bluuebunny/crossref_metadata_2025 huggingface dataset:
Properties of surface electronic states in layered organic conductors in out-of-plane magnetic field
Authors: Krstovska Danica , Skeparovski Aleksandar , Gjorgjevski Milan
Published: August 2022

In this paper, we have considered the properties of surface electronic states in quasi-two-dimensional organic conductors for an out-of-plane orientation of the magnetic field. The energies of these states have be calculated which allow the resonance magnetic fields and resonance angles corresponding to the positions of the peaks in oscillation spectra of surface resistance to be determined. We find that the energies of the magnetic-field induced surface states are decreasing significantly with increasing tilt angle from the surface. This is related to the fact that the surface states are realized due to electron transitions between different in size elliptical closed orbits obtained as cross-section of the Fermi surface with the plane [Formula: see text], [Formula: see text] const. In comparison to the case of in-plane magnetic field, where only the small closed orbits on the sides of the Fermi surface are involved in formation of the surface states, for out-of-plane magnetic field there are additionally present other, larger orbits that are spanning across the Fermi surface. We also find that the coordinate of the center of electron revolution is increasing significantly with increasing tilt angle but the maximum distance from the surface for the electrons involved in the surface states shows a steady increase indicating that the skipping trajectories are well confined within skin layer of the conductor. This indicates that the surface states can be observed for almost each field direction from the surface including those with higher quantum number. These studies allow to determine more accurately certain Fermi surface parameters such as the local radius of curvature in the plane perpendicular to the magnetic field as well as the Fermi velocity at each point on the elliptical cross-sections. We are highly convinced that our results will motivate new experimental investigations of surface phenomena in order to exploit the properties of surface electronic states for various scientific applications.
YOLO-F: YOLO for Flame Detection
Authors: Xu Kun , Xu Yuan , Xing Yuanxin , Liu Zhanwen
Published: August 2022

Flame detection is of great significance in a fire prevention system. YOLOv4 has poor real-time performance on flame detection caused by the complex structure and high parameter size. To address this problem, a novel flame detection framework, YOLO for flame (YOLO-F), is proposed in this paper. The backbone of YOLOv4 is simplified from the original 53 convolutional layers to 34 convolutional layers to reduce the number of parameters by simplifying the structure of the CSPBlock. Based on the FPN, an effective and light-weight feature pyramid architecture, namely FPNs-SE, is then proposed and the neck part of YOLOv4 is replaced by FPNs-SE to enhance the feature extraction ability of different scales. In addition, the CIoU loss in the YOLOv4 ignores the similarity measure of the area between the predicted bounding box and the ground-truth bounding box. An effective loss named ACIoU is proposed in this paper in order to handle the above issue and further improve the detection accuracy. The proposed methods are tested on FLAME dataset and network crawled dataset, respectively. The mAP, recall, and precision of YOLO-F are higher by 2.01%, 4.0%, 2.0% on average than those of YOLOv4. With input size of [Formula: see text] and on a single GTX 1660, the operating speed of our method can reach 24.53[Formula: see text]fps, which is improved by 38.04% compared with YOLOv4. The experimental results show that our method is more robust to the small flame and flame-like objects and can achieve the best balance of detection speed and accuracy. The code is made available at https://github.com/Windxy/YOLO-F .
A Novel Image Copy–Move Forgery Detection Algorithm Using the Characteristics of Local Descriptors
Authors: Zhong Jun-Liu , Yang Ji-Xiang , Zeng Hua , Zhao Ying-Qi
Published: August 2022

The image copy–move forgery can achieve the realistic effects without leaving any obvious manipulation traces because the copied source and pasted target belong to the homogenous sources. Image copy–move forgery detection (CMFD) is still a serious challenge issue for researchers, e.g. computational efficiency, occlusive (smoothing) object detection, and partial object detection, under various post-processing and geometrical transformations. This paper proposes a novel CMFD scheme using the characteristics of local descriptors. First, the proposed method deeply analyzes the structure and mines the inherent characteristics of the local descriptor (SURF) for feature extraction in the coarse and smooth regions. Subsequently, the proposed method takes the kernel features as coarse feature matching to decrease matching costs. Then, the found candidate keypoints with a relatively small quantity are used with complete features to perform fine keypoint matching for getting suspicious candidate keypoint pairs. Furthermore, based on the deep mining of the inherent local descriptor characteristics, the proposed method can indicate the forgery region localizations through keypoint pairs, even the forgeries suffering from various geometrical transformations. Then, the proposed method proposes adaptive dual-filtering algorithms of [Formula: see text]-means relying on keypoint characteristics, and spatial distance for hierarchical progress of feature filtering. Finally, Delaunay Triangulation relies on the true-positive keypoint pairs to perform the forgery region matting effectively and efficiently. The experimental results demonstrate that the proposed method can achieve the best F1 scores compared to the state-of-the-art methods in most cases, especially in anti-scaling transformations.
RESEARCH ON MAGNETO–ACOUSTIC IMAGING UNDER CHIRP CURRENT EXCITATION
Authors: ZHANG SHUNQI , MAI WENSHU , WANG YUHENG , YIN TAO , LIU ZHIPENG
Published: August 2022

