Miracle-dz/UniFAR-FTUs huggingface dataset:
Smoothing spline models for the analysis of nested and crossed samples of curves. Commentaries. Authors' reply

We introduce a class of models for an additive decomposition of groups of curves stratified by crossed and nested factors, generalizing smoothing splines to such samples by associating them with a corresponding mixed-effects model. The models are also useful for imputation of missing data and exploratory analysis of variance. We prove that the best linear unbiased predictors (BLUPs) from the extended mixed-effects model correspond to solutions of a generalized penalized regression where smoothing parameters are directly related to variance components, and we show that these solutions are natural cubic splines. The model parameters are estimated using a highly efficient implementation of the EM algorithm for restricted maximum likelihood (REML) estimation based on a preliminary eigenvector decomposition. Variability of computed estimates can be assessed with asymptotic techniques or with a novel hierarchical bootstrap resampling scheme for nested mixed-effects models. Our methods are applied to menstrual cycle data from studies of reproductive function that measure daily urinary progesterone: the sample of progesterone curves is stratified by cycles nested within subjects nested within conceptive and nonconceptive groups.
Bayesian Model Averaging Using the k-best Bayesian Network Structures

We study the problem of learning Bayesian network structures from data. We develop an algorithm for finding the k-best Bayesian network structures. We propose to compute the posterior probabilities of hypotheses of interest by Bayesian model averaging over the k-best Bayesian networks. We present empirical results on structural discovery over several real and synthetic data sets and show that the method outperforms the model selection method and the state of-the-art MCMC methods.
Enhancing the explanatory power of usability heuristics

Several published sets of usability heuristics were compared with a database of existing usability problems drawn from a variety of projects in order to determine what heuristics best explain actual usability problems. Based on a factor analysis of the explanations as well as an analysis of the heuristics providing the broadest explanatory coverage of the problems, a new set of nine heuristics were derived: visibility of system status, match between system and the real world, user control and freedom, consistency and standards, error prevention, recognition rather than recall, flexibility and efficiency of use, aesthetic and minimalist design, and helping users recognize, diagnose, and recover from errors.
Intraventricular thrombolysis with rt‐PA in patients with intraventricular hemorrhage

Dunatov S, Antoncic I, Bralic M, Jurjevic A. Intraventricular thrombolysis with rt‐PA in patients with intraventricular hemorrhage. Acta Neurol Scand: 2011: 124: 343–348. © 2011 John Wiley & Sons A/S.
Load signatures enhancement via odd-order harmonic currents

This paper examines the contribution of the Odd-Order Harmonic Currents to the development of robust and distinct Load Signatures that could, in turn, facilitate load identification in Non-Intrusive Load Monitoring (NILM) algorithms. The analysis is based on field measurements in various residences with single-phase grid connections. Measurements have been conducted both for stand-alone operation of each appliance and for various combination scenarios. The former enables the determination of the active and reactive power consumption, the instantaneous current values, and the magnitude of odd-order harmonic current under steady state operation, for realistic operating conditions regarding the operational time of each appliance. The latter, allows considering candidate aggregated signals for decomposition. The results indicate that the utilization of more distinct and enhanced Load Signatures, using odd-order harmonic currents, improves the efficiency of the identification procedure.
Battery-free, stretchable optoelectronic systems for wireless optical characterization of the skin

Stretchable, wireless health monitoring patches to evaluate heart rate, blood oximetry, UV exposure, and skin coloration. Recent advances in materials, mechanics, and electronic device design are rapidly establishing the foundations for health monitoring technologies that have “skin-like” properties, with options in chronic (weeks) integration with the epidermis. The resulting capabilities in physiological sensing greatly exceed those possible with conventional hard electronic systems, such as those found in wrist-mounted wearables, because of the intimate skin interface. However, most examples of such emerging classes of devices require batteries and/or hard-wired connections to enable operation. The work reported here introduces active optoelectronic systems that function without batteries and in an entirely wireless mode, with examples in thin, stretchable platforms designed for multiwavelength optical characterization of the skin. Magnetic inductive coupling and near-field communication (NFC) schemes deliver power to multicolored light-emitting diodes and extract digital data from integrated photodetectors in ways that are compatible with standard NFC-enabled platforms, such as smartphones and tablet computers. Examples in the monitoring of heart rate and temporal dynamics of arterial blood flow, in quantifying tissue oxygenation and ultraviolet dosimetry, and in performing four-color spectroscopic evaluation of the skin demonstrate the versatility of these concepts. The results have potential relevance in both hospital care and at-home diagnostics.
Regulatory T Cells: Serious Contenders in the Promise for Immunological Tolerance in Transplantation

Regulatory T cells (Tregs) play an important role in immunoregulation and have been shown in animal models to promote transplantation tolerance and curb autoimmunity following their adoptive transfer. The safety and potential therapeutic efficacy of these cells has already been reported in Phase I trials of bone-marrow transplantation and type I diabetes, the success of which has motivated the broadened application of these cells in solid-organ transplantation. Despite major advances in the clinical translation of these cells, there are still key questions to be addressed to ensure that Tregs attest their reputation as ideal candidates for tolerance induction. In this review, we will discuss the unique traits of Tregs that have attracted such fame in the arena of tolerance induction. We will outline the protocols used for their ex vivo expansion and discuss the future directions of Treg cell therapy. In this regard, we will review the concept of Treg heterogeneity, the desire to isolate and expand a functionally superior Treg population and report on the effect of differing culture conditions. The relevance of Treg migratory capacity will also be discussed together with methods of in vivo visualization of the infused cells. Moreover, we will highlight key advances in the identification and expansion of antigen-specific Tregs and discuss their significance for cell therapy application. We will also summarize the clinical parameters that are of importance, alongside cell manufacture, from the choice of immunosuppression regimens to the number of injections in order to direct the success of future efficacy trials of Treg cell therapy. Years of research in the field of tolerance have seen an accumulation of knowledge and expertise in the field of Treg biology. This perpetual progression has been the driving force behind the many successes to date and has put us now within touching distance of our ultimate success, immunological tolerance.
Software refinement with Perfect Developer

Perfect Developer is a software tool that supports the formal development of object-oriented programs by refinement, including formal verification of code. It is built around a single language that supports both specification and implementation. We critically examine how Perfect Developer supports programming by refinement, focusing on three refinement techniques: algorithm refinement, data refinement and delta refinement. In particular we examine the extent to which Perfect Developer provides formal verification for these techniques. We assess it as a tool for software construction and compare it with related tools.
Preserving privacy and frequent sharing patterns for social network data publishing

Social network data provide valuable information for companies to better understand the characteristics of their potential customers with respect to their communities. Yet, sharing social network data in its raw form raises serious privacy concerns because a successful privacy attack not only compromises the sensitive information of the target victim but also the relationship with his/her friends or even their private information. In recent years, several anonymization techniques have been proposed to solve these issues. Most of them focus on how to achieve a given privacy model but fail to preserve the data mining knowledge required for data recipients. In this paper, we propose a method to k-anonymize a social network dataset with the goal of preserving frequent sharing patterns, one of the most important kinds of knowledge required for marketing and consumer behaviour analysis. Experimental results on real-life data illustrate the trade-off between privacy and utility loss with respect to the preservation of frequent sharing patterns.
GeoDeepDive: statistical inference using familiar data-processing languages

We describe our proposed demonstration of GeoDeepDive, a system that helps geoscientists discover information and knowledge buried in the text, tables, and figures of geology journal articles. This requires solving a host of classical data management challenges including data acquisition (e.g., from scanned documents), data extraction, and data integration. SIGMOD attendees will see demonstrations of three aspects of our system: (1) an end-to-end system that is of a high enough quality to perform novel geological science, but is written by a small enough team so that each aspect can be manageably explained; (2) a simple feature engineering system that allows a user to write in familiar SQL or Python; and (3) the effect of different sources of feedback on result quality including expert labeling, distant supervision, traditional rules, and crowd-sourced data. Our prototype builds on our work integrating statistical inference and learning tools into traditional database systems. If successful, our demonstration will allow attendees to see that data processing systems that use machine learning contain many familiar data processing problems such as efficient querying, indexing, and supporting tools for database-backed websites, none of which are machine-learning problems, per se.
Microstructural investigation of α-β SiAlON/SiC composites by analytical transmission electron microscopy

The incorporation of SiC particles into ¡-¢ SiAlON matrix leads to an enhancement on the properties. The precise detection of SiC particles in the microstructure is therefore of major interest for understanding the nature of resulting material. Here, ¡-¢ SiAlON/SiC composite was analytically examined by using transmission electron microscopy (TEM). Considering the results, nano-sized spherical SiC grains were visualised to be encapsulated with ¡-¢ SiAlON matrix. A decisive contrast between the ¡-¢ SiAlON and SiC phases was not observed by conventional (C)TEM. However, the SiC grains, ¡-¢ SiAlON matrix and grain boundary/intergranular phases were easily able to distinguished to each other via C-K (284 eV), N-K (401 eV) and O-K (532 eV) edges in energy filtering (EF)TEM 3-window elemental mapping and scanning (S)TEM-spectrum imaging (SI)-electron energy loss spectroscopy (EELS) analyses. It is anticipated that analytical (A)TEM approach presented here helps the precise determination of different reinforcement particles and matrix phases in many kind of composite systems.
Risk Factors for Gambling Problems on Online Electronic Gaming Machines, Race Betting and Sports Betting

Growth of Internet gambling has fuelled concerns about its contribution to gambling problems. However, most online gamblers also gamble on land-based forms, which may be the source of problems for some. Studies therefore need to identify the problematic mode of gambling (online or offline) to identify those with an online gambling problem. Identifying most problematic form of online gambling (e.g., EGMs, race betting, sports betting) would also enable a more accurate examination of gambling problems attributable to a specific online gambling form. This study pursued this approach, aiming to: (1) determine demographic, behavioral and psychological risk factors for gambling problems on online EGMs, online sports betting and online race betting; (2) compare the characteristics of problematic online gamblers on each of these online forms. An online survey of 4,594 Australian gamblers measured gambling behavior, most problematic mode and form of gambling, gambling attitudes, psychological distress, substance use, help-seeking, demographics and problem gambling status. Problem/moderate risk gamblers nominating an online mode of gambling as their most problematic, and identifying EGMs (n = 98), race betting (n = 291) or sports betting (n = 181) as their most problematic gambling form, were compared to non-problem/low risk gamblers who had gambled online on these forms in the previous 12 months (n = 64, 1145 and 1213 respectively), using bivariate analyses and then logistic regressions. Problem/moderate risk gamblers on each of these online forms were then compared. Risk factors for online EGM gambling were: more frequent play on online EGMs, substance use when gambling, and higher psychological distress. Risk factors for online sports betting were being male, younger, lower income, born outside of Australia, speaking a language other than English, more frequent sports betting, higher psychological distress, and more negative attitudes toward gambling. Risk factors for online race betting comprised being male, younger, speaking a language other than English, more frequent race betting, engaging in more gambling forms, self-reporting as semi-professional/professional gambler, illicit drug use whilst gambling, and more negative attitude toward gambling. These findings can inform improved interventions tailored to the specific characteristics of high risk gamblers on each of these online activities.
Modelling the structure of Australian Wool Auction prices

The auction centres for wool in Australia are located in three regions, Northern (Sydney, Newcastle, Goulburn), Southern (Melbourne, Geelong, Adelaide, Launceston) and Western Australia (Fremantle). In an auction, raw wool is sold using the greasy price, expressed in cents per kilogram. This can be converted to a clean price estimate by multiplying greasy price by 100 and dividing by the yield. Here yield is the estimate of the clean fibre either after washing/scouring or processing of greasy wool. The response variable is the clean price in c/kg, which is the base price less the total discount. The base price for wool for a given style and fibre diameter (micron), assuming there are no faults for strength, length, vegetable matter or colour is expressed in c/kg clean.
Newly developed blockers of the M‐current do not reduce spike frequency adaptation in cultured mouse sympathetic neurons

The M‐current (IK(M)) is believed to modulate neuronal excitability by producing spike frequency adaptation (SFA). Inhibitors of M‐channels, such as linopirdine and 10,10‐bis(4‐pyridinylmethyl)‐9(10H)‐anthracenone (XE991), enhance depolarization‐induced transmitter release and improve learning performance in animal models. As such, they are currently being tested for their therapeutic potential for treating Alzheimer's disease. The activity of these blockers has been associated with the reduction of SFA and the depolarization of the membrane observed when IK(M) is inhibited. To test whether this is the case, the perforated patch technique was used to investigate the capacity of IK(M) inhibitors to alter the resting membrane potential and to reduce SFA in mouse superior cervical ganglion neurons in culture. Linopirdine and XE991 both proved to be potent blockers of IK(M) when the membrane potential was held at −30 mV (IC50 2.56 and 0.26 µm, respectively). However, their potency gradually declined upon membrane hyperpolarization and was almost null when the membrane potential was kept at −70 mV, indicating that their blocking activity was voltage dependent. Nevertheless, IK(M) could be inhibited at these hyperpolarized voltages by other inhibitors such as oxotremorine‐methiodide and barium. Under current‐clamp conditions, neither linopirdine (10 µm) nor XE991 (3 µm) was effective in reducing the SFA and both provoked only a small slowly developed depolarization of the membrane (2.27 and 3.0 mV, respectively). In contrast, both barium (1 mm) and oxotremorine‐methiodide (10 µm) depolarized mouse superior cervical ganglion neurons by about 10 mV and reduced the SFA. In contrast to classical IK(M) inhibitors, the activity of linopirdine and XE991 on the IK(M) is voltage dependent and, thus, these newly developed IK(M) blockers do not reduce the SFA. These results may shed light on the mode of action of these putative cognition enhancers in vivo.
Reducing courts' failure-to-appear rate by written reminders

This article examines the effectiveness of using different kinds of written reminders to reduce misdemeanor defendants’ failure-to-appear (FTA) rates. A subset of defendants was surveyed after their scheduled court date to assess their perceptions of procedural justice and trust and confidence in the courts. Reminders reduced FTA overall, and more substantive remind ers (e.g., with information on the negative consequences of FTA) were more effective than a simple reminder. FTA varied depending on several offense and offender characteristics, such as geographic location (urban vs. rural), type of offense, and number of offenses. The reminders were somewhat more effective for Whites and Hispanics than for Blacks. Defendants with higher institutional confidence and those who felt they had been treated more fairly by the criminal justice system were more likely to appear, though the effectiveness of the reminder was greatest among misdemeanants with low levels of trust in the courts. The implications for public policy and pretrial services are discussed.
Correct-by-design Control Synthesis for Multilevel Converters using State Space Decomposition

High-power converters based on elementary switching cells are more and more used in the industry of power electronics owing to various advantages such as lower voltage stress and reduced power loss. However, the complexity of controlling such converters is a major challenge that the power manufacturing industry has to face with. The synthesis of industrial switching controllers relies today on heuristic rules and empiric simulation. The state of the system is not guaranteed to stay within the limits that are admissible for its correct electrical behavior. We show here how to apply a formal method in order to synthesize a correct-by-design control that guarantees that the power converter will always stay within a predefined safe zone of variations for its input parameters. The method is applied in order to synthesize a correct-by-design control for 5-level and 7-level power converters with a flying capacitor topology. We check the validity of our approach by numerical simulations for 5 and 7 levels. We also perform physical experimentations using a prototype built by SATIE laboratory for 5 levels.
A Collaborative Reinforcement Learning Approach to Urban Traffic Control Optimization

The high growth rate of vehicles per capita now poses a real challenge to efficient urban traffic control (UTC). An efficient solution to UTC must be adaptive in order to deal with the highly-dynamic nature of urban traffic. In the near future, global positioning systems and vehicle-to-vehicle/infrastructure communication may provide a more detailed local view of the traffic situation that could be employed for better global UTC optimization. In this paper we describe the design of a next-generation UTC system that exploits such local knowledge about a junction's traffic in order to optimize traffic control. Global UTC optimization is achieved using a local adaptive round robin (ARR) phase switching model optimized using collaborative reinforcement learning (CRL). The design employs an ARR-CRL-based agent controller for each signalized junction that collaborates with neighbouring agents in order to learn appropriate phase timing based on the traffic pattern. We compare our approach to non-adaptive fixed-time UTC system and to a saturation balancing algorithm in a large-scale simulation of traffic in Dublin's inner city centre. We show that the ARR-CRL approach can provide significant improvement resulting in up to ~57% lower average waiting time per vehicle compared to the saturation balancing algorithm.
Crim1KST264/KST264 mice display a disruption of the Crim1 gene resulting in perinatal lethality with defects in multiple organ systems

Crim1 is a transmembrane protein, containing six vWF‐C type cysteine‐rich repeats, that tethers growth factors to the cell surface. A mouse line, KST264, generated in a LacZ insertion mutagenesis gene‐trap screen, was examined to elucidate Crim1 function in development. We showed that Crim1KST264/KST264 mice were not null for Crim1 due to the production of a shortened protein isoform. These mice are likely to represent an effective hypomorph or a dominant‐negative for Crim1. Transgene expression recapitulated known Crim1 expression in lens, brain, and limb, but also revealed expression in the smooth muscle cells of the developing heart and renal vasculature, developing cartilage, mature ovary and detrusor of the bladder. Transgene expression was also observed in glomerular epithelial cells, podocytes, mesangial cells, and urothelium in the kidney. Crim1KST264/KST264 mice displayed perinatal lethality, syndactyly, eye, and kidney abnormalities. The severe and complex phenotype observed in Crim1KST264/KST264 mice highlights the importance of Crim1 in numerous aspects of organogenesis. Developmental Dynamics 236:502–511, 2007. © 2006 Wiley‐Liss, Inc.
Power Thresholds and Pump Depletion in Brillouin Fiber Amplifiers

The Brillouin fiber amplifier (BFA) has been used in Brillouin optical time (frequency) domain analyzer based sensors. The performance of this sensor depends on pump depletion which occurs when the threshold is reached and when the Brillouin gain is saturated. Although threshold definitions are common for Brillouin fiber generators (BFG), there is no explicit threshold definition for BFA. More importantly we find the maximum gain point corresponds to the optimized distributed sensing system where the depletion effect remains small to moderate. We find that only the method based on the determination of the power for which the pump becomes depleted, and hence, the Stokes gain saturated (i.e. inflexion method), remains valid for BFA. We also derive an analytical relation accounting for the various sensor key parameters such as fiber type and length as well as input Stokes power. The thresholds obtained with the analytical relation are within 10% of experimental and numerical values, which is maximum power that can be launched for a given optimum sensing configuration.