Miracle-dz/UniFAR-FTUs huggingface dataset:
Marine and plant-based n-3 PUFA and atherosclerotic cardiovascular disease

n-3 PUFA may exert favourable effects on several processes that may inhibit the atherosclerotic process. However, the role of n-3 PUFA in lowering the risk of atherosclerotic CVD (ASCVD) has been fiercely debated. In the present paper, we summarise the main findings from previous follow-up studies of intake and studies using adipose tissue as an objective biomarker to investigate exposure to n-3 PUFA in relation to ASCVD risk and discuss some perspectives for further research. The majority of previous studies investigating intake of marine- and plant-based n-3 PUFA have focused on CHD while other ASCVD such as ischaemic stroke and peripheral artery disease have been less studied. However, recent data from Danish Diet, Cancer and Health cohort suggest that marine n-3 PUFA may be inversely associated with risk of myocardial infarction, ischaemic stroke and peripheral arterial disease caused by atherosclerosis. The effect of the plant-derived n-3 PUFA α-linolenic acid on ASCVD is less clear and several gaps in the literature remain to be explored.
The channels East of Olympus Mons, Mars

ABSTRACT Multiple layers of lava flows and channels characterize the region adjacent to the eastern slope of Olympus Mons, the largest volcano on Mars. We have mapped this volcanic region to survey and classify individual channel systems and determine their formative processes. As a final output of this mapping effort, we have produced a 1:1.9 million scale channel map that is first published in this paper in both GIS and static formats. GRAPHICAL ABSTRACT
Synchronization of Coupled Neural-Mass Models

This paper investigates synchronization of coupled neural-mass models. Compared with some existing papers which study the dynamical behaviors of single neural-mass model, some synchronization criteria of coupled neural-mass models are derived. Moreover, the adjacency coupling for neural- mass models is investigated, which is more generalized than the special coupling in some existing papers. Furthermore, those derived synchronization criteria can be used to study synchronization of neural-mass models with special coupling. Two simulation examples are used to reveal the effectiveness of derived synchronization criteria.
Prenatal vitamin D levels and child wheeze and asthma

Abstract Background: Maternal vitamin D status during pregnancy may influence lung development and risk of childhood wheeze and asthma. We investigated the relationship between prenatal vitamin D and child asthma in a racially diverse cohort with a high burden of vitamin D insufficiency and child asthma. Materials and methods: We included mother–child dyads in the prenatal Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE) cohort (2006–2011, Shelby County, Tennessee). Maternal plasma vitamin D [25(OH)D] was measured from second trimester (n = 1091) and delivery specimens (n = 907). At age 4–6 years, we obtained parent report of current child wheeze (symptoms within the past 12 months) and asthma (physician diagnosis and/or medication or symptoms within the past 12 months). We used multivariable logistic regression to assess associations of 25(OH)D and child wheeze/asthma, including an interaction term for maternal race. Results: Median second trimester 25(OH)D levels were 25.1 and 19.1 ng/ml in White (n = 366) and Black women (N = 725), respectively. We detected significant interactions by maternal race for second-trimester plasma 25(OH)D and child current wheeze (p = .014) and asthma (p = .011). Odds of current wheeze and asthma decreased with increasing 25(OH)D in dyads with White mothers and increased in dyads with Black mothers, e.g. adjusted odds ratio (95% confidence interval) for asthma: 0.63 (0.36–1.09) and 1.41 (1.01–1.97) per interquartile range (15–27 ng/ml 25[OH]D) increase, respectively. At delivery, protective associations in White dyads were attenuated. Conclusion: We detected effect modification by maternal race in associations between prenatal 25(OH)D and child wheeze/asthma. Further research in racially diverse populations is needed.
Global Annealing Strategy: Evolutionary Circuit Design Made Efficiently

