Analytical Framework Research Articles

Integrative Approaches to Abiotic Stress Management in Crops: Combining Bioinformatics Educational Tools and Artificial Intelligence Applications

Abiotic stresses, including drought, salinity, extreme temperatures and nutrient deficiencies, pose significant challenges to crop production and global food security. To combat these challenges, the integration of bioinformatics educational tools and AI applications provide a synergistic approach to identify and analyze stress-responsive genes, regulatory networks and molecular markers associated with stress tolerance. Bioinformatics educational tools offer a robust framework for data collection, storage and initial analysis, while AI applications enhance pattern recognition, predictive modeling and real-time data processing capabilities. This review uniquely integrates bioinformatics educational tools and AI applications, highlighting their combined role in managing abiotic stress in plants and crops. The novelty is demonstrated by the integration of multiomics data with AI algorithms, providing deeper insights into stress response pathways, biomarker discovery and pattern recognition. Key AI applications include predictive modeling of stress resistance genes, gene regulatory network inference, omics data integration and real-time plant monitoring through the fusion of remote sensing and AI-assisted phenomics. Challenges such as handling big omics data, model interpretability, overfitting and experimental validation remain there, but future prospects involve developing user-friendly bioinformatics educational platforms, establishing common data standards, interdisciplinary collaboration and harnessing AI for real-time stress mitigation strategies in plants and crops. Educational initiatives, interdisciplinary collaborations and trainings are essential to equip the next generation of researchers with the required skills to utilize these advanced tools effectively. The convergence of bioinformatics and AI holds vast prospects for accelerating the development of stress-resilient plants and crops, optimizing agricultural practices and ensuring global food security under increasing environmental pressures. Moreover, this integrated approach is crucial for advancing sustainable agriculture and ensuring global food security amidst growing environmental challenges.

Mobile genetic elements of Xylella fastidiosa and their contribution to pathogenicity

AbstractXylella fastidiosa is a destructive bacterial plant pathogen affecting hundreds of plant families, including important crops such as olive and citrus trees and vines. The pathogenicity of this bacterium rests in a group of genes that encode toxins, enzymes, fimbrial/afimbrial adhesins, cell–cell aggregation proteins and other virulence factors. We investigated the contribution of mobile genetic elements (MGEs) to the pathogenicity of X. fastidiosa. Using computational tools, we analysed 94 X. fastidiosa genomes corresponding to the three most important subspecies to identify insertion sequences (ISs) and prophages. Results indicate that the distribution and diversity of ISs are modest, with a few families widespread throughout the subspecies of X. fastidiosa. The prophages are abundant, and play a more significant role in the pathogenicity of X. fastidiosa. Prophages are common in the subspecies of X. fastidiosa and contribute to numerous genes related to pathogenicity. The phylogenetic analyses suggest that prophages are recently acquired and that the rearranging of pathogenicity genes triggered by them could generate strains with new pathogenic capacities. Finally, the contribution of MGEs to the pathogenesis of X. fastidiosa was evidenced by determining their association with virulence genes using a Bayesian framework for phylogenetic analysis of character evolution.

Spatially resolved analysis of pancreatic cancer identifies therapy-associated remodeling of the tumor microenvironment.

In combination with cell-intrinsic properties, interactions in the tumor microenvironment modulate therapeutic response. We leveraged single-cell spatial transcriptomics to dissect the remodeling of multicellular neighborhoods and cell-cell interactions in human pancreatic cancer associated with neoadjuvant chemotherapy and radiotherapy. We developed spatially constrained optimal transport interaction analysis (SCOTIA), an optimal transport model with a cost function that includes both spatial distance and ligand-receptor gene expression. Our results uncovered a marked change in ligand-receptor interactions between cancer-associated fibroblasts and malignant cells in response to treatment, which was supported by orthogonal datasets, including an ex vivo tumoroid coculture system. We identified enrichment in interleukin-6 family signaling that functionally confers resistance to chemotherapy. Overall, this study demonstrates that characterization of the tumor microenvironment using single-cell spatial transcriptomics allows for the identification of molecular interactions that may play a role in the emergence of therapeutic resistance and offers a spatially based analysis framework that can be broadly applied to other contexts.

Domestic and Family Violence Screening and Response: A Prospective, Cross-Sectional, Mixed Methods Survey in Private Mental Health Clients.

