Portable Microfluidic Integrated Plasmonic Platform for Pathogen Detection

Timely detection of infectious agents is critical in early diagnosis and treatment of infectious diseases. Conventional pathogen detection methods, such as enzyme linked immunosorbent assay (ELISA), culturing or polymerase chain reaction (PCR) require long assay times, and complex and expensive instruments, which are not adaptable to point-of-care (POC) needs at resource-constrained as well as primary care settings. Therefore, there is an unmet need to develop simple, rapid, and accurate methods for detection of pathogens at the POC. Here, we present a portable, multiplex, inexpensive microfluidic-integrated surface plasmon resonance (SPR) platform that detects and quantifies bacteria, i.e., Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) rapidly. The platform presented reliable capture and detection of E. coli at concentrations ranging from ~105 to 3.2 × 107 CFUs/mL in phosphate buffered saline (PBS) and peritoneal dialysis (PD) fluid. The multiplexing and specificity capability of the platform was also tested with S. aureus samples. The presented platform technology could potentially be applicable to capture and detect other pathogens at the POC and primary care settings

Discutindo a educação ambiental no cotidiano escolar: desenvolvimento de projetos na escola formação inicial e continuada de professores

A presente pesquisa buscou discutir como a Educação Ambiental (EA) vem sendo trabalhada, no Ensino Fundamental e como os docentes desta escola compreendem e vem inserindo a EA no cotidiano escolar., em uma escola estadual do município de Tangará da Serra/MT, Brasil. Para tanto, realizou-se entrevistas com os professores que fazem parte de um projeto interdisciplinar de EA na escola pesquisada. Verificou-se que o projeto da escola não vem conseguindo alcançar os objetivos propostos por: desconhecimento do mesmo, pelos professores; formação deficiente dos professores, não entendimento da EA como processo de ensino-aprendizagem, falta de recursos didáticos, planejamento inadequado das atividades. A partir dessa constatação, procurou-se debater a impossibilidade de tratar do tema fora do trabalho interdisciplinar, bem como, e principalmente, a importância de um estudo mais aprofundado de EA, vinculando teoria e prática, tanto na formação docente, como em projetos escolares, a fim de fugir do tradicional vínculo “EA e ecologia, lixo e horta”.Facultad de Humanidades y Ciencias de la Educació

Organizational learning on coopetition strategy: an exploratory research on a Turkish private banks credit card application

In the Turkish banking sector, competition and the banks' costs have become more important than ever due to the global financial crisis which began at 2008 and affected the world economic and financial systems. The banks, aim to increase their share in the credit card market which is one of the most profitable market in the sector, are cooperated with the other banks which have well-known credit card brand and wide POS network. This strategy is called as "coopetition"

Foreseeable impacts of sea level rise on the southern coast of the Marmara Sea (Turkey)

This paper represents the results of a case study of the interaction between sea level rise (SLR), subsidence and the consequences of this phenomenon on fresh water resources that may be subject to exacerbated salt-water intrusion. The possible reasons for rapid SLR at the permanent tide gauge station located on the southern coast of the Marmara Sea have been investigated based on time series data recorded since 1984. The population in the region relies mainly on groundwater resources for urban, tourism and agricultural water use, which represents a severe risk with regard to the replenishment of the coastal aquifer. Based on the findings, appropriate methods of assessing the coastal vulnerability to future SLR and recommendations for coastal zone management with emphasis on the protection of water resources are discussed

ASNET: A Novel AI Framework for Accurate Ankylosing Spondylitis Diagnosis from MRI

Background: Ankylosing spondylitis (AS) is a chronic, painful, progressive disease usually seen in the spine. Traditional diagnostic methods have limitations in detecting the early stages of AS. The early diagnosis of AS can improve patients’ quality of life. This study aims to diagnose AS with a pre-trained hybrid model using magnetic resonance imaging (MRI). Materials and Methods: In this research, we collected a new MRI dataset comprising three cases. Furthermore, we introduced a novel deep feature engineering model. Within this model, we utilized three renowned pretrained convolutional neural networks (CNNs): DenseNet201, ResNet50, and ShuffleNet. Through these pretrained CNNs, deep features were generated using the transfer learning approach. For each pretrained network, two feature vectors were generated from an MRI. Three feature selectors were employed during the feature selection phase, amplifying the number of features from 6 to 18 (calculated as 6 × 3). The k-nearest neighbors (kNN) classifier was utilized in the classification phase to determine classification results. During the information phase, the iterative majority voting (IMV) algorithm was applied to secure voted results, and our model selected the output with the highest classification accuracy. In this manner, we have introduced a self-organized deep feature engineering model. Results: We have applied the presented model to the collected dataset. The proposed method yielded 99.80%, 99.60%, 100%, and 99.80% results for accuracy, recall, precision, and F1-score for the collected axial images dataset. The collected coronal image dataset yielded 99.45%, 99.20%, 99.70%, and 99.45% results for accuracy, recall, precision, and F1-score, respectively. As for contrast-enhanced images, accuracy of 95.62%, recall of 80.72%, precision of 94.24%, and an F1-score of 86.96% were attained. Conclusions: Based on the results, the proposed method for classifying AS disease has demonstrated successful outcomes using MRI. The model has been tested on three cases, and its consistently high classification performance across all cases underscores the model’s general robustness. Furthermore, the ability to diagnose AS disease using only axial images, without the need for contrast-enhanced MRI, represents a significant advancement in both healthcare and economic terms

Synthesis, characterization and investigation of electrochemical and spectroelectrochemical properties of non-peripherally tetra-5-methyl-1,3,4-thiadiazole substituted copper(II) iron(II) and oxo-titanium (IV) phthalocyanines

AKCAY, Hakki Turker/0000-0002-8502-9608; KOCA, ATIF/0000-0003-0141-5817WOS: 000403855700014In this study novel substituted phthalonitrile (3) and non-peripherally tetra 5-Methyl-1,3,4-thiadiazole substituted copper(II) (4), iron(II) (5) and oxo-titanium (IV) (6) phthalocyanines were synthesized. These novel compounds were fully characterized by FT-IR, H-1 NMR, UV-vis and MALDI-TOF mass spectroscopic techniques. Voltammetric and in situ spectroelectrochemical measurements were performed for metallo-phthalocyanines (4-6). Ti(Iv)0Pc and (FePc)-Pc-II showed metal-based and ligand-based electron transfer reactions while (CuPc)-Pc-II shows only ligand-based electron transfer reaction. Voltammetric measurements indicated that the complexes have reversible, diffusion controlled and one electron redox reactions. the assignments of the redox processes and color of the electrogenerated species of the complexes were determined with in-situ spectroelectrochemical and electrocolorimetric measurements. These measurements showed that the complexes can be used as the electrochromic materials for various display technologies. (C) 2017 Elsevier B.V. All rights reserved

Synthesis, characterisation, photophysical and photochemical properties of free-base tetra-(5-chloro-2-(2,4-dichlorophenoxy) phenoxy)phthalocyanine and respective zinc(II) and lead(II) complexes

AKCAY, Hakki Turker/0000-0002-8502-9608;WOS: 000392681600021In this study, novel peripherally tetra-(5-chloro-2-(2,4-dichlorophenoxy)phenol) substituted metal-free (4), zinc(II) (5) and lead(II) (6) phthalocyanine derivatives were synthesised. the novel phthalocyanines (4-6) were characterised by general spectroscopic methods such as IR, H-1 NMR, UV-vis, mass spectrometry and elemental analysis. Once the solubilities of the compounds were investigated, it was noticed that they have excellent solubility and did not tend to aggregation behaviour in common solvents. the photophysical and photochemical properties of novel phthalocyanines (4-6) were investigated in dimethysulfoxide. the effects of substituted 5-chloro-2-(2,4-dichlorophenoxy)phenoxy group and central metal ion [zinc(II)/lead(II)] on photophysical and photochemical properties of the novel phthalocyanines have also been examined, and the results were compared with unsubstituted zinc (II) phthalocyanine. According to photophysical and photochemical investigation results, it was observed that the novel phthalocyanines (4-6) have a potential for PDT application. (C) 2016 Elsevier B.V. All rights reserved

InCR: Inception and concatenation residual block-based deep learning network for damaged building detection using remote sensing images

In February 2023, Turkey experienced a series of earthquakes that caused significant damage to buildings and affected many people. Detecting building damage quickly is crucial for helping earthquake victims, and we believe machine learning models offer a promising solution. In our research, we introduce a new, lightweight deep-learning model capable of accurately classifying damaged buildings in remote-sensing datasets.Our main goal is to create an automated damage detection system using a novel deep-learning model. We started by collecting a new dataset with two categories: damaged and undamaged buildings. Then, we developed a unique convolutional neural network (CNN) called the inception and concatenation residual (InCR) deep learning network, which incorporates concatenation-based residual blocks and inception blocks to improve performance.We trained our InCR model on the newly collected dataset and used it to extract features from images using global average pooling. To refine these features and select the most informative ones, we applied iterative neighborhood component analysis (INCA). Finally, we classified the refined features using commonly used shallow classifiers.To evaluate our method, we used tenfold cross-validation (10-fold CV) with eight classifiers. The results showed that all classifiers achieved classification accuracies higher than 98 %. This demonstrates that our proposed InCR model is a viable option for CNNs and can be used to create an accurate automated damage detection application.Our research presents a unique solution to the challenge of automated damage detection after earthquakes, showing promising results that highlight the potential of our approach

The novel Zn(II) phthalocyanines: Synthesis, characterization, photochemical, DNA interaction and cytotoxic/phototoxic properties

AKCAY, Hakki Turker/0000-0002-8502-9608WOS: 000541166600003[No abstract available]Scientific Research Coordination Unit of Karadeniz Technical UniversityKaradeniz Technical University [FHD-2019-8165]This study was supported by the Scientific Research Coordination Unit of Karadeniz Technical University (Project Number: FHD-2019-8165)