Narratives of solidarity: Eperimental evidence on shifting attitudestowards refugees

This study investigates the constitutive role of narratives–multilayered, story-like, normative communications–in shaping public attitudes towards one of the world's most systematically stigmatised groups: forcibly displaced migrants such as refugees, asylum seekers, and undocumented migrants. We introduce a novel sequential design where qualitative fieldwork informs the development of a large-scale online survey experiment (N= 1507). Our work tests the impact of solidarity-driven and bias-disrupting narratives in Turkey, a critical host country for refugees over the last decade, amidst intense public hostility, departing from experimental scholarship's common focus on negative narratives that highlight the outsider status of migrants. We demonstrate that even brief exposure to our narratives significantly improves both attitudinal solidarity and the willingness to take pro-refugee action in a challenging context. Critically, these effects are most pronounced among religious individuals, lower-income groups, and people who have minimal or no contact with refugees previously. These results provide strong evidence that carefully crafted narratives can shift public opinion and change the attitudes of some key groups towards refugees who are reported to hold firm anti-refugee and anti-migrant views. Overall, the study provides empirically grounded strategies for countering the pervasive narrative dominance of nativist actors who rely on sensationalised and misleading narratives. © 2026 Informa UK Limited, trading as Taylor & Francis Group.European Union's Horizon 202

Synthetic data generation and energy consumption prediction in district building energy modeling

This study presents a novel district building energy model by integrating the strengths of dynamic and statistical models. This multitier model can generate hourly synthetic energy consumption data for urban building stocks by incorporating building characteristics and local weather data and predict hourly building energy consumption. The methodology involves the following steps: (1) A dynamic model is created, and its key parameters are calibrated according to monthly metered data. (2) The calibrated dynamic model is then utilized to generate synthetic hourly energy consumption data. (3) Finally, statistical models are trained on synthetic data to predict hourly building energy consumption. Once the proposed methodology is tested on a university campus, the calibration reduces the monthly simulation error to an 11.9% Coefficient of Variation of the Root Mean Square Error (CV-RMSE) based on available metered energy consumption data, and the final statistical model predicts the hourly building energy consumption with a 1.5% CV-RMSE. This multitier model offers valuable insights for urban planners in identifying high-demand areas and implementing energy-efficient interventions by generating synthetic hourly energy consumption data.TÜBİTA

Wear performance of additive-manufactured and heat-treated CoCrMo alloy

This study examines the wear behavior of additive-manufactured CoCrMo alloy in as-built and heat-treated conditions. Suitable thermal processing modified fine cellular grains and grain-boundary carbides into equiaxed FCC grains and minor HCP phase. With increased load, coefficient of friction declined due to larger contact area and tribo-oxide formation during reciprocating wear experiments. At 10 N, wear is mainly abrasive in the as-built condition, whereas after heat treatment at 1200 degrees C it becomes dominated by stick-slip mode. At 40 N, there is a transition to delamination, ploughing, and subsurface fatigue cracking. Heat-treated samples, despite lower hardness, outperformed at 40 N while exhibiting lower wear rate.Turkiye Cumhuriyeti Kalkinma Bakanlig

Reactive power market design for unutilized grid-forming assets to address power factor penalties in Turkiye

The increasing penetration of small-scale PV distributed generation in medium-voltage networks has introduced unexpected challenges. While PV generation reduces the real power drawn from the transmission grid, the absence of monetization for reactive power means that reactive demand remains unchanged. This mismatch results in declining power factors and potential financial penalties for DSOs. A local reactive power market offers an alternative solution, not for voltage stability but specifically for maintaining the power factor. This paper proposes a reactive market framework tailored for Turkiye, covering its operational steps, market-clearing process, demand elasticity, payment structure, and mathematical model. The framework incorporates a ±10% forecast tolerance to discourage gaming and promote fairness. It introduces the concept of a sustainability threshold to ensure that energy sustainability remains central to the system operations. Finally, two key regulatory proposals are discussed to accelerate implementation: spatial aggregation of power factor limits to increase competitiveness and dynamic, seasonally-adjusted thresholds to reflect demand seasonality

Deterrence, prior experience, and drunk-driving intentions: A survey experiment among Turkish drivers

This study evaluates the core claims of deterrence theory in the context of drunk driving among Turkish drivers. Using a scenario-based, 3 × 3 factorial survey, 1153 respondents read one randomly assigned vignette that varied the likelihood of police detection (low/medium/high) and the severity of legal sanctions (fine only/fine + license suspension/fine + license suspension + imprisonment). Participants then reported (a) their perceived certainty of apprehension, (b) the perceived severity of punishment, and (c) their likelihood of driving after drinking. Additional items captured demographics, lifetime drunk-driving frequency and punishment history. Findings replicate several patterns in a non-Western setting. Higher perceived certainty and, to a lesser extent, higher perceived severity were associated with lower offending intentions. Environmental cues embedded in the vignettes systematically shifted certainty and severity perceptions. Prior drunk-driving experience lowered perceived certainty, but prior punishment did not raise it, offering only partial support for specific deterrence. Certainty effects emerged only above a 70 % subjective likelihood of apprehension, and severity mattered chiefly when certainty was moderate. The limited impact of formal punishment, together with evidence of compliance despite low perceived risk, suggests an important role for informal social controls in Turkey's drunk-driving deterrence landscape. © 2025 Elsevier Lt

Migration and local innovation: Evidence from fine-grained data from oecd countries

Does the presence of migrants influence innovation at the local level? This paper answers this question using novel data containing fine-grained information on the migrant population and geo-coded data on patent locations for a large set of 19 OECD countries over the 1990–2014 period. We find that a one percentage point increase in the local migrant share increases patent applications by 2.5%. This effect is driven by more urbanised and economically developed localities, where innovation levels are already higher to begin with. However, this impact becomes insignificant when aggregating observations at larger geographical levels, suggesting that the effect of migration on innovation is concentrated in space and features high rates of spatial decay. © 2025Publisher versio

Micro-laser-induced breakdown spectroscopy using GHz repetition rate pulses at nJ pulse energy

Using GHz repetition rate pulses in burst mode has shown significant attention, particularly in laser micromachining, due to its ability to enable highly efficient, low-energy material removal. In this work, we introduce the first Laser-Induced Breakdown Spectroscopy (LIBS) in the ablation-cooled regime. By employing GHz repetition rate pulses, we present a high-speed (100 kHz) micro-LIBS system that operates with ultra-low pulse energies in the range of 10 - 200 nJ. To achieve this, we employ our home-built 2.8 GHz burst-mode Yb-doped fiber laser, which delivers ∼40 ps pulses to the sample with a beam diameter of around 18 μ m. A systematic LIBS study was conducted on stainless steel (SS) under varying burst durations and burst energies to investigate their effects on the optical emission spectrum. Finally, the electron temperature and electron density were determined using the Boltzmann plot method and Stark-broadened line profile analysis, respectively. © 2025 The Author(s). Published by IOP Publishing Ltd.TÜBİTAKPublisher versio

A heat flux model for nucleate boiling on micro-cavity surfaces

This study investigates the influence of spacing (500-1000 mu m), cavity size (100-300 mu m), and subcooling (0-10 K) on nucleate pool boiling heat transfer performance using selectively micro-caved copper surfaces. The cavity spacings (S-p approximate to S/D-b <0.4 for saturated and S/D-b <0.5 for subcooled conditions) were optimized to minimize bubble interference, while cavity sizes were chosen based on active nucleation ranges derived from theoretical calculations. Micro-drilled surfaces generally demonstrated up to 69% higher critical heat flux (CHF) and significantly improved heat transfer coefficients (HTC) up to 10.1 x 104 W/m2K compared to plain surfaces. Subcooling enhanced the condensation rates of departing bubbles near the heating surface and delayed CHF, resulting in up to 46% higher CHF compared to saturated condition and steeper boiling curves. The larger spacing (1000 mu m) reduced thermal and hydrodynamic interactions, facilitating stable bubble detachment and efficient surface rewetting. In contrast, smaller cavities (100 mu m) increased the frequency of bubble departure and HTCs, while larger cavities (300 mu m) led to premature coalescence and persistent vapor layers, reducing heat transfer performance and approximating the results of plain surfaces with slightly smaller superheats. High-speed imaging provided detailed insights into isolated bubble departure dynamics and validated empirical models, while also verifying the predictive accuracy of the proposed model. The proposed heat flux model exhibits quite satisfactory reliability, with CHF predictions for micro-drilled surfaces within +/- 15% error. These findings highlight the complex interplay of geometric and thermal parameters in boiling heat transfer and offer a robust framework for optimizing surface designs and operating conditions in high-flux boiling applications.Istanbul Teknik Üniversites

A matheuristic for the joint replenishment problem with and without resource constraints

We study the Joint Replenishment Problem (JRP), which arises from the need for coordinating the replenishment of multiple items that share a common fixed cost. Even in the basic setting, determining the optimal replenishment plan is an NP-Hard problem. We analyze both the JRP under indirect grouping policy and its variant with restrictions like transportation capacity, budget capacity, and item transportation compatibility. Additionally, we consider uncertainty characteristics such as imperfect item quality, as highlighted in related literature studies. We propose a novel matheuristic method that determines the best basic cycle time while addressing the problem with a fixed cycle time using a linear integer model. The proposed method is quite versatile to handle additional real-life constraints effectively. Based on an extensive computational study, we conclude that for the basic setting under indirect grouping policy, the proposed algorithm outperforms the benchmark algorithms in the literature by 0.3% on average. For more complicated settings with additional restrictions, our proposed algorithm outperforms the benchmark algorithm by around 5% on average

Numerical simulations of non-fluorescent states of carboxyfluoresceins in presence of heavy iodine ions

In the present research, the effects of heavy iodine ions on dark transient state populations of carboxyfluorescein derivatives, each with a different number of bromine atoms attached, were computationally examined via numerical simula tions adapted to a widefield fluorescence microscopy integrated with a microfluidics platform. Numerical simulations were car ried out by considering geometrical profile of excitation laser beam, microscopy and microfluidics parameters of a proposed experimental design as well as electronic transition rates of fluorescent molecules. Electronic state model of studied dyes was treated as a system of first order ordinary differential equa tions and time-dependent solutions of long-lived, non-fluorescent dark state populations were computed for each dye at varying potassium-iodine [KI] concentrations. Analytical solutions of state populations were then adapted to a proposed experimental setup to systematically analyze how dark state populations evolve when carboxyfluorescein derivatives pass through exci tation beam field in a microfluidics chip under different flow speeds. Computational experiments have successfully uncovered systematic changes in dark triplet and photo-oxidized state populations upon the addition of iodine ions into fluorophore solutions.TÜBİTAKPost prin