Path Diversity Research Articles

KFEX-N : A table-text data question-answering model based on knowledge-fusion encoder and EX-N tree decoder

Answering questions about hybrid data combining tables and text is challenging. Recent research has employed encoder-tree decoder frameworks to simulate the reasoning process of arithmetic expressions for generating answers. However, this approach overlooks the inherent diversity of expressions; there might be multiple valid reasoning paths, leading to a decrease in the accuracy of inferred expression trees. Moreover, encoders, lacking rich domain knowledge, struggle to capture deep relationships between questions and supporting evidence; this limitation results in models making errors when selecting operation units. In this paper, we propose a Knowledge-Fusion encoder and EX-N tree decoder table-text data question-answering model(KFEX-N). During the encoding process, the integration of traditional encoders with cross-fusion encoders forms a knowledge-fusion encoder, endowing the model with rich domain knowledge and enhancing its understanding of the operational units required to answer questions. Additionally, we propose an EX-N tree decoder. It reduces the diversity of inference paths through a constrained structure and mitigates the occurrence of final answer errors resulting from decoding errors. We validate our model using publicly available Table-Text QA datasets (TAT-QA and Fin-QA) and achieve state-of-the-art performance.

Robust path-following guidance for an autonomous vehicle in the presence of wind

This paper presents a novel nonlinear guidance law for an autonomous unmanned aerial vehicle (UAV) that enables it to track any predefined path while taking into account wind effects. The approach involves treating the desired path as the trajectory of the virtual target, which the UAV tracks without relying on knowledge of the path's curvature. This makes the design applicable to paths with varying levels of complexity and smooth curvatures. Additionally, the proposed method draws inspiration from pursuit guidance, known for its simplicity and ease of implementation. Theoretical analysis ensures that the UAV will converge to the intended path within a fixed time, irrespective of its initial configuration relative to the path. Simulations demonstrate the effectiveness of the proposed method, showcasing the UAV's ability to accurately follow diverse curvilinear paths.

Research on the Cultivation Path of "Dual-teacher" Teacher Team in Higher Vocational Colleges Based on the Integration of Industry and Education

The essence of "dual-teacher" teacher team in higher vocational education remains that of educators, who should possess both theoretical and practical teaching capabilities. This requires teachers to have proficient industry practice skills and the ability to demonstrate these skills through various teaching methods to better assist in enhancing students' practical abilities. This article explores the establishment of a platform for cultivating "dual-teacher" teacher teams through the integration of industry and education, focusing on improving the practical and teaching abilities of higher vocational teachers. It discusses collaborative efforts with industry associations and enterprises to establish long-term and relatively stable cooperative forms, exploring diverse cooperative paths. The implementation of seven projects is proposed to promote the cultivation of "dual-teacher" teacher teams in higher vocational education. These projects include enterprise internships for higher vocational teachers to gain practical experience, the construction of full-time and part-time teacher teams, training and assessment for professional skill level certificates, engaging in social services, the development of practical training facilities, and the construction of course resources and innovation in teaching methods and reforms. These initiatives aim to foster a "dual-teacher" teacher workforce that is well-equipped with both theoretical knowledge and practical skills, thereby enhancing the quality of higher vocational education.

An Underwater Source Location Privacy Protection Scheme Based on Game Theory in a Multi-Attacker Cooperation Scenario.

Ensuring source location privacy is crucial for the security of underwater acoustic sensor networks amid the growing use of marine environmental monitoring. However, the traditional source location privacy scheme overlooks multi-attacker cooperation strategies and also has the problem of high communication overhead. This paper addresses the aforementioned limitations by proposing an underwater source location privacy protection scheme based on game theory under the scenario of multiple cooperating attackers (SLP-MACGT). First, a transformation method of a virtual coordinate system is proposed to conceal the real position of nodes to a certain extent. Second, through using the relay node selection strategy, the diversity of transmission paths is increased, passive attacks by adversaries are resisted, and the privacy of source nodes is protected. Additionally, a secure data transmission technique utilizing fountain codes is employed to resist active attacks by adversaries, ensuring data integrity and enhancing data transmission stability. Finally, Nash equilibrium could be achieved after the multi-round evolutionary game theory of source node and multiple attackers adopting their respective strategies. Simulation experiments and performance evaluation verify the effectiveness and reliability of SLP-MACGT regarding aspects of the packet forwarding success rate, security time, delay and energy consumption: the packet delivery rate average increases by 30%, security time is extended by at least 85%, and the delay is reduced by at least 90% compared with SSLP, PP-LSPP, and MRGSLP.

Review of AI Based Career Counselling

In the domain of technology-driven educational advancements, artificial intelligence (AI) has become pivotal in enriching student experiences. This abstract gives into the rising need for effective career counseling and proposes the development for a specialized AI-based software application to address this need. Recognizing the universal role of technology in students’ lives, leveraging AI for personalized career guidance becomes necessity. The envisioned desktop application aims to redefine traditional career counseling methods by using AI algorithms' advanced capabilities. It seeks to provide personized recommendations to individuals or students navigating diverse career paths by evaluating academic performance, skills, and interests. Targeting three main user groups students, career counselors, and educational institutions the application offers a user-friendly interface for students to input details and preferences, resulting in a personalized career roadmap. Career counselors benefit from AI-generated analytics, entitle them to offer more informed guidance. This abstract covers the transformative potential of AI in enhancing career counseling services and facilitating informed career decisions

Exploring paths underpinning the implementation of municipal waste sorting: Evidence from China

Urban residents' waste sorting plays a pivotal role in addressing the pressing challenge of the “waste siege” in China and is also closely associated with the quality of urban governance. We draw on the Technology–Organization–Environment framework to identify six key variables affecting municipal waste sorting in China: digital technology innovation, attention allocation, publicity and education, enforcement intensity, economic development level, and volunteer resources. Using the fuzzy set Qualitative Comparative Analysis (fsQCA) method to analyze the effect of conditions on municipal waste sorting, the results show the following: 1) A single condition is insufficient to ensure high levels of municipal waste sorting. We propose that the “multiple concurrency” of technological, organizational, and environmental conditions creates diverse paths for promoting municipal waste sorting. 2) We then identify three paths for waste-sorting promotion, which all require technological, organizational, and environmental conditions. In addition, the two paths obtained for low levels of municipal waste sorting are not the opposite of those obtained for high levels. By observing the above five paths of waste sorting, we deduced that digital technology innovation is indispensable in driving waste sorting, and 3) Our cross-case comparisons show that there are effective paths to waste-sorting governance that work for cities regardless of their location or piloting. In some cases, high levels of attention allocation and high levels of publicity and education are substitutes for each other. We recommend that local governments refer to their own unique characteristics and resource endowments when tailoring waste-sorting strategies.

Icograda: The International Council of Graphic Design Associations 1963-2013

Abstract This article follows the International Council of Graphic Design Associations throughout its first 50 years of activities. Initially shaped from Western European perspectives on graphic design, which included the pursuit of universal standards and favoritism towards designers from certain countries, the Council's quest for recognition led its change towards a more inclusive and diverse path. This article concludes by acknowledging the changes the Council went through throughout the years and the nature of its work, along with remarks about the potential contributions of its archive to graphic design history, with valuable documentation on its membership from 1963 to 2003.

The unseen invaders: Tracking phylogeographic dynamics and genetic diversity of cryptic Pomacea canaliculata and P.maculata (Golden apple snails) across Taiwan.

The cryptic invasion of golden apple snails (Pomacea canaliculata and P. maculata) in Taiwan has caused significant ecological and economical damage over the last few decades, however, their management remains difficult due to inadequate taxonomic identification, complex phylogeny, and limited population genetic information. We aim to understand the current distribution, putative population of origin, genetic diversity, and potential path of cryptic invasion of Pomacea canaliculata and P. maculata across Taiwan to aid in improved mitigation approaches. The present investigation conducted a nationwide survey with 254 samples collected from 41 locations in 14 counties or cities across Taiwan. We identified P. canaliculata and P. maculata based on mitochondrial COI and compared their genetic diversity across Taiwan, as well as other introduced and native countries (based on publicly available COI data) to understand the possible paths of invasion to Taiwan. Based on mitochondrial COI barcoding, sympatric and heterogeneous distributions of invasive P. canaliculata and P. maculata were noted. Our haplotype analysis and mismatch distribution results suggested multiple introductions of P. canaliculata in Taiwan was likely originated directly from Argentina, whereas P. maculata was probably introduced from a single, or a few, introduction event(s) from Argentina and Brazil. Our population genetic data further demonstrated a higher haplotype and genetic diversity for P. canaliculata and P. maculata in Taiwan compared to other introduced regions. Based on our current understanding, the establishment of P. canaliculata and P. maculata is alarming and widespread beyond geopolitical borders, requiring a concerted and expedited national and international invasive species mitigation program.

Protection of Handicraft Skills from the Perspective of Folklore Studies

Handicraft skills and material culture are a research perspective of folklore and a major landscape of various ethnic customs in China. The long history, vast territory, and clever and wise Chinese people have formed a colorful and diverse folk handicraft technique. Under the diverse paths of design participation in handicraft innovation, handicrafts have undergone semantic, functional, and situational transformations in contemporary times, presenting an ecosystem of alienation and diversification. This article takes the ceramic craftsmanship of Yaozhou kiln as an example to explore how to improve the construction of national cultural soft power by protecting local traditional handicrafts.

Exploring Vocational High School EFL Teacher’s Role in the Problem-based Learning: Emancipated Curriculum Context in Indonesia

The shift to a PBL-oriented approach necessitates a reevaluation of the roles and identities of teachers. In the context of vocational high school English classrooms, where there may be diverse student backgrounds, aspirations, and career paths, exploring how English teachers adapt their roles as facilitators, mentors, and content experts can provide crucial insights. Additionally, understanding the factors that influence teachers' willingness and ability to embrace these roles within the context of an emancipated curriculum remains largely unexplored. Thus, this research aims to discover teachers’ role in implementing problem-based learning in the Emancipated Curriculum. This qualitative case study employed an interview to one English honorarium teacher as the main instrument, which covered the questions regarding teacher’s understanding and practice of the teacher’s role in problem-based learning. Through thematic analysis, the study revealed that, in general, the teacher’s role is in line with the previous related study, theory, and the goals of the Emancipated Curriculum in which the role of the teacher is: as the facilitator, evaluator, and guide. The findings provide practical implications for educational policymakers, school administrators, teacher educators, and English teachers seeking to enhance student engagement, motivation, and skill development in vocational education settings, specifically the findings allow teachers to learn and understand the teacher’s role in the classroom to support students in achieving problem-based learning objectives.

Impacts of NEP 2020 on Vocational Education and Emerging role of counsellors

The National Education Policy (NEP) 2020 in India has brought about significant reforms aimed at transforming the educational landscape, particularly in the realm of vocational education. This paper provides an in-depth analysis of the impact of NEP 2020 on vocational education and the emerging roles of counsellors within this context. NEP 2020 emphasizes the integration of vocational education into mainstream curriculum from the secondary level onwards, aiming to equip students with practical skills and job-oriented training. This shift necessitates a revaluation of the role of counsellors, who are now tasked with guiding students towards diverse career paths and facilitating their transition into the workforce. Additionally, NEP 2020 underscores the importance of providing holistic support to students, including psychometric assessments, career guidance, and skill development. The paper examines the challenges and opportunities presented by NEP 2020 in implementing vocational education initiatives and highlights the crucial role of counsellors in supporting students' career aspirations and personal development. Furthermore, it discusses the need for counsellor training programs to adapt to the changing educational landscape and equip counsellors with the skills and knowledge required to effectively fulfil their emerging roles. Overall, this paper provides valuable insights into the transformative potential of NEP 2020 in shaping vocational education and the evolving responsibilities of counsellors in guiding students towards success in the dynamic job market of the 21st century.

