The increasing prevalence of water scarcity has emphasized the urgent need for effective management of water distribution systems, particularly in urban areas. To achieve rational management of facilities and ensure long-term customer comfort, water utilities on the worldwide are seeking solutions to find a good compromise to avoid the major problem of leaks in distribution networks. Several techniques exist to address this problem, including pressure modeling of distribution networks, which has become a widely used technique for reducing leak rates and extending the lifespan of installations. This work consists of proposing a methodology for optimizing leaks in a drinking water supply network in Bologhine city using hydraulic models and stochastic methods. Stochastic model namely BAT algorithm was employed to simulate various scenarios of demand fluctuations and pressure changes, allowing us to assess the risk and occurrence of leaks under different operational conditions. The optimization of pressure control was achieved by implementing a strategic pressure management system that dynamically adjusts pressure settings based on real-time demand data and identified vulnerabilities within the network. By employing these methodologies, cities like Bologhine can enhance their infrastructure resilience, reduce water loss, and promote sustainability in urban water systems.

The current research examined the catalytic efficiency of ash derived from date palm fronds for the production of biodiesel by the ethyl transesterification of waste cooking oil. The optimal conditions for synthesizing the catalyst were determined by subjecting date palm fronds to various calcination temperatures (ranging from 300 to 700 ◦C). The catalyst produced was subjected to characterization using thermogravimetric analysis (TG-DTG), X-ray diffraction (XRD), BET, and scanning electron microscopy (SEM). The ideal parameters were as follows: a temperature of 85 ◦C, a molar ratio of alcohol to oil of 9:1, a catalyst concentration of 7% (w/w), and a reaction period of 1.5 hour. These conditions led to the formation of biodiesel containing 81% ester content. The reusability of the catalyst was evidenced by its sustained catalytic performance, achieving an ester content exceeding 78% during the initial two reaction cycles. A sustainable and effective catalyst for biodiesel manufacture, the synthesis of a catalyst from date palm fronds has numerous benefits: it is low cost, readily synthesizable, and derived from generally accessible biomass waste.

This research aimed to investigates the recycling of date seeds, which is a real practical example of the sustainable and integrated use of renewable material resources, providing innovative and sustainable solutions that can contribute to reducing environmental waste and maximizing the use of available natural resources. Highlighting the role of date seeds in supporting local industries as sustainable and safe alternative to cosmetics and pharmaceuticals. It illustrates the economical and medicinal value of date seeds waste as a natural source of active compounds. Date seeds oil was extracted, and it applications in cosmetics and nutrition were studied along with phytochemical screening tests, antioxidant and approximate analysis. Three types of extracts were prepared: methanol, aqueous, and oily. The aqueous extract was found to be rich in flavonoids (+4), tannins (+3), terpenoids (+3), saponins (+2) and absent of alkaloids (-). The approximate analysis showed moisture content (11.70%), ether extract (5.23%), fiber (75.3%), protein (8.7%), and ash (37.5%). The radical's percentage inhibition (PI) of DPPH was significantly obtained by dose IC50 = 1000 µl. Date seeds aqueous extract, with IC50 (80%) have values of 38.3, 78.9, 90.1, and 95.2 mg/mL, which contribute to its strong DPPH radical scavenging activity. Date seed oil was found to contain a high percentage of saturated and unsaturated fatty acids, phenolic compounds, and antioxidant properties, which are used in many industries, such as cosmetics (skin and hair cream, soap, eyeliner, glycerin, and coarse and smooth sandpaper), nutrition, date kernel molasses and raw material for animal feeds.

