bluuebunny/crossref_metadata_2025 huggingface dataset:
Overview of the Fundamentals and Applications of Bifacial Photovoltaic Technology: Agrivoltaics and Aquavoltaics
Authors: Mouhib Elmehdi , Micheli Leonardo , Almonacid Florencia , Fernández Eduardo
Published: November 2022

Bifacial technology is attracting the attention of the photovoltaic community. Although considered premature, research and development activities still need to be carried out to improve bPV performance. In addition, the need for a standard test reference will aid bankability and increase confidence in this technology. This article describes the state of the art of bifacial technology, going through the bPV cell and its difference compared to conventional monofacial cells and listing the different sources of limitations, with an identification of different parameters that characterize the performance of the bifacial. Then, the paper reviews the different modeling methods that allow predicting the performance of bPV systems, and ends with the most important applications, whether for dual use of land to produce energy and food (agrivoltaic) or for placing bPV modules on water bodies instead of on the ground (aquavoltaics), or for vertical use as solar fences, acoustic barriers, or building-integrated photovoltaic modules.
Critical Reliability Improvement Using Q-Learning-Based Energy Management System for Microgrids
Authors: Maharjan Lizon , Ditsworth Mark , Fahimi Babak
Published: November 2022

This paper presents a power distribution system that prioritizes the reliability of power to critical loads within a community. The proposed system utilizes reinforcement learning methods (Q-learning) to train multi-port power electronic interface (MPEI) systems within a community of microgrids. The primary contributions of this article are to present a system where Q-learning is successfully integrated with MPEI to reduce the impact of power contingencies on critical loads and to explore the effectiveness of the subsequent system. The feasibility of the proposed method has been proven through simulation and experiments. It has been demonstrated that the proposed method can effectively improve the reliability of the local power system—for a case study where 20% of the total loads are classified as critical loads, the system average interruption duration index (SAIDI) has been improved by 75% compared to traditional microgrids with no load schedule.
A Data-Efficient Building Electricity Load Forecasting Method Based on Maximum Mean Discrepancy and Improved TrAdaBoost Algorithm
Authors: Li Kangji , Wei Borui , Tang Qianqian , Liu Yufei
Published: November 2022

Building electricity load forecasting plays an important role in building energy management, peak demand and power grid security. In the past two decades, a large number of data-driven models have been applied to building and larger-scale energy consumption predictions. Although these models have been successful in specific cases, their performances would be greatly affected by the quantity and quality of the building data. Moreover, for older buildings with sparse data, or new buildings with no historical data, accurate predictions are difficult to achieve. Aiming at such a data silos problem caused by the insufficient data collection in the building energy consumption prediction, this study proposes a building electricity load forecasting method based on a similarity judgement and an improved TrAdaBoost algorithm (iTrAdaBoost). The Maximum Mean Discrepancy (MMD) is used to search similar building samples related to the target building from public datasets. Different from general Boosting algorithms, the proposed iTrAdaBoost algorithm iteratively updates the weights of the similar building samples and combines them together with the target building samples for a prediction accuracy improvement. An educational building’s case study is carried out in this paper. The results show that even when the target and source samples belong to different domains, i.e., the geographical location and meteorological condition of the buildings are different, the proposed MMD-iTradaBoost method has a better prediction accuracy in the transfer learning process than the BP or traditional AdaBoost models. In addition, compared with other advanced deep learning models, the proposed method has a simple structure and is easy for engineering implementation.
Virtual Collection for Distributed Photovoltaic Data: Challenges, Methodologies, and Applications
Authors: Ge Leijiao , Du Tianshuo , Li Changlu , Li Yuanliang , Yan Jun , Rafiq Muhammad
Published: November 2022

In recent years, with the rapid development of distributed photovoltaic systems (DPVS), the shortage of data monitoring devices and the difficulty of comprehensive coverage of measurement equipment has become more significant, bringing great challenges to the efficient management and maintenance of DPVS. Virtual collection is a new DPVS data collection scheme with cost-effectiveness and computational efficiency that meets the needs of distributed energy management but lacks attention and research. To fill the gap in the current research field, this paper provides a comprehensive and systematic review of DPVS virtual collection. We provide a detailed introduction to the process of DPVS virtual collection and identify the challenges faced by virtual collection through problem analogy. Furthermore, in response to the above challenges, this paper summarizes the main methods applicable to virtual collection, including similarity analysis, reference station selection, and PV data inference. Finally, this paper thoroughly discusses the diversified application scenarios of virtual collection, hoping to provide helpful information for the development of the DPVS industry.
Agricultural and Forestry Biomass for Meeting the Renewable Fuel Standard: Implications for Land Use and GHG Emissions
Authors: Wang Weiwei
Published: November 2022

Agricultural land and forestland are considered as two largest potential biomass sources for meeting the Renewable Fuel Standard (RFS) mandate for cellulosic biofuels. However, the land use change and greenhouse gas (GHG) savings with both agricultural and forest biomass production are yet to be examined systematically. This paper examines the effects of implementing a 16-billion gallon (60 billion liters) cellulosic biofuel mandate by 2035 on the mix of agricultural and forest biomass, land use change and GHG emissions by using a dynamic partial equilibrium model of the agricultural, forestry and transportation sectors in the US. Our results show that crop residues play a significant role in supplying cellulosic ethanol before 2030, while energy crops are the major feedstocks used for meeting the RFS cellulosic mandate after 2030. Milling and logging residues are economically viable supplements to agricultural biomass for cellulosic ethanol production, though their role in total biomass is small. Across different scenarios of cellulosic ethanol mandate that can be met with either agricultural biomass only or with both agricultural and forest biomass, we find GHG savings from displacing the gasoline range from 0.61 to 0.82 B MgCO2e over the 2015–2035 period. Induced land use change effects associated with expanded feedstock production are modest between and within the agricultural and forestry sectors. We conclude that a mixed feedstock base maximizes the economic and environmental benefits of cellulosic biofuel production. The mitigation potential of cellulosic biofuels is severalfold larger than natural-based solutions such as grassland restoration.
The Impact of M&As on the Competitive Positioning of European Energy Firms and Market Power Concentration on EU National Energy Markets
Authors: Wasilewska Natalia , Wasilewski Mirosław , Zabolotnyy Serhiy , Osiichuk Dmytro
Published: November 2022

By studying M&A deals completed by European energy and power companies between 2002 and 2021, the paper inquires into the impact of corporate consolidation on the competitive positioning of individual energy firms and the concentration of market power on the national energy markets in the EU countries. Our evidence suggests that the European energy market may be moving towards a greater concentration of market power as market leaders are shown to primarily acquire their peers from national markets, while outsiders are more likely to diversify into non-energy sectors, which may further endanger their competitive positioning in the future. We also find that M&As allow energy and power companies to substantially increase their market share within national markets. The said impact is stronger in case of cross-border deals, including those within and outside of the EU. At the same time, only cross-border deals are associated with sufficiently strong revenue growth to advance firms’ relative positioning within national markets. The relative positioning of firms in the EU market remains unaffected by M&A activities, which may be indicative of extreme rigidity and segmentation of the EU market. While at the country level, M&As are found to contribute to a reduction in market concentration measured by a number of indicators, this negative link is documented to be entirely driven by non-core acquisitions involving targets from non-energy industries.
An Improved Transformer Framework for Well-Overflow Early Detection via Self-Supervised Learning
Authors: Yi Wan , Liu Wei , Fu Jiasheng , He Lili , Han Xiaosong
Published: November 2022

Oil drilling has always been considered a vital part of resource exploitation, and during which overflow is the most common and tricky threat that may cause blowout, a catastrophic accident. Therefore, to prevent further damage, it is necessary to detect overflow as early as possible. However, due to the unbalanced distribution and the lack of labeled data, it is difficult to design a suitable solution. To address this issue, an improved Transformer Framework based on self-supervised learning is proposed in this paper, which can accurately detect overflow 20 min in advance when the labeled data are limited and severely imbalanced. The framework includes a self-supervised pre-training scheme, which focuses on long-term time dependence that offers performance benefits over fully supervised learning on downstream tasks and makes unlabeled data useful in the training process. Next, to better extract temporal features and adapt to multi-task training process, a Transformer-based auto-encoder with temporal convolution layer is proposed. In the experiment, we used 20 min data to detect overflow in the next 20 min. The results show that the proposed framework can reach 98.23% accuracy and 0.84 F1 score, which is much better than other methods. We also compare several modifications of our framework and different pre-training tasks in the ablation experiment to prove the advantage of our methods. Finally, we also discuss the influence of important hyperparameters on efficiency and accuracy in the experiment.
Multi-Parameter Optimization of Heat Dissipation Structure of Double Disk Magnetic Coupler Based on Orthogonal Experimental Design
Authors: Wang Shuang , Ma Xin , Hu Zeyong , Sun Shousuo
Published: November 2022

The existing heat dissipation research on double disk magnetic couplers ignores the coupling influence of electromagnetic temperature–stress and other multiphysics fields, and the error between the calculation and analysis results and the measured values is large. Therefore, a multi-parameter optimization method for heat dissipation structures of double disk magnetic couplers based on orthogonal experimental design is proposed. Based on the double disk magnetic coupler model, a three-dimensional finite element model based on fluid–solid–heat coupling is established, with the axial air gap length, input motor speed, the thickness of the permanent magnet in the magnetizing direction, the thickness of the copper plate, the number of fins of the heat dissipation plate and the length of the fins of the heat dissipation plate as design variables. Six-factor and three-level simulation experiments are designed with the minimum temperature of the heat dissipation plate as the objective function, and additionally, orthogonal experiments were designed according to the actual working conditions by selecting the optimal combination of parameters and modifying the model to perform physical tests. The results show that the variables that have the most significant impact on heat dissipation performance from high to low are as follows: axial air gap length, input motor speed, the length of the fins of the heat dissipation plate, the thickness of the permanent magnet in the magnetizing direction, the number of fins of the heat dissipation plate and the thickness of the copper plate. The increase in axial air gap length can effectively reduce the temperature rise, and the maximum decrease can reach 9.76%. Under the same conditions, the input motor speeds are set to 300 r/min, 400 r/min, 500 r/min, 600 r/min and 700 r/min, respectively, and the simulation results are in good agreement with the physical test results, with a maximum error of 4.8%. The error between the simulation result and the physical test result is only 1.9% under the optimal combination of parameters obtained by the orthogonal experiment, which verifies the correctness of the optimization model. In conclusion, the study is of reference significance for the parameter optimization of the heat dissipation structure of the double disk magnetic coupler.
Impact of Environmental Factors on Short-Term Eye Strain Relief during COVID-19 Quarantine: A Pilot Study
Authors: Lu Yihao , Wang Jianan , Chen Jianhua , Yan Yufan , Zeng Haicong , Zhang Baowei , Ma Haohao , Hu Tingli
Published: November 2022

