bluuebunny/crossref_metadata_2025 huggingface dataset:
Configuration Selection for Renewable Energy Community Using MCDM Methods
Authors: Gribiss Hamza , Aghelinejad Mohammad Mohsen , Yalaoui Farouk
Published: March 2023

By 2050, the European Union plans to make Europe the first carbon-neutral continent and a global leader in climate-green industries. Recently, many decisions have been taken in the world to ensure the energy transition from fossil fuel to renewable energy. The creation of renewable energy communities (REC) is among the solutions used to increase this transition. This study presents 16 different configurations for energy self-consumption in RECs containing different industrial factories. One mathematical model is proposed for each configuration, and they have been solved according to different criteria. The comparisons are made between these configurations according to economic, environmental, technical, and social criteria. Then, four multi-criteria decision-making (MCDM) methods are used to choose the best configurations considering all the criteria. For this purpose, the achieved results from the mathematical models are used as input for the MCDM methods. The findings demonstrate that the most effective configurations combine both individual and collective self-consumption. Furthermore, the inclusion of collective production results in multiple advantages, including a 64.71% rise in economic gains, a 26.95% decrease in CO2 emissions, a 21.39% improvement in self-sufficiency, and a significant increase in job creation by 175.24%. In addition, incorporating storage enables a substantial rise in the degree of self-sufficiency, leading to reduced reliance on the power grid and consequent reduction in CO2 emissions.
Temperature-Based State-of-Charge Estimation Using Neural Networks, Gradient Boosting Machine and a Jetson Nano Device for Batteries
Authors: Wang Donghun , Hwang Jihwan , Lee Jonghyun , Kim Minchan , Lee Insoo
Published: March 2023

Lithium-ion batteries are commonly used in electric vehicles, mobile phones, and laptops because of their environmentally friendly nature, high energy density, and long lifespan. Despite these advantages, lithium-ion batteries may experience overcharging or discharging if they are not continuously monitored, leading to fire and explosion risks, in cases of overcharging, and decreased capacity and lifespan, in cases of overdischarging. Another factor that can decrease the capacity of these batteries is their internal resistance, which varies with temperature. This study proposes an estimation method for the state of charge (SOC) using a neural network (NN) model that is highly applicable to the external temperatures of batteries. Data from a vehicle-driving simulator were used to collect battery data at temperatures of 25 °C, 30 °C, 35 °C, and 40 °C, including voltage, current, temperature, and time data. These data were used as inputs to generate the NN models. The NNs used to generate the model included the multilayer neural network (MNN), long short-term memory (LSTM), gated recurrent unit (GRU), and gradient boosting machine (GBM). The SOC of the battery was estimated using the model generated with a suitable temperature parameter and another model generated using all the data, regardless of the temperature parameter. The performance of the proposed method was confirmed, and the SOC-estimation results demonstrated that the average absolute errors of the proposed method were superior to those of the conventional technique. In the estimation of the battery’s state of charge in real time using a Jetson Nano device, an average error of 2.26% was obtained when using the GRU-based model. This method can optimize battery performance, extend battery life, and maintain a high level of safety. It is expected to have a considerable impact on multiple environments and industries, such as electric vehicles, mobile phones, and laptops, by taking advantage of the lightweight and miniaturized form of the Jetson Nano device.
A Multiphysics Model Simulating the Electrochemical, Thermal, and Thermal Runaway Behaviors of Lithium Polymer Battery
Authors: Domalanta Marcel Roy B. , Paraggua Julie Anne D. R.
Published: March 2023

Lithium-ion batteries (LIBs) have circumvented the energy storage landscape for decades. However, safety concerns about liquid–electrolyte-based LIBs have challenged their mobilization. Lithium polymer (LiPo) batteries have gained rising interest due to their high thermal stability. Despite an array of commercially available LiPo batteries, limited studies have ventured into modeling. Numerical simulations allow low-cost optimization of existing battery designs through parameter analysis and material configuration, leading to safer and more energy-efficient batteries. This work examined the electrochemical, thermal, and thermal runaway behavior of a lithium cobalt oxide cathode, graphite anode, and poly(vinylidene fluoride-hexafluoropropylene) electrolyte pouch-type LiPo battery using COMSOL Multiphysics®, and validated results with experimental data. The simulated potential curve exhibited strong agreement with experiment data, while the temperature profile during discharge displayed qualitative discrepancies rationalized by the reversible heat generation. Thermal runaway simulations via oven tests revealed that the highest heat generation is from the cathode–electrolyte reaction, while the solid electrolyte interface decomposition initiates the heat generation process. These results suggest a thorough selection of cathode and electrolyte material to heighten battery safety. Overall, the developed models can be utilized as design tools to investigate various chemistries and designs to estimate the behavior and performance of batteries.
Estimation of Tax Expenditures Stimulating the Energy Sector Development and the Use of Alternative Energy Sources in OECD Countries
Authors: Tyurina Yuliya , Frumina Svetlana , Demidova Svetlana , Kairbekuly Aidyn , Kakaulina Maria
Published: March 2023

The energy crisis caused by global structural changes in the economic sphere is the cause accelerating the energy transition based on the concept of sustainable development. This study is to test the hypothesis about the incentive effect of tax expenditures on alternative energy and energy conservation. The objects of empirical research are the EU, OECD countries, OECD partner countries and Russia from 2018–2020. The tools of scientific research are based on methods of economic–statistical and comparative analysis and expert judgments. The concept of tax expenditures in terms of decarbonization is analyzed using a systematic approach. The integrated methodological approach shows the relationship between the tax policy and government strategies in achieving sustainable development goals to ensure the transition to rational energy consumption patterns and sustainable energy sources. The authors analyze incentives for the energy sector and alternative energy sources in the considered groups of countries, and they assess the scale of tax expenditures in the energy sector for OECD countries. There are two types of tax expenditures for achieving environmental sustainability—increasing renewable energy sources and improving the energy efficiency. The authors apply the multivariate average formula to assess the scale of tax incentives in OECD countries. The results are typified depending on the scale of tax expenditures as one of the tools and these results are grouped according to the dynamics. In the presented sample, a wide range of tax benefits and preferences is typical for the leading countries in the ranking. The countries at the bottom of the ranking support fossil fuels, but they have already started the energy transition.
Effect of Oxygen Vacancy on the Crystallinity and Optical Band Gap in Tin Oxide Thin Film
Authors: Dangi Rajesh , Basnet Bijaya , Pandey Manoj , Bhusal Sandip , Budhathoki Biplab , Parajuli Kshama , Tiwari Santosh K. , Kafle Bhim P.
Published: March 2023

Herein, we have prepared tin oxide (SnO2) nanoparticles (NPs), through a co-precipitation method, using SnCl2·2H2O dissolved in distilled water (DW) as a precursor. Then, the prepared NPs were heat treated in a muffle furnace, as a function of temperature, under an open atmosphere. The prepared SnO2 NPs were then re-dispersed in DW, followed by spray casting on a glass substrate, for preparing SnO2 thin films. The average thickness of the fabricated SnO2 thin films was 2.76 µm. We demonstrated a very clear variation in the structural, compositional, and morphological features of the different films (in particular, variation of the density of oxygen vacancies), which altered their electrical and optical properties. Raising the calcination temperature of the SnO2 thin films, from 250 °C to 650 °C, led to a monotonic reduction in the crystallite size, from 10.4 nm to 6.7 nm, and a decrease in the O/Sn ratio, from 5.60 to 4.79. A 14.5% decrease in the O/Sn ratio resulted in a decrease in the crystallite size by 3.7 nm (i.e., a 35.3% decrease in the NP size), and a decrease in the band gap of 0.11 eV. The lowering of the band gap, along with an increase in the oxygen vacancies in the films, accords well with previous studies. Besides, as the calcination temperature was raised, the refractive index and absorption coefficient values were also found to notably increase. Very interestingly, by simply altering the calcination temperature, we were able to produce SnO2 thin films with optical band gaps nearly equal to the fundamental band gap (2.96 eV), even though many earlier experimental studies had reported considerably greater values (3.36–4.24 eV). SnO2 thin films with lower oxygen vacancies exhibited relatively higher band gaps, which is likely to be favorable for the desired electron transport layer in perovskite solar cells.
Heat and Moisture Management for Automatic Air Conditioning of a Domestic Household Using FA-ZnO Nanocomposite as Smart Sensing Material
Authors: Tripathy Hara Prasada , Pattanaik Priyabrata , Mishra Dilip Kumar , Holderbaum William
Published: March 2023

Prior to the year 2000, air conditioning was not common in many cities throughout the world. However, today, 20 years later, air conditioning is common. This circumstance has a negative impact on the climate. Additionally, the situation regarding energy usage as a result of this is alarming. For a healthy and pleasant livelihood, indoor temperature and air flow must be controlled. False partitions with insulating layers have been used to regulate the temperature inside rooms, but they are unable to regulate the variation in humidity caused by the exchange of water between interior and exterior walls. In this manuscript, we provide a sensory system that can automatically detect relative humidity and temperature. Temperature is sensed at each layer of the false partition using an LM35-based integrated circuit and humidity is detected by an FA–ZnO nano-composite layer through an indoor false partition owing to changes in the material’s resistance. Depending upon the change in resistance based on the fluctuation in temperature, the corresponding current responds by arduino microcontroller, and thus triggers the automated ON and OFF switch for air conditioning. Living and non-living bodies both lead pleasant and healthy lives when indoor units are managed properly.
Thermal Impact of 5G Antenna Systems in Sandwich Walls
Authors: Lu Tao , Vähä-Savo Lauri , Lü Xiaoshu , Haneda Katsuyuki
Published: March 2023

The 5th generation (5G) cellular networks offer high speeds, low latency, and greater capacity, but they face greater penetration loss through buildings than 4G due to their higher frequency bands. To reduce this loss in energy-efficient buildings, a passive antenna system was developed and integrated into sandwich walls. However, the thermal effects of this system, which includes highly thermally conductive metals, require further study. In this research, three-dimensional heat transfer simulations were performed using COMSOL Multiphysics to determine the thermal transmittances (U-values) of 5G antenna walls. The results revealed that, using stainless steel as the connector material (current design), the U-value rose from 0.1496 (for the wall without antenna) to 0.156 W/m2K, leading to an additional heating loss per year of only 0.545 KWh/m2 in Helsinki. In contrast, with the previous design that used copper as the connector material, the U-value increased dramatically to 0.3 W/m2K, exceeding the National Building Code of Finland’s limit of 0.17 W/m2K and causing 12.8 KWh/m2 additional heat loss (23.5 times more than the current design). The current design significantly reduces thermal bridging effects. Additionally, three analytical methods were used to calculate antenna wall U-values: parallel paths, isothermal planes, and ISO 6946 combined. The isothermal planes method was found to be more accurate and reliable. The study also found that a wall unit cell with a single developed 5G antenna and a wall consisting of nine such cells arranged in a 3 × 3 grid pattern had the same U-values. Furthermore, areas affected by thermal bridging were typically smaller than the dimensions of a wall unit cell (150 mm × 150 mm).
Fault Identification and Classification of Asynchronous Motor Drive Using Optimization Approach with Improved Reliability
Authors: Venugopal Gopu , Udayakumar Arun , Balashanmugham Adhavan , Houran Mohamad , Alsaif Faisal , Elavarasan Rajvikram , Raju Kannadasan , Alsharif Mohammed
Published: March 2023

This article aims to provide a technique for identifying and categorizing interturn insulation problems in variable-speed motor drives by combining Salp Swarm Optimization (SSO) with Recurrent Neural Network (RNN). The goal of the proposed technique is to detect and classify Asynchronous Motor faults at their early stages, under both normal and abnormal operating conditions. The proposed technique uses a recurrent neural network in two phases to identify and label interturn insulation concerns, with the first phase being utilised to establish whether or not the motors are healthy. In the second step, it discovers and categorises potentially dangerous interturn errors. The SSO approach is used in the second phase of the recurrent neural network learning procedure, with the goal function of minimizing error in mind. The proposed CSSRN technique simplifies the system for detecting and categorizing the interturn insulation issue, resulting in increased system precision. In addition, the proposed model is implemented in the MATLAB/Simulink, where metrics such as accuracy, precision, recall, and specificity may be analysed. Similarly, existing methods such as Adaptive Neuro-Fuzzy Inference System (ANFIS), Recurrent Neural Network (RNN), and Salp Swarm Algorithm Artificial Neural Network (SSAANN) are utilised to evaluate metrics such as Root mean squared error (RMSE), Mean bias error (MBE), Mean absolute percentage error (MAPE), consumption, and execution time for comparative analysis.
Increasing Growth of Renewable Energy: A State of Art
Authors: Guchhait Rekha , Sarkar Biswajit
Published: March 2023

The growth of renewable energy actively takes part in decarbonizing the fossil-fuel-based energy system. It reduces carbon emissions, carbon footprint, and greenhouse gas emissions and increases clean energy. The usage of renewable resources reduces and solves several problems, such as increasing temperature, carbon footprint, greenhouse gas emissions, and energy waste. Every sector contributes to increasing the above-mentioned factors in the environment. One of the main reasons for this biodegradation and climate change is energy resources. Using renewable energy instead of fossil fuel can solve the problem. This paper aims to find open research problems about the application of renewable energy and to initiate new innovative ideas regarding renewable energy. A detailed state of the art includes trends for renewable energy resources, their theoretical evolution, and practical implementations. Methodologies used for decision analysis in renewable energy are discussed in detail. The time frame for this analysis of renewable energy is 2010 to >2022. An extensive literature review finds a huge research scope in applying renewable energy in other research, such as logistics, smart production management, and advanced inventory management. Then, major changes in the profit/cost of that system due to renewable energy can be analyzed. This research proposes some innovative new ideas related cost formulas for renewable energy for the corresponding open problems.
Special Issue “Energy Transition and Environmental Sustainability”
Authors: Pearce Prafula
Published: March 2023

This Special Issue on “Energy Transition and Environmental Sustainability” includes thirteen papers on policies including: the challenges of the United Nations Sustainable Development Goals regarding energy transition and legal reforms in Taiwan and Japan [...]
Investigating the Influence of Groundwater Flow and Charge Cycle Duration on Deep Borehole Heat Exchangers for Heat Extraction and Borehole Thermal Energy Storage
Authors: Brown Christopher S. , Doran Hannah , Kolo Isa , Banks David , Falcone Gioia
Published: March 2023

Decarbonisation of heat is essential to meeting net zero carbon targets; however, fluctuating renewable resources, such as wind or solar, may not meet peak periods of demand. Therefore, methods of underground thermal energy storage can aid in storing heat in low demand periods to be exploited when required. Borehole thermal energy storage (BTES) is an important technology in storing surplus heat and the efficiency of such systems can be strongly influenced by groundwater flow. In this paper, the effect of groundwater flow on a single deep borehole heat exchanger (DBHEs) was modelled using OpenGeoSys (OGS) software to test the impact of varying regional Darcy velocities on the performance of heat extraction and BTES. It is anticipated that infrastructure such as ex-geothermal exploration or oil and gas development wells approaching the end of life could be repurposed. These systems may encounter fluid flow in the subsurface and the impact of this on single well deep BTES has not previously been investigated. Higher groundwater velocities can increase the performance of a DBHE operating to extract heat only for a heating season of 6 months. This is due to the reduced cooling of rocks in proximity to the DBHE as groundwater flow replenishes heat which has been removed from the rock volume around the borehole (this can also be equivalently thought of as “coolth” being transported away from the DBHE in a thermal plume). When testing varying Darcy velocities with other parameters for a DBHE of 920 m length in rock of thermal conductivity 2.55 W/(m·K), it was observed that rocks with larger Darcy velocity (1e-6 m/s) can increase the thermal output by up to 28 kW in comparison to when there is no groundwater flow. In contrast, groundwater flow inhibits single well deep BTES as it depletes the thermal store, reducing storage efficiency by up to 13% in comparison to models with no advective heat transfer in the subsurface. The highest Darcy velocity of 1e-6 m/s was shown to most influence heat extraction and BTES; however, the likelihood of this occurring regionally, and at depth of around or over 1 km is unlikely. This study also tested varying temporal resolutions of charge and cyclicity. Shorter charge periods allow a greater recovery of heat (c. 34% heat injected recovered for 1 month charge, as opposed to <17% for 6 months charge).
Effects of Leaf Hydrophilicity and Stomatal Regulation on Foliar Water Uptake Capacity of Desert Plants
Authors: Wang Huimin , Li Zhoukang , Yang Jianjun
Published: March 2023

