bluuebunny/crossref_metadata_2025 huggingface dataset:
Two Types of Management for the Noninvasive Treatment of Pectus Excavatum in Neonatal Puppies—Case Reports
Authors: Pereira Keylla Helena Nobre Pacífico , Fuchs Kárita da Mata , Terçariol Lara Ataídes Arantes , Silva Renata Cesar , Camargo Gabriel de Azevedo , Mendonça Júlia Cosenza , Paulino Netelin Tainara , Zone Marcelo Alejandro , Oba Eunice , Lourenço Maria Lucia Gomes
Published: March 2023

Pectus excavatum is a deformity of the thorax characterized by ventrodorsal narrowing of the sternum bone and costal cartilages, which can lead to compression and cardiopulmonary alterations in dogs, presenting a high prevalence in brachycephalic breeds. The aim of this report was to describe two types of management for the noninvasive treatment of pectus excavatum in newborn puppies of the breeds French Bulldog and American Bully. The puppies presented dyspnea, cyanosis and substernal retraction during inspiration. The diagnosis was performed by physical examination and confirmed by chest X-ray. Two types of splints were performed (a circular splint with plastic pipe and a paper box splint on the chest), aiming at thoracic lateral compression and frontal chest remodeling. The management was effective for the conservative treatment of mild-grade pectus excavatum, resulting in the repositioning of the thorax and improvement of the respiratory pattern.
LC-YOLO: A Lightweight Model with Efficient Utilization of Limited Detail Features for Small Object Detection
Authors: Cui Menghua , Gong Guoliang , Chen Gang , Wang Hongchang , Jin Min , Mao Wenyu , Lu Huaxiang
Published: March 2023

The limited computing resources on edge devices such as Unmanned Aerial Vehicles (UAVs) mean that lightweight object detection algorithms based on convolution neural networks require significant development. However, lightweight models are challenged by small targets with few available features. In this paper, we propose an LC-YOLO model that uses detailed information about small targets in each layer to improve detection performance. The model is improved from the one-stage detector, and contains two optimization modules: Laplace Bottleneck (LB) and Cross-Layer Attention Upsampling (CLAU). The LB module is proposed to enhance shallow features by integrating prior information into the convolutional neural network and maximizing knowledge sharing within the network. CLAU is designed for the pixel-level fusion of deep features and shallow features. Under the combined action of these two modules, the LC-YOLO model achieves better detection performance on the small object detection task. The LC-YOLO model with a parameter quantity of 7.30M achieves an mAP of 94.96% on the remote sensing dataset UCAS-AOD, surpassing the YOLOv5l model with a parameter quantity of 46.61M. The tiny version of LC-YOLO with 1.83M parameters achieves 94.17% mAP, which is close to YOLOv5l. Therefore, the LC-YOLO model can replace many heavyweight networks to complete the small target high-precision detection task under limited computing resources, as in the case of mobile edge-end chips such as UAV onboard chips.
An Efficient Data Augmentation Method for Automatic Modulation Recognition from Low-Data Imbalanced-Class Regime
Authors: Wei Shengyun , Sun Zhaolong , Wang Zhenyi , Liao Feifan , Li Zhen , Mi Haibo
Published: March 2023

The application of deep neural networks to address automatic modulation recognition (AMR) challenges has gained increasing popularity. Despite the outstanding capability of deep learning in automatic feature extraction, predictions based on low-data regimes with imbalanced classes of modulation signals generally result in low accuracy due to an insufficient number of training examples, which hinders the wide adoption of deep learning methods in practical applications of AMR. The identification of the minority class of samples can be crucial, as they tend to be of higher value. However, in AMR tasks, there is a lack of attention and effective solutions to the problem of Imbalanced-class in a low-data regime. In this work, we present a practical automatic data augmentation method for radio signals, called SigAugment, which incorporates eight individual transformations and effectively improves the performance of AMR tasks without additional searches. It surpasses existing data augmentation methods and mainstream methods for solving low-data and imbalanced-class problems on multiple datasets. By simply embedding SigAugment into the training pipeline of an existing model, it can achieve state-of-the-art performance on benchmark datasets and dramatically improve the classification accuracy of minority classes in the low-data imbalanced-class regime. SigAugment can be trained for uniform use on different types of models and datasets and works right out of the box.
Enhanced Heterogeneous Activation of Peroxymonosulfate by Nitrogen–Sulfur Co-Doped Mofs-Derived Carbon
Authors: Zhang Chuning , Chu Huaqiang , Ma Qian , Chen Yanyan , Fan Jianwei
Published: March 2023

