bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting Treatment Outcomes in Patients with Drug-Resistant Tuberculosis and Human Immunodeficiency Virus Coinfection, Using Supervised Machine Learning Algorithm
Authors: Hosu Mojisola Clara , Faye Lindiwe Modest , Apalata Teke
Published: October 2024

Drug-resistant tuberculosis (DR-TB) and HIV coinfection present a conundrum to public health globally and the achievement of the global END TB strategy in 2035. A descriptive, retrospective review of medical records of patients, who were diagnosed with DR-TB and received treatment, was conducted. Student’s t-test was performed to assess differences between two means and ANOVA between groups. The Chi-square test with or without trend or Fischer’s exact test was used to test the degree of association of categorical variables. Logistic regression was used to determine predictors of DR-TB treatment outcomes. A decision tree classifier, which is a supervised machine learning algorithm, was also used. Python version 3.8. and R version 4.1.1 software were used for data analysis. A p-value of 0.05 with a 95% confidence interval (CI) was used to determine statistical significance. A total of 456 DR-TB patients were included in the study, with more male patients (n = 256, 56.1%) than female patients (n = 200, 43.9%). The overall treatment success rate was 61.4%. There was a significant decrease in the % of patients cured during the COVID-19 pandemic compared to the pre-pandemic period. Our findings showed that machine learning can be used to predict TB patients’ treatment outcomes.
Virtual Screening, Molecular Dynamics, and Mechanism Study of Homeodomain-Interacting Protein Kinase 2 Inhibitor in Renal Fibroblasts
Authors: Hu Xinlan , Wu Yan , Ouyang Hanyi , Wu Jiayan , Yao Mengmeng , Chen Zhuo , Li Qianbin
Published: October 2024

Background/Objectives: Homeodomain-interacting protein kinase 2 (HIPK2) is critically involved in the progression of renal fibrosis. This study aims to identify and characterize a novel HIPK2 inhibitor, CHR-6494, and investigate its therapeutic potential. Methods: Using structure-based virtual screening and molecular dynamics simulations, we identified CHR-6494 as a potent HIPK2 inhibitor with an IC50 of 0.97 μM. The effects of CHR-6494 on the phosphorylation of p53 in Normal Rattus norvegicus kidney cells (NRK-49F) induced by transforming growth factor-β (TGF-β) were assessed, along with its impact on TGF-β signaling and downstream profibrotic markers. Results: CHR-6494 significantly reduces p53 phosphorylation induced by TGF-β and enhances the interaction between HIPK2 and seven in absentia 2 (SIAH2), facilitating HIPK2 degradation via proteasomal pathways. Both CHR-6494 and Abemaciclib inhibit NRK-49F cell proliferation and migration induced by TGF-β, suppressing TGF-β/Smad3 signaling and decreasing profibrotic markers such as Fibronectin I (FN-I) Collagen I and α-smooth muscle actin (α-SMA). Additionally, these compounds inhibit nuclear factor kappa-B (NF-κB) signaling and reduce inflammatory cytokine expression. Conclusions: The study highlights the dual functionality of HIPK2 kinase inhibitors like CHR-6494 and Abemaciclib as promising therapeutic candidates for renal fibrosis and inflammation. The findings provide new insights into HIPK2 inhibition mechanisms and suggest pathways for the design of novel HIPK2 inhibitors in the future.
Preparation and Characterization of Hydrophobin 4-Coated Liposomes for Doxorubicin Delivery to Cancer Cells
Authors: Osmanagaoglu Fatma Hande , Ekmekcioglu Aysegul , Ozcan Busel , Bayram Akcapinar Gunseli , Muftuoglu Meltem
Published: October 2024

Background: The properties of nanoparticle surfaces are crucial in influencing their interaction with biological environments, as well as their stability, biocompatibility, targeting abilities, and cellular uptake. Hydrophobin 4 (HFB4) is a class II HFB protein produced by filamentous fungi that has a natural ability to self-assemble at hydrophobic-hydrophilic interfaces. The biocompatible, non-toxic, biodegradable, and amphipathic properties of HFB4 render it valuable for improving the solubility and bioavailability of hydrophobic drugs. We have investigated the physicochemical properties, cellular uptake, and anticancer effects of empty and Doxorubicin (Dox)-loaded HFB4 liposomes (HFB4L) and compared them to those of PEGylated liposomes (PPL). Methods: The Pichia pastoris KM71H strain was used for HFB4 purification. Liposomes were prepared through the thin film hydration method and characterized. The cytotoxic effects of free Dox, Dox-HFB4, and Dox-PPL were assessed in MCF7 cells using the SRB Assay. Results: All formulations showed good size homogeneity and a spherical shape. The HFB4 coating enhanced the physicochemical stability of Dox-HFB4L over 60 days at 4 °C without significantly affecting Dox release from HFB4L. It increased Dox release at pH 5.4 compared to pH 7.4, indicating higher delivery of drugs into acidic tumor environments, similar to Dox-PPL. While both formulations showed increased cellular uptake compared to free Dox, they exhibited a lower anticancer effect due to the sustained release of Dox. Notably, Dox-HFB4L displayed greater cytotoxicity than Dox-PPL in MCF7 cells. Conclusions: HFB4L may offer superior benefits in terms of delivering drugs to an acidic tumor environment in a stable, non-toxic, and sustained manner.
Salvia miltiorrhiza and Its Compounds as Complementary Therapy for Dyslipidemia: A Meta-Analysis of Clinical Efficacy and In Silico Mechanistic Insights
Authors: Lee Min-Seong , Lee Han-Young , Oh Seung-Hyun , Kim Chang-Bum , Kim Ji-Han , Yoo Seung-Hoon , Yoo Yeon-Joo , Lee Su-Yeon , Lee Byung-Cheol
Published: October 2024

