Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Unsupervised Cardinality Estimation

Cardinality estimation has long been grounded in statistical tools for density estimation. To capture the rich multivariate distributions of relational tables, we propose the use of a new type of high-capacity statistical model: deep autoregressive models. However, direct application of these models leads to a limited estimator that is prohibitively expensive to evaluate for range or wildcard predicates. To produce a truly usable estimator, we develop a Monte Carlo integration scheme on top of autoregressive models that can efficiently handle range queries with dozens of dimensions or more. Like classical synopses, our estimator summarizes the data without supervision. Unlike previous solutions, we approximate the joint data distribution without any independence assumptions. Evaluated on real-world datasets and compared against real systems and dominant families of techniques, our estimator achieves single-digit multiplicative error at tail, an up to 90x accuracy improvement over the second best method, and is space- and runtime-efficient.
A paradox regarding monogamy of entanglement

In density matrix theory, entanglement is monogamous. However, we show that qubits can be arbitrarily entangled in a different, recently constructed model of qubit entanglement [arXiv:1907.11805]. We illustrate the differences between these two models, analyse how the density matrix property of monogamy of entanglement originates in assumptions of classical correlations in the construction of that model, and explain the counterexample to monogamy in the alternative model. We conclude that monogamy of entanglement is a theoretical assumption, not necessarily a physical property, and discuss how contemporary theory relies on that assumption. The properties of entanglement entropy are very different in the two models; a priori, the entropy in the alternative model is classical.
FILO: FIx-LOcus Recommendation for Problems Caused by Android Framework Upgrade

Dealing with the evolution of operating systems is challenging for developers of mobile apps, who have to deal with frequent upgrades that often include backward incompatible changes of the underlying API framework. As a consequence of framework upgrades, apps may show misbehaviours and unexpected crashes once executed within an evolved environment. Identifying the portion of the app that must be modified to correctly execute on a newly released operating system can be challenging. Although incompatibilities are visibile at the level of the interactions between the app and its execution environment, the actual methods to be changed are often located in classes that do not directly interact with any external element. To facilitate debugging activities for problems introduced by backward incompatible upgrades of the operating system, this paper presents FILO, a technique that can recommend the method that must be changed to implement the fix from the analysis of a single failing execution. FILO can also select key symptomatic anomalous events that can help the developer understanding the reason of the failure and facilitate the implementation of the fix. Our evaluation with multiple known compatibility problems introduced by Android upgrades shows that FILO can effectively and efficiently identify the faulty methods in the apps.
Approximated Orthonormal Normalisation in Training Neural Networks

Generalisation of a deep neural network (DNN) is one major concern when employing the deep learning approach for solving practical problems. In this paper we propose a new technique, named approximated orthonormal normalisation (AON), to improve the generalisation capacity of a DNN model. Considering a weight matrix W from a particular neural layer in the model, our objective is to design a function h(W) such that its row vectors are approximately orthogonal to each other while allowing the DNN model to fit the training data sufficiently accurate. By doing so, it would avoid co-adaptation among neurons of the same layer to be able to improve network-generalisation capacity. Specifically, at each iteration, we first approximate (WW^T)^(-1/2) using its Taylor expansion before multiplying the matrix W. After that, the matrix product is then normalised by applying the spectral normalisation (SN) technique to obtain h(W). Conceptually speaking, AON is designed to turn orthonormal regularisation into orthonormal normalisation to avoid manual balancing the original and penalty functions. Experimental results show that AON yields promising validation performance compared to orthonormal regularisation.
Robust Learning Model-Predictive Control for Linear Systems Performing Iterative Tasks

In this article, a robust learning model-predictive controller (LMPC) for uncertain systems performing iterative tasks is presented. At each iteration of the control task, the closed-loop state, input, and cost are stored and used in the controller design. This article first illustrates how to construct robust control invariant sets and safe control policies exploiting historical data. Then, we propose an iterative LMPC design procedure, where data generated by a robust controller at iteration <inline-formula><tex-math notation="LaTeX">$j$</tex-math></inline-formula> are used to design a robust LMPC at the next iteration <inline-formula><tex-math notation="LaTeX">$j+1$</tex-math></inline-formula>. We show that this procedure allows us to iteratively enlarge the domain of the control policy, and it guarantees recursive constraints satisfaction, input-to-state stability, and performance bounds for the certainty equivalent closed-loop system. The use of different feedback policies along the horizon is the key element of the proposed design. The effectiveness of the proposed control scheme is illustrated on a linear system subject to bounded additive disturbances.
Voice-Face Cross-modal Matching and Retrieval: A Benchmark

