bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial X-ray detection system based on simultaneous communication and radar
Authors: Ma Weihong , Li Yao , Sheng Lizhi , Su Tong , Zhang Yingjun , Liu Jiani , Xia Fangyuan , Tan Zhenkun , Zhang Furui , Chen Rui
Published: November 2021

An integrated scheme of X-ray communication and detection is proposed in this paper, which is used for the detection of the unknown target inside the coating while communication. In contrast to the X-ray communication methods reported previously, simultaneous communication and radar detection have two distinct features. One is that both communication and detection signals share the same X-ray source and channel, so the spatial resources can be effectively utilized. The other is that X-ray can penetrate the metal shielding structure and detect the internal materials effectively. In order to achieve the above goals, the propagation feasibility of an X-ray signal in space and space sparse plasma environment are first analyzed. Simulation and experiment results indicate that the X-ray carrier can realize transmission without attenuation in space environment. Then, an X-ray radar and communication demonstration system is built to verify the detection ability of coated materials. Experimental results show that when the characteristic spectrum value of the unknown target is much higher than that of the rest shell, the spatial X-ray radar system can achieve more accurate discrimination. Finally, a conclusion is reached, and some feasible detection suggestions are provided for this simultaneous detection and communication system.
Impact of melting heat transfer in the bioconvective Casson nanofluid flow past a stretching cylinder with entropy generation minimization analysis
Authors: Liu Chunyan , Akhter Hafeez , Ramzan Muhammad , Alaoui Mohammed Kbiri
Published: November 2021

The nanofluids’ job is fundamental in the cooling of miniature electronic gadgets including microchips and associated gizmos. Having such interesting and useful applications of nanofluids in mind our objective is to deliberate the melting heat transfer impact in the flow of a Casson nanofluid past a stretched cylinder in a spongy medium. The stability of the nanoparticles is ascertained by considering the impact of the gyrotactic microorganisms. The entropy generation minimization analysis is also part of this study. A bvp4c built-in function of the MATLAB software is engaged to find the solution of the system of a nonlinear system of equations numerically. The consequences of the primary parameters versus emerging profiles are depicted and conversed in the view of their physical importance. The melting heat transfer parameter poses an opposing trend against the fluid velocity and temperature. Further, the gyrotactic microorganism distribution is lowered for the Peclet number. The entropy generation is enhanced for the sizeable estimates of the Reynolds and Brinkman numbers.
Hierarchy for groups acting on hyperbolic ℤn-spaces
Authors: Grecianu Andrei-Paul , Myasnikov Alexei , Serbin Denis
Published: November 2021

In [A.-P. Grecianu, A. Kvaschuk, A. G. Myasnikov and D. Serbin, Groups acting on hyperbolic [Formula: see text]-metric spaces, Int. J. Algebra Comput. 25(6) (2015) 977–1042], the authors initiated a systematic study of hyperbolic [Formula: see text]-metric spaces, where [Formula: see text] is an ordered abelian group, and groups acting on such spaces. The present paper concentrates on the case [Formula: see text] taken with the right lexicographic order and studies the structure of finitely generated groups acting on hyperbolic [Formula: see text]-metric spaces. Under certain constraints, the structure of such groups is described in terms of a hierarchy (see [D. T. Wise, The Structure of Groups with a Quasiconvex Hierarchy[Formula: see text] [Formula: see text]AMS-[Formula: see text], Annals of Mathematics Studies (Princeton University Press, 2021)]) similar to the one established for [Formula: see text]-free groups in [O. Kharlampovich, A. G. Myasnikov, V. N. Remeslennikov and D. Serbin, Groups with free regular length functions in [Formula: see text], Trans. Amer. Math. Soc. 364 (2012) 2847–2882].
Curing with Hemlock: Escaping the swampland using instabilities from string theory
Authors: Banerjee Souvik , Danielsson Ulf , Giri Suvendu
Published: November 2021

In this essay, we will take a wonderful ride on a dark bubble with strings attached, which carries our universe out of the swampland and makes it realizable in the landscape of string theory. To find the way to the landscape, we make use of apparently hostile corners of the swampland and their instabilities.
IMPACT OF FRACTALS EMERGING FROM THE FITNESS ACTIVITIES ON THE RETAIL OF SMART WEARABLE DEVICES
Authors: WANG FUZHANG , SOHAIL AYESHA , TANG QIWEI , LI ZHIWU
Published: November 2021

The smart wearable devices that can track the fitness activities are getting famous these days due to their easy-to-use features. The fitness trackers can work for an individual in a promising manner, provided that the user is well familiar with the device and is committed with the timelines. Several reports have provided evidence that these smart wearable devices have not showed promising results and in most of the cases, people have stopped using them, few weeks after the purchase. There are several reasons linked with this response. During this research, we have worked on the correlations of weight loss via smart device with the age, gender, body mass index (BMI) and ideal body weight (IBW), with the aid of gradient boosted decision trees (XGBoost) and support vector machine (SVM) learning tools. XGBoost and SVM are capable of dealing with complex datasets, with higher frequencies, and for data emerging from multiple sources. These machine learning tools use kernel functions for the clustering and other classification measures, and are thus better as compared to the logistic methods. Next, the time series forecasting tools are discussed with the Bayesian hyperparametric optimization. The time series of the weight loss monitoring of each individual, depicted in this manner, provided complex fractal patterns, with reduction in amplitude, with the passage of time.
KINETICS STUDY AND MECHANISM OF ELECTROPHORETIC DEPOSITION: A NEW INSIGHT BY SIGNAL/NOISE ANALYSIS
Authors: SHAKERI MOHAMMAD SADEGH
Published: November 2021

