bluuebunny/crossref_metadata_2025 huggingface dataset:
HEART:

H

ybrid Memory and

E

nergy-

A

ware

R

eal-

T

ime Scheduling for Multi-Processor Systems
Authors: Günzel Mario , Hakert Christian , Chen Kuan-Hsun , Chen Jian-Jia
Published: September 2021

Dynamic power management (DPM) reduces the power consumption of a computing system when it idles, by switching the system into a low power state for hibernation. When all processors in the system share the same component, e.g., a shared memory, powering off this component during hibernation is only possible when all processors idle at the same time. For a real-time system, the schedulability property has to be guaranteed on every processor, especially if idle intervals are considered to be actively introduced.

In this work, we consider real-time systems with hybrid shared-memory architectures, which consist of shared volatile memory (VM) and non-volatile memory (NVM). Energy-efficient execution is achieved by applying DPM to turn off all memories during the hibernation mode. Towards this, we first explore the hybrid memory architectures and suggest a task model, which features configurable hibernation overheads. We propose a multi-processor procrastination algorithm (HEART), based on partitioned earliest-deadline-first (pEDF) scheduling. Our algorithm facilitates reducing the energy consumption by actively enlarging the hibernation time. It enforces all processors to idle simultaneously without violating the schedulability condition, such that the system can enter the hibernation state, where shared memories are turned off. Throughout extensive evaluation of HEART, we demonstrate (1) the increase in potential hibernation time, respectively the decrease in energy consumption, and (2) that our algorithm is not only more general but also has better performance than the state of the art with respect to energy efficiency in most cases.
Killing Processes or Killing Flash? Escaping from the Dilemma Using Lightweight, Compression-Aware Swap for Mobile Devices
Authors: Wang Yong-Xuan , Tsai Chung-Hsuan , Chang Li-Pin
Published: September 2021

Android apps become increasingly memory-demanding as software vendors add more and more new features to their apps. In the mean time, Android users often launch multiple apps and conveniently switch back and forth among the apps. Although running multiple apps imposes a high pressure on memory management, virtual-memory swap, an essential feature to improve the degree of multitasking, is disabled in fear of premature retirement of flash-based storage devices. Instead, Android employs a termination-based, process-level memory reclaiming method. We observed that process killing is, unfortunately, not effective in memory reclaiming and is highly negative to user experience. In this study, we advocate re-thinking using swap in Android for improved user experience with managed write stress on flash storage. Based on a series of empirical analyses of swap activities, we propose an enhanced page replacement policy and a page-compressing frontswap module. The proposed page replacement policy jointly considers page activeness and compressibility to boost the compression ratio of swap writes. A sampled-based method for page compressibility prediction is introduced so that decisions on page replacement can be made without compressing every page. We also design a frontswap module that strategically organizes compressed pages in the swap space for reducing the overhead of swap I/O operations.
Experimental results showed that compared with process killing, our method improved the app launching time and energy consumption by 58% and 19%, respectively; compared with the original swap, our approach reduced the swap write stress
by 65%.
Precise Correlation Extraction for IoT Fault Detection With Concurrent Activities
Authors: Lee Gyeongmin , Kim Bongjun , Song Seungbin , Kim Changsu , Kim Jong , Kim Hanjun
Published: September 2021

In the Internet of Things (IoT) environment, detecting a faulty device is crucial to guarantee the reliable execution of IoT services. To detect a faulty device, existing schemes trace a series of events among IoT devices within a certain time window, extract correlations among them, and find a faulty device that violates the correlations. However, if a few users share the same IoT environment, since their concurrent activities make non-correlated devices react together in the same time window, the existing schemes fail to detect a faulty device without differentiating the concurrent activities. To correctly detect a faulty device in the multiple concurrent activities, this work proposes a new precise correlation extraction scheme, called PCoExtractor. Instead of using a time window, PCoExtractor continuously traces the events, removes unrelated device statuses that inconsistently react for the same activity, and constructs fine-grained correlations. Moreover, to increase the detection precision, this work newly defines a fine-grained correlation representation that reflects not only sensor values and functionalities of actuators but also their transitions and program states such as contexts. Compared to existing schemes, PCoExtractor detects and identifies 40.06% more faults for 4 IoT services with concurrent activities of 12 users while reducing 80.3% of detection and identification times.
Learning Nondeterministic Real-Time Automata
Authors: An Jie , Zhan Bohua , Zhan Naijun , Zhang Miaomiao
Published: September 2021

We present an active learning algorithm named
NRTALearning
for nondeterministic real-time automata (NRTAs). Real-time automata (RTAs) are a subclass of timed automata with only one clock which resets at each transition. First, we prove the corresponding Myhill-Nerode theorem for real-time languages. Then we show that there exists a unique minimal deterministic real-time automaton (DRTA) recognizing a given real-time language, but the same does not hold for NRTAs. We thus define a special kind of NRTAs, named residual real-time automata (RRTAs), and prove that there exists a minimal RRTA to recognize any given real-time language. This transforms the learning problem of NRTAs to the learning problem of RRTAs. After describing the learning algorithm in detail, we prove its correctness and polynomial complexity. In addition, based on the corresponding Myhill-Nerode theorem, we extend the existing active learning algorithm NL* for nondeterministic finite automata to learn RRTAs. We evaluate and compare the two algorithms on two benchmarks consisting of randomly generated NRTAs and rational regular expressions. The results show that
NRTALearning
generally performs fewer membership queries and more equivalence queries than the extended NL* algorithm, and the learnt NRTAs have much fewer locations than the corresponding minimal DRTAs. We also conduct a case study using a model of scheduling of final testing of integrated circuits.
Predictive Monitoring with Logic-Calibrated Uncertainty for Cyber-Physical Systems
Authors: Ma Meiyi , Stankovic John , Bartocci Ezio , Feng Lu
Published: September 2021

