Miracle-dz/UniFAR-FTUs huggingface dataset:
Solar‐induced chlorophyll fluorescence that correlates with canopy photosynthesis on diurnal and seasonal scales in a temperate deciduous forest

Previous studies have suggested that solar‐induced chlorophyll fluorescence (SIF) is correlated with Gross Primary Production (GPP). However, it remains unclear to what extent this relationship is due to absorbed photosynthetically active radiation (APAR) and/or light use efficiency (LUE). Here we present the first time series of near‐surface measurement of canopy‐scale SIF at 760 nm in temperate deciduous forests. SIF correlated with GPP estimated with eddy covariance at diurnal and seasonal scales (r2 = 0.82 and 0.73, respectively), as well as with APAR diurnally and seasonally (r2 = 0.90 and 0.80, respectively). SIF/APAR is significantly positively correlated with LUE and is higher during cloudy days than sunny days. Weekly tower‐based SIF agreed with SIF from the Global Ozone Monitoring Experiment‐2 (r2 = 0.82). Our results provide ground‐based evidence that SIF is directly related to both APAR and LUE and thus GPP, and confirm that satellite SIF can be used as a proxy for GPP.
Real-time 3D face identification from a depth camera

We present a real-time 3D face identification system using a consumer level depth camera (PrimeSensor). Our system takes a noisy sequence as input and produces reliable identification. Instead of registering a probe to all instances in the database, we propose to only register it with several intermediate references, which considerably reduces processing, while preserving the recognition rate. The presented system routinely achieves 100% identification rate when matching a (0.5-4 seconds) video sequence, and 97.9% for single frame recognition. These numbers refer to a real-world dataset of 20 people. The methodology extends directly to very large datasets. The process runs at 20fps on an off the shelf laptop.
Towards an Aesthetic Dimensions Framework for Dynamic Graph Visualisations

Most research on the readability of graph visualization focuses on node-link diagrams of static graphs. But in many applications graphs are not static, but change over time, or graphs are too dense to be drawn as node-link diagrams. In this paper we look at dynamic graph visualizations: We translate the general goal of graph visualization--to convey the underlying information of a graph--into aesthetic dimensions that are applicable in practice. These aesthetic dimensions help to design, compare, and evaluate dynamic graph visualizations.
LIBERTY, EQUALITY, AND KINDNESS?: HOW THE STRATEGIC CHOICE OF VALUES AFFECT POLICY ATTITUDES AND INFORMATION CHOICES

Why did the healthcare reform plan, the central issue of President Obama’s first four years – become so unpopular among members of the mass public in the U.S.? The answer may lie in the way the issue was framed by leaders of the parties in their communications with the public. Frames have been shown to significantly affect the opinions of subjects in the experimental lab (i.e. Chong and Druckman 2007a, b; Druckman 2010, 2011). However, fewer studies have attempted to document and test the causes behind these frame opinion changes. My dissertation focuses on answering how political policy issues can evolve from popular mandates to political time bombs when they are framed using values that are less convincing to the public. I show that frame strategy mistakes not only affect short-term evaluations of policies, but also the kind of news that one selects about that issue. This creates a feedback loop, in which strong frames create stronger connections to news that emphasizes the same message, and eventually may change the nature of an entire policy debate. In the case of policies like healthcare that involve social spending programs, I show that Democrats fail to frame successfully when they emphasize humanitarian values (defined as needs-based care for others). Using MTurk experiments with over 1900 subjects, I show that these humanitarian appeals are significantly less motivating to individuals – even those who rate high on humanitarian values – than appeals emphasizing egalitarianism or individualism. These differences are even more pronounced among those who are not strong partisans, and can result in significant changes in both policy attitudes and news choices. I conclude that Democrats would have garnered far more support had they used rhetoric emphasizing egalitarian, or equality-inducing themes, in selling healthcare reform to the American public.
Expression recognition using directional gradient local pattern and gradient-based ternary texture patterns

Facial expression is an important channel in human communication. Therefore, the problem of facial expression recognition (FER) attracts the growing attention of the research community in the recent years. In this context, the critical point for is the possibility to detect accurately the emotional features. An effective facial feature descriptor is an important issue in the design of a successful expression recongnition algorithm. Although recently there have been certain progress in this domain, extracting a face feature descriptor stable under changing environment is still a difficult task. In this paper, we illustrate empirically the algorithm of person-independent facial expression recognition based on statistical local features such as Directional gradient Local Pattern (DGLP) and gradient local ternary pattern (GLTP). The combined DGLP and GLTP operator encodes the local texture of an image by computing the gradient magnitudes of local neighborhood as well as the angle of direction of the edge and converts those values into feature vector. The results obtained indicate that the combined DGLP and GLTP method performs better than other methods used for facial expression recognition problems in high-textured facial regions.
Monetary Delegation : Credibility through Dynamic Incentives

We analyze delegation of monetary policy to an independent but accountable Central Banker (CB) in a setting with a dynamic Phillips curve. The paper describes a mechanism that resolves the government's time inconsistency problem. Our proposal closely resembles real-world institutional arrangements and delivers credible implementation of the social optimum by giving dynamic incentives to the CB. We show that delegation generates an inflation plan identical to the precom-mitment path when the cost of adjusting CB remuneration is negligible. When steady-state adjustment costs are nil, the government achieves perfect commitment in the steady-state. These results suggest that delegation is more robust as a commitment instrument than previously emphasized.
Forest Biophysical Parameter Retrieval Using PolSAR Technique

Synthetic Aperture Radar (SAR) polarimetry is an uprising and nascent area of research in radar remote sensing and it has proved its potential in the area of forest biophysical parameter retrieval. The key intention of the present study was to develop SAR polarimetry based semi-empirical model for Stem volume and Aboveground biomass estimation of forest area and check its reliability in implementation to the study area for the relationships between these forest biophysical parameters and Polarimetric SAR (PolSAR) decomposition components. Five scenes of Quadpol SLC ALOS PALSAR data which has been acquired over Southern Gujarat forest area covering portions of Surat, Valsad, The Dangs and Dadra & Nagar Haveli districts in March, April and May 2010 are used. A field calculated circumference at breast height and height of trees in 0.1 hectare plots designed using stratified random sample method has been collected from Forestry and Ecology Department, IIRS. This field data was utilized for plot-wise stem volume density and aboveground biomass estimation. Coherency matrix based decomposition was carried out, yielding three components and resultant generated restoring polarimetric information. Coherency matrix was utilized for polarization orientation angle shift compensation which demonstrated acknowledgeable overestimation of volume scattering mechanism and underestimation of double bounce scattering mechanism unaltering the odd bounce scattering information after decomposition. Coherency matrix was utilized for Radar Vegetation Index and backscattered HH, HV and VV polarimetric channels generation. HV backscattered polarimetric channel and volume scattering component were found to be best correlated with forest parameters. Radar Vegetation Index was correlated with the field retrieved stem volume density and aboveground biomass resulting coefficient of determination i.e., R = 0.573 and R2 = 0.617 respectively, which resulted in stating moderate potential for study area into consideration. Semiempirical Water Cloud Model was implemented for execution of parameter retrieval using the field estimated stem volume and aboveground biomass which proved its potential by illustrating higher coefficient of determination. KeywordsCoherency Matrix, Polarization Orientation Angle, Radar Vegetation Index, Water Cloud Model
Lens-sparing Vitrectomy for Stage 4 and Stage 5 Retinopathy of Prematurity

