bluuebunny/crossref_metadata_2025 huggingface dataset:
Unconventional Sites for Diagnosis of Leptospirosis in Bovine Anicteric Fetuses
Authors: Aymée Luiza , Di Azevedo Maria Isabel Nogueira , Reis Luiza , Mendes Julia , Castro Fúlvia de Fátima Almeida de , Carvalho-Costa Filipe Anibal , Souza Guilherme Nunes de , Lilenbaum Walter
Published: September 2023

Background: Bovine leptospirosis is an important reproductive disease and abortion is a major sign, leading to economic impacts. Due to its multifactorial etiology, the proper diagnosis of the cause of the abortion is crucial. Necropsy of the fetuses followed by molecular analysis is recommended for diagnosis, and the investigation mainly occurs in the kidneys and liver. This study aimed to analyze unconventional sites for the presence of leptospiral DNA in bovine anicteric aborted fetuses. Methods: Five fetuses of the same herd were received for necropsy and diagnosis. Conventional lipL32-PCR was performed in the fetuses’ kidneys, livers, lungs, hearts, spleens, subcapsular kidney content, abomasal fluid, and in the cavity’s hemorrhagic contents. To complete the investigation, the sera of 30 cows of the herd were collected to perform the serologic screening by Microscopic Agglutination Test. In addition, six subfertile non-pregnant cows from the same herd were selected due to their low reproductive performance, and genital samples (uterine fragment and cervicovaginal mucus) and urine were collected for lipL32-PCR. PCR-positive samples were submitted to a nested PCR of the secY gene and intended for sequencing. Results: The herd presented seroreactive animals (11/30, 36.6%), all against the Sejroe serogroup, with titers between 200 and 1600. In necropsy, four fetuses showed hemorrhagic and anicteric lesions, while one fetus had no macroscopic lesions. Regarding molecular analysis, all the fetuses were positive in lipL32-PCR and the positive sites were the heart, lungs, subcapsular kidney content, thymus, kidneys, liver, and abomasal fluid. Only one fetus presented positive results in the kidney and liver, while three fetuses were positive in the abomasal fluid. Five of six cows were positive for lipL32-PCR, all being positive only in genital samples. Of the fetuses and the cows, seven sequences were obtained and all were identified as Leptospira interrogans serogroup Sejroe serovar Hardjoprajitno. Conclusions: In order to improve the diagnosis of leptospirosis in cows, it is recommended to perform a comprehensive analysis of the samples, beyond the kidneys and liver. Thus, we highly encourage testing multiple organs by PCR to investigate abortions suspected of bovine leptospirosis, particularly in anicteric fetuses.
Endocannabinoid System Receptors at the Hip and Stifle Joints of Middle-Aged Dogs: A Novel Target for the Therapeutic Use of Cannabis sativa Extract in Canine Arthropathies
Authors: Zamith Cunha Rodrigo , Salamanca Giulia , Mille Fanny , Delprete Cecilia , Franciosi Cecilia , Piva Giuliano , Gramenzi Alessandro , Chiocchetti Roberto
Published: September 2023

The endocannabinoid system (ECS) has emerged as a potential therapeutic target in veterinary medicine due to its involvement in a wide range of physiological processes including pain, inflammation, immune function, and neurological function. Modulation of the ECS receptors has been shown to have anti-inflammatory, analgesic, and immunomodulatory effects in various animal models of disease, including dogs with osteoarthritis. The goal of this study was to identify and compare the cellular expression and distribution of cannabinoid receptor type 1 (CB1R) and type 2 (CB2R) and the cannabinoid-related G protein-coupled receptor 55 (GPR55) on the synovial cells of hip and stifle joints of seven dogs of different breeds without overt signs of osteoarthritis (OA). The synovial membranes of seven hips and seven stifle joints were harvested post mortem. The expression of the CB1R, CB2R, and GPR55 present in the synovial tissues was investigated using qualitative and quantitative immunofluorescence and Western blot (Wb) analysis. Synoviocytes of the stifle and hip joints expressed CB1R, CB2R, and GPR55 immunoreactivity (IR); no significant differences were observed for each different joint. Cannabinoid receptor 2- and GPR55-IR were also expressed by macrophages, neutrophils, and vascular cells. The ECS receptors were widely expressed by the synovial elements of dogs without overt signs of OA. It suggests that the ECS could be a target for the therapeutic use of Cannabis sativa extract in canine arthropathies.
Assessing the Activity under Different Physico-Chemical Conditions, Digestibility, and Innocuity of a GAPDH-Related Fish Antimicrobial Peptide and Analogs Thereof
Authors: Cashman-Kadri Samuel , Lagüe Patrick , Fliss Ismail , Beaulieu Lucie
Published: September 2023

