Explore the vast range of titles available.

هذه الرسائل هي بالفعل رسائل بيلاطس البنطي إلى صديقه سنيكا، وهي تعتبر وثائق تاريخية لما تضمنته من إشارات من واقع الأحداث في تلك الفترة. كما أنها ضوء جديد على الأحداث الهامة للغاية في تاريخ البشرية، من وجهة نظر الحاكم الروماني، الذي سجل لنا هذه الرسائل ومشاعره تجاه أنداده من ولاة الرومان في تلك المنطقة من العالم، وشعوره من نحو القديس يوحنا المعمدان ومن بعده يسوع المسيح، ثم كل الجماعات اليهودية ... وهي أيضا تكشف لنا عن الدوافع الحقيقية التي أدت به إلى إصدار الحكم على يسوع بالصلب، رغم من أنه متيقن من براءته، وان اليهود لفقوا له التهم بقصد التخلص منه.

Perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) are receiving global attention due to their persistence in the environment through wastewater effluent discharges and past improper industrial waste disposal. They are resistant to biological degradation and if present in wastewater are discharged into the environment. The US Environmental Protection Agency (USEPA) issued drinking water Health Advisories for PFOA and PFOS at 70 ng/L each and for the sum of the two. The need for an enforceable primary drinking water regulation under the Safe Drinking Water Act (SDWA) is currently being assessed. The USEPA faces stringent legal constraints and technical barriers to develop a primary drinking water regulation for PFOA and PFOS. This review synthesizes current knowledge providing a publicly available, comprehensive point of reference for researchers, water utilities, industry, and regulatory agencies to better understand and address cross-cutting issues associated with regulation of PFOA and PFOS contamination of drinking water.

The aim of this study is to improve the understanding of land changes in the Jiulong River watershed, a coastal watershed of Southeast China. We developed a stratified classification methodology for land mapping, which combines linear stretching, an Iterative Self-Organizing Data Analysis (ISODATA) clustering algorithm, and spatial reclassification. The stratified classification for 2002 generated less overall error than an unstratified classification. The stratified classifications were then used to examine temporal differences at 1986, 1996, 2002, 2007 and 2010. Intensity Analysis was applied to analyze land changes at three levels: time interval, category, and transition. Results showed that land use transformation has been accelerating. Woodland’s gains and losses were dormant while the gains and losses of Agriculture, Orchard, Built-up and Bare land were active during all time intervals. Water’s losses were active and stationary. The transitions from Agriculture, Orchard, and Water to Built-up were systematically targeting and stationary, while the transition from Woodland to Built-up was systematically avoiding and stationary.

The relative operating characteristic (ROC) is a widely-used method to measure diagnostic signals including predictions of land changes, species distributions, and ecological niches. The ROC measures the degree to which presence for a Boolean variable is associated with high ranks of an index. The ROC curve plots the rate of true positives versus the rate of false positives obtained from the comparison between the Boolean variable and multiple diagnoses derived from thresholds applied to the index. The area under the ROC curve (AUC) is a summary metric, which is commonly reported and frequently criticized. Our manuscript recommends four improvements in the use and interpretation of the ROC curve and its AUC by: (1) highlighting important threshold points on the ROC curve, (2) interpreting the shape of the ROC curve, (3) defining lower and upper bounds for the AUC, and (4) mapping the density of the presence within each bin of the ROC curve. These recommendations encourage scientists to interpret the rich information that the ROC curve can reveal, in a manner that goes far beyond the potentially misleading AUC. We illustrate the benefit of our recommendations by assessing the prediction of land change in a suburban landscape.

