Miracle-dz/UniFAR-FTUs huggingface dataset:
Enablers and barriers to the development of interprofessional collaboration between physicians and osteopaths: A mixed methods study

ABSTRACT Osteopathy is a complementary and alternative medicine (CAM) that is growing in popularity. Increasing numbers of parents are seeking pediatric osteopathic care in addition to conventional medical care. Information about the development of interprofessional collaboration (IPC) between these practitioners is scarce. This explanatory sequential mixed methods study aimed to explore enablers of and barriers to the development of IPC between physicians and osteopaths involved with pediatric patients in primary care in Quebec, Canada. Postal questionnaires about collaborative practices were first sent to all physicians and osteopaths working with pediatric patients in Quebec. Semi-structured individual interviews were then conducted with a subset of 10 physicians and 11 osteopaths. A total of 274 physicians (14%) and 297 osteopaths (42%) completed the survey. Forty-five percent (n = 122) of physicians reported that they referred at least one pediatric patient per month to an osteopath. Thirty-six percent (n = 96) of physicians and 41% (n = 122) of osteopaths indicated having professional relationships. Personal consultation, professional relationship, perceived utility of osteopathy and community practice were positively associated with osteopathic referrals. According to participants, the strongest enabler of the development of collaboration was positive clinical results reported by parents. Additional enablers included the osteopath having previous health professionals training such as physiotherapist, pediatric experience, mutual respect for professional boundaries and complementarity, perceived safety of osteopathy, and parents’ requests for collaboration. Barriers were the absence of a common language, the organizational and legal context, uncertainty regarding one another’s roles, lack of interprofessional interactions, and limited scientific evidence. These results related to enablers of and barriers to collaboration between physicians and osteopaths and the illustration of their dynamic interaction could be used to guide efforts to promote productive collaboration and safe patient-oriented care.
Structure–activity relationships of bumetanide derivatives: correlation between diuretic activity in dogs and inhibition of the human NKCC2A transporter

The N‐K‐Cl cotransporters (NKCCs) mediate the coupled, electroneutral movement of Na+, K+ and Cl− ions across cell membranes. There are two isoforms of this cation co‐transporter, NKCC1 and NKCC2. NKCC2 is expressed primarily in the kidney and is the target of diuretics such as bumetanide. Bumetanide was discovered by screening ∼5000 3‐amino‐5‐sulfamoylbenzoic acid derivatives, long before NKCC2 was identified in the kidney. Therefore, structure–activity studies on effects of bumetanide derivatives on NKCC2 are not available.
Bilateral Sampling Randomized Singular Value Decomposition

Designing fast singular value decomposition (SVD) is significantly interesting in applications. The random direct SVD (RSVD) has provided a fast scheme to compute the well-approximate SVD by unilateral randomized sampling. In this paper, we present an efficient random algorithm in a bilateral sampling way. We also prove that the proposed algorithms can be bounded well and have less computational complexity compared to RSVD when the objective matrix is approximately square. Numerical experiments on graph Laplacian and Hilbert matrix demonstrate the efficiency and stability of the proposed methods.
On Learning Mixtures of Well-Separated Gaussians

We consider the problem of efficiently learning mixtures of a large number of spherical Gaussians, when the components of the mixture are well separated. In the most basic form of this problem, we are given samples from a uniform mixture of k standard spherical Gaussians with means mu_1,. ,mu_k in R^d, and the goal is to estimate the means up to accuracy &#x03B4; using poly(k,d, 1/&#x03B4;) samples.In this work, we study the following question: what is the minimum separation needed between the means for solving this task? The best known algorithm due to Vempala and Wang [JCSS 2004] requires a separation of roughly min{k,d}^{1/4}. On the other hand, Moitra and Valiant [FOCS 2010] showed that with separation o(1), exponentially many samples are required. We address the significant gap between these two bounds, by showing the following results. &#x2022; We show that with separation o(&#x221A;log k), super-polynomially many samples are required. In fact, this holds even when the k means of the Gaussians are picked at random in d=O(log k) dimensions. &#x2022; We show that with separation &#x03A9;(&#x221A;log k), poly(k,d,1/&#x03B4;) samples suffice. Notice that the bound on the separation is independent of &#x03B4;. This result is based on a new and efficient accuracy boosting algorithm that takes as input coarse estimates of the true means and in time (and samples) poly(k,d, 1&#x03B4;) outputs estimates of the means up to arbitrarily good accuracy &#x03B4; assuming the separation between the means is &#x03A9;min &#x221A;(log k),&#x221A;d) (independently of &#x03B4;). The idea of the algorithm is to iteratively solve a diagonally dominant system of non-linear equations.We also (1) present a computationally efficient algorithm in d=O(1) dimensions with only &#x03A9;(&#x221A;{d}) separation, and (2) extend our results to the case that components might have different weights and variances. These results together essentially characterize the optimal order of separation between components that is needed to learn a mixture of k spherical Gaussians with polynomial samples.
Using Mobile Health Intervention to Improve Secondary Prevention of Coronary Heart Diseases in China: Mixed-Methods Feasibility Study

