bluuebunny/crossref_metadata_2025 huggingface dataset:
Buddy Stacks: Protecting Return Addresses with Efficient Thread-Local Storage and Runtime Re-Randomization
Authors: Zou Changwei , Wang Xudong , Gao Yaoqing , Xue Jingling
Published: March 2022

Shadow stacks play an important role in protecting return addresses to mitigate ROP attacks. Parallel shadow stacks, which shadow the call stack of each thread at the same constant offset for all threads, are known not to support multi-threading well. On the other hand, compact shadow stacks must maintain a separate shadow stack pointer in
thread-local storage (TLS)
, which can be implemented in terms of a register or the per-thread
Thread-Control-Block (TCB)
, suffering from poor compatibility in the former or high performance overhead in the latter. In addition, shadow stacks are vulnerable to information disclosure attacks.

In this paper, we propose to mitigate ROP attacks for single- and multi-threaded server programs running on general-purpose computing systems by using a novel stack layout, called a

buddy stack

(referred to as

Bustk

), that is highly performant, compatible with existing code, and provides meaningful security. These goals are met due to three novel design aspects in
Bustk
. First,
Bustk
places a parallel shadow stack just below a thread’s call stack (as each other’s buddies allocated together), avoiding the need to maintain a separate shadow stack pointer and making it now well-suited for multi-threading. Second,
Bustk
uses an efficient stack-based thread-local storage mechanism, denoted
STK-TLS
, to store thread-specific metadata in two TLS sections just below the shadow stack in dual redundancy (as each other’s buddies), so that both can be accessed and updated in a lightweight manner from the call stack pointer
rsp
alone. Finally,
Bustk
re-randomizes continuously (on the order of milliseconds) the return addresses on the shadow stack by using a new microsecond-level runtime re-randomization technique, denoted
STK-MSR
. This mechanism aims to obsolete leaked information, making it extremely unlikely for the attacker to hijack return addresses, particularly against a server program that sits often tens of milliseconds away from the attacker.

Our evaluation using web servers,
Nginx
and
Apache Httpd
, shows that
Bustk
works well in terms of performance, compatibility, and security provided, with its parallel shadow stacks incurring acceptable memory overhead for real-world applications and its
STK-TLS
mechanism costing only two pages per thread. In particular,
Bustk
can protect the
Nginx
and
Apache
servers with an adaptive 1-ms re-randomization policy (without observable overheads when IO is intensive, with about 17,000 requests per second). In addition, we have also evaluated
Bustk
using other non-server applications,
Firefox
,
Python
,
LLVM
,
JDK
and
SPEC CPU2006
, to demonstrate further the same degree of performance and compatibility provided, but the protection provided for, say, browsers, is weaker (since network-access delays can no longer be assumed).
Improving Unlinkability of Attribute-based Authentication through Game Theory
Authors: Zolotavkin Yevhen , Jeong Jongkil Jay , Kuchta Veronika , Slavnenko Maksym , Doss Robin
Published: March 2022

This article first formalizes the problem of unlinkable attribute-based authentication in the system where each user possesses multiple assertions and uses them interchangeably. Currently, there are no recommendations for optimal usage of assertions in such authentication systems. To mitigate this issue, we use conditional entropy to measure the uncertainty for a Relying Party who attempts to link observed assertions with user labels. Conditional entropy is the function of usage statistics for all assertions in the system. Personaldecisionsmade by the users about the usage of assertions contribute to these statistics. This collective effect from all the users impacts the unlinkability of authentication and must be studied using game theory. We specify several instances of the game where context information that is provided to the users differs. Through game theory and based on conditional entropy, we demonstrate how each user optimizes usage for the personal set of assertions. In the experiment, we substantiate the advantage of the proposed rational decision-making approaches: Unlinkability that we obtain under Nash equilibrium is higher than in the system where users authenticate using their assertions at random. We finally propose an algorithm that calculates equilibrium and assists users with the selection of assertions. This manifests that described techniques can be executed in realistic settings. This does not require modification of existing authentication protocols and can be implemented in platform-independent identity agents. As a use case, we describe how our technique can be used in Digital Credential Wallets: We suggest that unlinkability of authentication can be improved for Verifiable Credentials.
Joint Source-Channel Decoding of Polar Codes for HEVC-Based Video Streaming
Authors: Lin Jinzhi , Zhang Yun , Li Na , Jiang Hongling
Published: March 2022

