Miracle-dz/UniFAR-FTUs huggingface dataset:
Asymptotically Optimal Anomaly Detection via Sequential Testing

Sequential detection of independent anomalous processes among K processes is considered. At each time, only M (1 ≤ M ≤ K) processes can be observed, and the observations from each chosen process follow two different distributions, depending on whether the process is normal or abnormal. Each anomalous process incurs a cost per unit time until its anomaly is identified and fixed. Switching across processes and state declarations are allowed at all times, while decisions are based on all past observations and actions. The objective is a sequential search strategy that minimizes the total expected cost incurred by all the processes during the detection process under reliability constraints. We develop index-type algorithms for the case with both known observation distributions and the case when the observation distributions have unknown parameters. We show that the proposed algorithms are asymptotically optimal in terms of minimizing the total expected cost as the error constraints approach zero. Simulation results demonstrate strong performance in the finite regime.
Chinese Systemic Lupus Erythematosus Treatment and Research Group Registry IX: Clinical Features and Survival of Childhood-Onset Systemic Lupus Erythematosus in China

Background: Approximately 15–20% cases of systemic lupus erythematosus (SLE) are diagnosed in children. There have been a few studies reporting the epidemiological data of pediatric-onset SLE (cSLE) in China, neither comparing the differences between cSLE and adult-onset SLE (aSLE). The aim of this study was to describe the impact of age of onset on clinical features and survival in cSLE patients in China based on the Chinese SLE Treatment and Research group (CSTAR) database. Methods: We made a prospective study of 225 cSLE patients (aged < 16 years) and 1759 patients aged 16–50 years based on CSTAR registry. We analyzed initial symptoms, clinical presentations, SLE disease activity, damages, and outcomes of cSLE, as well as compared with aSLE patients. Results: The mean age of cSLE patients was 12.16 ± 2.92 years, with 187 (83.1%) females. Fever (P < 0.001) as well as mucocutaneous (P < 0.001) and renal (P = 0.006) disorders were found to be significantly more frequent in cSLE patients as initial symptoms, while muscle and joint lesions were significantly less common compared to aSLE subjects (P < 0.001). The cSLE patients were found to present more frequently with malar rash (P = 0.001; odds ratio [OR], 0.624; 95% confidence interval [CI], 0.470–0.829) but less frequently with arthritis (P < 0.001; OR, 2.013; 95% CI, 1.512–2.679) and serositis (P = 0.030; OR, 1.629; 95% CI, 1.053–2.520). There was no significant difference in SLE disease activity index scores between cSLE and aSLE groups (P = 0.478). Cox regression indicated that childhood onset was the risk factor for organ damage in lupus patients (hazard ratio 0.335 [0.170–0.658], P = 0.001). The survival curves between the cSLE and aSLE groups had no significant difference as determined by the log-rank test (0.557, P = 0.455). Conclusions: cSLE in China has different clinical features and more inflammation than aSLE patients. Damage may be less in children and there is no difference in 5- year survival between cSLE and aSLE groups.
Bilaterally Combined Electric and Acoustic Hearing in Mandarin-Speaking Listeners: The Population With Poor Residual Hearing

The hearing loss criterion for cochlear implant candidacy in mainland China is extremely stringent (bilateral severe to profound hearing loss), resulting in few patients with substantial residual hearing in the nonimplanted ear. The main objective of the current study was to examine the benefit of bimodal hearing in typical Mandarin-speaking implant users who have poorer residual hearing in the nonimplanted ear relative to those used in the English-speaking studies. Seventeen Mandarin-speaking bimodal users with pure-tone averages of ∼80 dB HL participated in the study. Sentence recognition in quiet and in noise as well as tone and word recognition in quiet were measured in monaural and bilateral conditions. There was no significant bimodal effect for word and sentence recognition in quiet. Small bimodal effects were observed for sentence recognition in noise (6%) and tone recognition (4%). The magnitude of both effects was correlated with unaided thresholds at frequencies near voice fundamental frequencies (F0s). A weak correlation between the bimodal effect for word recognition and unaided thresholds at frequencies higher than F0s was identified. These results were consistent with previous findings that showed more robust bimodal benefits for speech recognition tasks that require higher spectral resolution than speech recognition in quiet. The significant but small F0-related bimodal benefit was also consistent with the limited acoustic hearing in the nonimplanted ear of the current subject sample, who are representative of the bimodal users in mainland China. These results advocate for a more relaxed implant candidacy criterion to be used in mainland China.
Human adipose stem cells induced to osteogenic differentiation by an innovative collagen/hydroxylapatite hybrid scaffold