It is important to further enhance the performance of green and efficient non-homogeneous catalysts for advanced oxidation process of Peroxymonosulfate (PMS-AOP) for green treatment of industrial wastewater. In this paper, nitrogen–sulfur co-doped MOFs-derived carbon material (CoSN@C) was prepared by one-pot synthesis followed by carbonization, and its morphological structure was characterized by XRD and SEM. After pyrolysis, the CoSN@C still maintained the dodecahedral morphology and structure of ZIF-67. The synergistic effects of S and N significantly elevated the activation of PMS. The results show that the CoSN@C + PMS system can effectively activate PMS to degrade Rhodamine B (RhB), with a rate constant (1.85 min−1) four times higher than that of the CoN@C + PMS system (0.44 min−1). The optimal catalytic process parameters of material dosage, PMS concentration, temperature, pH, and other parameters were also investigated for the activation of PMS to remove Rhodamine B. The cyclic experiment shows that the CoSN@C has excellent recyclability and the degradation rate of RhB still reached 88.9% after four cycles. Radical capture experiments and EPR tests showed that the CoSN@C + PMS system generated a large amount of SO4·− and ·OH radicals adsorbed on the catalyst surface and a certain amount of singlet oxygen, and the free radical pathway and non-radical pathway worked together to degrade RhB efficiently and rapidly. While non-radical pathway with singlet oxygen as main reactive oxygen species played a key role in the CoN@C + PMS system. This work provides a new idea for the rational design of non-homogeneous catalysts for PMS-AOP system.
Machine Learning Techniques to Detect a DDoS Attack in SDN: A Systematic Review
Authors: Ali Tariq Emad , Chong Yung-Wey , Manickam Selvakumar
Published: March 2023

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approaches to identify DDoS attacks in SDN networks between 2018 and the beginning of November 2022. To search the contemporary literature, we have extensively utilized a number of digital libraries (including IEEE, ACM, Springer, and other digital libraries) and one academic search engine (Google Scholar). We have analyzed the relevant studies and categorized the results of the SLR into five areas: (i) The different types of DDoS attack detection in ML/DL approaches; (ii) the methodologies, strengths, and weaknesses of existing ML/DL approaches for DDoS attacks detection; (iii) benchmarked datasets and classes of attacks in datasets used in the existing literature; (iv) the preprocessing strategies, hyperparameter values, experimental setups, and performance metrics used in the existing literature; and (v) current research gaps and promising future directions.
An Access Control Model Based on System Security Risk for Dynamic Sensitive Data Storage in the Cloud
Authors: Alharbe Nawaf , Aljohani Abeer , Rakrouki Mohamed Ali , Khayyat Mashael
Published: March 2023

In cloud computing, dynamic storage of data generated by users, applications, tasks, workflows, etc. requires frequent access operations, so traditional encryption cannot be applied in this case. Considering the vulnerability of dynamic data, its protection needs to consider an efficient and dynamic security protection scheme. In data-oriented access control, the traditional approach is generally static policy matching, which cannot deal with emergencies and has the problem of privileged users. To solve this problem, this paper proposes a data-oriented risk-based access control model, which adds risk assessment to the traditional attribute-based access control and aims at the source of risk from three aspects: subject attribute, resource attribute, and environment attribute. A set of risk assessment indexes is proposed, and the calculation method of risk assessment is quantitatively analyzed by combining fuzzy consistency AHP analysis method, and finally, the realization of XACML is given. The validity of the proposed model is analyzed, and the carried out experimental analysis verifies its effectiveness. The proposed model benefits cloud data storage applications that require dynamic data storage, for example, medical/patient data storage.
Hybridised Network of Fuzzy Logic and a Genetic Algorithm in Solving 3-Satisfiability Hopfield Neural Networks
Authors: Azizan Farah Liyana , Sathasivam Saratha , Ali Majid Khan Majahar , Roslan Nurshazneem , Feng Caicai
Published: March 2023

This work proposed a new hybridised network of 3-Satisfiability structures that widens the search space and improves the effectiveness of the Hopfield network by utilising fuzzy logic and a metaheuristic algorithm. The proposed method effectively overcomes the downside of the current 3-Satisfiability structure, which uses Boolean logic by creating diversity in the search space. First, we included fuzzy logic into the system to make the bipolar structure change to continuous while keeping its logic structure. Then, a Genetic Algorithm is employed to optimise the solution. Finally, we return the answer to its initial bipolar form by casting it into the framework of the hybrid function between the two procedures. The suggested network’s performance was trained and validated using Matlab 2020b. The hybrid techniques significantly obtain better results in terms of error analysis, efficiency evaluation, energy analysis, similarity index, and computational time. The outcomes validate the significance of the results, and this comes from the fact that the proposed model has a positive impact. The information and concepts will be used to develop an efficient method of information gathering for the subsequent investigation. This new development of the Hopfield network with the 3-Satisfiability logic presents a viable strategy for logic mining applications in future.
Sublethal Biochemical Effects of Polyethylene Microplastics and TBBPA in Experimentally Exposed Freshwater Shrimp Palaemonetes argentinus
Authors: Ríos Juan Manuel , Attademo Andres M. , Horie Yoshifumi , Ginevro Paula María , Lajmanovich Rafael C.
Published: March 2023

The biochemical effects of sublethal exposure to polyethylene microplastics (PEM) of 40–48 µm particle size and the flame retardant tetrabromobisphenol A (TBBPA), a plastic additive, on the freshwater shrimp Palaemonetes argentinus were assessed. Here, we postulate that the use of enzyme and thyroid hormones as biomarkers contributes to the knowledge of the effects of microplastics and plastic additives on freshwater crustaceans. To address this, we evaluated the activities of acetylcholinesterase (AChE), glutathione S-transferase (GST), and carboxilesterase (CbE, using 1-naphthyl acetate (NA) as substrate) and levels of the thyroid hormones thyroxine (T4) and triiodothyronine (T3) after shrimp were exposed (for 96 h) to these xenobiotics at environmentally realistic concentrations. The results showed that the mixture of both xenobiotics led to a decrease in AChE and GST activities and increased T4 levels. We suggest that physiological processes could be compromised in freshwater organisms when exposed to microplastics and TBBPA together, and this could ultimately affect upper levels of the food web.
Temporal Stability of the Dynamic Resting-State Functional Brain Network: Current Measures, Clinical Research Progress, and Future Perspectives
Authors: Long Yicheng , Liu Xiawei , Liu Zhening
Published: March 2023

