Miracle-dz/UniFAR-FTUs huggingface dataset:
The oceanography and marine ecology of Ningaloo, a World Heritage Area

The Ningaloo coast of north-western Australia (eastern Indian Ocean) hosts one of the world’s longest and most extensive fringing coral reef systems, along with globally significant abundances of large marine fauna such as whale sharks. These characteristics – which have contributed to its inscription on the World Heritage list – exist because of the unique climatic, geomorphologic and oceanographic conditions. The region is hot and arid, so runoff of water from land is low, facilitating clear water that allows corals to grow close to the shore. The polewardflowing Leeuwin Current is an important influence, bringing warm water and generally suppressing coastal upwelling. During the austral summer, strong southerly winds generate the equatorwardflowing Ningaloo Current on the inner shelf – this current facilitates sporadic upwelling events that enhance concentrations of nutrients, which in turn enhance pelagic primary productivity that supports the reef’s biota. The coast has experienced several marine heatwaves since 2011 that have caused mortality of corals and probably seagrass, albeit relatively less than elsewhere along the coast. Wind-generated surface waves break over the fringing reef crest, causing cooling currents that tend to dampen warming – although this mechanism seems not to have prevented some areas from experiencing damaging heat, and corals in places that do not receive the wave-generated currents have experienced substantial mortality. Herbivores, from fish to green turtles, are abundant, and in the lagoon, extensive stands of large brown algae provide an important habitat for newly recruited fish. There has been a decline in abundance of some fish. Predictions of future pressures include a weaker but more variable Leeuwin Current and increased human use. The ability of Ningaloo’s
Structure shape and stability of nanometric sized particles

Nanoparticles are a state of matter that has properties different from either molecules or bulk solids. In the present work, we review the shape and structure of nanometer-sized particles; several shapes are discussed, such as the octahedron and truncated octahedron, the icosahedron, the Marks decahedron, the truncated “star-like” decahedron, the rounded decahedron and the regular decahedron. Experimental high-resolution transmission electron microscopy (TEM) images of each type of particle are presented together with the Fast Fourier Transform and a model of the particle. We consider only gold particles grown by vapor deposition or by colloidal methods. High-resolution TEM images of the particles in different orientations are shown. We discuss two basic types of particles uncapped and capped. Data for other metals and semiconductors are reviewed. We have also performed very extensive simulations obtaining the total energy and pair correlation functions for each cluster under study. Furthermore, distributions of single atom energy for every cluster are displayed in order to reveal the effect of surface on the stability of different types and sizes of clusters. We discuss the structure of the particles from ∼1 to ∼100 nm. The mechanisms for stress release as the particles grow larger are reviewed and a mechanism is suggested. Finally, we discuss the parameters that define the shape of a nanoparticle and the possible implications in technological applications.Nanoparticles are a state of matter that has properties different from either molecules or bulk solids. In the present work, we review the shape and structure of nanometer-sized particles; several shapes are discussed, such as the octahedron and truncated octahedron, the icosahedron, the Marks decahedron, the truncated “star-like” decahedron, the rounded decahedron and the regular decahedron. Experimental high-resolution transmission electron microscopy (TEM) images of each type of particle are presented together with the Fast Fourier Transform and a model of the particle. We consider only gold particles grown by vapor deposition or by colloidal methods. High-resolution TEM images of the particles in different orientations are shown. We discuss two basic types of particles uncapped and capped. Data for other metals and semiconductors are reviewed. We have also performed very extensive simulations obtaining the total energy and pair correlation functions for each cluster under study. Furthermore, distribut.
Convolutional Neural Network-Aided Tree-Based Bit-Flipping Framework for Polar Decoder Using Imitation Learning

Known for their capacity-achieving abilities and low complexity for both encoding and decoding, polar codes have been selected as the control channel coding scheme for 5G communications. To satisfy the needs of high throughput and low latency, belief propagation (BP) is chosen as the decoding algorithm. However, it suffers from worse error performance than that of cyclic redundancy check (CRC)-aided successive cancellation list (CA-SCL). Recently, convolutional neural network-aided bit-flipping (CNN-BF) is applied to BP decoding, which can accurately identify the erroneous bits to achieve a better error rate and lower decoding latency than prior critical-set bit-flipping (CS-BF) mechanism. However, successive BF, having better error correction capability, has not been explored in CNN-BF since the more complicated flipping strategy is out of the scope of supervised learning. In this work, by using imitation learning, a convolutional neural network-aided tree-based multiple-bits BF (CNN-Tree-MBF) mechanism is proposed to explore the benefits of multiple-bits BF. With the CRC information as additional input data, the proposed CNN-BF model can further reduce 5 flipping attempts. Besides, a tree-based flipping strategy is proposed to avoid useless flipping attempts caused by wrongly flipped bits. From the simulation results, our approach can outperform CS-BF and reduce flipping attempts by 89% when code length is 64, code rate is 0.5 and SNR is 1 dB. It also achieves a comparable block error rate (BLER) as CA-SCL.
An empirical analysis of phrase-based and neural machine translation

Two popular types of machine translation (MT) are phrase-based and neural machine translation systems. Both of these types of systems are composed of multiple complex models or layers. Each of these models and layers learns different linguistic aspects of the source language. However, for some of these models and layers, it is not clear which linguistic phenomena are learned or how this information is learned. For phrase-based MT systems, it is often clear what information is learned by each model, and the question is rather how this information is learned, especially for its phrase reordering model. For neural machine translation systems, the situation is even more complex, since for many cases it is not exactly clear what information is learned and how it is learned. To shed light on what linguistic phenomena are captured by MT systems, we analyze the behavior of important models in both phrase-based and neural MT systems. We consider phrase reordering models from phrase-based MT systems to investigate which words from inside of a phrase have the biggest impact on defining the phrase reordering behavior. Additionally, to contribute to the interpretability of neural MT systems we study the behavior of the attention model, which is a key component in neural MT systems and the closest model in functionality to phrase reordering models in phrase-based systems. The attention model together with the encoder hidden state representations form the main components to encode source side linguistic information in neural MT. To this end, we also analyze the information captured in the encoder hidden state representations of a neural MT system. We investigate the extent to which syntactic and lexical-semantic information from the source side is captured by hidden state representations of different neural MT architectures.
Chromium Oxidation by Disinfectants and Oxidants Used in Drinking Water Treatment

ii PUBLIC ABSTRACT . iv ACKNOWLEDGMENTS . v LIST OF TABLES . ix LIST OF FIGURES . x INTRODUCTION . 1 LITERATURE REVIEW . 4 Chemistry & Speciation . 4 Prevalence of Chromium . 8 Prevalence of Oxidants . 10 Redox Equations . 11 Previous Chromium Oxidation Studies . 12 Dissolved Oxygen . 12 Chlorine . 13 Monochloramine . 15 Chlorine Dioxide . 15 Potassium Permanganate . 16 Ozone . 17 Experiment Durations . 17 OBJECTIVES . 19 vii MATERIALS & METHODS . 21 Bench Scale Experiment Plan . 21 Experiment Conditions . 22 pH Monitoring . 22 Temperature . 23 Water Quality . 24 Experiment Setup . 26 Materials to Prepare Oxidants & Analytical Methods . 31 Residual Monitoring . 35 Chromium Analysis . 37 TotCr Analysis . 37 Cr(VI) Analysis . 39 Quality Assurance & Quality Control . 44 Data Analysis and Statistics . 46 First Order Kinetics . 46 Statistical Analysis . 49 RESULTS & DISCUSSION . 50 Oxidation Results . 50 Chlorine . 50 Monochloramine . 70 Chlorine Dioxide . 73 Potassium Permanganate . 83 Ozone . 91 CONCLUSION . 93 Overall Summary of Oxidant Performance . 93 Objective 1: Effect of pH . 95 Objective 2: Effect of Temperature . 97 Objective 3: Effect of Oxidant Dose . 97 Objective 4: Effect of Water Quality . 98 Objective 5: Effect of Initial Cr(III) Concentration . 99 viii ENGINEERING SIGNIFICANCE . 101 REFERENCES . 103 APPENDICES . 106 APPENDIX A . 107 Analytical Issues Related to Permanganate . 107 APPENDIX B . 110 Rate Constant Determination . 110
SCRIPT: Self-Critic PreTraining of Transformers

We introduce Self-CRItic Pretraining Transformers (SCRIPT) for representation learning of text. The popular masked language modeling (MLM) pretraining methods like BERT replace some tokens with [MASK] and an encoder is trained to recover them, while ELECTRA trains a discriminator to detect replaced tokens proposed by a generator. In contrast, we train a language model as in MLM and further derive a discriminator or critic on top of the encoder without using any additional parameters. That is, the model itself is a critic. SCRIPT combines MLM training and discriminative training for learning rich representations and compute- and sample-efficiency. We demonstrate improved sample-efficiency in pretraining and enhanced representations evidenced by improved downstream task performance on GLUE and SQuAD over strong baselines. Also, the self-critic scores can be directly used as pseudo-log-likelihood for efficient scoring.
Graph Self Supervised Learning: the BT, the HSIC, and the VICReg

Self-supervised learning and pre-training strategies have developed over the last few years especially for Convolutional Neural Networks (CNNs). Recently application of such methods can also be noticed for Graph Neural Networks (GNNs). In this paper, we have used a graph based self-supervised learning strategy with different loss functions (Barlow Twins[? ], HSIC[? ], VICReg[? ]) which have shown promising results when applied with CNNs previously. We have also proposed a hybrid loss function combining the advantages of VICReg and HSIC and called it as VICRegHSIC. The performance of these aforementioned methods have been compared when applied to two different datasets namely MUTAG and PROTEINS. Moreover, the impact of different batch sizes, projector dimensions and data augmentation strategies have also been explored. The results are preliminary and we will be continuing to explore with other datasets.
The added value of satellite observations of methane forunderstanding the contemporary methane budget

Surface observations have recorded large and incompletely understood changes to atmospheric methane (CH4) this century. However, their ability to reveal the responsible surface sources and sinks is limited by their geographical distribution, which is biased towards the northern midlatitudes. Data from Earth-orbiting satellites designed specifically to measure atmospheric CH4 have been available since 2009 with the launch of the Japanese Greenhouse gases Observing SATellite (GOSAT). We assess the added value of GOSAT to data collected by the US National Oceanic and Atmospheric Administration (NOAA), which have been the lynchpin for knowledge about atmospheric CH4 since the 1980s. To achieve that we use the GEOS-Chem atmospheric chemistry transport model and an inverse method to infer a posteriori flux estimates from the NOAA and GOSAT data using common a priori emission inventories. We find the main benefit of GOSAT data is from its additional coverage over the tropics where we report large increases since the 2014/2016 El Niño, driven by biomass burning, biogenic emissions and energy production. We use data from the European TROPOspheric Monitoring Instrument to show how better spatial coverage and resolution measurements allow us to quantify previously unattainable diffuse sources of CH4, thereby opening up a new research frontier. This article is part of a discussion meeting issue ‘Rising methane: is warming feeding warming? (part 1)’.
Calculating the weather : meteorology in the 20th century

Introduction. Part I. Meteorology in 1900. An Empirical Tradition: Climatology. A Theoretical Tradition: Physics of the Atmosphere. A Practical Tradition: Weather Forecasting. Part II. Meteorology in the First Half ofthe 20th Century. Vilhelm Bjerkness Program to Unify Meteorology. Lewis Fry Richardson: The First Person to Compute the Weather. The Growth of Meteorology. Meteorological Calculation in the Interwar Period. The Effect of World War II on Meteorology. Part III. The Beginning of the Computer Era in Meteorology. John von Neumanns Meteorology Project. The Acceptance of Numerical Meteorology. The Unification of Meteorology. The Recognition of Limits to Weather Prediction. Endnotes. Notes on Sources. References. Index.
Scheduling of power system cells integrating stochastic power sources

