Green concrete production incorporating waste carpet fiber and palm oil fuel ash

With the increasing amount of waste generation from various processes, there has been a growing interest in the utilization of waste in producing building materials to achieve potential benefits. This paper highlights the results of an experimental investigation on the performance of concrete incorporating waste carpet fiber (WCF) and palm oil fuel ash (POFA) as partial replacements of ordinary Portland cement (OPC). Six volume fractions varying from 0 to 1.25% of 20-mm-long carpet fiber were used with OPC concrete mixes. Another six mixes were made that replaced OPC with 20% POFA. The specimens were cured in water and tested for fresh and hardened state properties. The combination of WCF and POFA decreased the slump values and increased the VeBe time of fresh concrete. The addition of WCF to either OPC or POFA concrete mixes did not improve the compressive strength or modulus of elasticity. At 91 days, the compressive strength was in the range of 38.1e49.1 MPa. The positive interaction between WCF and POFA, however, leads to high tensile and flexural strengths, thereby increasing the concrete ductility with higher energy absorption and improved crack distribution. The maximum increases in tensile and flexural strengths compared to those of plain concrete were achieved by the addition of 0.5% carpet fiber at the age of 91 days. The ultrasonic pulse velocity (UPV) was examined and was classified as good quality concrete. The study showed that the use of waste carpet fiber and palm oil fuel ash in the production of sustainable green concrete is feasible both technically and environmentally

The recurrent missense mutation p.(Arg367Trp) in YARS1 causes a distinct neurodevelopmental phenotype

Abstract: Pathogenic variants in aminoacyl-tRNA synthetases (ARS1) cause a diverse spectrum of autosomal recessive disorders. Tyrosyl tRNA synthetase (TyrRS) is encoded by YARS1 (cytosolic, OMIM*603,623) and is responsible of coupling tyrosine to its specific tRNA. Next to the enzymatic domain, TyrRS has two additional functional domains (N-Terminal TyrRSMini and C-terminal EMAP-II-like domain) which confer cytokine-like functions. Mutations in YARS1 have been associated with autosomal-dominant Charcot-Marie-Tooth (CMT) neuropathy type C and a heterogenous group of autosomal recessive, multisystem diseases. We identified 12 individuals from 6 families with the recurrent homozygous missense variant c.1099C > T;p.(Arg367Trp) (NM_003680.3) in YARS1. This variant causes a multisystem disorder with developmental delay, microcephaly, failure to thrive, short stature, muscular hypotonia, ataxia, brain anomalies, microcytic anemia, hepatomegaly, and hypothyroidism. In silico analyses show that the p.(Arg367Trp) does not affect the catalytic domain responsible of enzymatic coupling, but destabilizes the cytokine-like C-terminal domain. The phenotype associated with p.(Arg367Trp) is distinct from the other biallelic pathogenic variants that reside in different functional domains of TyrRS which all show some common, but also divergent clinical signs [(e.g., p.(Phe269Ser)—retinal anomalies, p.(Pro213Leu)/p.(Gly525Arg)—mild ID, p.(Pro167Thr)—high fatality)]. The diverse clinical spectrum of ARS1-associated disorders is related to mutations affecting the various non-canonical domains of ARS1, and impaired protein translation is likely not the exclusive disease-causing mechanism of YARS1- and ARS1-associated neurodevelopmental disorders. Key messages: The missense variant p.(Arg367Trp) in YARS1 causes a distinct multisystem disorder.p.(Arg367Trp) affects a non-canonical domain with cytokine-like functions.Phenotypic heterogeneity associates with the different affected YARS1 domains.Impaired protein translation is likely not the exclusive mechanism of ARS1-associated disorders

Adaptation strategy to mitigate the impact of climate change on water resources in arid and semi-arid regions : a case study

