Miracle-dz/UniFAR-FTUs huggingface dataset:
A Neural, Interactive-predictive System for Multimodal Sequence to Sequence Tasks

We present a demonstration of a neural interactive-predictive system for tackling multimodal sequence to sequence tasks. The system generates text predictions to different sequence to sequence tasks: machine translation, image and video captioning. These predictions are revised by a human agent, who introduces corrections in the form of characters. The system reacts to each correction, providing alternative hypotheses, compelling with the feedback provided by the user. The final objective is to reduce the human effort required during this correction process. This system is implemented following a client-server architecture. For accessing the system, we developed a website, which communicates with the neural model, hosted in a local server. From this website, the different tasks can be tackled following the interactive–predictive framework. We open-source all the code developed for building this system. The demonstration in hosted in http://casmacat.prhlt. upv.es/interactive-seq2seq.
A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization

Decentralized optimization is a powerful paradigm that finds applications in engineering and learning design. This work studies decentralized composite optimization problems with non-smooth regularization terms. Most existing gradient-based proximal decentralized methods are known to converge to the optimal solution with sublinear rates, and it remains unclear whether this family of methods can achieve global linear convergence. To tackle this problem, this work assumes the non-smooth regularization term is common across all networked agents, which is the case for many machine learning problems. Under this condition, we design a proximal gradient decentralized algorithm whose fixed point coincides with the desired minimizer. We then provide a concise proof that establishes its linear convergence. In the absence of the non-smooth term, our analysis technique covers the well known EXTRA algorithm and provides useful bounds on the convergence rate and step-size.
Functional abilities in aging women with Rett syndrome – the Danish cohort

Abstract Rett syndrome (RTT) is a neurodevelopmental disorder, which mainly affects females and results in multiple disabilities. Many clinical descriptions of the symptoms and functional abilities have been made medically, though mainly in children with RTT. Previous reports have established that even though the syndrome causes severe psychomotor disability, women with RTT can live long into adulthood. Purpose: We aim to describe what to expect from aging women with RTT regarding some of the basic functional abilities that are used in daily activities and that could have an impact on quality of life in these women. Methods: A team of two medical doctors, a physiotherapist and an educational psychological adviser, performed clinical evaluations of 27 women with RTT in Denmark above 30 years of age and confirmed MECP2 mutation. Results: We found that 63% of the women were able to walk outside their homes and only 11% were not able to walk at all. However, 67% could not transfer from sitting to standing position without support. There was profound difficulties communicating, but 85.1% of the women could either consistently point with their hand or eyes to things of their interest. Conclusions: Women with RTT are very dependent on caregivers who maintain and rehabilitate their functional abilities. They can often walk short distances unassisted, but do have trouble transferring and thus getting up from a chair on their own. They have severe problems communicating and they often perform subtle signs that can be difficult to recognize. Implications for rehabilitation 3/4 of aging RTT women are household ambulators – daily training of motor functions and focus on assisting the initiation of movements are needed lifelong to maintain walking ability and participation in daily activities More than half of aging women with RTT can grab on to things – persons with hand function should be motivated to use this ability in the context of eating Communication is a difficult task especially for the aging RTT women – Communicative signs, their meaning and how to react to them should be written down for every woman in an easy accessible way to all caregivers The majority of aging RTT women can point out things of interest – they should be given the opportunity to participate in choice making
Endometriosis as a Comorbid Condition in Chronic Fatigue Syndrome (CFS): Secondary Analysis of Data From a CFS Case-Control Study

