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Radar arc and impairment detection and localization for the ITER ICRF antenna
No full textA RAdar Arc and impairments Detection and localization (RAAD) system for the protection of high-power RF transmission lines components is presented. It offers several benefits over existing techniques. It can perform fast detection, localization, and classification of arcs and impairments/degradations along the full path of the RF power (in less than 5 μs as required for the protection of ITER ICRF antenna). It also features completely independent operations from the RF power. The detection and monitoring of impairments/degradations enables the prevention of faults while the localization and classification of faults permits pinpoint maintenance operations. The RAAD system has been simulated in time domain adopting the Simulink tool, integrated into the complete ITER ICRF system (from the array antenna front-face up to the RF sources outputs, including the full transmission line and matching network). The radar signal is coupled into the transmission lines through a specifically designed coupling unit. Full wave simulations of the ITER ICRF system components have been performed in the radar bandwidth of operation, with and without arcs/impairments, to obtain S-matrices used in the time domain radar system simulations. All the arcs and impairments inserted in the components have been detected; the location obtained by the radar for each event has been compared to the one estimated analytically with excellent agreement. The radar simulations have demonstrated the ability to detect and localize arcs which cannot be detected by other systems such as low voltage arcs and series arcs. A solid solution, based on signal synchronization, for coping with high power interferences from ion cyclotron frequency harmonics in the radar bandwidth of operations has been implemented. Other events such as antenna load variations and matching elements modifications can be easily discriminated against arc events, being much slower than radar pulse repetition period. Next steps will be the implementation, testing and validation of a prototype of the complete RAAD system. This prototype will be tested on the ITER ICRF prototype antenna module and potentially on other operating ICRF installations
Finite element simulation of ICRF wave heating of core and edge plasmas in EAST
No full textIn recent years, simulations using the finite element method (FEM) have been conducted to study ion cyclotron resonance heating (ICRH) in the EAST tokamak (including SOL plasma). This paper improves the previous FEM for solving the perpendicular wavenumber [
Nucl. Fusion. 62. 7 076032 (2022)], aiming to correct the local deviation in solving the perpendicular wavenumber of cold plasma fast waves. Results show that ion cyclotron resonance heating of the minority ion H dominates energy absorption in the plasma core. The power absorption characteristics of ICRF waves are consistent with previous findings, with potential errors possibly caused by fast wave reflection on the high-field side. These results may provide a reference for future ICRF heating experiments and contribute to experimental optimization through program optimization
Low-frequency mode conversion of elastic waves enabled by coiling-up structures
No full textElastic wave mode conversion is a fundamental mechanism in wave manipulation. A key challenge is to achieve efficient longitudinal-to-transverse mode conversion at low frequencies. In this work, we numerically demonstrate that a pair of coiling-up structures embedded in a solid medium can induce nearly complete mode conversion at extremely low frequencies, where the wavelength is more than 50 times the structural period. Parametric studies and modeling reveal that the outermost opening of the coiling-up structure plays a dominant role in determining the conversion frequency. This structural detail has been largely overlooked in previous studies. A simplified Helmholtz resonator model is introduced to explain the observed effect. The proposed design offers a geometrically induced resonant yet structurally compact approach for low-frequency elastic wave control
Marketing Community-Based Approach to Food Security in Central Java
No full textThe Community-Based Marketing for Food Security (CBM-FS) Framework aims to enhance food security in Central Java, Indonesia, by addressing rice supply chain inefficiencies, market access barriers, and socio-economic constraints through community-driven marketing strategies. Drawing on literature from 2020 to 2025, this study identifies key challenges, research gaps, and integrates institutional Coordination, market access, community capacity, technology, and sustainability. A Python tool using Dijkstra's algorithm optimizes rice distribution logistics, reducing costs and delays. Supported by government regulations, the framework offers scalable, inclusive, and resilient solutions for food security. It aligns with Indonesia's national food sovereignty goals, fostering community empowerment and sustainable agricultural development
Intermediaries in Agricultural Supply Chains: Trends and Insights
No full textThe role of intermediaries in the agricultural supply chain has become a significant topic of interest due to their influence on efficiency, market access, and value addition. This study presents a bibliometric analysis aimed at getting a deeper understanding of the evolution of research on agricultural supply chain intermediaries. The analysis intends to identify key trends, influential studies, and emerging areas of interest that will contribute to the field of research. We retrieved metadata from the Scopus database, which included 1.074 articles published between 2014 and 2025. Statistical analysis was conducted to discover the leading publishers and authors in this field. A co-occurrence network and overlay visualization of author keywords were generated using VOS viewer to map the structure and progression of the research landscape. The analysis also presented emerging keywords and research issues corresponding to network visualization, highlighting this field's dynamic and evolving nature. These insights are valuable for researchers, policymakers, and practitioners seeking to understand and enhance the relationship between intermediaries and the agricultural supply chain
The Impact of Climate Change on the Profits of Chili Farms in Boyolali Regency
No full textThe agricultural sector, particularly cayenne pepper cultivation, is highly vulnerable to climate change, which poses a threat to food security and farmer profits. Therefore, this study aims to analyze the impact of climate change on the profitability of cayenne pepper farming in Boyolali Regency. Data were obtained from surveys and interviews with 60 farmers and analyzed using multiple linear regression after classical assumption tests. The results showed an average profit of Rp17,967,902.86 per hectare per planting season, which was relatively small. Simultaneously, all variables studied, including social, economic, and climate, significantly impacted profitability. The social variable showed a partially significant impact through labor, at the 95% level with a negative coefficient. The economic variable also had a partially significant impact through land area (99% significance) and household assets (99% significance), both with positive coefficients. Climate change variables significantly affected profitability, including damage from climate change (95% significance), high rainfall (95% significance), and drought (99% significance), all with a negative coefficient. Meanwhile, education, age, commodity prices, number of family members, and non-farm employment had no significant impact
Metabolomics Approach for Organic Agriculture to Assess Nutritional Quality and Build Consumer Trust
No full textOrganic farming plays an important role alongside conventional farming in the global food supply. Organic systems offer a sustainable alternative in agriculture. However, maintaining the nutritional consistency and build consumer trust of organic products remains a challenge. Metabolomics can help distinguish organic products from conventional products by analysing the biochemical composition of plants. This study used a simple systematic approach involving a search for scientific articles on Google Scholar over the past ten years (2014-2024). This review aims to examine the extent of metabolomics' role in contributing to organic farming, focusing on its comparison with nutritional studies and consumer perceptions. The results show that publications on metabolomics related to nutrition average 19,457 per year, metabolomics related to consumer perceptions average around 5,445 per year, and metabolomics related to organic farming average around 457 per year. Compared to metabolomics research related to nutrition, the contribution of metabolomics research to organic farming studies is only about 2.35%. Compared to metabolomics research related to consumer perceptions is only about 8.39%. This confirms that the use of metabolomics in the context of organic farming is still largely unexplored. In fact, organic farming is in dire need of scientific evidence regarding nutritional quality as well as building a more positive consumer perception. This study brings a new perspective for organic agricultural farmers to also focus on elaborating a metabolomics approach to improve the quality aspects that complement crop production quantity. The integration of metabolomics will strengthen nutritional claims, scientific transparency, credibility, and consumer trust
A Psychologically Informed Communication Model for Empowering Farmers Affected by Infrastructure Development in Indonesia's Agricultural and Food Systems
No full textTop-down communication practices commonly used in implementation Indonesia's National Strategic Projects tend to position farmers affected by these programs as passive recipients of information rather than active stakeholders. This study develops a communication framework grounded in psychological perspectives and enriched with socio-psychological and participatory development approaches to address these limitations and promote more responsive-inclusive interaction. Using descriptive qualitative research design, the study focuses on farmers impacted by construction of Solo-Yogyakarta toll road in Klaten Regency. It combines in-depth interviews with key stakeholders (farmers, local community leaders, and project management representatives) with quantitative data gathered through structured surveys. The findings indicate that mutual engagement, cultural relevance, and message consistency significantly enhance comprehension, acceptance, and cooperation while reducing resistance to project implementation. By integrating psychological concepts and principles of interpersonal communication into the analysis stakeholder engagement in infrastructure projects, this study advances the field development communication and offers transferable model for field practitioners and policymakers. Importantly, the model highlights communication as strategic tool for safeguarding agricultural livelihoods, maintaining local food production, and strengthening resilience of Indonesia's food systems amid expanding infrastructure development. So, it provides conceptual and practical bridge between infrastructure governance and development sustainable food system centered on farmers
Hand Gesture Recognition Model Using 2D Convolutional Neural Network
No full textHand gesture recognition is a crucial aspect of how we interact with computers, allowing machines to understand and respond to our movements in a natural way. This paper explores an advanced method for recognising hand gestures using a 2D convolutional neural network (2D CNN), a type of deep learning technology. We built and tested our model on a specialised dataset, evaluating its performance through several metrics, including loss function, accuracy, precision, recall, root mean squared error (RMSE), mean absolute error (MAE), and mean squared error (MSE). We compared two different data splitting ratios, 80:20 and 70:30, to determine which one performed better. Our approach effectively captures the complexities of hand gestures, thanks to the spatiotemporal features in the input data. To enhance the model's robustness against varying conditions, such as lighting, backgrounds, and hand positions, we also employed data augmentation techniques. Our findings indicate that the model achieved an impressive accuracy of 80% and a precision of 85% on the training data, along with solid results on the testing data, including an accuracy of 79%. Ultimately, the 80:20 data splitting ratio showed the best overall performance, highlighting its effectiveness for our gesture recognition task
Investigation of structural and morphological studies of Na
No full textSodium- ion conducting solid polymer electrolytes are considered a safe and sustainable alternative to liquid electrolytes for next- generation rechargeable batteries. In this work, nanocomposite membranes based on Poly (vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) and poly (vinyl chloride) (PVC) blend complexed with sodium tetrafluoroborate (NaBF4) and reinforced with TiO2 nanoparticles were fabricated by solution casting method. The recorded X-ray diffraction (XRD) patterns of these films revealed a significant reduction in polymer crystallinity upon the incorporation of salt and nanofiller, indicating enhanced amorphous character, which is favourable for ion transport. Scanning electron microscopy (SEM) confirmed a uniform dispersion of TiO2 and the formation of a porous, interconnected microstructure at intermediate TiO2 loadings. At higher filler concentrations, agglomeration and reduced porosity were observed, correlating with diminished structural uniformity. In brief, the findings confirm that TiO2 nanofillers are capable of directing the morphology and chain packing of PVDF-HFP/PVC/NaBF4 electrolytes, thereby paving the way for their use as solid electrolytes in sodium-ion energy storage systems