Most domestic and family violence (DFV) research has focused on establishing prevalence and screening rates in public health and community samples. This study sought to address a gap in the literature by evaluating DFV screening and response practices in a private mental healthcare inpatient service and determining if clients of the service had unmet DFV needs. A prospective, convenience sample, mixed methods, cross-sectional survey of adult inpatient mental health consumers was employed. Sixty-two participants completed the Royal Melbourne Hospital Patient Family Violence Survey. Quantitative Likert-type and categorical responses were collated and analysed descriptively (count and percentage). Free-text responses were analysed using qualitative description within a content analysis framework. Sixty-five percent of participants had been screened for at least one DFV issue, on at least one occasion, with 35% not being screened, to their recall. Twenty-three percent reported disclosing DFV concerns, 82% felt very supported by the clinician's response to their disclosure, and 86% were provided with information they found helpful. Unmet needs were identified in 13% of participants, who had wanted to disclose DFV concerns but not feel comfortable to do so. No unscreened respondents disclosed DFV concerns, highlighting the need to uphold best practice guidelines for direct enquiry. Most disclosing clients were positive about the support they received. Indicated areas for improvement were screening rates, active follow-up, increasing psychology support levels and safety planning.

Resolvent Analysis for Subsonic Compressor With Impedance Boundary Condition Casing Treatment

Abstract A resolvent analysis framework for the axial compressor is established, and the impedance optimization is achieved based on the resolvent analysis framework for the impedance boundary condition casing treatment. This framework is derived by treating the nonlinearity in the perturbation equations as an unknown forcing, the linear relationship between wall impedance and energy gains is obtained. The validity of this framework is confirmed through experiments on rotating inlet distortion, which captures the most susceptible frequency for the stall points of the compressor. The resolvent analysis framework further confirms that the first-order circumferential mode exhibits the highest energy in the given cases. Subsequently, the proposed impedance optimization method is tested under throttling operating conditions, especially focusing on the first-order circumferential mode. The introduction of a favorable impedance boundary condition notably reduces energy gain within the low-order circumferential mode and in the range of the rotor rotating frequency, particularly in near-stall operating conditions. The energy suppression mechanism of the impedance boundary condition casing treatment is investigated, demonstrating that the impedance boundary condition, with an optimal impedance value, significantly suppresses perturbations compared to the case with the solid wall boundary condition. Lastly, a design method for the impedance boundary condition casing treatment is discussed, offering a reliable theoretical design tool for enhancing the stall margin of axial compressors.

Stochastic Dynamic Buckling Analysis of Cylindrical Shell Structures Based on Isogeometric Analysis

In this paper, we extend our previous work on the dynamic buckling analysis of isogeometric shell structures to the stochastic situation where an isogeometric deterministic dynamic buckling analysis method is combined with spectral-based stochastic modeling of geometric imperfections. To be specific, a modified Generalized-α time integration scheme combined with a nonlinear isogeometric Kirchhoff–Love shell element is used to simulate the buckling and post-buckling problems of cylindrical shell structures. Additionally, geometric imperfections are constructed based on NURBS surface fitting, which can be naturally incorporated into the isogeometric analysis framework due to its seamless CAD/CAE integration feature. For stochastic analysis, the method of separation is adopted to model the stochastic geometric imperfections of cylindrical shells based on a set of measurements. We tested the accuracy and convergence properties of the proposed method with a cylindrical shell example, where measured geometric imperfections were incorporated. The ABAQUS reference solutions are also presented to demonstrate the superiority of the inherited smooth and high-order continuous properties of the isogeometric approach. For stochastic dynamic buckling analysis, we evaluated the buckling load variability and reliability functions of the cylindrical shell with 500 samples generated based on seven nominally identical shells reported in the geometric imperfection data bank. It is noted that the buckling load variability in the cylindrical shell obtained with static nonlinear analysis is also presented to show the differences between dynamic and static buckling analysis.

A Multicultural Islamic Religious Education Curriculum Development

Curriculum development is often based on inappropriate strategies, due to a lack of comprehensive understanding of objectives, starting points, methods and functions. This study examines the development of multicultural Islamic Religious Education (PAI) curriculum in Da’wa Management Study Program (Prodi MD), Faculty of Da’wah and communication of Sunan Kalijaga State Islamic University Yogyakarta. Type of qualitative research, with the method of Case Studies (case study). The approach used is Curriculum Development. The theory used as a framework for analysis is The Theory of Grass-Roots Initiative. Research findings show that the Da’wa Management Program the faculty of Da’wa Management and communication UIN (State Islamic University) Sunan Kalijaga developed a multicultural PAI curriculum in response to the development and needs of the community. Therefore, curriculum development is centered on the field experience of the academic community, both educators and learners. The paradigm used during the development process is naturalist-inclusive, where the material, learning process, and output are directed towards one goal, namely students who are tolerant, moderate, and able to bridge social gaps, both in the classroom and in society and industry. This article contributes to providing guidance for integrating multicultural values ​​into the Islamic Religious Education curriculum, in order to create inclusive and responsive learning towards diversity.

Parallel isogeometric boundary element analysis with T-splines on CUDA

We present a framework for parallel isogeometric boundary element analysis (BEA) of elastic solids on CUDA. To deal with traction discontinuities, we propose a BEA model that supports multiple nodes and semi-discontinuous elements. The multiplicity of a node is defined by the number of regions containing any element influenced by the node. A region is a group of connected elements delimited by a closed crease curve. The default shape function of an element is determined by a linear operator applied to a set of basis functions. A BEA model is supposed to be generated from a watertight boundary representation of a solid. In this paper, we employ bicubic analysis-suitable T-splines. In this case, the shape of an element is defined by its Bézier extraction operator applied to the tensor product of Bernstein polynomials of degree 3. We describe the data structures of the BEA model and the main algorithms of the analysis pipeline on CUDA. In particular, we describe two strategies for parallel assembling of the linear system of equations. We also introduce a novel approach for inside integration based on the subdivision of the singular region in triangles with constant aspect ratio. In the T-splines context, we extend the Bézier extraction to handle unstructured T-meshes with crease edges. Moreover, we propose a scheme for embedding the influence of linked tangency handles on the shape of an element directly into the Bézier extraction operator. Such an embedding enables the removal of the corresponding nodes from the BEA model and the application of an alternative collocation method we discuss in the paper. We present several experiments to evaluate the accuracy and efficiency of the proposed framework. The results demonstrate that the GPU can be advantageously employed for parallelizing T-spline-based isogeometric analysis using boundary elements, achieving a speedup of up to 29x compared to the sequential code on a current laptop. We make the BEA code available in a prototype in MATLAB with a graphical interface that allows users to apply boundary conditions and visualize analysis results on the boundary.

Using Normalisation Process Theory to explore the contribution of stakeholder workshops to the development and refinement of a complex behavioural intervention: the STAMINA lifestyle intervention

BackgroundThe National Institute for Health and Care Excellence (NICE) recommend that men with prostate cancer on androgen deprivation therapy (ADT) are offered twice weekly supervised aerobic and resistance exercise to address side effects of treatment. However, supervised exercise is not routinely offered in standard clinical practice. The STAMINA programme grant for applied research (PGfAR) has been designed to evaluate whether this recommendation can be delivered within standard NHS care. This paper describes how future implementation of NICE recommendations within the NHS was explored during complex intervention development to enable evaluation of a lifestyle intervention.MethodsTwo stakeholder workshops were conducted to explore factors pertinent to future implementation of the STAMINA Lifestyle intervention (SLI). Normalisation Process Theory (NPT) provided the theoretical framework for discussion and analysis. Stakeholder workshop 1 focussed on intervention coherence and buy-in. Stakeholder workshop 2 explored barriers and facilitators for embedding SLI into the context of the NHS, with delivery partner Nuffield Health, in the future.ResultsWorkshops were attended by healthcare professionals (n = 16), exercise professionals (n = 17), members of public involved in PPI including patients (n = 12), health psychologists (n = 2), clinical commissioners (n = 4), cancer charities (n = 3), a cancer alliance (n = 1) and health economist (n = 1). Stakeholders agreed that professional training packages should emphasise the uniqueness of the SLI and underpinning theory and evidence (Coherence). To further engagement, the use of STAMINA champions and information about the delivery partner were recommended to enhance confidence and knowledge (Cognitive participation). Furthermore, a simple communication (Collective Action) and progress reporting system (Reflexive Monitoring) was suggested to fit into existing infrastructure within the NHS and community partner.ConclusionsApplication of NPT within two stakeholder workshops enhanced complex intervention development. Context-specific strategies to support implementation of SLI within the context of a trial were proposed, sensed-checked, and considered acceptable. The organisational implications of embedding and sustaining the intervention in preparation for wider NHS roll-out were considered (if proven to be effective) and will be explored in the qualitative component of a process evaluation underpinned by NPT.Trial registration(ISRCTN: 46385239). Registered on July 30, 2020.

