bluuebunny/crossref_metadata_2025 huggingface dataset:
Advances in Molecular Breeding of Forage Crops: Technologies, Applications and Prospects
Authors: Chen Shuangyan
Published: February 2024

Molecular breeding has revolutionized the improvement of forage crops by offering precise tools to enhance the yield, quality, and environmental resilience. This review provides a comprehensive overview of the current technologies, applications, and future directions in the field of forage crop molecular breeding. Technological advancements in the field, including Quantitative Trait Loci (QTL) mapping, Genome-Wide Association Studies (GWASs), genomic selection (GS), and genome-editing tools such as CRISPR-Cas9, have significantly advanced the identification and incorporation of beneficial traits into forage species. These approaches have dramatically shortened the breeding cycles and increased the efficiency of developing cultivars with improved yield, disease resistance, stress tolerance, and nutritional profiles. The implementation of these technologies has led to notable successes, as demonstrated by case studies on various forage crops, showcasing enhanced forage quality and adaptability to challenging environmental conditions. Furthermore, the integration of high-throughput phenotyping with advanced bioinformatics tools has streamlined the management of large-scale genomic data, facilitating more precise selection and breeding decisions. Looking ahead, this review explores the potential of emerging technologies, such as the application of artificial intelligence in predictive breeding, along with the associated ethical and regulatory considerations. While we stand to gain benefit from these innovations, the future of molecular breeding in forage crops must also confront the challenges posed by climate change and the imperative of sustainable agricultural practices. This review concludes by emphasizing the transformative impact of molecular breeding on the improvement of forage crop and the critical need for ongoing research and collaboration to fully realize its potential.
Occurrence of Eimeria spp. and Intestinal Helminths in Free-Range Chickens from Northwest and Central Romania
Authors: Coroian Mircea , Fábián-Ravasz Tünde-Zsuzsánna , Dobrin Patricia Roxana , Györke Adriana
Published: February 2024

Chickens raised in backyard free-range systems are confronted with a significant threat of parasitic infections. Among the parasitic agents, protozoa belonging to the genus Eimeria and helminths, including Ascaridia galli, Capillaria spp., Heterakis gallinarum, and Strongyloides avium, stand out as the most prevalent. The sampling protocol included sixteen localities in four counties within the Transylvania region of Romania. Fecal samples were collected from chickens reared in a backyard system. Fecal samples were screened for oocysts (O) and eggs (E) by flotation method, and their number per gram of feces (OPG/EPG) was calculated after counting them by McMaster method. Positive samples for Eimeria spp. were further analyzed by PCR (polymerase chain reaction) method to identify the Eimeria species. A total of 145 flocks were tested and the overall prevalence of infection was 53.1%. The most prevalent infections were with A. galli/H. gallinarum (25.5%), and Eimeria spp. (24.8%), followed by Capillaria spp. and strongyles. The mean OPG/EPG values were as follows: 63,577 for Eimeria spp., 157 for Ascaridia/Heterakis, 362 for Capillaria spp., and 1671 for Strongyle eggs. Identified Eimeria species were E. acervulina (41.7%), E. tenella (27.8%), E. praecox (16.7%), E. brunetti (16.7%), OTUy (operational taxonomic unit y) (8.3%), OTUz (operational taxonomic unit z) (8.3%) and E. mitis (5.6%). Intestinal parasites exhibit a high prevalence among chickens in backyard poultry flocks, and the presence of significant parasite burdens can adversely affect both productive and economic aspects. To the best of our knowledge, this is the first comprehensive study that aimed to analyze the prevalence of gastrointestinal parasites in chickens raised in a backyard free-range system in Romania, and the first report of OTUy species in Europe.
A Review of Potential Feed Additives Intended for Carbon Footprint Reduction through Methane Abatement in Dairy Cattle
Authors: Hodge Ian , Quille Patrick , O’Connell Shane
Published: February 2024

Eight rumen additives were chosen for an enteric methane-mitigating comparison study including garlic oil (GO), nitrate, Ascophyllum nodosum (AN), Asparagopsis (ASP), Lactobacillus plantarum (LAB), chitosan (CHI), essential oils (EOs) and 3-nitrooxypropanol (3-NOP). Dose-dependent analysis was carried out on selected feed additives using a meta-analysis approach to determine effectiveness in live subjects or potential efficacy in live animal trials with particular attention given to enteric gas, volatile fatty acid concentrations, and rumen microbial counts. All meta-analysis involving additives GO, nitrates, LAB, CHI, EOs, and 3-NOP revealed a reduction in methane production, while individual studies for AN and ASP displayed ruminal bacterial community improvement and a reduction in enteric CH4. Rumen protozoal depression was observed with GO and AN supplementation as well as an increase in propionate production with GO, LAB, ASP, CHI, and 3-NOP rumen fluid inoculation. GO, AN, ASP, and LAB demonstrated mechanisms in vitro as feed additives to improve rumen function and act as enteric methane mitigators. Enzyme inhibitor 3-NOP displays the greatest in vivo CH4 mitigating capabilities compared to essential oil commercial products. Furthermore, this meta-analysis study revealed that in vitro studies in general displayed a greater level of methane mitigation with these compounds than was seen in vivo, emphasising the importance of in vivo trials for final verification of use. While in vitro gas production systems predict in vivo methane production and fermentation trends with reasonable accuracy, it is necessary to confirm feed additive rumen influence in vivo before practical application.
An Improved Adaptive Iterative Extended Kalman Filter Based on Variational Bayesian
Authors: Fu Qiang , Wang Ling , Xie Qiyue , Zhou Yucai
Published: February 2024

