bluuebunny/crossref_metadata_2025 huggingface dataset:
Trends in drowning mortality in Portugal from 1992 to 2019: comparing Global Burden of Disease and national data
Authors: Queiroga Ana Catarina , Seabra Rui , Franklin Richard Charles , Peden Amy E
Published: December 2021

Introduction

Imprecise data systems hinder understanding of drowning burden, even in high-income countries like Portugal, that have a well-implemented death certificate system. Consequently, national studies on drowning mortality are scarce. We aimed to explore drowning mortality in Portugal using national data and to compare these to Global Burden of Disease (GBD) estimates.

Methods

Data were obtained from the National Institute of Statistics (INE) for 1992–2019, using International Classification of Diseases (ICD)-9 and ICD-10 codes, by sex, age group and cause (unintentional; water transport and intentional). GBD unintentional drowning data were obtained online. Age-standardised drowning rates were calculated and compared.

Results

INE data showed 6057 drowning deaths, 4327 classified as unintentional (75.2% male; 36.7% 35–64 years; 31.5% 65+years; 15.2% 0–19 years). Following 2001, an increase in accidental drowning mortality and corresponding decrease in undetermined intent was observed, coincident with Portugal’s ICD-10 implementation. GBD modelled estimates followed a downward trend at an overall rate of decrease of −0.41/decade (95% CI (−0.45 to –0.37); R2adj=0.94; p<0.05). Conversely, INE data showed an increase in the rate of drowning deaths over the last decade (0.35/decade; 95% CI (−0.18 to 0.89)). GBD estimates were significantly different from the INE dataset (alpha=0.05), either underestimating as much as 0.567*INE in 1996 or overestimating as much as 1.473*INE in 2011.

Conclusions

While GBD mortality data estimates are valuable in the absence of routinely collected data, they smooth variations, concealing key advocacy opportunities. Investment in country-level drowning registries enables in-depth analysis of incident circumstances. Such data are essential to informing National Water Safety Plans.
Kerr–Schild–Kundt metrics in generic gravity theories with modified Horndeski couplings
Authors: Gürses Metin , Heydarzade Yaghoub , Şentürk Çetin
Published: December 2021

The Kerr–Schild–Kundt (KSK) metrics are known to be one of the universal metrics in general relativity, which means that they solve the vacuum field equations of any gravity theory constructed from the curvature tensor and its higher-order covariant derivatives. There is yet no complete proof that these metrics are universal in the presence of matter fields such as electromagnetic and/or scalar fields. In order to get some insight into what happens when we extend the “universality theorem” to the case in which the electromagnetic field is present, as a first step, we study the KSK class of metrics in the context of modified Horndeski theories with Maxwell’s field. We obtain exact solutions of these theories representing the pp-waves and AdS-plane waves in arbitrary D dimensions.
Off diagonal charged scalar couplings with the Z boson: Zee-type models as an example
Authors: Florentino Ricardo R. , Romão Jorge C. , Silva João P.
Published: December 2021

Models with scalar doublets and charged scalar singlets have the interesting property that they have couplings between one Z boson and two charged scalars of different masses. This property is often ignored in phenomenological analysis, as it is absent from models with only extra scalar doublets. We explore this issue in detail, considering $$h \rightarrow Z \gamma $$

h
→
Z
γ

, $$B \rightarrow X_s \gamma $$

B
→

X
s

γ

, and the decay of a heavy charged scalar into a lighter one and a Z boson. We propose that the latter be actively searched for at the LHC, using the scalar sector of the Zee-type models as a prototype and proposing benchmark points which obey all current experimental data, and could be within reach of the LHC.
A plain-text independent color image encryption system with multi-thread permutation and multi-channel diffusion
Authors: Zhang Hao , Li Zhenyu , Yan Pengfei , Wang Xiaoqing , Wang Xingyuan
Published: December 2021

In this paper, we present a novel multi-threaded parallel permutation and channel-combined diffusion for image encryption which is independent of plain text. In our proposed method, the coupled map lattice is used to generate the key sequences for multi-thread permutation and diffusion. Then intra- and inter-thread permutations are achieved using multi-threading in combination with the tent mapping. For the subsequent diffusion, this paper introduces a method based on channel-combined diffusing which simultaneously diffuses three channels. Experimental results indicate a high encryption performance with the capability of effectively resisting the known plain text and differential attacks. Our proposed method also has a lower computational complexity which enables its applicability in practical scenarios.
Percolation on interdependent networks with different group size distributions under targeted attack
Authors: Zang Weifei , Ji Xinsheng , Liu Shuxin , Li Yingle
Published: December 2021

Traditional research studies on interdependent networks with groups ignore the relationship between nodes in dependency groups. In real-world networks, nodes in the same group may support each other through cooperation and tend to fail or survive together. In this paper, based on the framework of group percolation, a cascading failure model on interdependent networks with cooperative dependency groups under targeted attacks is proposed, and the effect of group size distributions on the robustness of interdependent networks is investigated. The mutually giant component and phase transition point of networks with different group size distributions are analyzed. The effectiveness of the theory is verified through simulations. Results show that the robustness of interdependent networks with cooperative dependency groups can be enhanced by increasing the heterogeneity between groups under targeted attacks. The theory can well predict the numerical simulation results. This model provides some theoretical guidance for designing robust interdependent systems in real world.
MODEL UNCERTAINTY AND FINANCIAL FRICTIONS: IMPLICATIONS FOR OPTIMAL MONETARY POLICY
Authors: KANTUR ZEYNEP , ÖZCAN GÜLSERİM
Published: December 2021

The last decades proved that policymaking without considering uncertainty is impracticable. In an environment of uncertainty, policymakers have doubts about the policy models they routinely use. This paper focuses specifically on the situation where uncertainty on the financial side of the economy leads to misspecification in the policy model. We describe a coherent strategy for policymakers who are averse to model misspecification and analyze optimal policy design in the face of Knightian uncertainty. To do so, we augment a financial dynamic stochastic general equilibrium model with model misspecification in a simple minimax framework where the central bank plays a zero-sum game versus a hypothetical evil agent. The policy is tailored to insure against the worst-case outcomes. We show that model ambiguity on the financial side requires a passive monetary policy stance. However, if the uncertainty originates from the supply side of the economy, an aggressive response of interest rate is required. We also show the impact of an additional macroprudential tool on the dynamics of the economy.
The effect of hidden-color channel on the structure of strangeness S = −1 dibaryon
Authors: Zhang T. G. , Wang Y. H. , Chen L. N. , Dai L. R.
Published: December 2021

The study of dibaryons has gained extensive attention both theoretically and experimentally since the confirmation of six-quark exotic [Formula: see text] dibaryon (with spin 3 and isospin 0) by recent COSY experiment. We ever proposed the chiral SU(3) quark model and predicted the binding energy of the [Formula: see text] system, in which the hidden-color channel was shown to play an important role in its structure. In this work, we further study the structure of [Formula: see text] dibaryon (with spin 0 and isospin [Formula: see text]) and strangeness [Formula: see text] under the chiral SU(3) quark model. The results show that hidden-color channel has an obvious influence on the binding energy of [Formula: see text] system.
An Efficient Tongue Segmentation Model Based on U-Net Framework
Authors: Ruan Qunsheng , Wu Qingfeng , Yao Junfeng , Wang Yingdong , Tseng Hsien-Wei , Zhang Zhiling
Published: December 2021

In the intelligently processing of the tongue image, one of the most important tasks is to accurately segment the tongue body from a whole tongue image, and the good quality of tongue body edge processing is of great significance for the relevant tongue feature extraction. To improve the performance of the segmentation model for tongue images, we propose an efficient tongue segmentation model based on U-Net. Three important studies are launched, including optimizing the model’s main network, innovating a new network to specially handle tongue edge cutting and proposing a weighted binary cross-entropy loss function. The purpose of optimizing the tongue image main segmentation network is to make the model recognize the foreground and background features for the tongue image as well as possible. A novel tongue edge segmentation network is used to focus on handling the tongue edge because the edge of the tongue contains a number of important information. Furthermore, the advantageous loss function proposed is to be adopted to enhance the pixel supervision corresponding to tongue images. Moreover, thanks to a lack of tongue image resources on Traditional Chinese Medicine (TCM), some special measures are adopted to augment training samples.

Various comparing experiments on two datasets were conducted to verify the performance of the segmentation model. The experimental results indicate that the loss rate of our model converges faster than the others. It is proved that our model has better stability and robustness of segmentation for tongue image from poor environment. The experimental results also indicate that our model outperforms the state-of-the-art ones in aspects of the two most important tongue image segmentation indexes: IoU and Dice. Moreover, experimental results on augmentation samples demonstrate our model have better performances.
The Two-Stage Recognition Method Based on Texture Signals of the Heterogeneous Unsteady Iris
Authors: Liu Shuai , Liu Yuanning , Zhu Xiaodong , Liu Jing , Huo Guang , Zhou Zhiyong
Published: December 2021

In this paper, a two-stage multi-category recognition structure based on texture features is proposed. This method can solve the problem of the decline in recognition accuracy in the scene of lightweight training samples. Besides, the problem of recognition effect different in the same recognition structure caused by the unsteady iris can also be solved. In this paper’s structure, digitized values of the edge shape in the iris texture of the image are set as the texture trend feature, while the differences between the gray values of the image obtained by convolution are set as the grayscale difference feature. Furthermore, the texture trend feature is used in the first-stage recognition. The template category that does not match the tested iris is the elimination category, and the remaining categories are uncertain categories. Whereas, in the second-stage recognition, uncertain categories are adopted to determine the iris recognition conclusion through the grayscale difference feature. Then, the experiment results using the JLU iris library show that the method in this paper can be highly efficient in multi-category heterogeneous iris recognition under lightweight training samples and unsteady state.
HHO-Based Vector Quantization Technique for Biomedical Image Compression in Cloud Computing
Authors: Kumar T. Satish , Jothilakshmi S. , James Batholomew C. , Prakash M. , Arulkumar N. , Rekha C.
Published: December 2021

In the present digital era, the exploitation of medical technologies and massive generation of medical data using different imaging modalities, adequate storage, management, and transmission of biomedical images necessitate image compression techniques. Vector quantization (VQ) is an effective image compression approach, and the widely employed VQ technique is Linde–Buzo–Gray (LBG), which generates local optimum codebooks for image compression. The codebook construction is treated as an optimization issue solved with utilization of metaheuristic optimization techniques. In this view, this paper designs an effective biomedical image compression technique in the cloud computing (CC) environment using Harris Hawks Optimization (HHO)-based LBG techniques. The HHO-LBG algorithm achieves a smooth transition among exploration as well as exploitation. To investigate the better performance of the HHO-LBG technique, an extensive set of simulations was carried out on benchmark biomedical images. The proposed HHO-LBG technique has accomplished promising results in terms of compression performance and reconstructed image quality.
T2FRF Filter: An Effective Algorithm for the Restoration of Fingerprint Images
Authors: Antony Joycy K. , Kanagalakshmi K.
Published: December 2021

Images captured in dim light are hardly satisfactory and increasing the International Organization for Standardization (ISO) for a short duration of exposure makes them noisy. The image restoration methods have a wide range of applications in the field of medical imaging, computer vision, remote sensing, and graphic design. Although the use of flash improves the lighting, it changed the image tone besides developing unnecessary highlight and shadow. Thus, these drawbacks are overcome using the image restoration methods that recovered the image with high quality from the degraded observation. The main challenge in the image restoration approach is recovering the degraded image contaminated with the noise. In this research, an effective algorithm, named T2FRF filter, is developed for the restoration of the image. The noisy pixel is identified from the input fingerprint image using Deep Convolutional Neural Network (Deep CNN), which is trained using the neighboring pixels. The Rider Optimization Algorithm (ROA) is used for the removal of the noisy pixel in the image. The enhancement of the pixel is performed using the type II fuzzy system. The developed T2FRF filter is measured using the metrics, such as correlation coefficient and Peak Signal to Noise Ratio (PSNR) for evaluating the performance. When compared with the existing image restoration method, the developed method obtained a maximum correlation coefficient of 0.7504 and a maximum PSNR of 28.2467dB, respectively.
A Novel Ensemble Stacking Classification of Genetic Variations Using Machine Learning Algorithms
Authors: Jahnavi Yeturu , Elango Poongothai , Raja S. P. , Nagendra Kumar P.
Published: December 2021

Genetics is the clinical review of congenital mutation, where the principal advantage of analyzing genetic mutation of humans is the exploration, analysis, interpretation and description of the genetic transmitted and inherited effect of several diseases such as cancer, diabetes and heart diseases. Cancer is the most troublesome and disordered affliction as the proportion of cancer sufferers is growing massively. Identification and discrimination of the mutations that impart to the enlargement of tumor from the unbiased mutations is difficult, as majority tumors of cancer are able to exercise genetic mutations. The genetic mutations are systematized and categorized to sort the cancer by way of medical observations and considering clinical studies. At the present time, genetic mutations are being annotated and these interpretations are being accomplished either manually or using the existing primary algorithms. Evaluation and classification of each and every individual genetic mutation was basically predicated on evidence from documented content built on medical literature. Consequently, as a means to build genetic mutations, basically, depending on the clinical evidences persists a challenging task. There exist various algorithms such as one hot encoding technique is used to derive features from genes and their variations, TF-IDF is used to extract features from the clinical text data. In order to increase the accuracy of the classification, machine learning algorithms such as support vector machine, logistic regression, Naive Bayes, etc., are experimented. A stacking model classifier has been developed to increase the accuracy. The proposed stacking model classifier has obtained the log loss 0.8436 and 0.8572 for cross-validation data set and test data set, respectively. By the experimentation, it has been proved that the proposed stacking model classifier outperforms the existing algorithms in terms of log loss. Basically, minimum log loss refers to the efficient model. Here the log loss has been reduced to less than 1 by using the proposed stacking model classifier. The performance of these algorithms can be gauged on the basis of the various measures like multi-class log loss.
Preparation of Gentamicin Sulfate Nanoparticles using Eudragit RS-100 and Evaluation of Their Physicochemical Properties
Authors: Nejati Ladan , Maram Nader Shakiba , Ahmady Amanollah Zarei
Published: December 2021

