bluuebunny/crossref_metadata_2025 huggingface dataset:
Variability of Nutritional, Antioxidant, and Textural Traits of a Collection of Snap Beans of Different Colors
Authors: Menga Valeria , Fares Clara , Campa Ana , Ferreira Juan Jose , Bitocchi Elena , Papa Roberto , Beleggia Romina
Published: February 2023

A set of 54 snap bean lines grown under organic farming was characterized for different traits: pod color, pod cross-section shape, pod section width (PSW), protein content (PC), and sugar content (S). After cooking, the lines were analyzed for firmness and color parameters (CIE-L*, a*, b*). The snap bean lines were grouped based on pod cross-section shape and pod color into eight groups, and significant differences were observed among lines and groups for all the traits investigated. In particular, the yellow pods were harder than the other snap beans and less sweet due to the negative correlation between firmness and sugar content. Fourteen selected lines with contrasting firmness and belonging to different color groups were investigated for their phenolic composition and antioxidant activity (TEAC) before and after domestic cooking. A general decrease was observed only for vanillic acid, quercetin, and apigenin-8-C-glucoside. Quercetin-3-O-rutinoside and kaempferol-3-O-rutinoside were detected in all samples with the highest values in the SBP042 line in both raw and cooked samples. Antioxidant activity decreased with cooking (average of 39%), but purple line SBP053 showed the lowest and no significant loss (3.1%). The results reported in this study could be useful to design specific varieties for different markets and purposes.
Pre- and Post-Harvest Infection of Pasteurized Pickles with Fungi and Their Pectinolytic Potential to Soften the Product
Authors: Kersten Anne-Katrin , Scharf Sabrina , Jendro Anna , Meurer Peter , Büttner Carmen , Lentzsch Peter
Published: February 2023

Fungi and their enzymes have long been thought to cause the softening of pasteurized gherkins; however, the exact fungal species and timing of contamination are unknown. Ready-to-sell pickle jars and blossoms of growing gherkins were inoculated with DNA-sequenced fungi isolated from rotting gherkins to cause softening at various stages of production. Ready-to-sell gherkins inoculated with Fusarium oxysporum, Fusarium equiseti, Galactomyces geotrichum, Mucor circinelloides, Mucor hiemalis, Mucor fragilis, Plectosphaerella cucumerina, Alternaria sp., and Cladosporium sp. indicated a measurable texture reduction after pasteurization and 6 months of storage at room temperature. No texture changes were observed in gherkins infected during the growth phase. The fungi M. hiemalis, M. fragilis, and G. geotrichum tolerated the acidic-saline (approx. pH 4) environment in the jar for several days, thus the pectinolytic enzymes of these candidates were tested for heat and pH resistance. Although the measured endo-Polygalacturonase (PG) of M. fragilis had its optimum activity at pH < 4, all fungal enzymes were inactivated within 3 min at 80 °C corresponding to the pasteurization heat. Our study shows that conventionally occurring fungi and their enzymes have the potential to induce softening in pickles. Softening by these fungi is unlikely due to post- or pre-harvest contamination without any other influences.
Advances in the Strategic Approaches of Pre- and Post-Harvest Treatment Technologies for Peach Fruits (Prunus persica)
Authors: Shin Jin Song , Park Han Sol , Lee Ki Won , Song Ji Seop , Han Hea Yeon , Kim Hye Won , Cho Tae Jin
Published: February 2023

Peach (Prunus persica) is one of the representative climacteric fruits susceptible to environmental stresses, including microbial contamination. This article analyzed major findings from the literature on pre- and post-harvest technologies for maintaining the quality of peach fruit to figure out the strengths and limitations of each treatment strategy. The key implication from studies of pre-harvest agents directly applied to the fruit surface or supplemented as fertilizer was the application of a mixture regarding substances with diverse working mechanisms to prevent excessive use of the agent. The common objectives of previous research on pre-harvest treatments were not only the improvement in the quality of harvested fruit but also the storability during long-term refrigeration due to the short lifespan of peaches. In the case of post-harvest treatments, the efficacy was considerably affected by various determinant factors (e.g., a cultivar of fruit, the sort of technologies, and storage environments), and thus operating conditions optimized for peach fruit were described in this article. Whereas, although the combined treatment of technologies categorized into principles (physical, chemical, and biological approaches) has been adopted to achieve the synergistic effect, undesirable antagonistic effects (i.e., the inhibition of efficacies expectable from singular treatments) were also reported to highlight the importance for exploring adequate treatment conditions.
Probabilistic Approach to Tank Design in Rainwater Harvesting Systems
Authors: Di Chiano Maria Gloria , Marchioni Mariana , Raimondi Anita , Sanfilippo Umberto , Becciu Gianfranco
Published: February 2023