Foliar water uptake (FWU) is one of the primary water sources for desert plants. Desert plants’ water uptake capacity is essential in maintaining the balance of carbon and water. However, there are few studies on FWU capacity in desert plants and the physiological and ecological characteristics that lead to differences in FWU capacity. In order to clarify FWU strategies and the influencing factors of plants in desert ecosystems, this study measured the contact angle, FWU parameters, and hydraulic parameters to explore six desert plants’ FWU capacity and the effects of leaf wettability and hydraulic parameters on FWU capacity. The results showed that all six plants had FWU capacity, among which the leaves of Nitraria sibirica Pall. and Halimodendron halodendron (Pall.) Voss had a high foliar water uptake rate (k) and high foliar water uptake accumulation (FWU storage), and the leaves of Glycyrrhiza uralensis Fisch. had a high k and low FWU storage. The leaves of Populus euphratica Oliv., Apocynum hendersonii Hook. f., and Alhagi sparsifolia Shap. had a low k and low FWU storage. Additionally, FWU capacity was mainly affected by stomatal regulation compared with leaf wettability and leaf structure. The results of this study will help to improve the understanding of the physiological and ecological adaptability of desert plants.
Effects of Topography and Social Position on the Solar Radiation of Individual Trees on a Hillslope in Northwest China
Authors: Li Jiamei , Yu Pengtao , Wan Yanfang , Wang Yanhui , Liu Bingbing , Yu Yipeng
Published: March 2023

Solar radiation is a key factor influencing the photosynthesis and transpiration of trees. In mountainous regions, solar radiation income exhibits strong spatial heterogeneity due to topographical variations and the structural complexity of the forest. However, how the solar radiation income of individual trees in different social positions varies with slope position remains unclear. In this study, the daily solar radiation of the horizontal ground (Rh), different slope positions (i.e., at different locations on a hillslope, Rs) and individual trees with different social positions in the forest (Ri) were monitored from May to October in 2020 and 2021. The daily solar radiation income of a single hillslope (Rf) was applied to quantify the Rs response to the slope and aspect (i.e., slope effect) and the shade from the opposite mountain (i.e., shaded terrain effect). Our results showed that the Rf was 27.8% lower than Rh due to the slope effect of the sample slope. In the different slope positions, 2.7%–46.9% of solar radiation was lost due to the shaded terrain effect. A stronger limitation of Rs by the shaded terrain effect was detected on the bottom slope compared to that of the upper slope. The better the social position of an individual tree (i.e., tree dominance (Dom) and the distance between trees (D)), the more solar radiation it received, ranging from 22.4 to 95.3%. The dominant factor contributing to changes in Ri was slope position followed by D and Dom and, finally, Rh. These results provide an important basis for understanding the role of topography and tree social positions in solar radiation income in mountainous regions. Forest management measures should be varied with slope positions in mountainous regions, and forest density (i.e., distance between trees) should be considered as a key factor to optimize the forest functions.
Assessing Future Climate Change Impacts on Potato Yields — A Case Study for Prince Edward Island, Canada
Authors: Adekanmbi Toyin , Wang Xiuquan , Basheer Sana , Nawaz Rana Ali , Pang Tianze , Hu Yulin , Liu Suqi
Published: March 2023

Crop yields are adversely affected by climate change; therefore, it is crucial to develop climate adaptation strategies to mitigate the impacts of increasing climate variability on the agriculture system to ensure food security. As one of the largest potato-producing provinces in Canada, Prince Edward Island (PEI) has recently experienced significant instability in potato production. PEI’s local farmers and stakeholders are extremely concerned about the prospects for the future of potato farming industries in the context of climate change. This study aims to use the Decision Support System for Agrotechnology Transfer (DSSAT) potato model to simulate future potato yields under the Coupled Model Intercomparison Project Phase 6 (CMIP6) climate scenarios (including SSP1–1.9, SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5). The study evaluates the combined effects of changing climatic conditions at local scales (i.e., warming temperature and changing precipitation patterns) and increasing carbon dioxide (CO2) concentration in the atmosphere. The results indicate future significant declines in potato yield in PEI under the current farming practices. In particular, under the high-emission scenarios (e.g., SSP3–7.0 and SSP5–8.5), the potato yield in PEI would decline by 48% and 60% in the 2070s and by 63% and 80% by 2090s; even under the low-emission scenarios (i.e., SSP1–1.9 and SSP1–2.6), the potato yield in PEI would still decline by 6–10%. This implies that it is important to develop effective climate adaptation measures (e.g., adjusting farming practices and introducing supplemental irrigation plans) to ensure the long-term sustainability of potato production in PEI.
Current Perspectives on Viable but Non-Culturable Foodborne Pathogenic Bacteria: A Review
Authors: Zhang Jiawen , Yang Haoqing , Li Jing , Hu Jiamiao , Lin Guanyuan , Tan Bee K. , Lin Shaoling
Published: March 2023

Foodborne diseases caused by foodborne pathogens pose risks to food safety. Effective detection and efficient inactivation of pathogenic bacteria has always been a research hotspot in the field of food safety. Complicating these goals, bacteria can be induced to adopt a viable but non-culturable (VBNC) state under adverse external environmental stresses. When in the VBNC state, pathogens cannot form visible colonies during traditional culture but remain metabolically active and toxic. The resulting false negative results in growth-related assays can jeopardize food safety. This review summarizes the latest research on VBNC foodborne pathogens, including induction conditions, detection methods, mechanism of VBNC formation, and possible control strategies. It is hoped that this review can provide ideas and methods for future research on VBNC foodborne pathogenic bacteria.
Effects of Partial Replacement of NaCl with KCl on Protein Properties and Quality Attributes of Lightly Salted Tilapias Fillets
Authors: Jing Lunan , Xue Jingqi , Jiang Xin , Xiao Naiyong , Pan Hao , Li Jiarou , Wang Dajun , Jiang Qingqing , Shi Wenzheng
Published: March 2023

The evolution of quality attributes and their association with the protein properties of lightly tilapias fillets salted with different replacement proportions of NaCl with KCl (0%, 10%, 30%, 50%, 70%, 100%) at the same ionic strength were investigated. KCl replacements using optimal substitution (50% of KCl) contributed to maintaining desired quality properties. Further, KCl replacement (about 50~70% of KCl) led to the insolubilization and weakened stability of myofibrillar proteins, represented by the unfolding of the myofibrillar protein, increased surface hydrophilic points, and strengthened internal protein-protein interaction, resulting in the structurally reinforced hardness and lower water-holding capacity. Excessive replacement (more than 70% of KCl) showed apparent deterioration in taste quality, coloration, and hardness received by sensory sensation caused by immoderate hydrolysis and aggravated oxidation of the myofibrillar protein. In this sense, insights into KCl replacements on protein properties might be a positive approach to improving quality attributes of lightly salted tilapias fillets.
Enriched Red Wine: Phenolic Profile, Sensory Evaluation and In Vitro Bioaccessibility of Phenolic Compounds
Authors: Muñoz-Bernal Óscar A. , Vazquez-Flores Alma A. , de la Rosa Laura A. , Rodrigo-García Joaquín , Martínez-Ruiz Nina R. , Alvarez-Parrilla Emilio
Published: March 2023

The beneficial health effect of red wine depends on its phenolic content and the phenolic content in red wines is affected by ecological, agricultural, and enological practices. Enriched wines have been proposed as an alternative to increase the phenolic content in wines. Nevertheless, phenolic compounds are related to the sensory characteristics of red wines, so enrichment of red wines requires a balance between phenolic content and sensory characteristics. In the present study, a Merlot red wine was enriched with a phenolic extract obtained from Cabernet Sauvignon grape pomace. Two levels of enrichment were evaluated: 4 and 8 g/L of total phenolic content (gallic acid equivalents, GAE). Wines were evaluated by a trained panel to determine their sensory profile (olfactive, visual, taste, and mouthfeel phases). The bioaccessibility of phenolic compounds from enriched red wines was evaluated using an in vitro digestive model and phenolic compounds were quantified by High Performance Liquid Chromatography coupled to tandem mass spectrometry (HPLC-MS/MS). Enrichment increased mainly flavonols and procyanidins. Such an increase impacted astringency and sweetness perceived by judges. This study proposes an alternative to increase the phenolic content in wines without modifying other main sensory characteristics and offers a potential beneficial effect on the health of consumers.
Improving Drying Characteristics and Physicochemical Quality of Angelica sinensis by Novel Tray Rotation Microwave Vacuum Drying
Authors: Zang Zepeng , Huang Xiaopeng , He Cuncai , Zhang Qian , Jiang Chunhui , Wan Fangxin
Published: March 2023

In order to improve the shortcomings of uneven heating of traditional microwave drying and to maximally maintain food quality after harvest, a rotary microwave vacuum drying equipment was fabricated and used for drying experiments on Angelica sinensis to explore the effects of drying temperature, slice thickness, and vacuum degree on drying characteristics, physicochemical quality, and microstructure of dried Angelica sinensis products. The results showed that microwave vacuum drying can significantly shorten the drying time and improved the drying efficiency. Six different mathematical models were investigated and the Midilli model was the best-fitted model for all samples (R2 = 0.99903, Pearson’s r = 0.99952), and drying methods had various effects on different indexes and were confirmed by Pearson’s correlation analysis and principal component analysis. The optimal process parameters for microwave vacuum drying of Angelica sinensis were determined by entropy weight-coefficient of variation method as 45 °C, 4 mm, −0.70 kPa. Under this condition, well preserved of ferulic acid, senkyunolide I, senkyunolide H, ligustilide, total phenols and antioxidant activity, bright color (L* = 77.97 ± 1.89, ΔE = 6.77 ± 2.01), complete internal organizational structure and more regular cell arrangement were obtained in the samples. This study will provide a theoretical reference for the excavation of the potential value and the development of industrial processing of Angelica sinensis.
Research on Anthocyanins from Rubus “Shuofeng” as Potential Antiproliferative and Apoptosis-Inducing Agents
Authors: Zhao Fengyi , Zhao Huifang , Wu Wenlong , Wang Weifan , Li Weilin
Published: March 2023

Blackberries have high nutritional value and strong biological activities, such as antiproliferative activity. Anthocyanins are important functional components in blackberries. We collected 25 kinds (lines) of blackberries from our nursery to investigate antiproliferative agents in natural foods. Among them, the Shuofeng variety had the highest anthocyanin content, with 2.54 mg/g of fresh fruit, which increased to 357.75 mg/g of dried powder through ultrasound-assisted solvent extraction and macroporous resin adsorption. Additional experiments showed that Shuofeng’s anthocyanin content had high anti-HepG2 activity in vitro and in vivo, as well as activity against Hela (68.62 μg/mL), HepG2 (55.85 μg/mL), MCF-7 (181.21 μg/mL), and A549 cells (82.01 μg/mL), as determined by MTT assay. It also had no apparent toxic effects. The combination of DDP and DOX significantly enhanced the antiproliferative activity of the four cell lines. The IC50 value of Shuofeng’s anthocyanin content combined with DOX in HepG2 cells was the lowest at only 0.08 μg/mL, indicating that the combination of drugs had additive and synergistic effects. Shuofeng’s anthocyanin content might intercalate into DNA and alter or destroy DNA, causing apoptosis and inhibiting cell proliferation. Our results show that blackberry anthocyanins can inhibit the proliferation of cancer cells and their possible mechanisms. However, we must study the deeper mechanism and explore its targeting effects in the future.
Factors Associated with Willingness toward Organ Donation in China: A Nationwide Cross-Sectional Analysis Using a Social–Ecological Framework
Authors: Zeng Mengjun , Li Haomiao , Song Xiaohui , Jiang Jipin , Chen Yingchun
Published: March 2023

Improving public willingness toward organ donation is an important solution to the low organ donation rate. This study aimed to explore factors impacting public willingness for organ donation in China from a multi-agent perspective and further explore the impact of these factors on high or low willingness, using a social–ecological framework. Data from a total of 11,028 (effective rate, 94.18%) participants were analysed. Generalised linear model (GLM) and quantile regression were used to explore factors associated with willingness and high/low willingness toward organ donation, respectively. The mean willingness toward organ donation was 56.9 (range, 0–100) points. GLM regression revealed that age, family health, males, lower educational levels, and agricultural hukou were negatively associated with willingness. For personality, conscientiousness was negatively associated with willingness, whereas openness was positively associated with willingness. Health literacy perceived social support, and media utilisation were positively associated with willingness. Quantile regression further indicated that educational levels of college, bachelor, master’s, and PhD, openness, health literacy, perceived social support, and media utilisation were positively associated with organ donation willingness at all percentiles. It is necessary to adopt more targeted and diversified publicity, education, and guidance for different types of individuals. Meanwhile, social support needs to be strengthened. To enhance the willingness of the residents to donate organs, media publicity should be strengthened, particularly by using modern ways to improve their health literacy.
Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
Authors: Shaheed Kashif , Szczuko Piotr , Abbas Qaisar , Hussain Ayyaz , Albathan Mubarak
Published: March 2023

In recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia. First, a pre-processing method based on a Gaussian filter and logarithmic operator is applied to input chest X-ray (CXR) images to improve the poor-quality images by enhancing the contrast, reducing the noise, and smoothing the image. Second, robust features are extracted from each enhanced chest X-ray image using a Convolutional Neural Network (CNNs) transformer and an optimal collection of grey-level co-occurrence matrices (GLCM) that contain features such as contrast, correlation, entropy, and energy. Finally, based on extracted features from input images, a random forest machine learning classifier is used to classify images into three classes, such as COVID-19, pneumonia, or normal. The predicted output from the model is combined with Gradient-weighted Class Activation Mapping (Grad-CAM) visualisation for diagnosis. (3) Results: Our work is evaluated using public datasets with three different train–test splits (70–30%, 80–20%, and 90–10%) and achieved an average accuracy, F1 score, recall, and precision of 97%, 96%, 96%, and 96%, respectively. A comparative study shows that our proposed method outperforms existing and similar work. The proposed approach can be utilised to screen COVID-19-infected patients effectively. (4) Conclusions: A comparative study with the existing methods is also performed. For performance evaluation, metrics such as accuracy, sensitivity, and F1-measure are calculated. The performance of the proposed method is better than that of the existing methodologies, and it can thus be used for the effective diagnosis of the disease.
Anxiety among Central American Migrants in Mexico: A Cumulative Vulnerability
Authors: Gorn Shoshana Berenzon , Saavedra Nayelhi , Bojorquez Ietza , Reed Geoffrey , Wainberg Milton L. , Medina-Mora María Elena
Published: March 2023

Migration exposes Central American migrants, particularly those who migrate without documents, to a range of incidents, dangers, and risks that increase their vulnerability to anxiety symptoms. In most cases, the poverty, conflict, and violence they experience in their countries of origin are compounded by the unpredictable conditions of their journey through Mexico. The objective of this study was to explore the association between the presence of emotional discomfort and the experience of various vulnerabilities from the perspective of a group of Central American migrants in transit through Mexico. This is a descriptive, mixed-methods study (QUALI-QUAN). During the qualitative phase, thirty-five migrants were interviewed (twenty in Mexico City and six in Tijuana). During the quantitative phase, a questionnaire was administered to 217 migrants in shelters in Tijuana. An analysis of the subjects’ accounts yielded various factors associated with stress and anxiety, which were divided into five main groups: (1) precarious conditions during the journey through Mexico, (2) rejection and abuse due to their identity, (3) abuse by Mexican authorities, (4) violence by criminal organizations, and (5) waiting time before being able to continue their journey. The interaction of various vulnerabilities predisposes individuals to present emotional discomfort, such as anxiety. Migrants who reported experiencing three or more vulnerabilities presented the highest percentages of anxiety symptoms.
An Integrated System of Braden Scale and Random Forest Using Real-Time Diagnoses to Predict When Hospital-Acquired Pressure Injuries (Bedsores) Occur
Authors: Dweekat Odai Y. , Lam Sarah S. , McGrath Lindsay
Published: March 2023

Background and Objectives: Bedsores/Pressure Injuries (PIs) are the second most common diagnosis in healthcare system billing records in the United States and account for 60,000 deaths annually. Hospital-Acquired Pressure Injuries (HAPIs) are one classification of PIs and indicate injuries that occurred while the patient was cared for within the hospital. Until now, all studies have predicted who will develop HAPI using classic machine algorithms, which provides incomplete information for the clinical team. Knowing who will develop HAPI does not help differentiate at which point those predicted patients will develop HAPIs; no studies have investigated when HAPI develops for predicted at-risk patients. This research aims to develop a hybrid system of Random Forest (RF) and Braden Scale to predict HAPI time by considering the changes in patients’ diagnoses from admission until HAPI occurrence. Methods: Real-time diagnoses and risk factors were collected daily for 485 patients from admission until HAPI occurrence, which resulted in 4619 records. Then for each record, HAPI time was calculated from the day of diagnosis until HAPI occurrence. Recursive Feature Elimination (RFE) selected the best factors among the 60 factors. The dataset was separated into 80% training (10-fold cross-validation) and 20% testing. Grid Search (GS) with RF (GS-RF) was adopted to predict HAPI time using collected risk factors, including Braden Scale. Then, the proposed model was compared with the seven most common algorithms used to predict HAPI; each was replicated for 50 different experiments. Results: GS-RF achieved the best Area Under the Curve (AUC) (91.20 ± 0.26) and Geometric Mean (G-mean) (91.17 ± 0.26) compared to the seven algorithms. RFE selected 43 factors. The most dominant interactable risk factors in predicting HAPI time were visiting ICU during hospitalization, Braden subscales, BMI, Stimuli Anesthesia, patient refusal to change position, and another lab diagnosis. Conclusion: Identifying when the patient is likely to develop HAPI can target early intervention when it is needed most and reduces unnecessary burden on patients and care teams when patients are at lower risk, which further individualizes the plan of care.
Prevalence of Dementia among Patients Hospitalized with Type 2 Diabetes Mellitus in Spain, 2011–2020: Sex-Related Disparities and Impact of the COVID-19 Pandemic
Authors: Lopez-de-Andres Ana , Jimenez-Garcia Rodrigo , Zamorano-Leon Jose J. , Omaña-Palanco Ricardo , Carabantes-Alarcon David , Hernández-Barrera Valentin , De Miguel-Diez Javier , Cuadrado-Corrales Natividad
Published: March 2023

(1) Background: To assess changes in the prevalence of dementia among patients hospitalized with type 2 diabetes (T2DM), to analyze the effects of dementia on in-hospital mortality (IHM) in this population, to evaluate sex differences, and to determine the impact of the COVID-19 pandemic on these parameters. (2) Methods: We used a nationwide discharge database to select all patients with T2DM aged 60 years or over admitted to Spanish hospitals from 2011 to 2020. We identified those with all-cause dementia, Alzheimer’s disease (AD), and vascular dementia (VaD). The effect of sex, age, comorbidity, and COVID-19 on the prevalence of dementia subtypes and on IHM was assessed using multivariable logistic regression. (3) Results: We identified 5,250,810 hospitalizations with T2DM. All-cause dementia was detected in 8.31%, AD in 3.00%, and VaD in 1.55%. The prevalence of all subtypes of dementia increased significantly over time. After multivariable adjustment, higher values were observed in women for all-cause dementia (OR 1.34; 95% CI 1.33–1.35), AD (OR 1.6; 95% CI 1.58–1.62), and VaD (OR 1.12; 95% CI 1.11–1.14). However, female sex was a protective factor for IHM in patients with all-cause dementia (OR 0.90; 95% CI 0.89–0.91), AD (OR 0.89; 95% CI 0.86–0.91), and VaD (OR 0.95; 95% CI 0.91–0.99). IHM among patients with dementia remained stable over time, until 2020, when it increased significantly. Higher age, greater comorbidity, and COVID-19 were associated with IHM in all dementia subtypes. (4) Conclusions: The prevalence of dementia (all-cause, AD, and VaD) in men and women with T2DM increased over time; however, the IHM remained stable until 2020, when it increased significantly, probably because of the COVID-19 pandemic. The prevalence of dementia is higher in women than in men, although female sex is a protective factor for IHM.
Immune Checkpoint Inhibitor Related Rheumatological Complications: Cooperation between Rheumatologists and Oncologists
Authors: Pacholczak-Madej Renata , Kosałka-Węgiel Joanna , Kuszmiersz Piotr , Mituś Jerzy W. , Püsküllüoğlu Mirosława , Grela-Wojewoda Aleksandra , Korkosz Mariusz , Bazan-Socha Stanisława
Published: March 2023

In cancer, immune checkpoint inhibitors (ICIs) improve patient survival but may lead to severe immune-related adverse events (irAEs). Rheumatic irAEs are a distinct entity that are much more common in a real-life than in clinical trial reports due to their unspecific symptoms and them being a rare cause of hospitalization. This review focuses on an interdisciplinary approach to the management of rheumatic irAEs, including cooperation between oncologists, rheumatologists, and immunologists. We discuss the immunological background of rheumatic irAEs, as well as their unique clinical characteristics, differentiation from other irAEs, and treatment strategies. Importantly, steroids are not the basis of therapy, and nonsteroidal anti-inflammatory drugs should be administered in the front line with other antirheumatic agents. We also address whether patients with pre-existing rheumatic autoimmune diseases can receive ICIs and how antirheumatic agents can interfere with ICIs. Interestingly, there is a preclinical rationale for combining ICIs with immunosuppressants, particularly tumor necrosis factor α and interleukin 6 inhibitors. Regardless of the data, the mainstay in managing irAEs is interdisciplinary cooperation between oncologists and other medical specialties.
Patient Education Improves Pain and Health-Related Quality of Life in Patients with Established Spinal Osteoporosis in Primary Care—A Pilot Study of Short- and Long-Term Effects
Authors: Spångeus Anna , Willerton Catrin , Enthoven Paul , Grahn Kronhed Ann-Charlotte
Published: March 2023

Fragility fractures, in particular vertebral fractures, are associated with high morbidity, including chronic pain and reduced health-related quality of life. We aimed to investigate the short- and long-term effects of patient education, including interdisciplinary themes, with or without physical training or mindfulness/medical yoga for patients with established spinal osteoporosis in primary care. Osteoporotic persons aged sixty years or older with one or more vertebral fractures were randomized to theory only, theory and physical exercise, or theory and mindfulness/medical yoga and were scheduled to once a week for ten weeks. Participants were followed up by clinical tests and questionnaires. Twenty-one participants completed the interventions and the one-year follow-up. Adherence to interventions was 90%. Pooled data from all participants showed significant improvements after intervention on pain during the last week and worst pain, and reduced painkiller use (any painkillers at baseline 70% [opioids 25%] vs. post-intervention 52% [opioids 14%]). Significant improvements were seen regarding RAND-36 social function, Qualeffo-41 social function, balance, tandem walking backwards, and theoretical knowledge. These changes were maintained at the 1-year follow-up. Patient group education combined with supervised training seems to have positive effects on pain, and physical function in persons with established spinal osteoporosis. The improved quality of life was maintained at the 1-year follow-up.
Multimodal Physical Exercise and Functional Rehabilitation Program in Oncological Patients with Cancer-Related Fatigue—A Randomized Clinical Trial
Authors: Fernandez-Rodriguez Eduardo J. , Sanchez-Gomez Celia , Mendez-Sanchez Roberto , Recio-Rodriguez Jose I. , Puente-Gonzalez A. Silvia , Gonzalez-Sanchez Jesus , Cruz-Hernandez Juan J. , Rihuete-Galve Maria I.
Published: March 2023

The increase in life expectancy and survival time implies an increase in the possible side-effects of pharmacological treatments in patients. Cancer-related fatigue is one of these side-effects. The main objective of this study was to evaluate the effects of a multimodal program of physical exercise and functional rehabilitation on asthenia, pain, functional capacity, and quality of life in cancer patients with cancer-related fatigue. Methods: This was a randomized, parallel-controlled clinical trial, with two arms (experimental and control group), and it was conducted over the course of a year in the Oncology Hospitalization Unit at the University Hospital of Salamanca, Spain. Participants (n = 48) were assessed at three points during the study. The first assessment was prior to hospital discharge, the second assessment was after 15 days, and the final assessment was at one month post-hospital follow-up. The intervention lasted one month. The main variables studied were the dependency levels (Barthel), cancer-related fatigue (FACT-An), health-related quality of life (EuroQoL-5D), functional capacity (SPPB), and kinesiophobia (TSK-F). Results: Sample size (n = 44). Mean age 63.46 ± 12.36 years. Significant differences between control and experimental group participants in Barthel, FACT-An, TSK-F, and SPPB scores at follow-up and final assessment. Conclusions: There are beneficial effects of a multimodal physical exercise and functional rehabilitation program in improving the autonomy of cancer-related fatigue patients.