bluuebunny/crossref_metadata_2025 huggingface dataset:
Extraction and Microencapsulation of Phytochemical Compounds from Mango Peel (Mangifera indica L.) var. “Kent” and Assessment of Bioaccessibility through In Vitro Digestion
Authors: Roa-Tort Arantxa , Meza-Márquez Ofelia Gabriela , Osorio-Revilla Guillermo , Gallardo-Velázquez Tzayhri , Ramos-Monroy Oswaldo Arturo
Published: January 2024

The peel from mango (Mangifera indica L.) var. “Kent” is a good source of bioactive compounds (BC). BC are sensitive to oxygen, temperature, humidity, light, and gastrointestinal digestion, which change their biological function and health benefits. This study was aimed at the extraction of the bioactive compounds present in the peel from mango var. “Kent” and their microencapsulation using spray drying (SD) and spout-fluid bed drying (SFB). The bioaccessibility of BC was also evaluated. Two consecutive extractions of 90 min at 30 °C and 80% v/v ethanol were used. The microcapsules produced via SD and SFB presented high retention and encapsulation percentages of the bioactive compounds; nevertheless, SFB showed better protection during in vitro gastrointestinal digestion. The non-encapsulated extract showed a decrease (p ≤ 0.05) of BC at the end of in vitro gastrointestinal digestion. The results show that these microcapsules might be used in the food industry as an ingredient to produce functional foods and, thereby, to obtain the health benefits that the bioactive compounds provide.
Experimental Assessment of a Decentralized Control Strategy for a Back-to-Back Modular Multilevel Converter Operating in Low-Frequency AC Transmission
Authors: Ibaceta Efrain , Diaz Matias , Rajendran Saravanakumar , Arias Yeiner , Cárdenas Roberto , Rodriguez Jose
Published: January 2024

The Modular Multilevel Converter (MMC) has been widely used in high-power applications owing to its inherent advantages, including scalability, modularity, high-power density, and fault tolerance. MMCs have recently been used in Low-Frequency Alternating Current (LFAC) transmission, particularly in the integration of offshore wind power with onshore grids. However, LFAC applications produce significant voltage oscillations in floating capacitor voltages within the MMC. Early research efforts have successfully established and validated decoupled control strategies for LFAC-based MMC systems. However, validations are usually based on simulations or small-scale prototypes equipped with limited power cells. Consequently, this paper presents a decentralized voltage control strategy based on Nearest Level Control for an MMC-based LFAC system. Experimental results obtained with a 120-cell MMC prototype are presented to validate the effectiveness and operation of the MMC in LFAC applications.
Research on AGC Nonlinear Compensation Control for Electro-Hydraulic Servo Pump Control of a Lithium Battery Pole Strip Mill
Authors: Wang Kai , Chen Gexin , Zhang Cheng , Liu Keyi , Wang Fei
Published: January 2024

Electrode roll forming involves rolling a battery electrode into a preset thickness using a hydraulic roll gap thickness automatic control system (hydraulic AGC for short). The pump-controlled AGC is a highly nonlinear servo system, which is a combination of mechanical, hydraulic and electronic control disciplines; thus, as a new technology, it still faces many challenges in the field of pole plate rolling. In this paper, electro-hydraulic servo pump-controlled AGC technology is replaced by electro-hydraulic servo valve-controlled AGC technology. With pump-controlled AGC high-precision thickness control as the research objective, the fuzzy control method is selected to deal with complex nonlinear systems based on pump-controlled AGC nonlinear stiffness characteristics and nonlinear transmission characteristics. A characteristic compensation control strategy is proposed. At the same time, considering the load fluctuation caused by the uneven thickness of the electrode plate under the intermittent coating rolling condition of a lithium battery, the fuzzy internal model (IMC) compensation control strategy was proposed to compensate the structural characteristics of the electrode plate rolling. Comparative experiments show that the position control accuracy of the pump-controlled AGC system can be improved significantly by using a fuzzy IMC compensation control strategy. The steady-state accuracy of the slope signal can reach ±0.7 μm, and the position-following accuracy of the sinusoidal signal can reach ±1.8 μm. In addition, this study will assist technological upgrades to lithium battery electrode roll forming and fixed-roll-gap rolling, laying a theoretical foundation for the promotion of pump control technology in the field of electrode rolling.
Microbiome Structure of Activated Sludge after Adaptation to Landfill Leachate Treatment in a Lab-Scale Sequencing Batch Reactor
Authors: Kirilova Mihaela , Yotinov Ivaylo , Todorova Yovana , Dinova Nora , Lincheva Stilyana , Schneider Irina , Topalova Yana
Published: January 2024

