Miracle-dz/UniFAR-FTUs huggingface dataset:
Spectral Approaches to Learning Predictive Representations

A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must obtain an accurate environment model, and then plan to maximize reward. However, for complex domains, specifying a model by hand can be a time consuming process. This motivates an alternative approach: learning a model directly from observations. Unfortunately, learning algorithms often recover a model that is too inaccurate to support planning or too large and complex for planning to succeed; or, they require excessive prior domain knowledge or fail to provide guarantees such as statistical consistency. To address this gap, we propose spectral subspace identification algorithms which provably learn compact, accurate, predictive models of partially observable dynamical systems directly from sequences of actionobservation pairs. Our research agenda includes several variations of this general approach: batch algorithms and online algorithms, kernel-based algorithms for learning models in highand infinite-dimensional feature spaces, and manifold-based identification algorithms. All of these approaches share a common framework: they are statistically consistent, computationally efficient, and easy to implement using established matrixalgebra techniques. Additionally, we show that our framework generalizes a variety of successful spectral learning algorithms in diverse areas, including the identification of Hidden Markov Models, recovering structure from motion, and discovering manifold embeddings. We will evaluate our learning algorithms on a series of prediction and planning tasks involving simulated data and real robotic systems. We anticipate several difficulties while moving from smaller problems and synthetic problems to larger practical applications. The first is the challenge of scaling learning algorithms up to the higher-dimensional state spaces that more complex tasks require. The second is the problem of integrating expert knowledge into the learning procedure. The third is the problem of properly accounting for actions and exploration in controlled systems. We believe that overcoming these remaining difficulties will allow our models to capture the essential features of an environment, predict future observations well, and enable successful planning.
A Systematic Review of Sexuality and Depression of Cervical Cancer Patients

Abstract Objectives: The goal of this article is to investigate the correlation between sexuality and depression of cervical cancer (CC) patients. Methods: A bibliographical search was carried out in the databases CINAHL, PubMed, and Cochrane Library with the following terms in English for the years 2006 to 2017: sexuality, sexual function, sexual dysfunction, sexual problems, mood, depression, emotional distress, cervical cancer. Results: Fourteen studies were included. They present heterogeneity in the stage of the disease, the selected treatments, and their sample. From the studies, only 7 are evaluated as good methodologically. Sexual dysfunction and depression of CC patients persist for many years after treatments. The younger women, those who underwent radiotherapy, and those who had chronic fatigue, as an aftereffect of treatments, had increased depression. Women that underwent surgery and adjuvant therapy experienced the highest rates of depressive symptoms. There is a positive relationship between sexuality and depression in patients with CC. Conclusions: Sexuality and depression οf women with CC are affected by their therapies to a significant extent. There is a positive correlation between the two variables. The existing methodologically good studies are scarce, and for this reason the results cannot be generalized in all CC patients.
Group Transference Techniques for the Estimation of the Decoherence Times and Capacities of Quantum Markov Semigroups

Capacities of quantum channels and decoherence times both quantify the extent to which quantum information can withstand degradation by interactions with its environment. However, calculating capacities directly is known to be intractable in general. Much recent work has focused on upper bounding certain capacities in terms of more tractable quantities such as specific norms from operator theory. In the meantime, there has also been substantial recent progress on estimating decoherence times with techniques from analysis and geometry, even though many hard questions remain open. In this article, we introduce a class of continuous-time quantum channels that we called transferred channels, which are built through representation theory from a classical Markov kernel defined on a compact group. In particular, we study two subclasses of such kernels: Hörmander systems on compact Lie-groups and Markov chains on finite groups. Examples of transferred channels include the depolarizing channel, the dephasing channel, and collective decoherence channels acting on $d$ qubits. Some of the estimates presented are new, such as those for channels that randomly swap subsystems. We then extend tools developed in earlier work by Gao, Junge and LaRacuente to transfer estimates of the classical Markov kernel to the transferred channels and study in this way different non-commutative functional inequalities. The main contribution of this article is the application of this transference principle to the estimation of decoherence time, of private and quantum capacities, of entanglement-assisted classical capacities as well as estimation of entanglement breaking times, defined as the first time for which the channel becomes entanglement breaking. Moreover, our estimates hold for non-ergodic channels such as the collective decoherence channels, an important scenario that has been overlooked so far because of a lack of techniques.
Wireless information and power transfer in full-duplex communication systems

This paper considers the problem of maximizing the sum-rate for simultaneous wireless information and power transfer (SWIPT) in a full-duplex bi-directional communication system subject to energy harvesting and transmit power constraints at both nodes. We investigate the optimum design of the receive power splitters and transmit powers for SWIPT in full-duplex mode. Exploiting rate-split method, an iterative algorithm is derived to solve the non-convex problem. The effectiveness of the proposed algorithm is justified through numerical simulations.
Some Useful Sources

A number of commentators have discussed and criticised Esping-Andersen’s original classification. Some of the most important critiques have been related to the misspecification of states, including the Mediterranean countries, Australia, New Zealand, the UK and Japan. Others focus on the neglect of the gender dimension and methodological critiques associated with the decommodification index used by Esping-Andersen.
Using points at infinity for parameter decoupling in camera calibration

The majority of camera calibration methods, including the gold standard algorithm, use point-based information and simultaneously estimate all calibration parameters. In contrast, we propose a novel calibration method that exploits line orientation information and decouples the problem into two simpler stages. We formulate the problem as minimization of the lateral displacement between single projected image lines and their vanishing points. Unlike previous vanishing point methods, parallel line pairs are not required. Additionally, the invariance properties of vanishing points mean that multiple images related by pure translation can be used to increase the calibration data set size without increasing the number of estimated parameters. We compare this method with vanishing point methods and the gold standard algorithm and demonstrate that it has comparable performance.
Spitzer Microlensing Parallax Reveals Two Isolated Stars in the Galactic Bulge

We report the mass and distance measurements of two single-lens events from the 2017 Spitzer microlensing campaign. The ground-based observations yield the detection of finite-source effects, and the microlens parallaxes are derived from the joint analysis of ground-based observations and Spitzer observations. We find that the lens of OGLE-2017-BLG-1254 is a 0.60 ± 0.03 M⊙ star with DLS = 0.53 ± 0.11 kpc, where DLS is the distance between the lens and the source. The second event, OGLE-2017-BLG-1161, is subject to the known satellite parallax degeneracy, and thus is either a star with DLS = 0.40 ± 0.12 kpc or a star with DLS = 0.53 ± 0.19 kpc. Both of the lenses are therefore isolated stars in the Galactic bulge. By comparing the mass and distance distributions of the eight published Spitzer finite-source events with the expectations from a Galactic model, we find that the Spitzer sample is in agreement with the probability of finite-source effects occurring in single-lens events.
The role of electronic health record and “add-on” clinical decision support systems to enhance antimicrobial stewardship programs

Abstract Increasingly, demands are placed on healthcare systems to meet antimicrobial stewardship standards and reporting requirements. This trend, combined with reduced financial and personnel resources, has created a need to adopt information technology (IT) to help ease these burdens and facilitate action. The incorporation of IT into an antimicrobial stewardship program can help improve stewardship intervention efficiencies and facilitate the tracking and reporting of key metrics, including outcomes. This paper provides a review of the stewardship-related functionality within these IT systems, describes how these platforms can be used to improve antimicrobial use, and identifies how they can support current and potential future antimicrobial stewardship regulatory and accreditation standards. Finally, recommendations to help close the gaps in existing systems are provided and suggestions for future areas of development within these programs are delineated.
Calcul de la probabilité d'erreur pour une chaîne de tatouage audionumérique à bruit non gaussien

The considered digital audio watermarking scheme can be viewed as a particular digital communications system, because of the non gaussian additive noise on the one hand, and the weakness of the variable signal to noise ratio on the other hand. The goal of the presented study is to compute the theoritical error probability we can expect, taking into account the system particularities mentioned above. This theoritical study is a preamble for choosing an appropriate channel code for the considered digital audio watermarking system.
Out of the Box: A combined approach for handling occlusion in Human Pose Estimation

Human Pose estimation is a challenging problem, especially in the case of 3D pose estimation from 2D images due to many different factors like occlusion, depth ambiguities, intertwining of people, and in general crowds. 2D multi-person human pose estimation in the wild also suffers from the same problems - occlusion, ambiguities, and disentanglement of people's body parts. Being a fundamental problem with loads of applications, including but not limited to surveillance, economical motion capture for video games and movies, and physiotherapy, this is an interesting problem to be solved both from a practical perspective and from an intellectual perspective as well. Although there are cases where no pose estimation can ever predict with 100% accuracy (cases where even humans would fail), there are several algorithms that have brought new state-of-the-art performance in human pose estimation in the wild. We look at a few algorithms with different approaches and also formulate our own approach to tackle a consistently bugging problem, i.e. occlusions.
GASSER: An Auto-Tunable System for General Sliding-Window Streaming Operators on GPUs

