Interactions of Mean Climate Change and Climate Variability on Food Security Extremes

Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts

Hypoglycemic and hypolipidemic activity of aqueous leaf extract of Passiflora suberosa L

Leaves of Passiflora suberosa L. (Family: Passifloraceae; common name: wild passion fruit, devil’s pumpkin) are used in Sri Lankan traditional medicine for treating diabetes. The present study investigated the in vivo ability of P. suberosa leaves to manage blood sugar status and associated cholesterol levels. Mechanisms of action and toxicity were also determined. Phytochemical screening of aqueous extracts of P. suberosa leaves and carbohydrate content of the leaves were determined according to previously published methods. In two group of male mice (n = 9), effects on fasting and random blood glucose levels (BGLs) of different acute doses (0, 25, 50, 100 and 200 mg/kg) of the aqueous leaf extract (ALE) were evaluated at 1, 3, and 5 h post-treatment. In another set of mice, the fasting BGL was evaluated following treatment of 0 or 50 mg/kg ALE (dose prescribed in traditional medicine) for 30 consecutive days. The lipid profile, some mechanism of ALE action (diaphragm glucose uptake, glycogen content in the liver and skeletal muscles) and its toxicity (behavioural observation, food and water intake, hepatoxicity) were also assessed following 30-day treatment. However, sucrose and glucose tolerance tests and intestinal glucose uptake were conducted to determine portion of mechanisms of action following single dose of 50 mg/kg ALE. Phytochemical screening revealed the presence of alkaloids, unsaturated sterols, triterpenes, saponins, flavonoids, tannins and proanthocyanidins. Carbohydrate content of the leaves was 12.97%. The maximum hypoglycemic effect was observed after 4 h of 50 and 100 mg/kg ALE administration. The extract decreased fasting BGL (18%) following an oral sucrose challenge and inhibited (79%) glucose absorption from the intestine. Correspondingly, the levels of glycogen in the liver (61%) and in the skeletal muscles (57%) were found be higher than that of the control group. The levels of total cholesterol (17%) and tri-glyceraldehyde levels (12%) found to be reduced in treated groups. Furthermore, no significant toxic effects were observed in treated groups. The present results suggest that the leaves of P. suberosa can be used to manage blood glucose and cholesterol levels. Isolation of active compounds are recommended for further analysis

Anomaly detection in complex trading systems

System availability is one of the major requirements expected from systems in the trading domain. In order to prevent system outages that can deteriorate system availability, anomaly detection must be able to assess the status of the system and detect anomalies that can lead to failures on a real-time basis. This paper presents a framework for anomaly detection for complex trading systems based on supervised learning approaches. Multiple feature reduction techniques were experimented with, in order to eliminate the noisy features that were initially derived from the system parameters. A classification technique based on Radial Basis Function (RBF) kernel Support Vector Machine (SVM) along with a feature selection technique built on a tree-based ensemble displayed the most promising results

Mesophotic Hardground Revealed by Multidisciplinary Cruise on the Brazilian Equatorial Margin

The Amapá margin, part of the Brazilian Equatorial Margin (BEM), is a key region that plays a strategic role in the global climate balance between the North and South Atlantic Ocean as it is strictly tied to equatorial heat conveyance and the fresh/salt water equilibrium with the Amazon River. We performed a new scientific expedition on the Amapá continental shelf (ACS, northern part of the Amazon continental platform) collecting sediment and using instrumental observation at an unstudied site. We show here the preliminary outcomes following the applied methodologies for investigation. Geophysical, geological, and biological surveys were carried out within the ACS to (1) perform bathymetric and sonographic mapping, high-resolution sub-surface geophysical characterization of the deep environment of the margin of the continental platform, (2) characterize the habitats and benthic communities through underwater images and biological sampling, (3) collect benthic organisms for ecological and taxonomic studies, (4) define the mineralogical and (5) elemental components of sediments from the study region, and (6) identify their provenance. The geophysical data collection included the use of bathymetry, a sub-bottom profiler, side scan sonar, bathythermograph acquisition, moving vessel profiler, and a thermosalinograph. The geological data were obtained through mineralogical, elemental, and grain size analysis. The biological investigation involved epifauna/infauna characterization, microbial analysis, and eDNA analysis. The preliminary results of the geophysical mapping, shallow seismic, and ultrasonographic surveys endorsed the identification of a hard substrate in a mesophotic environment. The preliminary geological data allowed the identification of amphibole, feldspar, biotite, as well as other minerals (e.g., calcite, quartz, goethite, ilmenite) present in the substrata of the Amapá continental shelf. Silicon, iron, calcium, and aluminum composes ~85% of sediments from the ACS. Sand and clay are the main fraction from these sediments. Within the sediments, Polychaeta (Annelida) dominated, followed by Crustacea (Arthropoda), and Ophiuroidea (Echinodermata). Through TowCam videos, 35 taxons with diverse epifauna were recorded, including polychaetes, hydroids, algae, gastropods, anemones, cephalopods, crustaceans, fishes, and sea stars