Ultra High-Definition (UHD) and Virtual Reality (VR) video streaming over 5G networks are emerging, in which High-Efficiency Video Coding (HEVC) is used as source coding to compress videos more efficiently and polar code is used as channel coding to transmit bitstream reliably over an error-prone channel. In this article, a novel Joint Source-Channel Decoding (JSCD) of polar codes for HEVC-based video streaming is presented to improve the streaming reliability and visual quality. Firstly, a Kernel Density Estimation (KDE) fitting approach is proposed to estimate the positions of error channel decoded bits. Secondly, a modified polar decoder called R-SCFlip is designed to improve the channel decoding accuracy. Finally, to combine the KDE estimator and the R-SCFlip decoder together, the JSCD scheme is implemented in an iterative process. Extensive experimental results reveal that, compared to the conventional methods without JSCD, the error data-frame correction ratios are increased. Averagely, 1.07% and 1.11% Frame Error Ratio (FER) improvements have been achieved for Additive White Gaussian Noise (AWGN) and Rayleigh fading channels, respectively. Meanwhile, the qualities of the recovered videos are significantly improved. For the 2D videos, the average Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM) gains reach 14% and 34%, respectively. For the 360֯ videos, the average improvements in terms of Weighted-to-Spherically-uniform PSNR (WS-PSNR) and Voronoi-based Video Multimethod Assessment Fusion (VI-VMAF) reach 21% and 7%, respectively.
Armada: Automated Verification of Concurrent Code with Sound Semantic Extensibility
Authors: Lorch Jacob R. , Chen Yixuan , Kapritsos Manos , Ma Haojun , Parno Bryan , Qadeer Shaz , Sharma Upamanyu , Wilcox James R. , Zhao Xueyuan
Published: March 2022

Safely writing high-performance concurrent programs is notoriously difficult. To aid developers, we introduce Armada, a language and tool designed to formally verify such programs with relatively little effort. Via a C-like language and a small-step, state-machine-based semantics, Armadagives developers the flexibility to choose arbitrary memory layout and synchronization primitives so that they are never constrained in their pursuit of performance. To reduce developer effort, Armadaleverages SMT-powered automation and a library of powerful reasoning techniques, including rely-guarantee, TSO elimination, reduction, and pointer analysis. All of these techniques are proven sound, and Armadacan be soundly extended with additional strategies over time. Using Armada, we verify five concurrent case studies and show that we can achieve performance equivalent to that of unverified code.
FasterPose: A Faster Simple Baseline for Human Pose Estimation
Authors: Dai Hanbin , Shi Hailin , Liu Wu , Wang Linfang , Liu Yinglu , Mei Tao
Published: March 2022

The performance of human pose estimation depends on the spatial accuracy of keypoint localization. Most existing methods pursue the spatial accuracy through learning the high-resolution (HR) representation from input images. By the experimental analysis, we find that the HR representation leads to a sharp increase of computational cost, while the accuracy improvement remains marginal compared with the low-resolution (LR) representation. In this article, we propose a design paradigm for cost-effective network with LR representation for efficient pose estimation, named FasterPose. Whereas the LR design largely shrinks the model complexity, how to effectively train the network with respect to the spatial accuracy is a concomitant challenge. We study the training behavior of FasterPose and formulate a novel regressive cross-entropy (RCE) loss function for accelerating the convergence and promoting the accuracy. The RCE loss generalizes the ordinary cross-entropy loss from the binary supervision to a continuous range, thus the training of pose estimation network is able to benefit from the sigmoid function. By doing so, the output heatmap can be inferred from the LR features without loss of spatial accuracy, while the computational cost and model size has been significantly reduced. Compared with the previously dominant network of pose estimation, our method reduces 58% of the FLOPs and simultaneously gains 1.3% improvement of accuracy. Extensive experiments show that FasterPose yields promising results on the common benchmarks, i.e., COCO and MPII, consistently validating the effectiveness and efficiency for practical utilization, especially the low-latency and low-energy-budget applications in the non-GPU scenarios.
A Workflow Architecture for Cloud-based Distributed Simulation
Authors: Chaudhry Nauman Riaz , Anagnostou Anastasia , Taylor Simon J. E.
Published: March 2022

Distributed Simulation has still to be adopted significantly by the wider simulation community. Reasons for this might be that distributed simulation applications are difficult to develop and access to multiple computing resources are required. Cloud computing offers low-cost on-demand computing resources. Developing applications that can use cloud computing can be also complex, particularly those that can run on different clouds. Cloud-based Distributed Simulation (CBDS) is potentially attractive, as it may solve the computing resources issue as well as other cloud benefits, such as convenient network access. However, as possibly shown by the lack of sustainable approaches in the literature, the combination of cloud and distributed simulation may be far too complex to develop a general approach. E-Infrastructures have emerged as large-scale distributed systems that support high-performance computing in various scientific fields. Workflow Management Systems (WMS) have been created to simplify the use of these e-Infrastructures. There are many examples of where both technologies have been extended to use cloud computing. This article therefore presents our investigation into the potential of using these technologies for CBDS in the above context and the WORkflow architecture for cLoud-based Distributed Simulation (WORLDS), our contribution to CBDS. We present an implementation of WORLDS using the CloudSME Simulation Platform that combines the WS-PGRADE/gUSE WMS with the CloudBroker Platform as a Service. The approach is demonstrated with a case study using an agent-based distributed simulation of an Emergency Medical Service in REPAST and the Portico HLA RTI on the Amazon EC2 cloud.
Identification of Low-engaged Learners in Robot-led Second Language Conversations with Adults
Authors: Engwall Olov , Cumbal Ronald , Lopes José , Ljung Mikael , Månsson Linnea
Published: March 2022

The main aim of this study is to investigate if verbal, vocal, and facial information can be used to identify low-engaged second language learners in robot-led conversation practice. The experiments were performed on voice recordings and video data from 50 conversations, in which a robotic head talks with pairs of adult language learners using four different interaction strategies with varying robot-learner focus and initiative. It was found that these robot interaction strategies influenced learner activity and engagement. The verbal analysis indicated that learners with low activity rated the robot significantly lower on two out of four scales related to social competence. The acoustic vocal and video-based facial analysis, based on manual annotations or machine learning classification, both showed that learners with low engagement rated the robot’s social competencies consistently, and in several cases significantly, lower, and in addition rated the learning effectiveness lower. The agreement between manual and automatic identification of low-engaged learners based on voice recordings or face videos was further found to be adequate for future use. These experiments constitute a first step towards enabling adaption to learners’ activity and engagement through within- and between-strategy changes of the robot’s interaction with learners.
Solving Connectivity Problems Parameterized by Treewidth in Single Exponential Time
Authors: Cygan Marek , Nederlof Jesper , Pilipczuk Marcin , Pilipczuk Michał , Van Rooij Johan M. M. , Wojtaszczyk Jakub Onufry
Published: March 2022

For the vast majority of local problems on graphs of small treewidth (where, by local we mean that a solution can be verified by checking separately the neighbourhood of each vertex), standard dynamic programming techniques give
c

tw

|
V
|
O(1)
time algorithms, where
tw
is the treewidth of the input graph
G
= (
V,E
) and
c
is a constant. On the other hand, for problems with a global requirement (usually connectivity) the best–known algorithms were naive dynamic programming schemes running in at least
tw

tw

time.

We bridge this gap by introducing a technique we named Cut&Count that allows to produce
c

tw

|
V
|
O(1)
time Monte-Carlo algorithms for most connectivity-type problems, including
Hamiltonian Path
,
Steiner Tree
,
Feedback Vertex Set
and
Connected Dominating Set
. These results have numerous consequences in various fields, like parameterized complexity, exact and approximate algorithms on planar and
H
-minor-free graphs and exact algorithms on graphs of bounded degree. The constant
c
in our algorithms is in all cases small, and in several cases we are able to show that improving those constants would cause the Strong Exponential Time Hypothesis to fail. In all these fields we are able to improve the best-known results for some problems. Also, looking from a more theoretical perspective, our results are surprising since the equivalence relation that partitions all partial solutions with respect to extendability to global solutions seems to consist of at least
tw

tw

equivalence classes for all these problems. Our results answer an open problem raised by Lokshtanov, Marx and Saurabh [SODA’11].

In contrast to the problems aimed at
minimizing
the number of connected components that we solve using Cut&Count as mentioned above, we show that, assuming the Exponential Time Hypothesis, the aforementioned gap cannot be bridged for some problems that aim to
maximize
the number of connected components like
Cycle Packing
.
Multi-granularity Brushstrokes Network for Universal Style Transfer
Authors: Wang Quan , Li Sheng , Zhang Xinpeng , Feng Guorui
Published: March 2022

Neural style transfer has been developed in recent years, where both performance and efficiency have been greatly improved. However, most existing methods do not transfer the brushstrokes information of style images well. In this article, we address this issue by training a multi-granularity brushstrokes network based on a parallel coding structure. Specifically, we first adopt the content parsing module to obtain the spatial distribution of content image and the smoothness of different regions. Then, different brushstrokes features are transformed by a multi-granularity style-swap module guided by the region content map. Finally, the stylized features of the two branches are fused to enhance the stylized results. The multi-granularity brushstrokes network is jointly supervised by a new multi-layer brushstroke loss and pre-existing loss. The proposed method is close to the artistic drawing process. In addition, we can control whether the color of the stylized results tend to be the style image or the content image. Experimental results demonstrate the advantage of our proposed method compare with the existing schemes.
A Provably Robust Algorithm for Triangle-triangle Intersections in Floating-point Arithmetic
Authors: Mccoid Conor , Gander Martin J.
Published: March 2022

Motivated by the unexpected failure of the triangle intersection component of the Projection Algorithm for Nonmatching Grids (PANG), this article provides a robust version with proof of backward stability. The new triangle intersection algorithm ensures consistency and parsimony across three types of calculations. The set of intersections produced by the algorithm, called representations, is shown to match the set of geometric intersections, called models. The article concludes with a comparison between the old and new intersection algorithms for PANG using an example found to reliably generate failures in the former.
3D Scene Geometry Estimation from 360° Imagery: A Survey
Authors: da Silveira Thiago L. T. , Pinto Paulo G. L. , Murrugarra-Llerena Jeffri , Jung Cláudio R.
Published: March 2022

This article provides a comprehensive survey on pioneer and state-of-the-art 3D scene geometry estimation methodologies based on single, two, or multiple images captured under omnidirectional optics. We first revisit the basic concepts of the spherical camera model and review the most common acquisition technologies and representation formats suitable for omnidirectional (also called 360°, spherical or panoramic) images and videos. We then survey monocular layout and depth inference approaches, highlighting the recent advances in learning-based solutions suited for spherical data. The classical stereo matching is then revised on the spherical domain, where methodologies for detecting and describing sparse and dense features become crucial. The stereo matching concepts are then extrapolated for multiple view camera setups, categorizing them among light fields, multi-view stereo, and structure from motion (or visual simultaneous localization and mapping). We also compile and discuss commonly adopted datasets and figures of merit indicated for each purpose and list recent results for completeness. We conclude this article by pointing out current and future trends.
Algorithm 1021: SPEX Left LU, Exactly Solving Sparse Linear Systems via a Sparse Left-looking Integer-preserving LU Factorization
Authors: Lourenco Christopher , Chen Jinhao , Moreno-Centeno Erick , Davis Timothy A.
Published: March 2022

SPEX Left LU is a software package for exactly solving unsymmetric sparse linear systems. As a component of the sparse exact (SPEX) software package, SPEX Left LU can be applied to any input matrix,
A
, whose entries are integral, rational, or decimal, and provides a solution to the system

\( Ax = b \)

, which is either exact or accurate to user-specified precision. SPEX Left LU preorders the matrix
A
with a user-specified fill-reducing ordering and computes a left-looking LU factorization with the special property that each operation used to compute the
L
and
U
matrices is integral. Notable additional applications of this package include benchmarking the stability and accuracy of state-of-the-art linear solvers and determining whether singular-to-double-precision matrices are indeed singular. Computationally, this article evaluates the impact of several novel pivoting schemes in exact arithmetic, benchmarks the exact iterative solvers within Linbox, and benchmarks the accuracy of MATLAB sparse backslash. Most importantly, it is shown that SPEX Left LU outperforms the exact iterative solvers in run time on
easy
instances and in stability as the iterative solver fails on a sizeable subset of the tested (both easy and hard) instances. The SPEX Left LU package is written in ANSI C, comes with a MATLAB interface, and is distributed via GitHub, as a component of the SPEX software package, and as a component of SuiteSparse.
Optimization-Based Predictive Congestion Control for the Tor Network: Opportunities and Challenges
Authors: Döpmann Christoph , Fiedler Felix , Lucia Sergio , Tschorsch Florian
Published: March 2022

Based on the principle of onion routing, the Tor network achieves anonymity for its users by relaying user data over a series of intermediate relays. This approach makes congestion control in the network a challenging task. As of this writing, this results in higher latencies due to considerable backlog as well as unfair data rate allocation. In this article, we present a concept study of PredicTor, a novel approach to congestion control that tackles clogged overlay networks. Unlike traditional approaches, it is built upon the idea of distributed model predictive control, a recent advancement from the area of control theory. PredicTor is tailored to minimizing latency in the network and achieving max-min fairness. We contribute a thorough evaluation of its behavior in both toy scenarios to assess the optimizer and complex networks to assess its potential. For this, we conduct large-scale simulation studies and compare PredicTor to existing congestion control mechanisms in Tor. We show that PredicTor is highly effective in reducing latency and realizing fair rate allocations. In addition, we strive to bring the ideas of modern control theory to the networking community, enabling the development of improved, future congestion control. Thus, we demonstrate benefits and issues alike with this novel research direction.
Design and Synthesis of Heterometallic Ni–Co Organic Frameworks as Anode Materials for High-Performance Lithium Storage
Authors: Xu Ningning , Han Qing , Zhu Limin , Xie Lingling , Xu Jing , Zhang Weifan , Yang Xinli , Cao Xiaoyu
Published: March 2022

Reasonable design of high-rate, long-life anode materials is the key to manufacturing advanced lithium-ion batteries. Herein, we synthesized the heterometallic (Ni, Co) 4,4′-biphenyldicarboxylic metal organic framework (NiCo-MOF-1) and heterometallic (Ni, Co) 2,2′-bipyridine-5,5′-dicarboxylic metal organic framework (NiCo-MOF-2) by solvothermal method, and explored the applications as anode materials for lithium-ion batteries in depth. It was demonstrated that the initial discharge/charge specific capacities of NiCo-MOF-1 and NiCo-MOF-2 reached 2.04/1.12 and 1.99/1.11 mAh cm−2 at a current density of 0.1 mA cm−2 and the voltage window of 0.01 ∼ 3.0 V, respectively. Similarly, NiCo-MOF-2 could maintain a specific discharge/charge capacity of 0.65/0.64 mAh cm−2 after 150 cycles, which was higher than that of NiCo-MOF-1 (0.45/0.43 mAh cm−2). In addition, NiCo-MOF-2 delivers outstanding rate performance (0.29/0.29 mAh cm−2 at 1.0 mA cm−2), which came down to the strong conjugated carboxylate π–π interaction and the synergistic effect of nickel and cobalt bimetals. Through the kinetic analysis, the pseudocapacitance contribution was as high as 61.7% at 0.5 mV s−1. Ex-situ XPS verified the coordination mechanism of Li+ and COO− rings with benzene ring in NiCo-MOF-2 thus achieving high lithium storage capacity.
Characterizations of Ion-Sensitive Field-Effect Transistors with Silicon Wire Array Channels and Stack-Sensing Membrane
Authors: Chen Henry J. H. , Lee Tzu Nien , Tseng Shin-Lun , Chen Sun-Zen , Chiu Po-Wen
Published: March 2022

