PubMed İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/397

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Now showing 1 - 7 of 7
  • Article
    Citation - WoS: 6
    Citation - Scopus: 7
    Sustainability Assessment of Denim Fabric Made of PET Fiber and Recycled Fiber From Postconsumer PET Bottles Using LCA and LCC Approach With the EDAS Method
    (Wiley, 2024-11-01) Fidan, Fatma Sener; Aydogan, Emel Kizilkaya; Uzal, Nigmet
    The textile industry is under pressure to adopt sustainable production methods because its contribution to global warming is expected to rise by 50% by 2030. One solution is to increase the use of recycled raw material. The use of recycled raw material must be considered holistically, including its environmental and economic impacts. This study examined eight scenarios for sustainable denim fabric made from recycled polyethylene terephthalate (PET) fiber, conventional PET fiber, and cotton fiber. The evaluation based on the distance from average solution (EDAS) multicriteria decision-making method was used to rank scenarios according to their environmental and economic impacts, which are assessed using life cycle assessment and life cycle costing. Allocation, a crucial part of evaluating the environmental impact of recycled products, was done using cut-off and waste value. Life cycle assessments reveal that recycled PET fiber has lower freshwater ecotoxicity and fewer eutrophication and acidification impacts. Cotton outperformed PET fibers in human toxicity. Only the cut-off method reduces potential global warming with recycled PET. These findings indicated that recycled raw-material life cycle assessment requires allocation. Life cycle cost analysis revealed that conventional PET is less economically damaging than cotton and recycled PET. The scenarios were ranked by environmental and economic impacts using EDAS. This ranking demonstrated that sustainable denim fabric production must consider both economic and environmental impacts. Integr Environ Assess Manag 2024;00:1-19. (c) 2024 The Author(s). Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
  • Article
    Citation - WoS: 29
    Citation - Scopus: 32
    Life Cycle Sustainability Assessment of a Light Rail Transit System: Integration of Environmental, Economic, and Social Impacts
    (Wiley, 2021-04-01) Gulcimen, Sedat; Aydogan, Emel K.; Uzal, Nigmet
    The transition toward sustainable urban transportation has gained importance in recent decades. However, urban transportation has not been addressed for all dimensions of sustainability. This study presents a life cycle sustainability assessment of a light rail transit system in Kayseri, Turkey, by integrating environmental, economic, and social aspects. The sustainability performance of the light rail transit system is evaluated using a cradle-to-grave approach to assess three aspects of sustainability. For the environmental evaluation, a life cycle assessment was applied using SimaPro 8.4.1 PhD version based on ISO 14040 and 14044. The method, which includes nine environmental impact categories, was employed to assess the environmental performance of the light rail transit system with a functional unit of 1 passenger-km. For the economic assessment, life cycle costing was utilized with the functional unit of USD for 1 passenger-km. A social life cycle assessment was applied to assess the social performance of the light rail transit system based on guidelines published by the United Nations Environment Programme in collaboration with the Society of Environmental Toxicology and Chemistry. For the determination of social impacts, 11 subcategories and 18 social indicators were selected. The results showed that the global warming potential and abiotic depletion potential of the light rail system per passenger-km were 2.4E - 02 kg CO2 eq. and 2.7E - 01 MJ, respectively, with a service life of 50 years. The total life cycle cost of the light rail system was calculated as 0.046 USD for 1 passenger-km. The results also revealed that the main contributor to the total life cycle cost was energy cost, with 92% (2.88E + 08 USD) of the total cost. In the social performance evaluation, it is found that the industry performs well for society, the local community, and workers but has a weaker social performance for the consumer due to a weak feedback mechanism. Integr Environ Assess Manag 2021;00:1-13. (c) 2021 SETAC
  • Article
    Citation - Scopus: 1
    Image Processing Methodology for Patient-Specific Instrument Design
    (Wiley, 2020-09-12) Mohammad Sadeghi, Majid; Kececi, Emin Faruk
    Background Patient-specific instrumentation (PSI) improves accuracy of surgical operations. PSI needs software for preoperative planning and instrument design. In this study, we explain the methodology of developing a software tool for PSI guide design and preoperative planning in reverse shoulder arthroplasty (RSA). Methods Approaches used to prepare input data, transform them into meaningful features and use of those features to create special guide geometries are explained by describing different algorithms and libraries. Results The developed software is tested on three different patients' data. Preoperative planning is performed and guides designed by software and the patients' bones are manufactured and tested for RSA. The method of building a software is presented to do the preoperative planning and designing specific guides for each patient are shown to be properly functional. Conclusions This study proves processes in the development of the PSI software and the design of a specific guide for RSA.
  • Article
    Citation - WoS: 13
    Citation - Scopus: 20
    IGPRED: Combination of Convolutional Neural and Graph Convolutional Networks for Protein Secondary Structure Prediction
    (Wiley, 2021-05-25) Gormez, Yasin; Sabzekar, Mostafa; Aydin, Zafer
    There is a close relationship between the tertiary structure and the function of a protein. One of the important steps to determine the tertiary structure is protein secondary structure prediction (PSSP). For this reason, predicting secondary structure with higher accuracy will give valuable information about the tertiary structure. Recently, deep learning techniques have obtained promising improvements in several machine learning applications including PSSP. In this article, a novel deep learning model, based on convolutional neural network and graph convolutional network is proposed. PSIBLAST PSSM, HHMAKE PSSM, physico-chemical properties of amino acids are combined with structural profiles to generate a rich feature set. Furthermore, the hyper-parameters of the proposed network are optimized using Bayesian optimization. The proposed model IGPRED obtained 89.19%, 86.34%, 87.87%, 85.76%, and 86.54% Q3 accuracies for CullPDB, EVAset, CASP10, CASP11, and CASP12 datasets, respectively.
  • Article
    Citation - WoS: 17
    Citation - Scopus: 21
    Finite Element Analysis of the Stress Distribution Associated With Different Implant Designs for Different Bone Densities
    (Wiley, 2022-06-06) Kurtulus, Ikbal Leblebicioglu; Kilic, Kerem; Bal, Burak; Kilavuz, Ahmet; Leblebicioğlu Kurtuluş, Ikbal
    Purpose The main objective of this study was to investigate the influence of implant design, bone type, and abutment angulation on stress distribution around dental implants. Materials and methods Two implant designs with different thread designs, but with the same length and brand were used. The three-dimensional geometry of the bone was simulated with four different bone types, for two different abutment angulations. A 30 degrees oblique load of 200 N was applied to the implant abutments. Maximum principal stress and minimum principal stresses were obtained for bone and Von misses stresses were obtained for dental implants. Results The distribution of the load was concentrated at the coronal portion of the bone and implants. The stress distributions to the D4 type bone were higher for implant models. Increased bone density and increased cortical bone thickness cause less stress on bone and implants. All implants showed a good distribution of forces for non-axial loads, with higher stresses concentrated at the crestal region of the bone-implant interface. In implant types using straight abutments there was a decrease in stress as the bone density decreased. The change in the abutment angle also caused an increase in stress. Conclusions The use of different implant threads and angled abutments affects the stress on the surrounding bone and implant. In addition, it was observed that a decrease in density in trabecular bone and a decrease in cortical bone thickness increased stress.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    ConVarT: Search Engine for Missense Variants Between Humans and Other Organisms
    (Wiley, 2022-11) Pir, Mustafa S.; Cevik, Sebiha; Kaplan, Oktay I.
    ConVarT (https://convart.org/) is a search engine for searching for conjugate variants between humans and other species. The search engine is based on matching conjugate variants called MatchVars between species. Matching equivalent variants requires correct alignment of orthologous proteins with the use of multiple sequence alignments (MSA). Indeed, the ConVarT pipeline has performed over a million MSAs and integrated variants and variant-specific annotations (pathogenicity, phenotypic variants; etc.) into the corresponding positions on MSAs. When a clinically relevant variant is discovered whose functional relevance is unknown, ConVarT offers clinician scientists the possibility to search for a MatchVar in other species and to look for functional data on that variant. Fortunately, ConVarT enables users to paste a protein sequence in FASTA format to search for human orthologous proteins. A pairwise sequence alignment (PSA) is then performed between the provided protein sequence and the human orthologous protein, allowing users to visualize human variants on the PSA. Here, we describe the step-by-step usage of ConVarT.
  • Article
    Citation - WoS: 15
    Citation - Scopus: 16
    Computational Fluid Dynamics (CFD) Analysis of Bioprinting
    (Wiley, 2024-05-02) Fareez, Umar Naseef Mohamed; Naqvi, Syed Ali Arsal; Mahmud, Makame; Temirel, Mikail
    Regenerative medicine has evolved with the rise of tissue engineering due to advancements in healthcare and technology. In recent years, bioprinting has been an upcoming approach to traditional tissue engineering practices, through the fabrication of functional tissue by its layer-by-layer deposition process. This overcomes challenges such as irregular cell distribution and limited cell density, and it can potentially address organ shortages, increasing transplant options. Bioprinting fully functional organs is a long stretch but the advancement is rapidly growing due to its precision and compatibility with complex geometries. Computational Fluid Dynamics (CFD), a carestone of computer-aided engineering, has been instrumental in assisting bioprinting research and development by cutting costs and saving time. CFD optimizes bioprinting by testing parameters such as shear stress, diffusivity, and cell viability, reducing repetitive experiments and aiding in material selection and bioprinter nozzle design. This review discusses the current application of CFD in bioprinting and its potential to enhance the technology that can contribute to the evolution of regenerative medicine. Using computational fluid dynamics (CFD) allows the optimization of bioprinting by analyzing flow velocity, shear stress, and pressure distribution, which enhances the printability, nozzle design, and bioink formulations for tissue construction. CFD enhances bioink deposition and cell viability while reducing the need for repetitive experiments, curbing cost and time. Moreover, it enhances vascularization designs to mimic physiological conditions, thereby facilitating tissue development. image