bluuebunny/crossref_metadata_2025 huggingface dataset:
First principles computation of structural, electronic, magnetic and mechanical properties of new lithium based half Heusler alloys
Authors: Shakil M. , Ahmed Shahzad , Zeba I. , Khan M. I. , Gillani S. S. A.
Published: February 2021

First principles calculations have been accomplished for structural, electronic, magnetic and mechanical properties of half Heusler (HH) LiYZ ([Formula: see text], Rh and [Formula: see text], Se, Te, Sb) alloys using the density functional theory (DFT) within full potential-linearized augmented plane wave (FP-LAPW) method. To calculate the physical properties, Perdew–Burke–Ernzerhof (PBE) potential and generalized gradient approximation (GGA) are employed. The calculations are accomplished for three phases to obtain the most stable phase. The results of these calculations revealed that Type-III is the most stable of LiRhSe and LiRhSb, Type-I of LiRhAs, LiRhTe, LiRuAs, LiRuSb, LiRuSe and LiRuTe alloys. The structural optimization is obtained by plotting the graphs between minimum volume and the lowest energy of all considered alloys. The results of electronic properties including density of states (DOS) and band structures are also presented. The obtained total magnetic moment (MM) is negative for LiRhSb, LiRuSb, LiRhTe, LiRuTe, while it is positive for LiRhSe, LiRuSe, LiRhAs, LiRuAs Heusler alloys (HAs). To determine the mechanical stability, several parameters such as Poisson’s ratio, Pugh’s ratio, Lame’s coefficient, anisotropy factor, Kleinman parameter, Young’s modulus, Bulk modulus and Cauchy pressure are calculated and discussed in detail.
MSENet: Multi-Modal Squeeze-and-Excitation Network for Brain Tumor Severity Prediction
Authors: Bodapati Jyostna Devi , Shareef Shaik Nagur , Naralasetti Veeranjaneyulu , Mundukur Nirupama Bhat
Published: February 2021

Classification of brain tumors is one of the daunting tasks in medical imaging and incorrect decisions during the diagnosis process may lead to increased human fatality. Latest advances in artificial intelligence and deep learning have opened the path for the success of numerous medical image analysis tasks, including the recognition of brain tumors. In this paper, we propose a simple architecture based on deep learning that results in strong generalization without needing much preprocessing. The proposed Multi-modal Squeeze and Excitation model (MSENet) receives multiple representations of a given tumor image, learns end-to-end and effectively predicts the severity level of tumor. Convolution feature descriptors from multiple deep pre-trained models are used to effectively describe the tumor images and are supplied as input to the proposed MSENet. The squeeze and excitation blocks of the MSENet allow the model to prioritize tumor regions while giving less emphasis to the rest of the image, serving as an attention mechanism in the model. The proposed model is evaluated on the benchmark brain tumor dataset that is publicly accessible from the Figshare repository. Experimental studies reveal that in terms of model parameters, the proposed approach is simple and leads to competitive performance compared to those of existing complex models. By increasing complexity, the proposed model leads to generalize better and achieves state-of-the-art accuracy of 96.05% on Figshare dataset. Compared to the existing models, the proposed model neither uses segmentation nor uses augmentation techniques and without much pre-processing achieves competitive performance.
Development of a 2NN-MEAM potential for boron
Authors: Attarian Siamak , Xiao Shaoping
Published: February 2021

In this paper, we present the first work in developing a second nearest-neighbor modified embedded atom method (2NN-MEAM) potential function that can be used to model interatomic interactions in both [Formula: see text] boron and [Formula: see text] boron polymorphs. To fit the potential parameters by optimization, some physical properties and elastic constants of boron, calculated from the density functional theory, are adopted as the targets in the objective function. The developed potential is utilized in molecular dynamics (MD) simulations to calculate the physical, mechanical, and thermal properties of [Formula: see text] boron and [Formula: see text] boron. A comprehensive comparison is conducted between the MD simulations and various experimental studies if available to validate the developed potential function. It is concluded that the developed 2NN-MEAM potential can be practically employed in MD modeling and simulation of boron. This work will also enhance the future development of binary potentials for boron compounds to study boron-based composites via MD.
Industrial Federated Topic Modeling
Authors: Jiang Di , Tong Yongxin , Song Yuanfeng , Wu Xueyang , Zhao Weiwei , Peng Jinhua , Lian Rongzhong , Xu Qian , Yang Qiang
Published: February 2021

Probabilistic topic modeling has been applied in a variety of industrial applications. Training a high-quality model usually requires a massive amount of data to provide comprehensive co-occurrence information for the model to learn. However, industrial data such as medical or financial records are often proprietary or sensitive, which precludes uploading to data centers. Hence, training topic models in industrial scenarios using conventional approaches faces a dilemma: A party (i.e., a company or institute) has to either tolerate data scarcity or sacrifice data privacy. In this article, we propose a framework named
Industrial Federated Topic Modeling
(iFTM), in which multiple parties collaboratively train a high-quality topic model by simultaneously alleviating data scarcity and maintaining immunity to privacy adversaries. iFTM is inspired by federated learning, supports two representative topic models (i.e., Latent Dirichlet Allocation and SentenceLDA) in industrial applications, and consists of novel techniques such as private Metropolis-Hastings, topic-wise normalization, and heterogeneous model integration. We conduct quantitative evaluations to verify the effectiveness of iFTM and deploy iFTM in two real-life applications to demonstrate its utility. Experimental results verify iFTM’s superiority over conventional topic modeling.
Designing Personas for Expressive Robots
Authors: Whittaker Steve , Rogers Yvonne , Petrovskaya Elena , Zhuang Hongbin
Published: February 2021

