Corrosion behaviour of Al-Si cast alloy reinforced with titanium diboride (TiB2) and scandium (Sc)

The aluminium-silicon (Al-Si) based on Metal Matrix Composites (MMCs) is widely used in lightweight constructions and transport applications requiring a combination of high strength and ductility. A grain refinement plays a crucial role in improving characteristics and properties of Al alloys. In this investigation, titanium diboride (TiB2) and scandium (Sc) inoculants were added to the Al-Si alloys for grain refinement of an alloy. In this investigation, the corrosion resistance rate of Al-Si cast alloy reinforced by TiB2 and Sc were measured by potentiostat (AUTOLAB) instrument. The aim of this research is to investigate the corrosion rate for Al-Si-TiB2-Sc composites that immersed in different concentration of acidic solutions. Besides, the immersion time of acidic solutions also was investigated. All the samples were prepared accordingly for ASTM standard by the composition of 6.0 wt% TiB2 and 0.6wt% Sc. All the samples undergo cold mounting technique for easy handling on corrosion tests. Then the samples were immersed in two different concentrations acidic medium solutions, which were 0.1.and 1.0 M hydrochloric acids (HCl). The corrosion rate also was investigated for immersion samples of 1.0 M HCl for 21 days. From the results obtained, added TiB2 and Sc onto Al-Si alloy gave the better properties in corrosion resistance. Corrosion rates to reduce when the samples were immersed in a lower concentration of acidic medium, 0.1 HCl. However, there are some significant on the result but it still following the corrosion rates trend. Thus, improvements to reinforcement content need to be done in further research to cover the lack of this corrosion rates trend

Bedside nurses\u27 perceptions of effective nurse-physician communication in general medical units: A qualitative study

Background There is a dearth of research on successful interventions to improve nurse-physician communication (NPC). An important step is identifying what matters to bedside nurses and their perceptions of effective NPC communications and actions. Methods We conducted three focus groups with a total of 19 medical unit nurses across two hospitals in one academic medical center in the United States. Using a convenience sampling strategy, five to eight nurses voluntarily participated in each focus group. The recording was transcribed verbatim and two independent coders performed coding and resolved any discrepancies in codes. Qualitative content analysis was pursued to identify themes and associated quotes. Results The presence of direct communication between physicians and nurses was identified as the first theme and perceived by nurses as very important. Additional themes related to physician communication and attributes emerged including collegiality and respect (e.g., engaging nurses as partners in patient care), attentiveness and responsiveness (e.g., listening carefully and addressing concerns), and directness and support (e.g., backing nurses up in difficult situations). Effective NPC is further facilitated by organizational structure, relationship development separate from patient care, and consistent/timely use of technology. Conclusions Hospital bedside nurses provided valuable insight into improved physician communication and what attributes contribute to more effective NPC. Most importantly, they emphasized the significance of physicians in supporting them with difficult patients

Genome-Wide Discovery and Deployment of Insertions and Deletions Markers Provided Greater Insights on Species, Genomes, and Sections Relationships in the Genus Arachis

Small insertions and deletions (InDels) are the second most prevalent and the most abundant structural variations in plant genomes. In order to deploy these genetic variations for genetic analysis in genus Arachis, we conducted comparative analysis of the draft genome assemblies of both the diploid progenitor species of cultivated tetraploid groundnut (Arachis hypogaea L.) i.e., Arachis duranensis (A subgenome) and Arachis ipaënsis (B subgenome) and identified 515,223 InDels. These InDels include 269,973 insertions identified in A. ipaënsis against A. duranensis while 245,250 deletions in A. duranensis against A. ipaënsis. The majority of the InDels were of single bp (43.7%) and 2–10 bp (39.9%) while the remaining were >10 bp (16.4%). Phylogenetic analysis using genotyping data for 86 (40.19%) polymorphic markers grouped 96 diverse Arachis accessions into eight clusters mostly by the affinity of their genome. This study also provided evidence for the existence of “K” genome, although distinct from both the “A” and “B” genomes, but more similar to “B” genome. The complete homology between A. monticola and A. hypogaea tetraploid taxa showed a very similar genome composition. The above analysis has provided greater insights into the phylogenetic relationship among accessions, genomes, sub species and sections. These InDel markers are very useful resource for groundnut research community for genetic analysis and breeding applications

Probing the action of a novel anti-leukaemic drug therapy at the single cell level using modern vibrational spectroscopy techniques

Acute myeloid leukaemia (AML) is a life threatening cancer for which there is an urgent clinical need for novel therapeutic approaches. A redeployed drug combination of bezafibrate and medroxyprogesterone acetate (BaP) has shown anti-leukaemic activity in vitro and in vivo. Elucidation of the BaP mechanism of action is required in order to understand how to maximise the clinical benefit. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, Synchrotron radiation FTIR (S-FTIR) and Raman microspectroscopy are powerful complementary techniques which were employed to probe the biochemical composition of two AML cell lines in the presence and absence of BaP. Analysis was performed on single living cells along with dehydrated and fixed cells to provide a large and detailed data set. A consideration of the main spectral differences in conjunction with multivariate statistical analysis reveals a significant change to the cellular lipid composition with drug treatment; furthermore, this response is not caused by cell apoptosis. No change to the DNA of either cell line was observed suggesting this combination therapy primarily targets lipid biosynthesis or effects bioactive lipids that activate specific signalling pathways

A multi-center study of COVID-19 patient prognosis using deep learning-based CT image analysis and electronic health records

Purpose: As of August 30th, there were in total 25.1 million confirmed cases and 845 thousand deaths caused by coronavirus disease of 2019 (COVID-19) worldwide. With overwhelming demands on medical resources, patient stratification based on their risks is essential. In this multi-center study, we built prognosis models to predict severity outcomes, combining patients� electronic health records (EHR), which included vital signs and laboratory data, with deep learning- and CT-based severity prediction. Method: We first developed a CT segmentation network using datasets from multiple institutions worldwide. Two biomarkers were extracted from the CT images: total opacity ratio (TOR) and consolidation ratio (CR). After obtaining TOR and CR, further prognosis analysis was conducted on datasets from INSTITUTE-1, INSTITUTE-2 and INSTITUTE-3. For each data cohort, generalized linear model (GLM) was applied for prognosis prediction. Results: For the deep learning model, the correlation coefficient of the network prediction and manual segmentation was 0.755, 0.919, and 0.824 for the three cohorts, respectively. The AUC (95 CI) of the final prognosis models was 0.85(0.77,0.92), 0.93(0.87,0.98), and 0.86(0.75,0.94) for INSTITUTE-1, INSTITUTE-2 and INSTITUTE-3 cohorts, respectively. Either TOR or CR exist in all three final prognosis models. Age, white blood cell (WBC), and platelet (PLT) were chosen predictors in two cohorts. Oxygen saturation (SpO2) was a chosen predictor in one cohort. Conclusion: The developed deep learning method can segment lung infection regions. Prognosis results indicated that age, SpO2, CT biomarkers, PLT, and WBC were the most important prognostic predictors of COVID-19 in our prognosis model. © 202

Raman Spectroscopy and Regenerative Medicine: A Review

The field of regenerative medicine spans a wide area of the biomedical landscape—from single cell culture in laboratories to human whole-organ transplantation. To ensure that research is transferrable from bench to bedside, it is critical that we are able to assess regenerative processes in cells, tissues, organs and patients at a biochemical level. Regeneration relies on a large number of biological factors, which can be perturbed using conventional bioanalytical techniques. A versatile, non-invasive, non-destructive technique for biochemical analysis would be invaluable for the study of regeneration; and Raman spectroscopy is a potential solution. Raman spectroscopy is an analytical method by which chemical data are obtained through the inelastic scattering of light. Since its discovery in the 1920s, physicists and chemists have used Raman scattering to investigate the chemical composition of a vast range of both liquid and solid materials. However, only in the last two decades has this form of spectroscopy been employed in biomedical research. Particularly relevant to regenerative medicine are recent studies illustrating its ability to characterise and discriminate between healthy and disease states in cells, tissue biopsies and in patients. This review will briefly outline the principles behind Raman spectroscopy and its variants, describe key examples of its applications to biomedicine, and consider areas of regenerative medicine that would benefit from this non-invasive bioanalytical tool

Optimized cross-layer forward error correction coding for H.264 AVC video transmission over wireless channels

Forward error correction (FEC) codes that can provide unequal error protection (UEP) have been used recently for video transmission over wireless channels. These video transmission schemes may also benefit from the use of FEC codes both at the application layer (AL) and the physical layer (PL). However, the interaction and optimal setup of UEP FEC codes at the AL and the PL have not been previously investigated. In this paper, we study the cross-layer design of FEC codes at both layers for H.264 video transmission over wireless channels. In our scheme, UEP Luby transform codes are employed at the AL and rate-compatible punctured convolutional codes at the PL. In the proposed scheme, video slices are first prioritized based on their contribution to video quality. Next, we investigate the four combinations of cross-layer FEC schemes at both layers and concurrently optimize their parameters to minimize the video distortion and maximize the peak signal-to-noise ratio. We evaluate the performance of these schemes on four test H.264 video streams and show the superiority of optimized cross-layer FEC design.Peer reviewedElectrical and Computer Engineerin