bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review of Time-Series Forecasting Algorithms for Industrial Manufacturing Systems
Authors: Fatima Syeda Sitara Wishal , Rahimi Afshin
Published: June 2024

Time-series forecasting is crucial in the efficient operation and decision-making processes of various industrial systems. Accurately predicting future trends is essential for optimizing resources, production scheduling, and overall system performance. This comprehensive review examines time-series forecasting models and their applications across diverse industries. We discuss the fundamental principles, strengths, and weaknesses of traditional statistical methods such as Autoregressive Integrated Moving Average (ARIMA) and Exponential Smoothing (ES), which are widely used due to their simplicity and interpretability. However, these models often struggle with the complex, non-linear, and high-dimensional data commonly found in industrial systems. To address these challenges, we explore Machine Learning techniques, including Support Vector Machine (SVM) and Artificial Neural Network (ANN). These models offer more flexibility and adaptability, often outperforming traditional statistical methods. Furthermore, we investigate the potential of hybrid models, which combine the strengths of different methods to achieve improved prediction performance. These hybrid models result in more accurate and robust forecasts. Finally, we discuss the potential of newly developed generative models such as Generative Adversarial Network (GAN) for time-series forecasting. This review emphasizes the importance of carefully selecting the appropriate model based on specific industry requirements, data characteristics, and forecasting objectives.
An Improved Fault Diagnosis Method for Rolling Bearings Based on 1D_CNN Considering Noise and Working Condition Interference
Authors: Huang Kai , Zhu Linbo , Ren Zhijun , Lin Tantao , Zeng Li , Wan Jin , Zhu Yongsheng
Published: June 2024

Rolling bearings are prone to failure due to the complexity and serious operational environment of rotating equipment. Intelligent fault diagnosis based on convolutional neural networks (CNNs) has become an effective tool to ensure the reliable operation of rolling bearings. However, interference caused by environmental noise and variable working conditions can affect the data. To solve this problem, we propose an improved fault diagnosis method called deep convolutional neural network based on multi-scale features and mutual information (MMDCNN). In our approach, a multi-scale convolutional layer is placed at the front end of a 1D_CNN to maximize the retention of the multi-scale initial features. Meanwhile, the key fault features are further enhanced adaptively by introducing a self-attention mechanism. Then, the composite loss function is constructed by maximizing mutual information as an auxiliary loss based on cross-entropy loss; thus, the proposed method can extract robust fault features with high generalization performance. To demonstrate the superiority of MMDCNN, we compared the performance of our scheme with several existing deep learning models on two datasets. The results show that the proposed model successfully achieves bearing fault diagnosis with interference from noise and variable working conditions, possessing a powerful fault feature extraction capability.
Towards Analysis of Multivariate Time Series Using Topological Data Analysis
Authors: Zheng Jingyi , Feng Ziqin , Ekstrom Arne D.
Published: June 2024

Topological data analysis (TDA) has proven to be a potent approach for extracting intricate topological structures from complex and high-dimensional data. In this paper, we propose a TDA-based processing pipeline for analyzing multi-channel scalp EEG data. The pipeline starts with extracting both frequency and temporal information from the signals via the Hilbert–Huang Transform. The sequences of instantaneous frequency and instantaneous amplitude across all electrode channels are treated as approximations of curves in the high-dimensional space. TDA features, which represent the local topological structure of the curves, are further extracted and used in the classification models. Three sets of scalp EEG data, including one collected in a lab and two Brain–computer Interface (BCI) competition data, were used to validate the proposed methods, and compare with other state-of-art TDA methods. The proposed TDA-based approach shows superior performance and outperform the winner of the BCI competition. Besides BCI, the proposed method can also be applied to spatial and temporal data in other domains such as computer vision, remote sensing, and medical imaging.
The de Rham Cohomology Classes of Hemi-Slant Submanifolds in Locally Product Riemannian Manifolds
Authors: Gök Mustafa , Kılıç Erol
Published: June 2024

This paper aims to discuss the de Rham cohomology of hemi-slant submanifolds in locally product Riemannian manifolds. The integrability and geodesical invariance conditions of the distributions derived from the definition of a hemi-slant submanifold are given. The existence and non-triviality of de Rham cohomology classes of hemi-slant submanifolds are investigated. Finally, an example is presented.
Fault Detection and Diagnosis of Three-Wheeled Omnidirectional Mobile Robot Based on Power Consumption Modeling
Authors: Wang Bingtao , Zhang Liang , Kim Jongwon
Published: June 2024

Three-wheeled omnidirectional mobile robots (TOMRs) are widely used to accomplish precise transportation tasks in narrow environments owing to their stability, flexible operation, and heavy loads. However, these robots are susceptible to slippage. For wheeled robots, almost all faults and slippage will directly affect the power consumption. Thus, using the energy consumption model data and encoder data in the healthy condition as a reference to diagnose robot slippage and other system faults is the main issue considered in this paper. We constructed an energy model for the TOMR and analyzed the factors that affect the power consumption in detail, such as the position of the gravity center. The study primarily focuses on the characteristic relationship between power consumption and speed when the robot experiences slippage or common faults, including control system faults. Finally, we present the use of a table-based artificial neural network (ANN) to indicate the type of fault by comparing the modeled data with the measured data. The experiments proved that the method is accurate and effective for diagnosing faults in TOMRs.
Hypergraph-Based Multitask Feature Selection with Temporally Constrained Group Sparsity Learning on fMRI
Authors: Qu Youzhi , Fu Kai , Wang Linjing , Zhang Yu , Wu Haiyan , Liu Quanying
Published: June 2024

Localizing the brain regions affected by tasks is crucial to understanding the mechanisms of brain function. However, traditional statistical analysis does not accurately identify the brain regions of interest due to factors such as sample size, task design, and statistical effects. Here, we propose a hypergraph-based multitask feature selection framework, referred to as HMTFS, which we apply to a functional magnetic resonance imaging (fMRI) dataset to extract task-related brain regions. HMTFS is characterized by its ability to construct a hypergraph through correlations between subjects, treating each subject as a node to preserve high-order information of time-varying signals. Additionally, it manages feature selection across different time windows in fMRI data as multiple tasks, facilitating time-constrained group sparse learning with a smoothness constraint. We utilize a large fMRI dataset from the Human Connectome Project (HCP) to validate the performance of HMTFS in feature selection. Experimental results demonstrate that brain regions selected by HMTFS can provide higher accuracy for downstream classification tasks compared to other competing feature selection methods and align with findings from previous neuroscience studies.
Kamenev-Type Criteria for Testing the Asymptotic Behavior of Solutions of Third-Order Quasi-Linear Neutral Differential Equations
Authors: Alrashdi Hail S. , Albalawi Wedad , Muhib Ali , Moaaz Osama , Elabbasy Elmetwally M.
Published: June 2024

This paper aims to study the asymptotic properties of nonoscillatory solutions (eventually positive or negative) of a class of third-order canonical neutral differential equations. We use Riccati substitution to reduce the order of the considered equation, and then we use the Philos function class to obtain new criteria of the Kamenev type, which guarantees that all nonoscillatory solutions converge to zero. This approach is characterized by the possibility of applying its conditions to a wider area of equations. This is not the only aspect that distinguishes our results; we also use improved relationships between the solution and the corresponding function, which in turn is reflected in a direct improvement of the criteria. The findings in this article extend and generalize previous findings in the literature and also improve some of these findings.
INT-FUP: Intuitionistic Fuzzy Pooling
Authors: Rajafillah Chaymae , El Moutaouakil Karim , Patriciu Alina-Mihaela , Yahyaouy Ali , Riffi Jamal
Published: June 2024

Convolutional Neural Networks (CNNs) are a kind of artificial neural network designed to extract features and find out patterns for tasks such as segmentation, recognizing objects, and drawing up classification. Within a CNNs architecture, pooling operations are used until the number of parameters and the computational complexity are reduced. Numerous papers have focused on investigating the impact of pooling on the performance of Convolutional Neural Networks (CNNs), leading to the development of various pooling models. Recently, a fuzzy pooling operation based on type-1 fuzzy sets was introduced to cope with the local imprecision of the feature maps. However, in fuzzy set theory, it is not always accurate to assume that the degree of non-membership of an element in a fuzzy set is simply the complement of the degree of membership. This is due to the potential existence of a hesitation degree, which implies a certain level of uncertainty. To overcome this limitation, intuitionistic fuzzy sets (IFS) were introduced to incorporate the concept of a degree of hesitation. In this paper, we introduce a novel pooling operation based on intuitionistic fuzzy sets to incorporate the degree of hesitation heretofore neglected by a fuzzy pooling operation based on classical fuzzy sets, and we investigate its performance in the context of image classification. Intuitionistic pooling is performed in four steps: bifuzzification (by the transformation of data through the use of membership and non-membership maps), first aggregation (through the transformation of the IFS into a standard fuzzy set, second aggregation (through the transformation and use of a sum operator), and the defuzzification of feature map neighborhoods by using a max operator. IFS pooling is used for the construction of an intuitionistic pooling layer that can be applied as a drop-in replacement for the current, fuzzy (type-1) and crisp, pooling layers of CNN architectures. Various experiments involving multiple datasets demonstrate that an IFS-based pooling can enhance the classification performance of a CNN. A benchmarking study reveals that this significantly outperforms even the most recent pooling models, especially in stochastic environments.
A Comprehensive Decision-Making Approach for Strategic Product Module Planning in Mass Customization
Authors: Liu Shuo-Fang , Wang Shi-Yu , Tung Hsueh-Hung
Published: June 2024

This paper explores the integrated optimization of complex coupled industrial manufacturing systems and production strategies based on user customization needs. Two optimization metrics are considered: one is whether the production process of engineering manufacturing is simplified, and the other is whether it is based on the customization requirements of the customer. These two metrics are interrelated, and cases may even be conflicting. Considering the interdependence between engineering manufacturing and user requirements, this paper develops an integrated customized modular engineering manufacturing process to minimize production and maintenance costs and improve efficiency while meeting user customization requirements. This paper takes expert evaluation as an important decision indicator and optimizes the production process strategy on this basis. Finally, a case study is given to illustrate the applicability of the proposed process model.
Green and Sustainable Rare Earth Element Recycling and Reuse from End-of-Life Permanent Magnets
Authors: Cherkezova-Zheleva Zara , Burada Marian , Sobetkii (Slobozeanu) Anca Elena , Paneva Daniela , Fironda Sabina Andreea , Piticescu Radu-Robert
Published: June 2024

Rare earth elements (REEs) are key materials for the development of renewable energy devices such as high-power magnets for wind turbines, electric vehicles, or fuel cells for hydrogen generation, aiming to fulfill the objectives of the European Green Deal for a carbon-neutral economy. The increased demand for REEs and their criticality strongly require the improvement of their extraction technologies from primary resources and the enhancement of their circularity reuse rate from secondary resources. The aim of this paper is to focus attention on the possibilities offered by emerging methods such as microwave (MW) treatment and mechanochemistry in waste electric and electronic equipment (WEEE) processing and the reuse of end-of-life (EoL) magnets, directed toward the tailoring of rational REE material flows. The discussed investigation examples explore some key features of conventional and new methods for efficient, environmentally friendly, and scalable REE extraction and reuse, with the final goal of producing recycled NdFeB powders, with potential use in the redesign and fabrication of new REE-based magnets.
Comparison of Nitriding Behavior for Austenitic Stainless Steel 316Ti and Super Austenitic Stainless Steel 904L
Authors: Mändl Stephan , Manova Darina
Published: June 2024

In situ X-ray diffraction (XRD) was used to compare nitrogen low-energy ion implantation (LEII) into austenitic stainless steel 316Ti and super austenitic stainless steel 904L. While the diffusion and layer growth were very similar, as derived from the decreasing intensity of the substrate reflection, strong variations in the observed lattice expansion—as a function of orientation, the steel alloy, and nitriding temperature—were observed. Nevertheless, a similar resulting nitrogen content was measured using time-of-flight secondary ion mass spectrometry (ToF-SIMS). Furthermore, for some conditions, the formation of a double layer with two distinct lattice expansions was observed, especially for steel 904L. Regarding the stability of expanded austenite, 316Ti had already decayed in CrN during nitriding at 500 °C, while no such effect was observed for 904L. Thus, the alloy composition has a strong influence only on the lattice expansion and the stability of expanded austenite—but not the diffusion and nitrogen content.
The Effect of Heat Treatment on the Microstructure and Mechanical Properties of Powder Metallurgy Ti-48Al Alloy
Authors: Yan Mengjie , Zhang Hongtao , Yang Fang , Gui Yunwei , Han Zhijie , Fu Huadong
Published: June 2024

Heat treatment is the critical step in achieving a refined microstructure and enhanced mechanical properties of TiAl-based alloys. This study investigated the influence of heat treatment temperature, cooling method, and heat treatment time on the microstructure and mechanical properties of an extruded powder metallurgy Ti-48Al alloy, and achieved the control of fully lamellar fine microstructures and the enhancement of performance through a simple heat treatment, rather than the traditional approach of homogenization followed by heat treatment. The results indicate that the heat treatment temperature determines the type of microstructure, while the cooling rate dictates the lamellar width. As the heat treatment temperature was increased from the two-phase region to the α single-phase region, the microstructure transitioned from duplex to near lamellar, and the alloy strength initially increased and then decreased, influenced by both the lamellar colony ratio and grain size. A rapid cooling rate (water quenching) induces a non-diffusive massive phase transformation, whereas a slow cooling rate (air cooling) gradually forms α2/γ lamellar colonies. Therefore, a suitable heat treatment regime for the powder metallurgy Ti-48Al alloy was determined to be 1340 °C/5 min/air cooling. The microstructure of the alloy was near lamellar, consisting of lamellar colonies approximately 50 μm and a small number of γ equiaxed grains of about 10 μm. Subsequently, the alloy exhibited a room temperature tensile strength of 784 MPa and a yield strength of 763 MPa, representing improvements of 17.0% and 38.7% over the extruded alloy, respectively. This research provides a reference for establishing a heat treatment process for powder metallurgy TiAl alloys.
Dry Reforming of CH4 Using a Microreactor
Authors: Wedraogo Tarsida N. , Wu Jing , Li Huai Z.
Published: June 2024

In the present study, a comparison of the dry reforming of a gas mixture containing methane, carbon dioxide and nitrogen without contaminants to a ruthenium-based Ru/Al2O3 catalyst was carried out in a microreactor for the first time. The influence of the contact time, temperature and composition of the feed on the conversion was exhaustively investigated. The optimal operating conditions were found to be a contact time of 80 milliseconds, a temperature of 700 °C and a CH4:CO2 ratio of 1. The assessment of diffusional limitations reveals that there is no resistance to mass transfer, which reveals the potential benefit of the determination of intrinsic reaction kinetics within a microreactor.
Establishment of a Mouse Model of Mycoplasma pneumoniae-Induced Plastic Bronchitis
Authors: Jin Peng , Zhao Lin-Sheng , Zhang Tong-Qiang , Di Han , Guo Wei
Published: June 2024

Plastic bronchitis (PB) constitutes a life-threatening pulmonary disorder, predominantly attributed to Mycoplasma pneumoniae (MP) infection. The pathogenic mechanisms involved remain largely unexplored, leading to the absence of reliable approaches for early diagnosis and clear treatment. Thus, the present investigation aimed to develop an MP-induced mouse model of PB, thereby enhancing our understanding of this complex condition. In the first stage, healthy BALB/c mice were utilized to investigate the optimal methods for establishing PB. This involved the application of nebulization (15–20 min) and intratracheal administration (6–50 μL) with 2-chloroethyl ethyl sulfide (CEES) concentrations ranging from 4.5% to 7.5%. Subsequently, the MP model was induced by administering an MP solution (2 mL/kg/day, 108 CFU/50 μL) via the intranasal route for a duration of five consecutive days. Ultimately, suitable techniques were employed to induce plastic bronchitis in the MP model. Pathological changes in lung tissue were analyzed, and immunohistochemistry was employed to ascertain the expression levels of vascular endothelial growth factor receptor 3 (VEGFR-3) and the PI3K/AKT/mTOR signaling pathway. The administration of 4.5% CEES via a 6 µL trachea was the optimal approach to establishing a PB model. This method primarily induced neutrophilic inflammation and fibrinous exudate. The MP-infected group manifested symptoms indicative of respiratory infection, including erect hair, oral and nasal secretions, and a decrease in body weight. Furthermore, the pathological score of the MP+CEES group surpassed that of the groups treated with MP or CEES independently. Notably, the MP+CEES group demonstrated significant activation of the VEGFR-3 and PI3K/AKT/mTOR signaling pathways, implying a substantial involvement of lymphatic vessel impairment in this pathology. This study successfully established a mouse model of PB induced by MP using a two-step method. Lymphatic vessel impairment is a pivotal element in the pathogenetic mechanisms underlying this disease entity. This accomplishment will aid in further research into treatment methods for patients with PB caused by MP.
Simvastatin, Its Antimicrobial Activity and Its Prevention of Alzheimer’s Disease
Authors: Dhakal Sudip , Macreadie Ian G.
Published: June 2024

Simvastatin, a blockbuster drug for treating hypercholesterolemia, has multifactorial benefits as an antimicrobial agent and plays a preventative role in reducing the incidence of Alzheimer’s Disease (AD). Although most of the beneficial effects of simvastatin have been attributed to its ability to reduce cholesterol levels, recent scientific studies have suggested that its benefits are largely due to its pleiotropic effects in targeting other pathways, e.g., by inhibiting protein lipidation. There are certain pleiotropic effects that can be predicted from the inhibition of the mevalonate pathway; however, some of the effects of simvastatin in proteostasis lead to reduced levels of amyloid beta, the key contributor to AD. This review discusses the use of simvastatin as an antimicrobial agent and anti-AD drug.
Impact of Perioperative Dexamethasone Administration on Infection and Implant Osseointegration in a Preclinical Model of Orthopedic Device-Related Infection
Authors: Burch Marc-Antoine , Keshishian Aron , Wittmann Charlotte , Nehrbass Dirk , Thompson Keith , Arens Daniel , Richards R. Geoff , Mdingi Vuysa , Chitto Marco , Morgenstern Mario , Moriarty T. Fintan , Eijer Henk
Published: June 2024

Glucocorticoids may be given prior to major orthopedic surgery to decrease postoperative nausea, vomiting, and pain. Additionally, many orthopedic patients may be on chronic glucocorticoid therapy. The aim of our study was to investigate whether glucocorticoid administration influences Orthopedic-Device-Related Infection (ODRI) in a rat model. Screws colonized with Staphylococcus epidermidis were implanted in the tibia of skeletally mature female Wistar rats. The treated groups received either a single shot of dexamethasone in a short-term risk study, or a daily dose of dexamethasone in a longer-term interference study. In both phases, bone changes in the vicinity of the implant were monitored with microCT. There were no statistically significant differences in bacteriological outcome with or without dexamethasone. In the interference study, new bone formation was statistically higher in the dexamethasone-treated group (p = 0.0005) as revealed by CT and histopathological analysis, although with relatively low direct osseointegration of the implant. In conclusion, dexamethasone does not increase the risk of developing periprosthetic osteolysis or infection in a pre-clinical model of ODRI. Long-term administration of dexamethasone seemed to offer a benefit in terms of new bone formation around the implant, but with low osseointegration.
Molecular Mechanisms of Intestinal Protection by Levilactobacillus brevis 23017 against Salmonella typhimurium C7731-Induced Damage: Role of Nrf2
Authors: Shi Ziqi , Nan Yongchao , Zhou Xinyao , Zhang Wenzhi , Zhang Zheng , Zhang Chuankun , Duan Haoyuan , Ge Junwei , Zhao Lili
Published: June 2024