Imbuing robots with personality has been shown to be an effective design approach in HRI, promoting user trust and acceptance. We explore personality design in a non-anthropomorphic voice-assisted home robot. Our design approach developed three distinct robot personas: Butler, Buddy, and Sidekick, intended to differ in proactivity and emotional impact. Persona differences were signaled to users by a combination of humanoid (speech, intonation), and indirect cues (colors and movement). We use Big Five personality theory to evaluate perceived differences between personas in an exploratory Wizard of Oz study. Participants were largely able to recognize underlying personality traits expressed through these cue combinations in ways that were consistent with our design goals. The proactive Buddy persona was judged as more Extravert than the more passive Sidekick persona, and the Butler persona was perceived as more Conscientious and less Neurotic than either Buddy or Butler personas. Users also had clear preferences between different personas; they wanted robots that mimicked but accentuated their own personality. Results suggest that future designs might exploit abstract cues to signal personality traits.
HeM3D
Authors: Arka Aqeeb Iqbal , Joardar Biresh Kumar , Kim Ryan Gary , Kim Dae Hyun , Doppa Janardhan Rao , Pande Partha Pratim
Published: February 2021

Heterogeneous manycore architectures are the key to efficiently execute compute- and data-intensive applications. Through-silicon-via (TSV)-based 3D manycore system is a promising solution in this direction as it enables the integration of disparate computing cores on a single system. Recent industry trends show the viability of 3D integration in real products (e.g., Intel Lakefield SoC Architecture, the AMD Radeon R9 Fury X graphics card, and Xilinx Virtex-7 2000T/H580T, etc.). However, the achievable performance of conventional TSV-based 3D systems is ultimately bottlenecked by the horizontal wires (wires in each planar die). Moreover, current TSV 3D architectures suffer from thermal limitations. Hence, TSV-based architectures do not realize the full potential of 3D integration. Monolithic 3D (M3D) integration, a breakthrough technology to achieve “More Moore and More Than Moore,” opens up the possibility of designing cores and associated network routers using multiple layers by utilizing monolithic inter-tier vias (MIVs) and hence, reducing the effective wire length. Compared to TSV-based 3D integrated circuits (ICs), M3D offers the “true” benefits of vertical dimension for system integration: the size of an MIV used in M3D is over 100 × smaller than a TSV. This dramatic reduction in via size and the resulting increase in density opens up numerous opportunities for design optimizations in 3D manycore systems: designers can use up to millions of MIVs for ultra-fine-grained 3D optimization, where individual cores and routers can be spread across multiple tiers for extreme power and performance optimization. In this work, we demonstrate how M3D-enabled vertical core and uncore elements offer significant performance and thermal improvements in manycore heterogeneous architectures compared to its TSV-based counterpart. To overcome the difficult optimization challenges due to the large design space and complex interactions among the heterogeneous components (CPU, GPU, Last Level Cache, etc.) in a M3D-based manycore chip, we leverage novel design-space exploration algorithms to trade off different objectives. The proposed M3D-enabled heterogeneous architecture, called
HeM3D
, outperforms its state-of-the-art TSV-equivalent counterpart by up to 18.3% in execution time while being up to 19°C cooler.
Biomolecular Modeling and Simulation: A Prospering Multidisciplinary Field
Authors: Schlick Tamar , Portillo-Ledesma Stephanie , Myers Christopher G. , Beljak Lauren , Chen Justin , Dakhel Sami , Darling Daniel , Ghosh Sayak , Hall Joseph , Jan Mikaeel , Liang Emily , Saju Sera , Vohr Mackenzie , Wu Chris , Xu Yifan , Xue Eva
Published: February 2021

We reassess progress in the field of biomolecular modeling and simulation, following up on our perspective published in 2011. By reviewing metrics for the field's productivity and providing examples of success, we underscore the productive phase of the field, whose short-term expectations were overestimated and long-term effects underestimated. Such successes include prediction of structures and mechanisms; generation of new insights into biomolecular activity; and thriving collaborations between modeling and experimentation, including experiments driven by modeling. We also discuss the impact of field exercises and web games on the field's progress. Overall, we note tremendous success by the biomolecular modeling community in utilization of computer power; improvement in force fields; and development and application of new algorithms, notably machine learning and artificial intelligence. The combined advances are enhancing the accuracy andscope of modeling and simulation, establishing an exemplary discipline where experiment and theory or simulations are full partners.
Design and Numerical Analysis of a Novel Rectangular PCF (R-PCF)-Based Biochemical Sensor (BCS) in the THz Regime
Authors: Bulbul Abdullah Al-Mamun , Kouzani Abbas Z. , Mahmud M. A. Parvez , Nahid Abdullah-Al
Published: February 2021

