Miracle-dz/UniFAR-FTUs huggingface dataset:
Least quantile regression via modern optimization

We address the Least Quantile of Squares (LQS) (and in particular the Least Median of Squares) regression problem using modern optimization methods. We propose a Mixed Integer Optimization (MIO) formulation of the LQS problem which allows us to find a provably global optimal solution for the LQS problem. Our MIO framework has the appealing characteristic that if we terminate the algorithm early, we obtain a solution with a guarantee on its sub-optimality. We also propose continuous optimization methods based on first-order subdifferential methods, sequential linear optimization and hybrid combinations of them to obtain near optimal solutions to the LQS problem. The MIO algorithm is found to benefit significantly from high quality solutions delivered by our continuous optimization based methods. We further show that the MIO approach leads to (a) an optimal solution for any dataset, where the data-points $(y_i,\mathbf{x}_i)$'s are not necessarily in general position, (b) a simple proof of the breakdown point of the LQS objective value that holds for any dataset and (c) an extension to situations where there are polyhedral constraints on the regression coefficient vector. We report computational results with both synthetic and real-world datasets showing that the MIO algorithm with warm starts from the continuous optimization methods solve small ($n=100$) and medium ($n=500$) size problems to provable optimality in under two hours, and outperform all publicly available methods for large-scale ($n={}$10,000) LQS problems.
Psychometric properties of three single-item pain scales in patients with rheumatoid arthritis seen during routine clinical care: a comparative perspective on construct validity, reproducibility and internal responsiveness

Objective To investigate the construct validity, reproducibility (ie, retest reliability) and internal responsiveness to treatment change of common single-item scales measuring overall pain in patients with rheumatoid arthritis (RA) and to investigate the corresponding effect of common pain-related comorbidities and medical consultation on these outcomes. Methods 236 patients with RA completed a set of questionnaires including a visual analogue scale (VAS), a numerical rating scale (NRS) and a verbal rating scale (VRS) measuring overall pain before and immediately after routine medical consultation as well as 1 week after the patient's visit. Construct validity and retest reliability were evaluated using the Bravais-Pearson correlation while standardised response means (SRM) were calculated for evaluating internal responsiveness. Differences in the perception of pain were calculated using dependent samples t-tests. Results In the total sample, construct validity was good across all three time points (convergent validity of pain scales: rT1–T3=0.82–0.92, p<0.001; discriminant validity as correlation of pain scales with age: rage=0.01–0.16, p>0.05). In patients maintaining antirheumatic treatment, retest reliability of pain scales was confirmed for all scales and across time points (rVAS=0.82–0.95, rNRS=0.89–0.98, rVRS=0.80–0.90, p<0.001), while the internal responsiveness of scales to a change in treatment was low across all scales (SRM=0.08–0.21). The VAS especially suggested a change in pain perception after medical consultation in patients maintaining therapy. Conclusions The VAS, NRS and VRS are valid and retest reliable in an outpatient clinical practice setting. The low pain scales’ internal responsiveness to treatment change is likely to be due to the short follow-up period. Patients with RA maintaining antirheumatic therapy seem to experience less pain after medical consultation.
Spatially Discrete FitzHugh--Nagumo Equations

We consider pulse and front solutions to a spatially discrete FitzHugh--Nagumo equation that contains terms to represent both depolarization and hyperpolarization of the nerve axon. We demonstrate a technique for deriving candidate solutions for the McKean nonlinearity and present and apply solvability conditions necessary for existence. Our equation contains both spatially continuous and discrete diffusion terms.
Reinforcement Learning: a Biological Perspective the Three Basic Components of Reinforcement Learning

Reinforcement learning is an approach to learning problems that takes account of the interaction of the learner with their reactive environment. Despite its early connections to animal learning, reinforcement learning has been an active field of study in engineering and computer science. New research is now starting to connect reinforcement learning to identifiable biological systems. These connections may well provide direct insights into goal-directed learning and decision-making in biological organisms. INTRODUCTION Brain research during the last 50 years has focused on the metaphor of learning through interactions with an environment. The central idea here is interaction. All mobile creatures, including humans, are embedded in a rich, reactive environment. We move our eyes ± the visual scene changes. We push against a tree branch ± we feel its roughness, and it even pushes back. We shift our attention ± suddenly a sight or sound becomes clearer and easier to interpret. Even our bodies act as part of the reactive environment, as mere consideration of an action can cause a change in an animal's physiological state whether or not it actually moves. The learning mechanisms that are embedded in our nervous systems have evolved to deal with just such reactive aspects of environments. Reinforcement learning takes account of the idea that learners are situated in real-world settings which react to and may even adapt to the actions of the learner. In the words of modern reinforcement learning pioneers Sutton and BartòRein-forcement learning is learning what to do ± how to map situations to actions ± so as to maximize a numerical reward signal. ' In this framework, learning is specified as a complete problem of an agent interacting with an environment. Thus the properties of the agent and the environment and the dynamics of interaction must be specified in a reinforcement learning problem. As a class of problems, reinforcement learning problems are most closely related to mathematical problems of optimal control. One of the most important ideas that is built into all reinforcement learning systems is the concept of a goal-seeking agent. In reinforcement learning, the learner possesses goals that influence their selection of actions, the way they update their memory, and so on. From a biological perspective, the critical issue is to determine the physical mechanisms that define and control the goals and actions of the learner. In this article we shall outline one computational approach to reinforcement learning and its biological …
Performance Model for Inter- Chip Busses Considering Bandwidth and Cost

We present an analytical method to perform the design of the I/O subsystem of an IC given its throughput requirements. Our method can be used to select the IC package, along with the bus size and speed so as to minimize I/O cost. We have validated our model by conducting simulations on three industry-standard packages while varying the bus width, slew rate, and signal-to-power/ground ratio. Our experimental results track closely with the analytical model. We demonstrate for the packages considered that it is more cost effective to use faster, narrower busses rather than slower wider busses to achieve a desired system throughput. Author(s) Biography Brock J. LaMeres received his BSEE from Montana State University in 1998 and his MSEE from the University of Colorado in 2001. He is currently a Ph.D. candidate at the University of Colorado where his research focus is VLSI Circuit Design and High-Speed I/O for next generation IC’s. For the past 6 years he has worked as a hardware design engineer for Agilent Technologies in Colorado Springs where he designs logic analyzer probes and acquisition boards. LaMeres has published 25 technical articles in the area of signal integrity and has a patent in the field of logic analyzer probing. LaMeres is a registered Professional Engineer in the State of Colorado. Sunil P. Khatri is an Assistant Professor in the Department of Electrical Engineering at Texas A&M University. He is affiliated with the VLSI CAD group. He completed his Ph.D. from the University of California, Berkeley in 1999. Before this, he worked with Motorola, Inc on the designs of the MC88110 and PowerPC 603 RISC Microprocessors. Khatri obtained his M.S from the University of Texas at Austin, which followed his B.Tech. from the Indian Institute of Technology, Kanpur. His research is in the areas of VLSI Design and VLSI CAD. Some recent areas of interest are design automation for datapath circuits, cross-talk avoidance in on-chip buses, leakage-power reduction, extreme low power circuit design, asynchronous circuit design methodologies, timing estimation, efficient test generation, fast logic simulation and cross-talk immune VLSI design.
Stain-Free Quantification of Chromosomes in Live Cells Using Regularized Tomographic Phase Microscopy

Refractive index imaging is a label-free technique that enables long-term monitoring of the internal structures and molecular composition in living cells with minimal perturbation. Existing tomographic methods for the refractive index imaging lack 3-D resolution and result in artifacts that prevent accurate refractive index quantification. To overcome these limitations without compromising the capability to observe a sample in its most native condition, we have developed a regularized tomographic phase microscope (RTPM) enabling accurate refractive index imaging of organelles inside intact cells. With the enhanced accuracy, we quantify the mass of chromosomes in intact living cells, and differentiate two human colon cancer lines, HT-29 and T84 cells, solely based on the non-aqueous (dry) mass of chromosomes. In addition, we demonstrate chromosomal imaging using a dual-wavelength RTPM, which shows its potential to determine the molecular composition of cellular organelles in live cells.
Computer Vision and Image Understanding Incremental Learning of Human Activity Models from Videos

Learning human activity models from streaming videos should be a continuous process as new activities arrive over time. However, recent approaches for human activity recognition are usually batch methods, which assume that all the training instances are labeled and present in advance. Among such methods, the exploitation of the interrelationship between the various objects in the scene (termed as context) has proved extremely promising. Many state-of-the-art approaches learn human activity models continuously but do not exploit the contextual information. In this paper, we propose a novel framework that continuously learns both of the appearance and the context models of complex human activities from streaming videos. We automatically construct a conditional random field (CRF) graphical model to encode the mutual contextual information among the activities and the related object attributes. In order to reduce the amount of manual labeling of the incoming instances, we exploit active learning to select the most informative training instances with respect to both of the appearance and the context models to incrementally update these models. Rigorous experiments on four challenging datasets demonstrate that our framework outperforms state-of-the-art approaches with significantly less amount of manually labeled data.
Eager Comprehensions in Scheme The design of SRFI 42

This article is about a certain style of programming iterati ve programs. It is based on a concept we have named “eager comprehension,” which is a convenient and efficient alternative to tail recursion, do-loops, and lazy list comprehensions (aka “ZF expressions”). Eager comprehensions are syntactic forms that encapsulate the details of an accumulation process (counting elements, creating a list, etc.). Within these forms, expressions called gener ators hide the details of enumerating basic sequences (running through a list, through a range of integers, etc.). By combining these elements in a clearly structured and well-defined way, a concise and powe rful notation for writing loops emerges. Of course, this style of programming is not new—it is implicitly present in any form of loop-macro already—and so we discuss several concrete designs that aim for the same goal. Surprisingly, however, none of these designs has had much impact on Scheme, despite the fact that their common floor plan has been around f or decades. A particularly clean new design, SRFI 42, on the other hand has already made some friends in the first few years of its existence. Explaining the design and implementation of SRFI 42 constitutes the main part of this article.
Health Characteristics of Solo Grandparent Caregivers and Single Parents: A Comparative Profile Using the Behavior Risk Factor Surveillance Survey

Objectives. To describe the health characteristics of solo grandparents raising grandchildren compared with single parents. Methods. Using the 2012 Behavioral Risk Factor Surveillance System, respondents identified as a single grandparent raising a grandchild were categorized as a solo grandparent; grandparent responses were compared with single parents. Descriptive analysis compared health characteristics of 925 solo grandparents with 7,786 single parents. Results. Compared to single parents, grandparents have a higher prevalence of physical health problems (e.g., arthritis). Both parent groups have a high prevalence of lifetime depression. A larger share of grandparents actively smoke and did no recreational physical exercise in the last month. However, grandparents appear to have better access to health services in comparison with single parents. Conclusion. Solo grandparents may be at risk for diminished physical capacity and heightened prevalence of depression. Health professionals can be an important resource to increase grandparents' physical and emotional capacities.
Baseline Combination for InSAR DEM Altimetric Resolution Enhancement

Combination of several interferograms of a same area, each having its own ambiguity of altitude, allows producing a combined interferogram with either a better signal to noise ratio or a lower ambiguity of altitude, unreachable from a single interferometric pair. InSAR baseline combination by summation of interferograms allows reaching peculiar equivalent baselines while increasing signal to noise ratio in the resulting interferogram. Despite this drawback such combination revealed to be highly useful in atmospheric artifacts identification and localization. Choosing adequately the interferograms to combine allow to generate interferograms with very short baseline in which the topographic phase component can be neglected, revealing artifacts before going further in a then useless processing. Baseline combination by averaging can only be applied on unwrapped phases. Therefore, each interferogram must be unwrapped prior to combination. We thus implemented a three step phase unwrapping procedure allowing to take fully advantage of an interferometric data set containing several InSAR pairs of a given site. Phase averaging allows to lower substantially the phase standard deviation and thus to increase the altitude accuracy. Baseline combination process was developed in the frame of an ESA DUP project [1] and of a TELSAT IV project [2].
Review of microscopic and macroscopic routing algorithms in Opportunistic Networks

Opportunistic networks are highlighted with long latency and unstable network topology. It is a unique wireless network architecture which enables the mobile nodes to have communication with each other in environment where there is no continuous route between source and destination. In this network scenario there is no continuous routing path exist between source and destination. Using intermediate nodes information is conveyed to the destination. These networks espouse capture - move-forward behavior arising from the mobility of the mobile nodes for message relying. In this article we explicate about the challenges of the opportunistic networks, classification of routing protocols, also confer about the metrics required for the performance measurement of routing algorithms. For the message transfer, routing requires information about the neighborhood nodes. Based on routing behavior, we classify routing protocols as social zero information schemes and social aware information schemes. Social aware information schemes are further classified into microscopic schemes and macroscopic schemes depending upon content of the information. In this paper we discuss some of recent microscopic and macroscopic routing protocols and also confer the comparison among the reviewed algorithms.
The Cloud Personal Assistant for Providing Services to Mobile Clients

This paper introduces the original concept of a cloud personal assistant, a cloud service that manages the access of mobile clients to cloud services. The cloud personal assistant works in the cloud on behalf of its owner: it discovers services, invokes them, stores the results and history, and delivers the results to the mobile user immediately or when the user requests them. Preliminary experimental results that demonstrate the concept are included.
Who borrows among the poor ? MC use determinants in Guatemala , with particular reference to social ties January 14 , 2009

【Keywords】Micro Credit (MC), social ties, information asymmetry, creditworthiness, Guatemala, 【JEL code】C25, D14, Q14 【Abstract】Who borrows Micro Credit (MC) is the information needed to improve not only MC programs but also policies of poverty alleviation. This paper analyzes the MC use determinants taking social ties into account using data in Guatemalan Living Standard Measurement Study. It shows that the determinants are relatively different between the poor and the non-poor. It also shows that social ties could raise the possibility of MC utilization especially among the poor, which would verify the function of social ties as collateral of creditworthiness. Those excluded from MC may not be the poorest but the socially weakest.
Coccidioidomycosis as a Common Cause of Community-acquired Pneumonia

The early manifestations of coccidioidomycosis (valley fever) are similar to those of other causes of community-acquired pneumonia (CAP). Without specific etiologic testing, the true frequency of valley fever may be underestimated by public health statistics. Therefore, we conducted a prospective observational study of adults with recent onset of a lower respiratory tract syndrome. Valley fever was serologically confirmed in 16 (29%) of 55 persons (95% confidence interval 16%–44%). Antimicrobial medications were used in 81% of persons with valley fever. Symptomatic differences at the time of enrollment had insufficient predictive value for valley fever to guide clinicians without specific laboratory tests. Thus, valley fever is a common cause of CAP after exposure in a disease-endemic region. If CAP develops in persons who travel or reside in Coccidioides-endemic regions, diagnostic evaluation should routinely include laboratory evaluation for this organism.
High site fidelity, strong associations, and long-term bonds: Short-finned pilot whales off the island of Hawai‘i

Studies of short-finned pilot whales suggest they travel in stable mixed-sex groups composed of strongly associated individuals; however, temporal analyses of social structure are lacking. To examine site fidelity, association patterns, and temporal relationships, we analyzed data from 267 encounters of this species off the island of Hawai‘i from 2003 through 2007, identifying 448 distinctive individuals (68.1% seen more than once). About 72% of the whales were linked by association into a single social network, suggesting the possibility of multiple populations using the area. Sighting histories suggested that only some individuals exhibit high site fidelity. Individuals demonstrated preferential associations and community division was strongly supported by average-linkage hierarchical cluster analysis of the association data. Nine longitudinally stable social units composed of key individuals and their constant companions were identified. Qualitative assignment of age and sex classes of unit members indicated that some segregation between adult males and female/ calf pairs may occur. Temporal analyses of individuals encountered on the same day indicate stable long-term associations. Differential patterns of residency and site fidelity were unexpected and may be indicative of multiple populations around the main Hawaiian Islands. The presence of a resident population demonstrating strong, long-term site fidelity and associations off Hawai‘i Island may warrant special management considerations.
The Emergence of Dynamic Capabilities from a SME-Enterprise System Upgrade

Since the past decade, many studies have attempted to examine the Enterprise Systems (ES) implementations in multinational corporations (MNCs). However, there is a paucity of such research which focuses on ES implementation and upgrade for small and medium enterprises (SMEs). With respect to that, the upgrade of Sage ACCPAC system at Chio Lim Stone Forest (CLSF), the best performing Singapore-based SME accounting firm, provides us with a rich fertile ground to examine the mechanisms of achieving success in an ES system upgrade. Combining two theoretical lenses, the ES Experience Cycle and the Capability Development theory, a total of eight key actions that had developed into six key capabilities were identified from the one-year case study. Two theoretical contributions and four practical contributions were shared and documented in this paper.
Are There Differences between Fee and Non-Fee Cases?

IT 1s MORE THAN fifteen years since casework agencies began the practice of charging a fee for their service. A brief review of the literature during these years recalls the inner struggles of the profession in accepting the concept of payment for casework services. It recalls the developing conviction that this is a service worthy "of its hire. " Finally, it recalls the increasing attention devoted to how best to administer this innovation, recognized at last as a legitimate concomitant of communitysponsored casework.1 The initial philosophical reservations of the field were adequately handled because of the conviction that fee-charging would enable more people to use casework agencies. The concept of the sliding scale came into being; Ruth Fizdale's suggested "new look" is aimed at precisely this concept. The literature also demonstrated the concern that the practice of fee-charging should be a useful on~ for the client and a valid, therapeutic part of the service.2 The task of making it so has been approached in the literature by the functional as well as the diagnostic school of thought. Social science, albeit of a homespun variety, has also helped-the argument being
Optimizing Data Warehousing Strategies

Database technologies have evolved over the last two decades into different constructs to support the ever-growing information needs for organizations spanning the spectrum of operational and analytical processing. This paper examines the characteristics of transactional databases, operational data stores, data warehouses and virtual data warehouses. A framework is developed for an optimal data warehousing strategy based on organizational needs classified by the types of business processes defined by the requirements of supporting functional areas and the levels of decision structures. Enterprise architecture is described to provide an integrated and complementary view of various data warehousing constructs.
, Markov 2002 ; Kennings , Markov 2006 ; Kennings , Vorwerk Circuit Placement

Circuit Placement Name: Andrew A. Kennings1, Igor I. Markov2 Affil. /Addr. 1: Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada Affil. /Addr. 2: Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA