bluuebunny/crossref_metadata_2025 huggingface dataset:
Floods and Structural Anthropogenic Barriers (Roads and Waterworks) Affecting the Natural Flow of Waters: Hydraulic Modelling and Proposals for the Final Section of the River Segura (Spain)
Authors: Oliva Antonio , Olcina Jorge
Published: November 2024

Floods are the climate hazard that has the greatest socio-economic and territorial impact on the world. The root causes of these events are atmospheric and hydrological phenomena. However, human action usually aggravates their effects, as it alters the normal functioning of the river courses and water flows. The installation of road, rail and hydraulic infrastructures in a floodplain with no prior calculation or appropriate adaptation exacerbates the negative consequences of floods, increasing the extension of the flooded area and the height of the flood waters. This study addresses the problem of the barrier effect generated, on the one hand, by the layout of the N-332 road, as it is built at the same level as the ground, hindering the flow of overflowing water during episodes of flooding, and on the other hand, the channelling wall of the Segura River in the final stretch of its mouth, in the towns of San Fulgencio and Guardamar del Segura. These elements have aggravated flooding in this area. In order to analyse the consequences of the flood, IBER (v.3.3) software has been used to model a flood with similar effects to that of the episode of September 2019. The current situation has also been analysed with two openings in order to determine the effects that a future flood would have. After analysing the results, a proposal to correct the barrier effect of the N-332 road and the new channelling wall of the River Segura has been elaborated upon and then modelled. The results are positive and effective in reducing the negative effects of floods in the lower basin of the River Segura.
Non-Linear Effects of Gravity Change on Mantle Dynamics
Authors: Mancinelli Paolo , Ranalli Giorgio , Pauselli Cristina
Published: November 2024

Starting from observed variations of the length of day in the past 2.5 billion years, we calculate the corresponding gravity variation and evaluate the possible effects that such variation would have induced on the lithosphere and on mantle convection. The lithospheric stress induced by the observed gravity increase at the equator in 500 Ma is of the same order as the one associated with a convective cell. We model a gravity increase that would result in 1.3 × 10−2 µGal or 1.3 × 10−10 m s−2 over 10 years, a value that is not far from the detection thresholds of modern gravimeters. Gravity increase also affects mantle dynamics by improving convection efficiency. Our models demonstrate that gravity variations contribute to this phenomenon through faster and wider mixing. The results support a view where a convective system being subject to gravity changes responds through non-linear adjustments of its effective mixing at all scales. These findings contribute to a deeper understanding of how gravitational fluctuations may shape the behavior of Earth’s dynamic systems over geological timescales.
Mind the Gap: On the Absence of Writing Women in German-Language Literature of the Czech Lands
Authors: Jičínská Veronika , Ludewig Anna-Dorothea
Published: November 2024

The absence of female writing forms a particularly striking gap in the historiography of German-language literature in the Czech Lands during the decades around 1900. Women participated significantly in the literary scene of the period but were largely forgotten. Our article will discuss the conditions and discourses that enabled women to be active in the public space but later led to their absence in literary history. Approaches are sought that make future inclusion possible again. The first step for (re-)establishing a female presence in this area is to reconstruct biographies with a focus on female-specific social realities at the time and on the interaction of cultural, social and historical factors. In the next step, attention is brought to the “minor” or “simple”, rather non-canonical literary genres that were often used by women authors at the fin de siècle.
Prescription Patterns of Mycophenolate Mofetil in a Group of Patients from Colombia
Authors: Machado-Duque Manuel Enrique , Gaviria-Mendoza Andrés , Valladales-Restrepo Luis Fernando , Vallejos-Narváez Álvaro , Piragauta-Vargas Natalia , Machado-Alba Jorge Enrique
Published: November 2024

Background: Mycophenolate mofetil is used for the prevention of solid organ transplant rejection and for other indications, such as systemic lupus erythematosus (SLE). Objective: To determine the prescription patterns of mycophenolate mofetil in a group of Colombian patients. Methods: This was a cross-sectional study of patients receiving mycophenolate mofetil between 2021 and 2022. The data were obtained from a drug dispensing database. Sociodemographic, clinical (diagnostic), and pharmacological variables were identified. Results: A total of 979 patients who underwent treatment were identified; their mean age was 45.9 ± 17.1 years, and 87.4% were women. The main diagnosis associated with the use of mycophenolate mofetil was SLE (39.1%), followed by other rheumatic diseases (8.5%), nephrotic syndrome (7.5%), and solid organ transplantation (6.4%). The relationship between the mean dose and the defined daily dose was 0.75. Ten percent of patients received mycophenolate alone, whereas 32.9% received mycophenolate in combination therapy with conventional disease-modifying antirheumatic drugs and glucocorticoids. A total of 76.2% had polypharmacy (five or more drugs). Conclusions: Mycophenolate mofetil is used mainly in combination therapy for patients with SLE and other rheumatological diseases and for solid organ transplants at doses lower than those recommended.
Biological Characteristics, Domestication and Cultivation of Wild Tyromyces kmetii
Authors: Huang Haichen , Li Xiaomin , Hu Xin , Sun Huijuan , Zhang Junli , Wu Xiaoping , Fu Junsheng
Published: November 2024

To develop and utilize the wild fungi resources in Tibet, a wild fungal specimen collected from Qiangna Town, Milin County, Tibet was isolated, purified, and characterized. Through morphological examination and ITS sequence analysis, the strain—designated as X21266—was identified as Tyromyces kmetii. The effects of different carbon sources, nitrogen sources, pH, and temperature on the mycelial growth of T. kmetii under solid-state culture conditions were investigated. In addition, research on domestication cultivation was conducted. The results showed that the optimal carbon source for T. kmetii was fructose, the preferred nitrogen source was beef powder, and the optimal pH and temperature were pH 5.0 and 25 °C, respectively. Domestication cultivation results showed a mycelial initiation time of 34 days; primordia formation occurred after 17 days in an environment with appropriate light and low-temperature stimulation; and during the fruiting stage, a temperature of 25–28 °C and humidity above 90% were maintained, with mature fructification forming after 16 days. This study provides fundamental experimental data for the subsequent development and utilization of T. kmetii.
Smartphone-Based Leaf Colorimetric Analysis of Grapevine (Vitis vinifera L.) Genotypes
Authors: Bodor-Pesti Péter , Taranyi Dóra , Vértes Gábor , Fazekas István , Nyitrainé Sárdy Diána Ágnes , Deák Tamás , Varga Zsuzsanna , Baranyai László
Published: November 2024

Leaf chlorophyll content is a key indicator of plant physiological status in viticulture; therefore, regular evaluation to obtain data for nutrient supply and canopy management is of vital importance. The measurement of pigmentation is most frequently carried out with hand-held instruments, destructive off-site spectrophotometry, or remote sensing. Moreover, smartphone-based applications also ensure a promising way to collect colorimetric information that could correlate with pigmentation. In this study, four grapevine genotypes were investigated using smartphone-based RGB (Red, Green, Blue) and CIE-L*a*b* colorimetry and a portable chlorophyll meter. The objective of this study was to evaluate the correlation between leaf chlorophyll concentration and RGB- or CIE-L*a*b*-based color indices. A further aim was to find an appropriate model for discriminating between the genotypes by leaf coloration. For these purposes, fully developed leaves of ‘Chardonnay’, ‘Sauvignon blanc’, and ‘Pinot noir’ clones 666 and 777 were investigated with the Color Grab smartphone application to obtain RGB and CIE-L*a*b* values. Using these color values, chroma, hue, and a further 31 color indices were calculated. Chlorophyll concentrations were determined using an Apogee MC100 device, and the values were correlated with color values and color indices. The results showed that the chlorophyll concentration and color indices significantly differed between the genotypes. According to the results, certain color indices show a different direction in their relationship with leaf pigmentation for different grapevine genotypes. The same index showed a positive correlation for the leaf chlorophyll concentration for one variety and a negative correlation for another, which raises the possibility that the relationship is genotype-specific and not uniform within species. In light of this result, further study of the species specificity of the commonly used vegetation indices is warranted. Support Vector Machine (SVM) analysis of the samples based on color properties showed a 71.63% classification accuracy, proving that coloration is an important ampelographic feature for the identification and assessment of true-to-typeness.
TPTrans: Vessel Trajectory Prediction Model Based on Transformer Using AIS Data
Authors: Wang Wentao , Xiong Wei , Ouyang Xue , Chen Luo
Published: November 2024

The analysis of large amounts of vessel trajectory data can facilitate more complex traffic management and route planning, thereby reducing the risk of accidents. The application of deep learning methods in vessel trajectory prediction is becoming more and more widespread; however, due to the complexity of the marine environment, including the influence of geographical environmental factors, weather factors, and real-time traffic conditions, predicting trajectories in less constrained maritime areas is more challenging than in path network conditions. Ship trajectory prediction methods based on kinematic formulas work well in ideal conditions but struggle with real-world complexities. Machine learning methods avoid kinematic formulas but fail to fully leverage complex data due to their simple structure. Deep learning methods, which do not require preset formulas, still face challenges in achieving high-precision and long-term predictions, particularly with complex ship movements and heterogeneous data. This study introduces an innovative model based on the transformer structure to predict the trajectory of a vessel. First, by processing the raw AIS (Automatic Identification System) data, we provide the model with a more efficient input format and data that are both more representative and concise. Secondly, we combine convolutional layers with the transformer structure, using convolutional neural networks to extract local spatiotemporal features in sequences. The encoder and decoder structure of the traditional transformer structure is retained by us. The attention mechanism is used to extract the global spatiotemporal features of sequences. Finally, the model is trained and tested using publicly available AIS data. The prediction results on the field data show that the model can predict trajectories including straight lines and turns under the field data of complex terrain, and in terms of prediction accuracy, our model can reduce the mean squared error by at least 6×10−4 compared with the baseline model.
The Coordinated Changes in Platelet Glycan Patterns with Blood Serotonin and Exosomes
Authors: Kilic Fusun
Published: November 2024

The structures of glycans, specifically their terminal positions, play an important role as ligands for receptors in regulating the adhesion ability of platelets. Recent advances in our understanding of free/unbound serotonin (5-HT) in blood plasma at supraphysiological levels implicate it as one of the most profound influencers in remodeling the platelet’s surface N-glycans. Proteomic analysis of the membrane vesicles identified enzymes, specifically glycosyltransferases, only on the surface of the platelets isolated from the supraphysiological level of 5-HT-containing blood plasma. However, these enzymes can only be effective on the cell surface under certain biological conditions, such as the level of their substrates, temperature, and pH of the environment. We hypothesize that exosomes released from various cells coordinate the required criteria for the enzymatic reaction on the platelet surface. The elevated plasma 5-HT level also accelerates the release of exosomes from various cells, as reported. This review summarizes the findings from a wide range of literature and proposes mechanisms to coordinate the exosomes and plasma 5-HT in remodeling the structures of N-glycans to make platelets more prone to aggregation.
Metabolic, Inflammatory, and Molecular Impact of Cancer Cachexia on the Liver
Authors: Gonçalves Daniela Caetano , Gomes Silvio Pires , Seelaender Marília
Published: November 2024

Cancer-associated cachexia (CAC) is a severe wasting syndrome, marked by involuntary weight loss and muscle wasting. It is a leading cause of cancer-related morbidity and mortality, and is driven by systemic, chronic low-grade inflammation. Key cytokines, such as IL-6 and GDF15, activate catabolic pathways in many organs. This study examined the role of inflammation and metabolic disruption in the liver during CAC, focusing on its dual role as both a target and a source of inflammatory factors. The analysis covered protein and lipid metabolism disturbances, including the hepatic production of acute-phase proteins and insulin resistance. Hepatic inflammation contributes to systemic dysfunction in CAC. The increased production of C-Reactive Protein (CRP) impacts muscle wasting, while liver inflammation leads to insulin resistance and hepatic steatosis, aggravating the cachectic state. Therefore, understanding the molecular mechanisms of liver metabolism in CAC is essential for developing effective therapies. Potential interventions include anti-inflammatory treatments, anabolic strategies, and restoration of lipid metabolism. Further research is necessary to explore the liver’s full contribution to CAC and its systemic effects, allowing to the development of liver-targeted therapeutic strategies.
Novel Core Gene Signature Associated with Inflammation-to-Metaplasia Transition in Influenza A Virus-Infected Lungs
Authors: Savin Innokenty A. , Sen’kova Aleksandra V. , Goncharova Elena P. , Zenkova Marina A. , Markov Andrey V.
Published: November 2024

Respiratory infections caused by RNA viruses are a major contributor to respiratory disease due to their ability to cause annual epidemics with profound public health implications. Influenza A virus (IAV) infection can affect a variety of host signaling pathways that initiate tissue regeneration with hyperplastic and/or dysplastic changes in the lungs. Although these changes are involved in lung recovery after IAV infection, in some cases, they can lead to serious respiratory failure. Despite being ubiquitously observed, there are limited data on the regulation of long-term recovery from IAV infection leading to normal or dysplastic repair represented by inflammation-to-metaplasia transition in mice or humans. To address this knowledge gap, we used integrative bioinformatics analysis with further verification in vivo to elucidate the dynamic molecular changes in IAV-infected murine lung tissue and identified the core genes (Birc5, Cdca3, Plk1, Tpx2, Prc1. Rrm2, Nusap1, Spag5, Top2a, Mcm5) and transcription factors (E2F1, E2F4, NF-YA, NF-YB, NF-YC) involved in persistent lung injury and regeneration processes, which may serve as gene signatures reflecting the long-term effects of IAV proliferation on the lung. Further analysis of the identified core genes revealed their involvement not only in IAV infection but also in COVID-19 and lung neoplasm development, suggesting their potential role as biomarkers of severe lung disease and its complications represented by abnormal epithelial proliferation and oncotransformation.
Biological Insights and Recent Advances in Plant Long Non-Coding RNA
Authors: Zhao Zhihao , Yang Yaodong , Iqbal Amjad , Wu Qiufei , Zhou Lixia
Published: November 2024

Long non-coding RNA (lncRNA) refers to an RNA molecule longer than 200 nucleotides (nt) that plays a significant role in regulating essential molecular and biological processes. It is commonly found in animals, plants, and viruses, and is characterized by features such as epigenetic markers, developmental stage-specific expression, and tissue-specific expression. Research has shown that lncRNA participates in anatomical processes like plant progression, while also playing a crucial role in plant disease resistance and adaptation mechanisms. In this review, we provide a concise overview of the formation mechanism, structural characteristics, and databases related to lncRNA in recent years. We primarily discuss the biological roles of lncRNA in plant progression as well as its involvement in response to biotic and abiotic stresses. Additionally, we examine the current challenges associated with lncRNA and explore its potential application in crop production and breeding. Studying plant lncRNAs is highly significant for multiple reasons: It reveals the regulatory mechanisms of plant growth and development, promotes agricultural production and food security, and drives research in plant genomics and epigenetics. Additionally, it facilitates ecological protection and biodiversity conservation.
Dioxin-Induced PAI-1 Expression: A Novel Pathway to Pancreatic β-Cell Failure in Type 2 Diabetes
Authors: Im Suyeol , Kang Sora , Son Woo Jung , Son Minuk , Oh Seung Jun , Yoon Hye Ji , Pak Youngmi Kim
Published: November 2024

Exposure to environment-polluting chemicals (EPCs), which are ligands of the aryl hydrocarbon receptor (AhR), is associated with the development of type 2 diabetes (T2D). This study explores the mechanisms by which AhR ligands contribute to β-cell failure in T2D. Incubation of RINm5F rat pancreatic β-cells with low-dose 2,3,7,8-tetrachlorodibenzodioxin (TCDD), the most potent AhR ligand, inhibited glucose-stimulated insulin secretion (GSIS). A single injection of TCDD in wild type mice reduced the size of Langerhans islets, but not in AhR liver knock-out mice (AhR-LKO). RNA-seq database analysis identified Serpine1, encoding for plasminogen activator inhibitor type-1 (PAI-1) as a TCDD-mediated secretory protein that is synthesized in an AhR-dependent manner in the liver. Elevated PAI-1 levels were shown to induce Caspase-3/7-dependent apoptosis in RINm5F cells, suggesting a novel pathway through which EPCs exacerbate T2D. These findings support the hypothesis that chronic exposure to AhR ligands may directly inhibit GSIS in pancreatic β-cells and indirectly induce β-cell apoptosis through increased PAI-1. This study provides new insights into the EPC-PAI-1 axis as a missing link between pancreatic β-cell failure and the progression of T2D and offers a potential target for therapeutic intervention.
Prokaryote- and Eukaryote-Based Expression Systems: Advances in Post-Pandemic Viral Antigen Production for Vaccines
Authors: Khudainazarova Nelli S. , Granovskiy Dmitriy L. , Kondakova Olga A. , Ryabchevskaya Ekaterina M. , Kovalenko Angelina O. , Evtushenko Ekaterina A. , Arkhipenko Marina V. , Nikitin Nikolai A. , Karpova Olga V.
Published: November 2024

This review addresses the ongoing global challenge posed by emerging and evolving viral diseases, underscoring the need for innovative vaccine development strategies. It focuses on the modern approaches to creating vaccines based on recombinant proteins produced in different expression systems, including bacteria, yeast, plants, insects, and mammals. This review analyses the advantages, limitations, and applications of these expression systems for producing vaccine antigens, as well as strategies for designing safer, more effective, and potentially ‘universal’ antigens. The review discusses the development of vaccines for a range of viral diseases, excluding SARS-CoV-2, which has already been extensively studied. The authors present these findings with the aim of contributing to ongoing research and advancing the development of antiviral vaccines.
Two-Stage Combined Model for Short-Term Electricity Forecasting in Ports
Authors: Song Wentao , Cao Xiaohua , Jiang Hanrui , Li Zejun , Gao Ruobin
Published: November 2024

With an increasing emphasis on energy conservation, emission reduction, and power consumption management, port enterprises are focusing on enhancing their electricity load forecasting capabilities. Accurate electricity load forecasting is crucial for understanding power usage and optimizing energy allocation. This study introduces a novel approach that transcends the limitations of single prediction models by employing a Binary Fusion Weight Determination Method (BFWDM) to optimize and integrate three distinct prediction models: Temporal Pattern Attention Long Short-Term Memory (TPA-LSTM), Multi-Quantile Recurrent Neural Network (MQ-RNN), and Deep Factors. We propose a two-phase process for constructing an optimal combined forecasting model for port power load prediction. In the initial phase, individual prediction models generate preliminary outcomes. In the subsequent phase, these preliminary predictions are used to construct a combination forecasting model based on the BFWDM. The efficacy of the proposed model is validated using two actual port data, demonstrating high prediction accuracy with a Mean Absolute Percentage Error (MAPE) of only 6.23% and 7.94%. This approach not only enhances the prediction accuracy but also improves the adaptability and stability of the model compared to other existing models.
Sternal Wound Reconstruction Following Deep Sternal Wound Infection: Past, Present and Future: A Literature Review
Authors: Khashkhusha Arwa , Butt Sundas , Abdelghaffar Mariam , Wang William , Rajananthanan Asveny , Roy Sakshi , Khurshid Bakht Noor , Zeinah Mohamed , Harky Amer
Published: November 2024

This literature review critically examines the historical, current, and prospective dimensions of sternal wound reconstruction in the specific context of deep sternal wound infection (DSWI), aiming to enhance patient outcomes and optimise surgical techniques. Preventive measures, including prophylactic antibiotic administration and surgical site preparation, are crucial in reducing the incidence of DSWI. Effective management necessitates a multidisciplinary approach encompassing surgical debridement, drainage, and sternum repair utilising diverse procedures in conjunction with antibiotic therapy. Traditional approaches to managing DSWI involved closed irrigation and drainage techniques. While these methods exhibited certain advantages, they also exhibited limitations and varying degrees of success. The current care paradigms emphasise prophylactic antibiotic administration and surgical interventions like closed suction and irrigation, vacuum-assisted closure, and flap reconstruction. Future advancements in surgical techniques and technology hold promise for further enhancing sternal wound reconstruction. This review separates and emphasises the distinct roles of prophylaxis, antibiotic treatment, and reconstructive techniques, each relevant specifically to DSWI management. Collaborative efforts between cardiac and plastic surgeons, supported by ongoing research and innovation, are indispensable to advance sternal wound restoration and achieve superior outcomes in terms of patient welfare, morbidity and mortality reduction, and surgical efficacy.
Evaluation of Retinal and Posterior Segment Vascular Changes Due to Systemic Hypoxia Using Optical Coherence Tomography Angiography
Authors: Levinger Nadav , Erdinest Nir , Abu Rmeileh Ayman , Mouallem Eisa , Zahran Shadi , Shabat Sheer , Kolben Yotam , Aviv Talmon , Kuint Rottem , Tiosano Liran , Khateb Samer
Published: November 2024

