bluuebunny/crossref_metadata_2025 huggingface dataset:
Initiation of a New Nurse Preceptor Program in the Era of COVID-19
Authors: Kelly Debra E.
Published: May 2022

COVID-19 has impacted most hospitals around the world, resulting in changes to daily operations and the suspension of some programs. Preceptor training is an area that has been impacted by COVID-19 restrictions. These programs have a positive impact on the retention of new RNs, which is especially important as the pandemic continues to strain morale. A 12-week, step-by-step education plan that leverages audio/video technologies such as Zoom and FaceTime was developed to preserve the positive benefits of the preceptor–preceptee relationship in the setting of COVID-19.

[
J Contin Educ Nurs
. 2022;53(5):221–224.]
Developing and Pilot Testing E-Learning Training for Pediatric Nursing Burn Care
Authors: Farthing Julie , Le May Sylvie , Gauvin-Lepage Jérôme
Published: May 2022

Background

Nurses caring for pediatric patients who have burns need to be properly trained to provide optimal care. The aims of this pilot study were to (1) develop a pediatric nursing burn care e-learning training for novice nurses; (2) assess the feasibility and acceptability of this educational intervention; and (3) evaluate the preliminary effects of this intervention on novice nurses' knowledge of pediatric nursing burn care.

Method

A quasi-experimental, one-group, pre-test–posttest design was used.

Results

Feasibility was achieved because all of the participants completed the study. A significant difference was observed in the mean knowledge level of the novice nurses from before training to after training (87.7% ± 8.7% vs. 58.6% ± 14.5%;
p
< .001). The novice nurses' had a mean satisfaction of 95.5% after the intervention.

Conclusion

This new, evidence-based pediatric nursing burn care e-learning training appeared to be feasible. The novice nurses found it to be satisfactory, and it improved their knowledge regarding pediatric burn care.

[
J Contin Educ Nurs
. 2022;53(5):232–240.]
Community Goal Setting and Attainment: Organizational Characteristics and Indicators of Staff Adoption
Authors: Kolanowski Ann , Heid Allison R. , Behrens Liza , Riley Kiernan , Madrigal Caroline , Boltz Marie , Van Haitsma Kimberly , Resnick Barbara , Galik Elizabeth , Ellis Jeanette , Eshraghi Karen
Published: May 2022

In residential care communities (CCs), implementation strategies can improve the use of person-centered approaches for residents' behavioral symptoms of distress. We examined staff perceptions of how well their organizational goals for achieving person-centered care (PCC) were met following implementation of the strategy, Evidence Integration Triangle for Behavioral and Psychological Symptoms of Distress. We also identified organizational characteristics and indicators of staff adoption associated with perceived goal attainment. Goal attainment was evaluated by staff using goal attainment scaling (GAS) at the completion of the implementation trial in 26 CCs. Correlations,
t
tests, and linear regression were used to determine which factors were associated with goal attainment. Total time spent with the research facilitator, stable staff group membership, and presence of a survey deficiency during the study period explained 63% of the variance in goal attainment. Staff can set achievable organizational goals to improve PCC for residents' behavioral symptoms of distress. [
Journal of Gerontological Nursing, 48
(5), 5–12.]
Challenges in Heart Failure Disease Management in Skilled Nursing Facilities: A Qualitative Study
Authors: Morrow Cynthia D. , Perraillon Marcelo C. , Wald Heidi L. , Nelson Jennifer L. , Reeder Blaine P. , Battaglia Catherine , Boxer Rebecca S.
Published: May 2022

Clinical guidelines recommend clinicians in skilled nursing facilities (SNFs) monitor body weight and signs and symptoms related to heart failure (HF) and encourage a sodium restricted diet to improve HF outcomes; however, SNFs face considerable challenges in HF disease management (HF-DM). In the current study, we characterized the challenges of HF-DM with data from semi-structured, in-depth interviews with patients, caregivers, staff, and physicians from nine SNFs. Patients receiving skilled nursing care were interviewed together as a dyad with their caregiver. A data-driven, qualitative descriptive approach was used to understand the process and challenges of HF-DM. Coded text was categorized into descriptive themes. Interviews with five dyads (
n
= 10 individuals), SNF nurses and certified nursing assistants (
n
= 13), and physicians (
n
= 2) revealed that, among the sample, HF care was not prioritized above other competing health concerns. Staff operated in the challenging SNF environment largely without protocols or educational materials to prompt HF-DM. [
Journal of Gerontological Nursing, 48
(5), 13–17.]
Editorial
Authors: Franzato Carlo , Jacques Edu
Published: May 2022

We would like to present you this new number: the second of the current volume and the first regular of this year. In this new issue we publish five new papers with different perspectives about design.
Applying Theory of Change to strategy articulation cycles in design projects: Potentials and shortcomings through the Designscapes case study
Authors: Drabble David , Simeone Luca , Iacopini Giorgia , Morelli Nicola , De Götzen Amalia
Published: May 2022

Since the 1990s, the framework of Theory of Change has been used to address complex contexts of intervention especially in relation to planning and evaluating social practice. Theory of Change can be defined as the systematic and cumulative study of the links between the activities, outcomes, and context of an intervention. The aim of this paper is to explore through a case study whether Theory of Change can support more strategic approaches in design. In particular, the paper examines how Theory of Change was applied to DESIGNSCAPES - a project oriented, among other things, toward offering a supporting service for all those city actors interested in using design to develop urban innovation initiatives that tackle complex issues of broad concern.
How the Design Leadership and Strategic Design Drive New Value in Enterprises and Organizations
Authors: Hsieh Ying-Yi , Chen Chun-Ching , Chen Wen-Yin
Published: May 2022

Today's design has shifted from the original primary pursuit of appearance and function to processes and systems, creating new meanings for corporate strategies, products and services. Nowadays, enterprises are increasingly paying attention to the power of design, and regard design as the main innovation method and incorporate it into the organizations. Design began to be considered a key role at the top of large organizations. Although people recognize that design can bring good effects to enterprises and organizations, and there is growing interest in cultivating design thinking, what are the leaders who can lead enterprises, organizations and have design thinking? Their characteristics and how to formulate and plan strategic design still not fully elucidated. Therefore, this research uses related theories to understand the way of thinking and characteristics of design leaders, only in this way we formulate good strategic design for enterprises and organizations, and become an indispensable and important help in today rapidly changing world.
A Model of Network Security Situation Assessment Based on BPNN Optimized by SAA-SSA
Authors: Zhang Ran , Pan Zhihan , Yin Yifeng , Cai Zengyu
Published: May 2022

In order to address the problems that the accuracy and convergence of current network security situation assessment models need to be improved, a model of network security situation assessment based on SAA-SSA-BPNN is proposed. Using the characteristics of sparrow search algorithm (SSA) optimized by simulated annealing algorithm (SAA) with good stability, fast convergence speed and is not easy to fall into local optimum to improve the BP neural network (BPNN), so as to find the best fitness individual, and obtain the optimal weight and threshold, then assign them to the BP neural network as the initial values. The preprocessed index data is input into the improved BP neural network model for training, and finally the threat degree of the network system is assessed based on the trained model. Comparative experimental results show that this assessment model has higher accuracy and faster convergence than other situation assessment models based on improved BP neural network.
Seismic Response of Buildings Resting on Soil Isolated With EPS Geofoam Buffer
Authors: Sreya M. V. (5dad9c84-fd72-4b0a-b80c-72997108e2d5  , Jayalekshmi B. R. (6c140e76-cfc3-4abd-8ee7-940511fceb94  , Venkataramana Katta
Published: May 2022

The present study deals with analyzing the efficacy of EPS (epoxy polystyrene) geofoam buffer as a soil-isolation medium to reduce the seismic energy transferred and thereby to reduce the dynamic response of buildings under earthquake-induced loads. Finite element simulation of the transient response of an integrated soil isolation-building system in which buildings resting on raft foundation in medium dense sand beds with and without soil-isolation mechanism has been carried out using a recorded accelerogram of El Centro earthquake. Four sets of three-dimensional buildings (one, two, three, and four story) of single bay moment resisting concrete frames have been considered for the analysis. The EPS geofoam buffer of various thicknesses was placed at different depths below the raft foundation. The results under field-scale conditions indicate that soil isolation provided by the EPS geofoam buffer substantially reduces the earthquake energy transmission to the superstructure during a strong earthquake.
Seismic Hazard Analysis Using Fuzzy-Probabilistic Approach for Chennai City, South India
Authors: Menaka K. , Dodagoudar G. R.
Published: May 2022

Fuzzy-probabilistic seismic hazard analysis (FPSHA) is performed for Chennai city, South India incorporating both the random and fuzzy uncertainties. Randomness is handled using Monte-Carlo simulation technique, and fuzziness is accounted in the hazard analysis using fuzzy logic. The magnitude of earthquakes and epicentral distances are fuzzified and used as inputs in the fuzzy inference rules. Fuzzy attenuation relationships are developed as consequence of the inference rules with the help of ground-motion models and ANFIS. The proposed FPSHA method has the advantage over the conventional hazard analysis methods in respect of its preciseness, efficiency, practicability, and reliability. The ground motions compatible with the target spectrum (UHS) of 475 years return period are selected from the recorded accelerograms with appropriate scaling. The established spectrum compatible accelerograms are vital in the seismic analysis and design of infrastructure facilities and rehabilitation and strengthening of historical and critical structures.
A Big Data Pipeline and Machine Learning for Uniform Semantic Representation of Data and Documents From IT Systems of the Italian Ministry of Justice
Authors: Di Martino Beniamino , Colucci Cante Luigi , D'Angelo Salvatore , Esposito Antonio , Graziano Mariangela , Marulli Fiammetta , Lupi Pietro , Cataldi Alessandra
Published: May 2022

In this paper a Big Data Pipeline is presented, taking in consideration both structured and unstructured data made available by the Italian Ministry of Justice, regarding their Telematic Civil Process. Indeed, the complexity and volume of the data provided by the Ministry requires the application of Big Data analysis techniques, in concert with Machine and Deep Learning frameworks, to be correctly analysed and to obtain meaningful information that could support the Ministry itself in better managing Civil Processes. The Pipeline has two main objectives: to provide a consistent workflow of activities to be applied to the incoming data, aiming at extracting useful information for the Ministry's decision making tasks; to homogenize the incoming data, so that they can be stored in a centralized and coherent Datalake to be used as a reference for further analysis and considerations.
Tasks and Resources Allocation Approach with Priority Constraints in Cloud Computing
Authors: Almojel Nouf Ahmad , Ahmed Alaa E. S.
Published: May 2022

Cloud computing is the most developing technology, which allow users to access data, software and IT services. Cloud systems are characterized by the uncertainty of the resources availability. For that reason, its performance is greatly affected by the applied scheduling and allocation algorithm used to map submitted tasks to resources. This paper introduces a heuristic approach that combine Ant Colony and priority-aware schema to achieve task scheduling and resource allocation in cloud computing environments. The algorithm provides three prioritized levels of quality of services to be employed by users per their demand. A level’s priorities dynamically affect the way tasks are distributed in the system. The resources are allocated using a modified version of Ant Colony Optimization. Results show that the proposed algorithm improves the performance of the system by minimizing makespan, decreasing the degree of imbalance between virtual machines, and enhancing the Cloud’s quality of service by achieving user-priority goals.
Template-Based Question Answering System Over the Semantic Web
Authors: Dhandapani Aarthi , Vadivel Viswanathan
Published: May 2022

A question answering system is the most promising way of retrieving data from the available knowledge base to the end-users to get the appropriate result for their questions. Many question answering systems convert the questions into triples which are mapped to the knowledge base from which the answer is derived. However, these triples do not express the semantic representation of the question, due to which the answers cannot be located. To handle this, a template-based approach is proposed that classifies the question types and finds appropriate SPARQL query template for each type including comparatives and superlatives. The SPARQL query built is executed in the DBpedia endpoint and results are obtained. Compared with other factoid question answering systems, the proposed approach has the potential to deal with a large number of question types, including comparatives and superlatives. Also, the experimental evaluations of the system performed on the QALD 8 dataset presents good performance and can help users to find answers to their questions.
Energy-Aware VM Scheduler
Authors: Shukla Ram Narayan , Chaturvedi Anoop Kumar
Published: May 2022

Cost is the backbone of any business model to sustain and growth in the competitive business market. Considering this, higher energy consumption may affect the operational cost of any industry. Cloud computing is one of the most popular IT business model for service provider and its users. It is observed in many research, that the average cost of the services are highly dependent upon the run time and power consumption. More power consumption effect the environmental things as well. In this review, more than 100 research articles are considered to evaluate the energy consumption methods, issues and challenges from 2009 to 2021. Based on the study, the energy-aware load balancing methods are classified into four major clusters. The most cited methods are compared based on method used, platform where it is deployed, different evaluation parameters like cost, run time, Virtual Machine utilization, Service-level-agreement violation rate, and Quality-of-service QoS. The result of this review is presented as open research issues and challenges for forthcoming research.
Hole Drilling Route Optimization in Printed Circuit Boards Using Far-to-Near Metaheuristics
Authors: Dhouib Souhail
Published: May 2022

Drilling holes in Printed Circuit Board (PCB) is usually realized by Computer Numerical Controlled Machine (CNCM). In fact, affecting an optimal shortest drilling holes route for the CNCM will improve its processing time and inevitably its efficiency. This paper presents a new metaheuristic named Far-to-Near (FtN) in order to optimize the shortest drilling holes route in PCB. The generated solution will be used as an execution plan for robotic arm in CNCM. Several numerical applications illustrate the performance of the proposed metaheuristic FtN in order to generate the shortest drilling route and also to find the optimal circuit when changing the position of the initial starting position of the robotic arm.
Investigation on Corrosion Protection Systems and Wear Problems for a Ship Unloader
Authors: Upiah Prishnee Queensy , Surnam B. Yashwansingh R.
Published: May 2022

In the harbour of Port Louis, a wheat ship unloader was facing serious corrosion problems due to the severe marine environment. Therefore, the aim of this study is to propose an effective corrosion protection system for the wheat ship unloader. In addition, wear was observed in its conveyor system. Solutions were proposed to reduce this. Different coating systems were selected, based on ISO 12944-5, including the coating presently being used on the equipment. Outdoor atmospheric exposures and lab tests were performed. The latter consisted of immersion test, water vapour transmission rate of coatings, wet scrub abrasion test, scratch test, pull-out test and flexibility test. For investigating the wear in the conveyor system, flow simulations were performed on Soildworks using different materials. From the investigation performed, it was found that the combination of modified vinyl epoxy primer and acryline polyurethane acrylic top coat was the most suitable for the ship unloader. For the wear problem, aluminium 6061was found to be a more wear resistant material.
Hybrid Power Modulation Scheme for High Frequency Isolated Bidirectional Dual-Active-Bridge DC-DC Converter
Authors: Kumar Vikram , Kakkar Vipan , Kumar Krishan , Rana Vinaya
Published: May 2022

