Detection of Tomato leaf diseases for agro-based industries using novel PCA DeepNet

The advancement of Deep Learning and Computer Vision in the field of agriculture has been found to be an effective tool in detecting harmful plant diseases. Classification and detection of healthy and diseased crops play a very crucial role in determining the rate and quality of production. Thus the present work highlights a well-proposed novel method of detecting Tomato leaf diseases using Deep Neural Networks to strengthen agro-based industries. The present novel framework is utilized with a combination of classical Machine Learning model Principal Component Analysis (PCA) and a customized Deep Neural Network which has been named as PCA DeepNet. The hybridized framework also consists of Generative Adversarial Network (GAN) for obtaining a good mixture of datasets. The detection is carried out using the Faster Region-Based Convolutional Neural Network (F-RCNN). The overall work generated a classification accuracy of 99.60% with an average precision of 98.55%; giving a promising Intersection over Union (IOU) score of 0.95 in detection. Thus the presented work outperforms any other reported state-of-the-art.Web of Science11150011498

Novel proposals for FAIR, automated, recommendable, and robust workflows

Funding: This work is partly funded by NSF award OAC-1839900. This material is based upon work supported by the U.S. Department of Energy, Office of Science, under contract number DE-AC02-06CH11357. libEnsemble was developed as part of the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration. This research used resources of the OLCF at ORNL, which is supported by the Office of Science of the U.S. DOE under Contract No. DE-AC05-00OR22725.Lightning talks of the Workflows in Support of Large-Scale Science (WORKS) workshop are a venue where the workflow community (researchers, developers, and users) can discuss work in progress, emerging technologies and frameworks, and training and education materials. This paper summarizes the WORKS 2022 lightning talks, which cover five broad topics: data integrity of scientific workflows; a machine learning-based recommendation system; a Python toolkit for running dynamic ensembles of simulations; a cross-platform, high-performance computing utility for processing shell commands; and a meta(data) framework for reproducing hybrid workflows.Postprin

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

An Ensemble of Condition Based Classifiers for Device Independent Detailed Human Activity Recognition Using Smartphones

Human activity recognition is increasingly used for medical, surveillance and entertainment applications. For better monitoring, these applications require identification of detailed activity like sitting on chair/floor, brisk/slow walking, running, etc. This paper proposes a ubiquitous solution to detailed activity recognition through the use of smartphone sensors. Use of smartphones for activity recognition poses challenges such as device independence and various usage behavior in terms of where the smartphone is kept. Only a few works address one or more of these challenges. Consequently, in this paper, we present a detailed activity recognition framework for identifying both static and dynamic activities addressing the above-mentioned challenges. The framework supports cases where (i) dataset contains data from accelerometer; and the (ii) dataset contains data from both accelerometer and gyroscope sensor of smartphones. The framework forms an ensemble of the condition based classifiers to address the variance due to different hardware configuration and usage behavior in terms of where the smartphone is kept (right pants pocket, shirt pockets or right hand). The framework is implemented and tested on real data set collected from 10 users with five different device configurations. It is observed that, with our proposed approach, 94% recognition accuracy can be achieved

