bluuebunny/crossref_metadata_2025 huggingface dataset:
Herd Level Yield Gap Analysis in a Local Scale Dairy Farming System: A Practical Approach to Discriminate between Nutritional and Other Constraining Factors
Authors: Andrighetto Igino , Serva Lorenzo , Fossaluzza Davide , Marchesini Giorgio
Published: February 2023

This study performed a yield gap analysis to help farmers understand whether their constraints were mainly due to nutritional factors or management and health issues. Twenty-nine farms were periodically evaluated. Milk yield (MY), dry matter intake (DMI), total mixed ration (TMR) composition and homogeneity index (HI), TMR digestibility, income over feed cost (IOFC), and MY summer–winter ratio (SWR) were collected. Farms were divided and compared according to the average annual MY: Low (L), Medium (M) and High (H), characterised by <31.1, 31.1–36.7 and >36.7 kg/head/day. An ANOVA mixed model and a stepwise regression to assess the relationship between nutritional variables and MY were run. H farms showed higher IOFC (p < 0.001), DMI (p = 0.006), DDM (p < 0.001), digestible crude protein (DCP, p = 0.019), HI (p = 0.09), SWR (p = 0.041) and lower HI coefficient of variation (p = 0.04). The conversion of DDM into milk was higher in H and M farms. Stepwise regression for MY selected DDM and CP (R2 = 0.716, p < 0.05). M farms were mainly constrained by nutritional factors, whereas L farms were also affected by other factors such as those related to management and health.
Evolution of Antimicrobial Susceptibility to Penicillin in Invasive Strains of Streptococcus pneumoniae during 2007–2021 in Madrid, Spain
Authors: de Miguel Sara , Pérez-Abeledo Marta , Ramos Belén , García Luis , Arce Araceli , Martínez-Arce Rodrigo , Yuste Jose , Sanz Juan Carlos
Published: February 2023

The use of pneumococcal conjugate vaccines has affected the epidemiology and distribution of Streptococcus pneumoniae serotypes causing Invasive Pneumococcal Disease (IPD). The aim of this study was to analyze the evolution of the phenotypical profiles of antimicrobial susceptibility to penicillin (PEN) in all IPD strains isolated in Madrid, Spain, during 2007–2021. In total, 7133 invasive clinical isolates were characterized between 2007 and 2021. Levels of PENR and PNSSDR were 2.0% and 24.2%, respectively. In addition, 94.4% of all the PENR belonged to four serotypes, including 11A (33.6%), 19A (30.8%), 14 (20.3%) and 9V (9.8%). All the strains of serotype 11A, which is a non-PCV13 serotype, were detected after the year 2011. Serotypes 6C, 15A, 23B, 24F, 35B, 19F, 16F, 6B, 23F, 24B, 24A, 15F and a limited number of strains of serogroups 16 and 24 (non-typed at serotype level) were associated with PNSSDR (p < 0.05). PNSSDR strains of non-PCV13 serotypes 11A, 24F, 23B, 24B, 23A and 16F were more frequent from 2014 to 2021. The changes in S. pneumoniae serotype distribution associated with the use of conjugate vaccines had caused in our region the emergence of non-PCV13 pneumococcal strains with different PENR or PNSSDR patterns. The emergence of serotype 11A resistant to penicillin as the most important non-PCV13 serotype is a worrisome event with marked relevance from the clinical and epidemiological perspective.
Amelioration Strategies for Silver Diamine Fluoride: Moving from Black to White
Authors: Almuqrin Amjad , Kaur Inder Preet , Walsh Laurence J. , Seneviratne Chaminda Jayampath , Zafar Sobia
Published: February 2023

Topical cariostatic agents have become a reasonable alternative for managing dental caries in young children. Silver diamine fluoride (SDF) is a practical topical approach to arrest caries and avoid extensive and risky dental treatment. However, the literature demonstrates a parental hesitation towards accepting SDF because of black unaesthetic tooth discolouration following application. The rapid oxidation of ionic silver darkens demineralised tooth structure permanently. In this regard, nano-metallic antimicrobials could augment or substitute for silver, and thereby enhance SDF aesthetic performance. Recently, biomedical research has drawn attention to selenium nanoparticles (SeNPs) due to their antimicrobial, antioxidant, and antiviral potencies. Various in vitro studies have examined the effect of SeNPs on the virulence of bacteria. This narrative review explores practical issues when using SDF and suggests future directions to develop it, focusing on antimicrobial metals. Several methods are described that could be followed to reduce the discolouration concern, including the use of nanoparticles of silver, of silver fluoride, or of selenium or other metals with antimicrobial actions. There could also be value in using remineralising agents other than fluoride, such as NPs of hydroxyapatite. There could be variations made to formulations in order to lower the levels of silver and fluoride in the SDF or even to replace one or both of the silver and fluoride components completely. Moreover, since oxidation processes appear central to the chemistry of the staining, adding SeNPs which have antioxidant actions could have an anti-staining benefit; SeNPs could be used for their antimicrobial actions as well. Future research should address the topic of selenium chemistry to optimise how SeNPs would be used with or in place of ionic silver. Incorporating other antimicrobial metals as nanoparticles should also be explored, taking into account the optimal physicochemical parameters for each of these.
Implementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill Patients
Authors: Mena Manuel , Garcia Julio-Cesar , Bustos Rosa-Helena
Published: February 2023

In individualized therapy, the Bayesian approach integrated with population pharmacokinetic models (PopPK) for predictions together with therapeutic drug monitoring (TDM) to maintain adequate objectives is useful to maximize the efficacy and minimize the probability of toxicity of vancomycin in critically ill patients. Although there are limitations to implementation, model-informed precision dosing (MIPD) is an approach to integrate these elements, which has the potential to optimize the TDM process and maximize the success of antibacterial therapy. The objective of this work was to present an app for individualized therapy and perform a validation of the implemented vancomycin PopPK models. A pragmatic approach was used for selecting the models of Llopis, Goti and Revilla for developing a Shiny app with R. Through ordinary differential equation (ODE)-based mixed effects models from the mlxR package, the app simulates the concentrations’ behavior, estimates whether the model was simulated without variability and predicts whether the model was simulated with variability. Moreover, we evaluated the predictive performance with retrospective trough concentration data from patients admitted to the adult critical care unit. Although there were no significant differences in the performance of the estimates, the Llopis model showed better accuracy (mean 80.88%; SD 46.5%); however, it had greater bias (mean −34.47%, SD 63.38%) compared to the Revilla et al. (mean 10.61%, SD 66.37%) and Goti et al. (mean of 13.54%, SD 64.93%) models. With respect to the RMSE (root mean square error), the Llopis (mean of 10.69 mg/L, SD 12.23 mg/L) and Revilla models (mean of 10.65 mg/L, SD 12.81 mg/L) were comparable, and the lowest RMSE was found in the Goti model (mean 9.06 mg/L, SD 9 mg/L). Regarding the predictions, this behavior did not change, and the results varied relatively little. Although our results are satisfactory, the predictive performance in recent studies with vancomycin is heterogeneous, and although these three models have proven to be useful for clinical application, further research and adaptation of PopPK models is required, as well as implementation in the clinical practice of MIPD and TDM in real time.
Novel Resistance Regions Carrying TnaphA6, blaVIM-2, and blaPER-1, Embedded in an ISPa40-Derived Transposon from Two Multi-Resistant Pseudomonas aeruginosa Clinical Isolates
Authors: Papa-Ezdra Romina , Cordeiro Nicolás F. , Outeda Matilde , Garcia-Fulgueiras Virginia , Araújo Lucía , Seija Verónica , Ayala Juan A. , Bado Inés , Vignoli Rafael
Published: February 2023

Antibiotic resistance is an alarming problem throughout the world and carbapenem-resistant Pseudomonas aeruginosa has been cataloged as critical in the World Health Organization list of microorganisms in urgent need for the development of new antimicrobials. In this work, we describe two novel resistance regions responsible for conferring a multidrug resistance phenotype to two clinical isolates of P. aeruginosa (Pa873 and Pa6415) obtained from patients hospitalized in the ICU of University Hospital of Uruguay. Bacterial identification and antibiotic susceptibility tests were performed using MALDI-TOF and the Vitek 2 system, respectively. WGS was performed for both isolates using Oxford Nanopore Technologies and Illumina and processed by means of hybrid assembly. Both isolates were resistant to ceftazidime, cefepime, piperacillin–tazobactam, aztreonam, and imipenem. Strain Pa6415 also showed resistance to ciprofloxacin. Both strains displayed MICs below the susceptibility breakpoint for CAZ-AVI plus 4 mg/L of aztreonam as well as cefiderocol. Both resistance regions are flanked by the left and right inverted repeats of ISPa40 in two small regions spanning 39.3 and 35.6 kb, for Pa6415 and Pa873, respectively. The resistance region of Pa6415 includes TnaphA6, and the new Tn7516 consists of IRi, In899, qacEΔ1-sul1-ISCR1, qnrVC6-ISCR1-blaPER-1-qacEΔ1-sul1, araJ-like, IS481-like tnpA, ISPa17, and IRR. On the other hand, the resistance region of Pa873 includes Tnaph6 and the new Tn7517 (IRi, In899, qacEΔ1-sul1, ISCR1–blaPER-1–qacEΔ1-sul1, araJ-like, IS481-like tnpA, ISPa17, and IRR). It is necessary to monitor the emergence of genetic structures that threaten to invalidate the available therapeutic resources.
Pleiotropic Roles of a KEAP1-Associated Deubiquitinase, OTUD1
Authors: Oikawa Daisuke , Shimizu Kouhei , Tokunaga Fuminori
Published: February 2023

Protein ubiquitination, which is catalyzed by ubiquitin-activating enzymes, ubiquitin-conjugating enzymes, and ubiquitin ligases, is a crucial post-translational modification to regulate numerous cellular functions in a spatio–temporal-specific manner. The human genome encodes ~100 deubiquitinating enzymes (DUBs), which antagonistically regulate the ubiquitin system. OTUD1, an ovarian tumor protease (OTU) family DUB, has an N-terminal-disordered alanine-, proline-, glycine-rich region (APGR), a catalytic OTU domain, and a ubiquitin-interacting motif (UIM). OTUD1 preferentially hydrolyzes lysine-63-linked ubiquitin chains in vitro; however, recent studies indicate that OTUD1 cleaves various ubiquitin linkages, and is involved in the regulation of multiple cellular functions. Thus, OTUD1 predominantly functions as a tumor suppressor by targeting p53, SMAD7, PTEN, AKT, IREB2, YAP, MCL1, and AIF. Furthermore, OTUD1 regulates antiviral signaling, innate and acquired immune responses, and cell death pathways. Similar to Nrf2, OTUD1 contains a KEAP1-binding ETGE motif in its APGR and regulates the reactive oxygen species (ROS)-mediated oxidative stress response and cell death. Importantly, in addition to its association with various cancers, including multiple myeloma, OTUD1 is involved in acute graft-versus-host disease and autoimmune diseases such as systemic lupus erythematosus, rheumatoid arthritis, and ulcerative colitis. Thus, OTUD1 is an important DUB as a therapeutic target for a variety of diseases.
Agri-Food Wastes as Natural Source of Bioactive Antioxidants
Authors: Hrelia Silvana , Angeloni Cristina , Barbalace Maria Cristina
Published: February 2023

Nowadays, the health of the ecosystem and quality of life are jeopardized by the growing quantities of waste that are released into the environment [...]
Calcium and Reactive Oxygen Species Signaling Interplays in Cardiac Physiology and Pathologies
Authors: De Nicolo Bianca , Cataldi-Stagetti Erica , Diquigiovanni Chiara , Bonora Elena
Published: February 2023

Mitochondria are key players in energy production, critical activity for the smooth functioning of energy-demanding organs such as the muscles, brain, and heart. Therefore, dysregulation or alterations in mitochondrial bioenergetics primarily perturb these organs. Within the cell, mitochondria are the major site of reactive oxygen species (ROS) production through the activity of different enzymes since it is one of the organelles with the major availability of oxygen. ROS can act as signaling molecules in a number of different pathways by modulating calcium (Ca2+) signaling. Interactions among ROS and calcium signaling can be considered bidirectional, with ROS regulating cellular Ca2+ signaling, whereas Ca2+ signaling is essential for ROS production. In particular, we will discuss how alterations in the crosstalk between ROS and Ca2+ can lead to mitochondrial bioenergetics dysfunctions and the consequent damage to tissues at high energy demand, such as the heart. Changes in Ca2+ can induce mitochondrial alterations associated with reduced ATP production and increased production of ROS. These changes in Ca2+ levels and ROS generation completely paralyze cardiac contractility. Thus, ROS can hinder the excitation–contraction coupling, inducing arrhythmias, hypertrophy, apoptosis, or necrosis of cardiac cells. These interplays in the cardiovascular system are the focus of this review.
Zeolites: A Theoretical and Practical Approach with Uses in (Bio)Chemical Processes
Authors: Vasconcelos Arthur Abinader , Len Thomas , de Oliveira Alex de Nazaré , Costa Ana Alice Farias da , Souza Allan Rodrigo da Silva , Costa Carlos Emmerson Ferreira da , Luque Rafael , Rocha Filho Geraldo Narciso da , Noronha Renata Coelho Rodrigues , Nascimento Luís Adriano Santos do
Published: February 2023

This review provides a state-of-the-art summary of distributed zeolite technology, as well as identifying strategies to further promote the absorption of these materials in various areas of study. Zeolites are materials that can be synthesized or found in natural rock deposits a with a basic composition consisting in Al, Si, and O. Zeolite’s consideration as a future material is due to many facile synthesis methods to obtain different structures with variations in pore size, surface area, pore volume and physical properties. These methods are developed using the control of relevant synthesis parameters that influences structure formation, such as crystallization temperature, time of aging and/or crystallization, stoichiometric relationships between components of synthesis gel, pH of the medium, and in some cases the type of structure-directing agent. Each method will lead to geometric changes in the framework formation, making possible the formation of typical chemical bonds that are the fingerprint of any zeolitic structure (O-Si-O and Al-O-Si), forming typical acid sites that give specificity in zeolite and allows it to act as a nanoreactor. The specificity is a characteristic that in some cases depends on selectivity, a fundamental property derived of the porosity, mostly in processes that occur inside the zeolite. In processes outside the structure, the surface area is the main factor influencing this property. Moreover, there are many natural sources with adequate chemical composition to be used as precursors. Some of these sources are waste, minimizing the deposition of potential hazardous materials that can be recalcitrant pollutants depending on the environment. Besides its uses as a catalyst, zeolite serves as a support for many bioprocesses; therefore, this review aims to explain relevant aspects in chemical nature, physical properties, main methods of synthesis, main precursors used for synthesis, and relevant applications of zeolites in chemical catalysis and biological processes.
Surface Gloss, Radiopacity and Shear Bond Strength of Contemporary Universal Composite Resins
Authors: Atalay Cansu , Koc Vural Uzay , Tugay Baris , Miletić Ivana , Gurgan Sevil
Published: February 2023