Improving permeability and absorption of drugs are critical research challenges in pharmaceutical science. Gentamicin sulfate is an aminoglycoside antibiotic, which is very active against gram-negative bacteria; however, it has very poor bioavailability. This study aimed to prepare gentamicin nanoparticles with the intention of increased bioavailability. Accordingly, Eudragit RS-100 nanoparticles loaded with gentamicin sulfate were prepared by the double emulsification and solvent evaporation method, a proper technique for encapsulating hydrophilic molecules. Nanoparticles’ suspensions with polymer to drug ratios of 1:1 ([Formula: see text] and 2:1 ([Formula: see text]) were prepared, lyophilized and evaluated for their production yield, physicochemical properties and morphology. The mean particle size was 195.67[Formula: see text]nm and 228[Formula: see text]nm for [Formula: see text] and [Formula: see text], respectively. The formulations’ loading efficiencies were relatively high (85.73 for [Formula: see text] and 85.20 for [Formula: see text]). The nanoparticles’ surface charge (+40.5[Formula: see text]mV) was sufficient to inhibit their aggregation and facilitate the nanoparticles’ absorption through the gastrointestinal tract. The results of differential scanning calorimetry (DSC) and Fourier transform infrared spectroscopy (FT-IR) revealed that drug and polymer stabilized each other by physical interactions between their functional groups. Both formulations presented an initial burst drug release of nearly 20% after 30[Formula: see text]min in phosphate buffer (pH = 7.4). After 24[Formula: see text]h, [Formula: see text] did not release the drug completely, while [Formula: see text] released the whole drug. Overall, nanoparticles with proper characteristics were obtained. This study puts forward the necessity of conducting further research in order to explore the intestinal absorption of these nanoparticles and the possibility of being utilized for oral administration of gentamicin sulfate.
Hilbert bundles with ends
Authors: Kato Tsuyoshi , Kishimoto Daisuke , Tsutaya Mitsunobu
Published: December 2021

Given a countable metric space, we can consider its end. Then a basis of a Hilbert space indexed by the metric space defines an end of the Hilbert space, which is a new notion and different from an end as a metric space. Such an indexed basis also defines unitary operators of finite propagation, and these operators preserve an end of a Hilbert space. Then, we can define a Hilbert bundle with end, which lightens up new structures of Hilbert bundles. In a special case, we can define characteristic classes of Hilbert bundles with ends, which are new invariants of Hilbert bundles. We show Hilbert bundles with ends appear in natural contexts. First, we generalize the pushforward of a vector bundle along a finite covering to an infinite covering, which is a Hilbert bundle with end under a mild condition. Then we compute characteristic classes of some pushforwards along infinite coverings. Next, we will show the spectral decompositions of nice differential operators give rise to Hilbert bundles with ends, which elucidate new features of spectral decompositions. The spectral decompositions we will consider are the Fourier transform and the harmonic oscillators.
Homologically visible closed geodesics on complete surfaces
Authors: Allais Simon , Soethe Tobias
Published: December 2021

In this paper, we give multiple situations when having one or two geometrically distinct closed geodesics on a complete Riemannian cylinder, a complete Möbius band or a complete Riemannian plane leads to having infinitely many geometrically distinct closed geodesics. In particular, we prove that any complete cylinder with isolated closed geodesics has zero, one or infinitely many homologically visible closed geodesics; this answers a question of Alberto Abbondandolo.
Using Ensemble and TOPSIS with AHP for Classification and Selection of Web Services
Authors: Pandey Mithilesh , Jalal Sunita , Negi Chetan Singh , Yadav Dharmendra Kumar
Published: December 2021

Due to the increasing number of Web Services with the same functionality, selecting a Web Service that best serves the needs of the Web Client has become a tremendously challenging task. Present approaches use non-functional parameters of the Web Services but they do not consider any preprocessing of the set of functionally Similar Web Services. The lack of preprocessing results in increased use of computational resources due to unnecessary processing of Web Services that have a very low to no chance of satisfying the consumer’s requirements. In this paper, we propose an Ensemble classification method for preprocessing and a Web Service Selection method based on the Quality of Service (QoS) parameters. Once the most eligible Web Services are enumerated through classification, they are ranked using the Technique of Order Preference by Similarity to Ideal Solution (TOPSIS) method with Analytic Hierarchy Process (AHP) used for weight calculation. A prototype of the method is developed, and experiments are conducted on a real-world Web Services dataset. Results demonstrate the feasibility of the proposed method.
Evaluation of the Sealing Ability of Direct versus Direct‐Indirect Veneer Techniques: An In Vitro Study
Authors: Abdulrahman Mewan Salahalddin
Published: December 2021