Background/Objectives: Retinal vascular occlusions are a significant cause of visual impairment in older adults, resulting in ischemic retinal damage and sudden vision loss. This study evaluates the retinal, optic nerve head (ONH), and choroidal capillary networks in chronic and acute-on-chronic hypoxia compared to normal controls using optical coherence tomography angiography (OCT-A). Methods: We evaluated a prospective study including twenty patients in the hypoxic group (mean age 61.2 ± 10.2) in two phases, chronic hypoxia and acute-on-chronic hypoxia, and 21 control subjects (mean age 59 ± 9.4 years). All patients underwent a comprehensive eye examination, OCT, and OCT-A imaging. The data were analyzed using OCT-A analysis software (Zeiss OCT-A software 2.1.0.55513) and Fiji software (1.51a). Vascular density of the retina and ONH, choriocapillaries, and foveal avascular zone (FAZ) size were measured. Results: The superficial peripapillary vascular density was higher for the control group (0.387 ± 0.03) compared to the hypoxic patients with (0.383 ± 0.03) and without O2 supplementation (0.383 ± 0.03; p = 0.018). No retinal angiographic differences were identified between the two study groups. The ganglion cell layer (GCL) was thinner in the hypoxic group. Both hypoxic subgroups demonstrated denser choriocapillaries (mean 13,073 ± 1812 and 12,689 ± 1815, with and without O2 supplementation, respectively) compared to the control group (mean 9749 ± 2881, p < 0.001 for both groups). Hypoxic patients demonstrated increased area size of choriocapillaries (+O2 supplementation—mean 44,347 ± 10,563; −O2 supplementation—mean 46,984 ± 12,822) compared to the control group (mean 30,979 ± 9635; p < 0.01 and p < 0.001, respectively). Conclusions: Chronic and acute-on-chronic hypoxia did not affect the retinal vascular network, most probably due to the strong autoregulation of vascular function of the retina. However, compared to the control group, GCL, ONH vasculature density, and most choriocapillaries indices were significantly altered among hypoxic patients.
StepFit-18K: Improving Irritable Bowel Syndrome (IBS) Symptoms with a Simple, Structured Walking Intervention
Authors: Franco Isabella , Bianco Antonella , Prospero Laura , Riezzo Giuseppe , Bonfiglio Caterina , Bagnato Claudia Beatrice , Verrelli Nicola , Goscilo Francesco , D’Attoma Benedetta , Ignazzi Antonia , Coletta Sergio , Refolo Maria Grazia , Donghia Rossella , Russo Francesco
Published: November 2024

Background: Irritable Bowel Syndrome (IBS) is a chronic functional gastrointestinal (GI) disorder characterized by abdominal pain, altered bowel habits, and bloating, affecting approximately 10.1% of the global population. While current treatments emphasize dietary modifications and symptom management, emerging evidence suggests that physical activity (PA) may help alleviate IBS symptoms. This study evaluated the effects of a structured walking program, “StepFit-18K”, on IBS symptom relief. Methods: A total of 106 participants (68 females and 38 males) completed the 12-week intervention, which consisted of 18,000 additional steps per week (6000 extra steps on three days per week) tracked via fitness devices. The program emphasized step count, ease of adoption, and social support through walking groups. Results: As assessed by validated questionnaires, significant reductions in GI symptoms were observed. The IBS Symptom Severity Score (IBS-SSS) decreased from 118.30 ± 98.73 to 74.46 ± 74.93, with a delta score of −43.84%, highlighting bloating as the most improved symptom. No clinically significant changes were observed in anthropometric or biochemical markers. Conclusions: StepFit-18K is a simple, accessible, and effective form of physical activity that has demonstrated therapeutic benefits for IBS symptoms. This offers an additional application beyond its well-established role in preventing cardiovascular diseases.
A Comparison of Open Ventral Hernia Repair Risk Stratification Systems: A Call for Consensus
Authors: Talpai Tamás , Râmboiu Dumitru Sandu , Pîrvu Cătălin Alexandru , Pantea Stelian , Șelaru Mircea , Cârțu Dan , Preda Silviu Daniel , Pătrașcu Ștefan , Mărgăritescu Nicolae Dragoș , Bică Marius , Șurlin Valeriu-Marin
Published: November 2024

Background/Objectives: Ventral hernia repair (VHR) is a common surgical intervention linked to specific surgical site complications. In such occurrences, the related morbidity is often substantial. Although known risk factors have long been recognized, their systematic inclusion in risk stratification systems lacks universal validation. This study evaluates the effectiveness and correspondence of three risk assessment tools—CeDAR, VHWG, and the modified VHWG—in predicting postoperative wound complications in VHR patients. Methods: We analyzed data from 203 patients who underwent VHR for incisional midline or lateral wall hernia across two surgical departments between 2019 and 2023. Each patient was scored using CeDAR, VHWG, and the modified VHWG systems. Outcomes were assessed based on surgical site occurrences (SSOs) such as seroma formation, wound infections, and recurrences. Results: The incidence of SSOs was 8.9%, with two recorded deaths (0.89%). CeDAR scores showed a statistically significant relationship with SSOs but failed to accurately predict complication rates across subgroups. The VHWG grading system effectively predicted higher complication rates for grades III and IV compared to grades I and II, though its modified version did not show significant predictive improvements. Secondary outcomes indicated a higher SSO rate in patients requiring posterior component separation (TAR) and those with larger hernia defects, though the differences were not statistically significant. Major preoperative risk factors, including smoking, diabetes, and obesity, did not show significant correlations with SSO rates in this study. Conclusions: Current risk estimation tools inadequately predict SSOs in VHR. Enhancing prediction accuracy will require incorporating both patient-specific and surgical factors, potentially through advanced algorithms and large-scale studies.
ssc-cdi: A Memory-Efficient, Multi-GPU Package for Ptychography with Extreme Data
Authors: Tonin Yuri Rossi , Peixinho Alan Zanoni , Brandao-Junior Mauro Luiz , Ferraz Paola , Miqueles Eduardo Xavier
Published: November 2024

We introduce ssc-cdi, an open-source software package from the Sirius Scientific Computing family, designed for memory-efficient, single-node multi-GPU ptychography reconstruction. ssc-cdi offers a range of reconstruction engines in Python version 3.9.2 and C++/CUDA. It aims at developing local expertise and customized solutions to meet the specific needs of beamlines and user community of the Brazilian Synchrotron Light Laboratory (LNLS). We demonstrate ptychographic reconstruction of beamline data and present benchmarks for the package. Results show that ssc-cdi effectively handles extreme datasets typical of modern X-ray facilities without significantly compromising performance, offering a complementary approach to well-established packages of the community and serving as a robust tool for high-resolution imaging applications.
Data-Driven Analysis of Ocean Fronts’ Impact on Acoustic Propagation: Process Understanding and Machine Learning Applications, Focusing on the Kuroshio Extension Front
Authors: Xu Weishuai , Zhang Lei , Li Ming , Ma Xiaodong , Li Maolin
Published: November 2024

Ocean fronts, widespread across the global ocean, cause abrupt shifts in physical properties such as temperature, salinity, and sound speed, significantly affecting underwater acoustic communication and detection. While past research has concentrated on qualitative analysis and small-scale research on ocean front sections, a comprehensive analysis of ocean fronts’ characteristics and their impact on underwater acoustics is lacking. This study employs high-resolution reanalysis data and in situ observations to accurately identify ocean fronts, sound speed structures, and acoustic propagation features from over six hundred thousand Kuroshio Extension Front (KEF) sections. Utilizing marine big data statistics and machine learning evaluation metrics such as out-of-bag (OOB) error and Shapley values, this study quantitatively assesses the variations in sound speed structures across the KEF and their effects on acoustic propagation shifts. This study’s key findings reveal that differences in sound speed structure are significantly correlated with KEF strength, with the channel axis depth and conjugate depth increasing with front strength, while the thermocline intensity and depth excess decrease. Acoustic propagation features in the KEF environment exhibit notable seasonal variations.
Dual Transcriptome Analysis Reveals the Changes in Gene Expression in Both Cotton and Verticillium dahliae During the Infection Process
Authors: Li Yongtai , Li Yuanjing , Yang Qingwen , Song Shenglong , Zhang Yong , Zhang Xinyu , Sun Jie , Liu Feng , Li Yanjun
Published: November 2024

Cotton is often threatened by Verticillium wilt caused by V. dahliae. Understanding the molecular mechanism of V. dahlia–cotton interaction is important for the prevention of this disease. To analyze the transcriptome profiles in V. dahliae and cotton simultaneously, the strongly pathogenic strain Vd592 was inoculated into cotton, and the infected cotton roots at 36 h and 3 d post infection were subjected to dual RNA-seq analysis. For the V. dahliae, transcriptomic analysis identified 317 differentially expressed genes (DEGs) encoding classical secreted proteins, which were up-regulated at least at one time point during infection. The 317 DEGs included 126 carbohydrate-active enzyme (CAZyme) and 108 small cysteine-rich protein genes. A pectinesterase gene (VDAG_01782) belonging to CAZyme, designated as VdPE1, was selected for functional validation. VdPE1 silencing by HIGS (host-induced gene silencing) resulted in reduced disease symptoms and the increased resistance of cotton to V. dahliae. For the cotton, transcriptomic analysis found that many DEGs involved in well-known disease resistance pathways (flavonoid biosynthesis, plant hormone signaling, and plant–pathogen interaction) as well as PTI (pattern-triggered immunity) and ETI (effector-triggered immunity) processes were significantly down-regulated in infected cotton roots. The dual RNA-seq data thus potentially connected the genes encoding secreted proteins to the pathogenicity of V. dahliae, and the genes were involved in some disease resistance pathways and PTI and ETI processes for the susceptibility of cotton to V. dahliae. These findings are helpful in the further characterization of candidate genes and breeding resistant cotton varieties via genetic engineering.
The Use of Green Infrastructure in the Suburbs: Insights from Three European Cities
Authors: Hossu Constantina-Alina , Breuste Jürgen , Iojă Ioan-Cristian , Onose Diana Andreea , Vrînceanu Alexandra , Ponizy Lidia , Zwierzchowska Iwona , Kryger Roksana , Mizgajski Andrzej
Published: November 2024