Tracing the Diverse Paths of One-Carbon Metabolism in Cancer and Beyond.

One-carbon (1C) metabolism is a network of biochemical reactions distributed across organelles that delivers folate-activated 1C units to support macromolecule synthesis, methylation, and reductive homeostasis. Fluxes through these pathways are up-regulated in highly proliferative cancer cells, and anti-folates, which target enzymes within the 1C pathway, have long been used in the treatment of cancer. In this work, we review fundamental aspects of 1C metabolism and place it in context with other biosynthetic and redox pathways, such that 1C metabolism acts to bridge pathways across compartments. We further discuss the importance of stable-isotope-tracing techniques combined with mass spectrometry analysis to study 1C metabolism and conclude by highlighting therapeutic approaches that could exploit cancer cells' dependency on 1C metabolism.

A tree-recursive partitioned multicast mechanism for NoC-based deep neural network accelerator

In chip multiprocessor systems (CMPs), Network on Chip (NoC) has been widely used due to its advantages of favorable reusability, high reliability, and low power consumption. Recently, using NoC platforms to accelerate deep neural networks (DNNs) has become a new trend. This design can enable the intermediate computation results of DNNs to be transmitted within the chip, reducing the number of accesses to off-chip memory. However, a large amount of one-to-many traffic in the DNN accelerator will occupy the system bandwidth, which will significantly reduce the performance of the NoC platform dominated by one-to-one traffic. To address this issue, we propose a tree-based recursive partitioning multicast scheme (TRPM), which increases the path diversity and improves the system bandwidth. We also design a single-cycle per-hop router architecture, which effectively enhances the transmission efficiency of multicast packets. Detailed simulation results show that compared with the latest tree-based multicast algorithm for DNN accelerators, our scheme reduces the number of routed packets by 35%, the classification latency by 13.5% and the average packet latency by 14.5% on average.

Impact of Static Urban Traffic Flow-Based Traffic Weighted Multi-Maps Routing Strategies on Pollutant Emissions

Addressing urban traffic congestion is a pressing issue requiring efficient solutions that need to be analyzed regarding travel time and pollutant emissions. The traffic weighted multi-maps (TWM) method has been proposed as an efficient mechanism for congestion mitigation that enables differential traffic routing and path diversity by strategically distributing different network views (maps) to the drivers. Previous works have focused on TWM generation by creating optimal edge weights, but the complexity exponentially increases with the network size and traffic group diversity. This work describes how congestion and emissions can be addressed using TWM maps based on the k-shortest paths for the traffic flows (instead of individuals) that are optimally assigned and distributed to the components of the traffic flow. The map allocation strategies optimal TWM (OTV), optimal TWM per path flow with linear constraints (LCTV), and its variant unconstrained optimal TWM per path flow (UCTV) are described. They use maps generated from the k-shortest paths of the traffic flows (kSP-TWM). The heuristic solution obtained is compared with the theoretical static traffic assignment estimation baseline with different configurations, regarding congestion reduction, total travel time enhancement, and pollutant emissions. Experiments are developed using a synthetic traffic grid network scenario with a mesoscopic simulation. They show that the solution provided is adequate for its proximity to the theoretical equilibrium solutions and can generate minimum emissions patterns. The presented solution opens new possibilities for further congestion and pollutant management studies and seamless integration with existing traffic management frameworks.

Pay structure and firm technological innovation: comparative research based on three pay gaps

While previous research has extensively explored the correlation between pay gaps and firm innovation, the comprehensive investigation of various pay gaps within a unified framework remains an understudied domain. We advance the understanding of the intricate relationship between pay gaps and firm innovation by examining the tournament effect and social comparison effect. Through empirical analysis spanning the period from 2009 to 2019 of Chinese listed companies, our findings reveal a potential inverted U-shaped curve in the impact of all pay gaps on firm innovation. Specifically, the effects of internal pay gap and management pay gap exhibit the left half of an inverted U-shaped curve, while the external pay gap demonstrates a complete inverted U shape. Additionally, utilizing fsQCA, we unveil that small firms can stimulate innovation through management pay incentives, internal tournaments, or employee tournaments. Conversely, large firms can pursue diverse paths, including management equity incentives, strategic emphasis on low pay for firm growth, or a harmonious combination of management pay and equity incentives. The intricate interplay between pay gaps and firm innovation is contingent upon industry and firm characteristics. Consequently, our study underscores the importance of meticulously designing pay structures that align with strategic goals and unique attributes.

High-efficiency electromagnetic wave absorption of lightweight Nb2O5/CNTs/polyimide with excellent thermal insulation and compression resistance integration

With the widespread application of electronic devices, multifunctional electromagnetic wave (EMW) absorbing materials suitable for complex high-temperature and high-pressure environments, have attracted tremendous research attention. Herein, multifunctional polyimide (PI) composites doped with fluffy Nb2O5/CNTs microspheres (NBCP) were prepared by combining the ultrasonic spraying process and freeze-drying technique. Introduction of fillers results in the formation of diverse conduction paths and heterogeneous interfaces, which enhance the dielectric loss. Furthermore, the multi-porous structure of the PI matrix induces multiple reflection scattering events and improves the impedance matching. Such a multi-loss mechanism endows NBCP with an excellent EMW absorption performance. At 15 vol% filling, the minimum reflection loss is −41.66 dB, the effective absorption bandwidth is 2.63 GHz, and the radar cross-section is reduced by 85%. Furthermore, NBCP exhibits outstanding mechanical properties and a thermal insulation of over 100 °C in thermal environment at 150 °C. The proposed multifunctional NBCP is thus an efficient EMW absorber that offers significant potential for applications in harsh environments.

Combined effect mechanism of linear loading and disturbance with different amplitudes on sandstone

To comprehend the stress state and response characteristics of materials under complex conditions, researchers have decomposed stress states into fundamental paths and investigated diverse path combinations. To ensure comparability, four identical samples were carefully selected from a pool of 100 samples using ultrasonic tests based on the wave speed and waveform characteristics. These samples underwent specially designed stress paths to analyze the combined effects of linear loading and perturbation. Our result analysis centred on the perturbation amplitude and stress levels during composite action, revealing intricate relationships between the stress levels, strain, and nonlinear/linear energy evolution under complex stress paths. Simultaneously, 3D surface fractures were precisely reconstructed using the YOLOv5 and FAST feature point detection algorithms, elucidating the evolving patterns of the fractures. As a result of our study, the rotation trend of the main fracture was validated by integrating mechanics and P-wave reflection rules. Notably, our experimental results closely aligned with the theoretical predictions, showing the reliability of our study. These findings can significantly contribute to guiding safety protocols in the field of underground engineering.

Generalization of Deep-Learning Models for Classification of Local Distance Earthquakes and Explosions across Various Geologic Settings

Abstract Although accurately classifying signals from earthquakes and explosions at local distance (<250 km) remains an important task for seismic network operations, the growing volume of available seismic data presents a challenge for analysts using traditional source discrimination techniques. In recent years, deep-learning models have proven effective at discriminating between low-magnitude earthquakes and explosions measured at local distances, but it is not clear how well these models are capable of generalizing across different geological settings. To address the issue of generalization between regions, we train deep-learning models (convolutional neural networks [CNNs]) on time–frequency representations (scalograms) of three-component earthquake and explosion signals from eight different regions in the continental United States. We explore scenarios where models are trained on data from all regions, individual regions, or all but one region. We find that although CNN models trained on individual regions do not necessarily generalize well across different settings, models trained on multiple regions that include diverse path coverage generalize to new regions, with station-level accuracy of up to 90% or more for data sets from unseen regions. In general, CNN-based discrimination models significantly outperform models based on uncorrected P/S ratio (measured in the 10–18 Hz frequency band), even when CNN models are tested on data from entirely unseen regions.

