bluuebunny/crossref_metadata_2025 huggingface dataset:
Microbial community structure in recovering forests of Mount St. Helens
Authors: Maltz Mia Rose , Allen Michael F. , Phillips Michala L. , Hernandez Rebecca R. , Shulman Hannah B. , Freund Linton , Andrews Lela V. , Botthoff Jon K. , Aronson Emma L.
Published: November 2024

Introduction

The 1980 eruption of Mount St. Helens had devastating effects above and belowground in forested montane ecosystems, including the burial and destruction of soil microbes. Soil microbial propagules and legacies in recovering ecosystems are important for determining post-disturbance successional trajectories. Soil microorganisms regulate nutrient cycling, interact with many other organisms, and therefore may support successional pathways and complementary ecosystem functions, even in harsh conditions. Historic forest management methods, such as old-growth and clearcut regimes, and locations of historic short-term gopher enclosures (Thomomys talpoides), to evaluate community response to forest management practices and to examine vectors for dispersing microbial consortia to the surface of the volcanic landscape. These biotic interactions may have primed ecological succession in the volcanic landscape, specifically Bear Meadow and the Pumice Plain, by creating microsite conditions conducive to primary succession and plant establishment.

Methods and results

Using molecular techniques, we examined bacterial, fungal, and AMF communities to determine how these variables affected microbial communities and soil properties. We found that bacterial/archaeal 16S, fungal ITS2, and AMF SSU community composition varied among forestry practices and across sites with long-term lupine plots and gopher enclosures. The findings also related to detected differences in C and N concentrations and ratios in soil from our study sites. Fungal communities from previously clearcut locations were less diverse than in gopher plots within the Pumice Plain. Yet, clearcut meadows harbored fewer ancestral AM fungal taxa than were found within the old-growth forest.

Discussion

By investigating both forestry practices and mammals in microbial dispersal, we evaluated how these interactions may have promoted revegetation and ecological succession within the Pumice Plains of Mount St. Helens. In addition to providing evidence about how dispersal vectors and forest structure influence post-eruption soil microbiomes, this project also informs research and management communities about belowground processes and microbial functional traits in facilitating succession and ecosystem function.
Two novel sites determine genetic relationships between CPV-2 and FPV: an epidemiological survey of canine and feline parvoviruses in Changchun, China (2020)
Authors: Li Zishu , Cai Jiaxi , Feng Chuchu , Wang Yu , Fang Shuren , Xue Xianghong
Published: November 2024

Canine parvovirus (CPV-2) and feline parvovirus (FPV) cause severe hemorrhagic diarrhea disease in dogs, cats, and fur-bearing and wildlife carnivores worldwide, continuing to pose significant threats. In this study, 140 rectal swabs were collected from 70 domestic dogs and 70 cats with clinical diarrhea in veterinary clinics in Changchun during 2020. A total of 64.3% (45/70) of dogs and 55.7% (39/70) of cats tested positive for CPV-2 or FPV using colloidal gold strips. Amino acid (aa) sequence alignment of the VP2 protein from 39 CPV-2 and 36 FPV samples revealed that 79.5% (31/39) were CPV-2c, 17.9% (7/39) were a new CPV-2a, and 2.6% (1/39) were mink enteritis virus (MEV). and 8.3% (3/36) FPV from the cats was infected by CPV-2, which suggested that CPV-2c was the dominant variant in dogs and FPV was the major pathogen in cats in Changchun city. Phylogenetic relationships of VP2 genes showed that 26 parvoviruses were closely related to domestic strains previously published in China; however, 8 FPVs and CPV-JL-15/China/2020 were clustered in the lineage of South Asiatic and European countries, and 7 out of 8 FPVs were close to Italy. In addition to Q247H, I248Y, F544Y, and E/V545V/K, two novel site mutations of N23D or L630P in NS1 protein, associated with viral cross-species transmissions, were first found as a reminder of genetic relationships of CPV-2 variants and FPVs in the same branch. Thus, regular and massive virus surveillance of parvovirus is necessary to cope with its ongoing infection, circulation, mutations, and evolutions to new subtypes with strong survival abilities.
Establishment of a duplex TaqMan-based real time RT-PCR assay for simultaneous detection of BRSV and BVDV
Authors: Hao Fuxing , Fu Jinping , Chen Jun , Zhu Daoxian , Cai Bingyan , Li Yuxin , Liu Chuanmin
Published: November 2024

Bovine respiratory disease complex (BRDC) represents a global acute respiratory condition that imposes substantial economic burdens on the cattle industry due to its high morbidity and mortality rates. Various factors contribute to the development of BRDC, including pathogen infections, environmental stresses, weaning of calves, and herd relocation. Viral pathogens, notably bovine respiratory syncytial virus (BRSV) and bovine viral diarrhea virus (BVDV), play a critical role in the etiology of BRDC, with single or combined viral infections being particularly clinically significant. In this study, we developed a duplex TaqMan-based real-time RT-PCR assay targeting the conserved regions of the F gene of BRSV and the 5′ UTR sequence of BVDV. The limits of detection for BRSV and BVDV were 6.83 copies/μL and 5.24 copies/μL, respectively. Our validation data suggest the assay has excellent sensitivity, specificity and reproducibility. Testing of clinical samples revealed prevalence of BRSV and BVDV in local farms in Jiangsu Province, China. This study provides an efficient diagnostic tool for the epidemiological investigation of BRDC.
Correction: Silva, P.J. Computational Development of Inhibitors of Plasmid-Borne Bacterial Dihydrofolate Reductase. Antibiotics 2022, 11, 779
Authors: Silva Pedro J.
Published: November 2024

