bluuebunny/crossref_metadata_2025 huggingface dataset:
Cardiopulmonary exercise testing for heart failure: pathophysiology and predictive markers
Authors: Buber Jonathan , Robertson H Thomas
Published: April 2022

Despite the numerous recent advancements in therapy, heart failure (HF) remains a principle cause of both morbidity and mortality. HF with preserved ejection fraction (HFpEF), a condition that shares the prevalence and adverse outcomes of HF with reduced ejection fraction, remains poorly recognised in its initial manifestations. Cardiopulmonary exercise testing (CPET), defined as a progressive work exercise test that includes non-invasive continuous measurement of cardiovascular and respiratory parameters, provides a reliable mode to evaluate for early features and for the assessment of prognostic features of both forms of HF. While CPET measurements are standard of care for advanced HF and transplant programmes, they merit a broader clinical application in the early diagnosis and assessment of patients with HFpEF. In this review, we provide an overview of the pathophysiology of exercise intolerance in HF and discuss key findings in CPETs used to evaluate both severity of impairment and the prognostic implications.
Bronchodilatory Effect of Higenamine as Antiallergic Asthma Treatment
Authors: Du Jing , Mehrabi Nasab Entezar , Athari Seyyed Shamsadin , Qian Linlin
Published: April 2022

Asthma is a complex airway disease that affects more than 350 million humans worldwide. Allergic asthma symptoms are induced by Th2 immune response with the release of cytokines and allegro-inflammatory mediators that amplify the inflammatory response, airway hyper-responsiveness (AHR) and hyperproduction of mucus. Higenamine, as a chemical compound, is a β2 adrenoreceptor agonist and can be used as bronchodilator in allergic asthma.

BALB/c mice were allocated in four groups and then allergic asthma was induced in three groups. One of the asthmatic groups was treated with albuterol and other one was treated with higenamine. At least, methacholine challenge to determine the AHR, measurement of cytokines, total immunoglobulin E (IgE), LTB4 and LTC4 levels, evaluation of gene expression of Muc5ac, Muc5b, Agr2 and Arg1, and histopathological study were done.

Higenamine treatment reduced AHR, interleukin (IL)-4, IL-13 levels, mRNA expression of MUC5ac, MUC5b, Arg1 and Agr2, goblet cell hyperplasia and mucus hypersecretion. Higenamine had no significant effect on IL-5, interferon-γ (INF-γ), IgE, LTB4, LTC4 levels and eosinophilic inflammation in lung tissue.

Higenamine treatment controls asthma acute attack and breathlessness and can be used as asthma treatment with control of AHR and decrease of airflow obstruction and mucus hypersecretion and had allegro-immune-regulatory effect. But higenamine treatment had no notable effect on the inflammation and inflammatory factors.
Uncovering the size of the illegal corporate service provider industry in the Netherlands: a network approach
Authors: Garcia-Bernardo Javier , Witteman Joost , Vlaanderen Marilou
Published: April 2022

Economic crimes such as money laundering, terrorism financing, tax evasion or corruption almost invariably involve the use of a corporate entity. Such entities are regularly incorporated and managed by corporate services providers (CSPs). Given this potential for enabling economic crime, the CSP industry in the Netherlands is heavily regulated and CSPs require a license to operate. Operating without a licence is illegal. In this paper, we estimate the size of the illegal CSP sector in the Netherlands. For this, we develop a classification method to detect potentially illegal CSPs based on their similarity with licensed CSPs. Similarity is computed based on their position within the network of directors, companies and addresses, and the characteristics of such entities. We manually annotate a sample of the potential illegal CSPs and estimate that illegal CSPs constitute 31–51% of the total number of CSPs and manage 19–27% of all companies managed by CSPs. Our analysis provides a tool to regulators to improve detection and prevention of economic crime, and can be extended to the estimation of other illegal activities.
High-temperature adhesive properties of CF/PEKK composites applied fusion bonding and adhesive bonding
Authors: Park Seong-Jae , Park Ye-Rim , Park Soo-Jeong , Kim Yun-Hae
Published: April 2022

The chemical bonding of substrate and adhesive occurs in thermoplastic adhesive bonding, and the molecular deformation caused by the difference in chemical bonding affects the adhesive properties. Therefore, it is essential to investigate the correlation between the molecular deformation of interphase and the strength change behavior. As adhesive bonding involves the combination of two materials with different coefficients of thermal expansion, it is important to analyze the behavior at high temperatures. Therefore, to determine the effects of the molecular deformation of the interphase caused by differences in the adhesive type on the high-temperature performance when adhesive bonding is applied to thermoplastic composites, fusion and adhesive bonding were applied to carbon fiber/polyetherketoneketone thermoplastic composites. The lap shear strength test was conducted at three different temperatures to evaluate the adhesive performances. Scanning electron microscopy was used to determine the fracture mode and the molecular deformation of the interphase was analyzed by Fourier transform infrared spectroscopy. Temperature does not affect the strength of fusion bonded composites. When polyetheretherketone is used as an adhesive, the strength decreases as the temperature increases. When polyetherimide is used as an adhesive, the strength first increases at [Formula: see text]C and then decreases at [Formula: see text]C. The amount of C–O–C and C=C bond formation, diphenyl ketone group, and imide carbonyl group in the interphase followed the same trend as the strength.
Geography of Legendrian knot mosaics
Authors: Pezzimenti Samantha , Pandey Abhinav
Published: April 2022

