Impulse voltage distribution and frequency response of intershield windings

Impulse voltage distributions in continuous disk windings are nonlinear, due to the small series capacitance of the winding. Consequently, transformer manufacturers often design large power transformers with interleaved windings to increase series capacitance, but in doing so reduce the value of the initial impulse voltage distribution coefficient α given by α = √(Cg/Cs), (1) where Cg is the shunt capacitance and Cs is the series capacitance of the winding. Sometimes fully interleaved windings are employed because they are more reliable, ensuring that the transformer will operate properly under lightning strike

Assessment of urinary tract calculi with 16-MDCT: The axial versus coronal plane

The purpose of the current study was to compare the detection rate and size measurements of urinary tract calculi on coronal reformations versus the axial plane using 16-MDCT. In this cross sectional study 100 consecutive renal colic patients were evaluated using16- MDCT with collimation 1/5, axial thickness 2mm and coronal reformat thickness 2mm. Coronal and axial view randomly reported by two radiologist and then total images the other time reported by staff. 178 stones in axial and 168 stones in coronal view were detected but the mean number of detected stones in axial view was not significantly more than coronal view(p<0/05( . In two dimensional evaluation, maximum dimension of stones (kidneys and ureter totally) in coronal view was more than axial, but the difference was not significant (p<0/05). In two dimensional evaluation, maximum dimension of ureter stones the in coronal view was significantly more than axial. In 3D evaluation, stones size craniocaudaly in axial view was significantly more than coronal (0.001). The detection of stones was not improved using coronal view compared to axial view with thin thickness. Maximum size of ureter stones using coronal reformation was better estimated than axial view.Craniocaudal size of stone was overestimated in axial view than coronal probably because of partial volume effect

Prior Knowledge based Advanced Persistent Threats Detection for IoT in a Realistic Benchmark

The number of Internet of Things (IoT) devices being deployed into networks is growing at a phenomenal level, which makes IoT networks more vulnerable in the wireless medium. Advanced Persistent Threat (APT) is malicious to most of the network facilities and the available attack data for training the machine learning-based Intrusion Detection System (IDS) is limited when compared to the normal traffic. Therefore, it is quite challenging to enhance the detection performance in order to mitigate the influence of APT. Therefore, Prior Knowledge Input (PKI) models are proposed and tested using the SCVIC-APT- 2021 dataset. To obtain prior knowledge, the proposed PKI model pre-classifies the original dataset with unsupervised clustering method. Then, the obtained prior knowledge is incorporated into the supervised model to decrease training complexity and assist the supervised model in determining the optimal mapping between the raw data and true labels. The experimental findings indicate that the PKI model outperforms the supervised baseline, with the best macro average F1-score of 81.37%, which is 10.47% higher than the baseline.Comment: IEEE Global Communications Conference (Globecom), 2022, 6 pages, g figures, 6 table

SACOBRA with Online Whitening for Solving Optimization Problems with High Conditioning

Real-world optimization problems often have expensive objective functions in terms of cost and time. It is desirable to find near-optimal solutions with very few function evaluations. Surrogate-assisted optimizers tend to reduce the required number of function evaluations by replacing the real function with an efficient mathematical model built on few evaluated points. Problems with a high condition number are a challenge for many surrogate-assisted optimizers including SACOBRA. To address such problems we propose a new online whitening operating in the black-box optimization paradigm. We show on a set of high-conditioning functions that online whitening tackles SACOBRA's early stagnation issue and reduces the optimization error by a factor between 10 to 1e12 as compared to the plain SACOBRA, though it imposes many extra function evaluations. Covariance matrix adaptation evolution strategy (CMA-ES) has for very high numbers of function evaluations even lower errors, whereas SACOBRA performs better in the expensive setting (less than 1e03 function evaluations). If we count all parallelizable function evaluations (population evaluation in CMA-ES, online whitening in our approach) as one iteration, then both algorithms have comparable strength even on the long run. This holds for problems with dimension D Algorithms and the Foundations of Software technolog

Reduced order models for control of fluids using the Eigensystem Realization Algorithm

In feedback flow control, one of the challenges is to develop mathematical models that describe the fluid physics relevant to the task at hand, while neglecting irrelevant details of the flow in order to remain computationally tractable. A number of techniques are presently used to develop such reduced-order models, such as proper orthogonal decomposition (POD), and approximate snapshot-based balanced truncation, also known as balanced POD. Each method has its strengths and weaknesses: for instance, POD models can behave unpredictably and perform poorly, but they can be computed directly from experimental data; approximate balanced truncation often produces vastly superior models to POD, but requires data from adjoint simulations, and thus cannot be applied to experimental data. In this paper, we show that using the Eigensystem Realization Algorithm (ERA) \citep{JuPa-85}, one can theoretically obtain exactly the same reduced order models as by balanced POD. Moreover, the models can be obtained directly from experimental data, without the use of adjoint information. The algorithm can also substantially improve computational efficiency when forming reduced-order models from simulation data. If adjoint information is available, then balanced POD has some advantages over ERA: for instance, it produces modes that are useful for multiple purposes, and the method has been generalized to unstable systems. We also present a modified ERA procedure that produces modes without adjoint information, but for this procedure, the resulting models are not balanced, and do not perform as well in examples. We present a detailed comparison of the methods, and illustrate them on an example of the flow past an inclined flat plate at a low Reynolds number.Comment: 22 pages, 7 figure

The Association of Inflammatory Markers, IL-1α and TGF-β, with Dietary Insulin Load and Dietary Insulin Index in Overweight and Obese Women with Healthy and Unhealthy Metabolic Phenotypes: A Cross-Sectional Study

Context Research has shown IL-1α might play a role in the associations between the MH group and DII and DIL. Objective. We evaluated the association of inflammatory markers, IL-1α and TGF-β, with dietary insulin load and index in women with healthy and unhealthy obesity phenotypes. Materials and Methods. 228 obese/overweight women aged 18–48 years were included in this study. Biochemical factors were obtained from blood samples. Body composition, anthropometric measures, and physical activity assessments were performed. Dietary intakes, DII, and DIL were assessed. Results. Significant associations were observed between the MH group and the DII group (OR = 2.142, 95% CI = 1.421, 2.850, and p = 0.040), in which IL-1α may play a role. Discussion and Conclusion. Significant associations were observed between the MH group and DII. IL-1α might play a role in these associations

Retrieval of marine water constituents from AVIRIS data in the Hudson/Raritan Estuary

This paper reports on the validation of bio-optical models in estuarine and nearshore (case 2) waters of New Jersey-New York to retrieve accurate water leaving radiance spectra and chlorophyll concentration from the NASA Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data complemented with in situ measurements. The study area - Hudson/Raritan Estuary - is a complex estuarine system where tidal and wind-driven currents are modified by freshwater discharges from the Hudson, Raritan, Hackensack, and Passaic rivers. Over the last century the estuarine water quality has degraded, in part due to eutrophication, which has disrupted the pre-existing natural balance, resulting in phytoplankton blooms of both increased frequency and intensity, increasing oxygen demand and leading to episodes of hypoxia. During 1999-2001 data acquisitions by NASA AVIRIS field measurements were obtained to establish hydrological optical properties of the Hudson/Raritan Estuary: (1) concurrent above- and below-surface spectral irradiance; (2) sampling for laboratory determination of inherent optical properties; and (3) concentrations of optically-important water quality parameters. We used a bio-optical model based on Gordon et al. to predict the sub-surface irradiance reflectance from optically important water constituents. Modelling of reflectance is a prerequisite for processing remote sensing data to desired thematic maps for input into the geographical information system (GIS) for use as a management tool in water quality assessment. A Radiative Transfer Code - MODTRAN-4 - was applied to remove the effects of the atmosphere so as to infer the water leaving radiance from the AVIRS data. The results of this procedure were not satisfactory, therefore an alternative approach was tested to directly correct the AVIRIS image using modelled spectra based on measured optical characteristics. The atmospherically corrected AVIRIS ratio image was used to calculate a thematic map of water quality parameters (i.e. chlorophyll-a) concentration, which subsequently were integrated into a GIS for management of water quality purposes. © 2005 Taylor & Francis

The hematological improvement of rainbow trout (Oncorhynchus mykiss) during dietary supplementation with vitamin C after exposure to zinc nano-particles

The aim of this study was to examine the adverse effects of zinc nanoparticles on hematological indices of trout and investigate the improvement of these indices after vitamin C treatments. This study assesses the protective role of vitamin C in fish exposed to ZnO NPs. Two concentrations of ZnO-NPs (40 and 80 mg L^-1) and two doses of vitamin C (400 and 800 mg per kg of feed) were used to treat 162 specimens of Oncorhynchus mykiss. No mortality was observed during the test. After 5 and 10 days of exposure, hematological data were analyzed according to routine clinical methods. Statistical analysis showed significant changes in WBCs and RBC on day 10 (p0.05), while significant increase in neutrophils and monocytes, and decrease in lymphocyte cells were recorded (p<0.05). ZnO-NPs stimulated the immune system of O. mykiss, but this effect did not have any lethality on this species at 40 and 80 mg L^-1. Vitamin C in different concentrations could help to prevent rainbow trout from the toxic effects of this nano metal

Low-energy Pion-nucleon Scattering

This paper contains the results of an analysis of recent low-energy pion-nucleon scattering experiments. Obtained are phase shifts, the pion-nucleon coupling constant and an estimate of the Sigma term.Comment: 30 pages, 11 figures, LaTe