Incorporating affordability,efficiency, and quality in the ICT development index: Implications for index building and ICT policymaking

Abstract

International Telecommunication Union’s ICT Development Index and related measures of a country’s ICT development maturity suffer from several limitations, including subjective estimation of the weights of individual indicators and sub-indices, use of inappropriate quantitative models, specification bias arising from the exclusion of potential predictors from the estimation models, and a failure to capture the disparities among different groups of countries. To overcome these problems and provide a more reliable measure of ICT development, this study develops the Modified ICT Maturity Level Index using the 2015 data of 166 countries. This index adds affordability, efficiency, and quality to the existing sub-indices of access, use, and skills. Sub-index and indicator weights are determined in an outcome-orientated way using Partial Least Squares Structural Equation Modeling. We find that affordability, quality, and efficiency significantly explain the variation in the level of maturity of ICT development in addition to the previously used dimensions of International Telecommunication Union’s ICT Development Index and modified ICT Development Index (mIDI) developed by Gerpott and Ahmadi, and that their explanatory power differ by a country’s level of economic development. The new index produces significantly different country rankings. This has important implications for ICT policy priorities and provides a measure of ICT development maturity less prone to the innocent or intentional distortion of such policy priorities.     

Modified particle swarm optimization for optimum design of spread footing and retaining wall

This paper deals with the economically optimized design and sensitivity of two of the most widely used systems in geotechnical engineering: spread footing and retaining wall. Several recent advanced optimization methods have been developed, but very few of these methods have been applied to geotechnical problems. The current research develops a modified particle swarm optimization (MPSO) approach to obtain the optimum design of spread footing and retaining wall. The algorithm handles the problem-specific constraints using a penalty function approach. The optimization procedure controls all geotechnical and structural design constraints while reducing the overall cost of the structures. To verify the effectiveness and robustness of the proposed algorithm, three case studies of spread footing and retaining wall are illustrated. Comparison of the results of the present method, standard PSO, and other selected methods employed in previous studies shows the reliability and accuracy of the algorithm. Moreover, the parametric performance is investigated in order to examine the effect of relevant variables on the optimum design of the footing and the retaining structure utilizing the proposed method.     

A hybrid dielectrophoretic system for trapping of microorganisms from water

Assessment of the microbial safety of water resources is among the most critical issues in global water safety. As the current detection methods have limitations such as high cost and long process time, new detection techniques have transpired among which microfluidics is the most attractive alternative. Here, we show a novel hybrid dielectrophoretic (DEP) system to separate and detect two common waterborne pathogens, Escherichia coli (E. coli), a bacterium, and Cryptosporidium parvum (C. parvum), a protozoan parasite, from water. The hybrid DEP system integrates a chemical surface coating with a microfluidic device containing inter-digitated microelectrodes to impart positive dielectrophoresis for enhanced trapping of the cells. Trimethoxy(3,3,3-trifluoropropyl) silane, (3-aminopropyl)triethoxysilane, and polydiallyl dimethyl ammonium chloride (p-DADMAC) were used as surface coatings. Static cell adhesion tests showed that among these coatings, the p-DADMAC-coated glass surface provided the most effective cell adhesion for both the pathogens. This was attributed to the positively charged p-DADMAC-coated surface interacting electrostatically with the negatively charged cells suspended in water leading to increased cell trapping efficiency. The trapping efficiency of E. coli and C. parvum increased from 29.0% and 61.3% in an uncoated DEP system to 51.9% and 82.2% in the hybrid DEP system, respectively. The hybrid system improved the cell trapping by encouraging the formation of cell pearl-chaining. The increment in trapping efficiency in the hybrid DEP system was achieved at an optimal frequency of 1 MHz and voltage of 2.5 V_pp for C. parvum and 2 V_pp for E. coli, the latter is lower than 2.5 V_pp and 7 V_pp, respectively, utilized for obtaining similar efficiency in an uncoated DEP system.     

The effectiveness of the GeoGebra Programme in the development of academic achievement and survival of the learning impact of the mathematics among secondary stage students

Education and Information Technologies - The objective of this research is to identify the effectiveness of the GeoGebra program in developing academic achievement and ensuring survival of the...     

Right ventricular function in elite male athletes meeting the structural echocardiographic task force criteria for arrhythmogenic right ventricular cardiomyopathy

Athlete pre-participation screening is focused on detecting pathological conditions like arrhythmogenic right ventricular cardiomyopathy (ARVC). The diagnosis of ARVC is established by applying the revised 2010 ARVC Task Force Criteria (TFC) that assesses RV structure and function. Some athletes may meet structural TFC without having ARVC but we do not know the consequences for RV function. This study compared RV structural and functional indices in male athletes that meet the structural TFC (MTFC) for ARVC and those that do not (NMTFC). We recruited 214 male elite athletes. All participants underwent 2D, Doppler, tissue Doppler and strain (ε) echocardiography with a focused and comprehensive assessment of the right heart. Athletes were grouped on RV structural data: MTFC n = 34; NMTFC n = 180. Functional data were compared between groups. By selection, MTFC had larger absolute and scaled RV outflow tract (RVOT) diameter compared to NMTFC (P ?0.05) but these athletes did not develop a proportional increase in the RV inflow dimensions. There was no difference in global conventional RV systolic function between both groups however, there was significantly lower global RV ε in athletes that MTFC which can be explained, in part, by the RVOT dimension.     

Determining the SARS-CoV-2 serological immunoassay test performance indices based on the test results frequency distribution

IntroductionCoronavirus disease 2019 (COVID-19) is known to induce robust antibody response in most of the affected individuals. The objective of the study was to determine if we can harvest the test sensitivity and specificity of a commercial serologic immunoassay merely based on the frequency distribution of the SARS-CoV-2 immunoglobulin (Ig) G concentrations measured in a population-based seroprevalence study.Materials and methodsThe current study was conducted on a subset of a previously published dataset from the canton of Geneva. Data were taken from two non-consecutive weeks (774 samples from May 4-9, and 658 from June 1-6, 2020). Assuming that the frequency distribution of the measured SARS-CoV-2 IgG is binormal (an educated guess), using a non-linear regression, we decomposed the distribution into its two Gaussian components. Based on the obtained regression coefficients, we calculated the prevalence of SARS-CoV-2 infection, the sensitivity and specificity, and the most appropriate cut-off value for the test. The obtained results were compared with those obtained from a validity study and a seroprevalence population-based study.ResultsThe model could predict more than 90% of the variance observed in the SARS-CoV-2 IgG distribution. The results derived from our model were in good agreement with the results obtained from the seroprevalence and validity studies. Altogether 138 of 1432 people had SARS-CoV-2 IgG ≥ 0.90, the cut-off value which maximized the Youden’s index. This translates into a true prevalence of 7.0% (95% confidence interval 5.4% to 8.6%), which is in keeping with the estimated prevalence of 7.7% derived from our model. Our model can provide the true prevalence.ConclusionsHaving an educated guess about the distribution of test results, the test performance indices can be derived with acceptable accuracy merely based on the test results frequency distribution without the need for conducting a validity study and comparing the test results against a gold-standard test.     

Cultural acceptability and personal willingness of Iranian students toward cadaveric donation

Cadaver dissection stands as a crucial component in medical curricula around the world, although computer‐based multimedia programs have been introduced in order to replace the need for cadaver donations. Due to a decrease in the number of unclaimed bodies and rather few donations, there is an insufficient number of cadavers for anatomical studies in Iran. This study was carried out to evaluate medical students' awareness and willingness regarding body donation in Kashan University of Medical Sciences, Iran. In this study, a questionnaire was designed to focus on the cultural acceptability and personal willingness to donate one's body after death. Students from the university's anatomy classes (n = 331) participated in this study. Seventy‐seven percent of the students expressed their agreement toward the idea of utilizing body donation services, though only 25.4% of participants were willing to donate their own bodies. None of the demographic factors were associated with cultural acceptability or personal willingness towards body donation. These findings indicated that besides “payment”, other factors were associated with students' willingness to become donors. All factors of awareness except “previous awareness of organization” were associated with cultural acceptability. In this study, students suggested that encouraging people to register for body donation using mass media (25.6%) and teaching students to respect cadavers in the dissection environment (24.8%) were the best solutions for addressing the lack of cadavers. These findings indicated that a lack of awareness about body donation might be the main factor responsible for unwillingness towards body donation; therefore, improving the public's awareness and addressing the willingness of students regarding body donation may help overcome the current lack of donated cadavers. Anat Sci Educ 10: 120–126. © 2016 American Association of Anatomists.     

Bi-view semi-supervised active learning for cross-lingual sentiment classification

Recently, sentiment classification has received considerable attention within the natural language processing research community. However, since most recent works regarding sentiment classification have been done in the English language, there are accordingly not enough sentiment resources in other languages. Manual construction of reliable sentiment resources is a very difficult and time-consuming task. Cross-lingual sentiment classification aims to utilize annotated sentiment resources in one language (typically English) for sentiment classification of text documents in another language. Most existing research works rely on automatic machine translation services to directly project information from one language to another. However, different term distribution between original and translated text documents and translation errors are two main problems faced in the case of using only machine translation. To overcome these problems, we propose a novel learning model based on active learning and semi-supervised co-training to incorporate unlabelled data from the target language into the learning process in a bi-view framework. This model attempts to enrich training data by adding the most confident automatically-labelled examples, as well as a few of the most informative manually-labelled examples from unlabelled data in an iterative process. Further, in this model, we consider the density of unlabelled data so as to select more representative unlabelled examples in order to avoid outlier selection in active learning. The proposed model was applied to book review datasets in three different languages. Experiments showed that our model can effectively improve the cross-lingual sentiment classification performance and reduce labelling efforts in comparison with some baseline methods.