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Identification of molecular line emission using convolutional neural networks
No full textContext. Complex organic molecules (COMs) are found to be abundant in various astrophysical environments, particularly toward star-forming regions, where they are observed both toward protostellar envelopes as well as shocked regions. The emission spectrum, especially that of heavier COMs, might consist of up to hundreds of lines, where line blending hinders the analysis. However, identifying the molecular composition of the gas that leads to the observed millimeter spectra is the first step toward a quantitative analysis.
Aims. We have developed a new method based on supervised machine learning to recognize spectroscopic features of the rotational spectrum of molecules in the 3 mm atmospheric transmission band for a list of species including COMs, with the aim of obtaining a detection probability.
Methods. We used local thermodynamic equilibrium (LTE) modeling to build a large set of synthetic spectra of 20 molecular species, including COMs with a range of physical conditions typical for star-forming regions. We successfully designed and trained a convolutional neural network (CNN) that provides detection probabilities of individual species in the spectra.
Results. We demonstrate that the CNN model we developed has a robust performance to detect spectroscopic signatures from these species in synthetic spectra. We evaluated its ability to detect molecules according to the noise level, frequency coverage, and line-richness, as well as to test its performance for an incomplete frequency coverage with high detection probabilities for the tested parameter space, with no false predictions. Finally, we applied the CNN model to obtain predictions on observational data from the literature toward line-rich hot core-like sources, where the detection probabilities remain reasonable, with no false detections.
Conclusions. We demonstrate the use of CNNs in facilitating the analysis of complex millimeter spectra both on synthetic spectra, along with the first tests performed on observational data. Further analyses on its explainability, as well as calibration using a larger observational dataset, will help improve the performance of our method for future applications
Apprentissage vocal et cognition chez les oscines (oiseaux chanteurs) : une fenêtre sur les bases biologiques du langage
No full textLe chant des passériformes oscines constitue un modèle clé pour l’étude de l’apprentissage vocal, une capacité rare partagée avec les humains. Les jeunes oscines acquièrent leur chant par imitation au cours d’une période sensible, un processus analogue à l’acquisition du langage chez l’enfant. Leur cerveau comporte des circuits spécialisés dédiés à la production et à l’apprentissage du chant. De plus, ces oiseaux montrent des capacités cognitives telles que la mémoire, l’attention et la flexibilité comportementale, qui soutiennent cet apprentissage. Alors que l’intelligence générale correspond à une capacité globale de résolution de problèmes, l’hypothèse de modularité postule que la cognition est composée de modules spécialisés. Chez les oiseaux, l’apprentissage vocal pourrait ainsi refléter les capacités cognitives individuelles. Une étude récente a montré un lien entre la taille du répertoire vocal, l’imitation de sons variés et les performances en résolution de problèmes. Ces travaux confirment que le chant des oscines est un modèle pertinent pour comprendre les bases neurobiologiques et cognitives de l’apprentissage vocal, et soulignent l’intérêt des modèles animaux pour étudier les aspects évolutionnistes de la communication vocale
Investigation of raw timber elements for the design of a hunting stand structure
No full textThere is an increasing need for less resource-intensive and waste-reducing measures in the design and production of timber structures. Traditionally, irregular branches from tree crowns are often left unused, despite making up nearly 50% of a tree's volume in broadleaf trees. In a research seminar conducted at the RWTH Aachen University, students explored design and analysis concepts of using these unprocessed irregular timber elements for architectural and structural applications, drawing inspiration from early human shelters. Our interdisciplinary team, consisting of two civil engineering students and two architecture students, utilized 3D models of tree branch geometry generated from point cloud scans to design a hunting stand structure. A complete 3D model of the hunting stand was created and was structurally analyzed using finite element simulations of both the global system and selected critical joints, taking into account the anisotropic behavior of timber. This project showcases the potential of combining digital tools with minimally processed timber for resource-efficient and innovative designs
Architect's self-readiness for strengthening creative rationality and its implementation in design learning for architecture as livable space
No full textThis research departs from the desire to gain learning from the rationality in designing of architects who have produced extraordinary creative works. Through a qualitative study of the designing practice by research-participant architects, the researcher describes the architect's mental readiness to strengthen his rationality in designing. This research uses multiple case studies with case units of mental processes of designing architects at the conceptual design stage, involving 16 research-participant architects. The main data were explored through in-depth retrospective interviews, analyzed using qualitative content analysis techniques. Research reveals that to strengthen their rationality in designing, architects build cognitive and psychological readiness. Cognitive readiness contributed dominantly, including readiness for complex thinking, alternative thinking and utilizing knowledge in memory. This readiness is built utilizing internal conditions formed from experience, education, and learning from the environment. The implementation of these findings in architectural design learning leads to start learning by conditioning students to be ready to use ratio in designing. Readiness is built by taking advantage of personal internal conditions so that the results are very diverse. Learning to design architecture must be designed inclusively to reach this diversity. Design assignments are required to be very open, which allows each student to develop the most suitable project to develop and express his potential to the fullest. This kind of task model has not been applied to every level of learning in our architectural education system
Impact of the Ain Taoujdate Flexure on the Morphology of the Mikkes River Valley in the Saïs Basin (Sebou Basin, Morocco)
No full textThe Oued Mikkès is a left-bank tributary of the Oued Sebou, located in the Prerif region. Its watershed extends across three distinct morpho-structural units, from south to north: the western edge of the Middle Atlas plateau in the upstream section, the Saïs basin in the central part, and the Pre-Rif ridges and the Prerif in the downstream section. The central part of the basin, corresponding to the Saïs plain, is significantly influenced by active tectonics, mainly related to the Ain Taoujdate flexure. This major geological structure, with a general WNW-ESE orientation, crosses the basin and plays a key role in shaping both the hydrographic network and sedimentary deposits. The middle reach of the Oued Mikkès valley exhibits a complex morphology, directly linked to ongoing tectonic movements. These tectonic disturbances affect the riverbed slope, channel alignment, and the processes of erosion and sedimentation. Moreover, the interaction between active tectonics and regional climatic conditions contributes to shaping the current fluvial landscape. This study aims to examine the impact of the Ain Taoujdate flexure on the morphology of the middle reach of the Oued Mikkès valley, by highlighting the geomorphological and hydrological dynamics at work
Effect of washing duration using ozone and ultraviolet light treatments on the quality of
No full textThe washing horticultural commodity with ozone (O₃) and ultraviolet (UV) light presents an innovative technology to extend postharvest shelf life. This study aimed to analyze the effect of washing duration with ozone and UV light on the quality of
Capsicum frutescens L. during storage. A randomized complete block design (RCBD) with two factors was employed. The first factor was the washing treatment (ozone, UV light, and plain water) and the second factor was the washing duration (5, 10, and 15 minutes). The experiment was set up as a 3x3 factorial with three replications. The observed parameters included weight loss, color, texture, moisture content, and total microbial test, measured at 28 days of storage. The results indicated that the washing treatment had a significant effect (p<0.05) in weight loss and color in almost all day storage (exclude day 0), texture (day 14), moisture content in all days storage, and total microbial count (days 0, 14 and 21). Furthermore, washing duration and interaction of both factors had a significant effect only on moisture content (days 28). Among all treatments, ozone application for 15 minutes was identified as the most effective method in maintaining the physicochemical and microbiological quality of
Capsicum frutescens L
Complementary feeding innovation from soybean flour and dragon fruit peel powder: An agricultural adaptation strategy to enhance hemoglobin and iron outcomes
No full textMalnutrition in early childhood is a contributor to stunting in Indonesia, with prevalence still above the WHO target. One key cause is the inadequacy of complementary feeding in providing sufficient micronutrients, especially iron, which is essential for hemoglobin synthesis. Local food innovations such as soybean flour and dragon fruit peel powder offer potential as nutrient-dense and antioxidant-rich complementary foods. This study evaluated the effectiveness of complementary feeding made from soybean flour and dragon fruit peel powder in improving hemoglobin (Hb) and iron (Fe) levels. A true experimental pre-test and post-test control group design was conducted with three groups: negative control (K–, standard diet), positive control (K+, protein diet), and treatment (P, supplemented diet). The intervention lasted 28 days. Hemoglobin and serum iron levels were measured using spectrophotometry and analyzed t-tests and ANOVA (p<0.05). Results showed significant Hb improvement in all groups (K– p=0.006; K+ p=0.003; P p=0.000), with the highest increase in the treatment group. Between-group analysis confirmed significant differences in Hb and Fe between treatment and controls (p=0.000). In conclusion, complementary feeding innovation using soybean flour and dragon peel powder effectively improved Hb and Fe, supporting its role as an agricultural adaptation strategy to combat malnutrition and stunting
Bacteriological analysis of Oued Oum Er-Rbia water: Evolution and impact on quality and osmosis membrane
No full textThe Oued Oum Er-Rbia is an essential resource for Morocco's water supply, but is subject to increasing pollution from domestic and agricultural discharges. This study assesses microbiological contamination and its impact on reverse osmosis membranes in the Khénifra (2023-2024) and Tadla (2021-2023) treatment plants, using quarterly bacteriological analyses.Water samples were analyzed according to ISO 9308-1 [1] standards, including tests for total coliforms, E. coli and fecal streptococci. Polynomial regression modeling and 3D visualization were carried out using Python (Pandas, Scikit-learn, Matplotlib) to study the interactions between conductivity, residual chlorine and microbial proliferation (CFU/ml at 22°C).The results show that high conductivities (>3000 us/cm) favor membrane clogging, while stable residual chlorine (0.1-0.15 mg/l) limits bacterial proliferation. However, levels of revivable bacteria (>50 CFU/ml) indicate significant biofouling.The study recommends pre-treatment in Khénifra to reduce conductivity, and stabilization of residual chlorine in Tadla. Continuous monitoring and treatment optimization are essential to guarantee water that meets international standards and prolong the life of membranes
SORAME (sorghum and edamame) noodles: An innovative sorghum-based noodle enriched with edamame to enhance the nutritional value of noodles
No full textNoodles are a widely favored staple food. In 2023, Indonesia ranked second in global instant noodle consumption with 14.54 billion servings. This high demand highlights the potential of instant noodles but also reflects a heavy reliance on wheat. To reduce this dependency, sorghum could be cultivated as a local alternative, while edamame can enhance protein content. This study investigates the impact of adding sorghum and edamame on the physical and chemical properties of sorghum noodles. This research was conducted using a Completely Randomized Design (CRD) with one factor, namely the ratio of sorghum addition at 6 levels (100% wheat flour without edamame, 100% wheat flour with edamame (4% of total wheat/sorghum flour), and wheat flour:sorghum ratios of 80:20, 60:40, 40:60, & 20:80 with the addition of edamame 4%) with four replications. The parameters tested included physical properties (lightness, redness, yellowness, elongation, and cooking loss) and chemical properties (carbohydrates and protein). The results showed that the addition of sorghum and edamame increased the noodle’s carbohydrate and protein content, though they resulted in a darker color. Sorame noodles had lightness 26.90 – 77.36, redness –1.87 – 11.49, yellowness 12.15 – 32.85, elongation 26.67% – 176.17%, cooking loss 1.17% – 1.95%, carbohydrate content 48.81% – 77.81%, and protein content 3.33% – 5.58%
Sustainable aquaculture advancement via WISANGGENI: IoT-centered water quality and energy-efficient monitoring system
No full textAquaculture is one of the fastest-growing food production sectors; however, it faces persistent challenges related to limited water availability, environmental degradation, and production instability caused by inadequate water quality management. To address these issues, the Water Integrated System and Analysis for Sustainable Aquaculture Generation Initiative (WISANGGENI) is proposed as an integrated framework designed to optimize water use, maintain ecological balance, and enhance the long-term sustainability of aquaculture systems. WISANGGENI integrates real-time water quality monitoring, intelligent water treatment, and data-driven decision support into a unified adaptive platform. The system employs Internet of Things (IoT) sensors to continuously monitor key parameters such as temperature, pH, and turbidity, combined with recirculating water and biofiltration technologies to reduce waste and recycle resources. In addition, computational intelligence techniques, including machine learning, fuzzy logic, and predictive modeling, are applied to analyze sensor data and support operational decisions. Fuzzy logic is specifically utilized to manage uncertainty in water quality assessment by converting imprecise sensor inputs into actionable responses, such as aeration control, feeding regulation, and early warning alerts. Through this integrated approach, WISANGGENI improves feeding efficiency, optimizes aeration, reduces disease risk, and lowers freshwater consumption, thereby supporting more resilient, efficient, and environmentally sustainable aquaculture practices