Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of macromolecule resonances in 1H NMR spectra of human brain

Macromolecule resonances underlying metabolites in 1H NMR spectra were investigated in temporal lobe biopsy tissue from epilepsy patients and from localized 1H spectra of the brains of healthy volunteers. The 1H NMR spectrum of brain tissue was cornpared with that of cytosol and dialyzed cytosol after removal of low molecular weight molecules (4500 daltons) at 8.4 and 2.1 Tesla. The assignment of specific resonances to macromolecules in 2.1 Tesla, short‐ TE, localized human brain 1H NMR spectra in vivo was made on the basis of a J‐editing method using the spectral parameters (δ, J) and connectivities determined from 2D experiments in vitro. Two prominent corinectivities associated with macromolecules in vitro (0.93–2.05 δ and 1.6–3.00 δ) were also detected in vivo by the J‐editing method. Advantage was taken of the large difference in measured T1 relaxation times between macromolecule and metabolite resonances in the brain spectrum to acquire ‘metabolite‐nulled’ macromolecule spectra. These spectra appear identical to the spectra of macromolecules isolated in vitro.
Routine HIV Testing in Botswana: A Population-Based Study on Attitudes, Practices, and Human Rights Concerns

Background The Botswana government recently implemented a policy of routine or “opt-out” HIV testing in response to the high prevalence of HIV infection, estimated at 37% of adults. Methods and Findings We conducted a cross-sectional, population-based study of 1,268 adults from five districts in Botswana to assess knowledge of and attitudes toward routine testing, correlates of HIV testing, and barriers and facilitators to testing, 11 months after the introduction of this policy. Most participants (81%) reported being extremely or very much in favor of routine testing. The majority believed that this policy would decrease barriers to testing (89%), HIV-related stigma (60%), and violence toward women (55%), and would increase access to antiretroviral treatment (93%). At the same time, 43% of participants believed that routine testing would lead people to avoid going to the doctor for fear of testing, and 14% believed that this policy could increase gender-based violence related to testing. The prevalence of self-reported HIV testing was 48%. Adjusted correlates of testing included female gender (AOR = 1.5, 95% CI = 1.1–1.9), higher education (AOR = 2.0, 95% CI = 1.5–2.7), more frequent healthcare visits (AOR = 1.9, 95% CI = 1.3–2.7), perceived access to HIV testing (AOR = 1.6, 95% CI = 1.1–2.5), and inconsistent condom use (AOR = 1.6, 95% CI = 1.2–2.1). Individuals with stigmatizing attitudes toward people living with HIV and AIDS were less likely to have been tested for HIV/AIDS (AOR = 0.7, 95% CI = 0.5–0.9) or to have heard of routine testing (AOR = 0.59, 95% CI = 0.45–0.76). While experiences with voluntary and routine testing overall were positive, 68% felt that they could not refuse the HIV test. Key barriers to testing included fear of learning one's status (49%), lack of perceived HIV risk (43%), and fear of having to change sexual practices with a positive HIV test (33%). Conclusions Routine testing appears to be widely supported and may reduce barriers to testing in Botswana. As routine testing is adopted elsewhere, measures should be implemented to assure true informed consent and human rights safeguards, including protection from HIV-related discrimination and protection of women against partner violence related to testing.
Simulation of morphologically structured photo-thermal neural stimulation

Objective. Rational design of next-generation techniques for photo-thermal excitation requires the development of tools capable of modeling the effects of spatially- and temporally-dependent temperature distribution on cellular neuronal structures. Approach. We present a new computer simulation tool for predicting the effects of arbitrary spatiotemporally-structured photo-thermal stimulation on 3D, morphologically realistic neurons. The new simulation tool is based on interfacing two generic platforms, NEURON and MATLAB and is therefore suited for capturing different kinds of stimuli and neural models. Main results. Simulation results are validated using photo-absorber induced neuro-thermal stimulation (PAINTS) empirical results, and advanced features are explored. Significance. The new simulation tool could have an important role in understanding and investigating complex optical stimulation at the single-cell and network levels.
Contextual Communications Congestion Control for Cooperative Vehicular Networks

The wide scale deployment of cooperative vehicular ad-hoc networks will require the design of efficient congestion control policies that guarantee stable and reliable communications between vehicles and with infrastructure nodes. These policies should reduce the load on the communications channel, while satisfying the strict application's reliability requirements. To this aim, this letter proposes and evaluates a contextual cooperative congestion control policy that exploits the traffic context information of each vehicle to reduce the channel load, while satisfying the vehicular applications requirements.
OptorSim-A Grid Simulator for Studying Dynamic Data Replication Strategies

Computational Grids process large, computationally intensive problems on small data sets. In contrast, Data Grids process large computational problems that in turn require evaluating, mining and producing large amounts of data. Replication, creating geographically disparate identical copies of data, is regarded as one of the major optimisation techniques for reducing data access costs. In this paper, several replication algorithms are discussed. These algorithms were studied using the Grid simulator: OptorSim. OptorSim provides a modular framework within which optimisation strategies can be studied under different Grid configurations. The goal is to explore the stability and transient behaviour of selected optimisation techniques. We detail the design and implementation of OptorSim and analyse various replication algorithms based on different Grid workloads.
Modification of carbon nanotube transparent conducting films for electrodes in organic light-emitting diodes

Single-walled carbon nanotube (SWCNT) transparent conducting films (TCFs) were fabricated for the electrodes of organic light-emitting diodes (OLEDs); three types of film were studied. The as-prepared SWCNT TCFs displayed a relatively low sheet resistance of 82.6 Ω/sq at 80.7 T% with a relatively large surface roughness of 30 nm. The TCFs were top-coated with poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) to obtain PEDOT:PSS-coated TCFs. The PEDOT:PSS cover improved the conductivity and decreased the surface roughness to 12 nm at the cost of film transmittance. The SWCNT TCFs mixed with PEDOT:PSS (PM-TCFs) exhibited a high conductivity (70.6 Ω/sq at 81 T%) and a low surface roughness (3 nm) and were thus selected as the best TCFs for OLEDs. Blue flexible OLEDs with 4,4′-bis(2,2′-diphenylvinyl)-1,1′-biphenyl (Dpvbi) as the emitting layer were fabricated on TCFs with the same structures to evaluate the performances of the different types of SWCNT films for use in OLEDs. Of these three types of OLEDs, the PM-TCF devices exhibited the optimal performance with a maximum luminance of 2587 cd m−2 and a current efficiency of 5.44 cd A−1. This result was explored using field-emission scanning electron microscopy and atomic force microscopy to further study the mechanisms that are involved in applying SWCNT TCFs to OLEDs.
Unsupervised Segmentation of Words Using Prior Distributions of Morph Length and Frequency

We present a language-independent and unsupervised algorithm for the segmentation of words into morphs. The algorithm is based on a new generative probabilistic model, which makes use of relevant prior information on the length and frequency distributions of morphs in a language. Our algorithm is shown to outperform two competing algorithms, when evaluated on data from a language with agglutinative morphology (Finnish), and to perform well also on English data.
RAB-10-Dependent Membrane Transport Is Required for Dendrite Arborization

Formation of elaborately branched dendrites is necessary for the proper input and connectivity of many sensory neurons. Previous studies have revealed that dendritic growth relies heavily on ER-to-Golgi transport, Golgi outposts and endocytic recycling. How new membrane and associated cargo is delivered from the secretory and endosomal compartments to sites of active dendritic growth, however, remains unknown. Using a candidate-based genetic screen in C. elegans, we have identified the small GTPase RAB-10 as a key regulator of membrane trafficking during dendrite morphogenesis. Loss of rab-10 severely reduced proximal dendritic arborization in the multi-dendritic PVD neuron. RAB-10 acts cell-autonomously in the PVD neuron and localizes to the Golgi and early endosomes. Loss of function mutations of the exocyst complex components exoc-8 and sec-8, which regulate tethering, docking and fusion of transport vesicles at the plasma membrane, also caused proximal dendritic arborization defects and led to the accumulation of intracellular RAB-10 vesicles. In rab-10 and exoc-8 mutants, the trans-membrane proteins DMA-1 and HPO-30, which promote PVD dendrite stabilization and branching, no longer localized strongly to the proximal dendritic membranes and instead were sequestered within intracellular vesicles. Together these results suggest a crucial role for the Rab10 GTPase and the exocyst complex in controlling membrane transport from the secretory and/or endosomal compartments that is required for dendritic growth.
Learning sparse multiple cause models

Multiple cause models (MCM) are a way to describe patterns as a superposition of a selection of cause patterns. In contrast to clustering methods and dimensionality reduction, multiple cause models are capable of turning local features on and off and this makes them a more realistic model for many types of data. However, inference and learning in general multiple cause models takes an amount of time that is exponential in the number of causes. We present an approximate inference algorithm that examines only sparse cause patterns, i.e., those configurations of causes where only a small number of causes are active at a time. This leads to an approximate EM algorithm that maximizes a lower bound on the likelihood of a data set. We show that this sparse multiple cause model can model different types of human facial expression patterns. Performance comparison of the MCM classifier with the SNoW (sparse network of winnows) architecture and the nearest neighbor classifier reveals significant improvement in classification accuracy using the MCM classifier.
Variation in caesarean section rates in Cyprus, Italy and Iceland: an analysis of the role of the media.

INTRODUCTION Cyprus has Europe's highest rate of births by caesarean section (CS). In 2015 56% of all babies were born by CS. This compares with 36% in Italy, and 16% in Iceland, which is among the lowest rates in Europe. There is some evidence that CS rates are partly driven by maternal request and media representation. The aim of this review is to explore the depiction of childbirth by CS in the media, and more specifically in newspapers, television, web and informational leaflets in Cyprus, Italy and Iceland. EVIDENCE ACQUISITION A thematic review of the depiction of CS in the media of Cyprus, Italy and Iceland was carried out through an examination of newspapers, television, web, and informational material published or presented in the included countries in 2017. Materials were identified by searches in PubMed and Google Scholar, using pre-determined key words, inclusion and exclusion criteria, and inclusion was agreed by at least two of the authors. Key themes in each data source were triangulated with each other and between the three countries. EVIDENCE SYNTHESIS The review comprised 81 articles, 10 videos, six birth shows, two informational leaflets and one scientific paper. The central themes were: 1) CS as risky and unnecessary intervention, failure of maternity system; 2) CS as a necessary, life-saving intervention; 3) the ethical dimensions of CS; 4) the changing landscape of childbirth and medicalization; and 5) informed choices. In both Cyprus and Italy, the media focus was on a need to reduce high levels of CS. The focus in Iceland was on normal birth and midwife led care. The differing media messages in the three countries could partly explain the differing CS rates, suggesting that high CS rates are a social phenomenon, rather than a result of clinical need. The media may have a significant influence on the beliefs and choices of maternity service users, their families, and society in general, as well as health professionals and policy makers. CONCLUSIONS Those working in the media have an ethical responsibility to critically examine the impact of high national CS rates, and to report on solutions that could optimize both the safety and the wellbeing of mothers and babies.
TSFDC: A trading strategy based on forecasting directional change

Directional Change (DC) is a technique to summarize price movements in a financial market. According to the DC concept, data is sampled only when the magnitude of price change is significant according to the investor. In this paper, we develop a contrarian trading strategy named TSFDC. TSFDC is based on a forecasting model which aims to predict the change of the direction of market's trend under the DC context. We examine the profitability, risk and risk‐adjusted return of TSFDC in the FX market using eight currency pairs. The results suggest that TSFDC outperforms the buy and hold approach and another DC‐based trading strategy.
Cosserat Rods with Projective Dynamics

We present a novel method to simulate Cosserat rods with Projective Dynamics (PD). The proposed method is both numerically robust and accurate with respect to the underlying physics, making it suitable for a variety of applications in computer graphics and related disciplines. Cosserat theory assigns an orientation frame to each point and is thus able to realistically simulate stretching and shearing effects, in addition to bending and twisting. Within the PD framework, it is possible to obtain accurate simulations given the implicit integration over time and its decoupling of the local‐global solve. In the proposed method, we start from the continuous formulation of the Cosserat theory and derive the constraints for the PD solver. We extend the standard definition of PD and add body orientations as system variables. Thus, we include the preservation of angular momentum, so that twisting and bending can be accurately simulated. Our formulation allows the simulation of different bending behaviors with respect to a user‐defined Young's modulus, the radius of the rod's cross‐section, and material density. We show how different material specifications in our simulations converge within a few iterations to a reference solution, generated with a high‐precision finite element method. Furthermore, we demonstrate mesh independence of our formulation: Refining the simulation mesh still results in the same characteristic motion, which is in contrast to previous position based methods.
Adaptation to milking agropastoralism in Chilean goat herders and nutritional benefit of lactase persistence

The genetic trait of lactase persistence (LP) evolved as an adaptation to milking pastoralism in the Old World and is a well‐known example of positive natural selection in humans. However, the specific mechanisms conferring this selective advantage are unknown. To understand the relationship between milk drinking, LP, growth, reproduction, and survival, communities of the Coquimbo Region in Chile, with recent adoption of milking agropastoralism, were used as a model population.
Unacylated ghrelin stimulates steroidogenesis in lean rats and reverses reproductive dysfunction in high fat diet-fed rats

ABSTRACT This study investigated the effect of sub-chronic administration of unacylated ghrelin (UAG) on steroidogenesis, sperm parameter, and reproductive function in lean and high fat diet (HFD)-induced obese male rats. Rats were divided into 4 groups (n = 12 each) as 1) Control-fed standard diets (STD): (10 kcal%), 2) STD + UAG (200 ng/kg, i.p.), 3) HFD obese: fed HFD (45 kcal%), and 4) HFD + UAG. Diet regimen was continued for 16 weeks after which normal saline as a vehicle or UAG was administered to desired groups for the next 4 weeks. In vitro, testicular slices were incubated with increasing concentrations of UAG (10−8–10−6 M) in the presence or absence of GSH-R1a antagonist, [D-Lys-3]-GHRP-6 (10−6 M). UAG significantly increased the circulatory levels of FSH, LH and testosterone, increased testicular testosterone levels and sperm count and motility in lean and obese rats and reduced sperm morphological abnormalities and increased pregnancy rate and number of pups at birth in HFD-obese rats. Associated with the reduction in the final body and fat masses weights and independent of food intake, UAG post-therapy to both lean and HFD-fed rats significantly lowered fasting blood glucose and insulin levels, lowered HOMA-IR value, enhanced OGTT and ITT, lowered circulatory leptin levels, downregulated aromatase expression in adipose and testicular tissue and inhibited HFD-induced testicular oxidative stress and activation of cleaved caspase-3. Dysregulation of testicular levels of StAR, SF-1, CYP11A1 in the testis of both groups as well as in the in vitro preparation, in a dose-dependent manner, independent of GSH-R1a and not associated with activation of STAT3, a mediator of leptin signaling was apparent. In conclusion, administration of UAG can enhance reproductive function in lean rats and reverses HFD-induced reproductive dysfunction in obese rats. Abbreviations: AG: acylated ghrelin; BMI: body mass index; CHOL: cholesterol;FSH: follicular stimulating hormone; GHS: growth hormone secretagogues; GSH: reduced glutathione; HFD: high fat diet; HOMA-IR: homeostasis model assessment of insulin resistance: IR: insulin resistance; OGTT: oral glucose tolerance test; ITT: insulin tolerance test; LH: luteinizing hormone; MDA: malondialdehyde; STAT3: signal transducer and activator of transcription; SOD: superoxide dismutase; STD: standard diet; SF-1: steroidogenic factor-1; StAR: steroidogenic acute regulatory protein; CYP11A1: cholesterol side-chain cleavage enzyme (or P450scc); TGs: triglycerides; UAG: unacylated ghrelin.
Building digital capability

