Search Results (3,742)

In the development of artificial intelligence (AI) technology, utilizing datasets for model instruction to achieve higher predictive and reasoning efficacy has become a common technical approach. However, primordial datasets often contain a significant number of redundant features (RF), which can compromise the prediction accuracy and generalization ability of models. To effectively reduce RF in datasets, this work advances a new version of the Pufferfish Optimization Algorithm (POA), termed AMFPOA. Firstly, by considering the knowledge disparities among different groups of members and incorporating the concept of adaptive learning, an adaptive exploration strategy is introduced to enhance the algorithm’s Global Exploration (GE) capability. Secondly, by dividing the entire swarm into multiple subswarms, a three-swarm search strategy is advanced. This allows for targeted optimization schemes for different subswarms, effectively achieving a good balance across various metrics for the algorithm. Lastly, leveraging the historical memory property of Fractional-Order theory and the member weighting of Bernstein polynomials, a Fractional-Order Bernstein exploitation strategy is advanced, which significantly augments the algorithm’s local exploitation (LE) capability. Subsequent experimental results on 23 real-world Feature Selection (FS) problems demonstrate that AMFPOA achieves an average success rate exceeding 87.5% in fitness function value (FFV), along with ideal efficacy rates of 86.5% in Classification Accuracy (CA) and 60.1% in feature subset size reduction. These results highlight its strong capability for RF elimination, establishing AMFPOA as a promising FS method. Full article

Background/Objectives: Prostate artery embolization (PAE) has emerged as a relatively new, minimally invasive alternative for the treatment of benign prostatic hyperplasia. We aimed to compare the perioperative outcomes and trends of PAE versus transurethral resection of the prostate (TURP) and laser enucleation. Materials and Methods: We used the GeRmAn Nationwide inpatient Data (GRAND), provided by the Research Data Center of the Federal Bureau of Statistics, and performed multiple patient-level analyses. Patients with prostate cancer, acute hematuria, and emergent referral to the hospital were excluded. Results: Between 2017 and 2022, a total of 3665 PAEs were performed in Germany compared to 218,388 TURPs and 50,863 laser enucleations. Patients selected for PAE were slightly younger and presented with fewer comorbidities at baseline. The number of laser enucleations increased exponentially in these years, PAEs remained stable, whereas TURPs slightly decreased. Compared to PAE, laser enucleation was associated with higher odds of in-hospital incontinence (4.2% versus 2.7%, OR: 1.6, 95%CI: 1.3–1.9, p < 0.001). On the contrary, PAE was associated with lower odds of in-hospital urinary retention and shorter length of hospital stay compared to TURP (3.2% versus 7.1%, OR: 2.2, 95%CI: 1.8–2.6, p < 0.001, and a 2.6-day difference, 95%CI: 2.5–2.7, p < 0.001, respectively) and laser enucleation (3.2% versus 5%, OR: 1.5, 95%CI: 1.3–1.8, p < 0.001, and a 1.5-day difference, 95%CI: 1.4–1.6, p < 0.001, respectively). Conclusions: PAE offers more favorable perioperative outcomes compared to TURP and laser enucleation, but the use of this relatively new procedure has remained nearly stable in recent years. Full article

In this paper, we introduce the notion of intuitionistic fuzzy GE-algebra by combining the concepts of GE-algebras and intuitionistic fuzzy sets. We provide a necessary and sufficient condition for an intuitionistic fuzzy set to form an intuitionistic fuzzy GE-algebra. This study examines various properties and characterizations of intuitionistic fuzzy GE-algebra. In particular, we explore the roles of ${({\gimel }_A,t)}_{\in },{({ð}_A,s)}^{\in },{({\gimel }_A,t)}_q,{({ð}_A,s)}^q,{({\gimel }_A,t)}_{\in \vee q}$, and ${({ð}_A,s)}^{\in \vee q}$ sets in determining the subalgebra structures within GE-algebras. Examples illustrate the results, and counterexamples clarify the necessity of the conditions. These results not only enhance the theory of GE-algebras, but also contribute to the algebraic treatment of uncertainty using intuitionistic fuzzy logic. Full article