The treatment and prevention of pathogenic diseases by lactic acid bacteria (LAB) has attracted more and more attention. As a special LAB, Levilactobacillus brevis (L. brevis) has relatively less research on its antibacterial infection in vivo, and its protective effect and mechanism still need to be fully studied. In this study, we selected L. brevis 23017, which can regulate the intestinal immunity of the host animal and resist pathogen infection, to evaluate its protective role and potential molecular mechanisms in the mouse model of S. typhimurium C7731 infection. As expected, we confirmed that L. brevis 23017 reduced the diarrhea rate and increased the daily weight gain and survival rate of the mouse model, and inhibited S. typhimurium colonization in the jejunum and liver. It also reduced the level of oxidative damage and protected the integrity of intestinal tissue by increasing the activity of intestinal antioxidant enzymes (SOD, GSH-Px and T-AOC). From the perspective of intestinal mucosal barrier injury and repair, it was confirmed that L. brevis 23017 could increase the expression levels of intestinal tight junction proteins (ZO-1 and OCLN). Our research results also show that L. brevis 23017 inhibits the inflammatory response and promotes the occurrence of cellular immunity in the body by promoting the increase in IL-10 and inhibiting IL-13 in serum and intestinal tissue. Notably, L. brevis 23017 increased total secretory immunoglobulin A (SIgA) levels in the intestine, which were closely associated with elevated levels of IL-5, IL-13, pIgR, j-chain, and IgAα-chain. In addition, L. brevis 23017 increased the expression of antioxidant proteins Nrf2, NQO1, and HO-1 associated with Nrf2 signaling to inhibit intestinal oxidative damage. This mechanism may be responsible for its protective effect against S. typhimurium-infected intestine. Our study provides new evidence and theoretical support for the analysis of the anti-bacterial infection effect and mechanism of L. brevis, which will contribute to the development of L. brevis and the treatment of pathogenic bacteria intestinal infection.
Screening and Identification of Soil Selenium-Enriched Strains and Application in Auricularia auricula
Authors: Chen Yadong , Liu Zhenghan , Zeng Weimin , Liu Yang , Zhao Dandan , Zhang Yanlong , Jia Xiangqian
Published: June 2024

Selenium (Se) is an essential trace element for human physiological metabolism. The application of organic Se as a source to cultivate Se-rich plants for micronutrient supplementation has been receiving increasing attention. In our study, a bacterial strain named H1 was isolated from the soil in Heilongjiang Province, China, and under optimal culture conditions, the unit Se content could reach 3000 μg·g−1 and its 16S ribosomal DNA sequence seemed to be a new molecular record of an Enterobacter species. After the domestication of Se tolerance and Se-rich experiments, H1 can be used as a Se source for cultivation of Se-rich Auricularia auricula. The results showed that soluble protein, soluble sugar, free amino acid and vitamin C contents in Auricularia auricula were notably increased by 28.7%, 21.8%, 32.5% and 39.2% under the treatment of Se concentration of 0.24 mg·kg−1, respectively. These findings enhance our understanding that H1 is more conducive to Se uptake and nutrient accumulation.
Microbiota of Peri-Implant Healthy Tissues, Peri-Implant Mucositis, and Peri-Implantitis: A Comprehensive Review
Authors: Di Spirito Federica , Giordano Francesco , Di Palo Maria Pia , D’Ambrosio Francesco , Scognamiglio Bruno , Sangiovanni Giuseppe , Caggiano Mario , Gasparro Roberta
Published: June 2024

Understanding the microbiological profiles of peri-implant conditions is crucial for developing effective preventive and therapeutic strategies. This narrative review analyzes the microbial profiles associated with healthy peri-implant sites, peri-implant mucositis, and peri-implantitis, along with related microbiological sampling and analyses. Healthy peri-implant sites are predominantly colonized by Streptococcus, Rothia, Neisseria, and Corynebacterium species, in addition to Gram-positive cocci and facultatively anaerobic rods, forming a stable community that prevents pathogenic colonization and maintains microbial balance. In contrast, peri-implant mucositis shows increased microbial diversity, including both health-associated and pathogenic bacteria such as red and orange complex bacteria, contributing to early tissue inflammation. Peri-implantitis is characterized by even greater microbial diversity and a complex pathogenic biofilm. Predominant pathogens include Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Fusobacterium nucleatum, and unique species like Filifactor alocis and Fretibacterium fastidiosum. Additionally, less common species such as Staphylococcus and Enterobacteriaceae, contributing to disease progression through biofilm formation and increased inflammatory response, along with EBV and human cytomegalovirus with a still not defined role, and Candida albicans contribute to disease progression through biofilm formation, immune modulation, and synergistic inter-kingdom interactions. Future research should standardize diagnostic criteria, employ advanced molecular techniques, integrate microbial data with clinical factors, and highlight inter-kingdom interactions.
Left-Parietal Angiocentric Glioma: Our Experience and a Review of the Literature
Authors: Curcio Antonello , Espahbodinea Shervin , Li Trenta Eva Azzurra , Ferrarotto Rosamaria , Nanni Aristide , Arabia Noemi , Ciccolo Giorgio , Raffa Giovanni , Granata Francesca , Germanò Antonino
Published: June 2024

Background: Angiocentric glioma (AG) is a rare, benign, and slow-growing tumor. First described in 2005, it is now gaining attention with respect to the possibility of being diagnosed. Even with no statistical differences between sex, it has been reported both in children and the elderly. A total of 120 cases have been described in the literature. The aim of this study is to provide new data for a new statistical assessment of the prevalence and incidence of AG in populations. Case report: An 8-year-old male patient with no history of epilepsy and no need for antiepileptic therapy underwent surgery for a left-parietal brain lesion, revealed through MRI. Imaging was acquired after his first absence episode. The lesion was completely resected. Histological findings indicated angiocentric glioma. No signs of recurrency after two years of follow-up. Conclusion: AG is usually an epilepsy-related low-grade glioma. Few cases exhibit disease progression and exitus. Surgical management should aim for a gross total resection to avoid recurrence and persisting epilepsy. Surgery represents the gold standard in diagnosis and treatment and must be performed as soon as possible in consideration of its healing properties and its useful diagnosis.
Effects of Nitrogen Sources on Primary and Secondary Production from Annual Temperate and Tropical Pastures in Southern Brazil
Authors: da Silva Marcelo Ascoli , Simões Vicente José Laamon Pinto , Silveira Diógenes Cecchin , Savian Jean Victor , Kunrath Taíse Robinson , Duarte Lóren Pacheco , Coser Thais Rodrigues , Junklewitz Petra , de Faccio Carvalho Paulo César
Published: June 2024

Improvements in nitrogen use efficiency can be achieved through fertilizer management strategies that capitalize on nutrient synergies. However, limited research on synergies between nitrogen, sulfur, and calcium complicates understanding causal links and developing sustainable management. In this regard, the effects of different nitrogen sources on productivity and nitrogen use efficiency in Italian ryegrass (Lolium multiflorum Lam.) and pearl millet (Pennisetum glaucum (L.)), along with their impacts on forage quality and secondary production, were investigated. Treatments included: Urea (46% N), ammonium nitrate (NH4NO3; 32% N), ammonium nitrate supplemented with calcium and sulfur (NH4NO3 (+), 27% N + 5% Ca + 3.7% S), and control treatment with no N application. The application of fertilizers that combine nitrogen with calcium and sulfur enhances primary production in both winter and summer pastures. Fertilization with NH4NO3 (+) increased nitrogen use efficiency by 125% in Italian ryegrass compared to NH4NO3. However, within the framework of rotatinuous grazing management principles, optimizing plant nitrogen use efficiency does not necessarily lead to a better forage quality or animal performance. These findings highlight that using fertilizers that promote synergies among nutrients, such as the combination of nitrogen with calcium and sulfur, can bring benefits to the sustainability of pasture-based livestock production systems.
Obesity Increases Maternal Complications in Pregnant Women of Sinop: A Retrospective Cohort Study
Authors: Pinheiro Lilian G. V. , Sanches Nathalia M. , Soares Catharine L. R. , Lima Bruna L. O. , Ramos Eduarda B. , Ferreira Mariany S. , Loiola Matheus O. , Silva Rafaella R. , Prates João Sérgio N. , Silva Viviani C. , Queiroz Diogo A. , Queiroz Eveline A. I. F.
Published: June 2024

Obesity is a chronic metabolic disease that can promote serious comorbidities as maternal complications. Thus, the objective of this study was to analyze the prevalence of overweight and obesity, and the incidence of maternal complications in pregnant women of Sinop, Mato Grosso, Brazil. It was a retrospective cohort study with clinical and epidemiological data collected from the medical records of pregnant women diagnosed in 2020. Pregnant women were subdivided into three groups: eutrophic, overweight, and obese. Data from 700 pregnant women were evaluated, 251 in the eutrophic group, in the 220 overweight group and 229 in the obese group. The percentage of pregnant women with diabetes mellitus and arterial hypertension was significantly higher in the overweight and obesity groups when compared with the eutrophic group. The incidence of gestational diabetes mellitus was significantly higher in the overweight and obese groups when compared with the eutrophic group (p < 0.0001). The incidence of gestational arterial hypertension was also significantly higher in the overweight (6.8%) and obese (12.7%) groups when compared with the eutrophic group (1.2%) (p < 0.0001). The incidence of pre-eclampsia was also higher and statistically different in the overweight and obese groups. In conclusion, it was observed that most of the pregnant women presented with overweight/obesity and that this excess body weight contributed significantly to the incidence of several maternal complications.
Can Tumour Antigens Act as Biomarkers for the Early Detection of Non-Small Cell Lung Cancer?
Authors: Mohamed Eithar , Fletcher Daniel , Hart Simon , Guinn Barbara-ann
Published: June 2024

Lung cancer (LC) is one of the leading causes of cancer-related deaths. Pulmonary nodules are one of the risk factors, and their discovery rate has been increasing due to enhanced performance of chest CT scans, but more than 90% are non-malignant, causing unnecessary stress to patients and costs to healthcare providers. Early diagnosis of LC is associated with a 5-year survival rate of up to 75% following surgical resection, but LC is often diagnosed late due to a lack of symptoms and poor 5-year survival rates as low as 10%. The cost of LC diagnosis is high, with 40% of it associated with benign lesions, which are difficult to differentiate from malignant lesions. Tumour-associated antigens (TAAs) may provide one way in which LC could be diagnosed early using minimally-invasive techniques, under their association with immune responses and specificity for disease. Here we discuss the potential of cancer-testis antigens (CTAs) to act as non-invasive biomarkers for the early detection of non-small cell lung cancer.
Africa, ChatGPT, and Generative AI Systems: Ethical Benefits, Concerns, and the Need for Governance
Authors: Wakunuma Kutoma , Eke Damian
Published: June 2024

This paper examines the impact and implications of ChatGPT and other generative AI technologies within the African context while looking at the ethical benefits and concerns that are particularly pertinent to the continent. Through a robust analysis of ChatGPT and other generative AI systems using established approaches for analysing the ethics of emerging technologies, this paper provides unique ethical benefits and concerns for these systems in the African context. This analysis combined approaches such as anticipatory technology ethics (ATE), ethical impact assessment (EIA), and ethical issues of emerging ICT applications with AI (ETICA) with specific issues from the literature. The findings show that ChatGPT and other generative AI systems raise unique ethical concerns such as bias, intergenerational justice, exploitation of labour and cultural diversity in Africa but also have significant ethical benefits. These ethical concerns and benefits are considered crucial in shaping the design and deployment of ChatGPT and similar technologies responsibly. It further explores the potential applications of ChatGPT in critical domain areas such as education, agriculture, and healthcare, thereby demonstrating the transformative possibilities that these technologies can have on Africa. This paper underscores the critical role of AI governance as Africa increasingly adopts ChatGPT and similar AI systems. It argues that a comprehensive understanding of AI governance is essential not only for maximising the benefits of generative AI systems but also for facilitating a global dialogue. This dialogue aims to foster shared knowledge and insights between the Global North and the Global South, which is important for the development and creation of inclusive and equitable AI policies and practices that can be beneficial for all regions.
Shallow Trench Isolation Patterning to Improve Photon Detection Probability of Single-Photon Avalanche Diodes Integrated in FD-SOI CMOS Technology
Authors: Gao Shaochen , Vu Duc-Tung , Cazimajou Thibauld , Pittet Patrick , Le Berre Martine , Dolatpoor Lakeh Mohammadreza , Mandorlo Fabien , Orobtchouk Régis , Schell Jean-Baptiste , Kammerer Jean-Baptiste , Cathelin Andreia , Golanski Dominique , Uhring Wilfried , Calmon Francis
Published: June 2024

The integration of Single-Photon Avalanche Diodes (SPADs) in CMOS Fully Depleted Silicon-On-Insulator (FD-SOI) technology under a buried oxide (BOX) layer and a silicon film containing transistors makes it possible to realize a 3D SPAD at the chip level. In our study, a nanostructurated layer created by an optimized arrangement of Shallow Trench Isolation (STI) above the photosensitive zone generates constructive interferences and consequently an increase in the light sensitivity in the frontside illumination. A simulation methodology is presented that couples electrical and optical data in order to optimize the STI trenches (size and period) and to estimate the Photon Detection Probability (PDP) gain. Then, a test chip was designed, manufactured, and characterized, demonstrating the PDP improvement due to the STI nanostructuring while maintaining a comparable Dark Count Rate (DCR).
A Terahertz Programmable Digital Metasurface Based on Vanadium Dioxide
Authors: Pan Tianrui , Liu Chenxi , Peng Shuang , Lu Haiying , Zhang Han , Xu Xiaoming , Yang Fei
Published: June 2024

Metasurfaces can realize the flexible manipulation of electromagnetic waves, which have the advantages of a low profile and low loss. In particular, the coding metasurface can flexibly manipulate electromagnetic waves through controllable sequence encoding of the coding units to achieve different functions. In this paper, a three-layer active coding metasurface is designed based on vanadium dioxide (VO2), which has an excellent phase transition. For the designed unit cell, the top patterned layer is composed of two split square resonant rings (SSRRs), whose gaps are in opposite directions, and each SSRR is composed of gold and VO2. When VO2 changes from the dielectric state to the metal state, the resonant mode changes from microstrip resonance to LC resonance, correspondingly. According to the Pancharatnam-Berry (P-B) phase, the designed metasurface can actively control terahertz circularly polarized waves in the near field. The metasurface can manipulate the order of the generated orbital angular momentum (OAM) beams: when the dielectric VO2 changes to metal VO2, the order l of the OAM beams generated by the metasurface changes from −1 to −2, and the purity of the generated OAM beams is relatively high. It is expected to have important application values in terahertz wireless communication, radar, and other fields.
A Multi-Parameter Tunable and Compact Plasmon Modulator in the Near-Infrared Spectrum
Authors: Hu Xuefang , Wang Hongfei , Yang Sisi , Lu Changgui , Zhao Xiangyue , Lu Mengjia
Published: June 2024

To keep pace with the demands of modern photonic integration technology, the electro-optic modulator should feature multi-parameter tunable components and a compact size. Here, we propose a hybrid structure that can modulate the multi-parameters of surface plasmon polaritons (SPPs) simultaneously with a compact size by controlling the electron concentration of indium tin oxide (ITO) in the near-infrared spectrum. The length, width and height of the device are only 15 μm, 5 μm and 9 μm, respectively. The numerical results show that when the electron concentration in ITO changes from 7.5 × 1026 m−3 to 9.5 × 1026 m−3, the variation in amplitude, wavelength and phase are 49%, 300 nm and 347°, respectively. The demonstrated structure paves a new way for multi-parameter modulation and the realization of ultracompact modulators.
Enhancement of Mosquito Collection for Ultraviolet Light-Emitting Diodes Trapping System Using Cavity Reflectors
Authors: Chang Jui-Chen , Chen Yi-Chian , Lu Wei-Yu , Nguyen Xuan-Huy , Lee Hsiao-Yi
Published: June 2024

This research explores novel avenues for optimizing mosquito-catching efficiency using a multifaceted approach. While previous studies have primarily focused on singular parameters, such as light intensity or wind speed, this study delves into the intricate interplay between various factors. Experiment 1 challenges conventional wisdom by revealing a wider light divergence angle. When the reflective plate combined with the airflow board was set to 0 cm in length, the effectiveness of capturing mosquitoes was lower than that of the 3 cm unit, suggesting overlooked variables at play. Experiment 2 introduces a novel perspective by demonstrating the superior efficiency of the 5 cm unit, even with reduced wind speed and luminous area under optimized conditions, showcasing the significance of a holistic approach. Moreover, Experiment 3 uncovers nuanced insights, showcasing the differential performance of units in capturing small insects versus mosquitoes and moths, highlighting the need for tailored strategies. By integrating these findings, the study pioneers the development of two distinct mosquito collection units, emphasizing the critical importance of balancing diverse parameters for optimal results. The innovation lies in the thorough investigation of multifaceted optimization strategies, providing valuable insights to propel advancements in mosquito control technologies.
In Situ Structural Characterization of Cardiomyocyte Microenvironment by Multimodal STED Microscopy
Authors: Zhang Zhao , Gao Bruce Z. , Ye Tong
Published: June 2024

Within the myocardium, cardiomyocytes reside in a complex and dynamic extracellular matrix (ECM) consisting of a basement membrane (BM) and interstitial matrix. The interactions between cardiomyocytes and the myocardial ECM play a critical role in maintaining cardiac geometry and function throughout cardiac development and in adult hearts. Understanding how the structural changes of the myocardial ECM affect cardiomyocyte function requires knowledge of pericellular structures. These structures are of a size beyond the resolution of conventional optical microscopy. Here, we demonstrated multi-scale and multi-aspect characterization of the cardiomyocyte microenvironment in myocardial tissue sections using multimodal stimulated emission depletion (STED) microscopy. Second harmonic generation and autofluorescence facilitated multiplexed imaging, enabling the interpretation of protein distribution in 3D. STED imaging modality revealed BM structures of cardiomyocytes and myocardial capillaries at the subdiffractional level. Moreover, meaningful measurements retrieved from acquired images, such as sarcomere length and capillary density, enabled quantitative assessment of myocardial structures.
Resilience of Canola to Plasmodiophora brassicae (Clubroot) Pathotype 3H under Different Resistance Genes and Initial Inoculum Levels
Authors: Wen Rui , Song Tao , Tonu Nazmoon Naher , Franke Coreen , Peng Gary
Published: June 2024

In this study, we explored the resilience of a clubroot resistance (CR) stacking model against a field population of Plasmodiophora brassicae pathotype 3H. This contrasts with our earlier work, where stacking CRaM and Crr1rutb proved only moderately resistant to pathotype X. Canola varieties carrying Rcr1/Crr1rutb and Rcr1 + Crr1rutb were repeatedly exposed to 3H at low (1 × 104/g soil) and high (1 × 107/g soil) initial resting spore concentrations over five planting cycles under controlled environments to mimic intensive canola production. Initially, all resistant varieties showed strong resistance. However, there was a gradual decline in resistance over time for varieties carrying only a single CR gene, particularly with Crr1rutb alone and at the high inoculum level, where the disease severity index (DSI) increased from 9% to 39% over five planting cycles. This suggests the presence of virulent pathotypes at initially low levels in the 3H inoculum. In contrast, the variety with stacked CR genes remained resilient, with DSI staying below 3% throughout, even at the high inoculum level. Furthermore, the use of resistant varieties, carrying either a single or stacked CR genes, reduced the total resting spore numbers in soil over time, while the inoculum level either increased or remained high in soils where susceptible Westar was continuously grown. Our study demonstrates greater resistance resilience for stacking Rcr1 and Crr1rutb against the field population of 3H. Additionally, the results suggest that resistance may persist even longer in fields with lower levels of inoculum, highlighting the value of extended crop rotation (reducing inoculum) alongside strategic CR-gene deployment to maximize resistance resilience.
The Spatial Shifts and Vulnerability Assessment of Ecological Niches under Climate Change Scenarios for Betula luminifera, a Fast-Growing Precious Tree in China
Authors: Hu Xian-Ge , Chen Jiahui , Chen Qiaoyun , Yang Ying , Lin Yiheng , Jin Zilun , Sha Luqiong , Lin Erpei , Yousry El-Kassaby , Huang Huahong
Published: June 2024

The spatial shifts and vulnerability assessments of ecological niches for trees will offer fresh perspectives for sustainable development and preservation of forests, particularly within the framework of rapid climate change. Betula luminifera is a fast-growing native timber plantation species in China, but the natural resources have been severely damaged. Here, a comprehensive habitat suitability model (including ten niche-based GIS modeling algorithms) was developed that integrates three types of environmental factors, namely, climatic, soil, and ultraviolet variables, to assess the species contemporary and future distribution of suitable habitats across China. Our results suggest that the habitats of B. luminifera generally occur in subtropical areas (about 1.52 × 106 km2). However, the growth of B. luminifera is profoundly shaped by the nuances of its local environment, the most reasonable niche spaces are only 1.15 × 106 km2 when limiting ecological factors (soil and ultraviolet) are considered, generally considered as the core production region. Furthermore, it is anticipated that species-suitable habitats will decrease by 10 and 8% with climate change in the 2050s and 2070s, respectively. Our study provided a clear understanding of species-suitable habitat distribution and identified the reasons why other niche spaces are unsuitable in the future, which can warn against artificial cultivation and conservation planning.
Trends and Prospects of Genetic and Molecular Research in Plants
Authors: Jung Yu Jin , Kim Me-Sun , Cho Yong-Gu
Published: June 2024

With the exponential advancements in biotechnology research, various studies are being conducted to overcome productivity limitations in crop breeding [...]