bluuebunny/crossref_metadata_2025 huggingface dataset:
The Economic Burden of Localized Prostate Cancer and Insights Derived from Cost-Effectiveness Studies of the Different Treatments
Authors: Cantarero-Prieto David , Lera Javier , Lanza-Leon Paloma , Barreda-Gutierrez Marina , Guillem-Porta Vicente , Castelo-Branco Luis , Martin-Moreno Jose M.
Published: August 2022

Prostate cancer has huge health and societal impacts, and there is no clear consensus on the most effective and efficient treatment strategy for this disease, particularly for localized prostate cancer. We have reviewed the scientific literature describing the economic burden and cost-effectiveness of different treatment strategies for localized prostate cancer in OECD countries. We initially identified 315 articles, studying 13 of them in depth (those that met the inclusion criteria), comparing the social perspectives of cost, time period, geographical area, and severity. The economic burden arising from prostate cancer due to losses in productivity and increased caregiver load is noticeable, but clinical decision-making is carried out with more subjective variability than would be advisable. The direct cost of the intervention was the main driver for the treatment of less severe cases of prostate cancer, whereas for more severe cases, the most important determinant was the loss in productivity. Newer, more affordable radiotherapy strategies may play a crucial role in the future treatment of early prostate cancer. The interpretation of our results depends on conducting thorough sensitivity analyses. This approach may help better understand parameter uncertainty and the methodological choices discussed in health economics studies. Future results of ongoing clinical trials that are considering genetic characteristics in assessing treatment response of patients with localized prostate cancer may shed new light on important clinical and pharmacoeconomic decisions.
A Two-Step Cross-Linked Hydrogel Immobilization Strategy for Diacetylchitobiose Deacetylase
Authors: Sun Guoyun , Huang Ziyang , Zhang Zhiqian , Liu Yanfeng , Li Jianghua , Du Guocheng , Lv Xueqin , Liu Long
Published: August 2022

Free enzymes often face economic problems due to their non-recyclability, which limits their applications for industrial manufacturing. Organic biopolymers are frequently used to fabricate hydrogel for enzyme immobilization due to their advantages of non-toxicity, biocompatibility, biodegradability, and flexibility. However, for highly thermostable enzymes, simple cross-linking causes either low immobilizing efficiency or low thermal stability. Herein, we developed a novel enzyme immobilization strategy with two-step cross-linked gelatin hydrogel for thermostable enzymes working at high temperature. The hydrogel was firstly “soft cross-linked” to immobilize most enzyme molecules and then “hard cross-linked” to gain strong thermal stability. We selected the enzyme diacetylchitobiose deacetylase (Dac), which was firstly derived from hyperthermophilic bacteria, to demonstrate the advantages of our method. With the optimized fabrication steps, our hydrogel showed ~87% Dac immobilization efficiency and excellent stability against heating, dehydrating, long-time storing, and massive recycling. Importantly, our hydrogel showed ~85.0% relative enzyme activity at 80 °C and retained ~65.8% activity after 10 rounds of catalysis. This strategy showed high immobilizing efficiency and strong thermal stability and we believe it could improve the industrial potential for those enzymes.
Tips and Tricks—3 Use Cases of Interdisciplinary Knowledge Transfer in Minimally Invasive Pediatric Surgery
Authors: Grosshauser Mareike , Ohletz Tim , Oesch Valérie , Muller Cécile Olivia
Published: August 2022

In the pediatric surgical environment, we can enrich our knowledge and improve our skills through interdisciplinary knowledge transfer in exchange with other surgical or even non-surgical disciplines. To demonstrate this, we present in this article three patient cases of method transfer enabling new techniques in minimally invasive pediatric surgery. 1. The somewhat modified application of the AeroStat rigid tip laparoscopic cholangiography catheter during the single-step laparoscopic cholecystectomy facilitates the safe intraoperative cholangiography with common bile duct flushing. 2. A magnetic rod is used during laparoscopic enterotomy to locate and retrieve ingested magnets. 3. Using a patient-specific MRI 3D model representing a syndromic high anorectal malformation improves surgical planning and parental education.
Nasopharyngeal Carcinoma Progression: Accumulating Genomic Instability and Persistent Epstein–Barr Virus Infection
Authors: Liu Xue , Deng Yayan , Huang Yujuan , Ye Jiaxiang , Xie Sifang , He Qian , Chen Yong , Lin Yan , Liang Rong , Wei Jiazhang , Li Yongqiang , Zhang Jinyan
Published: August 2022

