bluuebunny/crossref_metadata_2025 huggingface dataset:
Solving a Fully Intuitionistic Fuzzy Transportation Problem Using a Hybrid Multi-Objective Optimization Approach
Authors: Niroomand Sadegh , Allahviranloo Tofigh , Mahmoodirad Ali , Amirteimoori Alireza , Mršić Leo , Samanta Sovan
Published: December 2024

In this study, a typical transportation problem involving intuitionistic fuzzy-type variables and parameters is focused on. The approaches proposed in the literature for such transportation problems have many shortcomings, such as the use of ranking functions and obtaining an infeasible solution with negative values for variables and objective functions in the presence of non-negative unit transportation charges. To overcome such weaknesses, a new approach without a ranking function is introduced in this paper. The proposed approach first constructs an equivalent crisp multi-objective form of the intuitionistic fuzzy transportation problem and then proposes a new hybrid multi-objective solution procedure to tackle the obtained crisp multi-objective problem. The conducted computer experiments with benchmark problems from the existing studies of the literature reflect the effectiveness of the proposed solution approach of this study in terms of the quality of the results when compared to the available approaches of the literature.
Deep Reinforcement Learning-Based Adversarial Attack and Defense in Industrial Control Systems
Authors: Kim Mun-Suk
Published: December 2024

Adversarial attacks targeting industrial control systems, such as the Maroochy wastewater system attack and the Stuxnet worm attack, have caused significant damage to related facilities. To enhance the security of industrial control systems, recent research has focused on not only improving the accuracy of intrusion detection systems but also developing techniques to generate adversarial attacks for evaluating the performance of these intrusion detection systems. In this paper, we propose a deep reinforcement learning-based adversarial attack framework designed to perform man-in-the-middle attacks on industrial control systems. Unlike existing adversarial attack methods, our proposed adversarial attack scheme learns to evade detection by the intrusion detection system based on both the impact on the target and the detection results from previous attacks. For performance evaluation, we utilized a dataset collected from the secure water treatment (SWaT) testbed. The simulation results demonstrated that our adversarial attack scheme successfully executed man-in-the-middle attacks while evading detection by the rule-based intrusion detection system, which was defined based on the analysis of the SWaT dataset.
Innovation Prioritization Decisions in the Product–Service Supply Chain: The Impact of Data Mining and Information Sharing Strategies
Authors: Shi Jinfa , Liu Wei , Su Yongqiang
Published: December 2024

Driven by the servicing and digital transformation of manufacturing enterprises, product and service innovation for manufacturers and service providers to promote integrated solutions collaboratively has become an important way for enterprises to maintain market competitiveness. Building on this foundation, this paper develops an innovation priority decision model for the product–service supply chain, which comprises manufacturers and service providers, considering the data mining and information sharing strategies of service providers. It analyzes the optimal decisions and profits of the members when product innovation is prioritized as well as when service innovation is prioritized, and subsequently explores the selection of innovation strategies for the product–service supply chain under varying conditions. The results of the study show that, firstly, service providers’ data mining and information sharing strategies are not always favorable to the innovation decisions of both parties. Only when data resources can be transformed into real innovation value at a reasonable cost can data mining and information sharing play the role of ‘external incentives’ to promote collaborative innovation between the two parties. Secondly, when service providers do not adopt data mining and information sharing strategies, the efficiency of product and service innovation plays a decisive role in innovation prioritization. The party with high innovation efficiency adopts the sub-priority innovation strategy, which can lead to a larger market share for the innovation results. Finally, under the service provider’s data mining and information sharing strategy, the innovation priority selection of the product–service supply chain depends on the information value transformation ability of the manufacturer and the service provider. Moreover, the profits of manufacturers and service providers under the same innovation priority do not always ‘advance or retreat together’, and there may be cases where one of them suffers a loss of profits. This study provides a theoretical basis for the choice of innovation strategies given to manufacturers and service providers, and promotes the development of collaborative innovation between them.
Statistical Inference on the Shape Parameter of Inverse Generalized Weibull Distribution
Authors: Zhuang Yan , Bapat Sudeep R. , Wang Wenjie
Published: December 2024

In this paper, we propose statistical inference methodologies for estimating the shape parameter α of inverse generalized Weibull (IGW) distribution. Specifically, we develop two approaches: (1) a bounded-risk point estimation strategy for α and (2) a fixed-accuracy confidence interval estimation method for α. For (1), we introduce a purely sequential estimation strategy, which is theoretically shown to possess desirable first-order efficiency properties. For (2), we present a method that allows for the precise determination of sample size without requiring prior knowledge of the other two parameters of the IGW distribution. To validate the proposed methods, we conduct extensive simulation studies that demonstrate their effectiveness and consistency with the theoretical results. Additionally, real-world data applications are provided to further illustrate the practical applicability of the proposed procedures.
A Novel DV-Hop Localization Method Based on Hybrid Improved Weighted Hyperbolic Strategy and Proportional Integral Derivative Search Algorithm
Authors: Zhang Dejing , Li Pengfei , Hou Benyin
Published: December 2024

As a range-free localization algorithm, DV-Hop has gained widespread attention due to its advantages of simplicity and ease of implementation. However, this algorithm also has some defects, such as poor localization accuracy and vulnerability to network topology. This paper presents a comprehensive analysis of the factors contributing to the inaccuracy of the DV-Hop algorithm. An improved proportional integral derivative (PID) search algorithm (PSA) DV-Hop hybrid localization algorithm based on weighted hyperbola (IPSA-DV-Hop) is proposed. Firstly, the first hop distance refinement is employed to rectify the received signal strength indicator (RSSI). In order to replace the original least squares solution, a weighted hyperbolic algorithm based on the degree of covariance is adopted. Secondly, the localization error is further reduced by employing the improved PSA. In addition, the selection process of the node set is optimized using progressive sample consensus (PROSAC) followed by a 3D hyperbolic algorithm based on coplanarity. This approach effectively reduces the computational error associated with the hopping distance of the beacon nodes in the 3D scenarios. Finally, the simulation experiments demonstrate that the proposed algorithm can markedly enhance the localization precision in both isotropic and anisotropic networks and reduce the localization error by a minimum of 30% in comparison to the classical DV-Hop. Additionally, it also exhibits stability under the influence of a radio irregular model (RIM).
The Improved Network Intrusion Detection Techniques Using the Feature Engineering Approach with Boosting Classifiers
Authors: Rai Hari Mohan , Yoo Joon , Agarwal Saurabh
Published: December 2024

In the domain of cybersecurity, cyber threats targeting network devices are very crucial. Because of the exponential growth of wireless devices, such as smartphones and portable devices, cyber risks are becoming increasingly frequent and common with the emergence of new types of threats. This makes the automatic and accurate detection of network-based intrusion very essential. In this work, we propose a network-based intrusion detection system utilizing the comprehensive feature engineering approach combined with boosting machine-learning (ML) models. A TCP/IP-based dataset with 25,192 data samples from different protocols has been utilized in our work. To improve the dataset, we used preprocessing methods such as label encoding, correlation analysis, custom label encoding, and iterative label encoding. To improve the model’s accuracy for prediction, we then used a unique feature engineering methodology that included novel feature scaling and random forest-based feature selection techniques. We used three conventional models (NB, LR, and SVC) and four boosting classifiers (CatBoostGBM, LightGBM, HistGradientBoosting, and XGBoost) for classification. The 10-fold cross-validation methods were employed to train each model. After an assessment using numerous metrics, the best-performing model emerged as XGBoost. With mean metric values of 99.54 ± 0.0007 for accuracy, 99.53 ± 0.0013 for precision, 99.54 ± 0.001 for recall, and an F1-score of 99.53 ± 0.0014, the XGBoost model produced the best performance overall. Additionally, we showed the ROC curve for evaluating the model, which demonstrated that all boosting classifiers obtained a perfect AUC value of one. Our suggested methodologies show effectiveness and accuracy in detecting network intrusions, setting the stage for the model to be used in real time. Our method provides a strong defensive measure against malicious intrusions into network infrastructures while cyber threats keep varying.
Prolactin Response to a Submaximal Dose of Ghrelin in Different Phases of the Normal Menstrual Cycle
Authors: Messini Christina I. , Anifandis George , Georgoulias Panagiotis , Dafopoulos Konstantinos , Sveronis George , Daponte Alexandros , Messinis Ioannis E.
Published: December 2024

Background and Objectives: A similar secretory pattern of prolactin (PRL) and growth hormone (GH) during the menstrual cycle has been reported in response to a high dose of ghrelin in adult healthy women. The present study aimed to assess the pattern of PRL and GH secretions in response to a submaximal dose of ghrelin during different menstrual phases in adult healthy women. Materials and Methods: Eight female subjects with normal cyclicity were enrolled. These subjects were either in the early follicular (EF), late follicular (LF), or mid-luteal (ML) phase of their cycles. Each subject received an IV dose of normal saline (2 mL each time) during the first cycle after enrollment, followed by an IV dose of ghrelin (0.30 μg/kg bw) in the second cycle. The blood samples were collected before and after the IV dosage at −15, 0, 15, 30, 45, 60, 75, 90 and 120 min, where 0 min denotes the time of IV dosage. Results: All the enrolled subjects experienced ovulatory cycles as assessed by increased serum progesterone levels. Serum estradiol levels were significantly higher in the LF than in the EF (p < 0.001) and ML phases (p < 0.01); these levels were also significantly higher in the ML than in the EF phase (p < 0.01). The administration of saline did not affect serum GH or PRL levels. Following the administration of ghrelin, plasma ghrelin levels and serum GH levels increased significantly (p < 0.001). The response amplitude of GH was similar in the three stages of cycle 2. In contrast to GH, the ghrelin injection induced a significant increase in serum PRL levels only in the LF phase (p < 0.05). Conclusions: These results show, for the first time, a different pattern of PRL and GH in response to a submaximal dose of ghrelin during the normal menstrual cycle. It is suggested that the ghrelin threshold for pituitary lactotrophs is higher than for somatotrophs and that, unlike GH, ghrelin-stimulated PRL secretion can be influenced by ovarian steroids.
Prevalence of Vitamin D Deficiency Among Adults in Kazakhstan: A Systematic Review and Meta-Analysis
Authors: Karibayeva Indira , Bilibayeva Galiya , Yerzhanova Aya , Alekesheva Roza , Iglikova Assiya , Maxudova Makhigul , Ussebayeva Neilya
Published: December 2024

