Large urban communication networks such as smart cities are an ecosystem of devices and services cooperating to address multiple issues that greatly benefit end users, cities, and the environment. ...LinkNYC is a first-of-its-kind urban communications network aiming to replace all payphones in the five boroughs of New York City (NYC) with kiosk-like structures providing free public Wi-Fi. We consolidate these networks with standalone edge cloud devices known as cloudlets and introduce geographically distributed content delivery cloudlets (CDCs) to store popular Internet content closer to end users; essential in environments with diverse and dynamic content interests. A content-centric and delivery framework is proposed leveraging NYC's population densities and CDCs for interest-based in-network caching. Analysis shows that although the adoption of multiple CDCs dramatically improves overall network performance, advanced caching policies are needed when considering increased content heterogeneity. Thus, we propose popularity-driven and cooperation-based caching policies at individual CDCs to account for user and content dynamics over time. The amalgamation of urban population densities, multiple CDC placements and smarter caching techniques helps exploit the ultimate benefits of a content-centric urban communications network and dramatically improves overall network performance and responsiveness. Our proposed solutions are validated using LinkNYC as a use-case.
Physico-chemical characteristics of milk are related to its composition for a particular animal species. Sheep milk contains higher levels of total solids and major nutrient than goat and cow milk. ...Lipids in sheep and goat milk have higher physical characteristics than in cow milk, but physico-chemical indices (i.e., saponification, Reichert Meissl and Polenske values) vary between different reports. Micelle structures in goat and sheep milk differ in average diameter, hydration, and mineralization from those of cow milk. Caprine casein micelles contain more calcium and inorganic phosphorus, are less solvated, less heat stable, and lose β-casein more readily than bovine casein micelles. Renneting parameters in cheese making of sheep milk are affected by physico-chemical properties, including pH, larger casein micelle, more calcium per casein weight, and other mineral contents in milk, which cause differences in coagulation time, coagulation rate, curd firmness, and amount of rennet needed. Renneting time for goat milk is shorter than for cow milk, and the weak consistency of the gel is beneficial for human digestion but decreases its cheese yield. Triacylglycerols (TAG) constitute the biggest part of milk lipids (nearly 98%), including a large number of esterified fatty acids. Sheep and goat milk also have simple lipids (diacylglycerols, monoacylglycerols, cholesterol esters), complex lipids (phospholipids), and liposoluble compounds (sterols, cholesterol esters, hydrocarbons). The average fat globule size is smallest (<3.5
μm) in sheep milk followed by goat and cow milk. Five fatty acids (C10:0, C14:0, C16:0, C18:0, and C18:1) account for >75% of total fatty acids in goat and sheep milk. Levels of the metabolically valuable short and medium chain fatty acids, caproic (C6:0) (2.9%, 2.4%, 1.6%), caprylic (C8:0) (2.6%, 2.7%, 1.3%), capric (C10:0) (7.8%, 10.0%, 3.0%), and lauric (C12:0) (4.4%, 5.0%, 3.1%) are significantly higher in sheep and goat than in cow milk, respectively. Principal caseins (CN) in goat, sheep and cow milk are α
s1-CN, α
s2-CN, β-CN and κ-CN. The main forms of caprine and ovine caseino-macropeptides (CMP), which are the soluble C-terminal derivatives from the action of chymosin on κ-casein during the milk clotting process of cheesemaking, have been identified and are a good source of antithrombotic peptides. Sheep and goat milk proteins are also important sources of bioactive angiotensin converting enzyme (ACE) inhibitory peptides and antihypertensive peptides. They can provide a non-immune disease defence and control of microbial infections. Important minor milk proteins include immunoglobulins, lactoferrin, transferrin, ferritin, proteose peptone, calmodulin (calcium binding protein), prolactin, and folate-binding protein. Non-protein nitrogen (NPN) contents of goat and human milks are higher than in cow milk. Taurine in goat and sheep milk derived from sulphur-containing amino acids has important metabolic functions as does carnitine, which is a valuable nutrient for the human neonate. Mineral and vitamin contents of goat and sheep milk are mostly higher than in cow milk.
Wood pellet is an important biomass-based source of cleaner and renewable energy with a growing global demand.
