Modeling the impact of spectral sensor configurations on the FLD retrieval accuracy of sun-induced chlorophyll fluorescence

Chlorophyll fluorescence is related to photosynthesis and can serve as a remote sensing proxy for estimating photosynthetic energy conversion and carbon uptake. Recent advances in sensor technology allow remote measurements of the sun-induced chlorophyll fluorescence signal (Fs) at leaf and canopy scale. The commonly used Fraunhofer Line Depth (FLD) principle exploits spectrally narrow atmospheric oxygen absorption bands and relates Fs to the difference of the absorption feature depth of a fluorescensing and a non-fluorescensing surface. However, due to the nature of these narrow bands, Fs retrieval results depend not only on vegetation species type or environmental conditions, but also on instrument technology and processing algorithms. Thus, an evaluation of all influencing factors and their separate quantification is required to further improve Fs retrieval and to allow a reproducible interpretation of Fs signals.Here we present a modeling study that isolates and quantifies the impacts of sensor characteristics, such as spectral sampling interval (SSI), spectral resolution (SR), signal to noise ratio (SNR), and spectral shift (SS) on the accuracy of Fs measurements in the oxygen A band centered at 760 nm (O₂-A). Modeled high resolution radiance spectra associated with known Fs were spectrally resampled, taking into consideration the various sensor properties. Fs was retrieved using the three most common FLD retrieval methods, namely the original FLD method (sFLD), the modified FLD (3FLD) and the improved FLD (iFLD). The analysis investigates parameter ranges, which are representative for field and airborne instruments currently used in Fs research (e.g., ASD FieldSpec, OceanOptics HR, AirFLEX, AISA, APEX, CASI, and MERIS).Our results show that the most important parameter affecting the retrieval accuracy is SNR, SR accounts for ≤ 40% of the error, the SSI for ≤ 12%, and SS for ≤ 7% of the error. A trade-off study revealed that high SR can partly compensate for low SNR. There is a strong interrelation between all parameters and the impact of specific parameters can compensate or amplify the influence of others. Hence, the combination of all parameters must be considered by the evaluation of sensors and their potential for Fs retrieval. In general, the standard FLD method strongly overestimates Fs, while 3FLD and iFLD provide a more accurate estimation of Fs. We conclude that technical sensor specifications and the retrieval methods cause a significant variability in retrieved Fs signals. Results are intended to be one relevant component of the total uncertainty budget of Fs retrieval and have to be considered in the interpretation of retrieved Fs signals.     

Iso-Kinematic Maps from statistical analysis of PS-InSAR data of Piemonte, NW Italy: Comparison with geological kinematic trends

SAR interferometry based on Permanent Scatterers (PS-InSAR™) is used here to study the present crustal mobility of a large area of NW Italy, in the Piemonte region.Thirty-eight satellite scenes (ERS SAR), taken from May 1992 to January 2001, were analysed for detecting more than 2 million PS on the study area. Continuous velocity surface maps (Iso-Kinematic Maps: IKM) were obtained from geo-statistical and spatial cluster techniques (Hot Spot analysis) of PS “short-period” data, to identify relative ground motions and to compare them with “long-period” tectonic mobility trends, i.e. those inferred at regional scale over geological times (some million years).The comparison was made by individuation of homogeneous kinematic areas, represented in the IKM, and characterization of the boundaries between them (Iso-Kinematic Boundaries: IKB). The IKB were used as tools to asses if the PS-InSAR data on present-day crustal mobility could fit with the distribution of real tectonic structures or field geological elements.IKM were drawn for uplifting geological sectors of Piemonte (Maritime Alps, Gran Paradiso, Langhe) where moderate to very low seismicity is recorded, and gravitational instabilities of rock mass on mountain slopes are widespread. The land sectors have been chosen in order to test the suitability of IKM in very different geo-morphological conditions.Different types of correspondence between the IKM and the geological kinematic trend were found:

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a first type in which the kinematic trend of short-period (a decade of years, i.e. the PS-InSAR detection time span) is in agreement with a long-period tectonic trend (some million years) and seem to be driven by well known faults subparallel to the IKB. These kinematic trends can be hidden by the slope movement due to gravitational instabilities;

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a second type in which the kinematic trend of short-period does not strictly correspond to the long-period trend, but can be considered as minor-order, uplifting-subsidence cycles, even if in contrast with the long-period kinematic trend. Alternatively, the short-period kinematic trends could reflect the action of deep-seated geological forces or structures, not yet known or inferable (at least with the recorded PS-InSAR velocities) on the basis of the available geological data and models.

     

Extending the notion of rationality of selfish agents: Second Order Nash equilibria

Motivated by the increasing interest of the Computer Science community in the study and understanding of non-cooperative systems, we present a novel model for formalizing the rational behavior of agents with a more farsighted view of the consequences of their actions. This approach yields a framework creating new equilibria, which we call Second Order equilibria, starting from a ground set of traditional ones. By applying our approach to pure Nash equilibria, we define the set of Second Order pure Nash equilibria and present their applications to the Prisoner’s Dilemma game, to an instance of Braess’s Paradox in the Wardrop model and to the KP model with identical machines.     

Learning to hash: forgiving hash functions and applications

The problem of efficiently finding similar items in a large corpus of high-dimensional data points arises in many real-world tasks, such as music, image, and video retrieval. Beyond the scaling difficulties that arise with lookups in large data sets, the complexity in these domains is exacerbated by an imprecise definition of similarity. In this paper, we describe a method to learn a similarity function from only weakly labeled positive examples. Once learned, this similarity function is used as the basis of a hash function to severely constrain the number of points considered for each lookup. Tested on a large real-world audio dataset, only a tiny fraction of the points (~0.27%) are ever considered for each lookup. To increase efficiency, no comparisons in the original high-dimensional space of points are required. The performance far surpasses, in terms of both efficiency and accuracy, a state-of-the-art Locality-Sensitive-Hashing-based (LSH) technique for the same problem and data set.     

A low-power wireless video sensor node for distributed object detection

In this paper we propose MicrelEye, a wireless video node for cooperative distributed video processing applications that involve image classification. The node is equipped with a low-cost VGA CMOS image sensor, a reconfigurable processing engine (FPGA, Microcontroller, SRAM) and a Bluetooth 100-m transceiver. It has a size of few cubic centimeters and its typical power consumption is approximately ten times less than that of typical commercial DSP-based solutions. As regards classification, a highly optimized hardware-oriented support vector machine-like (SVM-like) algorithm called ERSVM is proposed and implemented. We describe our hardware and software architecture, its performance and power characteristics. The case study considered in this paper is people detection. The obtained results suggest that the present technology allows for the design of simple intelligent video nodes capable of performing classification tasks locally.

A theoretical analysis of the influence of fixational instability on the development of thalamocortical connectivity

Under natural viewing conditions, the physiological instability of visual fixation keeps the projection of the stimulus on the retina in constant motion. After eye opening, chronic exposure to a constantly moving retinal image might influence the experience-dependent refinement of cell response characteristics. The results of previous modeling studies have suggested a contribution of fixational instability to the Hebbian maturation of the receptive fields of V1 simple cells (Rucci, Edelman, & Wray, 2000; Rucci & Casile, 2004). This letter examines the origins of such a contribution. Using quasilinear models of lateral geniculate nucleus units and V1 simple cells, we derive analytical expressions for the second-order statistics of thalamocortical activity before and after eye opening. We show that in the presence of natural stimulation, fixational instability introduces a spatially uncorrelated signal in the retinal input, which strongly influences the structure of correlated activity in the model. This input signal produces a regime of thalamocortical activity similar to that present before eye opening and compatible with the Hebbian maturation of cortical receptive fields.     

Entorhinal cortex grid cells can map to hippocampal place cells by competitive learning

'Grid cells' in the dorsocaudal medial entorhinal cortex (dMEC) are activated when a rat is located at any of the vertices of a grid of equilateral triangles covering the environment. dMEC grid cells have different frequencies and phase offsets. However, cells in the dentate gyrus (DG) and hippocampal area CA3 of the rodent typically display place fields, where individual cells are active over only a single portion of the space. In a model of the hippocampus, we have shown that the connectivity from the entorhinal cortex to the dentate granule cells could allow the dentate granule cells to operate as a competitive network to recode their inputs to produce sparse orthogonal representations, and this includes spatial pattern separation. In this paper we show that the same computational hypothesis can account for the mapping of EC grid cells to dentate place cells. We show that the learning in the competitive network is an important part of the way in which the mapping can be achieved. We further show that incorporation of a short term memory trace into the associative learning can help to produce the relatively broad place fields found in the hippocampus.     

Using fold-in and fold-out in the architecture recovery of software systems

In this paper we present an approach to automate the architecture recovery process of software systems. The approach is built on information retrieval and clustering techniques, and, in particular, uses Latent Semantic Indexing (LSI) to get similarities among software entities (e.g., programs or classes) and the k-means clustering algorithm to form groups of software entities that implement similar functionality. In order to improve computational time in the context of the software evolution and then reduce energy waste, the architecture recovery process can be also applied by using fold-in and fold-out mechanisms that, respectively, add and remove software entities to the LSI representation of the understudy software system. The approach has been implemented in a prototype of a supporting software system as an Eclipse plug-in. Finally, to assess the approach and the plug-in, we have conducted an empirical investigation on five open source software systems implemented using the programming languages Java and C/C++. In the investigation special emphasis has been also given to the effect of using the fold-in and fold-out mechanisms.     

The Serotonergic Agonists Quipazine, CGS-12066A, and α-Methylserotonin Alter Motor Activity and Induce Hindlimb Stepping in the Intact and Spinal Rat Fetus.

The effects of serotonergic agonists were examined in intact and spinal fetuses, using an in vivo fetal rat preparation. On Gestational Day 20, fetuses were prepared with a midthoracic or sham spinal transection. Dose-response curves were obtained for quipazine (nonselective 5-hydroxytryptamine [5-HT] agonist; 1.0-10.0 mg/kg), CGS-12066A (5-HT1B agonist; 1.0-30.0 mg/kg), and α-methylserotonin (α-Me-5-HT; 5-HT? agonist; 0.2-15.0 mg/kg). During a 10-min test, each of the agonists (delivered via intraperitoneal injection) influenced fetal behavior: They increased the occurrence of head movements, mouthing, and hindlimb stepping. Quipazine and α-Me-5-HT also promoted hindlimb activity in spinal fetuses. Thus, stimulation of the fetal 5-HT system modulates motor activity at multiple levels of the developing central nervous system. (PsycINFO Database Record (c) 2010 APA, all rights reserved)