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Consistency Problems of Conformal Killing Gravity
No full textTekin, Bayram/0000-0002-0792-9010We show that gravity field equations based on a tensor with rank greater than 2 have consistency problems in the sense that integration constants in the solutions, such as the parameter m in the Schwarzschild metric, do not allow for an interpretation in terms of conserved quantities in the theory. The recently introduced conformal Killing gravity, an interesting extension of general relativity that inherits all the solutions of the latter, and defined with a rank-3 tensor field equation that does not arise from a diffeomorphism-invariant action, is plagued with this problem. In this theory, it is not clear at all how one can define the energy and angular momentum for black hole solutions, or define the analogs of the formulas, such as the quadrupole formula, in the weak field limit for gravitational waves emitted by compact sources.TUBITAK [123F353]The authors thank M. Gurses for useful discussions. E. A. is supported by TUBITAK Grant No. 123F353
Breast Cancer Detection Using a New Parallel Hybrid Logistic Regression Model Trained by Particle Swarm Optimization and Clonal Selection Algorithms
No full textBreast cancer is one of the most widespread kinds of cancer, especially in women, and it has a high mortality rate. With the help of technology, it is possible to develop a computer-aided method for the diagnosis of breast cancer, which is crucial for effective treatment. Recent breast cancer diagnosis studies utilizing numerous machine learning models were efficient and innovative. However, it has been observed that they may have problems such as long training times and low accuracy rates. To this end, in this study, we present a new classifier that utilizes a hybrid of the clonal selection algorithm (CSA) and the particle swarm optimization (PSO) algorithm for the training of the logistic regression (LR) model, which is named CSA-PSO-LR. The proposed method is evaluated using two publicly accessible breast cancer datasets, that is, the Wisconsin Diagnostic Breast Cancer (WDBC) database and the Wisconsin Breast Cancer Database (WBCD), with 10-fold cross-validation and Bayesian hyperparameter optimization techniques. Additionally, a CPU parallelization method is applied, which substantially shortens the training time of the model. The efficacy of the CSA-PSO-LR classifier is compared with state-of-the-art machine learning algorithms and related studies in the literature. Performance analysis indicates that the proposed method achieves 98.75% accuracy and 98.27% F1-score on the WDBC dataset, and 97.94% accuracy and 97.35% F1-score on the WBCD dataset. These results demonstrate the potential of the proposed method as an effective approach for improving breast cancer diagnosis.TUEBiTAK ULAKBiMThis work was supported by TUEBiTAK ULAKBiM; through its agreement with Wiley, the open access fee for this publication has been covered
AI-Enhanced PV Power Forecasting Using Cloud Thickness and Motion in Kayseri, Türkiye
No full textThe incorporation of renewable energy in photovoltaic (PV) systems has made significant progress. The inherent intermittency nature of PV generation, nevertheless poses an obstacle to accurate energy forecasting. Historical PV production plus meteorological data such as temperature, humidity, and atmospheric pressure are largely utilized in present methods of forecasting. However, cloud thickness and dynamics-integrated system, has not been investigated and tested in real-world examples yet.This research seeks to fill this gap in research through the development of a new AI-based PV forecasting model that incorporates cloud thickness, cloud motion, and solar position into the forecasting model. Cloud properties and their impact on solar radiation are computed through a deep learning-based panel-shadowing model. For cloud movement forecasting, a gated recurrent unit (GRU) is used, while multiple convolutional neural networks (CNNs) are used for estimating cloud thickness. These outcomes are then integrated with measurements from environmental sensors to improve the accuracy of the predictions.The system was implemented and tested at Abdullah G & uuml;l University and exhibited a remarkable improvement in forecasting accuracy compared to current models. The results prove that cloud motion and thickness improve the accuracy of PV predictions, which is important for energy market stability and power grid operations.Qatar National LibraryThe publication of this article was funded by Qatar National Library