In this study, the characteristics of ion-sensitive field-effect transistors (ISFETs) with silicon wire array channels and sensing membrane stacks of 3-aminopropyltriethoxysilane (APTES)/SiO2 were investigated. Si wires were fabricated by nanoimprint lithography and Si anisotropic/isotropic reactive-ion etching processes. The Si wires, with a line width of ∼200 nm, were undercut and nearly suspended, which formed an

Ω

-shape cross-section. The aspects of wires were investigated using an optical microscope, an atomic force microscope, a scanning electron microscope, and a transmission electron microscope. The sensitivity, hysteresis, and drift of ISFETs were investigated. The above sensing properties were all significantly improved with the proposed channels and the sensing membrane stacks. As such, high-performance ISFETs can be realized for future biochemical applications.
Glial Purinergic Signaling-Mediated Oxidative Stress (GPOS) in Neuropsychiatric Disorders
Authors: Huang Lumei , Tang Yong , Sperlagh Beata
Published: March 2022

Oxidative stress (OS) has been implicated in the progression of multiple neuropsychiatric disorders, including schizophrenia (SZ), major depressive disorder (MDD), bipolar disorder, and autism. However, whether glial purinergic signaling interaction with oxidative/antioxidative system displays an important role in neuropsychiatric disorders is still unclear. In this review, we firstly summarize the oxidative/antioxidative pathways shared in different glial cells and highlight the cell type-specific difference in response to OS. Then, we collect the evidence showing the regulation of purinergic signaling in OS with an emphasis on adenosine and its receptors, P2Y1 receptor in the P2Y family and P2X7receptor in the P2X family. Available data shows that the activation of P1 receptors and P2X accelerates the OS; reversely, the activation of the P2Y family (P2Y1) causes protective effect against OS. Finally, we discuss current findings demonstrating the contribution of the purinergic signaling system to neuropsychiatric disorders and point out the potential role of OS in this process to propose a “glial purinergic-oxidative stress” (“GPOS”) hypothesis for future development of therapeutic strategies against a variety of neuropsychiatric disorders.
Calibration of Collaborative Robots Based on Position Information and Local Product of Exponentials
Authors: Gao Guanbin , Gao Yangtao , Liu Fei , Na Jing
Published: March 2022

To improve the positioning accuracy of collaborative robots, a novel modeling and calibration method for collaborative robots is proposed based on position information and modified local product of exponentials (LPoE). The kinematic error model is derived from the kinematic model through differential transformation. To solve the problem of the high redundancy and complexity of the error model that is difficult to identify, the errors of the kinematic parameters are all transferred to the initial position and posture matrix of the local coordinate system, which simplifies the error model and improves the speed and accuracy of the identification calculation. However, the simplified error model still requires posture data which are very difficult to acquire in practice. For this reason, the position error is separated from the kinematic model, and an error model based on position data is established. Then, a kinematic calibration method of the collaborative robot based on position data is proposed, which simplifies the measurement process and improves the efficiency of calibration. The effectiveness of the method is verified by simulations and experiments on a six degree-of-freedom collaborative robot.
Joint Optimization of Offloading and Resource Allocation for SDN-Enabled IoV
Authors: Lin Li , Zhang Lei
Published: March 2022

With the development of various vehicle applications, such as vehicle social networking, pattern recognition, and augmented reality, diverse and complex tasks have to be executed by the vehicle terminals. To extend the computing capability, the nearest roadside-unit (RSU) is used to offload the tasks. Nevertheless, for intensive tasks, excessive load not only leads to poor communication links but also results to ultrahigh latency and computational delay. To overcome these problems, this paper proposes a joint optimization approach on offloading and resource allocation for Internet of Vehicles (IoV). Specifically, assuming particle tasks assigned for vehicles in the system model are offloaded to RSUs and executed in parallel. Moreover, the software-defined networking (SDN) assisted routing and controlling protocol is introduced to divide the IoV system into two independent layers: data transmission layer and control layer. A joint approach optimized offloading decision, offloading ratio, and resource allocation (ODRR) is proposed to minimize system average delay, on the premise of satisfying the demand of the quality of service (QoS). By comparing with conventional offloading strategies, the proposed approach is proved to be optimal and effective for SDN-enabled IoV.
Effect of Heat-Treating on Microstructure and High Cycle Bending Fatigue Behavior of AZ91 and AZE911 Magnesium Alloys
Authors: Oliya Ahmad Yousefi Parchin , Azadi Mohammad , Parast Mohammad Sadegh Aghareb , Mokhtarishirazabad Mehdi
Published: March 2022