The Total Operating Characteristic (TOC) measures how the ranks of an index variable distinguish between presence and absence in a binary reference variable. Previous methods to generate the TOC required the reference data to derive from a census or a simple random sample. However, many researchers apply stratified random sampling to collect reference data because stratified random sampling is more efficient than simple random sampling for many applications. Our manuscript derives a new methodology that uses stratified random sampling to generate the TOC. An application to flood mapping illustrates how the TOC compares the abilities of three indices to diagnose water. The TOC shows visually and quantitatively each index’s diagnostic ability relative to baselines. Results show that the Modified Normalized Difference Water Index has the greatest diagnostic ability, while the Normalized Difference Vegetation Index has diagnostic ability greater than the Normalized Difference Water Index at the threshold where the Diagnosed Presence equals the Abundance of water. Some researchers consider only one accuracy metric at only one threshold, whereas the TOC allows visualization of several metrics at all thresholds. The TOC gives more information and clearer interpretation compared to the popular Relative Operating Characteristic. Our software generates the TOC from a census, simple random sample, or stratified random sample. The TOC Curve Generator is free as an executable file at a website that our manuscript gives.

The Total Operating Characteristic (TOC) is an improvement on the quantitative method called the Relative Operating Characteristic (ROC), both of which plot the association between a binary variable and a rank variable. TOC curves reveal the sizes of the four entries in the confusion matrix at each threshold, which make TOC curves more easily interpretable than ROC curves. The TOC has become popular, especially to assess the fit of simulation models to predict land change. However, the literature has shown variation in how authors apply and interpret the TOC, creating some misleading conclusions. Our manuscript lists best practices when applying and interpreting the TOC to help scientists learn from TOC curves. An example illustrates these practices by applying the TOC to measure the ability to predict the gain of crop in Western Bahia, Brazil. The application compares four ways to design the rank variable based on the distance to either pixels or patches of either the presence or change of crop. The results show that the gain of crop during the validation time interval is more strongly associated with the distance to patches rather than pixels of crop. The Discussion Section reveals that if authors show the TOC curves, then readers can interpret the results in ways that the authors might have missed. The Conclusion encourages scientists to follow best practices to learn the wealth of information that the TOC reveals.

Remote sensing, or Earth Observation (EO), is increasingly used to understand Earth system dynamics and create continuous and categorical maps of biophysical properties and land cover, especially based on recent advances in machine learning (ML). ML models typically require large, spatially explicit training datasets to make accurate predictions. Training data (TD) are typically generated by digitizing polygons on high spatial-resolution imagery, by collecting in situ data, or by using pre-existing datasets. TD are often assumed to accurately represent the truth, but in practice almost always have error, stemming from (1) sample design, and (2) sample collection errors. The latter is particularly relevant for image-interpreted TD, an increasingly commonly used method due to its practicality and the increasing training sample size requirements of modern ML algorithms. TD errors can cause substantial errors in the maps created using ML algorithms, which may impact map use and interpretation. Despite these potential errors and their real-world consequences for map-based decisions, TD error is often not accounted for or reported in EO research. Here we review the current practices for collecting and handling TD. We identify the sources of TD error, and illustrate their impacts using several case studies representing different EO applications (infrastructure mapping, global surface flux estimates, and agricultural monitoring), and provide guidelines for minimizing and accounting for TD errors. To harmonize terminology, we distinguish TD from three other classes of data that should be used to create and assess ML models: training reference data, used to assess the quality of TD during data generation; validation data, used to iteratively improve models; and map reference data, used only for final accuracy assessment. We focus primarily on TD, but our advice is generally applicable to all four classes, and we ground our review in established best practices for map accuracy assessment literature. EO researchers should start by determining the tolerable levels of map error and appropriate error metrics. Next, TD error should be minimized during sample design by choosing a representative spatio-temporal collection strategy, by using spatially and temporally relevant imagery and ancillary data sources during TD creation, and by selecting a set of legend definitions supported by the data. Furthermore, TD error can be minimized during the collection of individual samples by using consensus-based collection strategies, by directly comparing interpreted training observations against expert-generated training reference data to derive TD error metrics, and by providing image interpreters with thorough application-specific training. We strongly advise that TD error is incorporated in model outputs, either directly in bias and variance estimates or, at a minimum, by documenting the sources and implications of error. TD should be fully documented and made available via an open TD repository, allowing others to replicate and assess its use. To guide researchers in this process, we propose three tiers of TD error accounting standards. Finally, we advise researchers to clearly communicate the magnitude and impacts of TD error on map outputs, with specific consideration given to the likely map audience.

