bluuebunny/crossref_metadata_2025 huggingface dataset:
Glechoma curviflora Volatile Oil from Palestine: Chemical Composition and Neuroprotective, Antimicrobial, and Cyclooxygenase Inhibitory Activities
Authors: Al-Maharik Nawaf , Jaradat Nidal , Qneibi Mohammad , Abualhasan Murad N. , Emwas Nour
Published: November 2020

The rise of the emergence of microbial resistance of antibiotics, the dangerous side effects of nonsteroidal anti‐inflammatory drugs, and noncompetent medications of Alzheimer’s, Parkinson’s, and other neurodegenerative diseases prompt scientists to search for phytochemicals that could be utilized in the remedy of lethal diseases. Glechoma curviflora (Boiss.) Kuntze (Nepeta curviflora) is a medicinal herb growing in the eastern parts of the Mediterranean Sea Basin and is widely consumed as a tea. The leaves of this plant have been traditionally used for the treatment of various infectious diseases. The current research was designed to identify the chemical composition of Glechoma curviflora (Boiss.) essential oil (EO) and to assess its antibacterial, antifungal, and cyclooxygenase inhibitory activities and the biophysical gating effect on AMPA receptors. Twenty phytochemicals were identified from G. curviflora leaves and flowers EO amounting to almost 100% of the total constituents using GC‐MS technique, of which 1,6‐dimethylspiro[4.5]decane (27.51%) 1, caryophyllene oxide (20.08%) 2, and β‐caryophyllene (18.28%) 3 were the main constituents. The biophysical properties’ effect from the plant extract on various AMPA‐type receptors expressed in Human Embryonic Kidney (HEK293) cells was assessed by exploiting the whole‐cell patch‐clamp technique. Microdilution assay was adopted for assessing the antimicrobial property against eight virulent microbial strains whilst the cyclooxygenase inhibition effect was accomplished utilizing COX inhibitory screening colorimetric assay G. curviflora EO displayed potent activity against P. aeruginosa (MIC = 1.25 μg/mL), S. sonnei (MIC = 3.12 μg/mL), and E. coli (MIC = 1.25 μg/mL), compared with ciprofloxacin (positive control) and potent antibacterial activity against S. aureus, MRSA, S. sonnei, E. coli, and P. aeruginosa compared to Ampicillin (2nd positive control). It also showed anti‐Candida (MIC = 6.25 μg/mL) and antimold (MIC = 3.125 μg/mL) activities compared with fluconazole (antifungal positive control). Likewise, our results showed an inhibition and biophysical impact of G. curviflora on all AMPARs subunits.
Comparison of Traditional Chinese Exercises and Nontraditional Chinese Exercise Modalities on Cognitive and Executive Function in Community Middle‐Aged and Older Adults: A Cross‐Sectional Study
Authors: Ye Mingzhu , Xiong Jian , Zhao Fang , Sun Shanshan , Wang Lecong , Zheng Guohua
Published: November 2020

Background. Current evidence indicates that regular exercise can have a positive impact on cognitive function in older adults, but whether different exercise modalities may induce differential protective effects in different cognitive domains is uncertain. Objective. To compare the effect of traditional Chinese exercise (TCE) modalities and non‐traditional Chinese exercise (non‐TCE) modalities on cognitive and executive function in community middle‐aged and older adults through a cross‐sectional study. Methods. A total of 350 community middle‐aged and older adults aged over 55 years participated in this study. Information on demographic characteristics, lifestyle and behavioural habits, and regular exercise was collected by a self‐designed questionnaire. Global cognitive ability and executive function were assessed using the Montreal Cognitive Assessment (MoCA) scale, the clock drawing test (CDT), the animal naming test (ANT), and the trail making test (TMT). Eligible subjects were categorized into the no regular exercise (no‐RE), non‐TCE, or TCE groups according to their self‐reported exercise information. Comparisons of global cognitive and executive function among the three groups were conducted using ANOVA or the general linear model with adjustment for potential confounding factors. Results. The results showed that for the non‐TCE or TCE groups, the MoCA and CDT scores were significantly higher, and the TMT‐A test time was significantly shorter than those in the no‐RE group (all P < 0.05), but no significant difference was observed for the TMT‐B and ANT tests. After adjustment for potential confounding factors, the MoCA, the CDT, and TMT‐A scores in the TCE group were significant compared to those in the no‐RE group. In addition, subgroup analysis showed that in the TCE group, the MoCA scores were significantly higher than those in the non‐TCE group. Furthermore, in the TCE group, the CDT scores for those with an exercise duration of <5 years were higher and the TMT‐A test time for those with an exercise duration of ≥5 years was shorter than those in the non‐TCE group. Conclusions. Both TCE and non‐TCE have potential protective effects on global cognitive and executive function in community middle‐aged and older adults. Compared to the non‐TCE modality, the TCE modality may have a more positive association with these protective effects. Furthermore, prospective studies are needed to confirm these findings.
Improved Distance Functions for Instance-Based Text Classification
Authors: El Hindi Khalil , Abu Shawar Bayan , Aljulaidan Reem , Alsalamn Hussien
Published: November 2020

Text classification has many applications in text processing and information retrieval. Instance-based learning (IBL) is among the top-performing text classification methods. However, its effectiveness depends on the distance function it uses to determine similar documents. In this study, we evaluate some popular distance measures’ performance and propose new ones that exploit word frequencies and the ordinal relationship between them. In particular, we propose new distance measures that are based on the value distance metric (VDM) and the inverted specific-class distance measure (ISCDM). The proposed measures are suitable for documents represented as vectors of word frequencies. We compare these measures’ performance with their original counterparts and with powerful Naïve Bayesian-based text classification algorithms. We evaluate the proposed distance measures using the kNN algorithm on 18 benchmark text classification datasets. Our empirical results reveal that the distance metrics for nominal values render better classification results for text classification than the Euclidean distance measure for numeric values. Furthermore, our results indicate that ISCDM substantially outperforms VDM, but it is also more susceptible to make use of the ordinal nature of term-frequencies than VDM. Thus, we were able to propose more ISCDM-based distance measures for text classification than VDM-based measures. We also compare the proposed distance measures with Naïve Bayesian-based text classification, namely, multinomial Naïve Bayes (MNB), complement Naïve Bayes (CNB), and the one-versus-all-but-one (OVA) model. It turned out that when kNN uses some of the proposed measures, it outperforms NB-based text classifiers for most datasets.
Investigation on Properties of Cement Bitumen Emulsion Mortars (CBEM) in Consideration of Emulsifier Types
Authors: Liu Zhuoran , Huo Jinyang , Wang Zhenjun
Published: November 2020

In order to investigate the influences of emulsifier types on properties of cement bitumen emulsion mortars (CBEM), anionic and cationic emulsifiers were used to prepare CBEM in this work. Influences of anionic and cationic bitumen emulsions on workability, mechanical properties, and viscoelastic property of CBEM were studied. The workability of CBEM was evaluated by fluidity and extensibility tests. The mechanical properties were assessed by compressive strength and flexural strength tests. XRD was used to analyze the phase before and after bitumen emulsion was added. The viscoelastic property was studied by a dynamic mechanical analyzer (DMA). The results show that CBEM prepared by cationic bitumen emulsion (CBE) has better workability. The mechanical properties of CBEM are negatively affected by bitumen emulsion. The impact on the compressive strength of CBEM prepared by CBE is higher. Bitumen emulsion can significantly improve the viscoelastic property of CBEM. With the increase of bitumen emulsion dosage, the loss factor of CBEM increases. The viscoelastic property at low frequency is better than that at high frequency. In contrast to CBEM prepared by CBE, CBEM prepared with anionic bitumen emulsion (ABE) possesses better viscoelastic property.
Radial Basis Function Artificial Neural Network for the Investigation of Thyroid Cytological Lesions
Authors: Fragopoulos Christos , Pouliakis Abraham , Meristoudis Christos , Mastorakis Emmanouil , Margari Niki , Chroniaris Nicolaos , Koufopoulos Nektarios , Delides Alexander G. , Machairas Nicolaos , Ntomi Vasileia , Nastos Konstantinos , Panayiotides Ioannis G. , Pikoulis Emmanouil , Misiakos Evangelos P.
Published: November 2020

Objective. This study investigates the potential of an artificial intelligence (AI) methodology, the radial basis function (RBF) artificial neural network (ANN), in the evaluation of thyroid lesions. Study Design. The study was performed on 447 patients who had both cytological and histological evaluation in agreement. Cytological specimens were prepared using liquid-based cytology, and the histological result was based on subsequent surgical samples. Each specimen was digitized; on these images, nuclear morphology features were measured by the use of an image analysis system. The extracted measurements (41,324 nuclei) were separated into two sets: the training set that was used to create the RBF ANN and the test set that was used to evaluate the RBF performance. The system aimed to predict the histological status as benign or malignant. Results. The RBF ANN obtained in the training set has sensitivity 82.5%, specificity 94.6%, and overall accuracy 90.3%, while in the test set, these indices were 81.4%, 90.0%, and 86.9%, respectively. Algorithm was used to classify patients on the basis of the RBF ANN, the overall sensitivity was 95.0%, the specificity was 95.5%, and no statistically significant difference was observed. Conclusion. AI techniques and especially ANNs, only in the recent years, have been studied extensively. The proposed approach is promising to avoid misdiagnoses and assists the everyday practice of the cytopathology. The major drawback in this approach is the automation of a procedure to accurately detect and measure cell nuclei from the digitized images.
Sex Classification via 2D-Skeletonization
Authors: Contreras-Murillo Miguel , de-los-Cobos-Silva Sergio G. , Lara-Velázquez Pedro , Rincón-García Eric A. , Mora-Gutiérrez Román A. , Gutiérrez-Andrade Miguel Á.
Published: November 2020

Sex classification is a challenging open problem in computer vision. It is useful from statistics up to people recognition on surveillance video. So far, the best performance can be achieved by using 3D cameras, but this approach requires the use of some especial hardware. Other 2D approaches achieve good results on normal situations but fail when the person wears loose clothing and carries bags or the camera angle changes as they rely on calculating borders, silhouettes, or the energy of the person in the image. This work aims to provide a novel sex classification methodology based on the creation of a virtual skeleton for each individual from 2D images and video; then, the distances between some points of the skeleton are measured and work as input of a sex classifier. This improves the results since clothing, bags, and the camera angle affect little the skeletonization process.
A CNN-LSTM-Based Model to Forecast Stock Prices
Authors: Lu Wenjie , Li Jiazheng , Li Yifan , Sun Aijun , Wang Jingyang
Published: November 2020

Stock price data have the characteristics of time series. At the same time, based on machine learning long short-term memory (LSTM) which has the advantages of analyzing relationships among time series data through its memory function, we propose a forecasting method of stock price based on CNN-LSTM. In the meanwhile, we use MLP, CNN, RNN, LSTM, CNN-RNN, and other forecasting models to predict the stock price one by one. Moreover, the forecasting results of these models are analyzed and compared. The data utilized in this research concern the daily stock prices from July 1, 1991, to August 31, 2020, including 7127 trading days. In terms of historical data, we choose eight features, including opening price, highest price, lowest price, closing price, volume, turnover, ups and downs, and change. Firstly, we adopt CNN to efficiently extract features from the data, which are the items of the previous 10 days. And then, we adopt LSTM to predict the stock price with the extracted feature data. According to the experimental results, the CNN-LSTM can provide a reliable stock price forecasting with the highest prediction accuracy. This forecasting method not only provides a new research idea for stock price forecasting but also provides practical experience for scholars to study financial time series data.
On the Value of Order Number and Power in Secret Image Sharing
Authors: Yu Yongqiang , Li Longlong , Lu Yuliang , Yan Xuehu
Published: November 2020

Shadow images generated from Shamir’s polynomial-based secret image sharing (SSIS) may leak the original secret image information, which causes a significant risk. The occurrence of this risk is closely related to the basis of secret image sharing, Shamir’s polynomial. Shamir’s polynomial plays an essential role in secret sharing, but there are relatively few studies on the power and order number of Shamir’s polynomial. In order to improve the security and effectiveness of SSIS, this paper mainly studies the utility of two parameters in Shamir’s polynomial, order number and power. Through the research of this kind of utility, the choice of order number and power can be given under different security requirements. In this process, an effective shadow image evaluation algorithm is proposed, which can measure the security of shadow images generated by SSIS. The user can understand the influence rule of the order number and power in SSIS, so that the user can choose the appropriate order number and power according to different security needs.
Quantitative Investigation on the Contributing Factors to the Contact Angle of the CO2/H2O/Muscovite Systems Using the Frumkin-Derjaguin Equation
Authors: Shiga Masashige , Aichi Masaatsu , Sorai Masao
Published: November 2020

It is significant to understand the values and trends of the contact angle of CO2/brine/mineral systems to evaluate and model the sealing performance of CO2 Geo-Sequestration (CGS). It has been reported that the contact angles of the CO2/brine/muscovite systems increase as pressure increases from ambient conditions to reservoir conditions. This trend suggests a decrease in seal integrity. In this paper, we studied its mechanisms and the contributing factors by calculating the Frumkin-Derjaguin equation, which is based on the thermodynamics of the interfacial system. Results show that a decrease of pH is a critical factor for the wettability alteration at a lower pressure range (0.1 MPa to 3.0 MPa). In contrast, the increase of CO2 density and the decrease in the interfacial tension of CO2/brine are significant for the wettability change at a higher pressure range (3.0 MPa to 10.0 MPa). Also, sensitivity analysis shows that the contact angle is sensitive to the interfacial tension of CO2/brine and the coefficients of hydration forces.
Study on Penetration Grouting Mechanism Based on Newton Fluid of Time-Dependent Behavior of Rheological Parameters
Authors: Ding Yi , Yang Zhi-Quan , Yang Yi , Zhu Ying-Yan , Guo Yong-Fa , Zhang Jie , Chen Xin-Gui
Published: November 2020

Grouting mechanism is one of the important factors on the grouting effects of practical projects. At present, the vast majority of Newton fluid penetration grouting mechanisms are considering that the viscosity of Newton fluid during the grouting whole process was constant, so the theoretical diffusion radius calculated by them is far greater than the actual measurements in the grouting engineering. Carrying out theoretical analysis and experimental research, the rheological equation and seepage motion equation for Newton fluid of time-dependent behavior of rheological parameters were established; then, the penetration grouting mechanism of them was deduced. What is more, they were validated by means of designing the grouting verifying experiments. Experiment results show that the theoretical diffusion radius calculated by the formula of diffusion radius of penetration grouting mechanism based on Newton fluid of time-dependent behavior of rheological parameters was in accordance with the change regulation of the actual measurement diffusion radius by grouting experiments. Their difference within the range of 15% is far less than about 80% change between the theoretical diffusion radius calculated by the Maag formula and the actual measurement radius. In general, it can reflect the grout infiltration laws that Newton fluid changes with time. Therefore, research achievements may not only be able to provide a strong theoretical basis for perfecting the penetration grouting mechanism but also play a reference guiding role for the theoretical research, design, and construction in the grouting technique.
Research on English Online Education Platform Based on Genetic Algorithm and Blockchain Technology
Authors: Wu Xuezhong
Published: November 2020

