Browsing by Publisher "Multidisciplinary Digital Publishing Institute (MDPI)"
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Item Performance Optimization of a Thermoelectric Device by Using a Shear Thinning Nanofluid and Rotating Cylinder in a Cavity with Ventilation Ports(Multidisciplinary Digital Publishing Institute (MDPI), 2022) Ben Khedher N.; Selimefendigil F.; Kolsi L.; Aich W.; Said L.B.; Boukholda I.The combined effects of using a rotating cylinder and shear thinning nanofluid on the performance improvements of a thermoelectric generator (TEG)-installed cavity with multiple ventilation ports are numerically assessed. An optimization algorithm is used to find the best location, rotational speed and size of the cylinder to deliver the highest power generation of the TEG. The power generation features with varying Rew are different for the first nanofluid (NF1) when compared to the second one (NF2). The power rises with higher Rew when NF1 is used, and up to 49% enhancement is obtained. The output power variation between nanofluids NF1 and NF2 is the highest at Rew = 0, which is obtained as 68.5%. When the cylinder location is varied, the change in the output power becomes 61% when NF2 is used. The optimum case has 11.5%-and 161%-higher generated power when compared with the no-object case with NF1 and NF2. The computational effort of using the high-fidelity coupled system is reduced when optimization is considered. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.Item Do We Learn to Internalize Stigma from Our Parents? Comparison of Internalized Stigmatization in Adolescents Diagnosed with ADHD and Their Parents(Multidisciplinary Digital Publishing Institute (MDPI), 2022) Dikeç G.; Bilaç Ö.; Kardelen C.; Sapmaz Ş.Y.This study compared internalized stigmatization levels of adolescents diagnosed with attention deficit and hyperactivity disorder (ADHD) with those of their parents. The study’s data were collected from 107 adolescents diagnosed with ADHD and their parents between July 2020 and March 2021. The adolescents were followed up in the child and adolescent psychiatry outpatient clinic of a university hospital in western Turkey. The information forms for adolescents and parents, the Internalized Stigma of Mental Illness Scale—Adolescent Form (ISMI-AF) and the Parental Internalized Stigma of Mental Illness Scale (PISMI), were used to collect the data. There was no statistically significant difference between the total scores of internalized stigma and subscale mean scores of the adolescents and their parents (p > 0.05); only the subscale scores for stereotype endorsement were found to be significantly different (p < 0.05). PISMI scores affected ISMI-AF scores, which can be interpreted as parents’ perspectives and attitudes toward stigmatization affecting adolescents. For ADHD, whose frequency is increasing daily, intervention studies should be conducted to reduce adolescents’ and parents’ internalized stigma and to enhance the educational outcomes of adolescents. © 2022 by the authors.Item Correlation of Shear-Wave Elastography and Apparent Diffusion Coefficient Values in Breast Cancer and Their Relationship with the Prognostic Factors(Multidisciplinary Digital Publishing Institute (MDPI), 2022) Orguc S.; Açar Ç.R.Background: Diffusion-weighted imaging and elastography are widely accepted methods in the evaluation of breast masses, however, there is very limited data comparing the two methods. The apparent diffusion coefficient is a measure of the diffusion of water molecules obtained by diffusion-weighted imaging as a part of breast MRI. Breast elastography is an adjunct to conventional ultrasonography, which provides a noninvasive evaluation of the stiffness of the lesion. Theoretically, increased tissue density and stiffness are related to each other. The purpose of this study is to compare MRI ADC values of the breast masses with quantitative elastography based on ultrasound shear wave measurements and to investigate their possible relation with the prognostic factors and molecular subtypes. Methods: We retrospectively evaluated histopathologically proven 147 breast lesions. The molecular classification of malignant lesions was made according to the prognostic factors. Shear wave elastography was measured in kiloPascal (kPa) units which is a quantitative measure of tissue stiffness. DWI was obtained using a 1.5-T MRI system. Results: ADC values were strongly inversely correlated with elasticity (r = −0.662, p < 0.01) according to Pearson Correlation. In our study, the cut-off value of ADC was 1.00 × 10−3 cm2/s to achieve a sensitivity of 84.6% and specificity of 75.4%, and the cut-off value of elasticity was 105.5 kPa to achieve the sensitivity of 96.3% and specificity 76.9% to discriminate between the malignant and benign breast lesions. The status of prognostic factors was not correlated with the ADC values and elasticity. Conclusions: Elasticity and ADC values are correlated. Both cannot predict the