bluuebunny/crossref_metadata_2025 huggingface dataset:
Rizoma: a new comprehensive database on traditional uses of Chilean native plants
Authors: Cordero Sebastián , Abello Lucía , Gálvez Francisca
Published: March 2022

We describe Rizoma, a new comprehensive online database on traditional uses of Chilean flora. The Rizoma database was built by reviewing multiple data sources on the uses of native plants and integrating phytogeographic and ecological aspects of plant species. This database attempts to safeguard traditional knowledge by making it available and visible to society, providing 1380 use records from 736 vascular plant species native to Chile. In addition, it contributes to a better understanding of the use patterns of Chilean native plants.

The Rizoma database includes 1380 use records from 736 vascular plant species native to Chile, representing 399 genera and 128 families. Each species record provides information on geographic distribution, phytogeographic origin, life form, life span and use category. In addition, the online version includes information on the mode of use of each species, as well as common names and photographs. The database serves as a traditional knowledge repository that contributes to preserving local biological and cultural diversity for future generations.
The distribution and impact of an invasive plant species (Senecio inaequidens) on a dune building engineer (Calamagrostis arenaria)
Authors: Van De Walle Ruben , Massol François , Vandegehuchte Martijn L. , Bonte Dries
Published: March 2022

Disturbance is thought to enhance the probability of invasive species establishment, a prerequisite for naturalisation. Coastal dunes are characterised by disturbance in the form of sand dynamics. We studied the effect of this disturbance on the establishment and spread of an invasive plant species (Senecio inaequidens) in European coastal dunes. Local sand dynamics dictate the spatial configuration of marram grass (Calamagrostis arenaria). Therefore, marram grass configuration was used as a reliable proxy for disturbance. Since marram grass plays a crucial role in natural dune formation, we evaluated the possible effects S. inaequidens could have on this process, if it is able to naturalise in European coastal dunes.

We expected the highest probability of S. inaequidens establishment at intermediate marram grass cover because too low cover would increase sand burial, whereas high cover would increase competition. However, our results indicate that S. inaequidens is quite capable of handling higher levels of sand burial. Thus, the probability of S. inaequidens establishment was high under low marram cover but slightly lowered when marram cover was high, hinting at the importance of competition.

We expected a negative impact of Senecio-altered soils on marram grass growth mediated by soil biota. However, marram grass grew better in sand gathered underneath Senecio plants due to abiotic soil modifications. This enhanced growth may be caused by Senecio leaf litter elevating nutrient concentrations in an otherwise nutrient-poor substrate. If such increased plant growth is a general phenomenon, further expansion of S. inaequidens could accelerate natural succession in European coastal dunes.
The Development and Validation of a Communication Survey Instrument for Long-term Care Staff
Authors: Farrell Timothy W. , Towsley Gail L. , Eaton Jacqueline , Butler Jorie M. , Supiano Katherine P. , Stephens Caroline , Witt Catherine , Nelson Nancy M. , Edelman Linda S.
Published: March 2022

Information transfers in long-term care (LTC) settings between and among providers, staff, residents, and family caregivers are often fragmented. In order to identify training needs to improve communication, a survey instrument was developed and refined to assess the self-efficacy of LTC staff in communicating with staff, providers, residents, and caregivers. This 11-item survey instrument, based on a literature review, covered four key concepts (mutual respect, recognizing and responding to sensory deficits, limited health literacy, and changes in condition) relevant to communicating health information in LTC settings. Ten content experts evaluated each survey item using a 4-point scale. The content validity of the survey was established by using the content validity index to assess results at the item and scale levels. All items scored 0.90 or greater and were retained. Future work should entail broad-scale validation and testing of this survey across the United States. By assessing the self-efficacy of LTC staff in communicating with the interprofessional team, leadership teams can design personalized interprofessional continuing education activities aimed at improving communication skills.

[
J Contin Educ Nurs
. 2022;53(3):123–130.]
Nursing Education for the Acute Care Nurse on Pain Mechanisms of Sickle Cell Disease
Authors: Evelyn Antoinette Eldayrie , Kittelson Sheri , Mandernach Molly W. , Black Vandy , Duckworth Laurie , Wilkie Diana J.
Published: March 2022

Background

It is unknown whether nurses' knowledge about pain among patients with sickle cell disease (SCD) reflects the current standard of care. The authors evaluated changes in nurses' knowledge and simulated practice behavior after a continuing education program.

Method

Inpatient nurses completed an e-learning program on SCD pain; a pretest and a posttest with the same 10 questions; and two patient cases with four pain intervention options at the posttest.

Results

On the pretest, the mean percentage of correct answers was 83% (
SD
= 13%). The mean percentage of correct answers increased by 12% (
p
< .0001) on the posttest. For the first simulated patient case, 100% (
n
= 31) of the nurses selected an appropriate pain intervention option based on the patient-reported pain score. For the second simulated patient case, 84% (
n
= 26) did so.

Conclusion

Increased knowledge does not always translate into simulated practice change. The reasons for this are unknown, but they could include implicit bias from exposure to patients who have high use of acute care, although the minority of patients with SCD fit this description.

[
J Contin Educ Nurs
. 2022;53(3):137–144.]
Long-term Results of Partial Release Versus Nonrelease of the Posterior Cruciate Ligament at Cruciate-Retaining Total Knee Arthroplasty: Minimum 15-Year Follow-up
Authors: Chun Keun Churl , Baik Jong Seok , Kim Keon Rok , Chun Churl Hong
Published: March 2022

The goal of this study was to compare the clinical and radiologic results of posterior cruciate ligament (PCL) partial release and PCL nonrelease in performing cruciate-retaining total knee arthroplasty (CR-TKA) for a long-term follow-up period of greater than 15 years. A total of 224 patients underwent CR-TKA in our hospital from June 1996 to April 2002 with greater than 15 years of follow-up. We divided the subjects into 2 groups based on release of the PCL. Group 1 was the PCL partial release group (88 cases), and group 2 was the PCL nonrelease group (136 cases). The mean follow-up period was 16.8 years (range, 15.5-19.5 years). We compared the clinical results by measuring the Knee Society Score (KSS), Hospital for Special Surgery (HSS) score, and Western Ontario and McMaster Universities Osteoarthritis (WOMAC) score preoperatively and at the last follow-up. For radiologic results, the Knee Society Total Knee Arthroplasty Roentgenographic Evaluation and Scoring System was used and stress radiographs were obtained at the last follow-up to evaluate PCL function. There was no statistically meaningful difference in radiologic and clinical results between the 2 groups. Radiolucent lines were found for 13 patients radiologically (6 in group 1 and 7 in group 2). No instability as a result of PCL insufficiency required revision surgery on stress radiography at the last follow-up. If an appropriate procedure is performed according to PCL function intraoperatively, CR-TKA can produce a satisfactory result on long-term follow-up. [
Orthopedics
. 2022;45(4):233–238.]
Machine Learning With Electronic Health Record Data Outperforms a Risk Assessment Prediction Tool in Predicting Discharge Disposition After Total Joint Arthroplasty
Authors: Gabor Jonathan A. , Feng James E. , Schwarzkopf Ran , Slover James D. , Meftah Morteza
Published: March 2022

The Risk Assessment Prediction Tool (RAPT) predicts discharge disposition after total joint arthroplasty with only 75% accuracy. The goal of this study was to evaluate whether higher accuracy can be achieved with basic electronic health record (EHR) data combined with machine learning (ML) algorithms. Three ML analysis models were developed: model 1 (M1) evaluated the accuracy of predicted discharge disposition in concordance with the RAPT; model 2 (M2) used the RAPT questionnaire to develop an ML algorithm to predict the likelihood of discharge to home vs facility; and model 3 (M3) was developed with non-RAPT data (age, surgeon, and discharge preference) with the same ML training process as M2. Evaluation metrics included accuracy for home discharge (HD), positive predictive value for HD (PPV-HD), negative predictive value for HD (NPV-HD), sensitivity, specificity, and area under the receiver operating curve (AUROC). A total of 1405 patients were included. With M1, the overall accuracy for HD was 83.5%, PPVHD was 92.1%, NPV-HD was 45%, sensitivity was 0.88, and specificity was 0.56. With M2, the overall accuracy for HD decreased to 82.8%, PPV-HD was 91.7%, NPV-HD was 43.1%, sensitivity was 0.87, specificity was 0.53, and mean AUROC was 0.87±0.03. With M3, overall accuracy for HD increased to 90.3%, PPV-HD was 95.2%, NPV-HD was 68.6%, sensitivity was 0.93, specificity was 0.76, and AUROC was 0.91±0.02. The use of basic EHR data combined with ML can exceed the accuracy of the RAPT. Applying big data on an individual level for this purpose may allow for safer and more appropriate discharge planning. [
Orthopedics
. 2022;45(4):e211–e215.]
Interobserver and Intraobserver Reliability of the Sirveaux Classification of Scapular Notching After Reverse Total Shoulder Arthroplasty
Authors: Heckmann Nathanael D. , McKnight Braden , Chen Xiao T. , Chung Brian C. , Hill J. Ryan , Sivasundaram Lakshmanan , Omid Reza , Hatch George F.
Published: March 2022

The Sirveaux classification characterizes the severity of scapular notching after reverse total shoulder arthroplasty (rTSA). However, its reliability has not been validated. The goal of the current study was to determine the interobserver and intraobserver reliability of the Sirveaux classification. An online survey was sent to the American Shoulder and Elbow Surgeons (ASES), containing 10 radiographs showing a range of scapular notching. Members were asked to grade the degree of scapular notching with the Sirveaux classification system. Then ASES members from our institution regraded the images a second time after a minimum of 6 weeks. Fleiss' and Cohen kappa coefficients were calculated to determine the degree of interobserver and intraobserver reliability, respectively. A total of 50 ASES members graded the radiographs and 3 regraded images after more than 6 weeks. Fleiss' kappa coefficient was 0.2437, indicating fair interobserver agreement. Surgeons who perform more than 20 rTSA procedures per year (n=34) had a Fleiss' kappa of 0.2864. The mean Cohen kappa coefficient was 0.4763, indicating moderate intraobserver reliability. The Sirveaux classification system has fair interobserver and moderate intraobserver reliability. Surgeons should use additional means to describe the severity of notching, particularly when communicating with other physicians or publishing research. [
Orthopedics
. 2022;45(4):239–243.]
Cannabinoids in the Orthopedic Setting: A Literature Review
Authors: Carreira Dominic S. , Garden Steven , Huffman Allison , Ueland Thomas
Published: March 2022

Public interest in the analgesic potential of cannabinoids has grown, but there is no consensus regarding orthopedic applications. Available evidence was identified for cannabinoid use in arthritis, neuropathic pain, fibromyalgia, multiple sclerosis, and postoperative pain. Extracted information included the risks of preoperative use, associations with opioid dependence, and surgical complications. There is limited evidence for therapeutic benefit of cannabinoids in rheumatoid arthritis and fibromyalgia. Cannabinoids are not indicated for postoperative pain. Preoperative unregulated use has been linked with postoperative opioid dependence. Cannabinoids may be considered a second- or third-line treatment for analgesia for some orthopedic pathologies. [
Orthopedics
. 2022;45(4):e183–e189.]
Nonsuicidal Self-Injury: A Nurse-Led Quality Improvement Project to Address Self-Harm
Authors: Goodman Deborah , Pletch Allisyn , Paul Padmini , Anderson Elizabeth , Kverno Karan
Published: March 2022

Nonsuicidal self-injury (NSSI) behaviors, such as cutting, scratching, or more severe injuries, are frequently comorbid with neurodevelopmental, intellectual, trauma, personality, and major depressive disorders, complicating treatment and placing added care burdens on hospital nursing staff and advanced practice nurses. Although specific psychopharmacological treatment guidelines and approved medications for NSSI are non-existent, patients are treated with medications approved for co-morbid disorders and behavioral interventions targeting intrapersonal (poor emotional self-regulation) and interpersonal (communication of distress) functions. The current article describes a nurse-led quality improvement project, using the Plan-Do-Study-Act cycle, in a case example. Outcomes include improved staff competencies and policies, yet we remain challenged in implementing planned actions that add additional time burdens to already stretched care providers. [
Journal of Psychosocial Nursing and Mental Health Services, 60
(3), 7–10.]
Bacillus spp. as a new direction in biocontrol and deodorization of organic fertilizers
Authors: Nowocień Karolina ,   Department of Microbiology, Prof. Wacław Dąbrowski Institute of Agricultural and Food Biotechnology-State Research Institute 36 Rakowiecka Street, 02-532 Warsaw, Poland, Sokołowska Barbara
Published: March 2022

Bacteria belonging to the genus Bacillus are widely distributed in environments fulfilling several important functions. Due to their ability to produce antibiotics and other metabolites, these bacteria limit the development of pathogens and thus promote plant growth. They also play an important role in the deodorization of organic fertilizers, including manure, slurry, and dung. This article describes the characteristics of Bacillus spp., their properties, and their application in biocontrol.
Existence and asymptotic behavior of normalized solutions for the modified Kirchhoff equations in $ \mathbb{R}^3 $
Authors: Wang Zhongxiang ,   Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China
Published: March 2022

This paper is concerned with the following modified Kirchhoff type problem

   \begin{document}$ \begin{align*} -\left(a+b\int_{\mathbb{R}^3}|\nabla u|^2\right)\Delta u-u\Delta (u^2)-\lambda u=|u|^{p-2}u, \; \; \; x\in \mathbb{R}^3, \end{align*} $\end{document}

where $ a, b > 0 $ are constants and $ \lambda\in \mathbb R $. When $ p=\frac{16}{3} $, we prove that the existence of normalized solution with a prescribed $ L^2 $-norm for the above equation by applying constrained minimization method. Moreover, when $ p\in\left(\frac{10}{3}, \frac{16}{3}\right) $, we prove the existence of mountain pass type normalized solution for the above modified Kirchhoff equation by using the perturbation method. And the asymptotic behavior of normalized solution as $ b\rightarrow 0 $ is analyzed. These conclusions extend some known ones in previous papers.
Proximité entre riverains et pesticides en territoire de grandes cultures. Visibilité et invisibilité des micro-adaptations agricoles
Authors: Hermelin-Burnol Mathilde , Preux Thibaut
Published: March 2022

L’objet de cet article est d’interroger comment la proximité des riverains (entendus comme résidents limitrophes et promeneurs) avec les traitements aux pesticides affecte les pratiques d’agriculteurs. Nous étudions les adaptations et ajustements qu’elle entraîne au-delà de ce qui a été rendu obligatoire avec les zones non traitées (ZNT) fin 2019. Nous mobilisons la complémentarité entre un travail de terrain et une analyse spatiale par système d'information géographique (SIG) à l’échelle de l’aire urbaine de Poitiers, région agricole française de grandes cultures. Nous montrons que la rareté des conflits s’accompagne néanmoins de tensions ressenties par les agriculteurs. Les micro-ajustements temporels et spatiaux constatés traduisent une volonté d’éviter le contact avec les riverains lors de traitements. Finalement, ces adaptations prennent peu la forme d’écologisation des pratiques, dans un contexte où les pesticides sont réduits à la notion de nuisance agricole. Elles servent principalement à anticiper des tensions redoutées localement. Ces ajustements témoignent d’une prise en compte à une échelle parfois très fine des riverains par les agriculteurs.
Modelling of the Cloud Service Quality Factors Using ISM
Authors: Agarwal Rajesh , Dhingra Sanjay
Published: March 2022

In today's world, it is appallingly hard to run a global business, spread over multiple continents without adopting cloud computing technology. Cloud computing makes it easy, saves bucks, reduces IT burden, and helps organisations to focus on customer requirements, market strategy, growth, revenue, and profit, etc. While the organisations are busy planning, selecting, migrating their core business data and applications to the cloud, at the same time it is pertinent to evaluate the service quality of cloud service providers. This will help organisations to adopt the right cloud service provider as per their business requirements. Eleven cloud service quality factors have been explored through an extensive review of the literature and then interpretive structural modelling (ISM) has been used to find out the driving and dependent factors of the cloud service quality and contextual relations among them. This study reveals six driving factors of the cloud service quality namely availability, reliability, scalability, security, service responsiveness, and usability.
Marketing Analytics for Analyzing Social Media and Branding Efforts of Indian Telecom Operators
Authors: Joshi Sujata , Koparrati Sindhu , Singhal Vaishali
Published: March 2022

Business Analytics has become the new mantra in today’s digital transformation age. Digitization has changed the way marketing functions. Use of Marketing analytics and Social media platforms are some of the biggest digital transformations, seen in new marketing approaches. However, not much research has been done to witness the influence of the social media in the Indian telecom sector. So the objective of this paper is to study two digitization aspects in marketing which is the application marketing analytics for social media platform with respect to the Indian telecom operators Thus, the research intends to Study the impact of Social Media Efforts (SMME) on Branding and Customer Response (CR) with respect to Indian telecom brands. Primary data was collected from 184 respondents and statistical analysis has been performed to see the effect of SMME on branding and consumer response for telecom brands. Findings of the study confirm that Social Media Marketing Efforts (SMME) have significance impact on both Branding and Consumer Response (CR).
An Adaptive Mechanism for Virtual Machine Migration in the Cloud Environment
Authors: Singh Gurpreet , Malhotra Manisha , Sharma Ajay
Published: March 2022

To manage all the operations of data centers resources, virtualization is the effective technique. In virtualization the virtual machine migration is the way by which data center operator can easily adapt the replacement of virtual machine, improves the resource provisioning and any other maintenance function of data center. Despite of this the virtual machine migration scheme is the major challenge to improve the efficiency of data center. This paper proposed a virtual machine migration process which will be responsible to minimize the migration which leads to reduce the execution time.
A Case Study of Cloud Computing Service Models for the General Computing Environment in a University
Authors: Kang Ho Yeon , Lee Jong Yun , Noh Seo-Young
Published: March 2022

Cloud computing technology has emerged as the basic infrastructure technology in the 4th industrial revolution and has been utilized in various fields. Therefore, the authors analyze the requirements of academic and administrative affairs, education affairs, and affiliated institutions in the university. Proposed cloud computing service models in the universities are implemented using an OpenStack in CentOS 7.3 and Windows. To evaluate the performance, the author compares various performance factors including launching time, booting time, ping time, and software installation time. Lastly, the economic benefits in the university will be evaluated by comparing the adoption cost, maintenance cost, and total cost between the existing client-server system and cloud computing system. Future work aims to implement a cloud computing system that can be applied to the entire university. Finally, based on these studies, the authors will implement a regional base cloud system that can connect all universities in the region with one cloud computing system.
Efficient Resource Management Using Improved Bio-Inspired Algorithms for the Fog Computing Environment
Authors: Bulla Chetan M. , Birje Mahantesh N.
Published: March 2022

The resource monitoring and management services together play a vital role in improving the overall performance of fog computing services. The monitoring system continuously keeps track of all resources by collecting and analyzing the status information and alert the user when the performance decreases. Resource management involves load balancing, resource scheduling and allocation and it requires accurate resource status which is provided by resource monitoring system to take scheduling and allocation decisions. The resource management activities are NP-hard problems and require optimal techniques to improve resource utilization and reduce energy consumption and latency. This paper proposes resource management model using improved bio-inspired algorithms and fog monitoring model to improve resource utilization and reduce energy consumption. The simulation results show that the proposed model is effective in terms of execution time, response time and energy consumption compared to the state of art techniques.
An Empirical Analysis of Receiver's Psychological Characteristics in eWOM Engagement
Authors: Rani Anshu , Shivaprasad H. N.
Published: March 2022

