Miracle-dz/UniFAR-FTUs huggingface dataset:
X-GANs: Image Reconstruction Made Easy for Extreme Cases

Image reconstruction including image restoration and denoising is a challenging problem in the field of image computing. We present a new method, called X-GANs, for reconstruction of arbitrary corrupted resource based on a variant of conditional generative adversarial networks (conditional GANs). In our method, a novel generator and multi-scale discriminators are proposed, as well as the combined adversarial losses, which integrate a VGG perceptual loss, an adversarial perceptual loss, and an elaborate corresponding point loss together based on the analysis of image feature. Our conditional GANs have enabled a variety of applications in image reconstruction, including image denoising, image restoration from quite a sparse sampling, image inpainting, image recovery from the severely polluted block or even color-noise dominated images, which are extreme cases and haven't been addressed in the status quo. We have significantly improved the accuracy and quality of image reconstruction. Extensive perceptual experiments on datasets ranging from human faces to natural scenes demonstrate that images reconstructed by the presented approach are considerably more realistic than alternative work. Our method can also be extended to handle high-ratio image compression.
First-principles calculations of structural, electronic, magnetic and elastic properties of Mo2FeB2 under high pressure

The structural, electronic, magnetic and elastic properties of Mo2FeB2 under high pressure have been investigated with first-principles calculations. Furthermore, the thermal dynamic properties of Mo2FeB2 were also studied with the quasi-harmonic Debye model. The volume of Mo2FeB2 decreases with the increase in pressure. Using the analysis of the density of the states, atom population and Mulliken overlap population, it is observed that as the pressure increases, the B–B bonds are strengthened and the B–Mo covalency decreases. Moreover, for all pressures, Mo2FeB2 is detected in the anti-ferromagnetic phase and the magnetic moments decrease with the increase in pressure. The calculated bulk modulus, shear modulus, Young's modulus, Poisson's ratio and universal anisotropy index all increase with the increase in pressure. From thermal expansion coefficient analysis, it is found that Mo2FeB2 shows good volume invariance under high pressure and temperature. The examination of the dependence of heat capacity on the temperature and pressure shows that heat capacity is more sensitive to temperature than to pressure.
Using Microservices for Rapid Creation of Remote Sensing Products

Driven by the demands of various sensing data products, remote sensing software systems have increasingly been developed and applied to a wide range of fields. Due to the legacy monolithic product line, we used to satisfy the requirements on a project-by-project basis, only with reuse of some fundamental source codes and tools. By employing microservices to refactor our product line, we are now able to follow a divide-and-conquer strategy to maximize the reusability of component business capacities and create satellite remote sensing products at a much faster pace. This paper mainly introduces our microservice-oriented product line, and the data-analytics-visualization (DAV) pattern for logically organizing and managing relevant microservices of different products. In particular, two projects (namely archaeological detection and cultural heritage protection & urban planning and land use) are used to demonstrate how we prevent to develop thematic products from scratch.
Exploring patients’ and healthcare professionals’ experiences of patient‐witnessed resuscitation: A qualitative study protocol

AIM The aim of this study was to explore the experiences of patients and healthcare professionals regarding patients witnessing resuscitation on another patient in hospital clinical wards. DESIGN Phenomenological qualitative study. METHODS Participants will be recruited from nine wards in a university hospital in England. Data collection will include two in-depth interviews with patients who witnessed resuscitation: the first interview one week after witnessing resuscitation and the second interview after one month. Individual and focus group interviews with healthcare professionals will be also conducted. Data will be transcribed, managed in NVivo 11 and analysed using phenomenological analysis. The National Health Service, Health Research Authority and University Ethics Committee approved the study (May 2018). The study is funded by Resuscitation Council UK (December 2017) and will be conducted between May 2018-March 2019. CONCLUSION While witnessed resuscitation is a major topic of interest in nursing, specific research on the impact of patients who witness resuscitation on fellow patients is limited. This study will use qualitative methodology to inform the evidence base of a clinical problem with limited understanding. The findings of this study will contribute to the framework of witnessed resuscitation and to identifying the barriers and enablers towards a greater support of patients who witness resuscitation in hospital. This new acquired knowledge will be beneficial to the improvement of future nursing care. IMPACT The evidence gained from this study can support the development and implementation of guidelines and inform hospital policies to support patients witnessing resuscitation to optimize the quality of nursing care provided.
Initial Rotor Position Estimation of Single-phase Permanent Magnet Synchronous Motor with Asymmetric Air-gap