In this paper, mosaic tiles have been used to build knots and define invariants since they were introduced by Lomonaco and Kauffman to describe quantum knots. In this paper, we propose a modified set of tiles to describe the front projections of Legendrian knots. We explore the effect of stabilization on the mosaic number of a Legendrian knot by defining and classifying “two-cell” stabilizations. Inspired by a construction of Ludwig et al. in 2013, we provide an infinite family of Legendrian unknots whose mosaic numbers are realized only in non-reduced projections. Finally, we provide a census of known mosaic numbers for Legendrian unknots and trefoils.
ANALYSIS OF SiC GRINDING WHEEL WEAR AND SURFACE ROUGHNESS IN MACHINING OF Al2O3 ADVANCED CERAMIC USING REGRESSION MODEL
Authors: KANAKARAJAN P. , MOGANAPRIYA C. , RAJASEKAR R. , SUNDARAM S. , SYED THASTHAGIR M. , SOUNDARARAJAN S. , MANU BARATH K.
Published: April 2022

Presently, there are more new kinds of requirements for the production of advanced ceramic elements in the engineering field. These ceramic elements are to be machined for a better surface roughness value. Surface roughness of the machined elements is one of the main machining characteristics which play a vital role in determining the high quality of advanced ceramic elements in engineering. In this work, some machining tests were done on the advanced aluminum oxide (Al2O[Formula: see text] ceramic work material using a silicon carbide (SiC) grinding wheel under different process parameters. A parametric analytical model was developed using the method of regression analysis by taking into account of four process parameters, such as depth of cut, feed, grain size and spindle speed. The effectiveness of the model is evaluated based on the comparison of experimental results with the regression analysis. The predicted values of surface roughness ([Formula: see text] and wheel wear ([Formula: see text] with minimum average error are in line to the results of the acquired experiment.
Electromagnetic-gravitational perturbations of Kerr–Newman spacetime: The Teukolsky and Regge–Wheeler equations
Authors: Giorgi Elena
Published: April 2022

We derive the equations governing the linear stability of Kerr–Newman spacetime to coupled electromagnetic-gravitational perturbations. The equations generalize the celebrated Teukolsky equation for curvature perturbations of Kerr, and the Regge–Wheeler equation for metric perturbations of Reissner–Nordström. Because of the “apparent indissolubility of the coupling between the spin-1 and spin-2 fields”, as put by Chandrasekhar, the stability of Kerr–Newman spacetime cannot be obtained through standard decomposition in modes. Due to the impossibility to decouple the modes of the gravitational and electromagnetic fields, the equations governing the linear stability of Kerr–Newman have not been previously derived. Using a tensorial approach that was applied to Kerr, we produce a set of generalized Regge–Wheeler equations for perturbations of Kerr–Newman, which are suitable for the study of linearized stability by physical space methods. The physical space analysis overcomes the issue of coupling of spin-1 and spin-2 fields and represents the first step towards an analytical proof of the stability of the Kerr–Newman black hole.
Linear and orbital stability analysis for solitary-wave solutions of variable-coefficient scalar-field equations
Authors: Alammari Mashael , Snelson Stanley
Published: April 2022

We study general semilinear scalar-field equations on the real line with variable coefficients in the linear terms. These coefficients are uniformly small, but slowly decaying, perturbations of a constant-coefficient operator. We are motivated by the question of how these perturbations of the equation may change the stability properties of kink solutions (one-dimensional topological solitons). We prove existence of a stationary kink solution in our setting, and perform a detailed spectral analysis of the corresponding linearized operator, based on perturbing the linearized operator around the constant-coefficient kink. We derive a formula that allows us to check whether a discrete eigenvalue emerges from the essential spectrum under this perturbation. Known examples suggest that this extra eigenvalue may have an important influence on the long-time dynamics in a neighborhood of the kink. We also establish orbital stability of solitary-wave solutions in the variable-coefficient regime, despite the possible presence of negative eigenvalues in the linearization.
Consumption Optimization in G7 Countries: Evidence of Heterogeneous Asymmetry in Income and Price Differentials
Authors: Uche Emmanuel , Chang Bisharat Hussain , Gohar Raheel
Published: April 2022

The lack of comprehensive empirical narratives about the effects of income and price differentials, as well as possible distributional asymmetries on consumption in G7 countries, compelled this study by using both ARDL and Quantile ARDL models. NARDL results indicate that positive shocks in income have significant and positive effects on consumption in all countries. Moreover, evidence from the Quantile ARDL model indicates that positive and significant impacts were momentary except at the 95th quantile of consumption distributions in Canada. Furthermore, price variations negatively affected consumption in all G7 countries and across all distributions, with evidence of panic buying in Italy, the US and at the 5th quantile in Japan. Meanwhile, there is evidence of asymmetric effects from income and price variations on consumption in all G7 countries, whereas the influence of income variations on consumption is heterogeneous in Canada. Moreover, the asymmetric effects of price differentials were consistent across all the distributions in all the countries. Overall, to ensure consumption optimization and by extension, economic growth, differentiated policies to respond to income and price variations at all times are of the essence.
A Comparison of Outcomes of Reconstruction of Palmar versus Dorsal Defects of the Thumb Using a First Dorsal Metacarpal Artery Flap with a Cutaneous Bridge Segment
Authors: AGGAG Ahmad Mohammad , ABOEL-HASAN Waleed Saber , ABDEL-AAL Mohamed
Published: April 2022

Background: The aim of this study is to compare outcomes of reconstruction of palmar versus dorsal defects of the thumb using the first dorsal metacarpal artery (FDMA) flap with a cutaneous bridge segment.

Methods: All FDMA flaps done at our centre for reconstruction of traumatic thumb defects in the period from November 2017 to May 2019 were included in this study. Data with regard to the patient, the injury and the flap were recorded. The outcome measures recorded include flap survival, complications, duration of follow-up, static two-point discrimination (2-PD), cortical reorientation, paresthesia at the flap and donor site, pain at the flap and donor site, Kapandji score and aesthetic outcome.

Results: The study included 11 patients with an average age of 35 years. All patients were men, and the injury involved the dominant thumb in seven patients. There were five dorsal defects and six palmar defects, and the average defect size was 7.22 sq cm. All flaps survived and there were no complications. The mean follow-up period was 15.2 months. The mean static 2-PD was 9.35 mm, cortical reorientation was complete in six patients, paresthesia score at the flap was 0.27 and at the donor site was 0.36. The visual analogue scale (VAS) pain for the flap was 1.09 and for the donor site was 1.27. The average Kapandji score was 8.64 and patients rated the aesthetic outcome of the flap at 8 and of the donor site at 7.36. There were no differences in outcomes between palmar and dorsal defects except for the aesthetic outcome of the flap that was rated better for dorsal defects.

Conclusion: The FDMA flap designed with a cutaneous bridge segment provided reliable, single-stage reconstruction of dorsal and palmar thumb defects with good outcomes. Patients rated the aesthetic outcome of flaps used for dorsal reconstruction higher.

Level of evidence: Level IV (Therapeutic)
A Runtime Resource Management and Provisioning Middleware for Fog Computing Infrastructures
Authors: Miele Antonio , Zárate Henry , Cassano Luca , Bolchini Cristiana , Ortiz Jorge E.
Published: April 2022

The pervasiveness and growing processing capabilities of mobile and embedded systems have enabled the widespread diffusion of the Fog Computing paradigm in the Internet of Things scenario, where computing is directly performed at the edges of the networked infrastructure in distributed cyber-physical systems. This scenario is characterized by a highly dynamic workload and architecture in which applications enter and leave the system, as well as nodes and connections. This article proposes a runtime resource management and provisioning middleware for the dynamic distribution of the applications on the processing resources. The proposed middleware consists of a two-level hierarchy: (i) a global Fog Orchestrator monitoring the architecture status and (ii) a Local Agent on each node, performing a fine-grain tuning of its resources. The co-operation between these components allows one to dynamically adapt and exploit the fine-grain nodes view for fulfilling the defined system-level goals, for example, minimizing power consumption while meeting Quality of Service requirements such as application throughput. This hierarchical architecture and the adopted policies offer a unified optimization strategy that is unique with regard to existing approaches that typically focus on a single aspect of resource management at runtime. A middleware prototype is presented and experimentally evaluated in a Smart Building case study.
fgSpMSpV: A Fine-grained Parallel SpMSpV Framework on HPC Platforms
Authors: Chen Yuedan , Xiao Guoqing , Li Kenli , Piccialli Francesco , Zomaya Albert Y.
Published: April 2022

Sparse matrix-sparse vector (SpMSpV) multiplication is one of the fundamental and important operations in many high-performance scientific and engineering applications. The inherent irregularity and poor data locality lead to two main challenges to scaling SpMSpV over high-performance computing (HPC) systems: (i) a large amount of redundant data limits the utilization of bandwidth and parallel resources; (ii) the irregular access pattern limits the exploitation of computing resources. This paper proposes a fine-grained parallel SpMSpV (fgSpMSpV) framework on Sunway TaihuLight supercomputer to alleviate the challenges for large-scale real-world applications. First,fgSpMSpVadopts an MPI\( + \)OpenMP\( +X \)parallelization model to exploit the multi-stage and hybrid parallelism of heterogeneous HPC architectures and accelerate both pre-/post-processing and main SpMSpV computation. Second,fgSpMSpVutilizes an adaptive parallel execution to reduce the pre-processing, adapt to the parallelism and memory hierarchy of the Sunway system, while still tame redundant and random memory accesses in SpMSpV, including a set of techniques like the fine-grained partitioner, re-collection method, and Compressed Sparse Column Vector (CSCV) matrix format. Third,fgSpMSpVuses several optimization techniques to further utilize the computing resources.fgSpMSpVon the Sunway TaihuLight gains a noticeable performance improvement from the key optimization techniques with various sparsity of the input. Additionally,fgSpMSpVis implemented on an NVIDIA Tesal P100 GPU and applied to the breath-first-search (BFS) application.fgSpMSpVon a P100 GPU obtains the speedup of up to\( 134.38\times \)over the state-of-the-art SpMSpV algorithms, and the BFS application usingfgSpMSpVachieves the speedup of up to\( 21.68\times \)over the state-of-the-arts.
A Task-oriented Chatbot Based on LSTM and Reinforcement Learning
Authors: Hsueh Yu-Ling , Chou Tai-Liang
Published: April 2022

Thanks to the advancements in deep learning, chatbots are widely used in messaging applications. Undoubtedly, a chatbot is a new way of interaction between humans and machines. However, most of the chatbots act as a simple question answering system that responds with formulated answers. Traditional conversational chatbots usually adopt a retrieval-based model that requires a large amount of conversational data for retrieving various intents. Hence, training a chatbot model that uses low-resource conversational data to generate more diverse dialogues is desirable. We propose a method to build a task-oriented chatbot using a sentence generation model that generates sequences based on the generative adversarial network. The architecture of our model contains a generator that generates a diverse sentence and a discriminator that judges the sentences by comparing the generated and the ground-truth sentences. In the generator, we combine the attention model with the sequence-to-sequence model using hierarchical long short-term memory to extract sentence information. For the discriminator, our reward mechanism assigns low rewards for repeated sentences and high rewards for diverse sentences. Extensive experiments are presented to demonstrate the utility of our model that generates more diverse and information-rich sentences than those of the existing approaches.
Analytical Modelling of Material Removal in Copper Chemical Mechanical Polishing Incorporating the Scratch Hardness of the Passivated Layer on Copper Thin Film Wafer
Authors: Sharma Mohit , Chen Chao-Chang A.
Published: April 2022

Chemical mechanical polishing (CMP) is the most crucial process for semiconductor fabrication and the scale of its application is broadening year by year. And understanding the varied mechanical interaction at pad-wafer contact as well as chemical alteration of the wafer surface is essential to comprehend the mechanism of material removal in the CMP process. In this study, an analytical material removal model is established as a function of polishing pad properties and scratch hardness of copper thin film wafer in CMP slurry environment. The model incorporates both, the mechanical material wear of chemically altered surface and, the chemical dissolution of copper based on corrosion theory. The contact between the polishing pad, wafer and abrasive is analysed and, in addition, the effect of the polishing pad and wafer properties on material removal is simulated. The model predicted MRR is compared to the copper CMP experiment MRR. This study establishes a strong correlation between the experimentally measured polishing pad and wafer properties and the material removal within the nanoscale contact model assumptions. The model provides a theoretical and experimental framework for optimizing the CMP process parameters, which can be employed to develop a simulator to analyze the advanced node copper CMP process
Room-Temperature Nonreciprocal Charge Transport in an InAs-Based Rashba Channel
Authors: Ahn Jeong Ung , Han Ki Hyuk , Kim Seong Been , Lee OukJae , Kim Hyung-jun , Koo Hyun Cheol
Published: April 2022

Nonreciprocal charge transport is observed in a non-centrosymmetric system without a ferromagnetic layer. To observe the nonreciprocity of the Rashba system, an InAs-based two-dimensional electron gas channel is utilized and the angular dependent harmonic Hall measurement is performed. From the amplitude of the curve, a nonreciprocal coefficient of 1.36 A−1T−1 is extracted at 1.9 K. While the extracted value of the nonreciprocal coefficient decreases down to 0.44 A−1T−1 at 300 K, we can clearly observe the nonreciprocal charge transport at room temperature. In addition, the independent transport measurements clarify that the amplitude of nonreciprocal coefficient is closely connected with the strength of the Rashba effect.
Hypoxia-inducible factor protects against acute kidney injury via the Wnt/β-catenin signaling pathway
Authors: Xu Zhi-Hui , Wang Chang , He Yi-Xin , Mao Xin-Yue , Zhang Man-Zhu , Hou Yan-Pei , Li Bing
Published: April 2022

We investigated the role of hypoxia-inducible factor (HIF) in acute kidney injury in vivo and in vitro. Expression of HIF in the adaptive repair group was more rapid and sufficient than that in the maladaptive repair group during the early repair phase. HK-2 and EA.hy926 cells treated with hypoxia/reoxygenation were used to elucidate the cross talk between HIF and the Wnt/β-catenin signaling pathway by which HIF played a renoprotective role in acute kidney injury.
Prognostic Significance of Neutrophil/Lymphocytes Ratio (NLR) in Predicting Recurrence of Cervical Dysplasia
Authors: Origoni Massimo , Cantatore Francesco , Candotti Giorgio , Candiani Massimo
Published: April 2022

Objective. The objective of the present study was to investigate the potential prognostic role of neutrophil‐lymphocyte ratio (NLR) in comparison with known parameters of prediction for the detection of recurrences of cervical intraepithelial neoplasia (CIN) after treatment. Methods. We retrospectively evaluated patients who underwent surgical treatment for CIN2, CIN3, and carcinoma in situ (CIN2+) between 2010 and 2019. NLR was recorded before surgery, and the follow‐up records of patients were analyzed. Cases were splitted into two subgroups according to baseline NLR—low‐NLR for <2 and high‐NLR for ≥2 values of the index—and correlated with recurrences. Results. 428 cases fulfilled the criteria and were included in the study. Recurrence rate in patients with NLR <2.0 and NLR ≥2.0 was 15.2% and 27.3%, respectively, being the odd ratio for recurrence significantly higher in patients with NLR ≥2 (OR = 2.09; 95% CI 1.28‐3.41; p = 0.003). A highly significant statistical difference in recurrence rate was demonstrated, in both univariate and multivariate, for surgical margins, follow‐up HPV‐DNA status, and NLR values. Conclusion. Preoperative NLR categorization is a strong independent prognostic factor for recurrences after surgical excision of CIN. NLR evaluation is a simple, reproducible, and cost‐effective clinical instrument that could optimally be introduced in clinical practice in every setting.
Machine Vision-Based Object Detection Strategy for Weld Area
Authors: Liu Chenhua , Chen Shen , Huang Jiqiang
Published: April 2022

