As data science and machine learning continue to evolve, binary event classification has become increasingly important. Logistic Regression (LR) is a standard baseline, yet it can underestimate probabilities in rare-event settings. This study combines a 16-scenario simulation (rarity 5–10%, n∈ {1000,5000}, p∈ {3,5,7,10}, 100 repeats) with a real-world application to assess Support Vector Machines (SVM), Random Forest (RF), and Gradient Boosting (GB) as alternatives to LR. Training data were balanced using the SMOTETomek hybrid method. In simulation, LR attained the highest balanced performance (G_mean) across cases, with GB the closest competitor; SVM lagged, and RF yielded the lowest G_mean despite often leading test accuracy and precision. On a wine dataset adjusted to 5% and 10% rarity, RF/GB achieved top test accuracy/recall (e.g., ACC=0.998/0.997 with REC=0.958/0.989 at 5% and ACC=0.998/0.994 with REC=0.989/0.977 at 10%), mirroring their strong aggregate accuracy. Overall, the “best” model depends on the target metric: LR/GB when balanced minority–majority performance is critical, and RF when overall accuracy/precision is prioritized.

Electromagnetic memory effect is the residual velocity (a kick) acquired by free charges following the passage of electromagnetic waves. We compute the electromagnetic memory effect in de Broglie-Proca theory for particle scattering in four dimensional Minkowski spacetime as a function of the photon mass, and show that it is suppressed by Yukawa decay compared to usual Maxwell electrodynamics. Therefore, we suggest that its experimental detection would place bounds on, or potentially exclude, the existence of non-zero photon mass.

Antifreeze proteins (AFP) protect the organisms against freezing by increasing freezing tolerance. Insects inhabiting cold regions have been reported to utilize AFPs as part of their cold adaptation mechanisms. The tribe Helopini, a member of the Tenebrionidae family, which is distributed across cold environments ranging from lowlands to high-altitude areas. Cylindrinotus charlesi Nabozhenko, 2015, Odocnemis anatolica Pic, 1899, Nalassus clavicornis Allard, 1876, and Xanthomus ovulus Seidlitz, 1895 - four species belonging to the tribe Helopini (Coleoptera, Tenebrionidae) - are active during cold periods of the year and are known to inhabit cold environments such as under stones near snow or buried in cold dune areas in winter or early spring. Due to their cold habitat preferences, the presence of AFPs in these Helopini species was investigated. To begin, primers were designed. Then, genomic DNA was extracted from the specimens and amplified using polymerase chain reaction (PCR). All PCR samples were analyzed by agarose gel electrophoresis. The sequences were edited and aligned using the Geneious software. As a result, this study identified conserved repetitive amino acid sequences (TCTxSxxCxxAx) of antifreeze proteins in Cylindrinotus charlesi, Odocnemis anatolica, Nalassus clavicornis, and Xanthomus ovulus for the first time. Hypothetical 3D structures formed by these sequences were modeled and predicted using the Swiss-Model. The repeat motifs of Helopini AFPs whose sequences were determined, were analyzed using the MotifFinder. These AFPs were classified at the family levels using the SuperFamily database. In addition, the AFP sequences of Helopini species were compared to those of other beetle species available in the public database using BLAST analysis to assess sequence similarity.

HL1–HL5 Schiff bases were designed by attaching methyl, ethyl, isopropyl, and chloro substituents to the imine group of the 2-((phenylimino)methyl)phenol structure. The experimentally determined basicity constant of the Schiff bases were calculated at various computational levels and a comparative analysis was performed. The B3LYP/6-31G(d) level was determined as the optimal level. The geometries of HL1–HL5 Schiff bases were optimized at the B3LYP/6-31G(d) level. IR and NMR spectra were calculated. The ground state molecular structures of Schiff bases were characterized from IR stretching frequencies, 1H-NMR and 13C-NMR chemical shift values obtained from the optimized structures. Some molecular descriptors, basicity constants (pKb), and proton affinities (PA) of the HL1–HL5 Schiff bases were calculated from aqueous-phase and gas-phase optimizations, respectively. It was found that there is an almost linear proportional relationship between the pKb values of Schiff bases and their HOMO energies and proton affinities. Schiff bases were docked to protein chains with PDB codes 3HY3 and 1M17 in cell lines and their docking poses, binding energies (BE), interaction energies (IE) and total interaction energies (TIE) were calculated. To investigate whether there is a relationship between basicity strength and antitumor activity, BE, IE and TIE graphs were drawn against pKb values of Schiff bases. It was found that the antitumor activity of Schiff bases with high pKb values was generally high. However, it was determined that there was no linear relationship between pKb value and antitumor activity.

This study, which is the first araneo-fauna survey in Bayburt province, was carried out around the Bâbertî Campus of Bayburt University between June and September 2023. A total of 38 species belonging to 14 families were identified in the study. These species constitute the first locality records of Bayburt province. Of these species, Titanoeca tristis L. Koch, 1872 is determined as a new record for Türkiye. Also, the presence of Pardosa aquila Buchar & Thaler, 1998 is confirmed by the present study. Detailed descriptions, photographs and world distribution data of both species are presented. In addition, the copulatory organs of Pardosa aquila Buchar & Thaler, 1998 are compared with those of its closest relative, Pardosa italica Tongiorgi, 1966, found in the same region. All species identified in the study area are listed with their world distributions and references in Türkiye. Keywords: Araneae, Titanoeca tristis, biodiversity, Bayburt.

