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The mid-infrared lightweight tunable diode laser hygrometer, "Pico-Light H 2 O", the successor to Pico-SDLA H 2 O, is presented and its performances are evaluated during the AsA 2022 balloon-borne intercomparison campaign conducted at the CNES Aire-sur-l'Adour (AsA, 43.70° N; 0.25° W) balloon launch facility and the Aeroclub d'Aire-sur-l'Adour in France. The Pico-Light instrument has primarily been developed for sounding of the upper troposphere and stratosphere, although during the AsA 2022 campaign we expand the range of comparison to include additionally the lower troposphere. Three different types of hygrometer and two models of radiosonde were flown, operated by the French Space Agency (CNES) and the NOAA Global Monitoring Laboratory (GML) scientific teams: Pico-Light H 2 O, the NOAA Frost Point Hygrometer (FPH), the micro-hygrometer (in an early phase of development), and M20 and iMet-4 sondes. Within this framework, we intend to validate measurements of Pico-Light H 2 O through a first intercomparison with the NOAA FPH instrument. The in situ monitoring of water vapour in the upper troposphere–lower stratosphere continues to be very challenging from an instrumental point of view because of the very small amounts of water vapour to be measured in these regions of the atmosphere. Between the lapse rate tropopause (11–12.3 km) and 20 km, the mean relative difference between water vapour mixing ratio measurements by Pico-Light H 2 O and NOAA FPH was 4.2 % ± 7.7 %, and the mean tropospheric difference was 3.84 % ± 23.64 %, with differences depending on the altitude range considered. In the troposphere, relative humidity (RH) over water comparisons led to agreement between Pico-Light and NOAA FPH of - 0.2 % on average, with excursions of about 30 % RH due to moisture variability. Expanding the comparison to meteorological sondes, the iMet-4 sondes agree well with both Pico-Light and FPH between the ground and 7.5 km (within ± 3 % RH), as do the M20 sondes, up to 13 km, which are wet-biased by 3 % RH and dry-biased by 20 % in cases of saturation. [ABSTRACT FROM AUTHOR]

The mid-infrared lightweight stratospheric hygrometer, "Pico-Light H2O", the successor of Pico-SDLA H2O, is presented and its performances are evaluated during the AsA 2022 balloon-borne intercomparison campaign conducted at CNES Aire-sur-l'Adour (AsA) balloon launch facility and the Aeroclub d'Aire-sur-l'Adour. The Pico-Light instrument primarily been developed for sounding of the upper troposphere and stratosphere. Though, during the AsA 2022 campaign we expand the range of comparison including the lower troposphere additionally. Three different types of hygrometers and two models of radiosonde were flown, operated by the French Space Agency (CNES) and the NOAA Global Monitoring Laboratory (GML) scientific teams: Pico-Light H2O, the NOAA Frost Point Hygrometer (FPH), the micro hygrometer (in an early phase of development), M20 and iMet-4 sondes. In this frame, we intend to validate measurements of Pico-Light H2O through a first intercomparison with the NOAA FPH instrument. The in situ monitoring of water vapour in the UT-LS keeps being very challenging from an instrumental point of view because of the very small amounts of water vapour to be measured in these regions of the atmosphere. Between the lapse rate tropopause (11 to 12.3 km) and 20 km, the mean relative difference between water vapour mixing ratio measurements by Pico-Light H2O and NOAA FPH was (4.2 ± 7.7) %, mean tropospheric difference is was (3.84 ± 23.64)%, with differences depending on the altitude range considered. In the troposphere, relative humidity over water (RH) comparisons leads to an agreement between both Pico-Light and NOAA FPH of -0.2% on average, with excursions of about 30% RH due to moisture variability. Expanding the comparison to meteorological sondes, the iMet-4 sondes agree well with both Pico-Light and FPH between ground and 7.5 km (within ± 3% RH) and so does for M20 sondes, up to 13 km, which are wet biased by 3% RH and dry biased by 20% in case of saturation. [ABSTRACT FROM AUTHOR]

This article presents a fast and approximate multifrontal solver for large sparse linear systems. In a recent work by Liu et al., we showed the efficiency of a multifrontal solver leveraging the butterfly algorithm and its hierarchical matrix extension, HODBF (hierarchical off-diagonal butterfly) compression to compress large frontal matrices. The resulting multifrontal solver can attain quasi-linear computation and memory complexity when applied to sparse linear systems arising from spatial discretization of high-frequency wave equations. To further reduce the overall number of operations and especially the factorization memory usage to scale to larger problem sizes, in this article we develop a composite multifrontal solver that employs the HODBF format for large-sized fronts, a reduced-memory version of the nonhierarchical block low-rank format for medium-sized fronts, and a lossy compression format for small-sized fronts. This allows us to solve sparse linear systems of dimension up to 2.7 × larger than before and leads to a memory consumption that is reduced by 70% while ensuring the same execution time. The code is made publicly available in GitHub. [ABSTRACT FROM AUTHOR]

• Implemented K-CliqueWeight into the ProBiS-Dock algorithm, enhancing its capabilities for molecular docking. • Efficiently identifies the top N weighted k-cliques, addressing challenges in molecular docking and diverse problem domains. • Demonstrated superior performance of K-CliqueWeight, surpassing alternatives by several orders of magnitude. • Accessible to academia for free at http://insilab.org/kcliqueweight, facilitating widespread use. Molecular docking, a key process in drug discovery, is often used in the discovery of new bioactive compounds. In this technique, small molecules are systematically placed at a protein binding site to identify the ligands with the highest binding affinity. Here we have developed a new graph-theoretical algorithm called K-CliqueWeight. This algorithm efficiently identifies the top N highest weight k-cliques in different types of vertex-weighted graphs and can serve as a building block for various algorithms addressing different problems, including molecular docking. K-CliqueWeight and its variant K-CliqueDynWeight are extensions of our established and widely used maximum clique algorithm. Our new algorithm uses a novel approach to approximate graph coloring and provides efficient upper bounds on the size and weight of a k-clique within the branch-and-bound algorithm. It outperforms alternative methods and often shows a speedup of several orders of magnitude. Rigorous tests with general random graphs and those specifically designed for docking confirm its exceptional performance. K-CliqueWeight has been integrated into the existing ProBiS-Dock algorithm for molecular docking. The algorithm is freely available to the academic community at http://insilab.org/kcliqueweight. [Display omitted] [ABSTRACT FROM AUTHOR]

We present a fast and approximate multifrontal solver for large-scale sparse linear systems arising from finite-difference, finite-volume, or finite-element discretization of high-frequency wave equations. The proposed solver leverages the butterfly algorithm and its hierarchical matrix extension for compressing and factorizing large frontal matrices via graph distance guided entry evaluation or randomized matrix-vector multiplication-based schemes. Complexity analysis and numerical experiments demonstrate O (N log² N) computation and O (N) memory complexity when applied to an N X N sparse system arising from 3D high-frequency Helmholtz and Maxwell problems. [ABSTRACT FROM AUTHOR]

We present and discuss the advancements made in PyRETIS 3, the third instalment of our Python library for an efficient and user‐friendly rare event simulation, focused to execute molecular simulations with replica exchange transition interface sampling (RETIS) and its variations. Apart from a general rewiring of the internal code towards a more modular structure, several recently developed sampling strategies have been implemented. These include recently developed Monte Carlo moves to increase path decorrelation and convergence rate, and new ensemble definitions to handle the challenges of long‐lived metastable states and transitions with unbounded reactant and product states. Additionally, the post‐analysis software PyVisa is now embedded in the main code, allowing fast use of machine‐learning algorithms for clustering and visualising collective variables in the simulation data. [ABSTRACT FROM AUTHOR]

