Functional group analysis by H NMR/chemical derivatization for the characterization of organic aerosol from the SMOCC field campaign

Water soluble organic compounds (WSOC) in aerosol samples collected in the Amazon Basin in a period encompassing the middle/late dry season and the beginning of the wet season, were investigated by H NMR spectroscopy. HiVol filter samples (PM2.5 and PM>2.5) and size-segregated samples from multistage impactor were subjected to H NMR characterization. The H NMR methodology, recently developed for the analysis of organic aerosol samples, has been improved by exploiting chemical methylation of carboxylic groups with diazomethane, which allows the direct determination of the carboxylic acid content of WSOC. The content of carboxylic carbons for the different periods and sizes ranged from 12% to 20% of total measured carbon depending on the season and aerosol size, with higher contents for the fine particles in the transition and wet periods with respect to the dry period. A comprehensive picture is presented of WSOC functional groups in aerosol samples representative of the biomass burning period, as well as of transition and semi-clean atmospheric conditions. A difference in composition between fine (PM2.5) and coarse (PM>2.5) size fractions emerged from the NMR data, the former showing higher alkylic content, the latter being largely dominated by R-O-H (or R-O-R') functional groups. Very small particles (<0.14 &mu;m), however, present higher alkyl-chain content and less oxygenated carbons than larger fine particles (0.42&ndash;1.2 &mu;m). More limited variations were found between the average compositions in the different periods of the campaign

Source Code Classification for Energy Efficiency in Parallel Ultra Low-Power Microcontrollers

The analysis of source code through machine learning techniques is an increasingly explored research topic aiming at increasing smartness in the software toolchain to exploit modern architectures in the best possible way. In the case of low-power, parallel embedded architectures, this means finding the configuration, for instance in terms of the number of cores, leading to minimum energy consumption. Depending on the kernel to be executed, the energy optimal scaling configuration is not trivial. While recent work has focused on general-purpose systems to learn and predict the best execution target in terms of the execution time of a snippet of code or kernel (e.g. offload OpenCL kernel on multicore CPU or GPU), in this work we focus on static compile-time features to assess if they can be successfully used to predict the minimum energy configuration on PULP, an ultra-low-power architecture featuring an on-chip cluster of RISC-V processors. Experiments show that using machine learning models on the source code to select the best energy scaling configuration automatically is viable and has the potential to be used in the context of automatic system configuration for energy minimisation

Sustained low-efficiency dialysis (SLED) with prostacyclin in critically ill patients with acute renal failure

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Scalable Hierarchical Instruction Cache for Ultralow-Power Processors Clusters

High performance and energy efficiency are critical requirements for Internet of Things (IoT) end-nodes. Exploiting tightly coupled clusters of programmable processors (CMPs) has recently emerged as a suitable solution to address this challenge. One of the main bottlenecks limiting the performance and energy efficiency of these systems is the instruction cache architecture due to its criticality in terms of timing (i.e., maximum operating frequency), bandwidth, and power. We propose a hierarchical instruction cache tailored to ultralow-power (ULP) tightly coupled processor clusters where a relatively large cache (L1.5) is shared by L1 private (PR) caches through a two-cycle latency interconnect. To address the performance loss caused by the L1 capacity misses, we introduce a next-line prefetcher with cache probe filtering (CPF) from L1 to L1.5. We optimize the core instruction fetch (IF) stage by removing the critical core-to-L1 combinational path. We present a detailed comparison of instruction cache architectures' performance and energy efficiency for parallel ULP (PULP) clusters. Focusing on the implementation, our two-level instruction cache provides better scalability than existing shared caches, delivering up to 20% higher operating frequency. On average, the proposed two-level cache improves maximum performance by up to 17% compared to the state-of-the-art while delivering similar energy efficiency for most relevant applications

Species diversity and community composition of native arbuscular mycorrhizal fungi in apple roots are affected by site and orchard management

Arbuscular mycorrhizal fungi (AMF) are beneficial microrganisms which establish mutualistic symbioses with the roots of most food crops, improving plant performance, nutrient uptake and tolerance to biotic and abiotic stresses. A better understanding of the factors affecting AMF occurrence and diversity is fundamental to implement sustainable agricultural managements effectively profiting from beneficial plant symbionts. Here, we investigated AMF occurrence, diversity and community composition in the roots of apple trees from 21 orchards in South Tyrol, as affected by location, management (organic vs integrated) and altitude, by PCR cloning and sequencing and PCR-DGGE of partial 18S rRNA gene. The screening of 448 clones from 21 clone libraries allowed the identification of 6 native AMF at the species level: Glomus indicum, Sclerocystis sinuosa, Funneliformis mosseae, Rhizoglomus irregulare, Septoglomus constrictus and Claroideoglomus lamellosum. The most abundant genera were represented by Glomus (29.7% of the sequences), Paraglomus (19.4%), Claroideoglomus (17.2%), Sclerocystis (16.1%) and Rhizoglomus (12.3%). Septoglomus, Diversispora and Funneliformis sequences corresponded to less than 4% of total sequences. Although the degree of root colonization was unaffected by treatments, ANOSIM analysis of PCR-DGGE clusters revealed significant differences in apple root AMF diversity between sites and agricultural managements. Species richness was significantly higher in organically managed orchards than in integrated ones. Our findings provide insights into important factors affecting native AMF communities of apple trees, which could be exploited in sustainable fruit production systems, where beneficial soil biota boost biogeochemical cycles, energy fluxes and crop productivity

Grape pomace for topical application: Green nades sustainable extraction, skin permeation studies, antioxidant and anti-inflammatory activities characterization in 3d human keratinocytes

Food waste is a global problem due to its environmental and economic impact, so there is great demand for the exploitation of new functional applications. The winemaking process leads to an incomplete extraction of high-value compounds, leaving the pomace still rich in polyphenols. This study was aimed at optimising and validating sustainable routes toward the extraction and further valorisation of these polyphenols, particularly for cosmeceutical applications. New formulations based on red grape pomace polyphenols and natural deep eutectic solvents (NaDESs) were here investigated, namely betaine combined with citric acid (BET-CA), urea (BET-U) and ethylene glycol (BET-EG), in which DESs were used both as extracting and carrying agents for polyphenols. The flavonoid profile determined by HPLC-MS/MS analysis showed similar malvidin content (51\u201356 \ub5g mL 121 ) in the DES combinations, while BET-CA gave the best permeation performance in Franz cells, so it was further investigated in 3D human keratinocytes (HaCat spheroids) injured with the pro-oxidant agent menadione. BET-CA treatment showed good intracellular antioxidant activity (IC50 0.15 \ub1 0.02 \ub5g mL 121 in malvidin content) and significantly decreased (p &lt; 0.001) the release of the pro-inflammatory cytokine IL-8, improving cell viability. Thus, BET-CA formulation is worthy of investigation for potential use as a cosmetic ingredient to reduce oxidative stress and inflammation, which are causes of skin aging

MuSCA: A multi-scale source-sink carbon allocation model to explore carbon allocation in plants. An application to static apple tree structures

Background and aims: Carbon allocation in plants is usually represented at a topological scale, specific to each model. This makes the results obtained with different models, and the impact of their scales of representation, difficult to compare. In this study, we developed a multi-scale carbon allocation model (MuSCA) that allows the use of different, user-defined, topological scales of a plant, and assessment of the impact of each spatial scale on simulated results and computation time. Methods: Model multi-scale consistency and behaviour were tested on three realistic apple tree structures. Carbon allocation was computed at five scales, spanning from the metamer (the finest scale, used as a reference) up to first-order branches, and for different values of a sap friction coefficient. Fruit dry mass increments were compared across spatial scales and with field data. Key Results: The model was able to represent effects of competition for carbon assimilates on fruit growth. Intermediate friction parameter values provided results that best fitted field data. Fruit growth simulated at the metamer scale differed of ~1 % in respect to results obtained at growth unit scale and up to 60 % in respect to first order branch and fruiting unit scales. Generally, the coarser the spatial scale the more predicted fruit growth diverged from the reference. Coherence in fruit growth across scales was also differentially impacted, depending on the tree structure considered. Decreasing the topological resolution reduced computation time by up to four orders of magnitude. Conclusions: MuSCA revealed that the topological scale has a major influence on the simulation of carbon allocation. This suggests that the scale should be a factor that is carefully evaluated when using a carbon allocation model, or when comparing results produced by different models. Finally, with MuSCA, trade-off between computation time and prediction accuracy can be evaluated by changing topological scales

Towards an OpenMP Specification for Critical Real-Time Systems

OpenMP is increasingly being considered as a convenient parallel programming model to cope with the performance requirements of critical real-time systems. Recent works demonstrate that OpenMP enables to derive guarantees on the functional and timing behavior of the system, a fundamental requirement of such systems. These works, however, focus only on the exploitation of fine grain parallelism and do not take into account the peculiarities of critical real-time systems, commonly composed of a set of concurrent functionalities. OpenMP allows exploiting the parallelism exposed within real-time tasks and among them. This paper analyzes the challenges of combining the concurrency model of real-time tasks with the parallel model of OpenMP. We demonstrate that OpenMP is suitable to develop advanced critical real-time systems by virtue of few changes on the specification, which allow the scheduling behavior desired (regarding execution priorities, preemption, migration and allocation strategies) in such systems.The research leading to these results has received funding from the Spanish Ministry of Science and Innovation, under contract TIN2015-65316-P, and from the European Union's Horizon 2020 Programme under the CLASS Project (www.classproject. eu), grant agreement No 780622.Peer ReviewedPostprint (author's final draft

Pathogenic A&#946; A2V versus protective A&#946; A2T mutation : early stage aggregation and membrane interaction

We investigated the effects of punctual A-to-V and A-to-T mutations in the amyloid precursor protein APP, corresponding to position 2 of A\u3b21\u201342. Those mutations had opposite effects on the onset and progression of Alzheimer disease, the former inducing early AD pathology and the latter protecting against the onset of the disease. We applied Static and Dynamic Light Scattering and Circular Dichroism, to study the different mutants in the early stages of the aggregation process, essential for the disease. Comparative results showed that the aggregation pathways differ in the kinetics and extent of the process, in the size of the aggregates and in the evolution of the secondary structure, resulting in fibrils of different morphology, as seen by AFM. Mutated peptides had comparable toxic effects on N2a cells. Moreover, as assessed by X-ray scattering, all of them displayed disordering effects on the internal structure of mixed phospholipids-gangliosides model membranes

Recycling of multilayer packaging waste with switchable anionic surfactants

Switchable Anionic Surfactants (SAS) were used for delaminating flexible packaging waste composed of various plastic layers and aluminium, thereby promoting the recycling of such waste streams from a circular economy perspective. The delamination protocol was optimized on de-pulped food and beverage cartons containing low-density polyethylene (LDPE) and aluminium, varying the carboxylic acid and its counterion constituting the SAS (C8[sbnd]C18 carboxylic acids as the anionic part; inorganic bases and primary, secondary and tertiary amines as the cationic one) their molar ratio (carboxylic acid: base molar ratio from 1:1 to 1:3), SAS concentration (0.15, 0.3 and 0.5 wt%), time (0.5–3 h) and material weight in input (1–10 wt%). High-quality LDPE and aluminium were separated and recovered by using a diluted solution of a surfactant based on lauric acid and triethanolamine (C12-TEA), with performances not achievable with other anionic or cationic surfactants available on the market. The C12-TEA solution was then applied to a large variety of multilayer waste materials composed of polypropylene and aluminium, polyolefins/polyethylene terephthalate/aluminium, giving a material separation dependant on the structure and composition of the material in input. At the end of the process, lauric acid was recovered from the aqueous solution used for washing the separated materials by tuning its water solubility with CO2