Dry Conditions Research Articles

Suitability of calcined clay and ground granulated blast furnace slag geopolymer binder for hempcrete applications

PurposeHempcrete has the potential to reduce both CO2 emissions and energy usage in buildings. Hempcrete has a high sound absorption capacity, excellent moisture regulator and outstanding thermal insulation properties. However, hempcrete traditionally uses lime-based binders, which are carbon-intensive materials. The low-carbon binders to increase the sustainability of hempcrete are the current research gap. Geopolymer binders are low-carbon binders composed of aluminosilicate precursors dissolved in a high alkalinity solution. This study investigated the suitability of calcined clay and ground granulated blast furnace slag geopolymer binder as a low-carbon binder for hempcrete applications.Design/methodology/approachTwo types of hemp hurds with different water absorption capacity and particle size distributions were used. Hempcrete properties tested were compressive strength, bulk density, sound absorption coefficient by a two-microphone impedance tube and thermal conductivity by a Hot Disk system.FindingsThe particle size distribution and water absorption capacity of hemp hurds did not affect the compressive strength of hempcrete when following a mixing procedure, ensuring the hurds in a saturated surface dry condition. The geopolymer hempcrete achieved a compressive strength about four times higher than the reference hydrated lime hempcrete. All hempcrete specimens achieved outstanding acoustic performance. The increase in bulk density led to the decrease in the maximum sound absorption coefficient. The geopolymer hempcrete achieved the lowest thermal conductivity.Originality/valueThe outcomes of this paper reveal that the low-carbon geopolymer binder appears to be a promising option for manufacturing hempcrete, achieving significantly higher compressive strength and lower thermal conductivity than the reference hydrated lime-based hempcrete.

New insights into controlling factors of organic matter enrichment in Carboniferous−Permian shales based on machine learning

Shale deposits constitute Earth’s largest and most stable organic carbon reservoir. Organic matter enrichment of fine-grained sediments is paramount for carbon sink research and oil and gas exploration. The Carboniferous to Permian interval, an especially critical period in Earth’s ecosystem evolution that encompassed the late Paleozoic ice age, witnessed widespread accumulation of organic-rich shale. However, the mechanisms driving organic matter enrichment and the role of organic carbon burial as a carbon sink during this period remain contentious. Our study focuses on upper Carboniferous and lower Permian shale deposited on the North China Block (NCB). A total of 370 elemental geochemical datasets were obtained to elucidate paleoenvironmental conditions associated with these deposits. We employed random forest (RF) and artificial neural network (ANN) algorithms to elucidate the controlling mechanisms of organic matter enrichment during this time period and to offer a quantitative assessment of the magnitude of organic carbon burial. Our results suggest that upper Carboniferous and lower Permian shale accumulated contemporaneous with a dominantly warm, humid climate that experienced episodes of cooler, drier conditions. The water column exhibited low primary surface productivity, oxic-suboxic, saline water conditions, and elevated terrigenous input and sedimentation rates. RF and ANN analysis reveals that paleoclimate was the dominant factor influencing organic matter enrichment of fine-grained sediments during this time. The inferred warm, humid climate not only promoted enhanced organic carbon production but also favored increased delivery of organic matter as a result of increased chemical weathering and associated terrestrial input to the basin. Concurrently, elevated sedimentation rates and the establishment of saline water conditions facilitated enhanced preservation of deposited organic matter. Organic carbon burial associated with accumulation of the upper Carboniferous and lower Permian shale succession of the NCB reached 95.5 × 103 PgC. These deposits appear to have served as a significant carbon sink based on an estimated organic carbon burial rate of shale containing total organic carbon >6% of as great as 65.6 gC/m2/yr. Results of the present study enhance our understanding of the carbon cycle during the Carboniferous to Permian interval and provide guidance for shale gas exploration and development of Carboniferous and Permian shale deposits.

Induced drought in an Amazonian forest affects diversity but not foraging distance of generalist ants

Abstract Ongoing environmental change is forecast to lead to lower precipitation and concomitant species losses in tropical regions. These losses may affect generalist species that provide essential ecosystem services, such as controlling the rate at which nutrients become available for uptake by other organisms in tropical forests. Here, we use a long‐term (16 years) rainwater exclusion experiment in a primary Amazonian tropical rainforest (Caxiaunã National Forest, Northern Brazil) to test whether induced water stress (“drought”) affects the species richness of generalist ants, their abundance (i.e., nest density), and the distance at which they detect food resources (i.e., baits). The number of generalist ant species and colonies was reduced by 50% in the drought‐induced plot, and ant species composition differed between the control (typical moist forest) and drought‐induced plots. Although ants that nested in both control and drought plots had shorter estimated foraging distances than habitat specialists, the distance at which these colonies detected baits was not affected by drought. We conclude that the extremely high diversity of tropical forest ants may be able to buffer the detrimental effects of drought on the resource detection rates of generalist ants. Different generalist ant species were also functionally similar to wet‐forest species that cannot forage under drier conditions.

ОЦЕНКА ОБЕСПЕЧЕННОСТИ ПОЧВ ЛЕСОСТЕПНОЙ ЗОНЫ НИТРАТНЫМ АЗОТОМ ПО ПОЧВЕННОЙ ДИАГНОСТИКЕ

The purpose of the study is to generalize and evaluate the provision of nitrate nitrogen in arable soils of natural districts of the Krasnoyarsk Region depending on various factors and conditions. We summarized the results of a continuous agrochemical survey of soils for the content of nitrate nitrogen in three natural districts of the Krasnoyarsk Region: Central and Western, South Minusinsk and Eastern groups of districts included in the agrochemical service zone. We systematized the long-term results of an agrochemical survey on the content of nitrate nitrogen in the soils of the study objects depending on the following factors: weather conditions, predecessor, soil tillage. The influence of three methods of basic treatment of a fallow field on the content of mineral forms of nitrogen (dump processing, disking and cultivation) was studied. The soils were grouped according to the supply of soils with nitrate nitrogen, depending on the listed factors. Agrochemical survey of soils on farms in the forest-steppe zone of the Krasnoyarsk Region for the period 2011–2019 indicates that the proportion of fields with different groups according to the supply of nitrate nitrogen in different years was unequal, depending on the weather conditions of the year. Dry conditions during the growing season significantly reduced the activity of nitrate accumulation. Fallow fields do little to accumulate nitrates. Only 50 % of the fallows from the surveyed fields justify their purpose as optimal nitrogen precursors. The supply of nitrate nitrogen for grain crops, row crop predecessors, fallow, rapeseed and even perennial grasses is low and very low. A weak ability for nitrate accumulation was noted in soils of fields cultivated without moldboard. After cultivation, 40.7 % of the surveyed fields are characterized by a low supply of nitrate nitrogen; after disking, 46.2 % of the fields have very low nitrogen content. Dump processing promotes active nitrification. In most cases, plowing is significantly superior to non-moldboard cultivation. The following decreasing series of influences of factors on the intensity of nitrate accumulation and the provision of soils with this form of nitrogen has been formed: weather conditions > precursors > soil tillage methods.

НАСЛЕДУЕМОСТЬ ПРОДОЛЖИТЕЛЬНОСТИ ВЕГЕТАЦИОННОГО ПЕРИОДА ГИБРИДАМИ F2 ЧЕЧЕВИЦЫ В УСЛОВИЯХ ОМСКОЙ ОБЛАСТИ

The purpose of research is to identify the spectrum of genetic diversity of early ripening in hybrid combinations of the second generation of lentils to accelerate the selection of valuable genotypes and create varieties adapted to the climatic conditions of the region. Research was carried out from 2020 to 2022 at the experimental site of the educational and experimental farm of the Federal State Budgetary Educational Institution of Higher Education Omsk Civil Aviation in the southern forest-steppe of the Omsk Region. The value of the hydrothermal coefficient indicates very dry conditions in 2020 (HTC = 0.62) and 2021 (HTC = 0.68), slightly dry conditions in 2022 (HTC = 1.02). The soil of the experimental plot is medium-deep meadow-chernozemic (45 cm), low-humus (3.95 % humus), medium-loamy (35 % physical clay) with a soil solution reaction close to neutral (pH – 6.5). The predecessor is spring soft wheat. Four collection samples of lentils with a complex of economically valuable traits of different ecological and geographical origin were subject to study: k-2888 (Moldova), k-2849 (Russia, Altai Region), Rauza (Russia, Oryol Region), Vehovskaya (Russia, Saratov Region) – and four F2 hybrids obtained as a result of intraspecific crossing: k-2888 × Rauza, k-2888 × Vehovskaya, k-2849 × Rauza, k-2849 × Vehovskaya. Analysis of the data obtained showed that the duration of the growing season is characterized by low heredity (H2 = 19.0 %). This means that the phenotypic variability of the trait is determined by the natural and climatic conditions of the environment. It is advisable to select valuable early ripening genotypes in later generations of hybrids under favorable conditions. Hybrid combinations that are promising in practical selection of lentils for early ripening are: k-2849 × Vehovskaya and k-2888 × Vehovskaya.

