bluuebunny/crossref_metadata_2025 huggingface dataset:
Infection Prevention and Control Strategies According to the Type of Multidrug-Resistant Bacteria and Candida auris in Intensive Care Units: A Pragmatic Resume including Pathogens R0 and a Cost-Effectiveness Analysis
Authors: Fanelli Chiara , Pistidda Laura , Terragni Pierpaolo , Pasero Daniela
Published: August 2024

Multidrug-resistant organism (MDRO) outbreaks have been steadily increasing in intensive care units (ICUs). Still, healthcare institutions and workers (HCWs) have not reached unanimity on how and when to implement infection prevention and control (IPC) strategies. We aimed to provide a pragmatic physician practice-oriented resume of strategies towards different MDRO outbreaks in ICUs. We performed a narrative review on IPC in ICUs, investigating patient-to-staff ratios; education, isolation, decolonization, screening, and hygiene practices; outbreak reporting; cost-effectiveness; reproduction numbers (R0); and future perspectives. The most effective IPC strategy remains unknown. Most studies focus on a specific pathogen or disease, making the clinician lose sight of the big picture. IPC strategies have proven their cost-effectiveness regardless of typology, country, and pathogen. A standardized, universal, pragmatic protocol for HCW education should be elaborated. Likewise, the elaboration of a rapid outbreak recognition tool (i.e., an easy-to-use mathematical model) would improve early diagnosis and prevent spreading. Further studies are needed to express views in favor or against MDRO decolonization. New promising strategies are emerging and need to be tested in the field. The lack of IPC strategy application has made and still makes ICUs major MDRO reservoirs in the community. In a not-too-distant future, genetic engineering and phage therapies could represent a plot twist in MDRO IPC strategies.
Harnessing Bacteriophages to Combat Antibiotic-Resistant Infections in Africa: A Comprehensive Review
Authors: Fabiyi Kafayath , Sintondji Kevin , Agbankpe Jerrold , Assogba Phenix , Koudokpon Hornel , Lègba Boris , Gbotche Elodie , Baba-Moussa Lamine , Dougnon Victorien
Published: August 2024

The conventional treatment of bacterial infections with antibiotics is becoming increasingly ineffective due to the emergence of multidrug-resistant (MDR) pathogens. This literature review explores the potential of bacteriophages as an alternative or adjunctive therapy to antibiotics in combating MDR infections in Africa. This analysis focuses on current research regarding the integration of phage therapy into African healthcare, highlighting its challenges and opportunities. This review begins with the AMR crisis and the need for new treatments, then covers the history, mechanisms, benefits, and limitations of phage therapy. Key African studies are summarized, identifying major obstacles such as regulatory issues, infrastructure, and research standardization. Research efforts in West Africa that have made notable progress in bacteriophage research are highlighted. This review concludes with recommendations for policymakers, researchers, and healthcare professionals to enhance the development and use of phage therapy in Africa, aiming to reduce antibiotic resistance and improve patient outcomes. By addressing the identified challenges and leveraging the unique advantages of phages, there is potential to significantly mitigate the impact of antibiotic resistance and improve patient outcomes in Africa.
Increasing Fluroquinolone Susceptibility and Genetic Diversity of ESBL-Producing E. coli from the Lower Respiratory Tract during the COVID-19 Pandemic
Authors: Hrovat Katja , Seme Katja , Ambrožič Avguštin Jerneja
Published: August 2024

Lower respiratory tract infections (LRTIs) are the fourth leading cause of death worldwide, among which Escherichia coli (E. coli) pneumonia is considered a rare phenomenon. Treatment options for LRTIs have become limited, especially for extended-spectrum β-lactamase-producing E. coli (ESBL-EC), which are usually resistant to other groups of antimicrobials as well. The aim of our study was to compare the phenotypic resistance profiles and genotypes of ESBL-EC isolates associated with LRTIs before (pre-COVID-19) and during (COVID-19) the COVID-19 pandemic. All isolates were screened for antimicrobial resistance genes (ARGs) and virulence-associated genes (VAGs) and assigned to phylogenetic groups, sequence types and clonal groups by PCR. During the pandemic, a significantly lower proportion of ciprofloxacin-, levofloxacin- and trimethoprim-sulfamethoxazole-resistant ESBL-EC isolates was retrieved from lower respiratory tract (LRT) samples. PCR-based genotypization revealed greater clonal diversity and a significantly lower proportion of isolates with blaTEM, aac(6′)-Ib-cr and qacEΔ1 genes. In addition, a higher proportion of isolates with the integrase gene int1 and virulence genes sat and tsh was confirmed. The lower prevalence of fluoroquinolone resistance and greater genetic diversity of ESBL-EC isolated during the COVID-19 period may have been due to the introduction of new bacterial strains into the hospital environment, along with changes in clinical establishment guidelines and practices.
Rapid Molecular Diagnostics of Pneumonia Caused by Gram-Negative Bacteria: A Clinician’s Review
Authors: Pintea-Simon Ionela-Anca , Bancu Ligia , Mare Anca Delia , Ciurea Cristina Nicoleta , Toma Felicia , Man Adrian
Published: August 2024

With approximately half a billion events per year, lower respiratory tract infections (LRTIs) represent a major challenge for the global public health. Among LRTI cases, those caused by Gram-negative bacteria (GNB) are associated with a poorer prognostic. Standard-of-care etiologic diagnostics is lengthy and difficult to establish, with more than half of cases remaining microbiologically undocumented. Recently, syndromic molecular diagnostic panels became available, enabling simultaneous detection of tens of pathogen-related and antimicrobial-resistance genetic markers within a few hours. In this narrative review, we summarize the available data on the performance of molecular diagnostics in GNB pneumonia, highlighting the main strengths and limitations of these assays, as well as the main factors influencing their clinical utility. We searched MEDLINE and Web of Science databases for relevant English-language articles. Molecular assays have higher analytical sensitivity than cultural methods, and show good agreement with standard-of-care diagnostics regarding detection of respiratory pathogens, including GNB, and identification of frequent patterns of resistance to antibiotics. Clinical trials reported encouraging results on the usefulness of molecular assays in antibiotic stewardship. By providing early information on the presence of pathogens and their probable resistance phenotypes, these assays assist in the choice of targeted therapy, in shortening the time from sample collection to appropriate antimicrobial treatment, and in reducing unnecessary antibiotic use.
Drinking Water and Biofilm as Sources of Antimicrobial Resistance in Free-Range Organic Broiler Farms
Authors: Piccirillo Alessandra , Tolosi Roberta , Mughini-Gras Lapo , Kers Jannigje G. , Laconi Andrea
Published: August 2024

Drinking water distribution systems (DWDSs) represent an ideal environment for biofilm formation, which can harbor pathogenic and antimicrobial-resistant bacteria. This study aimed to assess longitudinally the microbial community composition and antimicrobial resistance (AMR), as determined by 16S rRNA NGS and qPCR, respectively, in drinking water (DW) and biofilm from DWDSs, as well as faeces, of free-range organic broiler farms. The role of DWDSs in AMR gene (ARG) dissemination within the farm environment and transmission to animals, was also assessed. DW and biofilm microbial communities differed from those of faecal samples. Moreover, potentially pathogenic and opportunistic bacteria (e.g., Staphylococcaceae) were identified in water and biofilms. High prevalence and abundance of ARGs conferring resistance to carbapenems (i.e., blaNDM), 3rd and 4th generation cephalosporins (i.e., blaCMY-2), (fluoro)quinolones (i.e., qnrS), and polymyxins (i.e., mcr-3 and mcr-5) were detected in DW, biofilm, and faecal samples, which is of concern for both animal and human health. Although other factors (e.g., feed, pests, and wildlife) may contribute to the dissemination of AMR in free-range organic poultry farms, this study indicates that DWDSs can also play a role.
Method for Assigning Railway Traffic Managers to Tasks along with Models for Evaluating and Classifying
Authors: Restel Franciszek , Haładyn Szymon , Mardeusz Ewa , Starčević Martin , Oziębłowski Mateusz
Published: August 2024

The occurrence of incidences in railway systems leads to impediments and often delays. Because the railway is an anthropotechnical system, two factors are considered as the source of incidents: technical and human. Minimizing adverse incidents in the railway system is the subject of much discussion and research. One of the areas affecting the performance of railway systems is employees. This article presents a method for assigning railway employees to tasks and models for evaluating and classifying railway employees, consisting of two stages. The first stage involves using a survey method and a fuzzy logic model. Each type of service is assigned feature values, obtaining three parameterized employee-role profiles for the train traffic officer. In the second stage, the participant goes through two of the three available evaluation scenarios, during which errors made during the tasks are counted. Validation results of the proposed approach indicate that the method is 87% effective.
Maintenance 4.0 Technologies for Sustainable Manufacturing
Authors: Jasiulewicz-Kaczmarek Małgorzata
Published: August 2024

Manufacturing companies are navigating two pivotal trends that significantly impact their operations: sustainability and digitalization [...]
A Semi-Analytical Solution of Two-Dimensional Unsteady Groundwater Flow Outside a Long-Strip Excavation Pit with a Cut-Off Wall
Authors: Chang Yinsheng , Lv Le , Wang Xudong , Xu Jin
Published: August 2024

