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Feasibility of
No full textSeaweed is a major source of foreign exchange and a leading export commodity in the fisheries sector. Seaweed farming offers many advantages, it also involves high risks. Study aims to analyze the feasibility of farming green and red varieties of Kappaphycus alvarezii, both from financial and nonfinancial perspectives. Research was conducted in Kawite Wite Village, Kabawo District, Muna Regency, Southeast Sulawesi Province. Nonfinancial analysis employed descriptive methods, while the financial feasibility was assessed using investment criteria, NPV, Net B/C, IRR and PP. Results of the nonfinancial feasibility analysis indicate that nearly all treatments in the seaweed farming business are considered feasible to implement. In the financial analysis, G50 treatment cultivation of the green variety of K. alvarezii at a distance of 50 m from the coastline was found to be financially feasible. However, R50 treatment cultivation of the red variety at the same distance was deemed not feasible. Both G75 treatment (green variety at 75 m) and R75 treatment (red variety at 75 m) were found to be financially feasible. Likewise, G100 treatment (green variety at 100 m) and R100 treatment (red variety at 100 m) were also considered feasible. Among all treatments, G100 demonstrated the best performance
Analysis of carbon footprint in fish cold storage using IoT-based inventory monitoring
No full textFish cold storage is a critical component for preserving product quality, yet it represents a major source of energy consumption and carbon emissions within the global fisheries supply chain. This study establishes a comprehensive four-year baseline of environmental impact by analyzing historical electricity data from 2020 to 2023 at a cold storage facility in Jakarta. This analysis revealed a cumulative carbon footprint of 396.42 tons of CO₂, providing the necessary justification for technical interventions. To address the documented inaccuracies in traditional stock recording that hinder precise emission modeling, a low-cost IoT-based instrument was developed using an ESP8266 microcontroller and a keypad–LCD interface. Field deployment conducted from July to September 2024 validated the system's operational reliability, achieving a high recording accuracy of 99.3% and a stable cloud-based data transmission success rate of 97.8%. By integrating these historical energy patterns with real-time digital inventory monitoring, this research offers a practical and scalable foundation for enhancing data transparency and energy efficiency. Such innovations are essential for supporting sustainable management and driving the digital transformation of the fisheries sector within the broader Blue Economy *framework
Distribution changes of seagrass beds area using sentinel-2A imagery in lancang island, seribu island, Indonesia
No full textSeagrass is a flowering plant (angiosperm) that inhabits shallow waters and plays a vital ecological role as a breeding ground, habitat, and food source for marine organisms. However, increasing human activities, including waste disposal, fishing, and coastal tourism, have contributed to the degradation of seagrass ecosystems. This study aims to map the spatial distribution and temporal changes of seagrass areas using Object-Based Image Analysis (OBIA) in the waters of Lancang Island, Seribu Islands, Indonesia. Image processing involved segmentation and multi-level classification (levels 1, 2, and 3) with optimal segmentation scales of 50, 10, and 1, respectively. The classification results identified three categories: non-seagrass, sparse seagrass, and dense seagrass. In 2016, seagrass covered 68.16 ha but declined to 42.37 ha by 2023, while non-seagrass areas expanded from 123.11 ha to 146.59 ha. Land-cover transitions revealed a conversion of 37.84 ha from seagrass to non-seagrass and 12.04 ha from non-seagrass to seagrass. Overall, seagrass experienced a net loss of 37.88 ha during the study period. The classification achieved an overall accuracy of 70%
Digital Media Engagement and Health Communication: Analyzing YouTube Reactions to a Brain Dead Pregnant Woman Case
No full textPublic discourse and emotional engagement on YouTube surrounding a controversial case of a brain-dead pregnant woman maintained on life support to sustain fetal development are examined in this study. A mixed methods design was used to analyze the comments on YouTube videos related to the case of a brain-dead pregnant woman kept on life support to allow the fetus to live. Machine driven classification of open responses (MDCOR) was used to identify how users constructed their comments around discursive frames and sentiment and affective network analysis (SENA) was used to determine if there were any differences in sentiment across the videos from different sources. Additionally, the study explored how health literacy emerged as a thematic pattern. The analysis revealed that the public’s responses to this controversial issue constructed different types of responses reflecting different attitudes and emotions towards the case. These in turn revealed differences in health literacy and in access to credible health information sources
Phase transitions and ensemble inequivalence in the generalized Curie–Weiss model with quartic interaction
No full textWe investigate the thermodynamic properties of a generalized Curie–Weiss model incorporating both conventional pairwise spin interactions and an additional quartic four-body interaction term with coupling strength I. Through exact analysis in both canonical and microcanonical ensembles, we demonstrate that this minimalistic model exhibits rich phase behavior including continuous and discontinuous phase transitions, ensemble inequivalence, and a tricritical point at . In the canonical ensemble, the transition changes from second order to first order as the quartic coupling I increases beyond the tricritical value. The microcanonical ensemble reveals additional anomalous features including negative specific heat and temperature jumps at first-order transitions. The model provides a paradigmatic example of how simple mean-field systems with higher order interactions can capture the complex phenomenology of long-range interacting systems, including ergodicity breaking and ensemble inequivalence, without requiring spatial complexity
From Fault Tolerance to Fault Detection: A DHR-Based Contrastive Testing Method and Its Validation on ADAS
No full textMany modern complex systems, such as advanced driver assistance systems (ADAS), face the problems of dynamic and diverse test environments and unpredictable test results when performing black-box testing. This may lead to imprecise fault localization and low test efficiency. Inspired by the Dynamic Heterogeneous Redundancy (DHR) architecture in the field of network security, this paper proposes a contrastive testing method to solve these problems. The core innovation of this method is the concept transfer from ``fault tolerance redundancy" to ``error detection redundancy." This approach uses a set of functionally equivalent but heterogeneous executors to expose defects in the Unit under Test (UUT) through output inconsistencies. The proposed framework is built on a hierarchical system architecture, which supports progressive testing from the top module to the bottom module to complete the precise localization of defects. The heterogeneity of these reference implementations (RIs) is the key to reducing common mode failures, which is ensured by a multidimensional quantization model. The majority consensus adjudication automates defect detection by treating the output of the majority of RIs as a behavioral baseline, eliminating the need for a priori expectations. Experimental results on an ADAS show that our approach reduces the testing time by 63.9% and successfully transitions the DHR architecture from cybersecurity to the testing domain, providing a robust and scalable solution for testing heterogeneous and uncertain systems under intellectual property (IP) constraints
Computational investigation of a superhard all-
No full textCarbon is one of the most fundamental elements in nature hosting comprehensive allotropes, the understanding of carbon is one of the central topics in condensed-matter physics and materials sciences. In this work, we report by ab initio calculations a systematic investigation on an all-sp3 hybridized carbon allotrope. This carbon structure has a body-centered cubic unit cell in symmetry ( , space group No. 206) with 64 carbon atoms, which can be discovered through a graph theoretic structural search method originally identified by Shi et al. (Phys. Rev. B, 97 (2018) 014104), and we term it as BC64 carbon in the present work. The dynamical stability of BC64 carbon has been confirmed with phonon band spectrum calculations and its thermal stability up to 1000 K has been confirmed with ab initio molecular-dynamics (AIMD) simulations. It is shown that BC64 is a superhard carbon allotrope with a large Vickers hardness of about 84.5 GPa. The electronic band structures calculations show that BC64 carbon is an insulator with an indirect band gap of about 4.52 eV. Remarkably, the simulated x-ray diffraction pattern of BC64 carbon matches well the experimental data derived from the chimney soot. Previously this experiment is mainly explained by a series of all-sp2 hybridized carbon allotropes such as bco-C16 and bct-C16, and only one all-sp3 hybridized sc-C46 is proposed to explain this experiment; however, BC64 shows a better match with this experiment comparing with sc-C46 carbon. Our work has provided systematical understanding of a superhard all-sp3 hybridized carbon allotrope, and also provided a reasonable explanation for previous experimental data, which will also supply guidance for future theoretical and experimental studies in related fields
Statistics of the projected angles between the black-hole spin and the host-galaxy rotation axes from NewHorizon
No full textUnderstanding the alignment between active galactic nucleus (AGN) jets and their host galaxies is crucial for interpreting AGN unification models, jet feedback processes, and the coevolution of galaxies and their central black holes (BHs). In this study, we use the high-resolution cosmological zoom-in simulation NE
Multi-wavelength emission in resistive pulsar magnetospheres
No full textContext. Neutron star magnetospheres are well described in the two extreme cases of a vacuum field and a plasma-filled force-free regime. However, neither of these descriptions allows for magnetic field dissipation into particle kinetic energy and thus high-energy radiation. Some physical processes must be invoked to produce observational signatures typical of pulsars.
Aims. In this paper, we compute a full set of neutron star magnetosphere structures from the basic vacuum regime to the dissipation-less force-free regime by implementing a resistive prescription for the plasma. A comparison to the radiation reaction limit is also discussed. We investigated the impact of these resistive magnetospheres on the multi-wavelength emission properties based on the polar cap model for radio wavelengths, the slot gap model for X-rays, and the striped wind model for γ-rays.
Methods. We performed time-dependent pseudo-spectral simulations of the full Maxwell equations including a resistive Ohm’s law. We deduced the polar cap shape and size, the Poynting flux, the magnetic field structure, and the current sheet surface, depending on magnetic obliquity χ and conductivity σ.
Results. We found that the geometry of the magnetosphere close to the stellar surface is not impacted by the amount of resistivity. Polar cap rims remain very similar in shape and size. However, the Poynting flux varies significantly, as well as the magnetic field sweep-back in the vicinity of the light cylinder. This bending of field lines reflects in the γ-ray pulse profiles, changing the γ-ray peak separation Δ as well as the time lag δ between the radio pulse and γ-ray peaks. X-ray pulse profiles are also drastically affected by resistivity.
Conclusions. A full set of multi-wavelength light curves can be compiled for future comparison with the third γ-ray pulsar catalogue. This systematic study will help constrain the amount of magnetic energy that flows into particle kinetic energy and is shared by radiation
How supermassive black holes shape central entropies in galaxy clusters
No full textA significant fraction of galaxy clusters show central cooling times of less than 1 Gyr and associated central cluster entropies below 30 keV cm2. We provide a straightforward explanation for these low central entropies in cool core systems and how this is related to accretion onto supermassive black holes (SMBHs). Assuming a time-averaged equilibrium between active galactic nucleus (AGN) jet heating of the radiatively cooling intracluster medium and Bondi accretion, we derived an equilibrium entropy that scales with the SMBH and cluster mass as . At fixed cluster mass, overly massive SMBHs would raise the central entropy above the cool core threshold, thus implying a novel way of limiting SMBH masses in cool-core clusters. We find a limiting mass of 1.4 × 1010 M⊙ in a cool-core cluster of mass 1015 M⊙. We carried out three-dimensional hydrodynamical simulations of an idealised Perseus-like cluster with AGN jets and find that they reproduce the predictions of our analytic model, once corrections for elevated jet entropies are applied when calculating X-ray emissivity-weighted cluster entropies. Our findings have significant implications for modelling galaxy clusters in cosmological simulations: a combination of overmassive SMBHs and high heating efficiencies precludes the formation of cool-core clusters