The detailed experimental investigation of the performance of a commercially available smart humidity sensor used for the measurement of relative humidity at elevated pressures (0.1–2 MPa) is reported. A dedicated set-up was developed for generating defined humidities in pressurized air. The measurements reveal that the pressure coefficient of the sensor deviation at a given relative humidity condition cannot be attributed solely to the enhancement factor of the humid air. For such microsensors, an additional sensor-specific pressure compensation factor was determined which is significant for precise measurements in applications with pressurized air.

The present work shows the fabrication of a printed RFID label using large-area printing processes, such as roto-screen and stencil printing, and the integration with advanced assembly methods of CMOS-based humidity and temperature sensors. The fabrication of the antenna and the PCB on flexible plastic substrates (i.e. polyethylene terephthalate - PET) was performed by means of roto-screen printing in combination with flash photonic sintering. This allows a high thermal transfer to the printed material, which is necessary for its sintering, while preserving the delicate polymeric substrate. Cost-effective and low temperature methods are also developed for the assembling of the components onto polymeric substrates. The electrical interconnections were stencil-printed with isotropic conductive adhesives by using laser-ablated stencil masks on polymer foils. Additionally, the label incorporates an RF remotely rechargeable thin film battery which is used for data logging. Finally, the roto-screen printing of copper oxide patterns and their reduction to copper by means of a Xenon flash photonic process is presented.

Several studies have shown that humans encode dynamic information such as rigid (e.g., rotations in depth) and non-rigid motion (e.g., facial expressions) for recognition purposes. Our goals in the present study were to extend previous work by using familiar objects which had a wide range of shapes and to determine possible influences of shape transformations on the encoding of dynamic information. We therefore tested the role of non-rigid shape changes in recognizing common animals and objects. To create these changes, we morphed between members of the same category (e.g., German shepherd and dachshund from the category dog). In a same/different categorization task, participants were shown a continuous morph sequence, followed by a static test image, and had to decide whether the image was from the same category as the morph sequence. Importantly, this paradigm does not presuppose that participants perform shape transformations. We found that participants responded more quickly if test images were sampled towards the end of the morph sequences, which replicates previous results with rigid rotations of objects and non-rigid facial expressions. This dynamic benefit was not a recency effect because it was eliminated when we scrambled the frame order of the morph sequences while preserving the continuity of the first and last 150 ms of the sequences. Overall these findings indicate that dynamic information plays a role in the recognition of diverse familiar shapes, and suggest a general mechanism that encodes continuous shape transformations.

The understanding of the nature of prosopagnosia - classically defined as a disorder of visual recognition specific to faces following brain damage - can inform about how visual face recognition is performed in the normal human brain. However, according to a long-standing alternative view of prosopagnosia, the prosopagnosic impairment would rather reflect a general difficulty for fine-grained discrimination in visually homogenous object categories (Faust, 1955; Damasio et al., 1982; Gauthier et al., 1999). We tested this hypothesis stringently with a well-known brain-damaged prosopagnosic patient (PS, Rossion et al., 2003), in three delayed matching experiments in which the visual similarity between the target and distractor was manipulated parametrically. We used 3 kinds of stimuli: novel 3D geometric shapes manipulated on single or multiple dimensions, morphed common objects (Hahn et al., 2009), and morphed photographs of a highly homogenous familiar category (cars). In every experiment, there was no evidence of a steeper increase of error rates and RTs with increasing levels of visual similarity for the patient, relative to normal observers. These data categorically rule out an account of acquired prosopagnosia in terms of a general problem of fine-grained discrimination in a visually homogenous category. Finally, a fourth experiment with faces showed that, compared to normal observers, the patient's impairment with morphed faces was best revealed at the easiest levels of discrimination, i.e. when individual faces differ clearly in global shape rather than in fine-grained details. Overall, these observations indicate that the alternative view of prosopagnosia as a more general impairment for fine-grained discrimination in visually homogeneous object categories does not hold.

Previous research suggested that the shape variability of objects from the same basic level category can be conceptualized by transformations which continuously change object shape (topological transformations). Experiments with line drawings (2D outline shapes) demonstrated that categorization latencies and error rates increase with increasing amount of shape transformation (Graf, 2001). We investigated whether these results generalize to more realistic gray-level images rendered from 3D object models. We also studied the effects of combined shape transformations and image-plane rotations on categorization performance. New category members were produced by morphing between objects from the same basic level category. Subjects were required to decide whether two sequentially presented objects belonged to the same basic level category or not. In Experiment 1 the amount of shape transformation was varied, while in Experiment 2 topological distance and image-plane orientation were manipulated. Categorization performance (latencies and accuracy) deteriorated systematically with increased shape transformation, both for upright (Exp. 1) and for rotated (Exp. 2) objects. Furthermore, Exp. 2 showed that categorization latencies increased with increasing amount of orientation change. There was no interaction between shape transformation and object orientation. The results confirm that categorization performance is systematically related to the amount of shape transformation, both for line drawings and gray-level images, as well as for upright and plane rotated objects. In addition, orientation dependency was corroborated with a basic level categorization task. Finally, categorization processes which compensate for shape changes and plane rotations seem to be independent, confirming previous evidence of independent effects for other combinations of spatial transformations (e.g. Lawson et al., 2000). The results support an image-based model of basic level categorization.

The development of low-cost, portable, metal-oxide gas sensors with high sensitivity, selectivity and material stability bears considerable scientific and commercial potential (Eranna et. al., 2004). Highly sensitive nanomaterial synthesis by direct, aerosol-based methods offer unique advantages in comparison to wet-routes including crack-free, highly pure deposits, and the fact that only few process steps are required (Madler et al., 2006). Sputtering, spray pyrolysis, cluster beam deposition, spray pulverization, combustion chemical vapor deposition (Liu et al., 2005) and, recently, flame spray pyrolysis (FSP) have been applied to yield nanostructured sensing layers. The FSP freshlydeposited layers, in particular, consist of highlyporous (98%), loosely interconnected, soft nanostructures (Madler et al., 2006). These, however, can be easily destroyed under mechanical stress and require stabilization. Here we present a CMOS-compatible, two-step method for deposition and in-situ mechanical stabilization of gas sensitive, metaloxide microlayers on wafer-level. Lace-like highly porous, Pt-doped SnO2 nanostructured layers are deposited at wafer-level on 69 microsensors. Second, these layers are converted in well-adhered, cauliflower-like structures (figure 1b, inset). The resulting sensor layer performance is characterized using the analytes CO and EtOH on microsensor devices. Figure 1 shows the resistance of a microsensor (inset a) with a nanostructured, trasparent SnO2/Pt layer (dXRD = 21.9 nm) (inset b) at different CO concentrations by heating the substrate surface at 450 °C. Below 20 ppm the microsensor response was in the range of seconds and a stable resistance was reached promptly (Fig. 1). Higher CO concentrations led to destabilization of the baseline due to the strong interaction between CO and Pt-doped SnO2 nanoparticle. The microsensor had a response of 1.7 for 1 ppm and 5.4 for 20 ppm CO. time, min 0 2 4 6 8 R es is ta nc e, O hm x 1 0 7 1 ppm CO 5 ppm

A flame process for in situ synthesis and micropatterned deposition of highly porous, self-assembled, lace-like nanostructured layers of pure or Pt-doped SnO2 is presented. These layers are stabilized in situ by rapid flame annealing that results in transparent cauliflower-like layers with strong adhesion to substrates containing integrated Circuitry, while exhibiting high CO sensitivity (f).

Tin oxide nanocrystals (5–10 nm) doped with silica (0–15 wt %) were made by flame‐spray‐pyrolysis direct deposition onto the sensing electrodes and in situ stabilization by rapid flame annealing. Although increased SiO2‐doping reduced the SnO2 crystal and grain size, its sensing performance to ethanol vapor (0.1–50 ppm) exhibited an optimum with respect to SiO2 content. The thermal stability and morphology of SiO2‐doped SnO2 nanoparticles were evaluated by sintering at 200–900 °C for 4–24 h in air. At low SiO2 content, sintering of SnO2 was prevented only partially resulting in small sinter necks (bottlenecks) between SnO2 primary particles (smaller than twice the Debye length). This morphology drastically enhanced the sensitivity toward the analyte by maintaining a thermally stable high surface area and fully depleted connections at the primary particle necks. This enhancement is attributed mostly to the decreasing neck size of the SnO2SiO2 heterojunctions rather than the decreasing SnO2 crystallite and grain sizes with increasing SiO2 doping. At high SiO2 contents, SnO2 sintering was inhibited as its grains were separated effectively by dielectric SiO2; this resulted in isolated SnO2 nanocrystals with drastically reduced sensitivity, thereby effectively being insulators.