Miracle-dz/UniFAR-FTUs huggingface dataset:
Views of general practitioners toward physiotherapy management of osteoarthritis—a qualitative study

ABSTRACT Background: Osteoarthritis (OA) is a major cause of pain and physical disability, and general practitioners (GPs) are usually the first point of contact for patients. Physiotherapy has been shown as effective in the management of lower-limb OA. The aim was to explore the beliefs of GPs on the physiotherapy management of lower-limb OA in primary care. Methods: This is a qualitative study evaluating GP views about physiotherapy in Sheffield, South Yorkshire, UK. Participating GPs were recruited by systematic sampling, and invitation was given to GPs in 10 practices in the four localities in Sheffield. Semistructured interviews were completed and framework analysis was used to analyze the data. Results: Eight GPs were interviewed and six themes emerged from analysis of the data: perspective on OA, management strategy, views on patients, views on physiotherapy, working collaboratively, and suggestions for service improvements. GPs had a positive impression and knowledge of physiotherapy, but lacked understanding of the processes involved in treatment and limited awareness of clinical guidelines regarding the management of OA. Improvements in communication and collaborative working were critical issues suggested by the participants. Conclusion: This study found that GPs who were interviewed had a limited understanding on the role of physiotherapists and of clinical guidelines. Interprofessional communication was not as good as it should have been. A reconfiguration of the Sheffield musculoskeletal pathway may help achieve more effective collaborative working and a better outcome for patients.
Organization and Independence or Interdependence? Study of the Neurophysiological Dynamics of Syntactic and Semantic Processing

In this article we present a multivariate model for determining the different syntactic, semantic, and form (surface-structure) processes underlying the comprehension of simple phrases. This model is applied to EEG signals recorded during a reading task. The results show a hierarchical precedence of the neurolinguistic processes : form, then syntactic and lastly semantic processes. We also found (a) that verbs are at the heart of phrase syntax processing, (b) an interaction between syntactic movement within the phrase, and semantic processes derived from a person-centered reference frame. Eigenvectors of the multivariate model provide electrode-times profiles that separate the distinctive linguistic processes and/or highlight their interaction. The accordance of these findings with different linguistic theories are discussed.
Current Status of Spinal Cord Regenerative Therapies: A Review

Abstract Spinal cord injury (SCI) is any injury resulting from an insult to the spinal cord that disrupts its major functions, either completely or incompletely, and it can be caused by both traumatic and nontraumatic events. The number of SCI patients has been continuously increasing due to increasing number of motor vehicles and average age of patients is constantly decreasing. After SCI, nerve cells located at the injured site are severely damaged and eventually die, and these dead cells are cleared away by the immune system and in turn a cavity remains. Unfortunately, till date no effective treatment strategy exists ensuring functional recovery after SCI. There is an imperative need for the development of therapies to reduce the enormous physical and financial burdens of people afflicted with SCI. The surgical treatment has been known to aid in rehabilitation, but cannot substantially improve neurologic and functional outcome after SCI. The stem cell–based therapy has been proposed as a promising treatment strategy for SCI. Many of the current strategies for treatment of SCI involve replacing the cells lost to injury with cells derived from alternative sources, such as Schwann cells, oligodendrocyte precursor cells, and neural stem cells. This review discusses the present status of various cell-based therapies, which are being used for treating SCI.
Experience: Open Fiscal Datasets, Common Issues, and Recommendations

Public administrations are continuously publishing open data, increasing the amount of government open data over time. The published data includes budgets and spending as part of fiscal data; publishing these data is an important part of transparent and accountable governance. However, open fiscal data should also meet open data publication guidelines. When requirements in data guidelines are not met, effective data analysis over published datasets cannot be performed effectively. In this article, we present Open Fiscal Data Publication (OFDP), a framework to assess the quality of open fiscal datasets. We also present an extensive open fiscal data assessment and common data quality issues found; additionally, open fiscal data publishing guidelines are presented. We studied and surveyed main quality factors for open fiscal datasets. Moreover, the collected quality factors have been scored according to the results of a questionnaire to score quality factors within the OFDP assessment framework. We gather and comprehensively analyze a representative set of 77 fiscal datasets from several public administrations across different regions at different levels (e.g., supranational, national, municipality). We characterize quality issues commonly arising in these datasets. Our assessment shows that there are many quality factors in fiscal data publication that still need to be taken care of so that the data can be analyzed effectively. Our proposed guidelines allow for publishing open fiscal data where these quality issues are avoided.
An experimental approach towards the development of an in vitro cortical-thalamic co-culture model

