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Marine phytoplankton are primary producers in ocean ecosystems and emit dimethyl sulfide (DMS) to the atmosphere. DMS emissions are the largest biological source of atmospheric sulfur and are one of the largest uncertainties in global climate modeling. DMS is oxidized to methanesulfonic acid (MSA), sulfur dioxide (SO2), and hydroperoxymethyl thioformate (HPMTF), all of which can be oxidized to sulfate. Ice core records of MSA are used to investigate past DMS emissions but rely on the implicit assumption that the relative yield of oxidation products from DMS remains constant. However, this assumption is uncertain because there are no long-term records that compare MSA to other DMS oxidation products. Here we share the first long-term record of both MSA and DMS-derived biogenic sulfate concentration in Greenland ice core samples from 1200 to 2006 CE. While MSA declines on average by 0.2 µg S kg-1 over the industrial era, biogenic sulfate from DMS increases by 0.8 µg S kg-1. This increasing biogenic sulfate contradicts previous assertions of declining North Atlantic primary productivity inferred from decreasing MSA concentrations in Greenland ice cores over the industrial era. The changing ratio of MSA to biogenic sulfate suggests that trends in MSA could be caused by time-varying atmospheric chemistry, and that MSA concentrations alone should not be used to infer past primary productivity. 

Anthropogenic sulfate aerosols are estimated to have offset sixty percent of greenhouse-gas-induced warming in the Arctic, a region warming four times faster than the rest of the world. However, sulfate radiative forcing estimates remain uncertain because the relative contributions from anthropogenic versus natural sources to total sulfate aerosols are unknown. Here we measure sulfur isotopes of sulfate in a Summit, Greenland ice core from 1850 to 2006 CE to quantify the contribution of anthropogenic sulfur emissions to ice core sulfate. We use a Keeling Plot to determine the anthropogenic sulfur isotopic signature (δ34Santhro = +2.9 ± 0.3 ‰), and compare this result to a compilation of sulfur isotope measurements of oil and coal. Using δ34Santhro, we quantify anthropogenic sulfate concentration separated from natural sulfate. Anthropogenic sulfate concentration increases to 68 ± 7% of non-sea-salt sulfate (65.1 ± 20.2 µg kg-1) during peak anthropogenic emissions from 1960 to 1990 and decreases to 45 ± 11% of non-sea-salt sulfate (25.4 ± 12.8 µg kg-1) from 1996 to 2006. These observations provide the first long-term record of anthropogenic sulfate distinguished from natural sources (e.g., volcanoes, dimethyl sulfide), and can be used to evaluate model characterization of anthropogenic sulfate aerosol fraction and radiative forcing over the industrial era. 

Security failures in software arising from failures to practice secure programming are commonplace. Improving this situation requires that practitioners have a clear understanding of the foundational concepts in secure programming to serve as a basis for building new knowledge and responding to new challenges. We developed a Secure Programing Concept Inventory (SPCI) to measure students' understanding of foundational concepts in secure programming. The SPCI consists of thirty-five multiple choice items targeting ten concept areas of secure programming. The SPCI was developed by establishing the content domain of secure programming, developing a pool of test items, multiple rounds of testing and refining the items, and finally testing and inventory reduction to produce the final scale. Scale development began by identifying the core concepts in secure programming. A Delphi study was conducted with thirty practitioners from industry, academia, and government to establish the foundational concepts of secure programming and develop a concept map. To build a set of misconceptions in secure programming, the researchers conducted interviews with students and instructors in the field. These interviews were analyzed using content analysis. This resulted in a taxonomy of misconceptions in secure programming covering ten concept areas. An item pool of multiple-choice questions was developed. The item pool of 225 was administered to a population of 690 students across four institutions. Item discrimination and item difficulty scores were calculated, and the best performing items were mapped to the misconception categories to create subscales for each concept area resulting in a validated 35 item scale. 

The Arctic is warming at almost four times the global rate. Cooling caused by anthropogenic aerosols has been estimated to offset sixty percent of greenhouse-gas-induced Arctic warming, but the contribution of aerosols to radiative forcing (RF) represents the largest uncertainty in estimating total RF, largely due to unknown preindustrial aerosol abundance. Here, sulfur isotope measurements in a Greenland ice core show that passive volcanic degassing contributes up to 66 ± 10% of preindustrial ice core sulfate in years without major eruptions. A state-of-the-art model indicates passive volcanic sulfur emissions influencing the Arctic are underestimated by up to a factor of three, possibly because many volcanic inventories do not include hydrogen sulfide emissions. Higher preindustrial volcanic sulfur emissions reduce modeled anthropogenic Arctic aerosol cooling by up to a factor of two (+0.11 to +0.29 W m-2), suggesting that underestimating passive volcanic sulfur emissions has significant implications for anthropogenic-induced Arctic climate change. 

SecTutor is a tutoring system that uses adaptive testing to select instructional modules that allow users to pursue secure programming knowledge at their own pace. This project aims to combat one of the most significant cybersecurity challenges we have today: individuals’ failure to practice defensive, secure, and robust programming. To alleviate this, we introduce SecTutor, an adaptive online tutoring system, to help developers understand the foundational concepts behind secure programming. SecTutor allows learners to pursue knowledge at their own pace and according to their own interests, based on assessments that identify and structure educational modules based on their current level of understanding. 

SecTutor is a tutoring system that uses adaptive testing to select instructional modules that allow users to pursue secure programming knowledge at their own pace. This project aims to combat one of the most significant cybersecurity challenges we have today: individuals’ failure to practice defensive, secure, and robust programming. To alleviate this, we introduce SecTutor, an adaptive online tutoring system, to help developers understand the foundational concepts behind secure programming. SecTutor allows learners to pursue knowledge at their own pace and according to their own interests, based on assessments that identify and structure educational modules based on their current level of understanding. 

Computing students are not receiving enough education and practice in secure programming. A key part of being able to successfully implement secure programming practices is the development of secure programming self-efficacy. This paper examines the development of a scale to measure secure programming self-efficacy among students participating in a secure programming clinic (SPC). The results show that the secure programming self-efficacy scale is a reliable and useful measure that correlates satisfactorily with related measures of programming expertise. This measure can be used in secure programming courses and other learning environments to assess students’ secure programming efficacy. 

Abstract Tidal disruption events (TDEs) are among the brightest transients in the optical, ultraviolet, and X-ray sky. These flares are set into motion when a star is torn apart by the tidal field of a massive black hole, triggering a chain of events which is – so far – incompletely understood. However, the disruption process has been studied extensively for almost half a century, and unlike the later stages of a TDE, our understanding of the disruption itself is reasonably well converged. In this Chapter, we review both analytical and numerical models for stellar tidal disruption. Starting with relatively simple, order-of-magnitude physics, we review models of increasing sophistication, the semi-analytic “affine formalism,” hydrodynamic simulations of the disruption of polytropic stars, and the most recent hydrodynamic results concerning the disruption of realistic stellar models. Our review surveys the immediate aftermath of disruption in both typical and more unusual TDEs, exploring how the fate of the tidal debris changes if one considers non-main sequence stars, deeply penetrating tidal encounters, binary star systems, and sub-parabolic orbits. The stellar tidal disruption process provides the initial conditions needed to model the formation of accretion flows around quiescent massive black holes, and in some cases may also lead to directly observable emission, for example via shock breakout, gravitational waves or runaway nuclear fusion in deeply plunging TDEs.