Semantic-Based Classification of Toxic Comments Using Ensemble Learning

A social media is rapidly expanding, and its anonymity feature completely supports free speech. Hate speech directed at anyone or any group because of their ethnicity, clan, religion, national or cultural their heritage, sex, disability, gender orientation, or other characteristics is a violation of their authority. Seriously encourages violence or hate crimes and causes social unrest by undermining peace, trustworthiness, and human rights, among other things. Identifying toxic remarks in social media conversation is a critical but difficult job. There are several difficulties in detecting toxic text remarks using a suitable and particular social media dataset and its high-performance, selected classifier. People nowadays share messages not only in person, but also in online settings such as social networking sites and online groups. As a result, all social media sites and apps, as well as all current communities in the digital world, require an identification and prevention system. Finding toxic social media remarks has proven critical for content screening. The identifying blocker in such a system would need to notice any bad online behavior and alert the prophylactic blocker to take appropriate action. The purpose of this research was to assess each text and find various kinds of toxicities such as profanity, threats, name-calling, and identity-based hatred. Jigsaw's designed Wikipedia remark collection is used for this

Crystal Structure of Escherichia coli CusC, the Outer Membrane Component of a Heavy Metal Efflux Pump

Background: While copper has essential functions as an enzymatic co-factor, excess copper ions are toxic for cells, necessitating mechanisms for regulating its levels. The cusCBFA operon of E. coli encodes a four-component efflux pump dedicated to the extrusion of Cu(I) and Ag(I) ions. Methodology/Principal Findings: We have solved the X-ray crystal structure of CusC, the outer membrane component of the Cus heavy metal efflux pump, to 2.3 A ˚ resolution. The structure has the largest extracellular opening of any outer membrane factor (OMF) protein and suggests, for the first time, the presence of a tri-acylated N-terminal lipid anchor. Conclusions/Significance: The CusC protein does not have any obvious features that would make it specific for metal ions, suggesting that the narrow substrate specificity of the pump is provided by other components of the pump, most likely by the inner membrane component CusA

Technology as a disruptive agent: Intergenerational perspectives

YesThis study explores how British South Asian parents perceive their children’s technology consumption through their collectivist lenses and interdependent values. The findings for this qualitative study indicate that second and third generation South Asian parents acknowledge the benefits of children’s technology use; but largely perceive technology as a disruptive agent, whereby children are becoming isolated and increasingly independent within the household. The analysis aims to understand how parents view their children’s relationship with others as a result of technology consumption. Accordingly, this paper proposes an extension of the Construal of self conceptualisation and contributes a Techno-construal matrix that establishes a dyadic connection between technology consumption and cultural values. Overall, the study reveals that children display less inter-reliance and conformance typically associated with collectivist cultures, resulting from their technology use. Consequently, parents interpret their children’s shift from interdependence to more independence as a disruptive and unsettling phenomenon within the household

Design and Implementation of a Power Conditioning Unit for Charging a Laptop using PV Cell Array

ABSTRACT: In the future, more and more pressure will be given on renewable smart applications. One type of renewable energy is the solar energy. Many applications are covered with solar cell or module as the energy source.A Power Conditioning Unit (PCU) is designed for the photovoltaic (PV) cell array, which are a highly promising alternative for non-renewable energy generation due to their modularity and cleanness to make it compatible for charging a laptop. The Power Conditioning Unit comprises mainly of a DC to DC Boost Converter and a Microcontroller. The output from the PV cell array varies widely, whereas modern laptops require 18 V to 20 V. The maximum power required is either 90 W or 100 W. A boost converter is used to step up the output voltage of the PV cell Array whose voltage regulation is achieved using the Pulse Width Modulation. This paper uses ATmega8 Microcontroller, with an inbuilt ADC and PWM generator for PWM generation and PV Cell Switching. A MOSFET is switched using this PWM signal to regulate the output voltage

Semantic-Based Classification of Toxic Comments Using Ensemble Learning

A social media is rapidly expanding, and its anonymity feature completely supports free speech. Hate speech directed at anyone or any group because of their ethnicity, clan, religion, national or cultural their heritage, sex, disability, gender orientation, or other characteristics is a violation of their authority. Seriously encourages violence or hate crimes and causes social unrest by undermining peace, trustworthiness, and human rights, among other things. Identifying toxic remarks in social media conversation is a critical but difficult job. There are several difficulties in detecting toxic text remarks using a suitable and particular social media dataset and its high-performance, selected classifier. People nowadays share messages not only in person, but also in online settings such as social networking sites and online groups. As a result, all social media sites and apps, as well as all current communities in the digital world, require an identification and prevention system. Finding toxic social media remarks has proven critical for content screening. The identifying blocker in such a system would need to notice any bad online behavior and alert the prophylactic blocker to take appropriate action. The purpose of this research was to assess each text and find various kinds of toxicities such as profanity, threats, name-calling, and identity-based hatred. Jigsaw's designed Wikipedia remark collection is used for this

Association Between Atrial Fibrillation and Occupational Exposure in Firefighters Based on Self-Reported Survey Data

Background Exposure to inhaled smoke, pollutants, volatile organic compounds, and polycyclic aromatic hydrocarbons in the firefighting environment has been associated with detrimental respiratory and cardiovascular effects, making firefighters a unique population with both personal and occupational risk factors for cardiovascular disease. Some of these exposures are also associated with development of atrial fibrillation. We aimed to study the association of atrial fibrillation and occupational exposure in firefighters. Methods and Results A cross-sectional survey was conducted between October 2018 and December 2019. Data were gathered electronically and stored in a secure REDCap database through Louisiana State University Health Shreveport. Firefighters who were members of at least 1 of 5 preselected professional organizations were surveyed via electronic links distributed by the organizations. The survey queried the number of fires fought per year as a measure of occupational exposure, as well as self-reported cardiovascular disease. A total of 10 860 active firefighters completed the survey, of whom 93.5% were men and 95.5% were aged ≤60 years. Firefighters who fought a higher number of fires per year had a significantly higher prevalence of atrial fibrillation (0-5 fires per year 2%, 6-10 fires per year 2.3%, 11-20 fires per year 2.7%, 21-30 fires per year 3%, 31 or more fires per year 4.5%; \u3c0.001). Multivariable logistic regression showed that a higher number of fires fought per year was associated with an increased risk of atrial fibrillation (odds ratio 1.14 [95% CI, 1.04-1.25]; =0.006). Conclusions Firefighters may have an increased risk of atrial fibrillation associated with the number of fires they fight per year. Further clinical and translational studies are needed to explore causation and mechanisms