Managing Apparent Loss and Real Loss from the Nexus Perspective Using System Dynamics

When water utilities establish water loss control programs, they traditionally focus on apparent loss rather than real loss when considering economic feasibility in the water sector. There is an urgent need for new management approaches that can address complex relationships and ensure the sustainability of natural resources among different sectors. This study suggests a novel approach for water utilities to manage water losses from the water-energy (WE) Nexus perspective. The Nexus model uses system dynamics to simulate twelve scenarios with the differing status of water loss and energy intensities. This analysis identifies real loss as one of the main causes of resource waste and an essential factor from the Nexus perspective. It also demonstrates that the energy intensity of each process in the urban water system has a significant impact on resource use and transfer. The consumption and movement of resources can be quantified in each process involved in the urban water system to distinguish central and vulnerable processes. This study suggests that the Nexus approach can strongly contribute to quantifying the use and movement of resources between water and energy sectors and the strategic formulation of sustainable and systematic water loss management strategies from the Nexus perspective.

The Structural Formation of Cement Stone Modified by a Solution of Superabsorbent Polymer

With the development of 3D technologies in construction, the development of formulations that are indifferent to the influence of the environment is in demand. Conditions of intense water loss from cement systems arise during the layer-by-layer printing process. This leads to a decrease in density, high shrinkage, and a decrease in the strength and durability of the composite. The use of superabsorbent polymer (SAP) solutions, in contrast to granules, will provide hardening Portland cement with a water supply for internal care of hydration processes. The aim of the work is to study the effect of SAP solution on the processes of structure formation of cement stone, hardening in unfavorable conditions. In this paper, the features of the structure formation of cement systems in the presence of SAP are established. It is shown that the use of polymer in an amount of no more than 1.5% by the weight of Portland cement provides the formation of a more perfect crystalline structure of the cement stone, which allows for an increase in the degree of cement hydration. When the amount of SAP is ≥ 1.5% by the weight of Portland cement, a decrease in the intensity of the maxima corresponding to hydration products is observed.

Effect of Osmo Dehydration on Quality Attributes of Bilimbi (Averroha bilimbi) Fruits

Background: Bilimbi is a profusely bearing tree and majority of fruits produced are wasted due to lack of proper preservation methods. Osmo-dehydration studies on quality attributes of bilimbi (Averroha bilimbi) was conducted with the objective to standardize the process variables for osmodehydrated bilimbi and to assess the retention of bioactive compounds. Methods: Harvested mature bilimbi fruits of uniform size were washed, surface dried, pricked and blanched in hot water for one minute. Blanched fruits were subjected to osmotic treatment, with sucrose solution of 40, 60 and 80°B for 60, 120 and 180 minutes. The osmodehydrated bilimbi fruits were analyzed for mass transfer, biochemical and sensory qualities. Best treatments were stored for four months in the room temperature. Result: Mass transfer characters viz., solid gain, water loss, percentage weight reduction, yield and biochemical parameters such as reducing sugar and total sugar increased with increase in osmotic concentration and immersion time whereas free acids, ascorbic acid and antioxidant activity were decreased. The osmotic treatment of 80°B for 180 minutes recorded the highest value for solid gain (5.10%), water loss (16.72%), weight reduction (22.57%), ratio of water loss to solid gain (3.25%) and yield (21.13%) which exhibited superior sensory scores for taste (8.43), flavor (8.27), texture (8.46) and overall acceptability (8.43). The best three treatments selected based on sensory analysis were subjected to storage stability studies under room temperature. Osmodehydrated bilimbi obtained highest sensory score at the end of storage.

Building a Barrier: The Influence of Different Wax Fractions on the Water Transpiration Barrier of Leaf Cuticles

Waxes are critical in limiting non-stomatal water loss in higher terrestrial plants by making up the limiting barrier for water diffusion across cuticles. Using a differential extraction protocol, we investigated the influence of various wax fractions on the cuticular transpiration barrier. Triterpenoids (TRPs) and very long-chain aliphatics (VLCAs) were selectively extracted from isolated adaxial leaf cuticles using methanol (MeOH) followed by chloroform (TCM). The water permeabilities of the native and the solvent-treated cuticles were measured gravimetrically. Seven plant species (Camellia sinensis, Ficus elastica, Hedera helix, Ilex aquifolium, Nerium oleander, Vinca minor, and Zamioculcas zamiifolia) with highly varying wax compositions ranging from nearly pure VLCA- to TRP-dominated waxes were selected. After TRP removal with MeOH, water permeability did not or only slightly increase. The subsequent VLCA extraction with TCM led to increases in cuticular water permeabilities by up to two orders of magnitude. These effects were consistent across all species investigated, providing direct evidence that the cuticular transpiration barrier is mainly composed of VLCA. In contrast, TRPs play no or only a minor role in controlling water loss.

An intelligent irrigation system based on internet of things (IoT) to minimize water loss

This paper proposes a comparison of three machine learning algorithms for a better intelligent irrigation system based on internet of things (IoT) for differents products. This work's major contribution is to specify the most accurate algorithm among the three machine learning algorithms (k-nearest neighbors (KNN), support vector machine (SVM), artificial neural network (ANN)). This is achieved by collecting irrigation data of a specific products and split it into training data and test data then compare the accuracy of the three algorithms. To evaluate the performance of our algorithm we built a system of IoT devices. The temperature and humidity sensors are installed in the field interact with the Arduino microcontroller. The Arduino is connected to Raspberry Pi3, which holds the machine learning algorithm. It turned out to be ANN algorithm is the most accurate for such system of irrigation. The ANN algorithm is the best choice for an intelligent system to minimize water loss for some products.