bluuebunny/crossref_metadata_2025 huggingface dataset:
Client Oriented Scale of Improvement in First-Time and Experienced Hearing Aid Users: An Analysis of Five Predetermined Predictability Categories through Audiometric and Speech Testing
Authors: Salvago Pietro , Vaccaro Davide , Plescia Fulvio , Vitale Rossana , Cirrincione Luigi , Evola Lucrezia , Martines Francesco
Published: July 2024

Objectives: The aim of our investigation was to explore the relationship between unaided pure-tone and speech audiometry and self-reported aided performance measured according to five predetermined COSI categories among first-time hearing aid users and experienced hearing aid users. Methods: Data from 286 patients were retrospectively evaluated. We divided the sample into first-time hearing aid users (G1) and experienced hearing aid users (G2). The correlation between unaided tonal and speech audiometry and five preliminary selected client-oriented scale of improvement (COSI) categories was studied. Results: A greater percentage of hearing aid users aged >80 years and a higher prevalence of severe-to-profound hearing loss in G2 group were observed (p < 0.05). For the total cohort, a mean hearing threshold of 60.37 ± 18.77 db HL emerged in the right ear, and 59.97 ± 18.76 db HL was detected in the left ear (p > 0.05). A significant statistical difference was observed in the group of first-time hearing aid users for the “Television/Radio at normal volume” item, where patients with a lower speech intellection threshold (SIT) were associated with higher COSI scores (p = 0.019). Studying the relationship between the speech reception threshold (SRT) and the COSI item “conversation with 1 or 2 in noise” evidenced worse speech audiometry in patients who scored ≤2 among experienced hearing aid users (p = 0.00012); a higher mean 4–8 kHz frequencies threshold for the better ear was found within the G2 group among those who scored ≤2 in the COSI item “conversation with 1 or 2 in quiet” (p = 0.043). Conclusions: Our study confirms a poor correlation between unaided tonal and speech audiometry and self-reported patient assessment. Although we included only five COSI categories in this study, it is clear that unaided audiometric tests may drive the choice of proper hearing rehabilitation, but their value in predicting the benefit of hearing aids remains limited.
A Network Analysis of Perinatal Depression, Anxiety, and Temperaments in Women in the First, Second, and Third Trimesters of Pregnancy
Authors: Mazza Marianna , Brisi Caterina , Veneziani Giorgio , Lisci Francesco Maria , Sessa Ilenia , Balocchi Marta , Rossi Sara , Di Stasio Enrico , Marano Giuseppe , Abate Francesca , Anesini Maria Benedetta , Boggio Gianluca , Ciliberto Michele , De Masi Valeria , Falsini Cecilia , Marzo Ester Maria , Avallone Carla , Serio Annamaria , Gonsalez del Castillo Angela , Kotzalidis Georgios Demetrios , Chieffo Daniela Pia Rosaria , Lanzone Antonio , Scambia Giovanni , Lai Carlo , Sani Gabriele
Published: July 2024

Background/Objectives: Although depression and anxiety are found to be affected by temperaments, little research has studied these relationships in pregnancy. The present study explored the associations among perinatal depression (PD), anxiety dimensions (state, trait, and generalized anxiety disorder (GAD)), and temperaments between women in the three trimesters of pregnancy through a network analysis approach. Moreover, differences in the severity of PD and anxiety between women in the three trimesters were evaluated. Methods: Women in first (N = 31), second (N = 184), and third (N = 54) trimesters of pregnancy were recruited in the present cross-sectional study. The network analysis included PD, anxiety dimensions, and temperaments. Three network models were estimated, and ANOVAs evaluated the differences in the severity of PD and anxiety, including trimesters as a between-subject factor. Results: PD and GAD were the nodes most strongly connected across the three groups. Cyclothymic, depressive, and anxious temperaments were most frequently associated with PD and GAD. Hyperthymic temperament was in the periphery of the three networks. Lastly, women in the first trimester had the highest severity of PD and GAD. Conclusions: PD and GAD showed the strongest associations. Anxiety dimensions had positive associations with PD and GAD, suggesting their role as possible risk factors. Temperaments were differently associated within the network between the three groups. Clinical interventions during pregnancy should target the central variables, considering their direct and indirect relationships.
Anthropometric and Somatotype Profile of Elite Finn Class Sailors
Authors: Pezelj Luka , Milavić Boris , Milić Mirjana
Published: July 2024

Determining the reference base of anthropometric parameters on a sample of elite athletes is one of the foundations of further research and forming a clearer picture of each sport and sports discipline. In this study, the aim was to describe the anthropometric and somatotype profiles of elite Finn class sailors and to determine the differences in the measured parameters between sailors at different levels of general competitive success. The subject sample included 57 Finn class sailors who competed at the open Finn European Championship. A set of 25 anthropometric variables were applied. The sailors were divided into three groups according to their level of general competitive success using World Sailing Rankings. Finn sailors had higher average values in almost all morphological characteristics when compared to the sailors in other Olympic classes. Considering the average values of somatotype categories, we determined that Finn sailors fit the endomorphic mesomorph somatotype category (3.94 ± 1.19 − 5.50 ± 1.19 − 1.63 ± 0.74). Significant differences were observed between more-successful, medium, and less-successful sailors in the variables of age, body mass, muscle mass, arm muscle mass, and endomorphy rating. These results indicate the possibility of selection processes and/or adaptation to sailing occurring in the Finn class. The anthropometric characteristics of Finn sailors compared to sailors in Olympic classes further “support” the Finn class being called the “heavy dinghy” male class. This study on anthropometric parameters, determined via a sample of top Finn sailors, may be of great help to coaches and young sailors when deciding on the selection of an adult sailing class.
Cost Modelling for Powder Bed Fusion and Directed Energy Deposition Additive Manufacturing
Authors: Khanna Navneet , Salvi Harsh , Karaş Büşra , Fairoz Ishrat , Shokrani Alborz
Published: July 2024

