Simulating a full-sky high resolution Galactic synchrotron spectral index map using neural networks

We present a model for the full-sky diffuse Galactic synchrotron spectral index with an appropriate level of spatial structure for a resolution of 56 arcmin (to match the resolution of the Haslam 408 MHz data). Observational data at 408 MHz and 23 GHz have been used to provide spectral indices at a resolution of 5 degrees. In this work we make use of convolutional neural networks to provide a realistic proxy for the higher resolution information, in place of the genuine structure. Our deep learning algorithm has been trained using 14.4 arcmin observational data from the 1.4 GHz Parkes radio continuum survey. We compare synchrotron emission maps constructed by extrapolating the Haslam data using various spectral index maps, of different angular resolution, with the Global Sky Model. We add these foreground maps to a total emission model for a 21 cm intensity mapping experiment, then attempt to remove the foregrounds. The different models all display different spectral or spatial behaviour and so each provide a useful and different tool to the community for testing component separation techniques. We find that for an experiment operating using a cosine aperture taper beam with a primary Full Width at Half Maximum between 1.1 and 1.6 degrees, and the principal component analysis technique of foreground removal, there is a discernible difference between synchrotron spectral index models with a resolution larger than 5 degrees but that no greater resolution than 5 degrees is required.Comment: 14 pages, 19 figures, Accepted by MNRA

Penerapan Konsep Fuzzy Dalam Variable-centered Intelligent Rule System (Studi Kasus: Pemilihan Jurusan Di Chinese University of Hongkong)

Variable-Centered Intelligent Rule System (VCIRS) is a system which is inspired by Rule-based System (RBS) and Ripple Down Rules (RDR). The system architecture is adapted from RBS, while from RDR this system obtained its advantages. The system organized Rule Base (RB) in a special structure so that easy knowledge building, powerful knowledge inferencing and evolutionally system performance refining can be obtained in the same time. In this paper, the architecture of VCIRS is used to build an expert system for helping students to choose a department at a university. The application of this expert system is able to handle fuzzy concepts (e.g., such as good, high or rather high) which is a prominent part of sentences in natural language. This system is able to cope with exact values, fuzzy (or inexact) values and combined reasoning, allowing fuzzy and normal terms to be freely mixed in the rules and facts. An application example in this paper is a RBS which is employed fuzzy logic and fuzzy number for inexact reasoning. It uses two inexact basic concepts, i.e., fuzziness and uncertainty. A case study presented here is the department admission at Chinese University of Hongkong, formed in a RB containing with fuzzy and normal terms. From experiments performed, there's the proper result obtained comparing with the result from Z-II system (i.e., a comprehensive expert system builder tool developed by Chinese University of Hongkong) which is this paper refers to. So that the conclusion is a fuzzy VCIRS proposed here, is working properly and producing the right and true results

Transovarial Transmission and Dengue Virus Serotypes in Aedes Aegypti in Kupang

Dengue is an endemic disease in almost all provinces in Indonesia, including NTT pro-vince and Kupang City. DHF prevention and control efforts need to be accompanied by understanding of the epidemiological and entomological aspects. This study proves the presence of transovarial transmission and serotypes of Dengue virus in Ae. aegypti in areas with different endemics in Kupang City. The study was conducted in endemic, sporadic and Dengue-free villages. Samples from each location were 30 head squash Ae. aegypti females for examination of Dengue virus by IHC methods and 10 Ae. aegypti females for serotypes check of Dengue virus with RTPCR. Data presented in tables and images then analyzed descriptively. This study finds that transovarial infection rates 9.2% with serotype Dengue virus-1. As many 97.5% of respondents have heard about Dengue by most cadres resources (24.5%) and health workers (24%). Transovarial infection is found in endemic, sporadic and free areas so that the Dengue vector control needs to be done in the three regions with different endemicity

Event by Event Analysis of High Multiplicity Events Produced in 158 A GeV/c 208 Pb- 208 Pb Collisions

An extensive analysis of individual high multiplicity events produced in 158 A GeV /c 208Pb- 208Pb collisions is carried by adopting different methods to examine the anomalous behavior of these rare events. A method of selecting the events with densely populated narrow regions or spikes out of a given sample of collision events is discussed.Employing this approach two events with large spikes in their eta- and phi- distributions are selected for further analysis. For the sake of comparison, another two events which do not exhibit such spikes are simultaneously analyzed. The findings suggest that the systematic studies of particle density fluctuations in one- and two-dimensional phase-spaces and comparison with those obtained from the studies of correlation free Monte Carlo events, would be useful for identifying the events with large dynamical fluctuations. Formation of clusters or jet like phenomena in multihadronic final states in individual events is also discussed and the experimental findings are compared with the independent particle emission hypothesis by carrying out Monte Carlo simulations

Pixel Entanglement: Experimental Realization of Optically Entangled D=3 and D=6 Qudits

We demonstrate a simple experimental method for creating entangled qudits. Using transverse-momentum and position entanglement of photons emitted in spontaneous parametric down-conversion, we show entanglement between discrete regions of space, i.e., pixels. We map each photon onto as many as six pixels, where each pixel represents one level of our qudit state. The method is easily generalizable to create even higher dimensional, entangled states. Thus, the realization of quantum information processing in arbitrarily high dimensions is possible, allowing for greatly increased information capacity

Effects of essential oil compounds on survival of Listeria monocytogenes and Escherichia coli O157:H7 in çiğ köfte

This study was undertaken to evaluate the effects of some essential oil compounds for the inactivation of Listeria monocytogenes and Escherichia coli O157:H7 in çiğ köfte. In experiment 1, a çiğ köfte batch was inoculated with high levels of E. coli O157:H7 or L. monocytogenes (7.00 log10 cfu/g) and the batches were divided into 6 groups. Each group was treated with 18 mL/kg of normal saline, cineole, limonene, carvone, linalool, or eugenol. Treatment with carvone, linalool, and eugenol resulted in a significant (P < 0.05) decrease in the numbers of both pathogens. In experiment 2, the çiğ köfte was inoculated with the same pathogens and each group was treated with 0 (control), 20, 22.5, and 25 mL/kg of eugenol. Increases in concentration did not cause a difference in pathogen reduction. The results showed that eugenol, carvone, and linalool can be used for the inactivation of E. coli O157:H7 and L. monocytogenes in çiğ köfte or similar foods

An Internet of Things based bed-egress alerting paradigm using wearable sensors in elderly care environment

The lack of healthcare staff and increasing proportions of elderly population is alarming. The traditional means to look after elderly has resulted in 255,000 reported falls (only within UK). This not only resulted in extensive aftercare needs and surgeries (summing up to £4.4 billion) but also in added suffering and increased mortality. In such circumstances, the technology can greatly assist by offering automated solutions for the problem at hand. The proposed work offers an Internet of things (IoT) based patient bed-exit monitoring system in clinical settings, capable of generating a timely response to alert the healthcare workers and elderly by analyzing the wireless data streams, acquired through wearable sensors. This work analyzes two different datasets obtained from divergent families of sensing technologies, i.e., smartphone-based accelerometer and radio frequency identification (RFID) based accelerometer. The findings of the proposed system show good efficacy in monitoring the bed-exit and discriminate other ambulating activities. Furthermore, the proposed work manages to keep the average end-to-end system delay (i.e., communications of sensed data to Data Sink (DS)/Control Center (CC) + machine-based feature extraction and class identification + feedback communications to a relevant healthcare worker/elderly) below 1 10 th of a second