bluuebunny/crossref_metadata_2025 huggingface dataset:
Return Instruction Classification in Binary Code Using Machine Learning
Authors: Qiu Jing , Geng Xiaoxu , Dong Feng
Published: September 2022

Binary code analysis is vital in source code unavailable cases, such as malware analysis and software vulnerability mining. Its first step could be function identification. Most function identification methods are based on function prologs/epilogs. However, functions may not have standard prologs/epilogs. To identify these functions, we need to use other methods. One approach is to identify return instructions first and then identify the start of a function. Currently, the multi-layer perceptron model is exploited to identify and validate a return instruction at a specific location. On this basis, a new approach is proposed to improve accuracy and provide more details. Specifically, a return instruction is classified into three classes: (1) false return instruction, (2) true return instruction inner a function but not the last instruction, and (3) true return instruction at the end of a function. The evaluation is performed on 5782 real-world binaries. Meanwhile, common classifiers including fully connected neural network, Two-layer Bidirectional Recurrent Neural Network (TBRNN), Two-layer Bidirectional Gate Recurrent Unit (TBGRU), Two-layer Bidirectional Long Short-term Memory Network (TBLSTM), Decision Tree, Random Forest, XGBoost, and Support Vector Machine (SVM) are evaluated on the same data set. The result shows that TBLSTM achieves an accuracy of 99.78%, which is higher than that of other classifiers in the evaluation, including the state-of-the-art tool IDA Pro 7.7.
The smooth 4-genus of (the rest of) the prime knots through 12 crossings
Authors: Brittenham Mark , Hermiller Susan
Published: September 2022

We compute the smooth 4-genera of the prime knots with 12 crossings whose values, as reported on the KnotInfo website, were unknown. This completes the calculation of the smooth 4-genus for all prime knots with 12 or fewer crossings.
PROPERTIES AND INTEGRAL INEQUALITIES INVOLVING WITH THE GENERALIZED s-TYPE PREINVEX MAPPINGS IN FRACTAL SPACE
Authors: YU SHUHONG , DU TINGSONG , YU BO
Published: September 2022

As a generalization of the convex mappings, the generalized [Formula: see text]-type preinvex mappings are firstly introduced. Their meaningful properties are then investigated and the Hermite–Hadamard-type integral inequalities via the newly proposed mappings in fractal space are developed. In accordance with the newly proposed identity with three parameters, it is interesting to present certain integral inequalities with regard to the mappings whose first-order derivatives in absolute value belong to the generalized [Formula: see text]-type preinvexity. As applications, on the basis of local fractional calculus, certain inequalities in view of numerical integration, [Formula: see text]-type special means, as well as moments of random variable, are acquired, respectively.
A NOVEL ANALYTICAL APPROACH TO FRACTAL NONLINEAR DISPERSIVE MODEL WITH VARIABLE COEFFICIENTS
Authors: WEI CHUN-FU , LUO JUN-WEI , ZHAI HAI-XIA
Published: September 2022

In this paper, the fractal nonlinear dispersive model (FNDM) with variable coefficients is investigated by variational perspective, and its fractal variational principle is constructed by using the He’s fractal semi-inverse method. Based on the fractal variational principle, a novel analytical algorithm is successfully established to solve the fractal model. Two examples are given to illustrate the efficiency and accuracy of the proposed algorithm.
Thickness Configuration Effect on Frequency and Critical Speed of Spinning Variable-Thickness Cylindrical Shells
Authors: Teng Mei Wen , Wang Yan Qing
Published: September 2022

The thickness configuration effect on natural frequency and critical speed of spinning variable-thickness cylindrical shells is investigated in this paper. Based on Love’s thin shell theory, the eigenfrequency equation is derived by employing the Rayleigh–Ritz method in conjunction with Chebyshev polynomials, considering the effects of Coriolis and centrifugal forces due to rotation. Seven types of thickness configurations and various classical boundary conditions are taken into account. Backward and forward wave frequencies, the critical speed, and the mode shapes of the spinning variable-thickness cylindrical shells are solved. Results show that the thickness configuration not only changes circumferential wave number corresponding to the lowest natural frequency, but also affects the critical speed. However, the influence of thickness configuration on mode shapes of the shell is not obvious. The stronger the boundary constraints, the more obvious effect of slope of thickness variation on the critical speed of spinning cylindrical shells.
EFFECTS OF STATIC RESISTANCE TRAINING OF NECK MUSCLES ON NECK-TYPE CERVICAL SPONDYLOSIS WITH UPPER CROSS SYNDROME
Authors: FU TIANLI , WANG YANXIA , JING QI , XIAO LIN , YU PEI , REN GUIFANG , ZHANG DENGFENG , LI ZONGRUN
Published: September 2022

The objective of this research is to study the effects of static resistance training of neck muscles on neck-type cervical spondylosis (NTCS) with upper cross syndrome (UCS). The NTCS patients with UCS were randomly divided into an observation group and a control group. The observation group was given conventional therapy plus static resistance training of neck muscles, while the control group was given conventional therapy plus ordinary cervical exercises. The scores of the visual analogue scale (VAS), neck disability index (NDI), and clinical assessment scale for cervical spondylosis (CASCS) and the cervical physiological curve were compared, and the overall efficacy was analyzed. After treatment, the VAS and NDI scores were lower in the observation group than in the control group. The cervical physiological curve was more significant in the observation group. The CASCS score was higher in the observation group than the control group after treatment. The observation group had obviously superior clinical efficacy. Therefore, in the treatment of NTCS with UCS, static resistance training of neck muscles can ameliorate the clinical symptoms of patients and restore the cervical physiological curve, with definite short-term efficacy, making it superior to ordinary cervical exercises, so it is worthy of clinical popularization.
TOWARDS EYE-TRACKING-BASED TECHNOLOGY ON SIGHT INTERPRETATION PERFORMANCE IMPROVEMENT
Authors: WANG XIAOWEI , GUO LIANG , YUAN ZHONGZHENG , TAMURA SHINICHI
Published: September 2022

This study used the recording of eye-tracking-based target domain (TD) fixation as the primary approach to explore the correlation between occupying fixation and sight interpretation (SI) performance. This paper records the gaze plot and gaze duration during the sight interpretation and analyzes the correlation between them and the interpretation performance. First, we designed the nine-point track calibration for a noninvasive study. Second, we carried out pre-experiments to find out the best experimental conditions. Finally, after eye rest, we performed the formal test. Extensive experiments were implemented to verify the factors that affect the SI performance, including the number of TD occupying fixations, the time-cost of TD occupying fixation, and the concentration of TD occupying fixation. Statistical analysis of experiments concluded that the psychological dictionary, Long-term Memory (LTM) information, and bilingual conversion skills are the main factors affecting the number and time of eye-tracking TD occupying fixation spots.
PREDICTION MODEL FOR IN-HOSPITAL MORTALITY OF PATIENTS WITH HEART FAILURE BASED ON OPTUNA AND LIGHT GRADIENT BOOSTING MACHINE
Authors: YANG JIE , YAN JUANJUAN , PEI ZHONGYANG , HU ANXIA , ZHANG YANBO
Published: September 2022

Background and objective: Heart failure (HF) is a lethal public health problem in the field of cardiovascular diseases with high incidence, rehospitalization, and mortality rates. Therefore, the prediction of in-hospital mortality of patients with HF is of paramount significance in providing clinical information to doctors. To improve the accuracy of prediction, this study constructed a prediction model for in-hospital mortality of patients with HF based on machine learning algorithms. Methods: We obtained the medical data of 1901 patients with HF from a public database and performed preprocessing to extract 19 variables as inputs of the prediction model. A prediction model was constructed based on the light gradient boosting machine (LightGBM) and its performance was improved using the Optuna framework to optimize the LightGBM hyperparameters. To evaluate the proposed algorithm, five machine learning algorithms widely used in the field of biomedicine were selected for comparison: support vector machine, classification and regression tree, random forests, gradient boosting decision tree, and LightGBM. Further, we explained the proposed model based on Deep SHapley Additive exPlanations. We also quantified the importance of each variable and analyzed its correlation with the results. Results: The accuracy rate of Optuna–LightGBM was [Formula: see text], the precision rate was [Formula: see text], the recall rate was [Formula: see text], the [Formula: see text]-measure was [Formula: see text], and the area under the receiver operating characteristic curve was [Formula: see text]. The results show that this model outperformed other models on all evaluation indicators. Conclusions: The proposed method can be used to construct a prediction model for in-hospital mortality of patients with HF. Optuna–LightGBM can assist clinicians to quickly classify the high-risk patients with HF so that the clinicians can provide timely care and optimize hospital resources.
DESIGN, KINEMATICS AND MANIPULABILITY ANALYSES OF A SERIAL-LINK ROBOT FOR MINIMALLY INVASIVE TREATMENT IN FEMORAL SHAFT FRACTURES
Authors: ZHU QING , TIAN MENGQIAN , LIU QINGYUN , WANG XINGSONG
Published: September 2022

The application of robot in orthopedic clinical surgery is more and more accepted. A femoral fracture reduction robot is described in the paper. The mechanism of the manipulator comprises a six-DOF serial-link robot, referred to as a 3P3R robot, with three prismatic joints and three rotational joints (including one for the knee). The manipulability of the system was analyzed, and its operability over the entire whole work space was verified. In addition, the existence of an inverse kinematic solution of the system was established, and the same was analytically implemented with physical meaningfulness. The kinematic analysis and investigation of the workspace confirmed the feasibility of the mechanism for the given design parameters. The joint displacements and rotation angles required to achieve the desired posture of the end-effector of the mechanism were also determined. The results of simulation substantiated the effectiveness of the developed robotic system, and its prospect for practical application through further research.
LIQUID PHANTOM-BASED MEASUREMENT OF JAW BONE DENSITY USING CBCT
Authors: CHEN XIAOZHAO , HUANG JINFENG , ZHANG WEI , LI RUORAN , KANG YAN
Published: September 2022