Mapping Public Health Nursing competencies: A comparative document analysis of competency frameworks and practice standards in the USA and Ireland.

The Public Health Nursing discipline plays a crucial role in promoting sustainable health services. The establishment of competency frameworks and practice standards pertaining to Public Health Nursing has emerged as a cornerstone for guiding practice, education, and research. This study aimed to identify contemporary Public Health Nursing competency frameworks and practice standards and establish a robust list of competency domains. This will inform a subsequent phase of this project that will conduct a review of recent scholarly literature to discern prevailing research trends and delineate strategic directives and research priorities for the discipline. A systematic search of three databases and a grey literature search was undertaken by incorporating keywords to identify existing Public Health Nursing-specific competency frameworks and practice standards. Through screening and selection based on our inclusion criteria, three documents were analyzed. A comprehensive document analysis was conducted to generate a unified domain list and associated descriptors. Three competency-based frameworks and practice standards emanating from two countries, the United States of America and the Republic of Ireland met the inclusion criteria. The document analysis identified 16 individual domains. There was consistent evidence of similarity across the three documents. There were minimal divergences featured within the frameworks which are discussed and compelling justifications for inclusion as universal domains are provided. This document analysis has generated a list of 16 common Public Health Nursing competency domains which will be utilized in phase two of this project as a foundational framework for the purpose of analyzing research trends, influencing research priorities, and enhancing the focal areas for future research agendas within the discipline.

An improved time series SAR interferometry (TSInSAR) for investigating earthquake-induced active unstable slopes (AUS) in Pakistan

ABSTRACT Time series interferometric SAR (TSInSAR) techniques face challenges related to the availability of highly coherent point targets in non-urban, vegetated, and mountainous regions. In this study, we tested an improved TSInSAR approach with the help of distributed scatterers (DS) detected through the fast statistically homogeneous pixel selection (faSHP) approach and jointly processed with persistent scatterers (PS) within the interferometric point target analysis (IPTA) framework. The method is applied to a seismically active and highly gradient terrain to investigate the earthquake-induced active unstable slopes (AUS) in the Muzaffarabad-Balakot region of northern Pakistan, particularly using sixteen PALSAR-2 images acquired between October 2014 and May 2020. However, its effectiveness was also assessed by using Sentinel-1 data from the same time period. The quantitative assessment showed the effectiveness of the method in delineating the sliding surfaces of the unstable slopes and achieving approximately four times higher point density as compared to the standard PSI approach when applied to PALSAR-2 data and approximately nine times higher point targets when Sentinel-1 data is used. Exhibiting an average deformation rate varying between −40 mm yr−1 and 20 mm yr−1 along the line of sight (LOS) direction, the obtained results from PALSAR-2 data revealed the existence of 451 AUS in the region. The study also reports the discovery of a giant destabilized slope (~2.30 sq. km) located near Patika Village along the Neelam River. The majority of these unstable slopes are found at altitudes above 780 m, with slope angles ranging from 15 to 50 degrees. The study also found a significant correlation between deformation patterns and local precipitation. The rainwater gradually penetrates into the joints and cracks, accelerating the processes of deformation and slope failure. The research and its findings could help decision-making entities by providing first-hand information for managing the risks associated with slope failure.

Solving Neutrosophic Multi-Dimensional Fixed Charge Transportation Problem

In the decision making problems, transportation problem (TP) is one of the most significant applications that aim to optimize the objective function of products shipped from different sources to different destinations. When an additional charge such as toll tax, parking fee, permit fee and so on are included in the transportation cost then the problem becomes a fixed charge TP. If the shipped products are damageable, they are affected by the type of vehicle and the distance of route. So it is quite evident that the vehicle type and the distance of route play a significant role in TP. In reality, along with sources and destinations, the decision maker (DM) desires to consider the parameters such as the mode of transport and routes of transportation that are used for shipment of the products from sources to destinations in order to minimize the loss of damageable products and to maximize the profit. As a result, mode of transport and routes of transportation are added to TP, then the TP becomes a four-dimensional TP. Sometimes, the data/parameters of the problems may not be always precise due to incomplete information, inadequate data or shortage of evidence. To deal with these obstacles, the parameters of the problem can be represented as the single-valued trapezoidal neutrosophic numbers (SVTrNNs). The neutrosophic data facilitate a reasonable and practicable way for DMs to tackle decisionmaking problems by managing indeterminacy and providing an effective framework for analysis and synthesis of complex decision scenarios. In view of this, in this paper we have considered the single objective four-dimensional fixed charge transportation problem (4DFCTP) with parameters, supply, demand, conveyance, transportation cost, fixed charge as single-valued trapezoidal neutrosophic numbers and the distance of routes as real numbers. First, the score function is utilized to transform the neutrosophic parameter into its deterministic parameter in order to avoid the negative values for the decision variable. Then the deterministic problem comprises deterministic parameters such as supply, demand, conveyance, transportation cost with fixed charges and distance of routes. Secondly, a novel approach namely, min zeromin cost approach is introduced for finding the optimal solution to the equivalent deterministic problem in polynomial time. The main objective of this paper is to optimize the breakable products and routing plan of vehicles in a way to minimize the total transportation cost with fixed cost of the business organizations using the proposed min zero-min cost approach. To demonstrate the problem’s validity and relevance, two numerical examples are solved using our proposed approach. To highlight the proposed approach, comparison of the solution with the LINGO software is performed. The obtained optimal solution from the proposed approach is the same as the LINGO software. At last, conclusions as well as future work related to the study are presented.

The EU soft regulation of digital campaigning: regulatory effectiveness through platform compliance to the code of practice on disinformation

ABSTRACT How does the European Union handle the soft regulation of digital political campaigning? We assesses the effectiveness of the EU's soft governance concerning digital campaigning by examining how global digital platforms respond to the EU Code of Practice on Disinformation. In doing so, we advance a framework for analysis which measures specific steps in the platform compliance with soft law. Our results, based on the content analysis of platforms' annual reports, show that compliance depends on the priority assigned to regulatory themes by on-line corporations. Overall, we find higher levels of platform formal commitment rather than symbolic commitment through forms of report editing to signal compliance with the code of practice. Our analysis also shows evidence of implementation following from formal commitments when reporting requirements are less rigid. Consequently, EU soft governance can be effective for digital campaigning in areas prioritised by the addressees of regulation.

Becoming Self Employed: Israeli Family Physicians' Push and Pull Factors.

As primary care is an important infrastructure for the entire health system, the employment structure choices of family physicians-whether to work in a managed care organization or be self-employed, can impact all effectiveness parameters of healthcare: quality, access, health equity, patients' experiences, and cost-effectiveness. The aim of this study is to assess the push and pull factors influencing family physicians' employment choices. This study employed a qualitative approach to explore the experiences of family physicians (FPs) who choose to work a self-employment practice. We conducted semi-structured interviews with twenty-seven self-employed FPs in Israel, selected through purposive and snowball sampling. The interviews were conducted via Zoom, recorded, and transcribed verbatim. Data analysis followed thematic analysis framework. The analysis yielded 10 themes, which were organized into two categories: pull and push factors. Pull factors, i.e., factors that attract family physicians to become self-employed, included professional self-fulfillment, higher income, professional and business autonomy, working with secretaries according to one's personal choice, designing the space of the clinic, and flexibility in working hours. Push factors, i.e., factors that demotivated family physicians to work under managed care and pushed them to choose self-employment included low control over the work environment, workload, decreased professional and organizational autonomy, managerial pressures on quality measures, engagement in marketing activities, and tensions with non-medical staff in the Health Maintenance Organization. There are obvious implications of this work for Health Maintenance Organizations' policy makers. Balancing managerial pressure and tensions between family physicians and non-medical administration and ensuring suitable working conditions increased physicians' control over the work environment, and professional autonomy may decrease push factors and retain family physicians as Health Maintenance Organization-employed. Understanding pull factors may help to develop a strategy for maximizing cooperation with self-employed family physicians and reinforce physicians' linkage to the healthcare system's treatment objectives.

Dynamic uncertainty propagation analysis framework for nonlinear control problem based on manifold learning and optimal polynomial method and its application on active suspension system

A novel uncertainty propagation method based on manifold learning and optimal polynomial model is proposed to quantify and analyze the dynamic uncertainties of the nonlinear feedback control system. To deal with the multiple objectives and constraints of the nonlinear control problem, a barrier Lyapunov-function-based nonlinear filtered backstepping controller is developed and applied to active suspension system to obtain superior ride comfort performance under limited structural constraints. Considering the errors in the production, manufacturing, and assembly, the probability density function is employed to quantify the structural parameter uncertainties in the nonlinear control system. Moreover, to reveal the dynamic propagation mechanism of uncertainties in the system with nonlinearity, the manifold learning method is proposed to reduce the dimensionality of the dynamic system to avoid the complexity of uncertainty propagation. Simultaneously, data-driven optimal polynomial model is utilized to accurately approximate the internal mechanism of nonlinear filtered backstepping control system. Based on that, the response uncertainties of the nonlinear control system are accurately and quickly quantified through dynamic moment information and uncertain fluctuation space. Finally, an active suspension system with nonlinearities and uncertainties is developed to verify the effectiveness of the controller with improved ride comfort and better handling safety and the superiority of the framework in terms of efficiency and accuracy of the dynamic uncertainty propagation analysis for nonlinear control problem.

Detection and Reconstruction of Bursting Oscillations in Complex Systems Using the HAVOK Analysis Framework

Multi-scale dynamical systems may exhibit bursting oscillations, which are typically identified by analyzing time series and phase portraits. However, in cases where bursting oscillations are not apparent, relying solely on these methods may have limitations in accurately detecting their occurrence. This paper introduces the HAVOK analysis framework to the field of bursting oscillations. By using single-variable time series data, models that may produce bursting oscillations are restructured into forced linear models. This approach allows for the rapid prediction of bursting oscillations by observing the forced terms. The results show that the intermittent periodic bursts in the visualizations of the forced eigen time series within the HAVOK framework are strongly correlated with the excitation states in bursting oscillations, enabling the prediction of their occurrence. Especially in cases where it is challenging to determine the presence of bursting oscillations through time series plots alone, this method can still sensitively detect them. Additionally, the embedded and reconstructed flow fields plotted using this approach can help understand the dynamics of bursting oscillations in certain scenarios.

Automated analysis framework of strain partitioning and deformation mechanisms via multimodal fusion and computer vision

Simultaneously investigating strain partitioning and the underlying deformation mechanisms for both the grain interior and the grain boundary (GB) is essential for understanding the complex plastic deformation of hexagonal close-packed metals. To this end, an automated analysis framework based on high-resolution digital image correlation (HRDIC) and electron backscatter diffraction (EBSD) data fusion and computer vision, integrating nanoscale resolution and a large field of view, is proposed. This framework consists of: (1) HRDIC-EBSD data fusion; (2) Segmenting the strain field into individual grains each with a core and a mantle; (3) Data clustering of the Matrix and slip bands (SBs) for each grain; (4) Full slip system (SS) identification and SS assignment to the SBs. The capabilities of this framework were demonstrated on Mg-10Y during compression. The strain field data, which was segmented into different clusters, including grain mantle, grain core, Matrix, and SBs, was analyzed statistically and quantitatively. The pixel-based slip activity, which considers the SB morphology, was obtained from a statistical perspective. Inter-granular accommodating mechanisms, including GB strain, slip transfer, and GB sliding, were quantitatively analyzed. Overall, this analysis framework, which can be applied to other materials, can automatically and statistically evaluate both nanoscale strain fields and underlying intra- and inter-granular deformation mechanisms grain-by-grain. This work provides valuable experimental insights into plastic deformation and accommodation mechanisms for polycrystals.

Patterns of change, driving forces and future simulation of LULC in the Fuxian Lake Basin based on the IM-RF-Markov-PLUS framework

