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In the context of the rising interest in code language models (code LMs) and vulnerability detection, we study the effectiveness of code LMs for detecting vulnerabilities. Our analysis reveals significant shortcomings in existing vulnerability datasets, including poor data quality, low label accuracy, and high duplication rates, leading to unreliable model performance in realistic vulnerability detection scenarios. Additionally, the evaluation methods used with these datasets are not representative of real-world vulnerability detection. To address these challenges, we introduce PRIMEVUL, a new dataset for training and evaluating code LMs for vulnerability detection. PRIMEVUL incorporates a novel set of data labeling techniques that achieve comparable label accuracy to humanverified benchmarks while significantly expanding the dataset. It also implements a rigorous data de-duplication and chronological data splitting strategy to mitigate data leakage issues, alongside introducing more realistic evaluation metrics and settings. This comprehensive approach aims to provide a more accurate assessment of code LMs’ performance in real-world conditions. Evaluating code LMs on PRIMEVUL reveals that existing benchmarks significantly overestimate the performance of these models. For instance, a state-of-the-art 7B model scored 68.26% F1 on BigVul but only 3.09% F1 on PRIMEVUL. Attempts to improve performance through advanced training techniques and larger models like GPT-3.5 and GPT-4 were unsuccessful, with results akin to random guessing in the most stringent settings. These findings underscore the considerable gap between current capabilities and the practical requirements for deploying code LMs in security roles, highlighting the need for more innovative research in this domain. 

Mass spectrometry is a powerful analytical technique used at every stage of the pharmaceutical research process. A specialized subset of this technique, mass spectrometry imaging (MSI) has emerged as an important technique for determining the spatial distribution of drugs in biological samples. Despite the importance of MSI, its quantitative capabilities are still limited due to the complexity of biological samples and the lack of separation prior to analysis. This makes the simultaneous quantification and visualization of analytes challenging. Several techniques have been developed to address this challenge and enable quantitative MSI. One of these techniques is the mimetic tissue model, which involves the incorporation of an analyte of interest into tissue homogenates at several concentrations. A calibration curve that accounts for signal suppression by the complex biological matrix is then created by measuring the signal of the analyte in the series of tissue homogenates. Herein, we use the mimetic tissue model on a triple quadrupole mass spectrometer (QqQ) in multiple reaction monitoring (MRM) mode to demonstrate the quantitative abilities of nanospray desorption electrospray ionization (nano-DESI) and compare these results with those obtained using atmospheric pressure matrix-assisted laser desorption/ionization (AP-MALDI). For the tested compounds, our findings indicate that nano-DESI achieves lower standard deviations than AP-MALDI which contributes to nano-DESI also achieving lower limits of detection (LOD) for the analytes studied. Additionally, we discuss the limitations of the mimetic tissue model in the quantification of certain analytes and the challenges involved with the implementation of the model. 

Polyethylene oxide (PEO)-based solid composite electrolytes (SCEs), with inorganic fillers, are studied extensively due to their effective balance between mechanical and electrochemical properties. The correlation between the composition of SCEs and their electrochemical behavior has been studied extensively, primarily focusing on the type of polymer matrix with a bias towards high lithium (Li) salt. In this study, we examine the changes in the properties of SCEs at two low EO : Li ratios, 43:1 and 18:1, in the PEO-LiTFSI matrix (with and without 10 wt% of 5 μm LLZTO) and evaluate their impact on Li stripping and plating reactions. Although higher salt concentration (18:1) results in substantially higher ionic conductivity (by approximately an order of magnitude), interestingly we observe that lower salt concentration (43:1) exhibits up to 3 times longer Li cycling life. Notably, electrolytes with low salt concentration (43:1) are much stiffer, with compressive modulus more than twice as high as the 18:1 counterpart. Although the ionic conductivity of the electrolyte is often the most immediate concern in the electrolyte design process, these findings accentuate the equal importance of mechanical properties in order to ensure successful electrolyte performance throughout prolonged Li cycling. 

Abstract Snow and ice topography impact and are impacted by fluxes of mass, energy, and momentum in Arctic sea ice. We measured the topography on approximately a 0.5 km²drifting parcel of Arctic sea ice on 42 separate days from 18 October 2019 to 9 May 2020 via Terrestrial Laser Scanning (TLS). These data are aligned into an ice-fixed, lagrangian reference frame such that topographic changes (e.g., snow accumulation) can be observed for time periods of up to six months. Usingin-situmeasurements, we have validated the vertical accuracy of the alignment to ± 0.011 m. This data collection and processing workflow is the culmination of several prior measurement campaigns and may be generally applied for repeat TLS measurements on drifting sea ice. We present a description of the data, a software package written to process and align these data, and the philosophy of the data processing. These data can be used to investigate snow accumulation and redistribution, ice dynamics, surface roughness, and they can provide valuable context for co-located measurements. 

Abstract BackgroundPathogenicLeptospiraspecies are globally important zoonotic pathogens capable of infecting a wide range of host species. In marine mammals, reports ofLeptospirahave predominantly been in pinnipeds, with isolated reports of infections in cetaceans. Case presentationOn 28 June 2021, a 150.5 cm long female, short-beaked common dolphin (Delphinus delphis delphis) stranded alive on the coast of southern California and subsequently died. Gross necropsy revealed multifocal cortical pallor within the reniculi of the kidney, and lymphoplasmacytic tubulointerstitial nephritis was observed histologically. Immunohistochemistry confirmedLeptospirainfection, and PCR followed bylfb1gene amplicon sequencing suggested that the infecting organism wasL.kirschneri. LeptospiraDNA capture and enrichment allowed for whole-genome sequencing to be conducted. Phylogenetic analyses confirmed the causative agent was a previously undescribed, divergent lineage ofL.kirschneri. ConclusionsWe report the first detection of pathogenicLeptospirain a short-beaked common dolphin, and the first detection in any cetacean in the northeastern Pacific Ocean. Renal lesions were consistent with leptospirosis in other host species, including marine mammals, and were the most significant lesions detected overall, suggesting leptospirosis as the likely cause of death. We identified the cause of the infection asL.kirschneri, a species detected only once before in a marine mammal – a northern elephant seal (Mirounga angustirostris) of the northeastern Pacific. These findings raise questions about the mechanism of transmission, given the obligate marine lifestyle of cetaceans (in contrast to pinnipeds, which spend time on land) and the commonly accepted view thatLeptospiraare quickly killed by salt water. They also raise important questions regarding the source of infection, and whether it arose from transmission among marine mammals or from terrestrial-to-marine spillover. Moving forward, surveillance and sampling must be expanded to better understand the extent to whichLeptospirainfections occur in the marine ecosystem and possible epidemiological linkages between and among marine and terrestrial host species. GeneratingLeptospiragenomes from different host species will yield crucial information about possible transmission links, and our study highlights the power of new techniques such as DNA enrichment to illuminate the complex ecology of this important zoonotic pathogen.