This work pioneers the thermocatalytic conversion of tagua seeds (or ivory nut) from the palm Phytelephas aequatorialis into key chemical building blocks, being levoglucosenone, furfural and levomannosan. Annually, ca. 100,000 metric ton of those seeds are produced in Ecuador. Mannan (a mannose-polymer similar to cellulose) is the main constituent in tagua. Thermocatalytic conversions were first explored on analytical scale to see if – and to which extent – e.g., levoglucosenone, was obtained from tagua, using catalysts with proven activity for cellulose conversion, being H3PO4 or ZnCl2. Non-catalytic fast pyrolysis led to levomannosan as main product (33.89 wt% ± 0.24 wt%), much like levoglucosan is the main product from cellulose pyrolysis. Catalytic fast pyrolysis using H3PO4 or ZnCl2 resulted in value-added levoglucosenone (max 6.64 wt% ± 0.27 wt%) and furfural (max 13.17 wt% ± 0.66 wt%) at the expense of levomannosan (between 12 wt.%–14 wt%). Validation experiments with a continuous fast pyrolysis auger reactor were successful and led to pyrolysis liquids with e.g., 3.69 wt% levoglucosenone, using H3PO4 -infused ivory nut. Although further optimization should follow this work, the results showcased a fundamental "mannan to levoglucosenone and furfural" conversion and therefore the potential of mannan-rich feedstock for biorefining. Moreover, these results can be translated to other mannan-rich agricultural residues, like açaí seeds, which are a major residue in Brazil (1.1 million metric ton annually). [Display omitted] • Mannan-rich tagua was demonstrated a valuable biorefinery feedstock. • Tagua was converted to levoglucosenone and furfural with H 3 PO 4 and ZnCl 2 , resp. • Analytical experiments were successfully translated to mini-plant scale experiments. • The biorefinery potential of mannan-rich ivory nut has been showcased. [ABSTRACT FROM AUTHOR]

We have ported the numerical factorization and triangular solve phases of the sparse direct solver STRUMPACK to GPU. STRUMPACK implements sparse LU factorization using the multifrontal algorithm, which performs most of its operations in dense linear algebra operations on so-called frontal matrices of various sizes. Our GPU implementation off-loads these dense linear algebra operations, as well as the sparse scatter–gather operations between frontal matrices. For the larger frontal matrices, our GPU implementation relies on vendor libraries such as cuBLAS and cuSOLVER for NVIDIA GPUs and rocBLAS and rocSOLVER for AMD GPUs. For the smaller frontal matrices we developed custom CUDA and HIP kernels to reduce kernel launch overhead. Overall, high performance is achieved by identifying submatrix factorizations corresponding to sub-trees of the multifrontal assembly tree which fit entirely in GPU memory. The multi-GPU setting uses SLATE (Software for Linear Algebra Targeting Exascale) as a modern GPU-aware replacement for ScaLAPACK. On 4 nodes of SUMMIT the code runs ∼ 10 × faster when using all 24 V100 GPUs compared to when it only uses the 168 POWER9 cores. On 8 SUMMIT nodes, using 48 V100 GPUs, the sparse solver reaches over 50TFlop/s. Compared to SuperLU, on a single V100, for a set of 17 matrices our implementation is faster for all but one matrix, and is on average 5 × (median 4 ×) faster • Ported the numerical factorization and triangular solve phases of the sparse direct multifrontal solver STRUMPACK to GPU. • GPU off-loading of dense linear algebra operations, as well as the sparse scatter–gather operations between frontal matrices. • Relying on vendor libraries such as cuBLAS and cuSOLVER for Nvidia GPUs and rocBLAS and rocSOLVER for AMD GPUs. • Multi-GPU setting uses SLATE (Software for Linear Algebra Targeting Exascale) as a modern GPU-aware replacement for ScaLAPACK. • On 4 nodes of SUMMIT the code runs ∼ 10 × faster when using all 24 V100 GPUs compared to when it only uses the 168 POWER9 cores. On 8 SUMMIT nodes, using 48 V100 GPUs, the sparse solver reaches over 50TFlop/s. Compared to SuperLU, on a single V100, for a set of 17 matrices our implementation is faster for all but one matrix, and is on average 5x faster. [ABSTRACT FROM AUTHOR]

