bluuebunny/crossref_metadata_2025 huggingface dataset:
An alternative vaccine target for bovine Anaplasmosis based on enolase, a moonlighting protein
Authors: Quiroz-Castañeda Rosa Estela , Aguilar-Díaz Hugo , Amaro-Estrada Itzel
Published: September 2023

The discovery of new targets for preventing bovine anaplasmosis has moved away from focusing on proteins that have already been extensively studied in Anaplasma marginale, including the Major Surface Proteins, Outer Membrane Proteins, and Type IV Secretion System proteins. An alternative is moonlighting or multifunctional proteins, capable of performing various biological functions within various cellular compartments. There are several reports on the role of moonlighting proteins as virulence factors in various microorganisms. Moreover, it is known that about 25% of all moonlighting is involved in the virulence of pathogens. In this work, for the first time, we present the identification of three enolase proteins (AmEno01, AmEno15, and AmEno31) in the genome of Mexican strains of A. marginale. Using bioinformatics tools, we predicted the catalytic domains, enolase signature, and amino acids binding magnesium ion of the catalytic domain and performed a phylogenetic reconstruction. In addition, by molecular docking analysis, we found that AmEno01 would bind to erythrocyte proteins spectrin, ankyrin, and stomatin. This adhesion function has been reported for enolases from other pathogens. It is considered a promising target since blocking this function would impede the fundamental adhesion process that facilitates the infection of erythrocytes. Additionally, molecular docking predicts that AmEno01 could bind to extracellular matrix protein fibronectin, which would be significant if we consider that some proteins with fibronectin domains are localized in tick gut cells and used as an adhesion strategy to gather bacteria before traveling to salivary glands. Derived from the molecular docking analysis of AmEno01, we hypothesized that enolases could be proteins driven by the pathogen and redirected at the expense of the pathogen’s needs.
Development of an artificial intelligence-based method for the diagnosis of the severity of myxomatous mitral valve disease from canine chest radiographs
Authors: Valente Carlotta , Wodzinski Marek , Guglielmini Carlo , Poser Helen , Chiavegato David , Zotti Alessandro , Venturini Roberto , Banzato Tommaso
Published: September 2023

An algorithm based on artificial intelligence (AI) was developed and tested to classify different stages of myxomatous mitral valve disease (MMVD) from canine thoracic radiographs. The radiographs were selected from the medical databases of two different institutions, considering dogs over 6 years of age that had undergone chest X-ray and echocardiographic examination. Only radiographs clearly showing the cardiac silhouette were considered. The convolutional neural network (CNN) was trained on both the right and left lateral and/or ventro-dorsal or dorso-ventral views. Each dog was classified according to the American College of Veterinary Internal Medicine (ACVIM) guidelines as stage B1, B2 or C + D. ResNet18 CNN was used as a classification network, and the results were evaluated using confusion matrices, receiver operating characteristic curves, and t-SNE and UMAP projections. The area under the curve (AUC) showed good heart-CNN performance in determining the MMVD stage from the lateral views with an AUC of 0.87, 0.77, and 0.88 for stages B1, B2, and C + D, respectively. The high accuracy of the algorithm in predicting the MMVD stage suggests that it could stand as a useful support tool in the interpretation of canine thoracic radiographs.
A monoclonal antibody-based sandwich ELISA for measuring canine Thymidine kinase 1 protein and its role as biomarker in canine lymphoma
Authors: Sharif Hanan , Saellström Sara , Kolli Bhavya , Jagarlamudi Kiran Kumar , Wang Liya , Rönnberg Henrik , Eriksson Staffan
Published: September 2023

Introduction

Dogs play an important role in society, which increased during the covid epidemics. This has led to a much higher workload for the veterinarians. Therefore, there is a need for efficient diagnostic tools to identify risk of malignant diseases. Here the development of a new test that can solve some of these problems is presented. It is based on serum Thymidine Kinase 1 (TK1), which is a biomarker for cell proliferation and cell lysis.

Methods

Anti-TK1 monoclonal antibodies were produced against two different epitopes, the active site of the TK1 protein and the C-terminal region of canine TK1. The antibodies were developed with hybridoma technology and validated using dot blot, Quartz Crystal Microbalance (QCM) technology, western blots, immunoprecipitation (IP), and enzyme-linked immunosorbent assay (ELISA). Clinical evaluation of Canine TK1 ELISA was done by using sera from 131 healthy dogs and 93 dogs with lymphoma. The two selected Anti-TK1 monoclonal antibodies have Kd values in the range of 10−9 M and further analysis with dot and western blots confirmed the high affinity binding of these antibodies. A sandwich Canine TK1 ELISA was developed using the anti-TK1 antibodies, and TK1 concentrations in serum samples were determined using dog recombinant TK1 as a standard.

Results

Serum TK1 protein levels were significantly higher in dogs with lymphoma compared to those in healthy dogs (p < 0.0001). Receiver operating curve analysis showed that the canine TK1-ELISA obtain a sensitivity of 0.80, at a specificity of 0.95. Moreover, the Canine TK1 ELISA has a positive predictive value (PPV) of 97%, and the negative predictive value (NPV) of 83%, reflecting the proportion of test results that are truly positive and negative. Furthermore, Canine TK1 ELISA had significantly higher capacity to differentiate dogs with T-cell lymphoma from those with B-cell lymphoma compared to earlier used TK1 activity assays.

