bluuebunny/crossref_metadata_2025 huggingface dataset:
Federated Learning for IoT Intrusion Detection
Authors: Lazzarini Riccardo , Tianfield Huaglory , Charissis Vassilis
Published: July 2023

The number of Internet of Things (IoT) devices has increased considerably in the past few years, resulting in a large growth of cyber attacks on IoT infrastructure. As part of a defense in depth approach to cybersecurity, intrusion detection systems (IDSs) have acquired a key role in attempting to detect malicious activities efficiently. Most modern approaches to IDS in IoT are based on machine learning (ML) techniques. The majority of these are centralized, which implies the sharing of data from source devices to a central server for classification. This presents potentially crucial issues related to privacy of user data as well as challenges in data transfers due to their volumes. In this article, we evaluate the use of federated learning (FL) as a method to implement intrusion detection in IoT environments. FL is an alternative, distributed method to centralized ML models, which has seen a surge of interest in IoT intrusion detection recently. In our implementation, we evaluate FL using a shallow artificial neural network (ANN) as the shared model and federated averaging (FedAvg) as the aggregation algorithm. The experiments are completed on the ToN_IoT and CICIDS2017 datasets in binary and multiclass classification. Classification is performed by the distributed devices using their own data. No sharing of data occurs among participants, maintaining data privacy. When compared against a centralized approach, results have shown that a collaborative FL IDS can be an efficient alternative, in terms of accuracy, precision, recall and F1-score, making it a viable option as an IoT IDS. Additionally, with these results as baseline, we have evaluated alternative aggregation algorithms, namely FedAvgM, FedAdam and FedAdagrad, in the same setting by using the Flower FL framework. The results from the evaluation show that, in our scenario, FedAvg and FedAvgM tend to perform better compared to the two adaptive algorithms, FedAdam and FedAdagrad.
Haplotypes of the tRNAleu-COII mtDNA Region in Russian Apis mellifera Populations
Authors: Kaskinova Milyausha D. , Gaifullina Luisa R. , Saltykova Elena S.
Published: July 2023

Analysis of the mtDNA tRNAleu-COII locus is a widely used tool to establish belonging to a particular evolutionary lineage of Apis mellifera L. (lineages A, M, C, O, and Y). In Russia, most of the area was once inhabited by Apis mellifera mellifera from the M evolutionary lineage, but the introduction of bee subspecies from the southern regions of Russia (A. m. caucasica, A. m. carnica) and from abroad (A. m. carnica, A. m. ligustica) led to fragmentation of their native range. In this study, the results of assessing the haplotype number for the tRNAleu-COII locus of mtDNA in Russian Apis mellifera populations were presented. We analyzed 269 colonies from 19 regions of Russia. As a result, two evolutionary lineages were identified: the East European lineage C (26.4%) and the Northwestern European lineage M (73.6%). A total of 29 haplotypes were identified, 8 of them were already reported, and 21 were found to be novel. From the C lineage, haplotypes C1, C2, C2c, C2j, and C3 were predominant. All M lineage samples from Russia belong to the M17 and M4’ haplogroups but have only minor variations in the form of nucleotide substitutions. An analysis of publications devoted to the tRNAleu-COII locus haplotypes, as well as an analysis of the available tRNAleu-COII sequences in GenBank, showed that there is still a problem with the haplotype nomenclature.
A Retrospective Clinico-Pathologic Study of 35 Dogs with Urethral Transitional Cell Carcinoma Undergoing Treatment
Authors: Ghisoni Giulia , Foglia Armando , Sabattini Silvia , Agnoli Chiara , Dondi Francesco , Perfetti Simone , Marconato Laura
Published: July 2023

Chemotherapy and cyclooxygenase inhibitors (COXi) are primary treatments for canine urethral transitional cell carcinoma (uTCC), a tumor known for its aggressiveness and poor prognosis. This retrospective study aimed to evaluate the clinico-pathological characteristics, treatment modalities, and prognostic factors of 35 dogs with confirmed uTCC that received chemotherapy and COXi. Upon admission, urethral obstruction (UO) and urinary tract infection (UTI) were observed in seven (20%) dogs each. Gemcitabine (n = 20; 57.1%) and vinblastine (n = 10; 28.6%) were commonly used as first-line therapies, with four dogs also receiving radiation therapy. Based on RECIST, one (2.9%) dog achieved complete remission, nine (25.7%) partial remission, 20 (57.14%) showed stable disease, and five (14.3%) progressed. Among dogs with UO, six (85.7%) showed resolution or improvement after the first chemotherapy dose. The median time to local progression was 171 days (range: 107–235), and the median survival time was 333 days (range: 158–508). Dogs with UO upon admission had a higher risk of local progression, while both UO and UTI were associated with an increased risk of overall disease progression and tumor-related death. Additionally, gemcitabine significantly improved metastatic control. This study identified UO and UTI as negative prognostic factors, highlighting the importance of a multimodal approach in managing uTCC.
Productive Performance, Physiological Variables, and Carcass Quality of Finishing Pigs Supplemented with Ferulic Acid and Grape Pomace under Heat Stress Conditions
Authors: Ospina-Romero María A. , Medrano-Vázquez Leslie S. , Pinelli-Saavedra Araceli , Sánchez-Villalba Esther , Valenzuela-Melendres Martín , Martínez-Téllez Miguel Ángel , Barrera-Silva Miguel Ángel , González-Ríos Humberto
Published: July 2023

The effect of individual and combined supplementation of FA and GPM on physiological variables, productive performance, and carcass characteristics of finishing pigs under heat stress conditions were investigated. Forty Yorkshire × Duroc pigs (80.23 kg) were individually housed and randomly distributed into 4 groups under a 2 × 2 factorial arrangement (n = 10): Control (basal diet, BD); FA, BD + 25 mg FA; GPM, BD with 2.5% GPM; and MIX, BD with 25 mg FA and 2.5% GPM. Additives were supplemented for 31 days. The inclusion of FA or GPM did not modify rectal temperature and respiratory rate. There was an effect of the interaction on FI, which increased when only GPM was supplemented, with respect to Control and MIX (p < 0.05). Average daily gain (ADG) and feed conversion (FC) were not affected by treatments (p > 0.05). The inclusion of FA improved hot and cold carcass weight, while the addition of GPM decreased the marbling (p < 0.05) and tended to increase loin area (p < 0.10). GPM increased liver weight (p < 0.05). The addition of GPM and FA can improve some carcass characteristics under heat stress conditions. It is necessary to continue investigating different levels of inclusion of GPM and FA in finishing pigs’ diets.
Is the Intrasexual Competition in Male Red Deer Reflected in the Ratio of Stable Isotopes of Carbon and Nitrogen in Faeces?
Authors: Vedel Giovanni , de la Peña Eva , Moreno-Rojas Jose Manuel , Carranza Juan
Published: July 2023

Isotopic analysis of carbon and nitrogen in faeces is a reliable methodology for studying ecology in wildlife. Here, we tested this technique to detect variations in carbon and nitrogen isotopic ratios (δ13C and δ15N) in two different intrasexual competition scenarios of male Iberian red deer (Cervus elaphus hispanicus) using faeces of individuals collected during hunting actions in South-eastern Spain. The carbon isotopic ratio (δ13C) was not found to be significant, likely due to similar diet composition in all individuals. However, the nitrogen isotopic ratio (δ15N) was found to be lower in populations where sexual competition between males during the rut was higher compared to low-competition populations. Therefore, this study suggests a different use of proteins by an individual male red deer depending on the sexually competitive context in which he lives. Although further research is needed, these results show the potential of isotopic analysis as a tool for studying individual and populational variations in the level of intrasexual competition, with implications in evolutionary ecology and population management.
Hematological Normality, Serum Biochemistry, and Acute Phase Proteins in Healthy Beef Calves in the Brazilian Savannah
Authors: Motta Guilherme Augusto , Neto Paulo Sabino Milhomen , Nociti Ricardo Perecin , Santana Áureo Evangelista
Published: July 2023

The Brazilian savannah region, characterized by high average temperatures, well-defined rainy and dry seasons, soil with low productive potential, and high pressure for parasitic diseases, is home to the highest percentage of the beef herd, which is the world’s largest commercial beef producer. Therefore, breeds that present rusticity combined with productivity are the focus of research in cattle breeding in the region. Considering their geographic particularities and their effects on the animals’ blood parameters, the objective was to study the behavior of hematological variables, serum biochemistry, and acute phase proteins in beef calves at weaning age. Jugular blood samples were collected in a single day from 30 weaning calves (about eight months old and 200 kg of body weight) from the following breeds: Nellore, Senepol, Nellore × Aberdeen Angus cross, Nellore × Senepol cross, and Nellore × Aberdeen Angus × Senepol cross. Hematological data were obtained using an automatic cell counter, serum biochemical measurements were obtained using commercial kits, and the electrophoretogram was obtained using the SDS-page technique. In general, the results were consistent with data already published in similar situations regarding health status, age, and level of metabolic activity. However, differences observed between groups can be explained by differences observed in other concurrent variables like temperament. The pure zebu breed was more reactive than pure taurine. While crossbreds showed intermediate values, and parasitic infestation, the pure taurine breed with higher parasite infestation, while the zebu breed had lower values, which produced effects in some laboratory tests, and generated differences between breeds. In conclusion, the reference intervals available for healthy animals can be routinely used without interference from the geographic region for animals produced without nutritional failures as long as changes are recorded in pathological, infectious, metabolic, or nutritional deficiency situations. However, it is suggested that a study covering a larger number of herds may demonstrate a greater geographic effect on the studied variables.
miR-430 microRNA Family in Fishes: Molecular Characterization and Evolution
Authors: Jiménez-Ruiz Claudio A. , de la Herrán Roberto , Robles Francisca , Navajas-Pérez Rafael , Cross Ismael , Rebordinos Laureana , Ruiz-Rejón Carmelo
Published: July 2023

The miR-430 microRNA family has been described in multiple fish species as one of the first microRNAs expressed by the zygote. It has been suggested that this family is implicated in maternal mRNA elimination, but may also play a role in steroidogenesis, sexual differentiation, and flatfish metamorphosis. The miR-430 sequences have been found in multiple-copy tandem clusters but evidence of their conservation outside of teleost fishes is scarce. In the present study, we have characterized the tandem repeats organization of these microRNAs in different fish species, both model and of interest in aquaculture. A phylogenetic analysis of this family has allowed us to identify that the miR-430 duplication, which took place before the Chondrostei and Neopterygii groups’ divergence, has resulted in three variants (“a”, “b”, and “c”). According to our data, variant “b” is the most closely related to the ancestral sequence. Furthermore, we have detected isolated instances of the miR-430 repeat subunit in some species, which suggests that this microRNA family may be affected by DNA rearrangements. This study provides new data about the abundance, variability, and organization of the miR-430 family in fishes.
Epidemiology of Antimicrobial Resistance Genes in Staphyloccocus aureus Isolates from a Public Database in a One Health Perspective—Sample Characteristics and Isolates’ Sources
Authors: Zaghen Francesca , Sora Valerio Massimo , Meroni Gabriele , Laterza Giulia , Martino Piera Anna , Soggiu Alessio , Bonizzi Luigi , Zecconi Alfonso
Published: July 2023

Staphylococcus aureus is considered one of the most widespread bacterial pathogens for both animals and humans, being the causative agent of various diseases like food poisoning, respiratory tract infections, nosocomial bacteremia, and surgical site and cardiovascular infections in humans, as well as clinical and subclinical mastitis, dermatitis, and suppurative infections in animals. Thanks to their genetic flexibility, several virulent and drug-resistant strains have evolved mainly due to horizontal gene transfer and insurgence of point mutations. Infections caused by the colonization of such strains are particularly problematic due to frequently occurring antibiotic resistance, particulary methicillin-resistant S. aureus (MRSA), and are characterized by increased mortality, morbidity, and hospitalization rates compared to those caused by methicillin-sensitive S. aureus (MSSA). S. aureus infections in humans and animals are a prime example of a disease that may be managed by a One Health strategy. In fact, S. aureus is a significant target for control efforts due to its zoonotic potential, the frequency of its illnesses in both humans and animals, and the threat posed by S. aureus antibiotic resistance globally. The results of an epidemiological analysis on a worldwide public database (NCBI Pathogen Detection Isolate Browser; NPDIB) of 35,026 S. aureus isolates were described. We considered the diffusion of antibiotic resistance genes (ARGs), in both human and animal setting, and the results may be considered alarming. The result of this study allowed us to identify the presence of clusters with specific ARG patterns, and that these clusters are associated with different sources of isolation (e.g., human, non-human).
Complex II Biology in Aging, Health, and Disease
Authors: Goetzman Eric , Gong Zhenwei , Zhang Bob , Muzumdar Radhika
Published: July 2023

Aging is associated with a decline in mitochondrial function which may contribute to age-related diseases such as neurodegeneration, cancer, and cardiovascular diseases. Recently, mitochondrial Complex II has emerged as an important player in the aging process. Mitochondrial Complex II converts succinate to fumarate and plays an essential role in both the tricarboxylic acid (TCA) cycle and the electron transport chain (ETC). The dysfunction of Complex II not only limits mitochondrial energy production; it may also promote oxidative stress, contributing, over time, to cellular damage, aging, and disease. Intriguingly, succinate, the substrate for Complex II which accumulates during mitochondrial dysfunction, has been shown to have widespread effects as a signaling molecule. Here, we review recent advances related to understanding the function of Complex II, succinate signaling, and their combined roles in aging and aging-related diseases.
Material Point Simulation Method for Concrete Medium Fracture and Fragmentation under Blast Loading
Authors: Liu Zheng , Liu Jun , Xie Xianqi , Zhen Mengyang , Wang Yue , Ou Chen , Zheng Haowen
Published: July 2023

The nature of the fracture and fragmentation processes in concrete medium under blast loading is the transformation of the medium from continuum to discontinuity. Coupled with the significant rate correlation of concrete medium, its mechanical behavior presents a high degree of complexity. When tackling this problem, the finite element method (FEM) frequently encounters problems such as grid distortion and even negative volume, whereas the material point method (MPM) can efficiently avoid these problems. Furthermore, the original Holmquist-Johnson-Cook (HJC) model does not take the segmented characteristics of the calculation function for the dynamic increasing factor into consideration. As a result, in this article, first, the calculation function for the dynamic increasing factor in the HJC model was modified by the Split-Hopkinson Pressure Bar (SHPB) experiment, and an improved HJC model was proposed; second, an MPM simulation program was developed, and the improved HJC concrete model was embedded into the simulation program; and finally, the simulation program was verified by numerical examples, and the results show that the developed simulation program can better simulate the fracture and fragmentation process of the concrete medium under blast loading, especially the pulverization characteristics of the medium in the near zone of the load.
Modeling of a Digital Twin for Magnetic Bearings
Authors: Taha Omer W. , Hu Yefa
Published: July 2023

