bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving NSGA-II for Multi-Constrained QoS Routing
Authors: Liu Xin , Zhao Jingyuan , Zheng Lin , Li Liying , Liu Li , Jiao Penglong , Liu Yao
Published: May 2021

With the development of 5G technology, the traffics which need multiple quality of service (QoS) constraints greatly increase. The existing QoS routing algorithms either support a single QoS constraint or support multiple constraints are mixed with fixed weights. The latter is essentially a single-constrained QoS algorithm. Few studies can provide the quality of service guaranteed under the true sense of multiple constraints, by which only one solution can be provided. In this paper, we propose NSGAII-MCR: a multi-constrained QoS routing algorithm based on non-dominated sorting genetic algorithm II (NSGA-II). In NSGAII-MCR, three representative constraints are selected: delay, bandwidth, and packet loss rate. The validity of the routing is guaranteed by a designed encoding and decoding scheme and a novel individual generation method. Meantime, the original NSGA-II crossover and mutation operators are modified. We further enhance the selection strategy to improve the diversity of solutions and the robustness of NSGAII-MCR. At last, multiple optional routes in the Pareto-optimal front are obtained. The experiment demonstrates that the proposed NSGAII-MCR can achieve high success rate by up to 95%. Compared with the benchmarking methods, NSGAII-MCR can support more constraints and finds more multi-constrained routes.
SHAPE PRESERVING ASPECTS OF BIVARIATE α-FRACTAL FUNCTION
Authors: VIJENDER N. , CHAND A. K. B.
Published: May 2021

In this paper, we study shape preserving aspects of bivariate [Formula: see text]-fractal functions. Its specific aims are: (i) to solve the range restricted problem for bivariate fractal approximation (ii) to establish the fractal analogue of lionized Weierstrass theorem of bivariate functions (iii) to study the constrained approximation by [Formula: see text]-bivariate [Formula: see text]-fractal functions (v) to investigate the conditions on the parameters of the iterated function system in order that the bivariate [Formula: see text]-fractal function [Formula: see text] preserves fundamental shapes, namely, positivity and convexity (concavity) in addition to the smoothness of [Formula: see text] over a rectangle (vi) to establish fractal versions of some elementary theorems in the shape preserving approximation of bivariate functions.
THE DIFFERENCE BETWEEN THE HURWITZ CONTINUED FRACTION EXPANSIONS OF A COMPLEX NUMBER AND ITS RATIONAL APPROXIMATIONS
Authors: HE YUBIN , XIONG YING
Published: May 2021

For regular continued fraction, if a real number [Formula: see text] and its rational approximation [Formula: see text] satisfying [Formula: see text], then, after deleting the last integer of the partial quotients of [Formula: see text], the sequence of the remaining partial quotients is a prefix of that of [Formula: see text]. In this paper, we show that the situation is completely different if we consider the Hurwitz continued fraction expansions of a complex number and its rational approximations. More specifically, we consider the set [Formula: see text] of complex numbers which are well approximated with the given bound [Formula: see text] and have quite different Hurwitz continued fraction expansions from that of their rational approximations. The Hausdorff and packing dimensions of such set are determined. It turns out that its packing dimension is always full for any given approximation bound [Formula: see text] and its Hausdorff dimension is equal to that of the [Formula: see text]-approximable set [Formula: see text] of complex numbers. As a consequence, we also obtain an analogue of the classical Jarník theorem in real case.
ON THE DISTINCTION BETWEEN FRACTAL AND SEASONAL DEPENDENCIES IN TIME SERIES DATA
Authors: KOOPMANS MATTHIJS
Published: May 2021

Many techniques are currently available to test time series data for fractal patterns, but concerns have been raised about the fact that they do not always yield consistent results. Furthermore, fractal and nonfractal patterns, such as seasonal variation, tend to be heavily correlated in time series data. It is therefore essential that fractal patterns are clearly distinguished from nonfractal ones in the estimation process. The study is concerned with this capability in the following techniques: detrended fluctuation analysis (DFA), re-scaled range analysis (R/S), Higuchi’s fractality dimension, smoothed spectral regression, Geweke & Porter Hudak’s (GPH) estimator, the spectral periodogram (Sperio) estimate, Whittle’s estimate and the fractional differencing parameter, as well as the conventional time series diagnostics (unit root test, autocorrelation function (ACF) plots). A brief overview is provided of each fractal estimation method and results are presented of their application to three existing time series data sets: annual recordings of the water discharge level of the River Nile (663 years), daily number of births to teens in the state of Texas (5 years) and daily attendance rates in one urban school (4 years). Results indicate that all techniques indicate fractality in two of the three data sets (River Nile flow, school attendance). The results for the births to teens data were equivocal with a strong suggestion of both seasonal and fractal patterns in the ACF plot, but only seasonality in the modeling results. On the other hand, the ACF plot of the school attendance data hints at seasonality that is not picked up in the estimation. For a better perspective on these results, a simulation study was undertaken testing the ability of these techniques to distinguish seasonal and fractal processes under variable input conditions. The results of these simulations show largely accurate fractality estimates in the absence of seasonality. However, fractality estimates tend to be inflated when seasonal variability is present in the data. An integrated analytical approach is therefore recommended for these types of data, triangulating the results from the time series diagnostics with the parameter estimates from formal modeling and making seasonal adjustments to the data if necessary.
A FRACTAL PERSPECTIVE ON FRACTURE INITIATION AND PROPAGATION OF RESERVOIR ROCKS UNDER WATER AND NITROGEN FRACTURING
Authors: LIANG XIN , HOU PENG , XUE YI , YANG XIAOJUN , GAO FENG , LIU JIA
Published: May 2021

This paper mainly investigated the fractal characteristics of crack propagation in hydraulic fracturing and the effect of fractal dimension of induced fractures on the rock breakdown pressure. A series of fracturing experiments with water and nitrogen (N[Formula: see text] as the fracturing fluids were conducted on coal, red sandstone and shale. The injection pressure curves, rock breakdown pressure and macro- and micro-morphologies of the induced fractures were analyzed. A new fractal crack initiation criterion was developed to evaluate the rock breakdown pressure in hydraulic fracturing. The validity of the new criterion was verified by comparing the theoretical and experimental rock breakdown pressures. Further, the difference between the water fracturing and N2 fracturing was analyzed and the influence of crack fractal effect on the rock breakdown pressure was discussed by considering different initial permeabilities of rocks, injection rates and viscosities of fracturing fluids. The results show: (1) N2 fracturing may reduce the rock breakdown pressure and induce more tortuous macro-fractures with larger fractal dimension; (2) ignoring the actual fractal dimension of induced fractures would cause the prediction values of the rock breakdown pressure to be larger; and (3) the influence degree of crack fractal dimension on the rock breakdown pressure is related to the initial permeability of rocks, injection rate and viscosity of fracturing fluids. Therefore, we suggest the crack fractal dimension is an important factor that should not be ignored in designing the fracturing operations.
Studies on Bearing Characteristic of Open-Ended and Close-Ended Pipe Piles under High-Speed Railway Loadings
Authors: Liu Junwei , Guo Zhen , Ling Xianzhang , Yu Xiuxia , Zhu Na
Published: May 2021

The pile foundation under a high-speed railway (HSR) not only bears the self-weight of the superstructure, but also bears a long-term vertical periodic load during its service. In this study, a large-scale vertical dynamic load test and particle flow numerical simulation method were adopted to investigate the axial cyclic performances of open piles in sand. The results from the dynamic test show that under a dynamic load with cyclic load ratios of 0.1 and 0.2, the surface displacement of the pile decays rapidly as the pile distance increases. Moreover, the higher the vibration amplitude and frequency, the larger the surface displacement. The influence range of the soil around the pile is approximately six times of the pile diameter. It is also found that the external frictional resistance of the upper part of the pile decreases, whereas that of the middle part increases. In addition, the internal friction resistance of the lower part of the pile decreases and gradually stabilizes after approximately 200 cycles. The simulation results show that the influence range of the pile on the surrounding soil is approximately 5–8 times the diameter of the pile under the action of dynamic loading; the vertical displacement of the pile mainly occurs at the beginning of the cycles. The total settlement of the pile foundation increases with an increase in the cyclic load ratio. With an increase in the cycle period, the friction resistance values on the outside of the pile and middle part significantly decrease and increase, respectively. After 10 cycles, the resistance gradually stabilizes, and no evident changes in the internal friction resistance of the pile are observed.
Dynamic Response of Wooden Columns in Traditional Timber Structures Under Horizontal Earthquake
Authors: Gao Chao , He Junxiao
Published: May 2021

Accurately predicting the structure’s response under external loads is a prerequisite for scientific protection of traditional timber structures. Wooden columns are the key components for transmitting the vertical loads and resisting the lateral loads in traditional timber structures. The dynamic response characteristics of wooden columns eccentrically overlain by top column component under horizontal earthquakes are investigated in this paper. The critical triggering conditions for different phases of the dynamic response are derived. The factors that determine the transition between various phases of the dynamic response are obtained. Based on the trigger conditions, the trigger sensitivity of each phase of the dynamic responses is studied. The results show that there are four phases of dynamic response that can be triggered on the wooden column, i.e. the static, uplift, uplift followed by slipping, and simultaneous uplift and slipping. Uplift is most likely to be triggered. Uplift with rocking is the main form of wooden columns. The results of theoretical analysis are verified by numerical simulation. This study provides the necessary theoretical basis for the phase assessment and protection of the traditional timber structures.
Effect of Machining Parameters for Surface Finish and Material Removal Rate of Al-4032/SiC Composite During End Milling Using TGRA and ANN
Authors: Saini Pardeep , Singh Pradeep K. , Kumar Deepak
Published: May 2021