Background Coronary heart disease (CHD) is the leading cause of cardiovascular mortality worldwide, yet implementation of evidence-based strategies for secondary prevention remains suboptimal. Objective This study aimed to evaluate the feasibility, specifically the usability and acceptability, and estimate the preliminary effectiveness of a mobile health (mHealth) intervention targeting both physicians and patients to improve adherence to evidence-based medications and lifestyle modifications. Methods We conducted a 12-week pre-post interventional pilot study at two sites in Shanghai and Hainan, China. Physicians used the app designed in this study to prescribe evidence-based medicines and record patient information. Eligible and consenting patients received automatic text messages or voice calls 4 to 5 times per week for 12 weeks on medication adherence and healthy behaviors. Interviews were conducted among 10 physicians and 24 patients at the two sites for their thoughts on medication adherence and feedback on the usability and acceptability. Questions on usability and acceptability were also asked in a patient follow-up survey. With regard to estimating effectiveness, the primary outcome was medication adherence (as estimated by the Morisky Green Levine Scale) at 12 weeks. Secondary outcomes included physical activity, smoking status, fruits and vegetables consumption, and facility visit frequency. Results Interview findings and patient survey showed the good usability and acceptability of the intervention. Among 190 patients who completed the intervention, there was a significant increase in medication adherence (odds ratio [OR] 1.80, 95% CI 1.14-2.85). The study also showed decrease of smokers’ percentage (−5%, P=.05), increase of daily vegetables consumption frequency (+0.3/day, P=.01), and community health care center visit frequency (+3 in 3 months, P=.04). The following site-specific differences were noted: medication adherence appeared to increase in Hainan (OR 14.68, 95% CI 5.20-41.45) but not in Shanghai (OR 0.61, 95% CI 0.33-1.12). Conclusions Our study demonstrated that the intervention was feasible in both a tertiary care center and an urban community health center in China. Preliminary results from pre-post comparison suggest the possibility that provider and patient-linked mHealth interventions may improve medication adherence and lifestyle modifications among CHD patients, especially in resource-scarce settings. Randomized controlled trials are needed to verify the findings.
Emerging Trends in Personality Identification Using Online Social Networks—A Literature Survey

Personality is a combination of all the attributes—behavioral, temperamental, emotional, and mental—that characterizes a unique individual. Ability to identify personalities of people has always been of great interest to the researchers due to its importance. It continues to find highly useful applications in many domains. Owing to the increasing popularity of online social networks, researchers have started looking into the possibility of predicting a user's personality from his online social networking profile, which serves as a rich source of textual as well as non-textual content published by users. In the process of creating social networking profiles, users reveal a lot about themselves both in what they share and how they say it. Studies suggest that the online social networking websites are, in fact, a relevant and valid means of communicating personality. In this article, we review these various studies reported in literature toward identification of personality using online social networks. To the best of our knowledge, this is the first reported survey of its kind at the time of submission. We hope that our contribution, especially in summarizing the previous findings and in identifying the directions for future research in this area, would encourage researchers to do more work in this budding area.
UIPicker: User-Input Privacy Identification in Mobile Applications

Identifying sensitive user inputs is a prerequisite for privacy protection. When it comes to today's program analysis systems, however, only those data that go through well-defined system APIs can be automatically labelled. In our research, we show that this conventional approach is far from adequate, as most sensitive inputs are actually entered by the user at an app's runtime: in our research, we inspect 17, 425 top apps from Google Play, and find that 35.46% of them involve sensitive user inputs. Manually marking them involves a lot of effort, impeding a large-scale, automated analysis of apps for potential information leaks. To address this important issue, we present UIPicker, an adaptable framework for automatic identification of sensitive user inputs. UIPicker is designed to detect the semantic information within the application layout resources and program code, and further analyze it for the locations where security-critical information may show up. This approach can support a variety of existing security analysis on mobile apps. We further develop a runtime protection mechanism on top of the technique, which helps the user make informed decisions when her sensitive data is about to leave the device in an unexpected way. We evaluate our approach over 200 randomly selected popular apps on Google-Play. UIPicker is able to accurately label sensitive user inputs most of the time, with 93.6% precision and 90.1% recall.
A Novel Approach for Model-Based Control of Smooth and Lossless Gear Shifts

