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Contributions of mindful parenting and parent–child relationships to children’s executive function: a structural equation model
(Springer, 2026-04-19) Acar, İbrahim Hakkı; Hamamcı, Beyza; Bostancı, Selen
Mindful parenting supports within-family functioning, including parent–child relationships, which may promote positive child outcomes. In the present study, we examined the contributions of mindful parenting and parent–child relationships (positive and negative aspects) to children’s executive function. The study sample consisted of 354 children (192 girls) between 31 and 101 months (M = 66.65, SD = 15.88) and their parents from relatively low socioeconomic backgrounds. Parents reported mindful parenting, parent–child relationships, and children’s executive function. Findings from the structural equation model indicated that higher levels of mindful parenting and positive parent–child relationships were associated with higher levels of children’s executive function. In contrast, a negative parent–child relationship was related to lower levels of executive function. Additionally, mindful parenting was indirectly related to children’s executive function through the parent–child relationship. Findings from the current study underlined the importance of mindful parenting for both parent–child relationships and children’s executive function. In detail, parents who are better at being present with their children and utilizing mindful discipline may exhibit more warmth and supportive relationships with their children. Consequently, positive relationships could lead children to display higher cognitive abilities, including executive function.
Experimental analysis and optimization of cutting strategies and parameters of thin-walled ABS thermoplastics
(Taylor and Francis Ltd., 2026-04-15) Keklik, Burak Taha; Kayıhan, Mete; Kuzu, Ali Taner; Bakkal, Mustafa
This study investigates the influence of tool path and milling parameters on the surface quality and dimensional accuracy of thin-walled structured thermoplastic polymer acrylonitrile butadiene styrene (ABS). Tests examined the effects of up-milling and down-milling on channels of two depths (10 and 20 mm) using three tool path strategies (zig-single direction, zigzag-double direction and follow periphery-peripheral cutting), five cutting speeds (25 to 125 m/min) and three feed rates (0.05, 0.1 and 0.2 mm/rev). The milling operation was carried out with an uncoated tungsten carbide end mill. Performance was evaluated through cutting forces (full and half immersion), surface roughness (base and side walls) and dimensional accuracy (channel width and 1 mm thin-wall deviations). A multi-objective optimization based on the chip removal rate (CRR), width deviation, wall deviations (left and right) and corresponding surface roughness values was conducted in order to determine the optimum cutting parameters. The results demonstrate that the Zig-Zag tool path combined with a cutting speed of 125 m/min yielded the optimal performance. Moreover, the optimization analysis revealed that the ideal feed rates for these conditions fall within the range of 0.05–0.09 mm/rev.
A deployment-oriented privacy-preserving CTI framework: integrating PIR, federated learning, differential privacy, and practical hardenings
(Institute of Electrical and Electronics Engineers Inc., 2026) Çamalan, Emre; Çeliktaş, Barış
Threat Intelligence Platforms (TIPs) enable organizations to share indicators of compromise (IoCs), yet the operational CTI lifecycle exposes multiple, largely independent privacy surfaces: query content and access-pattern leakage during IoC lookup, gradient and membership inference risks during collaborative model training, and residual metadata side-channels in network traffic. Existing work addresses these surfaces in isolation; no prior framework orchestrates their joint mitigation within a single, deploymentoriented CTI pipeline under explicit guarantee boundaries. We present a prototype workflow-level privacy orchestration for cyber threat intelligence that coordinates four mechanisms across the query-learn-update lifecycle: (i) Private Information Retrieval (PIR) to hide queried IoC indices, (ii) cross-silo federated learning (FL) to keep raw CTI data local, (iii) a formal client-level Differential Privacy (DP) mechanism for federated model training to protect against inversion and membership inference attacks, and (iv) practical privacy hardenings, namely fixed-shape PIR batching (a traffic-shaping mechanism, not a cryptographic PIR guarantee) and secure aggregation simulated under an honest-but-curious coordinator assumption, to mitigate residual side-channel leakage. The contribution is therefore one of CTI-specific workflow orchestration and systematic evaluation, not of new cryptographic primitives: formal (ε, δ) guarantees apply exclusively to the differentially private federated learning component, while the remaining mechanisms serve as deployment-oriented hardenings under stated assumptions. We implement a working prototype over a two-million-row AbuseIPDB-style IoC dataset. Under a two-server non-colluding assumption, PIR queries complete in approximately 40 seconds with 16MB transfer per fixed batch. Local Random Forest and Logistic Regression baselines reach 89.0% and 77.00% accuracy, respectively, while federated variants with DP-FedAvg (gradient clipping and RDP-based privacy accounting) demonstrate a quantified privacy–utility trade-off across multiple noise levels. A corrected canonical single-round (T=1) baseline establishes the reconciled reference operating point; reviewer-driven multi-round experiments (T ∈ {1, 10, 20}) and an auxiliary clip-norm sensitivity analysis (C ∈ {0.5, 1.0, 2.0}) further characterize how privacy budgets, model utility, and training stability evolve beyond the single-round setting, with all (ε, δ) values computed via RDP composition for the corresponding configuration. The framework aligns with recent advances in secure aggregation and privacy-preserving CTI analytics, and is designed to be compatible with GDPR, CCPA, ISO/IEC 27701, and NIST 800-53 privacy principles, demonstrating prototype-level feasibility for regulation-aware CTI collaboration across organizations.
