Modelling the Performance of Single-Photon Counting Kinetic Inductance Detectors

We present the first published results of near-infrared single-photon detection in aluminium lumped element kinetic inductance detectors (LEKIDs). Using aluminium as a well-understood material that follows conventional superconductor theory, we discuss and validate a model that describes the energy-resolving performance of a LEKID to single-photon absorption events. We also discuss data analysis techniques used to extract single-photon detections from noisy data. We measure an energy resolution of 662 meV for a 1550 nm photon source which is in close agreement to our model predictions for this non-optimised device limited by generation–recombination noise.     

Sociotechnical issues in the implementation of imaging technology

This study examined the implementation of imaging technology into two public sector organizations in the Midwest in the USA. The aims of the study were to analyze the impact of imaging technology on job characteristics and quality of working life, and the influence of the technological change process on employees and organizations. Quantitative and qualitative data were collected using questionnaire surveys and structured and semi-structured interviews. Results showed that imaging users reported more problems with technology and less job satisfaction than employees who were still using their 'old' computer systems. In addition, imaging users in the organization that utilized end user participation in the implementation of their imaging system rated their imaging systems better and reported higher job satisfaction than imaging users in the organization that did not incorporate end user participation in the implementation of the system. The results are discussed in terms of the importance of the technology implementation/ change process, and future directions for research are provided.     

Proteins variations in Listeria monocytogenes exposed to high salinities

Listeria monocytogenes Scott A grown in the minimal chemically defined medium M6LT was challenged to a concentration of either 35 or 65 g l(-1) of NaCl for 1 h in the presence of a [35S]cysteine-[35S]methionine labelling mix. The protein patterns were analysed by 2D-electrophoresis in the two conditions and isoosmotic condition (5 g l(-1) of NaCl in M6LT). A great number of proteins which were synthesized under isoosmotic conditions were either completely repressed or expressed at a reduced level, at 65 g l(-1) and to a lesser extent at 35 g l(-1) of NaCl. At 35 g l(-1) of NaCl, six proteins were up-regulated, five proteins showed no change in expression level and five were repressed. Among the proteins up-regulated at 35 g l(-1) of NaCl, a single one (18.7 kDa, pI 5.05) was up-regulated at 65 g l(-1) too. We observed 21 proteins which were repressed at 65 g l(-1) of NaCl, among which 11 completely disappeared. Some of the up-regulated proteins have characteristics of molecular weight and isoelectric point close to those of stress proteins reported elsewhere: the protein induced both at 35 and 65 g l(-1) might correspond to a previously proposed universal stress protein of Listeria. Some proteins which were repressed at 65 g l(-1) have molecular weights close to those of virulence proteins.     

Identification of ritual blood in African artifacts using TOF-SIMS and synchrotron radiation microspectroscopies

A new protocol is implemented to demonstrate the presence of blood in the patina of African art objects from Mali. Divided into three steps, the protocol first consists in demonstrating the presence of proteins and localizing them in the sample's cross sections using time-of-flight secondary ion mass spectrometry (TOF-SIMS) and synchrotron-based infrared microspectrometry (microFT-IR). In a second time, TOF-SIMS is used to investigate heme, which is a blood marker. If heme is missing, which could mean that it is too degraded to be detected, X-ray microfluorescence (microXRF) and X-ray absorption near-edge microspectroscopy (microXANES) are used to prove the presence of iron in the protein area and to get a fingerprint of its chemical environment. This permits us thus to demonstrate that iron is indeed linked with proteins and not with mineral phases of the sample. Coupled with the ritual context of the objects, this constitutes a proof of the use of blood. Thanks to this protocol, which has the major advantage of avoiding false positive results, the presence of blood has been demonstrated in seven out of the eight studied samples.     

A numerical hydrodynamic and thermal characterization of an inter-strata liquid cooling solution for 3D ICs

A novel integrated thermal management solution is proposed to alleviate hot spots in a contemporary 3D IC architecture. The solution employs a series of integrated microchannels, interconnected through each stratum by through silicon fluidic vias (TSFVs), and permits the transfer of heat, via a coolant, from hot to cold zones. This microfluidic system is driven by an integrated AC electrokinetic pump embedded in the channel walls. Recent advancements in electrokinetic micropump technology have allowed greater increases in fluid velocity (mm/s) while operating within the voltage constraints of a 3D IC. This paper presents a 2D simulation of an electrokinetic micropump operating at V_pp = 1.5 V in a 40 μm channel and examines its velocity profile for six frequencies in the range 100 ≤ ω ≤ 100 MHz. An optimum frequency of 100 kHz was established within this range and this was further examined with a constant heat flux of 186 W/cm2 imposed on the wall for an inlet fluid temperature of 40°C. Temperature profiles are presented at the channel-silicon interface and compared with theory.     

