Miracle-dz/UniFAR-FTUs huggingface dataset:
The Universal Patient Centeredness Questionnaire: scaling approaches to reduce positive skew

Purpose Surveys of patients’ experiences typically show results that are indicative of positive experiences. Unbalanced response scales have reduced positive skew for responses to items within the Universal Patient Centeredness Questionnaire (UPC-Q). The objective of this study was to compare the unbalanced response scale with another unbalanced approach to scaling to assess whether the positive skew might be further reduced. Patients and methods The UPC-Q was included in a patient experience survey conducted at the ward level at six hospitals in Norway in 2015. The postal survey included two reminders to nonrespondents. For patients in the first month of inclusion, UPC-Q items had standard scaling: poor, fairly good, good, very good, and excellent. For patients in the second month, the scaling was more positive: poor, good, very good, exceptionally good, and excellent. The effect of scaling on UPC-Q scores was tested with independent samples t-tests and multilevel linear regression analysis, the latter controlling for the hierarchical structure of data and known predictors of patient-reported experiences. Results The response rate was 54.6% (n=4,970). Significantly lower scores were found for all items of the more positively worded scale: UPC-Q total score difference was 7.9 (P<0.001), on a scale from 0 to 100 where 100 is the best possible score. Differences between the four items of the UPC-Q ranged from 7.1 (P<0.001) to 10.4 (P<0.001). Multivariate multilevel regression analysis confirmed the difference between the response groups, after controlling for other background variables; UPC-Q total score difference estimate was 8.3 (P<0.001). Conclusion The more positively worded scaling significantly lowered the mean scores, potentially increasing the sensitivity of the UPC-Q to identify differences over time and between providers. However, none of the groups exhibited large positive skew and ceiling effects, implying that such effects might not be a big measurement problem for either scaling format. We recommend using the standard scaling in surveys producing external indicators for inter-provider comparisons. The more positively worded scaling has greater relevance for local measurement work where the results of patient experience surveys have shown large positive skew, and intra-provider comparison is the primary goal.
Bayesian Hierarchical Modelling for Tailoring Metric Thresholds

Software is highly contextual. While there are cross-cutting 'global' lessons, individual software projects exhibit many 'local' properties. This data heterogeneity makes drawing local conclusions from global data dangerous. A key research challenge is to construct locally accurate prediction models that are informed by global characteristics and data volumes. Previous work has tackled this problem using clustering and transfer learning approaches, which identify locally similar characteristics. This paper applies a simpler approach known as Bayesian hierarchical modeling. We show that hierarchical modeling supports cross-project comparisons, while preserving local context. To demonstrate the approach, we conduct a conceptual replication of an existing study on setting software metrics thresholds. Our emerging results show our hierarchical model reduces model prediction error compared to a global approach by up to 50%.
Online Vehicle Front–Rear Distance Estimation With Urban Context-Aware Trajectories

Access to accurate relative front–rear distance information between vehicles is of great interest to drivers as such information can be utilized to improve driving safety. Acquiring such information based on systems such as the global positioning system (GPS) in urban settings is very challenging due to the high complexity of urban environments. In this paper, we propose a scheme, called relative urban positioning system (RUPS), to tackle the relative distance fixing problem. We first investigate the pervasive global system for mobile communication (GSM) signals and find that the received signal strength indicator measures of multiple GSM channels collected over a distance has ideal temporal–spatial characteristics for temporary fingerprinting. With this key insight, an RUPS-enabled vehicle first perceives the information of its GSM-aware trajectory while moving. Then, by exchanging and comparing its own trajectory with that of a neighboring vehicle, the vehicle can identify common locations overlapped between trajectories of itself and this neighbor. Finally, the relative distance between this pair of vehicles can be perceived by further comparing their geographical trajectories based on an identified common location. As a result, RUPS is a fully distributed and lightweight scheme, requiring only a minimum hardware deployment, and does not need synchronization between vehicles or any preconstructed signal maps. We implement a prototype system to validate the feasibility of the RUPS design. Extensive trace-driven simulation results show that RUPS can work stably under complex urban environments and overwhelm the performance of GPS by 2.7 times on average.
Situation semantics for things: everyday artifacts that come with pre-specified behaviours

This paper proposes the idea of providing artifacts with specifications of their situation transforming behaviour. Such specifications can be created by designers (and so would come together with the artifact on purchase) or end-users to implement smart things that transform their environment in meaningful ways. The specifications are based on situation semantics first developed for studies in linguistics.
Electricity Consumption Model Analysis based on Sparse Principal Components

The well-being of people, industry and economy depends on reliable, sustainable and affordable energy. The analysis on energy consumption model, especially on electricity consumption model, plays an important role in providing guidance that makes energy system stable and economical. In this paper, clustering based on electricity consumption model is imposed to categorize consumers, and Sparse Principal Components Analysis (SPCA) is employed to analyse electricity consumption model for each group clustered. Experimental results show that our methods can automatically divide a day into peak times and off-peak times, so as to reveal in detail the electricity consumption model of different types of consumers. Additionally, we study the relationships between social background of consumers and their electricity consumption model. Our experimental results show that social background of consumers has impact on their consumption model, as expected, but cannot fully determine it.
Biomedical Image Edge Detection Based on CNN

In this paper, the technique of biomedical image is presented by employing cellular neural networks (CNN) and linear matrix inequality (LMI). The main objective is to obtain the templates. Based on Cellular neural networks (CNN) is a high-speed parallel processor, this paper proposes a optimized templates for biomedical image edge detection.
Vesiculated Long Non-Coding RNAs: Offshore Packages Deciphering Trans-Regulation between Cells, Cancer Progression and Resistance to Therapies

Extracellular vesicles (EVs) are nanosized vesicles secreted from virtually all cell types and are thought to transport proteins, lipids and nucleic acids including non-coding RNAs (ncRNAs) between cells. Since, ncRNAs are central to transcriptional regulation during developmental processes; eukaryotes might have evolved novel means of post-transcriptional regulation by trans-locating ncRNAs between cells. EV-mediated transportation of regulatory elements provides a novel source of trans-regulation between cells. In the last decade, studies were mainly focused on microRNAs; however, functions of long ncRNA (lncRNA) have been much less studied. Here, we review the regulatory roles of EV-linked ncRNAs, placing a particular focus on lncRNAs, how they can foster dictated patterns of trans-regulation in recipient cells. This refers to envisaging novel mechanisms of epigenetic regulation, cellular reprogramming and genomic instability elicited in recipient cells, ultimately permitting the generation of cancer initiating cell phenotypes, senescence and resistance to chemotherapies. Conversely, such trans-regulation may introduce RNA interference in recipient cancer cells causing the suppression of oncogenes and anti-apoptotic proteins; thus favoring tumor inhibition. Collectively, understanding these mechanisms could be of great value to EV-based RNA therapeutics achieved through gene manipulation within cancer cells, whereas the ncRNA content of EVs from cancer patients could serve as non-invasive source of diagnostic biomarkers and prognostic indicators in response to therapies.
Focal Vibration Stretches Muscle Fibers by Producing Muscle Waves

Focal vibration is an effective intervention for the management of spasticity. However, its neuromechanical effects, particularly how tonic vibration reflex is induced explicitly, remain implicit. In this paper, we utilize a high-speed camera and a method of image processing to quantify the muscle vibration rigorously and disclose the neuromechanical mechanism of focal vibration. The vibration of 75 Hz is applied on the muscle belly of the biceps brachii and muscle responses are captured by a high-speed camera in profile. The muscle silhouettes are identified by the Canny edge detector to represent the stretch of muscle fibers, and the consistency between the muscle stretch and profile deformation has been confirmed by the magnetic resonance imaging in advance. Oscillations of muscle points discretized by pixels are identified by the fast Fourier transformation, respectively, and results demonstrate that focal vibration stretches muscle by producing muscle waves. Specifically, each point vibrates harmonically, and, given the linear phase modulation with transverse position, the muscle vibration propagates as traveling waves. The propagation of muscle waves is associated with muscle stretch, whose frequency is the same with the vibrator due to the curved baseline, and thus induces the tonic vibration reflex via spinal circuits.
MAGNETIC CYCLES IN A CONVECTIVE DYNAMO SIMULATION OF A YOUNG SOLAR-TYPE STAR

