Competitive Approach Research Articles

Interfacial evolution: A hydrothermal activation strategy to boost OER activity for stainless steel

BackgroundWater electrolysis is one of the most competitive approaches to generate hydrogen. The economical stainless steel, which consists of transition metals such as Ni and Fe, has impressive catalytic tunability and tremendous application potential in hydrogen production. MethodsIn this work, a hydrothermal activation strategy is proposed for breaking the inert oxide layer of stainless steel and producing an active catalytic layer dominated by NiFe2O4 spinel nanoparticles on the surface. The molybdate further complexes with the metal ions, disrupting the initial regular crystals of NiFe2O4 and exposing more defects. At the same time, Mo atoms can further optimize the electronic structure, which is conducive to the kinetic process of the reaction. Significant FindingsConsequently, the modified stainless steel requires only 270 mV to achieve a current density of 10 mA·cm−2, much lower than 387 mV of bare 304 stainless steel (SS304). Moreover, the robust catalytic layer, evolved from the stainless steel's own elements, grows firmly on the surface and shows excellent stability in the test of 120 h. This work provides a novel strategy for developing low-cost stainless steel electrodes with superior performance and stability for oxygen evolution.

Governing Global Spaces: the roles of the European Union and other major powers

ABSTRACTThis article offers a comparative assessment of the current roles of the European Union (EU) in the governance of the Global Spaces − the atmosphere, the high seas, the poles, outer space, and cyberspace. It does so from a twofold perspective: first, it compares the EU’s capacity to act and roles across the Global Spaces, drawing on actorness and role theory. Second, to contextualize the EU’s roles, it contrasts them with those of the United States, China and Russia. The findings show that the EU is still in the process of calibrating its roles in the governance of most of these Global Spaces. It is primarily a norm defender, which distinguishes its external action from the more competitive approaches of other major powers. The EU’s recent attempt to become more strategic has, for now, led to a gap between its role conception and performance, largely due to its limited actorness.

Competitive Latent Structures for the Comic Style Markers: Developing a Psychometrically Sound Short Version Using Spanish and US American Samples

The Comic Style Markers (CSM) is a questionnaire that allows a fine-grained description of how people differ in the way they display humor in their daily lives. It includes 48 statements capturing eight interrelated, yet distinct comic styles: fun, irony, wit, sarcasm, benevolent humor, satire, nonsense humor, and cynicism. Despite the independent conceptual roots of these humorous domains, the analysis of the CSM scales’ latent structure shows that their empirical distinction needs to be improved. Using the information derived from a competitive latent approach, including confirmatory factor analysis, bifactor analysis, and exploratory structural equation modeling, we proposed and validated a shorter 24-item version of the CSM in a large sample of 925 Spanish individuals (SP-CSM-24). This scale-refinement improved the psychometric differentiation of the eight comic styles without undermining the good internal consistency and the temporal stability of the CSM scores. Strong invariance was held for gender and age groups, and partial scalar invariance for countries also emerged using a sample of 318 U.S. American adults. Structural equation modeling also corroborated a convincing test-criterion validity for the SP-CSM-24, with dispositional expressions of benevolent humor (positively) and cynicism (negatively) outperforming other comic styles in accounting for individuals’ well-being.

Novel chitinolytic Bacillus spp. increase feed efficiency, feed digestibility, and survivability to Vibrio anguillarum in European seabass fed with diets containing Hermetia illucens larvae meal