Additive manufacturing (AM) is increasingly used for fabricating parts directly from digital models, usually by depositing and bonding successive layers of various materials such as polymers, metals, ceramics, and composites. The design freedom and reduced material consumption for producing near-net-shaped components have made AM a popular choice across various industries, including the automotive and aerospace sectors. Despite its growing popularity, the accurate estimation of production time, productivity and cost remains a significant challenge due to the ambiguity surrounding the technology. Hence, reliable cost estimation models are necessary to guide decisions throughout product development activities. This paper provides a thorough analysis of the state of the art in cost models for AM with a specific focus on metal Directed Energy Deposition (DED) and Powder Bed Fusion (PBF) processes. An overview of DED and PBF processes is presented to enhance the understanding of how process parameters impact the overall cost. Consequently, suitable costing techniques and significant cost contributors in AM have been identified and examined in-depth. Existing cost modelling approaches in the field of AM are critically evaluated, leading to the suggestion of a comprehensive cost breakdown including often-overlooked aspects. This study aims to contribute to the development of accurate cost prediction models in supporting decision making in the implementation of AM.
A High-Efficiency Theorical Model of Von Karman–Generalized Wagner Model–Modified Logvinovich Model for Solving Water-Impacting Problem of Wedge
Authors: Liu Weiqin , Liu Tao , Hu Qi , Wang Mingzhen , Song Xuemin , Chen Hao
Published: July 2024

The water-impacting behavior of a wedge is often studied in the slamming phenomenon of ships and aircraft. Many scholars have proposed theoretical models for studying the water-impacting problem of a wedge, but these models still have some shortcomings. This study combines Von Karman’s method, the Generalized Wagner Model (GWM), and Modified Logvinovich Model (MLM) to establish a converged theoretical Von Karman-GWM-MLM (VGM) model. The VGM model utilizes added mass to replace the fluid influence, which is derived from the velocity potential and boundary conditions. Considering the influence of impulse, the velocity is determined by the momentum theorem. Subsequently, the pressure, resultant force, and acceleration of the wedge can be calculated. By comparing with the published test data of other scholars, it is found that the velocity, acceleration, pressure, and force of the wedge obtained by the VGM model reached a consensus with experiments. The validity and accuracy of the VGM model are also verified. The efficiency and accuracy of problem-solving are both balanced when using the VGM model. The establishment of the VGM model is significant for solving water-impacting problems related to wedges.
Enhanced YOLOv7 for Improved Underwater Target Detection
Authors: Lu Daohua , Yi Junxin , Wang Jia
Published: July 2024

Aiming at the problems of the underwater existence of some targets with relatively small size, low contrast, and a lot of surrounding interference information, which lead to a high leakage rate and low recognition accuracy, a new improved YOLOv7 underwater target detection algorithm is proposed. First, the original YOLOv7 anchor frame information is updated by the K-Means algorithm to generate anchor frame sizes and ratios suitable for the underwater target dataset; second, we use the PConv (Partial Convolution) module instead of part of the standard convolution in the multi-scale feature fusion module to reduce the amount of computation and number of parameters, thus improving the detection speed; then, the existing CIou loss function is improved with the ShapeIou_NWD loss function, and the new loss function allows the model to learn more feature information during the training process; finally, we introduce the SimAM attention mechanism after the multi-scale feature fusion module to increase attention to the small feature information, which improves the detection accuracy. This method achieves an average accuracy of 85.7% on the marine organisms dataset, and the detection speed reaches 122.9 frames/s, which reduces the number of parameters by 21% and the amount of computation by 26% compared with the original YOLOv7 algorithm. The experimental results show that the improved algorithm has a great improvement in detection speed and accuracy.
Risk Performance Analysis on Navigation of MASS via a Hybrid Framework of STPA and HMM: Evidence from the Human–Machine Co-Driving Mode
Authors: Li Wei , Chen Weijiong , Guo Yunlong , Hu Shenping , Xi Yongtao , Wu Jianjun
Published: July 2024

