Miracle-dz/UniFAR-FTUs huggingface dataset:
Contrasting tectonic styles in the Neogene orogenic belts of Indonesia

Abstract The recent compilation of a new tectonic map of Indonesia as part of the Geotectonic Map Project of East Asia has prompted a reassessment of the contrasted tectonic styles represented by currently developing orogenic belts. These orogenic styles provide a range of models illustrating the diversity and complexity of tectonic processes which may provide the key to the interpretation of other orogenic belts elsewhere in the world. The following distinctive types of orogenies have been recognized within Indonesia. 1. Sunda Orogeny in Java and Nusa Tenggara: involving subduction of oceanic crust with normal convergence, producing an orogenic belt of Andean type with trench, accretionary complex, forearc basin and Quaternary magmatic arc with active volcanoes built on the margin of the Sundaland continent. 2. Barisan Orogeny in Sumatra: with strongly oblique convergence and major strike slip transcurrent fault movement within the magmatic arc, along which a segment of continental crust is being displaced northwards along the western margin of Sundaland. 3. Talaud Orogeny in the northern Molucca Sea: convergence of the Sangihe and Halmahera oceanic magmatic arcs as the Molucca Sea Plate subsides beneath them. 4. Sulawesi Orogeny in eastern Sulawesi: collision of microcontinental blocks with subduction systems along the eastern margin of Sundaland. 5. Banda Orogeny in the southern Banda Arc between Sumba and Tanimbar: collision of the northern margin of the Australian continent with the subduction system along the southern segment of the Banda Arc. 6. Melanesian Orogeny in Irian Jaya and Papua New Guinea: a more advanced stage in the collision of the northern margin of the Australian continent with a magmatic arc on the Philippine Sea plate, commencing in the early Miocene with a partial reversal of polarity and the subduction of the Caroline plate beneath the collision zone. The present phase of orogenic activity in most of these occurrences commenced in mid-Miocene times and orogenic processes are still in progress.
A nuclear magnetic resonance study of metabolism in the ferret heart during hypoxia and inhibition of glycolysis.

31P nuclear magnetic resonance was used to measure the relative concentrations of phosphorus‐containing metabolites in Langendorff‐perfused ferret hearts. Intracellular concentrations of inorganic phosphate ([Pi]i), phosphocreatine ([PCr]i), ATP ([ATP]i) and H+ (pHi) were monitored under control conditions and while oxidative phosphorylation and/or glycolysis were prevented. Mechanical performance was assessed by recording the pressure developed in a balloon placed in the left ventricle. Oxidative phosphorylation was prevented either by replacement of O2 with N2 or by addition of cyanide. When the rate of oxidative phosphorylation was reduced by either method, developed pressure fell to a stable level of about 35% of control after 5 min. The pHi (control value 6.98) first increased to a peak of 7.07 after 2 min but then decreased to give a stable acidosis (pH 6.85). [PCr]i decreased rapidly to about 15% of the control value after 5 min whereas [ATP]i declined very slowly, reaching about 90% of the control value after 10 min. Reduction in the rate of glycolysis was achieved either (i) by removal of external glucose and depletion of glycogen stores by a long (1‐2 h) period of stimulation or (ii) by removal of glucose and application of 2‐deoxyglucose (1 mM) for 30‐60 min. These procedures had only a small effect on pressure development, [ATP]i, [PCr]i and pHi. Measurements of lactate production showed that these procedures reduced the rate of glycolysis by a factor of about 10. When oxidative phosphorylation was prevented during periods when the rate of glycolysis was reduced, developed pressure fell to less than 5% of control after 5 min and there was a subsequent increase in resting pressure (hypoxic contracture). pHi (control value 7.03) first increased to a peak of 7.12 and then declined to about pH 7.00, but there was no subsequent acidosis. [PCr]i fell rapidly to about 10% of control after about 5 min while [ATP]i declined to about half of its control value over 10 min. It is concluded that (i) when oxidative phosphorylation alone is prevented, the changes in pHi can account for a substantial part of the changes in developed pressure. The increase in [Pi]i probably also contributes to the decline of developed pressure. (ii) When oxidative phosphorylation was prevented under conditions in which the rate of glycolysis was also reduced, the more pronounced decline in developed pressure which occurs within 5 min cannot be accounted for by pHi changes and is probably not explained by the rise in [Pi]i or by the moderate fall of [ATP]i. (ABSTRACT TRUNCATED AT 400 WORDS)
In the Light of Current Evidence, Critically Examine the Efficient Market Hypothesis the Efficient Market Hypothesis (emh)

