Miracle-dz/UniFAR-FTUs huggingface dataset:
The challenge of improving patient safety in primary care.

Improving patient safety in primary care is critical for the NHS. The majority of clinical encounters occur in primary care,1,2 and the sector is becoming more exposed with earlier discharge from hospital, increasing prescriptions of potentially dangerous drugs by GPs, and an increasing fragmentation of services.3,4 Nonetheless, little research has been carried out into risk management in the primary care setting.5 Although primary care may in some ways constitute a less safe environment than acute care, it has a relatively small and flat organisational structure, and a strong tradition of multidisciplinary teamwork; both of which are important factors in fostering a safer culture.4 Nonetheless, some have maintained that there have historically been few effective levers for improving the quality and safety of primary care, partly due to GPs' status as self-employed contractors which has allegedly inhibited coordination and effective intervention.6 For some this was borne out by the relative lack of impact of the first Quality and Outcomes Framework (QOF) on the improvement of quality, …
Monolithic III‐V Nanowire Solar Cells on Graphene via Direct van der Waals Epitaxy

Dr. P. K. Mohseni, Dr. A. Behnam, Dr. J. D. Wood, X. Zhao, N. C. Wang, Prof. J. W. Lyding, Prof. E. Pop, Prof. X. Li Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana , Illinois 61801 , USA E-mail: xiuling@illinois.edu K. J. Yu, Prof. A. Rockett, Prof. J. A. Rogers Department of Materials Science and Engineering University of Illinois at Urbana-Champaign Urbana , Illinois 61801 , USA
Anatomy and flow in normal and ischemic microvasculature based on a novel temporal fractal dimension analysis algorithm using contrast enhanced ultrasound

Strategies for improvement of blood flow by promoting new vessel growth in ischemic tissue are being developed. Recently, contrast-enhanced ultrasound (CEU) imaging has been used to assess tissue perfusion in models of ischemia-related angiogenesis, growth-factor mediated angiogenesis, and tumor angiogenesis. In these studies, microvascular flow is measured in order to assess the total impact of adaptations at different vascular levels. High-resolution methods for imaging larger vessels have been developed in order to derive "angiograms" of arteries, veins, and medium to large microvessels. We describe a novel method of vascular bed (microvessel and arterial) characterization of vessel anatomy and flow simultaneously, using serial measurement of the fractal dimension (FD) of a temporal sequence of CEU images. This method is proposed as an experimental methodology to distinguish ischemic from nonischemic tissue. Moreover, an improved approach for extracting the FD unique to this application is introduced
Translational control of nociception via 4E-binding protein 1

Activation of the mechanistic/mammalian target of rapamycin (mTOR) kinase in models of acute and chronic pain is strongly implicated in mediating enhanced translation and hyperalgesia. However, the molecular mechanisms by which mTOR regulates nociception remain unclear. Here we show that deletion of the eukaryotic initiation factor 4E-binding protein 1 (4E-BP1), a major mTOR downstream effector, which represses eIF4E activity and cap-dependent translation, leads to mechanical, but not thermal pain hypersensitivity. Mice lacking 4E-BP1 exhibit enhanced spinal cord expression of neuroligin 1, a cell-adhesion postsynaptic protein regulating excitatory synapse function, and show increased excitatory synaptic input into spinal neurons, and a lowered threshold for induction of synaptic potentiation. Pharmacological inhibition of eIF4E or genetic reduction of neuroligin 1 levels normalizes the increased excitatory synaptic activity and reverses mechanical hypersensitivity. Thus, translational control by 4E-BP1 downstream of mTOR effects the expression of neuroligin 1 and excitatory synaptic transmission in the spinal cord, and thereby contributes to enhanced mechanical nociception. DOI: http://dx.doi. org/10.7554/eLife.12002. 001
The Atomic-to-Molecular Transition in Galaxies. I. An Analytic Approximation for Photodissociation Fronts in Finite Clouds

In this series of papers, we study the structure of the atomic-to-molecular transition in the giant atomic-molecular complexes that are the repositories of most molecular gas in galaxies, with the ultimate goal of attaining a better understanding of what determines galaxies’ molecular content. Here we derive an approximate analytic solution for the structure of a photodissociation region (PDR) in a cloud of finite size that is bathed in an external dissociating radiation field. Our solution extends previous work, which with few exceptions has been restricted to a one-dimensional treatment of the radiation field. We show that our analytic results compare favorably to exact numerical calculations in the one-dimensional limit. However, our more general geometry provides a more realistic representation than a semi-infinite slab for atomic-molecular complexes exposed to the interstellar radiation field, particularly in environments such as low-metallicity dwarf galaxies, where the curvature and finite size of the atomic envelope cannot be neglected. For clouds that are at least 20% molecular, we obtain analytic expressions for the molecular fraction in terms of properties of the gas and radiation field that are accurate to tens of percent, while for clouds of lower molecular content we obtain upper limits. As a side benefit, our analysis helps to clarify when self-shielding is the dominant process in H2 formation, and under what circumstances shielding by dust makes a significant contribution.
Joint Estimation of Clock Skew and Offset in Pairwise Broadcast Synchronization Mechanism

