Miracle-dz/UniFAR-FTUs huggingface dataset:
The Active Sulfate-Reducing Microbial Community in Littoral Sediment of Oligotrophic Lake Constance

Active sulfate-reducing microorganisms (SRM) in freshwater sediments are under-examined, despite the well-documented cryptic sulfur cycle occurring in these low-sulfate habitats. In Lake Constance sediment, sulfate reduction rates of up to 1,800 nmol cm-3 day-1 were previously measured. To characterize its SRM community, we used a tripartite amplicon sequencing approach based on 16S rRNA genes, 16S rRNA, and dsrB transcripts (encoding the beta subunit of dissimilatory sulfite reductase). We followed the respective amplicon dynamics in four anoxic microcosm setups supplemented either with (i) chitin and sulfate, (ii) sulfate only, (iii) chitin only, or (iv) no amendment. Chitin was used as a general substrate for the whole carbon degradation chain. Sulfate turnover in sulfate-supplemented microcosms ranged from 38 to 955 nmol day-1 (g sediment f. wt.)-1 and was paralleled by a decrease of 90–100% in methanogenesis as compared to the respective methanogenic controls. In the initial sediment, relative abundances of recognized SRM lineages accounted for 3.1 and 4.4% of all bacterial 16S rRNA gene and 16S rRNA sequences, respectively. When normalized against the 1.4 × 108 total prokaryotic 16S rRNA gene copies as determined by qPCR and taking multiple rrn operons per genome into account, this resulted in approximately 105–106 SRM cells (g sediment f. wt.)-1. The three amplicon approaches jointly identified Desulfobacteraceae and Syntrophobacteraceae as the numerically dominant and transcriptionally most active SRM in the initial sediment. This was corroborated in the time course analyses of sulfate-consuming sediment microcosms irrespective of chitin amendment. Uncultured dsrAB family-level lineages constituted in sum only 1.9% of all dsrB transcripts, with uncultured lineage 5 and 6 being transcriptionally most active. Our study is the first holistic molecular approach to quantify and characterize active SRM including uncultured dsrAB lineages not only in Lake Constance but for lake sediments in general.
The Phi measure of integrated information is not well-defined for general physical systems

According to the integrated information theory of consciousness (IIT), consciousness is a fundamental observer-independent property of physical systems, and the measure Φ (Phi) of integrated information is identical to the quantity or level of consciousness. For this to be plausible, there should be no alternative formulae for Φ consistent with the axioms of IIT, and there should not be cases of Φ being ill-defined. This article presents three ways in which Φ, in its current formulation, fails to meet these standards, and discusses how this problem might be addressed.
Mechanical Properties of Bamboo Through Measurement of Culm Physical Properties for Composite Fabrication of Structural Concrete Reinforcement

Bamboo fibers with high mechanical properties can be a sustainable alternative to synthetic fibers for application in fiber reinforced polymer composites. The first aim of this study is to evaluate the dependence of mechanical properties of Dendrocalamus asper, known as bamboo Petung from Indonesia, on physical properties of the culm, including culm diameter, wall thickness, height, moisture content and specific density. Correlations between mechanical properties including tensile strength, modulus of rupture and modulus of elasticity in flexure and tension and culm physical properties have been studied. The results demonstrate that specific density is directly correlated with all these mechanical properties of bamboo while the moisture content values are correlated only with value of modules of rupture. Although wall thicknesses value of the culm are correlated with all of the mechanical properties studied, the culm diameter was only correlated with modulus of rupture and modulus of elasticity in flexure. Therefore, measurements of the culm geometry and specific density of raw bamboo have the potential for rapid, non-destructive evaluations of the quality of the bamboo, particularly in nurseries and forests where there is limited access to testing facilities. The second aim of this study is to evaluate whether such tests allow for an evaluation of the mechanical potential of the bamboo for production of high performance bamboo fiber reinforced polymer composites. Use of these formulas is illustrated through a case study of bamboo composite reinforcement for structural concrete. Pull-out tests and beam testing using this composite successfully validate the usefulness of this strategy for sustainable construction.
Aggregated Learning: A Deep Learning Framework Based on Information-Bottleneck Vector Quantization