This article investigates the influences of heat-treating on the microstructures and the high cycle fatigue (HCF) properties of AZ91 and AZE911 (AZ91 + 1%RE) magnesium alloys. For such an objective, AZ91 and AZE911 alloys were used after solution treatment at 415°C for 5 hours aged at 215°C for 3 hours and at 215°C for 5 hours, respectively. To investigate the HCF behavior, a rotational bending fatigue test was performed with stress ratio (R) −1 and frequency of 100 Hz at room temperature. Optical microscopy (OM) study demonstrates that heat treatment leads to a reduction in grain size and transformation of continuous and discontinuous precipitations into needle-shaped precipitations, which are located on the grains of the alpha phase. Scanning electron microscopy (SEM) showed both marks of quasicleavage and cleavage on the fracture surface of specimens. These planes indicated the brittle behavior of the fracture. Moreover, in heat-treated specimens, the size of cleavage patterns was smaller, and microcracks were shorter. These behaviors affected the strength of the material and the fatigue lifetime. The results of mechanical tests show a negligible influence of heat-treating on the HCF behaviors of AZ91-T6 and AZE911-T6 alloys. Stress-lifetime curves (S-N) show an increase in fatigue strength in 3.8 × 105 fatigue cycles, from 95 MPa to 125 MPa for the AZ91-T6 alloy and from 125 MPa to 155 MPa for the AZE911-T6 alloy, after heat treatment.
Vitamin D Supplementation for the Treatment of Depressive Symptoms in Women with Type 2 Diabetes: A Randomized Clinical Trial
Authors: Penckofer Sue , Ridosh Monique , Adams William , Grzesiak Meghan , Woo Jennifer , Byrn Mary , Kouba Joanne , Sheean Patricia , Kordish Colleen , Durazo-Arvizu Ramon , Wallis Diane , Emanuele Mary Ann , Halaris Angelos
Published: March 2022

Aim. To determine the efficacy and safety of vitamin D3 supplementation in reducing depressive symptoms in women with type 2 diabetes (T2D), depression, and low vitamin D. Methods. In this double-blind randomized active comparator-controlled trial, women with significant depressive symptoms as assessed by the Center for Epidemiologic Studies Depression (CES-D) scale received weekly oral vitamin D3 supplementation (50,000 IU) or an active comparator (5,000 IU) for 6 months. Assessments of vitamin D, 25-hydroxyvitamin D [25 (OH) D], and depression were measured at baseline, 3 months, and 6 months. Results. A total of 129 women were randomized, from which 119 completed the study (57 in lower dose and 62 in higher dose). Participants had an average 25 (OH) D and HbA1c of 20.8 ng/mL and 7.8%, respectively, at baseline. They were diverse (48% Black) and had a mean age of 50 and T2D for about 8 years. Upon completion of vitamin D3 supplementation, serum 25 (OH) D levels increased with 50,000 IU (+34 ng/mL) and 5,000 IU (+10 ng/mL). There was no difference in CES-D scores by treatment dose. Overall, depressive symptoms significantly improved over time with an average CES-D decline of 12.98 points (95% CI: −15.04 to −10.93;

p
<
0.001

). Among women with moderate baseline depressive symptoms, those receiving the lower dose had nominally lower depression scores at follow-up than those in the higher dose cohort. Among women with severe baseline depressive symptoms, the improvement in follow-up depression scores was the same regardless of dose. Conclusions. There was no difference in the dosing effect of vitamin D3 supplementation for the treatment of depressive symptoms in women with T2D who present with significant symptoms and low vitamin D. Regardless of the dose, participants’ mood improved over time. Further study of vitamin D to target depressive symptoms in comorbid populations is needed.
Conjugate Natural Convection: A Study of Optimum Fluid Flow and Heat Transfer in Eccentric Annular Channels
Authors: Jamal Ahmad , Mokheimer Esmail M. A.
Published: March 2022

Laminar natural convection-conduction heat transfer in vertically positioned annular channels with inherent eccentricity is investigated for optimum solid-fluid thermal conductivity ratio and optimum cylinder walls thicknesses allowing maximum induced fluid flow rate and heat transfer under varying geometry parameters, i.e., annulus eccentricity and radius ratio. A finite-difference technique is employed to solve the coupled momentum and energy equations for the cylindrical annulus walls and the annular fluid with Prandtl number 0.7. As part of the results, fluctuations in the induced fluid flow rate and heat transfer in the eccentric annular channel due to the conjugate effect, governed by the ratios of the solid and fluid thermal conductivities and thicknesses of outer and inner circular cylinder walls, are obtained for the boundary conditions of one wall heated isothermally and the other kept adiabatic. Commonly encountered ratios of the solid and fluid thermal conductivities and cylinder walls thicknesses are utilized in the present analysis. Results reveal that the optimum conductivity ratio and cylinder walls thicknesses increase nonlinearly with eccentricity and radius ratio. Such results can be very useful in effectively designing the heat transfer equipment for optimum performance.
Fabrication and Optimization Design of Multilayer Flyer Plates for
Laser-Driven Loading
Authors: Guo Wei , Cao Wei , Wang Xiang , Peng Qiqi , Wu Lizhi , Margarone Daniele
Published: March 2022

