Comparative study of residual stress prediction methods in additive manufacturing processes

The additive manufacturing (AM) of products involves various processes, such as raising the temperature of a work-piece (part) and substrate to the melting point and subsequent solidification, using a movable source of heat. The work piece is subjected to repeated cycles of heating and cooling. The main objective of this work was to present an overview of the various methods used for prediction of the residual stresses and how their contributions can be used to improve current additive manufacturing methods. These novel methods of manufacturing have several merits, compared to conventional methods. Some of these merits include the lower costs, higher precision and accuracy of manufacturing, faster processing time and more eco-friendly approaches to processes involved.

Deep Learning in Prostate Cancer Diagnosis Using Multiparametric Magnetic Resonance Imaging With Whole-Mount Histopathology Referenced Delineations

Background: Multiparametric magnetic resonance imaging (mpMRI) plays an important role in the diagnosis of prostate cancer (PCa) in the current clinical setting. However, the performance of mpMRI usually varies based on the experience of the radiologists at different levels; thus, the demand for MRI interpretation warrants further analysis. In this study, we developed a deep learning (DL) model to improve PCa diagnostic ability using mpMRI and whole-mount histopathology data.Methods: A total of 739 patients, including 466 with PCa and 273 without PCa, were enrolled from January 2017 to December 2019. The mpMRI (T2 weighted imaging, diffusion weighted imaging, and apparent diffusion coefficient sequences) data were randomly divided into training (n = 659) and validation datasets (n = 80). According to the whole-mount histopathology, a DL model, including independent segmentation and classification networks, was developed to extract the gland and PCa area for PCa diagnosis. The area under the curve (AUC) were used to evaluate the performance of the prostate classification networks. The proposed DL model was subsequently used in clinical practice (independent test dataset; n = 200), and the PCa detective/diagnostic performance between the DL model and different level radiologists was evaluated based on the sensitivity, specificity, precision, and accuracy.Results: The AUC of the prostate classification network was 0.871 in the validation dataset, and it reached 0.797 using the DL model in the test dataset. Furthermore, the sensitivity, specificity, precision, and accuracy of the DL model for diagnosing PCa in the test dataset were 0.710, 0.690, 0.696, and 0.700, respectively. For the junior radiologist without and with DL model assistance, these values were 0.590, 0.700, 0.663, and 0.645 versus 0.790, 0.720, 0.738, and 0.755, respectively. For the senior radiologist, the values were 0.690, 0.770, 0.750, and 0.730 vs. 0.810, 0.840, 0.835, and 0.825, respectively. The diagnosis made with DL model assistance for radiologists were significantly higher than those without assistance (P < 0.05).Conclusion: The diagnostic performance of DL model is higher than that of junior radiologists and can improve PCa diagnostic accuracy in both junior and senior radiologists.

Detection and development of a quantitation method for undeclared compounds in antidiabetic biologically active additives and its validation by high performance liquid chromatography

An isocratic, high-performance liquid chromatography (HPLC) quantitation method was developed for the quantitative determination of metformin, glibenclamide, gliclazide, glimepiride in some antidiabetic biologically active additives. A Nucleosil C18, 5 μm, 4.6 mm × 150 mm, column with mobile phase containing buffer (10 mm Na2HPO4, 10 mm sodium dodecyl sulfate): acetonitrile = 68 : 32 (V/V), pH = 7.5 was used. The flow rate was 1.0 mL/min, and effluents were monitored at 226 nm. The retention times of gliclazide glibenclamide, glimepiride and metformin, were 2.203, 4.587, 5.667 and 10.182 min, respectively. Linearity was studied by preparing standard solutions of gliclazide, glibenclamide, glimepiride and metformin at the concentration range of 50% to 150% of working concentration from a stock solution. The method was successfully applied to the estimation of gliclazide, glibenclamide, glimepiride and metformin in some antidiabetic biologically active additives. This method was validated to confirm its system suitability, selectivity, linearity, precision and accuracy according to international conference on harmonization (ICH) guidelines.

Precision and accuracy of sampling methods in thinned Pinus taeda L. stands

Different sampling methods can be used in forest surveys. It is important to know the precision and accuracy of these sampling methods, and which one is the most appropriate in specific conditions of the forest population. The aim of this study was to compare estimates of a forest inventory performed by different sampling methods with forest census results. The sampling methods evaluated were the fixed-area method and the variable-area methods of Bitterlich, Prodan, and Strand. The data were obtained in a 15-year-old thinned stand of Pinus taeda L., located in the municipality of Teixeira Soares, southern Brazil, with a total area of 12.80 ha. Initially, the forest census was carried out, and subsequently, the sample units for each sampling method were distributed in the stand, with a common starting point. The variables used to compare the sample results with the census means were quadratic diameter, number of trees, basal area, and volume, per hectare. Precision and accuracy were evaluated by sampling error and whether the confidence intervals covered the population means, respectively. The fixed-area and Bitterlich methods stood out in precision for all variables analysed. The fixed-area, Bitterlich and Strand methods with proportion to height provided more accurate estimates. The Prodan method provided inaccurate and imprecise estimates for the variables under analysis, except for the quadratic diameter.

High spectral stability and quantitative accuracy of LIBS by optimization of combined atomic and ionic line algorithm

Large spectral fluctuations bring large errors in laser-induced breakdown spectroscopy (LIBS) analysis, which impedes the improvement of precision and accuracy, limiting the large-scale application and commercialization. In this work, we...

Robotic arm- Automated real time object detection

In robotic industry, today, interactions between human and machine usually consists of programming and maintaining machine using human operator. Using a robotic system in any industry for work provides precision and a certain level of accuracy. A robotic entity such as a robotic arm will not ask for time out and can work efficiently day and night which will in turn increase efficiency in workplace. In this paper, we have explained about an arm created, which works in such a way that while the robotic arm is working, camera is able to identify any object it sees which is taken care by the worker looking over the arm. The major outcome and result is the increased efficiency in workplace, precision and accuracy in low cost which can also be used for house hold chores too.

Magnetic nanoprobes for rapid detection of copper ion in aqueous environment by surface-enhanced Raman spectroscopy

Magnetic SERS probes can rapidly detect copper ions within high precision and accuracy.

Household Transmission Investigation: Design, Reporting and Critical Appraisal.

Household transmission investigations (HHTI) contribute timely epidemiologic knowledge in response to emerging pathogens. HHTIs conducted in the context of the COVID-19 pandemic in 2020-21 reported variable methodological approaches, producing epidemiological estimates that vary in meaning, precision, and accuracy. Since specific tools to assist with the optimal design and critical appraisal of HHTIs are not available, the aggregation and pooling of HHTI to inform policy and interventions may be challenging. In this manuscript, we discuss key aspects of the HHTI design, we provide recommendations for the reporting of these studies, and propose an appraisal tool that contributes to the optimal design and critical appraisal of HHTI studies. The appraisal tool consists of 12 questions that explore 10 aspects of HHTIs and can be answered ‘yes’, ‘no’ or ‘unclear’. The manuscript seeks to fill a gap in the epidemiologic literature and contribute to standardise HHTI approaches across settings, to achieve richer and more informative datasets. The manuscript also calls for a periodic revision of HHTI protocols and critical appraisal tools