Channel and spatial attention mechanism for fashion image captioning

Image captioning aims to automatically generate one or more description sentences for a given input image. Most of the existing captioning methods use encoder-decoder model which mainly focus on recognizing and capturing the relationship between objects appearing in the input image. However, when generating captions for fashion images, it is important to not only describe the items and their relationships, but also mention attribute features of clothes (shape, texture, style, fabric, and more). In this study, one novel model is proposed for fashion image captioning task which can capture not only the items and their relationship, but also their attribute features. Two different attention mechanisms (spatial-attention and channel-wise attention) is incorporated to the traditional encoder-decoder model, which dynamically interprets the caption sentence in multi-layer feature map in addition to the depth dimension of the feature map. We evaluate our proposed architecture on Fashion-Gen using three different metrics (CIDEr, ROUGE-L, and BLEU-1), and achieve the scores of 89.7, 50.6 and 45.6, respectively. Based on experiments, our proposed method shows significant performance improvement for the task of fashion-image captioning, and outperforms other state-of-the-art image captioning methods

Designing a novel heterostructure AgInS₂@MIL-101(Cr) photocatalyst from PET plastic waste for tetracycline degradation

Semiconductor-containing porous materials with a well-defined structure could be unique scaffolds for carrying out selective organic transformations driven by visible light. We herein introduce for the first time a heterostructure of silver indium sulfide (AgInS(2)) ternary chalcogenide and a highly porous MIL-101(Cr) metal–organic framework (MOF) synthesised from polyethylene terephthalate plastic waste. Our results demonstrate that AgInS(2) nanoparticles were uniformly attached to each lattice plane of the octahedral MIL-101(Cr) structure, resulting in a nanocomposite with a high distribution of semiconductors in a porous media. We also demonstrate that the nanocomposite with up to 40% of AgInS(2) doping exhibited excellent catalytic activity for tetracycline degradation under visible light irradiation (∼99% tetracycline degraded after 4 h) and predominantly maintained its performance after five cycles. These results could promote a new material circularity pathway to develop new semiconductors that can be used to protect water from further pollution

Kinetics of Toehold-Mediated DNA Strand Displacement Depend on FeII4L4 Tetrahedron Concentration.

The toehold-mediated strand displacement reaction (SDR) is a powerful enzyme-free tool for molecular manipulation, DNA computing, signal amplification, etc. However, precise modulation of SDR kinetics without changing the original design remains a significant challenge. We introduce a new means of modulating SDR kinetics using an external stimulus: a water-soluble FeII4L4 tetrahedral cage. Our results show that the presence of a flexible phosphate group and a minimum toehold segment length are essential for FeII4L4 binding to DNA. SDRs mediated by toehold ends in different lengths (3-5) were investigated as a function of cage concentration. Their reaction rates all first increased and then decreased as cage concentration increased. We infer that cage binding on the toehold end slows SDR, whereas the stabilization of intermediates that contain two overhangs accelerates SDR. The tetrahedral cage thus serves as a versatile tool for modulation of SDR kinetics.George and Lilian Schiff Foundation Studentship; Winton Programme for the Physics of Sustainability; St. John’s Benefactors’ Scholarshi

Detection of lithium in nearby young late-M dwarfs

Late M-type dwarfs in the solar neighborhood include a mixture of very low-mass stars and brown dwarfs which is difficult to disentangle due to the lack of constraints on their age such as trigonometric parallax, lithium detection and space velocity. We search for young brown dwarf candidates among a sample of 28 nearby late-M dwarfs with spectral types between M5.0 and M9.0, and we also search for debris disks around three of them. Based on theoretical models, we used the color $I-J$, the $J$-band absolute magnitude and the detection of the Li I 6708 $\AA$ doublet line as a strong constraint to estimate masses and ages of our targets. For the search of debris disks, we observed three targets at submillimeter wavelength of 850 $\mu$m. We report here the first clear detections of lithium absorption in four targets and a marginal detection in one target. Our mass estimates indicate that two of them are young brown dwarfs, two are young brown dwarf candidates and one is a young very low-mass star. The closest young field brown dwarf in our sample at only $\sim$15 pc is an excellent benchmark for further studying physical properties of brown dwarfs in the range 100$-$150 Myr. We did not detect any debris disks around three late-M dwarfs, and we estimated upper limits to the dust mass of debris disks around them.Comment: 10 pages, 5 figures, accepted for publication in Astronomy and Astrophysic

Multichannel Photon Counting Lidar Measurements Using USB-based Digital Storage Oscilloscope

We present a simple method of making multichannel photon counting measurements of weak lidar signal from large ranges, using commonly available USB-based digital storage oscilloscopes. The single photon pulses from compact photomultiplier tubes are amplified and stretched so that the pulses are large and broad enough to be sampled efficiently by the USB oscilloscopes. A software interface written in Labview is then used to count the number of photon pulses in each of the prescribed time bins to form the histogram of LIDAR signal. This method presents a flexible alternative to the modular multichannel scalers and facilitate the development of sensitive lidar systems