Magneto–acoustic signals reflect the electrical properties of tissues, which is meaningful for the diagnosis of tumors, bleeding and other diseases. The low signal-to-noise ratio (SNR) of the magneto–acoustic signals limits the image quality of the magneto–acoustic imaging. A chirp coded excitation signal processing method for magneto–acoustic imaging is proposed in this paper. The SNR of magneto–acoustic signal is improved. In this paper, magneto–acoustic signals under different pulse widths chirp coded excitation are studied by simulation and experimental measurement. The SNRs of the magneto–acoustic signals are increased by 7.5, 16.3, 42.2, and 90.1 times under 10, 20, 50 and 100[Formula: see text][Formula: see text]s chirp excitation, respectively, for the beef and copper ring sample. At the same time, the processing time was significantly shortened to 1.2% of the average method under the single pulse excitation. The chirp coded method is of great significance to improve the SNR of magneto–acoustic signals, image quality and imaging efficiency.
PRACTICAL APPLICATION OF TAGUCHI OPTIMIZATION METHODOLOGY TO MEDICAL FACILITIES: AN INTEGRATED STUDY
Authors: PENG BING-RU , Pan LUNG-FA , HUANG SHIH-HSUN , CHEN CHIEN-YI , LIN CHIH-SHENG , CHIANG FU-TSAI , PAN LUNG-KWANG
Published: August 2022

A comprehensive review of applying Taguchi’s optimization methodology to medical facilities was evaluated in this study. Taguchi’s optimization methodology is one kind of robust designation and is reputed for integrating multiple factors to pursue one goal. According to Taguchi’s suggestion, the efficient and reliable arrangement of experimental groups with numerous factors shortened the observed timing and provided bountiful statistical data. Although this method is widely used in mechanical, civil, and chemical engineering fields, it became adopted in medical facilities only in the last decade. Most of Taguchi’s analyses focused on optimizing the imaging quality for diagnosis. The medical facilities include regular X-ray, cardiac X-ray, CT (computed tomography), CTA (computed tomography angiography), LINAC (medical linear accelerator), or gamma camera scans. The images were all manipulated according to various radiation-induced interactions; thus, the optimization process of imaging resolution can offer an essential contribution to this kind of facility. In this study, we summarized the Taguchi-related papers in medical facilities and evaluated common principles in organizing the unique orthogonal array, assigning various signal-to-noise ratios, using quantified gauges, and ranking or grading the obtained imaging quality in the datum analysis process. The further elaboration on how to preset the user demanded goal in the optimization process, the necessity of focusing on cross interaction among factors, dynamic analysis superiority over static one preset in Taguchi’s analysis, and how to preset an ideal signal-to-noise ratio to satisfy the researcher demand, the importance of verification or testification in clinical cases or the assistance of ANOVA to depict a complete concept of applying Taguchi’s optimization methodology.
EFFECT OF PERIOSTIN ON AUTOPHAGY AND FACTORS RELATED TO BONE METABOLISM IN OSTEOBLASTS
Authors: QIN HAN , CAI JUN
Published: August 2022

The purpose of this study was to explore the effect of periostin on autophagy and factors related to bone metabolism in osteoblasts. According to experimental design, some osteoblast-like cells (MC3T3-E1) were transfected by lentiviral vector to silence periostin gene. Celigo[Formula: see text] Image Cytometer and Real-Time PCR were used to assess target gene silencing effects. Western blotting was used to evaluate autophagy-associated factors (LC3B,Beclin1) and factors related to bone metabolism (RANKL, OPG, NF-[Formula: see text]B[Formula: see text]P65). Another part of osteoblasts was added with recombinant periostin protein at concentration of 75[Formula: see text]ng/mL. Monodansylcadaverine (MDC) detection was conducted to trace formation of autophagy vesicles. Factors associated with autophagy and bone metabolism were reassessed using western blotting. When periostin gene was silenced, western blotting analysis showed that the expression of LC3B-I, Beclin1, RANKL and NF-[Formula: see text]B[Formula: see text]P65 in experimental group was significantly increased; however, OPG expression was decreased. After adding recombinant periostin protein, MDC detection revealed significantly fewer green fluorescent particles in the experimental group. Western blotting results showed that the expression of LC3B, Beclin1, RANKL and NF-[Formula: see text]B[Formula: see text]P65 was decreased; however, OPG expression was increased. This study examined the regulatory mechanism of periostin in bone metabolism, which will provide a future reference for the treatment of primary teeth abnormal replacement caused by inflammation.
EFFECTS OF GRINDING, POLISHING AND AGING ON PHASE TRANSFORMATION AND PHYSICAL PROPERTIES OF DENTAL TRANSPARENT CERAMICS
Authors: ZHOU ZHIWEI , LIU YUWEI , NIU WANQIONG , REN LIJUAN , WANG ZHENHUA
Published: August 2022

Purpose: This study investigated the effects of grinding, polishing and aging on physical properties using self-made zirconia and commonly used ultraclear ceramic materials and glass ceramics in the clinic. Methods: The samples were prepared using 3% yttria-stabilized zirconia ceramic (3Y-TZP) powder containing alumina, which was granulated by ball milling. Then, it is pressed into a circular sheet together with Upcera and Wieland materials. The glass ceramic materials are molded. Finally, all materials were subjected to hydrothermal aging. Results: The self-made zirconia had better permeability than the commonly used ultratransparent ceramic materials and glass ceramics. The polishing after grinding improved the surface morphology and roughness of tooth transparent ceramic materials; Polishing after grinding improved the aging resistance of zirconia materials. The bending strength of self-made samples was less than that of two kinds of ceramics commonly used in clinic, but greater than that of glass ceramics. Aging improved the bending strength of zirconia. Conclusions: The self-made zirconia had better permeability than ultratransparent all-ceramic materials and glass ceramics, and its bending strength was better than that of glass ceramics. Grinding and polishing could improve not only the surface morphology and roughness but also the strength and aging resistance.
Magnetic black holes in AdS space with nonlinear electrodynamics, extended phase space thermodynamics and Joule–Thomson expansion
Authors: Kruglov S. I.
Published: August 2022

This paper studies thermodynamics of magnetically charged black holes in Anti-de Sitter space in an extended phase space. The cosmological constant is considered as a pressure and the black hole mass is treated as the chemical enthalpy. The black hole thermodynamics is similar to the Van der Walls liquid–gas thermodynamics. Quantities conjugated to the nonlinear electrodynamics parameter and a magnetic charge are obtained. The first law of thermodynamics and the generalized Smarr relation take place. We investigate critical behavior of black holes and Joule–Thomson expansion. The Gibbs free energy, the Joule–Thomson coefficient and the inversion temperature are calculated.
Decision Support System for Optimum Repair Technique of Concrete Bridges Girders in Egypt
Authors: Elhegazy Hosam , Mansour Dina , Ebid Ahmed , Mahdi Ibrahim , Arafat Hisham
Published: August 2022

Nowadays, value engineering (VE) has become an essential application in many fields, especially structural engineering. Bridges normally experience local damages throughout their service life, whether due to natural hazards, accidents, or harsh environmental conditions. These damages can compromise the integrity of the structure based on their severity. This paper aims to develop a decision support system (DSS) that selects the most optimal repair technique for girders of concrete bridges, considering different factors such as financial, technical, and logistical factors. The proposed DSS is developed by integrating the analytical hierarchy process (AHP) and VE to specify the optimum repair technique. Furthermore, the most common repair techniques are considered in this research, such as repairing using Steel plates, sheets of glass fiber reinforced polymers (GFRPs), laminates of carbon fiber reinforced polymers (CFRPs), external pre-stressing cables, and concrete jackets. The developed (DSS) was presented graphically as a map for the optimum repairing technique for certain (span, span/depth) combinations. Finally, the DSS was verified using collected case studies from the literature and showed good matching within the considered range of girder’s dimensions.
Concentric Dual-Chamber Pneumatic Artificial Muscles: Miniature Actuators Designed for Use in Minimally Invasive Surgical Instruments
Authors: Lathrop Robert , Ourak Mouloud , Deprest Jan , Poorten Emmanuel Vander
Published: August 2022

Development of high-performance flexible surgical instruments is important to simplify and enable new minimally invasive surgical procedures. New actuation technologies are necessary to produce flexible instrumentation that is capable of accessing difficult-to-reach anatomy and performing laborious tasks without damaging delicate tissues. Recently, concentric McKibben muscles and dual-chamber pneumatic artificial muscles (PAMs) have been proposed for use in miniature flexible robotic surgical instrumentation. In this study, several varieties of a hybrid concentric dual-chamber PAM design are built and their force generation and stroke length are compared to a contractile McKibben muscle. The concentric dual-chamber PAM is designed to provide surgical access for large diameter (1.5–2.0 mm) instruments to be delivered to the surgical site in a pneumatically sealed actuator suitable for miniaturization and integration into surgical devices used in fluid environments (fetal applications in particular). Force output of the concentric dual-chamber PAM is modeled and compared to experimental results. Initial results suggest that the newly introduced design produces a higher actuation force per unit length than traditional McKibben muscles. The prototype dual-channel PAM produced a maximum 15.25 N of force and 8.39 mm of stroke, in comparison to 13.31 N of force and 19.3 mm of stroke produced by a traditional contractile McKibben muscle of the same length, outer diameter, and materials.
Advancing SDN from OpenFlow to P4: A Survey
Authors: Liatifis Athanasios , Sarigiannidis Panagiotis , Argyriou Vasileios , Lagkas Thomas
Published: August 2022

Software-defined Networking (SDN) marked the beginning of a new era in the field of networking by decoupling the control and forwarding processes through the OpenFlow protocol. The Next Generation SDN is defined by Open Interfaces and full programmability of the data plane. P4 is a domain-specific language that fulfills these requirements and has known wide adoption over recent years from Academia and Industry. This work is an extensive survey of the P4 language covering domains of application, a detailed overview of the language, and future directions.
DIRECTGO
: A New
DIRECT
-Type
MATLAB
Toolbox for Derivative-Free Global Optimization
Authors: Stripinis Linas , Paulavičius Remigijus
Published: August 2022