Customer engagement in e-commerce (CEE) is paramount to success and CEE can be achieved by engaging customers in eWOM. However, every customer perceives the eWOM message from their perspective. There is a limited number of studies conducted on Receiver’s characteristics of eWOM and hence, the purpose of this research is to analyse the different personal characteristics of the Receivers of eWOM and their influence on eWOM communication’s effectiveness. The quantitative research is carried out with the help of existing scales items from relevant literature. The final analysis included 503 responses. Further, EFA, CFA and Structural Equation Modelling techniques are used to determine the empirical relationships among variables. Five major characteristics of Receivers were identified to understand their relationship with purchase intention, attitude change and brand image. The paper found a significant relationship between hypothesized variables. This study will contribute to the likelihood of profiling receivers and significantly improve the impact of eWOM on e-engagement.
Effect of Mass Media on Body Image and Self-Esteem of Teenage Girls
Authors: Shukla Vandana , Srivastava Sangita
Published: March 2022

This paper investigates whether mass media (social media) affects the body image and self-esteem of teenage girls. For most people, the beauty or covetable feminine body image of teenage girls is defined by a charming face and thin body shape commonly known as zero figures. But this definition of beauty cannot be true always because it is based on the experience of seeing which is not all-encompassing. The whole beauty of the girls can be defined by the combination of all the experiences, as experiences of seeing, listening, touching and all other which we are perceived by an individual. Now a day’s social media is the major source to share information among individuals. This paper provides the effects of social media on the body image and self-esteem of teenage girls. This study targets teenage girls because physical attractiveness is especially important to them and a thin and beautiful idealized image in social media plays a significant role in influencing their self-confidence. Further a data driven model using Artificial intelligence (AI) suggested for future challenges.
Fake Identities in Social Cyberspace
Authors: Topor Lev , Pollack Moran
Published: March 2022

Personation - the act of assuming another’s identity with intent to deceive, is an ancient phenomenon. In this article we seek to research online impersonation and to uncover the causes for this phenomenon. We do so by analyzing and comparing several case studies while referring to more traditional concepts of social identity. As discovered, on the one hand users can create fake identities to enhance their personalities for personal reasons such as voyeurism or as means of escaping reality, or even promote human rights by avoiding local authoritarian censorship. On the other hand, malicious users like terrorists or criminals manipulate online users with phishing attempts and frauds, making social cyber space less secure.
On the Analysis of Horror Stories in the Militants' Narratives as Markers of Violent Behavior and Conflict Identity
Authors: Kostyuchenko Yuriy V. , Pushkar Viktor
Published: March 2022

The paper considers the horror stories spread among the militants of illegal armed groups “L/DPR” in the period 2014-2021; examples from personal interviews of militants are given; an algorithm for narratives detection and analysis is proposed, a preliminary classification of such stories is proposed: narrative artifacts, trench legends and artificial propaganda narratives; estimates of the dynamics of the spread of such stories is described; conclusions are drawn on the origin and functionality of scary stories: the stories of pro-Russian militants are mostly products of a rethinking of Soviet military folklore, and their functions are the dissemination of group norms and initiation of newcomers. Assumption on militant’s identity and on the drivers of violent behavior are proposed.
Recent Trends in Child Sexual Abuse Material (CSAM) Distribution in Indian Cyberspace
Authors: Gautam Sanjay Kumar , Khajuria Himanshu , Gupta Reeta Rani , Nayak Biswa Prakash
Published: March 2022

The emergence and evolution of social media and technology poses challenges in the prevention of child sexual exploitation and abuse. This issue is not successfully addressed by the existing techno-legal apparatus and is posing risks to the children. In India, CSAM files are illegal and constitute an offense under Section 67(B), IT Act 2000. The technology has also made available various tools and techniques, to the predators who are always ready to groom and exploit teenagers & circulate their indecent images / videos. This research work has been carried out to assess a qualitative estimate of the quantum of Child Sexual Abuse Material (CSAM) circulated in Indian Cyberspace using peer-to-peer technology. Although CSAM is legally banned, many unique IP addresses were found to be distributing a total of 27,00,08,502 disturbing material depicting the sexual abuse of children distributed over 7 torrents spreading over 29 States and 5 Union Territories.
Techno-Radicalism
Authors: Arzroomchilar Ehsan
Published: March 2022

Today there is fairly rich literature to study how radical groups take advantage of technology to realize their goals. Something, however, is missing in such discussions as to how technology might affect the subjectivity of extremists. Technology, in the most of such inquiries, is taken to be merely a passive tool without any inherent bias. This instrumentalist approach to technology, however, turns out to be problematic. The contemporary studies of technology may provide us, as it will be argued, with insights to understand how technology might incline civilians towards radicalization. Two frameworks of postphenomenology and Actor-Network-Theory (ANT) will be the primary focus here to outline a schema of the impacts of technology on radicalization of minds. Although technology, with all its variety, is the general concern of the article, it will narrow the discussion down to social media platforms to make the point. It will be then suggested to ascribe an active role to technology in radicalism scholarship, thereby drawing attentions to the process of designing technologies.
Understanding the Community's Perceptions Towards Online Radicalisation
Authors: Neo Loo Seng
Published: March 2022

This study seeks to understand the community’s perceptions towards detecting signs of online radicalisation and examine whether different community members would exhibit different levels of understanding. A 57-item survey was administered to 160 undergraduates from Nanyang Technological University (NTU) and 160 Amazon Mechanical Turk (MTurk) workers. Based on the ratings of the 42 online radicalisation indicators identified by Neo (2020), two-factor analyses were separately conducted using oblique rotation to undercover a four-factor structure for the NTU sample and a three-factor solution for the MTurk sample. The results revealed valuable insights into how community members would identify terrorist threats. Furthermore, the survey revealed differences in the participants’ views on the role of the internet in radicalisation pathways and their perceptions regarding various counter-terrorism strategies. Together, the findings would contribute to the discussion of how law enforcement could better engage and work together with the community members to detect terrorist threats.
The Impact of the COVID-19 Pandemic on the Radical Behavior and Armed Conflict Escalation Risks
Authors: Kostyuchenko Yuriy , Pushkar Viktor , Malysheva Olga , Yuschenko Maxim
Published: March 2022

The paper considers the impact of the COVID-19 epidemic to the behavior of militants of illegal armed groups and the population in the militant-controlled territories. The study was conducted on the example of the territories of self-proclaimed “L/DPR” within Donbass (Eastern Ukraine) in the period March-May 2020. Based on the analysis of social networks and media, the main narratives related to the perception of threats of epidemic were identified and analyzed. Its prevalence and dynamics among the militants and population in comparison with radical groups and population of Ukraine was analyzed. The main types of moods and emotions that were associated with the perception of epidemic were identified. The management decisions of the “L/DPR” leaders during the epidemic were analyzed. It was found that the measures of militant's “authorities” were not aimed to protecting population, but to social management - channeling aggression and propaganda discourse constructing.
Influences of Digital Transformation on Life Expectancy and the Gender Gap in European Countries
Authors: Le Thanh Ha , Phuc Hai Nguyen , Xuan Nam Pham , Dinh Bao Ho
Published: March 2022

Our paper empirically examines the influence of the digital transformation process on life expectancy employing a sample of 20 European countries over the period from 2015 to 2020. In the models, digitalization is captured by six measures. Our results illustrate that using the internet and online activities reduce life expectancy, whereas business digitization, e-commerce, digital public services, and higher digital skills in the population can improve the life expectancy of men and women, leading to a reduction in the gender gap. Furthermore, we detect that men are significantly more affected by the implementation of digital transformation, while online administrative procedures also lead to a rise in life expectancy but only in women. These effects only exist in the long term. We also find that digital connectivity, business digitization, e-commerce, and digital skills help people survive longer during the Covid-19 pandemic.
Intrinsic Antecedents to mHealth Adoption Intention
Authors: Bhatt Vaidik , Chakraborty Samyadip
Published: March 2022

Healthcare is not left behind in the technological era, where almost every industry uses technological advances to serve customers' needs and wants. Increasingly, patients and doctors are using modern technological infrastructure to deliver care services. This study focuses on the intrinsic factors that lead to provider adoption of mHealth. The study uses PLS-SEM and neural networks to build on UTAUT theory. Study collects data from 316 care providers practicing in government and private health canters, hospitals and clinic found that intrinsic factors like self-efficacy, personal innovativeness, and performance expectancy positively related to mHealth adoption by physicians, whereas technology anxiety negatively related to adoption behaviour. Effort expectancy is not significant, indicating that m-Health adoption is driven by usefulness and result rather than convenience. If the expertise is not easily available, the physician's best interest for the patient may often drive them to adopt m-Health.
Designing an E-Voting Framework Using Blockchain Technology
Authors: AlAbri Raya , Shaikh Abdul Khalique , Ali Saqib , Al-Badi Ali Hamad
Published: March 2022

Blockchain technology provides a stable spot in electronic voting systems by providing a transparent platform for an election which prevents the failures faced by the traditional electronic voting systems and makes it a more accurate and secure platform for voting. However, little attention has been paid to the possible impacts of new technological disruptions on politics and the electoral systems. The main goal of this paper is to design a framework for electronic voting systems using Blockchain technology. To achieve this goal, the paper outlines these three objectives: (1) to explore and identify the challenges in existing voting systems, (2) to identify the methods that could enhance the security and privacy of the electoral voting systems using Blockchain technology, and (3) to design a framework for electronic voting systems that use Blockchain technology in order to address the flaws in current voting systems. A mixed approach is applied in this study to explore the opportunities and challenges of the Blockchain voting system, and design the framework accordingly.
Structure-Activity Relationship Studies of Staphylococcus aureus DNA Gyrase B Inhibitors as Antibacterial Agents Employing Random Forest Models
Authors: Fernandes Philipe Oliveira , Maltarollo Vinicius Gonçalves
Published: March 2022

Infections by Staphylococcus aureus are a serious healthcare problem, with a high alert for resistant strains. The World Health Organization characterized the methicillin-resistant S. aureus in the high priority group for the development of new antibiotics. Following this need, inhibition of DNA gyrase presents itself as an interesting drug target, due to the lack of homologs in mammalian, and it could be a way to overcome the resistance problem. In this study, classification structure-activity relationship models based on the Random Forest algorithm were employed to classify antibacterial compounds acting as DNA gyrase inhibitors. The models were generated and validated for the classification of antibacterial activity (external MCC = 0.775), DNA gyrase inhibition (external MCC = 0.577), and a consensus of these two endpoints (external MCC = 0.577). The structural interpretation highlighted the relevance of heterocycles substituents. This information may provide understanding in the structure-activity relationship of this compounds class, providing insights for further developments.
Stereo Seam Coupling and Depth Distortion Score in 3D Image Retargeting Using DMA Algorithm
Authors: Jagtap Mahendra Tulsiram , Jawalkar Dineshkumar
Published: March 2022

Preserving the highlighted contents in left and right stereo images by using seam carving technique is the challenging job in current digital era. The seam carving technique facilitates to minimise the trouble by eliminating unwanted seam patches from the stereo images by using saliency detection method. These images are popularly known as stereoscopic images. This paper addresses the issues in 2-D planer images and emphasised on 3-D stereoscopic images. We method enforces on the foreground pixels which are highly considerable by calculating the high energy pixels. The depth distortion estimation is performed by adjusting the aspect ratio. The viewpoints of left and right stereo images are somewhat different. Disparity Map Acquisition (DMA) algorithm maps the pixel points from the left stereo image to its corresponding right image pixels. The fusion of the left and right images is incorporating to minimise the depth distortion score.
Economics of Software Testing Using Discrete Approach
Authors: Shrivastava Avinash K. , Sharma Ruchi
Published: March 2022

In the last few years, researchers have proposed various cost modes to determine the optimal release and testing termination time considering continuous approach. However, it has been shown in the literature that it is better to develop the model by considering the number of test cases executed to remove faults. This is possible by using discrete modelling approach developed in the software reliability literature. There is no evidence of any research work in the direction of separating the release and testing termination using discrete approach. In this work, the authors have developed a discrete framework to determine the optimal release and testing termination under budgetary constraint. Numerical illustration suggests that it is better to release the software after executing lesser number of test cases and continue to execute the test cases during post-release. Also, the proposed total cost is significantly less in comparison to the existing approach using discrete approach.
The Factors Affecting Continuous Usage Intention of Computer-Aided Engineering (CAE) Software
Authors: Cho Yong Won , Kim Dae Sik , Phuong Huy Tung , Gim Gwangyong
Published: March 2022

The topic of improving manufacturing productivity has been constantly improving over a long period of time to compromise with unsatisfactory themes such as time, cost, and quality. It has recently faced a whole new challenge of pandemic as well as the various themes of the Fourth Industrial Revolution. At this point in time verifying the intent of continuing use to experts on Computer Engineering Simulation (CAE), one of the main topics of engineering areas for improving manufacturing productivity, is meaningful in determining the direction of future changes. To this end, CAE experts from manufacturing companies and government-funded research institutes conducted empirical studies on the impact of perceived value factors, information system factors, and brand factors on satisfaction and willingness to use. It found that the perceived economic, temporal value, information and service quality, and brand trust affect the degree of continuous use through satisfaction.
Automata-Based Approach to Manage Self-Adaptive Component-Based Architectures
Authors: Saadi Abdelfetah , Hammal Youcef , Oussalah Mourad Chabane
Published: March 2022

Dynamic software architectures in changing environments need human supervision to continue operation in all conditions. These changes may come from the software architecture or its environment. Such software architecture is required to monitor itself and its environment, detect changes, decide how to react, and act to perform such changes. Enhancing the software architecture with the ability to self-adapt offers a very interesting way forward. This work presents an automata based approach to manage self-adaptive component-based architecture. This approach allows software architecture to adjust itself to changes during runtime and without stopping its execution. It helps the maintenance of the consistency and the coherence of software architecture before, during and after adaptation. The proposed approach is based mainly on the use of the meta-model, automata concept, XML language and UPPAAL model checking tool for the verification of the software consistency before enacting adaptation.
Empirical Analysis of Pair Programming Using Bloom's Taxonomy and Programmer Rankers Algorithm to Improve the Software Metrics in Agile Development
Authors: Regis Anne W.  , Carolin Jeeva S.
Published: March 2022