Predictive monitoring—making predictions about future states and monitoring if the predicted states satisfy requirements—offers a promising paradigm in supporting the decision making of Cyber-Physical Systems (CPS). Existing works of predictive monitoring mostly focus on monitoring individual predictions rather than sequential predictions. We develop a novel approach for monitoring sequential predictions generated from Bayesian Recurrent Neural Networks (RNNs) that can capture the inherent uncertainty in CPS, drawing on insights from our study of real-world CPS datasets. We propose a new logic named
Signal Temporal Logic with Uncertainty
(STL-U) to monitor a flowpipe containing an infinite set of uncertain sequences predicted by Bayesian RNNs. We define STL-U strong and weak satisfaction semantics based on whether all or some sequences contained in a flowpipe satisfy the requirement. We also develop methods to compute the range of confidence levels under which a flowpipe is guaranteed to strongly (weakly) satisfy an STL-U formula. Furthermore, we develop novel criteria that leverage STL-U monitoring results to calibrate the uncertainty estimation in Bayesian RNNs. Finally, we evaluate the proposed approach via experiments with real-world CPS datasets and a simulated smart city case study, which show very encouraging results of STL-U based predictive monitoring approach outperforming baselines.
A switch in time
Authors: Edwards Chris
Published: September 2021

The introduction of the nanosheet transistor is just one step in the continuing attempt to stick to the spirit of Moore's Law.
Securing the wireless emergency alerts system
Authors: Lee Jihoon , Lee Gyuhong , Lee Jinsung , Im Youngbin , Hollingsworth Max , Wustrow Eric , Grunwald Dirk , Ha Sangtae
Published: September 2021

Modern cell phones are required to receive and display alerts via the Wireless Emergency Alert (WEA) program, under the mandate of the Warning, Alert, and Response Act of 2006. These alerts include AMBER alerts, severe weather alerts, and (unblockable) Presidential Alerts, intended to inform the public of imminent threats. Recently, a test Presidential Alert was sent to all capable phones in the U.S., prompting concerns about how the underlying WEA protocol could be misused or attacked. In this paper, we investigate the details of this system and develop and demonstrate the first practical spoofing attack on Presidential Alerts, using commercially available hardware and modified open source software. Our attack can be performed using a commercially available software-defined radio, and our modifications to the open source software libraries. We find that with only four malicious portable base stations of a single Watt of transmit power each, almost all of a 50,000-seat stadium can be attacked with a 90% success rate. The real impact of such an attack would, of course, depend on the density of cellphones in range; fake alerts in crowded cities or stadiums could potentially result in cascades of panic. Fixing this problem will require a large collaborative effort between carriers, government stakeholders, and cellphone manufacturers. To seed this effort, we also propose three mitigation solutions to address this threat.
Broadening participation by teaching accessibility
Authors: Walther Kendra , Ladner Richard E.
Published: September 2021

Strategies for incorporating accessibility into computing education.
Divide and conquer
Authors: Neville-Neil George V.
Published: September 2021

The use and limits of bisection.
The gastric conduction system in health and disease: a translational review
Authors: O’Grady Gregory , Gharibans Armen A. , Du Peng , Huizinga Jan D.
Published: September 2021

Gastric peristalsis is critically dependent on an underlying electrical conduction system. Recent years have witnessed substantial progress in clarifying the operations of this system, including its pacemaking units, its cellular architecture, and slow-wave propagation patterns. Advanced techniques have been developed for assessing its functions at high spatiotemporal resolutions. This review synthesizes and evaluates this progress, with a focus on human and translational physiology. A current conception of the initiation and conduction of slow-wave activity in the human stomach is provided first, followed by a detailed discussion of its organization at the cellular and tissue level. Particular emphasis is then given to how gastric electrical disorders may contribute to disease states. Gastric dysfunction continues to grow in their prevalence and impact, and while gastric dysrhythmia is established as a clear and pervasive feature in several major gastric disorders, its role in explaining pathophysiology and informing therapy is still emerging. New insights from high-resolution gastric mapping are evaluated, together with historical data from electrogastrography, and the physiological relevance of emerging biomarkers from body surface mapping such as retrograde propagating slow waves. Knowledge gaps requiring further physiological research are highlighted.
Transcytosis within PVN capillaries: a mechanism determining both hypertension-induced blood-brain barrier dysfunction and exercise-induced correction
Authors: Fragas Matheus Garcia , Cândido Vanessa Brito , Davanzo Gustavo Gastão , Rocha-Santos Carla , Ceroni Alexandre , Michelini Lisete C.
Published: September 2021

Although hypertension disrupts the blood-brain barrier (BBB) integrity within the paraventricular nucleus of hypothalamus (PVN) and increases the leakage into the brain parenchyma, exercise training (T) was shown to correct it. Since there is scarce and contradictory information on the mechanism(s) determining hypertension-induced BBB deficit and nothing is known about T-induced improvement, we sought to evaluate the paracellular and transcellular transport across the BBB within the PVN in both conditions. Spontaneously hypertensive rats (SHR) and WKY submitted to 4-wk aerobic T or sedentary (S) protocol were chronically catheterized for hemodynamic recordings at rest and intra-arterial administration of dyes (Rhodamine-dextran 70 kDa + FITC-dextran 10 kDa). Brains were harvesting for FITC leakage examination, qPCR evaluation of different BBB constituents and protein expression of caveolin-1 and claudin-5, the main markers of transcytosis and paracellular transport, respectively. Hypertension was characterized by increased arterial pressure and heart rate, augmented sympathetic modulation of heart and vessels, and reduced cardiac parasympathetic control, marked FITC extravasation into the PVN which was accompanied by increased caveolin-1 gene and protein expression, without changes in claudin-5 and others tight junctions’ components. SHR-T vs. SHR-S showed a partial pressure reduction, resting bradycardia, improvement of autonomic control of the circulation simultaneously with correction of both FITC leakage and caveolin-1 expression; there was a significant increase in claudin-5 expression. Caveolin-1 content was strongly correlated with improved autonomic control after exercise. Data indicated that within the PVN the transcytosis is the main mechanism governing both hypertension-induced BBB leakage, as well as the exercise-induced correction.
Acute high-intensity exercise and skeletal muscle mitochondrial respiratory function: role of metabolic perturbation
Authors: Lewis Matthew T. , Blain Gregory M. , Hart Corey R. , Layec Gwenael , Rossman Matthew J. , Park Song-Young , Trinity Joel D. , Gifford Jayson R. , Sidhu Simranjit K. , Weavil Joshua C. , Hureau Thomas J. , Jessop Jacob E. , Bledsoe Amber D. , Amann Markus , Richardson Russell S.
Published: September 2021

Recently it was documented that fatiguing, high-intensity exercise resulted in a significant attenuation in maximal skeletal muscle mitochondrial respiratory capacity, potentially due to the intramuscular metabolic perturbation elicited by such intense exercise. With the utilization of intrathecal fentanyl to attenuate afferent feedback from group III/IV muscle afferents, permitting increased muscle activation and greater intramuscular metabolic disturbance, this study aimed to better elucidate the role of metabolic perturbation on mitochondrial respiratory function. Eight young, healthy males performed high-intensity cycle exercise in control (CTRL) and fentanyl-treated (FENT) conditions. Liquid chromatography-mass spectrometry and high-resolution respirometry were used to assess metabolites and mitochondrial respiratory function, respectively, pre- and postexercise in muscle biopsies from the vastus lateralis. Compared with CTRL, FENT yielded a significantly greater exercise-induced metabolic perturbation (PCr: −67% vs. −82%, Pi: 353% vs. 534%, pH: −0.22 vs. −0.31, lactate: 820% vs. 1,160%). Somewhat surprisingly, despite this greater metabolic perturbation in FENT compared with CTRL, with the only exception of respiratory control ratio (RCR) (−3% and −36%) for which the impact of FENT was significantly greater, the degree of attenuated mitochondrial respiratory capacity postexercise was not different between CTRL and FENT, respectively, as assessed by maximal respiratory flux through complex I (−15% and −33%), complex II (−36% and −23%), complex I + II (−31% and −20%), and state 3CI+CII control ratio (−24% and −39%). Although a basement effect cannot be ruled out, this failure of an augmented metabolic perturbation to extensively further attenuate mitochondrial function questions the direct role of high-intensity exercise-induced metabolite accumulation in this postexercise response.
Trial-by-trial modulation of express visuomotor responses induced by symbolic or barely detectable cues
Authors: Contemori Samuele , Loeb Gerald E. , Corneil Brian D. , Wallis Guy , Carroll Timothy J.
Published: September 2021

Express visuomotor responses in humans appear to reflect subcortical sensorimotor transformation of visual inputs, potentially conveyed via the tecto-reticulo-spinal pathway. Here we show that the express responses are influenced by both symbolic and barely detectable spatial cues about stimulus location. The symbolic cue-induced effects suggest cortical top-down modulation of the putative subcortical visuomotor network. The effects of barely detectable cues may reflect exogenous facilitation mechanisms of the tecto-reticulo-spinal pathway.
Functional coupling between target selection and acquisition in the superior colliculus
Authors: Essig Jaclyn , Felsen Gidon
Published: September 2021

How do neural circuits ensure that selected targets are successfully acquired? Here, we examine whether choice-related activity in the superior colliculus (SC) promotes a motor plan for target acquisition. By demonstrating that choice-predictive SC neurons—including GABAergic neurons—remain active throughout movement, while the activity of rostral SC neurons increases during acquisition, and by recapitulating these dynamics with an attractor model, our results support a role for SC circuits in coupling target selection and acquisition.
Safety of Food and Food Warehouse Using VIBHISHAN
Authors: Khan Rijwan , Tyagi Nipun , Chauhan Nikita
Published: September 2021

Food is one of the integral parts of human life making the quality of food one of the prime factors in its selection for consumption. In order to maintain the food quality, it must be taken care of from the very first step where its quality may be affected, that is, warehouses. Food safety and safety of its warehouses is one of the major concerns, because many people lose their lives due to poor food quality. A robot that can ensure the safety of both food and warehouse can be one of the possible solutions, because taking care of huge warehouses is a tedious task and sometimes food present inside the warehouse gets unnoticed and thus get contaminated. Also safety of warehouses from intruders can be done by a robot, in any condition where it is difficult for human beings. This robot would be cheap and efficient and also make sure of safety, keeping the food intact and ensuring its fine quality.
Alkyl Hydroperoxide Reductase as a Determinant of Parasite Antiperoxide Response in Toxoplasma gondii
Authors: Wang Jinwen , Tan Qianqian , Chen Junpeng , Liu Xiaomei , Di Zeyan , Xiao Qianqian , Li Jinxuan , Zhao Xiaomin , Zhang Xiao
Published: September 2021

