise and understand students’ typical understandings and misunderstandings, the study demonstrated that the preservice teacher was capable of explaining some solution strategies but not all of them.
Computer Aided Tuberculosis Detection, A Review
Authors: Shukla Pragya , Saini Jasleen , Saini B.S.
Published: September 2021

This paper aims at presenting a complete picture of advances till now in the field of computer-aided detection of Pulmonary Tuberculosis using Chest X-ray Images. Advances are analyzed in chronological order as they happen and are divided into three phases in which technology shifted into new paradigms. Study concludes that although techniques that use Machine learning based methods for segmentation and classification are prevailing for the moment in terms of flexibility for very particular feature extraction in borderline cases where probabilistic methods can be tweaked according to requirements and accuracy, Deep Convolutional Neural Network based technique will secure higher standings as the computational capability and dataset management improves. Finally, briefly an attempt at using visualization techniques for borderline cases is discussed.
Food image recognition based on Mobile NetV2 using support vector machine
Authors: Yadav Sapna , Chand Satish
Published: September 2021

The rapid growth in deep learning has made convolutional neural networks deeper and more complex to realize higher accuracy. But many day-to-day recognition tasks need be performed in a limited computational platform. One of the applications is food image recognition which is very helpful in individual’s health monitoring, dietary assessment, nutrition analysis etc. This task needs small convolutional neural network based engine to do computations fast and accurate. MoblieNetV2 being simple and smaller in size can incorporate easily into small end devices. In this paper, MobileNetV2 and support vector machine are used to classify the food images. Simulation results show that the features extracted from Conv_1 layer, out_relu layer and Conv_1_bn layer of MobileNetV2 and classified using Support Vector Machine have achieved classification accuracies of 84.0%, 87.27% and 83.60% respectively. Because of fewer parameters, smaller size and lesser training time, MobileNetV2 is an excellent choice for real-life recognition tasks.
IoT-based Earthquake Prediction Using Fog and Cloud Computing
Authors: Saini Kanika , Kalra Sheetal
Published: September 2021

Earthquakes are severe, unexpected, life-threatening catastrophes that affect all kind of living beings. It frequently results in the loss of life and property. Predicting earthquake is the most important aspect of this field. With the golden age of the Internet of Things (IoT), an innovative new idea is to couple IoT technology with cloud and fog computing to improve the potency and accuracy of earthquake monitoring and forecasting. The embedded IoT-Fog-Cloud layered structure is adopted in this research to predict earthquakes using seismic signal data. This model transfers sensed seismic signals to fog for analysis of seismic data. At fog, Fast Walsh Hadamard transform is used to extract time and frequency domain features and PCA is employed to reduce the dimensionality of feature sets. Random Forest algorithm has been used to classify seismic signals into two different events, viz., earthquake and non-earthquake accompanied by the real-time warnings. When compared to other classification models, implementation findings indicate that the Random Forest classifier achieves high values of specificity, sensitivity, precision, and accuracy with average values of 88.50%, 90.25%, 89.50%, and 92.66%. Hence make this framework more real-time compliant for earthquake prediction.
Drowsy Driver Detection using MSER Feature Detection and Binarization on MATLAB
Authors: Jamesh Asma
Published: September 2021

Every year, 1.5 lakh people die in road mishaps in India. Among these accidents, 40% are due to ‘Drowsy or Sleep Driving’. According to several statistics, almost all commercial private drivers tend to drive continuously for 10 hours a day. Nearly all road accidents caused due to lack of sleep and drowsiness are highly hazardous and fatal. Drowsy Driver Detection Algorithm acquires real-time video and captures snapshots using an external Webcam. Using the Viola-Jones Algorithm, the face and the eyes of the driver are detected. The original RGB eye image is converted to a Gray image and then into a Binary image. Two techniques, Maximally Stable Extremal Regions Feature Detection and Binarization are deployed to determine the status of the driver. This research paper focuses on the development of a MATLAB algorithm to alert the driver or the co-passenger on-time by plotting the MSER Features and thresholding the acquired real-time images.
HATA Path Loss Model Optimization Using Particle Swarm Algorithm
Authors: Kakkar Deepti , Prashar Ashish , Latif Mehar , Konar Aitraiyee , Kumar Kishan , Tripathi Amitabh
Published: September 2021