Preoperative bone mineral density evaluation is a critical step in obtaining dental implant success. This paper summarizes the four most commonly used methods for evaluating the mineral density of jaw bone, discusses the shortcomings of these methods, and proposes a quantitative X-ray computed tomography (QCT) method for oral cone beam CT (CBCT) based on K2HPO4 liquid phantoms, in addition to describing the specific measurements. Moreover, this study evaluates K2HPO4 liquid phantoms’ uniformity, linearity, and stability in comparison with solid phantoms. The results show that CBCT bone density measurements based on K2HPO4 liquid phantoms are equivalent to those of conventional CT based on solid phantoms. In view of the low production cost and convenient and flexible configuration, the method based on liquid phantoms is worthy of clinical application.
PARAMETRIC DESIGN, MECHANICAL PROPERTIES AND PERMEABILITY OF BIOMEDICAL POROUS SCAFFOLDS BASED ON TYPICAL STRUCTURE UNITS
Authors: ZHANG QIANG , LI BAOQI , WEI GUIJIANG , LIU GUOHAO , LIU JUNMING
Published: September 2022

Structure unit type is the most important factor for the mechanical properties and permeability of biomedical porous scaffolds. Therefore, in this work, four kinds of commonly used structure units including three periodic minimal surface (Primitive (P) and Gyroid (G) structures), body-centered cubic (BCC) and diamond (D) structures were chosen to design the structure units and porous scaffolds with the same porosity, and the mechanical and permeability of the structure units and scaffolds were systematically analyzed by using the finite element method. The results show that the elastic modulus of scaffolds decreases with the increase of porosity, and the order of elastic modulus is: P [Formula: see text] D [Formula: see text] G [Formula: see text] BCC structure. P structure unit and porous scaffolds exhibit the best deformation resistance, but the structures have the most severe stress concentration at the joints. BCC structure unit and porous scaffolds have the worst deformation resistance, and the stress concentration at the joints is also obvious. Fluid simulation shows that the porous scaffolds exhibit good permeability and can meet the requirements for the use of biomedical porous scaffolds. The results of this paper provide a theoretical basis for the design and manufacture of porous scaffolds, and have a certain reference value.
Square integrals of the logarithmic derivatives of Selberg’s zeta functions in the critical strip
Authors: Hashimoto Yasufumi
Published: September 2022

In our previous work (Y. Hashimoto, Selberg’s zeta function for the modular group in the critical strip, Math. Nachr. 294 (2021) 1899–1904, https://doi.org/10.1002/mana.202000268 ), we proposed an upper bound of the logarithmic derivative of Selberg’s zeta function for the modular group in the critical strip. This paper studies the growth of its square integral for the modular group, co-compact arithmetic groups derived from indefinite quaternion algebras and their subgroups.
Supersingular conjectures for the Fricke group
Authors: Morton Patrick
Published: September 2022

A proof is given of several conjectures from a recent paper of Nakaya concerning the supersingular polynomial [Formula: see text] for the Fricke group [Formula: see text], for [Formula: see text]. One of these conjectures gives a formula for the square of [Formula: see text] (mod [Formula: see text]) in terms of a certain resultant, and the other relates the primes [Formula: see text] for which [Formula: see text] splits into linear factors (mod [Formula: see text]) to the orders of certain sporadic simple groups.
Explicit classification of isogeny graphs of rational elliptic curves
Authors: Barrios Alexander J.
Published: September 2022

Let [Formula: see text] be an integer such that [Formula: see text] has genus [Formula: see text], and let [Formula: see text] be a field of characteristic [Formula: see text] or relatively prime to [Formula: see text]. In this paper, we explicitly classify the isogeny graphs of all rational elliptic curves that admit a nontrivial isogeny over [Formula: see text]. We achieve this by introducing [Formula: see text] parameterized families of elliptic curves [Formula: see text] defined over [Formula: see text], which have the following two properties for a fixed [Formula: see text]: the elliptic curves [Formula: see text] are isogenous over [Formula: see text], and there are integers [Formula: see text] and [Formula: see text] such that the [Formula: see text]-invariants of [Formula: see text] and [Formula: see text] are given by the Fricke parameterizations. As a consequence, we show that if [Formula: see text] is an elliptic curve over a number field [Formula: see text] with isogeny class degree divisible by [Formula: see text], then there is a quadratic twist of [Formula: see text] that is semistable at all primes [Formula: see text] of [Formula: see text] such that [Formula: see text].
On the order of magnitude of Sudler products II
Authors: Grepstad Sigrid , Neumüller Mario , Zafeiropoulos Agamemnon
Published: September 2022

