Miracle-dz/UniFAR-FTUs huggingface dataset:
Explicit Sensor Network Localization using Semidefinite Representations and Facial Reductions

The sensor network localization (SNL) problem in embedding dimension $r$ consists of locating the positions of wireless sensors, given only the distances between sensors that are within radio range and the positions of a subset of the sensors (called anchors). Current solution techniques relax this problem to a weighted, nearest, (positive) semidefinite programming (SDP) completion problem by using the linear mapping between Euclidean distance matrices (EDM) and semidefinite matrices. The resulting SDP is solved using primal-dual interior point solvers, yielding an expensive and inexact solution. This relaxation is highly degenerate in the sense that the feasible set is restricted to a low dimensional face of the SDP cone, implying that the Slater constraint qualification fails. Cliques in the graph of the SNL problem give rise to this degeneracy in the SDP relaxation. In this paper, we take advantage of the absence of the Slater constraint qualification and derive a technique for the SNL problem, with exact data, that explicitly solves the corresponding rank restricted SDP problem. No SDP solvers are used. For randomly generated instances, we are able to efficiently solve many huge instances of this NP-hard problem to high accuracy by finding a representation of the minimal face of the SDP cone that contains the SDP matrix representation of the EDM. The main work of our algorithm consists in repeatedly finding the intersection of subspaces that represent the faces of the SDP cone that correspond to cliques of the SNL problem.
Dynamic Difficulty Adjustment for Maximized Engagement in Digital Games

Dynamic difficulty adjustment (DDA) is a technique for adaptively changing a game to make it easier or harder. A common paradigm to achieve DDA is through heuristic prediction and intervention, adjusting game difficulty once undesirable player states (e.g., boredom or frustration) are observed. Without quantitative objectives, it is impossible to optimize the strength of intervention and achieve the best effectiveness. In this paper, we propose a DDA framework with a global optimization objective of maximizing a player's engagement throughout the entire game. Using level-based games as our example, we model a player's progression as a probabilistic graph. Dynamic difficulty reduces to optimizing transition probabilities to maximize a player's stay time in the progression graph. We have successfully developed a system that applies this technique in multiple games by Electronic Arts, Inc., and have observed up to 9% improvement in player engagement with a neutral impact on monetization.
A Discourse Commitment-Based Framework for Recognizing Textual Entailment

In this paper, we introduce a new framework for recognizing textual entailment which depends on extraction of the set of publicly-held beliefs -- known as discourse commitments -- that can be ascribed to the author of a text or a hypothesis. Once a set of commitments have been extracted from a t-h pair, the task of recognizing textual entailment is reduced to the identification of the commitments from a t which support the inference of the h. Promising results were achieved: our system correctly identified more than 80% of examples from the RTE-3 Test Set correctly, without the need for additional sources of training data or other web-based resources.
Obesity, hypertension, social determinants of health and the epidemiologic transition among traditional Amazonian populations

Abstract Background: The health and nutritional situation of adults from three rural vulnerable Amazonian populations are investigated in relation to the Social Determinants of Health (SDH) and the epidemiologic transition. Aim: To investigate the role of the environment and the SDH on the occurrence of chronic-degenerative diseases in these groups. Subjects and methods: Anthropometric, blood pressure and demographic data were collected in adults from the RDS Mamirauá, AM (n = 149), Flona Caxiuanã, PA (n = 148) and quilombolas, PA (n = 351), populations living in a variety of socio-ecological environments in the Brazilian Amazon. Results: Adjusting for the effect of age, quilombola men are taller (F = 9.85; p < 0.001) and quilombola women present with higher adiposity (F = 20.43; p < 0.001) and are more overweight/obese. Men from Mamirauá present higher adiposity (F = 9.58; p < 0.001). Mamirauá women are taller (F = 5.55; p < 0.01) and have higher values of waist circumference and subscapular/triceps index. Quilombolas present higher prevalence of hypertension in both sexes and there are significant differences in rates of hypertension among the women (χ2 = 17.45; p < 0.01). The quilombolas are more dependent on government programmes, people from Mamirauá have more economic resources and the group from Caxiunã have the lowest SES. Conclusion: In these populations, the SDH play a key role in the ontogeny of diseases and the ‘diseases of modernity’ occur simultaneously with the always present infectoparasitic pathologies, substantially increasing social vulnerability.
A coordinated approach to cutaneous wound healing: vibrational microscopy and molecular biology

