Specific Path Research Articles

Research on the Operation Mechanism of Modern Apprenticeship System in Higher Vocational Education -- Taking H Vocational and Technical College as an Example

"Modern apprenticeship" as a positive response to the national policy call for the cultivation of higher vocational personnel practice exploration, not only can promote vocational education to accurately serve the social and economic development, but also promote the interactive development of the education system and the industrial economy, is to promote the construction of modern vocational education system is an important strategic choice. This paper takes H Vocational and Technical College as an example, analyzes the background, practical exploration and problems and effectiveness of modern apprenticeship operation mechanism, and strives to explore the specific path of the construction of modern apprenticeship operation mechanism of higher vocational colleges and universities under the current national conditions.

Capacitated Mobile Facility Location Problem with Mobile Demand: Efficient Relief Aid Provision to En Route Refugees

As a humanity crisis, the tragedy of forced displacement entails relief aid distribution efforts among en route refugees to alleviate their migration hardships. This study aims to assist humanitarian organizations in cost-efficiently optimizing the logistics of capacitated mobile facilities utilized to deliver relief aid to transiting refugees in a multi-period setting. The problem is referred to as the Capacitated Mobile Facility Location Problem with Mobile Demands (CMFLP-MD). In CMFLP-MD, refugee groups follow specific paths, and meanwhile, they receive relief aid at least once every fixed number of consecutive periods, maintaining continuity of service. To this end, the overall costs associated with capacitated mobile facilities, including fixed, service provision, and relocation costs, are minimized. We formulate a mixed integer linear programming (MILP) model and propose two solution methods to solve this complex problem: an accelerated Benders decomposition approach as an exact solution method and a matheuristic algorithm that relies on an enhanced fix-and-optimize agenda. We evaluate our methodologies by designing realistic instances based on the Honduras migration crisis that commenced in 2018. Our numerical results reveal that the accelerated Benders decomposition excels MILP with a 46% run time improvement on average while acquiring solutions at least as good as the MILP across all instances. Moreover, our matheuristic acquires high-quality solutions with a 2.4% average gap compared to best-incumbents rapidly. An in-depth exploration of the solution properties underscores the robustness of our relief distribution plans under varying migration circumstances. Across several metrics, our sensitivity analyses also highlight the managerial advantages of implementing CMFLP-MD solutions.

WTO Reform to Address the Exhaustion of Member States' Benefits

This article explores the need for World Trade Organization (WTO) reform and the direction it should take to adapt to and promote global trade developments. It begins with a discussion of the impact and current status of WTO membership on member countries, including the WTO's role and influence in global trade and the benefits it brings to member countries. The paper then outlines the reasons for the current depletion of benefits, new challenges and opportunities for global trade development, and the importance of reform for member countries and the global economy. In addition, it explores the principles and directions of reform, such as respect for the multilateral trading system, enhanced oversight and transparency, and improved dispute settlement mechanisms. The document also proposes specific reform measures and implementation paths, including increasing the participation and agenda-setting capacity of member countries, strengthening cooperation and coordination mechanisms among member countries, promoting trade facilitation and reducing trade barriers. Finally, this paper summarizes and looks forward to the future of WTO reform.

Analysis of TEC variations and prediction of TEC by RNN during Indonesian earthquakes occurred from 2004 to 2024 and comparison with IRI-2020 model

The Ionosphere, a crucial region of Earth’s atmosphere extending from approximately 50 to 1000 km above the Earth’s surface, plays a pivotal role in global communication, navigation, and satellite-based technologies. Among its various parameters, Total Electron Content (TEC) stands out as a key metric, representing the integrated electron density along a specific path through the ionosphere. This research focuses on analyzing TEC variations during Indonesian earthquakes between 2004 and 2024 using a Recurrent Neural Network (RNN) model. The study investigates the ionospheric response to seismic activity, particularly in Indonesia, a region prone to earthquakes due to its location within the Pacific Ring of Fire and complex tectonic setting involving multiple lithospheric plates. The RNN model, designed to predict TEC variations during earthquakes, utilizes data on solar and geomagnetic activity, including the Kp index, solar wind, and geomagnetic storm activity, obtained from the OMNIWEB data centre, along with TEC data from the IONOLAB data servers for the BAKO station in Cibinong, Indonesia. The earthquakes considered for observation include significant events such as the 2004 Indian Ocean earthquake and tsunami, the 2012 Wharton Basin earthquake, and subsequent seismic events up to 2024. Statistical metrics such as Mean Bias Deviation (MBD), Relative Error (REL_E), Absolute Error (ABS_E), and Root Mean Square Error (RMSE) are used to evaluate the predictive capability of the RNN model and compare it with the International Reference Ionosphere (IRI) 2020 model, a widely accepted empirical model for describing ionospheric parameters. The comparison reveals the performance of the RNN model in capturing TEC variations during seismic events, providing valuable insights for earthquake monitoring and early warning systems.

A Study on XANNs for Analyzing Failures in Guided Ultrasonic Wave-based Damage Localization

In the field of Structural Health Monitoring (SHM) using Guided Ultrasonic Waves (GUW), machine learning (ML) approaches for data analysis are becoming increasingly popular. Especially, deep learning with artificial neural networks (ANN) has proven effective due to its ability to process a large amount of data. ANN are commonly employed in damage localization tasks, where, with appropriate training, they deliver good results. However, a significant challenge persists in the application of ANN, namely, their "black-box" nature, which hinders the investigation of decision processes within the ANN and makes it difficult to understand why an ANN model fails under certain inputs. In the present work, an already introduced explainable artificial neural network (XANN) approach will be utilized to investigate when and why a trained XANN model fails with given inputs. The Open Guided Wave (GUW) platform's data is employed to train and test a XANN model designed to predict the location of artificial damage. Subsequently, individual inputs are modified (simulating malfunctions in specific sensor paths), and the impact on decision processes within the XANN architecture is examined. The aim of this study is to investigate and enhance the resilience and explainability of ANN approaches in the SHM domain.

Distance-based dynamic caching and replacement strategy in NDN-IoT networks

The amount of data on the Internet has risen noticeably due to the exponential increase in the number of Internet of Things (IoT) devices. Recently, Information-Centric Networking (ICN) is acknowledged as a suitable framework for creating IoT network protocols. One notable feature of ICN is in-network caching, which stores the data packets on intermediate routers/nodes that can be accessed by the subscribers when required. This work proposes a novel Distance-based dynamic caching and replacement strategy (DBDCRS) which involves a light weight calculation that utilizes the request aggregation to find the request weight of the requests stored in Pending interest table (PIT) and node weight of a node based on the distance from the subscriber and IoT publisher to accomplish the caching decision. To eliminate the data redundancy, the scheme caches a particular content on a single node along the specific interest-data path. Additionally, a custom cache replacement policy is introduced which retains the essential contents in cache. Simulation results show that our proposed DBDCRS scheme outperform other in-network cache placement schemes in terms of cache hit ratio, server hit reduction ratio, average response latency, and energy consumption.

Selective topological valley transport of elastic waves in a Bragg-type phononic crystal plate

Based on the quantum valley Hall effect analogy, this work proposes a phononic crystal plate with ligament-type beams to obtain the topological valley transmission of elastic waves. A pure Bragg degenerate state appears in the high-frequency region with a resonator introduced. By rotating the central scatterer and the beams, the mirror symmetry is broken to form a topological bandgap. Subsequently, this work finds that two selective edge states also appear beside the commonly non-trivial crossing edge states in the topological bandgap by calculating the projected band and eigenvalue spectrum of the supercell with different valley Hall phases phononic crystals. Their appearance is due to band separation of the topological edge states caused by an increase in the rotation angle. Both selective edge states can transmit topologically in specific paths. They will help further to broaden the width of the frequency band of topological transmission. Besides, an elastic wave splitter is designed and demonstrated numerically, which can form two channels and three channels in different frequency bands. With the topological selective edge state disappearing, a topological corner state exists in the edge bandgap. This work provides a theoretical reference for practical applications of broadband elastic wave topological transmission and elastic energy trapping.