Background/Objectives: Dyslipidemia is a significant risk factor for atherosclerotic cardiovascular disease (ASCVD), a leading cause of death worldwide. Salvia miltiorrhiza Burge is widely used in East Asia for cardiovascular health, showing potential benefits in lowering cholesterol and reducing inflammation. Methods: This study systematically reviewed and conducted a meta-analysis of randomized controlled trials (RCTs) to assess the clinical effectiveness of Salvia miltiorrhiza in treating dyslipidemia. Moreover, network pharmacology and molecular docking analyses were performed to explore the mechanisms underlying the effects of Salvia miltiorrhiza. Results: The meta-analysis revealed that when Salvia miltiorrhiza is combined with statin therapy, it significantly enhances lipid profiles, including reductions in total cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglycerides and improvements in high-density lipoprotein cholesterol (HDL-C), compared to statin therapy alone. The in silico analyses indicated that Salvia miltiorrhiza may influence key biological pathways, such as the PI3K/Akt, JAK/STAT, and HMGCR pathways, which are involved in inflammation, lipid metabolism, and the development of atherosclerosis. Conclusions: Salvia miltiorrhiza shows potential as a complementary therapy for dyslipidemia, offering additional lipid-lowering and anti-inflammatory benefits.
Can Pharmacovigilance Data Represent a Potential Tool for Early Detection of the Antibiotic Resistance Phenomenon?
Authors: Cagnotta Cecilia , Zinzi Alessia , Gargano Francesca , Liguori Valerio , Campitiello Maria Rosaria , Perrella Alessandro , Capuano Annalisa , Rafaniello Concetta , Trama Ugo
Published: October 2024

Background: Antibiotic resistance represents a growing concern. A new strategy developed to treat severe infections is represented by ceftazidime/avibactam (CZA/AVI). Despite the promising activities against more pathogens, continuous monitoring is required to identify potential antibiotic resistance in clinical practice settings. Therefore, real-world data from pharmacovigilance databases can help to better define the safety profile. Methods: We analyzed all Individual Case Safety Reports (ICSRs) collected in the EudraVigilance database focusing on ICSRs with at least one adverse event (AE) potentially suggestive of drug resistance (DR) and drug ineffectiveness (DI). Results: A total of 654 ICSRs related to CZA/AVI were retrieved from EudraVigilance, of which N = 378 (57.8%) were related to male and N = 230 (35.1%) to adult patients. A total of 80.2% of all AEs were serious but with a positive outcome. Overall, we found N = 129 (19.7%) cases of potential DR or DI after CZA/AVI administration. The majority of CZA/AVI-induced DR or DI occurred in adult male patients. The most frequently reported AEs were “drug ineffective” and “pathogen resistance”. Lastly, CZA/AVI was mostly used for the treatment of “Klebsiella infection” and “Pneumonia”. Conclusions: The present study showed how pharmacovigilance could play a key role in generating evidence about the safety profile of CZA/AVI. Further studies are warranted.
Display Field Communication: Enabling Seamless Data Exchange in Screen–Camera Environments
Authors: Singh Pankaj , Kim Yu-Jeong , Kim Byung Wook , Jung Sung-Yoon
Published: October 2024

Display field communication (DFC) is an emerging technology that enables seamless communication between electronic displays and cameras. It utilizes the frequency-domain characteristics of image frames to embed and transmit data, which are then decoded and interpreted by a camera. DFC offers a novel solution for screen-to-camera data communication, leveraging existing displays and camera infrastructures. This makes it a cost-effective and easily deployable solution. DFC can be applied in various fields, including secure data transfer, mobile payments, and interactive advertising, where data can be exchanged by simply pointing a camera at a screen. This article provides a comprehensive survey of DFC, highlighting significant milestones achieved in recent years and discussing future challenges in establishing a fully functional DFC system. We begin by introducing the broader topic of screen–camera communication (SCC), classifying it into visible and hidden SCC. DFC, a type of spectral-domain hidden SCC, is then explored in detail. Various DFC variants are introduced, with a focus on the physical layer. Finally, we present promising experimental results from our lab and outline further research directions and challenges.
One-Second Touchscreen Disinfection with Internal UVC-LEDs
Authors: Noller Kilian , Sicks Ben , Hessling Martin
Published: October 2024