Based on functional magnetic resonance imaging and multilayer dynamic network model, the brain network’s quantified temporal stability has shown potential in predicting altered brain functions. This manuscript aims to summarize current knowledge, clinical research progress, and future perspectives on brain network’s temporal stability. There are a variety of widely used measures of temporal stability such as the variance/standard deviation of dynamic functional connectivity strengths, the temporal variability, the flexibility (switching rate), and the temporal clustering coefficient, while there is no consensus to date which measure is the best. The temporal stability of brain networks may be associated with several factors such as sex, age, cognitive functions, head motion, circadian rhythm, and data preprocessing/analyzing strategies, which should be considered in clinical studies. Multiple common psychiatric disorders such as schizophrenia, major depressive disorder, and bipolar disorder have been found to be related to altered temporal stability, especially during the resting state; generally, both excessively decreased and increased temporal stabilities were thought to reflect disorder-related brain dysfunctions. However, the measures of temporal stability are still far from applications in clinical diagnoses for neuropsychiatric disorders partly because of the divergent results. Further studies with larger samples and in transdiagnostic (including schizoaffective disorder) subjects are warranted.
Supramarginal Gyrus and Angular Gyrus Subcortical Connections: A Microanatomical and Tractographic Study for Neurosurgeons
Authors: Şahin Mehmet Hakan , Akyüz Mehmet Emin , Karadağ Mehmet Kürşat , Yalçın Ahmet
Published: March 2023

Background and Objectives: This article aims to investigate the subcortical microanatomy of the supramarginal gyrus (SMG) and angular gyrus (AnG) using a microfiber dissection technique and diffusion tensor imaging (DTI)/fiber tractography (FT). The cortical and subcortical structures of this region are highly functional, and their lesions often present clinically. For this reason, the possibility of post-surgical deficits is high. We focused on the supramarginal gyrus and the angular gyrus and reviewed their anatomy from a topographic, functional and surgical point of view, and aimed to raise awareness especially for neurosurgeons. Methods: Four previously frozen, formalin-fixed human brains were examined under the operating microscope using the fiber dissection technique. Four hemispheres were dissected from medial to lateral under the surgical microscope. Brain magnetic resonance imaging (MRI) of 20 healthy adults was examined. Pre-central and post-central gyrus were preserved to achieve topographic dominance in dissections of brain specimens. Each stage was photographed. Tractographic brain magnetic resonance imaging of 10 healthy adults was examined radiologically. Focusing on the supramarginal and angular gyrus, the white matter fibers passing under this region and their intersection areas were examined. These two methods were compared anatomically from the lateral view and radiologically from the sagittal view. Results: SMG and AnG were determined in brain specimens. The pre-central and post-central gyrus were topographically preserved. The superior and medial temporal gyrus, and inferior and superior parietal areas were decorticated from lateral to medial. U fibers, superior longitudinal fasciculus II (SLF II), superior longitudinal fasciculus III (SLF III), arcuat fasciculus (AF) and middle longitudinal fasciculus (MdLF) fiber groups were shown and subcortical fiber structures belonging to these regions were visualized by the DTI/FT method. The subcortical fiber groups under the SMG and the AnG were observed anatomically and radiologically to have a dense and complex structure. Conclusions: Due to the importance of the subcortical connections of SMG and AnG on speech function, tumoral lesions and surgeries of this region are of particular importance. The anatomical architecture of the complex subcortical structure, which is located on the projection of the SMG and AnG areas, was shown with a DTI/FT examination under a topographic dominance, preserving the pre-central and post-central gyrus. In this study, the importance of the anatomical localization, connections and functions of the supramarginal and angular gyrus was examined. More anatomical and radiological studies are needed to better understand this region and its connections.
Reducing Bullying through Empathy Training: The Effect of Teacher’s Passive Presence
Authors: Palade Teodora , Pascal Emilia
Published: March 2023

Bullying is a serious problem in schools all around the globe, and implementing intervention strategies effective over time is still difficult, despite the consistent literature on the subject. In this study, we tested the efficiency of a 5-day intensive empathy training program in reducing bullying among third graders. The sample included three classes of third graders (N = 64, Mage = 9.45; SDage = 0.50) from a Romanian school. A 3 × 3 mixed experimental design was used where we manipulated the type of intervention (control group—no empathy training, experimental group 1—empathy training with the teacher present, and experimental group 2—empathy training without teacher present) and the time of measurement (pre-test, post-test, and 3 weeks’ follow-up). The results showed that the intervention determined a significant increase in empathy and a significant decrease in verbal bullying but only for the experimental group where the teacher was physically present in the classroom during the intervention. Moreover, the pattern of results showed that the effects of the intervention increased 21 days after it was completed, meaning that the program could have long-term effects. No significant change in physical bullying behaviors was observed.
Optimal Design of Ski Tracks in Construction Projects: Taking the Warm-Up and Training Ski Track of the South Area in the Yanqing Competition Zone of the Beijing 2022 Winter Olympic Games as an Example
Authors: Wu Yaoyi , Wu Xianfeng
Published: March 2023