Background: The study analyzes the mechanisms for protecting public law interests in criminal cases involving the return of property assets, as a factor in ensuring the *accessibility and effectiveness of justice, through traditional methods and tactics of financial investigations, as well as using the capabilities of artificial intelligence technology. The authors rely on the provisions of the criminal procedure legislation of the Republic of Kazakhstan, which reflect the types and features of financial investigations, with an emphasis on the impact on the effectiveness and accessibility of justice. By identifying the mandatory features and elements of a financial investigation under the legislation of Kazakhstan, parallels are drawn with other types of financial investigations provided for in developed Western countries. The directions of using artificial intelligence tools in financial investigation are proposed. The works of scientists devoted to the analysis of the effectiveness of the institute of financial investigation in the return of illegally acquired assets are considered. The authors present in the article practical and empirical data available on the territory of the Republic of Kazakhstan in the context of the issue under consideration. Special attention is paid to international experience in implementing measures aimed at developing financial investigations, as well as criminal procedure standards and the experience of countries such as the Netherlands and Estonia. From all the works of scientists, a selection of those provisions has been made that, according to the authors, contribute to the formation and improvement of the Kazakh model of the institution of a full-fledged financial investigation, which allows protecting public interests in the context of ensuring the effectiveness and accessibility of justice. Metods: The authors used a number of methods of scientific knowledge to achieve their goals and solve research problems, in particular, such methods as legal analysis (descriptive), comparative legal analysis, the method of legal modeling, as well as the method of comparative research. The analysis of the criminal procedure legislation of the Republic of Kazakhstan and institutional mechanisms for asset recovery was used to identify the specifics of the financial investigation in the context of the Kazakh experience. This analysis allows us to identify the features of financial investigations in the Republic of Kazakhstan, compare them with best practices, predict and suggest ways to introduce artificial intelligence technologies into these processes. The comparative legal analysis made it possible to compare models and procedures for the use of financial investigations in Western countries and in Kazakhstan, to formulate proposals for possible extrapolation. Attention is drawn to the doctrinal analysis of the concept of financial investigation, the author's approach to its understanding is highlighted in accordance with the FATF recommendations, which is of particular value for Kazakhstan. The formulated author's position can be adapted to improve the legal system of Kazakhstan, including as one of the factors ensuring the effectiveness and accessibility of justice through the protection of public interests. Specific cases have been studied within the framework of the procedure for the return of illegally acquired property, considered by the authorized bodies of the Republic of Kazakhstan, an analysis of legislation has been carried out, which has revealed the main trends in law enforcement practice that affect the effectiveness and accessibility of justice through the prism of ensuring public interests. A comprehensive study of the problem at various levels revealed the imperfection of the current model of the Kazakh institute of financial investigation and legal protection of public interests in the framework of the return of illegally acquired assets through the prism of ensuring the effectiveness and accessibility of justice. Results and Conclusion: Creating conditions for a fair system for the return of illegally acquired assets (including using traditional investigative techniques and tactics, as well as using artificial intelligence technologies), ensuring effective and public financial investigations are among the factors ensuring the protection of public interests not only of the state, but also of society as a whole, and this Ultimately, it is one of the factors important in ensuring the effectiveness and accessibility of justice in cases of this category. The creation of an effective tool for the protection of public law interests makes it possible to provide a correct legal assessment of the activities of law enforcement agencies in returning illegally acquired assets to the country.

Intelligent fault detection in photovoltaic (PV) systems plays a critical role in ensuring sustainable energy production and system reliability. This can be done using infrared thermal imagery from the Infrared Solar Modules dataset. In realworld, imbalanced dataset of low-resolution images may exist. This work applies artificial intelligence and image processing techniques to classify anomalies in solar panels. To address the class imbalance challenge, a convolutional neural network (CNN)-based model was developed alongside a comprehensive preprocessing pipeline, including data augmentation, class weighting, and undersampling of dominant classes. Model performance was evaluated using loss, accuracy, AUC-PR, F1-score, and G-Mean to ensure a robust and fair assessment. The results demonstrate that targeted preprocessing significantly improved generalization and minority class recognition, reducing false positives and negatives and enabling more balanced predictions. Nonetheless, persistent misclassifications highlight the need for further dataset enrichment, advanced architectures, and real-time integration. The findings reinforce the value of AI-driven diagnostics for PV monitoring while underscoring the importance of data quality and tailored pre-processing strategies.

Learning Digital signal processing (DSP) is considered as difficult and tedious task among undergraduate students. Our primary objective of the article is to overcome the difficulties among the students by providing hands-on experience by using Scilab and to learn the basics behind DSP. The primary motive is to discuss the applications of DSP and to implement their understanding of Fourier Theory and discrete time systems. This article has three folds: (i) Interpretation of signals by sampling frequency (Fs); (ii) Understanding the discrete Fourier transform (DFT) response with the interpretation of signals by Fs; and (iii) Gaining practical knowledge by exemplifying filter design techniques with electrocardiogram (ECG) signal processing. Scilab tool is used here to simulate the DSP concepts.

The peculiar location of West Africa on the World map suggests that the region is prone to be under severe atmospheric influences from other regions. With a population of over 300 million people, the human activity and its corresponding impact on the climate system of the region is worth noting. The meteorological exploration of funded projects like AERONET, AMMA, DACCIWA e.t.c. in West Africa shows the peculiarity of the danger that life-forms in West Africa might be facing in the next two decades. The documentation of salient discoveries over the West Africa Monsoon and whose challenges may be the possible answers to questions on the West Africa climate system. A review on the satellite exploration within 2002-2006 shows the anomalies which require intense concern by all and sundry.