The antimicrobial activity of SJGAP (skipjack tuna GAPDH-related antimicrobial peptide) and four chemical analogs thereof was determined under different physicochemical conditions, including different pH values, the presence of monovalent and divalent cations, and after a heating treatment. The toxicity of these five peptides was also studied with hemolytic activity assays, while their stability under human gastrointestinal conditions was evaluated using a dynamic in vitro digestion model and chromatographic and mass spectrometric analyses. The antibacterial activity of all analogs was found to be inhibited by the presence of divalent cations, while monovalent cations had a much less pronounced impact, even promoting the activity of the native SJGAP. The peptides were also more active at acidic pH values, but they did not all show the same stability following a heat treatment. SJGAP and its analogs did not show significant hemolytic activity (except for one of the analogs at a concentration equivalent to 64 times that of its minimum inhibitory concentration), and the two analogs whose digestibility was studied degraded very rapidly once they entered the stomach compartment of the digestion model. This study highlights for the first time the characteristics of antimicrobial peptides from Scombridae or homologous to GAPDH that are directly related to their potential clinical or food applications.
Chlorhexidine-Containing Electrospun Polymeric Nanofibers for Dental Applications: An In Vitro Study
Authors: de Carvalho Luana Dutra , Peres Bernardo Urbanetto , Shen Ya , Haapasalo Markus , Maezono Hazuki , Manso Adriana P. , Ko Frank , Jackson John , Carvalho Ricardo M.
Published: September 2023

Chlorhexidine is the most commonly used anti-infective drug in dentistry. To treat infected void areas, a drug-loaded material that swells to fill the void and releases the drug slowly is needed. This study investigated the encapsulation and release of chlorhexidine from cellulose acetate nanofibers for use as an antibacterial treatment for dental bacterial infections by oral bacteria Streptococcus mutans and Enterococcus faecalis. This study used a commercial electrospinning machine to finely control the manufacture of thin, flexible, chlorhexidine-loaded cellulose acetate nanofiber mats with very-small-diameter fibers (measured using SEM). Water absorption was measured gravimetrically, drug release was analyzed by absorbance at 254 nm, and antibiotic effects were measured by halo analysis in agar. Slow electrospinning at lower voltage (14 kV), short target distance (14 cm), slow traverse and rotation, and syringe injection speeds with controlled humidity and temperature allowed for the manufacture of strong, thin films with evenly cross-meshed, uniform low-diameter nanofibers (640 nm) that were flexible and absorbed over 600% in water. Chlorhexidine was encapsulated efficiently and released in a controlled manner. All formulations killed both bacteria and may be used to fill infected voids by swelling for intimate contact with surfaces and hold the drug in the swollen matrix for effective bacterial killing in dental settings.
Antioxidant Capacity of Polar and Non-Polar Extracts of Four African Green Leafy Vegetables and Correlation with Polyphenol and Carotenoid Contents
Authors: Fioroni Nelly , Mouquet-Rivier Claire , Meudec Emmanuelle , Cheynier Véronique , Boudard Frédéric , Hemery Youna , Laurent-Babot Caroline
Published: September 2023

In sub-Saharan Africa, chronic malnutrition is often associated with intestinal inflammation and oxidative stress. African green leafy vegetables (GLVs), commonly consumed by these populations and rich in bioactive compounds, may improve the antioxidant status. The aim of this study was to measure the antioxidant capacity using complementary assays (DPPH, FRAP, ABTS, ORAC and NO scavenging) in polar and non-polar leaf extracts of four African GLVs, cassava (Manihot esculenta), roselle (Hibiscus sabdariffa), jute mallow (Corchorus olitorius), and amaranth (Amaranthus spp.), with spinach (Spinacia oleracea) chosen as a reference. Their antioxidant capacity was correlated with their total polyphenol (TPC), flavonoid (TFC), condensed tannin, lutein, and β-carotene contents. Identification of phenolic compounds by UHPLC-DAD-MS/MS revealed the presence of three main classes of compound: flavonols, flavones, and hydroxycinnamic acids. Cassava and roselle leaves presented significantly higher TPC and TFC than amaranth, jute mallow, and spinach. They also exhibited the highest antioxidant capacity, even higher than that of spinach, which is known for its important antioxidant effect. The antioxidant capacity was 2 to 18 times higher in polar than non-polar extracts, and was more strongly correlated with TPC and TFC (R > 0.8) than with β-carotene and lutein contents. These findings provide new data especially for cassava and roselle leaves, for which studies are scarce, suggesting an appreciable antioxidant capacity compared with other leafy vegetables.
Tacrolimus Improves Therapeutic Efficacy of Umbilical Cord Blood-Derived Mesenchymal Stem Cells in Diabetic Retinopathy by Suppressing DRP1-Mediated Mitochondrial Fission
Authors: Jo Hang Hyo , Goh Yeong Seok , Kim Hye Jih , Kim Dae Hyun , Kim Hyemin , Hwang Jiyi , Jung Ji Seung , Kang Nanyoung , Park Sang Eun , Park Kyung Mee , Lee Hyun Jik
Published: September 2023

