bluuebunny/crossref_metadata_2025 huggingface dataset:
Spillover effects of adult children’s schooling on parents’ smoking cessation: evidence from China’s compulsory schooling reform
Authors: Xie Liyang , Xu Wei , Zhou Yi
Published: April 2021

Objective

As elderly parents today will share a longer life with their children than ever before, the spillover effects of children’s human capital on parents’ well-being become increasingly important. This study investigated whether children’s schooling leads parents to give up smoking and whether the effects were moderated by their education or child–parent contact frequency.

Methods

Using data from the China Health and Retirement Longitudinal Study, we conducted an instrumental variable (IV) analysis using China’s compulsory schooling reform in the 1980s as a natural experiment.

Results

The IV estimates suggest that elderly parents of more highly educated children are more likely to quit smoking. Moreover, the effects are more significant among parents who had not finished primary school and also slightly stronger among parents who live close to their children or meet their children frequently.

Discussion

Our findings add to current evidence regarding spillover effects of education on smoking cessation. A child’s education may exert an impact through the spillover of health knowledge.
Dental attendance and behavioural pathways to adult oral health inequalities
Authors: Guarnizo-Herreño Carol C , Scholes Shaun , Heilmann Anja , O'Connor Rhiannon , Fuller Elizabeth , Shen Jing , Watt Richard G , Morris Steve , Wildman John , Tsakos Georgios
Published: April 2021

Background

While inequalities in oral health are documented, little is known about the extent to which they are attributable to potentially modifiable factors. We examined the role of behavioural and dental attendance pathways in explaining oral health inequalities among adults in England, Wales and Northern Ireland.

Methods

Using nationally representative data, we analysed inequalities in self-rated oral health and number of natural teeth. Highest educational attainment, equivalised household income and occupational social class were used to derive a latent socioeconomic position (SEP) variable. Pathways were dental attendance and behaviours (smoking and oral hygiene). We used structural equation modelling to test the hypothesis that SEP influences oral health directly and also indirectly via dental attendance and behavioural pathways.

Results

Lower SEP was directly associated with fewer natural teeth and worse self-rated oral health (standardised path coefficients, −0.21 (SE=0.01) and −0.10 (SE=0.01), respectively). We also found significant indirect effects via behavioural factors for both outcomes and via dental attendance primarily for self-rated oral health. While the standardised parameters of total effects were similar between the two outcomes, for number of teeth, the estimated effect of SEP was mostly direct while for self-rated oral health, it was almost equally split between direct and indirect effects.

Conclusion

Reducing inequalities in dental attendance and health behaviours is necessary but not sufficient to tackle socioeconomic inequalities in oral health.
Real-time ultrasound-guided low thoracic epidural catheter placement: technical consideration and fluoroscopic evaluation
Authors: Kim Doo-Hwan , Lee Jong-Hyuk , Sim Ji Hoon , Jeong Wonyeong , Lee Dokyeong , Kwon Hye-Mee , Choi Seong-Soo , Jeong Sung-Moon
Published: April 2021

Background and objective

Thoracic epidural analgesia can significantly reduce acute postoperative pain. However, thoracic epidural catheter placement is challenging. Although real-time ultrasound (US)-guided thoracic epidural catheter placement has been recently introduced, data regarding the accuracy and technical description are limited. Therefore, this prospective observational study aimed to assess the success rate and describe the technical considerations of real-time US-guided low thoracic epidural catheter placement.

Methods

38 patients in the prone position were prospectively studied. After the target interlaminar space between T9 and T12 was identified, the needle was advanced under real-time US guidance and was stopped just short of the posterior complex. Further advancement of the needle was accomplished without US guidance using loss-of-resistance techniques to normal saline until the epidural space was accessed. Procedure-related variables such as time to mark space, needling time, number of needle passes, number of skin punctures, and the first-pass success rate were measured. The primary outcome was the success rate of real-time US-guided thoracic epidural catheter placement, which was evaluated using fluoroscopy. In addition, the position of the catheter, contrast dispersion, and complications were evaluated.

Results

This study included 38 patients. The T10–T11 interlaminar space was the most location for epidural access. During the procedure, the mean time for marking the overlying skin for the procedure was 49.5±13.8 s and the median needling time was 49 s. The median number of needle passes was 1.0 (1.0–1.0). All patients underwent one skin puncture for the procedure. The first-pass and second-pass success rates were 76.3% and 18.4%, respectively. Fluoroscopic evaluation revealed that the catheter tips were all positioned in the epidural space and were usually located between T9 and T10 (84.2%). The cranial and caudal contrast dispersion were observed up to 5.4±1.6 and 2.6±1.0 vertebral body levels, respectively. No procedure-related complications occurred.

Conclusion

Real-time US guidance appears to be a feasible option for facilitating thoracic epidural insertion. Whether or not this technique improves the procedural success and quality compared with landmark-based techniques will require additional study.

