DSpace Arşivi :: Ana Sayfa

İstanbul Gelişim Üniversitesi Kurumsal Açık Erişim Arşivi

DSpace@Gelişim, İstanbul Gelişim Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.

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Loading modulates monosynaptic transmission from spindle primary afferents to motoneurons in humans
(Springer Verlag, 2026) Yıldız, Nilgün; Sezikli, Selim; Kalaoğlu, Eser; Karacan, İlhan; Türker, Kemal Sıtkı
The literature does not provide a consistent account of how mechanical loading influences H-reflex excitability. Given the methodological diversity across previous studies, the present study investigated how different levels of mechanical load affect soleus H-reflex excitability during quiet stance in healthy adults. It incorporated several experimental controls to enhance the reliability and comparability of results. Eighteen participants were tested under five load conditions (10-100% of body weight) while maintaining a consistent M-wave amplitude and a relaxed muscle posture. H-reflex amplitude decreased progressively with increasing load, reaching significant suppression at full weight-bearing (F (4, 68) = 7.04, p < 0.001, partial η² = 0.293), whereas background EMG activity showed an opposite trend (χ² (4) = 26.97, p < 0.001). This dissociation suggests that muscle spindle-based spinal reflex excitability does not scale linearly with muscle activation, indicating enhanced premotoneuronal modulatory control under higher loading. These findings highlight that spinal circuits dynamically adjust reflexes to stabilise posture, prevent excessive contractions and fine motor control in response to increasing mechanical demands.
A novel method to estimate discharge-independent inhibition durations of spinal and brainstem circuits in humans
(American Physiological Society, 2026) Topkara Arslan, Betilay; Özyurt, M. Görkem; Türker, Kemal Sıtkı
Direct recordings from human motoneurons are not feasible; therefore, researchers have developed indirect methods to estimate postsynaptic potential profiles, that is, the functional inhibition or excitation, on firing motor units. Surface and intramuscular electromyography have shown that the duration of the functional inhibition varies depending on the neural circuit investigated and is influenced by stimulus intensity and muscle activity level. This study aimed to standardize the estimation of functional inhibition durations across three distinct spinal and brainstem circuits by leveraging the known dependence of inhibition duration on background motor unit discharge rate. We analyzed data from previous rat brain slice experiments in which known currents were injected into regularly discharging motoneurons. Regression of injected inhibition duration against discharge rate revealed a strong predictive relationship when extrapolated, accurately converging on the known duration. Specifically, this regression yielded the actual inhibition duration at a discharge rate of 0.98 imp/s (range: 0-5.91 imp/s). Building on these findings, we conducted three inhibition paradigms in human volunteers, targeting the masseter inhibitory reflex, the cutaneous silent period and recurrent inhibition mediated by Renshaw cells. Using extrapolated correlation plots of motor unit discharge rate versus functional inhibition duration, we derived discharge rate-independent inhibition durations. All three circuits demonstrated longer inhibition duration ranges than previously reported. This standardized approach enables more accurate estimation of inhibition duration across various circuits, independent of discharge rate. It holds promise for clinical applications in the early diagnosis and monitoring of neurological disorders affecting inhibitory circuits.NEW & NOTEWORTHY Direct recordings from human motoneurons are not feasible; therefore, synaptic inhibition must be estimated indirectly. Experiments on rat brain slices allow accurate prediction of inhibition duration, independent of motor unit discharge rate. Applying these predictions in human studies has revealed discharge rate-independent functional inhibitions across various brainstem and spinal circuits. This approach offers robust estimates of functional inhibition, with potential clinical applications for monitoring neurological disorders that affect neural circuits.
Artificial Neural Network Modeling to Predict Corrective Stress of a Two-layer Composite Plate under Fully Reversed Cyclic Loading Using the Finite Element Method & Morrow Method
(Nature Publishing Group, 2026) Alkhafaji, Ali; Khalaf, Mohammed I; Ismail Kh, Teeba; Sawaran Singh, Narinderjit Singh; Hussein, Shaymaa Abed; Alsaadi, Mohmood; Jasim, Dheyaa J.; Taner, Mahmut; Salahshour, Soheil
In this study, a single-hidden-layer feedforward Artificial Neural Network was developed to predict the maximum stress of a two-layer composite plate based on the Morrow correction method under fully reversed cyclic loading. A rectangular two-layer plate made of Epoxy Carbon Woven (230 GPa) was analyzed using the Finite Element Method for various fiber orientations of each layer (0°, 15°, 30°, 45°, 60°, 75°, and 90°) relative to the transverse axis. The results indicate that a 0° fiber orientation in both layers produced the maximum stress, potentially weakening the plate under tensile load, whereas a 90° orientation minimized stress and enhanced tensile strength. Increasing the second-layer angle while keeping the first layer fixed reduced stress, whereas decreasing the first-layer angle for a fixed second-layer angle increases stress. Maximum stress regions shifted from localized points to linear distributions, sometimes moving from uniform edge distributions to mid-edge concentrations. When both layers had identical angles, the stress magnitude increased, and the maximum stress shifted from the loaded edge to a corner, indicating stress concentration and a potential reduction in lifespan. The Artificial Neural Network demonstrated excellent predictive performance, achieving an optimal validation Mean Squared Error of 3.2266 × 10⁻⁴ at iteration 22, with a minimum overall Mean Squared Error of 6.5566 × 10⁻⁴ across all datasets. The correlation coefficients for the training, validation, test, and entire datasets were 0.99508, 0.98649, 0.99484, and 0.99485, respectively, indicating a strong agreement between the Mean Squared Error predictions and Finite Element Method-simulated values.
Effects of Grinding Penetration Depth and Abrasive Grain Spacing on Atomic Interactions and Material Removal Mechanisms in Silicon during Ultrasonic Vibration-Assisted Grinding: A Molecular Dynamics Study
(Nature Publishing Grou, 2026) Sawaran Singh, Narinderjit Singh; Hassan, Waqed H.; Alaloosi, Waleed; Younis, Watfaa Khayri; Haji, Banaz Shahab; Taner, Mahmut; Salahshour, Soheil; Sajadi, S. Mohammad
Grinding is an important finishing process for hard, brittle materials like silicon, where atomic-level finishing is critical for semiconductor and microelectronic applications. Ultrasonic vibration-assisted grinding has been shown to enhance grinding efficiency beyond conventional methods, but several of its atomic-level mechanisms remain incompletely understood. The interaction among the following was investigated in this study: mean abrasive grain spacing, grinding penetration depth, and abrasive grain physical properties. Atomic interactions and behaviors of the grinding process were modeled using molecular dynamics. An equilibration of 10 ns was first set up, during which extrinsic variables were manipulated to produce an equivalent environment, allowing the sample to evolve independently. This equilibration step was essential to achieve stabilization, since the potential and kinetic energies were −4.69 eV and 0.02 eV, respectively. It was observed that changing the grinding penetration depth from 10 Å to 16 Å significantly affected important atomic parameters: the number of detached atoms increased from 2231 to 2495, whereas the maximum stress rose from 10.26 to 12.27 GPa. This result was remarkable because it indicated strong stress localization and enhanced atomic bond breakage at deeper penetration depths, revealing the onset of severe atomic deformation. The highest force of the system increased from 606.67 to 725.05 GPa·nm². Increasing the mean abrasive grain spacing between abrasive grains from 31 to 45 Å resulted in a lower number of dissociative atoms (2231 → 2154) and a shallower penetration depth (10.75 → 10.29 Å). The maximum stress and, in turn, the force were found to decrease uniformly from 10.26 to 9.89 GPa and from 584.80 GPa·nm² to 560.80 GPa·nm², respectively.
An integrated BWM–THOR II–DEMATEL–QFD framework for scrap steel reverse logistics: linking strategy desirability with implementation feasibility in the Turkish automotive sector
(Pergamon Press, 2026) Şahin, Aybike Esra
Circular economy practices have elevated the role of reverse logistics in resource-intensive industries, where the recovery of high-value materials such as scrap steel is central to resource efficiency and environmental performance. This study develops an integrated multi-criteria framework addressing three questions typically treated in isolation: which reverse logistics strategy is most appropriate, which barriers shape its implementation, and which actions should be prioritised. The framework combines the Best-Worst Method (BWM) for criterion weighting, THOR II for ranking alternatives, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) for distinguishing driving from dependent barriers, and Quality Function Deployment (QFD) for translating the diagnosis into prioritised solutions. The empirical application draws on five senior practitioners in the Turkish automotive industry, supported by two academic consultants during criteria validation; the same panel contributed to all four quantitative stages. THOR II is implemented with criterion-specific indifference, preference, and discordance thresholds derived from the empirical dispersion of each criterion, departing from the uniform-threshold practice shown to yield non-robust rankings. Economic and regulatory criteria carry the highest priorities, and in-house operation emerges as the leading strategy across all dominance scenarios, with outsourcing and the digital lean model as complements and public-private partnership ranking last. The informal scrap economy, the absence of a clear regulatory framework, and gaps in technology, incentives, and operational knowledge are the most influential driving barriers; prioritised actions converge on strategic embedding, regulatory clarity, and digital monitoring. The contribution is the demonstration that strategy desirability in emerging manufacturing economies cannot be separated from implementation feasibility.