Diabetic retinopathy (DR) is a leading cause of blindness in diabetic patients. Umbilical cord blood-derived mesenchymal stem cells (UCB-MSCs) are emerging as a promising new drug for degenerative disease associated with diabetes. Recent studies have shown that high glucose-increased excessive calcium levels are a major risk factor for mitochondrial reactive oxygen species (mtROS) accumulation and apoptosis. This study aimed to investigate the role of high glucose-induced NFATC1 signaling in mitochondrial oxidative stress-stimulated apoptosis and the effect of tacrolimus on the therapeutic efficacy of subconjunctival transplantation of UCB-MSCs in a DR rat model. High glucose increased mtROS and cleaved caspase-9 expression in UCB-MSCs. High glucose conditions increased O-GlcNAcylated protein expression and nuclear translocation of NFATC1. Tacrolimus pretreatment recovered high glucose-induced mtROS levels and apoptosis. In the DR rat model, subconjunctival transplantation of tacrolimus-pretreated MSCs improved retinal vessel formation, retinal function, and uveitis. In high glucose conditions, tacrolimus pretreatment reduced protein and mRNA expression levels of DRP1 and inhibited mitochondrial fission. In conclusion, we demonstrated that high glucose-induced O-GlcNAcylation activates NFATC1 signaling, which is important for DRP1-mediated mitochondrial fission and mitochondrial apoptosis. Finally, we proposed NFATC1 suppression by tacrolimus as a promising therapeutic strategy to improve the therapeutic efficacy of UCB-MSC transplantation for DR treatment.
Redox Regulation of Nrf2 in Cisplatin-Induced Kidney Injury
Authors: Mapuskar Kranti A. , Pulliam Casey F. , Zepeda-Orozco Diana , Griffin Benjamin R. , Furqan Muhammad , Spitz Douglas R. , Allen Bryan G.
Published: September 2023

Cisplatin, a potent chemotherapeutic agent, is marred by severe nephrotoxicity that is governed by mechanisms involving oxidative stress, inflammation, and apoptosis pathways. The transcription factor Nrf2, pivotal in cellular defense against oxidative stress and inflammation, is the master regulator of the antioxidant response, upregulating antioxidants and cytoprotective genes under oxidative stress. This review discusses the mechanisms underlying chemotherapy-induced kidney injury, focusing on the role of Nrf2 in cancer therapy and its redox regulation in cisplatin-induced kidney injury. We also explore Nrf2's signaling pathways, post-translational modifications, and its involvement in autophagy, as well as examine redox-based strategies for modulating Nrf2 in cisplatin-induced kidney injury while considering the limitations and potential off-target effects of Nrf2 modulation. Understanding the redox regulation of Nrf2 in cisplatin-induced kidney injury holds significant promise for developing novel therapeutic interventions. This knowledge could provide valuable insights into potential strategies for mitigating the nephrotoxicity associated with cisplatin, ultimately enhancing the safety and efficacy of cancer treatment.
Aircraft Target Interpretation Based on SAR Images
Authors: Wang Xing , Hong Wen , Liu Yunqing , Hu Dongmei , Xin Ping
Published: September 2023

The focus of the current research is how to effectively identify aircraft targets in SAR images. There are only 2000 SAR images and 6556 aircraft instances in our dataset. SAR images have complex backgrounds, and the sizes of aircraft targets are multi-scale. How to improve the detection accuracy of aircraft targets is the research topic of this paper, especially for small target detection. We proposed four improved methods based on YOLOv5s. Firstly, this paper proposed the structure of the multi-scale receptive field and channel attention fusion. It is applied at the shallow layer of the backbone of YOLOv5s. It can adjust the weights of the multi-scale receptive field during the training process to enhance the extraction ability of feature information. Secondly, we proposed four decoupled detection heads to replace the original part in YOLOv5s. It can improve the efficiency and accuracy of SAR image interpretation for small targets. Thirdly, in the case of the limited amount of SAR images, this paper proposed multiple data-augmentation methods, which can enhance the diversity and generalization of the network. Finally, this paper proposed the K-means++ to replace the original K-means to improve the network convergence speed and detection accuracy. Experiments demonstrate that the improved YOLOv5s can enhance the accuracy of SAR image interpretation by 9.3%, and the accuracy of small targets is improved more obviously, reaching 13.1%.
Sensitivity Analysis of Structural Parameters of Unequal-Span Continuous Rigid Frame Bridge with Corrugated Steel Webs
Authors: Duan Maojun , Wang Fei , Wu Yutian , Tao Hao , Zhang Danping
Published: September 2023

To investigate the effect of structural parameters of bridges with unequal spans on the bridge alignment, the finite element model simulating the full-scale bridge was developed, considering the construction process. For ease of finite element modeling and investigation, the section of composite beam with corrugated steel web was first converted into the section composed of the same material. For this purpose, an equivalent method of replacing corrugated steel webs with concrete webs was proposed based on theoretical derivation. After equivalent replacement, the influences of material bulk density, internal prestress, pipe friction coefficient, and pipe deviation coefficient on the main beam at the maximum cantilever stage were analyzed, and the influences of external prestress on the main beam after bridge construction were analyzed. The results show that the most sensitive parameter to structural response is bulk density, subsequently the external prestress, internal prestress, pipe friction coefficient, and pipe deviation coefficient. Among them, the bulk density, internal prestress, and external prestress are all sensitive parameters, while pipe friction coefficient and pipe deviation coefficient are non-sensitive parameters.
Closed-Form Analytical Solutions for the Deflection of Elastic Beams in a Peridynamic Framework
Authors: Yang Zhenghao , Naumenko Konstantin , Ma Chien-Ching , Chen Yang
Published: September 2023

Peridynamics is a continuum theory that operates with non-local deformation measures as well as long-range internal force/moment interactions. The resulting equations are of the integral type, in contrast to the classical theory, which deals with differential equations. The aim of this paper is to analyze peridynamic governing equations for elastic beams. To this end, the strain energy density is formulated as a function of the non-local curvature. By applying the Lagrange principle, the peridynamic equations of motion are derived. Examples of non-local boundary conditions, including simple support, clamped edge, roller clamped edge, and free edge, are presented by introducing the interaction domain. Novel closed-form analytical solutions to integral equations are presented for beams with various boundary conditions, including clamped—simply supported, clamped–clamped, simply supported–roller-clamped, and clamped–roller-clamped beams. Furthermore, different types of loadings, including uniformly distributed load, concentrated force, and concentrated moment, are considered. The results are validated by comparing the derived solutions against solutions to the classical Bernoulli–Euler beam theory. A very good agreement between the non-local and the classical theories is observed for the case of the small horizon sizes, which shows the capability of the derived equations of motion and proposed boundary conditions.
Cancer Treatment: An Overview of Pulsed Electric Field Utilization and Generation
Authors: Alshahat Mahmoud A. , Elgenedy Mohamed A. , Aboushady Ahmed A. , Williams Mark T. S.
Published: September 2023

Patients diagnosed with cancer receive different types of treatments based on the type and the level of the tumour. An emerging treatment that differs from well-developed systematic therapies (i.e., Chemotherapy, Radiotherapy, and Immunotherapy) is Tumour Treating Field (TTF) treatment. Tumour behaviour under TTF treatment varies based on the electric field intensity; the process of exposing the tumour cells to an electric field is called electroporation. From the electrical perspective, the most efficient method for electroporation is to use a voltage pulse generator. Several pulse generator topologies have been introduced to overcome existing limitations, mitigate the drawbacks of classical generators, and provide more controllable, flexible, and portable solid-state voltage pulse generators. This paper provides a review of cancer treatment using TTF and highlights the key specifications required for efficient treatment. Additionally, potential voltage pulse generators are reviewed and compared in terms of their treatment efficacy and efficient use of electrical power.
Use of Carbon and Basalt Fibers with Adhesives to Improve Physical and Mechanical Properties of Laminated Veneer Lumber
Authors: Núñez-Decap Mario , Sandoval-Valderrama Bárbara , Opazo-Carlsson Camila , Moya-Rojas Boris , Vidal-Vega Marcela , Opazo-Vega Alexander
Published: September 2023

Climate change is one of the main factors influencing the research of environmentally friendly materials. This is why the use of engineering fibers as a reinforcement technique in wood, in order to increase its mechanical properties, has recently been investigated. This research presents the results obtained from the use of carbon and basalt fiber fabrics as a reinforcement for microlaminated Radiata Pine wood panels at a laboratory scale using the adhesives epoxy resin and polyvinyl acetate. Tests were carried out in comparison to the control boards, relating the physical properties obtained in terms of thickness swelling by 48 h-water immersion with a decrease of 19% for the polyvinyl acetate and carbon fiber matrix reinforcement, about the mechanical properties evaluated, a better performance was obtained for the epoxy resin and carbon fiber matrix reinforcement and in terms of flexural stiffness and strength (in flatwise), tensile strength and Janka hardness, with an increment of 31%, 38%, 56% and 41%, respectively.
Special Issue on Potentially Toxic Trace Elements in Contaminated Sites: Fate, Risk and Remediation
Authors: Pavoni Elena , Campanella Beatrice , Acquavita Alessandro
Published: September 2023

The occurrence of potentially toxic elements (PTEs, including As, Cd, Hg and Pb) of both anthropogenic and natural origin in the environment represents an issue of global concern, leading to a general decline in environmental quality in both continental and aquatic systems [...]
Synergistic Effect of Nonthermal Plasma and ZnO Nanoparticles on Organic Dye Degradation
Authors: Abdel-Fattah E. , Alotibi S.
Published: September 2023

The synergetic effect of nonthermal plasma and ZnO nanoparticles (NPs) on the degradation efficiency of methylene blue was investigated. First, the ZnO nanoparticles were synthesized via the hydrothermal route; the spherical nanoparticles had diameters of 30–50 nm, as observed with a scanning electron microscope (SEM), and had hexagonal ZnO lattice structures, which was confirmed by both X-ray diffraction (XRD) and Raman spectroscopy. The X-ray-photoemission spectroscopy confirmed the ZnO composition and the presence of oxygen vacancies; meanwhile, the optical band gap energy was 3.17 eV. The optical emission of plasma radiation confirmed the presence of various active plasma species. Second, it was found that the maximum degradation efficiency of MB after 60 min was 85% in plasma alone and increased to 95% when combined with 0.2 gL−1 ZnO; but this decreased to 75% when ZnO loading increased to 0.4 gL−1. These results clearly show that combining plasma with the right amount of ZnO is a promising advanced oxidation technique as it provides an additional source of hydroxyl radicals and, at the same time, a source of photons that can excite the ZnO catalyst. The degradation mechanism for plasma alone and the plasma in combination with ZnO was presented.
Improved Indoor Positioning Model Based on UWB/IMU Tight Combination with Double-Loop Cumulative Error Estimation
Authors: Zhu Wenjie , Zhao Rongyong , Zhang Hao , Lu Jianfeng , Zhang Zhishu , Wei Bingyu , Fan Yuhang
Published: September 2023

With the increasing applications of UWB indoor positioning technologies in industrial areas, to further enhance the positioning precision, the UWB/IMU combination method (UICM) has been considered as one of the most effective solutions to reduce non-line-of-sight (NLOS) errors. However, most conversional UICMs suffer from a high probability of positioning failure due to uncontrollable and cumulative errors from inertial measuring units (IMU). Hence, to address this issue, we improved the extended Kalman filter (EKF) algorithm of an indoor positioning model based on UWB/IMU tight combination with a double-loop error self-correction. Compared with conventional UICMs, this improved model consists of new modules for fixing time desynchronization, optimizing the threshold setting for UWB ranging, data fusion in NLOS, and double-loop error estimation, sequentially. Further, systematic error controllability analysis proved that the proposed model could satisfy the controllability of UWB indoor positioning systems. To validate this improved UICM, inevitable obstacles and atmospheric interferences were regarded as Gaussian white noises to verify its environmental adaptability. Finally, the experimental results showed that this proposed model outperformed the state-of-the-art UWB-based positioning models with a maximum deviation of 0.232 m (reduced by 83.93% compared to a pure UWB model and 43.14% compared to the conventional UWB/IMU model) and standard deviation of 0.09981 m (reduced by 88.35% compared to a pure UWB model and 22.21% compared to the conventional UWB-IMU model).
Antioxidant and Anti-Inflammatory Effects of Agarum cribrosum Extract and Its Fractions in LPS-Induced RAW 264.7 Macrophages
Authors: Kim Mi-Bo , Lee Hyeju , Vance Terrence , Lee Sang Gil
Published: September 2023

Excessive oxidative stress and chronic inflammation are implicated in the pathogenesis of chronic inflammation diseases. The purpose of this study was to determine whether the antioxidant and anti-inflammatory effects of Busan-grown Agarum cribrosum ethanol extract (ACE) and its organic solvent five fractions are exhibited in lipopolysaccharide (LPS)-stimulated RAW 264.7 macrophages. ACE and its five fractions from ACE evaluated the total antioxidant activity and the effect of pro-inflammatory cytokines and antioxidant genes expression in LPS-induced RAW 264.7 macrophages. ACE and its ethyl acetate (EtOAc) fraction showed a high total phenolic content and total antioxidant capacity by decreasing free radicals scavenging activity. ACE and its EtOAc fraction significantly repressed LPS-induced tumor necrosis factor α and interleukin-1β gene expression. Additionally, ACE and its EtOAc fraction significantly diminished the LPS-stimulated gene expression of inducible nitric oxide synthase and cyclooxygenase 2 genes with a concomitant decrease in their protein levels in the macrophages. The gene expression of NADPH oxidase 2 was significantly abolished by ACE and its EtOAc fraction in LPS-induced macrophages, while other antioxidant genes showed minimal effects. The results suggest that ACE and its EtOAc fraction exert inhibitory effects on LPS-stimulated inflammation and oxidative stress in macrophages accompanied by total antioxidant activity.
Quantitative Analysis of Coal Quality by a Portable Laser Induced Breakdown Spectroscopy and Three Chemometrics Methods
Authors: Dou Youquan , Wang Qingsong , Wang Sen , Shu Xi , Ni Minghui , Li Yan
Published: September 2023

Laser-induced breakdown spectroscopy (LIBS) technology has the characteristics of small sample demand, simple sample preparation, simultaneous measurement of multiple elements and safety, which has great potential application in the rapid detection of coal quality. In this paper, 59 kinds of coal commonly used in Chinese power plants were tested by a lab-designed field-portable laser-induced breakdown spectrometer. The data set division methods and the quantitative analysis algorithm of ash content, volatile matter and calorific value of coal samples were carried out. The accuracy and prediction accuracy of three kinds of dataset partitioning methods, random selection (RS), Kennard–Stone (KS) and sample partitioning based on joint X-Y distances (SPXY), coupled with three quantitative algorithms, partial least squares regression (PLS), support vector machine regression (SVR) and random forest (RF), were compared and analyzed in this paper. The results show that the model featuring SPXY combined with RF has the best prediction performance. The R2 of ash content by the RF and SPXY method is 0.9843, the RMSEP of ash content is 1.3303 and the mean relative error (MRE) is 7.47%. The R2 of volatile matter is 0.9801, RMSEP is 0.7843 and MRE is 2.19%. The R2 of calorific value is 0.9844, RMSEP is 0.7324 and MRE is 2.27%. This study demonstrates that the field-portable LIBS device combining appropriate chemometrics algorithms has a wide application prospect in the rapid analysis of coal quality.
Double-Constrained Consensus Clustering with Application to Online Anti-Counterfeiting
Authors: Carpineto Claudio , Romano Giovanni
Published: September 2023

