bluuebunny/crossref_metadata_2025 huggingface dataset:
The Upemba National Park (Upper Congo Basin, DR Congo): An Updated Checklist Confirming Its Status as an African Fish Biodiversity Hotspot
Authors: Katemo Manda Bauchet , Snoeks Jos , Chocha Manda Auguste , Abwe Emmanuel , Mukweze Mulelenu Christian , Ilunga Kayaba Micheline Kasongo , Kiwele Mutambala Pacifique , Ngoy Kalumba Lewis , Vreven Emmanuel J. W. M. N.
Published: August 2023

An annotated checklist of the ichthyofauna of the Upemba National Park, draining part of the Upper Lualaba basin and situated in the southern part of the Democratic Republic of the Congo, is presented, based on a literature review, a re-examination of museum collections, and a study of recent collections (2012–2020). In total, 247 native and 1 introduced species, Heterotis niloticus, are reported. The native species belong to 78 genera, 26 families, and 15 orders. Of these, 45 species (18%) are endemic to the park, 35 species (14%) await formal description, and 5 taxa (2%) need further study to clarify their status. With 51 species, the Cyprinidae is by far the most species-rich family, followed by the Mormyridae (26), Mochokidae (26), Alestidae (18), Distichodontidae (18), Amphiliidae (17), and Cichlidae (16). The remaining families are represented by less than 15 species. Comments about the species distribution and the fish fauna shared with adjacent ecoregions are provided. Although the park provides some protection for the fish species living within its borders by limiting human access to the core zone, the annex and buffer zones are both subject to strong anthropogenic pressure. These observations underscore the need for the implementation and further elaboration of fish-related preservation guidelines and plans to enable better protection/conservation of the park’s ichthyofauna.
Phylogenetic Constraints and Ecological Implications of Gut Bacterial Communities in Necrophagous Flies
Authors: Park Woong-Bae , Park Jun-Kyu , Do Yuno
Published: August 2023

This study examines the gut bacterial communities of four necrophagous fly species: Lucilia illustris, L. caesar, Chrysomya megacephala, and C. pinguis. The gut bacterial communities exhibited significant variation across species, showcasing a diverse range of bacterial phyla, classes, and genera. Each species harbored a unique set of bacteria, yet there was considerable overlap in taxa among species. Species richness was comparable across all species. However, measures that account for both richness and evenness, such as the Shannon diversity index and the inverse Simpson’s diversity index, indicated significant differences between species, especially between L. illustris and C. pinguis. The functional profiles of the gut bacterial communities mainly centered on metabolic and environmental information processing functions, with no marked differences between species. While this study had limitations in data collection, it still revealed a significant correlation between the phylogenetic distances of some fly species and the distances of their gut bacterial communities. This supports the hypothesis that the gut microbiota is not random but is influenced by the host’s evolutionary history or seasons. We confirmed that an association between phylogeny and gut bacterial community structure, as determined through entanglement analysis, exists. The study focused on only five individuals from the four fly species sampled during spring and summer, which might affect the generalizability of the results. Future research would benefit from replicating this study with a larger sample size across various seasons to ensure the more widespread applicability of the findings.
Distribution of Human Papillomavirus Genotypes among the Women of South Andaman Island, India
Authors: Parvez Rehnuma , Vijayachari Paluru , Saha Mrinmoy Kumar , Biswas Lipika , Ramasamy Jawahar , Vins Alwin , Beniwal Nisha , Vasanthi S. , Ramadoss Sasikala , Kaur Harpreet , Nagarajan Muruganandam
Published: August 2023

Background: Human Papillomavirus (HPV) causes various types of cancer in both men and women. Woman with HPV infection has a risk of developing invasive cervical cancer. Globally, HPV 16 and 18 were predominant. This study aims to find the distribution of various HPV types in South Andaman. Methods: A cross-sectional study was conducted among women in South Andaman, where cervical scrapes were collected after collecting written informed consent. Detection of HPV genotypes was carried out by using a PCR assay. Further, sequencing analysis was performed using MEGA11 to identify various genotypes in this territory. Result: Of these 1000 samples, 32 were positive for HR-HPV 16, and four were positive for HR-HPV 18. Fifteen HPV genotypes were detected using molecular evolutionary analysis. Six cases were identified with multiple genotypes. The most prevalent genotype is HPV 16 which belongs to Lineage-A and sub-lineage A2. HPV 18 identified in South Andaman belonged to the lineage A1 to A5. Discussion: Various HPV types were identified among women in South Andaman. Global burden of cervical cancer associated with various HPV sub-lineages. HPV-16 A1 sub-lineage was globally widespread, whereas sub-lineages A1, A2 and D1 prevailed in South Andaman. Conclusions: HR-HPV identified in this study enlightens the importance of HPV vaccination among women in remote places. These findings will help to strengthen public health awareness programs and prevention strategies for women in remote areas.
Endoscopic and Histopathological Characteristics of Gastrointestinal Lymphoma: A Multicentric Study
Authors: Tran Quang Trung , Nguyen Duy Thinh , Nguyen-Tran Bao Song , Nguyen-Thanh Tung , Ngo Quy Tran , Tran Thi Nam Phuong , Le Vi , Dang-Cong Thuan
Published: August 2023