The machining of metal matrix composites (MMCs) creates an extra challenge as compared to that of metals and alloys due to their hardness owing to the abrasive reinforcement particles. This paper presents the study on end milling of Al-4032/3% SiC composite considering the cutting speed (CS), feed rate (FR) and depth of cut (DOC) as the process parameters. Surface finish and material removal rate (MRR) have been taken as the response parameters. The Al-4032-based AMC has been prepared using stir casting process. Taguchi’s [Formula: see text] orthogonal array (OA) has been used for experimental trials. The optimum setting of the parameters has been obtained using TGRA. The resulting surface roughness (SR; [Formula: see text]) occurs in the range of 1.18–3.97[Formula: see text][Formula: see text]m, with the minimum value corresponding to the CS of 110[Formula: see text]m/min, FR of 0.05[Formula: see text]mm/tooth and DOC of 1.2[Formula: see text]mm. Bayesian regularization (BR), scaled conjugate gradient (SCG) and Levenberg–Marquardt (LM) algorithms have been employed for training, validating and testing the 3–[Formula: see text]–1 and 3–[Formula: see text]–2 ANN architectures ([Formula: see text]). Minimum root-mean-square error (RMSE) has been taken as the standard for evaluating the model. Neural network toolbox of MATLAB “R2019A” has been used for prediction of the response.
Global dynamics in an age-structured HIV model with humoral immunity
Authors: Xie Zhongzhong , Liu Xiuxiang
Published: May 2021

In this paper, we formulate an age-structured HIV model, in which the influence of humoral immunity and the infection age of the infected cells are considered. The model is governed by three ordinary differential equations and two first-ordered partial differential equations and admits three equilibria: disease-free, immune-inactivated and immune-activated equilibria. We introduce two important thresholds: the basic reproduction number [Formula: see text] and immune-activated reproduction number [Formula: see text] and further show the global stability of above three equilibria in terms of [Formula: see text] and [Formula: see text], respectively. The numerical simulations are presented to illustrate our results.
Stochastic dynamics of the transmission of Dengue fever virus between mosquitoes and humans
Authors: Guo Manjing , Hu Lin , Nie Lin-Fei
Published: May 2021

Considering the impact of environmental white noise on the quantity and behavior of vector of disease, a stochastic differential model describing the transmission of Dengue fever between mosquitoes and humans, in this paper, is proposed. By using Lyapunov methods and Itô’s formula, we first prove the existence and uniqueness of a global positive solution for this model. Further, some sufficient conditions for the extinction and persistence in the mean of this stochastic model are obtained by using the techniques of a series of stochastic inequalities. In addition, we also discuss the existence of a unique stationary distribution which leads to the stochastic persistence of this disease. Finally, several numerical simulations are carried to illustrate the main results of this contribution.
India and China: Perceptions of Images and the Lost Equilibrium
Authors: Deepak B. R.
Published: May 2021

This paper looks into perceptions and images that India and China have constructed over the span of civilizational, colonial and post-colonial periods by analyzing some of the socio-cultural, politico-economic and civilizational undercurrents. It argues that not having a correct understanding of these has resulted in misunderstandings and misperceptions. It also argues that the equilibrium that existed between India and China during the last three decades has been lost due to the balance of power favoring China; the Galwan military standoff that ended up in fatalities on both sides was just one of the manifestations of this. It concludes that both need to find a new equilibrium, which may take longer than the expected, however, policy recalibration through pragmatic constructivism could be a good beginning.
Analyzing Subword Techniques to Improve English to Sinhala Neural Machine Translation
Authors: Naranpanawa Rashmini , Perera Ravinga , Fonseka Thilakshi , Thayasivam Uthayasanker
Published: May 2021

Neural machine translation (NMT) is a remarkable approach which performs much better than the Statistical machine translation (SMT) models when there is an abundance of parallel corpus. However, vanilla NMT is primarily based upon word-level with a fixed vocabulary. Therefore, low resource morphologically rich languages such as Sinhala are mostly affected by the out of vocabulary (OOV) and Rare word problems. Recent advancements in subword techniques have opened up opportunities for low resource communities by enabling open vocabulary translation. In this paper, we extend our recently published state-of-the-art EN-SI translation system using the transformer and explore standard subword techniques on top of it to identify which subword approach has a greater effect on English Sinhala language pair. Our models demonstrate that subword segmentation strategies along with the state-of-the-art NMT can perform remarkably when translating English sentences into a rich morphology language regardless of a large parallel corpus.
A Security and Privacy Validation Methodology for e-Health Systems
Authors: Amato Flora , Casola Valentina , Cozzolino Giovanni , De Benedictis Alessandra , Mazzocca Nicola , Moscato Francesco
Published: May 2021

e-Health applications enable one to acquire, process, and share patient medical data to improve diagnosis, treatment, and patient monitoring. Despite the undeniable benefits brought by the digitization of health systems, the transmission of and access to medical information raises critical issues, mainly related to security and privacy. While several security mechanisms exist that can be applied in an e-Health system, they may not be adequate due to the complexity of involved workflows, and to the possible inherent correlation among health-related concepts that may be exploited by unauthorized subjects. In this article, we propose a novel methodology for the validation of security and privacy policies in a complex e-Health system, that leverages a formal description of clinical workflows and a semantically enriched definition of the data model used by the workflows, in order to build a comprehensive model of the system that can be analyzed with automated model checking and ontology-based reasoning techniques. To validate the proposed methodology, we applied it to two case studies, subjected to the directives of the EU GDPR regulation for the protection of health data, and demonstrated its ability to correctly verify the fulfillment of desired policies in different scenarios.
Functionalization-Mediated Preparation via Acid Precipitation and Photocatalytic Activity of In Situ Ag2WO4@WO3.H2O Nanoplates
Authors: Son Nguyen Hong , Nam Nguyen Giang , Anh Nguyen Tien , Bach Ta Ngoc , Thi Lan Anh Luu , Tung Nguyen Thanh , Trung Nguyen Ngoc , Chien Nguyen Duc , Lam Nguyen Huu , Nguyen Cong Tu
Published: May 2021

