Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of the SWMM model uncertainties within the generalized likelihood uncertainty estimation (GLUE) framework for a high‐resolution urban sewershed

This research incorporates the generalized likelihood uncertainty estimation (GLUE) methodology in a high‐resolution Environmental Protection Agency Storm Water Management Model (SWMM), which we developed for a highly urbanized sewershed in Syracuse, NY, to assess SWMM modelling uncertainties and estimate parameters. We addressed two issues that have long been suggested having a great impact on the GLUE uncertainty estimation: the observations used to construct the likelihood measure and the sampling approach to obtain the posterior samples of the input parameters and prediction bounds of the model output. First, on the basis of the Bayes' theorem, we compared the prediction bounds generated from the same Gaussian distribution likelihood measure conditioned on flow observations of varying magnitude. Second, we employed two sampling techniques, the sampling importance resampling (SIR) and the threshold sampling methods, to generate posterior parameter distributions and prediction bounds, based on which the sampling efficiency was compared. In addition, for a better understanding of the hydrological responses of different pervious land covers in urban areas, we developed new parameter sets in SWMM representing the hydrological properties of trees and lawns, which were estimated through the GLUE procedure. The results showed that SIR was a more effective alternative to the conventional threshold sampling method. The combined total flow and peak flow data were an efficient alternative to the intensive 5‐min flow data for reducing SWMM parameter and output uncertainties. Several runoff control parameters were found to have a great effect on peak flows, including the newly introduced parameters for trees. Copyright © 2013 John Wiley & Sons, Ltd.
Event-based RGB-D sensing with structured light

Event-based cameras (ECs) are bio-inspired sensors that asynchronously report brightness changes for each pixel. Due to their high dynamic range, pixel bandwidth, temporal resolution, low power consumption, and computational simplicity, they are beneficial for vision-based projects in challenging lighting conditions and they can detect fast movements with their microsecond response time. The first generation of ECs are monochrome, but color data is very useful and sometimes essential for certain vision-based applications. The latest technology enables manufacturers to build color ECs, trading off the size of the sensor and substantially reducing the resolution compared to monochrome models, despite having the same bandwidth. In addition, ECs only detect changes in light and do not show static or slowly moving objects. We introduce a method to detect full RGB events using a monochrome EC aided by a structured light projector. The projector emits rapidly changing RGB patterns of light beams on the scene, the reflection of which is captured by the EC. We combine the benefits of ECs and projection-based techniques and allow depth and color detection of static or moving objects with a commercial TI LightCrafter 4500 projector and a monocular monochrome EC, paving the way for frameless RGB-D sensing applications.
Design of Electric Vehicle Battery Management System

The Battery Management System (BMS) is a fundamental component of electric vehicles, primarily utilized to ensure battery safety and enhance battery lifespan. This article presents a design for both the hardware and software components of the BMS, enabling battery monitoring and management. The hardware component encompasses the design of voltage acquisition circuitry, second-order filtering circuitry, sampling and holding circuitry, CAN bus communication circuitry, and other relevant features. The software section comprises subroutines for battery information collection, equalization circuitry, SOC estimation, and other relevant features. The BMS developed in this study successfully collects voltage, temperature, current, and other relevant information, and accurately estimates SOC and other crucial parameters. Testing confirmed that the battery management system precisely collects battery voltage, current, and temperature information, while the SOC estimation achieves a relatively high degree of accuracy.
Paradoxes of Learning: On Becoming An Individual in Society

Preface. Part 1 The Development of the Social Self. 1 The Nature of Human Learning. 2 The Paradox of Living and Learning in Society. 3 Being and the Birth of the Self. 4 Understanding Conscious Action. 5 Learning and Action. 6 Interests and Learning. Part 2: Personal Growth Through Lifelong Learning. 7 Being a Person. 8 Authenticity, Autonomy and Self-Directed Learning. 9 Being and Having. 10 Meaning and Truth. 11 Learning, Personhood and the Workplace. 12 Aging and Wisdom. 13 Learning and Change. 14 The Political Dimension of Learning. 15 Implications for Teaching and Education. References. Index.
An assessment of sampling biases across studies of diel activity patterns in marine ray-finned fishes (Actinopterygii)

Understanding the promotion and regulation of circadian rhythms in marine fishes is important for studies spanning conservation, evolutionary biology, and physiology. Given numerous challenges inherent to quantifying behavioral activity across the full spectrum of marine environments and fish biodiversity, case studies offer a tractable means of gaining insights or forecasting broad patterns of diel activity. As these studies continue to accumulate, assessing whether, and to what extent, the cumulatively collected data are biased in terms of geography, habitat, or taxa represents a fundamentally important step in the development of a broad overview of circadian rhythms in marine fish. As such investigations require a phylogenetic framework, general trends in the phylogenetic sampling of marine fishes should be simultaneously assessed for biases in the sampling of taxa and trait data. Here, we compile diel activity data for more than 800 marine species from more than five decades of scientific studies to assess general patterns of bias. We found significant geographic biases that largely reflect a preference toward sampling warm tropical waters. Additionally, taxonomic biases likewise reflect a tendency toward conspicuous reef associated clades. Placing these data into a phylogenetic framework that includes all known marine fishes revealed significant under-dispersion of behavioral data and taxon sampling across the whole tree, with a few subclades exhibiting significant over-dispersion. In total, our study illuminates substantial gaps in our understanding of diel activity patterns and highlights significant sampling biases that have the potential to mislead evolutionary or ecological analyses.
Daily changes and short-term exposure patterns in time series studies of air pollution and acute health effects

This thesis investigated the effects of daily changes in exposure (delta) and short-term exposure patterns on the relationship between air pollution and health in time series studies. Using data from London and Hong Kong, delta was defined as the difference in particulate matter (PM10) concentration between successive days. Short-term exposure pattern series were defined based on number of peaks in PM10 within rolling weekly blocks. The mathematical equivalence of identifiable models for delta with conventional distributed lag model was derived and alternative model specifications were proposed. Measurement error and missing data exhibited more impact on delta than the absolute metrics in simulation studies. Evidence of association for delta PM10 with mortality was found only in Hong Kong which attenuated towards the null with more rigorous adjustment for weather. The pattern analysis approach hypothesized, in addition to amount (dose) and duration of exposure, epidemiological studies ought to take patterns of exposure into account. However, convincing evidence was not found for the effect of short-term exposure patterns on mortality risk estimates both in London and Hong Kong. Refining the definition of exposure patterns and methodological improvements including analysing data from multiple cities are highly recommended in related studies in the future.
Robotics and Autonomous Systems Timed Trajectory Generation Using Dynamical Systems: Application to a Puma Arm

We present an attractor based dynamics that autonomously generates trajectories with stable timing (limit cycle solutions), stably adapted to changing online sensory information. Autonomous differential equations are used to formulate a dynamical layer with either stable fixed points or a stable limit cycle. A neural competitive dynamics switches between these two regimes according to sensorial context and logical conditions. The corresponding movement states are then converted by simple coordinate transformations and an inverse kinematics controller into spatial positions of a robot arm. Movement initiation and termination is entirely sensor driven. In this article, the dynamic architecture was changed in order to cope with unreliable sensor information by including this information in the vector field. We apply this architecture to generate timed trajectories for a Puma arm which must catch a moving ball before it falls over a table, and return to a reference position thereafter. Sensory information is provided by a camera mounted on the ceiling over the robot. A flexible behavior is achieved. Flexibility means that if the sensorial context changes such that the previously generated sequence is no longer adequate, a new sequence of behaviors, depending on the point at which the changed occurred and adequate to the current situation emerges. The evaluation results illustrate the stability and flexibility properties of the dynamical architecture as well as the robustness of the decision-making mechanism implemented.
Author's Personal Copy Spatially Sparse Source Cluster Modeling by Compressive Neuromagnetic Tomography

a r t i c l e i n f o 1-norm convex optimization MEG EEG Compressed sensing Wavelet transform Magnetoencephalography enables non-invasive detection of weak cerebral magnetic fields by utilizing super-conducting quantum interference devices (SQUIDs). Solving the MEG inverse problem requires reconstructing the locations and orientations of the underlying neuronal current sources based on the extracranial measurements. Most inverse problem solvers explicitly favor either spatially more focal or diffuse current source patterns. Naturally, in a situation where both focal and spatially extended sources are present, such reconstruction methods may yield inaccurate estimates. To address this problem, we propose a novel ComprEssive Neuromagnetic Tomography (CENT) method based on the assumption that the current sources are compressible. The compressibility is quantified by the joint sparsity of the source representation in the standard source space and in a transformed domain. The purpose of the transformation sparsity constraint is to incorporate local spatial structure adaptively by exploiting the natural redundancy of the source configurations in the transform domain. By combining these complementary constraints of standard and transformed domain sparsity we obtain source estimates, which are not only locally smooth and regular but also form globally separable clusters. In this work, we use the ℓ 1-norm as a measure of sparsity and convex optimization to yield compressive estimates in a computationally tractable manner. We study the Laplacian matrix (CENT L) and spherical wavelets (CENT W) as alternatives for the transformation in the compression constraint. In addition to the two prior constraints on the sources, we control the discrepancy between the modeled and measured data by restricting the power of residual error below a specified value. The results show that both CENT L and CENT W are capable of producing robust spatially regular source estimates with high computational efficiency. For simulated sources of focal, diffuse, or combined types, the CENT method shows better accuracy on estimating the source locations and spatial extents than the minimum ℓ 1-norm or minimum ℓ 2-norm constrained inverse solutions. Different transformations yield different benefits: By utilizing CENT with the Laplacian matrix it is possible to suppress physiologically atypical activations extending across two opposite banks of a deep sulcus. With the spherical wavelet transform CENT can improve the detection of two nearby yet not directly connected sources. As demonstrated by simulations, CENT is capable of reflecting the spatial extent for both focal and spatially extended current sources. The analysis of in …
Effects of drought stress on some agronomic and morphological traits of durum wheat (Triticum durum Desf.) landraces under greenhouse condition

Although, drought stress has been well documented as an effective parameter in decreasing crop production; developing and releasing new varieties which are adaptable to water deficit conditions can be a constructive program to overcome unsuitable environmental conditions. The present study was carried out to study the effect of drought stress under greenhouse conditions in Islamic Azad University of Ardabil Branch, Iran. The agronomic and morphological traits of 25 durum wheat ( Triticum durum Desf.) genotypes were investigated. The present study was done based on randomized complete block design with three replications in drought stress and normal irrigation conditions in a greenhouse. The analysis of variance has indicated that there are significant differences among the genotypes in all the traits, which indicate that there are great variations among genotypes in order to use in improvement plans. Analysis of variance shows that drought stress has a significant effect on all studied traits except harvest index. The comparison of means indicated that the genotypes; poldash, sari boghda and germi in normal condition and sari boghda, omrabi-5, langan, germi and germi under stress condition, are the superior groups. Grain yield has shown a positive and significant correlation with peduncle length, number of grains per spike, 1000 grain weight, biological yield and harvest index. Cluster analysis divides the genotypes into three groups in each condition. The best genotypes were included in a group which confirms the results of the compared means yield. Key words: Agronomic traits, durum wheat, genetic diversity, yield components.
Effects of Palm Bunch Ash and Mineral Fertilizer Application on Soil Chemical Properties and on the Growth, Yield and Nitrogen Fixation of Three Pigeon Pea Varieties In The Semi–Deciduous Forest Zone Of Ghana

ii DEDICATION . v ACKNOWLEDGEMENTS . vi TABLE OF CONTENTS . vii LIST OF TABLES . xiv ABBREVIATIONS . xvii CHAPTER ONE . 1 1.0 INTRODUCTION . 1 1.
Tabulation and analysis of questionnaire results of subjective evaluation of seal robot in seven countries

This paper describes research on a ldquomental commitment robotrdquo. These robots have a different target audience to industrial robots, one that is not so rigidly dependent on objective measures such as accuracy and speed. The main goal of this research is to explore a new area in robotics, with the emphasis on human-robot interaction. In previous research, we classified robots into four categories, which related to their appearance. We then introduced a robot cat and a robot seal, which we evaluated by interviewing a large group of people. The results showed that physical interaction improved their subjective evaluation of the robots. Moreover, a priori knowledge of a subject has a considerable influence on the subjective interpretation and evaluation of mental commitment robots. In this paper, we asked several groups of subjects to evaluate the seal robot known as dasiaParopsila by answering questionnaires that were given out in exhibitions that were held in seven different countries; Japan, U.K., Sweden, Italy, Korea, Brunei and U.S. This paper reports the results of statistical analysis of the evaluation data.
Seismic trace interpolation with approximate message passing

Approximate message passing (AMP) is a computationally effective algorithm for recovering high dimensional signals from a few compressed measurements. In this paper we use AMP to solve the seismic trace interpolation problem. We also show that we can exploit the fast AMP algorithm to improve the recovery results of seismic trace interpolation in curvelet domain, both in terms of convergence speed and recovery performance by using AMP in Fourier domain as a preprocessor for the `1 recovery in Curvelet domain.
A Study on Employees' Attitudes towards Transformational Leadership and Organizational Attachment

The aim of this research is to determined the employees' attitudes on the organizational commitment and transformational leadership behaviors. The study was conducted in the four and five stars hotels in Antalya, Aydin and Mugla. The multiple factor leadership scale (MLQ) and Allen and Meyer's organizational commitment was used in the study. It is found that employees have middle level attitudes against to the organizational commitment and transformational leadership according to results.
Soil moisture active and passive microwave products : intercomparison and evaluation over a Sahelian site

