Sourcing the Sacred: Application of Reflectance Spectroscopy and Linear Morphometrics to Hopewell Mortuary Chert Discs

ABSTRACT: Despite being one of the most intensively-studied culture phenomena of precontact North America, Hopewell peoples and their communities remain largely enigmatic outside of ceremonial earthwork sites. This research aims to examine Ohio Hopewell community by proxy of the large cache of chert bifaces disinterred from Mound 2, located at the Hopewell Mound Group (33RO27) in Ross County, Ohio. Numbering approximately 8,600 bifaces, these artifacts exhibit broadly similar macroscopic traits, and have been attributed in past archaeological literature as coming from a single source in Indiana. This research hypothesizes that this attribution is erroneous, and that the interaction of geographically disparate Hopewell communities is visible here as a function of differential contributions of chert material that was locally available to them. Furthermore, it is hypothesized that if this locally-sourced chert was knapped into bifaces prior to deposition into Mound 2, that differences in gross form may represent individual communities practicing similar knapping techniques. These hypotheses are tested by subjecting a 172 member sample of the Mound 2 cache to VNIR/FTIR spectroscopy chert sourcing techniques coupled with linear morphometrics, agglomerative hierarchical clustering, and fuzzy k-means clustering. The results conclude that the 172 member sample group Mound 2 bifacial population is comprised of a variety of chert lithic materials that exhibit affinity to chert reference material obtained from multiple geographically distant chert sources within the Midwest and South. Their physical forms show broad differences in trends in biface manufacture between groups of artifacts sharing chert sources, suggesting multiple Hopewell communities gathering to participate in the construction of Mound 2

Drawing, Handwriting Processing Analysis: New Advances and Challenges

International audienceDrawing and handwriting are communicational skills that are fundamental in geopolitical, ideological and technological evolutions of all time. drawingand handwriting are still useful in defining innovative applications in numerous fields. In this regard, researchers have to solve new problems like those related to the manner in which drawing and handwriting become an efficient way to command various connected objects; or to validate graphomotor skills as evident and objective sources of data useful in the study of human beings, their capabilities and their limits from birth to decline

Size-tunable nanoneedle arrays for influencing stem cell morphology, gene expression and nuclear membrane curvature

High-aspect-ratio nanostructures have emerged as versatile platforms for intracellular sensing and biomolecule delivery. Here, we present a microfabrication approach in which a combination of reactive ion etching protocols was used to produce high-aspect-ratio, nondegradable silicon nanoneedle arrays with tip diameters that can be finely tuned between 20 and 700 nm. We used these arrays to guide the long-term culture of human mesenchymal stem cells (hMSCs). Notably, we used the nanoneedle tip diameter to control the morphology, nuclear size and F-actin alignment of interfaced hMSCs, and to regulate the expression of nuclear lamina genes, Yes-associated protein (YAP) target genes and focal adhesion genes. These topography-driven changes were attributed to signaling by Rho-family GTPase pathways, differences in the effective stiffness of the nanoneedle arrays and the degree of nuclear membrane impingement, with the latter clearly visualized using focused-ion beam scanning electron microscopy (FIB-SEM). Our approach to design high-aspect-ratio nanostructures will be broadly applicable to design biomaterials and biomedical devices used for long-term cell stimulation and monitoring

Generation of a Land Cover Atlas of environmental critic zones using unconventional tools

L'abstract è presente nell'allegato / the abstract is in the attachmen

Retrospective registration of tomographic brain images

In modern clinical practice, the clinician can make use of a vast array of specialized imaging techniques supporting diagnosis and treatment. For various reasons, the same anatomy of one patient is sometimes imaged more than once, either using the same imaging apparatus (monomodal acquisition ), or different ones (multimodal acquisition). To make simultaneous use of the acquired images, it is often necessary to bring these images in registration, i.e., to align their anatomical coordinate systems. The problem of medical image registration as concerns human brain images is addressed in this thesis. The specific chapters include a survey of recent literature, CT/MR registration using mathematical image features (edges and ridges), monomodal SPECT registration, and CT/MR/SPECT/PET registration using image features extracted by the use of mathematical morphology

Application-Dependent Wavelength Selection For Hyperspectral Imaging Technologies

Hyperspectral imaging has proven to provide benefits in numerous application domains, including agriculture, biomedicine, remote sensing, and food quality management. Unlike standard color imagery composed of these broad wavelength bands, hyperspectral images are collected over numerous (possibly hundreds) of narrow wavelength bands, thereby offering vastly more information content than standard imagery. It is this higher information content which enables improved performance in complex classification and regression tasks. However, this successful technology is not without its disadvantages which include high cost, slow data capture, high data storage requirements, and computational complexity. This research seeks to overcome these disadvantages through the development of algorithms and methods to enable the benefits of hyperspectral imaging in inexpensive portable devices that collect spectral data at only a handful (i.e., 5-7) of wavelengths specifically selected for the application of interest.This dissertation focuses on two applications of practical interest: fish fillet species classification for the prevention of food fraud and tissue oxygenation estimation for wound monitoring. Genetic algorithm, self-organizing map, and simulated annealing approaches for wavelength selection are investigated for the first application, combined with common machine learning classifiers for species classification. The simulated annealing approach for wavelength selection is carried over to the wound monitoring application and is combined with the Extended Modified Lambert-Beer law, a tissue oxygenation method that has proven to be robust to differences in melanin concentrations. Analyses for this second application included spectral convolutions to represent data collection with the envisioned inexpensive portable devices. Results of this research showed that high species classification accuracy (\u3e 90%) and low tissue oxygenation error (\u3c 1%) is achievable with just 5-7 selected wavelengths. Furthermore, the proposed wavelength selection and estimation algorithms for the wound monitoring application were found to be robust to variations in the peak wavelength and relatively wide bandwidths of the types of LEDs that may be featured in the designs of such devices

Population assessment of the mountain hares (Lepus timidus) of England: distribution, abundance and genetics

In the 1870s a small founder group of mountain hares (Lepus timidus) was translocated from Scotland to the Peak District moors, England. They succeeded as a pioneer of rewilding for 150 years, playing important ecological roles within the upland ecosystem,. Nonetheless these mountain hares frequently went unmonitored. From 1971 to 2002 only four formal studies attempted distribution or abundance assessments. Subsequently there were doubts regarding the persistence of the population. In 2008 the species was added to UK Biodiversity Action Plan, which recommended ongoing monitoring. The aim of the thesis was to provide a fundamental assessment of this mountain hare population, informing conservation status reviews and enabling subsequent potential population viability analysis. The research draws upon a considerable amount of newly collected field observations, citizen science records, geographic information and laboratory investigations. I employ new survey methods, quantitative ecology, geospatial analysis and genetic techniques to describe the distribution, abundance and genetic structure of this population This work presents evidence that Peak District mountain hares occupy a geographically confined set of hills comprising ~360km2. They favour cold environments at high elevations and appear completely dependent on heather for food and shelter. Mountain hares frequent different habitats than their sister species, the European brown hare (L. europaeus), because of different climatic and dietary preferences. Accordingly, the main threats to mountain hares are climate change which may reduce their range by ~80%; and impending competition with European brown hares. Surveys of mountain hares are notoriously challenging, since this nocturnal cryptic creature may hide by day to avoid predators. To evaluate day and night time survey methods, I compared daylight transect surveys with night-time thermal imaging and camera traps operating 24 hours per day for 5 months. Census surveys using daylight visual sampling are shown to be highly effective and statistically reliable. Consequently, some 800km of surveys were conducted, covering much rugged difficult ground, with sufficient encounter rates to enable robust estimation of density, based on high detection probability, observing ~20% of the sampled hares to a range of 520m. These surveys showed the mountain hares as a stable population of ~3,500 individuals (winter adults), with one population centre concentrated on a few square kilometres. Densities are not randomly distributed and appear influenced by anthropogenic land use. Numbers in restored blanket bog areas are highest; upon managed grouse moors numbers are two thirds less. This finding notably contradicts most preceding mountain hare research from the UK. Research sourced genetic material, mostly roadkill mountain hares, provide matter for DNA extraction and microsatellite sequencing. Owing to technical challenges, results were partial yet appeared to indicate the mountain hare population is mostly randomly mating, having a diverse genetic population structure. There appears to be a low level of hybridisation with European brown hares. Continued monitoring of this Peak District mountain hare population is necessary to support UK biodiversity conservation goals. The mountain hare population experiences the normal ecological factors that govern natural population fluctuations: weather, food availability, predators, parasites, disease and population cyclicity. There is substantial human caused mortality from roads and persecution. These could be greatly reduced, if society were willing. This thesis may serve as primary reference for conservation assessments

Development of computer-based algorithms for unsupervised assessment of radiotherapy contouring

INTRODUCTION: Despite the advances in radiotherapy treatment delivery, target volume delineation remains one of the greatest sources of error in the radiotherapy delivery process, which can lead to poor tumour control probability and impact clinical outcome. Contouring assessments are performed to ensure high quality of target volume definition in clinical trials but this can be subjective and labour-intensive. This project addresses the hypothesis that computational segmentation techniques, with a given prior, can be used to develop an image-based tumour delineation process for contour assessments. This thesis focuses on the exploration of the segmentation techniques to develop an automated method for generating reference delineations in the setting of advanced lung cancer. The novelty of this project is in the use of the initial clinician outline as a prior for image segmentation. METHODS: Automated segmentation processes were developed for stage II and III non-small cell lung cancer using the IDEAL-CRT clinical trial dataset. Marker-controlled watershed segmentation, two active contour approaches (edge- and region-based) and graph-cut applied on superpixels were explored. k-nearest neighbour (k-NN) classification of tumour from normal tissues based on texture features was also investigated. RESULTS: 63 cases were used for development and training. Segmentation and classification performance were evaluated on an independent test set of 16 cases. Edge-based active contour segmentation achieved highest Dice similarity coefficient of 0.80 ± 0.06, followed by graphcut at 0.76 ± 0.06, watershed at 0.72 ± 0.08 and region-based active contour at 0.71 ± 0.07, with mean computational times of 192 ± 102 sec, 834 ± 438 sec, 21 ± 5 sec and 45 ± 18 sec per case respectively. Errors in accuracy of irregularly shaped lesions and segmentation leakages at the mediastinum were observed. In the distinction of tumour and non-tumour regions, misclassification errors of 14.5% and 15.5% were achieved using 16- and 8-pixel regions of interest (ROIs) respectively. Higher misclassification errors of 24.7% and 26.9% for 16- and 8-pixel ROIs were obtained in the analysis of the tumour boundary. CONCLUSIONS: Conventional image-based segmentation techniques with the application of priors are useful in automatic segmentation of tumours, although further developments are required to improve their performance. Texture classification can be useful in distinguishing tumour from non-tumour tissue, but the segmentation task at the tumour boundary is more difficult. Future work with deep-learning segmentation approaches need to be explored.Funded by National Radiotherapy Trials Quality Assurance (RTTQA) grou

Developments Towards Chromophore-Selectivity in Photoacoustic Remote Sensing Microscopy

Medical imaging serves to diagnose and monitor illnesses in clinical settings. Several modalities such as X-Ray and Ultrasound have become ubiquitous due to their high utility. Photoacoustic microscopy, based on the photoacoustic effect originally discovered by Alexander Graham Bell, is sensitive to optical absorption contrast. This is highly useful in biomedical applications where the endogenous absorption contrast of tissue can directly be imaged, enabling label-free microscopy. Applications include histological assessment of tissue in support of cancerous tissue resection surgeries, as well as the functional imaging applications of blood oxygen saturation (sO2) and metabolic rate (MRO2) imaging. Recently, Photoacoustic Remote Sensing Microscopy (PARS), an all-optical implementation of photoacoustic microscopy, was pioneered by Parsin Haji Reza. This thesis makes three main contributions supporting the development of PARS microscopy. The first is the creation of an inverse model designed to solve for the concentrations of individual chromophores when imaged using several excitation wavelengths. To achieve this, constraints and considerations specific to PARS are designed and employed. The inverse model allows for the concentrations of oxy- and deoxyhemoglobin to be solved for, enabling sO2 estimation. This was performed in-vivo in an ocular setting, demonstrating the first non-contact photoacoustic measurement of sO2 in the eye. The second contribution is an in-depth experimental study of Stimulated Raman Scattering (SRS) in single-mode optical fiber as a means of generating multi-wavelength light from a conventional single-wavelength laser source. Effects associated with several laser parameters and properties of optical fiber are studied. Results of this study will find use in the apparatus design for nearly any multi-wavelength PARS application, typically where imaged absorbers must be unmixed, and in particular, in sO2 estimation. The final contribution is the development of a novel unsupervised time-domain feature-learning algorithm, designed to learn characteristic signal shapes. This allowed tissue sub-components to be discerned in PARS imagery of both unstained human breast tissue on slides and freshly resected murine brain tissue without the need to use multiple excitation wavelengths nor have any prior knowledge of the time-domain characteristics associated with individual components. The contributions made in this thesis represent significant steps towards the use of PARS for a broad range of applications where unmixing, or more specifically, discerning underlying components of the imaged target is required — beyond sO2 estimation or emulation of standard histological techniques. Furthermore, the improved understanding of how SRS can be used to generate additional excitation wavelengths opens the door to imaging an abundance of bio-molecules, thus broadening the scope and richness of the gamut of targets that PARS is capable of imaging