bluuebunny/crossref_metadata_2025 huggingface dataset:
Abnormal Emotion Detection of Tennis Players by Using Physiological Signal and Mobile Computing
Authors: Sun Xiaoyan
Published: May 2022

Emotion is an important research topic in the field of sports. The physiological changes caused by emotion have a great influence on the completion of sports. It cannot only fully mobilize the organism and maximize the exercise potential, but also lead to muscle stiffness, movement deformation, or muscle contraction weakness. Furthermore, it can affect the completion of exercise. In order to ensure the athlete can keep the best competitive level, it is necessary to estimate the athlete's emotion before competition. This paper adopts the pulse wave signal to implement the emotion estimation for the athletes. First, the pulse wave signals are collected by using a portable sensor via mobile computing. Then, the collected pulse wave signals have noises removed by wavelet transform. Last, the denoised pulse wave signals are represented as the features in time domain and frequency domain to input into a trained classifier for determining the current emotion status. The experimental results show that the proposed method can recognize more than 90% of the abnormal emotions.
Technical and Economic Evaluation and Development Policy Suggestions of LNG Power Plants
Authors: Li Jiaojiao , Zhao Linfeng
Published: May 2022

The return on investment (RIO) of a Liquefied natural gas (LNG) power plant is lower than that of conventional power plants with high pollution due to the “take or pay” supply mode of natural gas and the two-shift peak shaving operation mode in the LNG power plants. . In this paper, firstly, based on the characteristics of the gas turbine combined cycle (GTCC) unit for peak shaving and standby application, it is proposed to calculate the generation cost of LNG power plants according to the depreciation of operation life. Secondly, through the sensitivity analysis of power generation cost, it is found that fuel price and average efficiency are the first influencing factors. Next, to reflect the environmental protection characteristics of LNG power plants, the on-grid price included in the environmental value is put forward innovatively based on the calculation of the environmental cost and environmental value of natural gas power generation.
A Qualitative Study on Non-English Majored Learners' Adaptability to Blended Learning in College English
Authors: Yang Shuhan , Pu Ruihui
Published: May 2022

The success of blended learning depends on many factors. Among these, adaptability, though acknowledged as an important issue in blended learning, warrants further study, together with its influencing factors. This study aimed to explore non-English majored learners' adaptability to blended learning in College English from the perspective of English teachers. Semi-structured interviews with 16 English instructors from five universities were conducted, and the interview transcripts were qualitatively analyzed. The results showed that the non-English majored learners were not perceived to have fully adapted themselves to the new mode of College English, and their adaptability was highly affected by agentive factors and contextual factors. The findings emphasize the key role of learners' adaptability in blended learning environments. Additionally, this study further provides a vital insight for administrators and instructors to reconsider the role of learners' responses to the blended learning mode and apply this understanding to improve achievement in English courses.
Modeling, Integration, and Automation of Degradation to Generate Asset Lifespan Analytics Using
Authors: Obi (https://orcid.org/0000-0003-4976-6181) Emenike Raymond , Nwajana Augustine O.
Published: May 2022

The degradation of metallic industrial assets, equipment, and components costs governments, industries, and citizens billions of dollars a year. Also, the degradation of industrial assets and infrastructure proliferates a myriad of safety problems. AssessLIFE software addresses this strategic deficiency by focusing on forecasting strategies rather than on mitigation strategies in the active battle against industrial asset degradation. By employing tested and proven scientific analytical computations, forecasting, prediction, and analytics, the AssessLIFE software plans to significantly reduce the billions of dollars expended via inspection, treatment, and repair of degradation-prone assets and infrastructure. The AssessLIFE software leverages many scientific studies and research in many fields of engineering. The AssessLIFE software also emphasizes the computerization or automation of the processes of metallic (alloys and welds) degradation mechanisms and parameters using digital techniques.
Traffic Signal Timing Optimisation for Several Intersections in High-Priority Congested Networks Improved on Genetic Algorithm
Authors: Chaima Kouidri , Rochdi Bachir Bouiadjra , Faiza Mahi
Published: May 2022

Nowadays, getting around has become an essential aspect of everyday life, whether it be public transport or personal vehicles, the vast network formed by these means of transport is immensely complex to manage. Unfortunately, this activity presents serious problems in most cities around the world. In this paper we upgrade traffic capacity of intersections using Genetic algorithm in order to decrease traffic congestion and crossing time of a road network. The main focus of this study is on improving the quality of solutions for the traffic light optimization problem. This proposition calculated and simulated through programming. As it shows, It improve results for solving the cycle traffic light problem (CTLP).
Floptics
Authors: Sriphum Wiwat , Wills Gary B. , Green Nicolas G.
Published: May 2022

