bluuebunny/crossref_metadata_2025 huggingface dataset:
Circulating immune cell landscape in patients who had mild ischaemic stroke
Authors: Cho Young-Eun , Lee Hyangkyu , Bae Heekyong R. , Kim Hyungsuk , Yun Sijung , Vorn Rany , Cashion Ann , Rucker Mary Jo , Afzal Mariam , Latour Lawrence , Gill Jessica
Published: March 2022

Introduction

Patients who had a mild ischaemic stroke who present with subtle or resolving symptoms sometimes go undiagnosed, are excluded from treatment and in some cases clinically worsen. Circulating immune cells are potential biomarkers that can assist with diagnosis in ischaemic stroke. Understanding the transcriptomic changes of each cell population caused by ischaemic stroke is critical because they work closely in a complicated relationship. In this study, we investigated peripheral blood mononuclear cells (PBMCs) transcriptomics of patients who had a stroke using a single-cell RNA sequencing to understand peripheral immune response after mild stroke based on the gene expression in an unbiased way.

Methods

Transcriptomes of PBMCsfrom 10 patients who had an acute ischaemic stroke within 24 hours after stroke onset were compared with 9 race-matched/age-matched/gender-matched controls. Individual PBMCs were prepared with ddSeqTM(Illumina-BioRad) and sequenced on the Illumina NovaSeq 6000 platform.

Results

Notable population changes were observed in patients who had a stroke, especially in NK cells and CD14+ monocytes. The number of NK cells was increased, which was further confirmed by flow cytometry. Functional analysis implied that the activity of NK cells also is enhanced in patients who had a stroke. CD14+ monocytes were clustered into two groups; dendritic cell-related CD14+ monocytes and NK cell-related CD14+ monocytes. We found CD14+ monocyte subclusters were dramatically reduced in patients who had a stroke.

Discussion

This is the first study demonstrating the increased number of NK cells and new monocyte subclusters of mild ischaemic stroke based on the transcriptomic analysis. Our findings provide the dynamics of circulating immune response that could assist diagnosis and potential therapeutic development of mild ischaemic stroke.
Testing generalized spacetimes for black holes using the Hod function representation of the hoop conjecture
Authors: Nandi K. K. , Izmailov R. N. , Karimov R. Kh. , Garipova G. M. , Volotskova R. R. , Potapov A. A.
Published: March 2022

The hoop conjecture, due to Thorne, is a fundamental aspect of black holes in classical general relativity. Recently, generalized classes of regular spherically symmetric static black holes with arbitrary exponents coupled to nonlinear electrodynamics have been constructed in the literature. The conjecture in those spacetimes could be violated if only the asymptotic mass $$M_{\infty }$$

M
∞

is used. To avoid such violations, Hod earlier suggested the appropriate mass function and stated the conjecture in terms of what we call the Hod function. The conjecture can then be applied to any given static spacetime to test whether or not it represents black holes. It is shown here that the conjecture is protected in the above constructed class of generalized spacetimes thus supporting them as black holes. However, it is argued that there are factors, including violation of the conjecture, that militate against the proposed new class of solutions to be qualifying as black holes. Finally, we exemplify that the Hod mass $$M(r\le R)$$

M
(
r
≤
R
)

in the conjecture is exactly the matter counterpart of the Misner–Sharp geometrical quasilocal mass $$m(r\le R)$$

m
(
r
≤
R
)

of general relativity. Thus any conclusion based on Hod function is strictly a conclusion of general relativity.
Slope of orderable Dehn filling of two-bridge knots
Authors: Gao Xinghua
Published: March 2022

In this paper, we study the Riley polynomial of double twist knots with higher genus. Using the root of the Riley polynomial, we compute the range of rational slope [Formula: see text] such that [Formula: see text]-filling of the knot complement has left-orderable fundamental group. Further more, we make a conjecture about left-orderable surgery slopes of two-bridge knots.
Greybody factor and thermal fluctuations of rotating black hole with perfect fluid dark matter
Authors: Ama-Tul-Mughani Qanitah , Mumtaz Saadia , us Salam Wardat , Ikram Ayesha
Published: March 2022

This paper deals with formulation of analytic solution for greybody factor taking a rotating black hole (BH) in the vicinity of perfect fluid dark matter. To this end, the Klein–Gordon equation is transformed into the standard Schrödinger equation in order to portray the behavior of effective potential. We compute the asymptotic solutions in two different regimes, namely, BH and far field horizons under the influence of perfect fluid dark matter. The derived solutions are smoothly matched in an intermediate region for the sake of their viability. It is observed that a large amount of radiations approach infinity by decreasing intensity of dark matter in the surrounding of BH and hence the greybody factor increases. We also analyze the impact of thermal fluctuations on the considered gravitational background. In this context, the corrected entropy near the equilibrium state is computed which further modifies other thermodynamic potentials. We conclude that the larger BHs become more stable taking positive ranges of specific heat in the vicinity of quantum corrections.
PERSONALIZED FLOW DIVISION METHOD BASED ON THE LEFT-RIGHT CORONARY CROSS-SECTIONAL AREA
Authors: LI NA , LIU JINCHENG , LI BAO , BAI LAN , FENG YILI , LIU JIAN , ZHANG LIYUAN , YANG HAISHENG , LIU YOUJUN
Published: March 2022

This paper proposes a personalized method to estimate blood flow distribution based on the cross-sectional area of the left-right coronary artery openings. According to the cross-sectional area of the left-right coronary artery in 30 cases, a personalized flow distribution model was derived. A 0D/3D geometric multiscale model was used for the numerical simulation of FFR. To evaluate the accuracy of the cross-sectional area method, invasive FFR was used as the standard. The diagnostic efficiency of the proposed method was verified through the simulation results of the volume and the fixed ratio methods. The flow of the left-right coronary artery was proportional to the 3/4 power of the cross-sectional area. The 95% LOA between the cross-sectional area method, volume method, fixed ratio method and FFR were [Formula: see text]0.06 ([[Formula: see text]0.22, 0.10]), [Formula: see text]0.03 ([[Formula: see text]0.35, 0.28]), and [Formula: see text]0.05 ([[Formula: see text]0.30, 0.20]), the accuracy values were 94.44%, 77.78%, and 77.78%, respectively. Flow distribution based on the cross-sectional area represents the supply and demand relationship of the myocardium. The flow of the left-right coronary arteries is proportional to the 3/4 exponent of the cross-sectional area, which affects the accuracy of FFRCT by affecting the exit boundary conditions of the 0D/3D model.
Near Riesz and Besselian Hilbert–Schmidt operator sequences
Authors: Zhang Xiao-Li , Li Yun-Zhang
Published: March 2022

Hilbert–Schmidt frame (HS-frame) has interested some mathematicians in recent years, which is more general than g-frame. This paper addresses near Riesz and Besselian properties of HS-operator sequences. We characterize HS-frame and Riesz properties of g-operator sequences using their DSI-sequences; prove that an HS-Riesz basis is an exact HS-frame while the converse is not true, and an arbitrary HS-Riesz frame contains an HS-Riesz basis; and present the connection among near HS-Riesz property, Besselian property and the kernel space dimension of synthesis operator of an HS-operator sequence.
ANALYSIS OF THE CARBON ALLOWANCE ALLOCATION AND SECTORAL COVERAGE IN THE CARBON MARKET UNDER THE NEW CLIMATE AMBITION: A CASE STUDY IN CHINA
Authors: CHENG SI , ZHANG JIHONG , QI SHAOZHOU
Published: March 2022

Reasonable allocation of carbon allowances and determination of coverage in the carbon market are essential to the realization of the emissions reduction goal. Using China as an example, we propose a multi-criteria allocation scheme based on the principle of equity, efficiency and feasibility, considering carbon abatement costs and carbon leakage risks. An improved zero-sum gains-data envelopment analysis model in accordance with China’s new carbon intensity target in climate ambition is used for allowance allocation. Subsequently, the sectoral coverage choice of the carbon market is proposed. We obtain an optimal reallocation scheme after five iterations. The results show that the allocation method in this study can better promote the carbon market to reduce emissions at a lower cost while preventing carbon leakage to a certain extent. Based on the contribution to the overall emission reduction, the emission reduction costs and carbon leakage risks, we further classify the sectors into three categories. With China as an example, these findings lay a scientific basis for China to achieve its climate ambition through the carbon market, and also have global implications in regard to developing a more scientific allocation scheme, especially for carbon markets in emerging and developing countries.
Stratigraphic architecture, sedimentology and structure of the Middle Pleistocene Corinth Canal (Greece)
Authors: Caterina Basile , Rubi Romain , Hubert-Ferrari Aurélia
Published: March 2022

The artificial Corinth Canal connects the Aegean Sea with the Corinth Gulf, and displays high steep walls that enable the study of the sedimentological structure of this area. A former strait naturally connecting the gulf with the Aegean Sea is assumed to have existed in this area. Therefore, this exceptionally well-exposed site could be used as an analogue to study tidal straits after its stratigraphic architecture, sedimentology and structure have been defined. To do so, we used field observations associated with a 3D model built using drone imaging. We document a strait divided into a central zone and two adjacent dune-bedded strait zones. The centre is an active horst where sediment bypass occurred. On both sides of this, opposite-dipping conglomeratic dunes are represented by simple- and compound-dune foreset architectures with multiscale asymmetrical herringbone cross-stratifications. These observations document a tidal strait with conglomeratic dune-bedded strait zones in a micro-tidal context. These
c.
300 ka strait deposits are the only ones preserved in the canal area. After deposition ended, this connection disappeared due to regional uplift and the offset of the Kalamaki–Isthmia Fault. This palaeostrait helps to improve our understanding of Middle–Late Pleistocene palaeogeography and the structural controls on sea connections.
Seismic morphologies of submerged late glacial to Early Holocene landscapes at the eastern Dogger Bank, central North Sea Basin – implications for geo-archaeological potential
Authors: Andresen Katrine Juul , Hepp Daniel A. , Keil Hanno , Spiess Volkhard
Published: March 2022

