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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. 

Storm surge flooding caused by tropical cyclones is a devastating threat to coastal regions, and this threat is growing due to sea-level rise (SLR). Therefore, accurate and rapid projection of the storm surge hazard is critical for coastal communities. This study focuses on developing a new framework that can rapidly predict storm surges under SLR scenarios for any random synthetic storms of interest and assign a probability to its likelihood. The framework leverages the Joint Probability Method with Response Surfaces (JPM-RS) for probabilistic hazard characterization, a storm surge machine learning model, and a SLR model. The JPM probabilities are based on historical tropical cyclone track observations. The storm surge machine learning model was trained based on high-fidelity storm surge simulations provided by the U.S. Army Corps of Engineers (USACE). The SLR was considered by adding the product of the normalized nonlinearity, arising from surge-SLR interaction, and the sea-level change from 1992 to the target year, where nonlinearities are based on high-fidelity storm surge simulations and subsequent analysis by USACE. In this study, this framework was applied to the Chesapeake Bay region of the U.S. and used to estimate the SLR-adjusted probabilistic tropical cyclone flood hazard in two areas: One is an urban Virginia site, and the other is a rural Maryland site. This new framework has the potential to aid in reducing future coastal storm risks in coastal communities by providing robust and rapid hazard assessment that accounts for future sea-level rise. 

Understanding the interplay between the inherent disorder and the correlated fluctuating-spin ground state is a key element in the search for quantum spin liquids. H₃LiIr₂O₆is considered to be a spin liquid that is proximate to the Kitaev-limit quantum spin liquid. Its ground state shows no magnetic order or spin freezing as expected for the spin liquid state. However, hydrogen zero-point motion and stacking faults are known to be present. The resulting bond disorder has been invoked to explain the existence of unexpected low-energy spin excitations, although data interpretation remains challenging. Here, we use resonant X-ray spectroscopies to map the collective excitations in H₃LiIr₂O₆and characterize its magnetic state. In the low-temperature correlated state, we reveal a broad bandwidth of magnetic excitations. The central energy and the high-energy tail of the continuum are consistent with expectations for dominant ferromagnetic Kitaev interactions between dynamically fluctuating spins. Furthermore, the absence of a momentum dependence to these excitations are consistent with disorder-induced broken translational invariance. Our low-energy data and the energy and width of the crystal field excitations support an interpretation of H₃LiIr₂O₆as a disordered topological spin liquid in close proximity to bond-disordered versions of the Kitaev quantum spin liquid.

 

We began this project with three goals: (1) engage families in engineering activities, (2) increase the awareness of kids and caregivers as to what engineering is, and (3) increase children’ interest in engineering. We focused on caregivers and home environments because of the important role that at-home experiences with STEM play in triggering interest for many individuals who enter STEM professions. We created and distributed four different kits to families interested in engaging in STEM activities at home. Each kit included a challenge around engineering-related content (e.g., circuits, construction) and contained activity instructions (child) and a facilitation guide (caregivers). However, few instructions were given to caregivers about the expectations of their role while engaging with their children. This paper reports on the findings from family engagement in the Watercolor Bot kit. We sought to explore the roles enacted and behaviors utilized by caregivers as they supported their children during the activity. Our findings add to the conversation about how to define and conceptualize caregiver roles and how the home context/setting influences the types of supports caregivers provide. In contrast to emerging work on caregiver support, we argue that it may be more fruitful to think about the types of support (physical, verbal, content, and managerial) offered rather than defining specific roles (e.g., collaborator, project manager, etc.). We provide implications for designing kits and activities to include specific support for caregivers beyond simply providing project-specific instructions that address caregivers’ needs. 

In order to explore the consequences of spin–orbit coupling on spin–phonon interactions in a set of chemically similar mixed metal oxides, we measured the infrared vibrational properties of Co4B2O9 (B = Nb, Ta) as a function of temperature and compared our findings with lattice dynamics calculations and several different models of spin–phonon coupling. Frequency vs temperature trends for the Co2+ shearing mode near 150 cm−1 reveal significant shifts across the magnetic ordering temperature that are especially large in relative terms. Bringing these results together and accounting for noncollinearity, we obtain spin–phonon coupling constants of −3.4 and −4.3 cm−1 for Co4Nb2O9 and the Ta analog, respectively. Analysis reveals that these coupling constants are derived from interlayer (rather than intralayer) exchange interactions and that the interlayer interactions contain competing antiferromagnetic and ferromagnetic contributions. At the same time, beyond-Heisenberg terms are minimized due to fortuitous symmetry considerations, different from most other 4d- and 5d-containing oxides. Comparison with other contemporary oxides shows that spin–phonon coupling in this family of materials is among the strongest ever reported, suggesting an origin for magnetoelectric coupling. 

Graphene layers placed on SrTiO3 single-crystal substrates, i.e., templates for remote epitaxy of functional oxide membranes, were investigated using temperature-dependent confocal Raman spectroscopy. This approach successfully resolved distinct Raman modes of graphene that are often untraceable in conventional measurements with non-confocal optics due to the strong Raman scattering background of SrTiO3. Information on defects and strain states was obtained for a few graphene/SrTiO3 samples that were synthesized by different techniques. This confocal Raman spectroscopic approach can shed light on the investigation of not only this graphene/SrTiO3 system but also various two-dimensional layered materials whose Raman modes interfere with their substrates.