This paper shall firstly explain the Efficient Market Hypothesis (EMH), its history and its theoretical justification for explaining empirical evidence. Fundamental problems with the theory are then highlighted, followed by a summary of the most modern approaches to how markets work. The paper concludes that the EMH works by coincidence i.e.; by accident. The EMH tries to explain why stock market prices appear to follow a random walk i.e.; that their daily variation is a random value following the Gaussian distribution. This random walk of stock market prices had been originally noticed by Bachelier (1900) but had only become widely realised since Kendall (1953), at which point it was considered something rather unusual. The reason that a random walk appeared unusual was because from Neo‐Classical Economic theory (specifically Walrasian General Equilibrium Theory), markets were supposed to approach equilibrium over the medium to long run and they were supposed to do this by tâtonnement (the process of finding the market clearing prices to precisely match supply and demand). Prior to Arrow (1951) and Debreu (1959), it had not yet been realised just how restrictive the assumptions would have to be in order to enable Walrasian equilibrium whilst keeping the system from degenerating into indeterminacy 1. The EMH was originated by Fama (1965) in his PhD thesis, and given its modern three‐type form in Fama (1970). The EMH explains the random walk by assigning its occurrence to uncertainty i.e.; the existence of the future, whereby future events are unknown to or mispredicted by the market. As we now know that determinate Walrasian equilibrium requires perfect knowledge of the future, uncertainty causes substantial long‐term deviations from expected behaviour. There are three main forms of EMH, each becoming successively stronger in implication: 1. Weak form That market prices correctly represent all the information contained in the record of past prices and trading volume. 1 Subsequent to Arrow and Debreu's work, the Sonnenshein‐Mantel‐Debreu assumptions are the modern prerequisite for determinacy in micro‐economics. See Mas‐Colell's (1995) Microeconomic Theory starting at section 17.
Exploring the Parallel Programming Design Space of Proximate , a Multi-Tile Programmable Accelerator ( CS 758 Project Report )

The slowing of Moores law and Dennard scaling is limiting the performance improvements of single core processors. Increasing clock frequency any farther will lead to high leakage current and infeasible power consumption. Over the past decade, focus has been shifted to multi-core processors to increase throughput by having multiple cores to target different types of parallelism instruction (ILP), data (DLP) and thread (TLP). However, even the multi-core processors are not scalable for parallelization beyond a point due to Amdahl’s law. To address these challenges of rising dark silicon and the end of Dennard scaling, in recent years architects have turned to heterogeneous architectures with special purpose domain specific accelerators (DSAs), for higher performance and energy efficiency. While providing huge benefits, DSAs are prone to obsoletion due to domain volatility, have recurring design and verification costs, and have large area footprints when multiple DSAs are required in a single device to reap out the benefits of different application acceleration. To attack such problems of DSAs and multi-core processors, while still retaining programmability of general purpose processors and efficiency of DSAs, there is an on-going research in Vertical Research Group, University of Wisconsin-Madison aiming to build a general purpose multi-tile programmable accelerator called Proximate. This project focuses on exploring the parallel programming design space of Proximate, a multi-tile programmable hardware accelerator. The aim is to investigate the programming interface of Proximate, the parallel hardware improvements and in general explore the parallel programs run on proximate. We have tried to explore a new type of the multi-tile programmable architecture, its scalability and speedup of such accelerator architecture compared to a traditional server class multi-core processors for parallel programs. In summary, we explored different programming design points in the project and proximate is able to achieve speedups of 50-100x over a traditional server class multi-core processor. We try to analyze this trend over the coarse of this document by explaining the architecture, programming model and the performance results of proximate.
Abnormal Pattern Recognition in Spatial Data