The surface gloss, radiopacity and enamel/dentin shear bond strengths (SBS)s of five commercially available contemporary universal composite resins (CR)s were examined. The tested universal CRs were as follows: G-aenial A’CHORD (GA), Charisma Diamond (CD), Neo SpectraTMST(NS), Filtek(F) and Estelite Asteria(EA). Twelve cylindrical specimens per group were fabricated and gloss measurements were performed using a gloss meter after polishing and darkening. Five specimens of each group were radiographed using a CMOS sensor alongside an aluminum stepwedge, human enamel and dentin. The mean gray values were measured with a computer program. A total of 120 bonded human enamel and dentin specimens were subjected to SBS test. To analyze surface gloss, radiopacity and SBS we used Kruskall–Wallis, Wilcoxon signed rank, Welch tests and one-way ANOVA. Games–Howell, Tukey’s HSD tests, and Dunn’s multiple comparisons were used for multiple comparisons (p < 0.05). In terms of gloss units of the materials after polishing and darkening, the highest surface gloss was achieved with GA, followed by NS, F, CD and EA (p < 0.001). All the tested CRs showed significantly higher radiopacity values in comparison with dentin (p < 0.05). CD and NS presented higher radiopacity values, while other CRs were, in decreasing order; F, GA and EA (p < 0.001). The SBS ranking varied for enamel and dentin, and the adhesive failure was detected at a higher rate. Commercially available contemporary universal CRs display different surface gloss, radiopacity and SBS properties.
Dual-Encoder Transformer for Short-Term Photovoltaic Power Prediction Using Satellite Remote-Sensing Data
Authors: Cao Haizhou , Yang Jing , Zhao Xuemeng , Yao Tiechui , Wang Jue , He Hui , Wang Yangang
Published: February 2023

The penetration of photovoltaic (PV) energy has gained a significant increase in recent years because of its sustainable and clean characteristics. However, the uncertainty of PV power affected by variable weather poses challenges to an accurate short-term prediction, which is crucial for reliable power system operation. Existing methods focus on coupling satellite images with ground measurements to extract features using deep neural networks. However, a flexible predictive framework capable of handling these two data structures is still not well developed. The spatial and temporal features are merely concatenated and passed to the following layer of a neural network, which is incapable of utilizing the correlation between them. Therefore, we propose a novel dual-encoder transformer (DualET) for short-term PV power prediction. The dual encoders contain wavelet transform and series decomposition blocks to extract informative features from image and sequence data, respectively. Moreover, we propose a cross-domain attention module to learn the correlation between the temporal features and cloud information and modify the attention modules with the spare form and Fourier transform to improve their performance. The experiments on real-world datasets, including PV station data and satellite images, show that our model achieves better results than other models for short-term PV power prediction.
Advanced Analysis Technologies for Social Media
Authors: Guidi Barbara , Iglesias Carlos A. , Rossetti Giulio , Koidl Kevin
Published: February 2023

Interest in social media has only increased with time [...]
Hybrid Classifier-Based Federated Learning in Health Service Providers for Cardiovascular Disease Prediction
Authors: Yaqoob Muhammad Mateen , Nazir Muhammad , Khan Muhammad Amir , Qureshi Sajida , Al-Rasheed Amal
Published: February 2023

One of the deadliest diseases, heart disease, claims millions of lives every year worldwide. The biomedical data collected by health service providers (HSPs) contain private information about the patient and are subject to general privacy concerns, and the sharing of the data is restricted under global privacy laws. Furthermore, the sharing and collection of biomedical data have a significant network communication cost and lead to delayed heart disease prediction. To address the training latency, communication cost, and single point of failure, we propose a hybrid framework at the client end of HSP consisting of modified artificial bee colony optimization with support vector machine (MABC-SVM) for optimal feature selection and classification of heart disease. For the HSP server, we proposed federated matched averaging to overcome privacy issues in this paper. We tested and evaluated our proposed technique and compared it with the standard federated learning techniques on the combined cardiovascular disease dataset. Our experimental results show that the proposed hybrid technique improves the prediction accuracy by 1.5%, achieves 1.6% lesser classification error, and utilizes 17.7% lesser rounds to reach the maximum accuracy.
A Robust Adversarial Example Attack Based on Video Augmentation
Authors: Yin Mingyong , Xu Yixiao , Hu Teng , Liu Xiaolei
Published: February 2023

Despite the success of learning-based systems, recent studies have highlighted video adversarial examples as a ubiquitous threat to state-of-the-art video classification systems. Video adversarial attacks add subtle noise to the original example, resulting in a false classification result. Thorough studies on how to generate video adversarial examples are essential to prevent potential attacks. Despite much research on this, existing research works on the robustness of video adversarial examples are still limited. To generate highly robust video adversarial examples, we propose a video-augmentation-based adversarial attack (v3a), focusing on the video transformations to reinforce the attack. Further, we investigate different transformations as parts of the loss function to make the video adversarial examples more robust. The experiment results show that our proposed method outperforms other adversarial attacks in terms of robustness. We hope that our study encourages a deeper understanding of adversarial robustness in video classification systems with video augmentation.
Cervical Cancer Diagnosis Based on Multi-Domain Features Using Deep Learning Enhanced by Handcrafted Descriptors
Authors: Attallah Omneya
Published: February 2023