Shooting a Water Slug Into an Air Column with and without Vent
No full textCompressed air is used to shoot a single water slug into an upward sloping pipe with elbow and orifice at its upper end. The experiment concerns a 12 m long pipe of 0.1 m diameter connected to a 0.5 m3 air vessel. The 10 to 50 kg heavy slugs are initially at rest in the lower part of the system. Because the upper end is closed by a flange with orifice, the water slug is expected not to hit the upstream elbow. It causes - like a piston - a fast compression of the air column ahead of it. Sometimes the slug bounces back and forth, which results in a pressure oscillation of serious amplitude. Numerical simulations based on an elementary mathematical model are normally used to interpret the pressure measurements, not all of which are fully understood. Lessons learned are summarised, and suggestions for improved experiments and enhanced simulations are given. The research is of importance, for example, for steam lines where liquid condensates may collect in lower parts after power failure. Start-up of the system will then lead to rapid slug acceleration and potentially damaging impact on elbows, orifices, and machinery.Middle East Technical University Scientific Research Project Program [BAP-03-03-2017-002]; STW; MARIN; GTT; Liquefied Natural GasThe authors express their gratitude for the financial support offered by the Middle East Technical University Scientific Research Project Program with the project code BAP-03-03-2017-002. The third author participated in the SLING (Sloshing of Liquefied Natural Gas) project, which was funded by STW, MARIN, GTT, and eleven other companies and institutes. In relation to SLING, the authors thank MARIN (Maritime Research Institute Netherlands) for providing technical assistance in the experiments; in particular Hannes Bogaert and Ronnie van Ginkel are thanked for their encouraging attitude
Microstrip Stub Filter Design with Enhanced Performance Inspired by SIW Structures Operating at 1.93 GHz GSMBand
No full textThis paper reports a microstrip stub filter design operating at 1.93 GHz GSM band with enhanced performance inspired by SIW structures. In the designed filter additional vias are placed around the microstrip lines to enhance the encasing of the electromagnetic fields while propagating through the filter to develop the filter performance. The filter was examined with electromagnetic simulations for various numbers of vias and different via to microstrip line distances. Results show that the maximum transmission coefficient (S21 parameter) magnitude value reached in the pass band of the filter increases with the number of the vias and as the vias get closer to the lines. On the other hand, when the via number increases and the space between them and the lines narrows, the frequency at which the maximum S21 value is attained shifts to lower frequencies. The designed filters were manufactured, too. Results obtained in the measurements agree well with the simulation results. Additionally, a receiver system operating at 1.93 GHz band was constructed. System experiments were carried out with the constructed prototype for the manufactured filters. Results show that a greater signal level in the filter pass band is achieved and unwanted signals outside the filter pass band are suppressed more in the system where the filter with vias is used instead of the filter without any additional via. The findings indicate that the designed filters inspired by SIW structures are promising for applications requiring high signal quality
Effect of Bio-Mimicked Surface Texturing on the Shear Strength of Additively Manufactured Metal Single-Lap Joints: An Innovative Approach
No full textAtahan, Mithat Gokhan/0000-0002-8180-5876; Apalak, Mustafa Kemal/0000-0002-3263-5735;In this paper, we investigate the mechanical performance of metal single-lap joints featuring bio-mimicking surface textures. The inspiration for the surface textures was the foot and toe of the gecko, a creature whose ability to climb smooth shear surfaces is attributed to the mesoand micro-structures of its feet. Three surface textures were investigated: a hexagonal texture based on the central region of the foot, a lamellae-like texture based on the toe, and a mixed texture of both. Metal adherends with these textures were produced using the laser powder bed fusion (LPBF) additive manufacturing method. Finite element analysis was performed to examine the influence of surface texture on stress distribution in the adhesive layer, while mechanical testing was used to determine joint strength and failure mode. Compared to the as- printed surface texture, bio-mimicking surface textures improved the wettability of the bonding surfaces, and significantly improved the lap shear strength of the joints. Mechanical interlocking due to surface texture was more effective than the increase in bonding surface area in enhancing joint strength. The bio-mimicking textures improved the damage tolerance capacity of the joints by reducing local stress concentrations at the overlap edges of the adhesive layer and ensured that the adhesive failure type was mixed mode due to the mechanical interlocking effect. The presented novel bio-mimicked surface texture method offers promising results for both industrial applications and scientific studies.Scientific and Technological Research Council of Turkiye (TUBIdot;TAK 2219-International Postdoctoral Research Fellowship Program for Turkish Citizens); University of Nottingham, United KingdomThis research was supported by the Scientific and Technological Research Council of Turkiye (TUB & Idot;TAK 2219-International Postdoctoral Research Fellowship Program for Turkish Citizens) and the University of Nottingham, United Kingdom. The authors extend their thanks to the U.S. National Science Foundation for usage permission of the Gecko's foot photo
Investigation of SH2 Domains of Spleen Tyrosine Kinase Enzyme for Targeting Acute Myeloid Leukemia Using Both in Silico and in Vitro Studies
No full textAkut Miyeloid Lösemi (AML), genetik ve epigenetik anormalliklerle karakterize klonal bir malignitedir ve bu karmaşık hastalıkta potansiyel bir terapötik hedef olarak ortaya çıkan moleküllerden biri, amino terminalinde iki SH2 alanı ve bunu takip eden katalitik olarak aktif bir kinaz alanından oluşan Dalak Tirozin Kinaz'dır (Syk). Kansere yol açan anormal proteinlerin aktivasyonunu önlemek için kanser tedavi yöntemlerinde yapılan son çalışmalar, aktif kinaz alanlarına ek olarak SH2 alanlarının da önemli hedefler olduğunu ortaya koymuştur. Bu çalışmada, aday inhibitörler, COCONUT ve ENAMINE olmak üzere iki kütüphanenin taranmasıyla in silico çalışmalar yoluyla tanımlanmıştır. Daha sonra ENAMINE kütüphanesinden seçilen iki aday inhibitör (Z260816155 ve z2155444005) için in vitro bağlanma testleri yürütülmüş ve bağlanma, FRET teknolojisi ve Diferansiyel Taramalı Florimetri Testi (DSF) kullanılarak HEK293 hücrelerinde in vitro olarak doğrulanmıştır. Son olarak, amaç, AML hücrelerinde Syk'nin SH2 bölgelerini hedef alarak protein-protein etkileşimlerini inhibe etmenin biyolojik aktivitelerini araştırmaktır. Aday inhibitörler, THP-1 ve HL-60 hücrelerinde düşük mikromolar konsantrasyonlarda (1-25 µM) hücre canlılığını azaltmış ve kontrol hücrelerine kıyasla ilişkili bir şekilde apoptozu indükleyerek hücre döngüsünün durmasına neden olmuştur Ayrıca, TNF-α ve IL-1β gen ekspresyonunu modüle etmiş ve anti-apoptotik proteinler Bcl-2 ve Bcl-xL'yi etkili bir şekilde baskılamışlardır.Acute Myeloid Leukemia (AML) is a clonal malignancy characterized by genetic and epigenetic abnormalities and one molecule that has emerged as a potential therapeutic target in this complex disease is Spleen Tyrosine Kinase (Syk) which consists of two SH2 domains at its amino terminus followed by a catalytically active kinase domain. Recent studies in cancer treatment methods to prevent the activation of abnormal proteins that lead to cancer have revealed that SH2 domains are also important targets in addition to active kinase domains. In this study, candidate inhibitors were identified through in silico studies by screening two libraries, COCONUT and ENAMINE. In vitro binding tests were then conducted for two candidate inhibitors selected from the ENAMINE library (Z260816155 and z2155444005), and binding was confirmed in vitro in HEK293 cells using FRET technology and Differential Scanning Fluorimetry Assay (DSF). Finally, the aim was to investigate the biological activities of inhibiting protein-protein interactions by targeting the SH2 domains of Syk on AML cells. The candidate inhibitors used decreased cell viability at low micromolar concentrations (1-25 µM) in THP-1 and HL-60 cells and, in a correlated manner, induced apoptosis and caused cell cycle arrest cells compared to control cells. Furthermore, they modulated the gene expression of TNF-α and IL-1β and effectively suppressed the anti-apoptotic proteins Bcl-2 and Bcl-xL
Antifungal Efficacy of 3D-Cultured Palatal Mesenchymal Stem Cells and Their Secreted Factors Against Candida Albicans
No full textCandida albicans is among the life-threatening fungal species and the primary contributor to hospital-acquired systemic infections, accounting for nearly 70% of all fungal infections worldwide. The current treatment primarily relies on azoles, pyrimidine analogs, polyenes, and echinocandins. However, growing antifungal resistance highlights the urgent need for the development of alternative treatments against C. albicans. Mesenchymal stem cells (MSCs) offer huge therapeutic potential for the treatment of C. albicans-associated diseases. In this study, palatal adipose tissue-derived MSCs (PAT-MSCs) and PAT-MSCs cultured in 3D biomaterial using nanofibrillar cellulose were tested against C. albicans strains ATCC 10231 and ATCC MYA 2876 using an in vitro antifungal activity assay. In addition, the conditioned medium from both PAT-MSCs and PAT-MSCs cultured in 3D hydrogel biomaterial (CM-PAT-MSCs-3D) were evaluated for their antifungal activities. The combined effect of PAT-MSCs and their secreted factors was also investigated. The expression of five antimicrobial peptide (AMP)-encoding genes was analyzed by quantitative real-time PCR. The expression of antimicrobial peptides was further confirmed via immunocytochemical staining. PAT-MSCs significantly inhibited the growth of C. albicans strains at varying inoculum concentrations (500 and 2000 CFU). Similarly, a comparable antifungal effect was observed when Candida strains were treated with PAT-MSC secreted factors alone. Statistical analysis revealed significant differences between the antifungal activities of PAT-MSCs and CM-PAT-MSCs. Lastly, the combination of PAT-MSCs and CM-PAT-MSC-3D led to a marked reduction in fungal growth, with inhibition rates of 99.75% and 99.91% for C. albicans ATCC 10231 and ATCC MYA-2876, respectively, at 500 CFU inocula. At 2000 CFU inocula, inhibition rates were 99.54% and 99.91%, respectively (****P ≤ 0.0001). These antifungal activities were further confirmed by using RT-PCR and immunocytochemical analysis. Our findings underscore a perspective on the potent antifungal activity of secreted factors from PAT-MSCs cultured within a 3D hydrogel matrix, specifically against various strains of C. albicans. Particularly, the combination of PAT-MSCs with their secreted factors represents a promising therapeutic platform, potentially offering a safer and more effective alternative to conventional antifungal treatments. © 2025 Elsevier B.V., All rights reserved
Edge AI: A Taxonomy, Systematic Review and Future Directions
No full textXu, Minxian/0000-0002-0046-5153; Kumar, Surendra/0000-0003-1718-8102; Ali, Babar/0000-0003-0542-848X; Walia, Guneet Kaur/0000-0003-2481-2532;Edge Artificial Intelligence (AI) incorporates a network of interconnected systems and devices that receive, cache, process, and analyse data in close communication with the location where the data is captured with AI technology. Recent advancements in AI efficiency, the widespread use of Internet of Things (IoT) devices, and the emergence of edge computing have unlocked the enormous scope of Edge AI. The goal of Edge AI is to optimize data processing efficiency and velocity while ensuring data confidentiality and integrity. Despite being a relatively new field of research, spanning from 2014 to the present, it has shown significant and rapid development over the last five years. In this article, we present a systematic literature review for Edge AI to discuss the existing research, recent advancements, and future research directions. We created a collaborative edge AI learning system for cloud and edge computing analysis, including an in-depth study of the architectures that facilitate this mechanism. The taxonomy for Edge AI facilitates the classification and configuration of Edge AI systems while also examining its potential influence across many fields through compassing infrastructure, cloud computing, fog computing, services, use cases, ML and deep learning, and resource management. This study highlights the significance of Edge AI in processing real-time data at the edge of the network. Additionally, it emphasizes the research challenges encountered by Edge AI systems, including constraints on resources, vulnerabilities to security threats, and problems with scalability. Finally, this study highlights the potential future research directions that aim to address the current limitations of Edge AI by providing innovative solutions.Ministry of Education of the Turkish Republic; Ph.D. Scholarship at the Queen Mary University of London; National Natural Science Foundation of China [62071327, 62102408]; Tianjin Science and Technology Planning Project [22ZYYYJC00020]; HE ACES project [101093126]; Guangdong Basic and Applied Basic Research Foundation [2024A1515010251]; Shenzhen Industrial Application Projects of undertaking the National key R & D Program of China [CJGJZD20210408091600002]Funding M. Golec is supported by the Ministry of Education of the Turkish Republic. B. Ali is supported by the Ph.D. Scholarship at the Queen Mary University of London. H. Wu is supported by the National Natural Science Foundation of China (No. 62071327) and Tianjin Science and Technology Planning Project (No. 22ZYYYJC00020). F. Cuadrado has been supported by the HE ACES project (Grant No. 101093126). M. Xu is supported by the National Natural Science Foundation of China (No. 62102408), Guangdong Basic and Applied Basic Research Foundation (No. 2024A1515010251), Shenzhen Industrial Application Projects of undertaking the National key R & D Program of China (No. CJGJZD20210408091600002)
Characterization of Disease Gene
No full textHasta olmak insan yaşamının bir parçasıdır. Bazı hastalıklara sık rastlanırken bazı hastalıklar nadirdir. Günümüzde 7000den fazla nadir hastalık vardır ve sayısı artmaktadır. Silyopatiler de nadir hastalıklardan biridir. Silyopatiler, silyanın fonksiyonunu ya da yapısını etkileyen mutasyonlar sonucu oluşan hastalıklardır. Silya birçok kompartmandan oluşan, hücreden dışarıya doğru uzanan bir organeldir ve Hedgehog sinyal yolağı gibi bazı önemli sinyal yolaklarını etkiler. 2014 yılında EFCAB7'in EVC ve EVC2 proteinleri ile ilişkisi bulunmuştur. EVC ve EVC2 genlerindeki mutasyonlar Ellis van Creveld hastalığına sebep olmaktadır. 2023'de ise sendromik olmayan postaksial polidaktiliye sebep olduğu keşfedilmiştir. Ancak EFCAB7 ile silya arasındaki ilişki yeterince aydınlatılamamıştır. Bu çalışmada, mikroskobik yöntemler ve fonksiyonel deneylerle EFCAB7 ile cilia arasındaki ilişki incelenmiştir. Sonuçlarımız, efcab-7 mutantlarının silialarının vahşi tipe kıyasla önemli ölçüde daha kısa olduğunu, buna karşın IFT (intraflagellar transport) hızı ve partikül sayısında belirgin bir değişiklik olmadığını göstermiştir. Ayrıca, normal koşullarda silyaya girmeyen ELMOD-3 proteini, efcab-7 mutantlarında da silyaya giriş yapmamış ve bu durum silial geçidin sağlam olduğunu ortaya koymuştur. Beklenmedik bir şekilde, efcab-7 mutantlarının hareket kabiliyetinin azaldığı ve akson sayısının da azaldığı gözlemlenmiştir, bu da EFCAB7'nin nöronal veya kas fonksiyonunda ek bir rolü olabileceğini düşündürmektedir. Bu bulgular, EFCAB7'nin silya ve nöronal bütünlüğün korunmasındaki fonksiyonlarını genişletmekte ve ilişkili nadir hastalıkların patogenezi hakkında yeni bilgiler sağlamaktadır.Being sick is part of human life. Some disease can are common, while others are rare. There are more than 7000 rare diseases in present and is counting. Ciliopathies are one of the rare diseases. Ciliopathies are diseases caused by mutations that affect the function or structure of cilia. Cilia are organelles composed of many compartments that extend outward from the cell and affect some important signalling pathways, such as the Hedgehog signaling pathways. In 2014, the relationship between EFCAB7 and EVC-EVC2 proteins was discovered. Mutations in the EVC and EVC2 genes cause Ellis van Creveld disease. In 2023, it was found that it causes non-syndromic postaxial polydactyly. However, the relationship between EFCAB7 and cilia has not been sufficiently elucidated. In this study, it was investigated relationship between EFCAB7 and cilia using microscopic methods and functional assays. Our results indicated that cilia in efcab-7 mutants were significantly shorter than those in the wild type, whereas IFT velocity and particle number did not change noticeably. Moreover, ELMOD-3, which under normal conditions does not enter cilia, remained excluded in efcab-7 mutants and thus reported an intact ciliary gate. Unexpectedly, efcab-7 mutants also displayed attenuated motility and reduced axon number, suggesting an additional function of EFCAB7 in neuronal or muscle function. These findings expand the spectrum of EFCAB7 functions in maintaining ciliary and neuronal integrity and provide new insights into the pathogenesis of its associated rare diseases