Living close to green infrastructure (GI) components might be the dream of many people who are often exposed to cities’ pollution, congestion, or lack of green amenities. Due to its multiple benefits, green infrastructure plays a significant role in driving people’s decisions to leave inner-city areas and move to suburban locations. However, how GI components are used once people move into the suburbs must be better understood. Thus, this study explores residents’ rationales for leaving the inner city and moving to the suburbs and how they use suburban GI components. A survey was undertaken in six suburbs from three European cities: Poznań (Poland), Salzburg (Austria), and Bucharest (Romania). We found that people self-reported that green amenities were the main reason for choosing a suburban residence. Furthermore, those residents who moved to the suburbs were more interested in using their private gardens than larger parks and prefer natural green areas with high potential for recreation to agricultural landscapes for leisure. This study advocates for investment in private green spaces in suburban developments due to their deep interweaving with residents’ leisure preferences.
The Influences of Parameters on the Dynamic Characteristics of a Multi-Foil Aerodynamic Journal Bearing with Bump-Backing Foils: Model Predictions
Authors: Jiang Yulong , Zhu Qianjing , Xu Bo , Huang Zhongwen , Gao Dongyan
Published: November 2024

In this work, the development and implementation of a dynamic characteristics model for a specific multi-foil aerodynamic journal bearing with bump-backing foils (MFJB) is considered. Based on the previously established static characteristics model, the elastohydrodynamic influence is carefully considered, and the perturbation method is adopted, as this model is more effective and computationally efficient. The effects of the operational, structural, and geometric parameters on stiffness and damping coefficients are emphasized. The results show that the eccentricity ratio effects are more intensive when the bearing speed is at a moderately high level, which is no more than approximately 30,000 rpm. The foil thickness has obvious effects on dynamic characteristics, whereas the influence of the elastic modulus is limited. Within the research scope, the eight-foils bearing exhibits a better performance than the four-foils. This paper is designed to provide effective methods and supply theoretical guidance for improving the engineering design and operational stability of bearings.
Research on Active–Passive Training Control Strategies for Upper Limb Rehabilitation Robot
Authors: Yang Yongming
Published: November 2024

Due to accidents, upper limb movement disorders have become increasingly common. Training can help restore muscle strength and rebuild neurological function. However, the existing single mode has limitations in adapting to the training needs of different rehabilitation stages. Therefore, this paper conducts research on active–passive training control strategies for an upper limb rehabilitation robot. It establishes an upper limb kinematic model based on the Lagrange method and builds a man–machine integration dynamics model for upper limb rehabilitation in MATLAB (R2016a)/Simulink. A design active controller, passive controller, and switching controller based on PI and feedforward compensation strategies are proposed to improve training control accuracy. The output moment of the system during active training is planned to ensure the safety and stability of the training process. By utilizing neural networks to train sample data during rehabilitation training, the fuzzy rules and membership functions in fuzzy intention recognition algorithm are optimized to improve the accuracy of intention recognition during training. By adopting the independently developed experimental platform for the upper limb rehabilitation robot, active–passive training, intention recognition, and training mode switching are achieved. The results show that the active and passive training processes are smooth, the training intention recognition is accurate, and the switching between active and passive training modes is steady. This verifies the feasibility and effectiveness of the established mathematical model in upper limb rehabilitation training.
Multi-Axis Servo System Control Design Considering Low-Speed Friction Dynamics
Authors: Liu Huimin , Wang Rui
Published: November 2024

This paper introduces an extended state observer-based command filtered backstepping control method to improve the tracking accuracy and synchronization performance of multi-motor-driving servo systems under the condition of low-speed nonlinear friction dynamics. Firstly, a novel and effective four-motor synchronization scheme is designed and various groups of synchronization feedback signals are introduced to achieve accurate synchronization performance among motors. Then, the observer is designed to estimate the friction torque. And the controller is developed via command filtered backstepping technique to avoid additional computational complexity, making the control signals suitable for practical application. Finally, the stability of the closed-loop system is analyzed, and the tracking and synchronization performance is verified through designed experiments.
Comprehensive Evaluation Method of Privacy-Preserving Record Linkage Technology Based on the Modified Criteria Importance Through Intercriteria Correlation Method
Authors: Han Shumin , Li Yue , Shen Derong , Wang Chuang
Published: November 2024

The era of big data has brought rapid growth and widespread application of data, but the imperfections in the existing data integration system have become obstacles to its high-quality development. The conflict between data security and shared utilization is significant, with traditional data integration methods risking data leakage and privacy breaches. The proposed Privacy-Preserving Record Linkage (PPRL) technology, has effectively resolved this contradiction, enabling efficient and secure data sharing. Currently, many solutions have been developed for PPRL issues, but existing assessments of PPRL methods mainly focus on single indicators. There is a scarcity of comprehensive evaluation and comparison frameworks that consider multiple indicators of PPRL(such as linkage quality, computational efficiency, and security), making it challenging to achieve a comprehensive and objective assessment. Therefore, it has become an urgent issue for us to conduct a multi-indicator comprehensive evaluation of different PPRL methods to explore the optimal approach. This article proposes the use of an modified CRITIC method to comprehensively evaluate PPRL methods, aiming to select the optimal PPRL method in terms of linkage quality, computational efficiency, and security. The research results indicate that the improved CRITIC method based on mathematical statistics can achieve weight allocation more objectively and quantify the allocation process effectively. This approach exhibits exceptional objectivity and broad applicability in assessing various PPRL methods, thereby providing robust scientific support for the optimization of PPRL techniques.
A Novel Axial Load Inversion Method for Rock Bolts Based on the Surface Strain of a Bearing Plate
Authors: Lei Yongchao , Xu Xingliang , Tian Suchuan , Shi Hao
Published: November 2024

Anchor rock bolts are among the essential support components employed in coal mine support engineering. Measuring the axial load of the supporting anchor bolts constitutes an important foundation for evaluating the support effect and the mechanical state of the surrounding rock. The existing methods for measuring the axial load of rock bolts have difficulty meeting the actual demands in terms of accuracy and means. Therefore, we propose a novel inverse method for determining the axial load of rock bolts. On the basis of the dynamic relationship between the axial load of the anchor bolt and the strain of the plate, a calculation model for the inverse analysis of the axial load from the plate strain is presented, and it is verified and corrected through finite element analysis and indoor physical experiments. By combining the calculation model with the digital image correlation method, a low costinversion of the axial load of the anchor bolt in actual support engineering is achieved. The experimental results demonstrate that the average errors of the load inversion of anchor bolts in three different states via the theory and method proposed in this paper are less than 8.8% (4 kN), 3.6% (3.2 kN), and 14.7% (5.5 kN), respectively, and the average error of the axial load of the rock bolts in the proposed method is only 4.23 kN. It possesses relatively high accuracy and can be effectively applied in the actual production processes of mines.
Deep Neural Network Model for Hurst Exponent: Learning from R/S Analysis
Authors: Di Persio Luca , Dufera Tamirat Temesgen
Published: November 2024

This paper proposes a deep neural network (DNN) model to estimate the Hurst exponent, a crucial parameter in modelling stock market price movements driven by fractional geometric Brownian motion. We randomly selected 446 indices from the S&P 500 and extracted their price movements over the last 2010 trading days. Using the rescaled range (R/S) analysis and the detrended fluctuation analysis (DFA), we computed the Hurst exponent and related parameters, which serve as the target parameters in the DNN architecture. The DNN model demonstrated remarkable learning capabilities, making accurate predictions even with small sample sizes. This addresses a limitation of R/S analysis, known for biased estimates in such instances. The significance of this model lies in its ability, once trained, to rapidly estimate the Hurst exponent, providing results in a small fraction of a second.
Conjectures About Wheels Without One Edge with Paths and Cycles
Authors: Staš Michal , Timková Mária
Published: November 2024

The crossing number cr(G) of a graph G is the minimum number of edge crossings over all drawings of G in the plane. The main aim of this paper is to give the crossing numbers of the join products G*+Pn and G*+Cn for the connected graph G* obtained by removing one edge (incident with the dominating vertex) from the wheel W5 on six vertices, and where Pn and Cn are paths and cycles on n vertices, respectively. Finally, we also introduce four new conjectures concerning crossing numbers of the join products of Pn and Cn with Wm∖e obtained by removing one edge (of both possible types) from the wheel Wm on m+1 vertices.
A Mathematical Lens on the Zoonotic Transmission of Lassa Virus Infections Leading to Disabilities in Severe Cases
Authors: Ramzan Yasir , Alzubadi Hanadi , Awan Aziz Ullah , Guedri Kamel , Alharthi Mohammed , Fadhl Bandar M.
Published: November 2024

This study aims to analyze the dynamics of Lassa fever transmission and its impact on the brain and spinal cord then devise and analyze preventive actions. The stability of the infection-free equilibrium point is evaluated; the model’s precision is examined using empirical data; and all parameters are estimated and fitted. Subsequently, the basic reproductive number is determined, and subpopulation trends are observed over time. Sensitivity analysis is conducted to identify critical drivers influencing transmission dynamics. Two-dimensional plots visualize the impact of crucial parameters on the reproductive number. Through a comprehensive literature review and case analysis, an association between Lassa fever and various disabilities is established, including conditions such as encephalitis, hearing loss, ataxia, neuropsychiatric manifestations, meningitis, seizures, and coma. Solutions are devised and analyzed to enhance early detection, treatment, and mitigation of disease.