bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical outcomes of esophageal granular cell tumors with different endoscopic resection methods
Authors: Ryu Dae Gon , Choi Cheol Woong , Kim Su Jin , Hwang Chung Su , Kang Dae Hwan , Kim Hyung Wook , Park Su Bum , Son Bong Soo 
Published: July 2023

AbstractEsophageal granular cell tumors (GCTs), the second most common subepithelial tumors (SETs) of the esophagus, are potentially malignant with no definite management guidelines available. We retrospectively enrolled 35 patients with endoscopically resected esophageal GCTs between December 2008 and October 2021 and evaluated the clinical outcomes from the various methods performed. Several modified endoscopic mucosal resections (EMRs) were performed for treating esophageal GCTs. Clinical and endoscopic outcomes were evaluated. Mean age of patients was 55.8 ± 8.2, with majority being men (57.1%). Mean tumor size was 7.2 ± 2.6 mm, most (80.0%) were asymptomatic and present in the distal third of the esophagus (77.1%). Endoscopic characteristics predominantly included broad-based (85.7%) and whitish-to-yellowish color changes (97.1%). Endoscopic ultrasound (EUS) of 82.9% of the tumors revealed homogeneous hypoechoic SETs originating from the submucosa. The five endoscopic treatment methods used were: ligation-assisted (77.1%), conventional (8.7%), cap-assisted (5.7%), and underwater (5.7%) EMRs and ESD (2.9%). Mean procedure time was 6.6 ± 2.1 min, and no procedure-associated complications were noted. The en-bloc and complete histologic resection rates were 100% and 94.3%, respectively. No recurrences were noted during follow-up, and no significant differences in the clinical outcomes of the different methods of endoscopic resection were found. Based on tumor characteristics and therapeutic outcomes, modified EMR methods can be effective and safe. However, there were no significant differences in the clinical outcomes of the different methods of endoscopic resection.
Characteristic analysis of epileptic brain network based on attention mechanism
Authors: Yu Hong-Shi , Meng Xiang-Fu 
Published: July 2023

AbstractConstructing an efficient and accurate epilepsy detection system is an urgent research task. In this paper, we developed an EEG-based multi-frequency multilayer brain network (MMBN) and an attentional mechanism based convolutional neural network (AM-CNN) model to study epilepsy detection. Specifically, based on the multi-frequency characteristics of the brain, we first use wavelet packet decomposition and reconstruction methods to divide the original EEG signals into eight frequency bands, and then construct MMBN through correlation analysis between brain regions, where each layer corresponds to a specific frequency band. The time, frequency and channel related information of EEG signals are mapped into the multilayer network topology. On this basis, a multi-branch AM-CNN model is designed, which completely matches the multilayer structure of the proposed brain network. The experimental results on public CHB-MIT datasets show that eight frequency bands divided in this work are all helpful for epilepsy detection, and the fusion of multi-frequency information can effectively decode the epileptic brain state, achieving accurate detection of epilepsy with an average accuracy of 99.75%, sensitivity of 99.43%, and specificity of 99.83%. All of these provide reliable technical solutions for EEG-based neurological disease detection, especially for epilepsy detection.
Isolation and genotypic characterization of extended-spectrum beta-lactamase-producing Escherichia coli O157:H7 and Aeromonas hydrophila from selected freshwater sources in Southwest Nigeria
Authors: Bisi-Johnson Mary A. , Adedeji Atilade A. , Sulaiman Adebayo A. , Adefisoye Martins A. , Okoh Anthony I. 
Published: July 2023

AbstractThe proliferation of antibiotic-resistant bacteria and antimicrobial resistance is a pressing public health challenge because of their possible transfer to humans via contact with polluted water sources. In this study, three freshwater resources were assessed for important physicochemical characteristics as well as heterotrophic and coliform bacteria and as potential reservoirs for extended-spectrum beta-lactamase (ESBL) strains. The physicochemical characteristics ranged from 7.0 to 8.3; 25 to 30 °C, 0.4 to 93 mg/L, 0.53 to 8.80 mg/L and 53 to 240 mg/L for pH, temperature, dissolved oxygen (DO), biological oxygen demand (BOD5) and total dissolved solids, respectively. The physicochemical characteristics mostly align with guidelines except for the DO and BOD5 in some instances. Seventy-six (76) Aeromonas hydrophila and 65 Escherichia coli O157: H7 isolates were identified by preliminary biochemical analysis and PCR from the three sites. Among these, A. hydrophila displayed higher frequencies of antimicrobial resistance, with all 76 (100%) isolates completely resistant to cefuroxime and cefotaxime and with MARI ≥ 0.61. The test isolates showed more than 80% resistance against five of the ten test antimicrobials, with resistance against cefixime, a cephalosporin antibiotic being the highest at 95% (134/141). The frequency of the detection of the resistance genes in the A. hydrophila isolates generally ranged between 0% (blaSHV) and 26.3% (blaCTX-M), while the frequency of detection among the E. coli O157:H7 isolates ranged between 4.6% (blaCTX-M) and 58.4% (blaTEM). Our findings indicate that the distribution of antibiotic-resistant bacteria with diverse ESBL-producing capabilities and virulence genes in freshwater sources potentially threatens public health and the environment.
Mitochondrial DNA is a target of HBV integration
Authors: Giosa Domenico , Lombardo Daniele , Musolino Cristina , Chines Valeria , Raffa Giuseppina , Casuscelli di Tocco Francesca , D’Aliberti Deborah , Caminiti Giuseppe , Saitta Carlo , Alibrandi Angela , Aiese Cigliano Riccardo , Romeo Orazio , Navarra Giuseppe , Raimondo Giovanni , Pollicino Teresa 
Published: July 2023

AbstractHepatitis B virus (HBV) may integrate into the genome of infected cells and contribute to hepatocarcinogenesis. However, the role of HBV integration in hepatocellular carcinoma (HCC) development remains unclear. In this study, we apply a high-throughput HBV integration sequencing approach that allows sensitive identification of HBV integration sites and enumeration of integration clones. We identify 3339 HBV integration sites in paired tumour and non-tumour tissue samples from 7 patients with HCC. We detect 2107 clonally expanded integrations (1817 in tumour and 290 in non-tumour tissues), and a significant enrichment of clonal HBV integrations in mitochondrial DNA (mtDNA) preferentially occurring in the oxidative phosphorylation genes (OXPHOS) and D-loop region. We also find that HBV RNA sequences are imported into the mitochondria of hepatoma cells with the involvement of polynucleotide phosphorylase (PNPASE), and that HBV RNA might have a role in the process of HBV integration into mtDNA. Our results suggest a potential mechanism by which HBV integration may contribute to HCC development.
Human subsistence and signatures of selection on chemosensory genes
Authors: Veilleux Carrie C. , Garrett Eva C. , Pajic Petar , Saitou Marie , Ochieng Joseph , Dagsaan Lilia D. , Dominy Nathaniel J. , Perry George H. , Gokcumen Omer , Melin Amanda D. 
Published: July 2023

AbstractChemosensation (olfaction, taste) is essential for detecting and assessing foods, such that dietary shifts elicit evolutionary changes in vertebrate chemosensory genes. The transition from hunting and gathering to agriculture dramatically altered how humans acquire food. Recent genetic and linguistic studies suggest agriculture may have precipitated olfactory degeneration. Here, we explore the effects of subsistence behaviors on olfactory (OR) and taste (TASR) receptor genes among rainforest foragers and neighboring agriculturalists in Africa and Southeast Asia. We analyze 378 functional OR and 26 functional TASR genes in 133 individuals across populations in Uganda (Twa, Sua, BaKiga) and the Philippines (Agta, Mamanwa, Manobo) with differing subsistence histories. We find no evidence of relaxed selection on chemosensory genes in agricultural populations. However, we identify subsistence-related signatures of local adaptation on chemosensory genes within each geographic region. Our results highlight the importance of culture, subsistence economy, and drift in human chemosensory perception.
Rarity of molt evidence in early pennaraptoran dinosaurs suggests annual molt evolved later among Neornithes
Authors: Kiat Yosef , O’Connor Jingmai Kathleen 
Published: July 2023

AbstractFeathers are a primitive trait among pennaraptoran dinosaurs, which today are represented by crown birds (Neornithes), the only clade of dinosaurs to survive the end Cretaceous mass extinction. Feathers are central to many important functions and therefore, maintaining plumage function is of great importance for survival. Thus, molt – by which new feathers are formed to replace old ones, is an essential process. Our limited knowledge regarding molt in early pennaraptoran evolution is based largely on a single Microraptor specimen. A survey of 92 feathered non-avian dinosaur and stem bird fossils did not find additional molting evidence. Due to its longer duration, in ornithological collections evidence of molt is found more frequently in extant bird species with sequential molts compared to those with more rapid simultaneous molts. The low frequency of molt occurrence among fossil specimens resembles collections of bird species with simultaneous molts. The dearth of molt evidence in the forelimbs of pennaraptoran specimens may have interesting implications regarding molt strategy during early avian evolution, and suggests that the yearly molting cycle may have evolved later, among crown birds.
Dyke swarms record the plume stage evolution of the Atla Regio superplume on Venus
Authors: El Bilali Hafida , Ernst Richard E. , Buchan Kenneth L. , Head James W. 
Published: July 2023

AbstractAtla Regio, Venus, is interpreted as a young major mantle plume centre, and we address whether it is at plume head or plume tail stage. Our approach uses graben-fissure lineaments, interpreted as the surface expression of dykes. Mapping > 40,000 such lineaments reveals giant radiating dyke swarms associated with major volcanic centres of Maat (>1500 km dyke swarm radius), Ozza (>2000 km), Ongwuti (>1100 km) and Unnamed montes (>1100 km), indicating that each is due to plume head magmatism rather than plume tail magmatism (maximum swarm length ~ 100 km). The size of an underlying flattened plume head is estimated by the radius where the swarm transitions from a radiating to linear pattern. All four centres and their plume heads group within the 1200 km radius of the Ozza Mons plume head, consistent with a single event. Atla Regio is at the plume head stage with coeval triple-junction rifting, which on Earth would typically precede attempted continental breakup.
Car‐following strategy of intelligent connected vehicle using extended disturbance observer adjusted by reinforcement learning
Authors: Yan Ruidong , Li Penghui , Gao Hongbo , Huang Jin , Wang Chengbo 
Published: July 2023

AbstractDisturbance observer‐based control method has achieved good results in the car‐following scenario of intelligent and connected vehicle (ICV). However, the gain of conventional extended disturbance observer (EDO)‐based control method is usually set manually rather than adjusted adaptively according to real time traffic conditions, thus declining the car‐following performance. To solve this problem, a car‐following strategy of ICV using EDO adjusted by reinforcement learning is proposed. Different from the conventional method, the gain of proposed strategy can be adjusted by reinforcement learning to improve its estimation accuracy. Since the “equivalent disturbance” can be compensated by EDO to a great extent, the disturbance rejection ability of the car‐following method will be improved significantly. Both Lyapunov approach and numerical simulations are carried out to verify the effectiveness of the proposed method.
Adaptive state of charge estimation for lithium‐ion batteries using feedback‐based extended Kalman filter
Authors: Monirul Islam Md , Qiu Li , Ruby Rukhsana , Yu Junjie 
Published: July 2023

AbstractThe battery management system (BMS) is a crucial component of electric vehicles (EVs) owing to its sustainable operation. To ensure optimal performance of the BMS, state of charge (SOC) of the equipped battery is required to be effectively and accurately estimated. In this paper, the authors consider high‐order equivalent circuit model (ECM) to capture the dynamic characteristics of lithium‐ion batteries, which are connected in series with internal resistance by 2‐RC networks. The parameters of the RC network are determined by mathematically solving the working conditions of the two states. Moreover, the parameters of the battery can be derived by hybrid pulse power characterization (HPPC) tests. Then, based on the open‐circuit voltage, the proposed feedback‐based extended Kalman filtering (FEKF) algorithm is established. The parameters from the simulation have shown that the highest error is 0.0306 V, the optimal knowledge of which can improve the SOC estimation approach remarkably and can provide a reference value. Afterwards, the non‐linear predicting and corrective techniques are applied to the experiment in the extended calculation process. The original error is reduced by the FEKF algorithm, where the maximum and average errors are 0.0298 and 0.0240 V, respectively. Consequently, the established high‐order ECM utilizing the FEKF algorithm may provide SOC estimation with an error of 1.5% or less, resulting in superb performance from the lithium‐ion battery pack.
CAGAN: Classifier‐augmented generative adversarial networks for weakly‐supervised COVID‐19 lung lesion localisation
Authors: Li Xiaojie , Fei Xin , Yan Zhe , Ren Hongping , Shi Canghong , Zhang Xian , Mumtaz Imran , Luo Yong , Wu Xi 
Published: July 2023

AbstractThe Coronavirus Disease 2019 (COVID‐19) epidemic has constituted a Public Health Emergency of International Concern. Chest computed tomography (CT) can help early reveal abnormalities indicative of lung disease. Thus, accurate and automatic localisation of lung lesions is particularly important to assist physicians in rapid diagnosis of COVID‐19 patients. The authors propose a classifier‐augmented generative adversarial network framework for weakly supervised COVID‐19 lung lesion localisation. It consists of an abnormality map generator, discriminator and classifier. The generator aims to produce the abnormality feature map M to locate lesion regions and then constructs images of the pseudo‐healthy subjects by adding M to the input patient images. Besides constraining the generated images of healthy subjects with real distribution by the discriminator, a pre‐trained classifier is introduced to enhance the generated images of healthy subjects to possess similar feature representations with real healthy people in terms of high‐level semantic features. Moreover, an attention gate is employed in the generator to reduce the noise effect in the irrelevant regions of M. Experimental results on the COVID‐19 CT dataset show that the method is effective in capturing more lesion areas and generating less noise in unrelated areas, and it has significant advantages in terms of quantitative and qualitative results over existing methods.
Modelling and analysis of electromagnetic vibration in long sheet secondary tubular linear induction motors
Authors: Zhang Yichao , Xu Jin , Li Mingke , Yu Anbin , Wu Dingying 
Published: July 2023

AbstractThis paper aims to clarify the behaviour and mechanism of electromagnetic vibration in long sheet secondary tubular linear induction motors (LSS‐TLIMs). Firstly, the spatial and temporal characteristics of electromagnetic force acting in the stator are analysed. Secondly, based on the wave propagation method, an analytical model is established to calculate the vibration response of the stator, which is simplified as a finite cylindrical shell. The accuracy of the proposed model, as well as the rationality of the simplification, are verified by 3D FEM simulation. It is indicated that the electromagnetic vibration response of LSS‐TLIMs mainly depends on the “axial breathing mode” (ABM) and corresponding “modal participation factor”. Moreover, the influences of the spatial distribution of electromagnetic force and the structural dimensions on the vibration are investigated. Finally, the “static vibration test” is performed to validate the above analysis. It is concluded that, compared with a rotary motor, the low‐frequency vibration of LSS‐TLIMs can be easily controlled since the natural frequency of ABMs tends to be much higher than that of the circumferential mode.
Three‐stream RGB‐D salient object detection network based on cross‐level and cross‐modal dual‐attention fusion
Authors: Meng Lingbing , Yuan Mengya , Shi Xuehan , Liu Qingqing , Cheng Fei , Li Lingli 
Published: July 2023

AbstractThe effective integration of RGB and depth map features to improve the performance of RGB‐D salient object detection (SOD) has garnered significant research interest. The existing dual‐stream models can be used for high‐level feature fusion or unidirectionally transferring depth features to RGB features; however, they are unable to fully exploit the differences in modality. Furthermore, owing to the influence of image background information, the generated salient object is affected by background swallow. Herein, a three‐stream RGB‐D SOD method based on cross‐layer and cross‐modal dual‐attention (CMDA) fusion is proposed. In the encoding stage, the CMDA fusion module is used to fuse RGB and depth features layer by layer. Through this module, merged interactive features may be used to extract the richer features of salient objects, realize the commonality and complementarity of fusion features, and achieve effective cross‐modal fusion. In addition, for the decoding stage, a cross‐level feature fusion module that introduces global context features into the up‐sampling process, reduces the impact of salient objects being swallowed by the background, and helps to accurately detect salient areas is proposed. Three different branch features are used for simultaneous end‐to‐end training. The experimental results demonstrate that the proposed method outperforms other methods in terms of multiple evaluation metrics on four datasets. Furthermore, the authors visualize the precision–recall curve, F‐measure curve, and saliency map, which indicate that the detection effect of the proposed method is superior to those of other methods. During the testing stage, our model ran at 14 frames per second (FPS).
Techno‐economic and sensitivity analysis of a hybrid concentrated photovoltaic/thermal system and an organic Rankine cycle to supply energy to sports stadiums
Authors: Zhang Jing , Su Zhanguo , Meng Junyan , Yao Yuzhong , Alayi Reza 
Published: July 2023

AbstractOne of the main disadvantages of optical concentrators is that the temperature of the panel increases too much due to the radiation being concentrated on it. To reduce the temperature of solar panels, cooling technology is used utilizing an operating fluid (usually water). After cooling the system, the temperature of the operating fluid rises and its heat can be used in the cold seasons for heating purposes and in the hot seasons by the Organic Rankine Cycle (ORC) technology to generate electricity, and in this way, the overall efficiency of the system can be significantly increased. In the proposed system, first, a part of the concentrated solar radiation in the photovoltaic (PV) panel is converted into electrical energy, and the rest of the energy is in the form of heat, a part of which is emitted to the environment by convection and radiation heat transfer from the system itself, and the rest of the heat is emitted by the operating fluid turns the turbine and generates electricity. The simulation results of this system show that for the investment cost of the Rankine cycle in the amount of 1500–3100$/kW, the investment return time is 3.05–5.34 years.
A novel sparse recovery‐based space‐time adaptive processing algorithm based on gridless sparse Bayesian learning for non‐sidelooking airborne radar
Authors: Cui Weichen , Wang Tong , Wang Degen , Zhang Xinying 
Published: July 2023

AbstractNon‐sidelooking airborne radar encounters significant non‐stationary and heterogeneous clutter environments, resulting in a severe shortage of samples. Sparse recovery‐based space‐time adaptive processing (SR‐STAP) methods can achieve good clutter suppression performance with limited samples. Nonetheless, grid‐based SR‐STAP algorithms encounter off‐grid effects in non‐sidelooking arrays, which can severely degrade the clutter suppression performance. In this study, the authors propose a novel gridless SR‐STAP method in the continuous spatial‐temporal domain to address the issue of off‐grid effects. Inspired by the fact that sparse Bayesian learning (SBL) framework implicitly performs a structured covariance matrix estimation, the authors reparameterise its cost function to directly estimate the block‐Toeplitz structured matrix from the measurements in a gridless manner. Since the proposed cost function is non‐convex, we utilise a majorisation‐minimisation‐based iterative procedure to estimate the clutter covariance matrix. Finally, using the standard concept of semidefinite programming, the authors derive a convex gridless implementation of the SBL cost function for uniformly sampled radar systems. Extensive simulation experiments demonstrate the exceptional clutter suppression and target detection performance of the proposed algorithm.