In this paper, we propose an experimental approach to develop an in vitro dissociated cortical-thalamic co-culture model using a dual compartment neurofluidic device. The device has two compartments separated by 10 μm wide and 3 μm high microchannels. The microchannels provide a physical isolation of neurons allowing only neurites to grow between the compartments. Long-term viable co-culture was maintained in the compartmented device, neurite growth through the microchannels was verified using immunofluorescence staining, and electrophysiological recordings from the co-culture system was investigated. Preliminary analysis of spontaneous activities from the co-culture shows a distinctively different firing pattern associated with cultures of individual cell types and further analysis is proposed for a deeper understanding of the dynamics involved in the network connectivity in such a co-culture system.
Challenge Paper

Queues represent a setting where agents compete over a scarce resource: People wait for public transportation, jobs wait to be processed, patients await treatment at a hospital, and so on. While data logs record many aspects of our lives, information about queues is rarely recorded. Queue mining (Senderovich et al. 2015) is the process of revealing queue information from data logs for the purpose of discovering queueing models, conformance checking, and optimization. As such, queue mining enables bottleneck detection and delay prediction (Gal et al. 2017). A queueing network is the most general form of a queueing model, represented as a directed graph with nodes being the queueing stations (corresponding to types of resources), edges corresponding to routing between stations, and node attributes corresponding to station dynamics (e.g., arrival patterns, service time distributions, station capacity, and service policy—for example, first-come first-served). Customers arrive into a queueing station, wait (enqueued) before being served by the station, and then leave to the next station (or exit the system). Queueing networks are often assumed to have a single customer type and an immediate Markovian routing (after completion at a station a customer appears in the next station with some probability). Also, simple queueing networks
Incentive-Compatible Diffusion

Our work bridges the literature on incentive-compatible mechanism design and the literature on diffusion algorithms. We introduce the study of finding an incentive-compatible (strategy-proof) mechanism for selecting an influential vertex in a directed graph (e.g. Twitter»s network). The goal is to devise a mechanism with a bounded ratio between the maximal influence and the influence of the selected user, and in which no user can improve its probability of being selected by following or unfollowing other users. We introduce the Two Path mechanism which is based on the idea of selecting the vertex that is the first intersection of two independent random walks in the network. The Two Path mechanism is incentive compatible on directed acyclic graphs (DAGs), and has a finite approximation ratio on natural subfamilies of DAGs. Simulations indicate that this mechanism is suitable for practical uses.
Listing k-cliques in Sparse Real-World Graphs*

Motivated by recent studies in the data mining community which require to efficiently list all k-cliques, we revisit the iconic algorithm of Chiba and Nishizeki and develop the most efficient parallel algorithm for such a problem. Our theoretical analysis provides the best asymptotic upper bound on the running time of our algorithm for the case when the input graph is sparse. Our experimental evaluation on large real-world graphs shows that our parallel algorithm is faster than state-of-the-art algorithms, while boasting an excellent degree of parallelism. In particular, we are able to list all k-cliques (for any k) in graphs containing up to tens of millions of edges as well as all $10$-cliques in graphs containing billions of edges, within a few minutes and a few hours respectively. Finally, we show how our algorithm can be employed as an effective subroutine for finding the k-clique core decomposition and an approximate k-clique densest subgraphs in very large real-world graphs.
SCFG Decoding Without Binarization

Conventional wisdom dictates that synchronous context-free grammars (SCFGs) must be converted to Chomsky Normal Form (CNF) to ensure cubic time decoding. For arbitrary SCFGs, this is typically accomplished via the synchronous binarization technique of (Zhang et al., 2006). A drawback to this approach is that it inflates the constant factors associated with decoding, and thus the practical running time. (DeNero et al., 2009) tackle this problem by defining a superset of CNF called Lexical Normal Form (LNF), which also supports cubic time decoding under certain implicit assumptions. In this paper, we make these assumptions explicit, and in doing so, show that LNF can be further expanded to a broader class of grammars (called "scope-3") that also supports cubic-time decoding. By simply pruning non-scope-3 rules from a GHKM-extracted grammar, we obtain better translation performance than synchronous binarization.
Increased Serum Cystatin C in Early Parkinson's Disease with Objective Sleep Disturbances

Background: Sleep disturbance is one of the major non-motor symptoms which cause the disability of Parkinson's disease (PD) patients. Cystatin C (CysC) is a more sensitive biomarker than serum creatinine or estimated glomerular filtration rate. Previous studies have reported altered CysC levels in neurodegenerative disorders and sleep disorders. This study aimed to explore the correlations of serum CysC levels and objective sleep disturbances in early PD. Methods: We recruited 106 early PD patients and 146 age- and sex-matched controls. All participants underwent clinical investigation and video-polysomnography. Sleep parameters and serum levels of CysC were measured. Then, we investigated the relationships between CysC and clinical variables and objective sleep disturbances in early PD patients. Results: The mean serum level of CysC was significantly higher in patients with early PD (1.03 ± 0.19 mg/L) compared to controls (0.96 ± 0.15 mg/L, P = 0.009). There were significantly positive correlations between serum CysC levels and age (r = 0.334, P < 0.001), gender (r = 0.264, P = 0.013), and creatinine levels (r = 0.302, P = 0.018) in early PD patients. Increased serum CysC levels in early PD patients were significantly associated with higher apnea and hypopnea index (AHI) (r = 0.231, P = 0.017), especially hypopnea index (r = 0.333, P < 0.001). In early PD patients, elevated serum CysC levels were positively correlated with oxygen desaturation index (r = 0.223, P = 0.021), percentage of time spent at oxygen saturation (SaO2) <90% (r = 0.644, P < 0.001), arousal with respiratory event during sleep (r = 0.247, P = 0.013). On the contrary, the elevated serum CysC levels were negatively correlated with mean and minimal SaO2 (r = −0.323, −0.315, both P = 0.001) in PD patients. Conclusions: The level of serum CysC was higher in early PD patients. PD patients with elevated serum CysC levels had more respiratory events and more severe oxygen desaturation. Therefore, the serum CysC levels may predict the severities of sleep-disordered breathing problems in early PD patients.
Predicting Hurricane Trajectories using a Recurrent Neural Network

Hurricanes are cyclones circulating about a defined center whose closed wind speeds exceed 75 mph originating over tropical and subtropical waters. At landfall, hurricanes can result in severe disasters. The accuracy of predicting their trajectory paths is critical to reduce economic loss and save human lives. Given the complexity and nonlinearity of weather data, a recurrent neural network (RNN) could be beneficial in modeling hurricane behavior. We propose the application of a fully connected RNN to predict the trajectory of hurricanes. We employed the RNN over a fine grid to reduce typical truncation errors. We utilized their latitude, longitude, wind speed, and pressure publicly provided by the National Hurricane Center (NHC) to predict the trajectory of a hurricane at 6-hour intervals. Results show that this proposed technique is competitive to methods currently employed by the NHC and can predict up to approximately 120 hours of hurricane path.
Twin Classroom Dilemma: To Study Together or Separately?

There is little research to date on the academic implications of teaching twins in the same or different classroom. Consequently, it is not clear whether twin classroom separation is associated with positive or negative educational outcomes. As a result, parents and teachers have insufficient evidence to make a well-informed decision when twins start school. This study addresses two research questions: Are there average positive or negative effects of classroom separation? Are twins taught in different classes more different from each other than twins taught in the same class? Twin pairs from two large representative samples from Quebec (Canada) and the United Kingdom were evaluated across a large age range (7 to 16 years) on academic achievement, several cognitive abilities and motivational measures. Our results show almost no sizable positive or negative average effect of classroom separation on twins’ achievement, cognitive ability and motivation. Twin pairs at age 12 (Quebec, Canada) and at age 16 (United Kingdom) were slightly more similar on achievement if placed in the same classroom, with slightly greater similarity among monozygotic twins than dizygotic twins. However, the few effects found were weak, and it remains unclear whether they result from classroom separation or other factors. These results suggest that in terms of educational outcomes, policymakers should not impose rigid guidelines to separate twin pairs during their education. The choice of whether to educate twin pairs together or separately should be up to parents, twins and teachers, in response to twins’ individual needs.
The Paradox of Agency: Feeling Powerful Reduces Brokerage Opportunity Recognition yet Increases Willingness to Broker

Research suggests positions of brokerage in organizational networks provide many benefits, but studies tend to assume everyone is equally able to perceive and willing to act on brokerage opportunities. Here we challenge these assumptions in a direct investigation of whether people can perceive brokerage opportunities and are willing to broker. We propose that the psychological experience of power diminishes individuals’ ability to perceive opportunities to broker between people who are not directly connected in their networks, yet enhances their willingness to broker. In Study 1, we find that employees in a marketing and media agency who had a high sense of power were likely to see fewer brokerage opportunities in their advice networks. In Study 2, we provide causal evidence for this claim in an experiment where the psychological experience of power is manipulated. Those who felt powerful, relative to those who felt little power, tended to see fewer brokerage opportunities than actually existed, yet were more willing to broker, irrespective of whether there was a brokerage opportunity present. Collectively, these findings present a paradox of agency: Individuals who experience power are likely to underperceive the very brokerage opportunities for which their sense of agency is suited.
Transcriptome profiling of anthocyanin-related genes reveals effects of light intensity on anthocyanin biosynthesis in red leaf lettuce

Red leaf lettuce (Lactuca sativa L.) is popular due to its high anthocyanin content, but poor leaf coloring often occurs under low light intensity. In order to reveal the mechanisms of anthocyanins affected by light intensity, we compared the transcriptome of L. sativa L. var. capitata under light intensities of 40 and 100 μmol m−2 s−1. A total of 62,111 unigenes were de novo assembled with an N50 of 1,681 bp, and 48,435 unigenes were functionally annotated in public databases. A total of 3,899 differentially expressed genes (DEGs) were detected, of which 1,377 unigenes were up-regulated and 2,552 unigenes were down-regulated in the high light samples. By Kyoto Encyclopedia of Genes and Genomes enrichment analysis, the DEGs were significantly enriched in 14 pathways. Using gene annotation and phylogenetic analysis, we identified seven anthocyanin structural genes, including CHS, CHI, F3H, F3′H, DFR, ANS, and 3GT, and two anthocyanin transport genes, GST and MATE. In terms of anthocyanin regulatory genes, five MYBs and one bHLH gene were identified. An HY5 gene was discovered, which may respond to light-signaling and regulate anthocyanin structural genes. These genes showed a log2FC of 2.7–9.0 under high irradiance, and were validated using quantitative real-time-PCR. In conclusion, our results indicated transcriptome variance in red leaf lettuce under low and high light intensity, and observed a anthocyanin biosynthesis and regulation pattern. The data should further help to unravel the molecular mechanisms of anthocyanins influenced by light intensity.
Dimensions: re-discovering the ecosystem of scientific information

The overarching aim of this work is to provide a detailed description of the free version of Dimensions (new bibliographic database produced by Digital Science and launched in January 2018). To do this, the work is divided into two differentiated blocks. First, its characteristics, operation and features are described, focusing on its main strengths and weaknesses. Secondly, an analysis of its coverage is carried out (comparing it Scopus and Google Scholar) in order to determine whether the bibliometric indicators offered by Dimensions have an order of magnitude significant enough to be used. To this end, an analysis is carried out at three levels: journals (sample of 20 publications in 'Library & Information Science'), documents (276 articles published by the Journal of informetrics between 2013 and 2015) and authors (28 people awarded with the Derek de Solla Price prize). Preliminary results indicate that Dimensions has coverage of the recent literature superior to Scopus although inferior to Google Scholar. With regard to the number of citations received, Dimensions offers slightly lower figures than Scopus. Despite this, the number of citations in Dimensions exhibits a strong correlation with Scopus and somewhat less (although still significant) with Google Scholar. For this reason, it is concluded that Dimensions is an alternative for carrying out citation studies, being able to rival Scopus (greater coverage and free of charge) and with Google Scholar (greater functionalities for the treatment and data export).
Relation of maternal prepregnancy body mass index with offspring bone mass in childhood: is there evidence for an intrauterine effect?1234

Background: Evidence indicates that intrauterine skeletal development has implications for bone mass in later life and that maternal fat stores in pregnancy are important for fetal bone mineral accrual. Objective: We investigated whether childhood bone mass is influenced by maternal body mass index (BMI) via an intrauterine mechanism by comparing parental associations. Design: We conducted a multivariable regression analysis of 7121 children in the Avon Longitudinal Study of Parents and Children. Total body less head (TBLH) and spine bone measures were derived from dual-energy X-ray absorptiometry scans at a mean age of 9.9 y. Maternal and paternal BMI values were derived from self-reported weight and height during pregnancy. Results: Maternal prepregnancy BMI (SD score) was positively associated with offspring TBLH bone mineral content and bone mineral density (SD scores) [mean difference (95% CI): boys, 0.19 (0.16, 0.23) and 0.15 (0.12, 0.19), respectively; girls, 0.23 (0.19, 0.26) and 0.19 (0.16, 0.23), respectively] and spine bone mineral content and bone mineral density [boys, 0.20 (0.16, 0.24) and 0.18 (0.14, 0.22), respectively; girls, 0.22 (0.18, 0.26) and 0.21 (0.17, 0.25), respectively] and with TBLH and spine bone area–and spine area–adjusted bone mineral content. Associations of paternal BMI with these outcomes were similar, with no statistical evidence of a difference between maternal and paternal effects. Maternal associations were partly explained by offspring birth weight and gestational age and attenuated to the null after adjustment for offspring height and weight. Conclusion: The positive relation between maternal prepregnancy BMI and offspring bone mass is likely due to shared familial, genetic, and environmental characteristics rather than to an intrauterine mechanism.