The inundated Doggerland in the North Sea Basin has been a coveted research target for many years owing to its key location with respect to geological evolution since the last glaciation and its archaeological potential related to prehistoric hunter–gatherer populations. Still, many uncertainties related to glacial and sea-level forcing on erosion and deposition remain, and the first discovery of submerged settlements is yet to be reported. In this study, we present a range of seismic morphologies and facies characteristic for the late glacial and Holocene succession near a major drainage system at the eastern Dogger Bank. Five of these facies are dominant in the area while two facies can be associated with a terrestrial–fluvial landscape buried 0–22 m below the seafloor. We detect various erosion levels of the terrestrial–fluvial landscape that are greatest towards the south where sediment has been removed, probably owing to combined terrestrial–fluvial and marine erosion. We find that five subareas show geo-archaeological potential in terms of (1) the preservation degree of terrestrial strata based on erosion estimates, (2) the accessibility of terrestrial strata based on burial depths and (3) the palaeolandscape configuration based on the spatial setting in relation to the drainage system and the palaeocoastlines. We further document a geological evolution of the study area, which is comparable with the evolution at the western Dogger Bank. However, we find more evidence for an extended flooding period because of the vicinity to the major drainage system and the Elbe Paleo Valley. We propose that our approach can be used as a workflow for marine investigations that focus on submerged hunter–gatherer heritage.
AI-Based Efficient WUGS Network Channel Modeling and Clustered Cooperative Communication
Authors: R Kanthavel , R Dhaya , A Ahilan
Published: March 2022

Wireless underground sensor networks (WUSNs) are sub-ground-surface sensor node networks designed to establish real-time tracking capacities in diverse underground ecosystems composed of soil, water, oil, and other materials. The contact medium is the key distinction between USNs and terrestrial wireless sensor networks. The communication properties of electromagnetic (EM) waves in underwater resources like mud, water, oil, and other materials, as well as major variations between propagation in air, make classification of the underground wireless channel difficult. From the transmission of data, the channels modelling is involved to remove the noise and reduce the energy. After that Multi-driven Clustering Algorithm (MCA) method is used to cluster the channel based on the EDT method (Energy, Distance, and Time). Completing the transmission, the data can be transmitted to the destination. The experimental portion of the proposed method is analyzed by varying parameters such as energy, throughput, channel response, and time duration of the data transmission. From the experimental analysis, it is observed that 55% and 45% more energy levels can be saved with the proposed MCA method than with the LEACH methods for DR and SW media methods, respectively. The throughput of the proposed method is proven with 45% and 42% improvement over the time horizon in the median under the frequency for soil of the LEACH and LEACH-CO2 methods, correspondingly.
Equity-based CS Case Study: An Approach to Exploring White Teachers’ Conceptions of Race and Racism in a Professional Development Setting
Authors: Veeragoudar Sneha , Sullivan Florence R.
Published: March 2022

Here, we present the results of a study of in-service teachers’ responses to equity-based case study vignettes focused on racialized classroom incidents. This study was conducted in the context of an ongoing research practice partnership aimed at integrating computer science concepts in elementary grades. Our work took place in a public school district that enrolls primarily students of color, while largely employing White teachers and administrators. Using a racial literacy framework [Guinier
2004
], we conceptualized a continuum and developed codes to analyze teachers’ responses from racially liberal to racially literate. Our results describe a range of positions across the continuum, including those consistent with the racial liberalism viewpoint that expresses individualistic views of meritocracy and colorblindness that sometimes supports a deficit view of students, those that reside in the middle who validate equity work through minimal acknowledgment yet find ways to resist further engagement with race or equity, and those who express views consistent with racial literacy practices including student-centered perspectives, asset-orientations, and the willingness to engage race directly. Further, our results indicate that teachers may express contradictory views or views across the continuum. These findings point to the developmental nature of racial literacy and the difficulty of unlearning racist mindsets. We discuss the efficacy of our case study design: anonymized, locally derived vignettes, and our case study learning activity design: written reflections, small group dialogues, and whole group share-outs in supporting teacher reflection and learning. Finally, we demonstrate the special leadership role of teachers who are moving toward racial literacy.
Computational Mirror Cup and Saucer Art
Authors: Wu Kang , Chen Renjie , Fu Xiao-Ming , Liu Ligang
Published: March 2022

In the mirror cup and saucer art created by artists Yul Cho and Sang-Ha Cho, part of the saucer is directly visible to the viewer, while the other part of the saucer is occluded and can only be seen as a reflection through a mirror cup. Thus, viewers see an image directly on the saucer and another image on the mirror cup; however, the existing art design is limited to wavelike saucers. In this work, we propose a general computational framework for mirror cup and saucer art design. As input, we take from the user one image for the direct view, one image for the reflected view, and the base shape of the saucer. Our algorithm then generates a suitable saucer shape by deforming the input shape. We formulate this problem as a constrained optimization for the saucer surface. Our framework solves for the fine geometry details on the base shape along with its texture, such that when a mirror cup is placed on the saucer, the user-specified images are observed as direct and reflected views. Through extensive experiments, we demonstrate the effectiveness of our framework and the great design flexibility that it offers to users. We further validate the produced art pieces by fabricating the colored saucers using three-dimensional printing.
“Every Website Is a Puzzle!”
: Facilitating Access to Common Website Features for People with Visual Impairments
Authors: Barbosa Natã M. , Hayes Jordan , Kaushik Smirity , Wang Yang
Published: March 2022

