Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive and behavioral impairments caused by the dysfunction or death of nerve cells, severely affecting daily life activities. Current approaches for early detection rely on biomarkers and neuroimaging techniques. Among these, MRI is widely used for the early diagnosis of AD stages; however, the growing volume of data and aging population is making manual processing and analysis increasingly challenging. Recently, quantum artificial intelligence-based methods have emerged as promising tools for overcoming the limitations of classical approaches and achieving more efficient results, particularly in the early diagnosis and stage classification of AD using MRI data. In this study, we propose a quantum-based parallel model, inspired by classical model parallelism, to classify AD stages with high accuracy. The model was evaluated on two widely used datasets in the literature, OASIS-1 and ADNI. It incorporates two distinct quantum circuits with rotational (U3, RX, RY) and entanglement blocks (CNOT, CY, CCNOT) to exploit quantum advantages. The implementation was carried out on the state-vector simulator default.qubit provided by PennyLane 0.35.1, using 15 epochs and a batch size of eight. The experimental results demonstrate that, for the OASIS-1 dataset, the average training and validation accuracies reached 0.90 and 0.93, with training and validation losses of 1.65 and 1.85, respectively. For the ADNI dataset, the average training/validation accuracies were 0.85/0.81, and the corresponding losses were 1.66/1.86. These findings indicate that the proposed model offers a novel, generalizable, and robust approach for classifying stages of complex diseases such as Alzheimer’s disease.

Multicomponent substitutional solid solutions with several ions with similar crystal-chemical properties in one site exhibit property characteristics significantly exceeding those of single-component compounds. Interest is currently focused on metal–organic frameworks (MOFs), which consist of cations connected by an organic linker. The aim is to synthesize and characterize new multicomponent MOFs, obtained using a hydrothermal method by mixing RE³⁺(NO₃)₃·xH₂O (RE=La-Lu), H₃BTC (benzene-1,3,5-tricarboxylic acid), and NaOH in distilled water.

XRPD showed that single-phase (Eu,Tb,Dy,Er)BTC, (Sm,Eu,Tb,Dy)BTC, and (Sm,Eu,Tb,Er)ВТС crystallize in MIL-78-type (sp.gr. C2/m, Z=4; [(4RE)BTC]) and two-phase samples (usually with adding RE=La-Pr) and have REBTC(Сс) (sp.gr. Сс, Z=4; [(4RE)BTC(H₂O)₆]) and MIL-78 structures. In diffraction patterns of (4RE)BTC, redistribution of the intensities of main peaks is observed, which is caused by the type and content of RE in (4RE)BTC.

IR spectra of [(4RE)BTC] and [(4RE)BTC(H₂O)₆] confirm their compositions: the weak band at ~3070 cm^-1 and weak bands ~3480-~3230 cm^-1 correspond to adsorbed water and water in the framework, respectively.

According to DSC, (Sm,Eu,Tb,Er)ВТС has the highest chemical stability (DН=8057.0 J/g), which is greater than the other components. However, the highest thermal stability (560.72°C) is observed in the SmBTC component of (Sm,Eu,Tb,Dy)BTC and (Sm,Eu,Tb,Er)ВТС, which may be due to a higher degree of amorphism in multicomponent phases compared to single-component ones.

Funding: This study was funded by the Ministry of Science and Higher Education of the Russian Federation, grant № FSFZ-2024-0003.

Swarm is a three-satellite mission operated by the European Space Agency to monitor the Earth's magnetic field. The China Seismo Electromagnetic Satellite (CSES) is a satellite dedicated to studying the possible seismo-induced effects of seismic activity on the ionosphere, operated by the China National Space Administration in cooperation with the Italian Space Agency. Such satellites are placed in Low Earth Orbit at an altitude ranging from 460 km to 510 km.

We selected orbital combinations with the Swarm satellite in one hemisphere and CSES-01 in the opposite one to study the impact of magnetic pulsations on the ionospheric environment. We identified three orbital combinations: two of them closer to the equator and another one at higher latitudes. The data have been filtered in the frequency range of Pi2 pulsations (period between 40 s and 150 s). We inspected the filtered data in time and frequency domains, as time series and scalograms, respectively. Similar oscillations of a few nanoteslas of the magnetic field intensity were detected by both satellites, sometimes in phase and at other times in counterphase. Detected oscillations could be explained by interactions between the Sun's and Earth's magnetic fields or the effect of a satellite crossing the auroral ring currents at the Northern and Southern poles.

This work supports the cross-validation of magnetic data from multiple satellite missions in Low Earth Orbit, such as Swarm and CSES. Our results confirm the scientific reliability of magnetic data acquired from the above-cited satellite missions.

