Miracle-dz/UniFAR-FTUs huggingface dataset:
Block-Value Symmetries in Probabilistic Graphical Models

One popular way for lifted inference in probabilistic graphical models is to first merge symmetric states into a single cluster (orbit) and then use these for downstream inference, via variations of orbital MCMC [Niepert, 2012]. These orbits are represented compactly using permutations over variables, and variable-value (VV) pairs, but they can miss several state symmetries in a domain. We define the notion of permutations over block-value (BV) pairs, where a block is a set of variables. BV strictly generalizes VV symmetries, and can compute many more symmetries for increasing block sizes. To operationalize use of BV permutations in lifted inference, we describe 1) an algorithm to compute BV permutations given a block partition of the variables, 2) BV-MCMC, an extension of orbital MCMC that can sample from BV orbits, and 3) a heuristic to suggest good block partitions. Our experiments show that BV-MCMC can mix much faster compared to vanilla MCMC and orbital MCMC.
Eremias multiocellata : A PRELIMINARY STUDY

In this study we observed the embryonic development processes and compared the weight of eggs with neonates to identify the form of nutritional provisioning in Eremias multiocellata. We also used light microscopy to determine the features of chorioallontoic placenta during late stages of gestation. Neonatal dry weight was approximately 10.3% smaller than egg dry weight. Chorioallantoic membrane and uterine epithelium exhibited an indirect apposition without any fusion. No specialized region, placentome, has been found for nutrition transfer between these membranes. The chorioallontoic placenta of E. multiocellata is consistent with the simplest and most common type, Weekes type I. We infer that E. multiocellata is predominately lecithotrophic, meaning that nourishment for embryonic development is primarily supplied by the yolk. This kind of embryonic nutrition confirms the pattern found in most squamates with a simple placenta. This simple placenta adds anatomical evidence to understand the weak immune interaction between matrix and fetus in E. multiocellata. Finally, we discussed the implications for interpreting the evolution of viviparity and placentation.
Learning to Drive in a Day

We demonstrate the first application of deep reinforcement learning to autonomous driving. From randomly initialised parameters, our model is able to learn a policy for lane following in a handful of training episodes using a single monocular image as input. We provide a general and easy to obtain reward: the distance travelled by the vehicle without the safety driver taking control. We use a continuous, model-free deep reinforcement learning algorithm, with all exploration and optimisation performed on-vehicle. This demonstrates a new framework for autonomous driving which moves away from reliance on defined logical rules, mapping, and direct supervision. We discuss the challenges and opportunities to scale this approach to a broader range of autonomous driving tasks.
Confocal Imaging at 0.3 THz With Depth Resolution of a Painted Wood Artwork for the Identification of Buried Thin Metal Foils

A compact confocal terahertz microscope working at 0.30 THz based on all-solid-state components is used to locate buried thin metal foils in a painted wood artwork. Metal foils are used for decoration, and their precise localization under the pictorial layer is relevant information for conservation scientists and restorers, which can neither be obtained by X-ray radiography nor by spectroscopic imaging in the infrared, as we directly show here. The confocal microscopy principle based on the spatial pinhole concept is here implemented by positioning the first focus of an ellipsoidal reflector at the phase center of horn antennas coupled to Schottky diode detector and emitter mounted in rectangular waveguide blocks, together with an optical beamsplitter. The second focus of the reflector is mechanically scanned inside the sample in three dimensions. The predictions of diffraction theory for a confocal microscope at an imaging wavelength of 1.00 mm with numerical aperture of 0.53 are verified experimentally (1.2 and 2.8 mm for the lateral and the axial resolution, respectively). These values of resolution allow a precise determination of the position of buried metal foils in an ancient piece of art hence making restoration interventions possible.
Online Label Recovery for Deep Learning-based Communication through Error Correcting Codes

We demonstrate that error correcting codes (ECCs) can be used to construct a labeled data set for finetuning of “trainable” communication systems without sacrificing resources for the transmission of known symbols. This enables adaptive systems, which can be trained on-the-fly to compensate for slow fluctuations in channel conditions or varying hardware impairments. We examine the influence of corrupted training data and show that it is crucial to train based on correct labels. The proposed method can be applied to fully end-to-end trained communication systems (autoencoders) as well as systems with only some trainable components. This is exemplified by extending a conventional OFDM system with a trainable pre-equalizer neural network (NN) that can be optimized at run time.
Appearance-Based 3D Gaze Estimation with Personal Calibration

We propose a way to incorporate personal calibration into a deep learning model for video-based gaze estimation. Using our method, we show that by calibrating six parameters per person, accuracy can be improved by a factor of 2.2 to 2.5. The number of personal parameters, three per eye, is similar to the number predicted by geometrical models. When evaluated on the MPIIGaze dataset, our estimator performs better than person-specific estimators. To improve generalization, we predict gaze rays in 3D (origin and direction of gaze). In existing datasets, the 3D gaze is underdetermined, since all gaze targets are in the same plane as the camera. Experiments on synthetic data suggest it would be possible to learn accurate 3D gaze from only annotated gaze targets, without annotated eye positions.
Efficient iris sample data protection using selective JPEG2000 encryption of normalised texture

Biometrie system security requires cryptographic protection of sample data under certain circumstances. We assess low complexity selective encryption schemes applied to JPEG2000 compressed iris data by conducting iris recognition on the selectively encrypted data. This paper specifically investigates the effect of applying the approach to normalised texture data instead of original sample data in order to further reduce the amount of data to be processed (i.e. compressed and encrypted). Result generalisability is facilitated by the employment of four different iris feature extraction schemes and the systematic consideration of three encryption variants. Depending on the applied iris recognition scheme, protection equivalent to full encryption can be achieved when encrypting 1/60–1/12 of the data amount of a full iris sample encoded in a JPEG2000 file.
The Use of Complementary and Alternative Medicine in Children with Type 1 Diabetes Mellitus

The use of complementary and alternative medicine has been increasing in recent years. Complementary and alternative medicine in pediatrics are generally used in children with chronic illness/disabilities. Type 1 Diabetes Mellitus is also one of these chronic diseases. In this study, information on the use of complementary and alternative medicine in children with Type 1 Diabetes Mellitus was presented using scientific evidences. An literature search using the key words, “complementary”, “alternative”, “complementary and alternative medicine”, “integrative medicine”, “children with Type 1 Diabetes Mellitus” was performed by internet search in November-December, 2017 using Google Scholar, Pubmed, Cochrane Library, Science Direct, Web of Science. Researches between 2007-2017 have been included. Descriptive, cross-sectional, randomized controlled, double blind placebo controlled between 2007-2017; child and parent based studies have been examined and 13 studies have been included in the study. Although the studies on the use of complementary and alternative medicine in children with Type 1 Diabetes Mellitus are limited, their use varies between 18% and 56%, their use is affected by sociodemographic characteristics of the children and their parents. It is observed that the most used complementary and alternative medicine in children with Type 1 Diabetes Mellitus are herbal therapies, vitamins/minerals, nutritional/dietary supplements, prayer/spirutual practices, homeopathy and acupuncture. Studies have shown in children that these treatments are not particularly effective at HbA1c levels, that there is limited evidence of benefit-injury assessment, and that children with Type 1 Diabetes Mellitus require further evidence-based clinical trials.
Urocortin-2 Prevents Dysregulation of Ca2+ Homeostasis and Improves Early Cardiac Remodeling After Ischemia and Reperfusion