Young solar-type stars rotate rapidly and many are magnetically active. Some appear to undergo magnetic cycles similar to the 22 yr solar activity cycle. We conduct simulations of dynamo action in rapidly rotating suns with the three-dimensional magnetohydrodynamic anelastic spherical harmonic (ASH) code to explore dynamo action achieved in the convective envelope of a solar-type star rotating at five times the current solar rotation rate. We find that dynamo action builds substantial organized global-scale magnetic fields in the midst of the convection zone. Striking magnetic wreaths span the convection zone and coexist with the turbulent convection. A surprising feature of this wreath-building dynamo is its rich time dependence. The dynamo exhibits cyclic activity and undergoes quasi-periodic polarity reversals where both the global-scale poloidal and toroidal fields change in sense on a roughly 1500 day timescale. These magnetic activity patterns emerge spontaneously from the turbulent flow and are more organized temporally and spatially than those realized in our previous simulations of the solar dynamo. We assess in detail the competing processes of magnetic field creation and destruction within our simulations that contribute to the global-scale reversals. We find that the mean toroidal fields are built primarily through an Ω-effect, while the mean poloidal fields are built by turbulent correlations which are not well represented by a simple α-effect. During a reversal the magnetic wreaths propagate toward the polar regions, and this appears to arise from a poleward propagating dynamo wave. As the magnetic fields wax and wane in strength and flip in polarity, the primary response in the convective flows involves the axisymmetric differential rotation which varies on similar timescales. Bands of relatively fast and slow fluid propagate toward the poles on timescales of roughly 500 days and are associated with the magnetic structures that propagate in the same fashion. In the Sun, similar patterns are observed in the poleward branch of the torsional oscillations, and these may represent poleward propagating magnetic fields deep below the solar surface.
Scalable and precise multi-UAV indoor navigation using TDOA-based UWB localization

Ultra-wideband wireless positioning technologies based on IEEE 802.15. 4a have gained attention for various use cases requiring highly precise localization. Multi-rotor unmanned aerial vehicle (UAV) systems provide several sensors for stabilization and navigation. However, absolute indoor positioning poses a problem for autonomous robotic systems. The specific challenge addressed in this paper is enabling novel applications with autonomous UAV systems through tight integration with scalable and precise receiver-side time-difference of arrival (TDOA) based ultra-wideband (UWB) indoor localization. For the in-depth validation of the proposed approach, several experiments are performed. One proves the repeatability of the proposed method by following a predefined trajectory ten times achieving close to optical motion-capture based control performance, with a 3rd quartile of the alignment error lower than 10 cm. Another experiment addresses the simultaneous flight of three UAVs in close proximity and delivers an analysis of the real-time capabilities which in turn proves the multi-user scalability. The last experiment demonstrates a user-interactive application of the proposed approach in a logistics environment. A video along with the raw samples, reference data and processed positions of the aforementioned experiments is provided alongside this work.
Spexin Acts as Novel Regulator for Bile Acid Synthesis

