Miracle-dz/UniFAR-FTUs huggingface dataset:
Online Submodular Maximization under a Matroid Constraint with Application to Learning Assignments

Which ads should we display in sponsored search in order to maximize our revenue? How should we dynamically rank information sources to maximize the value of the ranking? These applications exhibit strong diminishing returns: Redundancy decreases the marginal utility of each ad or information source. We show that these and other problems can be formalized as repeatedly selecting an assignment of items to positions to maximize a sequence of monotone submodular functions that arrive one by one. We present an efficient algorithm for this general problem and analyze it in the no-regret model. Our algorithm possesses strong theoretical guarantees, such as a performance ratio that converges to the optimal constant of 1 1=e. We empirically evaluate our algorithm on two real-world online optimization problems on the web: ad allocation with submodular utilities, and dynamically ranking blogs to detect information cascades. Finally, we present a second algorithm that handles the more general case in which the feasible sets are given by a matroid constraint, while still maintaining a 1 1=e asymptotic performance ratio.
THE THEORY OF ATOM LASERS

We review the current theory of atom lasers. A tutorial treatment of second quantisation and the Gross-Pitaevskii equation is presented, and basic concepts of coherence are outlined. The generic types of atom laser models are surveyed and illustrated by specific examples. We conclude with detailed treatments of the mechanisms of gain and output coupling.
Can Public Employment Schemes Increase Equilibrium Wages? Evidence from a Natural Experiment in India

We estimate the impact of the Indian government’s major rural public works programme, the National Rural Employment Guarantee (NREG), on agricultural wages. The rollout of NREG in three phases is used to identify difference-in-difference estimates of the programme effect. Using monthly wage data from the period 2000-2011 for a panel of 209 districts across 18 Indian states, we find that on average NREG boosts the growth rate of real daily agricultural wages 4.8 per cent per year. The effect is concentrated in some states and in the agricultural season. The effect appears to be gender-neutral and biased towards unskilled labour. We argue that rural public employment programmes constitute a potentially important anti-poverty policy tool.
iTrack: Correlating user activity with system data

Human error has been identified one of the major factors behind system outages and network downtime in a number of previous research papers and surveys. Gartner statistics show that almost 40% of unplanned application downtime is caused due to operator errors such as unintentional changes to network configuration resulting in a network outage, patch installations, service restart, etc. Yet, system admin activities on production IT systems are rarely properly logged and monitored. Existing tools to track user activities either produce too much information without any hints of a potential outage scenario or too little information to be useful in a meaningful way. In this paper, we describe the design and implementation of iTrack - a framework for monitoring user activities and correlating them with system data. iTrack makes use of commonly available native monitoring and diagnostic utilities on operating systems to monitor systems events as well as system admin activity, correlates these two sets of information and categorizes the activity as potentially abnormal or harmful based on its impact on the system in terms of file system, network and process activities. We demonstrate the usefulness of iTrack through several use cases and real world examples such as detecting and diagnosing system outages in real time, conducting post mortem analysis of outages, and maintaining audit logs. Our experimental evaluation of iTrack confirms that its monitoring overhead in terms of CPU time, activity completion time and data generated is within the tolerance range of most production systems. In cases, where the overhead was found to be unacceptable, we detect the underlying cause and provide solutions. These solutions improve performance by up to 20% to 90%, in terms of managed server and iTrack server CPU utilization, respectively and by up to 2 times in terms of completion time of certain system admin activities on the managed server.
Pass Transistor Based Self-Checking Full Adder

—Self-checking designs will gain increasing interest in industrial applications if they satisfy the following requirements: high fault coverage and reduced hardware cost with reduced design effort. The aim of this work is to contribute to reach these requirements for the design of self-checking adders/ALUs. In this paper, we present efficient self-checking implementations for adder schemes using the dual duplication code. Among the known self-checking adder designs, the dual duplicated scheme has the advantage to be totally self-checking for single faults. The drawback of this scheme is that it requires generally the maximum hardware overhead. In this work, we propose a low cost implementation for self-checking adder. The proposed design is based on a novel differential XOR gate implemented in CMOS pass transistor logic, and performed with only four transistors.
Hiding Sound in Image by K-LSB Mutation