Discussion

These results demonstrate that the Canine TK1 ELISA can serve as an efficient tool in the diagnosis and management of dogs with lymphomas.
Dynamic Analysis of a Large Deployable Space Truss Structure Considering Semi-Rigid Joints
Authors: Yao Huaibo , Huang Yixin , Ma Wenlai , Liang Lei , Zhao Yang
Published: September 2023

Joints are widely used in large deployable structures but show semi-rigidity due to performance degradation and some nonlinear factors affecting the structure’s dynamic characteristics. This paper investigates the influence of semi-rigid joints on the characteristics of deployable structures in orbit. A virtual connection element of three DOFs is proposed to model the semi-rigid joints. The governing equations of semi-rigid joints are established and integrated into the dynamic equation of the structures. A series of numerical experiments are carried out to validate the proposed model’s accuracy and efficiency, and the deployable truss structures’ static and dynamic responses are analyzed. The results show that semi-rigid joints exacerbate the effects of an in-orbit microvibration on the stability of deployable truss structures. Semi-rigid joints lower the dominant frequencies of structures, leading to a ‘closely-spaced-frequencies’ phenomenon and altering the dynamic responses significantly. The effects of semi-rigid joints on deployable truss structures are long-term and can be used to establish a relationship model between structural performance and service life. Nonlinear effects vary with the external load and depend on the structures’ instantaneous status. These results indicate that semi-rigid joints significantly influence the characteristics of deployable structures, which must be considered in the design and analysis of high-precision in-orbit deployable structures.
Numerical Simulation of Spiral Cutter–Soil Interaction in Deep Vertical Rotary Tillage
Authors: Yang Wang , Xiao Xiong , Pan Ronghui , Guo Shengyuan , Yang Jian
Published: September 2023

Deep vertical rotary tillage (DVRT) is a new tillage method which combines the advantages of deep tillage and rotary tillage. However, limited research has been conducted on a critical component of the deep vertical rotary tiller, namely the spiral cutter. In clay loam, there are a lot of large clods in the topsoil layer after tillage, and the cutting resistance and vibration of the cutter are substantial. To reveal the reasons behind this, a simulation model of a spiral cutter–soil system was developed using Smoothed Particle Hydrodynamics (SPH). Using this model, the working process and force of a spiral cutter were thoroughly investigated. The results show that soil fragmentation, swelling, and loosening primarily result from the combined effects of the separation cutting, velocity difference cutting, auxiliary cutting, and the spiral blade’s lifting effect on soil. The reasons for the larger clods are that topsoil furrow slices are larger and the velocity difference cutting is insufficient. The substantial resistance of the cutter is mainly due to the greater resistance of the blade and the bottom edge, and too many blades cutting the soil simultaneously. Furthermore, due to the asymmetry of the cutter’s structure, the resistance’s amplitude reaches 1963.5 N, which causes the cutter’s large vibration. These findings would be an important basis for optimal cutter design.
Modulation of the Irrigation Practices in Croatia for More Sustainable Olive Growing
Authors: Šikić Zoran , Marcelić Šime , Brkić Bubola Karolina , Jukić Špika Maja , Gašparović Pinto Ana , Zorica Marko , Kolega Šimun , Pasković Igor , Novoselić Anja , Klisović Dora , Kos Tomislav
Published: September 2023

Olive groves in the Mediterranean may lose production sustainability because of their vulnerability to climatic change. Irrigation is an important measure that could significantly affect fruit yield, olive fruit fly infestation, and oil characteristics. The aim of paper was to compare the regulated deficit irrigation with different water management practices, in consecutive years, in two locations in Zadar County (Croatia), affecting fruit morphology, olive fruit fly infestation, and quantity and quality of the extracted Coratina cultivar oil. Treatments, namely C—rainfed, T1—deficit irrigation (produce’s practice), T2—regulated deficit irrigation, and T3—full irrigation (100% ECTO), were established. Irrigated treatments had a positive effect on all morphological characteristics of the fruit. The pulp mass, independently of the year, increased in irrigated treatment (ranging from 1.04 to 1.65 in C to 2.25 and 2.30 in the irrigated treatments) and resulted in a higher oil content on a fresh weight basis (ranging from 16.39% to 17.85% in C to 19.48% to 23.26% in the irrigated treatments). However, fruit yield per tree was only location-dependent. When olive fruit fly presence was high, fruit infestation was greatest in the irrigated compared to the rainfed treatment. According to quality parameters, all oils were classified as EVOO. Individual phenols were influenced by irrigation, while the composition of fatty acids was more influenced by location than treatment. The sensory characteristics of the resulting oil were slightly reduced compared to rainfed treatment. The results indicate that regulated deficit irrigation benefits water use sustainability without compromising the quality of the oil.
Nanotechnology as a Promising Tool against Phytopathogens: A Futuristic Approach to Agriculture
Authors: Ray Manjit Kumar , Mishra Awdhesh Kumar , Mohanta Yugal Kishore , Mahanta Saurov , Chakrabartty Ishani , Kungwani Neelam Amit , Avula Satya Kumar , Panda Jibanjyoti , Pudake Ramesh Namdeo
Published: September 2023