Ru₃Sn₇ crystallizes in the cubic Ir₃Ge₇-type structure (space group Im3m), a class of intermetallic compounds. Previous studies focused primarily on its crystal structure, band calculations, and basic transport properties. Here, we report a systematic investigation of high-quality single crystals via electrical resistivity, Hall effect, specific heat, and thermal transport measurements. The T₃X₇ intermetallic family—with its diverse electronic ground states—provides an ideal platform for exploring such topology–property relationships. Ru₃Sn₇ exhibits metallic behavior, with consistent Hall effect and Seebeck coefficient data indicating a compensated electron-hole two-band system. Temperature-dependent modulation of electronic states near the Fermi surface alters charge carrier transport, which may imply the presence of a Lifshitz transition in Ru₃Sn₇. More importantly, magnetic quantum oscillations are observed for the first time, confirming the presence of two Dirac points in its band structure. Full article

The development of hydrogen energy can significantly reduce the negative impact on the environment. For the successful implementation of hydrogen technologies, it is necessary to transform existing models of production, distribution, and consumption of both thermal and electrical energy. The processes of fuel conversion and combustion are complex and, in some cases, insufficiently studied. A complete replacement of natural gas with hydrogen requires an assessment of energy and environmental characteristics. This study aims to evaluate the operation of a gas turbine unit when transitioning to hydrogen fuel. The GE 6FA engine was chosen as the object of study. Mathematical modeling of this engine was conducted using the software complex “AS GRET” (Automated System for Gas Dynamic Calculations of Power Turbomachinery). Full article

Background/Objective: Plant-based diets are gaining global attention for their positive impact on health and sustainability; however, the nutritional value and health effects differ across plant food categories. We investigated the association of three plant-based diet indices and incident cardiovascular disease (CVD) and its subtypes. Methods: This study consisted of 10,030 Korean adults aged 40–69 years from the Korean Genome and Epidemiology Study (KoGES) in Ansan and Ansung. Using a validated food frequency questionnaire from the community-based cohorts of the KoGES, we derived three dietary indices based on food intake: (1) Overall Plant-Based Diet Index (PDI), (2) Healthful Plant-Based Diet Index (hPDI), and (3) Unhealthful Plant-Based Diet Index (uPDI). We analyzed the association between three plant-based diet indices and the incidence of CVD using a multivariate Cox proportional hazards regression model, adjusted for demographic and other CVD risk factors. Results: During 99,751 person-years, 597 CVD cases occurred. None of the three plant-based diet indices (PDI, hPDI, uPDI) were significantly associated with overall risk of CVD. When stratifying results by types of CVD, individuals with the highest adherence to uPDI had a higher risk of coronary heart disease (CHD), compared to the lowest group [HR (95% CI) = 1.62 (1.12–2.33), p-trend = 0.008], but not stroke [HR (95% CI) = 0.97 (0.66–1.42), p-trend = 0.964]. There were no associations between adherence to PDI and hPDI and the incidence of CHD and stroke. Conclusions: In this prospective cohort of Korean adults, none of the three plant-based diet indices were associated with CVD risk, whereas higher adherence to an unhealthful plant-based diet was associated with increased risk of CHD, but not stroke. These findings highlight the importance of plant food quality in CHD prevention and warrant confirmation in other populations. Full article

The precise identification, classification, sorting, and rapid and accurate quality assessment of soybean seeds are extremely important in terms of the continuity of agricultural production, varietal purity, seed processing, protein extraction, and food safety. Currently, commonly used methods for the identification and quality assessment of soybean seeds include morphological analysis, chemical analysis, protein electrophoresis, liquid chromatography, spectral analysis, and image analysis. The use of image analysis and artificial intelligence is the aim of the presented research, in which a method for the automatic classification of soybean varieties, the assessment of the degree of damage, and the identification of geometric features of soybean seeds based on numerical models obtained using a 3D scanner has been proposed. Unlike traditional two-dimensional images, which only represent height and width, 3D imaging adds a third dimension, allowing for a more realistic representation of the shape of the seeds. The research was conducted on soybean seeds with a moisture content of 13%, and the seeds were stored in a room with a temperature of 20–23 °C and air humidity of 60%. Individual soybean seeds were scanned to create 3D models, allowing for the measurement of their geometric parameters, assessment of texture, evaluation of damage, and identification of characteristic varietal features. The developed 3D-CNN network model comprised an architecture consisting of an input layer, three hidden layers, and one output layer with a single neuron. The aim of the conducted research is to design a new, three-dimensional 3D-CNN architecture, the main task of which is the classification of soybean seeds. For the purposes of network analysis and testing, 22 input criteria were defined, with a hierarchy of their importance. The training, testing, and validation database of the SB3D-NET network consisted of 3D models obtained as a result of scanning individual soybean seeds, 100 for each variety. The accuracy of the training process of the proposed SB3D-NET model for the qualitative classification of 3D models of soybean seeds, based on the adopted criteria, was 95.54%, and the accuracy of its validation was 90.74%. The relative loss value during the training process of the SB3D-NET model was 18.53%, and during its validation process, it was 37.76%. The proposed SB3D-NET neural network model for all twenty-two criteria achieves values of global error (GE) of prediction and classification of seeds at the level of 0.0992. Full article