Background: Extranodal non-Hodgkin lymphoma (NHL) is more prevalent in the gastrointestinal (GI) tract than in other sites. This study aimed to determine the endoscopic characteristics of primary gastrointestinal non-Hodgkin lymphomas. Methods: We investigated 140 patients from three tertiary referral hospitals with primary malignant lymphoma of the gastrointestinal tract. Characteristics of the lesions were evaluated and analyzed using image-enhanced endoscopy, endoscopic ultrasound, and histopathology. Results: The median age was 60.5 (range: 11–99), and 59 (42.1%) were female. The most frequent complaint was abdominal pain (74.3%), followed by bloody feces (10%) and diarrhea (2.9%). B symptoms were observed in 15 (10.7%) patients. GI obstruction was the most common complication (10.0%), followed by hemorrhage (7.9%) and perforation (1.5%). Regarding endoscopic findings, the identified sites were the following: the stomach (61.4%), colon (10%), small intestine (10%), ileocecum (8.6%), rectum (6.4%), and duodenum (3.6%). Diffuse large B-cell lymphoma (DLBCL) and mucosa-associated lymphoid tissue (MALT) lymphoma are most prevalent in the stomach. Helicobacter pylori was identified in 46 cases (39.0%), with MALT lymphoma being the most infected subtype. Nearly all gastrointestinal non-Hodgkin lymphomas manifested as superficial type (25–59.6%) and ulcer type (15.6–50%) under endoscopy. We found that fungating type and protruding with ulcer type were more frequent types of aggressive lymphomas (diffuse large B-cell lymphoma, mantle cell lymphoma, and T-cell lymphoma) compared to the indolent types (MALT lymphoma, follicular lymphoma, duodenal-type follicular lymphoma, and small lymphocytic lymphoma) (p < 0.05). Conclusions: This study showed that most subtypes of gastrointestinal non-Hodgkin lymphomas exhibited same endoscopic features (superficial type and ulcer type). Aggressive gastrointestinal non-Hodgkin lymphomas (diffuse large B-cell lymphoma, mantle cell lymphoma, and T-cell lymphoma) were highly suspected when fungating lesions and protruding with ulcer lesions were encountered under endoscopy. Endoscopists should be aware of the connection between enhanced endoscopic characteristics and histological varieties of gastrointestinal lymphoma to improve diagnosis.
SMAD Proteins in TGF-β Signalling Pathway in Cancer: Regulatory Mechanisms and Clinical Applications
Authors: Wang Qi , Xiong Fei , Wu Guanhua , Wang Da , Liu Wenzheng , Chen Junsheng , Qi Yongqiang , Wang Bing , Chen Yongjun
Published: August 2023

Suppressor of mother against decapentaplegic (SMAD) family proteins are central to one of the most versatile cytokine signalling pathways in metazoan biology, the transforming growth factor-β (TGF-β) pathway. The TGF-β pathway is widely known for its dual role in cancer progression as both an inhibitor of tumour cell growth and an inducer of tumour metastasis. This is mainly mediated through SMAD proteins and their cofactors or regulators. SMAD proteins act as transcription factors, regulating the transcription of a wide range of genes, and their rich post-translational modifications are influenced by a variety of regulators and cofactors. The complex role, mechanisms, and important functions of SMAD proteins in tumours are the hot topics in current oncology research. In this paper, we summarize the recent progress on the effects and mechanisms of SMAD proteins on tumour development, diagnosis, treatment and prognosis, and provide clues for subsequent research on SMAD proteins in tumours.
Comparison of Fine-Needle Biopsy (FNB) versus Fine-Needle Aspiration (FNA) Combined with Flow Cytometry in the Diagnosis of Deep-Seated Lymphoma
Authors: Yang Yilei , Aruna  , Cheng Bin , Xiong Dingkun , Kuang Dong , Cui Haochen , Xiong Si , Mao Xia , Feng Yunlu , Zhao Yuchong
Published: August 2023

Evidence comparing ultrasound endoscopy-guided fine-needle biopsy (EUS-FNB) with EUS-guided fine-needle aspiration (EUS-FNA) in deep-seated lymphoma tissue sampling is insufficient. This study aims to evaluate the diagnostic efficacy of immunohistochemistry (IHC) or flow cytometry (FCM) on specimens obtained from EUS-FNB and EUS-FNA in the diagnosis and staging of deep-seated lymphomas. This real-world, dual-center study prospectively evaluated all eligible specimens from patients who underwent EUS-FNB/FNA over an 8-year period. 53 patients were enrolled, with 23 patients in the EUS-FNB group and 30 patients in the EUS-FNA group. FNB yielded specimens with longer core tissues (0.80 mm [0.55, 1.00] vs. 0.45 mm [0.30, 0.50], p = 0.009) and higher scores of specimen adequacy [4 (3.75, 4.00) vs. 3 (1.00, 4.00), p = 0.025]. Overall analysis revealed that the diagnostic accuracy of IHC based on specimens acquired from EUS-FNB was significantly higher than that of EUS-FNA (91.30% vs. 60.00%, p = 0.013). After controlling confounding factors including lesion size and endoscopists, EUS-FNB with IHC maintained a higher-level diagnostic accuracy compared to EUS-FNA (OR = 1.292 [1.037–1.609], p = 0.023). When FCM was additionally used to analyze the specimen acquired from EUS-FNA, the diagnostic yield was significantly improved (ROC AUC: 0.733 vs. 0.550, p = 0.015), and the AUC of FNB alone or combined with FCM was 0.739 and 0.761. Conclusions: FNB needles generate higher histopathological diagnostic accuracy and specimen quality than FNA for the deep-seated lymphoma. Though the application of FCM significantly improves the diagnostic efficacy of EUS-FNA, FNB was still the preferred diagnostic modality with a shorter procedure time, comparable diagnostic accuracy, and better cost-effectiveness.
Computer-Based Diagnosis of Celiac Disease by Quantitative Processing of Duodenal Endoscopy Images
Authors: Molder Adriana , Balaban Daniel Vasile , Molder Cristian-Constantin , Jinga Mariana , Robin Antonin
Published: August 2023

Celiac disease (CD) is a lifelong chronic autoimmune systemic disease that primarily affects the small bowel of genetically susceptible individuals. The diagnostics of adult CD currently rely on specific serology and the histological assessment of duodenal mucosa on samples taken by upper digestive endoscopy. Because of several pitfalls associated with duodenal biopsy sampling and histopathology, and considering the pediatric no-biopsy diagnostic criteria, a biopsy-avoiding strategy has been proposed for adult CD diagnosis also. Several endoscopic changes have been reported in the duodenum of CD patients, as markers of villous atrophy (VA), with good correlation with serology. In this setting, an opportunity lies in the automated detection of these endoscopic markers, during routine endoscopy examinations, as potential case-finding of unsuspected CD. We collected duodenal endoscopy images from 18 CD newly diagnosed CD patients and 16 non-CD controls and applied machine learning (ML) and deep learning (DL) algorithms on image patches for the detection of VA. Using histology as standard, high diagnostic accuracy was seen for all algorithms tested, with the layered convolutional neural network (CNN) having the best performance, with 99.67% sensitivity and 98.07% positive predictive value. In this pilot study, we provide an accurate algorithm for automated detection of mucosal changes associated with VA in CD patients, compared to normally appearing non-atrophic mucosa in non-CD controls, using histology as a reference.
Aerial Torsional Work Utilizing a Multirotor UAV with Add-on Thrust Vectoring Device
Authors: Martinez Ricardo Rosales , Paul Hannibal , Shimonomura Kazuhiro
Published: August 2023

Aerial manipulation aims to combine the versatility and the agility of aerial platforms with the manipulation capabilities of robotic arms. Their fast deployment allows for their implementation in maintenance tasks and support during disaster situations. However, the under-actuated nature of multirotor UAVs limits the magnitude and direction of the forces an aerial vehicle can safely exert during manipulation tasks. In this paper, the problems associated with UAVs and torsional tasks constraints regarding valve turning are addressed. An add-on thrust vectoring device which enhances manipulation options available to a conventional multirotor UAV is developed and described. The proposed system allows for a partial decoupling of the attitude and velocity vector of a multirotor. This permits stable translational flight and higher torque capabilities for torsional tasks. The separation of attitude and the velocity vector that allows for the design of a passive mechanism for valve operation is presented in this paper as well. The experimental results illustrate the forces and torques that can be generated in the evaluated operation modes.
Identifying Vital Nodes in Hypergraphs Based on Von Neumann Entropy
Authors: Hu Feng , Tian Kuo , Zhang Zi-Ke
Published: August 2023

Hypergraphs have become an accurate and natural expression of high-order coupling relationships in complex systems. However, applying high-order information from networks to vital node identification tasks still poses significant challenges. This paper proposes a von Neumann entropy-based hypergraph vital node identification method (HVC) that integrates high-order information as well as its optimized version (semi-SAVC). HVC is based on the high-order line graph structure of hypergraphs and measures changes in network complexity using von Neumann entropy. It integrates s-line graph information to quantify node importance in the hypergraph by mapping hyperedges to nodes. In contrast, semi-SAVC uses a quadratic approximation of von Neumann entropy to measure network complexity and considers only half of the maximum order of the hypergraph’s s-line graph to balance accuracy and efficiency. Compared to the baseline methods of hyperdegree centrality, closeness centrality, vector centrality, and sub-hypergraph centrality, the new methods demonstrated superior identification of vital nodes that promote the maximum influence and maintain network connectivity in empirical hypergraph data, considering the influence and robustness factors. The correlation and monotonicity of the identification results were quantitatively analyzed and comprehensive experimental results demonstrate the superiority of the new methods. At the same time, a key non-trivial phenomenon was discovered: influence does not increase linearly as the s-line graph orders increase. We call this the saturation effect of high-order line graph information in hypergraph node identification. When the order reaches its saturation value, the addition of high-order information often acts as noise and affects propagation.
A Low Switching Frequency Model Predictive Control Method for an Induction Motor Fed by a 3-Level Inverter
Authors: Huang Jingtao , Jiang Guangxu , Zhang Peng , Chen Jixin
Published: August 2023

