Imbalances in directed multigraphs

In a directed multigraph, the imbalance of a vertex $v_{i}$ is defined as $b_{v_{i}}=d_{v_{i}}^{+}-d_{v_{i}}^{-}$, where $d_{v_{i}}^{+}$ and $d_{v_{i}}^{-}$ denote the outdegree and indegree respectively of $v_{i}$. We characterize imbalances in directed multigraphs and obtain lower and upper bounds on imbalances in such digraphs. Also, we show the existence of a directed multigraph with a given imbalance set

Mineral and heavy metals content in tilapia fish (Oreochromis niloticus) collected from the River Nile in Damietta governorate, Egypt and evaluation of health risk from tilapia consumption

This study was conducted to determine heavy metals and trace elements content in tilapia fish collected from three sources in Damietta governorate, Egypt and to evaluate the human health risk due to tilapia consumption. Tilapia samples were collected from two locations in the River Nile stream, tow fish farms and two sluiceways. Health risk assessment was evaluated based on the consumption habits of adult human. The results revealed that all samples vary in elements concentrations. The calculation of human health risk revealed that the consumption of tilapia in the three tested area does not pose any health risk except for Selenium. It could be concluded that consumption of such fish may be a risk for consumers who eat fish more than one time per week. Consequently, precautions should be taken and warning against eating tilapia fish caught from these regions should be announced.This study was conducted to determine heavy metals and trace elements content in tilapia fish collected from three sources in Damietta governorate, Egypt and to evaluate the human health risk due to tilapia consumption. Tilapia samples were collected from two locations in the River Nile stream, tow fish farms and two sluiceways. Health risk assessment was evaluated based on the consumption habits of adult human. The results revealed that all samples vary in elements concentrations. The calculation of human health risk revealed that the consumption of tilapia in the three tested area does not pose any health risk except for Selenium. It could be concluded that consumption of such fish may be a risk for consumers who eat fish more than one time per week. Consequently, precautions should be taken and warning against eating tilapia fish caught from these regions should be announced

Optimum spacing between grooved tubes: an experimental study

An experimental study on the optimum spacing between grooved tubes is reported in this paper. Two grooved tubes having a pitch of 10 mm and 15 mm and a plain tube were considered for the heat transfer analysis. The spacing between two tubes with the same pitch was varied from 10 mm to 35 mm with a step size of 5 mm. The velocity of air flowing over the tube surfaces was changed from 0.4 m/s to 1 m/s using a blower fan. Based on Nusselt number (Nu) the optimum spacing between the tubes was decided. The optimum spacing between grooved tubes of pitch 10 mm and 15 mm was compared with that of plain tubes. From the experimental analysis, it was noticed that with an increase in air velocity (increase in Reynolds number) the tube surface temperature reduced irrespective of any tube considered. Nu increased with an increase in air velocity for all the tubes. The important conclusion drawn from the present study was that there exists a limiting spacing (optimum) between the tubes above which no change in Nu was observed. The spacing of 30 mm was found to be the optimum spacing between the tubes irrespective of its surface geometry modifications

Deep Active Learning for Automatic Mitotic Cell Detection on HEp-2 Specimen Medical Images

Identifying Human Epithelial Type 2 (HEp-2) mitotic cells is a crucial procedure in anti-nuclear antibodies (ANAs) testing, which is the standard protocol for detecting connective tissue diseases (CTD). Due to the low throughput and labor-subjectivity of the ANAs' manual screening test, there is a need to develop a reliable HEp-2 computer-aided diagnosis (CAD) system. The automatic detection of mitotic cells from the microscopic HEp-2 specimen images is an essential step to support the diagnosis process and enhance the throughput of this test. This work proposes a deep active learning (DAL) approach to overcoming the cell labeling challenge. Moreover, deep learning detectors are tailored to automatically identify the mitotic cells directly in the entire microscopic HEp-2 specimen images, avoiding the segmentation step. The proposed framework is validated using the I3A Task-2 dataset over 5-fold cross-validation trials. Using the YOLO predictor, promising mitotic cell prediction results are achieved with an average of 90.011% recall, 88.307% precision, and 81.531% mAP. Whereas, average scores of 86.986% recall, 85.282% precision, and 78.506% mAP are obtained using the Faster R-CNN predictor. Employing the DAL method over four labeling rounds effectively enhances the accuracy of the data annotation, and hence, improves the prediction performance. The proposed framework could be practically applicable to support medical personnel in making rapid and accurate decisions about the mitotic cells' existence

