Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian inference in plant growth models for prediction and uncertainty assessment

Plant growth models aim to describe plant development and functional processes in interaction with the environment. They offer promising perspectives for many applications, such as yield prediction for decision support or virtual experimentation inthe context of breeding. This PhD focuses on the solutions to enhance plant growth model predictive capacity with an emphasis on advanced statistical methods. Our contributions can be summarized in four parts. Firstly, from a model design perspective, the Log-Normal Allocation and Senescence (LNAS) crop model is proposed. It describes only the essential ecophysiological processes for biomass budget in a probabilistic framework, so as to avoid identification problems and to accentuate uncertainty assessment in model prediction. Secondly, a thorough research is conducted regarding model parameterization. In a Bayesian framework, both Sequential Monte Carlo (SMC) methods and Markov chain Monte Carlo (MCMC) based methods are investigated to address the parameterization issues in the context of plant growth models, which are frequently characterized by nonlinear dynamics, scarce data and a large number of parameters. Particularly, whenthe prior distribution is non-informative, with the objective to put more emphasis on the observation data while preserving the robustness of Bayesian methods, an iterative version of the SMC and MCMC methods is introduced. It can be regarded as a stochastic variant of an EM type algorithm. Thirdly, a three-step data assimilation approach is proposed to address model prediction issues. The most influential parameters are first identified by global sensitivity analysis and chosen by model selection. Subsequently, the model calibration is performed with special attention paid to the uncertainty assessment. The posterior distribution obtained from this estimation step is consequently considered as prior information for the prediction step, in which a SMC-based on-line estimation method such as Convolution Particle Filtering (CPF) is employed to perform data assimilation. Both state and parameter estimates are updated with the purpose of improving theprediction accuracy and reducing the associated uncertainty. Finally, from an application point of view, the proposed methodology is implemented and evaluated with two crop models, the LNAS model for sugar beet and the STICS model for winter wheat. Some indications are also given on the experimental design to optimize the quality of predictions. The applications to real case scenarios show encouraging predictive performances and open the way to potential tools for yield prediction in agriculture.
Dynamic Ambient Occlusion and Indirect Lighting

14.1 Surface Elements In this chapter we describe a new technique for computing diffuse light transfer and show how it can be used to compute global illumination for animated scenes. Our technique is efficient enough when implemented on a fast GPU to calculate ambient occlusion and indirect lighting data on the fly for each rendered frame. It does not have the limitations of precomputed radiance transfer (PRT) or precomputed ambient occlusion techniques, which are limited to rigid objects that do not move relative to one another (Sloan 2002). Figure 14-1 illustrates how ambient occlusion and indirect lighting enhance environment lighting.
Interactions Between Herbicide Application and Timing of Nitrogen Fertilization in Maize Hybrids

Maize hybrids have different levels of tolerance to the herbicide nicosulfuron, depending on the dose, the environment, the phenological stage of the plant and the timing of nitrogen fertilization, and phytotoxic effects can occur without proper management. There is also limited information on the selectivity of current genetically modified hybrids for other recommended herbicides, such as tembotrione. Thus, the objective of this study was to evaluate the effects of herbicides (tembotrione and nicosulfuron) and the timing of nitrogen fertilization on the yield of maize hybrids. The experimental design was a randomized block design, in a 4 × 2 factorial arrangement, with 4 replicates. The treatments consisted of four treatments [weeding; nicosulfuron + atrazine (20 and 32 + 1250 g ha-1 ai) and tembotrione + atrazine (75.6 + 1250 g ha-1 ai)] and two nitrogen fertilization times (0 and 7 days after application). Maize hybrids P30F53 Leptra, DKB 230PRO3 and KWS 9004PRO2 were assessed in two growing seasons (1st and 2nd harvest) during the 2016/2017 growing season. The percentages of weed control; phytotoxicity at 7, 14 and 21 days after application (DAA); plant height; number of rows per ear; and yield at harvest were evaluated. All herbicides were more effective in controlling weeds at the 1st harvest because of favourable climatic conditions. Nitrogen fertilization can be carried out on the same day as the application of the herbicides nicosulfuron and tembotrione with no reduction in yield for the hybrids P30F53 Leptra, DKB 230PRO3 and KWS 9004PRO2.
16. COMPUTER SOFTWARE IN STATISTICS EDUCATION: STUDENT VIEWS ON THE IMPACT OF A COMPUTER PACKAGE ON AFFECTION AND COGNITION

The Data Analysis subdepartment of the department of Psychology and Educational Sciences is conducting several studies focus on the use of computers in statistics learning. One project investigates the computer as a learning environment for statistics. In an experimental setting, three different learning conditions are studied: computer-based independent learning, pen-and-paper-based independent learning, and lecture-based learning. The results of this research were presented at ICOTS IV Marrakech (Schuyten, Dekeyser, & Goeminne, 1994). A second project focuses on student characteristics; that is, individual differences in dealing with verbal explanations, graphical displays, and formula. Their impact on the learning of statistics is investigated. In this study, the computer is used not only as a research tool to register the activities of the students in logfiles, but also as a didactic tool to explore the possibilities of computer-based materials for differentiation and individualization. Some findings were presented at ISI in Beijing in August 1995 (Schuyten, Goeminne, & Dekeyser, 1995). A third project, discussed here, focuses on the added value of standard scientific computer packages. The added value of these packages to the traditional course (consisting of lectures and pen-and-paper exercises) is discussed. Students' views on the impact of the computer package on affection and cognition are collected with a structured questionnaire.
Intra-individual variability of sleep and nocturnal cardiac autonomic activity in elite female soccer players during an international tournament

Purpose This study provides insights into the individual sleep patterns and nocturnal cardiac autonomic activity responses of elite female soccer players during an international tournament. Materials and methods Twenty elite female soccer players (aged 25.2±3.1 years) wore wrist actigraph units and heart rate (HR) monitors during night-sleep throughout 9 consecutive days (6 day-time training sessions [DT], 2 day-time matches [DM], and 1 evening-time match [EM]) of an international tournament. Training and match loads were monitored using the session-rating of perceived exertion (s-RPE) and wearable 18-Hz GPS (total distance covered [TD], training and match exposure time, and high-speed running [HSR]) to characterize training and match loads. Results Individually, s-RPE, TD, exposure time, and HSR during training sessions ranged from 20 to 680 arbitrary units (AU), 892 to 5176 m, 20 to 76 min, and 80 to 1140 m, respectively. During matches, s-RPE, TD, exposure time, and HSR ranged from 149 to 876 AU, 2236 to 11210 m, 20 to 98 min, and 629 to 3213 m, respectively. Individually, players slept less than recommended (<7 hours) on several days of the tournament, especially after EM (n=8; TST ranging between 6:00-6:54 h). Total sleep time coefficient of variation (CV) ranged between 3.1 and 18.7%. However, all players presented good sleep quality (i.e., sleep efficiency ≥75%; individual range between: 75-98%) on each day of the tournament. Most of the players presented small fluctuations in nocturnal cardiac autonomic activity (individual nocturnal heart rate variability [HRV] ranged from 3.91-5.37 ms and HRV CV ranged from 2.8-9.0%), while two players presented higher HRV CV (11.5 and 11.7%; respectively). Conclusion Overall, elite female soccer players seemed to be highly resilient to training and match schedules and loads during a 9 day international tournament.
Spontaneous Twin Pregnancies Versus Twin Pregnancies Conceived with Assisted Reproductive Technologies

OBJECTIVE: To ev aluate the differences between spontaneous and assisted reproductiv e technology (ART) conceived twin pregnancies in respects of gestational and neonatal outcomes. STUDY DESIGN: The comparison was made between 52 twin pregnancies conceived by ART and 80 spontaneous twins, deliv ered between y ears 2002 and 2004. Statistical analysis was perf ormed by the SPSS program, v ersion 11.5. RESULTS: Rates of nulliparity, preterm labor, incidence of caesarean section, hospitalization time and neonatal mortality were signif icantly higher in the ART group. ART itself was not a risk f actor for specif ic pregnancy complications such as pregnancy-induced hy pertension, gestational diabetes mellitus and premature rupture of membranes. Gestational age at deliv ery, the birth weights of both the first and second twins were comparable between the groups. CONCLUSION: ART conceiv ed twin pregnancies pose the neonate to higher risks of complication related to morbidity and mortality than spontaneous twin pregnancies. Maternal morbidity rate was equal in both groups.
Geographic variation in the intensity of warming and phenological mismatch between Arctic shorebirds and invertebrates

