Investigating the Implications of Virtual Machine Introspection for Digital Forensics

Researchers and practitioners in computer forensics currently must base their analysis on information that is either incomplete or produced by tools that may themselves be compromised as a result of the intrusion. Complicating these issues are the techniques employed by the investigators themselves. If the system is quiescent when examined, most of the information in memory has been lost. If the system is active, the kernel and programs used by the forensic investigators are likely to influence the results and as such are themselves suspect. Using virtual machines and a technique called virtual machine introspection can help overcome these limits, but it introduces its own research challenges. Recent developments in virtual machine introspection have led to the identification of four initial priority research areas in virtual machine introspection including virtual machine introspection tool development, applications of virtual machine introspection to non-quiescent virtual machines, virtual machine introspection covert operations, and virtual machine introspection detection

Characterization of Intracellular and Extracellular Saxitoxin Levels in Both Field and Cultured Alexandrium spp. Samples from Sequim Bay, Washington

Traditionally, harmful algal bloom studies have primarily focused on quantifying toxin levels contained within the phytoplankton cells of interest. In the case of paralytic shellfish poisoning toxins (PSTs), intracellular toxin levels and the effects of dietary consumption of toxic cells by planktivores have been well documented. However, little information is available regarding the levels of extracellular PSTs that may leak or be released into seawater from toxic cells during blooms. In order to fully evaluate the risks of harmful algal bloom toxins in the marine food web, it is necessary to understand all potential routes of exposure. In the present study, extracellular and intracellular PST levels were measured in field seawater samples (collected weekly from June to October 2004–2007) and in Alexandrium spp. culture samples isolated from Sequim Bay, Washington. Measurable levels of intra- and extra-cellular toxins were detected in both field and culture samples via receptor binding assay (RBA) and an enzyme-linked immunosorbent assay (ELISA). Characterization of the PST toxin profile in the Sequim Bay isolates by pre-column oxidation and HPLC-fluorescence detection revealed that gonyautoxin 1 and 4 made up 65 ± 9.7 % of the total PSTs present. Collectively, these data confirm that extracellular PSTs are present during blooms of Alexandrium spp. in the Sequim Bay region

The Feasibility, Tolerability, Safety, and Accuracy of Low-radiation Dynamic Computed Tomography Myocardial Perfusion Imaging With Regadenoson Compared With Single-photon Emission Computed Tomography

Objectives: Computed tomography (CT) myocardial perfusion imaging (CT-MPI) with hyperemia induced by regadenoson was evaluated for the detection of myocardial ischemia, safety, relative radiation exposure, and patient experience compared with single-photon emission computed tomography (SPECT) imaging. Materials and Methods: Twenty-four patients (66.5 y, 29% male) who had undergone clinically indicated SPECT imaging and provided written informed consent were included in this phase II, IRB-approved, and FDA-approved clinical trial. All patients underwent coronary CT angiography and CT-MPI with hyperemia induced by the intravenous administration of regadenoson (0.4 mg/5 mL). Patient experience and findings on CT-MPI images were compared to SPECT imaging. Results: Patient experience and safety were similar between CT-MPI and SPECT procedures and no serious adverse events due to the administration of regadenoson occurred. SPECT resulted in a higher number of mild adverse events than CT-MPI. Patient radiation exposure was similar during the combined coronary computed tomography angiography and CT-MPI (4.4 [2.7] mSv) and SPECT imaging (5.6 [1.7] mSv) (P-value 0.401) procedures. Using SPECT as the reference standard, CT-MPI analysis showed a sensitivity of 58.3% (95% confidence interval [CI]: 27.7-84.8), a specificity of 100% (95% CI: 73.5-100), and an accuracy of 79.1% (95% CI: 57.9-92.87). Low apparent sensitivity occurred when the SPECT defects were small and highly suspicious for artifacts. Conclusions: This study demonstrated that CT-MPI is safe, well tolerated, and can be performed with comparable radiation exposure to SPECT. CT-MPI has the benefit of providing both complete anatomic coronary evaluation and assessment of myocardial perfusion

Accuracy of an Artificial Intelligence Deep Learning Algorithm Implementing a Recurrent Neural Network With Long Short-term Memory for the Automated Detection of Calcified Plaques From Coronary Computed Tomography Angiography

Purpose: The purpose of this study was to evaluate the accuracy of a novel fully automated deep learning (DL) algorithm implementing a recurrent neural network (RNN) with long short-term memory (LSTM) for the detection of coronary artery calcium (CAC) from coronary computed tomography angiography (CCTA) data. Materials and Methods: Under an IRB waiver and in HIPAA compliance, a total of 194 patients who had undergone CCTA were retrospectively included. Two observers independently evaluated the image quality and recorded the presence of CAC in the right (RCA), the combination of left main and left anterior descending (LM-LAD), and left circumflex (LCx) coronary arteries. Noncontrast CACS scans were allowed to be used in cases of uncertainty. Heart and coronary artery centerline detection and labeling were automatically performed. Presence of CAC was assessed by a RNN-LSTM. The algorithm's overall and per-vessel sensitivity, specificity, and diagnostic accuracy were calculated. Results: CAC was absent in 84 and present in 110 patients. As regards CCTA, the median subjective image quality, signal-to-noise ratio, and contrast-to-noise ratio were 3.0, 13.0, and 11.4. A total of 565 vessels were evaluated. On a per-vessel basis, the algorithm achieved a sensitivity, specificity, and diagnostic accuracy of 93.1% (confidence interval [CI], 84.3%-96.7%), 82.76% (CI, 74.6%-89.4%), and 86.7% (CI, 76.8%-87.9%), respectively, for the RCA, 93.1% (CI, 86.4%-97.7%), 95.5% (CI, 88.77%-98.75%), and 94.2% (CI. 90.2%-94.6%), respectively, for the LM-LAD, and 89.9% (CI, 80.2%-95.8%), 90.0% (CI, 83.2%-94.7%), and 89.9% (CI, 85.0%-94.1%), respectively, for the LCx. The overall sensitivity, specificity, and diagnostic accuracy were 92.1% (CI, 92.1%-95.2%), 88.9% (CI. 84.9%-92.1%), and 90.3% (CI, 88.0%-90.0%), respectively. When accounting for image quality, the algorithm achieved a sensitivity, specificity, and diagnostic accuracy of 76.2%, 87.5%, and 82.2%, respectively, for poor-quality data sets and 93.3%, 89.2% and 90.9%, respectively, when data sets rated adequate or higher were combined. Conclusion: The proposed RNN-LSTM demonstrated high diagnostic accuracy for the detection of CAC from CCTA

