nils-herrmann/clean_scirepeval huggingface dataset:
Generating the Future with Adversarial Transformers

We learn models to generate the immediate future in video. This problem has two main challenges. Firstly, since the future is uncertain, models should be multi-modal, which can be difficult to learn. Secondly, since the future is similar to the past, models store low-level details, which complicates learning of high-level semantics. We propose a framework to tackle both of these challenges. We present a model that generates the future by transforming pixels in the past. Our approach explicitly disentangles the models memory from the prediction, which helps the model learn desirable invariances. Experiments suggest that this model can generate short videos of plausible futures. We believe predictive models have many applications in robotics, health-care, and video understanding.
Large-scale generation and analysis of filamentous fungal DNA barcodes boosts coverage for kingdom fungi and reveals thresholds for fungal species and higher taxon delimitation

Species identification lies at the heart of biodiversity studies that has in recent years favoured DNA-based approaches. Microbial Biological Resource Centres are a rich source for diverse and high-quality reference materials in microbiology, and yet the strains preserved in these biobanks have been exploited only on a limited scale to generate DNA barcodes. As part of a project funded in the Netherlands to barcode specimens of major national biobanks, sequences of two nuclear ribosomal genetic markers, the Internal Transcribed Spaces and 5.8S gene (ITS) and the D1/D2 domain of the 26S Large Subunit (LSU), were generated as DNA barcode data for ca. 100 000 fungal strains originally assigned to ca. 17 000 species in the CBS fungal biobank maintained at the Westerdijk Fungal Biodiversity Institute,  Using more than 24 000 DNA barcode sequences of 12 000 ex-type and manually validated filamentous fungal strains of 7 300 accepted species, the optimal identity thresholds to discriminate filamentous fungal species were predicted as 99.6 % for ITS and 99.8 % for LSU. We showed that 17 % and 18 % of the species could not be discriminated by the ITS and LSU genetic markers, respectively. Among them, ∼8 % were indistinguishable using both genetic markers. ITS has been shown to outperform LSU in filamentous fungal species discrimination with a probability of correct identification of 82 % vs. 77.6 %, and a clustering quality value of 84 % vs. 77.7 %. At higher taxonomic classifications, LSU has been shown to have a better discriminatory power than ITS. With a clustering quality value of 80 %, LSU outperformed ITS in identifying filamentous fungi at the ordinal level. At the generic level, the clustering quality values produced by both genetic markers were low, indicating the necessity for taxonomic revisions at genus level and, likely, for applying more conserved genetic markers or even whole genomes. The taxonomic thresholds predicted for filamentous fungal identification at the genus, family, order and class levels were 94.3 %, 88.5 %, 81.2 % and 80.9 % based on ITS barcodes, and 98.2 %, 96.2 %, 94.7 % and 92.7 % based on LSU barcodes. The DNA barcodes used in this study have been deposited to GenBank and will also be publicly available at the Westerdijk Institute's website as reference sequences for fungal identification, marking an unprecedented data release event in global fungal barcoding efforts to date.
ElSe: ellipse selection for robust pupil detection in real-world environments

Fast and robust pupil detection is an essential prerequisite for video-based eye-tracking in real-world settings. Several algorithms for image-based pupil detection have been proposed in the past, their applicability, however, is mostly limited to laboratory conditions. In real-world scenarios, automated pupil detection has to face various challenges, such as illumination changes, reflections (on glasses), make-up, non-centered eye recording, and physiological eye characteristics. We propose ElSe, a novel algorithm based on ellipse evaluation of a filtered edge image. We aim at a robust, inexpensive approach that can be integrated in embedded architectures, e.g., driving. The proposed algorithm was evaluated against four state-of-the-art methods on over 93,000 hand-labeled images from which 55,000 are new eye images contributed by this work. On average, the proposed method achieved a 14.53% improvement on the detection rate relative to the best state-of-the-art performer. Algorithm and data sets are available for download: ftp://emmapupildata@messor.informatik.unituebingen.de (password:eyedata).
Through the Looking Glass - The 2018 Edition: Trends in Solid-State Circuits from the 65th ISSCC