Reservoir Management Using a Network Flow Optimization Model Considering Quadratic Convex Cost Functions on Arcs

The allocation of water resources between different users is a hard task for water managers because they must deal with conflicting objectives. The main objective is to obtain the most accurate distribution of the resource and the associated circulating flows through the system. This induces the need for a river basin optimization model that provides optimized results. This article presents a network flow optimization model to solve the water allocation problem in water resource systems. Managing a water system consists in providing water in the right proportion, at the right place and at the right time. Time expanded network allows to take into consideration the temporal dimension in the decision making. Since linear cost functions on arcs present many limitations and are not realistic, quadratic convex cost functions on arcs are considered here. The optimization algorithm developed herein extend the cycle canceling algorithm developed for linear cost functions. The methodology is applied to manage the three reservoirs of La Haute-Vilaine’s watershed located in the north west of France to protect a three vulnerable areas from flooding. The results obtained with the algorithm are compared to a reference scenario which consists in considering reservoirs transparent. The results show that the algorithm succeeds in managing the reservoir releases efficiently and keeps the flow rates below the vigilance flow in the vulnerable areas.     

Pre-survey suitability evaluation of the differential synthetic aperture radar interferometry method for landslide monitoring

The active remote-sensing technique differential radar interferometry (D-InSAR) is a powerful method for detection and deformation monitoring of landslides. But the radar-specific imaging geometry causes specific spatial distortions in radar images (as e.g. the layover and shadowing effect), which have a negative impact on the suitability of these images for D-InSAR applications. To address this issue, we present a geographical information system (GIS) procedure to accurately predict the areas in which layover and shadowing will occur, before the area of interest is recorded by radar. Additionally, the percentage of measurability of movement of a potential landslide can be ascertained. In the third part of the GIS procedure, the main types of land cover are classified in regard to their influence on applicability of the D-InSAR technique, depending on the characteristics of the sensor used. The results of the analyses are objective pre-survey estimation of the potential applicability of the D-InSAR technique for landslide monitoring prior to the costly investment of a radar survey.     

Evaluation of Localized Semantics: Data, Methodology, and Experiments

We present a new data set of 1014 images with manual segmentations and semantic labels for each segment, together with a methodology for using this kind of data for recognition evaluation. The images and segmentations are from the UCB segmentation benchmark database (Martin et al., in International conference on computer vision, vol. II, pp. 416–421, 2001). The database is extended by manually labeling each segment with its most specific semantic concept in WordNet (Miller et al., in Int. J. Lexicogr. 3(4):235–244, 1990). The evaluation methodology establishes protocols for mapping algorithm specific localization (e.g., segmentations) to our data, handling synonyms, scoring matches at different levels of specificity, dealing with vocabularies with sense ambiguity (the usual case), and handling ground truth regions with multiple labels. Given these protocols, we develop two evaluation approaches. The first measures the range of semantics that an algorithm can recognize, and the second measures the frequency that an algorithm recognizes semantics correctly. The data, the image labeling tool, and programs implementing our evaluation strategy are all available on-line (kobus.ca//research/data/IJCV_2007). We apply this infrastructure to evaluate four algorithms which learn to label image regions from weakly labeled data. The algorithms tested include two variants of multiple instance learning (MIL), and two generative multi-modal mixture models. These experiments are on a significantly larger scale than previously reported, especially in the case of MIL methods. More specifically, we used training data sets up to 37,000 images and training vocabularies of up to 650 words. We found that one of the mixture models performed best on image annotation and the frequency correct measure, and that variants of MIL gave the best semantic range performance. We were able to substantively improve the performance of MIL methods on the other tasks (image annotation and frequency correct region labeling) by providing an appropriate prior.     

A search space “cartography” for guiding graph coloring heuristics

We present a search space analysis and its application in improving local search algorithms for the graph coloring problem. Using a classical distance measure between colorings, we introduce the following clustering hypothesis: the high quality solutions are not randomly scattered in the search space, but rather grouped in clusters within spheres of specific diameter. We first provide intuitive evidence for this hypothesis by presenting a projection of a large set of local minima in the 3D space. An experimental confirmation is also presented: we introduce two algorithms that exploit the hypothesis by guiding an underlying Tabu Search (TS) process. The first algorithm (TS-Div) uses a learning process to guide the basic TS process toward as-yet-unvisited spheres. The second algorithm (TS-Int) makes deep investigations within a bounded region by organizing it as a tree-like structure of connected spheres. We experimentally demonstrate that if such a region contains a global optimum, TS-Int does not fail in eventually finding it. This pair of algorithms significantly outperforms the underlying basic TS algorithm; it can even improve some of the best-known solutions ever reported in the literature (e.g. for dsjc1000.9).