High frequency isolated bidirectional dual-active-bridge (HFIB-DAB) DC-DC converter is a bidirectional DC-DC converter. A hybrid power modulation scheme is introduced, resulting in improved efficiency over complete power range. This proposed hybrid modulation scheme combines two different types of power modulation techniques. Up to certain level of power modulation, the DPS power modulation technique is more efficient and after that the efficient performance of RF power modulation technique supersedes over the other. A switch over provision is proposed to choose the most efficient one for a given power transfer requirement in the HFIB-DAB DC-DC converter by using the proposed reconfigurable resonant tank network. The results are verified by using 4 kW HFIB-DAB DC-DC converter operating at 50 kHz. It is designed to interface two 400V DC bus voltages on either side of the HFIB-DAB DC-DC converter. The validation is done by using MATLAB/Simulink package and a maximum power transfer efficiency of 99.94% is achieved.
Trans_Proc
Authors: Sanyal Atri , Sinha Amitabha
Published: May 2022

A reconfigurable transform processor is proposed and implemented here. Firstly, a brief study of processors implementing different transformations is presented. We have categorized the transform processor as the one which can implement a number of linear transforms using reconfigurability. The theoretical suitability regarding the architecture of the processor is proved by graph theory method. Then the complete architecture of the overall processor and the processing element is presented and implemented using VHDL. The complete instruction set suitable to the processor is designed. The instructions are mapped to the sequence of control signals. Generating sequence of control signals for every type of instructions would finally create a hardwired control unit for the processor which was also presented. Next the processor is fed with data to simulate it. A three-phase simulation is carried out to prove the correctness of the design. Finally the same processor with a data bus width of 32 to 512 is implemented and compared in terms of speed and size.
Contextual Fuzzy Ranking for Web Services Discovery in a Hybrid Architecture
Authors: Abdelli Djallel Eddine , Fayçal Bouyakoub M'hamed
Published: May 2022

The fast increasing number of web services is transforming the web from a data-oriented repository to a service-oriented repository. This repositories offers a single search point for all shared services which makes the discovery of web services is one of main action in the service-oriented architecture. After a deep study of the existing repositories authors propose a hybrid architecture for web service discovery with multi-level domain services implemented with mult-iagent technology to fulfill some of the lacks in previous works. Also, propose a contextual fuzzy ranking approach to help the user to select the best services according to his needs.
Enhanced Parallel-Particle Swarm Optimization (EP-PSO) Approach for Solving Nurse Rostering Problem
Authors: Dharwadkar Nagaraj V. , Shingan Gautami G. , Mane Sandeep Uttam , Joshi Santosh
Published: May 2022

A Nurse Rostering Problem is a highly-constrained combinatorial optimization problem, where we assign several nurses to shifts by violating minimum constraints. Due to massive number of constraints, these problems are difficult to handle manually. The advantage of automating the task is to generate a roster having not only high quality but also more flexibility by reducing the workload, time and effort of head nurses. The PSO algorithm is extremely dependent upon settings of control parameters and balance the exploration and exploitation in search space. These problems are avoided by proposed an ES-PSO Algorithm. Highly constrained problems have huge search space to find an optimal solution, hence to cover that space and find the solution in the stipulated time necessary to increase population. However, it may take more time for particle updating and fitness evaluations. To improve execution time of the compute-intensive task, we have used OpenMP and CUDA framework. The adapted algorithm improves the outcome by minimizing penalty and reduces stuff of compute-intensive tasks.
Herding Exploring Algorithm With Light Gradient Boosting Machine Classifier for Effective Prediction of Heart Diseases
Authors: Bhavekar Girish S , Das Goswami Agam
Published: May 2022

Coronary heart diseases act as life threatening diseases. Prediction of these coronary diseases at an early time with higher rate of accuracy could be an effective solution for this problem. In places where the availability of medicos is low, the automatic prediction model plays an important role in saving the lives of many people. To enhance the prediction model, this paper proposed a HEOA-based LightGBM classifier for forecasting the coronary heart diseases. The preprocessing is performed using data imputation, which uplifts the features of the data and the formation of feature vector strengthens the process by adding supreme features. The significance of the research is proved by effectively tuning the parameters, which optimize the time period and achieve an accuracy rate of 93.064%, specificity rate of 95.618%, and sensitivity rate of 91.038%.
Whale Optimizer-Based Clustering for Breast Histopathology Image Segmentation
Authors: Ray Swarnajit , Das Arunita , Dhal Krishna Gopal , Gálvez Jorge , Naskar Prabir Kumar
Published: May 2022

Breast histopathology image segmentation is a complex task due to indiscernibly correlated and noisy regions of interest. Breast histopathological images are composed of different types of cells. Some of these cells can be harmful for humans due to the presence of cancer. Under such circumstances, many segmentation techniques for automatic detection of cancer cells have been proposed considering clustering schemes. However, such clustering methodologies are sensitive to initial cluster centers, which promote false-positive solutions. This paper presents the use of the Whale Optimization Algorithm (WOA) for proper clustering segmentation of breast histopathological images to overcome clustering issues. Also, a rigorous comparative study is conducted among the proposed approach and several state-of-art Nature-Inspired Optimization Algorithms (NIOAs) and traditional clustering techniques. The numerical results indicate that the proposed approach outperforms the other utilized clustering methods in terms of precision, robustness, and quality of the segmented outputs.
A Hybrid Whale Genetic Algorithm for Feature Selection in Biomedical Dataset
Authors: Agrawal Tarushi , Bist Priya , Jain Nimit , Agarwal Parul
Published: May 2022

One of the major concerns of biomedical datasets is high dimensionality. These dimensions may include irrelevant and redundant features that adversely affect the performance of classification algorithms. Extensive research has been done in the area of machine learning to handle high dimensionality. In literature, feature selection algorithms have been developed for this purpose. In this paper, a hybrid nature-inspired algorithm is proposed which is a combination of whale optimization algorithm and genetic algorithm for feature selection. The proposed algorithm is applied to four microarray datasets and one DNA sequence dataset and compared with classical feature selection methods. In all the algorithms decision tree classifier is mainly employed. To reach an approximate best solution and remove local solutions, the exploitation and exploration phases are balanced efficiently in the proposed algorithm. The convergence speed in the proposed algorithm is accelerated by the adaptive mechanisms. Overall results employ better performance on the majority of datasets.
Hate and Aggression Detection in Social Media Over Hindi English Language
Authors: Pareek Kapil , Choudhary Arjun , Tripathi Ashish , Mishra K. K. , Mittal Namita
Published: May 2022

In today’s time, everyone is familiar with social media platforms. It is quite helpful in connecting people. It has many advantages and some disadvantages too. Currently, in social media, hate and aggression have become a huge problem. On these platforms, many people make inflammatory posts targeting any person or society by using code mixed language, due to which many problems arise in the society. At the current time, much research work is being done on English language-related social media posts. The authors have focused on code mixed language. Authors have also tried to focus on sentences that do not use abusive words but contain hatred-related remarks. In this research, authors have used Natural Language Processing (NLP). Authors have applied Fasttext word embedding to the dataset. Fasttext is a technique of NLP. Deep learning (DL) classification algorithms were applied thereafter. In this research, two classifications have been used i.e. Convolutional Neural Network (CNN) and Bidirectional LSTM (Bi-LSTM).
Model-Based Method for Optimisation of an Adaptive System
Authors: Bachir Magagi Ali , Ismail Jelloulil , Said El Garouani , Souad Amjad
Published: May 2022

In a modern information system adaptation, optimization is a crucial aspect. Systems adaptation problematics have been explored in a large set of research, which have not been able to fix every single issue, leaving therefore so many challenges to be explored. It for this reason this paper presents a method, through a UML profile, to ensure the optimization of the performance of a production system. In the first place, a state of the art is presented to clarify the context of the study. This method consists in setting up a UML profile which will allow the real value of the production to be constantly assessed, the reaction take place when production is not satisfactory. The productivity assessment performs through the application of the simple algorithm, the simplex constraints are integrated through the OCL language. A code generator, based on acceleo, has been developed to propose code generation.
A Systematic Text-Analytics-Based Meta-Synthesis Approach for Smart Urban Development
Authors: Dhingra Mani , Chattopadhyay Subrata
Published: May 2022

‘Smart’ has become a leitmotif that is widely assumed to reach the goals of urban sustainability and improve the living standards of people. Though there is an exponential increase in the smart cities' research during the last two decades, the concept is still silent about the importance of existing cities and communities to achieve Smart Urban Development (SUD). Authors propose a Systematic Literature Search and Review framework, coupled with deductive text computational and inductive grounded theory methods for the meta-synthesis. This study contributes to the present research landscape by facilitating urban professionals for framing integrated strategies, instead of blindly fixing the urban spaces with technological components. The automated text analysis for meta-synthesis is a novel approach for analyzing a diverse concept like Smart City, by eliminating chances of human errors. The findings conclude that the three-dimensional objectives of SUD are achieving sustainable development, high quality of life, and inclusive development.
The Role of Teachers in Assisting Low-Proficiency Students' Writing Performance via WhatsApp
Authors: Haron Haeza , Kasuma Shaidatul Akma Adi
Published: May 2022

Globally, the COVID-19 pandemic has compelled educational institutions to explore alternatives to face-to-face instruction. The primary objective of this study is to identify the teacher’s role in the English argumentative writing performance of low proficiency university students via WhatsApp. In this case study, data were collected from multiple resources including WhatsApp discussions, interviews and students’ argumentative writing on thirteen undergraduate students from Universiti Sains Malaysia, chosen based on their Malaysian University English Test (MUET) results. The argumentative writing essays that the students sent every week for eight weeks after three days of discussion in WhatsApp with the teachers based on eight topics. The students' writing scores revealed that teacher’s role helped students’ improved in their writing skills and the students’ attitudes. The findings suggest that WhatsApp is recommended to support the students in writing, highlight the importance of teacher’s role in the students’ motivation, engagement and effective learning.
Cat Swarm Optimization Algorithm Tuned Multilayer Perceptron for Stock Price Prediction
Authors: Chandar Kumar S. , Punjabi Hitesh
Published: May 2022

Due to the non-linear and dynamic nature of stock data, prediction is one of the hard tasks in the financial market. Now, soft and bio-inspired computing algorithms have been used to forecast the stock price. This article assessed the efficiency of the hybrid prediction model using multi-layer perception (MLP) and cat swarm optimization (CSO) algorithm. CSO algorithm is a kind of bio-inspired algorithm motivated by the behavior traits of cats. CSO is employed to find appropriate value of MLP parameters. Technical indicators calculated from historical data are used as input variables to the proposed model. The performance of the model is validated by using historical data not used for training. The prediction efficiency of the model is evaluated in terms of MSE, MAPE, RMSE, and MAE. The results of the model are compared with other models optimized by various bio-inspired algorithms explored in the literature to prove its efficiency. The empirical findings proved that the proposed CSO-MLP prediction model provides best performance when compared to other models taken for analysis.
Exploring Customer Engagement on Social Networking Sites
Authors: Malhan Mohit , Dewani Prem Prakash , Nigam Achint , Vaz Daicy , Ogbeibu Emmanuel Akaehomen Abumere
Published: May 2022

The growth in popularity of social media and its perfunctory use by individuals throughout the day has sprouted the need to study Customer Engagement (CE) on Social Networking Sites (SNSs) from the consumer’s lens. To understand user behaviour, it is thus imperative to explore CE from their perspective. This study examines customer engagement and its antecedents and consequences on Social Networking Sites (SNSs) in an emerging economy. Data from 21 semi-structured focus group discussions (FGDs) and 42 in-depth interviews (IDIs) were analysed through a grounded theory approach using Nvivo coding. The results highlight the usage patterns and conditions faced by users on SNSs and establish the presence of information overload faced by users. The study also shows various parameters related to post and individual that lead to passive and active engagement on these platforms. Our study has direct implications for marketing managers across industries as it unravels various levers necessary to succeed on SNSs.
Research on COVID-19 Prevention and Control Model Based on Evolutionary Games
Authors: Tang Xinfa , Zhong Tian
Published: May 2022

In view of epidemic prevention costs and social benefits, an evolutionary game model of epidemic prevention and control strategies between government departments and local people was constructed based on evolutionary game theory to explore the influence of strategic behaviors between government departments and local people, and MATLAB was used to conduct systematic simulation of the game model. Studies have shown that local people will cooperate with government departments when they implement surveillance strategies. Reducing the cost of emergency epidemic prevention, and improving the social benefits of epidemic prevention are conducive to the development of government departments towards the direction of supervision strategy, and local people towards the direction of active epidemic prevention strategy, so as to achieve effective epidemic prevention and control.
How Does Interactivity Impact User Engagement Over Mobile Bookkeeping Applications?
Authors: Kumari Pooja
Published: May 2022

Purpose of this study to examine the effect of interactivity on musers’ engagement towards mobile bookkeeping application using stimulus-organism-response (S-O-R) theory and technology acceptance model (TAM). Further, moderation effect of users’ innovativeness was also examined. A total of 376 responses were analyzed for examining the proposed hypotheses. The results exhibited that, application interactivity enhances perceived usefulness (PU) and perceived ease of use (PEOU), in turn users’ engagement. Moreover, users’ innovativeness positively moderates the association between PU, PEOU and user engagement. The study suggests marketers how to enhance application interactivity to enhance users’ engagement.
An Economic Case Against Rent Regulations in Montgomery County, Maryland
Authors: Tollison Merritt
Published: May 2022

