bluuebunny/crossref_metadata_2025 huggingface dataset:
Delighting Palates with AI: Reinforcement Learning’s Triumph in Crafting Personalized Meal Plans with High User Acceptance
Authors: Amiri Maryam , Sarani Rad Fatemeh , Li Juan
Published: January 2024

Eating, central to human existence, is influenced by a myriad of factors, including nutrition, health, personal taste, cultural background, and flavor preferences. The challenge of devising personalized meal plans that effectively encompass these dimensions is formidable. A crucial shortfall in many existing meal-planning systems is poor user adherence, often stemming from a disconnect between the plan and the user’s lifestyle, preferences, or unseen eating patterns. Our study introduces a pioneering algorithm, CFRL, which melds reinforcement learning (RL) with collaborative filtering (CF) in a unique synergy. This algorithm not only addresses nutritional and health considerations but also dynamically adapts to and uncovers latent user eating habits, thereby significantly enhancing user acceptance and adherence. CFRL utilizes Markov decision processes (MDPs) for interactive meal recommendations and incorporates a CF-based MDP framework to align with broader user preferences, translated into a shared latent vector space. Central to CFRL is its innovative reward-shaping mechanism, rooted in multi-criteria decision-making that includes user ratings, preferences, and nutritional data. This results in versatile, user-specific meal plans. Our comparative analysis with four baseline methods showcases CFRL’s superior performance in key metrics like user satisfaction and nutritional adequacy. This research underscores the effectiveness of combining RL and CF in personalized meal planning, marking a substantial advancement over traditional approaches.
Effect of Intermittent Fasting on Cardiometabolic Health in the Chinese Population: A Meta-Analysis of Randomized Controlled Trials
Authors: Cheung Katy , Chan Vicky , Chan Stephanie , Wong Martin Ming Him , Chung Gary Ka-Ki , Cheng Wai-Yin , Lo Kenneth , Zeng Fangfang
Published: January 2024

The efficacy of intermittent fasting (IF), as an emerging weight management strategy, in improving cardiometabolic health has been evaluated in various populations, but that among Chinese individuals has not been systematically studied. A comprehensive search on multiple databases was performed to identify eligible randomized controlled trials (RCTs) up to October 2022. The primary outcome was post-intervention weight loss, and secondary outcomes included changes in cardiometabolic indicators. Effect estimates were meta-analyzed using a random-effects model. In total, nine RCTs with 899 Chinese participants were included. Time-restricted eating was the most adopted IF protocol in this study (six out of nine), followed by alternate-day fasting. The IF intervention significantly reduced body weight, body mass index, body fat mass, homeostatic model assessment of insulin resistance, low-density lipoprotein cholesterol, and triglycerides when compared with control groups. However, no statistically significant reductions in waist circumference, total cholesterol, high-density lipoprotein cholesterol, fasting glucose, systolic blood pressure, and diastolic blood pressure were found. To sum up, IF can be a weight management strategy and may improve the cardiometabolic health of Chinese adults, but more long-term trials using different IF strategies are required to generate robust evidence of its efficacy.
Bacterial Efflux Pump Inhibitors Reduce Antibiotic Resistance
Authors: Zhang Lan , Tian Xiaoyuan , Sun Lei , Mi Kun , Wang Ru , Gong Fengying , Huang Lingli
Published: January 2024

Bacterial resistance is a growing problem worldwide, and the number of deaths due to drug resistance is increasing every year. We must pay great attention to bacterial resistance. Otherwise, we may go back to the pre-antibiotic era and have no drugs on which to rely. Bacterial resistance is the result of several causes, with efflux mechanisms widely recognised as a significant factor in the development of resistance to a variety of chemotherapeutic and antimicrobial medications. Efflux pump inhibitors, small molecules capable of restoring the effectiveness of existing antibiotics, are considered potential solutions to antibiotic resistance and have been an active area of research in recent years. This article provides a review of the efflux mechanisms of common clinical pathogenic bacteria and their efflux pump inhibitors and describes the effects of efflux pump inhibitors on biofilm formation, bacterial virulence, the formation of bacterial persister cells, the transfer of drug resistance among bacteria, and mismatch repair. Numerous efforts have been made in the past 20 years to find novel efflux pump inhibitors which are known to increase the effectiveness of medicines against multidrug-resistant strains. Therefore, the application of efflux pump inhibitors has excellent potential to address and reduce bacterial resistance.
Toward the Rational Design of Organic Catalysts for Organocatalysed Atom Transfer Radical Polymerisation
Authors: Wang Zhilei , Wu Chenyu , Liu Wenjian
Published: January 2024

