Miracle-dz/UniFAR-FTUs huggingface dataset:
Zero Intelligence Plus and Gjerstad-Dickhaut Agents for Sealed Bid Auctions

The increasing prevalence of auctions as a method of conducting a variety of transactions has promoted interest in modelling bidding behaviours with simulated agent models. The majority of popular research has focused on double auctions, i.e. auctions with multiple buyers and sellers. In this paper we investigate agent models of sealed bid auctions, i.e. single seller auctions where each buyer submits a single bid. We propose an adaptation of two learning mechanisms used in double auctions, Zero Intelligence Plus (ZIP) and Gjerstad-Dickhaut (GD), for sealed bid auctions. The experimental results determine if a single agent adopting ZIP & GD bidding mechanisms is able to learn the known optimal strategy through experience. We experiment with two types of sealed bid auctions, first price sealed bid and second price sealed bid. Quantitive analysis shows that whilst ZIP agents learn a good strategy they do not learn the optimal strategy, whereas GD agents learn an optimal strategy in first price auctions.
A Method to Develop Description Logic Ontologies Iteratively with Automatic Requirement Traceability

Competency Questions (CQs) play an important role in the ontology development life-cycle, as they represent the ontology requirements. Although the main methodologies use them, there is room for improvement in the current practice of ontology engineering. One of the main problems is the lack of tools to check if CQs defined in OWL, are being fulfilled by an ontology, preferably in an automated way. Moreover, requirement (or CQ) traceability is rarely explored. Recently, there has been a trend on checking CQs against ontologies using RDF and SPARQL. Naturally, this language, being created for Semantic Networks, is inadequate to check the fulfillment of OWL CQs. In this paper, we introduce a semi-automatic, full-fledged method to develop ontologies iteratively, using CQs as requirements. It presents many novelties: a tracker to monitor the relations among CQs and the OWL code; an NLP component that translates CQs in natural language into OWL queries; a logic checker that confirms whether CQs are satisfied or not; a generator of new CQs, which comes into play when the CQ being dealt is not satisfied yet; and an axiom generator that suggests to the user new axioms to be included in the ontology.
The Failure to Examine Failures in Democratic Innovation

While empirical research on democratic innovations is characterised by steady growth in output, a study of the top journals in political science shows that in the last ten years the vast majority of these empirical studies focused on best practices. Empirical evaluation of the lessons that we can draw from failures in participatory and deliberative processes are extremely rare. This pattern of success and failure is not representative of reality. Various specialized monographs and studies in less prominent journals have investigated a variety of problems and failures. Why do we see this pattern of ‘failure neglect’ in top journals? In this paper we explore some of the causes of this pattern elucidating the impact of sampling bias, innovation bias, publication bias, and the loss of independence due to the difficulty of implementing participatory action research in politically contested projects. We argue that this lack of representativeness in the real-world cases of deliberation that command the attention of general political science audiences is currently a major barrier to understanding democratic improvements. Without a comparison of success and failure, our models for successful outcomes will be chronically overdetermined, which ultimately reduces their chances of adoption in practice.
Probabilistic Online Action Prediction

People display regularities in almost everything they do. This paper proposes characteristics of an idealized algorithm that would allow a user interface to adapt to an individual’s pattern of use. We describe a simple predictive method with these characteristics and show its predictive accuracy on a large dataset of UNIX commands to be better than others that have been considered, while using fewer computational and memory resources.
Optimal event sequence sanitization

Frequent event mining is a fundamental task to extract insight from an event sequence (long sequence of events that are associated with time points). However, it may expose sensitive events that leak confidential business knowledge or lead to intrusive inferences about groups of individuals. In this work, we aim to prevent this threat, by deleting occurrences of sensitive events, while preserving the utility of the event sequence. To quantify utility, we propose a model that captures changes, caused by deletion, to the probability distribution of events across the sequence. Based on the model, we define the problem of sanitizing an event sequence as an optimization problem. Solving the problem is important to preserve the output of many mining tasks, including frequent pattern mining and sequence segmentation. However, this is also challenging, due to the exponential number of ways to apply deletion to the sequence. To optimally solve the problem when there is one sensitive event, we develop an efficient algorithm based on dynamic programming. The algorithm also forms the basis of a simple, iterative method that optimally sanitizes an event sequence, when there are multiple sensitive events. Experiments on real and synthetic datasets show the effectiveness and efficiency of our method.
User feedback in human-robot interaction: prosody, gaze and timing

This paper investigates forms and functions of user feedback in a map task dialogue between a human and a robot, where the robot is the instruction-giver and the human is the instruction- follower. First, we investigate how user acknowledgements in task-oriented dialogue signal whether an activity is about to be initiated or has been completed. The parameters analysed include the users' lexical and prosodic realisation as well as gaze direction and response timing. Second, we investigate the relation between these parameters and the perception of uncertainty.
Do interactive learning spaces increase student achievement? A comparison of classroom context

Research on interactive learning space classrooms has reported that instructors and students find them engaging, and engagement is expected to increase learning outcomes. Positive findings about interactive classrooms, though, are often confounded with active learning pedagogy since instructors who teach in interactive classrooms tend to also promote active learning pedagogy. More research is needed to tease apart learning gains from the instructional design, classroom context, and the related incorporation of technology. This study examined the relationship between learning gains and classroom context (traditional and interactive learning space) in a pretest/posttest design and reviewed student survey responses about learning experiences. Participants were enrolled in one of two sections of a course. Both groups were taught by the same instructor using active learning pedagogy with the same activities, materials, and assignments. The results showed that classroom context did not result in differences in students learning overall. Some findings pointing to subtle differences, however, indicate that the interactive classroom could have made the classroom instruction more effective and efficient.
Differences in HIV Natural History among African and Non-African Seroconverters in Europe and Seroconverters in Sub-Saharan Africa

Introduction It is unknown whether HIV treatment guidelines, based on resource-rich country cohorts, are applicable to African populations. Methods We estimated CD4 cell loss in ART-naïve, AIDS-free individuals using mixed models allowing for random intercept and slope, and time from seroconversion to clinical AIDS, death and antiretroviral therapy (ART) initiation by survival methods. Using CASCADE data from 20 European and 3 sub-Saharan African (SSA) cohorts of heterosexually-infected individuals, aged ≥15 years, infected ≥2000, we compared estimates between non-African Europeans, Africans in Europe, and Africans in SSA. Results Of 1,959 (913 non-Africans, 302 Europeans - African origin, 744 SSA), two-thirds were female; median age at seroconversion was 31 years. Individuals in SSA progressed faster to clinical AIDS but not to death or non-TB AIDS. They also initiated ART later than Europeans and at lower CD4 cell counts. In adjusted models, Africans (especially from Europe) had lower CD4 counts at seroconversion and slower CD4 decline than non-African Europeans. Median (95% CI) CD4 count at seroconversion for a 15–29 year old woman was 607 (588–627) (non-African European), 469 (442–497) (European - African origin) and 570 (551–589) (SSA) cells/µL with respective CD4 decline during the first 4 years of 259 (228–289), 155 (110–200), and 199 (174–224) cells/µL (p<0.01). Discussion Despite differences in CD4 cell count evolution, death and non-TB AIDS rates were similar across study groups. It is therefore prudent to apply current ART guidelines from resource-rich countries to African populations.
Performance of Medium Access Control Protocols for Full-Duplex Wireless LANs

In this paper, we propose a medium access control (MAC) protocol for improving throughput in full-duplex WLANs. The proposed MAC protocol introduces a dynamic contention window (CW) control at access point (AP) to increase the opportunity for full- duplex operations. In the proposed MAC protocol, a threshold is set in the transmission queue length in APs. Small and large CWs are used adaptively. When the transmission queue length of an AP exceeds the threshold, the small CW is used for backoff time calculation, which prioritizes the AP's transmission opportunity. On the other hand, when the transmission queue length of an AP does not exceed the threshold, the large CW is used for backoff time calculation, which prioritizes client nodes. To the best of our knowledge, this is the first work to consider the contention window control for increasing the opportunity of full-duplex operation. From some simulated results, we show that the proposed MAC protocol is effective to improve throughput in full- duplex WLANs thanks to the adaptive control of contention window at AP.
Behavioral responses of newly hatched zebrafish (Danio rerio) to amino acid chemostimulants.

The zebrafish chemosensory systems of olfaction, taste and solitary chemosensory cells (SCCs) are established during the first week after fertilization (a.f.). These systems presumably support the early development of feeding behaviors required as yolk supplies diminish over the same period. Yet there is no previous data reporting early chemosensory responses in zebrafish. We therefore assayed the chemosensory behavior of newly hatched zebrafish on days 3, 4 and 5 a.f. Responses were compared between fish exposed to water alone versus water containing a mixture of 12 amino acids (100 microM each) flowing through a 50 ml test chamber at 4 ml/min; computer-assisted motion analysis was used to quantify responses. Behavioral responses were first observed at day 4 a.f. ; the number of fish swimming, their swimming speeds, and their net-to-gross displacement (NGDR) all increased significantly in response to amino acid stimulation. Because taste buds first appear 4-5 days a.f. and the SCCs may not respond to amino acids, these initial chemosensory responses of day 4 fish may be mediated by already established olfactory neurons. The onset of chemosensitivity in day 4 fish corresponded with an easily recognizable developmental phenotype of inactive floating; day 3 fish were inactive and resting on the bottom while day 5 fish were active and moving through the water column. The ease of identifying responsive day 4 fish suggests these animals may be useful for characterizing odorant sensitivity or developmental plasticity or for screening for chemosensory mutations.
Politics of presence: women’s safety and respectability at night in Mumbai, India

Abstract This article focuses on women’s mobility in urban public space in Mumbai, India while working night shifts in outsourced call centres. The outsourced call centre industry is heralded as the beacon of modernity, and its entry was facilitated under a neoliberal political economy. This industry disproportionately employs women relative to India’s broader Information Technology sector, resulting in high numbers of women commuting at night. The state has reworked safety-centred policies for women working night shifts in call centres, which have been differentially implemented by companies. Expanding on this variegation, I sketch out the nightscape of transportation and mobility around outsourced call centres. This article analyses how women conceive of safety, as well as its interplay with convenience and considerations of respectability while making decisions about navigating urban public space at night. Women working in call centres find themselves in the crosshairs of narratives that demonize them as ‘bad women’ for being out on the street at night, while working in industries that specifically seek women willing to work in night shifts. Their navigation of this paradox exposes contradictions within the neoliberal modernization of Mumbai and the meaning of public safety for women who make this modernization possible through their labour.
Bulk universality for Wigner matrices

We consider N × N Hermitian Wigner random matrices H where the probability density for each matrix element is given by the density ν(x) = e−U(x). We prove that the eigenvalue statistics in the bulk are given by the Dyson sine kernel provided that U ∈ C6( \input amssym $\Bbb R$) with at most polynomially growing derivatives and ν(x) ≥ Ce−C|x| for x large. The proof is based upon an approximate time reversal of the Dyson Brownian motion combined with the convergence of the eigenvalue density to the Wigner semicircle law on short scales. © 2010 Wiley Periodicals, Inc.
An autonomous control and monitoring system for lower limb orthosis: the gait project case

A wearable control and monitoring system has been developed for a novel active orthotic device. The development addresses the need of an autonomous tool for gait analysis during normal use of the orthotic device. The system has two basic components: the base unit and the ambulatory Uniu. The units communicate by means of a Bluetooth link. In order to test the system, a knee-ankle-foot orthosis has been instrumented for gait control and monitoring of biomechanical and comfort data during daily use by patients with muscular deficiencies. This paper describes the system developed, outlines its performance and presents measurements recorded while performing different activities.
ExcUseMe: Asking Users to Help in Item Cold-Start Recommendations

The item cold-start problem is of a great importance in collaborative filtering (CF) recommendation systems. It arises when new items are added to the inventory and the system cannot model them properly since it relies solely on historical users' interactions (e.g., ratings). Much work has been devoted to mitigate this problem mostly by employing hybrid approaches that combine content-based recommendation techniques or by devoting a portion of the user traffic for exploration to gather interactions from random users. We focus on pure CF recommender systems (i.e., without content or context information) in a realistic online setting, where random exploration is inefficient and smart exploration that carefully selects users is crucial due to the huge flux of new items with short lifespan. We further assume that users arrive randomly one after the other and that the system has to immediately decide whether the arriving user will participate in the exploration of the new items. For this setting we present ExcUseMe, a smart exploration algorithm that selects a predefined number of users for exploring new items. ExcUseMe gradually excavates the users that are more likely to be interested in the new items and models the new items based on the users' interactions. We evaluated ExcUseMe on several datasets and scenarios and compared it to state-of-the-art algorithms. Experimental results indicate that ExcUseMe is an efficient algorithm that outperforms all other algorithms in all tested scenarios.
Scheduling unrelated machines with costs

David B. Shmoys* We consider the problem of scheduling unrelated parallel machines with costs. Each job is to be processed by exactly one machine; processing job j on machine i requires time pi, and incurs a cost of cij. There are two optimization criteria: minimizing the makespan of the schedule, i.e., the maximum job completion time; and minimizing the total cost. Our main result is as follows. There is a polynomialtime algorithm that, given values C and T, finds a schedule of cost at most C and makespan at most 2T, if there exists a schedule of cost C and makespan T. We also extend this result to a variant of the problem where, instead of a fixed processing time p;j, there is a range of possible processing times for each machine-job pair, and the cost linearly increases as the processing time decreases. Finally, we show that these results imply a polynomial-time 2approximation algorithm to minimize a weighted sum of the cost and the makespan.
Incremental maintenance of horizontal view using PIVOT operation and differential files in relational DBMSs

To analyze multidimensional data conveniently and efficiently, OLAP(online analytical processing) systems are widely using views with horizontal form to represent measurement values over multiple dimensions, while conventional RDBMSs usually manage tables with vertical form. In this paper, we propose an incremental maintenance of these horizontal views which updates efficiently them according to the changes of base source tables. We first propose an overall framework processing queries over horizontal views transformed from source tables with vertical form. In order to execute this view maintenance process efficiently, we keep every changes of source tables into differential files then we modify the horizontal views with the differential files. Because differential files have vertical forms, their tuples are converted to horizontal forms which are identical to horizontal views then they are applied to the maintenance of these views. Experimental results show that the proposed method is more effective than existing methods.
Multiple Regression Analysis of the Variable Component in the Near-Infrared Region for Type 1 AGN MCG +08-11-011

We propose a new method of analyzing a variable component for type 1 active galactic nuclei (AGNs) in the near-infrared wavelength region. This analysis uses a multiple regression technique and divides the variable component into two components originating in the accretion disk at the center of an AGN and from the dust torus that far surrounds the disk. Applying this analysis to the long-term VHK monitoring data of MCG +08-11-011 that were obtained by the MAGNUM project, we found that the (H - K) color temperature of the dust component is T = 1635 ± 20 K, which agrees with the sublimation temperature of dust grains, and that the time delay of K to H variations is Δt ≈ 6 days, which indicates the existence of a radial temperature gradient in the dust torus. As for the disk component, we found that the power-law spectrum of fν ∝ να in the V to near-infrared HK bands varies with a fixed index of α ≈ -0.1 to +0.4, which is broadly consistent with the irradiated standard disk model. The outer part of the disk therefore extends out to a radial distance where the temperature decreases to radiate the light in the near-infrared.
Are unadjusted analyses of clinical trials inappropriately biased toward the null?

See related article, pages 888–894. One of the delights of clinical practice has proven to be a major nuisance for clinical research: patients are nonidentical. Indeed, patients have multiple characteristics that influence the likelihood of the outcome of a disease, which can make it difficult in the extreme to accurately discern the effects of therapy from casual clinical experience or even careful observational studies. Randomization, a process by which patients are assigned to a treatment arm by chance rather than by choice, was a brilliant innovation that has made possible causal inferences regarding a treatment’s effect. Although randomization is not perfect in practice, it is remarkably effective at ensuring the comparability between treatment groups, so much so that it has almost tricked us into thinking that patient differences in outcome risks have been rendered irrelevant in the context of clinical trials. However, randomization only ensures similarity of the outcome risks between treatment groups; it does nothing to mitigate the between-patient differences in outcome risks within treatment groups. These differences can lead to clinically important differences in treatment effects across patients such that the summary results of a trial may not apply to all, or even most, patients in the trial.1,2 Heterogeneity of risk can create an even more fundamental, and even less appreciated, problem with the summary results of clinical trials: Even in the absence of any heterogeneity of treatment effect (ie, when all patients get an identical treatment benefit), and in the absence of confounding and bias, risk heterogeneity can still play a very mischievous role such that an unadjusted (crude) analysis may be both inefficient and yield an inaccurate estimate of the summary treatment effect. In this issue of Stroke , Gray et al perform one of the more comprehensive analyses of the effects of risk …
Monitoring Distributed Streams using Convex Decompositions

Emerging large-scale monitoring applications rely on continuous tracking of complex data-analysis queries over collections of massive, physically-distributed data streams. Thus, in addition to the space- and time-efficiency requirements of conventional stream processing (at each remote monitor site), effective solutions also need to guarantee communication efficiency (over the underlying communication network). The complexity of the monitored query adds to the difficulty of the problem --- this is especially true for non-linear queries (e.g., joins), where no obvious solutions exist for distributing the monitored condition across sites. The recently proposed geometric method, based on the notion of covering spheres, offers a generic methodology for splitting an arbitrary (non-linear) global condition into a collection of local site constraints, and has been applied to massive distributed stream-monitoring tasks, achieving state-of-the-art performance. In this paper, we present a far more general geometric approach, based on the convex decomposition of an appropriate subset of the domain of the monitoring query, and formally prove that it is always guaranteed to perform at least as good as the covering spheres method. We analyze our approach and demonstrate its effectiveness for the important case of sketch-based approximate tracking for norm, range-aggregate, and join-aggregate queries, which have numerous applications in streaming data analysis. Experimental results on real-life data streams verify the superiority of our approach in practical settings, showing that it substantially outperforms the covering spheres method.