Collaborative programming is a co-operative effort of 2 teams to n-teams to share knowledge, synergize and produce better code. Pairing, Swarming and Mobbing are the standard of agile technology which are adapted by many organizations. In this paper, software development is carried out using Pair Programming(PP) in a medium sized organization developing mobile applications using android is presented. The first method uses the Programmers Competency Matrix (PCM) based on Blooms Taxonomy to assess the skill of the programmers. Since, the pairs are chosen randomly in the PCM method, a novel algorithm is proposed to pair the programmers by Programmer Ranking Algorithm (PRA). The two proposed methods are evaluated in an organization and the results are validated. The results prove that PP definitely improves the software development process than when it is developed by individual programmers. The PRA methodology outperforms the PCM because the PRA chooses the pair wisely using the programming skills of the programmer.
Depression Identification Through Tweet Clusters
Authors: Masand Abhishek , Chauhan Suryansh , Jain Tarun
Published: March 2022

Over the past few years, the awareness and popularity of Mental health have been on a rapid rise and people are becoming more aware of the surrounding problems. This has helped for mental illnesses like Depression to become recognized and be treated appropriately. Social media has played an integral part in this uproar due to its increased popularity and ease of use. This has allowed people to spread awareness, seek help and vent out their emotions. Our paper is a comparative study of different models for detecting depression with real-time Twitter data and proposing the best performing model. For depression detection, a collection of tweets per user spread over time was used. The data was augmented and then passed through the deep learning model to identify depression in Twitter users based on their Time-Distributed tweets. The proposed model achieved an accuracy of over 90%.
A Metaheuristic Optimization Approach-Based Anomaly Detection With Lasso Regularization
Authors: Verma Vivek Kumar , Garg Payal , Tiwari Pradeep Kumar , Jain Tarun K.
Published: March 2022

The paper here suggests a new intrusion detection method that is applied using an improved Lasso Regularization Metaheuristic Optimization. A comparison with other metaheuristic algorithms used to test the current method alongside the associated works is part of the proposed analysis herein. Because of the high processing capacity, network traffic in the intrusion detection system (IDS) has erratic behavior. The size of the device increases; the vast number of features must then be explored. However, the undesirable features and (or) any noisy data have a significant effect on the performance of the IDSs. Lasso regression implements L1 regularization, applying a penalty proportional to the absolute value the coefficient magnitude. Sparse formulas with few coefficients can result in this form of regularization; certain coefficients can become negative and be removed from the model. The algorithm for particle swarm optimization (PSO) is added to the selective features that increased the IDS' detection rate and accuracy.
Determining Optimal Release and Testing Stop Time of a Software Using Discrete Approach
Authors: Shrivastava Avinash K. , Sharma Ruchi
Published: March 2022

In the last 20 years researcher’s proposed to determine the optimal release and testing termination time considering the calendar time or continuous approach. However, it has been shown in the literature that it is better to develop the model by considering the number of test cases executed to remove faults. This is possible by using the discrete modelling approach developed in the software reliability literature. In the existing discrete software reliability literature, no work has been done in the direction of separating the release and testing termination time. In this work, we have developed a discrete framework to determine the optimal release and testing termination time under budgetary constraints. The numerical illustration suggests that it is better to release the software after executing a lesser number of testing periods. Also, the total cost in the proposed strategy is significantly less as compared to the existing discrete release time literature.
Forward Kinematic Analysis of 6-R Industrial Robot Using Active Sampled Neural Network Regressor
Authors: P. Kesaba , Choudhury Bibhuti Bhusan
Published: March 2022

This paper describes the estimation of robotic forward kinematics using Neural Network (NN). The quality of training data is highly essential for better accuracy of NN models. So, in this contribution, clustering-based refined training data selection is performed to improve the representativeness of the selected data. The k-means clustering algorithm is adopted to find the most distinct and informative training data. The 6-R MTAB Aristo-XT robot is selected as a case study to generate the experimental training and testing data for validation of ML techniques. Standard performance measures such as deviation error, Mean Square Error (MSE) are evaluated and graphical illustrations are presented for fair comparison of the results. Experimental results reveal that, instead of random sampling, the clustering-based active sampled training data selection is strongly suggested to improve the accuracy of NN regressor, and also it greatly reduces the time complexity to train the model.
Things-Net
Authors: Bouyakoub Samia , Belkhir Abdelkader
Published: March 2022

The Internet of things aims to create a continuity between real and digital worlds, by integrating physical objects into the digital universe. This will increase the number of connected machines and generate new applications. When combined according to an appropriate logic, IoT objects can produce value-added services that a single object cannot provide. In order to avoid costly errors, this execution logic has to be modeled and validated, using a formal model, before its effective deployment. To address the lack of special-purpose modeling languages for IoT applications, the authors propose the Things-Net model, designed specifically to meet the needs of IoT-based systems. It allows an easy modeling and verification of IoT time-dependent platforms, to ensure that the designed IoT solution fulfills the application's requirements. In order to illustrate the approach, authors apply the modeling and verification techniques to a prototype of an airport management system based on IoT.