Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparison of Two Nonlinear Data Assimilation Methods

Advanced numerical data assimilation (DA) methods, such as the four-dimensional variational (4DVAR) method, are elaborate and computationally expensive. Simpler methods exist that take time-variability into account, providing the potential of accurate results with a reduced computational cost. Recently, two of these DA methods were proposed for a nonlinear ocean model. The first method is Diffusive Back and Forth Nudging (D-BFN) which has previously been implemented in several complex models, most specifically, an ocean model. The second is the Concave-Convex Nonlinearity (CCN) method provided 5 by Larios and Pei that has a straightforward implementation and promising results. D-BFN is less costly than a traditional variational DA system but it requires integrating the model forward and backward in time over a number of iterations, whereas CCN only requires integration of the forward model once. This paper will investigate if Larios and Pei’s CCN algorithm can provide competitive results with the already tested D-BFN within simple chaotic models. Results show that observation density and/or frequency, as well as the length of the assimilation window, significantly impact the results for CCN, whereas D-BFN 10 is fairly adaptive to sparser observations, predominately in time.
Image Restoration Using Various Methods and Performance Using Various Parameters

In this paper brief introduction of digital image processing is described. Mainly this paper is related to image restoration, different types of noises are introduced and different methods which are used to remove noise are described. Different parameters are also described to compare the results of different methods which are used. All the work is done on medical images. At the end of paper reference and conclusion is also described.
Computer Aided Geometric Design

In this paper, we develop a domain-decomposed subspace and multigrid solver to analyze the stress distribution for large-scale ﬁnite element meshes with millions of degrees of freedom. Through the domain decomposition technique, the shape editing directly updates the data structure of local ﬁnite element matrices. Doing so avoids the expensive factorization step in a direct solver and provides users with a progressive feedback of the stress distribution corresponding to the mesh operations: a fast preview is achieved through the subspace solver, and the multigrid solver reﬁnes the preview result if the user needs to examine the stress distribution carefully at certain design stages. Our system constructs the subspace for stress analysis using reduced constrained modes and builds a three-level multigrid solver through the algebraic multigrid method. We remove mid-edge nodes and lump unknowns with the Schur complement method. The updating and solving of the large global stiffness matrix are implemented in parallel after the domain decomposition. Experimental results show that our solver outperforms the parallel Intel MKL solver. Speedups of 50% – 100% can be achieved for large-scale meshes with reasonable pre-computation costs when setting the stopping criterion of the multigrid solver to be 1e − 3 relative error.
Effects of skin care ingredients on keratinocytes - Interplay between osmotic stress, cell viability, and gene expression towards increased understanding of keratinocyte differentiation

The epidermis is composed of multiple cell strata where viable keratinocytes, in the basal layer (stratum basale (SB)), go through a range of steps with the final stage of being dead corneocytes in the outer most layer (stratum corneum (SC)). The differentiation, which can be thought of as programmed cell death, include several key processes that are essential for an intact skin barrier. The route from SB to SC is accompanied by changes, such as osmotic pressure and pH, that are believed to trigger some of these processes. In this project, HaCaT cells were incubated with, commonly used, skin care substances (urea, glycerol, transcutol and salicylic acid) to assess their impact on cell viability, by MTT-assay, and gene expression, by qPCR. Further, the relationship between osmotic pressure, viability and gene expression was studied. The excipients showed a dose-dependent decrease of keratinocyte viability which also was explained by elevated osmotic pressure when concentration was increased. Exceptions were however observed for transcutol, which showed protective features against osmotic stress. Upregulation of the genes were mainly observed when cells were treated with high concentrations. Involucrin was affected by the substances to a greater extent when compared to other markers. The upregulation of involucrin was however seen to be driven by the osmotic pressure rather than biological effects of the molecules. The project conclude that the viability and gene expression of the keratinocytes are highly related to the osmotic pressure and probably influences the differentiation to a greater extent than the molecules themselves.
Genetic variability and heritability studies in brinjal ( Solanum melongena L.)

In the latest research, 24 diverse brinjal genotypes were thoroughly examined to evaluate their genetic diversity. The results highlighted a significant and remarkable amount of variation among the genotypes, evident in various crucial characteristics such as plant height, flowering time, fruit dimensions, average fruit weight, and fruit yield per plant. Interestingly, the phenotypic coefficient of variation (PCV) surpassed the equivalent genotypic coefficient of variation (GCV) for all traits, indicating a strong influence of environmental factors on these features. Among all attributes, the number of fruits per plant and per cluster exhibited the most substantial estimates of both phenotypic and genotypic variation. Additionally, key features like average fruit weight, fruit yield per plant, cluster size, fruit length
HARD: Hyperplane ARrangement Descent

The problem of clustering points on a union of subspaces finds numerous applications in machine learning and computer vision, and it has been extensively studied in the past two decades. When the subspaces are low-dimensional, the problem can be formulated as a convex sparse optimization problem, for which numerous accurate, efficient and robust methods exist. When the subspaces are of high relative dimension (e.g., hyperplanes), the problem is intrinsically non-convex, and existing methods either lack theory, are computationally costly, lack robustness to outliers, or learn hyperplanes one at a time. In this paper, we propose Hyperplane ARangentment Descent (HARD), a method that robustly learns all the hyperplanes simultaneously by solving a novel non-convex non-smooth ℓ 1 minimization problem. We provide geometric conditions under which the ground-truth hyperplane arrangement is a coordinate-wise minimizer of our objective. Furthermore, we devise efficient algorithms, and give conditions under which they converge to coordinate-wise minimizes. We provide empirical evidence that HARD surpasses state-of-the-art methods and further show an interesting experiment in clustering deep features on CIFAR-10.
Tower-based C-band radar measurements of an alpine snowpack

To better understand the interactions between C-band radar waves and snow, a tower-based experiment was set up in the Idaho Rocky Mountains for the period of 2021-2023. The experiment objective was to improve understanding of the sensitivity of Sentinel-1 C-band backscatter radar signals to snow. The data were collected in the time domain to measure the backscatter profile from the various snowpack and ground surface layers. The data show that scattering is present throughout the snow volume, although it is limited for low snow densities. Contrasting layer interfaces, ice features and metamorphic 5 snow can have considerable impact on the backscatter signal. During snow melt periods, wet snow absorbs the signal and the soil backscatter becomes negligible. A comparison of the vertically integrated tower radar data with Sentinel-1 data shows that both systems have a similar temporal behavior, and both feature an increase in backscatter during the dry snow period in 2021-2022, even during weeks of nearly constant snow depth, likely due to morphological changes in the snowpack. The results demonstrate that C-band radar is sensitive to the dominant seasonal patterns in snow accumulation, but that changes in 10 microstructure, stratigraphy, melt-freeze cycles, and snow wetness may complicate satellite-based snow depth retrievals.
Modelling the behaviour of U.S. Inventories: A Cointegration-Euler Approach