Background and Objectives: Despite frequent references to the high prevalence of vitamin D deficiency in Kazakhstan, a comprehensive synthesis of existing research on this issue among adults is lacking. This systematic review and meta-analysis aim to address this gap by determining the mean prevalence of vitamin D deficiency among adults in Kazakhstan. A secondary objective is to evaluate whether the prevalence differs between healthy adults and those with chronic conditions. Materials and Methods: A systematic search was conducted in PubMed, Scopus, ScienceDirect, Web of Science, and Google Scholar by two independent researchers using the keywords: “vitamin D” AND “Kazakhstan”, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies were included if they reported the prevalence of vitamin D in adults in Kazakhstan, defined as a blood level of 25-hydroxyvitamin D 25(OH)D below 20 ng/mL. Results: Seven studies were included in this review, encompassing 3616 individuals, of whom 2239 had vitamin D deficiency. Using a random-effects model, the pooled mean prevalence of vitamin D deficiency among adults with chronic conditions was 60% (95% CI, 38–79%), with high heterogeneity. Similarly, the analysis of five studies involving healthy adults revealed a pooled mean prevalence of 55% (95% CI, 38–70%), also with high heterogeneity. Overall, the pooled mean prevalence of vitamin D deficiency in the adult population was 57% (95% CI, 45–69%). Conclusions: This analysis indicates a high prevalence of vitamin D deficiency among adults in Kazakhstan, with 57% of the population affected. Addressing this issue requires a multifaceted approach, including policy reforms that consider the impact of time zone changes on sunlight exposure and the active involvement of nurse practitioners in preventive strategies.
Utility of Aprepitant in the Management of Pediatric Patients with Cyclical Vomiting Syndrome
Authors: Thavamani Aravind , Malay Sindhoosha , Khatana Jasmine , Velayuthan Sujithra , Sankararaman Senthilkumar
Published: December 2024

Introduction: Cyclical vomiting syndrome (CVS) is a recurrent debilitating illness characterized by intense episodes of nausea and emesis with widely varied pharmacological management across the country. Aprepitant is now increasingly used in patients with CVS. The impact of aprepitant as an abortive therapy in the readmission of pediatric patients with CVS is currently unknown. Methodology: We analyzed all pediatric patients with a primary diagnosis of CVS using the ICD-10 code in the Pediatric Health Information System database of the Children’s Hospital Association. We evaluated the demographic data, comorbid conditions, and management details during the inpatient stay. CVS patients who received aprepitant during their inpatient hospitalization were compared with patients without aprepitant use. Seven-day readmission rate for CVS was used as the outcome variable to assess the effectiveness of the aprepitant in aborting an episode. Propensity score matching was used to match the two cohorts. Results: We analyzed 1775 patients of which 96 received aprepitant during the inpatient hospitalization. The aprepitant group had a more severe hospitalization course as evidenced by an increased duration of hospital stay (5 vs. 3 days) and total hospitalization costs ($11,790 vs. $6380). There were no significant differences in the 7-day (17% vs. 16%, p = 0.91) readmission rate and results were not altered by propensity score matching. Conclusions: Aprepitant use as an abortive therapy did not affect the 7-day CVS-related readmission rate. Further prospective studies are needed to explore the role of aprepitant as an abortive agent in the management of CVS in the pediatric population.
Bacterial Diversity in the Different Ecological Niches Related to the Yonghwasil Pond (Republic of Korea)
Authors: Kim Myung Kyum , Lim Bong-Soon , Lee Chang Seok , Srinivasan Sathiyaraj
Published: December 2024

The bacteriome profile was studied in freshwater ecosystems within the Yonghwasil pond, situated at the National Institute of Ecology, Seocheon-gun, Chungcheongnam-do, central western Korea. Six samples from water, mud, and soil niches were assessed, specifically from lake water, bottom mud (sediment), and root-soil samples of Bulrush, wild rice, Reed, and Korean Willow. Notably, the phylum Actinobacteria exhibited an upward trend moving from water to mud to soil samples, whereas Chloroflexi showed a contrasting decrease. Across the board, Proteobacteria emerged as the reigning phylum, and subsequent dominance was attributed to Firmicutes and Actinobacteria. The water samples were characterized by an enriched presence of Cyanobacteria and Bacteroidetes, whereas the mud samples distinctly housed a higher concentration of Chloroflexi. Assessing biodiversity through OTU and ACE indices revealed a subdued species richness in the water samples. On the contrary, mud samples stood out with the highest OTU and ACE metrics, signifying a microbially diverse habitat. Bulrush, wild rice, Reed, and Willow samples showed intermediate microbial diversity. The Shannon index further corroborated the pronounced microbial diversity in mud and Bulrush habitats with others. This research elucidates the microbial intricacies across different habitats within Yonghwasil Pond, emphasizing the pivotal role of environmental matrices in shaping bacterial communities.
Genome-Wide Identification and Analysis of Glycosyltransferases in Colletotrichum graminicola
Authors: Wang Yafei , Li Honglian , Chang Jiaxin , Zhang Yu , Li Jinyao , Jia Shaofeng , Shi Yan
Published: December 2024

Corn leaf blight and stem rot caused by Colletotrichum graminicola are significant diseases that severely affect corn crops. Glycosyltransferases (GTs) catalyze the transfer of sugar residues to diverse receptor molecules, participating in numerous biological processes and facilitating functions ranging from structural support to signal transduction. This study identified 101 GT genes through functional annotation of the C. graminicola TZ–3 genome. Subsequent analyses revealed differences among the C. graminicola GT (CgGT) genes. Investigation into subcellular localization indicated diverse locations of CgGTs within subcellular structures, while the presence of multiple domains in CgGTs suggests their involvement in diverse fungal biological processes through versatile functions. The promoter regions of CgGT genes are enriched with diverse cis-acting regulatory elements linked to responses to biotic and abiotic stresses, suggesting a key involvement of CgGT genes in the organism’s multi-faceted stress responses. Expression pattern analysis reveals that most CgGT genes were differentially expressed during the interaction between C. graminicola and corn. Integrating gene ontology functional analysis revealed that CgGTs play important roles in the interaction between C. graminicola and corn. Our research contributes to understanding the functions of CgGT genes and investigating their involvement in fungal pathogenesis. At the same time, our research has laid a solid foundation for the development of sustainable agriculture and the utilization of GT genes to develop stress-resistant and high-yield crop varieties.
Sulfate-Reducing Bacteria Isolated from an Oil Field in Kazakhstan and a Description of Pseudodesulfovibrio karagichevae sp. nov.
Authors: Bidzhieva Salimat K. , Tourova Tatyana P. , Grouzdev Denis S. , Samigullina Salima R. , Sokolova Diyana S. , Poltaraus Andrey B. , Avtukh Alexander N. , Tereshina Vera M. , Mardanov Andrey V. , Zhaparov Nurlan S. , Nazina Tamara N.
Published: December 2024

Sulfidogenic bacteria cause numerous issues in the oil industry since they produce sulfide, corroding steel equipment, reducing oil quality, and worsening the environmental conditions in oil fields. The purpose of this work was to isolate and taxonomically identify the sulfidogenic bacteria responsible for the corrosion of steel equipment at the Karazhanbas oil field (Kazakhstan). In this study, we characterized five sulfidogenic strains of the genera Pseudodesulfovibrio, Oleidesulfovibrio, and Acetobacterium isolated from the formation water of the Karazhanbas oil field (Kazakhstan). Sulfate-reducing strain 9FUST revealed 98.9% similarity of the 16S rRNA gene sequence with the closely related strain ‘Pseudodesulfovibrio methanolicus’ 5S69T and was studied in detail to enhance the taxonomic resolution. Strain 9FUST grew optimally at 23–28 °C, pH 6.5, and 0–2% (w/v) NaCl. The strain used lactate, pyruvate, methanol, ethanol, fructose, ribose, and H2/CO2 (in the presence of acetate) as carbon and energy sources for sulfate reduction. Iso-C17:1 ω11, C15:0, iso-C15:0, and C16:0 were the predominant fatty acids. The genome is 4.20 Mbp with a G + C content of 64.0%. The average nucleotide identity and digital DNA–DNA hybridization values with Pseudodesulfovibrio spp. genomes were 72.5–91.6% (<95%) and 18.5–45.0% (<70%), respectively, and supported our conclusion that 9FUST (=VKM B-3654T = KCTC 25498T) belonged to a novel Pseudodesulfovibrio species, for which the name Pseudodesulfovibrio karagichevae sp. nov. is proposed. Pangenome analysis of sixteen Pseudodesulfovibrio species and functional annotation analysis of identified genes revealed complete modules of enzymes of the main metabolic pathways, characteristic of bacteria of this genus, and unique genes highlighting the adaptations of strain 9FUST in carbohydrate metabolism, nutrient uptake, and environmental stress response. Isolation of these strains expands our understanding of the diversity of sulfidogens in oil reservoirs and can be used to test the effectiveness of biocides used in an oil field.
Lateral Flow Immunosensing of Salmonella Typhimurium Cells in Milk: Comparing Three Sequences of Interactions
Authors: Byzova Nadezhda A. , Safenkova Irina V. , Gorbatov Alexey A. , Biketov Sergey F. , Dzantiev Boris B. , Zherdev Anatoly V.
Published: December 2024

To ensure the safety of foodstuffs, widespread non-laboratory monitoring for pathogenic contaminants is in demand. A suitable technique for this purpose is lateral flow immunoassay (LFIA) which combines simplicity, rapidity, and productivity with specific immune detection. This study considered three developed formats of LFIA for Salmonella Typhimurium, a priority pathogenic contaminant of milk. Common sandwich LFIA with all immunoreagents pre-applied to the test strip (format A) was compared with incubation of the sample and (gold nanoparticle—antibody) conjugate, preceding the lateral flow processes (format B), and sequential passages of the sample and the conjugate along the test strip (format C). Under the chosen conditions, the detection limits and the assay times were 3 × 104, 1 × 105, and 3 × 105 cells/mL, 10, 15, and 20 min for formats A, B, and C, respectively. The selected format A of LFIA was successfully applied to test milk samples. The sample’s dilution to a fat content of 1.0% causes pathogen detection, with 70–110% revealing and 1.5–8.5% accuracy. The obtained results demonstrate that the developed LFIA allows the detection of lower concentrations of Salmonella cells and, in this way, accelerates decision-making in food safety control.
Physicochemical Surface Modification and Characterisation of Coal Fly Ash for Application in Rubber Composites
Authors: Moyo Dennis S. , Doucet Frédéric J. , Hlangothi Shanganyane P. , Woolard Christopher D. , Reynolds-Clausen Kelley , Kruger Richard A. , van der Merwe Elizabet M.
Published: December 2024