A novel PCF-based sensor has been presented in this paper to sense different chemicals and biocomponents. The proposed biochemical sensor (BCS) comprises a simple arrangement of rectangular holes. The competence of this BCS in detecting analytes is evaluated employing the full-vector finite element method (FEM). Performance metrics prove the competence of this BCS in sensing various analytes that have a refractive index in the range of 1.33–1.48. The proposed BCS shows ultralower values for both the bulk absorption and confinement loss. This BCS attains a maximum of about 95.82% relative sensitivity at 2.5 THz. Also, the dispersion for this sensor is only 0.12 ± 0.011 ps/THz/cm at the same point of interest. These results prove that the proposed BCS will play a key role in sensing toxic chemicals, illegal drugs, biocomponents, etc. Besides, the simple rectangle-based PCF structure ensures the feasibility of fabrication by practicing the existing fabrication strategies.
Sharp Bounds of the Coefficient Results for the Family of Bounded Turning Functions Associated with a Petal-Shaped Domain
Authors: Barukab Omar M. , Arif Muhammad , Abbas Muhammad , Khan Sher Afzal
Published: February 2021

The goal of this article is to determine sharp inequalities of certain coefficient-related problems for the functions of bounded turning class subordinated with a petal-shaped domain. These problems include the bounds of first three coefficients, the estimate of Fekete-Szegö inequality, and the bounds of second- and third-order Hankel determinants.
Research on Accounting Intelligence System Modeling of Financial Performance Evaluation
Authors: Chen Ziyue
Published: February 2021

In the current competitive market environment, both enterprises and academia attach great importance to the research of financial performance evaluation. The quality of financial performance directly affects the sustainable development of enterprises. With the deepening of enterprise management concept, enterprises pay more attention to the use of financial performance evaluation analysis to promote the sound development of the whole enterprise. In order to understand the development status and development trend of enterprises and improve the efficiency of enterprise management, it is of great significance to establish a scientific and professional financial performance evaluation model for the sustainable development of enterprises. In this paper, based on FCM clustering algorithm, a fuzzy decision model is established. Combined with the factors affecting the financial performance of enterprises, the corresponding indicators are selected from the four aspects of profitability, operation ability, debt paying ability, and development ability to construct the financial performance evaluation system, and the comprehensive fuzzy evaluation model is constructed according to the financial evaluation system. This paper selects listed companies as the research object to evaluate and analyze the performance of enterprises. The results show that the overall performance of listed companies is not ideal and solvency, operation ability, and development ability need to be enhanced. Finally, in view of the problems existing in the listed enterprises, this paper puts forward the following countermeasures: implement cost assessment and pay attention to cost analysis to strengthen cost control; strengthen the cooperation between industrial chain enterprises and R&D departments; and pay attention to the use of talents and improve the ability of independent innovation.
Mechanical Behavior of Triaxial Geogrid Used for Reinforced Soil Structures
Authors: Zhang Jun , Cao Wen-Zhao , Zhou Yan-Jun
Published: February 2021

Geosynthetics‐reinforced soil (GRS) structures have been widely used for the prevention of geological hazards. As a recently introduced product, the triaxial geogrid has been confirmed to provide improved performance due to the more stable grid structure. This paper presents an evaluation of the mechanical behavior based on a series of laboratory tests. The unconfined tensile strength of biaxial geogrid and triaxial geogrid in different loading directions relative to the orientation of ribs was investigated. Then, more than 8 pullout tests were conducted on the triaxial geogrid specimens embedded in the compacted sand. The internal displacements along the geogrid length were monitored. The results show that the triaxial geogrid has been shown to provide nearly uniform tensile strength in all loading directions as compared with the biaxial geogrid. The triaxial geogrid deformation is mainly characterized by rib bending and nodal distortion along with an inward squeeze perpendicular to the pullout direction. The interface friction between the soil and the geogrid develops in a progressive mode, and an elasto‐plastic‐softening characteristic is detected experimentally due to the extensibility of geogrid.
A Car‐Following Model Based on Safety Margin considering ADAS and Driving Experience
Authors: Wang Yugang , Lyu Nengchao
Published: February 2021

Existing studies had shown that advanced driver assistance systems (ADAS) and driver individual characteristics can significantly affect driving behavior. Therefore, it is necessary to consider these factors when building the car‐following model. In this study, we established a car‐following model based on risk homeostasis theory, which uses safety margin (SM) as the risk level quantization parameter. Firstly, three‐way Analysis of Variance (ANOVA) was used to analyze the influencing factors of car‐following behavior. The results showed that ADAS and driving experience have a significant effect on the drivers’ car‐following behavior. Then, according to these two significant factors, the car‐following model was established. The statistical method was used to calibrate the parameter reaction response τ. Other four parameters (SMDL, SMDH, α1, and α2) were calibrated using a classical genetic algorithm, and the effects of ADAS and driving experience in these four parameters were analyzed using T‐test. Finally, the proposed model was compared with the GHR model, and the result showed that the proposed model has a smaller Root Mean Square Error (RMSE) than the GHR model. The proposed model is a method of simulating different driving behaviors that are affected by ADAS and individual characteristics. Considering more driver individual characteristics, such as driving style, is the future research goal.
Serum Levels of 25-Hydroxyvitamin D in Patients with Seborrheic Dermatitis: A Case-Control Study
Authors: Rahimi Siavash , Nemati Negar , Shafaei-Tonekaboni Seyedeh Sareh
Published: February 2021

Several autoimmune papulosquamous skin conditions such as psoriasis, systemic lupus erythematous, and lichen planus have been associated with vitamin D deficiency or correlated with serum vitamin D level. This study was aimed at comparing the 25-hydroxyvitamin D (25(OH)D) status in patients with facial or scalp seborrheic dermatitis with healthy subjects. This case-control study included 289 patients (118 with psoriasis and 171 sex- and age-matched control subjects) from the outpatient clinic of two hospital dermatology departments in the west of Mazandaran province, Iran. All patients and control subjects were studied during one season to avoid seasonal variations in vitamin D levels. Serum mean ± standard deviation of 25(OH)D levels were signiﬁcantly lower in seborrheic dermatitis patients than in control subjects (20.71 ± 8.16 vs. 23.91 ± 7.78,

P

 = 0.007). Serum 25(OH)D levels were negatively associated with the risk of developing seborrheic dermatitis (odds ratio (OR): 0.898, 95% confidence interval (Cl): 0.840–0.960,

P

 = 0.002). Also, vitamin D under 30 ng/ml was associated with OR: 4.22 (95% Cl: 1.077–16.534,

P

 = 0.039) for seborrheic dermatitis. The severity of scalp disease was significantly associated with serum 25(OH)D level (

P

 = 0.003). Cases with severe scalp scores had significantly lower serum 25(OH)D level compared to moderate OR score (

P

 = 0.036). A similar trend was not seen in the facial disease. The 25(OH)D values are signiﬁcantly lower in seborrheic dermatitis patients than in healthy subjects. Furthermore, the scalp disease severity was associated with lower serum 25(OH)D level. Our results may suggest that vitamin D may play a role in the pathogenesis of seborrheic dermatitis.
A Combined Denoising Method for Microseismic Signals from Coal Seam Hydraulic Fracturing: Multithreshold Wavelet Packet Transform and Improved Hilbert‐Huang Transform
Authors: Yu Zhengxing , Wen Jinglin , Zhu Quanjie , Ma Haitao , Feng Yu
Published: February 2021

Coal seam hydraulic fracturing (CSHF) has recently been applied to mitigate frequent regional rockburst risk in deep mines before mining practice, as an effective substitute for conventional labor‐intensive and time‐consuming rockburst prevention measures. Due to the complex nature of CSHF microseismic signals—e.g., nonstationary, transient, and low signal‐to‐noise ratio—conventional denoising methods tend to yield undesirable results that may preclude reliable evaluation of hydraulic fracturing performance using microseismic data. We propose an advanced denoising method MWPT‐IHHT to achieve twice denoising in a fine and adaptive manner. This method combines a multithreshold wavelet packet transform (MWPT) and an improved Hilbert‐Huang transform (IHHT), with each being improved compared to their conventional counterparts. A quantitative comparison using synthetic signals suggests the outperformance of the proposed method over the commonly used denoising methods in suppressing noises in terms of signal‐to‐noise ratio, signal similarity, and energy percentage. The desirable denoising results of two typical real CSHF signals in a CSHF test at Huafeng Coal Mine further demonstrate the applicability and effectiveness of the proposed MWPT‐IHHT method.
Fuzzy Adaptive Variable Structure Control of Second-Order Robotic Manipulators with Dead Zones
Authors: Wang Songyu , Hou Xianmin
Published: February 2021

In this study, with respect to certain second-order robotic systems with dead zones, a fuzzy adaptive variable structure controller (VSC) is implemented. Some suitable adaptive fuzzy systems are used to estimate uncertain functions. Based on Lyapunov stability theorems, parameter adaptive laws are designed, and it is proven that all signals involved will remain bounded and the stability of the controlled system is also guaranteed. Our controller is effective for the system with or without sector nonlinearity. Finally, a simulation example is presented to illustrate the correctness of the theoretical derivation.
Effect of Emulsification on Enhanced Oil Recovery during Surfactant/Polymer Flooding in the Homogeneous and Heterogeneous Porous Media
Authors: Wang Xiaoyan , Zhang Jie , Yuan Guangyu , Wang Wei , Liang Yanbin , Wang Honggang , Li Yiqiang
Published: February 2021

Surfactant polymer (SP) flooding has become an important enhanced oil recovery (EOR) technique for the high-water cut mature oilfield. Emulsification in the SP flooding process is regarded as a powerful mark for the successful application of SP flooding in the filed scale. People believe emulsification plays a positive role in EOR. This paper uses one-dimensional homogenous core flooding experiments and parallel core flooding experiments to examine the effect of emulsification on the oil recoveries in the SP flooding process. 0.3 pore volume (PV) of emulsions which are prepared using ultralow interface intension (IFT) SP solution and crude oil with stirring method was injected into core models to mimic the emulsification process in SP flooding, followed by 0.35 PV of SP flooding to flood emulsions and remaining oil. The other experiment was preformed 0.65 PV of SP flooding as a contrast. We found SP flooding can obviously enhance oil recovery factor by 25% after water flooding in both homogeneous and heterogeneous cores. Compared to SP flooding, emulsification can contribute an additional recovery factor of 3.8% in parallel core flooding experiments. But there is no difference on recoveries in homogenous core flooding experiments. It indicates that the role of emulsification during SP flooding will be more significant for oil recoveries in a heterogeneous reservoir rather than a homogeneous reservoir.
Quantitative Analysis of Colistin‐Resistant Escherichia coli in Retail Meat from Local Vietnamese Markets
Authors: Nguyen Thang N. , Khong Diep T. , Le Ha V. , Tran Hoa T. , Phan Quang N. , Le Huong T. T. , Kawahara Ryuji , Yamamoto Yoshimasa
Published: February 2021