Based on the notion of information bottleneck (IB), we formulate a quantization problem called "IB quantization". We show that IB quantization is equivalent to learning based on the IB principle. Under this equivalence, the standard neural network models can be viewed as scalar (single sample) IB quantizers. It is known, from conventional rate-distortion theory, that scalar quantizers are inferior to vector (multi-sample) quantizers. Such a deficiency then inspires us to develop a novel learning framework, AgrLearn, that corresponds to vector IB quantizers for learning with neural networks. Unlike standard networks, AgrLearn simultaneously optimizes against multiple data samples. We experimentally verify that AgrLearn can result in significant improvements when applied to several current deep learning architectures for image recognition and text classification. We also empirically show that AgrLearn can reduce up to 80% of the training samples needed for ResNet training.
Continued Decay of HIV Proviral DNA Upon Vaccination With HIV-1 Tat of Subjects on Long-Term ART: An 8-Year Follow-Up Study

Introduction: Tat, a key HIV virulence protein, has been targeted for the development of a therapeutic vaccine aimed at cART intensification. Results from phase II clinical trials in Italy (ISS T-002) and South Africa (ISS T-003) indicated that Tat vaccination promotes increases of CD4+ T-cells and return to immune homeostasis while reducing the virus reservoir in chronically cART-treated patients. Here we present data of 92 vaccinees (59% of total vaccinees) enrolled in the ISS T-002 8-year extended follow-up study (ISS T-002 EF-UP, ClinicalTrials.gov NCT02118168). Results: Anti-Tat antibodies (Abs) induced upon vaccination persisted for the entire follow-up in 34/92 (37%) vaccinees, particularly when all 3 Ab classes (A/G/M) were present (66% of vaccinees), as most frequently observed with Tat 30 μg regimens. CD4+ T cells increased above study-entry levels reaching a stable plateau at year 5 post-vaccination, with the highest increase (165 cells/μL) in the Tat 30 μg, 3 × regimen. CD4+ T-cell increase occurred even in subjects with CD4+ nadir ≤ 250 cells/uL and in poor immunological responders and was associated with a concomitant increase of the CD4+/CD8+ T-cell ratio, a prognostic marker of morbidity/mortality inversely related to HIV reservoir size. Proviral DNA load decreased over time, with a half-life of 2 years and an estimated 90% reduction at year 8 in the Tat 30 μg, 3 × group. In multivariate analysis the kinetic and amplitude of both CD4+ T-cell increase and proviral DNA reduction were fastest and highest in subjects with all 3 anti-Tat Ab classes and in the 30 μg, 3 × group, irrespective of drug regimens (NNRTI/NRTI vs. PI). HIV proviral DNA changes from baseline were inversely related to CD4+/CD8+ T-cell ratio and CD4+ T-cell changes, and directly related to the changes of CD8+ T cells. Further, HIV DNA decay kinetics were inversely related to the frequency and levels of intermittent viremia. Finally, Tat vaccination was similarly effective irrespective of the individual immunological status or HIV reservoir size at study entry. Conclusions: Tat immunization induces progressive immune restoration and reduction of virus reservoirs above levels reached with long-term cART, and may represent an optimal vaccine candidate for cART intensification toward HIV reservoirs depletion, functional cure, and eradication strategies.
A Multiple Granular Cascaded Model of Object Tracking Under Surveillance Videos

Object tracking is one of the most important components in numerous applications of computer vision, and much progress has been made in recent years with efforts on sharing code and datasets. In this paper, we propose a multiple granular cascaded model of object tracking under surveillance video. For frames in surveillance video, we analyze the frames from different granularity levels. At the coarse level, we utilize Gaussian mixture model combined with a three-frame difference method to extract the foreground region of the frame. At the fine level, a cascaded multi-source feature fusion method is used to classify the region proposal and obtain the location of the target. Finally, we propose some optimization strategies for the online tracker updating. We conduct several comparative experiments on actual surveillance video. Experimental results demonstrate that the proposed model is able to obtain excellent results in practice.
NAIL: A General Interactive Fiction Agent