Kinetics of electrophoretic deposition (EPD) has been thoroughly investigated using equivalent circuit modeling in this paper. The aim of this work is the better understanding of the EPD mechanism. In this case, mass deposition in EPD was modeled as charging of the reservoir in an RC circuit. Accordingly, the weight–time ([Formula: see text]–[Formula: see text]) curves of EPD were regarded equivalent to the [Formula: see text]–[Formula: see text] curves of a reservoir. It was found out that the rate of deposition depends not only on the specific resistivity but also on the permittivity of the suspension. Furthermore, the mechanism of EPD was studied using large- and small-signal analyses conducted by the Simulink modeling toolbox of MATLAB software. In this case, the frequency of sinusoidal waves was equivalent to the probability of collision of particles. Results show that there is an alternative sinusoidal-like noise on the main signal of [Formula: see text]–[Formula: see text] curves. It predicts that charged particles move toward the opposite electrode during the EPD process and accumulate next to the electrode for losing their ionic power. Ultimately, the accumulated particles (including several particles not owing ionic power) depose on the electrode at once. The time which is needed for particles to decrease their ionic power is a delay (relaxation) time of the deposition process.
A Thermal Blended Facial Expression Analysis and Recognition System Using Deformed Thermal Facial Areas
Authors: Saha Priya , Bhattacharjee Debotosh , De Barin Kumar , Nasipuri Mita
Published: November 2021

There are many research works in visible as well as thermal facial expression analysis and recognition. Several facial expression databases have been designed in both modalities. However, little attention has been given for analyzing blended facial expressions in the thermal infrared spectrum. In this paper, we have introduced a Visual-Thermal Blended Facial Expression Database (VTBE) that contains visual and thermal face images with both basic and blended facial expressions. The database contains 12 posed blended facial expressions and spontaneous six basic facial expressions in both modalities. In this paper, we have proposed Deformed Thermal Facial Area (DTFA) in thermal expressive face image and make an analysis to differentiate between basic and blended expressions using DTFA. Here, the fusion of DTFA and Deformed Visual Facial Area (DVFA) has been proposed combining the features of both modalities and experiments and has been conducted on this new database. However, to show the effectiveness of our proposed approach, we have compared our method with state-of-the-art methods using USTC-NVIE database. Experiment results reveal that our approach is superior to state-of-the-art methods.
On the Galois symmetries for the character table of an integral fusion category
Authors: Burciu Sebastian
Published: November 2021

In this paper, we show that integral fusion categories with rational structure constants admit a natural group of symmetries given by the Galois group of their character tables. Based on these symmetries, we generalize a well-known result of Burnside from representation theory of finite groups. More precisely, we show that any row corresponding to a non-invertible object in the character table of a weakly integral fusion category contains a zero entry.
On classical 2-prime subsemimodules
Authors: Nikmehr M. J. , Nikandish R. , Yassine A.
Published: November 2021

In this paper, we introduce the notion of classical 2-prime subsemimodules of a semimodule M over a commutative semiring S with identity, which is a generalization of classical prime subsemimodules. A proper subsemimodule N of M having the property that for each [Formula: see text] and each subsemimodule K of M, the inclusion [Formula: see text] implies [Formula: see text] or [Formula: see text] is called classical 2-prime. We give some results concerning classical 2-prime subsemimodules. Also, the classical 2-prime avoidance theorem for subsemimodules is proved. Finally, the notion of valuation semimodules is introduced and some results on classical 2-prime subsemimodules in valuation semimodules are given.
Input Quantity Decision and Coordination Mechanism with Two Production Chances and Yield Uncertainty
Authors: Cai Jianhu , Sun Haining , Li Xuejiao , Ergu Daji
Published: November 2021

Conducting a second production run can improve the company’s capability of meeting the market demand. Few works examine optimal input quantity decisions under the mode with two production chances considering demand and yield uncertainty. We propose a vendor-managed inventory (VMI) supply chain with one supplier and one retailer. The supplier has two production chances and faces yield uncertainty in each production run. It is necessary for the supplier to make trade-offs between the cost and benefit of the second production run, then decide whether to conduct the second production run. We investigate the supplier’s optimal input quantity decision in each production run and obtain the supply chain members’ expected profits. As a comparison, the mode with one production chance is also developed. We find that two production chances can help improve the performance of the supply chain under yield uncertainty. A revenue-sharing contract is introduced to coordinate the supply chain with two production chances, and efficient profit allocation is achieved through adjusting the revenue-sharing ratio and the wholesale price. An extension is conducted for a sensitivity analysis of unit punishment cost on the supplier’s input quantity decisions.
Learner performance prediction in the e-learning platform using the optimized deep long short-term memory classifier
Authors: Alzubi Ahmad
Published: November 2021

