nils-herrmann/clean_scirepeval huggingface dataset:
Automatic Text Simplification Tools for Deaf and Hard of Hearing Adults: Benefits of Lexical Simplification and Providing Users with Autonomy
Venue: CHI
Year: 2020

Automatic Text Simplification (ATS) which replaces text with simpler equivalents, is rapidly improving. While some research has examined ATS reading assistance tools, little has examined preferences of adults who are deaf or hard of hearing (DHH) and none empirically evaluated lexical simplification technology (replacement of individual words) with these users. Prior research has revealed that U.S. DHH adults have lower reading literacy on average than their hearing peers, with unique characteristics to their literacy profile. We investigate whether DHH adults perceive a benefit from lexical simplification applied automatically or when users are provided with greater autonomy, with on demand control and visibility as to which words are replaced. Formative interviews guided the design of an experimental study, in which DHH participants read English texts in their original form and with lexical simplification applied automatically or on demand. Participants indicated that they perceived a benefit form lexical simplification, and they preferred a system with on demand simplification.
Supply Chain and Supply Chain Cases
Year: 2018

This chapter introduces the concepts of Supply Chain and Supply Chain Management (SCM) to academic and research library professionals. It starts with definitions and essential characteristics, explained in the context of library mission, organization, processes, and core products and services. It then summarizes a brief history on how supply chain and its management have grown into a broadly recognized discipline and how it became a strategy for creating value for end users. Finally, this chapter provides two brainstorming use cases related to products that are similar to core library services. The goal of this chapter is to establish the argument that libraries need to adopt the Supply Chain idea as a discipline, a standard practice, and a foremost priority.
Compressed Domain Feature Analysis for Efficient Action Recognition
Year: 2020

Video surveillance system that use video cameras to transmit a signal to a specific place, on a limited set of monitors by Closed circuit television (CCTV) that may need monitoring such as banks, casinos, airports, military installations, and convenience stores. Even though CCTV systems may monitor a particular event, it still requires recognized data are to be more accurate and appearance invariant when abnormal activities are occurred and analysed. Automatic Teller Machines (ATM) are widely used over the world for automatic banking transactions. Some of ATM users are facing with unlawful activities such as money snatching and customer assault by murder. CCTV devices are set up for security that becomes an important factor for covering criminal activities. Many researchers are trying to solve this issue in different ways of Human Activity Recognition. In our system, we tend to use compressed video sequences MPEG flow instead of computationally expensive Optical Flow (OF) Compressed domain features such as Motion Vectors (MV) and Discrete Cosine Transform (DCT) coefficients can be achieved by partial decoding that needs no prior segmentation and no spatial or temporal assignment therefore it can reduce time requirement and can effect in minimal training. Mapping of compressed domain features are effective for no variation in actions recognition because of noise reduction in motion contents. Bag Of Words model based descriptors are created for each group of features by motion segmentation getting accurate feature description. Our system tends to create reliable and real time action recognition with compressed domain features analysis.
Demografische veranderingen en ontwikkelingssamenwerking
Year: 2009

ADVISORY COUNCIL ON INTERNATIONAL AFFAIRS A I V De Adviesraad Internationale Vraagstukken is een adviesorgaan van de regering. Hij brengt adviezen uit aan de minister van Buitenlandse Zaken, de minister van Defensie, de minister voor Ontwikkelingssamenwerking, de staatssecretaris van Buitenlandse Zaken en het Parlement. De Adviesraad kent vier permanente commissies voor de advisering op de beleidsterreinen van mensenrechten, vrede en veiligheid, ontwikkelingssamenwerking en Europese integratie. De staf van de Adviesraad en permanente commissies bestaat uit: mw. mr. W.A. van Aardenne, mw. dr. D.E. Comijs, drs. T.D.J. Oostenbrink en mw. drs. A.M.C. Wester.
Standstill frequency response test for obtaining parameters of six phase double delta salient pole synchronous machine on example of claw pole alternator
Venue: 2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)
Year: 2016

The current publication introduces an approach for obtaining parameters of a six phase double delta salient pole synchronous machine, based on the standstill frequency response test. The described approach was verified by measurements on a automotive claw pole alternator, done in a laboratory on a test bench.
AlphaFold: Improved protein structure prediction using
Year: 2019