Interactive Fiction (IF) games are complex textual decision making problems. This paper introduces NAIL, an autonomous agent for general parser-based IF games. NAIL won the 2018 Text Adventure AI Competition, where it was evaluated on twenty unseen games. This paper describes the architecture, development, and insights underpinning NAIL's performance.
A Smart Sliding Chinese Pinyin Input Method Editor for Touchscreen Devices

This paper presents a smart sliding Chinese pinyin Input Method Editor (IME) for touchscreen devices which allows user finger sliding from one key to another on the touchscreen instead of tapping keys one by one, while the target Chinese character sequence will be predicted during the sliding process to help the user entering Chinese sequences. Moreover, the layout of the virtual keyboard of our IME adapts to user sliding for more efficient inputting. The layout adaption process is utilized with Recurrent Neural Networks (RNN) and deep reinforcement learning and the pinyin-to-character converter is implemented with a sequence-to-sequence (Seq2Seq) model to predict the target Chinese sequence. A sliding simulator is built to automatically produce sliding samples for model training and virtual keyboard test. The key advantage of our IME is that nearly all its built-in tactics can be optimized automatically with deep learning algorithms on user behavior data, and the empirical studies verifies the effectiveness of the proposed model.
Text Classification of Micro-blog's "Tree Hole" Based on Convolutional Neural Network

Rapid recognition of depression is an important step in the research of depression. With the development of social networking platform, more and more depressive patients regard micro-blog as one of the ways of self-expression. And this information provides support of data for the recognition of depression. In this study, the data crawled from micro-blog's "tree hole"[1] is used as experimental corpus. Combined with the features of micro-blog text with depression, a double-input convolutional neural network structure (D-CNN) is proposed. This method takes both the external features and the semantic features of text as input. By comparing the accuracy of classification with Support Vector Machine (SVM) and convolutional neural network (CNN) algorithm, it is finally shown that the D-CNN can further improve the accuracy of text classify.
Learning what you can do before doing anything

Intelligent agents can learn to represent the action spaces of other agents simply by observing them act. Such representations help agents quickly learn to predict the effects of their own actions on the environment and to plan complex action sequences. In this work, we address the problem of learning an agent's action space purely from visual observation. We use stochastic video prediction to learn a latent variable that captures the scene's dynamics while being minimally sensitive to the scene's static content. We introduce a loss term that encourages the network to capture the composability of visual sequences and show that it leads to representations that disentangle the structure of actions. We call the full model with composable action representations Composable Learned Action Space Predictor (CLASP). We show the applicability of our method to synthetic settings and its potential to capture action spaces in complex, realistic visual settings. When used in a semi-supervised setting, our learned representations perform comparably to existing fully supervised methods on tasks such as action-conditioned video prediction and planning in the learned action space, while requiring orders of magnitude fewer action labels. Project website: this https URL
Bayesian Online Detection and Prediction of Change Points

Online detection of instantaneous changes in the generative process of a data sequence generally focuses on retrospective inference of such change points without considering their future occurrences. We extend the Bayesian Online Change Point Detection algorithm to also infer the number of time steps until the next change point (i.e., the residual time). This enables us to handle observation models which depend on the total segment duration, which is useful to model data sequences with temporal scaling. In addition, we extend the model by removing the i.i. d. assumption on the observation model parameters. The resulting inference algorithm for segment detection can be deployed in an online fashion, and we illustrate applications to synthetic and to two medical real-world data sets.
Caracterização mecânica, térmica e acústica de um compósito que utiliza rejeitos de mármore, granito e EPS para a fabricação de blocos para a construção civil

A utilizacao de materiais compositos para a construcao civil tem sido tema de inumeros trabalhos cientificos no Brasil e no mundo. Um dos fatores que motivam essa busca e o deficit habitacional que os paises principalmente do terceiro mundo enfrentam. No Brasil esse deficit alcanca mais de 6,5 milhoes de moradias, em torno de 12% dos domicilios do pais. Esse trabalho apresenta um composito que foi obtido a partir de residuos gerados nos processos de obtencao de placas de granito e marmore, cimento, gesso, areia, EPS triturado e agua. Esses residuos causam grandes danos ao meio ambiente e sao jogados em aterros em grandes quantidades. O ineditismo do trabalho esta no estudo combinado termico, mecânico e acustica do composito obtido, em situacao real, de comodos que fazem parte de uma habitacao experimental. Foram confeccionados diversos blocos a partir de composicoes variadas e foram efetuados testes preliminares de resistencia mecânica e termica, escolhendo-se a proporcao mais apropriada. Serao apresentados os processos de fabricacao e montagem dos blocos produzidos, em numero de 500, para a fabricacao de uma residencia experimental. Estudou-se qual o tipo de bloco e de residuo, marmore ou granito, apresentou-se mais viavel para o fim proposto. A resistencia mecânica dos blocos produzidos esteve acima de 3,0 MPa. A resistencia termica dos blocos foi comprovada pela diferenca maxima entre as paredes interna e externa dos comodos edificados em torno 8,0 °C. A absorcao acustica para o comodo mais eficiente ficou em torno 31. Demonstrou-se a viabilidade de utilizacao dos blocos fabricados com o material composito proposto para a construcao civil.
Comprehensive analysis of lncRNA-associated competing endogenous RNA network in tongue squamous cell carcinoma

Background Increasing evidence has demonstrated that long non-coding RNAs (lncRNAs) play an important role in the competitive endogenous RNA (ceRNA) networks in that they regulate protein-coding gene expression by sponging microRNAs (miRNAs). However, the understanding of the ceRNA network in tongue squamous cell carcinoma (TSCC) remains limited. Methods Expression profile data regarding mRNAs, miRNAs and lncRNAs as well as clinical information on 122 TSCC tissues and 15 normal controls from The Cancer Genome Atlas (TCGA) database were collected. We used the edgR package to identify differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs) and miRNAs (DEmiRNAs) between TSCC samples and normal samples. In order to explore the functions of DEmRNAs, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed. Subsequently, a ceRNA network was established based on the identified DElncRNAs–DEmiRNAs and DEmiRNAs–DEmRNAs interactions. The RNAs within the ceRNA network were analyzed for their correlation with overall disease survival. Finally, lncRNAs were specifically analyzed for their correlation with clinical features in the included TSCC patient samples. Results A total of 1867 mRNAs, 828 lncRNAs and 81 miRNAs were identified as differentially expressed in TSCC tissues (—log 2fold change— ≥ 2; adjusted P value <0.01). The resulting ceRNA network included 16 mRNAs, 56 lncRNAs and 6 miRNAs. Ten out of the 56 lncRNAs were found to be associated with the overall survival in TSCC patients (P < 0.05); 10 lncRNAs were correlated with TSCC progression (P < 0.05). Conclusion Our study deepens the understanding of ceRNA network regulatory mechanisms in TSCC. Furthermore, we identified ten lncRNAs (PART1, LINC00261, AL163952.1, C2orf48, FAM87A, LINC00052, LINC00472, STEAP3-AS1, TSPEAR-AS1 and ERVH48-1) as novel, potential prognostic biomarkers and therapeutic targets for TSCC.
kuenm: an R package for detailed development of ecological niche models using Maxent

Background Ecological niche modeling is a set of analytical tools with applications in diverse disciplines, yet creating these models rigorously is now a challenging task. The calibration phase of these models is critical, but despite recent attempts at providing tools for performing this step, adequate detail is still missing. Here, we present the kuenm R package, a new set of tools for performing detailed development of ecological niche models using the platform Maxent in a reproducible way. Results This package takes advantage of the versatility of R and Maxent to enable detailed model calibration and selection, final model creation and evaluation, and extrapolation risk analysis. Best parameters for modeling are selected considering (1) statistical significance, (2) predictive power, and (3) model complexity. For final models, we enable multiple parameter sets and model transfers, making processing simpler. Users can also evaluate extrapolation risk in model transfers via mobility-oriented parity (MOP) metric. Discussion Use of this package allows robust processes of model calibration, facilitating creation of final models based on model significance, performance, and simplicity. Model transfers to multiple scenarios, also facilitated in this package, significantly reduce time invested in performing these tasks. Finally, efficient assessments of strict-extrapolation risks in model transfers via the MOP and MESS metrics help to prevent overinterpretation in model outcomes.
The Association Between Insulin Initiation and Adverse Outcomes After Hospital Discharge in Older Adults : a Population-Based Cohort Study