The e-learning platform gains significant attraction in the current scenario due to the outbreak of the epidemic COVID-19 as e-learning ensures the students continue their studies in the safest environment while maintaining the educational standard. The performance prediction is one of the significant tasks to be carried out in the e-learning platform to sort out the students who require immediate attention to enhance their grades before the final assessment. This paper proposes a prediction model that effectively predicts the learners’ performance in the e-khool learning management system (e-khool LMS) based on the proposed wolf-swarm optimization dependent Deep Long Short-term (wolf-swarm optimization-based Deep-LSTM) approach. The optimization algorithm tunes the optimal weights of the Deep-LSTM classifier, which inherits the hybrid characteristics of the traitors and particles. Initially, the learner data from the e-khool database is employed for classification based on the proposed wolf-swarm optimization dependent Deep-LSTM classifier. The effectiveness of the proposed prediction model is analyzed in terms of MSE and RMSE with the value of 5.93 and 2.426, respectively.
A general blow-up result for a degenerate hyperbolic inequality in an exterior domain
Authors: Jleli Mohamed , Kirane Mokhtar , Samet Bessem
Published: November 2021

In this paper, we consider a degenerate hyperbolic inequality in an exterior domain under three types of boundary conditions: Dirichlet-type, Neumann-type, and Robin-type boundary conditions. Using a unified approach, we show that all the considered problems have the same Fujita critical exponent. Moreover, we answer some open questions from the literature regarding the critical case.
The connectivity and Hamiltonian properties of second-order circuit graphs of wheel cycle matroids
Authors: Deng Zijian , Liu Bin , Huo Bofeng , Deng Bo
Published: November 2021

Let [Formula: see text] be the [Formula: see text]th-order circuit graph of a simple connected matroid M. The first-order circuit graph is also called a circuit graph. There are lots of results about connectivity and Hamiltonian properties of circuit graph of matroid, while there are few related results on the second-order circuit graph of a matroid. This paper mainly focuses on the connectivity and Hamiltonian properties of the second-order circuit graphs of the cycle matroid of wheels. It determines the minimum degree and connectivity of these graphs, and proves that the second-order circuit graph of the cycle matroid of a wheel is uniformly Hamiltonian.
Sampling-based approximate skyline calculation on big data
Authors: Xiao Xingxing , Li Jianzhong
Published: November 2021

Nowadays, big data is coming to the force in a lot of applications. Processing a skyline query on big data in more than linear time is by far too expensive and often even linear time may be too slow. It is obviously not possible to compute an exact solution to a skyline query in sublinear time, since an exact solution may itself have linear size. Fortunately, in many situations, a fast approximate solution is more useful than a slower exact solution. This paper proposes two sampling-based approximate algorithms for processing skyline queries. The first algorithm obtains a fixed size sample and computes the approximate skyline on it. The error of the algorithm is not only relatively small in most cases, but also is almost unaffected by the input size. The second algorithm returns an [Formula: see text]-approximation for the exact skyline efficiently. The running time of the algorithm has nothing to do with the input size in practical, achieving the goal of sublinearity on big data. Experiments verify the error analysis of the first algorithm, and show that the second is much faster than the existing skyline algorithms.
A refinement of Dyck paths: A combinatorial approach
Authors: Flórez Rigoberto , Ramírez José L. , Velandia Fabio A. , Villamizar Diego
Published: November 2021

Local maxima and minima of a Dyck path are called peaks and valleys, respectively. A Dyck path is called restricted [Formula: see text]-Dyck if the difference between any two consecutive valleys is at least [Formula: see text] (right-hand side minus left-hand side) or if it has at most one valley. In this paper, we use several techniques to enumerate some statistics over this new family of lattice paths. For instance, we use the symbolic method, the Chomsky–Schűtzenberger methodology, Zeilberger’s creative telescoping method, recurrence relations, and bijective relations. We count, for example, the number of paths of length [Formula: see text], the number of peaks, the number of valleys, the number of peaks of a fixed height, and the area under the paths. We also give a bijection between the restricted [Formula: see text]-Dyck paths and a family of binary words.
SUBSTITUTABILITY BETWEEN GOVERNMENT AND PRIVATE CONSUMPTION IN SUB-SAHARAN AFRICA
Authors: NKANSA ASANTE GRACE , AMANKWAH GIDEON , BRUCE NYARKOH GODWILL , TAWIAH BAIDOO SAMUEL
Published: November 2021

The question of whether private and public consumption are complements or substitutes has been an issue of concern and hence, attracted the attention of researchers and policy think tanks. This study therefore investigates this important phenomenon within the context of sub-Saharan Africa (SSA) to inform the design of fiscal policy measures. Using panel data spanning the period 1981–2016 for 21 sub-Saharan African countries, the results indicate that, government and private consumption are substitutes. This indicates that government spending crowds out private consumption in the sub region. Vital policy implications have been provided for consideration based on the findings.
Synergies Between COVID-19 and Climate Change Impacts and Responses
Authors: Pelling Mark , Kerr Rachel Bezner , Biesbroek Robert , Caretta Martina Angela , Cissé Guéladio , Costello Mark John , Ebi Kristie L. , Gunn Elena Lopez , Parmesan Camille , Schuster-Wallace Corinne J. , Tirado Maria Cristina , van Aalst Maarten , Woodward Alistair
Published: November 2021