The presence of unknown heavy-tailed noise can lead to inaccuracies in measurements and processes, resulting in instability in nonlinear systems. Various estimation methods for heavy-tailed noise exist. However, these methods often trade estimation accuracy for algorithm complexity and parameter sensitivity. To tackle this challenge, we introduced an improved variational Bayesian (VB)-based adaptive iterative extended Kalman filter. In this VB framework, the inverse Wishart distributionis used as the prior for the state prediction covariance matrix. The system state and noise parameter posterior distributions are then iteratively updated for adaptive estimation. Furthermore, we make adaptive adjustments to the IEKF filter parameters to enhance sensitivity and filtering accuracy, thus ensuring robust prediction estimation. A two-dimensional target tracking and nonlinear numerical UNGM simulation validated our algorithm. Compared to existing algorithms RKF-ML and GA-VB, our method showed significant improvements in RMSEpos and RMSEvel, with increases of 21.81% and 22.11% respectively, and a 49.04% faster convergence speed. These results highlight the method’s reliability and adaptability.
Arsenic in a Karstic Paddy Soil with a High Geochemical Background in Guangxi, China: Its Bioavailability and Controlling Factors
Authors: Li Xuezhen , Ma Xudong , Hou Qingye , Xia Xueqi , Li Bo , Lin Kun , Liu Xu , Wu Zhiliang , Ji Wenbing , Wang Lei , Yu Tao , Yang Zhongfang
Published: February 2024

Arsenic (As) is of widespread concern, as its elevated contents in soil and water have a serious impact on the ecological environment and human health. Soils in karst regions are characterized by a high geochemical background of As. However, the bioavailability of As in paddy soils and the potential risk of As transfer from the soil to rice remain unclear. In this study, 305 paired soil–rice samples were collected from karst regions in Guangxi, China, in order to examine the controlling variables and As bioavailability in the soil–rice system. According to this study, the karst region’s paddy soil had higher As concentrations than the non-karst region’s paddy soil. The As concentration in the rice grains was low, with only 0.62% of the rice samples exceeding the permissible value of inorganic As (0.2 mg/kg). Arsenic in the karstic paddy soils existed mainly in the residual fraction, while the water-soluble and exchangeable fractions, which are readily absorbed by rice, accounted for a relatively small proportion. The high content but low bioavailability of As in the karstic paddy soil was mostly attributed to the abundant Fe–Mn nodules, which contributed 64.45% of the As content in the soil. Within the Fe–Mn nodules, As was primarily bound to Fe-(oxyhydr)oxides, which could be released into the paddy soil under certain reduction conditions via the reductive dissolution of Fe-(oxyhydr)oxides. Under the natural pH conditions of the karstic paddy soil (pH 4.9–8.38), the leaching of As was almost negligible, and As could be steadily retained within the Fe–Mn nodules. However, extremely acidic or alkaline conditions promoted the release of As from the Fe–Mn nodules.
Evaluation of Machine Learning Models for Ozone Concentration Forecasting in the Metropolitan Valley of Mexico
Authors: Domínguez-García Rodrigo , Arellano-Vázquez Magali
Published: February 2024

In large and densely populated cities, the concentration of pollutants such as ozone and its dispersion is related to effects on people’s health; therefore, its forecast is of great importance to the government and the population. Given the increased computing capacity that allows for processing massive amounts of data, the use of machine learning (ML) as a tool for air quality analysis and forecasting has gotten a significant boost. This research focuses on evaluating different models, such as Random Forest (RF), Support Vector Regression (SVR), and Gradient Boosting (GB), to forecast ozone (O3) concentration 24 h in advance, using data from the Mexico City Atmospheric Monitoring System using meteorological variables that influence the phenomenon of ozone dispersion and formation.
Interacting with Smart Virtual Assistants for Individuals with Dysarthria: A Comparative Study on Usability and User Preferences
Authors: Jaddoh Aisha , Loizides Fernando , Rana Omer , Syed Yasir Ahmed
Published: February 2024

This study explores the effectiveness and user experience of different interaction methods used by individuals with dysarthria when engaging with Smart Virtual Assistants (SVAs). It focuses on three primary modalities: direct speech commands through Alexa, non-verbal voice cues via the Daria system, and eye gaze control. The objective is to assess the usability, workload, and user preferences associated with each method, catering to the varying communication capabilities of individuals with dysarthria. While Alexa and Daria facilitate voice-based interactions, eye gaze control offers an alternative for those unable to use voice commands, including users with severe dysarthria. This comparative approach aims to determine how the usability of each interaction method varies, conducted with eight participants with dysarthria. The results indicated that non-verbal voice interactions, particularly with the Daria system, were favored because of their lower workload and ease of use. The eye gaze technology, while viable, presented challenges in terms of the higher workload and usability. These findings highlight the necessity of diversifying interaction methods with SVAs to accommodate the unique needs of individuals with dysarthria.
New Methods for Assessing External Sulfate Attack on Cement-Based Specimens
Authors: Omikrine Metalssi Othman , Quiertant Marc , Jabbour Mike , Baroghel-Bouny Véronique
Published: February 2024

This paper presents two original methods for monitoring and evaluating concrete specimens/structures affected by external sulfate attack (ESA). The first is a drying method developed to assess the penetration depth of sulfate ions in a concrete structure, as this parameter is a relevant indicator of the progress of the ESA. This method has been specifically designed for on-site investigations. The second experimental method involves the use of optical fibers capable of measuring the swelling response of specimens to ESA in real time. According to the results obtained, these two new methods seem likely to be used to complement or replace traditional methods such as inductively coupled plasma (ICP) for determining the penetration depth of sulfate ions or as extensometers for measuring swelling. These traditional methods (ICP and extensometers) are generally considered painful and time-consuming, whereas, because of its simplicity, the proposed drying method will enable experts to regularly inspect concrete structures and make informed decisions on the measures to be taken to repair or prevent further damage induced by ESA, while the second method appears promising for experimental studies involving the monitoring of a large number of ESA-affected specimens.
A Novel Approach to Swell Mitigation: Machine-Learning-Powered Optimal Unit Weight and Stress Prediction in Expansive Soils
Authors: Alnmr Ammar , Ray Richard , Alzawi Mounzer Omran
Published: February 2024

Expansive soils pose significant challenges to structural integrity, primarily due to volumetric changes that can lead to detrimental consequences and substantial economic losses. This study delves into the intricate dynamics of expansive soils through loaded swelling pressure experiments conducted under diverse conditions, encompassing variations in the sand content, initial dry unit weight, and initial degree of saturation. The findings underscore the pronounced influence of these factors on soil swelling. To address these challenges, a novel method leveraging machine learning prediction models is introduced, offering an efficient and cost-effective framework to mitigate potential hazards associated with expansive soils. Employing advanced algorithms such as decision tree regression (DTR), random forest regression (RFR), gradient boosting regression (GBR), extreme gradient boosting (XGBoost), support vector regression (SVR), and artificial neural networks (ANN) in the Python software 3.11 environment, this study aims to predict the optimal applied stress and dry unit weight required for soil swelling mitigation. Results reveal that XGBoost and ANN stand out for their precision and superior metrics. While both performed well, ANN demonstrated exceptional consistency across training and testing phases, making it the preferred choice. In the tested dataset, ANN achieved the highest R-squared values (0.9917 and 0.9954), lowest RMSE (7.92 and 0.086), and lowest MAE (5.872 and 0.0488) for predicting optimal applied stress and dry unit weight, respectively.
Optimizing Controls to Track Moving Targets in an Intelligent Electro-Optical Detection System
Authors: Shen Cheng , Wen Zhijie , Zhu Wenliang , Fan Dapeng , Ling Mingyuan
Published: February 2024

Electro-optical detection systems face numerous challenges due to the complexity and difficulty of targeting controls for “low, slow and tiny” moving targets. In this paper, we present an optimal model of an advanced n-step adaptive Kalman filter and gyroscope short-term integration weighting fusion (nKF-Gyro) method with targeting control. A method is put forward to improve the model by adding a spherical coordinate system to design an adaptive Kalman filter to estimate target movements. The targeting error formation is analyzed in detail to reveal the relationship between tracking controller feedback and line-of-sight position correction. Based on the establishment of a targeting control coordinate system for tracking moving targets, a dual closed-loop composite optimization control model is proposed. The outer loop is used for estimating the motion parameters and predicting the future encounter point, while the inner loop is used for compensating the targeting error of various elements in the firing trajectory. Finally, the modeling method is substituted into the disturbance simulation verification, which can monitor and compensate for the targeting error of moving targets in real time. The results show that in the optimal model incorporating the nKF-Gyro method with targeting control, the error suppression was increased by up to 36.8% compared to that of traditional KF method and was 25% better than that of the traditional nKF method.
A SIR Epidemic Model Allowing Recovery
Authors: Pakes Anthony G.
Published: February 2024

The deterministic SIR model for disease spread in a closed population is extended to allow infected individuals to recover to the susceptible state. This extension preserves the second constant of motion, i.e., a functional relationship of susceptible and removed numbers, S(t) and R(t), respectively. This feature allows a substantially complete elucidation of qualitative properties. The model exhibits three modes of behaviour classified in terms of the sign of −S′(0), the initial value of the epidemic curve. Model behaviour is similar to that of the SIS model if S′(0)>0 and to the SIR model if S′(0)<0. The separating case is completely soluble and S(t) is constant-valued. Long-term outcomes are determined for all cases, together with determination of the rate of convergence. Determining the shape of the epidemic curve motivates an investigation of curvature properties of all three state functions and quite complete results are obtained that are new, even for the SIR model. Finally, the second threshold theorem for the SIR model is extended in refined and generalised forms.
Structures of Toxic Advanced Glycation End-Products Derived from Glyceraldehyde, A Sugar Metabolite
Authors: Sakai-Sakasai Akiko , Takeda Kenji , Suzuki Hirokazu , Takeuchi Masayoshi
Published: February 2024

Advanced glycation end-products (AGEs) have recently been implicated in the onset/progression of lifestyle-related diseases (LSRDs); therefore, the suppression of AGE-induced effects may be used in both the prevention and treatment of these diseases. Various AGEs are produced by different biological pathways in the body. Glyceraldehyde (GA) is an intermediate of glucose and fructose metabolism, and GA-derived AGEs (GA-AGEs), cytotoxic compounds that accumulate and induce damage in mammalian cells, contribute to the onset/progression of LSRDs. The following GA-AGE structures have been detected to date: triosidines, GA-derived pyridinium compounds, GA-derived pyrrolopyridinium lysine dimers, methylglyoxal-derived hydroimidazolone 1, and argpyrimidine. GA-AGEs are a key contributor to the formation of toxic AGEs (TAGE) in many cells. The extracellular leakage of TAGE affects the surrounding cells via interactions with the receptor for AGEs. Elevated serum levels of TAGE, which trigger different types of cell damage, may be used as a novel biomarker for the prevention and early diagnosis of LSRDs as well as in evaluations of treatment efficacy. This review provides an overview of the structures of GA-AGEs.
Strain Characteristics of Large-Size Non-Studded Concrete-Filled Steel Tube Column under Construction
Authors: Zhang Zhenyu , Jia Zhensheng , Jin Quan , Zhang Haitao , Mei Dongping , Zhang Huifeng , Mao Jin , Xiong Lun
Published: February 2024

Interplay between the outer steel tubes and the core concrete provides an important guarantee for the superior performance of concrete-filled steel tube (CFST) columns compared to that of reinforced concrete columns. In order to optimize the construction of the large-size non-studded CFST columns in an on-going practical project, the strain distributions in the column under construction were measured and tracked, and the law of the strain distributions of the column under construction is revealed. The study finds that the plane section assumption was not applicable to the strain distributions of the column. Nonlinear variations in the strain levels were observed under bi-directional bending of the column. The absence of studs inside the steel tube significantly weakened the interplay of the outer steel tube and the core concrete by means of a significant slip between the concrete and the steel tube at the column corners. The concrete and the steel tube tended to be stressed and deformed independently. Practical suggestions are given for the design and construction of this type of column. The study results are expected to lay a basic and valuable foundation for in-depth investigations on the mechanical behavior of large-size non-studded concrete-filled steel tube columns under construction.
Healing Spaces as a Design Approach to Optimize Emotional Regulation for Patients with Mood Disorders
Authors: Yan Shuaijie , Azmi Athira , Mansor Noranita , Wang Zhihao , Wang Yike
Published: February 2024

Healing spaces have played an important role in human history as arenas for healing and restoration of physical health. Current research from across disciplines identifies that engagement with space for people with mental illness can reduce emotional stress and thus improve health. This research leads to the central question of this paper: How do people with mood disorders achieve emotional regulation through healing spaces? In response to this question, this paper investigates the effects of sensory experience and architectural space on emotion regulation, with a particular focus on healing spaces. It proposes a model to analyze and explain how the design and use of healing spaces can create emotional experiences that stimulate patients’ senses and facilitate emotional regulation in individuals with mood disorders. The study emphasizes the importance of understanding how elements of healing spaces affect patients’ senses and contribute to the quality of emotion regulation. The paper argues that healing structures can effectively enhance the emotional experience of a space by creating a positive spatial atmosphere, thereby aiding in the healing process for patients with mood disorders. This paper’s analysis of the existing literature identifies key mechanisms by which healing spaces promote emotion regulation-healing structures-and breaks them down into three main structures: (a) Safety Guarantees Physical and Mental Development; (b) Functionality Supports the Treatment Process; (c) Ambiance Promotes Emotional Comfort, this study examines existing evidence to determine how healing structures promote emotionally regulated treatment. The study also explores representative examples of healing spaces and how they utilize spatial elements to stimulate the patient’s senses. This research results show that healing structures directly influence or facilitate eight primary spatial elements (color and form, light, sound, air and temperature, nature, materials, play and games, and activity and communication) which incorporate one or more dimensions of healing. Therefore, this paper aims to enhance our understanding and awareness of the correlation between interior space, human senses, and healing structures.
Filamin A Is a Prognostic Serum Biomarker for Differentiating Benign Prostatic Hyperplasia from Prostate Cancer in Caucasian and African American Men
Authors: Mahaveer Chand Nischal , Tekumalla Poornima K. , Rosenberg Matt T. , Dobi Albert , Ali Amina , Miller Gregory M. , Aristizabal-Henao Juan J. , Granger Elder , Freedland Stephen J. , Kellogg Mark D. , Srivastava Shiv , McLeod David G. , Narain Niven R. , Kiebish Michael A.
Published: February 2024