It is crucial to increase agricultural yields to fulfill the rising demand for food and the security it provides for a growing population. To protect human food supplies and agricultural outputs, disease management is essential. Plant infections are a silent enemy of economic crop production and cross-border commerce of agricultural goods, inflicting roughly 20–30% losses a year. If infections are accurately and rapidly detected and identified, this can be minimized, and specialized treatment can be given. The current methods of preventing plant diseases are utterly dependent on agrochemicals, which have adverse effects on the ecosystem. By improving their solubility, lengthening their shelf life, and lowering their toxicity, nanotechnology can help reduce the harmful effects of pesticides and fungicides in a sustainable and environmentally responsible way. Engineered nanoparticles can be used to control plant diseases either by using the nanoparticle itself or as a carrier for fungicides and antibiotics. Regardless of the many prospective benefits of using nanoparticles, few nanoparticle-based products have been made commercially available for use in more widespread applications. For rapid and accurate spotting of plant diseases, the combination of nanotechnology systems with molecular diagnostics acts as an alternative where the detection may be taken in on a portable miniaturized appliance. By minimizing the application of chemicals and adopting quick identification of infections, nanotechnology might sustainably minimize many issues in disease control. This review outlines the tools and techniques used in the diagnosis of plant diseases and their management and explains how nanotechnology works, along with the current tools and their prospects for the future of plant protection.
New Weapons to Fight against Staphylococcus aureus Skin Infections
Authors: Cela Eliana M. , Urquiza Dolores , Gómez Marisa I. , Gonzalez Cintia D.
Published: September 2023

The treatment of Staphylococcus aureus skin and soft tissue infections faces several challenges, such as the increased incidence of antibiotic-resistant strains and the fact that the antibiotics available to treat methicillin-resistant S. aureus present low bioavailability, are not easily metabolized, and cause severe secondary effects. Moreover, besides the susceptibility pattern of the S. aureus isolates detected in vitro, during patient treatment, the antibiotics may never encounter the bacteria because S. aureus hides within biofilms or inside eukaryotic cells. In addition, vascular compromise as well as other comorbidities of the patient may impede proper arrival to the skin when the antibiotic is given parenterally. In this manuscript, we revise some of the more promising strategies to improve antibiotic sensitivity, bioavailability, and delivery, including the combination of antibiotics with bactericidal nanomaterials, chemical inhibitors, antisense oligonucleotides, and lytic enzymes, among others. In addition, alternative non-antibiotic-based experimental therapies, including the delivery of antimicrobial peptides, bioactive glass nanoparticles or nanocrystalline cellulose, phototherapies, and hyperthermia, are also reviewed.
Assessment of Bio-Compounds Content, Antioxidant Activity, and Neuroprotective Effect of Red Cabbage (Brassica oleracea var. Capitata rubra) Processed by Convective Drying at Different Temperatures
Authors: Vega-Galvez Antonio , Gomez-Perez Luis S. , Zepeda Francisca , Vidal René L. , Grunenwald Felipe , Mejías Nicol , Pasten Alexis , Araya Michael , Ah-Hen Kong Shun
Published: September 2023

Parkinson’s disease (PD) is the second most common neurodegenerative disorder, and no efficient therapy able to cure or slow down PD is available. In this study, dehydrated red cabbage was evaluated as a novel source of bio-compounds with neuroprotective capacity. Convective drying was carried out at different temperatures. Total phenolics (TPC), flavonoids (TFC), anthocyanins (TAC), and glucosinolates (TGC) were determined using spectrophotometry, amino acid profile by LC-DAD and fatty acid profile by GC-FID. Phenolic characterization was determined by liquid chromatography-high-resolution mass spectrometry. Cytotoxicity and neuroprotection assays were evaluated in SH-SY5Y human cells, observing the effect on preformed fibrils of α-synuclein. Drying kinetic confirmed a shorter processing time with temperature increase. A high concentration of bio-compounds was observed, especially at 90 °C, with TPC = 1544.04 ± 11.4 mg GAE/100 g, TFC = 690.87 ± 4.0 mg QE/100 g and TGC = 5244.9 ± 260.2 µmol SngE/100 g. TAC degraded with temperature. Glutamic acid and arginine were predominant. Fatty acid profiles were relatively stable and were found to be mostly C18:3n3. The neochlorogenic acid was predominant. The extracts had no cytotoxicity and showed a neuroprotective effect at 24 h testing, which can extend in some cases to 48 h. The present findings underpin the use of red cabbage as a functional food ingredient.
Highly Selective MIF Ketonase Inhibitor KRP-6 Diminishes M1 Macrophage Polarization and Metabolic Reprogramming
Authors: Vámos Eszter , Kálmán Nikoletta , Sturm Eva Maria , Nayak Barsha Baisakhi , Teppan Julia , Vántus Viola Bagóné , Kovács Dominika , Makszin Lilla , Loránd Tamás , Gallyas Ferenc , Radnai Balázs
Published: September 2023