This paper presents an initial rotor position estimation algorithm of asymmetric air-gap single-phase permanent magnet synchronous motors without using a hall sensor. Generally, the common problem associated with the sensorless drive is the starting operation. Most sensorless control methods are based on back-EMF. However, when motor is at standstill or low speed, the back-EMF is too small to detect rotor position. Therefore, high frequency injection methods are widely used in the standstill or low speed region. In case of the SP-PMSM, when high frequency signal is injected to asymmetric air-gap single-phase PMSM motors, flux saturation is not occurred at air gap unlike 3-phase PMSM. Due to alternating magnetic field at the air-gap, initial rotor position of the SP-PMSM is hard to be estimated. As a result, in this paper, DC offset voltage is added to the high frequency injection signal to generate flux saturation at the air-gap of the SP-PMSM. The several experimental results show that the proposed algorithm is effectiveness and usefulness for SP-PMSM with non-uniform air-gap.
Genetic Analysis of Floral Symmetry Transition in African Violet Suggests the Involvement of Trans-acting Factor for CYCLOIDEA Expression Shifts

With the growing demand for its ornamental uses, the African violet (Saintpaulia ionantha) has been popular owing to its variations in color, shape and its rapid responses to artificial selection. Wild type African violet (WT) is characterized by flowers with bilateral symmetry yet reversals showing radially symmetrical flowers such as dorsalized actinomorphic (DA) and ventralized actinomorphic (VA) peloria are common. Genetic crosses among WT, DA, and VA revealed that these floral symmetry transitions are likely to be controlled by three alleles at a single locus in which the levels of dominance are in a hierarchical fashion. To investigate whether the floral symmetry gene was responsible for these reversals, orthologs of CYCLOIDEA (CYC) were isolated and their expressions correlated to floral symmetry transitions. Quantitative RT-PCR and in situ results indicated that dorsal-specific SiCYC1s expression in WT S. ionantha (SCYC1A and SiCYC1B) shifted in DA with a heterotopically extended expression to all petals, but in VA, SiCYC1s' dorsally specific expressions were greatly reduced. Selection signature analysis revealed that the major high-expressed copy of SCYC1A had been constrained under purifying selection, whereas the low-expressed helper SiCYC1B appeared to be relaxed under purifying selection after the duplication into SCYC1A and SiCYC1B. Heterologous expression of SCYC1A in Arabdiopsis showed petal growth retardation which was attributed to limited cell proliferation. While expression shifts of SCYC1A and SiCYC1B correlate perfectly to the resulting symmetry phenotype transitions in F1s of WT and DA, there is no certain allelic combination of inherited SiCYC1s associated with specific symmetry phenotypes. This floral transition indicates that although the expression shifts of SCYC1A/1B are responsible for the two contrasting actinomorphic reversals in African violet, they are likely to be controlled by upstream trans-acting factors or epigenetic regulations.
Controller Design for Takagi-Sugeno Fuzzy Systems with Nonlinear Consequent Part Via Sampled-Data Measurements

This paper investigates the controller design problem for a class of nonlinear systems by introducing a Takagi-Sugeno system with nonlinear consequent parts. In this regard, it is assumed that the measured variables are available at discrete-time instants with non-periodic sampling time. Using the Lyapunov-Krasovskii stability theory, some conditions are presented and expressed in the form of linear matrix inequalities such that the closed-loop system is asymptotically stable and achieves a prescribed H~ performance level. Finally, a numerical examples is provided to illustrate the effectiveness of the proposed method.
Polymer Optical Fiber Sensors in Wearable Devices: Toward Novel Instrumentation Approaches for Gait Assistance Devices

This paper presents the application of polymer optical fiber (POF) sensors in wearable devices for gait assistance. Intensity variation-based POF curvature sensor for the acquisition of joint angles and a POF insole based to detect gait events were developed. Three wearable devices were employed for the practical validation of the developed sensors: an active orthosis with one degree of freedom, a robotic exoskeleton, and a functional electrical stimulation (FES) system for gait assistance. POF is a viscoelastic material, which does not have a constant response to stress or strain and also can present hysteresis in dynamic measurements. In order to mitigate these effects, a compensation technique based on the polymer viscoelastic features was applied on both the curvature sensor and the instrumented insole. The results obtained for the POF curvature sensor on the knee joint angle measurement of the orthosis and the exoskeleton show root mean squared error of 3.7° and 3.8°, respectively. Regarding the POF insole results, it was used to identify five gait events in the FES system application. The reported results pave the way for new instrumentation approaches in wearable devices with flexible sensors that can be especially desirable in the rigid robots presented but also in soft robotics applications.
Resistance and possibility: Rethinking the concept of subject access from queer theoretical perspectives

This session will use queer theory to raise important questions about the role of information science in relation to queer communities. Using examples taken from both literary and popular culture, the session will look at the practices of classification in information systems, and how those practices, even when they attempt to facilitate access to resources for LGBTQ communities, ignore disjunctions and distortions that, far from being a barrier to access, form a fundamental aspect of queer expression.
Step Length Estimation Methods Based on Inertial Sensors: A Review

Inertial sensors are included in most of the current smart devices and many researchers have identified their ability to be used for analyzing different parameters of human behavior. Among them, the pedestrian’s step length provides very useful information for different applications, such as pedestrian dead reckoning positioning or gait analysis. During the last three decades, many step length estimation methods using inertial sensors have been proposed; however, there is no specific review work that reflects the current state of the art. In this paper, we will conduct a systematic and complete review that covers the whole workflow of tasks involved in the design, test, and evaluation of step length estimation methods based on inertial sensors. The main conclusion drawn from this review is that the lack of public data sets and standard methodologies to guide testing and evaluation makes it difficult to compare the different methods in a fair and robust way. Some reflections on how to move forward on this direction have been presented.
A topological characterization of Gauss codes

A (smooth) embedding of a closed curve on the plane with finitely many intersections is said to be generic if each point of self-intersection is crossed exactly twice and at non-tangent angles. A finite word $\omega$ where each character occurs twice is a Gauss code if it can be obtained as the sequence of traversed self-intersections of a generic plane embedding of a close curved $\gamma$. Then $\gamma$ is said to realize $\omega$. We present a characterization of Gauss codes using Seifert cycles. The characterization is given by an algorithm that, given a Gauss code $\omega$ as input, it outputs a combinatorial plane embedding of closed curve in linear time with respect to the number of characters of the word. The algorithm allows to find all the (combinatorial) embeddings of a closed curve in the plane that realize $\omega$. The characterization involve two functions between graphs embedded on orientable surfaces, invertible of each other. One produces an embedding of the Seifert graph of the word (or paragraph), and the other is its inverse operation. These operations might be of independent interest.
Optimal Deterministic Extractors for Generalized Santha-Vazirani Sources

Let F be a finite alphabet and D be a finite set of distributions over F . A Generalized SanthaVazirani (GSV) source of type (F ,D), introduced by Beigi, Etesami and Gohari (ICALP 2015, SICOMP 2017), is a random sequence (F1, . . . , Fn) in F, where Fi is a sample from some distribution d ∈ D whose choice may depend on F1, . , Fi−1. We show that all GSV source types (F ,D) fall into one of three categories: (1) non-extractable; (2) extractable with error n−Θ(1); (3) extractable with error 2−Ω(n). We provide essentially randomness-optimal extraction algorithms for extractable sources. Our algorithm for category (2) sources extracts one bit with error ε from n = poly(1/ε) samples in time linear in n. Our algorithm for category (3) sources extracts m bits with error ε from n = O(m+ log 1/ε) samples in time min{O(m2 · n), nO(|F|)}. We also give algorithms for classifying a GSV source type (F ,D): Membership in category (1) can be decided in NP, while membership in category (3) is polynomial-time decidable. 2012 ACM Subject Classification Theory of computation → Expander graphs and randomness extractors, Mathematics of computing → Probability and statistics, Mathematics of computing → Information theory
Unmasking cryptic biodiversity in polyploids: origin and diversification of Aster amellus aggregate

Background and Aims The origin of different cytotypes by autopolyploidy may be an important mechanism in plant diversification. Although cryptic autopolyploids probably comprise the largest fraction of overlooked plant diversity, our knowledge of their origin and evolution is still rather limited. Here we study the presumed autopolyploid aggregate of Aster amellus, which encompasses diploid and hexaploid cytotypes. Although the cytotypes of A. amellus are not morphologically distinguishable, previous studies showed spatial segregation and limited gene flow between them, which could result in different evolutionary trajectories for each cytotype. Methods We combine macroevolutionary, microevolutionary and niche modelling tools to disentangle the origin and the demographic history of the cytotypes, using chloroplast and nuclear markers in a dense population sampling in central Europe. Key Results Our results revealed a segregation between diploid and hexaploid cytotypes in the nuclear genome, where each cytotype represents a monophyletic lineage probably homogenized by concerted evolution. In contrast, the chloroplast genome showed intermixed connections between the cytotypes, which may correspond to shared ancestral relationships. Phylogeny, demographic analyses and ecological niche modelling supported an ongoing differentiation of the cytotypes, where the hexaploid cytotype is experiencing a demographic expansion and niche differentiation with respect to its diploid relative. Conclusions The two cytotypes may be considered as two different lineages at the onset of their evolutionary diversification. Polyploidization led to the occurrence of hexaploids, which expanded and changed their ecological niche.
Texture-oriented image denoising technique for the removal of random-valued impulse noise

Abstract. An iterative texture-oriented image denoising technique is proposed for the restoration of images corrupted with random-valued impulse noise (RVIN). The proposed technique opts a switching approach that first identifies the pixels corrupted by RVIN and then estimates their intensity values to restore the images. Textons of distinct orientations conforming to bilateral symmetry are proposed for the identification of corrupted pixels. To estimate the intensity values of the identified corrupted pixels, the textons having local similarity are used. As the textons are fundamental elements of texture perception, the proposed technique preserves the texture information of images, effectively. The performance of the proposed denoising technique is evaluated on standard benchmark test images under various intensities of RVIN by comparing it with state-of-the-art techniques. The simulation results depict the significant performance of the proposed denoising technique for low as well as higher intensities of RVIN.
Automatic Data Acquisition with Robots for Indoor Fingerprinting

This paper addresses the problem of automatic data collection for the purpose of indoor positioning via Received Signal Strength (RSS) fingerprinting. A robotic platform with basic odometer sensors was used in an university building to automate the process of data acquisition which becomes particularly time consuming when considering mapping of large spaces such as shopping malls or hospitals. More than 3000 observations were collected. We associated for each observation their two dimensional coordinates with the received MAC RSS vector. Preprocessing methods included data augmentation and feature normalization. We searched for multiple models and one of the best performance was achieved by using neural networks and post-filtering.
An Approach to Measure and Improve the Cognitive Capability of ADHD Affected Children Through EEG Signals

Attention Deficit Hyperactivity disorder (ADHD) is a common mental disorder that begins in childhood and can continue through adolescence and adulthood. It makes it hard for a child to focus and pay attention. The present work is mainly designed to predict the probable region of brain that shows abnormality due to ADHD syndrome. EEG data of non – ADHD and ADHD study participants of age group 4-17 years has been collected following a protocol which contains 4 events. Eyes close, Eyes open, Visual Cue and Motor activity. Single map analysis and Frequency map analysis is performed. Comparative analysis is carried out between the non – ADHD and ADHD paricipants.3-D plotting of the EEG signals is performed for ease of visualization. Neural network algorithm is used to distinguish between non – ADHD and ADHD participants for the same task performed. Higher power and higher standard deviation is found in the ADHD patients when eyes closed, eyes open and in motor activity, which is an indication of hyper active nature. However, in the non – ADHD participants, all the parameters show significantly lower values. The proposed work can be used for assessment of learning capability of ADHD affected children and based on which, new methodology or techniques of teaching can be adopted to enhance their learning capability.
Model Driven Approach for Virtual Lab Authoring - Chemical Sciences Labs

Virtual Labs allow performance of experiments without real world instrumentation needs. Most of these virtual experiments are simulation based and developed using proprietary or Open Source simulation, Adobe Flash, and other client side software. The procedural steps involved in conducting these experiments are hardwired and require software modification for enhancements or alignment to the course structure. We propose a model based approach that eases development of virtual experiments without dependency on software programmers for any changes. We demonstrate our model driven based approach on Chemical Sciences labs of Virtual Labs, a Government of India initiative. With our model driven based approach, the effort for new experiment development or FOSS conversion of existing experiments that were using outdated technologies is less than a person day as compared to more than a person month.
Clinical profile and treatment outcomes of metastatic neuroendocrine carcinoma: A single institution experience

Abstract Background: Neuroendocrine carcinoma (NEC) is a rare tumor arising from the diffuse neuroendocrine system. Most of these present in the advanced stage and palliative chemotherapy remains the only option. The prognosis remains poor with the standard chemotherapy regimen of platinum and etoposide (EP) providing modest survival benefit. Methods: The study was done for 3 years at a tertiary cancer center in South India. Patients with a diagnosis of metastatic NEC were analyzed for clinical and pathological characteristics. The treatment outcomes and prognostic factors were evaluated using appropriate statistical test. Results: A total of 114 patients of metastatic NEC satisfied the inclusion criteria and were analyzed. Gastrointestinal including hepatobiliary tract (33%) was the most common site of primary disease followed by lung (26%), genitourinary (15%), head and neck (14%), and unknown primary (9%). On analysis of pattern of metastasis, liver (65%) was the most common site followed by bone (54%) and lung (42%). The median overall survival was 11 months with a statistically significant difference between pulmonary and extrapulmonary disease (8 vs. 13 months; P = 0.003). Ki67% value was strongly associated with prognosis (hazard ratio 0.517, 95% confidence interval; 0.318–0.840, P = 0.008) whereas age, sex, and lactate dehydrogenase level did not show any relation with survival. Conclusion: The outcome of advanced NEC with standard chemotherapy remains poor. Larger studies with other therapeutic and novel agents are warranted to improve the treatment outcomes.
A Demand-Supply Oriented Taxi Recommendation System for Vehicular Social Networks

To realize the construction of intelligent transportation system, data mining based on large-scale taxi traces has become a hot research topic. A crucial direction for analyzing taxi GPS data set is to recommend cruising areas for taxi drivers. Most of the existing researches merely concentrate on how to maximize drivers’ profits while overlooking the benefit of passengers. Such imbalance makes the existing solutions do not work well in a real-world environment. In this paper, we construct a recommendation system by jointly considering the profits of both drivers and passengers. Specifically, we first investigate the real-time demand-supply level for taxis and then make an adaptive tradeoff between the utilities of drivers and passengers for different hotspots. At last, the qualified candidates are recommended to drivers based on the analysis results. Simulation results indicate that the constructed recommendation system can achieve a remarkable improvement on the global utility and make equilibrium between the utilities of drivers and passengers, simultaneously.