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Data-driven identification of macroscopic dynamics with implicit equation-free sampling and Gaussian process regression: for the example of an integrate-and-fire neural network
No full textWe investigate a data-driven approach to derive low-dimensional macroscopic models of complex systems with only high-dimensional microscopic descriptions available. This is achieved by sampling of the macroscopic behaviour at selected points using an implicit equation-free approach with appropriate initialisation of the microscopic system. This enables subsequent data-driven identification of the macroscopic dynamics with Gaussian process regression. We demonstrate the technique on a high-dimensional neural network of integrate-and-fire neurons. A numerical bifurcation analysis of the obtained macroscopic model is performed, showing both stable and unstable branches. The appropriate sampling using the implicit equation-free approach avoids grid distortion and prevents spurious states as well as other artefacts
Optimization of dehumidified cold air drying process on antioxidant activity and physicochemical properties of marungga leaf powder (
No full textMoringa leaves contain valuable antioxidant-rich bioactive compounds, yet these compounds are easily degraded by heat during drying. This study aimed to optimize a low-temperature drying method using dehumidified cold air to better preserve antioxidant stability while improving the physicochemical quality of moringa leaf powder. Optimization was performed using Response Surface Methodology with a Central Composite Design, involving two variables—drying temperature (35–45 °C) and time (4–6 hours). The responses evaluated included moisture content, yield, antioxidant activity, total flavonoids, protein content, solubility, and color. The model predicted optimal conditions at 37.75 °C for 4 hours, yielding moisture content of 10.418%, yield of 31.192%, antioxidant activity of 88.321%, total flavonoids of 44.281 mg GAE/g extract, protein content of 25.44%, solubility of 14.7%, and color value (a*) of 52.00 with SMER value of 0.73 kg/kWh. Both temperature and duration significantly affected most parameters (p < 0.05). The findings indicate that dehumidified cold air drying effectively maintains phytochemical stability and enhances the functional quality of moringa leaf powder, offering a promising approach for processing heat-sensitive plant materials
Cropping pattern as the key for sustainable agriculture in the dry land of the Gunungsewu Gunungkidul karst area
No full textDry land of karst area depends on rainfall for water supply, so cropping pattern as an important factor in agricultural sustainability. This research aimed to formulate cropping pattern as the key to sustainable agriculture in the dry land of karst area. Research was conducted in dry land of karst area, Gunungsewu, D.I. Yogyakarta, Indonesia, from January to July 2024. Observation, interview and literature study were conducted to formulate sustainable cropping pattern. Results showed that crop water requirement and rainfall determine cropping pattern. Effective rainfall in first growing season allows for cultivation of rice, corn, groundnut, soybean, and cassava. In second growing season, effective rainfall supports cultivation of corn, groundnut, soybean, and cassava. Without irrigation, third growing season is fallow. Resources in the form of water, sunlight, plant commodities, manure, chemical fertilizers, pesticides, litter, household waste, fuel and electricity are managed to support the success of cropping pattern. Successful cropping pattern are characterized by resource optimization, increased crop diversity and yield, improved soil fertility and nutrient, reduced soil degradation and crop failure, and greenhouse gas mitigation. As key to sustainable agriculture, cropping pattern are built on the basis of resource optimization, taking into account physical, economical, social and environmental aspects
Euclid: Quick Data Release (Q1) -- A photometric search for ultracool dwarfs in the Euclid Deep Fields
No full textWe present a catalogue of 5306 new ultracool dwarf (UCD) candidates in the three Euclid Deep Fields in the Q1 data release. They range from late M to late T dwarfs, and include 1200 L and T dwarfs. A total of 546 objects have been spectroscopically confirmed, including 329 L dwarfs and 26 T dwarfs. We also provide empirical Euclid colours as a function of spectral type. Our UCD selection criteria are based only on colour (IE- ^2, including 20 L and T dwarfs per mathrm The combined requirement for optical detection and a stringent signal-to-noise ratio threshold ensure a high purity of the sample, but at the expense of completeness, especially for T dwarfs. The detections range from magnitudes 19 and 24 in the near-infrared bands, and extend down to 26 in the optical band. We discuss Euclid's capability to identify UCD candidates based on its photometric passbands. The average surface density of detected UCDs on the sky is approximately 100 objects per mathrm deg deg ^2. This leads to an expectation of at least 1.4,million UCDs in the final data release of the Euclid Wide Survey, including at least 300,000 L dwarfs, and more than 2600 T dwarfs, using the strict selection criteria from this work
Fine-tuning nutrient electrical conductivity in substrate hydroponics to boost growth and early fruit set of melon in a smart greenhouse
No full textHydroponic melon (Cucumis melo L.) production is constrained by the high cost of standard standard AB Mix nutrients. This study evaluated an economical alternative (½ AB Mix + ½ Gandasil) at varied Electrical Conductivity (EC) levels (3, 4, 5 mS/cm) against a standard control (100% AB Mix, EC 3) within a Smart Green House (SGH). The experiment revealed a significant paradox while high-concentration treatments (C1EC5 and C0EC3) acted as potent stimulants, significantly accelerating early vegetative growth and initial fruit set, this advantage was completely nullified by the final harvest. Analysis of variance (ANOVA) confirmed no significant difference (ns) across any critical yield parameters, including fruit weight, diameter, and sweetness (°Brix). The data demonstrates that a non-nutritional, overriding limiting factor suppressed the crop's potential. Supra-optimal thermal stress, with ambient SGH temperatures averaging 32°C, impaired photosynthetic efficiency and assimilate translocation. We conclude that in this system, meticulous environmental temperature control is an indispensable prerequisite that must take precedence over optimizing nutrient concentration to achieve viable yields
Improvement of yolk coloration and egg quality in Japanese quail eggs through dietary phyto-carotenoid supplementation
