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As the digital world gets increasingly ingrained in our daily lives, cyberattacks—especially those involving malware—are growing more complex and common, which calls for developing innovative safeguards. Keylogger spyware, which combines keylogging and spyware functionalities, is one of the most insidious types of cyberattacks. This malicious software stealthily monitors and records user keystrokes, amassing sensitive data, such as passwords and confidential personal information, which can then be exploited. This research introduces a novel browser extension designed to effectively thwart keylogger spyware attacks. The extension is underpinned by a cutting-edge algorithm that meticulously analyzes input-related processes, promptly identifying and flagging any malicious activities. Upon detection, the extension empowers users with the immediate choice to terminate the suspicious process or validate its authenticity, thereby placing crucial real-time control in the hands of the end user. The methodology used guarantees the extension's mobility and adaptability across various platforms and devices. This paper extensively details the development of the browser extension, from its first conceptual design to its rigorous performance evaluation. The results show that the extension considerably strengthens end-user protection against cyber risks, resulting in a safer web browsing experience. The research substantiates the extension's efficacy and significant potential in reinforcing online security standards, demonstrating its ability to make web surfing safer through extensive analysis and testing. 

Brown carbon (BrC) plays an important role in global radiative budget but there have been few studies on BrC in Arctic despite rapid warming and increasing wildfires in this region. Here we investigate the optical properties of BrC from boreal fires in Alaska summer, with two sets of measurements from PILS-LWCC-TOC (Particle-Into-Liquid-Sampler – Liquid-Waveguide Capillary flow-through optical Cell - Total-Organic-Carbon analyzer) and filter measurements. We show that during intense wildfires, the mass absorption coefficient at 365 nm (MAC365) from water soluble organic carbon (WSOC) remained stable at ∼1 m2 g−1. With all plumes sampled and derived transport time, we show a decrease of MAC365 with plume age, with a shorter photobleaching lifetime (∼11 h) at 365 nm compared to 405 nm (∼20 h). The total absorption by organic aerosols measured from filters at 365 nm is higher than the absorption by WSOC by a factor 2–3, suggesting a dominant role of insoluble organic carbon. Overall BrC dominates absorption in the near-ultraviolet and visible radiation during wildfire season in Alaska summer. 

Against the backdrop of the ever-evolving IT industry, this comparative study explores the differences among various project management methods, highlighting key distinctions between Agile and traditional approaches by evaluating the benefits of Agile and the drawbacks of not adopting agile methods. Agile practices have gained recognition for their adaptability and efficiency, in addressing dynamic industry demands. Our multifaceted approach, which examines the pros and cons of Agile methodologies across various industries employs different machine learning algorithms—logistic regression, linear regression, and decision tree regressor. The study quantitatively measures Agile’s impact compared to other methodologies using prediction probabilities, classifications, confusion metrics, R-squared, and Mean Squared Error (MSE) for performance analysis. Results highlight that linear regression outperforms other models with 71% accuracy and 82% precision. These findings offer valuable insights into understanding Agile’s impact on IT industries, encouraging further exploration and refinements to make informed decisions on project management strategies and fostering future research to enhance IT project success rates. 

Numerous structures conducive to magnetic reconnection are frequently observed in the turbulent regions at quasi-parallel shocks. In this work, we use a particle-in-cell simulation to study 3D magnetic reconnection in shock turbulence. We identify and characterize magnetic null points, and focus on reconnection along the separator between them. We identify a reconnection region with strong parallel current, a finite parallel potential, and counterrotating electron flows. Electrons are shown to be accelerated by the parallel electric field before being scattered at the null.

 

We perform a 2.5-dimensional particle-in-cell simulation of a quasi-parallel shock, using parameters for the Earth’s bow shock, to examine electron acceleration and heating due to magnetic reconnection. The shock transition region evolves from the ion-coupled reconnection dominant stage to the electron-only reconnection dominant stage, as time elapses. The electron temperature enhances locally in each reconnection site, and ion-scale magnetic islands generated by ion-coupled reconnection show the most significant enhancement of the electron temperature. The electron energy spectrum shows a power law, with a power-law index around 6. We perform electron trajectory tracing to understand how they are energized. Some electrons interact with multiple electron-only reconnection sties, and Fermi acceleration occurs during multiple reflections. Electrons trapped in ion-scale magnetic islands can be accelerated in another mechanism. Islands move in the shock transition region, and electrons can obtain larger energy from the in-plane electric field than the electric potential in those islands. These newly found energization mechanisms in magnetic islands in the shock can accelerate electrons to energies larger than the achievable energies by the conventional energization due to the parallel electric field and shock drift acceleration. This study based on the selected particle analysis indicates that the maximum energy in the nonthermal electrons is achieved through acceleration in ion-scale islands, and electron-only reconnection accounts for no more than half of the maximum energy, as the lifetime of sub-ion-scale islands produced by electron-only reconnection is several times shorter than that of ion-scale islands.

 

As the importance of non-tailpipe particles (NTP) over tailpipe emissions from urban traffic has been increasing, there is a need to evaluate NTP contributions to ambient particulate matter (PM) using representative source profiles. The Brake and Tire Wear Study conducted in Los Angeles, California in the winter of 2020 collected 64 PM2.5 and 64 PM10 samples from 32 pairs of downwind-upwind measurements at two near-road locations (I-5 in Anaheim and I-710 in Long Beach). These samples were characterized for inorganic and organic markers and, along with locally-developed brake wear, tire wear, and road dust source profiles, subject to source apportionment using the effective-variance chemical mass balance (EV-CMB) model. Model results highlighted the dominance of resuspended dust in both PM2.5 (23–33%) and PM10 (32–53%). Brake and tire wear contributed more to PM2.5 than tailpipe exhausts (diesel + gasoline) for I-5 (29–30% vs. 19–21%) while they were comparable for I-710 (15–17% vs. 15–19%). For PM10, the brake and tire wear contributions were 2–3 times the exhaust contributions. Different fleet compositions on and near I-5 and I-710 appeared to influence the relative importance of NTP and exhaust sources. The downwind-upwind differences in source contributions were often insignificant, consistent with small and/or nearly equal impacts of adjacent highway traffic emissions on the downwind and upwind sites. The utility of sole markers, such as barium and zinc, to predict brake and tire wear abundances in ambient PM is evaluated.