Local Point Of View Research Articles

Screening China in Carnival: A Powerful China Framed in Participatory Documentary

ABSTRACT This article contributes to research into representations of China in current China–UK co-produced transnational documentary films. It examines Chinese New Year: The Biggest Celebration on Earth (2016) from the perspective of cinematographic styles and filmmaking techniques to demonstrate how this film frames a powerful image of China through a cultural lens, based on festive traditions and folk customs. The paper draws on Bill Nichols’ theory of participatory documentary and develops the discussion via the philosophical thinking of Mikhail Bakhtin on carnival. It argues that this film provides an example of how to write the story of modern China into an attractive narrative marked by the adaptation from localisation to globalisation through the engagement of non-fiction. With the employment of a multi-line narrative structure, this film maps diverse versions of gatherings that happened across towns and cities in China, highlighting how the festival reunites families and can be understood as an expression of familial love. Through the participation of hosts, the film invites audiences to attend festive celebrations from a local viewpoint, in particular family dinners, constructing the discourse of Da Tuan Yuan (great reunion). In the portrayal of people performing folk customs, the film indicates their cultural recognition of the significance of the Spring Festival. As such, this film constructs a representation of “Powerful China” supported by the Chinese government’s promotion of Chinese cultural identity, which aims to play its part in the solidification of national identity.

Modelling on COVID-19 control with double and booster-dose vaccination

COVID-19 vaccines have been illustrated to lessen the growth of sickness caused by the virus effectively. In any case, inoculation has consistently been controversial, with differing opinions and viewpoints. This has compelled some individuals to decide against receiving the vaccine. These divergent viewpoints have had a trivial impact on the epidemic’s dynamics and the disease’s development. In response to vaccinated individuals still falling ill, many countries have implemented booster vaccines to protect further.In this specific investigation, a mathematical model composed of seven compartments is employed to examine the effectiveness of a booster dose in preventing and treating the transmission of COVID-19. The principles of mathematics are employed to analyse and investigate the dynamics of the disease. Using a qualitative prototype analysis, we acquired valuable insights into its effectiveness. One essential aspect is the basic reproduction number, a critical determinant of the disease’s spread. This calculation is determined by studying the system’s equilibrium and evaluating its stability.Furthermore, we examined the balance from a local and global viewpoint, considering the possibility of bifurcation and the model’s reproductive number sensitivity index. Through numerical simulations, we have visually illustrated the analytical findings outlined in this research paper and presented a thorough examination of the efficacy of booster shots as a preventive and therapeutic measure in the spread dynamics of COVID-19.

Comparative analysis of RUSLE and SWPT for sub-watershed conservation prioritization in the Ayu watershed, Abay basin, Ethiopia

Ethiopia is currently facing a major environmental problem caused by soil erosion. In order to tackle this problem, it is essential to implement a comprehensive watershed management approach and give priority to conservation efforts depending on the level of severity. Therefore, the objective of this research is to evaluate the mean annual soil erosion and rank the sub-watersheds for conservations in the Ayu watershed, utilizing the Revised Universal Soil Loss Equation (RUSLE) model and the Sub-Watershed Prioritization Tool (SWPT). RUSLE was utilized to predict the annual average soil erosion rate, while SWPT was applied to conduct Weighted Sum Analysis (WSA) for ranking sub-watersheds. Support Vector Machine (SVM) was employed for classifying land use and land cover. The Relative importance of morphometric and topo-hydrologic features in the SWPT was analyzed using a Random Forest model. The Bland-Altman plot and Wilcoxon Signed Rank Test were employed to assess the agreement in prioritizing watersheds between RUSLE results and the SWPT. Furthermore, field observations were conducted to validate the land use classification by collecting ground data. In addition, the study was enhanced with local viewpoints by conducting focus group discussions with agricultural experts and farmers to obtain qualitative insights and validation of resuts. The findings showed that soil loss varied from 0 to 110 t/ha/yr, with an average of 8.95 t/ha/yr, resulting in a total loss of 384365.3 tons annually. The comparison of RUSLE and SWPT showed a moderate positive relationship (r = 0.59). The results of the Bland-Altman plot indicate a consistent agreement between the two methods. However, there is inconsistency among the five sub watersheds. This study enhances the knowledge of soil erosion patterns and offers useful guidance for watershed conservation techniques. It can be also used as a beneficial framework for managing watersheds, with possible uses outside of the Ayu watershed.

Multi-source data integration for explainable miRNA-driven drug discovery

Explainable drug discovery driven by miRNA offers substantial application potential due to the high targetability of miRNAs. Despite their effectiveness, the current graph neural network (GNN)-based methods encounters three significant challenges. Initially, GNN-based prediction models, disseminating messages throughout the miRNA–disease graph, are susceptible to “over-smoothing”. Secondly, these approaches frequently pinpoint potential miRNA drugs through established miRNA–disease associations (MDAs), neglecting the possible interdependence between unvalidated miRNAs and diseases. Thirdly, the lack of interpretability in these models, coupled with their dependence on specific dataset training, leads to suboptimal generalization capabilities. We present MS-EMD, an explainable model for miRNA-driven drug discovery that integrates subgraph estimation with an energy-constrained diffusion approach. This model aims to accurately forecast potential miRNA drugs by analyzing data from both local and global viewpoints. The MS-EMD model utilizes subgraph estimation to aggregate and update node representations using local subgraphs, thereby preventing over-smoothing. Simultaneously, it unveils potential miRNA–disease dependencies through a global attention mechanism driven by an energy-constrained diffusion process, improving model interpretability. Furthermore, we employ a data fusion technology that integrates diverse similarity data to strengthen the initial representations of miRNAs and diseases. Through various comparison and ablation studies, we verified the MS-EMD model’s efficiency and stability, highlighting its potential as an explainable tool for miRNA-driven drug discovery. Our code and data are available at: https://github.com/lizhen5000/MS-EMD.git.

Model checking distributed temporal logic

Abstract The distributed temporal logic (DTL) is a logic for reasoning about temporal properties of distributed systems from the local point of view of the system’s agents, which are assumed to execute sequentially and to interact by means of synchronous event sharing. Different versions of DTL have been provided over the years for a number of different applications, reflecting different perspectives on how non-local information can be accessed by each agent. In this paper, we propose an automata-theoretic model checking algorithm for DTL. To this end, we propose a notion of distributed transition system that will be used to specify the system to be verified. The properties that the system should meet are specified in DTL. In order to capture the models of these properties, we propose the notions of generalized distributed Büchi automaton and of distributed Büchi automaton. With these concepts, we are able to adapt results from automata-theoretic approaches to model checking in LTL to the distributed case.

Local knowledge and information initiatives in the conflict-affected eastern Democratic Republic of Congo

ABSTRACT Research process in humanitarian crises requires a meticulous synthesis of different skills. Most humanitarian operations are, critically and contextually dependent on the local environment, with its unique capabilities and constraints. Western humanitarians often rely on local brokers to gain trust and legitimacy through their networks. This article presents cases of local news reporting from Goma in the eastern Democratic Republic of Congo, evaluating two newsletters from a professional network for humanitarians (the SIDINL network). A positive interpretation of how these local news curators, acting as local brokers, could influence humanitarianism through the respect of subjectivity and sensemaking is suggested; however, the benefits of the local viewpoint could be substantially diminished if personal biases are not acknowledged properly through an honest and equal-as-possible relationship between locals and foreigners. The implications of these examples underscore the importance of ethical attention and respect in overcoming hostility towards any form of foreign intervention.

Perceptions of Vocational Education Students at Al-Balqa Applied University toward Vocational Education

This study aimed to explore the perceptions of vocational education students at Al-Balqa Applied University toward vocational education. The sample of the study comprised 768 students enrolled in the second semester of the academic year 2021/2022. To achieve the objectives of the study, the descriptive survey methodology was used.A questionnaire consisting of 32 items was designed. The questionnire items fell into four categories: Syllabi, vocational advising, educational environment, and local community viewpoint about vocational education. Results of the study revealed that students’ perceptions toward vocational educations are within a ‘medium’ level. Further, the study revealed no significant statistical differences at (∝=0.05) value in the responses of the subjects of the study attributed to the two variables of academic year and university college and there were statistically significant differences at the significance level (∝ = 0.05) in the responses of the study sample due to the gender variable and in favor of females. Considering these results, the study recommended raising the community awareness about the significance of vocational education and improving the way people perceive it.

Effects of source space resolution, randomization and averaging in focal EEG source localization: Estimation of forward and inverse errors

In this article, we study randomized multiresolution forward modeling and source localization in electroencephalography (EEG). Our goal is to determine numerically the effects of variable source space resolution on both forward modeling and source localization perspectives and to examine how it affects the detection of the sources at different depths inside the brain. Our concentration is in the main principles of multiresolution methods: random source space generation and the reconstruction obtained via averaging over multiple maximum a posteriori (MAP) estimations obtained at a finite set of different sub source spaces, and their suggested enhancement in distinguishability of weak components. The motivation of averaging is to reduce the discretization and optimization error and marginalize other variable factors. Due to the unguided randomized source space generation, multiple samples of the same size source spaces are needed. For this very reason, a large number of source spaces of multiple source counts are used to obtain statistically feasible results in this paper. This study verifies the described postulates of the multiresolution technique by showing averaging to be crucial in order to obtain a robust projection to a lower resolution, where the lead field matrix is overdetermined. From the viewpoint of source localization, the multiresolution approach was found to improve the reconstruction accuracy obtained with each resolution level below the highest and observed to be necessary to achieve an accuracy comparable to that of forward modeling.

Exploring Local Perspectives in Hospitality and Tourism Growth in Quirino Province

Purpose of the study: This study examines the development of Hospitality and Tourism in Quirino Province, including social, cultural, economic, and environmental effects, with a focus on local perspectives. Methodology: It uses the community-based tourism (CBT) framework to evaluate residents' perceptions of the effects of tourism, both positive and negative and assesses the attitudes of 200 residents towards tourism and its socio-cultural impacts through a structured questionnaire. Main Findings: The preliminary findings suggest that individuals have a favorable outlook on different aspects of life, particularly emphasizing the importance of preserving culture and raising awareness about heritage. Applications of the study: The study provides valuable insights for policymakers, tourism planners, and community leaders in promoting sustainable tourism practices in Quirino Province. Novelty/Originality of the study: This unique and innovative study examined and assessed the local viewpoint on the development of hospitality and tourism in the province of Quirino.

Oral Complications and Management Strategies for Cancer Patients: Principles of Supportive Oncology in Dentistry.

It is recognized that patients undergoing cancer treatment experience different adverse effects depending on the type of therapy they received. The objective of this work is to provide a scientific evidence-based protocol for oral care in cancer patients. Cancer resection surgery, chemotherapy, and radiotherapy can cause important complications that impact patients' quality of life. Cancer patients, from the moment of diagnosis to the end of treatment and subsequent follow-up, have diverse care needs, both from a systemic and local point of view. The implementation of oral care protocols before, during, and after cancer therapy is essential because it helps to identify risk factors for the development of predictable oral complications. It is essential to establish that all cancer patients, before starting treatment, undergo a systematic dental check-up to avoid limitations during treatment and also alter their quality of life. Regular professional oral care maintenance and follow-up programs are essential to maintaining a patient's long-term oral health.

A local rough set method for feature selection by variable precision composite measure

Feature selection using variable precision neighborhood rough sets (VPNRS) has garnered considerable attention in data mining and knowledge discovery. Nevertheless, the positive region of VPNRS may not be strictly divided due to the introduction of variable parameters, which could reduce the credibility of feature significance. Meanwhile, the calculation of approximate space is also complex and expensive. Hence, how to improve the computation efficiency is also an investigated issue. As for these issues, we propose a variable precision composite measure and design a novel local method for the feature selection of decision data. Firstly, we introduce the variable precision neighborhood rough set model to process uncertain information from global and local viewpoints. Furthermore, the variable precision composite measure is defined to evaluate the model’s accuracy and further used to select the essential features. Finally, a local forward algorithm is provided for feature selection to improve computing efficiency. All experiments on twelve datasets show that the local method is efficient, and the feature selection algorithm based on variable precision composite measure performs well in classification performance. Our work will provide a convenient tool for feature selection methods with uncertainty measures.

Local stakeholder's viewpoint on Vlassov's contribution.

Local stakeholder's viewpoint on Vlassov's contribution.

EEG-Oriented Self-Supervised Learning With Triple Information Pathways Network.

Recently, deep learning-based electroencephalogram (EEG) analysis and decoding have attracted widespread attention for monitoring the clinical condition of users and identifying their intention/emotion. Nevertheless, the existing methods generally model EEG signals with limited viewpoints or restricted concerns about the characteristics of the EEG signals, and thus represent complex spectro-/spatiotemporal patterns and suffer from high variability. In this work, we propose the novel EEG-oriented self-supervised learning methods and a novel deep architecture to learn rich representation, including information about the diverse spectral characteristics of neural oscillations, the spatial properties of electrode sensor distribution, and the temporal patterns of both the global and local viewpoints. Along with the proposed self-supervision strategies and deep architectures, we devise a feature normalization strategy to resolve the intra-/inter-subject variability problem. We demonstrate the validity of our proposed deep learning framework on the four publicly available datasets by conducting comparisons with the state of the art baselines. It is also noteworthy that we exploit the same network architecture for the four different EEG paradigms and outperform the comparison methods, thereby meeting the challenge of the task-dependent network architecture engineering in EEG-based applications.

Competitiveness of intermodal transport in the opinion of experts from the Baltic sea region

The article presents the results of a survey conducted among experts in the field of transport research, from the Baltic Sea region, on the competitiveness of intermodal transport in relation to road transport. The study aimed to identify factors that positively and negatively influence the choice of intermodal transport as an alternative to road transport along the entire transport route. The available literature was reviewed, and attention was paid to the problem of differences in the perception of intermodal transport by experts from different countries. It was also indicated that, depending on the approach to this problem and the local point of view, significantly different results can be obtained regarding the factors influencing the choice of intermodal transport as an alternative to road transport.

Unlocking the dynamics of open innovation: A conceptual exploration

This study explores the complex domain of open innovation, a conceptual framework in which the word "open" signifies sharing tacit organisational knowledge. Organisations increasingly expand their scope outside conventional bounds by using open innovation approaches and models to acquire necessary resources. The main aim of this academic undertaking is to examine informal networks that arise outside traditional contractual agreements and then analyse the tangible structure of these networks. The study's primary objective is to thoroughly examine, compare, and analyse nonlocal centrality measures, including global and local viewpoints, within a conceptual framework. This research investigates the utilisation of network analysis methodologies, such as Degree Centrality, Closeness Centrality, Eigenvector Centrality, Betweenness Centrality, Modularity, Community Detection, Vote Rank, and Digital Flaneurs, through the implementation of the Python NetworkX Programming Language. This research highlights its conceptual relevance as a significant and considerable addition to the current body of knowledge. This study provides a fundamental basis for further investigating and comprehending the complex interplay of nonlocal centrality measurements, dynamic capabilities, and open innovation tactics. Therefore, this study is a noteworthy contribution to the scholarly body of knowledge, presenting useful perspectives on the complex relationship between open innovation approaches, dynamic capabilities, and nonlocal centrality measurements. Furthermore, this research adds to the wider scholarly discourse on how organisations effectively manage the intricate challenges of the modern digital environment to achieve innovation and maintain a competitive edge.

