Miracle-dz/UniFAR-FTUs huggingface dataset:
Managing the cumulative distribution function of the profit: A producer risk management case

This paper presents a new framework for risk consideration of participants in electricity markets. Current approaches add risk measures to stochastic problem formulation in order to control the variation of the profits (costs). However, in the proposed method, cumulative distribution function of profit is utilized and it is shaped based on the preferred risk levels of the producer (buyer). The features of this new method are compared with the current approaches based on a detailed case study performed on the problem of a producer participating in a three settlement market.
Cell surface distribution of fibronectin and vitronectin receptors depends on substrate composition and extracellular matrix accumulation

We used antibodies against the alpha subunits of the human fibronectin receptor (FNR) and vitronectin receptor (VNR) to localize simultaneously FNR and VNR at major substrate adhesion sites of fibroblasts and melanoma cells with double-label immunofluorescence microscopy. In early (2-6-h) serum-containing cultures, both FNR and VNR coaccumulated in focal contacts detected by interference reflection microscopy. Under higher resolution immunoscanning electron microscopy, FNR and VNR were also observed to be distributed randomly on the dorsal cell surface. As fibronectin-containing extracellular matrix fibers accumulated beneath the cells at 24 h, FNR became concentrated at contacts with these fibers and was no longer detected at focal contacts. VNR was not observed at matrix contacts but remained strikingly localized in focal contacts of the 24-h cells. Since focal contacts represent the sites of strongest cell-to-substrate adhesion, these results suggest that FNR and VNR together play critical roles in the maintenance of stable contacts between the cell and its substrate. In addition, the accumulation of FNR at extracellular matrix contacts implies that this receptor might also function in the process of cellular migration along fibronectin-containing matrix cables. To define the factors governing accumulation of FNR and VNR at focal contacts, fibroblasts in serum-free media were plated on substrates coated with purified ligands. Fibronectin-coated surfaces fostered accumulation of FNR but not VNR at focal contacts. On vitronectin- coated surfaces, or substrata derivatized with a tridecapeptide containing the cell attachment sequence Arg-Gly-Asp, both FNR and VNR became concentrated at focal contacts. These observations suggest that the availability of ligand is critical to the accumulation of FNR and VNR at focal contacts, and that FNR might also recognize substrate- bound vitronectin.
Linear stereo matching

Recent local stereo matching algorithms based on an adaptive-weight strategy achieve accuracy similar to global approaches. One of the major problems of these algorithms is that they are computationally expensive and this complexity increases proportionally to the window size. This paper proposes a novel cost aggregation step with complexity independent of the window size (i.e. O(1)) that outperforms state-of-the-art O(1) methods. Moreover, compared to other O(1) approaches, our method does not rely on integral histograms enabling aggregation using colour images instead of grayscale ones. Finally, to improve the results of the proposed algorithm a disparity refinement pipeline is also proposed. The overall algorithm produces results comparable to those of state-of-the-art stereo matching algorithms.
Slider: An Efficient Incremental Reasoner

The Semantic Web has gained substantial momentum over the last decade. It contributes to the manifestation of knowledge from data, and leverages implicit knowledge through reasoning algorithms. The main drawbacks of current reasoning methods over ontologies are two-fold: first they struggle to provide scalability for large datasets, and second, the batch processing reasoners who provide the best scalability so far are unable to infer knowledge from evolving data. We contribute to solving these problems by introducing Slider, an efficient incremental reasoner. Slider goes a significant step beyond existing system, including i) performance, by more than a 70% improvement in average compared to the fastest reasoner available to the best of our knowledge, and ii) inferences on streams of semantic data, by using intrinsic features that are themselves streams-oriented. Slider is fragment agnostic and conceived to handle expanding data with a growing background knowledge base. It natively supports pdf and RDFS, and its architecture allows to extend it to more complex fragments with a minimal effort. In this demo a web-based interface allows the users to visualize the internal behaviour of Slider during the inference, to better understand its design and principles.
Adaptive RF stealth beamforming for frequency diverse array radar

This paper proposes an adaptive radio frequency (RF) stealth beamforming for frequency diverse array (FDA) radar using spoiled frequency increments. Since active radars are highly visible to intercept receivers, traditional high-gain phased-array antenna beam is replaced by a series of low-gain FDA beam with nonlinear frequency increments to reduce the system visibility, and it achieves the same performance as the original high-gain by jointly exploiting the spoiled beams. Equivalently the detection performance is not degraded. Numerical simulation results verify the proposed method.
Results from the Fourth WMO Filter Radiometer Comparison for aerosol optical depth measurements

Abstract. This study presents the results of the Fourth Filter Radiometer Comparison that was held in Davos, Switzerland, between 28 September and 16 October 2015. Thirty filter radiometers and spectroradiometers from 12 countries participated including reference instruments from global aerosol networks. The absolute differences of all instruments compared to the reference have been based on the World Meteorological Organization (WMO) criterion defined as follows: 95% of the measured data has to be within 0.005 ± 0.001∕m (where m is the air mass). At least 24 out of 29 instruments achieved this goal at both 500 and 865 nm, while 12 out of 17 and 13 out of 21 achieved this at 368 and 412 nm, respectively. While searching for sources of differences among different instruments, it was found that all individual differences linked to Rayleigh, NO2, ozone, water vapor calculations and related optical depths and air mass calculations were smaller than 0.01 in aerosol optical depth (AOD) at 500 and 865 nm. Different cloud-detecting algorithms used have been compared. Angstrom exponent calculations showed relatively large differences among different instruments, partly because of the high calculation uncertainty of this parameter in low AOD conditions. The overall low deviations of these AOD results and the high accuracy of reference aerosol network instruments demonstrated a promising framework to achieve homogeneity, compatibility and harmonization among the different spectral AOD networks in the near future.
Lactotransferrin: A candidate tumor suppressor—Deficient expression in human nasopharyngeal carcinoma and inhibition of NPC cell proliferation by modulating the mitogen‐activated protein kinase pathway

Lactotransferrin (LTF) has been shown to regulate tumorogenesis. However, little is known about the role of LTF in regulating the development of human nasopharyngeal carcinoma (NPC). The aim of our study was to investigate whether LTF could regulate the development of NPC by characterizing the pattern of LTF expression in human NPC tissues using cDNA and tissue microarrays. Loss of LTF expression was observed in a significantly higher frequency of NPC tissues compared to that in nontumor nasopharyngeal epithelial tissues. While 61.25% of NPC tissues at the T1/T2 stage were positive for LTF expression, only 40.82% of NPC at the T3/T4 stage were stained by anti‐LTF. Similarly, 41.58% of NPC with local lymph node metastasis displayed LTF expression, a value significantly lower than the 46.36% in primary tumors (p < 0.05). These findings suggest that LTF may negatively regulate the development and metastasis of NPC in vivo. Furthermore, overexpression of or treatment with LTF inhibited the proliferation of NPC cells and promoted cell cycle arrest at the G0/G1 phase in vitro. While LTF treatment downregulated expression of cyclin D1 and phosphorylation of retinoblastoma protein (Rb), expression of p21 and p27 in 5–8F NPC cells was enhanced. Moreover, LTF treatment modulated the mitogen‐activated protein kinase (MAPK) pathway, but did not affect p53 and STAT3 expression in 5–8F NPC cells. Thus LTF is likely to be a candidate tumor suppressor and downregulates the development of NPC by inhibiting NPC proliferation through induction of cell cycle arrest and modulation of the MAPK signaling pathway. Therefore, our findings provide new insights in understanding the mechanism(s) underlying the action of LTF in regulating the development of human NPC. © 2008 Wiley‐Liss, Inc.
Fundamentals of spherical parameterization for 3D meshes

Parameterization of 3D mesh data is important for many graphics applications, in particular for texture mapping, remeshing and morphing. Closed manifold genus-0 meshes are topologically equivalent to a sphere, hence this is the natural parameter domain for them. Parameterizing a triangle mesh onto the sphere means assigning a 3D position on the unit sphere to each of the mesh vertices, such that the spherical triangles induced by the mesh connectivity are not too distorted and do not overlap. Satisfying the non-overlapping requirement is the most difficult and critical component of this process. We describe a generalization of the method of barycentric coordinates for planar parameterization which solves the spherical parameterization problem, prove its correctness by establishing a connection to spectral graph theory and show how to compute these parameterizations.
An Algorithm for Distributed Lag Estimation Subject to Piecewise Monotonic Coe-cients

Linearly distributed-lag models as a time series tool have very useful applications in many dis- ciplines. In these models, the dependent variable de- pends on one independent variable and its lags. The speciflcation of the lag coe-cients is a crucial ques- tion to the e-cacy of a model. A new algorithm is proposed for the estimation of lag coe-cients subject to the condition that the sequence of the coe-cient estimates consists of a certain number of monotonic sections, where the positions of the extrema are also unknowns. The algorithm is iterative, each iteration taking a conjugate gradient step, then forming an esti- mate of the coe-cients and flnally adjusting this esti- mate to satisfy the given constraints. An immediate advantage is that the inversion of an ill-conditioned matrix that frequently occurs in practice is avoided. Moreover, the constraints provide a realistic repre- sentation of the prior knowledge and the calculation results in a highly e-cient time series estimation. The algorithm and its convergence are described, results from simulation experiments are presented and an application of the algorithm on real annual macroe- conomic data concerning the personal consumption expenditures against the GDP for the U.S.A. during 1929 - 2006 is given.
Central American mothers report family history of depression and alcohol abuse as a predictor of teenage health risk behaviors

