Review of True Experimental Research Studies in Applied Linguistics

The purpose of this paper is to provide an overview of true experimental research studies in the field of Applied Linguistics and to highlight the methodology and statistical application employed by the researchers. A total of ten true experimental studies are reviewed. The perspectives emerged from these studies have been identified and discussed

An Empirical Evaluation of Data Integrity Algorithm Performance in Non-Relational Document Databases

Non-relational document databases are a type of NoSQL databases, are gaining popularity owing to their flexibility, scalability, and performance. Document databases provide some distinct security issues. One of the most difficult security challenges is that they are frequently built to be extremely accessible. This can make them more vulnerable to assault if suitable security measures are not taken. Users of database can access data with weak authentication or authorization. Another issue is that they store data in a semi-structured or unstructured format. This makes it difficult to create and execute security safeguards. It may be difficult to detect and secure sensitive data that is kept. Document databases are certain data integrity problems. In this research work, we have developed Big Document DBCrypto’s architecture under which Middle ware provides users to use symmetric cryptography with any hashing algorithm or asymmetric cryptography with digital signatures to ensure data integrity

Phytoextraction of Lead Using a Hedge Plant [Alternanthera bettzickiana (Regel) G. Nicholson]: Physiological and Biochemical Alterations through Bioresource Management

Phytoremediation is a cost-effective and environmentally friendly approach that can be used for the remediation of metals in polluted soil. This study used a hedge plant–calico (Alternanthera bettzickiana (Regel) G. Nicholson) to determine the role of citric acid in lead (Pb) phytoremediation by exposing it to different concentrations of Pb (0, 200, 500, and 1000 mg kg−1) as well as in a combination with citric acid concentration (0, 250, 500 µM). The analysis of variance was applied on results for significant effects of the independent variables on the dependent variables using SPSS (ver10). According to the results, maximum Pb concentration was measured in the upper parts of the plant. An increase in dry weight biomass, plant growth parameters, and photosynthetic contents was observed with the increase of Pb application (200 mg kg−1) in soil while a reduced growth was experienced at higher Pb concentration (1000 mg kg−1). The antioxidant enzymatic activities like superoxide dismutase (SOD) and peroxidase (POD) were enhanced under lower Pb concentration (200, 500 mg kg−1), whereas the reduction occurred at greater metal concentration Pb (1000 mg kg−1). There was a usual reduction in electrolyte leakage (EL) at lower Pb concentration (200, 500 mg kg−1), whereas EL increased at maximum Pb concentration (1000 mg kg−1). We concluded that this hedge plant, A. Bettzickiana, has the greater ability to remediate polluted soils aided with citric acid application

Analytical performance of Envisia: a genomic classifier for usual interstitial pneumonia

Abstract Background Clinical guidelines specify that diagnosis of interstitial pulmonary fibrosis (IPF) requires identification of usual interstitial pneumonia (UIP) pattern. While UIP can be identified by high resolution CT of the chest, the results are often inconclusive, making surgical lung biopsy necessary to reach a definitive diagnosis (Raghu et al., Am J Respir Crit Care Med 183(6):788–824, 2011). The Envisia genomic classifier differentiates UIP from non-UIP pathology in transbronchial biopsies (TBB), potentially allowing patients to avoid an invasive procedure (Brown et al., Am J Respir Crit Care Med 195:A6792, 2017). To ensure patient safety and efficacy, a laboratory developed test (LDT) must meet strict regulatory requirements for accuracy, reproducibility and robustness. The analytical characteristics of the Envisia test are assessed and reported here. Methods The Envisia test utilizes total RNA extracted from TBB samples to perform Next Generation RNA Sequencing. The gene count data from 190 genes are then input to the Envisia genomic classifier, a machine learning algorithm, to output either a UIP or non-UIP classification result. We characterized the stability of RNA in TBBs during collection and shipment, and evaluated input RNA mass and proportions on the limit of detection of UIP. We evaluated potentially interfering substances such as blood and genomic DNA. Intra-run, inter-run, and inter-laboratory reproducibility of test results were also characterized. Results RNA content within TBBs preserved in RNAprotect is stable for up to 14 days with no detectable change in RNA quality. The Envisia test is tolerant to variation in RNA input (5 to 30 ng), with no impact on classifier results. The Envisia test can tolerate dilution of non-UIP and UIP classification signals at the RNA level by up to 60% and 20%, respectively. Analytical specificity studies utilizing UIP and non-UIP samples mixed with genomic DNA (up to 30% relative input) demonstrated no impact to classifier results. The Envisia test tolerates up to 22% of blood contamination, well beyond the level observed in TBBs. The test is reproducible from RNA extraction through to Envisia test result (standard deviation of 0.20 for Envisia classification scores on > 7-unit scale). Conclusions The Envisia test demonstrates the robust analytical performance required of an LDT. Envisia can be used to inform the diagnoses of patients with suspected IPF

