Hydrological controls of in situ preservation of waterlogged archaeological deposits

Environmental change caused by urban development, land drainage, agriculture or climate change may result in accelerated decay of in situ archaeological remains. This paper reviews research into impacts of environmental change on hydrological processes of relevance to preservation of archaeological remains in situ. It compares work at rural sites with more complex urban environments. The research demonstrates that both the quantity and quality of data on preservation status, and hydrological and chemical parameters collected during routine archaeological surveys need to be improved. The work also demonstrates the necessity for any archaeological site to be placed within its topographic and geological context. In order to understand preservation potential fully, it is necessary to move away from studying the archaeological site as an isolated unit, since factors some distance away from the site of interest can be important for determining preservation. The paper reviews what is known about the hydrological factors of importance to archaeological preservation and recommends research that needs to be conducted so that archaeological risk can be more adequately predicted and mitigated. Any activity that changes either source pathways or the dominant water input may have an impact not just because of changes to the water balance or the water table, but because of changes to water chemistry. Therefore, efforts to manage threatened waterlogged environments must consider the chemical nature of the water input into the system. Clearer methods of assessing the degree to which buried archaeological sites can withstand changing hydrological conditions are needed, in addition to research which helps us understand what triggers decay and what controls thresholds of response for different sediments and types of artefact

New approaches to mapping and managing palaeochannel resources in the light of future environmental change : a case study from the Trent Valley, UK

Abandoned river channels may provide rich primary sources of palaeoenvironmental and cultural information elucidating landscape evolution, climate change, vegetation history and human impact, especially since the beginning of the Holocene epoch. However, although potentially an important resource, palaeochannels are not often recorded systematically and only rarely enjoy robust statutory protection (in the UK as Sites of Special Scientific Interest). In consequence, it is challenging to mitigate and manage this important geoarchaeological resource effectively within the UK planning framework. Whilst palaeochannels have long been recognised on aerial photographs and historic maps, the advent of airborne laser scanning (Lidar) and other remote-sensing technologies has provided a hitherto unforeseen opportunity to record such landforms and related features at a catchment scale. This paper provides a case study from the Nottinghamshire reach of the Trent Valley, where a desk-based methodology that is now being extended across the entire catchment has been developed for recording, geospatially locating and defining the attributes of observed palaeochannels. After outlining the methodology, we consider how this approach to resource management can aid archaeological research and future heritage management, especially in the light of predicted climate and environmental change

Ultraluminous infrared galaxies: mergers of sub-L* galaxies?

A sample of 27 low-redshift, mostly cool, ultraluminous infrared galaxies (ULIRGs) has been imaged at 1.6 μm with the Hubble Space Telescope (HST) Near-Infrared Camera and Multi-Object Spectrometer (NICMOS). The majority (67%) of the sample's galaxies are multiple-nucleus galaxies with projected separations of up to 17 kpc, and the rest of the sample (33%) are single-nucleus galaxies, as determined by the NICMOS angular resolution limit. The average observed, integrated (host+nucleus) H magnitude of our HST H sample ULIRGs is -24.3, slightly above that of an L* galaxy (MH = -24.2), and 52% of the sample's galaxies have sub-L* luminosities. The ULIRGs in the HST H sample are not generated as a result of the merging of two luminous (i.e., ≥L*) spiral galaxies. Instead, the interactions and mergers occur in general between two, or in some cases more, less massive sub-L* (0.3-0.5L*) galaxies. Only one out of the 49 nuclei identified in the entire HST H sample has the properties of a bright quasar-like nucleus. On average, the brightest nuclei in the HST H sample galaxies (i.e., cool ULIRGs) are 1.2 mag fainter than warm ULIRGs and low-luminosity Bright Quasar Survey quasars (BQS QSOs) and 2.6 mag fainter than high-luminosity BQS QSOs. Since the progenitor galaxies involved in the merger are sub-L* galaxies, the mass of the central black hole in these ULIRGs would be only about (1-2) × 107 M☉, if the bulge-to-black hole mass ratio of nearby galaxies holds for ULIRGs. The estimated mass of the central black hole is similar to that of nearby Seyfert 2 galaxies but at least 1 order of magnitude lower than the massive black holes thought to be located at the center of high-luminosity QSOs. Massive nuclear starbursts with constant star formation rates of 10-40 M☉ yr-1 could contribute significantly to the nuclear H-band flux and are consistent with the observed nuclear H-band magnitudes of the ULIRGs in the HST H sample. An evolutionary merging scenario is proposed for the generation of the different types of ULIRGs and QSOs on the basis of the masses of the progenitors involved in the merging process. According to this scenario, cool ULIRGs would be the end product of the merging of two or more low-mass (0.3L*-0.5L*) disk galaxies. Warm ULIRGs and low-luminosity QSOs would be generated by a merger involving intermediate-mass (0.5 L*) disk galaxies. Under this scenario, warm ULIRGs could still be the dust-enshrouded phases of UV-bright low-luminosity QSOs, but cool ULIRGs, which are most ULIRGs, would not evolve into QSOs

Near-Earth initiation of a terrestrial substorm

Despite the characterization of the auroral substorm more than 40 years ago, controversy still surrounds the processes triggering substorm onset initiation. That stretching of the Earth's magnetotail following the addition of new nightside magnetic flux from dayside reconnection powers the substorm is well understood; the trigger for explosive energy release at substorm expansion phase onset is not. Using ground-based data sets with unprecedented combined spatial and temporal coverage, we report the discovery of new localized and contemporaneous magnetic wave and small azimuthal scale auroral signature of substorm onset. These local auroral arc undulations and magnetic field signatures rapidly evolve on second time scales for several minutes in advance of the release of the auroral surge. We also present evidence from a conjugate geosynchronous satellite of the concurrent magnetic onset in space as the onset of magnetic pulsations in the ionosphere, to within technique error. Throughout this time period, the more poleward arcs that correspond to the auroral oval which maps to the central plasma sheet remain undisturbed. There is good evidence that flows from the midtail crossing the plasma sheet can generate north-south auroral structures, yet no such auroral forms are seen in this event. Our observations present a severe challenge to the standard hypothesis that magnetic reconnection in stretched magnetotail fields triggers onset, indicating substorm expansion phase initiation occurs on field lines that are close to the Earth, as bounded by observations at geosynchronous orbit and in the conjugate ionosphere

Setting Sail for Early Learning Success: Using a Data-based Decision Making Process to Measure and Monitor Outcomes in Early Childhood Programs

The use of data to inform decision-making and monitor individual student progress is recognized as an important, yet elusive practice in early childhood programs. In this article, Data-based Navigation is presented as a five step data-based decision making process designed to help early childhood professionals measure and monitor desired programmatic outcomes. A case study that focuses on the reduction of challenging behaviors is provided to illustrate the process

Risk algorithm using serial biomarker measurements doubles the number of screen-detected cancers compared with a single-threshold rule in the United Kingdom collaborative trial of ovarian cancer screening

PURPOSE: Cancer screening strategies have commonly adopted single-biomarker thresholds to identify abnormality. We investigated the impact of serial biomarker change interpreted through a risk algorithm on cancer detection rates. PATIENTS AND METHODS: In the United Kingdom Collaborative Trial of Ovarian Cancer Screening, 46,237 women, age 50 years or older underwent incidence screening by using the multimodal strategy (MMS) in which annual serum cancer antigen 125 (CA-125) was interpreted with the risk of ovarian cancer algorithm (ROCA). Women were triaged by the ROCA: normal risk, returned to annual screening; intermediate risk, repeat CA-125; and elevated risk, repeat CA-125 and transvaginal ultrasound. Women with persistently increased risk were clinically evaluated. All participants were followed through national cancer and/or death registries. Performance characteristics of a single-threshold rule and the ROCA were compared by using receiver operating characteristic curves. RESULTS: After 296,911 women-years of annual incidence screening, 640 women underwent surgery. Of those, 133 had primary invasive epithelial ovarian or tubal cancers (iEOCs). In all, 22 interval iEOCs occurred within 1 year of screening, of which one was detected by ROCA but was managed conservatively after clinical assessment. The sensitivity and specificity of MMS for detection of iEOCs were 85.8% (95% CI, 79.3% to 90.9%) and 99.8% (95% CI, 99.8% to 99.8%), respectively, with 4.8 surgeries per iEOC. ROCA alone detected 87.1% (135 of 155) of the iEOCs. Using fixed CA-125 cutoffs at the last annual screen of more than 35, more than 30, and more than 22 U/mL would have identified 41.3% (64 of 155), 48.4% (75 of 155), and 66.5% (103 of 155), respectively. The area under the curve for ROCA (0.915) was significantly (P = .0027) higher than that for a single-threshold rule (0.869). CONCLUSION: Screening by using ROCA doubled the number of screen-detected iEOCs compared with a fixed cutoff. In the context of cancer screening, reliance on predefined single-threshold rules may result in biomarkers of value being discarded

Assessing riverine threats to heritage assets posed by future climate change: a methodological approach based on understanding geomorphological inheritance and predictive modelling, tested within the Derwent Valley Mills WHS, UK

Future climate change is likely to pose significant challenges for heritage management, especially in landscape settings such as river valleys as the magnitude, intensity and nature of geomorphological processes alter in response to changing threshold conditions. Industrial landscapes afford particular challenges for the heritage community, not only because the location of these historic remains is often intimately linked to the physical environment, but also because these landscapes can be heavily polluted by former (industrial) processes and, if released, the legacy of contaminants trapped in floodplain soils and sediments can exacerbate erosion and denudation. Responding to these challenges requires the development of methodologies that consider landscape change beyond individual sites and monuments and this paper reports the development of such an approach based on investigation of the Derwent Valley Mills World Heritage Site, Derbyshire, UK. Information on geomorphological evolution of the Derwent Valley over the last 1000 years, a time period encompassing the last two periods of major climatic deterioration, the Medieval Warm Period and Little Ice Age, has been dovetailed with archaeological and geochemical records to assess how the landscape has evolved to past landscape change. However, in addition to assessing past evolution, this methodology uses national climate change scenarios to predict future river change using the CAESAR-Lisflood model. Comparison of the results of this model to the spatial distribution of World Heritage Site assets highlights zones on the valley floor where pro-active mitigation might be required. The geomorphological and environmental science communities have long used predictive computer modelling to help understand and manage landscapes and this paper highlights an approach and area of research cross-over that would be beneficial for future heritage management

38766 Massively Parallel Reporter Assay Reveals Functional Impact of 3™-UTR SNPs Associated with Neurological and Psychiatric Disorders

ABSTRACT IMPACT: Screening the effect of thousands of non-coding genetic variants will help identify variants important in the etiology of diseases OBJECTIVES/GOALS: Massively parallel reporter assays (MPRAs) can experimentally evaluate the impact of genetic variants on gene expression. In this study, our objective was to systematically evaluate the functional activity of 3’-UTR SNPs associated with neurological disorders and use those results to help understand their contributions to disease etiology. METHODS/STUDY POPULATION: To choose variants to evaluate with the MPRA, we first gathered SNPs from the GWAS Catalog that were associated with any neurological disorder trait with p-value 0.8) and retrieved all the common 3’-UTR SNPs (allele-frequency > 0.05) within that region. We used an MPRA to measure the impact of these 3’-UTR variants in SH-SY5Y neuroblastoma cells and a microglial cell line. These results were then used to train a deep-learning model to predict the impact of variants and identify features that contribute to the predictions. RESULTS/ANTICIPATED RESULTS: Of the 13,515 3’-UTR SNPs tested, 400 and 657 significantly impacted gene expression in SH-SY5Y and microglia, respectively. Of the 84 SNPs significantly impacted in both cells, the direction of impact was the same in 81. The direction of eQTL in GTEx tissues agreed with the assay SNP effect in SH-SY5Y cells but not microglial cells. The deep-learning model predicted sequence activity level correlated with the experimental activity level (Spearman’s corr = 0.45). The deep-learning model identified several predictive motifs similar to motifs of RNA-binding proteins. DISCUSSION/SIGNIFICANCE OF FINDINGS: This study demonstrates that MPRAs can be used to evaluate the effect of non-coding variants, and the results can be used to train a machine learning model and interpret its predictions. Together, these can help identify causal variants and further understand the etiology of diseases