Purpose To describe the results of lens-sparing vitrectomy for the correction of retinal detachment associated with retinopathy of prematurity (ROP) and its associated complications. Methods Seventeen patients who underwent a lens-sparing vitrectomy for stage 4 and stage 5 ROP with plus disease at Seoul National University Children's Hospital between 1999 and 2003 were enrolled in this study. The patients who had bilateral retinal detachment of ROP underwent a lens-sparing vitrectomy in one eye and a scleral buckling surgery or lensectomy-vitrectomy in the other eye. The patients who had a retinal detachment in one eye and a regressed ROP in the other eye underwent unilateral lens-sparing vitrectomies. A review of their preoperative clinical findings (including the status of retinal detachment and plus disease), post-operative results, and any complications encountered was performed. Results In 17 patients, the postoperative success rate of lens-sparing vitrectomy was 58.8%. However, lens-sparing vitrectomy as a treatment for stage 5 ROP (25.0%) produced more negative post-operative results than it did when used to treat either those for stage 4a (75,0%) or 4b (66.7%) ROP. Among the 10 eyes in which the retina was attached, form vision was shown in six eyes, light could be followed by three eyes, and no light perception was present in one eye. Intra- and post-operative complications included retinal break formation, cataracts, vitreous hemorrhages, and glaucoma in patients with stages 4b and stage 5 ROP. Conclusions Lens-sparing vitrectomy resulted in encouraging surgical outcomes in the correction of retinal detachment of ROP, especially in stage 4 patients. Therefore, a lens-sparing vitrectomy for stage 4 ROP patient may be beneficial, although it is still associated with some intra- and post-operative complications.
TOWARDS AN AGENT-BASED CUSTOMER KNOWLEDGE MANAGEMENT SYSTEM (ABCKMS) IN E-COMMERCE ORGANIZATIONS

—Till date, e-commerce organizations still have competency challenges in Customer Knowledge Management (CKM). Organizations need to develop competencies in all aspects of CKM, from understanding who their customers really are and what they want, to designing platforms specifically for customers. It is particularly important for customer processes involving information for, collected from and about customers to be turned into knowledge, disseminated and really used. Also, most companies do not always take full advantage of the knowledge sources that exist through customers’ interaction with their websites. All these processes appear complex and fuzzy, which the introduction of agent technology in this paper poses a potential solution to this problem, in order to achieve an effective CKM in a dynamic business environment as e-commerce organizations.
Cake Cutting Mechanisms | Egor Ianovski

We examine the history of cake cutting mechanisms and discuss the efficiency of their allocations. In the case of piecewise uniform preferences, we define a game that in the presence of strategic agents has equilibria that are not dominated by the allocations of any mechanism. We identify that the equilibria of this game coincide with the allocations of an existing cake cutting mechanism.
Excessive Activation of Serotonin (5-HT) 1B Receptors Disrupts the Formation of Sensory Maps in Monoamine Oxidase A and 5-HT Transporter Knock-Out Mice

Deficiency in the monoamine degradation enzyme monoamine oxidase A (MAOA) or prenatal exposure to the monoamine uptake inhibitor cocaine alters behavior in humans and rodents, but the mechanisms are unclear. In MAOA knock-out mice, inhibiting serotonin synthesis during development can prevent abnormal segregation of axons in the retinogeniculate and somatosensory thalamocortical systems. To investigate this effect, we crossed MAOA knock-outs with mice lacking the serotonin transporter 5-HTT or the 5-HT1B receptor, two molecules present in developing sensory projections. Segregation was abnormal in 5-HTT knock-outs and MAOA/5-HTT double knock-outs but was normalized in MAOA/5-HT1B double knock-outs and MAOA/5-HTT/5-HT1B triple knock-outs. This demonstrates that the 5-HT1B receptor is a key factor in abnormal segregation of sensory projections and suggests that serotonergic drugs represent a risk for the development of these projections. We also found that the 5-HT1B receptor has an adverse developmental impact on beam-walking behavior in MAOA knock-outs. Finally, because the 5-HT1B receptor inhibits glutamate release, our results suggest that visual and somatosensory projections must release glutamate for proper segregation.
Black-Box Optimization in Machine Learning with Trust Region Based Derivative Free Algorithm