Mature civil engineering software and platforms can provide a dynamic correlated situation of the road design, generate a quick and accurate grading design in terrain model making, and, most importantly, improve the design efficiency and calculation accuracy and reduce the workload of designers in the construction project. However, the application of existing platforms in complex site engineering for the design of ski tracks has not been well developed. The design process of ski tracks requires consideration of elaborate requirements in complex environmental conditions. In this study, we aim to simplify digital elevation model (DEM) data, optimize ski track contour lines, and localize the design expression of the ski track designs based on the experience of the construction of the National Alpine Ski Center in the Yanqing Competition Zone for the Beijing 2022 Winter Olympic Games. This study examines the feasibility of the optimal digital approach combining mathematics and computer science based on the case study of the warm-up and training ski track of the south area in the Yanqing Competition Zone. This study will contribute to the optimal design of skiing tracks in construction projects and help to improve designers’ workload efficiency for the design and construction of ski tracks in the future.
Use of BIM as a Support for Tendering of Facility Management Services
Authors: Macek Daniel
Published: March 2023

Basic 3D models of real buildings are mainly used in the design phase, when they serve as a visualization of future projects or as a basis for the creation of project documentation. However, the possibilities of Building Information Modeling are much wider. The paper presents the options available during the tendering for the company’s support service providers within the framework of Building Information Modeling (BIM). The principle is based on defining the necessary content of the Building Information Modeling, which would enable a smooth transition between the implementation and operational phases. At the end of the implementation phase, the model should contain information that could be used for the needs of the selection process for facility management service providers, which, unlike normal construction production, have many of their own specificities, but are necessary for the operation of the facility. This information must be entered into the model during the entire construction process in the form of defined parameters, a defined format and the location of these parameters. The purpose of the Building Information Modeling should primarily be the optimization of costs during the entire life cycle of the construction project, as well as better and clearer availability of information and facilitation of cooperation between individual participating entities. Therefore, the prerequisite for using the Building Information Modeling as the main basis for tendering is its high-quality processing, which places high demands on all participants in the investment project.
Effect of C3-Alcohol Impurities on Alumina-Catalyzed Bioethanol Dehydration to Ethylene: Experimental Study and Reactor Modeling
Authors: Ovchinnikova Elena V. , Banzaraktsaeva Sardana P. , Kovgan Maria A. , Chumachenko Victor A.
Published: March 2023

The impact of feedstock impurities on catalytic process is among the crucial issues for processing real raw materials. A real and model 92%-bioethanol contaminated with 0.03–0.3% mol 1-propanol or 2-propanol were used to make ethylene on a proprietary alumina catalyst in isothermal flow reactor. We proposed a formal kinetic model to describe the impure bioethanol conversion to ethylene and byproducts and used it to evaluate the multi-tubular reactor (MTR) for 60 KTPA ethylene production. The simulated data agree well with experimental results. Under reaction-controlled conditions, C3-alcohols strongly suppress the formation of by-products and ethylene-from-ethanol, and slightly inhibit the formation of ethylene-via-ether. It is the suppression of the ethylene-via-ether route that causes a decrease in ethanol conversion. The predominant formation of ethylene-via-ether results in an increased ethylene yield but doubling the catalyst load is required to achieve conversion as for pure feedstock. 2-Propanol has a stronger effect on dehydration than 1-propanol. Diffusion inside the grain’s levels out the effect of C3-alcohols on the process in MTR, giving an ethylene yield as high as ~98% while dehydrating a contaminated 92% ethanol. However, impurities dilute ethanol and generate propylene (which contaminates target product), and these worsen feedstock consumption and ethylene productivity in MTR.
Sex Differences between Neuronal Loss and the Early Onset of Amyloid Deposits and Behavioral Consequences in 5xFAD Transgenic Mouse as a Model for Alzheimer’s Disease
Authors: Poon Chi Him , Wong San Tung Nicholas , Roy Jaydeep , Wang Yingyi , Chan Hui Wang Hujo , Steinbusch Harry , Blokland Arjan , Temel Yasin , Aquili Luca , Lim Lee Wei
Published: March 2023

A promising direction in the research on Alzheimer’s Disease (AD) is the identification of biomarkers that better inform the disease progression of AD. However, the performance of amyloid-based biomarkers in predicting cognitive performance has been shown to be suboptimal. We hypothesise that neuronal loss could better inform cognitive impairment. We have utilised the 5xFAD transgenic mouse model that displays AD pathology at an early phase, already fully manifested after 6 months. We have evaluated the relationships between cognitive impairment, amyloid deposition, and neuronal loss in the hippocampus in both male and female mice. We observed the onset of disease characterized by the emergence of cognitive impairment in 6-month-old 5xFAD mice coinciding with the emergence of neuronal loss in the subiculum, but not amyloid pathology. We also showed that female mice exhibited significantly increased amyloid deposition in the hippocampus and entorhinal cortex, highlighting sex-related differences in the amyloid pathology of this model. Therefore, parameters based on neuronal loss might more accurately reflect disease onset and progression compared to amyloid-based biomarkers in AD patients. Moreover, sex-related differences should be considered in studies involving 5xFAD mouse models.
Context-Dependent Role of Glucocorticoid Receptor Alpha and Beta in Breast Cancer Cell Behaviour
Authors: Butz Henriett , Saskői Éva , Krokker Lilla , Vereczki Viktória , Alpár Alán , Likó István , Tóth Erika , Szőcs Erika , Cserepes Mihály , Nagy Katalin , Kacskovics Imre , Patócs Attila
Published: March 2023