As an essential enabling technology to realize advanced concepts such as digitization, intelligence, and service, information technology plays a critical role in shaping modern society and driving innovation across various industries and domains. The concept of the digital twin is attracting attention from academics and industry, and how to apply it in various fields. In this paper, the performance of the magnetic bearing system may be simulated in real-time using a digital twin, especially the resulting vibration from the unbalanced rotor mass, which caused a drop in performance and a high risk of system instability and potential safety accidents. It is suggested to use a model-data combination driven digital twin model to examine its dynamic characteristics and vibration mechanism. The vibration data of the magnetic bearing was collected through experiments and compared with the data derived from the simulation results. The efficiency of the suggested strategy is demonstrated by confirming that digitally anticipated vibration signals are consistent with physical space measurements. The result shows that the fine digital twin geometric model of magnetic bearing is more consistent with the actual operation. By allowing the identification of problems before they become critical, using a digital twin may increase the dependability of magnetic bearings while reducing the possibility of unexpected downtime or failures.
Flexible Job Shop Scheduling Optimization for Green Manufacturing Based on Improved Multi-Objective Wolf Pack Algorithm
Authors: Li Jian , Li Huankun , He Pengbo , Xu Liping , He Kui , Liu Shanhui
Published: July 2023

Green manufacturing has become a new production mode for the development and operation of modern and future manufacturing industries. The flexible job shop scheduling problem (FJSP), as one of the key core problems in the field of green manufacturing process planning, has become a hot topic and a difficult issue in manufacturing production research. In this paper, an improved multi-objective wolf pack algorithm (MOWPA) is proposed for solving a multi-objective flexible job shop scheduling problem with transportation constraints. Firstly, a multi-objective flexible job shop scheduling model with transportation constraints is established, which takes the maximum completion time and total energy consumption as the optimization objectives. Secondly, an improved wolf pack algorithm is proposed, which designs individual codes from two levels of process and machine. The precedence operation crossover (POX) operation is used to improve the intelligent behavior of wolves, and the optimal Pareto solution set is obtained by introducing non-dominated congestion ranking. Thirdly, the Pareto solution set is selected using the gray relational decision analysis method and analytic hierarchy process to obtain the optimal scheduling scheme. Finally, the proposed algorithm is compared with other algorithms through a variety of standard examples. The analysis results show that the improved multi-objective wolf pack algorithm is superior to other algorithms in terms of solving speed and convergence performance of the Pareto solution, which shows that the proposed algorithm has advantages when solving FJSPs.
A New Hybrid Algorithm Based on Improved MODE and PF Neighborhood Search for Scheduling Task Graphs in Heterogeneous Distributed Systems
Authors: Lotfi Nasser , Ghadiri Nejad Mazyar
Published: July 2023

Multi-objective task graph scheduling is a well-known NP-hard problem that plays a significant role in heterogeneous distributed systems. The solution to the problem is expected to optimize all scheduling objectives. Pretty large state-of-the-art algorithms exist in the literature that mostly apply different metaheuristics for solving the problem. This study proposes a new hybrid algorithm comprising an improved multi-objective differential evolution algorithm (DE) and Pareto-front neighborhood search to solve the problem. The novelty of the proposed hybrid method is achieved by improving DE and hybridizing it with the neighborhood search method. The proposed method improves the performance of differential evolution by applying appropriate solution representation as well as effective selection, crossover, and mutation operators. Likewise, the neighborhood search algorithm is applied to improve the extracted Pareto-front and speed up the evolution process. The effectiveness and performance of the developed method are assessed over well-known test problems collected from the related literature. Meanwhile, the values of spacing and hyper-volume metrics are calculated. Moreover, the Wilcoxon signed method is applied to carry out pairwise statistical tests over the obtained results. The obtained results for the makespan, reliability, and flow-time of 50, 18, and 41, respectively, by the proposed hybrid algorithm in the study confirmed that the developed algorithm outperforms all proposed methods considering the performance and quality of objective values.
Catalytic Evaluation of Hafnium Modified SiO2 for the Dehydration of Alcohols
Authors: Esteban Benito Heriberto , García Alamilla Ricardo , García Serrano Luz Arcelia , Paraguay Delgado Francisco , Carmona García Juan Antonio
Published: July 2023

The influence of hafnium metal (Hf) and sulfate ions (SO42−) on the acidic properties of SiO2 mesopores synthesized by a non-hydrothermal method was studied using the following characterization techniques; TG-DTG, XRD, BET, SEM, TEM, EDS, FTIR, n-butylamine titration, FTIR-pyridine, and alcohol dehydration. The incorporation of 3.6% mol of Hf during the silicate synthesis step caused the characteristic structural arrangement of MCM-41 to collapse. However, an increase in the acid strength of the catalyst of up to 315 mV was observed, with Brönsted and Lewis-type acid sites being mostly present therein. Furthermore, the acidity of Hf- and (SO42−) -modified SiO2 in the dehydration of ethanol and methanol was evaluated, resulting in a selectivity towards ethylene and dimethyl ether, respectively. Acid solids have enormous potential to produce important compounds for the chemical industry using alternative routes other than petrochemical processes. They also represent a significant advance for biorefineries.
Is Corticosteroid Treatment Beneficial in Sudden Sensorineural Hearing Loss? A Large Retrospective Study
Authors: Chen Itay , Perez Ronen , Eligal Shalom , Menahem Ori , Salem Riki , Sichel Jean-Yves , Shaul Chanan
Published: July 2023