In this work, we utilize a Trust Region based Derivative Free Optimization (DFO-TR) method to directly maximize the Area Under Receiver Operating Characteristic Curve (AUC), which is a nonsmooth, noisy function. We show that AUC is a smooth function, in expectation, if the distributions of the positive and negative data points obey a jointly normal distribution. The practical performance of this algorithm is compared to three prominent Bayesian optimization methods and random search. The presented numerical results show that DFO-TR surpasses Bayesian optimization and random search on various black-box optimization problem, such as maximizing AUC and hyperparameter tuning.
Correlation in crude oil and natural gas markets

Correlation is a measure of dependency between stationary time series. In this chapter the stationary time series will be the τ−period log returns on crude oil and natural gas futures or forwards, denoted either xt = ln(Pt /Pt-τ) or x(t) = ln(S(t)/S(t-τ)) depending on whether we are considering a discrete time or a continuous time application. We consider only the simple linear pair-wise correlation ρxy = σxy/σxσy where σxy denotes the covariance between two log returns x and y (i.e. the first moment about the mean of their joint density)i and σx and σy denote the standard deviations of each marginal returns density.
The Role of Dietary Fiber in the Bioaccessibility and Bioavailability of Fruit and Vegetable Antioxidants

Antioxidants are abundant compounds primarily found in fresh fruits and vegetables, and evidence for their role in the prevention of degenerative diseases is continuously emerging. However, the bioaccessibility and bioavailability of each compound differs greatly, and the most abundant antioxidants in ingested fruit are not necessarily those leading to the highest concentrations of active metabolites in target tissues. Fruit antioxidants are commonly mixed with different macromolecules such as carbohydrates, lipids, and proteins to form a food matrix. In fruits and vegetables, carbohydrates are the major compounds found, mainly in free and conjugated forms. Dietary fiber, the indigestible cell wall component of plant material, is considered to play an important role in human diet and health. Most studies on antioxidant bioavailability are focused on foods and beverages from which antioxidants are easily released. There is evidence indicating that food microstructure affects the bioaccessibility and bioavailability of several nutrients, referring mostly to antioxidants. Nevertheless, the specific role of dietary fiber in the absorption of antioxidants has not been widely discussed. In this context, the purpose of the present review is to compile and analyze evidence relating to the association between dietary fiber and antioxidants, and the physical and chemical interactions that modulate their release from the chyme in the gastrointestinal tract.
©2001 ARTVILLE, LLC The

he last two decades have seen prolific research activity in the areas of multiscale analysis of signals and images. The number of important contributions in this area is so great that just listing all of them would more than exhaust the page budget of this article (for example, the bibliography in [16] is 17 pages). The basic idea, however, is quite simple: a signal is simplified via iterative filtering (see Fig. 1) in such a way that the output of each filtering stage is a " coarser " version of its input. (When we talk about something which is applicable to both one-dimensional (1-D) signals and two-dimensional (2-D) images, we will simply use the word " signal. ") The iteration number is called the scale: signals on the left of the diagram in Fig. 1 correspond to finer scales, signals on the right correspond to coarser scales. Below we give several examples of such iterative filtering; however, we avoid a precise definition of the terms simplification, fine, coarse, and scale. The intuition behind these notions is that each filter in Fig. 1 removes fine structures. This concept is very effectively illustrated in [17] using an analogy with cartography. A campus map of Purdue University has more detail than a map of West Lafayette, which, in turn, is finer than a map of Indiana. Maps of the United States, North America, and the whole globe represent progressively coarser scales. The resulting aggregation of coarsened versions of the input is called a scale-space (see, for example, Figs. 3(c), (d) and 4). The terms timescale (in 1-D) and multiscale or multiresolution analysis are also used in literature. We will not use the term timescale in this article since we will actually identify time with scale. In other words, the filter iterations of Fig. 1 occur one after another; the signal evolves from the initial data u 0 to its coarsened versions. In general, scale-spaces are redundant: for an N-point signal, we get a scale-space consisting of many N-point signals. Certain linear scale-spaces, however, can be squeezed (by filtering and downsampling) down to only N numbers—the wavelet coefficients—from which perfect reconstruction of the original signal is possible. The number of coefficients can often be reduced even further, without much loss of information, leading to very effective compression schemes. Both wavelet decomposition and reconstruction, moreover, are done with computational complexity which is linear in N …
Automated floating-point to fixed-point conversion with the fixify environment

Conversion from floating-point to fixed-point formats is a necessary step in the design process of embedded systems and is traditionally performed manually. Automating this conversion process brings significant and much needed improvement in the efficiency of the design process. The fixify environment presented here fully automates the conversion process and comprises three optimization methods. The restricted-set full search algorithm is suited to designs that will be implemented on DSP cores and is, for such designs, guaranteed to find globally optimal solutions. On the other hand, the greedy search algorithm finds solution in the continuous search space and produces nearly optimal results, with the shortest required runtime. The branch-and-bound algorithm also works in the continuous search space and finds optimal solutions, but requires relatively long runtimes.
Hand gesture recognition using fourier descriptors

Accurate, real-time hand gesture recognition is a challenging and crucial task due to the need of more natural human-computer interaction methods. The major problem lies in fining a good compromise between the accuracy of recognition and the computational load for the algorithm to run in real-time. In this paper we propose a method for static hand gesture recognition using Fourier descriptors for feature extraction with different classifiers. Fourier descriptors have the advantage of giving a set of features that are invariant to rotation, translation and scaling. They are also efficient in terms of speed as they only use a small number of points from the entire image. The proposed method is evaluated using images from the Cambridge Hand Gesture Dataset at different number of features and different classifiers. The effectiveness of the method is shown through simulation results.
Generation of Three-Dimensional Finite Element Meshes from CT Dataset of Human Femurs

Three-dimensional finite element meshes of human femur are generated using an automatic grid-based method for biomechanical analysis purpose. The meshing algorithm firstly preproceses the CT slices to extract geometrical information of the femur structure, and then organizes a tagged background grid based on the segmented imaging dataset. The surface triangular mesh is constructed by isosurface extraction, and grid cells inside the isosurface are decomposed into tetrahedral elements quickly using predefined tetrahedralizing stencils. With the background grid constructed in an octree data structure, graded mesh of the femur structure can be generated, resulting in finer tetrahedral elements constructed near the boundary and coarser ones insides. As compared to the uniformly sized method, the graded meshing method produces a lower number of elements and better computational efficiency.
Author ' s personal copy Combustion modeling using principal component analysis

The thermochemical state of a single-phase reacting system containing ns species is ns + 1 dimensional. However, it is widely recognized that low-dimensional manifolds exist in this space. The question then arises as to the best way to approximate these manifolds. Common chemistry reduction approaches for combustion simulation (such as laminar flamelet, equilibrium, and flame-sheet (Burke–Schuman) chemistry) specify a priori the manifold dimensionality and the parameters that form the basis for representing the thermochemical state, which is then prescribed as a unique function of these parameters. If high-fidelity data are available from experiment or direct numerical simulation (DNS), manifolds may be determined via a principal component analysis (PCA), with the principal components (PCs) forming a new basis for describing the thermochemical state. By considering a truncated set of PCs, one may approximate the thermochemical state with rigorous error bounds, extract a parameterized representation of the thermochemical state, and derive transport equations for the principal components. This paper outlines a methodology for constructing a reduced model for the thermochemical state from high-fidelity data with particular focus on the ability to parameterize source terms appearing in the transport equations for the principal components. The modeling approach allows quantitative a priori control of the error in the state-space parameterization, and can be applied to both laminar and turbulent simulations in all combustion regimes. 2009 The Combustion Institute. Published by Elsevier Inc. All rights reserved.