The problem of jointly estimating clock skew and offset for wireless sensor networks (WSNs) in a pairwise broadcast synchronization (PBS) protocol is considered. The random part of the delay is supposed to be an exponential random variable. We consider two estimators, i.e., joint maximum-likelihood estimator (JMLE) and generalized ML-like estimator (GMLLE) proposed by Leng and Wu . For both estimators, the corresponding algorithms are explicitly derived and presented. For the GMLLE, the corresponding performance bound based on the reduced set of observations is derived and the optimal value of a user-defined parameter is identified accordingly. At last, analytical results are corroborated by numerical experiments. We observe that: (i) JMLE usually outperforms GMLLE at the cost of larger computational complexity; (ii) JMLE, while achieving the same estimation accuracy as that of the LP method presented in , enjoys significantly lower computational complexity than that of the latter.
Dynamics of corticospinal motor control during overground and treadmill walking in humans

Increasing evidence suggests cortical involvement in the control of human gait. However, the nature of corticospinal interactions remains poorly understood. We investigated time-frequency analysis of electrophysiological activity acquired during treadmill and overground walking in 22 healthy, young adults. Participants walked at their preferred speed (4.2, SD 0.4 km h-1), which was matched across both gait conditions. Corticomuscular coherence (CMC) was assessed between EEG from bilateral sensorimotor cortices and EMG from the contralateral tibialis anterior (TA) muscle. Cortical power and CMC at theta, alpha, beta and gamma frequencies (4-45 Hz Hz) increased during the double support phase of the gait cycle for both overground and treadmill walking. High beta (21-30 Hz) CMC and theta (4-7 Hz) power was significantly increased during overground compared to treadmill walking. The phase spectra revealed positive time lags from EEG to EMG at alpha, beta and gamma frequencies, indicating that corticospinal interactions were governed by efferent activity. Phasic modulation of synchronization indicates that cortical control of human gait is not continuous but confined to the double support phase of the gait cycle. Frequency-band dependent differences in cortical and corticospinal synchronization between overground and treadmill walking suggest altered neural control for the two gait modalities, emphasizing the task-dependent nature of corticospinal processes during walking in humans. New & Noteworthy We investigated corticospinal dynamics during overground and treadmill walking in healthy adults. Corticospinal interactions at alpha, beta and gamma frequencies were of efferent nature and confined to the double support phase of the gait cycle. At high-beta frequencies corticospinal interactions were enhanced during overground compared to treadmill walking. These findings identify neurophysiological mechanisms that are important for understanding cortical control of human gait in health and disease.
Avian Vascular Imaging: A Review

Abstract Vascular diseases in birds are not uncommon, according to findings from postmortem surveys. Although atherosclerosis affecting psittacine birds appears overrepresented, some degenerative, infectious, neoplastic, and congenital vascular diseases may also occur. A variety of imaging diagnostic tools may be used to evaluate the avian vascular system, such as conventional radiography, fluoroscopy, rigid endoscopy, computed tomography, angiography, transcoelomic, and transesophageal ultrasound examination. The wide array of current diagnostic imaging tools offers the clinician capabilities to investigate avian cardiovascular abnormalities. Further research in this domain and constant efforts to apply several, and newer, vascular imaging modalities in clinical cases are needed to expand our avian cardiovascular knowledge base. The ability to diagnose vascular pathologic processes in small avian patients may be improved by recent developments in diagnostic imaging technology.
An electrophysiological approach to the diagnosis of neurogenic dysphagia: implications for botulinum toxin treatment

Objectives: Botulinum toxin (BTX) injection into the cricopharyngeal (CP) muscle has been proposed for the treatment of neurogenic dysphagia due to CP hyperactivity. The aim was to determine whether an electrophysiological method exploring oropharyngeal swallowing could guide treatment and discriminate responders from non-responders, based on the association of CP dysfunction with other electrophysiological abnormalities of swallowing. Methods: Patients with different neurological disorders were examined: Parkinson disease, progressive supranuclear palsy, multiple system atrophy-Parkinson variant, multiple system atrophy cerebellar variant, stroke, multiple sclerosis and ataxia telangiectasia. All patients presented with clinical dysphagia, and with complete absence of CP muscle inhibition during the hypopharyngeal phase of swallowing. Each patient underwent clinical and electrophysiological investigations before and after treatment with BTX into the CP muscle of one side (15 units of Botox). Clinical and electrophysiological procedures were performed in a blind manner by two different investigators. The following electrophysiological measures were analysed: (1) duration of EMG activity of suprahyoid/submental muscles (SHEMG-D); (2) duration of laryngopharyngeal mechanogram (LPM-D); (3) duration of the inhibition of the CP muscle EMG activity (CPEMG-ID); and (4) interval between onset of EMG activity of suprahyoid/submental muscles and onset of laryngopharyngeal mechanogram (I-SHEMG-LPM). Results: Two months after treatment, 50% of patients showed a significant improvement. Patients with prolonged or reduced SHEMG-D values and prolonged I-SHEMG-LPM values did not respond to BTX. Therefore, values for which BTX had no effect (warning values) were identified. Conclusions: This electrophysiological method can recognise swallowing abnormalities which may affect the outcome of the therapeutic approach to dysphagia with BTX treatment.
Exact Learning of Discretized Geometric Concepts