• Acid leaching breaks down the chemical structure of carbohydrates and proteins. • Pretreatment effects on pyrolysis volatiles have been discussed. • Removal of inorganics increased the relative yields in aromatics and aliphatics. • Influence of water-soluble and acid-soluble AAEM species was discussed. • Interactions between microalgae components and AAEMs catalysis were elucidated. This study compared the volatiles distribution in analytical scale pyrolysis (py-GC–MS) of Nannochloropsis gaditana (marine microalgae) and Scenedesmus almeriensis (freshwater microalgae) and their demineralized counterparts. The role of inorganic elements and their removal via ultrasonic treatment, water washing and (in)organic acid leaching were elucidated. Principal component analysis (PCA) and grey relational analysis were applied to analyze the pyrolysis volatiles distribution and demonstrate the influence of inorganic elements in pyrolysis, respectively. Demineralization affects (breaks down) the chemical structure of carbohydrates, followed by (to a lesser extent) proteins and lipids. Acid leaching promoted hydrolysis and suppressed the catalytic effect associated to inorganic elements in subsequent pyrolysis, compared to ultrasonic treatment and water washing. Elements like K and Na had a larger catalytic influence on microalgae pyrolysis than Ca and Mg. The composition and pyrolytic formation mechanism of major product groups at 500 °C were studied, including anhydrosugars, phenolics, furans, carboxylic acids, alcohols, aliphatic hydrocarbons, aromatic hydrocarbons, N-heterocyclic compounds, nitriles and amides. The results indicate that demineralization shows positive effects on fast pyrolysis of microalgae: (1) by disrupting the cell wall and releasing the lipids and cellular contents. Based on the py-GC–MS peak area normalized to sample mass, the relative contribution of hydrocarbons in the pyrolysis vapors increased from 25.5 % (NG: Nannochloropsis gaditana) to 32.1 % (NG-HCl: Nannochloropsis gaditana, HCl treated), and from 16.1 % (SA: Scenedesmus almeriensis) to 22.4 % (SA-HCl: Scenedesmus almeriensis, HCl treated); (2) by decreasing the relative yields in O-containing compounds resulting from the suppressed catalytic effects of alkali and alkaline earth metals (53.3 % (NG) to 37.1 % (NG-HCl), 57.5 % (SA) to 47.8 % (SA-HCl)) that would otherwise have been present in non-demineralized microalgae feedstock. The effects of demineralization on the denitrogenation of pyrolysis vapors were not that obvious. Suggestions for potential full scale applications have been proposed. [ABSTRACT FROM AUTHOR]

The long-term stability of biochar in soil is key for carbon capture and storage and soil amelioration. Yet, its assessment is hampered by the long time-horizons needed to actually probe biochar's stability. Therefore, quick and reliable estimation methods are sought. Analytical pyrolysis (Py-GC-MS) offers a quick tool to predict biochar's stability in soil, if adequate and validated metrics can be extracted from it. This work derives and validates stability scores from biochar pyrograms and advanced data analysis. The stability scores were benchmarked by comparison with other stability metrics (Edinburgh stability tool, fixed carbon content and atomic H/C ratio). Calibration of the stability scores with these stability metrics had an R 2 between 0.61 and 0.95; validation resulted in R 2 between 0.59 and 0.72. Overall, this work illustrates how Py-GC-MS can lead to simple and adequate predictors of biochar stability. [Display omitted] • Stability Scores derived from Py-GC-MS can probe the stability of biochar in soil. • Py-GC-MS and principal component analysis were combined to set up Stability Scores. • Stability scores were selected by comparison alternative stability metrics. • Stability scores were calibrated with max R2 of 0.95. • Stability scores were validated with max R2 of 0.72. [ABSTRACT FROM AUTHOR]

