bluuebunny/crossref_metadata_2025 huggingface dataset:
A Self-Supervised Model for Language Identification Integrating Phonological Knowledge
Authors: Zhan Qingran , Xie Xiang , Hu Chenguang , Cheng Haobo
Published: September 2021

In this paper, a self-supervised learning pre-trained model is proposed and successfully applied in language identification task (LID). A Transformer encoder is employed and multi-task strategy is used to train the self-supervised model: the first task is to reconstruct the masking spans of input frames and the second task is a supervision task where the phoneme and phonological labels are used with Connectionist Temporal Classification (CTC) loss. By using this multi-task learning loss, the model is expected to capture high-level speech representation in phonological space. Meanwhile, an adaptive loss is also applied for multi-task learning to balance the weight between different tasks. After the pretraining stage, the self-supervised model is used for xvector systems. Our LID experiments are carried out on the oriental language recognition (OLR) challenge data corpus and 1 s, 3 s, Full-length test sets are selected. Experimental results show that on 1 s test set, feature extraction model approach can get best performance and in 3 s, Full-length test, the fine-tuning approach can reach the best performance. Furthermore, our results prove that the multi-task training strategy is effective and the proposed model can get the best performance.
Digital Technologies for Innovative Mental Health Rehabilitation
Authors: Lopes Rui Pedro , Barroso Bárbara , Deusdado Leonel , Novo André , Guimarães Manuel , Teixeira João Paulo , Leitão Paulo
Published: September 2021

Schizophrenia is a chronic mental illness, characterized by the loss of the notion of reality, failing to distinguish it from the imaginary. It affects the patient in life’s major areas, such as work, interpersonal relationships, or self-care, and the usual treatment is performed with the help of anti-psychotic medication, which targets primarily the hallucinations, delirium, etc. Other symptoms, such as the decreased emotional expression or avolition, require a multidisciplinary approach, including psychopharmacology, cognitive training, and many forms of therapy. In this context, this paper addresses the use of digital technologies to design and develop innovative rehabilitation techniques, particularly focusing on mental health rehabilitation, and contributing for the promotion of well-being and health from a holistic perspective. In this context, serious games and virtual reality allows for creation of immersive environments that contribute to a more effective and lasting recovery, with improvements in terms of quality of life. The use of machine learning techniques will allow the real-time analysis of the data collected during the execution of the rehabilitation procedures, as well as enable their dynamic and automatic adaptation according to the profile and performance of the patients, by increasing or reducing the exercises’ difficulty. It relies on the acquisition of biometric and physiological signals, such as voice, heart rate, and game performance, to estimate the stress level, thus adapting the difficulty of the experience to the skills of the patient. The system described in this paper is currently in development, in collaboration with a health unit, and is an engineering effort that combines hardware and software to develop a rehabilitation tool for schizophrenic patients. A clinical trial is also planned for assessing the effectiveness of the system among negative symptoms in schizophrenia patients.
Design & Optimization of Large Cylindrical Radomes with Subcell and Non-Orthogonal FDTD Meshes Combined with Genetic Algorithms
Authors: Navarro Enrique A. , Portí Jorge A. , Salinas Alfonso , Navarro-Modesto Enrique , Toledo-Redondo Sergio , Fornieles Jesús
Published: September 2021

The word radome is a contraction of radar and dome. The function of radomes is to protect antennas from atmospheric agents. Radomes are closed structures that protect the antennas from environmental factors such as wind, rain, ice, sand, and ultraviolet rays, among others. The radomes are passive structures that introduce return losses, and whose proper design would relax the requirement of complex front-end elements such as amplifiers. The radome consists mostly in a thin dielectric curved shape cover and sometimes needs to be tuned using metal inserts to cancel the capacitive performance of the dielectric. Radomes are in the near field region of the antennas and a full wave analysis of the antenna with the radome is the best approach to analyze its performance. A major numerical problem is the full wave modeling of a large radome-antenna-array system, as optimization of the radome parameters minimize return losses. In the present work, the finite difference time domain (FDTD) combined with a genetic algorithm is used to find the optimal radome for a large radome-antenna-array system. FDTD uses general curvilinear coordinates and sub-cell features as a thin dielectric slab approach and a thin wire approach. Both approximations are generally required if a problem of practical electrical size is to be solved using a manageable number of cells and time steps in FDTD inside a repetitive optimization loop. These approaches are used in the full wave analysis of a large array of crossed dipoles covered with a thin and cylindrical dielectric radome. The radome dielectric has a thickness of ~λ/10 at its central operating frequency. To reduce return loss a thin helical wire is introduced in the radome, whose diameter is ~0.0017λ and the spacing between each turn is ~0.3λ. The genetic algorithm was implemented to find the best parameters to minimize return losses. The inclusion of a helical wire reduces return losses by ~10 dB, however some minor changes of radiation pattern could distort the performance of the whole radome-array-antenna system. A further analysis shows that desired specifications of the system are preserved.
Distributed Event-Triggered Approach for Multi-Agent Formation Based on Cooperative Localization with Mixed Measurements
Authors: Lin Yanjun , Lin Zhiyun , Sun Zhiyong
Published: September 2021