We first present an algorithm that uses membership and equivalence queries to exactly identify a discretized geometric concept defined by the union of m axis-parallel boxes in d-dimensional discretized Euclidean space where each coordinate can have n discrete values. This algorithm receives at most md counterexamples and uses time and membership queries polynomial in m and log n for any constant d. Furthermore, all equivalence queries can be formulated as the union of O(md log m) axis-parallel boxes. Next, we show how to extend our algorithm to efficiently learn, from only equivalence queries, any discretized geometric concept generated from any number of halfspaces with any number of known (to the learner) slopes in a constant dimensional space. In particular, our algorithm exactly learns (from equivalence queries only) unions of discretized axis-parallel boxes in constant dimensional space in polynomial time. Furthermore, this equivalence query only algorithm can be modified to handle a polynomial number of lies in the counterexamples provided by the environment. Finally, we introduce a new complexity measure that better captures the complexity of the union of $m$ boxes than simply the number of boxes and the dimension. Our new measure, $\sigma$, is the number of segments in the target, where a segment is a maximum portion of one of the sides of the target that lies entirely inside or entirely outside each of the other halfspaces defining the target. We present a modification of our first algorithm that uses time and queries polynomial in $\sigma$ and log n. In fact, the time and queries (both membership and equivalence) used by this single algorithm are polynomial for either m or d constant.
Simulation modelling to understand the evolution and management of glyphosate resistance in weeds.

BACKGROUND A simulation model is used to explore the influence of biological, ecological, genetic and operational (management) factors on the probability and rate of glyphosate resistance in model weed species. RESULTS Glyphosate use for weed control prior to crop emergence is associated with low risks of resistance. These low risks can be further reduced by applying glyphosate in sequence with other broad-spectrum herbicides prior to crop seeding. Post-emergence glyphosate use, associated with glyphosate-resistant crops, very significantly increases risks of resistance evolution. Annual rotation with conventional crops reduces these risks, but the proportion of resistant populations can only be reduced to close to zero by mixing two of three post-emergence glyphosate applications with alternative herbicide modes of action. Weed species that are prolific seed producers with high seed bank turnover rates are most at risk of glyphosate resistance evolution. The model is especially sensitive to the initial frequency of R alleles, and other genetic and reproductive parameters, including weed breeding system, dominance of the resistance trait and relative fitness, influence rates of resistance. CONCLUSION Changing patterns of glyphosate use associated with glyphosate-resistant crops are increasing risks of evolved glyphosate resistance. Strategies to mitigate these risks can be explored with simulation models. Models can also be used to identify weed species that are most at risk of evolving glyphosate resistance.
Finite Element 3D Modeling of Mechanical Behavior of Mineralized Collagen Microfibrils

Purpose The aim of this work is to develop a 3D finite elements model to study the nanomechanical behavior of mineralized collagen microfibrils, which consists of three phases, (i) collagen phase formed by five tropocollagen (TC) molecules linked together with cross-links, (ii) a mineral phase (Hydroxyapatite), and (iii) impure mineral phase, and to investigate the important role of individual properties of every constituent. Methods The mechanical and geometric properties (TC molecule diameter) of both tropocollagen and mineral were taken into consideration as well as cross-links, which was represented by spring elements with adjusted properties based on experimental data. In this paper an equivalent homogenized model was developed to assess the whole microfibril mechanical properties (Young's modulus and Poisson's ratio) under varying mechanical properties of each phase. Results In this study, both equivalent Young's modulus and Poisson's ratio, which were expressed as functions of Young's modulus of each phase, were obtained under tensile load with symmetric and periodic boundary conditions.
Star formation history of early-type galaxies in low density environments. IV. What do we learn from nuclear line-strength indices?

In this paper we analyze the line-strength indices in the Lick-system measured by Longhetti et al. (1998a, b) for a sample of 51 early-type galaxies located in low density en- vironments (LDE) and showing signatures of fine structures and/or interactions. The sample contains 21 shell-galaxies and 30 members of interacting pairs. Firstly we perform a preliminary comparison between three different sources of calibrations of the line strength indices, namely Buzzoni et al. (1992, 1994), Worthey (1992), Worthey et al. (1994) and Idiart et al. (1995), derived from stars with different effective temperature, gravity, and metallicity. Look- ing at the three indices in common, i.e. Mg2, Fe5270, and H, the calibrations by Buzzoni et al. (1992, 1994), Worthey (1992) and Worthey et al. (1994) lead to mutually consistent results. The calibration of H by Idiart et al. (1995) can be compared with the previous ones only for a limited range of ages, in which good agreement is found. Mg2 and Mgb indices predicted by the Idiart's et al. (1995) fitting functions result to be system- atically lower than those obtained from using Worthey (1992) calibrations. Secondly, we discuss the properties of the galaxies in our sample by comparing them both with theoretical Single Stellar Populations (SSPs) and the normal galaxies of the Gonz´ (1993: G93) sample. The analysis is performed by means of several diagnostic planes. In the , Mg2, Fe5270 and Fe5335 space, normal, shell- and pair-galaxies have a different behavior. First of all, normal and pair-galaxies follow the universal vs. Mg2 relation, whereas shell-galaxies lie above it; secondly the Fe versus Mg2 relation of normal, shell- and pair-galaxies is flatter than the theoreti- cal expectation. This fact hints for enhancement of -elements with respect to solar partition in galaxies with strong Fe indices and/or high velocity dispersion, mass and luminosity in turn. In the vs. H plane normal galaxies seem to follow a nice relation suggesting that objects with shallow gravitational po-
Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets

Imitation learning has traditionally been applied to learn a single task from demonstrations thereof. The requirement of structured and isolated demonstrations limits the scalability of imitation learning approaches as they are difficult to apply to real-world scenarios, where robots have to be able to execute a multitude of tasks. In this paper, we propose a multi-modal imitation learning framework that is able to segment and imitate skills from unlabelled and unstructured demonstrations by learning skill segmentation and imitation learning jointly. The extensive simulation results indicate that our method can efficiently separate the demonstrations into individual skills and learn to imitate them using a single multi-modal policy. The video of our experiments is available at this http URL
Mechanics of Compliant Nanoporous Gold

Compliant nanoporous gold is investigated with regards to its elastic modulus and deformation mechanisms. Samples are fabricated by dealloying AgAu alloys at elevated temperature and reduced dealloying potential compared with conventional methods in the literature. This procedure minimizes cracking and shrinkage that is typical from other dealloying methods. Furthermore, samples are found to be more compliant while immersed in water. Samples were tested in cyclic compression using a piezoelectric compression rig. Testing showed that the wet samples become stiffer upon drying and the effect is reversible with short drying times. This is attributed to microstructural effects as the ligament network becomes more connected as a result of drying, effectively shifting the dominant deformation mode from three-point bending to cantilever bending. At longer dry times, the effect is irreversible due to contact weld formation. Preliminary results on sputter deposited AgAuPt alloys show altered dealloying kinetics and crack formation.
Tenascin‐C patterns and splice variants in actinic keratosis and cutaneous squamous cell carcinoma

Background Tenascin‐C (Tn‐C) is an extracellular matrix protein with multiple functions that is present at low levels in normal tissues, but which is highly present in various tumours. The mRNA expression and protein level of Tn‐C including its various isoforms have not been investigated comprehensively so far in cutaneous squamous cell carcinoma (SCC) and the precursor lesion actinic keratosis (AK).
Rank Prediction in Graphs with Locally Weighted Polynomial Regression and EM of Polynomial Mixture Models

In this paper we describe a learning framework enabling ranking predictions for graph nodes based solely on individual local historical data. The two learning algorithms capitalize on the multi feature vectors of nodes in graphs that evolve in time. In the first case we use weighted polynomial regression (LWPR) while in the second we consider the Expectation Maximization (EM) algorithm to fit a mixture of polynomial regression models. The first method uses separate weighted polynomial regression models for each web page, while the second algorithm capitalizes on group behavior, thus taking advantage of the possible interdependence between web pages. The prediction quality is quantified as the similarity between the predicted and the actual rankings and compared to alternative baseline predictor. We performed extensive experiments on a real world data set (the Wikipedia graph). The results are very encouraging.
Authorship Attribution Using Word Network Features

In this paper, we explore a set of novel features for authorship attribution of documents. These features are derived from a word network representation of natural language text. As has been noted in previous studies, natural language tends to show complex network structure at word level, with low degrees of separation and scale-free (power law) degree distribution. There has also been work on authorship attribution that incorporates ideas from complex networks. The goal of our paper is to explore properties of these complex networks that are suitable as features for machine-learning-based authorship attribution of documents. We performed experiments on three different datasets, and obtained promising results.