Flow cytometry (FCM) determines the characteristics of individual biological cells using optical and fluorescence measurements. It is a widely used standard method for analysing blood samples in medical diagnostics, through identifying and quantifying the different types of cells in the samples. The multidimensional dataset obtained from FCM is large and complex, so it is difficult and time-consuming to analyse manually. The main process of differentiation and therefore labelling of the different cell populations in the data is referred to as Gating. This is the first step of FCM and is highly subjective, an issue that significant research has focussed on reducing. Existing automated gating techniques are time-consuming or retain subjectivity by requiring many user-defined parameters. This paper presents FLOPTICS: a novel automated gating technique that is a combination of density-based and grid-based clustering algorithms. FLOPTICS has an ability to classify and label cell populations in FCM data faster and with fewer user-defined parameters than many state-of-the-art techniques.
A Complex Networks Analysis of Ecological Corridors Classification with ECSuite
Authors: Podda Enrico , Fenu Gianni
Published: May 2022

The ecological corridors allow protected species to migrate autonomously between the areas defined by the Natura 2000 project. Although corridors bring multiple advantages in theory, in practice their addition increases exponentially the complexity of managing the territory and monitoring the fauna. Through the use of the software suite exposed in this paper, it is possible to study the ecological corridor simply and effectively, thanks to the classification and representation of the central and critical patches. The paper will focus on the structure and functioning of ECGraph, the software that deals with the logic needed to identify the crucial nodes of the corridor thanks to the theories of complex networks. Some considerations have also been added to the description of the software for its future refinement thanks to some metrics not yet implemented. Each step of its functioning will also be represented thanks to ECOverview, a graphic software designed and developed for a simpler representation of the results obtained by ECGraph.
Do Authentic Leadership and Transformational Leadership Promote LMX in a Context of Political Instability?
Authors: Ben Abdallah Istabrak , Sghari Amira , Chaabouni Jamil
Published: May 2022

In a context of change, the literature highlights the importance of both transformational and authentic leadership styles in maintaining the quality of the relationship between leaders and followers. To the authors' knowledge, no research has addressed this relationship in a context of political instability. So, this research seeks to study the influence of both transformational and authentic leadership styles on LMX in a period of political instability. The objective is to know whether these two styles of leadership remain effective in a context of democratic transition. To this end, a quantitative approach is adopted. A questionnaire was distributed to 126 managers belonging to industrial firms in Tunisia. Unlike the literature, authentic leadership does not influence the LMX. The latter is partially influenced by transformational leadership. Therefore, it is important to consider other factors such as political skills in order to maintain the quality of LMX in a situation of political instability.
Evolution of Artificial Intelligence in Bone Fracture Detection
Authors: Mishra Deepti , Mishra Amit Kumar
Published: May 2022

The objective of the paper is to present the techniques of Artificial Intelligence based on deep learning that can be applied to detect fractures in bones on X-rays. The paper comprises of discussions of various entities. Initially, there is a discussion on data formulation and processing. Following which, distinguished image processing techniques are presented for fracture detection. Later, there is an analysis of conventional and current neural network methodologies for fracture detection techniques. Furthermore, there is a comparative analysis for the same. Finally, in the end, a discussion is presented in the paper regarding problems and challenges confronted by researchers for fracture detection. The study shows, deep learning techniques provide accuracy in the diagnosis than the conventional methods in fracture detection on X-rays. The paper leads to a path for the researchers to deal with difficulties and issues encountered with the fracture detection on X-rays while using deep learning techniques.
An Extensive Survey on Blockchain-Based Electronic Health Record Systems
Authors: Bharimalla Pranab Kumar , Dash Satya Ranjan , Choudhury Hammad S.
Published: May 2022

Healthcare systems around the world are beset by problems due to the lack of effective communication. Significant problems relating to patient medical records access, transition, and storage have persisted due to the lack of resources to adequately interact and track records between all main participants. To overcome this challenge, a nationwide Electronic Health Record (EHR) solution may be utilized. To further enhance EHR efficiency, Blockchain technology can be used to improve security, performance, and cost. In this survey, various literature proposing Blockchain-based EHR systems are discussed, along with their benefits and potential research gaps. Also Authors proposed a comprehensive architecture that could bridge all the gaps.
Diagnosing COVID-19 From Chest CT Scan Images Using Deep Learning Models
Authors: Tiwari Shamik , Jain Anurag , Chawla Sunil Kumar
Published: May 2022

A novel coronavirus named COVID-19 has spread speedily and has triggered a worldwide outbreak of respiratory illness. Early diagnosis is always crucial for pandemic control. Compared to RT-PCR, chest computed tomography (CT) imaging is the more consistent, concrete, and prompt method to identify COVID-19 patients. For clinical diagnostics, the information received from computed tomography scans is critical. So there is a need to develop an image analysis technique for detecting viral epidemics from computed tomography scan pictures. Using DenseNet, ResNet, CapsNet, and 3D-ConvNet, four deep machine learning-based architectures have been proposed for COVID-19 diagnosis from chest computed tomography scans. From the experimental results, it is found that all the architectures are providing effective accuracy, of which the COVID-DNet model has reached the highest accuracy of 99%. Proposed architectures are accessible at https://github.com/shamiktiwari/CTscanCovi19 can be utilized to support radiologists and reserachers in validating their initial screening.
A Review of Axioms for Group Contest Success Functions
Authors: Hausken Kjell
Published: May 2022

Axioms are reviewed for group contest success functions for general production functions, focusing particularly on the additive production function and the multiplicative Cobb-Douglas production function. With one minor exception, these axioms already exist in the literature. This article clarifies which axioms apply and how they apply for group contest success functions. Essential for axioms satisfied by the additive production function, driven by substitutability across efforts, is the sufficiency of only one group member exerting effort. Essential for axioms satisfied by the multiplicative production function, driven by complementarity across efforts, is that all group members exert efforts. The additive production function satisfies an axiom where adding an amount to one effort and subtracting the same amount from a second equivalent substitutable effort does not change the winning probabilities. The Cobb-Douglas production function satisfies a strong homogeneity axiom where an equiproportionate change in matched group member efforts does not affect the winning probabilities.
Investigation of Mechanical and Tribological Properties of LM6-Fly Ash Metal Matrix Composite
Authors: Dhar Asim Kumar , Sutradhar Goutam
Published: May 2022

Composite materials assume a significant part in auto, aviation, marine, and defense applications due to its unique properties. Aluminum alloys have certain advantages over other alloys. In this paper, the composite material comprised of Aluminum Alloy LM6 and fly ash (150 – 175 μm) has been picked as lattice and supporting materials individually. Magnesium is added to lessen the surface pressure and evade the dismissal of the particles from the melts. Liquid state processing through stir casting procedure was adopted for fabrication of mmc into necessary shape and size according to the ASTM principles by energetically mixing at consistent speed and time. The fly ash with various syntheses (2%, 4%, 6%) were added with LM6 combination. XRD and EDAX were used to examine the structural analysis of MMC, and optical microscopy and SEM were used to investigate the microstructure on MMC. Wear test was also carried out on MMC to ascertain the wear rate and cof of different MMCs. There is substantial improvement of mechanical properties like tensile strength, micro hardness, and density of the composite.
Challenges to Current Sustainability Assessment Frameworks
Authors: Belinky Aron , Saraiva Mario H. , Miyake Alexandre
Published: May 2022

Assessing performance, risks and opportunities of companies from a sustainability perspective is a matter of growing interest to managers, investors and other stakeholders. However, it is also a challenging task, especially due to the combination between the complexity of the sustainable development agenda and the volume and diversity of information needed. Usual methods rely mainly on companies’ disclosures and environmental, social and governance (ESG) frameworks, but two recent facts are expected to re-shape the field: the United Nations’ Sustainable Development Goals (SDG), and the application of Big Data and Artificial Intelligence (BDAI) on the field of corporate sustainability. Building mainly on a series of roundtables and interviews with international experts and Brazilian companies, this article presents novel insights on BDAI applied to sustainability assessment of firms. Key conclusions include the recognition that BDAI has great potential contribution, but its effectiveness is deeply affected by specific institutional, methodological and technological factors.
Comparative Analysis of Conventional, Artificial Intelligence, and Hybrid-Based MPPT Technique for 852.6-Watt PV System
Authors: Yadav Dilip , Singh Nidhi
Published: May 2022

In this article, Matlab & Simulation software is used for analysis and comparison of 8(Eight) different MPPT. Different MPPT techniques that have been considered in this article are PWM-based, Perturb and Observation (P&O), Incremental Conductance (InC), and Modified InC (MIC) that comes under the Conventional Method. In the Artificial Intelligence, Fuzzy Logic Controller (FLC), Artificial Neural Network (ANN) is chosen and in Hybrid method Neuro-Fuzzy Network (NFN) and Adaptive Neural Fuzzy Inference System (ANFIS) has been considered. PV module of 852.2 Watt is designed with the Boost Converter which can boost the voltage up to 185 Volt for all MPPT. A set of data has been taken for FLC, ANN, NFN, and ANFIS. After implementation, the result has been analyzed for standard test conditions and for the different environmental conditions. In this article, both irradiation and the temperature have been varied together for all MPPT rest are kept constant.
Design of Authenticated and Trusted Academic Certification Using Blockchain Technology
Authors: Ofori-Mensah Joseph , Yaokumah Winfred , Sakyi Ebenezer Agyemang
Published: May 2022

It is more expensive to handle forged certificates rather than take stringent measures to prevent such occurrences. Forged certificates can lead to loss of integrity and credibility in the certificates and loss of public confidence and trust in the certificate awarding institutions. This study proposed a blend of emerging technologies that include Blockchain Smart Contract for authenticating academic certificates using the West African Examinations Council (WAEC) as the case study. The study presents a detailed design of authenticated and trusted academic certification using Blockchain technology. The Ethereum Smart Contract was used to govern, manage, and provide traceability and visibility in a manner that is secured, decentralized, and globally accessible with high integrity and transparency. Findings from the study revealed various processes by which WAEC authenticates the certificates they issued and that Blockchain technology tends to improve its methods of verification.
A Hybrid System for Heart Disease Diagnosis Based on HPCBE Method
Authors: Rani Pooja , Kumar Rajneesh , Jain Anurag
Published: May 2022

Heart disease is a type of chronic disease that can lead to death if not diagnosed in time. A clinical decision support system developed using machine learning technology can be used in the diagnosis of disease. Proper utilization of feature selection increases classification accuracy by reducing the computational cost. The purpose of this research work is to purpose a new Hybrid Pearson Correlation with Backward Elimination (HPCBE) feature selection method. Proposed HPCBE method is further used to develop a hybrid system for heart disease diagnosis (HSHDD).HPCBE is proposed by combining pearson correlation (PC) and backward elimination (BE) methods. Reduced feature subset selected by HPCBE method is used along with decision tree (DT), k-nearest neighbor (KNN), extreme gradient boosting (XGBoost) and adaptive boosting (AdaBoost) classifiers to develop HSHDD. The feature reduction ratio of 53.84% is achieved by the proposed HPCBE Feature Selection method. HSHDD achieved a maximum accuracy of 86.49% in heart disease classification with AdaBoost classifier.
Osmotic Message-Oriented Middleware for Internet of Things
Authors: Gamal Islam
Published: May 2022

In this paper will be addressing the managed operation of entities at various infrastructures to assist the automated orchestration of Internet of Things services which is a major challenge connected to the practical implementation of IoT. This concept is described to as “osmotic provisioning orchestration” which is basically the monitoring, automation, and orchestration principles so it can oversee the osmotic ecosystem. we will show in this paper the architectural design of an osmotic orchestrator tackling this challenge depending on trending protocols and technologies. the solution proposed will integrate will trending technologies like the cloud computing, with other more recent technologies like edge computing, osmotic computing, and osmotic provisioning. In addition, we will propose a prototype of the architecture that has been created using an open-source application and microservices technologies, taking into consideration the cloud and edge domains.
Modeling Autonomic Systems
Authors: Hachicha Marwa , Ben Halima Riadh , Kacem Ahmed Hadj
Published: May 2022

Today software systems are very complex and changing. Therefore, preserving their functionality and the quality of their service seems to be a difficult. Consequently, the concept of self-adaptation was introduced to handle the problem of the increasing complexity and dynamism of modern software systems. In this context, researchers have been studying self-adaptation for over a decade, which has resulted in a vast body of knowledge. Nevertheless, as technology progresses and software systems are increasingly integrated, new challenges emerge. Among these challenges are the need for new engineering approaches and methods to model and verify self-adaptive systems.In this paper, we provide a survey on modeling and verifying self-adaptive systems through presenting and classifying the main existing approaches that have made significant progress in this area.
Improved Particle Swarm Optimization With Spiral Updating Mechanism for Multimodal Image Registration
Authors: Saxena Sanjeev , Pohit Mausumi
Published: May 2022

A modified particle swarm optimization (PSO) algorithm is proposed with a spiral updating mechanism (Spiral-PSO) to optimize the balance between exploration and exploitation phases of the standard PSO. The Spiral-PSO approach reduces the possibility of the local optima trapping issue during the optimization process. The proposed algorithm has been tested with 23 standard benchmark functions to compare the Spiral-PSO with the standard PSO algorithm. We report the application of the Spiral-PSO for registration of multimodal remote sensing images and compared the registration results with that of the standard PSO. The proposed approach performs successful image registration and provide better optimization of objective functions as compared to conventional PSO.
A Study on Transfer Functions of Binary Particle Swarm Optimization for Energy-Efficient VM Placement
Authors: Tripathi Atul , Tripathi Isha Pathak , Vidyarthi Deo Prakash
Published: May 2022

Cloud computing has emerged as the backbone of the IT industry for infrastructural support. In cloud computing, resources are virtualized in form of Virtual Machines which eventually is mapped to physical infrastructure. Energy-efficient virtual machine placement is an important problem in cloud computing and has attracted the attention of researchers in recent. As virtual machine placement is an NP-hard problem, meta-heuristics have often been applied vastly for this. In one of our earlier works, Modified Binary Particle Swarm Optimization algorithm has been applied for the VM placement. It was observed therein that the transfer function, which plays an important role to obtain an optima, does not completely avoid the problem of local optima. Therefore, in this work, we have studied the behavior of eight different transfer functions towards this property. For this, energy-efficient VM placement problem is modelled as multi-objective optimization problem and Binary Particle Swarm Optimization is applied. The study is done by simulation and their statistical analysis.
Sine Cosine Algorithm for Solving Economic Load Dispatch Problem With Penetration of Renewables
Authors: Verma Diwakar , Soni Jatin , Kalathia Dhruv , Bhattacharjee Kuntal
Published: May 2022

Economic Load Dispatch is used to allocate power demand economically among connected generators by considering various constraints. The thermal generating units are incorporated with renewable sources like wind and solar units to reduce pollution and dependency on fuel cost. The uncertainty of output power from wind and solar plants is considered here. The 2-m point estimation method is used to get generated power from wind and solar units. The population-based Sine Cosine Algorithm is proposed to get the optimum solution of the presented complex ELD problem. The randomly placed search agents find an optimum solution according to their fitness values and keep path towards best solution attained by each search agent. The search agents avoid local optima in exploration stage and move towards the solution exploitation stage using sine and cosine functions. The proposed algorithm has been tested in various four test systems. The results proved that the proposed algorithm gives quite an effective, efficient and promising solution compared to other techniques.
Crow-Water Wave Optimization Algorithm for Privacy-Preserved Collaborative Data Publishing
Authors: Gnaneshwari G. R.  , Hema M. S.
Published: May 2022

The main motive of this research is the development of CWWO-based encoding algorithm for conserving the privacy of medical data. The privacy preservation of published data relies on the four privacy constraints. While publishing the record, the Service provider(SP) suggests the information to the unauthorized person in which the privacy needs to be preserved. The privacy preservation of medical record is relies on the constraints, like the k-anonymity, l-diversity, the m-privacy and f-sensitive. These privacy constraints are must be satisfied while publishing the data, and in case it is not satisfied, the C-mixture enhances these security constraints. Once the privacy parameters are satisfied, then the fitness value is computed. The fitness with minimum value is considered as best value for publishing the information and hence the privacy is to be enhanced.
Research on Detection and Recognition of Traffic Signs Based on Convolutional Neural Networks
Authors: Liu Hongwei , Li Xiang , Gong Wenyin
Published: May 2022

The road traffic sign detection and identification (TSDR) system is a subsystem of the advanced driver assistance system. It has received extensive attention from domestic and foreign researchers. The TSDR system is mainly composed of two parts: the detection of traffic signs and the identification and output of traffic signs. This paper focuses on the research of TSDR system and proposes a method based on faster R-CNN combined with part of the low-level feature map. The lightweight model MobileNet is used to finish the traffic sign detection. Experiments show that this method has a certain effect on the detection of small-scale traffic signs, and the detection speed is fast. The LeNet5 and Inception V3 network model are used for traffic sign recognition. The model is optimized by adjusting parameters such as the learning rate and batch size. It shows that for LeNet5, when the learning rate = 0.001, the recognition rate can reach 92.5%. For the Inception V3 model, when the learning rate is 0.005, it has a higher recognition rate than the LeNet5 model by 4.9 percentage points.
Performance Analysis of a Novel Optimal Antenna Selection Algorithm for Large MIMO
Authors: Suryawanshi Rajashree , Kavipriya P. , Patil B. P.
Published: May 2022

LTE MIMO is capable of providing some major enhancements in spectral efficiency and performance along with adding complexity to the system. One way to make sure that the sent data has reached the receiver end is to increase the number of antennas between them. But when the quantities of antennas are increased, there is increase in the probability that deep fading is experienced by at least some antennas. This results in giving out some undesirable outcomes which affects the overall efficiency of the MIMO system. To handle these issues, a reliable technique has been presented that involves selection of antenna subset. The proposed technique incorporates combination of SBO and PSO for antenna selection. The maximum channel capacity of the channel has been considered as the objective function for selecting optimal antennas. The comparison of the proposed approach’s performance and the existing approaches’ performance is done in terms of BER, energy efficiency, spectral efficiency and optimal transmit power.
Multi-Authority Fine-Grained Data Sharing and Search Scheme for Cloud Banking Systems
Authors: Mehla Rajan , Mamta  , Psannis Konstantinos
Published: May 2022

The migration of the banking system to the cloud seems inevitable in near future like any other industry. By leveraging cloud technology, the personal and financial data of any customer can be accessed and controlled by third-party service providers. However, in order to maintain confidentiality, this information should be kept in an encrypted format, which has an impact on the usefulness and flexibility of fundamental operations like search. Moreover, in a financial institution, a data owner may want to provide the searching capability to the users from diverse domains. Therefore, to provide such flexibility, a system of multi-authority fine-grained search is introduced where each authority manages a single but entirely disjoint domain of attributes. As a result, the proposed system is more scalable, it can handle a large number of users from diverse domains and manage their credentials effectively. While most of the schemes in the literature lack this feature, and have a performance bottleneck because of a single centralized trusted authority.
Progressive Study and Investigation of Machine Learning Techniques to Enhance the Efficiency and Effectiveness of Industry 4.0
Authors: Sharma Kaljot , Anand Darpan , Mishra K. K. , Harit Sandeep
Published: May 2022

The goal of this article is to assess the most recent work on Industry 4.0 as well as the present state of science on Industry 4.0 through papers produced between January 2017 and March 2020.A systematic review process with a 5-step approach to article selection was employed, which included the following steps: 1) Selection of database 2) Research of keyword 3) Collection of articles 4) Inclusion/Exclusion criteria 5) Examining Selected Articles. It is noticed that much of the research is philosophical or case-based in character. The prospective study direction described in this paper may be useful to researchers interested in the field of industry 4.0 for research. The paper's future study directions must undoubtedly be beneficial to researchers.
Cyber Security and COVID-19
Authors: Elleh Festus
Published: May 2022

An increasing number of teenagers are now using the internet through their computers, phones, ipads, ipods, laptops, tablets, etc. In the era of COVID-19, where School kids do home schooling using the internet, the number of teenagers using the web will be higher and their presence online will increase. The internet can be a major channel for their education, creativity, and self-expression. However, it also carries a spectrum of cyber risks to which teenagers are more vulnerable than adults. This paper focuses on online risks for teenagers under COVID-19 era and how to protect them from cyber predators. It examines direct and indirect precautionary measures available to these innocent teenagers and their parents to help mitigate online vulnerabilities. The paper believes that, to enhance the policy to protect teenagers online, governments and School Districts should enhance the coherence of their policy measures and tools in collaboration with parents, caregivers, educators, businesses, and civil societies.
City Growth Patterns Intensifying Complexities to Control Vehicular Exhaust Pollution in Pakistan
Authors: Ahmad Niaz
Published: May 2022

Unplanned constructions of high-rise buildings are continuing to fulfill the demand for commercialization in cities. This change in land use has overlooked to consider the associated infrastructure. Beside other problems, it thoroughly escalates vehicular movement and makes the environment more vulnerable. Symptomatic approaches from the government continue but could not succeed to avert the danger permanently. This research has examined circulation pattern and traffic flow on major roads of the city. Beside it, the performance of Vehicle Emission Testing Station is reviewed. The author found that disproportionate change in land use has intensified vehicular movement and the crammed road network spoiled all the curative measures. A professional’s interviews were carried out to understand the problem. During professional discussion many things were found missing within the management system of the city. Therefore, the researcher developed a systematic approach/model to incorporate all aspects of the missing components in order to curb air pollution effectively in cities.
Challenges and Factors Influencing the Adoption of Internet Banking in Qatar
Authors: Alsalem Amna , Abu-Shanab Emad Ahmed
Published: May 2022

The evolution of the Internet and smartphones, people are able to use Internet banking (IB). In addition, banks are able to reduce their operational costs and attract more customers when utilizing IB. The Covid-19 Virus outbreak in encouraged clients to use IB to limit their physical interactions with others. This research utilized the extended Unified Theory for Acceptance and Use of Technology (UTAUT-II) to assess how bank customers adopt IB. 375 online surveys were collected to test eight hypotheses. Results indicated that Performance Expectancy, Social Influence, Security, and Habit were significant predictors of the behavioral intentions to use IB, while Effort Expectancy, Facilitating Conditions, Perceived Value, were insignificant. Age was used as a moderator to habit-behavioral intentions relationship, but data failed to support its role. The overall coefficient of determination was 0.86, which exceeded the original model. Further discussions and conclusions are reported at the end of the paper.
Policy Proposal: Modifying the Federal Earned Income Tax Credit to Better Help Households with One or No Dependents
Authors: Draper Jimmy
Published: May 2022

This paper discusses four recommendations to improve the federal Earned Income Tax Credit, (EITC), which effectively acts as a wage boost for very-low-income and low-income workers. The credit amount varies tremendously depending on the number of dependents one has. This discrepancy is the paper’s main focus. This paper finds that the EITC’s failure to significantly help taxpayers without dependents, among other challenges, limits its ability to fulfill the program’s goals of incentivizing work and reducing poverty. The four recommendations on average would expand the availability and amount of the credit for most lower-income taxpayers. A conventional economic analysis suggests that these changes would likely incentivize work for many (though not all) affected individuals, increase consumer spending, reduce poverty, and increase equity. In a somewhat limited manner, this paper recommends the set of changes for enactment.
Parameter estimation of soil water retention curve with Rao-1 algorithm
Authors: Wang Zhongju , Huang Chao , Wang Long
Published: May 2022

The soil water retention curve (SWRC) has a significant role in determining the unsaturated properties of soil. A stochastic optimization algorithm named Rao-1 algorithm is employed to estimate the parameters of the SWRC model in this paper. The Rao-1 algorithm is a simple heuristic search algorithm containing only addition and multiplication operations. This paper introduces the method and its application in the determination of soil water retention model parameters in detail. In this study, van Genuchten model is used to depict the SWRC for its good fitting capacity, and parameters of the van Genuchten model are determined using Rao-1 algorithm. The feasibility and efficiency of the method are validated via the experimental results of 24 soil samples of 12 soil textural classes. Besides, the performance of Rao-1 algorithm is compared with that of Particle Swarm Optimization algorithm, Differential Evolution algorithm, and RETC program. Through comparative analysis, Rao-1 algorithm outperforms other methods in determining SWRC parameters.
Tentazioni e tentativi nel lavoro quotidiano dell’insegnante: riflessioni oltre la pedagogia della presenza
Authors: Negretti Monica , Negretti Daniela , Mascetti Myriam
Published: May 2022