Some policies implemented during the pandemic extended the time that students spend on electronic devices, increasing the risk of physical and eye strain. However, the role of different environments on eye strain recovery has not been determined. We recruited 20 undergraduate students (10 males and 10 females) from a university in eastern China and explored the restoration effects of their eye strain in different types of spaces (wayside greenspace, a playground, a square, and woodland) on campus through scale measurements. The results showed that the eye strain of the students accumulated by 15 min of e-learning was significantly relieved after 10 min of greenspace exposure compared to the indoor environment, and the recovery effect varied depending on the type of landscape. The effect of eye strain relief was found to be positively correlated with temperature, wind speed, visible sky ratio, canopy density, tree density, and solar radiation intensity, while it was negatively correlated with relative humidity. These findings enrich the research on the restoration benefits of greenspaces and provide a basis for predicting the effect of different environments on the relief of eye strain.
Epigenetic and Genetic Variability in Contrasting Latitudinal Fagus sylvatica L. Provenances
Authors: Guevara María Ángeles , Sánchez-Gómez David , Vélez María Dolores , de María Nuria , Díaz Luis Miguel , Ramírez-Valiente José Alberto , Mancha José Antonio , Aranda Ismael , Cervera María Teresa
Published: November 2022

The adaptive capacity of a species and its population is determined by both genetic and epigenetic variation, which defines the potential for adaptive evolution and plastic response to environmental changes. In this study, we used Methylation Sensitive Amplified Polymorphism (MSAP) and Amplified Fragment Length Polymorphism (AFLP), similar genome-wide profiling techniques, to analyze the epigenetic and genetic variability in European beech provenances from Germany (DE), Spain (ES) and Sweden (SE), representing the latitudinal distribution of the species. In addition, we evaluated the effect of moderate water stress on cytosine methylation dynamics by comparing two latitudinal contrasting provenances. Our analysis revealed that trees from ES showed lower values of epigenetic and genetic diversity than those from DE and SE. Analyses of molecular variance for MSAPs and AFLPs showed that 16% and 15% of the among population variations were associated with epigenetic and genetic variation, respectively. The study of the effect of water stress on cytosine methylation dynamics in seedlings from ES and SE revealed no significant levels of epigenetic differentiation between well-watered and stressed plants. Only 2% of the epigenetic variation was explained by the watering regime in ES without changes in SE. The results support that DNA methylation may play a role in the local adaptation of Fagus sylvatica to environmental variation.
Nipa Sap Can Be Both Carbon and Nutrient Source for Acetic Acid Production by Moorella thermoacetica (f. Clostridium thermoaceticum) and Reduced Minimal Media Supplements
Authors: Nguyen Dung Van , Rabemanolontsoa Harifara
Published: November 2022

Nipa sap is an excellent microbial nutrient and carbon source since it contains essential minerals and vitamins, in addition to sugars. In this study, nipa sap was successfully fermented to acetic acid by the industrially important Moorella thermoacetica without additional trace metals, without inorganics, or without yeast extract. Although microbial growth kinetics differed from one nutrient condition to another, acetic acid concentrations obtained without trace metals, without inorganics, and without yeast extract supplements were in the same range as that with full nutrient, confirming that nipa sap is a good nutrient source for M. thermoacetica. Fermentations in vials and fermenters showed comparable acetic acid production trends but acetic acid concentrations were higher in fermenters. Upon economic analysis, it was found that the most profitable nutrient condition was without yeast extract. It reduced the cost of culture medium from $1.7 to only $0.3/L, given that yeast extract costs $281/kg, while nipa sap can be available from $0.08/kg. Minimal medium instead of the traditional complex nutrient simplifies the process. This work also opens opportunities for profitable anaerobic co-digestion and co-fermentation of nipa sap with other biomass resources where nipa sap will serve as an inexpensive nutrient source and substrate.
Mutual Relations between Texture and Aroma of Cooked Rice—A Pilot Study
Authors: Wang Zihan , Wang Jun , Chen Xu , Li Enpeng , Li Songnan , Li Cheng
Published: November 2022