In deep excavation engineering, the implementation of cut-off walls stands as a crucial measure to ensure structural support stability. However, the existing theories for dewatering design often overlook the variations in cut-off wall penetration depths, potentially compromising the efficacy of groundwater control strategies. Addressing this gap, this study conducts a comprehensive investigation into the dynamics of groundwater levels within confined aquifers during the dewatering process of strip excavation pits with cut-off walls. Central to this inquiry is the conceptualization of the entire excavation pit as a singular large-diameter well, with the open part beneath the cut-off wall in the confined aquifer serving as a constant-flux boundary. Employing an advanced analytical modeling approach, the study formulates a robust framework to describe the intricate interplay of unsteady groundwater flow phenomena. Leveraging the techniques of the Laplace and finite cosine transform methods, a semi-analytical solution is derived to elucidate groundwater drawdown patterns over time. The validation of the proposed solution against finite element method results underscores its fidelity and applicability. The parametric analysis reveals a dynamic evolution in drawdown characteristics within the confined aquifer, transitioning from initially cone-shaped distributions to more linear profiles that eventually stabilize with prolonged dewatering. This evolution is governed by the aquifer’s inherent anisotropy and the barrier effect exerted by the depth of cut-off wall penetration. The parametric research also underscores the critical role of lateral boundary distance in influencing groundwater drawdown patterns. The presented solutions can be used to identify optimal penetration depth ratios tailored to specific parameters, thereby offering insights for optimizing dewatering strategies for deep excavation groundwater control. Moreover, a case study was included in this study using the proposed analytical solution, and a comparison was made with field data to validate the practical applicability of the approach.
Analytical Investigation of the Effects of Additional Load Mass on the Fundamental Frequency of Pedestrian Beam Bridges
Authors: Spasojević Šurdilović Marija , Zorić Andrija , Živković Srđan , Turnić Dragana
Published: August 2024

The aspect of resonant vibrations due to pedestrian movement is of great significance in engineering practice. Therefore, understanding the variations in the natural frequency of bridge structures under varying positions of additional mass is of particular interest. This paper presents a procedure for the straightforward determination of the natural frequencies of a beam pedestrian bridge for various positions of pedestrians or a service vehicle based on derived analytical solutions. The calculation takes into account the inertial effects of the additional load mass, modeled as either uniformly distributed or concentrated. The importance of additional load mass effects on the fundamental frequency of a beam pedestrian bridge and its dynamic response to a moving pedestrian load is demonstrated on a bridge example. The proposed solutions are also applicable to other girder system structures with uniform mass and stiffness along their span.
High-Resolution Identification of Sound Sources Based on Sparse Bayesian Learning with Grid Adaptive Split Refinement
Authors: Pan Wei , Feng Daofang , Shi Youtai , Chen Yan , Li Min
Published: August 2024

Sound source identification technology based on a microphone array has many application scenarios. The compressive beamforming method has attracted much attention due to its high accuracy and high-resolution performance. However, for the far-field measurement problem of large microphone arrays, existing methods based on fixed grids have the defect of basis mismatch. Due to the large number of grid points representing potential sound source locations, the identification accuracy of traditional grid adjustment methods also needs to be improved. To solve this problem, this paper proposes a sound source identification method based on adaptive grid splitting and refinement. First, the initial source locations are obtained through a sparse Bayesian learning framework. Then, higher-weight candidate grids are retained, and local regions near them are split and updated. During the iteration process, Green’s function and the source strength obtained in the previous iteration are multiplied to get the sound pressure matrix. The robust principal component analysis model of the Gaussian mixture separates and replaces the sound pressure matrix with a low-rank matrix. The actual sound source locations are gradually approximated through the dynamically adjusted sound pressure low-rank matrix and optimized grid transfer matrix. The performance of the method is verified through numerical simulations. In addition, experiments on a standard aircraft model are conducted in a wind tunnel and speakers are installed on the model, proving that the proposed method can achieve fast, high-precision imaging of low-frequency sound sources in an extensive dynamic range at long distances.
Modeling and Testing of ESD Protective Textiles
Authors: Hałgas Stanisław , Wilbik-Hałgas Bożena , Sidyk Piotr
Published: August 2024

This article discusses the important issue of designing textiles for electrostatic discharge (ESD) protection. ESD protective textiles are used to prevent the failure of electronic circuits. They also safeguard human health and life in explosive environments. The textiles are usually made of woven, knitted, or nonwoven fabrics incorporating a grid or strips of conductive fibers within a base material made of cotton, polyester, or blends of these materials. Various testing standards have been developed to evaluate the suitability of textiles for ESD protection. One of the most widely used is the EN 1149-3 standard, which outlines procedures for recording charge decay plots. The procedure can be used to evaluate all types of textiles. This paper discusses models corresponding to the standard developed in the general-purpose COMSOL Multiphysics software. Using the advanced numerical methods of the software, it is possible to graphically present the phenomena occurring during the application of the standard procedure and to determine the influence of the grid and material parameters on the shape of the charge decay plots. Furthermore, this article compares charge decay plots and shielding effectiveness measured in an accredited laboratory with simulation results.
Behaviour Analysis of Beam-Type Timber and Timber-Concrete Composite Panels
Authors: Briuka Elza , Serdjuks Dmitrijs , Akishin Pavel , Sahmenko Genadijs , Podkoritovs Andrejs , Ozolins Raimonds
Published: August 2024

This study addresses the enhancement of material efficiency and reduction in brittleness in timber-to-concrete adhesive connections for beam-type timber and timber-concrete composite panels. The research explores the potential benefits of adding longitudinal timber ribs to cross-laminated timber (CLT) beam-type panels. Three groups of flexure-tested specimens were analysed as follows: (1) timber panels (1400 mm × 400 mm) with two 100 mm thick CLT panels and two 60 mm thick CLT panels reinforced with 150 × 80 mm timber ribs; (2) eight specimens (600 mm × 100 mm × 150 mm) with CLT members (600 mm × 100 mm × 100 mm) connected to a 50 mm concrete layer using granite chips and Sikadur-31 (AB) epoxy adhesive; (3) six CLT panels (1400 mm × 400 mm × 50 mm) bonded to a 50 mm concrete layer, with two panels containing polypropylene microfibres and two panels incorporating polyethene dowels for mechanical connection. Specimens were subjected to three-point bending tests and analysed using the transformed section method, γ-method, and finite element method with ANSYS 2023R2 software. Results indicated a 53% increase in load-carrying capacity for ribbed CLT panels with no additional material consumption, a 24.8–41.1% increase for CLT panels strengthened with a concrete layer, and improved ductility and prevention of disintegration in timber-concrete composites with polypropylene microfibres.
Promoting Environmental Sustainability: The Role of Renewable Energy Systems and Environmental Taxes
Authors: He Yugang
Published: August 2024

This study examines the effects of renewable energy consumption and environmental taxes on CO2 emissions in OECD countries from 1990 to 2022, employing the cross-sectional autoregressive distributed lag (CS-ARDL) approach. The findings reveal that both renewable energy consumption and environmental taxes significantly reduce CO2 emissions in both the short and the long term, emphasizing their crucial roles in climate change mitigation and sustainability promotion. Furthermore, this study identifies that industrialization and urbanization contribute to increased emissions, whereas foreign direct investment aids in emission reduction through the facilitation of green technology transfer. Economic growth is initially associated with higher emissions, but this trend reverses as economies mature and adopt sustainable practices. These results highlight the importance of continuous investment in renewable energy infrastructure and the implementation of robust environmental tax policies to achieve long-term sustainability goals. The integration of environmental considerations into economic and urban planning, along with leveraging foreign direct investment for technological advancements, is imperative for balancing economic growth with the necessity to reduce carbon emissions and effectively address climate change. This research provides a better understanding of the diverse factors influencing CO2 emissions and offers critical insights for policymakers.
Energy Evolution Characteristics and Hydraulic Fracturing Roof Cutting Technology for Hard Roof Working Face during Initial Mining: A Case Study
Authors: Wang Chungang , Bai Jianbiao , Wang Tianchen , Wu Wenda
Published: August 2024

In the process of mining, a large area of hard roof will be exposed above a goaf and may suddenly break. This can easily induce rock burst and has a significant impact on production safety. In this study, based on the engineering background of the hard roof of the 2102 working face in the Balasu coal mine, the spatial and temporal characteristics of the strain energy of the roof during the initial mining process were explored in depth. Based on a theoretical calculation, it is proposed that hydraulic fracturing should be carried out in the medium-grained sandstone layer that is 4.8–22.43 m above the roof, and that the effective fracturing section in the horizontal direction should be within 30.8 m of the cutting hole of the working face. The elastic strain energy fish model was established in FLAC3D to analyze the strain energy accumulation of the roof during the initial mining process. The simulation and elastic strain energy results show that, as the working face advances to 70–80 m, the hard roof undergoes significant bending deformation. The energy gradient increases with the rapid accumulation of strain energy to a peak value of 140.54 kJ/m3. If the first weighting occurs at this moment in time, the sudden fracture of the roof will be accompanied by the release of elastic energy, which will induce rock burst. Therefore, it is necessary to implement roof cutting and pressure relief before reaching the critical step of 77 m. To this end, the comprehensive hydraulic fracturing technology of ‘conventional short drilling + directional long drilling’ is proposed. A field test shows that the hydraulic fracturing technology effectively weakens the integrity of the rock layer. The first weighting interval is 55 m, and it continues until the end of the pressure at the 70 m position. The roof collapses well, and the mining safety is improved. This study provides an important reference for hard roof control.
A Multiproject and Multilevel Plan Management Model Based on a Hybrid Program Evaluation and Review Technique and Reinforcement Learning Mechanism
Authors: Wang Long , Liu Haibin , Xia Minghao , Wang Yu , Li Mingfei
Published: August 2024

It is very difficult for manufacturing enterprises to achieve automatic coordination of multiproject and multilevel planning when they are unable to make large-scale resource adjustments. In addition, planning and coordination work mostly relies on human experience, and inaccurate planning often occurs. This article innovatively proposes the PERT-RP-DDPGAO algorithm, which effectively combines the program evaluation and review technique (PERT) and deep deterministic policy gradient (DDPG) technology. Innovatively using matrix computing, the resource plan (RP) itself is used for the first time as an intelligent agent for reinforcement learning, achieving automatic coordination of multilevel plans. Through experiments, this algorithm can achieve automatic planning and has interpretability in management theory. To solve the problem of continuous control, the second half of the new algorithm adopts the DDPG algorithm, which has advantages in convergence and response speed compared to traditional reinforcement learning algorithms and heuristic algorithms. The response time of this algorithm is 3.0% lower than the traditional deep Q-network (DQN) algorithm and more than 8.4% shorter than the heuristic algorithm.
The Impact of Exercise Order on Velocity Performance in the Bench Press and the Squat: A Comparative Study
Authors: Pereira Rogério Martins , Marques Diogo Luís , Alves Ana Ruivo , Marinho Daniel Almeida , Neves Pedro Pombo , Silva António José , Neiva Henrique Pereira
Published: August 2024

We analyzed the influence of exercise order using the bench press and squat as the first or second exercise of the session on velocity performance. Ten male trained individuals (20.9 ± 0.7 years) randomly performed two protocols of three sets of six repetitions at 80% of their one-repetition maximum with different exercise sequences: the bench press followed by the squat (BP + S) and the squat followed by the bench press (S + BP). A linear velocity transducer attached to the Smith machine barbell measured the mean propulsive velocity (MPV), peak velocity (PV), and time to peak velocity. Additionally, blood lactate and heart rate were measured. Regarding the bench press, differences were found in the MPV in the first (BP + S: 0.50 ± 0.07 m·s−1 vs. S + BP: 0.42 ± 0.08 m·s−1; p = 0.03, g = 0.72) and second sets (0.50 ± 0.06 m·s−1 vs. 0.42 ± 0.07 m·s−1; p = 0.03, g = 0.73), and in the PV in the second set (0.74 ± 0.09 m·s−1 vs. 0.63 ± 0.09 m·s−1; p = 0.02, g = 0.86). Regarding the squat, although the S + BP sequence tended to show higher velocities, no significant differences were found between protocols. These results showed that squatting first decreased subsequent bench press velocity performance. On the other hand, squat velocity performance was not impaired when preceded by the bench press.
Modifications to ArduSub That Improve BlueROV SITL Accuracy and Design of Hybrid Autopilot
Authors: Ng Patrick , Krieg Michael
Published: August 2024

Improvements to ArduSub for the BlueROV2 (BROV2) Heavy, necessary for accurate simulation and autonomous controller design, were implemented and validated in this work. The simulation model was made more accurate with new data obtained from real-world testing and values from the literature. The manual control algorithm in the BROV2 firmware was replaced with one compatible with automatic control. In a Robot Operating System (ROS), a proportional–derivative (PD) controller to assist augmented reality (AR) pilots in controlling angular degrees of freedom (DOF) of the vehicle was implemented. Open-loop testing determined the yaw hydrodynamic model of the vehicle. A general mathematical method to determine PD gains as a function of the desired closed-loop performance was outlined. Testing was carried out in the updated simulation environment. Step response testing found that a modified derivative gain was necessary. Comparable real-world results were obtained using settings determined in the simulation environment. Frequency response testing of the modified yaw control law discovered that the bandwidth of the nonlinear system had a one-to-one correspondence with the desired closed-loop natural frequency of a simplified linear approximation. The control law was generalized for angular DOF and linear DOF were operated with open-loop control. A full six-DOF simulated dive demonstrated excellent tracking.
Explainable AI (XAI) Techniques for Convolutional Neural Network-Based Classification of Drilled Holes in Melamine Faced Chipboard
Authors: Sieradzki Alexander , Bednarek Jakub , Jegorowa Albina , Kurek Jarosław
Published: August 2024

The furniture manufacturing sector faces significant challenges in machining composite materials, where quality issues such as delamination can lead to substandard products. This study aims to improve the classification of drilled holes in melamine-faced chipboard using Explainable AI (XAI) techniques to better understand and interpret Convolutional Neural Network (CNN) models’ decisions. We evaluated three CNN architectures (VGG16, VGG19, and ResNet101) pretrained on the ImageNet dataset and fine-tuned on our dataset of drilled holes. The data consisted of 8526 images, divided into three categories (Green, Yellow, Red) based on the drill’s condition. We used 5-fold cross-validation for model evaluation and applied LIME and Grad-CAM as XAI techniques to interpret the model decisions. The VGG19 model achieved the highest accuracy of 67.03% and the lowest critical error rate among the evaluated models. LIME and Grad-CAM provided complementary insights into the decision-making process of the model, emphasizing the significance of certain features and regions in the images that influenced the classifications. The integration of XAI techniques with CNN models significantly enhances the interpretability and reliability of automated systems for tool condition monitoring in the wood industry. The VGG19 model, combined with LIME and Grad-CAM, offers a robust solution for classifying drilled holes, ensuring better quality control in manufacturing processes.
Study on the Fluctuating Load Characteristics of the Submerged Radial Gate in the High-Head Flood Discharge Outlet
Authors: Lu Xiudi , Liu Yakun , Tan Shoulin , Bao Wei , Lu Yangliang , Zhao Xinmeng
Published: August 2024

The fluctuating pressure acting on the radial gate in the high-head flood discharge outlet is the main excitation source of flow-induced vibration. Therefore, this paper delves into the distribution characteristics of fluctuating pressure on the panel of the high-head submerged radial gate based on hydraulic model tests. Hydraulic tests were first conducted to obtain the distribution patterns of time-averaged pressure and the root mean square (RMS) of fluctuating pressure on the radial gate panel. Secondly, the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and HHT method was employed to identify the causes of the fluctuating pressure on the gate panel. Finally, the ICEEMDAN-SSA (the sparrow search algorithm)–LSTM (long short-term memory) method was utilized to achieve accurate prediction of the fluctuating pressure on the gate panel. The results show that the time-averaged pressure in the middle of the gate panel is higher than that at the top and near the bottom edge, which differs significantly from the static pressure distribution. The RMS of the fluctuating pressure near the bottom edge is higher than that in the middle and at the top. The fluctuating pressure acting on the gate panel in the time domain can be regarded as a stationary process. The fluctuating pressure on the gate panel is caused by the combined diffusion and random mixing of multi-scale vortices in the turbulent eddy structure. The ICEEMDAN-SSA-LSTM combined method significantly improves the prediction accuracy of fluctuating pressure on the gate panel compared to the LSTM and ICEEMDAN-LSTM methods.
Construction and Evaluation of Pepper Core Collection Based on Phenotypic Traits and SSR Markers
Authors: Deng Qin , Zhao Shuniu , Guan Congcong , Fu Genying , Yu Shuang , Lin Shisen , Wang Zhiwei , Fu Huizhen , Lu Xu , Cheng Shanhan
Published: August 2024

To streamline germplasm preservation, enhance resource utilization, and improve breeding efficiency, a core germplasm bank was established using 24 phenotypic traits and DNP markers from 155 pepper resources across various regions. Selection of the optimal core germplasm was based on intra-group retention ratio, overall retention scale, and intra-group stepwise clustering retention. Evaluation of phenotypic trait data for the core germplasm utilized mean, variance, range, and coefficient of variation, with principal component analysis confirming the selection. For molecular evaluation, the core germplasm pre-selection plan was based on SSR clustering, allele retention ratio, and Shannon-Weaver diversity index. This approach resulted in a core germplasm of 41 resources, including 6 var. fasciculatum, 7 var. grossum, 3 var. cerasiorme, 6 var. conoides, and 19 var. longum, representing the maximum phenotypic retention and genetic diversity of the 155 pepper resources. Additionally, a core germplasm of 32 resources was generated based on SSR markers, retaining all 54 polymorphic loci. By integrating phenotypic and molecular core collections, a combined core collection of 57 varieties was developed. This collection achieved a 92.55% phenotype retention ratio and a 100% polymorphism site retention ratio. With a 90% compression ratio, it encapsulates the broad genetic diversity of the original germplasm, serving as a comprehensive resource for further research and breeding applications.
Understanding the User Experience of Lumbar-Support-Assistive Devices in Lower-Back Pain Patients: Design Recommendations
Authors: Chen Zibin , Zhang Meng , Zhang Xi , Liu Chenyang , Wang Huize
Published: August 2024

A positive user experience is crucial for enhancing user adherence throughout the utilization of lumbar-support-assistive devices (LSAD). However, there is a lack of research for optimal user experience with LSAD in the existing literature. Therefore, this study aims to explore how patients with lower-back pain use LSAD and assess their satisfaction and overall experience. Based on this, we aim to provide design improvement recommendations for LSAD to researchers in the relevant field. Through in-depth interviews with 14 LSAD users, key themes were identified using reflexive thematic analysis. The results indicate that participants were “somewhat satisfied” with the overall experience with their LSAD. The key factors influencing the LSAD-wearing experience were: (1) key design challenges in improving LSAD (stability, fit and, comfort), (2) providing necessary assistance (potential barriers and prompts), and (3) individualizing needs and balance of design (aesthetics, dimensions, safety, and cleanliness). All participants reported that poor stability, fit, and comfort of LSAD were the main reasons for an adverse experience. It is worth noting that users may encounter potential barriers when initially using LSAD. Furthermore, younger participants perceived pressure related to appearance and expressed concerns about the exposure of their health privacy during social interactions involving the LSAD. Based on these findings, we have proposed a set of comprehensive LSAD design-improvement recommendations, which serve as a foundational reference for future improvements.
Physicochemical Characterization of Carao Honey Flour (Cassia grandis) and Its Effects on the Sensory Attributes in a Cookie
Authors: Fuentes Jhunior Marcía , de Jesús Álvarez Gil Manuel , Zumbado Fernández Héctor , Montero-Fernández Ismael , Martín-Vertedor Daniel , Yadav Ajitesh , Aleman Ricardo S.
Published: August 2024

Carao honey is a potential functional ingredient that can generate added value to food products enriched by reducing waste. In many countries, carao has been utilized for therapeutic purposes since this type of plant extract can inhibit the growth against the most common dermatophytes, a pathogenic fungus that grows on the skin, mucous membranes, hair, nails, feathers, and other body surfaces, causing ringworm and related diseases. The physicochemical characteristics of the cookies were also investigated, which included aW, proximate analysis, hardness, and color. A sensory study was carried out to determine the rejection threshold, acceptability, purchase intent, and general taste of 90 consumers. The gluten-free cookies were prepared with carao honey as a partial substitute for rice flour in different percentages (0%, 2.5%, 5%, and 10%). The carao honey proximate composition, rheological properties, and pasting properties were analyzed. It was emphasized that incorporating carao honey into cookies improves the ingredient’s sustainability. The impact of carao on the physicochemical and sensory properties of cookies was evident in color, flavor, and smell. According to the results, only samples with 2.5% carao were accepted regarding flavor and smell. Overall, liking scores, age, and flavor were the most significant predictors of purchase intent. The information given to panelists did not significantly (p < 0.05) influence liking scores only for cookies. According to physicochemical analysis, carao honey flour was high in carbohydrates (88%). The incorporation of carao produced cookies with darker colors and a softer texture. The study demonstrated that carao flour could be included to produce sensorial accepted cookies at a 2.5% addition level as an alternative in the food industry that benefits from environmental sustainability and, at the nutritional level, improves the availability of nutrients, mainly sugars and proteins.
Influence of the Initial Prestress Level on the Distribution of Regions of Dynamic Instability of Geiger Domes
Authors: Obara Paulina , Solovei Maryna
Published: August 2024

This paper provides a parametric analysis of cable–strut tensegrity domes subjected to periodic loads. This analysis aims at determining the main regions of dynamic instability (unstable regions). From the point of view of the physical interpretation of the phenomenon, if the load occurs in these regions, the amplitudes of the resulting vibrations increase, posing a risk to the durability of the structures. The consideration includes cable–strut structures called Geiger domes. Four dome design solutions known from the literature are compared, i.e., regular (patented by Geiger) and modified domes with a closed and an open upper section. In contrast to conventional cable–strut structures, Geiger domes are characterized by a self-equilibrated system of internal forces (initial prestress), which affects the shape and range of unstable regions. The main purpose is to answer the question as to which type of design solution is more sensitive to the risk of excitation vibrations. A nondimensional parameter λ is introduced for this quantitative assessment. This parameter reliably determines the change in the area of unstable regions as the initial prestress level increases. The range of the parameter λ is defined as a value between 1 and 0. In the case of λ=1, there is potential for the excitation of unstable motion, whereas in the case of λ=0, such a risk is absent. The analysis presented in this paper can be employed in the process of optimizing the initial prestress level, which will constitute the subsequent stage of this research. A geometrically non-linear model is used to evaluate the behavior of the considered structures.
Virtual Reality Immersive Simulations for a Forensic Molecular Biology Course—A Quantitative Comparative Study
Authors: Ewais Ahmed , Mystakidis Stylianos , Khalilia Walid , Diab Shadi , Christopoulos Athanasios , Khasib Said , Yahya Baha , Hatzilygeroudis Ioannis
Published: August 2024

Molecular biology is a complex, abstract, subject that can be challenging for higher education students to comprehend. The current manuscript describes the design, implementation, and evaluation of two immersive VR simulations of a DNA lab and a crime scene investigation (CSI) for a forensic molecular biology course in the context of the “TESLA” Erasmus+ project. It illustrates the instructional design and technical aspects of the VR simulations’ development. The experimental study employed a comparative quantitative research design. The guiding research questions examined how instructional modalities (online vs. face-to-face) affect learners’ perceptions of VR-based training in higher education and the key factors influencing learners’ intention for their adoption. Forty-six (n = 46) undergraduate students completed a 17-item questionnaire, which served as the main data collection instrument. Results demonstrate that both online and face-to-face VR-based instruction can effectively convey core concepts, thus challenging the traditional notion that face-to-face interaction is inherently superior. Its implications underscore the potential of VR simulations to supplement or even substitute traditional teaching methods, particularly for complex science subjects.
Effects of Allium ursinum L. Leaves and Egg Amount on Quality Attributes, Polyphenol Content, and Antioxidant Capacity of Pasta
Authors: Rosan Cristina Adriana , Bei Mariana Florica , Tocai (Moţoc) Alexandra Cristina , Gitea Manuel Alexandru , Vicas Simona Ioana
Published: August 2024

Pastas enriched with vegetables are premium nutritious products and their consumption can bring significant health benefits. Recent studies have reported a high content of bioavailable phytochemical compounds in Allium ursinum L.; as such, it can be used in the development of functional food products. This study involved the evaluation of 10 varieties of pasta. Five of these varieties were made from white flour and varying amounts of egg (Ctrl_1–Ctrl_5). The other five varieties (AU_1–AU_5) contained fresh shredded wild garlic leaves in equal proportions (20 g) in addition to the corresponding ingredients (white flour and egg). All pasta variants were investigated for their cooking properties and the presence of bioactive compounds and antioxidant capacity in the raw and cooked pasta. Sensory analysis was conducted on all types of cooked pasta, and results indicated that the pasta with the least quantity of eggs was the most favoured variant. Additionally, the pasta that was enhanced with wild garlic leaves received the highest rating for “overall quality”. According to our results, the optimal cooking time (OCT) increased when the quantity of eggs was raised, but when wild garlic leaves were present, OCT decreased in comparison to the control samples. A significant decrease (p < 0.05) in the cooking parameters, swelling index, and water absorption was observed in both egg pasta (Ctrl) and egg pasta enriched with A. ursinum L. (AU). However, compared to the corresponding egg pasta, the presence of wild garlic in pasta generally produced higher values in SI and WA. Pastas enriched with wild garlic are rich in polyphenols (TPh), with a content ranging from 82.44 to 94.62 µg GAE/g dw, and also exhibit antioxidant properties. The amount of total polyphenol significantly decreases (p < 0.05) during cooking varies depending on the composition of the pasta. The pasta with the highest egg content (AU_5) had the lowest loss of polyphenols, equivalent to 55.35%. Our investigations indicate that producing pasta with eggs and fresh wild garlic leaves results in a valuable food product with a good sensory score, enriched in bioactive components, with essential nutrients that maintains cooking qualities.
The Possibility of Detrimental Effects on Soil–Structure Interaction in Seismic Design Due to a Shift in System Frequency
Authors: Tao Weifeng , Fu Jia , Li Yugang
Published: August 2024

Soil–structure interaction (SSI) leads to a modification in the dynamic properties of structure, but due to the complexity of analysis, it is traditionally assumed in seismic designs that the structure is fixed-supported on the ground, which brings about potential risks to the seismic performances of structure. The study works on the possibility of SSI having detrimental effects by comparing the dynamic responses of the SSI system to a fixed-base structure, and presents charts for an evaluation of the system frequency of SSI for the purpose of engineering practice. In order to reveal the physical nature, the SSI model is reduced to its simplest form, consisting of a SDOF oscillator, a three-dimensional rectangular foundation, and a multi-layered half-space. The energy dissipation in the soil is achieved by foundation impedances and the substructure method. Previously, the foundation impedances are usually acquired by two-dimensional or axisymmetric three-dimensional models in uniform half-space to avoid the high cost of the more realistic, fully 3D models, while a high-precision indirect boundary element method is employed, combined with the non-singular Green’s functions of distributed loads to calculate the foundation impedances. Although SSI dampens the peak amplitude of structure response in the frequency domain, case studies on four buildings’ responses to 42 earthquakes in the time history show a possibility of 15–20% that SSI amplifies the dynamic responses of structures, such as the maximum and the mean values in the time history, depending on the properties of the structures and the site, as well as the frequency component of incident waves.
Fusion Network for Aspect-Level Sentiment Classification Based on Graph Neural Networks—Enhanced Syntactics and Semantics
Authors: Li Miaomiao , Lei Yuxia , Zhou Weiqiang
Published: August 2024

Aspect-level sentiment classification (ALSC) struggles with correctly trapping the aspects and corresponding sentiment polarity of a statement. Recently, several works have combined the syntactic structure and semantic information of sentences for more efficient analysis. The combination of sentence knowledge with graph neural networks has also proven effective at ALSC. However, there are still limitations on how to effectively fuse syntactic structure and semantic information when dealing with complex sentence structures and informal expressions. To deal with these problems, we propose an ALSC fusion network that combines graph neural networks with a simultaneous consideration of syntactic structure and semantic information. Specifically, our model is composed of a syntactic attention module and a semantic enhancement module. First, the syntactic attention module builds a dependency parse tree with the aspect term being the root, so that the model focuses better on the words closely related to the aspect terms, and captures the syntactic structure through a graph attention network. In addition, the semantic enhancement module generates the adjacency matrix through self-attention, which is processed by the graph convolutional network to obtain the semantic details. Lastly, the extracted features are merged to achieve sentiment classification. As verified by experiments, the model we propose can effectively enhance ALSC’s behavior.
Empirical Research on AI Technology-Supported Precision Teaching in High School Science Subjects
Authors: Hao Miaomiao , Wang Yi , Peng Jun
Published: August 2024

The empowerment of educational reform and innovation through AI technology has become a topic of increasing interest in the field of education. The advent of AI technology has made comprehensive and in-depth teaching evaluation possible, serving as a significant driving force for efficient and precise teaching. There were few empirical studies on the application of high-quality precision teaching models in the field of compulsory education, and the learning difficulty of technology and the teaching burden on teachers have become significant factors hindering the use of technology to support education. This study analyzed teaching models from the perspectives of teachers’ teaching burdens and students’ learning obstacles, and was committed to relying on intelligent technology to construct a new precision teaching model, an educational diagnosis–feedback–intervention path that covered the entire teaching process, from the dimensions of teacher behavior, student behavior, and parent behavior, aiming to assist teachers in efficient teaching and students in personalized learning. This study was conducted with nine science classes, including about 540 people in the second year of high school at a Middle School in China; six classes were the intervention groups while the last three classes were control groups, and a survey of 19 teachers from the intervention classes was carried out. The results showed that this model can significantly improve students’ academic performance in science subjects, especially in mathematics and chemistry. It has increased the proportion of high-achieving students, reduced the proportion of low-achieving students, stimulated students’ self-directed learning ability, cultivated a positive attitude towards science learning, and explained the key points of using a precision teaching model in different disciplines. It has achieved a deep integration of education and technology, helping to increase the efficiency and reduce the burden of teaching.