bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of haemodynamics on the risk of ischaemic stroke in patients with severe vertebral artery stenosis
Authors: Li Qing , Zhou Yinghua , Xing Yingqi , Yang Jie , Hua Yang
Published: December 2021

Objectives

Endovascular treatment strategies to optimise individualised care for patients with vertebral artery (VA) stenosis need to be revisited. This study aimed to investigate the relationship between net VA flow volume (NVAFV) and the risk of posterior circulation infarction (PCI) in a high-risk patient population.

Methods

We screened 1239 patients with extracranial VA stenosis, of whom 321 patients with severe VA V1 segment stenosis (≥70%) were enrolled in our study. We restratified the patients based on NVAFV and contralateral VA stenosis grades to analyse the proportion of each PCI mechanism—large artery atherosclerosis and branch artery occlusive disease. Furthermore, we estimated the incidence of recurrent ischaemic stroke between groups with different NVAFV over a follow-up period of 2 years.

Results

NVAFV was lower in the PCI group. Multiple logistic regression analysis showed that NVAFV is an independent risk factor for PCI and that the OR for PCI for the lowest NVAFV (<112.8 mL/min) was 4.19 (1.76 to 9.95, p=0.001). In patients with severe carotid artery disease, the OR for the lowest NVAFV was 14.03 (3.18 to 61.92, p<0.001). The lower NVAFV group had a higher incidence of recurrent ischaemic stroke events than the higher NVAFV group (HR 2.978, 95% CIs 1.414 to 6.272).

Conclusion

Our study demonstrated that NVAFV, as estimated by colour duplex ultrasonography, was associated with the incidence of PCI and subsequent ischaemic events and that a high-risk population could be identified for further posterior circulation revascularisation.
A symmetric DBI action theory and its applications to inflationary cosmology
Authors: Yang Xiaokun , Xu Wu-Long , Huang Yong-Chang
Published: December 2021

The Dirac-Born-Infeld (DBI) field theory in string theory is important and can provide the field of the universe’s inflation. At the same time, it provides a causal mechanism for generating the original density perturbation, thereby providing the necessary density perturbation for existing the dense and sparse matter distributions of the universe. We deduce a symmetric DBI action, introduce it into inflationary cosmology to calculate various inflation parameters, further calculate the scalar perturbation spectrum and the tensor-scalar ratio, which are compared with Planck + WMAP9 + BAO data, the power spectrum predicted by the new general DBI inflation theory satisfies the CMB Experiment constraints, i.e., is consistent with the current theories and experimental observations. Consequently, the theory of this paper conforms to current experiments and is supplying the current theories, and also a new way of explaining the inflation of the universe.
Charged lepton flavor violation in light of muon $$g-2$$
Authors: Hou Wei-Shu , Kumar Girish
Published: December 2021

The recent confirmation of the muon $$g-2$$

g
-
2

anomaly by the Fermilab $$g-2$$

g
-
2

experiment may harbinger a new era in $$\mu $$
μ
and $$\tau $$
τ
physics. In the context of general two Higgs doublet model, the discrepancy can be explained via one-loop exchange of sub-TeV exotic scalar and pseudoscalars, namely H and A, that have flavor changing neutral couplings $$\rho _{\tau \mu }$$

ρ

τ
μ

and $$\rho _{\mu \tau }$$

ρ

μ
τ

at $$\sim 20$$

∼
20

times the usual tau Yukawa coupling, $$\lambda _\tau $$

λ
τ

. Taking $$\rho _{\ell \ell ^\prime }\sim \lambda _{ \mathrm min(\ell , \ell ^\prime )}$$

ρ

ℓ

ℓ
′

∼

λ

m
i
n
(
ℓ
,

ℓ
′

)

, we show that the above solution to muon $$g-2$$

g
-
2

then predicts enhanced rates of various charged lepton flavor violating processes, which should be accessible at upcoming experiments. We cover muon related processes such as $$\mu \rightarrow e \gamma $$

μ
→
e
γ

, $$\mu \rightarrow eee$$

μ
→
e
e
e

and $$\mu N \rightarrow e N$$

μ
N
→
e
N

, and $$\tau $$
τ
decays $$\tau \rightarrow \mu \gamma $$

τ
→
μ
γ

and $$\tau \rightarrow \mu \mu \mu $$

τ
→
μ
μ
μ

. A similar one-loop diagram with $$\rho _{e\tau }= \rho _{\tau e} = \mathcal{O}(\lambda _e)$$

ρ

e
τ

=

ρ

τ
e

=
O

(

λ
e

)

induces $$\mu \rightarrow e\gamma $$

μ
→
e
γ

, bringing the rate right into the sensitivity of the MEG II experiment. The $$\mu e\gamma $$

μ
e
γ

dipole can be probed further by $$\mu \rightarrow 3e$$

μ
→
3
e

and $$\mu N \rightarrow eN$$

μ
N
→
e
N

. With its promised sensitivity range and ability to use different nuclei, the $$\mu N \rightarrow eN$$

μ
N
→
e
N

conversion experiments can not only make discovery, but access the extra diagonal quark Yukawa couplings $$\rho _{qq}$$

