Using computational learning for non-melanoma skin cancer and actinic keratosis near-infrared hyperspectral signature classification.

Background: The early detection of Non-Melanoma Skin Cancer (NMSC) is essential to ensure patients receive the most effective treatment. Diagnostic screening tools for NMSC are crucial due to high confusion rates with other types of skin lesions, such as Actinic Keratosis. Nevertheless, current means of diagnosing and screening patients rely on either visual criteria, that are often conditioned by subjectivity and experience, or highly invasive, slow, and costly methods, such as histological diagnoses.

Near-infrared hyperspectral imaging and robust statistics for in vivo non-melanoma skin cancer and actinic keratosis characterisation.

One of the most common forms of cancer in fair skinned populations is Non-Melanoma Skin Cancer (NMSC), which primarily consists of Basal Cell Carcinoma (BCC), and cutaneous Squamous Cell Carcinoma (SCC). Detecting NMSC early can significantly improve treatment outcomes and reduce medical costs. Similarly, Actinic Keratosis (AK) is a common skin condition that, if left untreated, can develop into more serious conditions, such as SCC.

Evidence from personal ornaments suggest nine distinct cultural groups between 34,000 and 24,000 years ago in Europe.

Mechanisms governing the relationship between genetic and cultural evolution are the subject of debate, data analysis and modelling efforts. Here we present a new georeferenced dataset of personal ornaments worn by European hunter-gatherers during the so-called Gravettian technocomplex (34,000-24,000 years ago), analyse it with multivariate and geospatial statistics, model the impact of distance on cultural diversity and contrast the outcome of our analyses with up-to-date palaeogenetic data. We demonstrate that Gravettian ornament variability cannot be explained solely by isolation-by-distance.

Recruiting a skeleton crew-Methods for simulating and augmenting paleoanthropological data using Monte Carlo based algorithms.

Objectives: Data collection is a major hindrance in many types of analyses in human evolutionary studies. This issue is fundamental when considering the scarcity and quality of fossil data. From this perspective, many research projects are impeded by the amount of data available to perform tasks such as classification and predictive modeling.

: A Novel Software to Register and Analyze Bone Surface Modifications Based on Three-Dimensional Documentation.

The study of bone surface modifications (BSM) is crucial in understanding site formation processes and the identification of the causal agent behind bone assemblages in the fossil record. In that line, many efforts have been made to generate referential models based on feeding experiments and human butchery simulations that can then be used to interpret the patterns observed in archaeological and paleontological sites. Considering these needs, we developed a novel open-access three-dimensional (3D) software called for the study of BSM distribution patterns on limb long bones.

Computer vision supports primary access to meat by early Homo 1.84 million years ago.

Human carnivory is atypical among primates. Unlike chimpanzees and bonobos, who are known to hunt smaller monkeys and eat them immediately, human foragers often cooperate to kill large animals and transport them to a safe location to be shared. While it is known that meat became an important part of the hominin diet around 2.

A Novel Approach for the Shape Characterisation of Non-Melanoma Skin Lesions Using Elliptic Fourier Analyses and Clinical Images.

The early detection of Non-Melanoma Skin Cancer (NMSC) is crucial to achieve the best treatment outcomes. Shape is considered one of the main parameters taken for the detection of some types of skin cancer such as melanoma. For NMSC, the importance of shape as a visual detection parameter is not well-studied.

Deep Convolutional Neural Support Vector Machines for the Classification of Basal Cell Carcinoma Hyperspectral Signatures.

Non-melanoma skin cancer, and basal cell carcinoma in particular, is one of the most common types of cancer. Although this type of malignancy has lower metastatic rates than other types of skin cancer, its locally destructive nature and the advantages of its timely treatment make early detection vital. The combination of multispectral imaging and artificial intelligence has arisen as a powerful tool for the detection and classification of skin cancer in a non-invasive manner.

A case of hominin scavenging 1.84 million years ago from Olduvai Gorge (Tanzania).

Meat eating is one of the hallmarks of human evolution. It has been linked to the beginning of stone tool use, to physiological changes leading to crucial anatomical transformations defining our genus, and to new socioreproductive and cognitive behaviors. Uncontroversial evidence of meat eating goes back to 2.

Hyperspectral imaging and robust statistics in non-melanoma skin cancer analysis.