In contrast to conventional and classical hybrid electric transmissions, multimode (hybrid electric) transmissions open new perspectives in gear shifting: The tradeoff between avoidance of propulsion torque interruption and dissipation in clutches can be resolved by smart utilization of the second, coequal, propulsion element, and rearrangement of standard shift phases (torque phase and inertia phase). The resulting smooth and lossless gear shifts reach a new level of performance combining comfort and efficiency. Therefore, modeling and control of these gear shifts is an ongoing automotive research topic since several years. However, so far there is no systematic, model-based approach, which would enable broad application in industry. This paper contributes to bridge this gap. The key point is a systematic determination of a consistent set of generalized coordinates, corresponding to a specific gear, i.e., set of locked clutches. This is achieved by exploiting the mechanical peculiarities of drivetrain topologies. Based on this, a straightforward transformation is proposed to derive a comprehensive state-space model for each gear of a given topology. This enables the statement of the control problem for smooth and lossless gear shifting in a novel compact and general form. Finally, a new shift procedure and a generic-model-based feedforward control is proposed and applied to an exemplary multimode transmission. Promising first simulation results confirm the significance of the proposed approach for further investigation and application.
Toward Programmable Microwave Photonics Processors

We describe the advances that we, and others, have reported during the last years in the area of programmable microwave photonic processors. Following a brief historical sketch, we provide a detailed account of the salient theoretical and experimental results recently reported on waveguide mesh optical core processors. The incorporation of a waveguide mesh optical core into the general microwave photonics programmable processor architecture is then addressed. We illustrate through different examples how this processor can be programmed to enable the most important functionalities required in microwave photonics.
Temporal validation of a simplified blastocyst grading system

Abstract We have recently established the clinical effectiveness and credibility of a simplified blastocyst grading system by demonstrating its prognostic potential and the inter- and intra-observer variability associated with it. To be considered clinically useful, however, the grading system also needs to be accurate (i.e. well calibrated with good discriminative ability). This study prospectively evaluates the performance of the grading system on subsequent patients from the same IVF unit in an attempt to temporally validate the model. All day 5 single embryo transfers between 1st July 2012 and 30th June 2014 were included in the study. The observed implantation, clinical pregnancy and live birth rates according to grade of embryo transferred were compared to the expected rates as predicted by the development data set and the statistical significance of any differences between the two were calculated using the Chi-square test. A total of 435 single embryo transfers were included. For each grade of embryo transferred, there was generally no significant difference between the observed and expected frequencies of implantation, clinical pregnancy and live birth suggesting that the simplified blastocyst grading system is accurate and temporal validation has been satisfactorily demonstrated. It is now necessary to externally validate the grading system to prove generality before further dissemination.
Processor array design with FPGA area constraint

Digital signal processing algorithms with multiple shift-invariant dependence graphs (DGs) can be mapped to field programmable gate array hardware in many different types of systolic processor arrays. Because of the finite amount of hardware resources, the problem is to use a "right" amount of hardware in a specific configuration so to maximize the processing speed. In this paper, the problem of finding the right processor array configuration is formulated as a constrained optimization problem where the cost function includes not only the cost of individual processor arrays but also the cost of interfacing circuits. Three heuristic algorithms are presented for the optimization problem. Among them, both the Lth axial neighbor algorithm and the simulated annealing algorithm produce good results on a test case. Simulation results on the test case also indicate that the initial configuration is important in getting a good configuration for both algorithms. The Lth axial neighbor algorithm has the extra advantage of requiring less amount of performance tuning.
Development of power assist system with motion estimation using model predictive control

Many kinds of control methods using electromyo-gram signals have been proposed for power-assist robots or electric prosthesises recently. However, it is considered that it is difficult to be adapted to unknown environment or conditions and to realize high power-assist ratio. Therefore, we propose a new power-assist system using model predictive control that can realize a stable power-assist with high ratio and predict the future human fingers touque and the future trajectory in real time. Our power-assist system is composed of a combination of a MPC system based on an expansion plant and a MPC system based on a plant model.
Detection of Coxiella burnetii in heart valve sections by fluorescence in situ hybridization

Purpose. Infective endocarditis is a severe and potentially fatal disease. Nearly a third of all cases remain culture‐negative, making a targeted and effective antibiotic therapy of patients challenging. In the past years, fluorescence in situ hybridization (FISH) has proven its value for the diagnosis of infective endocarditis, particularly when it is caused by fastidious bacteria. To increase the number of infective endocarditis causing agents, which can be identified by FISH, we designed and optimized a FISH‐probe for the specific detection of Coxiella burnetii in heart valve tissue. Methodology. Even with specific probes the detection and identification of bacteria can be complicated by the high autofluorescence due to calcification of the analysed tissue. To overcome this problem, we developed a protocol to detect C. burnetii by hybridizing, stripping and reprobing the identical section with different species‐specific probes repeatedly. Results/Key findings. The newly designed specific FISH probe and the developed protocol exemplarily allowed us to unequivocally identify C. burnetii in tissue sections of a patient with infective endocarditis. Conclusion. This method provides an add‐on to existing protocols for the unambiguous diagnosis of bacteria directly within tissues or other difficult tissue samples in cases with small sample size and limited sections.
A compact dualband circularly polarized GNSS antenna

A compact dual-band circularly polarized (CP) stacked slotted-microstrip antenna is proposed for global navigation satellite systems (GNSS). The measured results of the prototype antenna with an overall volume of 0. 265λ<inf>o</inf> × 0. 265λ<inf>o</inf> × 0. 02λ<inf>o</inf> at 1.227 GHz are: the bandwidth of 1.63% (1.219 GHz–1.241 GHz) at the L2-band and 2.56% (1.54 GHz–1.58 GHz) at L1-band for 2-VSWR; 1.0% (1.22 GHz–1.231 GHz) at the L2-band and 0.84% (1.552 GHz–1.565 GHz) at the L1-band for 3-dB axial ratio (AR); maximum gain of 3.9dBic at 1.226 GHz and 4.6dBic at 1.555 GHz; and 3-dB AR beamwidth of > 145° across the 3-dB AR bandwidth for both bands.
Interaction Proteomics Analysis of Polycomb Proteins Defines Distinct PRC1 Complexes in Mammalian Cells*

Polycomb group (PcG) proteins maintain transcriptional repression of hundreds of genes involved in development, signaling or cancer using chromatin-based epigenetic mechanisms. Biochemical studies in Drosophila have revealed that PcG proteins associate in at least two classes of protein complexes known as Polycomb repressive complexes 1 and 2 (PRC1 and PRC2). Drosophila core PRC1 is composed of four subunits, Polycomb (Pc), Sex combs extra (Sce), Polyhomeotic (Ph), and Posterior sex combs (Psc). Each of these proteins has multiple orthologs in vertebrates classified respectively as the CBX, RING1/RNF2, PHC, and BMI1/PCGF families. Mammalian genomes encode five CBX family members (CBX2, CBX4, CBX6, CBX7, and CBX8) that are believed to have distinct biological functions. Here, we applied a tandem affinity purification (TAP) approach coupled with tandem mass spectrometry (MS/MS) methodologies in order to identify interacting partners of CBX family proteins under the same experimental conditions. Our analysis identified with high confidence about 20 proteins co-eluted with CBX2 and CBX7 tagged proteins, about 40 with CBX4, and around 60 with CBX6 and CBX8. We provide evidences that the CBX family proteins are mutually exclusive and define distinct PRC1-like protein complexes. CBX proteins also interact with different efficiencies with the other PRC1 components. Among the novel CBX interacting partners, protein kinase 2 associates with all CBX-PRC1 protein complexes, whereas 14-3-3 proteins specifically bind to CBX4. 14-3-3 protein binding to CBX4 appears to modulate the interaction between CBX4 and the BMI1/PCGF components of PRC1, but has no effect on CBX4-RING1/RNF2 interaction. Finally, we suggest that differences in CBX protein interactions would account, at least in part, for distinct subnuclear localization of the CBX family members.
The CASE of FEMU: Cheap, Accurate, Scalable and Extensible Flash Emulator

FEMU is a software (QEMU-based) flash emulator for fostering future full-stack software/ hardware SSD research. FEMU is cheap (opensourced), relatively accurate (0.5-38% variance as a drop-in replacement of OpenChannel SSD), scalable (can support 32 parallel channels/chips), and extensible (support internal-only and split-level SSD research).
Heterogeneous Features Fusion with Collaborative Representation Learning for 3D Action Recognition

Human action recognition of depth sensors has drawn wide attentions in computer vision and multimedia processing areas. In contrast to simple periodic actions, irrelevant actions or sharing sub-actions between different classes of two-person non-periodic interactions make this task challenging. This paper presents heterogeneous features fusion with Collaborative Representation (CR) to address this challenge. Two effective high dimensional low-level features are developed from depth image sequence and skeleton pose sequence respectively. In the Canonical Correlations Analysis (CCA) feature space of these two features, Collaborative Representation (CR) is learned and adopted as the final high-level discriminative representation. Experiments on two depth action datasets (SBU Kinect-Interaction and MSR Action 3D) show that the proposed method is superior to the state-of-the-art methods compared, including some recent deep learning based methods.
Computer Modelling of Dynamic Fracture Experiments

In this work the time-domain boundary element method (BEM) is applied to simulate dynamic fracture experiments. The fast fracture is modelled by adding new boundary elements at the crack tip. The direction of crack growth is perpendicular to the direction of maximum circumferencial stress. The time dependent loading of specimens and velocities of crack growth are taken from experiments as input data for computer simulations. The method is used to analyze: a short beam specimen, a special mixed-mode specimen and a three-point bend specimen subjected to impact loads. The dynamic stress intensity factors (DSIF) and the crack paths are compared with the results obtained by other authors who used the finite element method (FEM) and experimental methods.