ρ

qq

. For the $$\tau $$
τ
lepton, we find that $$\tau \rightarrow \mu \gamma $$

τ
→
μ
γ

would probe $$\rho _{\tau \tau }$$

ρ

τ
τ

down to $$\lambda _\tau $$

λ
τ

or lower, while $$\tau \rightarrow 3\mu $$

τ
→
3
μ

would probe $$\rho _{\mu \mu }$$

ρ

μ
μ

to $$\mathcal{O}(\lambda _{\mu })$$

O
(

λ
μ

)

.
China’s Approach to South Asia
Authors: SINGH Antara Ghosal
Published: December 2021

South Asia has emerged as a “priority zone” for Chinese foreign policy with the highest density of early harvest projects under the Belt and Road Initiative and deepening Chinese engagements in realms beyond economics. Despite China’s growing presence in the region, there are few studies that track China’s internal discourse on the region, going beyond its targeted propaganda. Based on study of Chinese-language literature, this article aims to fill the knowledge gap in this domain and develop a basic framework depicting how China operates in South Asia as well as its mission and vision for the region.
Early post-breakup kinematic adjustments of continental–oceanic transform fault zones: Cape Range, Coromandal and Romanche transform margin case study
Authors: Nemčok Michal , Ledvényiová Lucia , Henk Andreas , Rybár Samuel , Sinha Sudipta Tapan , Pospíšil Lubomil , Mikuška Ján , Jánošík Michal , Csibri Tamás , Staniaszek Stanislaw , Baranowski Adam , Gontar Tadeusz
Published: December 2021

A comparison of transform margins that started their evolution as continental transforms shows differences in their tectonic style, which can be attributed to the variable kinematic adjustments they underwent during the post-breakup continental-oceanic stage of their development. Three end-member examples are presented in detail. The Cape Range transform fault zone (Western Australia) retained its strike-slip character during its entire continental-oceanic stage, as documented by the transform-perpendicular system of spreading-related magnetic stripe anomalies. The Coromandal transform fault zone (Eastern India) adjusted its kinematics to a transtensional one during its continental-oceanic stage, as indicated by the transform-oblique system of magnetic stripe anomalies and extensional component of movement indicated by a narrow zone of crustal thinning. The Romanche transform fault zone (Equatorial Africa) adjusted its kinematics to transpressional, as documented by the changing geometries of magnetic stripe anomalies and transpressional folding during its continental-oceanic development stage. Based on the recognition of the aforementioned adjustments, we suggest a new categorization of transforms into (1) those that experience transpressional adjustment, (2) those that experience transtensional adjustment and (3) those that do not experience any adjustment during their continental-oceanic development stage.
Neural Arabic Text Diacritization: State-of-the-Art Results and a Novel Approach for Arabic NLP Downstream Tasks
Authors: Fadel Ali , Tuffaha Ibraheem , Al-Ayyoub Mahmoud
Published: December 2021

In this work, we present several deep learning models for the automatic diacritization of Arabic text. Our models are built using two main approaches, viz. Feed-Forward Neural Network (FFNN) and Recurrent Neural Network (RNN), with several enhancements such as 100-hot encoding, embeddings, Conditional Random Field (CRF), and Block-Normalized Gradient (BNG). The models are tested on the only freely available benchmark dataset and the results show that our models are either better or on par with other models even those requiring human-crafted language-dependent post-processing steps, unlike ours. Moreover, we show how diacritics in Arabic can be used to enhance the models of downstream NLP tasks such as Machine Translation (MT) and Sentiment Analysis (SA) by proposing novel
Translation over Diacritization
(ToD) and
Sentiment over Diacritization
(SoD) approaches.
ConE: A Concurrent Edit Detection Tool for Large-scale Software Development
Authors: Maddila Chandra , Nagappan Nachiappan , Bird Christian , Gousios Georgios , van Deursen Arie
Published: December 2021

Modern, complex software systems are being continuously extended and adjusted. The developers responsible for this may come from different teams or organizations, and may be distributed over the world. This may make it difficult to keep track of what other developers are doing, which may result in multiple developers concurrently editing the same code areas. This, in turn, may lead to hard-to-merge changes or even merge conflicts, logical bugs that are difficult to detect, duplication of work, and wasted developer productivity. To address this, we explore the extent of this problem in the pull-request-based software development model. We study half a year of changes made to six large repositories in Microsoft in which at least 1,000 pull requests are created each month. We find that files concurrently edited in different pull requests are more likely to introduce bugs. Motivated by these findings, we design, implement, and deploy a service named Concurrent Edit Detector (ConE) that proactively detects pull requests containing concurrent edits, to help mitigate the problems caused by them. ConE has been designed to scale, and to minimize false alarms while still flagging relevant concurrently edited files. Key concepts of ConE include the detection of the
Extent of Overlap
between pull requests, and the identification of
Rarely Concurrently Edited Files
. To evaluate ConE, we report on its operational deployment on 234 repositories inside Microsoft. ConE assessed 26,000 pull requests and made 775 recommendations about conflicting changes, which were rated as useful in over 70% (554) of the cases. From interviews with 48 users, we learned that they believed ConE would save time in conflict resolution and avoiding duplicate work, and that over 90% intend to keep using the service on a daily basis.
What You See is What it Means! Semantic Representation Learning of Code based on Visualization and Transfer Learning
Authors: Keller Patrick , Kaboré Abdoul Kader , Plein Laura , Klein Jacques , Le Traon Yves , Bissyandé Tegawendé F.
Published: December 2021

Recent successes in training word embeddings for
Natural Language Processing
(
NLP
) tasks have encouraged a wave of research on representation learning for source code, which builds on similar NLP methods. The overall objective is then to produce code embeddings that capture the maximum of program semantics. State-of-the-art approaches invariably rely on a syntactic representation (i.e., raw lexical tokens, abstract syntax trees, or intermediate representation tokens) to generate embeddings, which are criticized in the literature as non-robust or non-generalizable. In this work, we investigate a novel embedding approach based on the intuition that source code has visual patterns of semantics. We further use these patterns to address the outstanding challenge of identifying semantic code clones. We propose the

WySiWiM

 (
‘
‘What You See Is What It Means
”
) approach where visual representations of source code are fed into powerful pre-trained image classification neural networks from the field of computer vision to benefit from the practical advantages of transfer learning. We evaluate the proposed embedding approach on the task of vulnerable code prediction in source code and on two variations of the task of semantic code clone identification: code clone detection (a binary classification problem), and code classification (a multi-classification problem). We show with experiments on the BigCloneBench (Java), Open Judge (C) that although simple, our
WySiWiM
 approach performs as effectively as state-of-the-art approaches such as ASTNN or TBCNN. We also showed with data from NVD and SARD that
WySiWiM
 representation can be used to learn a vulnerable code detector with reasonable performance (accuracy ∼90%). We further explore the influence of different steps in our approach, such as the choice of visual representations or the classification algorithm, to eventually discuss the promises and limitations of this research direction.
How Software Refactoring Impacts Execution Time
Authors: Traini Luca , Di Pompeo Daniele , Tucci Michele , Lin Bin , Scalabrino Simone , Bavota Gabriele , Lanza Michele , Oliveto Rocco , Cortellessa Vittorio
Published: December 2021

Refactoring aims at improving the maintainability of source code without modifying its external behavior. Previous works proposed approaches to recommend refactoring solutions to software developers. The generation of the recommended solutions is guided by metrics acting as proxy for maintainability (e.g., number of code smells removed by the recommended solution). These approaches ignore the impact of the recommended refactorings on other non-functional requirements, such as performance, energy consumption, and so forth. Little is known about the impact of refactoring operations on non-functional requirements other than maintainability.

We aim to fill this gap by presenting the largest study to date to investigate the impact of refactoring on software performance, in terms of execution time. We mined the change history of 20 systems that defined performance benchmarks in their repositories, with the goal of identifying commits in which developers implemented refactoring operations impacting code components that are exercised by the performance benchmarks. Through a quantitative and qualitative analysis, we show that refactoring operations can significantly impact the execution time. Indeed, none of the investigated refactoring types can be considered “safe” in ensuring no performance regression. Refactoring types aimed at decomposing complex code entities (e.g., Extract Class/Interface, Extract Method) have higher chances of triggering performance degradation, suggesting their careful consideration when refactoring performance-critical code.
A Practical Approach for Dynamic Taint Tracking with Control-flow Relationships
Authors: Hough Katherine , Bell Jonathan
Published: December 2021

Dynamic taint tracking, a technique that traces relationships between values as a program executes, has been used to support a variety of software engineering tasks. Some taint tracking systems only consider data flows and ignore control flows. As a result, relationships between some values are not reflected by the analysis. Many applications of taint tracking either benefit from or rely on these relationships being traced, but past works have found that tracking control flows resulted in over-tainting, dramatically reducing the precision of the taint tracking system. In this article, we introduce
Conflux
, alternative semantics for propagating taint tags along control flows.
Conflux
aims to reduce over-tainting by decreasing the scope of control flows and providing a heuristic for reducing loop-related over-tainting. We created a Java implementation of
Conflux
and performed a case study exploring the effect of
Conflux
on a concrete application of taint tracking, automated debugging. In addition to this case study, we evaluated
Conflux
’s accuracy using a novel benchmark consisting of popular, real-world programs. We compared
Conflux
against existing taint propagation policies, including a state-of-the-art approach for reducing control-flow-related over-tainting, finding that
Conflux
had the highest F1 score on 43 out of the 48 total tests.
Why Do Developers Reject Refactorings in Open-Source Projects?
Authors: Pantiuchina Jevgenija , Lin Bin , Zampetti Fiorella , Di Penta Massimiliano , Lanza Michele , Bavota Gabriele
Published: December 2021

Refactoring operations are behavior-preserving changes aimed at improving source code quality. While refactoring is largely considered a good practice, refactoring proposals in pull requests are often rejected after the code review. Understanding the reasons behind the rejection of refactoring contributions can shed light on how such contributions can be improved, essentially benefiting software quality.

This article reports a study in which we manually coded rejection reasons inferred from 330 refactoring-related pull requests from 207 open-source Java projects. We surveyed 267 developers to assess their perceived prevalence of these identified rejection reasons, further complementing the reasons.

Our study resulted in a comprehensive taxonomy consisting of 26 refactoring-related rejection reasons and 21 process-related rejection reasons. The taxonomy, accompanied with representative examples and highlighted implications, provides developers with valuable insights on how to ponder and polish their refactoring contributions, and indicates a number of directions researchers can pursue toward better refactoring recommenders.
A Tale of Two Cities: Software Developers Working from Home during the COVID-19 Pandemic
Authors: Ford Denae , Storey Margaret-Anne , Zimmermann Thomas , Bird Christian , Jaffe Sonia , Maddila Chandra , Butler Jenna L. , Houck Brian , Nagappan Nachiappan
Published: December 2021

The COVID-19 pandemic has shaken the world to its core and has provoked an overnight exodus of developers who normally worked in an office setting to working from home. The magnitude of this shift and the factors that have accompanied this new unplanned work setting go beyond what the software engineering community has previously understood to be remote work. To find out how developers and their productivity were affected, we distributed two surveys (with a combined total of 3,634 responses that answered all required questions) weeks apart to understand the presence and prevalence of the benefits, challenges, and opportunities to improve this special circumstance of remote work. From our thematic qualitative analysis and statistical quantitative analysis, we find that there is a
dichotomy
of developer experiences influenced by many different factors (that for some are a benefit, while for others a challenge). For example, a benefit for some was being close to family members but for others having family members share their working space and interrupting their focus, was a challenge. Our surveys led to powerful narratives from respondents and revealed the scale at which these experiences exist to provide insights as to how the future of (pandemic) remote work can evolve.
Guided Feature Identification and Removal for Resource-constrained Firmware
Authors: Williams Ryan , Ren Tongwei , De Carli Lorenzo , Lu Long , Smith Gillian
Published: December 2021

IoT firmware oftentimes incorporates third-party components, such as network-oriented middleware and media encoders/decoders. These components consist of large and mature codebases, shipping with a variety of non-critical features. Feature bloat increases code size, complicates auditing/debugging, and reduces stability. This is problematic for IoT devices, which are severely resource-constrained and must remain operational in the field for years.

Unfortunately, identification and complete removal of code related to unwanted features requires familiarity with codebases of interest, cumbersome manual effort, and may introduce bugs. We address these difficulties by introducing PRAT, a system that takes as input the codebase of software of interest, identifies and maps features to code, presents this information to a human analyst, and removes all code belonging to unwanted features. PRAT solves the challenge of identifying feature-related code through a novel form of differential dynamic analysis and visualizes results as user-friendly
feature graphs
.

Evaluation on diverse codebases shows superior code removal compared to both manual feature deactivation and state-of-art debloating tools, and generality across programming languages. Furthermore, a user study comparing PRAT to manual code analysis shows that it can significantly simplify the feature identification workflow.
Why Do Smart Contracts Self-Destruct? Investigating the Selfdestruct Function on Ethereum
Authors: Chen Jiachi , Xia Xin , Lo David , Grundy John
Published: December 2021

The
selfdestruct
function is provided by Ethereum smart contracts to destroy a contract on the blockchain system. However, it is a double-edged sword for developers. On the one hand, using the
selfdestruct
function enables developers to remove
smart contracts
(
SCs
) from Ethereum and transfers Ethers when emergency situations happen, e.g., being attacked. On the other hand, this function can increase the complexity for the development and open an attack vector for attackers. To better understand the reasons why SC developers include or exclude the
selfdestruct
function in their contracts, we conducted an online survey to collect feedback from them and summarize the key reasons. Their feedback shows that 66.67% of the developers will deploy an updated contract to the Ethereum after destructing the old contract. According to this information, we propose a method to find the self-destructed contracts (also called predecessor contracts) and their updated version (successor contracts) by computing the code similarity. By analyzing the difference between the predecessor contracts and their successor contracts, we found five reasons that led to the death of the contracts; two of them (i.e.,
Unmatched ERC20 Token and Limits of Permission
) might affect the life span of contracts. We developed a tool named
LifeScope
to detect these problems.
LifeScope
reports 0 false positives or negatives in detecting
Unmatched ERC20 Token
. In terms of
Limits of Permission
,
LifeScope
achieves 77.89% of F-measure and 0.8673 of AUC in average. According to the feedback of developers who exclude
selfdestruct
functions, we propose suggestions to help developers use
selfdestruct
functions in Ethereum smart contracts better.
Analyzing Uncertainty in Release Planning: A Method and Experiment for Fixed-Date Release Cycles
Authors: Oni Olawole , Letier Emmanuel
Published: December 2021

Release planning—deciding what features to implement in upcoming releases of a software system—is a critical activity in iterative software development. Many release planning methods exist, but most ignore the inevitable uncertainty in estimating software development effort and business value. The article’s objective is to study whether analyzing uncertainty during release planning generates better release plans than if uncertainty is ignored. To study this question, we have developed a novel release planning method under uncertainty, called BEARS, that models uncertainty using Bayesian probability distributions and recommends release plans that maximize expected net present value and expected punctuality. We then compare release plans recommended by BEARS to those recommended by methods that ignore uncertainty on 32 release planning problems. The experiment shows that BEARS recommends release plans with higher expected net present value and expected punctuality than methods that ignore uncertainty, thereby indicating the harmful effects of ignoring uncertainty during release planning. These results highlight the importance of eliciting and analyzing uncertainty in software effort and value estimations and call for increased research in these areas.
Back Propagation Neural Network-Based Magnetic Resonance Imaging Image Features in Treating Intestinal Obstruction in Digestive Tract Diseases with Chengqi Decoction
Authors: Li Yongfeng , Wang Kaina , Gao Li , Lu Xiaojun
Published: December 2021

This study was to explore the adoption effect of magnetic resonance imaging (MRI) image features based on back propagation neural network (BPNN) in evaluating the curative effect of Chengqi Decoction (CD) for intestinal obstruction (ileus), so as to evaluate the clinical adoption value of this algorithm. Ninety patients with ileus were recruited, and the patients were treated with CD and underwent MRI scans of the lower abdomen. A BPNN model was fabricated and applied to segment the MRI images of patients and identify the lesion. As a result, when the overlap step was 16 and the block size was 32 × 32, the running time of the BPNN algorithm was the shortest. The segmentation accuracy was the highest if there were two hidden layer (HL) nodes, reaching 97.3%. The recognition rates of small intestinal stromal tumor (SIST), colon cancer, adhesive ileus, and volvulus of MRI images segmented by the algorithm were 91.5%, 88.33%, 90.3%, and 88.9%, respectively, which were greatly superior to those of manual interpretation (

P
<
0.05

). After the intervention of CD, the percentages of patients with ileus that were cured, markedly effective, effective, and ineffective were 65.38%, 23.16%, 5.38%, and 6.08%, respectively. The cure rate after intervention of CD (65.38%) was much higher in contrast to that before intervention (13.25%) (

P
<
0.05

). In short, CD showed a good therapeutic effect on ileus and can effectively improve the prognosis of patients. In addition, MRI images based on BPNN showed a good diagnostic effect on ileus, and it was worth applying to clinical diagnosis.
The Impact of Fleet Coordination on Taxi Operations
Authors: Ruch Claudio , Hörl Sebastian , Gächter Joel , Hakenberg Jan
Published: December 2021

On-demand mobility has existed for more than 100 years in the form of taxi systems. Comparatively recently, ride-hailing schemes have also grown to a significant mode share. Most types of such one-way mobility-on-demand systems allow drivers taking independent decisions. These systems are not or only partially coordinated. In a different operating mode, all decisions are coordinated by the operator, allowing for the optimization of certain metrics. Such a coordinated operation is also implied if human-driven vehicles are replaced by self-driving cars. This work quantifies the service quality and efficiency improvements resulting from the coordination of taxi fleets. Results based on high-fidelity transportation simulations and data sets of existing taxi systems are presented for the cities of San Francisco, Chicago, and Zurich. They show that fleet coordination can strongly improve the efficiency and service level of existing systems. Depending on the operator and the city’s preferences, empty vehicle distance driven and fleet sizes could be substantially reduced, or the wait times could be reduced while maintaining the current fleet sizes. The study provides clear evidence that full fleet coordination should be implemented in existing mobility-on-demand systems, even before the availability of self-driving cars.
[Retracted] Graphene: A Multifunctional Nanomaterial with Versatile Applications
Authors: Murthy H. C. Ananda , Ghotekar Suresh , Vinay Kumar B. , Roy Arpita
Published: December 2021

Graphene is a 2D material of high quality obtained from a single atom with unique electronic properties. Graphene has the potential to improve the efficiency, versatility, and durability of a wide range of materials and their applications, but its commercial exploitation will require further study. Due to its flatness and semiconductivity in addition to its high surface area, high mechanical rigidity, high thermal stability, superior thermal conductivity, and electrical conductivity, good biocompatibility, and easy functionalization, graphene is the best candidate for multifunctional applications which opened up new possibilities for potential devices and systems. Every type of graphene material is found to exhibit different and unique tunable properties. Graphene is the best candidate in making nanocomposite‐based electrochemical sensors. Graphene is among the best electronic materials, but synthesizing a single sheet of graphene has received less attention. The objective of this chapter is to bring awareness to readers on the synthesis, properties, and applications of graphene. The limitations of the current knowledge base and prospective research directions related to graphene materials have also been illustrated.
Trajectory Tracking of Autonomous Ground Vehicles with Actuator Dead Zones
Authors: Zhang Pengfei , Chen Qiyuan , Yang Tingting
Published: December 2021

This paper investigates the trajectory tracking problem of autonomous ground vehicles (AGVs). The dynamics considered feature external disturbances, model uncertainties, and actuator dead zones. First, a novel time-varying yaw guidance law is proposed based on the line of sight method. By a state transformation, the AGV is proved to realize trajectory tracking control under the premise of eliminating guidance deviation. Second, a fixed time dead zone compensation control method is introduced to ensure the yaw angle tracking of the presented guidance. Furthermore, an improved fixed-time disturbance observer is proposed to compensate for the influence of the actuator dead zone on disturbance observation. Finally, the trajectory tracking control strategy is designed, and simulation comparison shows the effectiveness of the compensate method. The CarSim–MATLAB cosimulation shows that the proposed control strategy effectively makes the AGV follow the reference trajectory.
Computerized Tomography Imaging Omics under Iterative Reconstruction Algorithm in Diagnosis of Gastric Cancer
Authors: Zhou Chunfang , Tian Shufang , Lv Fei , Shang Rui , Zheng Xuejiao
Published: December 2021

This study aimed to explore the application value of computed tomography (CT) imaging radiomics based on a sinogram-affirmed iterative reconstruction algorithm (SAFIRE) in the diagnosis of gastric cancer. 59 patients who were clinically diagnosed with gastric cancer were selected as research objects and arranged CT examinations. The images obtained were optimized by the SAFIRE for the staging of gastric cancer. The pathological biopsy results were used as the gold standard to evaluate its diagnostic effect and compared with the filtered back-projection (FBP) method. The results showed that the carrier-to-noise ratio (CNR) (0.979) and signal-to-noise ratio (SNR) (0.967) of the CT image after the algorithm processing were significantly higher than those (0.781, 0.744) before (

P
<
0.05

). There was no significant difference in CT values between the FBP algorithm and S1, S2, and S3 (

P
>
0.05

); the area under the curve (AUC) (0.999) and sensitivity (0.98) of the CT training group under the SAFIRE algorithm for gastric cancer classification were higher than those of the verification group (0.958, 0.92). The preoperative CT staging kappa value was consistent with the postoperative pathological diagnosis of 0.882. CT images guided by SAFIRE can objectively and noninvasively assess the tumor asymmetry, discover additional information from subjective evaluation beyond the naked eye, and perform reasonable staging diagnosis of gastric cancer, which was useful for clinicians to develop high-quality individualized treatment plans.
Therapeutic Application of rTMS in Atypical Parkinsonian Disorders
Authors: Petsani Chrysi , Aloizou Athina-Maria , Siokas Vasileios , Messinis Lambros , Peristeri Eleni , Bakirtzis Christos , Nasios Grigorios , Dardiotis Efthimios
Published: December 2021

The terms atypical parkinsonian disorders (APDs) and Parkinson plus syndromes are mainly used to describe the four major entities of sporadic neuronal multisystem degeneration: progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), multiple system atrophy (MSA), and dementia with Lewy bodies (LBD). APDs are characterized by a variety of symptoms and a lack of disease modifying therapies; their treatment thus remains mainly symptomatic. Brain stimulation via repetitive transcranial magnetic stimulation (rTMS) is a safe and noninvasive intervention using a magnetic coil, and it is considered an alternative therapy in various neuropsychiatric pathologies. In this paper, we review the available studies that investigate the efficacy of rTMS in the treatment of these APDs and Parkinson plus syndromes. Τhe majority of the studies have shown beneficial effects on motor and nonmotor symptoms, but research is still at a preliminary phase, with large, double-blind studies lacking in the literature.
Fracture Morphology Analysis of Frozen Red Sandstone under Impact
Authors: Yang Yang , Zhang Niannian , Wang Jianguo
Published: December 2021

The deformation and failure characteristics of red sandstone under subzero temperature were studied by the split Hopkinson pressure bar (SHPB) dynamic impact test. The effects of different subzero temperatures on rock strength properties, fractal dimension, and dissipated energy were analyzed combined with microfracture morphology. The reasons for rock dynamic mechanical property deterioration under lower subzero temperatures were revealed. The research shows that low subzero temperature will cause “frostbite” of red sandstone. Under high strain rate loading, the rock will quickly lose its bearing capacity, and its dynamic mechanical strength will drop sharply. The dissipated energy WL of the frozen rock specimen is positively correlated with the fractal dimension D and closely related to the macroscopic failure characteristics. It could be concluded that greater dissipation energy leads to more serious damage of rock and accordingly results in a larger fractal dimension. Fracture morphology analysis shows that the lower subzero temperature generated remarkable cracks in the material interface of the red sandstone. The damage of the red sandstone could be explained by the fact that the crack tip had low plastic deformation ability under high strain rate loading and the composition of cement was vulnerable to the subzero temperature effect.
Mechanical Properties and Degradation Behaviors of Zn-xMg Alloy Fine Wires for Biomedical Applications
Authors: Bai Jing , Xu Yan , Fan Qizhou , Cao Ruihua , Zhou Xingxing , Cheng Zhaojun , Dong Qiangsheng , Xue Feng
Published: December 2021

Zn and Zn-based alloys exhibit biosafety and biodegradation, considered as candidates for biomedical implants. Zn-0.02 wt.% Mg (Zn-0.02 Mg), Zn-0.05 wt.% Mg (Zn-0.05 Mg), and Zn-0.2 wt.% Mg (Zn-0.2 Mg) wires (Φ 0.3 mm) were prepared for precision biomedical devices in this work. With the addition of Mg in Zn-xMg alloys, the grain size decreased along with the occurrence of Mg2Zn11 at the grain boundaries. Hot extrusion, cold drawing, and annealing treatment were introduced to further refining the grain size. Besides, the hot extrusion and cold drawing improved the tensile strength of Zn-xMg alloys to 240-270 MPa while elongation also increased but remained under 10%. Annealing treatment could improve the elongation of Zn alloys to 12% -28%, but decrease the tensile strength. Furthermore, Zn-xMg wires displayed an increase in degradation rate with Mg addition. The findings might provide a potential possibility of Zn-xMg alloy wires for biomedical applications.
Ultrasound-Assisted Extraction of Micro- and Macroelements in Fruit Peel Powder Mineral Supplement for Osteoporosis Patients and Their Determination by Flame Atomic Absorption Spectrometry
Authors: Saleem Muhammad , Durani Arjumand Iqbal , Alharthy Rima D. , Ahmed Mahmood , Shafiq Muhammad Imtiaz , Hameed Abdul , Mubasher Hussain Syed , Bashir Waqas
Published: December 2021

Osteoporosis is a worldwide disease depicted by the reduced bone mass, an adequate supply of minerals is needed to support bone remodeling, and their deficiency causes bone-related diseases, osteoporosis in particular, and has osteoprotective effects. The aim of this recent research was to quantify the micro- (Mn, Fe, Cu, and Zn) and macroelements (Mg, K, and Ca) in the peel powder of some common fruits (pomegranate, orange, lemon, mango, and grapefruit) by flame atomic absorption spectrometer (FAAS). The extraction of micro- and macroelements in peel powder was done by using dilute acids in an ultrasonic bath. Apple leaves were used as standard reference material (SRM, NIST 1515) to optimize the ultrasound-assisted extraction (UAE) method at varied operating parameters. Maximum response was obtained for extracting of minerals in 500 mg SRM at 60°C temperature, setting a vortexing time of 5 min while using 5.0 mL extracting agent HNO3 (0.5 M)-H2O2 (10%) at 90% sonication amplitude of ultrasound bath for 6 min. While analyzing the SRM, the percentage recovery was obtained in a range between 96.8 and 102.7% to assure the accuracy whereas repeatability (n = 10) study in terms of % RSD yielding ≤2.29 supports well the precision of the proposed method, and limits of quantitation (μg/g) were 0.034, 0.061, 0.065, 0.057, 0.017, 0.175, and 0.053 for Mn, Fe, Cu, Zn, Mg, K, and Ca, respectively. The proposed UAE method was reliable, efficient, and advantageous over the conventionally employed acid digestion method with regard to less consumption of reagents and short analysis time for the determination of micro- and macroelements in fruit peel powder.
[Retracted] Empirical Investigation on the Characteristics and Perceived Value of Patients in Medical Treatment Seeking: In‐Depth Research in Zhejiang Province of China
Authors: Qian Hui , Lu Wu , Zhang Daliang
Published: December 2021

Background. Patient Perceived Value (PPV) provides a valuable perspective to explain why the government reforms on health system in terms of functional medical treatment performance improvement did not decrease the crowded waiting line or increased patient satisfaction in China. Methods. Questionnaires comprising seven constructs were sent to patients from seven highly recognized hospitals in Zhejiang Province of China. It was collected via face‐by‐face in a twelve‐month period (2019), and 2586 valid data were collected for SPSS statistic accordingly. Results. Besides the significance of the functional medical treatment values (such as the treatment effectiveness, accurate price, standardization, and normalization), the emotional values (reasonable waiting time, convenient accessibility, communication with doctors/nurses) were significant in patients’ consciousness. Patient medical treatment seeking preferences were affected by patients’ background characteristics and perceived value, which consequently produced differentiated patients’ satisfaction. Patients’ characteristics, which related to the age, gender, illness conditions, educational, and income level, would have different demanding in medical treatment seeking. These young female patients in outpatient or in mild illness conditions with higher educational and income levels tend to be relatively high in timing and convenience demanding. Conclusion. This result would change the policy maker and hospitals to considerate the patients’ emotional value as well as functional value in providing medical treatment. Classified patients’ time arrangement tactics consistent with distinguished characteristics, equipped up with convenient accessibility and interconnected medical treatment environment design, can create valuable patients’ satisfaction in China.
Influence of Alkali Treatment and Maleated Polypropylene (MAPP) Compatibilizer on the Dry‐Sliding Wear and Frictional Behavior of Borassus Fruit Fine Fiber (BFF)/Polypropylene (PP) Polymer Composites for Various Engineering Applications
Authors: Nijjar Sumit , Sudhakara P. , Sharma Shubham , Saini Sanjeev , Teklemariam Aklilu , Mariselvam V. , Sampath Satheesh Kumar , Song J. I.
Published: December 2021

Tribological properties of the novel Borassus fruit fine fiber‐ (BFF‐) reinforced polypropylene (PP) composites with respect to fiber matrix surface modifications have been described. Composites were fabricated by an injection molding process using Borassus fruit fine fiber (BFF) of 5 wt.% as reinforcement and polypropylene (PP) as a matrix component. Fibers were treated with alkali (T) to remove the residual lignin (if present) and to enhance the interfacial adhesion between the fiber/matrix interface. Alkali treatment reveals additional reactive functional groups here on the surface of the Borassus fiber, allowing effective interaction bonding with the polypropylene matrix. Borassus fibers are primarily treated with an alkali solution to extract weaker unstructured amorphous constituents so that the fibers retain crystallized components, thereby strengthening the fiber’s strength. A 5 wt.% of maleated polypropylene (MAPP) was used as a compatibilizer to improve the interfacial adhesion between fiber and the polymer matrix. The wear and frictional behavior of BFF/PP composites with respect to the modifications were evaluated by steel counterface utilizing pin‐on‐disc test contraption under dry‐sliding conditions. The sliding velocity, applied load, and sliding distance were maintained as 2.198 m/s, 9.81–29.43 N, and 4000 m, respectively. The results demonstrate that the reinforcement of BFF to polypropylene matrix and the modifications improved the wear properties of the neat polymer matrix. Findings concluded that the abrasive wear resistance of T + PP + MAPP composite showed better interfacial adhesion and bonding, thus resulting in better tribological performance as compared to the other three compositions under different loading conditions. The effective substantial improvement of the coefficient of friction has been observed in alkali‐treated fiber and polypropylene matrix with MAPP compatibilizer (T + PP + MAPP) composites due to the presence of MAPP compatibilizer and alkali‐treated fibers. The frictional coefficient of T + PP + MAPP possesses better interfacial bonding strength upon NaOH treatment, and coupling agent, which results in enhancement of effective contact surface area and good surface friction characteristics, has been observed under different loading conditions. The fracture mechanism of worn‐out portions of BFF/PP composites was studied using high‐resolution scanning electron microscopy to analyze various imperfections like debonding, splits, fiber cracks, and wreckage or fragments formation.
A Chinese Lip-Reading System Based on Convolutional Block Attention Module
Authors: Lu Yuanyao , Xiao Qi , Jiang Haiyang
Published: December 2021

In recent years, deep learning has already been applied to English lip-reading. However, Chinese lip-reading starts late and lacks relevant dataset, and the recognition accuracy is not ideal. Therefore, this paper proposes a new hybrid neural network model to establish a Chinese lip-reading system. In this paper, we integrate the attention mechanism into both CNN and RNN. Specifically, we add the convolutional block attention module (CBAM) to the ResNet50 neural network, which enhances its ability to capture the small differences among the mouth patterns of similarly pronounced words in Chinese, improving the performance of feature extraction in the convolution process. We also add the time attention mechanism to the GRU neural network, which helps to extract the features among consecutive lip motion images. Considering the effects of the moments before and after on the current moment in the lip-reading process, we assign more weights to the key frames, which makes the features more representative. We further validate our model through experiments on our self-built dataset. Our experiments show that using convolutional block attention module (CBAM) in the Chinese lip-reading model can accurately recognize Chinese numbers 0–9 and some frequently used Chinese words. Compared with other lip-reading systems, our system has better performance and higher recognition accuracy.
Evaluation of the Volume Stability and Resource Benefit of Basic Oxygen Furnace Slag and Its Asphalt Mixture Based on Field Application
Authors: Zhao Yuechao , Song Jiangkai , Xie Jun , Wang Fusong , Chen Meizhu , Wu Shaopeng
Published: December 2021

Applying basic oxygen furnace (BOF) slag as aggregate in asphalt mixture is continuously investigated due to the increasing shortage of natural aggregate in recent years. However, the negative effect of BOF’s expansion in water greatly limits its further application in pavement construction. To address this problem, this paper studied the volume stability of BOF, and its asphalt mixture relied on actual engineering. The asphalt mixtures contained BOF aggregate was designed by the Marshall method with three different gradation types (AC‐16, AC‐20, and ATB‐25). Besides, both laboratory samples and the core samples from field drilling were investigated in volume expansion rate after curing in a water bath. The economic and resource benefits of BOF replacement of natural aggregates were also analyzed. The results showed that the free calcium oxide content of BOF slag is positively related to the particle sizes. Nevertheless, the expansion rates of both the BOF aggregate and its asphalt mixture were less than 1%, which meant the BOF aggregate applied to the asphalt mixture meets the practical engineering requirements. The maximum allowable free calcium oxide content for large‐grain size of steel slag is the smallest; it is also recommended that the expansibility of large‐grain steel slag should be the first concern in the application. The resource assessment indicated that the use of steel slag for the construction of a trial section of one kilometer of single lane can save 967 tons of natural aggregates. The economic evaluation showed that the use of steel slag instead of natural aggregates for surface course construction could reduce the investment by 16.87%. The experimental methods and conclusions mentioned in this article provide stable references to enhance the development of sustainable pavement by recycling metallurgical slag in highway construction.
Internet of Things Based Intelligent Techniques in Workable Computing: An Overview
Authors: Guo Jiayi , Nazir Shah
Published: December 2021

With the constant developments in Internet communication and the rise of the Internet of Things (IoT), technologies incorporating intelligent manufacturing have given birth to the growing industry and production lines. The network of IoT is generally interconnected with different devices through the Internet. The interactions of the IoT devices form smooth and functional communication require the connectivity of billions of objects. The devices of IoT can preserve, capture, share, and analyze data with nodes connected to the world. Various issues of the IoT such as monitoring the data, stealing the data, privacy of the data, tracking of the data, and many other aspects of the data are becoming challenges for the modern-day industry. The role of computational intelligence in proper analysis, managing, and many different perspectives of the IoT is prominent. Such computational intelligence can solve real-time problems with low cost and time. The IoT has provided solutions for poor scalability, system integration, and difficulties in coordinated operation across the emerging systems. The influence of the proposed study is to offer a wide-ranging overview of the current literature related to the Internet of Things based on intelligent techniques in workable computing. The study has considered the search process in the most popular libraries and presented an analysis of the research work done so far. The analysis and results of the study support the progress in the field, which will help researchers come up with new solutions.