Trial registration number

NCT03890640.
Timing ofMycobacterium tuberculosisexposure explains variation in BCG effectiveness: a systematic review and meta-analysis
Authors: Trauer James M , Kawai Andrew , Coussens Anna K , Datta Manjula , Williams Bridget M , McBryde Emma S , Ragonnet Romain
Published: April 2021

Rationale

The heterogeneity in efficacy observed in studies of BCG vaccination is not fully explained by currently accepted hypotheses, such as latitudinal gradient in non-tuberculous mycobacteria exposure.

Methods

We updated previous systematic reviews of the effectiveness of BCG vaccination to 31 December 2020. We employed an identical search strategy and inclusion/exclusion criteria to these earlier reviews, but reclassified several studies, developed an alternative classification system and considered study demography, diagnostic approach and tuberculosis (TB)-related epidemiological context.

Main results

Of 21 included trials, those recruiting neonates and children aged under 5 were consistent in demonstrating considerable protection against TB for several years. Trials in high-burden settings with shorter follow-up also showed considerable protection, as did most trials in settings of declining burden with longer follow-up. However, the few trials performed in high-burden settings with longer follow-up showed no protection, sometimes with higher case rates in the vaccinated than the controls in the later follow-up period.

Conclusions

The most plausible explanatory hypothesis for these results is that BCG protects against TB that results from exposure shortly after vaccination. However, we found no evidence of protection when exposure occurs later from vaccination, which would be of greater importance in trials in high-burden settings with longer follow-up. In settings of declining burden, most exposure occurs shortly following vaccination and the sustained protection observed for many years thereafter represents continued protection against this early exposure. By contrast, in settings of continued intense transmission, initial protection subsequently declines with repeated exposure toMycobacterium tuberculosisor other pathogens.
A complex regulatory network underlies de novo root regeneration in red maple (Acer rubrum)
Authors: Li Mengyi , Cheng Yunhe , Li Yanlin , Gan Dexin , Yu Xiaoying
Published: April 2021

Red maple (Acer rubrum L.) is ornamentally and medicinally valuable; however, its wider application is restricted by the difficulty of rooting from cuttings. We analyzed paraffin sections of roots regenerating using RNA-Seq to decipher the mechanisms underlying de novo root regeneration (DNRR) in red maple cuttings. This work contributes to improving the rooting rate and shortening the rooting time. We identified four stages during DNRR: 0 days after induction (DAI), no new cell formation; 30 DAI, root meristem organization; 36 DAI, root primordium formation; and 45 DAI, root elongation growth. We identified 37 959 unigenes by de novo assembly, with 25 477 (67.12%) functionally annotated. Furthermore, we identified 1285 differentially expressed genes (DEGs) between adjacent stages. From Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment networks, we found evidence that plant hormones are significant in DNRR of red maple cuttings. Specifically, 149 DEGs functioned in hormone signal transduction pathways, particularly those involving ethylene, auxin, and jasmonic acid (JA). We propose a complex regulatory network model of DNRR in red maple, where wounding induces root regeneration through pathways of JA and auxin signaling. The transcription factors ETHYLENE RESPONSE FACTOR 109 (ERF109) and ERF115 integrate JA signal and participate in DNRR directly by regulating SCARECROW activation and indirectly by promoting auxin biosynthesis.
Chirped, breathers, diamond and W-shaped optical waves propagation in nonself-phase modulation medium. Biswas–Arshed equation
Authors: Abdel-Gawad H. I.
Published: April 2021

Self-phase modulation (SPM) induces a varying refractive index of the medium due to the optical Kerr effect. The optical waves propagation (OWP) in a medium with SPM occupied a remarkable area of research in the literature. A model equation to describe OWP in the absence of SPM was proposed very recently by Biswas–Arshed equation (BAE). This work is based on constructing the solutions that describe the waves which arise from soliton-periodic wave collisions. A variety of geometric optical wave structures are observed. Here, a transformation that allows to investigate the multi-geometric structures of OW’s result from soliton-periodic wave collisions is introduced. Chirped, conoidal, breathers, diamond and W-shaped optical waves are shown to propagate in the medium in the absence of SPM. The exact solutions of BAE are obtained by using the unified method, which was presented recently. We mention that the results found here, are completely new.
Memory function of memristive Hindmarsh–Rose model driven by colored noise and electromagnetic induction
Authors: Li Tianyou , Lu Lulu , Jia Ya
Published: April 2021

Based on the three-dimensional memristive Hindmarsh–Rose model, the effects of Gaussian colored noise and electromagnetic induction on memory function of the memristor and neural firing states are investigated in this paper. It is found that the memory function of memristor can be suppressed by a higher signal frequency, while enhanced by a relatively larger coefficient of the memristor. The memory function of memristor is destroyed by larger values of noise intensity and correlation rate between noises. The neural firing state can be transformed from the spiking state to the chaotic state with the increase of noise intensity or correlation rate. The firing states transition induced by the higher electromagnetic induction intensity is opposite to that by the stronger Gaussian colored noise.
Community detection in social networks based on information propagation and user engagement
Authors: Nian Fuzhong , Luo Li , Yu Xuelong , Guo Xin
Published: April 2021

The iterative propagation of information between nodes will strengthen the connection strength between nodes, and the network can evolve into different groups according to difference edge strength. Based on this observation, we present the user engagement to quantify the influences of users different propagation modes to network propagation, and construct weight network to simulate real social network, and proposed the community detection method in social networks based on information propagation and user engagement. Our method can produce different scale communities and overlapping community. We also applied our method to real-world social networks. The experiment proved that the network spread and the community division interact with each other. The community structure is significantly different in the network propagation of different scales.
Generalized solutions to bounded-confidence models
Authors: Piccoli Benedetto , Rossi Francesco
Published: April 2021

Bounded-confidence models in social dynamics describe multi-agent systems, where each individual interacts only locally with others. Several models are written as systems of ordinary differential equations (ODEs) with discontinuous right-hand side: this is a direct consequence of restricting interactions to a bounded region with non-vanishing strength at the boundary. Various works in the literature analyzed properties of solutions, such as barycenter invariance and clustering. On the other side, the problem of giving a precise definition of solution, from an analytical point of view, was often overlooked. However, a rich literature proposing different concepts of solution to discontinuous differential equations is available. Using several concepts of solution, we show how existence is granted under general assumptions, while uniqueness may fail even in dimension one, but holds for almost every initial conditions. Consequently, various properties of solutions depend on the useddefinition and initial conditions.
Optimization of Leased Equipment Maintenance Policy Based on History Failure Data
Authors: Dong Ke , Chen Kehong
Published: April 2021

We propose a maintenance policy for new equipment on a repair-refund maintenance strategy in this paper and derive the optimal lease period from the lessor’s perspective based on independent and identical distribution of historical failure data which obey power law process. The cost model of a full refund and a proportional refund is studied, and the corresponding optimal leasing period is determined by reducing the expected total cost rate to the largest extent. We use a numerical example to illustrate the proposed cost model and analyze the sensitivity of related parameters. Furthermore, we show that the proportional refund policy is preferable than a full refund to the lessor. Finally, according to the simulation outcome, the proposed methods are effective and instructions for lessor in regard to equipment lease are provided.
Effects of Van Der Waals Forces on the Vibration of Stacked Multilayered Graphene/Black Phosphorus Heterostructures
Authors: Hou Dongchang , Wang Lifeng , Zhang Yiqing
Published: April 2021

In this paper, the vibration of a stacked multilayered graphene/black phosphorus (G/BP) heterostructure is investigated via the mesh-free method. The shape function and its derivatives are addressed by the moving least squares (MLS) approach. Optimization of the sequential quadratic programming method is adopted to calculate the distance between the arbitrary layers. Therefore, coefficients of the van der Waals (vdW) interaction between arbitrary layers of heterostructures are obtained. Then the frequencies and mode shapes of the multilayered G/BP heterostructure, considering the vdW interaction between arbitrary layers, are compared with considering only the vdW interaction among adjacent layers. The effects of the number of layers and aspect ratio of the G/BP heterostructure on the frequencies are investigated. The results demonstrate that coefficients of the vdW interaction, considering the arbitrary layers, are larger than those considering only adjacent layers. The difference between natural frequencies considering arbitrary layers and those considering adjacent layers is not clear for the low-order cases. Alternatively, the difference between natural frequencies obtained considering arbitrary layers and those considering adjacent layers are obvious for high-order cases. This paper provides a useful method to optimize the vdW interaction between multilayered G/BP heterostructures and can adequately simulate their vibration behaviors.
Correlation between the continuous-time quantum walk and cliques in graphs and its application
Authors: Wu Mingyou , Li Xi , Liu Zhihao , Chen Hanwu
Published: April 2021

The continuous-time quantum walk (CTQW) provides a new approach to problems in graph theory. In this paper, the correlation between the CTQW and cliques in graphs is studied, and an approximate algorithm for the maximum clique problem (MCP) based on the CTQW is given. Via both numerical and theoretical analyses, it is found that the maximum clique is related to the transmission characteristics of the CTQW on some special graphs. For general graphs, the correlation is difficult to describe analytically. Therefore, the transmission characteristics of the CTQW are applied as a vertex selection criterion to a classical MCP algorithm and it is compared with the original algorithm. Numerous simulation on general graphs shows that the new algorithm is more efficient. Furthermore, an approximate MCP algorithm based on the CTQW is introduced, which only requires a very small number of searches with a high approximation ratio.
Gel polymer electrolyte with high performances based on poly(methyl methacrylate) composited with hydroxypropyl methyl cellulose by phase inversion method for lithium-ion batteries
Authors: Gan Junyuan , Huang Yun , Guo Zhicheng , Li Saisai , Ren Wenhao , Li Xing , Wang Mingshan , Lin Yuanhua , Liu Li
Published: April 2021

A novel type of gel polymer electrolyte (GPE) based on poly(methyl methacrylate) (PMMA) composite natural polymer hydroxyl propyl methyl cellulose (HPMC) was prepared with high comprehensive performances for lithium ion batteries. In this study, the composite membrane was prepared through phase inversion method. When the mass ratio of PMMA to HPMC is 4:6, the composite membrane exhibits a very high liquid uptake of 1715.07 wt.%, and the corresponding ion conductivity is as high as 6.89 × 10[Formula: see text] S cm[Formula: see text], lithium ion transference number reaches up to 0.80, and electrochemical stability window is high enough up to 5.0 V at room temperature. In addition, through charge and discharge experimental test, Li/GPE/LiFePO4batteries exhibit excellent initial discharge capacities 166 and 121 mAh g[Formula: see text] at 0.2C and 1C rates, respectively. Therefore, the composite membrane with low cost and high performance researched in this work is an effective and promising GPE material, which presents a potential for applying in lithium-ion batteries (LIBs).
Experimental study of the mechanism of grouting colloidal nano-silica in over-broken coal mass
Authors: Pan Dongjiang , Hong Kairong , Fu Helin , Zhou Jianjun , Zhang Nong
Published: April 2021

Grouting is an important process for stability control of unfavourable geology. A multi-parameter grouting monitoring device was designed to monitor pump pressure, inlet density, outlet density, outlet electrical resistance and osmotic pressure. On the basis of multi-source information, this paper presents an experimental study of the process of grouting colloidal nano-silica into an over-broken coal mass, which was verified by percolation mechanics theory and numerical simulation simultaneously. The porosity and permeability of the injected sample were 15.34% and 5.45 mD. The results showed that the variation of pump pressure generally showed an obvious three-stage regularity. The time-dependent curves of outlet density and outlet resistance were consistent with that of pump pressure, whereas the curve of inlet density was opposite to that of pump pressure. The law of the dominant penetration mechanism was as follows: miscible displacement mechanism in the first stage (0–46 min), Darcy flow in the second stage (46–200 min) and filtration flow in the third stage. This research can guide grouting theory study and design in an over-broken rock mass.
A Systematic Review on Hadith Authentication and Classification Methods
Authors: Binbeshr Farid , Kamsin Amirrudin , Mohammed Manal
Published: April 2021

Background
: A hadith refers to sayings, actions, and characteristics of the Prophet Muhammad peace be upon him. The authenticity of hadiths is crucial, because they constitute the source of legislation for Muslims with the Holy Quran. Classifying hadiths into groups is a matter of importance as well, to make them easy to search and recognize.

Objective
: To report the results of a systematic review concerning hadith authentication and classification methods.

Data sources
: Original articles found in ACM, IEEE Xplore, ScienceDirect, Scopus, Web of Science, Springer Link, and Wiley Online Library.

Study selection criteria
: Only original articles written in English and dealing with hadith authentication and classification. Reviews, editorial, letters, grey literature, and restricted or incomplete articles are excluded.

Data extraction
: Two authors were assigned to extract data using a predefined data extraction form to answer research questions and assess studies quality.

Results
: A total of 27 studies were included in this review. There are 14 studies in authentication and 13 studies in classification. Most of the selected studies (17 of 27) were published in conferences, while the others (10 of 27) were published in scientific journals. Research in the area of hadith authentication and classification has received more attention in recent years (2016–2019).

Conclusions
: Hadith authentication methods are classified into machine learning, rule-based, and a hybrid of rule-based and machine learning and rule-based and statistical methods. Hadith classification methods are classified into machine learning and rule-based. All classification studies used Matn, while the majority of authentication studies used isnad. As a dataset source, Sahih Al-Bukhari was used by most studies. None of the used datasets is publicly available as a benchmark dataset, either in hadith authentication or classification. Recall and Precision are the most frequent evaluation metrics used by the selected studies.
Data Reduction for Maximum Matching on Real-World Graphs
Authors: Koana Tomohiro , Korenwein Viatcheslav , Nichterlein André , Niedermeier Rolf , Zschoche Philipp
Published: April 2021

Finding a maximum-cardinality or maximum-weight matching in (edge-weighted) undirected graphs is among the most prominent problems of algorithmic graph theory. For
n
-vertex and
m
-edge graphs, the best-known algorithms run in Õ(
m
√
n
) time. We build on recent theoretical work focusing on linear-time data reduction rules for finding maximum-cardinality matchings and complement the theoretical results by presenting and analyzing (thereby employing the kernelization methodology of parameterized complexity analysis) new (near-)linear-time data reduction rules for both the unweighted and the positive-integer-weighted case. Moreover, we experimentally demonstrate that these data reduction rules provide significant speedups of the state-of-the art implementations for computing matchings in real-world graphs: the average speedup factor is 4.7 in the unweighted case and 12.72 in the weighted case.
Taming Reflection
Authors: Sun Xiaoyu , Li Li , Bissyandé Tegawendé F. , Klein Jacques , Octeau Damien , Grundy John
Published: April 2021

Android developers heavily use reflection in their apps for legitimate reasons. However, reflection is also significantly used for hiding malicious actions. Unfortunately, current state-of-the-art static analysis tools for Android are challenged by the presence of reflective calls, which they usually ignore. Thus, the results of their security analysis, e.g., for private data leaks, are incomplete, given the measures taken by malware writers to elude static detection. We propose a new instrumentation-based approach to address this issue in a non-invasive way. Specifically, we introduce to the community a prototype tool called DroidRA, which reduces the resolution of reflective calls to a composite constant propagation problem and then leverages the COAL solver to infer the values of reflection targets. After that, it automatically instruments the app to replace reflective calls with their corresponding Java calls in a traditional paradigm. Our approach augments an app so that it can be more effectively statically analyzable, including by such static analyzers that are not reflection-aware. We evaluate DroidRA on benchmark apps as well as on real-world apps, and we demonstrate that it can indeed infer the target values of reflective calls and subsequently allow state-of-the-art tools to provide more sound and complete analysis results.
Architecting Internet of Things Systems with Blockchain
Authors: Yánez Wendy , Bahsoon Rami , Zhang Yuqun , Kazman Rick
Published: April 2021