Adaptive incident escalation in SOCs via AI-driven skill-aware assignment and tier optimization
(Institute of Electrical and Electronics Engineers Inc., 2026-04-15) Abuaziz, Ahmed; Çeliktaş, Barış
Modern Security Operations Centers (SOCs) face significant operational bottlenecks driven by escalating alert volumes, increasingly sophisticated cyberattack vectors, and chronic imbalances in analyst workloads. Conventional rule-based escalation models frequently fail to account for the multi-dimensional nature of incident characteristics, the nuances of analyst expertise, and fluctuating operational demands. This study proposes a comprehensive AI-driven framework for intelligent incident assignment and workload optimization. The framework introduces five primary contributions: 1) a multi-factor scoring model that integrates severity and complexity metrics with dynamic workload balancing; 2) two novel optimization algorithms, Quantile-Targeted Normality-Regularized Optimization (QT-NRO) and Joint Optimization of Weights and Thresholds (JOWT), to calibrate scoring coefficients against target analyst utilization; 3) a Large Language Model (LLM) engine leveraging Retrieval-Augmented Generation (RAG) for semantic alignment between incident requirements and analyst expertise; 4) an Adaptive Capacity Zoning mechanism for dynamic workload management; and 5) a novel RAG Relevance Score metric—a pre-resolution, semantic alignment indicator that quantifies analyst-incident assignment quality independently of resolution time, addressing a fundamental limitation of traditional temporal metrics such as Mean Time to Resolution (MTTR) and providing a reusable benchmark applicable to any skill-aware assignment system. In addition, the framework incorporates a feedback-based continuous learning mechanism that utilizes historical resolution data to inform future assignments. An experimental evaluation using 10,021 real-world incidents from Microsoft Defender demonstrates that the JOWT algorithm achieves a tier distribution alignment within 0.8% of targets. LLM-enhanced semantic matching yields improvements between 26.7% and 126.8% in skill alignment across both normal-load and high-load evaluations, while simulations indicate a 31.8% reduction in MTTR. These results substantiate the efficacy of AI-driven methodologies in enhancing SOC operational efficiency and response precision.
Optimizing peak age under intermittent satellite connectivity and store-and-forward
(IEEE Computer Society, 2025-10-29) Arı, Çağrı; Kartal, Özkan Tuğberk; Munari, Andrea; Badia, Leonardo; Uysal, Elif; Kaya, Onur
We consider a real-time task-oriented application operating over an intermittently available satellite-based communication network, aiming to collect status updates generated by a remote sensing device. The system is modeled as a scheduling problem over a finite horizon, corresponding to the duration of the task, to minimize the peak Age of Information at the destination. The number of updates that can be transmitted is constrained by a transmission budget. Moreover, the status updates are subject to delays caused by the store-and-forward operation of the satellites, which may vastly vary depending on the network conditions. We investigate three levels of awareness regarding the connectivity conditions of the satellite network: (i) scheduling without any information about connectivity conditions, (ii) scheduling based solely on the current conditions, and (iii) scheduling based on full connectivity knowledge. The first case admits a relatively simple structure, for which a periodic transmission strategy is adopted. The latter two cases are formulated as semi-Markov decision processes and solved to obtain the optimal transmission scheduling policy. Simulation results demonstrate the impact of connectivity awareness on the application performance at the destination. Through a simple modeling approach, we provide first insights into the practically relevant setting of store-and-forward satellite architectures.
