Miracle-dz/UniFAR-FTUs huggingface dataset:
Suomalaisten tutkijoiden sosiaalisen median käyttö: sosiaalisen median merkitys työssä, tiedonhankinnassa ja tieteellisen tiedon jakamisessa

The use of social media in scholarly communication has grown in recent years, and consequently, scholars’ uses of social media has gained importance as a research topic.The aim of this article is to shed light on the role of social media in scholars’ work. The research presents findings from a survey (N=528) conducted in Finland in late 2016. There exists no prior research on the role and uses social media among Finnish scholars. This research specifically focuses on the perceived role of social media in information seeking and sharing. We also study the differences between disciplines, age groups, and positions. Results show that scholars do not perceive social media as being central for their or information seeking and sharing, and that social media services are not replacing traditional publishing forums. Scholars do appreciate the social media services intended and developed for academic use, and find them as having value for their work than general social media services. However, according to our results, social media services have a marginal role in scholars’ information seeking and scholars infrequently share their readings in social media platforms. Some disciplinary differences existed, but there was no connection between scholars’ age or position and the role of social media. Our study shows that the role of social media in academic work and scholarly communication is still rather small. Further research is needed to find out what are the reasons for scholars lack of interest towards social media.
Fentanyl‐Associated Syndrome of Inappropriate Antidiuretic Hormone Secretion

A 43–year‐old woman with advanced pulmonary blastoma was admitted for worsening back pain. Her drug regimen included hydromorphone and benazepril. On admission, hydromorphone patient‐controlled analgesia (PCA) was started for acute pain control and dexamethasone for possible cord compression. Baseline laboratory tests were unremarkable, but magnetic resonance imaging revealed T3 and L3 lesions. Irradiation was started with improvement in her pain. In anticipation of discharge, a fentanyl transdermal patch was given, and PCA was tapered. Two days later, the patient became progressively confused and fell. Neurologic examination and computed brain tomography were normal. Her serum sodium was 119 mEq/L (normal 136–144 mEq/L) and was confirmed on repeat testing, urine sodium was 194 mEq/L, and urine and serum osmolalities were 554 mOsm/kg (normal 300–900 mOsm/kg) and 245 mOsm/kg (normal 280–300 mOsm/kg), respectively, consistent with the syndrome of inappropriate antidiuretic hormone secretion (SIADH). Fluids were restricted, hydromorphone PCA was started again, and fentanyl was discontinued. After 36 hours, her serum sodium increased to 136 mEq/L. Because we were unsure whether the fentanyl or her cancer was causative and were unable to find any published reports of fentanyl‐associated SIADH, we readministered the fentanyl patch 2 days later. Within 48 hours, serum sodium dropped to 123 mEq/L. Fentanyl was discontinued, fluids were restricted, and 3% saline was started. Her serum sodium increased to 132 mEq/L in 48 hours. The patient was prescribed oral hydromorphone and benazepril and was discharged. The repeated temporal relationship between the administration of fentanyl and the onset of SIADH strongly implicates fentanyl as the causative agent in this case. To our knowledge, this is the first report of fentanyl‐associated SIADH.
Nuclear Overhauser Enhancement Imaging of Glioblastoma at 7 Tesla: Region Specific Correlation with Apparent Diffusion Coefficient and Histology

Objective To explore the correlation between Nuclear Overhauser Enhancement (NOE)-mediated signals and tumor cellularity in glioblastoma utilizing the apparent diffusion coefficient (ADC) and cell density from histologic specimens. NOE is one type of chemical exchange saturation transfer (CEST) that originates from mobile macromolecules such as proteins and might be associated with tumor cellularity via altered protein synthesis in proliferating cells. Patients and Methods For 15 patients with newly diagnosed glioblastoma, NOE-mediated CEST-contrast was acquired at 7 Tesla (asymmetric magnetization transfer ratio (MTRasym) at 3.3ppm, B1 = 0.7 μT). Contrast enhanced T1 (CE-T1), T2 and diffusion-weighted MRI (DWI) were acquired at 3 Tesla and coregistered. The T2 edema and the CE-T1 tumor were segmented. ADC and MTRasym values within both regions of interest were correlated voxelwise yielding the correlation coefficient rSpearman (rSp). In three patients who underwent stereotactic biopsy, cell density of 12 specimens per patient was correlated with corresponding MTRasym and ADC values of the biopsy site. Results Eight of 15 patients showed a weak or moderate positive correlation of MTRasym and ADC within the T2 edema (0.16≤rSp≤0.53, p<0.05). Seven correlations were statistically insignificant (p>0.05, n = 4) or yielded rSp≈0 (p<0.05, n = 3). No trend towards a correlation between MTRasym and ADC was found in CE-T1 tumor (-0.310.05, n = 6). The biopsy-analysis within CE-T1 tumor revealed a strong positive correlation between tumor cellularity and MTRasym values in two of the three patients (rSp patient3 = 0.69 and rSp patient15 = 0.87, p<0.05), while the correlation of ADC and cellularity was heterogeneous (rSp patient3 = 0.545 (p = 0.067), rSp patient4 = -0.021 (p = 0.948), rSp patient15 = -0.755 (p = 0.005)). Discussion NOE-imaging is a new contrast promising insight into pathophysiologic processes in glioblastoma regarding cell density and protein content, setting itself apart from DWI. Future studies might be based on the assumption that NOE-mediated CEST visualizes cellularity more accurately than ADC, especially in the CE-T1 tumor region.
A systematic review of cognitive functioning among young people who have experienced homelessness, foster care, or poverty

ABSTRACT Young people who have experienced homelessness, foster care, or poverty are among the most disadvantaged in society. This review examines whether young people who have these experiences differ from their non-disadvantaged peers with respect to their cognitive skills and abilities, and whether cognitive profiles differ between these three groups. Three electronic databases were systematically searched for articles published between 1 January 1995 and 1 February 2015 on cognitive functioning among young people aged 15 to 24 years who have experienced homelessness, foster care, or poverty. Articles were screened using pre-determined inclusion criteria, then the data were extracted, and its quality assessed. A total of 31 studies were included. Compared to non-disadvantaged youth or published norms, cognitive performance was generally found to be impaired in young people who had experienced homelessness, foster care, or poverty. A common area of difficulty across all groups is working memory. General cognitive functioning, attention, and executive function deficits are shared by the homeless and poverty groups. Creativity emerges as a potential strength for homeless young people. The cognitive functioning of young people with experiences of impermanent housing and poverty has been relatively neglected and more research is needed to further establish cognitive profiles and replicate the findings reviewed here. As some aspects of cognitive functioning may show improvement with training, these could represent a target for intervention.
Locally Non-linear Embeddings for Extreme Multi-label Learning

The objective in extreme multi-label learning is to train a classifier that can automatically tag a novel data point with the most relevant subset of labels from an extremely large label set. Embedding based approaches make training and prediction tractable by assuming that the training label matrix is low-rank and hence the effective number of labels can be reduced by projecting the high dimensional label vectors onto a low dimensional linear subspace. Still, leading embedding approaches have been unable to deliver high prediction accuracies or scale to large problems as the low rank assumption is violated in most real world applications. This paper develops the X-One classifier to address both limitations. The main technical contribution in X-One is a formulation for learning a small ensemble of local distance preserving embeddings which can accurately predict infrequently occurring (tail) labels. This allows X-One to break free of the traditional low-rank assumption and boost classification accuracy by learning embeddings which preserve pairwise distances between only the nearest label vectors. We conducted extensive experiments on several real-world as well as benchmark data sets and compared our method against state-of-the-art methods for extreme multi-label classification. Experiments reveal that X-One can make significantly more accurate predictions then the state-of-the-art methods including both embeddings (by as much as 35%) as well as trees (by as much as 6%). X-One can also scale efficiently to data sets with a million labels which are beyond the pale of leading embedding methods.
On Universality and Saturation in Ocean Internal Waves

Abstract : The apparent regularity in energy distribution among internal-wave space and time scales may be a saturation phenomenon. This paper develops a model of the saturated internal-wave field based on the hypothesis that the saturated quantity is omega squared/N squared, the locally normalized squared vorticity. This quantity, which is a generalized inverse Richardson number for spatially varying flow, is shown in the linearized approximation to be the density of a conserved 'excitation; I; the excitation is assumed to be uniformly partitioned among the normal modes in a saturated field. The resulting energy distribution differs from that of Garratt and Munk in that energy is assigned preferentially to the lowest modes. Among the properties derived for this distribution, and subject to verification by ocean measurements, is a universal law, independent of the stratification profile N(z), for coherence spectra of isopycnals in the spatial domain.
Measurement‐Based Synthesis of Facial Microgeometry

We present a technique for generating microstructure‐level facial geometry by augmenting a mesostructure‐level facial scan with detail synthesized from a set of exemplar skin patches scanned at much higher resolution. Additionally, we make point‐source reflectance measurements of the skin patches to characterize the specular reflectance lobes at this smaller scale and analyze facial reflectance variation at both the mesostructure and microstructure scales. We digitize the exemplar patches with a polarization‐based computational illumination technique which considers specular reflection and single scattering. The recorded microstructure patches can be used to synthesize full‐facial microstructure detail for either the same subject or to a different subject. We show that the technique allows for greater realism in facial renderings including more accurate reproduction of skin's specular reflection effects.
Primary Pulmonary Arterial Hypertension in children: A Hospital Based study

Primary Pulmonary Arterial Hypertension in children: A Hospital Based study Authors Shailee Dixit, Rashmi Alva* *Corresponding Author Dr Rashmi Alva Abstract Context: Pediatric Primary pulmonary Arterial hypertension is a rare disease in infants and an important cause of mortality and morbidity. Timely detection and appropriate treatment strategies are challenges in pediatric age group. Treatable causes need to be identified earlier in the course. Aim: To study the clinical presentation, treatment and outcome at discharge in children with Primary Pulmonary Arterial Hypertension. Setting and Design: It is a Time bound retrospective descriptive chart based observational study. Data was collected by reviewing case records in a predesigned, structured proforma of children above 1 month of age with primary pulmonary hypertension from Jan 2017 to July 2018. Results: There were total 12 cases of primary pulmonary arterial hypertension. Mean age of presentation of primary pulmonary hypertension varied between 11⁄2 month to 11⁄2 years. Common symptoms at presentation were hurried breathing, cough, poor feeding. Primary Pulmonary hypertension was not suspected in majority of children at initial assessment because symptoms were variable. 11(92%) presented with signs of cardiac failure. Chest X Rays showed Cardiomegaly in 50% cases and prominent pulmonary conus in 16%. On ECHO, 100% had RA and RV dilatation and severe PAH. 58% children showed Right Ventricular dysfunction. All the cases were treated with Digoxin, Sildenafil, Milrinone. 4(33%) of them were treated with Thiamine in addition. Mortality rate was high (58%), though all children who were administered thiamine have survived. Conclusion: Primary pulmonary hypertension is a rare disease of infancy with atypical presentation. Mortality rate is high. Administration of Thiamine has proved to be beneficial.
Rare event probability estimation for connectivity of large random graphs

Spatial statistical models are of considerable practical and theoretical interest. However, there has been little work on rare-event probability estimation for such models. In this paper we present a conditional Monte Carlo algorithm for the estimation of the probability that random graphs related to Bernoulli and continuum percolation are connected. Numerical results are presented showing that the conditional Monte Carlo estimators significantly outperform the crude simulation estimators.
Activity analysis : finding explanations for sets of events

