Miracle-dz/UniFAR-FTUs huggingface dataset:
Children’s Negotiations of Visualization Skills During a Design-Based Learning Experience Using Nondigital and Digital Techniques

In the context of a 10-day summer camp makerspace experience that employed design-based learning (DBL) strategies, the purpose of this descriptive case study was to better understand the ways in which children use visualization skills to negotiate design as they move back and forth between the world of nondigital design techniques (i.e., drawing, 3-D drawing with hot glue, sculpture, discussion, writing) and digital technologies (i.e., 3-D scanning, 3-D modeling, 3-D printing). Participants included 20 children aged 6–12. This research was guided by Vossoughi, Hooper, and Escudé’s (2016) call for explicit attention to pedagogical practices during the integration of “making” activities. Content analysis was used to analyze qualitative data, including observation, researcher/facilitator field notes, think aloud protocols, daily reflective exit tickets, and participant artifacts. Findings highlight the ways in which participants negotiated visualization skills through (a) imagining, drawing, and seeing through creating 2-D sketches, (b) reasoning and relating through writing stories, (c) transforming through 3-D extrusion, (d) observing and noticing through 3-D sculpting and 3-D scanning, and (e) manipulating through digital 3-D modeling, mental rotation, and mental transformation. Implications for formal K–12 educational contexts and teacher preparation programs are discussed.
Parallel architecture for concatenated polar-CRC codes

This paper presents a parallel encoding and decoding method using concatenated polar-CRC codes to get high data throughput. Based on the proposed method, parallel architecture for concatenated polar-CRC codes is proposed. The proposed parallel concatenated polar-CRC decoding has better BER performance compared to conventional SC polar decoding without performance degradation in 3 dB SNR region.
ValenTO at SemEval-2018 Task 3: Exploring the Role of Affective Content for Detecting Irony in English Tweets

In this paper we describe the system used by the ValenTO team in the shared task on Irony Detection in English Tweets at SemEval 2018. The system takes as starting point emotIDM, an irony detection model that explores the use of affective features based on a wide range of lexical resources available for English, reflecting different facets of affect. We experimented with different settings, by exploiting different classifiers and features, and participated both to the binary irony detection task and to the task devoted to distinguish among different types of irony. We report on the results obtained by our system both in a constrained setting and unconstrained setting, where we explored the impact of using additional data in the training phase, such as corpora annotated for the presence of irony or sarcasm from the state of the art. Overall, the performance of our system seems to validate the important role that affective information has for identifying ironic content in Twitter.
Lough Neagh: the site of a Cenozoic pull-apart basin

Synopsis The Lough Neagh Basin in Northern Ireland is the site of a Cenozoic depocentre defined by gravity measurements and a thick succession of Paleocene basaltic lavas and Upper Oligocene clays. Much of the Cenozoic outcrop is concealed by Lough Neagh, but the rhombic outline of the lough provides some indication of the underlying structural control of the depocentre. Several authors have inferred that a Cenozoic pull-apart basin lies within the Lough Neagh area and suggest it is one of a number of transtensional basins, including the Bovey and Petrockstow basins in SW England, associated with NW to NNW-trending strike-slip fault zones. Solid geology maps and gravity data show that the structure of the Lough Neagh Basin is dominated by a segmented, orthogonal pattern of offset NNW and NE-trending faults. It is proposed that pull-apart basin formation took place in the Mid-Paleocene by dextral movement on these offset faults. The potential link between strike-slip tectonics and Cenozoic volcanism in the north of Ireland is briefly considered.
CitiusNLP at SemEval-2018 Task 10: The Use of Transparent Distributional Models and Salient Contexts to Discriminate Word Attributes

This article describes the unsupervised strategy submitted by the CitiusNLP team to the SemEval 2018 Task 10, a task which consists of predict whether a word is a discriminative attribute between two other words. Our strategy relies on the correspondence between discriminative attributes and relevant contexts of a word. More precisely, the method uses transparent distributional models to extract salient contexts of words which are identified as discriminative attributes. The system performance reaches about 70% accuracy when it is applied on the development dataset, but its accuracy goes down (63%) on the official test dataset.
Evolving strategies for the development and evaluation of a computerised melanoma image analysis system

AbstractThe rising incidence of melanoma has increased demand for early detection tools, which enable an objective decision and prevent the need for biopsies, the current gold standard in lesion diagnosis. In this study, we report the development of such a tool, a melanoma image analysis system (MIAS), designed to improve the standard of care and classify suspicious skin lesions as benign or malignant. In addition, our methodological approach to curate an image data-set (107 benign lesions and 94 melanomas) and subsequently divide into five balanced sets in order to create a quadratic discriminant analysis classifier, allowed us to determine the causes of weaknesses within our classifier. We identified the classifier’s weaknesses by analysing for which benign images the system failed and the reasons for being so. Further analysis also determined which benign categories were more difficult to classify and identified which features were useful for classification. Our classification system resulted in averag.
Non-Adherence to recommended Pap smear screening guidelines and its associated factors among women attending health clinic in Malaysia.

Introduction Cervical cancer ranks as the second most frequent cancer among women in Malaysia. Although a cervical screening program has been introduced since 1960s and is provided free of charge in all government health facilities, the coverage and adherence rate to recommendation among Malaysian women remains low. Objectives To determine the proportion of non-adherence to Pap smear screening guidelines and its associated factors among women attending a health clinic in Malaysia. Method A cross sectional study involving 316 women aged 20 to 65 years who had undergone a Pap smear. Universal sampling method was applied to select participants among women who attended the selected health clinic from January 2013 to May 2013. A self-administered questionnaire was used to obtain the socio-demographic characteristics, socio-health data and perceptions about cervical cancer and Pap smear screening. The data was analysed using descriptive statistics and multiple logistic regression. Result The proportion of non-adherence to Pap smear screening was 90.5%. Age, marital status, duration of marriage, education level, employment, household income and number of children were not significantly associated with non-adherence. Perceived severity, perceived susceptibility, perceived benefit, perceived barrier and cues to action did not show significant association with non-adherence to Pap smear screening. Conclusion Non-adherence to Pap smear screening was high among Malaysian women. Measures should be taken to increase Pap smear screening coverage in our country. Other factors beyond Health Belief Model that influence Pap smear screening practice among Malaysian women should be explored.
Bandwidth Slicing in Software-Defined 5G: A Stackelberg Game Approach

With the explosive development of mobile Internet and the emergence of multimedia-rich applications such as augmented reality, virtual reality, video streaming, online gaming, and social networks, the traffic demands in the incoming fifth-generation (5G) era could grow significantly. To accommodate this massive amount of data traffic, Internet service providers (ISPs) must deploy new infrastructures to expand the capacity of current networks, which results in high capital and maintenance costs. Furthermore, mobile Internet applications in 5G will have diverse quality-of-service (QoS) requirements in terms of latency, burst size, throughput, and packet arrival rate, and reliable QoS provisioning depends on efficient and on-demand resource allocation [1], [2]. However, it is difficult to realize intelligent resource allocation due to the coupling between service provisioning and the taskoriented hardware.
View From Outside the Viewing Sphere

The ‘viewing sphere’, as defined by Euclid and explored by Gibson as the ‘optic array’, is generally thought of as wrapped around the eye. Can an observer step out of it? With currently popular photographic techniques, the spectator is forced to, because the viewing sphere is presented as a pictorial object. Then the question is whether human observers are able to use such pictorial representations in an intuitive manner. Can the spectator ‘mentally step into the interior’ of the pictorial viewing sphere? We explore this issue in a short experiment. Perhaps unsurprisingly, because the eye cannot see itself, the short answer is no.
Highly Solvent Tolerance in Serratia marcescens IBBPo15

The aim of this study was to investigate the solvent tolerance mechanisms in Serratia marcescens strain IBBPo15 (KT315653). Serratia marcescens IBBPo15 exhibited remarkable solvent-tolerance, being able to survive in the presence of high concentrations (above 40%) of toxic organic solvents, such as cyclohexane, n-hexane, n-decane, toluene, styrene, and ethylbenzene. S. marcescens IBBPo15 produced extracellular protease and the enzyme production decreased in cells exposed to 5% cyclohexane, n-hexane, toluene, styrene, and ethylbenzene, as compared with the control and n-decane exposed cells. S. marcescens IBBPo15 cells produced carotenoid pigments and alteration of pigments profile (i.e., phytoene, lycopene) were observed in cells exposed to 5% cyclohexane, n-hexane, n-decane, toluene, styrene, and ethylbenzene. The exposure of S. marcescens IBBPo15 cells to 5% cyclohexane, n-hexane, n-decane, toluene, styrene, ethylbenzene induced also changes in the intracellular (e.g., 50 kDa protein) and extracellular (e.g., 39, 41, 43, 53, 110 kDa proteins) proteins profile. Significant RAPD, ARDRA, rep-PCR and PCR pattern modifications were not observed in DNA extracted from S. marcescens IBBPo15 cells exposed to 5% cyclohexane, n-hexane, n-decane, toluene, styrene, and ethylbenzene. Though only HAE1 and acrAB genes were detected in the genome of S. marcescens IBBPo15 cells, the unspecific amplification of other fragments being observed also when the primers for ompF and recA genes were used.
YNU Deep at SemEval-2018 Task 12: A BiLSTM Model with Neural Attention for Argument Reasoning Comprehension

This paper describes the system submitted to SemEval-2018 Task 12 (The Argument Reasoning Comprehension Task). Enabling a computer to understand a text so that it can answer comprehension questions is still a challenging goal of NLP. We propose a Bidirectional LSTM (BiLSTM) model that reads two sentences separated by a delimiter to determine which warrant is correct. We extend this model with a neural attention mechanism that encourages the model to make reasoning over the given claims and reasons. Officially released results show that our system ranks 6th among 22 submissions to this task.
Debris from terrestrial planet formation: the Moon-forming collision

We study the evolution of debris created in the giant impacts expected during the final stages of terrestrial planet formation. The starting point is the debris created in a simulation of the Moon-forming impact. The dynamical evolution is followed for 10 Myr including the effects of Earth, Venus, Mars and Jupiter. The spatial distribution evolves from a clump in the first few months to an asymmetric ring for the first 10 kyr and finally becoming an axisymmetric ring by about 1 Myr after the impact. By 10 Myr after the impact 20 per cent of the particles have been accreted on to Earth and 17 per cent on to Venus, with 8 per cent ejected by Jupiter and other bodies playing minor roles. However, the fate of the debris also depends strongly on how fast it is collisionally depleted, which depends on the poorly constrained size distribution of the impact debris. Assuming that the debris is made up of 30 per cent by mass mm–cm-sized vapour condensates and 70 per cent boulders up to 500 km, we find that the condensates deplete rapidly on ∼1000 yr time-scales, whereas the boulders deplete predominantly dynamically. By considering the luminosity of dust produced in collisions within the boulder–debris distribution we find that the Moon-forming impact would have been readily detectable around other stars in Spitzer 24 μm surveys for around 25 Myr after the impact, with levels of emission comparable to many known hot dust systems. The vapour condensates meanwhile produce a short-lived, optically thick, spike of emission. We use these surveys to make an estimate of the fraction of stars that form terrestrial planets, FTPF. Since current terrestrial planet formation models invoke multiple giant impacts, the low fraction of 10–100 Myr stars found to have warm (>rsim150 K) dust implies that per cent. For this number to be higher, it would require that either terrestrial planets are largely fully formed when the protoplanetary disc disperses, or that impact generated debris consists purely of sub-km objects such that its signature is short-lived.
Performance of Carbon Nano-Scale Allotropes in Detecting Midazolam and Paracetamol in Undiluted Human Serum

Nano-materials are highly exploited to enhance sensing performance of electrochemical electrodes by increasing the electro-active surface area (EASA). In this paper, an analytical calculation of the deposited EASA is presented and experimentally validated by comparing two kinds of nano-structured electrochemical sensors modified with multi-walled carbon nano-tubes (MWCNTs) and fullerenes. Further, the two differently nano-structured electrodes, prepared with equal optimum EASA, have been adopted as novel approach in the detection of paracetamol (APAP) and midazolam (MZ), two largely adopted and complementary sedative drugs. We have used the novel approach to let emerge the different nano-scale structures’ sensing performance at the same equivalent EASA. The analytical method for EASA calculation has been recently validated by our group on different nano-materials; hence the aim of the actual work is to present, for the first time, its efficient applicability also in comparing the performance of different allotropes of the same nature (carbon-based) in drug sensing, e.g., MZ and APAP. This paper also includes the comparison in undiluted human serum (HS), proposed here as complex bio-sample, to confirm the validity of our novel approach close to real applications. With respect to fullerenes, the MWCNTs-modified electrodes obtained the best limit of detection values in HS detection, as 0.3518 $\mu \text{M}$ and 0.5367 mm for APAP and MZ, respectively. Scanning electron microscopy analysis also confirmed the higher quality of MWCNTs-based surface in terms of homogeneity and denser coverage of the surface with respect to fullerene-based one, with a better-packed aggregate of assembled structures.
Unsupervised Rapid Flood Mapping Using Sentinel-1 GRD SAR Images

We present a new methodology for rapid flood mapping exploiting Sentinel-1 synthetic aperture radar data. In particular, we propose the usage of ground range detected (GRD) images, i.e., preprocessed products made available by the European Space Agency, which can be quickly treated for information extraction through simple and poorly demanding algorithms. The proposed framework is based on two processing levels providing event maps with increasing resolution. The first level exploits classic co-occurrence texture measures combined with amplitude information in a fuzzy classification system avoiding the critical step of thresholding. The second level consists of a change-detection approach applied to the full resolution GRD product. The discussion is supported by several experiments demonstrating the potentiality of the proposed methodology, which is particularly oriented toward the end-user community.
3D radiotherapy dose prediction on head and neck cancer patients with a hierarchically densely connected U-net deep learning architecture

The treatment planning process for patients with head and neck (H&N) cancer is regarded as one of the most complicated due to large target volume, multiple prescription dose levels, and many radiation-sensitive critical structures near the target. Treatment planning for this site requires a high level of human expertise and a tremendous amount of effort to produce personalized high quality plans, taking as long as a week, which deteriorates the chances of tumor control and patient survival. To solve this problem, we propose to investigate a deep learning-based dose prediction model, Hierarchically Densely Connected U-net, based on two highly popular network architectures: U-net and DenseNet. We find that this new architecture is able to accurately and efficiently predict the dose distribution, outperforming the other two models, the Standard U-net and DenseNet, in homogeneity, dose conformity, and dose coverage on the test data. Averaging across all organs at risk, our proposed model is capable of predicting the organ-at-risk max dose within 6.3% and mean dose within 5.1% of the prescription dose on the test data. The other models, the Standard U-net and DenseNet, performed worse, having an averaged organ-at-risk max dose prediction error of 8.2% and 9.3%, respectively, and averaged mean dose prediction error of 6.4% and 6.8%, respectively. In addition, our proposed model used 12 times less trainable parameters than the Standard U-net, and predicted the patient dose 4 times faster than DenseNet.
Profile of Polyphenolic and Essential Oil Composition of Polish Propolis, Black Poplar and Aspens Buds

In this work, we studied similarities and differences between 70% ethanol in water extract (70EE) and essential oils (EOs) obtained from propolis, black poplars (Populus nigra L.) and aspens (P. tremula L.) to ascertain which of these is a better indicator of the plant species used by bees to collect propolis precursors. Composition of 70EE was analyzed by UPLC-PDA-MS, while GC-MS was used to research the EOs. Principal component analyses (PCA) and calculations of Spearman’s coefficient rank were used for statistical analysis. Statistical analysis exhibited correlation between chemical compositions of propolis and Populus buds’ 70EE. In the case of EOs, results were less clear. Compositions of black poplars, aspens EOs and propolises have shown more variability than 70EE. Different factors such as higher instability of EOs compared to 70EE, different degradation pattern of benzyl esters to benzoic acid, differences in plant metabolism and bees’ preferences may be responsible for these phenomena. Our research has therefore shown that 70EE of propolis reflected the composition of P. nigra or complex aspen–black poplar origin.
Acceleration and evaluation of block-based motion estimation algorithms for x-ray fluoroscopy

This paper discusses acceleration methods for block-based motion estimation with the focus on the application to moving low-dose x-ray images (x-ray fluoroscopy). These images often exhibit a very low signal-to-noise ratio. If the frame rate is sufficiently high, these degradations can at least be partly compensated by temporally motion- compensated filtering, which requires first a motion estimation step. Due to the low signal-to-noise level and strong local motions standard algorithms are not suitable for application to fluoroscopy sequences. In an earlier work we developed a full search Bayesian block matching algorithm using spatial and temporal regularization. Based on the so-called Successive Elimination Algorithm by Li and Salari we developed several acceleration methods for the motion estimation step. Here, these methods and a detailed evaluation based on several synthetically generated motion types in fluoroscopy sequences are provided. Using a weighted block-norm based inequality, combined with an efficient calculation of the error measure which is partitioned into local measures, the number of search positions is remarkably reduced without significant loss in estimation quality.
ORIGINS OF REDUCTION IN EFFICIENCY IN MICROFLUIDIC PARTICLE SEPARATION

Microfluidic particle separation often gets degraded by defocusing of particles at high concentration due to hydrodynamic particle-particle interactions. We theoretically and experimentally studied the origins of these interactions; the reversing wake reflected from nearby channel walls is found to be the dominant interaction. In addition we present a unique mechanism for the dynamic self-assembly particles in finite-Reynolds number channel flow. Inertial lift forces and a parabolic flow field act together to stabilize interparticle spacings that otherwise would diverge to infinity due to viscous wakes.
Sensitivity of radiative forcing, ocean heat uptake, and climate feedback to changes in anthropogenic greenhouse gases and aerosols

We use both prescribed sea surface temperature and fully coupled versions of the Geophysical Fluid Dynamics Laboratory coupled climate model (CM3) to analyze the sensitivity of radiative forcing, ocean heat uptake, and climate feedback to changes in anthropogenic greenhouse gases and aerosols considered separately over the 1870 to 2005 period. The global anthropogenic aerosol climate feedback parameter (− α) of −1.13 ± 0.33 Wm−2 K−1 is indistinguishable from the greenhouse gas − α of −1.28 ± 0.23 Wm−2 K−1. However, this greenhouse gas climate feedback parameter is about 50% larger than that obtained for CM3 from a widely used linear extrapolation method of regressing Earth's top of atmosphere imbalance against surface air temperature change in idealized CO2 radiative forcing experiments. This implies that the global mean surface temperature change due to forcing over the 1870–2005 period is 50% smaller than that predicted using the climate feedback parameter obtained from idealized experiments. This difference results from time dependence in α, which makes the radiative forcing obtained by the fixed sea surface temperature method incompatible with that obtained by the linear extrapolation method fitted over the first 150 years after CO2 is quadrupled. On a regional scale, α varies greatly between the greenhouse gas and aerosol case. This suggests that the relationship between transient and equilibrium climate sensitivities obtained from idealized CO2 simulations, using techniques such as regional feedback analysis and heat uptake efficacy, may not hold for other forcing scenarios.