bluuebunny/crossref_metadata_2025 huggingface dataset:
Internet of Things-Driven Precision in Fish Farming: A Deep Dive into Automated Temperature, Oxygen, and pH Regulation
Authors: Nayoun Md. Naymul Islam , Hossain Syed Akhter , Rezaul Karim Mohammed , Siddiquee Kazy Noor e Alam , Islam Md. Shabiul , Jannat Tajnuva
Published: October 2024

The research introduces a revolutionary Internet of Things (IoT)-based system for fish farming, designed to significantly enhance efficiency and cost-effectiveness. By integrating the NodeMcu12E ESP8266 microcontroller, this system automates the management of critical water quality parameters such as pH, temperature, and oxygen levels, essential for fostering optimal fish growth conditions and minimizing mortality rates. The core of this innovation lies in its intelligent monitoring and control mechanism, which not only supports accelerated fish development but also ensures the robustness of the farming process through automated adjustments whenever the monitored parameters deviate from desired thresholds. This smart fish farming solution features an Arduino IoT cloud-based framework, offering a user-friendly web interface that enables fish farmers to remotely monitor and manage their operations from any global location. This aspect of the system emphasizes the importance of efficient information management and the transformation of sensor data into actionable insights, thereby reducing the need for constant human oversight and significantly increasing operational reliability. The autonomous functionality of the system is a key highlight, designed to persist in adjusting the environmental conditions within the fish farm until the optimal parameters are restored. This capability greatly diminishes the risks associated with manual monitoring and adjustments, allowing even those with limited expertise in aquaculture to achieve high levels of production efficiency and sustainability. By leveraging data-driven technologies and IoT innovations, this study not only addresses the immediate needs of the fish farming industry but also contributes to solving the broader global challenge of protein production. It presents a scalable and accessible approach to modern aquaculture, empowering stakeholders to maximize output and minimize risks associated with fish farming, thereby paving the way for a more sustainable and efficient future in the global food supply.
Pulsed Wave Mode of Fractional Radiofrequency Microneedling as a New Advance in the Treatment of Inflammatory Acne Vulgaris
Authors: Al-Bakaa Muhammad K. , Khalaf Fatimah K.
Published: October 2024

Inflammatory acne vulgaris (IAV) is a common skin condition characterized by the presence of reddish, inflamed, and painful lesions on the skin. IAV can drastically affect individuals, specifically their self-esteem, psychological health, and quality of their life in general. Despite new advances in the field, traditional treatment modalities withstand many challenges. Hence, in the current study, we sought to assess the efficacy and safety of a new pulsed wave mode of the fractional microneedling radiofrequency device in the treatment of IAV. This advanced technique employs insulated microneedles to administer energy to the deep dermis without causing damage to the epidermis. Eighty patients (40 males, 40 females, age 21 ± 3, Fitzpatrick skin type III and IV), with acne severity ranging from moderate to severe, were employed in this trial. They were randomly assigned into two groups, 40 patients each. The treated group (A) underwent four sessions of fractionated microneedle RF, 1.5-month apart, whereas group B was designated as the control group that received placebo treatment. Six months following the last session, the degree of improvement assessed by the quantity of IAV lesions and the overall skin appearance in terms of facial pores, sebum excretion, scar, skin tone, and texture. The RF-treated group showed significant improvement compared to the control group after the follow-up period (p-value = 0.0071). Regarding safety, very mild adverse effects were reported, such as discomfort during the session, pinpoint hemorrhage, and erythema, with no major side effects such as burns, scarring, hyperpigmentation, or hypopigmentation were reported. Thus, our data suggest a potential role of the fractional microneedling radiofrequency device in IAV treatment that is both effective and safe.
Acoustic and Clinical Data Analysis of Vocal Recordings: Pandemic Insights and Lessons
Authors: Carreiro-Martins Pedro , Paixão Paulo , Caires Iolanda , Matias Pedro , Gamboa Hugo , Soares Filipe , Gomez Pedro , Sousa Joana , Neuparth Nuno
Published: October 2024

Background/Objectives: The interest in processing human speech and other human-generated audio signals as a diagnostic tool has increased due to the COVID-19 pandemic. The project OSCAR (vOice Screening of CoronA viRus) aimed to develop an algorithm to screen for COVID-19 using a dataset of Portuguese participants with voice recordings and clinical data. Methods: This cross-sectional study aimed to characterise the pattern of sounds produced by the vocal apparatus in patients with SARS-CoV-2 infection documented by a positive RT-PCR test, and to develop and validate a screening algorithm. In Phase II, the algorithm developed in Phase I was tested in a real-world setting. Results: In Phase I, after filtering, the training group consisted of 166 subjects who were effectively available to train the classification model (34.3% SARS-CoV-2 positive/65.7% SARS-CoV-2 negative). Phase II enrolled 58 participants (69.0% SARS-CoV-2 positive/31.0% SARS-CoV-2 negative). The final model achieved a sensitivity of 85%, a specificity of 88.9%, and an F1-score of 84.7%, suggesting voice screening algorithms as an attractive strategy for COVID-19 diagnosis. Conclusions: Our findings highlight the potential of a voice-based detection strategy as an alternative method for respiratory tract screening.
The Unexpected Detection of Esophageal Varices Caused by Liver Cirrhosis in a 47-Year-Old Man Treated with a Growth Hormone in Childhood
Authors: Arisaka Osamu , Koyama Satomi , Imataka George , Naganuma Junko , Arisaka Takahiro , Akatsuka Sei
Published: October 2024

Background: We report a rare case highlighting the progression of liver disease in a male patient with idiopathic childhood-onset growth hormone (GH) deficiency. Case presentation: The patient was diagnosed with hypopituitarism at six years old and was treated with thyroxine therapy and GH for his short stature, with testosterone added at the age of 15. GH therapy was discontinued when the patient was 18 years old, but thyroid and testosterone treatments continued. The patient had been taking medication for hyperlipidemia until the age of 30 and was noted to have impaired glucose tolerance at the age of 40, but HbA1c levels remained normal. At the age of 47, esophageal varices were incidentally discovered via endoscopy, revealing liver cirrhosis. Laboratory tests showed liver dysfunction and abnormal lipid levels, and hepatitis viral markers were absent. The patient had no history of drinking alcohol or smoking, and no family history of diabetes. Results: Ultimately, this case demonstrates that metabolic dysfunction-associated steatotic liver disease (MASLD/metabolic dysfunction-associated steatohepatitis (MASH)) is under-recognized in GH deficiency cases and can progress to liver cirrhosis. Conclusions: Therefore, careful evaluation of MASLD/MASH in childhood-onset GH deficiency is necessary, and GH replacement therapy should continue into adulthood, if possible.
The Effect of Larger Orthodontic Forces and Movement Types over a Dental Pulp and Neuro-Vascular Bundle of Lower Premolars in Intact Periodontium—A Numerical Analysis
Authors: Moga Radu-Andrei , Olteanu Cristian Doru , Delean Ada Gabriela
Published: October 2024

Background/Objectives: This numerical analysis of stress distribution in the dental pulp and neuro-vascular bundle (NVB) of lower premolars assessed the ischemic and degenerative–resorptive risks generated by 2 and 4 N during orthodontic movements (rotation, translation, tipping, intrusion and extrusion) in intact periodontium. Methods: The numerical analysis was performed on nine intact periodontium 3D models of the second lower premolar of nine patients totaling 90 simulations. Results: In intact periodontium, both forces displayed a similar stress distribution for all five orthodontic movements but different amounts of stress (a doubling for 4 N when compared with 2 N), with the highest values displayed in NVB. In intact periodontium, 2 N and 4 N induced stresses lower than the maximum hydrostatic pressure (MHP) with no ischemic risks for healthy intact teeth. The rotation was seen as the most stressful movement, closely followed by intrusion and extrusion. Translation was quantitatively seen as the least stressful when compared with other movements. Conclusions: Larger orthodontic forces of 2 N and 4 N are safe (with any expected ischemic or resorptive risks) for the dental pulp and NVB of healthy intact teeth and in intact periodontium. Nevertheless, rotation and translation movements can induce localized circulatory disturbances in coronal pulp (i.e., vestibular and proximal sides) generating ischemic and resorptive risks on previously treated teeth (i.e., direct and indirect dental pulp capping). The intrusion and extrusion movements, due to the higher NVB-induced deformation when compared with the other three movements, could trigger circulatory disturbances followed by ischemia on previously traumatized teeth (i.e., occlusal trauma).
Drone Insights: Unveiling Beach Usage through AI-Powered People Counting
Authors: Herrera César , Connolly Rod M. , Rasmussen Jasmine A. , McNamara Gerrard , Murray Thomas P. , Lopez-Marcano Sebastian , Moore Matthew , Campbell Max D. , Alvarez Fernando
Published: October 2024

Ocean beaches are a major recreational attraction in many coastal cities, requiring accurate visitor counts for infrastructure planning and value estimation. We developed a novel method to assess beach usage on the Gold Coast, Australia, using 507 drone surveys across 24 beaches. The surveys covered 30 km of coastline, accounting for different seasons, times of day, and environmental conditions. Two AI models were employed: one for counting people on land and in water (91–95% accuracy), and another for identifying usage types (85–92% accuracy). Using drone data, we estimated annual beach usage at 34 million people in 2022/23, with 55% on land and 45% in water—approximately double the most recent estimate from lifeguard counts, which are spatially limited and prone to human error. When applying similar restrictions as lifeguard surveys, drone data estimated 15 million visits, aligning closely with lifeguard counts (within 9%). Temporal (time of day, day of the week, season) and spatial (beach location) factors were the strongest predictors of beach usage, with additional patterns explained by weather variables. Our method, combining drones with AI, enhances the coverage, accuracy, and granularity of beach monitoring, offering a scalable, cost-effective solution for long-term usage assessment.
Income Distribution, Inequality and Poverty: Evidence, Explanations and Policies
Authors: Clementi Fabio
Published: October 2024

In recent years, there has been an increasing focus on the complex challenges posed by income inequality and poverty, both in developed and developing nations [...]
Life Skills in Compulsory Education: A Systematic Scoping Review
Authors: Hvalby Lone , Guldbrandsen Astrid , Fandrem Hildegunn
Published: October 2024

The significance of life skills within educational settings has grown; however, there remains a gap regarding a comprehensive understanding of the overarching concept. This systematic scoping review addresses that need, with the aim to identify and map empirical research published between 2013 and 2023 focused on life skills in compulsory education (grade 1–10). In addition to mapping the studies according to their characteristics, how life skills are defined is also examined, with a specific focus on collectivistic and individualistic perspectives. Through a rigorous search process, 50 studies were identified. The studies are mainly concerned with evaluating the efficacy of life skills programs or interventions for adolescents. They define life skills by both the type of skill and what it achieves. Key trends include an emphasis on an individualistic understanding of the term, lacking collectivistic perspectives. The implications focus on life skills education connected to lifelong learning, Bildung, and holistic growth from a collectivistic perspective, suggesting that future research could include life skills education for younger children for more sustainable effects favorable for desired societal outcomes.
Magnetic Railway Sleeper Detector
Authors: Heindler Lukas , Hüttmayr Harald , Thurner Thomas , Zagar Bernhard
Published: October 2024

In an ever expanding railway network all around the world, the need for track maintenance grows steadily. Traditionally, one major part of track maintenance is ramming large vibrating steel picks into the gravel between and under railway sleepers to compress the gravel and generate a safe substructure. Even today, maintenance personnel still have to manually locate the sleepers if they cannot be detected by computer vision systems or visually by the operator. Here we developed a first of its kind magnetic sleeper detector, even able to find sleepers, buried in gravel, undetectable by vision based systems. Our approach of magnetic detection is based on a DC magnetic field excitation and a detector moving with respect to the rail system, including the sleepers and fasteners for mounting the rails. Due to railway application constraints a large air gap between the sensor and the sleeper structure is required, which significantly complicates the magnetic sensing task for robust sleeper detection. The design and optimization of the magnetic circuit was based on extensive 3D simulation studies to ensure highest possible variation in magnetic flux density at the sensor locations for absence and presence of a sleeper. Furthermore, a low noise and high sensitivity electronic circuit has been realized to cope with sensor signal offsets from unknown or changing sensor orientations with respect to the earth’s magnetic field, or magnetic interferences from other trains potentially passing by during active measurements. Since we only want to detect sleepers in close vicinity of the moving sensor system, digital signal processing of the acquired signals can easily compensate for disturbing slowly changing or static field components within real world application scenarios. We demonstrate that magnetic detection of even buried sleepers on railway tracks is possible for distances of up to 172 mm between the sensor and the sleeper. This enables an even higher level of railway maintenance automation previously impossible in certain scenarios.
Statistical Law between Areas and Perimeters Created by a Moving Trajectory
Authors: Ishikawa Atushi , Fujimoto Shouji , Mizuno Takayuki , Tanaka Yoshimi
Published: October 2024

Based on our interest in properties of human movement, we investigated Japanese GPS data, and arrived at the following three observations: (1) there is a strong correlation between the area of polygons created by human movement trajectories and their perimeters; (2) short-distance movement trajectories less than 5 km tend to enclose a large area like a circle; and (3) long-distance movement trajectories over 5 km tend to be straight. We also clarified the following four observations on individual attributes and external factors related to long-distance movements: (1) women tend to travel more linearly than men; (2) linearity is stronger on weekends and national holidays in areas with a large theme park; (3) linearity is weaker on weekends and holidays in areas with many historical tourist attractions; and (4) these variations are created by people visiting such areas. These properties should be incorporated when modeling the movement trajectories of humans.
Comparison of the Impacts of Background Distortion with Even and Odd Orders in the Supraharmonic Range on Grid-Connected Converters
Authors: Aboutaleb Abdellatif M. , Osheba Marwa S. , Desmet Jan , Knockaert Jos
Published: October 2024

In this paper, a comparison of the emissions of grid-connected converters under grid distortion in the supraharmonic range is performed. The investigated supraharmonic grid distortion is divided into two types, namely odd-integer and even-integer multiples of the grid frequency. It is found that the first distortion type does not affect the emissions of the grid-connected converters, while the second distortion is responsible for the 2N-harmonic emissions that appear in the frequency spectra of the grid-connected converters, which, in turn, interact with the supraharmonic primary emissions of these converters, resulting in additional supraharmonic emissions. To explain this behavior, a mathematical analysis is provided for two types of grid-connected converters with an inverter interface and with a diode bridge rectifier interface. Simulations and experimental studies are performed to verify the main findings of the mathematical analysis.
MWRD (Mamba Wavelet Reverse Diffusion)—An Efficient Fundus Image Enhancement Network Based on an Improved State-Space Model
Authors: Chen Tianle , Li Yu , Zhang Xuedong
Published: October 2024

This study introduces an efficient fundus image enhancement framework based on an improved Mamba model and the Denoising Diffusion Probabilistic Model (DDPM). By integrating wavelet transform for local feature extraction and applying a reverse diffusion process, this approach significantly improves the effectiveness and efficiency of enhancing low-quality fundus images. The model achieves high-precision enhancement of retinal vessel details while substantially reducing the number of parameters. Comprehensive tests on publicly available datasets show that the suggested approach surpasses various advanced low-light image enhancement methods in both quantitative and qualitative assessments.
Analysis of Optimal Diversity Combining with Imperfect Channel State Information for Cooperative Jamming-Aided Internet of Things Security
Authors: Mao Yu , Li Weishi , Wang Wenjing , Zhao Hongzhi , Shao Shihai
Published: October 2024

Cooperative jamming (CJ) combined with single-input multiple-output (SIMO) technology can effectively improve the security and reliability of Internet of Things (IoT) systems. However, imperfect main channel state information (CSI) leads to incomplete CJ cancellation, which degrades the performance after combining. In this paper, by considering channel estimation errors and residual CJ at each receiving antenna, the residual CJ power after jamming suppression is analyzed, and the optimal combining coefficient for maximizing the signal-to-jamming-noise ratio (SJNR) is derived. The output SJNR of optimal diversity combining is given, and the achievable secrecy rate is analyzed on this basis. The theoretical and simulation results verify the combined effect of channel estimation errors and residual CJ on the combining performance. Moreover, it is worth noting that the combining performance is closely related to the spatial correlation of residual CJ.
Rethinking the Non-Maximum Suppression Step in 3D Object Detection from a Bird’s-Eye View
Authors: Li Bohao , Song Shaojing , Ai Luxia
Published: October 2024

In camera-based bird’s-eye view (BEV) 3D object detection, non-maximum suppression (NMS) plays a crucial role. However, traditional NMS methods become ineffective in BEV scenarios where the predicted bounding boxes of small object instances often have no overlapping areas. To address this issue, this paper proposes a BEV intersection over union (IoU) computation method based on relative position and absolute spatial information, referred to as B-IoU. Additionally, a BEV circular search method, called B-Grouping, is introduced to handle prediction boxes of varying scales. Utilizing these two methods, a novel NMS strategy called BEV-NMS is developed to handle the complex prediction boxes in BEV perspectives. This BEV-NMS strategy is implemented in several existing algorithms. Based on the results from the nuScenes validation set, there was an average increase of 7.9% in mAP when compared to the strategy without NMS. The NDS also showed an average increase of 7.9% under the same comparison. Furthermore, compared to the Scale-NMS strategy, the mAP increased by an average of 3.4%, and the NDS saw an average improvement of 3.1%.
ResNet Modeling for 12 nm FinFET Devices to Enhance DTCO Efficiency
Authors: Huang Yiming , Li Bin , Wu Zhaohui , Liu Wenchao
Published: October 2024

In this paper, a deep learning-based device modeling framework for design-technology co-optimization (DTCO) is proposed. A ResNet surrogate model is utilized as an alternative to traditional compact models, demonstrating high accuracy in both single-task (I–V or C–V) and multi-task (I–V and C–V) device modeling. Moreover, transfer learning is applied to the ResNet model, using the BSIM-CMG compact model for a 12 nm FinFET SPICE model as the pre-trained source. Through this approach, superior modeling accuracy and faster training speed are achieved compared to a ResNet surrogate model initialized with random weights, thereby meeting the rapid and efficient demands of the DTCO process. The effectiveness of the ResNet surrogate model in circuit simulation for 12 nm FinFET devices is demonstrated.
Optimal Energy Storage Allocation for Combined Wind-PV-EVs-ES System Based on Improved Triangulation Topology Aggregation Optimizer
Authors: Fan Chuanxi , Wang Haizheng , Zhang Jinhua , Cheng Peng , Bian Yuhua
Published: October 2024

To determine the ES allocation based on a specific number of EVs connected to a combined WPESS, this paper develops an ESS allocation model that considers the impact of EV charging behavior on LSD, ES allocation cost, new energy utilization rate, and self-power rate. First, several scenarios are generated using Monte Carlo sampling (MCS), and a typical day is selected through Backward Reduction (BR). Next, the Monte Carlo method is employed to generate conventional EV charging curves and optimize EV charging behavior by considering LSD and user charging costs. Subsequently, an ES capacity allocation model is developed, considering system costs, new energy utilization rate, and self-power rate. Finally, an improved triangulation topology aggregation optimizer (TTAO) is proposed, incorporating the logistic map, Golden Sine Algorithm (Gold-SA) strategy, and lens inverse imaging learning strategy. These enhancements improve the algorithm’s ability to identify global optimal solutions and facilitate its escape from local optima, significantly enhancing the optimization effectiveness of TTAO. The analysis of the calculation example indicates that after optimizing the charging behavior of EVs, the average daily cost is reduced by 204.94, the self-power rate increases by 2.25%, and the utilization rate of new energy sources rises by 2.50%, all while maintaining the same ES capacity.
Towards an End-to-End Personal Fine-Tuning Framework for AI Value Alignment
Authors: Watson Eleanor , Viana Thiago , Zhang Shujun , Sturgeon Benjamin , Petersson Lukas
Published: October 2024