Spexin is a novel hormone involved in obesity and diabetes while its biofunctional significance in lipid metabolism is still to be comprehended. Global metabolomic analysis in the present study revealed multiple metabolic pathways altered by spexin intraperitoneal (i.p.) injection in rat serum, which are highlighted by the changes in several bile acid metabolites. In rats, spexin (300 μg/kg) could dramatically reduce hepatic and circulating total bile acids (TBA) level compared with the controls. Correspondingly, treatment with spexin by i.p. injection for 28 days led to significant decrease in serum TBA and gallbladder weight in C57BL/6J mice. In enterohepatic circulation system, spexin effectively reduced TBA levels in mouse liver and gallbladder but not the intestine. Hepatic cholesterol 7α-hydroxylase 1 (CYP7A1) expression, unsurprisingly, was suppressed by spexin injection. Both GALR2 and GALR3 antagonists reversed the inhibitory effects of spexin on concentrations of serum TBA and 7 α-hydroxy-4-cholesten-3-one (C4), and hepatic CYP7A1 expression. Finally, negative correlations were observed between serum spexin and total cholesterol (TC), total bile acid (TBA), tauro-chenodeoxycholate (TCDCA), as well as glycochenodeoxycholate (GCDCA) in 91 healthy volunteers. These findings illuminate the intrinsic importance of spexin in the regulation of bile acid synthesis and metabolism.
Induced Hyperproteinemia and Its Effects on the Remodeling of Fat Bodies in Silkworm, Bombyx mori

Hyperproteinemia, which is characterized by an abnormally elevated plasma protein concentration (PPC), is a high-mortality, metabolic complication associated with severe liver and kidney disease. It is difficult to clinically distinguish the difference between the impacts of primary diseases and hyperproteinemia on tissues and organs, and there are no available animal models of hyperproteinemia. Here, we constructed an animal model of hyperproteinemia with a controllable PPC and no primary disease effects in the silkworm Bombyx mori that has attracted interest owing to its potential use in the pathological analysis of model animals. Silkworm have an open circulatory system in which each organ is directly immersed in hemolymph. The fat body (FB) of a silkworm, as a major organ for nutrient storage and energy metabolism, can effectively reflect hyperproteinemia-induced metabolic abnormalities in damaged visceral tissues. A pathogenesis study showed that hyperproteinemia attenuated cell autophagy and apoptosis by attenuating an endocrine hormone, thereby preventing FB remodeling during metamorphosis. Meanwhile, hyperproteinemia increased oxidative stress in the FB and resulted in a dysfunction of amino acid conversion. Supplementation with exogenous 20-hydroxyecdysone effectively mitigated the hyperproteinemia-mediated inhibition of FB remodeling.
Visual Analytics for Explainable Deep Learning

Recently, deep learning has been advancing the state of the art in artificial intelligence to a new level, and humans rely on artificial intelligence techniques more than ever. However, even with such unprecedented advancements, the lack of explanation regarding the decisions made by deep learning models and absence of control over their internal processes act as major drawbacks in critical decision-making processes, such as precision medicine and law enforcement. In response, efforts are being made to make deep learning interpretable and controllable by humans. This article reviews visual analytics, information visualization, and machine learning perspectives relevant to this aim, and discusses potential challenges and future research directions.
Decay of Relevance in Exponentially Growing Networks

We propose a new preferential attachment-based network growth model in order to explain two properties of growing networks: (1) the power-law growth of node degrees and (2) the decay of node relevance. In preferential attachment models, the ability of a node to acquire links is affected by its degree, its fitness, as well as its relevance which typically decays over time. After a review of existing models, we argue that they cannot explain the above-mentioned two properties (1) and (2) at the same time. We have found that apart from being empirically observed in many systems, the exponential growth of the network size over time is the key to sustain the power-law growth of node degrees when node relevance decays. We therefore make a clear distinction between the event time and the physical time in our model, and show that under the assumption that the relevance of a node decays with its age τ, there exists an analytical solution of the decay function f_R with the form f_R(τ) = ? ^(τ1). Other properties of real networks such as power-law alike degree distributions can still be preserved, as supported by our experiments. This makes our model useful in explaining and analysing many real systems such as citation networks.
Safeguarding Millimeter Wave Communications Against Randomly Located Eavesdroppers