During adaptation to waters that are rich in xenobiotics, biological systems pass through multiple stages. The first one is related to the restructuring of communities, pronounced destruction of the structure, and multiplication of active biodegradants. The purpose of the present research was to describe the microbiome restructuring that occurs during the adaptation stage in landfill leachate treatment. In a model SBR (sequencing batch reactor), a 21-day purification process of landfill leachate was simulated. Wastewater was fed in increasing concentrations. When undiluted leachate entered, the activated sludge structure disintegrated (Sludge Volume Index—4.6 mL/g). The Chemical Oxygen Demand and ammonium nitrogen concentration remained at high values in the influent (2321.11 mgO2/L and 573.20 mg/L, respectively). A significant amount of free-swimming cells was found, and the number of aerobic heterotrophs and bacteria of the genera Pseudomonas and Acinetobacter increased by up to 125 times. The Azoarcus-Thauera cluster (27%) and Pseudomonas spp. (16%) were registered as the main bacterial groups in the activated sludge. In the changed structure of the microbial community, Gammaproteobacteria, family Rhizobiaceae, class Saccharimonadia were predominantly represented. Among the suspended bacteria, Microbactericeae and Burkholderiaceae, which are known for their ability to degrade xenobiotics, were present in larger quantities. The enzymological analysis demonstrated that the ortho-pathway of cleavage of aromatic structures was active in the community. The described changes in the leachate-purifying microbial community appear to be destructive at the technological level. At the microbiological level, however, trends of initial adaptation were clearly outlined, which, if continued, could provide a highly efficient biodegradation community.
Effects of Superabsorbent Polymer Addition on the Thermal Properties of Eutectic Phase Change Material
Authors: Lee Seok-Joon , Park Seul-Hyun
Published: January 2024

In this study, the influence of a super absorbent polymer (SAP) addition on the thermal properties of phase change material (PCM) was investigated. It was found that adding SAP reduced the melting temperature of PCM and improved phase separation properties. While the addition of 1.0 wt% of SAP to PCMs decreased latent heat by 3 J/g to 24.4 J/g, the addition was determined to be necessary to prevent leaks from a functional duct unit (FDU) and assure product stability. The results obtained from a series of brine refrigeration tests indicate that the supercooling temperature decreased by 0.3 °C to 1.7 °C when 1.0 wt% of SAP was added to PCM. The addition of SAP to PCM appears to promote supercooling by encouraging condensation during phase change. As a result of applying SAP-added PCM to the FDU, the isothermal operation performance was improved compared to existing refrigerators.
The Potential Material Flow of WEEE in a Data-Constrained Environment—The Case of Jordan
Authors: Al-Khatib Laila A. , Fraige Feras Y.
Published: January 2024

The rising concerns about electric and electronic equipment waste (WEEE) come from the rapid increase in demand for appliances and the decreasing lifetimes of equipment. Setting a sustainable WEEE management system that exploits this secondary resource is paramount to maximize resource efficiency, mitigate its environmental impact, and stimulate the circular economy. This paper aims, for the first time, to quantify the material flow expected from recycling the generated WEEE, propose the number of plants required to recycle this secondary resource, and outline the expected economic and environmental benefits that could be achieved from recycling operations. The findings of material flow calculations show that the amount of steel, copper, and aluminum is predominant in the WEEE composition. Also, the expected metal content in WEEE in 2022 is approximately 26 kt, 3.3 kt, and 2.5 kt, respectively. These are expected to substantially increase to approximately 109 kt, 11.9 kt, and 9 kt for the three metals in 2050, respectively. Other valuable metals are doubling their quantities between 2022 and 2050 to reach approximately 1133 kg silver and 475 kg gold. Approximately, four treatment plants are required to recover these materials in 2030 with relative installation costs of USD 100 million. The forecasted financial revenues of recovering materials included in WEEE and indicators for environmental impact based on life cycle assessment (LCA) are calculated. The results of this study can serve as a preliminary reference for future usage in guiding effective planning for WEEE recycling and sustainable management in the country.
Moving-Principal-Component-Analysis-Based Structural Damage Detection for Highway Bridges in Operational Environments
Authors: Yuan Ye , Zhu Xinqun , Li Jun
Published: January 2024

With the deterioration of bridge performance and ever-increasing amounts of traffic, bridge safety is becoming a concern for the engineering community. A method that can assess a bridge’s condition in real time is urgently needed. The main factors that hinder bridge condition assessment are the uncertain operational environments. A new moving principal component analysis (MPCA)-based method is developed for structural damage detection in bridges in operational environments in this paper. Two main operational environmental factors, the environmental temperature and traffic loads, are studied in the assessment process to verify the robustness and practicality of the proposed method. The numerical and experimental results show that the proposed method is effective and accurate in assessing the bridge’s condition in operational environments.
Configuration Investigation, Structure Design and Deployment Dynamics of Rigid-Reflector Spaceborne Antenna with Deviation-Angle Panel
Authors: Tan Guodong , Liu Kaiqi , Duan Xuechao , Wang Qunbiao , Zhang Dan , Yang Dongwu , Niu Dingchao
Published: January 2024

Rigid-reflector spaceborne antennas (RRSAs) are well-suited for high-frequency application scenarios due to their high surface accuracy. However, the low stowing efficiency of RRSAs limits the aperture diameters and further deteriorates the electromagnetic (EM) performances in terms of gain, resolution and sensitivity. After conducting systematic feature analysis with respect to several typical RRSAs, we propose a novel type of RRSA to solve the aforementioned problems. Inspired by the pose adjustment process for a higher stowing efficiency of traditional RRSAs, we also propose a new segmentation scheme of a reflective surface consisting of a deviation-angle panel that facilitates a higher stowing efficiency. Based on this scheme, its corresponding folded configuration is implemented by combining Euler’s rotation theorem and the idea of parameter identification. In addition, we also compare the stowing efficiency of different schemes to verify the high stowing efficiency of the configuration. Finally, we perform mechanism/structure design and deployment dynamics to demonstrate that the antenna can be successfully deployed and exhibits excellent deployment quality. The results suggest that the proposed antenna possesses higher stowing efficiency than that of the same kind, with a stable deployment and interference-free process.
Non-Contact Current Measurement for Three-Phase Rectangular Busbars Using TMR Sensors
Authors: Su Huafeng , Li Haojun , Liang Weihao , Shen Chaolan , Xu Zheng
Published: January 2024

This paper proposes a non-contact current measurement method for three-phase rectangular busbars based on TMR (tunneling magneto-resistance) sensors, due to their advantages of large dynamic range, wide bandwidth, light weight, and easy installation. A non-contact current sensor composed of only three TMR sensors is developed and the TMR sensors are respectively placed at a location with a certain distance from the surface of each rectangular busbar to measure the magnetic fields generated by the busbar currents. To calibrate the developed current sensor, i.e., to establish the relationship between the magnetic fields measured by the TMR sensors and the currents flowing in the three-phase rectangular busbars, we designed a thyristor-controlled resistive load as a calibrator, which is connected to a downstream branch of the distribution cabinet. By switching the resistive load, a calibration current, which can be identified from the background current, is generated in one rectangular busbar and its value is measured at the location of the calibrator, and transmitted wirelessly to the location of the TMR sensors. A new and robust method is proposed to extract the voltage components, corresponding to the calibration current, from the voltage waveforms of the TMR sensors. By calculating the proportional coefficients between the calibration currents and the extracted voltage components, online calibration of the current sensor is achieved. We designed and implemented a current measurement system consisting of a current sensor using TMR sensors, a thyristor-controlled resistive load for current sensor calibration, and a data acquisition circuit based on a multi-channel analog-to-digital converter (ADC). Current measurement experiments were performed in a practical distribution cabinet installed in our laboratory. Compared to the measurement results using a commercial current probe with an accuracy of 1%, the relative error of the measured currents in RMS is less than 2.5% and the phase error is less than 1°, while the nonlinearity error of the current sensor is better than 0.8%.
Recovery-Based Occluded Face Recognition by Identity-Guided Inpainting
Authors: Li Honglei , Zhang Yifan , Wang Wenmin , Zhang Shenyong , Zhang Shixiong
Published: January 2024

Occlusion in facial photos poses a significant challenge for machine detection and recognition. Consequently, occluded face recognition for camera-captured images has emerged as a prominent and widely discussed topic in computer vision. The present standard face recognition methods have achieved remarkable performance in unoccluded face recognition but performed poorly when directly applied to occluded face datasets. The main reason lies in the absence of identity cues caused by occlusions. Therefore, a direct idea of recovering the occluded areas through an inpainting model has been proposed. However, existing inpainting models based on an encoder-decoder structure are limited in preserving inherent identity information. To solve the problem, we propose ID-Inpainter, an identity-guided face inpainting model, which preserves the identity information to the greatest extent through a more accurate identity sampling strategy and a GAN-like fusing network. We conduct recognition experiments on the occluded face photographs from the LFW, CFP-FP, and AgeDB-30 datasets, and the results indicate that our method achieves state-of-the-art performance in identity-preserving inpainting, and dramatically improves the accuracy of normal recognizers in occluded face recognition.
Lightweight Tunnel Obstacle Detection Based on Improved YOLOv5
Authors: Li Yingjie , Ma Chuanyi , Li Liping , Wang Rui , Liu Zhihui , Sun Zizheng
Published: January 2024

Considering the high incidence of accidents at tunnel construction sites, using robots to replace humans in hazardous tasks can effectively safeguard their lives. However, most robots currently used in this field require manual control and lack autonomous obstacle avoidance capability. To address these issues, we propose a lightweight model based on an improved version of YOLOv5 for obstacle detection. Firstly, to enhance detection speed and reduce computational load, we modify the backbone network to the lightweight Shufflenet v2. Secondly, we introduce a coordinate attention mechanism to enhance the network’s ability to learn feature representations. Subsequently, we replace the neck convolution block with GSConv to improve the model’s efficiency. Finally, we modify the model’s upsampling method to further enhance detection accuracy. Through comparative experiments on the model, the results demonstrate that our approach achieves an approximately 37% increase in detection speed with a minimal accuracy reduction of 1.5%. The frame rate has improved by about 54%, the parameter count has decreased by approximately 74%, and the model size has decreased by 2.5 MB. The experimental results indicate that our method can reduce hardware requirements for the model, striking a balance between detection speed and accuracy.
Atrial Fibrillation Detection with Single-Lead Electrocardiogram Based on Temporal Convolutional Network–ResNet
Authors: Zhao Xiangyu , Zhou Rong , Ning Li , Guo Qiuquan , Liang Yan , Yang Jun
Published: January 2024

Atrial fibrillation, one of the most common persistent cardiac arrhythmias globally, is known for its rapid and irregular atrial rhythms. This study integrates the temporal convolutional network (TCN) and residual network (ResNet) frameworks to effectively classify atrial fibrillation in single-lead ECGs, thereby enhancing the application of neural networks in this field. Our model demonstrated significant success in detecting atrial fibrillation, with experimental results showing an accuracy rate of 97% and an F1 score of 87%. These figures indicate the model’s exceptional performance in identifying both majority and minority classes, reflecting its balanced and accurate classification capability. This research offers new perspectives and tools for diagnosis and treatment in cardiology, grounded in advanced neural network technology.
Sensitivity of Mass Geometry Parameters on E-Scooter Comfort: Design Guide
Authors: Cano-Moreno Juan David , Arenas Reina José Manuel , Parra Lanillos Victorina del Carmen , Islán Marcos Manuel Enrique
Published: January 2024

E-scooter vibrations are a problem recently studied. Theoretical models based on dynamic simulations and also real measurements have confirmed the high impact of e-scooter vibrations on driver comfort and health. Some authors recommend improving e-scooter damping systems, including tyres. However, it has not been suggested nor has any research been published studying how to improve e-scooter frame design for reducing driver vibrations and improving comfort. In this paper, we have modelled a real e-scooter to have a reference. Then, we have developed a multibody dynamic model for running dynamic simulations studying the influence of mass geometry parameters of the e-scooter frame (mass, centre of gravity and inertia moment). Acceleration results have been analysed based on the UNE-2631 standard for obtaining comfort values. Based on results, a qualitative e-scooter frame design guide for mitigating vibrations and increasing the comfort of e-scooter driver has been developed. Some application cases have been running on the multibody dynamic simulation model, finding improvements of comfort levels higher than 9% in comparison with the e-scooter reference model. The dynamic model has been qualitatively validated from real measurements. In addition, a basic sensor proposal and comfort colour scale is proposed for giving feedback to e-scooter drivers.
The Development of a Wearable Biofeedback System to Elicit Temporal Gait Asymmetry using Rhythmic Auditory Stimulation and an Assessment of Immediate Effects
Authors: Gouda Aliaa , Andrysek Jan
Published: January 2024

Temporal gait asymmetry (TGA) is commonly observed in individuals facing mobility challenges. Rhythmic auditory stimulation (RAS) can improve temporal gait parameters by promoting synchronization with external cues. While biofeedback for gait training, providing real-time feedback based on specific gait parameters measured, has been proven to successfully elicit changes in gait patterns, RAS-based biofeedback as a treatment for TGA has not been explored. In this study, a wearable RAS-based biofeedback gait training system was developed to measure temporal gait symmetry in real time and deliver RAS accordingly. Three different RAS-based biofeedback strategies were compared: open- and closed-loop RAS at constant and variable target levels. The main objective was to assess the ability of the system to induce TGA with able-bodied (AB) participants and evaluate and compare each strategy. With all three strategies, temporal symmetry was significantly altered compared to the baseline, with the closed-loop strategy yielding the most significant changes when comparing at different target levels. Speed and cadence remained largely unchanged during RAS-based biofeedback gait training. Setting the metronome to a target beyond the intended target may potentially bring the individual closer to their symmetry target. These findings hold promise for developing personalized and effective gait training interventions to address TGA in patient populations with mobility limitations using RAS.
Design of a Portable Analyzer to Determine the Net Exchange of CO2 in Rice Field Ecosystems
Authors: Bonilla-Cordova Mirko , Cruz-Villacorta Lena , Echegaray-Cabrera Ida , Ramos-Fernández Lia , Flores del Pino Lisveth
Published: January 2024

Global warming is influenced by an increase in greenhouse gas (GHG) concentration in the atmosphere. Consequently, Net Ecosystem Exchange (NEE) is the main factor that influences the exchange of carbon (C) between the atmosphere and the soil. As a result, agricultural ecosystems are a potential carbon dioxide (CO2) sink, particularly rice paddies (Oryza sativa). Therefore, a static chamber with a portable CO2 analyzer was designed and implemented for three rice plots to monitor CO2 emissions. Furthermore, a weather station was installed to record meteorological variables. The vegetative, reproductive, and maturation phases of the crop lasted 95, 35, and 42 days post-sowing (DPS), respectively. In total, the crop lasted 172 DPS. Diurnal NEE had the highest CO2 absorption capacity at 10:00 a.m. for the tillering stage (82 and 89 DPS), floral primordium (102 DPS), panicle initiation (111 DPS), and flowering (126 DPS). On the other hand, the maximum CO2 emission at 82, 111, and 126 DPS occurred at 6:00 p.m. At 89 and 102 DPS, it occurred at 4:00 and 6:00 a.m., respectively. NEE in the vegetative stage was −25 μmolCO2 m2 s−1, and in the reproductive stage, it was −35 μmolCO2 m2 s−1, indicating the highest absorption capacity of the plots. The seasonal dynamics of NEE were mainly controlled by the air temperature inside the chamber (Tc) (R = −0.69), the relative humidity inside the chamber (RHc) (R = −0.66), and net radiation (Rn) (R = −0.75). These results are similar to previous studies obtained via chromatographic analysis and eddy covariance (EC), which suggests that the portable analyzer could be an alternative for CO2 monitoring.
Coordinated Decision Control of Lane-Change and Car-Following for Intelligent Vehicle Based on Time Series Prediction and Deep Reinforcement Learning
Authors: Zhang Kun , Pu Tonglin , Zhang Qianxi , Nie Zhigen
Published: January 2024