This study introduces a novel architecture for value, preference, and boundary alignment in large language models (LLMs) and generative AI systems, accompanied by an experimental implementation. It addresses the limitations in AI model trustworthiness stemming from insufficient comprehension of personal context, preferences, and cultural diversity, which can lead to biases and safety risks. Using an inductive, qualitative research approach, we propose a framework for personalizing AI models to improve model alignment through additional context and boundaries set by users. Our framework incorporates user-friendly tools for identification, annotation, and simulation across diverse contexts, utilizing prompt-driven semantic segmentation and automatic labeling. It aims to streamline scenario generation and personalization processes while providing accessible annotation tools. The study examines various components of this framework, including user interfaces, underlying tools, and system mechanics. We present a pilot study that demonstrates the framework’s ability to reduce the complexity of value elicitation and personalization in LLMs. Our experimental setup involves a prototype implementation of key framework modules, including a value elicitation interface and a fine-tuning mechanism for language models. The primary goal is to create a token-based system that allows users to easily impart their values and preferences to AI systems, enhancing model personalization and alignment. This research contributes to the democratization of AI model fine-tuning and dataset generation, advancing efforts in AI value alignment. By focusing on practical implementation and user interaction, our study bridges the gap between theoretical alignment approaches and real-world applications in AI systems.
Photothermal Conversion Performance of Fe3O4/ATO Hybrid Nanofluid for Direct Absorption Solar Collector
Authors: Ham Jeonggyun , Kim Hyemin , Cho Honghyun
Published: October 2024

In order to enhance the efficiency of direct absorption solar collectors, this study carried out an experimental analysis about the optical and photothermal conversion performance of Fe3O4, ATO (Antimony-doped tin oxide), and Fe3O4/ATO nanofluids with a total concentration of 0.1 wt%. According to the results of the experiments, Fe3O4 nanofluid outperforms ATO nanofluid in terms of optical absorption; nevertheless, at wavelengths shorter than 600 nm, it also shows significant scattering reflection. The solar-weighted absorption coefficient of Fe3O4/ATO nanofluid rose from 0.863 (mFe3O4/mTotal = 0.2) to 0.932 (mFe3O4/mTotal = 0.8) when the optical path length increased from 0.01 m to 0.06 m. Moreover, the Fe3O4/ATO hybrid nanofluid achieved a photothermal conversion efficiency of 0.932 when the mass ratio of Fe3O4 to total mass was 0.2, surpassing the efficiencies of 0.892 and 0.898 recorded for 0.1 wt% ATO and Fe3O4 nanofluids, respectively. When present together, the opposing optical characteristics of Fe3O4 and ATO boost photothermal conversion performance, which is anticipated to raise the efficiency of direct absorption solar collectors.
Two-Stage Optimization Scheduling of Integrated Energy Systems Considering Demand Side Response
Authors: Zeng Shuang , Zhang Heng , Wang Fang , Zhang Baoqun , Ke Qiwen , Liu Chang
Published: October 2024

This study proposes a two-level optimization scheduling method for multi-region integrated energy systems (IESs) that considers dynamic time intervals within the day, addressing the diverse energy characteristics of electricity, heat, and cooling. The day-ahead scheduling aims to minimize daily operating costs by optimally regulating controllable elements. For intra-day scheduling, a predictive control-based dynamic rolling optimization model is utilized, with the upper-level model handling slower thermal energy fluctuations and the lower-level model managing faster electrical energy fluctuations. Building on the day-ahead plan, different time intervals are used for fast and slow layers. The slow layer establishes a decision index for command cycle intervals, dynamically adjusting based on ultra-short-term forecasts and incremental balance corrections. Case studies demonstrate that this method effectively leverages energy network characteristics, optimizes scheduling intervals, reduces adjustment costs, and enhances system performance, achieving coordinated operation of the IES network and multi-energy equipment.
Differences in the Genesis and Sources of Hydrocarbon Gas Fluid from the Eastern and Western Kuqa Depression
Authors: Yang Xianzhang , He Taohua , Wang Bin , Zhou Lu , Zhang Ke , Zhao Ya , Zeng Qianghao , Huang Yahao , He Jiayi , Wen Zhigang
Published: October 2024

The Kuqa Depression is rich in oil and gas resources and serves as a key production area in the Tarim Basin. However, controversy persists over the genesis of oil and gas in the various structural zones of the Kuqa Depression. This study employs natural gas composition analysis, gas carbon isotope analysis and gold pipe thermal simulation experiments, to comprehensively analyze the differences in the genesis and sources of hydrocarbon gas fluid from the eastern and western Kuqa Depression. The results show that the Kuqa Depression is dominated by alkane gas, with an average gas drying coefficient of 95.6, with nitrogen and carbon dioxide as the primary non-hydrocarbon gases. The average of δ13C1, δ13C2 and δ13C3 values in natural gas are −27.70‰, −20.43‰ and −21.75‰, respectively. Based on comprehensive natural gas geochemical maps, the CO2 in the natural gas from the Tudong and Dabei areas, as well as the KT-1 well of the Kuqa Depression, is thought to be of organic origin. Additionally, natural gas formation in the Tudong area is relatively simple, consisting entirely of thermally generated coal gas derived from the initial cracking of kerogen. The natural gas in the KT-1 well and the Dabei area are mixed gasses, formed by the initial cracking of kerogen from highly evolved lacustrine and coal-bearing source rocks, exhibiting characteristics resembling those of crude oil cracking gas. The methane (CH4) content of natural gas in the Dabei area is high and the carbon isotopes are unusually heavy. Considering the regional geological background, potential source rock characteristics and geochemical features may be related to the large-scale invasion of dry gas contributed by CH4 from highly evolved, underlying coal-bearing source rocks. Consequently, the CH4 content in the mixed gas is generally high (Ln (C1/C2) can reach up to 5.38), while the relative content of heavy components is low, though remains relatively unchanged. Thus, the map of the relative content of heavy components still reflects the characteristics of the original gas genesis (initial cracking of kerogen). Mixed-source gas was analyzed using thermal simulation experiments and natural gas composition ratio diagrams. The contributions of natural gas from deep, highly evolved coal-bearing source rocks in the KT-1 well and the Dabei area accounted for more than 90% and approximately 60%, respectively. This analysis provides theoretical guidance for natural gas exploration in the research area.
Computing the Network’s Equilibrium Point at the Fault Clearing Instant in Transient Stability Studies
Authors: Pizano-Martínez Alejandro , Ramírez-Betancour Reymundo , Zamora-Cárdenas Enrique A. , Fuerte-Esquivel Claudio R.
Published: October 2024

This paper proposes an approach for computing the network’s equilibrium point related to the fault clearing time in transient stability studies. The computation of this point is not a trivial task, particularly when the algebraic network’s equations are expressed in the power balance form. A natural attempt to solve this problem is using Newton’s method. However, convergence issues are found because of the lack of a general strategy for initializing nodal voltages at the clearing time. This problem has not been widely discussed in the existing literature and, therefore, is comprehensively analyzed in this paper. Furthermore, the paper proposes the use of a network’s model based on current injections and an extended admittance matrix to overcome the problem. This model is efficiently solved via the fixed-point iteration method, which involves factorization of the extended admittance matrix into the product of a lower triangular matrix [L] and an upper triangular matrix [U]. This solution executes a just once and only forward–backward substitution during the iterative solution process. Case studies clearly demonstrate the proposal’s effectiveness in computing the equilibrium point in operating conditions where Newton’s method fails to converge.
ISOS-SAB DC/DC Converter for Large-Capacity Offshore Wind Turbine
Authors: Cai Xipeng , Liu Yixin , Zhu Yihua , Zhou Yanbing , Luo Chao , Liu Qihui
Published: October 2024

This study offers a modular isolated grid-connected DC/DC medium-voltage DC aggregation converter to support offshore full DC wind farms’ need for lightweight and highly efficient power aggregation and transmission. The converter can simultaneously have a smaller transformer size and lower switching frequency during operation through the dual-voltage stabilization three-loop control strategy and phase-shift modulation strategy, which greatly reduces the space occupied by the converter and lowers the switching loss, Additionally, the use of a two-level structure at a lower switching frequency has lower loss, which effectively reduces the cost of the power device compared with the commonly used three-level converter. The input series output series connection between the converter sub-modules effectively lowers the voltage stress on each power switching device and facilitates expansion into a multi-module structure, expanding its application in high-voltage and large-capacity environments. This study analyzes the two working modes of the DC/DC converter and its control approach, in addition to providing a detailed introduction to the application scenarios of this converter. Ultimately, the efficacy and practicability of the suggested topology and control scheme are confirmed by simulations and experiments.
The Effect of Air Humidity on the Performance of DC Link Capacitor Components
Authors: Sun Xiaowu , Qiao Ying , Li Yinda , Cao Chongfeng , Zhang Jian , Yu Cheng
Published: October 2024

DC link capacitors (DCLCs) are key devices in converters. The relative humidity affects the performance of the elements of a DCLC. Currently, there are relatively few studies on the effect of relative humidity on the electrical characteristics of the elements of DCLCs during the production process. This study describes the effects and the control of the relative humidity in the production process. For this purpose, a DCLC component withstand voltage test platform and a DCLC component aging test platform were established. The voltage withstand tests were conducted during different processes and at different relative humidities, and life aging tests were conducted at different relative humidities and different storage times. The results show that after the winding and metal-spraying processes, the voltage withstand levels of the components stored at 30% RH, 60% RH, and 80% RH were very close to that of the components at 3000 VDC; after the heat-setting process, the voltage withstand levels of the components stored at 30% RH, 60% RH, and 80% RH showed a decreasing tendency compared with the level of the components at 3000 VDC. Regarding the samples, after the heat-setting process, stored at 30% RH and 60% RH for 24 h, 96 h, 168 h, 240 h, and 336 h and 2000 h of the aging tests, the capacitance decreases monotonically as the storage time is increased but never exceeds 3%, and the capacitance change decreases as the relative humidity increases. This study can provide important guidance for the humidity control of various processes in the production of DCLCs.
Comprehensive Review of Biomass Pyrolysis: Conventional and Advanced Technologies, Reactor Designs, Product Compositions and Yields, and Techno-Economic Analysis
Authors: Jerzak Wojciech , Acha Esther , Li Bin
Published: October 2024

