Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of a quality improvement program on care and outcomes for children with asthma.

OBJECTIVE To test a quality improvement intervention, a learning collaborative based on the Institute for Healthcare Improvement's Breakthrough Series methodology, specifically intended to improve care and outcomes for patients with childhood asthma. DESIGN Randomized trial in primary care practices. SETTING Practices in greater Boston, Mass, and greater Detroit, Mich. PARTICIPANTS Forty-three practices, with 13 878 pediatric patients with asthma, randomized to intervention and control groups. Intervention Participation in a learning collaborative project based on the Breakthrough Series methodology of continuous quality improvement. MAIN OUTCOME MEASURES Change from baseline in the proportion of children with persistent asthma who received appropriate medication therapy for asthma, and in the proportion of children whose parent received a written management plan for their child's asthma, as determined by telephone interviews with parents of 631 children. RESULTS After adjusting for state, practice size, child age, sex, and within-practice clustering, no overall effect of the intervention was found. CONCLUSIONS This methodologically rigorous assessment of a widely used quality improvement technique did not demonstrate a significant effect on processes or outcomes of care for children with asthma. Potential deficiencies in program implementation, project duration, sample selection, and data sources preclude making the general inference that this type of improvement program is ineffective. Additional rigorous studies should be undertaken under more optimal settings to assess the efficacy of this method for improving care.
Volume entropy and information flow in a brain graph

Entropy is a classical measure to quantify the amount of information or complexity of a system. Various entropy-based measures such as functional and spectral entropies have been proposed in brain network analysis. However, they are less widely used than traditional graph theoretic measures such as global and local efficiencies because either they are not well-defined on a graph or difficult to interpret its biological meaning. In this paper, we propose a new entropy-based graph invariant, called volume entropy. It measures the exponential growth rate of the number of paths in a graph, which is a relevant measure if information flows through the graph forever. We model the information propagation on a graph by the generalized Markov system associated to the weighted edge-transition matrix. We estimate the volume entropy using the stationary equation of the generalized Markov system. A prominent advantage of using the stationary equation is that it assigns certain distribution of weights on the edges of the brain graph, which we call the stationary distribution. The stationary distribution shows the information capacity of edges and the direction of information flow on a brain graph. The simulation results show that the volume entropy distinguishes the underlying graph topology and geometry better than the existing graph measures. In brain imaging data application, the volume entropy of brain graphs was significantly related to healthy normal aging from 20s to 60s. In addition, the stationary distribution of information propagation gives a new insight into the information flow of functional brain graph.
Drug Release from Phase-Changeable Nanodroplets Triggered by Low-Intensity Focused Ultrasound

Background: As one of the most effective triggers with high tissue-penetrating capability and non-invasive feature, ultrasound shows great potential for controlling the drug release and enhancing the chemotherapeutic efficacy. In this study, we report, for the first time, construction of a phase-changeable drug-delivery nanosystem with programmable low-intensity focused ultrasound (LIFU) that could trigger drug-release and significantly enhance anticancer drug delivery. Methods: Liquid-gas phase-changeable perfluorocarbon (perfluoropentane) and an anticancer drug (doxorubicin) were simultaneously encapsulated in two kinds of nanodroplets. By triggering LIFU, the nanodroplets could be converted into microbubbles locally in tumor tissues for acoustic imaging and the loaded anticancer drug (doxorubicin) was released after the microbubble collapse. Based on the acoustic property of shell materials, such as shell stiffness, two types of nanodroplets (lipid-based nanodroplets and PLGA-based nanodroplets) were activated by different acoustic pressure levels. Ultrasound irradiation duration and power of LIFU were tested and selected to monitor and control the drug release from nanodroplets. Various ultrasound energies were introduced to induce the phase transition and microbubble collapse of nanodroplets in vitro (3 W/3 min for lipid nanodroplets; 8 W/3 min for PLGA nanodroplets). Results: We detected three steps in the drug-releasing profiles exhibiting the programmable patterns. Importantly, the intratumoral accumulation and distribution of the drug with LIFU exposure were significantly enhanced, and tumor proliferation was substantially inhibited. Co-delivery of two drug-loaded nanodroplets could overcome the physical barriers of tumor tissues during chemotherapy. Conclusion: Our study provides a new strategy for the efficient ultrasound-triggered chemotherapy by nanocarriers with programmable LIFU capable of achieving the on-demand drug release.
Acute administration of tumour necrosis factor-&agr; induces spontaneous calcium release via the reactive oxygen species pathway in atrial myocytes

