This study presents a deterministic multi-objective framework for the energy-efficient design of a diaphragm spring for automotive clutch applications. The proposed methodology is based on the direct feasible-set approach and similarity theory, enabling synthesis-level optimal-rational design within a closed dimensionless parameter space. Unlike stochastic search-based optimization methods, the developed framework constructs a complete information set of admissible design solutions and identifies rational configurations through adaptive constraint management. The multi-objective analysis demonstrates the absence of a globally optimal solution and justifies the concept of optimal-rational design. The synthesized configurations achieve up to + 22% increase in compressive force, − 12% reduction in material volume, and improved stiffness characteristics compared to the reference configuration. To ensure mechanical admissibility, the analytical synthesis model is validated through nonlinear finite element analysis incorporating geometric nonlinearity and localized elastoplastic behavior. The peak equivalent stress reaches 2244 MPa but remains confined to highly localized regions with equivalent plastic strain below 0.004. Experimental validation under full actuator displacement (17 mm) confirms stable nonlinear behavior, ± 2% force variation over 5000 cycles, and moderate thermal rise (10–12 °C). Energy efficiency is quantitatively assessed through hysteresis analysis, revealing a 25% reduction in mechanical energy dissipation per cycle and improved mechanical efficiency. The strong agreement between analytical predictions, FEM simulations, and experimental measurements confirms the predictive reliability of the proposed deterministic optimization framework. The developed approach provides a transparent and computationally efficient methodology for energy-efficient diaphragm spring synthesis and can be extended to other nonlinear elastic components in transmission systems.

Cite this article
Baranovskyi, D., Sergienko, A., Kalinin, P. et al. Multi-objective optimization of an energy-efficient diaphragm spring for clutch applications. Sci Rep (2026). https://doi.org/10.1038/s41598-026-56129-w

This review analyses and logically structures modern intelligent sensor technologies in the context of animal husbandry, feed production, and veterinary medicine. The main research discussed in the article focuses on machine learning based on modern neural network models, computer vision, and sensor systems that are transforming the methods for assessing the health, behavior, and nutrition of farm animals. The first part examines modern approaches to quality control and optimization of mineral and vitamin premixes, including visual inspection using visual sensors and neural networks. Key roles are played by precise dosing, component stability (minerals, vitamins), and the transition to more bioefficient organic forms of micronutrients to reduce environmental impact. Improvements in feed and premix production are analyzed, including automation, energy management, and the use of machine learning for non-destructive quality control, defect detection, mixing homogeneity assessment, and vitamin stability prediction. The second part analyzes methods for animal location and behavior detection. This article presents computer vision-based systems, including modifications of YOLO, for automatically tracking and classifying key behavioral patterns (lying down, standing, feeding, and aggression) in cattle and pigs, even in crowded conditions. It also discusses the use of ultra-wideband (UWB) systems and accelerometers combined with machine learning for high-precision positioning and detection of specific behavioral anomalies, such as lameness and playfulness. The third section focuses on the application of machine learning in veterinary diagnostics, including the automated interpretation of medical images (X-ray, ultrasound, and MRI) as sensor data streams for the diagnosis of cardiovascular, oncological, and orthopedic diseases in farm and small animals. Furthermore, the article examines the use of machine learning models for proactive disease diagnosis in farm animals and poultry based on multimodal data and image analysis. Considerable attention is given to methods and tools for radiometric diagnosis of animal diseases at an early stage using microwave sensors, as well as laser therapy and surgery in veterinary medicine. The review concludes that the integration of intelligent systems enables a transition to data-driven livestock management, significantly improving animal welfare and, consequently, the efficiency and sustainability of agricultural production.

Keywords
accelerometry; spectrometry; tensometry; biosensorics; videomonitoring; telemetry; datastream; CNN; ML; DL; animals; diagnostics; premix

Kiktev, N.; Hradoboiev, D.; Pravilov, M.; Antypov, I.; Meish, Y.; Stroianovska, L.; Kielbasa, P.; Hutsol, T. Precision Livestock Farming and Biomedical Engineering: Assessing Feed Quality, Animal Health, and Behavior Using Machine Learning for Sensor Data. Sensors 2026, 26, 4015. https://doi.org/10.3390/s26134015

Ukrainian University in Europe – Foundation (UUE-F) acted as a co-organizer of the 11th International Scientific and Business Conference “Renewable Energy Sources”, which brought together representatives of academia, business, local governments, and the energy sector to discuss current challenges and future perspectives in renewable energy development.

The conference participants included representatives of municipalities, businesses, and scientific institutions from Poland, Ukraine, Slovakia, Germany, France, Lithuania, and Turkey. The event served as an international platform for knowledge exchange, the presentation of innovative solutions, and the development of partnerships in the fields of sustainable development and renewable energy sources.

The conference program included online and onsite presentations, official welcome addresses, scientific and business discussions, poster presentations, cultural activities, and study visits. During the event, participants presented contemporary scientific research, innovative technologies, and practical solutions related to energy efficiency, decarbonization, and sustainable development.

As part of the conference program, the Foundation delivered several thematic presentations. The principal topic focused on “International Cooperation of Public and Private Institutions in Sustainable Development Projects”. Participants discussed prospects for international cooperation among universities, local communities, scientific institutions, and businesses in the implementation of joint innovative projects.

UUE-F’s participation as a co-organizer confirms the organization’s active role in supporting international scientific initiatives, promoting innovation, and contributing to the development of a modern educational and research environment within the renewable energy sector.

We sincerely thank our partners, participants, and organizers for their cooperation, trust, and joint efforts in making this international event successful. We highly value the partnerships established during the conference and look forward to further collaborative initiatives in the fields of sustainable development and renewable energy.

Abstract

Przedmiotem zgłoszenia jest urządzenie do automatycznego sadzenia sztobr, zwłaszcza zdrewiałych sadzonek wierzby energetycznej i topoli, wyposażone w ramę (1) podpartą kołem napędowo-podporowym (6) charakteryzujące się tym, że koło napędowo-podporowe (6) połączone jest przekładnią cięgnową (8) z bębnem (9) będącym elementem mechanizmu selekcji (3) i mającym równomiernie rozmieszczone na obwodzie wzdłużne wybrania równoległe do osi wzdłużnej bębna (9) o długości równej jego wysokości i szerokości większej niż średnica sztobr, a rama (1) jest na przeciwległym końcu wyposażona w rolki dociskowe (7), przy czym pomiędzy kołem napędowo-podporowym (6), a rolkami dociskowymi (7) znajduje się redlica (5), nad którą zawieszony jest lej (4) prowadzący sztobry, nad którym z kolei znajduje się podpora (10) do siłowej zmiany pozycji poziomej sztobr wypadających z bębna (9) mechanizmu selekcyjnego (3), ponadto urządzenie wyposażone jest w otwarty od góry kontener (2) załadowczy o jednej parze ścian równoległych, przy czym odległość ścian równoległych od siebie jest większa od długości sztobr oraz o wzdłużnej szczelinie w dnie, równoległej do osi wzdłużnej bębna (9), której szerokość jest większa od średnicy sztobr.

Kowalchyk Z., Kubon, M., Kwasniewski, D., Mudryk, K., Glowacki, S., Hutsol T., Yermakov S., Kukharets S.: Urządzenie do automatycznego sadzenia sztobr, zwłaszcza zdrewiałych sadzonek wierzby energetycznej i topoli: Patent 248384 (2025).

This paper presents a methodological framework for integrating UAV-based photogrammetry and GIS technologies to generate a high-accuracy digital elevation model (DEM) for urban land-use planning. The study was conducted in an urbanized area characterized by heterogeneous topography, mixed vegetation cover, and fragmented land use, which complicate high-resolution terrain modeling. UAV surveys were performed using multiple photogrammetric blocks with centimeter-level ground sample distance and a dense ground control network supported by geoid-based height corrections. The resulting DEM was independently validated using control points derived from large-scale topographic data. The achieved vertical accuracy (RMSE ≈ 0.25 m) confirms the applicability of UAV-derived DEMs for large-scale mapping (1:1000–1:2000) and urban spatial analysis. Unlike studies focused on runoff simulation, this work emphasizes the accuracy-controlled generation and validation of DEMs as a primary spatial dataset for urban planning applications. The results demonstrate that DEM accuracy depends strongly on flight planning, ground control distribution, and hybrid automatic–manual point cloud refinement.

Keywords
unmanned aerial vehicles; unmanned aerial vehicle; digital elevation model; DEM; photogrammetry; GIS; urban terrain modeling; ground control points; elevation accuracy

Kulikovska, O.; Kolb, I.; Kovalyshyn, O.; Kolodiy, P.; Stupen, R.; Trzyniec, K.; Vasyuk, V.; Hutsol, T. Integration of UAV Photogrammetry and GIS for Digital Elevation Modeling in Urban Land Use Planning. Sustainability 2026, 18, 3047. https://doi.org/10.3390/su18063047

Open article

Abstract
Soil fertility is determined mainly by its level of compaction. For a single wheel, this level depends on the pressure, which is calculated by dividing the wheel’s vertical load by its contact patch area. The latter is directly related to the length of the tire’s contact patch with the soil (). In this regard, this article aims to develop a strategy for selecting the parameters of a tractor chassis system based on the analysis of such an analytical dependence for determining the length of the wheel-soil contact line, which would contain the radius () and the tire width (); the vertical load on the tire () and the air pressure in it (); the soil characteristic in the form of the coefficient of volumetric compression (). The results of theoretical and experimental studies of such a dependence have established that an increase in the contact line length of the wheel with the soil causes an increase in the values ​​of the parameters and on the one hand, and a decrease in the values ​​of , and parameters on the other. However, to practically implement the functional link of increasing the parameter and subsequently reduce the compaction effect of the wheel on the soil, it is necessary to increase the wheel radius and tire width, while reducing the tire air pressure and the vertical load on the wheel. From an agronomic perspective, it is necessary to create a soil structure with a lower coefficient of volumetric compression.

Keywords:
Vertical load, Wheel radius; Tire air pressure; Tire width; Soil volumetric; Compression

Nadykto, V., Horetska, I., Glowacki, S. et al. Determination of the contact patch length in tractor tire–soil interaction. Sci Rep (2026). https://doi.org/10.1038/s41598-026-37868-2