Miracle-dz/UniFAR-FTUs huggingface dataset:
Biological screening of natural products and drug innovation in China

Natural products have been applied to human healthcare for thousands of years. Drug discovery in ancient times was largely by chance and based on clinical practices. As understanding of therapeutic benefits deepens and demands for natural products increase, previously serendipitous discoveries evolve into active searches for new medicines. Many drugs presently prescribed by physicians are either directly isolated from plants or are artificially modified versions of natural products. Scientists are looking for lead compounds with specific structures and pharmacological effects often from natural sources. Experiences and successes of Chinese scientists in this specialized area have resulted in a number of widely used drugs. The tremendous progress made in life sciences has not only revealed many pathological processes of diseases, but also led to the establishment of various molecular and cellular bioassays in conjunction with high-throughput technologies. This is advantageous and permits certain natural compounds that are difficult to isolate and purify, and compounds that are difficult to synthesize, to be assayed. The transition from traditional to empirical and to molecular screening will certainly increase the probability of discovering new leads and drug candidates from natural products.
A model for hydraulic redistribution incorporating coupled soil-root moisture transport

One of the adaptive strategies of vegetation, par- ticularly in water limited ecosystems, is the development of deep roots and the use of hydraulic redistribution which enables them to make optimal use of resources available throughout the soil column. Hydraulic redistribution refers to roots acting as a preferential pathway for the movement of water from wet to dry soil layers driven by the mois- ture gradient - be it from the shallow to deep layers or vice versa. This occurs during the nighttime while during the day- time moisture movement is driven to fulfill the transpiration demand at the canopy. In this study, we develop a model to investigate the effect of hydraulic redistribution by deep roots on the terrestrial climatology. Sierra Nevada eco-region is chosen as the study site which has wet winters and dry summers. Hydraulic redistribution enables the movement of moisture from the upper soil layers to deeper zones during the wet months and this moisture is then available to meet the transpiration demand during the late dry season. It results in significant alteration of the profiles of soil moisture and water uptake as well as increase in the canopy transpiration, carbon assimilation, and the associated water-use-efficiency during the dry summer season. This also makes the pres- ence of roots in deeper soil layers much more important than their proportional abundance would otherwise dictate. Com- parison with observations of latent heat from a flux tower demonstrates improved predictability and provides valida- tion of the model results. Hydraulic redistribution serves as a mechanism for the interaction between the variability of deep layer soil-moisture and the land-surface climatology and could have significant implications for seasonal and sub- seasonal climate prediction.
Mortality and prognostic factors in Spanish patients with systemic sclerosis.

OBJECTIVE To determine survival and mortality in a cohort of Spanish patients with scleroderma (systemic sclerosis, SSc) and to analyse whether survival is influenced by demographic, clinical or immunological variables or the extent of skin involvement. METHODS The study included 79 patients diagnosed with SSc and taking part in a study to determine the extent of sclerosis, visceral involvement and immunological alterations. We studied the number of observed and expected deaths (the expected number being based on age- and sex-specific rates in the background population) and derived standardized mortality ratios with their 95% confidence intervals (CI). Cumulative survival after onset of the first symptom was estimated according to the Kaplan-Meier method. The Cox method was used to identify the prognostic factors. RESULTS The mortality rate was 0.0249 deaths per person-year. Survival at 15 yr was 0.62 (95% CI 0.410-0.778). The standardized mortality ratio was 429.4% (95% CI 222-750). On crude analysis, lung involvement [forced vital capacity (FVC) <70%, pulmonary hypertension], SSc renal crisis, an active capillaroscopic pattern, pericardial effusion and age over 60 yr at diagnosis were associated with shorter survival. On multivariate analysis, only age at diagnosis over 60 yr, FVC <70% and SSc renal crisis were independent prognostic factors. CONCLUSIONS The mortality rate associated with SSc showed a four-fold increase compared with the background population. Lung involvement and sclerodermal renal crisis were found to be independently associated with reduced survival.
An Interactive, Asymmetric and Extensional Method for Matching Conceptual Hierarchies

Our work deals with schema or ontology matching and is driven by the following statements: (1) Most of works only consider intensional description of schemas; (2) They mostly use symmetric similarity measures (and then they match similarity relations betwen concepts); (3) Few prototypes allow an interactive and visual match process. Therefore, we suggest an extensional and asymmetric matching method based on the discovery of significant implication rules between concepts described in textual documents. Our approach relies on the association rules paradigm and use a probabilistic model of deviation from independence, named implication intensity. Our matching method is divided into two consecutive stages: (1) the extraction in documents of relevant terms for each concept; (2) the discovery of significant implications between the concepts. And finally, we enclose this matching approach into an interactive visualization tool in order to facilitate the analyse, the validation and the editing of a mapping set for the knowledge engineer.
Hybrid connectionist-structural acoustical modeling in the ATROS system