Cervical cancer, among the most frequent adverse cancers in women, could be avoided through routine checks. The Pap smear check is a widespread screening methodology for the timely identification of cervical cancer, but it is susceptible to human mistakes. Artificial Intelligence-reliant computer-aided diagnostic (CAD) methods have been extensively explored to identify cervical cancer in order to enhance the conventional testing procedure. In order to attain remarkable classification results, most current CAD systems require pre-segmentation steps for the extraction of cervical cells from a pap smear slide, which is a complicated task. Furthermore, some CAD models use only hand-crafted feature extraction methods which cannot guarantee the sufficiency of classification phases. In addition, if there are few data samples, such as in cervical cell datasets, the use of deep learning (DL) alone is not the perfect choice. In addition, most existing CAD systems obtain attributes from one domain, but the integration of features from multiple domains usually increases performance. Hence, this article presents a CAD model based on extracting features from multiple domains not only one domain. It does not require a pre-segmentation process thus it is less complex than existing methods. It employs three compact DL models to obtain high-level spatial deep features rather than utilizing an individual DL model with large number of parameters and layers as used in current CADs. Moreover, it retrieves several statistical and textural descriptors from multiple domains including spatial and time–frequency domains instead of employing features from a single domain to demonstrate a clearer representation of cervical cancer features, which is not the case in most existing CADs. It examines the influence of each set of handcrafted attributes on diagnostic accuracy independently and hybrid. It then examines the consequences of combining each DL feature set obtained from each CNN with the combined handcrafted features. Finally, it uses principal component analysis to merge the entire DL features with the combined handcrafted features to investigate the effect of merging numerous DL features with various handcrafted features on classification results. With only 35 principal components, the accuracy achieved by the quatric SVM of the proposed CAD reached 100%. The performance of the described CAD proves that combining several DL features with numerous handcrafted descriptors from multiple domains is able to boost diagnostic accuracy. Additionally, the comparative performance analysis, along with other present studies, shows the competing capacity of the proposed CAD.
Digital Full-Mouth Reconstruction Assisted by Facial and Intraoral Scanners: A Case Report and Technique Description
Authors: Garaicoa Jorge , Jurado Carlos A. , Afrashtehfar Kelvin I. , Alhotan Abdulaziz , Fischer Nicholas G.
Published: February 2023

This report describes a technique integrating facial and dental scanners for treatment planning and execution of a tooth-borne full-mouth reconstruction (FMR) with zirconia fixed prostheses. A partially edentulous female adult presented generalized worn dentition in the incisal and occlusal surfaces. The patient accepted the option for treatment with a fixed FMR solution using a fully digital workflow. An intraoral scan (IoS) for both arches and facial scans collected the initial clinical situation. A digital diagnostic wax-up was generated as part of the treatment plan, and the models were printed. The intervention included crown lengthening of the maxillary teeth aided by a printed guide, installing milled provisional restorations, and delivering permanent milled zirconia partial restorations, single crowns (SCs), and fixed dental prostheses (FDPs). The functional extraoral scanner permitted designing an FMR that created a harmonious dental, gingival, and facial relationship with the patient’s esthetic consent approval. IoS captured the initial clinical situation to design (CAD) and fabricate (CAM) the PMMA provisional and zirconia final partial restorations, SCs, and FDPs. Facial and intraoral scanners are technologies that can synergistically assist oral health providers in the diagnosis, planning, and execution of fixed FMR using an entirely digital workflow.
Diffusion Model of Cement Slurry in Porous Media Considering Porosity Variation and Percolation Effect
Authors: Han Bo , Chen Xuemin , Pan Yanhui , Wang Chaojie , Shi Mingsheng , Chu Xuanxuan
Published: February 2023

The porosity of porous media is a key factor affecting cement slurry diffusion. In this paper, a theoretical model of cement slurry diffusion in porous media considering the variation of porosity is proposed. The model is validated through comparison with the experimental results in the literature. The influence of injection parameters (i.e., the water–cement ratio and the pore fractal dimension) on the porosity and strength of porous media is analyzed. The results indicate that: under the same pore fractal dimension, the porosity of the specimen increases gradually with the increase in diffusion distance, and the rate increases rapidly in the later stage. However, when the fractal dimension of porosity increases to 2.1, the porosity of the consolidated body after grouting does not change with the diffusion distance. The water–cement ratio also affects the porosity of the sample. At a distance below 1.0 m, the sample porosity is larger at a larger water–cement ratio of 1.5. When the distance is more than 1.0 m, the smaller the porosity decreases with increasing water–cement ratios. With the increase in distance, the compressive strength of the specimen first decreases slowly, and then rapidly from 90 kPa to 0 kPa. This is further verified by the pore variation law obtained by SEM. The model is applied to selecting grouting parameter design in road maintenance. The pavement deflection after grouting is effectively reduced, verifying the theoretical model’s applicability.
Study of Baffle Height and Wind Velocity Effect on the Characteristics of Pool Fires in a Wind Tunnel
Authors: Yu Zhilei , Huang Xin
Published: February 2023

Wind-blown pool fire accidents in a ventilated tunnel usually pose and present serious risks to properties and personal safety. In this paper, the flame characteristics and flow field changes of pool fires under the combined influence of baffles and crosswinds were investigated using wind tunnel experiments and numerical simulations. The fire experiments reveal that the flame length increases first, then decreases with increasing crosswind speeds up to 3 m/s and then becomes almost constant. Finally, as the wind speed continues to increase, the flame length remains constant. The flame height decreases with crosswind speed up to 3 m/s and then remains almost unchanged. As for the flame tilt angle, the flame above the baffle increases first and then remains unchanged when the velocity of crosswind increases from 2 to 5 m/s. According to the simulation results, the clockwise rotating eddy will be generated downstream of the baffle. The recirculation zone on the surface of the pool transfers the fresh air to the flame. The vortex zone downstream of the pool can retain heat and send back unignited fuel vapor to be burned rather than being blown away. The results may provide beneficial suggestions for understanding flame development behind obstacles for ventilated tunnels.
Predicting Multi-Gene Mutation Based on Lung Cancer CT Images and Mut-SeResNet
Authors: Sun Lichao , Dong Yunyun , Xu Shuang , Feng Xiufang , Fan Xiaole
Published: February 2023

Epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma (KRAS) are the most common driver genes in non-small cell lung cancer patients. However, frequent gene mutation testing raises a potential risk of cancer metastasis. In our paper, a Mut-SeResNet model based on the ResNet network that incorporated a residual block and attention mechanism was proposed to solve the performance degradation problem caused by a deepening of the network. We introduced a residual structure and extracted small differences between different levels to enhance the feature learning ability. The squeeze and excitation attention mechanism was adapted to fully extract the dependence between different channels of the feature image, and it calibrated the channel feature information. We used the dataset of 363 patients that were collected from collaborating hospitals to train our Mut-SeResNet model. The prediction accuracy for EGFR and KRAS mutations was 89.7% and 88.3%, respectively, with a loss accuracy of 6.4% and 9.2%, respectively. The results showed that the model provided a non-invasive and easy-to-use method to improve the accuracy and stability of clinical diagnosis.
Design and Application of Intelligent Transportation Multi-Source Data Collaboration Framework Based on Digital Twins
Authors: Zhang Xihou , Han Dingding , Zhang Xiaobo , Fang Leheng
Published: February 2023

The increasing urban traffic problems have made the transportation system require a large amount of data. Aiming at the current problems of data types redundancy and low coordination rate of intelligent transportation systems (ITS), this paper proposes an improved digital twin architecture applicable to ITS. Based on the improved digital twin architecture, a framework for dynamic and static data collaboration in ITS is constructed. For various collaboration methods, this paper specifically describes the collaboration methods and scopes, and designs the framework and interfaces for data mapping. Finally, the effectiveness of the framework is verified by case studies to mine the spatiotemporal distribution characteristics of data, capture human travel characteristics, and visualize intersections using digital twins. This paper provides a new data fusion idea for digital twin systems in ITS, and the framework covers all data types in digital twin systems for cross-integration analysis.
Blind People: Clothing Category Classification and Stain Detection Using Transfer Learning
Authors: Rocha Daniel , Soares Filomena , Oliveira Eva , Carvalho Vítor
Published: February 2023

The ways in which people dress, as well as the styles that they prefer for different contexts and occasions, are part of their identity. Every day, blind people face limitations in identifying and inspecting their garments, and dressing can be a difficult and stressful task. Taking advantage of the great technological advancements, it becomes of the utmost importance to minimize, as much as possible, the limitations of a blind person when choosing garments. Hence, this work aimed at categorizing and detecting the presence of stains on garments, using artificial intelligence algorithms. In our approach, transfer learning was used for category classification, where a benchmark was performed between convolutional neural networks (CNNs), with the best model achieving an F1 score of 91%. Stain detection was performed through the fine tuning of a deep learning object detector, i.e., the mask R (region-based)-CNN. This approach is also analyzed and discussed, as it allowed us to achieve better results than those available in the literature.
Investigation of the Antimicrobial Properties of Beetroot–Gelatin Films Containing Silver Particles Obtained via Green Synthesis
Authors: Puišo Judita , Adliene Diana , Paškevičius Algimantas , Vailionis Artūras
Published: February 2023

Silver nanoparticles are produced using various physical, chemical or physicochemical methods. Simple low-cost nontoxic environmentally friendly, or “green”, chemistry methods are important, especially for their invasive application in the medicine and food industries. Silver-nanoparticle-enriched biocompatible films were produced at room temperature from fresh beetroot juice, AgNO3 and gelatin–water solution using the photoreduction method. The optical, morphological and structural characteristics of the experimental samples were analyzed using UV-VIS, XRD and SEM techniques. The antimicrobial activity of newly produced films was investigated using the agar diffusion method. The synthesis of nanoparticles was approved their characteristic LSPR peaks in the UV-VIS absorbance spectra. According to the XRD patterns of the films, these nanoparticles were assigned to the cubic phase of metallic Ag. It was found that the antimicrobial activity of the silver nanoparticles in the beetroot–gelatin films might be effective; however, it depends on the silver ion concentrations used for the production of these films and on the medium’s pH.
Vertical Transmission of Salmonella enterica ser. Gallinarum in Dermanyssus gallinae by the Mean of the Baudruche-Based Artificial Feeding Device
Authors: Schiavone Antonella , Pugliese Nicola , Siddique Ifra , Samarelli Rossella , Saleh Medhat S. , Lombardi Roberto , Circella Elena , Camarda Antonio
Published: February 2023

The poultry red mite (PRM) Dermanyssus gallinae is well known for its vectorial role for pathogens, such as Salmonella enterica ser. Gallinarum, the causative agent of fowl typhoid. Here, we ascertained the vertical transmission of S. Gallinarum across the PRM life stages, combining the Baudruche-based in vitro feeding system and a PRM-fitting DNA extraction and detection method by qPCR. Small-sized pools (4–5 specimens) of adult mites, eggs, larvae, and protonymphs, as well as single eggs, were tested for S. Gallinarum. The pathogen was detected in 89% of adult mites, 5% of single eggs, 17% of pooled eggs, 9% of larvae, and 43% of protonymphs. Additionally, the feeding rate for infected and uninfected mites was similar, while differences in ovipositing and fecundity rate were observed. The method allowed to confirm the infection of mites through the bloodmeal and to strongly suggest the transmission of S. Gallinarum across the PRM life stages. Furthermore, it allows to avoid in vivo studies and it could be useful for further investigating the vectorial role of D. gallinae or other hematophagous arthropods for infectious agents.
Special Issue “Wireless Sensor Networks: Technologies, Applications, Prospects”
Authors: Araujo Alvaro
Published: February 2023

Wireless sensor networks (WSN) have a long history of research and development [...]
Three-Dimensional Geological Modeling of the Shallow Subsurface and Its Application: A Case Study in Tongzhou District, Beijing, China
Authors: He Hanhan , Xiao Jingze , He Jing , Wei Bo , Ma Xiaogang , Huang Fan , Cai Xiangmin , Zhou Yuanxin , Bi Jingyi , Zhao Yiting , Wang Chunjun , Wei Jingran
Published: February 2023

Three-dimensional (3D) geological models are currently needed and used independently for urban development. The main difficulty in constructing a 3D geological model of a shallow subsurface is to determine the stratigraphic distribution. Highly variable properties and geometries of geological units beneath lead to difficulty. It is key to find a practicable and efficient way to construct a model in practical work. This study takes Tongzhou District (Beijing) as a case; 476 boreholes (40 newly drilled and 436 existing engineering boreholes) were utilized combined with the cross-section method to construct an integrated 3D geological model. The framework and analyses contributed to the following applications: (1) High-quality information from new boreholes and existing engineering boreholes were used to define stratigraphy and build cross-sections. (2) The resulting geological model (up to 50 m beneath Tongzhou area) shows many details of the shallow subsurface. This includes 10 major layers which were grouped into three cyclothems representing cyclic sequences of clay, interbedded silt, sand, and gravel with variable quantities of lenses. (3) The new model was used as a tool to visualize the depth and geometry variations below ground and to characterize a large variety of properties (for example, the compression modulus analyzed in this paper) that each unit contains, and then to evaluate the underground geological conditions. (4) An analysis of a dynamic monitoring model based on the resulting 3D model indicated that the geological units (sand and silty clay) at depths between 30 m and 40 m, with an average vertical deformation of 0.97 mm, from July 2019 to September 2020, are suitable for underground construction, from the perspective of vertical stability in the study area. Monitoring models that take time into consideration based on a 3D framework will be further explored.
Damage and Failure of a Column-Supported RC Flat Slab Subjected to Impulsive Loading
Authors: Yankelevsky David Z. , Karinski Yuri S. , Feldgun Vladimir R.
Published: February 2023

RC flat slabs supported by an array of columns subjected to the action of impulsive pressure were investigated. The slabs were designed for static loads according to current standards. The dynamic responses of 4 × 4- and 8 × 8-column-supported slabs were similar, as were damage and failure. A simplified model consisting of a tributary area and a central column yielded similar results, demonstrating the accuracy of the simplified model and its reliability. These analyses exhibited modes of damage and failure characterized by large shear distortions in the slab–column connection zone. The rest of the span remained undamaged and in a horizontal position. In all analyses, the slab concrete around the column was fully damaged. The rebars failed within a limited zone at the slab–column connections. The early failure of integrity reinforcement indicated that it could not fulfill its duty; thus, a subsequent progressive collapse scenario was inevitable. All bent-up rebars failed, and their contribution to shear resistance was doubtful. The static analysis was entirely different from the dynamic failure mode. Impulsive loading damage and failure were similar to those in the case of slab-on-slab impact; in both cases, the slab underwent large displacement and severe damage in the narrow slab–column zone, whereas the rest of the slab remained almost completely flat and undamaged.
Dynamic Analysis of Fuzzy Systems
Authors: Barraza Manuel , Matía Fernando , Al-Hadithi Basil Mohammed
Published: February 2023

In this work, a new methodology for the dynamic analysis of non-linear systems is developed by applying the Mamdani fuzzy model. With this model, parameters such as settling time, peak time and overshoot will be obtained. The dynamic analysis of non-linear fuzzy systems with triangular membership functions is performed, and linguistic variables describing overly complex or ill-defined phenomena are used to fit the model. Scaling factors will simplify the modification of the variables, making them easier to find the system model. The specifications of second-order characteristics in the time domain, such as overshoot and peak time, will be represented graphically. As a case study, the proposed methods are implemented to analyse the dynamics of a tank and a simple pendulum for first-order and second-order systems, respectively, where it is observed that the proposed methodology offers highly positive results.
Study and Simulation of an Under-Actuated Smart Surface for Material Flow Handling
Authors: Bianchi Edoardo , Jorg Oliver Jonas , Fantoni Gualtiero , Brosed Dueso Francisco Javier Brosed , Yagüe-Fabra José A.
Published: February 2023