This session will introduce the outcomes from a recent open pilot of the Jisc digital discovery tool with over 100 universities, colleges and training providers in the UK. It will introduce why enhancing the digital capabilities of both staff and students is critical in today’s digital age; introduce the digital discovery tool and how it has been used in a variety of contexts across the UK; outline the pilot process; and discuss the findings from an evaluation of the tool from both staff and organisational perspectives.
Consumer Grade Weather Stations for Wooden Structure Fire Risk Assessment

During January 2014, Norway experienced unusually cold and dry weather conditions leading to very low indoor relative humidity (RH) in inhabited (heated) wooden homes. The resulting dry wood played an important role in the two most severe accidental fires in Norway recorded since 1923. The present work describes testing of low cost consumer grade weather stations for recording temperature and relative humidity as a proxy for dry wood structural fire risk assessment. Calibration of the weather stations relative humidity (RH) sensors was done in an atmosphere stabilized by water saturated LiCl, MgCl2 and NaCl solutions, i.e., in the range 11% RH to 75% RH. When calibrated, the weather station results were well within ±3% RH. During the winter 2015/2016 weather stations were placed in the living room in eight wooden buildings. A period of significantly increased fire risk was identified in January 2016. The results from the outdoor sensors compared favorably with the readings from a local meteorological station, and showed some interesting details, such as higher ambient relative humidity for a home close to a large and comparably warmer sea surface. It was also revealed that a forecast predicting low humidity content gave results close to the observed outdoor weather station data, at least for the first 48 h forecast.
On the Regret Minimization of Nonconvex Online Gradient Ascent for Online PCA

In this paper we focus on the problem of Online Principal Component Analysis in the regret minimization framework. For this problem, all existing regret minimization algorithms for the fully-adversarial setting are based on a positive semidefinite convex relaxation, and hence require quadratic memory and SVD computation (either thin of full) on each iteration, which amounts to at least quadratic runtime per iteration. This is in stark contrast to a corresponding stochastic i.i. d. variant of the problem, which was studied extensively lately, and admits very efficient gradient ascent algorithms that work directly on the natural non-convex formulation of the problem, and hence require only linear memory and linear runtime per iteration. This raises the question: can non-convex online gradient ascent algorithms be shown to minimize regret in online adversarial settings? In this paper we take a step forward towards answering this question. We introduce an \textit{adversarially-perturbed spiked-covariance model} in which, each data point is assumed to follow a fixed stochastic distribution with a non-zero spectral gap in the covariance matrix, but is then perturbed with some adversarial vector. This model is a natural extension of a well studied standard stochastic setting that allows for non-stationary (adversarial) patterns to arise in the data and hence, might serve as a significantly better approximation for real-world data-streams. We show that in an interesting regime of parameters, when the non-convex online gradient ascent algorithm is initialized with a "warm-start" vector, it provably minimizes the regret with high probability. We further discuss the possibility of computing such a "warm-start" vector, and also the use of regularization to obtain fast regret rates. Our theoretical findings are supported by empirical experiments on both synthetic and real-world data.
The Impact of Sharing Mechanism Design on Content Sharing in Online Social Networks

Research on online content diffusion is vast but has rarely examined contextual factors, including the influence of online sharing mechanisms, such as social plugins (e.g., Facebook’s “Like” button), on online social networks (OSNs). While these mechanisms generally enable the content flow between senders and recipients, they vary in protecting users’ social and institutional privacy on OSNs. Additionally, sharing mechanisms might differ with respect to their labeling (e.g., positive versus neutral), which might interact with the sharable content. We examined the effects of these three design aspects on users’ sharing behavior in a controlled experiment and two analyses of observational data. The results show that two types of sharing mechanisms negatively affect content sharing in the domain of news sharing: those that allow greater information flow control over the sharing process and thus protect users’ social privacy and those that employ two-click designs to preserve users’ institutional privacy. The.