Uncovering proteome variations and concomitant quality changes of different drying methods Cordyceps sinensis by 4D-DIA structural proteomics

IntroductionCordyceps sinensis is a fungus, serves dual purposes as both a medicinal herb and a food source. Due to its high water content, fresh Cordyceps sinensis is difficult to preserve, necessitating the drying necessary to process Cordyceps sinensis.MethodsUsing 4D-DIA proteomics, researchers analyzed the proteome profiles of fresh Cordyceps sinensis (CK) under three different drying conditions: vacuum freeze-drying (FD), oven-drying (OD), and air-drying (AD). In addition, it was found that the protein and free sulfhydryl content of Cordyceps sinensis decreased significantly and the disulfide bond content increased after different drying methods.Results and discussionA total of 3762 proteins were identified, showing variations between groups and high protein content. In the control groups consisting of fresh Cordyceps sinensis samples and the three drying methods, FD. vs CK exhibited the fewest differentially abundant proteins, with the majority being upregulated. On the other hand, CK vs OD displayed the greatest amount of distinct proteins, with a significant rise in both up-regulated and down-regulated proteins. Analysis of KEGG indicated that the distinct proteins were predominantly concentrated in pathways like the ribosome, synthesis of coenzymes, and metabolism of amino sugar and nucleotide sugar. Notably, there was a significant overlap between ribosome and ribosome biogenesis in eukaryotes pathways. The process of drying Cordyceps sinensis resulted in a significant upregulation of the expression of proteins linked to various metabolic pathways. This observation suggests that the drying treatment might activate or enhance certain biochemical processes within the organism, potentially influencing its overall metabolic activity. This finding highlights the importance of post-harvest dry methods on the biochemical properties of Cordyceps sinensis, which could have implications for its nutritional and medicinal value.This study provides a theoretical basis for the realization of Cordyceps sinensis resource utilization and storage methods, and provides theoretical support for guaranteeing the sustainable development of Cordyceps sinensis resources.

Three-dimensional analysis using a dental model scanner: Morphological changes of occlusal appliances used for sleep bruxism under dry and wet conditions.

This study used a dental model scanner and best-fit alignment to analyze the deformation patterns of stabilized occlusal appliances (OcAs) used to treat sleep bruxism when stored in wet or dry conditions. Eight OcAs were prepared using polymethyl methacrylate, stored in water at room temperature for 4 weeks (wet storage), and then in air for 4 weeks (dry storage). After being stored in water for one month for hydration, they were 3D-scanned and digitized on days 0, 28, and 56. 3D-deformation patterns were obtained by comparing the storage-D group data using a best-fit alignment program that aligns the nearest points of the corresponding images in a virtual space and calculates the difference between the two images. The maximum deviation and deformed area in the ± direction, and the volume of the wet (W) and the dry (D) condition groups were compared using Wilcoxon's signed rank test. OcA showed no obvious deformities in the W group at 4 weeks. However, in the D Group, a typical deformation pattern was detected at 4 weeks, with the posterior margin of the molars shrinking anteriorly, the palatal side of the molars lifted, and the buccal side retracted inward. The Ⅾ group was significantly larger than the W groups in terms of maximum deviation in the ± direction, deformed area, and volume. After 4 weeks of storage under dry conditions, OcA showed a typical deformation pattern of shrinkage toward the center, with in-center lifting toward the palatal side. Significantly greater surface deviations, deformation areas, and deformation volumes were observed under dry conditions than in wet conditions.

Multiscale Analysis of Corrosion Fatigue Crack Propagation Mechanism of High‐Strength Steel in Seawater Atmospheric Environment

ABSTRACTE690 high‐strength steel is widely used in ocean engineering due to its excellent properties. However, it is highly susceptible to fracture and failure under the coupled effects of corrosion and fatigue in marine environments. This paper investigates the corrosion fatigue fracture mechanisms through experimental and theoretical analyses. First, a series of corrosion fatigue tests on E690 steel specimens were conducted to study the crack propagation behavior, and the crack growth parameters were fitted using the Paris equation. Second, scanning electron microscopy was employed to analyze the corrosion fracture characteristics of the E690 steel specimens. Lastly, finite element analysis and molecular dynamics simulations were used to examine the crack propagation process and failure mechanisms from multiscales. The results show that under the influence of corrosion, dislocation accumulation at the crack tip leads to a plastic deformation mechanism dominated by dislocations during crack propagation. Furthermore, the combined effects of anodic dissolution and hydrogen embrittlement accelerate crack growth. In dry air conditions, loading frequency has no significant impact on the crack growth rate, whereas, in corrosive environments, the coupling of low frequency and corrosion shortens the corrosion fatigue life.

Safer Floors in Public Service Buildings Based on Machine Learning

Abstract This study investigates the effects of different floor surfaces on slip safety in public service buildings (PSBs) with heavy pedestrian traffic. The K-means clustering method is used to classify various floor types and slip safety risks. The dynamic friction coefficient (DCOF) for floor coverings, such as natural stone, ceramic, laminate, and PVC, were measured in both dry and wet conditions across thirty public institutions. These measurements were obtained using the GMG 200 and Wessex S885 pendulum testers, providing a comprehensive assessment of the slip resistance of these surfaces. The machine learning models employed in the study were XGBoost, K-Nearest Neighbors (KNN), and SVC. The models were evaluated using 5-fold cross-validation. The analysis revealed that the most significant parameter in DCOF predictions for the XGBoost model was environmental conditions (EC). Performance analysis showed that the SVC model achieved the highest F1 score (0.75 ± 0.01) and AUC value (0.83), outperforming the other models. Additionally, DCOF values from slip tests were grouped into five clusters using the K-means method, and a slip safety risk scale was developed. Statistically significant differences were observed in DCOF values based on usage areas, environmental conditions, test methods, and surface materials. For instance, hospital floors were found to be generally safe in dry conditions but posed a risk in wet conditions. Based on these findings, actionable safety measures were suggested, such as applying anti-slip coatings in high-risk areas, selecting flooring materials with higher DCOF values for moisture-prone environments, and implementing regular slip resistance testing to maintain safety standards. In conclusion, this study demonstrates that machine learning models can effectively assess the slip resistance of floor surfaces. The findings offer valuable guidance for construction industry professionals and researchers in improving safety measures and minimizing slip risks. Future research with larger datasets and diverse conditions could enhance the understanding of this issue and further improve model performance.

Factors Influencing Orchid Species Richness in the Central Balkans: The Importance of Belowground Organ Types

The Balkan Peninsula is considered one of the most important centres of orchid diversity in Europe. However, the patterns of orchid species richness in the Central Balkans have not been sufficiently studied so far. The aim of this study was, therefore, to identify the centres of orchid diversity and the factors that influence the spatial variation in orchid species richness in the Central Balkans. For the analyses, the area of the Central Balkans was divided into 10 × 10 km grid cells. The environmental variables determined for each grid cell and used in the analyses were altitude, bioclimatic variables, geological substrates and habitat types. A random forest (RF) analysis was used to identify the environmental predictors most strongly associated with species richness. In addition to the total number of taxa, orchids with three belowground organ types were analysed separately: (a) rhizomatous orchids, (b) orchids with palmately lobed and fusiform tubers (“palmate tuberous orchids”) and (c) orchids with spherical or ovoid tubers (“ovoid tuberous orchids”). In the Central Balkans, 54 orchid species and subspecies have been recorded, and the most important centres of diversity are the Tara, Zvijezda, Jadovnik and Zlatar Mountains and the Ovčar-Kablar Gorge. In general, two groups of grid cells with the largest number of orchid taxa, i.e., hotspots, stood out: (1) grid cells with a large altitudinal range and (2) grid cells occupied by gorges and ravines. The most important gradients influencing orchid species richness are specific habitat types and altitudinal ranges, while climatic factors and geological substrates are less important. The most important factors affecting the richness of total and rhizomatous orchids are altitudinal range and habitat types (Abieti-Fagenion, Ostryo-Carpinion orientalis and Pinion nigrae forests), highlighting the important role of habitat heterogeneity. The maximum altitude, percentage of Abieti-Fagenion and Vaccinio-Picetea forests and the minimum value of the mean temperature of the driest quarter are the most important factors for determining the richness of palmate tuberous orchids, whereas the percentage of xero-thermophilous habitat types (Ostryo-Carpinion orientalis, Asplenietea trichomanis and Pinion nigrae) has the greatest influence on the richness of ovoid tuberous orchids. These results confirm the hypothesis concerning the origin and development of underground organs in orchids, emphasising that palmate tuberous orchids are best adapted to cold and humid habitat conditions, whereas ovoid tuberous orchids have the ability to grow in habitats with very warm and dry conditions. This study provides a good basis for better orchid conservation planning and underlines the importance of belowground strategies as a feature of orchid life history that should be considered when studying patterns of orchid diversity.