We study the asymptotic behavior of Sudler products [Formula: see text] for quadratic irrationals [Formula: see text]. In particular, we verify the convergence of certain perturbed Sudler products along subsequences, and show that [Formula: see text] and [Formula: see text] whenever the maximal digit in the period of the continued fraction expansion of [Formula: see text] exceeds [Formula: see text]. This generalizes known results for the period one case [Formula: see text].
Improving the quality of service by continuous traffic monitoring using reinforcement learning model in VANET
Authors: Velmurugan P. , Ashok B.
Published: September 2022

The growing number of automobiles on the road has now become a significant source of traffic, accidents, and pollution. Intelligent Transportation Systems (ITSs) could be the key to finding solutions that drastically reduce these issues. The linked vehicular networks channel is a fast-expanding topic for workflow management system and development. Traffic detection is a big issue on city streets. To make informed decisions in order to prevent traffic jams, one of the solutions is the Vehicular Ad-Hoc Network (VANET). We describe an approach for detecting traffic jams in both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, which provides vehicle drivers with multiple alternatives for determining the location of congestion, its size, and how to prevent becoming stuck in a traffic jam. The data are sent to the driver to assist him in making the appropriate selection. Delivering Quality of Service (QoS) for automotive networks is a difficult challenge due to the characteristics such as terms of transmission or high mobility, congested and fragmented channels, hardware defects, and a large number of vehicular devices. As a result, it is extremely desired to get and distribute resources efficiently. This research uses Reinforcement Learning with Decision-Making Model (RLDMM) method to enhance channel allocation. By using latency, Signal-to-Interference Ratio (SIR) and QoS, the available channel is initially determined. This method is used to determine suitable channel for platoon members. As a result, the proposed RLDMM achieves an SINR reduction of 29 Db, 69 kbps of throughput, 21.4% of collision probability with 4[Formula: see text]ms of latency.
Study of Kerosene–Gold–DNA Nanoparticles in a Magnetized Radiative Poiseuille Flow with Thermo-Diffusion Impact
Authors: Mishra S. R. , Pattnaik P. K. , Baag S. , Bhatti M. M.
Published: September 2022

Due to their unique thermal and magnetic characteristics, gold-DNA nanoparticles have a wide spectrum of uses in pharmacology, drug delivery systems, treatment for cancer, and other disciplines. The current problem that analyzes the planar Poiseuille flow consists of gold nanoparticles with a typical fluid based on kerosene. The impact of mixed convection is considered in conjunction with the effects of radiative heat flow and thermo-diffusion (Soret). The numerical technique is utilized to solve the one-dimensional transformed equation for flow phenomena using the built-in MATLAB function bvp5c, with specific fixed values of relevant parameters adjusted. However, for different parameters that are either joint or unique, they are presented in both the surface and two-dimensional plots. It is observed that the particle concentration, as well as the resistive forces, favors greatly influencing the fluid velocity; nevertheless, raising the Peclet number also retards it owing to thermal conductivity retardation. The fluid concentration increases as the Reynolds number increases, but the shear rate decreases. Furthermore, in the conclusion section, the applications for the present research and future scope are discussed.
A Query Optimizer for Range Queries over Multi-Attribute Trajectories
Authors: Xu Jianqiu , Lu Hua , Bao Zhifeng
Published: September 2022

A multi-attribute trajectory consists of a spatio-temporal trajectory and a set of descriptive attributes. Such data enrich the representation of traditional spatio-temporal trajectories to have comprehensive knowledge of moving objects. Range query is a fundamental operator over multi-attribute trajectories. Such a query contains two predicates, spatio-temporal and attribute, and returns the objects whose locations are within a distance threshold to the query trajectory and attributes contain expected values. There are different execution plans for answering the query. To enhance the capability of a trajectory database, an optimizer is essentially required to (i) accurately estimate the cost for alternative query strategies in terms of disk accesses, (ii) build a decision-making module that automatically sorts the data in an appropriate way and selects the optimal query plan, and (iii) update the analytical models when new trajectories are arrived. The cost model supports both uniform and non-uniform spatio-temporal data distribution and incorporates attribute distribution. The optimizer is fully developed inside a database system kernel and comprehensively evaluated in terms of accuracy and effectiveness by using large real and synthetic datasets.
Edge-SLAM: Edge-Assisted Visual Simultaneous Localization and Mapping
Authors: Ben Ali Ali J. , Kouroshli Marziye , Semenova Sofiya , Hashemifar Zakieh Sadat , Ko Steven Y. , Dantu Karthik
Published: September 2022

Localization in urban environments is becoming increasingly important and used in tools such as ARCore [18], ARKit [34] and others. One popular mechanism to achieve accurate indoor localization and a map of the space is using Visual Simultaneous Localization and Mapping (Visual-SLAM). However, Visual-SLAM is known to be resource-intensive in memory and processing time. Furthermore, some of the operations grow in complexity over time, making it challenging to run on mobile devices continuously. Edge computing provides additional compute and memory resources to mobile devices to allow offloading tasks without the large latencies seen when offloading to the cloud.