Shaping Romania's National Recovery and Resilience Plan

During the shaping of Romania’s National Recovery and Resilience Plan (NRRP), an environment conducive to the creation of institutional arrangements for socio-centric governance was established. However, these arrangements were not enduring and could not modify the specific path dependency of state-centric governance arrangements. This research presents and analyzes perceptions regarding the extent and way Civil Society Organizations (CSOs) were engaged in the shaping process of Romania’s NRRP. Based on semi-structured interviews with the relevant CSOs, factors that have influenced the involvement of CSOs in shaping Romania’s NRRP about other European fund programming processes, the lessons learned from this process, as well as possibilities of enhancing the current governance regime specific to European funds management were examined.

Conditional Information Gain Trellis

Conditional computing processes an input using only part of the neural network’s computational units. Learning to execute parts of a deep convolutional network by routing individual samples has several advantages: This can facilitate the interpretability of the model, reduce the model complexity, and reduce the computational burden during training and inference. Furthermore, if similar classes are routed to the same path, that part of the network learns to discriminate between finer differences and better classification accuracies can be attained with fewer parameters. Recently, several papers have exploited this idea to select a particular child of a node in a tree-shaped network or to skip parts of a network. In this work, we follow a Trellis-based approach for generating specific execution paths in a deep convolutional neural network. We have designed routing mechanisms that use differentiable information gain-based cost functions to determine which subset of features in a convolutional layer will be executed. We call our method Conditional Information Gain Trellis (CIGT). We show that our conditional execution mechanism achieves comparable or better model performance compared to unconditional baselines, using only a fraction of the computational resources. We provide our code and model checkpoints used in the paper at: https://github.com/ufukcbicici/cigt/tree/prl/prl_scripts.

Financial and non-financial factors for the success of hybrid offerings: evidence from multinational enterprises in an emerging market

PurposeThe purpose of this study is to identify the financial and non-financial factors contributing to the success of hybrid offerings among Pakistani multinational enterprises (MNEs).Design/methodology/approachTo capture the complexity and interdependence of success factors, this study employed fuzzy-set qualitative comparative analysis (fsQCA). Data were collected from 213 chief executive officers (CEOs) of Pakistani MNEs.FindingsThe findings indicate that organizational support for service plays a vital role in hybrid offerings. Specific paths, such as a service-oriented corporate culture and management commitment to service, are necessary conditions for successful hybrid offerings.Originality/valueThe study sheds new light on the causal relationship underlying hybrid offerings in Pakistan, one of the Next Eleven countries, which is among the fastest-developing economies. We identified various paths to the financial and non-financial success of hybrid offerings within the Pakistani manufacturing MNE sector, which, to the best of our knowledge, has been underexplored. Additionally, we considered the digitalization dimension, which integrates and strengthens previous configurational models.

Single channel sound source localization by using combinations of multiple tubes

A method for localizing the direction arrival of the sound source with a single channel is proposed with the configuration of system consists of a single channel acoustic sensor and multiple inlets with specific path length of tubes or pipes. The time delay of arrival at each inlet can be estimated from the autocorrelation function measured at the sensor and the positions of peak in autocorrelation function are changed according to the incidence angle. By using this concept, the basic configurations are considered and the related investigations are conducted as solutions to several problems that need to be solved. The proposed concept is validated experimentally in anechoic chamber and outdoor conditions. As a method to expand the range of observation angle, the configuration with difference length is investigated and it is confirmed that the unique solution for the whole direction can be obtained by a combination of tubes and inlets.

Five-fold twin formation in face-centered cubic metals under impact loading

Five-fold twins (FFTs) are unique microstructural features in face-centered cubic (FCC) metals that significantly influence their mechanical strength. This study examines FFT formation in Cu, Au, and Ni under high-strain rate conditions induced by cold spray and compression shock impact loading, using atomistic simulations. We reveal a sequential twinning mechanism for FFT formation under impact loading, where the specific growth path varies, leading to inherently unstable FFTs that decompose post-formation. Interestingly, impact velocity had minimal influence, while elevated temperatures suppressed FFT formation, suggesting a dependency on the twinning mechanism. The stacking fault energy of the FCC metal greatly affected FFT propensity; metals with lower stacking fault energy (e.g., Au) readily formed FFTs, while those with higher stacking fault energy (e.g., Ni) encountered greater difficulty. These findings provide new insights into the behavior of FFTs under dynamic loading conditions, with implications for the design of high-strength nanocrystalline materials.

Research on the Value Distribution of China's Emerging Industries under the Background of "Double Carbon"

China's emerging industries have developed rapidly in recent years, still have significant growth, high added value, is the economic low-carbon environmental protection development of the positive driving force. Sanger algorithm is used to analyze the examples of emerging industries in China, explore efficient and scientific value distribution methods of emerging industries, promote rapid economic development, and summarize the specific construction paths of transforming traditional economic industries and developing emerging industries in various places, so as to provide reference for relevant departments to formulate and improve the healthy development of value distribution of developing emerging industries.

Depolarization effects when receiving radio waves on a moving object for various types and characteristics of the path

Depolarization is a change in the plane of oscillation of the vector of an electromagnetic wave during its propagation. It is important to take into account the depolarization of electromagnetic waves when designing a radio path, since each component (vertical and horizontal), depending on the propagation conditions, will have its own attenuation coefficient. In this regard, the choice of one or another type of polarization (linear, circular and elliptical) for a specific radio path will have a significant impact on the level of the received signal. In the course of this work, the most significant factors leading to the depolarization of electromagnetic waves along the propagation paths were identified. These factors included: scattering on bodies of suburban terrain (ground, forests, etc.), reflections (in combination with multipath propagation) from bodies of urban terrain, random (inclined) position of the antenna mobile terminal, Faraday rotation and dispersion in precipitation. As a result of the analysis of depolarization factors, mathematical models were formed that, due to their applied nature, made it possible to predict the effect of depolarization on the quality of reception by a subscriber station installed on a moving object, and also showed the relevance of using antenna systems with automated polarization adaptation.

Viewing the influence of Vkhutemas on the Bauhaus from the perspective of production art: Main concepts and directions

After the October Revolution of 1917, the Russian avant-garde established close relations with the German left wing. Vkhutemas, as the center of the Russian avant-garde, also had an important influence on the development of the Bauhaus. This study examines the specific path and results of the influence of Vkhutemas on the Bauhaus in terms of concept, structural transformation and production strategy in order to clarify the relationship between them. In this work, Vkhutemas is taken as the center, based on the analysis of conceptual principles, structural transformations and production strategies, specific ways and manifestations of the influence of the Russian avant-garde on the Bauhaus in various periods of the 1920s are explored. This comprehensive and multidimensional Russian influence not only develops the modern system of design education and finally consolidates the historical status of the Bauhaus, but also lays the foundation for its final fate. Firstly, on an ideological level, the goals of Russian production are directly related to the construction of socialism, to the creation of a system of proletarian culture, which Avartov calls proletarian, which largely coincides with the left-wing ideals of Gropius. Secondly, at the level of artistic thought, productivism and constructivism, as new ideas of the early 20th century, represented the contribution of the Russian avant-garde to modernist design. Finally, at the level of educational practice, thanks to the introduction of Russian constructivism by Moholy Nagy, the Bauhaus created a prototype of the three main components of modern design education, taking lessons from teaching composition by Vkhutemas, and opened the transition from expressionism to function. This was a new stage in the transformation of socialism, and thus formed the classic image of the Bauhaus for the outside world.

Tracing Student Activity Patterns in E-Learning Environments: Insights into Academic Performance

In distance learning educational environments like Moodle, students interact with their tutors, their peers, and the provided educational material through various means. Due to advancements in learning analytics, students’ transitions within Moodle generate digital trace data that outline learners’ self-directed learning paths and reveal information about their academic behavior within a course. These learning paths can be depicted as sequences of transitions between various states, such as completing quizzes, submitting assignments, downloading files, and participating in forum discussions, among others. Considering that a specific learning path summarizes the students’ trajectory in a course during an academic year, we analyzed data on students’ actions extracted from Moodle logs to investigate how the distribution of user actions within different Moodle resources can impact academic achievements. Our analysis was conducted using a Markov Chain Model, whereby transition matrices were constructed to identify steady states, and eigenvectors were calculated. Correlations were explored between specific states in users’ eigenvectors and their final grades, which were used as a proxy of academic performance. Our findings offer valuable insights into the relationship between student actions, link weight vectors, and academic performance, in an attempt to optimize students’ learning paths, tutors’ guidance, and course structures in the Moodle environment.

An Analysis on the Integration of Red Family Style into the Teaching of Ideological and Political Classes in High Schools: A Case Study of Sichuan and Chongqing

The family is the basic cell of society, the future and fate of the family is closely linked with the future and fate of the country and the nation. If the family style is positive, the people's hearts are simple; If the people are right, the society will be healthy. Sichuan and Chongqing area is rich in red family tradition resources, which plays an important role in the teaching of high school ideological and political courses. This paper takes the Sichuan and Chongqing red family tradition as the starting point, integrates the red family tradition into the teaching of high school ideological and political courses, analyzes the connotation and value of the red family tradition in this region, and implements the specific path of integrating the red family tradition into the teaching of high school ideological and political courses, aiming at helping the high school ideological and political courses to cultivate socialist core values and implement the fundamental task of cultivating morality and cultivating people.

Analyzing Temperature Distributions and Gradient Behaviors for Early-Stage Tumor Lesions in 3D Computational Model of Breast

The computational modelling and analysis of internal and external temperature distributions and their gradients, associated with the first stage of mammary tumors, was performed to relate thermal parameters to relevant tumor characteristics. A realistic 3D geometric model of breast anatomy was used to simulate tumor cases that were characterized in real life at their primary clinical stage. The thermophysical parameters of three tumors were extracted to implement the models; a fourth case without a tumor was used as a reference to provide quantitative measurements of temperature increases and gradient changes. The analysis considered superficial and internal temperature distributions and gradients, computed throughout specific paths. Finally, an evaluation was made of the ability of the thermometric technologies available today to detect the changes estimated in simulations. Maximum temperature increments in the range of 2.30 to 3.20 °C and in the range of 0.15 to 0.30 °C were found on internal and superficial paths, respectively. Internal gradient peak magnitudes fluctuated within the range of 0.34 to 1.14 °C/mm. Thermal results indicated a direct correlation between tumor size and temperature rise. Nevertheless, gradient results showed that the heat generation rate, an indicator of tumor malignancy, was directly proportional to internal gradient maximum peaks, which were related to tumor boundaries regardless of tumor size.

Predicting the pathways of string-like motions in metallic glasses via path-featurizing graph neural networks.

String-like motions (SLMs)-cooperative, "snake"-like movements of particles-are crucial for dynamics in diverse glass formers. Despite their ubiquity, questions persist: Do SLMs prefer specific paths? If so, can we predict these paths? Here, in Al-Sm glasses, our isoconfigurational ensemble simulations reveal that SLMs do follow certain paths. By designing a graph neural network (GNN) to featurize the environment around directional paths, we achieve a high-fidelity prediction of likely SLM pathways, solely based on the static structure. GNN gauges a structural measure to assess each path's propensity to engage in SLMs, akin to a "softness" metric, but for paths rather than for atoms. Our GNN interpretation reveals the critical role of the bottleneck zone along a path in steering SLMs. By monitoring "path softness," we elucidate that SLM-favored paths transit from fragmented to interconnected upon glass transition. Our findings reveal that, beyond atoms or clusters, glasses have another dimension of structural heterogeneity: "paths."

Research on the Construction of Modern Industrial Colleges in the Context of Industry-Education Integration

This paper describes the development progress of the construction of modern industrial colleges and analyzes the problems and difficulties in modern industrial colleges, enterprises, and the government. Chengdu Technological University is a modern industrial college that is constructed based on the “five integration” principle. This paper provides three specific paths for the construction of industrial colleges including improving the governance structure, constructing a talent training system, and developing an industry-university-research-application system according to the “five integration” principle.