Online control of AC/AC converter based SHEPWM technique

Conventional online control of AC/AC converter controlled by the selective harmonic elimination pulse width modulation technique (SHEPWM) is based on storing the offline calculated switching angle values in a form of lookup table. Then the required switching pattern of certain modulation index (M) is searched through the lookup table. This methodology suffers from limited system flexibility. This paper introduces a novel implementation scheme based on real-time calculation of the required SHEPWM switching pattern with linear control of the fundamental voltage component magnitude based on curve fitting technique for the exact switching angle trajectories. The accuracy of the derived polynomials is evaluated by calculating converter performance parameters using the approximated switching angles solutions obtained from the introduced method and the exact switching angles solutions. Detail of the introduced methodology is presented. Simulation and experimental results have been carried out to confirm the validity of the introduced algorithm

Antisense DNA parameters derived from next-nearest-neighbor analysis of experimental data

<p>Abstract</p> <p>Background</p> <p>The enumeration of tetrameric and other sequence motifs that are positively or negatively correlated with <it>in vivo </it>antisense DNA effects has been a useful addition to the arsenal of information needed to predict effective targets for antisense DNA control of gene expression. Such retrospective information derived from <it>in vivo </it>cellular experiments characterizes aspects of the sequence dependence of antisense inhibition that are not predicted by nearest-neighbor (NN) thermodynamic parameters derived from <it>in vitro </it>experiments. However, quantitation of the antisense contributions of motifs is problematic, since individual motifs are not isolated from the effects of neighboring nucleotides, and motifs may be overlapping. These problems are circumvented by a next-nearest-neighbor (NNN) analysis of antisense DNA effects in which the overlapping nature of nearest-neighbors is taken into account.</p> <p>Results</p> <p>Next-nearest-neighbor triplet combinations of nucleotides are the simplest that include overlapping sequence effects and therefore can encompass interactions beyond those of nearest neighbors. We used singular value decomposition (SVD) to fit experimental data from our laboratory in which phosphorothioate-modified antisense DNAs (S-DNAs) 20 nucleotides long were used to inhibit cellular protein expression in 112 experiments involving four gene targets and two cell lines. Data were fitted using a NNN model, neglecting end effects, to derive NNN inhibition parameters that could be combined to give parameters for a set of 49 sequences that represents the inhibitory effects of all possible overlapping triplet interactions in the cellular targets of these antisense S-DNAs. We also show that parameters to describe subsets of the data, such as the mRNAs being targeted and the cell lines used, can be included in such a derivation. While NNN triplet parameters provided an adequate model to fit our data, NN doublet parameters did not.</p> <p>Conclusions</p> <p>The methodology presented illustrates how NNN antisense inhibitory information can be derived from <it>in vivo </it>cellular experiments. Subsequent calculations of the antisense inhibitory parameters for any mRNA target sequence automatically take into account the effects of all possible overlapping combinations of nearest-neighbors in the sequence. This procedure is more robust than the tallying of tetrameric motifs that have positive or negative antisense effects. The specific parameters derived in this work are limited in their applicability by the relatively small database of experiments that was used in their derivation.</p

Chronic hepatitis c genotype-4 infection: role of insulin resistance in hepatocellular carcinoma

<p>Abstract</p> <p>Background</p> <p>Hepatitis C virus (HCV) is a major cause of chronic hepatitis and hepatocellular carcinoma (HCC) and different HCV genotypes show characteristic variations in their pathological properties. Insulin resistance (IR) occurs early in HCV infection and may synergize with viral hepatitis in HCC development. Egypt has the highest reported rates of HCV infection (predominantly genotype 4) in the world; this study investigated effects of HCV genotype-4 (HCV-4) on prevalence of insulin resistance in chronic hepatitis C (CHC) and HCC in Egyptian patients.</p> <p>Methods</p> <p>Fifty CHC patients, 50 HCC patients and 20 normal subjects were studied. IR was estimated using HOMA-IR index and HCV-4 load determined using real-time polymerase chain reaction. Hepatitis B virus was excluded by enzyme-linked immunosorbent assay. Standard laboratory and histopathological investigations were undertaken to characterize liver function and for grading and staging of CHC; HCC staging was undertaken using intraoperative samples.</p> <p>Results</p> <p>HCC patients showed higher IR frequency but without significant difference from CHC (52% vs 40%, p = 0.23). Multivariate logistic regression analysis showed HOMA-IR index and International Normalization Ratio independently associated with fibrosis in CHC; in HCC, HbA1c, cholesterol and bilirubin were independently associated with fibrosis. Fasting insulin and cholesterol levels were independently associated with obesity in both CHC and HCC groups. Moderate and high viral load was associated with high HOMA-IR in CHC and HCC (p < 0.001).</p> <p>Conclusions</p> <p>IR is induced by HCV-4 irrespective of severity of liver disease. IR starts early in infection and facilitates progression of hepatic fibrosis and HCC development.</p

Sensor networks and personal health data management: software engineering challenges

The advances of 5G, sensors, and information technologies enabled proliferation of smart pervasive sensor networks. 5G mobile networks provide low-power, high-availability, high density, and high-throughput data capturing by sensor networks and continuous streaming of multiple measured variables. Rapid progress in sensors that can measure vital signs, advances in the management of medical knowledge, and improvement of algorithms for decision support, are fueling a technological disruption to health monitoring. The increase in size and complexity of wireless sensor networks and expansion into multiple areas of health monitoring creates challenges for system design and software engineering practices. In this paper, we highlight some of the key software engineering and data-processing issues, along with addressing emerging ethical issues of data management. The challenges associated with ensuring high dependability of sensor network systems can be addressed by metamorphic testing. The proposed conceptual solution combines data streaming, filtering, cross-calibration, use of medical knowledge for system operation and data interpretation, and IoT-based calibration using certified linked diagnostic devices. Integration of blockchain technologies and artificial intelligence offers a solution to the increasing needs for higher accuracy of measurements of vital signs, high-quality decision-making, and dependability, including key medical and ethical requirements of safety and security of the data

Clinical, neuroimaging, and molecular spectrum of TECPR2‐associated hereditary sensory and autonomic neuropathy with intellectual disability

Bi‐allelic TECPR2 variants have been associated with a complex syndrome with features of both a neurodevelopmental and neurodegenerative disorder. Here, we provide a comprehensive clinical description and variant interpretation framework for this genetic locus. Through international collaboration, we identified 17 individuals from 15 families with bi‐allelic TECPR2‐variants. We systemically reviewed clinical and molecular data from this cohort and 11 cases previously reported. Phenotypes were standardized using Human Phenotype Ontology terms. A cross‐sectional analysis revealed global developmental delay/intellectual disability, muscular hypotonia, ataxia, hyporeflexia, respiratory infections, and central/nocturnal hypopnea as core manifestations. A review of brain magnetic resonance imaging scans demonstrated a thin corpus callosum in 52%. We evaluated 17 distinct variants. Missense variants in TECPR2 are predominantly located in the N‐ and C‐terminal regions containing β‐propeller repeats. Despite constituting nearly half of disease‐associated TECPR2 variants, classifying missense variants as (likely) pathogenic according to ACMG criteria remains challenging. We estimate a pathogenic variant carrier frequency of 1/1221 in the general and 1/155 in the Jewish Ashkenazi populations. Based on clinical, neuroimaging, and genetic data, we provide recommendations for variant reporting, clinical assessment, and surveillance/treatment of individuals with TECPR2‐associated disorder. This sets the stage for future prospective natural history studies

Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks