Miracle-dz/UniFAR-FTUs huggingface dataset:
Longitudinal Phenotypes of Respiratory Health in a High‐Risk Urban Birth Cohort

Rationale: Characterization of patterns of wheezing and allergic sensitization in early life may allow for identification of specific environmental exposures impacting asthma development. Objectives: To define respiratory phenotypes in inner‐city children and their associations with early‐life environmental exposures. Methods: Data were collected prospectively from 442 children in the URECA (Urban Environment and Childhood Asthma) birth cohort through age 7 years, reflecting symptoms (wheezing), aeroallergen sensitization, pulmonary function, and body mass index. Latent class mixed models identified trajectories of wheezing, allergic sensitization, and pulmonary function. Cluster analysis defined nonoverlapping groups (termed phenotypes). Potential associations between phenotypes and early‐life environmental exposures were examined. Measurements and Main Results: Five phenotypes were identified and mainly differentiated by patterns of wheezing and allergic sensitization (low wheeze/low atopy; low wheeze/high atopy; transient wheeze/low atopy; high wheeze/low atopy; high wheeze/high atopy). Asthma was most often present in the high‐wheeze phenotypes, with greatest respiratory morbidity among children with frequent wheezing and allergic sensitization. These phenotypes differentially related to early‐life exposures, including maternal stress and depression, antenatal environmental tobacco smoke, house dust microbiome, and allergen content (all P < 0.05). Prenatal smoke exposure, maternal stress, and depression were highest in the high‐wheeze/low‐atopy phenotype. The high‐wheeze/high‐atopy phenotype was associated with low household microbial richness and diversity. Early‐life aeroallergen exposure was low in high‐wheeze phenotypes. Conclusions: Patterns of wheezing, allergic sensitization, and lung function identified five respiratory phenotypes among inner‐city children. Early‐life environmental exposure to stress, depression, tobacco smoke, and indoor allergens and microbes differentially associate with specific phenotypes.
Automatic Assessment of CoI-Cognitive Presence within Asynchronous Online Learning

This paper aims to give instructors the opportunity to analyze learners' cognitive behavior. Thus we propose an automatic system to assess learners' CoI-Cognitive presence regarding their social participation within asynchronous online discussion. Using Natural Language Preprocessing and Machine learning techniques, we first make some pre-processing to the textual data in order to make it clean and understandable, then we represent each discussion transcript with a vector using Doc2Vec-based features method; a document embedding method for document representation; according to some context and LIWC features. Finally, the Naïve Bayes algorithm is applied to classify messages according to cognitive presence categories.
Conformal Peeling of Device-on-Substrate System in Flexible Electronic Assembly

Continuous peeling of thin chips and flexible devices from a donor to an acceptor is critical for high-efficiency roll-to-roll (R2R) manufacturing of flexible electronics. Here, we propose an R2R conformal peeling technique for the flexible device-on-substrate electronic assembly. First, a mechanical model is established for flexible multilayer structures conformed on curved surface, such as peeling blade, and the corresponding analytical solution of the interfacial shear stress and peeling stress of the adhesive layer is given. Then, the influence of material property and geometrical size of the device (Young’s modulus of different layers and thickness of various layers), the geometric shape of peeling blade (peeling radius and conformal angle), and R2R process parameters (tension and speed of substrate) are analyzed by the theoretical model and experimental test. The peelability law of delaminating devices from the substrate is established for the conformal peeling process. Finally, the design method for a peeling blade is proposed, and the core is to determine the diameter of the peeling blade. It is proofed by the peeling experiment of multilayer electronic devices in the packaging of radio-frequency identification tags.
Genetic and Biophysical Models Help Define Marine Conservation Focus Areas

CITATION: Mertens, L. E. A. Treml, E. A. Von Der Heyden, S. 2018. Genetic and biophysical models help define marine conservation focus areas. Frontiers in Marine Science, 5:268, doi:10.3389/fmars.2018. 00268.
The Prevalence and Risks of Inappropriate Combination of Aspirin and Warfarin in Clinical Practice: Results From WARFARIN-TR Study