In the original publication [...]
Potent Antimicrobial Azoles: Synthesis, In Vitro and In Silico Study
Authors: Özdemir Zeynep , Zenni Yaren Nur , Karakurt Arzu , Sari Suat , Saraç Selma , Akdağ Mevlüt , Merde İrem Bozbey , Kart Didem , Venanzoni Roberto , Flores Giancarlo Angeles , Angelini Paola , Kabier Muzammil , Mathew Bijo , Carradori Simone
Published: November 2024

Background/Objectives: The increase in fungal infections, both systemic and invasive, is a major source of morbidity and mortality, particularly among immunocompromised people such as cancer patients and organ transplant recipients. Because of their strong therapeutic activity and excellent safety profiles, azole antifungals are currently the most extensively used systemic antifungal drugs. Antibacterial properties of various topical antifungals, such as oxiconazole, which features oxime ether functionality, were discovered, indicating an exciting prospect in antimicrobial chemotherapy. Methods: In this study, eleven new oxime ether derivatives with the azole scaffold (5a–k) were synthesized and tested for their antimicrobial effects using the microdilution method to obtain broad-spectrum hits. Results: Although the title compounds showed limited efficacy against Candida species, they proved highly effective against dermatophytes. Compounds 5c and 5h were the most potent derivatives against Trichophyton mentagrophytes and Arthroderma quadrifidum, with minimum inhibitory concentration (MIC) values lower than those of the reference drug, griseofulvin. The MIC of 5c and 5h were 0.491 μg/mL and 0.619 μg/mL against T. mentagrophytes (MIC of griseofulvin: 2.52 μg/mL). The compounds were also tested against Gram-positive and Gram-negative bacteria. Briefly, 5c was the most active against Escherichia coli and Bacillus subtilis, with MIC values much better than that of ciprofloxacin (MIC of 5c = 1.56 μg/mL and 1.23 μg/mL, MIC of ciprofloxacin = 31.49 and 125.99 μg/mL, respectively). Molecular docking suggested a good fit in the active site of fungal lanosterol 14α-demethylase (CYP51) and bacterial FtsZ (Filamenting temperature-sensitive mutant Z) protein. Conclusions: As a result, the title compounds emerged as promising entities with broad antifungal and antibacterial effects, highlighting the utility of oxime ether function in the azole scaffold.
Adaptation of Object Detection Algorithms for Road Indicator Lights in Complex Scenes
Authors: Yao Ziyang , Hu Zunhao , Tian Peng , Sun Jun
Published: November 2024

In the realm of autonomous driving, practical driving scenarios are fraught with numerous complexities, including inclement weather conditions, nighttime blurriness, and ambient light sources that significantly hinder drivers’ ability to discern road indicators. Furthermore, the dynamic nature of road indicators, which are constantly evolving, poses additional challenges for computer vision-based detection systems. To address these issues, this paper introduces a road indicator light detection model, leveraging the advanced capabilities of YOLOv8. We have ingeniously integrated the robust backbone of YOLOv8 with four distinct attention mechanism modules—Convolutional Block Attention Module (CBAM), Efficient Channel Attention (ECA), Shuffle Attention (SA), and Global Attention Mechanism (GAM)—to significantly enhance the model performance in capturing nuanced features of road indicators and boosting the accuracy of detecting minute objects. Additionally, we employ the Asymptotic Feature Pyramid Network (AFPN) strategy, which optimizes the fusion of features across different scales, ensuring not only an enhanced performance but also maintaining real-time capability. These innovative attention modules empower the model by recalibrating the significance of both channel and spatial dimensions within the feature maps, enabling it to hone in on the most pertinent object characteristics. To tackle the challenges posed by samples rich in small, occluded, background-similar objects, and those that are inherently difficult to recognize, we have incorporated the Focaler-IOU loss function. This loss function deftly reduces the contribution of easily detectable samples to the overall loss, thereby intensifying the focus on challenging samples. This strategic balancing of hard-to-detect versus easy-to-detect samples effectively elevates the model’s detection performance. Experimental evaluations conducted on both a public traffic signal dataset and a proprietary headlight dataset have yielded impressive results, with both mAP50 and mAP50:95 metrics experiencing significant improvements exceeding two percentage points. Notably, the enhancements observed in the headlight dataset are particularly profound, signifying a significant step forward toward realizing safer and more reliable assisted driving technologies.
Investigating the Impact of Long-Term Use on Mattress Firmness and Sleep Quality—Preliminary Results
Authors: Vlaović Zoran , Klarić Nino , Domljan Danijela
Published: November 2024

Mattress comfort, often associated with firmness, is a complex construct influenced by factors such as material composition, construction, and personal preference. In this short communication paper, we indirectly investigated the effects of long-term mattress use on its hardness and sleep quality by observing the changes in the mattress. A mechanical durability test was performed on two structurally different mattress samples (with polyurethane core and pocket spring core) using a modified method based on the EN 1957 standard, aiming to understand the long-term effects of mattress characteristics on sleep quality. Preliminary results confirm that the mattress samples can maintain firmness and support during long-term use. The polyurethane foam mattress experienced initial compression but quickly stabilized, while the pocket spring mattress showed slight softening, maintaining overall firmness. For the polyurethane mattress, after the initial drop, the hardness value stabilized, varying between 7.53 and 9.03 N/mm, and at the end of the test, it stopped at 8.60 N/mm. The firmness rating stabilized at 4.3, showing minimal fluctuation between 4.0 and 4.6 throughout the process, while the total height loss was 3.79 mm. The hardness value of pocket spring mattresses generally decreased with increasing test cycles (it started at 5.86 N/mm and ended at 5.21 N/mm). The firmness remained relatively stable, varying between 7.3 and 7.1, and the total height loss was only 2.86 mm. The findings suggest that the firmness of a mattress can be changed with its use, highlighting the need for further research on a larger number of samples in the direction of the long-term implications of these changes on sleep comfort.
Research on Medical Text Parsing Method Based on BiGRU-BiLSTM Multi-Task Learning
Authors: Fan Yunli , Kang Ruiqing , Huang Wenjie , Li Lingyan
Published: November 2024

With the development of technology, the popularity of online medical treatment is becoming more and more widespread. However, the accuracy and credibility of online medical treatment are affected by model design and semantic understanding. In particular, there are still some problems in the accurate understanding of complex structured texts, which affects the accuracy of judging users’ intentions and needs. Therefore, this paper proposes a new method for medical text parsing, which realizes core tasks such as named entity recognition, intention recognition, and slot filling through a multi-task learning framework; uses BERT to obtain contextual semantic information; and combines BiGRU and BiLSTM neural networks, and uses CRF to realize sequence annotation and DPCNN to realize classification prediction. Thus, the task of entity recognition and intention recognition can be accomplished. On this basis, this paper builds a multi-task learning model based on BiGRU-BiLSTM, and uses CBLUE and CMID databases to verify the method. The verification results show that the accuracy of named entity recognition and intention recognition reaches 86% and 89%, respectively, which improves the performance of various tasks. The ability of the model to process complex text is enhanced. This method can improve the text generalization ability and improve the accuracy of online medical intelligent dialogue when it is used to analyze medical texts.
Stochastic Generation of Peak Ground Accelerations Based on Single Seismic Event Data for Safety Assessment of Structures
Authors: Seok Jihoon , Lee Jeeho
Published: November 2024

The Korean Peninsula, characterized by low-to-moderate seismicity, faces a shortage of strong ground motion records, posing challenges for the seismic safety assessment of critical infrastructures. Given the rarity of large-magnitude earthquakes, generating a variety of earthquakes with rational values of Peak Ground Acceleration (PGA) is essential for robust seismic fragility and risk analysis. To address this, a new stochastic approach is proposed to simulate artificial earthquakes at multiple source-to-site distances and derive the probability distribution of PGA based on recorded data from a single seismic event. Two key source parameters, seismic moment and corner frequency, are treated as random variables with a negative correlation, reflecting their uncertainties and dependence on source-to-site distance. The Monte Carlo simulation with copula sampling of the key source parameters generates Fourier spectra for artificial earthquakes, which are transformed into the time domain to yield PGA distributions at various distances. A comparison with recorded data shows that the proposed method effectively simulates ground motion intensities, with no statistically significant differences between the simulated results and recorded data (p>0.05). The present method of determining PGA distributions provides a robust framework to enhance seismic risk analysis for the safety assessment of structures.
The Influences of Selected Factors on Bending Moment Capacity of Case Furniture Joints
Authors: Hu Wengang , Zhao Yuan , Xu Wei , Liu Yuanqiang
Published: November 2024

This study experimentally investigated the effects of selected factors on the bending moment capacity (BMC) of case furniture joints. The main aim was to explore mixed applications of wood-based materials and fasteners in manufacturing case furniture to reduce material costs. The study examined the effects of the face member material—particle board (PB), plywood (PL), and block board (BB)—edge member material (PB, PL, and BB), and joint shape (T-shape and L-shape) on BMC. Additionally, the study evaluated the effects of joint type (two eccentrics (TE), two dowels (TD), and one eccentric and one dowel (ED)), and material type (PB, PL, and BB) on BMC for L-shaped joints. The results showed that joint shape and face member material significantly affected the BMC of case furniture joint. The BMCs of T-shaped joints were significantly greater than those of L-shaped joints, regardless of the material of the face and edge members, except when the face member was made of PL. For L-shaped joints with PL face members, the BMCs were significantly higher compared to others. Joints constructed with TE exhibited significantly higher BMC compared to ED and TD for the same material type. For PB, TE joints exhibited an increase of approximately 3.0 Nm and 2.0 Nm compared to TD and ED, respectively. For PL, TE showed an increase of 9.1 Nm and 4.1 Nm compared to ED and TD, respectively. For BB, the increases were 7.0 Nm and 6.6 Nm compared to ED and TD. The BMC of joints made with PL and constructed with TE and ED was significantly greater than those of BB, followed by PB. However, for joints assembled with TD, there was no significant difference among the three materials. The ratios of BMC for joints constructed with ED compared to the half-sum of TE and TD were 0.73, 1.04, and 0.79 for PB, PL, and BB, respectively. These results suggest that the face member material predominantly influences the BMC of case furniture joints, indicating the potential to reduce costs by combining different materials and joint types.
Single-Shot Time-Lapse Target-Oriented Velocity Inversion Using Machine Learning
Authors: Rincon Katerine , Araújo Ramon C. F. , Galvão Moisés M. , Xavier-de-Souza Samuel , de Araújo João M. , Barros Tiago , Corso Gilberto
Published: November 2024

In this study, we used machine learning (ML) to estimate time-lapse velocity variations in a reservoir region using seismic data. To accomplish this task, we needed an adequate training set that could map seismic data to velocity perturbation. We generated a synthetic seismic database by simulating reservoirs of varying velocities using a 2D velocity model typical of the Brazilian pre-salt ocean bottom node (OBN) acquisition, located in the Santos basin, Brazil. The largest velocity change in the injector well was around 3% of the empirical velocity model, which mimicked a realistic scenario. The acquisition geometry was formed by the geometry of 1 shot and 49 receivers. For each synthetic reservoir, the corresponding seismic data were obtained by estimating a one-shot forward-wave propagation using acoustic approximation. We studied the reservoir illumination to optimize the input data of the ML inversion. We split the set of synthetic reservoirs into two subsets: training (80%) and testing (20%) sets. We point out that the ML inversion was restricted to the reservoir zone, which means that it was inversion-oriented to a target. We obtained a good similarity between true and ML-inverted reservoir anomalies. The similarity diminished for a situation with non-repeatability noise.
Investigating the Effects of the Height-to-Diameter Ratio and Loading Rate on the Mechanical Properties and Crack Extension Mechanism of Sandstone-Like Materials
Authors: Gou Yunbo , Bai Jianbiao , Li Yanhui , Zhao Xiangqian , Tai Lianhai , Fu Zizhao
Published: November 2024

The causes of the size effect (SE) and loading rate effect (LR) for rocks remain unclear. Based on this, a gypsum-mixed material was used to simulate sandstone, where the dosing ratio was 7.5% river sand, 17.5% quartz, 58.3% α-high-strength gypsum, and 16.7% water. The specimens were designed to have a height-to-diameter ratio (HDR) of 0.6~2, and three strain rates (SRs)—static, quasi-dynamic, and dynamic—were used to perform single-factor rotational uniaxial compression experiments. PFC2D was used to numerically simulate the damage pattern of a sandstone-like specimen. The results showed that the physical parameters did not change monotonically, as was previously found. The main reason for this is that the end-face friction effect (EFE) is generated when the dynamic SR or the HDR is 0.6~1, with a damage pattern of “X”. Under mechanical analysis, the power consumed by the EFE was inversely proportional to the HDR and directly proportional to the LR, and it can reduce the actual amount of energy transferred inside the specimen. This paper may provide a foundation for the study of non-linear hazards in coal and rock.
A Text Generation Method Based on a Multimodal Knowledge Graph for Fault Diagnosis of Consumer Electronics
Authors: Wu Yuezhong , Sun Yuxuan , Chen Lingjiao , Zhang Xuanang , Liu Qiang
Published: November 2024

As consumer electronics evolve towards greater intelligence, their automation and complexity also increase, making it difficult for users to diagnose faults when they occur. To address the problem where users, relying solely on their own knowledge, struggle to diagnose faults in consumer electronics promptly and accurately, we propose a multimodal knowledge graph-based text generation method. Our method begins by using deep learning models like the Residual Network (ResNet) and Bidirectional Encoder Representations from Transformers (BERT) to extract features from user-provided fault information, which can include images, text, audio, and even olfactory data. These multimodal features are then combined to form a comprehensive representation. The fused features are fed into a graph convolutional network (GCN) for fault inference, identifying potential fault nodes in the electronics. These fault nodes are subsequently fed into a pre-constructed knowledge graph to determine the final diagnosis. Finally, this information is processed through the Bias-term Fine-tuning (BitFit) enhanced Chinese Pre-trained Transformer (CPT) model, which generates the final fault diagnosis text for the user. The experimental results show that our proposed method achieves a 4.4% improvement over baseline methods, reaching a fault diagnosis accuracy of 98.4%. Our approach effectively leverages multimodal fault information, addressing the challenges users face in diagnosing faults through the integration of graph convolutional network and knowledge graph technologies.
NHPP Software Reliability Model with Rayleigh Fault Detection Rate and Optimal Release Time for Operating Environment Uncertainty
Authors: Song Kwang Yoon , Chang In Hong
Published: November 2024

Software is used in diverse settings and depends on development and testing environments. Software development should improve the reliability, quality, cost, and stability of software, making the software testing period crucial. We proposed a software reliability model (SRM) that considers the uncertainty of software environments and the fault detection rate function as a Rayleigh distribution, with an explicit mean value function solution in the model. The goodness-of-fit of the proposed model relative to several existing nonhomogeneous Poisson process (NHPP) SRMs is presented based on three software application failure datasets. Further, a cost model is also presented that addresses the error-removal risk level and required time. The optimal testing release policy for minimizing the expected total cost (ETC) is also determined for NHPP SRMs. The impact of the software environment is studied by varying it, and the optimal release times and minimum ETCs are compared. The goodness-of-fit comparison confirmed that the proposed model has more accurate prediction values than other models. Further, whereas the existing models applied to the cost model do not change after a certain operation period, the proposed model yields changes in release time even for long operating periods.
Numerical Investigation with Failure Characteristic Analysis and Support Effect Evaluation of Deep-Turning Roadways
Authors: Wang Man , Ding Feng , Niu Zehua , Gao Yanan , Jiao Huice , Chen Zhaofan
Published: November 2024

In recent years, tunnel-boring machines (TBMs) have been widely applied in deep coal mining. Turning is an inevitable challenge in TBM tunneling, and a TBM turning roadway exhibits greater instability than a straight roadway, as engineering experience has indicated. This study aimed to explore the failure mechanism and evaluate the support performance of a deep-turning roadway. Several numerical models were established to investigate the deformation of the roadway, the stress distribution, and the failure zone of the surrounding rocks under different tunneling conditions. The results show that the tunneling depth influences the failure pattern of the turning roadway: deep tunneling with high in situ stress can cause asymmetric failure of the turning roadway, while shallow tunneling with low in situ stress does not. Moreover, the change in turning radius, namely the change in roadway geometry, does not influence the stability of the turning roadway. In addition, the support actions for both the straight and turning roadways do not differ significantly, and the amount of controlled deformation of the surrounding rocks is proportional to their natural deformation.
An Integrated Taylor Expansion and Least Squares Approach to Enhanced Acoustic Wave Staggered Grid Finite Difference Modeling
Authors: Zhang Min , Zhou Liming , Fu Daiguang , Chen Zhixue , Wu Haibo
Published: November 2024

The staggered grid finite difference method has emerged as one of the most commonly used approaches in finite difference methodologies due to its high computational accuracy and stability. Inevitably, discretizing over time and space domains in finite difference methods leads to numerical artifacts. This paper introduces a novel approach that combines the widely used Taylor series expansion with the least squares method to effectively suppress numerical dispersion. We have derived the coefficients for the staggered grid finite difference method by integrating Taylor series expansions with the least squares method. To validate the effectiveness of our approach, we conducted analyses on accuracy, dispersion, and stability, alongside simple and complex numerical examples. The results indicate that our method not only inherits the capabilities of the original Taylor series and least squares methods in suppressing numerical dispersion across small and medium wavenumber ranges but also surpasses the original methods. Moreover, it demonstrates robust dispersion suppression capabilities at high wavenumber ranges.
State of Charge Estimation of Lithium Battery Utilizing Strong Tracking H-Infinity Filtering Algorithm
Authors: Yuan Tianqing , Liu Yang , Bai Jing , Sun Hao
Published: November 2024

The ability to quickly and accurately estimate the state of charge (SOC) of lithium batteries is a key function of the battery management system (BMS). To enhance the accuracy of SOC estimation for lithium batteries, we propose a method that combines the dynamic factor recursive least squares (DFFRLS) algorithm and the strong tracking H-infinity filtering (STF-HIF) algorithm. To address the issue of fixed forgetting factors in recursive least squares (RLS) that struggle to maintain both fast convergence and stability in battery parameter identification, we introduce dynamic forgetting factors. This approach adjusts the forgetting factor based on the residuals between the model’s estimated and actual values. To improve the H-infinity filtering (HIF) algorithm’s poor performance in tracking sudden state changes, we propose a combined STF-HIF algorithm, integrating HIF with strong tracking filtering (STF). Simulation experiments indicate that, compared to the HIF algorithm, the STF-HIF algorithm achieves a maximum absolute SOC estimation error (MaxAE) of 0.69%, 0.72%, and 1.22%, with mean absolute errors (MAE) of 0.27%, 0.25%, and 0.38%, and root mean square errors (RMSE) of 0.33%, 0.30%, and 0.46% under dynamic stress testing (DST), federal urban driving schedules (FUDS), and Beijing dynamic stress testing (BJDST) conditions, respectively.
An Assist-as-Needed Control Strategy Based on a Subjective Intention Decline Model
Authors: Yan Hao , Zhang Fangcao , Li Xingao , Zhang Chenchen , Zhang Yunjia , Feng Yongfei
Published: November 2024

