Integration of Forage Production in Rice-Based Cropping Systems for Mitigating Forage Crisis of Ruminant Livestock - Studies in Bangladesh

Intensive rice cropping in Bangladesh is causing alarming shortages of forage and low ruminant productivity. This is also causing degeneration of soil fertility. Therefore it is imperative to identify some approach to integrate fodder production into rice cropping systems on rural farms. The integration of legume forage may improve soil fertility and soil structure, thus enhancing crop yield and may provide high quality feed for livestock (Haque 1992). Studies were done to investigate the effects of rice/forage integration on forage yield, soil fertility and also on milk yield of cows fed on the grown forages

Solvation free energy profile of the SCN- ion across the water-1,2-dichloroethane liquid/liquid interface. A computer simulation study

The solvation free energy profile of a single SCN- ion is calculated across the water-1,2-dichloroethane liquid/liquid interface at 298 K by the constraint force method. The obtained results show that the free energy cost of transferring the ion from the aqueous to the organic phase is about 70 kJ/mol, The free energy profile shows a small but clear well at the aqueous side of the interface, in the subsurface region of the water phase, indicating the ability of the SCN- ion to be adsorbed in the close vicinity of the interface. Upon entrance of the SCN- ion to the organic phase a coextraction of the water molecules of its first hydration shell occurs. Accordingly, when it is located at the boundary of the two phases the SCN- ion prefers orientations in which its bulky S atom is located at the aqueous side, and the small N atom, together with its first hydration shell, at the organic side of the interface

Elemental composition of vegetables cultivated over coal-mining waste

ABSTRACT We assessed elemental composition of the liver in mice subjected to one-time or chronic consumption of the juice of vegetables cultivated in a vegetable garden built over deposits of coal waste. Lactuca sativa L. (lettuce), Beta vulgaris L. (beet), Brassica oleracea L. var. italica (broccoli) and Brassica oleracea L. var. acephala (kale) were collected from the coal-mining area and from a certified organic farm (control). Elemental composition was analyzed by particle-induced X-ray emission (PIXE) method. Concentrations of Mg, S, and Ca of mice subjected to one-time consumption of broccoli and concentrations of these same elements plus Si of mice receiving kale were higher in the coal-mining area. Concentrations of P, K, and Cu were increase after chronic consumption of lettuce from the coal-mining area, whereas the levels of Si, P, K, Fe, and Zn were higher in the group consuming kale from the coal-mining area. Our data suggests that people consuming vegetables grown over coal wastes may ingest significant amounts of chemical elements that pose a risk to health, since these plants contain both essential and toxic metals in a wide range of concentrations, which can do more harm than good

Democratic population decisions result in robust policy-gradient learning: A parametric study with GPU simulations

High performance computing on the Graphics Processing Unit (GPU) is an emerging field driven by the promise of high computational power at a low cost. However, GPU programming is a non-trivial task and moreover architectural limitations raise the question of whether investing effort in this direction may be worthwhile. In this work, we use GPU programming to simulate a two-layer network of Integrate-and-Fire neurons with varying degrees of recurrent connectivity and investigate its ability to learn a simplified navigation task using a policy-gradient learning rule stemming from Reinforcement Learning. The purpose of this paper is twofold. First, we want to support the use of GPUs in the field of Computational Neuroscience. Second, using GPU computing power, we investigate the conditions under which the said architecture and learning rule demonstrate best performance. Our work indicates that networks featuring strong Mexican-Hat-shaped recurrent connections in the top layer, where decision making is governed by the formation of a stable activity bump in the neural population (a "non-democratic" mechanism), achieve mediocre learning results at best. In absence of recurrent connections, where all neurons "vote" independently ("democratic") for a decision via population vector readout, the task is generally learned better and more robustly. Our study would have been extremely difficult on a desktop computer without the use of GPU programming. We present the routines developed for this purpose and show that a speed improvement of 5x up to 42x is provided versus optimised Python code. The higher speed is achieved when we exploit the parallelism of the GPU in the search of learning parameters. This suggests that efficient GPU programming can significantly reduce the time needed for simulating networks of spiking neurons, particularly when multiple parameter configurations are investigated. © 2011 Richmond et al

