Miracle-dz/UniFAR-FTUs huggingface dataset:
Bio-inspired model with dual visual pathways for human action recognition

Spatio-temporal interesting points feature is a key technology for a wide class of computer vision approaches to recognize human actions. In this paper, a novel bio-inspired model based spatio-temporal interesting points (BIM-STIP) framework is proposed. Different from traditional STIP framework, the introduction of bio-inspired model provides a biological theory for interest points detection and spatio-temporal descriptor construction. Moreover, unlike existing bio-inspired model for action recognition with a single pathway, a dual pathway joint model with dorsal stream and ventral stream is constructed. Finally, this paper demonstrate how these feature to be used in a standard STIP framework for action recognition. Promising experimental results show that the proposed framework outperforms most of existing algorithms in action recognition, which encourages us to develop the BIM-STIP framework to other applications in future.
Characterization of a 10Hz double-pulse non-normal incidence pumped transient collisional Ni-like molybdenum soft x-ray laser for applications

Stable and reliable operation of a nickel-like molybdenum transient collisional soft x-ray laser at 18.9 nm demonstrated and studied with a 10Hz Ti:sapphire laser system proves the suitability of the double-pulse non-normal incidence pumping geometry for table-top high repetition soft x-ray lasers and broadens the attractiveness of x-ray lasers as sources of coherent radiation for various applications. X-ray laser emission with pulse energies well above 1 μJ is obtained for several hours at 10Hz repetition-rate without re-alignment under optimized double pumping pulse parameters including energy ratio, time delay, pulse duration and line focus width.
Monoclonal antibodies and conventional antisera to the GABAA receptor/benzodiazepine receptor/Cl- channel complex

Monoclonal antibodies (mAbs) and conventional antisera were raised to the affinity-purified GABAA receptor/benzodiazepine receptor/Cl- channel complex. The antibodies immunoprecipitated the affinity- purified complex in Triton X-100 and also reacted with the complex in a solid-phase radioimmunoassay. Immunoblots indicated that the mAb 62–3G1 reacted with the 57,000 Mr peptide subunit of the affinity-purified complex, while the antisera mainly reacted with the 51,000 Mr peptide subunit. The mAbs and the antisera also immunoprecipitated the GABAA receptor/benzodiazepine receptor/Cl- channel complex after being solubilized from cerebral cortex membranes by the zwitterionic detergent CHAPS. The immunoprecipitated complex bound 3H-muscimol, 3H- flunitrazepam (FNZ) and 35S-t-butylbicyclophosphorothionate (TBPS). The 3H-FNZ binding was stimulated by GABA, indicating that the functional interactions among the immunoprecipitated components of the complex were preserved. The mAb 62–3G1 also recognized the 57,000 Mr peptide in immunoblots with crude brain membranes. Immunocytochemistry experiments showed that the binding of both the mAb 62–3G1 and 3H-muscimol colocalized throughout the brain. The results suggest that (1) the 57,000 Mr peptide is the muscimol (GABAA receptor agonist) binding peptide of the complex, and (2) in the cerebral cortex, most of the GABAA receptors (GABARs), benzodiazepine receptors (BDZRs), and Cl- channels are physically coupled to one another.
CHARACTERIZATION OF DYNAMIC ASPERITY SOURCE MODELS FOR SIMULATING STRONG GROUND MOTION

Asperity source models are important since recent studies have clarified that the main contribution to strong ground motion comes from the asperity area. These models are defined by the fault parameters: fault area, average slip, maximum slip, peak slip velocity, and stress drop both of the overall fault and asperity area. The ratios of these parameters between the asperity and the total rupture area, together with the scaling relations of fault models, make feasible the definition of the asperity source model. Since dynamic rupture models take into account the physical conditions of the friction and stress distribution across the fault, we estimated the ratios between the above parameters from dynamic models capturing more realistic seismic source properties. We started assuming that the combined asperity area is 0.22 times the total rupture area as following the slip characterization for kinematic models of Somerville et al. [1]. Subsurface earthquakes, represented as circular faults, and surface earthquakes, represented as rectangular faults that break the free-surface, are simulated for single and multiple asperities. We assumed different conditions of stress drop surrounding the asperity (background area) that vary from –0.2 to 0.2 times the stress drop of the asperity area. A fixed rupture velocity (0.8 of Swave velocity) and the simple slip-weakening friction model on the fault were used for the dynamic rupture propagation. The dynamic rupture simulation suggests that the characterized source model of Somerville et al. [1] is valid when the ratios of stress drop between the background and asperity is between –0.05 to 0.1 for sub-surface earthquakes and between –0.15 to 0.05 for surface earthquakes. We also found that the average peak slip velocity in the background area with zero stress drop is around 0.3 times the one in the asperity area. These characterized parameters verified by dynamic faulting are playing an important role for practical application of strong ground motion prediction.
Model-Based Investigations of Different Vector-Related Intervention Strategies to Eliminate Visceral Leishmaniasis on the Indian Subcontinent

The elimination of infectious diseases requires reducing transmission below a certain threshold. The Visceral Leishmaniasis (VL) Elimination Initiative in Southeast Asia aims to reduce the annual VL incidence rate below 1 case per 10,000 inhabitants in endemic areas by 2015 via a combination of case management and vector control. Using a previously developed VL transmission model, we investigated transmission thresholds dependent on measures reducing the sand fly density either by killing sand flies (e.g., indoor residual spraying and long-lasting insecticidal nets) or by destroying breeding sites (e.g., environmental management). Model simulations suggest that elimination of VL is possible if the sand fly density can be reduced by 67% through killing sand flies, or if the number of breeding sites can be reduced by more than 79% through measures of environmental management. These results were compared to data from two recent cluster randomised controlled trials conducted in India, Nepal and Bangladesh showing a 72% reduction in sand fly density after indoor residual spraying, a 44% and 25% reduction through the use of long-lasting insecticidal nets and a 42% reduction after environmental management. Based on model predictions, we identified the parameters within the transmission cycle of VL that predominantly determine the prospects of intervention success. We suggest further research to refine model-based predictions into the elimination of VL.
Drs. Muth and Mills Meet Dr. Tiebout: Integrating Location-Specific Amenities into Multi-Community Equilibrium Models

We consider the problem of integrating spatial amenities into locational equilibrium models with multiple jurisdictions. We provide sufficient conditions under which models that assume a single housing price in each community continue to apply in the presence of location-specific amenities that vary both within and across communities. If these conditions are satisfied, the models, estimation methods, and results in Epple and Sieg (1999) are valid in the presence of (potentially unobserved) location-specific amenities. We also show how to construct sufficient statistics that capture location specific spatial heterogeneity. We apply these techniques using data from the Pittsburgh metropolitan area. We find that these amenity measures capture proximity to important local employment centers as well as heterogeneity in school quality within a given school district.
Causes for segmentation of keying sequences: a predictive model

Literature has been studied to find potential causes of segmentation during motor learning of a keying sequence in an attempt to make it possible to predict the segmentation of any sequence for any person. A categorization of causes for segmentation (also patterns or salient points) of a keying sequence has been made; procedural causes, sequence based causes, and participant related causes. It was investigated whether participants will segment a sequence at a salient point in the sequence, indicating predictability in segmentation might be possible. Inter hand transitions (IHTs) and runs of consecutive keys were chosen as salient points. Also, it was investigated whether a sequence entirely made up of salient points with one key transition without such a salient point would segment at the ‘dull point’, it did not. Little evidence for a successful prediction of consistent segmentation using IHTs was found, none using runs. Interpretation of the data was hindered by finger effects due to incomplete balancing. Recommendations for future experiments are given.
Clinicoeconomics and Outcomes Research Dovepress Cost-effectiveness of Edoxaban versus Rivaroxaban for Stroke Prevention in Patients with Nonvalvular Atrial Fibrillation (nvaf) in the Us