Cross-modal associations between voice and face from a person can be learnt algorithmically, which can benefit a lot of applications. The problem can be defined as voice-face matching and retrieval tasks. Much research attention has been paid on these tasks recently. However, this research is still in the early stage. Test schemes based on random tuple mining tend to have low test confidence. Generalization ability of models can not be evaluated by small scale datasets. Performance metrics on various tasks are scarce. A benchmark for this problem needs to be established. In this paper, first, a framework based on comprehensive studies is proposed for voice-face matching and retrieval. It achieves state-of-the-art performance with various performance metrics on different tasks and with high test confidence on large scale datasets, which can be taken as a baseline for the follow-up research. In this framework, a voice anchored L2-Norm constrained metric space is proposed, and cross-modal embeddings are learned with CNN-based networks and triplet loss in the metric space. The embedding learning process can be more effective and efficient with this strategy. Different network structures of the framework and the cross language transfer abilities of the model are also analyzed. Second, a voice-face dataset (with 1.15M face data and 0.29M audio data) from Chinese speakers is constructed, and a convenient and quality controllable dataset collection tool is developed. The dataset and source code of the paper will be published together with this paper.
Magnetic-Assisted Initialization for Infrastructure-free Mobile Robot Localization

Most of the existing mobile robot localization solutions are either heavily dependent on pre-installed infrastructures or having difficulty working in highly repetitive environments which do not have sufficient unique features. To address this problem, we propose a magnetic-assisted initialization approach that enhances the performance of infrastructure-free mobile robot localization in repetitive featureless environments. The proposed system adopts a coarse-to-fine structure, which mainly consists of two parts: magnetic field-based matching and laser scan matching. Firstly, the interpolated magnetic field map is built and the initial pose of the mobile robot is partly determined by the k-Nearest Neighbors (k-NN) algorithm. Next, with the fusion of prior initial pose information, the robot is localized by laser scan matching more accurately and efficiently. In our experiment, the mobile robot was successfully localized in a featureless rectangular corridor with a success rate of 88% and an average correct localization time of 6.6 seconds.
NN Scattering and Nuclear Uncertainties

Ab initio calculations in Nuclear physics for atomic nuclei require a specific knowledge of the interactions among their constituents, protons and neutrons. In particular, NN interactions can be constrained down to scale resolutions of Δr ~ 0.6 fm from the study of phase shifts below the pion production threshold. However, this allows for ambiguities and uncertainties which have an impact on finite nuclei, nuclear- and neutron-matter properties. On the other hand the nuclear many body problem is intrinsically difficult and the computational cost increases with numerical precision and number of nucleons. However, it is unclear what the physical precision should be for these calculations. In this contribution we review much of the work done in Granada to encompass both the uncertainties stemming from the NN scattering database in light nuclei such as triton and alpha particle and the numerical precision required by the solution method.
Reactive dynamics and spectroscopy of hydrogen transfer from neural network-based reactive potential energy surfaces

The ‘in silico’ exploration of chemical, physical and biological systems requires accurate and efficient energy functions to follow their nuclear dynamics at a molecular and atomistic level. Recently, machine learning tools have gained a lot of attention in the field of molecular sciences and simulations and are increasingly used to investigate the dynamics of such systems. Among the various approaches, artificial neural networks (NNs) are one promising tool to learn a representation of potential energy surfaces. This is done by formulating the problem as a mapping from a set of atomic positions x and nuclear charges Zi to a potential energy V(x). Here, a fully-dimensional, reactive neural network representation for malonaldehyde (MA), acetoacetaldehyde (AAA) and acetylacetone (AcAc) is learned. It is used to run finite-temperature molecular dynamics simulations, and to determine the infrared spectra and the hydrogen transfer rates for the three molecules. The finite-temperature infrared spectrum for MA based on the NN learned on MP2 reference data provides a realistic representation of the low-frequency modes and the H-transfer band whereas the CH vibrations are somewhat too high in frequency. For AAA it is demonstrated that the IR spectroscopy is sensitive to the position of the transferring hydrogen at either the OCH- or OCCH3 end of the molecule. For the hydrogen transfer rates it is demonstrated that the O–O vibration (at ∼250 cm−1) is a gating mode and largely determines the rate at which the hydrogen is transferred between the donor and acceptor. Finally, possibilities to further improve such NN-based potential energy surfaces are explored. They include the transferability of an NN-learned energy function across chemical species (here methylation) and transfer learning from a lower level of reference data (MP2) to a higher level of theory (pair natural orbital-LCCSD(T)).
Dental implant survival rate in well-controlled diabetic patients. A systematic review.

Antecedentes: Los implantes dentales se han convertido actualmente en una de las opciones mas populares para sustituir un diente perdido. Por otro lado, la diabetes mellitus es una enfermedad sistemica que afecta a gran parte de la poblacion y es considerada generalmente una contraindicacion absoluta o relativa en la terapia con implantes. Objetivo: Determinar mediante una revision sistematica la tasa de supervivencia de implantes dentales en pacientes diabeticos controlados. Materiales y metodos: Busqueda sistematica en las bases de datos biome­dicas Pubmed, SciELO y RedALyC. Los criterios de seleccion fueron: estudios publicados en los ultimos 10 anos, con al menos 20 pacientes diabeticos controlados, que reporten tasa de supervivencia y numero de implantes colocados, con un seguimiento igual o superior a 1 ano, con un grupo control de pacientes sanos. Se analizo la calidad metodologica de los estudios con las escalas Jadad y CMQ de Downs y Black. Resultados: Se analizaron tres articulos con un seguimiento de entre 1 y 12 anos. La tasa de supervivencia global de los implantes dentales en los pacientes diabeticos controlados fue de un 97.43%. Conclusion: La literatura revisada sugiere que la supervivencia de los implantes dentales en pacientes diabeticos bien controlados es similar a pacientes no diabeticos.
Effect of selected estrogens and progestins on human chromosomes in vitro.

Estradiol ethinyl estradiol mestranol progesterone megestrol acetate dimethisterone norethindrone acetate and chlormadinone acetate were added individually in varied concentrations to cultures of lymphocytes grown from the blood of healthy women in order to test the teratologic and neoplastic possibilities of these agents. Compounds were added to heparinized blood and tested in concentrations of 1-100 mcg/ml. The cells were affixed to slides by an air-dry method and stained with carbolfuchsin. Metaphase spreads were counted. Significant breaks and abnormal forms were absent with all agents. There was some problem in growing cells in compounds of the higher concentrations.
The Association Between Suicide and OIF/OEF Deployment History

Abstract : One of the most important questions in military suicide research at this time is whether deployment in support of Operations Iraqi or Enduring Freedom (OIF/OEF) is associated with an increased risk of suicide. The equivocal research conducted to date on this topic creates a confusing picture for military senior leaders and the American public. The Report of the Blue Ribbon Workgroup on Suicide Prevention in the Veteran Population (Peake, 2008) reviewed this body of literature and concluded that significant limitations and biases in many of the epidemiological approaches conducted to date contribute to the current confusion. The funded study is specifically designed to address many of the recommendations of that report in order to generate seminal results that will fill what is arguably the most important gap in the epidemiological study of military suicide. This collaborative DoD-VA study will utilize multiple enterprise level databases to determine whether a history of deployment in support of OIF/OEF is a risk factor for suicide. In addition, the proposed study will examine the suicide rates of post-deployed National Guard members and Reservists to determine whether these cohorts are at increased risk of suicide. Furthermore, it will examine rates of deaths of undetermined intent in military and civilian populations to determine whether potential misclassifications of deaths may confound military and civilian comparisons of suicide rates. In examining these suicide rates, the funded study will also specifically account for the potential confounding effect of service members who have not completed a full term of service (e.g., because of misconduct, substance abuse, etc.) and thus may be more likely to have risk factors for suicide.
Results of Autopsy 7 Months after Successful Endoluminal Treatment of an Infrarenal Abdominal Aortic Aneurysm

Purpose: To report the results of a postmortem examination in a patient who died of unrelated causes 7 months following endoluminal treatment of an infrarenal abdominal aortic aneurysm (AAA). Methods: As part of an FDA Phase I pilot study, a 73-year-old man underwent successful endoluminal exclusion of an infrarenal AAA using a 9-cm-long endograft (Endovascular Grafting System). Seven months later, he succumbed to complications of a spontaneous esophageal rupture. At autopsy, the aorta was dissected in situ by a vascular surgeon and pathologist before being explanted in order to examine the wound healing characteristics at the aorta-endograft interface. Particular attention was also directed to the hooks composing the attachment system at each end of the endograft. Results: Macroscopic and microscopic examination revealed that the graft had completely excluded the aneurysm sac from the circulation and was incorporated into the aortic wall at the proximal neck and distal cuff. A smooth pannus of endothelial cells covered the proximal end of the endograft at the areas of contact with the aorta, while microscopic examination of the distal end of the graft revealed poorly formed, fibrinous pannus. The neointima deep to the endothelium consisted of a collagenous matrix containing myofibroblasts and histiocytes, providing evidence of healing between the endograft and aorta. Both renal arteries were clear of the proximal end of the endograft, but a previously unrecognized right lower pole renal artery with an extremely caudal origin was excluded from the aortic lumen. Each hook of the attachment system was seen protruding through the adventitia of the aorta. There was no evidence of trauma to the aortic wall or the surrounding tissues caused by these hooks. Conclusion: There appears to be evidence that an endoluminally placed aortic graft may be incorporated by the host aortic tissue.
Cetuximab in combination with single agent daily cisplatin chemotherapy concurrent with radiotherapy in locally advanced nonsmall cell lung carcinoma: A feasibility study

Introduction | Despite the benefits from concurrent chemoradiotherapy (CCRT) regimens in patients with locally advanced non-small cell lung cancer (NSCLC), more efficacious treatment options are needed. Cetuximab, a monoclonal antibody that selectively binds to the epidermal growth factor receptor, has demonstrated activity in patients with metastatic NSCLC. This study assesses whether combining cetuximab with CCRT is feasible. Methods | Patients with inoperable locally advanced NSCLC, received cetuximab (400 mg/m2 on day 1, 250 mg/m2 q1w in weeks 2–6) in addition to radiotherapy (66 Gy in 24 fractions weeks 2–6) and cisplatin (6 mg/m2 q1d during weeks 2–6) daily. Early response was monitored using FDG PET/CT-scans performed 4 weeks after treatment and response was evaluated by CT-scan 6 weeks after the last fraction of radiotherapy. Results | Between March and July 2008, 12 consecutive patients were enrolled. Ten patients completed protocol treatment. Although generally well tolerated, two patients were unable to complete protocol treatment. Acneiform rash and dysphagia were the most common side effects (grade ≤3 according to CTCAE v 3.0). No unexpected toxicities were observed. Early response monitoring revealed a metabolic response in 8 (out of 10) patients. CT-scan evaluation showed a partial response in 8 patients. Four (out of 12) patients showed progressive disease after 12 months of follow up. Conclusions | The addition of cetuximab to CCRT in patients with NSCLC was generally well tolerated and early clinical responses were observed with this new therapy combination. A randomized phase II study comparing CCRT with CCRT and cetuximab is ongoing. 113 Cetuximab in combination with concurrent chemoradiation
Prevalência dos marcadores imunológicos Anti-GAD e Anti-IA2 em parentes de primeiro grau de diabéticos do tipo 1 em amostra da população da Grande São Paulo

BACKGROUND: Increasingly accurate prediction of Type1 Diabetes Mellitus (DM1), based on analysis of autoantibody markers, has become possible in first-degree relatives of patients with diabetes (PDM1). These markers indicate autoimmune process against pancreatic islet beta-cells. Anti-GAD and anti-IA2 are considered predictive of DM1, whose prevalences are considerably variable in different populations studied. There are few data about the frequency of these markers on the Brazilian population. The aim of this study is determine the prevalence of positivity for anti-GAD and for anti-IA2 among DM1 patients first-degree relatives (PDM1) in a sample of the Brazilian population of Great Sao Paulo City. METHODS: Forty-eight children and adolescents PDM1 with median of age of 14.5 years (range 6.7 to 17.9 years). Anti-GAD and anti-IA2 was mesured by radioassay (Kronus®, USA). The cut-off limit for both antibodies was set at the 99th percentile from normal subjects serum samples (anti-GAD: n=194; Median of age=13.4 yrs; range 9.7 to 64 yrs; anti-IA2: n=71; Median of age= 12.6; range 11.1 - 15.2 yrs). A subject was considered to be positive for anti-IA2 if specific binding exceeded the 99th among the analysis of 71 subjects. The limit to positivity was 1.72 U/ml to anti-GAD and 0.97 U/ml to anti-IA2. RESULTS: Five PDM1(10.4%) have showed positivity to anti-GAD, with significantly higher prevalence than controls (P<0.01). The anti-IA2 prevalence rate seems to be equivalent between PDM1 and controls. CONCLUSION: The prevalence of anti-GAD has been more prevalent among the PDM1. No differences were observed between prevalences for anti-IA2 showed by PDM1 and controls.
Repercussões tardias de um programa de reabilitação pulmonar sobre os índices de ansiedade, depressão, qualidade de vida e desempenho físico em portadores de DPOC

OBJECTIVE: To assess the 24-month effects of a pulmonary rehabilitation program (PRP) on anxiety, depression, quality of life and physical performance of COPD patients. METHODS: Thirty patients with COPD (mean age, 60.8 ± 10 years; 70% males) participated in a 12-week PRP, which included 24 physical exercise sessions, 24 respiratory rehabilitation sessions, 12 psychotherapy sessions and 3 educational sessions. All patients were evaluated at baseline (pre-PRP), at the end of the treatment (post-PRP) and two years later (current) by means of four instruments: the Beck Anxiety Inventory; the Beck Depression Inventory; Saint George's Respiratory Questionnaire; and the six-minute walk test (6MWT). RESULTS: The comparison between the pre-PRP and post-PRP values revealed a significant decrease in the levels of anxiety (pre-PRP: 10.7 ± 6.3; post-PRP: 5.5 ± 4.4; p = 0.0005) and depression (pre-PRP: 11.7 ± 6.8; post-PRP: 6.0 ± 5.8; p = 0.001), as well as significant improvements in the distance covered on the 6MWT (pre-PRP: 428.6 ± 75.0 m; post-PRP: 474.9 ± 86.3 m; p = 0.03) and the quality of life index (pre-PRP: 51.0 ± 15.9; post-PRP: 34.7 ± 15.1; p = 0.0001). There were no statistically significant differences between the post-PRP and current evaluation values. CONCLUSIONS: The benefits provided by the PRP in terms of the indices of anxiety, depression and quality of life, as well as the improved 6MWT performance, persisted throughout the 24-month study period.
O impacto odontológico no desempenho diário dos trabalhadores do departamento municipal de limpeza urbana de Porto Alegre, Rio Grande do Sul, Brasil

This study aimed to investigate the prevalence of oral health impact on daily performance in Brazilian adults. 276 civil servants 35 to 44 years of age from the Public Works and Waste Disposal Department of Porto Alegre, in southern Brazil, were interviewed and clinically examined. Oral Impacts on Daily Performance (OIDP) was used to evaluate the impact of oral health status on daily performance. 73.6% of all subjects had at least one daily performance affected by an oral impact in the previous six months. The most commonly affected performance was eating (48.6%), while the most common symptoms were discomfort (40.6%) and dissatisfaction with one's appearance (31.5%). Missing teeth (21.7%) and toothache (20.7%) were recognized as the main causes of oral impacts on daily performance. OIDP was useful for measuring (physically, psychologically, and socially) the oral impacts on daily performance.