This study evaluated the capability of coal fly ash (untreated and physicochemically modified) when utilised as a filler in cis-1,4-polyisoprene rubber. Physicochemical modification of the ash was achieved using two techniques: (1) ammonium sulphate roasting followed by controlled aqueous dissolution and (2) sulphuric acid leaching. In addition, the effectiveness of a silane-coupling agent (Si-69) in enhancing the compatibility of untreated and physically modified ash samples with natural rubber was investigated. The ammonium sulphate roasting route increased the surface area and roughness and decreased the particle–particle agglomeration of the fly ash sample. Sulphuric acid treatment decreased the particle–particle agglomeration. However, no increase in surface roughness was observed. The untreated fly ash samples were not significantly reinforcing, and the properties they imparted were inferior to the least reinforcing carbon black. Silane treatment resulted in improved dispersion and wetting of the fly ash in the rubber matrix, leading to improved reinforcement compared to neat rubber. In situ addition of the silane during preparation of the vulcanisates led to composites with better mechanical properties than the composites containing silane-pre-treated fly ash. Composites filled with ammonium sulphate-roasted-and-leached ash performed better than the composites filled with untreated ash and sulfuric acid-leached ash. These findings suggest that modified fly ash holds promise as an effective filler for rubber materials, offering potential environmental and economic benefits by repurposing coal combustion by-products.
An Evaluation of Whether Routine QTc Interval Screening Is Necessary Prior to Starting ADHD Medications: Experience from a Large Retrospective Study
Authors: Alsayouf Hamza A. , Dyab Lima M. , Al-Ghawanmeh Redab , Alhawawsha Luay S. , Alsarhan Osama , Al-Smadi Hadeel , Al-Taani Ghaith M. , Daoud Azhar , Elsadek Haitham E. , Khreisat Wael H.
Published: December 2024

Background/Objectives: Routine screening electrocardiograms (ECGs) prior to starting medications for attention-deficit/hyperactivity disorder (ADHD) remain controversial. This real-world study assessed corrected QT (QTc) interval data from pediatric patients who had a baseline ECG performed prior to initiating treatment with ADHD medications and ≥6 months of clinical follow-up. Methods: A retrospective chart review of children aged 2–18 years diagnosed with ADHD with/without autism spectrum disorder (ASD) at child neurology clinics in Jordan (June 2019 and June 2021) was performed, and children were prescribed with ADHD medications to manage symptoms. Patients had ≥6 months of follow-up and no known cardiac disease/family history. A baseline ECG and regular clinical exams were performed for each child. Results: Of 458 patients with baseline ECGs, 362 met the study inclusion criteria. Overall, 286 (79.0%) patients were diagnosed with ASD/comorbid ADHD and 76 (21.0%) with ADHD alone; 61 (16.9%) were prescribed atomoxetine, 38 (10.5%) methylphenidate, 134 (37.0%) risperidone, and 129 (35.6%) aripiprazole. The patients’ mean ± SD age was 6.4 ± 3.5 years, and most were male (n = 268, 74.0%). The mean baseline QTc interval was 400 ± 22 ms (median, 400 ms); one patient had a QTc interval >460 ms and was excluded from initiating treatment with any ADHD medications. During the ≥6-month follow-up, none of the patients had any signs or symptoms of adverse cardiac effects. Conclusions: Routine screening ECGs prior to treatment with ADHD medications may not be necessary in healthy children with no family history of cardiac disease. However, further studies are needed to evaluate the long-term effects of ADHD medications in low-risk pediatric patients.
Fixed Drug Eruption Due to Doxycycline Postexposure Prophylaxis
Authors: Nguyen Lee , Diamond Catherine
Published: December 2024

Doxycycline is a semi-synthetic antibiotic in the tetracycline family. The three common subtypes of tetracyclines include naturally occurring, semi-synthetic, and new agents. Each subtype shares specific commonalities but is substantially different in various clinical applications. The mechanism of antimicrobial activity is the same across subtypes. The structural changes to the core naphthacene ring do not alter the mechanism of action but are thought to alter the rates of adverse effects and mechanisms of resistance. Tetracyclines as a class are known to cause fixed drug eruptions, but the majority of these adverse effects were associated with naturally occurring tetracyclines. Semi-synthetic tetracyclines have limited reports of fixed drug eruptions. Here, we present a case of fixed drug eruption in a patient who previously had multiple treatment courses with doxycycline. The case involves the use of doxycycline not for the treatment of an infection but as postexposure prophylactic (PEP) antibiotic therapy to prevent the acquisition of a sexually transmitted infection. Doxycycline PEP has been shown to reduce the rate of bacterial sexually transmitted infection in men who have sex with men (MSM). Doxycycline PEP is a single dose taken orally within 24–72 h of unprotected sexual intercourse. The dosing structure allows for ease of adherence but also repeatedly exposes individuals to doxycycline, putting them at risk for adverse events such as fixed drug eruptions, as illustrated by this case report.
Advances in Soliton Crystal Microcombs
Authors: Liu Zhihui , Zhang Haoran , Song Yuhang , Zhu Xiaotian , Murray Caitlin E. , Bai Yunping , Tan Mengxi , Chu Sai T. , Moss David J. , Xu Xingyuan , Xu Kun
Published: December 2024

