We present a conceptual sampling electromagnetic calorimeter based on secondary electron emission process. The secondary electron emission process was implemented in Geant4 as a user physics class, ...which accurately reproduces the energy spectrum and yield of secondary electrons for thin metals. The simulation results for the response linearity and energy resolution are compared with that of a scintillation calorimeter. The response and energy resolution of the calorimeter were obtained for electron energies up to 50 GeV . The response linearity to electromagnetic showers is to within 1.5%, whereas the energy resolution is σ/E=(44%)GeV1/2/ E for 2.5 cm sampling of iron absorber.
We present updated results from a simulation study of a conceptual sampling electromagnetic calorimeter based on secondary electron emission process. We implemented the secondary electron emission ...process in Geant4 as a user physics list and produced the energy spectrum and yield of secondary electrons. The energy resolution of the SEE calorimeter was σ/E=(41%)GeV1/2/ E and the response linearity to electromagnetic showers was to within 1.5%. The simulation results were also compared with a traditional scintillator calorimeter.
Feature selection is essential in various fields of science and engineering, from remote sensing to computer vision. Reducing data dimensionality by removing redundant features and selecting the most ...informative ones improves machine learning algorithms' performance, especially in supervised classification tasks, while lowering storage needs. Graph-embedding techniques have recently been found efficient for feature selection since they preserve the geometric structure of the original feature space while embedding data into a low-dimensional subspace. However, the main drawback is the high computational cost of solving an eigenvalue decomposition problem, especially for large-scale problems. This paper addresses this issue by combining the graph embedding framework and representation theory for a novel feature selection method. Inspired by the high dimensional model representation, the feature transformation is assumed to be a linear combination of a set of univariate orthogonal functions carried out in the graph embedding framework. As a result, an explicit embedding function is created, which can be utilised to embed out-of-samples into low-dimensional space and provide a feature relevance score. The significant contribution of the proposed method is to divide an n -dimensional generalised eigenvalue problem into n small-sized eigenvalue problems. With this property, the computational complexity of the graph embedding is significantly reduced, resulting in a scalable feature selection method, which could be easily parallelized too. The performance of the proposed method is compared favourably to its counterparts in high-dimensional hyperspectral image processing in terms of classification accuracy, feature stability, and computational time.
Abstract Gliomas are the most common primary brain tumors. Particularly in adult patients, the vast majority of gliomas belongs to the heterogeneous group of diffuse gliomas, i.e . glial tumors ...characterized by diffuse infiltrative growth in the preexistent brain tissue. Unfortunately, glioblastoma, the most aggressive (WHO grade IV) diffuse glioma is also by far the most frequent one. After standard treatment, the 2-year overall survival of glioblastoma patients is approximately only 25%. Advanced knowledge in the molecular pathology underlying malignant transformation has offered new handles and better treatments for several cancer types. Unfortunately, glioblastoma multiforme (GBM) patients have not yet profited as although numerous experimental drugs have been tested in clinical trials, all failed miserably. This grim prognosis for GBM is at least partly due to the lack of successful drug delivery across the blood–brain tumor barrier (BBTB). The human brain comprises over 100 billion capillaries with a total length of 400 miles, a total surface area of 20 m2 and a median inter-capillary distance of about 50 μm, making it the best perfused organ in the body. The BBTB encompasses existing and newly formed blood vessels that contribute to the delivery of nutrients and oxygen to the tumor and facilitate glioma cell migration to other parts of the brain. The high metabolic demands of high-grade glioma create hypoxic areas that trigger increased expression of VEGF and angiogenesis, leading to the formation of abnormal vessels and a dysfunctional BBTB. Even though the BBTB is considered ‘leaky’ in the core part of glioblastomas, in large parts of glioblastomas and, even more so, in lower grade diffuse gliomas the BBTB more closely resembles the intact blood–brain barrier (BBB) and prevents efficient passage of cancer therapeutics, including small molecules and antibodies. Thus, many drugs can still be blocked from reaching the many infiltrative glioblastoma cells that demonstrate ‘within-organ-metastasis’ away from the core part to brain areas displaying a more organized and less leaky BBTB. Hence, drug delivery in glioblastoma deserves explicit attention as otherwise new experimental therapies will continue to fail. In the current review we highlight different aspects of the BBTB in glioma patients and preclinical models and discuss the advantages and drawbacks of drug delivery approaches for the treatment of glioma patients. We provide an overview on methods to overcome the BBTB, including osmotic blood–brain barrier disruption (BBBD), bradykinin receptor-mediated BBTB opening, inhibition of multidrug efflux transporters, receptor-mediated transport systems and physiological circumvention of the BBTB. While our knowledge about the molecular biology of glioma cells is rapidly expanding and is, to some extent, already assisting us in the design of tumor-tailored therapeutics, we are still struggling to develop modalities to expose the entire tumor to such therapeutics at pharmacologically meaningful quantities. Therefore, we must expand our knowledge about the fundamentals of the BBTB as a step toward the design of practical and safe devices and approaches for enhanced drug delivery into the diseased brain area.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
There are emerging trends to use the Industrial Internet of Things (IIoT) in manufacturing and related industries. Machine Learning (ML) techniques are widely used to interpret the collected IoT data ...for improving the company's operational excellence and predictive maintenance. In general, ML applications require high computational resource allocation and expertise. Manufacturing companies usually transfer their IIoT data to an ML-enabled third party or a cloud system. Although the transmission process uses encryption, ML applications still need decrypted data to perform ML tasks efficiently. Therefore, the third parties may have unacceptable access rights during the data processing to the content of IIoT data that contains a portrait of the production process. IIoT data may include hidden sensitive features, creating an information leakage for the companies. All these concerns prevent companies from sharing their IIoT data with third parties. This paper proposes a novel method based on the hybrid usage of Generative Adversarial Networks (GAN) and Differential Privacy (DP) to preserve sensitive data in IIoT operations. We aim to sustain IIoT data privacy with minimal accuracy loss without adding high additional computational costs to the overall data processing scheme. We demonstrate the efficiency of our approach with publicly available data sets and a realistic IIoT data set collected from a confectionery production process.
The objective of this study was to assess the rate of nosocomial infections (NIs), frequency of nosocomial pathogens and antimicrobial susceptibility changes in a 530-bed hospital over a five-year ...period. Hospital-wide laboratory-based NI surveillance was performed prospectively between 1999 and 2003. The Centers for Disease Control and Prevention's definitions were used for NIs and nosocomial surgical site infections, and NI rates were calculated by the number of NIs per number of hospitalized patients on an annual basis. NI rates ranged between 1.4% and 2.4%. Higher rates were observed in the neurology, neurosurgery, paediatric and dermatology departments; the low rate of NIs overall may be due to the surveillance method used. The most commonly observed infections were urinary tract, surgical site and primary bloodstream infections, and the most frequently isolated pathogens were
Escherichia coli,
Klebsiella pneumoniae,
Enterococcus spp. and
Staphylococcus aureus. Carbapenems were the most effective agents against enterobacteriaceae. Meticillin resistance among
S. aureus isolates was less than 50%, and all
S. aureus and
Enterococcus spp. isolates were susceptible to glycopeptides apart from one glycopeptide-resistant
E. faecium isolate identified in 2003. Data obtained by the same method enabled comparison between years and assisted in the detection of recent changes. Antimicrobial susceptibility data on nosocomial pathogens provided valuable guidance for empirical antimicrobial therapy of NIs.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Power flow calculations are crucial for the study of power systems, as they can be used to calculate bus voltage magnitudes and phase angles, as well as active and reactive power flows on lines. In ...this paper, a new approach, the Recycling Newton–Krylov (ReNK) algorithm, is proposed to solve the linear systems of equations in Newton–Raphson iterations. The proposed method uses the Generalized Conjugate Residuals with inner orthogonalization and deflated restarting (GCRO-DR) method within the Newton–Raphson algorithm and reuses the Krylov subspace information generated in previous Newton runs. We evaluate the performance of the proposed method over the traditional direct solver (LU) and iterative solvers (Generalized Minimal Residual Method (GMRES), the Biconjugate Gradient Stabilized Method (Bi-CGSTAB) and Quasi-Minimal Residual Method (QMR)) as the inner linear solver of the Newton–Raphson method. We use different test systems with a number of busses ranging from 300 to 70000 and compare the number of iterations of the inner linear solver (for iterative solvers) and the CPU times (for both direct and iterative solvers). We also test the performance of the ReNK algorithm for contingency analysis and for different load conditions to simulate optimization problems and observe possible performance gains.
•A novel recycling Krylov subspace approach for the power flow algorithm•Investigation of the angles between the Krylov subspaces generated from the Jacobians•ILU preconditioner is used once with AMD reordering for iterative solutions•Computational improvement due to similar subspaces for contingencies/varying loads•Extensive set of experiments for several different iterative and direct solvers.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Background
: Recent studies have indicated that polymorphisms of the interleukin-18 (IL-18) and interleukin-12 (IL-12) genes are associated with the development of Type 1 diabetes mellitus (T1 DM) in ...some populations, but not all.
Aim
: The present study was designed to examine the roles of polymorphisms in the IL-18 promoter and IL-12p40 with respect to susceptibility to T1 DM in Turkish patients.
Subjects and Methods
: Ninety-one patients with T1 DM and 87 unrelated healthy subjects were included in the study. The IL-18 polymorphisms at positions −607 and −137 were detected by a sequence-specific PCR method. The single nucleotide polymorphism in the IL-12p40 3′ untranslated region (3′-UTR) at position +1188 was analyzed by the PCR-restriction fragment length polymorphism (RFPL) method.
Results
: The allelic and genotypic frequencies of the IL-18 and IL-12p40 polymorphisms did not differ significantly between subjects with T1DM and the controls (
p
>0.05). However, diabetic patients with the −137 (CC) genotype showed a younger onset age compared to patients with the −137 (GG) genotype (
p
=0.02). In addition, patients with the −607 (CC) genotype had higher levels of glycated hemoglobin (HbA1 c) than patients with the −607 (AC) genotype (
p
=0.004). Furthermore, patients with the IL-12p40 (AC) genotype had higher HbA
1c
levels than patients with the IL-12p40 (AA) genotype (
p
=0.01).
Conclusions
: The results of the present study show that the IL-18 and IL-12p40 polymorphisms may have some effect on the onset age and deterioration of glycemic control in Turkish patients with T1 DM.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Abstract
Background
Even the mechanism of coronary artery ectasia (CAE) shares the common pathophysiologic steps and risk factors with atherosclerosis which led to assume that CAE is a variant of ...atherosclerosis, there are certain discrepancies or aspects incompatible of atherosclerosis.
Purpose
We hypothesized that pathophysiology of CAE might differ from that of atherosclerosis in terms of inflammatory parameters, infectious agents. Therefore, we assessed and compared the levels of IgG antibody against Chlamydia pneumonia, and Helicobacter Pylori, components of serum protein electrophoresis and plasma levels of total Ig G and Ig E.
Materials and methods
Seventy patients with coronary artery disease (CAD) and 30 patients with CAD coexisted with CAE comprised the study populations. Blood samples were allowed to clot at room temperature then centrifuged at 1500 rpm for 5 minutes then serum kept at deep freeze (−20°C) to be used for the measurement of IgG antibodies against C. pneumoniae and H. Pylori, total IgE, IgG levels and protein electrophoresis.
Results
There were not statistically significant differences between patients with and without CAE regarding the clinical and laboratory parameters except hemoglobin levels (Figure I). IgE, Alpha 2 macroglobulin, Beta-1 globulin levels were found to be higher in patients with CAE+CAD than those of CAD alone (Figure IIa). There was no statistically significant correlation between the Gensini score, and IgG antibody against H. Pylori (r=0.048, p=0.66) and C. Pneumoniae (r=−0.12, p=0.27) regarding the whole study population. Additionally, logistic regression analysis by including variables IgE, hemoglobin, Alpha 2 macroglobulin, beta-1 globulin, and gender, revealed that Ig E and alpha 2 macroglobulin were independently and positively associated with the presence of CAE (Figure IIb).
Conclusion
Independent association of serum IgE levels and alpha2 globulins with the presence of CAE underlines the divergent features of pathophysiology of CAE compared with atherosclerosis or CAD alone.
Funding Acknowledgement
Type of funding sources: None. Figure IFigure II
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