bluuebunny/crossref_metadata_2025 huggingface dataset:
Polyvinyl Alcohol/Nafion®–Zirconia Phosphate Nanocomposite Membranes for Polymer Electrolyte Membrane Fuel Cell Applications: Synthesis and Characterisation
Authors: Sigwadi Rudzani , Nemavhola Fulufhelo
Published: November 2023

PVA (polyvinyl alcohol)-ZrP (PVA/ZrP) and Nafion®/PVA-ZrP nanocomposite membranes were synthesised using the recasting method with glutaraldehyde (GA) as a crosslinking agent. The resulting nanocomposite membranes were characterised using a variety of techniques, including X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR). The results of SEM revealed well-distributed zirconia phosphate (ZrP) within the membrane matrix, and the SEM images showed a uniform and dense membrane structure. Because ZrP nanoparticles are hydrophilic, the Nafion®/PVA-ZrP nanocomposite membrane had a higher water uptake of 53% at 80 °C and higher 0.19 S/cm proton conductivity at room temperature than the commercial Nafion® 117 membrane, which had only 34% and 0.113 S/cm, respectively. In comparison to commercial Nafion® 117 membranes, PVA-ZrP and Nafion®/PVA-ZrP nanocomposite membranes had a higher thermal stability and mechanical strength and lower methanol crossover due to the hydrophilic effect of PVA crosslinked with GA, which can make strong hydrogen bonds and cause an intense intramolecular interaction.
Synthesis ZrON Films with Raman-Enhancement Properties Using Microwave Plasma
Authors: Muslimov Arsen , Antipov Sergey , Gadzhiev Makhach , Kanevsky Vladimir
Published: November 2023

The paper investigates the characteristics of the formation and morphology of microstructured zirconium oxynitride (ZrON) films, taking into account structural polymorphism during the impact of atmospheric-pressure microwave nitrogen plasma with the influx of active oxygen from the surrounding atmosphere. Optical, hydrophobic, Raman-active properties of ZrON films have been studied. X-ray diffractometry (XRD), scanning electron microscopy (SEM), ellipsometry method, and Raman spectroscopy, and moisture-resistance properties are used as analytical research methods. It is shown that during the short-term impact of microwave plasma, a morphologically heterogeneous ZrON film can be formed with a set of microhills with a uniform phase composition along the surface. The phase composition of the ZrON surface corresponds to the monoclinic structure of ZrO2. In the volume of the film, a predominantly tetragonal structure of ZrO2 is observed, as well as inclusions of the monoclinic structure of ZrO2. A mechanism for the formation of a ZrON film, taking into account polymorphism and phase transitions, is proposed. The optical properties of ZrON films are determined by both the dielectric phase of ZrO2 and the inclusions of the high-conductivity phase of ZrN. A combination of such factors as the developed microrelief and monoclinic surface structure, as well as nitride phase inclusions, enhance the hydrophobic properties of the ZrON film surface. It is shown that the surface hydrophobicity and resonant effects on ZrN inclusions allow for the enhancement of the Raman spectrum intensity due to the high concentration of analyte molecules in the scanning area.
Characterization of Cronobacter sakazakii and Cronobacter malonaticus Strains Isolated from Powdered Dairy Products Intended for Consumption by Adults and Older Adults
Authors: Parra-Flores Julio , Flores-Soto Fernanda , Flores-Balboa Carolina , Alarcón-Lavín María P. , Cabal-Rosel Adriana , Daza-Prieto Beatriz , Springer Burkhard , Cruz-Córdova Ariadnna , Leiva-Caro José , Forsythe Stephen , Ruppitsch Werner
Published: November 2023

The objective of this study was to characterize Cronobacter spp. and related organisms isolated from powder dairy products intended for consumption by adults and older adults using whole-genome sequencing (WGS), and to identify genes and traits that encode antibiotic resistance and virulence. Virulence (VGs) and antibiotic resistance genes (ARGs) were detected with the Comprehensive Antibiotic Resistance Database (CARD) platform, ResFinder, and MOB-suite tools. Susceptibility testing was performed using disk diffusion. Five presumptive strains of Cronobacter spp. were identified by MALDI–TOF MS and ribosomal MLST. Three C. sakazakii strains were of the clinical pathovar ST1, one was ST31, and the remaining isolate was C. malonaticus ST60. In addition, Franconibacter helveticus ST345 was identified. The C. sakazakii ST1 strains were further distinguished using core genome MLST based on 2831 loci. Moreover, 100% of the strains were resistant to cefalotin, 75% to ampicillin, and 50% to amikacin. The C. sakazakii ST1 strains were multiresistant (MDR) to four antibiotics. Additionally, all the strains adhered to the N1E-115 cell line, and two invaded it. Eighteen ARGs mainly involved in antibiotic target alteration and antibiotic efflux were detected. Thirty VGs were detected and clustered as flagellar proteins, outer membrane proteins, chemotaxis, hemolysins, and genes involved in metabolism and stress. The pESA3, pSP291-1, and pCMA1 plasmids were detected, and the prevalent mobile genetic elements (MGEs) were ISEsa1, ISEc52, and IS26. The isolates of C. sakazakii and C. malonaticus exhibited multiresistance to antibiotics, harbored genes encoding various antibiotic resistance proteins, and various virulence factors. Consequently, these contaminated powdered dairy products pose a risk to the health of hypersensitive adults.
HPLC–DAD Analysis, SFE-CO2 Extraction, and Antibacterial Activity on Bioactive Compounds from Mosla chinensis Maxim
Authors: Gao Ruixi , Han Bingchen , Zeng Yanfeng , Shen Linchuang , Liu Xinqiao , Wang Qiang , Liao Maochuan , Li Jun
Published: November 2023

Mosla chinensis Maxim is an annual herb with many potential purposes in agricultural, industrial, and pharmaceutical fields. At present, the extract of the whole plant from M. chinensis has been proven to demonstrate antifungal, antioxidant, and anti-inflammatory activities. Previous studies focused on the enzyme pretreatment in hydrodistillation from M. chinensis. However, organic solvent or supercritical fluid carbon dioxide extraction (SFE-CO2) methods, which are commonly utilized in industry, have seldom been studied and cannot provide multiple evaluations of yield. In this work, we analysed compounds from M. chinensis by HPLC–DAD, discussed n-hexane extraction, and conducted further investigations on SFE-CO2 through the design of response surface methodology (RSM). The sample obtained from pilot-scale SFE-CO2 was also tested against nine kinds of microorganisms. Single-factor results revealed that the extraction rates from M. chinensis by steam distillation, n-hexane extraction, and SFE-CO2 were 1%, 2.09%, and 3.26%, respectively. RSM results showed a significant improvement in extraction rate through optimising pressure and time, and the interaction of both factors was more important than that of temperature–pressure and temperature–time. A pilot-scale test with an extraction rate of 3.34% indicated that the predicted RSM condition was operable. In addition, samples from the pilot-scale SFE-CO2 showed antibacterial effects against three previously unreported bacteria (Gardnerella vaginalis, methicillin-resistant Staphylococcus aureus, and Propionibacterium acnes). These results fill the gap in previous research and provide more information for the application and development of M. chinensis in the future.
Polyaromatic Bis(indolyl)methane Derivatives with Antiproliferative and Antiparasitic Activity
Authors: Gonçalves Raquel C. R. , Peñalver Pablo , Costa Susana P. G. , Morales Juan C. , Raposo Maria Manuela M.
Published: November 2023

Bis(indolyl)methanes (BIMs) are a class of compounds that have been recognized as an important core in the design of drugs with important pharmacological properties, such as promising anticancer and antiparasitic activities. Here, we explored the biological activity of the BIM core functionalized with different (hetero)aromatic moieties. We synthesized substituted BIM derivatives with triphenylamine, N,N-dimethyl-1-naphthylamine and 8-hydroxylquinolyl groups, studied their photophysical properties and evaluated their in vitro antiproliferative and antiparasitic activities. The triphenylamine BIM derivative 2a displayed an IC50 of 3.21, 3.30 and 3.93 μM against Trypanosoma brucei, Leishmania major and HT-29 cancer cell line, respectively. The selectivity index demonstrated that compound 2a was up to eight-fold more active against the parasites and HT-29 than against the healthy cell line MRC-5. Fluorescence microscopy studies with MRC-5 cells and T. brucei parasites incubated with derivative 2a indicate that the compound seems to accumulate in the cell’s mitochondria and in the parasite’s nucleus. In conclusion, the BIM scaffold functionalized with the triphenylamine moiety proved to be the most promising antiparasitic and anticancer agent of this series.
Transition-Metal-Free One-Pot Synthesis of Fused Benzofuranamines and Benzo[b]thiophenamines
Authors: Liu Ran , Lv Lili , Yang Bingchuan , Gu Ziyi , Li Chenglong , Lv Xueyan , Ding Chengcheng , Huang Xianqiang , Yuan Dong
Published: November 2023

A series of benzofuran and benzo[b]thiophen derivatives was synthesized via a transition-metal-free one-pot process at room temperature. This one-pot protocol enables the synthesis of compounds with high reaction efficiency, mild conditions, simple methods, and a wide-ranging substrate scope. Regioselective five-membered heterocycles were constructed in good-to-excellent yields.
Epidemiology, Molecular Pathogenesis, Immuno-Pathogenesis, Immune Escape Mechanisms and Vaccine Evaluation for HPV-Associated Carcinogenesis
Authors: Jain Meenu , Yadav Dhananjay , Jarouliya Urmila , Chavda Vishal , Yadav Arun Kumar , Chaurasia Bipin , Song Minseok
Published: November 2023

Human papillomavirus (HPV) is implicated in over 90% of cervical cancer cases, with factors like regional variability, HPV genotype, the population studied, HPV vaccination status, and anatomical sample collection location influencing the prevalence and pathology of HPV-induced cancer. HPV-16 and -18 are mainly responsible for the progression of several cancers, including cervix, anus, vagina, penis, vulva, and oropharynx. The oncogenic ability of HPV is not only sufficient for the progression of malignancy, but also for other tumor-generating steps required for the production of invasive cancer, such as coinfection with other viruses, lifestyle factors such as high parity, smoking, tobacco chewing, use of contraceptives for a long time, and immune responses such as stimulation of chronic stromal inflammation and immune deviation in the tumor microenvironment. Viral evasion from immunosurveillance also supports viral persistence, and virus-like particle-based prophylactic vaccines have been licensed, which are effective against high-risk HPV types. In addition, vaccination awareness programs and preventive strategies could help reduce the rate and incidence of HPV infection. In this review, we emphasize HPV infection and its role in cancer progression, molecular and immunopathogenesis, host immune response, immune evasion by HPV, vaccination, and preventive schemes battling HPV infection and HPV-related cancers.
Gandhia gen. nov.—A New Diatom Genus with Unusual Morphology Split Off from the Genus Navicula Bory
Authors: Kulikovskiy Maxim S. , Thacker Mital , Glushchenko Anton M. , Kuznetsova Irina V. , Iurmanov Anton A. , Karthick Balasubramanian , Kociolek John Patrick
Published: November 2023

A new naviculoid diatom genus, Gandhia gen. nov., was described based on a detailed morphological investigation using light and scanning electron microscopy. Gandhia obtecta (Jüttner and Cox) Kulikovskiy, Glushchenko, Iurmanov, M.Thacker, B.Karthick and Kociolek comb. nov. was previously described as a member of the genus Navicula Bory sensu lato. This species differs from other species in the genus Navicula s.l. by the presence of an internal siliceous lamina covering the alveoli and forming the image of longitudinal lines on either side of the axial area, visible in LM. The presence of this siliceous lamina is similar to laminae in genera such as Pinnularia and Gomphoneis. This unusual morphology is not typical for Navicula sensu stricto, as previously noted by other scientists. Additional investigation of Gandhia obtecta comb. nov. and Gandhia ramosissimoides (H.P. Gandhi) Kulikovskiy, Glushchenko, M.Thacker, B.Karthick and Kociolek comb. nov. from waterbodies of the Western Ghats and the Himalayan region was conducted. Comparison with other species with the same morphological features included two additional species in the genus, namely, Gandhia jakovljevicii (Hustedt) Kulikovskiy, Glushchenko, M.Thacker, B.Karthick, and Kociolek comb. nov. and Gandhia lucida (Pantocsek) Kulikovskiy, Glushchenko, M.Thacker, B.Karthick and Kociolek comb. nov. We discuss the biogeographic patterns of the species, including disjuncts between Europe and Asia.
Significance of Pressure Drop, Changing Molar Flow, and Formation of Steam in the Accurate Modeling of a Multi-Tubular Fischer–Tropsch Reactor with Cobalt as Catalyst
Authors: Jess Andreas , Kern Christoph
Published: November 2023

A Fischer–Tropsch (FT) fixed-bed reactor was simulated with reactor models of different complexities to elucidate the impact of a pressure drop, a change in the total molar volume rate (induced by the reaction) along the tubes, and a change in the axial variation of the external radial heat transfer coefficient (external tube wall to cooling medium, here, boiling water) compared to disregarding these aspects. The reaction kinetics of CO conversion for cobalt as a catalyst were utilized, and the influence of inhibition of syngas (CO, H2) conversion reaction rate by steam, inevitably formed during FT synthesis, was also investigated. The analysis of the behavior of the reactor (axial/radial temperature profiles, productivity regarding the hydrocarbons formed, and syngas conversion) clearly shows that, for accurate reactor modeling, the decline in the total molar flow from the reaction and the pressure drop should be considered; both effects change the gas velocity along the tubes and, thus, the residence time and syngas conversion compared to disregarding these aspects. Only in rare cases do both opposing effects cancel each other out. The inhibition of the reaction rate by steam should also be considered for cobalt as a catalyst if the final partial pressure of steam in the tubes exceeds about 5 bar. In contrast, the impact of an axially changing heat transfer coefficient is almost negligible compared to disregarding this effect.
Hybrid Control of the DC Microgrid Using Deep Neural Networks and Global Terminal Sliding Mode Control with the Exponential Reaching Law
Authors: Sharaf Mohamed A. , Armghan Hammad , Ali Naghmash , Yousef Amr , Abdalla Yasser S. , Boudabbous Anis R. , Mehdi Hafiz , Armghan Ammar
Published: November 2023

The direct current (DC) microgrid is one of the key research areas for our advancement toward carbon-free energy production. In this paper, a two-step controller is designed for the DC microgrid using a combination of the deep neural network (DNN) and exponential reaching law-based global terminal sliding mode control (ERL-GTSMC). The DC microgrid under consideration involves multiple renewable sources (wind, PV) and an energy storage unit (ESU) connected to a 700 V DC bus and a 4–12 kW residential load. The proposed control method eliminates the chattering phenomenon and offers quick reaching time by utilizing the exponential reaching law (ERL). In the two-step control configuration, first, DNNs are used to find maximum power point tracking (MPPT) reference values, and then ERL-based GTSMC is utilized to track the reference values. The real dynamics of energy sources and the DC bus are mathematically modeled, which increases the system’s complexity. Through the use of Lyapunov stability criteria, the stability of the control system is examined. The effectiveness of the suggested hybrid control algorithm has been examined using MATLAB simulations. The proposed framework has been compared to traditional sliding mode control and terminal sliding mode control to showcase its superiority and robustness. Experimental tests based on the hardware-in-the-loop (HIL) setup are then conducted using 32-bit TMS320F28379D microcontrollers. Both MATLAB and HIL results show strong performance under a range of environmental circumstances and system uncertainties.
A Nondestructive Methodology for Determining Chemical Composition of Salvia miltiorrhiza via Hyperspectral Imaging Analysis and Squeeze-and-Excitation Residual Networks
Authors: Zhu Jieqiang , Bao Jiaqi , Tao Yi
Published: November 2023

The quality assurance of bulk medicinal materials, crucial for botanical drug production, necessitates advanced analytical methods. Conventional techniques, including high-performance liquid chromatography, require extensive pre-processing and rely on extensive solvent use, presenting both environmental and safety concerns. Accordingly, a non-destructive, expedited approach for assessing both the chemical and physical attributes of these materials is imperative for streamlined manufacturing. We introduce an innovative method, designated as Squeeze-and-Excitation Residual Network Combined Hyperspectral Image Analysis (SE-ReHIA), for the swift and non-invasive assessment of the chemical makeup of bulk medicinal substances. In a demonstrative application, hyperspectral imaging in the 389–1020 nm range was employed in 187 batches of Salvia miltiorrhiza. Notable constituents such as salvianolic acid B, dihydrotanshinone I, cryptotanshinone, tanshinone IIA, and moisture were quantified. The SE-ReHIA model, incorporating convolutional layers, maxpooling layers, squeeze-and-excitation residual blocks, and fully connected layers, exhibited Rc2 values of 0.981, 0.980, 0.975, 0.972, and 0.970 for the aforementioned compounds and moisture. Furthermore, Rp2 values were ascertained to be 0.975, 0.943, 0.962, 0.957, and 0.930, respectively, signifying the model’s commendable predictive competence. This study marks the inaugural application of SE-ReHIA for Salvia miltiorrhiza’s chemical profiling, offering a method that is rapid, eco-friendly, and non-invasive. Such advancements can fortify consistency across botanical drug batches, underpinning product reliability. The broader applicability of the SE-ReHIA technique in the quality assurance of bulk medicinal entities is anticipated with optimism.
Estimation of Tool Life in the Milling Process—Testing Regression Models
Authors: Paszkiewicz Andrzej , Piecuch Grzegorz , Żabiński Tomasz , Bolanowski Marek , Salach Mateusz , Rączka Dariusz
Published: November 2023

The article presents an attempt to identify an appropriate regression model for the estimation of cutting tool lifespan in the milling process based on the analysis of the R2 parameters of these models. The work is based on our own experiments and the accumulated database (which we make available for further use). The study uses a Haas VF-1 milling machine equipped with vibration sensors and based on a Beckhoff PLC data collector. As the acquired sensor data are continuous, and in order to account for dependencies between them, regression models were used. Support Vector Regression (SVR), decision trees and neural networks were tested during the work. The results obtained show that the best prediction results with the lowest error values were obtained for two-dimensional neural networks using the LBFGS solver (93.9%). Very similar results were also obtained for SVR (93.4%). The research carried out is related to the realisation of intelligent manufacturing dedicated to Industry 4.0 in the field of monitoring production processes, planning service downtime and reducing the level of losses resulting from damage to materials, semi-finished products and tools.
BIR: Biomedical Information Retrieval System for Cancer Treatment in Electronic Health Record Using Transformers
Authors: Ahmad Pir Noman , Liu Yuanchao , Khan Khalid , Jiang Tao , Burhan Umama
Published: November 2023

The rapid growth of electronic health records (EHRs) has led to unprecedented biomedical data. Clinician access to the latest patient information can improve the quality of healthcare. However, clinicians have difficulty finding information quickly and easily due to the sheer data mining volume. Biomedical information retrieval (BIR) systems can help clinicians find the information required by automatically searching EHRs and returning relevant results. However, traditional BIR systems cannot understand the complex relationships between EHR entities. Transformers are a new type of neural network that is very effective for natural language processing (NLP) tasks. As a result, transformers are well suited for tasks such as machine translation and text summarization. In this paper, we propose a new BIR system for EHRs that uses transformers for predicting cancer treatment from EHR. Our system can understand the complex relationships between the different entities in an EHR, which allows it to return more relevant results to clinicians. We evaluated our system on a dataset of EHRs and found that it outperformed state-of-the-art BIR systems on various tasks, including medical question answering and information extraction. Our results show that Transformers are a promising approach for BIR in EHRs, reaching an accuracy and an F1-score of 86.46%, and 0.8157, respectively. We believe that our system can help clinicians find the information they need more quickly and easily, leading to improved patient care.
Self-Position Determination Based on Array Signal Subspace Fitting under Multipath Environments
Authors: Cao Zhongkang , Li Pan , Tang Wanghao , Li Jianfeng , Zhang Xiaofei
Published: November 2023

A vehicle’s position can be estimated with array receiving signal data without the help of satellite navigation. However, traditional array self-position determination methods are faced with the risk of failure under multipath environments. To deal with this problem, an array signal subspace fitting method is proposed for suppressing the multipath effect. Firstly, all signal incidence angles are estimated with enhanced spatial smoothing and root multiple signal classification (Root-MUSIC). Then, non-line-of-sight (NLOS) components are distinguished from multipath signals using a K-means clustering algorithm. Finally, the signal subspace fitting (SSF) function with a P matrix is established to reduce the NLOS components in multipath signals. Meanwhile, based on the initial clustering estimation, the search area can be significantly reduced, which can lead to less computational complexity. Compared with the C-matrix, oblique projection, initial signal fitting (ISF), multiple signal classification (MUSIC) and signal subspace fitting (SSF), the simulated experiments indicate that the proposed method has better NLOS component suppression performance, less computational complexity and more accurate positioning precision. A numerical analysis shows that the complexity of the proposed method has been reduced by at least 7.64dB. A cumulative distribution function (CDF) analysis demonstrates that the estimation accuracy of the proposed method is increased by 3.10dB compared with the clustering algorithm and 11.77dB compared with MUSIC, ISF and SSF under multipath environments.
Unraveling False Positives in Unsupervised Defect Detection Models: A Study on Anomaly-Free Training Datasets
Authors: Qiu Ji , Shi Hongmei , Hu Yuhen , Yu Zujun
Published: November 2023

Unsupervised defect detection methods have garnered substantial attention in industrial defect detection owing to their capacity to circumvent complex fault sample collection. However, these models grapple with establishing a robust boundary between normal and abnormal conditions in intricate scenarios, leading to a heightened frequency of false-positive predictions. Spurious alerts exacerbate the work of reconfirmation and impede the widespread adoption of unsupervised anomaly detection models in industrial applications. To this end, we delve into the sole available data source in unsupervised defect detection models, the unsupervised training dataset, to introduce a solution called the False Alarm Identification (FAI) method aimed at learning the distribution of potential false alarms using anomaly-free images. It exploits a multi-layer perceptron to capture the semantic information of potential false alarms from a detector trained on anomaly-free training images at the object level. During the testing phase, the FAI model operates as a post-processing module applied after the baseline detection algorithm. The FAI algorithm determines whether each positive patch predicted by the normalizing flow algorithm is a false alarm by its semantic features. When a positive prediction is identified as a false alarm, the corresponding pixel-wise predictions are set to negative. The effectiveness of the FAI method is demonstrated by two state-of-the-art normalizing flow algorithms on extensive industrial applications.
Internet of Things in Pregnancy Care Coordination and Management: A Systematic Review
Authors: Hossain Mohammad Mobarak , Kashem Mohammod Abul , Islam Md. Monirul , Sahidullah Md. , Mumu Sumona Hoque , Uddin Jia , Aray Daniel Gavilanes , de la Torre Diez Isabel , Ashraf Imran , Samad Md Abdus
Published: November 2023

The Internet of Things (IoT) has positioned itself globally as a dominant force in the technology sector. IoT, a technology based on interconnected devices, has found applications in various research areas, including healthcare. Embedded devices and wearable technologies powered by IoT have been shown to be effective in patient monitoring and management systems, with a particular focus on pregnant women. This study provides a comprehensive systematic review of the literature on IoT architectures, systems, models and devices used to monitor and manage complications during pregnancy, postpartum and neonatal care. The study identifies emerging research trends and highlights existing research challenges and gaps, offering insights to improve the well-being of pregnant women at a critical moment in their lives. The literature review and discussions presented here serve as valuable resources for stakeholders in this field and pave the way for new and effective paradigms. Additionally, we outline a future research scope discussion for the benefit of researchers and healthcare professionals.
Dynamic Condition Adversarial Adaptation for Fault Diagnosis of Wind Turbine Gearbox
Authors: Zhang Hongpeng , Wang Xinran , Zhang Cunyou , Li Wei , Wang Jizhe , Li Guobin , Bai Chenzhao
Published: November 2023

While deep learning has found widespread utility in gearbox fault diagnosis, its direct application to wind turbine gearboxes encounters significant hurdles. Disparities in data distribution across a spectrum of operating conditions for wind turbines result in a marked decrease in diagnostic accuracy. In response, this study introduces a tailored dynamic conditional adversarial domain adaptation model for fault diagnosis in wind turbine gearboxes amidst cross-condition scenarios. The model adeptly adjusts the importance of aligning marginal and conditional distributions using distance metric factors. Information entropy parameters are also incorporated to assess individual sample transferability, prioritizing highly transferable samples during domain alignment. The amalgamation of these dynamic factors empowers the approach to maintain stability across varied data distributions. Comprehensive experiments on both gear and bearing data validate the method’s efficacy in cross-condition fault diagnosis. Comparative outcomes demonstrate that, when contrasted with four advanced transfer learning techniques, the dynamic conditional adversarial domain adaptation model attains superior accuracy and stability in multi-transfer tasks, making it notably suitable for diagnosing wind turbine gearbox faults.
Intelligent Fault Diagnosis of Hydraulic Multi-Way Valve Using the Improved SECNN-GRU Method with mRMR Feature Selection
Authors: Guan Hanlin , Yan Ren , Tang Hesheng , Xiang Jiawei
Published: November 2023

Hydraulic multi-way valves as core components are widely applied in engineering machinery, mining machinery, and metallurgical industries. Due to the harsh working environment, faults in hydraulic multi-way valves are prone to occur, and the faults that occur are hidden. Moreover, hydraulic multi-way valves are expensive, and multiple experiments are difficult to replicate to obtain true fault data. Therefore, it is not easy to achieve fault diagnosis of hydraulic multi-way valves. To address this problem, an effective intelligent fault diagnosis method is proposed using an improved Squeeze-Excitation Convolution Neural Network and Gated Recurrent Unit (SECNN-GRU). The effectiveness of the method is verified by designing a simulation model for a hydraulic multi-way valve to generate fault data, as well as the actual data obtained by establishing an experimental platform for a directional valve. In this method, shallow statistical features are first extracted from data containing fault information, and then fault features with high correlation with fault types are selected using the Maximum Relevance Minimum Redundancy algorithm (mRMR). Next, spatial dimension features are extracted through CNN. By adding the Squeeze-Excitation Block, different weights are assigned to features to obtain weighted feature vectors. Finally, the time-dimension features of the weighted feature vectors are extracted and fused through GRU, and the fused features are classified using a classifier. The fault data obtained from the simulation model verifies that the average diagnostic accuracy of this method can reach 98.94%. The average accuracy of this method can reach 92.10% (A1 sensor as an example) through experimental data validation of the directional valve. Compared with other intelligent diagnostic algorithms, the proposed method has better stationarity and higher diagnostic accuracy, providing a feasible solution for fault diagnosis of the hydraulic multi-way valve.
Machine Learning Approach for Pitch Type Classification Based on Pelvis and Trunk Kinematics Captured with Wearable Sensors
Authors: Gomaz Larisa , Bouwmeester Celine , van der Graaff Erik , van Trigt Bart , Veeger DirkJan
Published: November 2023

The large stream of data from wearable devices integrated with sports routines has changed the traditional approach to athletes’ training and performance monitoring. However, one of the challenges of data-driven training is to provide actionable insights tailored to individual training optimization. In baseball, the pitching mechanics and pitch type play an essential role in pitchers’ performance and injury risk management. The optimal manipulation of kinematic and temporal parameters within the kinetic chain can improve the pitcher’s chances of success and discourage the batter’s anticipation of a particular pitch type. Therefore, the aim of this study was to provide a machine learning approach to pitch type classification based on pelvis and trunk peak angular velocity and their separation time recorded using wearable sensors (PITCHPERFECT). The Naive Bayes algorithm showed the best performance in the binary classification task and so did Random Forest in the multiclass classification task. The accuracy of Fastball classification was 71%, whilst the accuracy of the classification of three different pitch types was 61.3%. The outcomes of this study demonstrated the potential for the utilization of wearables in baseball pitching. The automatic detection of pitch types based on pelvis and trunk kinematics may provide actionable insight into pitching performance during training for pitchers of various levels of play.
Novel Adsorbents and Adsorption Methods for Pollutant Removal
Authors: Wei Yuezhou , Wu Yan , Wang Xinpeng
Published: November 2023

Over the past few decades, with the rapid growth of the global population and economy, the increasing levels of various pollutants such as heavy metals, radionuclides, and organic/inorganic/biological toxins from various industries and human activities, which diffuse into aspects of the environment such as the atmosphere, soil, and natural water, have posed a serious threat to human health and the environment [...]
PRRSV-Vaccinated, Seronegative Sows and Maternally Derived Antibodies (I): Impact on PRRSV-1 Challenge Outcomes in Piglets
Authors: Fiers Jorian , Maes Dominiek , Cay Ann-Brigitte , Mostin Laurent , Parys Anna , Tignon Marylène
Published: November 2023

Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) remains an infectious agent with high importance in the swine industry. In this study, the influence of maternally derived antibodies (MDAs) on an experimental PRRSV-1 challenge is investigated. Piglets included in the study (n = 36) originated from a Belgian farrow-to-finish herd in which the sow population was routinely vaccinated with a modified live vaccine against PRRSV. Eighteen piglets were born from three PRRSV-seropositive sows (responders to vaccination) and had a clear presence of PRRSV-specific MDAs (E+ piglets). The other eighteen piglets were born from three PRRSV-seronegative sows (non-responders to vaccination) and did not have PRRSV-specific MDAs (E− piglets). In each group, twelve piglets were intranasally challenged with a high dose of the heterologous PRRSV-1 07V063 strain, the remaining piglets were mock-challenged (PBS) and served as controls. During the first days after infection, higher serum viremia and nasal shedding were observed in the challenged E− piglets compared to the challenged E+ piglets. However, at 10 days post-infection, the peak serum viremia was significantly higher in the E+ piglets in comparison to the E− piglets and serum viremia remained slightly higher in this group until the end of the study. Additionally, the two challenged groups had a different immune response to the PRRSV infection. The E− challenged piglets showed an earlier and more intense seroconversion, leading to significantly higher antibody titers at 10 dpi compared to the E+ challenged piglets. Furthermore, a trend towards both higher induction of serum IFN-γ and higher induction of IFN-γ secreting cells was observed in the E− challenged piglets. In contrast, a significantly higher induction of serum TNF-α at 7 dpi was seen in the E+ challenged piglets compared to the E− challenged piglets. The results gathered in this study suggest that PRRSV-specific MDAs induce partial protection during the early stages of infection but are not sufficient to protect against a high challenge dose. The presence of piglets lacking PRRSV-specific MDAs might pose a risk for PRRSV infection and enhanced transmission in pig farms in young piglets.
Dose Intervals and Time since Final Dose on Changes in Metabolic Indices after COVID-19 Vaccination
Authors: Alghamdi Amani , Wani Kaiser , Alnaami Abdullah M. , Al-Daghri Nasser M.
Published: November 2023

The rapid development and implementation of COVID-19 vaccines merit understanding its effects on metabolic indices. This retrospective longitudinal study investigated the influence of first-to-second-dose intervals and time since the final dose on the metabolic indices of individuals receiving COVID-19 vaccinations. A total of 318 Saudi subjects (59.7% females) aged 12–60 years received COVID-19 vaccines via the national vaccination program. We collected the anthropometric data and fasting blood samples at specific time points before vaccination and after the final vaccination dose, and biochemical metabolic indices, including glucose and lipid profile, were measured. We also collected the dates of vaccination and COVID-19 history during the study period. The participants were stratified into groups based on first-to-second-dose intervals and time since the final dose to compare pre-and post-vaccination changes in metabolic indices between the groups. Logistic regression analysis revealed no differences in pre- to post-vaccination metabolic status between groups based on first-to-second-dose intervals in either adolescents or adults. However, shorter intervals (≤6 months) between the final dose and follow-up were associated with a decrease in total cardiometabolic components, especially triglyceride levels (OR = 0.39, 95% CI: (0.22–0.68), p < 0.001) than longer intervals (>6 months) in adults. In conclusion, time duration since final dose was associated with pre- to post-vaccination changes in metabolic indices, especially triglyceride levels, indicating that post-vaccination improvements wane over time. Further research is needed to validate the observed relationship, as it may contribute to optimizing vaccine effectiveness and safety in the future.
Rollout of the 2022/2023 Seasonal Influenza Vaccination and Correlates of the Use of Enhanced Vaccines among Italian Adults
Authors: Pestarino Luca , Domnich Alexander , Orsi Andrea , Bianchi Federico , Cannavino Elisa , Brasesco Pier Claudio , Russo Gianluca , Valbonesi Simone , Vallini Giacomo , Ogliastro Matilde , Icardi Giancarlo
Published: November 2023

In Italy, several types of seasonal influenza vaccines (SIVs) are available for older adults, but for the 2022/2023 season there were no guidelines on their specific use. This cross-sectional study assessed the frequency and determinants of the use of enhanced (adjuvanted and high-dose) SIVs in Italian older adults, as compared to standard-dose non-adjuvanted formulations. Of 1702 vaccines administered to a representative outpatient sample of adults aged ≥ 60 years and residing in Genoa, 69.5% were enhanced SIVs. Older age (adjusted odds ratio (aOR) for each 1-year increase 1.10; p < 0.001), and the presence of cardiovascular disease (aOR 1.40; p = 0.011) and diabetes (aOR 1.62; p = 0.005) were associated with the use of enhanced vaccines. Compared with the adjuvanted SIV, subjects immunized with the high-dose vaccine were older (aOR for each 1-year increase 1.05; p < 0.001) and had higher prevalence of respiratory diseases (aOR 1.85; p = 0.052). Moreover, usage of the enhanced SIVs was driven by the period of immunization campaign, place of vaccination and physician. Despite their superior immunogenicity and effectiveness, the adoption of enhanced SIVs in Italy is suboptimal, and should be increased. Enhanced formulations are mostly used in the oldest, and in subjects with some co-morbidities.
Conceptual approaches to the assessment of the management system of APK organizations in the context of ESG transformation
Authors:   Russian Timiryazev State Agrarian University, Moscow, Russia, Khoruzhy L. I. , Katkov Yu. N. ,   Russian Timiryazev State Agrarian University, Moscow, Russia, Romanova A. A. ,   Russian Timiryazev State Agrarian University, Moscow, Russia, Katkova E. A. ,   Russian Timiryazev State Agrarian University, Moscow, Russia, Dzhikiya M. K. ,   Russian Timiryazev State Agrarian University, Moscow, Russia
Published: November 2023

To quickly obtain the necessary data, generate and present information on the level and dynamics of sustainable development of agro-industrial complex organizations, analytical tools are required that allow you to quickly assess the effectiveness of the organization’s management system To quickly obtain the necessary data, generate and present information on the level and dynamics of sustainable development of agro-industrial complex organizations, analytical tools are required that allow you to quickly assess the effectiveness of the organization’s management system To quickly obtain the necessary data, generate and present information on the level and dynamics of sustainable development of agro-industrial complex organizations, analytical tools are required that allow you to quickly assess the effectiveness of the organization’s management systemTo quickly obtain the necessary data, generate and present information on the level and dynamics of sustainable development of agro-industrial complex organizations, analytical tools are required that allow you to quickly assess the effectiveness of the organization’s management system itself. The article provides a theoretical justification of approaches to the development of a methodology for the formation of a management assessment system. This makes it possible to provide a preventive mechanism for making management decisions in the management system of agro-industrial complex organizations. Traditional tools for assessing management technologies of the domestic sector of the agro-industrial complex have been adapted to new unstable economic and political conditions. Disclosed is a system for managing agro-industrial complex organizations from the point of view of a systematic approach, its external and internal calls in the conditions of ESG transformation are described. A set of reference indicators for the assessment of the management system of APK organizations based on ESG principles is presented.
Pedagogías productivas y perspectivas de aprendizaje en estudiantes de Centros de Bachillerato Tecnológico Agropecuario
Authors: Rodríguez Guardado María del Socorro , Martínez Tomás Marisol
Published: November 2023

Esta investigación tuvo como objetivo determinar las perspectivas de aprendizaje en Ciencias Experimentales de los estudiantes de Centros de Bachillerato Tecnológico Agropecuario del Estado de Puebla, México, con respecto al semestre en el que se encuentran matriculados. El método utilizado fue cuantitativo, correlacional, con alcance descriptivo y transversal. Participaron 132 estudiantes de los cuales 60% (n=79) fueron mujeres y 40% (n= 53) hombres con edades entre 15-19 años quienes cursaban diferentes semestres y de forma voluntaria respondieron un cuestionario basado en las Pedagogías Productivas adaptado al contexto mexicano y revisado por expertos. Se realizó una prueba piloto previo a la aplicación de la muestra ampliada. Las perspectivas de los estudiantes dan cuenta de una mayor vinculación de los contenidos del aula y del contexto en los semestres avanzados en este sentido, las dimensiones de Calidad Intelectual y Contextualización de los Aprendizajes mostraron un promedio mayor en el estudiantado en estos semestres. Reflexionar sobre las prácticas pedagógicas en torno a las Pedagogías Productivas para contextualizar los aprendizajes desde los semestres iniciales puede propiciar un mayor acercamiento e interés en las Ciencias Experimentales por parte de los estudiantes de estos bachilleratos.
Holopraxis del docente universitario: Un nuevo pensamiento emergente…
Authors: Camero Shandra
Published: November 2023

La holopraxis docente universitaria, desde su configuración, ha venido incorporando distintas posturas paradigmáticas para su desempeño; enmarcándose dentro de una visión pragmática y funcionalista con todas las implicaciones que ello conlleva por tal motivo el propósito de esta investigación doctoral será construir un corpus teórico de la holopraxis docente universitaria hacia una educación sensibilizada. Desde la perspectiva filosófica de visionará con las teorías el holismo de Stamus (1926) el pragmatismo de Dewey (1952) y el humanismo de Roger (1942). Desde la perspectiva epistemológica, se ubica en el paradigma interpretativo, bajo el enfoque cualitativo, porque toma en cuenta al sujeto que investiga como agente de cambio socioeducativo, se implica en su propio proceso de cambio formativo lo cual, determina el método de investigación como fenomenológica, según Husserl (1934); quien refiere que la descripción, interpretación y la comprensión de los significados y experiencias son tareas propias de la fenomenología Como escenario se seleccionaran las universidades venezolanas. Los sujetos de estudios estarán conformados por cinco actores sociales, seleccionados de manera intencional. Las esencias y las significaciones se apresarán a través de la técnica de la entrevista en profundidad. Las evidencias fenomenológicas se interpretaran siguiendo las pautas de la categorización, triangulación estructuración y contrastación que permitirán configurar una comprensión filosófica epistemológica, axiológica y praxeológica del corpus teórico a partir del pragmatismo y cotidianidad del docente universitario.
Contribuciones del voluntariado en la educación superior
Authors: Claros Moscoso Ingrid Felicidad
Published: November 2023

En este estudio se realizó una revisión sistemática de la literatura para investigar los efectos del voluntariado en la educación superior en el desarrollo personal y profesional de los estudiantes. Se llevó a cabo una exhaustiva búsqueda en bases de datos académicas utilizando palabras clave relevantes, y se seleccionaron artículos que cumplían con los criterios de inclusión predefinidos. La metodología consistió en analizar y sintetizar los hallazgos de los estudios previos sobre el tema, examinando los resultados relacionados con los efectos del voluntariado en el desarrollo personal y profesional de los estudiantes universitarios. Se realizaron análisis cualitativos y se extrajeron los puntos clave de cada estudio para identificar patrones y tendencias. Los resultados de la revisión revelaron que el voluntariado en la educación superior tiene un impacto positivo en el desarrollo integral de los estudiantes, tanto a nivel personal como profesional. Los estudiantes que participaron en actividades de voluntariado experimentaron un crecimiento significativo en habilidades sociales, emocionales y profesionales. En conclusión los hallazgos respaldan la importancia de fomentar el voluntariado entre los estudiantes universitarios como una estrategia eficaz para mejorar su desarrollo personal y profesional. Además, destacan la necesidad de integrar el voluntariado en los programas académicos y promover su participación activa.
Neuroeducación y videojuegos en la educación superior
Authors: Sánchez Almanza Lola
Published: November 2023

En este artículo se analizó el tema de la neuroeducación como una especialidad que ha posibilitado, entre otros el desarrollo de una nueva generación de videojuegos educativos, basados en la predominancia de los hemisferios del cerebro aplicados, a la educación superior. La investigación fue desarrollada con base a un enfoque cualitativo y un tipo de estudio documental, dada la escasa información y aplicación en la educación superior en Bolivia. Las experiencias de este tipo en el ambiente universitario, se han dado a partir de iniciativas particulares de docentes de universidades privadas principalmente. Los resultados confirman el hecho de que el aprendizaje se puede ver enriquecido a través del juego, especialmente de videojuegos educativos creados en un entorno de neuroeducación. A partir de la neuroeducación, se han desarrollado un conjunto de videojuegos, que pueden contribuir de manera sustancial a mejorar la educación superior en Bolivia, debido a que plantean una serie de situaciones que contribuyen al aprendizaje a partir del juego, contribuyendo a complementar y superar procesos de aprendizaje, encarados a partir de la enseñanza convencional.
juego y la expresión corporal del niño en la edad preescolar
Authors: Salazar Arango Edwar , Roca Larrea Estefanny Vanessa , Orrala Rodríguez Esperanza Catalina
Published: November 2023

La investigación está direccionada en la Escuela de Educación Básica Abraham Lincoln, en el nivel preparatorio. Tuvo como propósito determinar la incidencia del uso del juego en el desarrollo de las habilidades expresivas corporales en niños de 5 años de edad. Se sustenta en el paradigma cualitativo con un estudio de campo documental y el análisis descriptivo. La técnica de recolección de información fue la ficha de observación y la encuesta tipo entrevista. Los resultados develaron que aplicar el juego para desarrollar habilidades expresivas permitió al niño conocer su propio cuerpo y expresar sus pensamientos y sentimientos. Dando como beneficio el desarrollo de la comunicación corporal a través de expresiones gestuales, emociones, y promoviendo la creatividad y la imaginación. En conclusión se logra propulsar la evolución integral y tomando en cuenta lo impactante que es aplicarlo en la primera infancia y la repercusión