•This study showed that the PD can be diagnosed by using sensors attached at underfoot from gait.•Feature extracted by Shifted 1D-LBP, which is sensitive to local changes in time signals.•Shifted ...1D-LBP has a simple algorithm. It can be used in real time applications.•Obtained detection accuracy is 88.8889%.•The accuracy results were compared with the results of previous studies in literature.
The Parkinson's disease (PD) is one of the most common diseases, especially in elderly people. Although the previous studies showed that the PD can be diagnosed by expert systems through its cardinal symptoms such as the tremor, muscular rigidity, disorders of movements and voice, it was reported that the presented approaches, which utilize simple motor tasks, were limited and lack of standardization. To achieve a standard approach in PD detection, an approach, which is built on shifted one-dimensional local binary patterns (Shifted 1D-LBP) and machine learning methods, was proposed. Shifted 1D-LBP is built on 1D-LBP, which is sensitive to local changes in a signal. In 1D-LBP the positions of neighbors around center data are constant and therefore, the number of patterns that can be exacted by it is limited. This drawback was solved by Shifted 1D-LBP by changeable positions of neighbors. In evaluation and validation stages, the Gait in Parkinson's Disease (gaitpdb) dataset, which consists of three gait datasets that were recorded in different tasks or experiment protocols, were employed. Statistical features were exacted from formed histograms of gait signals transformed by Shifted 1D-LBP. Whole features and selected features were classified by machine learning methods. Obtained results were compared with statistical features exacted from signals in both time and frequency domains and results reported in the literature. Achieved results showed that the proposed approach can be successfully employed in PD detection from gait. This work is not only an attempt to develop a PD detection method, but also a general-purpose approach that is based on detecting local changes in time ordered signals.
•In this study, two novel local binary patterns were proposed.•First one is based on spatial relations between neighbors with a distance parameter.•The second is based on relations between a ...reference pixel and its neighbor on the same orientation.•Two approaches are improved to detect special patterns in images.•The results show that the proposed approaches can be used in image processing areas.
The recent developments in the image quality, storage and data transmission capabilities increase the importance of texture analysis, which plays an important role in computer vision and image processing. Local binary pattern (LBP) is an effective statistical texture descriptor, which has successful applications in texture classification. In this paper, two novel descriptors were proposed to search different patterns in images built on LBP. One of them is based on the relations between the sequential neighbors with a specified distance and the other one is based on determining the neighbors in the same orientation through central pixel parameter. These descriptors are tested with the Brodatz-1, Brodatz-2, Butterfly and Kylberg datasets to show the applicability of the proposed nLBPd and dLBPα descriptors. The proposed methods are also compared with classical LBP. The average accuracies obtained by ANN with 10 fold cross validation, which are 99.26% (LBPu2 and nLBPd), 94.44% (dLBPα), 95.71% (nLBPdu2) and %99.64 (nLBPd), for Brodatz-1, Brodatz-2, Butterfly and Kylberg datasets, respectively, show that the proposed methods outperform significant accuracies.
Explores and illustrates how domestic and international factors shape the direction of democratization process with special reference to constitution making process in Turkey. Describes how all five ...Turkish constitutions were, by and large, the products of indigenous effort, although borrowing could be felt in certain limited areas. Argues that the constitutional reforms in the post-1983 period were the outco me of broad inter-party negotiations and agree ments as a response to the society’s demands for a more democratic and liberal political system. Finally, the constitutional revisions adopted since 1995 were strongly conditioned by Turkey’s hope of accession to the European Union. With these reforms, Turkey was successful in meeting the political criteria and started accession negotiations with the EU.
According to the common opinion in the literature, the sustainability of container ports is a tremendously complex topic owing to the maritime sector's excessively dynamic form and many highly ...complex, predictable and unpredictable uncertainties in this industry. The current paper proposes two powerful, practical, inspiring approaches to fill these gaps. It proposes a novel type-2 neutrosophic fuzzy numbers (T2NFNs) based Delphi method to determine the criteria logically and optimal and extends the WASPAS technique based on the T2NFNs for evaluating the alternatives. The current paper presents practical managerial implications that many stakeholders can consider, such as port authorities, ship owners, logistics service providers, governments, and local authorities, when making strategic and managerial decisions. In addition, the results of a comprehensive sensitivity analysis performed to test the robustness and applicability of the model approve the validity of the proposed T2NFN-based integrated approach.
•This paper employed a novel T2NFN -Delphi- WASPAS models for suitable port selection.•Evaluation 14 Turkish container ports in the Marmara region based on their sustainability performance.•Regional GDP emerged out as most surpassing criteria.•Marport is the best alternative having higher sustainability performance.•Sensitivity analysis performed to test the robustness and applicability of the model.
Recent developments in sensors increased the importance of action recognition. Generally, the previous studies were based on the assumption that the complex actions can be recognized by more ...features. Therefore, generally more than required body-worn sensor types and sensor nodes were used by the researchers. On the other hand, this assumption leads many drawbacks, such as computational complexity, storage and communication requirements. The main aim of this paper is to investigate the applicability of recognizing the actions without degrading the accuracy with less number of sensors by using a more sophisticated feature extraction and classification method. Since, human activities are complex and include variable temporal information in nature, in this study one-dimensional local binary pattern, which is sensitive to local changes, and the grey relational analysis, which can successfully classify incomplete or insufficient datasets, were employed for feature extraction and classification purposes, respectively. Achieved mean classification accuracies by the proposed approach are 95.69, 98.88, and 99.08 % while utilizing all data, data obtained from a sensor node attached to left calf and data obtained from only 3D gyro sensors, respectively. Furthermore, the results of this study showed that the accuracy obtained by using only a 3D acceleration sensor attached in the left calf, 98.8 %, is higher than accuracy obtained by using all sensor nodes, 95.69 %, and reported accuracies in the previous studies that made use of the same dataset. This result highlighted that the position and type of sensors are much more important than the number of utilized sensors.
We developed a new CTAB-based seven-step DNA extraction protocol to isolate DNA from herbarium specimens. DNA was extracted from five species belonging to five genera from four families of ...angiosperms. The spectrophotometric measurement of double-stranded DNA demonstrated DNA of sufficient quality and quantity for PCR analysis. DNA was tested with universal primers and amplification success was 95%. The protocol is applicable to different taxonomic groups of herbarium specimens, fresh and silica-dried samples, and requires only common laboratory consumables and equipment. It is possible to extract 30 samples in less than two hours and more than 120 samples in a working day. The cost of consumables per sample is less than in many traditional protocols and commercially available kits.
Abstract
Objectives
The aim of this study was to investigate the potential of preoperative neopterin levels as a predictive marker for postoperative acute kidney injury (AKI) in patients undergoing ...on-pump cardiac surgery, in addition to other potential risk factors.
Methods
This observational study included 91 patients who underwent elective cardiac surgery under cardiopulmonary bypass. Of these, 35 patients (38.46 %) experienced AKI following surgery, as outlined by the Kidney Disease Improving Global Outcomes (KDIGO) standards. The study participants were divided into two groups depending on whether they had developed AKI after the surgery or not. The study compared two groups and utilized logistic regression analysis to evaluate potential predictors. A receiver operating characteristic (ROC) analysis was conducted to determine the ability of preoperative neopterin levels to predict the occurrence of AKI.
Results
A comparison of the baseline demographic, clinical, laboratory, and echocardiographic characteristics was conducted between patients who suffered from AKI and those who did not. The multivariate analysis demonstrated that EuroSCORE II (OR, 4.525; 95 % CI, 1.29–15.87; p=0.019), X-clamp time (OR, 1.157; 95 % CI, 1.01–1.326; p=0.035), and neopterin levels (OR, 22.952; 95 % CI, 3.14–167.763; p=0.002) were independently predicted the post-cardiac surgery AKI. ROC analysis identified a cut-off value of 9.65 nmol/L, which had a sensitivity of 91.4 % and a specificity of 91.1 % (area under the curve, 0.98; 95 % CI, 0.958–1; p<0.001).