Background: Endometriosis (EM) is a recognized co-morbid condition in women with chronic fatigue syndrome (CFS). This analysis evaluates the impact of EM on the health of women with CFS by comparing selected health characteristics and laboratory parameters in women with CFS with and without EM (CFS+EM and CFS-only). Methods: This secondary analysis included all 36 women with CFS from a cross-sectional study of CFS in Wichita, KS, conducted between 2002 and 2003. The health characteristics and laboratory parameters of interest included functioning, fatigue, CFS-related symptoms, gynecologic history, routine laboratory parameters, inflammatory markers, cortisol levels, allostatic load, and sleep parameters (overnight polysomnography). We used parametric or non-parametric tests to compare group differences in the selected health characteristics and laboratory parameters. For examining the association between EM and variables of interest, logistic regression models were performed and odds ratios (OR) with 95% confidence intervals (CI) were reported for the magnitude of associations. Statistical significance was set at 0.05 (two-sided). Results: The mean age of this study sample was 50.9 years. Of women with CFS, 36.1% reported having EM. Age and body mass index (BMI) did not differ between CFS+EM and CFS-only groups. When examining the impact of EM, compared to women with CFS-only, women with both CFS and EM were more likely to report chronic pelvic pain [OR = 9.00 (95% CI, 1.47–55.25)] and hysterectomy [OR = 10.3 (1.82–58.39)], had more CFS symptoms (6.8 ± 0.3 vs. 5.5 ± 0.3, p = 0.02), younger mean age at menopause onset (36.4 ± 3.0 vs. 47.0 ± 2.7 years, p = 0.03), higher mean number of obstructive apnea episodes per hour (20.3 vs. 4.4, p = 0.05) and reported more negative life events (15.8 vs. 4.4, p = 0.05). Other parameters did not differ significantly between the two groups. Conclusions: We found more than a third of women with CFS reported endometriosis as a comorbid condition. The endometriosis comorbidity was associated with chronic pelvic pain, earlier menopause, hysterectomy, and more CFS-related symptoms. However, endometriosis in women with CFS did not appear to further impact functioning, fatigue, inflammatory markers, or other laboratory parameters. Further investigations including younger women are warranted.
Lyapunov Exponent of Rank One Matrices: Ergodic Formula and Inapproximability of the Optimal Distribution

The Lyapunov exponent corresponding to a set of square matrices $\mathcal{A} = \left\{ {{A_1}, \ldots ,{A_n}} \right\}$ and a probability distribution p over {1,…,n} is $\lambda (\mathcal{A},p): = {\lim _{k \to \infty }}\frac{1}{k}\mathbb{E}\log \left\| {{A_{{\sigma _k}}} \cdots {A_{{\sigma _2}}}{A_{{\sigma _1}}}} \right\|$, where σi are i.i. d. according to p. This quantity is of fundamental importance to control theory since it determines the asymptotic convergence rate${e^{\lambda (\mathcal{A},p)}}$ of the stochastic linear dynamical system ${x_{k + 1}} = {A_{{\sigma _k}}}{x_k}$. This paper investigates the following "design problem": given $\mathcal{A}$, compute the distribution p minimizing $\lambda (\mathcal{A},p)$. Our main result is that it is NP-hard to decide whether there exists a distribution p for which $\lambda (\mathcal{A},p) < 0$, i.e. it is NP-hard to decide whether this dynamical system can be stabilized.This hardness result holds even in the "simple" case where $\mathcal{A}$ contains only rank-one matrices. Somewhat surprisingly, this is in stark contrast to the Joint Spectral Radius – the deterministic kindred of the Lyapunov exponent – for which the analogous optimization problem over switching rules is known to be exactly computable in polynomial time for rank-one matrices.To prove this hardness result, we first observe that the Lyapunov exponent of rank-one matrices admits a simple formula and in fact is a quadratic form in p. Hardness of the design problem is shown through a reduction from the Independent Set problem. Along the way, simple examples are given illustrating that $p \mapsto \lambda (\mathcal{A},p)$ is neither convex nor concave in general, and a connection is made to the fact that the Martin distance on the (1,n) Grassmannian is not a metric
Non-convex functionals penalizing simultaneous oscillations along independent directions: rigidity estimates