The International Solid-State Circuits Conference (ISSCC) is the flagship conference of the IEEE Solid-State Circuits Society. This year, for the 65th ISSCC, the theme is "Silicon Engineering a Social World." Continued advances in solid-state circuits and systems have brought ever-more powerful communication and computational capabilities into mobile form factors. Such ubiquitous smart devices lie at the heart of a revolution shaping how we connect, collaborate, build relationships, and share information. These social technologies allow people to maintain connections and support networks not otherwise possible; they provide the ability to access information instantaneously and from any location, thereby helping to shape world events and culture, empowering citizens of all nations, and creating social networks that allow worldwide communities to develop and form bonds based on common interests.
Attractor of Smale – Williams Type in an Autonomous Distributed System

We consider an autonomous system of partial differential equations for a onedimensional distributed medium with periodic boundary conditions. Dynamics in time consists of alternating birth and death of patterns with spatial phases transformed from one stage of activity to another by the doubly expanding circle map. So, the attractor in the Poincaré section is uniformly hyperbolic, a kind of Smale – Williams solenoid. Finite-dimensional models are derived as ordinary differential equations for amplitudes of spatial Fourier modes (the 5D and 7D models). Correspondence of the reduced models to the original system is demonstrated numerically. Computational verification of the hyperbolicity criterion is performed for the reduced models: the distribution of angles of intersection for stable and unstable manifolds on the attractor is separated from zero, i.e., the touches are excluded. The example considered gives a partial justification for the old hopes that the chaotic behavior of autonomous distributed systems may be associated with uniformly hyperbolic attractors.
Interactive 3D Modeling with a Generative Adversarial Network

We propose the idea of using a generative adversarial network (GAN) to assist users in designing real-world shapes with a simple interface. Users edit a voxel grid with a Minecraft-like interface. Yet they can execute a SNAP command at any time, which transforms their rough model into a desired shape that is both similar and realistic. They can edit and snap until they are satisfied with the result. The advantage of this approach is to assist novice users to create 3D models characteristic of the training data by only specifying rough edits. Our key contribution is to create a suitable projection operator around a 3D-GAN that maps an arbitrary 3D voxel input to a latent vector in the shape manifold of the generator that is both similar in shape to the input but also realistic. Experiments show our method is promising for computer-assisted interactive modeling.
Direct versus indirect loading of orthodontic miniscrew implants—an FEM analysis

The mesialization of molars in the lower jaw represents a particularly demanding scenario for the quality of orthodontic anchorage. The use of miniscrew implants has proven particularly effective; whereby, these orthodontic implants are either directly loaded (direct anchorage) or employed indirectly to stabilize a dental anchorage block (indirect anchorage). The objective of this study was to analyze the biomechanical differences between direct and indirect anchorage and their effects on the primary stability of the miniscrew implants. For this purpose, several computer-aided design/computer-aided manufacturing (CAD-CAM)-models were prepared from the CT data of a 21-year-old patient, and these were combined with virtually constructed models of brackets, arches, and miniscrew implants. Based on this, four finite element method (FEM) models were generated by three-dimensional meshing. Material properties, boundary conditions, and the quality of applied forces (direction and magnitude) were defined. After solving the FEM equations, strain values were recorded at predefined measuring points. The calculations made using the FEM models with direct and indirect anchorage were statistically evaluated. The loading of the compact bone in the proximity of the miniscrew was clearly greater with direct than it was with indirect anchorage. The more anchor teeth were integrated into the anchoring block with indirect anchorage, the smaller was the peri-implant loading of the bone. Indirect miniscrew anchorage is a reliable possibility to reduce the peri-implant loading of the bone and to reduce the risk of losing the miniscrew. The more teeth are integrated into the anchoring block, the higher is this protective effect. In clinical situations requiring major orthodontic forces, it is better to choose an indirect anchorage in order to minimize the risk of losing the miniscrew.
Speaking their Mind: Populist Style and Antagonistic Messaging in the Tweets of Donald Trump, Narendra Modi, Nigel Farage, and Geert Wilders

The authors in this study examined the function and public reception of critical tweeting in online campaigns of four nationalist populist politicians during major national election campaigns. Using a mix of qualitative coding and case study inductive methods, we analyzed the tweets of Narendra Modi, Nigel Farage, Donald Trump, and Geert Wilders before the 2014 Indian general elections, the 2016 UK Brexit referendum, the 2016 US presidential election, and the 2017 Dutch general election, respectively. Our data show that Trump is a consistent outlier in terms of using critical language on Twitter when compared to Wilders, Farage, and Modi, but that all four leaders show significant investment in various forms of antagonistic messaging including personal insults, sarcasm, and labeling, and that these are rewarded online by higher retweet rates. Building on the work of Murray Edelman and his notion of a political spectacle, we examined Twitter as a performative space for critical rhetoric within the frame of nationalist politics. We found that cultural and political differences among the four settings also impact how each politician employs these tactics. Our work proposes that studies of social media spaces need to bring normative questions into traditional notions of collaboration. As we show here, political actors may benefit from in-group coalescence around antagonistic messaging, which while serving as a call to arms for online collaboration for those ideologically aligned, may on a societal level lead to greater polarization.
Peri-epiphyseal and Overuse Injuries in Adolescent Athletes

Overuse injuries of the musculoskeletal system in immature athletes are commonly seen in medical practice.



An analysis of published clinical, outcome, and biomechanical studies of adolescent epiphyseal and overuse injuries was performed through 2008 to increase recognition and provide treatment recommendations.



Adolescent athletes can sustain physeal and bony stress injuries. Recovery and return to play occur more swiftly if such injuries are diagnosed early and immobilized until the patient is pain-free, typically about 4 weeks for apophyseal and epiphyseal overuse injuries. Certain epiphyseal injuries have prolonged symptoms with delayed treatment, including those involving the bones in the hand, elbow, and foot. If such injuries are missed, prolonged healing and significant restrictions in athletic pursuits may occur.



Some of these injuries are common to all weightbearing sports and are therefore widely recognized. Several are common in gymnastics but are rarely seen in other athletes. Early recognition and treatment of these conditions lead to quicker recovery and so may prevent season-ending, even career-ending, events from occurring.
Polarization reconfigurable patch array antenna

A novel polarization reconfigurable array antenna is proposed and fabricated. Measured results validate the performance improvement in port isolation and cross polarization level. The antenna can operate with vertical and horizontal polarizations at the same time and hence realize polarization diversity. By adding a polarization switch, the antenna can provide either RHCP or LHCP radiations. A total of four polarization modes can be facilitated with this antenna array and may find applications in new and up-coming wireless communication standards that require polarization diversity.
Incentive Compatible Imbalance Settlement

Imbalance settlement markets are managed by the system operators and provide a mechanism for settling the inevitable discrepancies between contractual agreements and physical delivery. In European power markets, settlements schemes are mainly based on heuristic penalties. These arrangements have disadvantages: First, they do not provide transparency about the cost of the reserve capacity that the system operator may have obtained ahead of time, nor about the cost of the balancing energy that is actually deployed. Second, they can be gamed if market participants use the imbalance settlement as an opportunity for market arbitrage, for example if market participants use balancing energy to avoid higher costs through regular trade on illiquid energy markets. Third, current practice hinders the market-based integration of renewable energy and the provision of financial incentives for demand response through rigid penalty rules. In this paper we try to remedy these disadvantages by proposing an imbalance settlement procedure with an incentive compatible cost allocation scheme for reserve capacity and deployed energy. Incentive compatible means that market participants voluntarily and truthfully state their valuation of ancillary services. We show that this approach guarantees revenue sufficiency for the system operator and provides financial incentives for balance responsible parties to keep imbalances close to zero.
Robot transparency, trust and utility