Pyrolysis is an environmentally friendly and efficient method for converting biomass into a wide range of products, including fuels, chemicals, fertilizers, catalysts, and sorption materials. This review confirms that scientific research on biomass pyrolysis has remained strong over the past 10 years. The authors examine the operating conditions of different types of pyrolysis, including slow, intermediate, fast, and flash, highlighting the distinct heating rates for each. Furthermore, biomass pyrolysis reactors are categorized into four groups, pneumatic bed reactors, gravity reactors, stationary bed reactors, and mechanical reactors, with a discussion on each type. The review then focuses on recent advancements in pyrolysis technologies that have improved efficiency, yield, and product quality, which, in turn, support sustainable energy production and effective waste management. The composition and yields of products from the different types of pyrolysis have been also reviewed. Finally, a techno-economic analysis has been conducted for both the pyrolysis of biomass alone and the co-pyrolysis of biomass with other raw materials.
Medium- and Long-Term Power System Planning Method Based on Source-Load Uncertainty Modeling
Authors: Yao Wenfeng , Huo Ziyu , Zou Jin , Wu Chen , Wang Jiayang , Wang Xiang , Lu Siyu , Xie Yigong , Zhuo Yingjun , Liang Jinbing , Huang Run , Cheng Ming , Lu Zongxiang
Published: October 2024

In order to consider the impact of source-load uncertainty on traditional power system planning methods, a medium- and long-term optimization planning method based on source-load uncertainty modeling and time-series production simulation is proposed. First, a new energy output probability model is developed using non-parametric kernel density estimation, and the spatial correlation of the new energy output is described using pair-copula theory to model the uncertainty analysis of the new energy output. Secondly, a large number of source-load scenarios are generated using the Markov chain Monte Carlo simulation method, and the optimal selection method for discrete state numbers is provided, and then the scenario reduction is carried out using the fast forward elimination technology. Finally, the typical time-series curves of the source-load uncertainty characteristics obtained are incorporated into the optimization planning method together with various flexible resources, such as the demand-side response and energy storage, and the rationality of the planning scheme is judged and optimized based on key indicators such as the cost, wind–light abandonment rate, and loss-of-load rate. Based on the above methods, this paper offers an example of the power supply planning scheme for a certain region in the next 30 years, providing effective guidance for the development of new energy in the region.
Assessing the Impact of Vertical Greenery Systems on the Thermal Performance of Walls in Mediterranean Climates
Authors: Nocera Francesco , Costanzo Vincenzo , Detommaso Maurizio , Evola Gianpiero
Published: October 2024

This study investigates the impact of vertical greenery systems (VGSs) applied to several typical wall configurations on indoor thermal conditions in a building module situated in the Mediterranean climate of Catania, Italy. By means of dynamic simulations in TRNSYS vers.18, the research compares the thermal behavior of walls made of either hollow clay blocks (Poroton) or lava stone blocks against a lightweight wall setup already in place at the University of Catania. The primary focus is on evaluating the VGSs’ capability of reducing peak inner surface temperatures and moderating heat flux fluctuations entering the building. The findings indicate that adding an outer vertical greenery layer to heavyweight walls can decrease the peak inner surface temperature by up to 1.0 °C compared to the same bare wall. However, the greenery’s positive impact is less pronounced than in the case of the lightweight wall. This research underscores the potential of green facades in enhancing the indoor thermal environment in buildings in regions with climates like the Mediterranean one, providing valuable insights for sustainable building design and urban planning.
Analysis of Spatiotemporal Predictions and Drivers of Carbon Storage in the Pearl River Delta Urban Agglomeration via the PLUS-InVEST-GeoDetector Model
Authors: Cai Jinghang , Chi Hui , Lu Nan , Bian Jin , Chen Hanqing , Yu Junkeng , Yang Suqin
Published: October 2024