We study a family of non-convex functionals $\{\mathcal{E}\}$ on the space of measurable functions$u: \Omega_1\times\Omega_2 \subset \mathbb{R}^{n_1}\times\mathbb{R}^{n_2} \to \mathbb{R}$. These functionals vanish on the non-convex subset $S(\Omega_1\times\Omega_2)$ formed by functions of the form $u(x_1,x_2)=u_1(x_1)$ or $u(x_1,x_2)=u_2(x_2)$. We investigate under which conditions the converse implication "$\mathcal{E}(u) = 0 \Rightarrow u \in S(\Omega_1\times\Omega_2)$" holds. In particular, we show that the answer depends strongly on the smoothness of u. We also obtain quantitative versions of this implication by proving that (at least for some parameters) $\mathcal{E}(u)$ controls in a strong sense the distance of $u$ to $S(\Omega_1\times\Omega_2)$.
A hydrodynamic model for synchronization phenomena

We present a new hydrodynamic model for synchronization phenomena which is a type of pressureless Euler system with nonlocal interaction forces. This system can be formally derived from the Kuramoto model with inertia, which is a classical model of interacting phase oscillators widely used to investigate synchronization phenomena, through a kinetic description under the mono-kinetic closure assumption. For the proposed system, we first establish local-in-time existence and uniqueness of classical solutions. For the case of identical natural frequencies, we provide synchronization estimates under suitable assumptions on the initial configurations. We also analyze critical thresholds leading to finite-time blow-up or global-in-time existence of classical solutions. In particular, our proposed model exhibits the finite-time blow-up phenomenon, which is not observed in the classical Kuramoto models, even with a smooth distribution function for natural frequencies. Finally, we numerically investigate synchronization, finite-time blow-up, phase transitions, and hysteresis phenomena.
No-boarding buses: Synchronisation for efficiency

We investigate a no-boarding policy in a system of N buses serving M bus stops in a loop, which is an entrainment mechanism to keep buses synchronised in a reasonably staggered configuration. Buses always allow alighting, but would disallow boarding if certain criteria are met. For an analytically tractable theory, buses move with the same natural speed (applicable to programmable self-driving buses), where the average waiting time experienced by passengers waiting at the bus stop for a bus to arrive can be calculated. The analytical results show that a no-boarding policy can dramatically reduce the average waiting time, as compared to the usual situation without the no-boarding policy. Subsequently, we carry out simulations to verify these theoretical analyses, also extending the simulations to typical human-driven buses with different natural speeds based on real data. Finally, a simple general adaptive algorithm is implemented to dynamically determine when to implement no-boarding in a simulation for a real university shuttle bus service.
On Selecting Stable Predictors in Time Series Models

We extend the feature selection methodology to dependent data and propose a novel time series predictor selection scheme that accommodates statistical dependence in a more typical i.i. d sub-sampling based framework. Furthermore, the machinery of mixing stationary processes allows us to quantify the improvements of our approach over any base predictor selection method (such as lasso) even in a finite sample setting. Using the lasso as a base procedure we demonstrate the applicability of our methods to simulated and several real time series datasets.
Limitations and Biases in Facial Landmark Detection - An Empirical Study on Older Adults with Dementia

Accurate facial expression analysis is an essential step in various clinical applications that involve physical and mental health assessments of older adults (e.g. diagnosis of pain or depression). Although remarkable progress has been achieved toward developing robust facial landmark detection methods, state-of-the-art methods still face many challenges when encountering uncontrolled environments, different ranges of facial expressions, and different demographics of the population. A recent study has revealed that the health status of individuals can also affect the performance of facial landmark detection methods on front views of faces. In this work, we investigate this matter in a much greater context using seven facial landmark detection methods. We perform our evaluation not only on frontal faces but also on profile faces and in various regions of the face. Our results shed light on limitations of the existing methods and challenges of applying these methods in clinical settings by indicating: 1) a significant difference between the performance of state-of-the-art when tested on the profile or frontal faces of individuals with vs. without dementia; 2) insights on the existing bias for all regions of the face; and 3) the presence of this bias despite re-training/fine-tuning with various configurations of six datasets.
Neutrinoless double beta decay in effective field theory

We discuss the contributions of lepton-number-violating sources to neutrinoless double beta decay ($0\nu\beta\beta$). Assuming that these sources arise at scales well above the electroweak scale, they can be described within an effective field theory. Here, we outline the steps required to express the $0\nu\beta\beta$ half-life in terms of the effective interactions, focusing on the dimension-five operator that induces a Majorana mass for the neutrinos. This process involves the evolution of the operators down to scales of a few GeV where they can be matched onto Chiral Perturbation Theory. The resulting Chiral Lagrangian can then used be to derive the lepton-number violating potential, which, in combination with many-body methods, gives the $0\nu\beta\beta$ half-life. We will show that consistent renormalization requires the inclusion of a new contact interaction at leading order in this potential. We also briefly comment on the constraints that can be set on the operators appearing beyond dimension five.
Orbit equivalence for nilpotent Cantor actions.

We show that an action of a finitely-generated group G' on a Cantor space, which is continuously orbit equivalent to minimal equicontinuous action of a finitely-generated nilpotent group, must itself be a minimal equicontinuous action, and if the action of G' is effective, then G' is virtually nilpotent.
Phenotypic performance of transgenic potato (Solanum tuberosum L.) plants with pyramided rice cystatin genes (OCI and OCII)

The evaluation of transgenic plants which is usually carried out under controlled conditions in culture rooms and greenhouses can yield valuable information about the influence of introduced genes on a transgenic plant phenotype. However, an overall assessment of plant performance can only be made by testing transgenic plants in the field environment. Thus, the effects of pyramided rice cystatin genes OCI and OCII on morphological parameters of transgenic potato cv. Desiree, Dragacevka and Jelica lines were compared under in vitro, greenhouse, and field conditions. All analyzed OC co-expressing transgenic lines exhibited normal phenotype, both in vitro and in greenhouse conditions. In the field environment, eight of nine OCI/OCII lines were similar to the wild-type control plants in their general phenotypic appearance. Yield parameters, such as tuber number and tuber weight for these phenotypically normal OCI/OCII lines, were also comparable to the controls. Only transgenic cv. Jelica line 4 plants exhibited slightly reduced growth, atypical leaf morphology and, contrary to the plants of other transgenic lines and untransformed controls, failed to flower. However, despite the phenotypic and developmental changes under field conditions, the OCI/OCII Jelica line 4 did not exhibit a significant decrease in tuber yield. Stacking of OCI and OCII genes preserves important attributes of the parental lines, confirming that this approach could be suitable for improving agronomical traits in potato. [Projekat Ministarstva nauke Republike Srbije, br. ON173015]
Kármán vortex street in incompressible fluid models

This paper aims to provide a robust model for the well-known phenomenon of Kármán vortex street arising in fluid mechanics. The first theoretical attempt to model this pattern was given by von Kármán (1991 Göttinger Nachr., Math. Phys. Kl. 509–17); von Kármán (1912 Göttinger Nachr., Math. Phys. Kl. 547–56). He considered two parallel staggered rows of point vortices, with opposite strength, that translate at the same speed. Following the ideas of Saffman and Schatzman (1981 SIAM J. Sci. Stat. Comput. 2 285–95), we propose to study this phenomenon in the Euler equations by considering two infinite arrows of vortex patches. The key idea is to desingularize the point vortex model proposed by von Kármán. Our construction is flexible and can be extended to more general incompressible models.
Effects of exercise on fitness and cognition in progressive MS: a randomized, controlled pilot trial

