Miracle-dz/UniFAR-FTUs huggingface dataset:
Collecting Natural SMS and Chat Conversations in Multiple Languages: The BOLT Phase 2 Corpus

The DARPA BOLT Program develops systems capable of allowing English speakers to retrieve and understand information from informal foreign language genres. Phase 2 of the program required large volumes of naturally occurring informal text (SMS) and chat messages from individual users in multiple languages to support evaluation of machine translation systems. We describe the design and implementation of a robust collection system capable of capturing both live and archived SMS and chat conversations from willing participants. We also discuss the challenges recruitment at a time when potential participants have acute and growing concerns about their personal privacy in the realm of digital communication, and we outline the techniques adopted to confront those challenges. Finally, we review the properties of the resulting BOLT Phase 2 Corpus, which comprises over 6.5 million words of naturally-occurring chat and SMS in English, Chinese and Egyptian Arabic.
On the anonymizability of mobile traffic datasets

Preserving user privacy is paramount when it comes to publicly disclosed datasets that contain fine-grained data about large populations. The problem is especially critical in the case of mobile traffic datasets collected by cellular operators, as they feature elevate subscriber trajectory uniqueness and they are resistant to anonymization through spatiotemporal generalization. In this work, we investigate the $k$-anonymizability of trajectories in two large-scale mobile traffic datasets, by means of a novel dedicated measure. Our results are in agreement with those of previous analyses, however they also provide additional insights on the reasons behind the poor anonimizability of mobile traffic datasets. As such, our study is a step forward in the direction of a more robust dataset anonymization.
Crowdsourcing a Collective Sense of Place

Place can be generally defined as a location that has been assigned meaning through human experience, and as such it is of multidisciplinary scientific interest. Up to this point place has been studied primarily within the context of social sciences as a theoretical construct. The availability of large amounts of user-generated content, e.g. in the form of social media feeds or Wikipedia contributions, allows us for the first time to computationally analyze and quantify the shared meaning of place. By aggregating references to human activities within urban spaces we can observe the emergence of unique themes that characterize different locations, thus identifying places through their discernible sociocultural signatures. In this paper we present results from a novel quantitative approach to derive such sociocultural signatures from Twitter contributions and also from corresponding Wikipedia entries. By contrasting the two we show how particular thematic characteristics of places (referred to herein as platial themes) are emerging from such crowd-contributed content, allowing us to observe the meaning that the general public, either individually or collectively, is assigning to specific locations. Our approach leverages probabilistic topic modelling, semantic association, and spatial clustering to find locations are conveying a collective sense of place. Deriving and quantifying such meaning allows us to observe how people transform a location to a place and shape its characteristics.
Electromagnetic Interference and Digital Circuits: An Initial Study of Clock Networks

Radio frequency interference (RFI) can have adverse effects on commercial electronics. Current properties of high-performance integrated circuits (ICs), such as very small feature sizes, high clock frequencies, and reduced voltage levels, increase the susceptibility of these circuits to RFI, causing them to be more prone to smaller RFI levels. Besides, recent developments of mobile devices and wireless networks create a hostile electromagnetic environment for ICs. Therefore, it is important to generalize the susceptibility of ICs to RFI. In this study, we investigate the susceptibility levels and frequency ranges of RFI to the clock network of a digital device, an 8-bit ripple counter, designed and fabricated using AMI 0.5 μm process technology. Our experimental setup is designed to couple a pulse-modulated RF signal using the direct pin injection method. Our experiments show that relatively low levels of RFI (e.g., 16.8 dBm delivered RF peak power with carrier frequency of 1 GHz) could adversely affect the normal functioning of the device under testing. In the end, SPICE simulations show the sensitivity of a flip-flop, the basic building block of clock network, which further explains the experimental results.
Efficient Salient Foreground Detection for Images and Video using Fiedler Vectors

Automatic detection of salient image regions is a useful tool with applications in intelligent camera control, virtual cinematography, video summarization and editing, evaluation of viewer preferences, and many others. This paper presents an effective method for detecting potentially salient foreground regions. Salient regions are identified by eigenvalue analysis of a graph Laplacian that is defined over the color similarity of image superpixels, under the assumption that the majority of pixels on the image boundary show non-salient background. In contrast to previous methods based on graph-cuts or graph partitioning, our method provides continuously-valued saliency estimates with complementary properties to recently proposed color contrast-based approaches. Moreover, exploiting discriminative properties of the Fiedler vector, we devise an SVM-based classifier that allows us to determine whether an image contains any salient objects at all, a problem that has been largely neglected in previous works. We also describe how the per-frame saliency detection can be extended to improve its spatiotemporal coherence when computed on video sequences. Extensive evaluation on several datasets demonstrates and validates the state-of-the-art performance of the proposed method.
Multiply-Constrained DCOP for Distributed Planning and Scheduling

Distributed constraint optimization (DCOP) has emerged as a useful technique for multiagent planning and scheduling. While previous DCOP work focuses on optimizing a single team objective, in many domains, agents must satisfy additional constraints on resources consumed locally (due to interactions within their local neighborhoods). Such local resource constraints may be required to be private or shared for efficiency’s sake. This paper provides a novel multiplyconstrained DCOPalgorithm for addressing these domains. This algorithm is based on mutually-intervening search, i.e. using local resource constraints to intervene in the search for the optimal solution and vice versa, realized via three key ideas: (i) transforming n-ary constraints via virtual variables to maintain privacy; (ii) dynamically setting upper bounds on joint resource consumption with neighbors; and (iii) identifying if the local DCOP graph structure allows agents to compute exact resource bounds for additional efficiency. These ideas are implemented by modifying Adopt, one of the most efficient DCOP algorithms. Both detailed experimental results as well as proofs of correctness are presented.
Work, Stress, and Diurnal Bruxism: A Pilot Study among Information Technology Professionals in Bangalore City, India

The study assessed the prevalence of diurnal bruxism among information technology (IT) professionals and explored plausible predictors associated with the parafunctional habit. A cross-sectional study was designed and IT professionals were invited to participate. The inclusion criteria composed of participants in service for at least one year, having natural dentition, no history of cervical or facial injury and not undergoing orthodontic therapy. The participants (N = 147) were interviewed by a trained interviewer to record information. A pre-tested questionnaire that included questions related to work, stress symptoms and diurnal bruxism was completed by each participant. The prevalence of self-reported diurnal bruxism was 59%. Bivariate analyses revealed that work (P < 0.05) and work experience (P < 0.05) were significantly associated with self-reported diurnal bruxism. In the binary logistic regression analysis stress (Odds Ratio [OR] = 5.9, 95% Confidence Interval [CI] 2.6–13.3) was identified to be a strong predictor of diurnal bruxism. Professionals with 11 or more years of experience were less likely to report diurnal bruxism (OR = 0.04, 95% CI 0.00–0.43) than those with 1 to 5 years of work experience. The study revealed that stress and less work experience were associated with diurnal bruxism among IT professionals in Bangalore city.
Metabolomic profiling of breast tumors using ductal fluid

Identification of new biomarkers for breast cancer remains critical in order to enhance early detection of the disease and improve its prognosis. Towards this end, we performed an untargeted metabolomic analysis of breast ductal fluid using an ultra-performance liquid chromatography coupled with a quadrupole time-of-light (UPLC-QTOF) mass spectrometer. We investigated the metabolomic profiles of breast tumors using ductal fluid samples collected by ductal lavage (DL). We studied fluid from both the affected breasts and the unaffected contralateral breasts (as controls) from 43 women with confirmed unilateral breast cancer. Using this approach, we identified 1560 ions in the positive mode and 538 ions in the negative mode after preprocessing of the UPLC-QTOF data. Paired t-tests applied on these data matrices identified 209 ions (positive and negative modes combined) with significant change in intensity level between affected and unaffected control breasts (adjusted P-values <0.05). Among these, 83 ions (39.7%) showed a fold change (FC) >1.2 and 66 ions (31.6%) were identified with putative compound names. The metabolites that we identified included endogenous metabolites such as amino acid derivatives (N-Acetyl-DL-tryptophan) or products of lipid metabolism such as N-linoleoyl taurine, trans-2-dodecenoylcarnitine, lysophosphatidylcholine LysoPC(18:2(9Z,12Z)), glycerophospholipids PG(18:0/0:0), and phosphatidylserine PS(20:4(5Z,8Z,11Z,14Z). Generalized LASSO regression further selected 21 metabolites when race, menopausal status, smoking, grade and TNM stage were adjusted for. A predictive conditional logistic regression model, using the LASSO selected 21 ions, provided diagnostic accuracy with the area under the curve of 0.956 (sensitivity/specificity of 0.907/0.884). This is the first study that shows the feasibility of conducting a comprehensive metabolomic profiling of breast tumors using breast ductal fluid to detect changes in the cellular microenvironment of the tumors and shows the potential for this approach to be used to improve detection of breast cancer.
Cryptographic security of quantum key distribution

This work is intended as an introduction to cryptographic security and a motivation for the widely used Quantum Key Distribution (QKD) security definition. We review the notion of security necessary for a protocol to be usable in a larger cryptographic context, i.e., for it to remain secure when composed with other secure protocols. We then derive the corresponding security criterion for QKD. We provide several examples of QKD composed in sequence and parallel with different cryptographic schemes to illustrate how the error of a composed protocol is the sum of the errors of the individual protocols. We also discuss the operational interpretations of the distance metric used to quantify these errors.
Characterization and Prediction of Protein Phosphorylation Hotspots in Arabidopsis thaliana

The regulation of protein function by modulating the surface charge status via sequence-locally enriched phosphorylation sites (P-sites) in so called phosphorylation “hotspots” has gained increased attention in recent years. We set out to identify P-hotspots in the model plant Arabidopsis thaliana. We analyzed the spacing of experimentally detected P-sites within peptide-covered regions along Arabidopsis protein sequences as available from the PhosPhAt database. Confirming earlier reports (Schweiger and Linial, 2010), we found that, indeed, P-sites tend to cluster and that distributions between serine and threonine P-sites to their respected closest next P-site differ significantly from those for tyrosine P-sites. The ability to predict P-hotspots by applying available computational P-site prediction programs that focus on identifying single P-sites was observed to be severely compromised by the inevitable interference of nearby P-sites. We devised a new approach, named HotSPotter, for the prediction of phosphorylation hotspots. HotSPotter is based primarily on local amino acid compositional preferences rather than sequence position-specific motifs and uses support vector machines as the underlying classification engine. HotSPotter correctly identified experimentally determined phosphorylation hotspots in A. thaliana with high accuracy. Applied to the Arabidopsis proteome, HotSPotter-predicted 13,677 candidate P-hotspots in 9,599 proteins corresponding to 7,847 unique genes. Hotspot containing proteins are involved predominantly in signaling processes confirming the surmised modulating role of hotspots in signaling and interaction events. Our study provides new bioinformatics means to identify phosphorylation hotspots and lays the basis for further investigating novel candidate P-hotspots. All phosphorylation hotspot annotations and predictions have been made available as part of the PhosPhAt database at http://phosphat.mpimp-golm.mpg. de.
Working Paper Dynamic Risk Exposure in Hedge Funds Monica Billio Mila

We measure dynamic risk exposure of hedge funds to various risk factors during different market volatility conditions using the regime-switching beta model. We find that in the high-volatility regime (when the market is rolling-down) most of the strategies are negatively and significantly exposed to the Large-Small and Credit Spread risk factors. This suggests that liquidity risk and credit risk are potentially common factors for different hedge fund strategies in the down-state of the market, when volatility is high and returns are very low. We further explore the possibility that all hedge fund strategies exhibit idiosyncratic risk in a high volatility regime and find that the joint probability jumps from approximately 0% to almost 100% only during the Long-Term Capital Management (LTCM) crisis. Out-of-sample forecasting tests confirm the economic importance of accounting for the presence of market volatility regimes in determining hedge funds risk exposure.
Relationship between Age/Gender-Induced Survival Changes and the Magnitude of Inflammatory Activation and Organ Dysfunction in Post-Traumatic Sepsis

Age/gender may likely influence the course of septic complications after trauma. We aimed to characterize the influence of age/gender on the response of circulating cytokines, cells and organ function in post-traumatic sepsis. We additionally tested whether post-traumatic responses alone can accurately predict outcomes in subsequent post-traumatic sepsis. A mouse 2-hit model of trauma/hemorrhage (TH, 1st hit) and cecal ligation and puncture (CLP, 2nd hit) was employed. 3, 15 and 20 month (m) old female (♀) and male (♂) CD-1 mice underwent sublethal TH followed by CLP 2 days later. Blood was sampled daily until day 6 post-TH and survival was followed for 16 days. To compare general response patterns among groups, we calculated two scores: the inflammatory response (including KC, MIP-1α, TNFα, MCP-1, IFNγ, IL-1β,-5,-6,-10) and the organ dysfunction score (Urea, ALT, AST and LDH). Moreover, mice were retrospectively divided into survivors (SUR) and dying (DIE) based on post-CLP outcome. In general, females survived better than males and their survival did not correspond to any specific estrus cycle phase. Pre-CLP phase: the post-TH inflammatory score was weakest in 3 m♂ but there were no changes among remaining groups (similar lack of differences in the organ dysfunction score). TH induced a 40% increase of IFNγ, MIP-1α and IL-5 in 15 m♂ SUR (vs. DIE) but predictive accuracy for post-CLP outcomes was moderate. Post-CLP phase: while stable in males, inflammatory response score in 15 m and 20 m females decreased with age at day 1 and 2 post-CLP. SUR vs. DIE differences in inflammatory and organ dysfunction score were evident but their magnitude was comparable across age/gender. Nearly identical activation of the humoral inflammatory and organ function compartments, both across groups and according to sepsis severity, suggests that they are not directly responsible for the age/gender-dependent disparity in TH-CLP survival in the studied young-to-mature population.
Automatic Ellipsis Resolution: Recovering Covert Information from Text

Ellipsis is a linguistic process that makes certain aspects of text meaning not directly traceable to surface text elements and, therefore, inaccessible to most language processing technologies. However, detecting and resolving ellipsis is an indispensable capability for language-enabled intelligent agents. The key insight of the work presented here is that not all cases of ellipsis are equally difficult: some can be detected and resolved with high confidence even before we are able to build agents with full human-level semantic and pragmatic understanding of text. This paper describes a fully automatic, implemented and evaluated method of treating one class of ellipsis: elided scopes of modality. Our cognitively-inspired approach, which centrally leverages linguistic principles, has also been applied to overt referring expressions with equally promising results.
Detection of upper limit of normal values of anti-DNase B antibody in children’s age groups who were admitted to hospital with noninfectious reasons

OBJECTIVE: Anti-streptolysin O (ASO) and anti-DNase B (ADB) titers are used for the diagnosis of poststreptococcal complications. Ranges of normal values of ASO and ADB titers vary, depending on age, population and different time intervals. Although many studies have been performed for determination of the ASO titer in our country, only a few studies have been conducted for specification the upper limit of normal for (ULN) ADB. In our study we aimed to determine the upper limit of normal of ADB antibody titers in children aged 5–15. METHODS: One hundred and twenty one children aged from 5–15 who were admitted to our outpatient clinic of Haydarpaşa Numune Training and Research Hospital with noninfectious reasons between November 2013 and March 2014 were included in the study. Patients who met the following criteria were included in the study; absence of streptococcal infection in the last three months in physical examination and/or no growth of group A, C, and G of beta-haemolytic streptococci in throat culture, normal ranges of ASO and C reactive protein (CRP) levels. All serum samples were analyzed collectively by nephelometric method. The upper limit of normal value for anti-DNase B has been defined by separating the upper 20% from the lower 80% of all measurements. RESULTS: Anti-DNase B antibody levels were ranged between 50–576 IU/ml and its upper limit was 219.2 IU/ml. When analyzed according to age groups, anti-DNase B antibody levels in the group aged between 5–10, ranged between 50–576 IU/ml and its upper limit was 212.2 IU/ml, anti-DNase B antibody levels in the group aged 10–15, ranged between 50–408 IU/ml and its upper limit was 231.2 IU/ml (p=0.008). CONCLUSION: Based on our results, upper normal values ADB antibody showed variations with age in our results. Therefore national reference values should be detected by more comprehensive studies.
Disruption of the blood-brain barrier in open and closed cranial window preparations in rats.

The goal of this study was to determine whether the severity of disruption of the blood-brain barrier during acute hypertension is similar in open and closed cranial window preparations. Intravital fluorescent microscopy and fluorescein-labeled albumin were used to evaluate disruption of the blood-brain barrier under control conditions and during acute arterial hypertension in 10 rats equipped with an open cranial window and in six rats equipped with a closed cranial window. Permeability of the blood-brain barrier was quantified by calculating the clearance of fluorescein-labeled albumin and by counting the number of microvascular leaky sites under control conditions and during acute hypertension. Pressure in cerebral venules and intracranial pressure were measured in rats equipped with an open cranial window and a closed cranial window, respectively, under control conditions and during acute hypertension. In rats equipped with an open cranial window, arterial pressure increased from 118 +/- 6 to 189 +/- 3 mm Hg (mean +/- SEM) and pial venous pressure increased from 7 +/- 1 to 22 +/- 3 mm Hg during acute hypertension induced with 30 micrograms/kg/min phenylephrine for 5 minutes. In addition, the clearance of fluorescent albumin increased from 0.11 +/- 0.03 to 1.2 +/- 0.4 ml/sec x 10(-6) and the number of microvascular leaky sites increased from 0 to 25 +/- 1 during phenylephrine infusion. In rats equipped with a closed cranial window, arterial pressure increased from 122 +/- 5 to 187 +/- 7 mm Hg and intracranial pressure increased from 3 +/- 1 to 12 +/- 1 mm Hg during the intravenous infusion of 30 micrograms/kg/min phenylephrine for 5 minutes. (ABSTRACT TRUNCATED AT 250 WORDS)
Integration of genomic and epigenomic features to predict meiotic recombination hotspots in human and mouse

The regulatory mechanism of meiotic recombination hotspots is a fundamental problem in biology, with broad impacts on areas ranging from disease study to evolution. Recently, many genomic and epigenomic features have been associated with recombination hotspots, but none of them can explain hotspots consistently. It is highly desirable to integrate the different features into a predictive model, and study the relation of the features with hotspots and themselves with a systems approach. Moreover, due to rapid and dynamic evolution of recombination hotspots, regulatory mechanisms of hotspots that are evolutionarily conserved among species remain unclear. We propose a machine learning approach that encode genomic and epigenomic features into a support vector machine (SVM). Trained on known hotspots and coldspots in human and mouse genomes, the model is able to predict hotspots based on the features with good performance in both species. Moreover, the model reports a ranking of feature importance, uncovering the interactions of the features with hotspots and themselves. Applying the method to large-scale data, we identified evolutionarily conserved patterns of trans-regulators and feature importance between human and mouse hotspots. This is the first attempt to build a predictive model to identify evolutionarily conserved mechanisms for recombination hotspots by integrating both genomic and epigenomic features.
Nodular histiocytic/mesothelial hyperplasia as consequence of chronic mesothelium irritation by subphrenic abscess.

PURPOSE Pleural nodular histiocytic/mesothelial hyperplasia is a nodular histiocytic/mesothelial proliferation, often delimiting cystic cavities, due to irritation by a pulmonary noxa. Case report results: The patient had right pleural parietal and diaphragmatic thickness, with pleural effusion, without lung alterations. He previously underwent left hemicolectomy and liver resection, due to a diverticulitis and a liver histiocytes-rich abscess. Video-assisted thoracoscopy biopsy showed a double population of reactive mesothelial cells and histiocytes. CONCLUSION Nodular histiocytic/mesothelial hyperplasia represents a potential pitfall for pathologists. Immunohistochemistry is crucial for the differential diagnosis with some malignancies. We suggest that in our patient, a chronic mesothelium inflammation happened by transdiaphragmatic involvement as a consequence of the liver abscess. Some pathogenetic mechanisms are hypothesized.