Soliton crystal microcombs, as a new type of Kerr frequency comb, offer advantages such as higher energy conversion efficiency and a simpler generation mechanism compared to those of traditional soliton microcombs. They have a wide range of applications in fields like microwave photonics, ultra-high-speed optical communication, and photonic neural networks. In this review, we discuss the recent developments regarding soliton crystal microcombs and analyze the advantages and disadvantages of generating soliton crystal microcombs utilizing different mechanisms. First, we briefly introduce the numerical model of optical frequency combs. Then, we introduce the generation schemes for soliton crystal microcombs based on various mechanisms, such as utilizing an avoided mode crossing, harmonic modulation, bi-chromatic pumping, and the use of saturable absorbers. Finally, we discuss the progress of research on soliton crystal microcombs in the fields of microwave photonics, optical communication, and photonic neural networks. We also discuss the challenges and perspectives regarding soliton crystal microcombs.
Improving 795 nm Single-Frequency Laser’s Frequency Stability by Means of the Bright-State Spectroscopy with Rubidium Vapor Cell
Authors: Zhao Junye , Yang Yongbiao , Zhang Lulu , Li Yang , Wang Junmin
Published: December 2024

The utilization of atomic or molecular spectroscopy for frequency locking of single-frequency laser to improve laser frequency stability plays an important role in the experimental investigation of optically pumped atomic magnetometers, atomic clocks, laser cooling and trapping of atoms, etc. We have experimentally demonstrated a technique for frequency stabilization of a single-frequency laser employing the bright state spectroscopy (BSS) with a rubidium atomic vapor cell. By utilizing the counter-propagating dual-frequency 795 nm laser beams with mutually orthogonal linear polarization and a frequency difference of 6.834 GHz, which is equal to the hyperfine splitting of rubidium-87 ground state 5S1/2, an absorption-enhanced signal with narrow linewidth at the center of Doppler-broadened transmission spectroscopy is observed when continuous scanning the laser frequency over rubidium-87 D1 transition. This is the so-called BSS. Amplitude of the absorption-enhanced signal in the BSS is much larger compared with the conventional saturation absorption spectroscopy (SAS). The relationship between linewidth and amplitude of the BSS signal and laser beam intensity has been investigated. This high-contrast absorption-enhanced BSS signal has been employed for the laser frequency stabilization. The experimental results show that the frequency stability is 4.4×10−11 with an integration time of 40 s, near one order of magnitude better than that for using the SAS.
Polarization-Independent Focusing Vortex Beam Generation Based on Ultra-Thin Spiral Diffractive Lens on Fiber End-Facet
Authors: Wu Luping , Bai Zhiyong , Liu Rui , Wang Yuji , Yu Jian , Ran Jianjun , Chen Zikai , Luo Zilun , Liao Changrui , Wang Ying , He Jun , Chen George Y. , Wang Yiping
Published: December 2024

An ultra-thin spiral diffractive lens (SDL) was fabricated by using focused ion beam milling on a fiber end-facet coated with a 100 nm thick Au film. Focusing vortex beams (FVBs) were successfully excited by the SDLs due to the coherent superposition of diffracted waves and their azimuth dependence of the phase accumulated from the spiral aperture to the beam axis. The polarization and phase characteristics of the FVBs were experimentally investigated. Results show that the input beams with various polarization states were converted to FVBs, whose polarization states were the same as those of the input beams. Furthermore, the focal length of the SDL and the in-tensity and phase distribution at the focus spot of the FVBs were numerically simulated by the FDTD method in the ultra-wide near-infrared waveband from 1300 nm to 1800 nm. The focal length was tuned from 21.8 μm to 14.7 μm, the intensity profiles exhibited a doughnut-like shape, and the vortex phase was converted throughout the broadband range. The devices are expected to be candidates for widespread applications including optical communications, optical imaging, and optical tweezers.
Enhancing Wheat Spike Counting and Disease Detection Using a Probability Density Attention Mechanism in Deep Learning Models for Precision Agriculture
Authors: Li Ruiheng , Hong Wenjie , Wu Ruiming , Wang Yan , Wu Xiaohan , Shi Zhongtian , Xu Yifei , Han Zixu , Lv Chunli
Published: December 2024