Questo scritto si propone di rileggere la teoria di Michele Minolli sullo sviluppo dell’Io-Soggetto all’interno del contesto scolastico. Prendendo spunto dalla lettera aperta di un’insegnante, scritta durante la riapertura delle scuole dopo il primo lungo lockdown, la riflessione entra nella quotidianità scolastica per provare a raccontare un approccio educativo definito ‘Pedagogia della Presenza’ che si pone come obiettivo lo sviluppo dell’Io-Soggetto e che mette a fuoco la necessità di ripensare la relazione educativa tra adulto e bambino, relazione in cui anche l’adulto è coinvolto in un processo trasformativo ed è chiamato ad assumersi la responsabilità della qualità della sua Presenza. Il percorso di formazione e ‘metavisione’ qui proposto diventa il luogo di massima esplicitazione del lavoro dell’insegnante su sé stesso.
Commento al film: Lacci
Authors: Sedda Diego
Published: May 2022

Non disponibile
Commento al film: C’è un soffio di vita soltanto
Authors: Lumina Irene
Published: May 2022

Non disponibile
A modified fixation technique for the treatment of buried penis in children
Authors: Cui Xu , Gao Bing-Jing , Chen Liu , Huang Wen-Hua , Zhou Chao-Ming
Published: May 2022

For many years, surgical treatment of buried penis in children has been researched by several scholars, and numerous methods exist. This study aimed to explore the clinical effect of a modified fixation technique in treating buried penis in children. Clinical data of 94 patients with buried penis who were treated using the modified penile fixation technique from March 2017 to February 2019 in Fujian Maternity and Child Health Hospital (Fuzhou, China) were retrospectively collected, compared, and analyzed. Clinical data of 107 patients with buried penis who were treated using traditional penile fixation technique from February 2014 to February 2017 were chosen for comparison. The results showed that at 6 months and 12 months after surgery, the penile lengths in the modified penile fixation group were longer than those in the traditional penile fixation group (both P < 0.05). The incidence of postoperative skin contracture and penile retraction in the modified penile fixation group was less than that in the traditional penile fixation group (P = 0.034 and P = 0.012, respectively). When the two groups were compared in terms of parents’ satisfaction scores, the scores for penile size, penile morphology, and voiding status in the modified penile fixation group were higher than those in the traditional penile fixation group at 2-week, 6-month, and 12-month follow-ups after surgery (all P < 0.05). We concluded that the modified penile fixation technique could effectively reduce the incidence of skin contracture and penile retraction and improve the penile length and satisfaction of patients’ parents.
Socket shield technique
Authors: Sharma Ankit , Maheshwari Komal , Tiwari Bhawana , Naik Dwarakananda
Published: May 2022

The aim of this review is to present the currently available studies on the treatment outcome of socket shield technique (SST) with an attempt to compare it with the conventional technique for immediate implant placement. An electronic search was performed using PubMed, Google Scholar, and Cochrane databases. All relevant human studies reporting the treatment outcome of SST in conjunct with immediate implant placement were included. In vitro studies, case reports, reviews, systematic reviews and articles not related to SST were excluded. The initial electronic database search identified 606 articles. After removing the duplicates, reading the titles and abstracts, 19 articles were eligible for full-text reading. Two case series were excluded as the specific treatment outcomes of the clinical cases were not mentioned. Further, one article was included after hand searching of the reference lists. Eighteen articles were included for the final review. These 18 articles consisted of 15 full texts and 3 abstracts. Out of them, 3 were randomized controlled trials, 7 were retrospective studies, 4 were prospective studies, 1 was a prospective case series, 1 was a prospective nonrandomized controlled study and 2 were comparative studies. This review concludes that though the implant survival rate may be comparable in SST and the conventional technique, the SST seems to perform better in terms of bone preservation, esthetic outcome, and patient satisfaction. Furthermore, further randomized clinical trials are required to generate strong evidence for recommending SST over the conventional technique for long-lasting successful treatment outcomes with immediate implants.
Health-related quality of life and psychological well-being in chronic obstructive pulmonary diseases
Authors: Samajdar Shinjini , Halder Susmita
Published: May 2022

Background:

Chronic obstructive pulmonary disease (COPD) is a persistent inflammatory lung disease which is characterized by progressive and partially reversible symptoms. The incidence rate of COPD is accelerating and becoming remarkable among worldwide population. Increasing recognition of psychological comorbidities among patients with COPD is more likely to be seen than non-COPD patients. Impairment in physiological functioning and restricted lifestyle leads to higher rate of mental health deterioration. Understanding the spectrum of negative consequences related to the psychological and social functioning of the patients with COPD has been underrecognized, and deficits are mostly untreated. Due to deleterious effects of COPD on physical functioning, decline in quality of life (QOL) has been acknowledged.

