bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Features and Mortality Prediction of the 4C Score Early in COVID-19 Infection: A Retrospective Study in Saudi Arabia
Authors: Mohamed Rehab Abd Elfattah , Abdelsalam Eman Mahmoud , Maghraby Hend Maghraby , Al Jedaani Huda Shali , Rakha Ehab Badran , Hussain Khamrunissa , Sultan Intessar
Published: November 2021

The ISARIC4C consortium developed and internally validated the 4C Score for prediction of mortality only in hospitalized patients. We aimed to assess the validity of the 4C Score in mortality prediction of patients with COVID-19 who had been home isolated or hospitalized.

This retrospective cross-sectional study was performed after the first wave of COVID-19. Data of all PCR-positive COVID-19 patients who had been discharged, hospitalized, or died were retrospectively analyzed. Patients were classified into four risk groups according to the 4C Mortality Score. A total of (506) patients were classified as follows: low (57.1%), intermediate (27.9%), high (13%), and very high (2%) risk groups. Clinical, radiological, and laboratory data were significantly more severe in the high and very high-risk groups compared with other groups (p<0.001 for all). Mortality rate was correctly estimated by the model with 71% sensitivity, 88.6% specificity, and area under the curve of 0.9. The mortality rate was underestimated among the very high-risk group (66.2% vs 90%). The odds of mortality were significantly greater in the presence of hypoxia (OR 2.6, 95% CI 1.5 to 4.6, p<0.001) and high respiratory rate (OR 5.3, 95% CI 1.6 to 17.9, p<0.007), C reactive protein (CRP) (OR 3.5, 95% CI 1.8 to 6.8, p<0.001), and blood urea nitrogen (BUN) (OR 1.9, 95% CI 1.3 to 3.1, p<0.002). Other components of the model had non-significant predictions. In conclusion, the 4C Mortality Score has good sensitivity and specificity in early risk stratification and mortality prediction of patient with COVID-19. Within the model, only hypoxia, tachypnea, high BUN, and CRP were the independent mortality predictors with the possibility of overlooking other important predictors.
A field study on the load sharing behavior of a micropiled raft underpinned by a waveform micropile
Authors: Wang Chengcan , Han Jin-Tae , Kim Seokjung
Published: November 2021

A waveform micropile (WMP) uses the jet-grouting method to generate shear keys along the pile shaft for improving shaft resistance and cost efficiency. In this study, field loading tests were performed to characterize the load sharing behavior upon inclusion of a WMP in a group of four micropiles. First, single-pile compressive loading tests were conducted on three WMPs and five type A micropiles (MP). Subsequently, a group-pile loading test was performed on a piled raft comprising 2 × 2 MPs and a central WMP. The load–settlements, axial stiffnesses, and load transfer mechanisms of individual MPs were analyzed during the tests, including the short- and long-term effects of the axial stiffnesses of the MPs on the load sharing ratio of the micropiled raft. The single-pile loading test results revealed that the shear keys along the WMPs caused its bearing capacities and axial stiffnesses to be 1.5 times and 2–5 times higher than those of MPs, respectively. In the micropiled-raft loading test, the load sharing ratios of the MPs increased with their axial stiffnesses, and the highest load sharing capacity was exhibited by the WMP, which constituted 30% of the total load and 2–3 times that of MPs. Moreover, the influence of raft on the load-sharing capacity should be considered as well.
Geometry optimization for tunable band gap and wave guiding in periodic grid structures
Authors: Yang Shuai , Zhou Xiao-Liang , Li Chang-Qing , Zhang Shi-Ke
Published: November 2021

A proper lattice structure consisting of homogeneous material is designed in this paper to investigate the maximum bandwidth of perfect lattice structures and tunable property of waveguide with linear geometric defect by means of selecting optimal geometric lattice cell. A simulation model based on finite element method is used to calculate dispersion curves and transmission spectrums of lattice structures with different geometric parameters. Meanwhile, a simplified theoretical model of unit cell, which considers the mass of grid bar and stiffness of node area, is applied to validate the accuracy of simulation result and may provide an effective approach for prediction of band gap lower boundary. Then, the validated numerical results show different orders of widest band gap that can be realized by different optimal geometric structures. Moreover, waveguide property can be effectively controlled and manipulated by changing defect parameters. The present study may establish theoretical and simulation foundation to control and manipulate band structures and other acoustic propagation characteristics of waveguide devices.
Kinetics and Adsorption Model of Methylene Blue on g-C3N4@WO3.H2O Nanoplate Composite
Authors: Cuong Le Manh , Duc Bui Hoang , Thang Pham Van , Mai Nguyen Thi Tuyet , Chinh Huynh Dang , Tu Nguyen Cong , Anh Luu Thi Lan
Published: November 2021

g-C3N4@WO3.H2O nanoplate composite adsorbents were prepared in a simple acid precipitation method at room temperature. The g-C3N4@WO3.H2O nanoplate composite adsorbents were characterized by X-ray powder diffraction, micro-Raman spectroscopy, Fourier transform infrared spectra, scanning electron microscopy and UV-vis diffuse reflectance spectroscopy. The results show that the orthorhombic-phase WO3.H2O nanoplates with dimensions of [Formula: see text][Formula: see text]nm3 were successfully composited with g-C3N4. The methylene blue dye generation activity of these adsorbents was evaluated. The kinetics and absorption model of g-C3N4@WO3.H2O nanoplate composite adsorbents were further studied.
Fabrication of p-NiO/n-TiO2 Solar Device for Photovoltaic Application
Authors: Mouchou R. T. , Ukoba K. O. , Laseinde O. T. , Jen T. C.
Published: November 2021