The COVID-19 pandemic and anthropogenic climate change are global crises. We show how strongly these crises are connected, including the underlying societal inequities and problems of poverty, substandard housing, and infrastructure including clean water supplies. The origins of all these crises are related to modern consumptive industrialisation, including burning of fossil fuels, increasing human population density, and replacement of natural with human dominated ecosystems. Because business as usual is unsustainable on all three fronts, transformative responses are needed. We review the literature on risk management interventions, implications for COVID-19, for climate change risk and for equity associated with biodiversity, water and WaSH, health systems, food systems, urbanization and governance. This paper details the considerable evidence base of observed synergies between actions to reduce pandemic and climate change risks while enhancing social justice and biodiversity conservation. It also highlights constraints imposed by governance that can impede deployment of synergistic solutions. In contrast to the response to the COVID-19 pandemic, governance systems have procrastinated on addressing climate change and biodiversity loss as these are interconnected chronic crises. It is now time to address all three to avoid a multiplication of future crises across health, food, water, nature, and climate systems.
Advances in Heavy Metal Bioremediation: An Overview
Authors: Sayqal Ali , Ahmed Omar B.
Published: November 2021

The pollution of toxic heavy metals is considered one of the most important environmental issues which has accelerated dramatically due to changing industrial activities. This review focuses on the most common methods, strategies, and biological approaches of heavy metal bioremediation. Also, it provides a general overview of the role of microorganisms in the bioremediation of heavy metals in polluted environments. Advanced methods of heavy metal remediation include physicochemical and biological methods; the latter can be further classified into in situ and ex situ bioremediation. The in situ process includes bioventing, biosparging, biostimulation, bioaugmentation, and phytoremediation. Ex situ bioremediation includes land farming, composting, biopiles, and bioreactors. Bioremediation uses naturally occurring microorganisms such as Pseudomonas, Sphingomonas, Rhodococcus, Alcaligenes, and Mycobacterium. Generally, bioremediation is of very less effort, less labor intensive, cheap, ecofriendly, sustainable, and relatively easy to implement. Most of the disadvantages of bioremediation relate to the slowness and time-consumption; furthermore, the products of biodegradation sometimes become more toxic than the original compound. The performance evaluation of bioremediation might be difficult as it has no acceptable endpoint. There is a need for further studies to develop bioremediation technologies in order to find more biological solutions for bioremediation of heavy metal contamination from different environmental systems.
A Knowledge Graph System for the Maintenance of Coal Mine Equipment
Authors: Zhang Guozhen , Cao Xiangang , Zhang Mengyuan
Published: November 2021

With the rapid development of coal mine intelligent technology, the complexity of coal mine equipment has been continuously improved and the equipment maintenance resources have been continuously enriched. The traditional coal mine equipment maintenance knowledge management technology can no longer meet the current needs of equipment maintenance knowledge management, and the problems of low utilization rate, poor interoperability, and serious loss of knowledge have gradually emerged. It is urgent to study new knowledge system construction and knowledge management application technology for large-scale coal mine equipment maintenance resources. Knowledge graph is a technical method to describe the relationship between things in the objective world by using a graph model. It can effectively solve the problem of knowledge dynamic mining and management under large-scale data. Therefore, this paper focuses on the establishment of a coal mine equipment maintenance knowledge graph system by using knowledge graph technology. The main research contents are as follows: Firstly, based on the current situation that there is no unified basic knowledge system in the field of coal mine equipment maintenance, this paper establishes the coal mine equipment maintenance ontology (CMEMO) to effectively solve the problem that there are no unified representation, integration, and sharing of coal mine equipment maintenance knowledge in this field and provide support for the construction of coal mine equipment maintenance knowledge graph. Then, aiming at the problem that the traditional named-entity recognition method has a poor recognition effect and relies too much on artificial feature design, this paper proposes a named-entity recognition model for coal mine equipment maintenance based on neural network (BERT-BiLSTM-CRF) and applies the model to the coal mine equipment maintenance data set for verification. The experimental results show that, under the same data set, the entity recognition effect of this model is more leading than that of other models. Finally, through demand analysis and architecture design, combined with the constructed ontology model of coal mine equipment maintenance field, the entity identification of coal mine equipment maintenance is completed based on the BERT-BiLSTM-CRF model and the Django application framework is used to build the coal mine equipment maintenance knowledge graph system to realize the functions of each module of the knowledge graph system.
Evaluation and Image Analysis of Enterprise Human Resource Management Based on the Simulated Annealing‐Optimized BP Neural Network
Authors: Zhao Bo , Xu Yuanlin , Cheng Jun
Published: November 2021

With the continuous development of social economy and the intensification of social competition, human resource management plays a more and more important role in the whole resource system. How to give full play to the advantages of human resources has become the key issue of human resource management evaluation. However, the current human resource management evaluation system has some problems, such as poor timeliness, one‐sidedness, and subjectivity. Therefore, this paper proposes a BP image neural network optimized based on the simulated annealing algorithm to realize enterprise human resource management evaluation and image analysis. Through the learning of different time series samples, the average weight distribution scheme of main indicators is obtained, in which the average weight proportions of c1, c2, c3, and c4 are 25.5%, 24.8%, 17.9%, and 31.9%, respectively. In the comprehensive evaluation of enterprise employees, the error between the actual output and expected output is less than 4.5%. The results show that the BP image neural network based on simulated annealing algorithm has high accuracy in the image analysis and evaluation of enterprise human resource management. The output analysis results meet the actual needs of the enterprise and the personal development of employees and provide a decision‐making scheme for the evaluation of enterprise human resource management.
Deep‐Learning‐Based Approach for Iraqi and Malaysian Vehicle License Plate Recognition
Authors: Habeeb Dhuha , Noman Fuad , Alkahtani Ammar Ahmed , Alsariera Yazan A. , Alkawsi Gamal , Fazea Yousef , Al-jubari Ammar Mohammed
Published: November 2021

Recognizing vehicle plate numbers is a key step towards implementing the legislation on traffic and reducing the number of daily traffic accidents. Although machine learning has advanced considerably, the recognition of license plates remains an obstacle, particularly in countries whose plate numbers are written in different languages or blended with Latin alphabets. This paper introduces a recognition system for Arabic and Latin alphabet license plates using a deep‐learning‐based approach in conjugation with data collected from two specific countries: Iraq and Malaysia. The system under study is proposed to detect, segment, and recognize vehicle plate numbers. Moreover, Iraqi and Malaysian plates were used to compare these processes. A total of 404 Iraqi images and 681 Malaysian images were tested and used for the proposed techniques. The evaluation took place under various atmospheric environments, including fog, different contrasts, dirt, different colours, and distortion problems. The proposed approach showed an average recognition rate of 85.56% and 88.86% on Iraqi and Malaysian datasets, respectively. Thus, this evidences that the deep‐learning‐based method outperforms other state‐of‐the‐art methods as it can successfully detect plate numbers regardless of the deterioration level of image quality.
Ampelopsin Inhibits Cell Viability and Metastasis in Renal Cell Carcinoma by Negatively Regulating the PI3K/AKT Signaling Pathway
Authors: Zhao Zhonghe , Jiang Yan , Liu Zhongguo , Li Qingyan , Gao Tiantian , Zhang Shengxia
Published: November 2021

Background. Previous studies have shown that Ampelopsin has an inhibitory effect on human tumors. However, the effect of Ampelopsin on renal cell carcinoma (RCC) is rarely reported. Therefore, this study aims to explain the role of Ampelopsin in RCC. Methods. Different concentrations of Ampelopsin (0, 10, 25, 50, and 100 μM) were used to treat 786-O cells. Cell viability was detected by MTT assay, colony formation assay, and flow cytometry assay. Transwell assay and Wound healing assay were used to detect cell migration and invasion. Western blot analysis was applied to detect protein expression. Results. Ampelopsin inhibited cell proliferation and induced apoptosis in RCC. And Ampelopsin can inhibit cell migration and invasion in RCC. All these results changed in a dose-dependent manner. Ampelopsin (100 uM) had the strongest inhibitory effect on cell viability and metastasis. In addition, Ampelopsin negatively regulated the PI3K/AKT signaling pathway in RCC cells. Moreover, Ampelopsin was only cytotoxic to RCC cells. Conclusion. Ampelopsin inhibits cell viability and metastasis in RCC by negatively regulating the PI3K/AKT signaling pathway.
Secure Physical Layer Transmission and Authentication Mechanism Based on Compressed Sensing of Multiple Antenna Arrays
Authors: Zhang Xiaolong , Wu Wei , Zhou Bin
Published: November 2021

Large‐scale antenna technology has become one of the most promising technologies in 5G because of its ability to effectively improve the spectral efficiency and energy efficiency of the system, as well as its better robustness. In this paper, a large amount of CSI (channel state information) data is characterized by feature mining and law analysis, and a large number of channel characteristics of the physical layer have the advantages of randomness and uniqueness, etc. From the perspective of improving the security of the authentication mechanism and reducing the computational complexity of the authentication mechanism, the physical layer security authentication model is analyzed, and the signal security transmission path, signal authenticity, and channel estimation are used to propose an effective physical layer secure transmission and authentication mechanism, which can be used as a security enhancement and lightweight authentication mechanism for existing authentication mechanisms. In this paper, we analyze the security advantage mechanism of physical layer authentication and prove the security performance boundary; propose an authentication security enhancement method based on the channel feature generation key, a message authentication method based on superimposed tag signals; and propose a method based on private guide frequency for high‐speed service data authentication.
Application of Dual‐Channel Convolutional Neural Network Algorithm in Semantic Feature Analysis of English Text Big Data
Authors: Li Yang , Yin Chengbo
Published: November 2021