Premature convergence or fail on convergence within a limited period of time are difficulties in the field of evolutionary circuit design and the problems are related to the selection pressure of algorithms and population diversity. In this paper, we present a global annealing strategy for evolutionary circuit design, which is a new attempt to combine genetic algorithm and simulated annealing algorithm. Finally, an inverting amplifier is taken as a test case and a series of contrast experiments are conducted under the same experimental execution environment. The results reveal that the strategy presented performs better on capturing the desirable circuit with efficient search ability and it processes better convergence performance, namely, higher success rate within a limited evolutionary generation.
Color Inverse Halftoning Method with the Correlation of Multi-Color Components Based on Extreme Learning Machine

Look-up table (LUT) based method is a popular and effective way for inverse halftoning. However, it still has very large development space to improve the reconstructed color image quality for color halftone images, because most of the existing color inverse halftoning methods are the simple extension of LUT methods to each color components separately. To this end, this paper presents a novel color inverse halftoning method by exploiting the correlation of multi-color components. Through considering all existent contone values with the same halftone pattern in three color component tables, we firstly propose a concept of common pattern. Then the extreme learning machine (ELM) is employed to estimate the contone values for nonexistent patterns according to common patterns in color LUT, which can not only improve the fitting precision of nonexistent values but also has fast transformation speed. Experimental results show that the proposed method achieves a better image quality when compared to previously published methods.
Predicting duration of traffic accidents based on cost-sensitive Bayesian network and weighted K-nearest neighbor

Abstract With the development of urbanization, road congestion has become increasingly serious, and an important cause is the traffic accidents. In this article, we aim to predict the duration of traffic accidents given a set of historical records and the feature of the new accident, which can be collected from the vehicle sensors, in order to help guide the congestion and restore the road. Existing work on predicting the duration of accidents seldom consider the imbalance of samples, the interaction of attributes, and the cost-sensitive problem sufficiently. Therefore, in this article, we propose a two-level model, which consists of a cost-sensitive Bayesian network and a weighted K-nearest neighbor model, to predict the duration of accidents. After data preprocessing and variance analysis on the traffic accident data of Xiamen City in 2015, the model uses some important discrete attributes for classification, and then utilizes the remaining attributes for K-nearest neighbor regression prediction. The experiment results show that our proposed approach to predicting the duration of accidents achieves higher accuracy compared with classical models.
High Pressure Gas Xenon TPCs for Double Beta Decay Searches

This article reviews the application of high pressure gas xenon (HPXe) time projection chambers to neutrinoless double beta decay experiments. First, the fundamentals of the technology and the historical development of the field are discussed. Then, the state of the art is presented, including the prospects for the next generation of experiments with masses in the ton scale.
Double-threshold Model of the Activity Spreading in a Social Network

In this article, we introduce the model describing the interaction and mutual influence of agents in a social network. The interactions in the model are represented by the spreading of two opposite types of activity. Agents have beliefs of different strength and two activation thresholds of different heights. Depending on beliefs agents choose the type of activity, which they consider as their own and activate only by their own type, whichever of two activation thresholds is exceeded. Agents may have different sensitivities to the two types of external influence. The main properties of agents and principles of activity spreading are defined. The classification of agents according to their parameters is represented. The results of computational experiments are demonstrated.
Power Amplifiers for mm-Wave 5G Applications: Technology Comparisons and CMOS-SOI Demonstration Circuits

A review is presented of key power amplifier (PA) performance requirements for millimeter-wave 5G systems, along with a comparison of the potential of different semiconductor technologies for meeting those requirements. Output power, efficiency, and linearity considerations are highlighted, and related to semiconductor material characteristics. Prototype 5G PAs based on silicon technologies are then reviewed, with primary emphasis on CMOS-SOI. Stacked FET PAs based on nMOS and pMOS for 28-GHz operation are presented, along with outphasing and Doherty amplifiers. Peak power-added efficiency (PAE) up to 46% is demonstrated for a two-stack pMOS amplifier with saturation power (Psat) above 19 dBm. PAE at 6 dB backoff above 27% is shown for an nMOS Doherty PA with 22-dBm Psat. Operation with 64QAM OFDM modulation signals at 800-MHz bandwidth is reported, with up to 13-dBm output power and more than 17% PAE, without the use of digital predistortion. Future challenges for PA development are discussed.
The Promises and Pitfalls of Machine Learning for Detecting Viruses in Aquatic Metagenomes