As robot reasoning becomes more complex, debugging becomes increasingly hard based solely on observable behaviour, even for robot designers and technical specialists. Similarly, nonspecialist users find it hard to create useful mental models of robot reasoning solely from observed behaviour. The EPSRC Principles of Robotics mandate that our artefacts should be transparent, but what does this mean in practice, and how does transparency affect both trust and utility? We investigate this relationship in the literature and find it to be complex, particularly in non industrial environments where transparency may have a wider range of effects on trust and utility depending on the application and purpose of the robot. We outline our programme of research to support our assertion that it is nevertheless possible to create transparent agents that are emotionally engaging despite having a transparent machine nature.
NBER WORKING PAPER SERIES CREDIT FRICTIONS AND ‘SUDDEN STOPS’ IN SMALL OPEN ECONOMIES: AN EQUILIBRIUM BUSINESS CYCLE FRAMEWORK FOR EMERGING MARKETS CRISES

Financial frictions are a central element of most of the models that the literature on emerging markets crises has proposed for explaining the ‘Sudden Stop’ phenomenon. To date, few studies have aimed to examine the quantitative implications of these models and to integrate them with an equilibrium business cycle framework for emerging economies. This paper surveys these studies viewing them as ability-to-pay and willingness-to-pay variations of a framework that adds occasionally binding borrowing constraints to the small open economy real-business-cycle model. A common feature of the different models is that agents factor in the risk of future Sudden Stops in their optimal plans, so that equilibrium allocations and prices are distorted even when credit constraints do not bind. Sudden Stops are a property of the unique, flexible-price competitive equilibrium of these models that occurs in a particular region of the state space in which negative shocks make borrowing constraints bind. The resulting nonlinear effects imply that solving the models requires non-linear numerical methods, which are described in the survey. The results show that the models can yield relatively infrequent Sudden Stops with large current account reversals and deep recessions nested within smoother business cycles. Still, research in this area is at an early stage and this survey aims to stimulate further work. Cristina Arellano Enrique G. Mendoza Department of Economics Department of Economics Social Sciences Building University of Maryland Duke University College Park, MD 20742 Durham, NC 27708-0097 and NBER mendozae@econ.duke.edu
Improving adversarial neural machine translation with prior knowledge

Generative adversarial networks (GANs) has achieved great success in the field of image processing, Adversarial Neural Machine Translation(NMT) is the application of GANs to machine translation. Unlike previous work training NMT model through maximizing the likelihood of the human translation, Adversarial NMT minimizes the distinction between human translation and the translation generated by a NMT model. Even though Adversarial NMT has achieved impressive results, while using little in the way of prior knowledge. In this paper, we integrated bilingual dictionaries to Adversarial NMT by leveraging a character model. Extensive experiment shows that our proposed methods can achieve remarkable improvement on the translation quality of Adversarial NMT, and obtain better result than several strong baselines.
Phantom limbs and the concept of a neuromatrix

The phenomenon of a phantom limb is a common experience after a limb has been amputated or its sensory roots have been destroyed. A complete break of the spinal cord also often leads to a phantom body below the level of the break. Furthermore, a phantom of the breast, the penis, or of other innervated body parts is reported after surgical removal of the structure. A substantial number of children who are born without a limb feel a phantom of the missing part, suggesting that the neural network, or 'neuromatrix', that subserves body sensation has a genetically determined substrate that is modified by sensory experience.
Description of gamma radiation-resistant Geodermatophilus dictyosporus sp. nov. to accommodate the not validly named Geodermatophilus obscurus subsp. dictyosporus (Luedemann, 1968)

A gamma radiation-resistant, Gram reaction-positive, aerobic and chemoorganotrophic actinobacterium, initially designated Geodermatophilus obscurus subsp. dictyosporus G-5T, was not validly named at the time of initial publication (1968). G-5T formed black-colored colonies on GYM agar. The optimal growth range was 25–35 °C, at pH 6.5–9.5 and in the absence of NaCl. Chemotaxonomic and molecular characteristics of the isolate matched those described for members of the genus Geodermatophilus. The DNA G + C content of the strain was 75.3 mol  %. The peptidoglycan contained meso-diaminopimelic acid as diagnostic diamino acid. The main polar lipids were phosphatidylcholine, diphosphatidylglycerol, phosphatidylinositol, phosphatidylethanolamine and one unspecified glycolipid; MK-9(H4) was the dominant menaquinone and galactose was detected as a diagnostic sugar. The major cellular fatty acids were branched-chain saturated acids, iso-C16:0 and iso-C15:0. The 16S rRNA gene showed 94.8–98.4 % sequence identity with the members of the genus Geodermatophilus. Based on phenotypic results and 16S rRNA gene sequence analysis, strain G-5T is proposed to represent a novel species, Geodermatophilus dictyosporus and the type strain is G-5T (=DSM 43161T = CCUG 62970T = MTCC 11558T = ATCC 25080T = CBS 234.69T = IFO 13317T = KCC A-0154T = NBRC 13317T). The INSDC accession number is HF970584.
Learning to Interpret Satellite Images Using Wikipedia

Despite recent progress in computer vision, fine-grained interpretation of satellite images remains challenging because of a lack of labeled training data. To overcome this limitation, we propose using Wikipedia as a previously untapped source of rich, georeferenced textual information with global coverage. We construct a novel large-scale, multi-modal dataset by pairing geo-referenced Wikipedia articles with satellite imagery of their corresponding locations. To prove the efficacy of this dataset, we focus on the African continent and train a deep network to classify images based on labels extracted from articles. We then fine-tune the model on a humanannotated dataset and demonstrate that this weak form of supervision can drastically reduce the quantity of humanannotated labels and time required for downstream tasks.
Graph Signal Denoising via Trilateral Filter on Graph Spectral Domain

This paper presents a graph signal denoising method with the trilateral filter defined in the graph spectral domain. The original trilateral filter (TF) is a data-dependent filter that is widely used as an edge-preserving smoothing method for image processing. However, because of the data-dependency, one cannot provide its frequency domain representation. To overcome this problem, we establish the graph spectral domain representation of the data-dependent filter, i.e., a spectral graph TF (SGTF). This representation enables us to design an effective graph signal denoising filter with a Tikhonov regularization. Moreover, for the proposed graph denoising filter, we provide a parameter optimization technique to search for a regularization parameter that approximately minimizes the mean squared error w.r.t. the unknown graph signal of interest. Comprehensive experimental results validate our graph signal processing-based approach for images and graph signals.
A Conflict-Based Path-Generation Heuristic for Evacuation Planning

5 Evacuation planning and scheduling is a critical aspect of disaster management and national security applications. This paper proposes a conflict-based path-generation approach for evacuation planning. Its key idea is to decompose the evacuation planning problem into a master and a subproblem. The subproblem generates new evacuation paths for each evacuated area, while the master problem optimizes the flow of evacuees and produce an evacuation plan. Each new path is generated to remedy conflicts in the evacuation flows and adds new columns and a new row in the master problem. The algorithm is applied to a set of large-scale evacuation scenarios ranging from the Hawkesbury-Nepean flood plain (West Sydney, Australia) which require evacuating in the order of 70,000 persons, to the New Orleans metropolitan area and its 1,000,000 residents. Experiments illustrate the scalability of the approach which is able to produce evacuation for scenarios with more than 1,200 nodes, while a direct Mixed Integer Programming formulation becomes intractable for instances with more than 5 nodes. With this approach, realistic evacuations scenarios can be solved near-optimally in reasonable time, supporting both evacuation planning in strategic, tactical, and operational environments.