Climatic and human impacts on Patagonian terminal lakes.

We study the causes of the reduction in the surface area of five terminal lakes since 2007, within Laguna Blanca National Park, a Ramsar site in Patagonia (Southern South America). The terminal lakes in this park are critical habitats for several species of animals, some of which are endemic and endangered. We analyzed the lakes' area time series (1998-2024), a climatic index determining dry and wet periods, and human land use changes in the basin of the lakes. The area of the five terminal lakes decreased between 20 and 52% since 2007, with a higher reduction in the smaller lakes. From 2007 to 2024, the months with dry conditions increased by 29%, and the months with wet conditions decreased by 13%, compared to 1998-2006. Moreover, since October 2020, fifty-three (53) irrigation channels have been constructed on the basin of Laguna Blanca Lake. Before the construction of the channels, Laguna Blanca Lake had already decreased by 19% compared to 2007. The other four terminal lakes are outside the sub-basin affected by the channels. Therefore, the reduction in the surface area of all the terminal lakes was primarily due to an increase in dry conditions. However, the irrigation channels may accelerate the desiccation of Laguna Blanca Lake. As in our study, several terminal lakes are globally drying quickly due to climate change and human impact. This study shows international and local discussions are needed to prevent the disappearance of terminal lakes, as they are impacted even when located on protected land.

Designing nanohydrogels/organosilica composite membranes to stabilize CO2 separation performance in dry and wet conditions

Designing nanohydrogels/organosilica composite membranes to stabilize CO2 separation performance in dry and wet conditions

Development and evaluation of the modified and standardized rainfall anomaly indices for extreme variability analysis.

This study introduces two refined rainfall anomaly indices-the Modified Rainfall Anomaly Index (MRAI) and the Standardized Rainfall Anomaly Index (SRAI)-to address limitations in the traditional Rainfall Anomaly Index (RAI). The existing RAI struggles to effectively capture extreme wet and dry rainfall conditions and relies on a simplistic formulation. To evaluate these indices on a continental scale, data from the Integrated Multi-Satellite Retrievals for GPM (IMERG) was used for the Conterminous United States (CONUS), enabling scalability to ungaged locations and beyond. Additionally, daily annual maximum series (AMS) from 2,360 NOAA stations provided reference data to enhance the robustness of the analysis. IMERG data informed the MRAI and SRAI, while station data validated the RAI. Findings showed MRAI's kurtosis ranged from 0 to +0.9, consistently higher than SRAI and RAI, while SRAI exhibited a kurtosis range from -0.9 to -0.1. Median index ranges were -2 to 0 for SRAI, 0 to +2 for MRAI, and -1 to +1 for RAI. Comparing MRAI and RAI, performance metrics revealed average PRB of -23.5, RMSE of 0.93, MBR of 0.74, NSE of 0.82, and KGE of 0.53. For SRAI versus RAI, metrics showed PRB of -14.5, RMSE of 1.7, MBR of 0.8, NSE of 0.41, and KGE of 0.46. Spatially, MRAI effectively captured positive anomalies leaning toward wet extremes, while SRAI identified negative anomalies indicating dry extremes. These indices demonstrate significant potential for climate change studies, especially when applied together.

Enhanced anaerobic digestion model no.1 for high solids fermentation: Integrating homoacetogenesis and chain elongation.

