Early herding practices revealed through organic residue analysis of pottery from the early Neolithic rock shelter of Mala Triglavca, Slovenia

A collection of pottery from the early Neolithic site of Mala Triglavca was analysed with the aim of obtaining insights into vessel use and early animal domestication and husbandry practices in the Adriatic region. Total lipid extracts were submitted to gas chromatography (GC), GC-mass spectrometry (GC-MS) and GC-combustion-isotope ratio MS (GC-C-IRMS) in order to obtain molecular and stable carbon isotope signatures as the basis for determining the nature and origins of the residues. The extracts were dominated by degraded animal fats. The majority (70%) of the total lipid extracts displayed intact triacylglycerol distributions attributable to ruminant adipose and dairy fats, which were subsequently confirmed through C16:0 and C18:0 fatty acid δ13C values.Izbor keramičnih vzorcev iz zgodnje neolitskega najdišča Mala Triglavca je bil analiziran z namenom, da bi pridobili dodatne informacije o uporabi keramičnih posod ter značaju zgodnje živinoreje na Jadranskem prostoru. Lipidne ekstrakte vzorcev smo analizirali s pomočjo plinske kromatografije (GC), plinske kromatografije sklopljene z masno spektrometrijo (GC/MS) in plinske kromatografije sklopljene s sežigno masno spektrometrijo razmerij izotopov (GC-C-IRMS). V lipidnih ekstraktih so prevladovale živalske maščobe. V večini (70%) lipidnih ekstraktov so bile prisotne nespremenjene trigliceridne distribucije, ki jih lahko pripišemo tolščnim ter mlečnim maščobam prežvekovalcev. Lipidni izvor je bil nadalje potrjen z δ13C vrednostmi prostih maščobnih kislin C16:0 in C18:0

Early herding practices revealed through organic residue analysis of pottery from the early Neolithic rock shelter of Mala Triglavca, Slovenia

A collection of pottery from the early Neolithic site of Mala Triglavca was analysed with the aim of obtaining insights into vessel use and early animal domestication and husbandry practices in the Adriatic region. Total lipid extracts were submitted to gas chromatography (GC), GC-mass spectrometry (GC-MS) and GC-combustion-isotope ratio MS (GC-C-IRMS) in order to obtain molecular and stable carbon isotope signatures as the basis for determining the nature and origins of the residues. The extracts were dominated by degraded animal fats. The majority (70%) of the total lipid extracts displayed intact triacylglycerol distributions attributable to ruminant adipose and dairy fats, which were subsequently confirmed through C16:0 and C18:0 fatty acid δ13C values

Wrappings of power: a woman’s burial in cattle hide at Langwell Farm, Strath Oykel

A well-preserved burial, discovered during peat clearing on Langwell Farm in Strath Oykel, Easter Ross, consisted of a stone cist that held the skeleton of a woman who had died in 2200–1960 cal BC. Although the cist contents were disturbed and partly removed before archaeological investigation took place, the burial rite can be interpreted to some extent. The woman, who died in her late 20s, had been wrapped in brown cattle hide, and wooden and woven objects were placed with her body. Periodic waterlogging created conditions that allowed the rare, partial preservation of the organic materials. Analysis of bone histology indicated that decay of the human remains had been arrested, either by deliberate mummification or waterlogging. The cist had been set into a low knoll on the valley floor and it may have been covered with a low cairn or barrow. This spot had been the site of a fire several hundred years earlier, and it may have been a node on a cross-country route linking east and west coasts in the Early Bronze Age. The use of animal hide suggests the creation and use of particular identities, linking the dead to ancestors and to powerful spiritual properties attributed to the natural world. The work was carried out for Historic Scotland under the Human Remains Call-off Contract

Widespread exploitation of the honeybee by early Neolithic farmers.

This is the author's version of an article subsequently published in Nature. The definitive version is available from the publisher via: doi: 10.1038/nature15757.Copyright © 2015, Rights Managed by Nature Publishing GroupThe pressures on honeybee (Apis mellifera) populations, resulting from threats by modern pesticides, parasites, predators and diseases, have raised awareness of the economic importance and critical role this insect plays in agricultural societies across the globe. However, the association of humans with A. mellifera predates post-industrial-revolution agriculture, as evidenced by the widespread presence of ancient Egyptian bee iconography dating to the Old Kingdom (approximately 2400 BC). There are also indications of Stone Age people harvesting bee products; for example, honey hunting is interpreted from rock art in a prehistoric Holocene context and a beeswax find in a pre-agriculturalist site. However, when and where the regular association of A. mellifera with agriculturalists emerged is unknown. One of the major products of A. mellifera is beeswax, which is composed of a complex suite of lipids including n-alkanes, n-alkanoic acids and fatty acyl wax esters. The composition is highly constant as it is determined genetically through the insect's biochemistry. Thus, the chemical 'fingerprint' of beeswax provides a reliable basis for detecting this commodity in organic residues preserved at archaeological sites, which we now use to trace the exploitation by humans of A. mellifera temporally and spatially. Here we present secure identifications of beeswax in lipid residues preserved in pottery vessels of Neolithic Old World farmers. The geographical range of bee product exploitation is traced in Neolithic Europe, the Near East and North Africa, providing the palaeoecological range of honeybees during prehistory. Temporally, we demonstrate that bee products were exploited continuously, and probably extensively in some regions, at least from the seventh millennium cal BC, likely fulfilling a variety of technological and cultural functions. The close association of A. mellifera with Neolithic farming communities dates to the early onset of agriculture and may provide evidence for the beginnings of a domestication process.Natural Environment Research Council (NERC)English HeritageEuropean Research Council (ERC)Leverhulme TrustMinistère de la Culture et de la CommunicationMinistère de l’Enseignement Supérieur et de la RechercheRoyal SocietyWellcome Trus

Signatures of degraded body tissues and environmental conditions in grave soils from a Roman and an Anglo-Scandinavian age burial from Hungate, York

Despite the importance of human burials in archaeological investigations of past peoples and their lives, the soil matrix that accommodates the remains is rarely considered, attention being focused mainly on visible features. The decomposition of a buried corpse and associated organic matter influences both the organic composition and, directly or indirectly, the microstructure of the burial matrix, producing signatures that could be preserved over archaeological timescales. If preserved, such signatures have potential to reveal aspects of the individual’s lifestyle and cultural practices as well as providing insights into taphonomic processes. Using organic chemical analysis and soil micromorphology we have identified organic signatures and physical characteristics relating to the presence of the body, and its decomposition in grave soils associated with two human skeletons (one Roman age and one Anglo-Scandinavian age) from Hungate, York, UK. The organic signatures, including contributions from body tissues, gut contents, bone degradation and input from microbiota, exhibit spatial variations with respect to anatomical location and features of the immediate burial environment. In the Roman grave broad changes in redox conditions associated with the decomposition of the corpse and disturbance from the excavation and use of an Anglo-Scandinavian age cess pit that partially cuts the grave were evident. Leachate from the cess pit was shown to exacerbate the degradation of the skeletal remains in the regions closest to it, also degrading and depleting spherulites in the soil, through decalcification of the bone and liberation of bone-derived cholesterol into the soil matrix. The findings from this work have implications for future archaeo- and contemporary forensic investigations of buried human remains

Avtomatizirano planiranje z induciranimi kvalitativnimi modeli v dinamičnih robotskih domenah

Qualitative modeling enables autonomous learning agents to quickly learn generalized models from small samples of numerical data. By abstracting away certain numerical information, qualitative models provide better insights into the operating principles of a robotic system in comparison to traditional numerical models. This is of special interest to the areas of AI where experts can benefit from insights discovered by AI, or need to check whether AI\u27s decisions comply with human common sense. Planning with qualitative models is challenging in the sense that little or no numerical information is given with the model. Generalized plans or control strategies can be devised through the means of qualitative simulation. While these can provide further insights into the possible system\u27s behaviors, no known method is able to execute such plans without some additional trial-and-error type of numerical training. This dissertation proposes a general-purpose framework for qualitative planning in robotics domains, with a novel method to execute qualitative plans without the need for additional training. The execution adapts to the specific numerical properties of the system in real-time, and is usually successful on the first run, while its performance significantly improves on the second run. This way a working, although typically a suboptimal, solution can quickly be provided. The proposed methods are demonstrated on problem domains that have previously not been attempted qualitatively, or to a more limited extent.Kvalitativno modeliranje omogoča avtonomnim agentom hitro učenje posplošenih modelov iz majhnih naborov numeričnih podatkov. V primerjavi s klasičnimi numeričnimi modeli, kvalitativni modeli nudijo bolj jasen vpogled v principe upravljanja robotskega sistema, in sicer tako, da abstrahirajo določene numerične informacije. To je posebej zanimivo na področjih, kjer ugotovitve umetne inteligence lahko pripomorejo k razumevanju nekega probleme oz. kjer je potrebno preveriti skladnost odločitev umetne inteligence s praktičnim razumevanjem problema. Planiranje z uporabo kvalitativih modelov predstavlja poseben izziv, saj ti modeli vsebujejo malo ali nič numeričnih informacij. Z uporabo kvalitativne simulacije lahko izpeljemo posplošene plane ali strategije vodenja, ki omogočajo nadaljnje vpoglede v možna obnašanje sistema. Vendar pa ni znane metode, ki bi takšne plane lahko izvedla brez dodatnega numeričnega učenja s poskušanjem. V tej disertaciji predlagamo splošnonamenski sklop metod kvalitativnega planiranja ter izvajanja kvalitativnih planov v robotskih domenah, ki za izvajanje ne zahteva dodatnega učenja. Izvajanje se prilagodi na specifične numerične lastnosti sistema v realnem času in je običajno uspešno že prvič, ob ponovitvi pa se rezultat bistveno izboljša. Na ta način lahko hitro pridemo do delujoče, čeprav neoptimalne, rešitve. Predlagane metode demonstriramo na problemskih domenah, ki še niso bile obravnavane kvalitativno, ali pa v bolj omejenem obsegu

Distributed computation of homology in wireless sensor networks

Wireless sensor networks are networks of small and simple autonomous devices or nodes which perform measurements in the environment where they are located. The data obtained is processed and transmitted over a wireless communication channel to other neighboring nodes. Individual measurements are performed in a limited geometric range around sensors therefore random deployment of nodes may cause some areas to remain uncovered. Since wireless sensor network is capable of distributed processing it is able to autonomously check the coverage of its domain even if no information about geometric position and orientation of its nodes is available. Methods used to check the coverage using only connectivity information of the network have been introduced only a few years ago. The general idea is based on principles of computational topology. Using the connectivity graph of the network a simplicial complex called Rips complex is built which has been shown to contain information about the holes in the measurement domain. To capture this information, homology is used which produces a sequence of homology groups that we can use to derive a computable criterion for coverage verification. First algorithms to compute homology in wireless sensor networks have been centralized. In centralized approach all the connectivity data has to be gathered in one place where the processing is then carried out. The unit on which such algorithm is implemented requires high processing capabilities as computation of homology groups typically applies operations on large matrices. Networks without a central processing unit usually cannot run such algorithms since one node alone lacks the required processing performance. Divide-and-conquer approaches turned out to be the most efficient way to compute homology distributively. The network is divided into smaller parts where each node takes over the computation of its neighborhood. The main drawback of these algorithms are complicated procedures for dividing the network which usually require information about the edge of the domain called the fence. Since topology of the fence is limited to a cycle, such algorithms are not expected to work properly in all network topologies. In this thesis we present an algorithm for distributed computation of homology in wireless sensor networks which does not require a fence and works in any network topology. We take the approach of constructing larger network segments from smaller ones, capturing homology of the union during the process. We use a spanning tree of the network as a predefined path for merging, following the direction from leaves to the root. Initial network segments are small enough not to contain any holes. The criterion for detecting holes in the union of two segments was derived from the Mayer-Vietoris sequence and extended to fit the merging of larger sets of segments. Correctness of the algorithm has been tested and validated by extensive simulations. We had also measured its computational and communicational complexity. According to our results we conclude that the algorithm is suitable for use in real wireless sensor networks