Today’s stream processing systems handle high-volume data streams in an efficient manner. To achieve this goal, they are designed to <italic>scale out</italic> on large clusters of commodity machines. However, despite the efficient use of distributed architectures, they lack support to co-processors like graphical processing units (GPUs) ready to accelerate data-parallel tasks. The main reason for this lack of integration is that GPU processing and the streaming paradigm have different processing models, with GPUs needing a bulk of data present at once while the streaming paradigm advocates a <italic>tuple-at-a-time</italic> processing model. This paper contributes to fill this gap by proposing <monospace>Gasser</monospace>, a system for offloading the execution of <italic>sliding-window operators</italic> on GPUs. The system focuses on completely general functions by targeting the parallel processing of <italic>non-incremental queries</italic> that are not supported by the few existing GPU-based streaming prototypes. Furthermore, <monospace>Gasser</monospace> provides an <italic>auto-tuning approach</italic> able to automatically find the optimal value of the configuration parameters (i.e., batch length and the degree of parallelism) needed to optimize throughput and latency with the given query and data stream. The experimental part assesses the performance efficiency of <monospace>Gasser</monospace> by comparing its peak throughput and latency against Apache <monospace>Flink</monospace>, a popular and scalable streaming system. Furthermore, we evaluate the penalty induced by supporting completely general queries against the performance achieved by the state-of-the-art solution specifically optimized for incremental queries. Finally, we show the speed and accuracy of the auto-tuning approach adopted by <monospace>Gasser</monospace>, which is able to self-configure the system by finding the right configuration parameters without manual tuning by the users.
Dual Role of Interleukin-4 ( IL-4 ) in Pulmonary Paracoccidioidomycosis : Endogenous IL-4 Can Induce Protection or Exacerbation of Disease Depending on the Host Genetic Pattern

10.1128/IAI.72. 7.3932-3940.2004. 2004, 72(7):3932. DOI: Infect. Immun. Franco, Alexandre C. Keller and Vera L. G. Calich F. S. Kashino, Raquel A. Fazioli, Celidéia A. C. Vaz, Marcello Celina Arruda, Rita C. Valente-Ferreira, Adriana Pina, Suely Host Genetic Pattern Exacerbation of Disease Depending on the Endogenous IL-4 Can Induce Protection or Pulmonary Paracoccidioidomycosis: Dual Role of Interleukin-4 (IL-4) in
Functional evaluation of carboxy metabolites of synthetic cannabinoid receptor agonists featuring scaffolds based on L-valine or L-tert-leucine.

Indole- and indazole-based synthetic cannabinoid receptor agonists (SCRAs), featuring valine or tert-leucine substituents, are commonly abused new psychoactive substances (NPS). A major metabolic pathway for these SCRAs is hydrolysis of the terminal amide or methylester functionalities. Although these hydrolysis products were already detected as main ingredients in some "legal highs," these metabolites are often poorly characterized. Here, we report a systematic investigation of the activity of 7 common hydrolysis metabolites of 15 SCRAs featuring scaffolds based on L-valine or L-tert-leucine in direct comparison to their parent compounds. An activity-based cannabinoid receptor 1 (CB1 ) bio-assay was used for activity profiling of SCRAs and their metabolites in a stable HEK293T cell system. The recruitment of β-arrestin2 to the activated CB1 (each fused to one part of a split Nanoluciferase) was provoked by adding the (putative) SCRAs. Luminescence of the functionally complemented luciferase was monitored by a 96-well plate-reader. The major hydrolysis metabolites of 5F-AB-PINACA, ADB-CHMICA, ADB-CHMINACA, ADB-FUBICA, and their methyl- and ethylester derivatives showed no detectable CB1 activation at concentrations up to 1 μM. On the other hand, metabolites of 5F-ADB-PINACA, AB-CHMINACA, and ADB-FUBINACA did retain activity, although significantly reduced as compared to the parent compounds (EC50 values >100 nM). Activity-based characterization of SCRAs and their metabolites at CB1 may not only allow a better insight into the complex interplay between SCRAs and their metabolites in intoxications, but may also allow application of the concept of "activity equivalents" present in biological fluids or, alternatively, in confiscated materials.
CD90/Thy-1, a Cancer-Associated Cell Surface Signaling Molecule

CD90 is a membrane GPI-anchored protein with one Ig V-type superfamily domain that was initially described in mouse T cells. Besides the specific expression pattern and functions of CD90 that were described in normal tissues, i.e., neurons, fibroblasts and T cells, increasing evidences are currently highlighting the possible involvement of CD90 in cancer. This review first provides a brief overview on CD90 gene, mRNA and protein features and then describes the established links between CD90 and cancer. Finally, we report newly uncovered functional connections between CD90 and endoplasmic reticulum (ER) stress signaling and discuss their potential impact on cancer development.
Mantle cell lymphoma: therapeutic options in transplant-ineligible patients

Abstract Management of patients with newly diagnosed mantle cell lymphoma (MCL) depends on the age and fitness of the patient. For younger patients, the commonly accepted standard of care is a high-dose cytarabine-based induction chemotherapy followed by autologous stem cell transplantation (ASCT). In newly diagnosed patients with MCL ineligible for intensive therapy and ASCT, the standard-of-care has generally been R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone), followed by rituximab, maintenance. In recent years, bendamustine-based therapy has been increasingly adopted for older MCL patients and more recently, vincristine has been replaced by bortezomib in the R-CHOP combination as VR-CAP for previously untreated patients. Novel targeted agents now offer more promise than traditional chemotherapy or immunochemotherapy for both previously treated and untreated disease, and should also improve outcomes for older MCL patients. Here, we review standard therapies currently in use and novel agents that may soon be available for MCL patients and particularly for those unsuitable for ASCT.
Ex vivo confocal laser scanning microscopy: An innovative method for direct immunofluorescence of cutaneous vasculitis

Ex vivo confocal laser scanning microscopy (ex vivo CLSM) offers an innovative diagnostic approach through vertical scanning of skin samples with a resolution close to conventional histology. In addition, it enables fluorescence detection in tissues. We aimed to assess the applicability of ex vivo CLSM in the detection of vascular immune complexes in cutaneous vasculitis and to compare its diagnostic accuracy with direct immunofluorescence (DIF) microscopy. Eighty‐two sections of 49 vasculitis patients with relevant DIF microscopy findings were examined using ex vivo CLSM following staining with fluorescent‐labeled IgG, IgM, IgA, C3 and fibrinogen antibodies. DIF microscopy showed immunoreactivity of vessels with IgG, IgM, IgA, C3 and Fibrinogen in 2.0%, 49.9%, 12.2%, 59.2% and 44.9% of the patients, respectively. Ex vivo CLSM detected positive vessels with the same antibodies in 2.0%, 38.8%, 8.2%, 42.9% and 36.7% of the patients, respectively. The detection rate of positive superficial dermal vessels was significantly higher in DIF microscopy as compared to ex vivo CLSM (P < .05). Whereas, ex vivo CLSM identified positive deep dermal vessels more frequently compared to DIF microscopy. In conclusion, ex vivo CLSM could identify specific binding of the antibodies in vessels and showed a comparable performance to conventional DIF microscopy in diagnosing vasculitis.
Performance Evaluation of High-Frequency Mobile Satellite Communications

Communication satellites have a much longer propagation delay than terrestrial communication networks such as cellular or WiFi. In addition, as the carrier frequency moves up, mobile satellite communications show worse performances than the conventional fixed satellite communications. The mobile satellite service (MSS) has not been actively pursued with long latency at high-frequency bands for future applications. In this paper, the adverse impact of long propagation delay in the conventional satellite system is investigated with various user mobility and Doppler-shifted carrier frequency. The satellite network is modeled as a basic delayed feedback channel system and the communication performance is analyzed under delayed channel state information (CSI) for assessing the system feasibility in mobile conditions. The results of performance analysis are provided at high-frequency bands with high-speed user movement, specifically on the outage probability and the channel capacity exploiting three types of channel models: conventional land mobile satellite (LMS) channel models of E. Lutz and C. Loo, and Nakagami fading model. In the circumstance with various user speeds, system performances are evaluated with different propagation delays in the LMS channel models and for line-of-sight (LOS) components in the Nakagami fading. In addition, the conventional models are compared depending on different altitudes for geostationary orbit (GEO), medium earth orbit (MEO), and low earth orbit (LEO) satellites, as well as high-altitude platforms (HAP).
Dynamic Barycenter Averaging Kernel in RBF Networks for Time Series Classification

Radial basis function (RBF) network has been utilized in many applications due to its simple topological structure and strong capacity on function approximation. The core of RBF network is its static kernel function, which is based on the Euclidean distance and cannot obtain good performance for time series classification (TSC) due to the time-shift invariance, complex dynamics, and different length of temporal data.This paper proposed a new temporal kernel, namely, the dynamic barycenter averaging kernel (DBAK) and introduced it into the RBF network. First, we combine k-means clustering with a dynamic time warping (DTW)-based averaging algorithm called DTW barycenter averaging (DBA) to determine the center of DBAK. Then, in order to facilitate the stable gradient-training process in the whole network, a normalization term is added into the kernel formulation. By integrating the information of the whole time warping path, our DBAK-based RBF network performs efficiently for TSC tasks.