In this article, we present Edge-SLAM, a system that uses edge computing resources to offload parts of Visual-SLAM. We use ORB-SLAM2 [50] as a prototypical Visual-SLAM system and modify it to a split architecture between the edge and the mobile device. We keep the tracking computation on the mobile device and move the rest of the computation, i.e., local mapping and loop closing, to the edge. We describe the design choices in this effort and implement them in our prototype. Our results show that our split architecture can allow the functioning of the Visual-SLAM system long-term with limited resources without affecting the accuracy of operation. It also keeps the computation and memory cost on the mobile device constant, which would allow for the deployment of other end applications that use Visual-SLAM. We perform a detailed performance and resources use (CPU, memory, network, and power) analysis to fully understand the effect of our proposed split architecture.
Security Responses in Software Development
Authors: Lopez Tamara , Sharp Helen , Bandara Arosha , Tun Thein , Levine Mark , Nuseibeh Bashar
Published: September 2022

The pressure on software developers to produce secure software has never been greater. But what does security look like in environments that do not produce security-critical software? In answer to this question, this multi-sited ethnographic study characterizes security episodes and identifies five typical behaviors in software development. Using theory drawn from information security and motivation research in software engineering, this article characterizes key ways in which individual developers form security responses to meet the demands of particular circumstances, providing a framework managers and teams can use to recognize, understand, and alter security activity in their environments.
Mitigating the Effects of Stray-Current Attack on Non-Machined Surfaces in Electrochemical Machining Through Gas-Shielding in C6H5K3O7 Solution
Authors: Wang Jingtao , Xu Zhengyang , Liu Jia , Wei Haodi
Published: September 2022

Electrochemical machining (ECM) is a promising method for processing the leading and trailing edges of the blades that are composed of nickel-based superalloys (Inconel 718), but often leads to unwanted stray corrosion on non-machined surfaces. This study investigates the use of a novel C6H5K3O7 solution to fabricate the leading and trailing edges of the blade that is free of stray corrosion. First, the basic electrochemical dissolution behavior of Inconel 718 in the C6H5K3O7 solution is analyzed in comparison with that in NaNO3 solution by means of a potentiodynamic polarization. The results showed that Inconel 718 in the C6H5K3O7 solution has a lower breakdown potential and the structure of its passive film was looser than that in the NaNO3 solution. Second, the current efficiency of Inconel 718 in the C6H5K3O7 solution exhibited non-linear dissolution behavior, and the material removal rate was much lower than that in the NaNO3 solution. In-situ observations indicated that a stable and continuous insulating gaseous layer was induced surrounding the anode surface through C6H5K3O7 solution to suppress the stray-current attack on the non-machined surfaces. Third, corresponding models and simulations of ECM process in the C6H5K3O7 solution were formulated to examine the effects of gaseous layer on stray corrosion. Fourth, the effects of the parameters of pulse processing on stray corrosion on the non-machined surfaces was analyzed. Experimental results showed that the self-induced gaseous layer could suppress stray machining by insulation effect, and a pulsed current with a short-pulse duration and a high-pulse frequencies was helpful for reducing the zones of stray corrosion. Precise structure of the leading/trailing edges of the twisted blade free of stray corrosion were successfully fabricated in the C6H5K3O7 solution. In comparison with that manufactured in the NaNO3 solution, the zones of stray corrosion was reduced by 8.4 times under the same processing parameters. The results here verify the feasibility of C6H5K3O7 as an electrolyte to reduce the stray-current attack on non-machined surfaces.
Clinical Outcomes and Their Prognostic Factors among Cervical Cancer Patients with Bone Recurrence
Authors: Atjimakul Thiti , Hanprasertpong Jitti
Published: September 2022

Background. Bone recurrence occurs in 0.75%-8% of cervical cancer patients after primary treatment. Only a few previous studies have reported on survival times associated with prognostic factors for bone recurrent cervical cancer. This study aimed to evaluate the oncological outcomes and their predictors among cervical cancer patients with bone recurrence. Methods. The medical records of cervical cancer patients with bone recurrence who received primary treatment at Songklanagarind Hospital from January 2002 to December 2017 were retrospectively reviewed. Prognostic factors were identified using a Cox regression model. Results. The study included 6,354 cervical cancer patients, of whom 98 (1.54%) had bone recurrence at a median time of 25 months after the primary treatment (range 4.9-136 months). The most frequent site of bone recurrence was the spine (81.00%); the two most common visceral coexisting recurrence sites were the lungs and the liver. The median recurrence-free interval (RFI) was 21 months. Of the patients with recurrence, 75 (76.50%) were treated with combined radiation therapy and chemotherapy. The one-year overall survival (OS) after recurrence was 22.70%. On multivariate analysis, age under 60 years at the time of recurrence diagnosis (hazard ratio [HR] = 2.48, 95% CI = 1.47-4.18,

p
=
0.001

) and an RFI less than 21 months (HR = 1.63, 95% CI = 1.04-2.55,

p
=
0.03

) were independent prognostic factors for OS after recurrence. Conclusion. Bone recurrence in cervical cancer patients is rare and is associated with poor survival. Our study found that age and RFI were significant prognostic factors for OS in cervical cancer patients with bone recurrence.
[Retracted] Digital Protection of Historic Buildings in Urban Planning
Authors: He Shan , Wu Wei , Wang Xuan
Published: September 2022

