Measurement Of Moisture Content Research Articles

Effects of environmental humidity on the gap of mortise-tenon joints: experimental and numerical investigations

Mortise-tenon (MT) joints play a vital role in the lateral deformability and seismic performance of traditional timber structures. However, moisture exposure can cause shrinkage-induced gaps and then affect the durability of MT joints. Limited knowledge exists on the humidity response of MT joints. To investigate the effect of environmental humidity on the gaps between mortise and tenon, multiple measurements of moisture content (MC) and shrinkage deformation were conducted on straight MT joints that were subjected to humidity variations. Different ambient conditions and exposure levels were taken into account. Three-dimensional numerical models were established to simulate the humidity response of MT joints. Model validation was then performed by comparing the simulation and experimental results in terms of moisture distribution and gaps. On this basis, quantitative analysis was made to reveal the development mechanism and main influence factors of moisture-induced gaps. Results show that straight MT joints are vulnerable to environmental humidity changes. The observed gap is estimated to cause a decrease of up to 23.1% in the initial elastic stiffness. Although only contributed by the shrinkage deformation of tenons, the vertical gap is theoretically larger than the horizontal one which is attributed to a combination of both mortise and tenon. A clear linear relationship is found between the vertical gaps and the MC decrease, with the product of the radial shrinkage coefficient and tenon height as the theoretical ratio. Controlling the moisture exposure is considered the most effective way to reduce moisture-induced gaps in MT joints.

Effect of Particle Size on Physical Properties of Rambutan Seed Powder

Rambutan seed powder is derived from the crushing of dried seed of rambutan (Nephelium lappaceum L.) and it is promisingly used as an incorporating powder into food product. However, there is limited information on the effects of particle size on the handling and processing of rambutan seed powder in the industry. Therefore, a study was performed to determine the effects of particle sizes on physical properties of rambutan seeds powder. The physical properties measured moisture content, bulk and tapped density, as well as flowability characteristics. In this work, the powders were classified based on their mean diameter (d50) that ranged between less than 250 μm, between 250 μm and 750 μm and more than 750 μm. The fine rambutan seed powder (RSP) with particle 250 μm to 750 μm exhibited the best powder characteristics as it holds lowest moisture content, 5.42% and fair and passable flow properties, with Hausner ratio of 1.26 ± 1.20. The results indicated a significant impact of particle size on the cohesivity, where smaller particle size tended to decrease flowability and caused caking and agglomeration, which led to undesirable quality of food product.

Whey Protein Isolate as a Substrate to Design Calendula officinalis Flower Extract Controlled-Release Materials.

The use of natural active substances and the development of new formulations are promising directions in the cosmetic and pharmacy industries. The primary purpose of this research was the production of microparticles based on whey protein isolate (WPI) and calcium alginate (ALG) containing Calendula officinalis flower extract and their incorporation into films composed of gelatin, WPI, and glycerol. Both swollen and dry microparticles were studied by optical microscopy and their sizes were measured. Water absorption by the microparticles, their loading capacity, and the release profile of flower extract were also characterized. The films were analyzed by mechanical tests (Young's modulus, tensile strength, elongation at break), swelling capacity, contact angle, and moisture content measurements. The presented data showed that the active ingredient was successfully enclosed in spherical microparticles and completely released after 75 min of incubation at 37 °C. The incorporation of the microparticles into polymer films caused a decrease in stiffness and tensile strength, simultaneously increasing the ductility of the samples. Moreover, the films containing microparticles displayed higher swelling ability and moisture content compared to those without them. Hence, the materials prepared in this study with Calendula officinalis flower extract encapsulated into polymeric microspheres can be a starting point for the development of new products intended for skin application; advantages include protection of the extract against external factors and a controlled release profile.

Design, analysis and validation of a microstrip patch antenna with enhanced coupling for leaf moisture sensing: an IoT approach