The transmission of pathogens via touchscreens is a concern both in medical environments regarding nosocomial infections and in public spaces. This study presents the development of a self-disinfecting touchscreen system and its implementation into an existing medical device. The disinfection was achieved by irradiating UVC light laterally into the quartz front glass of the touchscreen. The system also included a two-stage safety shutdown feature to protect users from UVC exposure. To detect the presence of the user’s hand, a proximity sensor behind the front glass of the touch screen was installed in combination with touch input registration. A rapid disinfection of staphylococci was achieved without compromising usability and user safety. The prototype demonstrated a bacterial reduction of 99.96% or 3.4 (±0.36) log levels in less than 1 s. The results suggest that the technology has the potential to make a significant contribution to reducing the transmission of infections in healthcare settings and beyond.
Absorber-Free Mode-Locking of a Hybrid Integrated Diode Laser at Sub-GHz Repetition Rate
Authors: Memon Anzal , van Rees Albert , Mak Jesse , Fan Youwen , van der Slot Peter J. M. , Bastiaens Hubertus M. J. , Boller Klaus-Jochen
Published: October 2024

We demonstrate absorber-free passive and hybrid mode-locking at sub-GHz repetition rates, using a hybrid integrated extended cavity diode laser operating near 1550 nm. The laser is based on InP as a gain medium and a Si3N4 waveguide feedback circuit. Absorber-free Fourier domain mode-locking with ≈15 comb lines at around 0.2 mW total power is achieved with repetition rates around 500 MHz, using three highly frequency-selective micro-ring resonators that extend the on-chip cavity length to 0.6 m. To stabilize the repetition rate, hybrid mode-locking is demonstrated by weak RF modulation of the diode current. The RF injection reduces the Lorentzian linewidth component from 8.9 kHz to a detection-limited value of around 300 mHz. To measure the locking range of the repetition rate, the injected RF frequency is tuned with regard to the passive mode-locking frequency and the injected RF power is varied. The locking range increases approximately as a square-root function of the injected RF power. At 1 mW injection, a wide locking range of about 80 MHz is obtained. We also observe the laser maintaining stable mode-locking when the DC diode pump current is increased from 40 mA to 190 mA, provided that the cavity length is maintained constant with thermo-refractive tuning.
Unleashing the Potential of CRISPR/Cas9 Genome Editing for Yield-Related Traits in Rice
Authors: Thiruppathi Archana , Salunkhe Shubham Rajaram , Ramasamy Shobica Priya , Palaniswamy Rakshana , Rajagopalan Veera Ranjani , Rathnasamy Sakthi Ambothi , Alagarswamy Senthil , Swaminathan Manonmani , Manickam Sudha , Muthurajan Raveendran
Published: October 2024

Strategies to enhance rice productivity in response to global demand have been the paramount focus of breeders worldwide. Multiple factors, including agronomical traits such as plant architecture and grain formation and physiological traits such as photosynthetic efficiency and NUE (nitrogen use efficiency), as well as factors such as phytohormone perception and homeostasis and transcriptional regulation, indirectly influence rice grain yield. Advances in genetic analysis methodologies and functional genomics, numerous genes, QTLs (Quantitative Trait Loci), and SNPs (Single-Nucleotide Polymorphisms), linked to yield traits, have been identified and analyzed in rice. Genome editing allows for the targeted modification of identified genes to create novel mutations in rice, avoiding the unintended mutations often caused by random mutagenesis. Genome editing technologies, notably the CRISPR/Cas9 system, present a promising tool to generate precise and rapid modifications in the plant genome. Advancements in CRISPR have further enabled researchers to modify a larger number of genes with higher efficiency. This paper reviews recent research on genome editing of yield-related genes in rice, discusses available gene editing tools, and highlights their potential to expedite rice breeding programs.
High-Energy Density Pure Polyvinylidene Difluoride with the Magnetic Field Modulation of Free-Volume Pore Size and Other Microstructures
Authors: Liu Zhaoting , Qiao Jiale , Liu Chao , Qiao Shuotong
Published: October 2024

PVDF polymer dielectrics, renowned for their ultra-high-power density, ultra-fast response times, remarkable toughness, and lightweight properties, constitute the essential material foundation for the development of dielectric capacitors. Nevertheless, the low-energy density of these dielectrics presents a challenge to the advancement of dielectric capacitors. In this paper, in the process of preparing monolayer pure PVDF dielectric films by the solution casting method, a fixed-direction magnetic field and a rotating magnetic field were introduced in the horizontal direction, respectively, and this investigation explores the impact of magnetic field modulation on the polymer films’ free-volume pore size, grain size, phase structure, dielectric properties, and energy storage capabilities by altering the duration and orientation of the magnetic field’s influence. This study also discusses how microscopic alterations, particularly in the free-volume pore size, affect the macroscopic dielectric properties. Polymer films treated with a magnetic field of constant orientation for 3 min were obtained with the smallest free-volume hole size of 2.91 Å, the highest γ-phase contents of 54.8%, the smallest grain size of 68 Å, the largest electrical displacement of 10.64 and a very high discharge energy density of 12.68 J/cm3 (a 200% enhancement over pure PVDF).
Effect of Material and Structure of Ultra-High-Molecular-Weight Polyethylene Body Armor on Ballistic Limit Velocity: Numerical Simulation
Authors: Bian Jiang , Dai Kaida , Lv Xiaojiang , Huang Zilu , Wu Guangrun , Zhang Yuan
Published: October 2024