This paper presents a re-analysis of neutron capture and stellar weak interaction rates of 97Mo under astrophysical conditions. The Maxwellian-averaged cross sections (MACS), neutron capture rates, and β^- decay/positron capture rates are investigated employing the TALYS v1.96 nuclear reaction code and the pn-QRPA model, respectively. We conclude that neutron capture dominates over β^- decay at high stellar temperatures for s-process conditions. The calculated MACS values are consistent with the experimental data. The results shown are important for s-process nucleosynthesis modelling.

The aim of this study was to determine the antibiotic resistance profile of Pseudomonas aeruginosa strains collected from the Microbiology Laboratory of Çukurova University Hospital and evaluate the antibacterial effect of a plant-based bioactive molecule (BAM) mixture against these strains. The VITEK-2 system and antibiogram cards were utilized for organism identification and antibiotic susceptibility determination. P. aeruginosa (N = 37) demonstrated high resistance rates to common antibiotics, including Ampicillin-Sulbactam (100%), Tetracycline (100%), Trimethoprim-Sulfamethoxazole (100%), Tigecycline (97.3%), and Imipenem (64.86%). Resistance was also observed for Levofloxacin, Piperacillin, and Netilmicin (59.46%), Meropenem and Amikacin (56.76%), Ciprofloxacin (40.54%), Cefoperazone-Sulbactam (32.43%), Ceftazidime (25%), Cefepime (24.32%), and Piperacillin-Tazobactam (14.29%). None of the strains were resistant to Colistin. BAM showed significant antibacterial activity, with the highest effect observed in strain P4 (99%). Activity was also notable in strains P2 (98%), P12 (97%), P11 (94%), P37 (81%), P14 (78%), and P1 (35%). In conclusion, the BAM mixture demonstrated high antibacterial efficacy and holds promise as a natural agent for controlling multidrug-resistant (MDR) P. aeruginosa strains in the future.

Ab initio density functional theory (DFT) calculations have been used to determine the band gap of the 2D layered material WSe2 under uniaxial strain. This involves finding optimised lattice parameters and calculating the electronic band structure. We also note that by applying strains ranging from -15% to 15%, a wide range of band gaps can be obtained to study the behaviours of the semimetal and metal. We found, WSe2 structure becomes semi-metal at +12% and -13% strains then or also becomes metal after +12% and -13% strains. The ensuing outcomes are then applied to the domain of machine learning. Initially, PR, which is polynomial regression, is a machine learning method that can be studied with numpy, sklearn and scipy modules, and ANN (artificial neural network) is the application with tensorflow module that is applied to the optimised semi-metallic and metallic structures. The application of the latter involves the Least Squares method. The implementation of Leaky Relu (LRelu) and Elu functions is instrumental in facilitating the deployment of ANN. The potential dataset is obtained by using Quantum Espresso, and the calculations are made by using the National Center for High Performance Computing of Turkey (UYBHM). The PR and ANN results are calculated using the existing data set. The primary objective of utilising PR and artificial neural networks is to facilitate the plotting of Valance Band Maximum (VBM) and Conduction Band Minimum (CBM) graphs in the vicinity of the Fermi level. This study based on data which are already available and could therefore be considered to be data mining. on the electronic band structure for WSe2.

In recent years, mini screws used in the mouth have been widely used in orthodontics clinics to provide dental movements and to increase skeletal anchorage. In this study, bacteria were isolated from mini screws taken from patients who were treated in the Orthodontic Department of Eskişehir Osmangazi University Faculty of Dentistry Clinic and routinely applied mini screws to the anterior and posterior regions of the upper palate for jaw widening or support of dental movements. Streptococcus salivarus (15 isolates), Streptococcus anginosus (12 isolates) and Enterococcus feacalis (10 isolates) were the most isolated bacteria in the microbial composition. Rothia mucilaginosa (8 isolates) and Corynebacteria argentoratense (6 isolates) were isolated from the Actinobacteria phylum. Neisseria oralis, N. flava, N. subflava and N. flavescens species were determined from Proteobacteria phylum.

In response to growing environmental concerns related to water scarcity and industrial pollution, particularly from the textile sector, this study explores a green and sustainable method for synthesizing silver nanoparticles (Ag NPs) using Eucalyptus globulus leaf extract. The biosynthesized Ag NPs were applied for the degradation of Congo Red, a widely used but toxic azo dye. This approach not only offers an eco-friendly alternative to conventional wastewater treatment methods but also demonstrates the potential of plant-based NP synthesis in environmental remediation. The synthesized Ag NPs were thoroughly characterized to confirm their structure, composition, and morphology. UV-Vis spectroscopy indicated the presence of surface plasmon resonance band (405 nm), while STEM analyses revealed spherical NPs ranging around ⁓6 nm in size. EDX confirmed the silver content and XRD demonstrated the crystalline and metallic nature of the Ag NPs. FTIR analysis identified functional groups responsible for the bio reduction, capping, and stabilization, indicating successful green synthesis using Eucalyptus globulus extract. The biosynthesized Ag NPs demonstrated excellent photocatalytic activity, achieving up to 98.9% degradation of Congo Red (CR) dye within 8 min under visible light and 97.8% degradation within 55 under sun light irradiation. Optimization of parameters such as initial dye concentration, catalyst (Ag NP) dose, and light exposure time confirmed the efficiency of the process, which followed a pseudo-first-order kinetic model. These findings demonstrate that green-synthesized Ag NPs are highly effective for dye removal and hold significant potential for environmental and pharmaceutical applications.