The main treatment approaches for sudden sensorineural hearing loss (SSNHL) involve oral and intratympanic corticosteroids, but their efficacy remains controversial. The study objective was to evaluate the benefit of oral corticosteroids followed by intratympanic salvage treatment. This was conducted by comparing the hearing results of post-treatment patients arriving early and pretreatment patients arriving late over the same time points after the onset of HL. A cohort of 776 patients with SSNHL was classified into four groups by time from onset of symptoms to the initiation of treatment (weeks). The post-treatment audiometry of those patients presenting during the first and second week post-HL was compared to the pretreatment audiometry of those presenting in weeks three and four. The post-treatment audiometry of week one and pretreatment audiometry of week three was conducted 17.2 ± 4 and 19.4 ± 3 (p = 0.13) days post-HL onset, respectively. The post-treatment audiometry of week two and pretreatment audiometry of week four was conducted on days 24.6 ± 4 and 25.2 ± 3 (p = 0.32). The pure-tune average for week one and three groups was 36.7 ± 28 and 37.5 ± 19 dB (p = 0.55), and for weeks 2 and 4, it was 31.7 ± 22 and 36.6 ± 23 dB (p = 0.1). Similarly, no significant differences in speech recognition threshold and speech discrimination were found. These results question the benefit of corticosteroid treatment for SSNHL and suggest that improvements may be due to the natural healing process.
Power System Reliability Evaluation Based on Chronological Booth–Baleriaux Method
Authors: Oh Hyobin , Shin Hansol , Kwag Kyuhyeong , Hwang Pyeongik , Kim Wook
Published: July 2023

The complexity of modern power systems is increasing because of the development of various intermittent generators. In practical reliability evaluations, it is essential to include both the failure of conventional generators and the output characteristics of renewable energy; the use of the latter has increased rapidly. The weather-dependent nature of renewable energy output, which is inexplicable in the load duration curve method, highlights the need for further study of the methods of a reliability evaluation that can consider temporal characteristics. This paper proposes a deterministic reliability evaluation method based on the Booth–Baleriaux method, chronologically extended to address the preventative maintenance schedule of a generator and the characteristics of renewable energy. The proposed method was applied to an IEEE reliability test system for performance verification, and a reliability evaluation was performed considering various chronological patterns. The proposed method was also applied to determine the adequate capacity reserve that should be installed in a Korean power system. The proposed method is stable, and it produced robust results.
A Multi-Layer Feature Fusion Model Based on Convolution and Attention Mechanisms for Text Classification
Authors: Yang Hua , Zhang Shuxiang , Shen Hao , Zhang Gexiang , Deng Xingquan , Xiong Jianglin , Feng Li , Wang Junxiong , Zhang Haifeng , Sheng Shenyang
Published: July 2023

Text classification is one of the fundamental tasks in natural language processing and is widely applied in various domains. CNN effectively utilizes local features, while the Attention mechanism performs well in capturing content-based global interactions. In this paper, we propose a multi-layer feature fusion text classification model called CAC, based on the Combination of CNN and Attention. The model adopts the idea of first extracting local features and then calculating global attention, while drawing inspiration from the interaction process between membranes in membrane computing to improve the performance of text classification. Specifically, the CAC model utilizes the local feature extraction capability of CNN to transform the original semantics into a multi-dimensional feature space. Then, global attention is computed in each respective feature space to capture global contextual information within the text. Finally, the locally extracted features and globally extracted features are fused for classification. Experimental results on various public datasets demonstrate that the CAC model, which combines CNN and Attention, outperforms models that solely rely on the Attention mechanism. In terms of accuracy and performance, the CAC model also exhibits significant improvements over other models based on CNN, RNN, and Attention.
SF-ECG: Source-Free Intersubject Domain Adaptation for Electrocardiography-Based Arrhythmia Classification
Authors: Rafi Taki Hasan , Ko Young-Woong
Published: July 2023

Electrocardiography (ECG)-based arrhythmia classification intends to have a massive role in cardiovascular disease monitoring and early diagnosis. However, ECG datasets are mostly imbalanced and have regularization to use real-time patient data due to privacy concerns. Traditional models do not generalize on unseen cases and are also unable to preserve data privacy. Which incentivizes performance degradation in existing models with privacy limitations. To tackle generalization and privacy issues together, we introduce the framework SF-ECG, a source-free domain adaptation approach for patient-specific ECG classification. This framework does not require source data during adaptation, which solves the privacy issue during adaptation. We adopt a generative model (GAN) that learns to synthesize patient-specific ECG data in data-inefficient classes to make additional source data for imbalanced classes. Then, we use the local structure clustering method to strongly align target ECG features with similar neighbors. After seizing clustered target features, we use a classifier that is trained on source data with generated source samples, which makes the model generalizable in classifying unseen data. Empirical results under different experimental conditions in various interdomain datasets prove that the proposed framework achieves 0.8% improvements in UDA settings, along with preserving privacy and generalizability.
Using Ensemble OCT-Derived Features beyond Intensity Features for Enhanced Stargardt Atrophy Prediction with Deep Learning
Authors: Mishra Zubin , Wang Ziyuan , Sadda SriniVas R. , Hu Zhihong
Published: July 2023

