bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Fe Dilution and W Dissolution on Abrasive Wear Resistance of NiCrBSi–WC Composite Hardfacing Deposited by Plasma Transferred arc Hardfacing
Authors: Wanare S. P. , Kalyankar V. D.
Published: November 2021

The control of Fe dilution and carbide dissolution plays a vital role on the performance of metal matrix composite hardfacings. In this paper, the NiCrBSi–WC composite hardfacing is deposited on 304 austenitic stainless steel by plasma transferred arc hardfacing at 120[Formula: see text]A (specimen 1) and 140[Formula: see text]A (specimen 2) transferred arc current values to obtain different levels of Fe dilution and W dissolution for comparative investigations. The Fe dilution examined by scanning electron microscopy for specimen 1 was 24.54% and for specimen 2 was 33.09%. The microstructural investigations revealed higher W dissolution for specimen 2 due to higher heat input which led to significant reduction in the amount of WC and W2C hard phases. The slurry abrasive wear test performed as per ASTM G105 showed two times reduction in abrasive wear resistance of specimen 2 as compared to specimen 1. The significant reduction in the performance of specimen 2 is mainly due to higher Fe dilution and higher W dissolution caused due to higher heat input. Hence, selection of appropriate process parameters is vital to control Fe dilution and carbide dissolution in order to achieve superior performance of composite hardfacings.
A classification of conformally flat generalized Ricci recurrent pseudo-Riemannian manifolds
Authors: Loo Tee-How , De Avik
Published: November 2021

Conformally flat pseudo-Riemannian manifolds with generalized Ricci recurrent, [Formula: see text] structure are completely classified in this short report. A conformally flat generalized Ricci recurrent pseudo-Riemannian manifold is shown to be an Einstein manifold. In particular, a conformally flat generalized Ricci recurrent spacetime must be either a de Sitter spacetime or an anti-de Sitter spacetime.
On edge-degree based invariants of graphs
Authors: Ashrafi Ali Reza , Ghalavand Ali
Published: November 2021

Let [Formula: see text] be a graph with edge set [Formula: see text]. For an edge [Formula: see text] in [Formula: see text], we define [Formula: see text], where [Formula: see text] and [Formula: see text] are degrees of vertices [Formula: see text] and [Formula: see text] in [Formula: see text], respectively. For [Formula: see text], the graph invariants [Formula: see text], [Formula: see text] and [Formula: see text] are defined as [Formula: see text], [Formula: see text] and [Formula: see text], where [Formula: see text] means that the edges [Formula: see text] and [Formula: see text] are incident. In this paper, some relationship between these graph invariants and some classical topological indices were presented. Moreover, some bounds for [Formula: see text], [Formula: see text] and [Formula: see text] are obtained and trees with the first through the third smallest [Formula: see text] and [Formula: see text], as well as the trees with the first through the forth smallest [Formula: see text] are also characterized.
A generalization of the (b,𝜃)-enriched contractions based on the degree of nondensifiability
Authors: García G.
Published: November 2021

Based on the so-called degree of nondensifiability, DND, we provide a generalization of the recently introduced [Formula: see text]-enriched contractions, as well as a fixed point existence result for this new class of mappings. From our main result, and under suitable conditions, we derive a result to state the existence of fixed points for the sum of two mappings, one of them being compact. Also, our main result is more general than the other fixed point theorem based on the DND.
Some strong convergence theorems for eigenvalues of general sample covariance matrices
Authors: Yin Yanqing
Published: November 2021

The aim of this paper is to investigate the spectral properties of sample covariance matrices under a more general population. We consider a class of matrices of the form [Formula: see text], where [Formula: see text] is a [Formula: see text] nonrandom matrix and [Formula: see text] is an [Formula: see text] matrix consisting of i.i.d standard complex entries. [Formula: see text] as [Formula: see text] while m can be arbitrary but no smaller than p. We first prove that under some mild assumptions, with probability 1, for all large n, there will be no eigenvalues in any closed interval contained in an open interval which is outside the supports of the limiting distributions for all sufficiently large n. Then we get the strong convergence result for the extreme eigenvalues as an extension of Bai-Yin law.
New Antimicrobial Nitro Heteroaryl-1,3,4-Thiadiazole Derivatives Containing Piperazinyl Benzonitrile Moiety: Synthesis and in silico Study
Authors: Tahghighi Azar , Aghaee Sara , Bakhteari Elnaz , Azerang Parisa , Abdouss Majid , Eslamifar Ali , Foroumadi AliReza
Published: November 2021

