Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating the effects of China's pollution controls on inter-annual trends and uncertainties of atmospheric mercury emissions

Abstract. China's anthropogenic emissions of atmospheric mercury (Hg) are effectively constrained by national air pollution control and energy efficiency policies. In this study, improved methods, based on available data from domestic field measurements, are developed to quantify the benefits of Hg abatement by various emission control measures. Those measures include increased use of (1) flue gas desulfurization (FGD) and selective catalyst reduction (SCR) systems in power generation; (2) precalciner kilns with fabric filters (FF) in cement production; (3) mechanized coking ovens with electrostatic precipitators (ESP) in iron and steel production; and (4) advanced production technologies in nonferrous metal smelting. Investigation reveals declining trends in emission factors for each of these sources, which together drive a much slower growth of total Hg emissions than the growth of China's energy consumption and economy, from 679 metric tons (t) in 2005 to 750 t in 2012. In particular, estimated emissions from the above-mentioned four source types declined 3% from 2005 to 2012, which can be attributed to expanded deployment of technologies with higher energy efficiencies and air pollutant removal rates. Emissions from other anthropogenic sources are estimated to increase by 22% during the period. The species shares of total Hg emissions have been stable in recent years, with mass fractions of around 55, 39, and 6% for gaseous elemental Hg (Hg0), reactive gaseous mercury (Hg2+), and particle-bound mercury (Hgp), respectively. The higher estimate of total Hg emissions than previous inventories is supported by limited simulation of atmospheric chemistry and transport. With improved implementation of emission controls and energy saving, a 23% reduction in annual Hg emissions from 2012 to 2030, to below 600 t, is expected at the most. While growth in Hg emissions has been gradually constrained, uncertainties quantified by Monte Carlo simulation for recent years have increased, particularly for the power sector and particular industrial sources. The uncertainty (expressed as 95% confidence intervals) of Hg emissions from coal-fired power plants, for example, increased from −48–+73% in 2005 to −50–+89% in 2012. This is attributed mainly to increased penetration of advanced manufacturing and pollutant control technologies; the unclear operational status and relatively small sample sizes of field measurements of those processes have resulted in lower but highly varied emission factors. To reduce uncertainty and further confirm the benefits of pollution control and energy polices, therefore, systematic investigation of specific Hg pollution sources is recommended. The variability of temporal trends and spatial distributions of Hg emissions needs to be better tracked during the ongoing dramatic changes in China's economy, energy use, and air pollution status.
Metabolic Maturation of Auditory Neurones in the Superior Olivary Complex

Neuronal activity is energetically costly, but despite its importance, energy production and consumption have been studied in only a few neurone types. Neuroenergetics is of special importance in auditory brainstem nuclei, where neurones exhibit various biophysical adaptations for extraordinary temporal precision and show particularly high firing rates. We have studied the development of energy metabolism in three principal nuclei of the superior olivary complex (SOC) involved in precise binaural processing in the Mongolian gerbil (Meriones unguiculatus). We used immunohistochemistry to quantify metabolic markers for energy consumption (Na+/K+-ATPase) and production (mitochondria, cytochrome c oxidase activity and glucose transporter 3 (GLUT3)). In addition, we calculated neuronal ATP consumption for different postnatal ages (P0–90) based upon published electrophysiological and morphological data. Our calculations relate neuronal processes to the regeneration of Na+ gradients perturbed by neuronal firing, and thus to ATP consumption by Na+/K+-ATPase. The developmental changes of calculated energy consumption closely resemble those of metabolic markers. Both increase before and after hearing onset occurring at P12–13 and reach a plateau thereafter. The increase in Na+/K+-ATPase and mitochondria precedes the rise in GLUT3 levels and is already substantial before hearing onset, whilst GLUT3 levels are scarcely detectable at this age. Based on these findings we assume that auditory inputs crucially contribute to metabolic maturation. In one nucleus, the medial nucleus of the trapezoid body (MNTB), the initial rise in marker levels and calculated ATP consumption occurs distinctly earlier than in the other nuclei investigated, and is almost completed by hearing onset. Our study shows that the mathematical model used is applicable to brainstem neurones. Energy consumption varies markedly between SOC nuclei with their different neuronal properties. Especially for the medial superior olive (MSO), we propose that temporally precise input integration is energetically more costly than the high firing frequencies typical for all SOC nuclei.
Concurrent Processes Within Preliminary Spacecraft Design: an Autonomous Decisional Support Based on a Genetic Algorithms and Analytic Hierarchical Process

This paper proposes a method to support decisions to be taken within a concurrent approach for the space system preliminary design: the defined architecture is based on a Multi-Criteria Decision Making approach mixed with methodologies coming from the Approximate Reasoning domain. The method here presented is focused on saving analysts’ time and effort by addressing the decisions they have to make during the preliminary design process to solve inconsistency and bottlenecks risen from the parallel design of several subsystems From a theoretical point of view, revisited Genetic Algorithms are applied, within each single subsystem design domain, in order to obtain a nondominated solution set to be considered for solving conflicting design at system level; the Analytical Hierarchical Process – supported by dedicated blocks implemented by the Fuzzy Logic approach has been selected as the fittest tool to simulate the causal relationships between variables and objectives, normally prerogative of the analysts’ experience in the spacecraft design domain, within the system level point of view. Simulations showed the ability of the algorithm to find conflicts and suggest a set of subsystem parameters to be tuned to converge – consistently with a user defined cost functions vectors – to a final spacecraft configuration; the tool runs in real-time with the on-going space system design process, in order to support the team leader in making decisions. A comparison with a completely transparent optimization process, implemented by applying a Multi-criteria optimization based on a revised Genetic Algorithm approach, highlighted the capability of the proposed approach to move towards the final Pareto front solution.
Evolving Simulated Mutually Perceptive Creatures for Combat

A fundamental obstacle in evolutionary simulations is the necessity of designing more complex simulations to elicit more complex behaviors. We use a combat-based fitness measure to attempt to circumvent this problem. We have designed a simulation that simultaneously evolves the brains and bodies of creatures for one-on-one combat in a threedimensional environment with realistic physics. By giving the creatures a rich sensorium, we allow them to react sensibly to each others' actions. We discuss the effective, elegant and diverse simulated fighters that emerge, and examine whether qualitatively greater evolutionary complexity arises.
The Anatomy of MapReduce Jobs, Scheduling, and Performance Challenges

Hadoop is a leading open source tool that supports the realization of the Big Data revolution and is based on Google’s MapReduce pioneering work in the field of ultra large amount of data storage and processing. Instead of relying on expensive proprietary hardware, Hadoop clusters typically consist of hundreds or thousands of multi-core commodity machines. Instead of moving data to the processing nodes, Hadoop moves the code to the machines where the data reside, which is inherently more scalable. Hadoop can store a diversity of data types such as video files, structured or unstructured data, audio files, log files, and signal communication records. The capability to process a large amount of diverse data in a distributed and parallel fashion with built-in fault tolerance, using free software and cheap commodity hardware makes a very compelling business case for the use of Hadoop as the Big Data platform of choice for most commercial and government organizations. However, making a MapReduce job that reads in and processes terabytes of data spanning tens of hundreds of machines complete in an acceptable amount of time can be challenging as illustrated here. This paper first presents the Hadoop ecosystem in some detail and provides details of the MapReduce engine that is at Hadoop’s core. The paper then discusses the various MapReduce schedulers and their impact on performance.
Cyclical Dynamics in Three Industries

In this paper we offer a procedure to identify the industry cycles, and apply the procedure to the industrial data of three industries, namely semiconductors, PCs and FPDs. The identified cycles enable us to conduct two comparison analyses: (1) comparing the cycles with those suggested by industry experts in the corresponding industries; (2) comparing the industry cycles across the three industries. Moreover, we examine the factors possibly contributing to the cyclical dynamics of the industries built on three lines of explanations in the literature. Our vector auto regression (VAR) models establish that the dynamics of aggregate economy and capacity are among the most significant drivers in our semiconductor industry cycle.
Minimum Cycle Basis and All-Pairs Min Cut of a Planar Graph in Subquadratic Time

A minimum cycle basis of a weighted undirected graph $G$ is a basis of the cycle space of $G$ such that the total weight of the cycles in this basis is minimized. If $G$ is a planar graph with non-negative edge weights, such a basis can be found in $O(n^2)$ time and space, where $n$ is the size of $G$. We show that this is optimal if an explicit representation of the basis is required. We then present an $O(n^{3/2}\log n)$ time and $O(n^{3/2})$ space algorithm that computes a minimum cycle basis \emph{implicitly}. From this result, we obtain an output-sensitive algorithm that explicitly computes a minimum cycle basis in $O(n^{3/2}\log n + C)$ time and $O(n^{3/2} + C)$ space, where $C$ is the total size (number of edges and vertices) of the cycles in the basis. These bounds reduce to $O(n^{3/2}\log n)$ and $O(n^{3/2})$, respectively, when $G$ is unweighted. We get similar results for the all-pairs min cut problem since it is dual equivalent to the minimum cycle basis problem for planar graphs. We also obtain $O(n^{3/2}\log n)$ time and $O(n^{3/2})$ space algorithms for finding, respectively, the weight vector and a Gomory-Hu tree of $G$. The previous best time and space bound for these two problems was quadratic. From our Gomory-Hu tree algorithm, we obtain the following result: with $O(n^{3/2}\log n)$ time and $O(n^{3/2})$ space for preprocessing, the weight of a min cut between any two given vertices of $G$ can be reported in constant time. Previously, such an oracle required quadratic time and space for preprocessing. The oracle can also be extended to report the actual cut in time proportional to its size.
A comparative study of spectral clustering for i-vector-based speaker clustering under noisy conditions

The present paper dealt with speaker clustering for speech corrupted by noise. In general, the performance of speaker clustering significantly depends on how well the similarities between speech utterances can be measured. The recently proposed i-vector-based cosine similarity has yielded the state-of-the-art performance in speaker clustering systems. However, this similarity often fails to capture the speaker similarity under noisy conditions. Therefore, we attempted to examine the efficiency of spectral clustering on i-vector-based similarity for speech corrupted by noise because spectral clustering can yield robustness against noise by non-linear projection. Experimental comparisons demonstrated that spectral clustering yielded significant improvement from conventional methods, such as agglomerative clustering and k-means clustering, under non-stationary noise conditions.
Distinct Effects of Perceptual Quality on Auditory Word Recognition, Memory Formation and Recall in a Neural Model of Sequential Memory

Adults with sensory impairment, such as reduced hearing acuity, have impaired ability to recall identifiable words, even when their memory is otherwise normal. We hypothesize that poorer stimulus quality causes weaker activity in neurons responsive to the stimulus and more time to elapse between stimulus onset and identification. The weaker activity and increased delay to stimulus identification reduce the necessary strengthening of connections between neurons active before stimulus presentation and neurons active at the time of stimulus identification. We test our hypothesis through a biologically motivated computational model, which performs item recognition, memory formation and memory retrieval. In our simulations, spiking neurons are distributed into pools representing either items or context, in two separate, but connected winner-takes-all (WTA) networks. We include associative, Hebbian learning, by comparing multiple forms of spike-timing-dependent plasticity (STDP), which strengthen synapses between coactive neurons during stimulus identification. Synaptic strengthening by STDP can be sufficient to reactivate neurons during recall if their activity during a prior stimulus rose strongly and rapidly. We find that a single poor quality stimulus impairs recall of neighboring stimuli as well as the weak stimulus itself. We demonstrate that within the WTA paradigm of word recognition, reactivation of separate, connected sets of non-word, context cells permits reverse recall. Also, only with such coactive context cells, does slowing the rate of stimulus presentation increase recall probability. We conclude that significant temporal overlap of neural activity patterns, absent from individual WTA networks, is necessary to match behavioral data for word recall.
An empirical study on reducing omission errors in practice

Since studies based on mining software repositories sparked interests in the field of guiding software changes, many change recommendation techniques have been proposed to reduce omission errors. While these techniques only used existing software commit data sets to evaluate their effectiveness, we use the data set of supplementary patches which correct initial incomplete patches to investigate how much actual omission errors could be prevented in practice. We find that while a single trait is inadequate, combining multiple traits is limited as well for predicting supplementary change locations. Neither does a boosting approach improve accuracy significantly, nor filtering based on developer or package specific information necessarily improves the accuracy. Developers rarely repeat the same mistakes, making the potential value of history-based change prediction less promising. We share our skepticism that omission errors are hard to prevent in practice based on a systematic evaluation of a supplementary patch data set.
Universities online : a survey of online education and services in Australia

This publication reports on a study commissioned by the Department of Education, Science and Training (DEST) to ascertain the current extent of online education in Australian universities. The main findings are presented under the headings of: Online courses; Online units; Online services and support and include: the majority of online courses are at a postgraduate level; the most prevalent form of online delivery was web supplemented; and, online access to web libraries is high.
A trade-off between agility and resilience *

In many natural or artificial settings, agility and resilience are contradictory properties of agents and populations. The settings one can imagine for this contradiction include very different objects such as computer software (agile code is small, runs fast but is more vulnerable to attacks and failures, while resilient code can be bulky and run slowly but has built-in redundancy and robustness to all kinds of attacks and system failures), military units (nonarmored versus heavily armored units), commercial companies (small and lean, or large and slow), and many other situations of interest. In this paper we discuss a mathematical model which represents a population of agents in the presence of other malicious agents, and addresses the trade-off between (a) providing resilience to objects which gives them greater ability to resist attacks but reduces their mobility to attack and destroy their potential attackers, and (b) leaving them in a more agile state where they can more effectively search and destroy their potential attackers, but where they are themselves more vulnerable to attack.
Declarative specification of task-based grasping with constraint validation

