bluuebunny/crossref_metadata_2025 huggingface dataset:
The prediction of coronavirus disease 2019 outbreak on Bangladesh perspective using machine learning: a comparative study
Authors: Rahman Maqsudur , Ahmed Md. Tofael , Nur Shafayet , Touhidul Islam Abu Zafor Muhammad
Published: May 2022

Coronavirus disease 2019 (COVID-19) has made a huge pandemic situation in many countries of the world including Bangladesh. If the increase rate of this threat can be forecasted, immediate measures can be taken. This study is an effort to forecast the threat of present pandemic situation using machine learning (ML) forecasting models. Forecasting was done in three categories in the next 30 days range. In our study, multiple linear regression performed best among the other algorithms in all categories with R2 score of 99% for first two categories and 94% for the third category. Ridge regression performed great for the first two categories with R2 scores of 99% each but performed poorly for the third category with R2 score of 43%. Lasso regression performed reasonably well with R2 scores of 97%, 99% and 75% for the three categories. We also used Facebook Prophet to predict 30 days beyond our train data which gave us healthy R2 scores of 92% and 83% for the first two categories but performed poorly for the third category with R2 score of 34%. Also, all the models’ performances were evaluated with a 40-day prediction interval in which multiple linear regression outperformed other algorithms.
Optimal state estimation techniques for accurate measurements in internet of things enabled microgrids using deep neural networks
Authors: Rao Padupanambur Sudhakar , Riyaz Ahmed Mohammed , Divakar Bangalore Prabhakar
Published: May 2022

The employment of microgrids in smart cities is not only changing the landscape of power generation, transmission, and distribution but it helps in green alleviation by converting passive consumers into active produces (using renewable energy sources). Real-time monitoring is a crucial factor in the successful adoption of microgrids. Real-time state estimation of a microgrid is possible through internet-of-things (IoT). State estimation can provide the necessary monitoring of grid for many system optimization applications. We will use raw and missing data before we learn from data, the processing must be done. This paper describes various Kalman variants use for preprocessing. In this paper a formulated approach along with algorithms are described for optimal state estimation and forecasting, with weights update using deep neural networks (DNN) is presented to enable accurate measurements at component and system level model analysis in an IoT enabled microgrid. The real load data experiments are carried out on the IEEE 118-bus benchmark system for the power system state estimation and forecasting. This research paves a way for developing a novel DNN based algorithms for a power system under dynamically varying conditions and corresponding time dependencies.
Enhancing hybrid renewable energy performance through deep Q-learning networks improved by fuzzy reward control
Authors: Ameur Chahinaze , Faquir Sanaa , Yahyaouy Ali , Abdelouahed Sabri
Published: May 2022

In a stand-alone system, the use of renewable energies, load changes, and interruptions to transmission lines can cause voltage drops, impacting its reliability. A way to offset a change in the nature of hybrid renewable energy immediately is to utilize energy storage without needing to turn on other plants. Photovoltaic panels, a wind turbine, and a wallbox unit (responsible for providing the vehicle’s electrical need) are the components of the proposed system; in addition to being a power source, batteries also serve as a storage unit. Taking advantage of deep learning, particularly convolutional neural networks, and this new system will take advantage of recent advances in machine learning. By employing algorithms for deep Q-learning, the agent learns from the data of the various elements of the system to create the optimal policy for enhancing performance. To increase the learning efficiency, the reward function is implemented using a fuzzy Mamdani system. Our proposed experimental results shows that the new system with fuzzy reward using deep Q-learning networks (DQN) keeps the battery and the wallbox unit optimally charged and less discharged. Moreover confirms the economic advantages of the proposed approach performs better approximate to +25% Moreover, it has dynamic response capabilities and is more efficient over the existing optimization approach using deep learning without fuzzy logic.
Coronavirus disease 2019 detection using deep features learning
Authors: A. Khalaf Zainab , Shaheen Hammadi Saad , Khattar Mousa Alaa , Murtada Ali Hanan , Ramadhan Alnajar Hanan , Hashim Mohsin Raghdan
Published: May 2022

A Coronavirus disease 2019 (COVID-19) pandemic detection considers a critical and challenging task for the medical practitioner. The coronavirus disease spread so rapidly between people and infected more than one hundred and seventy million people worldwide. For this reason, it is necessary to detect infected people with coronavirus and take action to prevent virus spread. In this study, a COVID-19 classification methodology was adopted to detect infected people using computed tomography (CT) images. Deep learning was applied to recognize COVID-19 infected cases for different patients by employing deep features. This methodology can be beneficial for medical practitioners to diagnose infected patients. The results were based on a new data collection named BasrahDataset that includes different CT scan videos for Iraqi patients. The proposed system gave promised results with a 99% F1-score for detecting COVID-19.
Distributed rule execution mechanism in smart home system
Authors: Budi Agung Setia , Fitriyah Hurriyatul , Setiawan Eko , Primananda Rakhmadhany , Maulana Rizal
Published: May 2022