Storage tanks from rainwater harvesting systems (RWHs) are designed to provide flow equalization between rainfall and water demand. The minimum storage capacity required to take into account the maximum variations of stored water volumes, i.e., the active storage, depends basically on the magnitude and the variability of rainfall profiles and the size of the demand. Given the random nature of the variables involved in the hydrological process, probability theory is a suitable technique for active storage estimation. This research proposes a probabilistic approach to determine an analytical expression for the cumulative distribution function (CDF) of the active storage as a function of rainfall moments, water demand and the mean number of consecutive storm events in a deficit sub-period. The equation can be used by developers to decide on the storage capacity required at a desired non-exceedance probability and under a preset water demand. The model is validated through a continuous simulation of the tank behavior using rainfall time series from Milan (Northern Italy).
Reconstruction of Recharge and Discharge Pattern in the Polder Drainage Canal Network
Authors: Gilja Gordon , Kuspilić Neven , Lacko Martina , Romić Davor
Published: February 2023

Rainfed agriculture is dependent on rainfall and runoff patterns, especially in lowland areas that rely on pumping operation to remove excess water from the drainage network. Polder areas are extremely vulnerable to saltwater intrusion and subsequent soil salinization driven by rising sea levels and accelerated by climate change. The aim of this paper is to reconstruct the recharge and discharge pattern in the Vidrice polder, a drainage canal network within the Neretva River Delta agroecosystem used to collect the surface and subsurface runoff from the agricultural land and saltwater infiltration through the aquifer. Water regime data are collected over an 18-month period of real-time monitoring at 15 min intervals on three stations along the primary drainage canal and one station at the secondary canal. Analysis of water level flashiness in the Vidrice polder using the Richards-Baker flashiness index (R-Bindex) indicates that daily pumping of water infiltrated in the canal network is sub-optimal: discharge fluctuates significantly more than recharge, by 46% on average, resulting in unnecessary lowering of the water level in the drainage network. The results show that the correlation between the intensive rainfall events (>10 mm/day) and the recharge rates can be used to modify the daily pumping operation and maintain high freshwater levels in the canal network to increase the resistance to infiltration and reduce saltwater intrusion into the polder.
Effectiveness and Student Perceptions of Haptic Virtual Reality Simulation Training as an Instructional Tool in Pre-Clinical Paediatric Dentistry: A Pilot Pedagogical Study
Authors: Philip Nebu , Ali Kamran , Duggal Monty , Daas Hanin , Nazzal Hani
Published: February 2023

Simulation training for invasive dental procedures is a core component of the pre-clinical dental curriculum. Besides conventional mannequin-based simulators, dental schools are now incorporating haptic virtual reality simulation (HVRS) devices to facilitate the transition of students from the simulated dental learning environment to the clinical settings. This study aimed to assess student performance and perceptions of HVRS training as a pedagogical tool in pre-clinical paediatric dentistry. After practicing the primary molar pulpotomy procedure on plastic teeth, participants were randomized into test and control groups. Test group students performed the same procedure on a HVRS device, namely the SIMtoCARE Dente®. Subsequently, both the test and control group students attended another conventional pulpotomy simulation session where the quality of their access outline and pulp chamber deroofing steps were evaluated on plastic teeth. After the control group students also experienced the HVRS, all study participants completed a perception questionnaire on their experience. No significant differences were found between the study and control group students for the quantitative parameters assessed. Although the students regarded HVRS to be a useful adjunct to support their pre-clinical training, an overwhelming majority of the students did not consider HVRS to be a replacement for conventional pre-clinical simulation training.
Changes in Community-Dwelling Elderly’s Activity and Participation Affecting Depression during COVID-19 Pandemic: A Cross-Sectional Study
Authors: Tanikaga Miki , Uemura Jun-ichi , Hori Fumiko , Hamada Tomomi , Tanaka Masahiro
Published: February 2023

We determined the changes in the activity or participation of the community-dwelling elderly in Japan during the COVID-19 pandemic and identified the activities leading to depression. This will allow us to evaluate rehabilitation interventions that can be used to minimize or eliminate the negative impact of COVID-19 on today’s community-dwelling elderly. Herein, demographics, activity or participation (Activity Card Sort-Japan version: ACS-JPN), the number of social networks (Lubben Social Network Scale: LSNS), and depression (Geriatric Depression Scale: GDS) were examined in 74 community-dwelling elderly in Japan from August to October 2020. A statistical analysis was conducted to determine the effect of demographics on GDS, LSNS, and ACS-JPN, to compare the activity retention rates of the four domains using ACS-JPN, and to extract the activities that might affect depression using a generalized linear model. The results show that the retention of leisure activity with a high physical demand (H-leisure) and sociocultural activities was significantly lower than instrumental activities of daily living and leisure activity with a low physical demand (L-leisure). L-leisure and the number of social networks were possible risk factors for depression during the pandemic. This study highlighted the importance of maintaining the number of L-leisure and social networks at home to prevent depression in community-dwelling elderly when they could not perform outdoor activities and direct interpersonal interaction.
Can Environmental Information Disclosure Enhance Firm Value?—An Analysis Based on Textual Characteristics of Annual Reports
Authors: Cai Rongjiang , Lv Tao , Wang Cheng , Liu Nana
Published: February 2023

