bluuebunny/crossref_metadata_2025_split huggingface dataset:
Resistive Switching Transparent SnO2 Thin Film Sensitive to Light and Humidity
Authors: Kalateh Asiyeh , Jalali Ali , Ashtiani Mohammad Javad Kamali , Masoudi Mohammad Mohammadi , Bastami Hajieh , Mohseni Majid 
Published: August 2023

Abstract
Designing and manufacturing memristor devices with simple and cheap methods is very promising for its development. Here, an Ag/SnO2 /FTO(F-SnO2) structure is used through the deposition of the SnO2 layer attained by its sol via the air-brush method on an FTO substrate. This structure was investigated in terms of the memristive characteristics. The Negative differential resistance(NDR) effect was also observed in environment humidity conditions. In this structure, we have valance change memory (VCM) and electrometalization change memory (ECM) mechanisms that cause the current peak in the NDR region by forming an OH− conductive filament(CF). In addition, the photoconductivity effect has been found under light illumination and this structure shows the positive photoconductance (PPC) effect by increasing the conductivity. This effect has the highest value at wavelengths close to the absorption wavelength of SnO2 (~ 340 nm). Also, the device was examined for up to 100 cycles and significant stability was observed. This behavior is a valuable advantage because the stability of memristors is critical for their use in neuromorphic computing. The coexistence of the NDR effect and resistive switching (RS) memory behavior is useful for achieving high-level simulations of biomimetic or neuromorphic computing. This combination can lead to the creation of artificial synapses that can mimic the behavior of biological synapses.
Effective Hybrid Search Technique Based Constraint Mixed-Integer Programming for Smart Home Residential Load Scheduling
Authors: Abdelhameed Esam , Abdelraheem Samah , Mohamed Yehia , Diab Ahmed 
Published: August 2023

Abstract
In this study, the problem of scheduling smart homes (SHs) residential loads is considered aiming at minimizing the electricity bills and enhancing the user comfort. The problem is addressed as a multi-objective constraint mixed-integer optimization problem (CP-MIP) to model the constrained load operation. As the CP-MIP optimization problem is non-convex, a novel hybrid search technique, that combines Relaxation and Rounding (RnR) approach and metaheuristic algorithms to enhance the accuracy and relevance of decision variables, is proposed. This search technique is implemented through two stages: relaxation stage in which a metaheuristic technique is applied to get the optimal rational solution of the problem. Whereas, the second stage is the rounding process which is applied via stochastic rounding approach to provide a good-enough feasible solution. The scheduling process has been done under time-of-use (ToU) dynamic electricity pricing scheme and two powering modes (i.e. powering from the main grid only or powering from grid-tied photovoltaic (PV) residential power system), in addition, four metaheuristics (i.e. Binary Particle Swarm Optimization (BPSO), Self-Organizing Hierarchical PSO (SOH-PSO), JAYA algorithm, and Comprehensive Learning JAYA algorithm (CL-JAYA)) have been utilized. The results reported in this study verify the effectiveness of the proposed technique.
The Causal Relationship between Gut Microbiota and Non-alcoholic Fatty Liver Disease: A Mendelian Randomization Study
Authors: Li Liwei , Cai Fuqing , Xiong Guang , Qin Jiamin , Geng Yan , Huang Jie-an 
Published: August 2023