According to the antimicrobial activity of 1,3,4-thiadiazole compounds, a new series of derivatives was synthesized from the reaction of 5-nitro heteroaryl-1,3,4-thiadiazole with piperazinyl benzonitrile. The structure of the compounds was confirmed using Fourier transform infrared spectroscopy (FT-IR), proton nuclear magnetic resonance (1HNMR), and mass spectral data. The antimicrobial activities of the synthetic compounds against bacterial strains (Staphylococcus aureus and Escherichia coli) and fungal strains (Candida albicans and Saccharomyces Cerevisiae) showed compound E as the best antibacterial compound. After that, the molecular docking of the compounds with Escherichia coli dihydroorotase (PDB ID: 2EG7) and Klebsiella pneumoniae (PDB ID: 4OR7) was studied using ArgusLab software, which showed low binding energies [Formula: see text][Formula: see text]Kcal/mol and [Formula: see text][Formula: see text]Kcal/mol, respectively. Finally, the prediction of their drug-likeness by the assessment of some physical and chemical properties such as hydrogen bond donor/acceptor properties, water solubility, lipophilicity and acute oral toxicity acknowledged their drug-like properties.
Impact of modelling decisions and rock typing schemes on oil in place estimates in a giant carbonate reservoir in the Middle East
Authors: AlBreiki Mohamed , Geiger Sebastian , Corbett Patrick
Published: November 2021

We demonstrate how modelling decisions for a giant carbonate reservoir with a thick transition zone in the Middle East, most notably the approach to reservoir rock typing and modelling the initial fluid saturations, impact the hydrocarbon distributions and oil-in-place estimates in the reservoir. Rather than anchoring our model around a single base case with an upside and downside, we apply a comprehensive 3D multiple deterministic scenario workflow to compare-and-contrast how modelling decisions and geological uncertainties influence the volumetric estimates. We carry out a detailed analysis which shows that the variations in STOIIP estimates can be as high as 28% depending on the preferred modelling decision, which could potentially mask the impact of other geological uncertainties. These models were validated through repeated and randomised blind tests. We hence present a quantitative approach that helps us to assess if the static models are consistent in terms of the integration of geological and petrophysical data. Ultimately, the decision which of the different modelling options should be applied does not only influence STOIIP estimates, but also subsequent history matching & forecasts.
Denigrate Comment Detection in Low-Resource Hindi Language Using Attention-Based Residual Networks
Authors: Sangwan Saurabh R. , Bhatia M. P. S.
Published: November 2021

Cyberspace has been recognized as a conducive environment for use of various hostile, direct, and indirect behavioural tactics to target individuals or groups. Denigration is one of the most frequently used cyberbullying ploys to actively damage, humiliate, and disparage the online reputation of target by sending, posting, or publishing cruel rumours, gossip, and untrue statements. Previous pertinent studies report detecting profane, vulgar, and offensive words primarily in the English language. This research puts forward a model to detect online denigration bullying in low-resource Hindi language using attention residual networks. The proposed model Hindi Denigrate Comment–Attention Residual Network (HDC-ARN) intends to uncover defamatory posts (denigrate comments) written in Hindi language which stake and vilify a person or an entity in public. Data with 942 denigrate comments and 1499 non-denigrate comments is scraped using certain hashtags from two recent trending events in India: Tablighi Jamaat spiked Covid-19 (April 2020, Event 1) and Sushant Singh Rajput Death (June 2020: Event 2). Only text-based features, that is, the actual content of the post, are considered. The pre-trained word embedding for Hindi language from fastText is used. The model has three ResNet blocks with an attention layer that generates a post vector for a single input, which is passed through a sigmoid activation function to get the final output as either denigrate (positive class) or non-denigrate (negative class). An F-1 score of 0.642 is achieved on the dataset.
A Deep Content-Based Model for Persian Rumor Verification
Authors: Jahanbakhsh-Nagadeh Zoleikha , Feizi-Derakhshi Mohammad-Reza , Sharifi Arash
Published: November 2021

During the development of social media, there has been a transformation in social communication. Despite their positive applications in social interactions and news spread, it also provides an ideal platform for spreading rumors. Rumors can endanger the security of society in normal or critical situations. Therefore, it is important to detect and verify the rumors in the early stage of their spreading. Many research works have focused on social attributes in the social network to solve the problem of rumor detection and verification, while less attention has been paid to content features. The social and structural features of rumors develop over time and are not available in the early stage of rumor. Therefore, this study presented a content-based model to verify the Persian rumors on Twitter and Telegram early. The proposed model demonstrates the important role of content in spreading rumors and generates a better-integrated representation for each source rumor document by fusing its semantic, pragmatic, and syntactic information. First, contextual word embeddings of the source rumor are generated by a hybrid model based on ParsBERT and parallel CapsNets. Then, pragmatic and syntactic features of the rumor are extracted and concatenated with embeddings to capture the rich information for rumor verification. Experimental results on real-world datasets demonstrated that the proposed model significantly outperforms the state-of-the-art models in the early rumor verification task. Also, it can enhance the performance of the classifier from 2% to 11% on Twitter and from 5% to 23% on Telegram. These results validate the model's effectiveness when limited content information is available.
RWRoute: An Open-source Timing-driven Router for Commercial FPGAs
Authors: Zhou Yun , Maidee Pongstorn , Lavin Chris , Kaviani Alireza , Stroobandt Dirk
Published: November 2021