Texture and aroma are two important attributes for the eating quality of cooked rice, but their mutual relations are not clear. Cooked rice with a desirable texture might suffer from a deteriorated aroma property. To better understand the relations between texture and aroma, six different rice varieties with desirable eating qualities have been selected, with their texture and aroma profile characterized by a texture analyzer and gas chromatography-ion mobility spectrometry, respectively. A large variance of textural attributes and a total number of 39 major volatile organic components were observed for these cooked rice varieties. Pearson correlation showed that the hardness of cooked rice was positively correlated with the content of E-2-hexenal, 2-hexanol-monomer, 1-propanol, and E-2-pentenal, while stickiness was positively correlated with 5-methyl-2-furanmethanol and dimethyl trisulfide. Possible underneath mechanisms were discussed for these relations. These results could help the rice industry to develop rice products with both desirable texture and aroma property.
Reintegration of Food Industry By-Products: Potential Applications
Authors: Eliopoulos Christos , Markou Giorgos , Langousi Ioanna , Arapoglou Dimitrios
Published: November 2022

Numerous studies have indicated that fruits and vegetables are considered as significant sources of bioactive compounds. The generated by-products, which are derived from the food industry, reveal similar or higher antioxidant activity. On the other hand, intense industrialization results in the production of large volumes of by-products, raising serious environmental issues. Therefore, this situation creates the necessity to develop new strategies in order to exploit the generated wastes, securing the ability to develop new high-added-value products. This review aims to summarize the exploitation of fruit wastes, namely, apple and citrus, as well as vegetable by-products which are derived from tomato, potato and carrot cultivation. All the aforementioned by-products have found wide applications in the development of new high-added-value products in the food and feed industry owing to their improved nutritional profiles. Furthermore, these wastes are characterized by a strong antioxidant activity, justifying their valorization in other fields such as cosmetics and pharmaceutical industries.
Effects on Cell Membrane Integrity of Pichia anomala by the Accumulating Excessive Reactive Oxygen Species under Ethanol Stress
Authors: Chen Yanru , Wan Yin , Cai Wenqin , Liu Na , Zeng Jiali , Liu Chengmei , Peng Hong , Fu Guiming
Published: November 2022

Ethanol stress to yeast is well recognized and exists widely during the brewing process of alcohol products. Pichia anomala is an important ester-producing yeast in the brewing process of Chinese Baijiu and other alcohol products. Therefore, it is of great significance for the alcohol products brewing industry to explore the effects of ethanol stress on the growth metabolism of P. anomala. In this study, the effects of ethanol stress on the growth, esters production ability, cell membrane integrity and reactive oxygen species (ROS) metabolism of P. anomala NCU003 were studied. Our results showed that ethanol stress could inhibit the growth, reduce the ability of non-ethyl ester compounds production and destroy the cell morphology of P. anomala NCU003. The results also showed that 9% ethanol stress produced excessive ROS and then increased the activities of antioxidant enzymes (superoxide dismutase, catalase, aseorbateperoxidase and glutathione reductase) compared to the control group. However, these increased antioxidant enzyme activities could not prevent the damage caused by ROS to P. anomala NCU003. Of note, correlation results indicated that high content of ROS could promote the accumulation of malondialdehyde content, resulting in destruction of the integrity of the cell membrane and leading to the leakage of intracellular nutrients (soluble sugar and protein) and electrolytes. These results indicated that the growth and the non-ethyl ester compounds production ability of P. anomala could be inhibited under ethanol stress by accumulating excessive ROS and the destruction of cell membrane integrity in P. anomala.
Development of Lipid Nanoparticles Containing Omega-3-Rich Extract of Microalga Nannochlorpsis gaditana
Authors: Blanco-Llamero Cristina , Galindo-Camacho Ruth M. , Fonseca Joel , Santini Antonello , Señoráns Francisco J. , Souto Eliana B.
Published: November 2022

Microalgae are described as a new source of a wide range of bioactive compounds with health-promoting properties, such as omega-3 lipids. This biomass product is gaining attention mainly due to its potential to accumulate different compounds depending on the species and environment, and it has been commonly recognized as a valuable nutraceutical alternative to fish and krill oils. In this work, we obtained the extract of the microalga Nannochloropsis gaditana, selected on the basis of its content of eicosapentaenoic acid (EPA) and glycolipids, which were determined using GC-MS and high-performance liquid chromatography (HPLC), respectively. To develop an oral formulation for the delivery of the extract, we used a 23 factorial design approach to obtain an optimal lipid nanoparticle formulation. The surfactant and solid lipid content were set as the independent variables, while the particle size, polydispersity index, and zeta potential were taken as the dependent variables of the design. To ensure the potential use of the optimum LN formulation to protect and modify the release of the loaded microalga extract, rheological and differential scanning calorimetry analyses were carried out. The developed formulations were found to be stable over 30 days, with an encapsulation efficiency over 60%.
Preparation of Bio-Based Aerogel and Its Adsorption Properties for Organic Dyes
Authors: Li Penghui , Yang Chi , Xu Xuewen , Miao Chen , He Tianjiao , Jiang Bo , Wu Wenjuan
Published: November 2022