This study examines the impact of environmental information disclosure quality on firm value for Chinese listed companies in heavily polluting industries from 2010 to 2021. By controlling for the level of leverage, growth, and corporate governance, a fixed effects model is constructed to test this relationship. Furthermore, this study analyzes the moderating effects of annual report text features, such as length, similarity, and readability, on the relationship between environmental information disclosure and firm value and the heterogeneous impact of firm ownership on this relationship. The main findings of this study are as follows: There is a positive correlation between the level of environmental information disclosure and firm value for Chinese listed companies in heavily polluting industries. Annual report text length and readability positively moderate the relationship between environmental information disclosure and firm value. Annual report text similarity negatively moderates the relationship between environmental information disclosure and firm value performance. Compared with state-owned enterprises, the impact of environmental information disclosure quality on the firm value of no-state-owned enterprises is more significant.
Mental Health Disorders and Coping Strategies in Healthcare Workers during the COVID-19 Pandemic: An Analytical Cross-Sectional Study in Southeastern Mexico
Authors: Granados Villalpando Jesús Maximiliano , Baeza Flores Guadalupe del Carmen , Ble Castillo Jorge Luis , Celorio Méndez Karla del Socorro , Juárez Rojop Isela Esther , Morales Contreras José Antonio , Olvera Hernández Viridiana , Quiroz Gómez Sergio , Romero Tapia Sergio de Jesús , Ruíz Quiñones Jesús Arturo , Guzmán Priego Crystell Guadalupe
Published: February 2023

Mental health disorders are relatively common in the general population and were already an important issue for the healthcare sector before COVID-19. COVID-19, being a worldwide crucial event and evidently a great stressor has increased both the prevalence and incidence of these. Therefore, it is evident that COVID-19 and mental health disorders are closely related. Moreover, several coping strategies exist to endure said disorders such as depression and anxiety, which are used by the population to confront stressors, and healthcare workers are not the exception. This was an analytical cross-sectional study, conducted from August to November 2022, via an online survey. Prevalence and severity of depression, anxiety, and stress were assessed via the DASS-21 test, and coping strategies were assessed via the CSSHW test. The sample consisted of 256 healthcare workers and of those, 133 (52%) were males with a mean age of 40.4 ± 10.35, and 123 (48%) were females with a mean age of 37.28 ± 9.33. Depression was prevalent in 43%, anxiety in 48%, and stress in 29.7%. Comorbidities were a significant risk factor for both depression and anxiety with an OR of 10.9 and 4.18, respectively. The psychiatric background was a risk factor for depression with an OR of 2.17, anxiety with an OR of 2.43, and stress with an OR of 3.58. The age difference was an important factor in the development of depression and anxiety. The maladaptive coping mechanism was prevalent in 90 subjects and was a risk factor for depression (OR of 2.94), anxiety (OR of 4.46) and stress (OR of 3.68). The resolution coping mechanism was a protective factor for depression (OR of 0.35), anxiety (OR of 0.22), and stress (OR of 0.52). This study shows that mental health disorders are highly prevalent among healthcare workers in Mexico and that coping strategies are associated with their prevalence. It also implies that not only occupations, age, and comorbidities might affect mental health, but also the way patients confront reality and the behavior and decisions they take towards stressors.
Optimal Network of General Hospitals in Slovenia
Authors: Blatnik Patricia , Bojnec Štefan
Published: February 2023

This article explores how the minimum number of general hospital locations can be determined with optimal population coverage. Due to the increasing financial problems of hospitals and the poor organization of general hospital healthcare, Slovenia is currently working to reform the healthcare system. Defining the optimal network of hospital providers is one of the key elements in reforming the healthcare system. To define the optimal network of general hospitals, the allocation-location model was used, and the maximize attendance model was used as the central method. The chief purpose of maximize attendance model is to optimize the demand attendance with respect to distance and time spent getting to the point of demand. In the analysis of optimal locations and the number of Slovenian general hospitals, we used data on the locations of settlements with their number of inhabitants and data on the Slovenian road network, based on which we defined average travel speeds on the categorized road network. The hypothetical locations of general hospitals and the number of optimally located general hospitals that provide access to the nearest provider were determined in three different time intervals. We found that the same accessibility to hospital services as provided by the existing network of general hospitals can be achieved with only ten optimally located general hospitals within a 30-min time interval. This means that two general hospitals could be rationalized or reorganized, which would bring significant savings in the field of hospital activity, which creates a large loss in the health system in Slovenia.
Heart Rate from Progressive Volitional Cycling Test Is Associated with Endothelial Dysfunction Outcomes in Hypertensive Chilean Adults
Authors: Alvarez Cristian , Tuesta Marcelo , Reyes Álvaro , Guede-Rojas Francisco , Peñailillo Luis , Cigarroa Igor , Vásquez-Gómez Jaime , Cano-Montoya Johnattan , Durán-Marín Cristóbal , Rojas-Paz Oscar , Márquez Héctor , Izquierdo Mikel , Delgado-Floody Pedro
Published: February 2023

Background: A progressive volitional cycling test is useful in determining exercise prescription in populations with cardiovascular and metabolic diseases. However, little is known about the association between heart rate during this test and endothelial dysfunction (EDys) parameters in hypertensive (HTN) patients. Objective: To investigate the association between EDys markers (flow-mediated dilation [FMD], pulse wave velocity of the brachial artery [PWVba], and carotid-intima media thickness [cIMT]) and heart rate during a cycling test in HTN adults. A secondary aim was to characterize cardiovascular, anthropometric, and body composition outcomes in this population. Methods: This was a descriptive clinical study in which adults (men and women) were assigned to one of three groups: HTN, elevated blood pressure (Ele), or a normotensive control group (CG), and completed a progressive cycling test. The primary outcomes were FMD, PWVba, cIMT, and heart rate (HR) at 25–50 watts (HR25–50), 50–100 watts (HR50–100), and 75–150 watts (HR75–150) of the Astrand test. Secondary outcomes included body mass index (BMI), waist circumference, body fat percentage (BF%), skeletal muscle mass (SMM), resting metabolic rate (RMR), and estimated body age, as measured by a bio-impedance digital scale. Results: Analyses of the associations between FMD, PWV, and HR25–50, HR50–100, and HR75–150 watts revealed no significant association in the HTN, Ele, and CG groups. However, a significant association was found between cIMT and HR75–150 watts in the HTN group (R2 47.1, β −0.650, p = 0.038). There was also a significant trend (p = 0.047) towards increasing PWVba in the CG, Ele, and HTN groups. Conclusion: Heart rate during a progressive cycling test is associated with the EDys parameters cIMT in HTN patients, with particularly strong predictive capacity for vascular parameters in the second and third stages of the Astrand exercise test compared to normotensive control.
Exploring Factors Affecting Urban Park Use from a Geospatial Perspective: A Big Data Study in Fuzhou, China
Authors: Zeng Liguo , Liu Chunqing
Published: February 2023

Promoting research on urban park use is important for developing the ecological and environmental health benefits of parks. This study proposes uniquely integrated methods combined with big data to measure urban park use. It combines comprehensive geographic detectors and multiscale geographically weighted regression from a geospatial perspective to quantify the individual and interactive effects of the parks’ characteristics, accessibility, and surrounding environment features on weekday and weekend park use. The study also explores the degree of influence of spatial changes. The results indicate that the park-surrounding facilities and services factor contributed most to use, while its interaction effect with park service capacity had the greatest impact on park use. The interaction effects showed binary or nonlinear enhancement. This suggests that park use should be promoted within multiple dimensions. Many influencing factors had significant changes in the geographic space, suggesting that city-level park zoning construction should be adopted. Finally, park use was found to be affected by users’ subjective preference on weekends and convenience factors on weekdays. These findings provide a theoretical basis for the influencing mechanisms of urban park use, which can help urban planners and policymakers formulate more specific policies to successfully manage and plan urban parks.
Enhancing the Breast Histopathology Image Analysis for Cancer Detection Using Variational Autoencoder
Authors: Guleria Harsh Vardhan , Luqmani Ali Mazhar , Kothari Harsh Devendra , Phukan Priyanshu , Patil Shruti , Pareek Preksha , Kotecha Ketan , Abraham Ajith , Gabralla Lubna Abdelkareim
Published: February 2023

A breast tissue biopsy is performed to identify the nature of a tumour, as it can be either cancerous or benign. The first implementations involved the use of machine learning algorithms. Random Forest and Support Vector Machine (SVM) were used to classify the input histopathological images into whether they were cancerous or non-cancerous. The implementations continued to provide promising results, and then Artificial Neural Networks (ANNs) were applied for this purpose. We propose an approach for reconstructing the images using a Variational Autoencoder (VAE) and the Denoising Variational Autoencoder (DVAE) and then use a Convolutional Neural Network (CNN) model. Afterwards, we predicted whether the input image was cancerous or non-cancerous. Our implementation provides predictions with 73% accuracy, which is greater than the results produced by our custom-built CNN on our dataset. The proposed architecture will prove to be a new field of research and a new area to be explored in the field of computer vision using CNN and Generative Modelling since it incorporates reconstructions of the original input images and provides predictions on them thereafter.
The Effect of Design Rainfall Patterns on Urban Flooding Based on the Chicago Method
Authors: Chen Jian , Li Yaowei , Zhang Changhui
Published: February 2023

Design rainfall is the basis for deriving design floods in areas where rainfall data are lacking and has a significant impact on the construction of water engineering facilities and municipal engineering designs. The Chicago rainfall pattern method has great applicability for urban short-duration design rainfall. In order to analyze the influence of design storm rainfall patterns on urban flooding, numerical models of hydrological and hydrodynamic processes were applied to simulate design rainfall with different recurrence periods and different rain peaks and were also used to compare and analyze the total amount of water accumulation and inundation extent by taking the central city of Zhoukou as an example. The results show that when the design rainfall recurrence period is less than 20 years, the total volume and inundation extent of waterlogging in design rainfall with a smaller peak ratio is larger. When the return period is greater than 20 years, the pattern is reversed. However, as the return period grows, the difference in peak inundation volume due to different peak rainfall amounts decreases. This study has certain guiding significance for urban flood forecasting and early warning efforts.
Facet Dependence of Biosynthesis of Vivianite from Iron Oxides by Geobacter sulfurreducens
Authors: Luo Xiaoshan , Wen Liumei , Zhou Lihua , Yuan Yong
Published: February 2023

Vivianite plays an important role in alleviating the phosphorus crisis and phosphorus pollution. The dissimilatory iron reduction has been found to trigger the biosynthesis of vivianite in soil environments, but the mechanism behind this remains largely unexplored. Herein, by regulating the crystal surfaces of iron oxides, we explored the influence of different crystal surface structures on the synthesis of vivianite driven by microbial dissimilatory iron reduction. The results showed that different crystal faces significantly affect the reduction and dissolution of iron oxides by microorganisms and the subsequent formation of vivianite. In general, goethite is more easily reduced by Geobacter sulfurreducens than hematite. Compared with Hem_{100} and Goe_L{110}, Hem_{001} and Goe_H{110} have higher initial reduction rates (approximately 2.25 and 1.5 times, respectively) and final Fe(II) content (approximately 1.56 and 1.20 times, respectively). In addition, in the presence of sufficient PO43−, Fe(II) combined to produce phosphorus crystal products. The final phosphorus recoveries of Hem_{001} and Goe_H{110} systems were about 5.2 and 13.6%, which were 1.3 and 1.6 times of those of Hem_{100} and Goe_L{110}, respectively. Material characterization analyses indicated that these phosphorous crystal products are vivianite and that different iron oxide crystal surfaces significantly affected the size of the vivianite crystals. This study demonstrates that different crystal faces can affect the biological reduction dissolution of iron oxides and the secondary biological mineralization process driven by dissimilatory iron reduction.
How to Evaluate Green Development Policy Based on the PMC Index Model: Evidence from China
Authors: Ma Xiang-Fei , Ruan Yi-Fan
Published: February 2023

Implementing green development is important to realizing a harmonious relationship between humans and nature, and has attracted the attention of governments all over the world. This paper uses the PMC (Policy Modeling Consistency) model to make a quantitative evaluation of 21 representative green development policies issued by the Chinese government. The research finds: firstly, the overall evaluation grade of green development is good and the average PMC index of China’s 21 green development policies is 6.59. Second, the evaluation of 21 green development policies can be divided into four different grades. Most grades of the 21 policies are excellent and good; the values of five first-level indicators about policy nature, policy function, content evaluation, social welfare, and policy object are high, which indicates that the 21 green development policies in this paper are relatively comprehensive and complete. Third, most green development policies are feasible. In twenty-one green development policies, there are: one perfect-grade policy, eight excellent-grade policies, ten good-grade policies, and two bad-grade policies. Fourthly, this paper analyzes the advantages and disadvantages of policies in different evaluation grades by drawing four PMC surface graphs. Finally, based on the research findings, this paper puts forward suggestions to optimize the green development policy-making of China.
“We’re Not Going to Be as Prepared”: A Qualitative Study of Healthcare Trainees’ Experiences after One Year of the COVID-19 Pandemic
Authors: Blake Holly , Brewer Alex , Chouliara Niki
Published: February 2023

The COVID-19 pandemic had significant impacts on the mental health and academic experiences of healthcare trainees. Building on findings from earlier in the pandemic, we explore the impacts on healthcare trainees after a sustained pandemic period of 12–14 months, involving multiple lockdowns, changes in government COVID-19 regulations and the delivery of health education. A qualitative study was conducted between March–May 2021. Participants were 12 healthcare trainees (10 women, 2 men) of medicine, nursing, and midwifery, registered at one of three higher education institutions in the United Kingdom. Interviews were fully transcribed, and data were thematically analysed using a combination of deductive and inductive approaches. We identified three key themes with eight subthemes: (i) academic experiences (adjustment to online learning, loss of clinical experience, confidence in the university), (ii) impacts on wellbeing (psychosocial impacts, physical impacts, pandemic duration and multiple lockdowns), and (iii) support frameworks (university preparedness for increased student support needs, importance of relationship with academic tutors). Findings shed light on the long-lasting and emerging impacts of the pandemic over time. We identify support needs for trainees both during their academic studies, and as they move forwards into professional roles within the healthcare workforce. Recommendations are made for higher education institutions and healthcare employers.
Comparative Analysis of the Implementation of Support Vector Machines and Long Short-Term Memory Artificial Neural Networks in Municipal Solid Waste Management Models in Megacities
Authors: Solano Meza Johanna Karina , Orjuela Yepes David , Rodrigo-Ilarri Javier , Rodrigo-Clavero María-Elena
Published: February 2023

The development of methodologies to support decision-making in municipal solid waste (MSW) management processes is of great interest for municipal administrations. Artificial intelligence (AI) techniques provide multiple tools for designing algorithms to objectively analyze data while creating highly precise models. Support vector machines and neuronal networks are formed by AI applications offering optimization solutions at different managing stages. In this paper, an implementation and comparison of the results obtained by two AI methods on a solid waste management problem is shown. Support vector machine (SVM) and long short-term memory (LSTM) network techniques have been used. The implementation of LSTM took into account different configurations, temporal filtering and annual calculations of solid waste collection periods. Results show that the SVM method properly fits selected data and yields consistent regression curves, even with very limited training data, leading to more accurate results than those obtained by the LSTM method.
The Perceptions and Use of Urban Neighborhood Parks Since the Outbreak of COVID-19: A Case Study in South Korea
Authors: Lee Jiku , Chon Jinhyung , Park Yujin , Lee Junga
Published: February 2023