Stargardt disease is the most common form of juvenile-onset macular dystrophy. Spectral-domain optical coherence tomography (SD-OCT) imaging provides an opportunity to directly measure changes to retinal layers due to Stargardt atrophy. Generally, atrophy segmentation and prediction can be conducted using mean intensity feature maps generated from the relevant retinal layers. In this paper, we report an approach using advanced OCT-derived features to augment and enhance data beyond the commonly used mean intensity features for enhanced prediction of Stargardt atrophy with an ensemble deep learning neural network. With all the relevant retinal layers, this neural network architecture achieves a median Dice coefficient of 0.830 for six-month predictions and 0.828 for twelve-month predictions, showing a significant improvement over a neural network using only mean intensity, which achieved Dice coefficients of 0.744 and 0.762 for six-month and twelve-month predictions, respectively. When using feature maps generated from different layers of the retina, significant differences in performance were observed. This study shows promising results for using multiple OCT-derived features beyond intensity for assessing the prognosis of Stargardt disease and quantifying the rate of progression.
Comprehensive Comparative Study on Permanent-Magnet-Assisted Synchronous Reluctance Motors and Other Types of Motor
Authors: Du Guanghui , Zhang Guiyuan , Li Hui , Hu Chengshuai
Published: July 2023

At present, the induction motor (IM), synchronous reluctance motor (SynRM), ferrite-assisted synchronous reluctance motor (ferrite-assisted SynRM) and interior permanent magnet motor (IPM) are research hotspots, but comprehensive comparative research on the four motors is still rare. This paper mainly compares the four motors from the aspects of electromagnetic performance, material cost and temperature distribution. Firstly, the volume of the four motors is ensured to be the same. The influence of the rotor design parameters of the SynRM, ferrite-assisted SynRM and IPM on the electromagnetic properties of the machine is analyzed. Secondly, based on the effects of each parameter, the overall design parameters of the four motors are determined. The electromagnetic performance, material cost and temperature of the four motors are compared and discussed. Finally, the comparison results are summarized, and the advantages of the four motors are analyzed. In different applications, the electromagnetic performance, heat dissipation and cost requirements of the four motors are different. Therefore, this paper makes a comprehensive comparison of the four motors to provide a reference for the selection of motors for different applications.
Experimenting with Extreme Learning Machine for Biomedical Image Classification
Authors: Mercaldo Francesco , Brunese Luca , Martinelli Fabio , Santone Antonella , Cesarelli Mario
Published: July 2023

Currently, deep learning networks, with particular regard to convolutional neural network models, are typically exploited for biomedical image classification. One of the disadvantages of deep learning is that is extremely expensive to train due to complex data models. Extreme learning machine has recently emerged which, as shown in experimental studies, can produce an acceptable predictive performance in several classification tasks, and at a much lower training cost compared to deep learning networks that are trained by backpropagation. We propose a method devoted to exploring the possibility of considering extreme learning machines for biomedical classification tasks. Binary and multiclass classification in four case studies are considered to demonstrate the effectiveness of extreme learning machine, considering the biomedical images acquired with the dermatoscope and with the blood cell microscope, showing that the extreme learning machine can be successfully applied for biomedical image classification.
Analyzing the Risk Factors of Traffic Accident Severity Using a Combination of Random Forest and Association Rules
Authors: Wang Jianyu , Ma Shuo , Jiao Pengpeng , Ji Lanxin , Sun Xu , Lu Huapu
Published: July 2023

This study explores risk factors influencing the at-fault party in traffic accidents and analyzes their impact on traffic accident severity. Based on the traffic accident data of Shenyang City, Liaoning Province, China, from 2018 to 2020, 19 attribute variables including road attributes, time attributes, environmental attributes, and characteristics of the at-fault parties with either full responsibility, primary responsibility, or equal responsibility of the traffic accidents were extracted and analyzed in conjunction with the built environment attributes, such as road network density and POI (points of interest) density at the sites of traffic accidents. Using the RF-SHAP method to determine the relative importance of risk factors influencing the severity of traffic accidents with either motor vehicles or vulnerable groups at-fault, the top ten risk factors influencing the severity of traffic accidents with vulnerable road users as the at-fault parties are: functional zone, density of shopping POI, density of services POI, cause of accident, travel mode, collision type, season, road type, age of driver, and physical isolation. Travel mode, season, and road speed limit are more important risk factors for traffic accidents, with motor vehicle drivers as the at-fault parties. The density of service POI and cause of the accident are less critical for traffic accidents with motor vehicle drivers than traffic accidents with vulnerable road users who are at-fault. Subsequently, the Apriori algorithm based on association rules is used to analyze the important causal factors of traffic accidents, so as to explore the influence mechanism of multiple causal factors and their implied strong association rules. Our results show that most combined factors are associated with the matched Service and Shopping POI features. This study provides valuable information on the perceived risk of fatal accidents and highlights the built environment’s significant influence on fatal traffic accidents. Management strategies targeting the most typical combinations of accident risk factors are proposed for preventing fatalities and injuries in serious traffic accidents.
Implementation of Smart NFC Door Access System for Hotel Room
Authors: JosephNg Poh Soon , BrandonChan Pin Sen , Phan Koo Yuen
Published: July 2023

Security remains a top priority for those users in the hotel, even with the advent of innovative technological advances. This is because many tragic incidents, such as theft and crime, have occurred with unrestricted access. This paper proposes an intelligent door access system that would allow hotel guests to authenticate into their rooms without resorting to traditional closeness access methods. Therefore, research was conducted to solidify the understanding and refine the capabilities of the proposed system. This project aims to promote high-security aspects access system technology, which is Near-Field Communication with the use of application that have the function of simulated smart keys for explicit validation access. A Host-Card Emulator opens the opportunities for efficient financial benefit and the launch of a protective mechanism in the post-pandemic period. The suggested method was statistically and analytically accessed on hotel guests and staff from various hotels in Malaysia. The proposed system is a contactless NFC access control system that employs smartphone Host Card Emulation application technology to reduce the need for appropriate physical access, enhance security, and publicize the use of mobile access systems in the hospitality industry.
Influence of the Madden–Julian Oscillation (MJO) on Tropical Cyclones Affecting Tonga in the Southwest Pacific
Authors: Tu’uholoaki Moleni , Espejo Antonio , Sharma Krishneel K. , Singh Awnesh , Wandres Moritz , Damlamian Herve , Chand Savin
Published: July 2023

The modulating influence of the Madden–Julian oscillation (MJO) on tropical cyclones (TCs) has been examined globally, regionally, and subregionally, but its impact on the island scale remains unclear. This study investigates how TC activity affecting the Tonga region is being modulated by the MJO, using the Southwest Pacific Enhanced Archive of Tropical Cyclones (SPEArTC) and the MJO index. In particular, this study investigates how the MJO modulates the frequency and intensity of TCs affecting the Tonga region relative to the entire study period (1970–2019; hereafter referred to as all years), as well as to different phases of the El Niño southern oscillation (ENSO) phenomenon. Results suggest that the MJO strongly modulates TC activity affecting the Tonga region. The frequency and intensity of TCs is enhanced during the active phases (phases six to eight) in all years, including El Niño and ENSO-neutral years. The MJO also strongly influences the climatological pattern of genesis of TCs affecting the Tonga region, where more (fewer) cyclones form in the active (inactive) phases of the MJO and more genesis points are clustered (scattered) near (away from) the Tonga region. There were three regression curves that best described the movement of TCs in the region matching the dominant steering mechanisms in the Southwest Pacific region. The findings of this study can provide climatological information for the Tonga Meteorological Service (TMS) and disaster managers to better understand the TC risk associated with the impact of the MJO on TCs affecting the Tonga region and support its TC early warning system.
Robust Fisher-Regularized Twin Extreme Learning Machine with Capped L1-Norm for Classification
Authors: Xue Zhenxia , Cai Linchao
Published: July 2023

Twin extreme learning machine (TELM) is a classical and high-efficiency classifier. However, it neglects the statistical knowledge hidden inside the data. In this paper, in order to make full use of statistical information from sample data, we first come up with a Fisher-regularized twin extreme learning machine (FTELM) by applying Fisher regularization into TELM learning framework. This strategy not only inherits the advantages of TELM, but also minimizes the within-class divergence of samples. Further, in an effort to further boost the anti-noise ability of FTELM method, we propose a new capped L1-norm FTELM (CL1-FTELM) by introducing capped L1-norm in FTELM to dwindle the influence of abnormal points, and CL1-FTELM improves the robust performance of our FTELM. Then, for the proposed FTELM method, we utilize an efficient successive overrelaxation algorithm to solve the corresponding optimization problem. For the proposed CL1-FTELM, an iterative method is designed to solve the corresponding optimization based on re-weighted technique. Meanwhile, the convergence and local optimality of CL1-FTELM are proved theoretically. Finally, numerical experiments on manual and UCI datasets show that the proposed methods achieve better classification effects than the state-of-the-art methods in most cases, which demonstrates the effectiveness and stability of the proposed methods.
The Phytochemical Constituents of Medicinal Plants for the Treatment of Chronic Inflammation
Authors: Kim Young-Joo , Kang Ki Sung
Published: July 2023

Prolonged exposure to inflammatory mediators can lead to tissue damage, fibrosis, angiogenesis, and altered cellular metabolism [...]
Choice of Polymer, but Not Mesh Structure Variation, Reduces the Risk of Bacterial Infection with Staphylococcus aureus In Vivo
Authors: Schmitz Sophia M. , Helmedag Marius J. , Kroh Andreas , Heise Daniel , Klinge Uwe , Lambertz Andreas , Hornef Mathias W. , Neumann Ulf P. , Eickhoff Roman M.
Published: July 2023

Background: Synthetic mesh material is of great importance for surgical incisional hernia repair. The physical and biochemical characteristics of the mesh influence mechanical stability and the foreign body tissue reaction. The influence on bacterial infections, however, remains ill-defined. The aim of the present study was to evaluate the influence of a modified mesh structure with variation in filament linking on the occurrence of bacterial infection that is indicated by the occurrence of CD68+, CD4+, and CD8+ cells in two different materials. Methods: A total of 56 male Sprague Dawley rats received a surgical mesh implant in a subcutaneous abdominal position. The mesh of two different polymers (polypropylene (PP) and polyvinylidenfluoride (PVDF)) and two different structures (standard structure and bold structure with higher filament linking) were compared. During the implantation, the meshes were infected with Staphylococcus (S.) aureus. After 7 and 21 days, meshes were explanted, and the early and late tissue responses to infection were histologically evaluated. Results: Overall, the inflammatory tissue response was higher at 7 days when compared to 21 days. At 7 days, PP meshes of the standard structure (PP-S) showed the strongest inflammatory tissue response in comparison to all the other groups. At 21 days, no statistically significant difference between different meshes was detected. CD8+ cytotoxic T cells showed a significant difference at 21 days but not at 7 days. PP meshes of both structures showed a higher infiltration of CD8+ T cells than PVDF meshes. CD4+ T helper cells differed at 7 days but not at 21 days, and PVDF meshes in a bold structure showed the highest CD4+ T cell count. The number of CD68+ macrophages was also significantly higher in PP meshes in a standard structure when compared to PVDF meshes at 21 days. Conclusion: The inflammatory tissue response to S. aureus infection appears to be highest during the early period after mesh implantation. PP meshes showed a higher inflammatory response than PVDF meshes. The mesh material appears to be more important for the risk of infection than the variation in filament linking.
Cardiovascular Diseases: Therapeutic Potential of SGLT-2 Inhibitors
Authors: Frąk Weronika , Hajdys Joanna , Radzioch Ewa , Szlagor Magdalena , Młynarska Ewelina , Rysz Jacek , Franczyk Beata
Published: July 2023

Cardiovascular diseases (CVD) are a global health concern, affecting millions of patients worldwide and being the leading cause of global morbidity and mortality, thus creating a major public health concern. Sodium/glucose cotransporter 2 (SGLT2) inhibitors have emerged as a promising class of medications for managing CVD. Initially developed as antihyperglycemic agents for treating type 2 diabetes, these drugs have demonstrated significant cardiovascular benefits beyond glycemic control. In our paper, we discuss the role of empagliflozin, dapagliflozin, canagliflozin, ertugliflozin, and the relatively recently approved bexagliflozin, the class of SGLT-2 inhibitors, as potential therapeutic targets for cardiovascular diseases. All mentioned SGLT-2 inhibitors have demonstrated significant cardiovascular benefits and renal protection in clinical trials, in patients with or without type 2 diabetes. These novel therapeutic approaches aim to develop more effective treatments that improve patient outcomes and reduce the burden of these conditions. However, the major scientific achievements of recent years and the many new discoveries and mechanisms still require careful attention and additional studies.
Evolution of Cognitive Impairments in Treatment-Resistant Depression: Results from the Longitudinal French Centers of Expertise for Treatment-Resistant Depression (FACE-DR) Cohort
Authors: Vancappel Alexis , Dansou Yecodji , Godin Ophelia , Haffen Emmanuel , Yrondi Antoine , Stephan Florian , Richieri Raphaelle Marie , Molière Fanny , Holtzmann Jérôme , Horn Mathilde , Allauze Etienne , Genty Jean Baptiste , Bouvard Alex , Dorey Jean-Michel , Hennion Vincent , Camus Vincent , Fond Guillaume , Peran Barbara , Walter Michel , Anguill Loic , Scotto D’apolina Charlotte , Vilà Estelle , Fredembach Benjamin , Petrucci Jean , Rey Romain , Nguon Anne Sophie , Etain Bruno , Carminati Mathilde , Courtet Philippe , Vaiva Guillaume , Llorca Pierre Michel , Leboyer Marion , Aouizerate Bruno , Bennabi Djamila , El Hage Wissam
Published: July 2023

Previous studies set out profound cognitive impairments in subjects with treatment-resistant depression (TRD). However, little is known about the course of such alterations depending on levels of improvement in those patients followed longitudinally. The main objective of this study was to describe the course of cognitive impairments in responder versus non-responder TRD patients at one-year follow-up. The second aim was to evaluate the predictive aspect of cognitive impairments to treatment resistance in patients suffering from TRD. We included 131 patients from a longitudinal cohort (FACE-DR) of the French Network of Expert TRD Centers. They undertook comprehensive sociodemographic, clinical, global functioning, and neuropsychological testing (TMT, Baddeley task, verbal fluencies, WAIS-4 subtests, D2 and RLRI-16) at baseline (V0) and one-year follow-up (V1). Most patients (n = 83; 63.36%) did not respond (47 women, 49.47 ± 12.64 years old), while one-third of patients responded (n = 48, 30 women, 54.06 ± 12.03 years old). We compared the cognitive performances of participants to average theoretical performances in the general population. In addition, we compared the cognitive performances of patients between V1 and V0 and responder versus non-responder patients at V1. We observed cognitive impairments during the episode and after a therapeutic response. Overall, each of them tended to show an increase in their cognitive scores. Improvement was more prominent in responders at V1 compared to their non-responder counterparts. They experienced a more marked improvement in code, digit span, arithmetic, similarities, and D2 tasks. Patients suffering from TRD have significant cognitive impairments that persist but alleviate after therapeutic response. Cognitive remediation should be proposed after therapeutic response to improve efficiency and increase the daily functioning.