This study aims to improve the precision of wheat spike counting and disease detection, exploring the application of deep learning in the agricultural sector. Addressing the shortcomings of traditional detection methods, we propose an advanced feature extraction strategy and a model based on the probability density attention mechanism, designed to more effectively handle feature extraction in complex backgrounds and dense areas. Through comparative experiments with various advanced models, we comprehensively evaluate the performance of our model. In the disease detection task, our model performs excellently, achieving a precision of 0.93, a recall of 0.89, an accuracy of 0.91, and an mAP of 0.90. By introducing the density loss function, we are able to effectively improve the detection accuracy when dealing with high-density regions. In the wheat spike counting task, the model similarly demonstrates a strong performance, with a precision of 0.91, a recall of 0.88, an accuracy of 0.90, and an mAP of 0.90, further validating its effectiveness. Furthermore, this paper also conducts ablation experiments on different loss functions. The results of this research provide a new method for wheat spike counting and disease detection, fully reflecting the application value of deep learning in precision agriculture. By combining the probability density attention mechanism and the density loss function, the proposed model significantly improves the detection accuracy and efficiency, offering important references for future related research.
Impacts of Micro/Nanoplastics Combined with Graphene Oxide on Lactuca sativa Seeds: Insights into Seedling Growth, Oxidative Stress, and Antioxidant Gene Expression
Authors: Yuan Xuancheng , Zhang Fan , Wang Zhuang
Published: December 2024

Global pollution caused by micro/nanoplastics (M/NPs) is threatening agro-ecosystems, compromising food security and human health. Also, the increasing use of graphene-family nanomaterials (GFNs) in agricultural products has led to their widespread presence in agricultural systems. However, there is a large gap in the literature on the combined effects of MNPs and GFNs on agricultural plants. This study was conducted to explore the individual and combined impacts of polystyrene microplastics (PSMPs, 1 μm) or nanoplastics (PSNPs, 50–100 nm), along with agriculturally relevant graphene oxide (GO), on the seed germination and seedling growth of lettuce (Lactuca sativa). The results showed that the combined effects of mixtures of PSMPs/PSNPs and GO exhibited both synergism and antagonism, depending on different toxicity indicators. The cellular mechanism underlying the combined effects on the roots and shoots of seedlings involved oxidative stress. Three SOD family genes, namely, Cu/Zn-SOD, Fe-SOD, and Mn-SOD, played an important role in regulating the antioxidant defense system of seedlings. The extent of their contribution to this regulation was associated with both the distinct plastic particle sizes and the specific tissue locations within the seedlings.
Potential Regional Pollination Services of Spodoptera litura (Lepidoptera: Noctuidae) Migrants as Evidenced by the Identification of Attached Pollen
Authors: Li Xiaokang , Jia Huiru , Liu Dazhong , Zhou Xianyong , Wu Kongming
Published: December 2024

Many species of noctuid moths exhibit long-distance migratory behavior and have an important pollination service function in terrestrial ecosystems. Spodoptera litura (Fabricius) is a globally distributed insect; however, its role in pollination remains underexplored. In this study, the feeding preferences and inter regional pollination of S. litura adults were explored. We conducted pollen analysis on 1253 S. litura migrants captured from 2018 to 2021 on Beihuangcheng Island in the Bohai Strait of China, which is located in the East Asian insect migration path. The results show that an average of 51.1% of S. litura migrants carry plant pollen each year, and the carrying rate shows fluctuations based on sex, year, and season. By combining morphological identification and DNA barcoding, pollen species were identified from 40 species of plants, representing 21 families and 26 genera, mainly from angiosperms of Dicotyledoneae, with Asteraceae, Apocynaceae, and Amaranthaceae being the dominant taxa. The geographical distribution range of Chrysanthemum zawadskii and Adenophora trachelioides and a migration trajectory simulation analysis indicate that S. litura predominantly migrate from Liaoning Province in Northeast China to North China over the Bohai Sea in autumn. These findings indicate the potential pollination activities of S. litura in North China and Northeast China, enriching our understanding of the interaction between S. litura and the plants it pollinates.
Identification of QTLs and Key Genes Enhancing Lodging Resistance in Soybean Through Chemical and Physical Trait Analysis
Authors: Zhao Wanying , Zeng Depeng , Zhao Caitong , Han Dezhi , Li Shuo , Wen Mingxing , Liang Xuefeng , Zhang Xianfeng , Liu Zhihua , Ali Shahid , Jiang Zhenfeng
Published: December 2024

Lodging of soybean (Glycine max (L.) Merril.) significantly reduces seed yield and quality, particularly in high-yielding environments. This phenomenon occurs when stems weaken under the weight of the plants, complicating harvesting. This study investigated the relationship between soybean stem chemical composition, physical traits, and lodging resistance to improve yield and resilience. We found that as plant density increased, stem hardness decreased, and the elasticity increased, heightening the risk of lodging. Conversely, high temperature (28 °C) boosted lignin, cellulose and pectin content in the stem cell walls, enhancing the lodging resistance. Additionally, after excluding differences in phylogenetic relationships through cluster analysis, we mapped environment-stable genes linked to lodging resistance and identified new QTLs on Chr3 and Chr16. Candidate genes associated with these QTLs were confirmed using qRT–PCR and hormone treatments across diverse soybean varieties. It was found that the expression of stem tip genes was closely related to stem node diameter. These findings provide a theoretical foundation for breeding high-yielding soybean varieties with improved lodging resistance, and advance efforts to develop resilient soybean cultivars.
Modeling and Analysis of Internal Leakage Characteristics of the Internal Curve Motor by a CFD-Based Method
Authors: Ma Wei , Yang Guolai , Cao Wenbin , Bai Guixiang , Cao Chuanchuan , Song Shoupeng
Published: December 2024