[Display omitted] • A green and effective strategy for biomass valorization was proposed. • Citric acid (CA) washing promoted furfural production during the torrefaction step. • CA washing increased levoglucosan yield to 3.76 times for W250-FP compared to R250-FP. • Torrefaction reduced acetic acid yield by 65% for W250-FP compared to WRaw-FP. Converting agricultural waste biomass into value-added chemicals is attractive. However, a low selectivity for target chemicals hinders practical applications. This study presents a stepwise strategy to convert sugarcane trash (ST) into furfural and levoglucosan with high selectivity. The approach includes citric acid washing to reduce mineral content in ST, followed by torrefaction at different temperatures (210 °C, 250 °C and 290 °C) in a tube furnace and then fast pyrolysis at 500 °C in a micro-reactor. This study highlights the valorization potential of the torrefaction liquid, an often overlooked by-product from torrefaction, through significantly increasing furfural selectivity during the torrefaction of washed ST. Furthermore, the vapors from subsequent fast pyrolysis of washed-torrefied ST exhibited reduced acetic acid content compared to that of solely washed ST, which is advantageous for minimizing the acidity of the resulting bio-oil. Moreover, fast pyrolysis of ST, treated with washing and torrefaction at 250 °C, achieved a high levoglucosan yield while maintaining a high furfural yield obtained in the prior torrefaction step. The findings of this study provide valuable insights into future research and industrial applications in agricultural waste biomass utilization. [ABSTRACT FROM AUTHOR]

2-methyl furan (MF) is a fuel additive with improved fuel characteristics compared to bio-ethanol. Unfortunately, the production of MF (from furfural (FF) hydrogenation) is not economically feasible. Interestingly, molten salts in biomass pyrolysis have shown to promote the formation of furans (mainly FF). Because molten salts hydropyrolysis could be an alternative route to both produce FF and convert it into MF, an assessment is indispensable. Molten salts pyrolysis and hydropyrolysis of pinewood and wheat straw and related model compounds were studied in a micro-reactor. The effect of hydropyrolysis process variables was assessed on the total detectable condensable vapors and MF formation. At low pressures (0.4 MPa), the chloride salts favored the production of FF and acetic regardless of the reaction atmosphere. Under a high pressure of hydrogen though (1.6 and 3.0 MPa), the conversion of FF to MF was enhanced through hydrogenation, hydrodeoxygenation and demethylation reactions. Molten salts hydropyrolysis at 350 °C and pressures of either 1.6 MPa (biomass mass fraction of 0.09) or 3.0 MPa (biomass mass fraction of 0.24) were optimal and yielded ca. 8 wt% to 9 wt% MF. Reaction temperatures >350 °C were unfavorable for the MF yield and instead promoted furfural decarbonylation to furan. [Display omitted] • Hydropyrolysis in molten salts highly promoted 2-methyl furan formation. • Targeted production of 2-methyl furan as fuel additive. • Higher pressure and biomass mass fraction are beneficial to product yield. • Product portfolio and yield in molten salts pyrolysis is carrier gas dependent. [ABSTRACT FROM AUTHOR]