Climate change and drought phenomena impacts have become a growing concern for water resources engineers and policy makers, mainly in arid and semi-arid areas. This study aims to contribute to the development of a decision support tool to prepare water resources managers and planners for climate change adaptation. The Hydrologiska Byråns Vattenbalansavdelning (The Water Balance Department of the Hydrological Bureau) hydrologic model was used to define the boundary conditions for the reservoir capacity yield model comprising daily reservoir inflow from a representative example watershed with the size of 14,924 km2 into a reservoir with the capacity of 6.80 Gm3. The reservoir capacity yield model was used to simulate variability in climate change-induced differences in reservoir capacity needs and performance (operational probability of failure, resilience, and vulnerability). Owing to the future precipitation reduction and potential evapotranspiration increase during the worst case scenario (−40% precipitation and +30% potential evapotranspiration), substantial reductions in streamflow of between −56% and −58% are anticipated for the dry and wet seasons, respectively. Furthermore, model simulations recommend that as a result of future climatic conditions, the reservoir operational probability of failure would generally increase due to declined reservoir inflow. The study developed preparedness plans to combat the consequences of climate change and drought

Mapping tropical disturbed forests using multi-decadal 30 m optical satellite imagery

Tropical disturbed forests play an important role in global carbon sequestration due to their rapid post-disturbance biomass accumulation rates. However, the accurate estimation of the carbon sequestration capacity of disturbed forests is still challenging due to large uncertainties in their spatial distribution. Using Google Earth Engine (GEE), we developed a novel approach to map cumulative disturbed forest areas based on the 27-year time-series of Landsat surface reflectance imagery. This approach integrates single date features with temporal characteristics from six time-series trajectories (two Landsat shortwave infrared bands and four vegetation indices) using a random forest machine learning classification algorithm. We demonstrated the feasibility of this method to map disturbed forests in three different forest ecoregions (seasonal, moist and dry forest) in Mato Grosso, Brazil, and found that the overall mapping accuracy was high, ranging from 81.3% for moist forest to 86.1% for seasonal forest. According to our classification, dry forest ecoregion experienced the most severe disturbances with 41% of forests being disturbed by 2010, followed by seasonal forest and moist forest ecoregions. We further separated disturbed forests into degraded old-growth forests and post-deforestation regrowth forests based on an existing post-deforestation land use map (TerraClass) and found that the area of degraded old-growth forests was up to 62% larger than the extent of post-deforestation regrowth forests, with 18% of old-growth forests actually being degraded. Application of this new classification approach to other tropical areas will provide a better constraint on the spatial extent of disturbed forest areas in Tropics and ultimately towards a better understanding of their importance in the global carbon cycle

Savanna turning into forest: concerted vegetation change at the ecotone between the Amazon and “Cerrado” biomes

In the “Cerrado”–Amazon ecotone in central Brazil, recent studies suggest some encroachment of forest into savanna, but how, where, and why this might be occurring is unclear. To better understand this phenomenon, we assessed changes in the structure and dynamics of tree species in three vegetation types at the “Cerrado”–Amazon ecotone that are potentially susceptible to encroachment: open “cerrado” (OC), typical “cerrado” (TC) and dense woodland (DW). We estimated changes in density, basal area and aboveground biomass of trees with diameter ≥ 10 cm over four inventories carried out between 2008 and 2015 and classified the species according to their preferred habitat (savanna, generalist, or forest). There was an increase in all structural parameters assessed in all vegetation types, with recruitment and gains in basal area and biomass greater than mortality and losses. Thus, there were net gains between the first and final inventories in density (OC: 3.4–22.9%; TC: 1.8–12.6%; DW: 0.2–8.3%), in basal area (OC: 8.3–18.2%; TC: 2–12.7%; DW: 2.3–8.9%), and in biomass (OC: 10.6–16.4%; TC: 1–12%; DW: 5.2–18.7%). Furthermore, all vegetation types also experienced net gains in forest and generalist species relative to savanna species. A decline in recruitment of savanna species was a likely consequence of vegetation encroachment and environmental changes. Our results indicate, for the first time based on quantitative and standardized multi-site temporal data, that concerted structural changes caused by vegetation encroachment are occurring at the ecotone between the two largest biomes in Brazil