Smart surfaces are becoming more and more popular in the field of intralogistics, as they combine great flexibility with easy reprogrammability. Pursuing this trend, the following article proposes a modular surface to perform handling tasks, such as sorting, stopping, or slowing down material flows. Differently from the current technology, the surface used is under-actuated, thus, it exploits the speed, already possessed by the object, or the gravity to perform, with a simplified hardware, for the aforementioned tasks. In practice, these handling actions are completed using an array of rotors, of which only the direction of the rotation axis is controlled. Moreover, the axis can only assume certain discrete orientations in the plane, further simplifying the design. Thus, what is created is a controllable and under-actuated friction field, which, in contrast with similar existing systems, does not require active driving forces to manipulate the material flow. In the article, the analytic model of the surface is described, and a software simulation environment is introduced to demonstrate its functioning. In addition, examples of sorting, slowing down, and stopping operations and a validation of the simulation itself are presented.
Dynamic Behavior Analysis of I-Shaped RC Beams under Combined Blast and Impact Loads
Authors: Liu Jianyu , Yin Yiping , Zhao Yunlei , Li Yuan
Published: February 2023

The existing literature mainly focuses on the research of reinforced concrete (RC) beams under a single load such as blast or impact. In this paper, the slab–rib–slab RC beam, a new type of structure widely used in bridge structures, was taken as the research object. The explicit dynamic analysis software LS-DYNA was used to numerically analyze the dynamic response and failure behavior of I-shaped RC beams under combined blast and impact loads. For this reason, an effective numerical analysis model was obtained by carrying out experiments on I-shaped RC beams under contact explosion. The key factors affecting the dynamic response of the structure under combined loads were numerically analyzed. Numerical results showed that different load application sequences have important effects on the dynamic response of the structure. When the impact load was first applied to the structure, more severe concrete damage and deformation occured in the depth direction of the beam. However, when the blast load was first applied to the structure, the concrete at the lower flange was damaged in the span direction of the beam due to tension, and no large-scale concrete spallation occurred in the depth direction. This was mainly due to the different mechanisms of blast and impact loads. In addition, the vulnerability of the I-shaped RC beams varied with some structural parameters, including span, depth, and configuration of reinforcement. At the same time, the results showed that the structure is more sensitive to changes in structural parameters when it is first subjected to impact loads.
Lifting More Than Two Loads Compromises the Magnitude of the Load–Velocity Relationship Variables: Evidence in Two Variants of the Prone Bench Pull Exercise
Authors: Miras-Moreno Sergio , García-Ramos Amador , Fernandes John F. T. , Pérez-Castilla Alejandro
Published: February 2023

This study aimed to compare and associate the magnitude of the load–velocity relationship variables between the multiple-point and two-point methods and between the concentric-only and eccentric–concentric prone bench pull (PBP) variants. Twenty-three resistance-trained males completed a preliminary session to determine the concentric-only PBP one-repetition maximum (1 RM) and two experimental sessions that only differed in the PBP variant evaluated. In each experimental session they performed three repetitions against the 14 kg load (L1), two repetitions against the 85% 1 RM load (L4), three repetitions against an equidistant intermediate light load (L2), two repetitions against an equidistant intermediate heavy load (L3), and 1–5 1 RM attempts. The load–velocity relationship variables (i.e., load–axis intercept, velocity–axis intercept, and area under the load–velocity relationship line) were obtained from the multiple-point (L1-L2-L3-L4) and two-point (L1-L4) methods. All load–velocity relationship variables presented greater magnitudes when obtained by the two-point method compared with the multiple-point method (p < 0.001, ESrange = 0.17–0.43), while the load–velocity relationship variables were comparable between both PBP variants (p ≥ 0.148). In addition, the load–velocity relationship variables were highly correlated between both methods (rrange = 0.972–0.995) and PBP variants (rrange = 0.798–0.909). When assessing the load–velocity relationship variables, practitioners should prescribe only two loads, as this maximises the magnitudes of the variables and decreases fatigue.
Experimental Study on the Effect of Single Structural Plane on the Stability of Shallow Tunnel Surrounding Rock
Authors: Sun Zhijie , Li Pengfei , Du Xiuli , Yang Xuanyu
Published: February 2023

There are a large number of structural planes distributed in the surrounding rock of a tunnel, and this is one of the key factors causing a tunnel’s instability. Due to different geological and historical conditions, the distribution characteristics and the occurrence of structural planes in the rock mass also have significant differences. In engineering, it is common to encounter structural planes that cut across the tunnel section and have a significant impact on the stability. The occurrence of structural planes is a key factor controlling the mechanical behavior of the surrounding rock. Based on this, laboratory uniaxial compression tests were carried out by constructing a small tunnel physical model with single structural planes of different inclination angles. A related numerical simulation analysis was also carried out. This research indicates that: (1) Under the influence of a single structural plane, the dip direction with 30°–60° is the most dangerous situation, and when the dip angle of the structural plane is between 38 and 88°, it will slip along the structural plane. (2) According to the mechanical mechanism, there are three types of cracks: tensile cracks, shear cracks, and tensile shear cracks. According to the deformation characteristics, there are four types: tension, friction, bending, and shear. (3) There is a certain correlation between the strength of a single discontinuity rock mass and that of a multi-jointed rock mass. When the dip angle of the joints’ combination is 45°+60°, the rock mass is in its weakest state.