In this work, we introduce
DIRECTGO
, a new
MATLAB
toolbox for derivative-free global optimization.
DIRECTGO
collects various deterministic derivative-free
DIRECT
-type algorithms for box-constrained, generally constrained, and problems with hidden constraints. Each sequential algorithm is implemented in two ways: using static and dynamic data structures for more efficient information storage and organization. Furthermore, parallel schemes are applied to some promising algorithms within
DIRECTGO
. The toolbox is equipped with a graphical user interface (GUI), ensuring the user-friendly use of all functionalities available in
DIRECTGO
. Available features are demonstrated in detailed computational studies using a comprehensive
DIRECTGOLib v1.0
library of global optimization test problems. Additionally, 11 classical engineering design problems illustrate the potential of
DIRECTGO
to solve challenging real-world problems. Finally, the appendix gives examples of accompanying
MATLAB
programs and provides a synopsis of its use on the test problems with box and general constraints.
Ecology of Yellow Dwarf Viruses in Crops and Grasslands: Interactions in the Context of Climate Change
Authors: Peters Jasmine S. , Aguirre Beatriz A. , DiPaola Anna , Power Alison G.
Published: August 2022

Our understanding of the ecological interactions between plant viruses, their insect vectors, and their host plants has increased rapidly over the past decade. The suite of viruses known collectively as the yellow dwarf viruses infect an extensive range of cultivated and noncultivated grasses worldwide and is one of the best-studied plant virus systems. The yellow dwarf viruses are ubiquitous in cereal crops, where they can significantly limit yields, and there is growing recognition that they are also ubiquitous in grassland ecosystems, where they can influence community dynamics. Here, we discuss recent research that has explored ( a) the extent and impact of yellow dwarf viruses in a diversity of plant communities, ( b) the role of vector behavior in virus transmission, and ( c) the prospects for impacts of climate change—including rising temperatures, drought, and elevated CO2—on the epidemiology of yellow dwarf viruses.
The birth of experimental physiology
Authors: Forcieri Silvia , Beretta Egidio Paolo , Riva Michele Augusto
Published: August 2022

Antonio Maria Valsalva (1666–1723) was a pioneer in experimental physiology between the 17th and 18th centuries. The Valsalva maneuver is still a popular academic topic and has broad applications not only in physiology research, but also in the diagnosis and therapy of various diseases. The celebration of 300 years from his death could be a timely occasion to commemorate the scientific works of this illustrious scientist.
ADAM17 cleaves the insulin receptor ectodomain on endothelial cells and causes vascular insulin resistance
Authors: Ghiarone Thaysa , Castorena-Gonzalez Jorge A. , Foote Christopher A. , Ramirez-Perez Francisco I. , Ferreira-Santos Larissa , Cabral-Amador Francisco J. , de la Torre Roger , Ganga Rama R. , Wheeler Andrew A. , Manrique-Acevedo Camila , Padilla Jaume , Martinez-Lemus Luis A.
Published: August 2022

To our knowledge, this is the first study to investigate the involvement of ADAM17 in causing impaired insulin-induced vasodilation in T2D. We provide evidence that ADAM17 activity is increased in the vasculature of patients with T2D and support the notion that ADAM17-mediated shedding of endothelial IRα ectodomains is a novel mechanism causing vascular insulin resistance. Our results highlight that targeting ADAM17 activity may be a potential therapeutic strategy to correct vascular insulin resistance in T2D.
Percutaneous electrical stimulation-induced muscle contraction prevents the decrease in ribosome RNA and ribosome protein during pelvic hindlimb suspension
Authors: Kotani Takaya , Tamura Yuki , Kouzaki Karina , Kato Hikaru , Isemura Mako , Nakazato Koichi
Published: August 2022

Muscle inactivity reduces ribosome synthesis and content during atrophy. Whether percutaneous electrical muscle stimulation (pEMS)-induced muscle contraction rescues the ribosome synthesis and content during muscle unloading is unclear. Using a mouse hindlimb-unloading model with pelvic suspension, we provide evidence that daily pEMS-induced muscle contraction during hindlimb unloading rescues the reduction in the expression of some ribosome synthesis-related proteins and ribosome content in the gastrocnemius muscle.
Design of the Vocal Music Feature Recognition System Based on the Internet of Things Technology
Authors: Huang Haifeng
Published: August 2022

In order to meet the needs of vocal feature recognition, the author proposes a system design based on the Internet of things technology. The principle of the method is that the body sensory layer of the body puts the sound sensors in different positions, records the primary sound signal, and monitors and makes the sound signal using the TMS320VC5402 light red processor. The network transport layer audio signal processes and sends the voice signal database in the process layer. The sound characteristic analysis module in the application layer uses a real-time dynamic change algorithm to obtain the best similarity between the experimental model and the design, identify the characteristics of the sound set red, and identify the content of the voice feature, the music, and the emotional results of the song. Experiments have shown that the system is capable of recognizing speech in a noisy environment, with an accuracy of approximately 95%, resulting in better sound control and the ability to switch switches and remote control. The system, developed with the Internet of things technology, has been proven to improve voice recognition.
Effectiveness and Safety Analysis of Plasma Beam in the Treatment of Facial Depressed Scars
Authors: Li Juan , Zhang Xia
Published: August 2022