Protein structure prediction aims to determine the three dimensional shape of a protein from 11 its amino acid sequence1. This problem is of fundamental importance to biology as the struc12 ture of a protein largely determines its function2 but can be hard to determine experimen13 tally. In recent years, considerable progress has been made by leveraging genetic informa14 tion: analysing the co variation of homologous sequences can allow one to infer which amino 15 acid residues are in contact, which in turn can aid structure prediction3. In this work, we 16 show that we can train a neural network to accurately predict the distances between pairs 17 of residues in a protein which convey more about structure than contact predictions. With 18 this information we construct a potential of mean force4 that can accurately describe the 19 shape of a protein. We find that the resulting potential can be optimised by a simple gradient 20 descent algorithm, to realise structures without the need for complex sampling procedures. 21 The resulting system, named AlphaFold, has been shown to achieve high accuracy, even for 22 sequences with relatively few homologous sequences. In the most recent Critical Assessment 23 of Protein Structure Prediction5 (CASP13) a blind assessment of the state of the field of pro24 tein structure prediction, AlphaFold created high accuracy structures (with TM scores+ of 25 0.7 or higher) for 24 out of 43 free modelling domains whereas the next best method, using 26 sampling and contact information, achieved such accuracy for only 14 out of 43 domains. 27 AlphaFold represents a significant advance in protein structure prediction. We expect the in28 creased accuracy of structure predictions for proteins to enable insights in understanding the 29 function and malfunction of these proteins, especially in cases where no homologous proteins 30 have been experimentally determined7.
Bayesian Variational Optimization for Combinatorial Spaces
Venue: ArXiv
Year: 2020

This paper focuses on Bayesian Optimization in combinatorial spaces. In many applications in the natural science. Broad applications include the study of molecules, proteins, DNA, device structures and quantum circuit designs, a on optimization over combinatorial categorical spaces is needed to find optimal or pareto optimal solutions. However, only a limited amount of methods have been proposed to tackle this problem. Many of them depend on employing Gaussian Process for combinatorial Bayesian Optimizations. Gaussian Processes suffer from scalability issues for large data sizes as their scaling is cubic with respect to the number of data points. This is often impractical for optimizing large search spaces. Here, we introduce a variational Bayesian optimization method that combines variational optimization and continuous relaxations to the optimization of the acquisition function for Bayesian optimization. Critically, this method allows for gradient based optimization and has the capability of optimizing problems with large data size and data dimensions. We have shown the performance of our method is comparable to state of the art methods while maintaining its scalability advantages. We also applied our method in molecular optimization.
Ceramic Microbial Fuel Cells Stack: power generation in standard and supercapacitive mode
Venue: Scientific Reports
Year: 2018

In this work, a microbial fuel cell (MFC) stack containing 28 ceramic MFCs was tested in both standard and supercapacitive modes. The MFCs consisted of carbon veil anodes wrapped around the ceramic separator and air breathing cathodes based on activated carbon catalyst pressed on a stainless steel mesh. The anodes and cathodes were connected in parallel. The electrolytes utilized had different solution conductivities ranging from 2.0 mScm 1 to 40.1 mScm 1, simulating diverse wastewaters. Polarization curves of MFCs showed a general enhancement in performance with the increase of the electrolyte solution conductivity. The maximum stationary power density was 3.2 mW (3.2 Wm 3) at 2.0 mScm 1 that increased to 10.6 mW (10.6 Wm 3) at the highest solution conductivity (40.1 mScm 1) For the first time, MFCs stack with 1 L operating volume was also tested in supercapacitive mode, where full galvanostatic discharges are presented. Also in the latter case, performance once again improved with the increase in solution conductivity. Particularly, the increase in solution conductivity decreased dramatically the ohmic resistance and therefore the time for complete discharge was elongated, with a resultant increase in power. Maximum power achieved varied between 7.6 mW (7.6 Wm 3) at 2.0 mScm 1 and 27.4 mW (27.4 Wm 3) at 40.1 mScm 1.
Face Detection and Face Recognition in Android Mobile Applications
Year: 2016

The quality of the smartphoneaEUR(tm)s camera enables us to capture high quality pictures at a high resolution, so we can perform different types of recognition on these images. Face detection is one of these types of recognition that is very common in our society. We use it every day on Facebook to tag friends in our pictures. It is also used in video games alongside Kinect concept, or in security to allow the access to private places only to authorized persons. These are just some examples of using facial recognition, because in modern society, detection and facial recognition tend to surround us everywhere. The aim of this article is to create an appli cation for smartphones that can recognize human faces. The main goal of this application is to grant access to certain areas or rooms only to certain authorized persons. For example, we can speak here of hospitals or educational institutions where there are rooms where only certain employees can enter. Of course, this type of application can cover a wide range of uses, such as helping people suffering from Alzheimer's to recognize the people they loved, to fill gaps persons who canaEUR(tm)t remember the names of their relatives or for example to automatically capture the face of our own children when they smile.
Identification of MYOM2 as a candidate gene in hypertrophic cardiomyopathy and Tetralogy of Fallot, and its functional evaluation in the Drosophila heart
Venue: Disease Models Mechanisms
Year: 2020

The causal genetic underpinnings of congenital heart diseases, which are often complex and multigenic, are still far from understood. Moreover, there are also predominantly monogenic heart defects, such as cardiomyopathies, with known disease genes for the majority of cases. In this study, we identified mutations in myomesin 2 (MYOM2) in patients with Tetralogy of Fallot (TOF) the most common cyanotic heart malformation, as well as in patients with hypertrophic cardiomyopathy (HCM) who do not exhibit any mutations in the known disease genes. MYOM2 is a major component of the myofibrillar M band of the sarcomere, and a hub gene within interactions of sarcomere genes. We show that patient derived cardiomyocytes exhibit myofibrillar disarray and reduced passive force with increasing sarcomere lengths. Moreover, our comprehensive functional analyses in the Drosophila animal model reveal that the so far uncharacterized fly gene CG14964 [herein referred to as Drosophila myomesin and myosin binding protein (dMnM) may be an ortholog of MYOM2, as well as other myosin binding proteins. Its partial loss of function or moderate cardiac knockdown results in cardiac dilation, whereas more severely reduced function causes a constricted phenotype and an increase in sarcomere myosin protein. Moreover, compound heterozygous combinations of CG14964 and the sarcomere gene Mhc (MYH6/7) exhibited synergistic genetic interactions. In summary, our results suggest that MYOM2 not only plays a critical role in maintaining robust heart function but may also be a candidate gene for heart diseases such as HCM and TOF, as it is clearly involved in the development of the heart. This article has an associated First Person interview with Emilie Auxerre Plantie and Tanja Nielsen, joint first authors of the paper.  MYOM2 plays a critical role in establishing or maintaining robust heart function, and is a candidate gene for heart diseases, such as hypertrophic cardiomyopathy and Tetralogy of Fallot.
Continual Learning for Affective Robotics: Why, What and How?
Venue: 2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO MAN)
Year: 2020

Creating and sustaining closed loop dynamic and social interactions with humans require robots to continually adapt towards their users' behaviours, their affective states and moods while keeping them engaged in the task they are performing. Analysing, understanding and appropriately responding to human nonverbal behaviour and affective states are the central objectives of affective robotics research. Conventional machine learning approaches do not scale well to the dynamic nature of such real world interactions as they require samples from stationary data distributions. The real world is not stationary, it changes continuously. In such contexts, the training data and learning objectives may also change rapidly. Continual Learning (CL) by design, is able to address this very problem by learning incrementally. In this paper, we argue that CL is an essential paradigm for creating fully adaptive affective robots (why) To support this argument, we first provide an introduction to CL approaches and what they can offer for various dynamic (interactive) situations (what) We then formulate guidelines for the affective robotics community on how to utilise CL for perception and behaviour learning with adaptation (how) For each case, we reformulate the problem as a CL problem and outline a corresponding CL based solution. We conclude the paper by highlighting the potential challenges to be faced and by providing specific recommendations on how to utilise CL for affective robotics.
Particle sparged anaerobic membrane bioreactor with fluidized polyethylene terephthalate beads for domestic wastewater treatment: Modelling approach and fouling control.
Venue: Bioresource technology
Year: 2018

The study presents a mathematical model developed to better understand and control membrane fouling in a single staged, anaerobic fluidized bed membrane bioreactor (AFMBR) using polyethylene terephthalate (PET) beads as scouring media. The model was based on combining the anaerobic biological model AM2b and a fouling model applied in membrane filtration. The presented model was validated using experimental data obtained by a laboratory scaled AFMBR reactor run during 250 d under various operational conditions. The combined AM2b and fouling model was able to simulate volatile suspended solids, soluble COD concentration, soluble microbial products concentrations and the methane production rate at steady state condition with R2 of 95% as well as the trans membrane pressure with R2 of 99% The model was able to predict dominant fouling mechanism by assessing fouling resistances caused by cake formation and pore blocking separately.
Facebook: Help or hindrance? A study of the relationship between Facebook uses, gratifications, and depression symptoms in the older adult population
Year: 2017