Component-based reduced basis for parametrized symmetric eigenproblems

Background: A component-based approach is introduced for fast and flexible solution of parameter-dependent symmetric eigenproblems. Methods: Considering a generalized eigenproblem with symmetric stiffness and mass operators, we start by introducing a “ σ-shifted” eigenproblem where the left hand side operator corresponds to an equilibrium between the stiffness operator and a weighted mass operator, with weight-parameter σ>0. Assuming that σ=λ n >0, the nth real positive eigenvalue of the original eigenproblem, then the shifted eigenproblem reduces to the solution of a homogeneous linear problem. In this context, we can apply the static condensation reduced basis element (SCRBE) method, a domain synthesis approach with reduced basis (RB) approximation at the intradomain level to populate a Schur complement at the interdomain level. In the Offline stage, for a library of archetype subdomains we train RB spaces for a family of linear problems; these linear problems correspond to various equilibriums between the stiffness operator and the weighted mass operator. In the Online stage we assemble instantiated subdomains and perform static condensation to obtain the “ σ-shifted” eigenproblem for the full system. We then perform a direct search to find the values of σ that yield singular systems, corresponding to the eigenvalues of the original eigenproblem. Results: We provide eigenvalue a posteriori error estimators and we present various numerical results to demonstrate the accuracy, flexibility and computational efficiency of our approach. Conclusions: We are able to obtain large speed and memory improvements compared to a classical Finite Element Method (FEM), making our method very suitable for large models commonly considered in an engineering context.United States. Air Force Office of Scientific Research (OSD/AFOSR/MURI Grant FA9550-09-1-0613)United States. Office of Naval Research (ONR Grant N00014-11-1-0713)Deshpande Center for Technological Innovation (grant)Switzerland. Commission for Technology and Innovation (CTI

Carbon nanotube four-terminal devices for pressure sensing applications

Carbon nanotubes (CNTs) are of high interest for sensing applications,owing to their superior mechanical strength, high Young’s modulus and low density. In this work, we report on a facile approach for the fabrication of carbon nanotube devices using a four terminal configuration. Oriented carbon nanotube films were pulled out from a CNT forest wafer and then twisted into a yarn. Both the CNT film and yarn were arranged on elastomer membranes/diaphragms which were arranged on a laser cut acrylic frame to form pressure sensors. The sensors were calibrated using a precisely controlled pressure system, showing a large change of the output voltage of approximately 50 mV at a constant supply current of 100 μA and under a low applied pressure of 15 mbar. The results indicate the high potential of using CNT films and yarns for pressure sensing applications

Mapping for engagement: setting up a community based participatory research project to reach underserved communities at risk for Hepatitis C in Ho Chi Minh City, Vietnam

Background: Approximately 1. 07 million people in Vietnam are infected with hepatitis C virus (HCV). To address this epidemic, the South East Asian Research Collaborative in Hepatitis (SEARCH) launched a 600-patient cohort study and two clinical trials, both investigating shortened treatment strategies for chronic HCV infection with direct-acting antiviral drugs. We conducted ethnographic research with a subset of trial participants and found that the majority were aware of HCV infection and its implications and were motivated to seek treatment. However, people who inject drugs (PWID), and other groups at risk for HCV were under-represented, although injecting drug use is associated with high rates of HCV. Material and Methods: We designed a community-based participatory research (CBPR) study to engage in dialogues surrounding HCV and other community-prioritized health issues with underserved groups at risk for HCV in Ho Chi Minh City. The project consists of three phases: situation analysis, CBPR implementation, and dissemination. In this paper, we describe the results of the first phase (i.e., the situation analysis) in which we conducted desk research and organized stakeholder mapping meetings with representatives from local non-government and community-based organizations where we used participatory research methods to identify and analyze key stakeholders working with underserved populations. Results: Twenty six institutions or groups working with the key underserved populations were identified. Insights about the challenges and dynamics of underserved communities were also gathered. Two working groups made up of representatives from the NGO and CBO level were formed. Discussion: Using the information provided by local key stakeholders to shape the project has helped us to build solid relationships, give the groups a sense of ownership from the early stages, and made the project more context specific. These steps are not only important preliminary steps for participatory studies but also for other research that takes place within the communities

Noise and nonlinearities in high-throughput data

High-throughput data analyses are becoming common in biology, communications, economics and sociology. The vast amounts of data are usually represented in the form of matrices and can be considered as knowledge networks. Spectra-based approaches have proved useful in extracting hidden information within such networks and for estimating missing data, but these methods are based essentially on linear assumptions. The physical models of matching, when applicable, often suggest non-linear mechanisms, that may sometimes be identified as noise. The use of non-linear models in data analysis, however, may require the introduction of many parameters, which lowers the statistical weight of the model. According to the quality of data, a simpler linear analysis may be more convenient than more complex approaches. In this paper, we show how a simple non-parametric Bayesian model may be used to explore the role of non-linearities and noise in synthetic and experimental data sets.Comment: 12 pages, 3 figure