Aim:

The aim of the study is to compare the health-related QOL (HRQL) and psychological well-being between COPD patients and normal controls.

Methods:

In the present study, sixty individuals, thirty individuals diagnosed with COPD and 30 normal controls were taken of both genders, with the age range of 50–70 years. Measures were taken on the basis of psychological well-being and HRQOL.

Results:

Results suggest that individuals with COPD differed significantly in subjective psychological well-being and HRQOL in comparison with normal controls.

Conclusion:

In conclusion, COPD affects patients overall psychological well-being and QOL adversely, and requirement of comprehensive psychosocial management is recommended.
Advance directives for euthanasia in India
Authors: Anand Bhogaraju
Published: May 2022

This review article starts by defining Good death, Euthanasia, and Advance Directives (ADs). Most of the religions in India do not support self-annihilation although exceptions are made in cases of “Samadhi” by saints. Indian law permits the donation of organs in brain dead patients, while Euthanasia is viewed as a criminal act. The case of Aruna Shanbaug and a plea for Euthanasia resulted in the Honorable Apex court of India permitting passive euthanasia and also issued ADs. It is now for the parliament to debate and enact. The role of a psychiatrist at present appears limited in the context of Euthanasia and Advanced Directives, but in future, importance might increase with psychiatric comorbidities being higher in incurable conditions and suffering. Literature from foreign countries shows that patients with mental illness have also undergone Euthanasia which is of grave concern.
Opioid dependence growing concern
Authors: Rathee Sunila , Kumar Vinay , Singh Bhupendra , Gupta Rajiv
Published: May 2022

Background:

It is well-known that opioids are one of the world's most challenging substances which are growing rapidly. India too has a considerable problem of opioid use. State Drug Dependence and Treatment Center, Rohtak is only center in Haryana proving treatment with opioid substitution therapy.

Aim:

The present study was aimed to draw a profile of the patients attending this treatment facility.

Methods:

It was a retrospective secondary data-based study for the year 2018–2019. All the data records were reviewed and tabulated for the interpretation.

Results:

The present study found that maximum (46%) of the participants were from the age group of 20–29, almost males married and unmarried both were seeking treatment, 70% of them were educated at least up to secondary slandered but maximum (42%) were unemployed. Age of initiation was vary from 10 to 29 years and 74.2% were reported addiction of heroin. Chasing was the most popular method of consumption followed by oral and intravenous. Support from family was reflected in the referrals, and it can be considered as good for the better outcome and reduction of relapse.

Conclusion:

Opioid use is growing among adult males that need immediate attention of care.
Procrastination and self-compassion in individuals with anxiety disorders
Authors: Petwal Pratishtha , Sudhir Paulomi Matam , Mehrotra Seema
Published: May 2022

Background and Aim:

Literature on procrastination suggests that it is related to varied negative outcomes in the nonclinical population; however, there is a paucity of studies examining procrastination in the clinical population. We examined procrastination and self-compassion in persons with anxiety disorders.

Methods:

Forty-nine individuals diagnosed with an anxiety disorder, between 18 and 50 years of age, were recruited from a tertiary care center. Participants were assessed using the Decisional Procrastination Scale, the Adult Inventory of Procrastination, the Self-Compassion Scale, the Overall Anxiety Severity and Impairment Scale, and the Beck Depression Inventory-II.

Results:

Results indicated that individuals with anxiety disorders reported elevated procrastination and low self-compassion. Self-compassion and decisional procrastination were significantly negatively correlated. The subjective distress due to procrastination reported by the participants was significantly positively correlated with decisional procrastination. Self-compassion and anxiety severity were found to be negatively correlated. Self-compassion was a significant predictor of decisional procrastination and anxiety severity.

Conclusion:

The findings of the present study highlight the significance of assessing procrastination in anxiety disorders and indicate that self-compassion-based interventions may be helpful in alleviating anxiety symptoms and in reducing decisional procrastination.
Professor Julian Paul Leff
Authors: Hussain Hamza
Published: May 2022

Professor Julian Paul Leff was trained at University College Hospital and Maudsley hospital, he was emeritus professor at Institute of Psychiatry. He had 38 years of research experience with medical research council. He developed psychosocial interventions involving intensive group and individual work with families instead of treating patient alone. He was the pioneer in cultural psychiatry and conducted cross cultural studies demonstrating the association between high expressed emotions and relapse of psychosis in different cultures. With more than 150 researches, review articles, more than 10 books authored, co-authored and edited, he left treasury behind him and physically parted from us on February 23, 2021, surrounded by his family members.