The material properties and structural characteristics of ballistic composites are crucial to their ballistic performance. A numerical model of a 1.1 g FSP penetrating a UHMWPE target plate was established in this paper. The numerical results show that the failure process of the body armor target plate primarily involves shear failure, interlayer delamination, and tensile failure. Based on this, further research was conducted on the influence of material properties and structural characteristics on the ballistic limit velocity of the UHMWPE armor plate. Furthermore, the study evaluates the effects of elastic modulus, tensile strength, shear strength, number of layers, and interlayer strength on the ballistic limit velocity of UHMWPE body armor. The findings reveal that the ballistic limit velocity is most sensitive to changes in shear strength, with variation rates ranging from −18% to +11%, showing an approximate positive correlation, while the elastic modulus has the smallest impact on ballistic limit velocity, with variation rates ranging from −2% to +4%. Additionally, appropriate interlayer strength can improve the ballistic limit velocity of the body armor to a certain extent. This study provides theoretical methods and recommendations for optimizing anti-penetration performance of UHMWPE body armor.
Active Polymer Films with Olive Leaf Extract: Potential for Food Packaging, Biomedical, and Cosmetic Applications
Authors: Grabska-Zielińska Sylwia
Published: October 2024

This review paper highlights the latest advancements in polymer films modified with olive leaf extract (OLE) for various applications, particularly in food packaging. The overview is focused on the preparation, properties, and multifunctionality of OLE-enhanced polymer materials. Olive leaf extract, known for its antibacterial, antifungal, and antioxidant properties, is also shown to enhance the physicochemical characteristics of polymer films. This review consolidates current knowledge on using OLE as a bioactive additive in polymer-based packaging materials, improving their structural integrity and functionality. In addition to food packaging, the review explores other applications of OLE-modified polymer films in industries such as biomedicine, pharmaceuticals, and cosmetics. The paper also addresses future perspectives in polymer food packaging, suggesting that OLE-modified films offer significant potential for industrial and academic research due to their enhanced properties. Overall, this review provides a comprehensive overview of the role of olive leaf extract in improving the performance of polymer films in diverse fields.
Study on the Effect of an Alternate Injection Pattern of Proppant on Hydraulic Fracture Closure Morphology
Authors: Wang Xiang , Chen Fuhu , Zhu Xinchun , Fang Yanjun , Hu Aiguo , Nie Fajian
Published: October 2024

In previous studies of the transportation of proppants within fractures and the morphology of proppant-supported fractures, researchers have generally treated the fractures as static and have overlooked the interactions between fractures and the proppant during the dynamic closure caused by filtration. To address this limitation, we propose a semi-implicit method to calculate the complete fluid–structure interaction equations for the fracture, fluid, and proppant. The results show that there are three types of closed fracture patterns formed by alternate proppant injection at the end of filtration loss, and the third pattern of fracture formed by injecting small particles first and then large particles has the best support length and filling effect. More effects of the particle size and injection pattern of the injected proppant on the fracture closure pattern after the end of filtration loss are shown graphically and analyzed in detail.
The Investigation of Overflow Water-Powered Projectile-Assisted Injection Molded Short-Glass-Fiber-Reinforced Polypropylene
Authors: Zhang Wei , Wang Mao-Zeng , Kuang Tang-Qing , Liao Qian-Sheng , Jiang Shi-Yu , Liu He-Sheng
Published: October 2024

Water-powered projectile-assisted injection molding (W-PAIM) is a novel injection molding technology that has been recently developed based on the ripe water-assisted injection molding (WAIM). Fiber orientation pattern and residual wall thickness (RWT) are two crucial factors determining the quality of W-PAIM parts composed of short fiber-reinforced thermoplastics (SFRTCs). However, limited work has been conducted on W-PAIM of SFRTC parts, which restricts its application process. In this work, an intensive investigation of W-PAIM parts composed of short fiber-reinforced polypropylene was conducted via a newly lab-developed W-PAIM platform. The results indicated that fibers were quite well oriented in the region extending from the core zone to the water channel, especially in the water channel zone, but randomly aligned in a small region near the mold wall. Nevertheless, fibers in the water channel zone of W-PAIM part were highly oriented, presenting an opposite alignment trend in fiber orientation compared to that in the water channel zone of the WAIM part as reported earlier. These disparities in fiber orientation between W-PAIM and WAIM parts were primarily attributed to the strong flow fields generated by projectile penetration. Additionally, the influence of three main processing parameters that significantly affected the projectile penetration on these two crucial factors was also investigated using the single-factor method. It was discovered that water injection delay time constituted the primary factor affecting the projectile penetration process, and reducing this time could greatly increase the relative thickness of the ordered area and the uniformity of RWT. More importantly, within the value range of the tested processing parameters, increased water pressure, elevated melt temperatures, and shorter water injection delay time could simultaneously improve fiber orientation and the uniformity of RWT in W-PAIM parts, which may improve the properties of W-PAIM parts and enlarge their application scope. This work provides a comprehensive guide for the fabrication of W-PAIM parts of SFRTCs.
A Comparison of Financial Risk-Tolerance Assessment Methods in Predicting Subsequent Risk Tolerance and Future Portfolio Choices
Authors: Kwak Eun Jin , Grable John E.
Published: October 2024

This study explores the effectiveness of various methods for measuring risk tolerance, with the aim to better understand the risk-taking attitudes and behaviors of financial decision-makers. Using data collected between October 2020 and March 2021, the research investigates three key areas: (a) the stability of risk tolerance over a six-month period, (b) the individual and household characteristics that predict future risk tolerance, and (c) the predictive accuracy of various risk-tolerance assessment methods in relation to portfolio choices made by financial decision-makers. The results show that risk-tolerance scores derived from a psychometrically developed scale provide the most accurate insights into future risk-taking attitudes and portfolio decisions. For those looking for a simple way to assess both current and future risk tolerance and portfolio choices, a stated-preference item can be effective. Although less consistent, a revealed-preference test can also be used to predict risk tolerance and risk-taking behavior. Findings provide guidance for financial decision-makers and financial advisors by comparing the key features of the three primary risk-tolerance assessment methods evaluated in this study. The study also establishes a foundational basis for selecting the most appropriate evaluation approach, based on the variables identified in the findings.
MBFE-UNet: A Multi-Branch Feature Extraction UNet with Temporal Cross Attention for Radar Echo Extrapolation
Authors: Geng Huantong , Zhao Han , Shi Zhanpeng , Wu Fangli , Geng Liangchao , Ma Kefei
Published: October 2024

Radar echo extrapolation is a critical technique for short-term weather forecasting. Timely warnings of severe convective weather events can be provided according to the extrapolated images. However, traditional echo extrapolation methods fail to fully utilize historical radar echo data, resulting in limited accuracy for future radar echo prediction. Existing deep learning echo extrapolation methods often face issues such as high-threshold echo attenuation and blurring distortion. In this paper, we propose a UNet-based multi-branch feature extraction model named MBFE-UNet for radar echo extrapolation to mitigate these issues. We design a Multi-Branch Feature Extraction Block, which extracts spatiotemporal features of radar echo data from various perspectives. Additionally, we introduce a Temporal Cross Attention Fusion Unit to model the temporal correlation between features from different network layers, which helps the model to better capture the temporal evolution patterns of radar echoes. Experimental results indicate that, compared to the Transformer-based Rainformer, the MBFE-UNet achieves an average increase of 4.8% in the critical success index (CSI), 5.5% in the probability of detection (POD), and 3.8% in the Heidke skill score (HSS).
Review on Hardware Devices and Software Techniques Enabling Neural Network Inference Onboard Satellites
Authors: Diana Lorenzo , Dini Pierpaolo
Published: October 2024

Neural networks (NNs) have proven their ability to deal with many computer vision tasks, including image-based remote sensing such as the identification and segmentation of hyperspectral images captured by satellites. Often, NNs run on a ground system upon receiving the data from the satellite. On the one hand, this approach introduces a considerable latency due to the time needed to transmit the satellite-borne images to the ground station. On the other hand, it allows the employment of computationally intensive NNs to analyze the received data. Low-budget missions, e.g., CubeSat missions, have computation capability and power consumption requirements that may prevent the deployment of complex NNs onboard satellites. These factors represent a limitation for applications that may benefit from a low-latency response, e.g., wildfire detection, oil spill identification, etc. To address this problem, in the last few years, some missions have started adopting NN accelerators to reduce the power consumption and the inference time of NNs deployed onboard satellites. Additionally, the harsh space environment, including radiation, poses significant challenges to the reliability and longevity of onboard hardware. In this review, we will show which hardware accelerators, both from industry and academia, have been found suitable for onboard NN acceleration and the main software techniques aimed at reducing the computational requirements of NNs when addressing low-power scenarios.
Dexterous Manipulation Based on Object Recognition and Accurate Pose Estimation Using RGB-D Data
Authors: Manawadu Udaka A. , Keitaro Naruse
Published: October 2024

This study presents an integrated system for object recognition, six-degrees-of-freedom pose estimation, and dexterous manipulation using a JACO robotic arm with an Intel RealSense D435 camera. This system is designed to automate the manipulation of industrial valves by capturing point clouds (PCs) from multiple perspectives to improve the accuracy of pose estimation. The object recognition module includes scene segmentation, geometric primitives recognition, model recognition, and a color-based clustering and integration approach enhanced by a dynamic cluster merging algorithm. Pose estimation is achieved using the random sample consensus algorithm, which predicts position and orientation. The system was tested within a 60° field of view, which extended in all directions in front of the object. The experimental results show that the system performs reliably within acceptable error thresholds for both position and orientation when the objects are within a ±15° range of the camera’s direct view. However, errors increased with more extreme object orientations and distances, particularly when estimating the orientation of ball valves. A zone-based dexterous manipulation strategy was developed to overcome these challenges, where the system adjusts the camera position for optimal conditions. This approach mitigates larger errors in difficult scenarios, enhancing overall system reliability. The key contributions of this research include a novel method for improving object recognition and pose estimation, a technique for increasing the accuracy of pose estimation, and the development of a robot motion model for dexterous manipulation in industrial settings.
MPSA-Conformer-CTC/Attention: A High-Accuracy, Low-Complexity End-to-End Approach for Tibetan Speech Recognition
Authors: Wu Changlin , Sun Huihui , Huang Kaifeng , Wu Long
Published: October 2024

