Establishing hybrid deep learning models for regional daily rainfall time series forecasting in the United Kingdom

Accurate daily rainfall predictions are becoming increasingly important, particularly in the era of changing climate conditions. These predictions are essential for various sectors, including agriculture, water resource management, flood preparedness, and pollution monitoring. This study delves into the complex relationship between meteorological data, with a focus on the accurate forecasting of rainfall by identifying the impact of temperature variations on rainfall patterns in different regions of the United Kingdom (UK). The meteorological data was collected from the National Aeronautics and Space Administration (NASA) and covers daily observations from January 1, 1981, to July 31, 2023, in four distinct regions of the UK: England, Wales, Scotland, and Northern Ireland. The main objective of this research is to introduce hybrid deep learning models, namely Convolutional Neural Networks (CNN) with Long Short Term Memory (LSTM) and Recurrent Neural Networks (RNN) with Long Short Term Memory (LSTM), for predicting daily rainfall using time-series data from the four UK countries, specifically designed for daily rainfall forecasting of four regions in the UK. The models are fine-tuned using the hyperparameter optimisation method. Comprehensive performance evaluations, including Loss Function, Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE), are employed to compare the effectiveness of our proposed hybrid models with established baseline models, including LSTM, stacked LSTM, and Bidirectional LSTM. Additionally, a visual analysis of actual and predicted rainfall data is conducted to identify the most proficient forecasting model for each region. Results reveal that the proposed hybrid models consistently outperform other models in terms of both quantitative performance metrics and visual assessments across all four regions in the UK. This research contributes to improved rainfall forecasting methodologies, which are critical for sustainable agricultural practices and resource management

A study on the level of stress and the influence of socio-demographic factors on stress level among the working women in the state of Kerala

Women play vital roles in the process of decision making both in work place and family. Indian culture considers women as care takers of the family members. In contrary to the traditional notions, women are moving from home maker’s par name to working women. More number of women is entering into workforce that is very much challenging and innovative. Aforementioned state gives a double role to most of the women as working women and house wives without any interval. Here a study is undertaken on the level of stress of women who are in the dual standards of family and profession. The study tries to identify the stressful life faced by women in the society. The result indicates that financial position of the family, travelling time and mode of travelling affect the intensity of stress among the working women. It provides us an opportunity to give suggestions to women in facing and challenging critical situations of their lives effectively. Keywords: Stress, Working women, Socio-demographi

Electron and ion stagnation at the collision front between two laser produced plasmas

We report results from a combined optical interferometric and spectrally resolved imaging study on colliding laser produced aluminium plasmas. A Nomarski interferometer was used to probe the spatio-temporal distribution of electron densities at the collision front. Analysis of the resulting interferograms reveals the formation and evolution of a localized electron density feature with a well-defined profile reminiscent of a stagnation layer. Electron stagnation begins at a time delay of 10 ns after the peak of the plasma generating laser pulse. The peak electron density was found to exceed 10^19 cm^−3 and the layer remained well defined up to a time delay of ca 100 ns. Temporally and spectrally resolved optical imaging was also undertaken, to compare the Al^+ ion distribution with that of the 2D electron density profile. This revealed nascent stagnation of singly charged ions at a delay time of 20 ns. We attribute these results to the effects of space charge separation in the seed plasma plumes

Helium bubble formation in ultrafine and nanocrystalline tungsten under different extreme conditions

We have investigated the effects of helium ion irradiation energy and sample temperature on the performance of grain boundaries as helium sinks in ultrafine grained and nanocrystalline tungsten. Irradiations were performed at displacement and non-displacement energies and at temperatures above and below that required for vacancy migration. Microstructural investigations were performed using Transmission Electron Microscopy (TEM) combined with either in-situ or ex-situ ion irradiation. Under helium irradiation at an energy which does not cause atomic displacements in tungsten (70 eV), regardless of temperature and thus vacancy migration conditions, bubbles were uniformly distributed with no preferential bubble formation on grain boundaries. At energies that can cause displacements, bubbles were observed to be preferentially formed on the grain boundaries only at high temperatures where vacancy migration occurs. Under these conditions, the decoration of grain boundaries with large facetted bubbles occurred on nanocrystalline grains with dimensions less than 60 nm. We discuss the importance of vacancy supply and the formation and migration of radiation-induced defects on the performance of grain boundaries as helium sinks and the resulting irradiation tolerance of ultrafine grained and nanocrystalline tungsten to bubble formatio

A comprehensive review on bonding between monolithic ceramics and tooth structure with different adhesive agents.

Reliable bonding between the prepared tooth and monolithic ceramics can be achieved by various luting agents available on the market. The selection of luting agent and cementation technique plays an important role in the success of the restoration. With the advent of resin-based adhesive systems as luting agents, clinicians\u27 perspectives have changed to a more conservative approach. Recent systems, chemically adhere the crowns to the prepared tooth structure showing higher bond strength. To reach the aesthetic demands of the patients, all-ceramic restorations were considered over metal-ceramic crowns. Few all-ceramic crowns are brittle, the strength is dependent on the chemical structure and method of fabrication. While some all-ceramic restorations gain strength after cementation. Thus, the choice of luting agent used in cementing all-ceramic crowns is crucial. Even though many luting agents are being introduced no single luting agent fulfilled all the requirements. Among them, adhesive cements showed greater bond strength and enhanced the retention of minimal preparation, which are less retentive. Traditional non-adhesive agents can be used in retentive preparations that bond through mechanical means rather than the chemical bond seen in newer adhesive cements. Also, surface treatments of zirconia showed greater bond strengths irrespective of the luting agent being used. These include air abrasion, acid etching, applying silane couplers, and primers that increase the surface area for adhesion. The use of all-ceramic restorations, the need for surface treatments, types of surface treatments, adhesion and adhesive agents, and evidence from current in vitro research on monolithic ceramics and tooth adhesion were all discussed in this review