status of prognostic factors and differentiate between molecular subtypes. © 2022 by the authors.Item Tumor Budding Should Be in Oral Cavity Cancer Reporting: A Retrospective Cohort Study Based on Tumor Microenvironment(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Tan A.; Taskin T.The utility of histological grading, which is useful in predicting prognosis in many tumors, is controversial for oral squamous cell carcinoma (OSCC). Therefore, new histopathological parameters should be added to histopathology reports of OSCCs. The study aimed to evaluate the parameters of worst invasion pattern (WPOI) and tumor budding in patients with OSCC, to compare them with other histopathological parameters, clinical data and overall survival, and to evaluate these results within the literature. A total of 73 OSCC cases with excisional biopsies were included in this study. WPOI, tumor budding, cell nest size, tumor-stroma ratio, stromal lymphocyte infiltration and stroma type, as well as classical histopathological parameters, were evaluated on hematoxylin-eosin-stained sections. Perineural invasion, lymph node metastases, advanced stage, presence of more than five buds and single cell invasion pattern in univariate survival analyses are characterized by a shortened overall survival time. While there was no significant difference between WPOI results and survival in the survival analysis, WPOI 5 was associated with more frequent lymph node metastasis and advanced stage at the time of diagnosis compared to WPOI 4. We concluded that tumor budding and single-cell invasion should be considered prognostic histopathologic parameters in OSCC. © 2023 by the authors.Item Evaluation of Sustainable Slope Stability with Anti-Slide Piles Using an Integrated AHP-VIKOR Methodology(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Tuskan Y.; Basari E.The sustainable design of major civil engineering projects, such as landslide management and slope stability, provides new opportunities for our society regarding the global energy crisis. These sources offer an effective solution to environmental issues and human energy needs. Slope stability, as a critical aspect of ensuring public safety and protection of infrastructure, often leads to disastrous consequences, highlighting the significance of designing effective and sustainable measures to mitigate the risks associated with landslides. Although anti-slide piles have become a widely used method to enhance slope stability, this paper investigates how the Analytic Hierarchy Process (AHP) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methodologies can be combined to achieve a sustainable design for anti-slide piles, simultaneously considering environmental, economic, safety, and technical factors. Through the integration of AHP-VIKOR and a case study, this paper demonstrates an effective approach to prioritizing sustainability in the design process of anti-slide pile systems, evaluating five main criteria—slope stability, sustainability, anti-slide pile capacity, cost, and ease of construction—and five sub-criteria. The proposed methodology is validated through a case study, wherein various design alternatives for anti-slide piles are evaluated based on sustainable requirements. The results indicate that the slope stability criterion has the highest weight of 0.404, followed by anti-slide pile capacity (0.283), sustainability (0.129), and cost (0.146) criteria. The ease of construction has the lowest weight of 0.038. As a result of the evaluations, it has been seen that, if the sustainability criteria are included in the analyses, the anti-slide pile alternatives are determined in the range of ξ = 0.1–0.3 and s/D = 2.0–3.0, compared to the scenarios where only the economic and technical criteria are satisfied. A pile geometry of diameter, D = 1.00 m, is the most sustainable value within the selected pile spacing intervals, meeting the criteria of slope safety, pile capacity, cost, and ease of construction. This hybrid approach allows for a more balanced consideration of a multi-criteria decision, while considering the sustainability aspects of anti-slide pile selection. © 2023 by the authors.Item Self-Perceived Clinical Competence of Nurses in Different Working Experiences: A Cross-Sectional Study(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Notarnicola I.; Ivziku D.; Tartaglini D.; Filomeno L.; Gualandi R.; Ricci S.; Lommi M.; Porcelli B.; Raffaele B.; Montini G.; Ferramosca F.M.P.; Di Maria E.; De Benedictis A.; Baysal E.; Latina R.; Rocco G.; Stievano A.Background: Competence is an essential concept for measuring nurses’ performance in terms of effectiveness and quality. To this end, our analysis highlighted the process of acquiring competencies, their self-evaluation into clinical practice, and how their proficiency levels change throughout the nursing career. In detail, this research explored nurses’ perceived level of competence and the factors that influence it in different contexts. Methods: A cross-sectional survey using a structured questionnaire to assess the nursing participants’ perception of their competencies in different clinical settings was accomplished. Results: A descriptive and bivariate analysis was performed on 431 nurses. Most respondents assessed their level of competence to be higher than their roles required. The Kruskal–Wallis test confirmed that nursing experience was a relevant factor influencing nursing competencies. Conclusions: We suggest improving the competence of practicing nurses, using experience as a measurable effect of their development. © 2023 by the authors.Item Advancing Shear Capacity Estimation in Rectangular RC Beams: A Cutting-Edge Artificial Intelligence Approach for Assessing the Contribution of FRP(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Ezami N.; Özyüksel Çiftçioğlu A.; Mirrashid M.; Naderpour H.Shear strength prediction in FRP-bonded reinforced concrete beams is crucial for ensuring structural integrity and safety. In this extensive investigation, advanced machine learning algorithms are harnessed to achieve precise shear strength predictions for rectangular RC beams reinforced with FRP sheets. The aim of this research is to enhance the accuracy and reliability of shear strength estimation, providing valuable insights for the design and assessment of FRP-strengthened structures. The primary contributions of this study lie in the meticulous comparison of various machine learning algorithms, including Xgboost, Gradient Boosting, Random Forest, AdaBoost, K-nearest neighbors, and ElasticNet. Through comprehensive evaluation based on predictive performance, the most suitable model for accurately estimating the shear strength of FRP-reinforced rectangular RC beams is identified. Notably, Xgboost emerges as the superior performer, boasting an impressive R2 value of 0.901. It outperforms other algorithms and demonstrates the lowest RMSE, MAE, and MAPE values, establishing itself as the most accurate and reliable predictor. Furthermore, a sensitivity analysis is conducted using artificial neural networks to assess the influence of input variables. This additional research facet sheds light on the critical factors shaping shear strength outcomes. The study, as a whole, represents a substantial contribution to advancing the development of accurate and dependable prediction models. The practical implications of this work are far-reaching, particularly for engineering applications in the realm of structures reinforced with FRP. The findings have the potential to transform the approach to the design and assessment of such structures, elevating safety, efficiency, and performance to new heights. © 2023 by the authors.Item Totally Goldie*-Supplemented Modules(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Güroğlu A.T.In this paper, we first consider the properties of the Goldie*-supplemented modules, and we study the properties of totally Goldie*-supplemented modules as a version of the Goldie*-supplemented modules. A module M is called Goldie*-supplemented module if, for every submodule U of M, there exists a supplement submodule S of M such that Uβ∗S. A module M is called a totally Goldie*-supplemented module if, for every submodule A of M, A is a Goldie*-supplemented module. We emphasize that if M is totally Goldie*-supplemented, then (Formula presented.) is totally Goldie*-supplemented for some small submodule U of M. In addition, (Formula presented.) is totally Goldie*-supplemented if A and B are totally Goldie*-supplemented. Furthermore, we mention the connection between totally Goldie*-supplemented, totally supplemented, and Goldie*-supplemented. © 2023 by the author.Item A Real-Time Nut-Type Classifier Application Using Transfer Learning(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Özçevik Y.Smart environments need artificial intelligence (AI) at the moment and will likely utilize AI in the foreseeable future. Shopping has recently been seen as an environment needing to be digitized, especially for payment processes of both packaged and unpackaged products. In particular, for unpackaged nuts, machine learning models are applied to newly collected dataset to identify the type. Furthermore, transfer learning (TL) has been identified as a promising method to diminish the time and effort for obtaining learning models for different classification problems. There are common TL architectures that can be used to transfer learned knowledge between different problem domains. In this study, TL architectures including ResNet, EfficientNet, Inception, and MobileNet were used to obtain a practical nut-type identifier application to satisfy the challenges of implementing a classifier for unpackaged products. In addition to the TL models, we trained a convolutional neural network (CNN) model on a dataset including 1250 images of 5 different nut types prepared from online-available and manually captured images. The models are evaluated according to a set of