Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploiting Intersentence Information for Better Question-Driven Abstractive Summarization: Algorithm Development and Validation

Background Question-driven summarization has become a practical and accurate approach to summarizing the source document. The generated summary should be concise and consistent with the concerned question, and thus, it could be regarded as the answer to the nonfactoid question. Existing methods do not fully exploit question information over documents and dependencies across sentences. Besides, most existing summarization evaluation tools like recall-oriented understudy for gisting evaluation (ROUGE) calculate N-gram overlaps between the generated summary and the reference summary while neglecting the factual consistency problem. Objective This paper proposes a novel question-driven abstractive summarization model based on transformer, including a two-step attention mechanism and an overall integration mechanism, which can generate concise and consistent summaries for nonfactoid question answering. Methods Specifically, the two-step attention mechanism is proposed to exploit the mutual information both of question to context and sentence over other sentences. We further introduced an overall integration mechanism and a novel pointer network for information integration. We conducted a question-answering task to evaluate the factual consistency between the generated summary and the reference summary. Results The experimental results of question-driven summarization on the PubMedQA data set showed that our model achieved ROUGE-1, ROUGE-2, and ROUGE-L measures of 36.01, 15.59, and 30.22, respectively, which is superior to the state-of-the-art methods with a gain of 0.79 (absolute) in the ROUGE-2 score. The question-answering task demonstrates that the generated summaries of our model have better factual constancy. Our method achieved 94.2% accuracy and a 77.57% F1 score. Conclusions Our proposed question-driven summarization model effectively exploits the mutual information among the question, document, and summary to generate concise and consistent summaries.
Sexual Self-Concept Differentiation: An Exploratory Analysis of Online and Offline Self-Perspectives

Self-concept differentiation (SCD) has been of interest to researchers, mainly as a structural concept indicative of social specialization or self-concept fragmentation. Nevertheless, this aspect of self-representation has not been studied in regard to sexuality and the extent to which the sexual self may vary across different roles or situations. With the emergence of the Internet, people found new opportunities to explore and express aspects of their sexuality in multiple online scenes, thus increasing the complexity of human sexual experience and expanding the reach of sexual identity. The aim of this study is to investigate SCD in relation to the sexual self-concept, as experienced in the online and offline environments, and its effects on sexual identity, sexual satisfaction and online sexual behaviors. Data analysis pointed towards a fragmented self-view with high degrees of differentiation between the online and offline sexual self-instances being linked to a weaker sense of sexual identity, less sexual satisfaction in real life and less partnered online interactions. However, there were some indications that these relationships were influenced by how people perceive themselves sexually in one instance compared to the other. The results obtained in this study encourage further research on SCD as an important factor in understanding the real-world consequences of online sexual expression.
Composite corporate traveling‐wave power dividers for slot array waveguide antennas

A composite corporate traveling‐wave power divider is presented. The single‐layer structure is composed of three parts: two interdigital traveling‐wave subsections combined with a power splitter. An iterative design technique is described in which the divider is split into a number of basic blocks. Large‐scaled networks are then easily designed because the whole structure does not need to be simulated. A method to take into account the insertion losses is also proposed and bandwidth enhancement is discussed, which is done by increasing the number of corporate layers. Experimental results are also shown for a 1:4 subsection. It provides equal output power with 0.5 dB of insertion loss. The phase‐shift between output ports is close to the specifications of −150° at 30 GHz, with an error of less than 2°. It is also shown that this topology is well suited for frequency scanning antenna. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.
Position‐aided fast millimetre‐wave beam training with compressive sensing

A novel position-aided fast millimetre-wave beam training using compressive sensing (PAF-CS) is proposed. In particular, the position information is used to obtain the angle-of-arrival, and this operation can facilitate beam alignment with significantly reduced system overhead. Aiming to resolve the position uncertainty, the PAF-CS method first identifies a critical area by using the statistical information of the position error, and finds the best beams by using CS method. Theoretical analysis and simulation validate the superiority of the PAF-CS method.
Evaluation of cancer outcome assessment using MRI: A review of deep-learning methods