In the recent years, abnormal spatial pattern recognition has received a great deal of attention from both industry and academia, and has become an important branch of data mining. Abnormal spatial patterns, or spatial outliers, are those observations whose characteristics are markedly different from their spatial neighbors. The identification of spatial outliers can be used to reveal hidden but valuable knowledge in many applications. For example, it can help locate extreme meteorological events such as tornadoes and hurricanes, identify aberrant genes or tumor cells, discover highway traffic congestion points, pinpoint military targets in satellite images, determine possible locations of oil reservoirs, and detect water pollution incidents. Numerous traditional outlier detection methods have been developed, but they cannot be directly applied to spatial data in order to extract abnormal patterns. Traditional outlier detection mainly focuses on “global comparison” and identifies deviations from the remainder of the entire data set. In contrast, spatial outlier detection concentrates on discovering neighborhood instabilities that break the spatial continuity. In recent years, a number of techniques have been proposed for spatial outlier detection. However, they have the following limitations. First, most of them focus primarily on single-attribute outlier detection. Second, they may not accurately locate outliers when multiple outliers exist in a cluster and correlate with each other. Third, the existing algorithms tend to abstract spatial objects as isolated points and do not consider their geometrical and topological properties, which may lead to inexact results. This dissertation reports a study of the problem of abnormal spatial pattern recognition, and proposes a suite of novel algorithms. Contributions include: (1) formal definitions of various spatial outliers, including single-attribute outliers, multi-attribute outliers, and region outliers; (2) a set of algorithms for the accurate detection of single-attribute spatial outliers; (3) a systematic approach to identifying and tracking region outliers in continuous meteorological data sequences; (4) a novel Mahalanobis-distance-based algorithm to detect outliers with multiple attributes; (5) a set of graph-based algorithms to identify point outliers and region outliers; and (6) extensive analysis of experiments on several spatial data sets (e.g., West Nile virus data and NOAA meteorological data) to evaluate the effectiveness and efficiency of the proposed algorithms.
Helping the Noncompliant Child: Family-Based Treatment for Oppositional Behavior

Child Compliance and Noncompliance. Parent Training. Overview of the "Helping the Noncompliant Child" (HNC) Parent Training Program. Assessment Methods and Procedures. The Feedback Session and Sample Program Outline. Phase I: The Skills of Differential Attention. Phase II: The Skills of Compliance Training. Adjunctive Interventions. Wells, Adaptations for Specific Populations. Review of Treatment Research and Current Directions. Appendix A: Parent's Consumer Satisfaction Questionnaire. Appendix B: Parent Handouts and Record Sheets. Appendix C: Social Learning Criterion Tests and Scoring Keys. Appendix D: Mealtime Brochure.
Managing Organizational Behavior