In this paper a novel approach to hide sound files in a digital image is proposed and implemented such that it becomes difficult to conclude about the existence of the hidden data inside the image. In this approach, we utilize the rightmost k-LSB of pixels in an image to embed MP3 sound bits into a pixel. The pixels are so chosen that the distortion in image would be minimized due to embedding. This requires comparing all the possible permutations of pixel values, which may would lead to exponential time computation. To speed up this, Cuckoo Search (CS) could be used to find the most optimal solution. The advantage of using proposed CS is that it is easy to implement and is very effective at converging in relatively less iterations/generations.
Supplementary information for "Selective sweeps in growing microbial colonies"

This is supplementary information for arXiv:1204.4896, which also appeared in Physical Biology 9, 026008 (2012). Main text abstract: Evolutionary experiments with microbes are a powerful tool to study mutations and natural selection. These experiments, however, are often limited to the well-mixed environments of a test tube or a chemostat. Since spatial organization can significantly affect evolutionary dynamics, the need is growing for evolutionary experiments in spatially structured environments. The surface of a Petri dish provides such an environment, but a more detailed understanding of microbial growth on Petri dishes is necessary to interpret such experiments. We formulate a simple deterministic reaction-diffusion model, which successfully predicts the spatial patterns created by two competing species during colony expansion. We also derive the shape of these patterns analytically without relying on microscopic details of the model. In particular, we find that the relative fitness of two microbial strains can be estimated from the logarithmic spirals created by selective sweeps. The theory is tested with strains of the budding yeast Saccharomyces cerevisiae, for spatial competitions with different initial conditions and for a range of relative fitnesses. The reaction-diffusion model also connects the microscopic parameters like growth rates and diffusion constants with macroscopic spatial patterns and predicts the relationship between fitness in liquid cultures and on Petri dishes, which we confirmed experimentally. Spatial sector patterns therefore provide an alternative fitness assay to the commonly used liquid culture fitness assays.
Understanding the role of the mentor in developing research competency among undergraduate researchers

Abstract Undergraduate research and creative activities are established high-impact practices that provide students with both advanced knowledge of their academic disciplines and the ability to apply that knowledge to creatively answer questions. At the center of these experiences, is the close relationship between a student researcher and a mentor. Using survey data from 69 recent undergraduate researchers at one university, we investigated the characteristics and impact of these mentor–mentee relationships. We found that active mentoring practices were a significant influence on how competent students perceived themselves as scholars. These practices were more influential than practical aspects of mentoring. Our findings reflect the complicated nature of mentoring in higher education and identify key characteristics of successful mentoring relationships. With greater understanding of this essential component of undergraduate research, we are equipped to make more informed decisions regarding faculty and administrative support for future undergraduate research and creative activities.
Ten-year experience of esophageal endoscopic submucosal dissection of superficial esophageal neoplasms in a single center.

BACKGROUND/AIMS Endoscopic submucosal dissection (ESD) of a superficial esophageal neoplasm (SEN) is a technically difficult procedure. We investigated the clinical outcomes of ESD to determine its feasibility and effectiveness for the treatment of SEN. METHODS Patients who underwent ESD for SEN between August 2005 and June 2014 were eligible for this study. The clinical features of patients and tumors, histopathologic characteristics, adverse events, results of endoscopic resection, and survival were investigated. RESULTS ESD was performed in 225 patients with 261 lesions, including 70 cases (26.8%) of dysplasias and 191 cases (73.2%) of squamous cell carcinomas. The median age was 65 years (range, 44 to 86), and the male to female ratio was 21.5:1. Median tumor size was 37 mm (range, 5 to 85) and median procedure time was 45 minutes (range, 9 to 160). En bloc resection was performed in 245 of 261 lesions (93.9%), with complete resection in 234 lesions (89.7%) and curative resection in 201 lesions (77.0%). Adverse events occurred in 33 cases (12.6%), including bleeding (1.5%), perforation (4.6%), and stricture (6.5%). During a median follow-up period of 35.0 months (interquartile range, 18 to 62), none of the patients showed local recurrence. The 5-year overall and disease-specific survival rates were 89.7% and 100%, respectively. CONCLUSIONS ESD is a feasible and effective procedure for the treatment of SEN based on our 10-year experience, which showed favorable outcomes.
Switching dynamics of multi-agent learning

This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcement learning agents and replicator dynamics in stateless multi-agent games. More precisely, in this work we use a combination of replicator dynamics and switching dynamics to model multi-agent learning automata in multi-state games. This is the first time that the dynamics of problems with more than one state is considered with replicator equations. Previously, it was unclear how the replicator dynamics of stateless games had to be extended to account for multiple states. We use our model to visualize the basin of attraction of the learning agents and the boundaries of switching dynamics at which an agent possibly arrives in a new dynamical system. Our model allows to analyze and predict the behavior of the different learning agents in a wide variety of multi-state problems. In our experiments we illustrate this powerful method in two games with two agents and two states.
Market Power in a Storable-Good Market: Theory and Applications to Carbon and Sulfur Trading

We consider a market for storable pollution permits in which a large agent and a fringe of small agents gradually consume a stock of permits until they reach a long-run emissions limit. The subgame-perfect equilibrium exhibits no market power unless the large agent's share of the initial stock of permits exceeds a critical level. We then apply our theoretical results to a global market for carbon dioxide emissions and the existing US market for sulfur dioxide emissions. We characterize competitive permit allocation profiles for the carbon market and find no evidence of market power in the sulfur market.
Guard Zone Protected Capacity in Multi-Cell MISO Networks under Fading and Shadowing

SUMMARY The exact power distribution of the inter-cell interference is obtained explicitly for cell edge users who are surrounded by circular guard zones. Compared with recent works, the underlying channel model is generalized from Rayleigh fading to a combination of Nakagami fading and Gamma shadowing. In addtion, asymptotic analysis shows that the mean power of intercell interference changes from infinite to finite with a guard zone. Based on this interference distribution, the average capacity at the cell edge is further obtained. Special case approximation indicates that the capacity scales proportionally to the exponential of the guard zone size. Analytical capacities are validated by Monte Carlo simulations.
Striking a new balance between program instrumentation and debugging time

Although they are helpful in many cases, state-of-the-art bug reporting systems may impose excessive overhead on users, leak private information, or provide little help to the developer in locating the problem. In this paper, we explore a new approach to bug reporting that uses partial logging of branches to record the path leading to a bug. We use static and dynamic analysis (both in isolation and in tandem) to identify the branches that need to be logged. When a bug is encountered, the system uses symbolic execution along the partial branch trace to reproduce the problem and find a set of inputs that activate the bug. The partial branch log drastically reduces the number of paths that would otherwise need to be explored by the symbolic execution engine. We study the tradeoff between instrumentation overhead and debugging time using an open-source Web server, the diff utility, and four coreutils programs. Our results show that the instrumentation method that combines static and dynamic analysis strikes the best compromise, as it limits both the overhead of branch logging and the bug reproduction time. We conclude that our techniques represent an important step in improving bug reporting and making symbolic execution more practical for bug reproduction.
Efficient parametric inference for stochastic biological systems with measured variability

Abstract Stochastic systems in biology often exhibit substantial variability within and between cells. This variability, as well as having dramatic functional consequences, provides information about the underlying details of the system’s behavior. It is often desirable to infer properties of the parameters governing such systems given experimental observations of the mean and variance of observed quantities. In some circumstances, analytic forms for the likelihood of these observations allow very efficient inference: we present these forms and demonstrate their usage. When likelihood functions are unavailable or difficult to calculate, we show that an implementation of approximate Bayesian computation (ABC) is a powerful tool for parametric inference in these systems. However, the calculations required to apply ABC to these systems can also be computationally expensive, relying on repeated stochastic simulations. We propose an ABC approach that cheaply eliminates unimportant regions of parameter space, by addressing computationally simple mean behavior before explicitly simulating the more computationally demanding variance behavior. We show that this approach leads to a substantial increase in speed when applied to synthetic and experimental datasets.
Mobility of Bodies in Contact — Part II : How Forces are Generated by Curvature Effects

This paper considers how forces are produced by compliance and surface curvature effects in systems where an object B is kinematically immobilized to second-order by finger bodies A1; ;Ak. A class of configuration-space based elastic deformation models is introduced. Using these elastic deformation models, it is shown that any object which is kinematically immobilized to first or second-order is also dynamically locally asymptotically stable with respect to perturbations. Moreover, it is shown that for preloaded grasps kinematic immobility implies that the stiffness matrix of the grasp is positive definite. The stability result provides physical justification for using second-order effects for purposes of immobilization in practical applications. Simulations illustrate the concepts.
An Alternative Pre-Processing Technique Applied to Power Quality Disturbances Identification

This research presents the development of an alternative pre-processing technique of signals based on the fractal dimension calculation, entropy and signal energy that will be applied to disturbances classification occurring in an electrical power system (EPS). With respect to the power quality disturbances, the voltage sags, voltage swells, oscillatory transients and interruptions were considered for this application. In order to test and validate the proposed technique, a representative database has been obtained through computer simulations of a real EPS using the ATP software. Through windows data and the pre-processing technique proposed, the data were directed to Artificial Neural Network (ANN) architecture to classify the power quality events. The results shown that, combining both the data pre-processing techniques and ANNs, a satisfactory performance of all the proposed methodology can be obtained.
APPLICATIONS OF A NONNEGATIVELY CONSTRAINED ITERATIVE METHOD WITH STATISTICALLY BASED STOPPING RULES TO CT, PET, AND SPECT IMAGING

Abstract. In this paper, we extend a nonnegatively constrained iterat v method and three stopping rules for its iteration to the medical imaging inverse problems of compute d tomography (CT), positron emission tomography (PET), and single photon emission computed tomography (SPECT) ; the iterative method and stopping rules were introduced for the use in astronomical imaging. The paper begi ns with a brief introduction to the CT, PET, and SPECT mathematical and statistical models.
DISPERSION COMPENSATION IN OPTICAL COMMUNICATION LINK USING APF’S

All pass filters (APFs) are used in dispersion compensation which is the foremost requirement in an optical fiber link. All pass filters can correct any order of dispersion by the careful design of multistage all pass filters starting from very simple components with the use of N port devices. Multiple channels, as in wavelength division multiplexed (WDM) system, can be compensated with a single device since these filters are periodic in phase response. In this paper we have designed and implemented these filters to compensate dispersion an some results has shown.
Research of the ForCES Routing Optimization

The research on For CES technology has made a great progress. However current researches on For CES mainly focus on architecture and techniques. In order to ensure For CES architecture network works well, it is significant to take account of performance (such as routing) optimization for For CES architecture. In this paper, we introduced a minimizing sum of path-cost model based on multiple traffic matrices, combined with negative valence ring algorithm, to optimize the traffic at FE sides in For CES architecture. At last, we give the feasibility discussion of the routing optimization for For CES.
Fixed-parameter tractability and logic

We exhibit a close connection between parameterized complexity theory and logic. Our approach is that of descriptive complexity theory. We study the definability of parameterized problems and try to obtain information about the parameterized complexity of the problems through the syntactical structure of the defining sentences. On the one hand, we use this approach to prove that certain problems are fixed-parameter tractable because they can be defined by syntactically simple formulas. On the other hand, we characterize classes of intractable problems by syntactical means.
Being in a process of transition to psychosis, as narrated by adults with psychotic illnesses acutely admitted to hospital

Accessible summary Early intervention to prevent and reduce new episodes of psychosis involves patients, relatives and mental health personnel recognizing the early signs of psychosis. Twelve participants with psychotic illnesses narrated how they experienced becoming psychotic before they were admitted to acute psychiatric wards. The results of this study demonstrate that participants and their close others who sensed, understood and articulated experienced changes as signs of psychosis established a dialogue with mental health personnel and initiated treatment and care. Participants who did not perceive the experienced changes as signs of psychosis articulated the experienced changes as an awareness of a poor health condition and illness. These participants, who had no other people to advocate for them, appeared to experience poor communication and coercion during intervention. Abstract To assist in improving early interventions for psychosis, this study explored how adult people narrated their experience of becoming psychotic, and how contact with mental health personnel was established. Narrative interviews were conducted with 12 participants with psychotic illnesses recruited from acute psychiatric wards. The interviews were content analysed. Participants described being in a process of transition to psychosis as follows: experiencing changes as well-known signs of psychosis, experiencing sudden unexpected changes as signs of psychosis and experiencing unidentified changes as signs of illness. Our results show that participants and their close others who knew the signs of psychosis established a dialogue with mental health personnel and were better equipped to prevent and mitigate the psychosis. Our results demonstrate that participants who did not perceive the signs of psychosis and did not have other people to advocate for them were at risk for delayed treatment, poor communication and coercive interventions. Furthermore, participants who did not know the signs of psychosis perceived these changes as deterioration in their health and awareness of illness. We suggest that participants' experiential knowledge of transitioning to psychosis and an awareness of illness can be used to improve the communication during interventions for psychosis.
Subject-independent natural action recognition

A primitive-based dynamic Bayesian networks are proposed for subject-independent natural action recognition. Inferred by high-level knowledge, primitives are distinctive features that describe the context information and the motion information representing human action as well as pose. Dynamic Bayesian networks could fuse multi-information so that many kinds of weak information could function as strong information for inference. The experimental results show that primitive-based dynamic Bayesian networks not only increase the recognition rate but also improve the robustness.