Traditional model predictive control (MPC) for the induction motor fed by a three-level inverter needs to explore 27 voltage vectors to obtain the optimal one, which leads to high switching frequency and requires too much computation. To solve this issue, a low switching frequency model predictive control with partition optimization is proposed. First, the reference voltage vector can be gained from the prediction model at the next time, and the space voltage vector plane is divided into 12 sectors for further vector choice. Furthermore, considering inverter constraints, the candidate voltage vectors are determined according to the sector location of the reference voltage vector. In this way, the candidate vectors can be reduced to 3 at most. Then, a boundary circle limit is designed to avoid unnecessary switch changes. If the reference voltage vector is within the boundary limit, the switches do not act, which can reduce the system switching frequency without introducing the extra weight coefficient into the cost function. These selected voltage vectors are substituted into the cost function to determine the optimal one. Finally, the neutral point voltage deviation is controlled by the positive and negative redundant small vectors to realize the multi-objective constraint without weighting coefficients. The simulation results show that the proposed control method can significantly reduce the switching frequency; at the same time, both the dynamic and steady performances can be maintained well, and the cost function has no weight coefficients.
Novel Application of Open-Source Cyber Intelligence
Authors: Sufi Fahim
Published: August 2023

The prevalence of cybercrime has emerged as a critical issue in contemporary society because of its far-reaching financial, social, and psychological implications. The negative effects of cyber-attacks extend beyond financial losses and disrupt people’s lives on social and psychological levels. Conventional practice involves cyber experts sourcing data from various outlets and applying personal discernment and rational inference to manually formulate cyber intelligence specific to a country. This traditional approach introduces personal bias towards the country-level cyber reports. However, this paper reports a novel approach where country-level cyber intelligence is automatically generated with artificial intelligence (AI), employing cyber-related social media posts and open-source cyber-attack statistics. Our innovative cyber threat intelligence solution examined 37,386 tweets from 30,706 users in 54 languages using sentiment analysis, translation, term frequency–inverse document frequency (TF-IDF), latent Dirichlet allocation (LDA), N-gram, and Porter stemming. Moreover, the presented study utilized 238,220 open-intelligence cyber-attack statistics from eight different web links, to create a historical cyber-attack dataset. Subsequently, AI-based algorithms, like convolutional neural network (CNN), and exponential smoothing were used for AI-driven insights. With the confluence of the voluminous Twitter-derived data and the array of open-intelligence cyber-attack statistics, orchestrated by the AI-driven algorithms, the presented approach generated seven-dimensional cyber intelligence for Australia and China in complete automation. Finally, the topic analysis on the cyber-related social media messages revealed seven main themes for both Australia and China. This methodology possesses the inherent capability to effortlessly engender cyber intelligence for any country, employing an autonomous modality within the realm of pervasive computational platforms.
Application of Vibration Data Mining and Deep Neural Networks in Bridge Damage Identification
Authors: Hou Yi , Qian Songrong , Li Xuemei , Wei Shaodong , Zheng Xin , Zhou Shiyun
Published: August 2023

The aim of this paper is to mine the information contained in the bridge health monitoring data as well as to improve the shortcomings of traditional identification methods. In this paper, a bridge damage identification method based on the combination of data mining and deep neural networks is introduced. Firstly, a noise reduction method based on parameter optimisation of wavelet threshold decomposition is proposed, which further removes the noise signal by introducing two adjustment parameters in the threshold function to adapt to different wavelet decomposition layers. Furthermore, the Fast Fourier Transform is used to analyse the feature pattern of the original signal in the frequency domain, and the modal frequency features that exhibit the difference in damage categories are extracted from the spectrogram through sliding windows. Finally, a large number of irrelevant variables with small weight contributions are discarded by principal component analysis, and only the sensitive features with the most informative categories are retained as the input to the deep neural networks. The experimental results show that the new metrics after the feature engineering process improve the ability of damage identification and have stronger robustness, while our damage identification scheme achieves a good balance between the model computation and recognition accuracy. Furthermore, the recognition accuracy of the deep neural networks reaches over 93% with only three feature dimensions retained.
A New Blockchain-Based Authentication Framework for Secure IoT Networks
Authors: Al Hwaitat Ahmad K. , Almaiah Mohammed Amin , Ali Aitizaz , Al-Otaibi Shaha , Shishakly Rima , Lutfi Abdalwali , Alrawad Mahmaod
Published: August 2023

Most current research on decentralized IoT applications focuses on a specific vulnerability. However, for IoT applications, only a limited number of techniques are dedicated to handling privacy and trust concerns. To address that, blockchain-based solutions that improve the quality of IoT networks are becoming increasingly used. In the context of IoT security, a blockchain-based authentication framework could be used to store and verify the identities of devices in a decentralized manner, allowing them to communicate with each other and with external systems in a secure and trust-less manner. The main issues in the existing blockchain-based IoT system are the complexity and storage overhead. To solve these research issues, we have proposed a unique approach for a massive IoT system based on a permissions-based blockchain that provides data storage optimization and a lightweight authentication mechanism to the users. The proposed method can provide a solution to most of the applications which rely on blockchain technology, especially in assisting with scalability and optimized storage. Additionally, for the first time, we have integrated homomorphic encryption to encrypt the IoT data at the user’s end and upload it to the cloud. The proposed method is compared with other benchmark frameworks based on extensive simulation results. Our research contributes by designing a novel IoT approach based on a trust-aware security approach that increases security and privacy while connecting outstanding IoT services.
E-HRNet: Enhanced Semantic Segmentation Using Squeeze and Excitation
Authors: Kim Jin-Seong , Park Sung-Wook , Kim Jun-Yeong , Park Jun , Huh Jun-Ho , Jung Se-Hoon , Sim Chun-Bo
Published: August 2023

In the field of computer vision, convolutional neural network (CNN)-based models have demonstrated high accuracy and good generalization performance. However, in semantic segmentation, CNN-based models have a problem—the spatial and global context information is lost owing to a decrease in resolution during feature extraction. High-resolution networks (HRNets) can resolve this problem by keeping high-resolution processing layers parallel. However, information loss still occurs. Therefore, in this study, we propose an HRNet combined with an attention module to address the issue of information loss. The attention module is strategically placed immediately after each convolution to alleviate information loss by emphasizing the information retained at each stage. To achieve this, we employed a squeeze-and-excitation (SE) block as the attention module, which can seamlessly integrate into any model and enhance the performance without imposing significant parameter increases. It emphasizes the spatial and global context information by compressing and recalibrating features through global average pooling (GAP). A performance comparison between the existing HRNet model and the proposed model using various datasets show that the mean class-wise intersection over union (mIoU) and mean pixel accuracy (MeanACC) improved with the proposed model, however, there was a small increase in the number of parameters. With cityscapes dataset, MeanACC decreased by 0.1% with the proposed model compared to the baseline model, but mIoU increased by 0.5%. With the LIP dataset, the MeanACC and mIoU increased by 0.3% and 0.4%, respectively. The mIoU also decreased by 0.1% with the PASCAL Context dataset, whereas the MeanACC increased by 0.7%. Overall, the proposed model showed improved performance compared to the existing model.
Exploring the Limitations of Electric Field Energy Harvesting
Authors: Riba Jordi-Roger , Arbat Ricard , Ndong Yaye Oumy , Moreno-Eguilaz Manuel
Published: August 2023

Energy harvesting systems are key elements for the widespread deployment of wireless sensor nodes. Although many energy harvesting systems exist, electric field energy harvesting is a promising choice because it can provide uninterrupted power regardless of external conditions and depends only on the presence of AC voltage in the grid, regardless of the magnitude of the line current, even under no-load conditions. However, it also has some disadvantages, such as low power availability, the need for storage, or reliance on capacitive coupling, which is a complex phenomenon that depends on parasitic capacitances. This paper aims to provide useful and practical information on the possibilities of electric field energy harvesting for both high- and low-voltage applications. Since the objective of this paper is to quantify the physical limit of the harvested energy, it considers only the physical harvester itself and not the electronic circuitry required to transfer the harvested energy to the load. Theoretical, simulation, and experimental results show the feasibility of this energy source for low-power applications such as wireless sensor nodes.
Review: The Energy Implications of Averting Climate Change Catastrophe
Authors: Moriarty Patrick , Honnery Damon
Published: August 2023

Conventional methods of climate change (CC) mitigation have not ‘bent the curve’ of steadily rising annual anthropic CO2 emissions or atmospheric concentrations of greenhouse gases. This study reviews the present position and likely future of such methods, using the recently published literature with a global context. It particularly looks at how fast they could be implemented, given the limited time available for avoiding catastrophic CC (CCC). This study then critically examines solar geoengineering, an approach often viewed as complementary to conventional mitigation. Next, this review introduces equity considerations and shows how these even further shorten the available time for effective action for CC mitigation. The main findings are as follows. Conventional mitigation approaches would be implemented too slowly to be of much help in avoiding CCC, partly because some suggested technologies are infeasible, while others are either of limited technical potential or, like wind and solar energy, cannot be introduced fast enough. Due to these problems, solar geoengineering is increasingly advocated for as a quick-acting and effective solution. However, it could have serious side effects, and, given that there would be winners and losers at the international level as well as at the more regional level, political opposition may make it very difficult to implement. The conclusion is that global energy consumption itself must be rapidly reduced to avoid catastrophic climate change, which requires strong policy support.
The Impact of Fossil Fuels, Renewable Energy, and Nuclear Energy on South Korea’s Environment Based on the STIRPAT Model: ARDL, FMOLS, and CCR Approaches
Authors: Zimon Grzegorz , Pattak Dulal Chandra , Voumik Liton Chandra , Akter Salma , Kaya Funda , Walasek Robert , Kochański Konrad
Published: August 2023