Cyclical contractions are often referred to as inventory cycles, in part because movements in inventories can amplify cyclical fluctuations in output. An unanticipated slowing in demand generally leads to an unintended buildup of inventories: only with a lag do firms adjust production and their actual holding of inventories relative to the desired level. A possible explanation for this accumulation is that the costs of adjusting inventory holdings outweigh the disequilibrium costs, i.e., the cost of temporarily deviating from the equilibrium level of inventories. In this paper, the relative importance of the disequilibrium costs to adjustment costs of inventories is evaluated. An estimate of the rate of inventory adjustment towards its long-run equilibrium level is provided in the United States by means of a linear-quadratic model with integrated processes. A limited-information approach allows the time-series properties of the data to be exploited and consistent estimates of the structural parameters of the Euler equation obtained. Evidence is provided that the actual level of U.S. inventories was generally above the target level during the past six recession periods and that inventories fell below their desired level following an economic downturn. Furthermore, the actual level of inventories appears to have been at desired levels between the 1960 and the 1969-70 recessions and since the last recession in 1990­1991--two periods of sustained economic growth. These findings support the view that inventory imbalances can amplify the business cycle. The empirical estimates also imply that adjustment costs are substantially more important than disequilibrium costs. The estimate of the speed of adjustment suggests that firms adjust their holdings of inventories slowly as it takes about a year for 95 per cent of the adjustment of the actual level to the target level to be completed.
Bank of Canada Banque du Canada Working Paper 2000-11 / Document de travail 2000-11 Identifying Policy-makers ’ Objectives : An Application to the Bank of Canada by

In this paper, we develop a new way to test hypotheses about policy-makers’ targets, and we implement that test for Canadian monetary policy. If, for example, the Bank of Canada is using interest rates to target an inflation rate of 2 per cent and there is an 8-quarter lag in the effect of the interest rate on inflation, then deviations of inflation from 2 per cent should be unforecastable and uncorrelated with any information in the Bank of Canada’s information set lagged by 8 quarters. This would imply that empirical causality tests of monetary policy on inflation could be very misleading. Our test indicates that there was indeed a major change in the Bank of Canada’s objectives about the time when formal inflation targets were announced. JEL classification: E52, E61 Bank classification: Monetary policy Résumé Les auteurs proposent une nouvelle façon de tester les hypothèses formulées au sujet des cibles visées par les autorités monétaires et appliquent leur test au cas canadien. Si, par exemple, l’instrument d’intervention de la Banque du Canada est le taux d’intérêt, que celle-ci vise un taux d’inflation de 2 % et que le taux d’intérêt met huit trimestres à agir sur le taux d’inflation, les écarts de l’inflation observée par rapport à la cible devraient être imprévisibles et ne pas être corrélés avec l’information, retardée de huit trimestres, à la disposition des autorités monétaires. Cette façon de procéder implique que l’on ne pourrait se fier aux tests empiriques servant à vérifier l’effet de causalité de la politique monétaire sur l’inflation. Selon les résultats du test effectué par les auteurs, un changement important serait en effet survenu dans les objectifs de la Banque du Canada à peu près au moment où cette dernière a annoncé l’établissement de cibles explicites en matière d’inflation. Classification JEL : E52, E61 Classification de la Banque : Politique monétaire
Record-breaking climate anomalies lead to severe drought and environmental disruption in western Patagonia in 2016

Traditionally a temperate and hyper-humid region, western Patagonia experienced its most severe drought during the summer and fall of 2016. Along with precipitation deficits larger than 50% there was a similar reduction in river discharge into coastal waters, a decline in vegetation productivity, excessive solar radiation at the surface, and frequent upwelling-favorable wind events offshore. The combination of these regional-scale anomalies seems to have set the stage for environmental disturbances that, although not new in western Patagonia, occurred with unprecedented magnitude, including severe urban air pollution episodes, large forest fires, and the worst ever recorded harmful algae bloom (HAB). The local climate anomalies were in turn related to the concomitant strong El Niño (through atmospheric teleconnections) and, to a lesser extent, anthropogenic climate change mediated by the positive polarity of the Southern Annular Mode (SAM) and internal variability, as both modes weakened the westerlies. Dryer than present conditions are consistently projected for northern Patagonia during the 21st century as a consequence of anthropogenic increases in radiative forcing; superposition of El Niño events in this altered climate may result in a higher frequency of extreme droughts and environmental disruptions like those observed in 2016.
Climbing up the hills: expansion of agriculture around the Ruma National Park, Kenya

ABSTRACT A major factor driving changes in land use and land cover (LULC) is the human population growth associated with an expanded agricultural production. In the Lambwe valley in Homabay County, Kenya, the most important reason for accelerated population growth in the last decades was the control of the tsetse fly, the biological vector of trypanosomiasis. The goal of our study is to quantify the changes of LULC in the Lambwe valley in the last 30 years, giving special attention to the Ruma National Park. We classified three Landsat images of the Lambwe valley from 1984, 2002, and 2014 by Random Forests. The Ruma National Park itself showed a diverse composition probably supported by frequent fires that lead to a short-term reduction of savanna. Nevertheless, the national park is well protected, and no profound changes could be observed. Outside the national park, agricultural area increased by about 12%, savanna and the dense forest, that used to grow at higher altitudes, decreased by about 8% and 6%, respectively. In particular, agriculture expands towards higher altitudes with steeper slopes thus leading to a larger risk of soil erosion.
MRI On The Fly: Accelerating MRI Imaging Using LDA Classi(cid:12)cation with LDB Feature Extraction (cid:3)

1 Acknowledgments I, Joy Ko, wish to acknowledge, with deep gratitude, my ever-growing family. Their support proved invaluable and their curiosity in the development and execution of this thesis sustained my own. I wish also to thank my partner, Michael Taylor, with whom it has been my privilege and pleasure to work. As partner, instructor, team-player, he has admirably demonstrated in all roles that patience, indeed, is key. I, Michael Taylor, would like to thank my mother, Mary-Lynne, who has supported me sellessly from the beginning of time. I am grateful to Rodney Page, my high school computer science instructor , for his amazing enthusiasm and encouragement. I thank Jee Swartz for helping to develop my abilities and for his excellent ability to atter. Scott Silver requires signiicant recognition because his advice and experience (both in and out of class) have been a much appreciated resource. Finally, I thank my partner, Joy Ko, who never ceases to impress me. Working and learning with her has been one of the great highlights of my Dartmouth experience. Additionally, we would like to thank Geoo Davis, Sumit Chawla and Doug Warner, who proved great resources in the development of our thesis. Finally, we would like to thank Dr. Dennis Healy, our thesis advisor. His perspective, guidance and experience were extremely valuable; his patience during our temper tantrums was admirable. This joint thesis is but one result of a ve term partnership that began in the summer of 1994. We have progressed from working within the connnes of assignments given in the classroom to the free and internally motivated area of research. By necessity, our topic is situated along the boundary of computer science and mathematics, a position that enabled each of us to lend unique (and often exclusive) expertise to the problems involved. This precarious position proved particularly valuable because it forced us out of our comfort zones into elds in which we had little experience. As a result, this thesis was a continuous learning experience. Such an arrangement required that we work eeectively and closely together. This was not always an easy task, but we think that this thesis is a good indication of our success.
Assessing the Importance of Content Versus Design for Successful Crowdfunding of Health Education Games: Online Survey Study.

Background Health education games make health-related tasks enjoyable and interactive, thereby encouraging user participation. Entrepreneurs and health educators can leverage online crowdfunding platforms, such as Kickstarter, to transform their innovative ideas into funded projects. Objective This research focuses on health education game initiatives on Kickstarter. Through an online user survey, it aims to understand user perceptions and evaluate the significance of 8 distinct components that may influence the success of such crowdfunding initiatives. Methods A total of 75 participants evaluated games using 8 dimensions: game rules, learning objectives, narrative, content organization, motivation, interactivity, skill building, and assessment and feedback. The survey data were analyzed using descriptive statistical analysis, exploratory factor analysis, the Wilcoxon-Mann-Whitney test, and multivariate analysis. Results Exploratory data analysis showed that, among the 8 dimensions, skill building, content organization, and interactivity were the top-ranking dimensions most closely associated with crowdfunding health education game. The 8 dimensions can be grouped into 3 categories from the exploratory factor analysis: game content-, instruction-, and game design-related components. Further statistical analysis confirmed the correlation between these dimensions with the successful crowdfunding of health education games. Conclusions This empirical analysis identified critical factors for game proposal design that can increase the likelihood of securing crowdfunding support.
Ancient and historical DNA in conservation policy

Although since the rst Biological (CBD) in 1993, it has rarely been included in conservation policies and regulations. Even less appreciated is the role that ancient and historical DNA (aDNA and hDNA, respectively) could play in unlocking the temporal dimension of genetic diversity, allowing key conservation issues to be resolved, including setting baselines for intraspecies genetic diversity, estimating changes in effective population size ( N e) and identifying the genealogi-cal continuity of populations. Here, we discuss how genetic information from ancient and historical specimens can play a central role in preserving biodiversity and highlight speci ﬁ c conservation policies that could incorporate such data to help countries meet their CBD obligations.
Smith ScholarWorks Smith ScholarWorks

An increasing body of research on critical consciousness explores how youth understand and react to inequality in their social contexts. The operationalization of critical consciousness remains inchoate, however. Developmental psychology traditionally conceptualizes critical consciousness as three components (critical reflection, political efficacy, and critical action), but how levels of these components combine for different youth or relate to outcomes remains unclear. This paper uses latent class analysis to examine how components of critical consciousness pattern together in a sample 448 of marginalized (racial/ethnic minority) youth, and relate to demographic characteristics, socioemotional outcomes, and academic well-being. We identify four classes of critical consciousness components differentiated by their level of critical reflection, beliefs about the fairness of the U.S., and external and internal political efficacy. Ethnicity was related to class membership, but gender and SES were not. Controlling for race/ethnicity, we find differences in cross-sectional measures of depression, academic engagement, academic competence, and grades of youth across these classes and identify socipolitical efficacy as a key predictor of positive youth development. Our findings provide theoretical clarity and practical insight into the complexity of critical consciousness and the combination of components that is most beneficial for positive youth development.
Quantum State Tomography A Comparison Between Linear Inversion, Maximum Likelihood Estimation and Bayesian Inference

Building a successful universal quantum computer will be a revolutionary break-through and have a significant impact on current challenges in the scientific community. There are many problems that need to be solved before this becomes a reality. One of these issues stems from the fact that quantum states collapse when measured, rendering the information limited. Quantum State Tomography aims to solve this problem, which can be implemented using different models. In this thesis three models, Linear Inversion, Maximum Likelihood Estimation and Bayesian Inference, have been numerically implemented in Python along with code to simulate quantum measurements. All 3 models show potential, but each have their advantages and disadvantages. One has to be careful due to the fact that Linear Inversion can return non physical states if the purity of the state is near unity and if the number of measurements are sufficiently low. With Maximum Likelihood Estimation one can risk that the resulting state has eigenvalues equal to zero, in the same parameter extrema as Linear Inversion. Bayesian Inference solves both these issues, but the computational time is significantly higher. All three models have shown their robustness on simulated data and are capable of running at least 4 qubit tomography. In addition, the tomographic models were implemented on superconducting qubits. All 3 Quantum State Tomography models performed well on the data, showing that control of the qubit was achieved. Which demonstrates their functionality on experimental data.
COLLEGIUM OF ECONOMIC ANALYSIS

This paper compares the aggregate and distributional eﬀects of three ﬁs-cal policy instruments: government expenditures, unemployment beneﬁts and transfers. To this end, the Diamond-Mortensen-Pissarides model of frictional labor market is embedded into an otherwise standard Heterogeneous Agent New Keynesian framework. The model calibrated to match the moments characterizing the US economy successfully replicates the empirical distributions of households across: disposable income, consumption expenditures and net worth. The solution method developed by Reiter (2009) is applied to quantify the aggregate and distributional responses to changes in the analyzed ﬁscal measures. Moreover, the stabilizing role of government expenditures, unemployment beneﬁts and transfers is assessed.