Natural Tragedy Commendation Hasty Alert Using Tweet Events Over Distributed Processing Framework

An Event processing is the scheme of streams that related with information (data) about things that happen (events), and deriving a conclusion from tweet in real time. Twitter is a social network platform that consists of billions of users all over the world where people collaborate and Share information related to real world events. An important characteristic of Twitter is its real-time nature and also investigate the real-time interaction of events such as cyclones in Twitter and propose a framework to monitor tweets to detect a target event. These large scales tweet data processing are done by placing those tweet events in a distributed system. The server processes the tweet queue and executes the operations based on it. An devise classifier of tweets based on features such as the keywords in a tweet, the number of character, the number of words, and their context. The status update which almost pinpoints what is happening in and around an individual user and also tracks the user location. This small content with real world information when processed with some statistical tool may assist us to predict a live occurring event (e.g. cyclone) and regard each twitter user as a feeler and apply particle filtering, which are widely used for location estimation. Tweet in the message queue is done by Apache Kafka which is a distributed publish-subscribe messaging queue system. These frameworks will parallelize our computations over a cluster of machines

Fouling Mitigation Using Helixchanger Heat Exchangers

One of the major indeterminates in the design as well as operation of heat exchangers is the rate of fouling a select heat exchanger geometry would exhibit over the operation cycles. Gradual deterioration of heat exchanger performance due to the accumulation of fouling film on the heat transfer surface is often accounted for in the form of a fouling resistance, or commonly known as the fouling factor, while determining the heat transfer surface required for a specific heat duty. More often, the fouling mechanism responsible for the deterioration of heat exchanger performance is flow-velocity dependent. Maldistribution of flow, wakes and eddies caused by poor heat exchanger geometry can have detrimental effect on heat exchanger performance and reliability. Helixchanger heat exchangers have demonstrated significant improvements in the fouling behavior of heat exchangers in operation. In a Helixchanger heat exchanger, the quadrant shaped shellside baffle plates are arranged at an angle to the tube axis creating a helical flow pattern on the shellside. Uniform velocities and near plug flow conditions achieved in a Helixchanger heat exchanger, provide low fouling characteristics, offering longer heat exchanger run-lengths between scheduled cleaning of tube bundles. This article demonstrates the Helixchanger heat exchanger option in reducing the velocity-dependent fouling in heat exchangers

Microstructural Characterization and Mechanical Behavior of Copper Matrix Composites Reinforced by B4C and Sea Shell Powder

This paper investigates the microstructural and mechanical properties of copper metal matrix composites reinforced with B4C and crushed sea shell particles (fabricated using powder metallurgy). In powder form, copper is widely used in structural applications. Copper also possesses very good electrical and thermal conductivity, ductility, and corrosion resistance. B4C is the third-hardest-known material that also possesses excellent toughness and wear resistance. Sea shells are readily available along coastal areas. Therefore, an attempt has been made in this work to investigate the feasibility of its utilization in powder metallurgy. Two batches of samples were prepared. In the first batch, the percentage of boron carbide and copper powder were varied, and seashell powder was not included. In the second batch, the percentages of B4C, copper, and sea shell powder were varied in order to assess the change effected by the sea shell material. The sintered samples of both batches were subjected to microstructural characterization to ascertain the homogeneous distribution of the reinforcements. The microhardness and wear resistance of all of the fabricated samples were assessed. The results confirmed that the inclusion of 2% sea shell powder (by weight) with 10% boron carbide improved the wear resistance and hardness of the composite

Emissions of methane from coal fields, thermal power plants, and wetlands and their implications for atmospheric methane across the south Asian region

Atmospheric methane (CH4) is a potent climate change agent responsible for a fraction of global warming. The present study investigated the spatiotemporal variability of atmospheric-column-averaged CH4 (XCH4) concentrations using data from the Greenhouse gases Observing SATellite (GOSAT) and the TROPOspheric Monitoring Instrument on board the Sentinel-5 Precursor (S5P/TROPOMI) from 2009 to 2022 over the south Asian region. During the study period, the long-term trends in XCH4 increased from 1700 to 1950 ppb, with an annual growth rate of 8.76 ppb yr−1. Among all natural and anthropogenic sources of CH4, the rate of increase in XCH4 was higher over the coal site at about 10.15 ± 0.55 ppb yr−1 (Paschim Bardhaman) followed by Mundra Ultra Mega Power Project at about 9.72 ± 0.41 ppb yr−1. Most of the wetlands exhibit an annual trend of XCH4 of more than 9.50 ppb yr−1, with a minimum rate of 8.72 ± 0.3 ppb yr−1 over Wular Lake. The WetCHARTs-based emissions of CH4 from the wetlands were minimal during the winter and pre-monsoon seasons. Maximum CH4 emissions were reported during the monsoon, with a maximum value of 23.62 ± 3.66 mg m−2 per month over the Sundarbans Wetland. For the 15 Indian agroclimatic zones, significant high emissions of CH4 were observed over the Middle Gangetic Plain, Trans-Gangetic Plain, Upper Gangetic Plain, Eastern Coastal Plains, Lower Gangetic Plain, and East Gangetic Plain. Further, the bottom-up anthropogenic CH4 emissions data are mapped against the XCH4 concentrations, and a high correlation was found in the Indo-Gangetic Plain region, indicating the hotspots of anthropogenic CH4.</p

Beyond factor analysis: Multidimensionality and the Parkinson’s Disease Sleep Scale-Revised

Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson’s disease (PD). The Parkinson’s Disease Sleep Scale (PDSS) and its variants (the Parkinson’s disease Sleep Scale-Revised; PDSS-R, and the Parkinson’s Disease Sleep Scale-2; PDSS-2) quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model) is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA) and REM sleep behaviour disorder (RBD) symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments