Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust fault detection filter design for uncertain switched systems with adaptive threshold setting

In this paper, the fault detection (FD) problem of uncertain discrete-time switched systems under the constrained switching law and external disturbances is addressed. In the multiple Lyapunov functions (MLF) framework with ℋ-/ℋ∞ performance index, a robust fault detection filter (RFDF) is designed in order to generate a residual signal which is sensitive to the faults and robust against the disturbances. The design method is formulated to be solved by linear matrix inequality (LMI) technique. The main contribution in this paper is to improve the performance of the FD for switched systems by considering switch detection logics. The design of the RFDF is based on the local performance index of each subsystem. An adaptive threshold is set based on both, the bounds of disturbances and the individual performance index for each subsystem.
Eradication of murine bladder carcinoma by intratumor injection of a bicistronic adenoviral vector carrying cDNAs for the IL-12 heterodimer and its inhibition by the IL-12 p40 subunit homodimer.

IL-12 is a heterodimeric immunoregulatory cytokine composed of covalently linked p40 and p35 subunits and exhibits antitumor activity in a variety of laboratory models. The efficacy of systemically administered cytokines for cancer therapy is often limited by toxicity. The gene therapy approach provides a mechanism to achieve temporary and high local concentrations of cytokines within a tumor with less risk of systemic toxicity. We constructed replication-defective adenoviruses containing the murine IL-12 p40 subunit (Ad.mp40) or a bicistronic vector containing cDNAs for the p40 and p35 subunits (Ad.mIL-12). Murine MB49 bladder cancer cells infected with Ad.mIL-12 secrete high concentrations of biologically active IL-12, while those infected with Ad.mp40 produce the p40 homodimer. Tumors injected with Ad.mIL-12 show rapid increases in IL-12 and IFN-gamma expression over 2 to 5 days and a return to baseline by 7 to 14 days. Injection of tumors with Ad.mIL-12 (1 x 10(9) plaque-forming units) results in a complete tumor regression in all mice, while those treated with control adenovirus succumb to their tumor. Efficacy is reduced when studies are performed in mice depleted of CD4+ and CD8+ cells or in nude mice. Mice cured of their tumor by Ad.mIL-12 demonstrate specific protective immunity upon rechallenge. Ad.mp40 does not exhibit antitumor activity and may antagonize the activity of rIL-12 or Ad.mIL-12. In summary, gene therapy strategies for cancer using adenoviral vectors containing IL-12 are highly effective with no significant toxicity in mice.
CoBots: Collaborative robots servicing multi-floor buildings

In this video we briefly illustrate the progress and contributions made with our mobile, indoor, service robots CoBots (Collaborative Robots), since their creation in 2009. Many researchers, present authors included, aim for autonomous mobile robots that robustly perform service tasks for humans in our indoor environments. The efforts towards this goal have been numerous and successful, and we build upon them. However, there are clearly many research challenges remaining until we can experience intelligent mobile robots that are fully functional and capable in our human environments.
Cardiovascular, autonomic, and plasma catecholamine responses in unilateral and bilateral carotid artery stenosis

OBJECTIVE To determine impairment of baroreceptor afferent activity, which may affect cardiovascular autonomic function in patients with unilateral and bilateral carotid artery stenosis. Comparison was made with normal subjects and hypertensive patients. METHODS A series of cardiovascular autonomic function tests along with plasma noradrenaline (norepinephrine) measurements were performed in 46 patients with carotid artery stenosis (CAS); 23 had unilateral and 23 had bilateral stenosis. Comparison was made with 21 hypertensive patients (with a similar degree of raised blood pressure), and 27 normal subjects. RESULTS Over a third of patients with unilateral and bilateral CAS had postural hypotension. Heart rate did not rise appropriately in CAS despite the postural fall in blood pressure. Pressor responses in CAS were preserved. Heart rate responses to respiratory stimuli were attenuated. Plasma noradrenaline concentrations rose normally during head up tilt. CONCLUSION A substantial proportion with CAS had postural hypotension and attenuated heart rate responses. This was not due to sympathetic vasoconstrictor or cardiac parasympathetic failure, thus suggesting impaired afferent baroreceptor activity, probably secondary to involvement of the carotid sinus. Cardiovascular autonomic testing and assessment of postural hypotension and factors enhancing it may be of clinical relevance in such patients, especially as the symptoms of postural hypotension overlap with those due to thromboembolism.
Pre-transplant Quantitative Determination of NPM1 Mutation Significantly Predicts Outcome of AIlogeneic Hematopoietic Stem Cell Transplantation in Patients with Normal Karyotype AML in Complete Remission.