Fallacious path loss predictions before the placing of base station(BS) cause under evaluation of circulation areas which gives rise to unabating call drops & cross talks. The escalating demands of meeting overhaul needs of applications by users makes the consequence worst, which significantly influences competence of the cellular wireless system. Propagation model is a keystone of coverage planning. To slash cost, proper planning is needed in coverage of network in order to upgrade the quality of service. Now, K factor is taken into account in order to improve or enhance propagation model based on particles swarm optimization(PSO).The root mean square error(RMSE) between confirmed or verified measurements data & data we obtain from prediction model is used to test and validate the technique used. The values of the RMSE acquired by enhancedmodel and those attained by the standard Hata model are also juxtaposed. We reckoned that the model developed using PSO is better than the HATA model and is errorless.
A Review on Fractal Geometry Enhanced Vehicular Communication under 5G Environment
Authors: Raghavendra K , Kakkar Deepti
Published: September 2021

A lot of technological advancements in the field of vehicular communication has seen in the past decade, which has brought an increasing in a great extent day by day and it’s becoming as a leading research area which provides the scope in terms of safe driving, accident controllability, enhanced security and portability. As we are moving towards the fifth generation, which is showing its dominance on vehicular communication in the next coming years. In this regards the antennas which are used for communication is also an important factor and this paper brings a complete vision over vehicular communication, relevant antennas specified for the latest 5G communication and the paper is concluded with discussion on Internet of vehicles. The impact of Fractal geometry based antennas in the fields of vehicular communication as well as 5G for connected autonomous vehicles are also discussed through this paper.
A Theoretical Framework for the 6G Wireless Communication Standard Vision, Applications and Challenges
Authors: Nazir Faizan , Sood Neetu
Published: September 2021

With the 5G standard being completely solidified and currently being rolled out in multiple countries with total commercial deployment being expected by 2022, focus has now shifted towards conceptualization and standardisation of Beyond 5G (B5G) and 6G wireless systems. Research has already begun in various countries on what to expect from the next generation of wireless communication which is being expected to be deployed early in the next decade. In this article a vision for the next generation of wireless communication is presented based on the trend in usage scenarios around the globe. Some of the promising technologies in 6G such as Reconfigurable Intelligent Surfaces, Smart terminals etc. are explained and the major challenges the next generation of wireless communication faces are also defined. The emergence of Artificial Intelligence (AI) as an inherent part of the 6G intelligent networks and the increased Virtualization of the system is also discussed.
Study the Effect of Body Postures on Skin Conductance Response and Heart Rate
Authors: Soni Ankita , Rawal Kirti
Published: September 2021

Skin Conductance (SC) and Heart Rate (HR) are the two basic tools to evaluate any small physical change that occurred in the human body. Skin conductance demonstrates the electrical conductivity response of the skin. Skin conductance response is the evaluating tool of sympathetic activation of the autonomic nervous system (ANS). When external or internal sensations arise that are physiologically stimulating, the skin temporarily becomes a stronger conductor of electricity. Heart rate shows the beat to beat interval of our heart. The purpose of this paper is to explore the effectiveness of various physical activities on skin conductance and heart rate. To this end, on the self-recorded data set of twenty subjects, the sample entropy is evaluated for the SC, and HR is evaluated. The mean value of skin conductance and heart rate was also examined along with the p-value to evaluate the impact of body positions on the skin conductance response and heart rate. For this purpose, the skin conductance response and HR is recorded for 10 minutes in the position of supine and standing simultaneously. By evaluating the results, it is observed that the value of skin conductance (SC) response and heart rate are increased as the activity is shifted from supine to standing. From the results, it is inferred that there is a substantial decrease in the sample entropy of SC and HR in the standing posture, which indicates an increase in the sympathetic activation of the autonomic nervous system (ANS) in the standing position. A positive correlation is found between the response of skin conductance and heart rate when the position of the body is changed from supine (rest) to standing posture.
Task Scheduling Algorithms for Cloud Computing: A Critical Review and Open Research Challenges
Authors: Kaur Gagandeep , Sharma Anurag
Published: September 2021

Cloud computing is the most preferred platform to access resources remotely. The benefit of cloud computing over traditional computing techniques is that it provides on-demand services and serves millions of users at the same time. However, scheduling the tasks of users is quite crucial in cloud computing. To overcome this challenge, various task scheduling algorithms have been designed for cloud computing. In this paper, we have done a critical review of various traditional and metaheuristic algorithms based on task scheduling algorithms. The critical review shows that the metaheuristic algorithms are better than traditional algorithms to find the optimal scheduling of the task. Besides that, based on the study, we have defined the open research challenges of the metaheuristic algorithms that help other authors to contribute their research in this field.
ASD Diagnoses using Deep Learning and Neuroimaging as A Biomarker: A Review
Authors: Beri Sonali , Khosla Arun
Published: September 2021

Autism Spectrum Disorder (ASD) is a commonly occurring neurodevelopmental disorder characterized by problems occurring in social communication and the presence of restricted and repetitive behavior and interests. Up to now, ASD is being diagnosed considering clinical interview, behavior and developmental factors. Early diagnosis of it can help the autistic people to deal well in their lives. For this early detection different biomarker like Neuro-imaging data can be used which includes structural and functional magnetic resonance imaging. In order to explore the functional and structural differences in between TC and autistic group deep learning methods can be used. These deep learning methods will help in efficient classification and thus can help in autism diagnosis as well. In this paper studies related to various Deep Learning techniques used to diagnose autism are being looked at.
Role of Serious Games in enriching Watershed Conservation Manoeuvres
Authors: Singh Parampreet , Khan Nadeem Ahmad , Khosla Arun , Pujar Girish
Published: September 2021

Watershed management is important for sustainable development. But now because of lack of education, faulty practices and other uncertain factors, watersheds are deteriorating and that needs to be checked. Already, lots of government/non-government projects and are going on in that direction. Serious games or educational games are also being used as a tool to teach watershed conservation. This paper brings out the importance of serious games in the enriching of watershed conservation activities. How these games can solve various issues regarding watershed management and can bring about coherence in authorities and stakeholders to work together. In this paper, we will evaluate a few games about how they help to enhance knowledge among individuals, teach them good practices about watershed conservation and refrain them from using their ongoing wrong practices that have the potential to harm them and their surroundings in the long term.
Classification Comparative Analysis for Detection of Brain Tumor Using Neural Network, Logistic Regression & KNN Classifier with VGG19 Convolution Neural Network Feature Extraction
Authors: Kamble Vijaya , Daruwala Rohin
Published: September 2021

In recent years due to advancements in digital imaging machine learning techniques are used in medical image analysis for the prognosis and diagnosis of various abnormalities in the human body. Various Machine learning algorithms, convolution and deep neural networks are used for classification, detection and prediction of various brain tumors. The proposed approach is a different comparative classification analysis approach which is based on three different classification namely KNN classifier,Logistic regression & neural network as classifier. It is based on a deep learning feature extraction technique using VGG19. This VGG 19-layer image recognition model trained on Imgenet. Generally, MRI data sequences are analyzed in terms of different modalities and every modality contains rich tissue information. So, feature exaction from MRI sequences is very important task for brain tumor classification. Our approach demonstrated fair classification on BRATS Benchmarks 2018 data set with different modalities and sizes of images,results are without any human annotations. Based on selected classifiers all the classifiers gives accuracy above 90%. It is good compared to other state of art methods.
Simulation of Counter Based DPWM for Implementation on FPGA
Authors: Sood Vindhyali , Prasad MPR
Published: September 2021

A Digital Pulse Width Modulation technique based on the counter has been considered for analysis and simulation. It utilizes one of the many functions due to the advanced characteristics already present on the field-programmable gate array (FPGA) which is a huge advantage. Delay Locked Loop (DLL) is one of those features on the FPGA that is used. This architecture merged a counter-comparator-based synchronous block with an asynchronous block that uses the Delay Locked Loop (DLL). This action helps to achieve a better or higher resolution. The architecture proposed is to be executed on an inexpensive but lower-speed FPGA. This FPGA is given a 32 MHz clock externally that helps us to get a time resolution under 2ns. To use the DLL on FPGA, the Digital Clock Manager (DCM) block is used.
Organic Thin Film Transistors for Flexible Electronics
Authors: Sircar Aenakshi
Published: September 2021

Progress in electronics gave rise to the concept of flexible electronics. Which are widely being used for medical and aerospace research. Further development in the fields of flexible electronics unfolded another branch of this electronics system called organic flexible electronics. Organic thin-film transistors, Organic light-emitting diodes are a few of the many forms of organic flexible electronics. Organic materials being used as the substrates increase the flexibility of the electronic circuit. The conductivity of these substrates can be controlled as per requirement by varying the doping concentration of the substrate. The cost of production of organic flexible electronics is low as compared to electronics circuits using a silicon substrate. This paper illustrates the various properties of organic materials and their applications and suitability in flexible electronics.
Comparative Analysis of Multiplications Technique Conventional, Booth, Array Multiplier and Vedic Arithmetic Using VHDL
Authors: Kumar Akash , Chaudhary Tarun , Ram Vijay Kumar
Published: September 2021

The multiplication operation is one of the often used operation in many computer and electronic devices. Low power utilization is one of the most essential attributes for meeting several challenges in many applications. In this paper different type of implementation of Booth multiplier has been studied. Multipliers has great importance in digital signal processing, so designing a high speed multiplier is the need the hour. Structures of 4X4 bits Urdhva Tiryagbhya, Nikhilam Sutra have been executed on Spartan 3 XC3S50-5-PQ-208.The determined calculation delay for 4X4 Urdhva Tiryagbhyam was 14.14 ns and force is 20.60 mw. For Nikhilam Sutra the determined computational postponement is 16.16 ns and all out force utilization is 24.60 mw.
Design of Reed-Solomon Encoder for Error Detection in DRAM Cells
Authors: Asthana Prateek , Khanna Gargi , Sankhyan Sahil , Chaudhary Tarun
Published: September 2021

This paper investigates the design of Reed Solomon (RS) encoder. Based on the message symbols, the RS encoder generates the code-word. By carrying out a polynomial division using Galois Field algebra, the parity symbols are calculated. Reed-Solomon codes are one of the most effective and effective non-binary error codes to detect and correct burst errors. This is the focus work for my dissertation to implement RS encoder and decoder that is a complex algorithm and it is used for the reliable memory operation in a system. The RS Encoder and decoder are design in structural modeling and develop the hardware. The sift and multiplier type divider is used for Encoder and Syndrome module design.
SCIENCE VERSUS PHILOSOPHY, PROPOUNDED BY ANNMBHATT SPECIAL PERSPECTIVE ON GRAVITY
Authors: Gupta Ayush
Published: September 2021

Annambhatna, the author of the argument, has said "adyapatana samvayikaranam gravitvam"1 while defining the property called gravity in the order of merits in the collection of arguments. That is to say that the unusual cause of the first reaction is called gravity. Ã¢Â€ÂœDvitiya dipatnasyavega samvayikaranatvada veges tivyaptivaranayadyetiÃ¢Â€Â i.e. to prevent overlapping in velocity etc There is an unusual reason for that first process. Here it is certainly necessary to appreciate the subtle vision and technical and scientific knowledge of Annabhatt. The symptoms were also reasonable to some extent but they knew that once the deceleration process has started in the object, the velocity generated by that deceleration process is the cause of the forward reaction. Thus the progressively generated velocity is the cause of the progressive deceleration process. The scientific explanation of the process is as follows.
THE YACYRETA HOUSING COMPLEX: 20 YEARS LATER
Authors:   Postgraduate School - National University of Itapua - Encarnacion, Paraguay., Servin Santa Cruz M.A. , Servin Nasich M.R. ,   Postgraduate School - National University of Itapua - Encarnacion, Paraguay., Insfran O.A. ,   Forest Ecology and Restoration Group - University of Alcala - Madrid, Spain.
Published: September 2021

