LLukas22/scidocs huggingface dataset:
Improving Consistency and Correctness of Sequence Inpainting using Semantically Guided Generative Adversarial Network

Contemporary benchmark methods for image inpainting are based on deep generative models and specifically leverage adversarial loss for yielding realistic reconstructions. However, these models cannot be directly applied on image/video sequences because of an intrinsic drawbackthe reconstructions might be independently realistic, but, when visualized as a sequence, often lacks fidelity to the original uncorrupted sequence. The fundamental reason is that these methods try to find the best matching latent space representation near to natural image manifold without any explicit distance based loss. In this paper, we present a semantically conditioned Generative Adversarial Network (GAN) for sequence inpainting. The conditional information constrains the GAN to map a latent representation to a point in image manifold respecting the underlying pose and semantics of the scene. To the best of our knowledge, this is the first work which simultaneously addresses consistency and correctness of generative model based inpainting. We show that our generative model learns to disentangle pose and appearance information; this independence is exploited by our model to generate highly consistent reconstructions. The conditional information also aids the generator network in GAN to produce sharper images compared to the original GAN formulation. This helps in achieving more appealing inpainting performance. Though generic, our algorithm was targeted for inpainting on faces. When applied on CelebA and Youtube Faces datasets, the proposed method results in significant improvement over the current benchmark, both in terms of quantitative evaluation (Peak Signal to Noise Ratio) and human visual scoring over diversified combinations of resolutions and deformations. Figure 1. Exemplary success of our model in simultaneously preserving facial semantics(appearance and expressions) and improving inpaiting quality. Benchmark generative models such as DIP [49] are agnostic to holistic facial semantics and thus generate independently realistic, yet structurally inconsistent solutions.
Millimetre-Wave Backhaul for 5G Networks: Challenges and Solutions

The trend for dense deployment in future 5G mobile communication networks makes current wired backhaul infeasible owing to the high cost. Millimetre-wave (mm-wave) communication, a promising technique with the capability of providing a multi-gigabit transmission rate, offers a flexible and cost-effective candidate for 5G backhauling. By exploiting highly directional antennas, it becomes practical to cope with explosive traffic demands and to deal with interference problems. Several advancements in physical layer technology, such as hybrid beamforming and full duplexing, bring new challenges and opportunities for mm-wave backhaul. This article introduces a design framework for 5G mm-wave backhaul, including routing, spatial reuse scheduling and physical layer techniques. The associated optimization model, open problems and potential solutions are discussed to fully exploit the throughput gain of the backhaul network. Extensive simulations are conducted to verify the potential benefits of the proposed method for the 5G mm-wave backhaul design.
Early Detection of Students at Risk – Predicting Student Dropouts Using Administrative Student Data and Machine Learning Methods

Suggested Citation: Berens, Johannes; Oster, Simon; Schneider, Kerstin; Burghoff, Julian (2018) : Early Detection of Students at Risk Predicting Student Dropouts Using Administrative Student Data and Machine Learning Methods, Schumpeter Discussion Papers, No. 2018-006, University of Wuppertal, Schumpeter School of Business and Economics, Wuppertal, http://nbn-resolving.de/urn:nbn:de:hbz:468-20180719-085420-5
Classification of time series by shapelet transformation

Time-series classification (TSC) problems present a specific challenge for classification algorithms: how to measure similarity between series. A shapelet is a time-series subsequence that allows for TSC based on local, phase-independent similarity in shape. Shapelet-based classification uses the similarity between a shapelet and a series as a discriminatory feature. One benefit of the shapelet approach is that shapelets are comprehensible, and can offer insight into the problem domain. The original shapelet-based classifier embeds the shapelet-discovery algorithm in a decision tree, and uses information gain to assess the quality of candidates, finding a new shapelet at each node of the tree through an enumerative search. Subsequent research has focused mainly on techniques to speed up the search. We examine how best to use the shapelet primitive to construct classifiers. We propose a single-scan shapelet algorithm that finds the best $$k$$ k shapelets, which are used to produce a transformed dataset, where each of the $$k$$ k features represent the distance between a time series and a shapelet. The primary advantages over the embedded approach are that the transformed data can be used in conjunction with any classifier, and that there is no recursive search for shapelets. We demonstrate that the transformed data, in conjunction with more complex classifiers, gives greater accuracy than the embedded shapelet tree. We also evaluate three similarity measures that produce equivalent results to information gain in less time. Finally, we show that by conducting post-transform clustering of shapelets, we can enhance the interpretability of the transformed data. We conduct our experiments on 29 datasets: 17 from the UCR repository, and 12 we provide ourselves.
Human Re-identification through Distance Metric Learning based on Jensen-Shannon Kernel

Human re-identification, i. e., human identification across cameras without an overlapping view, has important applications in video surveillance. The problem is very challenging due to color and illumination variations among cameras as well as the pose variations of people. Assuming that the color of human clothing does not change quickly, previous work relied on color histogram matching of clothing. However, naive color histogram matching across camera network is not robust enough for human re-identification. Therefore, we learned an optimal distance metric between color histograms using a training dataset. The Jensen-Shannon kernel is proposed to learn nonlinear distance metrics. The effectiveness of the proposed method is validated by experimental results.
Hyaluronic acid-based nanocomposite hydrogels for ocular drug delivery applications.

Hyaluronic acid (HA) is a widely investigated biomaterial for many therapeutic applications owing to its unique properties of biocompatibility, biodegradation, and viscoelasticity. HA being a natural component of eye tissue with significant role in wound healing is a natural choice as a carrier for ocular drug delivery, provided the incorporated drugs are released in a sustained manner. However, localized sustained release of drugs inside eye has been difficult to achieve because of the inability to retain carriers for long periods in the eye. Using noncrosslinked (soluble) HA offers limited control over site retention of drugs. In order to obtain prolonged sustained delivery, two HA-based composite hydrogels incorporating nanocarriers, have been synthesized and characterized for swelling, rheology, degradation, and in vitro release of latanoprost, a drug used to reduce intraocular pressure. The HA is first chemically modified, mixed with drug-loaded liposomes, and then crosslinked to obtain nanocomposite hydrogels. In vitro release study shows longer sustained release of latanoprost from composite hydrogels as compared to liposomes or hydrogels alone indicating additional resistance to drug diffusion because of the incorporation of liposomes inside the hydrogels. It is believed that these nanocomposite hydrogels, with controlled degradation properties and sustained release, could serve as potential drug delivery systems for many ocular diseases.
Dual-Band Multi-Pole Directional Filter for Microwave Multiplexing Applications

A novel microstrip directional filter for multiplexing applications is presented. This device uses composite right-left-handed transmission lines and resonators to achieve dual-band frequency response. In addition, by cascading two or more stages using dual frequency immitance inverters, multi-pole configurations can be obtained. Simulation and experimental results are presented with good agreement.
Phase I dose-escalating study of SU11654, a small molecule receptor tyrosine kinase inhibitor, in dogs with spontaneous malignancies.

PURPOSE
The purpose of the following study was to investigate the safety and efficacy of the novel multitargeted indolinone receptor tyrosine kinase (RTK) inhibitor, SU11654, using a canine model of spontaneous tumors. This p.o. bioavailable compound exhibits potent inhibitory activity against members of the split kinase family of RTKs, including vascular endothelial growth factor receptor, platelet-derived growth factor receptor, Kit, and Flt-3, resulting in both direct antitumor and antiangiogenic activity.


EXPERIMENTAL DESIGN
This was a Phase I trial in which successive cohorts of dogs with spontaneous tumors that had failed standard treatment regimens received escalating doses of SU11654 as oral therapy. Pharmacokinetics, toxicity, and tumor response were assessed.


RESULTS
Fifty-seven dogs with a variety of cancers were enrolled; of these, 10 experienced progressive disease within the first 3 weeks. Measurable objective responses were observed in 16 dogs (including 6 complete responses), primarily in mast cell tumors (n = 11), mixed mammary carcinomas (n = 2), soft tissue sarcomas (n = 2), and multiple myeloma (n = 1), for an overall response rate of 28% (16 of 57). Stable disease of sufficient duration to be considered clinically meaningful (>10 weeks) was seen in an additional 15 dogs, for a resultant overall biological activity of 54% (31 of 57).


CONCLUSIONS
This study provides the first evidence that p.o. administered kinase inhibitors can exhibit activity against a variety of spontaneous malignancies. Given the similarities of canine and human cancers with regard to tumor biology and the presence of analogous RTK dysregulation, it is likely that such agents will demonstrate comparable antineoplastic activity in people.
Vocal masculinity is a robust dominance signal in men

Dominance assessment is important in mating competition across a variety of species, but little is known about how individuals’ own quality affects their assessment of potential rivals. We conducted two studies to test whether men’s own dominance affects their attentiveness to a putative dominance signal, vocal masculinity, when assessing competitors. Study I examined dominance ratings made by men in relation to their self-rated physical dominance. Study II examined dominance ratings made by men in relation to objective measures of their physical dominance, including size, strength, testosterone, and physical aggressiveness. Vocal masculinity strongly affected dominance ratings, but a man’s own dominance did not alter his attention to vocal masculinity when assessing dominance. However, men who rated themselves high on physical dominance rated the voices of other men lower on dominance and reported more sex partners (study I). Men with intermediate testosterone concentrations rated the voices of other men lower on dominance (study II). These results confirm the effect of vocal masculinity on dominance perceptions, provide further evidence that dominance is relevant to mating success, and shed new light on how men assess the dominance of rivals and potential allies. Our results suggest that attention to dominance signals may depend less on the observer’s own dominance in species with coalitional aggression, where individuals must assess others not only in relation to themselves but also in relation to each other. Among men, the effect of a deep, masculine voice on perceptions of dominance appears to be robust and unmediated by the formidability of the listener.
Tissue plasminogen activator levels change with plasma fibrinogen concentrations during pregnancy

To investigate the relationship between coagulation activities and the fibrinolytic system during normal pregnancy, we measured the plasma concentrations of coagulation factors, antithrombin III (AT III), D-dimer, tissue plasminogen activator (tPA), total protein S (TPS), and plasminogen activator inhibitor type 1 (PAI-1) in 436 apparently healthy pregnant, postpartum, and nonpregnant women. There were no significant changes in AT III, TPS, and factor XI concentrations during pregnancy and puerperium. However, factor VII, VIII, IX, and XII activities increased gradually as pregnancy progressed, reached maximum values in the third trimester, and returned to nonpregnant levels by 5–8 weeks postpartum. Plasma D-dimer levels in the third trimester of pregnancy were 1.23±0.42 µg/ml, significantly higher than for the first trimester (0.34±0.16 µg/ml, P<0.01). The tPA antigen levels averaged 1.8-fold higher in the late third trimester than in the first trimester; the plasma fibrinogen concentrations averaged 1.6-fold higher in the late third trimester than in the first trimester. Compared to the peak values during pregnancy, tPA levels averaged 39.8% lower and plasma fibrinogen concentrations averaged 40.0% lower at 5–8 weeks postpartum. The tPA levels correlated strongly with the plasma fibrinogen concentrations (r=0.52, P<0.01). In short, this study shows that tPA levels change in parallel with plasma fibrinogen concentrations during and after normal pregnancy.
ASSESSMENT AND COLLABORATION IN ONLINE LEARNING

Assessment can be seen as the engine that drives student course activity, online or off. It is particularly important in encouraging and shaping collaborative activity online. This paper discusses three sorts of online collaborative activity—collaborative discussion, small group collaboration, and collaborative exams. In each of these areas, it provides both theoretical grounding and practical advice for assessing, and so encouraging, collaboration in online courses.
Effects of dronedarone on clinical outcomes in patients with lone atrial fibrillation: pooled post hoc analysis from the ATHENA/EURIDIS/ADONIS studies.

INTRODUCTION
Dronedarone has been shown to reduce cardiovascular hospitalizations or death in patients with atrial fibrillation (AF) and additional risk factors. This post hoc exploratory analysis examines its effects in the subgroup of lone AF patients.


METHODS AND RESULTS
Individual data from patients with lone AF enrolled in the EURIDIS, ADONIS, and ATHENA trials were entered in a central database. The effects of dronedarone compared to placebo on the composite endpoint of cardiovascular hospitalizations or death, and their individual components, were evaluated. A total of 432 (192 placebo and 240 dronedarone) patients (7% of the total population) were classified as having lone AF (69.4% male patients, mean age 64 ± 13 years). The patients were followed for 13.8 ± 7.2 months. The risk for first cardiovascular hospitalizations or death from any cause in the placebo group after 1 year was 25% in the lone AF group compared to 29% the rest of the population. For patients with lone AF, dronedarone led to a 44% reduction of cardiovascular hospitalizations or death (hazard ratio (HR) 0.56; 95%CI 0.36-0.88, P = 0.004) and to a 46% reduction in cardiovascular hospitalizations alone (HR 0.54; 95%CI 0.34-0.87, P = 0.004) compared to placebo. HR for all-cause mortality was 1.02 (95%CI 0.31-3.34, P = 0.885). All findings were homogeneous across the 3 studies and similar to those observed in the overall population.


CONCLUSION
According to this post hoc analysis, patients with lone AF have a high risk for cardiovascular hospitalization within 1 year. Dronedarone when added to standard of care reduces the risk of cardiovascular hospitalizations in this population.
The Effectiveness of Mobile-Health Technology-Based Health Behaviour Change or Disease Management Interventions for Health Care Consumers: A Systematic Review

BACKGROUND
Mobile technologies could be a powerful media for providing individual level support to health care consumers. We conducted a systematic review to assess the effectiveness of mobile technology interventions delivered to health care consumers.


METHODS AND FINDINGS
We searched for all controlled trials of mobile technology-based health interventions delivered to health care consumers using MEDLINE, EMBASE, PsycINFO, Global Health, Web of Science, Cochrane Library, UK NHS HTA (Jan 1990-Sept 2010). Two authors extracted data on allocation concealment, allocation sequence, blinding, completeness of follow-up, and measures of effect. We calculated effect estimates and used random effects meta-analysis. We identified 75 trials. Fifty-nine trials investigated the use of mobile technologies to improve disease management and 26 trials investigated their use to change health behaviours. Nearly all trials were conducted in high-income countries. Four trials had a low risk of bias. Two trials of disease management had low risk of bias; in one, antiretroviral (ART) adherence, use of text messages reduced high viral load (>400 copies), with a relative risk (RR) of 0.85 (95% CI 0.72-0.99), but no statistically significant benefit on mortality (RR 0.79 [95% CI 0.47-1.32]). In a second, a PDA based intervention increased scores for perceived self care agency in lung transplant patients. Two trials of health behaviour management had low risk of bias. The pooled effect of text messaging smoking cessation support on biochemically verified smoking cessation was (RR 2.16 [95% CI 1.77-2.62]). Interventions for other conditions showed suggestive benefits in some cases, but the results were not consistent. No evidence of publication bias was demonstrated on visual or statistical examination of the funnel plots for either disease management or health behaviours. To address the limitation of the older search, we also reviewed more recent literature.


CONCLUSIONS
Text messaging interventions increased adherence to ART and smoking cessation and should be considered for inclusion in services. Although there is suggestive evidence of benefit in some other areas, high quality adequately powered trials of optimised interventions are required to evaluate effects on objective outcomes.
Summarizing Neonatal Time Series Data

We describe our investigations in generating textual summaries of physiological time series data to aid medical personnel in monitoring babies in neonatal intensive care units. Our studies suggest that summarization is a communicative task that requires data analysis techniques for determining the content of the summary. We describe a prototype system that summarizes physiological time series.
STAR, a sprawl tuned autonomous robot

This paper presents a six-legged, sprawl-tuned autonomous robot (STAR). This novel robot has a variable leg sprawl angle in the transverse plane to adapt its stiffness, height, and leg-to-surface contact angle. The sprawl angle can be varied from nearly positive 60 degrees to negative 90 degrees, enabling the robot to run in a planar configuration, upright, or inverted (see movie). STAR is fitted with spoke wheel-like legs which provide high electromechanical conversion efficiency and enable the robot to achieve legged performance over rough surfaces and obstacles, using a high sprawl angle, and nearly wheel-like performance over smooth surfaces for small sprawl angles. Our model and experiments show that the contact angle and normal contact forces are substantially reduced when the sprawl angle is low, and the velocity increases over smooth surfaces, with stable running at all velocities up to 5.2m/s and a Froude number of 9.8.
Measuring consumer satisfaction in internet banking: a core framework

What service-quality attributes must Internet banks offer to induce consumers to switch to online transactions and keep using them?
Monitoring during peripheral nerve blockade.

PURPOSE OF REVIEW
Objective monitors to warn against adverse events specific to the performance of nerve blockade are relatively unsophisticated compared with monitors used during general anesthesia. The purpose of this review is to outline the various monitors available, and how they can be used to reduce nerve block-related complications.


RECENT FINDINGS
Evidence is accumulating for three objective means of preventing complications. Electrical nerve stimulation is insensitive, but specific, at detecting intraneural needle placement, such that if a motor response is obtained with a current of 0.2 mA or less, the needle tip is positioned intraneurally. Ultrasonography allows for reduction of the volume of local anesthetic required to accomplish a nerve block, reducing the potential for systemic toxicity. The value of ultrasound in reducing inadvertent puncture of neighboring structures, while intuitive, is less clear. Finally, injection pressure monitoring helps objectively distinguish between an injection into low versus high compliance tissue (e.g. intrafascicular versus extrafascicular).


SUMMARY
Peripheral nerve blockade has evolved from an entirely blind procedure to a more reproducible subspecialty. Several monitors exist to objectively guide and monitor needle placement and application of local anesthetics. Because these monitors are complementary, best practice may involve combining all of these monitoring options when performing peripheral nerve blocks.
Multiflow: Multicast clean-slate with anticipated route calculation on OpenFlow programmable networks

Abs tract. Increasingly popular, Internet applications for multimedia broadcasting require multipoint communication, in order to reduce network traffic rates. However, the widespread adoption of traditional multicast protocols is still held back by the current Internet structure, where the responsibility for management of multicast groups is distributed among network devices. By using distributed algorithms, such protocols generate delays in processing control groups events. In this paper we propose a clean-slate approach for multimedia multicasting, where the end to end calculation of the best route is performed to decrease delays in group configuration. The prototype developed implements this approach using OpenFlow technology. Results obtained through experimentation show a performance gain in relation to traditional IP multicasting.
Generation of quadrilateral mesh over analytical curved surfaces

An automatic adaptive quadrilateral mesh conversion scheme for the generation of adaptive refinement meshes over analytical curved surfaces is proposed. The starting point of the quadrilateral mesh generator is a background triangular mesh of the curved surface. By a carefully controlled process to merge two triangles at a time the triangular mesh can be completely converted to quadrilaterals. A rapidly graded quadrilateral mesh with node spacing compatible with the desired element size distribution can be obtained from a well-graded triangular mesh. The quality of the quadrilateral mesh can be subsequently enhanced by a series of mesh modifications and element shape improvement procedures. The present scheme can be used in conjunction with an adaptive surface triangular mesh generator to generate quadrilateral meshes suitable for adaptive shell refinement analysis. © 1997 Elsevier Science B.V.