The Wolf of SUTD (TWOS): A dataset of malicious insider threat behavior based on a gamified competition

In this paper we present open research questions and options for data analysis of our previously designed dataset called TWOS: The Wolf of SUTD. In specified research questions, we illustrate the potential use of the TWOS dataset in multiple areas of cyber security, which does not limit only to malicious insider threat detection but are also related to authorship verification and identification, continuous authentication, and sentiment analysis. For the purpose of investigating the research questions, we present several state-of-the-art features applicable to collected data sources, and thus we provide researchers with a guidance how to start with data analysis. The TWOS dataset was collected during a gamified competition that was devised in order to obtain realistic instances of malicious insider threat. The competition simulated user interactions in/among competing companies, where two types of behaviors (normal and malicious) were incentivized. For the case of malicious behavior,we designed two types of malicious periods that was intended to capture the behavior of two types of insiders – masqueraders and traitors. The game involved the participation of 6 teams consisting of 4 students who competed with each other for a period of 5 days. Their activities were monitored by several data collection agents and producing data for mouse, keyboard, process and file-system monitor, network traffic, emails, and login/logout data sources. In total, we obtained 320 hours of active participation that included 18 hours of masquerader data and at least two instances of traitor data. In addition to expected malicious behaviors, students explored various defensive and offensive strategies such as denial of service attacks and obfuscation techniques, in an effort to get ahead in the competition. The TWOS dataset was made publicly accessible for further research purposes. In this paper we present the TWOS dataset that contains realistic instances of insider threats based on a gamified competition. The competition simulated user interactions in/among competing companies, where two types of behaviors (normal and malicious) were incentivized. For the case of malicious behavior, we designed sessions for two types of insider threats (masqueraders and traitors). The game involved the participation of 6 teams consisting of 4 students who competed with each other for a period of 5 days, while their activities were monitored considering several heterogeneous sources (mouse, keyboard, process and file-system monitor, network traffic, emails and login/logout). In total, we obtained 320 hours of active participation that included 18 hours of masquerader data and at least two instances of traitor data. In addition to expected malicious behaviors, students explored various defensive and offensive strategies such as denial of service attacks and obfuscation techniques, in an effort to get ahead in the competition. Furthermore, we illustrate the potential use of the TWOS dataset in multiple areas of cyber security, which does not limit to malicious insider threat detection, but also areas such as authorship verification and identification, continuous authentication, and sentiment analysis. We also present several state-of-the-art features that can be extracted from different data sources in order to guide researchers in the analysis of the dataset. The TWOS dataset is publicly accessible for further research purposes. © 2018, Innovative Information Science and Technology Research Group. All rights reserved

A Spectroscopic study of laser-induced Tin-Lead plasma: transition probabilities for spectral lines of Sn I

In this paper, we present transition probabilities for 97 spectral lines of Sn I, corresponding to transitions n(n = 6,7,8)s → 5p2, n(n = 5,6,7)d → 5p2, 5p3 → 5p2, n(n = 7)p → 6s, determined by measuring the intensities of the emission lines of a Laser-induced breakdown (emission) spectrometry (LIBS). The optical emission spectroscopy from a laser-induced plasma generated by a 10 640 Å radiation, with an irradiance of 1.4 × 1010 Wcm− 2 on an Sn–Pb alloy (an Sn content of approximately 20%), in vacuum, was recorded at 0.8 µs, and analysed between 1900 and 7000 Å. The population-level distribution and corresponding temperature were obtained using Boltzmann plots. The electron density of the plasma was determined using well-known Stark broadening parameters of spectral lines. The plasma under study had an electron temperature of 13,200 K and an electron number density of 2 × 1016 cm− 3. The experimental relative transition probabilities were put on an absolute scale using the branching ratio method to calculate Sn I multiplet transition probabilities from available radiative lifetime data of their upper states and plotting the Sn I emission spectrum lines on a Boltzmann plot assuming local thermodynamic equilibrium (LTE) to be valid and following Boltzmann's law. The LTE conditions and plasma homogeneity have been checked. Special attention was paid to the possible self-absorption of the different transitions. The experimental results obtained have been compared with the experimental values given by other authors

Emission features of femtosecond laser ablated carbon plasma in ambient helium

We investigated the optical emission features of plasmas produced by 800 nm, 40 fs ultrafast laser pulses on a carbon target in the presence of ambient helium or nitrogen gases at varied pressures. Fast photography employing intensified charge coupled device, optical emission spectroscopy, and temporally spatially resolved optical time of flight emission spectroscopy were used as diagnostic tools. Spatio-temporal contours of excited neutral, ionic, as well as molecular carbon species in the plume were obtained using time of flight emission spectroscopy. These contours provided detailed account of molecular species evolution and expansion dynamics and indicate that three-body recombination is a major mechanism for carbon dimers generation in ultrafast laser ablation plumes in the presence of ambient gas. A systematic comparison of the emission features from ns and fs laser ablation carbon plumes as well as their expansion in ambient helium is also given. C 2 vibrational temperatures were estimated during carbon plasma expansion with lower values in ambient helium compared to nitrogen and showed decreasing values with respect to space and ambient gas pressure. V C 2013 AIP Publishing LLC. [http://d