Prostate cancer represents a significant health risk to aging men, in which diagnostic challenges to the identification of aggressive cancers remain unmet. Prostate cancer screening is driven by the prostate-specific antigen (PSA); however, in men with benign prostatic hyperplasia (BPH) due to an enlarged prostate and elevated PSA, PSA’s screening utility is diminished, resulting in many unnecessary biopsies. To address this issue, we previously identified a cleaved fragment of Filamin A (FLNA) protein (as measured with IP-MRM mass spectrometry assessment as a prognostic biomarker for stratifying BPH from prostate cancer and subsequently evaluated its expanded utility in Caucasian (CA) and African American (AA) men. All men had a negative digital rectal examination (DRE) and PSA between 4 and 10 ng/mL and underwent prostate biopsy. In AA men, FLNA serum levels exhibited diagnostic utility for stratifying BPH from patients with aggressive prostate cancer (0.71 AUC and 12.2 OR in 48 men with BPH and 60 men with PCa) and outperformed PSA (0.50 AUC, 2.2 OR). In CA men, FLNA serum levels also exhibited diagnostic utility for stratifying BPH from patients with aggressive prostate cancer (0.74 AUC and 19.4 OR in 191 men with BPH and 109 men with PCa) and outperformed PSA (0.46 AUC, 0.32 OR). Herein, we established FLNA alone as a serum biomarker for stratifying men with BPH vs. those with high Gleason (7–10) prostate cancers compared to the current diagnostic paradigm of using PSA. This approach demonstrates clinical actionability of FLNA alone without the requirement of prostate volume measurement as a test with utility in AA and CA men and represents a significant opportunity to decrease the number of unnecessary biopsies in aggressive prostate cancer diagnoses.
Study on the Degradation Effect of Tetracycline Using a Co-Catalyst Loaded on Red Mud
Authors: Yue Yang , Wu Qu , Zheng Chaofan , Sun Yongjun , Shah Kinjal J.
Published: February 2024

Red mud was modified by impregnation with Co element loading. The Co-RM catalyst was characterized using scanning electron microscopy (SEM), X-ray powder diffraction (XRD), X-ray fluorescence (XRF), and UV full-band scanning. The results showed that the modified Co-RM catalyst successfully loaded the Co element and formed an irregular pore structure on the surface, thereby increasing the number of active sites of the red mud catalyst and effectively improving the degradation efficiency of tetracycline. Under the optimal conditions of a catalyst dosage of 0.3 g/L, a persulfate dosage of 3 g/L, a reaction temperature of 50 °C, and a pH value of 7, a removal rate of 50 mg/L of tetracycline can be achieved: 89.5% after 90 min. The effects of common anions and humic acids in water, as well as radical quenchers (anhydrous ethanol and tert-butanol), on the degradation of tetracycline were investigated. The results showed that Cl−, CO32−, HCO3−, H2PO4−, NO32−, HPO42−, and humic acids showed inhibitory effects on the degradation of tetracycline, while SO42− showed a promoting effect on the degradation of tetracycline. The free radical quenching experiment showed that the most important free radicals that can degrade tetracycline in the system are sulfate radicals.
Vitamin D Level and Immune Modulation in Children with Recurrent Wheezing
Authors: Feketea Gavriela , Vassilopoulou Emilia , Andreescu Oana , Berghea Elena Camelia , Pop Raluca Maria , Sabin Octavia , Zdrenghea Mihnea , Bocsan Ioana Corina
Published: February 2024

Introduction and aim: A direct causal relationship between vitamin D (vit D) deficiency and recurrent wheezing has not been proven. The present study investigated the role of vit D in enhancing the risk of asthma or recurrent wheezing by modifying the intensity of the inflammatory process. Material and method: Forty children with wheezing presenting at the emergency service and sixteen healthy control subjects were included in the study. Children with wheezing were either in the first episode (20) or with recurrent wheezing (20). Children with chronic diseases, and other conditions that present with acute wheezing or that might influence the vit D level, were excluded. Blood samples were taken at presentation and 3–6 months later, to evaluate the serum levels of total IgE, vit D, IL-10 and IL-31. Statistical analysis was performed using the SPSS 25 program, with a significance level of p < 0.05. Results and conclusion. The vit D level was lower in patients with recurrent wheezing compared with those with a single episode and with the control group, and this increased with time. IL-10 was significantly higher in children with wheezing than in the control group, with the highest values in those with an acute episode of wheezing. IL-31 was higher in children with recurrent wheezing than in those with a first episode only at the initial point, while at the final time point it was lower. Low levels of vit D appear to be detected more frequently in recurrent wheezing than in simple wheezing. Immune modulation, as measured by Th2 status reflected by IL-10 and IL-31 levels, appears to depend on the wheezing phenotype and on the general health status.
The Complete Mitochondrial Genomes of Aelia sibirica and A. fieberi (Hemiptera, Pentatomidae), and Phylogenetic Implications
Authors: Liu Dajun , Zhang Hufang , Fu Shuhui , Wang Yating , Zhao Wanqing , Zhao Qing
Published: February 2024

Species of genus Aelia are important pests of wheat crops in arid areas. In this study, the mitogenomes of A. sibirica and A. fieberi were sequenced using high-throughput sequencing technology. The mitochondrial genome characteristics of both Aelia species were compared and analyzed, and the phylogenetic relationships of Pentatomidae were constructed based on protein-coding genes. In addition, the taxonomic status of the genus Aelia was confirmed. The results showed that the total length of the mitogenome sequences of A. sibirica and A. fieberi were 15,372 bp and 15,450 bp, respectively, including 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes, and a control region. By comparing the mitochondrial genome structure, base composition, codon usage, RNA secondary structure, and other characteristics, it was found that the mitochondrial genome characteristics of the two species were similar. Phylogenetic analysis showed that Phyllocephalinae and Asopinae both formed monophyletic groups, but the relationship between Podopinae and Pentatominae was not resolved. Within the subfamily Pentatominae, (Nezarini + Antestiini), (Aeliini + Carpocorini), and (Strachiini + Pentatoma) formed stable clades. Aelia sibirica and A. fieberi were found to be a stable sibling pair, and the clade was closely related to Dolycoris baccarum.
Multi-Beam Beamforming-Based ML Algorithm to Optimize the Routing of Drone Swarms
Authors: Myers Rodman J. , Perera Sirani M. , McLewee Grace , Huang David , Song Houbing
Published: February 2024

The advancement of wireless networking has significantly enhanced beamforming capabilities in Autonomous Unmanned Aerial Systems (AUAS). This paper presents a simple and efficient classical algorithm to route a collection of AUAS or drone swarms extending our previous work on AUAS. The algorithm is based on the sparse factorization of frequency Vandermonde matrices that correspond to each drone, and its entries are determined through spatiotemporal data of drones in the AUAS. The algorithm relies on multibeam beamforming, making it suitable for large-scale AUAS networking in wireless communications. We show a reduction in the arithmetic and time complexities of the algorithm through theoretical and numerical results. Finally, we also present an ML-based AUAS routing algorithm using the classical AUAS algorithm and feed-forward neural networks. We compare the beamformed signals of the ML-based AUAS routing algorithm with the ground truth signals to minimize the error between them. The numerical error results show that the ML-based AUAS routing algorithm enhances the accuracy of the routing. This error, along with the numerical and theoretical results for over 100 drones, provides the basis for the scalability of the proposed ML-based AUAS algorithms for large-scale deployments.
A Hardware Realization Framework for Fuzzy Inference System Optimization
Authors: Gorgin Saeid , Karvandi Mohammad Sina , Moghari Somaye , Fallah Mohammad K. , Lee Jeong-A
Published: February 2024

Fuzzy inference systems (FISs) are a key focus for decision-making in embedded systems due to their effectiveness in managing uncertainty and non-linearity. This study demonstrates that optimizing FIS hardware enhances performance, efficiency, and capabilities, improving user experience, heightened productivity, and cost savings. We propose an ultra-low power FIS hardware framework to address power constraints in embedded systems. This framework supports optimizations for conventional arithmetic and Most Significant Digit First (MSDF) computing, ensuring compatibility with MSDF-based sensors. Within the MSDF-computing FIS, fuzzification, inference, and defuzzification processes occur on serially incoming data bits. To illustrate the framework’s efficiency, we implemented it using MATLAB, Chisel3, and Vivado, starting from high-level FIS descriptions and progressing to hardware synthesis. A Scala library in Chisel3 was developed to connect these tools seamlessly, facilitating design space exploration at the arithmetic level. We applied the framework by realizing an FIS for autonomous mobile robot navigation in unknown environments. The synthesis results highlight the superiority of our designs over the MATLAB HDL code generator, achieving a 43% higher clock frequency, and 46% and 67% lower resource and power consumption, respectively.
Interaction between LMFP and NCMA and Its Effect on Blending Cathode-Based Cells
Authors: Liu Jingyuan , Chen Si , Kong Dewen , Wu Meiyuan , Liu Haijing
Published: February 2024

Li-ion cells with a LiMnxFe1−xPO4 (LMFP) and LiNi1−x−y−zCoxMnyAlzO2 (NCMA) blending cathode show their benefits of lower cost and higher safety compared to barely NCMA cathode-based cells. However, the rate capability of LMFP material is relatively poor compared to NCMA or even LiFePO4, which is because of the low electronic conductivity of LMFP material and the 1D diffusion channel in its structure. This work discusses the effect on electrochemical performance when blends of various ratios of LMFP are used in an NCMA cathode, with data verified by a 5 Ah pouch cell. This work further investigated the interaction between NCMA and LMFP during charge/discharge. Combining results from experiment and simulation, it evidences that blending more LMFP does not always lead to worse discharge rate but reduces charge rate. Moreover, it is found that, in a constant current discharge/charge process, although the system is under continuous discharge/charge, LMFP works intermittently. This leads to different diffusion polarization states of LMFP in the discharge/charge process and further results in a difference in discharge/charge rate capability. Therefore, to improve rate capability, especially charging rate, using smaller-sized or doped LMFP to improve its diffusion coefficient is an optimized strategy.
Enhancing the Storage Performance and Thermal Stability of Ni-Rich Layered Cathodes by Introducing Li2MnO3
Authors: Yang Jun , Yang Pingping , Wang Hongyu
Published: February 2024

