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A statistical approach to site-specific thresholding for burn severity maps using bi-temporal Landsat-8 images
No full textBurn severity mapping facilitates post-fire management and restoration and predicts surface erosion and landslide risk. Different severity levels are usually distinguished by fixed threshold values with remote sensing techniques. Since the climate, ecosystem, geology, and morphology control the destruction level of forest fires, site-specific class thresholds should be considered to discriminate severity classes precisely. Therefore, the purpose of this study is to produce an accurate burn severity map using spectral indices with site-specific thresholds for unburned, low, moderate and high severity classes. In this context, pre- and post-fire Landsat 8 images were used to produce bi-temporal burn severity indices such as normalized burn ratio (NBR), normalized burned index (NBI), normalized difference vegetation index (NDVI), and green optimized soil adjusted vegetation index (GOSAVI). An alternative classification method based on a statistical distribution-based clustering approach was employed on the differential indices to determine severity class thresholds. The proposed thresholds were validated by the composite burn severity index (CBI) ratings of the field sampling points. The overall classification accuracy was found to be between 50% and 92.5%. In addition, the results were compared with the thresholds published in the literature. Consequently, this methodology can be used as adaptive thresholding in similar ecological and morphological zone to determine the burn severity classes
Chemopreventive mechanisms of amentoflavone: recent trends and advancements
No full textIn parallel to the continuous rise of new cancer cases all over the world, the interest of scientific community in natural anticancer agents has steadily been increased. In the past decades, numerous phytochemicals have been shown to possess a strong anticancer potential in preclinical conditions. One of such interesting compounds, derived from different plants such as ginkgo, hinoki, and St. John`s wort, is amentoflavone. In this review article, a wide range of anticancer properties of this natural biflavone are described, revealing its ability to suppress the malignant growth and lead tumor cells to apoptotic death, besides impeding also angiogenic and metastatic processes. Therefore, amentoflavone can be considered a potential lead compound for the development of novel anticancer drug candidates, definitely deserving further in vivo studies and also initiation of clinical trials. It is expected that this plant biflavone might be important, either alone or in combination with the current standard chemotherapeutics, in providing some alleviation for the continuous rise of global cancer burden
Real-time stress detection from smartphone sensor data using genetic algorithm-based feature subset optimization and k-nearest neighbor algorithm
No full textStress is the mood of pressure and tension that a person feels. Usually, when the pressure on an individual decrease, the body begins to stabilize the state and calm down. Hence, stress detection in real-time is a critical duty in medical systems. However, acquiring physiological data requires additional equipment and is difficult for users to carry with them at all times. Depending on this problem, it is possible to detect stress through behavioral data. Smartphones are devices that provide various behavioral data that people use constantly throughout the day. In this study, a real-time stress detection system based on soft keyboard typing behaviors was developed with the data obtained from linear acceleration, gravity, gyroscope sensors, and a touchscreen panel of the smartphone. 172 attributes were extracted from the raw sensor data. However, such a high number of dimensions could negatively affect the performance of machine learning algorithms. To address this problem, the number of features was reduced by various techniques such as filter-based methods and standard binary-code chromosome Genetic Algorithm as a contribution to this study. Then, writing behaviors were classified with the commonly used machine learning methods namely, C4.5, kNN, and Bayesian Networks. As a result of the experiments, the best classification was obtained from the kNN method using the features selected by the Genetic Algorithm with a classification accuracy of 89.61% and F-Measure of 0.9052. Another contribution of this study is that a mobile service and a relaxation application were developed for stress detection and to reduce stress levels using the selected feature vector
Assessment of biological rhythm disturbances and emotion recognition in individuals with or without obstructive sleep apnea syndrome: The role of eating patterns
No full textAlthough a vast amount of research efforts including a plethora of distinct methodologies have been put forth, the pathophysiology of obstructive sleep apnea syndrome (OSAS) has not been compromised and multidimensional aspects of biological rhythm disruptions has not been evaluated yet. Twenty individuals with severe OSAS and 20 individuals without OSAS were administered. The Biological Rhythm Interview of Assessment In Neuropsychiatry and the Emotion Recognition Task to evaluate biological rhythm disruptions multidimensionally and emotion recognition abilities dynamically for the first time in OSAS. More disrupted eating patterns (p = 0.03), diminished durations of non-REM 1 and 3 sleep stages, and preserved emotion recognition abilities were found in severe OSAS, thus emphasizing the role of eating patterns in OSAS. Allowing for the multifactorial nature of biological rhythm disruptions and emotion recognition abilities, the content and the course and the interplay between them should be pegged away before arriving at firm judgment
Missing link in ‘new-normal’ for higher education: nexus between online experiential marketing, perceived-harm, social distancing concern and university brand evangelism in China
No full textChinese universities were the first to experience the massive shock waves of the COVID-19 pandemic that disrupted higher education globally. Despite extensive research on higher education in the ‘new normal’, empirical evidence on the potential role of online experiential marketing and university brand evangelism is still little to none. To address this critical research gap, the present study is the first to explore university brand evangelism in China and how it is influenced by online experiential marketing. In addition, the moderating effects of perceived harm and social distancing concern on the relationship between online experiential marketing and university brand evangelism were also tested. Based on a sample of university students in China (N = 242) and covariance-based structural equation modeling (CB-SEM), the findings revealed that online experiential marketing (including sense, feel, think, act, and relate dimensions) significantly magnifies university brand evangelism in China. Interestingly, this relationship becomes more strengthened when the Chinese students have a high intensity of perceived harm of COVID-19 and social distancing concerns. These novel findings provide new insights to both policymakers and marketers globally about the powerful medium of online experiential marketing to successfully promote university brands (during and after the global pandemic) using university brand evangelism more strategically
The asymmetry in the sagitta of four mugilid species obtained from Köyceğiz Lagoon, Aegean Sea, Turkey
No full textOtolith features such as size and weight were analysed in 656 fish specimens of Chelon auratus, Chelon labrosus, Chelon saliens and Mugil cephalus collected from the Köyceğiz Lagoon System, Aegean Sea, southwest Turkey. The aim was to calculate the asymmetry value of the otolith length (OL), otolith width (OW) and otolith weight (OWe). The asymmetry value of OL was greater than that of OW and OWe. The asymmetry value of the three otolith parameters increased with an increase in the fish's length. The probable cause of asymmetry in the otolith parameters investigated has been determined relative to the variability in growth prompted by ecological impact linked with the disparity in water temperature, salinity, depth and contaminants existing in the Köyceğiz Lagoon System
The Relationship Between Functional Status and Fatigue After COVID-19 Infection
No full textIntroduction: After COVID-19 infection, symptoms last for weeks or months. In this study, it was aimed to examine the relationship between functional status and fatigue and the associated factors in patients with COVID-19.
Method: Patients with COVID-19 infection who applied to 13 centers were included into the study according to the inclusion criteria. Age, gender, height, body weight, body mass index (BMI), marital status, smoking status and amount, presence, duration of chronic disease, Charlson comorbidity index, regular exercise habit, time of diagnosis with COVID-19, presence of hospitalization,length of hospital stay, intubation status, home oxygen therapy need, participation in PR program, presence of dyspnea, cough, sputum, mMRC score, post-COVID functional status scale, fatigue severity scale, EQ-5D-5L Questionnaire scores were recorded.
Results: Of the 1095 patients, 603 (55%) were male and 492 (45%) were female. Their mean age was 50±14 years. The most common chronic lung disease was COPD (11%), while 266 patients (29%) had non-pulmonary systemic disease. The median time of COVID-19 diagonosis was 5 months ago with 47% hospitalization rate. The median value of post-COVID functional status scale was 1 (0:4), and fatigue severity scale score was 4.4 (1:7). There was a significant correlation between post-COVID functional status and fatigue severity scale (r=0.43, p <0.01).
Conclusion: Functional status and fatigue were found to be related primarily to quality of life and then patients' age, BMI, presence of chronic and systemic lung disease, regular exercise habits before COVID-19, hospitalization and its duration, home oxygen therapy and symptoms
Letter to the editor: “Validation and predictive capacity of a Dutch version of the FLARE‐RA questionnaire within the context of a TNFi‐tapering trial”
No full textLetter to edito
Effects of Hypericum perforatum extract on 6-hydroxydopamine neurotoxicity in differentiated SH-SY5Y cells
No full textBackground and objectiveParkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease. In our study, PD model was created as a result of exposure to 6-hydroxydopamine (6-OHDA) in SH-SY5Y cells, which is a human neuroblastoma cell line. The protective effect of Hypericum perforatum on PD was investigated. Materials and methodsPhytochemical analysis of H. perforatum extract was performed. Then, SH-SY5Y cells were differentiated using retinoic acid and then administered 6-OHDA neurotoxin. To determine the protective effects of H. perforatum extract, we investigated the changes in the mRNA expression level of caspase-3, total oxidant status, and antioxidant levels in differentiated SH-SY5Y.Results and conclusion According to our results, H. perforatum extract contains glycosides, tannins, flavonoids, and carbohydrates as the major secondary metabolites. H. perforatum extract significantly reduced caspase-3 gene expression against 6-OHDA toxicity in differentiated SH-SY5Y cells. It was found that total oxidant status level increased significantly in the 6-OHDA experimental group compared with the control and H. perforatum experimental groups. It was found that H. perforatum extract has an inhibitory effect on caspase-3 gene expression, which plays an important role in apoptosis. Therfore, H. perforatum extract has been shown to have a therapeutic potential against 6-OHDA toxicity
The effect of complex decongestive therapy on spatio-temporal parameters and balance in women with breast cancer-related upper extremity unilateral lymphedema
No full textBackground: The aim of this study was to investigate the effect of complex decongestive therapy on spatio-temporal parameters and balance in individuals with breast cancer-related upper extremity unilateral lymphedema. Methods: The study was designed as a prospective, cross-sectional study. Thirty sessions of complex decongestive therapy were applied. Participants' pre-and post-treatment spatio-temporal parameters and balance parameters were evaluated with the Win Track platform. In addition, the Timed Up and Go test was used to evaluate the dynamic balance. Plethysmography, a water displacement method, was used to measure upper extremity volume. Findings: Significant improvement was observed in limb volume asymmetry after complex decongestive therapy. While the stride length of the affected side was 409.93 mm before the treatment, it increased to 500.93 mm after the treatment, and a significant increase was observed (p = 001). Significant improvements were found in the other spatio-temporal parameters of the participants. Compared to the pre-treatment, a significant decrease was detected in the average cadence value, Timed Up and Go value, double stance time, and maximum plantar pressure point of the participants. Significant improvements were found in the participants' balance. Interpretation: Complex decongestive therapy applied to individuals with unilateral upper extremity lymphedema provides significant improvement in both spatio-temporal and balance parameters. However, we recommend complex decongestive therapy as an effective and safe treatment to reduce the volume of lymphedema. Patients with unilateral lymphedema that may cause postural asymmetry should be informed about balance and gait disturbance and should be encouraged to receive lymphedema treatment as soon as possible