Macrophage polarization is highly involved in autoimmunity. M1 polarized macrophages drive inflammation and undergo metabolic reprogramming, involving downregulation of mitochondrial energy production and acceleration of glycolysis. Macrophage migration inhibitory factor (MIF), an enigmatic tautomerase (ketonase and enolase), was discovered to regulate M1 polarization. Here, we reveal that KRP-6, a potent and highly selective MIF ketonase inhibitor, reduces MIF-induced human blood eosinophil and neutrophil migration similarly to ISO-1, the most investigated tautomerase inhibitor. We equally discovered that KRP-6 prevents M1 macrophage polarization and reduces ROS production in IFN-γ-treated cells. During metabolic reprogramming, KRP-6 improved mitochondrial bioenergetics by ameliorating basal respiration, ATP production, coupling efficiency and maximal respiration in LPS+IFN-γ-treated cells. KRP-6 also reduced glycolytic flux in M1 macrophages. Moreover, the selective MIF ketonase inhibitor attenuated LPS+IFN-γ-induced downregulation of PARP-1 and PARP-2 mRNA expression. We conclude that KRP-6 represents a promising novel therapeutic compound for autoimmune diseases, which strongly involves M1 macrophage polarization.
Nimbolide Inhibits SOD2 to Control Pancreatic Ductal Adenocarcinoma Growth and Metastasis
Authors: Mehmetoglu-Gurbuz Tugba , Lakshmanaswamy Rajkumar , Perez Karla , Sandoval Mayra , Jimenez Casandra A. , Rocha Jackelyn , Goldfarb Rachel Madeline , Perry Courtney , Bencomo Alejandra , Neela Nishkala , Barragan Jose A. , Sanchez Raquel , Swain Risa Mia , Subramani Ramadevi
Published: September 2023

Reactive oxygen species are frequently associated with various cancers including pancreatic ductal adenocarcinomas (PDACs). Superoxide dismutase 2 (SOD2) is an enzyme that plays an important role in reactive oxygen species (ROS) signaling. Investigating the molecular function and biological functions of SOD2 can help us develop new therapeutic options and uncover new biomarkers for PDAC diagnosis and prognosis. Here, we show that nimbolide (NB), a triterpene limonoid, effectively blocks the growth and metastasis of PDACs by suppressing the expression and activity of SOD2. To identify the role of SOD2 in NB-induced anticancer activity, we used RNA interference to silence and plasmid transfection to overexpress it. Silencing SOD2 significantly reduced the growth and metastatic characteristics like epithelial-to-mesenchymal transition, invasion, migration, and colony-forming capabilities of PDACs, and NB treatment further reduced these characteristics. Conversely, the overexpression of SOD2 enhanced these metastatic characteristics. ROS signaling has a strong feedback mechanism with the PI3K/Akt signaling pathway, which could be mediated through SOD2. Finally, NB treatment to SOD2-overexpressing PDAC xenografts resulted in significant inhibition of tumor growth and metastasis. Overall, this work suggests that NB, a natural and safe phytochemical that silences SOD2 to induce high levels of ROS generation, results in increased apoptosis and reduced growth and progression of PDACs. The role of SOD2 in regulating NB-induced ROS generation presents itself as a therapeutic option for PDACs.
Inhibitory Effects of Ehretia tinifolia Extract on the Excessive Oxidative and Inflammatory Responses in Lipopolysaccharide-Stimulated Mouse Kupffer Cells
Authors: Lim Jae Sung , Lee Sung Ho , Yun Hyosuk , Lee Da Young , Cho Namki , Yoo Guijae , Choi Jeong Uk , Lee Kwang Youl , Bach Tran The , Park Su-Jin , Cho Young-Chang
Published: September 2023

Ehretia tinifolia (E. tinifolia) L., an evergreen tree with substantial biological activity, including antioxidant and anti-inflammatory effects, has been used in many herbal and traditional medicines. To elucidate its antioxidant and anti-inflammatory activity and the underlying mechanisms, we applied a methanol extract of E. tinifolia (ETME) to lipopolysaccharide (LPS)-stimulated mouse immortalized Kupffer cells. ETME suppressed the LPS-induced increase in nitric oxide, a mediator for oxidative stress and inflammation, and restored LPS-mediated depletion of total glutathione level by stabilizing antioxidative nuclear factor erythroid 2-related factor 2 (Nrf2) and the subsequent increase in heme oxygenase-1 levels. Furthermore, ETME inhibited the LPS-induced production of pro-inflammatory cytokines, including tumor necrosis factor-α, interleukin (IL)-1β, and IL-6. The inhibitory effects of ETME on pro-inflammatory responses were regulated by ETME-mediated dephosphorylation of mitogen-activated protein kinases (MAPKs: p38, p44/p42, and stress-associated protein kinase/c-Jun N-terminal kinase) and inhibition of nuclear localization of nuclear factor kappa B (NF-κB). These results suggest that ETME is a possible candidate for protecting Kupffer cells from LPS-mediated oxidative stress and excessive inflammatory responses by activating antioxidant Nrf2/HO-1 and inhibiting pro-inflammatory NF-κB and MAPKs, respectively.
Chemical Property Evaluation and Tensile Strength Correlation of XLPE Insulators Based on Accelerated Thermal Aging
Authors: Kwak Byeong Sub , Jeon Taehyun , Kim Ah-Reum , Kim Eunyoung , Kim Jae-Kon , Min Youngje , Park Hyunjoo
Published: September 2023

Cross-linked polyethylene (XLPE) cable is a representative power transmission cable. XLPE has excellent mechanical properties, chemical and heat resistance, and insulation. However, XLPE insulation deteriorates during operation due to electrical, mechanical, and thermal stresses. Among these, thermal stress is a major factor and reduces insulation properties due to a change in molecular structure. Therefore, XLPE characteristic evaluation by heat exposure is essential for power cable condition evaluation. Herein, deteriorated XLPE samples were characterized by tensile strength, X-ray diffraction, Fourier-transform infrared spectroscopy, differential scanning calorimetry, and ultraviolet-visible spectroscopy after exposure to various temperatures and durations. Comparing the tensile strength with other analysis results yielded correlations. Each characteristic showed a linear relationship. The correlation between tensile strength and carbonyl index was the strongest, and the coefficient of determination, R2, was 0.9299. Therefore, these results will provide important information on chemical properties when establishing operational management standards for XLPE insulators in the future.
A Hybrid Human Activity Recognition Method Using an MLP Neural Network and Euler Angle Extraction Based on IMU Sensors
Authors: Mao Yaxin , Yan Lamei , Guo Hongyu , Hong Yujie , Huang Xiaocheng , Yuan Youwei
Published: September 2023

Inertial measurement unit (IMU) technology has gained popularity in human activity recognition (HAR) due to its ability to identify human activity by measuring acceleration, angular velocity, and magnetic flux in key body areas like the wrist and knee. It has propelled the extensive application of HAR across various domains. In the healthcare sector, HAR finds utility in monitoring and assessing movements during rehabilitation processes, while in the sports science field, it contributes to enhancing training outcomes and preventing exercise-related injuries. However, traditional sensor fusion algorithms often require intricate mathematical and statistical processing, resulting in higher algorithmic complexity. Additionally, in dynamic environments, sensor states may undergo changes, posing challenges for real-time adjustments within conventional fusion algorithms to cater to the requirements of prolonged observations. To address these limitations, we propose a novel hybrid human pose recognition method based on IMU sensors. The proposed method initially calculates Euler angles and subsequently refines them using magnetometer and gyroscope data to obtain the accurate attitude angle. Furthermore, the application of FFT (Fast Fourier Transform) feature extraction facilitates the transition of the signal from its time-based representation to its frequency-based representation, enhancing the practical significance of the data. To optimize feature fusion and information exchange, a group attention module is introduced, leveraging the capabilities of a Multi-Layer Perceptron which is called the Feature Fusion Enrichment Multi-Layer Perceptron (GAM-MLP) to effectively combine features and generate precise classification results. Experimental results demonstrated the superior performance of the proposed method, achieving an impressive accuracy rate of 96.13% across 19 different human pose recognition tasks. The proposed hybrid human pose recognition method is capable of meeting the demands of real-world motion monitoring and health assessment.
The Influence of Circular Physical Human–Machine Interfaces of Three Shoulder Exoskeletons on Tissue Oxygenation
Authors: Linnenberg Christine , Reimeir Benjamin , Eberle Robert , Weidner Robert
Published: September 2023

Occupational shoulder exoskeletons need to provide meaningful torques to achieve the desired support, thereby high pressures can occur within the physical human–machine interface (pHMI) of exoskeletons that may lead to discomfort, pain, or soft tissue injuries. This pilot study investigates the effects of occurring circumferential pressures within the pHMI in three different shoulder exoskeletons on the tissue oxygenation underneath the interfaces in resting position and dynamic use of the exoskeletons in 12 healthy subjects using near-infrared spectroscopy. Similar to standard Vascular Occlusion Tests, the tissue oxygen decreases while wearing the exoskeletons at rest (−2.1 (1.4) %/min). Dynamic use of the exoskeleton enhances the decrease in tissue oxygen (−7.3 (4.1) %/min) significantly and leads to greater resaturation after reopening the interface compared to resting position. This can be a sign of restricted blood supply to the upper extremity while wearing the exoskeleton. The shape and width of the circular interfaces showed no effect on the tissue oxygenation during use. Tissue oxygenation can be established as an additional safety criterion of exoskeletal pHMIs. The design of pHMI of shoulder exoskeletons should be reconsidered, e.g., in terms of open structures or the elasticity of closure straps to avoid occlusion effects.
ER-LAC: Span-Based Joint Entity and Relation Extraction Model with Multi-Level Lexical and Attention on Context Features
Authors: Zhu Yaqin , Li Xuhang , Wang Zijian , Li Jiayong , Yan Cairong , Zhang Yanting
Published: September 2023

In recent years, joint entity–relation extraction (ERE) models have become a hot research topic in natural language processing (NLP). Several studies have proposed a span-based ERE framework, which utilizes simple span embeddings for entity and relation classification. This framework addresses the issues of overlap and error propagation that were present in previous entity–relation extraction models. However, span-based models overlook the influence of lexical information on the semantic representation of the span and fail to consider relations with a strong intrinsic connection between span pairs. To tackle these aforementioned issues, we present a new ERE model called ER-LAC (Span-based Joint Entity and Relation Extraction Model with Multi-level Lexical and Attention on Context Features). This model is designed with multi-granularity lexical features to enhance the semantic representation of spans, and a transformer classifier is employed to capture the internal connections between span pairs, thereby improving the performance of relational classification. To demonstrate the effectiveness of the proposed model, ablation experiments were conducted on the CoNLL04 dataset. The proposed model was also compared with other models on three datasets, showcasing its computational efficiency. The results indicate that the introduced lexical features and classifier enhance the F1 score for entity extraction by 0.84% to 2.04% and improve the F1 score for relationship classification by 0.96% to 2.26% when compared to the previous state-of-the-art (SOTA) model and the baseline SpERT model, respectively.
Evaluating the Time-Dependent Behavior of Deeply Buried Tunnels in Soft Rock Environments and Relevant Measures Guaranteeing Their Long-Term Stability
Authors: Frenelus Wadslin , Peng Hui
Published: September 2023

The time-dependent behavior and long-term stability of deep-buried tunnels in soft rocks have received lots of considerations in tunnel engineering and allied sciences. To better explore and deepen the engineering application of rock creep, extensive research studies are still needed, although fruitful outcomes have already been obtained in many related investigations. In this article, the Weilai Tunnel in China’s Guangxi province is studied, taking its host rocks as the main research object. In fact, aiming at forecasting the time-varying deformation of this tunnel, a novel elasto-visco-plastic creep constitutive model with two variants is proposed, by exploiting the typical complex load–unload process of rock excavation. The model is well validated, and good agreements are found with the relevant experimental data. Moreover, the time-dependent deformation rules are properly established for the surrounding rocks, by designing two new closed-form solutions based on the proposed creep model and the Hoek–Brown criterion. To investigate the effects of the major creep parameters and the geological strength index (GSI) of the surrounding rocks on the time-dependent trend of the tunnel, an in-depth parametric study is carried out. It is shown that the convergence deformation of the surrounding rocks is remarkably influenced by the GSI and creep parameters. The convergence deformations calculated from the closed-form solutions conform well to the on-site monitoring data. In only 27 days after excavation, the creep deformation of the Weilai tunnel overtakes 400 mm, which is enormous. To guarantee the long-term stability of this tunnel, a robust support scheme and its long-term monitoring with appropriate remote sensors are strongly suggested.
Identification of Damage in Beams by Modal Curvatures Using Acoustic Beamformers
Authors: Pau Annamaria , Eroğlu Uğurcan
Published: September 2023

This paper presents an approach to damage identification in beams by modal curvatures based on the use of beamforming algorithms. These processors have been successfully used in acoustics for the last thirty years to solve the inverse problems encountered in source recognition and image reconstruction, based on ultrasonic waves. In addition, beamformers apply to a broader range of problems in which the forward solutions are computable and measurable. This especially concerns the field of structural vibrations, where the use of such estimators has not received attention to date. In this paper, modal curvatures will play the role of replica vectors of the imaging field. The choice to use modal curvatures is motivated by means of numerical studies and experimental tests on a steel beam. Furthermore, we compare the performance of the Bartlett and minimum variance distortionless response (MVDR) beamformers with an estimator based on the simple minimization of the difference between model and measured data. The results suggest that the application of the MVDR beamformer is highly effective, especially in cases of slight damage between two sensors. MVDR enables both damage localization and quantification.
The Micromobility Tendencies of People and Their Transport Behavior
Authors: Kalašová Alica , Čulík Kristián
Published: September 2023

Addressing transport in cities requires a change in people’s behavior and a better distribution of different transport modes’ performances—a change in the modal split. This article focuses on detailed research on the transport behaviors of residents and their attitudes towards possible changes. We developed a questionnaire and distributed it online and physically. The data came from an anonymous survey, and basic statistical methods and a correlation analysis were applied to them. One of the research tasks was to find the correlations between individual characteristics. The analysis showed that the respondents’ education influenced their opinions about transport behavior. The results showed that the most common means of shared mobility was bicycles. The paper contains detailed results regarding the use of private cars and transport behavior in general. In addition, the study presents other significant findings regarding the average number of vehicles in households, the types of vehicles, and their usage patterns. The results of our study are useful for practical applications, because they describe traffic behavior patterns and can improve future decision making and transport planning.
SbMBR Tree—A Spatiotemporal Data Indexing and Compression Algorithm for Data Analysis and Mining
Authors: Guan Runda , Wang Ziyu , Pan Xiaokang , Zhu Rongjie , Song Biao , Zhang Xinchang
Published: September 2023

In the field of data analysis and mining, adopting efficient data indexing and compression techniques to spatiotemporal data can significantly reduce computational and storage overhead for the abilities to control the volume of data and exploit the spatiotemporal characteristics. However, traditional lossy compression techniques are hardly suitable due to their inherently random nature. They often impose unpredictable damage to scientific data, which affects the results of data mining and analysis tasks that require certain precision. In this paper, we propose a similarity-based minimum bounding rectangle (SbMBR) tree, a tree-based indexing and compression method, to address the aforementioned problem. Our method can hierarchically select appropriate minimum bounding rectangles according to the given maximum acceptable errors and use the average value contained in each selected MBR to replace the original data to achieve data compression with multi-layer loss control. This paper also provides the corresponding tree construction algorithm and range query processing algorithm for the indexing structure mentioned above. To evaluate the data quality preservation in cross-domain data analysis and mining scenarios, we use mutual information as the estimation metric. Experimental results emphasize the superiority of our method over some of the typical indexing and compression algorithms.
Tunability of Radiation Pattern of the H-Polarized Natural Waves of Dielectric Waveguide with Infinite Graphene Plane and Finite Number of Graphene Strips at THz
Authors: Kaliberda Mstyslav E. , Pogarsky Sergey A.
Published: September 2023