Ni-rich layered cathodes are deemed as a potential candidate for high-energy-density lithium-ion batteries, but their high sensitivity to air during storage and poor thermal stability are a vital challenge for large-scale applications. In this paper, distinguished from the conventional surface modification and ion doping, an effective solid-solution strategy was proposed to strengthen the surface and structural stability of Ni-rich layered cathodes by introducing Li2MnO3. The structural analysis results indicate that the formation of Li2CO3 inert layers on Ni-rich layered cathodes during storage in air is responsible for the increased electrode interfacial impedance, thereby leading to the severe deterioration of electrochemical performance. The introduction of Li2MnO3 can reduce the surface reactivity of Ni-rich cathode materials, playing a certain suppression effect on the formation of surface Li2CO3 layer and the deterioration of electrochemical performances. Additionally, the thermal analysis results show that the heat release of Ni-rich cathodes strongly depends on the charge of states, and Li2MnO3 can suppress oxygen release and significantly enhance the thermal stability of Ni-rich layered cathodes. This work provides a method to improving the storage performance and thermal stability of Ni-rich cathode materials.
An Econometric Analysis of the Energy-Saving Performance of the Italian Plastic Manufacturing Sector
Authors: Costantini Valeria , D’Angeli Mariagrazia , Mancini Martina , Martini Chiara , Paglialunga Elena
Published: February 2024

In a scenario characterised by mitigation concerns and calls for greater resilience in the energy sector, energy audits (EAs) emerge as an essential mean for enhancing end-use energy consumption awareness and efficiency. Such a tool allows us to assess the different energy carriers consumed in a productive sector, offering insight into existing energy efficiency improvement opportunities. This opens avenues for research to devise an econometrics-based methodology that encapsulate production sites and their environmental essentials. This paper contributes to the literature by exploiting the EAs received by the Italian National agency for New technologies, Energy, and Sustainable Economic Development (ENEA) in 2019 from the Italian plastics manufacturing sector, matched with Italian firm-based data extracted from the Analisi Informatizzata delle Aziende Italiane (Italian company information and business intelligence) (AIDA) database. In particular, we investigate how the implementation of energy efficiency measures (EEMs) is influenced by a set of contextual factors, as well as features relating to the companies and EEMs themselves. The empirical investigation focuses on the EAs submitted to ENEA in 2019, which was strategically chosen due to its unique data availability and adequacy for extensive analysis. The selection of 2019 is justified as it constitutes the second mandatory reporting period for energy audits, in contrast to the 2022 data, which are currently undergoing detailed refinement. In line with the literature, the adopted empirical approach involves the use of both the OLS and logistic regression models. Empirical results confirm the relevance of economic and financial factors in guiding the decisions surrounding the sector’s energy performance, alongside the analogous influence of the technical characteristics of the measures themselves and of the firms’ strategies. In particular, the OLS model with no fixed effects shows that a one-percent variation in investments is associated with an increase in savings performance equal to 0.63%. As for the OLS model, including fixed effects, the elasticity among the two variables concerned reaches 0.87%, while in the logistic regression, if the investment carried out by the production sites increases, the expected percentage change in the probability that the energy-saving performance is above its average is about 187.77%. Contextual factors that prove to be equally influential include the incentive mechanism considered and the traits of the geographical area in which the companies are located. Relevant policy implications derived from this analysis include the importance of reducing informational barriers about EEMs and increasing technical assistance, which can be crucial for identifying and implementing effective energy solutions.
Quasi-Resonant Converter for Electric Vehicle Charging Applications: Analysis, Design, and Markov Model Use for Reliability Estimation
Authors: Sampath Harini , Nallaperumal Chellammal , Hossain Md. Jahangir
Published: February 2024

This article presents a quasi-resonant converter (QRC) with multiple sources. A QRC has many benefits, such as high gain, constant current, and nominal voltage stress on MOSFET, with an up to 49% duty cycle with fewer switches. These features of the converter make it suitable for electrical vehicle (EV) off-board charging, which requires significant voltage gain. As the switch operates under soft switching condition, the converter has reduced power loss, improved efficiency, and increased reliability. To reduce grid dependency, the suggested QRC is housed with a grid and PV at the input ports. The proposed converter is modeled using mathematical equations and examined using the MATLAB platform under different operating conditions. In this work, analysis of the steady state, along with components design, estimation of the voltage and current stresses, are addressed. Further, the reliability of the QRC based on the probability of components failure is carried out using the Markov model. The hardware results are observed to validate the design, operation, efficiency, and suitability of the proposed QRC for EV off-board charging applications. A 400-watt test rig is designed to assess the performance of QRC.
Research on the End-Milling Surface Quality of Paulownia Based on Response Surface Model in Terms of Force and Chip Morphology
Authors: Wang Jinxin , Wu Zhanwen , Zhang Feng , Song Chaojun , Hu Wei , Zhu Zhaolong , Guo Xiaolei , Cao Pingxiang
Published: February 2024