Abstract
Aims
The association between the gut microbiota and non-alcoholic fatty liver disease (NAFLD) has been documented; however, the causal relationship between them remains unclear. The aim of this study was to explore the causal relationship between the gut microbiota and NAFLD using Mendelian randomization.
Methods
We conducted a Mendelian randomization study, using gut microbiota data (n = 18340) from MiBioGen consortium as the exposure and the NAFLD dataset from FinnGen R9 release data (n = 377,277) as the outcome. Inverse variance weighted was employed as the primary analysis method, and sensitivity analysis was performed. Additionally, a network graph resembling a phylogenetic tree was created to further reveal the evolutionary relationships among gut microbiota.
Results
Six bacterial features exhibited causal relationships with NAFLD: Actinomycetales (OR = 1.50, 95% CI: 1.01–2.21, p = 0.043), Actinomycetaceae (OR = 1.49, 95% CI: 1.01–2.20, p = 0.043), Actinomyces (OR = 1.36, 95% CI: 1.09–1.71, p = 0.006), Prevotella 7 (OR = 1.19, 95% CI: 1.01–1.39, p = 0.039) exhibited potential detrimental effects on NAFLD, whereas Anaerofilum (OR = 0.85, 95% CI: 0.72–0.99, p = 0.042) and Gordonibacter (OR = 0.84, 95% CI: 0.72–0.98, p = 0.024) exhibited potential protective effects. Furthermore, Actinomycetales, Actinomycetaceae, and Actinomyces are located on the same evolutionary branch.
Conclusions
Our study revealed a causal relationship between six gut bacteria and NAFLD. These findings shed light on the role of specific gut bacteria in the pathogenesis of NAFLD and offer valuable insights into future therapeutic interventions and preventive strategies.
The morphological and functional rationale for the potential compensatory role of disseminated postsplenectomy splenosis in an experiment
Authors: Klyuev Sergey , Gorodkov Sergey 
Published: August 2023

Abstract
Aim
to investigate disseminated post-splenectomy splenosis (DPSS) by creating an experimental model and analysing the timing, frequency, morphological features, and functional capabilities of splenosis nodules.
Materials and methods
The experiment involved surgical modelling of DPSS in white laboratory rats and a sham operation group. The rats were euthanized at different time points after the surgery, and the DPSS foci were examined histologically. Functional assessments were conducted by evaluating phagocytic parameters and morphological examination of erythrocytes.
Results
DPSS foci were observed in the majority of rats (79%) at various time points after the surgery. The foci appeared as dark cherry-coloured round formations of different sizes and were commonly found on the greater omentum, stomach serous membrane, colon serous membrane, and root of the mesentery. Histological examination revealed a cell composition similar to the spleen, including white pulp components and a high number of plasma cells. However, the typical histological architecture of the spleen was not preserved in the DPSS nodules. The phagocytic index and phagocytic number were within normal range in rats with DPSS after 30 days, indicating normal phagocytic activity. However, after splenectomy, these parameters were lower compared to the DPSS group. The opsonic index was significantly below normal levels in the early stages after splenectomy but reached normal values later on. Morphological examination of erythrocytes showed poikilocytic deviations and increased Howell-Jolly bodies, indicating inadequate utilization of degenerative forms of erythrocytes by DPSS nodules.
Conclusion
The DPSS showed partial functional activity in experiment, including phagocytic capabilities, although the histological architecture of the spleen was not fully preserved. The study provides valuable insights into the characteristics of DPSS nodules and their potential functional role.
An acoustic feedback canceller using probe noise and informative data
Authors: Eren Yusuf , Güvenç Buket Çolak , Mengüç Engin Cemal 
Published: August 2023

Abstract
One of the important issues encountered in acoustic feedback canceller (AFC) systems is the bias occurring in the estimation of the acoustic feedback (AF) path. In the literature, a common solution is to inject the probe noise into the loudspeaker to reduce the correlation between the input signal and the loudspeaker signal, that is, to remove the bias occurring in the estimation of the AF path. This approach significantly improves the performance of the AFC systems. However, when considering high filter orders and large-scale input signals, such systems designed by probe noise injection suffer from the data processing cost, and thus their real-time implementations on a chip generally become challenging. To this end, in this paper, we propose an AFC system using jointly probe noise and informative data, named the probe noise-online censoring-least mean square (PN-OC-LMS) based AFC. Thanks to both the OC mechanism and the probe noise injection approach, the proposed PN-OC-LMS based AFC system significantly not only reduces the data processing cost but also effectively removes the bias effect in the AF path. The mentioned effectiveness of the proposed AFC system is supported by two comprehensive different experiments on a real-world AF path measured from a behind-the-ear hearing aid. As a result, in the proposed AFC system, the use of both informative data and the injection of probe noise will enable the design of a long-term working wearable hearing aid device that provide slow data processing cost and correctly estimates the AF path.
Bioinformatic analysis reveals CCNA2 as Lung Adenocarcinoma hub gene and is associated with cell proliferation and epithelial- mesenchymal transition
Authors: Tan Juofang , Sun Siying , Meng Wangyang , Han Yichao , Guo Wei , Wu Xuefeng , Li Hecheng 
Published: August 2023

Abstract

Lung adenocarcinoma (LUAD) is one of the malignant tumors worldwide. The purpose of this study is to identify the hub genes related to LUAD using bioinformatics analysis. Three gene expression datasets (GSE27262, GSE74706, GSE75037) were obtained from GEO database. Identification of DEGs was performed using GEO2R and constructed protein-protein interaction network using STRING and cytoscape. GO, KEGG and GSEA analysis were carried out through R package “clusterprofiler”. GEPIA was used to verify the survival of hub genes, UALCAN database and HPA database were used to determine protein expression, complemented by IHC staining results. Lastly, CCK-8 and colony formation assays were used to verify PC9 cell growth ability and we used western blot, Transwell and scratch wound assays for validation of PC9 cells migration and EMT markers. We identified 107 up-regulated genes and 344 down-regulated genes. Thirty hub genes were identified and the 12 hub genes with a rank of degrees > 30 are as follow: CCNA2, AURKA, HMMR, EZH2, TTK, TPX2, CCNB1, ANLN, ECT2, CEP55, MAD2L1 and PBK. CCNA2 as one of the genes having the highest node degree of 35 was chosen for subsequent analysis. Our findings indicated that high expression of CCNA2 had the highest enrichment effects on cell cycle and was associated with poor prognosis. CCK-8 and colony formation analysis further verified that CCNA2 contributed to the progression of LUAD and the protein expression was significantly elevated in tumor tissues compared to the normal lung tissues. In addition, high expression of CCNA2 is related to the EMT process and may play a role in EMT-induced metastasis in LUAD. Briefly, CCNA2 was identified as one of the hub genes and can promote lung cancer cell growth, migration and invasion via epithelial-mesenchymal transition. Moreover, could avail as a biomarker or therapeutic target to judge the prognosis of LUAD.
EI-StyleGAN: A High Quality Face Cartoon Style Transfer Model
Authors: Li Rui , Fu Fenli 
Published: August 2023

Abstract

Cartoonization of face images is a new art forms applicable to various scenes, but there are problems in the research of incomplete extraction of image details after style transfer, simple superposition between domains, and poor generation quality. Since StyleGAN has better results in the generation of artistic images, on this basis, this paper proposes a new EI-StyleGAN to construct a network model applicable to face style migration, in which the inner and outer style restriction modules are introduced to obtain different detailed features in the images of the two domains, respectively. Meanwhile, the latent space coding is obtained by image inversion before inputting into the generated model, which can perform the transformation between images between the source and target domains. The whole process adopts an incremental generation strategy to smoothly transform the generation space of the model to the target domain, and gradually generates high-quality face cartoon style transfer result image. Experiments demonstrate the effectiveness of the method in improving the image quality after style transfer and the smooth conversion between different styles.
Why Do Some Adult Who are Smoking Perceive E-cigarettes to be More Harmful than Combustible Cigarettes?
Authors: McKeganey Neil , Notley Sophie , Coyle Joanne , Barnard Gabriel 
Published: August 2023

Abstract
Whilst e-cigarettes have been characterised by respected public health bodies as being substantially less harmful than combustible tobacco products, nevertheless research has shown that a significant minority of adults, including those who are smoking, perceive e-cigarettes to be as harmful or more harmful than combustible cigarettes. In this paper we draw upon qualitative data from interviews with U.K. adults who are smoking to look at the reasons why e-cigarettes may be viewed as more harmful than combustible cigarettes. The belief that e-cigarettes may be more harmful than combustible cigarettes was based on a complex array of knowledge, belief, reasons, fears, predictions, reactions, and judgements covering such topics as the technological i.e. non-natural nature of e-cigarettes, uncertainties as to the content of e-liquids, perceptions that these devices expose the user to greater harm resulting from their being used with greater frequency than combustible tobacco products, fear around long-term harm of e-cigarettes, scare stories in the media and concerns around addiction. There is an important need for clear communication from responsible public health bodies and the media conveying the important information to those adults who are continuing to smoke that e-cigarettes are substantially less harmful than combustible tobacco products, and that those adults who are unable or unwilling to quit smoking using validated means of smoking cessation should consider switching to e-cigarettes or other non-combustible tobacco products as a way of reducing the harms they are being exposed to as a result of continuing to smoke.
Approximate Moment Functions for Logistic Stochastic Differential Equations
Authors: Çetin Coşkun , Ðordević Jasmina 
Published: August 2023

Abstract

In this paper, we introduce an iterative procedure for approximate moment functions of logistic stochastic differential equations. We first reduce the solutions of the moment functions of such an equation to an infinite system of linear ordinary differential equations. Then, we determine certain upper and lower bounds on the moment functions, and utilize these bounds to solve the corresponding systems approximately via some truncations, iterations and a local improvement step. By focusing on the stochastic Verhulst systems, we compare these moment approximations with numerical solutions via simulation-based methods that include discretizations of the pathwise solutions as well as convergent numerical procedures like partially implicit Euler methods. In particular, we discuss performance of these approximations for certain parameter values.
Green access to flavonols by one-pot serial aldol-condensation/Algar-Flynn- Oyamada reaction catalyzed by new bio-based catalyst of alkaline-amylopectin
Authors: Tamaddon Fatemeh , Rashidi Hossein 
Published: August 2023

Abstract
Herein, alkaline-amylopectin (AAp) was prepared under chemo-mechanically dry conditions, characterized by base capacity, FT-IR, FESEM, TEM, and TGA analyses, and held as a new bio-organic base catalyst in the one-pot synthesis of flavonols. With a base capacity of 7.3 mmolHO-/g, AAp catalyzed initial aldol condensation and co-operated with the aqueous hydrogen peroxide in the further Algar-Flynn-Oyamada reaction to give high yield of flavonol anti-oxidants. So, either the first aldol-condensation or the latter oxidative cyclization/hydroxylation of the in situ formed 2´-hydroxy-chalcons proceeded successfully in a pot and flavonol products formed with no aurone side product. The structure of the supra-molecular base catalyst AAp was found to be well preserved after five times reusing. This protocol rewards the simple available reactants, no aurone side product, short reaction time, high yield, and catalyst reusability.
FED-AT-VIDEO NETS - A Federated Capsule – Self Gated Learning Architecture for the Multi-View Video Summarization Technique.
Authors: KANDASWAMY VIJAY ANAND , BALACHANDER BHUVANESWARI 
Published: August 2023

Abstract

Video analytics using the huge amount of data from the surveillance networks has become a core function for multiple applications such as object detection, human activity recognition, health care diagnosis and so on. Due to its massive nature, achieving efficient video summarization has become a vital challenge for constructing video analytics architecture. Moreover, these video contains private information, and security against different intruders has also added fuel to the existing challenges. In recent years, a number of architectures have been proposed to achieve better and secured multi-view summarization (MVS) techniques that can aid in better video analytics. Unfortunately, existing architecture needs brighter light of research to eradicate the aforementioned challenges. In this article, federated deep gated attention architecture (FDGAA) is proposed for attaining the secured MVS by organizing the computing and networking resources of cloud and edge cameras collectively. The proposed architecture is modeled as a three-tier framework which is precisely given as 1) Video collection unit (VDU) that collects the videos from the different views of the camera installed. 2) Distributed Training network(DTN) which consists of federated learning self-attention saliency Gated recurrent units(SAS-GRU) in which the training is collaboratively shared among the edges without sacrificing the privacy of video information. 3) Finally the extracted deep features are summarized in the cloud for further processing. Utilizing a variety of datasets and NVIDIA Nano Boards as edge nodes, substantial research is conducted to develop the Google Federated Tensorflow Libraries-based federated learning architecture. Performance has been compared with other MVS systems that are currently based on deep learning to demonstrate the superiority of the proposed framework. In comparison to other state-of-the-art MVS approaches, the experimental evaluation shows that the suggested model performs better.
Multi-feature output deep network ensemble learning for face recognition and verification
Authors: Li Chaorong 
Published: August 2023