Smart home systems become an interesting topics in the last few years. Many researchers have been studied some features. Most of smart home system use a centralized architecture know as centralized smart home system (CSHS). The centralizedmechanism is easy to manage and to configure. However, in fault-tolerant systemparadigm it produces a problem. The entire system will fail, if the master station fails.Another problem of CSHS is centralized mechanism gives more data-flow. This condition makes the system has a greater delay time. To solve the problem, we proposea distributed rule execution mechanism (DREM). Compared to the centralized mechanism, the DREM allows a device to provide its service without any commands fromthe master station. In this mechanism, since the information does not need to go tothe master station, the data-flow and the delay-time can be decreased. The experimentresults show that the DREM is able to mask the failure in the master station by directlytransmit the data from trigger device to service device. This mechanism makes the services provision without master station possible. The mathematical analysis also shows that the delay time of the service provision of the DREM is less than the delay time ofCSHS.
Design of a new backstepping controller for control of microgrid sources inverter
Authors: Zadehbagheri Mahmoud , Kiani Mohammad Javad , Sutikno Tole , Moghadam Rasoul Arvin
Published: May 2022

Emergency power supply is becoming an important capability for many home or industrial electronic and computer devices. Therefore, the performance of the designed unintermptible power supplies (UPS) inverters has low distortion at the output voltage. Initially, such inverters were controlled by proportional integral (PI) control classic rules. This method is difficult to understand the limitations of stability and to apply transient response to strong external disturbances. In this paper, an inverter is simulated and offered for single-phase and three-phase voltage controlled by a non-linear controller. For this purpose, a comparison has been made between the controller performance and the PI controller. In the first step, there is a backstepping regulator that uses the stability tool next to the Lyapunov function. And the other regulator operates according to the PI method. The performance of these two regulators is simulated during a change in reference or a load change in MATLAB. Also, a method of feedback voltage control based on the Lyapunov theory for controlling of the distributed generation (DG) unit independent Inverter is presented. The proposed controller is not only simple, but also against the sudden changes in load and the unspecified system is resistant.
The Security–Sustainability Nexus: Lithium Onshoring in the Global North
Authors: Riofrancos Thea
Published: May 2022

The political economy of lithium, a “critical mineral” for the renewable energy transition, is marked by two striking developments. First, Global North governments that have historically offshored mining are onshoring lithium to enhance “supply chain security.” Second, these governments have committed to “sustainably sourcing” lithium. In this article, I theorize both developments in terms of a novel security–sustainability nexus: an interlocking set of policies and justifications that promote lithium extraction and emphasize the environmental credentials of Global North mining. The security–sustainability nexus evidences an alignment between state and corporate interests. For public officials, onshoring policies counter China’s “dominance” over battery supply chains. For mining and auto firms, onshoring translates into lucrative incentives, supply security, and reputational benefits. However, despite this state–corporate alignment, the tensions within the security–sustainability nexus illuminate the contradictions of green capitalism. I conclude that the geopolitical and socioenvironmental conflicts over the material foundations of the energy transition are reshaping the inequalities linked to extractive sectors.
A novel post-processing method for progressive failure analysis of brittle composite compression
Authors: Cutting Rebecca A , Favaloro Anthony J , Goodsell Johnathan E
Published: May 2022

Finite element analysis of brittle materials in axial compression typically uses element deletion to allow continued global deformation post-element-failure. However, element deletion produces cyclic load-displacement curves that underestimate energy absorption and are not representative of a continuum system. Two key observations support the conclusion that results from an appropriately discretized model can be an adequate representation of a continuum system. Specifically, the frequency of the oscillations in the load-displacement curve is directly dependent upon element length in the loading direction, and the peak amplitudes of oscillations are mesh size independent. A method of post-processing the analysis results, by connecting the peak amplitudes of oscillations, is proposed and applied to a series of continuous carbon fiber composite crush tubes. The load-displacement curve, stable crushing load, and specific energy absorption of the post-processed results compare well to an experimental study of crush tubes with similar layups.
Effectiveness in Fostering Metacognition: Analysis Into the State of Metacognition within South African Physical Science Classrooms with the Aim of Improving Attainment
Authors: Rajcoomar Ronesh , Morabe Olebogeng Nico , Breed Betty
Published: May 2022

This research analyzed the state of metacognition in South African Physical Science classrooms, the extent to which South African Physical Science teachers possess metacognitive awareness, and how effective the teachers are in fostering metacognition. Assessment of the current state of metacognition in a sample of Physical Science classes at two KwaZulu-Natal districts, inferring the observed and analyzed level of metacognition of the participants, was based on the assumption that low levels of metacognitive awareness was the reason for achieved poor results. The major findings of this research found; there is a poor state of metacognitive awareness within the studied Physical Science classrooms.
Business-to-Business Projects, Task Configuration, and Innovation
Authors: Ghazimatin Elham , Mooi Erik A. , Heide Jan B.
Published: May 2022

Many new products and processes originate from projects. In two studies, the authors consider how a project's organizational design, as captured by its particular task configuration, impacts its ability to promote product and process innovation. Study 1 involves an analysis of panel data spanning 2001 through 2015 and involving 429 business-to-business projects in the construction industry. The authors test hypotheses regarding the role of project size, subcontractor diversity, and task configuration on product and process innovation. Their empirical tests show a pattern of nuanced effects on the two innovation types. A project's task configuration, as reflected in the general contractor's participation in project tasks, plays a coordination role that helps unlock a positive effect of project size on product innovation. At the same time, such participation impedes process innovation due to subcontractor concerns about information leakage. Study 2 bolsters the first study through a survey of 230 subcontractors in the U.S. construction industry to show how leakage concerns arise, their outcomes, and how they are mitigated. The authors also bolster their central study through (1) interviews with professional construction managers and (2) survey evidence across five industries. They draw on their findings to develop implications for innovation management, business-to-business marketing, and marketing organization.
Self-Paced Endurance Performance and Cerebral Hemodynamics of the Prefrontal Cortex: A Scoping Review of Methodology and Findings
Authors: Hyland-Monks Robert , Marchant David , Cronin Lorcan
Published: May 2022

Recent research has suggested that top-down executive function associated with the prefrontal cortex is key to the decision-making processes and pacing of endurance performance. A small but growing body of literature has investigated the neurological underpinnings of these processes by subjecting the prefrontal cortex to functional near-infrared spectroscopy (fNIRS) measurement during self-paced endurance task performance. Given that fNIRS measurement for these purposes is a relatively recent development, the principal aim of this review was to assess the methodological rigor and findings of this body of research. We performed a systematic literature search to collate research assessing prefrontal cortex oxygenation via fNIRS during self-paced endurance performance. A total of 17 studies met the criteria for inclusion. We then extracted information concerning the methodology and findings from the studies reviewed. Promisingly, most of the reviewed studies reported having adopted commonplace and feasible best practice guidelines. However, a lack of adherence to these guidelines was evident in some areas. For instance, there was little evidence of measures to tackle and remove artifacts from data. Lastly, the reviewed studies provide insight into the significance of cerebral oxygenation to endurance performance and the role of the prefrontal cortex in pacing behavior. Therefore, future research that better follows the guidelines presented will help advance our understanding of the role of the brain in endurance performance and aid in the development of techniques to improve or maintain prefrontal cortex (PFC) oxygenation to help bolster endurance performance.
Using Multimodal Public Service Announcement Video Projects as Communicative Language Assessments
Authors: Greenblatt Philip , McDonald Peter
Published: May 2022

Although multimodality has received vigorous attention and debate in English as a foreign language (EFL) research and classroom pedagogies, the practicality of using multimodal activities in curricula that are designed to teach language skills rather than multimodality is under researched. This paper contributes to the ongoing need for practical applications of multimodality in classroom contexts by describing how a multimodal video project was introduced into an EFL classroom in a Japanese university. The class was following a communicative curriculum prescribed by the university, which had not previously focused on multimodal approaches. The multimodal project was used to assess student's communicative performance. The students worked in groups to create public service announcement (PSA) videos, with the aim of delivering an informative message to highlight a health or social issue that they felt was important. In the project the students: (1) analysed several PSA videos; (2) researched social and health issues; and (3) worked together to plan, film, and edit a final digital product that was displayed in class for their peers. The authors found that the multimodal project worked successfully as a means of assessing communicative language because it generated a wide range of learning opportunities for improvement in English language proficiency and the students could engage in communicative activities with a high degree of autonomy and motivation. Moreover, students could gain experience communicating through multimodal platforms and improve their understanding of multimodal literacies. However, the multimodal project created challenges for the teacher in how to give effective feedback on students linguistic output as well as their multimodal output within the constraints of a busy language classroom.
Effect of Risk Message Framing on Tourists’ Travel Intention: Roles of Resilience and Impulsivity
Authors: Xie Chaowu , Zhang Jiangchi , (Sam) Huang Songshan
Published: May 2022

The effect of risk message framing on travel intention requires more empirical investigations in long-term high-risk situations like the current COVID-19 pandemic. Based on frame theory, this study employed an experimental design to examine how two contrasting approaches of COVID-19 risk message framing (amplifying vs. attenuating) affected post-pandemic travel intention via the mediation of perceived safety and travel fear, and how resilience and impulsivity as tourist traits moderate these relationships. Survey results based on 481 responses revealed that: (1) risk messages significantly predicted tourists’ perceived safety, travel fear, and travel intention; (2) tourists’ perceived safety and travel fear mediated the effects of risk messages on travel intention; (3) while resilience moderated the effects of message framing on perceived safety and travel intention, impulsivity only moderated the effect of message framing on travel fear. The study provides a theoretical basis and practical implications for destination risk communications.
Considerations when using rating scales to support teacher professional development: A commentary on Weadman, Serry and Snow (2022)
Authors: Mathers Sandra J.
Published: May 2022

While observational rating scales such as the Emergent Literacy and Language Early Childhood Checklist for Teachers (ELLECCT) have potential to support Early Childhood Teachers in improving their practice, the existence of a valid and reliable tool is no guarantee of success. A carefully constructed model of teacher professional development will be required to ensure benefits for instructional practice and child language outcomes. This commentary considers the evidence available to guide intelligent design of such a model.
Longitudinal Psychological Family Studies in Austria: A Scoping Review
Authors: Freischlager Laura , Siegel Magdalena , Friedrich Amos S. , Zemp Martina
Published: May 2022

Longitudinal psychological research on family outcomes provides crucial information about families in a changing society, but an evidence synthesis for Austria is currently lacking. Therefore, we aim to summarize psychological longitudinal research on family-related outcomes in Austria using a scoping review approach. Adhering to PRISMA guidelines, we searched five scientific databases (PsycInfo, PSYNDEX, Pubmed, Scopus, and Web of Science) and conducted manual searches to identify additional grey literature. Ten sources reporting on six data collection efforts between 1991 and 2015 were identified. Most samples consisted of heterosexual nuclear families, while research on more diverse family types is needed. Methods were primarily quantitative with conventional designs, but noteworthy exceptions exist. Comprehensive longitudinal data collection efforts across child development are lacking for the new millennium. State-of-the-art research implementing a triangulation of methods, designs, and perspectives that incorporate diverse family types is needed to draw accurate conclusions about the changing family landscape in Austria.
Glottic and Subglottic Injury and Development of Pediatric Airway Stenosis
Authors: Pinzas Lauren A. , Bedwell Joshua R. , Ongkasuwan Julina
Published: May 2022

Objective

To determine how often children with airway injury at the time of tracheostomy develop airway stenosis.

Study Design

A 7‐year retrospective review of a prospectively maintained database of pediatric patients who underwent endotracheal intubation followed by tracheostomy with concurrent and follow‐up direct laryngoscopy.

Setting

Tertiary care hospital.

Methods

Outcomes included glottic or subglottic injury and progression to stenosis. Univariate and multivariate analyses were performed via SPSS.

Results

Of the 222 patients (median age at surgery, 0.6 years; 54% male) who met study criteria, 46% had airway injury at the time of tracheostomy. Patients with congenital cardiovascular disease had 2.33‐times increased risk of developing airway injury (P = .01). Patients with airway injury on initial direct laryngoscopy developed stenosis significantly more frequently than those without injury (30% vs 12%, P < .01). Risks factors for developing stenosis in children with airway injury include prematurity (P = .02), younger age at time of surgery (P < .01), endotracheal tube size (P < .01), Down syndrome (P = .03), and neonatal (P = .02) and/or congenital cardiovascular (P < .01) diagnosis. However, none of these variables were significant on multivariate analysis.

Conclusions

Intubated patients with evidence of glottic or subglottic injury at the time of tracheotomy are more likely to develop airway stenosis than those without. Congenital heart disease was associated with twice the risk of developing airway injury, while progression to stenosis was associated with younger age, prematurity, and/or comorbid diagnoses.
Prognostic value of a novel dNLR-PNI score in patients with acute coronary syndrome undergoing percutaneous coronary intervention
Authors: Fan Wenjun , Liu Yixiang , Zhang Ying , Gao Xiuxin , Shi Fei , Liu Jingyi , Sun Lixian
Published: May 2022