No full textPhyto-Carotenoids act as natural colour pigments in a wide variety of plants which are responsible for the yellow, orange, and red hues found in fruits, vegetables, and flowers. This study aimed to evaluate the effect of carotenoids as natural yolk colorants, such as paprika raw meal and marigold flower raw meal on performance, the quail egg quality, and carotenoid content in the yolk. A total of 180 quails were divided into 3 treatment groups with different levels of carotenoid supplementation, as follows: control group, 2% paprika and 2 % marigold flower. Parameters observed included egg production performance, yolk colour intensity, yolk carotenoid concentration, and overall egg quality traits such as shell thickness, albumen height, and Haugh unit. The results demonstrated that carotenoid supplementation significantly improved yolk pigmentation and carotenoid deposition without adverse effects on production performance. Moreover, egg quality indicators such as yolk colour score and antioxidant capacity were enhanced in the supplemented groups compared to the control. These results suggest that paprika and marigold extracts are effective in improving yolk colour and maintaining egg quality without compromising performance
The role of green technology systems on environmental monitoring and eco-tourism sustainability: Insight for eco-certifications and ESG marketing
No full textThis research aims to examine stakeholders’ use of green technologies in ecological monitoring, how it can be strengthened, and how it contributes to sustainable practices in the tourism ecosystem. The empirical investigation was conducted in an exploratory design across four waves of the regional stakeholder network, including standardised assessments of their engagement, certification history, and behavioural indicators. The methodology is based on a combination of SEM to identify the pathways of the green system in eco-tourism and regression analyses to compare their interactions and outcomes, supplemented by the Analytical Hierarchy Process (priority weights) and clustering. The results demonstrate that a relatively small segment of the operators in the three stakeholder clusters is strongly influenced by ESG marketing intensity and sustainable spending in certified networks. It is concluded that, as platform participation increases to build resilience against fragmented practices, stakeholders report a relatively stable improvement in trust and awareness of the impact of digital certification, leading to coherent engagement. The proposed research framework for measuring green technology performance can be applied both to comparative analyses of eco-tourism for operators from different regions and governance contexts and to improved sustainability evaluation
GreenCount: AI-Powered Tree Counting and Vegetation Monitoring from UAV and Satellite Imagery
No full textTraditional tree counting relied on field surveys or semi-automated methods, such as NDVI thresholding and clustering. These methods are slow, labor-intensive, and often inaccurate in cases of dense or overlapping canopies. Even recently, most of the deep learning-based solutions have focused on detecting trees only, without proactive monitoring, long-term vegetation analysis, or policy integrations.GreenCount overcomes these limitations through an AI-driven system combining computer vision, image analytics, and deep learning that count trees with high accuracy and scalability. It is built using TensorFlow, PyTorch, and OpenCV; it follows a structured pipeline of preprocessing, segmentation, and canopy detection; and it provides high accuracy across diverse environments. It then adds historical imagery analysis for monitoring long-term vegetation changes, and it translates technical outputs into actionable insights through dashboards for policymakers and conservation teams.Interoperable by design, GreenCount can be integrated with government environmental portals to enable transparent and evidence-based decision-making. It cuts manual effort by more than 70%, increases accuracy to 93–95% in dense canopies, and processes imagery at almost five times the speed. Integrating the detection of real-time alerts and change tracking into a unified system, GreenCount offers a holistic and policy-relevant solution to sustainable environmental management
Nutrient management to increase rice productivity in dry land
No full textNutrient application into soil with the right dose and time will support growth and increase rice yield. This study aimed to determine the nutrient management based on differences in the frequency and timing of application in supporting plant growth and increasing rice productivity in dry land. The study was conducted in dry land Gunungkidul, D.I. Yogyakarta, Indonesia, during dry season. NPK 15-15-15 fertilizer at the dose of 300 kg ha-1 and N 46% at the dose of 200 kg ha-1 were used in this research. Nutrient management with three fertilizer applications was compared with farmer practices with two fertilizer applications, repeated 11 times. The results showed that nutrient management increased grain productivity by 1.16 times compared to farmer practices, and straw productivity by 1.02 times. Nutrient management reduced the percentage of empty grain, by 33.63% compared to farmer practice. Nutrient management also increased the tiller number at harvest, and carbon absorption in grain and straw. Adoption of nutrient management at farmer level is user-friendly and gives beneficial impact on nutrient. Nutrient management application can be suitable strategy to support dry land agriculture
Mixture of multi-strain probiotic and ketapang leaf (
No full textThe aim of this study was to evaluate the effects of mixture multi-strain probiotics (MP) and katapang leaves extract (CE) on performance and digestive organ weight of broiler chickens during the finisher period. Two hundred 21- day old broiler chicken were randomly placed to the five treatments and four replicates, with ten 10 chicken each replicate. Experimental diets included a basal diet only (T1), a basal diet with 6 g/kg MP and 1 g/kg CE (T2), a basal diet with 6 g/kg MP and 1.5 g//kg CE (T3), a basal diet with 6 g/kg MP and 2 g/kg CE (T4), and a basal diet with 6 g/kg MP and 2.5 g/kg CE (T5). The variables were initial weight, live weight gain (LWG), feed intake, and feed conversion ratio (FCR) and digestive organ weight. The data were analysed using analysis of variance and the Duncan test. The results demonstrated that adding CE along with MP substantially increased LWG and improved FCR (p0.05). In conclusion, inclusion of 1.5 g/kg Terminalia catappa L. extract combined with 6 g/kg multi-strain probiotics significantly improved live weight gain and feed efficiency in finisher broilers, without affecting digestive organ weight. Therefore, the optimum dose rate is 1.5 g/kg Terminalia catappa L. extract with 6 g/kg multi-strain probiotics in the diet