Abstract
In facial recognition systems, the sample size of face data is often limited, making it difficult to improve recognition performance through transfer learning using pre-trained deep neural network models (DCNNs). Furthermore, in complex environments, the recognition performance of a single DCNN is greatly weakened. To address these issues, this paper proposes a multi-feature DCNN ensemble learning method based on machine learning for facial recognition and verification. First, the characterization ability of face details is enhanced by expanding the output feature dimension of the DCNN model. Then, machine learning methods with few or no parameters are used for secondary learning on small sample databases to improve recognition/verification performance.In this work, we utilized several mainstream network models such as ResNet50 and SENet to expand and integrate features. The experimental results show that our proposed method can improve the recognition/validation accuracy of existing DCNN models by up to 10%. Moreover, this method does not require training the network, has relatively low computational costs, and has a wide range of practical applications.
An Efficient Multi-Step Framework for Malware Packing Identification
Authors: Kim Jong-Wouk , Moon Yang-Sae , Choi Mi-Jung 
Published: August 2023

Abstract
Packing is a disruptive factor in the field of cybersecurity, as it obstructs the analysis of packed malware and prolongs the lifespan of malware samples. Malware equipped with anti-analysis technologies evades antivirus software and analysis tools. Therefore, detecting and analyzing packed malware is a technically challenging and resource-intensive task. The situation becomes even worse when malware classifiers are trained on the characteristics of packers instead of malware itself. Training models with numerous inadequate data inadvertently renders them impractical for classifying actual malware. Therefore, researchers should consider packetizing to construct practical malware classifier models. In this paper, we aim to propose an opportunity to reconcile the problem of packetizing with identifying it. We present a dataset consisting of over 200K actual malware samples. We propose a multi-step framework for classifying and identifying packed samples. The framework includes pseudo-optimal feature selection, machine learning-based classifiers, and packer identification steps. The framework preselects the top 20 important features using the CART algorithm and permutation importance in the first step. In the second step, each model trains on the preselected 20 features to classify the packed files with the highest performance. The XGBoost algorithm, trained on the features preselected by XGBoost with the permutation importance, demonstrated the best performance among all experimental scenarios, achieving an accuracy of 99.67%, an F1-Score of 99.46%, and an area under the curve of 99.98%. The proposed framework identifies the packer only for samples classified as Well-Known Packed in the third step.
Analysis of FctB3 crystal structure and insight into its structural stabilization and pilin linkage mechanisms
Authors: Takebe Katsuki , Suzuki Mamoru , Sangawa Takeshi , Kreikemeyer Bernd , Yamaguchi Masaya , Uzawa Narikazu , Sumitomo Tomoko , Kawabata Shigetada , Nakata Masanobu 
Published: August 2023

Abstract
Streptococcus pyogenes harboring an FCT type 3 genomic region display pili composed of three types of pilins. In this study, the structure of the base pilin FctB from a serotype M3 strain (FctB3) was determined at 2.8 Å resolution. In accordance with the previously reported structure of FctB from a serotype T9 strain (FctB9), FctB3 was found to consist of an immunoglobulin-like domain and proline-rich tail region. Data obtained from structure comparison reveled main differences in the omega loop structure and the proline-rich tail direction. In the omega loop structure, a differential hydrogen bond network was observed, while the lysine residue responsible for linkage to growing pili was located at the same position in both structures, which indicated that switching of the hydrogen bond network in the omega loop without changing the lysine position is advantageous for linkage to the backbone pilin FctA. The difference in direction of the proline-rich tail is potentially caused by a single residue located at the root of the proline-rich tail. Also, the FctB3 structure was found to be stabilized by intramolecular large hydrophobic interactions instead of an isopeptide bond. Comparisons of the FctB3 and FctA structures indicated that the FctA structure is more favorable for linkage to FctA. Additionally, the heterodimer formation of FctB with Cpa or FctA was shown to be mediated by the putative chaperone SipA. Together, these findings provide an alternative FctB structure as well as insight into the interactions between pilin proteins.