Automatic activity recognition is the computational process of analysing visual input and reasoning about detections to understand the performed events. In all but the simplest scenarios, an activity involves multiple interleaved events, some related and others independent. The activity in a car park or at a playground would typically include many events. This research assumes the possible events and any constraints between the events can be defined for the given scene. Analysing the activity should thus recognise a complete and consistent set of events; this is referred to as a global explanation of the activity. By seeking a global explanation that satisfies the activity’s constraints, infeasible interpretations can be avoided, and ambiguous observations may be resolved. An activity’s events and any natural constraints are defined using a grammar formalism. Attribute Multiset Grammars (AMG) are chosen because they allow defining hierarchies, as well as attribute rules and constraints. When used for recognition, detectors are employed to gather a set of detections. Parsing the set of detections by the AMG provides a global explanation. To find the best parse tree given a set of detections, a Bayesian network models the probability distribution over the space of possible parse trees. Heuristic and exhaustive search techniques are proposed to find the maximum a posteriori global explanation. The framework is tested for two activities: the activity in a bicycle rack, and around a building entrance. The first case study involves people locking bicycles onto a bicycle rack and picking them up later. The best global explanation for all detections gathered during the day resolves local ambiguities from occlusion or clutter. Intensive testing on 5 full days proved global analysis achieves higher recognition rates. The second case study tracks people and any objects they are carrying as they enter and exit a building entrance. A complete sequence of the person entering and exiting multiple times is recovered by the global explanation.
Cellular Automata Associated with Σ-Algebras

SUMMARY In this paper we present a novel treatment of cellular automata (CA) from an algebraic point of view. CA on monoids associated with Σ -algebras are introduced. Then an extension of Hedlund’s theorem which connects CA associated with Σ -algebras and continuous functions between prodiscrete topological spaces on the set of conﬁgurations are discussed.
PERCEPTUAL CONSTRAINTS FOR MUSIC INFORMATION RETRIEVAL SYSTEMS

In developing systems for music information retrieval (MIR), perceptual constraints often provide useful guidelines for design and evaluation. We show here three different types of MIR systems and illustrate how perceptual constraints shape their development. Perceptual similarity of music is an important attribute for music browsing, searching and playlist-ing. We are conducting a large-scale experiment in which listeners rank the similarity of musical-excerpt pairs. From the data we will create a low-dimensional space of perceptual music similarity and then attempt to assign the dimensions to acoustic qualities. We have also developed a method for music "mood" classiﬁcation that is based on extensive perceptual research aimed at identifying the most objective mood types across listeners. Here, we use mood labels that were judged consistent across listeners and thus provide a more useful set of communication criteria to relate the mood of music. Finally, we have used perceptual guidelines in the development and assessment of music tempo extraction. Previous work has shown that the perceptual tempo of music can be ambiguous in that tempi of different metrical levels can often be equally perceived by different listeners. Our system for automatic music tempo extraction takes this tempo ambiguity into account and provides estimates of the relative perceptual salience of different tempi for individual pieces of music.
Long-term treatment of osteoporosis in postmenopausal women: a review from the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO) and the International Osteoporosis Foundation (IOF)

Abstract Introduction: Postmenopausal osteoporosis is a chronic disease requiring treatment that balances long-term fracture efficacy against risk. Methods: We reviewed the efficacy and safety of calcium and vitamin D, the selective estrogen receptor modulators (SERMs), the bisphosphonates, denosumab, and strontium ranelate in studies of 3 years or longer. Results: Six trials lasted for 5 years, and seven went beyond that. The evidence beyond 5 years is generally weak, mainly due to methodological issues (open-label design, small samples, or absence of placebo control). Although calcium and vitamin D appear to be beneficial, the data are insufficient to evaluate benefits and risk beyond 3 years. The fracture efficacy of SERMs beyond 5 years is not known, though increases in bone mineral density (BMD) appear to be maintained. The SERMs have good long-term safety, including protective effects against breast cancer. The bisphosphonates have established fracture efficacy to 3 years, and 4 or 5 years with alendronate and risedronate. The evidence beyond 5 years indicates sustained increases in BMD. The safety of the bisphosphonates does not appear to be modified with time, with the possible exceptions of atypical subtrochanteric fracture and other events of unknown frequency. Denosumab has been tested up to 5 years, with continued increased in BMD and no reported safety issues. There is evidence for fracture efficacy of strontium ranelate, and sustained increases in BMD over 10 years. Strontium ranelate has good long-term safety. Conclusion: Robust long-term studies are relatively rare for the osteoporosis treatments, and generally show maintenance of BMD and, for some agents, an additional reduction in fracture incidence.
General Practitioners’ Concerns About Online Patient Feedback: Findings From a Descriptive Exploratory Qualitative Study in England