Studying land use and land cover (LULC) patterns, identifying driving forces, and simulating future scenarios are vital for grasping the complex connection between human actions and the environment. This helps in shaping sustainable land management strategies and preparing for the impacts of climate change. However, there is a necessity for a comprehensive system modeling framework that can accurately capture spatial and temporal changes in LULC, analyze driving mechanisms, and provide an integrated analysis of future simulations. In this paper, a comprehensive IM-RF-Markov-PLUS analysis framework is developed, focusing on the Fuxian Lake Basin (FLB) as a study area. The study aims to achieve accurate prediction of LULC by combining the microscopic LULC change trend and the contribution of macroscopic driving forces. The results show that: (1) The IM-RF-Markov-PLUS framework can explore the change patterns and driving mechanisms of LULC in the FLB, and accurately predict the LULC in the FLB. Compared with the PLUS model, its accuracy is improved by 2 %. (2) IM analysis reveals that LULC transformation in the FLB is both general and specific. Although the area of grassland, buildings, roads and structures converted to desert and bare land is minimal, it shows relatively tendentious and specific change characteristics. (3) Different land types are significantly affected by driving factors, with the expansion of LULCs is constrained by major factors. The distance to the lake has the most significant impact on the distribution of garden land, while the primary road has the greatest impact on the distribution of forestland. (4) Under different scenarios, the spatial heterogeneity of LULC patterns is obvious. In 2035, under baseline and economic development scenarios, cultivated land will decrease, while other LULC types will increase. Under the cultivated land protection scenario, cultivated land is protected, with an increase of 5.85 %. Under the ecological protection scenario, there is an increase in ecological land. The largest increase is in forestland, which increases by a total of 3.46 %. The ecological protection scenario presents a viable approach for ensuring the sustainable development of the FLB. The results of this paper may serve as a reliable foundation for implementing LULC strategies in the FLB and offer guidance for crafting sustainable development regulations at the regional level.

LSTM-GCN based multidimensional parameter relationship analysis and prediction framework for system level experimental bench

In nuclear power plants (NPPs) operations, the prediction of multi-dimensional parameters is found to help operators to grasp the condition of the system. However, majority of existing studies are focused on single-dimensional parameter prediction. In this study, a multi-dimensional parameter prediction framework of NPPs based on Long Short-Term Memory Network and Graph Convolution Network (LSTM-GCN) and a multi-model integrated parameter correlation analysis framework (PCAF) are proposed, in which PCAF is used to build a parameter correlation network for GCN, and LSTM-GCN is used to predict multi-dimensional parameter of NPPs. To verify the feasibility of the LSTM-GCN framework, multi-dimensional parameter prediction researches are conducted using data from a thermohydraulic experimental bench that simulates the operation of NPPs. Results indicate that compared to traditional prediction models, LSTM-GCN framework enhances the prediction accuracy of multi-dimensional parameter, which benefits from the ability of LSTM-GCN to utilize the temporal dependencies and spatial correlations of parameters.

Synthesis of agro-industrial wastes/sodium alginate/bovine gelatin-based polysaccharide hydrogel beads: Characterization and application as controlled-release microencapsulated fertilizers

Synthesis of novel agro-industrial wastes/sodium alginate/bovine gelatin-based polysaccharide hydrogel beads, micromeritic/morphometric characteristics of the prepared formulations, greenhouse trials using controlled-release microencapsulated fertilizers, and acute fish toxicity testing were conducted simultaneously for the first time within the scope of an integrated research. In the present analysis, for the first time, 16 different morphometric features, and 32 disinct plant growth traits of the prepared composite beads were explored in detail within the framework of a comprehensive digital image analysis. The hydrogel beads composed of 19 different agro-industrial wastes/materials were successfully synthesized using the ionotropic external gelation technique and CaCl2 as cross-linker. According to micromeritic characteristics, the ionotropically cross-linked beads exhibited 77.86 ± 3.55 % yield percentage and 2.679 ± 0.397 mm average particle size. The dried microbeads showed a good swelling ratio (270.02 ± 80.53 %) and had acceptable flow properties according to Hausner's ratio (1.136 ± 0.028), Carr's index (11.94 ± 2.17 %), and angle of repose (25.03° ± 5.33°) values. The settling process of the prepared microbeads was observed in the intermediate flow regime, as indicated by the average particle Reynolds numbers (169.17 ± 82.81). Experimental findings and non-parametric statistical tests reveal that dried fertilizer matrices demonstrated noteworthy performance on the cultivation of red hot chili pepper plant (Capsicum annuum var. fasciculatum) according to the results of greenhouse trials. Surface morphologies of the best-performing fertilizer matrices were also characterized by Scanning Electron Microscopy. Moreover, the static fish bioassay experiment confirmed that no abnormalities and acute toxic reactions occurred in shortfin molly fish (Poecilia sphenops) fed with dried leaves of red hot chili pepper plants grown with formulated fertilizers. This study showcased a pioneering investigation into the synthesis of microcapsules using synthesized hydrogel beads along with digital image processing for bio-waste management and sustainable agro-application.