Narrative conflicts: a tri-modal computational analysis of antagonism in Shakespeare’s Julius Caesar
(CEUR-WS, 2025-09-26) Yavuz, Mehmet Can; Cascone, Lucia; Özkan, Aylin; Ertaş, İrem
This study introduces a novel computational framework to analyze multi-modal antagonisms—semantic, emotional, and relational—in dramatic literature, specifically focusing on Shakespeare’s Julius Caesar. Employing natural language processing (NLP) techniques, text embeddings, emotion classifiers, and network-based character analyses, we systematically extract and quantify antagonistic relationships within the play. Semantic antagonisms are identified through hierarchical clustering and dimensionality reduction of character embeddings, revealing rhetorical groupings aligned closely with narrative functions. Emotional antagonisms, captured via emotion distribution profiles and variance analysis, illuminate characters’ affective dynamics and their alignment with dramatic roles. Relational antagonisms are explored through co-occurrence networks, highlighting unexpected centrality of minor characters as critical mediators of conflict. Integrating these modalities with Hegelian dialectics and Nietzschean interpretations, our tri-modal analysis provides fresh insights into ideological tensions, character motivations, and narrative structure. This interdisciplinary approach demonstrates the effectiveness of AI-driven tools in enriching literary criticism opening new avenues for exploring conflict dynamics in canonical texts.
Inverse problems for reflector systems
(Institute of Electrical and Electronics Engineers Inc., 2025-09-12) Hasanoğlu, Elman
A comprehensive solution to the three-dimensional inverse problem of transforming wavefronts of arbitrary configuration after two reflections within the geometrical optics (GO) approximation is presented. We establish necessary and sufficient conditions that determine whether a given wavefront mapping can be realized using two mirrors, either prior to or without explicitly computing the mirror surfaces. The cases of spherical and plane wavefronts are analyzed separately, where we demonstrate that the governing equations simplify significantly, reducing to a single equation. Additionally, two-dimensional variants of the problem are considered, and it is shown that, in these cases, the equations for determining the mirror profiles can be solved in quadrature.
Analog PI synchronization circuit design for a memristive Chua's chaotic oscillator
(Institute of Electrical and Electronics Engineers Inc., 2025-12-17) Mazak, Ali; Astekin, Dorukhan; Adıgüzel, Fatih
This paper presents master and slave synchronization of two op-amp-based Chua's circuits using a feedback-linearization-based proportional-integral (PI)-type controller defined on the error signals between the two oscillators. A single control input is applied to the first state of the slave system for practical simplicity without sacrificing performance. The asymptotic synchronization is shown in the sense of Lyapunov stability theory. The designed synchronization scheme is verified comparatively in both MATLAB and LTspice environments.
Volatility spillovers and structural breaks across traditional and digital assets: an econometric investigation (2020–2025)
(Springer Nature, 2026-04) Özyeşil, Mustafa; Teker, Dilek; Teker, Suat; Tembelo, Havane
The need to comprehend the linkages of volatility is more pronounced now owing to the rise of different asset classes, both traditional and digital. In this light, this study focuses on examining the volatility spillovers and structural breaks of four selected key financial instruments: S&P 500 Index, NASDAQ Composite Index, Gold Futures, and Bitcoin. Specifically, this research is designed to investigate how volatility is evolving and transmitting in the presence of economic shocks using a high-frequency dataset for the period January 2020 to May 2025. To capture the dynamic dependencies and regime shifts, sophisticated econometric methods such as GARCH models, the Diebold–Yilmaz spillover index, wavelet coherence, and structural break tests were applied. The results exhibit that Bitcoin is characterized by greater conditional volatility relative to traditional assets. In addition, there is strong volatility clustering across all series. Furthermore, strong volatility spillovers, especially from equities to crypto assets, were identified, and several structural breaks align with important macro-financial milestones such as the COVID-19 crisis and inflationary shocks. It’s shown that the interlinkages among financial markets appear to be on the rise, with asset class volatility increasingly transmitted across them freely. The traits exhibited by digital assets such as Bitcoin differ significantly from those of traditional financial instruments, highlighting the need for more sophisticated risk management strategies. This research fills the gap in the literature cross-market volatility with a time-domain, frequency-domain, and structural change approach. These findings are timely for digital finance in relation to portfolio diversification, strategic asset allocation, and instep with new policies on digital assets.