As the COVID-19 pandemic continues, the stress of city dwellers is increasing, and some adapt to the pandemic by pursuing physical and psychological well-being in neighborhood parks. To improve the resilience of the social-ecological system against COVID-19, it is important to understand the mechanism of adaptation by examining the perception and use of neighborhood parks. The purpose of this study is to investigate users’ perceptions and use of urban neighborhood parks since the outbreak of COVID-19 in South Korea using systems thinking. To verify the hypotheses about the relationship between variables involved in COVID-19 adaptive feedback, two research objectives were set. First, this study determined the causal structure leading to park visits using systems thinking. Second, the relationship between stress, motivation, and the frequency of visits to neighborhood parks was empirically verified. To conduct the research, the system of use and perceptions of parks were analyzed through a causal loop diagram to determine the feedback between psychological variables. Then, a survey was conducted to verify the relationship between stress, motivation for visits, and visit frequency, which are the major variables derived from the causal structure. A total of three feedback loops were derived in the first step, including a loop in which COVID-19 stress was relieved by visits to parks and a loop in which COVID-19 stress worsened due to crowding in parks. Finally, the relationship of stress leading to park visits was confirmed, and the empirical analysis showed that anger about contagion and social disconnection were linked as motives for park visits, and that park visits were mainly motivated by the desire to go out. The neighborhood park functions as an adaptive space for the stress of COVID-19 and will maintain its role as social distancing becomes more important to various socio-ecological changes. The strategies driven by the pandemic can be adapted in park planning to recover from stress and improve resilience.
Trajectories of Social Participation and Its Predictors in Older Adults: Based on the CLHLS Cohorts from 2002 to 2018
Authors: Zhang Chi , Zhao Yinan , Chen Xi , Li Xiaoyang , Liu Qingcai , Peng Ruotong , Chen Yifei , Feng Hui
Published: February 2023

Social participation is a key factor in achieving active aging. This study aimed to explore the trajectories and predictors of social participation changes among older adults in China. The data used in this study are from the ongoing national longitudinal study CLHLS. A total of 2492 older adults from the cohort study were included. Group-based trajectory models (GBTM) were used to identify potential heterogeneity in longitudinal changes over time and investigate associations between baseline predictors and trajectories for different cohort members using logistic regression. Four different trajectories of social participation were reported in older adults, namely, stable (8.9%), slow decline (15.7%), lower score with decline (42.2%), and higher score with decline (9.5%). On multivariate analyses, age, years of schooling, pension, mental health, cognitive function, instrumental activities of daily living, and initial social participation scores significantly impact the rate of change in social participation over time. Four trajectories of social participation were identified in the Chinese elderly population. Management of mental health, physical function, and cognitive function appear to be important in maintaining the long-term social participation of older people in the community. Early identification of factors influencing the rapid decline in social participation and timely interventions can maintain or improve social participation levels in older adults.
Comprehensible Machine-Learning-Based Models for the Pre-Emptive Diagnosis of Multiple Sclerosis Using Clinical Data: A Retrospective Study in the Eastern Province of Saudi Arabia
Authors: Olatunji Sunday O. , Alsheikh Nawal , Alnajrani Lujain , Alanazy Alhatoon , Almusairii Meshael , Alshammasi Salam , Alansari Aisha , Zaghdoud Rim , Alahmadi Alaa , Basheer Ahmed Mohammed Imran , Ahmed Mohammed Salih , Alhiyafi Jamal
Published: February 2023

Multiple Sclerosis (MS) is characterized by chronic deterioration of the nervous system, mainly the brain and the spinal cord. An individual with MS develops the condition when the immune system begins attacking nerve fibers and the myelin sheathing that covers them, affecting the communication between the brain and the rest of the body and eventually causing permanent damage to the nerve. Patients with MS (pwMS) might experience different symptoms depending on which nerve was damaged and how much damage it has sustained. Currently, there is no cure for MS; however, there are clinical guidelines that help control the disease and its accompanying symptoms. Additionally, no specific laboratory biomarker can precisely identify the presence of MS, leaving specialists with a differential diagnosis that relies on ruling out other possible diseases with similar symptoms. Since the emergence of Machine Learning (ML) in the healthcare industry, it has become an effective tool for uncovering hidden patterns that aid in diagnosing several ailments. Several studies have been conducted to diagnose MS using ML and Deep Learning (DL) models trained using MRI images, achieving promising results. However, complex and expensive diagnostic tools are needed to collect and examine imaging data. Thus, the intention of this study is to implement a cost-effective, clinical data-driven model that is capable of diagnosing pwMS. The dataset was obtained from King Fahad Specialty Hospital (KFSH) in Dammam, Saudi Arabia. Several ML algorithms were compared, namely Support Vector Machine (SVM), Decision Tree (DT), Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Adaptive Boosting (AdaBoost), and Extra Trees (ET). The results indicated that the ET model outpaced the rest with an accuracy of 94.74%, recall of 97.26%, and precision of 94.67%.
Integrative Study on Flow Characteristics and Impact of Non-Submerged Double Spur Dikes on the River System
Authors: Gu Zhenghua , Cao Xiaomeng , Cao Minxiong , Lu Weizhen
Published: February 2023

The flow characteristics around non-submerged spur dikes continuously placed in the channel on the same side with orthogonal angle to the wall were investigated by numerical simulations and experimental measurements. Three-dimensional (3D) numerical simulations with the standard k−ε Model for incompressible viscous flow based on finite volume method and the rigid lid assumption for free surface treatment were conducted. A laboratory experiment was applied to verify the numerical simulation. The experimental data indicated that the developed mathematical model can effectively predict 3D flow around non-submerged double spur dikes (NDSDs). The flow structure and turbulent characteristics around them were analyzed and it was found that a distinct cumulative effect of turbulence exists between the dikes. By examining the interaction rules of NDSDs, the judgment criterion of spacing threshold was generalized as whether velocity distributions at the cross-sections of NDSDs along the main flow approximately coincided or not. It can be used to investigate the impact scale of the spur dike groups on the straight and prismatic channels and it is of great significance for artificial scientific river improvement and the assessment of river system health under human activities.
Discovering Geographical Flock Patterns of CO2 Emissions in China Using Trajectory Mining Techniques
Authors: Zhang Pengdong , Miao Lizhi , Wang Fei , Li Xinting
Published: February 2023

Carbon dioxide (CO2) emissions are considered a significant factor that results in climate change. To better support the formulation of effective policies to reduce CO2 emissions, specific types of important emission patterns need to be considered. Motivated by the flock pattern that exists in the domain of moving object trajectories, this paper extends this concept to a geographical flock pattern and aims to discover such patterns that might exist in CO2 emission data. To achieve this, a spatiotemporal graph (STG)-based approach is proposed. Three main parts are involved in the proposed approach: generating attribute trajectories from CO2 emission data, generating STGs from attribute trajectories, and discovering specific types of geographical flock patterns. Generally, eight different types of geographical flock patterns are derived based on two criteria, i.e., the high–low attribute values criterion and the extreme number–duration values criterion. A case study is conducted based on the CO2 emission data in China on two levels: the province level and the geographical region level. The results demonstrate the effectiveness of the proposed approach in discovering geographical flock patterns of CO2 emissions and provide potential suggestions and insights to assist policy making and the coordinated control of carbon emissions.
The Influence of Foreign Direct Investment on Physical Health of Rural-Urban Migrants—Empirical Evidence from China Migrants Dynamic Survey
Authors: Han Guixin , Liu Pengcheng , Zhao Yihang , Liang Yinyin , Wang Xiaojie
Published: February 2023

The purpose of this study is to explore the influence of Foreign Direct Investment (FDI) on rural-urban migrants’ physical health and its influencing mechanism. A total of 134,920 rural-urban migrant samples are matched based on the China Migrants Dynamic Survey in 2017 and the China Urban Statistical Yearbook in 2016. On the basis of the samples, a Binary Probit Model is used to explore the relationship between the degree of FDI and rural-urban migrants’ physical health. The results show that compared with migrants who lived in cities with a lower FDI level, rural-urban migrants who lived in cities with a higher FDI level are better in physical health. The results of the mediation effect model show that the degree of FDI has a significant positive impact on employment rights and benefits the protection of rural-urban migrants, improving rural-urban migrants’ physical health, which means employment rights and benefits protection plays an intermediary role in the process of FDI affecting rural-urban migrants’ physical health. Therefore, when formulating public policies such as plans to improve the physical health of rural-urban migrants, not only the availability of medical services for rural-urban migrants needs to be improved, but the positive spillover effect of FDI should be taken into account. By doing so, FDI can positively affect the physical health of rural-urban migrants.
Examination of the Cumulative Risk Assessment and Nutritional Profiles among College Ballet Dancers
Authors: Moore Kenya , Uriegas Nancy A. , Pia Jessica , Emerson Dawn M. , Pritchett Kelly , Torres-McGehee Toni M.
Published: February 2023

This study examined female collegiate ballet dancers’ (n = 28) Female Athlete Triad (Triad) risk via the Cumulative Risk Assessment (CRA) and nutritional profiles (macro- and micronutrients; n = 26). The CRA identified Triad return to play criteria (RTP: Full Clearance, Provisional Clearance, or Restricted/Medical Disqualified) by assessing eating disorder risk, low energy availability, menstrual cycle dysfunction, and low bone mineral density. Seven-day dietary assessments identified any energy imbalances of macro- and micronutrients. Ballet dancers were identified as low, within normal, or high for each of the 19 nutrients assessed. Basic descriptive statistics assessed CRA risk classification and dietary macro- and micronutrient levels. Dancers averaged 3.5 ± 1.6 total score on the CRA. Based on these scores, the RTP outcomes revealed Full Clearance 7.1%, n = 2; Provisional Clearance 82.1%, n = 23; and Restricted/Medical Disqualification 10.7%, n = 3. Dietary reports revealed that 96.2% (n = 25) of ballet dancers were low in carbohydrates, 92.3% (n = 24) low in protein, 19.2% (n = 5) low in fat percent, 19.2% (n = 5) exceeding saturated fats, 100% (n = 26) low in Vitamin D, and 96.2% (n = 25) low in calcium. Due to the variability in individual risks and nutrient requirements, a patient-centered approach is a critical part of early prevention, evaluation, intervention, and healthcare for the Triad and nutritional-based clinical evaluations.
Early Heart Rate Recovery after a 6-min Walking Test Predicts Clinical Benefits in Patients after Percutaneous Aortic Valve Implantation
Authors: Aleksandrowicz Krzysztof Artur , Aleksandrowicz Katarzyna Maria , Witkowski Tomasz Grzegorz , Kosowski Michał , Kübler Piotr , Grześkowiak Karolina , Golański Grzegorz Piotr , Kulig Damian Janusz , Rachwalik Maciej Filip , Przybylski Roman , Reczuch Krzysztof , Protasiewicz Marcin
Published: February 2023