The production of volatile fatty acids (VFA) through high-solids anaerobic fermentation of organic waste offers a promising route for resource recovery. This study used a batch-mode anaerobic leach bed reactor (LBR) with leachate circulation to ferment the organic fraction of municipal solid waste, producing high concentrations of butyric acid, along with notable amounts of lactic and caproic acids. These results provide valuable insights and underscore the need for process optimization within conventional fermentation systems. To better model the LBR's complex dynamics, the Anaerobic Digestion Model No.1 (ADM1) was modified and extended to account for slow hydrolysis in dry fermentation conditions, thermodynamic constraints imposed by Gibbs Free Energy and hydrogen partial pressures, as well as lactic acid production and chain elongation pathways including homoacetogenesis and caproic acid formation. These enhancements provided deeper insights into high-solids anaerobic fermentation, advancing strategies for improved process control and system optimization.

Sorption behavior of Cu0–loaded hexagonal boron nitride for effective iodine capture under dry and humid conditions

Sorption behavior of Cu0–loaded hexagonal boron nitride for effective iodine capture under dry and humid conditions

ELM‐Wet: Inclusion of a Wet‐Landunit With Sub‐Grid Representation of Eco‐Hydrological Patches and Hydrological Forcing Improves Methane Emission Estimations in the E3SM Land Model (ELM)

AbstractWetlands are the largest emitters of biogenic methane (CH4) and represent the highest source of uncertainty in global CH4 budgets. Here, we aim to improve the realism of wetland representation in the U.S. Department of Energy's Exascale Earth System Model land surface model, ELM, thereby reducing uncertainty of CH4 flux predictions. We develop an updated version, ELM‐Wet, where we activate a separate landunit for wetlands that handles multiple wetland‐specific eco‐hydrological patch functional types. We introduce more realistic hydrological forcing through prescribing site‐level constraints on surface water elevation, which allows resolving different sustained inundation depth for different patches, and if data exists, prescribing inundation depth. We modified the calculation of aerenchyma transport diffusivity based on observed conductance per leaf area for different vegetation types. We use Bayesian Optimization to parameterize CO2 and CH4 fluxes in the developed wet‐landunit. Site‐level simulations of a coastal non‐tidal freshwater wetland in Louisiana were performed with the updated model. Eddy covariance observations of CO2 and CH4 fluxes from 2012 to 2013 were used to train the model and data from 2021 were used for validation. Patch‐specific chamber flux observations and observations of CH4 concentration profiles in the soil porewater from 2021 were used for evaluation of the model performance. Our results show that ELM‐Wet reduces the model's CH4 emission root mean squared error by up to 33% and is able to represent inter‐daily CO2 and CH4 flux variability across the wetland's eco‐hydrological patches, including during periods of extreme dry or wet conditions.

Self-healing PVA/Chitosan/MXene triple network hydrogel for strain and temperature sensors.

Conductive hydrogels have attracted intensive attention for their promising applications in flexible electronics, sensors, and electronic skins. However, extremely poor adaptability under cold or dry environmental conditions along with inferior repairability seriously hinders the development of hydrogels in wearable electronics. Here, a triple network conductive hydrogel (PBCPA-MXene) was prepared by proportionally mixing polyvinyl alcohol (PVA), borax, chitosan (CS), phytic acid (PA), and MXene. The prepared triple network hydrogels composed of robust chitosan polysaccharide as the first network, tough PVA biopolymer gel as the second network, and MXene nanosheets as the third network. Facilitated by triple networks, multiple hydrogen bonds, and electrostatic interactions of CS and PA, the obtained hydrogels not only exhibited outstanding mechanical properties (tensile strain of ∼1580%, stress of ∼280kPa) and electrical properties (∼ 2.72S/m), but also possessed excellent self-healing, self-adhesion, anti-freezing and anti-drying properties. This work presents a strategy for the development of biopolysaccharide hydrogels for applications in the field of sensors.

Mechanical Characterization of Amniotic-Based Scaffolds Containing Silk Fibroin and Sodium Alginate Nanofibers.