Tungsten oxide hydrate (WO3.H2O) nanoplates were in situ functionalized with AgNO3 via a one-step acid precipitation method at room temperature. The functionalized product was the nanocomposite of Ag2WO4 and WO3.H2O. Both pristine and functionalized samples had nanoplate morphology. The nanoplates’ dimension and uniformity decreased with the increase in the AgNO3 amount, resulting in increased specific surface area. The AgNO3 functionalization supported a growth via the orthorhombic WO3.H2O structure, caused a change in the dominant facet from (020) to (111), lessened the micro-strain, and enhanced the photocatalytic activity of samples under visible-light irradiation (λ ≥ 450 nm). The samples functionalized with 5 mass % of AgNO3 showed the highest methylene blue degradation efficiency of 49% and a degradation rate of 0.122 mg g−1 × min, which could be assigned to the largest specific surface area and the synergistic effect caused by the Ag2WO4@WO3.H2O junction. These results suggested a simple method for tailoring the dominant facet and morphology of WO3.H2O-based materials for visible-light-driven applications.
Synthesis and Characterization of Adsorbent Biochar/MnFe2O4Composite from Agricultural Residue for Wastewater Treatment
Authors: Akhtar M. Wasim , Gabol Nasir M. , Memon Muddassir Ali , Shaikh Aqsa , Shahbaz Raja , Khan M. Yasir
Published: May 2021

Agriculture residue is produced every year in millions of tons worldwide and can be used as cheaper and environmentally friendly adsorbent. Herein, the biochar was synthesized by pyrolysis from coconut hull, corncob, rice husk, peanut hull and wheat straw. Total organic carbon was determined by standard TC-IC method, i.e., for Wheat Straw was found 20% highest among others agricultural residue and selected for biochar/MnFe2O4composite synthesis. FTIR spectroscopy showed a band at 630 cm−1that confirms the presence of MnFe2O4. BET surface analysis data showed the average specific surface area of biochar in the range of (4.3–79.389 m2g−1). The surface area of biochar/MnFe2O4composite was 149.96 m2g−1, which was highest of all synthesized biochar’s. Adsorption study was carried out by using a specified amount of biochar for the specified time in a 50 ml wastewater sample of known chemical oxygen demand (COD) value. Biochar/MnFe2O4adsorbent composite showed greater COD reducing the capacity of 70% than that of biochar produced without the formation of precipitates of MnFe2O4. The combination of various appealing attributes including cost-effective, environmentally friendly, and good COD reducing ability makes adsorbent a good option to be used in industrial applications specifically in the field of water treatment.
Effects of Dielectric Passivation on Device Performance of AlGaN/GaN High-Electron-Mobility Transistors
Authors: Kim Jaeho , Oh Jaejoon , Kim Jongseob , Cho Jaehee
Published: May 2021

Various dielectrics deposited on the surfaces of AlGaN/GaN-based metal-gate high-electron-mobility transistors (HEMTs) were investigated to understand their effects on the device characteristics. The observed increase by 30% in the two-dimensional electron gas (2DEG) sheet carrier density by the deposition of SiO2, Si3N4, or Al2O3 was in line with the improved output and transfer characteristics of the HEMT devices with the deposited dielectrics, as compared to those of the bare HEMT device without dielectric. The improvements seemed to result from the strain accumulation in AlGaN due to the difference in thermal expansion between AlGaN and the dielectric and from the effective treatment of surface electrical passivation by the deposited dielectric. Furthermore, suppression of current collapse was observed in the SiO2− and Si3N4−deposited samples, as compared to the bare HEMT device.
Review—Important Considerations Regarding Device Parameter Process Variations in Semiconductor-Based Manufacturing
Authors: Huff Michael
Published: May 2021

This paper reviews the topic of the device parameter variations using semiconductor-based manufacturing of micro- and nano-devices. There is considerable misunderstanding about the precision of these types of manufacturing methods and that smaller does not always mean more precise. This issue is very important to many types of devices made using semiconductor manufacturing, particularly those having analog functionality including MEMS, NEMS, photonics, analog ICs, and nanotechnologies. It also is getting increased attention in digital ICs as the gate lengths have decreased. It is shown that the relative variations using these manufacturing methods are generally larger in magnitude compared to more conventional methods of production such as traditional machining operations. Moreover, since many of the devices made using semiconductor-based manufacturing methods have analog-functionality, device parameter variations can have a magnified impact on the variations exhibited in the device output behavior. Methods to estimate the impact of device parameter variations on the device output behavior are given, including an analytical method and Monte Carlo analysis. The impact of these variations on the manufacturing yield is explained and demonstrated. Lastly, a number of techniques that can be used to manage these device parameter variations so as to improve the manufacturing yield are given.
CD4+CD25+ Regulatory T Cells in Intracranial Thrombi Are Inversely Correlated with Hemorrhagic Transformation after Thrombectomy: A Clinical‐Immunohistochemical Analysis of Acute Ischemic Stroke
Authors: Gong Li , Zheng Xiaoran , Zhang Weiyan , Shu Zhongwen , Wang Haichao , Dong Qiong , Sun Letao , Zhang Xiang , Zhao Yanxin , Liu Xueyuan
Published: May 2021

Mechanical thrombectomy is not only effective for managing patients with acute ischemic stroke (AIS), but it also enables a valuable histological analysis of thrombi. Previous studies indicated that regulatory T cells (Treg) adoptive transfer might alleviate the hemorrhagic transformation. However, whether Treg in intracranial thrombi correlates with hemorrhagic transformation after mechanical thrombectomy remains unclear. This study mainly analyzed the colocation of Treg markers in serial thrombus sections stained serially for CD4 and CD25 in groups of hemorrhagic or nonhemorrhagic transformation. Second, to investigate whether these immunohistochemical parameters could provide any additional information beyond hemorrhagic transformation, we compared the overlap between Treg markers among other groups, such as functional outcomes, stroke subtypes, and gender. Our results showed that the number of CD4+CD25+ Treg cells was lower in the hemorrhagic transformation thrombi than in the nonhemorrhagic group (p < 0.001) but there were no significant differences otherwise. The present finding of CD4+CD25+ Treg cell reductions in thrombi associated with hemorrhagic transformation provides the histological evidence supporting that thromboinflammation might involve in the pathological process of an acute stroke after mechanical thrombectomy.
Key
n
-Gram Extractions and Analyses of Different Registers Based on Attention Network
Authors: Wu Haiyan , Liu Ying , Shi Shaoyun , Wu Qingfeng , Huang Yunlong
Published: May 2021

Key

n

-gram extraction can be seen as extracting

n

-grams which can distinguish different registers. Keyword (as

n
=
1

, 1-gram is the keyword) extraction models are generally carried out from two aspects, the feature extraction and the model design. By summarizing the advantages and disadvantages of existing models, we propose a novel key

n

-gram extraction model “attentive

n

-gram network” (ANN) based on the attention mechanism and multilayer perceptron, in which the attention mechanism scores each

n

-gram in a sentence by mining the internal semantic relationship between words, and their importance is given by the scores. Experimental results on the real corpus show that the key

n

-gram extracted from our model can distinguish a novel, news, and text book very well; the accuracy of our model is significantly higher than the baseline model. Also, we conduct experiments on key

n

-grams extracted from these registers, which turned out to be well clustered. Furthermore, we make some statistical analyses of the results of key

n

-gram extraction. We find that the key

n

-grams extracted by our model are very explanatory in linguistics.
Clinicopathological Significance of FOXO4 Expression and Correlation with Prx1 in Head and Neck Squamous Cell Carcinoma
Authors: Lu Yunping , Shen Yajun , Li Lingyu , Zhang Min , Wang Min , Ge Lihua , Yang Jing , Tang Xiaofei
Published: May 2021

Objective. Forkhead box O 4 (FOXO4), a key albumen in the forkhead box O (FOXOs) family, plays crucial roles as a tumor suppressor in the cancer development. In our previous study, Peroxiredoxin1 (Prx1) promoted the development of oral cancer and was predicted to bind to FOXO4. The aim of this study was to investigate the clinicopathological significance of FOXO4 expression and its potential mechanism in head and neck squamous cell carcinomas (HNSCC). Methods. The function of FOXO4 correlation with HNSCC prognosis was analyzed via ONCOMINE, UALCAN, Human Protein Atlas, and cBioPortal. The expression of FOXO4 was detected in Prx1 silenced CaL27 and SCC9 cell lines by Western blot. FOXO4 protein expression was observed via immunohistochemistry (IHC) and the binding of Prx1 to FOXO4 measured by Duolink analysis in a 4-nitro-quinoline-1-oxide- (4NQO-) induced tongue carcinogenesis model in Prx1+/+ and Prx1+/− mice. Results. By the analysis of Bioinformation Databases, there was a significant interaction of FOXO4 down expression to clinical tumor stages and pathological grades in the patients with HNSCC. Reduced mRNA and protein expression of FOXO4 were found to be significantly correlated with the poor overall survival (OS) of HNSCC patients. FOXO4 expression is negatively related to Prx1 significantly in HNSCC tissues. By employing a 4NQO-induced oral carcinogenesis mouse model, we confirmed that FOXO4 expression was reduced in 4NQO-induced squamous cell carcinoma (SCC) tongue tissues compared with those in normal tissues. Prx1 knockdown resulted in the upregulation of FOXO4 expression in the SCC tissues and CaL27 and SCC9 cell lines. Furthermore, the interaction of Prx1 with FOXO4 was observed in mouse tongue tissues by Duolink analysis. Conclusion. FOXO4 plays an important role in the development of HNSCC. The lower expression of FOXO4 is significantly correlated with the shorter OS in patients with HNSCC. FOXO4 is negatively regulated via interaction with Prx1. FOXO4 could be a potential molecular target for the treatment and prognosis of HNSCC.
Chaotic Reversible Watermarking Method Based on IWT with Tamper Detection for Transferring Electronic Health Record
Authors: Nazari Mahboubeh , Maneshi Arash
Published: May 2021

Health IoT deals with sensitive medical information of patients, therefore security concerns need to be addressed. Confidentiality of Electronic Health Record (EHR) and privacy are two important security requirements for IoT based healthcare systems. Recently, watermarking algorithms as an efficient response to these requirements is in the spotlight. Further, as smart city-based applications have to react to real-time situations, efficient computation is a demand for them. In this paper, a secure, lightweight, reversible, and high capacity watermarking algorithm with tamper detection capability is proposed for IoT based healthcare systems. The scheme has applied Integer Wavelet Transform (IWT) and chaotic map for efficiency and increasing security. EHR is encrypted and then embedded into the Least Significant Bits (LSB) of wavelet coefficients of medical images. The proposed method has been extensively tested for various color and grayscale commonly used medical and general images. Investigations on experimental results and criterions such as Peak Signal to Noise Ratio (PSNR) and Bit Error Ratio (BER) above 45.41 dB and 0.04, respectively, for payload of 432,538 bits indicate that the proposed method, besides providing security, being reversible, tamper detection capability, and high embedding capacity, has high imperceptibility and adequate resistance against different types of attacks.
Application of VR Technology in Jewelry Display
Authors: Jin Cuiling , Li Jiapei
Published: May 2021

As a special symbolic cultural carrier that reflects people’s material life and spiritual state, jewelry plays an increasingly important role in life. How can we accelerate brand promotion, promote jewelry product sales, and establish a rapid market response mechanism? High efficiency, high quality, and low cost to meet consumers’ increasingly personalized and diversified needs are the problems we currently need to solve. The purpose of this article is to explore the application of VR technology in jewelry displays and provide a brand new idea for jewelry display. In order to realize the virtualization of the jewelry design process, this article uses the Cult 3D VR platform to complete the design and realization of the interactive function of the jewelry virtual model, uses the Photoshop software to design the jewelry virtual display system interface, and finally completes the jewelry virtual display system in the Dreamweaver software integration and release. Through detailed example application, the feasibility of the viewpoint of this subject was effectively verified. In this paper, the two algorithms BRSK and SURF are used in conjunction, and the multiscale expression characteristics of BRISK in space and the rotation-invariant characteristics of SURF are used. Studies have shown that the experimental results of the rotation performance of the method in this paper show that the accuracy is improved by 60%, and the time-consuming is relatively less. Therefore, under the premise of ensuring the rapidity, the method in this paper can guarantee the accuracy and time cost of control matching.
Variation of PPARG Expression in Chemotherapy-Sensitive Patients of Hypopharyngeal Squamous Cell Carcinoma
Authors: Lian Meng , Tao Yong , Chen Jiaming , Shen Xixi , Hou Lizhen , Cao Shaolong , Fang Jugao
Published: May 2021

Our previous study showed that the upregulation of peroxisome proliferator-activated receptor gamma (PPARG) could promote chemosensitivity of hypopharyngeal squamous cell carcinoma (HSCC) in chemotherapeutic treatments. Here, we acquired two more independent expression data of PPARG to validate the expression levels of PPARG in chemotherapy-sensitive patients (CSP) and its individualized variations compared to chemotherapy-non-sensitive patients (CNSP). Our results showed that overall PPARG expression was mildly downregulated (

log
 
fold
 
change
=
−
0.55

;

p

value = 0.42; overexpression in three CSPs and reduced expression in four CSPs), which was not consistent with previous results (

log
 
fold
 
change
=
0.50

;

p
=
0.22

; overexpression in nine CSPs and reduced expression in three CSPs). Both studies indicated that PPARG expression variation was significantly associated with the Tumor-Node-Metastasis (TNM) stage (

p
=
7.45
e
−
7

and

6.50
e
−
4

, for the first and second studies, respectively), which was used as one of the predictors of chemosensitivity. The new dataset analysis revealed 51 genes with significant gene expression changes in CSPs (

LFC
>
1

or <-1;

p

value < 0.01), and two of them (TMEM45A and RBP1) demonstrated strong coexpression with PPARG (

Pearson
 
correlation
 
coefficient
>
0.6

or <-0.6). There were 21 significant genes in the data from the first study, with no significant association with PPARG and no overlap with the 51 genes revealed in this study. Our results support the connection between PPARG and chemosensitivity in HSCC tumor cells. However, significant PPARG variation exists in CSPs, which may be influenced by multiple factors, including the TNM stage.
Complete Convergence for Weighted Sums of Widely Acceptable Random Variables under Sublinear Expectations
Authors: Hu Rong , Wu Qunying
Published: May 2021

Using different methods than the probability space, under the condition that the Choquet integral exists, we study the complete convergence theorem for weighted sums of widely acceptable random variables under sublinear expectation space. We proved corresponding theorem which was extended to the sublinear expectations’ space from the probability space, and similar results were obtained.
Tibetan Medicines and Tibetan Prescriptions for the Treatment of Diabetes Mellitus
Authors: Gao Jie , Pan Lin , Bi Ruohong , Shi Yi , Han Yunfeng , Tang Xi , Lai Xianrong
Published: May 2021

Diabetes mellitus (DM) is one of the most serious diseases threatening human health and because of that, it is imperative to look for drugs to tackle it. The Tibetan medicine, a traditional medical system used in China, is currently being the focus of research towards the discovery of new effective drugs against several diseases. Based on the literature survey of Tibetan medicine monographs and drug standards, the Tibetan medicine, and Tibetan prescription used in the traditional Tibetan medical system, here, we summarise the methods indicated for DM treatment. In the Tibetan medical system, 56 types of Tibetan medicine and 25 Tibetan prescriptions were found for the treatment of DM. The most commonly used are Curcuma, Berberidis Cortex, and Carthami Flos. Their names, families, medicinal parts, phytochemical components, and pharmacological activities were described in detail in our research. These Tibetan medicines and prescriptions are valuable gifts from the Tibetan medicine to the world and may be the source of potential drugs for the treatment of DM. With the help of modern phytochemistry, pharmacology, metabonomics, and/or clinical trial methods, further research is needed to prove its medicinal value, identify bioactive components, elucidate potential mechanisms of action, and assess potential side effects or toxicity. This study provides the first available data compilation for the ethnic medical knowledge of Tibetan medicine for the treatment of DM, providing new ideas and sources for drugs against DM.
SMSEI‐SDN: A Suppression Method of Security Incident Impact for the Inter‐Domain Routing System Based on Software‐Defined Networking
Authors: Zhu Huihu , Qiu Han , Zhu Junhu , Chen Di
Published: May 2021

Security incidents such as natural disasters and power outages can cause inter‐domain routing system regional failures, significantly impact the Internet’s safety. Reducing the impact of security incidents is essential for maintaining the stability of the Internet. One of the major impacts of security incidents is that many UPDATE messages will generate, which may easily cause network oscillations. This paper presents the UPDATE messages analysis during the six security incidents and finds that many duplicates and invalid messages are the leading cause of network instability. To effectively process these UPDATE messages, this paper proposes an UPDATE message preprocessing algorithm by analyzing the UPDATE operating mechanism to remove duplicate and invalid messages. Aiming at the problem of slow route search in existing route update methods using software‐defined networking (SDN), this paper designs a RIB hierarchical structure for multi‐level retrieval and proposes SMSEI‐SDN combination with current route update strategies. Experimental results show that when a security incident occurs, by removing duplicate and invalid messages, SMSEI‐SDN can reduce the total number of messages by an average of 19% and a maximum of 34.9% within the 60 s of caching time. Besides, SMSEI‐SDN can reduce the routing update time by more than 99.98% compared to existing methods. This work provides insights for network operators and researchers interested in security incident impact suppression in the inter‐domain routing system.
On Some Structural Components of Nilsolitons
Authors: Kadioglu Hulya
Published: May 2021

In this paper, we study nilpotent Lie algebras that admit nilsoliton metric with simple pre-Einstein derivation. Given a Lie algebra

η

, we would like to compute as much of its structure as possible. The structural components we consider in this study are the structure constants, the index, and the rank of the nilsoliton derivations. For this purpose, we prove necessary or sufficient conditions for an algebra to admit such metrics. Particularly, we prove theorems for the computation of the Jacobi identity for a given algebra so that we can solve the system of the equation(s) and find the structure constants of the nilsoliton.
A Fast and Reliable Method to Interpret Short-Term Mortality in Perforated Peptic Ulcer: Red Cell Distribution Width is Sensitive and Specific
Authors: Akturk Okan Murat , Çakır Mikail , Vardar Yaşar Murat , Yıldırım Doğan , Akıncı Muzaffer
Published: May 2021

Introduction. Peptic ulcer is an important health problem worldwide with a prevalence of around 5%. Peptic ulcer perforation is a potentially mortal complication of peptic ulcer disease. We aimed to investigate the potential use of red cell distribution width as a prognostic marker in peptic ulcer perforation. Methods. The files, operation notes, biochemical and hematological parameters, and prognosis of patients who were operated for a peptic ulcer perforation were reviewed in a retrospective cohort study. The relation of red cell distribution width (RDW) to main outcome in-hospital mortality was assessed. Results. The mean age of the 172 patients was 40 ± 17.89. There were 158 (92%) males and 14 (8%) females. The in-hospital mortality was 8.7% (15/172). The median RDW in the group with mortality was 15.00 (interquartile range (IQR): 14.30–17.20) compared with the median RDW in the group with no mortality as 13.2 (IQR: 12.80–14.00,

p
≤
0.001

). Receiver operator characteristic curves were plotted for RDW to identify nonsurvivors and yielded a significant area under the curve as 0.812 (95% confidence interval: 0.682–0.942). The sensitivity and specificity of RDW at a cutoff value of 14.25% were calculated with an accuracy of 81.98 (95% confidence interval: 75.40–87.41) as 80.00 (51.91–95.67) and 82.17 (75.27–87.81), respectively. Conclusion. Increased RDW may be of use to interpret mortality in patients with peptic ulcer perforation.
Association of AFF3 Gene Polymorphism rs10865035 with Rheumatoid Arthritis: A Population-Based Case-Control Study on a Pakistani Cohort
Authors: Ali Yasir , Khan Suleman , Chen Yangchao , Farooqi Nadia , Islam Zia-Ul , Akhtar Mehran , Aamir  , Aman Aisha , Shah Aftab Ali , Jamal Muhsin , Jalil Fazal
Published: May 2021

Rheumatoid arthritis (RA) is one of the complex diseases with the involvement of the genetic as well as environmental factors in its onset and severity. Different genome-wide association and candidate gene studies have shown the role of several genetic variants in multiple loci/genes with ethnical and geographical variations. This study was designed to detect the association of a single-nucleotide polymorphism (SNP) rs10865035 in the AFF3 gene with the genetic background of rheumatoid arthritis (RA) in the Pakistani cohort. A total of 703 individuals, including 409 RA patients and 294 healthy controls, were genotyped using TaqMan assay and Tri primer ARMS-PCR (amplification-refractory mutation system-polymerase chain reaction) methods. The association of rs10865035 with the RA was statistically determined using different models. Interestingly, besides the homozygous recessive model (G/G vs. A/G + A/A) (OR = 1.693(1.06–2.648);

P

 = 0.025), all other models, which included the codominant (χ2 = 5.169;

P

 = 0.075), homozygous dominant (A/A vs. G/G + A/G) (OR = 0.867 (0.636–1.187);

P

 = 0.41), heterozygous (A/G vs. A/A + GG) (OR = 0.491 (0.667–1.215);

P

 = 0.49), and additive model (OR = 0.826 (0.665–1.027);

P

 = 0.08) showed insignificant distribution of the genotypes among the cases and controls. These findings suggest that the AFF3 gene (rs10865035) has no significant role in the onset of RA in the Pakistani population.
Regularized Feature Selection in Categorical PLS for Multicollinear Data
Authors: Mehmood Tahir
Published: May 2021

Article presents the algorithm which models the categorical multicollinear data by providing the balance in model accuracy on test data and number of selected features in the model. In all scientific fields, multicollinear data is being generated, where obviously some variables are noise and some are influential reference to response variable. Features and response appeared to be categorical in mathematical and statistical modeling of public health data. These datasets usually appeared to collinear, where partial least squares (PLS) is the potential method, which is not feature selection at its default level and deals with quantitative features. Recently, categorical PLS (Cat-PLS) is introduced. We have implemented the regularized feature selection in Cat-PLS where filter-based feature selection and categorical mean through Cramer’s V, Phi coefficient, Tschuprow’s T coefficient, Contingency Coefficient, and Yule’s Q and Yule’s Y are used. Monte carlo simulation with 100 runs indicates

Cramer 
V
∗
VIP

is the better choice in terms of better model performance, number of feature selection, and interpretations for modeling the stillbirths, which is taken as the case study. The framework can be used in related areas to explore and model the related data structures.
Virtual Reality Video Image Classification Based on Texture Features
Authors: Qin Guofang , Qin Guoliang
Published: May 2021

As one of the most widely used methods in deep learning technology, convolutional neural networks have powerful feature extraction capabilities and nonlinear data fitting capabilities. However, the convolutional neural network method still has disadvantages such as complex network model, too long training time and excessive consumption of computing resources, slow convergence speed, network overfitting, and classification accuracy that needs to be improved. Therefore, this article proposes a dense convolutional neural network classification algorithm based on texture features for images in virtual reality videos. First, the texture feature of the image is introduced as a priori information to reflect the spatial relationship between pixels and the unique characteristics of different types of ground features. Second, the grey level cooccurrence matrix (GLCM) is used to extract the grey level correlation features of the image in space. Then, Gauss Markov Random Field (GMRF) is used to establish the statistical correlation characteristics between neighbouring pixels, and the extracted GLCM‐GMRF texture feature and image intensity vector are combined. Finally, based on DenseNet, an improved shallow layer dense convolutional neural network (L‐DenseNet) is proposed, which can compress network parameters and improve the feature extraction ability of the network. The experimental results show that compared with the current classification method, this method can effectively suppress the influence of coherent speckle noise and obtain better classification results.
Research on Ultrasonic Image Recognition Based on Optimization Immune Algorithm
Authors: Zeng Xueqiang , Chen Sufen
Published: May 2021

With the rapid development of science and technology, ultrasound has been paid more and more attention by people, and it is widely used in engineering, diagnosis, and detection. In this paper, an ultrasonic image recognition method based on immune algorithm is proposed for ultrasonic images, and its method is applied to medical ultrasound liver image recognition. Firstly, this paper grays out the ultrasound liver image and selects the region of interest of the image. Secondly, it extracts the feature based on spatial gray matrix independent matrix, spatial frequency decomposition, and fractal features. Then, the immune algorithm is used to classify and identify the normal liver, liver cirrhosis, and liver cancer ultrasound images. Finally, based on the deficiency of the immune algorithm, it is combined with the support vector machine to form an optimized immune algorithm, which improves the performance of ultrasonic liver image classification and recognition. The simulation shows that this paper can effectively classify the normal liver, liver cirrhosis, and liver cancer ultrasound images. Compared with the traditional immune algorithm, this paper combines the immune algorithm with the support vector machine, and the optimized immune algorithm can effectively improve the performance of ultrasonic liver image classification and recognition.