Background: It was hypothesized that the time-appropriate return to a resting heart rate (HR) after cessation of exercise could be a marker for predicting outcomes in patients with heart failure (HF). We aimed to evaluate the prognostic value of HR recovery in functional improvement among adults with severe aortic stenosis undergoing percutaneous aortic valve implantation (TAVI). Methods: We performed a 6 min walk test (6MWT) in 93 individuals before TAVI and 3 months after the procedure. The change in walking distance was calculated. During the pre-TAVI 6MWT, we analyzed the differences between baseline HR, HR at the end of the test, and HR at the 1st, 2nd, and 3rd minute of recovery. Results: After 3 months, 6MWT distances improved by 39 ± 63 m and reached a total of 322 ± 117 m. Multiple linear regression proved the differences between HR after 2 min of recovery and baseline HR in pre-TAVI after a 6MWT was the only significant predictor of waking distance improvement during follow-up. Conclusions: Our study suggests that analysis of HR recovery after a 6MWT may be a helpful and easy parameter to assess improvements in exercise capacity after TAVI. This simple method can help to identify patients in whom no significant benefit in functional improvement can be expected despite successful valve implantation.
Understanding Determinants of Electronic Cigarette and Heated Tobacco Product Use among Young Adults in Lebanon: Prevention and Policy Implications
Authors: Mugharbil Sanaa , Tleis Malak , Romani Maya , Salloum Ramzi G. , Nakkash Rima
Published: February 2023

In line with the global trends, electronic cigarettes (e-cigarettes) and heated tobacco products (HTPs) have found their way to the Lebanese market. The present study aims to explore the determinants of e-cigarette and HTP use among young adults in Lebanon. Convenience and snowball sampling were used to recruit participants aged 18–30 residing in Lebanon, who were familiar with e-cigarettes products. Twenty-one consenting participants were interviewed via Zoom and the verbatim transcriptions were analyzed thematically. The outcome expectancy theory was used to categorize the results into determinants and deterrents of use. HTPs were viewed by participants as another mode of smoking. The results showed that most participants perceived e-cigarettes and HTPs to be healthier alternatives to cigarettes/waterpipes and to be used as smoking cessation tools. Both e-cigarettes and HTPs were found to be easily accessible in Lebanon; although, in the recent economic crisis, e-cigarettes have become unaffordable. More research is needed to investigate the motivations and behaviors of e-cigarette and HTP users if effective policies and regulations are to be developed and enforced. Furthermore, greater public health efforts need to be made to increase awareness of the harmful impacts of e-cigarettes and HTPs and to implement evidence-based cessation programs tailored to those modes of smoking.
Understanding How School-Based Interventions Can Tackle LGBTQ+ Youth Mental Health Inequality: A Realist Approach
Authors: McDermott Elizabeth , Kaley Alex , Kaner Eileen , Limmer Mark , McGovern Ruth , McNulty Felix , Nelson Rosie , Geijer-Simpson Emma , Spencer Liam
Published: February 2023

Globally, research indicates that LGBTQ+ young people have elevated rates of poor mental health in comparison with their cisgender heterosexual peers. The school environment is a major risk factor and is consistently associated with negative mental health outcomes for LGBTQ+ young people. The aim of this UK study was to develop a programme theory that explained how, why, for whom, and in what context school-based interventions prevent or reduce mental health problems in LGBTQ+ young people, through participation with key stakeholders. Online realist interviews were conducted in the UK with (1) LGBTQ+ young people aged between 13–18 years attending secondary schools (N = 10); (2) intervention practitioners (N = 9); and (3) school staff (N = 3). A realist retroductive data analysis strategy was employed to identify causal pathways across different interventions that improved mental health outcomes. The programme theory we produced explains how school-based interventions that directly tackle dominant cisgender and heterosexual norms can improve LGBTQ+ pupils’ mental health. We found that context factors such as a ‘whole-school approach’ and ‘collaborative leadership’ were crucial to the delivery of successful interventions. Our theory posits three causal pathways that might improve mental health: (1) interventions that promote LGBTQ+ visibility and facilitate usualising, school belonging, and recognition; (2) interventions for talking and support that develop safety and coping; and (3) interventions that address institutional school culture (staff training and inclusion polices) that foster school belonging, empowerment, recognition, and safety. Our theoretical model suggests that providing a school environment that affirms and usualises LGBTQ+ identities and promotes school safety and belonging can improve mental health outcomes for LGBTQ+ pupils.