This paper concentrates on multi-agent formation control problems under mixed measurements of distance and bearing. Towards this objective, a distributed event-triggered estimation-based control framework is developed such that only at necessary time instants, the event for estimation (namely, cooperative localization among a subgroup of agents) is triggered to recover relative position information by utilizing a mixed distance and bearing measurements from different agents. Firstly, it is shown by using the stiffness theory that a subgroup of agents are capable of recovering relative position information if a sufficient number of independent distance and range measurements are available. Secondly, a distributed event-triggered mechanism is presented for achieving an affine formation control, which can be implemented in an asynchronous manner and also ensures Zeno-free behavior. Simulation studies are provided to demonstrate the effective performance of the proposed approach.
Application of Machine Learning to a Medium Gaussian Support Vector Machine in the Diagnosis of Motor Bearing Faults
Authors: Lin Shih-Lin
Published: September 2021

In recent years, artificial intelligence technology has been widely used in fault prediction and health management (PHM). The machine learning algorithm is widely used in the condition monitoring of rotating machines, and normal and fault data can be obtained through the data acquisition and monitoring system. After analyzing the data and establishing a model, the system can automatically learn the features from the input data to predict the failure of the maintenance and diagnosis equipment, which is important for motor maintenance. This research proposes a medium Gaussian support vector machine (SVM) method for the application of machine learning and constructs a feature space by extracting the characteristics of the vibration signal collected on the spot based on experience. Different methods were used to cluster and classify features to classify motor health. The influence of different Gaussian kernel functions, such as fine, medium, and coarse, on the performance of the SVM algorithm was analyzed. The experimental data verify the performance of various models through the data set released by the Case Western Reserve University Motor Bearing Data Center. As the motor often has noise interference in the actual application environment, a simulated Gaussian white noise was added to the original vibration data in order to verify the performance of the research method in a noisy environment. The results summarize the classification results of related motor data sets derived recently from the use of motor fault detection and diagnosis using different machine learning algorithms. The results show that the medium Gaussian SVM method improves the reliability and accuracy of motor bearing fault estimation, detection, and identification under variable crack-size and load conditions. This paper also provides a detailed discussion of the predictive analytical capabilities of machine learning algorithms, which can be used as a reference for the future motor predictive maintenance analysis of electric vehicles.
Model-Based Range Prediction for Electric Cars and Trucks under Real-World Conditions
Authors: Dollinger Manfred , Fischerauer Gerhard
Published: September 2021

The further development of electric mobility requires major scientific efforts to obtain reliable data for vehicle and drive development. Practical experience has repeatedly shown that vehicle data sheets do not contain realistic consumption and range figures. Since the fear of low range is a significant obstacle to the acceptance of electric mobility, a reliable database can provide developers with additional insights and create confidence among vehicle users. This study presents a detailed, yet easy-to-implement and modular physical model for both passenger and commercial battery electric vehicles. The model takes consumption-relevant parameters, such as seasonal influences, terrain character, and driving behavior, into account. Without any a posteriori parameter adjustments, an excellent agreement with known field data and other experimental observations is achieved. This validation conveys much credibility to model predictions regarding the real-world impact on energy consumption and cruising range in standardized driving cycles. Some of the conclusions, almost impossible to obtain experimentally, are that winter conditions and a hilly terrain each reduce the range by 7–9%, and aggressive driving reduces the range by up to 20%. The quantitative results also reveal the important contributions of recuperation and rolling resistance towards the overall energy budget.
Building Pareto Frontiers for Ecosystem Services Tradeoff Analysis in Forest Management Planning Integer Programs
Authors: Marques Susete , Bushenkov Vladimir , Lotov Alexander , G. Borges José
Published: September 2021

Decision making in modern forest management planning is challenged by the need to recognize multiple ecosystem services and to address the preferences and goals of stakeholders. This research presents an innovative a posteriori preference modeling and multi-objective integer optimization (MOIP) approach encompassing integer programming models and a new technique for generation and interactive visualization of the Pareto frontier. Due to the complexity and size of our management problems, a decomposition approach was used to build the Pareto frontier of the general problem using the Pareto frontiers of its sub-problems. The emphasis was on the approximation of convex Edgeworth–Pareto hulls (EPHs) for the sub-problems by systems of linear inequalities; the generation of Edgeworth–Pareto hulls by the convex approximation of the Pareto frontier evinced a very small discrepancy from the real integer programming solutions. The results thus highlight the possibility of generating the Pareto frontiers of large multi-objective integer problems using our approach. This research innovated the generation of Pareto frontier methods using integer programming in order to address multiple objectives, locational specificity requirements and product even-flow constraints in landscape-level management planning problems. This may contribute to enhancing the analysis of tradeoffs between ecosystem services in large-scale problems and help forest managers address effectively the demand for forest products while sustaining the provision of services in participatory management planning processes.
Evaluating the Recreation Value of Alishan National Forest Recreation Area in Taiwan
Authors: Liu Wan-Yu , Fang Bo-Sheng , Hsieh Chi-Ming
Published: September 2021

This study aimed to construct an effective model to estimate the recreation value and total annual recreation benefits of the Alishan National Forest Recreation Area (ANFR) through the travel cost method. Negative binomial regression was also employed to estimate the demand function. This study sorted participants based on gender, age, level of education, personal monthly income, occupation, and place of residence to examine their differences in perceived recreation value and recreation demand. The survey responses revealed that most tourists were mainly middle aged, and took family vacations. The findings indicate that the recreation benefits of traveling to Alishan per person each year equaled NTD 1703. Furthermore, the annual recreation benefits of Alishan were approximately between NTD 2,157,121,944 and NTD 2,452,136,112 based on a total of 1,353,276 visits traveling to Alishan in 2019. Recommendations and suggestions are drawn for ANFR based the results.
Forest Resistance to Extended Drought Enhanced by Prescribed Fire in Low Elevation Forests of the Sierra Nevada
Authors: van Mantgem Phillip J. , Caprio Anthony C. , Stephenson Nathan L. , Das Adrian J.
Published: September 2021

Prescribed fire reduces fire hazards by removing dead and live fuels (small trees and shrubs). Reductions in forest density following prescribed fire treatments (often in concert with mechanical treatments) may also lessen competition so that residual trees might be more likely to survive when confronted with additional stressors, such as drought. The current evidence for these effects is mixed and additional study is needed. Previous work found increased tree survivorship in low elevation forests with a recent history of fire during the early years of an intense drought (2012 to 2014) in national parks in the southern Sierra Nevada. We extend these observations through additional years of intense drought and continuing elevated tree mortality through 2017 at Sequoia and Kings Canyon National Parks. Relative to unburned sites, we found that burned sites had lower stem density and had lower proportions of recently dead trees (for stems ≤47.5 cm dbh) that presumably died during the drought. Differences in recent tree mortality among burned and unburned sites held for both fir (white fir and red fir) and pine (sugar pine and ponderosa pine) species. Unlike earlier results, models of individual tree mortality probability supported an interaction between plot burn status and tree size, suggesting the effect of prescribed fire was limited to small trees. We consider differences with other recent results and discuss potential management implications including trade-offs between large tree mortality following prescribed fire and increased drought resistance.
Contribution of Urban Forests to the Ecosystem Service of Air Quality in the City of Santo Domingo, Dominican Republic
Authors: Bonilla-Duarte Solhanlle , González Claudia Caballero , Rodríguez Leonardo Cortés , Jáuregui-Haza Ulises Javier , García-García Agustín
Published: September 2021

A survey on pollutants that affect air quality was carried out at 27 points in the city of Santo Domingo, National District. The removal of air pollutants was estimated in relation to the city’s forest cover; using the iTree Canopy software. A principal components analysis and a correlation analysis was also performed to identify the association of these variables. The results show that the average percentage of green infrastructure in the sampling points was 26%. Also, positive correlation was identified between the presence of NO2 and SO2 at the sampling points. It was observed that the higher the presence of forest cover, the higher the concentration of CO and the lower the presence of pollutants. Although five hot spots were defined in terms of air pollution levels in the National District, the study does not show conclusive results regarding the relationship between green infrastructure and air quality in Santo Domingo. Results show that urban planning for environmental quality requires inter-institutional coordination, permanent ecological quality monitoring, and coordinated public policies to establish adequate indicators comparable to the World Health Organization standards.
Expression Patterns and Gene Analysis of the Cellulose Synthase Gene Superfamily in Eucalyptus grandis
Authors: Liu Guo , Xie Yaojian , Shang Xiuhua , Wu Zhihua
Published: September 2021

Cellulose is the world’s most abundant renewable energy resource, and a variety of cellulose synthase genes are involved in the biosynthesis of cellulose. In the process of cellulose synthesis, all cellulose synthases are interrelated and act synergistically. In this study, we analyzed the contents of cellulose, hemicellulose, and lignin in the different parts and tissues of E. grandis. The results showed that the cellulose content had greater differences among three different heights. On this basis, we carried out the transcriptome-wide profiling of gene expression patterns using RNA sequencing. A total of 2066 differentially expressed genes were identified for three pairwise comparisons between three different heights, most of which were related to the programmed photosynthetic membrane and photosystem. A total of 100 transcripts of CSs (58 CesA and 42 Csl) were obtained from transcriptome libraries. The expression pattern of these genes indicated that different CS genes had a wide range of expression profiles. A phylogenetic analysis of 135 reference CS genes showed that the CSs of E. grandis were clustered into six major groups (CesA1-9, CslA, CslB/H, CslD, CslE, and CslG). Based on the weighted gene co-expression network analysis, a dual-directional regulation mechanism between Csl and CesA proteins in the cellulose biosynthesis was identified. The gene expression profile analysis, using qRT-PCR in different tissues of E. grandis, demonstrated that the CSs were highly expressed in xylem, and CesAs had a higher relative expression than Csls. The analysis of sequence similarity combined with the expression pattern indicated that the CesA1, 3, and 6 transcripts were associated with the biosynthesis of the secondary cell wall, and CesA4, 5, and 7 transcripts were more likely to associate with the biosynthesis of the primary cell wall. Finally, the qRT-PCR analysis confirmed the expression of 11 selected CSs in three different parts of E. grandis.
Physiological and Genetic Analysis of Leaves from the Resprouters of an Old Ginkgo biloba Tree
Authors: Yan Jiali , Zhang Sixuan , Tong Miaomiao , Lu Jinkai , Wang Tongfei , Xu Yuan , Li Weixing , Wang Li
Published: September 2021