Objective. The study aimed to analyze the effectiveness and safety of microplasma beam in the treatment of facial depression scars. Methods. 106 patients with facial depression scars treated in the hospital between January 2017 and September 2021 were selected as the observation subjects. According to different treatment methods, the patients were divided into the control group (receiving ultrapulsed carbon dioxide lattice laser treatment, n = 51) and the observation group (undergoing plasma beam treatment, n = 55). The two groups were treated for 6 months, and the treatment effects were compared between the two groups. The Visual Analogue Scale (VAS) was used to compare the pain between the two groups, and the duration of pain and the time of scab shedding were recorded. The improvement of scars was compared between the two groups according to the Evaluation Clinique des Cicatrices d’ Acne (ECCA), and the adverse reactions during treatment were compared between the two groups. Results. A clinical effective rate of 94.55% in the observation group was higher than a clinical effective rate of 82.35% in the control group (

P
<
0.05

). The VAS score in the observation group was lower than that in the control group, and the pain duration and the scab shedding time were shorter than those in the control group (

P
<
0.05

). ECCA scores in the observation group after twice and 3 times of treatments were lower than those in the control group (

P
<
0.05

). The total incidence rate of adverse reactions of 10.91% in the observation group was lower, whereas it was 25.49% in the control group (

P
>
0.05

). Conclusion. Plasma beam has a significant efficacy in the treatment of facial depressed scars, and it has mild pain, quick recovery, and high safety. Clinical Trial Registration Number. The clinical trial registration number is T2017081.
Improvement and Implementation of Calculation Method for Prestressed Concrete Cylinder Pipes
Authors: Zhang Zhu , Li Tongchun , Li Hongen , Qi Huijun
Published: August 2022

Prestressed concrete cylinder pipe (PCCP) is a type of composite pipes frequently used in water diversion projects. However, the existing methods for structural analysis of such pipes are complex; thus, very few standards are available for use in practical design. In this paper, the new straightforward technique for analyzing PCCP based on available standards is proposed in order to address the shortcomings of the existing standard and improve the convergence of subsequent calculations. The verification and comparison of case study given in the main standards showed that the proposed method is rational and useful. In addition, an advanced finite element model was utilized in practical design case that considered proper constitutive relationships, contact model, prestress of wires, and practical aspects of manufacturing, installation, and operation. Meantime, the results obtained by nonlinear FEA and the improved method are assessed and compared, which showed that nonlinear FEA based on corresponding intrinsic model and the improved method are recommendable to aid in practical design projects.
Systematic Analysis of Molecular Subtypes and Immune Prediction Based on CD8 T Cell Pattern Genes Based on Head and Neck Cancer
Authors: Yanwei Li , He Feng , Liu Shuang , Pan Zhanyu
Published: August 2022

CD8+ T lymphocytes, also known as cytotoxic T lymphocytes, are the most powerful antitumour cells in the human body. Patients with head and neck squamous cell carcinoma (HNSCC) in whom CD8+ T lymphocyte infiltration is high have a better prognosis. However, the clinical significance and prognostic significance of CD8+ T cell-related regulatory genes in HNSCC remain unclear, and further research is required. In total, 446 CD8+ T cell-related genes were obtained using WGCNA. It was discovered that 111 genes included within the TCGA and GSE65858 datasets were intimately linked to the patient’s prognosis. These genes were included in the subsequent analysis. According to consensus clustering analysis, HNSCC samples were classified into 3 subtypes (IC1, IC2, and IC3). There were substantial differences between the three subtypes in terms of immunological molecules, immune function, and the response to drug treatment. In addition, the 8-gene signature, which was generated premised on CD8+ T cell-related genes, exhibited stable prognostic prediction in the TCGA and GEO datasets and different HNSCC patient subgroups and independently served as a prognostic indicator for HNSCC. More importantly, the 8-gene signature effectively predicted immunotherapy response. We first constructed a molecular subtype of HNSCC based on CD8+ T cell-related genes. Between the three subtypes, there were significant differences in the prognosis, clinical features, immunological molecules, and drug treatment response. The 8-gene signature that was further constructed effectively predicted prognosis and immunotherapy response.
Eliminating Data Duplication in CQA Platforms Using Deep Neural Model
Authors: Rani Seema , Kumar Avadhesh , Kumar Naresh
Published: August 2022