parameters including validation loss, validation accuracy, and F1-score. According to the evaluation results, TL models show a promising performance with 96% validation accuracy. © 2023 by the author.Item Developing an Advanced Software Requirements Classification Model Using BERT: An Empirical Evaluation Study on Newly Generated Turkish Data(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Yucalar F.Requirements Engineering (RE) is an important step in the whole software development lifecycle. The problem in RE is to determine the class of the software requirements as functional (FR) and non-functional (NFR). Proper and early identification of these requirements is vital for the entire development cycle. On the other hand, manual identification of these classes is a timewaster, and it needs to be automated. Methodically, machine learning (ML) approaches are applied to address this problem. In this study, twenty ML algorithms, such as Naïve Bayes, Rotation Forests, Convolutional Neural Networks, and transformers such as BERT, were used to predict FR and NFR. Any ML algorithm requires a dataset for training. For this goal, we generated a unique Turkish dataset having collected the requirements from real-world software projects with 4600 samples. The generated Turkish dataset was used to assess the performance of the three groups of ML algorithms in terms of F-score and related statistical metrics. In particular, out of 20 ML algorithms, BERTurk was found to be the most successful algorithm for discriminating FR and NFR in terms of a 95% F-score metric. From the FR and NFR identification problem point of view, transformer algorithms show significantly better performances. © 2023 by the author.Item In Vitro and In Silico Evaluations of the Antileishmanial Activities of New Benzimidazole-Triazole Derivatives(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Eser M.; Çavuş İ.Benzimidazole and triazole rings are important pharmacophores, known to exhibit various pharmacological activities in drug discovery. In this study, it was purposed to synthesize new benzimidazole-triazole derivatives and evaluate their antileishmanial activities. The targeted compounds (5a–5h) were obtained after five chemical reaction steps. The structures of the compounds were confirmed by spectral data. The possible in vitro antileishmanial activities of the synthesized compounds were evaluated against the Leishmania tropica strain. Further, molecular docking and dynamics were performed to identify the probable mechanism of activity of the test compounds. The findings revealed that compounds 5a, 5d, 5e, 5f, and 5h inhibited the growth of Leishmania tropica to various extents and had significant anti-leishmanial activities, even if some orders were higher than the reference drug Amphotericin B. On the other hand, compounds 5b, 5c, and 5g were found to be ineffective. Additionally, the results of in silico studies have presented the existence of some interactions between the compounds and the active site of sterol 14-alpha-demethylase, a biosynthetic enzyme that plays a critical role in the growth of the parasite. Therefore, it can be suggested that if the results obtained from this study are confirmed with in vivo findings, it may be possible to obtain some new anti-leishmanial drug candidates. © 2023 by the authors.Item Knowledge, Beliefs, and Behaviors of Turkish Parents about Childhood Vaccination(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Emlek Sert Z.; Topçu S.; Çelebioğlu A.Background and Objectives: Vaccination is critical to the prevention and control of infectious disease outbreaks and is also one of the most important public health successes. When it comes to childhood vaccinations, parents’ consent is very important. For this reason, childhood vaccination rates are directly related to the knowledge, beliefs, and behaviors of the parents. Therefore, this study aimed to evaluate the knowledge, beliefs, and behaviors of parents of children aged 0–5 regarding childhood vaccinations and how these beliefs affect their vaccination behaviors. Material and Methods: This descriptive, cross-sectional study was conducted on 302 parents from February to June 2020. Data were collected using a questionnaire form with 26 questions. Sociodemographic characteristics were reported as frequencies, means, and percentages. Multiple regression analysis was utilized to evaluate vaccination behaviors and affective factors. Results: About 87.1% of the parents know that vaccines protect their children from infectious diseases, and 76.8% know that vaccines can have side effects. Although 97.7% of the parents had their children fully vaccinated according to the Extended Immunization Program, 2.3% did not vaccinate their children. Moreover, 98% of the parents trust the information given by healthcare professionals about vaccination. The parents’ beliefs explain 53% (R2 = 0.53) of the parents’ child vaccination behavior. Conclusion: This study found that although the knowledge level of parents about vaccines is quite good, negative knowledge and beliefs that may affect vaccination also exist. Considered by parents as a reliable source of information, healthcare professionals should impart their knowledge, beliefs, and concerns regarding immunization. © 2023 by the authors.Item Recent Advances in Nanoencapsulated and Nano-Enhanced Phase-Change Materials for Thermal Energy Storage: A Review(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Khlissa F.; Mhadhbi M.; Aich W.; Hussein A.K.; Alhadri M.; Selimefendigil F.; Öztop H.F.; Kolsi L.Phase-change materials (PCMs) are becoming more widely acknowledged as essential elements in thermal energy storage, greatly aiding the pursuit of lower building energy consumption and the achievement of net-zero energy goals. PCMs are frequently constrained by their subpar heat conductivity, despite their expanding importance. This in-depth research includes a thorough categorization and close examination of PCM features. The most current developments in nanoencapsulated PCM (NEPCMs) techniques are also highlighted, along with recent developments in thermal energy storage technology. The assessment also emphasizes how diligently researchers have worked to advance the subject of PCMs, including the creation of devices with improved thermal performance using nano-enhanced PCMs (NEnPCMs). This review intends to highlight the progress made in improving the efficiency and efficacy of PCMs by providing a critical overview of these improvements. The paper concludes by discussing current challenges and proposing future directions for the continued advancement of PCMs and their diverse applications. © 2023 by the authors.Item Increasing the Personal Development of White-Collar Employees for Sustainable Employability(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Özcan B.M.; Ozcan S.E.; Geyikci U.B.; Gülova A.; Sancak F.M.This qualitative study evaluated a training intervention aimed at increasing the personal development curves of the ABC company’s white-collar employees and developing presentation preparation techniques. The participants prepared presentations using the 10/20/70 learning rule for the competencies they identified. After academicians and business managers evaluated the presentations, semi-structured one-on-one interviews were conducted to identify the intervention’s benefits and limitations. The eight participants, who were white-collar professionals from the ABC company, were identified using non-probabilistic purposive sampling and interviewed online for about 30 min using Microsoft Teams. The interviews were audio recorded. The Maxqda-2022 program was used to examine the interview data. The analysis showed that the participants had negative feelings about the performance process based on their personal development competencies, particularly regarding process management. They also mentioned having the opportunity to learn through experience and conducting interviews. The participants agreed that their organizations should increase their development awareness and conduct 360-degree evaluations. They also said that intensive practical training at universities was needed because they felt their undergraduate education had not changed their perspectives or prepared them for a career. © 2023 by the authors.Item Photovoltaic Thermal Management by Combined Utilization of Thermoelectric Generator and Power-Law-Nanofluid-Assisted Cooling Channel(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Selimefendigil F.; Okulu D.; Öztop H.F.In this study, two different cooling systems for the thermal management of a photovoltaic (PV) module were developed. A PV/thermoelectric generator (TEG) and PV/TEG-mini-channel cooling systems were considered; in the later system, water and water-based (Formula presented.) nanofluids were used in the cooling channel. The effective cooling of the PV module was achieved by using higher-loading nanoparticles in the base fluid, while the nanofluid exhibited a non-Newtonian behavior. The PV/TEG with a cooling channel system was numerically assessed with respect to various values of Reynolds numbers (between 5 and 250), inlet nanofluid temperatures (between 288.15 K and 303.15 K), and nanoparticle volume fractions in the base fluid (between 1% and 5%). Variations in average cell temperature, PV power, TEG power, and efficiencies were computed by varying the pertinent parameters of interest with Galerkin’s weighted residual finite element method. The most favorable case for cooling was obtained with TEG-cooling channel at (Formula presented.) = 5% and Re = 250. In this case, PV electrical power increased by about 8.1% and 49.2% compared to the PV/TEG and PV system without cooling, respectively. The TEG output power almost doubled when compared to the PV/TEG system for all channel models at Re = 250. The inlet temperature of the nanofluid has a profound impact on the overall efficiency and power increment of the PV module. The use of the PV/TEG-cooling channel with the lowest fluid inlet temperature (288.15 K) and nanofluid at the highest particle loading ((Formula presented.) = 5%) resulted in a PV efficiency increment of about 52% and 10% compared to the conventional PV system without cooling and the PV/TEG system. In this case, the TEG efficiency rises by about 51% in the PV/TEG nanofluid model compared to the PV/TEG model. © 2023 by the authors.Item Quantifying the Operational Benefits of Dry Port Integrated Cooperation in Port Clusters: A Microsimulation Study(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Yıldırım M.S.As marine cargo traffic continues to grow, ports are experiencing increasing problems with congestion. To address this issue without requiring significant capital investment, neighboring ports can share their capacity to meet the rising demand for cargo throughput. While there are many planning level studies on inter-port cooperation, there is a scarcity of operational-level studies, and there is currently no available dry port integrated cooperation scheme for port clusters that utilizes a microsimulation approach. This study aims to contribute to the existing literature by proposing a conceptual port integration scheme that includes a dry port for improved coordination between ports in clusters. The discrete event simulation (DES) approach was used to construct three representative microsimulation models with dry port integration considering vessel transfer policies and no-cooperation scenario. The outputs of the models were evaluated using performance metrics (vessel delays, storage capacities, and the number of serviced vessels) using t-test statistics. The results show that the cooperation scheme with the vessel transfer policy and the strategic management of vessel transfer can significantly reduce the vessel operation delay by over 39% for the no-cooperation scenario with an integrated dry port and this value is further improved to 62% if a simulation-based port selection module (PSM) is used for vessel transfer policy. Additionally, the mean number of containers of the average of two port storages decreased by 40% and further decreased by 69% with the PSM. In terms of decision-making performance for vessel transfer decisions with varying quay lengths, PSM was determined to be superior to the vessel transfer policy considering the number of vessels in port queues. The proposed conceptual port integration model and approach can assist decision-makers in evaluating the effectiveness of different cooperation schemes and vessel transfer policies for adjacent ports in port clusters. © 2023 by the author.Item The Effect of Cognitive Dissonance Theory and Brand Loyalty on Consumer Complaint Behaviors: A Cross-Cultural Study(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Yakın V.; Güven H.; David S.; Güven E.; Bărbuță-Mișu N.; Güven E.T.A.; Virlanuta F.O.Consumers tend to exhibit e-WOM behavior or retention behavior or communicate with official channels rather than the brand, which can damage the brand in cases where the channels through which customers are expected to reach the brand for their complaints are dysfunctional. This study aims to examine the relationship between cognitive dissonance and brand loyalty factors as well as their impact on consumer complaint behavior in terms of differences between Turkish and Romanian consumers. For this purpose, a simultaneous quantitative research study was conducted in these two countries, with a total of 790 participants surveyed. The findings showed that the consumers’ level of brand loyalty had a significant positive effect on the level of cognitive dissonance, which significantly impacted complaint behavior. On the other hand, it was concluded that brand loyalty did not significantly affect complaint behavior. The comparative analysis revealed that Romanian customers’ brand loyalty was higher than Turkish customers’, and the dimensions concerning cognitive dissonance and complaint behavior were higher among Turkish customers. © 2023 by the authors.Item Emerging and Re-Emerging Parasitic Infections of the Central Nervous System (CNS) in Europe(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Tunali V.; Korkmaz M.In a rapidly evolving global landscape characterized by increased international travel, migration, and ecological shifts, this study sheds light on the emergence of protozoal and helminthic infections targeting the central nervous system (CNS) within Europe. Despite being traditionally associated with tropical regions, these infections are progressively becoming more prevalent in non-endemic areas. By scrutinizing the inherent risks, potential outcomes, and attendant challenges, this study underscores the intricate interplay between diagnostic limitations, susceptibility of specific population subsets, and the profound influence of climate fluctuations. The contemporary interconnectedness of societies serves as a conduit for introducing and establishing these infections, warranting comprehensive assessment. This study emphasizes the pivotal role of heightened clinician vigilance, judicious public health interventions, and synergistic research collaborations to mitigate the potential consequences of these infections. Though rare, their profound impact on morbidity and mortality underscores the collective urgency required to safeguard the neurological well-being of the European populace. Through this multifaceted approach, Europe can effectively navigate the complex terrain posed with these emergent infections. © 2023 by the authors.Item Determination of Energy Savings via Fuel Consumption Estimation with Machine Learning Methods and Rule-Based Control Methods Developed for Experimental Data of Hybrid Electric Vehicles(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Arıkuşu Y.S.; Bayhan N.; Tiryaki H.In this study, a parallel hybrid electric vehicle produced within the scope of our project titled “Development of Fuel Efficiency Enhancing and Innovative Technologies for Internal Combustion Engine Vehicles” has been modeled. Firstly, a new rule-based control method is proposed to minimize fuel consumption and carbon emission values in driving cycles in the experimental model of the parallel hybrid electric vehicle produced within the scope of this project. The proposed control method ensures that the internal combustion engine (ICE) operates at the optimum point. In addition, the electric motor (EM) is activated more frequently at low speeds, and the electric motor can also work as a generator. Then, a new dataset was also created on a traffic-free racetrack with the proposed control method for fuel consumption estimation of a parallel hybrid electric vehicle using ECE-15 (Urban Driving Cycle), EUDC (Extra Urban Driving Cycle), and NEDC (New European Driving Cycle) driving cycles. The data set is dependent on 11 different input variables, which complicates the system. Afterward, the fuel estimation process is made with seven different machine learning methods (ML), and these methods are compared using the obtained data set. To avoid overfitting machine learning, two different test data sets were created. The Random Forest algorithm is the most suitable technique in terms of training and testing the fuel consumption model using correlation coefficient ((Formula presented.)), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) simulation appropriateness for both test datasets. Moreover, the random forest algorithm achieved an impressive accuracy of 97% and 90% for both test datasets, outperforming the other algorithms. Furthermore, the proposed method consumes 4.72 L of fuel per 100 km, while the gasoline-powered vehicle consumes 7 L of fuel per 100 km. The results show that the proposed method emits 4.69 kg less (Formula presented.) emissions. The effectiveness of the Random Forest Algorithm has been verified by both simulation results and real-world data. © 2023 by the authors.Item Evaluation of the Antecedent Saturation and Rainfall Conditions on the Slope Failure Mechanism Triggered by Rainfalls(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Durukan S.The stability analysis of rainfall-induced slope failures considers a number of factors including the characteristics of the rainfall, vegetation, geometry of the slope, unsaturated soil characteristics, infiltration capacity, and saturation degree variations. Amongst all these factors, this study aims to investigate the effects of the antecedent rainfall and saturation conditions. A numerical modeling study was conducted using finite difference code software on a representative slope geometry with two different soil types. Two scenarios were followed: The first involved the application of three different rainfall intensities for varying initial saturation levels between 40% and 60%, representing the antecedent saturation conditions. The second scenario involved modeling successive rainfalls for a typical initial saturation degree of 50%. The impact of antecedent rainfall was assessed by determining the time required for failure during the application of a main extreme rainfall after a preceding rainfall of varying durations. Consequently, a zone of susceptible time for failure was suggested for use as a criterion in hazard management, allowing for the tracking of rainfall and its duration through the proposed chart for potential failures. Once the anticipated critical rainfall intensities have been determined through a meteorological analysis, a risk assessment for a specific slope can be conducted using the proposed practical procedure. Accordingly, a control mechanism may be established to detect the potential for a natural hazard. Furthermore, the proposed procedure was applied to a case study, whose modeling insights were in harmony with the real conditions of the slope failure. Thus, this demonstrated the significance of the antecedent conditions in modeling landslides triggered by rainfalls. © 2024 by the author.