This study presents the design, development, and evaluation of an intelligent fruit-picking robot that integrates convolutional vision, adaptive gripping mechanisms, and kinematic control to enable automated harvesting in diverse orchard environments. The proposed system combines a dualmanipulator platform with an extendable scissor-lift mechanism to achieve wide workspace coverage, allowing efficient access to fruits located at varying canopy heights. A deep learning-based recognition module, trained on a Mixed Fruit Dataset, is employed to detect and classify fruits under challenging conditions characterized by occlusions, variable illumination, and dense foliage. Visualization of feature activations confirms that the model effectively focuses on discriminative fruit regions, supporting precise alignment of the end-effector during grasping. The adaptive gripper, designed with compliant materials and multi-configuration geometry, ensures gentle handling across fruits of different shapes and sizes, minimizing mechanical damage. Experimental evaluations demonstrate that the system performs reliably across multiple fruit species, achieving accurate identification, robust segmentation, and stable manipulation in real-field scenarios. The integrated results highlight the robot’s potential to reduce labor dependency, improve harvesting efficiency, and support scalable automation in mixed-crop orchards. Future work will address enhancements in real-time processing, autonomous navigation, and cross-species generalization to advance fully autonomous orchard operations. © (2026), (Science and Information Organization). All right reserved.

This study explores the transformation of Akbakay gold ore waste into effective sorbents for heavy metal removal through phosphoric acid modification (20–35 wt.%) and thermal treatment at temperatures ranging from 400 to 800 °C. A range of characterization techniques—including XRD, EPMA, FTIR, SEM, BET surface area analysis, and zeta potential measurements— revealed notable structural changes. These included the formation of phosphate phases (such as lipscombite), increased porosity, surface fragmentation, and a more negative surface charge (up to −20.1 mV). Among the samples, the one treated at 600 °C with 20 wt.% acid (Sample 3) demonstrated outstanding Cu²⁺removal efficiency (>97 %) across initial concentrations of 1–40 mg/L, achieving a maximum adsorption capacity of 1.33 mg/g. The adsorption behavior followed the Langmuir isotherm model, indicating monolayer adsorption on a uniform surface. Kinetic analysis showed rapid metal uptake, with over 99 % removal within 120 minutes, best described by a mixed-order model that reflects both physical and chemical adsorption mechanisms. Fixed-bed column experiments further confirmed the material's performance, achieving a dynamic capacity of 0.847 mg/g and over 83 % Cu²⁺ removal. Breakthrough occurred at approximately 25 mL, with no 95 % breakthrough observed even at 300 mL. Overall, this work highlights a promising approach for converting mining waste into efficient, low-cost sorbents, contributing to sustainable heavy metal remediation and waste valorization efforts

The Karazhanbas oil field in the Mangystau region of Kazakhstan contains high-sulfur oil (1.6–2.2 %). It is known that sulfur negatively affects the operational properties of petroleum products, causes the corrosion of pipelines, and adversely affects the environment and the human body. Therefore, the development of biodesulfurization technology, taking into account local features, is relevant for this field. The purpose of the study is to develop biodesulfurization of high–sulfur oil from the Karazhanbas field in Kazakhstan using deep eutectic solvents. Research objectives: isolation of sulfate-oxidizing and sulfate-reducing bacteria from the studied oils; identification of isolated bacteria; study of the effect of heavy metal Cr(VI) and sulfur on microbial activity; testing of native strains for the potential for desulfurization of crude oil. The research methodology was based on the application of the Koch methods to determine the total number of microorganisms; light microscopy – for the study of microbiological preparations; genetic identification of bacteria based on the analysis of the nucleotide sequence of a fragment of the 16S rRNA gene; synthesis of deep eutectic solvents; testing of isolated bacteria – for sensitivity to Cr (VI), for the ability of microorganisms to use hydrocarbons of high-sulfur oil, for activity in sulfur-containing crude oil, for determination of the mass fraction of sulfur. From 12 aerobic bacterial cultures isolated from oil samples, 9 strains with active and moderate growth in a medium with high-sulfur oil were selected during testing, followed by two strains (Bacillus paramycoides SFN-1, Bacillus cereus SFN-2), which were the most resistant to Cr (VI) and two strains (Bacillus cereus SFN2, Bacillus thuringiensis SFN3), which have shown sulfur-oxidizing abilities. The native bacterial strains selected during the study showed high disulfurization activity without the addition of deep eutectic solvents (hereinafter referred to as DES) (Bacillus thuringiensis SFN3), with the addition of DES-1 (Bacillus cereus SFN2) and with the addition of DES-2 (Bacillus thuringiensis SFN3). As a result of a comparative analysis of microbial desulfurization processes, it was found that the highest biodesulfurization rate at the end of the experiment was recorded in cultures of Pseudomonas aeruginosa B-5807 (96.3 %), Bacillus thuringiensis SFN-3 (96.1 %), and Rhodococcus erythropolis AC 1039 (96 %).

This paper analyzes part of the reactor experiments on the study of tritium and helium release from promising two-phase lithium ceramic (Li2TiO3 and Li4SiO4) of natural lithium enrichment conducted by vacuum extraction. The basis for such an analysis was a more careful study of the time trend of pressure changes of gases in the chamber with the test samples. In a particular case, it was clearly shown that the pressure fluctuations observed during irradiation for gases with mass number M4 (to which both HT and He molecules correspond) are determined only by He, which leaves the intergranular regions of the ceramic through open channels or cracks. The kinetics of changes in the amount of helium that is released during irradiation was traced and both the rate of helium release and the frequency of emissions were determined. It was assumed that the observed emissions correspond to a certain “formation of free paths” from the internal cavities of the irradiated ceramics into the chamber of the facility. The data obtained for the helium emissions were compared with the release of tritium-containing molecules from the ceramics. The quasi-equilibrium levels of the release of tritium-containing molecules and their dependence on the reactor power were estimated. The release of helium and tritium was compared with the calculated values of the tritium generation rate in the test sample. © 2022 The Author(s)

The investigation of hydrogen storage properties of hydride perovskites have been emerged as great research domain in recent times. The current study focuses on the first principles exploration of lithium based hydrides, LiXH 3(X=Al, Ga, In), for hydrogen storage and other physical properties. The structural properties of these hydrides show that the lattice constants of LiAlH 3, LiGaH 3 and LiInH 3 are 3.68, 3.74, and 4.09 Å. respectively. The gravimetric hydrogen storage capacity (C wt%) of LiAlH 3, LiGaH 3 and LiInH 3 is 7.57, 3.66 and 2.37%, respectively. The negative formation energy for these compounds show the stability of these hydrides. The electronic band structures and density of states of under study hydride perovskites validate their metallic nature. The complex dielectric constant, reflectivity and absorption coefficient are investigated to reveal optical response of LiXH 3(X=Al, Ga, In). The significant thermodynamic parameters like Debye temperature, specific heat capacities, entropy and thermal expansion coefficient under the effect of temperature and pressure are elaborated to determine the thermodynamic stability. For better understanding of thermoelectric characteristics of these compounds, thermoelectric parameters under wide range of temperature are also studied. The excellent gravimetric hydrogen storage capacity and volumetric hydrogen storage density of these hydride perovskites make them promising materials for hydrogen storage applications. © 2024 Hydrogen Energy Publications LLC

The problem of optimizing oil production has always been one of the most pressing. The article is focused on the problem of improving the energy efficiency and optimizing the operating modes of this unit for oil production using rod pumping units (SHS). The article pays special attention to accounting for a decrease in the level of oil in the well, which affects the hydrostatic pressure and the load on the pump. The results of kinematic and kinetostatic analyzes of the transforming mechanism of the rod pump unit Drive are obtained. Based on the same results, the wattmetrogram was calculated. With its help, it allows not only to control energy consumption, but also to fine-tune the balance mechanisms and drive systems to increase the overall efficiency and identify its weaknesses. The decrease in the oil level reduces the overall load and, accordingly, we see that the amplitude of the wattmetrogram decreases. The oil dynamogram adds dynamic vibrations to the load, complicating the power profile. Together, the two factors make the reports more realistic, which is important for the correct selection and adjustment of counterweights, engine power, and optimization of the operation of the MSS. The results in the article are obtained taking into account the characteristics of the Electromotive and reducer used in the straight-line guide converter mechanism of a Class II quadruple drive of a specific SHS unbalanced drive. © 2025, Kazakh-British Technical University. All rights reserved.

MXene derivatives and composites are becoming fresh and promising two-dimensional (2D) materials because of their unique properties, performance, and multifunctionalities. This review covers the general aspects of MXenes (family of 2D transition metal carbides, nitrides, and carbonitrides), their MAX phase (a diverse class of nanolaminate materials with intriguing properties that have received incredible global research attention because they bridge the divide separating metals and ceramics.) precursors, dissimilarities and similarities between MAX phases and MXenes, and special properties of both materials. The important focuses are made on the methods of MXene synthesis and their stability and conductivity, as well as on synthesizing new MXene composites with desired characteristics. The impacts of MXenes in energy storage systems, especially supercapacitors, are discussed based on the high specific surface area, tunable porosity, and optimized inter-layer spacing. Here, various aspects of MXene materials, including properties, synthesis, and applications, have been discussed to highlight their importance for the development of energy storage systems and material science research.

One of the most critical problems faced by modern civilization is the depletion of freshwater resources due to their continuous consumption and contamination with different organic and inorganic pollutants. This paper considers the potential of already discovered MXenes in combination with carbon nanomaterials to address this problem. MXene appears to be a highly promising candidate for water purification due to its large surface area and electrochemical activity. However, the problems of swelling, stability, high cost, and scalability need to be overcome. The synthesis methods for MXene and its composites with graphene oxide, carbon nanotubes, carbon nanofibers, and cellulose nanofibers, along with their structure, properties, and mechanisms for removing various pollutants from water, are described. This review discusses the synthesis methods, properties, and mechanisms of water purification using MXene and its composites. It also explores the fundamental aspects of MXene/carbon nanocomposites in various forms, such as membranes, aerogels, and textiles. A comparative analysis of the latest research on this topic shows the progress in this field and the limitations for the practical application of MXene/carbon nanocomposites to solve the problem of drinking water scarcity. Consequently, this review demonstrates the relevance and promise of the material and underscores the importance of further research and development of MXene/carbon nanocomposites to provide effective water treatment solutions. © 2024 by the authors.

Organic additives with multiple functional groups have shown great promise in improving the performance and stability of perovskite solar cells. The functional groups can passivate undercoordinated ions to reduce nonradiative recombination losses. However, how these groups synergistically affect the enhancement beyond passivation is still unclear. Specifically, isomeric molecules with different substitution patterns or molecular shapes remain elusive in designing new organic additives. Here, we report two isomeric carbazolyl bisphosphonate additives, 2,7-CzBP and 3,6-CzBP. The isomerism effect on passivation and charge transport process was studied. The two molecules have similar passivation effects through multiple interactions, e.g., P = O···Pb, P = O···H–N and N–H···I. 2,7-CzBP can further bridge the perovskite crystallites to facilitates charge transport. Power conversion efficiencies (PCEs) of 25.88% and 21.04% were achieved for 0.09 cm2 devices and 14 cm2 modules after 2,7-CzBP treatment, respectively. The devices exhibited enhanced operational stability maintaining 95% of initial PCE after 1000 h of continuous maximum power point tracking. This study of isomerism effect hints at the importance of tuning substitution positions and molecular shapes for organic additives, which paves the way for innovation of next-generation multifunctional aromatic additives. (Figure presented.) © The Author(s) 2025.

This study introduces a novel YOLO-like multi-branch deep learning architecture designed for accurate apple detection and segmentation in orchard environments, addressing the persistent challenges of occlusion, illumination variability, and fruit clustering. The proposed model integrates an enhanced backbone with C2f modules and a Spatial Pyramid Pooling Fast (SPPF) block to capture multi-scale receptive fields, while a Feature Pyramid Network (FPN) combined with a Path Aggregation Network (PAN) ensures effective top-down and bottom-up feature fusion. To extend beyond bounding box localization, a prototype-based segmentation head is incorporated, enabling precise instance mask generation with reduced computational overhead. The model was comprehensively evaluated on the MinneApple dataset, consisting of high-resolution orchard images with polygonal annotations, and compared against state-of-the-art detection and segmentation frameworks, including Faster R-CNN, Mask R-CNN, SSD, YOLO variants, YOLACT, and SOLOv2. Quantitative results demonstrated that the proposed approach achieved superior mean Average Precision (mAP@0.5 = 0.76), precision (0.83), and F1-score (0.76), while maintaining a competitive inference speed of 40 FPS, confirming its suitability for real-time agricultural applications. Qualitative analysis further highlighted robustness in complex orchard conditions, reinforcing the model’s applicability for automated harvesting, yield estimation, and orchard monitoring. These findings advance the state of agricultural computer vision by unifying detection and segmentation in a lightweight, high-performance framework. © (2025), (Science and Information Organization). All rights reserved.