Pearcesellers6343

Blockchain has been applied to quality control in manufacturing, but the problems of false defect detections and lack of data transparency remain. This paper proposes a framework, Blockchain Quality Controller (BCQC), to overcome these limitations while fortifying data security. BCQC utilizes blockchain and Internet-of-Things to form a peer-to-peer supervision network. This paper also proposes a consensus algorithm, Quality Defect Tolerance (QDT), to adopt blockchain for during-production quality control. Simulation results show that BCQC enhances data security and improves defect detections. Although the time taken for the quality control process increases with the number of nodes in blockchain, the application of QDT allows multiple inspections on a workpiece to be consolidated at a faster pace, effectively speeding up the entire quality control process. The BCQC and QDT can improve the quality of parts produced for mass personalization manufacturing.Iron (Fe) toxicity is a major abiotic stress which severely reduces rice yield in many countries of the world. Genetic variation for this stress tolerance exists in rice germplasms. Mapping of gene(s)/QTL controlling the stress tolerance and transfer of the traits into high yielding rice varieties are essential for improvement against the stress. A panel population of 119 genotypes from 352 germplasm lines was constituted for detecting the candidate gene(s)/QTL through association mapping. STRUCTURE, GenAlEx and Darwin softwares were used to classify the population. The marker-trait association was detected by considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) analyses. Wide genetic variation was observed among the genotypes present in the panel population for the stress tolerance. Linkage disequilibrium was detected in the population for iron toxicity tolerance. The population was categorized into three genetic structure groups. Marker-trait association study considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) showed significant association of leaf browning index (LBI) with markers RM471, RM3, RM590 and RM243. Three novel QTL controlling Fe-toxicity tolerance were detected and designated as qFeTox4.3, qFeTox6.1 and qFeTox10.1. A QTL reported earlier in the marker interval of C955-C885 on chromosome 1 is validated using this panel population. The present study showed that QTL controlling Fe-toxicity tolerance to be co-localized with the QTL for Fe-biofortification of rice grain indicating involvement of common pathway for Fe toxicity tolerance and Fe content in rice grain. Fe-toxicity tolerance QTL qFeTox6.1 was co-localized with grain Fe-biofortification QTLs qFe6.1 and qFe6.2 on chromosome 6, whereas qFeTox10.1 was co-localized with qFe10.1 on chromosome 10. The Fe-toxicity tolerance QTL detected from this mapping study will be useful in marker-assisted breeding programs.

Tyrosine kinase inhibitors (TKIs) therapy targets at epidermal growth factor receptor (EGFR) gene mutations in non-small-cell lung cancer (NSCLC). We aimed to compare the EGFR mutation-guided target therapy versus empirical chemotherapy for first-line treatment of advanced NSCLC in the public healthcare setting of Hong Kong.

A Markov model was designed to simulate outcomes of a hypothetical cohort of advanced (stage IIIB/IV) NSCLC adult patients with un-tested EGFR-sensitizing mutation status. Four treatment strategies were evaluated Empirical first-line chemotherapy with cisplatin-pemetrexed (empirical chemotherapy group), and EGFR mutation-guided use of a TKI (afatinib, erlotinib, and gefitinib). Model outcome measures were direct medical cost, progression-free survival, overall survival, and quality-adjusted life-years (QALYs). Incremental cost per QALY gained (ICER) was estimated. selleck Sensitivity analyses were performed to examine robustness of model results.

Empirical chemotherapy and EGFR mutation-guided gefitinib gained lower QALYs at higher costs than the erlotinib group. Comparing with EGFR mutation-guided erlotinib, the afatinib strategy gained additional QALYs with ICER (540,633 USD/QALY). In 10,000 Monte Carlo simulations for probabilistic sensitivity analysis, EGFR mutation-guided afatinib, erlotinib, gefitinib and empirical chemotherapy were preferred strategy in 0%, 98%, 0% and 2% of time at willingness-to-pay (WTP) 47,812 USD/QALY (1x gross domestic product (GDP) per capita), and in 30%, 68%, 2% and 0% of time at WTP 143,436 USD/QALY (3x GDP per capita), respectively.

EGFR mutation-guided erlotinib appears to be the cost-effective strategy from the perspective of Hong Kong public healthcare provider over a broad range of WTP.

EGFR mutation-guided erlotinib appears to be the cost-effective strategy from the perspective of Hong Kong public healthcare provider over a broad range of WTP.

Identified in December 2019 in the city of Wuhan, China, the outbreak of COVID-19 spread throughout the world and its impacts affect different populations differently, where countries with high levels of social and economic inequality such as Brazil gain prominence, for understanding of the vulnerability factors associated with the disease. Given this scenario, in the absence of a vaccine or safe and effective antiviral treatment for COVID-19, nonpharmacological measures are essential for prevention and control of the disease. However, many of these measures are not feasible for millions of individuals who live in territories with increased social vulnerability. The study aims to analyze the spatial distribution of COVID-19 incidence in Brazil's municipalities (counties) and investigate its association with sociodemographic determinants to better understand the social context and the epidemic's spread in the country.

This is an analytical ecological study using data from various sources. The study period risk of the illness.

Social inequality increased the risk of COVID-19 in the municipalities. Better social development of the municipalities was associated with lower risk of the disease. Greater access to health services improved the diagnosis and notification of the disease and was associated with more cases in the municipalities. Despite universal susceptibility to COVID-19, populations with increased social vulnerability were more exposed to risk of the illness.