Energy demand is increasing globally owing to population growth. Solar cell development has gained considerable attention because of its potential to provide everyone with sustainable, affordable, clean, and globally accessible energy. A heterojunction solar device for photovoltaic applications was developed in this study, using nickel oxide (NiO) as the p-type and titanium oxide (TiO2) as the n-type. The material chosen was motivated by the affordability, availability, and performance compared to existing silicon that is more efficient but less affordable and available. The TiO2 and NiO2 were synthesised and characterised before the deposition and characterisation of the solar cells. The characterisation was carried out using Fourier transform infrared spectroscopy (FTIR), Transmission Electron Microscopy (TEM), scanning electron microscopy (SEM), EDX, X-ray Diffraction (XRD), and a four-point probe. The deposition parameters were fine-tuned to achieve optimum optoelectronic properties for the solar device. The final device exhibited an open-circuit voltage of 370 mV, a current density of 1.7 mA, and solar cells efficiency of 3.7.
DDA Simulation Study on Mechanical Failure of Heterogenous Rock
Authors: Ning Youjun , Lv Xinyang , Yang Zheng
Published: November 2021

Heterogeneity is an important characteristic that affects the mechanical behavior of rock. In the present work, a statistical rock mesoheterogeneity model based on the Weibull distribution function is introduced into the discontinuous deformation analysis (DDA) method to simulate the mechanical failure of heterogeneous rock, in which the general heterogeneity degree is controlled by a heterogeneity index and the mechanical property of each subblock element is randomly assigned. Brazilian disc and uniaxial compressive rectangular specimens are simulated as examples. Results show that it is more reasonable to consider the heterogeneity of elasticity properties (the elastic modulus and Poisson’s ratio) and strength properties (the tensile strength, cohesion, and friction angle) simultaneously in the heterogeneity model. It is also shown that with a larger heterogeneity index, which means a lower degree of heterogeneity, the reproducibility of the macroscopic response curves of a specimen gets better, while the exact cracking always differs but with less scattered cracks, and the global fracturing failure pattern and mode are weakly influenced by the heterogeneity. Moreover, with the increase in the heterogeneity index, the macroscopic equivalent modulus and strength get larger and approach those of a homogeneous specimen. This work indicates the importance of heterogeneity for rock mechanical behaviors including the macroscopic equivalent response and the fracturing failure. By the subblock DDA method to simulate fracturing realistically, the fracturing failure process of heterogeneous rock can be successfully reproduced, which builds good foundation for the simulation study of heterogeneous rock fracturing in practical problems, e.g., coal and rock fracturing in fluidization mining in the future.
Named Data Networking‐Based On‐Demand Secure Vehicle‐To‐Vehicle Communications
Authors: Saleem Qudsia , Din Ikram Ud , Almogren Ahmad , Alkhalifa Ibrahim , Khattak Hasan Ali , Rodrigues Joel J. P. C.
Published: November 2021

The detection of secure vehicles for content placement in vehicle to vehicle (V2V) communications makes a challenging situation for a well‐organized dynamic nature of vehicular ad hoc networks (VANET). With the increase in the demand of efficient and adoptable content delivery, information‐centric networking (ICN) can be a promising solution for the future needs of the network. ICN provides a direct retrieval of content through its unique name, which is independent of locations. It also performs better in content retrieval with its in‐network caching and named‐based routing capabilities. Since vehicles are mobile devices, it is very crucial to select a caching node, which is secure and reliable. The security of data is quite important in the vehicular named data networking (VNDN) environment due to its vital importance in saving the life of drivers and pedestrians. To overcome the issue of security and reduce network load in addition to detect a malicious activity, we define a blockchain‐based distributive trust model to achieve security, trust, and privacy of the communicating entities in VNDN, named secure vehicle communication caching (SVC‐caching) mechanism for the placement of on‐demand data. The proposed trust management mechanism is decentralized in nature, which is used to select a trustworthy node for cluster‐based V2V communications in the VNDN environment. The SVC‐caching strategy is simulated in the NS‐2 simulator. The results are evaluated based on one‐hop count, delivery ratio, cache hit ratio, and malicious node detection. The results demonstrate that the proposed technique improves the performance based on the selected parameters.
A Novel Framework for Authority Management Based on Knowledge Base Completion of the Graph Neural Network
Authors: Wang Jianmin , Xia Yukun , Zhao Wenbin , Zhang Yuhang , Wu Feng
Published: November 2021

Big data is massive and heterogeneous, along with the rapid increase in data quantity, and the diversification of user access, traditional database, and access control methods can no longer meet the requirements of big data storage and flexible access control. To solve this problem, an entity relationship completion and authority management method is proposed. By combining the weighted graph convolutional neural network and the attention mechanism, a knowledge base completion model is given. On this basis, the authority management model is formally defined and the process of multilevel trust access control is designed. The effectiveness of the proposed method is verified by experiments, and the authority management of knowledge base is more fine‐grained and more secure.
Liquid Crystal Display (LCD) and Organic Light Emitting Diode (OLED) Applications on Natural Fibre Reinforced Polymer Matrix Composites
Authors: Senthil Nayagam V. , Anamika  , Gopinath D. , Vetri Velmurugan K. , Fathima Rani , Joy Kinol Mary , Alias Surendhar Prasath , Christopher David
Published: November 2021

Natural materials are the alternative source for the manufacture of products due to environmental requirements. Hot injection moulding techniques make the composite product with fibreglass, granite waste filler, and polylactic acid (PLA). Five samples of each set and sampled with better hardness varied the volumetric percentage of glass fibre and the waste nanogranite particles. This effort is mainly concerned with evaluating the wear of dry sliding and friction of composites. Varying 15, 25, 35, and 45 N load, 750 and 1500 m sliding distance tested the composite materials, respectively. Parametric condition experiments were carried out at the stated process to record answers. Nanogranite composite materials are better than higher concentrations of glass fibre in PLA matrices composites, which are more resistant to wear and friction coefficients. The nanogranite powder is added with the filler element in the PLA matrix to provide a better coefficient of wear and rubbing. A high load of 45 N and a sliding distance of 1500 m were measured at low wear and low friction coefficients.
Identifying IoT Devices Based on Spatial and Temporal Features from Network Traffic
Authors: Yin Feihong , Yang Li , Ma Jianfeng , Zhou Yasheng , Wang Yuchen , Dai Jiahao
Published: November 2021

With the rapid growth of the Internet of Things (IoT) devices, security risks have also arisen. The preidentification of IoT devices connected to the network can help administrators to set corresponding security policies according to the functionality and heterogeneity of the devices. However, the existing methods are based on manually extracted features and prior knowledge to identify the IoT devices, which increases the difficulty of the device identification task and reduces the timeliness. In this paper, we present CBBI, a novel IoT device identification approach. On the one hand, CBBI uses a hybrid neural network model Conv-BiLSTM to automatically learn the representative spatial and temporal features from the network traffic, such as the position relationship of the internal organization structure in network communication traffic, the time sequence of the data packets, and the duration of the network flow. On the other hand, CBBI contains the data augmentation module FGAN that solves the problem of data imbalance in deep learning and improves the accuracy of the model. Finally, we used the public dataset and laboratory dataset to evaluate CBBI from multiple dimensions. The evaluation results for different datasets show that our approach achieves the accurate identification of IoT devices.
Long-Term Follow-Up of SAPHO Syndrome for 15 Years Led to a Diagnosis of Temporomandibular Joint Pain and Trismus
Authors: Takamatsu Koki , Sato Hitoshi , Moriya Takashi , Yasuda Arisa , Kamatani Takaaki , Shirota Tatsuo
Published: November 2021

Synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome is a systemic disease with symptoms of pustular skin disease and sterile osteoarticular lesions. This disease rarely involves the temporomandibular joint (TMJ). Although it is a disease with a good long-term prognosis, its treatment remains challenging. We describe a case with long-term follow-up of SAPHO syndrome for 15 years in which TMJ pain and trismus led to the diagnosis. A 30-year-old woman with TMJ pain and trismus was referred to our department. Her medical history included palmoplantar pustulosis. Sterile inflammation in the left TMJ and diffuse sclerosing osteomyelitis of the mandible were observed. Thus, she was diagnosed with SAPHO syndrome. The symptoms of severe TMJ pain, trismus, and left cheek swelling presented three times in the 15 years. Symptomatic treatment with nonsteroidal anti-inflammatory drugs, antibiotics, corticosteroids, and bisphosphonates was administered several times. There has been no relapse of symptoms over the past nine years. The patient must be continuously kept under observation to look for the relapse of symptoms.
Warfarin Use Is Associated with Increased Mortality at One Year in Patients with Idiopathic Pulmonary Fibrosis
Authors: Naqvi Syeda Fatima , Sohail Amir Humza , Lakhani Dhairya A. , Maurer James , Sofka Sarah , Hadi Yousaf B.
Published: November 2021

Rationale. Previous data suggest that warfarin may worsen outcomes in IPF in patients with no indication for anticoagulation when compared to placebo. However, warfarin continues to be widely used for cardiac and thromboembolic indications in this patient population due to unavailability of data comparing warfarin with other anticoagulants in patients with IPF. Objectives. We studied the safety and efficacy of warfarin compared to direct acting oral anticoagulant use in patients with IPF. Methods. We conducted a retrospective cohort study of all patients with IPF who were prescribed warfarin or direct acting oral anticoagulants (DOACs) for cardiac or thromboembolic indications and followed at our institute for their care. Univariate tests and multivariable logistic regression analyses were used for assessing association of variables with outcomes. Results. A total of 73 patients were included in the study with 28 and 45 patients in the warfarin and DOAC groups, respectively. Univariable analysis revealed a significant difference in mortality in one year between warfarin and DOAC groups (7/28 vs. 3/45,

p

value 0.027). Significantly more patients in the warfarin group suffered an exacerbation that required hospitalization within one year (9/28 vs. 5/45,

p

value 0.026). Multivariate logistic regression analysis showed that anticoagulation with warfarin was independently associated with mortality at one-year follow-up (OR: 77.4, 95% CI: 5.94–409.3,

p

value: 0.007). Conclusion. In our study of patients with IPF requiring anticoagulants, we noted statistically significant higher mortality with warfarin anticoagulation when compared to DOAC use. Further larger prospective studies are needed to confirm these findings.
Study and Analysis of a Multilayer Multipair Electret-Based Thin-Film Mechanical Antenna
Authors: Zhou K. P. , Niu Y. T. , Liu W. N. , Wang Z. D. , Guo S. H. , Li B. , Wang Z. , Zhao X. K.
Published: November 2021

Very low-frequency (VLF) and ultralow-frequency (ULF) electromagnetic waves have the advantage of high penetration and low propagation loss in wireless communication systems and are mainly used for underwater and underground communications, as well as for earthquake and lightning forecasting. At present, VLF and ULF antennas are mostly bulky and require hundreds of antennas and more to be set up, which is costly and inefficient. In this paper, we propose to generate VLF and ULF signals by rotating a multilayer multipair electret thin-film electret driven by an excitation device, which improves the problem of low radiation efficiency of VLF and ULF signals and the large size of conventional low-frequency transmitting antennas. Based on a multilayer, multipair electret film mechanical antenna, a magnetic field propagation model is developed, and the relationship between the magnetic flux density mode and the number of layers of electret films, as well as the relationship between the antenna emission frequency and the motor rotation frequency and the number of pairs of electret films, is analyzed. The selection of a suitable model for practical situations based on conditions such as antenna size and propagation distance is illustrated. The research work is of great importance for guiding the design of mechanical antennas and optimizing antenna structures.
The Modification of the Perforated Plate in the Fluidized-Bed Combustor to Analyze Heat Convection Rate and Temperature
Authors: Erdiwansyah  , Mahidin  , Husin Husni , Faisal Muhammad , Muhtadin  , Gani Asri , Sardjono R. E , Mamat Rizalman
Published: November 2021

Investigation of combustion temperature through experiments with a wide range of fuels, both solid and liquid, is continuously being conducted by scientists around the world, while the measurement of heat transfer rate can be analyzed when the combustion process occurs. Previous research has generally been conducted using liquefied gas, fossil fuels, and alcohol additives. Specifically, the research in this work investigated the convection heat rate and combustion temperature through the modification of the perforated plate. The experiment was conducted in the fluidized-bed combustor (FBC) fuel chamber using solid waste fuel of oil palm biomass. Measurements were performed at four different points using the HotTemp HT-306 Digital Thermometer. The results of the experiment showed that the convection heat rate in measurement one (M-I) reached 8.258 W/m2 for palm kernel shell (PKS) fuel. Meanwhile, in measurement two (M-II), the convection rate of 7.392 W/m2 was produced by oil palm midrib (OPM) fuel. The highest combustion temperature was recorded with OPM fuel (884°C) at M-I. However, the combustion temperature of the PKS combustion process is higher at 896°C but shows a less good trend than OPM. Overall, the measurement results of the three types of fuel used to modify the perforated plate applied in the FBC fuel chamber are excellent. It can be proven that the fuel is put into the combustion chamber with nothing left.
Construction and Research of Safety Management System for Machine Patrol Operation
Authors: Zhang Ying , Guo Jin Chao , Liao Jian Dong
Published: November 2021

Aiming at the flight safety problems existing in UAV power patrol inspection, this study proposes a UAV patrol inspection safety management system (SMS) scheme, which takes the safety target level specified in soar as the target management, based on safety management, modern control theory, risk management, and UAV operation regulations, combined with the actual needs of machine patrol inspection of China Southern Power Grid and the requirements of local government. The UAV SMS scheme is developed from four parts: safety policy, risk management, safety guarantee, and safety promotion, and the application analysis is carried out in combination with the Kobe accident case in 2020. The experimental results demonstrate that the implementation of SMS scheme can effectively reduce the accident risk level during UAV power patrol inspection.
Two Cases of Leigh Syndrome in One Family: Diagnostic Challenges and Clinical Management Experience in Latvia
Authors: Katkevica Arta , Kreile Madara , Grinfelde Ieva , Taurina Gita , Micule Ieva , Dzivite-Krisane Iveta , Smite-Laguna Arta , Malniece Ieva
Published: November 2021

Leigh syndrome is a neurodegenerative disorder with an incidence of 1 : 40,000 live births. The clinical presentation of LS is highly variable with heterogeneity in the disease-associated symptoms of cerebellar, motor, and extrapyramidal dysfunction and common infections. There is no effective treatment for this condition; as such, the prognosis of this condition is very poor with death occurring within the first few years of life. In this study, we report the first LS case in Latvia with SURF1 pathogenic variants in two siblings. The difficulties encountered establishing a diagnosis for the first proband and the effective prenatal diagnosis for the second offspring that led to termination of the pregnancy are discussed.
Modeling and Quantifying Interaction of Information and Capacity in Public Transport Disruptions
Authors: Rahimi Siegrist Mahsa , Corman Francesco
Published: November 2021

Disruption in public transport networks has adverse implications for both passengers and service managers. To evaluate the effects of disruptions on passengers’ behaviour, various methods, simulation modules, and mathematical models are widely used. However, such methods included many assumptions for the sake of simplicity. We here use multiagent microsimulation modules to simulate complex real-life scenarios. Aspects that were never explicitly modelled together are the capacity of the network and the effect of disruption to on-board passengers, who might need to alight the disrupted services. In addition, our simulation and developed module provide a framework that can be applied for both transport planning and real-time management of disruption for the large-scale network. We formalize the agent-based assignment problem in capacitated transit networks for disrupted situations, where some information is available about the disruption. We extend a microsimulation environment to quantify precisely the impact and the number of agents directly and indirectly affected by the disruption, respectively, those passengers who cannot perform their trip because of disrupted services (directly affected passengers), and those passengers whose services are not disrupted but experience additional crowding effects (indirectly affected passengers). The outcomes are discussed both from passengers’ perspective and for extracting more general planning and policy recommendations. The modeling and solution approaches are applied to the multimodal public transport system of Zürich, Switzerland. Our results show that different information dissemination strategies have a large impact on direct and indirect effects. By earlier information dissemination, the direct effects get milder but larger in space, and indirect negative effects arise. The scenarios with the least information instead are very strongly affecting few passengers, while the less negative indirect effect for the rest of the network.
Advanced Oxidation Protein Product Promotes Oxidative Accentuation in Renal Epithelial Cells via the Soluble (Pro)renin Receptor‐Mediated Intrarenal Renin‐Angiotensin System and Nox4‐H2O2 Signaling
Authors: Xue Kai , Wang Yurong , Wang Yan , Fang Hui
Published: November 2021

Full‐length (pro)renin receptor (fPRR), a research hotspot of the renin‐angiotensin system (RAS), plays a serious role in kidney injury. However, the relationship between fPRR and advanced oxidation protein product (AOPP) remains largely unexplored. This study was aimed at exploring the effect of fPRR, especially its 28 kDa soluble form called soluble PRR (sPRR), in AOPP‐induced oxidative stress in HK‐2 cells, a renal proximal tubular epithelial cell line. Incubation of HK‐2 cells with 100 μg/ml AOPP resulted in significant upregulation of fPRR expression and caused an approximately fourfold increase in medium sPRR secretion. However, unmodified albumin did not demonstrate the same effects under the same concentration. Treatment of HK‐2 cells with the site‐1 protease (S1P) inhibitor PF429242 (40 μM) or S1P siRNA significantly inhibited AOPP‐induced sPRR generation. fPRR decoy inhibitor PRO20 and PF429242 treatment for 24 h remarkably attenuated the AOPP‐induced upregulation of RAS components. Furthermore, PF429242 significantly reduced the AOPP‐stimulated expression of NADPH oxidase 4 (Nox4) and H2O2 expression. The use of a small recombinant protein, named sPRR‐His, reversed these alterations. In conclusion, these results provided the first demonstration of AOPP‐promoted activation of sPRR. Increased renal proximal tubule Nox4‐derived H2O2 contributed to the aggravation of oxidative stress. Targeting S1P‐derived sPRR is a promising intervention strategy for chronic kidney disease.
P-ANCA Systemic Vasculitis Induced by Brucellosis in an Elderly Male Patient
Authors: Cheikh Mohammed , Kabli Abdulrahman , Sendi Esraa , Almoallim Hani
Published: November 2021

One of the most prevalent causes of vasculitis is bacterial infection. An infection that causes anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is uncommon and not reported frequently. We report a case of a 74-year-old male who presented with fever for ten days and was found to have brucellosis. Then, he was diagnosed with Guillain-Barré syndrome (GBS) and started on immunoglobulin (IVIG) for one week without a response. His fever was still persistent despite appropriate antibiotic therapy. Rheumatology evaluation revealed a history of multiple joint pain and swelling, elevated inflammatory marker, and a high titer of P-ANCA. Steroid therapy was started initially on the background of antibiotics therapy. His fever and other symptoms showed marked improvement after one week. However, P-ANCA titer was still elevated. The decision was made to treat the patient as a case of brucellosis-induced P-ANCA vasculitis. Azathioprine was added, and steroid was maintained for one month and then it was tapered gradually. All symptoms improved from the third month of follow-up except weakness from peripheral neuropathy with normalization of P-ANCA titer. His condition remained stable after six months of follow-up. Clinicians should be aware of the possibility of infection-induced vasculitis, particularly when patients’ symptoms persist despite the appropriate use of antibiotics.
[Retracted] Music Online Education Reform and Wireless Network Optimization Using Artificial Intelligence Piano Teaching
Authors: Guo Rui , Ding Jingna , Zang Weihua
Published: November 2021