Tools allowing for the identification of viral sequences in host-associated and environmental metagenomes allows for a better understanding of the genetics and ecology of viruses and their hosts. Recently, new approaches using machine learning methods to distinguish viral from bacterial signal using k-mer sequence signatures were published for identifying viral contigs in metagenomes. The promise of these content-based approaches is the ability to discover new viruses, with no or few known relatives. In this perspective paper, we examine the use of the content-based machine learning tool VirFinder for the identification of viral sequences in aquatic metagenomes and explore the possibility of using ecosystem-focused models targeted to marine metagenomes. We discuss the impact of the training set composition on the tool performance and the current limitation for the retrieval of low abundance viral sequences in metagenomes. We identify potential biases that could arise from machine learning approaches for viral hunting in real-world datasets and suggest possible avenues to overcome them.
Near-Infrared-Light Induced Nanoparticles with Enhanced Tumor Tissue Penetration and Intelligent Drug Release

Tumor tissue presents much denser and stiffer extracellular matrix (ECM), which can hinder the penetration of most nanoparticles (NPs) and contribute to the tumor cell proliferation. Here, NIR-activated losartan was encapsulated in hollow mesoporous prussian blue nanoparticles (HMPBs) to degrade ECM. The results showed that losartan enhanced the penetration of DOX, 1.47% of the injected dose (ID) of DOX reached the tumor tissues, which was 3.00-fold higher than the control group (0.49%). In addition, as the existence of thermo-sensitive lauric acid, (Losartan + DOX)@HMPBs could achieve near "zero drug leakage" during blood circulation, so as to reduce the damage of DOX to normal tissues. Furthermore, the animal experiments proved tumor inhibition ability of (Losartan + DOX)@HMPBs in synergistic of photothermal/chemotherapy, with the tumor growth inhibition rate of 81.3%. Taken together, these findings can be a candidate for developing vectors with enhanced tumor penetration and therapeutic effect in future clinical application. STATEMENT OF SIGNIFICANCE: Due to the existence of denser extracellular matrices (ECM), only 0.7% of the administered nanoparticles dose is delivered to tumor, which will limit the tumors' therapeutic effect. Degradation of ECM can improve the penetration of nanoparticles in tumors. However, no researchers has encapsulated losartan in nanoparticles to degrade ECM. Herein, we developed a NIR induced losartan and DOX co-delivery system based on hollow mesoporous prussian blue nanoparticles (HMPBs) to degrade ECM and improve the penetration of nanoparticles in tumors. The prepared nanoparticles can also acheive near "zero drug leakage" during blood circulation and "fixed-point drug release" in tumor, so as to reduce the damage of DOX to normal tissues. We believe the prepared nanoparticles provide a new platform for cancer treatment.
Rapid Quantification of NETs In Vitro and in Whole Blood Samples by Imaging Flow Cytometry

Neutrophil extracellular trap (NET) formation involves the release of DNA outside the cell to neutralize pathogens. Techniques such as live microscopy, flow cytometry, and intravital imaging allow the characterization of NETs, but these either cannot be applied in vivo, lack specificity or require invasive procedures. We developed an automated analysis method to rapidly acquire and characterize cells as NETs or NET precursors, as opposed to cells undergoing other forms of cell death, using imaging flow cytometry. NETs were maintained in solution using a novel three‐dimensional cell culture system in which cells are suspended at the interface of two liquids of different density. Critically, we identify NETs using an image analysis algorithm based on morphological data showing the extrusion of DNA beyond the cell boundaries. In vitro, we used this technique to demonstrate different requirements for NET formation in human and mouse neutrophils. We also measured NETs in whole blood during infection of mice with the malaria parasite Plasmodium yoelii. We expect this technique will provide a valuable approach to better understand the process of NET formation and its importance in disease. © 2019 International Society for Advancement of Cytometry
Considerations on Probe Design for Affinity‐Guided Protein Conjugation