Background: The use of warfarin and aspirin in combination is restricted to limited patients under relevant guidelines. Aims: To evaluate the prevalence of the inappropriate combination of aspirin and warfarin therapy in daily practice and its risks. Study Design: Cross-sectional study. Methods: The awareness, efficacy, safety, and time in the therapeutic range of warfarin in the Turkish population study is a multi-center observational study that includes 4987 patients using warfarin for any reason between January 1, 2014, and December 31, 2014. To determine the prevalence of inappropriate combination use in daily practice, all patients who had a history of atherosclerotic disease (ischemic heart disease, peripheral artery disease) or cerebrovascular disease (n=1498) were excluded. The data of 3489 patients were analyzed. We defined inappropriate combination as all patients who received aspirin and warfarin regardless of the indication for warfarin use, under the direction of the European Society of Cardiology guideline recommendation. Results: The mean age of patients was 59.2±13.8 years (41.8% male). The prevalence of the inappropriate use of warfarin and aspirin combination was 20.0%. The prevalence of combination therapy in patients with a primary indication for mechanical heart valve, non-valvular atrial fibrillation, and other reasons was 20.5%, 18.7%, and 21.0%, respectively. Multivariate logistic regression analysis revealed that age (odds ratio, 1.009; 95% confidence interval, 1.002-1.015; p=0.010), heart failure (odds ratio, 1.765; 95% confidence interval, 1.448-2.151; p<0.001), smoking (odds ratio, 1.762; 95% confidence interval, 1.441-1.153; p<0.010), chronic kidney disease (odds ratio, 2.057; 95% confidence interval, 1.494-2.833; p<0.001), and deep vein thrombosis (odds ratio, 0.463; 95% confidence interval, 0.229-0.718; p=0.001) were independent predictors of combination therapy (r2=0.66). The mean time in therapeutic range of patients receiving combination therapy was significantly lower than in those on warfarin monotherapy (51.6±27.05 vs. 54.7±23.93; p=0.006). Overall, 19.4% (n=677) of patients had a bleeding event (major bleeding 13.0%, n=88) within a year. Percentages of patients with combination therapy were significantly higher in patients with major bleeding than in patients without major bleeding (29.5% vs. 19.7%; p=0.023). Conclusion: Our study demonstrated that 20.0% of patients taking warfarin use concomitant aspirin inappropriately in daily practice. Patients receiving aspirin with warfarin were demonstrated to have more comorbidities, lower time in therapeutic range levels, and higher bleeding rates.
Identification of Pedestrians From Confused Planar Objects Using Light Field Imaging

Recognizing a fake pedestrian on a planar surface (2-D fake pedestrian) is an essential and challenging task in the field of machine vision because of its wide range of applications. In this paper, a 2-D fake pedestrian recognition method is proposed based on light-field (LF) imaging and support vector machine (SVM). This method can recognize a 2-D fake pedestrian with only one sensor in a single exposure. To evaluate the method, we construct a new pedestrian dataset comprising more than 1000 samples using LF imaging. The experimental results show that the highest accuracy of this method is greater than 96%. Moreover, due to the efficient SVM classifier and obvious shape difference between a 2-D fake pedestrian and the real one in LF depth images, an accessible accuracy (85%) will be obtained even if the number of training samples is not large (120 training samples). This preliminary work demonstrates that the proposed approach is quite valid for the recognition of a 2-D fake pedestrian and has potential application in the machine vision field.
Touch-screen-guided task reveals a prosocial choice tendency by chimpanzees (Pan troglodytes)

Humans help others even without direct benefit for themselves. However, the nature of altruistic (i.e., only the other benefits) and prosocial (i.e., self and other both benefit) behaviors in our closest living relative, the chimpanzee, remains controversial. To address this further, we developed a touch-screen-guided task that allowed us to increase the number of trials for a thorough test of chimpanzees’ prosocial and altruistic tendencies. Mother-offspring dyads were tested in the same compartment; one was the actor while the other was the recipient. In Experiment 1, the actor chose among three options: prosocial, selfish (only the actor benefited) and altruistic. To better understand the nature of the chimpanzees’ choices and to improve experimental control, we conducted two additional experiments. Experiment 2 consisted of two-option choices interspersed with three-option choices, and in Experiment 3 the two-option choice were blocked across all trials. The results of Experiment 1 clearly showed that chimpanzees acted prosocially in the touch-screen-guided task, choosing the prosocial option on an average of 79% of choices. Five out of the six chimpanzees showed the preference to act prosocially against chance level. The preference for the prosocial option persisted when conditions were changed in Experiments 2 and 3. When only selfish and altruistic options were available in Experiments 2 and 3, chimpanzees preferred the selfish option. These results suggest that (1) most individuals understood the nature of the task and modified their behavior according to the available options, (2) five out of the six chimpanzees chose to act prosocially when they had the option to, and (3) offspring counterbalanced between altruistic and selfish, when given those two options perhaps to avoid suffering repercussions from the mother.
Racing to Remember: A Theory of Decision Control in Event-Based Prospective Memory

Event-based prospective memory (PM) requires remembering to perform intended deferred actions when particular stimuli or events are encountered in the future. We propose a detailed process theory within Braver’s (2012) proactive and reactive framework of the way control is maintained over the competing demands of prospective memory decisions and decisions associated with ongoing task activities. The theory is instantiated in a quantitative “Prospective Memory Decision Control” (PMDC) architecture, which uses linear ballistic evidence accumulation (Brown & Heathcote, 2008) to model both PM and ongoing decision processes. Prospective control is exerted via decision thresholds, as in Heathcote, Loft, and Remington’s (2015) “Delay Theory” of the impact of PM demands on ongoing-task decisions. However, PMDC goes beyond Delay Theory by simultaneously accounting for both PM task decisions and ongoing task decisions. We use Bayesian estimation to apply PMDC to experiments manipulating PM target focality (i.e., the extent to which the ongoing task directs attention to the features of PM targets processed at encoding) and the relative importance of the PM task. As well as confirming Delay Theory’s proactive control of ongoing task thresholds, the comprehensive account provided by PMDC allowed us to detect both proactive control of the PM accumulator threshold and reactive control of the relative rates of the PM and ongoing-task evidence accumulation processes. We discuss potential extensions of PMDC to account for other factors that may be prevalent in real-world PM, such as failures of memory retrieval.
A Spark-Based High Performance Computational Approach for Simulating Typhoon Wind Fields

The impacts of typhoons on coastal areas around the globe necessitate the risk assessments of typhoon events to analyze their paths, intensity, and impacts on the environment for disaster prevention and reduction as well as for the scientific assessments of typhoon impacts. To this end, the typhoon wind field needs to be obtained by inversion to attain its temporal and spatial scopes of influence and disaster-inducing intensities using simulation algorithms that are based on the existing typhoon path data. The wind field calculation is a typical kind of compute-intensive processing. It is time-consuming (especially when the temporal resolution and the spatial resolution are high) to an extent, which makes it difficult for a traditional stand-alone computation to meet the application needs for typhoon risk assessments. Therefore, studies need to be conducted to accelerate the wind field calculations. Currently, the most economical and relatively feasible method is to rapidly generate a large quantity of typhoon risk data using multi-thread, graphics processing unit computing or clustering technologies (e.g., cloud computing). Hence, we have attempted to use the latest cloud computing framework, Spark, for the rapid simulation of the typhoon wind field. This paper proposed a storage model for typhoon paths and wind fields under the Spark environment, as well as a wind field parallel acceleration method based on Spark. Using this approach, we have calculated a total of 1038 historical wind fields that impacted the northwestern Pacific Ocean from 1949 to 2014. The results indicate that the Spark-based wind field computation method proposed in this paper has a greater advantage in terms of performance, which facilitates the typhoon risk assessment feasibility.
Anticancer effect of SZC015 on pancreatic cancer via mitochondria‐dependent apoptosis and the constitutive suppression of activated nuclear factor κB and STAT3 in vitro and in vivo

Pancreatic cancer is the fourth leading cause of cancer‐related death worldwide. Advances in therapeutic strategies such as chemotherapy have improved the clinical outcomes for pancreatic cancer patients. However, developing new therapeutic compounds against pancreatic cancer is still urgent due to the poor prognosis. Here, we show that SZC015, an oleanolic acid derivative, exhibits potent inhibitory effect on both pancreatic cancer cells in vitro and the corresponding xenograft tumors in vivo. Mechanistically, the activation of intrinsic apoptosis and G1 phase arrest resulting from mitochondria damage caused by SZC015 contribute significantly to the anticancer effects of SZC015. SZC015 also has remarkably inhibitory effects on the transcription factors that are extensively activated in pancreatic cancer tissues. As a constitutively activated transcription factor in pancreatic cancer, the nuclear factor κB is highly suppressed after SZC015 treatment in vitro or administration in vivo. Based on the bioinformatics analysis of microarray data, we validate that JAK2/STAT3 signaling is indeed activated in the human pancreatic cancer tissues and SZC015 also shows inhibitory effect on this signaling both in vitro and in vivo. These data suggest the potent effects of SZC015 on pancreatic cancer and also provided novel insights into the mechanisms of SZC015 as a new potent candidate for treating pancreatic cancer.
Phase Current Reconstruction for the Grid-Side Converter With Four-Switch Three-Phase Topology in a DFIG-WT

To increase the reliability of a doubly fed induction generator-based wind turbine (DFIG-WT), this paper proposes a fault-tolerant four-switch three-phase (FSTP) grid-side converter (GSC) with a phase current reconstruction strategy. The proposed strategy is effective when the semiconductor open-circuit fault and phase current sensor failure occur simultaneously, which is a kind of hybrid fault. Only one current sensor is applied for measuring the currents flowing between the ac and dc sides of the GSC, and the phase current information can be derived by combining this information with the switching states of FSTP GSC. In the proposed current reconstruction strategy, only two scenarios of duty ratio allocation are needed to be considered. In addition, the space vector pulsewidth modulation (SVPWM) technique is simplified by obtaining the unified expressions for the duty ratios for the remaining four switches in GSC, and the sector identification is removed. Besides, the voltage balancing on the dc bus is achieved. Furthermore, the limitation of the proposed current reconstruction strategy is presented, and the dead zones for SVPWM techniques in both six-switch three-phase and FSTP converters are analyzed. Simulations are carried out in MATLAB/Simulink to verify the proposed hybrid fault-tolerant strategy for the GSC in a 1.5-MW DFIG-WT.
Distributed Louvain Algorithm for Graph Community Detection

In most real-world networks, the nodes/vertices tend to be organized into tightly-knit modules known as communities or clusters, such that nodes within a community are more likely to be "related" to one another than they are to the rest of the network. The goodness of partitioning into communities is typically measured using a well known measure called modularity. However, modularity optimization is an NP-complete problem. In 2008, Blondel, et al. introduced a multi-phase, iterative heuristic for modularity optimization, called the Louvain method. Owing to its speed and ability to yield high quality communities, the Louvain method continues to be one of the most widely used tools for serial community detection. In this paper, we present the design of a distributed memory implementation of the Louvain algorithm for parallel community detection. Our approach begins with an arbitrarily partitioned distributed graph input, and employs several heuristics to speedup the computation of the different steps of the Louvain algorithm. We evaluate our implementation and its different variants using real-world networks from various application domains (including internet, biology, social networks). Our MPI+OpenMP implementation yields about 7x speedup (on 4K processes) for soc-friendster network (1.8B edges) over a state-of-the-art shared memory multicore implementation (on 64 threads), without compromising output quality. Furthermore, our distributed implementation was able to process a larger graph (uk-2007; 3.3B edges) in 32 seconds on 1K cores (64 nodes) of NERSC Cori, when the state-of-the-art shared memory implementation failed to run due to insufficient memory on a single Cori node containing 128 GB of memory.
A Revised Taxonomy of Diplonemids Including the Eupelagonemidae n. fam. and a Type Species, Eupelagonema oceanica n. gen. & sp.

Recent surveys of marine microbial diversity have identified a previously unrecognized lineage of diplonemid protists as being among the most diverse heterotrophic eukaryotes in global oceans. Despite their monophyly (and assumed importance), they lack a formal taxonomic description, and are informally known as deep‐sea pelagic diplonemids (DSPDs) or marine diplonemids. Recently, we documented morphology and molecular sequences from several DSPDs, one of which is particularly widespread and abundant in environmental sequence data. To simplify the communication of future work on this important group, here we formally propose to erect the family Eupelagonemidae to encompass this clade, as well as a formal genus and species description for the apparently most abundant phylotype, Eupelagonema oceanica, for which morphological information and single‐cell amplified genome data are currently available.
Three‐dimensional printing and virtual surgery for congenital heart procedural planning

Complex unrepaired congenital heart disease requires extensive planning to determine the optimal procedural approach. Conventional noninvasive diagnostic imaging initially provides only two‐dimensional (2D) representations of the complex, three‐dimensional cardiovascular anatomy. With the expansion of 3D visualization techniques in imaging, a paradigm shift has occurred in complex congenital heart disease surgical planning using digital and 3D printed heart models. There has been early success in demonstrating the benefit of these models in interdisciplinary communication and education. The future goal of this work is to demonstrate a clinical outcome benefit using digital and 3D printed models to plan both surgical and catheterization‐based interventional procedures. Ultimately, the hope is that advanced procedural planning with virtual surgery and 3D printing will enhance decision‐making in complex congenital heart disease cases resulting in improved perioperative performance by reducing operative times, complications, and reoperations.
CRAFTER: A Tree-Ensemble Clustering Algorithm for Static Datasets with Mixed Attributes and High Dimensionality

Clustering is an important aspect of data mining, while clustering high-dimensional mixed-attribute data in a scalable fashion still remains a challenging problem. In this paper, we propose a tree-ensemble clustering algorithm for static datasets, CRAFTER, to tackle this problem. CRAFTER is able to handle categorical and numeric attributes simultaneously, and scales well with the dimensionality and the size of datasets. CRAFTER leverages the advantages of a tree-ensemble to handle mixed attributes and high dimensionality. The concept of the class probability estimates is utilized to identify the representative data points for clustering. Through a series of experiments on both synthetic and real datasets, we have demonstrated that CRAFTER is superior than Random Forest Clustering (RFC), an existing tree-based clustering method, in terms of both the clustering quality and the computational cost.
Current understanding of thalamic structure and function in migraine

Objective To review and discuss the literature on the role of thalamic structure and function in migraine. Discussion The thalamus holds an important position in our understanding of allodynia, central sensitization and photophobia in migraine. Structural and functional findings suggest abnormal functional connectivity between the thalamus and various cortical regions pointing towards an altered pain processing in migraine. Pharmacological nociceptive modulation suggests that the thalamus is a potential drug target. Conclusion A critical role for the thalamus in migraine-related allodynia and photophobia is well established. Additionally, the thalamus is most likely involved in the dysfunctional pain modulation and processing in migraine, but further research is needed to clarify the exact clinical implications of these findings.
Smart Hardware for Smart Objects: Microwave Electronic Circuits to Make Objects Smart

Let? s conform electronics to objects! Up to now, the most common approach has been exactly the opposite: the size, weight, and shape of the electronic devices around us have been conformed to the electronics. However, the Internet of Things (IoT) vision will necessarily lead to a paradigm shift, where the electronics need to conform to the objects.