The emergence of protometabolic reactions that evolved into today’s metabolic pathways is unclear. Now, evidence suggests that the chemical origin of biological carbon metabolism may have relied on ...the versatility of a single primitive C1 feedstock molecule — hydrogen cyanide.
Get on top of your chemistry! An “on water”, palladium‐catalyzed, phosphine‐free direct CH arylation of indoles, with iodoarenes at 25–30 °C, is disclosed (see scheme; ...TBDMS=N‐tert‐butyldimethylsilyl ether; SEM=N‐2‐(trimethylsilyl)ethoxymethyl; Bn=benzyl, Piv=pivabyl). The mildness of the reaction conditions permits the tolerance of a variety of N1‐protected indoles.
Ion conduction through graphene oxide (GO) nanosheets that is pH-switchable between H
+
(in acid) and OH
−
(in base) ions is demonstrated. This finding is the first observation of this type for ion ...conductive materials and demonstrates an example of stimuli-driven ion-conduction switching.
Ion conduction through graphene oxide nanosheets that is pH-switchable between H
+
and OH
−
ions is demonstrated.
Confronting the blue revolution Islam, Saidul
Confronting the blue revolution,
2014, 20140127, 2014, 2014-01-27, 2014-02-05
eBook
In Confronting the Blue Revolution, Md Saidul Islam uses the shrimp farming industry in Bangladesh and across the global South to show the social and environmental impact of industrialized ...aquaculture.
A central problem for the prebiotic synthesis of biological amino acids and nucleotides is to avoid the concomitant synthesis of undesired or irrelevant by-products. Additionally, multistep pathways ...require mechanisms that enable the sequential addition of reactants and purification of intermediates that are consistent with reasonable geochemical scenarios. Here, we show that 2-aminothiazole reacts selectively with two- and three-carbon sugars (glycolaldehyde and glyceraldehyde, respectively), which results in their accumulation and purification as stable crystalline aminals. This permits ribonucleotide synthesis, even from complex sugar mixtures. Remarkably, aminal formation also overcomes the thermodynamically favoured isomerization of glyceraldehyde into dihydroxyacetone because only the aminal of glyceraldehyde separates from the equilibrating mixture. Finally, we show that aminal formation provides a novel pathway to amino acids that avoids the synthesis of the non-proteinogenic α,α-disubstituted analogues. The common physicochemical mechanism that controls the proteinogenic amino acid and ribonucleotide assembly from prebiotic mixtures suggests that these essential classes of metabolite had a unified chemical origin.
The effect of interlayer distance and oxygen content on proton conductivity of graphite oxide is presented. Bulk-state proton conductivities were measured using coin-shaped pellets of three different ...graphite oxide samples, namely, H-GO, S-GO, and B-GO, generated respectively from the techniques of Hummers, Staudenmaier, and Brodie. The extent of oxidation, nature of functional groups, interlayer distances, and morphologies are studied through Raman spectroscopy, XPS, powder XRD pattern, and SEM images. The proton conductivities follow the trend H-GO > S-GO > B-GO. In the XPS study, the total oxygen contents were found to follow the trend H-GO > B-GO > S-GO, whereas the interlayer distances obtained from the powder XRD patterns show the trend H-GO > S-GO > B-GO. Beside the nature of the functional groups and extent of oxidation, the interlayer distance displays a significant effect on the proton conductivity values. The temperature-dependent Arrhenius plots reveal the activation energy (E a) of the samples as 0.274, 0.291, and 0.296 eV. These low E a values imply the Grotthuss mechanism for proton conduction. The high conductivity value and low activation energy of H-GO with a maximum interlayer distance indicate that hydronium ion’s rotational movement and re-formation of hydrogen bonds by the Grotthuss mechanism are supported by a more flexible interlayer. We propose that this physical insight might be considered to improve the proton conductivity through modulating layer distances not only in carbon allotropes but also in other materials.
•Seasonal rice extent and rice cropping intensity mapped for a major rice producing country.•Accurate rice area estimates derived at same level of detail as published agricultural statistics.•Rice ...classes validated to high levels of accuracy across all three seasons using field data observations.
Rice is the most consumed staple food in the world and a key crop for food security. Much of the world’s rice is produced and consumed in Asia where cropping intensity is often greater than 100% (more than one crop per year), yet this intensity is not sufficiently represented in many land use products. Agricultural practices and investments vary by season due to the different challenges faced, such as drought, salinity, or flooding, and the different requirements such as varietal choice, water source, inputs, and crop establishment methods. Thus, spatial and temporal information on the seasonal extent of rice is an important input to decision making related to increased agricultural productivity and the sustainable use of limited natural resources. The goal of this study was to demonstrate that hyper temporal moderate-resolution imaging spectroradiometer (MODIS) data can be used to map the spatial distribution of the seasonal rice crop extent and area. The study was conducted in Bangladesh where rice can be cropped once, twice, or three times a year.
MODIS normalized difference vegetation index (NDVI) maximum value composite (MVC) data at 500m resolution along with seasonal field-plot information from year 2010 were used to map rice crop extent and area for three seasons, boro (December/January–April), aus (April/May–June/July), and aman (July/August–November/December), in Bangladesh. A subset of the field-plot information was used to assess the pixel-level accuracy of the MODIS-derived rice area. Seasonal district-level rice area statistics were used to assess the accuracy of the rice area estimates. When compared to field-plot data, the maps of rice versus non-rice exceeded 90% accuracy in all three seasons and the accuracy of the five rice classes varied from 78% to 90% across the three seasons. On average, the MODIS-derived rice area estimates were 6% higher than the sub-national statistics during boro, 7% higher during aus, and 3% higher during the aman season. The MODIS-derived sub-national areas explained (R2 values) 96%, 93%, and 96% of the variability at the district level for boro, aus, and aman seasons, respectively.
The results demonstrated that the methods we applied for analysing and interpreting moderate spatial and high temporal resolution imagery can accurately capture the seasonal variability in rice crop extent and area. We discuss the robustness of the approach and highlight issues that must be addressed before similar methods are used across other areas of Asia where a mix of rainfed, irrigated, or supplemental irrigation permits single, double, and triple cropping in a single calendar year.
This paper introduces a special issue of Aquaculture that brings together the largest collection of research on aquaculture value chains compiled to date, comprising 19 individual papers and this ...introductory review. The introduction identifies five themes emerging from research on aquaculture value chains in the special issue, namely: multi-polarity, diversity and scale, dynamics of transformation, performance and equity, and technical and institutional innovation. Contrary to much research to date, the papers addressing these themes show how the expansion of aquaculture has resulted highly diverse configurations of production for consumption in the global South. Collectively, the papers highlight the need for greater attention to neglected value chain segments and categories of actor, modes of production, regulation, and innovation, and patterns of access to benefits. The papers synthesized also affirm the need for more rigorous and diverse future value chain research to illuminate the aquaculture sector's ongoing development, and contribute to the sustainable expansion as an increasingly important component of the global food system.
•Synthesis of five core themes on aquaculture value chain research.•Aquaculture value chains not as global as commonly thought.•Diverse configurations of aquaculture production, trade and consumption in global South.•Diverse approaches and methodologies for aquaculture value chain research available.•Research focus needed on value chains in context of wider global food system.
State-of-the-art healthcare technologies are incorporating advanced Artificial Intelligence (AI) models, allowing for rapid and easy disease diagnosis. However, most AI models are considered "black ...boxes," because there is no explanation for the decisions made by these models. Users may find it challenging to comprehend and interpret the results. Explainable AI (XAI) can explain the machine learning (ML) outputs and contribution of features in disease prediction models. Electroencephalography (EEG) is a potential predictive tool for understanding cortical impairment caused by an ischemic stroke and can be utilized for acute stroke prediction, neurologic prognosis, and post-stroke treatment. This study aims to utilize ML models to classify the ischemic stroke group and the healthy control group for acute stroke prediction in active states. Moreover, XAI tools (Eli5 and LIME) were utilized to explain the behavior of the model and determine the significant features that contribute to stroke prediction models. In this work, we studied 48 patients admitted to a hospital with acute ischemic stroke and 75 healthy adults who had no history of identified other neurological illnesses. EEG was obtained within three months following the onset of ischemic stroke symptoms using frontal, central, temporal, and occipital cortical electrodes (Fz, C1, T7, Oz). EEG data were collected in an active state (walking, working, and reading tasks). In the results of the ML approach, the Adaptive Gradient Boosting models showed around 80% accuracy for the classification of the control group and the stroke group. Eli5 and LIME were utilized to explain the behavior of the stroke prediction model and interpret the model locally around the prediction. The Eli5 and LIME interpretable models emphasized the spectral delta and theta features as local contributors to stroke prediction. From the findings of this explainable AI research, it is expected that the stroke-prediction XAI model will help with post-stroke treatment and recovery, as well as help healthcare professionals, make their diagnostic decisions more explainable.
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