The repair of cutaneous wounds in the adult body involves a complex series of spatially and temporally organized processes to prevent infection and restore homeostasis. Three characteristic phases of wound repair (inflammation, proliferation including re‐epithelialization and remodelling) overlap in time and space. We have utilized a human skin wound‐healing model to correlate changes in genotype and pheno‐type with infrared (IR) and confocal Raman spectroscopic images during the re‐epithelialization of excisional wounds. The experimental protocols validated as IR images clearly delineate the keratin‐rich migrating epithelial tongue from the collagen‐rich wound bed. Multivariate statistical analysis of IR datasets acquired 6 days post‐wounding reveal subtle spectral differences that map to distinct spatial distributions, which are correlated with immunofluorescent staining patterns of different keratin types. Images computed within collagen‐rich regions expose complementary spatial patterns and identify elastin in the wound bed. The temporal sequence of events is explored through a comparison of gene array analysis with confocal Raman microscopy. Our approach demonstrates the feasibility of acquiring detailed molecular structure information from the various proteins and their subclasses involved in the wound‐healing process.
Candida albicans-Secreted Aspartic Proteinases Modify the Epithelial Cytokine Response in an In Vitro Model of Vaginal Candidiasis

ABSTRACT Secreted aspartyl proteinases (Saps) are important virulence factors of Candida albicans during mucosal and disseminated infections and may also contribute to the induction of an inflammatory host immune response. We used a model of vaginal candidiasis based on reconstituted human vaginal epithelium (RHVE) to study the epithelial cytokine response induced by C. albicans. In order to study the impact of the overall proteolytic activity and of distinct Sap isoenzymes, we studied the effect of the proteinase inhibitor pepstatin A on the immune response and compared the cytokine expression pattern induced by the wild-type strain SC5314 with the pattern induced by Sap-deficient mutants. Infection of RHVE with the C. albicans wild-type strain induced strong interleukin 1α (IL-1α), IL-1β, IL-6, IL-8, IL-10, granulocyte-macrophage colony-stimulating factor, gamma interferon, and tumor necrosis factor alpha responses in comparison with cytokine expression in noninfected tissue. Addition of the aspartyl proteinase inhibitor pepstatin A strongly reduced the cytokine response of RHVE. Furthermore, SAP-null mutants lacking either SAP1 or SAP2 caused reduced tissue damage and had a significantly reduced potential to stimulate cytokine expression. In contrast, the vaginopathic and cytokine-inducing potential of mutants lacking SAP4 to SAP6 was similar to that of the wild-type strain. These data show that the potential of specific Saps to cause tissue damage correlates with an epithelium-induced proinflammatory cytokine response, which may be crucial in controlling and managing C. albicans infections at the vaginal mucosa in vivo.
Intrusions detection based on Support Vector Machine optimized with swarm intelligence

Intrusion Detection Systems(IDS) have become a necessary component of almost every security infrastructure. Recently, Support Vector Machines (SVM) has been employed to provide potential solutions for IDS. With its many variants for classification SVM is a state-of-the-art machine learning algorithm. However, the performance of SVM depends on selection of the appropriate parameters. In this paper we propose an IDS model based on Information Gain for feature selection combined with the SVM classifier. The parameters for SVM will be selected by a swarm intelligence algorithm (Particle Swarm Optimization or Artificial Bee Colony). We use the NSL-KDD data set and show that our model can achieve higher detection rate and lower false alarm rate than regular SVM.
Effect of the coadministration of citalopram with mirtazapine or atipamezole on rat contextual conditioned fear

Background Mirtazapine, a noradrenergic and specific serotonergic antidepressant, which blocks the α2-adrenergic autoreceptors and heteroreceptors, has shown anxiolytic properties in clinical trials and preclinical animal experiments. The addition of mirtazapine to selective serotonin reuptake inhibitors (SSRIs) is clinically suggested to be more effective for anxiety disorders. In this study, we examined the combined effects of mirtazapine and citalopram, an SSRI, on the freezing behavior of rats, which was induced by contextual conditioned fear as an index of anxiety or fear. Methods Male Sprague Dawley rats individually received footshocks in a shock chamber, and 24 hours later, they were given citalopram and/or mirtazapine injections. One hour after citalopram and 30 minutes after mirtazapine administration, freezing behavior was analyzed in the same shock chamber without shocks. Results Mirtazapine decreased freezing in a dose-dependent manner, which is consistent with a previous report; it also enhanced an anxiolytic-like effect at a high dose (30 mg/kg) of citalopram. Because mirtazapine blocks α2-adrenoreceptors, the combined effect of atipamezole, a selective α2 receptor antagonist, with citalopram was also examined. Similar to mirtazapine, atipamezole reduced freezing dose-dependently, but the enhancement of citalopram’s effects by atipamezole was not clear when compared with mirtazapine. Conclusion The present findings suggest that mirtazapine has an anxiolytic-like effect and may enhance the anxiolytic-like effect of SSRIs, but this enhancement may not be explained by its anti-α2 property alone.
Reduced Freezing in Posttraumatic Stress Disorder Patients while Watching Affective Pictures

Besides fight and flight responses, animals and humans may respond to threat with freezing, a response characterized by bradycardia and physical immobility. Risk assessment is proposed to be enhanced during freezing to promote optimal decision making. Indeed, healthy participants showed freezing-like responses to threat cues. Posttraumatic stress disorder (PTSD) patients are characterized by hypervigilance and increased threat responsiveness. We propose that threat responses will be characterized by decreased freezing in PTSD, eliminating possibilities for rejecting cognitive distortions, such as harm expectancy, and thereby contributing to the maintenance of the disorder. However, freezing responses have hardly been investigated in PTSD. Using a stabilometric platform to assess body sway as an indicator of freezing-like behavior, we examined whether veterans with PTSD would show diminished freezing responses to unpleasant versus neutral and pleasant pictures. Fourteen PTSD patients and 14 healthy matched controls watched the pictures, while body sway and heart rate (HR) were continuously assessed. Replicating previous findings, healthy controls showed decreased body sway and HR in response to unpleasant pictures, indicative of freezing-like behavior. In contrast, this response pattern was not observed in PTSD patients. The results may indicate a reduced freezing response in PTSD. As reduced freezing may hinder appropriate risk assessment, it may be an important factor in the maintenance of PTSD. Future research might clarify whether impaired freezing is a PTSD-specific or a transdiagnostic symptom, being present in threat-related disorders.
Laparoscopic adjustable gastric banding. A prospective randomized study comparing the Swedish Adjustable Gastric Band and the MiniMizer Extra: one-year results