This study intends to shed light on the environmental impacts of energy decisions in South Korea by analyzing the correlation between energy consumption patterns and environmental indicators such as carbon dioxide emissions. In 2021, global CO2 emissions increased by 6%—to the highest ever level of 36.3 billion tons—according to the International Energy Agency (IEA). This increase in CO2 emissions is a big problem for all countries around the world. The aim of this article is an analyze the impact of fossil fuels, renewable energy, and nuclear energy on South Korea’s environment based on the STIRPAT (stochastic impact by regression on population, affluence, and technology) model. Exploring the intricate nexus between economic and energy indicators and environmental outcomes, this study employs the STIRPAT model to analyze the influence of GDP, population dynamics, fossil fuels, renewable energy, and nuclear energy on South Korea’s environment. The yearly data from 1972 to 2021 are analyzed in this paper using an autoregressive distributed lag (ARDL) model. The reliability of this study is also examined by employing FMOLS (fully modified ordinary least squares) and CCR (canonical cointegrating regression) estimators. This study confirms the findings of previous research by showing that the rising South Korea GDP and population can lead to higher CO2 emissions and that a strategy switching to renewable energy can cut down on CO2 emissions in Korea, as it exhibits a coefficient of −0.085 *. The robustness results of FMOLS and CCR’s findings support baseline ARDL findings.
NVH Analysis and Optimization of Construction Hoist Drive System
Authors: Huang Bo , Tan Bangyu , Wang Jian , Liu Kang , Zhang Yuhang
Published: August 2023

The construction hoist drive system is a critical component of the construction hoist, and high speed and low vibration noise are essential development directions. In order to improve the NVH level of the construction hoist drive system, this paper carries out research and analysis of construction hoist drive system excitation, establishes the drive system rigid-flexible coupling dynamics model, and completes the establishment of the vibration and noise model of the drive system, simulation analysis, and optimization work. Ansys Motor CAD 2020 was used to establish the parametric model of the asynchronous motor and it was combined with the virtual work method to calculate Maxwell’s electromagnetic force to arrive at the radial electromagnetic force as the main cause of electromagnetic noise. For the mechanical excitation generated by the gearbox, the time-varying stiffness excitation, mesh shock excitation, and transmission error excitation are considered, and the transmission error of helical gears under different working conditions is calculated by combining it with Romax software 2020. The rigid-flexible coupling model of the construction hoist drive system is established. The load distribution analysis of the unit length of the tooth surface is completed for the first- and third-stage helical gears under different working conditions. The primary source of the drive system excitation is the tooth surface bias load. Based on the dynamic response analysis theory of the vibration superposition method, the maximum vibration speed of the drive system was analyzed by Romax. The maximum noise value of 78.8 dB was calculated from the acoustic power simulation of the drive system using Actran acoustic software 2022 in combination with acoustic theory, and the magnetic density amplitude of the stator teeth of the asynchronous motor was optimized based on the microscopic shaping design of the helical gear by Romax. The vibration and noise simulation of the optimized drive system shows that the vibration value is reduced to 0.75 mm/s, and the maximum noise is reduced to 70.2 dB, which is 10.9% lower than before the optimization. The overall NVH level has been improved. The optimization method to reduce the vibration noise of the drive system is explored, which can be used for vibration noise prediction and control during the development of the construction hoist drive system.
Degradation Prediction and Cost Optimization of Second-Life Battery Used for Energy Arbitrage and Peak-Shaving in an Electric Grid
Authors: Li Rongheng , Hassan Ali , Gupte Nishad , Su Wencong , Zhou Xuan
Published: August 2023

With the development of the electric vehicle industry, the number of batteries that are retired from vehicles is increasing rapidly, which raises critical environmental and waste issues. Second-life batteries recycled from automobiles have eighty percent of the capacity, which is a potential solution for the electricity grid application. To utilize the second-life batteries efficiently, an accurate estimation of their performance becomes a crucial portion of the optimization of cost-effectiveness. Nonetheless, few works focus on the modeling of the applications of second-life batteries. In this work, a general methodology is presented for the performance modeling and degradation prediction of second-life batteries applied in electric grid systems. The proposed method couples an electrochemical model of the battery performance, a state of health estimation method, and a revenue maximization algorithm for the application in the electric grid. The degradation of the battery is predicted under distinct charging and discharging rates. The results show that the degradation of the batteries can be slowed down, which is achieved by connecting numbers of batteries together in parallel to provide the same amount of required power. Many works aim for optimization of the operation of fresh Battery Energy Storage Systems (BESS). However, few works focus on the second-life battery applications. In this work, we present a trade-off between the revenue of the second-life battery and the service life while utilizing the battery for distinct operational strategies, i.e., arbitrage and peak shaving against Michigan’s DTE electricity utility’s Dynamic Peak Pricing (DPP) and Time of Use (TOU) tariffs. Results from case studies show that arbitrage against the TOU tariff in summer is the best choice due to its longer battery service life under the same power requirement. With the number of retired batteries set to increase over the next 10 years, this will give insight to the retired battery owners/procurers on how to increase the profitability, while making a circular economy of EV batteries more sustainable.
Distributed Generation Applied to Residential Self-Supply in South America in the Decade 2013–2023: A Literature Review
Authors: Chabla-Auqui Leonardo , Ochoa-Correa Danny , Villa-Ávila Edisson , Astudillo-Salinas Patricio
Published: August 2023

The implementation of residential distributed generation (DG) in South America has shown significant growth in the last decade, driven by increased research on photovoltaics and renewable energy sources. Regulatory policies and business models have been crucial in fostering the adoption of DG in the region, with residential self-supply being the most receptive sector for implementing the concept. This article presents a literature review on DG as applied to residential self-supply in South America by comprehensively analyzing documents published between 2013 and 2023, applying the PRISMA methodology. In total, 37 literature resources have been systematically selected and reviewed to contribute to the identification of trends and developments in the field of DG in the residential sector, as well as to highlight areas that require further research and attention from stakeholders, including policymakers, investors, technology providers, and consumers in the South American context.
Recent Advances in Battery Pack Polymer Composites
Authors: Azzopardi Brian , Hapid Abdul , Kaleg Sunarto , Sudirja Sudirja , Onggo Djulia , Budiman Alexander C.
Published: August 2023

The use of a polymer composite material in electric vehicles (EVs) has been extensively investigated, especially as a substitute for steel. The key objective of this manuscript is to provide an overview of the existing and emerging technologies related to the application of such a composite, especially for battery pack applications, in which its high strength-to-weight ratio, corrosion resistance, design flexibility, and durability are advantageous compared to any metal in general. This study explores the key considerations in the design and fabrication of composites, including base material selection, structural design optimization, reinforcement material, manufacturing processes, and integration with battery systems. The paper also discusses the performance characteristics of composite battery pack structures, such as mechanical properties, thermal management, safety aspects, and environmental sustainability. This study aims to contribute to sharpening the direction of future research and innovations in the area of composite battery pack technology.
Design and Implementation of Self-Limiting Two-Stage LC Oscillators Using Cascade Structure of Monolithic CCIIs as Active Elements
Authors: Pandiev Ivaylo
Published: August 2023

This paper presents the structure and principle of operation of two circuit configurations of self-limiting LC oscillators using monolithic positive second-generation current conveyors (CCII+s), that are implemented using Current-Feedback Operational Amplifiers (CFOAs) with an available compensation pin (Z). The proposed LC oscillators are synthesized using a systematic approach in the design of analog electronic circuits and can be considered as variants of the basic three-point oscillators, implemented using transistors (BJTs or FETs). Based on the analysis of the structure and electrical parameters of the CFOAs with a compensation pin (Z), electronic circuits of oscillators with two-stage amplifier blocks are synthesized. The characteristic equations and self-oscillation conditions are derived for the obtained analog circuits, and recommendations for designing circuits with arbitrary frequencies are defined. To verify the efficiency of the proposed LC oscillators, an experimental study is performed in the frequency range from 100 kHz to 10 MHz. The CFOAs AD844A with an external terminal z of the internal current conveyor are used as active elements. The obtained experimental results well match the results of the simulation modelling and the parameters based on the derived analytical expressions. The developed LC oscillators are intended to be used in schematic configurations of gas sensors based on surface acoustic wave (SAW) resonators.
Assessing the Correlation between Citizen Science and Carbon Footprint: Introduction of COMPAIR’s CO2 Calculator
Authors: Orfanou Athanasia , Vakalis Stergios , Karelis Christos , Alexopoulos Charalampos , Charalabidis Yannis , Lekkas Demetris Francis
Published: August 2023

The citizen’s carbon footprint is affected by various factors, but mostly by electricity consumption, daily transportation, travelling habits, as well as municipal solid waste management, a critical factor that is not frequently incorporated in carbon footprint estimations. This paper proposes a new carbon footprint calculator, the Carbon Footprint Simulation Dashboard—COMPAIR’s CO2 calculator. The CO2 calculator employs Citizen Science (CS) information in order to assist citizens in understanding and comparing how future carbon emissions will be modified in accordance with changes in their daily routines. The calculator offers several statistics, e.g., the country’s average carbon footprint and comparisons between EU members with respect to sectors that shape it, along with several recommendations for those domains where carbon footprint is significantly higher than the desired limits. The novelty of this tool is the integration of waste management strategies as a dimension of the total CO2 calculation. In this framework, the study presents the development of the Carbon Footprint Simulation Dashboard while two different waste management scenarios are applied with different citizen behaviours on recycling and composting. The applications highlighted the consumption in buildings that account for almost 50% of the total CO2 emissions, while the crucial role of transportation is also a key parameter. The different waste management scenarios showed a correlation between the CO2 footprint and the overall consumption/disposal habits of citizens. In the case of advanced recycling and composting, waste management accounted for up to 7% of the CO2 emissions, and this highlights the significance of behavioural choices.
Robust Speed Control of Uncertain Two-Mass System
Authors: Wróbel Karol , Śleszycki Kacper , Kahsay Amanuel Haftu , Szabat Krzysztof , Katsura Seiichiro
Published: August 2023

The main purpose of this work is to present a robust speed control structure for a two-mass system. The tested system consists of a PI controller with two additional feedback. The coefficients of the control system are selected using a pattern-search optimization method in order to obtain robustness to changes in the system parameters. The control system requires information about non-measurable state variables. For this purpose, it is proposed to use a multilayer observer. In order to show the advantages of the MLO system, this article also presents comparative studies with a classical observer. A number of simulation and experimental tests are carried out. The obtained results confirmed a much higher quality of control in the system cooperating with a multilayer observer compared to the system with a classical observer.
Resilience of Natural Gas Pipeline System: A Review and Outlook
Authors: Yang Zhaoming , Xiang Qi , He Yuxuan , Peng Shiliang , Faber Michael Havbro , Zio Enrico , Zuo Lili , Su Huai , Zhang Jinjun
Published: August 2023

A natural gas pipeline system (NGPS), as a crucial energy transportation network, exhibits intricate systemic characteristics. Both uncertain disturbances and complex characteristics result in higher requirement of supply safety. The investigation into NGPS resilience addresses the constraints of pipeline integrity and reliability, centering around the vulnerability, robustness, and recovery of an NGPS. Based on a literature review and practical engineering insights, the generalized concept of NGPS resilience is elucidated. The research methodologies of NGPS resilience are classified into three types: indicator construction method, process analysis method, and complex networks method. The practical applications of NGPS resilience research are analyzed, which are based on NGPS operation safety, information safety, and market safety. The ongoing applications and detailed measures are also concluded, which can guide the researchers and engineers from NGPS resilience.
HPPC Test Methodology Using LFP Battery Cell Identification Tests as an Example
Authors: Białoń Tadeusz , Niestrój Roman , Skarka Wojciech , Korski Wojciech
Published: August 2023

The aim of this research was to create an accurate simulation model of a lithium-ion battery cell, which will be used in the design process of the traction battery of a fully electric load-hull-dump vehicle. Discharge characteristics tests were used to estimate the actual cell capacity, and hybrid pulse power characterization (HPPC) tests were used to identify the Thevenin equivalent circuit parameters. A detailed description is provided of the methods used to develop the HPPC test results. Particular emphasis was placed on the applied filtration and optimization techniques as well as the assessment of the quality and the applicability of the acquired measurement data. As a result, a simulation model of the battery cell was created. The article gives the full set of parameter values needed to build a fully functional simulation model. Finally, a charge-depleting cycle test was performed to verify the created simulation model.
Analysing Effective and Ineffective Impacts of Maintenance Strategies on Electric Power Plants: A Comprehensive Approach
Authors: Al Ameeri Tareq Ali , Ab Rahman Mohd Nizam , Muhamad Norhamidi
Published: August 2023

The maintenance strategy used in an electric power plant plays a crucial role in its overall performance and operational efficiency. An effective maintenance strategy describes the approach to exploiting various forms of maintenance (corrective, preventive, predictive, proactive, etc.) in an electric power plant. In this paper, the effective and ineffective impacts of maintenance strategies on power plants were examined. Also, the distinction between corrective, preventive, and aggressive maintenance was considered. In terms of effective impacts, a well-designed and executed maintenance strategy enhances the reliability and availability of the electric power plant by minimising unplanned downtime. It extends the lifespan of critical equipment, improves safety measures, increases energy efficiency, and contributes to long-term cost savings. However, in terms of ineffective impacts, poorly planned or executed maintenance strategies can result in increased downtime, higher repair costs, safety risks, decreased efficiency, and regulatory compliance issues. Neglecting maintenance can lead to equipment failures, reduced productivity, and potential environmental incidents.
Potential of Scots Pine for a Push Strategy against the European Spruce Bark Beetle Ips typographus
Authors: Favaro Riccardo , Andriolo Alessandro , Sieder Cinthia , Angeli Sergio
Published: August 2023

Ips typographus, the European spruce bark beetle, is a destructive forest insect that attacks spruce trees. It poses a significant threat to the forestry industry, causing widespread tree mortality and economic losses, and its management through chemical ecology is a promising approach. Attraction relies on aggregation pheromones while repellency is achieved via antiaggregation pheromones combined with mixtures of nonhost volatiles (NHVs), but an effective push and pull strategy has not been established yet. In this study, we observed the beetle colonization dynamic and density comparing pure Norway spruce stacks and Norway spruce stacks with 20% Scots pine logs. We collected the spruce bark volatiles before the beetle colonization and at the end of the trial, and tested the behavioral effects on the beetles of both spruce and pine essential oils in olfactometer trials. In the stacks with Scots pine, we observed a delayed primary colonization and a 65% reduction of the secondary colonization, confirming the colonization disruption mediated by NHVs. Volatile analysis showed a significant change in the bark emission profiles, and the reaching of the antiaggregation phase was marked by the release of verbenone. Behavioral experiments confirmed the attractivity of spruce essential oil and the strong repellency of the pine essential oil. The study supports the use of complex NHVs blends for the beetle behavioral manipulation in the field. Further studies are needed to assess if the same results can be achieved by deploying essential oils in forest stands.