Blockchain offers a distributed ledger to record data collected from Internet of Thing (IoT) devices as immutable and tamper-proof transactions and securely shared among authorized participants in a Peer-to-Peer (P2P) network. Despite the growing interest in using blockchain for securing IoT systems, there is a general lack of systematic research and comprehensive review of the design issues on the integration of blockchain and IoT from the software architecture perspective. This article presents a catalog of architectural tactics for the design of IoT systems supported by blockchain as a result of a Systematic Literature Review (SLR) on IoT and blockchain to extract the commonly reported quality attributes, design decisions, and relevant architectural tactics for the architectural design of this category of systems. Our findings are threefold: (i) identification of security, scalability, performance, and interoperability as the commonly reported quality attributes; (ii) a catalog of twelve architectural tactics for the design of IoT systems supported by blockchain; and (iii) gaps in research that include tradeoffs among quality attributes and identified tactics. These tactics might provide architects and designers with different options when searching for an optimal architectural design that meets the quality attributes of interest and constraints of a system.
Machine Learning–enabled Scalable Performance Prediction of Scientific Codes
Authors: Chennupati Gopinath , Santhi Nandakishore , Romero Phill , Eidenbenz Stephan
Published: April 2021

Hardware architectures become increasingly complex as the compute capabilities grow to exascale. We present the Analytical Memory Model with Pipelines (AMMP) of the Performance Prediction Toolkit (PPT). PPT-AMMP takes high-level source code and hardware architecture parameters as input and predicts runtime of that code on the target hardware platform, which is defined in the input parameters. PPT-AMMP transforms the code to an (architecture-independent) intermediate representation, then (i) analyzes the basic block structure of the code, (ii) processes architecture-independent virtual memory access patterns that it uses to build memory reuse distance distribution models for each basic block, and (iii) runs detailed basic-block level simulations to determine hardware pipeline usage.

PPT-AMMP uses machine learning and regression techniques to build the prediction models based on small instances of the input code, then integrates into a higher-order discrete-event simulation model of PPT running on Simian PDES engine. We validate PPT-AMMP on four standard computational physics benchmarks and present a use case of hardware parameter sensitivity analysis to identify bottleneck hardware resources on different code inputs. We further extend PPT-AMMP to predict the performance of a scientific application code, namely, the radiation transport mini-app SNAP. To this end, we analyze multi-variate regression models that accurately predict the reuse profiles and the basic block counts. We validate predicted SNAP runtimes against actual measured times.
Integration of Multimodal Data for Deciphering Brain Disorders
Authors: Chen Jingqi , Dong Guiying , Song Liting , Zhao Xingzhong , Cao Jixin , Luo Xiaohui , Feng Jianfeng , Zhao Xing-Ming
Published: April 2021

The accumulation of vast amounts of multimodal data for the human brain, in both normal and disease conditions, has provided unprecedented opportunities for understanding why and how brain disorders arise. Compared with traditional analyses of single datasets, the integration of multimodal datasets covering different types of data (i.e., genomics, transcriptomics, imaging, etc.) has shed light on the mechanisms underlying brain disorders in greater detail across both the microscopic and macroscopic levels. In this review, we first briefly introduce the popular large datasets for the brain. Then, we discuss in detail how integration of multimodal human brain datasets can reveal the genetic predispositions and the abnormal molecular pathways of brain disorders. Finally, we present an outlook on how future data integration efforts may advance the diagnosis and treatment of brain disorders.
An Adaptive Protection of Flooding Attacks Model for Complex Network Environments
Authors: Khalaf Bashar Ahmad , Mostafa Salama A. , Mustapha Aida , Mohammed Mazin Abed , Mahmoud Moamin A. , Al-Rimy Bander Ali Saleh , Abd Razak Shukor , Elhoseny Mohamed , Marks Adam
Published: April 2021

Currently, online organizational resources and assets are potential targets of several types of attack, the most common being flooding attacks. We consider the Distributed Denial of Service (DDoS) as the most dangerous type of flooding attack that could target those resources. The DDoS attack consumes network available resources such as bandwidth, processing power, and memory, thereby limiting or withholding accessibility to users. The Flash Crowd (FC) is quite similar to the DDoS attack whereby many legitimate users concurrently access a particular service, the number of which results in the denial of service. Researchers have proposed many different models to eliminate the risk of DDoS attacks, but only few efforts have been made to differentiate it from FC flooding as FC flooding also causes the denial of service and usually misleads the detection of the DDoS attacks. In this paper, an adaptive agent-based model, known as an Adaptive Protection of Flooding Attacks (APFA) model, is proposed to protect the Network Application Layer (NAL) against DDoS flooding attacks and FC flooding traffics. The APFA model, with the aid of an adaptive analyst agent, distinguishes between DDoS and FC abnormal traffics. It then separates DDoS botnet from Demons and Zombies to apply suitable attack handling methodology. There are three parameters on which the agent relies, normal traffic intensity, traffic attack behavior, and IP address history log, to decide on the operation of two traffic filters. We test and evaluate the APFA model via a simulation system using CIDDS as a standard dataset. The model successfully adapts to the simulated attack scenarios’ changes and determines 303,024 request conditions for the tested 135,583 IP addresses. It achieves an accuracy of 0.9964, a precision of 0.9962, and a sensitivity of 0.9996, and outperforms three tested similar models. In addition, the APFA model contributes to identifying and handling the actual trigger of DDoS attack and differentiates it from FC flooding, which is rarely implemented in one model.
Lipid Profile and Vascular Remodelling in Young Dyslipidemic Subjects Treated with Nutraceuticals Derived from Red Yeast Rice
Authors: Puato Massimo , Zambon Alberto , Nardin Chiara , Faggin Elisabetta , Pesavento Raffaele , Spinazzè Alice , Pauletto Paolo , Rattazzi Marcello
Published: April 2021

Background and Aims. A relevant role is emerging for functional foods in cardiovascular prevention. The aim of this study was to assess the effect of a nutraceutical multitargeted approach on lipid profile and inflammatory markers along with vascular remodelling in a cohort of dyslipidemic subjects without history of cardiovascular (CV) disease. Methods and Results. We enrolled 25 subjects (mean age 48.2 years) with low to moderate CV risk profile and total cholesterol (TC) levels between 150 and 250 mg/dl. The patients were assigned to receive for one year a tablet/die of a nutraceutical combination containing red yeast rice (RYR) extract (Monacolin 3 mg/tablet) and coenzyme Q10 (30 mg/tablet). Treatment with the nutraceutical compounds led to a significant reduction of TC (from 227 to 201 mg/dl,

p
<
0.001

), LDL-c (from 150 to 130 mg/dl,

p
=
0.001

), triglycerides (from 121 to 109 mg/dl,

p
=
0.013

), non-HDL-cholesterol (from 168 to 141 mg/dl,

p
<
0.001

), hs-CRP (from 1.74 to 1.20 mg/l,

p
=
0.015

), and osteoprotegerin (from 1488 to 1328 pg/ml,

p
=
0.045

). Levels of HDL-c, Lp(a), glucose, liver enzyme, CPK, or creatinine did not change over time. An ultrasound study was performed to assess changes in mean carotid intima-media thickness (IMT) and maximum IMT (M-MAX) as well as modification in local carotid stiffness by means of determining the carotid compliance coefficient (CC) and distensibility coefficient (DC). At the end of the treatment, we observed small but significant reductions in both mean-IMT (from 0.62 to 0.57 mm,

p
=
0.022

) and M-MAX (from 0.79 to 0.73 mm,

p
=
0.002

), and an improvement in carotid elasticity (DC from 22.4 to

24.3
×

10

−
3

/
kPa

,

p
=
0.006

and CC from 0.77 to 0.85 mm2/kPa,

p
=
0.019

). Conclusions. A long-term treatment with a combination of RYR and coenzyme Q10 showed lipid-lowering activity along with a reduction of inflammatory mediators and an improvement of vascular properties in young subjects with a low-to-moderate CV risk profile.
The Planar Wide-Frequency Vibration Characteristics of Heavy-Load Radial Tires
Authors: Cheng Hongjie , Gao Lei , Liu Zhihao , Gao Qinhe , Liu Xiuyu
Published: April 2021

This paper investigates the planar wide-frequency vibration characteristics of heavy-load radial tires with a large aspect ratio. A proposed tire model with a piecewise flexible beam on an elastic foundation is investigated and validated using experimental modal analysis and theoretical modeling method. The reproducibility of frequency response functions below 400 Hz is discussed. The experimental modal analysis particularly assesses the coupling of features across the circumferential and cross-sectional directions of heavy-load radial tire carcass. Piecewise circumferential modal characteristics were investigated experimentally, leading to the suggestion of a piecewise flexible beam on an elastic tire foundation. Using a genetic algorithm (GA), the structural parameters EI,

ρ
A

, and kr and damping coefficients

η

and cr for the proposed tire model are identified, and the piecewise transfer functions and the planar transfer functions for a heavy-load radial tire are compared with planar hammer test. Experimental and theoretical results show the following: (1) the sectional vibration characteristics for a heavy-load radial tire with a large aspect ratio result from the cross-sectional vibration of the tire carcass; (2) the piecewise transfer function is mainly influenced by the circumferential vibration of the flexible carcass, and this is consistent with a model where a flexible beam is placed on an elastic tire foundation; (3) the analytical transfer functions calculated for the proposed tire model, drawing on the identified structural parameters and damping coefficients, agree well with the experimental results.
[Retracted] Cannabinoid WIN 55,212‐2 Inhibits Human Glioma Cell Growth by Triggering ROS‐Mediated Signal Pathways
Authors: Wang Kun , Wang Qian , Li Qinghao , Zhang Zhaoqiang , Gao Jing , Fan Cundong , Sun Baoliang , Ni Qingbin
Published: April 2021

Glioblastoma is a highly invasive primary malignant tumor of the central nervous system. Cannabinoid analogue WIN 55,212‐2 (WIN) exhibited a novel anticancer effect against human tumors. However, the anticancer potential and underlying mechanism of WIN against human glioma remain unclear. Herein, the anticancer efficiency and mechanism of WIN in U251 human glioma cells were investigated. The results showed that WIN dose‐dependently inhibited U251 cell proliferation, migration, and invasion in vitro. WIN treatment also effectively suppressed U251 tumor spheroids growth ex vivo. Further studies found that WIN induced significant apoptosis as convinced by the caspase‐3 activation and release of cytochrome C. Mechanism investigation revealed that WIN triggered ROS‐mediated DNA damage and caused dysfunction of VEGF‐AKT/FAK signal axis. However, ROS inhibition effectively attenuated WIN‐induced DNA damage and dysfunction of VEGF‐AKT/FAK signal axis and eventually improved U251 cell proliferation, migration, and invasion. Taken together, our findings validated that WIN had the potential to inhibit U251 cell proliferation, migration, and invasion and induce apoptosis by triggering ROS‐dependent DNA damage and dysfunction of VEGF‐AKT/FAK signal axis.
Opposing and Operated Side Electroacupuncture Generates Similar Analgesic Effects on Pain after Knee Surgery
Authors: Huang Hai , Song Xiuling , Wang Jiayou , Xing Man , Kang Bingxin , Ma Chenghao , Li Wenbiao , Han Wenjun , Xiao Lianbo , Chen Yuelai
Published: April 2021

The purpose of this study was to investigate whether opposing electroacupuncture (EA) could produce similar analgesic effects as operated side EA after knee surgery in rats. Sprague Dawley rats were randomly divided into the sham surgery group, and three surgery groups: opposing EA, operated side EA, and model. After surgery, compared with the sham surgery group, three kinds of pain behavior test methods (mechanical withdrawal threshold (MWT), cumulative pain score [CPS], and mechanical hypersensitivity of knee) were used to assess the pain behavior of the rats in the surgery groups. After knee surgery, the three surgery groups were intervened for three consecutive days: EA on the nonoperated side in the opposing EA group, EA on the operated side in the operated side EA group, and no intervention in the model group. It was shown that MWT was higher and CPS was lower in the two EA groups than in the model group on the first and second days after surgery. On the third day after surgery, MWT in the two EA groups was the highest among the 3 days, CPS was the lowest among the 3 days, and the number of nonvocalizations in rats also increased compared with the model group. Moreover, the MWT of the nonoperated side increased more in the opposing EA group than in the model and operated side EA groups. This indicated that both opposing EA and operated side EA methods can be used to relieve pain after knee joint surgery.
Deep Reinforcement Learning for Vectored Thruster Autonomous Underwater Vehicle Control
Authors: Liu Tao , Hu Yuli , Xu Hui
Published: April 2021

Autonomous underwater vehicles (AUVs) are widely used to accomplish various missions in the complex marine environment; the design of a control system for AUVs is particularly difficult due to the high nonlinearity, variations in hydrodynamic coefficients, and external force from ocean currents. In this paper, we propose a controller based on deep reinforcement learning (DRL) in a simulation environment for studying the control performance of the vectored thruster AUV. RL is an important method of artificial intelligence that can learn behavior through trial‐and‐error interactions with the environment, so it does not need to provide an accurate AUV control model that is very hard to establish. The proposed RL algorithm only uses the information that can be measured by sensors inside the AUVs as the input parameters, and the outputs of the designed controller are the continuous control actions, which are the commands that are set to the vectored thruster. Moreover, a reward function is developed for deep RL controller considering different factors which actually affect the control accuracy of AUV navigation control. To confirm the algorithm’s effectiveness, a series of simulations are carried out in the designed simulation environment, which is a method to save time and improve efficiency. Simulation results prove the feasibility of the deep RL algorithm applied to the control system for AUV. Furthermore, our work also provides an optional method for robot control problems to deal with improving technology requirements and complicated application environments.
Effects of Continuous Positive Airway Pressure on Sleep EEG Characteristics in Patients with Primary Central Sleep Apnea Syndrome
Authors: Zhang Cheng , Chen Kun , Wang Guangfa , Zhang Jue , Ma Jing
Published: April 2021

This study aimed to investigate the effects of continuous positive airway pressure (CPAP) on the electroencephalographic (EEG) characteristics of patients with primary central sleep apnea syndrome (CSAS). Nine patients with primary CSAS were enrolled in this study. The raw sleep EEG data were analyzed based on two main factors: fractal dimension (FD) and zero-crossing rate of detrended FD. Additionally, conventional EEG spectral analysis in the delta, theta, alpha, and beta bands was conducted using a fast Fourier transform. The FD in patients with primary CSAS who underwent CPAP treatment was significantly decreased during nonrapid eye movement (NREM) sleep but increased during rapid eye movement (REM) sleep (

p
<
0.05

). Regarding the EEG spectral analysis, the alpha power increased, while the delta/alpha ratio decreased during REM sleep in patients with CSAS (

p
<
0.05

). In conclusion, CPAP treatment can reduce FD in NREM sleep and increase FD during REM sleep in patients with primary CSAS. FD may be used as a new biomarker of EEG stability and improvement in brain function after CPAP treatment for primary CSAS.
Implementation of Blockchain Consensus Algorithm on Embedded Architecture
Authors: Frikha Tarek , Chaabane Faten , Aouinti Nadhir , Cheikhrouhou Omar , Ben Amor Nader , Kerrouche Abdelfateh
Published: April 2021

The adoption of Internet of Things (IoT) technology across many applications, such as autonomous systems, communication, and healthcare, is driving the market’s growth at a positive rate. The emergence of advanced data analytics techniques such as blockchain for connected IoT devices has the potential to reduce the cost and increase in cloud platform adoption. Blockchain is a key technology for real-time IoT applications providing trust in distributed robotic systems running on embedded hardware without the need for certification authorities. There are many challenges in blockchain IoT applications such as the power consumption and the execution time. These specific constraints have to be carefully considered besides other constraints such as number of nodes and data security. In this paper, a novel approach is discussed based on hybrid HW/SW architecture and designed for Proof of Work (PoW) consensus which is the most used consensus mechanism in blockchain. The proposed architecture is validated using the Ethereum blockchain with the Keccak 256 and the field-programmable gate array (FPGA) ZedBoard development kit. This implementation shows improvement in execution time of 338% and minimizing power consumption of 255% compared to the use of Nvidia Maxwell GPUs.
Study on Mechanical Properties of the Expansive Soil Treated with Iron Tailings Sand
Authors: Chu Chengfu , Zhang Fei , Wu Daoxiang , Zhan Meihuang , Liu Yun
Published: April 2021

Aiming at researching shear strength parameters of expansive soil modified by industrial waste iron tailings sand, the enhancement of expansive soil is explored from macroscopic and microscopic aspects. After characterization and testing by various means, the results show that expansive soil modified by iron tailings sand will increase the maximum dry density of the improved soil and reduce its optimal moisture content, which is beneficial in tuning the moisture content at the construction site. In addition, iron tailings sand can improve the shear strength of expansive soils. The influence of iron tailings sand on cohesion increases first, then decreases, and reaches the peak value at 30%, while the effect on internal friction angle exhibits a continuously increasing trend. Furthermore, according to mercury intrusion tests and microangle analysis, the addition of iron tailings sand can reduce the tiny pores and enhance the occlusal force of the soil. Simultaneously, it increases the number of large pores, maximizing the macroscopic strengthening of iron tailings sand towards the expansive soil.
Solution of Fully Bipolar Fuzzy Linear Programming Models
Authors: Mehmood Muhammad Athar , Akram Muhammad , Alharbi Majed G. , Bashir Shahida
Published: April 2021

The Yin-Yang bipolar fuzzy set is a powerful mathematical tool for depicting fuzziness and vagueness. We first extend the concept of crisp linear programming problem in a bipolar fuzzy environment based on bipolar fuzzy numbers. We first define arithmetic operations of unrestricted bipolar fuzzy numbers and multiplication of an unrestricted trapezoidal bipolar fuzzy number (TrBFN) with non-negative TrBFN. We then propose a method for solving fully bipolar fuzzy linear programming problems (FBFLPPs) with equality constraints in which the coefficients are unrestricted triangular bipolar fuzzy numbers and decision variables are nonnegative triangular bipolar fuzzy numbers. Furthermore, we present a method for solving FBFLPPs with equality constraints in which the coefficients and decision variables are unrestricted TrBFNs. The FBFLPP is transformed into a crisp linear programming problem, and then, it is solved to achieve the exact bipolar fuzzy optimal solution. We illustrate the proposed methodologies with several numerical examples.
[Retracted] Intelligent Garden Planning and Design Based on Agricultural Internet of Things
Authors: Jia Aijun
Published: April 2021

As the application of the Internet of Things technology continues to deepen in various fields, it also continues to develop in the agricultural field and the agricultural landscape. This article uses the agricultural Internet of Things to conduct an in‐depth analysis and research on the planning and design of smart gardens and combines field research and project practice on the basis of theoretical analysis. Through the combination of agricultural Internet of Things technology and agricultural landscape, the planning and design of smart gardens are studied. The theories used include Internet of Things technology, agricultural industrialization theory, sustainable agricultural development theory, new rural construction theory in agricultural disciplines, ecotourism theory, tourism psychology theory in tourism disciplines, landscape ecology theory, landscape aesthetics theory, and garden planning and design theory. From related theories to planning and design practice, a more systematic study of the smart park has been carried out to provide scientific guidance for the agriculture of the smart park. To provide scientific guidance for the planning and design of agricultural IoT of smart gardens, the theoretical system of planning and design of smart gardens based on the integration of agricultural IoT is proposed and systematically elaborated, including its concept, characteristics, related theories, and guidance methods.