Accurate evaluation of tumor response to treatment is critical to allow personalized treatment regimens according to the predicted response and to support clinical trials investigating new therapeutic agents by providing them with an accurate response indicator. Recent advances in medical imaging, computer hardware, and machine-learning algorithms have resulted in the increased use of these tools in the field of medicine as a whole and specifically in cancer imaging for detection and characterization of malignant lesions, prognosis, and assessment of treatment response. Among the currently available imaging techniques, magnetic resonance imaging (MRI) plays an important role in the evaluation of treatment assessment of many cancers, given its superior soft-tissue contrast and its ability to allow multiplanar imaging and functional evaluation. In recent years, deep learning (DL) has become an active area of research, paving the way for computer-assisted clinical and radiological decision support. DL can uncover associations between imaging features that cannot be visually identified by the naked eye and pertinent clinical outcomes. The aim of this review is to highlight the use of DL in the evaluation of tumor response assessed on MRI. In this review, we will first provide an overview of common DL architectures used in medical imaging research in general. Then, we will review the studies to date that have applied DL to magnetic resonance imaging for the task of treatment response assessment. Finally, we will discuss the challenges and opportunities of using DL within the clinical workflow.
A Buck-Boost DC/DC Converter with High Efficiency Suitable for Renewable Energies

Abstract In this paper, a non-isolated buck-boost dc/dc converter with only one switch is presented. The proposed converter consists of one switch in the input side (S), four inductors, four diodes, six capacitors and a capacitor in the output side (Co). In fact, the combination of the inductor, diode and capacitor leads voltage level is increased. Actually, the voltage stress on power switch is decreased for higher power limits at various duty-cycles by combining these components. Therefore, conduction losses can be reduced by using a switch with lower resistance RDS(ON). Another advantage of the proposed converter is that the normalized voltage stress on diodes is low. As a result, the efficiency of proposed converter is high. In order to investigate the competences of the proposed converter, comparison results with other structures are provided. The principle of operation, theoretical analysis and the experimental prototype of proposed converter in about 120 W with operating at 25 kHz are provided.
Analysis of Microbial Community, Volatile Flavor Compounds, and Flavor of Cigar Tobacco Leaves From Different Regions

Despite the booming international trade in cigar tobacco leaves (CTLs), the main characteristics of tobacco leaves from different producing areas are rarely reported. This study aimed to characterize the microbial community, volatile flavor compounds (VFCs), and flavor of CTLs from four famous cigar-producing areas, including Dominica, Brazil, Indonesia, and China. High-throughput sequencing results showed that the dominant genera in CTLs were Staphylococcus, Pseudomonas, Aspergillus, Sampaiozyma, and Alternaria. Sensory analysis revealed that Indonesian and Chinese CTLs were characterized by leathery, peppery, and baked aroma. Brazilian CTLs were dominated by caramel and herb aroma. Dominican CTLs had aromas of milk, fruity, sour, cream, flower, nutty, and honey. Supplemented with the determination of volatile flavor compounds (VFCs), the flavor of CTLs could be scientifically quantified. Most of these VFCs were aldehydes and ketones, and 20 VFCs showed significant differences in CTLs from different regions. The microbial community, VFCs, and flavor of CTLs vary widely due to geographic differences. Network analysis revealed the microbial community was closely related to most VFCs, but the relationships between the fungal community and VFCs were less than the bacterial community, and most of them were negative. Furthermore, it also found that the bacterial community had a greater contribution to the flavor of CTLs than the fungal community. This study obtained essential information on CTLs, which laid a foundation for deeply excavating the relationship between microbes and VFCs and flavor, and establishing a tobacco information database.
Case report of a rare primary intracranial malignant melanoma, reviewing the literature and guidance for management

Primary intracranial malignant melanoma (PIMM), is a rare intracranial malignancy arising from melanocytes lining leptomeningeal tissue. It accounts for approximately 1% of all melanomas and 0.07% of all brain malignancies (1). It can be classified into 2 types—diffuse meningeal melanomatosis or solitary (discrete) solid tumours depending on imaging pattern (2). PIMMs rarely metastasize beyond the central nervous system (CNS) and are histologically similar to melanomas of other sites. They are often diagnosed after excluding the presence of extracranial lesions from careful physical examinations and positron emission tomography-computed tomography (PET-CT) imaging. Specific molecular mutations in GNAQ and GNA11 genes may also be helpful to distinguish PIMMs from metastatic melanoma (3,4). Given the rarity of this disease, there are no standard management guidelines and most of the evidence for treatment comes from shared experiences of case reports or are inferred from the treatment of metastatic melanoma. We present a recent case experience in accordance with the CARE reporting checklist (available at https://tro.amegroups.com/article/ view/10.21037/tro-21-32/rc) and referenced the evidence to guide our management decisions. Case Report
Towards In-mould Antennas for Geolocation Tags

This paper presents a preliminary study for the construction of an in-mould smart tag as a robust flexible and battery-free label with a radiofrequency energy harvesting sub-system and enhanced geolocation features. The proposed flexible geolocation tag is realized by means of a specific production process applied over printed antennas and hybridized rigid control module. Advanced materials such as highly conductive inks and nanocellulose-based substrates, as well as innovative manufacturing processes covered by the in-mould electronics framework, are investigated. Through simulations and experimental validation, the effect over printed antennas of an over-moulded layer of Thermoplastic Polyurethane (TPU) is explored. Such material due to its dielectric properties and thickness tends to down-shift the resonance frequency of the antenna, favouring miniaturization, but also increases its loss resistance. A 1.25 mm thick TPU was chosen for the final tag to ensure both flexibility and a realized positive gain of +0.7 dBi at 865 MHz. For further development of the tag, materials electrical and dielectric properties must be clearly defined in simulation to correct frequency shifts.
Driver Fatigue Detection Systems: A Review

Driver fatigue has been attributed to traffic accidents; therefore, fatigue-related traffic accidents have a higher fatality rate and cause more damage to the surroundings compared with accidents where the drivers are alert. Recently, many automobile companies have installed driver assistance technologies in vehicles for driver assistance. Third party companies are also manufacturing fatigue detection devices; however, much research is still required for improvement. In the field of driver fatigue detection, continuous research is being performed and several articles propose promising results in constrained environments, still much progress is required. This paper presents state-of-the-art review of recent advancement in the field of driver fatigue detection. Methods are categorized into five groups, i.e., subjective reporting, driver biological features, driver physical features, vehicular features while driving, and hybrid features depending on the features used for driver fatigue detection. Various approaches have been compared for fatigue detection, and areas open for improvements are deduced.
Virtual Reality for Urban Sound Design: A Tool for Architects and Urban Planners

Urban sound is one of the main concerns of architects and urban planners in contempo- rary cities: how to control it, what to do about noise pollution, where silent areas should be situated, or which urban decisions must be made. These questions, among others, are based on spatial sound. Virtual reality is a powerful technology that can serve as a design tool to find some answers to these questions. Due to its power to generate realistic images of the environments that are studied, it is easy to see that virtual reality could contribute to the visualization and auralization of spaces before their construction. This task is one of architects’ responsibilities, and such a tool could be very useful to them. This chapter highlights the principles and some applications of virtual reality in urban sound design. Two big differences separate the experience of illuminating and sonic phenomena. The first consists of the fact that most visual objects are not sources of light, but simply objects, in the usual sense of the word, with light shining on them. Physicists are therefore quite accustomed to distinguishing light from the objects that reflect it. If the object itself gives out light, then we say it is a light “source”. With sound there is nothing like this. In the overwhelming majority of sonic phenomena, sound as origi-nating from “sources” is emphasized. However, the classic distinction in optics between sources and objects has not been imposed in acoustics. Attention has been given to the sound (as we say the light) considered as an emanation from a source, its paths and deformations, without the appreciation of the shapes and contours of this sound apart from the reference to its source [2] .
The effects of students’ perceived usefulness and trustworthiness of peer feedback on learning satisfaction in online learning environments

In this study, students' perceived usefulness and trustworthiness of peer feedback on learning satisfaction in the online learning environment were investigated using a pre-test and post-test research design at Wageningen University and Research. In total, 135 undergraduate students participated in this study. Students’ peer feedback performance was observed in argumentative essay writing. A module called “Argumentative Essay Writing” was designed and students were asked to write an essay, provide peer feedback on peers’ essays, and revise their essay based on the received feedback. Then students were asked to fill out the learning satisfaction and the attitude award to peer feedback surveys. The results showed that students’ perceived usefulness and trustworthiness of peer feedback affect their learning satisfaction. This study adds to our understanding of the importance of the perceived usefulness and trustworthiness of peer feedback in online learning environments particularly in the context of argumentative essay writing. Keywords: learning satisfaction; online peer feedback; perceived usefulness; perceived trustworthiness.
Nonlinearizable solutions in an eigenvalue problem for Maxwell's equations with nonhomogeneous nonlinear permittivity in a layer

The paper focuses on a problem arising in nonlinear guided wave optics. The problem for Maxwell's equations with nonhomogeneous nonlinear constitutive law is reduced to an eigenvalue problem for a system of nonlinear ordinary differential equations with local boundary conditions. We suggest a novel approach to study eigenvalue problems for nonlinear nonautonomous equations based on studying an integral characteristic equation (ICE) of the problem. Using asymptotical analysis of the ICE, we prove existence of infinitely many eigenvalues and find their distribution. It is important that the corresponding linear problem has only a finite number of eigenvalues.
Resolving the fine structure in the energy landscapes of repeat proteins

Abstract Abstract Ankyrin (ANK) repeat proteins are coded by tandem occurrences of patterns with around 33 amino acids. They often mediate protein–protein interactions in a diversity of biological systems. These proteins have an elongated non-globular shape and often display complex folding mechanisms. This work investigates the energy landscape of representative proteins of this class made up of 3, 4 and 6 ANK repeats using the energy-landscape visualisation method (ELViM). By combining biased and unbiased coarse-grained molecular dynamics AWSEM simulations that sample conformations along the folding trajectories with the ELViM structure-based phase space, one finds a three-dimensional representation of the globally funnelled energy surface. In this representation, it is possible to delineate distinct folding pathways. We show that ELViMs can project, in a natural way, the intricacies of the highly dimensional energy landscapes encoded by the highly symmetric ankyrin repeat proteins into useful low-dimensional representations. These projections can discriminate between multiplicities of specific parallel folding mechanisms that otherwise can be hidden in oversimplified depictions.
Moderne Parametrik in der Tragwerksplanung – Werkbericht

Vor 150 Jahren bildeten Feder und Papier die hauptsächlichen Werkzeuge zur bildlichen Darstellung technischer Zusammenhänge. Mit dem Eintritt ins Computerzeitalter ging ein radikaler Wandel der Darstellungsmethoden einher. Die Vorteile einer digitalen Zeichnung liegen auf der Hand: Anstatt bei Änderungen eine Linie mühsam vom Papier zu kratzen, reichen wenige Mausklicks; verlustfreie Vervielfältigung am Computer ersetzt das Lichtpausen. Im Zusammenspiel mit computerunterstützter Fertigung eröffnet sich zudem die Möglichkeit einer durchgehenden digitalen Arbeitskette, die vom ersten Entwurf bis zum fertigen Produkt reicht.
Brooding Temperature Alters Yolk Sac Absorption and Affected Ovarian Development in Goslings

Simple Summary It is well known that brooding temperature affects yolk sac absorption so as to affect the growth and development of geese. In order to explore the brooding temperature on the absorption of yolk sac and the ovary development of goslings, the weight and fatty acid composition of yolk sac, body weight, ovary weight and structure was measured. The expression of ovary development related genes was quantified. The results suggested that 29 °C brooding temperature in the early stage could promote the absorption of fatty acids from yolk sac, which is conducive to ovary and body weight, and the expression of ovarian development-related genes of CHK1, FGF12, and SMAD4. The results could provide guidance on gosling brooding for farmers. Abstract In order to explore the brooding temperature on the absorption of yolk sac and the ovary development of goslings, 126 1-day-old female goslings were randomly divided into three groups with three replicates in each group. The brooding temperatures were set at 32 °C, 29 °C and 26 °C (represent G32, G29 and G26), respectively, in each group. At 48, 60 and 72 h, two goslings from each replicate were weighed, and the yolk sac was collected and weighed. The fatty acid composition of yolk sac fluid was determined by gas chromatography-mass spectrometry (GC-MS). At 1, 2, 3, and 4 weeks of age, goslings from each replicate were weighed, the ovaries were weighed and fixed for hematoxylin-eosin (HE) staining, Cell cycle checkpoint kinase 1 (CHK1), fibroblast growth factor 12 (FGF12) and Sma-and Mad-related protein 4 (SMAD4) which related to regulation of ovarian development were determined by qRT-PCR. The body weight of G29 and G26 was significantly higher than that of G32 at 72 h (p < 0.05). The contents of C14:0, C16:0, C18:2n6c and total fatty acid (ΣTFA) from G32 were significantly higher than that of G26 (p < 0.05), and the contents of C18:1n9t and C22:0 in G29 were significantly higher than that of G26 (p < 0.05). The ovary index, ovary and body weight were significantly higher in G29 than those of G32 and G26 at 2 weeks of age (p < 0.05). The number of primordial follicles, number of primary follicles and diameter of primary follicles were significantly higher in G29 than those in G32 and G26 at 4 weeks of age (p < 0.05). In G29, the expression of CHK1 and SMAD4 was significantly higher than that in G32, and the expression of FGF12 and SMAD4 was significantly higher (p < 0.05) than that in G26 at 2 and 4 weeks of age. In conclusion, brooding temperature at 29 °C could promote the absorption of fatty acids in yolk sac, body weight gain, and ovarian development through up-regulating the expression of CHK1, FGF12 and SMAD4.
Automatic Detection of Atrial Fibrillation and Other Arrhythmias in ECG Recordings Acquired by a Smartphone Device

Atrial fibrillation (AF) is the most common cardiac disease and is associated with other cardiac complications. Few attempts have been made for discriminating AF from other arrhythmias and noise. The aim of this study is to present a novel approach for such a classification in short ECG recordings acquired using a smartphone device. The implemented algorithm was tested on the Physionet Computing in Cardiology Challenge 2017 Database and, for the purpose of comparison, on the MIT-BH AF database. After feature extraction, the stepwise linear discriminant analysis for feature selection was used. The Least Square Support Vector Machine classifier was trained and cross-validated on the available dataset of the Challenge 2017. The best performance was obtained with a total of 30 features. The algorithm produced the following performance: F1 Normal rhythm = 0.92; F1 AF rhythm: 0.82; F1 Other rhythm = 0.75; Global F1 = 0.83, obtaining the third best result in the follow-up phase of the Physionet Challenge. On the MIT-BH ADF database the algorithm gave the following performance: F1 Normal rhythm = 0.98; F1 AF rhythm: 0.99; Global F1 = 0.98. Since the algorithm reliably detect AF and other rhythms in smartphone ECG recordings, it could be applied for personal health monitoring systems.