Ionic liquids at electrified interfaces

Until recently, “room-temperature” (<100–150 °C) liquid-state electrochemistry was mostly electrochemistry of diluted electrolytes(1)–(4) where dissolved salt ions were surrounded by a considerable amount of solvent molecules. Highly concentrated liquid electrolytes were mostly considered in the narrow (albeit important) niche of high-temperature electrochemistry of molten inorganic salts(5-9) and in the even narrower niche of “first-generation” room temperature ionic liquids, RTILs (such as chloro-aluminates and alkylammonium nitrates).(10-14) The situation has changed dramatically in the 2000s after the discovery of new moisture- and temperature-stable RTILs.(15, 16) These days, the “later generation” RTILs attracted wide attention within the electrochemical community.(17-31) Indeed, RTILs, as a class of compounds, possess a unique combination of properties (high charge density, electrochemical stability, low/negligible volatility, tunable polarity, etc.) that make them very attractive substances from fundamental and application points of view.(32-38) Most importantly, they can mix with each other in “cocktails” of one’s choice to acquire the desired properties (e.g., wider temperature range of the liquid phase(39, 40)) and can serve as almost “universal” solvents.(37, 41, 42) It is worth noting here one of the advantages of RTILs as compared to their high-temperature molten salt (HTMS)(43) “sister-systems”.(44) In RTILs the dissolved molecules are not imbedded in a harsh high temperature environment which could be destructive for many classes of fragile (organic) molecules

Evaluation of metals that are potentially toxic to agricultural surface soils, using statistical analysis, in northwestern Saudi Arabia

© 2015, Springer-Verlag Berlin Heidelberg. Heavy metals in agricultural soils enter the food chain when taken up by plants. The main purpose of this work is to determine metal contamination in agricultural farms in northwestern Saudi Arabia. Fifty surface soil samples were collected from agricultural areas. The study focuses on the geochemical behavior of As, Cd, Co, Cr, Cu, Hg, Pb and Zn, and determines the enrichment factor and geoaccumulation index. Multivariate statistical analysis, including principle component analysis and cluster analysis, is also applied to the acquired data. The study shows considerable variation in the concentrations of the analyzed metals in the studied soil samples. This variation in concentration is attributed to the intensity of agricultural activities and, possibly, to nearby fossil fuel combustion activities, as well as to traffic flows from highways and local roads. Multivariate analysis suggests that As, Cd, Hg and Pb are associated with anthropogenic activities, whereas Co, Cr, Cu and Zn are mainly controlled by geogenic activities. Hg and Pb show the maximum concentration in the analyzed samples as compared to the background concentration

The role of hypothalamic H1 receptor antagonism in antipsychotic-induced weight gain

Treatment with second generation antipsychotics (SGAs), notably olanzapine and clozapine, causes severe obesity side effects. Antagonism of histamine H1 receptors has been identified as a main cause of SGA-induced obesity, but the molecular mechanisms associated with this antagonism in different stages of SGA-induced weight gain remain unclear. This review aims to explore the potential role of hypothalamic histamine H1 receptors in different stages of SGA-induced weight gain/obesity and the molecular pathways related to SGA-induced antagonism of these receptors. Initial data have demonstrated the importance of hypothalamic H1 receptors in both short- and long-term SGA-induced obesity. Blocking hypothalamic H1 receptors by SGAs activates AMP-activated protein kinase (AMPK), a well-known feeding regulator. During short-term treatment, hypothalamic H1 receptor antagonism by SGAs may activate the AMPK—carnitine palmitoyltransferase 1 signaling to rapidly increase caloric intake and result in weight gain. During long-term SGA treatment, hypothalamic H1 receptor antagonism can reduce thermogenesis, possibly by inhibiting the sympathetic outflows to the brainstem rostral raphe pallidus and rostral ventrolateral medulla, therefore decreasing brown adipose tissue thermogenesis. Additionally, blocking of hypothalamic H1 receptors by SGAs may also contribute to fat accumulation by decreasing lipolysis but increasing lipogenesis in white adipose tissue. In summary, antagonism of hypothalamic H1 receptors by SGAs may time-dependently affect the hypothalamus-brainstem circuits to cause weight gain by stimulating appetite and fat accumulation but reducing energy expenditure. The H1 receptor and its downstream signaling molecules could be valuable targets for the design of new compounds for treating SGA-induced weight gain/obesity

Action to protect the independence and integrity of global health research

Storeng KT, Abimbola S, Balabanova D, et al. Action to protect the independence and integrity of global health research. BMJ GLOBAL HEALTH. 2019;4(3): e001746