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Synthesis of bimetallic electrocatalysts for CO₂ reduction using atomic layer deposition results in changes in chemical state and product selectivity. 

Abstract. A portion of Alaska's Fairbanks North Star Borough was designated as nonattainment for the 2006 24 h fine particulate matter 2.5 µm or less in diameter (PM2.5) National Ambient Air Quality Standards (NAAQS) in 2009. PM2.5 NAAQS exceedances in Fairbanks mainly occur during dark and cold winters, when temperature inversions form and trap high emissions at the surface. Sulfate (SO42-), often the second-largest contributor to PM2.5 mass during these wintertime PM episodes, is underpredicted by atmospheric chemical transport models (CTMs). Most CTMs account for primary SO42- and secondary SO42- formed via gas-phase oxidation of sulfur dioxide (SO2) and in-cloud aqueous oxidation of dissolved S(IV). Dissolution and reaction of SO2 in aqueous aerosols are generally not included in CTMs but can be represented as heterogeneous reactive uptake and may help better represent the high SO42- concentrations observed during Fairbanks winters. In addition, hydroxymethanesulfonate (HMS), a particulate sulfur species sometimes misidentified as SO42-, is known to form during Fairbanks winters. Heterogeneous formation of SO42- and HMS in aerosol liquid water (ALW) was implemented in the Community Multiscale Air Quality (CMAQ) modeling system. CMAQ simulations were performed for wintertime PM episodes in Fairbanks (2008) as well as over the Northern Hemisphere and Contiguous United States (CONUS) for 2015–2016. The added heterogeneous sulfur chemistry reduced model mean sulfate bias by ∼ 0.6 µg m−3 during a cold winter PM episode in Fairbanks, AK. Improvements in model performance are also seen in Beijing during wintertime haze events (reducing model mean sulfate bias by ∼ 2.9 µg S m−3). This additional sulfur chemistry also improves modeled summertime SO42- bias in the southeastern US, with implications for future modeling of biogenic organosulfates. 

In cloud-native environments, containers are often deployed within lightweight virtual machines (VMs) to ensure strong security isolation and privacy protection. With the growing demand for customized cloud services, third-party vendors are turning to infrastructure-as-a-service (IaaS) cloud providers to build their own cloud-native platforms, necessitating the need to run a VM or a guest that hosts containers inside another VM instance leased from an IaaS cloud. State-of-the-art nested virtualization in the x86 architecture relies heavily on the host hypervisor to expose hardware virtualization support to the guest hypervisor, not only complicating cloud management but also raising concerns about an increased attack surface at the host hypervisor. This paper presents the design and implementation of PVM, a high-performance guest hypervisor for KVM that is transparent to the host hypervisor and assumes no hardware virtualization support. PVM leverages two key designs: 1) a minimal shared memory region between the guest and guest hypervisor to facilitate state transition between different privilege levels and 2) an efficient shadow page table design to reduce the cost of memory virtualization. PVM has been adopted by a major IaaS cloud provider for hosting tens of thousands of secure containers on a daily basis. Our experiments demonstrate that PVM significantly outperforms current nested virtualization in KVM for memory virtualization, particularly for concurrent workloads, while maintaining comparable performance in CPU and I/O virtualization. 

To date, it has remained challenging to achieve N-polar AlN, which is of great importance for high power, high frequency, and high temperature electronics, acoustic resonators and filters, ultraviolet (UV) optoelectronics, and integrated photonics. Here, we performed a detailed study of the molecular beam epitaxy and characterization of N-polar AlN on C-face 4H-SiC substrates. The N-polar AlN films grown under optimized conditions exhibit an atomically smooth surface and strong excitonic emission in the deep UV with luminescence efficiency exceeding 50% at room temperature. Detailed scanning transmission electron microscopy (STEM) studies suggest that most dislocations are terminated/annihilated within ∼200 nm AlN grown directly on the SiC substrate due to the relatively small (1%) lattice mismatch between AlN and SiC. The strain distribution of AlN is further analyzed by STEM and micro-Raman spectroscopy, and its impact on the temperature-dependent deep UV emission is elucidated. 

L-type voltage-gated calcium (Ca²⁺) channels (L-VGCC) dysfunction is implicated in several neurological and psychiatric diseases. While a popular therapeutic target, it is unknown whether molecular mechanisms leading to disrupted L-VGCC across neurodegenerative disorders are conserved. Importantly, L-VGCC integrate synaptic signals to facilitate a plethora of cellular mechanisms; however, mechanisms that regulate L-VGCC channel density and subcellular compartmentalization are understudied. Herein, we report that in disease models with overactive mammalian target of rapamycin complex 1 (mTORC1) signaling (or mTORopathies), deficits in dendritic L-VGCC activity are associated with increased expression of the RNA-binding protein (RBP) Parkinsonism-associated deglycase (DJ-1). DJ-1 binds the mRNA coding for the alpha and auxiliary Ca²⁺channel subunits Ca_V1.2 and α2δ2, and represses their mRNA translation, only in the disease states, specifically preclinical models of tuberous sclerosis complex (TSC) and Alzheimer’s disease (AD). In agreement, DJ-1-mediated repression of Ca_V1.2/α2δ2 protein synthesis in dendrites is exaggerated in mouse models of AD and TSC, resulting in deficits in dendritic L-VGCC calcium activity. Finding of DJ-1-regulated L-VGCC activity in dendrites in TSC and AD provides a unique signaling pathway that can be targeted in clinical mTORopathies.