Global change alters coastal plankton food webs by promoting the microbial loop: An inverse modelling and network analysis approach on a mesocosm experiment

Marine organisms are currently, and will continue to be, exposed to the simultaneous effects of multiple environmental changes. Plankton organisms form the base of pelagic marine food webs and are particularly sensitive to ecosystem changes. Thus, warming, acidification, and changes in dissolved nutrient concentrations have the potential to alter these assemblages, with consequences for the entire ecosystem. Despite the growing number of studies addressing the potential influence of multiple drivers on plankton, global change may also cause less obvious alterations to the networks of interactions among species. Using inverse analyses applied to data collected during a mesocosm experiment, we aimed to compare the ecological functioning of coastal plankton assemblages and the interactions within their food web under different global change scenarios. The experimental treatments were based on the RCP 6.0 and 8.5 scenarios developed by the IPCC, which were extended (ERCP) to integrate the future predicted changes in coastal water nutrient concentrations. Overall, we identified that the functioning of the plankton food web was rather similar in the Ambient and ERCP 6.0 scenarios, but substantially altered in the ERCP 8.5 scenario. Using food web modelling and ecological network analysis, we identified that global change strengthens the microbial loop, with a decrease of energy transfer efficiency to higher trophic levels. Microzooplankton responded as well by an increased degree of herbivory in their diet and represented, compared to mesozooplankton, by far the main top-down pressure on primary producers. We also observed that the organisation of the food web and its capacity to recycle carbon was higher under the ERCP 8.5 scenario, but flow diversity and carbon path length were significantly reduced, illustrating an increased food web stability at the expense of diversity. Here, we provide evidence that if global change goes beyond the ERCP 6.0 scenario, coastal ecosystem functioning will be subjected to dramatic changes.

Anatomizing online collaborative inquiry using directional epistemic network analysis and trajectory tracking

AbstractAccurate assessment and effective feedback are crucial for cultivating learners' abilities of collaborative problem‐solving and critical thinking in online inquiry‐based discussions. Based on quantitative content analysis (QCA), there has been a methodological evolvement from descriptive statistics to sequential mining and to network analysis for mining coded discourse data. Epistemic network analysis (ENA) has recently gained increasing recognition for modelling and visualizing the temporal characteristics of online discussions. However, due to methodological restraints, some valuable information regarding online discussion dynamics remains unexplained, including the directionality of connections between theoretical indicators and the trajectory of thinking development. Guided by the community of inquiry (CoI) model, this study extended generic ENA by incorporating directional connections and stanza‐based trajectory tracking. By examining the proposed extensions with discussion data of an online learning course, this study first verified that the extensions are comparable with QCA, indicating acceptable assessment validity. Then, the directional ENA revealed that two‐way connections between CoI indicators could vary over time and across groups, reflecting different discussion strategies. Furthermore, trajectory tracking effectively detected and visualized the fine‐grained progression of thinking. At the end, we summarize several research and practical implications of the ENA extensions for assessing the learning process.Practitioner notesWhat is already known about this topic Assessment and feedback are crucial for cultivating collaborative problem‐solving and critical thinking in online inquiry‐based discussions. Cognitive presence is an important construct describing the progression of thinking in online inquiry‐based discussions. Epistemic network analysis is gaining increasing recognition for modelling the temporal characteristics of online inquiries. What this paper adds Directional connections between discourses can reflect different online discussion strategies of groups and individuals. A pair of connected discourses coded with the community of inquiry model can have different meanings depending on their temporal order. A trajectory tracking approach can uncover the fine‐grained progression of thinking in online inquiry‐based discussions. Implications for practice and/or policy Besides the occurrences of individual discourses, examining the meanings of directional co‐occurrences of discourses in online discussions is worthwhile. Groups and individuals can employ different discussion strategies and follow diverse paths to thought development. Developmental assessment is crucial for understanding how participants achieve specific outcomes and providing adaptive feedback.