Interactions between predators and prey are often characterized by strong selection pressures that shape extreme physiological adaptations. Venom resistance in large-bodied South American opossums (Clade Didelphini) is a striking example, as these marsupials prey on venomous snakes and exhibit remarkable resistance to their venom. While resistance is well documented in Didelphini, relatively little is known about venom resistance in the smaller, more diverse members of Didelphidae, which inhabit the same regions and encounter the same predators. Moreover, resistance of opossum von Willebrand factor (VWF) to the venom C-type lectin-like proteins has not been previously studied under simulated vascular flow states. Here, we use microfluidic devices to investigate venom resistance in the small-bodied opossum, Monodelphis domestica, examining platelet adhesion and fibrin deposition in response to purified venom components. Additionally, we conduct platelet aggregometry and assays of serum protease inhibitors in the presence of venom from sympatric and allopatric vipers to examine patterns of species-specificity and adaptation. Our results show that M. domestica resists venom-induced disruptions to platelet function in the presence of platelet-disrupting venom components botrocetin and convulxin, while aspercetin disrupts platelet and fibrin function similarly in opossum and human samples. Whole blood aggregometry and serum protease inhibition showed patterns consistent with species-specific adaptation of mammals to their local snake venom. Unexpectedly, we find that M. domestica VWF requires increased shear force to elongate, a previously unknown aspect of opossum blood physiology that may contribute to venom resistance and may have relevance to human coagulopathies. Our findings demonstrate resistance under natural shear stress, and document venom resistance beyond large-bodied Didelphini, suggesting it is a widespread trait in South American marsupials.

This paper applies methods of multiple resolution map comparison to quantify characteristics for 13 applications of 9 different popular peer-reviewed land change models. Each modeling application simulates change of land categories in raster maps from an initial time to a subsequent time. For each modeling application, the statistical methods compare: (1) a reference map of the initial time, (2) a reference map of the subsequent time, and (3) a prediction map of the subsequent time. The three possible two-map comparisons for each application characterize: (1) the dynamics of the landscape, (2) the behavior of the model, and (3) the accuracy of the prediction. The three-map comparison for each application specifies the amount of the prediction’s accuracy that is attributable to land persistence versus land change. Results show that the amount of error is larger than the amount of correctly predicted change for 12 of the 13 applications at the resolution of the raw data. The applications are summarized and compared using two statistics: the null resolution and the figure of merit. According to the figure of merit, the more accurate applications are the ones where the amount of observed net change in the reference maps is larger. This paper facilitates communication among land change modelers, because it illustrates the range of results for a variety of models using scientifically rigorous, generally applicable, and intellectually accessible statistical techniques.

Irradiating a ferromagnet with a femtosecond laser pulse is known to induce an ultrafast demagnetization within a few hundred femtoseconds. Here we demonstrate that direct laser irradiation is in fact not essential for ultrafast demagnetization, and that electron cascades caused by hot electron currents accomplish it very efficiently. We optically excite a Au/Ni layered structure in which the 30 nm Au capping layer absorbs the incident laser pump pulse and subsequently use the X-ray magnetic circular dichroism technique to probe the femtosecond demagnetization of the adjacent 15 nm Ni layer. A demagnetization effect corresponding to the scenario in which the laser directly excites the Ni film is observed, but with a slight temporal delay. We explain this unexpected observation by means of the demagnetizing effect of a superdiffusive current of non-equilibrium, non-spin-polarized electrons generated in the Au layer. The ultrafast dynamic phenomena associated with thin magnetic films irradiated by a laser pulse have been proposed to occur through a process involving spin transport. The observation that this is also the case when the films are covered by a non-magnetic capping layer provides compelling evidence in favour of this scenario.