BACKGROUND: Starting insulin therapy in hospitalized patients may be associated with an increase in serious adverse events after discharge. OBJECTIVE: Determine whether post-discharge risks of death and rehospitalization are higher for older hospitalized patients prescribed new insulin therapy compared with oral hypoglycemic agents (OHAs). DESIGN: Retrospective population-based cohort study including hospital admissions in Ontario, Canada, between April 1, 2004, and Nov 30, 2013. PATIENTS: Persons aged 66 and over discharged after a hospitalization and dispensed a prescription for insulin and/or an OHA within 7 days of discharge. We included 104,525 individuals, subcategorized into four mutually exclusive exposure groups based on anti-hyperglycemic drug use in the 7 days post-discharge and the 365 days prior to the index admission. MAIN MEASURES: Prescriptions at discharge were categorized as new insulin (no insulin before admission), prevalent insulin (prescribed insulin before admission), new OHA(s) (no OHA or insulin before admission), and prevalent OHA (prescribed OHA only before admission) as the referent category. The primary and secondary outcomes were 30-day deaths and emergency department (ED) visits or readmissions respectively. KEY RESULTS: Of 104,525 patients, 9.2% were initiated on insulin, 4.1% died, and 26.2% had an ED visit or readmissionwithin 30 days of discharge.Deaths occurred in 7.14% of new insulin users, 4.86% of prevalent insulin users, 3.25% of new OHA users, and 3.45% of prevalent OHA users. After adjustment for covariates, new insulin users had a significantly higher risk of death (adjusted hazard ratio (aHR) 1.59, 95% confidence interval (CI) 1.46 to 1.74) and ED visit/readmissions (aHR 1.17, 95% CI 1.12 to 1.22) than prevalent OHA users. CONCLUSIONS: Initiation of insulin therapy in older hospitalized patients is associated with a higher risk of death and ED visits/readmissions after discharge, highlighting a need for better transitional care of insulin-treated patients.
Low Back Pain: A Pain That May Not Be Harmless

Abdominal aortic aneurysms are defined as vascular dilatations greater than 50% of the normal proximal segment or those that have a maximum diameter above 3 cm. Risk factors include male gender, age over 75 years, history of vascular pathology, hypertension and arteriosclerosis. The Authors describe a case of a 74-year-old man, evaluated in an emergency setting for right lumbar pain lasting 4 days. The pain did not respond to analgesia and became progressively worse. Due to the severity of symptoms, CT angiography was performed, which showed an active rupture of a partially contained aneurysm associated with aortic dissection. Early diagnosis and timely management of aortic aneurysms are essential in preventing complications, namely rupture (50–83% patients die after rupture and before receiving medical care). Acute aortic dissection is a surgical emergency and the risk of rupture is proportional to the size of the aneurysm and its rate of growth. LEARNING POINTS This article shows how difficult it is sometimes to make the right diagnosis in an emergency department. Although a very common symptom, low back pain should not be regarded as harmless.
Estudi i disseny d'un sistema de fusió de dades d'actitud i posició a bord per al seguiment de trajectòries d'un UAV

En aquest projecte es proposa dissenyar i programar un sistema a bord que fusioni les dades de posicio proporcionades per un GPS diferencial, amb RTK, i les dades d'actitud d'una unitat de mesura inercial. El resultat es la posicio, velocitats i acceleracions (tant lineals com angulars) del vehicle on es troben aquests sensors. La fusio de les dades es realitza mitjancant un filtre de Kalman i la seva implementacio ha de ser eficient.Amb la informacio proporcinoada pel sistema de fusio es dissenyara i implementara el control de trajectoria de la nau aprofitant els controls d'actitud i velocitat ja incorporats.