Mapping Forest Health Using Spectral And Textural Information Extracted From Spot-5 Satellite Images

Forest health is an important variable that we need to monitor for forest management decision making. However, forest health is difficult to assess and monitor based merely on forest field surveys. In the present study, we first derived a comprehensive forest health indicator using 15 forest stand attributes extracted from forest inventory plots. Second, Pearson’s correlation analysis was performed to investigate the relationship between the forest health indicator and the spectral and textural measures extracted from SPOT-5 images. Third, all-subsets regression was performed to build the predictive model by including the statistically significant image-derived measures as independent variables. Finally, the developed model was evaluated using the coefficient of determination (R2) and the root mean square error (RMSE). Additionally, the produced model was further validated for its performance using the leave-one-out cross-validation approach. The results indicated that our produced model could provide reliable, fast and economic means to assess and monitor forest health. A thematic map of forest health was finally produced to support forest health management

Estimation of Forest Structural Diversity Using the Spectral and Textural Information Derived from SPOT-5 Satellite Images

Uneven-aged forest management has received increasing attention in the past few years. Compared with even-aged plantations, the complex structure of uneven-aged forests complicates the formulation of management strategies. Forest structural diversity is expected to provide considerable significant information for uneven-aged forest management planning. In the present study, we investigated the potential of using SPOT-5 satellite images for extracting forest structural diversity. Forest stand variables were calculated from the field plots, whereas spectral and textural measures were derived from the corresponding satellite images. We firstly employed Pearson’s correlation analysis to examine the relationship between the forest stand variables and the image-derived measures. Secondly, we performed all possible subsets multiple linear regression to produce models by including the image-derived measures, which showed significant correlations with the forest stand variables, used as independent variables. The produced models were evaluated with the adjusted coefficient of determination (R 2 adj) and the root mean square error (RMSE). Furthermore, a ten-fold cross-validation approach was used to validate the best-fitting models (R 2 adj \u3e 0.5). The results indicated that basal area, stand volume, the Shannon index, Simpson index, Pielou index, standard deviation of DBHs, diameter differentiation index and species intermingling index could be reliably predicted using the spectral or textural measures extracted from SPOT-5 satellite images

Ultrasound characteristics of the cervical vagus nerve in patients with type 2 diabetes and diabetic peripheral neuropathy

Introduction: Diabetic peripheral neuropathy (DPN) and autonomic neuropathy are commonly coexistent in patients with type 2 diabetes mellitus (T2DM). Current assessment tools for diabetic neuropathy remain complicated and limited. We aimed to investigate the sonographic changes of the cervical vagus nerve in DPN patients with T2DM. Material and methods: Patients with T2DM were divided into a DPN group (DPN, n = 44) and non-DPN controls (NDPN, n = 43) based on electromyogram results. Another 43 healthy controls (CON) were included. High-frequency ultrasound (HFU) of the vagus nerve was performed in all participants. Results: Compared with controls, the honeycomb structure of the vagus nerve in patients with T2DM decreased, p < 0.001. The DPN group had higher cross-sectional area (CSA) of the right vagus nerve than the NDPN group (1.60 ± 0.52 vs. 2.00 ± 0.57 mm2, p =0.001). Logistic regression showed that right vagus nerve CSA was a risk factor of DPN (odds ratio [OR] = 3.924, p = 0.002). Right vagus nerve CSA was positively correlated with diabetes duration (p = 0.003), and negatively correlated with the motor conduction velocity (MCV) of the ulnar, median, and common peroneal nerves (p < 0.001 for all), as well as the sensor conduction velocity (SCV) of the ulnar and median nerve (both p < 0.005). Conclusion: HFU shows thickening of the cervical vagus nerve in patients with DPN, which is a potential diagnostic feature of diabetic neuropathy

AhNRAMP1 Enhances Manganese and Zinc Uptake in Plants

Manganese (Mn) and zinc (Zn) play essential roles in plants. Members of the natural resistance-associated macrophage protein (NRAMP) family transport divalent metal ions. In this research, the function of peanut (Arachis hypogaea L.) AhNRAMP1 in transporting Mn and Zn, as well as its potential for iron(Fe) and Zn biofortification was examined. AhNRAMP1 transcription was strongly induced by Mn- or Zn-deficiency in roots and stems of peanut. Yeast complementation assays suggested that AhNRAMP1 encoded a functional Mn and Zn transporter. Exogenous expression of AhNRAMP1 in tobacco and rice enhanced Mn or Zn concentrations, improving tolerance to Mn or Zn deficiency. With higher Mn concentration, transgenic plants exhibited inhibited growth under Mn excess condition; similar results were obtained under excessive Zn treatment. AhNRAMP1 expression increased biomass in transgenic tobacco and rice, as well as yield in transgenic rice grown on calcareous soil. Compared with non-transformed (NT) plants, Fe and Zn concentrations were elevated whereas concentrations of Mn, copper (Cu), and cadmium (Cd) were not enhanced. These results revealed that AhNRAMP1 contributes to Mn and Zn transport in plants and may be a candidate gene for Fe and Zn biofortification

Secondary metabolites of Alternaria: A comprehensive review of chemical diversity and pharmacological properties

Fungi are considered to be one of the wealthiest sources of bio-metabolites that can be employed for yielding novel biomedical agents. Alternaria, including parasitic, saprophytic, and endophytic species, is a kind of dark fungi that can produce a broad array of secondary metabolites (SMs) widely distributed in many ecosystems. These are categorized into polyketides, nitrogen-containing compounds, quinones, terpenes, and others based on the unique structural features of the metabolites. New natural products derived from Alternaria exhibit excellent bioactivities characterized by antibacterial, antitumor, antioxidative, phytotoxic, and enzyme inhibitory properties. Thus, the bio-metabolites of Alternaria species are significantly meaningful for pharmaceutical, industrial, biotechnological, and medicinal applications. To update the catalog of secondary metabolites synthesized by Alternaria fungi, 216 newly described metabolites isolated from Alternaria fungi were summarized with their diverse chemical structures, pharmacological activity, and possible biosynthetic pathway. In addition, possible insights, avenues, and challenges for future research and development of Alternaria are discussed

Determining thresholds for spatial urban design and transport features that support walking to create healthy and sustainable cities:findings from the IPEN Adult study

An essential characteristic of a healthy and sustainable city is a physically active population. Effective policies for healthy and sustainable cities require evidence-informed quantitative targets. We aimed to identify the minimum thresholds for urban design and transport features associated with two physical activity criteria: at least 80% probability of engaging in any walking for transport and WHO's target of at least 15% relative reduction in insufficient physical activity through walking. The International Physical Activity and the Environment Network Adult (known as IPEN) study (N=11 615; 14 cities across ten countries) provided data on local urban design and transport features linked to walking. Associations of these features with the probability of engaging in any walking for transport and sufficient physical activity (≥150 min/week) by walking were estimated, and thresholds associated with the physical activity criteria were determined. Curvilinear associations of population, street intersection, and public transport densities with walking were found. Neighbourhoods exceeding around 5700 people per km(2), 100 intersections per km(2), and 25 public transport stops per km(2) were associated with meeting one or both physical activity criteria. Shorter distances to the nearest park were associated with more physical activity. We use the results to suggest specific target values for each feature as benchmarks for progression towards creating healthy and sustainable cities

Discovery of PTN as a serum-based biomarker of pro-metastatic prostate cancer.

Distinguishing clinically significant from indolent prostate cancer (PC) is a major clinical challenge. We utilised targeted protein biomarker discovery approach to identify biomarkers specific for pro-metastatic PC. Serum samples from the cancer-free group; Cambridge Prognostic Group 1 (CPG1, low risk); CPG5 (high risk) and metastatic disease were analysed using Olink Proteomics panels. Tissue validation was performed by immunohistochemistry in a radical prostatectomy cohort (n = 234). We discovered that nine proteins (pleiotrophin (PTN), MK, PVRL4, EPHA2, TFPI-2, hK11, SYND1, ANGPT2, and hK14) were elevated in metastatic PC patients when compared to other groups. PTN levels were increased in serum from men with CPG5 compared to benign and CPG1. High tissue PTN level was an independent predictor of biochemical recurrence and metastatic progression in low- and intermediate-grade disease. These findings suggest that PTN may represent a novel biomarker for the presence of poor prognosis local disease with the potential to metastasise warranting further investigation

Multiperiod supply chain network equilibrium model with electronic commerce and multicriteria decision-making

In this paper, we develop a supply chain network equilibrium model in which electronic commerce in the presence of both B2B (business-to-business) and B2C (business-to-consumer) transactions, multiperiod decision-making and multicriteria decision-making are integrated. The model consists of three tiers of decision-makers (manufacturers, retailers and consumers at demand markets) who compete within a tier but may cooperate between tiers. Both manufacturers and retailers are concerned with maximization of profit as well as minimization of risk, whereas consumers take both the prices charged by manufacturers and retailers, along with the corresponding costs of transacting, in making their consumption decisions. Increasing relationship levels are assumed to decrease costs of transacting as well as risk costs. Establishing and maintaining these relationship levels incur some costs that have to be borne by the various decision-makers. We study the interaction among different tiers of decision-makers, describe their multicriteria decision-making behavior and derive the optimality conditions as well as the equilibrium conditions which are then shown to satisfy a finite-dimensional variational inequality problem. We then establish qualitative properties of the equilibrium model under some reasonable assumptions and illustrate the model with several numerical examples