bluuebunny/crossref_metadata_2025 huggingface dataset:
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: The Migration Games in Deduplicated Systems
Authors: Kisous Roei , Kolikant Ariel , Duggal Abhinav , Sheinvald Sarai , Yadgar Gala
Published: September 2022

Deduplication reduces the size of the data stored in large-scale storage systems by replacing duplicate data blocks with references to their unique copies. This creates dependencies between files that contain similar content and complicates the management of data in the system. In this article, we address the problem of data migration, in which files are remapped between different volumes as a result of system expansion or maintenance. The challenge of determining which files and blocks to migrate has been studied extensively for systems without deduplication. In the context of deduplicated storage, however, only simplified migration scenarios have been considered.

In this article, we formulate the general migration problem for deduplicated systems as an optimization problem whose objective is to minimize the system’s size while ensuring that the storage load is evenly distributed between the system’s volumes and that the network traffic required for the migration does not exceed its allocation.

We then present three algorithms for generating effective migration plans, each based on a different approach and representing a different trade-off between computation time and migration efficiency. Our
greedy algorithm
provides modest space savings but is appealing thanks to its exceptionally short runtime. Its results can be improved by using larger system representations. Our
theoretically optimal algorithm
formulates the migration problem as an integer linear programming (ILP) instance. Its migration plans consistently result in smaller and more balanced systems than those of the greedy approach, although its runtime is long and, as a result, the theoretical optimum is not always found. Our
clustering algorithm
enjoys the best of both worlds: its migration plans are comparable to those generated by the ILP-based algorithm, but its runtime is shorter, sometimes by an order of magnitude. It can be further accelerated at a modest cost in the quality of its results.
A Generalized Realizability and Intuitionistic Logic
Authors: Konovalov Aleksandr
Published: September 2022

Let
V
be a set of number-theoretical functions. We define a notion of
V
-realizability for predicate formulas in such a way that the indices of functions in
V
are used for interpreting the implication and the universal quantifier. In this article, we prove that Intuitionistic Predicate Calculus is sound with respect to the semantics of
V
-realizability if and only if some natural conditions for
V
hold.
RNA-Based Vaccination of Plants for Control of Viruses
Authors: Voloudakis Andreas E. , Kaldis Athanasios , Patil Basavaprabhu L.
Published: September 2022

Plant viruses cause nearly half of the emerging plant diseases worldwide, contributing to 10–15% of crop yield losses. Control of plant viral diseases is mainly accomplished by extensive chemical applications targeting the vectors (i.e., insects, nematodes, fungi) transmitting these viruses. However, these chemicals have a significant negative effect on human health and the environment. RNA interference is an endogenous, cellular, sequence-specific RNA degradation mechanism in eukaryotes induced by double-stranded RNA molecules that has been exploited as an antiviral strategy through transgenesis. Because genetically modified crop plants are not accepted for cultivation in several countries globally, there is an urgent demand for alternative strategies. This has boosted research on exogenous application of the RNA-based biopesticides that are shown to exhibit significant protective effect against viral infections. Such environment-friendly and efficacious antiviral agents for crop protection will contribute to global food security, without adverse effects on human health.
A Trait-Based Approach to Predicting Viral Host-Range Evolvability
Authors: Strobel Hannah M. , Stuart Elizabeth C. , Meyer Justin R.
Published: September 2022

Predicting the evolution of virus host range has proven to be extremely difficult, in part because of the sheer diversity of viruses, each with unique biology and ecological interactions. We have not solved this problem, but to make the problem more tractable, we narrowed our focus to three traits intrinsic to all viruses that may play a role in host-range evolvability: mutation rate, recombination rate, and phenotypic heterogeneity. Although each trait should increase evolvability, they cannot do so unbounded because fitness trade-offs limit the ability of all three traits to maximize evolvability. By examining these constraints, we can begin to identify groups of viruses with suites of traits that make them especially concerning, as well as ecological and environmental conditions that might push evolution toward accelerating host-range expansion.
Multilayer Laminated Copper Electrodeposits and Their Mechanical Properties
Authors: Shin Han-Kyun , Kim Sang-Hyeok , Park Hyun , Lee Hyo-Jong
Published: September 2022

Copper (Cu) foils are used as anode current collectors in secondary batteries and to increase their capacity thin foils 8 μm thick, or less, have been commercialized. The change of mechanical properties according to the thickness of the foils was investigated from the viewpoint of the crystallographic microstructure. The elongation tends to decrease with decreasing thickness of the Cu foils but is limited by an increase in the ratio (D/t) of the grain size (D) to the thickness (t), which can lead to anisotropic plastic deformation. Two electroplating methods are proposed based on the concentration of the additive in the plating solution and by modulating the current density to develop multilayer laminate structures with alternating layers exhibiting different recrystallization behaviors to enhance the mechanical properties of Cu foils. Cycling between two electroplating solutions with different additive concentrations enables the control of the recrystallization behavior, although it likely presents challenges at the production scale. Alternatively, the periodic variation of the current density is used to alter the microstructure and recrystallization behaviors, enabling the formation of locally irregular grain extrusions between the layers. Mechanical measurements reveal a Hall-Petch relationship between the grain size and yield strength in the multilayer laminated foils.
SnO2 Nanoparticles: Green Synthesis, Characterization, and Water Treatment
Authors: Salwa A.S. , Ahmed Azza El-Sayed , Wasly H. S. , Abd El-Sadek M. S.
Published: September 2022

The green synthesis approach was utilized to synthesize tin dioxide (SnO2) nanoparticles (NPs) using Ocimum Basilicum leaves extract with different concentrations (10, 15, 20 ml) and different reaction temperatures (30, 60, 90 °C). The green synthesis method is considered economical, environmentally friendly, and non-toxic. X-ray diffraction patterns of the synthesized SnO2 NPs have displayed a tetragonal crystalline structure. The crystallite size of SnO2 NPs increased from 15.12 to 17.9 nm with increasing reaction temperature while decreasing from 20.68 to 17.9 nm with increasing extract concentrations. The morphology of the synthesized SnO2 NPs was investigated using high-energy transmission electron microscopy (HR-TEM). The optical energy gap was determined using the diffuse reflectance UV–vis spectra range (300–1200) nm of SnO2 NPs at different reaction temperatures and different extract concentrations. UV/Visible Spectrophotometer was used for studying the photodegradation of methylene blue dye (MB) dye. The photocatalytic degradation of MB revealed that SnO2 NPs at reaction temperature 90 °C degraded 69% of MB solution when exposed to UV illumination for 90 min while the degradation reaches 90% for 180 min of exposure. It was obvious that the degradation rate of MB was increased with the increase of reaction temperature, and the extract concentration.
Cooperative Advertising in Dual Channel Supply Chain System with Different Contracting Schemes
Authors: Tan Qi , Yao Fengmin , Li Tao , Liu Bin
Published: September 2022

This paper deals with the efficacy of revenue-sharing and cost-sharing contracts in a dual-exclusive channel, in which each manufacturer announces a cooperative advertising policy, such as cost-sharing contract, revenue-sharing contract, or neither of them, to its retailer. Under such cooperative advertising schemes, two models are developed—one in which each manufacturer determines the sharing rate endogenously or exogenously under the Stackelberg game approach and the other in which each manufacturer and its exclusive retailer cooperatively determine the sharing rate under the Nash bargaining approach. Some counterintuitive findings suggest that the advertising coordination mechanism critically depends on parameters, such as the basic demand share and product substitution. Most notably, the higher sharing rate can lead the retailer’s performance to be worse, especially when the competition becomes fierce. Furthermore, the cost-sharing contract is more beneficial to the cooperative advertising mechanism than the revenue-sharing contract.
Design of Student Homework Management System in Private Colleges and Universities Based on Computer Software Technology
Authors: Li Jing , Sun Hua
Published: September 2022

This paper takes the job management of a private university as the research object and analyzes the function, performance, and operating environment of the job management system. We design the overall design scheme of the job management system according to the requirements and carry out the general design, detailed design, and database design of the system. By comparing and analyzing the characteristics of different MPPT algorithms, in view of the shortcomings of the fruit fly optimization algorithm, this paper proposes an improved fruit fly optimization algorithm to realize the maximum power point tracking of photovoltaic systems. The initialization position is improved, and the iterative optimization is carried out by means of variable step size. Compared with the traditional fruit fly optimization algorithm, the improved algorithm has a faster convergence speed, and the optimization process is stable and less oscillating, and the tracking of MPPT is improved. The accuracy can effectively avoid the system falling into local optimum. Based on the understanding of user demand analysis, the problems to be solved by this system are obtained, and solutions to these problems are given. Through the analysis and comparison of various technologies commonly used in the current website development and combined with the characteristics of the problem, the ASP-based Browser/Server (B/S) architecture is used to realize it. This system realizes the digitization of traditional paper work, solves the problems of slow speed, poor real-time performance, difficult inquiries, and difficult statistics in traditional homework management, effectively improves the quality of homework management in private colleges and universities, and has certain effects on improving the quality of school teaching.
Experimental and Numerical Simulation Study on Shear Strength and Secondary Particle Breakage of Coarse Sand with Different Dry Densities
Authors: Luo Rui , Zhu Fangcai , Liu Qing , Zhang Shaolong , Wu Binbin , Shang Yaxin , Chen Qi
Published: September 2022

In order to guarantee perpendicularity of rotary cast-in-place pile in Karst areas, filling, like sand, etc., is commonly used between the inner steel casing and the outer steel sleeve; while the outer steel sleeve is pulled out or a vertical load is applied on the top of the pile, the sand will move, contact, and push against each other, which leads to recrushing; therefore, shear characteristics and secondary breakage are a meaningful problem to study with regard to the influence of different sand densities. Through experimental direct shear tests, with different dry densities, shear stress versus shear displacement curves are obtained and internal friction angles are analyzed. The results show that internal friction angles increase along with increment of dry densities; more interesting is that the secondary breakage ratio also increases. A comparative numerical 2D model is set up using PFC2D, with lower porosity used to simulate a large dry density, and similar results are obtained, that is to say, with increase of dry densities, internal friction angles also increase.
Analysis of Flexural Bearing Capacity and Failure Mode of Precast LSFRC Pavement Slab
Authors: Wang Zi-Jian , Ban Yi-Xuan , Luo Wen-Yu , Fan Han-Xiu , Zhang Bin , Wu Li-Ming , Wang Si-Chang
Published: September 2022

To promote practical use of the top-and-bottom layered steel fiber reinforced concrete (LSFRC) plates, an appropriate constitutive model is selected using ABAQUS software to analyze the bearing capacity, failure pattern, and deformation of the LSFRC plates. An LSFRC plate model is established for the analysis and calculation. Meanwhile, a test was carried out to measure the bearing capacity of 10 LSFRC plates. The results show that, after going through the elastic stage, crack growth, and failure stage, when the maximum crack width reaches 0.1 mm, the load of the LSFRC plates can be used as the ultimate bearing load. When failure appears to be bending the LSFRC plates, the neutral axis will shift upwards, showing a pseudoplastic failure. There is a larger tensile stress area after the first crack appears at the bottom of the steel fiber concrete. The change before and after the maximum load is relatively gentle. After becoming plastic, the plate witnesses a rapid crack growth on its bottom. With similar results from the test and numerical simulation, small errors can be minimized by further analysis to provide a more accurate model for the subsequent bearing capacity analysis of the LSFRC plates.
Empirical Study on the Grain Output Based on Regression Analysis
Authors: Xu Jiahao , Tang Sai , Li Pengyan , Zhang Hexu
Published: September 2022

Based on a literature review of influencing factors and forecasting methods for grain production, the empirical analysis of the influencing factors of China’s grain output is performed using the full subset regression method, the ridge regression method, and the LASSO regression method. The results show that (1) the increase in the sown area of grain crops is the main reason for the increase in grain output, (2) the use of agricultural fertilizers and the increase in rural electricity consumption are the driving factors for the increase in grain output, (3) the impact of total power of agricultural machinery is limited, and (4) natural disasters have a certain negative impact on food production.
Homoharringtonine Attenuates Dextran Sulfate Sodium-Induced Colitis by Inhibiting NF-κB Signaling
Authors: Liu Jiangrui , Shi Liangpan , Huang Wenchang , Zheng Zhihua , Huang Xiaohui , Su Yibin
Published: September 2022

Homoharringtonine (HHT) exhibits an anti-inflammatory activity. The potential protective effects and mechanisms of HHT on dextran sulfate sodium- (DSS-) induced colitis were investigated. DSS-induced colitis mice were intraperitoneally injected with HHT. Body weight, colon length, disease activity index (DAI), and histopathological change were examined. The relative contents of interleukin- (IL-) 1β, tumor necrosis factor- (TNF-) α, IL-6, and the chemokine (C-C motif) ligand 2 (CCL2) in the colon tissues and HHT-treated RAW264.7 cells were detected with the enzyme-linked immunosorbent assay. In the meantime, the levels of p-p65 and p-IκBα were detected by Western blot. The proportion of macrophages (CD11b+F4/80+) in the colon tissues was detected by flow cytometry. HHT alleviated DSS-induced colitis with downregulated TNF-α, IL-1β, IL-6, and CCL2 expression; reduced activation of nuclear factor-kappa B (NF-κB) signaling; and diminished proportion of recruited macrophages in colon tissues. It was further testified that HHT inhibited lipopolysaccharide-induced macrophage activation with reduced activation of NF-κB signaling. In addition, HHT inhibited the M1 polarization of both human and mouse macrophages, while HHT did not affect the differentiation of human CD4 T cells into Th17, Th1, or Treg cells and did not affect the proliferation and migration of human colon epithelial cells. In summary, HHT attenuates DSS-induced colitis by inhibiting macrophage-associated NF-κB activation and M1 polarization, which could be an option for the treatment of ulcerative colitis.
Channel Competition and Coordination of E-Commerce Platforms under Low-Carbon Environment: A Cooperative Game Approach
Authors: Liu Yijiao , Zhang Shiyuan , Jia Fu , Wu Zhiqu
Published: September 2022