Aims: Urocortin-2 (Ucn-2) is a potent cardioprotector against Ischemia and Reperfusion (I/R) injuries. However, little is known about its role in the regulation of intracellular Ca2+ concentration ([Ca2+]i) under I/R. Here, we examined whether the addition of Ucn-2 in reperfusion promotes cardioprotection focusing on ([Ca2+]i handling. Methods and Results: Cardiac Wistar rat model of I/R was induced by transient ligation of the left coronary artery and experiments were conducted 1 week after surgery in tissue and adult cardiomyocytes isolated from risk and remote zones. We observed that I/R promoted significant alteration in cardiac contractility as well as an increase in hypertrophy and fibrosis in both zones. The study of confocal [Ca2+]i imaging in adult cardiomyocytes revealed that I/R decreased the amplitude of [Ca2+]i transient and cardiomyocytes contraction in risk and remote zones. Interestingly, intravenous infusion of Ucn-2 before heart’s reperfusion recovered significantly cardiac contractility and prevented fibrosis, but it didn’t affect cardiac hypertrophy. Moreover, Ucn-2 recovered the amplitude of [Ca2+]i transient and modulated the expression of several proteins related to [Ca2+]i homeostasis, such as TRPC5 and Orai1 channels. Using Neonatal Rat Ventricular Myocytes (NRVM) we demonstrated that Ucn-2 blunted I/R-induced Store Operated Ca2+ Entry (SOCE), decreased the expression of TRPC5 and Orai1 as well as their interaction in reperfusion. Conclusion: Our study provides the first evidences demonstrating that Ucn-2 addition at the onset of reperfusion attenuates I/R-induced adverse cardiac remodeling, involving the [Ca2+]i handling and inhibiting the expression and interaction between TRPC5 and Orai1.
A cavity-backed end-fire dipole antenna using SISL technology for 24 GHz automotive anti-collision radar system

This paper presents a cavity-backed dipole antenna based on substrate-integrated suspended line (SISL) platform. By utilizing the double side substrate-integrated suspended line (DSISL) feeding network, the substrate and radiation loss are significantly decreased, thus efficiency of better than 95.50% is achieved. The proposed antenna obtained the measured 10 dB impedance bandwidth of 7.18 GHz, i.e., from 21.75 to 28.93 GHz, which covers the 24.25–26.65 GHz automotive anti-collision radar system band. Moreover, the proposed antenna can be fabricated by conventional printed circuit board (PCB) process, and it can be easily integrated with other planar circuit and applied in the 24-GHz radar system.
Synovial Predictors of Differentiation to Definite Arthritis in Patients With Seronegative Undifferentiated Peripheral Inflammatory Arthritis: microRNA Signature, Histological, and Ultrasound Features

Objectives: To examine synovial tissue (ST) predictors of clinical differentiation in patients with seronegative undifferentiated peripheral inflammatory arthritis (UPIA). Methods: Fourty-two patients with IgA/IgM-Rheumatoid Factor and anti-citrullinated peptide antibodies negative UPIA, naive to Disease-Modifying Anti-Rheumatic Drugs, underwent Gray Scale (GSUS) and power Doppler (PDUS) evaluation and Ultrasound (US) guided ST biopsy. CD68, CD3, CD21, CD20, and CD31 synovial expression was evaluated by immunohistochemistry. Whole ST microRNA expression was assessed using miScript miRNA PCR Array. Peripheral blood (PB) and synovial fluid (SF) IL-6, VEGF-A, and VEGF-D levels were measured by ELISA and ST TNF expression was assessed by RT-PCR. Each patient was prospectively monitored and classified at baseline and within 1 year as UPIA, Rheumatoid Arthritis (RA), Spondyloarthritis (SpA) or Psoriatic Arthritis (PsA), respectively. Results: At baseline, CD68+ cells were the most common cells within the lining layer (p < 0.001) in seronegative UPIA, directly correlating with GSUS (R = 0.36; p = 0.02) and PDUS (R = 0.55; p < 0.001). Synovial CD31+ vessels count directly correlated with GSUS (R = 0.41; p = 0.01) and PDUS (R = 0.52; p < 0.001). During the follow-up, 6 (14.3%) UPIA reached a definite diagnosis (2 RA, 2 SpA and 2 PsA, respectively). At baseline, UPIA who differentiated had higher GSUS (p = 0.01), PDUS scores (p = 0.02) and higher histological scores for CD68+ (p = 0.005 and p = 0.04 for lining and sublining respectively), sublining CD3+ cells (p = 0.002), CD31+ vessels count (p < 0.001) and higher IL-6 PB levels (p = 0.01) than patients who remained as UPIA. MiRNA PCR Array showed that among the 86 tested miRNA species, at baseline, miR-346 and miR-214 were significantly down-regulated (p = 0.02 for both) in ST of UPIA who differentiated than in patients who remained as UPIA, inversely correlating with the lining CD68+ cells IHC score (R = −0.641; p = 0.048) and CD31+ vessels count (R = −0.665; p = 0.036) and with higher baseline ST expression of TNF (p = 0.014). Finally, logistic regression analysis demonstrated that baseline GSUS and PDUS scores ≥1.5 [OR:22.93 (95%CI:0.98–534.30)] and CD31+ vessels count ≥24.3 [OR:23.66 (95%CI:1.50–373.02)] were independent factors associated with the development of definite arthritis. Conclusions: MiRNA signature, histological and US features of ST may help in the identification of seronegative UPIA with high likelihood of clinical differentiation toward definite seronegative arthritis.
Flexible Compensation Strategy for Voltage Source Converter Under Unbalanced and Harmonic Condition Based on a Hybrid Virtual Impedance Method