Aims The arrhythmogenic mechanisms of atrial fibrillation (AF) that are induced by acute inflammation, such as postoperative AF, are not well understood. We investigated the acute effects of tumour necrosis factor-α (TNF-α) that mimic acute inflammation on Ca2+ handling in isolated atrial myocytes and its underlying mechanisms. Methods and results Cytosol Ca2+ handling and mitochondrial reactive oxygen species (ROS) production were studied in freshly isolated atrial myocytes of wild-type mice that were exposed to TNF-α (0.05 ng/mL) for 2 h by Ionoptix and confocal microscopy. The acute effects of TNF-α on Ca2+ handling were decreased amplitudes and prolonged decay times of Ca2+ transients in isolated atrial myocytes. A significant reduction in the sarcoplasmic reticulum (SR) Ca2+ content was detected in TNF-α treated cells, which was associated with increased spontaneous Ca2+ release events. In particular, physiological concentrations of TNF-α dramatically promoted the frequency of spontaneous Ca2+ waves and Ca2+ sparks, while the spark mass presented with reduced amplitudes and prolonged durations. The underlying mechanisms of pro-arrhythmic effects of TNF-α were further investigated. Acute exposure to TNF-α rapidly promoted mitochondrial ROS production that was correlated with the acute effect of TNF-α on Ca2+ handling, and enhanced the oxidation of calcium/calmodulin-dependent protein kinase II (CaMKII) and the phosphorylation of RyR2. However, the performance of ROS inhibitor, DL-Dithiothreitol (DTT), reversed Ca2+ handling disorders induced by TNF-α. Conclusion Tumour necrosis factor-α rapidly increases spontaneous Ca2+ release and promotes atrial arrhythmogenesis via the ROS pathway, which suggests that antioxidant therapy is a promising strategy for acute inflammation related AF.
CHAPTER 7:Ultrafast Optical Imaging and Microspectroscopy

Ultrafast microscopy combines the capabilities of femtosecond pump probe spectroscopy with the ability to image and monitor individual objects, down to the single particle and single molecule level. This combination of temporal, spatial and spectral resolution is necessary when studying charge and energy transfer processes in heterogeneous and nanostructured materials, which are increasingly common in the fields of photovoltaics and photocatalysis. Acquisition of images evolving on the femtosecond timescale, similarly to the acquisition of femtosecond photoluminescence and absorption spectra, must rely on optical gating techniques as there are no electronic devices capable of operating in this time domain. In this chapter we describe two all-optical realizations of femtosecond microscopy which are most general and straightforward to implement: wide-field Kerr-gated fluorescence microscopy (KGFM) and scanning pump probe transient absorption microscopy (PPTAM).
An Easy-to-Use Tool for Rotational-XOR Cryptanalysis of ARX Block Ciphers

An increasing number of lightweight cryptographic primitives have been published recently. Some of these proposals are ARX primitives, which have shown a great performance in software. RotationalXOR cryptanalysis is a statistical technique to attack ARX primitives. In this paper, a computer tool to speed up and make easier the security evaluation of ARX block ciphers against rotational-XOR cryptanalysis is shown. Our tool takes a Python implementation of an ARX block cipher and automatically finds an optimal rotational-XOR characteristic. Compared to most of the automated tools, which only support a small set of primitives, our tool supports any ARX block cipher and it is executed with a simple shell command.
Long-term Forecasting using Tensor-Train RNNs

We present Tensor-Train RNN (TT-RNN), a novel family of neural sequence architectures for multivariate forecasting in environments with nonlinear dynamics. Long-term forecasting in such systems is highly challenging, since there exist long-term temporal dependencies, higher-order correlations and sensitivity to error propagation. Our proposed tensor recurrent architecture addresses these issues by learning the nonlinear dynamics directly using higher order moments and high-order state transition functions. Furthermore, we decompose the higher-order structure using the tensor-train (TT) decomposition to reduce the number of parameters while preserving the model performance. We theoretically establish the approximation properties of Tensor-Train RNNs for general sequence inputs, and such guarantees are not available for usual RNNs. We also demonstrate significant long-term prediction improvements over general RNN and LSTM architectures on a range of simulated environments with nonlinear dynamics, as well on real-world climate and traffic data.
Inflammatory response during slow‐ and fast‐twitch muscle regeneration

Introduction: Skeletal muscles are characterized by their unique ability to regenerate. Injury of a so‐called fast‐twitch muscle, extensor digitorum longus (EDL), results in efficient regeneration and reconstruction of the functional tissue. In contrast, slow‐twitch muscle (soleus) fails to properly reconstruct and develops fibrosis. This study focuses on soleus and EDL muscle regeneration and associated inflammation. Methods: We determined differences in the activity of neutrophils and M1 and M2 macrophages using flow cytometry and differences in the levels of proinflammatory cytokines using Western blotting and immunolocalization at different times after muscle injury. Results: Soleus muscle repair is accompanied by increased and prolonged inflammation, as compared to EDL. The proinflammatory cytokine profile is different in the soleus and ED muscles. Conclusions: Muscle repair efficiency differs by muscle fiber type. The inflammatory response affects the repair efficiency of slow‐ and fast‐twitch muscles. Muscle Nerve 55: 400–409, 2017
Prenatal attachment and sociodemographic and clinical factors in Portuguese couples

Abstract Objectives: To observe differences between maternal and paternal prenatal attachment as a function of sociodemographic and clinical/obstetric factors. Methods: Quantitative descriptive correlational study. Instruments: Sociodemographic and Clinical Questionnaire; Maternal and Paternal Antenatal Attachment Scale (Portuguese version by Camarneiro & Justo). Assessments were conducted in antenatal clinics in Central Portugal. Participants: Couples (N = 407), women and men in the second trimester of pregnancy. Results: Significant differences in maternal prenatal attachment were observed as a function of age, education, socioeconomic status, pregnancy planning, previous pregnancies, pregnancy interruptions and gestational age. Significant differences in paternal prenatal attachment were observed as a function of age, number of children, socioeconomic status, occupational status, family household and pregnancy planning. Conclusions: Women and men present variations in prenatal attachment according to some sociodemographic and clinical variables. These results should be taken into account in interventions focused on the promotion of prenatal attachment.
A Meta-Analysis of Brief Tobacco Interventions for Use in Integrated Primary Care

Introduction The integration of behavioral health services in primary care settings presents an opportunity to enhance the delivery of tobacco cessation interventions in the primary care setting, but guidance on evidence-based treatments for tobacco use disorder that fits the brief format of integrated primary care (IPC) is limited. This meta-analysis summarizes the outcomes of brief behavioral interventions targeting tobacco use that can be delivered in IPC settings. Methods A literature search was conducted to locate empirical studies examining tobacco cessation interventions that could be implemented in an IPC setting. A random effects meta-analytic approach was utilized with odds ratios as the effect size. Subgroup analyses were conducted to determine the extent to which a number of study, participant, and intervention characteristics affected treatment outcome. Results A total of 36 studies were included (n = 12975 patients). Patients in the intervention groups exhibited significantly greater odds of smoking cessation compared with those in the comparison groups (OR = 1.78, p < .001). Subgroup analyses did not reveal significant sources of heterogeneity attributable to moderators such as methodological quality, gender, bioverification, follow-up time period, or intervention characteristics (such as setting, type, or length of intervention). Conclusions Brief tobacco cessation interventions that can be delivered in IPC settings were found to be effective. Future research in this area might evaluate ways to improve the dissemination and implementation of these types of interventions in IPC settings. Implications The integration of behavioral health services into primary care presents a unique opportunity to increase the delivery of tobacco cessation interventions, as behavioral health providers in these settings are experts in behavior change interventions and may have more time to deliver these interventions than primary care providers. Results from the current meta-analysis demonstrate that brief tobacco cessation interventions that can be implemented in the IPC setting are effective. Future research in this area might examine ways to improve the dissemination and implementation of brief interventions for tobacco use in IPC settings.
New twist on artificial muscles

Lightweight artificial muscle fibers that can match the large tensile stroke of natural muscles have been elusive. In particular, low stroke, limited cycle life, and inefficient energy conversion have combined with high cost and hysteretic performance to restrict practical use. In recent years, a new class of artificial muscles, based on highly twisted fibers, has emerged that can deliver more than 2,000 J/kg of specific work during muscle contraction, compared with just 40 J/kg for natural muscle. Thermally actuated muscles made from ordinary polymer fibers can deliver long-life, hysteresis-free tensile strokes of more than 30% and torsional actuation capable of spinning a paddle at speeds of more than 100,000 rpm. In this perspective, we explore the mechanisms and potential applications of present twisted fiber muscles and the future opportunities and challenges for developing twisted muscles having improved cycle rates, efficiencies, and functionality. We also demonstrate artificial muscle sewing threads and textiles and coiled structures that exhibit nearly unlimited actuation strokes. In addition to robotics and prosthetics, future applications include smart textiles that change breathability in response to temperature and moisture and window shutters that automatically open and close to conserve energy.
Strategic bargaining in wireless networks: basics, opportunities and challenges

Strategic bargaining cooperative games have found extensive applications to resource management in wireless networks. In this survey, basics of a strategic bargaining game and solution concepts are firstly presented. Geometrical interpretations are introduced to better understand real meanings of them. Then, the authors survey the applications of various strategic bargaining games for the emerging wireless networks, where the authors concentrate on several interesting problems based on their previous systematic studies: (i) distributed resource management design for cognitive radio networks based on geometrical interpretation of the cooperative solution; (ii) asymmetric bargaining modelling for green communications; (iii) a unified utility tradeoff design between spectral and energy efficiency in heterogeneous cellular networks; (iv) the cooperative rate splitting game for Long Term Evolution-coordinated multi-point system; and (v) a general bargaining formulation with different tradeoffs between efficiency and fairness. In addition, the authors survey the applications of strategic bargaining games to cooperation incentive mechanism, bargaining game on capacity region of interference channel and multiuser and multimedia applications. Finally, challenges and potential research direction are summarised in this work.
Dynamic joint model of capacitive charge pumps and on‐chip photovoltaic cells for CMOS micro‐energy harvesting

On‐chip energy harvesting by means of integrated photovoltaic cells in standard CMOS technology can be successfully used to recharge or power‐up integrated circuits with the use of charge pumps for voltage boosting. In this paper, a tool to facilitate the design of such structures is proposed consisting of an accurate model of the joint dynamics of the micro‐photovoltaic cell and a capacitive DC/DC converter in the slow‐switching limit regime. The model takes into account both the top and bottom parasitic capacitances of the flying capacitors. We assume a classical model for the photodiode whose photogenerated current is extracted from device‐level simulations. The joint model is verified by circuit‐level simulations achieving high accuracy and computation time savings of up to 1700×. The joint model shows that the voltage generated by an integrated photovoltaic cell connected to a capacitive DC/DC converter is not constant even under constant illumination. This phenomenon can only be reproduced through the joint model and failing to take it into account results in an error in the estimation of the time needed by the DC/DC converter to reach a given output voltage. We also demonstrate that the maximum output voltage reached by a DC/DC converter in the slow‐switching limit regime when a photovoltaic cell is used as energy transducer depends on the switching frequency. Finally, the applicability of the model is illustrated through the optimization of time response and charge efficiency for the Dickson, Fibonacci, and exponential topologies in the case of implantable devices. Copyright © 2016 John Wiley & Sons, Ltd.
Automatic facial expression interpretation: Where human-computer interaction, artificial intelligence and cognitive science intersect

