bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial Characteristics and Temporal Trend of Urban Heat Island Effect over Major Cities in India Using Long-Term Space-Based MODIS Land Surface Temperature Observations (2000–2023)
Authors: Nayak Suren , Vinod Arya , Prasad Anup Krishna
Published: December 2023

The alteration of the Earth’s surface due to urbanization and the formation of urban heat islands is one of the most evident and widely discussed anthropogenic impacts on Earth’s microclimate. The elevated land surface temperature in the urban perimeter compared with the surrounding non-urban area is known as the surface urban heat island (SUHI) effect. India has experienced swift urban growth over the past few decades, and this trend is expected to persist in years to come. The literature published on SUHI in India focuses only on a few specific cities, and there is limited understanding of its geospatial variation across a broader region and its long-term trend. Here, we present one of the first studies exploring the long-term diurnal (daytime, and nighttime), seasonal, and annual characteristics of SUHI in the 20 largest urban centers of India and its neighboring countries. The study highlights a statistically significant (95% confidence interval) rise in nighttime surface temperatures across major cities based on a linear fit over 23 years (2000–2023) of MODIS land surface temperature satellite observations. The nighttime SUHI was found to be more conspicuous, positive, and consistent when compared with daytime satellite observations. The nighttime SUHI for April–May–June representing the pre-monsoon and onset of monsoon months for the top 10 cities, ranged from 0.92 to 2.33 °C; for December–January–February, representing the winter season, it ranged from 1.38 to 2.63 °C. In general, the total change in the nighttime SUHI based on linear fit (2000–2023) for the top ten cities showed warming over the urban region ranging from 2.04 to 3.7 °C. The highest warming trend was observed during the months of May–June–July (3.7 and 3.01 °C) in Ahmedabad and Delhi, cities that have undergone rapid urbanization in the last two to three decades. The study identified strongly positive annual SUHI intensity during nighttime, and weakly negative to moderately positive annual SUHI intensity during daytime, for major cities. Jaipur (India), Lahore (Pakistan), Dhaka (Bangladesh), and Colombo (Sri Lanka) showed a nighttime SUHI intensity of 2.17, 2.33, 0.32, and 0.21 °C, respectively, during the months of April–May–June, and a nighttime SUHI intensity of 2.63, 1.68, 0.94, 0.33 °C, respectively, for the months of December–January–February (2000–2023). It is apparent that the geographical location (inland/coastal) of the city has a high influence on the daytime and nighttime SUHI patterns. The current research is intended to help city planners and policymakers better understand SUHI intensity (day and night/seasonal basis) for developing strategies to mitigate urban heat island effects.
The Nonlinear Dynamic Characteristics of an Industrial Turbine Engine with Eccentric Squeeze Film Dampers
Authors: Zeng Shan , Luo Sigui , Wang Fei , Lan Xifan , Ma Xinrui , Lu Yuxin
Published: December 2023

Squeeze film dampers are often used to suppress vibration in turbine engines and play an important role in rotor systems. In this paper, the nonlinear dynamic characteristics of an industrial turbine engine fitted with squeeze film dampers are investigated with the static eccentricity of the SFDs. A recently developed time domain technique that combines the finite element method and the fixed interface modal synthesis method is applied to predict the nonlinear unbalance response of the industrial turbine engine under different unbalanced and static eccentricity configurations. By comparing the results obtained using SFDs with and without static eccentricity, it can be concluded that increasing the static eccentricity of the SFDs promotes non-periodic motion, while an increase in the unbalance level promotes the jump phenomenon. The efficiency of the rotor system would improve with an appropriate amount of unbalance applied to compressor IV, resulting in a reduction in the vibration level. If static sprung eccentricity occurs, the center of the journal orbit would be offset from the SFD center, rendering it inefficient or even leading to rub impact. Therefore, it is crucial to control the static eccentricity of the SFDs for optimal performance. The time domain technique is verified by the experimental results reported in the literature.
Global Time-Varying Path Planning Method Based on Tunable Bezier Curves
Authors: Jia Longfei , Zeng Si , Feng Lei , Lv Bohan , Yu Zhiyuan , Huang Yuping
Published: December 2023

In this paper, a novel global time-varying path planning (GTVP) method is proposed. In the method, real-time paths can be generated based on tunable Bezier curves, which can realize obstacle avoidance of manipulators. First, finite feature points are extracted to represent the obstacle information according to the shape information and position information of the obstacle. Then, the feature points of the obstacle are converted into the feature points of the curve, according to the scale coefficient and the center point of amplification. Furthermore, a Bezier curve representing the motion path at this moment is generated to realize real-time adjustment of the path. In addition, the 5-degree Bezier curve planning method consider the start direction and the end direction is used in the path planning to avoid the situation of abrupt change with oscillation of the trajectory. Finally, the GTVP method is applied to multi-obstacle environment to realize global time-varying dynamic path planning. Through theoretical derivation and simulation, it can be proved that the path planned by the GTVP method can meet the performance requirements of global regulation, real-time change and multi-obstacle avoidance simultaneously.
Effect of Spindle Speed and Feed Rate on Surface Roughness and Milling Duration in the Fabrication of Milled Complete Dentures: An In Vitro Study
Authors: Akiyama Yo , Iwaki Maiko , Komagamine Yuriko , Minakuchi Shunsuke , Kanazawa Manabu
Published: December 2023

Milling machines have made denture fabrication possible with high accuracy in a short time. However, the relationship between the milling conditions, accuracy, and milling duration has not been clarified. This study aimed to clarify the effects of milling conditions on surface roughness and milling duration. The specimen was designed using CAD software and milled using PMMA disks. In milling, the parameters of finishing the specimen surface were adjusted. Three different spindle speeds and four different feed rates were set. Twelve combinations of each parameter were used for milling, and the surface roughness and milling duration were measured. Results showed that the surface roughness significantly increased with the feed rate on the slopes of the specimen. The surface roughness differed with the spindle speed on the left and right slopes. The spindle speed and feed rate did not affect the surface roughness on the flat surface. The milling duration was not affected by the spindle speed but decreased as the feed rate increased. In conclusion, by increasing both the spindle speed and feed rate, the milling duration could be shortened while maintaining a constant surface quality. The optimum milling conditions were a spindle speed of 40,000 rpm and feed rate of 3500 mm/min.
Multi-Scalar Oblique Photogrammetry-Supported 3D webGIS Approach to Preventive Mining-Induced Deformation Analysis
Authors: Zhu Xiaoyu , Yang Huachao , Bian Hefang , Mei Yang , Zhang Bolun , Xue Peng
Published: December 2023

Underground coal mining will inevitably cause serious ground deformation, and therefore, preventive mining-induced deformation analysis (MIDA) is of great importance in assisting mining planning and decision-making. Current web-based Geographic Information System (webGIS)-based applications usually use 2D GIS data and lack a holistic framework. This study presents a multi-scalar oblique photogrammetry-supported unified 3D webGIS framework for MIDA applications to fill this gap. The developed web platform uses multiple open-source JavaScript libraries, and the prototype system provides user-friendly interfaces for GIS data collecting and corresponding database establishment, geo-visualization and query, dynamic prediction, and spatial overlapping analysis within the same framework. The proposed framework was tested and evaluated in the Qianyingzi mining area in eastern China. The results demonstrated that multi-scalar oblique photogrammetry balances data quality and acquisition efficiency and provides a good source of GIS datasets, and the web-based platform has a good absolute and relative spatial accuracy verified by two types of validation data. Practical application results proved the feasibility and reliability of the system. The developed web-based MIDA prototype system attains an appealing performance and can be easily extended to similar geoscience applications.
Predicting Temperature and Humidity in Roadway with Water Trickling Using Principal Component Analysis-Long Short-Term Memory-Genetic Algorithm Method
Authors: Wu Dong , Jia Zhichao , Zhang Yanqi , Wang Junhui
Published: December 2023

The heat dissipated from high geo-temperature underground surrounding rocks is the main heat source of working faces, while thermal water upwelling and trickling into the roadway will notably deteriorate the mine’s climate and thermal comfort. Predicting airflow temperature and relative humidity (RH) is conductive to intelligent control of air conditioning cooling and ventilation regulation. To accommodate this issue, an intelligent technique was proposed, integrating a genetic algorithm (GA) and long short-term memory (LSTM) based on rock temperature, inlet air temperature, water temperature, water flow rate, RH, and ventilation time. A total of 21 input features including over 200 pieces of data were collected from an independently developed modeling roadway to construct a dataset. Principal component analysis (PCA) was conducted to reduce features, and GA was used to tune the LSTM and PCA-LSTM architectures for best performance. The following research results were yielded. The proposed PCA-LSTM-GA model is more reliable and efficient than the single LSTM model or hybrid LSTM-GA model in predicting the air temperature Tfout and humidity RHout at the end of the water trickling roadway. The importance scores (ISs) indicate that Tfout is mainly influenced by the surrounding rock temperature (IS 0.661) and the inlet air temperature (IS 0.264). While RHout is primarily influenced by the rock temperature in the water trickling section (IS 0.577), the inlet air temperature (IS 0.187), and the trickling water temperature and flow rate (total IS 0.136), and it has an evident time effect. In addition, we developed relevant equipment and provided engineering practice methods to use the machine learning model. The proposed model, which can predict the mine microclimate, serves to facilitate coal and geothermal resource co-mining as well as thermal hazard control.
Convolutional Neural Network-Based Classification of Steady-State Visually Evoked Potentials with Limited Training Data
Authors: Kołodziej Marcin , Majkowski Andrzej , Rak Remigiusz J. , Wiszniewski Przemysław
Published: December 2023

One approach employed in brain–computer interfaces (BCIs) involves the use of steady-state visual evoked potentials (SSVEPs). This article examines the capability of artificial intelligence, specifically convolutional neural networks (CNNs), to improve SSVEP detection in BCIs. Implementing CNNs for this task does not require specialized knowledge. The subsequent layers of the CNN extract valuable features and perform classification. Nevertheless, a significant number of training examples are typically required, which can pose challenges in the practical application of BCI. This article examines the possibility of using a CNN in combination with data augmentation to address the issue of a limited training dataset. The data augmentation method that we applied is based on the spectral analysis of the electroencephalographic signals (EEG). Initially, we constructed the spectral representation of the EEG signals. Subsequently, we generated new signals by applying random amplitude and phase variations, along with the addition of noise characterized by specific parameters. The method was tested on a set of real EEG signals containing SSVEPs, which were recorded during stimulation by light-emitting diodes (LEDs) at frequencies of 5, 6, 7, and 8 Hz. We compared the classification accuracy and information transfer rate (ITR) across various machine learning approaches using both real training data and data generated with our augmentation method. Our proposed augmentation method combined with a convolutional neural network achieved a high classification accuracy of 0.72. In contrast, the linear discriminant analysis (LDA) method resulted in an accuracy of 0.59, while the canonical correlation analysis (CCA) method yielded 0.57. Additionally, the proposed approach facilitates the training of CNNs to perform more effectively in the presence of various EEG artifacts.
Multi-Defect Detection Network for High-Voltage Insulators Based on Adaptive Multi-Attention Fusion
Authors: Hu Yiming , Wen Bin , Ye Yongsheng , Yang Chao
Published: December 2023

Insulators find extensive use across diverse facets of power systems, playing a pivotal role in ensuring the security and stability of electrical transmission. Detecting insulators is a fundamental measure to secure the safety and stability of power transmission, with precise insulator positioning being a prerequisite for successful detection. To overcome challenges such as intricate insulator backgrounds, small defect scales, and notable differences in target scales that reduce detection accuracy, we propose the AC-YOLO insulator multi-defect detection network based on adaptive attention fusion. To elaborate, we introduce an adaptive weight distribution multi-head self-attention module designed to concentrate on intricacies in the features, effectively discerning between insulators and various defects. Additionally, an adaptive memory fusion detection head is incorporated to amalgamate multi-scale target features, augmenting the network’s capability to extract insulator defect characteristics. Furthermore, a CBAM attention mechanism is integrated into the backbone network to enhance the detection performance for smaller target defects. Lastly, improvements to the loss function expedite model convergence. This study involved training and evaluation using publicly available datasets for insulator defects. The experimental results reveal that the AC-YOLO model achieves a notable 5.1% enhancement in detection accuracy compared to the baseline. This approach significantly boosts detection precision, diminishes false positive rates, and fulfills real-time insulator localization requirements in power system inspections.
The Impact of Lytic Viruses on Bacterial Carbon Metabolism in a Temperate Freshwater Reservoir (Naussac, France)
Authors: Pradeep Ram Angia Sriram , Mauduit Marie-Eve , Colombet Jonathan , Perriere Fanny , Thouvenot Antoine , Sime-Ngando Télesphore
Published: December 2023

In aquatic systems, the impact of the viral regulation of bacterial carbon metabolism (BCM) is often overlooked compared with nutrient supply. To address this gap, an investigation was conducted in the euphotic and aphotic zones of a mesotrophic freshwater reservoir (Naussac, France) to assess the relative influence of lytic viral infection on key bacterial metabolic parameters, specifically bacterial production (BP) and respiration (BR), as indicators of BCM. Measured using flow cytometry, the abundance of viral sub-groups (V1–V3) exhibited a consistent pattern in tandem with their bacterial hosts across both time and space. A more significant relationship between bacterial and viral parameters than between physicochemical factors suggested a prevailing internal control mechanism that was potentially driven by viral lysis. Viral-mediated bacterial mortality up to 65% was evident in the euphotic zone. The observed variation in BCM (ranging from 7% to 32%) was explained by an uncoupling between BR and BP. Notably, BR was significantly higher (three-fold) than BP in bacterial communities subjected to low in situ phosphate concentrations (<0.5 µM P) and high nutrient stoichiometric ratios (N:P > 60, C:P > 900). An antagonistic relationship between lytic viruses and BCM, whereby the repression of bacterial growth results in elevated respiratory demands, could potentially be attributed to substrate availability constraints.
Formaldehyde Continuous Monitoring at a Rural Station North of Rome: Appraisal of Local Sources Contribution and Meteorological Drivers
Authors: Vichi Francesca , Bassani Cristiana , Ianniello Antonietta , Esposito Giulio , Montagnoli Mauro , Imperiali Andrea
Published: December 2023

The formaldehyde (HCHO) dataset collected from January to December 2022 at the CNR Liberti Observatory (42.10° N; 12.64° E), a rural site located 30 km NE of Rome, is reported. The daily, weekly, and seasonal trends are examined. The highest average seasonal HCHO concentration (1.9 ppb) was measured during summer, whereas similar values (1.5 ppb) were found for winter and spring periods. The meteorological parameters monitored at the site allowed the interpretations of the maxima observed during the period investigated. The daily trends examined for the different seasonal periods, along with other pollutants available (NO2, NO, and O3), showed how the sources gradually shifted from primary to secondary. The occurrence of wildfires and other events in the area were also considered in explaining peak events (>4.2 ppb). The site examined was sometimes impacted by the nearby urban anthropic pressure of Rome, but in many cases, particularly during the summer months, the influence of the natural background surrounding the site was evident.
Aircraft Measurements of Tropospheric CO2 in the North China Plain in Autumn and Winter of 2018–2019
Authors: Zhang Hui , Yang Qiang , Yuan Hongjie , Ma Dongliang , Liu Zhilei , Jia Jianguang , Wang Guan , Zhang Nana , Su Hailiang , Shi Youyu , Ma Yongjing , Dai Lindong , Li Baojiang , Huang Xiao
Published: December 2023

Quantifying the level of CO2, the main greenhouse gas (GHG), is essential for research on regional and global climate change, especially in the densely populated North China Plain with its severe CO2 emissions. In this study, 12 airborne flights were managed and conducted during the autumn–winter period of 2018–2019 in downtown Shijiazhuang and its surrounding areas, which are representative of the typical urban conditions in the North China Plain, to explore the spatial and temporal distributions of CO2. The results showed that the measured columnar averages of CO2 ranged between 399.9 ± 1.5 and 443.8 ± 31.8 ppm; the average of the 12 flights was 412.1 ppm, slightly higher than the globally averaged 410.5 ± 0.20 ppm and the 2 background concentrations of 411.6 ± 2.1 ppm and 411.4 ± 0.2 ppm in low-latitude Mauna Loa and middle-latitude Waliguan in 2019, indicating the potential influences of anthropogenic activities. The typical stratification of the planetary boundary layer (PBLH), residual layer (RL), and elevated inversion layer (IL) was crucial in constraining the high CO2 concentrations. This illustrated that the warming effect of CO2 within the PBLH may also have some influences on regulating the thermal structure of the low troposphere. Based on a backward trajectory analysis, it was evidenced that there were three different categories of air masses for autumn and one category for winter. Both trajectories in the PBL, i.e., below 1000 m, from the local and southern areas with tremendous anthropogenic emissions (autumn) and from the western regions (winter) led to comparatively high levels of CO2, but the mid-tropospheric CO2 concentrations above 1000 m were commonly homogeneously distributed, with higher levels appearing in winter because the concentration in the free troposphere followed the global seasonal pattern, with a summer minimum and winter maximum as a result of the seasonality of the net CO2 exchange and the balance between photosynthesis and respiration. These results provide an in-depth understanding of the vertical concentrations of tropospheric CO2 in the North China Plain, which will offer scientific references for the evaluation of carbon accounting and carbon emissions.
Neuroprotective Action of Humanin and Humanin Analogues: Research Findings and Perspectives
Authors: Karachaliou Chrysoula-Evangelia , Livaniou Evangelia
Published: December 2023

Humanin is a 24-mer peptide first reported in the early 2000s as a new neuroprotective/cytoprotective factor rescuing neuronal cells from death induced by various Alzheimer’s disease-associated insults. Nowadays it is known that humanin belongs to the novel class of the so-called mitochondrial-derived peptides (which are encoded by mitochondrial DNA) and has been shown to exert beneficial cytoprotective effects in a series of in vitro and/or in vivo experimental models of human diseases, including not only neurodegenerative disorders but other human diseases as well (e.g., age-related macular degeneration, cardiovascular diseases, or diabetes mellitus). This review article is focused on the presentation of recent in vitro and in vivo research results associated with the neuroprotective action of humanin as well as of various, mainly synthetic, analogues of the peptide; moreover, the main mode(s)/mechanism(s) through which humanin and humanin analogues may exert in vitro and in vivo regarding neuroprotection have been reported. The prospects of humanin and humanin analogues to be further investigated in the frame of future research endeavors against neurodegenerative/neural diseases have also been briefly discussed.
Enalapril Is Superior to Lisinopril in Improving Endothelial Function without a Difference in Blood–Pressure–Lowering Effects in Newly Diagnosed Hypertensives
Authors: Nagy Attila , Májer Réka , Boczán Judit , Sipka Sándor , Szabó Attila , Enyedi Enikő Edit , Tatai Ottó , Fagyas Miklós , Papp Zoltán , Csiba László , Tóth Attila
Published: December 2023

Angiotensin–converting enzyme (ACE) inhibitors are the primarily chosen drugs to treat various cardiovascular diseases, such as hypertension. Although the most recent guidelines do not differentiate among the various ACE inhibitory drugs, there are substantial pharmacological differences. Goal: Here, we tested if lipophilicity affects the efficacy of ACE inhibitory drugs when used as the first therapy in newly identified hypertensives in a prospective study. Methods: We tested the differences in the cardiovascular efficacy of the hydrophilic lisinopril (8.3 ± 3.0 mg/day) and the lipophilic enalapril (5.5 ± 2.3 mg/day) (n = 59 patients). The cardiovascular parameters were determined using sonography (flow-mediated dilation (FMD) in the brachial artery, intima-media thickness of the carotid artery), 24 h ambulatory blood pressure monitoring (peripheral arterial blood pressure), and arteriography (aortic blood pressure, augmentation index, and pulse wave velocity) before and after the initiation of ACE inhibitor therapy. Results: Both enalapril and lisinopril decreased blood pressure. However, lisinopril failed to improve arterial endothelial function (lack of effects on FMD) when compared to enalapril. Enalapril-mediated improved arterial endothelial function (FMD) positively correlated with its blood–pressure–lowering effect. In contrast, there was no correlation between the decrease in systolic blood pressure and FMD in the case of lisinopril treatment. Conclusion: The blood–pressure–lowering effects of ACE inhibitor drugs are independent of their lipophilicity. In contrast, the effects of ACE inhibition on arterial endothelial function are associated with lipophilicity: the hydrophilic lisinopril was unable to improve, while the lipophilic enalapril significantly improved endothelial function. Moreover, the effects on blood pressure and endothelial function did not correlate in lisinopril-treated patients, suggesting divergent mechanisms in the regulation of blood pressure and endothelial function upon ACE inhibitory treatment.
Advances of Genome Editing with CRISPR/Cas9 in Neurodegeneration: The Right Path towards Therapy
Authors: Klinkovskij Aleksandr , Shepelev Mikhail , Isaakyan Yuri , Aniskin Denis , Ulasov Ilya
Published: December 2023

The rate of neurodegenerative disorders (NDDs) is rising rapidly as the world’s population ages. Conditions such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and dementia are becoming more prevalent and are now the fourth leading cause of death, following heart disease, cancer, and stroke. Although modern diagnostic techniques for detecting NDDs are varied, scientists are continuously seeking new and improved methods to enable early and precise detection. In addition to that, the present treatment options are limited to symptomatic therapy, which is effective in reducing the progression of neurodegeneration but lacks the ability to target the root cause—progressive loss of neuronal functioning. As a result, medical researchers continue to explore new treatments for these conditions. Here, we present a comprehensive summary of the key features of NDDs and an overview of the underlying mechanisms of neuroimmune dysfunction. Additionally, we dive into the cutting-edge treatment options that gene therapy provides in the quest to treat these disorders.
A Multi-Agent Reinforcement Learning Method for Omnidirectional Walking of Bipedal Robots
Authors: Mou Haiming , Xue Jie , Liu Jian , Feng Zhen , Li Qingdu , Zhang Jianwei
Published: December 2023

Achieving omnidirectional walking for bipedal robots is considered one of the most challenging tasks in robotics technology. Reinforcement learning (RL) methods have proved effective in bipedal walking tasks. However, most existing methods use state machines to switch between multiple policies and achieve omnidirectional gait, which results in shaking during the policy switching process for bipedal robots. To achieve a seamless transition between omnidirectional gait and transient motion for full-size bipedal robots, we propose a novel multi-agent RL method. Firstly, a multi-agent RL algorithm based on the actor–critic framework is designed, and policy entropy is introduced to improve exploration efficiency. By learning agents with parallel initial state distributions, we minimize reliance on gait planner effectiveness in the Robot Operating System (ROS). Additionally, we design a novel heterogeneous policy experience replay mechanism based on Euclidean distance. Secondly, considering the periodicity of bipedal robot walking, we develop a new periodic gait function. Including periodic objectives in the policy can accelerate the convergence speed of training periodic gait functions. Finally, to enhance the robustness of the policy, we construct a novel curriculum learning method by discretizing Gaussian distribution and incorporate it into the robot’s training task. Our method is validated in a simulation environment, and the results show that our method can achieve multiple gaits through a policy network and achieve smooth transitions between different gaits.
Giant Armadillo Optimization: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems
Authors: Alsayyed Omar , Hamadneh Tareq , Al-Tarawneh Hassan , Alqudah Mohammad , Gochhait Saikat , Leonova Irina , Malik Om Parkash , Dehghani Mohammad
Published: December 2023

In this paper, a new bio-inspired metaheuristic algorithm called Giant Armadillo Optimization (GAO) is introduced, which imitates the natural behavior of giant armadillo in the wild. The fundamental inspiration in the design of GAO is derived from the hunting strategy of giant armadillos in moving towards prey positions and digging termite mounds. The theory of GAO is expressed and mathematically modeled in two phases: (i) exploration based on simulating the movement of giant armadillos towards termite mounds, and (ii) exploitation based on simulating giant armadillos’ digging skills in order to prey on and rip open termite mounds. The performance of GAO in handling optimization tasks is evaluated in order to solve the CEC 2017 test suite for problem dimensions equal to 10, 30, 50, and 100. The optimization results show that GAO is able to achieve effective solutions for optimization problems by benefiting from its high abilities in exploration, exploitation, and balancing them during the search process. The quality of the results obtained from GAO is compared with the performance of twelve well-known metaheuristic algorithms. The simulation results show that GAO presents superior performance compared to competitor algorithms by providing better results for most of the benchmark functions. The statistical analysis of the Wilcoxon rank sum test confirms that GAO has a significant statistical superiority over competitor algorithms. The implementation of GAO on the CEC 2011 test suite and four engineering design problems show that the proposed approach has effective performance in dealing with real-world applications.
Green Synthesis of Gold Nanoparticles Using Peach Extract Incorporated in Graphene for the Electrochemical Determination of Antioxidant Butylated Hydroxyanisole in Food Matrices
Authors: Döll Emanuela Grechi , Santana Edson Roberto , Winiarski João Paulo , Baumgarten Luan Gabriel , Vieira Iolanda Cruz
Published: December 2023

Butylated hydroxyanisole (BHA) is a synthetic phenolic antioxidant widely used in various food matrices to prevent oxidative rancidity. However, its presence has been associated with liver damage and carcinogenesis in animals. Thus, an electrochemical sensor was built using a composite of gold nanoparticles synthesized in peach extract (Prunus persica (L.) Batsch) and graphene. Peach extract served as a reducing and stabilizing agent for gold nanoparticles, as a dispersing agent for graphene, and as a film former to immobilize the composite on the surface of a glassy carbon electrode. The gold nanoparticles were characterized using spectroscopic and microscopic techniques, and the electrodes were electrochemically characterized using electrochemical impedance spectroscopy and cyclic voltammetry. The sensor provided higher current responses and lower charge transfer resistances compared to the unmodified glassy carbon electrode. Under the established optimized working conditions (0.1 mol L−1 Britton–Robinson buffer, pH 4.0, and differential pulse voltammetry), the calibration curve exhibited a linear range from 0.2 to 9.8 µmol L–1, with a detection limit of 70 nmol L−1. The proposed sensor represented a sensitive and practical analytical tool for the accurate determination of BHA in mayonnaise samples.
Health-Related Quality of Life in Kindergarten Children with Developmental Language Disorder: Child–Mother Agreement
Authors: Boukouvala Maria , Hyphantis Thomas , Koullourou Iouliani , Tzotzi Alexandra , Mitropoulou Andromachi , Mantas Christos , Petrikis Petros , Serdari Aspasia , Siafaka Vassiliki , Kotsis Konstantinos
Published: December 2023

Language disorders are associated with difficulties in various aspects of life, such as academic and social functioning, resulting in impaired health-related quality of life (HRQoL). Most studies use a parent proxy method to assess HRQoL. Since HRQoL refers to the subjective experience of an individual, it is necessary to assess children’s perspectives along with their mothers’. The aim of the current study is to explore HRQoL rating agreement between children and their mothers, since the literature on other conditions suggests that discrepancies seem to reflect their different perspectives. Thus, 53 Greek-speaking children diagnosed with DLD attending kindergarten and their mothers completed, respectively, self-report and parent proxy PedsQLTM questionnaires. Mothers reported significantly better HRQoL than their children with developmental language disorder (DLD) in all HRQoL domains (p < 0.001). Poor agreement was revealed after comparing the scores from both responders, both in abstract domains, such as emotional functioning, as well as in more observable ones, such as physical health (ICC ranged from −0.05 to 0.07). Bland–Altman plots also showed poor agreement on HRQoL. Our results expand on the already known, from other conditions, importance of evaluating children’s subjective experience of their HRQoL in kindergarten children with DLD. A multi-informant approach is ideal, and clinicians should prioritize children’s view about their lives even when they are kindergarten-age. This approach could inform interventions focusing not only on language skills but also on other areas where it is necessary, depending on the child’s subjective experience combined with the maternal perspective.
Factors Affecting Disaster or Emergency Coping Skills in People with Intellectual Disabilities
Authors: Park Eun-Young
Published: December 2023

This study aimed to investigate the disaster or emergency coping skills of people with intellectual disabilities and the factors that affect these skills. The panel survey on the lives of people with disabilities from the 3rd dataset (2020) of the Korea Development Institute for the Disabled was used for this analysis. Response data from 275 people with intellectual disabilities aged 10 years or older were analyzed. Differences between disaster or emergency coping skill levels and sub-questions of skills, according to the general characteristics of people with intellectual disabilities, were identified, as well as factors affecting the level of disaster or emergency coping skills. The results show that the coping skills level was low; among the sub-questions, the use of fire extinguishers and awareness of the location of fire extinguishers or emergency bells in the event of a disaster or emergency were also low. Factors affecting the level of coping skills were found to be the level of education and experience in comprehensive disaster coping training. The results of this study suggest that training and education on disaster or emergency coping skills for people with intellectual disabilities are necessary and that programs should be developed for this purpose.
Risk Management Practices in Ethiopian Somali Regional State Construction Projects
Authors: Kivrak Serkan , Udan Omar Hiis
Published: December 2023

Risk management practices are critical for construction companies to prevent any problems caused by uncertainties in the projects. This study examines how risk management is practiced in construction projects of the Somali Regional State in Ethiopia. It also identifies the most influential risk factors in the region which need to be given a higher consideration when practicing risk management. Within this context, a questionnaire survey was conducted among construction professionals in the Somali region. Based on the findings, there is a deficient practice of risk management in Somali Regional State construction projects due to a lack of knowledge or budget. Risk factors like design errors, top management changes, insufficient experienced staff, and delays in payment are found to have the highest probability of occurrence in Somali Regional State construction projects. Findings from this study can help construction managers to better understand the risk factors influencing construction projects in the Somali region in the context of improving project performance.
Energy Analysis of a Net-Zero Energy Building Based on Long-Term Measured Data: A Case Study in South Korea
Authors: Hong Jungki , Park Jaewan , Kim Seongmi , Lim Cheolsoo , Kong Minsuk
Published: December 2023

In this study, the energy consumption and generation characteristics, the operation status of a photovoltaic (PV) system, and the energy balance of a net-zero energy building (nZEB) in South Korea were analyzed based on the data collected over a 10-year period (2012–2021). The average annual power consumption of the nZEB was 101.3 MWh, 6.2% higher than the estimated power consumption. The PV system of the nZEB had an annual power generation capacity of 105.8 MWh, indicating an increase of 10.6% compared to the estimated value. The failure of PV systems such as module cracks, inverter failures, and performance degradation led to a decrease of 21.5% in the power generation. Energy balance analysis was conducted by comparing the energy consumption and generation data based on yearly, monthly, daily, and hourly time intervals. In addition, load coverage factor (LCF) and supply coverage factor (SCF) were used to evaluate the load matching rate. The nZEB achieved a net-zero energy status for 5 out of the 7 years of normal operation (2012–2018) based on average annual data. However, the energy balance analysis using hourly measured data showed that there was both a surplus and a shortage of power every year, and that the average annual power surplus and shortage were 56.4 MWh and 54.3 MWh, respectively. In addition, the load matching analysis showed that the annual LCF and SCF were approximately 0.36 and 0.32, respectively. Thus, the advanced nZEB design, hourly data-based energy analysis, fault diagnosis and maintenance, and the strategies enhancing the self-consumption rate should be considered to expand nZEB dissemination.
Effects of Composition Variations on Mechanochemically Synthesized Lithium Metazirconate-Based Ceramics and Their Resistance to External Influences
Authors: Abyshev Bauyrzhan K. , Giniyatova Sholpan G. , Kozlovskiy Artem L.
Published: December 2023

The study examines the influence of variations in the compositions of components for the production of lithium-containing ceramics based on lithium metazirconate obtained by the method of mechanochemical grinding and subsequent thermal sintering. For component variation, two compositions were used, consisting of zirconium dioxide (ZrO2) and two distinct types of lithium-containing materials: lithium perchlorate (LiClO4·3H2O) and lithium carbonate (Li2CO3). Adjusting the concentration of these components allowed for the production of two-phase ceramics with varying levels of impurity phases. Using X-ray phase analysis methods, it was determined that the use of LiClO4·3H2O results in the formation of a monoclinic phase, Li2ZrO3, with impurity inclusions in the orthorhombic phase, LiO2. On the other hand, when Li2CO3 is used, the resulting ceramics comprise a mixture of two phases, Li2ZrO3 and Li6Zr2O7. During the studies, it was established that the formation of impurity inclusions in the composition of ceramics leads to an increase in the stability of strength properties with varying mechanical test conditions, as well as stabilization of thermophysical parameters and a decrease in thermal expansion during long-term high-temperature tests. It has been established that in the case of two-phase ceramics Li2ZrO3/Li6Zr2O7 in which the dominance of the Li6Zr2O7 phase is observed during high-temperature mechanical tests, a more pronounced decrease in resistance to cracking is observed, due to thermal expansion of the crystal lattice.
Evaluation of the DigiBete App, a Self-Management App for Type 1 Diabetes: Experiences of Young People, Families, and Healthcare Professionals
Authors: Kime Nicky , Zwolinsky Steve , Pringle Andy
Published: December 2023

Type 1 diabetes (T1DM) is a public health issue for children, young people, and families (CYPF) and requires innovative interventions. The DigiBete app is a self-management and educational app to help CYPF and healthcare professionals (HCPs) manage T1DM, featuring educational advice and resources such as guidance, quizzes, and educational and instructional videos on how to manage T1DM. To assess the impact and implementation of the app, the service-level evaluation deployed a mixed-methods design. App data were captured via the DigiBete platform and an online survey with a non-probability sample of HCPs (N = 178) and CYPF (N = 1165) = 1343. Overall, 55.7% (n = 512/919) of app users were female, and 4855 videos were viewed across the participating areas, with an average of 1213 videos per site (range 776–1679) and 4.4 videos per app user. The most popular videos were how to give a glucagon injection and “My Sick Day Rules”, which showed what to do when CYPF were unwell due to T1DM. Interviews (n = 63) were undertaken with 38 CYPF and 25 HCPs. The findings indicate that CYPF and HCPs found the app an essential tool in the management of T1DM. CYPF and HCPs felt the app provided a valuable educational resource in a central location that was invaluable in an emergency or unknown situation. The app was a trusted and bona-fide source of information that could be accessed at any time. HCPs validated DigiBete in helping CYPF to manage their T1DM. At the same time, the app saved HCPs’ service time and money and helped CYPF take back some of the control in managing their diabetes.
Precipitation Projection in Cambodia Using Statistically Downscaled CMIP6 Models
Authors: Duong Seyhakreaksmey , Song Layheang , Chhin Rattana
Published: December 2023

The consequences of climate change are arising in the form of many types of natural disasters, such as flooding, drought, and tropical cyclones. Responding to climate change is a long horizontal run action that requires adaptation and mitigation strategies. Hence, future climate information is essential for developing effective strategies. This study explored the applicability of a statistical downscaling method, Bias-Corrected Spatial Disaggregation (BCSD), in downscaling climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and then applied the downscaled data to project the future condition of precipitation pattern and extreme events in Cambodia. We calculated four climate change indicators, namely mean precipitation changes, consecutive dry days (CDD), consecutive wet days (CWD), and maximum one-day precipitation (rx1day) under two shared socioeconomic pathways (SSPs) scenarios, which are SSP245 and SSP585. The results indicated the satisfactory performance of the BCSD method in capturing the spatial feature of orographic precipitation in Cambodia. The analysis of downscaled CMIP6 models shows that the mean precipitation in Cambodia increases during the wet season and slightly decreases in the dry season, and thus, there is a slight increase in annual rainfall. The projection of extreme climate indices shows that the CDD would likely increase under both climate change scenarios, indicating the potential threat of dry spells or drought events in Cambodia. In addition, CWD would likely increase under the SSP245 scenario and strongly decrease in the eastern part of the country under the SSP585 scenario, which inferred that the wet spell would have happened under the moderate scenario of climate change, but it would be the opposite under the SSP585 scenario. Moreover, rx1day would likely increase over most parts of Cambodia, especially under the SSP585 scenario at the end of the century. This can be inferred as a potential threat to extreme rainfall triggering flood events in the country due to climate change.
Inducing Cough Reflex by Capsaicin Spray Stimulation in Patients with Acquired Brain Injury: A Preliminary Test and Proof of Concept
Authors: Spezzano Luisa , Cortese Maria Daniela , Quintieri Maria , Pignolo Loris , Tonin Paolo , Lucca Francesca Lucia , Tomaiuolo Francesco , Calabrò Rocco Salvatore , Morone Giovanni , Cerasa Antonio
Published: December 2023

Individuals with acquired brain injuries (ABIs) may experience various complications related to poor coughing or impaired cough reflex (including risk of aspiration pneumonia or respiratory infections). For this reason, cough assessment is an important component in the clinical evaluation since patients with ABI are not able to cough voluntarily due to severe motor deficits. When voluntarily coughing is not possible, it is essential for clinical practices to find a quick and minimally invasive way to induce a cough reflex. In the present study, we evaluated the cough reflex in ABI patients using a new method based on a capsaicin spray stimulation test. In total, 150 healthy controls demographically matched with 50 ABI patients were included in this study. Clinical observations demonstrated robust cough response in both healthy controls and ABI patients, as well as the safety and tolerability of capsaicin spray stimulation. ABI patients with dysphagia were characterized by slower and delayed cough responses. Further studies are needed to validate this feasible, less-invasive, and simple-to-comprehend technique in inducing cough reflex. According to this preliminary evidence, we believe that this test might be translated into a simple and effective treatment to improve reflexive cough modulation in ABI patients.
Early Ambulation Shortened the Length of Hospital Stay in ICU Patients after Abdominal Surgery
Authors: Amari Takashi , Matta Daiki , Makita Yukiho , Fukuda Kyosuke , Miyasaka Hiroki , Kimura Masami , Sakamoto Yuta , Shimo Satoshi , Yamaguchi Kenichiro
Published: December 2023

The optimal time to ambulation remains unclear for intensive care unit (ICU) patients following abdominal surgery. While previous studies have explored various mobilization techniques, a direct comparison between ambulation and other early mobilization methods is lacking. Additionally, the impact of time to ambulation on complications and disuse syndrome prevention requires further investigation. This study aimed to identify the optimal time to ambulation for ICU patients after abdominal surgery and considered its potential influence on complications and disuse syndrome. We examined the relationship between time to ambulation and hospital length of stay (LOS). Patients were categorized into the nondelayed (discharge within the protocol time) and delayed (discharge later than expected) groups. Data regarding preoperative functioning, postoperative complications, and time to discharge were retrospectively collected and analyzed. Of the 274 postsurgical patients managed in the ICU at our hospital between 2018 and 2020, 188 were included. Time to ambulation was a significant prognostic factor for both groups, even after adjusting for operative time and complications. The area under the curve was 0.72, and the cutoff value for time to ambulation was 22 h (sensitivity, 68%; specificity, 77%). A correlation between time to ambulation and complications was observed, with both impacting the hospital LOS (model 1: p < 0.01, r = 0.22; model 2: p < 0.01, r = 0.29). Specific cutoff values for time to ambulation will contribute to better surgical protocols.
Microstructure and Texture of Pure Copper under Large Compression Deformation and Different Annealing Times
Authors: Li Xiuqing , Zhang Qian , Lou Wenpeng , Li Fengjun , Liang Jianjun , Gu Shimin
Published: December 2023

In this study, the plastic deformation of pure copper under room-temperature compression and different annealing times was examined, and the microstructure and texture evolution were studied via scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and microhardness tests. The results showed that when the deformation degree was 93.75%, the microhardness increased from 76 HV (Vickers hardness) before deformation to 110 HV. After annealing, the hardness decreased with increasing annealing time, and the pure copper grain size could be refined from 150 μm to 6.15 μm. An increase in annealing time did not continue to promote recrystallization, while the effect on grain refinement was weakened. The geometrically necessary dislocation (GND) density decreased from 6.0 × 1014/m2 to 4.83 × 1014/m2 after annealing, which implies that static recrystallization occurs at the cost of dislocation consumption during the annealing process. The compression deformation of pure copper produced a strong deformation weave (<001> orientation), and a portion of the deformation weave within the material was transformed into a recrystallization weave (<111> orientation) after the annealing process.