The Dulong Sn-polymetallic deposit in Yunnan Province of southwestern China serves as a unique case study for unraveling the evolution of skarn systems and tin mineralization. Four distinct garnet types (Grt I to Grt IV) were classified based on petrographic observations. Compositional analysis reveals a progression from Grt I to Grt III, marked by increasing andradite components, and elevated tin concentrations, peaking at 5039 ppm. These trends suggest crystallization from Sn-enriched magmatic-hydrothermal fluids. In contrast, Grt IV garnet exhibits dominant almandine components and minimal tin content (<2 ppm). Its association with surrounding rocks (schist) further implies its metamorphic origin, distinct from the magmatic origin of the other garnet types. Combined with previously published sulfur and lead isotopic data, as well as trace element compositions of garnet, our study suggests that Laojunshan granites supply substantial ore-forming elements such as S, Pb, W, Sn, In, and Ga. In contrast, elements such as Sc, Y, and Ge are inferred to be predominantly derived from, or buffered by, the surrounding rocks. The geochemical evolution of the garnets highlights the critical role of redox fluctuations and fluid chemistry in controlling tin mineralization. Under neutral-pH fluid conditions, early-stage garnets incorporated significant tin. As the oxygen fugacity of the ore-forming fluid declined, cassiterite precipitation was triggered, leading to tin mineralization. This study reveals the interplay between fluid redox dynamics, garnet compositional changes, and mineral paragenesis in skarn-type tin deposits. Full article

Uncooled microbolometers play a pivotal role in infrared detection owing to their compactness, low power consumption, and cost-effectiveness. This review comprehensively summarizes recent progress in thermistor materials and focal plane arrays (FPAs), highlighting improvements in sensitivity and integration. Vanadium oxide (VO_x) remains predominant, with Al-doped films via atomic layer deposition (ALD) achieving a temperature coefficient of resistance (TCR) of −4.2%/K and significant 1/f noise reduction when combined with single-walled carbon nanotubes (SWCNTs). Silicon-based materials, such as phosphorus-doped hydrogenated amorphous silicon (α-Si:H), exhibit a TCR exceeding −5%/K, while titanium oxide (TiO_x) attains TCR values up to −7.2%/K through ALD and annealing. Emerging materials including GeSn alloys and semiconducting SWCNT networks show promise, with SWCNTs achieving a TCR of −6.5%/K and noise equivalent power (NEP) as low as 1.2 mW/√Hz. Advances in FPA technology feature pixel pitches reduced to 6 μm enabled by vertical nanotube thermal isolation, alongside the 3D heterogeneous integration of single-crystalline Si-based materials with readout circuits, yielding improved fill factors and responsivity. State-of-the-art VO_x-based FPAs demonstrate noise equivalent temperature differences (NETD) below 30 mK and specific detectivity (D*) near 2 × 10¹⁰ cm⋅Hz ^1/2/W. Future advancements will leverage materials-driven innovation (e.g., GeSn/SWCNT composites) and process optimization (e.g., plasma-enhanced ALD) to enable ultra-high-resolution imaging in both civil and military applications. This review underscores the central role of material innovation and system optimization in propelling microbolometer technology toward ultra-high resolution, high sensitivity, high reliability, and broad applicability. Full article

Accurate normalization is crucial for reliable gene expression quantification and depends on stably expressed housekeeping genes (HKGs) as internal controls. However, HKGs expression varies with developmental stage, tissue type, and treatments, potentially introducing bias and compromising data accuracy. Thus, validating candidate reference genes under defined conditions is essential. Reynoutria, also known as giant Asian knotweeds, is a Polygonaceae family genus of several medicinal plants producing a diverse array of specialized metabolites of pharmacological interest. Outside their native range, these plants are also noxious invasive weeds, causing significant environmental and economic threats. Research on stable reference genes in these species is limited, with a primary focus on R. japonica. To enable accurate gene expression analysis related to specialized metabolism and natural product biosynthesis, we aimed to identify the most stable reference genes across the most common species: R. japonica Houtt., R. sachalinensis (F. Schmidt) Nakai, and their hybrid—R. × bohemica Chrtek & Chrtková. In this study, we evaluated twelve candidate HKGs (ACT, TUA, TUB, GAPDH, EF-1γ, UBQ, UBC, 60SrRNA, eIF6A, SKD1, YLS8, and NDUFA13) across three tissue types (rhizomes, leaves, and flowers) from three Reynoutria species sampled at peak flowering. Primer specificity and amplification efficiency were confirmed through standard-curve analysis. We assessed expression stability using ΔCt, geNorm, NormFinder, and BestKeeper, and generated comprehensive rankings with RefFinder. Our integrated analysis revealed organ- and species-dependent stability differences, yet identified up to three reference genes suitable for interspecific normalization in Reynoutria. This represents the first systematic, comparative validation of HKGs across closely related knotweed species, providing a robust foundation for future transcriptomic and functional studies of their specialized metabolism and other biological processes. Full article

We propose a novel telescope concept based on Earth’s gravitational lensing effect, optimized for the detection of distant dark matter sources, particularly axion-like particles (ALPs). When a unidirectional flux of dark matter passes through Earth at sufficiently high velocity, gravitational lensing can concentrate the flux at a distant focal region in space. Our method combines this lensing effect with stimulated backward reflection (SBR), arising from ALP decays that are induced by directing a coherent electromagnetic beam toward the focal point. The aim of this work is to numerically analyze the structure of the focal region and to develop a framework for estimating the sensitivity to ALP–photon coupling via this mechanism. Numerical calculations show that, assuming an average ALP velocity of 520 km/s—as suggested by the observed stellar stream S1—the focal region extends from $9\times {10}^9$ m to $1.4\times {10}^{10}$ m, with peak density near $9.6\times {10}^9$ m. For a conservative point-like ALP source located approximately 8 kpc from the solar system, based on the S1 stream, the estimated sensitivity in the eV mass range reaches $g/M=\mathcal{O}\left({10}^{-22}\right){\mathrm{GeV}}^{-1}$. This concept thus opens a path toward a general-purpose, space-based ALP observatory that could, in principle, detect more distant sources—well beyond $\mathcal{O}\left(10\right)\mathrm{kpc}$—provided that ALP–photon coupling is sufficiently strong, that is, $M\ll M_{\mathrm{Planck}}$. Full article

This study employed the solid-state method to prepare perovskite-type high-entropy oxide materials La(Co_0.2Cr_0.2Fe_0.2Mn_0.2Ni_0.2)O₃ and La(Co_0.2Cr_0.2Ni_0.2Ga_0.2Ge_0.2)O₃ with equimolar ratios at the B-site and explored the effects of sintering temperature on the phase structure and electrochemical properties of high-entropy oxide ceramics. The results show that after sintering at 1300$°\mathrm{C}$, both samples exhibit orthorhombic perovskite structures. Both have a relative density of >97%, while La(Co_0.2Cr_0.2Ni_0.2Ga_0.2Ge_0.2)O₃ has a significantly larger grain size. Using these materials as electrodes, the cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD) results indicate that the working electrode made of La(Co_0.2Cr_0.2Ni_0.2Ga_0.2Ge_0.2)O₃ shows higher oxidation reaction activity in CV measurements and achieved a specific capacitance of 74.3 F/g at a current density of 1 A/g in GCD measurements, which still maintained 73% of its initial specific capacitance (54.3 F/g) when the current density was increased to 10 A/g. Its capacitance retention rate is 10 percentage points higher than that of La(Co_0.2Cr_0.2Fe_0.2Mn_0.2Ni_0.2)O₃ at high current densities, demonstrating superior rate performance. Full article