In the rehabilitation training process for stroke patients, the level of excitement in the patient’s physiological state has a positive impact on the efficacy of the training. In order to improve patients’ initiative during training and prevent dependence on assistive systems, this study proposes an assist-as-needed control strategy based on a subjective intention decline model. The strategy primarily consists of two modules: a subjective intention decline control module and a limb movement assessment module. The subjective intention decline module collects surface electromyography (sEMG) data during patient training and optimizes support vector machine (SVM) using quantum particle swarm optimization (QPSO) algorithms to establish a subjective intention decline model. The limb movement assessment module collects information such as interaction force and position error during training and proposes a method for evaluating the motion state of the affected limb. This model combines traditional impedance control with a method for assessing limb movement and subjective status, automatically adjusting the level of assistive force on the affected limb in real time to enhance its active participation in tasks. Finally, we performed two verification experiments to assess the patient’s initiative in participating in the training. The experimental results show that the proposed method effectively reduced the average assist force by 65.66% for the traditional impedance control training system and effectively the average assist force by 35.2% for the control training system using only the assist force module based on force position information. At the same time, the accuracy of the subjective intention attenuation module established in the experiment to identify the fatigue level of the subjects reached 93.41%. Therefore, the proposed method effectively improves the initiative of trainers and also prevents patients from relying on the assist-as-needed control training system.
Review of Lyme Borreliosis in Africa—An Emerging Threat in Africa
Authors: Doss Nejib , Morrone Aldo , Forgione Patrizia , Trevisan Giusto , Bonin Serena
Published: November 2024

Lyme borreliosis (LB) is more common in the Northern Hemisphere. It is endemic mainly in North America, where the vectors are Ixodes scapularis and Ixodes pacificus, and in Eurasia, where the vectors are Ixodes ricinus and Ixodes persulcatus. Both tick-borne diseases and LB are influenced by climate change. Africa and South America are crossed by the equator and are situated in both the Northern and Southern Hemispheres. In Africa, the LB is present on the Mediterranean and the Indian Ocean coasts. Borrelia lusitaniae is prevalent in countries bordering the Mediterranean Sea, such as Tunisia, Morocco, Algeria, and Egypt. Ticks were detected in the Ixodes Ricinus, which are carried by migratory birds and the Ixodes inopinatus and captured by the Psammodromus algirus lizards. The Borreliae Lyme Group (LG) and, in particular, Borrelia garinii, have been reported in countries bordering the Indian Ocean, such as Kenya, Tanzania, and Mozambique, transported by migratory birds from North African countries, where the vector was identified as Hyalomma rufipes ticks. This review aims to document the presence of Borreliae LG and LB in Africa.
High-Affinity Fully Human Anti-EpCAM Antibody with Biased IL-2 Exhibits Potent Antitumor Activity
Authors: Wang Zhi , Wang Mingkai , Li Quanxiao , Wu Yanling , Ying Tianlei
Published: November 2024

Monoclonal antibodies (mAbs) are widely used in cancer therapy but often show limited efficacy for solid tumors. Enhancing anti-tumor activity by fusing cytokines to tumor-targeting mAbs, which specifically activate immune cells within the tumor microenvironment, represents a promising strategy. However, the optimal design and therapeutic efficacy of antibody–cytokine fusion formats remain unclear. The epithelial cell adhesion molecule (EpCAM), frequently overexpressed in a variety of carcinomas, serves as the target for immunotherapies. In this study, we identified a fully human mAb targeting EpCAM, designated as m801, from a previously constructed phage-displayed fully human antibody library. By fusing m801 with an IL-2 variant (IL-2v) in two configurations, m801.2 (2 anti-EpCAM Fab + 1 IL-2v) and m801.3 (1 anti-EpCAM Fab + 1 IL-2v), we identified m801.2 as the lead candidate due to its superior biophysical properties, including high thermal stability, homogeneity, and low aggregation. Furthermore, m801.2 showed strong binding affinity to EpCAM, with KD values of 0.6 nM, and an EpCAM-expressing tumor cell line, comparable to the original IgG m801. Additionally, m801.2 exhibited IL-2 receptor β subunit (IL-2Rβ)-biased binding activity, with a KD of 27.3 nM, resulting in superior effective T cell activation. In an SW480 xenograft mice model, m801.2 significantly inhibited tumor growth and demonstrated high tolerability. These findings suggest a valuable framework for the future design of immunocytokine therapies.
miR-193b-5p and miR-374b-5p Are Aberrantly Expressed in Endometriosis and Suppress Endometrial Cell Migration In Vitro
Authors: Frisendahl Caroline , Tang Yiqun , Boggavarapu Nageswara Rao , Peters Maire , Lalitkumar Parameswaran Grace , Piltonen Terhi T. , Arffman Riikka K. , Salumets Andres , Götte Martin , Korsching Eberhard , Gemzell-Danielsson Kristina
Published: November 2024

(1) Background: Endometriosis is a highly prevalent gynecological disease affecting 10% of women of reproductive age worldwide. miRNAs may play a role in endometriosis, though their exact function remains unclear. This study aimed to identify differentially expressed miRNAs in endometriosis and study their functions in the disease. (2) Methods: Endometrial tissue was collected from women with endometriosis (n = 15) and non-endometriosis controls (n = 17). Dysregulated miRNAs were identified through small RNA-sequencing, and their biological significance was explored by target gene prediction and pathway analysis. Selected miRNAs were examined in paired ectopic endometriomas and eutopic endometrium (n = 10) using qRT-PCR. Their roles in cell migration and proliferation were further examined in vitro using functional assays. To identify potential target genes, we performed mRNA sequencing on transfected cells and the endometrioma cohort. (3) Results: We identified 14 dysregulated miRNAs in the eutopic endometrium of women with endometriosis compared to endometrial tissue from women without endometriosis. Pathway analysis indicated enrichment in cell migration and proliferation-associated pathways. Further ex vivo studies of miR-193b-5p and miR-374b-5p showed that both miRNAs were upregulated in endometrioma. Overexpression of these two miRNAs in vitro inhibited cell migration, and mRNA sequencing revealed several migration-related genes that are targeted by these miRNAs. (4) Conclusions: Our study identified two key endometrial miRNAs that may be involved in the pathogenesis of endometriosis by regulating cell migration.
The Role of Probiotics in Modulating Myocardial Infarction and Depression-like Symptoms: A Study on Sex-Specific Responses
Authors: Gagné Marc-André , Frégeau Geneviève , Godbout Roger , Rousseau Guy
Published: November 2024