This study addresses the challenges of low accuracy and high computational demands in Tibetan speech recognition by investigating the application of end-to-end networks. We propose a decoding strategy that integrates Connectionist Temporal Classification (CTC) and Attention mechanisms, capitalizing on the benefits of automatic alignment and attention weight extraction. The Conformer architecture is utilized as the encoder, leading to the development of the Conformer-CTC/Attention model. This model first extracts global features from the speech signal using the Conformer, followed by joint decoding of these features through CTC and Attention mechanisms. To mitigate convergence issues during training, particularly with longer input feature sequences, we introduce a Probabilistic Sparse Attention mechanism within the joint CTC/Attention framework. Additionally, we implement a maximum entropy optimization algorithm for CTC, effectively addressing challenges such as increased path counts, spike distributions, and local optima during training. We designate the proposed method as the MaxEnt-Optimized Probabilistic Sparse Attention Conformer-CTC/Attention Model (MPSA-Conformer-CTC/Attention). Experimental results indicate that our improved model achieves a word error rate reduction of 10.68% and 9.57% on self-constructed and open-source Tibetan datasets, respectively, compared to the baseline model. Furthermore, the enhanced model not only reduces memory consumption and training time but also improves generalization capability and accuracy.
Condition Monitoring Using a Latent Space of Variational Autoencoder Trained Only on a Healthy Machine
Authors: Komorska Iwona , Puchalski Andrzej
Published: October 2024

Machine learning generative models have opened up a new perspective for automated machine diagnostics. These methods improve decision-making by extracting features, classifying, and creating new observations using deep neural networks. Generative modeling aims to determine the joint distribution of input data. This contrasts traditional methods used in diagnostics based on discriminative models and the conditional probability distribution of the target variable at known feature values. In the variational autoencoder (VAE) algorithms trained by the authors, the parameters of diagnostic features are random variables, the distributions of which can be approximated based on data, and the identification of probability distributions is based on variational inference. Variational inference is a tool that deals with difficult statistical problems and is usually faster than classical methods. VAEs can detect anomalies, predict failures, and optimize processes. This paper proposes an unsupervised approach to fault diagnosis using only healthy data with automatic feature extraction from the continuous probabilistic latent subspace of the VAE encoder and reduction in PCA or t-SNE. The solution, verified in the example of simulation data, is a response to a common problem related to the lack or difficulty of obtaining marked data in defected states of devices and mechanical structures.
Motion State Estimation with Bandwidth Constraints and Mixed Cyber-Attacks for Unmanned Surface Vehicles: A Resilient Set-Membership Filtering Framework
Authors: Wang Ziyang , Lou Peng , Wang Yudong , Li Juan , Wang Jiasheng
Published: October 2024

This paper investigates the motion state estimation problem of the unmanned surface vehicle (USV) steering system in wireless sensor networks based on the binary coding scheme (BCS). In response to the presence of bandwidth constraints and mixed cyber-attacks in USV communication networks, this paper proposes an improved set-membership state estimation algorithm based on BCS. This algorithm partially addresses the problem of degraded performance in USV steering motion state estimation caused by mixed cyber-attacks and bandwidth constraints. Furthermore, this paper proposes a robust resilient filtering framework considering the possible occurrence of unknown but bounded (UBB) noises, model parameter uncertainties, and estimator gain perturbations in practical scenarios. The proposed framework can accurately estimate the sway velocity, yaw velocity, and roll velocity of the USV under the concurrent presence situation of mixed cyber-attacks, communication capacity constraints, UBB noises, model parameter uncertainties, and estimator gain perturbations. This paper first utilizes mathematical induction to provide the sufficient conditions for the existence of the desired estimator, and obtains the estimator gain by solving a set of linear matrix inequalities. Then, a recursive optimization algorithm is utilized to achieve optimal estimation performance. Finally, the effectiveness of the proposed estimation algorithm is verified through a simulation experiment.
Application and Prospect of Strapdown Inertial Navigation System in Coal Mining Equipment
Authors: Liang Minfu , Zheng Daqian , Li Kewei , Fang Xinqiu , Wu Gang
Published: October 2024

In recent years, with the rapid construction of a safe, clean, efficient and sustainable modern energy system, the intelligence of coal mining has become the inevitable direction of the development of the coal mining industry. The intelligence of coal mining system and equipment is the core of intelligent mining, and the positioning technology of mining equipment is the key to underground intelligent mining. The strapdown inertial navigation system can make up for the shortcomings of traditional GPS positioning systems and laser positioning because of its strong anti-interference, high precision and real-time monitoring, and ability to carry out real-time dynamic positioning of mining equipment in underground coal mines. This paper briefly introduces the basic principle of the strapdown inertial navigation system, analyzes the application of the existing strapdown inertial navigation system in mining equipment, and lists and analyzes the research status of the improvement strategy of the inertial navigation system, such as zero speed correction and integrated navigation technology. Finally, by analyzing the application and future development trend of inertial navigation systems in mining equipment, this paper provides more data and method support for the positioning of mining equipment in the future.
Transmission Line Defect Target-Detection Method Based on GR-YOLOv8
Authors: Hao Shuai , Ren Kang , Li Jiahao , Ma Xu
Published: October 2024

In view of the low levels of speed and precision associated with fault detection in transmission lines using traditional algorithms due to resource constraints, a transmission line fault target-detection method for YOLOv8 (You Only Look Once version 8) based on the Rep (Representational Pyramid) Visual Transformer and incorporating an ultra-lightweight module is proposed. First, the YOLOv8 detection network was built. In order to address the needs of feature redundancy and high levels of network computation, the Rep Visual Transformer module was introduced in the Neck part to integrate the pixel information associated with the entire image through its multi-head self-attention and enable the model to learn more global image features, thereby improving the computational speed of the model; then, a lightweight GSConv (Grouped and Separated Convolution, a combination of grouped convolution and separated convolution) convolution module was added to the Backbone and Neck to share computing resources among channels and reduce computing time and memory consumption, by which the computational cost and detection performance of the detection network were balanced, while the model remained lightweight and maintained its high precision. Secondly, the loss function Wise-IoU (Intelligent IOU) was introduced as the Bounding-Box Regression (BBR) loss function to optimize the predicted bounding boxes in these grid cells and shift them closer to the real target location, which reduced the harmful gradients caused by low-quality examples and further improved the detection precision of the algorithm. Finally, the algorithm was verified using a data set of 3500 images compiled by a power-supply inspection department over the past four years. The experimental results show that, compared with the seven classic and improved algorithms, the recall rate and average precision of the proposed algorithm were improved by 0.058 and 0.053, respectively, compared with the original YOLOv8 detection network; the floating-point operations per second decreased by 2.3; and the picture detection speed was increased to 114.9 FPS.
Assessing the Antimicrobial Efficacy of Graphene Oxide and Its PEGylated Derivative Against Staphylococcus aureus
Authors: Gilsanz-Muñoz María F. , Martínez-Martínez Mónica , Pérez-Piñeiro Javier , Roldán Miriam , Arce Mariana P. , Blasco Rodrigo , Rico-San Román Laura , Esperón-Fajardo Fernando , Cerpa-Naranjo Arisbel , Martín-Maldonado Bárbara
Published: October 2024

The rise of antimicrobial resistance (AMR) has become a critical health challenge. This, plus the antimicrobial discovery void, had led scientists to search for an effective alternative to antimicrobials. In this context, nanomaterials, such as graphene oxide (GO), a two-dimensional (2D) carbon molecule with oxidized functional groups, have been shown to interact physically and chemically with bacteria. Moreover, the addition of polyethylene glycol (PEG) to its surface enhances GO’s biocompatibility and water solubility, making it a promising candidate for biomedical applications. This study evaluates the antimicrobial efficacy of GO and its polyethylene glycol-modified form (GO-PEG) against Staphylococcus aureus, a bacterium responsible for numerous hospital-acquired and multidrug-resistant infections. After their production, both nanomaterials were characterized using various techniques to provide insight into their morphology, stability, and functional group composition. Then, the antimicrobial activity of GO and GO-PEG was assessed using the Müeller–Hinton broth microdilution method, determining the minimum inhibitory concentration (MIC) for S. aureus among ten different concentrations of both nanomaterials (from 0.0625 to 32 mg/mL). The results demonstrate the potential of GO as an effective antimicrobial agent at 16 and 32 mg/mL, offering new strategies in the fight against AMR. Further research could establish its role in future therapeutic applications.
Investigation of Metoprolol Concentrations in Plasma Using Automated Sample Preparation and LC-MS/MS Detection
Authors: Cioroiu Ionel-Bogdan , Dobrin Mona-Elisabeta , Niculaua Marius , Nechita Constantin-Bogdan , Cotea Valeriu V.
Published: October 2024

Metoprolol (MTP), a selective beta-1 adrenergic blocker, is commonly administered in the form of succinate or tartrate salts, depending on the pharmaceutical formulation. It is typically prescribed in oral forms as either immediate-release or extended-release tablets. This study describes a chromatographic method using automated sample clean-up and elution via a reversed-phase mechanism. A TurboFlow approach was applied with a Cyclone P column, and the elution was performed isocratically using a mobile phase of water and acetonitrile (0.1% v/v formic acid) within 4.5 min. Quantification of MTP was achieved using triple quadrupole mass spectrometry, with the transition m/z 268.1 → m/z 130.96 for metoprolol, while bisoprolol fumarate, the internal standard, was detected at m/z 326.3 → m/z 116.2. The method was validated according to bioequivalence guidelines. Selectivity was assessed by checking for potential interferences from blank samples or related compounds formed during sample preparation. Precision and accuracy were evaluated both within and between runs, with a maximum coefficient of variation (CV%) of 10.28 and a maximum relative error (ER%) of 5.38. Linearity was demonstrated over the range of 5 ng/L to 1000 ng/L, with a lower limit of quantification at 0.042 ng/L, made possible by injecting larger sample volumes. A matrix effect of 89% was considered acceptable when compared to standard solutions. Plasma concentrations of MTP were monitored in patients administered either 50 mg or 100 mg doses. For the 50 mg dose, plasma levels reached up to 34 μg/L, while the 100 mg dose produced concentrations ranging from 3.56 to 50.81 μg/L. Although the higher dose generally resulted in elevated plasma levels, significant variability was observed. A strong correlation (r = 0.992) was found between the administered dose and plasma concentration, though variations in absorption rates and patient demographics likely contributed to the observed variability. This method provides a reliable analytical approach suitable for pharmacokinetic and clinical studies involving metoprolol.
What Does ‘Having Close Friends from Abroad’ Mean for the Intercultural Competencies: A New View on the Antecedents of Cultural Intelligence
Authors: Jurásek Miroslav , Wawrosz Petr
Published: October 2024