Background The growth in the volume of online patient feedback, including online patient ratings and comments, suggests that patients are embracing the opportunity to review online their experience of receiving health care. Very little is known about health care professionals’ attitudes toward online patient feedback and whether health care professionals are comfortable with the public nature of the feedback. Objective The aim of the overall study was to explore and describe general practitioners’ attitudes toward online patient feedback. This paper reports on the findings of one of the aims of the study, which was to explore and understand the concerns that general practitioners (GPs) in England have about online patient feedback. This could then be used to improve online patient feedback platforms and help to increase usage of online patient feedback by GPs and, by extension, their patients. Methods A descriptive qualitative approach using face-to-face semistructured interviews was used in this study. A topic guide was developed following a literature review and discussions with key stakeholders. GPs (N=20) were recruited from Cambridgeshire, London, and Northwest England through probability and snowball sampling. Interviews were transcribed verbatim and analyzed in NVivo using the framework method, a form of thematic analysis. Results Most participants in this study had concerns about online patient feedback. They questioned the validity of online patient feedback because of data and user biases and lack of representativeness, the usability of online patient feedback due to the feedback being anonymous, the transparency of online patient feedback because of the risk of false allegations and breaching confidentiality, and the resulting impact of all those factors on them, their professional practice, and their relationship with their patients. Conclusions The majority of GPs interviewed had reservations and concerns about online patient feedback and questioned its validity and usefulness among other things. Based on the findings from the study, recommendations for online patient feedback website providers in England are given. These include suggestions to make some specific changes to the platform and the need to promote online patient feedback more among both GPs and health care users, which may help to reduce some of the concerns raised by GPs about online patient feedback in this study.
Predictive Monitoring for Improved Management of Glucose Levels

Background: Recent developments and expected near-future improvements in continuous glucose monitoring (CGM) devices provide opportunities to couple them with mathematical forecasting models to produce predictive monitoring systems for early, proactive glycemia management of diabetes mellitus patients before glucose levels drift to undesirable levels. This article assesses the feasibility of data-driven models to serve as the forecasting engine of predictive monitoring systems. Methods: We investigated the capabilities of data-driven autoregressive (AR) models to (1) capture the correlations in glucose time-series data, (2) make accurate predictions as a function of prediction horizon, and (3) be made portable from individual to individual without any need for model tuning. The investigation is performed by employing CGM data from nine type 1 diabetic subjects collected over a continuous 5-day period. Results: With CGM data serving as the gold standard, AR model-based predictions of glucose levels assessed over nine subjects with Clarke error grid analysis indicated that, for a 30-minute prediction horizon, individually tuned models yield 97.6 to 100.0% of data in the clinically acceptable zones A and B, whereas cross-subject, portable models yield 95.8 to 99.7% of data in zones A and B. Conclusions: This study shows that, for a 30-minute prediction horizon, data-driven AR models provide sufficiently-accurate and clinically-acceptable estimates of glucose levels for timely, proactive therapy and should be considered as the modeling engine for predictive monitoring of patients with type 1 diabetes mellitus. It also suggests that AR models can be made portable from individual to individual with minor performance penalties, while greatly reducing the burden associated with model tuning and data collection for model development.