GIS-based research on climate suitable region of Loquat in Lishui, Zhejiang province of China

To develop a climatic suitability index and conduct the cultivation division of loquat in Lishui, Zhejiang province of China, we introduced the multi-indicator comprehensive risk assessment method to combine with the hazard factor model, necessary climatic elements during the growing season of loquat and geographic information elements. Results show that the annual active accumulated temperature (rainfall ) over most Lishui is more than 4500°C (1600mm). The two climatic factors above can well meet the needs of loquat growth. The frozen injury days over most Lishui during the young fruit period of loquat are more than 10.0 days, which are higher than those during the flowering period. The annual mean number of continuous overcast rain occurrences is less than 4.5. The climatic mean annual occurrence of persistent abnormal high temperature weather is less than 1. Overall, the most suitable area for the cultivation of loquat mainly located over the relatively flat areas such as river valleys and basins, especially the banks of the Oujiang River in Qingtian and Xiaoxi River valley in Jingning. The excellent combinations of light, heat and water with relatively few meteorological disasters just like frozen injury, continuous rain and high temperature provide a good climatic conditions of the high-quality of loquat planting.

Indicators of reproducibility and suitability for assessing the quality of production services

<p>A technique is proposed for estimating the probability of the possible appearance of defective products or the inconsistency of the production service on the basis of indexes of suitability and reproducibility of the production process.</p><p>The index of reproduction is recommended to be calculated on the basis of the standard deviation, which can be established by the average span of the control map and the limits of the tolerance field. At the same time, the production process must necessarily be in a state of statistical controllability. The suitability index cannot be calculated on the basis of the control card characteristics, but it is evaluated solely on the basis of the total of the standard deviation, which is calculated by the Bessel formula and the tolerance limits. The production process does not need to be statistically controllable. Conclusions on the suitability or insufficiency of the products (production services) are based on the value of the indexes of reproduction and suitability, which can take values less than or greater than one. On the basis of these indexes of obtained values, the probability of production appearance or characteristics of the production process, that does not match the established requirements, is established.</p>

Suitable Areas for Apiculture Expansion Determined by Antioxidant Power, Chemical Profiles, and Pesticide Residues in Caldcluvia paniculate Honey and Beeswax Samples

Forty-two samples of Tiaca Honey (Caldcluvia paniculata) obtained from beehives belonging to 14 apiaries (three honey samples per apiary) were collected at the end of January near Osorno (40°34′ S, 73°8′ W), Puyehue (40°40′ S, 72°37′ W) and Frutillar 41°7′ S, 72°59′ W) covering an area of 1240 km2. They presented the highest phenol contents (0.36 mg gallic acid equivalent/kg) and antioxidant power (1.27 mM equivalent of Fe+2/g of sample), and were among the highest for antiradical activity. Phenol contents and antioxidant power (r = 0.72, p-value < 0.01) and total phenol contents and antiradical activity (r = 0.69; p-value < 0.01) displayed linear correlations. Only two beeswax samples showed residues of the pesticide fenhexamid. The respective sites (Purranque [40°55′ S, 73°10′ W] and Coligual [40°49′ S, 72°54′ W]) were the only areas located near active farms. Additionally, the m/z value 163.1091 was found as an element to identify honeys. Data were used to construct a mapped suitability index ranking for pesticide-free areas with high biological quality. The provided chemical profiles will aid local beekeepers in obtaining international certifications, particularly for the EU market. In turn, the constructed maps indicate suitable areas for apiculture expansion, while differentiated pesticide detection in honey and beeswax requires further comparative research.

Structure and Performance Attributes Optimization and Ranking of Gamma Irradiated Polymer Hybrids for Industrial Application

The selection of suitable composite material for high-strength industrial applications, from the list of available alternatives, is a tedious task as it requires an optimized structural performance-based solution. This study aimed to optimize the concentration of fillers, i.e., vinyl tri-ethoxy silane and absorbed gamma-dose, to enhance the properties of an industrial scale polymer, i.e., ultra-high molecular weight polyethylene (UHMWPE). The UHMWPE hybrids, in addition to silane, were treated with (30, 65, and 100 kGy) gamma dose and then tested for ten application-specific structural and performance attributes. The relative importance of attributes based on an 11-point fuzzy conversation was used for establishing the material assessment graph and corresponding adjacency matrix. Afterwards, the normalized values of attributes were used to establish the decision matrix for each alternative. The normalization was performed after the identification of high obligatory valued (HOV) and low obligatory valued (LOV) attributes. After this, suitability index values (SIVs) were calculated for ranking the hybrids that revealed hybrids 65 kGy irradiated the hybrid as the best choice and ranked as first among the existing alternatives. The major responsible factors were higher oxidation strength, a dense cross-linking network, and elongation at break. The values of the aforementioned factors for 65 kGy irradiated hybrids were 0.24, 91, and 360 MPa, respectively, as opposed to 0.54, 75, and 324 MPa for 100 kGy irradiated hybrids, thus placing the latter in second place regarding higher values of Yield Strength and Young Modulus. Finally, it is believed that the reported results and proposed model in this study will improve preoperative planning as far as considering these hybrids for high-strength industrial applications including total joint arthroplasty, textile-machinery pickers, dump trucks lining ships, and harbors bumpers and sliding, etc.

Development of Application Specific Intelligent Framework for the Optimized Selection of Industrial Grade Magnetic Material

This article attempts to introduce a simple and robust way for the classification of soft magnetic material by using multivariate statistics. The six magnetic properties including coercive magnetic field, relative magnetic permeability, electrical resistivity magnetic inductions, i.e., remanence and saturation along with Curie temperature are used for the classification of 16 soft magnetic materials. Descriptive statistics have been used for defining the prioritization order of the mentioned magnetic characteristics with coercive magnetic field and Curie temperature as the most and least important characteristics for classification of soft magnetic material. Moreover, it has also justified the usage of cluster analysis and principal component analysis for classifying the enlisted materials. After descriptive statistics, cluster analysis is used for classification of materials into four groups, i.e., excellent, good, fair and poor while defining the prioritization order of materials on a relative scale. Principal component analysis reveals that the relative permeability is responsible for defining 99.69% of total variance and is also negatively correlated with the coercive magnetic field. Therefore, these two characteristics are considered the responsible factors for categorically placing the enlisted materials into four clusters. Furthermore, principal component analysis also helps in figuring out the fact that a combined influential consequence of relative permeability, coercive magnetic field, electrical resistivity and critical temperature are responsible for defining prioritization ordering of materials within the clusters. The material’s suitability index is identified while making use of adjacency and decision matrices obtained from material assessment graph and relative importance of magnetic properties, respectively. Afterward this material suitability index is used to rank the enlisted materials based on selected attributes. According to the suitability index, the best choice among enlisted soft magnetic materials is Supermalloy, Magnifer 7904 which is present in group 1 labeled as excellent by multivariate analysis. Therefore, the results of graph theory are in accordance with cluster analysis and principal component analysis, thus confirming the potential of this intelligent approach for the selection application specific magnetic materials.

Modeling of habitat suitability for sea cucumber ranching in Sintok Island, Karimunjawa National Park, Indonesia

Increasing demand for marine resources, such as sea cucumber, has led to widespread interest in their conservation, one of which is sea ranching. This study sought to identify habitat suitability for sea cucumber Holothuria scabra ranching. The proposed location was Sintok Island, one small island part of Karimunjawa Archipelagos. The HSI (Habitat Suitability Index) model was used to identify potential sites for sea cucumber ranching. Twelve habitat factors were used as input variables for the HSI model: sediment classification, water temperature, salinity, pH, dissolved oxygen, depth, transparency, current, depth, organic matter and chlorophyll-a of the sediment, seagrass density, and tide. The weighting of each habitat factor was defined through the Delphi method. Sediment classification and seagrass density were the most and less important condition affecting the HSI of H. scabra in the different study areas with weighing index of 0.2191 and 0.015 respectively. The HSI of Southern Station (Station 1) was relatively low (0.79-0.81), meaning the site was not suitable for sea ranching of H. scabra. In contrast, the western (Station 2) and the northern part (Station 3) of Sintok Island, were preferable sites, suitable as habitats for restoration efforts in sea ranching.

Landfill Site Selection Using GIS and (AHP): Case Study of Ranya City

Ranya City is located in North West of Sulaymaniyah Governorate, Iraq. It has an area of (76.7) km2. In 2018, it was home for (102,571) inhabitants. Presently, there are no landfills in the study area that fulfills necessary environmental requirements; thus, informal and unsuitable solid waste dumping is negatively impacting human health and the environment. Land fill site selection can be a difficult task as it is impacted by different factors and regulations. This study is an attempt to identify and evaluate suitable landfill locations in the study area using Analytical Hierarchy Process (AHP) and Geographic Information System (GIS). Ten criteria are used in this process which includes: groundwater depth, surface water, residential areas, Geological formations, slope, elevation, soil type, land use, roads and archeological sites. AHP was used to determine the weight for each criteria using pairwise comparison matrix. Three classes of suitability index were found: unsuitable (98.47%), moderately suitable (0.003%) and suitable (1.52%) of the study area. Three suitable landfill sites were identified as candidate sites that meet the requirements with an area of (0.29) km2, (0.12) km2 and (0.098) km2 respectively.

Modelling the Spatial Distribution of Habitats of Main Cephalopod Taxa in Inshore Waters of Zhejiang Province at Spring and Autumn

Due to the declining catch of the ground fish, cephalopod as a short-lived invertebrate with commercially important value has become the main fishery target species of East China Sea (ECS) in recent decades. Therefore, it is necessary to explore its habitat for the sustainable utilization. In this study, with the individual density of cephalopod derived from the fishery survey data in the coast of Zhejiang Province from 2014 to 2019 and remote sensing data, the habitat suitability index (HSI) model of typical cephalopod (Loliginidae, Octopodidae, Sepiidae, and Sepiolidae) in spring and autumn was obtained. The habitat isolines of core zone, common zone and marginal zone were also established and then compared among different typical cephalopod taxa based on arithmetic mean model (AMM). The distribution ranges of SST and chlorophyll-a of cephalopod were respectively 12.95~21.91 ℃ and 0.52~5.57 mg/m3 in spring and 17.02~22.94℃ and 0.26~6.02 mg/m3 in autumn. The prediction results of the HSI model suggested that the cephalopod distribution areas were concentrated in the range of 122°~124°E, 29.5°~31°N, displaying the distribution direction from coastal area to the northeast. The accumulative density of the four cephalopod taxa in the area with HSI>0.6 accounted for 73.9%. The overlap between the prediction results of HSI model and the actual density in 2019 also proved the good predictability of HSI model based on AMM. Four cephalopod taxa showed distribution differences. Sepiolidae had the widest distribution area, whereas Octopodidae had the narrowest distribution area.

On the Optimization of Self-Organization and Self-Management Hardware Resource Allocation for Heterogeneous Clouds

There is a tendency, during the last years, to migrate from the traditional homogeneous clouds and centralized provisioning of resources to heterogeneous clouds with specialized hardware governed in a distributed and autonomous manner. The CloudLightning architecture proposed recently introduced a dynamic way to provision heterogeneous cloud resources, by shifting the selection of underlying resources from the end-user to the system in an efficient way. In this work, an optimized Suitability Index and assessment function are proposed, along with their theoretical analysis, for improving the computational efficiency, energy consumption, service delivery and scalability of the distributed orchestration. The effectiveness of the proposed scheme is being evaluated with the use of simulation, by comparing the optimized methods with the original approach and the traditional centralized resource management, on real and synthetic High Performance Computing applications. Finally, numerical results are presented and discussed regarding the improvements over the defined evaluation criteria.