Energy supply and climate change are nowadays two of the most outstanding problems which societies have to cope with under a context of increasing energy needs. Public awareness of these problems is driving political willingness to take actions for tackling them in a swift and efficient manner. Such actions mainly focus in increasing energy efficiency, in decreasing dependence on fossil fuels, and in reducing greenhouse gas emissions. In this context, power systems are undergoing important changes in the way they are planned and managed. On the one hand, vertically integrated structures are being replaced by market structures in which power systems are unbundled. On the other, power systems that once relied on large power generation facilities are witnessing the end of these facilities' life-cycle and, consequently, their decommissioning. The role of distributed energy resources such as wind and solar power generators is becoming increasingly important in this context. However, the large-scale integration of such type of generation presents many challenges due, for instance, to the uncertainty associated to the variability of their production. Nevertheless, advanced forecasting tools may be combined with more controllable elements such as energy storage devices, gas turbines, and controllable loads to form systems that aim to reduce the impacts that may be caused by these uncertainties. This thesis addresses the management under market conditions of these types of systems that act like independent societies and which are herewith named power system cells. From the available literature, a unified view of power system scheduling problems is also proposed as a first step for managing sets of power system cells in a multi-cell management framework. Then, methodologies for performing the optimal day-ahead scheduling of single power system cells are proposed, discussed and evaluated under both a deterministic and a stochastic framework that directly integrates the uncertainty information into the scheduling process. Results show that the utilization of the proposed approaches may lead to important advantages for operators managing these types of power system cells.
Property Tax Base Erosion: A South Carolina Study

ii DEDICATION . iii ACKNOWLEDGEMENTS . iv LIST OF TABLES . ix CHAPTER ONE: INTRODUCTION . 1 Property tax reform . 4 Property tax as a revenue source . 5 Salient features of the property tax . 6 Tax revenue system evaluation criteria . 7 Efficiency . 8 Equity . 9 Revenue adequacy . 11 Property tax base erosion in South Carolina . 12 Business location incentives . 13 Exempt property for nonprofit organizations . 15 Research importance . 16 CHAPTER TWO: HISTORICAL AND INSTITUTIONAL CONTEXT . 17 Institutional efficiency and Pareto improvements . 18 Institutional change . 20 South Carolina political institutions . 20 The revenue system in South Carolina . 21 Revenue system issues in South Carolina . 22 How the property tax works in South Carolina . 24 From valuation to revenue . 31 The property tax in public revenue . 37 Methods of comparing taxes. 39 Comparing taxes: South Carolina, the Southeast and the Nation . 41
Distributed Differential Privacy in Multi-Armed Bandits

We consider the standard $K$-armed bandit problem under a distributed trust model of differential privacy (DP), which enables to guarantee privacy without a trustworthy server. Under this trust model, previous work largely focus on achieving privacy using a shuffle protocol, where a batch of users data are randomly permuted before sending to a central server. This protocol achieves ($\epsilon,\delta$) or approximate-DP guarantee by sacrificing an additional additive $O\! \left(\! \frac{K\log T\sqrt{\log(1/\delta)}}{\epsilon}\! \right)\! $ cost in $T$-step cumulative regret. In contrast, the optimal privacy cost for achieving a stronger ($\epsilon,0$) or pure-DP guarantee under the widely used central trust model is only $\Theta\! \left(\! \frac{K\log T}{\epsilon}\! \right)\! $, where, however, a trusted server is required. In this work, we aim to obtain a pure-DP guarantee under distributed trust model while sacrificing no more regret than that under central trust model. We achieve this by designing a generic bandit algorithm based on successive arm elimination, where privacy is guaranteed by corrupting rewards with an equivalent discrete Laplace noise ensured by a secure computation protocol. We also show that our algorithm, when instantiated with Skellam noise and the secure protocol, ensures \emph{R\'{e}nyi differential privacy} -- a stronger notion than approximate DP -- under distributed trust model with a privacy cost of $O\! \left(\! \frac{K\sqrt{\log T}}{\epsilon}\! \right)\! $.
Optimized Signal Peptide for Secretory Expression of Human Recombinant Somatropin in E. coli