There is currently limited information on the prognostic value of the dNLR-PNI (the combination of the derived neutrophil-to-lymphocyte ratio [dNLR] and prognostic nutritional index [PNI]) score for patients with acute coronary syndrome (ACS). We aimed to explore the predictive value of a dNLR-PNI score on the long-term prognosis of patients with ACS undergoing percutaneous coronary intervention (PCI). A total of 1773 patients with ACS who underwent PCI were consecutively enrolled from January 2016 to December 2018. The cutoff values of dNLR and PNI to predict major adverse cardiovascular events (MACE) were calculated using receiver operating characteristic curves. The patients were divided into three groups based on the dNLR-PNI score, and Kaplan–Meier curves and Cox regression models were used for survival analysis. The endpoints were MACE, including all-cause mortality and rehospitalisation for severe heart failure during follow-up. A total of 1542 patients with ACS who underwent PCI were included. Kaplan–Meier curves showed that a higher level of dNLR, PNI, or dNLR-PNI score was associated with a higher risk of MACE (all p < .001). In multivariate Cox regression models, the dNLR-PNI two score (hazard ratio 3.049, 95% confidence interval 1.503–6.184, p = .002) was found to be an independent predictor of all-cause mortality and rehospitalization for severe heart failure. A high dNLR-PNI score was independently associated with a higher risk of developing MACE in patients with ACS undergoing PCI. The dNLR-PNI score may be a useful prognostic parameter for identifying high-risk ACS patients after PCI.
Duplication of the inferior vena cava: a case series
Authors: Li Wen-rui , Feng Hai , Jin Lei , Chen Xue-ming , Zhang Zhi-wen
Published: May 2022

The inferior vena cava (IVC) may develop abnormally because of its complex embryogenesis. An understanding of congenital variants such as duplication of the IVC is essential for clinical interventions, particularly those performed by surgeons and radiologists. We herein describe five patients who were diagnosed with duplication of the IVC by computed tomography or angiography and summarize their imaging and clinical features. All five patients were men aged 46 to 78 years. Two of the patients had pulmonary embolism and deep vein thrombosis and were treated by placement of an IVC filter and catheter-directed thrombolysis. The IVC in all patients ascended on either side of the abdominal aorta. All left IVCs terminated in the left renal vein, which crossed the aorta and joined the right IVC. The average follow-up time was 29 months (range, 14–46 months), and no patients developed venous thromboembolism or recurrence of thrombosis. Duplication of the IVC can be diagnosed by computed tomography and angiography. Its course and relationship with the renal vein must be identified for accurate planning of IVC filter placement in the setting of deep vein thrombosis and pulmonary embolism.
Automated Vehicles: Use, Share, Own? Young Adults’ Perceptions of Automated Vehicles
Authors: Bagli Hannah , Shay Elizabeth , Combs Tabitha
Published: May 2022

Automated Vehicles (AVs) will change the transportation landscape in still-uncertain ways. The timeline for this change depends not just on the pace of technological advancement, but also on public attitudes about AVs. These attitudes include perceptions of safety and tolerance of new vehicle ownership structures that will likely emerge when and if fully self-driving models are available. This study aims to determine the extent to which young people are open to using AVs and forgoing ownership of conventional personal vehicles in favor of AV-based shared mobility. With the potential for widespread AV deployment in the near term, the perspectives of this age group are important for understanding the impacts of AVs on the mobility landscape. An online survey was distributed through professional networks across the country in early 2020 to gauge comfort levels in riding in AVs, relying on shared mobility, and owning an AV. Univariate and bivariate chi-square tests were performed to test the correlation between explanatory variables and perceptions of AVs. The responses revealed ambivalence toward AVs. Significant relationships indicate that gender identity and urbanicity matter when it comes to willingness to use AVs and shared mobility. Results also show that young adults may not be as ready for AVs as some have hypothesized. The results of this study help address gaps in AV perception research and gauge current attitudes of young adults toward a future of transportation that includes connected and automated vehicles.
Migraine Pathophysiology in Children and Adolescents: A Review of the Literature
Authors: Førland-Schill Astrid , Berring-Uldum Amalie , Debes Nanette Mol
Published: May 2022

Although migraine in adult and pediatric patients are overall very similar to each other, differences in prevalence, presentation, and treatment efficacy may reflect slight differences in the pathophysiological processes underlying migraine in these patient groups, perhaps because of ongoing development of the nervous system during childhood and adolescence. Although major gains have been made in understanding the pathophysiology of migraine in adults in recent years, equivalent research on migraine in pediatric patients continues to lag behind. In this review, we will describe the current state of migraine research in pediatric patients with regard to presentation and frequency of prodromal and postdromal symptoms, ictal and interictal calcitonin gene-related peptide elevation, and evidence for cortical spreading depression, thus covering all phases of migraine, and discuss how the findings seen here may relate to possible underlying pathophysiological mechanisms of migraine. We aim to elucidate possible differences between migraine in children and adults, and the need for further research specific to pediatric patients with migraine in order to improve treatment in this patient group.
Childhood Sexual Abuse and Associated Suicidal Ideation and Attempts Among Gay and Bisexual Men in China: A Moderated Mediation Model
Authors: Xue Shuang , Xu Wenjian
Published: May 2022

Childhood sexual abuse (CSA) is a critical risk factor for suicidal ideation and attempts, especially among gay and bisexual men who experience living as a minority. However, whether internalized homophobia (IH) underlies suicide risk and the role of outness to one’s family in this association warrants investigation to inform preventive interventions. Using a cross-sectional survey of 570 gay and bisexual men in China, we examined the relationship between CSA and suicidality in the Chinese context and tested a moderated mediation model in this relationship. Nearly 65.6% of the participants had experienced suicidal ideation and 36.8% had attempted suicide. Participants with a history of CSA had higher suicidal ideation ( r = 0.33, p < .01) and attempts ( r = 0.48, p < .01). Our bootstrapped mediation analysis showed that IH partially mediated the relationship between CSA and suicidal ideation and attempts. Moreover, outness to one’s family (parents and other family members) strengthened the direct association of CSA and IH, and the indirect relationship between CSA and suicidal ideation and attempts. These findings highlight the significance of identifying risk factors and mechanisms for suicidality among Chinese gay and bisexual men, suggesting the importance of early intervention, especially for those who have experienced CSA, to eliminate their IH and to improve family support for coming out to prevent the onset of suicidal ideation and attempts.
Understanding the Missing and Murdered Indigenous Women Crisis: An Analysis of the NamUs Database
Authors: Hawes Morgan B. , Slakoff Danielle C. , Anguelov Nikolay
Published: May 2022

Within the United States, there is an epidemic of missing and murdered Indigenous women. Using data from the National Missing and Unidentified Persons System (NamUs) repositories on missing and unidentified women, we examined how demographic and regional differences affected case status. Within the NamUs database, we found that American Indian/Alaska Native women are 135% more likely to be listed within the “unidentified remains” cases than women of other races. The results also showed that in states with relatively high urban population densities, women of all races were 250% more likely to be found dead and remain unidentified than women in places with a low urban population. We conclude by discussing three areas in which policy can help bring Indigenous women’s plight back to the fore: (a) in data collection efforts, (b) in increased support for Tribal police, and (c) via the media’s purposeful focus on Indigenous issues.
Building Spiritual Care Competency in Undergraduate Psychiatric Mental Health Nursing Students: A Quality Improvement Project
Authors: Bush Rachel S. , Baliko Beverly , Raynor Phyllis
Published: May 2022

Purpose: The spiritual care of patients is often overlooked in health care as many nurses are unprepared to provide competent, holistic care that addresses patients’ spiritual needs. Since undergraduate academic instruction prepares nurses for practice, innovative strategies that train pre-licensure nurses to care for the spiritual needs of patients are essential. Design: A course needs assessment identified spiritual care as the most deficient competency for undergraduate psychiatric students. A three-phase quality improvement project designed to increase student awareness and practice of spiritual care included (a) development of a quality improvement plan, (b) implementation, and (c) outcome evaluation. Methods: Spiritual care was introduced into the Spring 2020 semester through didactic content and experiential practice. Additionally, an evidence-based spiritual assessment tool (i.e., HOPE questions) was integrated into the course to train students for use in clinical and simulation. Surveys were used to compare the 2019 and 2020 cohorts. Findings: Results showed a statistically significant increase in students’ perception of spiritual care competency after project completion. Conclusions: Future implications include the use of similar methods to improve spiritual care competency for pre-licensure nursing students. Keywords: Spiritual care, undergraduate nurse, spiritual assessment.
Current Marital Status and Epigenetic Clocks Among Older Adults in the United States: Evidence From the Health and Retirement Study
Authors: Yu Yan-Liang
Published: May 2022

Objectives: This study examines how current marital status is associated with epigenetic aging. Methods: Data from the 2016 Health and Retirement Study were used to examine marital status differences in the four epigenetic clocks, that is, GrimAge, DunedinPoAm, PhenoAge, and Zhang ( N = 3765). Weighted ordinary least square regression models were estimated separately for men and women. Results: Remarried, cohabiting, divorced/separated and widowed older adults showed greater epigenetic aging than the continuously married similarly among men and women. Distinct sex difference was observed among the never married. While never-married women exhibited greater epigenetic aging than their continuously married counterparts, older men in lifelong singlehood showed comparable epigenetic aging to their continuously married peers. Discussion: The findings speak to the importance of marital context for epigenetic aging in later life and the biological risk associated with lifelong singlehood for older women in the US.
The role of orthopedic screws threads properties on the success of femoral fracture fixation
Authors: Torabi Masoud , Khorramymehr Siamak , Nikkhoo Mohammad , Rostami Mostafa
Published: May 2022

Stress shielding is created following a reduction in bone density due to the reduction or elimination of mechanical stimuli and the resultant stresses around the implant site in bone tissue. Increased stress shielding can cause the implant or screw to detach or loosen over time, which in turn can lead to severe side effects such as pain, infection, necrosis, and dysfunction. The geometric shape and characteristics of the screws are among the most important factors involved in creating the stress shielding. Hence, the current study aimed to evaluate the influence of bone screw design parameters (i.e., thread profile, thread pitch, screw diameter, and elastic modulus) on stress shielding around the standard screws after implantation in the proximal femur using a viscoelastic finite element modelling. Stress transfer parameters (STP) and strain energy density transfer parameters (SEDTP) were used to evaluate the stress shielding and the risk of screw loosening using the finite element method. This study was performed on screws with titanium and beta-titanium alloy materials as well as HB, HC, and HD ISO threads that are considered as implants for fracture fixation. The results indicated that the HB ISO thread has the least stress shielding and looseness. It was also found that reducing the modulus of elasticity of the screws, increasing the number of threads per screw, reducing the pitch of the screws and the diameter of the screws shaft reduce the amount of the stress shielding and loosening of the screws. This study can provide surgeons with valuable quantitative data for selecting the effective types of screws for bone fracture fixations towards enhanced clinical outcomes.
Review on latest trends in friction-based additive manufacturing techniques
Authors: Venkit Hari , Selvaraj Senthil Kumaran
Published: May 2022

Additive manufacturing comprises layer-by-layer construction of 3D parts using computer controls. This present-day study reveals a list of novel concepts for additive manufacturing, where the addition of material is achieved in solid-state. Materials joined by solid-state techniques exhibits properties beyond those exhibited by material joined by conventional techniques. This has been investigated in both theoretical and experimental manner in length. However, with the development of additive manufacturing techniques, a wide range of possibilities for fabricating complex structures have been identified, which can never be accomplished by conventional techniques. Research on metal-based additive manufacturing has been comparatively less as these products deprive lateral and transverse strength and have issues of anisotropy, making them unfit for structural applications. Moreover, these techniques are not cost-effective. So to overcome these issues, methods incorporating friction into additive manufacturing have been developed. These solid-state techniques use the principle of layer-by-layer deposition. Most of these techniques utilize the principle of selective deposition of materials to form the desired material layer. In this literature review, different advances, approaches, features, and principles of friction-based material joining techniques alongside additive manufacturing are discussed in detail, which recommends new openings for researchers to work in interdisciplinary research to fabricate structures that can exhibit unique properties. This literature portrays an extensive account of the contemporary methods in the fabrication of structures using friction-based additive manufacturing techniques and highlights areas that are worth further research and necessitate a consistent effort on account of the aforementioned disciplines to advance the modernistic technique. Initially, a brief review of different solid-state additive manufacturing techniques is presented, followed by a comprehensive summary of friction stir-based additive manufacturing techniques such as friction assisted seam welding (FASW), additive friction stir (AFS) process, and friction stir additive manufacturing (FSAM) process.
Optimizing the performance of solar panel cooling apparatus by application of response surface methodology
Authors: Singh Vineet , Yadav Vinod Singh
Published: May 2022

The high temperature of the solar photovoltaic module reduced the power output and efficiency of the solar panel. Water cooling is one of the best options for reducing the temperature of solar panels. In this research paper, an experimental setup of solar panel with water cooling arrangements has been developed and optimized. The measured experimental data and data generated by model equations have been optimized by the Response Surface Methodology (RSM) tool in the Design of Experiment. The optimized responses are the efficiency of solar panels, module temperature (MT) of solar panel, and exergetic efficiency. The main input parameters solar flux, water inlet velocity, and atmospheric temperature varied from 600 W/m2 to 1000 W/m2, 0.5 to 0.9 m/s, and 25°C to 45°C, respectively. The best set of input parameters after optimization in RSM is 705 W/m2 solar flux, 0.7263 m/s water inlet velocity, and 32.87°C atmospheric temperature on which the values of responses MT, exergetic efficiency and solar panel efficiency are 48.98 °C, 19.18 %, and 18.88 % respectively. The experimental setup of solar panel cooling has been run on these input parameters setting and responses are validated with the predicted value of the RSM and the previous research. The calculated percentage error in MT is 2.41%, solar panel efficiency is 1.62%, and exergetic efficiency is 3.82%.
Deep meta-learning and variational autoencoder for coupling fault diagnosis of rolling bearing under variable working conditions
Authors: Che Changchang , Wang Huawei , Lin Ruiguan , Ni Xiaomei
Published: May 2022