BACKGROUND/AIM Minimal residual disease (MRD) in patients with acute myeloid leukemia (AML) before allogeneic hematopoietic stem cell transplantation (alloHSCT) can influence the results of therapy. With the aim of evaluating the potential role of pre-transplant MRD, we studied the impact of pre-transplant MRD level on the outcome of alloHSCT in patients with AML in complete remission (CR). PATIENTS AND METHODS From 2/2005 to 9/2014, 60 patients with a median age of 54 years (range=30-66 years) with normal karyotype-AML harboring nucleophosmin 1 (NPM1) mutation [53% Fms-related tyrosine kinase receptor 3 internal tandem duplication (FLT3/ITD)-positive] in first (n=45) or second (n=15) CR underwent myeloablative (n=16) or reduced-intensity (n=44) alloHSCT (27% related, 73% unrelated). The MRD level was determined from bone marrow samples using real-time polymerase chain reaction for detection of NPM1 mutations before starting the conditioning regimen. RESULTS The estimated probabilities of 3-year relapse, event-free survival (EFS) and overall survival (OS) for the whole cohort were 28%, 54%, and 59%, respectively. Statistical analysis showed that only age over 63 years and high MRD level affected alloHSCT outcome. Pre-transplant MRD level of 10 mutant copies of NPM1 per 10,000 Abelson murine leukemia viral oncogene homolog 1 (ABL) copies had the strongest statistical significance, and detection of higher MRD level (>10 NPM1-mutant copies) before alloHSCT was associated with increased overall mortality (hazard ratio=3.71; 95% confidence interval=1.55-9.06; p=0.004). The estimated probabilities of 3-year relapse, EFS, and OS were 6%, 72%, and 75% for patients with a low level of MRD and 48%, 35%, and 40% for patients with a higher level. CONCLUSION Our data showed that the pre-transplant level of MRD in patients with normal karyotype AML harboring NPM1 mutation in CR provides important prognostic information, which as an independent prognostic factor predicts transplant results.
Stock Market Predictability in the MENA: Evidence from New Variance Ratio Tests and Technical Trade Analysis

The objective of this paper is to test for predictability in the Middle-Eastern North African (MENA) markets by investigating both the weak-form efficiency hypothesis (WFEMH) and the presence of abnormal returns. Starting with tests for the random-walk hypothesis, we use daily data returns and a battery of econometric tests including unit-root analysis, individual and multiple variance ratio, wild bootstrapping and non-parametric tests based on ranks. Our results suggest that only the region’s largest markets, Israel and Turkey, follow a random walk. Turning to technical trade analysis, our results reinforce the hypothesis of stock market predictability. Both variable moving average (VMA) and trade range breaking (TRB) trade rules yield significant abnormal returns. We complete the analysis with profit simulations based on the breakeven costs computation methodology and taking into account local transaction costs. Our findings highlight the presence of significant portfolio investment opportunities in the MENA.
Accurate image registration by combining feature-based matching and GLS-based motion estimation

In this paper, an accurate Image Registration method is presented. It combines a feature-based method, which allows to recover large motion magnitudes between images, with a Generalized Least-Squares (GLS) motion estimation technique which is able to estimate motion parameters in an accurate manner. The feature-based method gives an initial estimation of the motion parameters, which will be refined using the GLS motion estimator. Our approach has been tested using challenging real images using both affine and projective motion models.
Configuration of Dual Connectivity with Flow Control in a Realistic Urban Scenario

