Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14517/19

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A Multi-Layer Neural Network Approach for Solving Fractional Heat Equations
(Toronto Metropolitan University, 2025) Ali, Amina Hassan; Senu, Norazak; Ahmadian, Ali
In this study, a new multi-layer neural network (MLNN) approach designed to solve fractional heat equations (FHEs) is introduced. To handle the fractional derivative, the Laplace transform for approximation was applied. The results of our approach with those obtained using the finite difference method(FDM) are compared. The findings highlight the flexibility and computational efficiency of the proposed approach, making it a promising technique for solving FHEs. © 2025 Elsevier B.V., All rights reserved.
Search for Medium Effects Using Jet Axis Decorrelation in Inclusive Jets from PbPb Collisions at = 5.02 TeV
(Springer Science and Business Media Deutschland GmbH, 2025) Tchekhovski, V. A.; Hayrapetyan, Aram A.; Makarenko, V. V.; Tumasyan, A. R.; Adam, Wolfgang; Andrejkovic, J. W.; Damanakis, Konstantinos
The jet axis decorrelation in inclusive jets is studied using lead-lead (PbPb) collisions at a center-of-mass energy per nucleon pair of 5.02 TeV. The jet axis decorrelation is defined as the angular difference between two definitions of the jet axis. It is obtained by applying two recombination schemes on all the constituents of a given jet reconstructed by the anti-kT sequential algorithm with a distance parameter of R = 0.4. The data set, corresponding to an integrated luminosity of 0.66 nb−1, was collected in 2018 with the CMS detector at the CERN LHC. The jet axis decorrelations are examined across collision centrality selections and intervals of jet transverse momentum. A centrality dependent evolution of the measured distributions is observed, with a progressive narrowing seen in more central events. This narrowing could result from medium-induced modification of the internal jet structure or reflect color charge effects in energy loss. This new measurement probes jet substructure in previously unexplored kinematic domains and show great promise for providing new insights on the color charge dependence of energy loss to jet-quenching models. © 2025 Elsevier B.V., All rights reserved.
Search for Excited Tau Leptons in the ττγ Final State in Proton-Proton Collisions at = 13 TeV
(Springer Science and Business Media Deutschland GmbH, 2025) Hayrapetyan, Aram A.; Tumasyan, A. R.; Adam, Wolfgang; Andrejkovic, J. W.; Benato, Lisa; Bergauer, Thomas; Hussain, P. S.
Results are presented for a test of the compositeness of the heaviest charged lepton, τ, using data collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 13 TeV at the CERN LHC. The data were collected in 2016–2018 and correspond to an integrated luminosity of 138 fb−1. This analysis searches for tau lepton pair production in which one of the tau leptons is produced in an excited state and decays to a ground state tau lepton and a photon. The event selection consists of two isolated tau lepton decay candidates and a high-energy photon. The mass of the excited tau lepton is reconstructed using the missing transverse momentum in the event, assuming the momentum of the neutrinos from each tau lepton decay are aligned with the visible decay products. No excess of events above the standard model background prediction is observed. This null result is used to set lower bounds on the excited tau lepton mass. For a compositeness scale Λ equal to the excited tau lepton mass, excited tau leptons with masses below 4700 GeV are excluded at 95% confidence level; for Λ = 10 TeV this exclusion is set at 2800 GeV. This is the first experimental result covering this production and decay process in the excited tau mass range above 175 GeV. © 2025 Elsevier B.V., All rights reserved.
Search for Bosons of an Extended Higgs Sector in B Quark Final States in Proton-Proton Collisions at s = 13 TeV
(Springer Science and Business Media Deutschland GmbH, 2025) Tchekhovski, V. A.; Hayrapetyan, Aram A.; Makarenko, V. V.; Tumasyan, A. R.; Adam, Wolfgang; Andrejkovic, J. W.; Damanakis, Konstantinos
A search for beyond-the-standard-model neutral Higgs bosons decaying to a pair of bottom quarks, and produced in association with at least one additional bottom quark, is performed with the CMS detector. The data were recorded in proton-proton collisions at a centre-of-mass energy of 13 TeV at the CERN LHC and correspond to an integrated luminosity of 36.7–126.9 fb−1, depending on the probed mass range. No signal above the standard model background expectation is observed. Upper limits on the production cross section times branching fraction are set for Higgs bosons in the mass range of 125–1800 GeV. The results are interpreted in benchmark scenarios of the minimal supersymmetric standard model, as well as suitable classes of two-Higgs-doublet models. © 2025 Elsevier B.V., All rights reserved.
Integration of Artificial Intelligence Tools into Interior Architecture Education: A Study on Textual and Visual Representations
(Centro de investigacion de la Facultad de Arquitectura y Urbanismo, Universidad de Cuenca, 2025) Deval, Özge; Öztürk Kösenciĝ, Kamile; Acirli, Zeynep
Despite numerous Artificial Intelligence (AI) applications in the field, there is currently a lack of empirical evidence supporting their integration into design education, as well as limitations due to the novelty of these applications. Therefore, this study proposes a workflow integrating AI-assisted ideation and visualization into interior architecture education. An empirical study was conducted with six interior architecture students. The design process has been researched in addition to capturing the functional limitations and difficulties encountered by students who experienced the suggested educational framework. The findings were analyzed using descriptive analysis, a qualitative research method. Findings revealed that AI tools can effectively support the early design phase with the recommended workflow. However, participants often struggled to apply it critically, relying heavily on AI suggestions. This study provides a novel perspective by elucidating the potential benefits, challenges and impacts of AI applications in interior architecture education. © 2025 Elsevier B.V., All rights reserved.
Parametric Dynamic Instability of a Nonlocal Axially Moving Nano-Beam with Harmonic Length Under Thermo-Mechanical Forces
(Elsevier B.V., 2025) Ali, Ali B.M.; Al-Nussairi, Ahmed Kateb Jumaah; Sawaran Singh, Narinderjit Singh; Naser, Ghazi Faisal; Salahshour, Soheil; Sajadi, S. Mohammad; Sahramaneshi, Hani
This paper investigates the dynamic instability behavior of an axially moving nano-beam with time-varying length, placed in a thermal environment and resting on a viscoelastic Pasternak-type foundation while subjected to axial loading. The governing equations of motion are formulated using the Euler–Bernoulli beam theory, incorporating nonlocal elasticity effects, and derived via Hamilton's principle. Floquet theory is employed to identify regions of parametric instability in the amplitude–frequency domain of the beam's longitudinal oscillations. A comprehensive parametric study is conducted to evaluate the influence of various physical factors, including geometric dimensions, axial velocity, nonlocal effects, thermal variations, axial forces, and viscoelastic foundation properties. The results demonstrate that the dynamic stability of the nano-beam is highly sensitive to these parameters. Notably, increasing the length of the nano-beam and the amplitude of longitudinal oscillations makes the system more prone to instability, whereas greater beam thickness and foundation stiffness enhance system stability. Thermal loads and compressive axial forces tend to destabilize the structure, while tensile loading and viscoelastic damping promote stability. The findings provide fundamental insights into the design of nano-scale moving beam systems under coupled thermal and mechanical fields and offer design guidelines for achieving dynamic robustness in advanced nanoelectromechanical systems (NEMS). © 2025 Elsevier B.V., All rights reserved.
Reweighting Simulated Events Using Machine-Learning Techniques in the CMS Experiment
(Springer Nature, 2025) Hayrapetyan, Aram A.; Tumasyan, A. R.; Adam, Wolfgang; Andrejkovic, J. W.; Benato, Lisa; Bergauer, Thomas; Hussain, P. S.
Data analyses in particle physics rely on an accurate simulation of particle collisions and a detailed simulation of detector effects to extract physics knowledge from the recorded data. Event generators together with a geant-based simulation of the detectors are used to produce large samples of simulated events for analysis by the LHC experiments. These simulations come at a high computational cost, where the detector simulation and reconstruction algorithms have the largest CPU demands. This article describes how machine-learning (ML) techniques are used to reweight simulated samples obtained with a given set of parameters to samples with different parameters or samples obtained from entirely different simulation programs. The ML reweighting method avoids the need for simulating the detector response multiple times by incorporating the relevant information in a single sample through event weights. Results are presented for reweighting to model variations and higher-order calculations in simulated top quark pair production at the LHC. This ML-based reweighting is an important element of the future computing model of the CMS experiment and will facilitate precision measurements at the High-Luminosity LHC. © 2025 Elsevier B.V., All rights reserved.
A Review of Impinging Jet Ventilation for Indoor Environment Control
(Elsevier B.V., 2025) Ameen, Arman; Rashid, Farhan Lafta; Al-Obaidi, Mudhar A.; Bouabidi, Abdallah; Agyekum, Ephraim Bonah; Chibani, Atef; Kezzar, Mohamed
Impinging Jet Ventilation (IJV) has emerged as a promising strategy for indoor environmental control, offering an alternative to conventional such as Mixing Ventilation (MV) systems. This review critically examines the performance of IJV in terms of thermal comfort, indoor air quality (IAQ), energy efficiency, and design flexibility, with a broader focus on the system implementation and a particular focus on office environments under moderate heating and cooling loads. The focus of the review is to compare the IJV system with the MV system. In comparison to MV, IJV delivers conditioned air to the occupied zone more effectively by providing stratified, low-mixing airflow and requiring a lower airflow rate to maintain acceptable thermal comfort conditions. This results in improved thermal comfort, reduced energy usage, and enhanced pollutant removal. The system also facilitates thermal stratification and supports higher supply air temperature differentials, allowing for increased energy savings without compromising comfort. The review explores key performance metrics such as Predicted Mean Vote (PMV), Predicted Percentage of Dissatisfied (PPD), draught rate, and ventilation effectiveness, highlighting the conditions under which IJV outperforms MV. Additionally, challenges such as sensitivity to diffuser configuration, nozzle placement, and return vent positioning are addressed. The paper also evaluates recent advancements, including the integration of Internet of Things (IoT) technologies, machine learning, and hybrid systems combining IJV with passive or personalized ventilation. Despite its advantages, IJV remains underutilized due to design complexity and lack of standardizations. To enable broader adoption, future research should focus on simplified modelling tools, performance-based design standards, and scalable applications for various building types. Overall, IJV represents a viable, energy-efficient solution for modern ventilation design, particularly in environments requiring high indoor air quality and localized comfort control. © 2025 Elsevier B.V., All rights reserved.
Measurement of the Inclusive Cross Sections for W and Z Boson Production in Proton-Proton Collisions at s = 5.02 and 13 TeV
(Springer Science and Business Media Deutschland GmbH, 2025) Hayrapetyan, Aram A.; Tumasyan, A. R.; Adam, Wolfgang; Andrejkovic, J. W.; Bergauer, Thomas; Chatterjee, Suman; Jeitler, Manfred A.
Measurements of fiducial and total inclusive cross sections for W and Z boson production are presented in proton-proton collisions at s = 5.02 and 13 TeV. Electron and muon decay modes (ℓ = e or μ) are studied in the data collected with the CMS detector in 2017, in dedicated runs with reduced instantaneous luminosity. The data sets correspond to integrated luminosities of 298 ± 6 pb−1 at 5.02 TeV and 206 ± 5 pb−1 at 13 TeV. Measured values of the products of the total inclusive cross sections and the branching fractions at 5.02 TeV are σ(pp → W + X)B(W → ℓν) = 7300 ± 10 (stat) ± 60 (syst) ± 140 (lumi) pb, and σ(pp → Z+X)B(Z → ℓ+ℓ−) = 669 ± 2 (stat) ± 6 (syst) ± 13 (lumi) pb for the dilepton invariant mass in the range of 60–120 GeV. The corresponding results at 13 TeV are 20480 ± 10 (stat) ± 170 (syst) ± 470 (lumi) pb and 1952 ± 4 (stat) ± 18 (syst) ± 45 (lumi) pb. The measured values agree with cross section calculations at next-to-next-to-leading-order in perturbative quantum chromodynamics. Fiducial and total inclusive cross sections, ratios of cross sections of W+ and W− production as well as inclusive W and Z boson production, and ratios of these measurements at 5.02 and 13 TeV are reported. © 2025 Elsevier B.V., All rights reserved.