Due to its availability and biocompatibility, the human amniotic membrane (hAM) is being investigated by a large number of researchers with the goal of gaining a better understanding of the materials' mechanical behavior and structural integrity and optimizing them for various Tissue Engineering applications. In this research, biopolymers sodium alginate (SA) and silk fibroin (SF) were electrospun onto a decellularized hAM, resulting in two types of hybrid scaffolds: hAM/SF and hAM/SF/SA. The mechanical characteristics of these nanofibers were then analyzed to guide scaffold optimization for applications using these materials. Two mechanical experiments were conducted; uniaxial tension in both wet and dry configurations, and stress-relaxation tests. According to the results, the mechanical characteristics of the manufactured materials were significantly different from those of the amniotic membrane, indicating the effect of novel materials. Tensile testing in the dry condition revealed a small variation in stiffness between the amniotic membrane and the new nanofibers. Simultaneously, a significant reduction in maximum tension and stretch was observed in the aforementioned materials compared to amniotic matrices. In addition, tensile testing in a wet configuration indicated that the new nanofibers are stronger and stiffer than amniotic membrane but less stretchy, owing to the improved mechanical properties of SF, which can be considered as the membrane's or tissue's load-bearer. The addition of SF increases the stiffness and durability of the fabricated scaffold. In addition, when compared to the amniotic membrane, relaxation tests revealed significant differences in peak tension rather than equilibrium state for the novel nanofibers in wet conditions. The results of this investigation will enable us to have a comprehensive grasp of the mechanical properties of freshly created wound dressings.

Assessing consistency in drought risks in India with multiple multivariate meteorological drought indices (MMDI) under climate change.

This study investigates the spatio-temporal consistency of different MMDI formulations and their role in meteorological drought characterization uncertainty under historic and future climates using ERA5 reanalysis, and outputs from eight Coupled Model Intercomparison Project Phase 6 models, respectively, across different climate zones and shared socioeconomic pathways (SSP) in the Indian subcontinent. Six MMDI formulations namely the Standardized Precipitation Evaporation Index (SPEI), Reconnaissance Drought Index (RDI), and self-calibrated Palmer Drought Severity Index (scPDSI), Standardized Palmer Drought Index (SPDI), Standardized Moisture Anomaly Index (SZI) and Supply Demand Drought Index (SDDI) are used. A suite of analysis including agreement mapping, category difference analysis and uncertainty contribution analysis using global sensitivity analysis (GSA) are employed to quantify the consistency of MMDIs and uncertainty in drought characterization due to the MMDI formulation. The variation in MMDI consistency due to different reference evapotranspiration (ETo) methods is also studied. Results demonstrate strong agreement among the MMDIs under historic climate. Under climate change scenarios our findings demonstrate broad agreement among majority of the MMDIs across the study domain, but in substantial areas where MMDI not agree, especially for higher emission scenarios and arid zones. Increased uncertainty under climate change is due to SDDI and SPEI projecting dryer conditions while scPDSI projecting wetter conditions in the far future period owing to varying degrees of sensitivity of MMDIs to its constituent variables (Precipitation and ETo). Results also show that the uncertainty due to MMDIs varied considerably based on ETo methods as well. Finally, based on GSA analysis, the most significant sources of uncertainty in drought projections under climate change are attributed to MMDI-GCM interactions and MMDIs for the Penman-Monteith method. Discrepancies in drought estimates caused by the MMDI selection highlight the need for careful evaluation of drought indices before adopting for climate change impact assessment.

Integrating renewable energy in sewage sludge treatment through greenhouse solar drying: A review.

Sewage sludge is the main by-product of wastewater treatment plants, requiring significant environmental and economic burdens for its management and disposal. Recently, solar drying processes, often performed through solar greenhouses, received interest due to their limited energy requirement and renewable energy exploitation. The dried sludge shows significant volume and mass reductions, reducing transportation and disposal costs. However, its physicochemical and microbiological characteristics must be properly assessed, especially if agricultural reuse is the final sludge destination, due to the possible accumulation of (micro)pollutants in the soil. This review depicts the state-of-the-art solar drying processes of sewage sludge, with a focus on the technological aspects and the sludge quality. The review discusses greenhouse-specific features, sludge composition (organic matter, pathogens, heavy metals and emerging pollutants) and drying conditions (seasonality, ventilation, sludge mixing and thickness, and drying speed). The economic aspects connected to sludge solar drying are presented. The limitations of this technology are discussed as well, including the limited applicability to wet sludge and the environmental issues connected to greenhouse structure degradation. A wider application of sludge solar drying is recommended to increase the sustainability of small and medium wastewater treatment plants, especially in areas with high amounts of solar radiation and dry weather conditions, while thermal drying still appears preferable for large plants. More agronomic studies must be conducted to assess the possible pollutant accumulation in crops, and alternative uses of the dried sludge (e.g., energy recovery through incineration, pyrolysis or gasification; utilization in construction materials) should be explored, also using life cycle assessment.