Considering the characteristics of rolling bearing such as variable working conditions, unbalanced fault sample size, and multiple coupling fault types, it is a great challenge to achieve general accurate fault diagnosis model. In this paper, deep meta-learning and variational autoencoder (DML-VAE) is applied for coupling fault diagnosis of rolling bearing under variable working conditions. The collected vibration signals of rolling bearing are divided into long time series samples, including normal samples, single fault samples, and coupling fault samples. Then, variational autoencoder (VAE) is utilized for data augmentation of time series samples, and the generated samples are brought into one-dimensional deep convolutional neural network (1-DCNN) for further classification of multiple coupling faults. Subsequently, the trained 1-DCNN is regarded as embedding model. Training samples and other working condition samples are defined as support set and query set. Based on metric-based meta-learning method, sample pairs composed of support set and query set are constructed and brought into the embedding model to get the category with shortest metric distance as the classification result. In addition, the embedding model can be optimized by minimizing the contrastive loss among these sample pairs. The case study shows that the DML-VAE can achieve accurate classification results under the coupling of two faults and three faults, and maintain high diagnostic accuracy under variable working conditions. Compared with other models, the proposed model can also get the most accurate fault diagnosis results for all categories under unbalanced samples.
Assessing and prospecting decoupling effect of carbon emissions from economic growth: Empirical studies from Chinese provinces
Authors: Zhang Xinyue , Guo Xiaopeng , Zhang Xingping
Published: May 2022

China has proposed ambitious goals of carbon peak and carbon neutrality, and will pay more attention to the relationship between economic development and carbon emissions. It's significant to assess the current environmental decoupling and prospect the future conditions in China. This article studies the decoupling status and influencing factors in Chinese provinces from 1996 to 2018 through Tapio decoupling index and decomposition model. The results show that most provinces are currently in a weak decoupling state. The growth of per capita GDP and population will affect the process of strong decoupling, while the optimization of energy intensity, energy structure and industrial structure will promote the realization of strong decoupling. Moreover, this paper prospects the decoupling scenarios of Chinese provinces from 2019 to 2035 and finds that all provinces will achieve strong decoupling before 2040, 2035 and 2030 under different carbon emissions scenarios respectively. To achieve the strong decoupling of economic output and carbon emissions as soon as possible, the government must improve energy efficiency, use renewable energy in large quantities, and promote the industrial transformation and upgrading.
Simulation extrapolation method for measurement error: A review
Authors: Sevilimedu Varadan , Yu Lili
Published: May 2022

Measurement error is pervasive in statistics due to the non-availability of authentic data. The reasons for measurement error mainly relate to cost, convenience, and human error. Measurement error can result in non-negligible bias due to attenuated estimates, reduced power of statistical tests, and lower coverage probabilities of the coefficient estimators in a regression model. Several methods have been proposed to correct for measurement error, all of which can be grouped into two broad categories based on the underlying model—functional and structural. Functional models provide flexibility and robustness to estimators by placing minimal or no assumptions on the distribution of the mismeasured covariate or by treating them as a fixed entity, as opposed to a structural model which treats the underlying mismeasured covariates as random with a specified structure. The simulation extrapolation method is one method that is used for the partial correction of measurement error in both structural and functional models. Reviews of measurement error correction techniques are available in the literature. However, none of the previously conducted reviews has exclusively focused on simulation extrapolation and its application in continuous measurement error models, despite its widespread use and ease of application. We attempt to close this gap in the literature by highlighting its development over the past two and a half decades.
Experimental study on magnetorheological polishing fluids composition in reciprocating magnetorheological polishing
Authors: Wang Rensheng , Sun Cong , Xiu Shichao , Li Shanshan , Li Bo , Liang Dongming
Published: May 2022

As the main factor of magnetorheological polishing (MRP), the magnetorheological polishing fluids (MRP fluids) directly affect the machining results of the workpiece surface. In this study, the preparation and performance test of MRP fluids are carried out. It is to evaluate the polishing effects of the workpiece by experimental design of the prepared MRP fluids composition, that is, the concentration of carbonyl iron particles (CIPs), the concentration of cerium oxide (CeO2), and the size of cerium oxide (CeO2) using reciprocating polishing method and establish regression equation models. Further, the optimum MRP fluids composition parameters are obtained by the optimization of regression models of the ΔRa and MRR, and the correctness of optimization results of regression models is validated by experimental verification. The results show that the ΔRa and MRR of the workpiece are affected by the MRP fluids composition parameters. The optimum MRP fluids composition parameters are found at 40 vol.% concentration of CIPs, 5 vol.% concentration of CeO2, and 7000 mesh size of CeO2. The experimental results of the ΔRa and MRR are deviated by 4.95% and 4.17% from the response results respectively by experimental verification.