Internal curve motors (ICMs) are used in construction and port machinery owing to their low speed and strong torque. The internal leakage of an ICM has a direct impact on its working performance; however, research on the internal leakage of ICMs is unclear. A method, based on the Computational Fluid Dynamics (CFD) transient simulation of an ICM, for obtaining the transient pressure in the plunger chamber and combining the mathematical model of internal leakage is calculated, and the internal leakage is proposed. We one-factor analyzed the internal leakage of the ICM and the effect of the valve pair and plunger pair leakage, and conducted multifactor analysis on the effect of the interaction between those two factors on the internal leakage of the ICM. The results show that the internal leakage mechanisms affecting the ICM were, in descending order of impact, the inlet pressure, oil temperature, and rotational speed, and a significant interaction existed between the inlet pressure and oil temperature, whereas the influence of rotational speed was not significant.
The Integration of Image Intensity and Texture for the Estimation of Particle Mass in Sorting Processes
Authors: Compais Pedro , Morales Belén , Gala Alberto , Guerrero Marta
Published: December 2024

Although mass is one of the most relevant process variables, industries may lack an inline monitoring of mass, which has a high cost in some cases. Due to their availability in sorting processes, cameras have potential as a low-cost alternative for the estimation of mass in recycling applications. Nevertheless, further research is needed to transform image information into mass. This work tackles this challenge by proposing a novel method of converting image information into mass of particles, complementing size measures with intensity and texture features extracted from the whole picture. Models were adjusted, employing machine learning techniques, using an industrial waste sample of post-consumer plastic film. The visual properties showed a dependency on mass labels, and the models achieved an error of 9 g for subsamples between 2 and 82 g. The analysis and validation of this image processing method provide a new alternative for the estimation of particle mass.
A Study on the Application of a Deep Thermal Reservoir by Using a Magnetotelluric Sounding Method: Taking an Example of Geothermal Resources’ Exploration in the Western Taikang Uplift of the Southern North China Basin
Authors: Xu Bowen , Zhu Huailiang , Zhang Min , Yang Zhongyan , Ye Gaofeng , Liu Zhilong , Hu Zhiming , Shao Bingsong , Zhang Yuqi
Published: December 2024

Geothermal resources are abundant in the Southern North China Basin, which is one of the prospective areas hosting low–medium-temperature geothermal resources in sedimentary basins in China. The purpose of this work is to reveal the formation and storage conditions of the geothermal resources in the western margin of the Taikang Uplift and delineate the range of potential geothermal reservoirs. This paper uses five magnetotelluric sounding profiles for data processing and analysis, including the calculation of 2D skewness and electric strike. Data processing, analysis, and NLCG 2D inversion were performed on MT data, which consisted of 111 measurement points, and reliable two-dimensional resistivity models and resistivity planes were obtained. In combination with drilling verification and the analysis of geophysical logging data, the stratigraphic lithology and the range of potential geothermal reservoirs were largely clarified. The results show that using the magnetotelluric sounding method can well delineate the range of deep geothermal reservoirs in sedimentary basins and that the MT method is suitable for exploring buried geothermal resources in deep plains. The analytical results showed that the XZR-1 well yielded 1480 cubic meters of water per day, with the water temperature of the wellhead being approximately 78 °C, and combined with the results of this electromagnetic and drilling exploration, a geothermal geological model and genesis process of the west of the Taikang Uplift area was constructed. The water yield and temperature were higher than those of previous exploration results, which has important guiding significance for the future development and utilization of karst fissure heat reservoirs in the western Taikang Uplift.
Evaluation of Mixing Process in Batch Mixer Using CFD-DEM Simulation and Automatic Post-Processing Method
Authors: Li Guangming , Zhang Zhenbang , Xiang Jiahong , Zhao Haili , Jiao Feng , Chen Tao , Li Guo
Published: December 2024

A batch mixer is an important piece of equipment for polymer filling modification, and the kinematics of agglomerate breakup and distribution are necessary for the structure design and mixing process optimization of the rotor, particularly in light of the cohesive forces that exist within the agglomerate. In this paper, computational fluid dynamics (CFD) was coupled with discrete element method (DEM) to simulate the mixing process, including breakup and distribution, which was further quantitatively evaluated by the post-processing involving numerical method. To study the mixing process of an agglomerate composed of massive spherical particles (individual particle ratio was r), the coordinates of the particles were exported from the CFD-DEM simulation results. Then, the coordinate data were automatically processed with an automate custom-built post-processing program to obtain the average radius of gyration (Rgy) and the particle distribution density (ε). The kinematics analyzation of breakup and distribution was represented by curve of Rgy/r versus mixing time (t) and curve of ε versus t, respectively. The value of Rgy/r and ε decreased over time until they reached an equilibrium and vibrated around a certain value. In particular, a notable decline in the value of Rgy/r was observed following an increase prior to critical time. The increase in Rgy/r stated that the agglomerate or aggregates undergo stretching deformation. Additionally, mixing processes of rotors with different pressurization coefficients (S) and rotation speeds could be facilitated and intensified by large S and high rotation speed. Finally, a “breakup-line” was developed by considering the influence of cohesive force and rotation speed on the agglomerate breakup process. The agglomerate could be broken if the combination of rotation speed and bonding strength was above the “breakup line”, otherwise the agglomerate was not broken. Furthermore, rotors with larger slopes exhibited stronger breakup ability.