Background. The dual role of GCs has been observed in breast cancer; however, due to many concomitant factors, GR action in cancer biology is still ambiguous. In this study, we aimed to unravel the context-dependent action of GR in breast cancer. Methods. GR expression was characterized in multiple cohorts: (1) 24,256 breast cancer specimens on the RNA level, 220 samples on the protein level and correlated with clinicopathological data; (2) oestrogen receptor (ER)-positive and -negative cell lines were used to test for the presence of ER and ligand, and the effect of the GRβ isoform following GRα and GRβ overexpression on GR action, by in vitro functional assays. Results. We found that GR expression was higher in ER− breast cancer cells compared to ER+ ones, and GR-transactivated genes were implicated mainly in cell migration. Immunohistochemistry showed mostly cytoplasmic but heterogenous staining irrespective of ER status. GRα increased cell proliferation, viability, and the migration of ER− cells. GRβ had a similar effect on breast cancer cell viability, proliferation, and migration. However, the GRβ isoform had the opposite effect depending on the presence of ER: an increased dead cell ratio was found in ER+ breast cancer cells compared to ER− ones. Interestingly, GRα and GRβ action did not depend on the presence of the ligand, suggesting the role of the “intrinsic”, ligand-independent action of GR in breast cancer. Conclusions. Staining differences using different GR antibodies may be the reason behind controversial findings in the literature regarding the expression of GR protein and clinicopathological data. Therefore, caution in the interpretation of immunohistochemistry should be applied. By dissecting the effects of GRα and GRβ, we found that the presence of the GR in the context of ER had a different effect on cancer cell behaviour, but independently of ligand availability. Additionally, GR-transactivated genes are mostly involved in cell migration, which raises GR’s importance in disease progression.
Development of an Improved YOLOv7-Based Model for Detecting Defects on Strip Steel Surfaces
Authors: Wang Rijun , Liang Fulong , Mou Xiangwei , Chen Lintao , Yu Xinye , Peng Zhujing , Chen Hongyang
Published: March 2023

The detection of defects on the surface is of great importance for both the production and the application of strip steel. In order to detect the defects accurately, an improved YOLOv7-based model for detecting strip steel surface defects is developed. To enhances the ability of the model to extract features and identify small features, the ConvNeXt module is introduced to the backbone network structure, and the attention mechanism is embedded in the pooling module. To reduce the size and improves the inference speed of the model, an improved C3 module was used to replace the ELAN module in the head. The experimental results show that, compared with the original models, the mAP of the proposed model reached 82.9% and improved by 6.6%. The proposed model can satisfy the need for accurate detection and identification of strip steel surface defects.
Highly Hydrophobic Organic Coatings Based on Organopolysilazanes and Silica Nanoparticles: Evaluation of Environmental Degradation
Authors: Pérez-Gandarillas Lucía , Aragón Daniel , Manteca Carmen , Gonzalez-Barriuso Marina , Soriano Laura , Casas Abraham , Yedra Angel
Published: March 2023

Hydrophobic coatings have potential applications in various fields, including for corrosion and weathering protection. In this study, we investigated the use of organopolysilazanes (OPSZs) combined with hydrophobic nanoparticles (NPs) on steel as a substrate to obtain hydrophobic coatings. The coatings were characterized using various techniques, and their hydrophobic properties and corrosion and weathering resistance were evaluated under near-shore marine conditions with high salinity, humidity and UV radiation. Our results show that the coatings exhibited excellent hydrophobic properties and significantly improved corrosion and weathering resistance compared to an uncoated steel and a pristine polymer. These findings suggest that the developed coatings have the potential to provide protection against corrosion for atmospheric and splash exposures in marine environments.
Characterisations of La-Sr-Mn-O (LSMO) Thin Film Fabricated by RF Sputtering
Authors: Wong Yan Jing , Lau Lik Nguong , Lim Kean Pah , Hon Xiao Tong , Daud Nur Amira Azira , Kechik Mohd Mustafa Awang , Chen Soo Kien , Shabdin Muhammad Kashfi Bin , Shaari Abdul Halim , Miryala Muralidhar
Published: March 2023