In this paper, efficient pecG-n (n = 1, 2) basis sets for the 4th period p-elements, Ga, Ge, As, Se, and Br, specified for the optimization of molecular structures, are proposed. These basis sets were optimized via the property-energy consistent (PEC) algorithm directed to the minimization of molecular energy gradient relative to the bond lengths. The performance of the presented basis sets was tested against both theoretical and gas phase electron diffraction experimental reference data relative to the other popular basis sets that are usually employed for the geometry optimization of molecular structures. It was shown that the pecG-n (n = 1, 2) basis sets give equilibrium molecular structures of the quality that considerably surpasses the quality provided by the other commensurate basis sets. Full article

Osteoporosis is a common disease characterized by a reduction in bone mineral density (BMD), leading to an increased risk of pathological fractures and even mortality. Although menopause is a major risk factor, osteoporosis can also occur in premenopausal women. The aim of this study was to identify genetic variants associated with the development of osteoporosis in Korean premenopausal women. Subjects were recruited from the Anseong and Ansan cohorts of the Korean Genome and Epidemiology Study (KoGES). Clinical and epidemiological characteristics were assessed, and participants were classified based on BMD values measured at the distal radius and mid-shaft tibia. Individuals with confounding risk factors such as low body weight, smoking, high alcohol consumption, steroid/hormone therapy, or relevant medical history were excluded. A total of 247 healthy controls and 57 osteoporosis patients were included. Genotyping was performed using the Illumina Infinium HumanExome BeadChip and the Affymetrix Axiom Exome Array. Data were analyzed using the SNP and Variation Suite and PLINK, with quality control thresholds set at MAF ≥ 0.05 and HWE p ≥ 0.01. Functional annotation and protein structure predictions were performed using PolyPhen-2, SIFT, and PROVEAN. Genome-wide association analyses identified 113 single-nucleotide polymorphisms (SNPs) in 69 genes significantly associated with osteoporosis (p < 0.05) in both platforms, with 18 SNPs showing high cross-platform consistency (p < 0.01). Several of these genes were implicated in bone metabolism (e.g., ESRRG, PECAM1, COL6A5), vitamin D metabolism (e.g., NADSYN1, EFTUD1), skeletal muscle function (e.g., PACSIN2, ESRRG), and reproductive processes (e.g., CPEB1, EFCAB6, ASXL3). Notably, the CPEB1 rs783540 SNP exhibited the strongest association (p < 0.001) in both analyses. Our findings suggest that genetic polymorphisms in pathways related to bone metabolism, vitamin D signaling, muscle–bone interaction, and reproductive hormone regulation may contribute to the development of osteoporosis in Korean premenopausal women. These results provide a genetic basis for early identification of at-risk individuals and warrant further functional studies to elucidate the underlying mechanisms. Full article

Gallium-68 is a widely used positron-emitting radionuclide in nuclear medicine, traditionally obtained from ⁶⁸Ge/⁶⁸Ga generators. However, increasing clinical demand has driven interest in alternative production methods, such as medical cyclotrons equipped with solid targets. This study evaluates the functional equivalence of gallium-68 chloride obtained from cyclotron solid target and formulated to be equivalent to the eluate from a germanium-gallium generator, aiming to determine whether this production method can serve as a reliable alternative for PET radiopharmaceutical applications. Preparations of [⁶⁸Ga]Ga-PSMA-11 and [⁶⁸Ga]Ga-DOTATOC, labeled with cyclotron-derived gallium-68 chloride, were subjected to quality control analysis using radio thin layer chromatography and radio high performance liquid chromatography. Subsequently, biodistribution studies were performed in mouse oncological models of expression of PSMA antigen and SSTR receptor to compare uptake of preparations produced with generator and cyclotron-derived isotopes. All tested formulations met the required radiochemical purity specifications. Moreover, tumor accumulation of the radiolabeled compounds was comparable regardless of the isotope source. The results support the conclusion that gallium-68 produced via cyclotron is functionally equivalent to that obtained from a generator, demonstrating its potential for interchangeable use in clinical and research radiopharmaceutical applications. Full article