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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14411/18
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Article SHAP-Guided Feature Selection for Cross-Dataset Generalization in Network Intrusion Detection Systems(IEEE, 2026) Şengül, Gökhan; Kılıç, CanFlow-based machine learning intrusion detection systems (IDS) often achieve near-perfect performance when trained and tested on a single benchmark dataset; nonetheless, their ability to generalize across datasets is a crucial and mostly unresolved challenge. This study analyzes the cross-dataset generalization behavior of an explainable, flow-based IDS trained on CICIDS2017 and externally evaluated on the CSE-CIC-IDS2018 dataset, which represents a more realistic network environment with varying attack implementations, traffic compositions, and background services. Two frequently used ensemble models, Random Forest and XGBoost, are trained solely on flow-level metadata without packet payload examination. After removing non-behavioral identifiers (Flow ID, Source IP, Destination IP, and Timestamp) and harmonizing feature schemas, the datasets are aligned into a unified 80-dimensional feature space extracted with CICFlowMeter. SHAP (TreeSHAP) is used to calculate global feature importance and create multiple explainability-driven feature subsets, such as model-specific Top-20 sets, a COMMON-10 intersection, and a UNION-30 superset. Although both models attain near-perfect accuracy and weighted F1-scores on CICIDS2017 (macro-F 1 ≈ 0.90 ), when evaluated on CSE-CIC-IDS2018, macro-F1 drops to 0.127 for Random Forest and 0.119 for XGBoost, despite high overall accuracy, indicating a strong bias toward majority classes under domain shift conditions. SHAP-guided feature reduction provides a measurable but limited improvement for Random Forest, increasing macro-F1 from 0.127 to 0.166, while an additional port-removal ablation further improves macro-F1 to 0.207. In contrast, no significant cross-dataset improvement is observed for XGBoost. An additional practical observation is that SHAP-guided feature rankings remain highly stable across sample sizes: class-balanced subsets of approximately 400 flows (50 samples per class) produce highly similar Top-20 rankings to those obtained from 10,000 flows (1250 samples per class), supporting the feasibility of computationally efficient explainability. Overall, the results show that explainability-driven feature analysis improves transparency, compactness, and feature prioritization; however, it does not fully resolve the broader distributional shift challenges that limit cross-dataset generalization in flow-based intrusion detection systems.Article Weyl Double Copy in Lifshitz Spacetimes(Amer Physical Soc, 2026-04-27) Gumu, Mehmet Kemal; Alkac, Gokhan; Olpak, Mehmet AliLifshitz black hole solutions pose particular challenges for reconciling the two main formulations of the classical double copy: the Kerr-Schild double copy and the Weyl double copy. Recent work has suggested that consistency between the two can be restored, in certain cases, only by adopting a regularization prescription in the Weyl double copy. In this paper, we test this prescription on three examples from the literature, each with a distinct novel feature, and show that the prescription remains valid in all cases.Article Thermal and Optical Signatures of Einstein-Dyonic ModMax Black Holes with GUP and Plasma Modifications(Elsevier, 2026-05) Sakallı, İzzet; Sucu, Erdem; Dengiz, SuatWe explore the thermodynamic and optical properties of Einstein-Dyonic-ModMax (EDM) black holes (BHs) incorporating quantum gravity corrections and plasma effects. The ModMax theory promotes the classical Maxwell theory to a non-linear electrodynamics with a larger symmetry structure (electromagnetic duality plus conformal invariance), and provides dyonic BH solutions characterized by both electric and magnetic charges modulated by the nonlinearity parameter gamma. Using the Hamilton-Jacobi tunneling formalism, we derive the Hawking radiation spectrum and demonstrate how the Generalized Uncertainty Principle (GUP) modifies the thermal emission, potentially leading to stable remnants. Our analysis of gravitational lensing employs the Gauss-Bonnet theorem to compute light deflection angles in both vacuum and plasma environments, revealing strong dependencies on the ModMax parameter and plasma density. We extend this to axion-plasmon environments, uncovering frequency-dependent modifications that could serve as dark matter signatures. The photon motion analysis in plasma media shows how the exponential damping term e-gamma affects electromagnetic backreaction on spacetime geometry. We compute quantum-corrected thermodynamic quantities, including internal energy, Helmholtz free energy, pressure, and heat capacity, using exponentially modified entropy models. The heat capacity exhibits second-order phase transitions with critical points shifting as functions of gamma, indicating rich thermodynamic phase structures. The energy condition analysis shows that classical ModMax electrodynamics satisfies the null and weak energy conditions, while the observed near-horizon violations arise only after incorporating quantum-corrected entropy effects.Article The Effect of Lactoferrin on Cytosolic Antioxidant Enzymes, Glucose Uptake, and Wound Healing in Caco-2 Cells(Bayrakol Medical Publisher, 