Backgrounds. Marginal discoloration, microleakage, wear, and marginal fractures are all prevalent problems with composite veneers, and this scenario leads the esthetic outcome to deteriorate with time, resulting in patient discontent. Aim of the Study. The study’s goal was to determine the marginal sealing ability of composite laminate veneers when employing two types of veneer techniques: direct and direct‐indirect veneers, as well as two types of composite resin: nanohybrid and microfilled composite resin restorations, using dye penetration method. Materials and Methods. In this study, forty extracted human teeth were utilized. Following a standardized veneer preparation on the labial surface of the teeth, they were separated into two groups of 20 teeth each, using the following composite application techniques: group A: direct veneers and group B: direct‐indirect veneers. Following that, each major group was separated into two subgroups of ten teeth each, based on the type of composite employed: subgroup 1 used nanohybrid composite resin, while subgroup 2 used microfilled composite resin. All of the samples were kept in distilled water, thermocycled, and soaked in 2% basic fuchsine dye. These specimens were sectioned and examined under a stereomicroscope for dye penetration at the gingival margin. The data was analyzed using independent T‐tests using SPSS 22. Result. Using direct‐indirect veneer technique with nanohybrid composite resin material resulted in the most negligible dye penetration at the gingival margin, while using direct veneer technique with microfilled composite resin material resulted in the maximum dye penetration. For both composite materials, gingival microleakage was lower when using the direct‐indirect veneer technique than when using the direct technique, and the difference was statistically significant (P < 0.05). In both techniques, gingival microleakage was lower with nanohybrid composite than with microfilled composite, and the difference was statistically highly significant (P = 0.001). Conclusion. The sealing ability of the gingival margin of tooth/composite interface is better when applying direct‐indirect veneer technique with nanohybrid composite resin than that of direct veneer technique with microfilled composite resin material.
[Retracted] A Survey Research on the Willingness of Gynecologists to Employ Mobile Health Applications
Authors: Alazzam Malik Bader , Al-Radaideh Ahmad Tawfig , Alhamarnah Raed Ahmed , Alassery Fawaz , Hajjej Fahima , Halasa Azmi
Published: December 2021

In gynecological care, mHealth (mobile health) technology may play an important role. Medical professionals’ willingness to use this technology is the key to its acceptance. Most doctors utilize mobile health technology; however, there is still room for improvement in the use of mHealth. Gynecologists were asked to participate in this research to see how open they were to use mobile health technologies. In this descriptive‐analytical investigation, the researchers determined the average scores for each variable. The overall mean for preparedness to embrace mobile medical technology is 1.8 out of 2, as shown in Table 1. When it came to their desire to embrace mobile health technology, doctors’ years of experience correlated negatively with their age. According to our findings, the amount of interest in mobile health technology is high. Patients’ private information must be protected throughout the usage of this technology though. Mobile health technology may effectively reach patients in remote areas, but it is not a substitute for face‐to‐face encounters with medical professionals.
Effects of Health Literacy Intervention on Health Literacy Level and Glucolipid Metabolism of Diabetic Patients in Mainland China: A Systematic Review and Meta-Analysis
Authors: Chen Yangli , Ran Xue , Chen Yalan , Jiang Kui
Published: December 2021

Objective. To systematically evaluate the effects of health literacy intervention on health literacy level and glycolipid metabolism of people with diabetes in mainland China. Methods. A systematic review of journal articles discussing diabetes and health literacy was performed by searching PubMed, Embase, the Science Citation Index Expanded (SCIE) database of Web of Science, the China National Knowledge Infrastructure (CNKI) database, the Chinese Scientific and Technical Journals database (CQVIP), and the Wanfang database. Cochrane Effective Practice and Organization of Care Review Group (EPOC) standards were applied for quality assessment. A meta-analysis was performed using Stata 12.0 software. Results. A total of 44 articles, including seven controlled before-and-after trials (CBAs), 27 randomized controlled trials (RCTs), and 10 nonrandomized controlled trials (non-RCTs), were included. The results showed that (1) health literacy level in the intervention group was improved compared with the preintervention and the control group; (2) fasting plasma glucose (FPG) (standardized mean difference

SMD

=
−
1.85

, 95% CI: −2.28, −1.42), 2-hour plasma glucose (2hPG) (

SMD
=
−
2.18

, 95% CI: −2.68, −1.68), and HbA1c (weighted mean difference

WMD

=
−
1.21

, 95% CI: −1.48, −0.94) were significantly reduced in the intervention group; (3) total cholesterol (TC) (

WMD
=
−
0.43

, 95% CI: −0.64, −0.23) was significantly reduced in the intervention group, although there were no statistically significant differences for triglycerides (TG) (

WMD
=
−
0.34

, 95% CI: −0.73, 0.05), low-density lipoprotein cholesterol (LDL-C) (

WMD
=
−
0.20

, 95% CI: −0.46, 0.07), or high-density lipoprotein cholesterol (HDL-C) (

WMD
=
−
0.06

, 95% CI: −0.29, 0.17). Conclusion. Intervention based on health literacy can effectively improve health literacy levels and reduce glucose metabolism and TC level among people with diabetes mellitus, although it has no significant effect on TG, LDL-C, or HDL-C.
Research on Quantitative Evaluation Methods and Influencing Factors of Natural Gas Reservoir Development
Authors: Li Haitao , Yu Guo , Chen Yanru , Zhang Dongming
Published: December 2021

Current methods of evaluating the effects of gas reservoir exploitation primarily focus on evaluating production statistics of a well or field, and they often have a certain subjectivity. In order to further analyze key indexes that affect a gas reservoir during production, this paper considered the characteristic parameters of different types of gas reservoirs and established an index system of evaluating a gas reservoir “exploitation effect” from the three aspects of gas reservoir characteristics, rock characteristics, and economic benefits. There are numerous factors affecting the exploitation effect of a gas reservoir. The relationships between different factors are complicated, and the evaluation result of each factor can also be vague. A fuzzy optimization theoretical model for gas reservoir evaluation and optimization was established on the basis of a quantitative study on the evaluation parameters in fuzzy mathematics. In order to clearly understand the influence of each factor on the gas reservoir exploitation effect, numerical simulation was used to perform a multifactor numerical simulation study of the quantitative sensitivity to determine the sequence of different influencing factors in terms of influencing the gas reservoir exploitation effect. This study provides a quantitative scientific basis for the evaluation of gas reservoir exploitation effect.
Design and Application of Mobile Education Information System Based on Psychological Education
Authors: Ko Chun-Hung , Shen Yucheng
Published: December 2021

With the continuous development of society, the pressure of human beings is increasing, and the problem of psychological counseling for school students is getting more and more serious, which has brought great challenges to the education and management of school students. Universities should cultivate students’ professional ability on knowledge and practical skills; we should pay more attention to their psychological counseling and develop and design a simple and efficient learning environment. It is very necessary to establish a psychological evaluation system for college students. This article is based on the design and application of the mobile education information system for psychological education. It highlights that the current psychological counseling problems in school education are indispensable. To better manage the psychological counseling problems faced by many students, 67% of the students have many psychological problems, and the mental health of students in school education and psychological counseling have become the common concern and urgent problems of all college managers. This paper uses the methods of literature research, behavior interview, and experimental investigation to investigate the complementary relationship between the connotation of education and psychological counseling from the data of the fuzzy integral model of psychological counseling, so as to pay more attention to the students’ mental health problems and make the students grow up healthily. The experimental results of this article show that there is still a lot of room for improvement in the use of mobile education information systems to improve their ability to carry out psychological counseling work.
IoT-IE: An Information-Entropy-Based Approach to Traffic Anomaly Detection in Internet of Things
Authors: Sun Yizhen , Yu Jianjiang , Tian Jianwei , Chen Zhongwei , Wang Weiping , Zhang Shigeng
Published: December 2021

Security issues related to the Internet of Things (IoTs) have attracted much attention in many fields in recent years. One important problem in IoT security is to recognize the type of IoT devices, according to which different strategies can be designed to enhance the security of IoT applications. However, existing IoT device recognition approaches rarely consider traffic attacks, which might change the pattern of traffic and consequently decrease the recognition accuracy of different IoT devices. In this work, we first validate by experiments that traffic attacks indeed decrease the recognition accuracy of existing IoT device recognition approaches; then, we propose an approach called IoT-IE that combines information entropy of different traffic features to detect traffic anomaly. We then enhance the robustness of IoT device recognition by detecting and ignoring the abnormal traffic detected by our approach. Experimental evaluations show that IoT-IE can effectively detect abnormal behaviors of IoT devices in the traffic under eight different types of attacks, achieving a high accuracy value of 0.977 and a low false positive rate of 0.011. It also achieves an accuracy of 0.969 in a multiclassification experiment with 7 different types of attacks.
Angle-Resolved Intensity of In-Axis/Off-Axis Polarized Micro-Raman Spectroscopy for Monocrystalline Silicon
Authors: Chang Ying , He Saisai , Sun Mingyuan , Xiao Aixia , Zhao Jiaxin , Ma Lulu , Qiu Wei
Published: December 2021

Monocrystalline silicon (c-Si) is still an important material related to microelectronics/optoelectronics. The nondestructive measurement of the c-Si material and its microstructure is commonly required in scientific research and industrial applications, for which Raman spectroscopy is an indispensable method. However, Raman measurements based on the specific fixed Raman geometry/polarization configuration are limited for the quantified analysis of c-Si performance, which makes it difficult to meet the high-end requirements of advanced silicon-based microelectronics and optoelectronics. Angle-resolved Raman measurements have become a new trend of experimental analysis in the field of materials, physics, mechanics, and optics. In this paper, the characteristics of the angle-resolved polarized Raman scattering of c-Si under the in-axis and off-axis configurations are systematically analyzed. A general theoretical model of the angle-resolved Raman intensity is established, which includes several alterable angle parameters, including the inclination angle, rotation angle of the sample, and polarization directions of the incident laser and scattered light. The diversification of the Raman intensity is given at different angles for various geometries and polarization configurations. The theoretical model is verified and calibrated by typical experiments. In addition, this work provides a reliable basis for the analysis of complex polarized Raman experiments on silicon-based structures.
Mechanical Behavior, Energy Release, and Crack Distribution Characteristics of Water‐Saturated Phyllite under Triaxial Cyclic Loading
Authors: Zhou Yang , Su Shengrui , Li Peng
Published: December 2021

Many geological engineering hazards are closely related to the dynamic mechanical behaviors of rock materials. However, the dynamic mechanical behaviors of phyllite are less studied. In this study, we have carried out a series of triaxial cyclic tests on dry and water‐saturated phyllite by employing the MTS 815 servohydraulic testing system and AE testing equipment to reveal the mechanical behavior, energy release, and crack distribution characteristics of phyllite. Results show that phyllite is a water‐sensitive rock. Water and cyclic loading substantially affect the compressive strength, crack damage stress, deformation parameters, dilatancy, energy release, and crack distribution characteristics of phyllite. Furthermore, based on the dissipated energy, a new damage variable for phyllite is established. The critical damage variable for phyllite is approximately 0.80; this variable can be used as an index to predict the failure of phyllite. The water saturation effect of phyllite is very obvious; that is, it results in the weakness of mechanical properties of phyllite and changes the AE energy release and crack distribution characteristics of phyllite. This research can provide guidance for engineering construction and disaster prevention and control.
Local Surface Plasmonic Resonance, Surface-Enhanced Raman Scattering, Photoluminescence, and Photocatalytic Activity of Hydrothermal Titanate Nanotubes Coated with Ag Nanoparticles
Authors: Thuy Pham Thi , Minh Vo Cao , Mai Vo Quang , Tuan Nguyen Tri , Van Tuan Pham , Cuong Hoang Ba , Sang Nguyen Xuan
Published: December 2021

In this work, we successfully fabricated homogeneous hydrothermal titanate nanotubes (TNTs) coated with Ag nanoparticles (NPs) and elucidated the role of Ag NPs on local surface plasmonic resonance, surface-enhanced Raman scattering, and the enhanced photocatalytic activity of TNT/Ag nanocomposite. The results showed that the photodegradation process reached equilibrium in just ~5 min for the TNT/Ag nanocomposite, which was much shorter than that of the TNT sample (~90 min). TEM micrographs showed that Ag NPs were well dispersed on the walls of the nanotubes. XRD patterns and Raman spectra indicated that the TNTs were in the monoclinic structure of H2Ti3O7. Furthermore, Raman active modes of the TNTs were significantly enhanced in the TNT/Ag sample, which was attributed to surface-enhanced Raman spectroscopy. The enhanced photocatalytic activity of the TNT/Ag sample was explained by UV-vis diffuse reflectance spectroscopy and photoluminescence emission spectroscopy, which showed local surface plasmonic resonance-induced visible light absorption enhancement and effective charge separation, respectively.
Genetic Parameters for Determining Useful Parents in Mungbean (Vigna radiata (L.) Wilczek) Breeding for Early Maturity, Small Seed Size, and High Seed Yield
Authors: Trustinah  , Iswanto Rudi , Hapsari Ratri T. , Nugrahaeni Novita , Soehendi Rudy , Sundari Titik , Suhartina  , Indriani Febria C. , Mejaya Made J.
Published: December 2021

Early maturity, small seed size, and high seed yield are important characters of mungbean in Indonesia. The objective of the study was to determine the useful parents in mungbean crosses for early maturity, small seed size, and high seed yield varieties by estimating the genetic parameters and their inheritance. The study was conducted at the ILETRI, Malang, East Java, Indonesia, during the dry season of 2014. 20 F1 and 5 parents were evaluated using a randomized block design, repeated three times. Results of the study showed that all observed traits showed the importance of both additive and dominance gene effects. The relative value of general combining ability (GCA) was greater than specific combining ability (SCA) for number of pod clusters per plant, number of branches per plant, plant height, days to maturity, and 100-seed weight which indicated the importance of additive gene effect. The dominance gene effect occurred on number of pods and seed yield per plant. Among five parents, G3 was the best combiner for all the observed characters except pod length; therefore, G3 could be exploited for late maturity, small seed size, high number of branches and pod cluster, and high seed yield. G5 has a high GCA for 100-seed weight. G1 and G2 have good GCA for early maturity. G3 and G5 genotypes are useful as parents in mungbean breeding for small and large seed size varieties, respectively. The best combination for seed yield was G2 × G3 and G3 × G1 crosses and could be proceeded with selection for early maturity, small seed size, and high seed yield varieties.
[Retracted] Implementation of Machine Learning Models for the Prevention of Kidney Diseases (CKD) or Their Derivatives
Authors: Twarish Alhamazani Khalid , Alshudukhi Jalawi , Aljaloud Saud , Abebaw Solomon
Published: December 2021

Chronic kidney disease (CKD) is a global health issue with a high rate of morbidity and mortality and a high rate of disease progression. Because there are no visible symptoms in the early stages of CKD, patients frequently go unnoticed. The early detection of CKD allows patients to receive timely treatment, slowing the disease’s progression. Due to its rapid recognition performance and accuracy, machine learning models can effectively assist physicians in achieving this goal. We propose a machine learning methodology for the CKD diagnosis in this paper. This information was completely anonymized. As a reference, the CRISP‐DM® model (Cross industry standard process for data mining) was used. The data were processed in its entirety in the cloud on the Azure platform, where the sample data was unbalanced. Then the processes for exploration and analysis were carried out. According to what we have learned, the data were balanced using the SMOTE technique. Four matching algorithms were used after the data balancing was completed successfully. Artificial intelligence (AI) (logistic regression, decision forest, neural network, and jungle of decisions). The decision forest outperformed the other machine learning models with a score of 92%, indicating that the approach used in this study provides a good baseline for solutions in the production.
Deployment of Background Knowledge and Performance in Comprehension Passage Reading among Primary School Learners in Vihiga County, Kenya
Authors: Anyiendah Mary Susan , Odundo Paul A. , Kibui Agnes W.
Published: December 2021

Background. Primary school learners in Vihiga County have been recording a lower mean score in English language examinations than their counterparts in neighbouring counties, with the score being lower in comprehension passage than in grammar sections. Few previous studies conducted in Kenya have investigated the issue from the instructional dimension, thereby limiting stakeholders’ understanding of the issue and delaying appropriate interventions. Aim. To determine how the deployment of learners’ background knowledge influences performance in reading comprehension passages. Method. Solomon Four-Group Design guided the study. Data were sourced in mid-2017 from standard six learners and English language teachers. Regression analysis generated two models, one for the experimental and control groups, each. Results. In both models, deployment of background knowledge had a significant positive effect on the performance in reading comprehension passages, which prompted rejection of the null hypothesis. However, the effect was stronger in the experimental group than in the control group. The variation was attributed to training provided to the experimental group teachers, which improved their skills in activating learners’ background knowledge. Conclusions. Activating learners’ background knowledge is a vital antecedent to better performance in reading comprehension passages and the English language. Although prereading vocabulary is vital for the activation of learners’ background knowledge, overreliance on a single strategy to activate learners’ background knowledge undermines optimal deployment of background knowledge skills in reading, albeit with implications on performance.
Research on Continuous Wave Electromagnetic Effect in Swept Frequency Radar
Authors: Du Xue , Wei Guanghui , Zhao Hongze , Pan Xiaodong
Published: December 2021

In order to establish the prediction model of radar equipment in multisource complex electromagnetic environment, the blocking effect and false alarm interference effect caused by single-frequency CW (continuous wave) electromagnetic interference on typical radar equipment are studied. Taking a certain sweep radar as the research object, the equivalent injection test of EMI (electromagnetic interference) is carried out. Based on the theory of radar front door coupling, the interference mechanism of EMI to radar receiver RF front end is revealed, and the variation law of blocking target and false alarm target level is analyzed. The results show that, under the single-frequency CW-EMI, the target echo level decreases with the increase of the interference field strength, and the false alarm level increases with the increase of the interference field strength. The blocking jamming sensitive bandwidth is about

f

0

±
200
 
MHz

, and the false alarm jamming sensitive bandwidth is about

f

0

±
80
 
MHz

.
Clinical, Histological, and Scintigraphic Comparative Study of the Use of Mandibular Bone Marrow and Peripheral Blood in Bone Neoformation
Authors: Pasquali Paulo José , André Dall’Agnol Rodrigo , Garcia Rezende Lucas , Martinez Elizabeth Ferreira
Published: December 2021

Background and Purpose. To evaluate the capacity of mandibular bone marrow blood aspirate associated with biomaterials to stimulate bone tissue neoformation compared to the use of peripheral blood aspirate in patients with bone loss in the premaxillary region. Materials and Methods. The study included 16 patients with maxillary atresia. The region was grafted with xenograft blocks associated with the following treatments: G1, the patient’s peripheral blood during surgery, and G2, dripping of mandibular bone marrow blood until the xenograft was completely wet. After 7 and 14 days, scintigraphic images of the regions of interest (ROI) were taken to quantify pixels, which indicate osteogenic activity. Additionally, trephined samples obtained at the time of implant placement were stained in H&E, and newly formed bone tissue was quantified. The data were tabulated and statistically analyzed at a significance level of 5%. Results. Scintigraphic data showed greater osteogenic activity with mandibular bone marrow blood (G2) at all times evaluatedp<0.05. As for the histomorphometric analysis, a greater amount of bone tissue was observed in samples treated with mandibular bone marrow blood (G2) compared to peripheral blood (G1)p<0.05. Conclusions. The appositional bone reconstruction technique in the block associated with mandibular bone marrow blood increased bone neoformation and osteogenic activity compared to conventional graft treatment with peripheral blood.
Pricing Vulnerable Options in a Mixed Fractional Brownian Motion with Jumps
Authors: Cheng Panhong , Xu Zhihong
Published: December 2021

A new framework for pricing European vulnerable options is developed in the case where the underlying stock price and firm value follow the mixed fractional Brownian motion with jumps, respectively. This research uses the actuarial approach to study the pricing problem of European vulnerable options. An analytic closed-form pricing formula for vulnerable options with jumps is obtained. For the purpose of understanding the pricing model, some properties of this pricing model are discussed in the paper. Finally, we compare and analyze the pricing results of different pricing models and discuss the influences of basic parameters on the pricing results of our proposed model by using numerical simulations, and the corresponding economic analyses about these influences are given.