First year design education inspired by site-specific and site-determined artworks
(Istanbul Teknik Universitesi, Faculty of Architecture, 2026-03-30) Boyacıoğlu, Didem; Durhan, Özlem Sıla
This research explores the potential implementation of site-specific and site-determined artworks as a pedagogical tool for the basic design studios of first-year architectural education, investigating whether these artistic creations can pragmatically contribute to the genesis of new spatial concepts. This study also aims to assess the effectiveness of Kolb’s Experiential Learning Theory (ELT) in the context of studio pedagogy. The basic design course is rooted in process-oriented and student-centred studio pedagogy, drawing on Kolb’s Experiential Learning Theory, and is structured around three site-specific projects that focus on the reproduction of space and the potential of spatial studies. These projects range from building scale to urban pattern, with a focus on various facets of a place, including tangible and intangible qualities, as well as explicit and implicit characteristics, while also exploring the dynamics of human-space relationships. Qualitative data were collected through participant observation, informal interviews, and the analysis of students’ work documents. The course’s progression and outcomes are evaluated in terms of spatial perception, critical and conceptual thinking, and multisensory engagement with space. This course enhanced students’ abilities to interpret spatial experiences, develop a critical perspective, and produce original solutions to spatial problems within the framework of site-specific and site-determined design approaches. The process of the course exposes the latent potential within user-space interactions and the intermediate spatial practices bridging art and architecture. The research is original in that it suggests that many possibilities for interaction, dialogue, and collaboration between art and architecture can be incorporated into architectural education.
Why self-help housing failed in urban Turkey: A policy and legislation misalignment
(Istanbul Teknik Universitesi, Faculty of Architecture, 2026-03) Çelikcan, Elif Cemre; Özsoy, Ahsen
Housing low-income households in Turkey’s urban areas has remained an enduring challenge. During the 1960s, growing housing shortages and economic constraints urged efforts to prevent and upgrade squatter settlements, leading Turkey to adopt self-help housing (SHH) programs for low-cost housing provision. Under the first two five-year development plans (FYDPs), government-assisted SHH initiatives were launched in major cities as part of squatter prevention zones (SPZs). However, the successful beginning of the projects did not lead to successful conclusions; the policy failed to reach its goals in urban areas of Turkey despite the extensive research support. This study investigates the legislative causes behind this failure. It draws on SHH’s core characteristics to analyse its alignment—or misalignment—with Turkey’s policy framework, offering a structured approach to legislative reform. The SHH model is examined across four thematic axes: (1) design process, (2) construction process, (3) actors and roles, and (4) financing mechanisms. The study maps SHH-related regulations in Turkey through a chronological inventory of housing policies, laws, and FYDP targets. Findings highlight the need to restore research-policy dialogue and rethink legislative frameworks to enable viable SHH programs. This study is the first to systematically map Turkey’s legislative misalignments with SHH requirements. It contributes to scholarly debate and future policy-making by offering a novel framework linking architectural theory with policy analysis.
Industrial wastes for soil stabilization
(CRC Press, 2026-01-01) Etminan, Ehsan
Soil stabilization is an important geotechnical engineering method designed to enhance the engineering properties of soil, including its strength, durability, and load-bearing capacity. These improvements are essential for the effective implementation of infrastructure projects, including roadways, embankments, foundations, and airfields. Traditional methods of stabilizing soil usually involve adding materials like cement, lime, or bitumen to soft and expansive clay soils. Although effective, these traditional technologies are frequently economically unfeasible and ecologically unsustainable due to their substantial energy demands and carbon emissions. Recent studies have looked at using industrial by-products-like fly ash, blast furnace slag, red mud, bagasse ash, and cement kiln dust (CKD)-as alternative stabilizers in order to lower the environmental impact of conventional materials and cut costs. Often considered as environmental liabilities, these industrial byproducts can have major technical benefits when used for soil stabilization projects. This integration reduces landfill use and promotes recycling, so it follows ideas of the circular economy. This chapter aims to review conventional and innovative stabilization methods, evaluate industrial waste and their stabilization procedures, compile worldwide laboratory and field case studies, and offer technical and financial evaluations. It concludes with policies, research gaps, and prospective directions.