The occurrence of a morphologically altered individual identified as Portunus segnis is reported in this note. An adult male of this species with additional chela in the left cheliped, which could results in difficulties for reproduction and escape from predators. There are some hypotheses and the cause of the malformation remains unknown, but the results are indicative that is most likely due to errors in morphogenetic processes.

Soil samples collected from auto-mechanic workshops in Nnewi, Anambra state, Nigeria, were analysed using gas chromatography-flame ionization detector (GC-FID) after petroleum hydrocarbon extraction and clean up. GC-FID resolved aliphatic hydrocarbons (AHCs) present in the samples were composed of C8, C10 and C16 – C35 n-alkanes for sample-1, C16, C25, C28 and C30 – C36 n-alkanes for sample-2 and for sample-3, C16 - C18, C21 – C36 n-alkanes with observed unresolved complex mixture (UCM) of hydrocarbons from C22 – C36. These n-alkane carbon number ranges suggest gasoline, diesel, lube oil and grease sources for contamination of sample-1 soils, diesel and grease sources for sample-2 soils and diesel, lube oil and grease sources for sample-3 soils. In all the soil samples, the kerosene range n-alkanes from C10 – C15 were completely absent. Petroleum products contribution to the hydrocarbon mix in the soil samples were estimated from composition of n-alkanes. The chemical composition features suggest grease as the major source of hydrocarbon contamination in the soils with varying inputs from gasoline, diesel and lube oil. The presence of UCM of hydrocarbons in sample-3 indicated the aliphatic hydrocarbons in the soil had undergone degradation.

This paper is focused on horizontal, vertical, and temperature-dependent distributions, size composition of bottom and mid-water trawl catches, and biomass estimations of smooth lumpsucker Aptocyclus ventricosus (Cycl1opteridae) within the Russian Exclusive Economic Zone (EEZ) of the northwestern Sea of Japan. This species is distributed very widely throughout the study area inhabiting both near-bottom layers and water column. It is less abundant in small bays and in the northern Tatar Strait (north to 50°N). Despite wide bathymetric (0 to 940 m) and temperature (-1.1 to +12.2°С) ranges this species occurred mainly within the lower mesopelagic zone of 400-800 m depths and cold temperatures of -0.5 - 1°C. In the near-bottom layer catches of smooth lumpsucker were represented by fish with TL 5-45 cm (mean 28.1 cm, dominant lengths 29-37 cm) while in water column its TL varied 4 to 41 cm with mean 17.9 cm, most abundant were fish with TL 8-15 and 24-31 cm; the difference is associated with specific life history aspects of the species considered. Recent increase of smooth lumpsucker biomass in the study area was observed with estimated value of 3000 t in the northern Primorye.

This study aimed at determining the transpiration characters of Juniperus macrocarpa in a close to 40-year-old even-aged stand categorized into three classes based on canopy size, over a two-year period (2011-2012). The site is located in Palaiochora, 77 km south of Chania, on the southwest coast of Crete. Sap flow techniques (Granier-type) were used to determine water use. Annual trends in sap flow were generally bell-shaped, and varying significantly between seasons and canopy classes. Winter sap flow was minimal but trees were active when temperatures were above freezing point and trees depended on deep water (below 60 cm) for transpiration. Rates increased from 1.46Ld-1 in winter to 3.32 Ld-1 in the spring, irrespective of tree canopy class, because of improvement in weather conditions. Maximum transpiration rates were observed during the growing season with an average of 134.42 Ld-1 for dominant trees and 8.68Ld-1 for suppressed ones. The daily variations in photosynthetically active radiation, vapor pressure deficit, air temperature, and surface soil water were the principal drivers for transpiration during the growing season. The findings have shown that climate in Crete does not limit the expansion of J. macrocarpa and that this expansion will have potentially significant impacts on the ecohydrology of the system.

This paper explores the use of multi-criteria optimization to find better combination of parameters of friction welding process to provide better mechanical properties at the welded joints. This is achieved by developing a new hybrid methodology by integrating TOPSIS method and entropy measurement. TOPSIS method is used to find the order preference by similarity to ideal solution. Entropy method is used to find the weights of output responses. The mechanical strength of friction welded joints depends on several process parameters namely size of work piece, spindle speed, friction time, forging time, friction pressure, etc., Better combination of process parameters leads to quality joint, reduction of cost and wastages. Hybrid TOPSIS method was proposed to predict parameters that resulting superior mechanical properties. Specimen were produced with the predicted parameters and tested to confirm the superiority. Taguchi’s L9 orthogonal array is selected for conducting experiments. It is observed that friction time and spindle speed are the foremost factors but friction pressure influences less on mechanical strength.