Dams tend to have both positive and negative social, economic and environmental impacts in their area of influence. This article focuses on the social impacts, especially those related to the housing of the relocated population in the San Roque Gonzalez de Santa Cruz neighborhood, also known as the Arroyo Pora Housing Complex, located in the municipality of Cambyreta (Paraguay), 20 years after the first wave of relocations (1999). The objective of the study is to describe the current situation of these housing units, considering aspects such as housing tenure, conformity, modifications and maintenance, to mention some variables, according to the passage of time. For this purpose, it uses a semi-structured survey to a sample of the aforementioned population. The study found that the displaced population had to adapt the house given to them for relocation purposes to their needs, mainly due to an increase in the population per family unit. Additionally, during this research new owners were identified, as well as caretakers and tenants, who settled after the relocation period, resulting in a loss of homogeneity of the population. These situations could indicate that the recommendations related to the management of involuntary resettlement processes were not taken into account in this case.
IMPACT OF DIGITAL WALLETS ON CONSUMER BEHAVIOR IN INDIA
Authors:   Delhi Public School, R.K. Puram., Singh Sarna Ishaan
Published: September 2021

In todays tech-driven world, digital wallets such as Paytm, GPay, MobiKwik, and so on, are gaining immense popularity among consumers. With economies becoming digital as more and more consumers opt for computerized alternatives to the traditional leather wallet, the industry has become a profitable base for potential investors. In India, specifically, the growth of digital wallets has been propelled by the demonetization policy, which significantly reduced the volume of currency in circulation, implemented by the government in 2016. One of the major consequences of an increase in the popularity of digital wallets has been a shift in the behaviors and spending habits of consumers, particularly in India, where the transition to a cashless economy has been considerably rapid. The goal of this study is to assess the apparent impact of the transition to digital economies on consumer behavior, and the various factors associated with this shift. This assessment was made by surveying users of digital wallets, between the ages 18 and 65, to seek their responses on how shifting to digital wallets has impacted them, their spending habits, etc. The responses were closely analyzed and interpreted to come to a conclusion.
A STUDY ON THE DIFFICULTIES IN PRONUNCIATION OF ESL LEARNERS
Authors:   B.Tech Student, School of Electrical Engineering (SELECT), Vellore Institute of Technology, Chennai, Tamilnadu, India., Nanda Subham , B.R Aravind ,   Research Associate, School of Social Sciences and Languages (SSL), Vellore Institute of Technology, Chennai, Tamilnadu, India., V Rajasekaran ,   Assistant Professor Senior, School of Social Sciences and Languages (SSL), Vellore Institute of Technology, Chennai, Tamilnadu, India.
Published: September 2021

In many ESL classes across the globe, English pronunciation is still not given enough attention. One of the primary reasons why it is overlooked is because there arent many pronunciation techniques accessible to instructors in the context of the school setting. The purpose of this research is to identify the problems in English pronunciation that learners experience as a result of the presence of Mother Tongue (MT) interference in their speech. In this article, the survey technique was used to gather information from a variety of sources, including interviews, personal conversations over the phone, and meetings. The report also included suggestions and recommendations for reducing the pronunciation difficulties that ESL learners encounter. There were a total of 102 samples gathered through Google forms in India. The findings of the study are discussed in detail in the interpretation.
STOCK MARKET LINKAGES AND CAUSAL RELATIONSHIPS: EMPIRICAL INVESTIGATION OF EM7 ECONOMIES
Authors:   Senior Research Fellow, Department Of Commerce, University of Kashmir, J&K, India., Ud Din Dar Mearaj , Ahmad Butt Khursheed ,   Senior Professor, Department Of Commerce, University of Kashmir, J&K, India.
Published: September 2021

