Application of Machine Learning Techniques to Parameter Selection for Flight Risk Identification

In recent years, the use of data mining and machine learning techniques for safety analysis, incident and accident investigation, and fault detection has gained traction among the aviation community. Flight data collected from recording devices contains a large number of heterogeneous parameters, sometimes reaching up to thousands on modern commercial aircraft. More data is being collected continuously which adds to the ever-increasing pool of data available for safety analysis. However, among the data collected, not all parameters are important from a risk and safety analysis perspective. Similarly, in order to be useful for modern analysis techniques such as machine learning, using thousands of parameters collected at a high frequency might not be computationally tractable. As such, an intelligent and repeatable methodology to select a reduced set of significant parameters is required to allow safety analysts to focus on the right parameters for risk identification. In this paper, a step-by-step methodology is proposed to down-select a reduced set of parameters that can be used for safety analysis. First, correlation analysis is conducted to remove highly correlated, duplicate, or redundant parameters from the data set. Second, a pre-processing step removes metadata and empty parameters. This step also considers requirements imposed by regulatory bodies such as the Federal Aviation Administration and subject matter experts to further trim the list of parameters. Third, a clustering algorithm is used to group similar flights and identify abnormal operations and anomalies. A retrospective analysis is conducted on the clusters to identify their characteristics and impact on flight safety. Finally, analysis of variance techniques are used to identify which parameters were significant in the formation of the clusters. Visualization dashboards were created to analyze the cluster characteristics and parameter significance. This methodology is employed on data from the approach phase of a representative single-aisle aircraft to demonstrate its application and robustness across heterogeneous data sets. It is envisioned that this methodology can be further extended to other phases of flight and aircraft

A novel structure of secondary alcohol derived from (+)-&#916;<SUP>3</SUP>-carene with pseudo three-fold symmetry

The crystal structure of C12OH20 (lR-6R-4R-2 R-3,7,7-trimethyl-4-(2-hydroxyethyl) bicyclo [4.1.0] hept-2-ene) has been determined by X-ray diffraction. The compound crystallizes in space group P212121 witha = 5.893(1),b = 22.572(2), c = 26.164(3) &#197;,V = 3480.3 &#197;3, Z= 12. The structure was solved by modified direct methods and refined to anR value of 0.081 for 607 unique reflections. Each asymmetric unit has three molecules which are held together through intermolecular hydrogen bonds resulting in a novel spiral-type arrangement of molecules. The six-membered ring has a half-chair conformation

An RxLR effector from phytophthora infestans prevents re-localisation of two plant NAC transcription factors from the endoplasmic reticulum to the nucleus

The plant immune system is activated following the perception of exposed, essential and invariant microbial molecules that are recognised as non-self. A major component of plant immunity is the transcriptional induction of genes involved in a wide array of defence responses. In turn, adapted pathogens deliver effector proteins that act either inside or outside plant cells to manipulate host processes, often through their direct action on plant protein targets. To date, few effectors have been shown to directly manipulate transcriptional regulators of plant defence. Moreover, little is known generally about the modes of action of effectors from filamentous (fungal and oomycete) plant pathogens. We describe an effector, called Pi03192, from the late blight pathogen Phytophthora infestans, which interacts with a pair of host transcription factors at the endoplasmic reticulum (ER) inside plant cells. We show that these transcription factors are released from the ER to enter the nucleus, following pathogen perception, and are important in restricting disease. Pi03192 prevents the plant transcription factors from accumulating in the host nucleus, revealing a novel means of enhancing host susceptibility

The Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX): overview and preliminary results

While the demand for enhancing rainfall through cloud seeding is strong and persistent in the country, considerable uncertainty exists on the success of such an endeavour at a given location. To understand the pathways of aerosol-cloud interaction through which this might be achieved, a national experiment named Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX) in two phases, was carried out. The rationale of CAIPEEX, the strategy for conducting the experiment, data quality and potential for path-breaking science are described in this article. Pending completion of quality control and calibration of the CAIPEEX phase-II data, here we present some initial results of CAIPEEX phase-I aimed at documenting the prevailing microphysical characteristics of aerosols and clouds and associated environmental conditions over different regions of the country and under different monsoon conditions with the help of an instrumented research aircraft. First-time simultaneous observations of aerosol, cloud condensation nuclei (CCN) and cloud droplet number concentration (CDNC) over the Ganges Valley during monsoon season show very high concentrations (&gt; 1000 cm-3) of CCN at elevated layers. Observations of elevated layers with high aerosol concentration over the Gangetic valley extending up to 6 km and relatively less aerosol concentration in the boundary layer are also documented. We also present evidence of strong cloud- aerosol interaction in the moist environments with an increase in the cloud droplet effective radius. Our observations also show that pollution increases CDNC and the warm rain depth, and delays its initiation. The critical effective radius for warm rain initiation is found to be between 10 and 12 µm in the polluted clouds and it is between 12 and 14 µm in cleaner monsoon clouds

Structure-Based Screen Identifies a Potent Small Molecule Inhibitor of Stat5a/b with Therapeutic Potential for Prostate Cancer and Chronic Myeloid Leukemia.

Bypassing tyrosine kinases responsible for Stat5a/b phosphorylation would be advantageous for therapy development for Stat5a/b-regulated cancers. Here, we sought to identify small molecule inhibitors of Stat5a/b for lead optimization and therapy development for prostate cancer and Bcr-Abl-driven leukemias. In silico screening of chemical structure databases combined with medicinal chemistry was used for identification of a panel of small molecule inhibitors to block SH2 domain-mediated docking of Stat5a/b to the receptor-kinase complex and subsequent phosphorylation and dimerization. We tested the efficacy of the lead compound IST5-002 in experimental models and patient samples of two known Stat5a/b-driven cancers, prostate cancer and chronic myeloid leukemia (CML). The lead compound inhibitor of Stat5-002 (IST5-002) prevented both Jak2 and Bcr-Abl-mediated phosphorylation and dimerization of Stat5a/b, and selectively inhibited transcriptional activity of Stat5a (IC50 = 1.5μmol/L) and Stat5b (IC50 = 3.5 μmol/L). IST5-002 suppressed nuclear translocation of Stat5a/b, binding to DNA and Stat5a/b target gene expression. IST5-002 induced extensive apoptosis of prostate cancer cells, impaired growth of prostate cancer xenograft tumors, and induced cell death in patient-derived prostate cancers when tested ex vivo in explant organ cultures. Importantly, IST5-002 induced robust apoptotic death not only of imatinib-sensitive but also of imatinib-resistant CML cell lines and primary CML cells from patients. IST5-002 provides a lead structure for further chemical modifications for clinical development for Stat5a/b-driven solid tumors and hematologic malignancies

Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis

Bambara groundnut (Vigna subterranea (L.) Verdc.) is an African legume and is a promising underutilized crop with good seed nutritional values. Low temperature stress in a number of African countries at night, such as Botswana, can effect the growth and development of bambara groundnut, leading to losses in potential crop yield. Therefore, in this study we developed a computational pipeline to identify and analyze the genes and gene modules associated with low temperature stress responses in bambara groundnut using the cross-species microarray technique (as bambara groundnut has no microarray chip) coupled with network-based analysis. Analyses of the bambara groundnut transcriptome using cross-species gene expression data resulted in the identification of 375 and 659 differentially expressed genes (p<0.01) under the sub-optimal (23°C) and very sub-optimal (18°C) temperatures, respectively, of which 110 genes are commonly shared between the two stress conditions. The construction of a Highest Reciprocal Rank-based gene co-expression network, followed by its partition using a Heuristic Cluster Chiseling Algorithm resulted in 6 and 7 gene modules in sub-optimal and very sub-optimal temperature stresses being identified, respectively. Modules of sub-optimal temperature stress are principally enriched with carbohydrate and lipid metabolic processes, while most of the modules of very sub-optimal temperature stress are significantly enriched with responses to stimuli and various metabolic processes. Several transcription factors (from MYB, NAC, WRKY, WHIRLY & GATA classes) that may regulate the downstream genes involved in response to stimulus in order for the plant to withstand very sub-optimal temperature stress were highlighted. The identified gene modules could be useful in breeding for low-temperature stress tolerant bambara groundnut varieties

Non-invasive or minimally invasive autopsy compared to conventional autopsy of suspected natural deaths in adults: a systematic review

Objectives: Autopsies are used for healthcare quality control and improving medical knowledge. Because autopsy rates are declining worldwide, various non-invasive or minimally invasive autopsy methods are now being developed. To investigate whether these might replace the invasive autopsies conventionally performed in naturally deceased adults, we systematically reviewed original prospective validation studies. Materials and methods: We searched six databases. Two reviewers independently selected articles and extracted data. Methods and patient groups were too heterogeneous for meaningful meta-analysis of outcomes. Results: Sixteen of 1538 articles met our inclusion criteria. Eight studies used a blinded comparison; ten included less than 30 appropriate cases. Thirteen studies used radiological imaging (seven dealt solely with non-invasive procedures), two thoracoscopy and laparoscopy, and one sampling without imaging. Combining CT and MR was the best non-invasive method (agreement for cause of death: 70 %, 95%CI: 62.6; 76.4), but minimally invasive methods surpassed non-invasive methods. The highest sensitivity for cause of death (90.9 %, 95%CI: 74.5; 97.6, suspected duplicates excluded) was achieved in recent studies combining CT, CT-angiography and biopsies. Conclusion: Minimally invasive autopsies including biopsies performed best. To establish a feasible alternative to conventional autopsy and to increase consent to post-mortem investigations, further research in larger study groups is needed. Key points: • Health care quality control benefits from clinical feedback provided by (alternative) autopsies. • So far, sixteen studies investigated alternative autopsy methods for naturally deceased adults. • Thirteen studies used radiological imaging modalities, eight tissue biopsies, and three CT-angiography. • Combined CT, CT-angiography and biopsies were most sensitive diagnosing cause of death