Ginkgo biloba is a well-known long-lived tree with important economical, ornamental and research value. New stems often resprout naturally from the trunk or roots of old trees to realize rejuvenation. However, the physiological and molecular mechanisms that underlie the resprouting from old trees are still unknown. In this study, we investigated a 544-year-old female ginkgo tree with vigorous resprouters along the trunk base in Yangzhou, China. We compared the morphological and physiological traits of leaves between resprouters (SL) and old branches (OL) and found a significantly higher thickness, fresh weight, and water content in SL. In particular, the depth and number of leaf lobes were dramatically increased in SL, suggesting the juvenile characteristics of sprouters in old ginkgo trees. Transcriptome data showed that the expression of genes related to photosynthetic capacity, the auxin signaling pathway, and stress-associated hormones was upregulated in SL. Importantly, levels of the most important secondary metabolites, including kaempferol, isorhamnetin, ginkgolide A, ginkgolide B, and ginkgolide C, were significantly higher in SL. We also identified high expression of key genes in SL, such as PAL and FLS, which are involved in flavonoid synthesis, and GGPS, which is involved in the synthesis of terpene lactones. These findings reveal the distinct physiological and molecular characteristics as well as secondary metabolite synthesis in leaves of resprouting stems in old ginkgo trees, providing new insight into rejuvenation physiology in old tree aging.
Pretreatment of Corn Stover Using an Extremely Low-Liquid Ammonia (ELLA) Method for the Effective Utilization of Sugars in Simultaneous Saccharification and Fermentation (SSF) of Ethanol
Authors: Le Tin Diep Trung , Nguyen Truong Vi Phuong , Ngo My Thi Tra , Kim Tae Hyun , Oh Kyeong Keun
Published: September 2021

Extremely low-liquid ammonia (ELLA) pretreatment using aqueous ammonia was investigated in order to enhance the enzymatic saccharification of corn stover and subsequent ethanol production. In this study, corn stover was treated with an aqueous ammonia solution at different ammonia loading rates (0.1, 0.2, and 0.3 g NH3/g biomass) and various liquid-to-solid (L/S) ratios (0.55, 1.12, and 2.5). The ELLA pretreatment was conducted at elevated temperatures (90–150 °C) for an extended period (24–120 h). Thereafter, the pretreated material was saccharified by enzyme digestion and subjected to simultaneous saccharification and fermentation (SSF) tests. The effects of key parameters on both glucan digestibility and xylan digestibility were analyzed using analysis of variance (ANOVA). Under optimal pretreatment conditions (L/S = 2.5, 0.1 g-NH3/g-biomass, 150 °C), 81.2% glucan digestibility and 61.1% xylan digestibility were achieved. The highest ethanol yield achieved on the SSF tests was 85.4%. The ethanol concentration was 14.5 g/L at 96 h (pretreatment conditions: liquid-to-solid ratio (L/S) = 2.5, 0.1 g-NH3/g-biomass, 150 °C, 24 h. SSF conditions: microorganism Saccharomyces cerevisiae (D5A), 15 FPU/g-glucan, CTech2, 3% w/v glucan, 37 °C, 150 rpm).
Evaluation on the Effect of Fishery Insurance Policy: Evidence Based on Text Mining
Authors: Wei Xinyi , Hu Qiuguang , Ma Jintao
Published: September 2021

As a quasi-public product, fishery insurance has become an important starting point for the construction of the modern fishery industry chain, supply chain and value chain risk management mechanism. We used visual data processing methods and text mining technology to screen policy samples. We then built a fishery insurance policy evaluation system based on the Policy Modeling Consistency (PMC) index model. We combined the PMC index score and PMC surface to quantitatively analyze the policy samples. This paper has four important findings: (1) After three adjustments and developments, the fishery insurance policy has grown in terms of initial attention, changes, and development and gradually matured. (2) A gap exists between the content of the fishing insurance policy text and the actual demand. The scoring results of the policy samples are concentrated in the acceptable range, the policy effects are not satisfactory, and the formulation of fishery insurance policies has weak links that need to be improved. (3) The consistency and effectiveness of fishery insurance policies have developed simultaneously with fishery insurance research, and the practical effects of high-quality fishery insurance policies are conducive to the development of theoretical research. (4) The policy text of fishery insurance has major problems, such as missing joint force of issuing institutions, low professionalism of the text, inadequate subdivision guidance of fishery insurance, weak social effectiveness, high dependence on financial subsidies, lack of incentive sustainability and corresponding laws and regulations and reduction in policy feasibility among others. Considering the above issues, this paper puts forward relevant policy optimization paths and safeguard measures on the basis of giving priority to greater absolute value.
The Role of Sensory Perception in Consumer Demand for Tinned Meat: A Contingent Valuation Study
Authors: Vecchiato Daniel , Torquati Biancamaria , Venanzi Sonia , Tempesta Tiziano
Published: September 2021

This study presents an analysis of consumer preferences for a new food product: Tinned Chianina meat. Respondents (N = 249) participated in a sensory test, where they were also asked to declare their willingness to pay (WTP) for the tasted product. The WTP data were collected after the sensory test by means of the contingent valuation method using a payment card elicitation format. Data were analysed with Cragg’s double-hurdle model to understand which factors influenced market participation (WTP > 0) and then the variables that influenced the declared WTP. According to our results, sensory perception played a key role in explaining both participation in the market and the magnitude of the expressed WTP. Moreover, we found that the sensory aspects have a different effect on the decision to participate in the market and on the magnitude of the expressed WTP. Smell and flavour are the most important in determining the probability of entering the market, while texture has the greatest impact on the declared WTP.
3D Printing of Shiitake Mushroom Incorporated with Gums as Dysphagia Diet
Authors: Liu Zhenbin , Bhandari Bhesh , Guo Chaofan , Zheng Wenqi , Cao Shangqiao , Lu Hongyu , Mo Haizhen , Li Hongbo
Published: September 2021

With the speeding tendency of aging society, the population experienced dysphagia is increasing quickly. Desirable dysphagic diets should be safe, visually appealing and nutritious. 3D printing allows for creation of personalized nutritious foods with regular-like appearance. Shiitake mushroom, rich in protein and bioactive compounds, is suitable for elderly, but its hard texture was not friendly to the elderly with dysphagia. This study investigated the feasibility of production of dysphagic product using shiitake mushroom by 3D printing with various gums addition, including arabic gum (AG), xanthan gum (XG) and k-carrageenan gum (KG) at concentrations of 0.3%, 0.6% and 0.9% (w/w). Data suggested that XG and KG incorporation significantly increased inks’ mechanical strength by decreasing water mobility and promoting the formation of hydrogen bond, enabling 3D printed objects with great self-supporting capacity. The XG containing and KG-0.3% samples were categorized into level 5—minced and moist dysphagia diet within international dysphagia diet standardization initiative (IDDSI) framework. AG addition decreased mechanical strength and viscosity, hardness and self-supporting capacity of 3D printed constructions. AG-0.3% and AG-0.6% samples could not be classified as dysphagia diets based on IDDSI tests. This study provides useful information for dysphagia diet development with appealing appearance by 3D printing.
On Weighted (k, s)-Riemann-Liouville Fractional Operators and Solution of Fractional Kinetic Equation
Authors: Samraiz Muhammad , Umer Muhammad , Kashuri Artion , Abdeljawad Thabet , Iqbal Sajid , Mlaiki Nabil
Published: September 2021

In this article, we establish the weighted (k,s)-Riemann-Liouville fractional integral and differential operators. Some certain properties of the operators and the weighted generalized Laplace transform of the new operators are part of the paper. The article consists of Chebyshev-type inequalities involving a weighted fractional integral. We propose an integro-differential kinetic equation using the novel fractional operators and find its solution by applying weighted generalized Laplace transforms.
Genetic Diversity of Microneme Protein 2 and Surface Antigen 1 of Eimeria tenella
Authors: Võ Tuấn Cường , Naw Haung , Flores Rochelle A. , Lê Hương Giang , Kang Jung-Mi , Yoo Won Gi , Kim Woo-Hyun , Min Wongi , Na Byoung-Kuk
Published: September 2021

Avian coccidiosis is a disease caused by members of the genus Eimeria. Huge economic losses incurred by the global poultry industry due to coccidiosis have increased the need for cost-effective and easily available recombinant vaccines. Microneme protein 2 (MIC2) and surface antigen 1 (SAG1) of E. tenella have been recognised as potential vaccine candidates. However, the genetic diversity of the antigens in field isolates, which affects vaccine efficacy, has yet to be largely investigated. Here, we analysed genetic diversity and natural selection of etmic2 and etsag1 in Korean E. tenella isolates. Both genes exhibited low levels of genetic diversity in Korean isolates. However, the two genes showed different patterns of nucleotide diversity and amino acid polymorphism involving the E. tenella isolates obtained from different countries including China and India. These results underscore the need to investigate the genetic diversity of the vaccine candidate antigens and warrant monitoring of genetic heterogeneity and evolutionary aspects of the genes in larger numbers of E. tenella field isolates from different geographical areas to design effective coccidial vaccines.
Stabilization of the Lower Jamuna River in Bangladesh—Hydraulic and Morphological Assessment
Authors: Giri Sanjay , Thompson Angela , Donchyts Gennady , Oberhagemann Knut , Mosselman Erik , Alam Jahangir
Published: September 2021

This paper presents a hydraulic and morphological analysis of the Lower Jamuna in Bangladesh with a focus on two key bifurcations that are important for stabilization of the Lower Jamuna reach. We used ground measurements, historical data, multispectral satellite images from various sources as well as numerical models. We carried out hydraulic analyses of the changes and their peculiarities, such as flow distributions at the bifurcation and hysteresis of the stage–discharge relationships. We supplemented our analysis by using numerical models to simulate discharge distribution at the bifurcations under various flow and riverbed conditions. We developed an advanced and automated satellite image processing application for the Lower Jamuna, referred to as Morphology Monitor (MoMo), using the Google Earth Engine. MoMo was found to be an effective tool for a rapid assessment and analysis of the changes in deep-channel and sandbar areas. It is also useful for monitoring and assessing riverbank and char erosion and accretion, which is important not only for morphological but also ecological impact assessment. The application can be adapted as an operational tool as well. Furthermore, we assessed the evolution of deep channels at the bifurcations based on regularly and extensively measured bathymetry data. The analysis was carried out in complement with morphological modeling, particularly for short-term prediction. In this paper we present the major findings of the analysis and discuss their implications for adaptive river management.
Inter-Professional Collaboration and Occupational Well-Being of Physicians Who Work in Adverse Working Conditions
Authors: Viruez-Soto José , Delgado Bolton Roberto C. , San-Martín Montserrat , Vivanco Luis
Published: September 2021

Inter-professional collaboration, empathy and lifelong learning, components of medical professionalism, have been associated with occupational well-being in physicians. However, it is not clear whether this role persists in adverse working conditions. This study was performed to assess whether this is the case. These three abilities, and the self-perception of somatization, exhaustion and work alienation, were measured in a sample of 60 physicians working in a hospital declared to be in an institutional emergency. A multiple regression model explained 40% of the variability of exhaustion, with a large effect size (Cohen’s-f2 = 0.64), based on a linear relationship with teamwork (p = 0.01), and more dedication to academic (p < 0.001) and management activities (p < 0.003). Neither somatization nor alienation were predicted by empathy or lifelong learning abilities. Somatization, exhaustion, or alienation scores either explained empathy, inter-professional collaboration or lifelong learning scores. These findings indicate that, in adverse working environments, physicians with a greater sense of inter-professional collaboration or performing multi-task activities are more exposed to suffering exhaustion.
Factors Associated with Burden in Caregivers of Patients with End-Stage Kidney Disease (A Systematic Review)
Authors: Alshammari Bushra , Noble Helen , McAneney Helen , Alshammari Farhan , O’Halloran Peter
Published: September 2021

Background: Caring for a patient with end-stage kidney disease (ESKD) is highly stressful and can impact negatively on the physical and psychological well-being of caregivers. To accurately assess caregiver burden (CB), health care providers (HCPs) need to identify characteristics associated with an increase in CB. Aim: The aim of this review is to explore CB in caregivers of adult patients with ESKD and to identify characteristics associated with any increase in CB. Method: A comprehensive literature search was completed using five electronic databases. Medline, Embase, CINHAL, PsycINFO, and Scopus. The Joanna Briggs Institute checklist (JBI) was used to quality appraise full text papers included in the review. No time limit for the date of publication of studies was employed, to enable the inclusion of more extensive literature. Results: A total of 38 relevant studies from 18 countries were identified and included in the review. A variety of patient and caregiver factors can impact positively or negatively on CB, including socio-demographic factors of patients and caregivers, disease-related factors, situational and relational factors, environmental factors, and psychological factors. Conclusion: This review provides awareness to HCPs of the important factors associated with CB, when assessing or targeting interventions for caregivers experiencing burden.
Protocol for the Analysis of Cross-Sections from Gilded Surfaces
Authors: Burgio Lucia , Gregory Thomas
Published: September 2021

This paper describes the protocol currently used at the Victoria and Albert Museum for the scientific analysis of water, oil and lacquer gilding in cultural heritage objects. The purpose of the protocol is to guide scientists, curators and conservators in their routine investigations, and address questions about the characteristics of gilded surfaces, their number, sequence, date, composition and stratigraphic details. Each protocol step is described in detail and is accompanied by practical examples taken from the analysis of an 18th-century Chippendale table and the 20th-century statue of the Spirit of Gaiety. The merits of individual analytical techniques and equipment are also evaluated.
Extending Shelf Life and Maintaining Quality of Tomato Fruit by Calcium Chloride, Hydrogen Peroxide, Chitosan, and Ozonated Water
Authors: Shehata Said A. , Abdelrahman Said Z. , Megahed Mona M. A. , Abdeldaym Emad A. , El-Mogy Mohamed M. , Abdelgawad Karima F.
Published: September 2021

Tomatoes are perishable fruit that makes them deteriorate rapidly during the post-harvest chain. Therefore, the effect of calcium chloride (CaCl2), chitosan, hydrogen peroxide (H2O2), and ozonated water on the storage abil\ity and quality of tomato fruit (Solanumlycopersicum L. cv. 448) stored at 10 °C for 28 d was studied. Weight loss, firmness, fruit color, total soluble solids (TSS), titratable acidity, total carotenoids, and ascorbic acid content (AsA) of treated tomato fruit were recorded. Our results revealed that all tested treatments significantly extended the shelf-life and maintained quality of tomato fruit compared to the control. Chitosan and CaCl2 were the most effective treatments in maintaining quality attributes. Furthermore, a correlation study suggested that AsA and total carotenoids played a vital role in conserving tomato fruit quality during storage. PC1 had strong positive loading for pH, appearance, firmness, AsA, TSS, carotene, fruit color (L* & b*) and a strong negative loading for lycopene content, color (a), weight loss, and color index. PC2 had high positive loading for total acidity and total sugar content.
Racial Disparities in Health Risk Indicators Reported by Alabamians Diagnosed with COPD
Authors: Stellefson Michael , Wang Min-Qi , Kinder Caitlin
Published: September 2021

Chronic Obstructive Pulmonary Disease (COPD) is a growing public health problem in the southern United States, particularly in Alabama. However, very little is known about specific health risk factors disproportionately impacting Alabamians with COPD. We conducted a latent class analysis of 2015–2019 Behavioral Risk Factor Surveillance System data from 4057 Alabamians with COPD (White = 2947, Black = 873, Other = 237). Eighteen risk indicators were examined across three health-related domains: (1) comorbidities, (2) limited healthcare access, and (3) substance use/abuse. Racial disparities between Black and white Alabamians with COPD were assessed using configural similarity analysis. Findings showed that almost one-third (31%) of Alabamians with COPD were in the high-risk class for eight comorbidities, and nearly one-half (48.88%) belonged to the high-risk class for limited healthcare access. Black Alabamians with COPD who did not have health insurance were much more likely to be at high risk for limited healthcare access (94.44%) when compared to their counterparts with insurance (5.56%), χ2(df = 2) = 1389.94, p < 0.0001. Furthermore, the proportion of high-risk, uninsured Black Alabamians with COPD (94.44%) substantially exceeded the percentage of high-risk, uninsured white Alabamians with COPD (59.70%). Most Alabamians with COPD (82.97%) were at low risk for substance use/abuse. Future research should explore new mechanisms for facilitating better healthcare access among high-risk Alabamians living with COPD and other prevalent comorbidities. Greater attention should be focused on Black Alabamians with COPD who cannot afford adequate health insurance.
Association between Physical Activity and Sleep Difficulties among Adolescents in Germany: The Role of Socioeconomic Status
Authors: Blume Miriam , Rattay Petra
Published: September 2021

We examined sleep difficulties among adolescents in Germany and the association with physical activity (PA). Furthermore, we analyzed whether the association varied with the socioeconomic status (SES) among adolescent girls and boys in Germany. Using data from the German Health Interview Examination Survey for Children and Adolescents (KiGGS) study (Wave 2), 6599 adolescents aged 11 to 17 years were included in the analyses. We conducted sex-stratified logistic regression analyses. Dependent variables were unrecommended sleep duration (defined as a duration of sleep that does not meet the recommended duration), sleep-onset difficulties, trouble sleeping, and daytime sleepiness. Most adolescent girls and boys reported sleep difficulties. While no associations between PA and sleep difficulties were observed, a significant interaction between PA and SES was found for sleep duration in boys and daytime sleepiness in girls. Thus, adolescents with low SES had fewer sleep difficulties if they met the recommendation for PA, compared with those in other SES groups. In Germany, a large proportion of adolescents have sleep difficulties. We found that the experience of sleep difficulties varied according to PA, sex, and the family SES. Future sleep promotion programs should consider these differences.
Digital Citizen Science for Responding to COVID-19 Crisis: Experiences from Iran
Authors: Vahidi Hossein , Taleai Mohammad , Yan Wanglin , Shaw Rajib
Published: September 2021

The Coronavirus Disease 2019 (COVID-19) pandemic has so far been the most severe global public health emergency in this century. Generally, citizen science can provide a complement to authoritative scientific practices for responding to this highly complex biological threat and its adverse consequences. Several citizen science projects have been designed and operationalized for responding to COVID-19 in Iran since the infection began. However, these projects have mostly been overlooked in the existing literature on citizen science. This research sheds light on the most significant online citizen science projects to respond to the COVID-19 crisis in Iran. Furthermore, it highlights some of the opportunities and challenges associated with the strengths and weaknesses of these projects. Moreover, this study captures and discusses some considerable insights and lessons learned from the failures and successes of these projects and provides solutions to overcome some recognized challenges and weaknesses of these projects. The outcomes of this synthesis provide potentially helpful directions for current and future citizen science projects—particularly those aiming to respond to biological disasters such as the COVID-19 pandemic.
From Clinical Practice to the Classroom. Advantages and Disadvantages of Video and Paper Cases on the Motivation and Clinical Reasoning of Occupational Therapy Students
Authors: Rodríguez-Bailón María , Fernández-Solano Ana Judit , Merchán-Baeza Jose Antonio , Vidaña-Moya Laura
Published: September 2021