We discuss here one of our projects, aimed at developing an automatic facial expression interpreter, mainly in terms of signaled emotions. We present some of the relevant findings on facial expressions from cognitive science and psychology that can be understood by and be useful to researchers in Human-Computer Interaction and Artificial Intelligence. We then give an overview of HCI applications involving automated facial expression recognition, we survey some of the latest progresses in this area reached by various approaches in computer vision, and we describe the design of our facial expression recognizer. We also give some background knowledge about our motivation for understanding facial expressions and we propose an architecture for a multimodal intelligent interface capable of recognizing and adapting to computer users? affective states. Finally, we discuss current interdisciplinary issues and research questions which will need to be addressed for further progress to be made in the promising area of computational facial expression recognition.
Topographic Organization of Cholinergic Innervation From the Basal Forebrain to the Visual Cortex in the Rat

Acetylcholine is an important neurotransmitter for the regulation of visual attention, plasticity, and perceptual learning. It is released in the visual cortex predominantly by cholinergic projections from the basal forebrain, where stimulation may produce potentiation of visual processes. However, little is known about the fine organization of these corticopetal projections, such as whether basal forebrain neurons projecting to the primary and secondary visual cortical areas (V1 and V2, respectively) are organized retinotopically. The aim of this study was to map these basal forebrain-V1/V2 projections. Microinjections of the fluorescent retrograde tracer cholera toxin b fragment in different sites within V1 and V2 in Long–Evans rats were performed. Retrogradely labeled cell bodies in the horizontal and vertical limbs of the diagonal band of Broca (HDB and VDB, respectively), nucleus basalis magnocellularis, and substantia innominata (SI), were mapped ex vivo with a computer-assisted microscope stage controlled by stereological software. Choline acetyltranferase immunohistochemistry was used to identify cholinergic cells. Our results showed a predominance of cholinergic projections coming from the HDB. These projections were not retinotopically organized but projections to V1 arised from neurons located in the anterior HDB/SI whereas projections to V2 arised from neurons located throughout the whole extent of HDB/SI. The absence of a clear topography of these projections suggests that BF activation can stimulate visual cortices broadly.
FPGA-Based Architecture for Managing Ultrasonic Beacons in a Local Positioning System

During past decades, local positioning systems (LPSs) have become more and more important for different robotic and automation applications, as well as for service-oriented developments. One of the emerging technologies for that purpose is ultrasounds, since they provide positioning errors in the range of centimeters with low-cost deployments. Nevertheless, they present some drawbacks, which constrain their use and spreading. The performance of ultrasonic LPS (ULPS) can be significantly enhanced by applying encoding techniques to ultrasonic transmissions. The use of encoding techniques and the deployment of multiple beacon units require the availability of more sophisticated control modules capable of carrying out a suitable configuration of the system operation and processing the ultrasonic transmissions in these complex environments. In this way, this paper presents the design of a system in charge of managing a beacon unit used for the deployment of ULPS in wide spaces. The design consists of a system-on-chip architecture based on a field-programmable gate array device. The proposed system allows the flexible run-time configuration of a beacon unit in terms of the data to be transmitted and the bandwidth and frequencies used. The design has been successfully validated in an ULPS installed in a highly complex environment, where a robot has been correctly positioned during navigation.