Preface. 1. Introduction. An Historical View of Contemporary Organizational Behavior. Organizational Theory. Organizational Behavior. Current Trends and Challenges. Managing Organizational Performance. Plan of This Book. 2. Personality and Individual Differences. Personality. The Bases of Personality. Approaches to Learning. Personality in Organization Settings. 3. Attitudes, Perception and Judgement. The Nature of Attitudes. Why Attitudes Are Important. Cognitive Dissonance. Perception. Judgement Tendencies. 4. Organizational Accommodation: Socialization, Careers and Commitment: Careers and Career Paths. Organizational Socialization. Organizational Commitment. Diversity and Work in Organizations. 5. Theories of Motivation. Need Theories of Motivation. The Job Characteristics Approach. Achievement / Power Theory. Reinforcement Theory. Goal Setting Theory. Justice Theories of Motivation. 6. Applied Motivation Theories. Management by Objectives. Positive Reinforcement Programs. Gainsharing. High Involvement Organizations. 7. Stress in Organizations. Stress and Coping. Stress Manifestations. Sources of Stress. Stress and Individual Differences. 8. Group and Team Performance Environment. Why Groups Form. Types of Groups. A Model of Group Effectiveness. The Group Performance Environment. 9. Group Process and Effectiveness. Group Development. Group Norms. Group Cohesiveness, Cooperation and Competition. Social Influences. What Makes Groups Effective? 10. Conflict. The Nature of Conflict. Conflict Reaction Styles. Diagnosing Conflict. Improving Organizational Response to Conflict. 11. Decision Making. Characteristics of the Decision Process. Models of Decision Making. Improving Individual Decision Making. Improving Group Decision Making. 12. Cultures: National and Organizational. The Hofstede Model of National Cultures. Organizational Consequences of Cultural Differences. Organizational Culture. Types of Organizational Culture. Organizational Culture - Special Cases. 13. Organization Structure and Design. The Nature of Organization Structure. Organization Environments. Organization Design. Formal Organization Structures. 14. Power and Politics in Organizations. The Bases of Influence. Acquiring and Maintaining Organizational Based Influence. Acquiring and Maintaining Personal Based Influence. Using Managerial Power in Organizations. 15. Leadership in Organizations. Trait Approaches to Leadership. Behavioral Approaches to Leadership. Contingency Theories of Leadership. Process Theories of Leadership. Substitutes for Leadership. 16. Organizational Change. How Our Work Life Is Changing. Resistance to Change. Stages of Successful Change. Helping Individuals Cope with Change. Implementing Change. Glossary. Index.
Simultaneous feature selection and clustering with mixed features by multi objective genetic algorithm

In this paper, we propose a novel evolutionary clustering algorithm for mixed type data numerical and categorical. It is doing clustering and feature selection simultaneously. Feature subset selection improves quality of clustering. It also improves understandability and scalability. It unfastens attraction on numerical or categorical dataset only. K-prototype KP is a well-known partitional clustering algorithm for mixed type data. However, this type of algorithm is sensitive to initialization and may converge to local optima. It is optimizing a single measure only i.e. minimizations of intra cluster distance. We have considered clustering as a multi objective optimization problem MOOP. Minimization of intra cluster distance and maximization of inter cluster distance are two objectives of optimization. Multi objective genetic algorithm MOGA is a well-known algorithm which can be applicable for MOOP to find out near global optimal solution. So in this paper we have developed a hybridized genetic clustering algorithm by combining the global search ability of MOGA and local search ability of KP. Experiments on real-life benchmark datasets from UCI machine learning repository prove the superiority of the proposed algorithm.
Scheduling Storms and Streams in the Cloud

Motivated by emerging big streaming data processing paradigms (e.g., Twitter Storm, Streaming MapReduce), we investigate the problem of scheduling graphs over a large cluster of servers. Each graph is a job, where nodes represent compute tasks and edges indicate data-flows between these compute tasks. Jobs (graphs) arrive randomly over time, and upon completion, leave the system. When a job arrives, the scheduler needs to partition the graph and distribute it over the servers to satisfy load balancing and cost considerations. Specifically, neighboring compute tasks in the graph that are mapped to different servers incur load on the network; thus a mapping of the jobs among the servers incurs a cost that is proportional to the number of "broken edges''. We propose a low complexity randomized scheduling algorithm that, without service preemptions, stabilizes the system with graph arrivals/departures; more importantly, it allows a smooth trade-off between minimizing average partitioning cost and average queue lengths. Interestingly, to avoid service preemptions, our approach does not rely on a Gibbs sampler; instead, we show that the corresponding limiting invariant measure has an interpretation stemming from a loss system.
Searching for galaxy clusters using the aperture mass statistics in 50 VLT fields