Measurement of the Inclusive tt¯ Cross Section in Final States with at Least One Lepton and Additional Jets with 302 pb−1 of pp Collisions at s = 5.02 TeV
(Springer Science and Business Media Deutschland GmbH, 2025) Hayrapetyan, Aram A.; Tumasyan, A. R.; Adam, Wolfgang; Andrejkovic, J. W.; Bergauer, Thomas; Chatterjee, Suman; Jeitler, Manfred A.
A measurement of the top quark pair (tt¯) production cross section in proton-proton collisions at a centre-of-mass energy of 5.02 TeV is presented. The data were collected at the LHC in autumn 2017, in dedicated runs with low-energy and low-intensity conditions with respect to the default configuration, and correspond to an integrated luminosity of 302 pb−1. The measurement is performed using events with one electron or muon, and multiple jets, at least one of them being identified as originating from a b quark (b tagged). Events are classified based on the number of all reconstructed jets and of b-tagged jets. Multivariate analysis techniques are used to enhance the separation between the signal and backgrounds. The measured cross section is 62.5±1.6stat−2.5+2.6syst±1.2lumi pb. A combination with the result in the dilepton channel based on the same data set yields a value of 62.3 ± 1.5 (stat) ± 2.4 (syst) ± 1.2 (lumi) pb, to be compared with the standard model prediction of 69.5−3.7+3.5 pb at next-to-next-to-leading order in perturbative quantum chromodynamics. © 2025 Elsevier B.V., All rights reserved.
Recent Innovations and Developments in MOF-Based Aptasensors
(Elsevier Inc., 2025) Khosravi, Arezoo; Zarepour, Atefeh; Iravani, Siavash; Zarrabi, Ali
Metal-organic framework (MOF)-based aptasensors represent a cutting-edge technology with remarkable potential for biosensing applications. These sensors combine the distinctive characteristics of MOFs with high specificity of aptamers, enabling precise and sensitive detection of target analytes in various fields. In this context, there are different points that should be concerned including achieving efficient immobilization of aptamers on MOF surfaces while maintaining their bioactivity, enhancing MOF stability under physiological conditions, and optimizing sensor regeneration and reusability. Moreover, the synthesis, scalability, functionalization, biocompatibility, and cost considerations pose significant hurdles that require interdisciplinary collaboration and innovative solutions. These types of sensors could be used for the development of portable and miniaturized sensor platforms for point-of-care diagnostics, and design of smart and responsive sensing systems for personalized medicine, precision agriculture, and wearable health monitoring. By exploring the unique properties and functionalities of MOFs and aptamers, this review highlights the potential of MOF-based aptasensors in enabling precise and selective recognition of target analytes for various applications such as environmental monitoring, food safety, biomedical diagnostics, etc. Additionally, by outlining future perspectives such as nanomaterial integration, miniaturization, and personalized sensing solutions, we aim to inspire further research and advancements in the field. © 2025 Elsevier B.V., All rights reserved.
The Role of Nanotechnology and Artificial Intelligence in Optimizing Thermal Energy Systems
(Elsevier Ltd, 2025) Mohammed, Hayder I.; Rashid, Farhan Lafta; Togun, Hussein; Agyekum, Ephraim Bonah; Ameen, Arman; Hammoodi, Karrar A.; Abbas, Walaa Nasser
The growing demand for clean energy and the limitations of conventional thermal systems necessitates the integration of advanced technologies to enhance efficiency, adaptability, and sustainability. This review critically examines recent advancements in the application of nanotechnology and artificial intelligence for optimizing thermal energy systems, including solar collectors, heat exchangers, and latent heat storage units. Nanotechnology (particularly the use of nano-enhanced phase change materials and nanofluids such as Al₂O₃ and CuO) has shown to improve thermal conductivity by up to 28.8 %, accelerating energy absorption and storage rates. Concurrently, artificial intelligence algorithms, especially artificial neural networks and particle swarm optimization, enable predictive modelling, real-time system control, and fault detection, with some models achieving prediction accuracies above 97 % under complex operational conditions. The review emphasizes the synergistic potential of combining these technologies to create intelligent, self-regulating thermal energy systems. However, the paper also identifies critical challenges including computational overhead, cost of nanoparticle synthesis, lack of reproducibility in artificial intelligence implementations, and insufficient validation under extreme scenarios. Commercial deployment case studies (such as artificial intelligence-driven phase change material-based heating, ventilation, and air conditioning systems in smart buildings) are discussed to illustrate practical viability, reporting energy savings of up to 28 % with return-on-investment periods under three years. The paper concludes by proposing integrated research directions that combine multiscale material innovation with robust artificial intelligence training on dynamic datasets. This dual approach is essential to developing scalable, cost-effective, and resilient thermal energy systems capable of supporting global energy transitions. © 2025 Elsevier B.V., All rights reserved.