Genomic instability facilitates the evolution of cells, tissues, organs, and species. The progression of human malignancies can be regarded as the accumulation of genomic instability, which confers a high evolutionary potential for tumor cells to adapt to continuous changes in the tumor microenvironment. Nasopharyngeal carcinoma (NPC) is a head-and-neck squamous-cell carcinoma closely associated with Epstein–Barr virus (EBV) infection. NPC progression is driven by a combination of accumulated genomic instability and persistent EBV infection. Here, we present a review of the key characteristics of genomic instability in NPC and the profound implications of EBV infection. We further discuss the significance of profiling genomic instability for the assessment of disease progression and treatment efficacy, as well as the opportunities and challenges of targeted therapies for NPC based on its unique genomic instability.
The Vulnerability of South African Estuaries to Climate Change: A Review and Synthesis
Authors: van Niekerk Lara , Lamberth Stephen J. , James Nicola C. , Taljaard Susan , Adams Janine B. , Theron Andre K. , Krug Marjolaine
Published: August 2022

This review evaluates the vulnerability of South African estuaries to Climate Change in a data-limited environment. The regional-scale assessment is based on physical characteristics and predicted/measured changes in the abiotic drivers and ecosystem responses. The major Climate Change stressors were identified in order of importance as change in climatic and hydrological processes, ocean circulation and temperature regimes, sea level rise, increase in frequency and intensity of sea storms, and ocean acidification. Flow-related ecosystem responses included changes in mouth state, salinity regimes, biochemical regimes (nutrient fluxes), and floods and related sediment deposition/erosion cycles. The regional vulnerability assessment provides a summary of the key shifts scaled as high, medium, and low in estuary state. Changes in oceanic processes and temperature regimes drive shifts in nearshore temperatures of the transitional zones, with related ecological responses (e.g., range expansion). However, most structural and functional changes are expected along cool temperate and subtropical biogeographical regions, leading to notable shifts in mouth closures and salinity regimes, which in turn will affect estuary function and estuary-associated species. Monitoring and management of resources (e.g., fresh water and fisheries allocations) need to consider this in long-term planning.
Evaluation of Various Ejector Profiles on CO2 Transcritical Refrigeration System Performance
Authors: Elbarghthi Anas F. A. , Dvořák Václav
Published: August 2022

This study examines the potential impact of the different ejector profiles on the CO2 transcritical cooling system to highlight the contribution of the multi-ejector in the system performance improvement. The research compares the implementation of an ejector-boosted CO2 refrigeration system over the second-generation layout at a motive flow temperature of 35 °C and discharge pressure of 90 bar to account for the transcritical operation mode. The result revealed a significant energy saving by reducing the input power to the maximum of 8.77% when the ejector was activated. Furthermore, the multi-ejector block could recover up to 25.4% of the expansion work losses acquired by both ejector combinations VEJ1 + 2. In addition, the behavior of the multi-ejector geometries and operation conditions greatly influence the system exergy destruction. The analysis shows a remarkable lack of exergy destruction during the expansion process by deploying the ejector in parallel with the HPV.
Multi-Objective Optimization of a Multilayer Wire-on-Tube Condenser: Case Study R134a, R600a, and R513A
Authors: Heredia-Aricapa Yonathan , Belman-Flores Juan M. , Soria-Alcaraz Jorge A. , Pérez-García Vicente , Elizalde-Blancas Francisco , Alfaro-Ayala Jorge A. , Ramírez-Minguela José
Published: August 2022

This study presents the optimization of a multilayer wire-on-tube condenser exposed to forced convection, using the Optimized Multi-objective Particle Swarm Optimization (OMOPSO) algorithm. The maximization of the heat transfer and the minimization of the heat exchange area were defined as objective functions. In the optimization process, the variations of eight geometric parameters of the condenser were analyzed, and the Multi-objective Evolutionary Algorithm based on Decomposition (MOEAD), Non-dominated Sorting Genetic Algorithm-II (NSGAII), and OMOPSO algorithms were statistically explored. Furthermore, the condenser optimization analysis was extended to the use of alternative refrigerants to R134a such as R600a and R513A. Among the relevant results, it can be commented that the OMOPSO algorithm presented the best option from the statistical point of view compared to the other two algorithms. Thus, optimal designs for the wire-on-tube condenser were defined for three proposed study cases and for each refrigerant, providing an overview of compact designs. Likewise, the reduction of the condenser area was analyzed in more detail, presenting a maximum reduction of 15% for the use of R134a compared to for the current design. Finally, the crossflow condition was studied with respect to the current one, concluding in a greater heat transfer and a smaller heat exchange surface.
Embedded Real-Time Clothing Classifier Using One-Stage Methods for Saving Energy in Thermostats
Authors: Medina Adán , Méndez Juana Isabel , Ponce Pedro , Peffer Therese , Molina Arturo
Published: August 2022

