Miracle-dz/UniFAR-FTUs huggingface dataset:
DECISION SCIENCES INSTITUTE

This paper focuses on basic concepts and thinking logic of systems science and shows how powerful they can be when employed to address business and economics problems. We look at how such view of the world can produce thought-provoking results. By analyzing how household members interact, an iff condition under which Becker’s Rotten-Kid Theorem holds is developed. By studying the board of directors and CEO of a publicly traded company, it is shown that the CEO could pursue any number of short-term projects. By considering personal value systems, it shows why the principles of management efficiency and organizational inefficiency hold.
A 10-mW 16-b 15-MS/s Two-Step SAR ADC With 95-dB DR Using Dual-Deadzone Ring Amplifier

Low-noise ring amplifiers required for high-precision analog–digital converters (ADCs) greater than 16 b remain unexplored. This article demonstrates a two-step successive approximation (SAR) ADC achieving 91-dB signal-to-noise-and-distortion-ratio (SNDR) with 6-V differential input resulting in a low-frequency Schreier-figure-of-merit ( $\text {FOM}_{S,lf}$ ) of 179.8 dB at 15 MS/s. The state-of-the-art performance is enabled by the ring-amplifier design that enables low noise during amplification and robust control of the transient dynamics. The ADC also features an on-chip residue amplifier (RA) settling characterization using the backend SAR ADC. The ADC is fabricated in a 180-nm CMOS process and occupies an active area of 1.82 mm2.
Scale without Mass : Business Process Replication and Industry Dynamics

Since the mid-1990s, productivity growth has accelerated in the U.S. economy. In this paper, we identify several other changes in the economy that have occurred during the same time and argue that they are consistent with an increased use of information technology (IT) in general and enterprise information technology in particular. In a series of case studies, we find that IT can enable firms to more rapidly replicate improved business processes throughout an organization, thereby not only increasing productivity but also market share and market value. We develop a simple model that shows how this process will increase both turbulence and concentration in affected industries. We then document a substantial increase in firm-level turbulence starting in the 1990s, as measured by the average intra-industry rank change in sales, enterprise value, and other metrics. Furthermore, we find that IT-intensive industries account for most of this increase in turbulence, especially after 1996. Before 1996, IT-intensive industries were becoming less concentrated than non IT-intensive industries; this situation reversed in the late 1990s. The combination of increased turbulence and concentration, especially among IT-intensive industries, is consistent with an increasingly Schumpeterian style of competition. We conclude that the improved ability of firms to replicate business innovations has affected not only productivity, but also the nature of business competition itself.
Score-based Fusion Schemes for Plant Identification from Multi-organ Images

This paper describes some fusion techniques for achieving high accuracy species identification from images of different plant organs. Given a series of different image organs such as branch, entire, flower, or leaf, we firstly extract confidence scores for each single organ using a deep convolutional neural network. Then, various late fusion approaches including conventional transformation-based approaches (sum rule, max rule, product rule), a classification-based approach (support vector machine), and our proposed hybrid fusion model are deployed to determine the identity of the plant of interest. For single organ identification, two schemes are proposed. The first scheme uses one Convolutional neural network (CNN) for each organ while the second one trains one CNN for all organs. Two famous CNNs (AlexNet and Resnet) are chosen in this paper. We evaluate the performances of the proposed method in a large number of images of 50 species which are collected from two primary resources: PlantCLEF 2015 dataset and Internet resources. The experiment exhibits the dominant results of the fusion techniques compared with those of individual organs. At rank-1, the highest species identification accuracy of a single organ is 75.6% for flower images, whereas by applying fusion technique for leaf and flower, the accuracy reaches to 92.6%. We also compare the fusion strategies with the multi-column deep convolutional neural networks (MCDCNN) [1]. The proposed hybrid fusion scheme outperforms MCDCNN in all combinations. It obtains from + 3.0% to + 13.8% improvement in rank-1 over MCDCNN method. The evaluation datasets as well as the source codes are publicly available. Keywords: Plant identification, Convolutional neural network, Deep learning, Fusion.
Inference of epistatic effects and the development of drug resistance in HIV-1 protease

10 Understanding the complex mutation patterns that give rise to drug resistant viral strains provides a foundation for developing more effective treatment strategies for HIV/AIDS. Multiple sequence alignments of drug-experienced HIV-1 protease sequences contain networks of many pair correlations which can be used to build a (Potts) Hamiltonian model of these mutation patterns. Using this Hamiltonian 15 model we translate HIV protease sequence covariation data into quantitative predictions for the stability and fitness of individual proteins containing therapy-associated ∗Corresponding author: ronlevy@temple.edu 1 not peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was . http://dx.doi. org/10.1101/063750 doi: bioRxiv preprint first posted online Jul. 13, 2016;
Populism Across the Atlantic: The Popular Retort to Globalism and Modernization in the United States, United Kingdom, and Germany

This paper explores the similarities and differences between the election of Donald Trump as President of the United States, the United Kingdom’s decision to withdraw from the European Union, and the rise of the Alternative for Deutschland (AfD), a populist political party in Germany. Happening over a period of just a few years, these events mark a high point in an increasing populistic trend that is changing the political landscape on both sides of the Atlantic. Trump’s election marks a major turning point in the United States as he wins an election after having specifically campaigned against free trade, establishment politicians, and immigration. In the United Kingdom, the movement to leave the European Union was motivated by similar concerns about immigration and jobs. And in Germany, the recent rise of the AfD and their viability as a serious contender in the upcoming elections show a trend towards populism in a country that was long considered immune to populist tendencies. This paper intends to take a deeper look at these different populist movements, examining their histories, successes, failures, and the demographics of their supporters. While populism is not new to the United States or Europe, does the fact that these movements have similar aims suggest their rise may be part of a popular retort to globalism and modernization? To answer this question, this paper will additionally look at the general effects of globalism and modernization, specifically in the United States, United Kingdom, and Germany. Although, generally, progress in these fields is considered a move forward, this paper will look specifically at those who have been passed over by these rapid changes, and how their disenfranchisement may be the catalyst for populism in the United States and Europe. So even though these populist movements tend to target the “elite” or “ruling class” as scapegoats for their problems, this paper suggests that perhaps the real POPULISM ACROSS THE ATLANTIC 3 motivator of transatlantic populism lies beyond the White House, 10 Downing Street, or the Germany Chancellery.
DIVISION OF THE HUMANITIES AND SOCIAL SCIENCES

We explore an equilibrium model of games where players’ choice behavior is given by logit response functions, but their payoff responsiveness is heterogeneous. We extend the definition of quantal response equilibrium to this setting, calling it heterogeneous quantal response equilibrium (HQRE), and prove existence under weak conditions. We generalize HQRE to allow for limited insight, in which players can only imagine others with low responsiveness. We identify a formal connection between this new equilibrium concept, called truncated quantal response equilibrium (TQRE), and the Cognitive Hierarchy (CH) model. We show that CH can be approximated arbitrarily closely by TQRE. We report a series of experiments comparing the performance of QRE, HQRE, TQRE and CH. A surprise is that the fit of the models are quite close across a variety of matrix and dominance-solvable asymmetric information betting games. The key link is that in the QRE approaches, strategies with higher expected payoffs are chosen more often than strategies with lower expected payoff. In CH this property is not built into the model, but generally holds true in the experimental data. JEL classification numbers: 024, 026
Robust Search-Free Car Number Plate Localization Incorporating Hierarchical Saliency

Automatic license plate recognition (ALPR) has become increasingly popular in intelligent transportation systems. ALPR consists of three main stages: localization, segmentation, and optical character recognition (OCR). The quality of images taken by traffic cameras throughout the city is rapidly improving and therefore the size and the resolution of these images have been moderated. Most of the available localization methods, which have to deal with large-size images in real-time scenarios, become computationally intensive when cars are moving and therefore, very time-consuming. Developing more adequate algorithms for localization of car number plates for faster processing of such large images often becomes necessary.
The relative contribution of waves, tides, and nontidal residuals to extreme total water levels on U.S. West Coast sandy beaches

To better understand how individual processes combine to cause flooding and erosion events, we investigate the relative contribution of tides, waves, and nontidal residuals to extreme total water levels (TWLs) at the shoreline of U.S. West Coast sandy beaches. Extreme TWLs, defined as the observed annual maximum event and the simulated 100 year return level event, peak in Washington, and are on average larger in Washington and Oregon than in California. The relative contribution of wave‐induced and still water levels (SWL) to the 100 year TWL event is similar to that of the annual maximum event; however, the contribution of storm surge to the SWL doubles across events. Understanding the regional variability of TWLs will lead to a better understanding of how sea level rise, changes in storminess, and possible changes in the frequency of major El Niños may impact future coastal flooding and erosion along the U.S. West Coast and elsewhere.
Living with drought: the case of the Maasai pastoralists of northern Kenya

Pastoralism, which is the main source of livelihood to about 120 million pastoralists worldwide, is practiced in the drylands that are characterized by low rainfall and frequent droughts. In the semi arid and arid lands of Kenya (88% of the Kenya landmass), pastoralism accounts for 90% of the employment and 95% of the family incomes and livelihood security. It contributes to about 10% of the country’s gross domestic product (GDP) and 50% of the agricultural GDP. However, frequent droughts have threatened this important sector which offers a viable production system in the vast drylands of the country. This paper highlights on the effects of droughts on pastoralism and the coping and adaptive strategies employed by the Maasai pastoralists of northern Kenya with special reference to Mukogodo Division of the semi arid Laikipia District.
Evaluation of wine grape varieties for growth and yield under northern dry zone of Karnataka

The present study was conducted during 2014-15 to know the variation in growth and yield of eleven wine grape genotypes. The highest shoot length (75.34 cm) was recorded in Chenin Blanc at 60 days after back pruning. The maximum shoot girth (1.61cm) was recorded in Sauvignon Blanc at 105 days after pruning. The vigour of individual shoot increased with the decreased canes per vine. Chenin Blanc registered the maximum number of leaves per shoot (17.94) at 90 days after pruning and also Chenin Blanc had long period ( 20.00 days ) for panicle emergence. The genotype Medika recorded the maximum length of berry (1.64 cm), diameter of berry (1.59 cm) and mean weight of berry (3.08 cm) at different intervals.The bunch length and weight of 50 berries varied significantly among the treatments. The maximum bunch length (23.33 cm) was found in Medika. However, Medika had the highest 50 berry weight (121.53 g) among the genotypes, Sirius was found to be an early where harvesting was done in 115 days. The maximum number of bunches per vine (110.44) was recorded in Grenache Blanc. The genotype Medika recorded the maximum bunch weight (419.15 g). However, the genotype Tempranillo registered the highest tonnage (60.88 t/ha) followed by Grenache Blanc (53.98 t/ha).
Internal Dynamics of a Free-Surface Viscoplastic Flow Down an Inclined Channel

This paper presents preliminary experimental results concerning the internal dynamics of a free surface viscoplastic flow down an inclined channel. Experiments are conducted in an inclined channel whose bottom is constituted of an upward-moving conveyor belt with controlled velocity. Carbopol microgel was used as a homogeneous transparent viscoplastic fluid. This experimental setup allows generating and observing stationary gravity-driven surges in the laboratory frame. We used PIV technique (Particle Image Velocimetry) to obtain velocity fields both in the uniform zone and within the front zone where flow thickness is variable and where recirculation takes place. Experimental velocity profiles and determination of plug position are presented and compared to theoretical predictions based on the lubrication approximation.
Rendezvous Without Coordinates

We study minimalism in sensing and control by considering a multi-agent system in which each agent moves like a Dubins car and has a limited sensor that reports only the presence of another agent within some sector of its windshield. Using a simple quantized control law with three values, each agent tracks another agent (its target) assigned to it by maintaining that agent within this windshield sector. We use Lyapunov analysis to show that by acting autonomously in this way, the agents will achieve rendezvous given a connected initial assignment graph and the assumption that an agent and its target will merge into a single agent when they are sufficiently close. We then proceed to show that, by making the quantized control law slightly stronger, a connected initial assignment graph is not required and the sensing model can be weakened further. A distinguishing feature of our approach is that it does not involve any estimation procedure aimed at reconstructing coordinate information. Our scenario thus provides an example in which an interesting task is performed with extremely coarse sensing and control, and without state estimation. The system was implemented in computer simulation, accessible through the Web, of which the results are presented in the paper.
Semiannual variability of the California Undercurrent along the Southern California Current System: A tropical generated phenomenon

We used a high-resolution numerical model implementation to analyze the California Undercurrent (CU) dynamics along the Southern California Current System. In agreement with reported observations, the modeled CU was stronger during June–July and December–January, when it flowed continuously along Baja California and Southern California reaching long-term averages up to 6 cm s−1. Previous research has associated the biannual CU intensification to the local dynamics off Southern California. Our results evidenced, however, that the passage of remote Semiannual Coastal-Trapped Waves (SCTW) primarily explained the semiannual CU variability. The CU was stronger 2–3 months after the passage of the upwelling SCTW phase, when the offshore propagation of Rossby waves, brought about by the SCTW transit, induced an energetic cross-shore pressure gradient that strengthened the subsurface poleward circulation along the continental slope. The SCTW were independent of the local wind; they corresponded to the northward extension of semiannual equatorial Kelvin waves that have been observed along the northeastern tropical Pacific.
Resilient Critical Infrastructure Planning Under Disruptions Considering Recovery Scheduling

Reliable and safe critical infrastructures are crucial for the sustainability of modern societies. To cope with increasing disruptive events such as man-made and natural disasters attacking infrastructures, resilience should be considered as an integrated perspective into the system planning process. This paper presents a p-robust optimization model for infrastructure network planning against spatially localized disruptions. The optimization aims at minimizing the investment costs for system hardening and expansion and the total system costs under nominal operating conditions, while incorporating resilience requirements by the p-robustness constraints. Importantly, instead of only mitigating system vulnerability, the proposed model integrates the arranging of the repair sequence of damaged components under limited repair resources into the preevent system planning. The complexity of the proposed model is analyzed, and a hybrid algorithm that combines scenario-based decomposition and variable neighborhood search is developed for its efficient solution. The effectiveness of the approach is illustrated through an application to a real power transmission system. Quantitative analysis can assist managers in decision making regarding investing in different system protection actions and making a tradeoff between desired resilience and budget constraints.
Loyola eCommons Loyola eCommons

— This study investigated the impact of the Exploring Computer Science (ECS) program on the likelihood that students of all races and gender would pursue further computer science coursework in high school. ECS is designed to foster deep engagement through equitable inquiry around computer science concepts. If the course provides a meaningful and relevant experience, it will increase students' expectancies of success as well as increase their perceived value for the field of computer science. Using survey research, we sought to measure whether the relevance of students' course experiences influenced their expectancies and value and whether those attitudes predicted whether students pursued further computer science coursework. The results indicate that students whose course experience increased expectancies for success were more likely to take another course.
Programs with Quasi-Stable Channels are Effectively Recognizable

1 I n t r o d u c t i o n There are several models which can be used to study distributed algori thms and communicat ing protocols. The model we use in this paper is that of systems of communicat ing finite states machines (CFSMs). It consists of programs represented by finite state machines which communicate over unbounded channels. This model is widely used both for verification and validation in languages such ESTELLE, SDL and LOTOS [15]. It has also its own theoretical interest as shown by the li terature it has generated in the last few years [1,2,6,9] . However, this model has the power of Turing machines since i t 's possible to simulate them by a system of two communicat ing finite state machines [5,10], thus verification is undecidable for non-trivial problems. This l imitat ion motivates the study of classes of systems for which verification algori thms are possible [1,2,6,8,9,12,14]. The class introduced by Pachl [14], systems with a recognizable teachability set, is interesting since it covers a wide number of protocols and since the reachability problem is solved for it. However, the need to list recognizable sets makes this algori thm inefficient! Moreover, i t 's not possible to decide whether a given system has a recognizable reachability set, which is the s tar t ing point for using Pachl's result.
Super-Resolution Channel Estimation for Massive MIMO via Clustered Sparse Bayesian Learning

This correspondence paper provides a novel super-resolution downlink channel estimation approach for massive multiple-input multiple-output (MIMO) systems, by jointly learning the parametric dictionary and recovering the sparse channel components. Specifically, we exploit a Markov spike and slab prior to characterize the clustered sparse channel structure resulting from small local scatterers in the angular domain. The proposed algorithm is developed within a variational expectation maximization framework and integrated with the generalized approximate message passing technique to calculate the intractable posterior distribution. Simulation results illustrate that our approach attains a significant performance improvement over existing methods.
Document object model (dom) level 1 specification

Status of this document This document has been reviewed by W3C Members and other interested parties and has been endorsed by the Director as a W3C Recommendation. It is a stable document and may be used as reference material or cited as a normative reference from another document. W3C's role in making the Recommendation is to draw attention to the specification and to promote its widespread deployment. This enhances the functionality and interoperability of the Web. The authors of this document are the DOM Working Group members, different chapters may have different editors. Comments on this document should be sent to the public mailing list www-dom@w3.org. A list of current W3C Recommendations and other technical documents can be found at Abstract This specification defines the Document Object Model Level 1, a platform-and language-neutral interface that allows programs and scripts to dynamically access and update the content, structure and style of documents. The Document Object Model provides a standard set of objects for representing HTML and XML documents, a standard model of how these objects can be combined, and a standard interface for accessing and manipulating them. Vendors can support the DOM as an interface to their proprietary data structures and APIs, and content authors can write to the standard DOM interfaces rather than product-specific APIs, thus increasing interoperability on the Web. The goal of the DOM specification is to define a programmatic interface for XML and HTML. The DOM Level 1 specification is separated into two parts: Core and HTML. The Core DOM Level 1 section provides a low-level set of fundamental interfaces that can represent any structured document, as well as defining extended interfaces for representing an XML document. These extended XML interfaces need not be implemented by a DOM implementation that only provides access to HTML documents; all of the fundamental interfaces in the Core section must be implemented. A compliant DOM implementation that implements the extended XML interfaces is required to also implement the fundamental Core interfaces, but not the HTML interfaces. The HTML Level 1 section provides additional, higher-level interfaces that are used with the fundamental interfaces defined in the Core Level 1 section to provide a more convenient view of an HTML document. A compliant implementation of the HTML DOM implements all of the fundamental Core interfaces as well as the HTML interfaces.