This paper presents a comparison and an evalu- ation of five soil moisture products based on satellite-based passive and active microwave measurements. Products are evaluated for 2005-2006 against ground measurements ob- tained from the soil moisture network deployed in Mali (Sa- hel) in the framework of the African Monsoon Multidisci- plinary Analysis project. It is shown that the accuracy of the soil moisture products is sensitive to the retrieval approach as well as to the sensor type (active or passive) and to the signal frequency (from 5.6 GHz to 18.8 GHz). The spatial patterns of surface soil moisture are compared between the different products at meso-scale (14.5 N - 17.5 N and 2 W - 1 W). A general good consistency between the different satellite soil moisture products is shown in terms of meso-scale spa- tial distribution, in particular after convective rainfall occur- rences. Comparison to ground measurement shows that al- though soil moisture products obtained from satellite gener- ally over-estimate soil moisture values during the dry sea- son, most of them capture soil moisture temporal variations in good agreement with ground station measurements.
Analysis of TCP Performance over Mobile Ad Hoc Networks -- Part I: Problem Discussion and Analysis of Results

Mobile ad hoc networks have gained a lot of attention lately as a means of providing continuous network connectivity to mobile computing devices regardless of physical location. Recently, a large amount of research has focused on the routing protocols needed in such an environment. In this two-part report, we investigate the effects that link breakage due to mobility has on TCP performance. Through simulation, we show that TCP throughput drops significantly when nodes move because of TCP''s inability to recognize the difference between link failure and congestion. We also analyze specific examples, such as a situation where throughput is zero for a particular connection. We introduce a new metric, "expected throughput", for the comparison of throughput in multi-hop networks, and then use this metric to show how the use of explicit link failure notification (ELFN) techniques can significantly improve TCP performance. In this paper (Part I of the report), we present the problem and an analysis of our simulation results. In Part II of this report, we present the simulation and results in detail.
Verification of WRF Simulation Capacity on PBL Characteristic and Analysis of Surface Meteorological Characteristic over Complex Terrain

Three planetary boundary layer(PBL) parameterizations(YSU,MYJ and ACM2) in WRF model are used to simulate surface temperature and wind in Lanzhou during 25~28 January 2005.Comparing with the simulations and the data from captive balloon sounding and Auto Weather Station,the results shows that:(1) Local MYJ scheme presents more reasonable diurnal changes of surface temperature than the other unlocal schemes(YSU and ACM2). (2) As to the simulation of potential temperature profiles,the results at the nighttime are better than that in the daytime.In the low-layer PBL,the potential temperature profiles from local and unlocal ACM2 schemes give better agreement with the observation;while in the upper PBL,local MYJ scheme is more suitable for the simulation of vertical profiles for potential temperature. (4) The spatial distributions of temperature over Lanzhou in winter from three PBL parameterization schems are similar,while the temperature at the nighttime from MYJ scheme is higher than that from YSU and ACM2 schemes,but opposite in the daytime.
C:N stoichiometry of the biological pump in the North Atlantic: Constraints from climatological data

Recently and independently published estimates of global net community production which were based on seasonal changes of either nutrients (NO3 and PO4 (Louanchi and Najjar, 2000)) and salinity normalized dissolved inorganic carbon (NCt (Lee, 2001)) in the surface ocean indicate that the stoichiometry of new production strongly differs from the well‐established remineralization ratios in the deep ocean (the Redfield ratio). This difference appears to be most pronounced in the North Atlantic Ocean. Data quality issues as well as methodological differences in the data analysis applied in the published studies, however, make this comparison of nutrient‐ and carbon‐based estimates ambiguous. Here I present an analysis based on a combination of historical data (World Ocean Atlas and Data 1998) and empirical approaches and provide a reassessment of the C:N elemental ratio of new (export) production in the North Atlantic. It is found that the estimate of winter nutrient fields is the most crucial step in estimating basin‐scale, time‐integrated C:N ratios of new production. An approach is developed which allows an estimate of winter nitrate and total CO2 concentrations which are consistent with estimates from an isopycnal outcrop analysis where these are available. Regional trends in the spring + summer integrated C:N ratio of new production suggest an increase from high latitudes toward the subtropics. The basin‐integrated C:N ratio of new production between 40°N and 65°N is 11.4 ± 1.4, far exceeding the Redfield ratio. The bulk Corg:Cinorg rain ratio estimated for the same region is 7.7. The fate of organic carbon produced in excess of the Redfield equivalent of nitrate uptake is discussed. It is suggested that a considerable fraction of excess carbon is remineralized above the depth of the winter mixed layer.