Miracle-dz/UniFAR-FTUs huggingface dataset:
Shape-stable region boundary extraction via affine morphological scale space (AMSS)

In this paper we present a new approach towards the extraction of affine image regions based on detecting shape-stable boundaries from a multi-scale image representation. We construct an affine morphological scale space (AMSS) representation [1], which performs anisotropic diffusion while preserving boundaries and being invariant to affine transformations. We extract the transition boundaries of the diffusivity velocity map and track their evolution at each level of the scale-space. We then determine the stability of the boundary shape through a minimization process over different scales. Unlike most state of the art detectors which use the Gaussian scale space for multi-scale image representation, our approach is intrinsically affine invariant. We evaluate our detector by measuring repeatability of regions in transformed images of the same scene and comparing it to the state-of-the-art region detectors [2].
Sliding surface design via linear matrix inequalities and Finsler's Lemma

This paper presents a novel sliding surface design for uncertain linear systems. The proposed approach is twofold inspired: on the one hand, it acknowledges the increasing interest of the sliding control community to formulate their problems in terms of linear matrix inequalities since they are efficiently solved via convex optimization techniques; on the other hand, it incorporates recent developments based on Finsler's Lemma for Lyapunov-based design. It is shown that former results are included as particular cases of the new approach. Illustrative examples are provided.
Augmented B Lymphocyte Response to Antigen in the Absence of Antigen-Induced B Lymphocyte Signaling in an IgG-Transgenic Mouse Line

IgG-containing B cell antigen receptor (IgG-BCR), the BCR mostly expressed on memory B cells, contains a distinct signaling function from IgM-BCR or IgD-BCR expressed on naïve B cells. Because naïve B cells transgenic for IgG exhibit augmented response to antigens similar to memory B cells, the distinct signaling function of IgG-BCR appears to play a role in augmented antibody responses of memory B cells. However, how IgG-BCR signaling augments B cell responses is not yet well understood. Here we demonstrate that B cells from IgG-transgenic mice are anergic with defect in generation of BCR signaling upon BCR ligation. However, these IgG-transgenic B cells generate markedly augmented antibody response to a T cell-dependent antigen, probably due to hyper-responsiveness to a T cell-derived signal through CD40. Both BCR signaling defect and augmented response to CD40 ligation are partially restored in xid IgG-transgenic mice in which BCR signaling is down-modulated due to a loss-of-function mutation in the tyrosine kinase Btk crucial for BCR signaling. Thus, IgG-BCR induces augmented B cell responses in the absence of antigen-induced BCR signaling probably through high ligand-independent BCR signaling that may “idle” B cells to make them ready to respond to T cell help. This finding strongly suggests a crucial role of ligand-independent signaling in receptor function.
Bayesian Sparse Factor Models and DAGs Inference and Comparison

In this paper we present a novel approach to learn directed acyclic graphs (DAGs) and factor models within the same framework while also allowing for model comparison between them. For this purpose, we exploit the connection between factor models and DAGs to propose Bayesian hierarchies based on spike and slab priors to promote sparsity, heavy-tailed priors to ensure identifiability and predictive densities to perform the model comparison. We require identifiability to be able to produce variable orderings leading to valid DAGs and sparsity to learn the structures. The effectiveness of our approach is demonstrated through extensive experiments on artificial and biological data showing that our approach outperform a number of state of the art methods.
Covert Operations: Orthographic Recoding as a Basis for Repetition Priming in Word Identification the Problem of Priming Due to Generation

When a word is generated from a semantic cue, coincident orthographic visualization of that word may cause priming on a subsequent perceptual identification test. A task was introduced that required subjects to visualize the orthographic pattern of auditorily presented words. When used at study, this task produced a pattern of priming similar to that produced by a generate study task. When used at test, equal priming on the orthographic task was produced by read and generate study tasks but not by a generate study task that failed to invite orthographic visualization. Priming on perceptually based word identification tests that results from a generate study episode may be largely due to orthographic recoding of the target rather than to conceptual processing. The beneficial effects of prior encoding of a stimulus on subsequent encoding of that stimulus are generally governed by the principles that characterize the transfer-appropriate processing In particular, repetition-priming benefits are most powerful when the processing operations applied during the initial encoding of a stimulus are most similar to those applied when the stimulus is presented on a later occasion. So, for example, completion of visually presented word fragments with target words is more likely if those targets were previously experienced as printed words rather than as auditorily presented words or as drawings of objects corresponding to those words (Rajaram & Roediger, 1993). Another important example of the principles of transfer-appropriate processing is Jacoby's (1983) demonstration that although prior visual exposure to words led to enhanced accuracy on a subsequent masked word identification task, prior generation of those items from their antonyms, in which the target words were not actually seen, produced little or no enhancement. reported similar results using other forms of target generation at study, such as definitional phrases or anagrams , followed by a word-stem or word-fragment completion test or a masked word identification test. Despite the ineffectual contributions of generate encoding tasks to apparently perceptually based word identification tests, these encoding tasks consistently produce reliably better performance on tests that are strongly supported by conceptually driven processing, such as recognition and generation of category members A persistent exception to this coherent pattern of results has been the finding that under a rather wide range of conditions, generation of target words from semantic cues is sufficient to produce as much repetition priming on a subsequent masked word identification test as is produced by an encoding task that …
Object-oriented technology: getting beyond the hype