Adaptive cruise control and autonomous lane-change systems represent pivotal advancements in intelligent vehicle technology. To enhance the operational efficiency of intelligent vehicles in combined lane-change and car-following scenarios, we propose a coordinated decision control model based on hierarchical time series prediction and deep reinforcement learning under the influence of multiple surrounding vehicles. Firstly, we analyze the lane-change behavior and establish boundary conditions for safe lane-change, and divide the lane-change trajectory planning problem into longitudinal velocity planning and lateral trajectory planning. LSTM network is introduced to predict the driving states of surrounding vehicles in multi-step time series, combining D3QN algorithm to make decisions on lane-change behavior. Secondly, based on the following state between the ego vehicle and the leader vehicle in the initial lane, as well as the relationship between the initial distance and the expected distance with the leader vehicle in the target lane, with the primary objective of maximizing driving efficiency, longitudinal velocity is planned based on driving conditions recognition. The lateral trajectory and conditions recognition are then planned using the GA-LSTM-BP algorithm. In contrast to conventional adaptive cruise control systems, the DDPG algorithm serves as the lower-level control model for car-following, enabling continuous velocity control. The proposed model is subsequently simulated and validated using the NGSIM dataset and a lane-change scenarios dataset. The results demonstrate that the algorithm facilitates intelligent vehicle lane-change and car-following coordinated control while ensuring safety and stability during lane-changes. Comparative analysis with other decision control models reveals a notable 17.58% increase in driving velocity, underscoring the algorithm’s effectiveness in improving driving efficiency.
An Experimental Performance Assessment of Galileo OSNMA
Authors: Hammarberg Toni , García José M. Vallet , Alanko Jarno N. , Bhuiyan M. Zahidul H.
Published: January 2024

We present Galileo Open Service Navigation Message Authentication (OSNMA) observed operational information and key performance indicators (KPIs) from the analysis of a ten-day-long dataset collected in static open-sky conditions in southern Finland and using our in-house-developed OSNMA implementation. In particular, we present a timeline with authentication-related events, such as authentication status and type, dropped navigation pages, and failed cyclic redundancy checks. We also report other KPIs, such as the number of simultaneously authenticated satellites over time, time to first authenticated fix, and percentage of authenticated fixes, and we evaluate the accuracy of the authenticated position solution. We also study how satellite visibility affects these figures. Finally, we analyze situations where it was not possible to reach an authenticated fix, and offer our findings on the observed patterns.
A Semantic Hybrid Temporal Approach for Detecting Driver Mental Fatigue
Authors: Ansari Shahzeb , Du Haiping , Naghdy Fazel , Hoshu Ayaz Ahmed , Stirling David
Published: January 2024

Driver mental fatigue is considered a major factor affecting driver behavior that may result in fatal accidents. Several approaches are addressed in the literature to detect fatigue behavior in a timely manner through either physiological or in-vehicle measurement methods. However, the literature lacks the implementation of hybrid approaches that combine the strength of individual approaches to develop a robust fatigue detection system. In this regard, a hybrid temporal approach is proposed in this paper to detect driver mental fatigue through the combination of driver postural configuration with vehicle longitudinal and lateral behavior on a study sample of 34 diverse participants. A novel fully adaptive symbolic aggregate approximation (faSAX) algorithm is proposed, which adaptively segments and assigns symbols to the segmented time-variant fatigue patterns according to the discrepancy in postural behavior and vehicle parameters. These multivariate symbols are then combined to prepare the bag of words (text format dataset), which is further processed to generate a semantic report of the driver’s status and vehicle situations. The report is then analyzed by a natural language processing scheme working as a sequence-to-label classifier that detects the driver’s mental state and a possible outcome of the vehicle situation. The ground truth of report formation is validated against measurements of mental fatigue through brain signals. The experimental results show that the proposed hybrid system successfully detects time-variant driver mental fatigue and drowsiness states, along with vehicle situations, with an accuracy of 99.6% compared to state-of-the-art systems. The limitations of the current work and directions for future research are also explored.
The Extraction of Bioactive Agents from Calophyllum inophyllum L., and Their Pharmacological Properties
Authors: Ferdosh Sahena
Published: January 2024

Calophyllum inophyllum L. has been used for many generations by Pacific Islanders because of its numerous health and aesthetic advantages. The leaves, stems, roots, fruits, flowers, and seeds of this plant contain significant phytochemicals, including flavonoids, coumarins, fatty acids, and xanthones, which have been shown to have wound healing, analgesic, anti-inflammatory, antiaging, anti-arthritic, anti-cancer, anti-proliferative, anti-diabetic, anti-microbial, and anti-HIV effects. The chemical profiles and bioactive potential may vary due to different extraction techniques, plant parts, and geographical origins. Extraction is the essential first step in the analysis of bioactive compounds that leads to further separation, identification, and characterization. Conventional methods like maceration, Soxhlet, and percolation are often used to extract bioactive compounds from C. inophyllum. However, little study has been carried out on non-conventional methods such as pressured liquid extraction, supercritical fluid extraction (SFE), and ultrasound-assisted extraction. The SFE method can be used to extract bioactive compounds from C. inophyllum to retain their pharmacological properties for application in pharmaceutical and cosmetic products.
Victims of Child Grooming: An Evaluation in University Students
Authors: Alonso-Ruido Patricia , Estévez Iris , Regueiro Bibiana , Varela-Portela Cristina
Published: January 2024

The appearance of new ways of committing sexual violence via technological media and virtual spaces has produced countless situations where sexual abuse of minors may occur. This is the digital scenario surrounding the phenomenon of grooming. The present study focuses on analyzing grooming experienced by Spanish university students during childhood. The sample comprised 3293 students in higher education, 68.3% of whom were female, 30.5% were male, and 1.2% identified as non-binary. The mean age was 18.83 years (SD = 2.28). The results confirmed that sexual abuse of minors has moved towards virtual environments, indicating a prevalence of 12.2% for grooming, which was more likely to have affected women and non-binary people. In addition, student victims of grooming were more often also victims of sextortion. Consumption of pornography was also shown to be particularly important, with the results indicating that students who consumed it and started consuming it before they were 16 years old were more often victims of grooming. These findings should encourage the educational community to develop preventive actions that match the reality of online child sexual abuse. In summary, the only path towards preventing and detecting grooming is to invest in high-quality digital education and sex education from a gender perspective.
The Role of Subjective Well-Being in Cuban Civil Protest against the Government: A Moderated Mediation Model
Authors: Vara-Horna Arístides , Asencios-Gonzalez Zaida , López-Odar Dennis , Aguirre-Morales Marivel , Cirilo-Acero Ingrid
Published: January 2024

This empirical study sought to understand the drivers behind civil protest participation in authoritarian contexts, explicitly focusing on Cuba. The data were sourced from 658 respondents via online surveys facilitated by CubaData, an independent social research agency specializing in Cuban studies, employing a secure panel system that guarantees the confidentiality and anonymity of participants. Our research primarily investigated the role of satisfaction with government policies in terms of the intention to participate in civil protests, introducing subjective well-being as a moderating variable. Utilizing the Process module of SMART-PLS 4 to emulate Process Model 58 for moderated mediation analysis, we accounted for measurement errors to ensure robust findings. Further controls were incorporated for age and political self-efficacy. The results revealed that subjective well-being significantly moderates the link between satisfaction with government policies and actual participation in civil protests. These findings suggest that the happiness level can change resistance dynamics within authoritarian settings. This research has implications for academic understandings of political behavior in autocratic regimes and practical applications in policy making and activism in Cuba.
Post-Activation Performance Enhancement (PAPE) Increases Jumping Power in Elite Female Volleyball Athletes
Authors: Heynen Rahel , Gross Micah , Betschen Thomas , Hübner Klaus
Published: January 2024

This study investigated PAPE effects of two conditioning activities (CA) and recovery times on the peak jumping power (PP) of elite female volleyball athletes. Players performed CA separately: three sets of three repetitions of back squats with 85% of 1RM (BS) or one set of five depth drops (DD). PP was measured with countermovement (CMJ) and squat jumps (SJ) before (pre-test) and two minutes (post-test 1) and six hours (post-test 2) after each CA. BS significantly reduced PP at post-test 1 (CMJ and SJ: p < 0.04, d between −0.36 and −0.28). At post-test 2, following BS, PP for both jump forms was significantly greater than at post-test 1 (p < 0.001, d between 0.54 and 0.55) and at pre-test (p < 0.048, d between 0.21 and 0.30). DD increased PP significantly (CMJ and SJ p < 0.05, d between 0.40 and 0.41) relative to pre-test at post-test 2 (there was no significant difference between pre-test and post-test 1). Comparing BS with DD, there were no significant differences (p > 0.05). The greatest PAPE effects were observed six hours after BS. CA are recommended for female athletes to improve jumping performance, but individual responses should be determined prior to use.
Follow-Up Weekly Training Distribution and Accumulated Internal Load Effects on Young Football Players’ Well-Being, Physical Fitness, and Technical Performance
Authors: Riansoi Yutthana , Tongnillpant Nuntapol , Thammawong Sakdarin , Ribeiro João , Zacca Rodrigo , Chainok Phornpot
Published: January 2024

This study aimed to quantify the relationships among internal training load, wellness, physiological, isokinetic profile, and technical performance and assessed changes before and after a six-week pre-season structured combining physical fitness, small-sided-game and skill-based training program in young soccer players. Forty-five national-level young male soccer players (16.8 ± 0.9 years) were evaluated. There were no significant correlations between the wellness index and the physiological, isokinetic, or specific soccer skill parameters. Moderate correlations were observed between fatigue and stress (r = 0.47, moderate, p < 0.01), fatigue and average muscle soreness (r = 0.38, moderate, p = 0.01), and a large correlation between average stress and muscle soreness (r = 0.53, large, p < 0.01) were presented. All physiological, isokinetic, and technical parameters improved after a six-week pre-season training program (0.1 to −61.0%). Significant alterations in the physiological domain were observed after a six-week period, particularly in the fatigue index of the Bangsbo sprint test, YO-YO IR1 performance, and YO-YO peak La- (p < 0.01; −61.0%, 25.3%, and −19.8%, respectively). As such, the implementation of structured training and the monitoring of stress responses can lead to appropriate adaptation and balancing in the psychological and physical well-being of young national-level soccer players, particularly in the pre-season period.
An Efficient Computational Analysis and Modelling of Transferred Aerodynamic Loading on Direct-Drive System of 5 MW Wind Turbine and Results Driven Optimisation for a Sustainable Generator Structure
Authors: Szatkowski Szymon , Jaen-Sola Pablo , Oterkus Erkan
Published: January 2024

The study presents an efficient computational investigation on the behaviour of the direct-drive system integrated into the offshore 5 MW NREL wind turbine model under demanding aerodynamic loading conditions with the aim of optimising and developing more sustainable key structural components. The research was based on computational simulation packages in order to verify the use of real-world wind data and the loading conditions on the blade structures through aero-elastic simulation studies as well as analyse the behaviour of the drive system. Through the application of validated aerodynamic loading conditions, resulting normal forces on the blades structure were obtained and applied to a dedicated simplified model that was also previously validated to estimate the transferred loads into the powertrain. The adopted methodology allowed for the identification of shaft misalignment induced air gap eccentricity. The impact of shaft deflections on resulting magnetomotive force was considered by making use of the Maxwell stress distribution expression. By taking into account the resulting loading cases on the generator structure, as well as the inherent typical loads generated by the electrical machine, a procedure including structural parametric and topology optimisation was developed and performed, achieving a rotor mass reduction between 8.5 and 9.6% compared to the original model.
Analyzing Technical Efficiency in Cereal Production across Selected European Union Countries
Authors: Aljohani Emad S. , Chidmi Benaissa
Published: January 2024

This paper investigates the technical efficiency of cereal production in European Union (EU) countries from 2008 to 2018. The primary purpose is to estimate technical efficiency scores by country and crop and explain their variation using macroeconomic and agricultural policy variables using the stochastic frontier production function. The results indicate that the United Kingdom has the highest efficiency in barley production, while Finland has the lowest. France exhibits the highest efficiency in common wheat, and Romania has the lowest efficiency in grain maize production. This study also explores the impact of various factors on technical efficiency, finding, for example, the positive effects of female wages and foreign direct investment on barley production efficiency and the negative effects of forest area and subsidies. Similar analyses were conducted for wheat and maize production. The results indicate a variation in technical efficiency scores across crops and countries. This diversity in performance not only reflects the inherent complexities within each crop but also emphasizes the crucial role played by macroeconomic variables and agricultural policies in shaping efficiency outcomes on a country-wide scale.
Toward Sustainable Indoor Environments: Assessing the Impact of Thermal Insulation Measures on Air Quality in Buildings—A Case Study in Temuco, Chile
Authors: Martinez-Soto Aner , Jimenez-Gallardo Carlos , Villarroel-Lopez Andrés , Reyes-Riveros Alejandro , Höhl Johanna
Published: January 2024

In Chile, an Atmospheric Decontamination Plan (PDA) has been developed to reduce concentrations of fine particulate matter (PM 2.5) in cities deemed “saturated” with these particles. The plan includes various measures, such as the thermal insulation of homes and the replacement of heaters. This study presents an analysis of the indices of four indoor air quality variables (temperature, humidity, carbon dioxide, and PM 2.5) in different types of homes with varying levels of PDA implementation in the city of Temuco, Chile. Regarding the temperature variable, only one type of home was found to be within comfort limits, with an average of 20.6 °C and a variation of ±3.52 °C (SD). Concerning humidity, independently owned homes with complete and moderate ADP implementation had average humidity levels between 64.82% ± 7.19% and 55.6% ± 6.11%, respectively. For CO2, only homes with moderate implementation showed averages slightly below (average 991 ppm) the maximum allowed (1000 ppm). As for PM 2.5, all homes exceeded the standard, ranging from 44.4 µg/m3 to 130 µg/m3, with very high variations. This demonstrates that PM 2.5 concentrations consistently exceeded the limits established by the World Health Organization (15 µg/m3).
Novel Sustainable Alternatives for the Study of the Chemical Composition of Cork
Authors: Verdum María , Jové Patricia
Published: January 2024

Cork is a natural and renewable material extracted from the cork oak Quercus suber L. (1) Background: The cellular structure and chemical composition of the plant wall give cork its physical and mechanical properties. Chemically, the composition of cork is principally dominated by the presence of suberin as the main structural cell wall component and affected by its close association with other components. The usual chemical analysis of cork has been partially adapted from wood and other lignocellulosic analytical methods and it is a method with extensive procedures. This study aims to (i) find quicker and more sustainable methods for testing the cork chemical composition, (ii) conduct extraction tests using alternative techniques, (iii) optimize alternative methodologies, and (iv) validate the proposed sustainable methodologies. (2) Methods: Microwave-assisted extraction (MAE) and accelerated solvent extraction (ASE) are explored as alternative systems to the traditional method. The percentages of the extractives obtained via MAE are lower than the percentages obtained by means of the classical composition. (3) Results: However, the percentages of suberin are very similar in both methods: 46.39% in the case of the classical composition and 45.11% in the case of microwave-assisted extraction. No significant differences are observed between the content of the extractives in the dichloromethane, ethanol, and water obtained via ASE and the results obtained with the classical methodology. (4) Conclusions: MAE and ASE are faster methods; they use less solvents and provide more reproducible results than the classical chemical composition methodology. These data pave the way for novel sustainable alternatives relative to the studies of the chemical composition of cork.
Collaborative Model-Based Systems Engineering Using Dataspaces and SysML v2
Authors: Li Zirui , Faheem Faizan , Husung Stephan
Published: January 2024

Collaborative Model-based Systems Engineering between companies is becoming increasingly important. The utilization of the modeling possibilities of the standard language SysML v2 and the multilateral data exchange via Dataspaces open new possibilities for efficient collaboration. Based on systemic approaches, a modeling concept for decomposing the system into sub-systems is developed as a basis for the exchange. In addition, based on the analysis of collaboration processes in the context of Systems Engineering, an architectural approach with a SysML editor and Dataspace for the exchange is elaborated. The architecture is implemented on the basis of open-source solutions. The investigations are based on an application example from precision engineering. The potential and challenges are discussed.
Toxicity of Three Optical Brighteners: Potential Pharmacological Targets and Effects on Caenorhabditis elegans
Authors: Castro-Sierra Isel , Duran-Izquierdo Margareth , Sierra-Marquez Lucellys , Ahumedo-Monterrosa Maicol , Olivero-Verbel Jesus
Published: January 2024

Optical brighteners (OBs) have become an integral part of our daily lives and culture, with a growing number of applications in various fields. Most industrially produced OBs are derived from stilbene, which has been found in environmental matrices. The main objectives for this work are as follows: first, to identify protein targets for DAST, FB-28, and FB-71, and second, to assess their effects in some behaviors physiologic of Caenorhabditis elegans. To achieve the first objective, each OB was tested against a total of 844 human proteins through molecular docking using AutoDock Vina, and affinities were employed as the main criteria to identify potential target proteins for the OB. Molecular dynamics simulations took and validated the best 25 docking results from two protein databases. The highest affinity was obtained for the Hsp70-1/DAST, CD40 ligand/FB-71, and CD40 ligand/FB-28 complexes. The possible toxic effects that OBs could cause were evaluated using the nematode C. elegans. The lethality, body length, locomotion, and reproduction were investigated in larval stage L1 or L4 of the wild-type strain N2. In addition, transgenic green fluorescent protein (GFP) strains were employed to estimate changes in relative gene expression. The effects on the inhibition of growth, locomotion, and reproduction of C. elegans nematodes exposed to DAST, FB-71, and FB-28 OBs were more noticeable with respect to lethality. Moreover, an interesting aspect in OB was increased the expression of gpx-4 and sod-4 genes associated with oxidative stress indicating a toxic response related to the generation of reactive oxygen species (ROS). In all cases, a clear concentration-response relationship was observed. It is of special attention that the use of OBs is increasing, and their different sources, such as detergents, textiles, plastics, and paper products, must also be investigated to characterize the primary emissions of OBs to the environment and to develop an adequate regulatory framework.
Effect of Temperature, pH, and aw on Cereulide Synthesis and Regulator Genes Transcription with Respect to Bacillus cereus Growth and Cereulide Production
Authors: Wang Yating , Liu Yangtai , Yang Shuo , Chen Yuhang , Liu Yang , Lu Dasheng , Niu Hongmei , Ren Fanchong , Xu Anning , Dong Qingli
Published: January 2024

Bacillus cereus is a food-borne pathogen that can produce cereulide in the growth period, which causes food poisoning symptoms. Due to its resistance to heat, extreme pH, and proteolytic enzymes, cereulide poses a serious threat to food safety. Temperature, pH, and aw can influence cereulide production, but there is still a lack of research with multi-environmental impacts. In this study, the effects of temperature (15~45 °C), pH (5~8), and aw (0.945~0.996) on the emetic reference strain B. cereus F4810/72 growth, cereulide production, relevant ces genes (cesA, cesB, cesP), and transcription regulators genes (codY and abrB) expression at transcription level were studied. B. cereus survived for 4~53 h or grew to 6.85~8.15 log10 CFU/mL in environmental combinations. Cereulide accumulation was higher in mid-temperature, acidic, or high aw environments. Increased temperature resulted in a lower cereulide concentration at pH 8 or aw of 0.970. The lowest cereulide concentration was found at pH 6.5 with an increased aw from 0.970 to 0.996. Water activity had a strong effect on transcriptional regulator genes as well as the cesB gene, and temperature was the main effect factor of cesP gene expression. Moreover, environmental factors also impact cereulide synthesis at transcriptional levels thereby altering the cereulide concentrations. The interaction of environmental factors may result in the survival of B. cereus without growth for a period. Gene expression is affected by environmental factors, and temperature and pH may be the main factors influencing the correlation between B. cereus growth and cereulide formation. This study contributed to an initial understanding of the intrinsic link between the impact of environmental factors and cereulide formation and provided valuable information for clarifying the mechanism of cereulide synthesis in combined environmental conditions.