2025) Isgor, Yasemin Gulgun; Bodur, Mahmut; Ozcelik, Ayse Ozfer; Ayan, Firat; Isgor, Sultan BelginAim: The aim of this study is to investigate the dose-dependent effects of lactoferrin (LF) on glucose uptake, wound healing, and antioxidant enzyme activities in human colon carcinoma cells (Caco-2). Materials and Methods: Caco-2 cells were treated with LF (0-250 mu g/mL, 1:2 dilution), and its effects on cell viability using the MTT assay, glucose uptake using the 2-NBDG assay, wound healing using the scratch assay, and antioxidant enzyme activities by measuring superoxide dismutase (SOD), glutathione peroxidase (GPx), and glutathione-S-transferase (GST) activities were evaluated. Results: Lactoferrin showed a dose-dependent cytotoxic effect, with IC50 values of 249.7 mu g/mL (24h) and 74.91 mu g/mL (48h). Glucose uptake was inhibited by 14% and 8% at 62.5 mu g/mL and 125 mu g/mL LF, respectively (p < 0.001). Lactoferrin significantly accelerated wound healing, achieving 90% closure at 72 hours, with 62.5 mu g/mL being the most effective dose. Antioxidant enzyme activity increased significantly, with SOD (155%), GPx (85%), and GST (53%) reaching peak levels at 125 mu g/mL LF (p < 0.001). Discussion: In conclusion, LF reduced glucose uptake, increased antioxidant enzyme activity, and accelerated wound healing in Caco-2 cells. These findings suggest that lactoferrin may have potential therapeutic applications in conditions related to oxidative stress, impaired glucose metabolism, and delayed wound healing, such as diabetes and chronic wounds. Further in vivo and human studies are needed to explore its clinical relevanceArticle Profits, Wages, and Taxes: Understanding Inflation Dynamics in Türkiye(Sosyoekonomi Soc, 2026-04-28) Sakarya, Burçhan; Bülbül, Duran; Duvan, Osman BerkeThe COVID-19 pandemic and the Russia-Ukraine conflict have led to a global living standards shock, increasing interest in the interactions between firm profits and inflation. This study examines profit-driven inflation dynamics in Türkiye, also considering wages and net taxes. Using the deflator decomposition method and the Local Projections model, it analyses their effects on consumer inflation. Findings show that unit profit inflation is a key driver of price increases, while wage-price pass-through is nonlinear, and tax effects are delayed but significant. The study highlights the need for an integrated policy approach that combines monetary, fiscal, and competition policies to manage inflation effectively.Article Optimizing Drone-Based Humanitarian Relief in Post-Disaster Scenarios: A Hybrid MCDM and Maximum Coverage Approach(Springer Heidelberg, 2026-05-02) Vural, DanismentThis study proposes a novel hybrid decision-making framework that integrates expert-driven supply prioritization via the Stepwise Weight Assessment Ratio Analysis (SWARA) method with an operationally constrained Maximum Coverage Problem (MCP) model to optimize drone-based humanitarian logistics in post-disaster scenarios. Grounded in a real-world case study of the 2023 Kahramanmaraş earthquake, the model systematically elicits expert preferences to rank critical supplies such as food, medical items, and cold chain products, and embeds these weights directly into a constrained MCP formulation. The model incorporates drone-specific operational limits, including battery consumption, payload capacity, and round-trip feasibility, to ensure realistic deployment strategies. Results show that scenario configurations with four to five strategically located drone bases, each equipped with four to five drones, can increase the achieved priority-weighted delivered quantity by up to 35-40% compared to minimal base-drone configurations within the proposed model framework. Moreover, the proposed framework improves responsiveness by prioritizing urgent deliveries and supporting more timely allocation decisions under operational constraints. Unlike traditional MCP approaches that rely on static weights, this method offers a context-sensitive and scalable optimization model informed by field expertise. The findings underscore the potential of structured expert-based weighting combined with operational optimization to enhance the efficiency and responsiveness of drone-assisted disaster relief systems.Article Nutritional Composition, Phenolic Constituents, and Antioxidant Activity of the Edible Desert Truffle Terfezia Claveryi (Chatin)(Wiley, 2026-01) Bulut, Onur; Altunbas, Osman; Sonmez, CaglaThe edible desert truffle, Terfezia claveryi, is a highly valued wild macrofungal species native to the semiarid regions of Central Anatolia. This study provides molecular identification and a comprehensive biochemical evaluation of T. claveryi, using lyophilized material to assess its nutritional composition, phenolic profile, and antioxidant potential. Proximate analysis revealed high carbohydrate (69.93 +/- 1.69%) and moderate protein (13.8 +/- 0.55%) contents, a low lipid level (3.45 +/- 0.14%), and notably high vitamin C concentration (86.90 +/- 0.33 mg 100 g(-1) DW). Linoleic (C18:2%, 67.63%), oleic (C18:1%, 17.29%), and palmitic (C16:0%, 10.81%) acids predominated in the fatty acid profile. Amino acid analysis showed an exceptionally high lysine proportion (30.9% of total amino acids) and an essential-to-nonessential amino acid ratio (1.64) exceeding the FAO/WHO reference value, indicating superior protein quality. Mycotoxins were not detected using