These days, everyone in the Information Systems (IS) world is talking about object-oriented technology --- known as "OO" to its aficionados. The enthusiasm about OO has even reached the mainstream press (Hammonds, 1991) and executives are hearing success stories about dramatic productivity gains and "programming with lego blocks" (Hammonds, 1991). Within IS, some people are talking about an OO "revolution" that will dramatically change how IS does its work and which has the potential to eliminate or significantly reduce IS staffs.All this hype is putting IS managers under pressure to get on the OO bandwagon. Once again, managers are being asked to make critical decisions about an unproven technology. On the one hand, IS is actively looking for new ways of improving its quality and productivity. On the other hand, managers know from bitter experience the problems and costs of introducing a new technology. This paper attempts to look critically, beyond the hype, at the current state of OO technology to identify the issues managers must face in making decisions about using it in their organizations.In order to explore and assess what IS organizations are doing with OO technology, the authors convened a focus group of senior IS managers from ten leading Canadian firms representing five industry sectors: retailing, manufacturing, banking, communications, and insurance. Group members were asked to speak about their current encounters with OO, the benefits and problems they have experienced to date, and other issues they are dealing with surrounding the introduction of OO technology in their organizations. This paper first gives a brief overview of OO technology and its relationship to other IS technologies. It then evaluates the key benefits and problems organizations can expect in introducing and using OO. Finally, it attempts to answer some key questions about how and when to introduce OO in an organization.
‘Masculine Domination’

This article reprises 1970s discussions of gender inequality in feminist anthropology to critique contemporary assumptions regarding gender construction, advocating a psycho-cultural explanation for the ubiquity of masculine domination. The currency of what I term ‘culturalist empiricism’, in its emphasis on cultural difference, downplays inquiry into human commonalities with respect to gender and entails questionable assumptions regarding how culture operates to construct. Analysis of Chinese patriliny understood as a ‘mode of production of desire’ provides a case in point toward rethinking how cultures can differ with respect to gender construction without abandoning anthropology’s commitment to comprehending human commonalities. The approach is relevant beyond China’s culturally particular context, and it suggests substantial revision of idealist assumptions regarding anthropology’s object — culture.
Repertoires of ADHD in UK newspaper media

This article takes a discursive approach to examine how Attention Deficit Hyperactivity Disorder has been represented and debated in UK newspapers in the last decade. Two repertoires of ADHD were identified as the biological and the psychosocial. Subject positions such as problem child, abnormal or ordinary naughty child and ineffectual or neglectful parents are embedded in these alternative versions of ADHD. The biological repertoire justifies and encourages drug treatment for problem children while the psychosocial repertoire makes available the subject position of ordinary naughty child and supports moral judgements about poor parenting practices in a ‘sick society’. Such representations have challenged the media medicalization of ADHD common in a previous decade. Although the biological and the psychosocial repertoires are competing explanations for ADHD, they both perform a common function in representing families as in need of regulation.
Improved compensation in flow cytometry by multivariable optimization

Conventional compensation of flow cytometry (FMC) data of an N‐stained sample requires additional data sets, of N single‐stained control samples, to estimate the spillover coefficients. Single‐stained controls however are the least rigorous controls because any of the multi‐stained controls are closer to the N‐stained sample. In this article, a new, optimization based, compensation method has been developed that is able to use not only single‐ but also multi‐stained controls to improve estimates of the spillover coefficients. The method is demonstrated on a data set from five‐stained dentritic cells (DCs) with five single‐stained and eight multi‐stained controls. This approach is practical and leads to significant improvements in FCM compensation. © 2011 International Society for Advancement of Cytometry
Self-Control Depletion and Narrative: Testing a Prediction of the TEBOTS Model

This study tests propositions derived from the larger notion that entertainment narratives offer the individual a means by which to alleviate the psychological demands of the self. Specifically, individuals in a state of reduced self-control were expected to experience greater enjoyment, audience response, transportation, and identification during narrative exposure. After a manipulation that depleted self-control resources, participants were exposed to a short story. They then reported their enjoyment and response to the story, as well as their transportation and identification during reading. Results supported the predictions, as enjoyment, audience response, and transportation were significantly greater in the depleted group. Identification showed a nonsignificant difference. Additionally, transportation was found to be a mediator of self-control depletion's effect on enjoyment. Subsequent analyses ruled out alternative mood management and emotion regulation explanations, demonstrating that depleted self-control resources, rather than affect or story valence, accounted for greater narrative engagement.
Stimulation of Endothelin B Receptor Modulates the Inflammatory Activation of Rat Astrocytes

Abstract: Inside the brain tissue, endothelins play numerous important biological roles. One of the targets, astrocytes, predominantly display endothelin receptor subtype B (ETB). On cultured primary rat astroglial cells, we analyzed the effect of IRL 1620, a selective ETB receptor agonist, on the production of nitric oxide (NO) and the synthesis of interleukin (IL)‐6 and tumor necrosis factor (TNF)‐α. We performed these experiments in the presence or absence of interferon‐γ (IFN‐γ) and/or lipopolysaccharide (LPS). IRL 1620 decreases NO production under basal conditions and after IFN‐γ stimulation. However, during LPS‐induced NO production, IRL 1620 enhances this release. The basal IL‐6 secretion and especially the LPS‐induced synthesis are enhanced by the IRL 1620 stimulation. The LPS‐dependent TNF‐α production is increased by the ETB stimulation. The IRL 1620‐induced decrease of basal NO production is not dependent on Ca2+ entry or on phospholipase C (PLC) activation, as shown by the use of LaCl3 and U73122, respectively. In the presence of LPS, the IRL 1620 potentiation of NO production is inhibited by LaCl3 and U73122. The IRL 1620‐induced increase of IL‐6 is dependent on PLC activation. These results suggest that endothelins can have dual effects depending on the costimulatory factors present. Endothelins thus have important immunomodulatory functions in the brain.
MINING CUSTOMER KNOWLEDGE FOR CHANNEL AND PRODUCT SEGMENTATION

Segmentation is particularly challenging in current markets. Hence, companies operating on consumer markets face significant implementation complexities. However, successful implementation of market segmentation is reported problematic, despite being extensively researched and widely acknowledged as a powerful concept in practice. The desired outcome, and the knowledge discovery of market segmentation, is to reap the benefits of competitive advantage. This study takes Computers/Communications/Consumer (3C) products as an example and uses a two-step data mining approach to the cluster analysis and association rules to analyze customer channels and product segmentation. Moreover, we look at what kinds of products and brands customers of different segments prefer and how these preferences differ in relation to varying channel types. Thus, this study finds some 3C product-buying behavior patterns, including customer purchase preferences and customer purchase demands, in order to generate different 3C segmentation marketing alternatives.
Multilevel Selection 4: Modeling the Relationship of Indirect Genetic Effects and Group Size

Indirect genetic effects (IGE) occur when individual trait values depend on genes in others. With IGEs, heritable variance and response to selection depend on the relationship of IGEs and group size. Here I propose a model for this relationship, which can be implemented in standard restricted maximum likelihood software.
Distant Homology Modeling of LCAT and Its Validation through In Silico Targeting and In Vitro and In Vivo Assays

LCAT (lecithin:cholesterol acyltransferase) catalyzes the transacylation of a fatty acid of lecithin to cholesterol, generating a cholesteryl ester and lysolecithin. The knowledge of LCAT atomic structure and the identification of the amino acids relevant in controlling its structure and function are expected to be very helpful to understand the enzyme catalytic mechanism, as involved in HDL cholesterol metabolism. However - after an early report in the late ‘90 s - no recent advance has been made about LCAT three-dimensional structure. In this paper, we propose an LCAT atomistic model, built following the most up-to-date molecular modeling approaches, and exploiting newly solved crystallographic structures. LCAT shows the typical folding of the α/β hydrolase superfamily, and its topology is characterized by a combination of α-helices covering a central 7-strand β-sheet. LCAT presents a Ser/Asp/His catalytic triad with a peculiar geometry, which is shared with such other enzyme classes as lipases, proteases and esterases. Our proposed model was validated through different approaches. We evaluated the impact on LCAT structure of some point mutations close to the enzyme active site (Lys218Asn, Thr274Ala, Thr274Ile) and explained, at a molecular level, their phenotypic effects. Furthermore, we devised some LCAT modulators either designed through a de novo strategy or identified through a virtual high-throughput screening pipeline. The tested compounds were proven to be potent inhibitors of the enzyme activity.
Desktop Context Detection Using Implicit Feedback

The personal information stored on the desktop usually reaches huge dimensions nowadays. Its handling is even more difficult, taking into account complex environments and tasks we work with. An efficient method of identifying the present working context would mean an easier management of the needed resources. In this paper we propose a new way of identifying desktop usage contexts, based upon a distance between documents, which also takes into account their access timestamps. We investigate and compare our technique with traditional term vector clustering, our initial experiments showing promising results with our proposed approach.
We Are What We Post? Self‐Presentation in Personal Web Space

This article examines personal Web sites as a conspicuous form of consumer self-presentation. Using theories of self-presentation, possessions, and computer-mediated environments (CMEs), we investigate the ways in which consumers construct identities by digitally associating themselves with signs, symbols, material objects, and places. Specifically, the issues of interest include why consumers create personal Web sites, what consumers want to communicate, what strategies they devise to achieve their goal of self-presentation, and how those Web space strategies compare to the self-presentation strategies of real life (RL). The data reveal insights into the strategies behind constructing a digital self, projecting a digital likeness, digitally associating as a new form of possession, and reorganizing linear narrative structures.
Supercritical Space-Width Trade-offs for Resolution

We show that there are CNF formulas which can be refuted in resolution in both small space and small width, but for which any small-width proof must have space exceeding by far the linear worst-case upper bound. This significantly strengthens the space-width trade-offs in [Ben-Sasson '09]}, and provides one more example of trade-offs in the "supercritical" regime above worst case recently identified by [Razborov '16]. We obtain our results by using Razborov's new hardness condensation technique and combining it with the space lower bounds in [Ben-Sasson and Nordstrom '08].
Concept extraction and clustering for search result organization and virtual community construction

This study proposes a concept extraction and clustering method, which improves Topic Keyword Clustering by using Log Likelihood Ratio for semantic correlation and Bisection K-Means for document clustering. Two value-added services are proposed to show how this approach can benefit information retrieval (IR) systems. The first service focuses on the organization and visual presentation of search results by clustering and bibliographic coupling. The second one aims at constructing virtual research communities and recommending significant papers to researchers. In addition to the two services, this study conducts quantitative and qualitative evaluations to show the feasibility of the proposed method; moreover, comparison with the previous approach is also performed. The experimental results show that the accuracy of the proposed method for search result organization reaches 80%, outperforming Topic Keyword Clustering. Both the precision and recall of virtual community construction are higher than 70%, and the accuracy of paper recommendation is almost 90%.
Dynamic fault diagnosis in chemical process based on SVM-HMM

Based on Hidden Markov Support Vector Machines (SVM-HMM) we present a novel dynamic fault diagnosis approach, in which the dynamic of chemical process is considered through augmenting each observation vector by using mean value and variance of the previous observations. Herein, SVM-HMM is a good method for dynamic continuous data which indentifies multiple kinds of faults with only one uniform discriminative model instead of multiple ones. A benchmark of Tennessee Eastman Process (TEP), a chemical engineering problem, is carried out to generate datasets to examine the performance of our new method. And the experiment results show the faults are identified more accurately applying the proposed method than that done by the state-of-the-art approaches.
Japanese experience with milnacipran, the first serotonin and norepinephrine reuptake inhibitor in Japan

Milnacipran is a serotonin and norepinephrine reuptake inhibitor (SNRI), with a balanced potency for the inhibition of the reuptake of the two monoamines. In this, it contrasts with venlafaxine and duloxetine which, while possessing a dual action, have a selectivity of the order of 30-fold and 10-fold respectively for the reuptake of serotonin. Milnacipran has mainly been launched in countries where the selective serotonin reuptake inhibitors (SSRIs) and venlafaxine had been established for several years. As such it has attracted relative little interest from clinician investigators as a research tool. Japan, however, represents a unique situation because in 1999 milnacipran was launched within months of the first SSRI and is still the only SNRI in Japan together with only two SSRIs (a third has just been introduced). This has led to a large number of investigative clinical studies, many of which give interesting insights into the potential of milnacipran in the treatment of depression and of other disorders. This article reviews these Japanese studies with milnacipran.
A General Multi-Party Protocol for Minimal Communication and Local Computation

A client wishes to outsource computation on confidential data to a network of servers. He does not trust a server on its own, but believes that servers do not collude. To solve this problem we introduce a new scheme called \emph{JOS} for perfect security in the context of secure multiparty computation in the semi-honest model that naturally requires at least three parties. It differs from classical work such as Yao, GMW, BGW or GRR through an explicit distinction of keys and encrypted values rather than having (equal) shares of a secret. Furthermore, JOS makes use of the distributive and associative nature of its encryption schemes and, at times, "double" encrypts values. Any Boolean circuit $C$ in disjunctive normal form with $w$ variables per clause can be evaluated in O($\log k$) rounds using messages of size O($2^{w-k}$) for an arbitrary parameter $k \in [2,w]$ and O($|C|\cdot 2^{w-k}$) bit operations. We allow for collusion of up to $n-2$ parties. On the theoretical side JOS improves a large body of work in one or several metrics. On the practical side, our local computation requirements improve on the run-time of GRR using Shamir's secret sharing up to several orders of magnitude.