Analysis and design of a resistor-less DC-bus active discharge and dynamic braking scheme using IGBTs in the active region
(Institute of Electrical and Electronics Engineers Inc., 2026-04) Sezer, Mustafa Murat; Deshmukh, Akshay Vijayrao; Hava, Ahmet Masum; Akın, Bilal
During shutdowns, emergency conditions, and dynamic braking, fully discharging the dc-bus capacitor or clamping the dc-bus voltage in industrial systems is typically managed using power resistors and additional switches. This conventional approach increases system cost, size, and complexity. This article introduces a compact, cost-effective, resistor-less method for two functions: 1) active discharge and 2) dynamic braking in low-power industrial systems. The proposed technique operates IGBTs in their active region with low gate-emitter voltages ($V_{\text {GE}}$ ), creating high impedance in the discharge path to limit current. For active discharge, a constant-power strategy is implemented using pulse frequency modulation (PFM), where the on-time (t_{\text {on}}$ ) of each pulse is fixed and the pulse frequency is ramped up to accelerate energy dissipation. This approach enables complete discharge of a 600-V dc-bus within 1 s, handled entirely by a single IGBT. The method is validated across three different IGBT vendors, showing consistent results and long-term reliability with no parameter degradation after over 200000 completed discharge cycles. For dynamic braking, the PFM method with fixed pulse frequency enables continuous power dissipation between 50 and 150 W for over 30 min. It effectively replaces conventional internal braking resistors typically rated from 20 to 200 W with resistance values of 5-$120~\Omega $. The system can also tolerate brief overloads up to 50% beyond IGBT current ratings for 10-20 s, providing sufficient time to complete braking without failure, as confirmed by test results. All these benefits are achieved through a simple gate driver modification that supplies partial $V_{\text {GE}}$ levels (3-10 V), eliminating bulky resistors, reducing cost by at least 50%, and saving space-making the solution ideal for high-volume industrial applications.
Automating cyber risk assessment with public LLMs: an expert-validated framework and comparative analysis
(Institute of Electrical and Electronics Engineers Inc., 2026-03-26) Ünal, Nezih Mahmut; Çeliktaş, Barış
Traditional cyber risk assessment methodologies face a critical dilemma: they are either quantitative yet static and context-agnostic (e.g., CVSS), or context-aware yet highly labor-intensive and subjective (e.g., NIST SP 800-30). Consequently, organizations struggle to scale risk assessment to match the pace of evolving threats. This paper presents an automated, context-aware risk assessment framework that leverages the reasoning capabilities of publicly available Large Language Models (LLMs) to operationalize expert knowledge. Rather than positioning the LLM as the final decision-maker, the framework decouples semantic interpretation from risk scoring authority through a transparent, deterministic Dynamic Metric Engine. Unlike complex closed box machine learning models, our approach anchors the AI's reasoning to this expert-validated metric schema, with weights derived using the Rank Order Centroid (ROC) method from a survey of 101 cybersecurity professionals. We evaluated the framework through a comparative study involving 15 diverse real-world vulnerability scenarios (C1-C15) and three supplementary sensitivity stress tests (C16-C18). The validation scenarios were independently assessed by a cohort of ten senior human experts and two state-of-the-art LLM agents (GPT-4o and Gemini 2.0 Flash). The results show that the LLM-driven agents achieve scoring consistency closely aligned with the human median (Pearson r ranging from 0.9390 to 0.9717, Spearman ρ from 0.8472 to 0.9276) against a highly reliable expert baseline (Cronbach's α =0.996), while reducing the assessment cycle time by more than 100× (averaging under 4 seconds per case vs. a human average of 6 minutes). Furthermore, a dedicated context sensitivity analysis (C13-C15) indicates that the framework adapts risk scores based on organizational context (e.g., SME vs. Critical Infrastructure) for identical technical vulnerabilities. Importantly, the system is designed not merely to replicate expert intuition, but to enforce bounded, policy-consistent risk evaluation under predefined governance constraints. Overall, these findings suggest that commercially available LLMs, when constrained by expert-validated metric schemas, can support reproducible, transparent, and real-time risk assessments.
Effects of laurocerasus officinalis roem (Cherry Laurel) on cognitive function and neurobiochemical pathways in a streptozotocin-induced nontransgenic Alzheimer's disease model
(Multidisciplinary Digital Publishing Institute (MDPI), 2026-03-08) Özsoy, Fulya; Yanar, Karolin; Sayılı, Uğurcan; Atukeren, Pınar; Uzun, Hafize
Background: This study investigated the effects of Laurocerasus officinalis Roem (cherry laurel; CL), a traditionally consumed fruit, on cognitive performance and selected neurobiochemical and metabolic pathways in a nontransgenic streptozotocin (STZ)-induced Alzheimer’s disease (i.c.v. STZ) model and an STZ-induced type 2 diabetes mellitus (T2DM; i.p. STZ) model. Method: Fifty-seven adult male Sprague–Dawley rats were allocated to control, T2DM, and Alzheimer (ALZ) model groups, with subgroup interventions including CL supplementation and, in the T2DM model, metformin as a comparator. Spatial learning and memory were assessed using the Morris Water Maze. Serum and brain tissue levels of GSK3-β, glutathione (GSH), interleukin-1 (IL-1), GLUT4, GLP-1, β-amyloid (Aβ), and acetylcholinesterase (AChE) were quantified. Results: Serum GSK3-β levels did not differ significantly between groups, whereas brain tissue GSK3-β showed significant between-group differences. CL increased GSH levels in both models, with significant elevations in serum and brain tissue GSH in the ALZ model following CL administration; in the T2DM model, GSH increased after both CL and metformin. In the ALZ model, CL was associated with decreased serum Aβ and AChE levels and improved Morris Water Maze performance, reflected by reduced escape latencies. Conclusions: CL supplementation was associated with antioxidant enhancement and modulation of amyloid- and cholinergic-related measures, alongside improved spatial learning performance in the STZ-induced nontransgenic ALZ model. In addition, CL reduced blood glucose in the T2DM model. Given the likely contribution of fruit phytochemicals (including total phenolics), further studies are warranted to better define the bioactive composition and mechanisms underlying these effects.
Development and validation of a short form of the mentalization scale (MentS-11)\: an evidence-based measure for Turkish adults
(Springer Science and Business Media Deutschland GmbH, 2026-03-03) Ünver, Buket
This study aimed to create a brief Turkish version of the Mentalization Scale (MentS-11) and to evaluate its reliability and validity in a large community sample. Turkish-speaking adults (N = 953) completed the original 25-item MentS, the Interactive Mentalization Questionnaire, and the Interpersonal Neurobiology–Based Prefrontal Cortex Functions Scale. Scale reduction combined exploratory and confirmatory factor analyses with graded-response item response theory. A three-factor solution—Self-related Mentalization (4 items), Other-related Mentalization (4 items), and Motivation to Mentalize (3 items)—displayed acceptable fit (CFI = 0.92, RMSEA = 0.08). Item-response analyses yielded strong discrimination (α = 0.93–2.07) and thresholds spanning the full latent range. Reliability was McDonald’s ωₜ = 0.84 for the total score, 0.81 for Other, 0.77 for Self, and 0.60 for Motivation. Scores on the MentS-11 were nearly identical to those on the 25-item form for the total scale (r =.92) and strongly aligned on their respective subscales (r =.72–0.81). Expected links with external measures confirmed convergent and criterion validity. The MentS-11 retains the theoretical scope and psychometric integrity of the original Turkish scale while halving administration time, making it a practical, time-efficient tool for assessing mentalization in both clinical practice and research.
Economic dynamics of air pollution in Türkiye and Pakistan: an empirical assessment of the Environmental Kuznets Curve and pollution-led growth
(IGI Global, 2026) Taşbaşı, Aslı; Akhtar, Maham
Türkiye and Pakistan, despite differing levels of economic development, face similar macroeconomic challenges such as income inequality, inflation and debt. Both countries also experience environmental pressures from industrialization and rapid urbanization, with air pollution emerging as a critical concern affecting economic productivity and sustainable development. This study conducts a comparative analysis of air pollution in Türkiye and Pakistan from 1980 to 2023, using the Autoregressive Distributed Lag (ARDL) bounds testing approach to examine the short and long run relationships between air pollution, urbanization, industrialization, energy consumption and macroeconomic policies. The analysis tests the Environmental Kuznets Curve (EKC) for Türkiye and the pollution-led growth hypothesis for Pakistan. Findings reject the EKC for Türkiye but confirm pollution-led growth in Pakistan, offering insights for effective environmental regulation and sustainable development strategies.
The Killing magnetic curves in the anti-de Sitter space H31
(TUBITAK, 2026-03-10) Dursun, Uğur
In this paper, we study space-like, time-like and light-like Killing magnetic curves derived from Killing magnetic vector fields of the anti-de Sitter space H31 by using the half-space model H31 of H31 . We find the first integrals of the system of nonlinear differential equations that describe the Killing magnetic curves corresponding to some Killing vector fields of H31 , and then we give some particular solutions to obtain space-like, time-like and light-like magnetic curves of H31 . Also, we calculate the curvature and torsion of some space-like and time-like Killing magnetic curves, and the torsion of light-like Killing magnetic curves of H31.
Infrequent rebalancing, risk deferral, and equity returns at the turn of the month
(Elsevier Ltd, 2026-03-13) Kayaçetin, Nuri Volkan
We examine equity returns at the turn of the month using return data from thirty countries over the thirty-year period from January 1, 1994, to December 31, 2023. Our analysis reveals that the mean daily return on trading days surrounding the end of the month is significantly larger at 10 bps across the markets examined as compared to 0 bps on other days, with a narrow window bracketing month-ends accounting for all or nearly all positive mean return in each of the countries examined. Linking this pattern to the interaction between slow moving institutional capital and market frictions, we provide evidence in line with the idea that the observed pattern might be sustained by a dual-channel mechanism. First, the effect appears to be amplified hierarchically due to overlapping rebalancing mandates, peaking at lower frequencies due to the synchronization of a larger number of rebalancing schedules. Second, and more importantly, the effect also seems to be conditioned by the deferral of risky investments to structured rebalancing nodes during periods of market distress. Consistent with this mechanism, its magnitude is significantly larger after periods of market turbulence and during recessions, when investors are likely to store more cash in safe assets. Our findings thus provide a robust economic framework for understanding the enduring presence of the turn-of-the-month effect, suggesting that it may emerge as a joint consequence of infrequent rebalancing and risk deferral.
From policy to practice: a sector-agnostic operational framework for post-quantum cryptography transition
(Institute of Electrical and Electronics Engineers Inc., 2026-03-02) Birgin, Berat; Çeliktaş, Barış
The pace of quantum computing development necessitates not only the adoption of post-quantum cryptographic algorithms, but also the establishment of an executable and auditable institutional transition process. Although guidance documents published by the National Institute of Standards and Technology (NIST) and roadmaps proposed by the Post-Quantum Cryptography Coalition (PQCC) articulate strategic objectives, they largely remain procedural constructs lacking a concrete operational execution model. This paper presents an industry-neutral operational framework that translates policy-level post-quantum cryptography (PQC) guidance into deterministic, proof-producing process flows encompassing cryptographic asset discovery, classification, risk modeling, algorithm selection, deployment, monitoring, and governance enforcement. Central to the framework is a deterministic Quantum Risk Scoring (QRS) function, calibrated using the Analytical Hierarchy Process (AHP), which enables reproducible asset prioritization and policy-driven enforcement decisions. Framework executability is further strengthened through cryptography-aware continuous integration/continuous deployment (CI/CD) validation gates and downgrade protection mechanisms, ensuring the generation of verifiable and immutable audit artifacts. A scenario-based operational validation, implemented using open-source toolchains, demonstrates the framework’s operability, auditability, and governance alignment without relying on empirical cryptographic performance benchmarks, confirming that PQC transition can be operationalized as a verifiable lifecycle process bridging policy guidance with enforceable technical actions. Rather than introducing new cryptographic primitives, this work formalizes PQC transition as an operational systems-engineering problem centered on governance-enforced execution and lifecycle verifiability.

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