Case-based learning enables the application of theory to practice using real-life patient cases. The present study aims to compare the effect between video cases and paper cases on motivation for learning and knowledge acquisition to perform a clinical reasoning case exercise by occupational therapy students. A mixed-methods design was used with 120 students randomized into two groups. All students conducted a clinical reasoning case exercise on the same case, although in different presentation formats: paper case and video case. The quantitative measures of this study were the scores of motivation for learning from the Instructional Material Motivation Survey and the grades of a clinical reasoning case exercise. The qualitative part was based on the positive and negative aspects perceived by the participants. The results showed that the motivation for learning was significantly higher for the video case compared to the paper case, although there were no differences in the grades of the clinical reasoning case exercise between the two groups. The video cases were perceived as more relevant to professional practice and more informative in terms of non-verbal communication and context. In light of the results, teachers could use these two formats of presentation of cases with different objectives.
Temporal Geospatial Analysis of COVID-19 Pre-Infection Determinants of Risk in South Carolina
Authors: Lyu Tianchu , Hair Nicole , Yell Nicholas , Li Zhenlong , Qiao Shan , Liang Chen , Li Xiaoming
Published: September 2021

Disparities and their geospatial patterns exist in morbidity and mortality of COVID-19 patients. When it comes to the infection rate, there is a dearth of research with respect to the disparity structure, its geospatial characteristics, and the pre-infection determinants of risk (PIDRs). This work aimed to assess the temporal–geospatial associations between PIDRs and COVID-19 infection at the county level in South Carolina. We used the spatial error model (SEM), spatial lag model (SLM), and conditional autoregressive model (CAR) as global models and the geographically weighted regression model (GWR) as a local model. The data were retrieved from multiple sources including USAFacts, U.S. Census Bureau, and the Population Estimates Program. The percentage of males and the unemployed population were positively associated with geodistributions of COVID-19 infection (p values < 0.05) in global models throughout the time. The percentage of the white population and the obesity rate showed divergent spatial correlations at different times of the pandemic. GWR models fit better than global models, suggesting nonstationary correlations between a region and its neighbors. Characterized by temporal–geospatial patterns, disparities in COVID-19 infection rate and their PIDRs are different from the mortality and morbidity of COVID-19 patients. Our findings suggest the importance of prioritizing different populations and developing tailored interventions at different times of the pandemic.
Spatial Analysis of Citizens’ Environmental Complaints in China: Implications in Environmental Monitoring and Governance
Authors: Ji Xuepeng , Tong Daoqin , Cheng Lisha , Chuai Xiaowei , Mao Xiyan , Liu Binglin , Huang Xianjin
Published: September 2021

Citizen environmental complaints play a key role in China’s current environmental monitoring network and environmental governance system. Based on 5796 cases of environmental complaints lodged by citizens via hotline and the internet to the MEP of China, we examined the spatial characteristics and influencing factors of citizen complaints for the period of 2013–2017 using spatial analysis methods and spatial econometric models. The roles of citizen complaints in the two systems were then reevaluated. The results show that, among all cases, 75.88% of cases were identified as verified complaints, while nearly a 25% noisy rate directed large amounts of inspection resources to be utilized in response to nonverified cases. Air pollution received the most attention by citizens in China, accounting for 67.22% of total cases. The hotspots of citizen complaints were mostly distributed in the three major national urban agglomerations in China. We found that industrial wastewater and SO2 were positively associated with the likelihood of citizens filing complaints, while the effect of industrial soot/dust emission was insignificant. Citizen complaints might be triggered by certain, but not all, forms of pollutants, even though highly visible particulate pollutants did not necessarily induce corresponding complaints. Moreover, the negative relationship between citizen complaints and per capita GDP revealed the unbalanced geographical pattern between economical development and environmental quality. The proliferation of the internet greatly facilitated citizens lodging complaints through various ways. The synergy mechanism between citizen environmental complaints and other parts in China’s environmental monitoring and governance system should be established in the future.
Psychological Distress and Work Environment Perception by Physical Therapists from Southern Italy during COVID-19 Pandemic: The C.A.L.A.B.R.I.A Study
Authors: de Sire Alessandro , Marotta Nicola , Raimo Simona , Lippi Lorenzo , Inzitari Maria Teresa , Tasselli Anna , Gimigliano Alessandra , Palermo Liana , Invernizzi Marco , Ammendolia Antonio
Published: September 2021

The psychosocial impact of the work environment during the COVID-19 pandemic on health professionals is a growing issue. The present study examined specific psychosocial work environment indicators during the COVID-19 pandemic, through a multiple regression model of a self-administered cross-sectional online survey in a cohort of physical therapists from a region of Southern Italy from March 2020 to May 2021. The questionnaire contained items on work and healthcare issues related to COVID-19. Eighty physical therapists (29 male and 51 female), mean age 32.5 ± 10.1 years, were involved in this survey. The multiple regression analysis showed that “management activity” was significantly correlated to “therapist frustration” during the COVID-19 pandemic (ΔR2 = 0.16; p < 0.03). Findings of this study underline the importance of a healthy psychosocial work environment to enhance job satisfaction of all health professionals and to avoid role conflict and burnout syndrome during the COVID-19 pandemic.