To investigate the impact of different milling parameters on milling forces, chip morphology, and machined surface quality during the Paulownia milling process, we conducted experiments using cemented carbide single-tooth shank milling cutters. Additionally, we established a response surface model (RSM) to analyze milling surface quality. The key findings are as follows: milling forces along the parallel and tangential axes decrease with an increased tool rake angle and spindle’s rotational frequency, but they exhibit a positive correlation with milling depth. The effect of spindle’s rotational frequency on the milling force along the lateral axis differs due to the complex fiber characteristics of Paulownia. As milling depth decreases, chip morphology transitions from a block structure to a sheet structure, eventually becoming fragmented with shallow milling. Higher spindle’s rotational frequency and tool rake angle lead to a more fragmented direction in Paulownia chip morphology, while machined surface quality improves. Notably, under specific conditions, a striped chip morphology significantly enhances machined surface quality compared to similar milling parameters. The established RSM for machined Paulownia surface roughness is reliable and holds reference value for inhibiting surface damage in Paulownia machining.
Molecular Phylogenetics and Light Microscopy Reveal “True” and “False” Calacarines and Novel Genital Structures in Gall Mites (Acariformes, Eriophyoidea)
Authors: Chetverikov Philipp E. , Craemer Charnie , Gankevich Vladimir D. , Le Nhung Thi Tuyet , Nguyen Viet Duc , Trinh Hoat Xuan , Amrine James
Published: February 2024

Gall mites (Eriophyoidea) are cosmopolitan microscopic phytoparasites that often transmit viruses and induce gallogenesis. The tribe Calacarini is diagnosed by a set of plesiomorphic and homoplastic traits, including elimination of setae sc shared with other lineages of Eriophyoidea. We reviewed data on the generic diversity of calacarines, revised the concept of the type genus Calacarus Keifer 1940, and proposed three zones (MZ, SMZ, LZ) in the prodorsal shields of calacarines to simplify descriptions of their shield patterns. We describe three new calacarine species (Calacarus baviensisn. sp., C. burchelliaen. sp., and Viginticus searsiaen. sp.) from indigenous dicotyledonous trees from South Africa and Vietnam and report on new findings of Paracalacarus podocarpi Keifer in Brazil, Jiangsuacarus sp. in the USA, and Calacarus pusillus Pye in Latvia and Russia. The latter represents the new most northern locality of Calacarini. Reinvestigating the type species of Jaranasia Chandrapatya & Boczek 2000 revealed that absence of setae l’’ II is the only character separating it from Jiangsuacarus Xue 2009. We proposed two new combinations: Jiangsuacarus sesleriae (Skoracka 2004) n. comb. (transferred from Jaranasia) and Procalacarus mussaendae (Keifer 1977) n. comb. (transferred from Calacarus). Partial sequences of Cox1 and 28S genes were obtained for six calacarines, some of them originating from old ethanol material kept at room temperature. Molecular phylogenetics revealed a stable cluster of “true” calacarine sequences comprising Calacarus, Jaranasia, Latitudo, and Viginticus and a polyphyletic group of erroneous sequences assigned to Calacarini in GenBank. All investigated females of calacarines have a pair of genital tubules associated with the vestibulum and hypothesized to participate in fertilization. This finding may contribute to resolving the question on how the fusion of gametes happens in gall mites.
Dynamic Optimization of Lactic Acid Production from Grape Stalk Solid-State Fermentation with Rhizopus oryzae Applying a Variable Temperature Profile
Authors: Groff María Carla , Noriega Sandra Edith , Gil Rocío Mariel , Pantano Nadia , Scaglia Gustavo
Published: February 2024

Lactic acid is widely used in the food industry. It can be produced via chemical synthesis or biotechnological pathways by using renewable resources as substrates. The main challenge of sustainable production lies in reaching productivities and yields that allow for their industrial production. In this case, the application of process engineering becomes a crucial tool to improve the performance of bioprocesses. In this work, we performed the solid-state fermentation of grape stalk using Rhizopus oryzae NCIM 1299 to obtain lactic acid, employing three different temperatures (22, 35, and 40 °C) and a relative humidity of 50%. The Logistic and First-Order Plus Dead Time models were adjusted for fungal biomass growth, and the Luedeking and Piret with Delay Time model was used for lactic acid production, obtaining higher R2 values in all cases. At 40 °C, it was observed that Rhizopus oryzae grew in pellet form, resulting in an increase in lactic acid productivity. In this context, the effect of temperature on the kinetic parameters was evaluated with a polynomial correlation. Finally, using this correlation, a smooth and continuous optimal temperature profile was obtained by a dynamic optimization method, improving the final lactic acid concentration by 53%.
Modern Trends in Multi-Agent Systems
Authors: Kenyeres Martin , Budinská Ivana , Hluchý Ladislav , Poggi Agostino
Published: February 2024

The term “multi-agent system” is generally understood as an interconnected set of independent entities that can effectively solve complex and time-consuming problems exceeding the individual abilities of common problem solvers [...]