Mm-wave offers a sensible solution to the capacity crunch faced by 5G wireless communications. This paper comprehensively studies physical layer security in a multi-input single-output mm-wave system, where multiple single-antenna eavesdroppers are randomly located. Concerning the specific propagation characteristics of mm-wave, we investigate two secure transmission schemes, namely maximum ratio transmitting beamforming and artificial noise (AN) beamforming. Specifically, we first derive closed-form expressions of the connection probability for both schemes. We then analyze the secrecy outage probability in both non-colluding eavesdroppers and colluding eavesdroppers scenarios. Also, we maximize the secrecy throughput under a secrecy outage probability constraint, and obtain optimal transmission parameters, especially the power allocation between AN and the information signal for AN beamforming. Numerical results are provided to verify our theoretical analysis. We observe that the density of eavesdroppers, the spatially resolvable paths of the destination and eavesdroppers all contribute to the secrecy performance and the parameter design of mm-wave systems.
Short-to-Medium-Range Order and Atomic Packing in Zr48Cu36Ag8Al8 Bulk Metallic Glass

Due to its excellent glass-forming ability (GFA), the Zr48Cu36Al8Ag8 bulk metallic glass (BMG) is of great importance in glass transition investigations and new materials development. However, due to the lack of detailed structural information, the local structure and atomic packing of this alloy is still unknown. In this work, synchrotron measurement and reverse Monte Carlo simulation are performed on the atomic configuration of a Zr-based bulk metallic glass. The local structure is characterized in terms of bond pairs and Voronoi tessellation. It is found that there are mainly two types of bond pairs in the configuration, as the body-centered cubic (bcc)-type and icosahedral (ico)-type bond pairs. On the other hand, the main polyhedra in the configuration are icosahedra and the bcc structure. That is, the bcc-type bond pairs, together with the ico-type bond pairs, form the bcc polyhedra, introducing the distortion in bcc clusters in short range. However, in the medium range, the atoms formed linear or planar structures, other than the tridimensional clusters. That is, the medium-range order in glass is of 1D or 2D structure, suggesting the imperfect ordered packing feature.
Alpinia Essential Oils and Their Major Components against Rhodnius nasutus, a Vector of Chagas Disease

Species of the genus Alpinia are widely used by the population and have many described biological activities, including activity against insects. In this paper, we describe the bioactivity of the essential oil of two species of Alpinia genus, A. zerumbet and A. vittata, against Rhodnius nasutus, a vector of Chagas disease. The essential oils of these two species were obtained by hydrodistillation and analyzed by GC-MS. The main constituent of A. zerumbet essential oil (OLALPZER) was terpinen-4-ol, which represented 19.7% of the total components identified. In the essential oil of A. vittata (OLALPVIT) the monoterpene β-pinene (35.3%) was the main constituent. The essential oils and their main constituents were topically applied on R. nasutus fifth-instar nymphs. In the first 10 min of application, OLALPVIT and OLALPZER at 125 μg/mL provoked 73.3% and 83.3% of mortality, respectively. Terpinen-4-ol at 25 μg/mL and β-pinene at 44 μg/mL provoked 100% of mortality. The monitoring of resistant insects showed that both essential oils exhibited antifeedant activity. These results suggest the potential use of A. zerumbet and A. vittata essential oils and their major constituents to control R. nasutus population.
A Collaborative Approach for Surface Inspection Using Aerial Robots and Computer Vision

Aerial robots with cameras on board can be used in surface inspection to observe areas that are difficult to reach by other means. In this type of problem, it is desirable for aerial robots to have a high degree of autonomy. A way to provide more autonomy would be to use computer vision techniques to automatically detect anomalies on the surface. However, the performance of automated visual recognition methods is limited in uncontrolled environments, so that in practice it is not possible to perform a fully automatic inspection. This paper presents a solution for visual inspection that increases the degree of autonomy of aerial robots following a semi-automatic approach. The solution is based on human-robot collaboration in which the operator delegates tasks to the drone for exploration and visual recognition and the drone requests assistance in the presence of uncertainty. We validate this proposal with the development of an experimental robotic system using the software framework Aerostack. The paper describes technical challenges that we had to solve to develop such a system and the impact on this solution on the degree of autonomy to detect anomalies on the surface.