Toxoplasma gondii is a protozoan parasite that is widely parasitic in the nucleated cells of warm‐blooded animals. Bioinformatic analysis of alkyl hydroperoxide reductase 1 (AHP1) of T. gondii is a member of the Prxs family and exhibits peroxidase activity. Cys166 was certified to be a key enzyme active site of TgAHP1, indicating that the enzyme follows a cysteine‐dependent redox process. TgAHP1 was present in a punctate staining pattern anterior to the T. gondii nucleus. Oxidative stress experiments showed that the ∆Ahp1 strain was more sensitive to tert‐butyl hydroperoxide (tBOOH) than hydrogen peroxide (H2O2), indicating that tBOOH may be a sensitive substrate for TgAHP1. Under tBOOH culture conditions, the ∆Ahp1 strain was significantly less invasive, proliferative, and pathogenic in mice. This was mainly due to the induction of tBOOH, which increased the level of reactive oxygen species in the parasites and eventually led to apoptosis. This study shows that TgAHP1 is a peroxisomes protein with cysteine‐dependent peroxidase activity and sensitive to tBOOH.
Polyphyllin I Inhibits Propionibacterium acnes-Induced IL-8 Secretion in HaCaT Cells by Downregulating the CD36/NOX1/ROS/NLRP3/IL-1β Pathway
Authors: Yang Shuyun , Jiang Ying , Yu Xiuqin , Zhu Liping , Wang Lu , Mao Jingzhu , Wang Miaomiao , Zhou Naihui , Yang Ziliang , Liu Ying , Zhu Tingting
Published: September 2021

Acne vulgaris (AV) is a chronic skin disease involving inflammation of the pilosebaceous units. Propionibacterium acnes (P. acnes) hypercolonization is one pathogenic factor for AV. P. acnes that triggers interleukin-1β (IL-1β) by activating the pyrin domain-containing 3 protein (NLRP3) inflammasome of the NOD-like receptor family in human monocytes. Reactive oxygen species (ROS) acts as a trigger for the production of IL-8 and activates theNLRP3 inflammasome. IL-8 promotes the metastasis and multiplication of different cancerous cells, whereas keratinocyte proliferation and migration contribute to the progression of AV. A steroidal saponin called polyphyllin I (PPI) that is extracted from Paris polyphylla’s rhizomes has anti-inflammatory properties. This study investigates the regulatory role of P. acnes in the secretion of IL-8 mediated by the CD36/NADPH oxidase 1 (NOX1)/ROS/NLRP3/IL-1β pathway and the effects of PPI on the CD36/NOX1/ROS/NLRP3/IL-1β/IL-8 pathway and human keratinocyte proliferation and migration. HaCaT cells were cultured and stimulated with 108 CFU/ml of P. acnes for 0, 6, 12, 18, 24, 30, and 36 hours. P. acnes induced IL-8 secretion from HaCaT cells via the CD36/NOX1/ROS/NLRP3/IL-1β pathway. PPI inhibited the CD36/NLRP3/NOX1/ROS/IL-8/IL-1β pathway and HaCaT cell proliferation and migration. PPI alleviates P. acnes-induced inflammatory responses and human keratinocyte proliferation and migration, implying a novel potential therapy for AV.
Microscopic Analysis of the Rejuvenation Mechanism and Rejuvenation Effect of Asphalt Binders
Authors: Shan Ke , Bao Chonghao , Li Dandan , Zheng Chuanfeng
Published: September 2021

This study investigates the rejuvenation mechanism of asphalt binders at the microscopic level and compares the rejuvenation effects of rejuvenators. A model of rejuvenated asphalt was established on the basis of molecular simulation by adding different doses of two rejuvenators to the aged asphalt. This model was validated in terms of density and surface free energy. The diffusion ability of the rejuvenator was investigated by using a diffusion model and mean square displacement. The deagglomeration ability of rejuvenators on asphaltene was explored by using a radial distribution function. The microscopic mechanism of asphalt rejuvenation was explained. Results show that small molecule structures are more diffusible than long‐chain structures, and aromatic ring structures are more attracted than polar functional groups. The rejuvenating effect of the rejuvenator was evaluated in terms of viscosity and cohesive energy density. Results show that the long‐chain structure reduces the viscosity value more than the small molecule structure. The aromatic ring structure in the aged asphalt helps to restore the compatibility between the fractions. This study serves as a guide for the selection and development of future rejuvenators.
New Improved Inequalities Associated with Ratios of Gamma Functions
Authors: Cringanu Jenica
Published: September 2021

In this paper, we improve the estimate for the products

∏

k
=
1

n

4
k
−
3

/

4
k

and

∏

k
=
1

n

4
k
−
1

/

4
k

, obtained by Cringanu “inequalities associated with ratios of gamma functions.”
The Risk Analysis and Modeling of Byco Petroleum in Pakistan Using Extreme Value Theory
Authors: Syed Zishan Ali , Ahmed Almazah Mohammad Mohammad , Iqbal Zahid , Khan Ghulam Raza
Published: September 2021