Background: Exercise may have beneficial effects on both well-being and walking ability in multiple sclerosis (MS). Exercise is shown to be neuroprotective in rodents and may also enhance cognitive function in humans. It may, therefore, be particularly useful for MS patients with pronounced neurodegeneration. Objective: To investigate the potential of standardized exercise as a therapeutic intervention for progressive MS, in a randomized-controlled pilot trial. Methods: Patients with progressive MS and moderate disability (Expanded Disability Status Scale (EDSS) of 4–6) were randomized to one of three exercise interventions (arm ergometry, rowing, bicycle ergometry) for 8–10 weeks or a waitlist control group. We analyzed the drop-out rate as a measure of feasibility. The primary endpoint of the study was aerobic fitness. Secondary endpoints were walking ability, cognitive function as measured by a neuropsychological test battery, depression and fatigue. Results: A total of 42 patients completed the trial (10.6% drop-out rate). Significant improvements were seen in aerobic fitness. In addition, exercise improved walking ability, depressive symptoms, fatigue and several domains of cognitive function. Conclusion: This study indicated that aerobic training is feasible and could be beneficial for patients with progressive MS. Larger exercise studies are needed to confirm the effect on cognition. Trial Registration: ISRCTN (trial number 76467492) http://isrctn.org
The $q$-multiple gamma functions of Barnes-Milnor type

The multiple gamma functions of BM (Barnes-Milnor) type and the $q$-multiple gamma functions have been studied independently. In this paper, we introduce a new generalization of the multiple gamma functions called the $q$-BM multiple gamma function including those functions and prove some properties the BM multiple gamma functions satisfy for them.
Efficacy and safety of certolizumab pegol induction therapy in an unselected Crohn's disease population: Results of the FACTS survey†

Background: Switzerland was the first country to approve certolizumab pegol (Cimzia, CZP) for the treatment of patients with moderate to severe Crohn's disease (CD) in September 2007. This phase IV study aimed to evaluate the efficacy and safety of CZP in a Swiss multicenter cohort of practice‐based patients. Methods: Baseline and Week 6 evaluation questionnaires were sent to all Swiss gastroenterologists in hospitals and private practices. Disease activity was assessed with the Harvey–Bradshaw Index (HBI) and adverse events were evaluated according to WHO guidelines. Results: Fifty patients (31 women, 19 men) were included; 56% had complicated disease (stricture or fistula) and 52% had undergone prior CD‐related surgery. All patients had prior exposure to systemic steroids, 96% to immunomodulators, 78% to infliximab, and 50% to adalimumab. A significant decrease in HBI was observed at Week 6 (versus Week 0) following induction therapy with CZP 400 mg subcutaneously at Weeks 0, 2, and 4 (12.6 ± 4.7 Week 0 versus 6.2 ± 4.4 Week 6, P < 0.001). Response and remission rates at Week 6 were 54% and 40%, respectively. We identified 8/11 CD patients undergoing a 50% fistula response (P = 0.021). The frequency of adverse drug reactions attributed to CZP was 6%. CZP was continued in 80% of patients beyond Week 6. Conclusions: In a population of CD patients with complicated disease behavior, CZP induced a response and remission in 54% and 40% of patients, respectively. This series provides the first evidence of the effectiveness of CZP in perianal fistulizing CD. Inflamm Bowel Dis 2010
Semi-Supervised Monocular Depth Estimation with Left-Right Consistency Using Deep Neural Network

There has been tremendous research progress in estimating the depth of a scene from a monocular camera image. Existing methods for single-image depth prediction are exclusively based on deep neural networks, and their training can be unsupervised using stereo image pairs, supervised using LiDAR point clouds, or semi-supervised using both stereo and LiDAR. In general, semi-supervised training is preferred as it does not suffer from the weaknesses of either supervised training, resulting from the difference in the cameras and the LiDARs field of view, or unsupervised training, resulting from the poor depth accuracy that can be recovered from a stereo pair. In this paper, we present our research in single-image depth prediction using semi-supervised training that outperforms the state-of-the-art. We achieve this through a loss function that explicitly exploits left-right consistency in a stereo reconstruction, which has not been adopted in previous semi-supervised training. In addition, we describe the correct use of ground truth depth derived from LiDAR that can significantly reduce prediction error. The performance of our depth prediction model is evaluated on popular datasets, and the importance of each aspect of our semi-supervised training approach is demonstrated through experimental results. Our deep neural network model has been made publicly available.1.