An innovative IoT-based system utilizing a modified slotted microstrip patch antenna with enhanced coupling is presented for precise measurement of leaf moisture content. The antenna employs a rectangular slot above the feed point with an advanced coupling technique to enhance sensitivity. The antenna, fabricated on a 0.8 mm F4B substrate, is designed to resonate within the 2.40 to 3.0 GHz range under unloaded conditions. A parametric analysis focusing on leaf permittivity ranging from 20 to 30 is conducted to determine the antennas’ sensitivity. Experimental measurements of the reflection coefficient (S11) with respect to resonant frequency shift are performed with leaf samples as the samples under test (SUT). Experimental results reveal that the proposed patch antenna’s sensitivity is significantly enhanced, ranging from 0.57 to 1.67 times greater than that of traditional patch antennas for the five leaf samples tested. The antenna exhibits a sensitivity of 0.06 GHz and 0.02 GHz for the modified and enhanced coupling designs, respectively. The mean relative error between predicted and measured moisture content values is low at 0.038. The findings highlight the antenna’s increased sensitivity in detecting leaf moisture content and illustrate the potential of the proposed IoT-based system for real-time agricultural monitoring, marking an advancement in precision farming practices. The study validates the microstrip patch antenna’s capability as a moisture sensor through detailed sensitivity analysis, frequency shift measurements, and regression modeling.

Innovative dispersion techniques of graphene nanoplatelets (GNPs) through mechanical stirring and ultrasonication: Impact on morphological, mechanical, and thermal properties of epoxy nanocomposites

Graphene nanoplatelets (GNPs) have attracted tremendous interest due to their unique properties and bonding capabilities. This study focuses on the effect of GNP dispersion on the mechanical, thermal, and morphological behavior of GNP/epoxy nanocomposites. This study aims to understand how the dispersion of GNPs affects the properties of epoxy nanocomposite and to identify the best dispersion approach for improving mechanical performance. A solvent mixing technique that includes mechanical stirring and ultrasonication was used for producing the nanocomposites. Fourier transform infrared spectroscopy was used to investigate the interaction between GNPs and the epoxy matrix. The measurements of density and moisture content were used to confirm that GNPs were successfully incorporated into the nanocomposite. The findings showed that GNPs are successfully dispersed in the epoxy matrix by combining mechanical stirring and ultrasonication in a single step, producing well-dispersed nanocomposites with improved mechanical properties. Particularly, the nanocomposites at a low GNP loading of 0.1 wt%, demonstrate superior mechanical strength, as shown by increased tensile properties, including improved Young's modulus (1.86 GPa), strength (57.31 MPa), and elongation at break (4.98). The nanocomposite with 0.25 wt% GNP loading performs better, according to the viscoelastic analysis and flexural properties (113.18 MPa). Except for the nanocomposite with a 0.5 wt% GNP loading, which has a higher thermal breakdown temperature, the thermal characteristics do not significantly alter. The effective dispersion of GNPs in the epoxy matrix and low agglomeration is confirmed by the morphological characterization. The findings help with filler selection and identifying the best dispersion approach, which improves mechanical performance. The effective integration of GNPs and their interaction with the epoxy matrix provides the doorway for additional investigation and the development of sophisticated nanocomposites. In fields like aerospace, automotive, and electronics where higher mechanical performance and functionality are required, GNPs' improved mechanical properties and successful dispersion present exciting potential.

Drying Performance and Economic Analysis of a Greenhouse Solar Dryer for Tomatoes

Purpose: The purpose of this study was to assess the drying performance and economic feasibility of a Greenhouse Solar Dryer for Tomatoes. With a focus on small-scale tomato drying, the study aimed to evaluate the effectiveness of the greenhouse in comparison to traditional sun drying methods. Additionally, the economic analysis sought to determine the investment attractiveness of the greenhouse dryer by considering the initial investment, operational costs, and potential revenue generation. Methodology: The methodology involved conducting drying experiments using the Greenhouse Solar Dryer for Tomatoes under existing weather conditions. The dryer's components include the steel frame, greenhouse plastic cover, and concrete floor. The temperature and relative humidity contributed to the environment inside the greenhouse that facilitated the drying process. Moisture content measurements were taken at regular intervals to assess the drying kinetics and effectiveness of the greenhouse. Economic analysis was conducted to evaluate the project's financial viability, considering initial investment, revenue generation, and operational costs. Findings: The findings revealed that the Greenhouse Solar Dryer outperformed sun drying methods, achieving higher temperatures and faster drying times for tomatoes. Specifically, the greenhouse reached maximum temperatures of 38.4 °C and 45.5 °C on the first and second days, respectively, leading to a moisture content of 14.9% wet basis within 11 hours on the second day. In contrast, sun drying resulted in a significantly higher moisture content of 37.9% at the same time, highlighting the effectiveness of the greenhouse. Economic analysis demonstrated that the project had a payback period of 1.6 years, indicating its attractiveness as an investment opportunity for farmers. Unique Contribution to theory, practice and policy: This study makes a unique contribution to knowledge by providing empirical evidence of the drying performance and economic viability of a Greenhouse Solar Dryer for Tomatoes. By demonstrating the effectiveness of the greenhouse in achieving faster drying times and lower moisture content compared to sun drying methods, the study underscores the potential of solar drying technologies in small-scale agricultural settings. Additionally, the economic analysis offers valuable insights into the financial feasibility of adopting greenhouse dryers, particularly for farmers seeking to enhance their income through value-added tomato products.

Modification of Hilhorst model for saturated extract electrical conductivity estimation of coir using frequency domain reflectometry sensors – A laboratory study

Frequency domain reflectometry (FDR) sensors can measure moisture content and electrical conductivity (EC) of growing media, thus providing information for effective water and nutrient management of crops. FDR sensors generally provide the bulk EC (σb) value, which is different from the saturated extract EC (σe) values that most growers and practical studies generally use. To properly estimate σe of media, we modified the previous Hilhorst model that calculates pore water EC (σp) from FDR sensor readings. The 16 coir samples with four moisture and four EC levels were prepared, and their changes in the dielectric constant of bulk medium (εb), σb, and medium temperature from the FDR sensors were recorded and used for analysis. As a result, the εσb=0 (εb when σb is 0) of the coir used in this experiment was 1.64, which was much lower than the εσb=0 suggested for mineral soil (4.1), indicating that the medium-specific εσb=0 should be adjusted. Although σe value estimation through the Hilhorst model with adjusted εσb=0 improved, the values were still unreliable to represent the actual σe values (root mean square error, RMSE = 2.280, R2 = 0.30). To convert the σp derived from the Hilhorst model with adjusted εσb=0 to actual σe, the regression equation was applied as σe = 0.5381 × σp + 1.6493. The adjusted Hilhorst model could provide a more reliable σe estimation (RMSE = 0.929, R2 = 0.62). These results indicate that proper adjustment of εσb=0 for the specific medium is necessary, and adjusting the equation for converting σp into σe would be helpful to properly interpret the σb to practically utilize the FDR sensors for effective water and nutrient management.

Characterisation of hygroelastic properties of compression and opposite wood found in branches of Norway spruce

AbstractThe differential swelling seen between softwood opposite wood (OW) and its neighbouring compression wood (CW) developed in branches prompts several engineering issues such as dimensional instability and cracking. For a more efficient use of resources, the inevitable CW and OW should not be discarded or used as fuel, but incorporated into engineered wood products. Swelling is a hygroelastic phenomenon, where both the swelling and elastic properties of CW and OW are needed in order to make proper structural predictions. In this paper, swelling coefficients and moisture dependent elastic moduli for both CW and OW in the three principal material directions are provided along with measurements of moisture content, density, and microfibril angle. The small deformations necessitate the use of precise X-ray micro-computed tomography for measurements. The results indicate that CW and OW from Norway spruce branches differ in swelling, especially in longitudinal direction at low moisture content. It is noted that CW is a wood type with less pronounced anisotropic behaviour than both OW and normal wood from the stem, with the elastic moduli less sensitive to moisture changes in both longitudinal and transverse directions.

Subgrade Strength Recovery of Fine-Grained-Soil-Containing Roads in Western Oregon Forest

Forest roads are composed of surface and subsurface layers. Determining the seasonal strength and associated moisture changes in these roads is required to understand their capacity. This study looks at changes in the subgrade layer. Laboratory and field studies were conducted to determine the changes in subgrade conditions by measuring moisture content and subgrade strength for fine-grained, non-plastic soils in Western Oregon. One field and one laboratory experiment were conducted. Drying in the field experiment occurred during the summer months in the absence of rainfall, while the laboratory study allowed drying for 48 h under controlled suction. In both cases, there was a slight reduction in the subgrade’s moisture content and no significant improvement in subgrade strength. These findings are supported by the soil physics theory that shows that limited water content reduction is expected for these fine-grained soils, as the numerous tiny soil pores can hold water at high capillary tensions. Adding rock layers adds an insulation effect for the subgrade, further reducing evaporation. Consequently, the moisture content remains high, and there will be little change in subgrade strength during the measurement periods.

