Test Excavations of a Stone Foundation at Ayr Mount Historic Site, Hillsborough, North Carolina

Technical Report No. 28, Research Laboratories of Archaeology, University of North Carolina at Chapel Hill. Reports in this series present the findings of archaeological surveys and test excavations completed by the RLA between 1983 and present

Sensor Data Qualification System (SDQS) Implementation Study

The Sensor Data Qualification System (SDQS) is being developed to provide a sensor fault detection capability for NASA s next-generation launch vehicles. In addition to traditional data qualification techniques (such as limit checks, rate-of-change checks and hardware redundancy checks), SDQS can provide augmented capability through additional techniques that exploit analytical redundancy relationships to enable faster and more sensitive sensor fault detection. This paper documents the results of a study that was conducted to determine the best approach for implementing a SDQS network configuration that spans multiple subsystems, similar to those that may be implemented on future vehicles. The best approach is defined as one that most minimizes computational resource requirements without impacting the detection of sensor failures

Discrete Data Qualification System and Method Comprising Noise Series Fault Detection

A Sensor Data Qualification (SDQ) function has been developed that allows the onboard flight computers on NASA s launch vehicles to determine the validity of sensor data to ensure that critical safety and operational decisions are not based on faulty sensor data. This SDQ function includes a novel noise series fault detection algorithm for qualification of the output data from LO2 and LH2 low-level liquid sensors. These sensors are positioned in a launch vehicle s propellant tanks in order to detect propellant depletion during a rocket engine s boost operating phase. This detection capability can prevent the catastrophic situation where the engine operates without propellant. The output from each LO2 and LH2 low-level liquid sensor is a discrete valued signal that is expected to be in either of two states, depending on whether the sensor is immersed (wet) or exposed (dry). Conventional methods for sensor data qualification, such as threshold limit checking, are not effective for this type of signal due to its discrete binary-state nature. To address this data qualification challenge, a noise computation and evaluation method, also known as a noise fault detector, was developed to detect unreasonable statistical characteristics in the discrete data stream. The method operates on a time series of discrete data observations over a moving window of data points and performs a continuous examination of the resulting observation stream to identify the presence of anomalous characteristics. If the method determines the existence of anomalous results, the data from the sensor is disqualified for use by other monitoring or control functions

A quality monitor and monitoring technique employing optically stimulated electron emission

A light source directs ultraviolet light onto a test surface and a detector detects a current of photoelectrons generated by the light. The detector includes a collector which is positively biased with respect to the test surface. Quality is indicated based on the photoelectron current. The collector is then negatively biased to replace charges removed by the measurement of a nonconducting substrate to permit subsequent measurements. Also, the intensity of the ultraviolet light at a particular wavelength is monitored and the voltage of the light source varied to maintain the light a constant desired intensity. The light source is also cooled via a gas circulation system. If the test surface is an insulator, the surface is bombarded with ultraviolet light in the presence of an electron field to remove the majority of negative charges from the surface. The test surface is then exposed to an ion field until it possesses no net charge. The technique described above is then performed to assess quality

Response of Congo Grass (Brachiaria ruziziensis L. Germain and Evard) to Nitrogen Fertilization on an Oxisol in Western Highlands Agro-ecological Zone of Cameroon

In the context of climate change, sustainable fertilization management can be achieved by the use of minimum external agricultural inputs capable of generating both economic and environmental benefits. In this regard, a study conducted in western highlands agro-ecological zone of Cameroon revealed the response of Brachiaria ruziziensis (an important cover crop and forage) to a range of nitrogen levels (0, 50, 100, 150, and 200 kgN.ha-1) combined with a constant level of P2O5 (100 kgN.ha-1) and K2O (50 kg%252Fha) evaluated using a randomized complete block design. The findings showed that in a regularly cultivated soil, Congo grass is capable of meeting its mineral needs by searching for them in strata of the soil below the cultural profile (0-25 cm). As a result, in comparison to non-fertilized units (27.75 t.ha-1), fertilized units did not provide a significant dry matter yield (P gt%253B 0.05). Despite the lack of a significant difference, the yield increased with the addition of nitrogen until it reached 100 kg%252Fha, and then decreased until it reached 200 kg N.ha-1. As a result, Congo grass should be used as a biological pump, bringing lixiviated minerals to the surface to favor soil fertility replenishment and shorten fallow period

Sequencing and analysis of the gene-rich space of cowpea

<p>Abstract</p> <p>Background</p> <p>Cowpea, <it>Vigna unguiculata </it>(L.) Walp., is one of the most important food and forage legumes in the semi-arid tropics because of its drought tolerance and ability to grow on poor quality soils. Approximately 80% of cowpea production takes place in the dry savannahs of tropical West and Central Africa, mostly by poor subsistence farmers. Despite its economic and social importance in the developing world, cowpea remains to a large extent an underexploited crop. Among the major goals of cowpea breeding and improvement programs is the stacking of desirable agronomic traits, such as disease and pest resistance and response to abiotic stresses. Implementation of marker-assisted selection and breeding programs is severely limited by a paucity of trait-linked markers and a general lack of information on gene structure and organization. With a nuclear genome size estimated at ~620 Mb, the cowpea genome is an ideal target for reduced representation sequencing.</p> <p>Results</p> <p>We report here the sequencing and analysis of the gene-rich, hypomethylated portion of the cowpea genome selectively cloned by methylation filtration (MF) technology. Over 250,000 gene-space sequence reads (GSRs) with an average length of 610 bp were generated, yielding ~160 Mb of sequence information. The GSRs were assembled, annotated by BLAST homology searches of four public protein annotation databases and four plant proteomes (<it>A. thaliana</it>, <it>M. truncatula, O. sativa</it>, and <it>P. trichocarpa</it>), and analyzed using various domain and gene modeling tools. A total of 41,260 GSR assemblies and singletons were annotated, of which 19,786 have unique GenBank accession numbers. Within the GSR dataset, 29% of the sequences were annotated using the Arabidopsis Gene Ontology (GO) with the largest categories of assigned function being catalytic activity and metabolic processes, groups that include the majority of cellular enzymes and components of amino acid, carbohydrate and lipid metabolism. A total of 5,888 GSRs had homology to genes encoding transcription factors (TFs) and transcription associated factors (TAFs) representing about 5% of the total annotated sequences in the dataset. Sixty-two (62) of the 64 well-characterized plant transcription factor (TF) gene families are represented in the cowpea GSRs, and these families are of similar size and phylogenetic organization to those characterized in other plants. The cowpea GSRs also provides a rich source of genes involved in photoperiodic control, symbiosis, and defense-related responses. Comparisons to available databases revealed that about 74% of cowpea ESTs and 70% of all legume ESTs were represented in the GSR dataset. As approximately 12% of all GSRs contain an identifiable simple-sequence repeat, the dataset is a powerful resource for the design of microsatellite markers.</p> <p>Conclusion</p> <p>The availability of extensive publicly available genomic data for cowpea, a non-model legume with significant importance in the developing world, represents a significant step forward in legume research. Not only does the gene space sequence enable the detailed analysis of gene structure, gene family organization and phylogenetic relationships within cowpea, but it also facilitates the characterization of syntenic relationships with other cultivated and model legumes, and will contribute to determining patterns of chromosomal evolution in the Leguminosae. The micro and macrosyntenic relationships detected between cowpea and other cultivated and model legumes should simplify the identification of informative markers for marker-assisted trait selection and map-based gene isolation necessary for cowpea improvement.</p

Relating spin-polarized STM imaging and inelastic neutron scattering in the van-der-Waals ferromagnet Fe3GeTe2

C.T. and P.W. acknowledge funding through Grants No. EP/R031924/1 and No. EP/T031441/1, L.C.R. through the Royal Commission for the Exhibition of 1851, I.B. through the International Max Planck Research School for Chemistry and Physics of Quantum Materials, and H.L. through the ISIS facility development studentship program.Van-der-Waals (vdW) ferromagnets have enabled the development of heterostructures assembled from exfoliated monolayers with spintronics functionalities, making it important to understand and ultimately tune their magnetic properties at the microscopic level. Information about the magnetic properties of these systems comes so far largely from macroscopic techniques, with little being known about the microscopic magnetic properties. Here, we combine spin-polarized scanning tunneling microscopy and quasi-particle interference imaging with neutron scattering to establish the magnetic and electronic properties of the metallic vdW ferromagnet Fe3GeTe2. By imaging domain walls at the atomic scale, we can relate the domain wall width to the exchange interaction and magnetic anisotropy extracted from the magnon dispersion as measured in inelastic neutron scattering, with excellent agreement between the two techniques. From comparison with Density Functional Theory calculations we can assign the quasi-particle interference to be dominated by spin-majority bands. We find a dimensional dichotomy of the bands at the Fermi energy: bands of minority character are predominantly two-dimensional in character, whereas the bands of majority character are three-dimensional. We expect that this will enable new design principles for spintronics devices.Publisher PDFPeer reviewe

Comparison of first principles and semi-empirical models of the structural and electronic properties of Ge1−xSnx alloys

We present and compare three distinct atomistic models—based on first principles and semi-empirical approaches—of the structural and electronic properties of Ge1−xSnx alloys. Density functional theory calculations incorporating Heyd–Scuseria–Ernzerhof (HSE), local density approximation (LDA) and modified Becke–Johnson (mBJ) exchange-correlation functionals are used to perform structural relaxation and electronic structure calculations for a series of Ge1−xSnx alloy supercells. Based on HSE calculations, a semi-empirical valence force field (VFF) potential and sp3s∗ tight-binding (TB) Hamiltonian are parametrised. Comparing the HSE, LDA+mBJ and VFF+TB models, and using the HSE results as a benchmark, we demonstrate that: (1) LDA+mBJ calculations provide an accurate first principles description of the electronic structure at reduced computational cost, (2) the VFF potential is sufficiently accurate to circumvent the requirement to perform first principles structural relaxation, and (3) VFF+TB calculations provide a good quantitative description of the alloy electronic structure in the vicinity of the band edges. Our results also emphasise the importance of Sn-induced band mixing in determining the nature of the conduction band structure of Ge1−xSnx alloys. The theoretical models and benchmark calculations we present inform and enable predictive, computationally efficient and scalable atomistic calculations for disordered alloys and nanostructures. This provides a suitable platform to underpin further theoretical investigations of the properties of this emerging semiconductor alloy