The remote control ship is considered to be the most likely implementation of maritime autonomous surface ships (MASS) in the near-term future. With collaborative control from onboard controllers and operators ashore, ships may operate in three navigation control modes (NCMs), manual, autonomous, and remote control, based on different levels of control authority. The scientific selection of the appropriate NCM for MASS under multiple driving modes is crucial for ensuring ship navigation safety and holds significant importance for operators and regulatory authorities overseeing maritime traffic within specific areas. To aid in selecting the proper NCM, this study introduces a risk-based comparison method for determining optimal control modes in specific scenarios. Firstly, safety control paths and processes for MASS under different NCMs are constructed and analyzed using system-theoretic process analysis (STPA). By analyzing unsafe system control actions, key Risk Influencing Factors (RIFs) and their interrelationships are identified. Secondly, a Hidden Markov Model (HMM) process risk assessment model is developed to infer risk performance (hidden state) through measuring RIF states. Cloud modeling with expert judgments is utilized to parameterize the HMM while addressing inherent uncertainty. Lastly, the applicability of the proposed framework was verified through simulation case studies. Typical navigation scenarios of conventional ships in coastal waters were chosen, and real-time data collected by relevant sensors during navigation were used as simulation inputs. Results suggest that in the same scenario, process risks differ among the analyzed NCMs. Traffic complexity, traffic density, and current become the primary factors influencing navigation risks, and it is necessary to select the appropriate NCM based on their real-time changes.
CFFI-Vit: Enhanced Vision Transformer for the Accurate Classification of Fish Feeding Intensity in Aquaculture
Authors: Liu Jintao , Becerra Alfredo Tolón , Bienvenido-Barcena José Fernando , Yang Xinting , Zhao Zhenxi , Zhou Chao
Published: July 2024

The real-time classification of fish feeding behavior plays a crucial role in aquaculture, which is closely related to feeding cost and environmental preservation. In this paper, a Fish Feeding Intensity classification model based on the improved Vision Transformer (CFFI-Vit) is proposed, which is capable of quantifying the feeding behaviors of rainbow trout (Oncorhynchus mykiss) into three intensities: strong, moderate, and weak. The process is outlined as follows: firstly, we obtained 2685 raw feeding images of rainbow trout from recorded videos and classified them into three categories: strong, moderate, and weak. Secondly, the number of transformer encoder blocks in the internal structure of the ViT was reduced from 12 to 4, which can greatly reduce the computational load of the model, facilitating its deployment on mobile devices. And finally, a residual module was added to the head of the ViT, enhancing the model’s ability to extract features. The proposed CFFI-Vit has a computational load of 5.81 G (Giga) Floating Point Operations per Second (FLOPs). Compared to the original ViT model, it reduces computational demands by 65.54% and improves classification accuracy on the validation set by 5.4 percentage points. On the test set, the model achieves precision, recall, and F1 score of 93.47%, 93.44%, and 93.42%, respectively. Additionally, compared to state-of-the-art models such as ResNet34, MobileNetv2, VGG16, and GoogLeNet, the CFFI-Vit model’s classification accuracy is higher by 6.87, 8.43, 7.03, and 5.65 percentage points, respectively. Therefore, the proposed CFFI-Vit can achieve higher classification accuracy while significantly reducing computational demands. This provides a foundation for deploying lightweight deep network models on edge devices with limited hardware capabilities.
Wind Energy Production in Italy: A Forecasting Approach Based on Fractional Brownian Motion and Generative Adversarial Networks
Authors: Di Persio Luca , Fraccarolo Nicola , Veronese Andrea
Published: July 2024

This paper focuses on developing a predictive model for wind energy production in Italy, aligning with the ambitious goals of the European Green Deal. In particular, by utilising real data from the SUD (South) Italian electricity zone over seven years, the model employs stochastic differential equations driven by (fractional) Brownian motion-based dynamic and generative adversarial networks to forecast wind energy production up to one week ahead accurately. Numerical simulations demonstrate the model’s effectiveness in capturing the complexities of wind energy prediction.
Joint Statistical Inference for the Area under the ROC Curve and Youden Index under a Density Ratio Model
Authors: Liu Siyan , Tian Qinglong , Liu Yukun , Li Pengfei
Published: July 2024

The receiver operating characteristic (ROC) curve is a valuable statistical tool in medical research. It assesses a biomarker’s ability to distinguish between diseased and healthy individuals. The area under the ROC curve (AUC) and the Youden index (J) are common summary indices used to evaluate a biomarker’s diagnostic accuracy. Simultaneously examining AUC and J offers a more comprehensive understanding of the ROC curve’s characteristics. In this paper, we utilize a semiparametric density ratio model to link the distributions of a biomarker for healthy and diseased individuals. Under this model, we establish the joint asymptotic normality of the maximum empirical likelihood estimator of (AUC,J) and construct an asymptotically valid confidence region for (AUC,J). Furthermore, we propose a new test to determine whether a biomarker simultaneously exceeds prespecified target values of AUC0 and J0 with the null hypothesis H0:AUC≤AUC0 or J≤J0 against the alternative hypothesis Ha:AUC>AUC0 and J>J0. Simulation studies and a real data example on Duchenne Muscular Dystrophy are used to demonstrate the effectiveness of our proposed method and highlight its advantages over existing methods.
A Condition-Monitoring Methodology Using Deep Learning-Based Surrogate Models and Parameter Identification Applied to Heat Pumps
Authors: Rousseau Pieter , Laubscher Ryno
Published: July 2024

Online condition-monitoring techniques that are used to reveal incipient faults before breakdowns occur are typically data-driven or model-based. We propose the use of a fundamental physics-based thermofluid model of a heat pump cycle combined with deep learning-based surrogate models and parameter identification in order to simultaneously detect, locate, and quantify degradation occurring in the different components. The methodology is demonstrated with the aid of synthetically generated data, which include the effect of measurement uncertainty. A “forward” neural network surrogate model is trained and then combined with parameter identification which minimizes the residuals between the surrogate model results and the measured plant data. For the forward approach using four measured performance parameters with 100 or more measured data points, very good prediction accuracy is achieved, even with as much as 20% noise imposed on the measured data. Very good accuracy is also achieved with as few as 10 measured data points with noise up to 5%. However, prediction accuracy is reduced with less data points and more measurement uncertainty. A “backward” neural network surrogate model can also be applied directly without parameter identification and is therefore much faster. However, it is more challenging to train and produce less accurate predictions. The forward approach is fast enough so that the calculation time does not impede its application in practice, and it can still be applied if some of the measured performance parameters are no longer available, due to sensor failure for instance, albeit with reduced accuracy.
Experimental and Theoretical Studies on Indigo-Dye-Modified Conjugated Polymers
Authors: Douglas Tionna , Singh Neetika , Riaz Ufana
Published: July 2024

The present work reports the synthesis of indigo-dye-incorporated polyaniline (Indigo-PANI), poly(1-naphthylamine) (Indigo-PNA), poly(o-phenylenediamine) (Indigo-POPD), polypyrrole (Indigo-PPy), and polythiophene (Indigo-PTh) via an ultrasound-assisted method. The synthesized oligomers were characterized using FTIR, UV–visible spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), fluorescence studies, and thermogravimetric analysis (TGA). The experimental data were theoretically compared to analyze the vibrational and electronic spectra via time-dependent density-functional theory (TD-DFT) by applying the Becke, three-parameter, and Lee-Yang-Parr (B3LYP) method with a 6-311G (d,p) basis set. The experimental, theoretical vibrational, and electronic spectra were found to be in close agreement and confirmed the successful incorporation of indigo dye in PANI, PNA, POPD, PPy, and PTh. These studies confirmed that multifunctional oligomers could be synthesized through a facile technique by incorporating dye moieties to enhance their optoelectronic properties, allowing them to be utilized as near-infrared-emitting probes for photodynamic therapy.
Cultural Heritage as a Didactic Resource through Extended Reality: A Systematic Review of the Literature
Authors: Dordio Andrea , Lancho Eva , Merchán María José , Merchán Pilar
Published: July 2024

Extended reality, which encompasses virtual, augmented, and mixed reality, emerges as an important didactic resource, offering great potential to bring heritage closer to the educational environment. Heritage education is a challenge for today’s society, contributing to cultural and social development. Therefore, the aim of this systematic review is to analyze documents related to heritage in education through extended reality. The search was conducted using Scopus and Web of Sciences databases, allowing for an international search. We excluded any document that was not a scientific article published in a journal. A total of 52 documents were analyzed, all of which were open-access articles. Preliminary results indicate that virtual reality and augmented reality are utilized in education to work with architectural, historical, archaeological, and musical heritage. Extended reality has been applied in all the stages of the education system, and in formal and non-formal settings, thereby demonstrating its versatility. These experiences increase motivation and academic performance in comparison to less innovative methodologies, which is in line with other studies on this topic. In conclusion, extended reality has the potential to make a significant impact on education, particularly when combined with heritage. The creation of multidisciplinary groups will enhance research in the near future.
Chemical Compositions and Fumigation Effects of Essential Oils Derived from Cardamom, Elettaria cardamomum (L.) Maton, and Galangal, Alpinia galanga (L.) Willd, against Red Flour Beetle, Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae)
Authors: Wanna Ruchuon , Khaengkhan Parinda , Bozdoğan Hakan
Published: July 2024

This study explores the use of essential oils from cardamom (Elettaria cardamomum (L.) Maton) and galangal (Alpinia galanga (L.) Willd) as alternatives to synthetic insecticides for controlling the red flour beetle, Tribolium castaneum (Herbst). The chemical compositions of these oils were analyzed using GC-MS, and their fumigation effects were tested in a vapor-phase bioassay. The experiment followed a factorial design with four types of essential oils, namely, those manually extracted from cardamom leaves (MCL) and galangal leaves (MGL) and those commercially produced from cardamom seeds (CCS) and galangal rhizomes (CGR), at seven concentrations (0, 50, 100, 150, 200, 250, and 300 µL/L air). The manually extracted oils yielded 0.6% from cardamom leaves and 0.25% from galangal leaves. MCL contained 28 components, with eucalyptol (25.2%) being the most abundant, while CCS had 34 components, primarily α-terpinyl acetate (46.1%) and eucalyptol (31.2%). MGL included 25 components, mainly caryophyllene (28.7%) and aciphyllene (18.3%), whereas CGR comprised 27 components, with methyl cis-cinnamate (47.3%) and safrole (19.8%) as the major constituents. The fumigation bioassay results revealed that CGR was the most effective, demonstrating the highest mortality rates of T. castaneum across all the tested periods and concentrations, achieving up to 96% mortality at 168 h with a concentration of 300 µL/L air. Statistical analyses showed significant differences in mortality based on the type and concentration of essential oil, particularly after 96 h. These findings highlight the potential of CGR, with its advantages and differences in chemical composition, as an effective biopesticide against T. castaneum, with increasing efficacy over time and at higher concentrations.
Diurnal High Temperatures Affect the Physiological Performance and Fruit Quality of Highbush Blueberry (Vaccinium corymbosum L.) cv. Legacy
Authors: González-Villagra Jorge , Ávila Kevin , Gajardo Humberto A. , Bravo León A. , Ribera-Fonseca Alejandra , Jorquera-Fontena Emilio , Curaqueo Gustavo , Roldán Cecilia , Falquetto-Gomes Priscilla , Nunes-Nesi Adriano , Reyes-Díaz Marjorie M.
Published: July 2024

In this study, the physiological performance and fruit quality responses of the highbush blueberry (Vaccinium corymbosum) cultivar Legacy to high temperatures (HTs) were evaluated in a field experiment. Three-year-old V. corymbosum plants were exposed to two temperature treatments between fruit load set and harvest during the 2022/2023 season: (i) ambient temperature (AT) and (ii) high temperature (HT) (5 °C ± 1 °C above ambient temperature). A chamber covered with transparent polyethylene (100 µm thick) was used to apply the HT treatment. In our study, the diurnal temperature was maintained with a difference of 5.03 °C ± 0.12 °C between the AT and HT treatments. Our findings indicated that HT significantly decreased CO2 assimilation (Pn) by 45% and stomatal conductance (gs) by 35.2% compared to the AT treatment. By contrast, the intercellular CO2 concentration (Ci) showed higher levels (about 6%) in HT plants than in AT plants. Fruit quality analyses revealed that the fruit weight and equatorial diameter decreased by 39% and 13%, respectively, in the HT treatment compared to the AT treatment. By contrast, the firmness and total soluble solids (TSS) were higher in the HT treatment than in the AT treatment. Meanwhile, the titratable acidity showed no changes between temperature treatments. In our study, Pn reduction could be associated with stomatal and non-stomatal limitations under HT treatment. Although these findings improve our understanding of the impact of HTs on fruit growth and quality in V. corymbosum, further biochemical and molecular studies are need.
In the Qaidam Basin, Soil Nutrients Directly or Indirectly Affect Desert Ecosystem Stability under Drought Stress through Plant Nutrients
Authors: Zhao Yunhao , Chen Hui , Sun Hongyan , Yang Fan
Published: July 2024

The low nutrient content of soil in desert ecosystems results in unique physiological and ecological characteristics of plants under long-term water and nutrient stress, which is the basis for the productivity and stability maintenance of the desert ecosystem. However, the relationship between the soil and the plant nutrient elements in the desert ecosystem and its mechanism for maintaining ecosystem stability is still unclear. In this study, 35 sampling sites were established in an area with typical desert vegetation in the Qaidam Basin, based on a drought gradient. A total of 90 soil samples and 100 plant samples were collected, and the soil’s physico-chemical properties, as well as the nutrient elements in the plant leaves, were measured. Regression analysis, redundancy analysis (RDA), the Theil–Sen Median and Mann–Kendall methods, the structural equation model (SEM), and other methods were employed to analyze the distribution characteristics of the soil and plant nutrient elements along the drought gradient and the relationship between the soil and leaf nutrient elements and its impact on ecosystem stability. The results provided the following conclusions: Compared with the nutrient elements in plant leaves, the soil’s nutrient elements had a more obvious regularity of distribution along the drought gradient. A strong correlation was observed between the soil and leaf nutrient elements, with soil organic carbon and alkali-hydrolyzed nitrogen identified as important factors influencing the leaf nutrient content. The SEM showed that the soil’s organic carbon had a positive effect on ecosystem stability by influencing the leaf carbon, while the soil’s available phosphorus and the mean annual temperature had a direct positive effect on stability, and the soil’s total nitrogen had a negative effect on stability. In general, the soil nutrient content was high in areas with a low mean annual temperature and high precipitation, and the ecosystem stability in the area distribution of typical desert vegetation in the Qaidam Basin was low. These findings reveal that soil nutrients affect the stability of desert ecosystems directly or indirectly through plant nutrients in the Qaidam Basin, which is crucial for maintaining the stability of desert ecosystems with the background of climate change.
Information Gap Decision Theory-Based Robust Economic Dispatch Strategy Considering the Uncertainty of Electric Vehicles
Authors: Guo Yongqing , Yu Junhui , Yang Yan , Ma Hengrui
Published: July 2024

With the development of renewable energy power systems, electric vehicles, as an important carrier of green transportation, are gradually having an impact on the power grid load curve due to their charging behavior. However, the significant influx of electric vehicles (EVs) and distributed power sources has led to multiple uncertainties, increasing the difficulty in making grid scheduling decisions. Traditional robust scheduling strategies tend to be overly conservative, resulting in poor economic performance. Therefore, this paper proposes a robust and economic dispatch strategy for park power grids based on the information gap decision theory (IGDT). Firstly, based on the probabilistic characteristics of the spatial and temporal distribution of EVs charging, the Monte Carlo method is used to generate typical electricity usage scenarios for EVs. Simultaneously, an economic dispatch model for the park power grid is established with the objective of minimizing operating costs. Taking into account the uncertainty of renewable energy output, simulation analysis is conducted through the IGDT model. Finally, through the verification of the improved IEEE-33 node test system and comparison with other methods, the proposed approach in this paper can reduce decision conservatism and effectively reconcile the contradiction. Through analysis, the proposed method in this paper can reduce the total operational cost of the system by up to 3.2%, with a computational efficiency of only 8.9% of the traditional stochastic optimization time.
Hepatoprotective Effects of Aqueous Extract of Perilla fructescens against Alcohol-Induced Liver Injury in Mice
Authors: Jo Ara , Han Songiy , Lim Sungchul , Choi Chulyung
Published: July 2024

Excessive alcohol intake leads to significant physiological complications, particularly alcoholic liver diseases (ALD). The extent of liver damage caused by ethanol correlates with increased oxidative stress and accumulation of lipids in the hepatic tissue. In this study, we investigated the defense properties of the aqueous extract of Perilla frutescens Briton Var. acuta Kudo (PF) on hepatic injury in chronically ethanol-treated mice. The mice were orally administered the water extract from PF for 4 weeks with ethanol treatment (3 g/kg. P.O.). The level of malondialdehyde (MDA) in the liver tissues was determined. A substantial increase in MDA generation was detected in the livers of mice subjected to ethanol exposure, whereas the administration of PF markedly reduced MDA levels in hepatic tissues. Additionally, histological analysis of the liver tissue was performed. Histopathological investigation revealed a significant reduction in hepatocellular necrosis in the PF-treated group. This study demonstrated that the aqueous extract of Perilla frutescens Briton Var. acuta Kudo (PF) attenuated chronic ethanol-induced liver injury by augmenting the antioxidant capacity of mice. These results can be utilized for the development of high-value-added products using PF.
Fluid Modeling of a Non-Thermal Plasma with Dielectric Barrier Discharge and Argon as a Diluent Gas
Authors: Mas-Peiro Cristina , Llovell Fèlix , Pou Josep O.
Published: July 2024

Non-thermal plasma (NTP) conversion applications have become an emerging technology of increasing global interest due to their particular ability to perform at atmospheric pressure and ambient temperature. This study focuses on a specific case of a dielectric barrier discharge NTP reactor for carbon dioxide conversion with the usage of argon as diluent gas. The plasma computations in COMSOL® Multiphysics are compared to experimental results and coupled with previous thermodynamic characterization of argon species and fluid dynamic calculations. The model is defined as a time-dependent study with a 2D-Geometry of pure argon, with both fluid flow and plasma phenomena. Firstly, the model showcases an accurate understanding of the plasma physics involved, in the form of electron density, excited argon, argon ions, and mean electron energy. It also allows a direct comparison of the velocity, vorticity, pressure, and dynamic viscosity results with fluid flow computations. Secondly, the impact of several variables is studied, notably the inlet volumetric rate, dielectric barrier thickness and material, and reactor length. Limitations in the plasma characterization can occur by not including packed material or all relevant species in experimental CO2 conversion and their respective reactions, which should be aimed at in future contributions.
Method for the Quantitative Evaluation of Low-Permeability Reservoir Damage in the East China Sea Based on Experimental Evaluation and Modeling Calculation
Authors: Zhao Xingbin , Jiang Yiming , Xu Peng , Yu Jun , Xie Lingzhi
Published: July 2024

Reservoir damage is a key factor affecting reservoir evaluation, ensuring stable reservoir production and improving the utilization rate of oil and gas resources. At present, the evaluation of damage caused by reservoir drilling fluid is too empirical, and there is a lack of methods for the high-precision evaluation of reservoir damage after drilling fluid invasion and pollution. In a block in the East China Sea, the production capacity is limited due to an excessive balance of drilling fluid and long exposure time. In order to ensure safe drilling, the dynamic damage mechanism of drilling fluid during drilling was analyzed. The core of the main reservoir of well XH-1 in a block in the East China Sea was selected for carrying out an experiment evaluating the dynamic damage caused by drilling fluid. According to the experimental results, the damage rate of reservoir permeability caused by drilling fluid invasion ranges between 58.25 and 87.25%, and the overall dynamic damage degree can be classified between medium and high. Combined with the experimental parameters, a mathematical model of drilling fluid invasion depth was established, and the calculation formulas of drilling fluid invasion depth and contaminated skin were derived. The results showed that the drilling fluid depth of the reservoir section corresponding to the core of well XH-1 was 0.47~0.83 m, and the contaminated skin factor was 1.22~13.41, which made up for the lack of evaluation methods of reservoir damage caused by drilling fluid and provided a theoretical basis for the optimization of drilling fluid parameters and exploration drilling technology in oilfield operations.
Occupational Chemical Exposure and Health Status of Wildland Firefighters at the Firefront: A Systematic Review
Authors: Teixeira Tatiana , Almeida Liliana , Dias Isabel , Baptista João Santos , Santos Joana , Vaz Mário , Guedes Joana
Published: July 2024

Wildland firefighting represents a physically and mentally demanding endeavour fraught with various risk factors. The primary aim of this study is to delineate occupational chemical exposure within the firefighting work environment on the firefront and its implications for firefighters’ health status. A systematic literature review was conducted utilising diverse keyword combinations across Scopus, Web of Science, Academic Search Complete, and ScienceDirect databases. Only English-language journal articles, real-world monitoring reports, and studies featuring samples of firefighters were considered for inclusion. Forty-one studies were analysed, with 26 focusing on firefighters’ occupational exposure to chemical agents during wildland firefighting and 15 addressing the health impairments of wildland firefighting activities. Polycyclic aromatic hydrocarbons (PAHs), VOCs, and particulates emerged as the most prevalent chemical agents in the exposure profiles of frontline firefighters. They were shown to be the main incidents of cardiovascular disease, respiratory disease, and work-related cancer. The rigorous demands of wildland firefighting have been demonstrated to significantly impact firefighter health, resulting in a notable prevalence of fatalities and illnesses. Given that an elevated number of health issues are common in this occupation, adopting advanced assessment technologies is imperative.
State Aspirations for Social and Cultural Transformations in Qatar
Authors: Amin Hira , Sakbani Khoulood , Tok Evren
Published: July 2024

Qatar is on a mission to cultivate a thriving, globally competitive, knowledge-based economy, shifting away from its rentier economic model, as well as being a key international player on the world stage. This article focuses on Qatar’s social and cultural sphere, exploring the Qatari state’s vision for society in the midst of these grand agendas. Through a systematic analysis of six key national documents (KNDs), such as the Qatar National Vision 2030 and the National Development Strategy, it extracts the state’s aspirations for its society, as well as the values or traits they are attempting to preserve or inculcate. We identify five key overarching themes in the KNDs: (1) the advancement of society; (2) the preservation of traditions and values; (3) keeping up with the Gulf, Arab and Islamic countries and the world; (4) the empowerment of women; and (5) the importance of the family. The paper concludes with an assessment of some top-down initiatives and policies that were designed to achieve these ambitious agendas, and highlights some of their pitfalls. These issues include a lack of civic participation and engagement; the need for more localisation and indigenous social innovation; and, lastly, more attention given to social dynamics, including their inter- and intra-relations, which often lead to unintended consequences.
An improved estimation method of secondary path uncertainties for feedback active noise control earphones
Authors: Guo Jianfeng , Xun Ziyou , Ren Zhenxing , Yin Lan , Wang Han
Published: July 2024

The fixed feedback control has been widely used for active noise-canceling earphones due to its simple structure and higher performance for low-frequency noise reduction. Although some disk-based models have been done to design robust controllers, they usually overestimate the uncertainty
and thus limit noise reduction. In this article, we analyze the distribution of measured secondary paths and propose the tri-rectangle model to provide the uncertainty bound. The cascade biquad controllers are optimized by solving the multi-constrained optimization problem, with H2 performance
criteria and H1 performance criteria and constraints of secondary path uncertainty and noise amplification. Simulation and experiment results show that the proposed tri-rectangle model provides a more accurate estimate of the uncertainty than disk-based models, and the designed controller
achieves good noise attenuation with acceptable noise enhancement and strong stability.
Therapeutic Effects and Mechanism of Panax ginseng in Improving Spermatogenesis: Evidence from Network Pharmacology and Molecular Docking
Authors: Tran Nhat Minh , Hoang Thi Ai Phuong , Dang Ngoc Phuc , Nguyen Thanh Tung
Published: July 2024

Background: Spermatogenesis is a complex process involving mitotic cell division, meiosis, and spermiogenesis. This study aimed to examine the therapeutic effects and mechanisms of Panax ginseng in improving spermatogenesis, using a systematic network pharmacology approach and molecular docking.

Methods: Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Herbal Ingredients’ Targets (HIT) databases were used to screen for bioactive compounds in Panax ginseng. The SwissTargetPrediction, BATMAN-TCM, HIT, and TCMSP databases were used to identify and obtain the targets. The OMIM database and GeneCards Version 5.20 were searched to obtain targets related to spermatogenesis. The protein-protein interaction (PPI) network was constructed using common targets from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The DAVID tool was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. AutoDock Vina software was used for molecular docking analysis.

Results: A total of 250 overlapping target genes were identified in Panax ginseng and during spermatogenesis. PPI network analysis revealed that tumor protein P53, heat shock protein 90, Alpha Family Class A Member 1, AKT Serine/Threonine Kinase 1, Jun Proto-Oncogene, AP-1 Transcription Factor Subunit, Signal Transducer and Activator of Transcription 3, and Mitogen-Activated Protein Kinase 1 were the top ten most relevant targets. The results of the GO and KEGG analyses showed that the common targets of Panax ginseng and spermatogenesis were mainly involved in pathways related to cancer, p53, MAPK, lipid and atherosclerosis, and the human T-cell leukemia virus 1 infection signaling pathway. Molecular docking analysis suggested that potential targets for Panax ginseng, including quercetin, stigmasterol, inermin, ginsenoside Rg5 had the lowest docking energy for STAT3 and HSP90AA1.