Application of the aperture mass ( M ap -) statistics provides a weak lensing method for the detection of cluster-sized dark matter halos. We present a new aperture filter function and maximise the effectiveness of the M ap -statistics to detect cluster-sized halos using analytical models. We then use weak lensing mock catalogues generated from ray-tracing through N -body simulations, to analyse the effect of image treatment on the expected number density of halos. Using the M ap -statistics, the aperture radius is typically several arcminutes, hence the aperture often lies partly outside a data field, consequently the signal-to-noise ratio of a halo detection decreases. We study these border effects analytically and by using mock catalogues. We find that the expected number density of halos decreases by a factor of two if the size of a field is comparable to the diameter of the aperture used. We finally report on the results of a weak lensing cluster search applying the M ap -statistics to 50 randomly selected fields which were observed with FORS1 at the VLT. Altogether the 50 VLT fields cover an area of 0.64 square degrees. The I -band images were taken under excellent seeing conditions (average seeing $\approx 0\hbox{$.\! \! ^{\prime\prime}$}6$) which results in a high number density of galaxies used for the weak lensing analysis ($n\approx 26\,{\rm arcmin}^{-2}$). In five of the VLT fields, we detect a significant M ap -signal which coincides with an overdensity of the light distribution. These detections are thus excellent candidates for shear-selected clusters.
Content-based Routing For ebXML Messages in E-commerce

The main component of electronic commerce (E-commerce) is the exchange of documents and messages. In the field of commercial messages standardization, the ebXML framework offers the valid standard for message modeling. Due to the importance of standardization ebXML framework in E-commerce, creating more facilities, in the ebXML messaging is so important. Today, the exchange of messages within the ebXML framework uses explicit addressing, in which, the message ultimate recipient is determined based on message producer partner and the information existed in collaboration agreement. In case of explicit addressing Use, among the messages that are reached by the partners in the business process, only a few of them may be appropriate to the needs of the recipient and as a result the recipient is forced to discard some of them. Due to releasing a large number of relatively high-volume messaging in system, not only the bandwidth consumption will rise, but it also slows down the message precision regarding to the message received by the partner that is appropriate to its needs or not. The purpose of this paper is providing a method in order to convert an explicit addressing to the implicit addressing for ebXML messages. The proposed method is based on an algorithm called "Rendezvous", that’s one of the algorithms which have been widely used in networks based on contents and specifically in publish/subscribe systems. At the end of work though, bandwidth parameters, speed and precision in both traditional ebXML messaging method and the proposed messaging method are compared. General Terms Content-based routing for ebXML message
Optimizing B Uchi Automata

We describe a family of optimizations implemented in a translation from a linear temporal logic to B uchi automata. Such optimized automata can enhance the eeciency of explicit state model checking, as practiced in tools such as Spin. Some of our optimizations are applied during preprocessing of temporal formulas, others are applied during the translation algorithm itself, while other key optimizations are applied directly to the resulting B uchi automata independent of how they arose. Among these latter optimizations we apply a practical variant of fair simulation reduction based on color reenement. Although there are weaker notions of fair simulation available in the literature, leading to potentially greater reduction, the best algorithms for computing these weaker notions appear at present to be impractical. We have implemented our optimizations in a translation of an extension to LTL described in Ete99], which allows expression of all ! -regular properties. Inspired by this work, a subset of the optimizations outlined here has been added to a recent version of Spin. Both implementations begin with an underlying translation based on the algorithm of GPVW95]. We describe the results of tests we have conducted, both to see how the optimizations improve the sizes of resulting automata, as well as to see how the smaller sizes for the automata aaect the running time of Spin's explicit state model checking algorithm. One surprising nding is that, when error paths exist in the model, a smaller number of states in the automaton does not necessarily improve the running time and can actually hurt it in ways that are diicult to predict. Our translation is available via a web-server which includes a GUI that depicts the resulting automata: