Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermodynamic limits of energy harvesting from outgoing thermal radiation

Significance A large part of the research on renewable energy has focused on harvesting power from solar radiation. But, for the Earth to maintain its temperature, it must radiate to the outer space an amount of power approximately equal to that of the incoming solar radiation. However, far less is understood about the theoretical limits of harvesting power from such outgoing radiation. Here, we identify a duality relation between harvesting incoming and outgoing thermal radiation and use it to derive fundamental limits of harvesting outgoing thermal radiation. Our results indicate a theoretical limit that far exceeds what was previously thought to be possible and highlight the significant potential for harvesting outgoing thermal radiation for renewable energy applications. We derive the thermodynamic limits of harvesting power from the outgoing thermal radiation from the ambient to the cold outer space. The derivations are based on a duality relation between thermal engines that harvest solar radiation and those that harvest outgoing thermal radiation. In particular, we derive the ultimate limit for harvesting outgoing thermal radiation, which is analogous to the Landsberg limit for solar energy harvesting, and show that the ultimate limit far exceeds what was previously thought to be possible. As an extension of our work, we also derive the ultimate limit of efficiency of thermophotovoltaic systems.
Learning Generative ConvNets via Multi-grid Modeling and Sampling

This paper proposes a multi-grid method for learning energy-based generative ConvNet models of images. For each grid, we learn an energy-based probabilistic model where the energy function is defined by a bottom-up convolutional neural network (ConvNet or CNN). Learning such a model requires generating synthesized examples from the model. Within each iteration of our learning algorithm, for each observed training image, we generate synthesized images at multiple grids by initializing the finite-step MCMC sampling from a minimal 1 Ã— 1 version of the training image. The synthesized image at each subsequent grid is obtained by a finite-step MCMC initialized from the synthesized image generated at the previous coarser grid. After obtaining the synthesized examples, the parameters of the models at multiple grids are updated separately and simultaneously based on the differences between synthesized and observed examples. We show that this multi-grid method can learn realistic energy-based generative ConvNet models, and it outperforms the original contrastive divergence (CD) and persistent CD.
Distributed Adaptive Sliding Mode Control of Vehicular Platoon With Uncertain Interaction Topology

In a platoon control system, a fixed and symmetrical topology is quite rare because of adverse communication environments and continuously moving vehicles. This paper presents a distributed adaptive sliding mode control scheme for more realistic vehicular platooning. In this scheme, adaptive mechanism is adopted to handle platoon parametric uncertainties, while a structural decomposition method deals with the coupling of interaction topology. A numerical algorithm based on linear matrix inequality is developed to place the poles of the sliding motion dynamics in the required area to balance quickness and smoothness. The proposed scheme allows the nodes to interact with each other via different types of topologies, e.g., either asymmetrical or symmetrical, either fixed or switching. Different from existing techniques, it does not require the exact values of each entity in the topological matrix, and only needs to know the bounds of its eigenvalues. The effectiveness of this proposed methodology is validated by bench tests under several conditions.
Epileptic seizure detection based on video and EEG recordings

Clinical data from epileptic patients reveal important information about the characteristics of the particular type of epilepsy. Such data is often acquired in a bimodal fashion, e.g. video recordings are collected with the standard Electroencephalogram (EEG) data, in order to help the specialists validate their assessment based on one modality with the other. Manual annotation of the onset of seizures across several days' worth of data is time consuming. This paper proposes an automated epilepsy seizure detection method based on a combination of features from EEG and video data, and compares it against detectors using either modality alone.
Comparing the dosimetric characteristics of the electron beam from dedicated intraoperative and conventional radiotherapy accelerators

The specific design of the mobile dedicated intraoperative radiotherapy (IORT) accelerators and different electron beam collimation system can change the dosimetric characteristics of electron beam with respect to the conventional accelerators. The aim of this study is to measure and compare the dosimetric characteristics of electron beam produced by intraoperative and conventional radiotherapy accelerators. To this end, percentage depth dose along clinical axis (PDD), transverse dose profile (TDP), and output factor of LIAC IORT and Varian 2100C/D conventional radiotherapy accelerators were measured and compared. TDPs were recorded at depth of maximum dose. The results of this work showed that depths of maximum dose, R90,R50, and RP for LIAC beam are lower than those of Varian beam. Furthermore, for all energies, surface doses related to the LIAC beam are substantially higher than those of Varian beam. The symmetry and flatness of LIAC beam profiles are more desirable compared to the Varian ones. Contrary to Varian accelerator, output factor of LIAC beam substantially increases with a decrease in the size of the applicator. Dosimetric characteristics of beveled IORT applicators along clinical axis were different from those of the flat ones. From these results, it can be concluded that dosimetric characteristics of intraoperative electron beam are substantially different from those of conventional clinical electron beam. The dosimetric characteristics of the LIAC electron beam make it a useful tool for intraoperative radiotherapy purposes. PACS number: 87.56. ‐v, 87.56. bd
Prediction of long time creep rupture properties of welded joints using the results of short duration creep crack incubation tests

The aim of this research project is to examine the applicability of the LICON methodology for predicting the long–time creep rupture strength of a dissimilar metal weld. The LICON methodology is an approach for predicting the lifetime of materials under creep loading conditions. The LICON method predicts long–time uniaxial creep strength using the results from several short duration creep crack incubation tests in conjunction with the outcome of a mechanical analysis on the testpiece (e.g. a reference stress solution). In the late 1990s, this method was successfully applied to advanced 9%Cr pipe steels (including their welded joints) and later, reports on applicability of the method for a high creep strength 1CrMoV were published. This study has re-examined the previous application of the LICON methodology for 9%Cr and 1CrMoV steels. It has shown that application of the original LICON method (based on reference stress solutions) for certain materials is not appropriate. Application of reference stress solutions is limited to materials which achieve complete stress redistribution before the onset of crack extension (e.g. for advanced 9%Cr pipe steels). For ’non-reference stress’ materials (creep brittle, notch sensitive materials such as high creep strength 1CrMoV) crack initiation occurs before complete stress redistribution. Application of the original LICON method (based on reference stress solutions) for such materials is therefore not recommended. This study has shown that application of the LICON method to ’non-reference stress’ materials requires careful adoption of a more sophisticated mechanical analysis approach (e.g. finite element method). Careful examination has shown that the creep finite element analysis of a structure can result in non-unique numerical representations if the assessment procedure has not been carefully defined. In particular, this study has highlighted the importance of considering a reliable stress regime dependent creep constitutive model for analysis of structures with a wide range of redistributing stresses. This study introduced a new (primary–secondary–tertiary)
Higher agrobiodiversity is associated with improved dietary diversity, but not child anthropometric status, of Mayan Achí people of Guatemala

Abstract Objective Child undernutrition remains one of the greatest challenges for public health nutrition in rural areas in developing countries. Interventions aiming to increase and conserve agrobiodiversity seem to be promising alternatives to improve child nutrition. However, the existing literature on these interventions is not conclusive about their effectiveness in combating child undernutrition. We tested the hypothesis that ‘higher agrobiodiversity is associated with greater dietary diversity and better anthropometric status’ in rural Guatemala. Design/Setting/Subjects In the summer of 2016, we conducted a cross-sectional study with a sample of 154 children (6–60 months). We conducted dietary recalls and structured interviews, measured children’s weight and height, and visited food production systems (Milpas, home gardens, coffee plantations). Crop species richness, nutritional functional diversity, dietary diversity scores and anthropometric status were calculated. Results Higher food self-sufficiency, nutritional functional diversity and dietary diversity scores were positively correlated with higher crop and animal species richness. Contrarily, remoteness to the local market was negatively correlated with dietary diversity scores. However, higher dietary diversity scores were not correlated with better child anthropometric status. Better child anthropometric status was positively correlated with improved sanitary conditions and maternal education; and negatively correlated with large household size and frequent child morbidity. Conclusions Agricultural diversification could diversify diets, increase nutrient availability and improve child anthropometry. However, these interventions need to be accompanied by sanitation improvements, family planning, nutritional education and women’s empowerment to strengthen their positive effect on diet and nutrition.
Can reactivity and regulation in infancy predict inattentive and hyperactive/impulsive behavior in 3-year-olds?

Abstract A need to identify early infant markers of later occurring inattentive and hyperactive/impulsive behaviors has come to the fore in the current attention-deficit/hyperactivity disorder literature. The purpose of such studies is to identify driving mechanisms that could enable early detection of attention-deficit/hyperactivity disorder liability and thus facilitate early intervention. Here we study independent and interactive effects of cognitive regulation (inhibition and sustained attention), temperament (reactive and regulatory aspects), and maternal sensitivity (as external regulation) in a sample of 112 typically developing 10-month-old infants (59 boys, 52.7%), in relation to inattentive and hyperactive/impulsive behavior at 3 years. The results showed that infant temperamental regulation and maternal sensitivity made independent contributions to both inattention and hyperactivity/impulsivity, in that higher levels of temperamental regulation and maternal sensitivity were related to less inattentive and hyperactive/impulsive behavior. In addition, the temperamental factor positive affectivity/surgency made a significant contribution to later hyperactivity/impulsivity, in that higher levels of positive affectivity/surgency were related to more hyperactive/impulsive behavior. No interaction effects were found. Our findings suggest temperament and parental regulation as potential and independent markers of later inattentive and hyperactive/impulsive behavior.
Protocol for validation of the 4AT, a rapid screening tool for delirium: a multicentre prospective diagnostic test accuracy study

Introduction Delirium is a severe neuropsychiatric syndrome of rapid onset, commonly precipitated by acute illness. It is common in older people in the emergency department (ED) and acute hospital, but greatly under-recognised in these and other settings. Delirium and other forms of cognitive impairment, particularly dementia, commonly coexist. There is a need for a rapid delirium screening tool that can be administered by a range of professional-level healthcare staff to patients with sensory or functional impairments in a busy clinical environment, which also incorporates general cognitive assessment. We developed the 4 ’A’s Test (4AT) for this purpose. This study’s primary objective is to validate the 4AT against a reference standard. Secondary objectives include (1) comparing the 4AT with another widely used test (the Confusion Assessment Method (CAM)); (2) determining if the 4AT is sensitive to general cognitive impairment; (3) assessing if 4AT scores predict outcomes, including (4) a health economic analysis. Methods and analysis 900 patients aged 70 or over in EDs or acute general medical wards will be recruited in three sites (Edinburgh, Bradford and Sheffield) over 18 months. Each patient will undergo a reference standard delirium assessment and will be randomised to assessment with either the 4AT or the CAM. At 12 weeks, outcomes (length of stay, institutionalisation and mortality) and resource utilisation will be collected by a questionnaire and via the electronic patient record. Ethics and dissemination Ethical approval was granted in Scotland and England. The study involves administering tests commonly used in clinical practice. The main ethical issues are the essential recruitment of people without capacity. Dissemination is planned via publication in high impact journals, presentation at conferences, social media and the website www.the4AT. com. Trial registration number ISRCTN53388093; Pre-results.
Use of E-Learning by University Students in Malaysian Higher Educational Institutions: A Case in Universiti Teknologi Malaysia

This paper examines university students’ intention to utilize e-learning. In this paper, we apply and use the theory of a technology acceptance model. We employ the structural equation modeling approach with a SmartPLS software to investigate students’ adoption process. Findings indicate that the content of e-learning and self-efficacy has a positive impact and substantially associated with perceived usefulness and student satisfaction, which impact university students’ intention to utilize e-learning. Although e-learning has gained acceptance in universities around the world, the study of the intention to use e-learning is still largely unexplored in Malaysia. The developed model is employed to explain the university student’s intention to utilize e-learning. The study concludes that university students in Malaysia have positive perceptions toward e-learning and intend to practice it for educational purposes.
Neonatal Immunization: Rationale, Current State, and Future Prospects

Infections take their greatest toll in early life necessitating robust approaches to protect the very young. Here, we review the rationale, current state, and future research directions for one such approach: neonatal immunization. Challenges to neonatal immunization include natural concern about safety as well as a distinct neonatal immune system that is generally polarized against Th1 responses to many stimuli such that some vaccines that are effective in adults are not in newborns. Nevertheless, neonatal immunization could result in high-population penetration as birth is a reliable point of healthcare contact, and offers an opportunity for early protection of the young, including preterm newborns who are deficient in maternal antibodies. Despite distinct immunity and reduced responses to some vaccines, several vaccines have proven safe and effective at birth. While some vaccines such as polysaccharide vaccines have little effectiveness at birth, hepatitis B vaccine can prime at birth and requires multiple doses to achieve protection, whereas the live-attenuated Bacille Calmette–Guérin (BCG), may offer single shot protection, potentially in part via heterologous (“non-specific”) beneficial effects. Additional vaccines have been studied at birth including those directed against pertussis, pneumococcus, Haemophilus influenza type B and rotavirus providing important lessons. Current areas of research in neonatal vaccinology include characterization of early life immune ontogeny, heterogeneity in and heterologous effects of BCG vaccine formulations, applying systems biology and systems serology, in vitro platforms that model age-specific human immunity and discovery and development of novel age-specific adjuvantation systems. These approaches may inform, de-risk, and accelerate development of novel vaccines for use in early life. Key stakeholders, including the general public, should be engaged in assessing the opportunities and challenges inherent to neonatal immunization.
A hybrid process-mining approach for simulation modeling

This paper presents a hybrid Modeling and Simulation framework to address business process challenges. The framework has integrated process mining techniques in the conceptual modeling phase to support developing simulation models that are unbiased and close reflection of reality in a timely manner. The hybrid approach overcomes the pitfalls of traditional conceptual modeling by using process mining techniques to discover valuable process knowledge from the analysis of event logs. The proposed hybrid framework has been applied to an Emergency Department (ED) in order to identify performance bottlenecks and explore improvement strategies in an attempt to meet national performance targets. A large number of unique process flows (i.e. patient pathways) within the ED were uncovered and deviations from process guidelines were accurately identified. Results show that unblocking of ED outflows have a significant impact on patients length of stay (over 80% improvement) rather than increasing the ED physical capacity.
Expression of the microRNA-143/145 cluster is decreased in hepatitis B virus-associated hepatocellular carcinoma and may serve as a biomarker for tumorigenesis in patients with chronic hepatitis B

The aims of the present study were to identify the expression profile of microRNA (miR)-143/145 in hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC), explore its association with prognosis and investigate whether the serum miR-143/145 expression levels may serve as a diagnostic indicator of HBV-associated HCC. The microRNA (miRNA) chromatin immunoprecipitation dataset was obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus databases, and analyzed using the Wilcoxon signed-rank test. It was observed that the expression of miR-143 and miR-145 was decreased 1.5-fold in HBV-associated HCC samples compared with non-tumor tissue in the TCGA and the GSE22058 datasets (P<0.01). Using the reverse transcription-quantitative polymerase chain reaction, it was further confirmed that miR-143/145 and their host gene MIR143HG were downregulated in HBV-associated HCC tissues compared with corresponding distal non-tumor tissues. The lower level of miR-143 and miR-145 expression was associated with tumor differentiation, and may thus be responsible for a poor prognosis of patients with HBV-associated HCC. The receiver-operating characteristic (ROC) curves were used to explore the potential value of miR-143 and miR-145 as biomarkers for predicting HBV-associated HCC tumorigenesis. In serum, miR-143/145 were identified to be significantly decreased in patients with HBV-associated HCC compared with negative control patients, and their associated areas under the ROC curves were calculated at 0.813 and 0.852 (P<0.05), with each having a sensitivity and a specificity close to 0.80. These results indicated that the decreased expression of the miR-143/145 cluster and their host gene MIR143HG in HBV-associated HCC tissue was associated with prognosis, and each of these miRNAs may serve as a valuable diagnostic biomarker for predicting HBV-associated HCC tumorigenesis.
Viscoelastic Large Strain Model of Bitumen Used for Corrosion Protection in Subsea Cables and Umbilicals

Bitumen is used as anticorrosion material to protect armor wires in subsea cables and umbilicals. Establishing bitumen’s viscoelastic properties is essential for developing analytical models of how bitumen influences the cable’s mechanical properties, in particular the bending stiffness. A new laboratory instrument has been developed for establishing the viscoelastic properties of bitumen subject to equally large strains as in real-life cables. This paper presents the basic principle of the new instrument and derives how to calculate bitumen’s viscoelastic properties from the measurements logged by the instrument. The paper also models bitumen’s viscoelastic properties as function of strain amplitude, strain frequency, and bitumen temperature, using multi-variable data analysis. These models show that the viscoelastic properties are highly temperature dependent. Bitumen’s shear stress / shear strain amplitude ratio grows with increasing rate as the temperature decreases.Copyright © 2015 by ASME
A Graph Summarization: A Survey

While advances in computing resources have made processing enormous amounts of data possible, human ability to identify patterns in such data has not scaled accordingly. Thus, efﬁcient computational methods for condensing and simplifying data are becoming vital for extracting actionable insights. In particular, while data summarization techniques have been studied extensively, only recently has summarizing interconnected data, or graphs , become popular. This survey is a structured, comprehensive overview of the state-of-the-art methods for summarizing graph data. We ﬁrst broach the motivation behind and the challenges of graph summarization. We then categorize summarization approaches by the type of graphs taken as input and further organize each category by core methodology. Finally, we discuss applications of summarization on real-world graphs and conclude by describing some open problems in the ﬁeld.
The Role of Immune and Inflammatory Cells in Idiopathic Pulmonary Fibrosis

The contribution of the immune system to idiopathic pulmonary fibrosis (IPF) remains poorly understood. While most sources agree that IPF does not result from a primary immunopathogenic mechanism, evidence gleaned from animal modeling and human studies suggests that innate and adaptive immune processes can orchestrate existing fibrotic responses. This review will synthesize the available data regarding the complex role of professional immune cells in IPF. The role of innate immune populations such as monocytes, macrophages, myeloid suppressor cells, and innate lymphoid cells will be discussed, as will the activation of these cells via pathogen-associated molecular patterns derived from invading or commensural microbes, and danger-associated molecular patterns derived from injured cells and tissues. The contribution of adaptive immune responses driven by T-helper cells and B cells will be reviewed as well. Each form of immune activation will be discussed in the context of its relationship to environmental and genetic factors, disease outcomes, and potential therapies. We conclude with discussion of unanswered questions and opportunities for future study in this area.