Populus
spp. (poplars) are fast-growing trees with high productivity potential in the ...southeastern US. Selected pellet-quality parameters were examined as a proxy for assessing if the feedstock quality of poplar stem wood was affected by stand location (Coastal, Piedmont, Mountains of North Carolina, clone “140”), stand age (five vs. seven years, clone-“140”), clones (“140”, “176”, “230”, “185”, “356”) and stem sections (clone-“356”) by examining sulfur, ash, volatile-matter, fixed-carbon, gross caloric, carbon, hydrogen, and nitrogen contents of moisture-free samples. Location-study samples significantly varied (
p≤0.027
) in ash (0.6–0.9 wt%), and gross caloric (19.75–19.89 MJ/kg) contents and study clones significantly differed (
p≤0.0271
) in ash (means: 0.75–0.97 wt%), volatile-matter (means: 80.5–82.7 wt%), fixed-carbon (means: 16.5–18.7 wt%) and hydrogen (means: 4.19–4.78 wt%) contents. The only other significant variations were hydrogen (mean: 4.19–4.67 wt%) content with stand age (
p≤0.009
) and gross caloric values (19.5–19.9 MJ/kg) among stem sections (
p = 0.0003
). This study showed that poplars have stem-wood quality suitable for pellet production and most of the studied feedstock samples had ash, nitrogen, sulfur, and caloric (at 10% moisture content) contents that would meet the EN
plus
pellet-quality standards. Results from this study can be used for facilitating decisions about managing poplar stands for sustainable pellet feedstock production in the southeastern US, including selecting optimum rotation length, pellet-suitable clones, and sites.
Understanding Writing Transfer Randall Bass, Jessie L. Moore / Randall Bass, Jessie L. Moore
2017, 2023-07-03, 2017-01-20
eBook
While education is based on the broad assumption that what one learns here can transfer over there across critical transitions what do we really know about the transfer of knowledge?The question ...is all the more urgent at a time when there are pressures to unbundle higher education to target learning particular subjects and skills for occupational credentialing to the detriment of integrative education that enables students to make connections and integrate their knowledge, skills and habits of mind into a adaptable and critical stance toward the worldThis book the fruit of two-year multi-institutional studies by forty-five researchers from twenty-eight institutions in five countries identifies enabling practices for, and five essential principles about, writing transfer that should inform decision-making by all higher education stakeholders about how to generally promote the transfer of knowledge.This collection concisely summarizes what we know about writing transfer and explores the implications of writing transfer research for universities institutional decisions about writing across the curriculum requirements, general education programs, online and hybrid learning, outcomes assessment, writing-supported experiential learning, e-portfolios, first-year experiences, and other higher education initiatives. This volume makes writing transfer research accessible to administrators, faculty decision makers, and other stakeholders across the curriculum who have a vested interest in preparing students to succeed in their future writing tasks in academia, the workplace, and their civic lives, and offers a framework for addressing the tensions between competency-based education and the integration of knowledge so vital for our society.
Z -number is the general representation of real-life information with reliability, and it has adequate description power from the point of view of human perception. This study develops an innovative ...method for addressing multicriteria group decision-making (MCGDM) problems with Z -numbers under the condition that the weight information is completely unknown. Processing Z -numbers requires effective support of reliable tools. Then, the normal cloud model can be employed to analyze the Z -number construct. First, the potential information involved in Z -numbers is invoked, and a novel concept of normal Z + -value is proposed with the aid of the normal cloud model. The operations, distance measurement, and power aggregation operators of normal Z + -values are defined. Moreover, an MCGDM method is developed by incorporating the defined distance measurement and power aggregation operators into the MultiObjective Optimization by Ratio Analysis plus the Full Multiplicative Form. Finally, an illustrative example concerning air pollution potential evaluation is provided to demonstrate the proposed method. Its feasibility and validity are further verified by a sensitivity analysis and comparison with other existing methods.
In this letter, a high-gain circularly polarized (CP) array antenna with low profile and low grating lobe property is proposed. The array is composed of high-gain and low sidelobe CP patch elements ...based on odd high-order modes. By adding perturbation structure, a pair of orthogonal modes (TM 30 /TM 03 ) of the patch with 90° phase difference is diagonally excited. Meanwhile, by introducing five circular slots on the patch, four sidelobes of the element radiation pattern in x o z plane and y o z plane are effectively reduced. Consequently, the large grating lobes of array antenna can be avoided. Then, a 2 × 2 array prototype is designed and fabricated for verification. The thickness of array is only 0.5 mm (0.027 λ 0 ). The peak gain and aperture efficiency reach up to 17.5 dBic and 55.5%, respectively. When the element spacing is more than 1 λ 0 , the measured maximum grating lobe level at 16.25 GHz is only −15 dB.
The objective of the present study was to evaluate whether the content of sugar, protein, fat, or fibre in commercially available and specially formulated plant-based beverages (oat, soya and pea) ...influences the growth rates of Listeria. Beverages were inoculated with a strain cocktail of Listeria (approximately 1 × 103 CFU/mL), and the data demonstrated that Listeria could proliferate in all tested beverages. Moreover, varying concentrations of naturally occurring or added sugar (0–3.3%), protein (3.3–5%), fat (1.1–3.5%) and added fibre (0–1.5%) did not have a statistically significant (p > 0.05) impact on the growth rates of Listeria in the tested plant-based beverages. These data suggest that the wide variety of commercial plant-based beverages serve as an ideal medium for the growth of Listeria irrespective of product composition. All the various products tested provided sufficient nutrients to support at least a 2.6-log increase of Listeria within 16 h at room temperature, with some beverages supporting a 3-log increase. Therefore, these data highlight the importance of careful storage and handling of these increasingly varied and popular products.
•Plant-based drinks support the rapid growth of Listeria at 20oC.•Growth rates were consistent across a wide variety of beverages.•Lower sugar, protein or fat did not reduce growth rates.•On-package recommendations should be considered.
One of the most common approaches to reducing the environmental impact of nitrogen (N) fertilisation in intensive agrosystems is to adjust the N input of the crop requirement. This adjustment is ...frequently related to the nitrogen nutrition index (NNI) based on the concepts of the critical and actual N absorbed (kg/ha) in the crop canopy (respectively, NC and CNC). Accurate estimation of the NC and CNC at the field scale over large areas based on freely available satellite imagery is thus a key issue to address. Relying on a large dataset of farmers' fields, this study highlights the high correlation (R2 = 0.90) between the wheat CNC and canopy chlorophyll content (CCC) retrieved from Sentinel-2 (S2) with an Artificial Neural Network (ANN). The estimation is related to errors of 4 and 21 kg/ha (depending on the growing stage), which is a promising result for evaluating the NNI. There are four major outcomes from this result: (i) the importance of working at the canopy level; (ii) the independence of the relationship to the considered cultivars; (iii) the dependence of the relationship on the growing stage; and (iv) the potential to use only the 10 m S2 bands, opening the way for precision agriculture. In parallel, estimation accuracies were investigated for the three biophysical variables (BV) related to the CNC and NC, i.e., the green area index (GAI), leaf chlorophyll content (Cab) and CCC. From this analysis, the added value of the red-edge bands for improving the estimation of the 3 BVs of interest was quantified as was the performance reduction related to the field heterogeneity.
•The wheat nitrogen content can be estimated only with the 10 m bands of Sentinel-2.•The wheat nitrogen content is accurately estimated at the canopy level.•Within-pixel heterogeneity affects the GAI estimation accuracy.•The red-edge bands increase the GAI estimation accuracy along the growing season.
In the era of the Internet of Things, spatial relationships are mostly constructed based on physical location information, and graph convolutional neural networks are used to solve the problem of ...multipoint noise prediction with the spatial distribution. To solve the problems of insufficient relation mining and poor long-term prediction accuracy in building spatial relations based on physical distance in graph convolution, the diffusion graph convolution recursive neural network (DCRNN) noise prediction system (<inline-formula><tex-math notation="LaTeX"> \alpha</tex-math></inline-formula>DTW-DCRNN) based on the <inline-formula><tex-math notation="LaTeX"> \alpha</tex-math></inline-formula> coefficient dynamic time warping (<inline-formula><tex-math notation="LaTeX"> \alpha</tex-math></inline-formula>DTW) method is proposed. First, the 3<inline-formula><tex-math notation="LaTeX">\sigma</tex-math></inline-formula> criterion is innovatively used to deal with sparse zero-value noise data, and the DTW method is proposed to mine the spatial relationship. Second, the <inline-formula><tex-math notation="LaTeX">\alpha</tex-math></inline-formula>DTW method is proposed to calculate the similarity distance of unaligned periodic sequences using the penalty coefficient. Moreover, spatial relationships are reconstructed using <inline-formula><tex-math notation="LaTeX">\alpha</tex-math></inline-formula>DTW and noise is predicted using DCRNN for long-term forecasting needs. Finally, the Kalman filter driven by traffic flow data is used to correct prediction noise to improve prediction stability. Experimental results show that the proposed system can save training time, reduce prediction errors, and make long-term prediction more accurate. Compared with the DCRNN model, the <inline-formula><tex-math notation="LaTeX">\alpha</tex-math></inline-formula>DTW-DCRNN system reduces the root-mean-square error and the mean absolute error by 11% and 5%, respectively, and reduces mean absolute percentage error by 5.26%.
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