Novel biomaterials are of paramount importance for bone regrowth. In this study, we investigated human adipose stem cells (hASCs) for osteogenic, osteoconductivity, and osteoinductivity effects of an innovative collagen/hydroxylapatite hybrid scaffold. In hASCs that were grown on this scaffold, osteogenic genes were analyzed for their expression profiles, together with adhesion and extracellular matrix genes. In hASC integrins, basement membrane constituents and collagens were up‐regulated, together with cell proliferation. In addition, expression of osteopontin and activated focal adhesion kinase was studied at the protein level. Our in vitro data indicate that hASCs, together with hybrid biomaterial, is an important model of study to investigate in vitro bone induction. —Mazzoni, E. , D’Agostino, A. , Manfrini, M. , Maniero, S. , Puozzo, A. , Bassi, E. , Marsico, S. , Fortini, C. , Trevisiol, L. , Patergnani, S. , Tognon, M. Human adipose stem cells induced to osteogenic differentiation by an innovative collagen/hydroxylapatite hybrid scaffold. FASEB J. 31, 4555–4565 (2017). www.fasebj. org
Hydro-mechanical modelling of damage-plasticity couplings in unsaturated geomaterials

This thesis work objective is the development of a hydro-mechanical constitutive model which accounts for damage-plasticity couplings in unsaturated geomaterials. The coupling of this model with hydraulic transfers is made possible by its implementation into the Finite Element code Theta-Stock. In order to achieve this implementation, a specific stress-point algorithm has been developed. Fully coupled hydro-mechanical problems have been simulated, such as the creation of the Excavation Damaged Zone around a tunnel and the initiation of damage due to desiccation and humidification. A double effective stress incorporating both the effect of suction and damage (assumed isotropic) is defined based on thermodynamical considerations. The advantage of this approach is that it results in a unique stress variable being thermodynamically conjugated to elastic strains. A pressure-dependent hyperelastic formulation is used to describe the behaviour inside the elastic domain. The evolution of elastic rigidities with damage is then studied. Two hypotheses are compared, the principle of strain equivalence and the principle of equivalent energy. Coupling between damage and plasticity phenomena is achieved by following the principle of strain equivalence and incorporating the effective stress into plasticity equations. The plasticity framework is based on the Barcelona Basic Model (Alonso extit{et al.}, 1990), itself based on the Cam-Clay model. Two distinct criteria are defined for damage and plasticity, which can be activated either independently or simultaneously. Their formulation in terms of effective stress and suction allows them to evolve in the total stress space with suction and damage changes. This leads to a direct coupling between damage and plasticity and allows the model to capture the ductile/brittle behaviour transition occurring when clays are drying. A specific explicit algorithm has been developed to handle the association of the two dissipative phenomena. The implementation of the constitutive model into the Finite Element code Theta-Stock allowed for the simulation of fully coupled hydro-mechanical problems. The hydraulic transfer laws also consider the saturation state. This fully coupled model is first applied to simulate the development of micro-cracks during desiccation of a soil sample. Damage initiation is explained mainly by the important pressure gradient appearing at the boundary when applying a high suction change. Finally, a full-scale problem is simulated. The excavation of a tunnel, the desaturation of the surrounding soil and the creation of the excavation damaged zone are studied
Portulaca Extract Attenuates Development of Dextran Sulfate Sodium Induced Colitis in Mice through Activation of PPARγ