The volume penalization (VP) or the Brinkman penalization (BP) method is a diffuse interface method for simulating multiphase fluid-structure interaction (FSI) problems in ocean engineering and/or phase change problems in thermal sciences and engineering. The method relies on a penalty factor (which is inversely related to body's permeability κ) that must be large to enforce rigid body velocity in the solid domain. When the penalty factor is large, the discrete system of equations becomes stiff and difficult to solve numerically. In this paper, we propose a projection method-based preconditioning strategy for solving volume penalized (VP) incompressible and low-Mach Navier-Stokes equations. The projection preconditioner enables the monolithic solution of the coupled velocity-pressure system in both single phase (uniform density and viscosity) and multiphase (variable density and viscosity) flow settings. In this approach, the penalty force is treated implicitly, which is allowed to take arbitrary large values without affecting the solver's convergence rate or causing numerical stiffness. It is made possible by including the penalty term in the pressure Poisson equation (PPE), which was not included in previous works that solved VP incompressible Navier-Stokes equations using the projection method. We show how and where the Brinkman penalty term enters the PPE by re-deriving the projection algorithm for the VP method. Solver scalability under grid refinement is demonstrated, i.e., convergence is achieved with the same number of iterations regardless of the problem size. A manufactured solution in a single phase setting is used to determine the spatial accuracy of the penalized solution. Various values of body's permeability κ are considered. Second-order pointwise accuracy is achieved for both velocity and pressure solutions for reasonably small values of κ. Error saturation occurs when κ is extremely small, but the convergence rate of the solver does not degrade. The solver converges faster as κ decreases, contrary to prior experience. Two multiphase fluid-structure interaction (FSI) problems from the ocean engineering literature are also simulated to evaluate the solver's robustness and performance (in terms of its number of iterations). The proposed solver also allows us to investigate the effect of κ on the motion of the contact line over the surface of the immersed body. It also allows us to investigate the dynamics of the free surface of a solidifying metal. • A projection preconditioner for volume penalized multiphase incompressible/low Mach Navier-Stokes equations is proposed. • The new projection method considers the Brinkman penalty term in both pressure Poisson and velocity update equations. • In contrast to prior experience, the solver convergence rate improves with decrease in body's permeability. • Second-order pointwise accuracy is achieved for both velocity and pressure solutions for reasonably small permeability values. • Challenging multiphase fluid-structure interaction and phase change problems are simulated using the proposed preconditioner. [ABSTRACT FROM AUTHOR]

We present a novel method for graph partitioning, based on reinforcement learning and graph convolutional neural networks. Our approach is to recursively partition coarser representations of a given graph. The neural network is implemented using SAGE graph convolution layers, and trained using an advantage actor critic (A2C) agent. We present two variants, one for finding an edge separator that minimizes the normalized cut or quotient cut, and one that finds a small vertex separator. The vertex separators are then used to construct a nested dissection ordering to permute a sparse matrix so that its triangular factorization will incur less fill-in. The partitioning quality is compared with partitions obtained using METIS and SCOTCH, and the nested dissection ordering is evaluated in the sparse solver SuperLU. Our results show that the proposed method achieves similar partitioning quality as METIS, SCOTCH and spectral partitioning. Furthermore, the method generalizes across different classes of graphs, and works well on a variety of graphs from the SuiteSparse sparse matrix collection. [ABSTRACT FROM AUTHOR]

Background: An isovolumetric intragastric balloon to continuously measure gastric phasic contractility was recently developed by us. We aimed to investigate the readout of this technique in relation to gastric content and gastric emptying. Methods: In this crossover investigation, the VIPUNTM Gastric Monitoring System, which comprises a double lumen nasogastric feeding tube with integrated intragastric balloon, was used to assess phasic gastric contractility by interpretation of the pressure in an isovolumetric balloon in 10 healthy subjects. Balloon pressure was recorded in fasted state, during a 2‐hour intragastric nutrient infusion (1 kcal/ml at 25, 75, or 250 ml/h) and 4 hours post‐infusion, and quantified as Gastric Balloon Motility Index (GBMI), ranging from 0 (no contractility) to 1 (maximal contractility). Gastric accumulation was quantified with magnetic resonance imaging and gastric emptying with a13C‐breath test. Results are expressed as mean(SD). Key Results: GBMI was significantly lower during infusion at 250 ml/h compared to baseline (0.13(0.05) versus 0.46(0.12)) and compared to infusion at 25 (0.54(0.21)) and 75 ml/h (0.43(0.20)), all P < 0.005. Gastric content volume was larger after infusion at 250 versus 75 ml/h (P < 0.001). Half‐emptying time and accumulation were both negatively correlated with postprandial contractility. Postprandial GBMI was significantly lower when GCV>0 ml compared to when the stomach was empty. Conclusions and Inferences: Enteral nutrition dose‐dependently decreased the contractility readout. This decrease was linked to gastric accumulation of enteral nutrition. [ABSTRACT FROM AUTHOR]

It is still unclear which outcome measures should be used in future clinical trials of adult patients with Becker Muscular Dystrophy (BMD) because of the paucity of studies and its heterogeneous progression. We evaluated a wide range of clinical and magnetic resonance imaging (MRI) outcome measures in 21 adults with BMD and 21 age- and sex-matched controls at baseline and after 9 and 18 months of follow-up. We used 6-point Dixon imaging with semi-automated 3D muscle segmentation to measure proton density fat fraction (PDFF) in all entire leg muscles (n=17 in thighs, n=10 in lower legs). In patients, PDFF increased significantly over 9 months in 14/17 thigh muscles, with a mean overall increase of 1.3±1.1% (p<0.001). This increase was significantly higher than that in controls (p=0.018), who increased 0.6±0.6% (p<0.001). Data of 18-months follow-up and lower leg PDFF are currently still under analysis. The north star ambulatory assessment (NSAA; -1.3 points, p=0.013), 32-point motor function measurement (MFM-32; -1.3%, p=0.017) and activity limitations scale (ActivLim; -0.3 logits, p=0.018) deteriorated significantly over 9 months. In the subgroup of patients with abnormal thigh muscle MRI findings, Biodex® isometric dynamometry measurement of peak torque decreased significantly in the quadriceps muscle group (-2.64 Nm, p=0.030), but not in the hamstrings. In all patients, the six-minute walk distance, 10-meter walk test, time to rise from floor test, time to climb 4 stairs test, timed up and go test, and Medical Research Council sum scores (150 and 60-points) did not change significantly over 9 months. All clinical outcome measures correlated strongly to total thigh PDFF at baseline. We conclude that analyzing PDFF in entire thigh muscles is a highly sensitive outcome measure to track progressive muscle fat replacement in patients with BMD, even after 9 months of follow-up. The NSAA, MFM-32 and ActivLim could also be used as outcome measures in future clinical trials. [ABSTRACT FROM AUTHOR]

This study outlines the effect of citric acid leaching on the quality and stability of fast pyrolysis bio-oils from sugarcane bagasse (SCB) and sugarcane trash (SCT). The quality of bio-oil was probed by GC-MS analysis, elemental composition, higher heating value, water and solids content, pH, dynamic viscosity and stability (ageing). Pyrolysis was performed at 500 °C in a fully controlled, continuously operated plant with a biomass throughput of ca. 300 g.hr−1. While citric acid leaching causes a decrease of the average bio-oil yield with 5%, it does not lead to a bio-oil with improved fuel-related properties. However, the bio-oil composition became more advantageous in light of its biorefining. Indeed, citric acid leaching led to an increased levoglucosan concentration – a promising platform chemical – of 17% for SCB and of to 35% for SCT (based on relative abundance in GC-MS). In tandem, the concentration of carboxylic acids and phenols in the bio-oil decreased after citric acid leaching, which is beneficial for downstream purification of levoglucosan. Regarding the non-condensable gases, CO and CO 2 represented between 88% and 91% by weight of the total non-condensable gases produced in pyrolysis. Therefore, the results of this study demonstrate that optimized biomass demineralization pretreatment with citric acid could produce bio-oil at high yield and rich in high-value chemical compounds like levoglucosan. Biomass demineralization pretreatment however, does not result in bio-oil with improved quality for fuel purposes, nor does it necessarily lead to bio-oil having higher stability. • Mild pretreatment with CA is effective in ash removal in sugarcane residues. • CA pretreated feedstock has higher bio-oil yields on pretreated feedstock basis. • Fresh/aged trash derived bio-oils have lower viscosity than bagasse derived bio-oils. • CA pretreatment holds no major benefit for bio-oil composition in terms of fuel use. • Major increase in anhydrosugar content after mild CA pretreatment of sugarcane residues. [ABSTRACT FROM AUTHOR]

Over recent years, pyrolysis has grown into a mature technology with added value for producing soil improvers. Further innovations of this technology lie in developing tailor-made products from specific feedstocks (or mixtures thereof) in combination with adjusted mixing ratio-temperature regimes. In this context, co-pyrolysis of pig manure (PM) and the invasive plant Japanese knotweed (JK) at different mixture ratios (w/w) of 3:1 (P3J1), 1:1 (P1J1), and 1:3 (P1J3) and varying temperatures (400–700 °C) was studied to address the low carbon properties and heavy metals (HMs) risks of manure-derive biochars and beneficially ameliorate the bio-invasion situation by creating value from the plant biomass. Co-pyrolysis of PM with JK increased by nearly 1.5 folds the fixed carbon contents in the combined feedstock biochars obtained at 600 °C compared with PM-derived biochar alone, and all combined feedstock biochars met the requirements for soil improvement and carbon sequestration. The total HMs in PM biochars were significantly reduced by adding JK. The combined feedstock biochar P1J1 generated at 600 °C was the most effective in transforming Cu and Zn into more stable forms, accordingly reducing the associated environmental risk of heavy metal leaching from the biochar. In addition, the accumulation of macronutrients can be an added benefit of the co-pyrolysis process, and P1J1-600 was also the biochar that retained the most nutrients (P, Ca, Mg, and K). [Display omitted] • Japanese knotweed addition improved the aromaticity of pig manure-derived biochar. • Co-pyrolysis reduced total Cu and Zn compared to pig manure-derived biochar. • Cu and Zn transformed to stable forms reduce the environmental risk of the biochar. • Co-pyrolysis retained higher nutrients than Japanese knotweed-derived biochar alone. • A 1:1 ratio of pig manure to Japanese knotweed at 600 °C was the optimal condition. [ABSTRACT FROM AUTHOR]

Limb-Girdle Muscular Dystrophy autosomal recessive type 12 (LGMDR12) is a rare hereditary muscle disease for which outcome measures are lacking. We evaluated intramuscular fat fraction as an outcome measure to track disease progression, to determine if this could be useful in future clinical trials to evaluate potential therapies. We prospectively performed a 6-point Dixon MRI of the thighs in 24 genetically confirmed, adult LGMDR12 patients and 24 age- and sex-matched healthy controls at baseline and after 1 and 2 years. The most affected muscles were the semimembranosus, biceps femoris long head and adductor magnus, respectively, and there was generally an increase in proton density fat fraction (PDFF) with increasing age and disease duration. Patients with intermediate stage thigh muscle fat replacement at baseline (PDFF 20-70%) already showed a significant increase in PDFF in 8/14 evaluated thigh muscles after one year. The standardized response mean (SRM) demonstrated a high responsiveness to change in PDFF for 6 individual muscles over 2 years in this group. We also found that tracking PDFF changes in individual muscles over time was more sensitive than PDFF measurements in muscle groups as a whole. In patients with early (<20%) or end stage (>70%) muscle fat replacement, or in the control group, PDFF did not increase significantly over two years of follow-up. Finally, we observed a moderately strong correlation between total thigh PDFF and the following clinical outcome measures at baseline: six-minute walk distance (6MWD), 10-meter walk test (10MWT), Medical Research Council (MRC) sum scores and Biodex® isometric dynamometry. We conclude that thigh muscle PDFF imaging is a sensitive outcome measure to track progressive muscle fat replacement in selected LGMDR12 patients even after one year of follow-up and should be included as an outcome measure in future clinical trials. [ABSTRACT FROM AUTHOR]