Conclusion: The present study identified the active components and probable molecular therapeutic mechanisms of Panax ginseng in enhancing spermatogenesis, providing a foundation for the widespread use of Panax ginseng in the male reproductive system.

Key words: Panax ginseng, spermatogenesis, network pharmacology, TP53, MAPK, quercetin, molecular docking.
Development and evaluation of virtual reality cases for clinical reasoning training in primary care: A Pilot Study at Hue University of Medicine and Pharmacy
Authors: Nguyen Minh Tam , Nguyen Vu Quoc Bao , Le Ho Thi Quynh Anh , Ho Dac Truong An , Nguyen Hoang Bach , Duong Quang Tuan , Che Thi Len Len , Nguyen Duc Hoang , Le Van Chi , Valcke Martin , Huynh Van Minh , Nguyen Vu Quoc Huy
Published: July 2024

Background: Integrating virtual reality (VR) into medical education can revolutionize teaching and learning clinical reasoning, yet it remains relatively limited in Vietnam. This study represents the first effort to develop and evaluate VR-based clinical cases for clinical reasoning training at Hue University of Medicine and Pharmacy. Methods: This quasi-experimental study uses a pretest‐posttest design with 298 fifth-year medical students. VR scenarios were designed to simulate clinical reasoning skills, including ordering laboratory tests, providing diagnoses, and making clinical decisions. A structured questionnaire assessed students’ readiness for VR-integrated learning, while clinical reasoning skills were evaluated using a four-station OSCE format and a VR-based examination. Results: A VR system and cases for clinical reasoning training were developed. The majority of students showed high readiness for VR-integrated learning. The paired sample T-test revealed significant improvements in clinical reasoning skills, with a mean OSCE score increase of 4.85 (p < 0.001). Significant gains were observed in students’ abilities to suggest medication regimens, provide diagnoses, and order diagnostic tests (p < 0.001) but not in health behavior management planning. Conclusions: Our study highlights the value of VR in enhancing clinical reasoning skills, supporting the evidence for VR-based education in healthcare. Improving VR training, incorporating an integrated curriculum design, and fostering multidisciplinary collaboration in creating VR cases are strongly recommended to optimize learning outcomes.
Key words: virtual reality; medical education; clinical reasoning education; primary care.
Evaluation of the surgical treatment outcomes for abnormal uterine bleeding in menopausal women
Authors: Tran Doan Tu , Nguyen Phu Hao , Hoang Ngoc Tu , Le Si Phuc An , Chau Khac Tu
Published: July 2024

Background: Menopause is determined after 12 consecutive months of amenorrhoea in women with regular menstruation. During this period, women often encounter many health disorders that affect quality of life such as vascular disorders, insomnia, migraines, breast pain, menstrual disorders, and urogenital symptoms,…This study aims to survey the causes of abnormal uterine bleeding in postmenopausal women undergoing surgery and the surgical treatment outcomes in menopausal women. Materials and method: A cross-sectional descriptive study was constructed in 32 women of menopausal age hospitalized for abnormal uterine bleeding at the Center of Obstetrics and Gynecology, Hue Central Hospital, from December 2022 to December 2023. The questionnaire is designed to collect general information, menstrual history, reason for hospitalization, etc. Clinical examination to evaluate abnormal uterine bleeding. Uterus and adnexal ultrasound, sonohysterography (if possible) to evaluate the reason and to evaluate endometrial thickness. Treatment methods include curettage of the uterine cavity to obtain specimens for pathology to rule out malignant originations or/and surgery to eliminate the cause. For endometrial cancer, cancer staging according to FIGO (Federation Internationale de Gynecologie et d’Obstetrique). Results: The mean age and standard deviation of the patients was 56.2 ± 7.8 years. Endometrial hyperplasia and uterine polyps were the main causes with 56.3% and 21.9%, respectively. The major treatment method was uterine curettage and biopsy accounted for 46.8%, following with hysteroscopy and hysterectomy (open/laparoscopic) with 37.5% and 15.7%, respectively. 96.9% of cases had no complications after treatment, the only complication obtained in the study was bleeding, accounting for 3.1%. Conclusion: Endometrial hyperplasia is one of the main causes of abnormal uterine bleeding in menopausal women. Uterine curettage/biopsy and hysteroscopy are safe and reliable methods for evaluating and treating these lesions. The surgical treatment results are relatively safe and only mild complications occur.
Key words: Abnormal uterine bleeding (AUB), menopausal, hysterectomy, PALM-COEIN.
Antidepressants of The Last Decades: New Mechanisms, New Opportunities
Authors: Евсегнеев Р.А.
Published: July 2024

Статья представляет собой краткий обзор современной литературы по истории создания, направлениям поиска, механизмам действия антидепрессантов в последние 3–4 десятилетия. Обсуждаются основные результаты, достижения и трудности на этом пути, эволюция взглядов психиатров за этот период, включая личный опыт автора, а также перспективы и дальнейшие направления поиска.

The article provides a brief review on the historical background, prerequisites, directions of the search, the operating mechanisms of the antidepressants during last 3–4 decades. The main results, achievements and hardships on this traversed path, the evolution of views of practical psychiatrists (including first-hand experience of the author), as well as impending perspectives and some direction of further investigation are also discussed.