Dual connectivity (DC) is a promising technique to boost the user throughput performance by allowing user equipments (UEs) to receive data simultaneously from a macro cell and a small cell. In order to ensure high degree of realism and practical relevance of the results, we investigate the performance of DC in a realistic deployment based on three-dimensional data from a dense urban European capital area, assuming realistic flow control on the backhaul connections between the macro and small cell eNBs. It is found that the configuration of UEs with DC plays a critical role in the performance of DC under realistic conditions. A modified opportunistic cell association algorithm is proposed. Simulation results show that with proper configuration of UEs with DC, the performance of DC exhibits similar gains as observed in generic 3GPP scenarios.
Memory Reuse Analysis in the Polyhedral Model

In the context of developing a compiler for a ALPHA, a functional data-parallel language based on systems of affine recurrence equations (SAREs), we address the problem of transforming scheduled single-assignment code to multiple assignment code. We show how the polyhedral model allows us to statically compute the lifetimes of program variables, and thus enables us to derive necessary and sufficient conditions for reusing memory.
Maximizing the Natriuretic Peptide System in Experimental Heart Failure: Subcutaneous Brain Natriuretic Peptide and Acute Vasopeptidase Inhibition

Background—A hallmark of congestive heart failure (CHF) is the elevation of the cardiac natriuretic peptides (NPs), which have natriuretic, renin-inhibiting, vasodilating, and lusitropic properties. We have reported that chronic subcutaneous (SQ) administration of brain natriuretic peptide (BNP) in experimental CHF improves cardiorenal function. Vasopeptidase inhibitors (VPIs) are single molecules that simultaneously inhibit both neutral endopeptidase 24.1 (NEP) and ACE. We hypothesized that acute VPI administration would potentiate the cardiorenal actions of SQ BNP in experimental CHF. Methods and Results—We determined the cardiorenal and humoral responses to acute VPI alone with omapatrilat (OMA) (1 &mgr;mol/kg IV bolus) (n=6), acute low-dose SQ BNP (5 &mgr;g/kg) alone (n=5), acute VPI plus low-dose SQ BNP (n=5), and acute high-dose SQ BNP (25 &mgr;g/kg) alone in 4 groups of anesthetized dogs with experimental CHF produced by ventricular pacing for 10 days. Plasma BNP was greater with VPI+low-dose SQ BNP compared with VPI alone or low-dose SQ BNP alone and was similar to high-dose SQ BNP alone. Urinary BNP excretion was greatest with VPI+SQ BNP. Urinary sodium excretion was also highest with VPI+SQ BNP, with the greatest increase in glomerular filtration rate. VPI+SQ BNP resulted in a greater increase in cardiac output and reduction in cardiac filling pressures as compared with low-dose SQ BNP, high-dose SQ BNP, or VPI alone. Conclusions—This study reports that acute VPI potentiates the cardiorenal actions of SQ BNP in experimental CHF. This study advances the concept that protein therapy with BNP together with vasopeptide inhibition represents a novel therapeutic strategy in CHF to maximize the beneficial properties of the natriuretic peptide system.
Decadal prediction skill of BCC‐CSM1.1 climate model in East Asia

The forecast skill of BCC‐CSM1.1 model in summer East Asian climate was evaluated with the decadal prediction experiments launched annually during 1961–2005. Results of the decadal prediction were compared with those of the historical simulation to estimate contribution of the initialization. Improved prediction skill is found for summer surface air temperature (SAT) in central eastern China measured by both root mean square error (RMSE) and anomaly correlation coefficient (ACC) for the forecast years 2–5. The decadal hindcast of precipitation in central eastern China shows increased skill in RMSE but not ACC. Such improvement in East Asia is related to enhanced prediction skill of the western Pacific (WP) sea surface temperature (SST) originated from the oceanic initialization. In the decadal hindcast, the lower tropospheric atmospheric circulation associated with warm WP exhibits an anticyclone over the South China Sea, which resembles the observation. The southwesterly increases over southeast China associated with warm WP, favouring higher SAT in central eastern China. This reveals that the decadal predictions could more realistically reproduce the relationship between summer East Asian atmospheric circulation and WP SST. The 4‐year average forecast within a decade shows that the initialization increases the ACC skill up to forecast years 4–7 for summer SAT in central eastern China.
Adversarial scheduling in discrete models of social dynamics†

In this paper we advocate the study of discrete models of social dynamics under adversarial scheduling. The approach we propose forms part of a foundational basis for a generative approach to social science (Epstein 2007). We highlight the feasibility of the adversarial scheduling approach by using it to study the Prisoners's Dilemma Game with Pavlov update, a dynamics that has already been investigated under random update in Kittock (1994), Dyer et al. (2002), Mossel and Roch (2006) and Dyer and Velumailum (2011). The model is specified by letting players at the nodes of an underlying graph G repeatedly play the Prisoner's Dilemma against their neighbours. The players adapt their strategies based on the past behaviour of their opponents by applying the so-called win–stay lose–shift strategy. With random scheduling, starting from any initial configuration, the system reaches the fixed point in which all players cooperate with high probability. On the other hand, under adversarial scheduling the following results hold: — A scheduler that can select both game participants can preclude the system from reaching the unique fixed point on most graph topologies. — A non-adaptive scheduler that is only allowed to choose one of the participants is no more powerful than a random scheduler. With this restriction, even an adaptive scheduler is not significantly more powerful than the random scheduler, provided it is ‘reasonably fair’.
AutoFolio: An Automatically Configured Algorithm Selector

Algorithm selection (AS) techniques - which involve choosing from a set of algorithms the one expected to solve a given problem instance most efficiently - have substantially improved the state of the art in solving many prominent AI problems, such as SAT, CSP, ASP, MAXSAT and QBF. Although several AS procedures have been introduced, not too surprisingly, none of them dominates all others across all AS scenarios. Furthermore, these procedures have parameters whose optimal values vary across AS scenarios. This holds specifically for the machine learning techniques that form the core of current AS procedures, and for their hyperparameters. Therefore, to successfully apply AS to new problems, algorithms and benchmark sets, two questions need to be answered: (i) how to select an AS approach and (ii) how to set its parameters effectively. We address both of these problems simultaneously by using automated algorithm configuration. Specifically, we demonstrate that we can automatically configure CLASPFOLIO 2, which implements a large variety of different AS approaches and their respective parameters in a single, highly-parameterized algorithm framework. Our approach, dubbed AUTOFOLIO, allows researchers and practitioners across a broad range of applications to exploit the combined power of many different AS methods. We demonstrate AUTOFOLIO can significantly improve the performance of CLASPFOLIO 2 on 8 out of the 13 scenarios from the Algorithm Selection Library, leads to new state-of-the-art algorithm selectors for 7 of these scenarios, and matches state-of-the-art performance (statistically) on all other scenarios. Compared to the best single algorithm for each AS scenario, AUTOFOLIO achieves average speedup factors between 1:3 and 15:4.
A basic cognitive system for interactive continuous learning of visual concepts

Interactive continuous learning is an important characteristic of a cognitive agent that is supposed to operate and evolve in an everchanging environment. In this paper we present representations and mechanisms that are necessary for continuous learning of visual concepts in dialogue with a tutor. We present an approach for modelling beliefs stemming from multiple modalities and we show how these beliefs are created by processing visual and linguistic information and how they are used for learning. We also present a system that exploits these representations and mechanisms, and demonstrate these principles in the case of learning about object colours and basic shapes in dialogue with the tutor.
Biological measures of the standard of living.

When economists investigate long-term trends and socioeconomic differences in the standard of living or quality of life, they have traditionally focused on monetary measures such as gross domestic product--which has occupied center stage for over 50 years. In recent decades, however, scholars have increasingly recognized the limitations of monetary measures while seeking useful alternatives. This essay examines the unique and valuable contributions of four biological measures--life expectancy, morbidity, stature, and certain features of skeletal remains--to understand levels and changes in human well-being. People desire far more than material goods and in fact they are quite willing to trade or give up material things in return for better physical or psychological health. For most people, health is so important to their quality of life that it is useful to refer to the "biological standard of living. " Biological measures may be especially valuable for historical studies and for other research circumstances where monetary measures are thin or lacking. A concluding section ruminates on the future evolution of biological approaches in measuring happiness.
Dynamic Concept Composition for Zero-Example Event Detection

In this paper, we focus on automatically detecting events in unconstrained videos without the use of any visual training exemplars. In principle, zero-shot learning makes it possible to train an event detection model based on the assumption that events (e.g. birthday party) can be described by multiple mid-level semantic concepts (e.g. ``blowing candle'', ``birthday cake''). Towards this goal, we first pre-train a bundle of concept classifiers using data from other sources. Then we evaluate the semantic correlation of each concept w.r. t. the event of interest and pick up the relevant concept classifiers, which are applied on all test videos to get multiple prediction score vectors. While most existing systems combine the predictions of the concept classifiers with fixed weights, we propose to learn the optimal weights of the concept classifiers for each testing video by exploring a set of online available videos with free-form text descriptions of their content. To validate the effectiveness of the proposed approach, we have conducted extensive experiments on the latest TRECVID MEDTest 2014, MEDTest 2013 and CCV dataset. The experimental results confirm the superiority of the proposed approach.
Feature Tracking Evaluation for Pose Estimation in Underwater Environments

In this paper we present the computer vision component of a 6DOF pose estimation algorithm to be used by an underwater robot. Our goal is to evaluate which feature trackers enable us to accurately estimate the 3D positions of features, as quickly as possible. To this end, we perform an evaluation of available detectors, descriptors, and matching schemes, over different underwater datasets. We are interested in identifying combinations in this search space that are suitable for use in structure from motion algorithms, and more generally, vision-aided localization algorithms that use a monocular camera. Our evaluation includes frame-by-frame statistics of desired attributes, as well as measures of robustness expressed as the length of tracked features. We compare the fit of each combination based on the following attributes: number of extracted key points per frame, length of feature tracks, average tracking time per frame, number of false positive matches between frames. Several datasets were used, collected in different underwater locations and under different lighting and visibility conditions.
Learn to wipe: A case study of structural bootstrapping from sensorimotor experience

In this paper, we address the question of generative knowledge construction from sensorimotor experience, which is acquired by exploration. We show how actions and their effects on objects, together with perceptual representations of the objects, are used to build generative models which then can be used in internal simulation to predict the outcome of actions. Specifically, the paper presents an experiential cycle for learning association between object properties (softness and height) and action parameters for the wiping task and building generative models from sensorimotor experience resulting from wiping experiments. Object and action are linked to the observed effect to generate training data for learning a non-parametric continuous model using Support Vector Regression. In subsequent iterations, this model is grounded and used to make predictions on the expected effects for novel objects which can be used to constrain the parameter exploration. The cycle and skills have been implemented on the humanoid platform ARMAR-IIIb. Experiments with set of wiping objects differing in softness and height demonstrate efficient learning and adaptation behavior of action of wiping.
erum unconjugated bisphenol A concentrations in men ay influence embryo quality indicators during in vitro ertilization

Here we assess bisphenol A (BPA) in couples undergoing in vitro fertilization (IVF) and indicators of embryo quality; embryo cell number (ECN) and embryo fragmentation score (EFS). Twenty-seven couples provided serum on the day of oocyte retrieval. Unconjugated BPA was measured by HPLC with Coularray detection. Odds ratios (OR) were generated using ordinal logistic regression including female and male BPA concentrations, age and race, and day of embryo transfer for ECN. Inverse associations are suggested for male BPA with ECN (OR = 0.70, P = 0.069), and EFS (OR = 0.54, P = 0.009), but not for women. Male BPA exposure may affect embryo quality during IVF. ssisted reproduction