Conceptual aerodynamic design of a 150-seat Prandtlplane aircraft

This conceptual design study of a 150-seat short-rang aircraft was undertaken to investigate whether a Prandtlplane (box-wing) configuration with a similar lifting surface area to an Airbus A320 could prove to be more efficient and feasible from an aerodynamic point of view than the A320. Using vortex lattice analysis via the well-proven Athena Vortex Lattice (AVL) software, a variety of geometric parameter sweeps were conducted in order to assess the influence of vertical wing separation, horizontal wing separation, aspect ratio, anhedral and dihedral, wing sweep and other such parameters on aerodynamic qualities such lift coefficient, induced drag coefficient, Oswald efficiency factor and ultimately the lift-to-drag efficiency of the configuration, while keeping the lifting surface area constant between all models in order to maintain comparability. The results found that for the Prandtlplane of this size, judicious design and a concept of a double-decker aircraft could bring up to almost 40% improvement in overall lift-to-drag efficiency for wings of the same span as the baseline aircraft. These kinds of staggering results demand further research, as does the fact that the most efficient configuration was in fact not a conventional Prandtlplane (with one aft-swept wing and one forward-swept wing) at all but a configuration incorporating two forward swept-wings with attached vertical endplates. This kind of configuration is not present in any design studies found before, and requires thorough verification and research before it can be recommended as the ideal configuration to pursue. In terms of the geometric sweeps conducted, the vertical separation was found to have the greatest influence, but also the horizontal separation was found to have an influence at short distance (leading to the biplane model). The version of the Prandtlplane with the wings fixed as having an aspect ratio equal to the baseline aircraft did not fare so well in the feasibility trials, but the aircraft with the same wingspan arrived at the results mentioned above. More research needs to be conducted and a multi-disciplinary design model considering both aerodynamic and structural effects needs to be developed alongside wind tunnel testing and flow visualisation to gain a better understanding of how these geometries might actually work in real life. Important stability and control issues also need to be considered but overall this kind of configuration holds great promise for future aircraft design

CXCL12 chemokine expression suppresses human pancreatic cancer growth and metastasis.

Pancreatic ductal adenocarcinoma is an unsolved health problem with nearly 75% of patients diagnosed with advanced disease and an overall 5-year survival rate near 5%. Despite the strong link between mortality and malignancy, the mechanisms behind pancreatic cancer dissemination and metastasis are poorly understood. Correlative pathological and cell culture analyses suggest the chemokine receptor CXCR4 plays a biological role in pancreatic cancer progression. In vivo roles for the CXCR4 ligand CXCL12 in pancreatic cancer malignancy were investigated. CXCR4 and CXCR7 were consistently expressed in normal and cancerous pancreatic ductal epithelium, established cell lines, and patient-derived primary cancer cells. Relative to healthy exocrine ducts, CXCL12 expression was pathologically repressed in pancreatic cancer tissue specimens and patient-derived cell lines. To test the functional consequences of CXCL12 silencing, pancreatic cancer cell lines stably expressingthe chemokine were engineered. Consistent with a role for CXCL12 as a tumor suppressor, cells producing the chemokine wereincreasingly adherent and migration deficient in vitro and poorly metastatic in vivo, compared to control cells. Further, CXCL12 reintroduction significantly reduced tumor growth in vitro, with significantly smaller tumors in vivo, leading to a pronounced survival advantage in a preclinical model. Together, these data demonstrate a functional tumor suppressive role for the normal expression of CXCL12 in pancreatic ducts, regulating both tumor growth andcellulardissemination to metastatic sites

Complete Comparison Display (CCD) evaluation of ethanol extracts of <i>Centella asiatica</i> and <i>Withania somnifera</i> shows that they can non-synergistically ameliorate biochemical and behavioural damages in MPTP induced Parkinson's model of mice

<div><p>Parkinson’s disease remains as one of the most common debilitating neurodegenerative disorders. With the hopes of finding agents that can cure or reduce the pace of progression of the disease, we studied two traditional medicinal plants: <i>Centella asiatica</i> and <i>Withania somnifera</i> that have been explored in some recent studies. In agreement with the previous work on ethanol extracts of these two plants in mice model, we saw an improvement in oxidative stress profile as well as behavioral performance in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) induced Parkinson-like symptoms in Balb/c mice. Given the known potential of both the herbal extracts in improving Parkinson-like symptoms, we expected the combination of the two to show better results than either of the two but surprisingly there was no additivity in either oxidative stress or behavioural recovery. In fact, in some assays, the combination performed worse than either of the two individual constituents. This effect of mixtures highlights the need of testing mixtures in supplements market using enthomedicine. The necessity of comparing multiple groups in this study to get most information from the experiments motivated us to design a ladder-like visualization to show comparison with different groups that we call complete comparison display (CCD). In summary, we show the potential of <i>Centella asiatica</i> and <i>Withania somnifera</i> to ameliorate Parkinson’s disorder.</p></div