Respiratory Parameter Estimation Using Pharyngeal Phonetics and Machine Learning: Breaking Free from Spirometry
(Elsevier Ltd, 2025) Moshayedi, Ata Jahangir; Aghda, Abolfazl Moradian; Eftekhari, S. Ali; Emadi Andani, Mehran; Salahshour, Soheil
The capacity to screen for respiratory diseases is vital for clinical diagnostics. Forced Expiratory Volume in 1 relevant second and Forced Vital Capacity are the two most common parameters or measures of respiratory health. Although respiratory health may be assessed using spirometry or other traditional forms of diagnostics, spirometry has variances in device availability, patient compliance during testing, and complexity of the testing procedure. This study found a novel, non-invasive means of estimating pulmonary function based on the voiced pharyngeal sound of “He” using analysis of the voiced sound. The study explored a model for estimating Forced Expiratory Volume in 1 s and Forced Vital Capacity values based on the outputs from traditional spirometry and features extracted from voice signals. There were a total of 21 features that were extracted from the voiced segments of the pharyngeal sound. All machine learning models of Forced Expiratory Volume in 1 s and Forced Vital Capacity used three machine learning algorithms. Data was collected from 18 male participants, aged 33–49 years old, from June 2022 to August 2022, which resulted in 56 recordings. Among the models that were evaluated in comparison to the linear, neural network, and quadratic models, the quadratic model performed the worst, while the neural network performed the best. The neural network model that used three features estimated Forced Expiratory Volume in 1 s with a mean error of 0.24 % while the two-feature neural network model estimated Forced Vital Capacity with a mean error of 0.58 %. © 2025 Elsevier B.V., All rights reserved.
The Method of Φ-Laplace Adomian Decomposition for Φ-Caputo Fractional Bloch Equations
(Institute of Physics, 2025) Shahrezaee, M.; Arabameri, Maryam; Ahmadian, Ali
This article studies the Bloch equations (BEs), which form a system of macroscopic equations used for the simulation of nuclear magnetization as a function of time, when the relaxation times T1 and T2 are given. These equations have been applied to describe nuclear magnetic resonance (NMR), electron spin resonance (ESR), and magnetic resonance imaging (MRI). In this work, we present analytic solutions to the fractional Bloch equations (FBEs). The fractional derivatives in the Bloch equations under consideration are in the sense of Φ-Caputo; we use the Φ-Laplace Adomian decomposition procedure (Φ-LADP) to solve the FBEs. This procedure combines both the Adomian decomposition and Φ-Laplace transform methods. To explain the analytical solutions of the system of Φ-Caputo fractional Bloch equations (Φ-CFBEs) of the order η with known initial conditions, we apply the two-dimensional and three-dimensional phase portraits. We compare these solutions by considering diverse functions in place of Φ(t) and values of 0 < η ≤ 1. Finally, to show the usefulness of our proposed method, we discuss the advantages of the new method compared to the existing methods for solving Caputo FBEs. © 2025 Elsevier B.V., All rights reserved.
An Investigation into the Effects of Various Phase Change Materials on Industrial Electronic Systems' Cooling Rates Through Experimentation Based on a Specific Dimensionless Number
(Elsevier Ltd, 2025)
The development of electronic equipment depends on the performance of their processors, which themselves require operating at low temperatures. So, solutions that can keep their temperatures low are significant for the advancement of this valuable industry. This study attempts to find an effective solution to this problem in a practical case, which is the ASUS GT 730 silent graphics card. The working condition of this processor's heatsink is simulated by a heat source with 1.7- and 2.1-W heat flow rates. To cool down the system, a new experimental setup is proposed, in which the heatsink is placed inside an aluminum box where water flows through a copper pipe. In addition, two phase change materials (PCM), including Lauric Acid and Paraffin wax, with different volume percentages, are separately injected into the box to examine the influence of the properties of these materials on energy storage. Hence, 18 modes are obtained based on heat flux, PCM type, and their volume percentages. To compare the effectiveness, a dimensionless number is introduced as a special measure based on the time duration recorded for each mode, named dimensionless melting time efficiency (DMTE). This number, which adapts to the physics of the process, is defined as the ratio of the total heat input to the total heat capacity of PCM (sensible and latent). This new setup, together with the definition of the dimensionless number, provides an appropriate tool for achieving the best arrangement selection for higher thermal energy absorption. The results show that the presence of phase change materials, regardless of their type, will increase the efficiency of the system. Furthermore, using the maximum volume percentage of the phase change material will maximize the cooling efficiency of the system, where DMTE can be reduced by around 64 % for both PCMS and both input heat flow rates from 25 % volume percentage to full. Also, it is concluded that the choice of Lauric acid as phase material change for this case can enhance the performance of the system, where DMTE of Lauric acid decreases by 6.25 % for an input heat flow rate of 1.7 W and 9.68 % for 2.1 W than paraffin wax when the volume percentage of PCMs is maximum. © 2025 Elsevier B.V., All rights reserved.
Artificial Intelligence in Human-Centric Resilience, Sustainable Systems
(Springer Science and Business Media Deutschland GmbH, 2025) Özok, Ahmet Fahri
Human-Centric Artificial Intelligence (HCAI) is a field of scientific study that concentrates on creating systems and finding solutions. Basically, HCAI is related with abstractions, theories, paradigms, Cognitive Ergonomics and Ethical Concepts. Depending on different factors in every country, HCAI can be used in different levels. The deployment of HCAI gives us the opportunity to consider the social aspects of the environment and consequently to comprehend the interaction between human and all other parameters. Cognitive ergonomies enriches the field of Human-AI collaboration by establishing a rather comprehensive framework. In Human-Centered Man-Machine System (MMS) Design it is not enough the emphasize optimizing the common area between individual operators and their immediate physical and psycho-social environment. © 2025 Elsevier B.V., All rights reserved.
Dual Three-Phase Sparse Inverter: Topology Analysis, PWM Scheme, and Common Mode Voltage Elimination
(Institute of Electrical and Electronics Engineers Inc., 2025) Aghaei, Hadi; Babaei, Ebrahim; Sharifian, Mohammad Bagher Bannae; Iqbal, Atif
Dual three-phase drives offer significant advantages for medium and high-power applications, including reduced current ratings for power switches, lower torque ripple, and enhanced fault tolerance compared to conventional three-phase drives. However, traditional three-level inverters used to drive these motors often escalate system costs due to their large number of power switches. This paper introduces a dual three-phase sparse inverter designed to address these limitations. The proposed inverter utilizes only 16 power switches, a substantial reduction compared to conventional three-level inverters. This paper also propose a carrier-based Pulse Width Modulation (PWM) scheme that uniquely imposes no computational burden on the microcontroller. This PWM strategy incorporates a 180-degree phase shift between carriers of two three-phase systems, effectively eliminating common-mode voltage (CMV) in the topology. A comprehensive comparative study was conducted, assessing the proposed inverter against both two-level and conventional three-level inverters based on Total Harmonic Distortion (THD) and efficiency. To validate its performance, experimental results are provided for the proposed dual three-phase inverter driving a 746 W induction motor using a constant volt/Hz open-loop control method. © 2025 Elsevier B.V., All rights reserved.
Energy-Food Commodity Price Movement and Equation in Kyoto (2006) Perspectiv: Factor Analysis and Nonlinear Framework
(Springer Science and Business Media Deutschland GmbH, 2025) Pala, Aynur; Bouchafaa, Bahia
Energy and food are two major commodities. From a macro point of view, the movement and the relationship between commodity duos’ prices are highly concerning researchers, policymakers, and economists. This paper aims to investigate the link between energy and food price using a nonlinear framework for the period of 1991–2020. For this purpose, we calculated proxy factor index variables instead of each commodity duo by a factor analysis method using all contents of international commodity price indexe: FAO Food Price Index and IMF Commodity Energy Price Index. We applied Enders and Granger (J Bus Econ Stat 16:304–311, 1998) MTAR and KSS (2003) nonlinear unit root tests, KSS (2006) nonlinear cointegration test, and Diks and Panchenko (J Econ Dyn Control 30:1647–1669, 2006) nonlinear causality test. The results of nonlinear causality test indicated that there is a bidirectional relationship from food to energy price in the full sample. The Kyoto Protocol (2006), the most important treatment for decreasing carbon emission, caused to increase nonfood use of agricultural production, and this changed the relationship between energy and food prices. In the Kyoto (2006) break perspective, the results show that there is no nonlinear causality relationship between energy and food price in the pre-Kyoto (2006) subsample. But in post-2006 subsample, there is a nonlinear unidirectional causal relationship running from energy to food price. The causal effect is fluctuant for energy and food price nonlinear causality, which requires us to identify different causality fields for solving a specific problem. © 2025 Elsevier B.V., All rights reserved.
Outcomes of Tracheostomy in a Pediatric Intensive Care Unit: A Single-Center Experience
(Logos Medical Publishing, 2025) Kiliç, Sinan; Başak Kılıç, Ayten
Objectives: This study aims to evaluate the indications and complications of tracheostomy procedures performed in the pediatric intensive care unit (PICU) of a private healthcare institution. Patients and methods: Twenty-one pediatric patients (13 males, 8 females; mean age: 6.7±4.4 years; range, 3 months to 18 years) who underwent surgical tracheostomy between October 1, 2018, and June 1, 2023, were retrospectively analyzed. Results: The mean duration of tracheostomy was 38±16.5 days (range, 9 to 75 days). The most common indication for tracheostomy was prolonged mechanical ventilation due to neuromuscular conditions (cerebral palsy-associated pneumonia) in 17 (80.9%) patients, followed by upper airway obstruction in three (14%) patients. One (4.8%) patient underwent tracheostomy due to coronavirus disease 2019 (COVID-19) pneumonia. Eighteen (85.7%) patients were discharged, while three (14.3%) patients died during intensive care follow-up. Conclusion: Tracheostomy is a surgical procedure that can be safely performed in PICUs, particularly in cases requiring prolonged mechanical ventilation. The timing of tracheostomy should be individually assessed based on the clinical condition of the patient by the pediatric intensive care specialist. © 2025 Elsevier B.V., All rights reserved.
Natural Convection in Square Cavities with Mono and Hybrid Nano-Fluids: A Comprehensive Review
(Springer Science and Business Media B.V., 2025) Rashid, Farhan Lafta; Al-Obaidi, Mudhar A.; Alkhekany, Zainab Abdul Karim; Ahmad, Shabbir; Chibani, Atef; Agyekum, Ephraim Bonah; Junjua, Moin Ud Din
This review evaluates the effects of natural convection in square cavities using both mono-and hybrid Nano-fluids, focusing on the thermal management limitations of conventional fluids. The review highlights that there is a need for improved thermal solutions in engineering since regular fluids fail under low Rayleigh number conditions. Particularly, it shows that nano-fluids can increase significantly the rate of heat transfer with the Nusselt (Nu) number increasing as high as 60% compared to pure fluids, depending on nano-particle concentration, particle size, and material properties. For instance, the introduction of 4% Al2O3 nano-particles into a water-based solution can increase the average Nusselt number from 7.5 to around 12.0 under corresponding conditions of heating. Moreover, hybrid nano-fluids possess excellent opportunities as efficient heat transfer promoters with over 30% improvement in efficiency rates. This kind of assessment indicates the revolutionary impact of nano-fluids on thermal applications, but more work is needed to explore their behavior when considering various ranges of temperatures and flow rates in order to develop trustworthy predictive models. © 2025 Elsevier B.V., All rights reserved.

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