The Philippines was placed under several lockdowns to limit movements and prevent the spread of the virus during the COVID-19 pandemic. The imposed restrictions reduced the transport and industrial operations, which are primary contributors of air pollution, mainly in the cities of Metro Manila. Satellite measurements of aerosol optical depth (AOD) and greenhouse gases (GHG) such as carbon dioxide (CO₂) and tropospheric ozone (O₃) can improve surface monitoring of particulate matter (PM_1,2.5,10) and GHG but this requires a better understanding of the relationship between satellite and ground monitoring data. In this study, we used the MODIS MAIAC land AOD data at 550 nm, Sentinel-5P TROPOMI O₃ data, and OCO2 X_CO2 for the satellite data over Manila, Philippines with a concurring 5-year continuous measurement of PM_1.0,2.5,10, O₃, and CO₂ from a ground monitoring station near a busy highway. This measurement coincides with the lockdown from the COVID-19 pandemic and shows how human activities can greatly affect air quality. The results show that PM values before the lockdown period have the highest values and exceed WHO limits, while the lowest values were measured after lockdown period for the whole study period. On the other hand, CO₂ and O₃ values increased. This study also shows the correlation between satellite and ground monitoring data and shows the possibility of using remote satellite data as alternative for ground air quality measurement in Manila. Overall, these findings provide supplemental information for operative policymaking to mitigate air pollution and improve air quality in highly urbanized areas.

This research addresses microplastic contamination in water systems, where particles <5 mm are detected in 80% of global drinking water samples. We aim to develop a cost-effective, high-efficiency filtration system for scalable water treatment applications. This work introduces the first integrated system combining Surface Acoustic Wave (SAW) technology with machine learning algorithms (YOLOv8 and DeepSORT) for microplastic detection and filtration. The novel architecture features graphene-fabricated Interdigital Transducer (IDT) electrodes and replaces conventional lithium niobate with zinc oxide–glass lite substrate integrated with cellulose acetate butyrate, achieving 95% cost reduction while preserving performance. Current filtration technologies struggle to balance high removal efficiency with cost-effectiveness for large-scale deployment. Integrating acoustic manipulation with intelligent detection systems offers targeted, energy-efficient processing solutions. The SAW system uses 9 MHz signals transmitted to graphene-enhanced IDT electrodes, generating Rayleigh waves via the piezoelectric substrate. These waves concentrate microplastics at pressure antinodes, directing particles to a dedicated outlet while purified water exits independently. YOLOv8 and DeepSORT algorithms activate the signal generator only upon microplastic identification, optimizing energy consumption. The system achieves 93% removal efficiency, processing one liter every ten minutes. Machine learning detection shows 10–15% enhancement over baseline methods, identifying particles as small as 0.16 mm. Applications include residential filtration, aquaculture, and industrial processes. This integrated SAW-ML system provides scalable microplastic removal with substantial cost reduction, enabling widespread implementation. Future work includes ML hardware upgrades and real-time monitoring systems.

Electrospun nanocomposite fibers have emerged as promising scaffold materials in tissue engineering due to their high surface area, tunable porosity, and structural resemblance to the native extracellular matrix. However, their limited surface functionality and poor bioactivity often restrict effective cell–material interactions, posing challenges for successful tissue integration and regeneration. In this study, cerium oxide (CeO₂) nanoparticles were incorporated into polyvinylidene fluoride (PVDF) nanocomposite fibers to enhance their mechanical and interfacial properties for scaffold-based biomedical applications. CeO₂, known for its antioxidant, anti-inflammatory, and regenerative characteristics, was embedded into the PVDF matrix via electrospinning. The inclusion of CeO₂ led to a significant increase in surface roughness, Young’s modulus, and surface energy key features that positively influence cell adhesion, spreading, and proliferation. Additionally, uniform nanoparticle dispersion within the PVDF matrix ensured consistent fiber morphology and improved mechanical stability. The engineered nanofibers demonstrate a synergistic combination of enhanced mechanical integrity and surface bioactivity, directly addressing limitations associated with conventional polymer scaffolds. These improvements suggest that CeO₂-functionalized PVDF nanocomposite fibers represent a viable approach for developing advanced tissue engineering scaffolds. This work contributes to the advancement of functional biomaterials designed to support favorable cellular responses and improve therapeutic outcomes in regenerative medicine and tissue repair.

Egypt has a hot and dry climate, making it a hyper-arid country, receiving only scant rainfall annually. Most rainfall falls along the northern coast during the winter months (December to February), with the heaviest rainfall recorded in the Mediterranean city of Alexandria. With extreme weather events increasing worldwide due to global warming, Alexandria experienced unusual weather conditions in the early hours of May 31, 2025. Unusually heavy precipitation fell for this time of year, accompanied by strong winds, lightning, and thunder. The storm caused the collapse of some building balconies, damaged numerous buildings and restaurant facades, and brought traffic to a complete standstill. This sudden storm caused widespread panic among the population. This research aims to investigate the causes of this unusual weather event and the factors that contributed to the rapid development of clouds over Alexandria, resulting in rain and hail within a short period of time, through a synoptic study of the atmospheric pressure systems, wind speeds, and directions at various pressure levels up to 200 millibars. We also evaluate the influence of the sea surface temperature on the formation of these Cb clouds over the city. Since this extreme weather event lasted less than an hour and was limited to Alexandria, we compared different types of reanalysis data for rainfall to gain further insights.

Mechanical subsoiling serves as a highly effective practice for eliminating soil compaction caused by years of consecutive mechanical operations. It also significantly enhances water infiltration and promotes the robust development of crop roots. The bending subsoiling tool (BST), a fundamental implement in subsoiling activities, is employed to optimize soil structure and boost the ability of crops to absorb nutrients and water from the soil. In this study, the discrete element method was utilized to investigate the impacts of the BST's working speed, ranging from 1.5 to 9.5 km/h, on soil disturbance behaviors and tillage forces. The findings revealed that a proper increment in the BST's working speed could elevate a greater amount of moist soils from the deep seed and middle layers into the shallow seed zone, without severely affecting the mixing between the deep layer and other layers. The working speed of the BST had a restricted influence on the lateral soil disturbance range. As the BST's working speed increased from 1.5 to 9.5 km/h, it led to a larger draught force, greater soil surface flatness, a higher soil rupture distance ratio, and a lower soil loosening efficiency. Notably, when the BST's working speed increased from 7.5 to 9.5 km/h, the soil surface flatness increased rapidly. Taking soil layer mixing, soil loosening efficiency, and soil surface flatness into consideration, it is advisable that the BST operate at working speeds lower than 9.5 km/h.

Energy plays a crucial role in supporting human existence today. Renewable energy and sustainable energy sources that are attracting significant interest include solar power, wind power, and hydropower. Nevertheless, given that these energies are not consistently accessible, this study focuses on enhancing and developing the properties of materials utilized as supercapacitors. The synthesis of graphene oxide (GO) was accomplished through a modified Hummer's method, while the preparation of polyaniline (PANI)/GO nanocomposites was carried out using an in situ chemical polymerization method. The influence of reaction times and GO content on the characteristics of synthesized nanocomposites was investigated. Subsequently, the layer films of PANI/GO were coated on fluorine-doped tin oxide (FTO) glass for use in supercapacitor application. The morphology, composition, and electrochemical properties of the produced samples were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), Raman spectroscopy, and cyclic voltammetry (CV). The experimental findings indicated that a reaction duration of 30 minutes, combined with a weight ratio of aniline (ANI) monomer to GO at 1:1.5, provided a perfect specific capacitance value of 13.30 F/g. The powerful electrochemical performance of the PANI/GO electrode might result from the enhanced active sites for PANI deposition, related to the large surface areas of GO. The outcomes highlighted the significance and remarkable potential of GO in advancing high-performance supercapacitors using PANI.

This study explores in detail how the surface characteristics of soccer balls—specifically the geometric structure of dimples and seams—influence their aerodynamic behavior and overall flight trajectory. Utilizing advanced 3D printing techniques, researchers fabricated eight distinct soccer ball prototypes, each featuring different dimple shapes, including conical, hemispherical, and cylindrical forms, as well as varying seam structures with differences in depth and width. These balls were then subjected to controlled wind tunnel experiments designed to measure critical aerodynamic forces such as drag, lift, and lateral deviation.

The experimental data revealed that both the quantity and shape of dimples had a profound impact on the critical Reynolds number (Re_crit), which is the threshold at which airflow transitions from laminar to turbulent. Soccer balls equipped with conical dimples and deeper seams demonstrated higher drag coefficients but reached supercritical airflow conditions at lower speeds, indicating an earlier transition. This suggests that such features enhance aerodynamic stability under specific conditions. A particularly strong linear correlation (R² = 0.98) was identified between the ratio of surface area occupied by dimples and seams and the corresponding Re_crit value. This finding highlights the importance of surface texture in regulating aerodynamic flow.

Additionally, balls with a reduced number of dimples—ranging from 25% to 50% of the typical count—exhibited lower overall drag and delayed airflow transitions. The study concludes that surface roughness plays a more critical role in ball aerodynamics than previously assumed, surpassing even panel count and basic ball shape.