Navigating unfamiliar websites is challenging for users with visual impairments. Although many websites offer visual cues to facilitate access to pages/features most websites are expected to have (e.g., log in at the top right), such visual shortcuts are not accessible to users with visual impairments. Moreover, although such pages serve the same functionality across websites (e.g., to log in, to sign up), the location, wording, and navigation path of links to these pages vary from one website to another. Such inconsistencies are challenging for users with visual impairments, especially for users of screen readers, who often need to linearly listen to content of pages to figure out how to access certain website features. To study how to improve access to main website features, we iteratively designed and tested a command-based approach for main features of websites via a browser extension powered by machine learning and human input. The browser extension gives users a way to access high-level website features (e.g., log in, find stores, contact) via keyboard commands. We tested the browser extension in a lab setting with 15 Internet users, including 9 users with visual impairments and 6 without. Our study showed that commands for main website features can greatly improve the experience of users with visual impairments. People without visual impairments also found command-based access helpful when visiting unfamiliar, cluttered, or infrequently visited websites, suggesting that this approach can support users with visual impairments while also benefiting other user groups (i.e., universal design). Our study reveals concerns about the handling of unsupported commands and the availability and trustworthiness of human input. We discuss how websites, browsers, and assistive technologies could incorporate a command-based paradigm to enhance web accessibility and provide more consistency on the web to benefit users with varied abilities when navigating unfamiliar or complex websites.
Technologies to Assess Drug Response and Heterogeneity in Patient-Derived Cancer Organoids
Authors: Skala Melissa C. , Deming Dustin A. , Kratz Jeremy D.
Published: March 2022

Patient-derived cancer organoids (PDCOs) are organotypic 3D cultures grown from patient tumor samples. PDCOs provide an exciting opportunity to study drug response and heterogeneity within and between patients. This research can guide new drug development and inform clinical treatment planning. We review technologies to assess PDCO drug response and heterogeneity, discuss best practices for clinically relevant drug screens, and assert the importance of quantifying single-cell and organoid heterogeneity to characterize response. Autofluorescence imaging of PDCO growth and metabolic activity is highlighted as a compelling method to monitor single-cell and single-organoid response robustly and reproducibly. We also speculate on the future of PDCOs in clinical practice and drug discovery.Future development will require standardization of assessment methods for both morphology and function in PDCOs, increased throughput for new drug development, prospective validation with patient outcomes, and robust classification algorithms.
Flow Chemistry: A Sustainable Voyage Through the Chemical Universe en Route to Smart Manufacturing
Authors: Volk Amanda A. , Campbell Zachary S. , Ibrahim Malek Y.S. , Bennett Jeffrey A. , Abolhasani Milad
Published: March 2022

Microfluidic devices and systems have entered many areas of chemical engineering, and the rate of their adoption is only increasing. As we approach and adapt to the critical global challenges we face in the near future, it is important to consider the capabilities of flow chemistry and its applications in next-generation technologies for sustainability, energy production, and tailor-made specialty chemicals. We present the introduction of microfluidics into the fundamental unit operations of chemical engineering. We discuss the traits and advantages of microfluidic approaches to different reactive systems, both well-established and emerging, with a focus on the integration of modular microfluidic devices into high-efficiency experimental platforms for accelerated process optimization and intensified continuous manufacturing. Finally, we discuss the current state and new horizons in self-driven experimentation in flow chemistry for both intelligent exploration through the chemical universe and distributed manufacturing.
Editors’ Choice—Lithium Primary Batteries Employing Multi-Electron Carbon-Fluorine Bond Cleavage in Perfluoroalkylated Reactants
Authors: Gao Haining , Sevilla Alejandro , Gallant Betar M.
Published: March 2022

While Li−carbon monofluoride (CFx) is the current energy leader among primary batteries, the technology is maturing, motivating further fundamental study of Li battery chemistry based on C−F redox. This study examines the possibility to conduct multi-electron carbon reduction using a candidate class of liquid CFx analogues, perfluoroalkyl iodides (CnF2n+1I, with F/C ratios of x > 2), in supporting electrolyte as catholytes for Li cells. The large, polarizable iodine supports electrochemical reduction with concerted F− ligand expulsion, forming lithium fluoride (LiF) as the main solid discharge product. Under initial conditions (1 M reactant and 0.3 mA cm−2 in dimethylsulfoxide), only limited defluorination (1.5 e−/molecule) is accessed. Governing factors for C−F bond redox are further investigated, including reactant concentration, discharge rate, temperature, and solvent properties (e.g. catholyte viscosity). A maximum of 8 e−/C6F13I, or 8/13 available F, is accessible in the voltage range 2.8−1.9 V vs Li/Li+ with low reactant concentrations (0.1 M) and rates (20 μA cm−2). The data indicate that multiple handles exist to tailor extended C−F bond activation in these reactants. However, premature reaction termination caused by deactivation of intermediates, which is particularly exacerbated at higher concentrations and/or rates, is likely to be a persistent challenge for practical applications.
Communication—Exploration of Plasma Oxidized Copper Oxide as a Copper Passivation Layer
Authors: Su Jia Quan , Kuo Yue
Published: March 2022

Passivation properties of the plasma oxidized copper oxide on the copper line have been studied using the electromigration stress method. The self-aligned copper oxide passivation layer has the unique property of gettering copper atoms diffused through it at the high temperature raised from the stress current induced Joule heating. On the other hand, the line broken time is shortened with the increase of the copper oxide passivation layer thickness. Therefore, for the passivation application, a thin copper oxide layer is better than a thick copper oxide layer.
On Computation of Degree-Based Entropy of Planar Octahedron Networks
Authors: Sun Tian-Le , Ali Haidar , Ali Bilal , Ali Usman , Liu Jia-Bao , Ali Parvez
Published: March 2022

Chemical graph theory is the combination of mathematical graph theory and chemistry. To analyze the biocompatibility of the compounds, topological indices are used in the research of QSAR/QSPR studies. The degree-based entropy is inspired by Shannon’s entropy. The connectivity pattern such as planar octahedron network is used to predict physiochemical activity. In this article, we present some degree-based entropies of planar octahedron network.
A Method for Improving Prediction of Human Heart Disease Using Machine Learning Algorithms
Authors: Saboor Abdul , Usman Muhammad , Ali Sikandar , Samad Ali , Abrar Muhmmad Faisal , Ullah Najeeb
Published: March 2022

A great diversity comes in the field of medical sciences because of computing capabilities and improvements in techniques, especially in the identification of human heart diseases. Nowadays, it is one of the world’s most dangerous human heart diseases and has very serious effects the human life. Accurate and timely identification of human heart disease can be very helpful in preventing heart failure in its early stages and will improve the patient’s survival. Manual approaches for the identification of heart disease are biased and prone to interexaminer variability. In this regard, machine learning algorithms are efficient and reliable sources to detect and categorize persons suffering from heart disease and those who are healthy. According to the recommended study, we identified and predicted human heart disease using a variety of machine learning algorithms and used the heart disease dataset to evaluate its performance using different metrics for evaluation, such as sensitivity, specificity, F-measure, and classification accuracy. For this purpose, we used nine classifiers of machine learning to the final dataset before and after the hyperparameter tuning of the machine learning classifiers, such as AB, LR, ET, MNB, CART, SVM, LDA, RF, and XGB. Furthermore, we check their accuracy on the standard heart disease dataset by performing certain preprocessing, standardization of dataset, and hyperparameter tuning. Additionally, to train and validate the machine learning algorithms, we deployed the standard K-fold cross-validation technique. Finally, the experimental result indicated that the accuracy of the prediction classifiers with hyperparameter tuning improved and achieved notable results with data standardization and the hyperparameter tuning of the machine learning classifiers.
A Hybrid Multi-Objective Particle Swarm Optimization with Central Control Strategy
Authors: Yang Meilan , Liu Yanmin , Yang Jie
Published: March 2022

In recent years, researchers have solved the multi-objective optimization problem by making various improvements to the multi-objective particle swarm optimization algorithm. However, we propose a hybrid multi-objective particle swarm optimization (CCHMOPSO) with a central control strategy. In this algorithm, a disturbance strategy based on boundary fluctuations is first used for the updated new particles and nondominant particles. To prevent the population from falling into a local extremum, some particles are disturbed. Then, when the external archive capacity reaches the extreme value, we use a central control strategy to update the external archive, so that the archive solution gets a good distribution. When the dominance of the current particle and the individual best particle cannot be determined, to enhance the diversity of the population, the combination method of the current particle and the individual best particle can be used to update the individual best particle. The experimental results show that CCHMOPSO is better than four multi-objective particle swarm optimization algorithms and four multi-objective evolutionary algorithms. It is a feasible method for solving multi-objective optimization problems.
Space Information Network Resource Scheduling for Cloud Computing: A Deep Reinforcement Learning Approach
Authors: Wang Yufei , Liu Jun , Yin Yanhua , Tong Yu , Liu Jiansheng
Published: March 2022

With the development of satellite technology, space information networks (SINs) have been applied to various fields. SINs can provide more and more complex services and receive more and more tasks. The existing resource scheduling algorithms are difficult to play an efficient role in such a complex environment of resources and tasks. We propose a resource allocation scheme based on reinforcement learning. Firstly, according to the characteristics of the resources of SINs, we established the cloud computing architecture of SINs to manage the resources uniformly. Next, we adopt a variable granularity resources clustering algorithm based on fuzzy and hierarchical clustering algorithms. This algorithm can adaptively adjust the resource size and reduce the scheduling range. Finally, we model the resource scheduling process by a reinforcement learning algorithm to solve the joint resource scheduling problem. The simulation results show that the scheme can effectively reduce resources consumption, shorten the task execution time, and improve the resource utilization efficiency of SINs.
Preventive Potential of the Aqueous Extract of the Mixture of Bidens pilosa (Asteraceae) and Cymbopogon citratus (Poaceae) Aerial Parts on Hypertension Induced by a Chronic Salt and Alcohol Consumption on the Rats
Authors: Tcheutchoua Yannick Carlos , Bilanda Danielle Claude , Dzeufiet Paul Désiré Djomeni , Djunie Neali Oriane Corine , Owona Pascal Emmanuel , Bidingha Ronald à Goufani , Ngapout Rodrigue Fifen , Mbolang Lohik Nguegan , Noubom Michel , Dimo Théophile , Kamtchouing Pierre
Published: March 2022

High blood pressure (HBP) is currently one of the main risk factors for cardiovascular and kidney diseases. Nowadays, populations make extensive use of alternative medicine for their health problems. Bidens pilosa (B. pilosa) and Cymbopogon citratus (C. citratus) are used individually in the traditional treatment of cardiovascular disorders. This study assessed the effects of the mixture of these two plants aqueous extract on HBP in rats. Male rats (42) were divided into 7 groups of 6 rats each. Normotensive rats received only distilled water and formed group 1. The other animals received ethanol + salt preceded by distilled water (10 mL/kg; group 2) and spironolactone (10 mg/kg; group 3); the aqueous extracts of the mixture (100 and 200 mg/kg; groups 4 and 5) isolated plants B. pilosa (200 mg/kg; group 6) and C. citratus (200 mg/kg; group 7). Animals were treated for 7 weeks during which water consumption and urine volume were assessed; then, hemodynamic parameters were recorded, and rats were sacrificed. Serum and some organs (liver, kidney, heart, and aorta) were used to evaluate biochemical parameters. Ingestion of ethanol + salt leads to a significant increase in urinary volume and water intake that were significantly prevented by the extracts from the mixture and isolated plants. Ethanol + salt solution significantly increased the blood pressure, heart rate, triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-chol), very-low-density lipoprotein cholesterol (VLDL-chol), atherogenic indices, liver and kidney function parameters, and malondialdehyde (MDA) levels. However, the levels of high-density lipoprotein cholesterol (HDL-chol), albumin, reduced glutathione (GSH), catalase, and superoxide dismutase (SOD) activity were significantly reduced. The extracts of the mixture and isolated plants significantly prevented all these variations with a more pronounced action for the lowest dose of the mixture on the lipid profile, oxidative stress, and kidney function. These observations confirm the beneficial effects of B. pilosa and C. citratus to manage hypertension.
Midazolam Suppresses Hepatocellular Carcinoma Cell Metastasis and Enhances Apoptosis by Elevating miR-217
Authors: Shen Qian , Xia Yanqiong , Yang Leilei , Wang Bo , Peng Jian
Published: March 2022

Background. Hepatocellular carcinoma (HCC) is a significant cause of human death in the world. Recently, it is found that midazolam can modulate miRs to participate in HCC progression. This research project was designed to elucidate the impacts of midazolam and miR-217 on HCC cell metastasis and apoptosis. Methods. Human HCC cell strains (Hep3B and SK-HEP-1) were selected and intervened by midazolam at different concentrations in our research. miR-217-inhibitor intervened in the two HCC cell strains to observe the alterations of cell migration, invasiveness, and apoptosis. The miR-217 level in HCC cells was identified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Results. As midazolam concentration was elevated, Hep3B and SK-HEP-1 viabilities were more obviously suppressed. The 10 μg/mL concentration was selected for analysis since Hep3B and SK-HEP-1 had an IC50 of 10.57 μg/mL and 9.35 μg/m, respectively. The qRT-PCR results showed the decreased of miR-217 in HCC cells, which was enhanced notably by midazolam intervention. Compared with the blank group, the invasiveness and migration (Transwell assay) of miR-217-inhibitor-transfected HCC cells were distinctly enhanced and the apoptosis rate (flow cytometry) was noticeably reduced. Conclusion. Midazolam can upregulate miR-217 in HCC cells, thus inhibiting HCC cell metastasis and apoptosis.
Homogeneous Decision Community Extraction Based on End-User Mental Behavior on Social Media
Authors: Gupta Suneet , Kumar Sumit , Bangare Sunil L. , Nuhmani Shibili , Alguno Arnold C. , Samori Issah Abubakari
Published: March 2022

Aiming at the inadequacy of the group decision-making method with the current attribute value as interval language information, an interval binary semantic decision-making method is proposed, which considers the decision maker’s psychological behavior. The scope of this research is that this paper is based on localized amplification method. The localized amplification method used in this research may amplify physiological movement after removing unwanted noise, allowing the movement trend to be seen with the naked eye, improving the CNN network’s mental identification accuracy. These two algorithms analyze the input picture from various perspectives, allowing the CNN network to extract more information and enhance identification accuracy. A new distance formula with interval binary semantics closer to decision-makers thinking habits is defined; time degree is introduced. An optimization model is established to solve the time series weights by considering the comprehensive consistency of expert evaluation. Based on prospect theory, a prospect deviation value is constructed and minimized weight optimization model, using the interactive multiple attribute decision community making (TODIM) method based on the new distance measure to calculate the total overall dominance of the schemes to rank the schemes. Taking the selection and evaluation of supply chain collaboration partners as an example, the effectiveness and rationality of the proposed method are verified.
A Mining Strategy for Minimizing Waiting Time in Blockchains for Time-Sensitive Applications
Authors: Ramezan Gholamreza , Leung Cyril , Miao Chunyan
Published: March 2022

Blockchain, as proposed in Bitcoin, focuses on securing financial transactions. However, in recent years, the use of blockchain has expanded to a wide range of networks and application domains. This includes time-sensitive applications which need transactions to be processed fast enough to meet delay requirements. Reducing the transaction waiting time in the mining process is key to the successful adoption of blockchain in such applications. In this paper, we propose a mining strategy that is aimed at minimizing the average waiting time per transaction by ensuring a certain minimum required block size, based on the average transaction arrival rate, mining service rate, and maximum block size. We derive an expression for the average transaction waiting time of the proposed mining strategy and determine the optimal mining rule. Numerical results show that the average waiting time per transaction can be reduced by up to

15
%

using the proposed mining strategy compared to the traditional strategy in which miners immediately start the next mining round using the transactions already waiting in the pool.
Expression of Peripheral Blood DCs CD86, CD80, and Th1/Th2 in Sepsis Patients and Their Value on Survival Prediction
Authors: Du Ke , Hao Shaobo , Luan Heyun
Published: March 2022

Objective. To explore the expression of peripheral blood dendritic cells (DCs) CD86, CD80, and Th1/Th2 in patients with sepsis and their value on survival prediction. Methods. 118 patients with sepsis from January 2019 to December 2020 were selected, According to the prognosis, the patients were divided into the death group (

n
=
46

) and survival group (

n
=
72

). The general data and pathogen division of the two groups were collected, and the levels of peripheral blood DCs CD86, CD80, and Th1/Th2; APACHE II score; inflammatory factor (procalcitonin (PCT)); and cell growth chemokine (GRO) were compared between the two groups heparin-binding protein (HBP) and myocardial enzyme indexes (creatine kinase (CK), creatine kinase isozyme (CK-MB), and lactate dehydrogenase (LDH)) to explore the relationship between CD86, CD80, Th1/Th2, and various serological indexes and the evaluation value of prognosis. Results. 124 strains of pathogenic bacteria were isolated from 118 patients, including 78 strains of gram-negative bacteria (62.90%), 31 strains of Gram-positive bacteria (25.00%), and 15 strains of fungi (12.10%). The scores of CD86, CD80, Th1, Th2, Th1/Th2, and APACHE II in the dead group were higher than those in the surviving group, and the difference was statistically significant (

P
<
0.05

). PCT, GRO-α, HBP, LDH, CK-MB, and CK levels of patients in death group were higher than those in survival group, and the difference was statistically significant (

P
<
0.05

). The levels of peripheral blood DCs CD86, CD80, and Th1/Th2 were positively correlated with PCT, GRO-α, HBP, LDH, CK-MB, and CK (

P
<
0.05

). ROC curve analysis showed that the AUC of the combined detection of DCs CD86, CD80, and Th1/Th2 in peripheral blood was 0.951, which was higher than 0.882, 0.883, and 0.734 of single index (

P
<
0.05

). Conclusion. All patients with sepsis have immune imbalance, and the peripheral blood CD86, CD80, and Th1/Th2 of the dead patients are higher than those of the survivors. The combined detection of these three indicators has the highest predictive value for the prognosis of patients.
Flow Field Simulation of Swirling Abrasive Jet Nozzle for Hard Rock Breaking
Authors: Dongqing Zhang , Jingbin Li , Xiao Hu , Xin Liu , Kang Cheng
Published: March 2022

Radial jet drilling (RJD) technology has been proved to be an economical and efficient stimulation technology for oil and gas, geothermal, hydrate, etc. but conventional RJD technology adopts pure water jet to break rock and form laterals, which has low rock breaking efficiency and is unable to effectively break hard rock such as shale. Swirling abrasive jet is proposed to promote the development of RJD. Here, the characteristics of the flow field of the swirling abrasive jet nozzle and the influence of the key impeller parameters are studied by numerical simulation. The distribution and development of axial velocity, tangential velocity, and radial velocity of water and abrasive are analyzed. The results show that the swirling abrasive jet has no constant velocity core, has stronger diffusivity, and can form a larger impact area than the direct jet. Abrasive particles and water can acquire large tangential and radial velocity which can break rock under the action of shear and tensile stress efficiently. With the increase of the spinning angle, the axial velocity of the fluid decreases, and the tangential velocity increases gradually. With the increase of blade thickness, the axial velocity decreases, and the tangential velocity increases. With the increase of the number of blades, the axial velocity decreases, and the tangential velocity increases. The spinning direction almost has no effect on the flow field. Therefore, the spinning angle is recommended to be no less than 270°, blade thickness is 2.5 mm, and number of blades are 3. The research results provide theoretical guidance for the structural design of swirling abrasive jet nozzles.
Architecture of Network-on-Chip (NoC) for Secure Data Routing Using 4-H Function of Improved TACIT Security Algorithm
Authors: Kumar N. Ashok , Shyni G. , Peter Geno , Stonier Albert Alexander , Ganji Vivekananda
Published: March 2022