Non-Melanoma skin cancer is one of the most frequent types of cancer. Early detection is encouraged so as to ensure the best treatment, Hyperspectral imaging is a promising technique for non-invasive inspection of skin lesions, however, the optimal wavelengths for these purposes are yet to be conclusively determined. A visible-near infrared hyperspectral camera with an ad-hoc built platform was used for image acquisition in the present study.

Taphonomic and spatial analyses from the Early Pleistocene site of Venta Micena 4 (Orce, Guadix-Baza Basin, southern Spain).

Venta Micena is an area containing several palaeontological sites marking the beginning of the Calabrian stage (Early Pleistocene). The richness of the fossil accumulation including species of Asian, African and European origin, makes Venta Micena a key site for the the palaeoecological and palaeoenvironmental study of southern Europe during the Early Pleistocene. Thus, research has been focused on Venta Micena 3, which was originally interpreted as a single palaeosurface associated with a marshy context, in which most of the fauna was accumulated by Pachycrocuta brevirostris.

Developments in data science solutions for carnivore tooth pit classification.

Competition for resources is a key question in the study of our early human evolution. From the first hominin groups, carnivores have played a fundamental role in the ecosystem. From this perspective, understanding the trophic pressure between hominins and carnivores can provide valuable insights into the context in which humans survived, interacted with their surroundings, and consequently evolved.

Towards a Combined Use of Geophysics and Remote Sensing Techniques for the Characterization of a Singular Building: "El Torreón" (the Tower) at Ulaca (Solosancho, Ávila, Spain).

This research focuses on the study of the ruins of a large building known as "El Torreón" (the Tower), belonging to the Ulaca (Solosancho, Province of Ávila, Spain). Different remote sensing and geophysical approaches have been used to fulfil this objective, providing a better understanding of the building's functionality in this town, which belongs to the Late Iron Age (ca. 300-50 BCE).

A 3D taphonomic model of long bone modification by lions in medium-sized ungulate carcasses.

Here, we present the first three-dimensional taphonomic analysis of a carnivore-modified assemblage at the anatomical scale of the appendicular skeleton. A sample of ten carcasses composed of two taxa (zebra and wildebeest) consumed by wild lions in the Tarangire National Park (Tanzania) has been used to determine element-specific lion damage patterns. This study presents a novel software for the 3D spatial documentation of bone surface modifications at the anatomical level.

Obtaining new resolutions in carnivore tooth pit morphological analyses: A methodological update for digital taphonomy.

Modern day investigation in fields of archaeology and palaeontology can be greatly characterised by an exponential growth of integrated new technologies, nevertheless, while these advances are of great significance to multiple lines of research, their evaluation and update over time is equally as important. Here we present an application of inter and intra-observer analysis in taphonomy based geometric morphometrics, employing robust non-parametric statistical analyses for the study of experimental carnivore tooth pit morphologies. To fully understand the influence of measurement errors in the collection of this data, our statistical assessment was performed on fully superimposed, partially superimposed and raw landmark coordinates collected from 3D surface scanning.

Application of artificially intelligent systems for the identification of discrete fossiliferous levels.

The separation of discrete fossiliferous levels within an archaeological or paleontological site with no clear stratigraphic horizons has historically been carried out using qualitative approaches, relying on two-dimensional transversal and longitudinal projection planes. Analyses of this type, however, can often be conditioned by subjectivity based on the perspective of the analyst. This study presents a novel use of Machine Learning algorithms for pattern recognition techniques in the automated separation and identification of fossiliferous levels.

The use of canid tooth marks on bone for the identification of livestock predation.

Historically wolves and humans have had a conflictive relationship which has driven the wolf to extinction in some areas across Northern America and Europe. The last decades have seen a rise of multiple government programs to protect wolf populations. Nevertheless, these programs have been controversial in rural areas, product of the predation of livestock by carnivores.

Testing accuracy in 2D and 3D geometric morphometric methods for cut mark identification and classification.

The analysis of bone surface modifications (BSMs) is a prominent part of paleoanthropological studies, namely taphonomic research. Behavioral interpretations of the fossil record hinge strongly upon correct assessment of BSMs. With the significant impact of microscopic analysis to the study of BSMs, multiple authors have discussed the reliability of these technological improvements for gaining resolution in BSM discrimination.