The spread of drug‐resistant bacteria via food has contributed to the dissemination of resistant bacteria among humans. However, the status of food contamination with resistant bacteria, particularly the quantitative level of resistant bacteria in food, has not yet been well elucidated. In this study, the abundance of colistin‐resistant Escherichia coli in meat samples was quantified to understand the origin of the contamination of meat available in local Vietnamese markets. Fifteen samples each of chicken and pork meat purchased from local Vietnamese markets were assessed for the presence of colistin‐resistant E. coli with the mobile colistin resistance gene, mcr. The results showed that 40% (6/15) and 66% (10/15) of the pork and chicken meat samples, respectively, were contaminated with colistin‐resistant E. coli. The median quantitative levels of colistin‐resistant E. coli in the contaminated pork and chicken samples were 1.8 × 104 and 4.2 × 103 CFU/g, respectively. The results of phylogenetic analysis of isolates from a chicken meat sample showed that the contaminated colistin‐resistant E. coli was a mix of multiple phylogenetical clones of bacteria that may have multiplied during sale. This is the first study to quantify the abundance of colistin‐resistant E. coli in meat samples.
Remote Limb Ischemic Postconditioning Protects against Ischemic Stroke via Modulating Microglia/Macrophage Polarization in Mice
Authors: Han Dong , Wang Jue , Wen Lulu , Sun Miao , Liu Hang , Gao Yan
Published: February 2021

Aim. The protection against ischemia/reperfusion injury mediated by remote limb ischemic postconditioning (RIPC) shows great clinical value in ischemic stroke therapy, but the particular mechanism of RIPC remains unclear. Methods. We carried out middle cerebral artery occlusion/reperfusion (MCAO/R) surgery on C57BL/6 male mice. RIPC was generated by 10-minute occlusion followed by the same period of reperfusion of the bilateral hind limb femoral artery and repeated for 3 cycles. Infarct size and neurological score were performed to assess stroke outcomes. Ly6Chi monocytes were quantified in the blood and brain by flow cytometry. Real-time PCR, ELISA, and immunofluorescence were utilized to detect phenotype of proinflammatory M1 and anti-inflammatory M2 microglia/macrophage. Nuclear factor κB (NF-κB) and peroxisome proliferator-activated receptor γ (PPARγ) levels were detected using Western blot. Results. At 24 and 72 h after MCAO, RIPC drastically attenuated infarct size and ameliorated the neurological deficits of mice and facilitated transmigration of Ly6Chi monocytes to the brain postischemia reperfusion. Furthermore, RIPC contributed to increased M2 and reduced M1 microglia/macrophage through inhibiting NF-κB and promoting PPARγ activation. Conclusion. Our results reveal pharmacological effect of RIPC in promoting microglia/macrophage transferring from M1 to M2 phenotype after MCAO/R in mice, which provides theoretical support for the therapeutic effect of RIPC in ischemic stroke.
Personalized Movie Recommendation Method Based on Deep Learning
Authors: Liu Jingdong , Choi Won-Ho , Liu Jun
Published: February 2021

With the rapid development of network technology and entertainment creation, the types of movies have become more and more diverse, which makes users wonder how to choose the type of movies. In order to improve the selection efficiency, recommend Algorithm came into being. Deep learning is a research field that has received extensive attention from scholars in recent years. Due to the characteristics of its deep architecture, deep learning models can learn more complex structures. Therefore, deep learning algorithms in speech recognition, machine translation, image recognition, and other fields have achieved impressive results. This article mainly introduces the research of personalized movie recommendation methods based on deep learning and intends to provide ideas and directions for the research of personalized movie recommendation under deep learning. This paper proposes a research method of personalized movie recommendation methods based on deep learning, including an overview of personalized recommendation and collaborative filtering recommendation algorithms, which are used to conduct research experiments on personalized movie recommendation methods based on deep learning. The experimental results in this paper show that the accuracy of the training set of the Seq2Seq model based on the LSTM recurrent neural network reaches 96.27% and the accuracy of the test set reaches 95.89%, which can be better for personalized movie recommendation.
Behaviour of Textile‐Reinforced Concrete Beams versus Steel‐Reinforced Concrete Beams
Authors: Alrshoudi Fahed
Published: February 2021

There has been a rising interest in utilising textile reinforcement such as carbon tows in constructing concrete components to enhance the performance of conventional reinforced concrete. Textile‐reinforced concrete (TRC) has been used as a construction material mostly as primary reinforcement. However, the structural performance of TRC members has not been investigated in depth. Therefore, to better understand TRC beams’ behaviour under bending load, a widespread experimental investigation was conducted. The results of tensile stress‐strain, load‐deflection, moment‐curvature, and tension stiffening behaviours of TRC beams were associated with conventional steel‐reinforced concrete (SRC) beams. In this study, the four‐point bending and tensile strength tests were performed. The results revealed that, unlike the stress‐strain behaviour observed in steel, textile reinforcement does not exhibit yielding strain. The flexural behaviour of TRC beams shows no similarity to that of SRC beams at postcracking formation. Besides, the moment capacity and tension stiffening of TRC beams were found 56% and 7 times higher than those of SRC beams, respectively. Therefore, in light of these results, it can be said that TRC beams behaviour differs from that of SRC beams.
Orthotic Bracing or Minimally Invasive Surgery? A Summary of 767 Pectus Carinatum Cases for 9 Years
Authors: Shang Ziyin , Hong Chun , Duan Xianlun , Li Xiangyong , Si Yuan
Published: February 2021

Orthotic bracing and minimally invasive surgery are currently the treatment methods for pectus carinatum. We present our experience with the advantages, method selection criteria, and precautions for both treatment methods. A total of 767 pediatric patients (596 boys and 171 girls) with pectus carinatum were retrospectively analyzed. All of them received orthotic bracing, and 108 pediatric patients received minimally invasive surgery, achieving good outcomes. Among the 767 pediatric patients, 644 obtained satisfactory chest appearance through orthotic bracing, with a success rate of 84.0%. Younger pediatric patients had better orthotic outcomes. Among the 123 failure cases, 108 pediatric patients underwent minimally invasive surgery as the treatment. Seventy‐six pediatric patients with simple chondrogladiolar prominence underwent a minimally invasive sternal depression procedure, whereas 32 pediatric patients with complex chondromanubrial prominence underwent surgery. All 108 pediatric patients successfully completed the surgery. The operation time was 112.8 ± 23.5 min, and the average length of hospital stay after the surgery was 7 days. A follow‐up was conducted for at least 3 months and up to 3 years. The orthotic effect was satisfactory. For younger pediatric patients with pectus carinatum, noninvasive orthotic bracing treatment should be considered first. For older pediatric patients, the failure rate of the bracing was higher, and the outcomes were often unsatisfactory. Especially for patients over 15 years old, minimally invasive sternal depression may be the preferred treatment for pectus carinatum.
An Empirical Assessment and Validation of Redundancy Metrics Using Defect Density as Reliability Indicator
Authors: Amara Dalila , Fatnassi Ezzeddine , Ben Arfa Rabai Latifa
Published: February 2021

Software metrics which are language-dependent are proposed as quantitative measures to assess internal quality factors for both method and class levels like cohesion and complexity. The external quality factors like reliability and maintainability are in general predicted using different metrics of internal attributes. Literature review shows a lack of software metrics which are proposed for reliability measurement and prediction. In this context, a suite of four semantic language-independent metrics was proposed by Mili et al. (2014) to assess program redundancy using Shannon entropy measure. The main objective of these metrics is to monitor program reliability. Despite their important purpose, they are manually computed and only theoretically validated. Therefore, this paper aims to assess the redundancy metrics and empirically validate them as significant reliability indicators. As software reliability is an external attribute that cannot be directly evaluated, we employ other measurable quality factors that represent direct reflections of this attribute. Among these factors, defect density is widely used to measure and predict software reliability based on software metrics. Therefore, a linear regression technique is used to show the usefulness of these metrics as significant indicators of software defect density. A quantitative model is then proposed to predict software defect density based on redundancy metrics in order to monitor software reliability.
BDVCM about the Steel Box Girder Reliability Prediction Based on Monitoring Extreme Stresses
Authors: Liu Yuefei , Fan Xueping , Yang Guanghong , Shang Zhipeng , Zhao Xiaoxiong
Published: February 2021

To reasonably predict the steel box girder reliability considering the dynamic dependence among the performance functions corresponding to the failure modes of the multiple monitoring points, this paper firstly adopts the dynamic monitoring extreme stresses of the multiple control points to build the Bayesian Dynamic Vine Copula Model (BDVCM) taking into account the dynamic dependence of the multiple monitoring variables through combining the vine copula technique with Bayesian Dynamic Linear Models (BDLM); secondly, with first‐order second‐moment method and the built BDVCM, the steel box girder reliability, taking into account dynamic dependence among the performance functions corresponding to the failure modes of the multiple monitoring points, is predicted; finally, the monitoring data from the five sections of an existing steel box girder were provided to illustrate the proposed model and approach. The analytical results illustrated that the predicted results, without considering the dynamic nonlinear dependence among the failure modes of the multiple monitoring points, are conservative.
A Comparative Study of Wind Tunnel Tests and Design Codes in Evaluation of Along‐Wind Effects on Towers
Authors: Lee Seungho , Kim Sooyong , Kwon Soon-Duck
Published: February 2021

This study aims to estimate the wind loads acting on a tower structure by comparing and reviewing design codes and the results of wind tunnel tests. To this end, the modal properties of the tower were identified through short‐term on‐site measurements of the Busan Tower in Korea. The wind load acting on the tower was calculated using four design codes: KBC2009 (Korea), ASCE7‐10 (USA), EUROCODE (Europe), and AIJ2004 (Japan). Additionally, force measurement tests and aeroelastic model tests were conducted for comparison. The results obtained indicated that the design wind velocity of each design code differed slightly, reflecting the individual characteristics of each country. The base shear force, base moment, and maximum displacement obtained from each design code were similar to those obtained in the wind tunnel tests. The magnitudes of the base moments and maximum displacements calculated by each design code were in the order of KBC > AIJ ≈ EUROCODE > ASCE7. The overall results indicate that each design code reasonably estimates the wind forces and the responses of the tower and also has an appropriate safety margin. The scatter in the predicted wind loads occurs primarily from the variations in the design wind velocity in the respective design codes.
Sex Differences in the Renal Vascular Responses of AT1 and Mas Receptors in Two-Kidney-One-Clip Hypertension
Authors: Pezeshki Zahra , Nematbakhsh Mehdi
Published: February 2021