Nowadays, with the rapid development of network technology, the online examination mode has gradually replaced the traditional paper examination mode. This paper introduces computer technology into English teaching and studies and designs an English online test system for English subjects. The system introduces the design module and introduces the genetic algorithm for analysis. By using the artificial intelligence of the genetic algorithm to analyze the examination process, the online examination system completes a series of tasks from questions to examination results, making the examination work intelligent, standardized, and highly efficient. At the same time, it also gives candidates greater fairness and flexibility, making the entire examination process more efficient and convenient.
Tocilizumab Use in a Chronic Hemodialysis Patient for the Management of COVID-19-Associated Pneumonia and Acute Respiratory Distress Syndrome
Authors: Gupta Sudeendra , Madhyastha Rakesh , Hamed Fadi , Balkis Maher , El Nekidy Wasim , Attallah Nizar
Published: November 2020

Novel coronavirus disease 2019 (COVID-19) is a highly infectious, rapidly spreading viral disease. As of writing this article, there are over 4.4 million people affected by COVID-19, and unfortunately, 300,000 have succumbed to the infection. In this article, we address a particularly more susceptible group of the population of end-stage renal disease (ESRD) patients on dialysis who may potentially benefit from being treated with tocilizumab. The use of tocilizumab has not been reported widely in ESRD patients on dialysis to treat COVID-19. In this case report, we describe a patient with ESRD on hemodialysis who was admitted to the intensive care unit, with severe pneumonia secondary to COVID-19 infection. This patient was treated with tocilizumab 400 mg intravenous and had a favorable outcome with no apparent adverse events.
Clinicopathological and Prognostic Roles of STAT3 and Its Phosphorylation in Glioma
Authors: Liang Bo , Li Shuang-Yang , Gong Hui-Zhi , Wang Ling-Xue , Lu Jia , Zhao Yu-Xiu , Gu Ning
Published: November 2020

Glioma is defined as a common brain tumor which causes severe disability or death. As many genes are reported to relate with glioma’s occurrence and development, their prognostic and therapeutic value still remains uncertain. This study aimed at investigating the association between STAT3/p-STAT3 and glioma prognosis. Nine studies (12 trials) scored ≥5 on the Newcastle-Ottawa scale were meta-analysed from the Medline, Embase, and Web of Science databases. We found that STAT3/p-STAT3 overexpression in glioma patients was associated with worse overall survival (

hazard
 
 
ratio
 
 

HR

=
1.40

,

95
%
confidence
 
 
interval
 
 

CI

=
1.05
~
1.86

,

P
=
0.020

), progression-free survival (

HR
=
2.05

,

95
%
CI
=
1.63
~
2.58

,

P
<
0.001

), and better recurrence-free survival (

HR
=
0.37

,

95
%
CI
=
0.15
~
0.95

,

P
<
0.039

). Subgroup analysis implied that STAT3/p-STAT3 overexpression was associated with worse OS in standard treatment (

HR
=
1.80

,

95
%
CI
=
1.06
~
3.04

,

P
=
0.030

), and in China (

HR
=
2.18

,

95
%
CI
=
1.77
~
2.70

,

P
<
0.001

), and metaregression analysis indicated countries (

P
=
0.001

) may be the source of heterogeneity in our study. In conclusion, we suggested STAT3/p-STAT3 was associated with poor prognosis in patients with glioma, which indicated that STAT3/p-STAT3 might be a valuable prognostic biomarker and a promising therapeutic target for glioma.
Train Type Identification at S&C
Authors: Kratochvílová Martina , Podroužek Jan , Apeltauer Jiří , Vukušič Ivan , Plášek Otto
Published: November 2020

The presented paper concerns the development of condition monitoring system for railroad switches and crossings that utilizes vibration data. Successful utilization of such system requires a robust and efficient train type identification. Given the complex and unique dynamical response of any vehicle track interaction, the machine learning was chosen as a suitable tool. For design and validation of the system, real on-site acceleration data were used. The resulting theoretical and practical challenges are discussed.
Viability and Alkaline Phosphatase Activity of Human Dental Pulp Cells after Exposure to Yellowfin Tuna Bone-Derived Hydroxyapatite In Vitro
Authors: Haniastuti Tetiana , Susilowati Heni , Rinastiti Margareta
Published: November 2020

The bone of yellowfin tuna (Thunnus albacares) contains high calcium and phosphor and can be synthesized into hydroxyapatite (HA). Due to its mineral content and similarity in chemical composition with human hard tissue, HA may have potency as a pulp capping material. The aim of this in vitro study was to evaluate the viability and alkaline phosphatase (ALP) activity of dental pulp cells after exposure to HA synthesized from yellowfin tuna bone (THA). Pulp cells were isolated from human-impacted third molar. To evaluate the viability of the pulp cells, the cells were cultured and exposed to various concentrations (6.25 to 200 μg/ml) of THA for 24, 48, and 72 hours. For ALP activity assay, pulp cells were cultured with odontoblastic differentiation media and exposed to THA for 7, 11, and 15 days. ALP activity was then determined using an ALP colorimetric assay kit. Results showed that the viability of the cells was more than 91% after exposure to various concentrations of THA and the cells demonstrated normal cell morphology in all observation periods. The ALP activity test revealed that groups exposed to THA for 7, 11, and 15 days showed higher ALP activity than the control groups (

p
<
0.05

). It is concluded that THA had no cytotoxic effect on pulp cells; furthermore, it enhanced proliferation as well as ALP activity of the pulp cells.
Geological Hazards in Loess Induced by Agricultural Irrigation in Arid and Semiarid Regions of China
Authors: Xu Yuan-jun , Wang Jia-ding , Gu Tian-feng , Kong Jia-xu
Published: November 2020