Energy-saving is a mandatory research topic since the growing population demands additional energy yearly. Moreover, climate change requires more attention to reduce the impact of generating more CO2. As a result, some new research areas need to be explored to create innovative energy-saving alternatives in electrical devices that have high energy consumption. One research area of interest is the computer visual classification for reducing energy consumption and keeping thermal comfort in thermostats. Usually, connected thermostats obrtain information from sensors for detecting persons and scheduling autonomous operations to save energy. However, there is a lack of knowledge of how computer vision can be deployed in embedded digital systems to analyze clothing insulation in connected thermostats to reduce energy consumption and keep thermal comfort. The clothing classification algorithm embedded in a digital system for saving energy could be a companion device in connected thermostats to obtain the clothing insulation. Currently, there is no connected thermostat in the market using complementary computer visual classification systems to analyze the clothing insulation factor. Hence, this proposal aims to develop and evaluate an embedded real-time clothing classifier that could help to improve the efficiency of heating and ventilation air conditioning systems in homes or buildings. This paper compares six different one-stage object detection and classification algorithms trained with a small custom dataset in two embedded systems and a personal computer to compare the models. In addition, the paper describes how the classifier could interact with the thermostat to tune the temperature set point to save energy and keep thermal comfort. The results confirm that the proposed real-time clothing classifier could be implemented as a companion device in connected thermostats to provide additional information to end-users about making decisions on saving energy.
Experimental Study and Numerical Simulation of Removing Water Blocking by Hot-Gas Injection in Tight Cores
Authors: Yang Zhao , Liu Hongji , Guo Chaohua
Published: August 2022

Compared with oil, natural gas has been the focus of the energy industry in recent years. Renewable energy is the goal and trend of future developments, and it has made considerable progress; however, it has not reached the ideal popularization rate. Therefore, natural gas is still very important so far. In this paper, the influence of thermal gas injection and room temperature gas injection on gas reservoir recovery is analyzed, and the method of water plugging by hot gas injection in tight gas reservoir is put forward. Indoor simulation experiments were carried out to evaluate the effect of hot-gas injection in cut pore water and the degree of water blockage. On this basis, the numerical simulation of removing water blockage by hot-gas injection was carried out. The changes in core temperature and remaining water saturation were discussed by using simulation models. Results of this study can provide a theoretical basis for removing water blockage in actual oil and gas reservoirs.
Site Selection for a Deep Geological Repository in Switzerland: The Role of Performance Assessment Modeling
Authors: Papafotiou Alexandros , Li Chao , Zbinden Dominik , Hayek Mohamed , Hannon Michael J. , Marschall Paul
Published: August 2022

In the development of deep geological repositories (DGRs), performance assessment modeling is used to evaluate the integrity and performance of the engineered and geological barriers for thousands or millions of years of evolution of the disposal system. To evaluate the suitability of a site for a DGR, geoscientific data from dedicated site investigation programs are integrated into site-specific assessments. This paper presents the development and implementation of a modeling workflow aimed at comparing three potential siting areas for a DGR in Switzerland from the viewpoint of long-term safety and technical feasibility. The workflow follows the guidelines of the national regulator addressing safety relevant criteria such as the barrier efficiency of the host rock and its mechanical and chemical integrity in response to repository-induced influences and the long-term stability of the repository site over geological scales. In the regulatory requirements, the role of parametric, conceptual, and scenario uncertainty has been identified as an issue of special importance in the site selection process. The assessment approach comprises a portfolio of numerical models for the simulation of solute, gas and heat transport in the repository nearfield. The modeling was performed with deterministic as well as probabilistic variants integrated in an indicator-based approach that allows the consistent comparison of the candidate sites using quantitative dimensionless performance indices. The model-based assessment of the sites allows a traceable, transparent, and verifiable implementation of the site selection process.
Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
Authors: Rao Sivakavi Naga Venkata Bramareswara , Yellapragada Venkata Pavan Kumar , Padma Kottala , Pradeep Darsy John , Reddy Challa Pradeep , Amir Mohammad , Refaat Shady S.
Published: August 2022

The modern-day urban energy sector possesses the integrated operation of various microgrids located in a vicinity, named cluster microgrids, which helps to reduce the utility grid burden. However, these cluster microgrids require a precise electric load projection to manage the operations, as the integrated operation of multiple microgrids leads to dynamic load demand. Thus, load forecasting is a complicated operation that requires more than statistical methods. There are different machine learning methods available in the literature that are applied to single microgrid cases. In this line, the cluster microgrids concept is a new application, which is very limitedly discussed in the literature. Thus, to identify the best load forecasting method in cluster microgrids, this article implements a variety of machine learning algorithms, including linear regression (quadratic), support vector machines, long short-term memory, and artificial neural networks (ANN) to forecast the load demand in the short term. The effectiveness of these methods is analyzed by computing various factors such as root mean square error, R-square, mean square error, mean absolute error, mean absolute percentage error, and time of computation. From this, it is observed that the ANN provides effective forecasting results. In addition, three distinct optimization techniques are used to find the optimum ANN training algorithm: Levenberg–Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient. The effectiveness of these optimization algorithms is verified in terms of training, test, validation, and error analysis. The proposed system simulation is carried out using the MATLAB/Simulink-2021a® software. From the results, it is found that the Levenberg–Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results.
Comparison of Axial Flow and Swirling Flow on Particle Pickup in Horizontal Pneumatic Conveying
Authors: Ji Yun , Hao Yating , Yi Ning , Guan Tianyuan , Gao Dianrong , Liang Yingna
Published: August 2022

Pneumatic conveying is widely used in coal mining. As the lowest conveying velocity of materials, the pickup velocity is the key to the study of gas–solid two-phase flow. In this study, the pickup velocity of pebble particles was experimentally investigated. When the particle size is 3–9 mm, the airflow velocity was found to suitably describe the results as a function of the pickup velocity and have a high correlation. When the swirl number is 0.2, the optimal swirl number was found for which the highest particle pickup ratio was observed. Based on four different methods, namely, visual observation, mass weighing, coefficient of difference analysis, and determination of the peak-average ratio of the pressure drop in the flow field to measure the pickup velocity of the spraying material, the results showed that the accuracy of the particle pickup velocity obtained through visual observation was the lowest, and when the mass–loss rate of the particle was selected as the measurement index of the pickup velocity, the accuracy was the highest. The results will help to realize the long-distance transportation of spraying materials in inclined roadway under the shaft.
Artificial Intelligence in Adaptive and Intelligent Educational System: A Review
Authors: Dong Jingwen , Mohd Rum Siti Nurulain , Kasmiran Khairul Azhar , Mohd Aris Teh Noranis , Mohamed Raihani
Published: August 2022

There has been much discussion among academics on how pupils may be taught online while yet maintaining a high degree of learning efficiency, in part because of the worldwide COVID-19 pandemic in the previous two years. Students may have trouble focusing due to a lack of teacher–student interaction, yet online learning has some advantages that are unavailable in traditional classrooms. The architecture of online courses for students is integrated into a system called the Adaptive and Intelligent Education System (AIES). In AIESs, reinforcement learning is often used in conjunction with the development of teaching strategies, and this reinforcement-learning-based system is known as RLATES. As a prerequisite to conducting research in this field, this paper undertakes the consolidation and analysis of existing research, design approaches, and model categories for adaptive and intelligent educational systems, with the hope of serving as a reference for scholars in the same field to help them gain access to the relevant information quickly and easily.
Reline Jacket: Efficient Reduction of Frost-Heave Uplift of Piles in Warming Permafrost
Authors: Alyavdin Dmitriy , Belyakov Vladimir , Levin Artemiy , Alekseev Andrey , Grechishcheva Erika , Kozlova Olga , Makhota Roman
Published: August 2022

Air temperature in the Northern Hemisphere has been progressively warming in the recent decades, and the ground temperatures have increased correspondingly. The air temperature increasing due to the climate change induces degradation of permafrost and frost heaving activation. The frost heaving forces cause unevenly distributed damaging displacement of foundations and thus poses problems to the development of Arctic regions. Frost-heave uplift forces can be reduced by protecting piles with an OSPTReline (or Reline) polymer heat-shrinkable jacket. The interaction of heaving soil with a pile covered with the Reline jacket is modeled in laboratory to estimate the uplift force and the related shear strength of frozen soil along the soil-pile adfreeze surface at temperatures from −6 to −1 °C. The data are obtained for silty sand and silty clay soils and mortar (1:5 cement-sand mixture). The experiments show that frost-heave uplift forces on Reline-protected piles are 52% to 85% lower than on uncovered steel piles (steel grade 09G2S—analog to European steel grade S355JR), depending on soil type and temperature.
Participatory Action Research for Tackling Distress and Burnout in Young Medical Researchers: Normative Beliefs before and during the Greek Financial Crisis
Authors: Sifaki-Pistolla Dimitra , Mechili Enkeleint , Melidoniotis Evangelos , Argyriadis Alexandros , Patelarou Evridiki , Chatzea Vasiliki-Eirini
Published: August 2022

(1) Background: We aimed to explore Young medical researchers (YMR) normative beliefs and perceived causes of distress and burnout, prior and during the financial crisis in Greece, and to assess their views on Participatory Action Research (PAR) interventions towards tackling these disorders. (2) Methods: A Participatory Learning and Action (PLA) methodology was performed in two time periods (prior crisis: December 2008; during crisis: February–March 2017). In both time periods, three different groups (Group 1: females, Group 2: males, Group 3: mixed) of 5–7 participants and two sessions (≈1 h/session) per group took place in each site. Overall, 204 sessions with 1036 YMR were include in the study. (3) Results: Several socio-demographic characteristics of YMR altered during the crisis (lower income, higher smoking/alcohol consumption, etc.). The majority of YMR conceived distress and burnout as serious syndromes requiring professional support. Feeling very susceptible and the necessity for establishing PAR interventions were frequently reported during the crisis. Numerous (a) barriers and (b) cues to action were mentioned: (a) lack of time, money and support from friends/family/colleagues (b) being extensively informed about the intervention, participation of their collaborators, and raising awareness events. (4) Conclusions: The changing pattern of Greek YMR’s beliefs and needs during the crisis stresses the necessity of interventions to tackle distress and burnout. Effectiveness of these interventions could be enhanced by the suggested cues to action that emerged from this study.
The Role of the Context of Physical Activity for Its Association with Affective Well-Being: An Experience Sampling Study in Young Adults
Authors: Li Yu-Mei , Hachenberger Justin , Lemola Sakari
Published: August 2022

Physical activity and being outdoors both improve affective well-being. However, little is known about the synergistic effects between them and the influences of contextual factors such as the life domain of physical activity (work-, chores-, leisure, or sports-related) or the type of the outdoor environment (green space, blue space, or city area) on mood. This study investigates the synergistic effects of physical activity and being outdoors as well as the potential role of contextual factors on mood. A total of 158 individuals aged 18–25 years (133 females) participated in a 14-day experience sampling study. Participants received seven prompts per day and answered questions about their physical activity, contextual factors, and affective well-being. Physical activity and being outdoors were associated with concurrent higher levels of positive and lower levels of negative affect compared to being physically inactive or being indoors, respectively. However, no synergistic effects were found. Being outdoors in a city area was associated with a less positive and more negative affect than being in nature. Work- and chores-related physical activity was associated with less positive affect and more negative affect compared to sports- or leisure-related physical activity. To foster positive affect, people should schedule leisure-related physical activity in nature.
Temporal and Spatial Variation (2001–2020) Characteristics of Wind Speed in the Water Erosion Area of the Typical Black Soil Region, Northeast China
Authors: Pei Liang , Wang Chunhui , Sun Liying , Wang Lili
Published: August 2022

Soil erosion is one of the driving factors leading to the land degradation in the black soil region of Northeast China. It is of great significance to analyze the temporal and spatial variation characteristics of wind speed there for the study of wind erosion impacts and geomantic erosion. Based on the daily meteorological data of 51 meteorological stations from 2001 to 2020, the interannual variation, seasonal variation, and spatial characteristics of wind speed were analyzed by cumulative anomaly method, Mann–Kendall test method, and Kriging interpolation method. The natural factors affecting wind speed were discussed by using geographic detectors, and the potential effects of wind speed on soil erosion were further analyzed. The results showed that the maximum annual wind speed in the water erosion area of the typical black soil region fluctuated with a decreasing trend. However, the mean annual wind speed demonstrated a decreasing trend before 2014, and then showed increasing trend. The proportion of the meteorological stations with decreasing mean annual wind speed and maximum annual wind speed during years 2001–2020 was 70% and 60%, respectively. The seasonal variation of the mean monthly wind speed and maximum monthly wind speed showed the same trend as Spring > Autumn > Winter > Summer. The spatial variation of the mean annual wind speed and maximum annual wind speed was consistent. According to the results of the geographic detectors, DEM and temperature are the main factors affecting the spatial heterogeneity of the maximum annual wind speed. The area of ‘severe’ and ‘extremely severe’ of wind impacts account for 23.4%, and specific concerns should be paid to the areas of Nenjiang, Yilan, Tonghe, and Baoqing, located in the north and east sides of the study area. The results of the article could provide reference for the study of wind–water complex erosion in the water erosion area of the typical black soil region for better soil erosion control and ecological protection.
How Preemption Can Lead to Inequity
Authors: Yang Y. Tony , Berg Carla J.
Published: August 2022

American cities and localities have historically been places of innovation and incubation when it comes to advancing equity and inclusion. Now, local governments in many states are leading the fight for stronger public health protections against COVID-19—through mask mandates, stay-at-home orders, and paid leave provisions, among other actions. However, state lawmakers have long used preemption—state laws that block, override, or limit local ordinances—to stifle local government action, often under pressure from corporate interests and political ideology. Through preemption, state lawmakers have obstructed local communities—often majority-minority communities—from responding to the expressed needs and values of their residents through policies. In this article, we first look at the context behind preemption and its disparate effects. After establishing a conceptual framework for measuring disparities, we discuss how the current COVID-19 pandemic is disproportionately harming the same communities that have been preempted from taking local action, limiting their ability to effectively combat the public health crisis. We argue that all stakeholders interested in health equity have a role to play in addressing the misuse of state preemption.
Socioeconomic-Related Inequalities in COVID-19 Vulnerability in South Africa
Authors: Shifa Muna , Gordon David , Leibbrandt Murray , Zhang Mary
Published: August 2022

Individuals’ vulnerability to the risk of COVID-19 infection varies due to their health, socioeconomic, and living circumstances, which also affect the effectiveness of implementing non-pharmacological interventions (NPIs). In this study, we analysed socioeconomic-related inequalities in COVID-19 vulnerability using data from the nationally representative South African General Household Survey 2019. We developed a COVID-19 vulnerability index, which includes health and social risk factors for COVID-19 exposure and susceptibility. The concentration curve and concentration index were used to measure socioeconomic-related inequalities in COVID-19 vulnerability. Recentred influence function regression was then utilised to decompose factors that explain the socioeconomic-related inequalities in COVID-19 vulnerability. The concentration index estimates were all negative and highly significant (p < 0.01), indicating that vulnerability to COVID-19 was more concentrated among the poor. According to the decomposition analysis, higher income and education significantly (p < 0.01) positively impacted lowering socioeconomic-related COVID-19 vulnerability. Living in an urban region, being Black, and old all had significant (p < 0.01) positive impacts on increasing socioeconomic-related COVID-19 vulnerability. Our findings contribute to a better understanding of socially defined COVID-19-vulnerable populations in South Africa and the implications for future pandemic preparedness plans.
A Qualitative Investigation of the Impact of COVID-19 on United States’ Frontline Health Care Workers and the Perceived Impact on Their Family Members
Authors: Schaffer Gary Edward , Kilanowski Lisa , Lee Brian En Chyi
Published: August 2022

Although previous research has documented the mental and physical health impacts that COVID-19 had on frontline health workers in the United States, little is known about how the pandemic affected their families. This study sought to explore the impact COVID-19 had on the individual functioning of frontline health care workers in the USA and the perceived impact it had on their family members during the initial nine months of the pandemic. More specifically, this study sought to explore if and how family roles, routines, rules, and social-emotional well-being changed as a result of COVID-19. Twenty-eight frontline health care workers across the United States who were parents to at least one child residing in the home under 24 were interviewed. Data were analyzed using reflexive thematic analysis. From the analysis, four major themes emerged with regard to the changes and perceived impact to family functioning, family experiences of new hygiene practices, and stigma related to being a health care practitioner or having a family member working in health care, and psychological distress. The results of this study can be used by mental health clinicians to inform policy, develop practice guidelines, and help identify and target interventions for health care workers and their family members.
Associations between Parents’ Digital Media Habits, Engagement, Awareness, and Movement Guidelines among Preschool-Age Children: International Ipreschooler Surveillance Study
Authors: Guo Hongzhi , Ma Jiameng , Chua Terence Buan Kiong , Tay Lee Yong , Chia Michael Yong Hwa , Kim Hyunshik
Published: August 2022

The 24-hour movement guidelines (24-h MG) recommend behaviors (physical activity, screen time, sleep) to aid appropriate physical and mental development in early childhood. This research examined parents’ digital media habits (DMH), engagement (DME), and awareness (DMA) among parents in relation to their preschool-aged children’s 24-h MG in Japan and identified and compared the modifiable determinants of adherence to 24-h MG in urban and rural regions. This cross-sectional study included 867 participants and data were obtained from the International Ipreschooler Surveillance Study Among Asians and OtheRs (IISSAAR). The results revealed that adherence to weekend screen time recommendations and weekday sleep duration were higher in the urban region. The parents’ digital media variables that predicted moderate-intensity to vigorous-intensity physical activity among preschool-aged children were parents’ DME and DMA in the urban regions and parents’ DME in the rural regions. The children’s screen time was significantly associated with parents’ DMH, DME, and DMA in the urban regions and with parents’ DMH and DMA in the rural regions (p < 0.005, p < 0.001, respectively). This study confirmed that parents’ DMH, DME, and DMA are strong predictors of adherence to 24-h MG among preschool-aged children living in both rural and urban regions in Japan.
Is Ocular Accommodation Influenced by Dynamic Ambient Illumination and Pupil Size?
Authors: Yu Hanyang , Li Wentao , Chen Ziping , Chen Mengzhen , Zeng Junwen , Lin Xijiang , Zhao Feng
Published: August 2022

Purpose: We investigated ocular accommodative responses and pupil diameters under different light intensities in order to explore whether changes in light intensity aid effective accommodation function training. Methods:A total of 29 emmetropic and myopic subjects (age range: 12–18 years) viewed a target in dynamic ambient light (luminance: 5, 100, 200, 500, 1000, 2000 and 3000 lux) and static ambient light (luminance: 1000 lux) at a 40 cm distance with refractive correction. Accommodation and pupil diameter were recorded using an open-field infrared autorefractor and an ultrasound biological microscope, respectively. Results: The changes in the amplitude of accommodative response and pupil diameter under dynamic lighting were 1.01 ± 0.53 D and 2.80 ± 0.75 mm, respectively, whereas in static lighting, those values were 0.43 ± 0.24 D and 0.77 ± 0.27 mm, respectively. The amplitude of accommodation and pupil diameter change in dynamic lighting (t = 6.097, p < 0.001) was significantly larger than that under static lighting (t = 16.115, p < 0.001).The effects of light level on both accommodation and pupil diameter were significant (p < 0.001). Conclusion: Accommodation was positively correlated with light intensity. The difference was about 1.0 D in the range of 0–3000 lux, which may lay the foundation for accommodative training through light intervention.
Predictors of Low Back Pain Risk among Rubber Harvesters
Authors: Chokprasit Parnchon , Yimthiang Supabhorn , Veerasakul Siriluk
Published: August 2022

Low back pain (LBP) is a significant work-related musculoskeletal disorder among rubber farmers. This major occupational health problem was highly reported in the agricultural sector. While rubber farming is a profession with high risk of LBP, predictors for LBP remain unclear. This study was designed to investigate the risk predictors of LBP among rubber farmers during the harvesting process. A cross-sectional study was conducted between January and March 2021, in which an interviewer administered a pretested structured questionnaire. Bivariate and multivariate binary logistic regression analyses were performed. A total of 317 rubber farmers were recruited with a 100% response rate. The prevalence of LBP was 71.2% with 95% confidence interval (CI) of (0.716–1.900). Significant risk predictors were working experience (adjusted odds ratio (AOR): 1.743, 95% CI (1.034–2.937)), agricultural registration (AOR: 2.022, 95% CI (1.078–3.792)), work without training (AOR: 2.037, 95% CI (1.083–3.832)), heavy workload (AOR: 2.120, 95% CI (1.242–3.621)), and prolonged standing (AOR: 2.944, 95% CI (1.586–5.465)). Intriguingly, those with sufficient income had a reduced risk of LBP than those with insufficient income. This study confirmed that LBP is a major work-related musculoskeletal disorder among rubber farmers. The result here suggests that the five predictors reported above should be prioritized for further disease prevention.
How about an Educational Framework for Nursing Staff in Long-Term Care Facilities to Improve the Care of Behavioral and Psychological Symptoms of Dementia?
Authors: Kim Dayeong , Choi Young-Rim , Lee Ye-Na , Park Won-Hee , Chang Sung-Ok
Published: August 2022

Behavioral and psychological symptoms of dementia (BPSD) are common in residents of long-term care facilities (LTCFs). In LTCFs, nursing staff, including nurses and care workers, play a crucial role in managing BPSD as those most in contact with the residents. However, it is ambiguous where their focus should be for effective BPSD care. Thus, this paper aims to reveal BPSD care competencies for nursing staff in LTCFs and to outline an initial frame of education. A multiphase mixed-methods approach, which was conducted through topic modeling, qualitative interviews, and a Delphi survey, was used. From the results, a preliminary educational framework for nursing staff with categories of BPSD care competence was outlined with the four categories of BPSD care competence: using knowledge for assessment and monitoring the status of residents, individualizing approaches on how to understand residents and address BPSD, building relationships for shared decision-making, and securing a safe environment for residents and staff in LTCFs. This preliminary framework illuminates specific domains that need to be developed for competent BPSD care in LTCFs that are centered on nursing staff who directly assess and monitor the changing and deteriorating state of residents in LTCFs.
Hierarchical Structure Model of Safety Risk Factors in New Coastal Towns: A Systematic Analysis Using the DEMATEL-ISM-SNA Method
Authors: Guan Chenlei , Dong Damin , Shen Feng , Gao Xin , Chen Linyan
Published: August 2022

When a coastal town transforms from a rural area to an emerging city, it faces many safety risks. Some are new risks from urban construction, while some are traditional risks that belong to this coastal area. The joint efforts of these risks may lead to new hazards, harming public health, but this problem has not been noticed in previous studies. Therefore, this study constructs the Triangular Framework for Safety Risk in New Towns to identify the risks and proposes strategies to reduce the risks. In this study, multiple methods are integrated, including Decision-Making Trial and Evaluation Laboratory (DEMATEL), Interpretive Structural Modeling (ISM), and Social Network Analysis (SNA). This study takes the Lin-gang Special Area in China as a case study to verify the framework’s effectiveness. Sixteen disaster-causing factors are identified, and the internal linkages among these factors are clarified. Results show that the hybrid method performs well in quantitatively analyzing the risk factors of new coastal towns. A typhoon, public risk perception, and population migration are essential influencing factors. Disaster prevention capability of high-rise buildings, disaster prevention capacity of port facilities, and transportation are the most direct influencing factors. Environmental degradation is the most conductive among all elements. This study contributes to the theoretical theory by proposing an effective framework to analyze the safety risks in new coastal towns. In addition, it provides practical references for governments to make emergency plans in the city.
Influence of Screen Time during COVID-19 on Health-Related Quality of Life of Early Adolescents
Authors: Cheung Mei-Chun , Yip Joanne , Cheung Jason Pui Yin
Published: August 2022

This study investigated the influence of screen time during COVID-19 on the physical and mental domains of the health-related quality of life of early adolescents. A total of 860 early adolescents were recruited. The 36-Item Short Form Health Survey was used to measure their health-related quality of life. The early adolescents reported their average daily time spent using smartphones and computers and watching television over the previous week. The results show that most early adolescents, on average, spent less than 1 h to more than 4 h per day during COVID-19 using smartphones (n = 833, 96.9%) and computers (n = 783, 91.0%), and watching television (n = 804, 93.5%), respectively. Though early male and female adolescents spent a similar amount of time daily on average using smartphones, early male adolescents spent more time using computers and watching television than early female adolescents and reported a significantly lower mean score for three out of the eight scales in the physical and mental domains of health-related quality of life. While health-related quality of life of early female adolescents was negatively associated with time spent using smartphones only, early male adolescents were adversely affected by the time spent using smartphones and computers and watching television (p < 0.05). Therefore, early adolescents who spent more time using display devices during COVID-19 had significantly poorer outcomes in their health-related quality of life, and gender difference was found in the influence of screen time on health-related quality of life.
Sweet as Sugar—How Shared Social Identities Help Patients in Coping with Diabetes Mellitus
Authors: Frenzel Svenja B. , Kaluza Antonia J. , Junker Nina M. , van Dick Rolf
Published: August 2022

Social identification is health-beneficial as social groups provide social support (i.e., the social cure effect). We study this social cure effect in diabetes patients by focusing on two relevant sources of social support, namely medical practitioners (MP) and fellow patients. As both groups have diabetes-specific knowledge, we predict that sharing an identity with them provides access to specific support, which, in turn, optimizes individuals’ diabetes management and reduces diabetes-related stress. We further predict that identifying with their MP or fellow patients will be more strongly related to perceived social support among individuals with lower diabetes-specific resilience because they pay more attention to supportive cues. We tested this moderated mediation model in a two-wave study with n = 200 diabetes patients. Identification with the MP related to more support, which, in turn, was related to better diabetes management and less diabetes-specific stress. Identification with fellow patients related to more support; however, social support was unrelated to diabetes management and stress. Resilience only moderated the relationship between MP identification and support, as people with lower resilience levels reported more support from their MP. This study shows the importance of social identification with the MP and other diabetes patients, especially for people with lower resilience levels.
Does Forest Therapy Have Physio-Psychological Benefits? A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Yi Yunjeong , Seo Eunju , An Jiyeon
Published: August 2022

Forest therapy involves visiting forests or conducting forest-based treatment activities to improve one’s health. Studies have investigated the health benefits of forests, but consensus has not been reached. This study comprised a systematic review and meta-analysis to determine how forest therapy affects the physiological and psychological health of adults. The Cumulative Index to Nursing and Allied Health Literature, Embase, and Medline databases were searched on 31 August 2021. Systematic review and meta-analysis, risk evaluation, GRADE evaluation, and advertisement effect evaluation were performed for each article. The effect size was calculated by dividing blood pressure as a physiological indicator and depression as a psychological indicator. Of the 16,980 retrieved studies, 17 were selected based on the inclusion criteria. Of these, eight studies were included in the meta-analysis. The effect size of forest therapy on improving systolic and diastolic blood pressure was not significant; however, it significantly reduced depression. While the results have limited generalizability due to the inclusion of few studies, the effects of forest therapy on reducing depression have been confirmed. Since the application of forest therapy was heterogeneous in these studies, a moderator effect analysis or subgroup analysis in meta-analysis should be performed in the future.
Extraction of Urban Quality of Life Indicators Using Remote Sensing and Machine Learning: The Case of Al Ain City, United Arab Emirates (UAE)
Authors: Yagoub Mohamed. M. , Tesfaldet Yacob T. , Elmubarak Marwan G. , Al Hosani Naeema
Published: August 2022

Urban quality of life (UQoL) study is very important for many applications such as services distribution, urban planning, and socioeconomic analysis. The objective of this study is to create an urban quality of life index map for Al Ain city in the United Arab Emirates (UAE). The research aligns with the United Nations Sustainable Development Goals number ten (reduce inequalities) and eleven (sustainable cities and communities). In this study, remote sensing images and GIS vector datasets were used to extract biophysical and infrastructure facility indicators. The biophysical indicators are normalized difference vegetation index (NDVI), normalized difference water index (NDWI), modified normalized difference water index (MNDWI), soil adjusted vegetation index (SAVI), enhanced normalized difference impervious surfaces index (ENDISI), normalized difference built-up index (NDBI), land surface temperature (LST), slope, and land use land cover (LULC). In addition, infrastructure facility indicators such as distances to main roads, parks, schools, and hospitals were obtained. Additional infrastructure facility variables namely built-up to green area and build-up to bare soil area ratio were extracted from the LULC map. Machine learning was used to classify satellite images and generate LULC map. Random Forest (RF) was found as the best machine learning classifier for this study. The overall classification and Kappa hat accuracy was 95.3 and 0.92, respectively. Both biophysical and infrastructure facility indicators were integrated using principal component analysis (PCA). The PCA analysis identified four components that explain 75% of the variance among the indicators. The four factors were interpreted as the effect of LULC, infrastructure facility, ecological, and slope. Finally, the components were assigned weights based on the percentage of variance they explained and developed the UQoL map. Overall, the result showed that greenness has a greater effect on the spatial pattern of UQoL in Al Ain city. The study could be of a value to policy makers in urban planning and socioeconomic departments.