Introduction A number of different adjustable gastric bands are available for laparoscopic adjustable gastric banding (LAGB). Few attempts have been made to compare the influence of band design differences for efficiency and complication rate and conflicting results have emerged from comparative studies. Aim To compare SAGB (Swedish Adjustable Gastric Band) and MiniMizer Extra adjustable gastric bands. Material and methods One hundred and three patients were included in the prospective randomized study. All patients underwent LAGB. The SAGB was used in 49 and MiniMizer Extra in 54 patients. The primary endpoint was weight loss, and secondary endpoints were complication rate, correction of co-morbidities and improvement of quality of life. Results There were no early complications. A significant difference in the proportion of patients who have reached good or excellent weight loss results (≥ 50% of initial excess body mass index loss) was found in favour of the MiniMizer Extra group (29.6% vs. 8.2%, p = 0.006). No difference was found in other weight loss parameters, resolution of co-morbidities and improvement of quality of life. One oesophageal dilatation and one leakage were diagnosed in the MiniMizer Extra group. Five band penetrations (9.3%) were diagnosed in the MiniMizer Extra group and no penetrations in the SAGB group (p = 0.069). Conclusions No major significant differences were found between the compared bands. Further results need to be confirmed by longer follow-up.
Identifying featured articles in wikipedia: writing style matters

Wikipedia provides an information quality assessment model with criteria for human peer reviewers to identify featured articles. For this classification task "Is an article featured or not? " we present a machine learning approach that exploits an article's character trigram distribution. Our approach differs from existing research in that it aims to writing style rather than evaluating meta features like the edit history. The approach is robust, straightforward to implement, and outperforms existing solutions. We underpin these claims by an experiment design where, among others, the domain transferability is analyzed. The achieved performances in terms of the F-measure for featured articles are 0.964 within a single Wikipedia domain and 0.880 in a domain transfer situation.
Neural CRF Parsing

This paper describes a parsing model that combines the exact dynamic programming of CRF parsing with the rich nonlinear featurization of neural net approaches. Our model is structurally a CRF that factors over anchored rule productions, but instead of linear potential functions based on sparse features, we use nonlinear potentials computed via a feedforward neural network. Because potentials are still local to anchored rules, structured inference (CKY) is unchanged from the sparse case. Computing gradients during learning involves backpropagating an error signal formed from standard CRF sufficient statistics (expected rule counts). Using only dense features, our neural CRF already exceeds a strong baseline CRF model (Hall et al., 2014). In combination with sparse features, our system achieves 91.1 F1 on section 23 of the Penn Treebank, and more generally outperforms the best prior single parser results on a range of languages.
The Development of a Metabolic Disease Phenotype in CTP:Phosphoethanolamine Cytidylyltransferase-deficient Mice*

Phosphatidylethanolamine (PE) is an important inner membrane phospholipid mostly synthesized de novo via the PE-Kennedy pathway and by the decarboxylation of phosphatidylserine. CTP:phosphoethanolamine cytidylyltransferase (Pcyt2) catalyzes the formation of CDP-ethanolamine, which is often the rate regulatory step in the PE-Kennedy pathway. In the current investigation, we show that the reduced CDP-ethanolamine formation in Pcyt2+/− mice limits the rate of PE synthesis and increases the availability of diacylglycerol. This results in the increased formation of triglycerides, which is facilitated by stimulated de novo fatty acid synthesis and increased uptake of pre-existing fatty acids. Pcyt2+/− mice progressively accumulate more diacylglycerol and triglycerides with age and have modified fatty acid composition, predominantly in PE and triglycerides. Pcyt2+/− additionally have an inherent blockage in fatty acid utilization as energy substrate and develop impaired tolerance to glucose and insulin at an older age. Accordingly, gene expression analyses demonstrated the up-regulation of the main lipogenic genes and down-regulation of mitochondrial fatty acid β-oxidation genes. These data demonstrate for the first time that to preserve membrane PE phospholipids, Pcyt2 deficiency generates compensatory changes in triglyceride and energy substrate metabolism, resulting in a progressive development of liver steatosis, hypertriglyceridemia, obesity, and insulin resistance, the main features of the metabolic syndrome.
Twins: Device-free object tracking using passive tags

