Posterior Probability Modeling and Image Classification for Archaeological Site Prospection: Building a Survey Efficacy Model for Identifying Neolithic Felsite Workshops in the Shetland Islands

The application of custom classification techniques and posterior probability modeling (PPM) using Worldview-2 multispectral imagery to archaeological field survey is presented in this paper. Research is focused on the identification of Neolithic felsite stone tool workshops in the North Mavine region of the Shetland Islands in Northern Scotland. Sample data from known workshops surveyed using differential GPS are used alongside known non-sites to train a linear discriminant analysis (LDA) classifier based on a combination of datasets including Worldview-2 bands, band difference ratios (BDR) and topographical derivatives. Principal components analysis is further used to test and reduce dimensionality caused by redundant datasets. Probability models were generated by LDA using principal components and tested with sites identified through geological field survey. Testing shows the prospective ability of this technique and significance between 0.05 and 0.01, and gain statistics between 0.90 and 0.94, higher than those obtained using maximum likelihood and random forest classifiers. Results suggest that this approach is best suited to relatively homogenous site types, and performs better with correlated data sources. Finally, by combining posterior probability models and least-cost analysis, a survey least-cost efficacy model is generated showing the utility of such approaches to archaeological field survey.

Coupling short-term (B2G model) and long-term (g-function) models for ground source heat exchanger simulation in TRNSYS. Application in a real installation

Ground-source heat pump (GSHP) systems represent one of the most promising techniques for heating and cooling in buildings. These systems use the ground as a heat source/sink, allowing a better efficiency thanks to the low variations of the ground temperature along the seasons. The ground-source heat exchanger (GSHE) then becomes a key component for optimizing the overall performance of the system. Moreover, the short-term response related to the dynamic behaviour of the GSHE is a crucial aspect, especially from a regulation criteria perspective in on/off controlled GSHP systems. In this context, a novel numerical GSHE model has been developed at the Instituto de Ingeniería Energética, Universitat Politècnica de València. Based on the decoupling of the short-term and the long-term response of the GSHE, the novel model allows the use of faster and more precise models on both sides. In particular, the short-term model considered is the B2G model, developed and validated in previous research works conducted at the Instituto de Ingeniería Energética. For the long-term, the g-function model was selected, since it is a previously validated and widely used model, and presents some interesting features that are useful for its combination with the B2G model. The aim of the present paper is to describe the procedure of combining these two models in order to obtain a unique complete GSHE model for both short- and long-term simulation. The resulting model is then validated against experimental data from a real GSHP installation.

Identification of Microturbine Model for Long-term Dynamic Analysis of Distribution Networks

As one of the most successfully commercialized distributed energy resources, the long-term effects of microturbines (MTs) on the distribution network has not been fully investigated due to the complex thermo-fluid-mechanical energy conversion processes. This is further complicated by the fact that the parameter and internal data of MTs are not always available to the electric utility, due to different ownerships and confidentiality concerns. To address this issue, a general modeling approach for MTs is proposed in this paper, which allows for the long-term simulation of the distribution network with multiple MTs. First, the feasibility of deriving a simplified MT model for long-term dynamic analysis of the distribution network is discussed, based on the physical understanding of dynamic processes that occurred within MTs. Then a three-stage identification method is developed in order to obtain a piecewise MT model and predict electro-mechanical system behaviors with saturation. Next, assisted with the electric power flow calculation tool, a fast simulation methodology is proposed to evaluate the long-term impact of multiple MTs on the distribution network. Finally, the model is verified by using Capstone C30 microturbine experiments, and further applied to the dynamic simulation of a modified IEEE 37-node test feeder with promising results.

TRPV2 Channels Contribute to Stretch-Activated Cation Currents and Myogenic Constriction in Retinal Arterioles

Purpose: Activation of the transient receptor potential channels, TRPC6, TRPM4, and TRPP1 (PKD2), has been shown to contribute to the myogenic constriction of cerebral arteries. In the present study we sought to determine the potential role of various mechanosensitive TRP channels to myogenic signaling in arterioles of the rat retina.

Methods: Rat retinal arterioles were isolated for RT-PCR, Fura-2 Ca2+ microfluorimetry, patch-clamp electrophysiology, and pressure myography studies. In some experiments, confocal immunolabeling of wholemount preparations was used to examine the localization of specific mechanosensitive TRP channels in retinal vascular smooth muscle cells (VSMCs).

Results: Reverse transcription-polymerase chain reaction analysis demonstrated mRNA expression for TRPC1, M7, V1, V2, V4, and P1, but not TRPC6 or M4, in isolated retinal arterioles. Immunolabeling revealed plasma membrane, cytosolic and nuclear expression of TRPC1, M7, V1, V2, V4, and P1 in retinal VSMCs. Hypoosmotic stretch-induced Ca2+ influx in retinal VSMCs was reversed by the TRPV2 inhibitor tranilast and the nonselective TRPP1/V2 antagonist amiloride. Inhibitors of TRPC1, M7, V1, and V4 had no effect. Hypoosmotic stretch-activated cation currents were similar in Na+ and Cs+ containing solutions suggesting no contribution by TRPP1 channels. Direct plasma membrane stretch triggered cation current activity that was blocked by tranilast and specific TRPV2 pore-blocking antibodies and mimicked by the TRPV2 activator, Δ9-tetrahydrocannabinol. Preincubation of retinal arterioles with TRPV2 blocking antibodies prevented the development of myogenic tone.

Conclusions: Our results suggest that retinal VSMCs express a range of mechanosensitive TRP channels, but only TRPV2 appears to contribute to myogenic signaling in this vascular bed.