Land use and land cover change (LUCC) significantly influences the dynamics of carbon storage in thin terrestrial ecosystems. Investigating the interplay between land use alterations and carbon sequestration is crucial for refining regional land use configurations, sustaining the regional carbon balance, and augmenting regional carbon storage. Using land use data from the Pearl River Delta Urban Agglomeration (PRDUA) from 2010 to 2020, this study employed PLUS-InVEST models to analyze the spatiotemporal dynamics of land use and carbon storage. Projections for the years 2030, 2040, and 2050 were performed under three distinct developmental scenarios, namely, natural development (ND), city priority development (CPD), and ecological protection development (EPD), to forecast changes in land use and carbon storage. The geographic detector model was leveraged to dissect the determinants of the spatial and temporal variability of carbon storage, offering pertinent recommendations. The results showed that (1) during 2010–2020, the carbon storage in the PRDUA showed a decreasing trend, with a total decrease of 9.52 × 106 Mg, and the spatial distribution of carbon density in the urban agglomeration was imbalanced and showed an overall trend in increasing from the center to the periphery. (2) Clear differences in carbon storage were observed among the three development scenarios of the PRDUA between 2030 and 2050. Only the EPD scenario achieved an increase in carbon storage of 1.10 × 106 Mg, and it was the scenario with the greatest potential for carbon sequestration. (3) Among the drivers of the evolution of spatial land use patterns, population, the normalized difference vegetation index (NDVI), and distance to the railway had the greatest influence on LUCC. (4) The annual average temperature, annual average rainfall, and GDP exerted a significant influence on the spatiotemporal dynamics of carbon storage in the PRDUA, and the interactions between the 15 drivers and changes in carbon storage predominantly manifested as nonlinear and double-factor enhancements. The results provide a theoretical basis for future spatial planning and achieving carbon neutrality in the PRDUA.
Forecasting Motor Vehicle Ownership and Energy Demand Considering Electric Vehicle Penetration
Authors: Mao Ning , Ma Jianbing , Chen Yongzhi , Xie Jinrui , Yu Qi , Liu Jie
Published: October 2024

Given the increasing environmental concerns and energy consumption, the transformation of the new energy vehicle industry is a key link in the innovation of the energy structure. The shift from traditional fossil fuels to clean energy encompasses various dimensions such as technological innovation, policy support, infrastructure development, and changes in consumer preferences. Predicting the future ownership of electric vehicles (EVs) and then estimating the energy demand for transportation is a pressing issue in the field of new energy. This study starts from dimensions such as cost, technology, environment, and consumer preferences, deeply explores the influencing factors on the ownership of EVs, analyzes the mechanisms of various factors on the development of EVs, establishes a predictive model for the ownership of motor vehicles considering the penetration of electric vehicles based on system dynamics, and then simulates the future annual trends in EV and conventional vehicle (CV) ownership under different scenarios based on the intensity of government funding. Using energy consumption formulas under different power modes, this study quantifies the electrification energy demand for transportation flows as fleet structure changes. The results indicate that under current policy implementation, the domestic ownership of EVs and CVs is projected to grow to 172.437 million and 433.362 million, respectively, by 2035, with the proportion of EV ownership in vehicles and energy consumption per thousand vehicles at 28.46% and 566,781 J·km−1, respectively. By increasing the technical and environmental factors by 40% and extending the preferential policies for purchasing new energy vehicles, domestic EV ownership is expected to increase to 201.276 million by 2035. This study provides data support for the government to formulate promotional policies and can also offer data support for the development of basic charging infrastructure.
Methodology for Testing Selected Parameters of Low-Current Vacuum Electric Arc
Authors: Lech Michał , Węgierek Paweł , Kozak Czesław , Pachulski Przemysław
Published: October 2024

This article presents the author’s methodology for testing selected parameters of a low-current vacuum arc, implemented using an innovative test stand based on a vacuum discharge chamber with a contact system mounted inside. In order to verify the validity of the adopted research methodology, as well as the correctness of the operation of the developed laboratory bench, measurements and calculations were made, among other things, of the energy and burning time of the vacuum arc, depending on selected factors, such as pressure and the delay time of the contact opening, calculated from the “passage through zero” of the sinusoid of the current flowing through the system. The tests were performed at 230 V and a current of 5 A for two pressure values: p1 = 1.00 × 105 Pa (atmospheric pressure) and p2 = 4.00 × 10−3 Pa (high vacuum environment). It was found that the vacuum insulation technique allows a significant reduction in the value of the arc energy and the burning time of the arc. It was also observed that in the case of a high vacuum environment, the ignition of the vacuum arc occurs after a time equal to about 3 ms from the “passage through zero” of the current flowing through the system. Below this value, the phenomenon did not occur. The results obtained provide an opportunity for the design and manufacturing of vacuum switchgear, where there is the prospect of reducing the negative effects associated with the arc burning process in the contact gap.
An Experimental Investigation of Pressure Drop in Two-Phase Flow during the Condensation of R410A within Parallel Microchannels
Authors: Huang Long , Guo Luyao , Liu Baoqing , Jin Zhijiang , Qian Jinyuan
Published: October 2024

In this study, the flow condensation of R-410A within 18 square microchannels arranged horizontally in parallel was experimentally investigated. All components of pressure drop, including expansion, contraction, deceleration, and friction, were quantified specifically for microchannels. The test conditions included saturation temperature, vapor quality, and mass flux, ranging from 18.86 to 24.22 bar, 0.09 to 0.92, and 200 to 445 kg/m2·s, respectively. The frictional pressure loss made up approximately 92.89% of the overall pressure reduction. The findings demonstrate that the pressure drop rises with higher mass flux and a lower saturation temperature. By comparing with correlations and semi-empirical models outlined in the literature across various scales, specimen types, and refrigerant media, correlations developed for two-phase adiabatic flows in multi-channel configurations can effectively predict the pressure drop in microchannel condensation processes. The model introduced by Sakamatapan and Wongwises demonstrated the highest predictive accuracy, with a mean absolute deviation of 8.4%.