Responses to climate change can vary across functional groups and trophic levels, leading to a temporal decoupling of trophic interactions or “phenological mismatches. ” Despite a growing number of single-species studies that identified phenological mismatches as a nearly universal consequence of climate change, we have a limited understanding of the spatial variation in the intensity of this phenomenon and what influences this variation. In this study, we tested for geographic patterns in phenological mismatches between six species of shorebirds and their invertebrate prey at 10 sites spread across ~13° latitude and ~84° longitude in the Arctic over three years. At each site, we quantified the phenological mismatch between shorebirds and their invertebrate prey at (1) an individual-nest level, as the difference in days between the seasonal peak in food and the peak demand by chicks, and (2) a population level, as the overlapped area under fitted curves for total daily biomass of invertebrates and dates of the peak demand by chicks. We tested whether the intensity of past climatic change observed at each site corresponded with the extent of phenological mismatch and used structural equation modeling to test for causal relationships among (1) environmental factors, including geographic location and current climatic conditions, (2) the timing of invertebrate emergence and the breeding phenology of Manuscript received 4 May 2018; revised 5 May 2019; accepted 17 May 2019. Corresponding Editor: Viviana Ruiz-Gutierrez. 15 Present address: Department of Behavioural Ecology and Evolutionary Genetics, Max Planck Institute for Ornithology, Seewiesen, 82319 Germany 16 Present address: Upper Midwest Environmental Sciences Center, U.S. Geological Survey, La Crosse, Wisconsin 54603 USA. 17 Present address: Pacifica Ecological Services, Anchorage, Alaska 99516 USA. 18 Present address: Hakalau Forest National Wildlife Refuge, Hilo, Hawaii 96720 USA. 19 Present address: Department of Multidisciplinary Studies Bilingual Biology Program, Glendon College, York University, Toronto, Ontario M4N 3M6 Canada. 20 Present address: National Park Service, Alaska Regional Office, Anchorage, Alaska 99507 USA. 21 Present address: Anchorage Fish and Wildlife Conservation Office, U.S. Fish and Wildlife Service, Anchorage, Alaska 99507 USA. 22 Present address: Department of Biological Sciences, University of South Carolina, Columbia, South Carolina 29208 USA. 23 Present address: Department of Terrestrial Ecology, Norwegian Institute for Nature Research, 7485 Trondheim, Norway. 24 E-mail: eunbi.kwon@gmail.com Article e01383; page 1 Ecological Monographs, 0(0), 2019, e01383 © 2019 by the Ecological Society of America
A kinetic, biomechanical model of the foot and ankle

A four-segment kinetic model of the foot and ankle was developed for use with existing kinematic motion analysis equipment. That system is capable of describing the kinematic behavior of the foot and ankle during stance and swing phases of gait. Preliminary results indicate that the enhanced kinetic model is suitable for further implementation. Sagittal plane data is compared to published data from other whole body motion analysis studies. <<ETX>>
GENETICS OF LEAF RUST RESISTANCE IN ELEVEN CROSSES DERIVED FROM TWO LOW RESISTANT AND EIGHT HIGH RUST SEVERITY EGYPTIAN WHEAT CULTIVARS AT SEEDLING AND ADULT PLANT STAGES

Leaf rust caused by the biotrophic fungus Puccinia triticina, is one of the most important diseases of worldwide countries and Egypt. The use of resistance genes is of a great interest in numerous breeding programs. Our objectives were to determine the number of resistance gene pairs to wheat leaf rust present in eleven crosses derived from two low rust severity wheat cultivars i.e. Gemmeiza 9 and Sakha 94 with six and five high rust severity wheat cultivars, respectively, at both seedling in greenhouse and at adult plant stages under field conditions. The obtained results showed a high effective response against artificial and natural infection of wheat leaf rust at adult plant than these recorded at seedling stage. The study of combination between traditional wheat cultivars of Egyptian origin showing durable resistance proved to have a great value since they can provide new sources of resistance to such a disease.
EARS (Easy Approach to Requirements Syntax)

The development of complex systems frequently involves extensive work to elicit, document and review stakeholder requirements. Stakeholder requirements are usually written in unconstrained natural language, which is inherently imprecise. During system development, problems in stakeholder requirements inevitably propagate to lower levels. This creates unnecessary volatility and risk, which impact programme schedule and cost. Some experts advocate the use of other notations to increase precision and minimise problems such as ambiguity. However, use of non-textual notations requires translation of the source requirements, which can introduce further errors. There is also a training overhead associated with the introduction of new notations. A small set of structural rules was developed to address eight common requirement problems including ambiguity, complexity and vagueness. The ruleset allows all natural language requirements to be expressed in one of five simple templates. The ruleset was applied whilst extracting aero engine control system requirements from an airworthiness regulation document. The results of this case study show qualitative and quantitative improvements compared with a conventional textual requirements specification.
Personality traits and investor sentiment

Purpose This paper examines the relation between the Big Five model of personality traits and behavioral biases (overconfidence, disposition effect, anchoring, representativeness, metal accounting, emotional bias and herding) of Indian individual investors when making investment decisions. Design/methodology/approach The authors use a structured questionnaire to obtain responses from 515 stock investors in India between August 2016 and January 2017. Based on components identified through factor analysis, the authors use structural equation modeling to examine the effect of specific personality traits. Findings The findings indicate a significant association between the traits of neuroticism, extroversion and conscientiousness as well as behavioral biases of individual investors. Openness has a significant relation with only mental accounting and the agreeableness trait has no relation with the behavioral biases examined. Research limitations/implications The findings imply that understanding investor personality differences and investment psychology can help financial advisors and wealth managers modify products and services to better suit client needs. Originality/value To the best of the authors’ knowledge, no previous study has examined the impact of the Big Five model of personality traits on various behavioral biases among Indian investors.
Social Network Analysis of Researchers' Communication and Collaborative Networks Using Self-reported Data

vi CHAPTER 1: INTRODUCTION 1 1.1. Statement of the Research Problem 1 1.2. Proposed Solution 7 1.3. Statement of Research Objectives 10 CHAPTER 2: AN EVALUATION OF COLLABORATIVE RESEARCH IN A COLLEGE OF ENGINEERING: A SOCIAL NETWORK APPROACH 15 2.
Architectures and design techniques for real-time image-processing IC's

A set of eight chips that perform real-time image-processing tasks was designed and fabricated with a 4-/spl mu/m NMOS technology. The chips include a 3/spl times/3 linear convolver, a 3/spl times/3 sorting filter, a 7/spl times/7 logical convolver, a contour tracer, a feature extractor, a lookup-table ROM, and two postprocessors for the linear convolver. All chips were designed with architectures that are dedicated to the particular image-processing task to be performed. The image-processing circuits operate on 10-MHz video data (512/spl times/512-pixel images). The design time for the chips was kept to 1.5 man-years by reusing hardware and using (and developing) appropriate CAD tools, ROM generators and a data-path generator were developed to reduce the circuit design time. An image recognition system was built with these custom chips that can recognize two-dimensional objects that are characterized by their closed outer contours. The complete system is controlled by a Sun workstation and operates at rates up to 15 frames/s. The recognition system achieved a 98% recognition rate for eight objects over a wide range of orientation and size variations and a 100% recognition rate without size variations.
Tools for Automatic Audio Indexing

Current web search engines generally do not enable searches into audio files. Informative metadata would allow searches into audio files, but producing such metadata is a tedious manual task. Tools for automatic production of metadata are therefore needed. This project investigates methods for audio segmentation and speech recognition, which can be used for this metadata extraction. Classification models for classifying speech and music are investigated. A feature set consisting of zero-crossing rate, short time energy, spectrum flux, and mel frequency cepstral coefficients is integrated over a 1 second window to yield a 60-dimensional feature vector. A number of classifiers are compared including artificial neural networks and a linear discriminant. The results obtained using the linear discriminant are comparable with the performance of more complex classifiers. The dimensionality of the feature vectors is decreased from 60 to 14 features using a selection scheme based on the linear discriminant. The resulting model using 14 features with the linear discriminant yields a test misclassification of 2.2%. A speaker change detection algorithm based on a vector quantization distortion (VQD) measure is proposed. The algorithm works in two steps. The first step finds potential change-points and the second step compensates for the false alarms produced by the first step. The VQD metric is compared with two other frequently used metrics: Kullback Leibler divergence (KL2) and Divergence Shape Distance (DSD) and found to yield better results. An overall F-measure of 85.4% is found. The false alarm compensation shows a relative improvement in precision of 59.7% with a relative loss of 7.2% in recall in the found change-points. The choice of parameters based on one data set generalize well to other independent data sets. The open source speech recognition system SPHINX-4 is used to produce transcripts of the speech segments. The system shows an overall word accuracy of \verb+~+ 75%.
A Formally Verified Algorithm for Interactive Consistency Under a Hybrid Fault Model

P. Thambidurai and Y. -K. Park (1988) have proposed an algorithm for interactive consistency that retains resilience to the arbitrary (or Byzantine) fault mode, while tolerating more faults of simpler kinds than standard Byzantine-resilient algorithms. Unfortunately, and despite a published proof of correctness, their algorithm is flawed. The authors detected this while undertaking a formal verification of the algorithm. They present a corrected algorithm that has been subjected to mechanically checked formal verification. Because informal proofs seem unreliable in this domain, and the consequences of failure could be catastrophic, the authors believe formal verification should become standard for algorithms intended for safety-critical applications.
Rule-Based Forecasting Vs. Damped-Trend Exponential Smoothing

This paper evaluates the ex ante performance of rule-based time series forecasting systems proposed in earlier research. The author shows that comparable performance can be obtained with a simpler alternative, a damped-trend version of exponential smoothing fitted to minimize the Mean-Absolute-Deviation MAD criterion. The results suggest that the performance of rule-based systems would be improved through this alternative and that time series forecasters should consider MAD fits in model development.
On the application of ultra-fast fMRI and high resolution multiband fMRI at high static field strengths

An ultrafast functional magnetic resonance imaging (fMRI) technique, called generalized inverse imaging (GIN), is proposed, which combines inverse imaging with a phase constraint leading to a less underdetermined reconstruction and physiological noise correction. A single 3D echo planar imaging (EPI) prescan is sufficient to obtain the necessary coil sensitivity information and reference images that are used to reconstruct standard images, so that standard analysis methods are applicable. A moving dots stimulus paradigm was chosen to assess the performance of GIN. We find that the spatial localization of activation for GIN is comparable to an EPI protocol and that maximum z-scores increase significantly. The high temporal resolution of GIN (50 ms) and the acquisition of the phase information enable unaliased sampling and regression of physiological signals. Using the phase time courses obtained from the 32 channels of the receiver coils as nuisance regressors in a general linear model results in significant improvement of the functional activation, rendering the acquisition of external physiological signals unnecessary. The proposed physiological noise correction can in principle be used for other fMRI protocols, such as simultaneous multislice acquisitions, which acquire the phase information sufficiently fast and sample physiological signals unaliased. Generalized INverse Imaging (GIN) 37
Fault immunization technique for artificial neural networks

By injecting some chemical substances to a cell, it is able to enhance the ability of the cell to fight against the intruder. This immunization concept in biological cells has been applied to enhance the fault tolerance capability in a perceptron-like neuron. In this paper, we consider only the case where each neuron separates its input vectors into two classes. We mathematically model the cell immunization in terms of weight vector relocation and propose a polynomial time weight relocating algorithm. This algorithm can be generalized to the case where each neuron separating the input vectors into more than two classes.