Determining the optimum level of resource allocation on cotton farms in Southwest Tennessee by Linear Programmming technique

Cotton production is one of the most important farm enterprises in the farm economy of the United States; According to the 1954 Census of Agriculture cotton was grown on 18.1 percent of all farms and on 5.7 percent of the cropland harvested. The farm cash receipts from cotton lint and cotton seed were 7 percent of total farm cash receipts recorded in 1954. In the Old South, the farm income from cotton was 35 percent of total farm income from all enterprises. In the midsouthern hilly area, classified as Region III in the special report on cotton, and in which the present study area is located, cotton is also of major importance. In 1954, 66.9 percent of all farms in this region grew cotton; and the farms which obtained major share of income from cotton - the cotton farms, made up 89.1 percent of all commercial farms. The farms were classified in the 1954 Census of Agriculture, into six economic groups. The percentage distribution of cotton farms among these economic classes is quite revealing in that it provides strong indicators of the low average income of cotton farms in this region. For example, only 1.3 percent of Cotton farms had gross sales of $10,000 or more in 1954, but 75.6 percent had gross income of less than$2,500. Less than a fourth were in the $2,500-$9,999 income group. The corresponding figures for the whole of United States were 21.9 percent, 49.3 percent, and 28.8 percent, respectively

Purification And Characterization Of Four Novel Proteases From The Periplasmic Space Of Escherichia Coli K12

Intracellular proteases are ubiquitous in nature. This extensive distribution necessarily implicates their participation in a wide variety of cellular events. Escherichia coli, contains a variety of proteases and peptidases. For the most part, the known endoproteases of E. coli have been characterized from cells grown to stationary phase on enriched media. Surprisingly, no studies have addressed the question of what proteases are present in exponentially growing E. coli, despite the fact that significant protein turnover occurs.;Previous studies from this laboratory revealed the presence of a unique Ca{dollar}\sp{lcub}2+{rcub}{dollar}-activated proteolytic activity in E. coli. This activity was maximal in mid-log grown cells but absent at stationary phase and was restricted to the periplasmic space of E. coli. The periplasmic fraction was initially analyzed by DEAE-cellulose chromatography. The observation that the periplasm contained multiple proteolytic activities is the basis for the studies reported here.;These samples were purified by conventional column chromatography techniques. This approach has resulted in the isolation of four apparently distinct proteases designated Protease peri 3, peri 4, An, and X. Proteases peri 3 and peri 4 are monomeric metalloendoproteases of 94 kDa and 102 kDa respectively. These enzymes degrade both casein and insulin B chain. Protease peri 3 is stabilized by Ca{dollar}\sp{lcub}2+{rcub}{dollar} or Mn{dollar}\sp{lcub}2+{rcub}{dollar}, cleaves insulin B chain at four positions and is immunologically distinct from other periplasmic proteases, including Protease III. Protease peri 4 cleaves insulin B chain at a single location.;Proteases An and X mainly degrade casein and were further examined due to their size ({dollar}\u3e{dollar}3000 kDa) on gel filtration. Protease An is a metalloendoprotease activated by ATP. Protease X, however, is a serine protease which is unaffected by ATP. These two proteases exhibit a number of properties similar to the proteasomes observed in eukaryotic systems.;Whether each of these proteases represent a unique gene product remains to be established. It is the hope that this study will promote future work that may then primarily focus on the physiological role of these proteases in the periplasm

Leap-frogging the urban-poor to a high income economy: a case study from a developing country / Mahendhiran Nair & Santha Vaithilingam.

Urban-poverty is a major concern for policy-makers in the developing world. If measures are not taken to address urban-poverty, it will result in growing social problems, which can lead to economic and political instability. It is widely recognized that ICT is a leap-frogging technology that can close the knowledge-divide and income gap between the ‘haves’ and ‘have-nots’. In this study, we examine if ICT diffusion can improve the income level of urban-poor communities in Malaysia. Three types of ICT were considered in this study, namely mobile phones, computers and internet. The study was conducted using survey data for 434 respondents from selected urban-poor communities in the Klang Valley region in Malaysia. The empirical analysis showed that all three ICTs enhanced the income level of this marginalised community. This provides evidence that ICT diffusion strategies should be an integral part of national development plans to address urban-poverty in developing countries

Higher order feature extraction and selection for robust human gesture recognition using CSI of COTS Wi-Fi devices

Device-free human gesture recognition (HGR) using commercial o the shelf (COTS) Wi-Fi devices has gained attention with recent advances in wireless technology. HGR recognizes the human activity performed, by capturing the reflections ofWi-Fi signals from moving humans and storing them as raw channel state information (CSI) traces. Existing work on HGR applies noise reduction and transformation to pre-process the raw CSI traces. However, these methods fail to capture the non-Gaussian information in the raw CSI data due to its limitation to deal with linear signal representation alone. The proposed higher order statistics-based recognition (HOS-Re) model extracts higher order statistical (HOS) features from raw CSI traces and selects a robust feature subset for the recognition task. HOS-Re addresses the limitations in the existing methods, by extracting third order cumulant features that maximizes the recognition accuracy. Subsequently, feature selection methods derived from information theory construct a robust and highly informative feature subset, fed as input to the multilevel support vector machine (SVM) classifier in order to measure the performance. The proposed methodology is validated using a public database SignFi, consisting of 276 gestures with 8280 gesture instances, out of which 5520 are from the laboratory and 2760 from the home environment using a 10 5 cross-validation. HOS-Re achieved an average recognition accuracy of 97.84%, 98.26% and 96.34% for the lab, home and lab + home environment respectively. The average recognition accuracy for 150 sign gestures with 7500 instances, collected from five di erent users was 96.23% in the laboratory environment.Taylor's University through its TAYLOR'S PhD SCHOLARSHIP Programmeinfo:eu-repo/semantics/publishedVersio

A creative learning ecosystem, quality of education and innovative capacity: a perspective from higher education

Globally, governments recognize the importance of creativity and innovation for sustainable socioeconomic development, and many invest resources to develop learning environments that foster these capacities. This paper provides a systematic framework based on Nair’s Innovation Helix model for studying the factors of a country’s creative learning ecosystem (CLE), the quality of its education system (QES), and its innovative capacity (IC). The CLE factors are infrastructure/infostructure (physical and digital infrastructure), intellectual capital, interaction, integrity systems, incentives, and institutions. Using a composite CLE index for 113 countries, the findings indicate a strong correlation between a country’s CLE, QES and IC. Through brief case studies of countries that measure highly in CLE, QES and IC, this study points out their higher education strategies and their best practices for other countries to emulate, in order to facilitate creativity and innovation through higher education

Calculating Radius of Robust Feasibility of Uncertain Linear Conic Programs via Semi-definite Programs

The radius of robust feasibility provides a numerical value for the largest possible uncertainty set that guarantees robust feasibility of an uncertain linear conic program. This determines when the robust feasible set is non-empty. Otherwise, the robust counterpart of an uncertain program is not well defined as a robust optimization problem. In this paper, we address a key fundamental question of robust optimization: How to compute the radius of robust feasibility of uncertain linear conic programs, including linear programs? We first provide computable lower and upper bounds for the radius of robust feasibility for general uncertain linear conic programs under the commonly used ball uncertainty set. We then provide important classes of linear conic programs where the bounds are calculated by finding the optimal values of related semi-definite linear programs, among them uncertain semi-definite programs, uncertain second-order cone programs and uncertain support vector machine problems. In the case of an uncertain linear program, the exact formula allows us to calculate the radius by finding the optimal value of an associated second-order cone program.This research was partially supported by the Australian Research Council, Discovery Project DP120100467 and the Ministry of Science, Innovation and Universities of Spain and the European Regional Development Fund (ERDF) of the European Commission, Grant PGC2018-097960-B-C22

Electron Beam Irradiation Effects on Dielectric Parameters of SiR–EPDM Blends

The survival of an electrical system is mostly governed by the endurance limit of the dielectric material employed in it. The five different compositions of SiR–EPDM blends were prepared. Electron beam radiation has been widely used in the cable manufacturing industries in order to increase the life of the cable. Hence, the five blends were irradiated to 5, 15 and 25 Mrad dose levels by electron beam accelerator. The dielectric parameters such as breakdown voltage (BDV), dielectric strength (DS), dielectric constant (DC), and dissipation factor (DF) were measured as per ASTM/IEC standards. This chapter evaluates the effect of electron beam irradiation on dielectric parameters of SiR–EPDM blends