bluuebunny/crossref_metadata_2025 huggingface dataset:
Feature Weighted Cycle Generative Adversarial Network with Facial Landmark Recognition and Perceptual Color Distance for Enhanced Face Animation Generation
Authors: Lo Shih-Lun , Cheng Hsu-Yung , Yu Chih-Chang
Published: December 2024

We propose an anime style transfer model to generate anime faces from human face images. We improve the model by modifying the normalization function to obtain more feature information. To make the face feature position of the anime face similar to the human face, we propose facial landmark loss to calculate the error between the generated image and the real human face image. To avoid obvious color deviation in the generated images, we introduced perceptual color loss into the loss function. In addition, due to the lack of reasonable metrics to evaluate the quality of the animated images, we propose the use of Fréchet anime inception distance to calculate the distance between the distribution of the generated animated images and the real animated images in high-dimensional space, so as to understand the quality of the generated animated images. In the user survey, up to 74.46% of users think that the image produced by the proposed method is the best compared with other models. Also, the proposed method reaches a score of 126.05 for Fréchet anime inception distance. Our model performs the best in both user studies and FAID, showing that we have achieved better performance in human visual perception and model distribution. According to the experimental results and user feedback, our proposed method can generate results with better quality compared to existing methods.
Integrated Junction Barrier Schottky Diode and MOS-Channel Diode in SiC Planar MOSFETs for Optimization of Reverse Performances
Authors: Li Xinyu , He Feng , Niu Xiping , Sang Ling , He Yawei , Xu Kaixuan , Tian Yan , Zhou Xintian , Jia Yunpeng , Jin Rui
Published: December 2024

A novel planar silicon carbide (SiC) MOSFET integrated with both MOS-channel diode (MCD) and junction barrier Schottky diode (JBS) on the same chip (MCD-JBSFET) is proposed and investigated through Technology Computer-Aided Design (TCAD) simulations in this paper. The proposed device features the lowest turn-on voltage and the best current conduction capability under the reverse-biased conditions, allowing it to achieve the same reverse conduction capability with fewer MCDs compared to conventional MOSFET with MCD structures (MCDFET). This reduction in the number of MCDs enables more channels to operate under forward-biased conditions, thereby improving power density. Compared to a conventional MOSFET integrated with JBS structure (JBSFET), the reverse current in the MCD-JBSFET flows through both the MCD and JBS, which suppresses the peak lattice temperature at Schottky contact and enhances the high-temperature robustness, especially under surge current conditions. In addition, the split-gate structure in the proposed structure optimizes the reverse capacitance and the figure of merit Ron,sp × Qg by factors of 0.65 and 2.15, respectively. Finally, the switching losses are reduced by 40.2%, indicating the suitability of MCD-JBSFET for high-frequency and high-current applications.
A Container Escape Detection Method Based on a Dependency Graph
Authors: Chen Kai , Zhao Yufei , Guo Jing , Gu Zhimin , Han Longxi , Tang Keyi
Published: December 2024

With the rapid advancement in edge computing, container technology has gained widespread adoption. This is due to its lightweight isolation mechanisms, high portability, and fast deployment capabilities. Despite these advantages, container technology also introduces significant security risks. One of the most critical is container escape. However, current detection research is incomplete. Many methods lack comprehensive detection coverage or fail to fully reconstruct the attack process. To address these gaps, this paper proposes a container escape detection method based on a dependency graph. The method uses various nodes and edges to describe diverse system behaviors. This approach enables the detection of a broader range of attack types. It also effectively captures the contextual relationships between system events, facilitating attack traceability and reconstruction. We design a method to identify container processes on the dependency graph through label generation and propagation. Based on this, container escape detection is implemented using file access control within the graph. Experimental results demonstrate the effectiveness of the proposed method in detecting container escapes.
The Use of Machine Learning Models with Optuna in Disease Prediction
Authors: Lai Li-Hsing , Lin Ying-Lei , Liu Yu-Hui , Lai Jung-Pin , Yang Wen-Chieh , Hou Hung-Pin , Pai Ping-Feng
Published: December 2024

Effectively and equitably allocating medical resources, particularly for minority groups, is a critical issue that warrants further investigation in rural hospitals. Machine learning techniques have gained significant traction and demonstrated strong performance across various fields in recent years. The determination of hyperparameters significantly influences the performance of machine learning models. Thus, this study employs Optuna, a framework specifically designed for optimizing the hyperparameters of machine learning models. Building on prior research, machine learning models with Optuna (MLOPTA) are introduced to forecast diseases of indigenous patients. The numerical results reveal that the designed MLOPTA system can accurately capture the occurrences of specified diseases. Therefore, the MLOPTA system offers a promising approach for disease forecasting. The disease forecasting results can serve as crucial references for allocating hospital resources.
Wearable System for Continuous Estimation of Transepidermal Water Loss
Authors: Matsui Natsumi , Ohnishi Ayumi , Uyama Ayaka , Sugino Tetsuzo , Terada Tsutomu , Tsukamoto Masahiko
Published: December 2024

To maintain skin moisture, we need to maintain good stratum corneum barrier function, which prevents moisture evaporation from the inside of the skin. Transepidermal water loss (TEWL), the amount of water that evaporates from the skin, indicates the state of barrier function. The barrier function of facial skin is easily damaged in daily life, and the condition of the skin becomes worse without us noticing. We should constantly monitor TEWL to prevent worsening skin conditions. In this paper, we propose a wearable device that continuously measures TEWL. We estimate TEWL using machine learning from temperature and humidity values of water evaporation from the skin and parameters that affect TEWL, such as skin surface temperature and galvanic skin response. We experimented with the prototype device in a controlled environment. We confirmed that the prototype device could estimate TEWL accurately enough to judge the skin’s condition in stationary and conversational situations. Then, we experimented to verify the environmental conditions for estimating TEWL using the prototype device. The prototype device could estimate TEWL with sufficient precision in an office without airflow. However, we could not estimate TEWL in the office with airflow and outdoor.
Influence of Parameters on the Excitation Power of Third Harmonic Brushless Hybrid Excitation Generator
Authors: Xia Yonghong , Xu Jianxin , Hu Jinhui , Yu Yeguo , Chen Ying , Zhang Jingming
Published: December 2024

Hybrid-excited generators have a wide voltage regulation capability or a wide range of variable-speed constant-voltage output capability, providing a significant advantage in the new energy power generation field. To achieve the optimal design of brushless hybrid excitation synchronous generators with third harmonic excitation, it is necessary to grasp the influence of design parameters on excitation power accurately. Firstly, this paper elaborates on the structure and principle of the hybrid excitation synchronous generator. From the perspective of excitation power generation, the expression for excitation power in hybrid excitation generators has been derived, identifying the primary factors influencing excitation power, which include winding parameters, structural parameters, and magnetic circuit saturation. Secondly, qualitatively calculate the influence of the number of turns and arrangement, turns in rotor harmonic, air gap length, and thickness of the permanent magnet on the excitation power, which is verified by the electromagnetic field finite element method. The results showed that the use of full pitch and a moderate increase in turns, a decrease in air gap length, and an increase in the thickness of the permanent magnet can all increase the rotor excitation power. A brushless hybrid excitation synchronous generator prototype based on third harmonic excitation was developed, the correctness of theoretical analysis and calculation were verified by test results.
Assessing the Emission Reduction Policies on Global Value Chains: The Renewable Energy Policy Framework
Authors: Wuri Josephine , Rahayu Caecilia Wahyu Estining , Hardanti Yuliana Rini , Kristianti Ni Kadek Ayu
Published: December 2024

To mitigate climate change problems, a low-carbon renewable energy policy is needed. Evaluating the impact of these problems on global value chains is essential to ensure an effective transition to sustainable economic development. This study analyzes the impact of emission reduction policies on Global Value Chains (GVC) using the Global Trade Analysis Project-Energy (GTAP-E) model by addressing three fundamental research questions. First, how does the implementation of B40 renewable energy policy combined with carbon tax affect Indonesia’s energy sector output and carbon emissions? Second, to what extent does this policy influence Indonesia’s participation in GVC, particularly in the crude palm oil (CPO) industry? Third, what are the implications for economic growth and social welfare? Our analysis focuses on the CPO sector, considering Indonesia’s position as the world’s largest producer and its potential for sustainable biofuel production through clean technological processes. The results of this study show that the policy effectively reduces carbon emissions through decreased fossil fuel production while promoting renewable energy adoption. It significantly increases Indonesia’s forward GVC participation in the CPO sector, enhancing value addition and international competitiveness. Furthermore, the policy generates positive impacts on economic growth and social welfare. This study emphasizes the importance of international policy coordination and the crucial role of technological innovation in achieving sustainable economic development for a low-carbon economy and strengthening Indonesia’s position in the global value chain.
Fallen Leaves as a Substrate for Biogas Production
Authors: Wysocka-Czubaszek Agnieszka , Czubaszek Robert
Published: December 2024

Fallen leaves in cities are often treated as waste; therefore, they are collected, transported outside urban areas, and composted, which contributes to greenhouse gas (GHG) emissions. Instead of this conventional management approach, fallen leaves could be utilized as a feedstock in biogas production, helping to reduce GHG emissions, increase renewable energy generation, and provide fertilizer. The aim of this study was to compare the mono-digestion of fallen leaves from three tree species commonly found in parks and along streets—northern red oak (Quercus rubra L.), small-leaved lime (Tilia cordata Mill.), and Norway maple (Acer platanoides L.)—in both wet and dry anaerobic digestion (AD) systems. A biochemical methane potential (BMP) test was conducted in batch assays for each of the three substrates in both AD technologies at a temperature of 38 ± 1 °C. The highest specific methane yield (SMY) was obtained from Quercus leaves in wet AD technology, with a methane yield of 115.69 ± 4.11 NL kgVS−1. The lowest SMY (55.23 ± 3.36 NL kgVS−1) was observed during the dry AD of Tilia leaves. The type of technology had no significant impact on the SMY of Acer and Tilia leaves; however, the methane yield from Quercus leaves in wet AD was significantly higher (p < 0.05) than that from dry AD. Studies on the use of fallen leaves from Tilia cordata, Quercus rubra, and Acer platanoides as substrates in mono-digestion technology have shown their limited suitability for biogas production. Nevertheless, this feedstock may be more effectively used as a co-substrate, mainly due to the low concentrations of ammonia (NH3) and hydrogen sulfide (H2S) in the biogas produced from these leaves, both of which are considered inhibitors of the AD process.
The Extreme Temperature Weather Impact Mechanism Analysis of MMC-HVDC’s Harmonic Impedance and Its Dynamic Stability
Authors: Zhou Hongling , Li Baohong , Jiang Qin , Liu Tianqi , Zhang Yingmin , Yin Yue
Published: December 2024

In recent years, the small-signal stability of modular multilevel converter (MMC)-based high-voltage direct current (HVDC) systems has garnered significant attention. But little attention has been paid to the impact of extreme temperature weather, although it may change the parameters of outdoor devices and lead to oscillations in a weak system. To explore the impact of environmental temperature on the stability of the MMC-HVDC system, this paper firstly establishes a comprehensive harmonic state space (HSS) model, incorporating the effect of temperature on the impedance of AC and DC transmission lines based on the thermal balance equation. By comparing the theoretical and simulation results, the accuracy of the model is validated. Subsequently, the mechanisms through which extreme temperature conditions affect system stability were analyzed. The results indicate that under extreme high-temperature conditions, the impedance of the MMC is significantly affected, weakening system stability and potentially causing small-signal instability. In contrast, extreme low-temperature conditions show no noticeable impact on system stability.
A Study on Cyclical Learning Rates in Reinforcement Learning and Its Application to Temperature and Power Consumption Control of Refrigeration System
Authors: Wang Jingchen , Motegi Kazuhiro , Shiraishi Yoichi , Hashimoto Seiji
Published: December 2024

In recent years, with the advancement of computer hardware technology, an increasing number of complex control systems have begun employing reinforcement learning over traditional PID controls to address the challenge of managing multiple outputs simultaneously. In this study, we have for the first time adopted the cyclical learning rate method, which is widely used in deep learning, and applied it to deep reinforcement learning. Utilizing MATLAB Simulink, a detailed simulation model was developed with the RSD-4TFK5J model refrigeration storage as the reference object. We precisely evaluated the effects of various cyclical learning rate strategies on the training process of the model. The simulation results demonstrate the effectiveness of the cyclical learning rate method during the training phase, showcasing its potential to enhance learning efficiency and system performance in complex control environments.
Simulating Water Invasion Dynamics in Fractured Gas Reservoirs
Authors: Li Yueyang , Zhang Enli , Yue Ping , Zhao Han , Xie Zhiwei , Liu Wei
Published: December 2024

The Longwangmiao Formation gas reservoir in the Moxi block of the Sichuan Basin is a complex carbonate reservoir characterized by a low porosity and permeability, strong heterogeneity, developed natural fractures, and active water bodies. The existence of natural fractures allows water bodies to easily channel along these fractures, resulting in a more complicated mechanism and dynamic law of gas-well water production, which seriously impacts reservoir development. Therefore, a core-based simulation experiment was designed for oil–water two-phase flow. Three main factors influencing the water production of the gas reservoir, namely fracture permeability, fracture penetration, and water volume multiple, were analyzed using the orthogonal test method. The experimental results showed that the influences of the experimental parameters on the recovery factor and average water production can be ranked as water volume multiple > fracture penetration > fracture permeability, with the influence of the water volume multiple being slightly greater than that of the other two parameters. It provides a certain theoretical basis for water control of the gas reservoir.
Examining the Nexus Between Renewable Energy, CO2 Emissions, and Economic Factors: Implications for Countries Marked by High Rates of Coronary Heart Disease
Authors: Salahodjaev Raufhon , Sadikov Avazbek
Published: December 2024

This study investigates the complex interconnections between renewable energy adoption, carbon dioxide (CO2) emissions, and economic factors in 50 countries marked by high rates of coronary heart disease (CHD) between 2000 and 2020. Utilizing a sophisticated two-step system generalized method of moments (GMM) estimator and panel data method, our analysis reveals a significant negative impact of renewable energy on greenhouse gas emissions, emphasizing the role of sustainable energy sources in mitigating environmental and quality of life degradation. Additionally, our findings support the existence of the environmental Kuznets curve (EKC), demonstrating an inverted U-shaped relationship between gross domestic product (GDP) per capita and CO2 emissions. In line with nascent studies, the EKC for CO2 emissions suggests that as a country’s GDP per capita increases, the CO2 emissions initially rise but eventually decline after reaching a certain level of economic development, forming an inverted U-shaped relationship. Specifically, nations facing high cardiovascular heart disease mortality rates display an important link between renewable energy integration and improved environmental quality. These insights underscore the urgency for countries to transition rapidly to green energy, advocating for policies that promote renewable technologies through partnerships between the public, private sector, and government entities. Furthermore, the study emphasizes the necessity of innovative structural reforms in developing countries to stimulate economic growth beyond the EKC turning point, ensuring sustainable development while curbing their carbon footprint resulting from economic activities. Future research should explore the broader global contexts, considering variables like social capital and globalization to inform targeted policies aimed at safeguarding public health and the environment.
A Preliminary Experimental and Numerical Analysis of a Novel Solar Dryer
Authors: Muciaccia Pio Francesco , Nigro Alessandra , Aquilanti Alessia , Tomassetti Sebastiano , Muccioli Matteo , Di Nicola Giovanni
Published: December 2024

In this study, a novel solar dryer is presented and analyzed experimentally and numerically. The proposed device is a small, passive, indirect solar dryer that works in an unconventional way. The product is mainly heated by irradiation from the walls of the drying chamber, while its moisture is removed by an airflow caused by natural convection. In addition, it is a low-cost solar dryer made of readily available materials and has a variable geometry that allows it to increase its thermal performance. Two types of experimental tests were conducted to analyze its performance. Thermal tests without load were carried out to assess the suitability of the drying chamber temperatures. Load tests with various masses and types of food were carried out to evaluate its drying performance. The results of the experimental tests demonstrated that the solar dryer achieved temperatures suitable for food drying and was able to dry the tested foods. Finally, a Computational Fluid Dynamics (CFD) model was developed to predict the performance of the proposed solar dryer. The validation of the numerical model with experimental data confirms their reliability in accurately predicting the temperatures within the dryer.
Evaluating the Policy Implications of Renewable Portfolio Standards on Grid Reliability in the United States: An Instrumental Variable Quantile Analysis
Authors: Singh Sanjay B. , Alsabhan Talal H. , Alshagri Reem
Published: December 2024

This paper investigates the influence of Renewable Portfolio Standards (RPSs) on the reliability of grids while considering key indicators, including the System Average Interruption Duration Index (SAIDI), System Average Interruption Frequency Index (SAIFI), and Customer Average Interruption Duration Index (CAIDI), both without and with the inclusion of Major Event Days (MEDs). The study adopted the instrumental variable quantile regression (IVQR) method for estimation purposes. The first-stage 2SLS results confirm the robustness and validity of the instruments used, including the Democrats’ Participation Rate, Real Average Household Income, and Renewable Energy Capacity, which show strong relevance and satisfy the conditions of homogeneity. Our findings demonstrated that the adoption of RPS policies has significantly decreased the interruption of power in all of the considered quantiles. The impact is more potent in states facing more severe reliability challenges. The results proved the important role of the policies of RPSs in improving the stability of grids in the context of states having relatively poor reliability. In summary, the obtained findings demonstrate significant insights related to the policies of renewable energy in the resilience of infrastructure. Finally, the findings suggest that the government authorities should promote the RPS as a tool for enhancing the performance of grids in different states.
Well-Interference Characteristics of the Production of Shale Well Pads: A Case in the Southern Sichuan Basin
Authors: Zeng Bo , Chen Liqing , Zhang Zhen , Sun Qimeng , Zhu Haiyan , Tang Xuanhe , Wang Chen
Published: December 2024

With the development of shale gas horizontal well-filling technology, by drilling infill wells between wells, the well spacing is continuously reduced to make shale reservoir reconstruction more effective. However, in shale gas reservoirs in China, the problem of inter-well interference is becoming increasingly serious, which not only affects the production of well groups but also causes wellbore damage. Currently, the process of interference in the production process is unclear. This study addresses the inter-well interference issue in deep shale gas reservoirs. An integrated numerical simulation method combining the Discrete Fracture Network, Finite Element Method, and Finite Difference Method is proposed. A comprehensive reservoir numerical model considering the production process is proposed. According to the actual reservoir model parameters and operation parameters, a multi-factor analysis model under multiple production conditions was established. Cumulative gas production and inter-well interference were analyzed. Finally, a field model was established, and the history matching of formation pressure was carried out. According to the history-matching results, the pressure expansion range in the production stage was analyzed. These research results provide a scientific basis and practical suggestions for the effective management and mitigation of inter-well interference and are expected to play an important role in practical engineering applications.
Kinematics Analysis and Oil Film Lubrication Characteristics in the Piston–Cylinder Interface of a Bent-Axis-Type Piston Motor
Authors: Yu Jinlin , Hu Xiaozhou
Published: December 2024

Hydraulic piston motors are characterized by their excellent starting performance, high transmission torque, good sealing performance, compact design, and lightweight. These attributes make them highly applicable in fields such as construction machinery and marine applications. With the advancement of hydraulic transmission technology, higher performance requirements have been set for hydraulic motors. While extensive research has been conducted on hydraulic pumps, studies focusing on the performance of hydraulic motors remain relatively limited. Therefore, this paper is novel in that, based on the motion and force conditions of the piston, it differs from previous research on swashplate-type machinery by considering the complex structure of the bent-axis motor; it employs a micro finite element method to analyze the oil film characteristics at the piston–cylinder interface in a bent-axis piston motor, the structural changes in the piston assembly in the bent-axis motor are comprehensively considered, and a fluid–structure coupling model for the piston–cylinder interface is established. The leakage and viscous friction power loss equations for the piston–cylinder interface are derived. Simulation analyses are conducted using MATLAB R2016a to reveal the variation patterns of leakage and viscous friction power loss under different operating conditions and structural parameters, providing valuable insights for the operation analysis, energy loss evaluation, structural design optimization, and engineering applications of bent-axis piston motors.
A Comprehensive Review of Biogeochemical Modeling of Underground Hydrogen Storage: A Step Forward in Achieving a Multi-Scale Approach
Authors: Vasile Nicolò Santi
Published: December 2024

This paper presents an in-depth investigation of the biogeochemical modeling approaches applied to underground hydrogen storage. It delves into the intricate dynamics of hydrogen in the subsurface, focusing on small (pore-lab scale) and reservoir-scale models, highlighting the importance of capturing microbial, geochemical, and fluid flow dynamic interactions in porous media to simulate storage performance accurately. Small-scale models offer detailed insights into localized phenomena, such as microbial hydrogen consumption and mineral reactions, and can be verified and calibrated against laboratory data. Conversely, large-scale models are essential to assess the feasibility of a project and forecast the storage performance, but cannot be proven by real data yet. This work addresses the challenge of transitioning from fine-scale to reservoir models, integrating spatial heterogeneity and long-term dynamics while retaining biogeochemical complexity. Through the use of several simulation tools, like PHREEQC, Comsol, DuMuX, Eclipse, CMG-GEM, and others, this study explores how modeling approaches are evolving to incorporate multiphysics processes and biochemical feedback loops, which are essential for predicting hydrogen retention, flow, and potential risks. The findings highlight the strengths and limitations of current modeling techniques and suggest a workflow for exploiting at best existing modeling capabilities and developing reservoir models to support hydrogen storage appraisal and management.
Response of Larix sibirica Radial Growth to Climate Change in Kanas, Northern Xinjiang, China
Authors: Hou Jiannan , Chen Feng , Li Jianrong
Published: December 2024

Understanding how forest ecosystems respond to climate variability is critical for predicting the impacts of climate change on semi-arid and temperate regions. This study examines the climatic drivers of radial growth in Larix sibirica Ledeb in the Kanas Lake region, northern Xinjiang, China, to explore how climate change may alter forest growth patterns. Using tree-ring chronologies, we examine the relationships between temperature, precipitation, and drought conditions, as well as the influence of large-scale atmospheric circulation patterns on growth. Results indicate that high summer temperatures negatively affect tree growth, while adequate precipitation plays a crucial role in mitigating water stress, especially during key growth periods. Positive correlations with the Palmer Drought Severity Index further underscore the importance of long-term moisture availability. Moreover, the study highlights the role of the El Niño-Southern Oscillation in influencing moisture transport, with significant correlations between sea surface temperatures in the Niño 4 region and tree-ring growth. Future growth simulations under two climate scenarios suggest that moderate warming (SSP 2–4.5) may enhance growth, while more extreme warming (SSP 5–8.5) introduces greater uncertainty and potential growth instability. These findings provide critical guidance for forest management strategies in the face of climate change.
Alternative Uses of Fermented Wheat Bran: A Mini Review
Authors: Ma Longteng , Wang Hao , Qiu Yutao , Bai Ziyue , Yang Zizhong , Li Enkai , Ma Xiaokang , Xiao Dingfu
Published: December 2024

Bran is a by-product primarily derived from the milling of grains, notably wheat and rice. It is rich in dietary fiber, vitamins, minerals, and phytochemicals yet often remains underutilized in its raw form. This raw material is abundant and readily available, offering significant potential for value-added applications. In its unprocessed state, bran boasts a complex chemical composition that includes proteins, lipids, and carbohydrates. However, it also contains antinutritional components such as phytic acid and enzyme inhibitors, which may limit its nutritional efficacy. Through further processing or storage, these components can be transformed to enhance their antioxidant properties and overall nutritional value. Bran is used in both animal feed and human food applications, though its use is often hindered by its high fiber content and antinutritional factors. To maximize its utility, innovative processing techniques are required to improve its digestibility and nutrient availability. Fermentation presents a viable method for enhancing the nutritional profile of bran. This process typically employs microorganisms such as bacteria, yeast, or fungi to break down complex compounds, thereby increasing the bioavailability of nutrients. After fermentation, bran exhibits improved chemical composition and nutritional value. The process reduces antinutritional components while enriching the bran with beneficial compounds like amino acids and probiotics. Utilizing fermented bran in animal feed offers numerous advantages, including enhanced digestive health, improved nutrient absorption, and augmented disease resistance. It serves as a sustainable feed alternative that supports livestock growth while aligning with ecological goals. The processing of bran through fermentation not only maximizes its nutritional potential but also contributes to sustainable agricultural practices by reducing waste. Future research should focus on optimizing fermentation techniques and exploring novel applications in both feed and food industries to fully realize the benefits of this versatile by-product.
Evaluating Black Soldier FLY (Hermetia illucens) Frass and Larval Sheddings in the Production of a Quality Compost
Authors: Kenchanna Dhanush , Waliczek Tina Marie , Drewery Merritt L.
Published: December 2024

Black Soldier Fly (Hermetia illucens) is well-known for having a high protein and lipid content during its larval stage and is cultivated for animal feed. Rearing Black Soldier Fly larvae (BSFL) produces byproducts known as frass and larval sheddings in large volumes with limited applications. Therefore, there is a need to identify viable sustainable management strategies to prevent potential environmental issues associated with their accumulation. Accordingly, the purpose of this study was to evaluate BSFL frass and larval sheddings as viable ingredients in composts that utilize additional nitrogen feedstocks. Four experimental compost piles (22.7 m3) with different ratios of BSFL frass and sheddings were developed based on previous research; two piles included 25% frass, whereas the other two included 30% frass. Across these piles, the inclusion of wood chips, food waste, and livestock manure varied to determine the best proportions for compost. The compost piles were maintained for five months, including a curing phase. After curing, samples from each pile were collected to analyze their pH, macro- and micro-nutrients, particle size, stability, and maturity. The findings indicated that the pH levels (7.1–8.1) and carbon-to-nitrogen ratios (10.40–13.20) were within the optimal ranges for all piles. The phosphorus levels (0.75–1.30%) of each pile exceeded typical ranges, likely due to the high phosphorus content of the frass itself. The moisture content varied widely (24.5–51.7%), with some piles falling below optimal levels. Stability and maturity tests yielded mixed results, with some piles demonstrating continued decomposition activity. Overall, the findings indicated that inclusion rates of 25–30% of BSFL frass and sheddings produced compost with generally favorable characteristics when high nitrogen feedstocks were also incorporated into the compost piles. These findings align with those from previous research and highlight both the potential and challenges of incorporating BSFL frass into compost production.
SIGNIFY: Leveraging Machine Learning and Gesture Recognition for Sign Language Teaching Through a Serious Game
Authors: Ulrich Luca , Carmassi Giulio , Garelli Paolo , Lo Presti Gianluca , Ramondetti Gioele , Marullo Giorgia , Innocente Chiara , Vezzetti Enrico
Published: December 2024

Italian Sign Language (LIS) is the primary form of communication for many members of the Italian deaf community. Despite being recognized as a fully fledged language with its own grammar and syntax, LIS still faces challenges in gaining widespread recognition and integration into public services, education, and media. In recent years, advancements in technology, including artificial intelligence and machine learning, have opened up new opportunities to bridge communication gaps between the deaf and hearing communities. This paper presents a novel educational tool designed to teach LIS through SIGNIFY, a Machine Learning-based interactive serious game. The game incorporates a tutorial section, guiding users to learn the sign alphabet, and a classic hangman game that reinforces learning through practice. The developed system employs advanced hand gesture recognition techniques for learning and perfecting sign language gestures. The proposed solution detects and overlays 21 hand landmarks and a bounding box on live camera feeds, making use of an open-source framework to provide real-time visual feedback. Moreover, the study compares the effectiveness of two camera systems: the Azure Kinect, which provides RGB-D information, and a standard RGB laptop camera. Results highlight both systems’ feasibility and educational potential, showcasing their respective advantages and limitations. Evaluations with primary school children demonstrate the tool’s ability to make sign language education more accessible and engaging. This article emphasizes the work’s contribution to inclusive education, highlighting the integration of technology to enhance learning experiences for deaf and hard-of-hearing individuals.
Policy-Based Smart Contracts Management for IoT Privacy Preservation
Authors: Rouached Mohsen , Akremi Aymen , Macherki Mouna , Kraiem Naoufel
Published: December 2024

This paper addresses the challenge of preserving user privacy within the Internet of Things (IoT) ecosystem using blockchain technology. Several approaches consider using blockchain and encryption to enhance the privacy of IoT applications and constrained IoT devices. However, existing blockchain platforms such as Ethereum and Hyperledger Fabric already use encryption to store data blocks and secure communication. Therefore, introducing an additional cryptographic layer on top of these platforms could potentially increase processing overhead and reduce response time. In this work, we investigate the integration of IoT and blockchain for privacy preservation. More specifically, we propose a new model that leverages the properties of private blockchain and smart contracts to ensure user data privacy when shared with others. We define policy-based algorithms and notations to assist users in managing smart contracts responsible for registering and controlling their IoT devices. We also specify multiple smart contracts designed to enhance privacy by creating a private channel for communication between the user and the blockchain network.
Rethinking Blockchain Technologies for the Maritime Industry: An Overview of the Current Landscape
Authors: Kim Heejoo , Xiao Zhe , Zhang Xiaocai , Fu Xiuju , Qin Zheng
Published: December 2024

This survey aims to provide an up-to-date and succinct yet informative overview of the blockchain technologies for the maritime industry. We synthesize the recent advancements in blockchain development and its adoption across maritime sectors, highlighting the key blockchain use cases, including promoting maritime sustainability and optimizing maritime supply chain management through improved traceability, advancing smart shipping with automated processes and fostering collaboration among stakeholders by enhancing transparency. Through an analysis of current implementations, pilot projects, and case studies, we especially focus on identifying the challenges and barriers, reasoning on the status quo, and the opportunities and future perspectives for blockchain in maritime.
Study on Smoke Characteristics in Cavern Complexes of Pumped-Storage Power Stations
Authors: Hu Peifeng , Xu Tong , Liu Chang , Wang Kai , Chong Fazheng , Shang Fengju , Wu Jiansong
Published: December 2024

The underground power houses of pumped-storage power stations (PSPSs) are highly complex, with interconnected and multidimensional structures, including various tunnels, such as the main and auxiliary power houses (MAPH), main transformer tunnel (MTT), tailrace gate tunnel (TGT), access tunnels (ATs), cable tunnels (CTs) etc. During intensive civil construction and electromechanical installation, fire risk becomes particularly prominent. Current research mainly examines fire incidents within individual tunnels, lacking comprehensive analyses of smoke spread across the entire cavern network. Therefore, in this study, a numerical model of a cavern complex in a PSPS was established to analyze smoke behavior and temperature distribution under various fire scenarios. The results indicated that when a fire occurred in the MAPH, the fire risk was relatively higher compared to fires in other places. Using the example of smoke spread from the MAPH to the MTT, the smoke spread process through key connecting caverns was analyzed. Initially, the temperature and velocity were stable, and the CTs and traffic cable tunnel in the auxiliary powerhouse (TCTAP) were the main smoke paths. After 7 min, the heat release rate (HRR) became stable, and CTs and ATs became the main paths for smoke spread, which could provide a reference for improving fire design in underground cavern systems.
Study on the Chemical Composition and Anti-Tumor Mechanisms of Clausena lansium Fruit By-Products: Based on LC-MS, Network Pharmacology Analysis, and Protein Target Validation
Authors: Zhang Ziyue , Zhang Liangqian , Wu Pengfei , Tian Yuan , Wen Yao , Xu Meina , Xu Peihao , Jiang Ying , Ma Nan , Wang Qi , Dai Wei
Published: December 2024

Clausena lansium (Lour.) Skeels, commonly known as Wampee, are valued for their edible and medicinal qualities, yet their pericarp and seeds are often discarded, resulting in wasted resources. This study investigates the anti-tumor potential of these by-products, focusing on their chemical composition and underlying mechanisms of action. A combination of metabolomics, network pharmacology, molecular docking, and experimental validation was employed in our study. Cytotoxicity screening demonstrated that the pericarp extract exhibited notable anti-tumor effects against MDA-MB-231 breast cancer cells, while the seed extract showed no similar activity. Chemical profiling identified 122 compounds in the pericarp and seeds, with only 26.23% overlap, suggesting that distinct compounds may drive the pericarp’s anti-tumor activity. Network pharmacology and molecular docking analyses identified PTGER3, DRD2, and ADORA2A as key targets, with several alkaloids, flavonoids, coumarins, and sesquiterpenes exhibiting strong binding affinities to these proteins. Western blot analysis further validated that the pericarp extract upregulated DRD2 and downregulated ADORA2A, indicating a possible mechanism for its anticancer effects. These findings suggest that Wampee pericarp holds promise as a source of active compounds with therapeutic potential for breast cancer, with implications for its use in the food and pharmaceutical industries.
Citrus bergamia Extract, a Natural Approach for Cholesterol and Lipid Metabolism Management: A Randomized, Double-Blind Placebo-Controlled Clinical Trial
Authors: Spina Amelia , Amone Fabio , Zaccaria Vincenzo , Insolia Violetta , Perri Anna , Lofaro Danilo , Puoci Francesco , Nobile Vincenzo
Published: December 2024

Strategies for controlling cholesterol and lipid metabolism, including the use of food supplements, are part of the non-pharmacological intervention to ameliorate cardiovascular health. To demonstrate the efficacy of a standardized flavonoids (150 mg/day) extract from Citrus bergamia on cholesterol and lipid management, a placebo-controlled clinical trial on 64 subjects with high cholesterol was carried out. The total study duration was 4 months, with intermediate checkpoints at 1-month intervals. Low-density lipoprotein (LDL-C), high-density lipoprotein (HDL-C) cholesterol, total cholesterol (TC) levels, oxidized low-density lipoprotein (ox-LDL), and paraoxonase activity (PON1) were measured as primary endpoints (efficacy evaluation), while weight, blood pressure, hepatic and renal function blood markers were measured as secondary endpoints (safety evaluation). After 4 months, both TC and LDL-C significantly decreased by 8.8% and 11.5%, respectively, along with a 5.5% increase in HDL-C which was trending towards significance. In addition, ox-LDL was significantly reduced by 2.0%, while PON1 was significantly increased by 6.5%. The secondary endpoints were not changed during the study, demonstrating a good tolerability of the test product. Our findings demonstrate the efficacy of the extract as a natural approach for cholesterol and lipid metabolism management.
A Black Sticky Rice-Derived Functional Ingredient Improves Anxiety, Depression, and Stress Perception in Adult Volunteers
Authors: Natthee Pattamaporn , Wattanathorn Jintanaporn , Thukham-mee Wipawee , Paholpak Pongsatorn , Rangseekajee Poonsri , Piyavhatkul Nawanant , Wattanathorn Suphayanakorn , Muchimapura Supaporn , Tong-Un Terdthai
Published: December 2024

We hypothesized that consumption of a diet containing the functional ingredient from black sticky rice, which is rich in anthocyanin, over a five-day period would improve anxiety, depression, and stress perception in adult volunteers based on the benefits of this compound. In this study, a total of 46 male and female adult volunteers with mild and moderate stress level were assigned to groups consuming a breakfast meal containing an anthocyanin-enriched functional ingredient at doses of 2 and 4 g per day for 5 days. The volunteers consumed three meals with a low DII but high DAQ-S, and the total calories consumed during the study period was 2000 kcal/day. Mental well-being, including depression, anxiety, and stress, together with AChE, MAO, Nrf2, 8OHdG, MDA, and the density of Lactobacillus and Bifidobacterium spp., were assessed at baseline and at the end of the study. Safety parameters were also examined. A diet containing both doses of the anthocyanin-enriched functional ingredient with a low DII but high DAQ-S was found to improve anxiety, depression, and stress, with changes in 8-OHdG and IL-6 levels. No other changes and toxicity-related parameters were observed. Our results show that the novel functional ingredient can improve anxiety, depression, and stress perception partly by decreasing oxidative stress and inflammation; however, randomized, double-blind, placebo-controlled studies with a larger sample size should be performed to confirm this benefit.
Meat and Meat Products: Explorations of Microbiota, Flavor, and Quality
Authors: Wang Huiping , Kong Baohua , Chen Qian
Published: December 2024

Meat and meat products have a very important position in the human diet, and are an important source of essential nutrients such as protein, fat, minerals, and vitamins [...]
Determination of Geographical Origin of Southern Shaanxi Congou Black Teas Using Sensory Analysis Combined with Gas Chromatography–Ion Mobility Spectrometry
Authors: Yan Fei , Chen Xiaohua , Qu Dong , Huang Wei , He Lijuan , Wan Tian , Zhang Lijun , Wang Qi , Hu Ching Yuan
Published: December 2024

Southern Shaanxi is one of China’s high-quality congou black tea production areas. However, the differences in geography, cultivation, and management techniques and production processes lead to uneven qualities of southern Shaanxi congou black tea in different production areas. This study used sensory analysis combined with gas chromatography–ion mobility spectrometry (GC-IMS) to determine southern Shaanxi congou black teas’ geographical origin and volatile fingerprints to prevent economic losses caused by fraudulent labeling. A total of 61 volatile compounds were identified and quantified by GC-IMS. Three main aroma types were found by sensory analysis coupled with significant difference analysis, and a clear correlation between volatile compounds, aroma type, and geographical origin was found by sensory and gallery plot analysis. The black tea with a green/grassy-roast aroma type was mainly distributed in production areas with an altitude of 400–800 m and 1-pentanol, cyclohexanone, 1-penten-3-one, 2-heptanone, dihydroactinidiolide and butyrolactone were the key aroma markers. The black teas produced in production areas with an altitude of 800–1000 m mainly presented strong honey and caramel-like aromas, and sotolone, furaneol, and phenylacetaldehyde played an important role. These results will be helpful for discriminating black tea from different tea production areas in southern Shaanxi.
Energy Evolution and Fractal Characteristics of Sandstones Under True Triaxial Cyclic Loading and Unloading
Authors: Zhang Qihang , Meng Xiangrui , Zhao Guangming
Published: December 2024

To study the fractal characteristics and energy evolution of sandstones under true three-dimensional stress states, a true triaxial compression test and a cyclic loading and unloading test of sandstone specimens under different loads were carried out using a self-developed true triaxial disturbance testing system. Based on the evolution law of true triaxial cyclic loading and unloading stress–strain, the types of loading and unloading in the cyclic loading and unloading test were delineated, and the reasons for the change in peak maximum principal stress intensity under different paths were analyzed. By analyzing the crushing characteristics of rock samples under different paths, it was found that the staged cyclic loading and unloading caused the greatest damage to the rock mass, while the equal-amplitude and unequal-lower-limit staged loading and unloading caused the least damage to the rock mass. Based on fractal theory, it was found that the rock samples under path V had the highest fractal dimension D. The elastic energy density, dissipated energy density, and input energy density of true triaxial cyclic loading and unloading under different paths were calculated by graphical area integration and superposition methods, respectively, to analyze the evolution of the three with the increase in the loading and unloading cycles and the energy distribution during the loading and unloading process. True triaxial cyclic loading and unloading tests revealed a linear relationship between the elastic energy density and total input energy density of the rock mass, and the energy storage coefficient exceeded 0.5, regardless of the loading path.