The laser-driven flyer plate is an important loading technology in high
energy physics, shock wave physics, and explosive initiation application.
How to generate a high-velocity and intact flyer plate by using the laser is
a matter of concern for laser driving. In this study, the multilayer flyer
plates (MFPs) of Al/Al2O3/Al and
TiO2/Al/Al2O3/Al
with adjustable performance were designed and fabricated by magnetron
sputtering and analyzed by scanning electron microscopy (SEM), laser
reflectance spectrometer, and differential thermal analysis (DTA). The
effects of the structure and material on the output performance of MFPs were
analyzed by photon Doppler velocimetry (PDV) and ultrahigh-speed video. The
morphology results showed that the structure of MFPs had uniform and clear
boundaries between side-by-side layers. The MFP velocity was controlled in
the range of 4.0–6.0 km/s by adjusting the film thickness, structure, and
thermite material with 43.1 J/cm2 laser ablation. Among
them, the energetic flyers with the thermite ablation layer had the highest
final velocity of 5.38 km/s due to the prestored energy of
TiO2/Al. By appropriately increasing the thickness
of Al2O3 from 0.4
μm to 0.8 μm, the
complete flight of the flyer plate to 3.72 mm can be realized. In addition,
TiO2/Al thermite film had characteristics of
reaction heat release and lower laser reflectivity (72.13%) than the Al
layer (80.55%), which explained the velocity enhancement effect of energetic
flyer plates. This work provides facile strategy to enhance the output
performance of MFPs, which may facilitate the practical applications of
laser driving technology.
The Indoor Space Layout of University Laboratories Based on Wireless Communication and Artificial Intelligence Decision-Making
Authors: Xia Lei
Published: March 2022

In recent years, people have found that the use of contactless wireless communication can be more quickly interactive information transmission, which greatly facilitates our daily life. However, in the past, wireless communication is generally large-scale regional information dissemination. In recent years, with the further development of closed scenes, people are thinking about whether wireless communication can be used in closed scenes to do small and fast information transmission. The purpose of this paper is to study the indoor space layout of university laboratories based on wireless communication and artificial intelligence decision-making support. We are looking at the information about wireless communication to learn that wireless communication was often used in military transmission of signals and information; it has been vigorously developed and popularized, is now mainly used for civilian use, and can be combined with artificial intelligence to implement rapid information transmission transfer, in the data processing volume at a certain time basically achieving second transmission. Wireless communication and artificial intelligence decision-making can be used to conduct research on the indoor layout of college laboratories. In response, after data query and data comparison, we applied to the school for a computer lab and several idle laboratories to cooperate in experiments to facilitate the completion of the architecture of wireless communication and artificial intelligence systems, as well as subsequent data processing analysis. After a period of time of experiments, according to the results of the experiment, the use of wireless communication and artificial intelligence decision-making can help college laboratories according to their own functions, the installation of intelligent equipment, and the indoor layout of better arrangements.
A Spatial-Temporal-Semantic Method for Location Prediction in Indoor Spaces
Authors: Wang Peng , Yang Jing , Zhang Jianpei
Published: March 2022

While a large number of works concentrated on forecasting trajectories in the outdoor environment, predicting the movement of users in indoor settings has attracted much more attention recently because of the development of smartphones and maturity of Wi-Fi services, e.g., in office buildings. Predicting a user’s movement in indoor spaces can not only help better understand his/her intentions but also improve his/her living experience. While most of the prediction approaches to date tackle the problem by constructing the mathematical models to learn the mobility of objects, they cannot efficiently model the movement of indoor users in the constraint but filled with spatial-temporal-semantic info settings. In order to solve this issue, we propose a frequent subtrajectory-based Markov model that incorporates the spatial location, the temporal aspect, and the shop category context into a unified framework. We first present the frequent subtrajectory algorithm to model and predict adjacent moving points from physical movement perspective, and then, by taking the duration of stay at a specific location into account, we further improve the prediction precision. Finally, by taking location context in the indoor environment (e.g., shop categories) into consideration, we successfully model and predict the user’s future visiting points from the semantic perspective. To validate the effectiveness of our model, we conduct a complete evaluation on a large-scale real-world dataset with more than 261,269 trajectories collected from over 120,000 customers in a shopping mall. The experiment results demonstrate that our method performs significantly superior prediction performance comparing the state-of-the-art models.
Appointment Scheduling Problem in Complexity Systems of the Healthcare Services: A Comprehensive Review
Authors: Ala Ali , Chen Feng
Published: March 2022

This paper provides a comprehensive review of Appointment Scheduling (AS) in healthcare service while we propose appointment scheduling problems and various applications and solution approaches in healthcare systems. For this purpose, more than 150 scientific papers are critically reviewed. The literature and the articles are categorized based on several problem specifications, i.e., the flow of patients, patient preferences, and random arrival time and service. Several methods have been proposed to shorten the patient waiting time resulting in the shortest idle times in healthcare centers. Among existing modeling such as simulation models, mathematical optimization techniques, Markov chain, and artificial intelligence are the most practical approaches to optimizing or improving patient satisfaction in healthcare centers. In this study, various criteria are selected for structuring the recent literature dealing with outpatient scheduling problems at the strategic, tactical, or operational levels. Based on the review papers, some new overviews, problem settings, and hybrid modeling approaches are highlighted.
Study on Effect of Perforation Orientation on Hydraulic Fracturing of Shale
Authors: Li Jian , Wang Dong , Wang Hongjian , Zhao Fei , Ma Qingqing , Qiao Qi , Yao Zhiyang
Published: March 2022

The core technology to realize the development of unconventional oil and gas resources is the large-scale volume transformation of shale reservoirs, but volume fracturing is a complex physical and mechanical process, and its mechanism remains to be further studied. In this paper, starting from the current research status of shale volumetric fracturing, the perforation orientation of volumetric fracturing is numerically simulated by using the finite element software. The following conclusions are drawn: ① when the ground stress conditions are equal, with the increase of perforation angle, the maximum principal stress at the front of perforation decreases gradually; that is, when the perforation is along the horizontal minimum principal stress, the maximum principal stress at the front of perforation is the largest, which is most conducive to fracturing of shale reservoirs. ② When the perforation is along the direction of the horizontal minimum principal stress and the horizontal stress difference is zero, the smaller the horizontal stress, the greater the maximum principal stress at the front of the perforation. Therefore, the smaller the horizontal stress, the more conducive to the rupture of shale reservoirs. ③ When the perforation is along the horizontal minimum principal stress, the maximum principal stress at the front of the perforation increases with the increase of the horizontal stress difference. Therefore, the larger the horizontal stress difference, the more favorable for the fracture of shale reservoirs.
Effect of Combining Conventional and Telehealth Methods on Managing Peritoneal Dialysis Patients: A Retrospective Single-Center Study
Authors: Wang Zhi , Yan Wenjing , Lu Ying , Song Kai , Shen Huaying , Wang Yun , Feng Sheng
Published: March 2022

Objective. This study aimed to explore follow-up mode changes for peritoneal dialysis (PD) patients and their effects on PD quality during the COVID-19 pandemic. Methods. A retrospective single-center study was conducted. All patients who received PD treatment at the Second Affiliated Hospital of Soochow University between January 2018 and March 2020 were enrolled in this study. Patient data during the first quarter of 2018 (Q1-2018), the first quarter of 2019 (Q1-2019), and the first quarter of 2020 (Q1-2020) were collected. Results. No significant differences were observed for any serum examinations in different follow-up periods (

P
>
0.05

). A significantly reduced outpatient follow-up rate was observed in Q1-2020 compared with Q1-2018 and Q1-2019 (71.6% Vs 78.9% Vs 84.7%,

P
<
0.001

), accompanied by a significantly increased remote follow-up rate (28.4% Vs 21.1% Vs 15.3%,

P
<
0.001

). Compared with Q1-2018 and Q1-2019, the hospitalization rate (27.7% Vs 30.9% Vs 15.7%,

P
<
0.001

) and the incidence of peritonitis (0.162 Vs 0.186 Vs 0.08 per patient-year,

P
<
0.001

) decreased significantly in Q1-2020. PD patients had a significant decline in the drop-out rate for Q1-2020 compared with Q1-2019 (4.4% Vs 7.3% Vs 2.2%,

P
<
0.001

). No differences in the incidence of catheter-related infections were observed. No significant differences were observed for any peritoneal dialysis key performance indicators (KPIs) between outpatient follow-up and remote follow-up patients. Conclusion. During the COVID-19 pandemic (Q1-2020), our center practiced more remote follow-up procedures in PD patients. The hospitalization rate and peritonitis incidence were significantly decreased compared with the same time in previous years. No statistical differences were observed in other KPIs for peritoneal dialysis. This study shows that telehealth methods are a reasonable alternative to in-person care in the care/management of PD patients.
Based on the Network Pharmacology to Investigate the Mechanism of Qingjie Fuzheng Granules against Colorectal Cancer
Authors: Fang Yi , Yang Chi , Lu Yao , Wei Lihui , Zhao Jinyan , Lu Lisha , Lin Jiumao
Published: March 2022

Qingjie Fuzheng granules (QFG) exert an anticancer effect against colorectal cancers (CRC). However, the pharmacological molecular mechanisms are still unclear. This study was aimed to establish a simple method to predict targets of QFG against CRC by the network pharmacology strategy. 461 compounds and 1559 targets in QFG were enriched by BATMAN-TCM. 21 of the common targets were obtained by the groups of “Jun,” “Chen,” “Zuo,” and “Shi” medicine in QFG. The enrichment analyses of GO functional terms, KEGG pathway, and OMIM/TTD diseases displayed the targets in the different and complementary effects of four functional medicines in QFG. Then, 613 differential targets for QFG in CRC were identified. GO functional terms and KEGG pathway analyses showed that QFG regulated the inflammatory function and lipid metabolic process. There were also targets that played a role in the binding to the receptors in membranes, in the activation of the transportation signal, and provided pain relief by regulation of the neural related pathways. Next, the protein-protein interaction network was analyzed, and the levels of the predicted targets in CRC primary tumor were explored, and 7 candidate targets of QFG against CRC were obtained. Furthermore, with real-time PCR and enzyme-linked immunosorbent assay (ELISA) analysis, downregulation of dopamine D2 receptor (DRD2) and interleukin-6 (IL-6), and upregulation of interleukin-10 (IL-10) were identified following the treatment of QFG. At last, the survival and prognosis of the potential targets of QFG in CRC patients were analyzed by GenomicScape, and IL-6 was suggested to be an index for the regulation of QFG in CRC. These results might elucidate the possible antitumor mechanism of QFG and highlight the candidate therapeutic targets and the application direction in clinical treatment for QFG.