Grasping objects and using them in a task-oriented manner is challenging for a robot. It requires an understanding of the object, the robot's capabilities, and the task to be executed. We argue that an explicit representation of these domains increases reusability and robustness of the resulting system. We present the declarative Grasp Domain Definition Language (GDDL) which enables the explicit grasp-planner-independent specification of grasping problems. The formal model underlying GDDL enables the definition of formal constraints that are validated during design time and run time. Our approach has been realized on two real robots.
Study Abroad as a Transformative Experience: Measuring Transformative Learning Phases and Outcomes

Study Abroad as a Transformative Experience: Measuring Transformative Learning Phases and Outcomes Garrett Anderson Stone Department of Recreation Management, BYU Master of Science The purpose of this study was to verify Mezirow’s (1978) Transformative Learning Theory as a model to explain how study abroad participation facilitates efforts to internationalize students in higher education. Specifically this study used block-entry, logistic and linear regression models to explore the relationship between transformative learning processes and study abroad outcomes. Data were collected from business students (N =107) at Brigham Young University using a retrospective pretest method. Findings indicated transformative learning was occurring in short term study abroad settings and transformative learning phases were related to increases in Intercultural Competence. These findings were consistent between year cohorts suggesting the impacts were lasting.
Multi-Channel Gabor Filter Design for Finger-Vein Image Enhancement

Finger-vein recognition has been considered as one of the most convenient and effective biometric ways for personal identification. Extracting vein characteristics is crucial for finger-vein classification. However, the finger-vein extraction results always are greatly sensitive to noises due to the low contrast of finger-vein images. To robustly exploit real vein information, this paper proposes a novel method of finger-vein enhancement based on multi-channel Gabor filters. Firstly, multi-channel Gabor filters are used to prominently protrude vein vessel information with variances in widths and orientations in images. The vein information in different scales and orientations of Gabor filters is then combined together to generate an enhanced finger-vein image using a reconstruction rule. Experimental results show that the proposed method is capable of enhancing fingervein images effectively and reliably.
Output feedback networked control of singular perturbation

In this paper, an observer-based output feedback control of a plant having singular perturbation structure is investigated, where a feedback loop that is closed with a network with a fixed sampling. In the framework of model based, if the model plant is strong controllable and strong observable, the characterization of singular perturbation for overall systems is preserved. Based on the approximated slow and fast subsystems of the overall system on each sampling interval, a lower order test matrix for stability on the whole time interval is obtained. Then, the globally exponential stability for the overall system via a network is shown for small ε > 0. Finally, a numerical simulation illustrates the result.
FAVORED WORKFLOWS IN LIGHT FIELD EDITING

Light fields —4D representations of a scene coding luminance as a function of both position and angle— are becoming increasingly easy to capture. A number of handheld light field cameras, such as those by Lytro, Raytrix, or Pelican Imaging, have already entered the consumer market and are bringing light field photography to the wide public. This gives rise to a new need: Interfaces and tools for light field editing. In this work we provide a detailed description of subjects’ performance and preferences for a number of possible editing tasks. We believe these insights can aid researchers and designers in their creation of new light field editing tools and interfaces.
Effect on Microbial Growth of a New Skin Protectant Formulation

Objective: Evaluate the effect of a new investigational skin protectant formulation on the growth of various microorganisms in vitro. Approach: An in vitro laboratory assay with various species of gram-positive bacteria, gram-negative bacteria, and yeast grown on agar plates was used to verify that a new investigational product used for the management of incontinence-associated dermatitis (IAD) does not support microbial growth. Results: The investigational product did not support the growth of all organisms tested for 48 h in these assays. The results demonstrate the barrier properties of this investigational formulation against bacteria and yeast that are relevant to incontinent patients. Innovation: IAD accompanied by skin damage is difficult to manage with currently available products. A new skin protectant that can be applied as a liquid and polymerizes into a breathable film in situ even in the presence of exudate (as shown previously) has been developed and tested to ensure that it does not support microbial growth. Conclusion: This work verifies that this new product does not support microbial growth in vitro using organisms relevant for the intended application.
Artificial Conversational Companions

This document describes the problem statement, the methodological framework, the current state of the work and the expected contribution of my doctoral dissertation. The main focus of my dissertation is long-term interaction with an Artificial Conversational Companion in the context of conversation training for second language acquisition. I use a data-driven approach and conversation analysis methods to build computational models for long-term interaction as a meaningful activity. I work on the concept of interaction profiles for human-agent interaction. The resulting models will be integrated in an AIML-based chatbot that helps to practice conversation in a foreign language.