The plethora of methods developed for the creation of protein conjugates often differs significantly with regard to the heterogeneity of the resulting products, in the degree of genetic manipulation of the protein required, and in the technical skills required to perform the conjugation procedure. Affinity‐guided protein conjugation is a protein labeling methodology based on noncovalent binding interactions between a labeling probe and the protein of interest. These interactions increase the local concentration of a reactive group in the probe on the protein surface thus facilitating the conjugation in proximity of the complexation site. The ability to produce high‐quality conjugates from nongenetically modified proteins both in vitro, but also in cells, demonstrates the power of affinity‐guided protein conjugation. Here, we present the progress of affinity‐guided protein conjugation in relation to selective protein labeling in living systems and the formation of high‐quality protein conjugates. Furthermore, the probe design will be discussed in relation to the utility of the probe for labeling in vitro or in living systems.
Study Habits and Learning Experiences of Undergraduate Students in a Physical Education Major Online Kinesiology Course

This study investigated undergraduate students’ study habits and learning experiences in an online lifespan motor development course. The study was based on the theory of transactional distance. Seven undergraduate physical education majors enrolled in an online course at a Midwestern public university in the United States participated in this study. Data were collected via face-to-face interviews, e-mail communication, bulletin board discussion logs, computer-based quizzes and exams, and a research writing project. Four interrelated themes underpinned by the theory of transactional distance emerged. Data were interpreted through a constant comparative method including (a) transition from experiential to visual learning , (b) how to use a textbook in an online course , (c) computer-based test anxieties , and (d) social justice and diversity sensitivity . The ideal online course puts a set of student tasks (i.e., lectures, projects, and assignments) at the center of the course to constitute the learning experiences of students either independently or collaboratively. Although the study was conducted in the context of the lifespan motor development online course, the recommendations can be applied across different content areas in the kinesiology field. Subscribe to TPE
Combined Immunodeficiency With Late-Onset Progressive Hypogammaglobulinemia and Normal B Cell Count in a Patient With RAG2 Deficiency

Proteins expressed by recombination activating genes 1 and 2 (RAG1/2) are essential in the process of V(D)J recombination that leads to generation of the T and B cell repertoires. Clinical and immunological phenotypes of patients with RAG deficiencies correlate well to the degree of impaired RAG activity and this has been expanding to variants of combined immunodeficiency (CID) or even milder antibody deficiency syndromes. Pathogenic variants that severely impair recombinase activity of RAG1/2 determine a severe combined immunodeficiency (SCID) phenotype, whereas hypomorphic variants result in leaky (partial) SCID and other immunodeficiencies. We report a patient with novel pathogenic compound heterozygous RAG2 variants that result in a CID phenotype with two distinctive characteristics: late-onset progressive hypogammaglobulinemia and highly elevated B cell count. In addition, the patient had early onset of infections, T cell lymphopenia and expansion of lymphocytes after exposure to herpes family viruses. This case highlights the importance of considering pathogenic RAG variants among patients with preserved B cell count and CID phenotype.
MicroRNA-133a and Myocardial Infarction

Myocardial infarction (MI) is the leading cause of morbidity and mortality in the world. The infarcted heart displays typical cell death cascades characterized by a loss of cells and fibrotic scarring in the myocardium. Cardiac hypertrophy and fibrosis largely contribute to ventricular wall thickening and stiffening, altogether defining an adverse cardiac remodeling that ultimately leads to impaired cardiac function and subsequent heart failure. Finding a strategy to promote therapeutic, instead of detrimental, cardiac remodeling may pose as a potent MI treatment. Accumulating evidence shows that microRNAs (miRNAs) may play an essential role in cardiovascular diseases. In particular, microRNA-133a (miR-133a) is one of the most abundant miRNAs in the heart. Multiple studies have demonstrated that miR-133a participates in the early pathology of MI, as well as in subsequent cardiac remodeling. In this review, we summarize recent research progress highlighting the regulatory effects of miR-133a in ischemic myocardial diseases, such as inhibiting angiogenesis, apoptosis, fibrosis, hypertrophy, and inflammation, while promoting therapeutic cardiac remodeling. The goal is to elicit a critical discussion on the translational direction of miRNA-mediated treatments towards a safe and effective MI therapy.
Epidemiological Interface of Sylvatic and Dog Rabies in the North West Province of South Africa

Rabies is a viral zoonosis that causes an estimated 59,000 preventable human fatalities every year. While more than 120 countries remain endemic for dog-mediated rabies, the burden is the highest in Africa and Asia where 99% of human rabies cases are caused by domestic dogs. One such rabies-endemic country is South Africa where an estimated 42 preventable human deaths occur every year. Although canine rabies had been well described for most of the provinces in South Africa, the epidemiology of rabies within the North West Province had not been well defined prior to this investigation. As such, the aim of this study was to use nucleotide sequence analyses to characterise the extant molecular epidemiology of rabies in the North West Province of South Africa—with specific focus on the interface between dogs and sylvatic species. To this end, Rabies lyssavirus isolates originating from the North West Province were subjected to molecular epidemiological analyses relying on the Bayesian Markov Chain Monte Carlo methodology on two distinct gene regions, viz. the G-L intergenic region and partial nucleoprotein gene. Our results provided strong evidence in support of an endemic cycle of canine rabies in the East of the province, and three independent endemic cycles of sylvatic rabies spread throughout the province. Furthermore, evidence of specific events of virus spill-over between co-habiting sylvatic species and domestic dogs was found. These results suggest that the elimination of canine-mediated rabies from the province will rely not only on eliminating the disease from the dog populations, but also from the co-habiting sylvatic populations using oral rabies vaccination campaigns.
Police detentions of ‘mentally disordered persons’: A multi-method investigation of section 136 use in Sussex

This research was conducted in response to governmental and public concern regarding the escalating use of section 136 of the Mental Health Act (1983) nationally and of the excessive use of police custody as a place of safety in Sussex in particular. A retrospective analysis of all detentions in Sussex during 2012 was combined with qualitative data from 37 people with lived experience of detention, as well as police, National Health Service (NHS) and allied staff and volunteers. Predominantly, police used s136 as suicide prevention (80%) when no other services or help were available. During the period of study (2013–2016), effective joint working strategies, such as the street triage pilot, were able to reduce the overall rates of s136 detentions and to increase access to NHS place of safety suites markedly. Although the research acknowledges idiosyncratic local factors which contribute to the high rate of detentions across Sussex, the results have wider implications for national policy and practice.
Adaptation of Dominant Species to Drought in the Inner Mongolia Grassland – Species Level and Functional Type Level Analysis

The adaptation of plants to drought through the adjustment of their leaf functional traits is a hot topic in plant ecology. However, while there is a good understanding of how individual species adapt to drought in this way, the way in which different functional types adapt to drought along a precipitation gradient remains poorly understood. In this study, we sampled 22 sites along a precipitation gradient in the Inner Mongolia grassland and measured eight leaf functional traits across 39 dominant species to determine the adaptive strategies of plant leaves to drought at the species and plant functional type levels. We found that leaf functional traits were mainly influenced by both aridity and phylogeny at the species level. There were four types of leaf adaptations to drought at the functional type level: adjusting the carbon-nitrogen ratio, the specific leaf area, the nitrogen content, and the specific leaf area and leaf nitrogen content simultaneously. These findings indicate that there is the trade-offs relationship between water and nitrogen acquisition as the level of drought increases, which is consistent with the worldwide leaf economics spectrum. In this study, we highlighted that the leaf economic spectrum can be adopted to reveal the adaptations of plants to drought in the Inner Mongolia grassland.