chromatographic methods, confirming the safety of the samples. Solvent extracts of lyophilized T. claveryi were prepared using methanol-water and acetone-water mixtures at varying ratios, as well as ethyl acetate and hexane. Total phenolic and flavonoid contents were highest in aqueous methanol and acetone extracts, which also exhibited strong radical scavenging and reducing activities in DPPH, FRAP, and ABTS assays. RP-HPLC analysis identified gallic acid, rutin, quercetin, and vanillic acid as major phenols, with gallic acid being predominant (154.81 +/- 5.50 mu g g(-1) DW). A strong correlation (R-2 > 0.95; p < 0.001) was observed between phenolic content and antioxidant capacity. Overall, T. claveryi represents a safe, nutrient-rich, and phenolic-dense functional food with significant potential to complement lysine-deficient cereal-based diets.Article Next Generation Mood Adaptive Behavioral Modeling for Decarbonizing Office Buildings and Optimizing Thermal Comfort(MDPI, 2026-04-08) Alkan, Nese; Turhan, Cihan; Doruk, Ozgur Resat; Ozbey, Mehmet Furkan; Thapa, Samar; Chen Austin, Miguel; Austin, Miguel Chen; Pekcan, PoyrazConventional Heating, Ventilation, and Air Conditioning (HVAC) control systems primarily rely on environmental and physiological parameters, largely ignoring the critical influence of psychological states on thermal comfort. Overlooking this factor often leads to suboptimal occupant satisfaction, energy inefficiency and thus carbon dioxide (CO2) emissions. To this aim, this study introduces a novel mood-adaptive HVAC control system integrating psychological feedback to decrease CO2 emissions in office buildings by reducing energy consumption and optimizing comfort. A total of 7000 thermal facial measurement records and high-resolution camera images were collected across seven mood state conditions using video stimuli and the Profile of Mood States (POMS) questionnaire to evaluate mood variations. A dual artificial intelligence system was developed: a Convolutional Neural Network (CNN) for analyzing facial expressions and an Artificial Neural Network (ANN) for processing facial temperatures via thermal imaging. These models collectively predict occupant mood in real-time, and a custom-designed wearable necklace interface transmits this data to dynamically adjust HVAC setpoints. To evaluate system performance, energy consumption was directly measured in real-life operations using an energy analyzer, without relying on simulations. Results indicate that this prototype personalized mood-driven system has the potential to enhance perceived thermal comfort while achieving up to a 20% reduction in carbon emissions compared to conventional systems. This human-centered approach significantly advances intelligent building management and climate change mitigation.Article Magneto-Electrochemical Biosensing for Pathogen Detection Using Nuclease-Responsive Nanohybrids(Springer Wien, 2026-05) Dursun, Ali Dogan; Ozalp, Veli Cengiz; Kibar, Gunes; Borsa, Baris A.; Hernandez, Frank J.; Kavruk, MuratThe development of sustainable and highly sensitive diagnostic platforms is critical for rapid pathogen identification and effective disease management. Here, a green, magneto-electrochemical biosensing strategy is reported for the selective detection of Streptococcus pneumoniae based on pathogen-specific nuclease activity. Uniform organic-inorganic hybrid polyhedral oligomeric silsesquioxane (POSS) nanoparticles were synthesized via an ultrafast UV-initiated emulsion polymerization within 5 min using an eco-friendly approach. The nanoparticles were sequentially functionalized by in situ deposition of superparamagnetic iron oxide nanoparticles and biomimetic polydopamine coating, enabling robust and high-density immobilization of nuclease-responsive oligonucleotide probes. The resulting PDA@SPION/POSS nanohybrids exhibit controlled size, preserved structural integrity, and strong superparamagnetic behavior, allowing efficient magnetic manipulation and electrochemical signal transduction. Upon exposure to S. pneumoniae, nuclease-mediated probe cleavage produces a pronounced electrochemical response, enabling label-free detection over a wide dynamic range (102-10(8) CFU mL(-)& sup1;) with a detection limit of 102 CFU mL(-)& sup1;. High selectivity against non-target bacteria highlights the specificity of the enzymatic recognition mechanism. This work establishes a sustainable and amplification-free biosensing platform with strong potential for rapid clinical diagnostics.Article Light Cone QCD Sum Rules Study of the Rare Radiative Ξbb* → Ξbγ Decay(Amer Physical Soc, 2026-05-08) Sarac, Y.; Ozpineci, A.; Aliev, T. M.The rare radiative decay Xi(bb)*-Xi(b)gamma is investigated within the light cone QCD sum rules approach. This decay proceeds through the flavor changing neutral current b -> s transition in the Standard Model. The hadronic matrix element of the considered decay is parameterized in terms of four tensor form factors T-1(V) (q(2)), T-2(V) (q(2)), T-1(A)(q(2)), and T-2(A)(q(2)). The sum rules for these form factors describing the Xi(bb)* -> Xi(b)gamma decay are derived at q(2) = 0 point using the b distribution amplitudes. The results of the form factors are employed to calculate the corresponding decay width. Our finding indicates that this weak radiative decay could be within reach of future high statistics studies of doubly heavy baryons at LHCb and upcoming facilities.