Thanks to their diversity, organic photocatalysts (PCs) have been widely used in manufacturing polymeric products with well-defined molecular weights, block sequences, and architectures. Still, however, more universal property-performance relationships are needed to enable the rational design of such PCs. That is, a set of unique descriptors ought to be identified to represent key properties of the PCs relevant for polymerisation. Previously, the redox potentials of excited PCs (PC*) were used as a good descriptor for characterising very structurally similar PCs. However, it fails to elucidate PCs with diverse chromophore cores and ligands, among which those used for polymerisation are a good representative. As showcased by model systems of organocatalysed atom transfer radical polymerisation (O-ATRP), new universal descriptors accounting for additional factors, such as the binding and density overlap between the PC* and initiator, are proposed and proved to be successful in elucidating the experimental performances of PCs in polymerisation. While O-ATRP is exemplified here, the approach adopted is general for studying other photocatalytic systems.
Bio-Based Polymers for Environmentally Friendly Phase Change Materials
Authors: Pielichowska Kinga , Nowicka-Dunal Katarzyna , Pielichowski Krzysztof
Published: January 2024

Phase change materials (PCMs) have received increasing attention in recent years as they enable the storage of thermal energy in the form of sensible and latent heat, and they are used in advanced technical solutions for the conservation of sustainable and waste energy. Importantly, most of the currently applied PCMs are produced from non-renewable sources and their carbon footprint is associated with some environmental impact. However, novel PCMs can also be designed and fabricated using green materials without or with a slight impact on the environment. In this work, the current state of knowledge on the bio-based polymers in PCM applications is described. Bio-based polymers can be applied as phase-change materials, as well as for PCMs encapsulation and shape stabilization, such as cellulose and its derivatives, chitosan, lignin, gelatin, and starch. Vast attention has been paid to evaluation of properties of the final PCMs and their application potential in various sectors. Novel strategies for improving their thermal energy storage characteristics, as well as to impart multifunctional features, have been presented. It is also discussed how bio-based polymers can extend in future the potential of new environmentally-safe PCMs in various industrial fields.
Ultrasensitive Detection of PSA Using Antibodies in Crowding Polyelectrolyte Multilayers on a Silicon Nanowire Field-Effect Transistor
Authors: Presnova Galina V. , Presnov Denis E. , Ulyashova Mariya M. , Tsiniaikin Ilia I. , Trifonov Artem S. , Skorb Ekaterina V. , Krupenin Vladimir A. , Snigirev Oleg V. , Rubtsova Maya Yu.
Published: January 2024

Immunosensors based on field-effect transistors with nanowire channels (NWFETs) provide fast and real-time detection of a variety of biomarkers without the need for additional labels. The key feature of the developed immunosensor is the coating of silicon NWs with multilayers of polyelectrolytes (polyethylenimine (PEI) and polystyrene sulfonate (PSS)). By causing a macromolecular crowding effect, it ensures the “soft fixation” of the antibodies into the 3-D matrix of the oppositely charged layers. We investigated the interaction of prostate-specific antigen (PSA), a biomarker of prostate cancer, and antibodies adsorbed in the PEI and PSS matrix. In order to visualize the formation of immune complexes between polyelectrolyte layers using SEM and AFM techniques, we employed a second clone of antibodies labeled with gold nanoparticles. PSA was able to penetrate the matrix and concentrate close to the surface layer, which is crucial for its detection on the nanowires. Additionally, this provides the optimal orientation of the antibodies’ active centers for interacting with the antigen and improves their mobility. NWFETs were fabricated from SOI material using high-resolution e-beam lithography, thin film vacuum deposition, and reactive-ion etching processes. The immunosensor was characterized by a high sensitivity to pH (71 mV/pH) and an ultra-low limit of detection (LOD) of 0.04 fg/mL for PSA. The response of the immunosensor takes less than a minute, and the measurement is carried out in real time. This approach seems promising for further investigation of its applicability for early screening of prostate cancer and POC systems.
Stability Qualification of Resins/Metallic Oxide Composites for Surface Oxidative Protection
Authors: Zaharescu Traian , Mirea Radu , Borbath Tunde , Borbath Istvan
Published: January 2024

The accelerated degradation of alkyd resins via γ-irradiation is investigated using non-isothermal chemiluminescence. The stability qualification is possible through the comparison of emission intensities on a temperature range starting from 100 °C up to 250 °C under accelerated degradation caused by radiolysis scission. The measurements achieved in the samples of cured state resin modified by various inorganic oxides reveal the influence of metallic traces on the aging amplitude, when the thermal resistance increases as the irradiation dose is augmented. Even though the unirradiated samples present a prominent chemiluminescence intensity peak at 80 °C, the γ-processed specimens show less intense spectra under the pristine materials and the oxidation starts smoothly after 75 °C. The values of activation energies required for oxidative degradation of the sample subjected to 100 kGy are significantly higher in the composite states than in the neat resin. The degradation mechanism of polymerized resins is discussed taking into account the effects of fillers on the stability of studied epoxy resin at various temperatures when the degradation and crosslinking are in competition for the decay of free radical.
Blind Man, Mirror, and Fire: Aquinas, Avicenna, and Averroes on Thinking
Authors: Cai Zhenyu
Published: January 2024

In Islamic tradition, the Falsafa school is well known for its naturalistic account of religion. When Falsafa’s theory of religion made its way to the Latin West, it was embraced and developed into the so-called “double truth theory” in Latin Averroism. However, this theory quickly lost its influence in the Latin tradition, primarily due to the critique by Thomas Aquinas. One of the key aspects of Aquinas’s critique is his criticism of the emanation theory of concepts and the doctrine of the unity of the intellect, which in turn undermines the foundation of Falsafa’s theory of religion, particularly their theory of natural prophecy. This paper aims to revisit the debate between Aquinas and Falsafa regarding the theory of intellect as the basis for natural prophecy, with a focus on highlighting Falsafa’s perspective. In particular, I examine how Aquinas’s arguments overlook the key insights that underpin Falsafa’s doctrine of the intellect.
First Old WomanMan and the Mesoamerican Diphrastic Kenning of Engendering
Authors: Freidel David
Published: January 2024

The royalty of the Classic Maya of Mesoamerica, and later sages of the Maya, used a powerful diphrastic kenning chab akab’, glossed as “generation-darkness” to convey a range of objectives, conjuring foremost among them. Known principally from hieroglyphic written expressions, but also depicted in the form of sacrificial instruments and offerings, Eleanor Harrison-Buck, following Timothy Knowlton, proposed that the kenning references sexual intercourse. This essay proposes that a black steatite carved figure stylistically dating to the Middle Preclassic period (900–350 CE) depicts this incantation as an old woman giving birth to her maleness in the form of a circumcised penis. A second Middle Preclassic figure of a dancing child, found as an heirloom in a Classic tomb, is compared to show the link between Preclassic and Classic meaning.
Upconversion-Powered Photoelectrochemical Bioanalysis for DNA Sensing
Authors: Liu Hong , Wei Weiwei , Song Jiajun , Hu Jin , Wang Zhezhe , Lin Peng
Published: January 2024

In this work, we report a new concept of upconversion-powered photoelectrochemical (PEC) bioanalysis. The proof-of-concept involves a PEC bionanosystem comprising a NaYF4:Yb,Tm@NaYF4 upconversion nanoparticles (UCNPs) reporter, which is confined by DNA hybridization on a CdS quantum dots (QDs)/indium tin oxide (ITO) photoelectrode. The CdS QD-modified ITO electrode was powered by upconversion absorption together with energy transfer effect through UCNPs for a stable photocurrent generation. By measuring the photocurrent change, the target DNA could be detected in a specific and sensitive way with a wide linear range from 10 pM to 1 μM and a low detection limit of 0.1 pM. This work exploited the use of UCNPs as signal reporters and realized upconversion-powered PEC bioanalysis. Given the diversity of UCNPs, we believe it will offer a new perspective for the development of advanced upconversion-powered PEC bioanalysis.
Segmentation of Low-Light Optical Coherence Tomography Angiography Images under the Constraints of Vascular Network Topology
Authors: Li Zhi , Huang Gaopeng , Zou Binfeng , Chen Wenhao , Zhang Tianyun , Xu Zhaoyang , Cai Kunyan , Wang Tingyu , Sun Yaoqi , Wang Yaqi , Jin Kai , Huang Xingru
Published: January 2024

Optical coherence tomography angiography (OCTA) offers critical insights into the retinal vascular system, yet its full potential is hindered by challenges in precise image segmentation. Current methodologies struggle with imaging artifacts and clarity issues, particularly under low-light conditions and when using various high-speed CMOS sensors. These challenges are particularly pronounced when diagnosing and classifying diseases such as branch vein occlusion (BVO). To address these issues, we have developed a novel network based on topological structure generation, which transitions from superficial to deep retinal layers to enhance OCTA segmentation accuracy. Our approach not only demonstrates improved performance through qualitative visual comparisons and quantitative metric analyses but also effectively mitigates artifacts caused by low-light OCTA, resulting in reduced noise and enhanced clarity of the images. Furthermore, our system introduces a structured methodology for classifying BVO diseases, bridging a critical gap in this field. The primary aim of these advancements is to elevate the quality of OCTA images and bolster the reliability of their segmentation. Initial evaluations suggest that our method holds promise for establishing robust, fine-grained standards in OCTA vascular segmentation and analysis.
Cross-Video Pedestrian Tracking Algorithm with a Coordinate Constraint
Authors: Huang Cheng , Li Weihong , Yang Guang , Yan Jiachen , Zhou Baoding , Li Yujun
Published: January 2024

Pedestrian tracking in surveillance videos is crucial and challenging for precise personnel management. Due to the limited coverage of a single video, the integration of multiple surveillance videos is necessary in practical applications. In the realm of pedestrian management using multiple surveillance videos, continuous pedestrian tracking is quite important. However, prevailing cross-video pedestrian matching methods mainly rely on the appearance features of pedestrians, resulting in low matching accuracy and poor tracking robustness. To address these shortcomings, this paper presents a cross-video pedestrian tracking algorithm, which introduces spatial information. The proposed algorithm introduces the coordinate features of pedestrians in different videos and a linear weighting strategy focusing on the overlapping view of the tracking process. The experimental results show that, compared to traditional methods, the method in this paper improves the success rate of target pedestrian matching and enhances the robustness of continuous pedestrian tracking. This study provides a viable reference for pedestrian tracking and crowd management in video applications.
Spatial Visual Imagery (SVI)-Based Electroencephalograph Discrimination for Natural CAD Manipulation
Authors: Cao Beining , Niu Hongwei , Hao Jia , Yang Xiaonan , Ye Zinian
Published: January 2024

With the increasing demand for natural interactions, people have realized that an intuitive Computer-Aided Design (CAD) interaction mode can reduce the complexity of CAD operation and improve the design experience. Although interaction modes like gaze and gesture are compatible with some complex CAD manipulations, they still require people to express their design intentions physically. The brain contains design intentions implicitly and controls the corresponding body parts that execute the task. Therefore, building an end-to-end channel between the brain and computer as an auxiliary mode for CAD manipulation will allow people to send design intentions mentally and make their interaction more intuitive. This work focuses on the 1-D translation scene and studies a spatial visual imagery (SVI) paradigm to provide theoretical support for building an electroencephalograph (EEG)-based brain–computer interface (BCI) for CAD manipulation. Based on the analysis of three spatial EEG features related to SVI (e.g., common spatial patterns, cross-correlation, and coherence), a multi-feature fusion-based discrimination model was built for SVI. The average accuracy of the intent discrimination of 10 subjects was 86%, and the highest accuracy was 93%. The method proposed was verified to be feasible for discriminating the intentions of CAD object translation with good classification performance. This work further proves the potential of BCI in natural CAD manipulation.
Sol-Gel Synthesized Amorphous (InxGa1−x)2O3 for UV Photodetection with High Responsivity
Authors: Zhang Yupeng , Zhou Ruiheng , Liu Xinyan , Bi Zhengyu , Ruan Shengping , Ma Yan , Li Xin , Liu Caixia , Chen Yu , Zhou Jingran
Published: January 2024

β-Ga2O3 photodetectors have the advantages of low dark current and strong radiation resistance in UV detection. However, the limited photocurrent has restricted their applications. Herein, MSM UV photodetectors based on (InxGa1−x)2O3 (x = 0, 0.1, 0.2, 0.3) by a sol-gel method were fabricated and studied. The doping of indium ions in Ga2O3 leads to lattice distortion and promotes the formation of oxygen vacancies. The oxygen vacancies in (InxGa1−x)2O3 can be modulated by various proportions of indium, and the increased oxygen vacancies contribute to the enhancement of electron concentration. The results show that the amorphous In0.4Ga1.6O3 photodetector exhibited improved performances, including a high light-to-dark current ratio (2.8 × 103) and high responsivity (739.2 A/W). This work provides a promising semiconductor material In0.4Ga1.6O3 for high-performance MSM UV photodetectors.
Sensor-Integrated Chairs for Lower Body Strength and Endurance Assessment
Authors: Lee Alexander W. , Lee Melissa S. , Yeh Daniel P. , Yeh Hsi-Jen J.
Published: January 2024

This paper describes an automated method and device to conduct the Chair Stand Tests of the Fullerton Functional Test Battery. The Fullerton Functional Test is a suite of physical tests designed to assess the physical fitness of older adults. The Chair Stand Tests, which include the Five Times Sit-to-Stand Test (5xSST) and the 30 Second Sit-to-Stand Test (30CST), are the standard for measuring lower-body strength in older adults. However, these tests are performed manually, which can be labor-intensive and prone to error. We developed a sensor-integrated chair that automatically captures the dynamic weight and distribution on the chair. The collected time series weight–sensor data is automatically uploaded for immediate determination of the sit-to-stand timing and counts, as well as providing a record for future comparison of lower-body strength progression. The automatic test administration can provide significant labor savings for medical personnel and deliver much more accurate data. Data from 10 patients showed good agreement between the manually collected and sensor-collected 30CST data (M = 0.5, SD = 1.58, 95% CI = 1.13). Additional data processing will be able to yield measurements of fatigue and balance and evaluate the mechanisms of failed standing attempts.
Development of Location-Data-Based Orchard Passage Map Generation Method
Authors: Han Joong-hee , Park Chi-ho , Jang Young Yoon
Published: January 2024

Currently, pest control work using speed sprayers results in increasing numbers of safety accidents such as worker pesticide poisoning and rollover of vehicles during work. To address this, there is growing interest in autonomous driving technology for speed sprayers. To commercialize and rapidly expand the use of self-driving speed sprayers, an economically efficient self-driving speed sprayer using a minimum number of sensors is essential. This study developed an orchard passage map using location data acquired from positioning sensors to generate autonomous driving paths, without installing additional sensors. The method for creating the orchard passage map presented in this study was to create paths using location data obtained by manually driving the speed sprayer and merging them. In addition, to apply the orchard passage map when operating autonomously, a method is introduced for generating an autonomous driving path for the work start point movement path, work path, and return point movement path.
Sensors for Digital Transformation in Smart Forestry
Authors: Ehrlich-Sommer Florian , Hoenigsberger Ferdinand , Gollob Christoph , Nothdurft Arne , Stampfer Karl , Holzinger Andreas
Published: January 2024

Smart forestry, an innovative approach leveraging artificial intelligence (AI), aims to enhance forest management while minimizing the environmental impact. The efficacy of AI in this domain is contingent upon the availability of extensive, high-quality data, underscoring the pivotal role of sensor-based data acquisition in the digital transformation of forestry. However, the complexity and challenging conditions of forest environments often impede data collection efforts. Achieving the full potential of smart forestry necessitates a comprehensive integration of sensor technologies throughout the process chain, ensuring the production of standardized, high-quality data essential for AI applications. This paper highlights the symbiotic relationship between human expertise and the digital transformation in forestry, particularly under challenging conditions. We emphasize the human-in-the-loop approach, which allows experts to directly influence data generation, enhancing adaptability and effectiveness in diverse scenarios. A critical aspect of this integration is the deployment of autonomous robotic systems in forests, functioning both as data collectors and processing hubs. These systems are instrumental in facilitating sensor integration and generating substantial volumes of quality data. We present our universal sensor platform, detailing our experiences and the critical importance of the initial phase in digital transformation—the generation of comprehensive, high-quality data. The selection of appropriate sensors is a key factor in this process, and our findings underscore its significance in advancing smart forestry.
Trend Decomposition for Temperature Compensation in a Radar-Based Structural Health Monitoring System of Wind Turbine Blades
Authors: Simon Jonas , Moll Jochen , Krozer Viktor
Published: January 2024

The compensation of temperature is critical in every structural health monitoring (SHM) system for achieving maximum damage detection performance. This paper analyses a novel approach based on seasonal trend decomposition to eliminate the temperature effect in a radar-based SHM system for wind turbine blades that operates in the frequency band from 58 to 63.5 GHz. While the original seasonal trend decomposition searches for the trend of a periodic signal in its entirety, the new method uses a moving average to determine trends for each point of a periodic signal. The points of the seasonal signal no longer need to have the same trend. Based on the determined trends, the measurement signal can be corrected by temperature effects, providing accurate damage detection results under changing temperature conditions. The performance of the trend decomposition is demonstrated with experimental data obtained during a full-scale fatigue test of a 31 m long wind turbine blade subjected to ambient temperature variations. For comparison, the well-known optimal baseline selection (OBS) approach is used, which is based on multiple baseline measurements at different temperature conditions. The use of metrics, such as the contrast in damage indicators, enables the performance assessment of both methods.
How Does Fertility Policy Relaxation Affect Household Financial Asset Allocation? Evidence from the Universal Two-Child Policy in China
Authors: Wang Yujie , Ge Run , Gao Wenjing , Tang Dunzhe
Published: January 2024

Both fertility policy and the healthy development of financial markets are important topics for sustainable economic and social development. By using the difference-in-difference (DID) model, this paper investigates how the universal two-child policy (UTCP) in China aiming to improve fertility affects household financial asset allocation, based on the China Family Panel Studies (CFPS) data from 2010 to 2018. The results show that the implementation of UTCP has a significant negative impact on household risk asset holdings. Specifically, the policy decreases the probability of households participating in the financial market by 3.1 percentage points, reduces the total value of risk assets held by 50.2%, and lowers the proportion of risk asset investment by 1.76 percentage points. Mechanism analysis suggests that the implementation of the policy has a significantly negative impact on labor market outcomes for women, which decreases household income and increases the time and effort spent on caring for children. As a result, the financial resources available for household financial asset investment are diminished, and the time for activities such as information gathering and financial asset transactions is squeezed out, ultimately leading to a decrease in household risk asset investment. Heterogeneity analysis reveals that households with self-employed wives (higher income instability), households without a co-resident status with grandparents (more time spent on childcare), and high-income households (stronger willingness to have more children) are more affected by the policy. This study provides new supplements on how fertility policies affect the allocation of household financial assets and proposes constructive suggestions on how to establish a comprehensive system of childcare welfare and alleviate the economic pressure of family childcare in developing countries.
Unit Commitment Considering Electric Vehicles and Renewable Energy Integration—A CMAES Approach
Authors: Niu Qun , Tang Lipeng , Yu Litao , Wang Han , Yang Zhile
Published: January 2024

Global fossil fuel consumption and associated emissions are continuing to increase amid the 2022 energy crisis and environmental pollution and climate change issues are becoming even severer. Aiming at energy saving and emission reduction, in this paper, a new unit commitment model considering electric vehicles and renewable energy integration is established, taking into account the prediction errors of emissions from thermal units and renewable power generations. Furthermore, a new binary CMAES, dubbed BCMAES, which uses a signal function to map sampled individuals is proposed and compared with eight other mapping functions. The proposed model and the BCMAES algorithm are then applied in simulation studies on IEEE 10- and IEEE 118-bus systems, and compared with other popular algorithms such as BPSO, NSGAII, and HS. The results confirm that the proposed BCMAES algorithm outperforms other algorithms for large-scale mixed integer optimization problems with over 1000 dimensions, achieving a more than 1% cost reduction. It is further shown that the use of V2G energy transfer and the integration of renewable energy can significantly reduce both the operation costs and emissions by 5.57% and 13.71%, respectively.
Novel MPPT Controller Augmented with Neural Network for Use with Photovoltaic Systems Experiencing Rapid Solar Radiation Changes
Authors: Dawahdeh Ahmad , Sharadga Hussein , Kumar Sunil
Published: January 2024

A maximum power point tracking (MPPT) controller optimizes power harvesting in photovoltaic (PV) systems under varying conditions. The perturb and observation (P&O) algorithm is commonly used for MPP tracking, but suffers from slow response, loss of tracking direction, and entrapment. The current research proposes a neural network (NN) integrated with the P&O algorithm to enhance tracking performance during sudden variations in solar irradiance. The proposed neural network updates the duty cycle change when detecting sudden changes. It effectively estimates the duty cycle change even when trained with a small dataset. The integration between the NN and P&O significantly improves tracking performance compared with the conventional P&O algorithm, especially under sudden irradiance changes.
The Role of River Vigilance Committees to Address New Socio-Climatic Conditions in Chile: Insights from Ostrom’s Design Principles for Common-Pool Resource Institutions
Authors: Julio Natalia , Álvez Amaya , Castillo Rodrigo , Iglesias Kimberly , Rivera Diego , Ochoa Fernando , Figueroa Ricardo
Published: January 2024

Chile is currently facing a mega-drought, which is expected to lead to a significant increase in the water stress level. Social conflicts related to water use are linked to the effects of climate change and a governance system marked by the privatization of the natural resources of public interest. This study aims to analyze whether the current Chilean water governance scheme can adapt to the effects of climate change through a critical observation of the role of the River Vigilance Committees (RVCs; private user organizations exercising the public function of water management), from the perspective of Ostrom’s design principles for long-enduring Common-pool Resource (CPR) institutions. We analyze legal approaches, management mechanisms, and decision-making processes under the socio-climatic conditions that the country is currently facing. The results indicate that, with a few exceptions, the Chilean governance system does not allow RVCs to effectively incorporate the design principles—and, therefore, to achieve adaptation—due to dispersed functions, the exclusion of water users, and a lack of planning at different levels. We propose that water governance should consider the creation of River Basin Boards with broader planning powers, as well as the incorporation of different relevant stakeholders.
Multiple-Zone Synchronous Voltage Regulation and Loss Reduction Optimization of Distribution Networks Based on a Dual Rotary Phase-Shifting Transformer
Authors: Shao Chen , Yan Xiangwu , Yang Yaohui , Aslam Waseem , Jia Jiaoxin , Li Jiayao
Published: January 2024

For the problem in which accessing a high proportion of renewable energy results in exceeding the limit in distribution network voltage, the existing regulating method experiences difficulty in considering the two-way voltage regulation and loss reduction optimization function. This study proposes a series-type dual rotary phase-shifting transformer (DRPST) based on the principle of phase volume synthesis. This transformer exhibits bidirectional voltage regulation, high reliability, and low cost. First, the topology, operating principle, and equivalent circuit of DRPST are introduced, and its simplified circuit model is established. On the basis of this model, the causes of voltage exceeding the limits are analyzed and the active distribution network model that contains DRPST is constructed. A real-time rolling two-layer optimization strategy based on DRPST is proposed. The inner layer model is solved using the multi-objective particle swarm optimization algorithm with the objective of minimizing voltage deviation and line loss. The optimal compromise solution of the Pareto solution set of the inner layer model is determined using the fuzzy subordinate degree function method. The outer model is based on the optimal compromise solution of the inner model, and the DRPST output rotor angle is controlled without deviation through double closed-loop proportional–integral regulation. Finally, the correctness and effectiveness of the proposed topology and control method are verified via simulation and experimental analysis.
Sustaining Organizational Outcomes in Manufacturing Firms: The Role of HRM and Occupational Health and Safety
Authors: Ateeq Ali , Al-refaei Abd Al-Aziz , Alzoraiki Mohammed , Milhem Marwan , Al-Tahitah Ali Nasser , Ibrahim Abdulhadi
Published: January 2024

While there is burgeoning interest in the influence of human resource management (HRM) on sustainability organizational outcomes (SOO), the intricate interplay with Occupational Health and Safety (OHS) has not yet been explored, particularly in manufacturing firms’ contexts. Therefore, this study aims to probe the symbiotic relationship between HRM practices, OHS, and SOO, spotlighting manufacturing firms. Data collection was conducted by utilizing a cross-sectional survey, convenience sampling technique, and a web-based form among the 256 respondents from an industrial company (Balexco) in Bahrain. Structural Equation Modeling (SEM) by Smart-PLS was used to analyze the collected data. Our analysis highlighted a significant positive relationship between HRM, SOO, and OHS. Moreover, this study highlighted the dual impact of direct and indirect HRM on SOO, mediated by OHS. These multi-layered insights reinforce the assumption that a comprehensive approach to HRM, aligning performance aspirations with employee well-being, is instrumental in improving SOO. This study is a novel contribution to the literature because, by uncovering the intricate interplay of HRM, OHS, and SOO, practical implications and limitations were provided.
Examining the Impact of External Debt, Natural Resources, Foreign Direct Investment, and Economic Growth on Ecological Sustainability in Brazil
Authors: Saleem Saleem Haji , Ahmed Dildar Haydar , Samour Ahmed
Published: January 2024

Although some recent papers have explored the impacts of external debt on environmental sustainability, the impacts of external debt on the load capacity factor (LCF) have been ignored. In this regard, this work aims to examine the influence of renewable energy, FDI, and external debt on the LCF in Brazil over the period 1970–2021; this indicator implies the country’s strength to promote the population based on current lifestyles. This paper uses the novel augmented autoregressive distributive lag (A-ARDL) technique. The findings from the A-ARDL show that renewable energy positively influenced ecological sustainability by promoting the LCF by 0.451% in the short run and 0.038% in the long run. In addition, the findings show that an increase in the rent of natural resources promotes the LCF. In contrast, the outcomes illustrate that an increase in the external debt led to an adverse impact on ecological sustainability by decreasing the level of LCF by 0.093% in the short run and 0.162% in the long run. Furthermore, the findings demonstrated that FDI negatively affects the ecological sustainability quality by reducing the LCF in the country. The study provides beneficial recommendations to policymakers in Brazil for achieving sustainable development in Brazil.
Techno-Economic Feasibility of the Use of Floating Solar PV Systems in Oil Platforms
Authors: Veliathur Chinnasamy Srinivasan Chellapillai , Soori Prashant Kumar , Ghaith Fadi A.
Published: January 2024

Offshore facilities have high energy demands commonly accomplished with local combustion-based power generators. With the increased commercialization of the marine renewable energy sector, there is still a need for research on floating photovoltaic installations on their performance and economic perspective. This paper investigates the techno-commercial feasibility of installing a battery-integrated floating solar photovoltaic (FPV) system for an offshore oil platform facility in Abu Dhabi. The performance analysis of two floating PV design schemes has been evaluated using the PVsyst design tool. The proposed system’s annual solar energy availability from the PVsyst 7.2.21 output was validated with MATLAB Simulink R2022b with a deviation of 1.85%. The optimized solution achieved the Levelized Cost of Electricity (LCOE) of 261 USD/MWh with a Discounted Payback Period of 9.5 years. Also, the designed system could reduce carbon emissions by 731 tons per year. Furthermore, it was recognized that the contribution of the marine sector to the construction of floating platforms influences the success of floating PV systems. Independently authorized floating PV system designs would guarantee insurability from the viewpoints of investors and end users.
In Vitro Assessment of Ozone-Treated Deoxynivalenol by Measuring Cytotoxicity and Wheat Quality
Authors: Sun Chao , Mao Chuncai , Zhou Zhie , Xiao Jianhui , Zhou Wenwen , Du Juan , Li Jun
Published: January 2024

Deoxynivalenol (DON), a trichothecene mycotoxin, could lead to cytotoxicity in both animal bodies and plant seed cells. Ozone degradation technology has been applied to DON control. However, the safety and quality of the contaminated grain after DON degradation are largely obscured. In this work, we evaluated the cytotoxicity of ozone-treated DON through seed germination experiments and cytotoxicity tests. Cell experiments showed that the inhibition rate of HepG2 viability gradually increased within the concentrations of 1–10 mg/L of DON, alongside which an IC50 (half maximal inhibitory concentration) of 9.1 mg/L was determined. In contrast, degrading DON had no significant inhibitory effect on cell growth. Moreover, a 1–10 mg/L concentration of DON increased production of a large amount of reactive oxygen radicals in HepG2, with obvious fluorescence color development. However, fluorescence intensity decreased after DON degradation. Further, DON at a concentration of >1 mg/L significantly inhibited the germination of mung bean seeds, whereas no significant inhibition of their germination or growth were observed if DON degraded. Changes in total protein content, fatty acid value, and starch content were insignificant in wheat samples suffering ozone degradation, compared to the untreated group. Lastly, the ozone-treated wheat samples exhibited higher tenacity and whiteness. Together, our study indicated that the toxicity of DON-contaminated wheat was significantly reduced after ozone degradation.
A Dam Safety State Prediction and Analysis Method Based on EMD-SSA-LSTM
Authors: Yang Xin , Xiang Yan , Wang Yakun , Shen Guangze
Published: January 2024

The safety monitoring information of the dam is an indicator reflecting the operational status of the dam. It is a crucial source for analyzing and assessing the safety state of reservoir dams, possessing strong real-time capabilities to detect anomalies in the dam at the earliest possible time. When using neural networks for predicting and warning dam safety monitoring data, there are issues such as redundant model parameters, difficulty in tuning, and long computation times. This study addresses real-time dam safety warning issues by first employing the Empirical Mode Decomposition (EMD) method to decompose the effective time-dependent factors and construct a dam in a service state analysis model; it also establishes a multi-dimensional time series analysis equation for dam seepage monitoring. Simultaneously, by combining the Sparrow Optimization Algorithm to optimize the LSTM neural network computation process, it reduces the complexity of model parameter selection. The method is compared to other approaches such as RNN, GRU, BP neural networks, and multivariate linear regression, demonstrating high practicality. It can serve as a valuable reference for reservoir dam state prediction and engineering operation management.
Waveform Imaging Based on Linear Forward Representations for Scalar Wave Seismic Data
Authors: Lu Fangzheng , Chen Shengchang , Chen Guoxin
Published: January 2024

The current reverse-time migration, which is based on wave equations for imaging wavefields, employs an imaging formula derived from Claerbout’s imaging principle. This imaging formula is only valid for plane waves with small incident angles on the perfectly flat reflecting surface. However, the complexity of seismic wave propagation may lead to situations that do not meet this requirement. Therefore, this paper divides the subsurface into local scattering and reflecting bodies. It proposes linear forward representations for scattering and reflection data based on perturbations in the physical parameters and wave impedance, respectively. To further describe the effect on the reflecting body boundary, the local reflection coefficient is defined and the linear forward representation for the reflection data based on it is obtained. After that, the proposed linear forward representations are used as the forward equations for the linear inverse of the seismic data, and the seismic data waveform imaging method is developed based on linear inversion theory. At the same time, the specific waveform imaging calculation formulas for scalar wave scattering data and scalar wave reflection data are provided and validated via numerical experiments. Compared with the current reverse-time migration, waveform migration not only has the correct phase and higher resolution in theory but also does not increase the computational complexity. To some extent, it improves the deficiencies of the current structural imaging and provides a basis for subsurface lithological imaging.
Economic knowledge: digital professional culture of a modern graduate
Authors:   Department of Finance and Accounting, National Institute of Business, Moscow, Russian Federation, Baranova Svetlana Viktorovna , Lidinfa Elena Petrovna ,   Department of Vocational Training and Business, Oryol State University named after I.S. Turgenev, Orel, Russian Federation
Published: January 2024

The article presents the authors' opinion on the problems of forming economic knowledge in the digital professional culture of modern graduates. The authors show that the need to update professional knowledge and acquire additional professional competencies is currently due to the sharp development of socioeconomic ties and changes in the formats of global interaction, which requires the formation of a wide range of digital competencies.
Interview technology in the multimedia space: conducting tactics
Authors:   Faculty of Journalism, Institute of Mass Media and Advertising, Russian State University for the Humanities, Moscow, Russian Federation, Savostyanov Aleksandr Ivanovich
Published: January 2024

The article discusses the specifics of conducting interviews on domestic television. The author examines a number of features that influence interviewing, including the constraints and influence of political ideology, sensationalism, effective headlines, the use of condensed interview formats, and the role of interviewing in social media. The article offers a broad overview of the topic and can be used for training in Journalism major, as well as for those interested in media roles on Russian television.
Analysis of the unemployment rate in the Sakhalin Region (2019–2021)
Authors:   Department of Applied Informatics and Statistics, Moscow University for the Humanities, Bashina Olga Emilievna , Puntusova Viktoriya Viktorovna ,   Faculty of Economics, Management and International Relations, Moscow University for the Humanities, Gastyunina Olesya Dmitrievna ,   Faculty of Economics, Management and International Relations, Moscow University for the Humanities
Published: January 2024

The authors address demographic and economic problems in the Sakhalin Region, which is an island region, the only one of its kind in Russia. The Sakhalin Region includes the island of Sakhalin, the islands of Moneron and Tyuleniy, and the Kuril Islands. The area of the Sakhalin Region is 87.1 thousand km2, including the largest territorial part on the island of Sakhalin, whose area is 78 thousand km2. The unemployment rate on Sakhalin, as well as the effectiveness of measures taken by the local administration and the state to reduce it are analyzed.
Using neural networks to sort municipal solid waste
Authors:   Department of Computer Science, Plekhanov Russian University of Economics, Popov Aleksey Anatolievich , Kuklev Roman Evgenievich ,   Department of Computer Science, Plekhanov Russian University of Economics, Egorov Dmitriy Georgievich ,   Faculty of Economics, Management and International Relations, Moscow University for the Humanities
Published: January 2024

The article proposes the criteria for selecting a suitable neural network architecture for sorting solid waste. The cases of using neural network methods for sorting solid waste are given. This is a fairly new and promising direction in the field of waste disposal; this article will help readers understand the principles of operation of neural networks and the advantages of their use in this task. The materials of the article can be used as part of training in areas related to economics and information technology.
Main trends and current problems of demographic development of Moscow
Authors:   Department of Applied Informatics and Statistics, Moscow University for the Humanities, Bashina Olga Emilievna , Matveeva Darya Sergeevna ,   Department of Economics, Management and International Relations, Moscow University for the Humanities, Kolachik Darya Alekseevna ,   Department of Economics, Management and International Relations, Moscow University for the Humanities, Samoilik Eva Igorevna ,   Department of Economics, Management and International Relations, Moscow University for the Humanities
Published: January 2024

The demographic indicators of the city of Moscow are analyzed and key trends are identified. It is shown that Moscow, being one of the largest cities in the world, is constantly developing, and data on demographic changes that are in continuous dynamics are presented. The city has a long history of population growth, which has been fueled by various factors: the influx of population from former Soviet republics and regions, birth and death rates, the standard of living and the financial situation of city residents. Moscow has always been an attractive place for migrants, both from Russia and other countries. Every year many natives of other regions come here to study and work. All this is expressed in the demographic indicators of Moscow, the dynamics of which are determined by political, economic, and socio-cultural factors. The materials of the article can be used as part of training in areas related to economics and statistics.