Diffusion of information in the present era has become very fast, whether it is related to natural phenomena or human activities. Due to the technological advancement and fast face globalisation and liberalisation, events happening in financial markets are no exception, especially due to electronic stock exchanges and free flow of capital and financial information across borders. The present study aims to examine return patterns and find inter linkages/integration among the stock markets of seven largest emerging economies popularly known as EM7 (India, China, Russia, Brazil, Indonesia, Mexico and Turkey) by examining the monthly return data from Jan 2010 to Dec 2019. The study used descriptive analysis, correlation analysis, regression analysis and causality test to attain its objectives. The results indicate that EM7 stock markets are not interlinked, suggesting markets are quite segmented and there is scope for fund managers and both international and domestic investors to reap the advantages of portfolio diversification and mitigate the risks associated with their investments.
The emergence of soft skills in agricultural education
Authors: Juhász Tímea , Horváth-Csikós Gabriella
Published: September 2021

As the possession of soft skills is becoming an essential part of the basic skill set of entrants, it is undoubtedly essential to research and develop these skills. The purpose of this study was to examine how students studying at the largest agricultural university in Hungary perceive their soft skills to be in line with employers’ expectations, i.e. whether demand matches supply, in what qualities students feel strong, what employers expect, how well supply and demand in the agricultural labor market match in terms of soft skills. Furthermore, whether educational institutions are able to develop these qualities in students and what other possibilities there might be to strengthen these qualities. The research results confirmed that the university students in the sample perceive the quality of their soft skills to be influenced by several factors, including age, gender and work experience. They show that women over 40 with work experience tend to have stronger emotional soft skills, while men of the same age who have not started their careers are stronger in leadership skills. The study also concluded that students do not feel that current schooling in institutions can strengthen the soft skills expected by the labor market (the average on a five-point Likert scale was 2.74), while the development of these soft skills was considered by respondents to be as important as the development of hard skills (agreement was very high with an average of 4.52 on a five-point Likert scale).
How can we govern large-scale green infrastructure for multiple water security benefits?
Authors: Pecharroman Lidia Cano , Williams Christopher , Nylen Nell Green , Kiparsky Michael
Published: September 2021

Traditional, limited purpose grey infrastructure has failed to address the world's interrelated water challenges. Improving water security will increasingly require more integrated responses. This paper examines large-scale green infrastructure (LSGI), planned natural or hybrid systems that materially affect water security at the watershed scale, as one such response. This paper examines key challenges for governing and financing LSGI, which hinder its broader use. We report on four case studies located in the United States where LSGI is being employed to improve water security. Through analysis of these case studies and related literature, we identify three themes important for LSGI governance: cost sharing, performance monitoring, and legitimization. First, we hypothesize that formal cost sharing based on the multiple benefits LSGI provides could enable wider adoption, but find that in these examples cost sharing is limited and informal. Second, our research suggests that expanding performance monitoring to encompass key secondary benefits could help clarify how the benefits and burdens of a project are distributed across stakeholders, facilitate cost sharing, and enhance project legitimacy. Finally, LSGI will require further legitimization – developing a broader perception that LSGI is an appropriate alternative or complement to grey infrastructure – to develop as a viable contributor to water security.
Organic matter parameters in WWTP – a critical review and recommendations for application in activated sludge modelling
Authors: Ahnert Markus , Schalk Thomas , Brückner Heike , Effenberger Johannes , Kuehn Volker , Krebs Peter
Published: September 2021

This paper includes a comprehensive literature review of sludge composition data from wastewater treatment plants. 722 data sets from 249 sources were used to establish typical ratios between COD and solids-based parameters and to verify rule-of-thumb values, respectively. Confirmation of these typical ratios can also be accomplished by using biochemical composition data. It is shown that a correlation between data from proteins, lipids and carbohydrates analysis can be related to COD/VSS ratios. Finally, using the findings from the literature review, the organic and inorganic conversion factors of COD fractions in activated sludge models are adjusted to solids-based parameters. It was shown that with the adjustments of the factors and a partition of the particulate inert fraction into a fraction assigned to the influent and a fraction assigned to the endogenous products, a better agreement with the ratios of COD/VSS in the individual sludge streams can be established.
Provision of Gefitinib as Targeted Therapy in Lung Adenocarcinoma with EGFR Mutation and Brain Metastatic
Authors: Widiasari Komang Sri Rahayu
Published: September 2021

Adenocarcinoma is a malignant epithelial tumor with glandular differentiation or mucin production. Adenocarcinoma covers 30% of lung cancers in Europe and America. This report described a case of an unusual chronic headache since 3 years ago without any complementing symptom except for nausea. The primary tumor was detected with Thorax CT scan and confirmed by histopathology examination. Patient treated with gefitinib (1 x 250 mg) and showed a satisfying result. Gefitinib, as first-line therapy for patients with epidermal growth factor receptor ( EGFR) mutation, was effective and well-tolerated in this patient.
Myastehenia Gravis is Caused by the Thymoma in Anterosuperior Mediastinum Sinistra and Posteroinferior Sinistra
Authors: Irfan Ferdy Syah , Djajalaksana Susanthy
Published: September 2021

Background: Thymoma is the most common thymus tumor; it covers 30% of the anterior mediastinum mass in adult. Almost half of thymoma does not present with any symptom and is found by accident. In 40% of patients have symptom of myasthenia gravis; other symptoms include chest pain, symptoms of bleeding and compression to other mediastinumâ€™s structures. Ninety percent of thymoma is located in anterior mediastinum.Case: A 42-year-old woman came to Saiful Anwar Hospital with a complaint of difficulty in swallowing since three months before admission. We performed physical examination and chest X-ray APâ€™ and the result was within normal limit. In USG examination, there was no abnormality. From the laboratory examination, we found leucocytosis and from the CT-scan imaging, we found pocketed pleural effusion sinistra at the postero-inferior part.Based on these findings, we diagnosed (pre-operation diagnosis) this patient as anterosuperior mediastinum tumor: suspect thymoma. The pulmonologist consulted to Surgical Department for surgery. The surgeon performed sternotomy-tumor excision. The result from the vries coup and histopathogical examination was thymoma. FOB after the surgery showed an edema at the right vocal cord (post-extubation). Post-operative chest X-ray showed no mass in antero-superior mediastinum.
The Role of Surgical Resection as A Salvage Therapy and Immunohistochemical Stain to Confirm Mediastinal Yolk Sac Tumor
Authors: Eka Agustina Dwi Rosa , Pratiwi Suryanti Dwi , Retnani Diah Prabawati , Isharanto Artono , Erawati Rachma Dini
Published: September 2021

Background: Mediastinal germ cell tumors are uncommon, representing less than 1% of all malignancies. They mostly occur in young men after puberty and have a poor prognosis with over all long term survival rate 42%. Case Report: We reported a case report in Saiful Anwar Malang Hospital, Indonesia, a young man, 26 years old with an anterior mediastinum tumor and VCSS The CT scan of the chest showed an anterosuperior mediastinal mass which compress the superior vena cava. The result from transthoracic FNAB with USG guidance showed an extragonadal germ cell tumor which resemble an Embryonal Carcinoma from mediastinum. The AFP serum level was elevated. Patient underwent a radiotherapy and a surgical debulking. The biopsy showed an Endodermal Sinus Tumor (Yolk Sac). Immunohistochemical stain for cytokeratin was positive in the tumor cells while stain for CD30 was negative. These were confirming the diagnosis of primary mediastinal yolk sac tumor. Patient received a combination chemotherapy for a total 6 cycles.Conclusion: Some procedures like biopsy, tumor marker, immunohistochemical stain, could differentiate the subtype of mediastinal germ cell tumor. The multimodality treatment by combining chemotherapy with surgical therapy or radiotherapy could increase the survival outcome of patients.
Virtual Reality in Health Care: Bibliometric Analysis
Authors: Pawassar Christian Matthias , Tiberius Victor
Published: September 2021

Background

Research into the application of virtual reality technology in the health care sector has rapidly increased, resulting in a large body of research that is difficult to keep up with.

Objective

We will provide an overview of the annual publication numbers in this field and the most productive and influential countries, journals, and authors, as well as the most used, most co-occurring, and most recent keywords.