The objective of “low-carbon supply chain” and the development of e-commerce platforms (as e-platform) has boosted the production and sales of low-carbon products. Although the e-platform’s involvement promotes the efficiency of low-carbon products circulation, it leads to channel competition and double marginalization. To mitigate these negative effects, in the context of low-carbon production, a three-player supply chain that contains a low-carbon manufacturer, an e-platform, and a retailer are investigated. By introducing the Stackelberg game and cooperative game theory, the supply chain is coordinated under a cooperative framework considering the commission rate of e-platforms. Subsequently, Mathematica is used for numerical simulation. The results show that intensified channel competition and excessive commission rates will lead to malicious price cuts by supply chain members, which is not conducive to the low-carbon production of manufacturers. Appropriate cooperation strategies can improve the value and identity of low-carbon products and optimize the supply chain system. For coordination of supply chain, three cooperative game-theoretic mechanisms can coordinate low-carbon dual-channel supply chain of the e-commerce platform (LCDESC) well under different situations. These findings provide managerial insights for managers of LCDESC.
Optimization of Land Use Regression Modelling of PM2.5 Spatial Variations in Different Seasons across China
Authors: Chai Jun , Song Jun , Zhang Le , Guo Bing , Xu Yawen
Published: September 2022

Fine particulate matter (PM2.5), one of the main components of haze, is of wide concern for its potential negative health effects. In order to further improve ambient air quality, it is essential to conclude the spatial variability of pollutants by investigating air pollution exposure. We divide China into two parts, north and south, and use a Land Use Regression (LUR) model to extract data including meteorological data, land use factors, and AOD retrievals, and use the machine learning algorithm to optimize the model to achieve predictions of the spatial distribution of near-surface PM2.5 mass concentrations in southern and northern China. We evaluated the seasonal consistency of the models in southern and northern China, and in northern China, we found a better fit with better seasonal consistency for the heating season and annual average model, while in southern China, we did not find a more fitted seasonal phase. The study illustrates that it is feasible to simulate the spatial distribution of PM2.5 mass concentration in large-scale areas based on the LUR model, and the seasonal consistency of the LUR model has been done to some extent.
Inchinkoto, the Traditional Japanese Kampo Medicine, Enhances Intestinal Epithelial Barrier Function In Vitro
Authors: Nakao Ayaka , Hu Ailing , Yamaguchi Takuji , Tabuchi Masahiro , Ikarashi Yasushi , Kobayashi Hiroyuki
Published: September 2022

Inchinkoto (ICKT), a traditional herbal medicine that is often used as a hepatoprotective drug in Japan, has pharmacological properties that include antioxidant, anti-inflammatory, and choleretic actions. Genipin is a metabolite of geniposide and the most abundant ingredient of ICKT; furthermore, it is considered to be the active substance responsible for its pharmacological properties in the liver. Drugs with such pharmacological characteristics are expected to prevent intestinal barrier dysfunction, which causes inflammatory bowel diseases (IBDs). However, no studies have investigated the effects of ICKT on the intestinal epithelial barrier. Therefore, we investigated the activity of ICKT in intestinal tight junctions by using cultured Caco-2 cell monolayers. The action of the compound on tight junctions was examined by measuring transepithelial electrical resistance (TEER) and sodium fluorescein (Na-F) permeability in the presence or absence of lipopolysaccharide (LPS). Moreover, the expression of the tight junction protein claudin-1 was assessed by using immunofluorescent staining. ICKT and genipin increased TEER and decreased Na-F permeability, which was suggestive of enhanced intestinal epithelial barrier function. Moreover, they prevented the LPS-induced destruction of the barrier, i.e., a decrease in TEER and an increase in Na-F permeability. Immunofluorescence staining revealed a high claudin-1 expression level on the cell surface, whereas exposure to LPS downregulated claudin-1. In turn, ICKT and genipin prevented the LPS-mediated reduction of claudin-1. These results suggest that ICKT enhances intestinal epithelial barrier function by upregulating claudin-1. Furthermore, genipin contributed to these effects. ICKT may be a promising medicine for the prevention and treatment of diseases associated with intestinal barrier disruption, such as IBD, obesity, and metabolic disorders.
A Novel Framework for Fog-Assisted Smart Healthcare System with Workload Optimization
Authors: Abdellatif Ahmed A. H. , Singh Aman , Aldribi Abdulaziz , Ortega-Mansilla Arturo , Ibrahim Muhammad
Published: September 2022

Fog-assisted and IoT-enabled smart healthcare system with rapid response rates is the major area of concern now a days. Dynamic and heterogeneous fog networks are difficult to manage and a considerable amount of overhead could be realized while managing ever increasing load on foglets. Fog computing plays a vital role in managing ever increasing processing demands from diverse IoT-based applications. Smart healthcare systems work with the assistance of sensor-based devices and automatic data collection and processing can speed up overall system functionality. In the proposed work, a novel framework for smart health care is presented where a series of activities are performed with prime objective of reducing latency and execution time. Principal component analysis is used for feature reduction and support vector machines with radial basis function kernel is used for classification purpose. Workload optimization on the fog nodes is implemented using genetic algorithm. Data collection process also involves preprocessing as a leading step for generating cleaner data. Amalgamation of intelligent and optimization techniques in the presented framework certainly improves the efficiency of the overall system. Experimental results reveal that proposed work outperforms the existing fog-assisted smart healthcare systems in terms of latency, execution time, overall system accuracy, and system stability.
The Scalable Fuzzy Inference-Based Ensemble Method for Sentiment Analysis
Authors: Isikdemir Yunus Emre , Yavuz Hasan Serhan
Published: September 2022

Internet environments such as social networks, news sites, and blogs are the platforms where people can share their ideas and opinions. Many people share their comments instantly on the internet, which results in creating large volumes of entries. It is important for institutions and organizations to analyze this big data in an efficient and rapid manner to produce summary information about the feelings or opinions of individuals. In this study, we propose a scalable framework that makes sentiment classification by evaluating the compound probability scores of the most widely used methods in sentiment analysis through a fuzzy inference mechanism in an ensemble manner. The designed fuzzy inference system makes the sentiment estimation by evaluating the compound scores of valance aware dictionary, word embedding, and count vectorization processes. The difference of the proposed method from the classical ensemble methods is that it allows weighting of base learners and combines the strengths of each algorithm through fuzzy rules. The sentiment estimation process from text data can be managed either as a 2-class (positive and negative) or as a 3-class (positive, neutral, and negative) problem. We performed the experimental work on four available tagged social network data sets for both 2-class and 3-class classifications and observed that the proposed method provides improvements in accuracy.
Methylene Blue Adsorption BY UV-Treated Graphene Oxide Nanoparticles (UV/n-GO): Modeling and Optimization Using Response Surface Methodology and Artificial Neural Networks
Authors: Ratnam M. Venkata , Murugesan Manikkampatti Palanisamy , Komarabathina Srikanth , Samraj S. , Abdulkadir Mohammedsani , Kalifa Muktar Abdu
Published: September 2022

To mitigate the negative effects of pollution produced by the growing levels of pollutants in the environment, research and development of novel and more effective materials for the treatment of pollutants originating from a variety of industrial sources should be prioritized. In this research, a UV-irradiated nano-graphene oxide (UV/n-GO) was developed and studied for methylene blue (MB) adsorption. Furthermore, the batch adsorption studies were modelled using response surface modelling (RSM) and artificial neural networks (ANNs). Investigations employing FTIR, XRD, and SEM were carried out to characterize the adsorbent. The best MB removal of 95.81% was obtained at a pH of 6, a dose of 0.4 g/L, an MB concentration of 25 mg/L, and a period of 40 min. This was accomplished with a desirability score of 0.853. A three-layer backpropagation network with an ideal structure of 4-4-1 was used to create an ANN model. The R2 and MSE values determined by comparing the modelled data with the experimental data were 0.9572 and 0.00012, respectively. The % MB removal predicted by ANN was 94.76%. The kinetics of adsorption corresponded well with the pseudo-second-order model (R2 > 0.97). According to correlation coefficients, the order of adsorption isotherm models is Redlich–Peterson > Temkin > Langmuir > Freundlich. Thermodynamic investigations show that MB adsorption was both spontaneous and endothermic.
Spatial Characteristics and Genesis of Tight Clastic Reservoirs in Yingcheng Formation of Changling Fault Depression in the Southern Songliao Basin
Authors: Mu Hansheng , Li Ruilei , Zhu Jianfeng , Xu Wen , Qu Xiyu
Published: September 2022

Tight oil and gas has become a hot spot for unconventional oil and gas exploration. How to find high-quality reservoirs under the conditions of low porosity and permeability has become a key issue restricting tight oil and gas exploration. This paper takes the deep-seated tight clastic rocks in the Changling fault depression in the Songliao Basin as the research object and comprehensively applies various technologies and methods such as microscopic observation, temperature measurement of inclusions and paleopressure recovery, and water-rock simulation experiments, to summarize the storage of tight reservoirs. Set space types and analyze their formation mechanism. The research results show that (1) the tight clastic reservoir space types of Yingcheng Formation in the Longfengshan subsag of the Changling fault depression in the southern Songliao Basin include residual primary pores, secondary dissolved pores, and microfractures, with mainly secondary dissolved pores; (2) pore lining chlorite is an important mechanism for the preservation of primary pores; (3) water-rock simulation experiments have confirmed that volcanic rock cuttings are easy to dissolve and are the main contributor to the secondary dissolution pores in the study area; and (4) the Raman displacement technique of methane inclusions has confirmed the existence of overpressure, which is the cause of hydrocarbon generation and pressurization and is the main motivation for a microcrack formation.
Effect of Prebreakdown Time on Shock Wave Generation Characteristics of Underwater Plasma Sound Source
Authors: Liu Xiao-Long , Cui Lin , Lei Kai-Zhou
Published: September 2022

Acoustic array bunching is an effective method to realize the directional radiation of underwater plasma sound source (UPSS). The prebreakdown time is one of the decisive factors for the performance of acoustic array bunching. The working characteristics of the underwater plasma sound source and the prebreakdown process of underwater plasma arc discharge are deeply analyzed. The precondition of plasma sound source array bunching is given by analyzing the waveforms of electrical signals and acoustic signals. Through the experiments of arc discharge based on different aqueous solutions, a feasible scheme of underwater plasma sound source array bunching in salt water is proposed. Through the arc discharge experiments based on different system discharge parameters, the variation of prebreakdown time under the influence of different charging voltage, conductivity, and other parameters was studied. The experimental results show that the prebreakdown time decreases with the increase of charging voltage and conductivity. At the same time, the discharge current increases, the oscillation time decreases, and the energy injection rate on the electrode accelerates. The research results are helpful to understand the prebreakdown mechanism of plasma sound source and optimize the underwater plasma sound source array bunching scheme and the acoustic shock wave waveform.
A Miniaturized Electrochemical Nitrate Sensor and the Design for Its Automatic Operation Based on Distributed Model
Authors: Ren Zhenxing , Li Yang
Published: September 2022

As one of the most common inorganic ions in daily food and ecological environment, nitrate (NO3−) is potentially harmful to both environment and humans. Therefore, the detection of nitrate concentration is quite important. Chemical sensors, as analytical measurement tools, usually demonstrate high selectivity, fast analysis speed, simple structure, convenient operation, and low cost and are considered to be a promising method for ion identification and detection. In this paper, a miniaturized electrochemical electrode is fabricated based on the microfabrication technology, and an electrochemical sensor for the detection of nitrate concentration in water is developed by combining the deposition technology of nanometal particles with electrochemical analysis technique. The developed electrochemical sensor utilizes electrochemical deposition to prepare a copper (Cu) granular sensitive film with a branch-cluster structure on the surface of a circular working electrode (Pt). Using copper’s characteristics of electrocatalytic reduction of NO3− in the acid solution environment (pH = 2), the concentration of NO3− in the water sample was calculated by measuring the reduction current on the working electrode when the electrocatalytic reduction reaction of NO3− occurred on the surface of the copper-sensitive membrane. The sensitive film is characterized and detected both with the scanning electron microscope (SEM) and X-ray diffraction analysis (XRD) technique; and the microsensor is used to detect nitrate standard samples; a high detection sensitivity (24.9 μA/mmol·L−1) is achieved in the concentration range of 0.0 to 3.0 mmol/L. At the same time, a MEMS three-electrode sensor without gold wire bonding and insulating glue packaging is designed, and an automatic detection system is constructed with a STM32f103 microcontroller as the controller to realize the automated detecting process for nitrate ions. At the same time, a distributed system is constructed, which can describe the nitrate concentration in every position of the water area and realize the monitoring of the whole water area. The detection system can meet the working environment under most conditions and has practical significance.
[Retracted] Outbound Data Legality Analysis in CPTPP Countries under the Environment of Cross‐Border Data Flow Governance
Authors: Li Jing
Published: September 2022

The governance of cross‐border data flows around the digital economy, data security, and data sovereignty has become a crucial global governance issue. This paper evaluates the legitimacy of data exit rules of CPTPP countries based on machine learning algorithm models under the perspective of cross‐border data flow governance. In this study, four machine learning algorithms, namely, logistic regression, decision tree, random forest, and GBDT, are used to build an outbound data assessment and evaluation model. The confusion matrix is used to classify the outbound data legitimacy dichotomously. The recall, precision, and F1 scores are evaluated to compare the empirical results of each model. Based on this, a logistic regression‐based outbound data risk scoring model is introduced to quantify the outbound data risk at a deeper level and to classify the outbound data risk level for the reference of regulators to make more scientific and reasonable decisions. The experimental results show that the machine learning models can meet the needs and applications of practical work and make accurate predictions of outbound data risks.
[Retracted] Nursing Teaching Curriculum Setting by Introducing Postcompetency Model under the Vision of Internet Informatization
Authors: Xiao Lan , Men Yi
Published: September 2022

The nursing curriculum is to be modernized to improve the student’s skills in meeting the recent trends in medical and healthcare fields. The curriculum improvements are based on expert recommendations, authors, and informative data from different web sources. The challenging task is to improve the readability and understandability of the curriculum to real‐time standards. Considering the above facts, this article introduces a refined curriculum with Internet information analysis (RC‐IIA) method. The proposed method incorporates the distributed Internet, journal, and previous curriculum information within the active nursing syllabus. This prevents repetitions and less‐informative content within the active curriculum. Besides, classification learning for knowledge‐based representations is used within the curriculum to improve competency. Based on the refined information, a recommendation‐based curriculum is preferred for varying information across different standards. The proposed analysis method relies on existing and distributed information across multiple curriculum providers for leveraging the visibility and prolonging the stealth of the nursing curriculum.
Influence of Water Injection Pressure on Methane Gas Displacement by Coal Seam Water Injection
Authors: Shi Tianwei , Pan Yishan , Zheng Wenhong , Wang Aiwen
Published: September 2022

It is of great significance to study the pattern of displacing methane gas with water in the coal seam water injection process for the prevention and control of gas disasters. A two-phase displacement test device was used to conduct experiments on the water injection of coal samples to displace methane gas under different water injection pressures, and the influence of the water injection pressure on the displacement was analyzed. The test results show that with the same displacement time, the ratio of displaced methane increases with the increase in the water injection pressure. The displacement rate increases with the increase in the water injection pressure at the stage without water discharge, while the water displacement rate under different water injection pressures differed slightly; in the later displacement stage, a higher water injection pressure of the coal sample results in a faster attenuation of the displacement rate and water displacement rate due to the decrease in the methane content in the coal sample. There is a critical water injection pressure to displace methane gas. When the critical water injection pressure is exceeded, the displacement time does not change appreciably. Flowing water can displace a large amount of methane gas in coal, and the methane displacement rate increases with the increase in the water injection pressure. The high solubility of methane in water is the reason for the high methane displacement rate. The results of this study can provide theoretical guidance for coal seam water injection to control gas disasters.
The Impact of Digital Economy on Industrial Carbon Emission Efficiency: Evidence from Chinese Provincial Data
Authors: Xie Ning-Yu , Zhang Yang
Published: September 2022

Digital economy has become an important driving force for green economic growth in China. Based on the province-level data of China from 2003 to 2018, this paper constructed the Total-factor Nonradial Directional Distance Function (TNDDF) model to measure the carbon emission efficiency of industrial sector and discussed the impact of digital economy on carbon emission efficiency. Empirical analysis shows that the carbon emission efficiency of China’s industrial sector is low, and there is obvious regional heterogeneity where the carbon emission efficiency of eastern China is higher than that of central and western China. Areas with high level of digital economy development have higher carbon emission efficiency, and digital economy is conducive to promoting energy conservation and pollution reduction in China’s industrial sector. The optimal threshold interval of digital economy for promoting carbon emission efficiency is explored by means of threshold model. In view of this, the Chinese government should vigorously develop the digital economy, promote industrial enterprises to networking and digital evolution, and improve the efficiency of carbon emission as well.
Research on Optimal Route Planning for Self-Driving Tour Based on Road Network Structure
Authors: Zong Ping , Han Yao , Xu Chenbo
Published: September 2022

Today’s social and economic development continues to improve people’s quality of life, and private cars are widely popularized, and self-driving tours have developed. The rapid development of self-driving travel has played an important role in the development of the national economy, and self-driving travel has become popular. Because the development of self-driving tours has caused some problems, the road network structure has become more and more complex, and the roads have become very congested. Especially during the holidays, there are more private cars in tourist attractions and the roads are more congested. How to use the information of roads and attractions and then choose the optimal travel route becomes particularly important. In response to this problem, we first analyze the topology of the road network, then analyze the accessibility of scenic spots and related factors that affect self-driving travel, and use the A∗ algorithm, Dijkstra algorithm, and other calculation methods to calculate the optimal path. The experiment found that there are many influencing factors of self-driving travel, and the road network structure has the greatest influence on it. The A∗ algorithm has obvious advantages over the Dijkstra algorithm.
Determination and Difference Analysis of Phenolic Compounds in Smokers’ Saliva and Mainstream Smoke
Authors: Si Xiaoxi , Yang Jianyun , Zhang Fengmei , Zhu Ruizhi , Liu Chunbo , Jiang Wei , Shen Qingpeng , He Pei , Tang Shiyun , Li Zhenjie , Liu Zhihua , You Junheng , Di Zhang
Published: September 2022

To study the differences in phenolic compounds between tobacco smokers’ saliva and mainstream smoke, a method was developed for the analysis of 12 phenolic compounds in saliva and mainstream smoke based on ultrahigh-performance liquid chromatography with fluorescence detection (UPLC-FLD). The contents and distributions of phenolic compounds in tobacco smokers’ saliva and mainstream smoke were compared. The results were as follows: (1) Phenolic compounds were quantitatively analyzed by the internal standard method using 4-fluorophenol as an internal standard. For smokers’ saliva samples, the limits of quantification (LOQs) ranged from 2.2 to 19.1 μg/L, and the recoveries were from 80.2% to 119.2% at the three spiked levels. For mainstream smoke samples, the LOQs ranged from 0.03 to 0.26 μg/cig, and the recoveries ranged from 84.9% to 107.0% at the three spiked levels. (2) The contents of phenolic compounds from 14 cigarettes in mainstream smoke and smokers’ saliva were determined. In mainstream smoking, the main phenolic compounds were hydroquinone, catechol, phenol, meta- and para-Cresol, and o-methylhydroquinone. In smokers’ saliva, the main phenolic compounds were phenol and meta- and para-Cresol and the contents of phenolic compounds in smokers’ saliva from different cigarettes were significantly different. (3) The content distribution patterns of phenolic compounds in smokers’ saliva differed from those in mainstream smoke. The predominant phenolic compound in mainstream smoke was dihydroxybenzene, while monophenols predominated in smokers’ saliva. (4) The contents of phenolic compounds from five kinds of cigarettes were analyzed in the saliva of different smokers using principal component analysis, which indicated that cigarettes with different sensory effects were clearly distinguished by differences in the contents of phenolic compounds in saliva.
Stability for a Non-Smooth Filippov Ratio-Dependent Predator-Prey System through a Smooth Lyapunov Function
Authors: Yang Yi , Dai Xiangguang , Zhang Xianxiu , Feng Yuelei , Zhang Yashu , Xiang Changcheng
Published: September 2022

For nonsmooth Filippov systems, the stability of the system is assumed to be proved by nonsmooth Lyapunov functions, such as piecewise smooth Lyapunov functions. This extension was based on the Filippov solution and Clarke generalized gradient. However, it is difficult to estimate the gradient of a non-smooth Lyapunov function. In some cases, the nonsmooth system can be divided into continuous and discontinuous components. If the Lebesgue measure of the discontinuous components is zero, the smooth Lyapunov function can be utilized to prove the stability of the system owing to the inner product of the gradient of the Lyapunov function of the discontinuous components being zero. In this paper, we apply the smooth Lyapunov function to prove the stability of the nonsmooth ratio-dependent predator-prey system. In contrast to the existing literature, in this paper, although the system is divided into continuous and discontinuous components, the inner product of the gradient of the Lyapunov function of the discontinuous part is not zero but negative. In the proof of stability, the negative value condition is stricter than the zero-value condition. This proof method only needs to construct a smooth Lyapunov function, which is simpler than a non-smooth Lyapunov function or other methods.
Application of Big Data Technology and Visual Neural Network in Emotional Expression Analysis of Oil Painting Theme Creation in Public Environment
Authors: Guo HanZe , Liang XinYu , Yu Yawei
Published: September 2022

With the progress of science and technology and the arrival of the big data era, people increasingly rely on computers to deal with daily life and related affairs. In recent years, machine learning has become more and more popular and has achieved good results in some fields, which also makes machine learning widely used. Among them, visual neural network technology can more intelligently analyze the emotional expression of oil painting, which is one of the current research hotspots, involving machine vision, pattern recognition, image processing, artificial intelligence, and other fields. However, in the art field, oil painting is still very different from other images. At present, there is no deep learning algorithm to identify the application of emotional expression analysis in oil painting theme creation. This paper will start with the neural network algorithm and combine the big data recognition technology to analyze the emotional expression of the oil painting subject in the public environment and establish the emotional expression analysis model of oil painting creation based on big data and neural network. The experiment shows that the graphics synthesized by this model have high resolution and good definition, but the speed is slow in the process of experimental operation. It takes about one hour to complete a round of image optimization.
The Study of Dosimetric Characteristics of the XHA600D Medical Linear Accelerator Based on a Monte Carlo Code
Authors: Wang Ningyu , Cui Fengjie , Gu Shaoxian , Yin Chuou , Zhang Shengyuan , Hu Jinyou , Cai Yunzhu , Wu Zhangwen , Wang Jun , Gou Chengjun
Published: September 2022

By investigating the influence of initial electrons on dosimetric characteristics, reasonable incident electron parameters for the nominal 6 MV photon beam of the XHA600D accelerator are finally established, i.e., a 6 MeV monoenergetic electron beam with a radial intensity FWHM of 2.5 mm and an angular divergency of 0.15°. Based on reasonable initial parameters, Percentage Depth Doses (PDDs), Off-Axis Ratios (OARs), total scatter factors, beam qualities, and penumbra widths of both flatteningfilter (FF) and flattening-filter-free (FFF) beams for fields ranging from 4 × 4 to 30 × 30 cm2 are simulated systematically with EGSnrc codes. Not only the simulated dosimetric properties are in excellent agreement with the measurements, but also the dosimetric discrepancies between FF and FFF beams are consistent with the laws of previous studies on other accelerators. Therefore, reasonable incident electron parameters are able to accurately verify the performance of the XHA600D accelerator and can be used for further dosimetry research.