The extreme value theory (EVT) has been used to model and measure the distribution of extreme minima of Byco Petroleum in the Pakistan stock market over the period from 2005 to 2012. This paper covers the investigation of distributions that are mostly used in finance including the generalized extreme value (GEV), generalized logistics (GL), and generalized Pareto (GPA) distribution. L-moment ratio diagram is being used to find the appropriate distributions among the distributions. L-moment diagram depicts that GEV and GL distributions are suitable to represent the extremes of Byco Petroleum Pakistan Limited. Thereafter, the probability weighted moment (PWM) method has been used in order to estimate the parameters of probability distributions. Furthermore, Anderson–Darling (AD) goodness-of-fit test is employed to test the goodness of fit among GEV and GL distributions, and it is clear from the results that the GL distribution is more reliable and applicable for extreme minima of Byco Petroleum Company in the Pakistan stock exchange market. EVT and traditional methods are used for value-at-risk (VaR) analysis. The analysis indicates that EVT methods are more suitable for risk measurement in comparison with traditional methods.
Exponential Time Differencing Method for Studying Prey-Predator Dynamic during Mating Period
Authors: Aljahdaly Noufe H. , Ashi H. A.
Published: September 2021

This paper addresses a first numerical simulation to the nonlinear dynamic system of equations that describes the prey-predator model at the predator mating period. Some male species accompany the females during the mating period. In this case, both male and female feed on the same prey. The presented work shows the numerical solution for this specific case of the prey-predator mathematical model via an exponential time differencing method. In addition, the paper provides the biological implication of the solution.
BOP1 Used as a Novel Prognostic Marker and Correlated with Tumor Microenvironment in Pan-Cancer
Authors: Li Wei , Song Peipei , Zhao Mengyuan , Gao Lina , Xie Jianqin , You Chongge
Published: September 2021

Previous studies have indicated the important role of block of proliferation 1 (BOP1) in the progression of several malignant tumors; no comprehensive pan-cancer analysis of BOP1 has been performed. Here, we aim to systematically identify the expression, prognostic value, and potential immunological functions of BOP1 in 33 malignancies. We obtained the gene expression data and clinical information from multiple public databases to assess the expression level and prognostic value of BOP1 in 33 cancers. We also analyzed the relationship between BOP1 expression and DNA methylation, tumor microenvironment (TME), microsatellite instability (MSI), tumor mutational burden (TMB), and immune checkpoints. Moreover, we conducted gene set enrichment analysis (GSEA) to investigate the biological function and signal transduction pathways of BOP1 in different types of tumors. Finally, we validated the expression of BOP1 in lung cancer cell line and detected the influence of BOP1 on lung cancer cell migration and the expression of epithelial-mesenchymal transition- (EMT-) related genes. Collectively, our findings elucidated that BOP1 has the potential to be a promising molecular prognostic biomarker for predicting poor survival in various malignant tumors, as well as a cancer-promoting gene involved in tumorigenesis and tumor immunity.
Safety and Efficacy of Topical Lotilaner Ophthalmic Solution 0.25% for the Treatment of Demodex Blepharitis: A Pilot Study
Authors: Gonzalez-Salinas Roberto , Yeu Elizabeth , Holdbrook Mark , Baba Stephanie N. , Ceballos Juan Carlos , Massaro-Corredor Martha , Corredor-Ortega Claudia , Ramos-Betancourt Nallely , Quiroz-Mercado Hugo
Published: September 2021

Purpose. Evaluate safety and efficacy of topical lotilaner ophthalmic solution, 0.25% for the treatment of Demodex blepharitis. Patients and Methods. 15 patients with Demodex blepharitis, defined as >10 collarettes on the upper lid, lid margin erythema, and Demodex density of ≥1.5 mites/lash on microscopy, were treated bid for 28 days with lotilaner ophthalmic solution, 0.25%. Contact lens wear, artificial eyelashes, and lid structural abnormalities were among the exclusion criteria. No other antibacterial, antiparasitic, or anti-inflammatory treatment or lid hygiene products were permitted. Patients were assessed on Days 7, 14, 28, 60, and 90. Outcome measures were changes in collarette grade and mite density on Day 28. Adverse events and changes in intraocular pressure (IOP), corrected distance visual acuity (CDVA), and slit-lamp biomicroscopy were assessed. Results. Mean collarette grade (upper lids) improved from 3.07 ± 0.21 to 0.79 ± 0.19 on Day 28; the change was statistically significant for both upper and lower lids from Day 14 on. Mean mite density per lash decreased from 2.28 ± 0.16 at baseline to 0.14 ± 0.05 at Day 28

p
<
0.0001

. Mite eradication (0 mites) was documented in 57.1% of eyes. The effects were durable through Day 90. There were no adverse events and little to no change in CDVA or IOP. The drop was well tolerated, with no discontinuations due to ocular irritation. Conclusion. Topical lotilaner ophthalmic solution, 0.25% for 4 weeks, showed promising efficacy for the treatment of Demodex blepharitis. This novel treatment appears to be safe and well tolerated. Randomized controlled studies are needed to confirm the results.
Static Analysis of Stiffened Shells Using an Edge-Based Smoothed MITC3 (ES-MITC3) Method
Authors: Pham Quoc Hoa , Nguyen Phu-Cuong
Published: September 2021

A novel approach for solving the stiffened shell structures by using an edge-based smoothed MITC3 finite element method (ES-MITC3) is presented in this paper. The ES-MITC3 method is an efficient finite element method by combining the edge-based smoothed finite element method (ES-FEM) with the original MITC3 triangular element to not only significantly improve the accuracy but also overcome the shear-locking phenomenon in the Reissner–Mindlin shell analysis. In this study, the ES-MITC3 method is applied for shell structures and then reinforced by stiffeners based on the Timoshenko beam theory to achieve more durability and strength structures. The transverse displacements of the shell structures and stiffeners at the contact positions are assumed compatible. Numerical results of the ES-MITC3 element are compared with those of available other numerical results to demonstrate a good convergence and accuracy of the present method.
A Secure and Efficient Lightweight Vehicle Group Authentication Protocol in 5G Networks
Authors: Miao Junfeng , Wang Zhaoshun , Miao Xue , Xing Longyue
Published: September 2021

When mobile network enters 5G era, 5G networks have a series of unparalleled advantages. Therefore, the application of 5G network technology in the Internet of Vehicles (IoV) can promote more intelligently vehicular networks and more efficiently vehicular information transmission. However, with the combination of 5G networks and vehicular networks technology, it requires safe and reliable authentication and low computation overhead. Therefore, it is a challenge to achieve such low latency, security, and high mobility. In this paper, we propose a secure and efficient lightweight authentication protocol for vehicle group. The scheme is based on the extended chaotic map to achieve authentication, and the Chinese remainder theorem distributes group keys. Scyther is used to verify the security of the scheme, and the verification results show that the security of the scheme can be guaranteed. In addition, through security analysis, the scheme can not only effectively resist various attacks but also guarantee security requirements such as anonymity and unlinkability. Finally, by performance analysis and comparison, our scheme has less computation and communication overhead.
Improved Powder Equivalence Model for the Mix Design of Self‐Compacting Concrete with Fly Ash and Limestone Powder
Authors: Zhang Jingbin , Lv Miao , An Xuehui , Shen Dejian , He Xinyi , Nie Ding
Published: September 2021

The use of fly ash (FA) limestone and powder (LP) in combination with cement in concrete has several practical, ecological, and economic advantages by reducing carbon dioxide emissions, reducing the excessive consumption of natural resources, and contributing to a cleaner production of self‐compacting concrete (SCC). A mix design method for SCC based on paste rheological threshold theory can guide the SCC mix design by paste tests. This method can be visualized by the self‐compacting paste zone (SCP zone), a plane area where all the mix points meet the paste threshold theory, and SCC zone, a plane area consisting of all the mix points satisfying the criteria of qualified SCC. In the case of cement SCC, the SCP zone coheres with the SCC zone. However, in the case of the addition of FA or LP with different granulometry and shape characteristics from cement, experimental results indicate that the SCP zone is separated from the SCC zone. This work quantitatively studied the influence of FA and LP on the movement of the SCP zone by introducing the improved powder equivalence model. The improved model was obtained by powder equivalence coefficients calculated through the mortar test results with or without FA or LP, instead of SCC tests in the former method. The equivalence coefficients by volume of FA and LP are 0.55 and 0.79, respectively, which means that 1.82 unit volume of FA or 1.27 unit volume of LP is equivalent to one unit volume of cement. The improved powder equivalence model was verified by the successful preparation of SCC incorporating FA or LP simply and effectively. The equivalent SCP zone cohered better with the SCC zone than the former SCP zone, which could guide the quick mix design of SCC without SCC premix tests.
A Stock Closing Price Prediction Model Based on CNN‐BiSLSTM
Authors: Wang Haiyao , Wang Jianxuan , Cao Lihui , Li Yifan , Sun Qiuhong , Wang Jingyang
Published: September 2021

As the stock market is an important part of the national economy, more and more investors have begun to pay attention to the methods to improve the return on investment and effectively avoid certain risks. Many factors affect the trend of the stock market, and the relevant information has the nature of time series. This paper proposes a composite model CNN‐BiSLSTM to predict the closing price of the stock. Bidirectional special long short‐term memory (BiSLSTM) improved on bidirectional long short‐term memory (BiLSTM) adds 1 − tanh(x) function in the output gate which makes the model better predict the stock price. The model extracts advanced features that influence stock price through convolutional neural network (CNN), and predicts the stock closing price through BiSLSTM after the data processed by CNN. To verify the effectiveness of the model, the historical data of the Shenzhen Component Index from July 1, 1991, to October 30, 2020, are used to train and test the CNN‐BiSLSTM. CNN‐BiSLSTM is compared with multilayer perceptron (MLP), recurrent neural network (RNN), long short‐term memory (LSTM), BiLSTM, CNN‐LSTM, and CNN‐BiLSTM. The experimental results show that the mean absolute error (MAE), root‐mean‐squared error (RMSE), and R‐square (R2) evaluation indicators of the CNN‐BiSLSTM are all optimal. Therefore, CNN‐BiSLSTM can accurately predict the closing price of the Shenzhen Component Index of the next trading day, which can be used as a reference for the majority of investors to effectively avoid certain risks.
One‐Two Punch Therapy for the Treatment of T‐Cell Malignancies Involving p53‐Dependent Cellular Senescence
Authors: Qing Yingjie , Li Hui , Zhao Yunzi , Hu Po , Wang Xiangyuan , Yu Xiaoxuan , Zhu Mengyuan , Wang Hongzheng , Wang Zhanyu , Guo Qinglong , Hui Hui
Published: September 2021

T‐cell malignancies are still difficult to treat due to a paucity of plans that target critical dependencies. Drug‐induced cellular senescence provides a permanent cell cycle arrest during tumorigenesis and cancer development, particularly when combined with senolytics to promote apoptosis of senescent cells, which is an innovation for cancer therapy. Here, our research found that wogonin, a well‐known natural flavonoid compound, not only had a potential to inhibit cell growth and proliferation but also induced cellular senescence in T‐cell malignancies with nonlethal concentration. Transcription activity of senescence‐suppression human telomerase reverse transcriptase (hTERT) and oncogenic C-MYC was suppressed in wogonin‐induced senescent cells, resulting in the inhibition of telomerase activity. We also substantiated the occurrence of DNA damage during the wogonin‐induced aging process. Results showed that wogonin increased the activity of senescence‐associated β‐galactosidase (SA‐β‐Gal) and activated the DNA damage response pathway mediated by p53. In addition, we found the upregulated expression of BCL‐2 in senescent T‐cell malignancies because of the antiapoptotic properties of senescent cells. Following up this result, we identified a BCL‐2 inhibitor Navitoclax (ABT‐263), which was highly effective in decreasing cell viability and inducing apoptotic cell death in wogonin‐induced senescent cells. Thus, the “one‐two punch” approach increased the sensibility of T‐cell malignancies with low expression of BCL‐2 to Navitoclax. In conclusion, our research revealed that wogonin possesses potential antitumor effects based on senescence induction, offering a better insight into the development of novel therapeutic methods for T‐cell malignancies.
Doppler Spread Estimation Based on Machine Learning for an OFDM System
Authors: Yoon Eunchul , Kwon Soonbum , Yun Unil , Kim Sun-Yong
Published: September 2021

In this paper, we propose a Doppler spread estimation approach based on machine learning for an OFDM system. We present a carefully designed neural network architecture to achieve good performance in a mixed‐channel scenario in which channel characteristic variables such as Rician K factor, azimuth angle of arrival (AOA) width, mean direction of azimuth AOA, and channel estimation errors are randomly generated. When preprocessing the channel state information (CSI) collected under the mixed‐channel scenario, we propose averaged power spectral density (PSD) sequence as high‐quality training data in machine learning for Doppler spread estimation. We detail intermediate mathematical derivatives of the machine learning process, making it easy to graft the derived results into other wireless communication technologies. Through simulation, we show that the machine learning approach using the averaged PSD sequence as training data outperforms the other machine learning approach using the channel frequency response (CFR) sequence as training data and two other existing Doppler estimation approaches.
A Systematic Analysis of Regression Test Case Selection: A Multi-Criteria-Based Approach
Authors: Rehan Muhammad , Senan Norhalina , Aamir Muhammad , Samad Ali , Husnain Mujtaba , Ibrahim Noraini , Ali Sikandar , Khatak Hizbullah
Published: September 2021

In applied software engineering, the algorithms for selecting the appropriate test cases are used to perform regression testing. The key objective of this activity is to make sure that modification in the system under test (SUT) has no impact on the overall functioning of the updated software. It is concluded from the literature that the efficacy of the test case selection solely depends on the following metrics, namely, the execution cost of the test case, the lines of the code covered in unit time also known as the code coverage, the ability to capture the potential faults, and the code modifications. Furthermore, it is also observed that the approaches for the regression testing developed so far generated results by focusing on one or two parameters. In this paper, our key objectives are twofold: one is to explore the importance of the role of each metric in detail. The secondary objective is to study the combined effect of these metrics in test case selection task that is capable of achieving more than one objective. In this paper, a detailed and comprehensive review of the work related to regression testing is provided in a very distinct and principled way. This survey will be useful for the researchers contributing to the field of regression testing. It is noteworthy that our systematic literature review (SLR) included the noteworthy work published from 2007 to 2020. Our study observed that about 52 relevant studies focused on all of the four metrics to perform their respective tasks. The results also revealed that about 30% of the different categories of regression test case reported the results using metaheuristic regression test selection (RTS). Similarly, about 31% of the literature reported results using the generic regression test case selection techniques. Most of the researchers focus on the datasets, namely, Software-Artefact Infrastructure Repository (SIR), JodaTime, TreeDataStructure, and Apache Software Foundation. For validation purpose, following parameters were focused, namely, the inclusiveness, precision, recall, and retest-all.
SAR Target Recognition Based on Joint Representation of Multimode Representations
Authors: Qiu Youchun
Published: September 2021

For the problems of feature extraction and decision making in synthetic aperture radar (SAR) image target recognition, a method based on multimode clustering and decision fusion is proposed. The bidimensional variational mode decomposition (BVMD) is used to decompose the SAR image to obtain multiple modes, which provide multilevel descriptions of the target characteristics. Clustering is performed based on the intrinsic correlation of multiple modes, and several subsets with different modes are selected. Based on the joint sparse representation (JSR), each mode subset is classified, and the corresponding reconstruction error vector is obtained. The linear weighted fusion is employed to fuse the results from different mode subsets. Finally, a decision is made based on the fused results. Experiments are carried out based on the MSTAR dataset. The results show the effectiveness of the method under the standard operating condition (SOC) and robustness under extended operating conditions (EOCs).
Optimizing Lock Operations and Ship Arrivals through Multiple Locks on Inland Waterways
Authors: Guan Hongxu , Xu Yanmin , Li Longhao , Huang Xin
Published: September 2021

Locks are important components of a waterway system. To improve the efficiency of inland waterway transport, it is important to ensure ships passing locks without having to spend unnecessary waiting times at lock entrances. Meanwhile, with the trends towards digitalized and smart waterways, it is also worth investigating how the information availability could contribute to optimizing lock operations and ship arrivals on inland waterways. Therefore, this paper proposes an optimization method to schedule ships’ arrivals and their placements in locks on inland waterways, based on a mixed-integer programming model, and solves the optimization problem with large neighborhood search based heuristics. The optimization objective is threefold: first, optimizing the arrival sequence of ships at the locks; second, maximize the utilization of each lockage operation; and third, reducing the overall time that each ship spends from entering the waterway area till leaving the last lock on the waterway. Simulations are carried out to evaluate the performance of the proposed method.
Protective Effects of Total Flavonoids from Lysimachia christinae on Calcium Oxalate-Induced Oxidative Stress in a Renal Cell Line and Renal Tissue
Authors: Wang Jian , Chen Jia-Jian , Huang Jia-Hao , Lv Bo-Dong , Huang Xiao-Jun , Hu Qing , Fu Jun , Huang Wen-Jie , Tao Ting-Ting
Published: September 2021

Oxidative stress (OS) in renal tubular epithelial cells (RTECs) is induced by calcium oxalate (CaOx) stones and plays an important role in the pathology of CaOx nephrolithiasis. The nuclear factor-E2-related factor 2 (Nrf2)/antioxidant response element (ARE) pathway is an important endogenous antioxidant pathway. Flavonoids are compounds with 2-phenylchromone as the basic mother nucleus and are natural antioxidant components of Lysimachia christinae. Our previous studies demonstrated that the total flavonoids from L. christinae (TFL) reduced calcium and oxalic acid concentrations in urine, thus inhibiting CaOx stone formation. We also showed that TFL can reduce OS in renal tissue. However, whether TFL inhibit the formation of CaOx stones through the Nrf2/ARE pathway requires further investigation. Here, we found that TFL protected against injury to a renal cell line and renal tissue, reduced CaOx-induced OS in renal tissue, and reduced CaOx crystal formation. In addition, TFL significantly increased nuclear Nrf2 and the expression of the downstream antioxidant genes heme oxygenase 1 (HO-1) and NAD(P)H quinone oxidoreductase 1 (NQO-1). Furthermore, TFL increased superoxide dismutase (SOD) activity and decreased the malondialdehyde (MDA) content, thereby alleviating OS in RTECs. Silencing Nrf2 expression blocked the protective effect of TFL on CaOx-induced OS. Taken together, our findings indicate that TFL reduce CaOx-induced OS in renal tissue by activating the Nrf2/ARE pathway.
Clinical Application of Three-Dimensional Reconstruction Technique in Thoracoscopic Pneumonectomy
Authors: Li Dong , Li Zhanxin , Li Libin , Zheng Jiangmin , Wang Qingwei , Zhang Li , Guo Zhigang
Published: September 2021

Objective. To investigate the clinical value of 3D computed tomography bronchoangiography (3D CTBA) in thoracoscopic anatomical lung segment resection or combined lung segment resection. Methods. The clinical data of 25 patients with non-small-cell lung cancer who underwent thoracoscopic radical lobectomy and pulmonary segmentectomy with pulmonary nodules were retrospectively analyzed. All patients underwent preoperative thin-slice CT scan, and the bronchus, pulmonary artery, and pulmonary vein were reconstructed by DeepInsight software. Meanwhile, pulmonary nodules, tumors, or enlarged lymph nodes were reconstructed. Accurate preoperative planning was carried out through preoperative reconstruction of three-dimensional images, especially the variation of pulmonary bronchus and blood vessels, the relationship between tumors and enlarged lymph nodes and pulmonary blood vessels, and the precise positioning of pulmonary nodules in pulmonary segments. Compared with preoperative three-dimensional reconstruction, intraoperative real-time navigation can achieve accurate operation. The intraoperative conversion to thoracotomy, operative time, intraoperative bleeding and postoperative hospitalization time, drainage tube removal time and total drainage volume, and the incidence of perioperative complications were recorded. Results. The anatomical structure and variation of bronchus and pulmonary vessels were clearly reconstructed in all patients, and the reconstruction of the relationship between central tumor and enlarged lymph nodes and blood vessels was satisfactory. The location of pulmonary nodules in pulmonary segments was clearly defined, and preoperative planning was performed accurately. All patients underwent real-time intraoperative navigation, and precise surgery was performed according to the preoperative planning. The operation was successfully completed without any transfer to thoracotomy or intraoperative accidental bleeding. The operative time was (147.60 ± 37.77) min, the intraoperative blood loss was (33.82 ± 22.17) mL, the postoperative hospital stay was (7.02 ± 1.78) d, drainage tube removal time was (4.68 ± 1.60) d, and postoperative total drainage volume was (221.00 ± 135.03) mL; there were no severe complications and no death during perioperative period. Conclusion. The application of three-dimensional reconstruction technique for preoperative evaluation and subsequent thoracoscopic pulmonary segmental resection can achieve accurate, safe, and effective pulmonary segmental resection, reduce the difficulty of thoracoscopic pulmonary segmental resection, reduce the risk of surgery, and improve the surgical effect.