Methods

Based on a data set of 356 publications and 20,363 citations derived from Web of Science, we conducted a bibliometric analysis using BibExcel, HistCite, and VOSviewer.

Results

The strongest growth in publications occurred in 2020, accounting for 29.49% of all publications so far. The most productive countries are the United States, the United Kingdom, and Spain; the most influential countries are the United States, Canada, and the United Kingdom. The most productive journals are the Journal of Medical Internet Research (JMIR), JMIR Serious Games, and the Games for Health Journal; the most influential journals are Patient Education and Counselling, Medical Education, and Quality of Life Research. The most productive authors are Riva, del Piccolo, and Schwebel; the most influential authors are Finset, del Piccolo, and Eide. The most frequently occurring keywords other than “virtual” and “reality” are “training,” “trial,” and “patients.” The most relevant research themes are communication, education, and novel treatments; the most recent research trends are fitness and exergames.

Conclusions

The analysis shows that the field has left its infant state and its specialization is advancing, with a clear focus on patient usability.
Exploring the Use of Genomic and Routinely Collected Data: Narrative Literature Review and Interview Study (Preprint)
Authors: Daniels Helen , Jones Kerina Helen , Heys Sharon , Ford David Vincent
Published: September 2021

BACKGROUND

Advancing the use of genomic data with routinely collected health data holds great promise for health care and research. Increasing the use of these data is a high priority to understand and address the causes of disease.

OBJECTIVE

This study aims to provide an outline of the use of genomic data alongside routinely collected data in health research to date. As this field prepares to move forward, it is important to take stock of the current state of play in order to highlight new avenues for development, identify challenges, and ensure that adequate data governance models are in place for safe and socially acceptable progress.

METHODS

We conducted a literature review to draw information from past studies that have used genomic and routinely collected data and conducted interviews with individuals who use these data for health research. We collected data on the following: the rationale of using genomic data in conjunction with routinely collected data, types of genomic and routinely collected data used, data sources, project approvals, governance and access models, and challenges encountered.

RESULTS

The main purpose of using genomic and routinely collected data was to conduct genome-wide and phenome-wide association studies. Routine data sources included electronic health records, disease and death registries, health insurance systems, and deprivation indices. The types of genomic data included polygenic risk scores, single nucleotide polymorphisms, and measures of genetic activity, and biobanks generally provided these data. Although the literature search showed that biobanks released data to researchers, the case studies revealed a growing tendency for use within a data safe haven. Challenges of working with these data revolved around data collection, data storage, technical, and data privacy issues.

CONCLUSIONS

Using genomic and routinely collected data holds great promise for progressing health research. Several challenges are involved, particularly in terms of privacy. Overcoming these barriers will ensure that the use of these data to progress health research can be exploited to its full potential.
A era dos deveres: a necessidade de um estatuto da pessoa humana para a eficácia social dos direitos fundamentais
Authors: Dias da Costa Lyra José Francisco , Preis Marco Antônio , Homem de Siquiera Julio , Fabriz Daury Cesar
Published: September 2021

A eficácia dos direitos fundamentais passa, atualmente, por uma crise: os esforços pelo reconhecimento desses direitos não têm sido acompanhados pela sua real e efetiva concretização. O resultado é um grande número de direitos reconhecidos para os membros de uma sociedade que até obtém êxito ao reivindicá-los, mas não em deles usufruir de maneira adequada. A proposta deste trabalho é, a partir do uso do método dialógico, demonstrar como o cumprimento de deveres fundamentais pode contribuir para a cada vez maior concretização dos direitos. Para demonstrar essa tese, desenvolve-se, em primeiro lugar, a defesa sobre a necessidade de um estatuto da pessoa humana, baseado não apenas em seus direitos, mas também e principalmente, em seus deveres; em segundo lugar, agrega-se à ideia de um estatuto uma proposta de como operacionalizar a relação entre o cumprimento de deveres e a concretização de direitos de maneira cíclica. A conclusão alcançada com essa proposta é a de que o resgate da categoria dos deveres pode contribuir para o fortalecimento dos direitos para todos, superada a visão estritamente individual.