We investigate the radiation of the THz natural waves of the dielectric waveguide with graphene plane scattered by finite number of graphene strips. Our mathematically accurate analysis uses the singular integral equations method. The discretization scheme employs the Nystrom-type algorithm. The complex-valued propagation constants of the natural waves and corresponding fields are determined numerically from the equation, which also involves the kernel-function of the singular integral equation. The method we use is meshless and full-wave. The convergence is provided by the mathematical theorems. By varying the chemical potential of graphene and structural geometrical parameters, we examine the elevation angle of the main lobe of the radiation pattern and the radiated power.
Jade for Bones in Hongshan Craftsmanship: Human Anatomy as the Genesis of a Prehistoric Style
Authors: Larrivé-Bass Sandrine
Published: September 2023

Jade artifacts produced in prehistoric China continue to generate extensive scholarly interest. In the absence of textual data, inferring how works functioned in Jade Age communities remains challenging. This paper focuses on Hongshan 红山 culture (4500–3000 BCE) jades, a distinctively styled corpus primarily recovered from late fourth millennium BCE graves in northeastern China. Recent finds within and beyond the Hongshan core zone have enriched the jade inventory and expanded the known scope of its stylistic variations. The analysis sheds light on enigmatic types, reveals the complex representational nature of this corpus, and clarifies the mimetic intentions that resulted in the soft rounded forms characteristic of the style. Most objects examined were unearthed at Hongshan ceremonial centers and have sound excavation pedigrees. Their study relies on contextual archaeological data and comparative visual analysis and draws on the broader Hongshan material world. Further considerations include environment, funerary practices, materiality, cognition, and human anatomy. Ultimately, the paper uncovers new paradigms of figural representation that should open fresh investigative avenues for specialists of early China. Preliminary evaluation of jades unearthed further south at Lingjiatan 凌家滩 and Liangzhu 良渚 sites suggests that some late Neolithic societies adopted Hongshan practices. Current evidence hints at members of prehistoric communities attempting, through jade works, to rationalize their physical circumstances and assert their social power by symbolically fusing with elements of their environments.
Automatic Recommendation of Forum Threads and Reinforcement Activities in a Data Structure and Programming Course
Authors: Plaza Laura , Araujo Lourdes , López-Ostenero Fernando , Martínez-Romo Juan
Published: September 2023

Online learning is quickly becoming a popular choice instead of traditional education. One of its key advantages lies in the flexibility it offers, allowing individuals to tailor their learning experiences to their unique schedules and commitments. Moreover, online learning enhances accessibility to education, breaking down geographical and economical boundaries. In this study, we propose the use of advanced natural language processing techniques to design and implement a recommender that supports e-learning students by tailoring materials and reinforcement activities to students’ needs. When a student posts a query in the course forum, our recommender system provides links to other discussion threads where related questions have been raised and additional activities to reinforce the study of topics that have been challenging. We have developed a content-based recommender that utilizes an algorithm capable of extracting key phrases, terms, and embeddings that describe the concepts in the student query and those present in other conversations and reinforcement activities with high precision. The recommender considers the similarity of the concepts extracted from the query and those covered in the course discussion forum and the exercise database to recommend the most relevant content for the student. Our results indicate that we can recommend both posts and activities with high precision (above 80%) using key phrases to represent the textual content. The primary contributions of this research are three. Firstly, it centers on a remarkably specialized and novel domain; secondly, it introduces an effective recommendation approach exclusively guided by the student’s query. Thirdly, the recommendations not only provide answers to immediate questions, but also encourage further learning through the recommendation of supplementary activities.
Literature-Based Discovery to Elucidate the Biological Links between Resistant Hypertension and COVID-19
Authors: Kartchner David , McCoy Kevin , Dubey Janhvi , Zhang Dongyu , Zheng Kevin , Umrani Rushda , Kim James J. , Mitchell Cassie S.
Published: September 2023

Multiple studies have reported new or exacerbated persistent or resistant hypertension in patients previously infected with COVID-19. We used literature-based discovery to identify and prioritize multi-scalar explanatory biology that relates resistant hypertension to COVID-19. Cross-domain text mining of 33+ million PubMed articles within a comprehensive knowledge graph was performed using SemNet 2.0. Unsupervised rank aggregation determined which concepts were most relevant utilizing the normalized HeteSim score. A series of simulations identified concepts directly related to COVID-19 and resistant hypertension or connected via one of three renin–angiotensin–aldosterone system hub nodes (mineralocorticoid receptor, epithelial sodium channel, angiotensin I receptor). The top-ranking concepts relating COVID-19 to resistant hypertension included: cGMP-dependent protein kinase II, MAP3K1, haspin, ral guanine nucleotide exchange factor, N-(3-Oxododecanoyl)-L-homoserine lactone, aspartic endopeptidases, metabotropic glutamate receptors, choline-phosphate cytidylyltransferase, protein tyrosine phosphatase, tat genes, MAP3K10, uridine kinase, dicer enzyme, CMD1B, USP17L2, FLNA, exportin 5, somatotropin releasing hormone, beta-melanocyte stimulating hormone, pegylated leptin, beta-lipoprotein, corticotropin, growth hormone-releasing peptide 2, pro-opiomelanocortin, alpha-melanocyte stimulating hormone, prolactin, thyroid hormone, poly-beta-hydroxybutyrate depolymerase, CR 1392, BCR-ABL fusion gene, high density lipoprotein sphingomyelin, pregnancy-associated murine protein 1, recQ4 helicase, immunoglobulin heavy chain variable domain, aglycotransferrin, host cell factor C1, ATP6V0D1, imipramine demethylase, TRIM40, H3C2 gene, COL1A1+COL1A2 gene, QARS gene, VPS54, TPM2, MPST, EXOSC2, ribosomal protein S10, TAP-144, gonadotropins, human gonadotropin releasing hormone 1, beta-lipotropin, octreotide, salmon calcitonin, des-n-octanoyl ghrelin, liraglutide, gastrins. Concepts were mapped to six physiological themes: altered endocrine function, 23.1%; inflammation or cytokine storm, 21.3%; lipid metabolism and atherosclerosis, 17.6%; sympathetic input to blood pressure regulation, 16.7%; altered entry of COVID-19 virus, 14.8%; and unknown, 6.5%.
Isotopic Overlap of Invasive and Native Consumers in the Food Web of Lake Trasimeno (Central Italy)
Authors: Cicala Davide , Guerra Maria Teresa , Bardelli Roberta , Di Muri Cristina , Ludovisi Alessandro , Vizzini Salvatrice , Mancinelli Giorgio
Published: September 2023

An advanced characterization of the trophic niche of non-indigenous species (NIS) may provide useful information on their ecological impact on invaded communities. Here, we used carbon and nitrogen stable isotopes to estimate pairwise niche overlaps between non-indigenous and native consumers in the winter food web of Lake Trasimeno (central Italy). Overall, a relatively low pairwise overlap of isotopic niches was observed between NIS and native species. The only exception was the Louisiana crayfish Procambarus clarkii, which showed a relatively high and diffuse overlap with other native invertebrates. Our findings highlighted a high niche divergence between non-indigenous and native species in Lake Trasimeno, suggesting a potentially low degree of interspecific competition that may facilitate coexistence and, in turn, limit the strength of impacts. The divergent results obtained for the Louisiana crayfish indicate that additional control measures for this invasive species are needed to mitigate its impact on the Lake Trasimeno system.
Taxonomic Composition and Salinity Tolerance of Macrozoobenthos in Small Rivers of the Southern Arid Zone of the East European Plain
Authors: Golovatyuk Larisa V. , Nazarova Larisa B. , Kalioujnaia Irina J. , Grekov Ivan M.
Published: September 2023

This study investigated the species composition, distribution, and salinity tolerance of macrozoobenthos in 17 small rivers in the southern arid region of the East European Plain, which are characterized by a small channel gradient, slow-flowing or stagnant water bodies, and a wide range of water salinity, varying between 0.18 and 30 g L−1. In total, 156 taxa were found, among which 66 were Diptera species. The study revealed that the formation of benthic communities in the rivers is influenced by natural factors of the catchment basins, including the flat landscape with sparsely developed relief differentiation, climate aridity, and the widespread occurrence of saline soils and groundwater, largely related to the sedimentation of the ancient Caspian Sea and modern climate changes. These conditions are favorable for the occurrence of lacustrine macrozoobenthic species in freshwater, euryhaline, and halophilic ecological groups. The investigation revealed a decrease in species richness in response to an increase in water salinity. The five identified halophilic species Tanytarsus kharaensis, Glyptotendipes salinus, Cricotopus salinophilus, Chironomus salinarius, and Palpomyia schmidti can be used as indicators of river ecosystem salinization.
The Basolateral Amygdala: The Core of a Network for Threat Conditioning, Extinction, and Second-Order Threat Conditioning
Authors: Sepahvand Tayebeh , Power Kyron D. , Qin Tian , Yuan Qi
Published: September 2023

Threat conditioning, extinction, and second-order threat conditioning studied in animal models provide insight into the brain-based mechanisms of fear- and anxiety-related disorders and their treatment. Much attention has been paid to the role of the basolateral amygdala (BLA) in such processes, an overview of which is presented in this review. More recent evidence suggests that the BLA serves as the core of a greater network of structures in these forms of learning, including associative and sensory cortices. The BLA is importantly regulated by hippocampal and prefrontal inputs, as well as by the catecholaminergic neuromodulators, norepinephrine and dopamine, that may provide important prediction-error or learning signals for these forms of learning. The sensory cortices may be required for the long-term storage of threat memories. As such, future research may further investigate the potential of the sensory cortices for the long-term storage of extinction and second-order conditioning memories.