Rate-induced tipping in complex high-dimensional ecological networks.

In an ecosystem, environmental changes as a result of natural and human processes can cause some key parameters of the system to change with time. Depending on how fast such a parameter changes, a tipping point can occur. Existing works on rate-induced tipping, or R-tipping, offered a theoretical way to study this phenomenon but from a local dynamical point of view, revealing, e.g., the existence of a critical rate for some specific initial condition above which a tipping point will occur. As ecosystems are subject to constant disturbances and can drift away from their equilibrium point, it is necessary to study R-tipping from a global perspective in terms of the initial conditions in the entire relevant phase space region. In particular, we introduce the notion of the probability of R-tipping defined for initial conditions taken from the whole relevant phase space. Using a number of real-world, complex mutualistic networks as a paradigm, we find a scaling law between this probability and the rate of parameter change and provide a geometric theory to explain the law. The real-world implication is that even a slow parameter change can lead to a system collapse with catastrophic consequences. In fact, to mitigate the environmental changes by merely slowing down the parameter drift may not always be effective: Only when the rate of parameter change is reduced to practically zero would the tipping be avoided. Our global dynamics approach offers a more complete and physically meaningful way to understand the important phenomenon of R-tipping.

Between Taking and Making Place: Exploring the Linkages Between Serres’ Le Parasite and the Research Practice of Creative Intervention

This article explores the linkages between Serres’ Le Parasite and the research practice of creative intervention via the analysis of an experimental film produced for the 2022 Space and Culture Conference on Taking Place and Making Place. The experimental film is intended as a provocation, in that it seeks to exceed the forms of conventional scholarship. In an effort to invent new modes of thought production, documented research materials of local sites are combined with a range of ideas and theories, blurring boundaries between theory, poetry, and practice, the dystopia of the virtualization of everyday life and the figuration of possible realities, glimpsed from a local viewpoint which follows the fluxes of emergences.

Local advertising practices in the San Miguel de Salcedo parish in Ecuador

In general, the research carried out by the different social sciences on advertising has privileged commercial discourses from the media and the mass media. Other forms of advertising communication are part of the culture and traditions of community contexts that have lacked analysis. Therefore, this article aims to describe the advertising practices that occur at the local level in the parish of San Miguel de Salcedo in Ecuador. The article corresponds to a qualitative, descriptive and reflective research, where a phenomenological and methodological design is applied, the data management is nourished by the application of instruments such as documentary literature review, participant observation and qualitative content analysis. The results address the forms of local advertising and its characteristics, both in community media as well as in squares and markets. Thus, it contributes to the knowledge on this topic, and at the same time constitutes a contribution to the scientific field of advertising from a local point of view.

Rigidity of holomorphic mappings from local and global viewpoints

Rigidity of holomorphic mappings from local and global viewpoints

The suspension of the Democratic Governance Facility in Uganda: the illusion of “politically smart aid”

ABSTRACT In 2021, the President of Uganda suspended the “Democratic Governance Facility” (DGF), which is a European basket fund aimed at providing financial support in areas such as democracy, human rights, and rule of law. Paradoxically, the DGF had explicitly adopted a new “politically smart framework”, which is a development approach that promises to deliver aid more effectively and sustainably in contentious environments. This raises the question: what went wrong? Informed by post-development theoretical arguments and through a discursive analysis of the DGF’s implementation of this new aid framework, this paper argues that this framework itself does not allow proper understanding of what makes aid “political”; in casu that it does not allow appreciation of local viewpoints of democracy, representation, and ownership. Then, rather than improving the status quo, this paper argues in favour of making aid “political” through a fundamental reconsideration of the very substance and infrastructure of aid itself.