The effective utilization of biomass and the purification of dye wastewater are urgent problems. In this study, a biomass aerogel (CaCO3@starch/polyacrylamide/TEMPO-oxidized nanocellulose, CaCO3@STA/PAM/TOCN) was prepared by combining nanocellulose with starch and introducing calcium carbonate nanoparticles, which exhibited a rich three-dimensional layered porous structure with a very light mass. Starch and nanocellulose can be grafted onto the molecular chain of acrylamide, while calcium carbonate nanopores can make the gel pore size uniform and have excellent swelling properties. Here, various factors affecting the adsorption behavior of this aerogel, such as pH, contact time, ambient temperature, and initial concentration, are investigated. From the kinetic data, it can be obtained that the adsorption process fits well with the pseudo-second-order. The Langmuir isotherm model can fit the equilibrium data well. The thermodynamic data also demonstrated the spontaneous and heat-absorbing properties of anionic and cationic dyes on CaCO3@STA/PAM/TOCN aerogels. The adsorption capacity of Congo red (CR) and methylene blue (MB) by CaCO3@STA/PAM/TOCN was 277.76 mg/g and 101.01 mg/g, respectively. Therefore, cellulose and starch-based aerogels can be considered promising adsorbents for the treatment of dye wastewater.
Cr(III) Ion-Imprinted Hydrogel Membrane for Chromium Speciation Analysis in Water Samples
Authors: Dakova Ivanka , Vasileva Penka , Karadjova Irina
Published: November 2022

Novel Cr(III)-imprinted poly(vinyl alcohol)/sodium alginate/AuNPs hydrogel membranes (Cr(III)-IIMs) were obtained and characterized and further applied as a sorbent for chromium speciation in waters. Cr(III)-IIMs were prepared via solution blending method using blends of poly(vinyl alcohol) and sodium alginate as film-forming materials, poly(ethylene glycol) as a porogen agent, sodium alginate stabilized gold nanoparticles (SA-AuNPs) as a crosslinking and mechanically stabilizing component, and Cr(III) ions as a template species. The physicochemical characteristics of pre-synthesized AuNPs and obtained hydrogel membranes Cr(III)-IIM were studied by UV-vis and FTIR spectroscopy, TEM and SEM observations, N2 adsorption–desorption measurements, and XRD analysis. The mechanism of the adsorption process toward Cr(III) was best described by pseudo-first-order kinetic and Langmuir models. Experiments performed showed that quantitative retention of Cr(III) is attained in 20 h at pH 6 and temperature 40 °C. Under the same conditions, the adsorption of Cr(VI) is below 5%. A simple and sensitive analytical procedure was developed for the speciation of Cr in an aquatic environment using dispersive solid phase extraction of Cr(III) by Cr(III)-IIM prior to selective Cr(VI) measurement by ETAAS in the supernatants. The detection limits and reproducibility achieved for the Cr speciation analysis fulfill the requirements for their monitoring in waters under the demand of the Water Framework Directive.
Race and Racism in Bermuda
Authors: Jeffries Bayyinah S.
Published: November 2022

The legacy of chattel slavery persists in the lives of Black people all over the world. The current state of race relations in Bermuda is shaped by the underlying features of European domination and imperialism that gave birth to chattel slavery. The current racial climate in Bermuda is an example of the long-term impact of chattel slavery and the system of controls that followed. The damaging consequences of these systems of exploitation and oppression continue to shape the life chances and opportunities of Black people. Racial ideas, attitudes, and behaviors influence contemporary race relations between Black and White people throughout the African Diaspora, including Bermuda, which is the focus of this essay.
Machine Learning Techniques for Gully Erosion Susceptibility Mapping: A Review
Authors: Mohebzadeh Hamid , Biswas Asim , Rudra Ramesh , Daggupati Prasad
Published: November 2022

Gully erosion susceptibility mapping (GESM) through predicting the spatial distribution of areas prone to gully erosion is required to plan gully erosion control strategies relevant to soil conservation. Recently, machine learning (ML) models have received increasing attention for GESM due to their vast capabilities. In this context, this paper sought to review the modeling procedure of GESM using ML models, including the required datasets and model development and validation. The results showed that elevation, slope, plan curvature, rainfall and land use/cover were the most important factors for GESM. It is also concluded that although ML models predict the locations of zones prone to gullying reasonably well, performance ranking of such methods is difficult because they yield different results based on the quality of the training dataset, the structure of the models, and the performance indicators. Among the ML techniques, random forest (RF) and support vector machine (SVM) are the most widely used models for GESM, which show promising results. Overall, to improve the prediction performance of ML models, the use of data-mining techniques to improve the quality of the dataset and of an ensemble estimation approach is recommended. Furthermore, evaluation of ML models for the prediction of other types of gully erosion, such as rill–interill and ephemeral gully should be the subject of more studies in the future. The employment of a combination of topographic indices and ML models is recommended for the accurate extraction of gully trajectories that are the main input of some process-based models.
Effectiveness of Acupuncture in Parkinson’s Disease Symptoms—A Systematic Review
Authors: Pereira Catarina Ramos , Machado Jorge , Rodrigues Jorge , de Oliveira Natália M. , Criado Maria Begoña , Greten Henri J.
Published: November 2022

Background: Parkinson’s disease (PD) is the second most common neurodegenerative disease. Several pharmacological and surgical therapies have been developed; however, they are accompanied by some adverse effects. As a result, many patients have been resorting to complementary medicine, namely acupuncture, in the hope of obtaining symptomatic improvements without having disruptive side effects. Therefore, advances in research in this area are very important. This work presents a systematic review of the effectiveness of acupuncture treatments in relieving PD symptoms. Methods: EMBASE, Medline, Pubmed, Science Direct, The Cochrane Library, Cochrane Central Register of Controlled Trials (Central) and Scielo databases, were systematically searched from January 2011 through July 2021. Randomised controlled trials (RCTs) published in English with all types of acupuncture treatment were included. The selection and analysis of the articles was conducted by two blinding authors through Rayyan application. Results: A total of 720 potentially relevant articles were identified; 52 RCTs met our inclusion criteria. After the exclusion of 35 articles, we found 17 eligible. The included RCTs reported positive effects for acupuncture plus conventional treatment compared with conventional treatment alone in the UPDRS score. Conclusions: Although all the studies reviewed pointed out a positive effect of acupuncture on improving motor and non-motor symptoms in Parkinson’s disease, we found great discrepancies regarding the studies’ design and methodology, making difficult any comparison between them.
Effect of the Sway Bed on Autonomic Response, Emotional Responses, and Muscle Hardness in Children with Severe Motor and Intellectual Disabilities: A Pilot Study
Authors: Ozaki Mitsuki , Murata Jun , Sato Katsuya , Tanaka Goro , Imamura Akira , Iwanaga Ryoichiro
Published: November 2022

This cross-sectional study aimed to examine the effects of being swayed in a sway bed on children with severe motor and intellectual difficulties by examining potential differences in their autonomic and emotional responses, as well as their muscle hardness, and by comparing them with “a control condition without any stimulation”. Children’s heart rate variability, rectus femoris hardness, and passive hip abduction range of motion (ROM) were measured in two experimental conditions, differentiated by the presence of a 5-min sway stimulus. In each condition, the children’s faces were video-recorded and retrospectively rated subjectively by their homeroom teacher concerning the visible expression of eight emotions. Significant intervention-related effects were observed on the heart rate variability and the “Relax” item of the emotional response indicators but not on muscle hardness or hip ROM. Our findings provide evidence that using a motorized sway bed can promote relaxation in children with severe motor and intellectual disabilities by influencing their autonomic response.
Abnormal Alpha-1 Antitrypsin Levels and Other Risk Factors Associated with Lung Function Impairment at 6 and 12 Months after Hospitalization Due to COVID-19: A Cohort Study
Authors: Jiménez-Rodríguez Beatriz María , Triviño-Ibáñez Eva Maria , Gutiérrez-Fernández José , Romero-Ortiz Ana Dolores , Ramos-Urbina Eldis Maria , Morales-García Concepción
Published: November 2022

Respiratory function deficits are common sequelae for COVID-19. In this study, we aimed to identify the medical conditions that may influence lung function impairment at 12 months after SARS-CoV2 infection and to analyze the role of alpha-1 antytripsin (AAT) deficiciency (AATD). A cohort study was conducted on hospitalized COVID-19 pneumonia patients in Granada (Spain) during the first infection wave who were referred to a post-COVID-19 hospital clinic. The patients were monitored with three follow-up visits from May 2020 to May 2021. Previous medical history, hospital admission data, baseline parameters and physical examination data were collected at the first visit. Pulmonary function tests were performed at 6 and 12 months together with the determination of AAT level and AATD genotype. After 12 months, 49 out of 157 patients (31.2%) continued to have lung function impairment. A multivariate analysis showed a statistically significant association of lung function impairment with: higher Charlson index; pneumonia with a central and/or mixed distribution; anemia on admission; time in intensive care; need for corticosteroid boluses; abnormal respiratory sounds at 6 months; elevated lactate dehydrogenase at 12 months; abnormal AAT; and MZ genotype. Our results suggest that these medical conditions predispose COVID-19 patients to develop long-term lung function sequelae.
Quality of Life and Anxiety Levels in Latin American Immigrants as Caregivers of Older Adults in Spain
Authors: Fernández-Carrasco Francisco Javier , Molina-Yanes Erika Marbely , Antúnez-Calvente Irene , Rodríguez-Díaz Luciano , Riesco-González Francisco Javier , Gómez-Salgado Juan , Palomo-Gómez Rocío , Vázquez-Lara Juana María
Published: November 2022

Increased life expectancy in Spain has highlighted the need for formal caregivers who care for older adults who live at home. In many cases, families choose to hire immigrants from Latin America who, on many occasions, have been forced to emigrate, which causes a considerable psychological impact on them. To this, other factors such as precarious working conditions, loneliness, or high workload are added, which leads to many caregivers becoming sick. The aim of this study was to assess the quality of life and the level of anxiety derived from the workload of Latin American immigrants who come to Spain to care for older adults. A descriptive cross-sectional study was carried out using two validated questionnaires to measure this relationship. A correlation was also established between quality of life and anxiety as expressed by the participants. The sample consisted of a total of 426 subjects. One of the main results showed that the lower the caregiver’s quality of life, the higher their level of anxiety (OR = 1.06; 95% CI). Live-in caregivers had a lower quality of life than people who did not live in the same house as the cared-for person (OR = 2.22; 95% CI). Working long hours and having a high workload was associated with poorer quality of life and higher levels of anxiety. Assessing immigrants who are formal caregivers and providing them with the support that helps to improve their quality of life is suggested to reduce the occurrence of anxiety disorders.
A Comparative Study of Potential Evapotranspiration Estimation by Three Methods with FAO Penman–Monteith Method across Sri Lanka
Authors: Abeysiriwardana Himasha Dilshani , Muttil Nitin , Rathnayake Upaka
Published: November 2022

Among numerous methods that have been developed to estimate potential evapotranspiration (PET), the Food and Agricultural Organization Penman–Monteith model (FAO P–M) is often recognized as a standard method to estimate PET. This study was conducted to evaluate the applicability of three other PET estimation methods, i.e., Shuttleworth–Wallace (S–W) model, Thornthwaite (TW) and pan methods, to estimate PET across Sri Lanka with respect to the FAO P–M model. The meteorological data, i.e., temperature, relative humidity, wind speed, net solar radiation, and pan evaporation, recorded at 14 meteorologic stations, representing all climate and topographic zones of Sri Lanka, were obtained from 2009 to 2019. The models’ performances were assessed based on three statistical indicators: root mean squared error (RMSE), bias, and Pearson correlation coefficient (R). In comparison with the FAO P–M model estimates, the seasonal and annual estimates of all three models show great differences. The results suggested that pan and S–W methods perform better in the dry zone of the country. Both S–W and pan methods underestimated PET over the entire county in all seasons. TW does not show consistent results over the country, thus being found as the least reliable alternative. Although S–W is highly correlated with the FAO P–M model, the application of the model in a data-scarce region is more constrained, as it requires more parameters than the FAO P–M model. Thus, the study suggests employing alternative methods based on the region of the country instead of one single method across the entire country.
Hydropolitical System Archetypes: Feedback Structures, Physical Environments, Unintended Behaviors, and a Diagnostic Checklist
Authors: Shahbazbegian Mohammadreza , Noori Roohollah
Published: November 2022

Hydropolitics is defined as the systematic study of conflict and cooperation in transboundary water basins, affecting around 40% of the world’s population. There has been great advancement in studies endeavoring to explore linkages between hydropolitical drivers and hydropolitical situations in transboundary basins. To add to this, we posit that hydropolitics would benefit from a system thinking approach that has remained less addressed in the literature. For this purpose, considering a transboundary basin as a system, this study is built on the main principle of system dynamics, which implies that a system’s structure determines its behavior. Incorporating system archetypes into hydropolitics can provide a framework for assessing hydropolitical behavior according to the potential structure of archetypes. In this paper, we discuss five hydropolitical system archetypes and their feedback loop structures, the required physical environments, and potential unintended behavior over time. Finally, an example of a diagnostic checklist is presented that will help riparian states recognize patterns of behavior they may face in the future. This paper lays the groundwork for gaining insight into using system archetypes in projecting plausible hydropolitical behaviors and understanding past behaviors in transboundary basins.
Soil Erosion, Sediment Yield, and Runoff Modeling of the Megech Watershed Using the GeoWEPP Model
Authors: Admas Mulugeta , Melesse Assefa M. , Abate Brook , Tegegne Getachew
Published: November 2022

Modeling soil erosion, sediment yield, and runoff are crucial for managing reservoir capacity, water quality, and watershed soil productivity. However, the monitoring and modeling of soil erosion and sedimentation rates in developing countries such as Ethiopia is not well practiced; thus, the reservoir capacity is diminishing at faster rates. In this study, the soil erosion, sediment yield, and runoff in the Megech watershed, Upper Blue Nile Basin, Ethiopia were modeled using the physically-based geospatial interface, the Water Erosion Prediction Project (GeoWEPP). The GoWEPP model was calibrated and validated at the Angereb sub-watershed and simulated to representative sites to capture the spatiotemporal variability of soil erosion and sediment yield of the Megech watershed. The model parameter sensitivity analysis showed that the hydraulic conductivity (Ke) for all soil types was found to be the dominant parameter for runoff simulation, while rill erodibility (Kr), hydraulic conductivity (Ke), critical shear stress (τc), and inter rill erodibility (Ki) were found to be sensitive for sediment yield and soil loss simulation. The model calibration (2000–2002) and validation (2003–2004) results showed the capability of the GeoWEPP model; with R2 and NSE values, respectively, of 0.94 and 0.94 for calibration; and 0.75 and 0.65 for validation. In general, the results show that the sediment yield in the study watershed varied between 10.3 t/ha/year to 54.8 t/ha/year, with a weighted mean value of 28.57 t/ha/year. The GeoWEPP model resulted in higher sediment value over that of the design sediment yield in the study basin, suggesting the implementation of the best watershed management practices to reduce the rates of watershed sediment yield. Moreover, the mean soil loss rate for the Angerb sub-watershed was found to be 32.69 t/ha/year.
Assessing and Predicting Green Credit Risk in the Paper Industry
Authors: Zhao Yue , Chen Yan
Published: November 2022