Portulaca oleracea L. is a traditional Chinese medicine, which has been used as adjuvant therapy for inflammatory bowel disease (IBD). However, the mechanism of its activity in IBD still remains unclear. Since previous studies have documented the anti-inflammatory effect of peroxisome proliferator activated receptors-γ (PPAR-γ), Portulaca regulation of PPAR-γ in inflammation was examined in current study. Ulcerative colitis (UC) was generated by 5% dextran sulfate sodium (DSS) in mice and four groups were established as normal control, DSS alone, DSS plus mesalamine, and DSS plus Portulaca. Severity of UC was evaluated by body weight, stool blood form, and length of colorectum. Inflammation was examined by determination of inflammatory cytokines (TNF-a, IL-6, and IL-1a). Portulaca extract was able to attenuate development of UC in DSS model similar to the treatment of mesalazine. Moreover, Portulaca extract inhibited proinflammatory cytokines release and reduced the level of DSS-induced NF-κB phosphorylation. Furthermore, Portulaca extract restored PPAR-γ level, which was reduced by DSS. In addition, Portulaca extract protected DSS induced apoptosis in mice. In conclusion, Portulaca extract can alleviate colitis in mice through regulation of inflammatory reaction, apoptosis, and PPAR-γ level; therefore, Portulaca extract can be a potential candidate for the treatment of IBD.
Optimization and characterization of the formation of oil-in-water diazinon nanoemulsions: Modeling and influence of the oil phase, surfactant and sonication

ABSTRACT Nanoemulsions are particularly suitable as a platform in the development of delivery systems for lipophilic functional agents. Current research describes the formation of oil-in-water (O/W) diazinon nanoemulsions using synthetic and natural additives by adopting a high-energy (ultrasound) emulsification method. The diazinon nanoemulsions were spontaneously formed by adding dropwise a mixture of diazinon, solvent and co-solvent in an aqueous solution containing a surfactant (tween or lecithin) with continuous stirring. The nanoemulsions were then formed by ultra-sonication. The effects of three levels of active ingredient, solvent, co-solvent, surfactant, sonication time and sonication cycle and power were performed by Minitab software to design the experiment. Effects of these factors on droplet size, polydispersity index (PDI), viscosity and pH of nanoemulsions were investigated. The results of the modeling showed that the experimental data could be adequately adapted in a second-order polynomial model with a multiple regression coefficient r2 of 0.821 for the prediction of particle size, PDI and viscosity. The long-term and thermodynamic stability of the prepared nanoemulsions were tested. The droplet size and morphology of the nanoemulsions were measured by dynamic light scattering (DLS) and transmission electron microscopy (TEM). On this basis, a water-insoluble insecticide diazinon was incorporated into 26 optimized nanoemulsion systems to demonstrate potential applications in pest control. The results of DLS and TEM measurements showed that most of prepared nanoemulsions had an almost monodisperse droplet size distribution (PDI < 200 nm). Incorporation of diazinon had no significant effect on the size and stability of the nanoemulsions and the formulated nanoemulsion remained stable after four months of storage.
Propensity for Bistability of Bursting and Silence in the Leech Heart Interneuron

The coexistence of neuronal activity regimes has been reported under normal and pathological conditions. Such multistability could enhance the flexibility of the nervous system and has many implications for motor control, memory, and decision making. Multistability is commonly promoted by neuromodulation targeting specific membrane ionic currents. Here, we investigated how modulation of different ionic currents could affect the neuronal propensity for bistability. We considered a leech heart interneuron model. It exhibits bistability of bursting and silence in a narrow range of the leak current parameters, conductance (gleak) and reversal potential (Eleak). We assessed the propensity for bistability of the model by using bifurcation diagrams. On the diagram (gleak, Eleak), we mapped bursting and silent regimes. For the canonical value of Eleak we determined the range of gleak which supported the bistability. We use this range as an index of propensity for bistability. We investigated how this index was affected by alterations of ionic currents. We systematically changed their conductances, one at a time, and built corresponding bifurcation diagrams in parameter planes of the maximal conductance of a given current and the leak conductance. We found that conductance of only one current substantially affected the index of propensity; the increase of the maximal conductance of the hyperpolarization-activated cationic current increased the propensity index. The second conductance with the strongest effect was the conductance of the low-threshold fast Ca2+ current; its reduction increased the propensity index although the effect was about two times smaller in magnitude. Analyzing the model with both changes applied simultaneously, we found that the diagram (gleak, Eleak) showed a progressively expanded area of bistability of bursting and silence.
Machine Learning Methods to Predict Density Functional Theory B3LYP Energies of HOMO and LUMO Orbitals

Machine learning algorithms were explored for the fast estimation of HOMO and LUMO orbital energies calculated by DFT B3LYP, on the basis of molecular descriptors exclusively based on connectivity. The whole project involved the retrieval and generation of molecular structures, quantum chemical calculations for a database with >111 000 structures, development of new molecular descriptors, and training/validation of machine learning models. Several machine learning algorithms were screened, and an applicability domain was defined based on Euclidean distances to the training set. Random forest models predicted an external test set of 9989 compounds achieving mean absolute error (MAE) up to 0.15 and 0.16 eV for the HOMO and LUMO orbitals, respectively. The impact of the quantum chemical calculation protocol was assessed with a subset of compounds. Inclusion of the orbital energy calculated by PM7 as an additional descriptor significantly improved the quality of estimations (reducing the MAE in >30%).
MERS-CoV 4b protein interferes with the NF-κB-dependent innate immune response during infection

Middle East respiratory syndrome coronavirus (MERS-CoV) is a novel human coronavirus that emerged in 2012, causing severe pneumonia and acute respiratory distress syndrome (ARDS), with a case fatality rate of ~36%. When expressed in isolation, CoV accessory proteins have been shown to interfere with innate antiviral signaling pathways. However, there is limited information on the specific contribution of MERS-CoV accessory protein 4b to the repression of the innate antiviral response in the context of infection. We found that MERS-CoV 4b was required to prevent a robust NF-κB dependent response during infection. In wild-type virus infected cells, 4b localized to the nucleus, while NF-κB was retained in the cytoplasm. In contrast, in the absence of 4b or in the presence of cytoplasmic 4b mutants lacking a nuclear localization signal (NLS), NF-κB was translocated to the nucleus leading to the expression of pro-inflammatory cytokines. This indicates that NF-κB repression required the nuclear import of 4b mediated by a specific NLS. Interestingly, we also found that both in isolation and during infection, 4b interacted with α-karyopherin proteins in an NLS-dependent manner. In particular, 4b had a strong preference for binding karyopherin-α4 (KPNA4), which is known to translocate the NF-κB protein complex into the nucleus. Binding of 4b to KPNA4 during infection inhibited its interaction with NF-κB-p65 subunit. Thereby we propose a model where 4b outcompetes NF-κB for KPNA4 binding and translocation into the nucleus as a mechanism of interference with the NF-κB-mediated innate immune response.
Histogram-based Outlier Score (HBOS): A fast Unsupervised Anomaly Detection Algorithm

Unsupervised anomaly detection is the process of nding outliers in data sets without prior training. In this paper, a histogrambased outlier detection (HBOS) algorithm is presented, which scores records in linear time. It assumes independence of the features making it much faster than multivariate approaches at the cost of less precision. A comparative evaluation on three UCI data sets and 10 standard algorithms show, that it can detect global outliers as reliable as state-of-theart algorithms, but it performs poor on local outlier problems. HBOS is in our experiments up to 5 times faster than clustering based algorithms and up to 7 times faster than nearest-neighbor based methods.
Towards complete consistency checks of Clafer models