In the technical world, NoC (network-on-chip) is a noticeable communication subsystem based on integrated circuits. It is mainly used in improving the performance of system-on-chip (SoC) by bridging the intellectual properties in the SoCs. But there is a need of protected architecture which is dealing with routing and processing data in the multicore system-on-chip (SoC). The recent issue with the above is there is still a drawback in enabling a better network routing system for accessing physical networks. The methodology of NoC mainly depends on the routing scheme, switching techniques, and structuring topologies. In this paper, we propose a new technique in implementing the chip in order to maintain the data privacy of NoC routers. There are many works with different algorithms that were evolved in enabling the secureness of NoCs, but due to the key size and block size, it is still not able to reach the expected effectiveness. Our proposed work is intended in designing a NoC architecture by means of embedding advanced TACIT security algorithm in Virtex-5 FPGA. Here, we used a hash function which is under a 4 hash function (4-H) scheme. The main advantage of this key generation scheme is it is applicable for block size and key size up to ‘

n

’ bit. Thus, this TACIT security algorithm enables ‘

n

’ bit using the software VHDL programming language in Xilinx ISE 14.2 and Modelsim 10.1 b which are applicable for 1024 bit and ‘

N

’ bits of block size on Virtex-5 FPGA systems. This design system can be enhanced by improving the factors like timing parameters, supporting memory, higher frequencies, and utilized summaries.
A Novel Self-Adaptive Mixed-Variable Multiobjective Ant Colony Optimization Algorithm in Mobile Edge Computing
Authors: Gong Yiguang , Wang Weixue , Gong Siqi
Published: March 2022

Mobile edge computing (MEC) provides physical resources closer to end users, becoming a good complement to cloud computing. The booming MEC brings many multiobjective optimization problems. The paper proposes a multiobjective optimization (MOO) algorithm called SAMOACOMV, which provides a new choice for solving MOO problems of MEC. We improve the ACOMV algorithm that is only suitable for solving mixed-variable single-objective optimization (SOO) problems and propose a MOACOMV algorithm suitable for solving mixed-variable MOO problems. And aiming at the dependence of MOACOMV algorithm performance on parameter setting, we proposed the SAMOACOMV algorithm using a self-adaptive parameter setting scheme. Furthermore, the paper also designs some mixed-variable MOO benchmark problems for the purpose to test and compare the performance of the SAMOACOMV algorithm. The experiments indicate that the SAMOACOMV algorithm has excellent comprehensive performance and is an ideal choice for solving mixed-variable MOO problems.
Cross-Border E-Commerce Logistics Transportation Alternative Selection: A Multiattribute Decision-Making Approach
Authors: Nie Xiangling
Published: March 2022

Cross-border e-commerce logistics and transportation system is important link in the cross-border e-commerce supply chain. How to choose a fast, safe, reliable, and low-cost logistics transportation mode is an urgent problem to be solved in cross-border e-commerce logistics. In view of this, this paper first analyzes the system characteristics of cross-border e-commerce logistics transportation systems and analyzes the factors affecting the choice of transportation mode from the perspective of reliability. Then, based on the ELECTRE method system, a multiattribute decision-making method for cross-border e-commerce logistics transportation mode selection is proposed. Finally, through a data example, it is verified that the model constructed in this paper and the proposed multiattribute decision-making method can effectively help cross-border e-commerce choose logistics transportation mode according to goods.
Efficient Lane Detection Technique Based on Lightweight Attention Deep Neural Network
Authors: Yao Zhiting , Chen Xiyuan
Published: March 2022

For self-driving vehicles, detecting lane lines in changeable scenarios is a fundamental yet challenging task. The rise of deep learning in recent years has contributed to the thriving of autonomous driving. However, existing methods of lane detection based on deep learning have high requirements on computing environment, so their applicability is further restricted. This paper proposed an improved attention deep neural network (DNN), a lightweight semantic segmentation architecture catering for efficient computation in low memory, which contains two branches worked in different resolution. The proposed network integrates fine details captured by local interaction of pixels at high resolution into global contexts at low resolution, computing dense feature maps for prediction task. Based on the attributes of disparate feature resolution characteristics, different attention mechanisms are adopted to guide the network to effectively exploit the model parameters. The proposed network achieves comparable results with state-of-the-art methods on two popular lane detection benchmarks (TuSimple and CULane), with faster calculation efficiency at 259 frames-per-second (FPS) on CULane dataset, and the total number of model parameters only requires 1.57 M. This study provides a practical and meaningful reference for the application of lane detection in memory constrained devices.