Purpose: The human somatropin is a single-chain polypeptide with a pivotal role in various biological processes. Although Escherichia coli is considered as a preferred host for the production of human somatropin, the high expression of this protein in E. coli results in the accumulation of protein as inclusion bodies. Periplasmic expression using signal peptides could be used to overcome the formation of inclusion bodies; still, the efficiency of each of the signal peptides in periplasmic transportation is varied and often is protein specific. The present study aimed to use in silico analysis to identify an appropriate signal peptide for the periplasmic expression of human somatropin in E. coli. Methods: A library containing 90 prokaryotic and eukaryotic signal peptides were collected from the signal peptide database, and each signal’s characteristics and efficiency in connection with the target protein were analyzed by different software. The prediction of the secretory pathway and the cleavage position was determined by the signalP5 server. Physicochemical properties, including molecular weight, instability index, gravity, and aliphatic index, were investigated by ProtParam software. Results: The results of the present study showed that among all the signal peptides studied, five signal peptides ynfB, sfaS, lolA, glnH, and malE displayed high scores for periplasmic expression of human somatropin in E. coli, respectively. Conclusion: In conclusion, the results indicated that in-silico analysis could be used for the identification of suitable signal peptides for the periplasmic expression of proteins. Further laboratory studies can evaluate the accuracy of the results of in silico analysis.
Understanding quantum physics : a user's manual

(NOTE: All chapters conclude with Final Thoughts, and Exercises and Problems most also include Annotated Selected Readings.) I. WHAT'S IT ALL ABOUT? : A QUALITATIVE INTRODUCTION. 1. Introductory: Why Quantum Physics? 2. Into the Microworld: Duality and the Double Slit. II. STARTING FROM SCRATCH. 3. First Postulates: The State Function and Its Interpretation. 4. An Illustrative Interlude: Wave Packets in One Dimension. 5. Observables in Quantum Physics: A Pragmatist's Approach. 6. A Quantum Equation of Motion: The Schrodinger Equation At Last. 7. Simplifying Matters: The Time-Independent Schrodinger Equation. III. EXAMPLES, EXAMPLES, EXAMPLES. 8. States of a Particle in One Dimension I: Mainly Piecewise-Constant Potentials. 9. States of a Particle in One Dimension II: Mainly Continuous Potentials. IV. TOOLS OF THE TRADE MORE FORMALISM. 10. Operators in Quantum Mechanics I: The Importance of Being Hermitian. 11. Operators in Quantum Mechanics II: To Commute or Not to Commute. 12. Eigenfunction Expansions: How to Solve Any Problem in Quantum Mechanics. 13. Altered States: The Great Measurement Mystery. Appendixes. A. SI Units (The International System of Units. B. Fundamental Constants in SI (and CGS) Units. C. Order-of-Magnitude Estimates. D. Conversion Tables. E. Prefix Dictionary. F. A User's Guide to Atomic Units. G. The Greek Alphabet. H. Handy Trigonometric identities. I. Integrals You Should Know. J. Integrals Involving the Gaussian Function. K. Review of Complex Numbers. L. The Dirac Delta Function. Bibliography. Index.
Automorphism Groups of Trees: Generalities and Prescribed Local Actions

This article is an expanded version of the talks given by the authors at the Arbeitsgemeinschaft "Totally Disconnected Groups", held at Oberwolfach in October 2014. We recall the basic theory of automorphisms of trees and Tits' simplicity theorem, and present two constructions of tree groups via local actions with their basic properties: the universal group associated to a finite permutation group by M. Burger and S. Mozes, and the $k$-closures of a given group by C. Banks, M. Elder and G. Willis.