Clafer is a general purpose modeling language that combines UML-like class and meta-modeling with feature-oriented variability modeling and first-order logic constraints. The considerable expressiveness of Clafer makes automated reasoning about properties like model consistency (i.e., finding a valid model instance) very challenging. In particular, multiplicity annotations and recursive model structures yield a potentially unbounded number of model instances resulting in an infinite search space. Existing approaches for consistency checking encode Clafer models into finite constraint-satisfaction problems by either manually or heuristically, setting bounds for the search space. Hence, if no valid model instance has been found, it is unknown whether the model is inconsistent, or whether the bounds have been chosen too tight. In this paper, we characterize a restricted sub-language of Clafer with complex inheritance relations that is crucial for facilitating sound and complete model-consistency checking. To this end, we present the idea of a novel technique for automated search-space restriction, by flattening Clafer models and encoding them as Integer Linear Programs (ILP). Our evaluation shows very promising results of our approach in terms of runtime efficiency for both flattening of complex inheritance hierarchies as well as sound and complete consistency checking.
Aquatic exposures of chemical mixtures in urban environments: Approaches to impact assessment

Urban regions of the world are expanding rapidly, placing additional stress on water resources. Urban water bodies serve many purposes, from washing and sources of drinking water to transport and conduits for storm drainage and effluent discharge. These water bodies receive chemical emissions arising from either single or multiple point sources, diffuse sources which can be continuous, intermittent, or seasonal. Thus, aquatic organisms in these water bodies are exposed to temporally and compositionally variable mixtures. We have delineated source‐specific signatures of these mixtures for diffuse urban runoff and urban point source exposure scenarios to support risk assessment and management of these mixtures. The first step in a tiered approach to assessing chemical exposure has been developed based on the event mean concentration concept, with chemical concentrations in runoff defined by volumes of water leaving each surface and the chemical exposure mixture profiles for different urban scenarios. Although generalizations can be made about the chemical composition of urban sources and event mean exposure predictions for initial prioritization, such modeling needs to be complemented with biological monitoring data. It is highly unlikely that the current paradigm of routine regulatory chemical monitoring alone will provide a realistic appraisal of urban aquatic chemical mixture exposures. Future consideration is also needed of the role of nonchemical stressors in such highly modified urban water bodies. Environ Toxicol Chem 2018;37:703–714. © 2017 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.
Neuroeconomic Measures of Social Decision-Making Across the Lifespan

Social and decision-making deficits are often the first symptoms of a striking number of neurodegenerative disorders associated with aging. These includes not only disorders that directly impact dopamine and basal ganglia, such as Parkinson’s disorder, but also degeneration in which multiple neural pathways are affected over the course of normal aging. The impact of such deficits can be dramatic, as in cases of financial fraud, which disproportionately affect the elderly. Unlike memory and motor impairments, however, which are readily recognized as symptoms of more serious underlying neurological conditions, social and decision-making deficits often do not elicit comparable concern in the elderly. Furthermore, few behavioral measures exist to quantify these deficits, due in part to our limited knowledge of the core cognitive components or their neurobiological substrates. Here we probe age-related differences in decision-making using a game theory paradigm previously shown to dissociate contributions of basal ganglia and prefrontal regions to behavior. Combined with computational modeling, we provide evidence that age-related changes in elderly participants are driven primarily by an over-reliance in trial-and-error reinforcement learning that does not take into account the strategic context, which may underlie cognitive deficits that contribute to social vulnerability in elderly individuals.
Steps Towards a Theory of Visual Information: Active Perception, Signal-to-Symbol Conversion and the Interplay Between Sensing and Control

This manuscript describes the elements of a theory of information tailored to control and decision tasks and specifically to visual data. The concept of Actionable Information is described, that relates to a notion of information championed by J. Gibson, and a notion of "complete information" that relates to the minimal sufficient statistics of a complete representation. It is shown that the "actionable information gap" between the two can be reduced by exercising control on the sensing process. Thus, senging, control and information are inextricably tied. This has consequences in the so-called "signal-to-symbol barrier" problem, as well as in the analysis and design of active sensing systems. It has ramifications in vision-based control, navigation, 3-D reconstruction and rendering, as well as detection, localization, recognition and categorization of objects and scenes in live video. This manuscript has been developed from a set of lecture notes for a summer course at the First International Computer Vision Summer School (ICVSS) in Scicli, Italy, in July of 2008. They were later expanded and amended for subsequent lectures in the same School in July 2009. Starting on November 1, 2009, they were further expanded for a special topics course, CS269, taught at UCLA in the Spring term of 2010.