Insect meals (IM) are being pointed out as a promising sustainable protein source. However, chitin in IM may negatively interfere with fish performance and nutrient availability. Given that carnivorous fish have a low or inexistent ability to digest chitin, novel strategies are needed to overcome chitin-imposed bottlenecks. Carbohydrolytic sporeforming probiotics offer a competitive industrial approach, being able to resist the harsh feed manufacturing process, transport, storage, and animal's gastrointestinal tract, while being able to increase the digestibility of otherwise indigestible components. Aiming to increase IM chitin digestibility, two chitinolytic sporeforming fish isolates (Fish isolates 645 (FI645) and 658 (FI658)), closely related to Bacillus licheniformis, were isolated from European sea bass (ESB) gastrointestinal tract, and incorporated (individually or as a mixture) in ESB diets with high defatted Hermetia illucens larvae meal (HM) levels (30% inclusion). FI were evaluated regarding their effects on ESB growth performance and digestibility. The spores were able to maintain their viability throughout the 180 days of diet storage at room temperature. Dietary inclusion of FI645 led to higher chitin digestibility. Concomitantly, the digestibility of dry matter, protein, and energy increased, overall leading to higher feed efficiency and protein efficiency ratio. Dietary inclusion of FI645 led to increased plasma N-acetylglucosamine (GlcNAc) levels. This is the first evidence for diet-mediated modulation of plasma GlcNAc concentrations. Dietary inclusion of FI645 also increased the expressions of the genes coding for N-acetylglucosamine kinase (nagk) and GlcNAc phosphomutase (pgm3), key enzymes from the GlcNAc salvage pathway and the hexosamine biosynthetic pathway (HBP). On the other hand, no differences were found for the expression of N-acetyl-D-glucosamine-6-phosphate deacetylase (amdhd2), a precursor enzyme for GlcNAc redirection to glycolysis. These results hint that free GlcNAc resulting from increased chitin digestibility might be preferentially redirected to protein O-GlcNAcylation processes through HBP in fish cells. Additionally, when challenged with Vibrio anguillarum, and after being feed for one month with the same diets, D645 also increased ESB survival from 52.5% to 77.5%, when compared to the control. Together, these results establish the potential of using FI645 as a probiotic for enhancing chitin digestion and acting as a prophylactic agent for ESB protection against V. anguillarum infection. This strategy opens novel possibilities for using commodities, including high chitin levels in aquafeeds, and reducing the use of antibiotics in aquaculture.

The tip protein PAAR is required for the function of the type VI secretion system.

Bacteria are constantly competing to colonize crowded ecological niches, such as the human gut. The type VI secretion system (T6SS) is a critical bacterial weapon in this warfare. It resembles a crossbow with a poisoned arrow allowing bacteria to inject toxic effectors directly into target cells. This machinery is formed by an envelope-spanning complex which recruits the baseplate, an assembly platform allowing the polymerization of a contractile structure. The tail consists of a tube surrounded by a sheath and topped by the needle complex composed of the VgrG and PAAR proteins. In the enteric pathogen enteroaggregative Escherichia coli (EAEC), the Tle1 phospholipase toxin ensures the antibacterial activity of the T6SS-1. For its transport, Tle1 interacts directly with the trimeric spike protein VgrG. However, the importance and the function of the tip protein PAAR in the T6SS remain unclear. Here, we characterized the PAAR protein of EAEC using biochemical, fluorescence microscopy, and antibacterial competition approaches. Using pull-down assays and cryo-electron microscopy analysis of the (VgrG)3-(Tle1)3-PAAR complex, we show that PAAR tops and closes the β-prism structure of the VgrG spike. The PAAR protein structure is further tightened by the zinc atom coordinated via conserved residues essential for its function. We provide evidence that PAAR is necessary for T6SS-1-mediated killing due to its requirement for proper T6SS baseplate assembly and further sheath polymerization. Our results suggest that the PAAR protein is an essential component of T6SS. IMPORTANCE The type VI secretion system (T6SS) is a bacterial contractile injection system involved in bacterial competition by the delivery of antibacterial toxins. The T6SS consists of an envelope-spanning complex that recruits the baseplate, allowing the polymerization of a contractile tail structure. The tail is a tube wrapped by a sheath and topped by the tip of the system, the VgrG spike/PAAR complex. Effectors loaded onto the puncturing tip or into the tube are propelled in the target cells upon sheath contraction. The PAAR protein tips and sharpens the VgrG spike. However, the importance and the function of this protein remain unclear. Here, we provide evidence for association of PAAR at the tip of the VgrG spike. We also found that the PAAR protein is a T6SS critical component required for baseplate and sheath assembly.

Stacking Model for Heart Stroke Prediction using Machine Learning Techniques

The paper presents an adaptive model that utilized the machine learning algorithms to predict the heart diseases. As heart disease is one of the leading causes of death and understanding its mechanism, effective prevention, diagnosis, and treatment is very crucial. With the help of data analytics, machine learning, artificial intelligence, it is possible to provide optimal solution to the heart diseases. But still getting optimal accuracy is a challenging issue. Identifying the data pattern, correlation and algorithms affects the accuracy very much. In this work, a stacking model has been proposed to find the best models out of it and validate the model for better prediction accuracy. The model is stacked with seven algorithms different machine learning algorithms such as Radom Forest, Naïve Bayes, Linear Regression, Decision Tree, Ad boost, K Nearest Neighbour, and Gradient Boosting. The experiment was carried out with a training and testing ration of 80:20 in ration. Evaluations are carried out in different measures such as Precision, Recall, F Score, and Accuracy to demonstrate the efficiency of the algorithms. Form the experimentation it is observed that the gradient boosting outperforms the other competitive approaches as this algorithm combines weak predictive models to form a stronger ensemble model that can make highly accurate predictions with an accuracy of 94.67 percentages.

Interwoven Models of Peacemaking – the Israeli-Palestinian Case and Beyond

ABSTRACT Two competitive approaches are dominant in the debate about the optimal strategy to cope with the Israeli-Palestinian conflict: Conflict-Management and Conflict-Resolution. This paper suggests looking at them as complementary. It presents four models of peacemaking. The first, the Strong Leader Model, involves drastic unilateral initiatives taken by one of the parties. The second, the Social Reformer Model, encourages domestic reforms within each of the parties. The third, the Political Elite Model, offers various forms of diplomatic interactions and is the dominant experience in Middle East peace processes. The fourth, the Public Assembly Model, proposes the creation of a major Israeli-Palestinian Public Negotiating Congress, based on the multiparty talks used in South Africa and Northern Ireland during the 1990s. This paper concludes that a multifaceted approach, which uses insights from all models in an integrated fashion, has the potential to create a momentum for a revolutionary peacemaking process.

MMPosE: Movie-Induced Multi-Label Positive Emotion Classification Through EEG Signals

Emotional information plays an important role in various multimedia applications. Movies, as a widely available form of multimedia content, can induce multiple positive emotions and stimulate people's pursuit of a better life. Different from negative emotions, positive emotions are highly correlated and difficult to distinguish in the emotional space. Since different positive emotions are often induced simultaneously by movies, traditional single-target or multi-class methods are not suitable for the classification of movie-induced positive emotions. In this paper, we propose TransEEG, a model for multi-label positive emotion classification from a viewer's brain activities when watching emotional movies. The key features of TransEEG include (1) explicitly modeling the spatial correlation and temporal dependencies of multi-channel EEG signals using the Transformer structure based model, which effectively addresses long-distance dependencies, (2) exploiting the label-label correlations to guide the discriminative EEG representation learning, for that we design an Inter-Emotion Mask for guiding the Multi-Head Attention to learn the inter-emotion correlations, and (3) constructing an attention score vector from the representation-label correlation matrix to refine emotion-relevant EEG features. To evaluate the ability of our model for multi-label positive emotion classification, we demonstrate our model on a state-of-the-art positive emotion database CPED. Extensive experimental results show that our proposed method achieves superior performance over the competitive approaches.

Asymmetric Feature Fusion Network for Hyperspectral and SAR Image Classification.

Joint classification using multisource remote sensing data for Earth observation is promising but challenging. Due to the gap of imaging mechanism and imbalanced information between multisource data, integrating the complementary merits for interpretation is still full of difficulties. In this article, a classification method based on asymmetric feature fusion, named asymmetric feature fusion network (AsyFFNet), is proposed. First, the weight-share residual blocks are utilized for feature extraction while keeping separate batch normalization (BN) layers. In the training phase, redundancy of the current channel is self-determined by the scaling factors in BN, which is replaced by another channel when the scaling factor is less than a threshold. To eliminate unnecessary channels and improve the generalization, a sparse constraint is imposed on partial scaling factors. Besides, a feature calibration module is designed to exploit the spatial dependence of multisource features, so that the discrimination capability is enhanced. Experimental results on the three datasets demonstrate that the proposed AsyFFNet significantly outperforms other competitive approaches.

Bi-Objective Modeling and Optimization for Stochastic Two-Stage Open Shop Scheduling Problems in the Sharing Economy

Nowadays, many manufacturing and service industries prefer to share resources such as facilities and workers to cooperatively perform tasks, which can efficiently improve resource utilization and customer satisfaction. Generally, the decision-makers need to pay more for resource usage, leading to an urgent demand to decrease operational costs. This article proposes a stochastic bi-objective two-stage open shop scheduling problem that models a vehicle maintenance process where tasks are appointed to be completed by multiple third-party companies with professional equipment. We formulate this optimization problem by minimizing the total tardiness and processing cost subject to various resource constraints. A hybrid multiobjective migrating birds optimization combined with a genetic operation and a discrete event system is designed by considering problem characteristics to solve the problem. In this method, the migrating birds optimization with some particular strategies aims at searching candidate solutions from the entire solution domain. Simultaneously, the discrete event system, by using stochastic simulation and discrete event-based simulation approaches, focuses on evaluating the performance of searched solutions. Simulation experiments are performed, and state-of-the-art algorithms are used as competitive approaches. The results confirm that this approach has an excellent performance in handling our considered problem.

The Effect of Cooperative Learning Approach, Competitive and Physical Fitness on Basketball Dribble Skills

The condition of learning basketball games in physical education in junior high schools (SMP) is still not optimally carried out in the implementation of the teaching and learning process, especially in the context of developing learning outcomes of basketball skills. The method used in this research is an experimental method with Anava 2 x 2 design. The population in this study were seventh grade students of SMP Negeri 2 Sawan as many as 78 students. The sampling technique uses the Verducci technique, to be as many as 78 people according to what is needed in the study.The instrument chosen by the author is the physical fitness test from AAHPERD for the junior high level and for basketball dribbling skills with a validity level of 0.89, namely the dribble test from Horrison. The author's hypothesis in this study is (1) The learning outcomes of students' basketball skills taught through the Cooperative learning approach are better than the Competitive learning approach as a whole. (2) There is an interaction between learning approaches and physical fitness on learning outcomes of basketball skills. (3) The learning outcomes of basketball skills of student groups taught through the Competitive learning approach are better than those of student groups taught through the Cooperative learning approach in groups of students who have high fitness. (4) The learning outcomes of basketball skills of student groups taught through the Cooperative learning approach are better than those of student groups taught through the Competitive learning approach in groups of students who have low fitness.

Competitive strategies and integration expanses in the large shipping container industry during an era of consecutive global crises

Purpose: This research aims to examine the competitive strategies and integration expanses of three of the largest shipping container companies worldwide, attempting to provide a helpful insight into the strategies adopted and implemented by the shipping container companies in question, in order to overcome the multiple significant obstacles resulting from the consecutive global crises of recent years (the post 2008 global financial crisis, pandemic, and war in Ukraine). Design/approach: The present paper (as a Case Study) examined three large shipping container companies that have played a crucial role in global trade over the years. These are three of the largest in 2023 (Hapag Lloyd, COSCO Shipping Lines, and Maersk). The criteria of these selected companies were mainly the authors’ focus on the significance for the industry of the mentioned three large shipping container companies, as well as the volume of information that could gathered by secondary data sources. Secondary data was collected by reviewing the existing branding literature as discussed in academic and trade journals, books, information databases, professional magazines, government publications, and specialized internet sites (Emerald, Science Direct, Google Scholar, and Scirus). Findings: This research identified that large shipping container companies do not solely adopt Cost Leadership, Differentiation, or Focus Strategy when planning their competitive strategies. Consequently, the decision of competitive strategy choice by large shipping container companies is not a trichotomous one between complete Cost Leadership, Differentiation, or Focus Strategy, but is a matter of combination. Many macro- and micro-environmental and organizational factors have a bearing on such decisions. This study identified that the balance of combination is dependent upon a number of reasons and factors, such as (mainly) macro- and micro-environmental factors, company resources and capabilities, customers’ willing to pay, barriers in the shipping liner industry, and revenue and cost approaches. Research limitations/ implications: The study contains several shortcomings. The theoretical view may contain conceptual elements which hinder more specific observations, e.g., the exhaustive examination of the industry’s competition elements based on Porter’s five forces rivalry view about competition between companies: (1) Rivalry between Existing Competitors, (2) Threat of New Entry, (3) Threat of Substitution, (4) Buyers’ Bargaining Power, and (5) Suppliers’ Bargaining Power. There is a recommendation for future research, which will be on how other large shipping container companies have dealt mainly with the post global financial crisis, as well as the post pandemic era, in terms of a competitive strategies approach having been adopted. This could include qualitative or quantitative research, along with a larger number of case study approaches (and not only large shipping container companies, but medium- and small-sized shipping container firms), which would produce useful results and insights. However, despite limitations, the study contains some managerial implications. Originality/value: The paper reports on the findings of one of the first in its kind (competitive strategies in large shipping container companies during an era of consecutive global crises) of research study carried out in the sector- in general, there are few research papers about competitive strategies in the shipping industry. The findings that emerged attempt to set the foundation for helping the various stakeholders in the sector, contributing towards building their strong international presence.

Antiviral Effect of 5'-Arylchalcogeno-3-aminothymidine Derivatives in SARS-CoV-2 Infection.

The understanding that zidovudine (ZDV or azidothymidine, AZT) inhibits the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 and that chalcogen atoms can increase the bioactivity and reduce the toxicity of AZT has directed our search for the discovery of novel potential anti-coronavirus compounds. Here, the antiviral activity of selenium and tellurium containing AZT derivatives in human type II pneumocytes cell model (Calu-3) and monkey kidney cells (Vero E6) infected with SARS-CoV-2, and their toxic effects on these cells, was evaluated. Cell viability analysis revealed that organoselenium (R3a-R3e) showed lower cytotoxicity than organotellurium (R3f, R3n-R3q), with CC50 ≥ 100 µM. The R3b and R3e were particularly noteworthy for inhibiting viral replication in both cell models and showed better selectivity index. In Vero E6, the EC50 values for R3b and R3e were 2.97 ± 0.62 µM and 1.99 ± 0.42 µM, respectively, while in Calu-3, concentrations of 3.82 ± 1.42 µM and 1.92 ± 0.43 µM (24 h treatment) and 1.33 ± 0.35 µM and 2.31 ± 0.54 µM (48 h) were observed, respectively. The molecular docking calculations were carried out to main protease (Mpro), papain-like protease (PLpro), and RdRp following non-competitive, competitive, and allosteric inhibitory approaches. The in silico results suggested that the organoselenium is a potential non-competitive inhibitor of RdRp, interacting in the allosteric cavity located in the palm region. Overall, the cell-based results indicated that the chalcogen-zidovudine derivatives were more potent than AZT in inhibiting SARS-CoV-2 replication and that the compounds R3b and R3e play an important inhibitory role, expanding the knowledge about the promising therapeutic capacity of organoselenium against COVID-19.

Exploring energetic, exergetic, economic and environmental (4E) performance of waste heat power generation in nuclear power plant systems: A perspective of pattern recognition

Combined cogeneration systems are employed to recover waste heat from the sCO2 cycle in nuclear power generation systems. However, dealing with their multidimensional and nonlinear design and optimization spaces is a complex challenge for designers. In this study, the combined cogeneration system is parameterized and modeled: 4E models including energetic, exergetic, economic and environmental are established for sCO2 combined Organic Rankine Cycle (sCO2/ORC) and trans-critical CO2 Cycle (sCO2/tCO2) respectively. Several decision variables and five performance indicators are selected. To gain a deeper understanding of the mechanisms and optimize the combined cogeneration system, pattern recognition methods including the Self-Organizing Map (SOM), an unsupervised competitive learning approach, and Statistical Sobol Global Sensitivity Analysis methods are proposed. These techniques help identify key parameters and system patterns within the design space. Then, the Non-Dominated Sorting Whale Optimization Algorithm (NSWOA) is adopted to build a Pareto-optimal decision space, and the SOM and PCPs are proposed to visualize and mining based on pattern recognition and graph visualization interaction. The design parameters of the top cycle, P2, PRc, and x, have been confirmed as having a substantial impact on the system's performance. The multiple attributes, criterions and objectives problems in the combined cogeneration system are ultimately simplified to “Economy-Environment”, double objectives problem, and three trade-offs’ solutions are discussed: prioritizing economics, prioritizing the environment, and finding a balanced economic-environmental compromise. Pattern recognition method provides decision-makers with a fresh perspective for gaining a deeper understanding of the multi-criteria objectives space and potential trade-offs. The integration of pattern recognition into the thermodynamic, economic, and environmental models outlined in this paper represents a substantial and valuable advancement in the analysis and optimization of combined cogeneration cycles.

Growth Reduction of Similarity-Transformed Electronic Hamiltonians in Qubit Space.

Accurately solving the electronic structure problem through the variational quantum eigensolver (VQE) is hindered by the available quantum resources of current and near-term devices. One approach to relieving the circuit depth requirements for VQE is to "pre-process" the electronic Hamiltonian by a similarity transformation incorporating some degree of electronic correlation, with the remaining correlation left to be addressed by the circuit ansatz. This often comes at the price of a substantial increase in the number of terms to measure in the similarity-transformed Hamiltonian. In this work, we propose an efficient approach to sampling elements from the complete Pauli group for N qubits which minimizes the onset of new terms in the transformed Hamiltonian while facilitating substantial energy lowering. We benchmark the growth-mitigating generator selection technique for ground state energy estimations applied to models of the H4, N2, and H2O molecular systems. It is found that utilizing a selection procedure which obtains the growth-minimizing generator from the set of operators with the maximal energy gradient is the most competitive approach to reducing the onset of Hamiltonian terms while achieving systematic energy lowering of the reference state.

Efficient numerical simulation of steel-UHPC composite structures based on a fiber beam-column model

To satisfy the demands of different engineering scenarios, ultra-high performance concrete (UHPC) is usually combined with steel to form various steel-UHPC composite structures. This study proposes an efficient numerical method for simulating steel-UHPC composite structures. A finite element analysis program, SU-COMPONA, is developed, which combines the fiber beam-column model and the concept of smeared cracks. Rational material constitutive laws are proposed and integrated into the program to describe the uniaxial behavior of UHPC and steel fibers. The proposed numerical method is validated against sufficient experimental data for various steel-UHPC composite structures, including reinforced UHPC beams and slabs, steel-UHPC composite beams and slabs and steel-UHPC-steel sandwich beams. In addition, the simulation performance is evaluated quantitatively. The results show that the proposed method can predict the ultimate capacity, the load-deflection curve and the development of crack widths with satisfactory accuracy and stability. Compared with the elaborate three-dimensional finite element method, the proposed method based on the fiber beam-column model is a competitive numerical approach that can achieve higher efficiency with slightly less accuracy.

Entrepreneurship Skills Development, Delinking the Aspirations of İnstitutional Development from the Implementation Realities. What Could Be The Potential Opportunities For Growth?

In the advent of new public management, expressed as the bureaucratization of university education, the competitive approaches by the management systems, the corporatization of governance structures, and the commodification of knowledge, it can thus be surmised that it is no longer business as usual in entrepreneurship skills development. Entrepreneurship skills development is one case in point that is fast becoming of great interests to scholars of social sciences and humanities. It ought to be so due to the power relations and the materialist interests that the new public management seems to promote and also how some university functions may have to respond, as a result. The scholarship project on which this article reports, sought to problematise, analyse and explain the power dynamics behind what appeared as the growth path in one case of entrepreneurship skills development in a university institution in South Africa. While the growth path could be easily commendable, what remained elusive were seemingly the challenges of effective institutional relations which therefore could be declared as marring the opportunities for optimising the potential that such a function could realise. Keywords: Entrepreneurship skills development, New Public Management, Organisational learning, Critical realism, Excellence.

FACTORS INFLUENCING THE SUCCESS IN PROFESSIONAL SKILLS COMPETITIONS

This article deals with professional mastery competitions in Russian education as an important part of the national system of teacher growth. The annual wide participation in them and the constant rotation of the participants allow us to speak about the contests as the most eff ective way of the teachers’ professional development. The performance of a contestant depends on many factors, the degree of infl uence of which is studied on the basis of both open and collected by the author data of the contest “Teacher of the Year of Russia”, as the most status of all competitions held at the moment. The infl uence of such factors as participant’s region, teaching subject, gender, age, work experience and status of educational institution on the result is investigated. Changes in the concept of competitive tests and approaches to their evaluation throughout the history of the competition are discussed in detail. The author off ers his own approach to performance, considering not only absolute victory, as traditionally accepted in the competition movement, but also the achievement of the titles “laureate” and rizewinner”. This approach allows us to rethink stereotypes in the preparation of teachers for competitive tests and increase motivation to participate in such events.

Modeling and monitoring multilayer attributed weighted directed networks via a generative model

As data with network structures are widely seen in diverse applications, the modeling and monitoring of network data have drawn considerable attention in recent years. When individuals in a network have multiple types of interactions, a multilayer network model should be considered to better characterize its behavior. Most existing network models have concentrated on characterizing the topological structure among individuals, and important attributes of individuals are largely disregarded in existing works. In this article, first, we propose a unified static Network Generative Model (static-NGM), which incorporates individual attributes in network topology modeling. The proposed model can be utilized for a general multilayer network with weighted and directed edges. A variational expectation maximization algorithm is developed to estimate model parameters. Second, to characterize the time-dependent property of a network sequence and perform network monitoring, we extend the static-NGM model to a sequential version, namely, the sequential-NGM model, with the Markov assumption. Last, a sequential-NGM chart is developed to detect shifts and identify root causes of shifts in a network sequence. Extensive simulation experiments show that considering attributes improves the parameter estimation accuracy and that the proposed monitoring method also outperforms the three competitive approaches, static-NGM chart, score test-based chart (ST chart) and Bayes factor-based chart (BF chart), in both shift detection and root cause diagnosis. We also perform a case study with Enron E-mail data; the results further validate the proposed method.

Research on the Cooperative Development Mode of Rural Tourism Resorts — Taking Huangpu River Source Tourism Resort as an Example

The Huangpu River Source Tourism Resort, situated within Anji County, Zhejiang Province, encompasses the administrative boundaries of Baofu Town, Zhangcun Town, and Hanggai Town. With the establishment of the resort's management committee, upper-level planning and coordination have gradually fallen into place, facilitating the full-scale construction of the resort. As a rural-oriented tourism destination aimed at fostering comprehensive development across these three townships, disparities are anticipated in terms of development foundations, tourism competitiveness, and development approaches. The purpose of this paper is to establish an evaluation index system for rural tourism competitiveness within the region. Utilizing factor analysis via the SPSS tool, it seeks to assess the strengths and weaknesses of each town's development factors, thereby evaluating the tourism development foundation and potential across the three towns. This endeavor aims to provide more effective guidance for the scientific construction and management of the Huangpu River Source Tourism Resort in Anji County and to explore a linked development model for the resort.