Characterization and utilization of sawdust waste generated from advanced manufacture for its application as a thermal insulation in sustainable buildings using the blowing technique

The construction industry is vital for economic development, but it accounts for 40% of energy consumption and 45% of global greenhouse gas emissions. In this context, research has focused on reducing energy demand in homes, particularly through the development of insulation materials. Sawdust is a byproduct available annually in Chile in quantities exceeding 4.5 million tons. Therefore, the objective of this study was to characterize the physical and thermal properties of this waste to evaluate its use as a thermal insulation material. Stability and thermal conductivity tests, as well as density and moisture content measurements, were conducted on the sawdust. Additionally, to assess the functionality of this thermal insulator, the material was applied using the blowing technique in partitions, followed by physical tests. The results indicate that the proposed insulation material has thermal stability up to 270 °C. The thermal conductivity was comparable to conventional mineral wool and fiberglass (0.042–0.048 [W/mK]). The density ranged from 123.77 to 198.15 [kg/m³] depending on the filling time of the specimens but remained low compared to other organic materials. The moisture content was 11.31%, suitable for maintaining good thermal conductivity. This study concludes that sawdust is a viable alternative for thermal insulation, especially when applied through blowing. Its stability and thermal conductivity are comparable to conventional materials, while its thermal inertia is 200% higher than that of glass wool. Furthermore, the low moisture content suggests that there would be no proliferation of pathogens, making it a promising thermal insulator for sustainable construction development. Finally, it is mentioned that the material carbonizes within a limited time, leading to self-extinguishment of the flame.

Globe-LFMC 2.0, an enhanced and updated dataset for live fuel moisture content research.

Globe-LFMC 2.0, an updated version of Globe-LFMC, is a comprehensive dataset of over 280,000 Live Fuel Moisture Content (LFMC) measurements. These measurements were gathered through field campaigns conducted in 15 countries spanning 47 years. In contrast to its prior version, Globe-LFMC 2.0 incorporates over 120,000 additional data entries, introduces more than 800 new sampling sites, and comprises LFMC values obtained from samples collected until the calendar year 2023. Each entry within the dataset provides essential information, including date, geographical coordinates, plant species, functional type, and, where available, topographical details. Moreover, the dataset encompasses insights into the sampling and weighing procedures, as well as information about land cover type and meteorological conditions at the time and location of each sampling event. Globe-LFMC 2.0 can facilitate advanced LFMC research, supporting studies on wildfire behaviour, physiological traits, ecological dynamics, and land surface modelling, whether remote sensing-based or otherwise. This dataset represents a valuable resource for researchers exploring the diverse LFMC aspects, contributing to the broader field of environmental and ecological research.

An Adjusted Waveguide Antenna with A Woodpile-Shaped EBG for Eucalyptus Wood Moisture Content Measurement

An Adjusted Waveguide Antenna with A Woodpile-Shaped EBG for Eucalyptus Wood Moisture Content Measurement

A dual-parameters microwave measurement approach for spruce moisture content

ABSTRACT Moisture content (MC) serves as a pivotal metric for assessing the wood quality, impacting crucial properties such as density, stiffness, and strength. Accurate determination of MC is imperative for ensuring quality and meeting specifications. This study introduces a novel dual-parameters microwave measurement methodology designed for precise MC quantification in spruce. By analyzing the sensitivity and linearity of the S21 with MC across both the S and X bands, we identify the most effective measurement parameters. Experimental work further investigates the correlation between the amplitude and phase of S21 and the MC in spruce, laying the groundwork for a comprehensive understanding of moisture influence on wood properties through microwave techniques. Finally, considering the impact of MC on both the amplitude and phase of S21, we introduce a dual-parameters microwave approach for accurately determining spruce MC. This method has been validated through case studies in both X and S bands. Our discussion extends to the effects of wood material characteristics, moisture distribution within samples, wood texture directions, and specimen dimensions on S21. Experimental results confirm that this approach significantly improves the precision of MC measurements in spruce, achieving an error rate of 0.15% in X band and 0.49% in S band measurements.

Estimating Near-Surface Soil Hydraulic Properties through Sensor-Based Soil Infiltrability Measurements and Inverse Modeling

Near-surface soil hydraulic properties (SHPs) are fundamental for describing and predicting water and energy exchange processes, particularly at the soil–atmosphere interface, and regulating evapotranspiration, infiltration, and runoff in different ecosystems. In this study, a new method was proposed to estimate near-surface SHPs by combining sensor-based soil infiltrability measurements with inverse modeling using HYDRUS-2D. The infiltration rate (IR) was estimated by combining the linear source inflow method with image processing, and Ks was estimated from the near-surface steady-state IR (NSIRM). The SWRC parameters described by the van Genuchten model were estimated using the inverse modeling method of HYDRUS-2D for the fitting of sensor-measured infiltration data. Subsequently, the parameters of the van Genuchten model, including α, n, and l, were inversely estimated. Three undisturbed soils, including two stand humus samples from cork oak (Quercus suber L.) and oleander (Pinus tabuliformis L.) stands and one sandy loam from a farmland, were sampled near the soil surface to validate the proposed method. The estimated Ks was evaluated by the constant head method (CHM). The estimated parameters of the SWRC were validated by those determined through the simultaneous measurement of the soil moisture content and water potential using sensor techniques. The results showed that the Ks estimated from the NSIRM for each soil sample were 23.40 ± 1.21, 23.86 ± 1.83, and 22.99 ± 2.26 mm h−1, respectively. In comparison, the Ks determined by the CHM were 24.41 ± 1.53, 24.26 ± 0.37, and 23.81 ± 0.10 mm/h, respectively. The relative errors of the proposed method were 4.14%, 1.64%, and 3.42%, respectively. For the SWRC estimation, the normalized root mean square errors (NRMSEs) between the measurements and the estimates for each soil sample were 0.1724, 0.1454, and 0.0606, respectively. Based on this, the AWC was obtained, and Ku was deduced from the estimated Ks and SWRC parameters for each soil sample. In general, the proposed method successfully estimates near-surface SHPs, simplifies the measurement device, and provides a new perspective for the in situ determination of near-surface SHPs under field conditions in the near future.

Stem moisture content prediction model for Larix olgensis based on beta regression.

To investigate the longitudinal variation patterns of sapwood, heartwood, bark and stem moisture content along the trunk of artificial Larix olgensis, we constructed mixed effect models of moisture content based on beta regression by combining the effects of sampling plot and sample trees. We used two sampling schemes to calibrate the model, without limiting the relative height (Scheme Ⅰ) and with a limiting height of less than 2 m (Scheme II). The results showed that sapwood and stem moisture content increased gradually along the trunk, heartwood moisture content decreased slightly and then increased along the trunk, and bark moisture content increased along the trunk and then levelled off before increasing. Relative height, height to crown base, stand area at breast height per hectare, age, and stand dominant height were main factors driving moisture content of L. olgensis. Scheme Ⅰ showed the stable prediction accuracy when randomly sampling moisture content measurements from 2-3 discs to calibrate the model, with the mean absolute percentage error (MAPE) of up to 7.2% for stem moisture content (randomly selected 2 discs), and the MAPE of up to 7.4%, 10.5% and 10.5% for sapwood, heartwood and bark moisture content (randomly selected 3 discs), respectively. Scheme Ⅱ was appropriate when sampling moisture content measurements from discs of 1.3 and 2 m height and the MAPE of sapwood, heartwood, bark and stem moisture content reached 7.8%, 11.0%, 10.4% and 7.1%, respectively. The prediction accuracies of all mixed effect beta regression models were better than the base model. The two-level mixed effect beta regression models, considering both plot effect and tree effect, would be suitable for predicting moisture content of each part of L. olgensis well.

Prediction and visualization of moisture content in Tencha drying processes by computer vision and deep learning.

It is important to monitor and control the moisture content throughout the Tencha drying processing procedure so that its quality is ensured. Workers often rely on their senses to perceive the moisture content, leading to relative subjectivity and low reproducibility. Traditional drying methods, which are used for measuring moisture content, are destructive to samples. This research was conducted using computer vision combined with deep learning to detect moisture content during the Tencha drying process. Different color space components of Tencha drying sample images were first extracted by computer vision. The color components were preprocessed using MinMax and Z score. Subsequently, one-dimensional convolutional neural networks (1D-CNN), partial least squares, and backpropagation artificial neural networks models were built and compared. The 1D-CNN model and Z scorepreprocessing achieved superior predictive accuracy, with correlation coefficient of prediction (Rp ) = 0.9548 for moisture content. The migration of moisture content during the Tencha drying process was eventually visualized by mapping its spatial and temporal distributions. The results indicated that computer vision combined with 1D-CNN was feasible for moisture prediction during the Tencha drying process. This study provides technical support for the industrial and intelligent production of Tencha. © 2024 Society of Chemical Industry.

GRU–Transformer: A Novel Hybrid Model for Predicting Soil Moisture Content in Root Zones

The accurate measurement of soil moisture content emerges as a critical parameter within the ambit of agricultural irrigation management, wherein the precise prediction of this variable plays an instrumental role in enhancing the efficiency and conservation of agricultural water resources. This study introduces an innovative, cutting-edge hybrid model that ingeniously integrates Gated Recirculation Unit (GRU) and Transformer technologies, meticulously crafted to amplify the precision and reliability of soil moisture content forecasts. Leveraging meteorological and soil moisture datasets amassed from eight monitoring stations in Hebei Province, China, over the period from 2011 to 2018, this investigation thoroughly assesses the model’s efficacy against a diverse array of input variables and forecast durations. This assessment is concurrently contrasted with a range of conventional machine learning and deep learning frameworks. The results demonstrate that (1) the GRU–Transformer model exhibits remarkable superiority across various aspects, particularly in short-term projections (1- to 2-day latency). The model’s mean square error (MSE) for a 1-day forecast is notably low at 5.22%, reducing further to a significant 2.71%, while the mean coefficient of determination (R2) reaches a high of 89.92%. Despite a gradual increase in predictive error over extended forecast periods, the model consistently maintains robust performance. Moreover, the model shows exceptional versatility in managing different soil depths, notably excelling in predicting moisture levels at greater depths, thereby surpassing its performance in shallower soils. (2) The model’s predictive error inversely correlates with the reduction in parameters. Remarkably, with a streamlined set of just six soil moisture content parameters, the model predicts an average MSE of 0.59% and an R2 of 98.86% for a three-day forecast, highlighting its resilience to varied parameter configurations. (3) In juxtaposition with prevalent models such as Support Vector Regression (SVR), K-Nearest Neighbors (KNN), Gradient Boosting Decision Tree (GBDT), XGBoost, Random Forest, and deep learning models like Deep Neural Network (DNN), Convolutional Neural Network (CNN), and standalone GRU-branch and Transformer-branch models, the GRU–Transformer framework demonstrates a significant advantage in predicting soil moisture content with enhanced precision for a five-day forecast. This underscores its exceptional capacity to navigate the intricacies of soil moisture data. This research not only provides a potent decision-support tool for agricultural irrigation planning but also makes a substantial contribution to the field of water resource conservation and optimization in agriculture, while concurrently imparting novel insights into the application of deep learning techniques in the spheres of agricultural and environmental sciences.

Decline of a North American rocky intertidal foundation species linked to extreme dry, downslope Santa Ana winds

Foundation species are essential to ecosystem function, but their role as habitat providers is predicated on their spatial dominance. Worldwide, kelps, seagrasses, corals, and other marine foundation species have declined. This is true also for rockweeds, the canopy-forming analog of subtidal kelp forests in temperate rocky intertidal ecosystems. On the west coast of North America, dense beds of the rockweed Silvetia compressa occur across large biogeographic regions, benefitting numerous species by ameliorating physical stress caused by sun exposure, desiccation, heat, and wave disturbance. Like many rockweed species, Silvetia is long-lived, slow-growing, and short-dispersing – characteristics that reduce its resilience to disturbance. Using a generalized additive mixed-effects model with explicit spatial effects, we analyzed canopy cover data from 30 sites spanning 18 years, and we tested the hypothesis that Silvetia population trends are tightly linked to atmospheric climate conditions, particularly Santa Ana wind events (SAWs): strong, hot, and dry downslope winds that originate inland and move offshore. We found that the rockweed had declined markedly, particularly at sites south of the major biogeographic break, Point Conception (PC), including the California Channel Islands and southern California mainland, and a highly significant negative effect of dewpoint depression, a measure of moisture content in the atmosphere, on Silvetia cover across all three regions in this study. Our results suggest that any increases in the frequency or intensity of SAWs are likely to lead to large declines and possible extirpation of Silvetia, as well as the important ecological services the species provides.

Impact of Rice Husk Ash on the Compaction Characteristics of Soil

Usually, the measurement of maximum dry density (MDD) and optimum moisture content (OMC) is important for assessing the quality control of the compacted fill or earthwork constructions as the compaction parameters. Rice husk ash (RHA), plentifully available in many rice-producing countries, can be used as a building material. This study mainly tries to investigate the effect of RHA on compaction features of sandy soil classified as A-2-4 or SM for soil stabilization. Nominal to a maximal dosage of RHA addition in the soil was considered for the experiments by the standard Proctor compaction tests. The result revealed that by increasing the amount of RHA in the soil, MDD was reduced and OMC increased significantly. It can be concluded that applying a soil-RHA combination is beneficial to soil improvement. Jagannath University Journal of Science, Volume 10, Number II, Dec. 2023, pp. 87-93

Optical measurement of paper moisture content with application in paper pressing

Optical measurement of paper moisture content with application in paper pressing