With the rapid development of urbanization, urban land has been expropriated and developed on a large scale. Moreover, people’s awareness of the protection of historical buildings is relatively weak, so some historical buildings have been demolished or rebuilt. Historical buildings have played an important role in the spread of national culture, so how to use some methods to protect historical buildings from being destroyed has become an urgent problem to be solved. The protection of historical buildings includes a series of complicated and rigorous procedures, such as on‐site drawing and mapping, survey and design, and scheme discussion and construction. The surveying and mapping of traditional historical buildings require people to do it by themselves, so it is inevitably time‐consuming and labor‐intensive. This paper first discussed and analyzed the significance of historical building protection, and then used digital technology to make up for the shortcomings of traditional manual surveying and mapping and historical building protection methods. Modern technologies such as three‐dimensional laser scanning technology and virtual reality technology are used to restore the style and appearance of historical buildings. Among them, in terms of the color of historical buildings, the restoration degree of buildings based on digital protection technology has reached 56.1%; at the same time, the efficiency of information collection and processing, and virtual model construction has also been improved. Thus, the ultimate goal of historical building protection is achieved, and it provides a reference for the digital protection of historical buildings.
Vandermonde-Based Unitary Precoding Method for Integer-Forcing Design
Authors: Jiang Hua , Kong Linghong , Du Sidan
Published: September 2022

An integer-forcing linear receiver has significantly better performance than conditional receivers for slow-fading channels because it directly recovers an integer linear combination of signals instead of decoding all signals. The performance in terms of achievable rate, outage probability, and error rate can be improved with a unitary matrix precoder imposed at each channel realization. In this paper, a new special unitary matrix precoding approach is proposed to reduce the computational complexity. Different from the parameterization technique with many parameters, the new method constructs a unitary Vandermonde matrix with only a single parameter. The optimal Vandermonde matrix is determined on the basis of the shortest vector of a lattice generated by the precoding matrix in which the single parameter is searched. Therefore, its complexity is reduced to a polynomial time, whereas the traditional unitary precoder has exponential complexity. Simulation results show that the proposed scheme can achieve the performance similar to the benchmark schemes but with much lower complexity. The scheme offers a good trade-off between performance and complexity.
Potential Targets and Action Mechanism of Gastrodin in the Treatment of Attention-Deficit/Hyperactivity Disorder: Bioinformatics and Network Pharmacology Analysis
Authors: Song Zhe , Luo Guangzhi , Han Chengen , Jia Guangyuan , Zhang Baoqing
Published: September 2022

Objective. Gastrodin is a main medicinal component of traditional Chinese medicine (TCM) Gastrodia elata Blume (G. elata), presenting the potential for the treatment of attention-deficit/hyperactivity disorder (ADHD). However, the underlying targets and action mechanisms of the treatment have not been identified. Methods. The gastrodin-related microarray dataset GSE85871 was obtained from the GEO database and analyzed by GEO2R to obtain differentially expressed genes (DEGs). Subsequently, the targets of gastrodin were supplemented by the Encyclopedia of Traditional Chinese Medicine (ETCM), PubChem, STITCH, and SwissTargetPrediction databases. ADHD-associated genes were collected from six available disease databases (i.e., TTD, DrugBank, OMIM, PharmGKB, GAD, and KEGG DISEASE). The potential targets of gastrodin during ADHD treatment were obtained by mapping gastrodin-related targets with ADHD genes, and their protein–protein interaction (PPI) relationship was constructed by the STRING database. The GO function and KEGG pathway enrichment analyses were performed using the ClueGO plug-in in the Cytoscape software and DAVID database, respectively. Finally, the binding affinity between gastrodin and important targets was verified by molecular docking. Results. A total of 460 gastrodin-related DEGs were identified from GSE85871, and 124 known gastrodin targets were supplemented from 4 databases, including ETCM. A total of 440 genes were collected from the above 6 disease databases, and 267 ADHD-relevant genes were obtained after duplicate removal. Through mapping the 584 gastrodin targets to the 267 ADHD genes, 16 potential therapeutic targets were obtained, among which the important ones were DRD2, DRD4, CHRNA3, CYP1A1, TNF, IL6, and KCNJ3. The enrichment analysis results indicated that 16 potential targets were involved in 25 biological processes (e.g., dopamine (DA) transport) and 22 molecular functions (e.g., postsynaptic neurotransmitter receptor activity), which were mainly localized at excitatory synapses. The neuroactive ligand-receptor interaction, cholinergic synapse, and dopaminergic synapse might be the core pathways of gastrodin in ADHD treatment. Through molecular docking, it was preliminarily verified that gastrodin showed good binding activity to seven important targets and formed stable binding conformations. Conclusions. Gastrodin might exert an anti-ADHD effect by upgrading the dopaminergic system and central cholinergic system, inhibiting the inflammatory response and GIRK channel, and exerting a synergistic effect with other drugs on ADHD. For this reason, gastrodin should be considered a multitarget drug for ADHD treatment.
Global Trends in Research of NF-κB in Melanoma from 2000 to 2021: A Study of Bibliometric Analysis
Authors: Wang Jun , Liao Xuan , Jiang Xiao , Liu Hongwei
Published: September 2022

In the pathogenesis of melanoma, NF-κB is a key signaling pathway. Appling bibliometric analysis, we identify the frontiers and hotspots about NF-κB in melanoma, as well as distinguishing features of scientific research and output all over the world during the past 22 years. 2226 publications published from 2000 to 2021 and related information were retrieved based on Science Citation Index Expanded (SCI-expanded) of Web of Science Core Collection (WoSCC). VOSviewer and Citespace were used to analyze bibliometric indicators and visualize the hotspots and research trend of studies on NF-κB in melanoma. The results indicated that despite fluctuations, the number of publications (Np) related to the research of NF-κB in melanoma per year increased over the past 22 years. The USA had the most publications. H-index and the number of citations (Nc) of the USA were also in the first place. PloS One was the most productive journal, and League of European Research Universities (LERU) was the most productive affiliation. Recently, the keywords “NF-kappa-b,” “melanoma,” “apoptosis,” “expression,” “activation,” “cancer,” and “metastasis” appeared most frequently. Our study suggested that articles associated with NF-κB in melanoma tend to increase. In this field, the USA was an influential country and a big producer. Most publications focused on clinical and basic research in the past 22 years, and keywords “tumor necrosis factor” and “trail induced apoptosis” had the highest burst strength.
Development and Comprehensive Evaluation of Ecological Agriculture Industry Chain System Based on Genetic Algorithm
Authors: Jia Peiyao , Chu Jiankun , Niu Wenjia , Jia Puyao , Zhang Ling
Published: September 2022

Due to the constraints of traditional agricultural development factors, the existing agricultural industrial chain structure was unreasonable, which can not only promote the development of related industries but also affect the sustainable development of the whole agriculture. Therefore, it was of great significance to build a scientific and orderly ecological agriculture industry chain system and optimize it on the existing basis for improving the industrial benefits of modern agriculture and enhancing the vitality of agricultural development. From the perspective of the construction of an ecological agriculture industry chain system, this study put forward the development and evaluation system of the agricultural industry chain system based on genetic algorithm, in order to provide support for better promoting the development of modern agriculture. First, based on summarizing the related concepts of ecological agriculture and industrial structure, the definition and organization of agricultural industrial chain were given. Second, it expounded the basic theory of genetic algorithm and its application in the optimization of agricultural industrial structure, and put forward the optimization model of ecological agricultural industrial structure combined with the objectives of agricultural industry development. Finally, by constructing the evaluation index system of ecological agriculture industry chain system, a comprehensive evaluation model of ecological agriculture industry chain system based on genetic algorithm was designed. Through the case verification and comparative analysis, the results showed that the ecological agriculture industry chain system evaluation system and evaluation model based on genetic algorithm proposed in this study had certain feasibility and effectiveness, and can better evaluate the changing trend of various industries in the process of agricultural industry development.
The Influence of Different Modes of Exercise on Healthy and Injured Tendons
Authors: Wang Kaiyong , Zhao Linlin
Published: September 2022

Tendons are essential components of the musculoskeletal system that links the skeletal muscle to the skeleton. This dense connective tissue exhibits great plasticity. Therefore, research on the influence of types of exercise, including acute and long-term training, on the structural and mechanical properties of tendons in athletic and sedentary populations is of critical importance in the design of scientific-based exercise plans and effective tendinopathy treatment. Here, we review recent studies on the relationship between exercise and tendon health and tendinopathy repair to provide a general understanding of how exercise may reshape tendons.
Key Technologies of Software Engineering Based on T-ACO Algorithm
Authors: Lu Litao
Published: September 2022

The main core of software engineering key technologies is the development of software services, ensuring the scientificity, security, and stability of the application software engineering system. At present, China’s economic development urgently needs the support of software engineering technology. Based on the T-ACO algorithm, the scientificity of software engineering and the accuracy of data have been significantly improved compared with traditional software engineering technology. It plays an important role in promoting the follow-up software engineering technology. In order to effectively analyze the key technology of engineering software, an improved ant colony algorithm based on T distribution is proposed in this paper. Because the basic ant colony algorithm is easy to fall into the local optimum and the optimization accuracy is low, in the optimization process, at the beginning of the pheromone update, the introduction of the T distribution is helpful for the basic ant colony algorithm to make up for its shortcomings. Adding pheromone variables to the basic ant colony algorithm improves the diversity of the ant colony, thereby eliminating the limitations of local optimal solutions. At the same time, the T-ACO algorithm also improves the search accuracy and convergence speed of automatic data generation in software engineering. In this paper, the performance of the T-ACO algorithm is simulated by experiments. Experimental analysis shows that when the population size is small, the T-ACO algorithm may sometimes not converge to the optimal solution, but when the population size is large (≥50), the T-ACO algorithm may converge to the optimal solution. It can realize the coverage of the total path by the output test case set. While the other two algorithms can achieve full path coverage, they are not stable, resulting in an average coverage between 90% and 100%. The T-ACO algorithm not only has good accuracy in creating test case sets, but also has good algorithm performance, and it is suitable as a multipath test case creation algorithm.
A Scalable Blockchain Framework for ELA Assessment
Authors: Tian Chunxia
Published: September 2022

As a popular technology in the information age, blockchain is having a profound impact on various industries, including the field of education. Blockchain technology can accelerate the modernization of education in China, adapt to the new situation of epidemic prevention and control needs, and promote the renewal of the management and training modes of college students. Blockchain technology is decentralized, tamper-proof, traceable, trackable, open and transparent, which is conducive to the realization of individual student-centered teaching and learning, as well as an open, and transparent teaching process, which can motivate the learning motivation of English majors and improve the effectiveness of the student management and training models. To address the problem of low accuracy of the traditional English proficiency classification methods, this article aims to explore the application of blockchain technology in the management and training model of English majors and its feasibility. We propose a proficiency evaluation model based on a Discrete Hopfield Neural Network (DHNN). Firstly, the hierarchical analysis method is used to construct the evaluation index system of students’ English ability, and then the ability classification indexes are divided into 5 levels.The network achieves the classification of students’ English proficiency through the associative memory of the classification criteria, and the classification results are compared with those of the BPNN model. The simulation results show that the classification accuracy of the BPNN model is 80.0% and that of the DHNN model is 100.0%. The DHNN model has improved the classification accuracy and generalization ability, and the model establishment process is simple and the results are intuitive, which verifies the effectiveness of the proposed model
[Retracted] Construction of a Basic Japanese Teaching Resource Base Based on a Deep Neural Network under a Big Data Environment
Authors: Wang Yue , Ma Jianhua , Zhang Tong
Published: September 2022

A challenge for education and teaching in universities is posed by “Internet plus,” which has made numerous educational resources at universities richer and more accessible. The development of a professional Japanese teaching resource base should be centered on the needs and characteristics of Japanese teaching in universities, as well as establish and enhance the mechanism for resource base construction. All forms of instructional resources should also continuously be updated and improved in order to realize the diversified, systematic, open, and long‐term development of Japanese instructional resources. In light of the current state of the information technology industry’s rapid expansion, this essay examines a few issues with the building of a Japanese teaching resource database. A fundamental Japanese teaching resource database built on DNN was created as a result. The CNN technology is used in this study to create the Arduino device identification application. Utilizing gadgets in the learning process, learners can obtain learning resources using the Arduino device identification program before engaging in learning activities. The experimental findings also demonstrate that the precision rate and recall rate of the Japanese teaching resource database system developed in this study may achieve about 93 and 94 percent, respectively. Its performance is better than the conventional teaching resource system, and it can offer top‐notch teaching resources for teaching fundamental Japanese.
Frost Heaving Properties of Gravelly Soils in Alpine Seasonally Frozen Regions
Authors: Chen Cheng , Zhang Zhigang , Ling Li , He Baoyuan , Jiang Yanjia , Cheng Zhihe
Published: September 2022

To investigate the frost heaving properties of gravelly soil in alpine seasonally frozen regions and provide a foundation for the antifrost heaving design of the foundation tower in the Manzhouli 500 kV electrical transmission line. First, particle analysis and compaction tests were used to assess the basic characteristics of gravelly soil. Then, to investigate, a unidirectional freezing test of graded sand was performed to analyze the regularity and properties of the frozen process of graded sand. The test results demonstrate that the temperature gradient and the number of freeze-thaw cycles considerably affect the freezing of graded sand. The greater the temperature gradient and the number of freeze-thaw cycles, the greater the frost heave. In the freezing process, graded sand with zero fine-grain content exhibits obvious freezing shrinkage and thawing settlement. Still, the frost heave of sand is small. The frozen damage of graded sand is not caused by frost heaving deformation but by the deterioration of soil structure and the decrease of bearing capacity under hydrothermal coupling. Finally, experimental research is used to propose prevention and control measures for frost heave of power transmission and transformation projects.