On graph energy, maximum degree and vertex cover number

For a simple graph $G$ with $n$ vertices and $m$ edges having adjacency eigenvalues $\lambda_1,\lambda_2, \dots,\lambda_n$, the energy $E(G)$ of $G$ is defined as $E(G)=\sum_{i=1}^{n} |\lambda_i|$. We obtain the upper bounds for $E(G)$ in terms of the vertex covering number $\tau$, the number of edges $m$, maximum vertex degree $d_1$ and second maximum vertex degree $d_2$ of the connected graph $G$. These upper bounds improve some recently known upper bounds for $E(G)$. Further, these upper bounds for $E(G)$ imply a natural extension to other energies like distance energy and Randi\'{c} energy associated to a connected graph $G$

Structural representations of DNA regulatory substrates can enhance sequence-based algorithms by associating functional sequence variants

The nucleotide sequence representation of DNA can be inadequate for resolving protein-DNA binding sites and regulatory substrates, such as those involved in gene expression and horizontal gene transfer. Considering that sequence-like representations are algorithmically very useful, here we fused over 60 currently available DNA physicochemical and conformational variables into compact structural representations that can encode single DNA binding sites to whole regulatory regions. We find that the main structural components reflect key properties of protein-DNA interactions and can be condensed to the amount of information found in a single nucleotide position. The most accurate structural representations compress functional DNA sequence variants by 30% to 50%, as each instance encodes from tens to thousands of sequences. We show that a structural distance function discriminates among groups of DNA substrates more accurately than nucleotide sequence-based metrics. As this opens up a variety of implementation possibilities, we develop and test a distance-based alignment algorithm, demonstrating the potential of using the structural representations to enhance sequence-based algorithms. Due to the bias of most current bioinformatic methods to nucleotide sequence representations, it is possible that considerable performance increases might still be achievable with such solutions.Comment: 20 pages, 8 figures, 3 tables, conferenc

Magnetic resonance lung function – a breakthrough for lung imaging and functional assessment? A phantom study and clinical trial

BACKGROUND: Chronic lung diseases are a major issue in public health. A serial pulmonary assessment using imaging techniques free of ionizing radiation and which provides early information on local function impairment would therefore be a considerably important development. Magnetic resonance imaging (MRI) is a powerful tool for the static and dynamic imaging of many organs. Its application in lung imaging however, has been limited due to the low water content of the lung and the artefacts evident at air-tissue interfaces. Many attempts have been made to visualize local ventilation using the inhalation of hyperpolarized gases or gadolinium aerosol responding to MRI. None of these methods are applicable for broad clinical use as they require specific equipment. METHODS: We have shown previously that low-field MRI can be used for static imaging of the lung. Here we show that mathematical processing of data derived from serial MRI scans during the respiratory cycle produces good quality images of local ventilation without any contrast agent. A phantom study and investigations in 85 patients were performed. RESULTS: The phantom study proved our theoretical considerations. In 99 patient investigations good correlation (r = 0.8; p ≤ 0.001) was seen for pulmonary function tests and MR ventilation measurements. Small ventilation defects were visualized. CONCLUSION: With this method, ventilation defects can be diagnosed long before any imaging or pulmonary function test will indicate disease. This surprisingly simple approach could easily be incorporated in clinical routine and may be a breakthrough for lung imaging and functional assessment