In this paper, we introduce several hybrid connectionist-structural acoustic models for contextindependent phone-like units in the atros recognition system. The structural part of the acoustic models has been modeled with Markov chains, and a multilayer perceptron (or a committee of multilayer perceptrons) is used to estimate the emission probabilities of the Markov chains. We compare the recognition performance attained by these models with the performance obtained by classical continuous density hidden Markov models on a semantic restricted task.
The Influence of Two-way Conflicts of Medical Staff work-families on Burnout

The long working hours and high-intensity work pressure of medical staff cause conflicts between their family and work roles, a high level of burnout, and various psychological and physical problems, which are urgently needed to be resolved. Therefore, with the medical staff as the research object, the following conclusions were drawn through questionnaire distribution and statistical analysis of data: Medical staff have more obvious two-way conflicts and job burnout of work-families, and there are different degrees of differences in the work department, the number of children, and academic qualifications. In addition to family-work conflicts for emotional exhaustion, there is a significant positive correlation between two-way conflicts between work families and job burnout and their dimensions and the two-way conflict of work-families has a significant positive impact and a significant positive predictive effect on burnout. Based on the conclusions of this study, it is proposed from the three perspectives of hospital administrators, medical staff and society to reduce the two-way conflict and job burnout of work-families, especially for the conflict and burnout of medical staff in the context of two children. Keywords—work-family two-way conflict; work-family conflict; family-work conflict; burnout
Everyday mobility context classification using radio beacons

Inferring mobility states such as being stationary, walking, or driving is critical for transportation studies, urban planning, health monitoring and epidemiology. Our goal is to build a pervasive mobility classification system using smartphones while focusing on large deployment, which poses new design requirements: low processing complexity, high energy efficiency and high user-time coverage. Previous work focused on fine-grained location-based mobility inference using global positioning system (GPS) data. However, GPS-based mobility characterization raises many issues, such as spotty coverage and battery drainage, that makes it inadequate to meet our application goals. In this paper, we propose a new mobility classification method using radio beacons such as Global System for Mobile communications (GSM) and Wi-Fi traces. This method enables mobility-based applications to provide users with ubiquitous services while using energy-inexpensive existing infrastructures. We demonstrate how coarser-grained mobility states can be satisfactorily inferred from our method using a data set of five hours gathered from one user in five differently- characterized areas with 80.2% precision and 80.3% recall.
eHealth technologies to support nutrition and physical activity behaviors in diabetes self-management

Diabetes is a chronic, complex condition requiring sound knowledge and self-management skills to optimize glycemic control and health outcomes. Dietary intake and physical activity are key diabetes self-management (DSM) behaviors that require tailored education and support. Electronic health (eHealth) technologies have a demonstrated potential for assisting individuals with DSM behaviors. This review provides examples of technologies used to support nutrition and physical activity behaviors in the context of DSM. Technologies covered include those widely used for DSM, such as web-based programs and mobile phone and smartphone applications. In addition, examples of novel tools such as virtual and augmented reality, video games, computer vision for dietary carbohydrate monitoring, and wearable devices are provided. The challenges to, and facilitators for, the use of eHealth technologies in DSM are discussed. Strategies to support the implementation of eHealth technologies within practice and suggestions for future research to enhance nutrition and physical activity behaviors as a part of broader DSM are provided.
Mobility and bulk electron-phonon interaction in two-dimensional materials

We present calculations of the phonon-limited mobility in intrinsic n-type monolayer graphene, silicene and MoS2. The material properties, including the electron-phonon interaction, are calculated from first principles. Unlike graphene, the carriers in silicene show strong interaction with the out-of-plane modes. However, we find that graphene only has a slightly higher mobility compared to silicene. For MoS2 we obtain several orders of magnitude lower mobilities and in agreement with other recent theoretical results. The simulations illustrate the predictive capabilities of the newly implemented Boltzmann Transport Equation (BTE) solver in the Atomistix ToolKit (ATK) simulation tool.
Image indexing using weighted color histogram

Image indexing is the process of image retrieval from databases of images or videos based on their contents. Specifically histogram-based algorithms are considered to be effective for color image indexing. We suggest a new method of color space quantization in the CIELUV color space, named weighted LUV quantization. With this method, each bin in the LUV space has a different weighting factor, which is applied to the histogram intersection. The weighted LUV histogram intersection provides the advantage of perceptual uniformity of the CIELUV color space. An additional advantage is the consideration of perceptual sensitivity to more saturated colors by the use of a weighting factor.
Combining insulin with metformin or an insulin secretagogue in non-obese patients with type 2 diabetes: 12 month, randomised, double blind trial

Objectives To study the effect of insulin treatment in combination with metformin or an insulin secretagogue, repaglinide, on glycaemic regulation in non-obese patients with type 2 diabetes. Design Randomised, double blind, double dummy, parallel trial. Setting Secondary care in Denmark between 2003 and 2006. Participants Non-obese patients (BMI ≤27) with preserved beta cell function. Interventions After a four month run-in period with repaglinide plus metformin combination therapy, patients with a glycated haemoglobin (HbA1c) concentration of 6.5% or more were randomised to repaglinide 6 mg or metformin 2000 mg. All patients also received biphasic insulin aspart 70/30 (30% soluble insulin aspart and 70% intermediate acting insulin aspart) 6 units once a day before dinner for 12 months. Insulin dose was adjusted aiming for a fasting plasma glucose concentration of 4.0-6.0 mmol/l. The target of HbA1c concentration was less than 6.5%. Treatment was intensified to two or three insulin injections a day if glycaemic targets were not reached. Main outcome measure HbA1c concentration. Results Of the 459 patients who were eligible, 102 were randomised, and 97 completed the trial. Patients had had type 2 diabetes for approximately 10 years. At the end of treatment, HbA1c concentration was reduced by a similar amount in the two treatment groups (insulin plus metformin: mean (standard deviation) HbA1c 8.15% (1.32) v 6.72% (0.66); insulin plus repaglinide: 8.07% (1.49) v 6.90% (0.68); P=0.177). Total daily insulin dose and risk of hypoglycaemia were also similar in the two treatment groups. Weight gain was less with metformin plus biphasic insulin aspart 70/30 than with repaglinide plus biphasic insulin aspart 70/30 (difference in mean body weight between treatments −2.51 kg, 95% confidence interval −4.07 to −0.95). Conclusions In non-obese patients with type 2 diabetes and poor glycaemic regulation on oral hypoglycaemic agents, overall glycaemic regulation with insulin in combination with metformin was equivalent to that with insulin plus repaglinide. Weight gain seemed less with insulin plus metformin than with insulin plus repaglinide. Trial registration NCT00118963
Detection and recognition of traffic signs using Gabor filters

The paper proposes a three steps algorithm that automatically detects, classifies and recognizes traffic signs from images taken from a car running along European road. Traffic signs are detected by analyzing the color information contained in the images using HSV color space. Detected signs are then classified using correlation with standard sign shapes. The recognition step uses the minimum distance classification based on calculating the Euclidean distance between two feature vectors composed using a Gabor filter with different parameters.
A Minimal Encoding Approach to Feature Discovery

This paper discusses unsupervised learning of orthogonal concepts on relational data. Relational predicates, while formally equivalent to the features of the concept-learning literature, are not a good basis for defining concepts. Hence the current task demands a much larger search space than traditional concept learning algorithms, the sort of space explored by connectionist algorithms. However the intended application, using the discovered concepts in the Cyc knowledge base, requires that the concepts be interpretable by a human, an ability not yet realized with connectionist algorithms. Interpretability is aided by including a characterization of simplicity in the evaluation function. For Hinton's Family Relations data, we do find cleaner, more intuitive features. Yet when the solutions are not known in advance, the difficulty of interpreting even features meeting the simplicity criteria calls into question the usefulness of any reformulation algorithm that creates radically new primitives in a knowledge-based setting. At the very least, much more sophisticated explanation tools are needed.
Online recognition and segmentation for time-series motion with HMM and conceptual relation of actions

In this paper, we propose a robust online action recognition algorithm with a segmentation scheme that detects start and end points of action occurrences. In other words, the algorithm estimates reliably what kind of actions occurring at present time. The algorithm has following characteristics: 1) The algorithm incorporates human knowledge about relation between action names in order to simplify and toughen the algorithm, thus our algorithm can label robustly multiple action names at the same time. 2) The algorithm uses time-series action probability that represents the likelihood of each action occurrence at every frame time. 3) The classification technique with hidden Markov models (HMMs) enables the algorithm to detect robustly and immediately the segmental points. The experimental results using real motion capture data show that our algorithm not only decreases effectively the latency for detecting the segmental points but also prevents the system from making unnecessary segments due to the error of time-series action probability.
Evidence for a fence that impedes the diffusion of phosphatidylinositol 4,5-bisphosphate out of the forming phagosomes of macrophages

Fluorescence correlation spectroscopy and fluorescence recovery after photobleaching measurements on macrophages injected with fluorescent phosphatidylinositol 4,5-bisphosphate (PIP2) suggest that a barrier impedes the diffusion of plasma membrane PIP2 into and out of forming phagosomes.
A client-server oriented algorithm for virtually synchronous group membership in WANs

We describe a novel scalable group membership service designed explicitly for wide area networks. Our membership service is scalable in the number of groups supported, in the number of members in each group, and in the topology each group spans. Our service also supplies the hooks needed to provide clients with full virtual synchrony semantics. Our service attains, on average, a low message overhead by agreeing on membership within a single message round. Furthermore, our service avoids notifying the application of obsolete membership views when the network is unstable, yet it converges when the network has stabilized.
The Human Genomic Melting Map

In a living cell, the antiparallel double-stranded helix of DNA is a dynamically changing structure. The structure relates to interactions between and within the DNA strands, and the array of other macromolecules that constitutes functional chromatin. It is only through its changing conformations that DNA can organize and structure a large number of cellular functions. In particular, DNA must locally uncoil, or melt, and become single-stranded for DNA replication, repair, recombination, and transcription to occur. It has previously been shown that this melting occurs cooperatively, whereby several base pairs act in concert to generate melting bubbles, and in this way constitute a domain that behaves as a unit with respect to local DNA single-strandedness. We have applied a melting map calculation to the complete human genome, which provides information about the propensities of forming local bubbles determined from the whole sequence, and present a first report on its basic features, the extent of cooperativity, and correlations to various physical and biological features of the human genome. Globally, the melting map covaries very strongly with GC content. Most importantly, however, cooperativity of DNA denaturation causes this correlation to be weaker at resolutions fewer than 500 bps. This is also the resolution level at which most structural and biological processes occur, signifying the importance of the informational content inherent in the genomic melting map. The human DNA melting map may be further explored at http://meltmap.uio. no.
Selection of Key Performance Indicators for Supply Chain monitoring using MCDA

Key Performance Indicators (KPIs) are very important for monitoring Supply Chains. The problem of selecting KPIs is considered as a multi-objective problem. This paper presents a framework for the ranking and the selection of KPIs using a Multi-Criteria Decision Analysis (MCDA). The research was carried out using Analytical Hierarchy Process (AHP) to make pairwise comparison of KPIs in terms of several criteria. The suggested framework is used for selecting relevant KPIs for monitoring a public sector pharmaceutical products supply chain in a developing country.
American Journal of Epidemiology Original Contribution Pregnancy-associated Hypertensive Disorders and Adult Cognitive Function among Danish Conscripts

The authors examined the association of gestational hypertensive disorders (hypertension, preeclampsia, eclampsia) with adult cognitive function among men born in 1978–1983 in a well-defined geographic area of northern Denmark. Data from the Danish Medical Birth Registry, the Danish National Registry of Patients, and draft board records were linked. Cognitive function was measured at conscription by using the Boerge Prien group intelligence test. Test scores were converted to the conventional IQ scale (mean ¼ 100 (standard deviation, 15)). Low cognitive function was defined as IQ <85. Of the 17,457 men who underwent intelligence testing, 891 (5.1%) were born after a pregnancy involving hospitalization for a gestational hypertensive disorder. Compared with conscripts born after normotensive pregnancy, conscripts exposed to maternal gestational hypertension had an adjusted prevalence ratio for low cognitive function of 1.34 (95% confidence interval (CI): 1.01, 1.77). For those exposed to mild preeclampsia and severe preeclampsia/eclampsia, adjusted prevalence ratios were 1. In this study, prenatal exposure to gestational hypertensive disorders was associated with slightly reduced adult cognitive performance among male conscripts. Pregnancy-associated hypertensive disorders affect about 8% of gestations (1). Preeclampsia, affecting 3%–5% of pregnancies (2), accounts for the majority of these disorders. Compared with offspring of normotensive pregnancies, offspring of preeclamptic pregnancies have a 1.5-to 2-fold increased risk of perinatal or infant mortality (3). About one-third of babies born after a preeclamptic pregnancy are growth restricted (1), and preeclampsia is responsible for 15% of all preterm births (1). Little information exists about the neurodevelopmental outcome of offspring of hypertensive gestations. A recent large, population-based cohort study reported a 1.2-to 2.5-fold increase in the risk of epilepsy for children born at term after a preeclamptic gestation (4). A few studies have examined the association of gestational hypertensive disorders with offspring's cognitive function (5–8), but each of these studies had few subjects, focused on childhood outcomes of infants born preterm or small for gestational age, and produced conflicting results (5–7). In the only known study to date of adult cognitive function, Seidman et al. (8) reported the IQ of sons of preeclamptic mothers to be on average 1.2 points lower than that of sons of nonpreeclamptic mothers; the result was interpreted as absence of an association. That study did not examine cognitive outcome after gestational hypertension and did not address effects of preeclampsia severity. We aimed to examine an association of gestational