you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms Background: Understanding the value of new anticoagulation therapies compared with existing therapies is of paramount importance in today's cost-conscious and efficiency-driven health care environment. Edoxaban and rivaroxaban for stroke prevention in nonvalvular atrial fibrillation (NVAF) patients with CHADS 2 scores $2 have been evaluated in pivotal trials versus warfarin. The relative value of edoxaban versus rivaroxaban would be of interest to health care stakeholders and patients who prefer a once-daily treatment option for long-term stroke prevention in NVAF. Objective: To evaluate the relative cost-effectiveness of two once-daily regimens of novel oral anticoagulation therapy – edoxaban (60 mg/30 mg dose-reduced) versus rivaroxaban (20 mg/15 mg dose-reduced) – for stroke prevention in NVAF patients from a US health-plan perspective. Materials and methods: A Markov model simulated lifetime risk and treatment of stroke, systemic embolism, major bleeding, clinically relevant nonmajor bleeding, myocardial infarc-tion, and death in NVAF patients treated with edoxaban or rivaroxaban. Efficacy and safety data were derived from a network meta-analysis that utilized data from patients enrolled in ENGAGE AF-TIMI 48 and ROCKET-AF. Health care cost and utility data were obtained from published sources. Incremental cost-effectiveness ratios of ,US$50,000, $50,000–$150,000, and . $150,000 per quality-adjusted life year (QALY) gained were used as thresholds for " highly cost-effective " , " cost-effective " , and " not cost-effective " treatment options, respectively, as per American Heart Association/American College of Cardiology guidelines. Results: Edoxaban was dominant relative to rivaroxaban, such that it was associated with lower total health care costs and better effectiveness in terms of QALYs in the base-case analysis. Results were supported by probabilistic sensitivity analyses that showed edoxaban as either dominant or a highly cost-effective alternative (incremental cost-effectiveness ratio ,$50,000) to rivaroxaban in 88.4% of 10,000 simulations. Conclusion: Results of this study showed that the once-daily edoxaban (60 mg/30 mg dose-reduced) regimen is a cost-saving or highly cost-effective treatment relative to rivaroxaban (20 mg/15 mg dose-reduced) for stroke prevention in NVAF patients with CHADS 2 $2.
Considerations for using bacteriophages for plant disease control

The use of bacteriophages as an effective phage therapy strategy faces significant challenges for controlling plant diseases in the phyllosphere. A number of factors must be taken into account when considering phage therapy for bacterial plant pathogens. Given that effective mitigation requires high populations of phage be present in close proximity to the pathogen at critical times in the disease cycle, the single biggest impediment that affects the efficacy of bacteriophages is their inability to persist on plant surfaces over time due to environmental factors. Inactivation by UV light is the biggest factor reducing bacteriophage persistence on plant surfaces. Therefore, designing strategies that minimize this effect are critical. For instance, application timing can be altered: instead of morning or afternoon application, phages can be applied late in the day to minimize the adverse effects of UV and extend the time high populations of phage persist on leaf surfaces. Protective formulations have been identified which prolong phage viability on the leaf surface; however, UV inactivation continues to be the major limiting factor in developing more effective bacteriophage treatments for bacterial plant pathogens. Other strategies, which have been developed to potentially increase persistence of phages on leaf surfaces, rely on establishing non-pathogenic or attenuated bacterial strains in the phyllosphere that are sensitive to the phage(s) specific to the target bacterium. We have also learned that selecting the correct phages for disease control is critical. This requires careful monitoring of bacterial strains in the field to minimize development of bacterial strains with resistance to the deployed bacteriophages. We also have data that indicate that selecting the phages based on in vivo assays may also be important when developing use for field application. Although bacteriophages have potential in biological control for plant disease control, there are major obstacles, which must be considered.
Learning to estimate user interest utilizing the variational Bayes estimator

Many studies of man-machine interaction using eye trackers have been tackled over recent decades. In this paper, we present a new learning system to estimate user interest with gaze sensory information. In short, a statistical learning scheme, especially the variational Bayes (VB), is incorporated for building probabilistic model parameters, dealing with the uncertainty of estimated user interest. Several computational results show how the VB can cope with user interest estimation, by selectively modeling their uncertainty.
Beat-to-beat analysis of P waves in patient with atrial fibrillation history

P wave morphology has been shown to be modified in patients with paroxysmal atrial fibrillation (AF) and in healthy subjects of different age. These changes are commonly evaluated in the signal averaged ECG, thus in average P waves. Aim of this study is to assess beat-to-beat variations in P wave characteristics. Five-minute 12-lead ECG were recorded from 10 healthy subjects (C group), 10/10 patients with/without an AF recurrence (R/NR groups), after electrical cardioversion. Principal component analysis was performed on a beat-to-beat basis. The dynamic of the first three eigenvalues series and the beat-to-beat variability of the first three principal components (PCs) morphology were analyzed by calculating the distance between the average morphology over all the beats acquired and the morphology identified on each beat for the first three PCs. Most of the indexes were statistically different between C group and the patients with history of AF, highlighting higher regularity of the eigenvalues series as well as more similar PCs in healthy subjects. In addition, the series of the first eigenvalues was significantly less regular in R group compared NR group (Reg: 0.029 ± 0.020, 0.062 ± 0.033, p<0.05, R vs NR group).
Blind estimation of timing errors in interleaved AD converters

Parallel A/D converter structures is one way to increase the sampling rate. Instead of increasing the sample rate in one A/D converter, several A/D converters with lower sampling rate can be used instead. A problem in these structures is that the time between samples is usually not equal because there are errors in the delays between the A/D converters. We present a method to estimate the timing offset errors. The estimation algorithm works without any special calibration signal, instead the normal input signal is used. The only assumption that we need on the input signal is that most of the energy is concentrated to a low pass band, below about 1/3 of the Nyquist frequency. Simulations of the time-interleaved A/D converter show that the method estimates the errors with high accuracy.
DTI and MR Volumetry of Hippocampus-PC/PCC Circuit: In Search of Early Micro- and Macrostructural Signs of Alzheimers's Disease

Hippocampal damage, by DTI or MR volumetry, and PET hypoperfusion of precuneus/posterior cingulate cortex (PC/PCC) were proposed as biomarkers of conversion from preclinical (MCI) to clinical stage of Alzheimer's disease (AD). This study evaluated structural damage, by DTI and MR volumetry, of hippocampi and tracts connecting hippocampus to PC/PCC (hipp-PC/PCC) in 10 AD, 10 MCI, and 18 healthy controls (CTRL). Normalized volumes, mean diffusivity (MD), and fractional anisotropy (FA) were obtained for grey matter (GM), white matter (WM), hippocampi, PC/PCC, and hipp-PC/PCC tracts. In hippocampi and hipp-PC/PCC tracts, decreased volumes and increased MD were found in AD versus CTRL (P < .001). The same results with lower significance (P < .05) were found in MCI versus CTRL. Verbal memory correlated (P < .05) in AD with left hippocampal and hipp-PC/PCC tract MD, and in MCI with FA of total WM. Both DTI and MR volumetry of hippocampi and hipp-PC/PCC tracts detect early signs of AD in MCI patients.
Inflation Uncertainty and Interest Rates: Theory and Empirical Tests

This paper develops two models, one involving risk neutrality and the other risk aversion, which suggest that inflation uncertainty affects interest rates. Both models give rise to essentially the same interest rate equation for estimation. Empirical evidence supports the hypothesis that inflation uncertainty affects interest rates. Interpreted in terms of the risk neutral model, the empirical results suggest that inflation uncertainty has a negative impact on nominal interest rates and a positive impact on the expected real rate. If the results are interpreted in terms of the risk averse model, inflation uncertainty has a negative impact on nominal interest rates. The expected real rate is not of direct interest in a risk averse world. The results raise real questions about the use of the Fisherian definition of the real interest rate in situations when there is uncertainty about inflation rates. It is argued that even with risk neutrality the Fisherian definition of the real rate is not the appropriate concept upon which to base economic decisions if inflation uncertainty is present. The appropriate concept is an expected real rate which involves an adjustment for uncertainty. Moreover, if the world is risk averse, the expected real rate is not a relevant concept for economic decisions.
Minimal-Bracketing Sets for High-Dynamic-Range Image Capture

This paper considers the problem of high-dynamic-range (HDR) image capture using low-dynamic-range (LDR) cameras. We present three different minimal-bracketing algorithms for computing minimum-sized exposure sets bracketing of HDR scenes. Each algorithm is applicable to a different HDR-imaging scenario depending on the amount of target-scene-irradiance information and real-time image processing available at the time of image acquisition. We prove the optimality of each algorithm with respect to its ability to obtain a theoretically minimum-size bracketing set of exposures. We also provide closed-form expressions for computing minimal-bracketing exposure sets for two common types of HDR-imaging systems, those with geometrically varying and arithmetically varying exposure settings. We experimentally demonstrate the advantages of the proposed methods by capturing and processing multiple HDR scenes using minimal-bracketing and 1-stop bracketing methods. The results show that minimal-bracketing can be used to produce high-quality HDR images, while requiring only one third as many LDR images be acquired compared to 1-stop bracketing. We also perform a detailed SNR analysis that quantifies the tradeoff between signal-to-noise ratio and image-bracketing-set size.
Executive Stock Options , Risk Taking , and Performance

While the relation between equity-based compensation and firm performance has been widely discussed, a comprehensive study of how executive stock options (ESOs) affect firm value still remains open. This research intends to examine the risk-taking effect of executive stock options on firm performance with consideration ofmanagers’ personal risk aversion.3SLS is adopted to examine a system with an equation of option compensation, an equation of risk-taking, and an equation of performance. The evidences confirm that executive stock options increase managerial risk taking, but such risk taking is stil constrained by managers’ personal risk aversion. Higher managerial option holding actually decrease risk taking. The evidences indicate that managerial risk taking induced by ESOs would increase long-term stock price, but decrease long-term return on investments. On the other hand, the risk taking effect of ESOs increases both near-term stock return and near-term return on investment. Such results may be referred to that managers concern more about stock price increase when they make investment decision. That is, the purpose of awarding ESO to executives is not well-responded and ESO awards are not well-designed to increase the firm value and wealth of shareholders who hold the firms’shares in the long-term manner. A robustness check is done by taking capital investment as endogenous variable jointly determined with ESOs. The evidences confirm the results that risk-taking effect of ESOs increases long-term stock return but decreases long-term return on investment.
Optimal coverage of Wireless Sensor Network using Termite Colony Optimization Algorithm

Due to great advancement in the field of science and technology, Wireless Sensor Network (WSN) has been become one of the most attractive and intriguing research area in last few years. Large-scale sensor networks has been deployed by interconnecting several hundred to a few thousand sensors nodes opens up diverse technical challenges and tremendous application possibilities. This paper presents a Termite Colony Optimization (TCO) algorithm, an adaptable and balanced way, which optimizes a minimal number of sensors while covering a maximum area. TCO is a population based metaheuristic approach developed from the intelligent behavior of termite that is known to us as Swarm Intelligence. It has the ability to solve the presented problem in efficient way that has shown more effectiveness and robustness compared to other population based algorithms. In this paper, we have justified our simulation results with the results of other papers. After that we have experimented with varying different parameters like grid size, number of sensors and termites. It has also proved the capability of our TCO over the constraints and difficulties as well.
Do Media Consumers Really Dislike Advertising? An Empirical Assessment of a Popular Assumption in Economic Theory

This paper uses data on the population of German magazines for the period 1973 to 2004 to show that, contrary to conventional wisdom, there is little evidence for magazine readers disliking advertising. Many magazines in fact have readers who appreciate advertising. The degree of appreciation increases in reader age and decreases with income as well as with education.