329: Assessing national critical care capacity: A snapshot of facilities across Pakistan

Introduction: As the COVID-19 pandemic threatens to strain health care systems worldwide, the presence of gaps in the global critical care capacity has become glaringly obvious, particularly in less developed countries like Pakistan. To identify existing gaps, an assessment of the critical care units across Pakistan was carried out.Methods: A novel checklist for assessing critical care units was developed based on the Partners in Health 4S Framework. Our checklist evaluated the following key components: Space/Infrastructure, Staffing, Stuff/Equipment, and Systems/Protocols. A series of surveys was conducted using telephonic and on-site interviews at hospitals identified by the Ministry of Health in Pakistan.Results: Critical care facilities at 53 hospitals were surveyed. The majority were from the public sector (62%) and located in metropolitan cities (62%). In terms of infrastructure, the majority of units were adequate, with gaps primarily being identified for negative-pressure rooms (21%), donning-doffing areas (58%) and isolation rooms (64%). In terms of staffing, the majority of hospitals had trainee doctors (94%) and nursing staff (100%) available, with gaps being identified in terms of presence of qualified intensivists (47%) and ancillary staff (ethicists – 17%, dietitians – 45%). Furthermore, an adequate nurse-to-patient ratio of 1:2 or 1:3 was only present in 53% of the hospitals. Equipment was present in the majority of facilities including ventilators (96%, n=9.7±1.1) and BIPAP machines (85%, n=4.5±0.6), with a relative lack of high-flow nasal cannulas (64%, n=3.2±0.9). More than 80% of hospitals had protocols in place for COVID-19 management and staffing, but fewer had them for patient surge (60%), clinician credentialing (58%) and risk mitigation (49%). On chi-square analysis, statistically significant differences (p\u3c0.05) were noted between public and private sectors as well as metropolitan and rural hospitals in terms of availability of negative pressure rooms, ancillary staff like dietitians, and optimal nurse-to-patient ratio.Conclusions: The results from this study will be pivotal to guide policy makers in devising strategies for improving the quality of critical care units across Pakistan during the COVID-19 pandemic and beyond

329: Assessing National Critical Care Capacity: A Snapshot of Facilities Across Pakistan

Introduction: As the COVID-19 pandemic threatens to strain health care systems worldwide, the presence of gaps in the global critical care capacity has become glaringly obvious, particularly in less developed countries like Pakistan. To identify existing gaps, an assessment of the critical care units across Pakistan was carried out.Methods: A novel checklist for assessing critical care units was developed based on the Partners in Health 4S Framework. Our checklist evaluated the following key components: Space/Infrastructure, Staffing, Stuff/Equipment, and Systems/Protocols. A series of surveys was conducted using telephonic and on-site interviews at hospitals identified by the Ministry of Health in Pakistan.Results: Critical care facilities at 53 hospitals were surveyed. The majority were from the public sector (62%) and located in metropolitan cities (62%). In terms of infrastructure, the majority of units were adequate, with gaps primarily being identified for negative-pressure rooms (21%), donning-doffing areas (58%) and isolation rooms (64%). In terms of staffing, the majority of hospitals had trainee doctors (94%) and nursing staff (100%) available, with gaps being identified in terms of presence of qualified intensivists (47%) and ancillary staff (ethicists – 17%, dietitians – 45%). Furthermore, an adequate nurse-to-patient ratio of 1:2 or 1:3 was only present in 53% of the hospitals. Equipment was present in the majority of facilities including ventilators (96%, n=9.7±1.1) and BIPAP machines (85%, n=4.5±0.6), with a relative lack of high-flow nasal cannulas (64%, n=3.2±0.9). More than 80% of hospitals had protocols in place for COVID-19 management and staffing, but fewer had them for patient surge (60%), clinician credentialing (58%) and risk mitigation (49%). On chi-square analysis, statistically significant differences (p\u3c0.05) were noted between public and private sectors as well as metropolitan and rural hospitals in terms of availability of negative pressure rooms, ancillary staff like dietitians, and optimal nurse-to-patient ratio.Conclusions: The results from this study will be pivotal to guide policy makers in devising strategies for improving the quality of critical care units across Pakistan during the COVID-19 pandemic and beyond

Additional file 1 of Analytical performance of Envisia: a genomic classifier for usual interstitial pneumonia

RNA-seq raw counts of samples used in Envisia analytical verification studies. This file includes the raw expression counts of 190 classifier genes across all samples (n=292) used in the analytical verification studies described in this manuscript; each row represents a gene and each column represents a sample. (CSV 199 kb