Primary research to detect duplicate question pairs within community-based question answering systems is based on datasets made of English questions only. This research put forward a solution to the problem of duplicate question detection by matching semantically identical questions in transliterated bilingual data. Deep learning has been implemented to analyze informal languages like Hinglish which is a bilingual mix of Hindi and English on Community Question Answering (CQA) platforms to identify duplicacy in questions. The proposed model works in two sequential modules. First module is a language transliteration module which converts input questions into a mono-language text. The next module takes the transliterated text where a hybrid deep learning model which is implemented using multiple layers is used to detect duplicate questions in the mono-lingual data. The similarity between the question pairs is done utilizing this hybrid model combining a Siamese neural network with identical capsule network as the subnetworks and a decision tree classifier. Manhattan distance function is used with the Siamese network for computing the similarity between questions. The proposed model has been validated on 150 pairs of questions which were scrapped from various social media platforms, such as Tripadvisor and Quora which achieves accuracy of 87.0885% and AUC-ROC value of 0.86.
The System of the Dissemination Characteristics of Internet Public Opinion Big Data Based on Artificial Intelligence
Authors: Wu Xiaobo , Liu Sitong
Published: August 2022

In the era we live in today, the network is often used to analyze a large number of complex systems. With the development of the information society, there are more and more ways to disseminate public information through social networks. Public opinion dissemination refers to the process of disseminating public opinion information through social networks. Because the dissemination of public opinion is the basis for the exchange of ideas among multiple communicators of public opinion, the network community will certainly have an impact on the dissemination and development of public opinion. This article is based on artificial intelligence to study the network public opinion big data dissemination characteristic analysis system, introduces the network public opinion analysis system based on the characteristics of the network public opinion, introduces in detail multiple methods and clustering algorithms for extracting the text information of Internet public opinion, and proposes the Kmeans + Canopy + semantic similarity algorithm, and uses the A event to compare the parameters of the network clustering coefficient, the correlation measure and the degree centrality measure, and the performance of the Kmeans + Canopy algorithm and the Kmeans + Canopy + semantic similarity algorithm. The results of the experiment found that the clustering coefficient of “People’s Daily” in the network dissemination of A event was 0.038, which was the highest among all nodes. It shows that 3.8% of the nodes established by the “People’s Daily” can interact one-to-one to deliver information and intelligence resources. Although the complexity of the algorithm has increased and the time consumed by the system has increased, the accuracy of clustering has been improved, especially for cultural articles, the accuracy rate has been as high as 75%, and entertainment articles can reach up to 70%, and stabilize at around 70%.
Rolling Prediction of Emergency Supplies Based on Postdisaster Multisource Time‐Varying Information
Authors: Li Wei , Zhang Ming , Li Boquan , Li Songrui , Qiu Zhifeng
Published: August 2022

Accurate prediction of material demands is key to ensuring the overall efficiency of emergency rescue operations. From the perspective of the prediction method, the single‐material static prediction method based on the overall data has limitations. This method cannot flexibly adjust multiperiod material demands. Considering data sources, acquiring data regarding material demands in historical disasters is more difficult and has more uncertainty compared with statistical data on deaths. This study investigates a rolling prediction method for emergency supplies based on postdisaster multisource time‐varying information to ensure prediction accuracy. First, the proposed method uses historical cases, real‐time disasters, and time‐sharing simulation data as the source data. The method implements attribute reduction of original data samples based on rough set theory and predicts cumulative death tolls in each rolling period by using the rolling time‐domain as the basic framework and combining a support vector machine (SVM). Second, the proposed method estimates the material demands in the corresponding period by using the material demand model according to the prediction results in a single period. Finally, the proposed method is verified by an experiment with a general mean prediction error of 10.96%. However, the general mean prediction error of SVM reaches 17.77% in the static multistep prediction. Moreover, the general mean prediction error of the methods in the references is 14.13%. Overall, the method has high accuracy and strong timeliness. Prediction results can not only be used as a basis for material estimation, but also provide several scientific and effective references for the allocation and scheduling of emergency supplies.
Research on Named Entity Recognition Based on Multi-Task Learning and Biaffine Mechanism
Authors: Gao Wenchao , Li Yu , Guan Xiaole , Chen Shiyu , Zhao Shanshan
Published: August 2022

Commonly used nested entity recognition methods are span-based entity recognition methods, which focus on learning the head and tail representations of entities. This method lacks obvious boundary supervision, which leads to the failure of the correct candidate entities to be predicted, resulting in the problem of high precision and low recall. To solve the above problems, this paper proposes a named entity recognition method based on multi-task learning and biaffine mechanism, introduces the idea of multi-task learning, and divides the task into two subtasks, entity span classification and boundary detection. The entity span classification task uses biaffine mechanism to score the resulting spans and select the most likely entity class. The boundary detection task mainly solves the problem of low recall caused by the lack of boundary supervision in span classification. It captures the relationship between adjacent words in the input text according to the context, indicates the boundary range of entities, and enhances the span representation through additional boundary supervision. The experimental results show that the named entity recognition method based on multi-task learning and biaffine mechanism can improve the F1 value by up to 7.05%, 12.63%, and 14.68% on the GENIA, ACE2004, and ACE2005 nested datasets compared with other methods, which verifies that this method has better performance on the nested entity recognition task.
Genotype by Environmental Interaction and Measurements of Stability on Eight Orange-Fleshed Sweet Potato (Ipomoea batatas) Varieties: East Gojjam Zone, North West Ethiopia
Authors: Nigussie Zebider Temesgen , Gebeyehu Solomon Ali , Mulugeta Sintayehu Mussie , Guadie Yalmtesfa Firew
Published: August 2022

Sweet potato is grown for its nature of versatility and adaptability and is a secure food crop in southern parts of Ethiopia. Therefore, this research has been conducted to determine the magnitude of GEI for yield and yield-related traits and to evaluate the adaptability and stability of eight orange-fleshed sweet potato varieties across locations in North West Ethiopia. The experiment was conducted from 2018 to 2019 under rainfed conditions in four districts of East Gojjam Zone (Baso liben, Gozamin, Gonchasiso enesie, and Enbsie Sar mider) using eight OFSP varieties (Kulfo, Kabode, Vitea, Naspot 13, Naspot 12, Nekawango, RW-11, and Mayai). Data were collected on yield and yield-related traits. Genstat statistical software was used to deploy both combined analysis of variance and meta-analysis of the collected data. The combined ANOVA revealed that environment, varieties, and their interaction affect the tested varieties significantly across locations. Debremedhanite was the high-yielding environment (35.9 t/ha), and Kulfo was the best-performing variety (30.67 t/ha) over different environments. Based on the AMMI result, the environment contributes at large (48.49%) to the total variation of variety performance followed by variety (27.18%) and their interaction (24.23%). The testing locations fall in two mega environments that implies that variety recommendation needs to be specific for each mega environment. Hence, Kulfo and Naspot 12 are recommended for Debremedhanit, Arasma, and Degesech based on yield potential and stability of the varieties, and Naspot 13 is recommended for Yelamgej, Eneba, and Getesemani testing locations. This result is useful for breeders and nutritionists who are working on breeding of sweet potatoes and nutrition.
A Random Matrix Model of Business Administration Based on Business Process Orientation in Market Economic Environment
Authors: Liu Qitao
Published: August 2022

The optimization of business management strategy is a research hotspot in the field of resource processing under the market economy environment. Based on the theory of business process orientation, this paper constructs a reactive power optimization method of random matrix for business management and verifies the correctness and effectiveness of the method through an example. The random matrix construction method of enterprise management network and the feature extraction method that can reflect the operating state of the system are optimized, and the conflict problem in the process of enterprise management resource competition is solved. In the process of OpenDSS/Matlab cosimulation, the business management network state data and random matrix index data are processed by means of statistical modeling and feature extraction, and the random Petri net technology is used to construct a continuous time random matrix. The experimental results show that, combined with the verification of the business management network simulation model of the transformed IEEE-37 node, the traditional optimization method takes 96.63 s, while the business process-oriented scene matching method takes 1.32 s, which shows that the business process-oriented method constructed in this paper takes 96.63 s. The business management random matrix has obvious advantages in optimizing the operation speed, which verifies the accuracy, feasibility, and rapidity of the method and effectively improves the performance of the system.
Design of Experiential Teaching System for Solfeggio in Normal Universities Based on Machine Learning Algorithm
Authors: Liu Ke , Awang bin Othman Johan
Published: August 2022

At present, with the rapid development of the Internet and its close connection with our life, more and more educators apply the Internet to teaching. However, there is little research on the application of the Internet in solfeggio teaching, and there are some problems in the teaching process, such as nonstandard use methods, inability to highlight teaching objectives, and mismatch with students’ professional level. On the premise of fully understanding the teaching objectives of solfeggio in China, this paper designs an experiential teaching system of solfeggio in normal universities based on machine learning algorithm, studies the application of digital technology in solfeggio, including Internet technology, multimedia digital technology, and the use of music software, and analyzes the auxiliary role of digital technology in solfeggio teaching by combining the specific teaching contents of online solfeggio teaching during the epidemic period. In this experiment, the average classification accuracy of WNB algorithm is 0.767, while that of BP algorithm is 0.683. Experimental results show that WNB algorithm outperforms BP algorithm in classification. At the same time, in terms of time efficiency, the average time consumption of WNB algorithm in this experiment is about 0.026 s, while that of BP algorithm is about 0.45 s. Compared with WNB algorithm, the time consumption of WNB algorithm is less. Through concrete practice, it is proved that the combination of solfeggio teaching and digital technology is of great significance to both teachers’ teaching and students’ learning.
Visual Monitoring Technology for Substation Vulnerable High-Voltage Electrical Equipment Based on ISSA-LSTM Deep Learning Model Coupling Video Overlay Algorithm
Authors: Wang Shifeng , Ding Xueyong , Tan Qingji
Published: August 2022

To enhance the visualization effect of substation high-voltage electrical equipment vulnerability, this study proposes an ISSA-LSTM coupled video overlay algorithm-based substation high-voltage electrical equipment vulnerability visualization and monitoring model. Using the improved

α

blending algorithm combined with the inverse sampling of video background color, overlaying visible video as well as infrared video, using the improved adaptive weighted two-dimensional principal component analysis (W2DPCA) to fuse the base layer, selecting the detail layer as the final detail layer, obtaining the final fusion frame, and realizing the visualization and monitoring of substation high-voltage electrical equipment vulnerability, and introducing the improved sparrow search algorithm (ISSA) to establish long and short-term memory network prediction model to reduce the prediction error and improve the monitoring accuracy rate. The experimental results show that the monitoring frames obtained by this method can reflect rich details of substation high-voltage electrical equipment, and the texture color and equipment edge contrast are enhanced to facilitate accurate determination of substation high-voltage electrical equipment vulnerability, and the prediction accuracy of ISSA-LSTM model is as high as 99.85%.
Efficacy of Human-Recombinant Epidermal Growth Factor Combined with Povidone-Iodine for Pressure Ulcers and Its Influence on Inflammatory Cytokines
Authors: Zhao Zunjiang , Lv Dalun , Zhang Baode , Yong Liu , Zhang Rongtao , Wang Xiukun
Published: August 2022

Purpose. To determine the clinical efficacy of recombinant human epidermal growth factor (rh-EGF) combined with povidone-iodine (PVI) on patients with pressure ulcers (PUs). Methods. One hundred and five PU patients treated between January 2018 and January 2021 were enrolled and retrospectively analyzed. Of them, 50 patients who received conventional treatment were assigned to the control group (Con group), while 55 patients treated with rh-EGF combined with PVI were assigned to the observation group (Obs group). The two groups were compared in clinical efficacy, PU alleviation (total area reduction rate, total depth reduction rate, and total volume reduction rate), healing time, pain degree (Visual Analog Scale [VAS] score), inflammatory indexes (interleukin-8 [IL-8], tumor necrosis factor-α [TNF-α], and hypersensitive C reactive protein [hs-CRP]), and hydroxyproline content in the wound. Results. The Obs group yielded a higher total effective rate than the Con group (

P
<
0.05

). The Obs group also experienced statistically shorter healing time and milder pain, with better PU alleviation and lower levels of inflammation indexes compared with the Con group (all

P
<
0.05

). In addition, a higher hydroxyproline content in the wound was found in the Obs group. Conclusions. All in all, rh-EGF combined with PVI has a definite curative effect on patients with PUs. It can promote PU alleviation and hydroxyproline secretion in the wound and inhibit pain and inflammatory reactions, which is worthy of clinical promotion.
RFID Indoor Positioning Based on AP Clustering and Improved Particle Swarm Algorithm
Authors: Manman Zhang , Peng Li , He Xu , Ruchuan Wang
Published: August 2022

This paper proposes a method based on AP clustering and an improved particle swarm algorithm for radio frequency identification (RFID) indoor positioning, called the AP-PSO method. Firstly, an AP clustering algorithm is used to cluster the RSSI values of the experimental region tags with similarity, in order to achieve the division of tagged regions, reduce the search area of the later improved particle swarm algorithm, and reduce the search time. Secondly, the learning factor of the particle swarm algorithm is dynamically adjusted, in order to improve the search ability and convergence speed of the global optimal solution of particles. The experimental results show that the algorithm can effectively achieve RFID indoor positioning of the tags to be measured, with high positioning accuracy and with the algorithm spending less time.
Examine the Effectiveness of Fiber Addition and Its Length on the Mechanical Properties of Flax and Nanographene‐Based Biocomposites
Authors: Alsaiari Norah Salem , Sivakumar S. , Annamalai Selvam , Thiyagu M. , Viji M. , Singh Rahul , Wabaidur Saikh Mohammed , Seikh A. H. , Alemayehu Agonafir
Published: August 2022

Organic fiber biocomposites have figured prominently in various industries of commerce during the last 3 to 5 years owing to their remarkable physical and mechanical abilities. The main purpose of this experimental research is to evaluate the biomechanical and geomorphologic belongings of nanostructured substance under naturalistic situations. To accomplish such a cognitive approach, flaxseed strands are employed as reinforcing, nano‐based graphene as an additive, and epoxy as a matrix phase, with the following restrictions in imagination: (i) fiber lengths, (ii) fiber volume fraction, and (iii) weight proportions of nanoparticles. The nanocomposites are combined by means of the hand lay‐up process based on the Taguchi orthogonal specification. The material characteristics of the substance, like bending, tension, and shock characteristics, are assessed in line with the standard specification. The material properties of mixtures’ second levels are the highest when compared to all other configurations. The elastic modulus of nanoparticle biocomposites revealed that 2% graphene provides 32.39 percent, 4% graphene provides 36.39 percent, and 6% nanoparticle pertains to 31.23 percent. Fractured images captured using scanning electron microscope of cracked samples have been used to comprehend the overall failure mechanism of a composite in mechanical characterization.
Rotational Differential-Linear Attack on Chaskey
Authors: Qin Yuan , Wang Gaoli , Zhang Guoyan
Published: August 2022

Rotational/Rotational-XOR differential-linear attack is a kind of powerful attack on ARX primitives. In this paper, we analyse the message authentication code algorithm—Chaskey—by using rotational differential-linear attack and using partitioning technique for key recovery. We presentthe results of distinguishing attack under weak-key and related-key settingswith correlation

2

−
55.636

for 9-round Chaskey. This is for the first time rotational differential-linear distinguisher has been used to analyse Chaskey. It is concluded that Chaskey can resist against rotational differential-linear attack.