Semi-supervised consensus clustering is a promising strategy to compensate for the subjectivity of clustering and its sensitivity to design factors, with various techniques being recently proposed to integrate domain knowledge and multiple clustering partitions. In this article, we present a new approach that makes double use of domain knowledge, namely to build the initial partitions, as well as to combine them. In particular, we show how to model and integrate must-link and cannot-link constraints into the objective function of a generic consensus clustering (CC) framework that maximizes the similarity between the consensus partition and the input partitions, which have, in turn, been enriched with the same constraints. In addition, borrowing from the theory of functional dependencies, the integrated framework exploits the notions of deductive closure and minimal cover to take full advantage of the logical implication between constraints. Using standard UCI benchmarks, we found that the resulting algorithm, termed CCC double-constrained consensus clustering), was more effective than plain CC at combining base-constrained partitions, with an average performance improvement of 5.54%. We then argue that CCC is especially well-suited for profiling counterfeit e-commerce websites, as constraints can be acquired by leveraging specific domain features, and demonstrate its potential for detecting affiliate marketing programs. Taken together, our experiments suggest that CCC makes the process of clustering more robust and able to withstand changes in clustering algorithms, datasets, and features, with a remarkable improvement in average performance.
Comparative Analysis of Urban Heat Island Cooling Strategies According to Spatial and Temporal Conditions Using Unmanned Aerial Vehicles(UAV) Observation
Authors: Cho Young-Il , Yoon Donghyeon , Lee Moung-Jin
Published: September 2023

Heat island cooling strategies (HICSs) are used to mitigate urban heat island phenomena and adapt to climate change as proposed by the U.S. Environmental Protection Agency (EPA), the Intergovernmental Panel on Climate Change (IPCC), and the World Health Organization (WHO). This study investigated urban heat island reduction and assessed the cooling effect of HICSs under various temporal and spatial conditions in urban areas. The study area was the Mugye-dong urban area in South Korea. To identify the effectiveness of heat island cooling strategies (HICSs), unmanned aerial vehicle (UAV)-based remote sensing and microclimate sensors were used to generate land cover, sky view factor (SVF) distribution, and land surface temperature (LST) maps of the study area. Differences in cooling effect according to spatial density (SD) were identified by dividing the SVF into five intervals of 0.2. Temporal changes were investigated throughout the day and under cloudiness-based meteorological conditions affected by solar radiation or less affected by solar radiation. Lower SD was associated with a greater cooling effect; meteorological conditions affected by solar radiation had a stronger cooling effect. The variation of the daytime cooling effect increased with decreasing SD. The difference in cooling effect between morning and afternoon was <1 °C under conditions less affected by solar radiation. Under conditions affected by solar radiation, the maximum temperatures were −6.716 °C in urban green spaces and −4.292 °C in shadow zones, whereas the maximum temperature was −6.814 °C in ground-based albedo modification zones; thus, differences were greater under conditions affected by solar radiation than under conditions less affected by solar radiation. As a result, it was found that HICS show a high cooling effect, high diurnal variation, and high morning-afternoon deviation under weather conditions with low SD and under conditions affected by solar radiation. This study quantitatively calculated the cooling effect of HICSs applied in urban areas under various spatiotemporal conditions and compared differences by technology. Accordingly, it is believed that it will serve as a basis for supporting the practical effects of the concepts presented by international organizations for climate change adaptation.
Research on Low-Frequency Oscillation Damping Control of Wind Storage System Based on Pareto and Improved Particle Swarm Algorithm
Authors: Song Yu , Wu Shouyuan
Published: September 2023

Aiming at the low-frequency oscillation problem of high-proportion wind power and energy storage connected to the power system, this paper establishes a system small signal model according to the matrix similarity theory, which lays a foundation for the research on oscillation characteristics, mechanism analysis, and suppression measures. Combined with the different installation positions of the inverter-side converter and the inverter-side POD (Power Oscillation Damper) controller of the energy storage device, the suppression mechanism and damping oscillation ability of the two on low-frequency oscillation were analyzed. Under multiple optimization objectives, the parameters of the damping controller are optimized by Pareto and improved particle swarm algorithms. Finally, through Matlab/Simulink simulation, the effectiveness of the Pareto and improved particle swarm algorithm in suppressing low-frequency oscillation of the system is verified.
A Biomedical Relation Extraction Method Based on Graph Convolutional Network with Dependency Information Fusion
Authors: Yang Wanli , Xing Linlin , Zhang Longbo , Cai Hongzhen , Guo Maozu
Published: September 2023

Biomedical texts are relatively obscure in describing relations between specialized entities, and the automatic extraction of drug–drug or drug–disease relations from massive biomedical texts presents a challenge faced by many researchers. To this end, this paper designs a relation extraction method based on dependency information fusion to improve the predictive power of the model for the relations between given biomedical entities. Firstly, we propose a local–global pruning strategy for the dependency syntax tree. Next, we propose the construction of a dependency type matrix for the pruned dependency tree to incorporate sentence dependency information into the model to feature extraction. We then incorporate attention mechanism into the graph convolutional model by calculating the attention weights of word–word dependencies, thus improving the traditional graph convolutional network. The model distinguishes the importance of different dependency information by attention weights, thus weakening the influence of interfering information such as word-to-word dependencies that are unrelated to entities in long sentences. In this paper, our proposed Dependency Information Fusion Attention Graph Convolutional Network (DIF-A-GCN) is evaluated on two biomedical datasets, DDI and CIVIC. The experimental results show that our proposed method based on dependency information fusion outperforms current state-of-the-art biomedical relation extraction models.
Path Planning for Autonomous Vehicles in Unknown Dynamic Environment Based on Deep Reinforcement Learning
Authors: Hu Hui , Wang Yuge , Tong Wenjie , Zhao Jiao , Gu Yulei
Published: September 2023

Autonomous vehicles can reduce labor power during cargo transportation, and then improve transportation efficiency, for example, the automated guided vehicle (AGV) in the warehouse can improve the operation efficiency. To overcome the limitations of traditional path planning algorithms in unknown environments, such as reliance on high-precision maps, lack of generalization ability, and obstacle avoidance capability, this study focuses on investigating the Deep Q-Network and its derivative algorithm to enhance network and algorithm structures. A new algorithm named APF-D3QNPER is proposed, which combines the action output method of artificial potential field (APF) with the Dueling Double Deep Q Network algorithm, and experience sample rewards are considered in the experience playback portion of the traditional Deep Reinforcement Learning (DRL) algorithm, which enhances the convergence ability of the traditional DRL algorithm. A long short-term memory (LSTM) network is added to the state feature extraction network part to improve its adaptability in unknown environments and enhance its spatiotemporal sensitivity to the environment. The APF-D3QNPER algorithm is compared with mainstream deep reinforcement learning algorithms and traditional path planning algorithms using a robot operating system and the Gazebo simulation platform by conducting experiments. The results demonstrate that the APF-D3QNPER algorithm exhibits excellent generalization abilities in the simulation environment, and the convergence speed, the loss value, the path planning time, and the path planning length of the APF-D3QNPER algorithm are all less than for other algorithms in diverse scenarios.
Fatty Acid Profile, Atherogenic and Thrombogenic Indices, and Meat Quality as the Effect of Feed Additive in African Catfish Clarias gariepinus (Burchell, 1822)
Authors: Bušová Milena , Kouřimská Lenka , Doležal Marek , Ilko Vojtech , Revenco Diomid , Zare Mahyar , Matoušek Jan , Ferrocino Ilario , Franciosa Irene , Smejkal Petr , Přeslička Matěj , Prokešová Markéta
Published: September 2023

Humic substances (HS) are often used as feesd additives in livestock feeding. The long-term effects of different concentrations of HS additives in aquafeed on growth and production performance, antioxidant status, stress resistance, gut microbiome, overall health condition, final product yield, sensory properties of fresh and cooked meat, and composition of fatty acids of market size in African catfish (Clarias gariepinus) originating from aquaculture were compared in this study. C. gariepinus were exposed to dietary inclusions of HS (0, 1, and 3, and 6% w/w) in a long-term experiment (six months in total) until fish reached market size. The growth parameters, condition factor, and selected somatic indices did not differ (p > 0.05) between the tested groups (HS0–HS6). Biochemical parameters were not different between the tested HS groups by the end of experiment, and only glucose (GLC) levels significantly increased (p < 0.05) with increasing concentrations of HS fed as an additive. The levels of cortisol (COR) and GLC did not differ between the tested groups (p > 0.05) after the stress challenge, but the results of GLC levels before and after the stress challenge showed an increasing tendency with increasing levels of HS addition in the diet. The levels of COR were slightly lower in groups HS3 and HS6 than in HS1 and the control group. In the case of protein and fat contents, differences between groups (HS0–HS6) were statistically insignificant. Significant differences were found, however, in water and ash content. In some cases, statistically significant differences were found in fatty acid profiles and in nutritional indices assessing fatty acids between samples. Sensory characteristics of fresh fillets did not differ between the tested groups HS0–HS6. The total content of polyphenols increased depending on the addition of humates. The main gut microbiota of samples analyzed (HS0–HS3 group) comprised the following three genera: Ralstonia, Pseudomonas and Cetobacterium; other genera were present in all samples at a low relative abundance: Staphylococcus, Bradyrhizobium, Bacillus, and Anaerobacillus. The relative abundance of Pseudomonas decreased while the presence of Cetobacterium increased in samples fed with 3% of HS. The results of our study yielded a comprehensive set of experimental results about African catfish fed with HS as additives. Although a significant effect of HS on overall performance of C. gariepinus was not proven, a positive effect on antioxidant status was seen as well as a decrease in gut microorganisms that can be present as pathogenic contaminants in aquatic environments.
WASPAS Based Multi Response Optimization in Hard Turning of AISI 52100 Steel under ZnO Nanofluid Assisted Dual Nozzle Pulse-MQL Environment
Authors: Khatai Saswat , Kumar Ramanuj , Panda Amlana , Sahoo Ashok Kumar
Published: September 2023

Hard turning is an emerging machining technology that evolved as a substitute for grinding in the production of precision parts from hardened steel. It offers advantages such as reduced cycle times, lower costs, and environmental benefits over grinding. Hard turning is stated to be difficult because of the high hardness of the workpiece material, which causes higher tool wear, cutting temperature, surface roughness, and cutting force. In this work, a dual-nozzle minimum quantity lubrication (MQL) system’s performance assessment of ZnO nano-cutting fluid in the hard turning of AISI 52100 bearing steel is examined. The objective is to evaluate the ZnO nano-cutting fluid’s impacts on flank wear, surface roughness, cutting temperature, cutting power consumption, and cutting noise. The tool flank wear was traced to be very low (0.027 mm to 0.095 mm) as per the hard turning concern. Additionally, the data acquired are statistically analyzed using main effects plots, interaction plots, and analysis of variance (ANOVA). Moreover, a novel Weighted Aggregated Sum Product Assessment (WASPAS) optimization tool was implemented to select the optimal combination of input parameters. The following optimal input variables were found: depth of cut = 0.3 mm, feed = 0.05 mm/rev, cutting speed = 210 m/min, and flow rate = 50 mL/hr.
Development of a 7-DOF Biodynamic Model for a Seated Human and a Hybrid Optimization Method for Estimating Human-Seat Interaction Parameters
Authors: Alabi Abeeb Opeyemi , Song Byoung-Gyu , Bae Jong-Jin , Kang Namcheol
Published: September 2023

Existing biodynamic models adopt apparent mass and seat-to-head transmissibility to predict the response of seated humans to whole-body vibration, limiting their ability to capture the actual response of distinct body segments in different excitation conditions. This study systematically develops a 7-DOF seated human model, a vibration experiment, and a novel hybrid optimization to estimate unknown mechanical parameters and predict the response of different human body segments to vertical vibrations. Experimental results showed that the upper trunk and head were most susceptible to transmitted vibrations. Combining the 7-DOF model and HOM resulted in accelerated optimization, improved numerical stability, and significant minimization of the objective function value compared to conventional algorithms. Notably, the estimated parameters, particularly stiffness, remained consistent regardless of increasing excitation magnitude or change in the body segment data used. Additionally, the model captured the non-linearity in human biodynamics through stiffness softening. These findings are applicable in seating systems optimization for comfort and safety.
MixerNet-SAGA A Novel Deep Learning Architecture for Superior Road Extraction in High-Resolution Remote Sensing Imagery
Authors: Wu Wei , Ren Chao , Yin Anchao , Zhang Xudong
Published: September 2023

In this study, we address the limitations of current deep learning models in road extraction tasks from remote sensing imagery. We introduce MixerNet-SAGA, a novel deep learning model that incorporates the strengths of U-Net, integrates a ConvMixer block for enhanced feature extraction, and includes a Scaled Attention Gate (SAG) for augmented spatial attention. Experimental validation on the Massachusetts road dataset and the DeepGlobe road dataset demonstrates that MixerNet-SAGA achieves a 10% improvement in precision, 8% in recall, and 12% in IoU compared to leading models such as U-Net, ResNet, and SDUNet. Furthermore, our model excels in computational efficiency, being 20% faster, and has a smaller model size. Notably, MixerNet-SAGA shows exceptional robustness against challenges such as same-spectrum–different-object and different-spectrum–same-object phenomena. Ablation studies further reveal the critical roles of the ConvMixer block and SAG. Despite its strengths, the model’s scalability to extremely large datasets remains an area for future investigation. Collectively, MixerNet-SAGA offers an efficient and accurate solution for road extraction in remote sensing imagery and presents significant potential for broader applications.
Contextual Explanations for Decision Support in Predictive Maintenance
Authors: Kozielski Michał
Published: September 2023

Explainable artificial intelligence (XAI) methods aim to explain to the user on what basis the model makes decisions. Unfortunately, general-purpose approaches that are independent of the types of data, model used and the level of sophistication of the user are not always able to make model decisions more comprehensible. An example of such a problem, which is considered in this paper, is a predictive maintenance task where a model identifying outliers in time series is applied. Typical explanations of the model’s decisions, which present the importance of the attributes, are not sufficient to support the user for such a task. Within the framework of this work, a visualisation and analysis of the context of local explanations presenting attribute importance are proposed. Two types of context for explanations are considered: local and global. They extend the information provided by typical explanations and offer the user greater insight into the validity of the alarms triggered by the model. Evaluation of the proposed context was performed on two time series representations: basic and extended. For the extended representation, an aggregation of explanations was used to make them more intuitive for the user. The results show the usefulness of the proposed context, particularly for the basic data representation. However, for the extended representation, the aggregation of explanations used is sometimes insufficient to provide a clear explanatory context. Therefore, the explanation using simplification with a surrogate model on basic data representation was proposed as a solution. The obtained results can be valuable for developers of decision support systems for predictive maintenance.
Two Scenario-Based Heuristics for Stochastic Shift Design Problem with Task-Based Demand
Authors: Wu Zhiying , Chen Qingxin , Mao Ning , Xu Guoning
Published: September 2023

In this paper, we propose a deterministic shift design model with task-based demand and give the corresponding stochastic version with a probability constraint such that the shift plan designed is staffed with the workforce with a certain probability of performing all given tasks. Since we currently find no suitable methods for solving this stochastic model from the literature related to solving stochastic shift design models, we developed a single-stage heuristic method based on statistics, whose main idea is to reduce the occurrence of manpower shortage by prolonging the resource occupation time of a task, but this leads to a serious waste of resources, which is common in solving resource allocation problems with uncertain durations. To reduce the cost of wastage, we also propose a two-stage heuristic approach that is a two-stage heuristic with an evolutionary strategy. The two heuristics show their effectiveness in solving the proposed stochastic model in numerical experiments, and the two-stage heuristic significantly outperforms the one-stage heuristic in cost optimization and solution time stability.