The current Internet data explosion is expecting an ever‐higher demand for text emotion analysis that greatly facilitates public opinion analysis and trend prediction, among others. Therefore, this paper proposes to use a dual‐channel convolutional neural network (DCNN) algorithm to analyze the semantic features of English text big data. Following the analysis of the effect of CNN, artificial neural network (ANN), and recurrent neural network (RNN) on English text data analysis, the more effective long short‐term memory (LSTM) and the gated recurrent unit (GRU) neural network (NN) are introduced, and each network is combined with the dual‐channel CNN, respectively, and comprehensively analyzed under comparative experiments. Second, the semantic features of English text big data are analyzed through the improved SO‐pointwise mutual information (SO‐PMI) algorithm. Finally, the ensemble dual‐channel CNN model is established. Under the comparative experiment, GRU NN has a better feature detection effect than LSTM NN, but the performance increase from dual‐channel CNN to GRU NN + dual‐channel CNN is not obvious. Under the comparative analysis of GRU NN + dual‐channel CNN model and LSTM NN + dual‐channel CNN model, GRU NN + dual‐channel CNN model ensures the high accuracy of semantic feature analysis and improves the analysis speed of the model. Further, after the attention mechanism is added to the GRU NN + dual‐channel CNN model, the accuracy of semantic feature analysis of the model is improved by nearly 1.3%. Therefore, the ensemble model of GRU NN + dual‐channel CNN + attention mechanism is more suitable for semantic feature analysis of English text big data. The results will help the e‐commerce platform to analyze the evaluation language and semantic features for the current network English short texts.
Light Source Layout Optimization Strategy Based on Improved Artificial Bee Colony Algorithm
Authors: Li Bo , Wang Jue , Gao Zijun , Gao Ning
Published: November 2021

In order to optimize the indoor lighting effect and reduce the energy consumption of indoor lighting, the light source layout of conventional rooms and special rooms is studied in this paper. Firstly, the indoor space lighting model is analyzed, and the expressions of light source output and illumination on the target plane are derived. Secondly, in order to improve the search ability of the algorithm in specific areas, combined with the artificial bee colony algorithm, an improved artificial bee colony algorithm suitable for indoor lighting optimization is proposed. Using the average square difference of the illuminance of the target plane as the adaptation function, a penalty function is introduced, and the minimum circle surrounding strategy is used to search the specific location of the light source. Finally, the obtained layout is fitted by engineering standardization, and the indoor light source layout is obtained. Through the simulation of illuminance effect in conventional room and irregular room, it is proved that the proposed method can effectively improve the lighting effect and reduce the energy consumption of indoor lighting under the same number of light sources and the same illuminance index.
Optimization of the Plastic Area of a Borehole Based on the Gas Extraction Effect and Its Engineering Application
Authors: Wu Kuan , Shi Shiliang , Lu Yi , Li He , Li Min
Published: November 2021

Gas extraction is most commonly used to control gas disasters in coal mines. The distribution of the plastic zone around a borehole and the sealing quality are key factors affecting gas extraction. In this paper, the plastic zone was simulated by COMSOL, and a theoretical equation of the plastic zone radius was derived. In addition, an antispray hole equipment and the “two plugging and one injection” sealing technology were proposed. The results show that a larger borehole pore size corresponds to a larger plastic zone and larger range of pressure relief of the borehole. The error between the calculated and simulated plastic zone radii is within 1%, and the modified equation is applicable to Puxi mine. The loss and harm caused by borehole spraying are reduced by applying antispray hole equipment. By applying the “two plugging and one injection” sealing technology and phosphogypsum-based self-produced gas expansion paste material to block the borehole, the sealing quality is improved and an accurate gas mixing flow, pure flow, and concentration were obtained. As the plastic zone enlarges, the gas extraction flow gradually increases with, but the relative variation of flow first increases and subsequently decreases. Considering the safety and economy of construction, the optimal radius of the plastic zone is 64.9 mm.
[Retracted] Obesity Mass Monitoring in Medical Big Data Based on High‐Order Simulated Annealing Neural Network Algorithm
Authors: Ren Lijian , Wu Xiaoyu , Zhao Kaiqing
Published: November 2021

With the rapid development of information technology, hospital informatization has become the general trend. In this context, disease monitoring based on medical big data has been proposed and has aroused widespread concern. In order to overcome the shortcomings of the BP neural network, such as slow convergence speed and easy to fall into local extremum, simulated annealing algorithm is used to optimize the BP neural network and high‐order simulated annealing neural network algorithm is constructed. After screening the potential target indicators using the random forest algorithm, based on medical big data, the experiment uses high‐order simulated annealing neural network algorithm to establish the obesity monitoring model to realize obesity monitoring and prevention. The results show that the training times of the SA‐BP neural network are 1480 times lower than those of the BP neural network, and the mean square error of the SA‐BP neural network is 3.43 times lower than that of the BP neural network. The MAE of the SA‐BP neural network is 1.81 times lower than that of the BP neural network, and the average output error of the obesity monitoring model is about 2.35 at each temperature. After training, the average accuracy of the obesity monitoring model was 98.7%. The above results show that the obesity monitoring model based on medical big data can effectively complete the monitoring of obesity and has a certain contribution to the diagnosis, treatment, and early warning of obesity.
Resection of Recurrent Pancreatic Cancer: Who Can Benefit?
Authors: Nienhüser Henrik , Büchler Markus W. , Schneider Martin
Published: November 2021

Background: Recurrence after resection of pancreatic cancer occurs in up to 80% of patients in the first 2 years after complete resection. While most patients are not eligible for surgical treatment due to disseminated disease, a certain group of patients can be evaluated for re-resection of local recurrence. This review summarizes the current literature on surgical treatment of recurrent pancreatic cancer and potential prognostic factors. Summary: Re-resection of recurrent pancreatic cancer provides a significant survival benefit to selected patients with acceptable procedure-related mortality. Median overall survival after re-resection of recurrent pancreatic cancer is up to 28 months. The most relevant clinical parameters associated with a prognostic benefit are young patient age (<65 years), time to initial resection (>10 months), and preoperative chemotherapy before re-resection. Molecular markers are currently under investigation and might help to improve patient selection in the future. Key Message: Re-resection of recurrent pancreatic cancer is safe and feasible in experienced hands. Selected patients benefit from surgical treatment, but future studies are needed to identify reliable prognostic markers predicting survival.
Modeling the Ventral and Dorsal Cortical Visual Pathways Using Artificial Neural Networks
Authors: Han Zhixian , Sereno Anne
Published: November 2021

Although in conventional models of cortical processing, object recognition and spatial properties are processed separately in ventral and dorsal cortical visual pathways respectively, some recent studies have shown that representations associated with both objects' identity (of shape) and space are present in both visual pathways. However, it is still unclear whether the presence of identity and spatial properties in both pathways have functional roles. In our study, we have tried to answer this question through computational modeling. Our simulation results show that both a model ventral and dorsal pathway, separately trained to do object and spatial recognition, respectively, each actively retained information about both identity and space. In addition, we show that these networks retained different amounts and kinds of identity and spatial information. As a result, our modeling suggests that two separate cortical visual pathways for identity and space (1) actively retain information about both identity and space (2) retain information about identity and space differently and (3) that this differently retained information about identity and space in the two pathways may be necessary to accurately and optimally recognize and localize objects. Further, modeling results suggests these findings are robust and do not strongly depend on the specific structures of the neural networks.
Black Lives and Asian Medicine
Authors: Wu Yi-Li
Published: November 2021

This essay examines the intersections between Asian medicines, racial healthcare inequities, and social justice movements, and explains how they are illuminated by the interviews and essays in this special issue. Important themes include: how the protests following the murder of George Floyd in May 2020 spurred US organizations of alternative, complementary, and integrative medicine to undertake antiracist initiatives; how acupuncturists have been working to properly acknowledge the contributions of African American practitioners in their historical narratives; and how acupuncture may be a useful tool for mitigating racial health disparities.
Acupuncture, the Black Panther Party, and People’s Medicine
Authors: Burton-Rose Daniel , Wu Yi-Li
Published: November 2021

Tolbert Small (b. 1943) is a physician and civil rights activist best known for his advocacy for research on sickle cell anemia. In the summer of 2020 two of Asian Medicine’s editors, Daniel Burton-Rose and Yi-Li Wu, interviewed Small about his clinical career of more than fifty years. The interview focuses on Small’s experience with acupuncture, the practice of Chinese medicine in the United States, and his commitment to social justice. Small was introduced to acupuncture in 1972 as a member of a delegation of the Black Panther Party to the People’s Republic of China, and he incorporated it into his clinical practice upon his return to Oakland, California. Small began practicing acupuncture at a time when instructional materials and therapeutic implements were difficult to obtain. He witnessed the gradual mainstreaming of Chinese medicine in the United States, accompanied by problems of differential access based on race and income.
Fighting Medical Racism with Education and Action
Authors: Wu Yi-Li , Tyson Denise
Published: November 2021

Denise Tyson is the president of the Maryland Acupuncture Society (US), one of the state-level professional organizations that comprises the American Society of Acupuncturists. Following the police murder of George Floyd on May 25, 2020, she called on her colleagues in the acupuncture profession to take meaningful action against racism and to educate themselves about the long history of racist violence against African Americans. In July 2020 an editor of Asian Medicine interviewed Tyson to learn about her medical career and her perspectives on race and health care. The main themes of the interview include: her affinity for acupuncture and Chinese medicine, her experiences with racial bias in both biomedicine and integrative medicine, strategies for making acupuncture organizations more inclusive, and the crucial role that education plays in combating racism.
The Implications of Economic Change in Indonesia for Social Class Formation
Authors: Booth Anne
Published: November 2021

This article investigates the relationship between economic growth and changing class structures in Indonesia over the last century, with particular emphasis on the post-independence decades. Investigations carried out in the colonial era found that access to land and to government employment were crucial determinants of both income and social status. After 1950, these factors continued to be important, but in addition some studies also examined the growth of the private sector outside agriculture and its implications for changing social stratification among indigenous Indonesians. In recent times, contributions to the literature on the middle class have been made by international agencies (such as the Asian Development Bank and the World Bank). These studies have defined the middle class in terms of household income or expenditures and have argued that the middle class in Indonesia is growing and is now larger than the number of people living in poverty. The implications of this for future government policies are discussed.
Ethnic ‘Ferociousness’ in Colonial Wars
Authors: Oostindie Gert , Steijlen Fridus
Published: November 2021

This article explores the myths and evidence surrounding extreme violence and the framing of ‘ethnic soldiers’ as loyal and indispensable Moluccan soldiers in the Dutch army in the Indonesian War of Independence, 1945–1949. In this article, we first interrogate the origins of this framing in the Dutch–Indonesian case and the type of sources underlying this perspective. Next, we present the results of our research, which combines a study of Dutch veterans’ ego documents and oral-history projects. Based on this analysis, we reconsider both the framing and the evidence, after which we conclude with some comparative observations on ‘ethnic soldiers’ and the sources and perspectives underlying the ambivalent, but increasingly critical, framing of these men. Our methodology includes the use of digital-humanities techniques.
Dual Language Instruction: Teaching Civics in Three Public Primary Schools in Tanzania
Authors: Upor Rose A. , Mihayo Maziku
Published: November 2021

It is a widely shared hypothesis in Tanzania among educators and the general public that low academic achievement scores are typically due to pupils’ deficiencies in English comprehension. Although in most public primary schools kiSwahili is the language of instruction, while a select few use English, there is evidence showing that even where monolingual instruction is on offer in Tanzania, lessons are held most of the time in both languages concurrently. Much of the research into dual language instruction is driven by the question of whether using English as the language of instruction is superior to using another language, leaving open the question of whether learning in both kiSwahili and English concurrently delivers a better pedagogical result than classroom usage of either language in isolation from the other. In this study, experimenting with the use of Dual Language Instruction (DLI) in three public primary schools indicates that when students are taught in two languages they perform better on tests than those who receive the same lesson content through monolingual instruction.
Lugha ya Kiswahili na Ukombozi wa Kifikra katika Afrika: Mkabala wa Kimapinduzi wa Frantz Fanon
Authors: Mutembei Aldin
Published: November 2021

Ikisiri

Uchaguzi wa mtu kuitumia lugha yake kama njia ya ukombozi huanza na uamuzi wa kifikra. Uamuzi huo wa kifikra ni hatua ya ukombozi. Ni uamuzi ambao hatimaye humpa mtumiaji wa lugha mamlaka ya kuchukua hatua zaidi za kujitegemea. Ni ukombozi wa kiisimu ambao, hatimaye humpatia mtumiaji wa lugha nguvu binafsi. Lugha ni mamlaka; na wakati mwingi mamlaka huzaa nguvu. Ingawa hapa ‘nguvu’ inamaanisha uwezo wa mtu binafsi; na ‘mamlaka’ ni dhana ya kisheria, lakini dhana hizi mbili zinahusiana katika uchambuzi huu wa kujenga uwezeshaji kupitia matumizi ya lugha. Katika kuchunguza mawazo ya Frantz Fanon kuhusu dhana ya ukombozi wa fikra kwa Waafrika kama inavyojitokeza kupitia Lugha ya Kiswahili, nadharia ya Bobby Wright ya fikraufu inatoa nafasi kuangalia namna utambulisho wa watu unavyoweza kubomolewa kupitia matumizi ya lugha isiyokuwa ya asili kwao.
Stylistic Analysis of Selected Sermons Delivered by Pentecostal Preachers
Authors: Goodness Devet
Published: November 2021

The language style of three Pentecostal sermons reveals figures of speech that not only carry artistic and rhetorical ingenuity but also enhance the effectiveness of the sermons’ impact on a congregation of believers. Pentecostal sermons make extensive use of the second singular personal pronoun ‘you’ to warn, rebuke, remind, and to command. These sermons engage both literal and metaphorical speech acts. To understand the Christian message conveyed in a sermon, factors including image schemas, the choice of pronoun and the speaker’s ecclesiastic knowledge should be addressed.
Fasihi ya Kiafrika kama nyenzo ya kuelezea historia ya Afrika
Authors: Samwel Method
Published: November 2021

Ikisiri

Wanahistoria na wanafasihi wameendelea kujadili uwezo wa fasihi ya Kiafrika kusawiri historia ya Afrika. Baadhi ya wataalamu wanadai kwamba fasihi ya Kiafrika haina uwezo wa kuakisi ukweli wa kihistoria; wengine wanaona kwamba ni baadhi tu ya tanzu za fasihi zinazoweza kusawiri historia ya jamii fulani. Aidha, wengine wanaona kuwa fasihi, kwa ujumla wake, bila kujali utanzu, husawiri historia ya jamii fulani. Data zilizobainishwa hapa zinaonyesha kwamba aina zote za kazi za fasihi – ushairi, tamthilia, riwaya, na fasihi simulizi – zimesawiri historia ya jamii mahususi za Kiafrika. Hivyo, kazi za fasihi ni miongoni mwa vyanzo muhimu vya data za kihistoria.