The study analyzes the impact of intercultural friendship on cultural intelligence (CQ), which is defined as an individual’s ability to operate effectively in a new intercultural environment. Two hypotheses were tested using an online questionnaire completed in the autumn of 2022 by 358 university students from a private university in Prague, Czech Republic. The participants represented 26 countries, with the majority being Czech nationals. The hypotheses were as follows: (1) overall cultural intelligence, and (2) all its components (metacognitive, cognitive, motivational, and behavioral) would be higher or lower depending on whether individuals had close social ties, operationalized by the binary variable “intercultural friendship”. The first hypothesis was confirmed. However, the second hypothesis was only supported for the motivational and cognitive facets of CQ. Our results indicate that CQ is fundamentally a relational construct, developing primarily through contact with members of other cultures. Contextual factors, such as language skills, travel to foreign countries, residence abroad, and the frequency of intercultural contacts, create situational prerequisites for establishing closer intercultural relationships. However, they do not contribute directly to the development of intercultural skills but rather do so indirectly through these relationships.
Narrow Margins and Misinformation: The Impact of Sharing Fake News in Close Contests
Authors: Rhodes Samuel
Published: October 2024

This study investigates the impact of candidates disseminating fake news on voter behavior and electoral outcomes in highly competitive, partisan races. While the effects of fake news on electoral outcomes have been studied, research has yet to examine the impact of candidates’ strategic use of fake news in elections where it may have the greatest impact—close races. This research explores whether the use of fake news influences voter support, particularly among independent voters, in tightly contested elections. Through a conjoint survey experiment involving participants from Amazon MTurk, this study analyzes how variables such as race competitiveness, perceived risk of alienating independents, and the presence of partisan labels affect voter responses to candidates who spread misinformation. The findings indicate that while the competitiveness of a race does not significantly enhance support for candidates sharing fake news, the presence of partisan labels does. These results suggest that voter behavior in response to fake news is more closely tied to partisan identity than to strategic electoral considerations. This study highlights the complex dynamics of misinformation in electoral contexts and its implications for democratic processes.
Control, Passion and Possession: Love as a Space of Violence in Adolescence
Authors: Aragón Victoria , Lozano Antonio
Published: October 2024

Adolescence is a time of elation and sublime emotions which are also reflected in partner relationships, within a context characterised by materialism and social structures in which gender relations are affected by the domination/subordination model. This paper analyses the affective-sexual relationships of adolescents as a place of violence, power relations, domination and submission. It also studies the importance of social networks in their way of interacting and learning. The methodology used was, on the one hand, the review of bibliographic material regarding romance, partner relationships, gender violence and using of networks, and, on the other hand, the analysis of the results obtained from two studies carried out by the University of Granada, with quantitative and qualitative information on adolescents in Andalusia. The results of this research indicate that relationships are permeated by the idealisation of romantic love and by stereotypes leading to practices of control and possession.
Processing Municipal Waste for Phytostabilization of Heavy Metal Contaminated Soils
Authors: Hazratqulov Shohnazar , von Ahlefeldt Georgina , Liu Rui , Bessler Holger , Almuina-Villar Hernán , Dieguez-Alonso Alba , Engels Christof
Published: October 2024

Background: Organic amendments are often used for the phytostabilization of heavy metal-contaminated soils. This study investigated the suitability of different municipal waste processing methods for phytostabilization. Methods: The two feedstocks, biowaste, and green waste, were tested without pretreatment after composting or after pyrolysis at different temperatures and atmosphere compositions. The suitability of the differently pretreated amendments for phytostabilization was tested on sewage farm soil contaminated with Cd, Cu, Ni, and Zn by measurement of maize growth, mineral content, and mobile heavy metal concentrations in the bulk and rhizosphere soil. Results: In contaminated soils, shoot and root growth increased markedly due to the soil amendments. Shoot concentrations of all four heavy metals were significantly higher in contaminated than non-contaminated soil, whereas Fe concentrations were lower in contaminated soil. The amendments increased shoot Cd concentrations and did not significantly affect the other elements. In contaminated soil, concentrations of heavy metals were generally lower in the rhizosphere than in the bulk soil. The soil amendments markedly lowered soil heavy metal concentrations, whereby the decrease was significantly influenced by feedstock and pretreatment. The differences in the amendments’ ability to reduce the soil mobile heavy metals were primarily, but not exclusively, determined by their effect on soil pH. Conclusion: The feedstock processing conditions significantly influenced the phytostabilization performance of green waste and biowaste. Optimal processing for phytostabilization depends on the heavy metal most important in the contamination of a specific site.