Purpose: The purpose of this study was to explore the relationships of family history of depression and alcohol abuse as a predictor of health risk behaviors among Central American teenagers. Data sources: Demographic data were collected from a convenience sample of 101 Central American mothers with a teenage daughter ages 12–17 years who were living in Northern Virginia. The research questions assessed the family history of depression, alcohol abuse, and maternal depression. Scores were calculated to predict risk of teenage health risk behaviors. Conclusions: The Hispanic mothers in this study reported that their teenagers had significant health risk behaviors, including school dropout and expulsion, alcohol and substance use, pregnancy, and gang membership. Family history of depression and alcohol abuse in a first degree relative predicted teenage risk behavior 71% of the time. Clinical Implications: There is no consensus on a standard screening approach for depression in teenagers. Developing a standardized approach to gathering information from teenagers that includes genetic family traits may have significant effects on interventions for teenage health risk behavior and ways to provide the best services for vulnerable teenagers. The results of this study have implications for nurse practitioners caring for teenagers.
Role of Projections from Ventral Medial Prefrontal Cortex to Nucleus Accumbens Shell in Context-Induced Reinstatement of Heroin Seeking

In humans, exposure to contexts previously associated with heroin use can provoke relapse. In rats, exposure to heroin-paired contexts after extinction of drug-reinforced responding in different contexts reinstates heroin seeking. This effect is attenuated by inhibition of glutamate or dopamine transmission in nucleus accumbens shell, or inactivation of ventral medial prefrontal cortex (mPFC). Here, we used an anatomical asymmetrical disconnection procedure to demonstrate that an interaction between glutamatergic projections from ventral mPFC to accumbens shell and local dopamine D1 postsynaptic receptors contributes to context-induced reinstatement of heroin seeking. We also combined the marker of neuronal activity, Fos, with the retrograde tracer Fluoro-Gold to assess activation in this pathway during context-induced reinstatement. Rats were trained to self-administer heroin for 12 d; drug infusions were paired with a discrete tone–light cue. Lever pressing was subsequently extinguished in a nondrug-associated context in the presence of the discrete cue. Rats were then tested in the heroin- or extinction-associated contexts under extinction conditions. Injections of muscimol + baclofen into ventral mPFC in one hemisphere and D1-family receptor antagonist SCH 23390 into the contralateral or ipsilateral accumbens shell decreased context-induced reinstatement. Unilateral injections of muscimol + baclofen into ventral mPFC or SCH 23390 into the accumbens shell had no effect. Context-induced reinstatement was associated with increased Fos expression in ventral mPFC neurons, including those projecting to accumbens shell, with higher double-labeling in the ipsilateral projection than in the contralateral projection. Our results demonstrate that activation of glutamatergic projections from ventral mPFC to accumbens shell, previously implicated in inhibition of cocaine relapse, promotes heroin relapse.
Economic Activity and Trends in Ambient Air Pollution

Background One challenge in assessing the health effects of human exposure to air pollution in epidemiologic studies is the lack of widespread historical air pollutant monitoring data with which to characterize past exposure levels. Objectives Given the availability of long-term economic data, we relate economic activity levels to patterns in vehicle-related particulate matter (PM) over a 30-year period in New Jersey, USA, to provide insight into potential historical surrogate markers of air pollution. Methods We used statewide unemployment and county-level trucking industry characteristics to estimate historical coefficient of haze (COH), a marker of vehicle-related PM predominantly from diesel exhaust. A total of 5,920 observations were included across 25 different locations in New Jersey between 1971 and 2003. Results A mixed-modeling approach was employed to estimate the impact of economic indicators on measured COH. The model explained approximately 50% of the variability in COH as estimated by the overall R2 value. Peaks and lows in unemployment tracked negatively with similar extremes in COH, whereas employment in the trucking industry was positively associated with COH. Federal air quality regulations also played a large and significant role in reducing COH levels over the study period. Conclusions This new approach outlines an alternative method to reconstruct historical exposures that may greatly aid epidemiologic research on specific causes of health effects from urban air pollution. Economic activity data provide a potential surrogate marker of changes in exposure levels over time in the absence of direct monitoring data for chronic disease studies, but more research in this area is needed.
Interference cancellation based on compressive sensing for passive coherent radar (PACOR)

Interference cancellation is crucial for passive radar and has been well developed. A novel interference cancellation model based on compressive sensing (CS) is proposed in this paper. The sparse matrix is constructed by exploiting the sparsity of the interference signal in delay-Doppler domain, with each column of which is the cross ambiguity function (CAF) of a delayed and Doppler shifted replica of the reference signal. However, the generation of the sparse matrix will be computationally extensive by routine processing, so a fast method is developed based on the fact that all the CAFs can be obtained from the self-ambiguity function (SAF) of the reference signal by approximating. The orthogonal matching pursuit (OMP) algorithm is then applied to obtain the estimator of the sparse vector, which includes the information of the complex amplitude, delay and Doppler of the interference signal. With these parameters, the interference signal is reconstructed and removed from the surveillance signal. Besides dealing with both the stationary and moving clutter, the proposed cancellation algorithm can eliminate the strong target if required by modifying parameters accordingly. Simulation results show that the residual power of interference after cancellation is extremely low, which is meaningful for weak target detection.
Adaptive resource allocation for wildlife protection against illegal poachers

Illegal poaching is an international problem that leads to the extinction of species and the destruction of ecosystems. As evidenced by dangerously dwindling populations of endangered species, existing anti-poaching mechanisms are insufficient. This paper introduces the Protection Assistant for Wildlife Security (PAWS) application - a joint deployment effort done with researchers at Uganda's Queen Elizabeth National Park (QENP) with the goal of improving wildlife ranger patrols. While previous works have deployed applications with a game-theoretic approach (specifically Stackelberg Games) for counter-terrorism, wildlife crime is an important domain that promotes a wide range of new deployments. Additionally, this domain presents new research challenges and opportunities related to learning behavioral models from collected poaching data. In addressing these challenges, our first contribution is a behavioral model extension that captures the heterogeneity of poachers' decision making processes. Second, we provide a novel framework, PAWS-Learn, that incrementally improves the behavioral model of the poacher population with more data. Third, we develop a new algorithm, PAWS-Adapt, that adaptively improves the resource allocation strategy against the learned model of poachers. Fourth, we demonstrate PAWS's potential effectiveness when applied to patrols in QENP, where PAWS will be deployed.
Human single-neuron responses at the threshold of conscious recognition

We studied the responses of single neurons in the human medial temporal lobe while subjects viewed familiar faces, animals, and landmarks. By progressively shortening the duration of stimulus presentation, coupled with backward masking, we show two striking properties of these neurons. (i) Their responses are not statistically different for the 33-ms, 66-ms, and 132-ms stimulus durations, and only for the 264-ms presentations there is a significantly higher firing. (ii) These responses follow conscious perception, as indicated by the subjects' recognition report. Remarkably, when recognized, a single snapshot as brief as 33 ms was sufficient to trigger strong single-unit responses far outlasting stimulus presentation. These results suggest that neurons in the medial temporal lobe can reflect conscious recognition by “all-or-none” responses.
Molecular Sciences Synthesis, Characterization and Thermal Studies of Zn(ii), Cd(ii) and Hg(ii) Complexes of N-methyl-n-phenyldithiocarbamate: the Single Crystal Structure of [(c 6 H 5 )(ch 3 )ncs 2 ] 4 Hg 2

Zn(II), Cd(II) and Hg(II) complexes of N-methyl-N-phenyl dithiocarbamate have been synthesized and characterized by elemental analysis and spectral studies (IR, 1 H and 13 C-NMR). The single crystal X-ray structure of the mercury complex revealed that the complex contains a Hg centre with a distorted tetrahedral coordination sphere in which the dinuclear Hg complex resides on a crystallographic inversion centre and each Hg atom is coordinated to four S atoms from the dithiocarbamate moiety. One dithiocarbamate ligand acts as chelating ligand while the other acts as chelating bridging ligand between two Hg atoms, resulting in a dinuclear eight-member ring. The course of the thermal degradation of the complexes has been investigated using thermogravimetric and differential thermal analyses techniques. Thermogravimetric analysis of the complexes show a single weight loss to give MS (M = Zn, Cd, Hg) indicating that they might be useful as single source precursors for the synthesis of MS nanoparticles and thin films.
Uncoupled Analysis of Stochastic Reaction Networks in Fluctuating Environments

The dynamics of stochastic reaction networks within cells are inevitably modulated by factors considered extrinsic to the network such as, for instance, the fluctuations in ribosome copy numbers for a gene regulatory network. While several recent studies demonstrate the importance of accounting for such extrinsic components, the resulting models are typically hard to analyze. In this work we develop a general mathematical framework that allows to uncouple the network from its dynamic environment by incorporating only the environment's effect onto the network into a new model. More technically, we show how such fluctuating extrinsic components (e.g., chemical species) can be marginalized in order to obtain this decoupled model. We derive its corresponding process- and master equations and show how stochastic simulations can be performed. Using several case studies, we demonstrate the significance of the approach.