Online preconcentration ICP-MS analysis of rare earth elements in seawater

The rare earth elements (REEs) with their systematically varying properties are powerful tracers of continental inputs, particle scavenging intensity and the oxidation state of seawater. However, their generally low (∼pmol/kg) concentrations in seawater and fractionation potential during chemical treatment makes them difficult to measure. Here we report a technique using an automated preconcentration system, which efficiently separates seawater matrix elements and elutes the preconcentrated sample directly into the spray chamber of an ICP-MS instrument. The commercially available “seaFAST” system (Elemental Scientific Inc.) makes use of a resin with ethylenediaminetriacetic acid and iminodiacetic acid functional groups to preconcentrate REEs and other metals while anions and alkali and alkaline earth cations are washed out. Repeated measurements of seawater from 2000 m water depth in the Southern Ocean allows the external precision (2σ) of the technique to be estimated at <23% for all REEs and <15% for most. Comparison of Nd concentrations with isotope dilution measurements for 69 samples demonstrates that the two techniques generally agree within 15%. Accuracy was found to be good for all REEs by using a five point standard addition analysis of one sample and comparing measurements of mine water reference materials diluted with a NaCl matrix with recommended values in the literature. This makes the online preconcentration ICP-MS technique advantageous for the minimal sample preparation required and the relatively small sample volume consumed (7 mL) thus enabling large data sets for the REEs in seawater to be rapidly acquired

Predicting flood insurance claims with hydrologic and socioeconomic demographics via machine learning: exploring the roles of topography, minority populations, and political dissimilarity

Current research on flooding risk often focuses on understanding hazards, de-emphasizing the complex pathways of exposure and vulnerability. We investigated the use of both hydrologic and social demographic data for flood exposure mapping with Random Forest (RF) regression and classification algorithms trained to predict both parcel- and tract-level flood insurance claims within New York State, US. Topographic characteristics best described flood claim frequency, but RF prediction skill was improved at both spatial scales when socioeconomic data was incorporated. Substantial improvements occurred at the tract-level when the percentage of minority residents, housing stock value and age, and the political dissimilarity index of voting precincts were used to predict insurance claims. Census tracts with higher numbers of claims and greater densities of low-lying tax parcels tended to have low proportions of minority residents, newer houses, and less political similarity to state level government. We compared this data-driven approach and a physically-based pluvial flood routing model for prediction of the spatial extents of flooding claims in two nearby catchments of differing land use. The floodplain we defined with physically based modeling agreed well with existing federal flood insurance rate maps, but underestimated the spatial extents of historical claim generating areas. In contrast, RF classification incorporating hydrologic and socioeconomic demographic data likely overestimated the flood-exposed areas. Our research indicates that quantitative incorporation of social data can improve flooding exposure estimates

Global Phylogeography with Mixed-Marker Analysis Reveals Male-Mediated Dispersal in the Endangered Scalloped Hammerhead Shark (Sphyrna lewini)

Background: The scalloped hammerhead shark, Sphyrna lewini, is a large endangered predator with a circumglobal distribution, observed in the open ocean but linked ontogenetically to coastal embayments for parturition and juvenile development. A previous survey of maternal (mtDNA) markers demonstrated strong genetic partitioning overall (global W ST = 0.749) and significant population separations across oceans and between discontinuous continental coastlines. Methodology/Principal Findings: We surveyed the same global range with increased sample coverage (N = 403) and 13 microsatellite loci to assess the male contribution to dispersal and population structure. Biparentally inherited microsatellites reveal low or absent genetic structure across ocean basins and global genetic differentiation (FST = 0.035) over an order of magnitude lower than the corresponding measures for maternal mtDNA lineages (W ST = 0.749). Nuclear allelic richness and heterozygosity are high throughout the Indo-Pacific, while genetic structure is low. In contrast, allelic diversity is low while population structure is higher for populations at the ends of the range in the West Atlantic and East Pacific. Conclusions/Significance: These data are consistent with the proposed Indo-Pacific center of origin for S. lewini, and indicate that females are philopatric or adhere to coastal habitats while males facilitate gene flow across oceanic expanses. This study includes the largest sampling effort and the most molecular loci ever used to survey the complete range of

The Science Performance of JWST as Characterized in Commissioning

This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies.Comment: 5th version as accepted to PASP; 31 pages, 18 figures; https://iopscience.iop.org/article/10.1088/1538-3873/acb29