For the noisy industrial environment, the welded parts will have different types of defects in the weld area during the welding process, which need to be polished, and there are disadvantages such as low efficiency and high labor intensity when polishing manually; machine vision is used to automate the polishing and achieve continuous and efficient work. In this study, the Faster R-CNN object detection algorithm of two-stage is used to investigate the relationship between flops and the number of network parameters on the model by using a V-shaped welded thick plate as the research object and establishing the workpiece dataset with different lighting and angles, using six regional candidate networks for migration learning, comparing the convergence degree of different Batch and Mini-Batch on the model, and exploring the relationship between flops and the number of network parameters on the model. The optimal learning rate is selected for training to form a weld area object detection network based on the weld plate workpiece under few samples. The study shows that the VGG16 model is the best in weld seam area recognition with 91.68% average accuracy and 25.02 ms average detection time in the validation set, which can effectively identify weld seam areas in various industrial environments and provide location information for subsequent automatic grinding of robotic arms.
Bond Slip Behavior of Grout-Filled Concrete Members with Different Interface Materials
Authors: Zhu Eryu , Li Teng , Liu Lei , Zhu Li , Tian Yuanyuan
Published: April 2022

The present paper investigates the relationship between pressure (bond stress) and displacement at the failure load for different materials through testing and modeling. First, single-end tests were conducted on prebonded stressed and perforated concrete specimens with corrugated plastic, metal, and rubber extractive pipes. These tests reveal that corrugated plastic pipes provide good bonding performance with concrete and grout. Hence, they can be applied in the hole-forming process of posttensioned prestressed bonded structures, along with corrugated metal pipes and rubber extractive pipes. Based on the experimental observations and results, a theoretical approach for applying corrugated plastic pipes in projects such as China’s high-speed rail has finally been demonstrated.
Analysis of the Impact of Ecological Governance Capacity on the Enterprise Capital Configuration Efficiency: Mediating Effects Based on Social Responsibility
Authors: Li Hua , Yan Huining , Sun Qiubai
Published: April 2022

Improving the ecological governance capacity is necessary in order to achieve high-quality economic development. As the main part of the promotion of social and economic development, enterprises’ inefficient investment (overinvestment and underinvestment) has impeded the development of the economy chronically and steadily. Therefore, improving the efficiency of enterprises’ capital allocation has become a problem that needs to be studied and solved urgently. This article mainly studies the influence of ecological governance capability on the enterprise capital configuration efficiency and mechanism of action by using Shanghai and Shenzhen A-share listed companies data from 2011 to 2017. The study found that ecological governance capability can remarkably strengthen the corporate capital allocation efficiency, and it can do so by improving corporate social responsibility (CSR). This conclusion is supported after the replacement of robustness tests, for example, the enterprise capital configuration efficiency and the measurement indicators of CSR. The heterogeneity test indicates that the ecological governance can obviously forward the enterprise capital configuration efficiency in state-owned enterprises and less-polluting enterprises. These findings can provide some theoretical support to the mechanism of ecological governance capacity effect on corporate capital allocation efficiency from the aspect of corporate social responsibility.
Correlation of PD-L1 Expression with Clinicopathological and Genomic Features in Chinese Non-Small-Cell Lung Cancer
Authors: Li Yue , Li Chong , Jiang Ya , Han Xue , Liu Sisi , Xu Xiuxiu , Tang Wanxiangfu , Ou Qiuxiang , Bao Hua , Wu Xue , Shao Yang , Xing Minyan , Zhang Yixiang , Wang Yuezhen
Published: April 2022

Programmed cell death 1 ligand 1 (PD-L1) has been approved as predictive biomarker for non-small-cell lung cancer (NSCLC) patients treated with PD-(L)1 blockade therapy. The clinical/genomic features associated with PD-L1 are not well studied. Genomic profiling of tumor biopsies from 883 Chinese NSCLC patients was performed by targeted next-generation sequencing. Immunohistochemical analysis was conducted to evaluate PD-L1 expression levels using antibodies Dako 22C3 and 28-8, respectively. Our study showed distinct correlation between PD-L1 expression and clinical/genomic characteristics when using different PD-L1 antibodies and in different histological subtypes including adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively. PD-L1 high expression (22C3) was associated with male and lymph node metastasis only in ADC patients. Furthermore, mutations of TP53 and KRAS, KIF5B-RET fusion, copy number gains of PD-L1 and PD-L2, and arm-level amplifications of chr.12p were significantly associated with PD-L1 positive status in ADC patients. For SCC patients, the gain of EGFR and MDM2 and loss of PTPRD were negatively associated with PD-L1 expression. We also compared our results with other studies and found conflicting results presumably because of the multiplicity of antibody clones and platforms, the difference of cutoffs for assigning PD-L1 expression levels, and the variation in study populations. Our study can help to understand the utility and validity of PD-L1 as biomarker of response to immune checkpoint inhibitors.
BIM Model Management for BIM‐Based Facility Management in Buildings
Authors: Lin Yu Cheng , Hsu Ya Ting , Hu Hsin Tzu
Published: April 2022

Building information modeling (BIM) has recently gained popularity in the architecture, engineering, and construction industry. Specifically, BIM has been applied in facilities management (FM). However, FM‐integrated BIM and MM‐integrated BIM are likely to fail when BIM‐FM models are not effectively updated or maintained. Thus, it is critical to focus on the management of BIM‐FM models during the operation stage of buildings. While several researchers have examined BIM applications and system developments in the context of FM, there is a dearth of research on BIM management, particularly in the operation stage of sustainable buildings. Thus, an approach for BIM‐FM models management is herein proposed for building projects. A BIM‐FM models management (BFMM) system for owners during the operation stage was developed to ensure effective implementation for the management of BIM‐FM models. Using a building in Taiwan as a case study, this study discussed and evaluated the effectiveness of the proposed BFMM system. The results reveal that the BFMM system significantly increases the efficiency of BIM‐FM model management. The results of this study can provide a useful reference for those interested in adopting BIM to manage building project facilities. This study concludes by presenting the advantages and limitations of BIM‐FM models as well as suggestions for future applications.
High-Resolution Ex-Vivo Imaging of Retina with a Laptop-Based Portable Endoscope
Authors: Ge Yanni , Jin Kai , Wang Yao , Xu Yufeng , Lu Haitong , Ye Juan
Published: April 2022

Purpose. Ophthalmic endoscopy is useful in vitreoretinal surgery with opaque anterior segments or anatomically challenging structures. However, standard ophthalmic endoscopy devices are usually large and costly. Thus, the development of a portable endoscope is necessary. Methods. The portable endoscope consisted of a probe, an illumination system, a high-resolution camera module, and a universal serial bus (USB). It was connected to a laptop and applied for intraocular imaging of porcine eyes in vitro. Basic parameters and pictures of the same tissue target were compared with those of the standard Endo Optiks E4 system. Results. The retinal images were displayed on the laptop screen, which clearly showed the overall appearance of the central and peripheral retina, and the details of the retinal vasculature and ciliary body. Compared with a standard endoscope, our portable endoscope is smaller and more affordable. It can be taken anywhere for intraocular imaging and vitreoretinal surgery. Conclusion. A laptop-based portable endoscope is a promising device in vitreoretinal surgery. It provides high-resolution images of intraocular tissues that should make a noticeable difference in intraocular surgery with disordered anterior segments. With its portability and high-resolution imaging, it may promote the application of endoscopes in ophthalmology.
HGVul: A Code Vulnerability Detection Method Based on Heterogeneous Source-Level Intermediate Representation
Authors: Song Zihua , Wang Junfeng , Liu Shengli , Fang Zhiyang , Yang Kaiyuan
Published: April 2022

Vulnerability detection on source code can prevent the risk of cyber-attacks as early as possible. However, lacking fine-grained analysis of the code has rendered the existing solutions still suffering from low performance; besides, the explosive growth of open-source projects has dramatically increased the complexity and diversity of the source code. This paper presents HGVul, a code vulnerability detection method based on heterogeneous intermediate representation of source code. The key of the proposed method is the fine-grained handling on heterogeneous source-level intermediate representation (SIR) without expert knowledge. It first extracts graph SIR of code with multiple syntactic-semantic information. Then, HGVul splits the SIR into different subgraphs according to various semantic relations, which are used to obtain semantic information conveyed by different types of edges. Next, a graph neural network with attention operations is deployed on each subgraph to learn representation, which captures the subtle effects from node neighbors on their representation. Finally, the learned code feature representations are utilized to perform vulnerability detection. Experiments are conducted on multiple datasets. The F1 of HGVul reaches 96.1% on the sample-balanced Big-Vul-VP dataset and 88.3% on the unbalanced Big-Vul dataset. Further experiments on actual open-source project datasets prove the better performance of HGVul.
Correlation between Serum Oxidative Stress Level and Serum Uric Acid and Prognosis in Patients with Hepatitis B-Related Liver Cancer before Operation
Authors: Yu Maowen , Zhang Chaozhu , Tang Hongbo , Xiao Chaohui
Published: April 2022

Aiming to explore the correlation between preoperative serum oxidative stress level and serum uric acid and prognosis of hepatitis B-related liver cancer, the clinical data of 712 patients with hepatitis B-related liver cancer from January 2019 to December 2020 were retrospectively analyzed. By using the receiver operating curve, the optimal critical values of preoperative superoxide dismutase (SOD), malondialdehyde (MDA), and serum uric acid (SUA) are determined. The single-factor and multifactor Cox models are applied to screen out the suspicious factors affecting the prognosis of patients with hepatitis B-related liver cancer. According to the survival status of patients, the optimal thresholds of SOD, MDA, and SUA before operation were 58.055/mL, 10.825 nmol/L, and 312.77 nmol/L, respectively. The results of univariate analysis show that the prognosis of patients is significantly correlated with preoperative SOD, MDA, and SUA levels and TNM staging

P
<
0.05

. Additionally, multivariate analysis demonstrates that preoperative SOD < 58.055 U/mL and SUA ≥ 312.770 mmol/L and TNM stage III-IV are independent risk factors for postoperative prognosis

P
<
0.05

. Our study suggests that SOD, SUA, and TNM staging have certain value in judging the early prognosis of patients with hepatitis B-related liver cancer. Patients with high preoperative SOD level and low preoperative SUA level can obtain better prognosis.
Adsorption of Water Molecule in Graphene/MoS2 Heterostructure with Vacancy Defects in Mo Sites
Authors: Neupane Hari Krishna , Adhikari Narayan Prasad
Published: April 2022

First-principle calculations based on the spin-polarized density functional theory (DFT) with vdW corrections by DFT-D2 approach have been carried out to study structural, electronic, and magnetic properties of water-adsorbed graphene/MoS2 heterostructures (system-I), and water-adsorbed graphene/MoS2 heterostructures with vacancy defects in Mo sites (systems-II). We consider vacancy defects in different Mo sites such as centre-1Mo atom vacancy defect (system-IIa), left-1Mo atom vacancy defect (system-IIb), and 2Mo atom vacancy defects (system-IIc). All the systems considered in this study are structurally stable; however, the stability of defected systems decreases with an increase in defect concentrations. The calculated binding energies of HS used in this study agree with the reported work. Electronic properties of system-I and systems-II reveal that they have metallic characteristics. Our investigation shows that system-I is nonmagnetic and systems-II are magnetic. The magnetic moment in the defected systems (system-IIa, system-IIb, and system-IIc) is developed by unpaired up and down-spins of electrons created in the orbitals of atoms due to vacancy defects in Mo atoms.
Dynamic Detection and Placement for VSFs over Edge Computing Scenarios: An ACO-Based Approach
Authors: Bu Chao , Zhang Xinyang , Lv Jianhui , Wang Jinsong
Published: April 2022

As an extension of cloud computing, the edge computing has become an important pattern to deal with novel service scenarios of the Internet of Everything (IoE), especially for the rapidly increasing different kinds of service requests from edge equipment. It is still a great challenge to satisfy the demands of delay-sensitive applications, so as to optimize the service provision delay for edge equipment under 5G. In this paper, by introducing virtualized service functions (VSFs) into edge computing pattern, the mechanism of service function detection and placement among multiple Edge Computing Servers (ECSs) is proposed. We firstly improve the Ant colony optimization (ACO) method to adapt to the situation that the service requests may frequently change from different edge network domains. Based on the improved ACO, a scheme of searching for the locations (i.e., ECSs) of the requested service functions is devised, so as to optimize the service searching delay. Then, a service function placement scheme is presented, and it deploys most of appropriate service functions in each ECS by predicting the future requested frequencies of functions, which further reduces the overall service provision delay. In addition, it also improves the ECS computing capacity utilization. The simulation results show that the proposed mechanism is feasible and effective.
LncRNA SBF2-AS1 Facilitates Nonsmall Cell Lung Cancer Progression by Targeting miR-520a-3p
Authors: Wang Yi , Zou Yanzhi , Zhang Qingmei , Chen Defu , Lin Lin
Published: April 2022

Background. Long noncoding RNA (lncRNA) SET-binding factor 2 (SBF2) antisense RNA1 (SBF2-AS1), which acts as an oncogene in various cancers, can promote tumors progression. The study aimed to explore the role and molecular mechanism of SBF2-AS1 in nonsmall cell lung cancer (NSCLC). Methods. qRT-PCR was introduced to detect SBF2-AS1 and miR-520a-3p expression in NSCLC. The effects of SBF2-AS1 and miR-520a-3p on the proliferation, migration, and invasion of NSCLC cells were assessed through cell counting kit-8 (CCK-8) and transwell assay. Furthermore, the relationship of SBF2-AS1 and miR-520a-3p was verified by the RNA immunoprecipitation (RIP) assay, dual-luciferase assay, and Spearman correlation analysis. Results. In NSCLC tissues, SBF2-AS1 was highly expressed, while miR-520a-3p expression has decreased. The overall survival of NSCLC patients with high SBF2-AS1 expression was lower. SBF2-AS1 silencing repressed the proliferation, migration, and invasion of NSCLC cells. SBF2-AS1 directly interacted with miR-520a-3p, and a negative relationship was observed between their expression levels in NSCLC tissues. More importantly, the suppression of SBF2-AS1 silencing on the proliferation, migration, and invasion in NSCLC cells was counteracted by miR-520a-3p inhibition. Conclusion. SBF2-AS1 accelerated the proliferation, migration, and invasion of NSCLC cells via mediating miR-520a-3p, thus promoting NSCLC progression.
Kinect and Few-Shot Technology-Based Simulation of Physical Fitness and Health Training Model for Basketball Players in Plateau Area
Authors: Hong Xijun
Published: April 2022

Players in modern basketball have a lot of physical contact, a lot of bumps, and a lot of physical struggles. The competition for the ball, whether in the air or on the ground, is fierce, putting higher demands on the players’ physical abilities. Coaches frequently use plateau physical training, which is very effective in developing athletes’ cardiopulmonary function, among many other training methods. The proportional length and active area of arms are obtained using the skin color model of the human body, the angle and posture information of each joint is extracted from dynamics, and the 3D posture of arms and dynamic arms is trained and recognized in this paper, which is based on Kinect. The findings revealed that mild hypoxia in the plateau significantly lowered basketball players’ performance and that basketball players’ maximum heart rate and 1-minute heart rate recovery in high-intensity exercise were lower than those in flat area training.
Convolutional Neural Networks for Structural Damage Identification in Assembled Buildings
Authors: You Chunhua , Liu Wenxiang , Hou Lei
Published: April 2022

This paper investigates the migration learning AlexNet-based algorithm for the recognition of assembly building structures and the recognition based on an improved algorithm, and gives an analysis of the results. The structure of AlexNet convolutional neural network is introduced and the basic principles of migration learning are analysed. The optimal model for the ceiling damage recognition task was obtained through parameter adjustment, with a test accuracy of 96.6%. The maximum improvement in test accuracy is about 4%, with 82.6% and 79.7% for beam and column damage recognition and infill wall damage recognition respectively.
Combined Training Intervention Targeting Medical and Nursing Staff Reduces Ciprofloxacin Use and Events of Urinary Tract Infection
Authors: Forster Johannes , Schulze Petra , Burger Claudia , Krone Manuel , Vogel Ulrich , Surat Güzin
Published: April 2022

Inappropriate diagnosis of urinary tract infections (UTI) contributes to antimicrobial overuse. A combined training intervention for medical and nursing staff mainly addressing the analytic process reduced UTI events (9.20 vs. 7.36 per 1000 PD, −20.0%,

p

 = 0.003) and the utilization rate of ciprofloxacin (11.6 vs. 3.5, −69.6

p

 = 0.001) in a Bavarian University Hospital. Combined training intervention—as part of an antibiotic stewardship program—can be effective in avoiding unnecessary urinalysis and reducing antibiotic consumption.
Machine Learning-Based Performance Comparison to Diagnose Anterior Cruciate Ligament Tears
Authors: Awan Mazhar Javed , Mohd Rahim Mohd Shafry , Salim Naomie , Rehman Amjad , Nobanee Haitham
Published: April 2022

In recent times, knee joint pains have become severe enough to make daily tasks difficult. Knee osteoarthritis is a type of arthritis and a leading cause of disability worldwide. The middle of the knee contains a vital portion, the anterior cruciate ligament (ACL). It is necessary to diagnose the ACL ruptured tears early to avoid surgery. The study aimed to perform a comparative analysis of machine learning models to identify the condition of three ACL tears. In contrast to previous studies, this study also considers imbalanced data distributions as machine learning techniques struggle to deal with this problem. The paper applied and analyzed four machine learning classification models, namely, random forest (RF), categorical boosting (Cat Boost), light gradient boosting machines (LGBM), and highly randomized classifier (ETC) on the balanced, structured dataset of ACL. After oversampling a hyperparameter adjustment, the above four models have achieved an average accuracy of 95.72%, 94.98%, 94.98%, and 98.26%. There are 2070 observations and eight features in the collection of three diagnosis ACL classes after oversampling. The area under curve value was approximately 0.998, respectively. Experiments were performed using twelve machine learning algorithms with imbalanced and balanced datasets. However, the accuracy of the imbalanced dataset has remained under 76% for all twelve models. After oversampling, the proposed model may contribute to the investigation of ACL tears on magnetic resonance imaging and other knee ligaments efficiently and automatically without involving radiologists.
Reform Method of University Legal Education Based on Artificial Intelligence and Wireless Communication
Authors: Wu Junyan , Tang Wenjun
Published: April 2022

The construction and development of legal education in colleges and universities are an important driving force for the construction of a society ruled by law. Looking at the history of the development of legal education in colleges and universities, it can be said that every major change in it has an important relationship with the changes in the social background. Under the background of the rapid development of wireless communication and artificial intelligence technology at this stage, legal education in colleges and universities has also ushered in a new opportunity for upgrading. The purpose of this paper is at studying the realization path of legal education reform in colleges and universities based on the background of the new era. To consolidate the achievements in this field through active reform and to solve the main problems by constructing an optimized teaching system, in the selection of the survey method, the research uses the questionnaire survey method as the main source of data. According to the questionnaire, 60% of the students indicated that they would take the initiative to study and continue to try new assessment methods to adapt to the autonomous learning of the law. Teachers should try their best to let students fully experience law teaching under wireless communication and AI in their usual teaching.
Mechanical Properties and Constitutive Model of Selective Laser Melting 316L Stainless Steel at Different Scanning Speeds
Authors: Li Yongling , Ge Yongsheng , Lei Jingfa , Bai Wei
Published: April 2022

To investigate the effects of different scanning speeds on the mechanical properties of selective laser melting 316L stainless steel (SLM 316L SS), process specimens with scanning speeds at 350 mm/s, 650 mm/s, 950 mm/s, and 1250 mm/s were prepared using the SLM technique in this paper. The quasistatic and dynamic compressive mechanical properties of the four specimens were tested by electrohydraulic servo experimental machine and Hopkinson compression bar experimental device, and the mechanical differences of the specimens were analyzed by microscopic observation. Finally, the modified Johnson-Cook (J-C) model was adopted to describe the dynamic mechanical properties of SLM 316L SS. Results showed that the four process steel specimens exhibited typical viscoplastic characteristics and significant strain rate strengthening effects in the mechanical property tests. Moreover, the scanning speed significantly affects the internal defects and melt pool characteristics of the SLM 316L specimens, and the yield strength decreases significantly with the disappearance of the melt pool characteristics. Finally, the modified J-C model can better describe the mechanical behavior of SLM 316L SS material more accurately. This study can provide theoretical references for improving the fabrication process of SLM 316L SS to broaden the practical application of this material.