Conclusions
Our study emphasizes the potential of preoperative neopterin levels, EuroSCORE II, and X-clamp time as independent predictors of postoperative AKI, even in milder cases, in individuals undergoing on-pump cardiac surgery.
Tensile strength and impact toughness of inter-layer hybrid composites, made of twill woven E-glass fabric and unidirectional carbon fiber in epoxy resin matrix with/without surface crack, were ...experimentally investigated. Hybrid laminates with eight, ten and twelve layers were prepared by employing the vacuum-assisted resin transfer molding method, while carbon and E-glass layers were stacked in an alternating sequence. Specimens were cut for uniaxial tensile loading, low-velocity Charpy impact tests, and for resin burn-off process, while additional specimens with standard artificial surface crack were also prepared for the tensile tests. The results of the quasi-static tensile tests surprisingly showed that tensile properties are a function of number of layers. It is seen that, ultimate tensile stress increases with number of plies by 20 ± 6% and 38 ± 11%, on an average basis for the uncracked and cracked specimens, respectively. This increase is less pronounced for ultimate strain and initial tensile modulus. As for the impact toughness of the specimens, those with twelve layers showed the largest toughness. In all cases, the rate of increase in mechanical properties decreases with increasing number of layers. It is also shown that the existence of surface crack generally increases the ultimate strain at the expense of a drop in ultimate tensile stress, because the laminates are more glass dominated. Reinforcement efficiency factors for uncracked specimens were found to be the constant value of 0.37. A detailed failure analysis has been also presented by scanning electron microscopy of the fracture surface. Charpy impact tests revealed that impact toughness of hybrid laminates increases with the number of layers. Failure modes are reported qualitatively in macroscopic and microscopic scales.
Graphic abstract
The aim of this study is to determine the landscape use opportunities of natural plants of wetland habitats (river, stream, rill, moist meadows, etc.) within Şanlıurfa province. In this study, 58 ...plants were determined from wetland habitats that can be evaluated in terms of landscape use. The characteristics of these plants for their landscape use (life form, structure, flowering period, flower color, landscape value, color, and scent effect) were determined. The obtained data were evaluated using PAST 4.03 data analysis software and Principal Component Analysis (PCA). In addition, cluster analysis was performed to examine the distribution of these plants according to the determined landscape use parameters. With the classification practices, plants were defined in 4 different groups, and it was observed that the parameters were effective in the classification of the species. It was concluded that PC1 and PC2 heavily determined the grouping with parameters such as life form, flowering period, color effect and flower color.
Bu çalışmanın amacı, Şanlıurfa il sınırları içerisindeki sulak alan habitatlarındaki (nehir, dere, nemli çayırlar vb.) doğal bitkilerinin peyzaj kullanım olanaklarının belirlenmesidir. Çalışmada sulak alan habitatlarından peyzaj kullanımı açısından değerlendirilebilecek 58 bitki tespit edilmiştir. Bu bitkilerin peyzaj kullanımına yönelik özellikleri (yaşam formu, yapısı, çiçeklenme dönemi, çiçek rengi, peyzaj değeri, rengi ve koku etkisi) belirlenmiştir. Elde edilen veriler, PAST 4.03 veri analiz yazılımı ve Temel Bileşen Analizi (PCA) kullanılarak değerlendirilmiştir. Ayrıca bu bitkilerin belirlenen peyzaj kullanım parametrelerine göre dağılımını incelemek için küme analizi yapılmıştır. Sınıflandırma uygulamaları ile bitkiler 4 farklı grupta tanımlanmış, parametrelerin türlerin sınıflandırılmasında etkili olduğu gözlemlenmiştir. PC1 ve PC2’nin yoğun olarak yaşam formu, çiçeklenme dönemi, renk etkisi ve çiçek rengi gibi parametreler ile gruplandırmayı belirlediği sonucuna ulaşılmıştır.
