Copyrighting the Past? Emerging Intellectual Property Rights Issues in Archaeology1

Rights to intellectual property have become a major issue in eth- nobotany and many other realms of research involving Indige- nous communities. This paper examines intellectual-property- rights-related issues in archaeology, including the relevance of such rights within the discipline, the forms these rights take, and the impacts of applying intellectual property protection in archaeology. It identifies the “products” of archaeological re- search and what they represent in a contemporary sociocultural context, examines ownership issues, assesses the level of protec- tion of these products provided by existing legislation, and dis- cusses the potential of current intellectual property protection mechanisms to augment cultural heritage protection for Indige- nous communities

What Sets the Radial Locations of Warm Debris Disks?

The architectures of debris disks encode the history of planet formation in these systems. Studies of debris disks via their spectral energy distributions (SEDs) have found infrared excesses arising from cold dust, warm dust, or a combination of the two. The cold outer belts of many systems have been imaged, facilitating their study in great detail. Far less is known about the warm components, including the origin of the dust. The regularity of the disk temperatures indicates an underlying structure that may be linked to the water snow line. If the dust is generated from collisions in an exo-asteroid belt, the dust will likely trace the location of the water snow line in the primordial protoplanetary disk where planetesimal growth was enhanced. If instead the warm dust arises from the inward transport from a reservoir of icy material farther out in the system, the dust location is expected to be set by the current snow line. We analyze the SEDs of a large sample of debris disks with warm components. We find that warm components in single-component systems (those without detectable cold components) follow the primordial snow line rather than the current snow line, so they likely arise from exo-asteroid belts. While the locations of many warm components in two-component systems are also consistent with the primordial snow line, there is more diversity among these systems, suggesting additional effects play a role

A Comprehensive Dust Model Applied to the Resolved Beta Pictoris Debris Disk from Optical to Radio Wavelengths

We investigate whether varying the dust composition (described by the optical constants) can solve a persistent problem in debris disk modeling--the inability to fit the thermal emission without over-predicting the scattered light. We model five images of the beta Pictoris disk: two in scattered light from HST/STIS at 0.58 microns and HST/WFC3 at 1.16 microns, and three in thermal emission from Spitzer/MIPS at 24 microns, Herschel/PACS at 70 microns, and ALMA at 870 microns. The WFC3 and MIPS data are published here for the first time. We focus our modeling on the outer part of this disk, consisting of a parent body ring and a halo of small grains. First, we confirm that a model using astronomical silicates cannot simultaneously fit the thermal and scattered light data. Next, we use a simple, generic function for the optical constants to show that varying the dust composition can improve the fit substantially. Finally, we model the dust as a mixture of the most plausible debris constituents: astronomical silicates, water ice, organic refractory material, and vacuum. We achieve a good fit to all datasets with grains composed predominantly of silicates and organics, while ice and vacuum are, at most, present in small amounts. This composition is similar to one derived from previous work on the HR 4796A disk. Our model also fits the thermal SED, scattered light colors, and high-resolution mid-IR data from T-ReCS for this disk. Additionally, we show that sub-blowout grains are a necessary component of the halo.Comment: 23 pages, 20 figures, accepted to Ap

Feather barbs as a good source of mtDNA for bird species identification in forensic wildlife investigations

Background: The ability to accurately identify bird species is crucial for wildlife law enforcement and bird-strikeinvestigations. However, such identifications may be challenging when only partial or damaged feathers areavailable for analysis.Results: By applying vigorous contamination controls and sensitive PCR amplification protocols, we found that itwas feasible to obtain accurate mitochondrial (mt)DNA-based species identification with as few as two featherbarbs. This minimally destructive DNA approach was successfully used and tested on a variety of bird species,including North American wild turkey (Meleagris gallopavo), Canada goose (Branta canadensis), blue heron (Ardeaherodias) and pygmy owl (Glaucidium californicum). The mtDNA was successfully obtained from ‘fresh’ feathers,historic museum specimens and archaeological samples, demonstrating the sensitivity and versatility of thistechnique.Conclusions: By applying appropriate contamination controls, sufficient quantities of mtDNA can be reliablyrecovered and analyzed from feather barbs. This previously overlooked substrate provides new opportunities foraccurate DNA species identification when minimal feather samples are available for forensic analysis

3D Pharmacophoric Similarity improves Multi Adverse Drug Event Identification in Pharmacovigilance

Adverse drugs events (ADEs) detection constitutes a considerable concern in patient safety and public health care. For this reason, it is important to develop methods that improve ADE signal detection in pharmacovigilance databases. Our objective is to apply 3D pharmacophoric similarity models to enhance ADE recognition in Offsides, a pharmacovigilance resource with drug-ADE associations extracted from the FDA Adverse Event Reporting System (FAERS). We developed a multi-ADE predictor implementing 3D drug similarity based on a pharmacophoric approach, with an ADE reference standard extracted from the SIDER database. The results showed that the application of our 3D multi-type ADE predictor to the pharmacovigilance data in Offsides improved ADE identification and generated enriched sets of drug-ADE signals. The global ROC curve for the Offsides ADE candidates ranked with the 3D similarity score showed an area of 0.7. The 3D predictor also allows the identification of the most similar drug that causes the ADE under study, which could provide hypotheses about mechanisms of action and ADE etiology. Our method is useful in drug development, screening potential adverse effects in experimental drugs, and in drug safety, applicable to the evaluation of ADE signals selected through pharmacovigilance data mining

3D Pharmacophoric Similarity improves Multi Adverse Drug Event Identification in Pharmacovigilance

Adverse drugs events (ADEs) detection constitutes a considerable concern in patient safety and public health care. For this reason, it is important to develop methods that improve ADE signal detection in pharmacovigilance databases. Our objective is to apply 3D pharmacophoric similarity models to enhance ADE recognition in Offsides, a pharmacovigilance resource with drug-ADE associations extracted from the FDA Adverse Event Reporting System (FAERS). We developed a multi-ADE predictor implementing 3D drug similarity based on a pharmacophoric approach, with an ADE reference standard extracted from the SIDER database. The results showed that the application of our 3D multi-type ADE predictor to the pharmacovigilance data in Offsides improved ADE identification and generated enriched sets of drug-ADE signals. The global ROC curve for the Offsides ADE candidates ranked with the 3D similarity score showed an area of 0.7. The 3D predictor also allows the identification of the most similar drug that causes the ADE under study, which could provide hypotheses about mechanisms of action and ADE etiology. Our method is useful in drug development, screening potential adverse effects in experimental drugs, and in drug safety, applicable to the evaluation of ADE signals selected through pharmacovigilance data mining