Background. The prevalence and severity of hypertension, as well as the activity of the systemic and local renin angiotensin systems (RASs), are gender related, with more symptoms in males than in females. However, the underlying mechanisms are not well understood. In this study, we investigated sex differences in renal vascular responses to angiotensin II (Ang II) administration with and without Ang II type 1 and Mas receptor (AT1R and MasR) antagonists (losartan and A779) in the 2K1C rat model of renovascular hypertension. Methods. Male and female 2K1C rats were divided into 8 experimental groups (4 of each sex) treated with vehicle, losartan, A779, or A779+losartan. Responses of mean arterial pressure (MAP), renal blood flow (RBF), and renal vascular resistance (RVR) to Ang II were determined. Results. In both sexes, the basal MAP, RBF, and RVR were not significantly different between the four groups during the control period. The Ang II administration decreased RBF and increased RVR in a dose-related manner in both sexes pretreated with vehicle or A779 (

P

dose

<
0.0001

), but in vehicle pretreated groups, RBF and RVR responses were different between male and female rats (

P

group

<
0.05

). AT1R blockade increased RBF and decreased RVR responses to Ang II, and no difference between the sexes was detected. Coblockades of AT1R and MasR receptors increased RBF response to Ang II significantly in males alone but not in females (

P

group

=
0.04

). Conclusion. The impact of Ang II on RBF and RVR responses seems to be gender related with a greater effect on males, and this sex difference abolishes by Mas receptor blockade. However, the paradoxical role of dual losartan and A779 may provide the different receptor interaction in RAS between male and female rats.
Factors Affecting Knowledge Management and Its Effect on Organizational Performance: Mediating the Role of Human Capital
Authors: Rezaei Forouzan , Khalilzadeh Mohammad , Soleimani Paria
Published: February 2021

This study aims to investigate and identify the factors affecting the empowerment and implementation of knowledge management in organizations as well as the impact of knowledge management on organizational performance. This study also examines the mediating role of human capital in the relationship between knowledge management and performance of Kabul Steel Plant, which is the largest steel plant in Afghanistan. The research model was developed through the literature review. The initial data were collected through a questionnaire containing 48 questions. Participants were 108 managers and administrative staff of the company. The collected data were analyzed by using the SPSS and SmartPLS software. The hypotheses regarding the impact of strategy and technology on knowledge management were rejected by using correlation analysis and t-test statistic. Finally, the findings showed the positive effects of variables of structure, culture, leadership, and trust on knowledge management in an organization. Also, knowledge management influences the organizational performance, both directly and through the mediating variable of human capital. This research encourages the managers and employees of organizations to use the available organizational resources to implement knowledge management in organizations and improve knowledge management practices and human resources that are the most valuable resources of any organization in order to remain competitive in the markets.
Coincidence of Large Adrenal Cyst and Prominent Hyporeninemic Hyperaldosteronism
Authors: Sakaue Takaaki , Okuno Yosuke , Mukai Kosuke , Fujita Shingo , Kozawa Junji , Nishizawa Hitoshi , Matsuoka Taka-Aki , Iwahashi Hiromi , Norikazu Maeda , Yamazaki Yuto , Sasano Hironobu , Otsuki Michio , Shimomura Iichiro
Published: February 2021

A 67-year-old Japanese woman who had end-stage renal disease was referred to our hospital for kidney transplantation. Abdominal CT revealed a large adrenal mass with inhomogeneity. She had a history of hospitalization for stroke and heart failure and exhibited prominent hyporeninemic hyperaldosteronism. Histological examination of the resected tumor with anti-CYP11B2 antibody indicated that she had a vascular endothelial cyst with primary aldosteronism (PA) due to multiple adrenocortical micronodules. This report implicates the pathological interaction between adrenal vascular cysts and PA-mediated vascular damage of the adrenal vein.
Impact of Negative Symptom Domains and Other Clinical Characteristics on Functional Outcomes in Patients with Schizophrenia
Authors: Okada Hiroki , Hirano Daisuke , Taniguchi Takamichi
Published: February 2021

Negative symptoms of schizophrenia have generally been defined using five factors; however, few studies have examined the relationship between these five factors and functional outcomes. In addition, there is no definitive conclusion regarding the association between negative symptoms and various aspects of functional outcomes (daily living, social, and vocational). This study is aimed at examining the relationship between these five domains of negative symptoms and different functional outcomes. Patients diagnosed with chronic schizophrenia (n = 100) were selected for the evaluation. We used the Brief Negative Symptom Scale to assess negative symptoms, the Brief Psychiatric Rating Scale to assess positive symptoms, the Schizophrenia Cognition Rating Scale to assess cognition, and the Evaluative Beliefs Scale (negative self‐assessment) to assess psychological factors. We analyzed their relative impact on Social Functioning Scale domains using hierarchical multiple regression analysis. Concerning the relationship between daily living and negative symptoms, cognitive function showed the highest association with residential outcomes, such as self‐care and shopping, while avolition appeared to show an additional contribution; however, for recreational outcomes, avolition showed the main association, whereas cognitive function showed no additional contribution. For social outcomes, asociality and negative self‐assessment showed the main associations, while vocational outcomes were determined by both cognitive function and multiple negative symptoms, such as avolition, anhedonia, asociality, and alogia. Since negative symptom domains appear to differentially impact each outcome, specifically daily living outcome, it is important to evaluate the residential outcomes and recreational outcomes separately. Overall, the present study points to the importance of formulating psychosocial treatment strategies specific for each type of preferred outcome in patients with schizophrenia.
The Specific and Nonspecific Effects of Tai Chi and Its Possible Central Responses: A Protocol of Neuroimaging Study
Authors: Liu Tianyu , Teng Yuke , Yang Sha , Guo Yuyi , Yin Tao , Chen Jingwen , Ying Rongtao , He Zhaoxuan , Yu Shuguang , Wu Jianwei , Zeng Fang
Published: February 2021

Tai Chi has been proven to be a safe and effective assistant therapy for healthcare and disease treatment. However, whether the adjuvant therapeutic effect of Tai Chi is general or disease-oriented remains uncertain. This trial focuses on exploring the specific and nonspecific effects of Tai Chi and its potential central responses. The results will deepen our understanding of the characteristics of Tai Chi exercise for adjuvant therapeutic effects and promote its application in the clinic. In this neuroimaging trial, 40 functional constipation (FC) patients and 40 healthy subjects (HS) will be recruited and will receive 10 weeks of Tai Chi exercise. The motor function, respiratory function, stool-related symptoms, quality of life, and emotional state of the participants will be evaluated at the baseline, the 5-week Tai Chi practice, and the end of practice. The potential changes in the heart rate variability and the cerebral function will be recorded by the 24 h dynamic electrocardiogram at the baseline and the functional magnetic resonance imaging at the end of practice. The possible correlations among the clinical variables, the heart rate variability, and the cerebral activity alterations in FC patients and HS will be analyzed. The healthcare and therapeutic effects of Tai Chi exercise might consist of the specific and nonspecific effects. This study provides not only a new perspective for understanding Tai Chi but also a new approach for investigating the mind-body exercise. This trial was registered in the Chinese Clinical Trial Registry (http://www.chictr.org.cn/showproj.aspx?proj=33243) on 28 November 2018 (registration number: ChiCTR1800019781; protocol version number: V1.0). This trial is currently in the stage of recruiting patients. The first patient was included on 1 December 2018. To date, 18 FC patients and 20 HS have been included. Recruitment will be completed in December 2020.
Análise da qualidade de serviços turísticos na Fortaleza de São José da Ponta Grossa – Florianópolis, utilizando o TOURQUAL
Authors: Mondo Tiago Savi , Soares Maria Helena Alemany , Leite Fabiana Calçada de Lamare , Tonera Roberto
Published: February 2021

O turismo de patrimônio tem se consolidado como um segmento em destaque no escopo de oferta de produtos turísticos. Tornar o atrativo competitivo se torna um desafio para os seus gestores e a oferta de um serviço turístico de qualidade auxilia na construção de valor e imagem positivas e consequente desenvolvimento do negócio. O objetivo dessa pesquisa é analisar a percepção de turistas com relação a qualidade de serviços turísticos oferecida na Fortaleza de São José da Ponta Grossa em Florianópolis – SC. Para tanto, realizou-se uma pesquisa aplicada, quantitativa, de campo. O Instrumento foi o questionário fechado baseado no modelo Tourqual. Os dados foram coletados de Maio a Novembro de 2019. A amostra foi composta por 398 turistas, considerada não probabilística por conveniência. Os dados foram analisados por meio de estatística descritiva, teste de normalidade, regressão linear múltipla e correlação de Spearman no SPSS 22. Os principais resultados indicam um nível de satisfação de 9,55 (máximo 10) e uma média dos indicadores de qualidade de 8,48. Os melhores indicadores para os turistas foram: Beleza no Atrativo, Fuga da Rotina do Turista/Novas experiências e Serviço do Guia ao visitante. Enquanto os piores avaliados foram Acessibilidade, Tecnologia e Banheiros acessíveis. Ao aplicar o modelo de regressão linear múltipla encontrou-se que 96,1% da variância dos indicadores de qualidade explica a variância do constructo satisfação do turista, demonstrando que a qualidade é realmente antecedente causal da satisfação e que a gestão dos indicadores leva ao desenvolvimento do atrativo como produto turístico.
Um relato de experiência do Projeto Elas SobreOTatame: impactos de um ciberativismo feminista
Authors: Assis Ingrid Pereira de , Betti Juliana Gobbi , Abreu Larissa Silva , Silva Joceline Conrado da
Published: February 2021

O Elas SobreOTatame é um projeto desenvolvido sob coordenação das mulheres do portal maranhense SobreOTatame (SOT), que trabalha temas a partir de um olhar feminista, produzindo conteúdos jornalísticos e eventos em ciclos temáticos, com a participação de profissionais especialistas no tema debatido. Este relato de experiência foi produzido a partir dos resultados de uma pesquisa realizada com as participantes dos eventos ocorridos em 2019, cujo objetivo foi compreender os impactos do projeto na vida dessas mulheres. Foi aplicada uma entrevista semiestruturada, tendo como direcionamento a compreensão da emancipação, autonomia e formação de conhecimento acerca das temáticas abordadas. Este relato de experiência traz os resultados apreendidos nesta pesquisa, visando contribuir para a formação e desenvolvimento de iniciativas comunicacionais de fortalecimento da mulher frente a uma sociedade desigual.