Cosine Lobe Based Relighting from Gradient Illumination Photographs

We present an image-based method for relighting a scene by analytically fitting cosine lobes to the reflectance function at each pixel, based on gradient illumination photographs. Realistic relighting results for many materials are obtained using a single per-pixel cosine lobe obtained from just two color photographs: one under uniform white illumination and the other under colored gradient illumination. For materials with wavelength-dependent scattering, a better fit can be obtained using independent cosine lobes for the red, green, and blue channels, obtained from three achromatic gradient illumination conditions instead of the colored gradient condition. We explore two cosine lobe reflectance functions, both of which allow an analytic fit to the gradient conditions. One is non-zero over half the sphere of lighting directions, which works well for diffuse and specular materials, but fails for materials with broader scattering such as fur. The other is non-zero everywhere, which works well for broadly scattering materials and still produces visually plausible results for diffuse and specular materials. We also perform an approximate diffuse/specular separation of the reflectance, and estimate scene geometry from the recovered photometric normals to produce hard shadows cast by the geometry, while still reconstructing the input photographs exactly.

Self-motion perception training: thresholds improve in the light but not in the dark

We investigated perceptual learning in self-motion perception. Blindfolded participants were displaced leftward or rightward by means of a motion platform and asked to indicate the direction of motion. A total of eleven participants underwent 3,360 practice trials, distributed over twelve (Experiment 1) or 6 days (Experiment 2). We found no improvement in motion discrimination in both experiments. These results are surprising since perceptual learning has been demonstrated for visual, auditory, and somatosensory discrimination. Improvements in the same task were found when visual input was provided (Experiment 3). The multisensory nature of vestibular information is discussed as a possible explanation of the absence of perceptual learning in darkness.

A nonlinear QCT-based finite element model validation study for the human femur tested in two configurations in vitro

Purpose Femoral fracture is a common medical problem in osteoporotic individuals. Bone mineral density (BMD) is the gold standard measure to evaluate fracture risk in vivo. Quantitative computed tomography (QCT)-based homogenized voxel finite element (hvFE) models have been proved to be more accurate predictors of femoral strength than BMD by adding geometrical and material properties. The aim of this study was to evaluate the ability of hvFE models in predicting femoral stiffness, strength and failure location for a large number of pairs of human femora tested in two different loading scenarios. Methods Thirty-six pairs of femora were scanned with QCT and total proximal BMD and BMC were evaluated. For each pair, one femur was positioned in one-legged stance configuration (STANCE) and the other in a sideways configuration (SIDE). Nonlinear hvFE models were generated from QCT images by reproducing the same loading configurations imposed in the experiments. For experiments and models, the structural properties (stiffness and ultimate load), the failure location and the motion of the femoral head were computed and compared. Results In both configurations, hvFE models predicted both stiffness (R2=0.82 for STANCE and R2=0.74 for SIDE) and femoral ultimate load (R2=0.80 for STANCE and R2=0.85 for SIDE) better than BMD and BMC. Moreover, the models predicted qualitatively well the failure location (66% of cases) and the motion of the femoral head. Conclusions The subject specific QCT-based nonlinear hvFE model cannot only predict femoral apparent mechanical properties better than densitometric measures, but can additionally provide useful qualitative information about failure location.

Sparse representation based action and gesture recognition

In this paper we present a solution to the problem of action and gesture recognition using sparse representations. The dictionary is modelled as a simple concatenation of features computed for each action or gesture class from the training data, and test data is classified by finding sparse representation of the test video features over this dictionary. Our method does not impose any explicit training procedure on the dictionary. We experiment our model with two kinds of features, by projecting (i) Gait Energy Images (GEIs) and (ii) Motion-descriptors, to a lower dimension using Random projection. Experiments have shown 100% recognition rate on standard datasets and are compared to the results obtained with widely used SVM classifier.

Assessing sustainable forest management under REDD+: a community-based labour perspective

Reducing emissions from deforestation and forest degradation plus (REDD+) encourages economic support for reducing deforestation and conserving or increasing existing forest carbon stocks. The way in which incentives are structured affects trade-offs between local livelihoods, carbon emission reduction, and the cost-effectiveness of a REDD + programme. Looking at first-hand empirical data from 208 farming households in the Bolivian Amazon froma household economy perspective, our study explores two policy options: 1) compensated reduction of emissions fromold-growth forest clearing for agriculture, and 2) direct payments for labour input into sustainable forest anagement combined with a commitment not to clear old-growth forest. Our results indicate that direct payments for sustainable forest management – an approach that focuses on valuing farmers' labour input – can be more cost-effective than compensated reduction and in some cases is themost appropriate choice for achieving improved household incomes, permanence of changes, avoidance of leakages, and community-based institutional enforcement for sustainable forest management.

An optimized lead system for long-term esophageal electrocardiography

Long-term electrocardiography (ECG) featuring adequate atrial and ventricular signal quality is highly desirable. Routinely used surface leads are limited in atrial signal sensitivity and recording capability impeding complete ECG delineation, i.e. in the presence of supraventricular arrhythmias. Long-term esophageal ECG might overcome these limitations but requires a dedicated lead system and recorder design. To this end, we analysed multiple-lead esophageal ECGs with respect to signal quality by describing the ECG waves as a function of the insertion level, interelectrode distance, electrode shape and amplifier's input range. The results derived from clinical data show that two bipolar esophageal leads, an atrial lead with short (15 mm) interelectrode distance and a ventricular lead with long (80 mm) interelectrode distance provide non-inferior ventricular signal strength and superior atrial signal strength compared to standard surface lead II. High atrial signal slope in particular is observed with the atrial esophageal lead. The proposed esophageal lead system in combination with an increased recorder input range of ±20 mV minimizes signal loss due to excessive electrode motion typically observed in esophageal ECGs. The design proposal might help to standardize long-term esophageal ECG registrations and facilitate novel ECG classification systems based on the independent detection of ventricular and atrial electrical activity.

Internet-based exercises and mini-exams for production and operations management

The purpose of the internet-based teachware mySCM is that students of economics, informatics and industrial engineering get familiar with quantitative methods for supply chain management. Input-output-relationships of various optimization methods can be detected by sampling input values, parameters, and alternative methods for the same problem. Students can gain extra benefits by passing so-called mini-exams that motivate active learning. mySCM can be used for free, round-the-clock, and any place where access to the Internet is available.

Simultaneous registration of ECG and cardiac motion by a single esophageal probe

Long-term surface ECG is routinely used to diagnose paroxysmal arrhythmias. However, this method only provides information about the heart's electrical activity. To this end, we investigated a novel esophageal catheter that features synchronous esophageal ECG and acceleration measurements, the latter being a record of the heart's mechanical activity. The acceleration data were quantified in a small study and successfully linked to the activity sequences of the heart in all subjects. The acceleration signals were additionally transformed into motion. The extracted cardiac motion was proved to be a valid reference input for an adaptive filter capable of removing relevant baseline wandering in the recorded esophageal ECGs. Taking both capabilities into account, the proposed recorder might be a promising tool for future long-term heart monitoring.

True four-dimensional analysis of thoracic aortic displacement and distension using model-based segmentation of computed tomography angiography.

Previous analyses of aortic displacement and distension using computed tomography angiography (CTA) were performed on double-oblique multi-planar reformations and did not consider through-plane motion. The aim of this study was to overcome this limitation by using a novel computational approach for the assessment of thoracic aortic displacement and distension in their true four-dimensional extent. Vessel segmentation with landmark tracking was executed on CTA of 24 patients without evidence of aortic disease. Distension magnitudes and maximum displacement vectors (MDV) including their direction were analyzed at 5 aortic locations: left coronary artery (COR), mid-ascending aorta (ASC), brachiocephalic trunk (BCT), left subclavian artery (LSA), descending aorta (DES). Distension was highest for COR (2.3 ± 1.2 mm) and BCT (1.7 ± 1.1 mm) compared with ASC, LSA, and DES (p < 0.005). MDV decreased from COR to LSA (p < 0.005) and was highest for COR (6.2 ± 2.0 mm) and ASC (3.8 ± 1.9 mm). Displacement was directed towards left and anterior at COR and ASC. Craniocaudal displacement at COR and ASC was 1.3 ± 0.8 and 0.3 ± 0.3 mm. At BCT, LSA, and DES no predominant displacement direction was observable. Vessel displacement and wall distension are highest in the ascending aorta, and ascending aortic displacement is primarily directed towards left and anterior. Craniocaudal displacement remains low even close to the left cardiac ventricle.

Being Moved by the Self and Others: Influence of Empathy on Self-Motion Perception

BACKGROUND: The observation of conspecifics influences our bodily perceptions and actions: Contagious yawning, contagious itching, or empathy for pain, are all examples of mechanisms based on resonance between our own body and others. While there is evidence for the involvement of the mirror neuron system in the processing of motor, auditory and tactile information, it has not yet been associated with the perception of self-motion. METHODOLOGY/PRINCIPAL FINDINGS: We investigated whether viewing our own body, the body of another, and an object in motion influences self-motion perception. We found a visual-vestibular congruency effect for self-motion perception when observing self and object motion, and a reduction in this effect when observing someone else's body motion. The congruency effect was correlated with empathy scores, revealing the importance of empathy in mirroring mechanisms. CONCLUSIONS/SIGNIFICANCE: The data show that vestibular perception is modulated by agent-specific mirroring mechanisms. The observation of conspecifics in motion is an essential component of social life, and self-motion perception is crucial for the distinction between the self and the other. Finally, our results hint at the presence of a "vestibular mirror neuron system".

Rainfall input, throughfall and stemflow of nutrients in a central African rain forest dominated by ectomycorrhizal trees

Incident rainfall is a major source of nutrient input to a forest ecosystem and the consequent throughfall and stemflow contribute to nutrient cycling. These rain-based fluxes were measured over 12 mo in two forest types in Korup National Park, Cameroon, one with low (LEM) and one with high (HEM) ectomycorrhizal abundances of trees. Throughfall was 96.6 and 92.4% of the incident annual rainfall (5370 mm) in LEM and HEM forests respectively; stemflow was correspondingly 1.5 and 2.2%. Architectural analysis showed that ln(funneling ratio) declined linearly with increasing ln(basal area) of trees. Mean annual inputs of N, P, K, Mg and Ca in incident rainfall were 1.50, 1.07, 7.77, 5.25 and 9.27 kg ha(-1), and total rain-based inputs to the forest floor were 5.0, 3.2, 123.4, 14.4 and 37.7 kg ha-1 respectively. The value for K is high for tropical forests and that for N is low. Nitrogen showed a significantly lower loading of throughfall and stemflow in HEM than in LEM forest, this being associated in the HEM forest with a greater abundance of epiphytic bryophytes which may absorb more N. Incident rainfall provided c. 35% of the gross input of P to the forest floor (i. e., rain-based plus small litter inputs), a surprisingly high contribution given the sandy P-poor soils. At the start of the wet season leaching of K from the canopy was particularly high. Calcium in the rain was also highest at this time, most likely due to washing off of dry-deposited Harmattan dusts. It is proposed that throughfall has an important `priming' function in the rapid decomposition of litter and mineralization of P at the start of the wet season. The contribution of P inputted from the atmosphere appears to be significant when compared to the rates of P mineralization from leaf litter.

Development and Validation of a Symptom-Based Activity Index for Adults with Eosinophilic Esophagitis

BACKGROUND & Aims: Standardized instruments are needed to assess the activity of eosinophilic esophagitis (EoE), to provide endpoints for clinical trials and observational studies. We aimed to develop and validate a patient-reported outcome (PRO) instrument and score, based on items that could account for variations in patients' assessments of disease severity. We also evaluated relationships between patients' assessment of disease severity and EoE-associated endoscopic, histologic, and laboratory findings. METHODS We collected information from 186 patients with EoE in Switzerland and the US (69.4% male; median age, 43 years) via surveys (n = 135), focus groups (n = 27), and semi-structured interviews (n = 24). Items were generated for the instruments to assess biologic activity based on physician input. Linear regression was used to quantify the extent to which variations in patient-reported disease characteristics could account for variations in patients' assessment of EoE severity. The PRO instrument was prospectively used in 153 adult patients with EoE (72.5% male; median age, 38 years), and validated in an independent group of 120 patients with EoE (60.8% male; median age, 40.5 years). RESULTS Seven PRO factors that are used to assess characteristics of dysphagia, behavioral adaptations to living with dysphagia, and pain while swallowing accounted for 67% of the variation in patients' assessment of disease severity. Based on statistical consideration and patient input, a 7-day recall period was selected. Highly active EoE, based on endoscopic and histologic findings, was associated with an increase in patient-assessed disease severity. In the validation study, the mean difference between patient assessment of EoE severity and PRO score was 0.13 (on a scale from 0 to 10). CONCLUSIONS We developed and validated an EoE scoring system based on 7 PRO items that assesses symptoms over a 7-day recall period. Clinicaltrials.gov number: NCT00939263.

Monte Carlo based beam model using a photon MLC for modulated electron radiotherapy

PURPOSE Modulated electron radiotherapy (MERT) promises sparing of organs at risk for certain tumor sites. Any implementation of MERT treatment planning requires an accurate beam model. The aim of this work is the development of a beam model which reconstructs electron fields shaped using the Millennium photon multileaf collimator (MLC) (Varian Medical Systems, Inc., Palo Alto, CA) for a Varian linear accelerator (linac). METHODS This beam model is divided into an analytical part (two photon and two electron sources) and a Monte Carlo (MC) transport through the MLC. For dose calculation purposes the beam model has been coupled with a macro MC dose calculation algorithm. The commissioning process requires a set of measurements and precalculated MC input. The beam model has been commissioned at a source to surface distance of 70 cm for a Clinac 23EX (Varian Medical Systems, Inc., Palo Alto, CA) and a TrueBeam linac (Varian Medical Systems, Inc., Palo Alto, CA). For validation purposes, measured and calculated depth dose curves and dose profiles are compared for four different MLC shaped electron fields and all available energies. Furthermore, a measured two-dimensional dose distribution for patched segments consisting of three 18 MeV segments, three 12 MeV segments, and a 9 MeV segment is compared with corresponding dose calculations. Finally, measured and calculated two-dimensional dose distributions are compared for a circular segment encompassed with a C-shaped segment. RESULTS For 15 × 34, 5 × 5, and 2 × 2 cm(2) fields differences between water phantom measurements and calculations using the beam model coupled with the macro MC dose calculation algorithm are generally within 2% of the maximal dose value or 2 mm distance to agreement (DTA) for all electron beam energies. For a more complex MLC pattern, differences between measurements and calculations are generally within 3% of the maximal dose value or 3 mm DTA for all electron beam energies. For the two-dimensional dose comparisons, the differences between calculations and measurements are generally within 2% of the maximal dose value or 2 mm DTA. CONCLUSIONS The results of the dose comparisons suggest that the developed beam model is suitable to accurately reconstruct photon MLC shaped electron beams for a Clinac 23EX and a TrueBeam linac. Hence, in future work the beam model will be utilized to investigate the possibilities of MERT using the photon MLC to shape electron beams.

Local environmental knowledge: a key input for the sustainable development of Andean mountain communities

Local knowledge is crucial to both human development and environmental conservation. This is especially the case in mountain regions, where a combination of remoteness, harsh climatic conditions, rich cultural heritage, and high biological diversity has led to the development of complex local environmental knowledge systems. In the Andes for instance, rural populations mainly rely on their own environmental knowledge to ensure their food security and health. Recent studies conducted within Quechua communities in Peru and Bolivia showed that this knowledge was both persistent and dynamic, and that it responded to socio-economic and environmental changes through cultural resistance and adaptation. As this paper argues, combining local knowledge and so-called scientific knowledge – especially in development projects – can lead to innovative solutions to the socio-environmental challenges facing mountain communities in our globalized world. Based on experiences from the Andes, this paper will provide concrete recommendations to policymakers and practitioners for integrating local knowledge into development and natural resource management initiatives.

Range-based Weighted-likelihood Particle Filter for RSS-based Indoor Tracking

Attractive business cases in various application fields contribute to the sustained long-term interest in indoor localization and tracking by the research community. Location tracking is generally treated as a dynamic state estimation problem, consisting of two steps: (i) location estimation through measurement, and (ii) location prediction. For the estimation step, one of the most efficient and low-cost solutions is Received Signal Strength (RSS)-based ranging. However, various challenges - unrealistic propagation model, non-line of sight (NLOS), and multipath propagation - are yet to be addressed. Particle filters are a popular choice for dealing with the inherent non-linearities in both location measurements and motion dynamics. While such filters have been successfully applied to accurate, time-based ranging measurements, dealing with the more error-prone RSS based ranging is still challenging. In this work, we address the above issues with a novel, weighted likelihood, bootstrap particle filter for tracking via RSS-based ranging. Our filter weights the individual likelihoods from different anchor nodes exponentially, according to the ranging estimation. We also employ an improved propagation model for more accurate RSS-based ranging, which we suggested in recent work. We implemented and tested our algorithm in a passive localization system with IEEE 802.15.4 signals, showing that our proposed solution largely outperforms a traditional bootstrap particle filter.