No abstract

Accurate and real-time land use/land cover (LULC) maps are important to provide precise information for dynamic monitoring, planning, and management of the Earth. With the advent of cloud computing platforms, time series feature extraction techniques, and machine learning classifiers, new opportunities are arising in more accurate and large-scale LULC mapping. In this study, we aimed at finding out how two composition methods and spectral–temporal metrics extracted from satellite time series can affect the ability of a machine learning classifier to produce accurate LULC maps. We used the Google Earth Engine (GEE) cloud computing platform to create cloud-free Sentinel-2 (S-2) and Landsat-8 (L-8) time series over the Tehran Province (Iran) as of 2020. Two composition methods, namely, seasonal composites and percentiles metrics, were used to define four datasets based on satellite time series, vegetation indices, and topographic layers. The random forest classifier was used in LULC classification and for identifying the most important variables. Accuracy assessment results showed that the S-2 outperformed the L-8 spectral–temporal metrics at the overall and class level. Moreover, the comparison of composition methods indicated that seasonal composites outperformed percentile metrics in both S-2 and L-8 time series. At the class level, the improved performance of seasonal composites was related to their ability to provide better information about the phenological variation of different LULC classes. Finally, we conclude that this methodology can produce LULC maps based on cloud computing GEE in an accurate and fast way and can be used in large-scale LULC mapping.

Diabetes, as a low‐grade chronic inflammatory disease, causes disruption in proper function of immune and metabolic system. Chromium is an important element required for normal lipid and glucose metabolism. Chromium deficiency is correlated with elevation in cardiometabolic risk, which results from increased inflammation. This systematic review was conducted to discover the potential roles of chromium on inflammatory biomarkers. Eligible studies were all in vitro, animal and human studies published in English‐language journals from inception until October 2018. PubMed, Scopus, Embase, ProQuest and Google Scholar databases were searched to fined interventional studies from the effects of chromium on inflammatory biomarkers such as tumour necrosis factor a (TNF‐a), C‐reactive protein (CRP), interleukins, monocyte chemoattractant protein–1 (MCP‐1), intercellular adhesion molecule‐1 (ICAM‐1) and adipocytokines in hyperglycaemia and diabetes. Out of 647 articles found in the search, only 14 articles were eligible for analysis, three in vitro studies, eight animal studies and three human studies. Twelve of the 14 studies included in this review, chromium significantly decreased inflammatory factors. The findings of this review indicate, based on in vitro and in vivo studies, that chromium might have potential anti‐inflammatory properties, but some of the studies did not show anti‐inflammatory effects for chromium (two studies). There are only three studies in humans with controversial results. Therefore, more consistent randomized double‐blind controlled trials are needed to reach relevant clinical recommendations, as well as to determine the precise mechanism, of chromium on inflammation in diabetes.

One of the main challenges of using unmanned aerial vehicles (UAVs) in forest data acquisition is the implementation of Ground Control Points (GCPs) as a mandatory step, which is sometimes impossible for inaccessible areas or within canopy closures. This study aimed to test the accuracy of a UAV-mounted GNSS RTK (real-time kinematic) system for calculating tree height and crown height without any GCPs. The study was conducted on a Cupressus arizonica (Greene., Arizona cypress) plantation on the Razi University Campus in Kermanshah, Iran. Arizona cypress is commonly planted as an ornamental tree. As it can tolerate harsh conditions, this species is highly appropriate for afforestation and reforestation projects. A total of 107 trees were subjected to field-measured dendrometric measurements (height and crown diameter). UAV data acquisition was performed at three altitudes of 25, 50, and 100 m using a local network RTK system (NRTK). The crown height model (CHM), derived from a digital surface model (DSM), was used to estimate tree height, and an inverse watershed segmentation (IWS) algorithm was used to estimate crown diameter. The results indicated that the means of tree height obtained from field measurements and UAV estimation were not significantly different, except for the mean values calculated at 100 m flight altitude. Additionally, the means of crown diameter reported from field measurements and UAV estimation at all flight altitudes were not statistically different. Root mean square error (RMSE < 11%) indicated a reliable estimation at all the flight altitudes for trees height and crown diameter. According to the findings of this study, it was concluded that UAV-RTK imagery can be considered a promising solution, but more work is needed before concluding its effectiveness in inaccessible areas.

Objective Nonalcoholic fatty liver disease (NAFLD) is a complicated disease and is considered as a severe global health problem affecting 30% of adults worldwide. The present study aimed to evaluate changes in oxidative stress, adipokines, liver enzyme, and body composition following treatment with chromium picolinate (CrPic) among patients with NAFLD. Participants and methods The current randomized, double-blind, placebo-controlled study was conducted on 46 NAFLD patients with the age range of 20–65 years. Patients were randomly classified into two groups, receiving either 400 µg CrPic tablets in two divided doses of 200 µg (23 patients) or placebo (23 patients) daily for 12 weeks. The participants’ body composition and biochemical parameters were evaluated at the baseline and after 12 weeks. Results Serum levels of liver enzymes reduced significantly only in the CrPic group (P < 0.05 for all), but not between the groups after the intervention. Besides, there were significant differences between the study groups regarding body weight and body fat mass, total antioxidant capacity, superoxide dismutase, malondialdehyde, leptin, and adiponectin post-intervention (P = 0.017, P = 0.032, P = 0.003, P = 0.023, P = 0.012, P = 0.003, and P = 0.042, respectively). However, glutathione peroxidase and resistin levels did not differ significantly between groups (P = 0.127 and P = 0.688, respectively). Discussion and conclusion This study showed that consuming 400 µg/day of CrPic for 12 weeks in patients with NAFLD causes a significant change in leptin, adiponectin, oxidative stress (expect glutathione peroxidase), and body weight, compared to baseline. Nevertheless, it does not affect liver enzymes. Therefore, the CrPic supplementation may improve adipokines, some anthropometric indices, and oxidative stress in patients with NAFLD.