A new light rail system threatens to increase pressure on Montgomery County’s already-chronic housing shortage for low- and middle-income residents. The 16-mile Purple Line rail corridor, expected to be completed in 2026, will run adjacent to a substantial proportion of the county’s naturally occurring affordable housing and a large population of vulnerable cost-burdened renters. Proposed economic development around the new transit stations could usher in an increase in economic development that portends rapid increases in home values, rents, and land prices. To preserve affordable housing and reduce displacement in the wake of this development, the Montgomery County Council is debating rent regulations for a county-wide transit-centered buffer zone. This policy, however, would have a negative effect as economists overwhelmingly agree that rent controls cause inefficiency, inequity, negative externalities, disutility, and restricted mobility. This paper uses an economic analysis to show that local rent regulations would fail to mitigate the chronic housing shortage and that costs to communities and businesses will outweigh the benefits provided to protected tenants. Montgomery County should reconsider implementing the proposed rent regulations, reevaluate similar policies, and expand efficient, targeted support for low-income renters.
In Order to Combat Climate Change, The United States Must Look to Expand its Global Nuclear Infrastructure
Authors: Liguori Julia
Published: May 2022

While it is almost never the first source of clean energy that comes to mind, nuclear energy may hold the key to replacing the highest amount of carbon emissions in the quickest time possible with the least disturbance to our current energy infrastructure.
An Economic Response to the Substance Use Crisis
Authors: Berro Malka
Published: May 2022

Behavioral economic theories can be applied to substance use in an effort to understand an individual’s demand, utility maximization, and consumption over time for addictive goods. These theories can shape public policy in a way that would both reduce the consumption of addictive substances and help people on their road to recovery. This paper examines the current research on behavioral economic theories on substance use as well as the implications of these theories on public policy.
At What Cost? An Evaluation of the Health and Human Services Proposed Rule, “Proposed Modifications to the HIPAA Privacy Rule to Support, and Remove Barriers to, Coordinated Care and Individual Engagement”
Authors: Kaufman Catherine
Published: May 2022

As a final act of the Trump administration, the Office for Civil Rights (OCR) within the U.S. Department of Health and Human Services (HHS or the Department) proposed a deregulatory rule entitled, “Proposed Modifications to the HIPAA Privacy Rule to Support, and Remove Barriers to, Coordinated Care and Individual Engagement” (HHS 2021). OCR announced the proposed changes on December 10, 2020, and it was published in the Federal Register on January 21, 2021. While the Biden administration has withdrawn or proposed modifications to other last-minute Trump administration notices, it has taken no action to date on this proposed rulemaking. During the public comment period, which closed on May 6, 2021, I filed a comment on this proposal (Kaufman 2021). This article is based on my publicly submitted evaluation of the Department’s proposed rule.
Subsidizing Interest Rates to Bridge the Racial Wealth Gap
Authors: Royal Gabe
Published: May 2022

There is a large, persistent, and worsening wealth gap between Black and White households in the United States. Black families’ median and mean wealth is less than 15 percent that of White families (Bhutta et al. 2020). New research shows current monetary policies designed to aid in the economic recovery from the COVID-19 recession will likely exacerbate this wealth gap (Bartscher et al. 2021, 33). This paper proposes issuing a government-subsidized two percent mortgage interest rate reduction for prospective Black homebuyers to provide a financial incentive for Black households to build wealth and to promote integrative behavior among neighborhoods.
La scuola come luogo per una ‘clinica del sociale’ (PolisAnalisi)
Authors: Pergola Rocco Filipponeri , Rosati Costanza
Published: May 2022

La scuola è rimasto l’unico incubatore di capitale semiotico - risorse di significato - e rigeneratore di capitale sociale. Perciò compito dell’insegnante-educatore è primariamente ‘insegnare a vivere’, ossia permettere a ciascuno di sviluppare la conoscenza di sé stesso e il legame con gli altri - gli altri dentro di sé e gli altri fuori di sé; preparare ad affrontare le molteplici incertezze e difficoltà dell’esistenza, facendo fronte al senso d’impotenza radicale e d’indefinibilità del sé che vive il ‘bambino sovrano’ ora cresciuto. Centrale sarà una rieducazione ai limiti, alla mentalizzazione, alla cura dello spazio di convivenza comune. A tal fine anche il processo di apprendimento-insegnamento va interpretato come qualcosa riguardante anzitutto le dinamiche emotivo-affettive, in gran parte inconsce, che configurano la rete gruppale di relazioni tra tutti gli attori del teatro scolastico: transfert, controtransfert, collusioni, il gruppoclasse come mente unica, l’istituzione, la specifica cultura di ogni scuola. Il docente potrà ritrovare nella propria stessa mente il suo principale strumento di lavoro, a patto che abbia spazi e tempi per coscientizzare e metabolizzare quanto si agita in sé stesso a livello inconscio attraverso opportune metodologie gruppali - Balint e Psicodramma. L’allievo, dal canto suo, andrà aiutato a transitare da una cultura dell’adempimento al sentirsi ‘cliente’ che vive la scuola come tempo per coltivare sé stesso e implementare Beni Relazionali, quali reciprocità, cooperazione e fiducia. Si tratta di operare un vero e proprio atto di ‘clinica del sociale’.
L’apporto dei gruppi a mediazione nella clinica contemporanea. Il metodo Photolangage®
Authors: Micheloni Alessandra
Published: May 2022