The purpose is to realize the intelligent reform of piano online teaching and the intelligent optimization of wireless networks. Empirical research is realized with quantitative research and algorithm simulation as the starting point. First, regression fitting algorithm and Relief F weight algorithm are adopted to extract the effectiveness of each characteristic variable. Next, under the guidance of metric learning theory, K‐Nearest Neighbors (KNN) in Projected Feature Space (P‐KNN) algorithm is proposed to complete the hierarchical recognition of piano teaching influence features. Metric Learning With Support Vector Machine (ML‐SVM) classification algorithm is employed to identify the feature performance affecting piano teaching. Finally, the performance of P‐KNN algorithm and ML‐SVM algorithm is compared with KNN algorithm and Information‐Theoretic‐Metric‐Learning (ITML) algorithm. It is concluded that the recognition accuracies of P‐KNN and ML‐SVM are 82.78% and 83.97%, respectively. Based on the quantitative research on the characteristics affecting piano teaching, artificial intelligence and wireless network optimization are combined to explore the implementation path of intelligent technology in piano teaching reform, reflect the use value of modern science and technology in piano teaching, and innovate the process of music online education reform of piano teaching.
Construction and Evaluation of Intelligent Medical Diagnosis Model Based on Integrated Deep Neural Network
Authors: Ma Lina , Yang Tao
Published: November 2021

In recent years, as human life expectancy increases, birth rate decreases and health management concerns; the traditional Healthcare imaging system, with its uneven Healthcare imaging resources, high Healthcare imaging costs, and diagnoses often relying on doctors’ clinical experience and equipment level limitations, has affected people’s demand for health, so there is a need for a more accurate, convenient, and affordable Healthcare imaging system that allows all people to enjoy fair and quality Healthcare imaging services. This paper discusses the construction and evaluation of an intelligent medical diagnostic model based on integrated deep neural networks, which not only provides a systematic diagnostic analysis of the various symptoms input by the inquirer but also has higher accuracy and efficiency compared with traditional medical diagnostic models. The construction of this model provides a theoretical basis for integrating deep neural networks applied to medical neighborhoods with big data algorithms.
Wireless Network of Silver Film Lysozyme Aptasensor Based on Fractal Measurement
Authors: Wang Zhiyou , Wang Maojin
Published: November 2021

In this work, we reported a wireless network composed of silver film-based graphene oxide-fluorescence resonance energy transfer (GO-FRET) lysozyme aptasensor nodes. At the sensor node level, we optimized silver substrate structure, concentrations of the aptamers, and graphene oxide and tested lysozyme detection performance with a model analyte. At the network level, we analyzed the complexity and transmission success rate using fractal measurements. We implemented the wireless network composed of the aptasensor with a portable Wi-Fi fluorescent reader. Transmission success rate testing results show that an increase in node hops can promote the rate of transmission success dramatically. When the hop count is larger than 6, the rate of transmission success can reach more than 90% if the transmission failure probability and sleep probability are 0.1 and 0.5, respectively.
Prediction of Mineralization Prospects Based on Geological Semantic Model and Mobile Computer Machine Learning
Authors: An Zhengzhen , Zhao Yue , Zhang Yanfei , Li Xuguang
Published: November 2021

Mineral resources are indispensable in the development of human society and are the foundation of national economic development. As the prospecting target shifts from outcrop ore to concealed ore, from shallow to deep, the difficulty of prospecting becomes more and more difficult. Therefore, the prediction of mineralization prospects is of great significance. This paper is aimed at completing the prediction of mineralization prospects by constructing geological semantic models and using mobile computer learning to improve the accuracy of prediction of mineralization prospects and expanding the application of semantic mobile computing. We use five different semantic relations to build a semantic knowledge library, realize semantic retrieval, complete information extraction of geological text data, and study mineral profiles. Through the distributed database of mobile computing, the association rules and random forest algorithm are used to describe the characteristics of minerals and the ore‐controlling elements, find the association rules, and finally combine the geological and mineral data of the area and use the random forest algorithm to realize the prospect of mineralization district forecast. The geological semantic model constructed in the article uses the knowledge library for associative search to achieve an accuracy rate of 87.9% and a recall rate of 96.5%. The retrieval effect is much higher than that of traditional keyword retrieval methods. The maximum value of the posterior result of the mineralization prospect is 0.9027, the average value is 0.0421, and the standard deviation is 0.1069. The picture is brighter, and the probability of mineralization is higher.
A Study of Data-Driven Enterprise Human Resource Management Model
Authors: Yang Jing , Lang Lili , Song Shaojuan
Published: November 2021

With the deepening of diversified and professional business philosophy in large enterprises, enterprises play more and more abundant social functions in society. Sense of mission and honor play an important role in the healthy development of enterprises. With the in-depth integration of enterprise management and computer technology, some human resource management problems related to corporate social responsibility often appear in this process. From the traditional human resource management paradigm to people-oriented social responsibility human resource management, “strengthening effectiveness” has become the main research direction of enterprise management in the electronic age. On this basis, through the discrete modeling method of a large amount of data, this paper creatively puts forward the coupling correlation between corporate social responsibility and enterprise human resource management based on grey correlation algorithm. Compared with the management mode based on trapezoidal data analysis and cluster center adopted in the current mainstream enterprise human resource management research, the innovation of this algorithm is to analyze the dynamic data of corporate social responsibility and enterprise human resources and establish a coupling model related to corporate social responsibility. It can not only realize the dynamic tracking of human resource data, but also make full use of the relevant characteristic information of the coupling relationship between enterprise human resource management and corporate social responsibility. According to the dynamic big data such as employee welfare, employee compensation, employee training, employee overtime, and timeliness of transaction processing, this paper analyzes the social problems such as corporate social responsibility evaluation index, employee turnover rate, and enterprise income, so as to provide theoretical support for enterprise business strategy.
The Effect of Fairness Concern on Carbon Emission Reduction and Revenue Distribution in Construction Supply Chain: Power Structure Perspective
Authors: Jiang Wen , Pu Linqing , Huang Ting , Yuan Li , Gan Lu
Published: November 2021

This paper invested a two-echelon construction supply chain that consists of a general contractor and a subcontractor. This paper constructs the centralized model and the decentralized models, respectively, and studies the emission reduction and revenue distribution strategies of construction supply chain considering fairness concern and cap-and-trade. Numerical analysis is carried out to analyze the influence of cap-and-trade and fairness concern on the optimal decision and the maximum profit of construction supply chain. This paper shows that, under cap-and-trade policy, the centralized model has the best emission reduction effect and the highest supply chain profit without fairness concern, while the general contractor’s Stackelberg model has the best emission reduction effect and the highest supply chain profit with fairness concern. In the two scenarios, the Vertical Nash model is the most unfavorable to emission reduction, and it will also seriously damage the interests of enterprises. In practice, supply chain should choose the general contractor’s Stackelberg model and avoid the Vertical Nash model. Because fairness concern of the subcontractor will damage the supply chain profits and emission reduction performance, the general contractor shall try to select the subcontractor with lower fairness concern to avoid the loss of profit. Besides, enterprises should actively take measures to reduce fairness concern, such as enterprises signing the contract price confidentiality clause, which aims to reduce fairness concern of the subcontractor. The results of this paper can not only enrich the research content of construction supply chain management, but also provide references for the government to formulate emission reduction policies.
A New Definition of Pyroptosis‐Related Gene Markers to Predict the Prognosis of Lung Adenocarcinoma
Authors: Zhang Guanran , Yan Zhangzhe
Published: November 2021

Pyroptosis, the prototype of programmed cell death, is crucial to the development of multicellular organisms. Lung cancer is one of the most lethal cancers in the world. Because lung cancer progresses quickly, it is mostly found at an advanced stage, resulting in a very poor prognosis of lung cancer. At present, there is no treatment with good prognosis, but pyroptosis‐based tumor therapy may be able to solve this problem. In the past few decades, it has been found that pyroptosis can affect the invasion, proliferation, and metastasis of tumor and apoptosis is an important system to resist cancer. Our study is aimed at constructing a prognostic model within pyroptosis‐related genes. We developed a prognostic model by using TCGA and GEO database, and differentially expressed genes (DEGs) were identified. Five genes (NLRP1, NOD1, NLRC4, CASP9, and PLCG1) were identified to construct a prognostic model. According to the median risk score calculated by our formula, we divided patients into the high‐ and low‐risk groups. Pyroptosis‐related genes play important roles in tumor immunity and can be used to predict the prognosis of lung adenocarcinoma (LUAD).
Cross-Efficiency Evaluation under Probabilistic Hesitant Fuzzy Environment and Its Application to the Portfolio Selection Process
Authors: Zhang Yutong , Zhou Wei , Luo Danxue , He Xiaorong
Published: November 2021

In the case of insufficient quantitative data, qualitative evaluation information is very important for investment decision-making. However, if it is completely based on qualitative evaluation information, the results may be subjective. In response to this problem, this paper proposes a method, namely, probabilistic hesitant fuzzy cross-efficiency evaluation (PHFCEE) method, based on probabilistic hesitant fuzzy theory, cross-efficiency data envelopment analysis (CEDEA). This method uses probabilistic hesitant fuzzy sets to collect qualitative evaluation information and then uses the cross-efficiency DEA model to fuse quantitative data and qualitative information. And finally, an investment portfolio is built based on the cross-efficiency value and its variance. In addition, this article gives the specific operating steps of the PHFCEE method and uses the construction of a portfolio of 10 stocks in the China CSI 300 Index as an example to illustrate the effectiveness of this method.
Application of Image Style Transfer Technology in Interior Decoration Design Based on Ecological Environment
Authors: Liu Shan , Bo Yun , Huang Lingling
Published: November 2021

With the further development of the social economy, people pay more attention to spiritual and cultural needs. As the main place of people’s daily life, the family is very important to the creation of its cultural atmosphere. In fact, China has fully entered the era of interior decoration, and people are paying more and more attention to decorative effects and the comfort and individual characteristics of decoration. Therefore, it is of practical significance to develop the application of decorative art in interior space design. However, the transfer effect of current interior decoration art design tends to be artistic, which leads to image distortion, and image content transfer errors are easy to occur in the process of transfer. The application of image style transfer in interior decoration art can effectively solve such problems. This paper analyzes the basic theory of image style transfer through image style transfer technology, Gram matrix, and Poisson image editing technology and designs images from several aspects such as image segmentation, content loss, enhanced style loss, and Poisson image editing constrained image spatial gradient. The application process of style transfer in interior decoration art realizes the application of image style transfer in interior decoration art. The experimental results show that the application of image style transmission in interior decoration art design can effectively avoid the contents of the interior decoration errors and distortions and has a good style transfer effect.
A Multiview SAR Target Recognition Method Using Inner Correlation Analysis
Authors: Lei Lei , Guo Dongen , Feng Zhihui
Published: November 2021

This paper proposes a synthetic aperture radar (SAR) image target recognition method using multiple views and inner correlation analysis. Due to the azimuth sensitivity of SAR images, the inner correlation between multiview images participating in recognition is not stable enough. To this end, the proposed method first clusters multiview SAR images based on image correlation and nonlinear correlation information entropy (NCIE) in order to obtain multiple view sets with strong internal correlations. For each view set, the multitask sparse representation is used to reconstruct the SAR images in it to obtain high‐precision reconstructions. Finally, the linear weighting method is used to fuse the reconstruction errors from different view sets and the target category is determined according to the fusion error. In the experiment, the tests are conducted based on the MSTAR dataset, and the results validate the effectiveness of the proposed method.
Pericardial Relapse of Acute Lymphoblastic Leukemia (ALL)
Authors: Maslov Diana V. , Badari Ambuga
Published: November 2021

Acute lymphoblastic leukemia (ALL) is a neoplasm of the B cell or T cell. Diagnosis is made by peripheral blood smear and bone marrow biopsy. Those with relapse/measurable residual disease (MRD) present with fever, weakness, fatigue, and easy bruising due to bone marrow infiltration (Kantarjian et al., 2017). A 59-year-old male with history of relapsed acute lymphoblastic leukemia and allogeneic stem cell transplant presented to the Emergency Department (ED) multiple times with shortness of breath. 2D Echo revealed recurrent pericardial effusion. His MRD was discovered in the pericardium. He underwent the creation of a pericardial window with cytology and culture which confirmed B cell lymphoblastic leukemia/lymphoma, consistent with relapsed disease. We present a case of a patient with B-ALL and MRD who presented with symptoms of shortness of breath. His MRD was discovered not in the bone marrow, but in the pericardium.
Length of Stay in Older Patients Undergoing Transcatheter Aortic Valve Replacement: Value of a Geriatric Approach
Authors: Bobet Anne Sophie , Brouessard Céline , Le Tourneau Thierry , Manigold Thibaut , de Decker Laure , Boureau Anne-Sophie
Published: November 2021

Background: For patients with transcatheter aortic valve replacement (TAVR), increased length of stay (LOS) is associated with increased long-term mortality. The main objective of our study was to analyze the association between geriatrics factors and the hospital LOS for older patients undergoing TAVR for severe aortic stenosis. Methods: This retrospective single-center study included all patients aged ≥75 who underwent TAVR between January 2018 and January 2019. Hospital LOS and postoperative complications were analyzed regarding the geriatric factors recorded during a systematic preoperative, comprehensive geriatric assessment (CGA). The individualized-care plans established after the preoperative CGA were also analyzed. Results: median LOS of the 196 patients included was 6 days (interquartile range: 4–8), and 29% of patients had prolonged LOS. In a multivariable analysis, the preoperative factors associated with a prolonged hospital LOS were EuroSCORE I (p value = 0.02), prior major neurocognitive disorders (p value = 0.01), femoral access (p value <0.001), all complications (p value <0.001), and discharge in a rehabilitation center (p value <0.001). One-fourth (27%) of the patients had at least 1 geriatric complication. After CGA, 69 patients did not need any geriatric recommendation, whereas for the 127 other patients, an individualized-care plan was established but only 46 (36%) of them were followed up. Conclusion: Our results favor the preoperative screening for major neurocognitive disorders in order to reduce LOS. Furthermore, the proposed individual-care plans after CGA were poorly followed. Practitioners may perceive the preoperative CGA as a screening tool, but its primary objective is to develop an individualized-care plan as a prehabilitation plan in order to optimize the physical, functional, and social issues.