The paper industry is closely related to forestry resources, which constitute an essential part of achieving sustainable development. Green credit can provide financial support to assist the paper industry in achieving carbon neutrality. To develop a method for performing green credit risk assessments in the paper industry, first, an initial index system was established on the basis of two dimensions: financial risk and socio-environmental risk. Then, the KMV model was applied to measure credit risk. The combined results of this model, along with the environmental penalties of an enterprise, formed the basis for the classification of green credit risk. Third, the Gini index was used to filter out, one by one, the indexes with the least influence among the factors, and then random forest iterations were performed until the prediction accuracy reached the optimum, thus establishing a green credit risk prediction model for the paper industry. The results show that the accuracy of the sample classification reached 93.75%, and the accuracy of the sample classification for high-risk enterprises reached 100%. The established index system offers good guidance for the assessment of green credit risk in the paper industry, in which the interest coverage ratio, current ratio, asset-liability ratio, and green emissions are the main factors affecting green credit risk.
The Impact of a Yoga-Based Mindfulness Intervention versus Psycho-Educational Session for Older Adults with Mild Cognitive Impairment: The Protocol of a Randomized Controlled Trial
Authors: Farhang Maryam , Rojas Graciela , Martínez Pablo , Behrens Maria Isabel , Langer Álvaro I. , Diaz Marcela , Miranda-Castillo Claudia
Published: November 2022

Background: There is a global agreement in the medical community that a significant proportion of dementia cases could be prevented or postponed. One of the factors behind this agreement comes from scientific evidence showing that mind-body interventions such as mindfulness and yoga for the elderly have been related to a range of positive outcomes, including improved cognition performance in seniors with mild cognitive impairment (MCI). Objective: This study aims to evaluate the effectiveness of a yoga-based mindfulness intervention (YBM) versus psychoeducational sessions for older adults with MCI attending Hospital Clinic Universidad de Chile in Santiago. Method: Two-arm, individually randomized controlled trial (RCT) will be carried out at Clinical Hospital Universidad de Chile in Santiago. Older people over 60 years with any type of MCI using a score < 21 in the Montreal Cognitive Assessment (MoCA) test and a score of 0.05 in the Clinical Dementia Rating (CDR) Scale; and with preserved activities of daily living will be randomly assigned with an allocation ratio of 1:1 in either the yoga-based mindfulness intervention or the active control group based on the psycho-educational program. People who have performed yoga and/or mindfulness in the last 6 months or/and people with a psychiatric clinical diagnosis will be excluded from the study. Montreal Cognitive Assessment, the Lawton Instrumental Activities of Daily Living Scale (IADL), the Barthel Index (BI), the Pemberton happiness index, the Geriatric Anxiety Inventory (GAI) as well as the Geriatric Depression Scale (GDS-5) will be administered by blinded outcomes assessors before random assignment (Pre-test), the week following the last session of the intervention (post-test), and then after 3- and 6-months follow-up. Results: The YBM intervention protocol based on a video recording has been adapted and designed. This is the first RCT to examine the effects of a yoga-based mindfulness intervention in improving cognitive and physical functions and mental health outcomes for Chilean elderly diagnosed with MCI. It is expected to be implemented as an acceptable and effective non-pharmacological option for older people with MCI. Conclusion: Providing evidence-based programs such as preventive therapy for Alzheimer’s disease has relevant implications for public mental health services in Chile.
Awareness of Behavioural Intervention Strategies in Curbing Mental Health Issues among Youth in Malaysia
Authors: Gopinathan Sharmini , Kaur Anisha Haveena , Ming Lai Ming , Alias Mazni Binti , Veeraya Segaran
Published: November 2022

Mental health is a growing concern among people worldwide. Mental health issues are one of the main factors contributing to adolescent health-related burden. Malaysia, in particular, has seen an increase in the number of youths facing mental health issues. The government aims to take action by promoting mental health well-being as well as providing care and recovery to those who are affected. This study aimed to examine measures that could potentially improve and curb mental health issues among youth in Malaysia by adopting the use of behavioural intervention technologies. Three underlying models of intervention were studied, namely, the internet intervention model, Fogg behaviour model, and persuasive system design. A total of 103 respondents between the ages of 18 to 23 years participated in the research survey, and the results revealed that mood changes and thoughts, feelings, and actions were the intervention strategies that showed a positive significance in the improvement of mental health among youth in Malaysia. Social distractions, peer motivation, ease of access to help, and sense of belonging and mindfulness did not show a positive significance when it came to behavioural intervention technologies used to improve mental health.