One of the key obstacles to pervasive deployment of FPGA accelerators in data centers is their cumbersome programming model. Open source tooling is suggested as a way to develop alternative EDA tools to remedy this issue. Open source FPGA CAD tools have traditionally targeted academic hypothetical architectures, making them impractical for commercial devices. Recently, there have been efforts to develop open source back-end tools targeting commercial devices. These tools claim to follow an alternate data-driven approach that allows them to be more adaptable to the domain requirements such as faster compile time. In this paper, we present RWRoute, the first open source timing-driven router for UltraScale+ devices. RWRoute is built on the RapidWright framework and includes the essential and pragmatic features found in commercial FPGA routers that are often missing from open source tools. Another valuable contribution of this work is an open-source lightweight timing model with high fidelity timing approximations. By leveraging a combination of architectural knowledge, repeating patterns, and extensive analysis of Vivado timing reports, we obtain a slightly pessimistic, lumped delay model within 2% average accuracy of Vivado for UltraScale+ devices. Compared to Vivado, RWRoute results in a 4.9× compile time improvement at the expense of 10%
Quality of Results (QoR)
loss for 665 synthetic and six real designs. A main benefit of our router is enabling fast partial routing at the back-end of a domain-specific flow. Our initial results indicate that more than 9× compile time improvement is achievable for partial routing. The results of this paper show how such a router can be beneficial for a
low touch
flow to reduce dependency on commercial tools.
The Hubbard Model: A Computational Perspective
Authors: Qin Mingpu , Schäfer Thomas , Andergassen Sabine , Corboz Philippe , Gull Emanuel
Published: November 2021

The Hubbard model is the simplest model of interacting fermions on a lattice and is of similar importance to correlated electron physics as the Ising model is to statistical mechanics or the fruit fly to biomedical science. Despite its simplicity, the model exhibits an incredible wealth of phases, phase transitions, and exotic correlation phenomena. Although analytical methods have provided a qualitative description of the model in certain limits, numerical tools have shown impressive progress in achieving quantitative accurate results over the past several years. This article gives an introduction to the model, motivates common questions, and illustrates the progress that has been achieved over recent years in revealing various aspects of the correlation physics of the model.
How Many Cell Types Are in the Kidney and What Do They Do?
Authors: Balzer Michael S. , Rohacs Tibor , Susztak Katalin
Published: November 2021

The kidney maintains electrolyte, water, and acid-base balance, eliminates foreign and waste compounds, regulates blood pressure, and secretes hormones. There are at least 16 different highly specialized epithelial cell types in the mammalian kidney. The number of specialized endothelial cells, immune cells, and interstitial cell types might even be larger. The concerted interplay between different cell types is critical for kidney function. Traditionally, cells were defined by their function or microscopical morphological appearance. With the advent of new single-cell modalities such as transcriptomics, epigenetics, metabolomics, and proteomics we are entering into a new era of cell type definition. This new technological revolution provides new opportunities to classify cells in the kidney and understand their functions.
Design of Online Music Teaching System Based on B/S Architecture
Authors: Dai Dan Dan
Published: November 2021

Under the global epidemic situation, offline face-to-face teaching has not adapted to the current teaching environment. Using computer technology to carry out online assisted teaching has become an inevitable choice for music teaching in colleges and universities. Offline teaching also has many disadvantages, such as single and backward teaching methods, poor sharing of audio-visual resources, and inconsistent teaching contents. The survey found that music teachers urgently need an online teaching platform to enable teachers to obtain effective, standardized, and comprehensive teaching resources anytime and anywhere so that students can enjoy high-quality music teaching resources as much as possible. Based on these requirements, the development of online music teaching system under B/S architecture has an important practical significance.
Early‐Life Exposure to Low‐Dose Cadmium Accelerates Diethylnitrosamine and Diet‐Induced Liver Cancer
Authors: Men Hongbo , Young Jamie L. , Zhou Wenqian , Zhang Haina , Wang Xiang , Xu Jianxiang , Lin Qian , Tan Yi , Zheng Yang , Cai Lu
Published: November 2021

Maternal exposure to cadmium causes obesity and metabolic changes in the offspring, including nonalcoholic fatty liver disease‐like pathology. However, whether maternal cadmium exposure accelerates liver cancer in the offspring is unknown. This study investigated the impact of early‐life exposure to cadmium on the incidence and potential mechanisms of hepatocellular carcinoma (HCC) in offspring subjected to postweaning HCC induction. HCC in C57BL/6J mice was induced by diethylnitrosamine (DEN) injection at weaning, followed by a long‐term high‐fat choline‐deficient (HFCD) diet. Before weaning, liver cadmium levels were significantly higher in mice with early‐life cadmium exposure than in those without cadmium exposure. However, by 26 and 29 weeks of age, hepatic cadmium fell to control levels, while a significant decrease was observed in copper and iron in the liver. Both male and female cadmium‐exposed mice showed increased body weight compared to non‐cadmium‐treated mice. For females, early‐life cadmium exposure also worsened insulin intolerance but did not significantly promote DEN/HFCD diet‐induced liver tumors. In contrast, in male mice, early‐life cadmium exposure enhanced liver cancer induction by DEN/HFCD with high incidence and larger liver tumors. The liver peritumor tissue of early‐life cadmium‐exposed mice exhibited greater inflammation and disruption of fatty acid metabolism, accompanied by higher malondialdehyde and lower esterified triglyceride levels compared to mice without cadmium exposure. These findings suggest that early‐life exposure to low‐dose cadmium accelerates liver cancer development induced by a DEN/HFCD in male mice, probably due to chronic lipotoxicity and inflammation caused by increased uptake but decreased consumption of fatty acids.
Electric Transverse Emissivity of Sinusoidal Surfaces Determined by a Differential Method: Comparison with Approximation of Geometric Optics
Authors: Ghabara Taoufik
Published: November 2021

We present in this paper a numerical study of the validity limit of the optics geometrical approximation in comparison with a differential method which is established according to rigorous formalisms based on the electromagnetic theory. The precedent studies show that this method is adopted to the study of diffraction by periodic rough surfaces. For periods much larger than the wavelength, the mechanism is analog to what happens in a cavity where a ray is trapped and undergoes a large number of reflections. For gratings with a period much smaller than the wavelength, the roughness essentially behaves as a transition layer with a gradient of the optical index. Such a layer reduces the reflection there by increasing the absorption. The code has been implemented for TE polarization. We determine by the two methods such as differential method and the optics geometrical approximation the emissivity of gold and tungsten cylindrical surfaces with a sinusoidal profile, for a wavelength equal to 0.55 microns. The obtained results for a fixed height of the grating allowed us to delimit the validity domain of the optic geometrical approximation for the treated cases. The emissivity calculated by the differential method and that given on the basis of the homogenization theory are satisfactory when the period is much smaller than the wavelength.
[Retracted] A Retrospective Study on the Efficacy of Two Different Rehabilitation Interventions on KOA: Shock Wave Therapy vs. Electroacupuncture Therapy
Authors: Zhao Yuhui , Wang Xuebing , Zhang Dianquan
Published: November 2021

Objective. In this paper, we retrospectively reviewed the difference in clinical effectiveness of shock wave therapy and electroacupuncture therapy on knee osteoarthritis. Methods. A total of 128 treatment cases of knee osteoarthritis patients were extracted from the medical record system of Shenzhen Longhua District Central Hospital during the period from January 1, 2018, to January 30, 2020. The cases were divided into three groups for different treatments: shock wave group (n = 54), electroacupuncture group (n = 41), and control group (n = 33). The shock wave group was given shock wave therapy combined basis clinical treatment; meanwhile, the electroacupuncture group was given electroacupuncture on the basis of actual clinical treatment. The control group was given conventional topical nonsteroidal anti‐inflammatory drugs (Voltaren). Osteoarthritis index scale, NRS scale, and WHOQOL‐BREF were observed before treatment, after 2 weeks, and 4 weeks after treatment. Results. This study found that the osteoarthritis index scale and NRS scale of the shock wave group and the electroacupuncture group were lower than those before treatment; it had significant difference (P < 0.001). In WHOQOL‐BREF, the shock wave group and the electroacupuncture group improved significantly four weeks after treatment (P < 0.001), which was statistically different from the conventional group (P = 0.04). Conclusion. Physical and rehabilitation medicine treatment (shock wave therapy) and traditional medical treatment (electroacupuncture) have better clinical effects on knee osteoarthritis, compared with conventional treatment. Shock wave and electric acupuncture have no apparent adverse reaction, suggesting that the treatment is safe and effective.
Fault Diagnosis of Data-Driven Photovoltaic Power Generation System Based on Deep Reinforcement Learning
Authors: Dai Shuang , Wang Dingmei , Li Weijun , Zhou Qiang , Tian Guangke , Dong Haiying
Published: November 2021

Aiming at the problem of fault diagnosis of the photovoltaic power generation system, this paper proposes a photovoltaic power generation system fault diagnosis method based on deep reinforcement learning. This method takes data-driven as the starting point. Firstly, the compressed sensing algorithm is used to fill the missing photovoltaic data and then state, action, strategy, and return functions from the environment. Based on the interaction rules and other factors, the fault diagnosis model of the photovoltaic power generation system is established, and the deep neural network is used to approximate the decision network to find the optimal strategy, so as to realize the fault diagnosis of the photovoltaic power generation system. Finally, the effectiveness and accuracy of the method are verified by simulation. The simulation results show that this method can accurately diagnose the fault types of the photovoltaic power generation system, which is of great significance to enhance the security of the photovoltaic power generation system and improve the intelligent operation and maintenance level of the photovoltaic power generation system.
Experimental Investigation of a Novel Extracting Water System from Air by Soil Cold Source
Authors: Yao Jianan , Wang Xingtian , Zhu Junfeng , Wang Binbin , Niu Junkui
Published: November 2021

The distribution of fresh water resources is extremely uneven at home and abroad, and the air contains a large amount of water vapor that can be used, so air water has been a widespread concern. Air condensation method is simple and efficient and has strong water intake capacity, but it often needs to consume huge energy. Therefore, this work proposes a new simple and innovative method of drawing water from the air, based on extracting water from air process achieved by using the soil as the cold source. The new type of ground cold air water intake system is designed by the new innovative method, which uses the soil with constant temperature as the cold source to reduce energy consumption. By comparing the central composite design experiment with the field experiment and analyzing the condensate water and outlet temperature under different wind speed and humidity conditions, the quadratic equation expression of condensate water and outlet temperature is obtained, and the optimal import wind speed range under a certain humidity range is obtained according to the mathematical model. The experimental results show that the heat transfer effect between air and soil is ideal, the water intake can reach 2.2 kg in 20-hour continuous collection experiment, the air temperature is close to the soil temperature after cooling, and the effect of water intake is good, which confirms the feasibility of soil as a cold source of air condensation.
Closed-Form Solution of a Rational Difference Equation
Authors: Ibrahim Tarek F. , Khan Abdul Qadeer , Oğul Burak , Şimşek Dağistan
Published: November 2021

In this paper, we study the solution of the difference equation

Ω

m
+
1

=

Ω

m
−

7
q
+
6

/

1
+

∏

t
=
0

5

Ω

m
−

q
+
1

t
−
q

, where the initials are positive real numbers.
Privacy-Aware Data Forensics of VRUs Using Machine Learning and Big Data Analytics
Authors: Babar Muhammad , Tariq Muhammad Usman , Almasoud Ahmed S. , Alshehri Mohammad Dahman
Published: November 2021

The present spreading out of big data found the realization of AI and machine learning. With the rise of big data and machine learning, the idea of improving accuracy and enhancing the efficacy of AI applications is also gaining prominence. Machine learning solutions provide improved guard safety in hazardous traffic circumstances in the context of traffic applications. The existing architectures have various challenges, where data privacy is the foremost challenge for vulnerable road users (VRUs). The key reason for failure in traffic control for pedestrians is flawed in the privacy handling of the users. The user data are at risk and are prone to several privacy and security gaps. If an invader succeeds to infiltrate the setup, exposed data can be malevolently influenced, contrived, and misrepresented for illegitimate drives. In this study, an architecture is proposed based on machine learning to analyze and process big data efficiently in a secure environment. The proposed model considers the privacy of users during big data processing. The proposed architecture is a layered framework with a parallel and distributed module using machine learning on big data to achieve secure big data analytics. The proposed architecture designs a distinct unit for privacy management using a machine learning classifier. A stream processing unit is also integrated with the architecture to process the information. The proposed system is apprehended using real-time datasets from various sources and experimentally tested with reliable datasets that disclose the effectiveness of the proposed architecture. The data ingestion results are also highlighted along with training and validation results.
Third Trimester Lower Extremity Lymphorrhea
Authors: Morimoto Kaori , O’Rourke Luke
Published: November 2021

Introduction. Lower extremity edema is one of the most common complaints among pregnant patients. However, there is no literature mentioning weeping edema (i.e., lymphorrhea) in a pregnant woman who has no concordant underlying renal and/or cardiac pathology. There is also a lack of evidence and recommendations regarding the therapeutic benefit and safety profile of diuretic use to treat profound pregnancy-associated edema. Herein, we present the case of 32-year-old female who presented with a significant lymphorrhea during the third trimester without cardiac or renal comorbidity and was successfully treated with torsemide. Case Report. We report a case of a 32-year-old multigravida patient pregnant with her third child and has two living full-term children (G3P2003). Her pregnancy was complicated by obesity, smoking (vape), and previous history of fetal growth restriction. The patient presented for routine prenatal care at 9-week gestation. She was diagnosed with chronic hypertension at 19 weeks of pregnancy based upon systolic blood

pressure
>
140

. Lifestyle modifications were recommended, but the patient did not comply. At her 31-week office visit, the patient presented with anasarca and clear, slightly viscous fluid seeping through the atraumatic skin of her lower extremities. Preeclampsia, renal, cardiac, vascular, and infectious complications were all ruled out. The patient responded positively to loop diuretic therapy. Torsemide was found to be far more beneficial than furosemide. The patient was induced at 37 weeks secondary to chronic hypertension requiring antihypertensive therapy. Delivery was uncomplicated. The patient gave birth to a healthy male with birth weight of 2,920 g via spontaneous vaginal delivery. Discussion. Pitting edema of lower limbs frequently occurs as a result of fluid overload and chronic venous insufficiency, and pregnancy is one of the known risk factors. Additionally, the blockage of lymphatic channel with the gravida uterus likely was the main contributing factor for her lymphorrhea. In this patient, the capillary hydrostatic pressure was likely accentuated due to hypertension, obesity, and vaping. Furosemide was minimally effective to alleviate her symptoms. Torsemide provided much more effective diuresis and symptom control. However, her symptoms persisted until delivery. Conclusion. Torsemide provided significant therapeutic benefit over furosemide in this patient without adverse maternal, fetal, or neonatal outcomes. Further study is needed to assess the safe use of loop diuretics in the pregnant population who suffers from significant lower extremity edema.
Nonlinear Characteristics of the Effect of Manufacturing Servitization on Consumer Business Performance
Authors: Long Guoqiong , Li Chong , Li Shuai , Xu Tianxiang
Published: November 2021

Servitization is an important trend in the transformation and upgrading of the manufacturing industry, but whether it can significantly improve enterprise performance is the key to the transformation. Based on the sample of Chinese A-share listed companies from 2011 to 2019, we analyze the business scope of 2502 annual reports to identify the service level of consumer goods manufacturing enterprises. The results show the following. (1) The “service performance” curve shows obvious nonlinear trends and heterogeneity in different industries and different performance conditions. The curve between servitization and return on assets tends to show a positive “U” shape, but the relationship between servitization and revenue per employee obviously shows an inverted “U” shape. (2) Manufacturing enterprises with relatively low technical complexity and relatively high industry competition will reach the inflection point of service performance “U” curve more quickly and get rid of “service trap” more easily. (3) The automobile manufacturing industry invests in software development and other fields that are not related to its own advantages, which violates the correlation law of the industrial value chain, leading to the coexistence of “service trap” and “principle-agent dilemma.” The clothing and electrical appliances industries are more likely to fall into the “service trap” because they face the challenge of “Internet + manufacturing” transformation. The beverage and wine manufacturing industry has induced a “service spillover” effect, which is mainly due to its low technical complexity and service based on the industrial chain. It is proposed that manufacturing enterprises explore business growth points from the perspective of industrial value chain extension and strengthen upstream product R&D and terminal e-commerce services.
A Novel Method for Navigational Risk Assessment in Wind Farm Waters Based on the Fuzzy Inference System
Authors: Lv Peilin , Zhen Rong , Shao Zheping
Published: November 2021

Offshore wind power is an effective way to solve the energy crisis problem and achieve sustainable economic development. Aiming at the problems that the navigational risk of ships in the waters of offshore wind farms is difficult to quantify due to complex factors, this paper proposes a method of navigational risk assessment in the waters of offshore wind farms based on a fuzzy inference system. Firstly, through the analysis of the factors affecting the navigation system of wind farm waters, it is found that the navigational risk is affected by natural factors and navigational environment factors. Then, the visibility, the number of traffic flows, the number of encounter areas, and the distance between the sailing route and the wind farm are extracted to evaluate the risk of natural factors and the risk of the sailing environment in the navigation system of the wind farm waters, respectively. Considering the mutual influence of the factors, the fuzzy inference rules of navigational risk influence are established according to the expert experience, and a method of navigational risk assessment based on the fuzzy inference system in offshore wind farm waters is developed. In order to verify the effectiveness of the proposed method, a comprehensive evaluation of the navigational risk of wind farm waters in Changle offshore sea of Fujian Province is carried out, and the evaluation results are consistent with the actual situation. The proposed method has important theoretical significance for the navigational safety supervision of offshore wind farm waters.
Analysis and Evaluation of CDPR Cable Sagging Based on ANFIS
Authors: Tho Tuong Phuoc , Thinh Nguyen Truong
Published: November 2021

The cable sagging problem of cable-driven parallel robots (CDPRs) is very complicated, because several models for calculating cable sag based on the well-known catenary equation have been studied, but time and computational efficiency are a problem to be solved. There is still no simple mathematical model to calculate cable sag by considering all relevant conditions due to the complexity and nonlinearity of the cable sagging model, which involves many dominant variables and their influence on the position accuracy of CDPRs. In this study, we proposed an ANFIS (adaptive neuro-fuzzy inference system) architecture to estimate cable sag for large-sized CDPRs. The ANFIS model can be used to solve nonlinear functions and detect nonlinear factors online in the control system; this characteristic is consistent with the nonlinear model of cable sag. The trained data for ANFIS models were taken from calculation results by Trust-Region-Dogleg algorithm based on two cable tension calculation algorithms as Dual Simplex Algorithm and Force Distribution in Closed Form. Cable sagging data obtained from ANFIS and Trust-Region-Dogleg algorithm are compared and evaluated by statistical factors of evaluations consisting of root-mean-square error, correlation coefficients, and scatter index. The analytical results show that the ANFIS gave computed results with small errors and can be applied to predict cable sagging for any CDPR configuration, with the advantage of fast calculation time and high precision. The results of these models are also applied on a CDPR that contains two redundant actuators.
Effect of the WeChat Platform Health Management and Refined Continuous Nursing Model on Life Quality of Patients with Acute Myocardial Infarction after PCI
Authors: Xu Meifang , Yang Xiaofang , Liu Lin , Dai Yunlang , Xu Mingzhu , Shi Lin
Published: November 2021

The purpose was to explore the effect of the WeChat platform health management and refined continuous nursing model on life quality of patients with acute myocardial infarction (AMI) after PCI. 100 AMI patients treated in the cardiovascular medicine of the First Affiliated Hospital of Soochow University from June 2018 to June 2019 were selected as the study subjects and randomly divided into research group and reference group, with 50 cases in each group. The reference group received routine nursing after PCI, while the research group received WeChat platform health management and continuous refined nursing. There were no significant differences in sex ratio, age, BMI, complications, education level, and residence between the two groups of patients (

P
>
0.05

). The MPR values of patients in the two groups after intervention were significantly higher than those before intervention (

P
<
0.05

), and the MPR value in the research group after intervention was significantly higher than that in the reference group (

P
<
0.05

). The SF-36 scores of patients in the two groups after intervention were significantly higher than those before intervention (

P
<
0.001

), and the SF-36 score in the research group after intervention was higher than that in the reference group (

P
<
0.001

). The emotional, physical, and economic dimensions of patients in the research group after intervention were significantly lower than those in the reference group (

P
<
0.001

). The HAMA and HAMD scores of patients in the research group after intervention were significantly lower than those in the reference group (

P
<
0.001

). The nursing satisfaction score of patients in the research group was significantly higher than that in the reference group (

P
<
0.001

). The total incidence of complications of patients in the research group after intervention was significantly lower than that in the reference group (

P
<
0.05

). The WeChat platform health management and refined continuous nursing model can effectively improve the medication compliance of patients after PCI, improve the life quality, alleviate depression and anxiety, and reduce postoperative complications, with a definite effect, which is worthy of promotion and application.
Facilitators’ Engagement in Advocacy towards Inclusion of Adults with Disabilities in the Literacy Training Program in Gedeo Zone, Ethiopia
Authors: Matsana Damene , Negassa Dawit , Seyoum Yilfashewa , Tekle Asmerom
Published: November 2021

The study aimed at investigating facilitators’ engagement in advocacy towards inclusion of adults with disabilities in the literacy training program in the Gedeo Zone, Ethiopia. A mixed-methods approach with the explanatory sequential design was employed. The study involved a sample of 214 facilitators by using stratifying random sampling technique. A Likert-type scale questionnaire was administered to the facilitators with a response rate of 98.6% (N = 211). In addition, a total of 13 respondents (3 principals, 3 supervisors, 3 adults with disabilities, and 4 experts) were selected purposively for interview based on their active participation in the program. The quantitative data were analyzed using SPSS version 23, while the qualitative data were analyzed using narrative analysis. The results from both the quantitative and qualitative strands revealed that facilitators are engaged in advocacy services by providing awareness-raising training to speak up about them, by sensitizing the community, by working collaboratively with the colleagues and the local government to make the training environment accessible to all adults. Pearson’s correlation coefficient for providing an awareness-raising training (r (211) = 0.683

∗∗

,

p
<
0.01

), working collaboratively with colleagues (r (211) = 0.754

∗∗

,

p
<
0.01

), working collaboratively with the local governments (r (211) = 0.766

∗∗

,

p
<
0.01

), and participating in the community sensitization programs (r (211) 0.821

∗∗

,

p
<
0.01

) showed that the items are statistically significant and positively correlated.
Research on the Influence Mechanism of the Across-Industrial-Chain Investment Speed on Innovation Performance of AI Enterprises: Improvement Path of Artificial Intelligence Technology Application
Authors: Chen Yan , Si Fan , Lu Xiying , Li Xin
Published: November 2021

This paper presents a regression analysis by using the system generalized method of moments (SYS-GMM) model as the main regression model and combining it with the fixed effect of panel data and acquires the basic empirical research data from Wind database. The research shows that the speed of cross-industrial-chain investment can improve the innovation ability of AI enterprises, and AI enterprises with deep technology accumulation can improve their innovation performance in the rapid across-industrial-chain investment. In this paper, an across-industrial-chain investment decision path model for AI enterprises is proposed for the first time, suggesting that AI enterprises should pay attention to the related factors of industry and AI enterprises when making across-industrial-chain investment decisions. This helps to express the determination of investment, integration, and reconstruction to the target AI enterprises, and it can also facilitate fast across-industrial-chain investment and improve the innovation performance of AI enterprises.
Mechanical and Formability Evaluation of ST14 Alloys Welded by Friction Stir Welding
Authors: Afshari Mahmoud , Fakhralmobasheri Nima , Samadi Mohammad Reza , Alavi Amirhossein , Foroushani Hossein Norozi
Published: November 2021

Friction stir welding as one of the modern methods of solid‐state welding of steel sheets and aluminum is a highly regarded industry. In these studies, the experimental design and response surface methodology were used. Optimization of experimental conditions and results which are compared with good agreement between the results was observed. The mechanical properties and ductility of welded plates under optimal conditions were studied. Microhardness testing, metallography, tensile testing, and limiting dome height were used to investigate the mechanical properties and formability limit diagram attached, respectively. The results showed that the heat‐affected zone is very small and narrow and not easily distinguished from the base metal. In all tests, the failure of the dome height limit in the area was chaos. In all samples welded with the optimal parameters, tensile failure occurred in the base metal region. Turbulence in the region confirms the presence of WC particles. Experimental design and response surface methodology could introduce an optimal state, and the creation of common defects in the FSW process can prevent the binding strength of the guarantee. But due to the lack of proper stirring in the perturbation area in the samples welded with non‐optimized parameters, the strength of the connection is not suitable, and samples were broken from the SZ region.
Trajectory Planning for Emergency Landing of VTOL Fixed-Wing Unmanned Aerial Vehicles
Authors: Deng Zhao , Guo Zhiming , Wu Liaoni , You Yancheng
Published: November 2021

In recent years, inspired by technological progress and the outstanding performance of Unmanned Aerial Vehicles (UAVs) in several local wars, the UAV industry has witnessed explosive development, widely used in communication relay, logistics, surveying and mapping, patrol, surveillance, and other fields. Vertical Take-Off and Landing fixed-wing UAV has both the advantages of vertical take-off and landing of rotorcraft and the advantages of long endurance of fixed-wing UAV, which broadened its application field and is the most popular UAV at present. Recently, fixed-wing UAV failure analysis highlights that cruise engine shutdown is the most common reason for emergency landing, which is also a governing factor for Vertical Take-Off and Landing (VTOL) fixed-wing UAV failures. Nevertheless, the emergency landing trajectory of the latter UAV type after engine shutdown is different from that of the conventional fixed-wing UAVs due to the VTOL power system. Hence, spurred by the requirement of a safe emergency landing trajectory for VTOL fixed-wing UAVs, this paper develops an architecture capable of safe emergency landing for such platforms. The suggested method develops a particle dynamics model of the VTOL UAV and analyzes its aerodynamic characteristics utilizing Computational Fluid Dynamics (CFD) results. The UAV’s trajectory is divided into three parts for enhanced planning. For the guidance stage, the initial position and heading angle are arbitrary. Hence, the Dubins shortest cross-range and the fastest descent trajectory are adopted to steer the UAV above the landing window quickly. The spiral stage comprises a conical and cylindrical part combined with a spiral descent trajectory of variable radius for energy management and landing course alignment. Given the limited energy storage of VTOL power systems, the landing stage exploits an optimal control trajectory problem solved by a Gaussian pseudospectral method, involving trajectory conventional landing planning, unpowered landing, distance optimal landing, and wind-resistant landing. All trajectories meet the dynamics constraints, terminal constraints, and sliding performance constraints and cover both 2-dimensional and 3-dimensional trajectories. A large number of simulation experiments demonstrate that the proposed trajectories manage broad applicability and strong feasibility for VTOL fixed-wing UAVs.
Research on Enterprise Financial Customer Classification Method and Preference Based on Intelligent Algorithm
Authors: Fu Ze , Zhang Bo , Ou Lingjun , Sun Kaiyang , Sun Xinyi , Chen Ningyan
Published: November 2021

Compared with the past questionnaire survey, this paper applies the intelligent algorithm developed rapidly in recent years to identify the tendency of customers to buy financial products in the market. In addition, for the single state customer classification indicators based on the previous demographic information and action information, it is proposed to combine the action of market activities with demographic information; that is, the static integrated customer classification index is further combined with the improved neural network model to study the classification and preference of enterprise financial customers. Firstly, the enterprise financial customer classification model based on neural network algorithm is studied. Aiming at the shortcomings of easy falling into the local optimal solution of neural network algorithm, slow convergence speed of algorithm, and difficult setting of network structure, combined with the characteristics of genetic algorithm, the concept of adaptive genetic neural network algorithm is proposed. Then, the design of adaptive genetic neural network model is studied. Secondly, combined with the customer data of a financial enterprise and the characteristics of enterprise finance, this paper analyzes the risk influencing factors of enterprise financial customers, analyzes the customer data, evaluates the enterprise financial customers through the adaptive genetic neural network model, and realizes the classification of enterprise financial customers. Through an example, it is proved that the enterprise financial customer classification and preference model based on the adaptive genetic neural network algorithm discussed in this paper has better customer classification accuracy and can provide better method support for enterprise financial customer management.
Improved Verifier-Based Three-Party Password-Authenticated Key Exchange Protocol from Ideal Lattices
Authors: Tang Yongli , Li Ying , Zhao Zongqu , Zhang Jing , Ren Lina , Li Yuanhong
Published: November 2021

With the advent of large-scale social networks, two communication users need to generate session keys with the help of a remote server to communicate securely. In the existing three-party authenticated key exchange (3PAKE) protocols, users’ passwords need to be stored on the server; it cannot resist the server disclosure attack. To solve this security problem, we propose a more efficient 3PAKE protocol based on the verification element by adopting a public-key cryptosystem and approximate smooth projection hash (ASPH) function on an ideal lattice. Using the structure of separating authentication from the server, the user can negotiate the session key only after two rounds of communication. The analysis results show that it can improve the efficiency of computation and communication and resist the server disclosure attack, quantum algorithm attack, and replay attack; moreover, it has session key privacy to the server. This protocol can meet the performance requirement of the current communication network.