Distribusi Perokok Berdasarkan Berbagai Latar Belakang Demografi (Menurut Data Susenas 2001 Dan 1995)

Smoking habit is a pleasure for a person and may be dangerous for the others. The main ingredient of cigarette, kretek and cigar is tobacco. Tobacco has been known to contain a lot of chemical substances including nicotin, alkaloids, safrol, ammonia and tar whichare harmful to health. This study was carried out to depict smokers among community in any characteristics of demographic background. The data of smoking habit among peoples of 15 years old or above were collected from the National Health Survey (Survey Kesehatan Nasional) and Household Health Survey (SKRT) 2001 and 1995. More than 12.000 respondents had been interviewed. The result showed that during the last five years the proportion of smokers was increasing in all age groups among male but decreasing among female. Smokers were most prevalence in low educated population and in rural areas. The prevalence was also found to be higher in Sumatera compared to those in Java or eastern part of Indonesia. It is suggested that serious measures should be taken against the campaign of tobacco company including strengtheninglaw enforcement and enhance punishment to the people or company violating the tobacco regulation

Improving route discovery in on-demand routing protocols using local topology information in MANETs

Most existing routing protocols proposed for MANETs use flooding as a broadcast technique for the propagation of network control packets; a particular example of this is the dissemination of route requests (RREQs), which facilitate route discovery. In flooding, each mobile node rebroadcasts received packets, which, in this manner, are propagated network-wide with considerable overhead. This paper improves on the performance of existing routing protocols by reducing the communication overhead incurred during the route discovery process by implementing a new broadcast algorithm called the adjusted probabilistic flooding on the Ad-Hoc on Demand Distance Vector (AODV) protocol. AODV [3] is a well-known and widely studied algorithm which has been shown over the past few years to maintain an overall lower routing overhead compared to traditional proactive schemes, even though it uses flooding to propagate RREQs. Our results, as presented in this paper, reveal that equipping AODV with fixed and adjusted probabilistic flooding, instead, helps reduce the overhead of the route discovery process whilst maintaining comparable performance levels in terms of saved rebroadcasts and reachability as achieved by conventional AODV\@. Moreover, the results indicate that the adjusted probabilistic technique results in better performance compared to the fixed one for both of these metrics

Identification of six potato virus Y isolates from Saudi Arabia

Six potato virus Y (PVY) were isolated from 20 potato plants (Solanum tuberosum sp. tuberosum L.) from the Riyadh region of Saudi Arabia showing leaf systemic symptoms (necrotic spots and mild mosaicism). 16 virus-infected plants gave positive indirect enzyme-linked immunosorbent assay (ELISA) results with PVY commercial antiserum. Electron microscopy revealed the presence of rod-shaped particles (300 × 17 nm). Sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) indicated the 34 kDa viral coat protein and agarose gel of the immunocapture reverse transcription-polymerase chain reaction (IC-RT-PCR) products indicated the 800 bp cp gene. The sequences were aligned together, narrowed to six (one PVY-N and five PVY-O isolates) and then aligned with all published worldwide PVY cp sequences. The highest similarity index among the six isolates was shown between PVY-saudi-O1 and PVY-saudi-O4 (99.9%), while the least involved PVY-saudi-N and PVY-saudi-O3 (99.1%). The phylogenetic analysis of the cp gene nucleotide sequence revealed a cluster of PVY-saudi-N and the Egyptian strain GU980964. The results indicate the need for more sensitive detection of the virus in the imported seeds or tubers from countries, especially in the Middle East like Egypt, to avoid high threat to the Saudi potato trade.Key words: Reverse transcription-polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assay (ELISA), sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE), coat protein (CP), sequence alignment, similarity index

Electrohydrodynamic (EHD) Refrigerant Pump

An electrohydrodynamic (EHD) pump increases refrigerant flow rate and the resulting pressure in a vapor compression based cooling system for permitting reduced compressor sizes and power demands. The EHD pump disposes electrodes in a liquid path of the refrigerant flow, and increases fluid flow and resulting pressure by an induced liquid flow between a pair of asymmetric electrodes. Voltage applied to these electrodes results in a conduction pumping mechanism associated with heterocharge layers in the vicinity of the electrodes based on disassociation of a neutral electrolyte species in the refrigerant fluid and recombination of the generated ions. The induced flow draws the liquid due to a net fluid flow toward one of the electrodes based on the asymmetry of the electrode pair. Electrodes are disposed on an inner surface of a refrigerant vessel, in communication with an annular liquid film that forms around the inner circumference in two-phase fluid systems

Constraints on stable equilibria with fluctuation-induced forces

We examine whether fluctuation-induced forces can lead to stable levitation. First, we analyze a collection of classical objects at finite temperature that contain fixed and mobile charges, and show that any arrangement in space is unstable to small perturbations in position. This extends Earnshaw's theorem for electrostatics by including thermal fluctuations of internal charges. Quantum fluctuations of the electromagnetic field are responsible for Casimir/van der Waals interactions. Neglecting permeabilities, we find that any equilibrium position of items subject to such forces is also unstable if the permittivities of all objects are higher or lower than that of the enveloping medium; the former being the generic case for ordinary materials in vacuum.Comment: 4 pages, 1 figur

Optimization of hot press forging parameters in direct recycling of aluminium chip (AA 6061)

This study introduces a new approach of direct recycling using the hot press forging process that eliminates the two intermediate processes of cold-compact and pre-heating. This method leads to low energy consumption without intervening the metallurgical processes. In this study, the optimum of machined chips from high speed milling is recycled by hot press forging. The mechanical properties and surface integrity of the different chips were investigated. The performance of recycled aluminium AA 6061 chips in the mechanical and physical properties were compared with the original aluminium billet. Response surface methodology (RSM) was used to develop mathematical model of the effects on pre-compaction cycle, holding time and suitable pressure significant to the process. It is hoped that, utilization of primary metal could be fully utilized by direct recycling technique (hot press forging) introduced in this study and at the same time developing a sustainable manufacturing process technology for future needs

On Neural Architectures for Astronomical Time-series Classification with Application to Variable Stars

Despite the utility of neural networks (NNs) for astronomical time-series classification, the proliferation of learning architectures applied to diverse datasets has thus far hampered a direct intercomparison of different approaches. Here we perform the first comprehensive study of variants of NN-based learning and inference for astronomical time-series, aiming to provide the community with an overview on relative performance and, hopefully, a set of best-in-class choices for practical implementations. In both supervised and self-supervised contexts, we study the effects of different time-series-compatible layer choices, namely the dilated temporal convolutional neural network (dTCNs), Long-Short Term Memory (LSTM) NNs, Gated Recurrent Units (GRUs) and temporal convolutional NNs (tCNNs). We also study the efficacy and performance of encoder-decoder (i.e., autoencoder) networks compared to direct classification networks, different pathways to include auxiliary (non-time-series) metadata, and different approaches to incorporate multi-passband data (i.e., multiple time-series per source). Performance---applied to a sample of 17,604 variable stars from the MACHO survey across 10 imbalanced classes---is measured in training convergence time, classification accuracy, reconstruction error, and generated latent variables. We find that networks with Recurrent NN (RNNs) generally outperform dTCNs and, in many scenarios, yield to similar accuracy as tCNNs. In learning time and memory requirements, convolution-based layers are more performant. We conclude by discussing the advantages and limitations of deep architectures for variable star classification, with a particular eye towards next-generation surveys such as LSST, WFIRST and ZTF2.Comment: Submitted to ApJ