This paper presents a flexible compensation strategy for voltage source converter (VSC) connected to an unbalanced and harmonic distorted grid, which can achieve flexible tradeoff between the two common control targets, i.e., compensating the voltage at the point of common coupling (PCC), and compensating the output current of the VSC. To achieve the control target, a hybrid virtual impedance method is proposed, which uses both the feedforward of the PCC voltage and the feedback of the output current to develop the harmonic (including the negative sequence) voltage references. Compared with the conventional virtual impedance methods using only feedforward or only feedback, the proposed hybrid method can control the harmonic output impedance of the VSC in a wider range, without the potential overmodulation or instability problems caused by the conventional methods when the desired virtual impedance varies in a wide range. The effectiveness and superiority of the proposed strategy is theoretically analyzed and experimentally verified.
Learning structured sparse representation for single sample face recognition

In this paper, we propose a robust sparse representation method to address single sample per person problem by simultaneously exploiting the local and global structure of data. Considering the fact that most sparse representation methods use each testing sample separately and ignore the prior information from testing data, we seek the sparse representation of all testing samples together to capture the global structure of data. Moreover, we adopt an intra-class variance dictionary to describe various facial changes that can not be captured by the single training sample. To make use of local structure, we divide each face image into some blocks consisting of overlapped patches and assume the overlapped patches in a local block are different samples from the same class, which makes their coefficients have row-wise sparse structure. Finally, by imposing group sparsity constraint and sparsity constraint respectively on the coefficients corresponding to the training patches dictionary and variance dictionary, we obtain more discriminative sparse representation, whose coefficients can be directly utilized for classification. Experimental results on three public databases not only demonstrate effectiveness of the proposed approach but also show robustness to various facial variation.
Gaussian Signalling for Covert Communications

In this paper, we examine the optimality of Gaussian signalling for covert communications with an upper bound on <inline-formula> <tex-math notation="LaTeX">$\mathcal {D}(p_{_{1}}||p_{_{0}})$ </tex-math></inline-formula> or <inline-formula> <tex-math notation="LaTeX">$\mathcal {D}(p_{_{0}}||p_{_{1}})$ </tex-math></inline-formula> as the covertness constraint, where <inline-formula> <tex-math notation="LaTeX">$\mathcal {D}(p_{_{1}}||p_{_{0}})$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\mathcal {D}(p_{_{0}}||p_{_{1}})$ </tex-math></inline-formula> are different due to the asymmetry of Kullback–Leibler divergence, <inline-formula> <tex-math notation="LaTeX">$p_{_{0}}(y)$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$p_{_{1}}(y)$ </tex-math></inline-formula> are the likelihood functions of the observation <inline-formula> <tex-math notation="LaTeX">${y}$ </tex-math></inline-formula> at the warden under the null hypothesis (no covert transmission) and alternative hypothesis (a covert transmission occurs), respectively. Considering additive white Gaussian noise at both the receiver and the warden, we prove that the Gaussian signalling is optimal in terms of maximizing the mutual information of transmitted and received signals for covert communications with an upper bound on <inline-formula> <tex-math notation="LaTeX">$\mathcal {D}(p_{_{1}}||p_{_{0}})$ </tex-math></inline-formula> as the constraint. More interestingly, we also prove that the Gaussian signalling is not optimal for covert communications with an upper bound on <inline-formula> <tex-math notation="LaTeX">$\mathcal {D}(p_{_{0}}||p_{_{1}})$ </tex-math></inline-formula> as the constraint, for which as we explicitly show skew-normal signalling can outperform the Gaussian signalling in terms of achieving higher mutual information. Finally, we prove that, for Gaussian signalling, an upper bound on <inline-formula> <tex-math notation="LaTeX">$\mathcal {D}(p_{_{1}}||p_{_{0}})$ </tex-math></inline-formula> is a tighter covertness constraint in that it leads to lower mutual information than the same upper bound on <inline-formula> <tex-math notation="LaTeX">$\mathcal {D}(p_{_{0}}||p_{_{1}})$ </tex-math></inline-formula>, by proving <inline-formula> <tex-math notation="LaTeX">$\mathcal {D}(p_{_{0}}||p_{_{1}}) \leq \mathcal {D}(p_{_{1}}||p_{_{0}})$ </tex-math></inline-formula>.
Rewards that make you play: The Distinct effect of monetary rewards, virtual points and social rewards on play persistence in substance dependent and non-dependent adolescents

Designers of persuasive games typically apply various types of rewards to increase the player's play persistence and to motivate the player for real world goals such as a behavioral change. In this paper, we tested if different major types of game-rewards resulted in different play persistence behavior. Additionally, we investigated if rewards were suitable to apply in persuasive games within a therapeutic context for substance dependent patients, since people with substance-related disorders have a decreased neurological reward system. In a within-subject experiment, among 20 substance dependent and 25 non-dependent participants, we examined whether play persistence and reward evaluation were affected by three separate types of rewards (monetary rewards, virtual points, and social rewards) and by player type (substance dependent versus non-dependent adolescents). As to type of reward, results showed that participants played longer and evaluated the game more positively when playing for money. As to player type, in contrast to our expectations, both substance dependent and non-dependent participants were equally motivated by rewards. Moreover, the former group was even more motivated by monetary rewards in play persistence than the latter group.
Accurate Uncertainties for Deep Learning Using Calibrated Regression

Methods for reasoning under uncertainty are a key building block of accurate and reliable machine learning systems. Bayesian methods provide a general framework to quantify uncertainty. However, because of model misspecification and the use of approximate inference, Bayesian uncertainty estimates are often inaccurate -- for example, a 90% credible interval may not contain the true outcome 90% of the time. Here, we propose a simple procedure for calibrating any regression algorithm; when applied to Bayesian and probabilistic models, it is guaranteed to produce calibrated uncertainty estimates given enough data. Our procedure is inspired by Platt scaling and extends previous work on classification. We evaluate this approach on Bayesian linear regression, feedforward, and recurrent neural networks, and find that it consistently outputs well-calibrated credible intervals while improving performance on time series forecasting and model-based reinforcement learning tasks.
The Effects of Sinapic Acid on the Development of Metabolic Disorders Induced by Estrogen Deficiency in Rats

Sinapic acid is a natural phenolic acid found in fruits, vegetables, and cereals, exerting numerous pharmacological effects. The aim of the study was to investigate the influence of sinapic acid on biochemical parameters related to glucose and lipid metabolism, as well as markers of antioxidant abilities and parameters of oxidative damage in the blood serum in estrogen-deficient rats. The study was performed on 3-month-old female Wistar rats, divided into 5 groups, including sham-operated control rats, ovariectomized control rats, and ovariectomized rats administered orally with estradiol (0.2 mg/kg) or sinapic acid (5 and 25 mg/kg) for 28 days. The levels of estradiol, progesterone, interleukin 18, insulin, glucose, fructosamine, lipids, and enzymatic and nonenzymatic antioxidants (superoxide dismutase, catalase, and glutathione); total antioxidant capacity; and oxidative damage parameters (thiobarbituric acid-reactive substances, protein carbonyl groups, and advanced oxidation protein products) were determined in the serum. Estradiol counteracted the carbohydrate and cholesterol metabolism disorders induced by estrogen deficiency. Sinapic acid increased the serum estradiol concentration; decreased insulin resistance and the triglyceride and total cholesterol concentrations; and favorably affected the parameters of antioxidant abilities (reduced glutathione, superoxide dismutase) and oxidative damage (advanced oxidation protein products).