Background/Objectives: This study explores the effects of two probiotics, Lactobacillus helveticus R0052 and Bifidobacterium longum R0175, on myocardial infarction (MI) and associated depression-like behaviours, with a focus on sex differences. Methods: MI was induced in adult male and female rats by occluding the left anterior coronary artery for 30 min, followed by 24 h of reperfusion. Probiotics were administered via drinking water for at least two weeks before ischemia. Infarct size, plasma C-reactive protein (CRP), estradiol levels, and intestinal permeability were then measured. Two weeks after, MI subgroups of rats were tested for depression-like behaviours. Results: We found a significant interaction between sex and probiotics in relation to infarct size. Probiotics significantly reduced the infarct size compared to the vehicle group in female rats but not in males. Probiotics increased the plasma estradiol levels and reduced the CRP concentrations in females, suggesting anti-inflammatory and cardioprotective properties. Probiotics significantly increased intestinal resistance following MI in males only, suggesting sex-specific physiological responses to treatment. Probiotics enhanced social interaction in males with MI but not in females. Similarly, in the forced swim test, probiotics reduced immobility in males with MI but increased it in females, further underscoring the sex-dependent effects of probiotics. Conclusions: This study reports cardioprotective effects of probiotics upon MI in female rats, while benefits in male rats were rather at the behavioural level. These results highlight distinct physiological and behavioural responses between sexes, emphasizing the need to account for sex differences in future tests of probiotics as a prophylactic treatment for MI.
Methylglyoxal: A Key Factor for Diabetic Retinopathy and Its Effects on Retinal Damage
Authors: Klochkov Vladlen , Chan Chi-Ming , Lin Wan-Wan
Published: November 2024

Background: Diabetic retinopathy is the most common retinal vascular disease, affecting the retina’s blood vessels and causing chronic inflammation, oxidative stress, and, ultimately, vision loss. Diabetes-induced elevated glucose levels increase glycolysis, the main methylglyoxal (MGO) formation pathway. MGO is a highly reactive dicarbonyl and the most rapid glycation compound to form endogenous advanced glycation end products (AGEs). MGO can act both intra- and extracellularly by glycating molecules and activating the receptor for AGEs (RAGE) pathway. Conclusions: This review summarizes the sources of MGO formation and its actions on various cell pathways in retinal cells such as oxidative stress, glycation, autophagy, ER stress, and mitochondrial dysfunction. Finally, the detoxification of MGO by glyoxalases is discussed.
Time to Rethink Bronchiolitis Obliterans Syndrome Following Lung or Hematopoietic Cell Transplantation in Pediatric Patients
Authors: Jaing Tang-Her , Wang Yi-Lun , Chiu Chia-Chi
Published: November 2024

Background: Similar in histological characteristics and clinical manifestations, bronchiolitis obliterans syndrome (BOS) can develop following lung transplantation (LTx) or hematopoietic cell transplantation (HCT). In contrast to lung transplantation, where BOS is restricted to the lung allograft, HCT-related systemic graft-versus-host disease (GVHD) is the root cause of BOS. Because lung function declines following HCT, diagnosis becomes more difficult. Given the lack of proven effective medicines, treatment is based on empirical evidence. Methods: Cross-disciplinary learning is crucial, and novel therapies are under investigation to improve survival and avoid LTx. Recent advances have focused on updating the understanding of the etiology, clinical features, and pathobiology of BOS. It emphasizes the significance of learning from experts in other transplant modalities, promoting cross-disciplinary knowledge. Results: Our treatment algorithms are derived from extensive research and expert clinical input. It is important to ensure that immunosuppression is optimized and that any other conditions or contributing factors are addressed, if possible. Clear treatment algorithms are provided for each condition, drawing from the published literature and consensus clinical opinion. There are several novel therapies currently being investigated, such as aerosolized liposomal cyclosporine, Janus kinase inhibitors, antifibrotic therapies, and B-cell-directed therapies. Conclusions: We urgently need innovative treatments that can greatly increase survival rates and eliminate the need for LTx or re-transplantation.
Catalytic CO2 Desorption from MEA Solution of Al-FeOOH Composite Catalysts’ Desorption Performance, Structure–Activity Relationship, and New Mechanism
Authors: Shi Huancong , Lv Junge , Feng Yongcheng , Zhang Haoran , Xiong Zhibo , Lu Shijian , Jin Jing , Tontiwachwuthikul Paitoon
Published: November 2024

In order to reduce the massive heat duty of amine-based CO2 capture technology, an AlOOH/FeOOH composite catalyst (AF-M/N) was synthesized to speed up the CO2 desorption rates and reduce the heat duty of an aqueous MEA solution. The catalysis of AF-M/M from 1/9 to 9/1 was investigated comprehensively, with characterization of the catalytic desorption with heat duty and desorption factors. Results indicated the special composite catalyst (AF-1/9) possessed optimized catalysis with a relative heat duty of 78.7% and a desorption factor of 0.0037 × 10−3 (mol CO2/L2 kJ min) and relative desorption factor of 194.7%. The structure–activity correlations indicated that the mesopore surface area (MSA), which reached 329 m2/g, and Brϕnsted/Lewis acid ratio (B/L ratio) of 0.11 were the most important factors for enhancing catalysis. Furthermore, molecular simulations were conducted for the catalytic carbamate breakdown mechanism, focusing on the “isomerization” of “carbamate acid” vs. “Zwitterion” as the key step. From the DFT study, the isomerization was most likely to proceed with H2O as catalyst via intermolecular proton transfer instead of intramolecular proton transfer, with an activation energy Ea of 85.9 kJ/mol. With the aid of AlOOH the isomerization was further facilitated due to stabilized Zwitterion, and the Ea decreased to 69.2 kJ/mol. The results not only synthesized a new heterogeneous catalyst but also revealed the map of “isomerization” on a molecular level. Such a discovery indicates that water-assisted proton transfer is advantageous for catalytic carbamate breakdown.
Sustainable Strategies to Current Conditions and Climate Change at U.S. Military Bases and Other Nations in the Arctic Region: A 20-Year Comparative Review
Authors: Kaushal Vinayak , Kashyap Amey
Published: November 2024

Amidst the backdrop of growing great power competition, heightened United States presence via military bases has manifested in the Arctic. However, the then design and implementation have hampered the resilience of these bases in a region warming at nearly four times the rate of the rest of the globe. Two-thirds of the United States’ 79 military bases in the Arctic remain underprepared against permafrost thaw and rising sea levels despite rampant calls for sustainable strategies. Damages emanating from climate-related failures will continue to cost the U.S. billions of dollars and render crucial infrastructure unusable. The objective of this study is to present a comprehensive literature review of the extent of Arctic warming and its significance for U.S. bases, the negative implications of military infrastructure deterioration, and methods to adapt both existing and forthcoming bases to a rapidly warming atmosphere. Eighty published papers that directly or indirectly referenced U.S. military bases or climate-oriented engineering in the aforementioned contexts were identified and analyzed over a 20-year period from 2004 to 2024. The literature review concludes that warming concerns were often not taken into much account by civil engineers during initial base construction, an oversight that now jeopardizes runways, docks, and highways. Other nations that have a sizeable footprint in the Arctic Circle, such as Canada and Russia, have demonstrated progress by utilizing pile-driven substructures, thawing permafrost before construction, and ventilated crawlspaces. Alternative solutions, such as cooling permafrost via thermosiphons or refrigeration systems, employing spatially oriented foundations composed of specific materials, and preventative measures such as floodwalls and revetments, have also shown considerable promise in simulations and practice. A table illustrating a holistic literature summary of sustainable strategies to current conditions and climate change at U.S. Military Bases in the Arctic region is also developed. Modeling successful engineering concepts and incorporating existing innovations into military infrastructure should be at the forefront of the United States’ sustainable policy.
New Material of Thylacocephala from the Early Ladinian (Middle Triassic) of Northern Grigna (Lecco, Lombardy, Northern Italy)
Authors: Ji Cheng , Tintori Andrea
Published: November 2024

Here we report and describe a new assemblage of Thylacocephala (Crustacea) from the Early Ladinian Buchenstein Fm. (Middle Triassic) of Grigna, Northern Italy. The assemblage consists of at least four species from three different genera: Ankitokazocaris lariensis sp. n., Ankitokazocaris sp., Austriocaris sp., Stoppanicaris grignaensis gen. et sp. n. This thylacocephalan assemblage is rather diverse compared to the others of the Triassic. The largest size and ornamentation type of thylacocephalan species is compared among different periods of the Triassic and indicates that taxa with ridges on the carapace are generally smaller than those with smooth carapaces. This may be related to their different modes of life, such as inside or above the sediment with low oxygen levels. Large and smooth taxa were possibly more adapted to a life above sandy bottoms in shallow waters, under a somewhat high wave energy, while small, ornamented taxa are better suited for deeper environments with muddy bottoms, inside which they could move freely. The EDS analysis of Austriocaris sp. reveals that the cuticle mainly consists of apatite, which is in accordance with previous interpretations.
Towards a Datatset of Digitalized Historical German VET and CVET Regulations
Authors: Reiser Thomas , Dörpinghaus Jens , Steiner Petra , Tiemann Michael
Published: November 2024

The digitization of historical documents has gained particular interest in recent years in the digital humanities. The goal is to digitize historical documents by extracting and structuring text from scanned images. Here, we focus on the processing of historical German VET (vocational education and training) and CVET (continuing vocational education and training) regulations to support educational research. This dataset contains data from 1908 to the present and includes 2125 documents as PDF, 983 fully converted XML documents, and additional metadata for 7090 documents from the archive. We present an overview of the historical background and the challenges of processing different historical documents from three different federal states.