Non disponibile
Editorial
Authors: Polito Laura
Published: May 2022

Not available
Commento al caso clinico: Stati alterati di coscienza
Authors: Rossi Matteo
Published: May 2022

Non disponibile
The associations between mental health and environmental factors in New Zealand: A region-based analytical study
Authors: Viehoff Morten , Grossman Daniel , Huang Leona , Jiang Jianwei , Zheng Pan
Published: May 2022

INTRODUCTION: Connections between environmental factors and mental health issues have been postulated in many different countries around the world. Previously undertaken research has shown many possible connections between these fields, especially in relation to air quality and extreme weather events. However, research on this subject is lacking in New Zealand, which is difficult to analyse as an overall nation due to its many micro-climates and regional differences.OBJECTIVES: The aim of this study and subsequent analysis is to explore the associations between environmental factors and poor mental health outcomes in New Zealand by region and predict the number of people with mental health-related illnesses corresponding to the environmental influence.METHODS: Data are collected from various public-available sources, e.g., Stats NZ and Coronial services of New Zealand, which comprised four environmental factors of our interest and two mental health indicators data ranging from 2016 up until 2020. The four environmental factors are air pollution, earthquakes, rainfall and temperature. Two mental health indicators include the number of people seen by District Health Boards (DHBs) for mental health reasons and the statistics on suicide deaths. The initial analysis is carried out on which regions were most affected by the chosen environmental factors. Further analysis using Auto-Regressive Integrated Moving Average(ARIMA) creates a model based on time series of environmental data to generate estimation for the next two years and mental health projected from the ridge regression.RESULTS: In our initial analysis, the environmental data was graphed along with mental health outcomes in regional charts to identify possible associations. Different regions of New Zealand demonstrate quite different relationships between the environmental data and mental health outcomes. The result of later analysis predicts that the suicide rate and DHB mental health visits may increase in Wellington, drop-in Hawke's Bay and slightly increase in Canterbury for the year 2021 and 2022 with different environmental factors considered.CONCLUSION: It is evident that the relationship between environmental and mental health factors is regional and not national due to the many micro-climates that exist around the nation. However, it was observed that not all factors displayed a good relationship between the regions. We conclude that our hypotheses were partially correct, in that increased air pollution was found to correlate to increased mental health-related DHB visits. Rainfall was also highly correlated to some mental health outcomes. Higher levels of rainfall reduced DHB visits and suicide rates in some areas of the country.
Existence of stationary vortex sheets for the 2D incompressible Euler equation
Authors: Cao Daomin , Qin Guolin , Zou Changjun
Published: May 2022

We construct a new type of planar Euler flows with localized vorticity. Let
$\kappa _i\not =0$
,
$i=1,\ldots , m$
, be m arbitrarily fixed constants. For any given nondegenerate critical point
$\mathbf {x}_0=(x_{0,1},\ldots ,x_{0,m})$
of the Kirchhoff–Routh function defined on
$\Omega ^m$
corresponding to
$(\kappa _1,\ldots , \kappa _m)$
, we construct a family of stationary planar flows with vortex sheets that have large vorticity amplitude and concentrate on curves perturbed from small circles centered near
$x_{0,i}$
,
$i=1,\ldots ,m$
. The proof is accomplished via the implicit function theorem with suitable choice of function spaces.
Effects of urban wetland patch pattern on the biodiversity of aquatic birds in Nairobi, Kenya
Authors: Toroitich Caleb , Njuguna Mugwima , Karanja Dennis
Published: May 2022

Urban wetlands are ubiquitous landscape elements that affect the spatial pattern and functions of cities. Despite being rich and important habitats for a variety of birds, they are continually being isolated or lost. Isolation and loss negatively impact on the integrity of the urban landscape pattern and compromises on biophilic planning and development. Since urbanization is a continuous cultural process, it is important to investigate how its impacts, which are invariably in conflict with nature, would portend for aquatic bird communities in urban areas. This study sought to determine the variability and relationship between the structural patch pattern of palustrine wetlands in Nairobi and the species richness and abundance of aquatic birds in these wetlands. From a population of 300 wetlands, this study used heterogeneous sampling to identify and investigate 31 palustrine wetlands spread across the city of Nairobi. For each of these wetlands, a variety of landscape metrics were calculated and the species diversity of aquatic birds was quantified. Multiple regression analysis was performed in IBM SPSS Statistics 21 to determine the relationships between wetland patch pattern and wetland biodiversity. The study found that patch pattern significantly affects aquatic bird biodiversity, R² = .516, F (7, 23) = 3.498, p < .05. It was also found that the characteristics of the wetland neighbourhood significantly affected aquatic bird biodiversity, R² = .301, F (3, 27) = 3.867, p < .05. This study highlights the need to mainstream, plan, and design for the conservation and monitoring of spatial patterns and biodiversity of palustrine wetlands in urban landscapes. In doing so, biophilic cities are created, bio-systemic urban infrastructure is generated, human wellbeing is enhanced, and urban wetland ecosystem services are valued.