The development of agriculture in the arid and semiarid regions of China mainly depends on agricultural irrigation. Until 2016, water required for agricultural irrigation has accounted for more than 90% of the total water consumption. But traditionally extensive broad irrigation causes frequent loess geological hazards in irrigation area and it threatens security of local life and property. In this paper, we selected the Heifangtai irrigation district in Yongjing County, Gansu Province, where frequent instabilities occur, as the study area. We used laboratory tests and numerical simulation to examine the mechanism of loess landslides owing to the irrigation hydrological cycle. Irrigation changes the local natural hydrogeological conditions because of the loose and macroporous structure of loess. The numerous pores and fissures constitute preferential migration pathways of irrigation water; thus, irrigation can increase the groundwater level and hydraulic gradient. Broad irrigation is the main inducing factor of geological hazards (including landslides, collapses, and soil salinization) in arid and semiarid regions, and the development of fissures and sinkholes increases the risk of landslides. New water‐saving irrigation methods need to replace the traditional irrigation methods and improve the utilization of water resources. A monitoring and warning system in susceptible areas should be established to ensure the sustainability of local agriculture.
Evaluating the Toxicity and Histological Effects of Al2O3 Nanoparticles on Bone Tissue in Animal Model: A Case-Control Study
Authors: Soltaninejad Hossein , Zare-Zardini Hadi , Hamidieh Amir Ali , Sobhan Mohammad Reza , Saeed-Banadaky Seyed Houssein , Amirkhani Mohammad Amir , Tolueinia Behnaz , Mehregan Mohsen , Mirakhor Mahnaz , Eshaghi Farzaneh sadat
Published: November 2020

The applications of nanostructures have been limited by their different toxicities. So, the investigation of these toxicities is necessary before nanostructure application. This study aimed to evaluate the effect of aluminum oxide (Al2O3) nanoparticles on bone density in Wistar rat. Al2O3 nanoparticle was prepared by the sol-gel method. Characterization was done by X-ray diffraction (XRD) and transmission electron microscopy (TEM). Sixty-four male adult Wistar rats were divided into eight groups including six groups intravenously treated with Al2O3 nanoparticle at concentrations of 25, 50, 100, 250, 500, and 1000 µg/ml: one group received food and water as the control group, and one group received food and water as well as intravenously distilled water as an injection control group. After 41 days, bone density was analyzed by dual-energy X-ray absorptiometry (DEXA). According to X-ray diffraction, the average particle size for Al2O3 nanoparticles was 20.85 nm. The data of densitometry showed that the bone density of right and left foot was reduced in concentrations of 250, 500, and 1000 µg/ml that were statistically significant in comparison with the control group. The reduction of bone density was increased with the enhancement of nanostructures concentration. The effect of Al2O3 nanoparticles on bone density was similar in the left and right legs. Histopatholological assessment also showed that Al2O3 nanoparticles (250, 500, and 1000 µg/ml) lead to significant reduction of trabeculae. Empty lacunae are observed in these three groups. Considering that high concentrations of Al2O3 nanoparticles had toxicity on bone tissue, it must be used by more caution, especially its use as a coating in different devices such as implants, surgical instruments, and bone prostheses.
The Abnormal Detection for Network Traffic of Power IoT Based on Device Portrait
Authors: Fei Jiaxuan , Yao Qigui , Chen Mingliang , Wang Xiangqun , Fan Jie
Published: November 2020

The construction of power Internet of things is an important development direction for power grid enterprises. Although power Internet of things is a kind of network, it is denser than the ordinary Internet of things points and more complex equipment types, so it has higher requirements for network security protection. At the same time, due to the special information perception and transmission mode in the Internet of things, the information transmitted in the network is easy to be stolen and resold, and traditional security measures can no longer meet the security protection requirements of the new Internet of things devices. To solve the privacy leakage and security attack caused by the illegal intrusion in the network, this paper proposes to construct a device portrait for terminal devices in the power Internet of things and detect abnormal traffic in the network based on device portrait. By collecting traffic data in the network environment, various network traffic characteristics are extracted, and abnormal traffic is analyzed and identified by the machine learning algorithm. By collecting the traffic data in the network environment, the features are extracted from the physical layer, network layer, and application layer of the message, and the device portrait is generated by a machine learning algorithm. According to the established attack mode, the corresponding traffic characteristics are analyzed, and the detection of abnormal traffic is achieved by comparing the attack traffic characteristics with the device portrait. The experimental results show that the accuracy of this method is more than 90%.
Privacy-Protection Scheme Based on Sanitizable Signature for Smart Mobile Medical Scenarios
Authors: Xu Zhiyan , Luo Min , Kumar Neeraj , Vijayakumar Pandi , Li Li
Published: November 2020

With the popularization of wireless communication and smart devices in the medical field, mobile medicine has attracted more and more attention because it can break through the limitations of time, space, and objects and provide more efficient and quality medical services. However, the characteristics of a mobile smart medical network make it more susceptible to security threats such as data integrity damage and privacy leakage than those of traditional wired networks. In recent years, many digital signature schemes have been proposed to alleviate some of these challenges. Unfortunately, traditional digital signatures cannot meet the diversity and privacy requirements of medical data applications. In response to this problem, this paper uses the unique security attributes of sanitizable signatures to carry out research on the security and privacy protection of medical data and proposes a data security and privacy protection scheme suitable for smart mobile medical scenarios. Security analysis and performance evaluation show that our new scheme effectively guarantees data security and user privacy while greatly reducing computation and communication costs, making it especially suitable for mobile smart medical application scenarios.
Evolution of a Technology Standard Alliance Based on an Echo Model Developed through Complex Adaptive System Theory
Authors: Jiang Hong , Chen Chen , Zhao Shukuan , Wu Yuhao
Published: November 2020

The evolution of the technology standard alliance (TSA) is examined using complex adaptive system (CAS) theory. Taking TSA as a dynamic CAS, an echo model is constructed to depict the mechanism of its evolution, and a model is simulated on the NetLogo platform. The echo model includes a basic model, an extended model, and a three-layer echo model. The adhesive aggregation of agents is explained, and the three evolutionary stages of agents’ entry, migration, and exit are analyzed. Moreover, the adaptability of agents in TSA is quantified. The results of simulation show the evolution of the TSA in relation to the two aspects of agent adhesion aggregation and agent resource interaction, and they demonstrate the dynamic and complex hierarchical structure of the TSA system. It is proposed that greater matching ability, moderate behavior income, and lower behavior cost are more conducive to the evolution and development of TSA. Additionally, the echo model is reconstructed to expand the range of application of CAS theory.
Moving Window Differential Evolution Independent Component Analysis-Based Operational Modal Analysis for Slow Linear Time-Varying Structures
Authors: Zong Yongshuo , Chen Jinling , Tao Siyi , Wang Cheng , Xiahou Jianbing
Published: November 2020

In order to identify time-varying transient modal parameters only from nonstationary vibration response measurement signals for slow linear time-varying (SLTV) structures which are weakly damped, a moving window differential evolution (DE) independent component analysis- (ICA-) based operational modal analysis (OMA) method is proposed in this paper. Firstly, in order to overcome the problems in traditional ICA-based OMA, such as easy to go into local optima and difficult-to-identify high-order modal parameters, we combine DE with ICA and propose a differential evolution independent component analysis- (DEICA-) based OMA method for linear time invariant (LTI) structures. Secondly, we combine the moving widow technique with DEICA and propose a moving window differential evolution independent component analysis- (MWDEICA-) based OMA method for SLTV structures. The MWDEICA-based OMA method has high global searching ability, robustness, and complexity of time and space. The modal identification results in a three-degree-of-freedom structure with slow time-varying mass show that this MWDEICA-based OMA method can identify transient time-varying modal parameters effectively only from nonstationary vibration response measurement signals and has better performances than moving window traditional ICA-based OMA.
Improved Conditional Differential Analysis on NLFSR-Based Block Cipher KATAN32 with MILP
Authors: Xing Zhaohui , Zhang Wenying , Han Guoyong
Published: November 2020

In this paper, a new method for constructing a Mixed Integer Linear Programming (MILP) model on conditional differential cryptanalysis of the nonlinear feedback shift register- (NLFSR-) based block ciphers is proposed, and an approach to detecting the bit with a strongly biased difference is provided. The model is successfully applied to the block cipher KATAN32 in the single-key scenario, resulting in practical key-recovery attacks covering more rounds than the previous. In particular, we present two distinguishers for 79 and 81 out of 254 rounds of KATAN32. Based on the 81-round distinguisher, we recover 11 equivalent key bits of 98-round KATAN32 and 13 equivalent key bits of 99-round KATAN32. The time complexity is less than

2

31

encryptions of 98-round KATAN32 and less than

2

33

encryptions of 99-round KATAN32, respectively. Thus far, our results are the best known practical key-recovery attacks for the round-reduced variants of KATAN32 regarding the number of rounds and the time complexity. All the results are verified experimentally.
Research on Damage Assessment of Concrete-Filled Steel Tubular Column Subjected to Near-Field Blast Loading
Authors: Cui Ying , Song Meimei , Qu Zhan , Sun Shanshan , Zhao Junhai
Published: November 2020

Concrete-filled steel tubular (CFST) columns are widely used in engineering structures, and they have many different cross section types. Among these, normal solid sections and concrete-filled double-skin steel tubular sections are often used. Although many studies have been conducted on CFST columns with these two section types, no studies have been conducted on their damage assessment under blast loading. In this study, experimental analysis and a numerical simulation method were integrated to evaluate the responses and assess the damage of two concrete-filled steel tubular (CFST) columns with different cross sections subjected to near-field blast loading. The results showed that for a scaled distance of 0.14 m/kg1/3, plastic bending deformation occurred on the surfaces of the two CFST columns facing the explosive. The antiexplosion performance of the normal solid-section (NSS) CFST column was better than that of the concrete-filled double-skin steel tubular (CFDST) column. The explosion centre was set at the same height as the middle of column, and the distributions of the peak pressure values of the two columns were similar: the peak pressures at the middle points of the columns were the greatest, and the peak pressures at the bottom were higher than those at the top. With the analysis of the duration of the positive pressure, the damage at the middle was the most severe when subjected to blast loading. Using pressure-impulse damage theory and the validated numerical simulations, two pressure-impulse damage evaluation curves for NSS and CFDST columns were established separately by analysing the experimental and simulation data. Finally, based on the two pressure-impulse damage evaluation curves, the two pressure-impulse damage criteria for these two different fixed-end CFST columns were defined based on the deflection of the surfaces facing the explosives. Furthermore, the mathematical formulae for the two different column types were established to generate pressure-impulse diagrams. With the established formulae, the damage of the CFST columns with these two cross section types can be evaluated. Damage to other similar CFST columns with different cross section types due to near-field blast loading can also be evaluated by this method.
Multichannel Saliency Detection Based on Visual Bionics
Authors: Cheng Lidan , Li Tianyi , Zha Shijia , Wei Wei , Gu Jihua
Published: November 2020

Inspired by the visual properties of the human eyes, the depth information of visual attention is integrated into the saliency detection to effectively solve problems such as low accuracy and poor stability under similar or complex background interference. Firstly, the improved SLIC algorithm was used to segment and cluster the RGBD image. Secondly, the depth saliency of the image region was obtained according to the anisotropic center-surround difference method. Then, the global feature saliency of RGB image was calculated according to the colour perception rule of human vision. The obtained multichannel saliency maps were weighted and fused based on information entropy to highlighting the target area and get the final detection results. The proposed method works within a complexity of O(N), and the experimental results show that our algorithm based on visual bionics effectively suppress the interference of similar or complex background and has high accuracy and stability.
The Effect of the Teach-Back Method on Knowledge, Performance, Readmission, and Quality of Life in Heart Failure Patients
Authors: Rahmani Ali , Vahedian-Azimi Amir , Sirati-Nir Masoud , Norouzadeh Reza , Rozdar Hamid , Sahebkar Amirhossein
Published: November 2020

Background. Among chronic diseases, heart failure has always been a serious challenge imposing high costs on health systems and societies. Therefore, nurses should adopt new educational strategies to improve self-care behaviors and reduce the readmissions in heart failure patients. This study aimed to determine the effect of the teach-back method on knowledge, performance, readmission, and quality of life in these patients. Methods. This clinical trial was conducted in patients with heart failure (n = 70) hospitalized in the internal wards of the Baqiyatallah al-Azam Medical Center in Tehran (2019). Routine discharge educations were provided in control patients. Self-care topics were taught to the intervention groups by the teach-back method. A cardiac self-care questionnaire was used to assess the knowledge and practice of patients immediately after intervention and three months after patient discharge. Also, SF-36 was presented to each patient. Readmission(s) and quality of life were followed up by telephone interviews three months after patient discharge. Repeated measures analysis of variance and related post-hoc tests were performed for within-group comparisons before, immediately after, and 3 months after teach-back education. Wilks’ lambda multivariate tests were conducted for simultaneous comparison of quality of life subscales between intervention and control groups. Also, logistic regressions were after controlling for baseline measures and confounders. Results. Findings showed significant improvement in the patients’ knowledge and performance immediately after teach-back education, though this effect was slow in the long term after discharge. Also, the frequency of readmissions decreased and the quality of life (except physical function) increased in the patients through teach-back education. By controlling for the pretest effect, the posttest scores for the relevant components of the quality of life suggested improvement in both intervention and control patients. This improvement in the quality of life was confirmed by controlling for baseline measurements using binary logistic regression analysis. Conclusion. Teach-back education improved patients’ knowledge and performance, readmission frequency, and quality of life.
An Improved AGV Real-Time Location Model Based on Joint Compatibility Branch and Bound
Authors: Yang Yang , Li Juntao , Li Xiaoling
Published: November 2020

Automated Guided Vehicle (AGV) indoor autonomous cargo handling and commodity transportation are inseparable from AGV autonomous navigation, and positioning and navigation in an unknown environment are the keys of AGV technology. In this paper, the extended Kalman filter algorithm is used to match the sensor observations with the existing features in the map to determine the accurate positioning of the AGV. This paper proposes an improved joint compatibility branch and bound (JCBB) method to divide the data and then randomly extract part of the data in the divided data set, thereby reducing the data association space; then, the JCBB algorithm is used to perform data association and finally merge the associated data. This method can solve the problem of the increased computational complexity of JCBB when the amount of data to be matched is large to achieve the effect of increasing the correlation speed and not reducing the accuracy rate, thereby ensuring the real-time positioning of the AGV.
Modified SOR-Like Method for Absolute Value Equations
Authors: Li Cui-Xia , Wu Shi-Liang
Published: November 2020

In this paper, based on the work of Ke and Ma, a modified SOR-like method is presented to solve the absolute value equations (AVE), which is gained by equivalently expressing the implicit fixed-point equation form of the AVE as a two-by-two block nonlinear equation. Under certain conditions, the convergence conditions for the modified SOR-like method are presented. The computational efficiency of the modified SOR-like method is better than that of the SOR-like method by some numerical experiments.
MYC Activity Inference Captures Diverse Mechanisms of Aberrant MYC Pathway Activation in Human Cancers
Authors: Schaafsma Evelien , Zhao Yanding , Zhang Lanjing , Li Yong , Cheng Chao
Published: November 2020

c-MYC (MYC) is deregulated in more than 50% of all cancers. While MYC amplification is the most common MYC-deregulating event, many other alterations can increase MYC activity. We thus systematically investigated MYC pathway activity across different tumor types. Using a logistic regression framework, we established tumor type–specific, transcriptomic-based MYC activity scores that can accurately capture MYC activity. We show that MYC activity scores reflect a variety of MYC-regulating mechanisms, including MYCL and/or MYCN amplification, MYC promoter methylation, MYC mRNA expression, lncRNA PVT1 expression, MYC mutations, and viral integrations near the MYC locus. Our MYC activity score incorporates all of these mechanisms, resulting in better prognostic predictions compared with MYC amplification status, MYC promoter methylation, and MYC mRNA expression in several cancer types. In addition, we show that tumor proliferation and immune evasion are likely contributors to this reduction in survival. Finally, we developed a MYC activity signature for liquid tumors in which MYC translocation is commonly observed, suggesting that our approach can be applied to different types of genomic alterations. In conclusion, we developed a MYC activity score that captures MYC pathway activity and is clinically relevant.

Implications:

By using cancer type–specific MYC activity profiles, we were able to assess MYC activity across many more tumor types than previously investigated. The range of different MYC-related alterations captured by our MYC activity score can be used to facilitate the application of future MYC inhibitors and aid physicians to preselect patients for targeted therapy.
A Tumor Suppressor Enhancer ofPTENin T-cell Development and Leukemia
Authors: Tottone Luca , Lancho Olga , Loh Jui-Wan , Singh Amartya , Kimura Shunsuke , Roels Juliette , Kuchmiy Anna , Strubbe Steven , Lawlor Matthew A. , da Silva-Diz Victoria , Luo Shirley , Gachet Stéphanie , García-Prieto Carlos A. , Hagelaar Rico , Esteller Manel , Meijerink Jules P.P. , Soulier Jean , Taghon Tom , Van Vlierberghe Pieter , Mullighan Charles G. , Khiabanian Hossein , Rocha Pedro P. , Herranz Daniel
Published: November 2020

Long-range oncogenic enhancers play an important role in cancer. Yet, whether similar regulation of tumor suppressor genes is relevant remains unclear. Loss of expression of PTEN is associated with the pathogenesis of various cancers, including T-cell acute lymphoblastic leukemia (T-ALL). Here, we identify a highly conserved distal enhancer (PE) that interacts with the PTEN promoter in multiple hematopoietic populations, including T cells, and acts as a hub of relevant transcription factors in T-ALL. Consistently, loss of PE leads to reduced PTEN levels in T-ALL cells. Moreover, PE-null mice show reduced Pten levels in thymocytes and accelerated development of NOTCH1-induced T-ALL. Furthermore, secondary loss of PE in established leukemias leads to accelerated progression and a gene expression signature driven by Pten loss. Finally, we uncovered recurrent deletions encompassing PE in T-ALL, which are associated with decreased PTEN levels. Altogether, our results identify PE as the first long-range tumor suppressor enhancer directly implicated in cancer.

Significance:

Here, we identify a PTEN enhancer that is recurrently deleted in patients with T-ALL. Loss of this enhancer leads to reduced PTEN levels in T cells together with accelerated generation and progression of NOTCH1-induced leukemia in vivo. These results uncover long-range regulation of tumor suppressor genes as a relevant mechanism in cancer.

This article is highlighted in the In This Issue feature, p. 1
Vitamin D in Preterm and Full-Term Infants
Authors: Abrams Steven A.
Published: November 2020

Vitamin D is necessary for the active (transcellular) absorption of calcium and for skeletal health. Inadequate vitamin D in infants leads to increased risks of poor bone mineralization and ultimately rickets. Rickets is uncommon in full-term infants with a much higher risk in very premature infants. However, the primary cause of rickets in premature infants is a deficiency of calcium and phosphorus, not vitamin D. Available research, as well as most guidelines, recommend an intake of 400 IU daily of vitamin D as adequate for bone health in preterm and full-term infants. Higher doses have not been consistently shown to have specific clinical benefits for healthy infants. There are no strong data to support either routine testing of serum 25-hydroxyvitamin D or targeting high serum 25-hydroxyvitamin D levels (e.g., 30 ng/mL) in healthy preterm or full-term infants. Vitamin D is commonly provided to infants via drops for breastfed babies or via infant formula, although alternative dosing approaches exist for breastfed infants, which some families may prefer. These include the use of drops placed on the mother’s breast, dissolvable doses, and high maternal doses (approximately 6,400 IU daily). Infant formula contains vitamin D, and most infants will reach an intake from formula of about 400 IU daily within the first 2 months of life if they are consuming routine cow milk-based formula. Although vitamin D toxicity is very uncommon, caution should be used to avoid extremely concentrated high doses found in some commercially available drops. Infants with liver or kidney disease may need special attention to vitamin D intake and status. Further research is needed to define the role of vitamin D in non-bone health outcomes of infants and to identify methods to enhance compliance with current recommendations for vitamin D intake in infants.