Device-free based object tracking provides a promising solution for many localization and tracking systems to monitor non-cooperative objects which do not carry any transceiver such as intruders. However, existing device-free solutions mainly use sensors and active RFID tags, which are much more expensive compared to passive tags. In this paper, we propose a novel motion detection and tracking method using passive RFID tags, named Twins. The method leverages a phenomenon called critical state caused by interference among passive tags. We theoretically explain this phenomenon via an interference model and conduct extensive experiment to validate it. We design a practical Twins based intrusion detection system and implement a real prototype with commercial off-the-shelf reader and tags. Experimental results show that Twins is effective in detecting the moving object, with low location errors of 0.75m in average.
Compressing Neural Networks with the Hashing Trick

As deep nets are increasingly used in applications suited for mobile devices, a fundamental dilemma becomes apparent: the trend in deep learning is to grow models to absorb ever-increasing data set sizes; however mobile devices are designed with very little memory and cannot store such large models. We present a novel network architecture, HashedNets, that exploits inherent redundancy in neural networks to achieve drastic reductions in model sizes. HashedNets uses a low-cost hash function to randomly group connection weights into hash buckets, and all connections within the same hash bucket share a single parameter value. These parameters are tuned to adjust to the HashedNets weight sharing architecture with standard backprop during training. Our hashing procedure introduces no additional memory overhead, and we demonstrate on several benchmark data sets that HashedNets shrink the storage requirements of neural networks substantially while mostly preserving generalization performance.
Endometrial and subendometrial perfusion are impaired in women with unexplained subfertility.

BACKGROUND We used three-dimensional power Doppler angiography (3D-PDA) to examine the periodic changes in endometrial development and subendometrial vascularity during the normal menstrual cycle in 29 women with unexplained subfertility and 19 controls. METHODS 3D-PDA was performed on alternate days from day 3 of the cycle until ovulation and then every 4 days until menses. VOCAL (Virtual Organ Computer-aided AnaLysis) and shell-imaging were used to define and to quantify the power Doppler signal within the endometrial and subendometrial regions producing indices of their relative vascularity. RESULTS Women with unexplained subfertility demonstrated significant changes with time (P<0.001) in the indices of vascularity within the endometrium and subendometrium during the menstrual cycle characterized by a pre-ovulatory peak and post-ovulatory fall. These changes mirrored those observed in the control group but were significantly reduced in the endometrium and subendometrium during the mid-late follicular phase and early luteal phase. There were no differences in endometrial thickness or volume between the groups or in the plasma concentrations of estradiol or progesterone. CONCLUSIONS Endometrial and subendometrial vascularity are significantly reduced in women with unexplained subfertility during the mid-late follicular phase irrespective of estradiol or progesterone concentrations and endometrial morphometry.
Hybrid transmit waveform design based on beam-forming and orthogonal space-time block coding

We derive a hybrid of beam-forming (BF) and space-time block coding (STBC), where the space-time code is transmitted over the beams generated by the steering vectors corresponding to the channel path directions. This is for the practical case where the transmit array may have adequate information on the departure angles of the dominant paths between transmitter and receiver, but unreliable information on the associated complex path gains. We compute analytically the signal-to-noise ratio (SNR) of the proposed hybrid for the specific case of a two-path channel model and using the orthogonal Alamouti code, and compare the result to the SNR of optimal linear precoding (LP) and the theoretically possible SNR of orthogonal STBC (OSTBC). Simulation results show that the performance of the BF/STBC hybrid can be very close to LP /sup n/der certain conditions - or even better in the practical case where there are phase estimation errors in the path gain estimates employed at the transmitter.
Exact model matching and disturbance rejection for general linear time delay systems via measurement output feedback

The problem of exact model matching with simultaneous disturbance rejection (EMMDR) for general neutral multi-delay systems, via proportional realizable controller feeding back measurable disturbances and measurement outputs, is studied. The desired model is assumed to be left-invertible. For this problem the following two major issues are resolved: the necessary and sufficient conditions for the problem to have a realizable solution and the general analytical expression of the controller matrices solving the problem. The results have been applied to control an internal combustion (IC) engine