A revisited study of perovskite-based manganite La0.67Sr0.33MnO3 (LSMO) deposited onto corning-glass (CG) substrates is reported here. The LSMO films were fabricated with RF sputtering with different deposition times, varying from 60 to 180 min, resulting in films with thicknesses of 35.0–109.7 nm. Rietveld refinements of the XRD spectrum showed that the samples exhibited hexagonal structures with a space group of R-3c (167) and remained unmodified structures. Clusters of monolayer growth were observed from the morphologies of the films. Interestingly, the average particle size obtained with an AFM perceived an insignificant variation of 31.7–35.6 nm despite the film thickness increment. Optical, electrical and magnetic properties were studied, as particle-size variation usually has a notable contribution to changes in these properties. It was found that the optical band gap (Eg) was in direct variation with the deposition time due to enhanced thickness and surface roughness. The temperature dependence of the resistivity graph was fitted with the percolation model to obtain further enlightenment on the electrical transport in the films. Low-field magnetoresistance (LFMR) was observed for all samples. Ferromagnetic to paramagnetic transition was observed in the vicinity of all samples’ TC values.
Numerical and Experimental Study of the Front Surface Recombination Velocities and Base Widths Effect in Multi-Crystalline Silicon Solar Cell Quantum Efficiency
Authors: Abdouli Bilel , Khezami Lotfi , Guesmi Ahlem , Assadi Aymen Amine , Rabha Mohamed Ben
Published: March 2023

Photovoltaic research activities are related to material innovation that can be obtained at a comparatively low cost. Semiconductor p-type multi-crystalline Czochralskyc (CZ)-grown silicon wafers were used in this study. The effects of front surface recombination velocities and base thickness in solar cells’ quantum efficiency are theoretically calculated. The results denote that both the surface recombination velocities and the base widths significantly impact the quantum efficiency. The results are of universal technical importance in designing solar cells and their surface structures. The main goal of this paper was to confirm the validity of the above theoretical calculations; for this purpose, silicon solar cells with front-thin porous silicon and rear interdigitated contact have been produced. A good agreement was obtained between experimentally obtained solar cells’ quantum efficiency data and the theoretical results. Therefore, the quantum efficiency of the mc-Si solar cells with porous silicon and rear interdigitated contact was enhanced up to 25% at 580–1100 nm wavelength range and up to 50% at short wavelength (400–570 nm), compared to reference mc-Si solar cells. The obtained results indicate that the rear interdigitated contact maximizes the surface area of the metal contact and improves the current collection. At the same time, the porous silicon layer passivates the front surface and reduces recombination losses.
Magnetic and Magnetoelectric Properties of AurivilliusThree- and Four-Layered Intergrowth Ceramics
Authors: Veenachary Vadla , Ramana Eskilla Venkata , Babu Simhachalam Narendra , Puli Venkata Sreenivas , Srinivas Adiraj , Srinivasan Gopalan , Saha Sujoy , Prasad Guduru , Prasad Nandiraju Venkata
Published: March 2023

In this work, we have prepared intergrowth of multiferroic compounds namely Bi4RTi3Fe0.7Co0.3O15-Bi3RTi2Fe0.7Co0.3O12−δ (BRTFCO15-BRTFCO12) (rare earth (R) = Dy, Sm, La) by solid-state reaction method. From the X-ray diffraction Rietveld refinement, the structure of the intergrowths was found to be orthorhombic in which satisfactory fittings establish the existence of three-layered (space group: b 2 c b) and four-layered compounds (space group: A21am). Analysis of magnetic measurements confirmed a larger magnetization for theSm-modified intergrowth compound (BSTFCO15-BSTFCO12) compared to Dy- and La-doped ones. The emergence of higher magnetic properties can be due to distortion in the unit cell when some Bi3+ ions are replaced with the Sm3+, bonding of Fe3+-O-Co3+ as well as a possible mixture of FexCoy-type nanoparticles that are formed generally in the synthesis of intergrowths. The changes in the magnetic state of the Aurivillius intergrowths have been reflected in the magnetoelectric (ME) coupling: higher ME coefficient (~30 mV/Cm-Oe) at lower magnetic fields and is constant up to 3 kOe. The results were corroborated by Raman spectroscopy and variation of temperature with magnetization data. The results revealed that the RE-modified intergrowth route is an effective preparative method for higher-layer Aurivillius multiferroic ceramics.
Novel Nanomaterials for Catalytic and Biological Applications
Authors: Shaik Mohammed Rafi , Adil Syed Farooq , Khan Mujeeb
Published: March 2023

Currently, nanotechnology has become an integral part of science and technology and has played a crucial role in the development of a variety of technological advancements in different industries [...]
Review on Research and Development of Abrasive Scratching of Hard Brittle Materials and Its Underlying Mechanisms
Authors: Qian Huina , Chen Mengkai , Qi Zijian , Teng Qi , Qi Huan , Zhang Li , Shan Xiaohang
Published: March 2023

Hard brittle materials such as ceramics and crystals are commonly utilized in various industries, including information technology, mechanical engineering, and semiconductors. These materials, known for their high brittleness and hardness but low fracture toughness, pose challenges in efficient and high-quality machining. Current abrasive machining techniques involve rough grinding, fine grinding, and polishing processes, with the latter being the most time-consuming and accounting for over half of the total machining time. Improving processing parameters in rough and fine grinding can increase machining efficiency, reduce surface and subsurface damage, and improve workpiece quality, ultimately reducing the polishing time. This paper explores the abrasive scratching of hard brittle materials, examining the nucleation and propagation of cracks causing surface and subsurface damage, and the underlying mechanisms. The research provides suggestions for enhancing abrasive machining efficiency and ensuring the surface quality of hard brittle materials.
Numerical and Experimental Investigation on the Abrasive Flow Machining of Artificial Knee Joint Surface
Authors: Ji Renquan , Qi Zijian , Chen Junchao , Zhang Li , Lin Kaifeng , Lu Shasha , Li Yanbiao
Published: March 2023

The titanium alloy artificial knee joint is used extensively in the current medical industry due to its distinct characteristics and properties that are like the real human knee joint, but it does need to be polished to improve its performance and service life before it can be used. Due to the complicated surface profile, the traditional abrasive flow machining technique cannot achieve a good surface finish offering uniformity and quality. Thus, in this paper, a proper constrained flow channel is designed to conduct the abrasive flow machining of the titanium alloy artificial knee joint surface to overcome these issues. A numerical study is first conducted to explore the distribution of abrasive flow velocity and pressure near the target surface in the constrained flow channel by using the COMSOL Multiphysics software, and it is found from the distribution of the dimensionless material removal rate on the target surface that the exchange of the abrasive flow inlet and outlet during the machining process is recommended to improve the surface finish uniformity. Then, the corresponding experiments are conducted to analyze the surface morphology before and after the abrasive flow machining process. It is found that the surface roughness of the target surface decreases from approximately 394 nm to 171 nm with good uniformity as well. Therefore, the proposed abrasive flow machining method with a properly designed constrained flow channel is useful for the rough polishing and fine finishing of the titanium alloy artificial joint.
Investigation of Factors Affecting the Color of Serpentine Jade from Shandong, China
Authors: Deng Shidie , Guo Ying
Published: March 2023

The color of serpentine jade is affected not only by the chemical composition, but also by some external factors. In this research, we quantitatively analyzed the color of serpentine jade and the influence of light sources, backgrounds, and thickness on its color. Thirty-six gem-quality serpentine jade samples from Tai’an, Shandong, China, were studied using eighteen Munsell neutral gray backgrounds, and three light sources (D65, F2, and A). It was found that the D65 light source appeared to be the most suitable for the display and sale of serpentine jade and the Munsell N9 background can make the color grading of serpentine jade more effective.
Roving Diver Survey as a Rapid and Cost-Effective Methodology to Register Species Richness in Sub-Antarctic Kelp Forests
Authors: Bravo Gonzalo , Kaminsky Julieta , Bagur María , Alonso Cecilia Paula , Rodríguez Mariano , Fraysse Cintia , Lovrich Gustavo , Bigatti Gregorio
Published: March 2023

Underwater sampling needs to strike a balance between time-efficient and standardized data that allow comparison with different areas and times. The roving diver survey involves divers meandering and actively searching for species and has been useful for producing fish species lists but has seldom been implemented for benthic taxa. In this study, we used this non-destructive technique to register species associated with kelp forests at the sub-Antarctic Bécasses Island (Beagle Channel, Argentina), detecting numerous species while providing the first multi-taxa inventory for the area, including macroalgae, invertebrates, and fish, with supporting photographs of each observation hosted on the citizen science platform iNaturalist. This research established a timely and cost-effective methodology for surveys with scuba diving in cold waters, promoting the obtention of new records, data sharing, and transparency of the taxonomic curation. Overall, 160 taxa were found, including 41 not reported previously for this area and three records of southernmost distribution. Other studies in nearby areas with extensive sampling efforts arrived at similar richness estimations. Our findings reveal that the roving diver survey using photographs is a good approach for creating inventories of marine species, which will serve for a better understanding of underwater biodiversity and future long-term monitoring to assess the health of kelp environments.
First Record of Megamphopus katagani Bakir, Sezgin & Myers, 2011 (Amphipoda, Photidae) in the Italian Waters: A Species Associated with the “Amphioxus Sand” Biocenosis
Authors: Mancini Emanuele , Catalano Giuseppe , Lezzi Marco , Tiralongo Francesco , Bonifazi Andrea
Published: March 2023

The biocenosis of coarse sand and gravel exposed to bottom currents (SGCF) is the typical habitat of the amphioxus Branchiostoma lanceolatum (Pallas, 1774). This species and the habitat where it lives are threatened, and there are few reports of this biocenosis in the Italian and European waters. During a sampling survey carried out along the eastern Sicily coast (Ionian Sea) the macrozoobenthic community associated with this biocenosis was investigated. In this work, we report the presence of “Amphioxus sand” habitat in the Ionian Sicilian coast and the first record of the amphipod Megamphopus katagani Bakir, Sezgin and Myers, 2011 in the Italian waters.
Chitons from Deep-Water Mollusk-Rich Deposits in the Southwestern Adriatic Sea (Mollusca, Polyplacophora)
Authors: Taviani Marco , Sosso Maurizio , Dell’Angelo Bruno
Published: March 2023

Sea-bottom sampling at bathyal depths off the Apulian margin (southwestern Adriatic Sea) recovered shelly biogenic sediments rich in mollusk remains. Noteworthy is the occurrence in such taphocoenoses of loose chiton valves, rarely reported in these environments. We identified four species of Polyplacophora, Leptochiton asellus (Gmelin, 1791), Belknapchiton alveolus (M. Sars MS, Lovén, 1846), Hanleya hanleyi (Bean in Thorpe, 1844), and the new species Leptochiton antondohrni. L. asellus (Gmelin, 1791) and B. alveolus are primarily of North Atlantic (boreo-celtic) affinity and thus considered to belong to last Pleistocene glacial assemblages, whose presence in the study area has long been ascertained. The same could be true for the valves of H. hanleyi and, possibly, Leptochiton antondohrni n. sp. Finally, we updated the list of mollusks found thus far in the deep-sea taphocoenoses of this area, including new records of North Atlantic-type taxa considered at present extinct in the Mediterranean basin.
Radar-Based Microwave Breast Imaging Using Neurocomputational Models
Authors: Bicer Mustafa Berkan
Published: March 2023

In this study, neurocomputational models are proposed for the acquisition of radar-based microwave images of breast tumors using deep neural networks (DNNs) and convolutional neural networks (CNNs). The circular synthetic aperture radar (CSAR) technique for radar-based microwave imaging (MWI) was utilized to generate 1000 numerical simulations for randomly generated scenarios. The scenarios contain information such as the number, size, and location of tumors for each simulation. Then, a dataset of 1000 distinct simulations with complex values based on the scenarios was built. Consequently, a real-valued DNN (RV-DNN) with five hidden layers, a real-valued CNN (RV-CNN) with seven convolutional layers, and a real-valued combined model (RV-MWINet) consisting of CNN and U-Net sub-models were built and trained to generate the radar-based microwave images. While the proposed RV-DNN, RV-CNN, and RV-MWINet models are real-valued, the MWINet model is restructured with complex-valued layers (CV-MWINet), resulting in a total of four models. For the RV-DNN model, the training and test errors in terms of mean squared error (MSE) are found to be 103.400 and 96.395, respectively, whereas for the RV-CNN model, the training and test errors are obtained to be 45.283 and 153.818. Due to the fact that the RV-MWINet model is a combined U-Net model, the accuracy metric is analyzed. The proposed RV-MWINet model has training and testing accuracy of 0.9135 and 0.8635, whereas the CV-MWINet model has training and testing accuracy of 0.991 and 1.000, respectively. The peak signal-to-noise ratio (PSNR), universal quality index (UQI), and structural similarity index (SSIM) metrics were also evaluated for the images generated by the proposed neurocomputational models. The generated images demonstrate that the proposed neurocomputational models can be successfully utilized for radar-based microwave imaging, especially for breast imaging.
A Web-Based Platform for the Automatic Stratification of ARDS Severity
Authors: Yahyatabar Mohammad , Jouvet Philippe , Fily Donatien , Rambaud Jérome , Levy Michaël , Khemani Robinder G. , Cheriet Farida
Published: March 2023

Acute respiratory distress syndrome (ARDS), including severe pulmonary COVID infection, is associated with a high mortality rate. It is crucial to detect ARDS early, as a late diagnosis may lead to serious complications in treatment. One of the challenges in ARDS diagnosis is chest X-ray (CXR) interpretation. ARDS causes diffuse infiltrates through the lungs that must be identified using chest radiography. In this paper, we present a web-based platform leveraging artificial intelligence (AI) to automatically assess pediatric ARDS (PARDS) using CXR images. Our system computes a severity score to identify and grade ARDS in CXR images. Moreover, the platform provides an image highlighting the lung fields, which can be utilized for prospective AI-based systems. A deep learning (DL) approach is employed to analyze the input data. A novel DL model, named Dense-Ynet, is trained using a CXR dataset in which clinical specialists previously labelled the two halves (upper and lower) of each lung. The assessment results show that our platform achieves a recall rate of 95.25% and a precision of 88.02%. The web platform, named PARDS-CxR, assigns severity scores to input CXR images that are compatible with current definitions of ARDS and PARDS. Once it has undergone external validation, PARDS-CxR will serve as an essential component in a clinical AI framework for diagnosing ARDS.
Incidence of Intoxications in the Emergency Department of Galati Hospital with Examples of Cardiovascular Effects of MDMA Intoxication
Authors: Dragomir Liliana , Marina Virginia , Anghele Mihaela , Anghele Aurelian-Dumitrache , Moscu Cosmina Alina
Published: March 2023

MDMA (3,4-methylenedioxymethamphetamine; commonly referred to as “Molly” or “ecstasy”) is a synthetic compound, structurally and pharmacologically similar to both amphetamines and mescaline. MDMA differs somewhat from traditional amphetamines in that it is not structurally similar to serotonin. Cocaine is rare and cannabis is consumed less frequently than in Western Europe. Heroin is the drug of choice for the poor in Bucharest, Romania’s capital of two million people, and alcoholism is common in villages where more than a third of the population lives in poverty. By far, the most popular drugs are Legal Highs (Romanians call them “ethnobotanics”). All of these drugs have significant effects on cardiovascular function that contribute significantly to adverse events. Most adverse cardiac events occur in young adults and are potentially reversible. Poisoning among patients aged 17 years and over was commonly seen in the Emergency Departments of a large tertiary hospital in the city centre, accounting for 3.2% of all patients. In a third of the poisonings, more than one substance was used. Intoxication with ethnobotanicals was the most frequently observed, followed by use of drugs from the amphetamine group. The majority of patients presenting to the Emergency Department were male. Therefore, this study suggests further research on hazardous alcohol consumption and drug abuse.