Building on the uses and gratifications theory, this research used online survey to examine the relationship between self reported depression symptoms and the use of Facebook among older adults in Iowa. The purpose of this research was to establish the type of relationship that Facebook use has with those who exhibit depressive symptoms in the population above the age of 65. Existing research has primarily looked at the young adult population, specifically collegeage participants, and the relationship has been found to be negative that Facebook use negatively impacts mental health. This research focused on a different demographic, the older adult population, and the impact that Facebook use has on their mental health. The analysis found that the needs Facebook gratifies the most among older adults are entertainment and interaction based with the most variance explained by social affection and informational gratifications. The results also indicate that Facebook, overall, is more of a hindrance.
Strength of a carbonate silt at the solid fluid transition and submarine landslide run out
Year: 2015

Submarine landslide run out is governed by the rheology of the sediment as it evolves from a soil to a viscous fluid. It has been shown previously that the geotechnical characterization of fine grained sediments can be extended into the liquid range in a continuous fashion (Boukpeti et al. 2012) In this paper, we present the results of strength measurements on a carbonate silt over a wide range of water contents and compare them with results reported previously for two other soils.We then show that a reasonable estimate of submarine slide run out can be obtained from a simplified analysis based on the energy dissipation through sliding at the base of the slide. Results of the simplified analysis are validated through comparison with run out predictions obtained using the one dimensional depth averaged modelling softwareUWA SM3. Using a simple formulation to account for water entrainment in the run out analysis, the influence of the soil rheology on the final run out is demonstrated. In this case, difference in the rheology of the carbonate silt compared to the non carbonate fine grained soils leads to a stronger influence of water entrainment on run out distance.
Guaranteeing Secrecy using Artificial Noise
Venue: IEEE Transactions on Wireless Communications
Year: 2008

The broadcast nature of the wireless medium makes the communication over this medium vulnerable to eavesdropping. This paper considers the problem of secret communication between two nodes, over a fading wireless medium, in the presence of a passive eavesdropper. The assumption used is that the transmitter and its helpers (amplifying relays) have more antennas than the eavesdropper. The transmitter ensures secrecy of communication by utilizing some of the available power to produce 'artificial noise' such that only the eavesdropper's channel is degraded. Two scenarios are considered, one where the transmitter has multiple transmit antennas, and the other where amplifying relays simulate the effect of multiple antennas. The channel state information (CSI) is assumed to be publicly known, and hence, the secrecy of communication is independent of the secrecy of CSI.
Water nebulization to counteract urban overheating: Development and experimental test of a smart logic to maximize energy efficiency and outdoor environmental quality
Venue: Applied Energy
Year: 2019

Several mature urban climate mitigation technologies have been proposed to date. What mostly hinders their wide implementation is that their efficiency heavily depends on the local microclimatic specificities, since they cannot self adjust to the environmental changes. This study aims at investigating benefits and impacts of smart logics applied to outdoor cooling, by field testing a web of nebulizers coupled to a bespoke fuzzy controller piloting the pump. The cooling action was tweaked as convenient to maintain comfortable conditions and to avoid energy wastage whenever unneeded. To the best of the authors' knowledge, this is the first application of fuzzy logic to water spraying systems (or to any other controllable urban climate mitigation technology) targeting comfort and energy optimization. The prototype was field monitored in comparison with the conventional on off control, in two Italian urban contexts (Cfa and Csa climatic zones) over 15 days in the hottest months of the year. The cooling and humidification action was thoroughly characterized by mapping both the horizontal and vertical profiles and by applying advanced Artificial Intelligence techniques to spot the main environmental drivers. The maximum cooling (measured between the sprayed area and an undisturbed reference) touched 7.5 degC and 6.14 degC in the two locations, respectively. The energy saving achieved under fuzzy control versus the temporized control, was spectacularly high in the wetter and windier location with an average of 51.2% and a maximum of 67.5% The comfort benefit was also substantial: the temperature never deviated from neutrality by more than 2 degC, whereas with the on off, this threshold was surpassed between the 14% and the 20% of the time by even more than 5 degC. The results suggest that smartly controlled nebulization is an energy efficient and comfort effective strategy to counteract urban overheating. Furthermore, solar powered solutions are well suited as proved by the preliminary design estimation we included.
La transformacion territorial de la ciudad de Rio Grande en Tierra del Fuego a partir de las migraciones generadas por decisiones geopoliticas
Year: 2019

La ciudad de Rio Grande, provincia de Tierra del Fuego, en el extremo sur de la Republica Argentina, crecio muy aceleradamente en las ultimas cuatro decadas a partir de la localizacion de actividades economicas incentivadas por una ley de promocion, producto de una decision geopolitica de ocupar el territorio con poblacion argentina. Esto dio lugar a un importante flujo migratorio desde otras provincias. El sector urbano de Margen Sur ha sido el mayor receptor de migrantes pero, dado que lo hicieron en asentamientos, el resultado ha sido una zona donde se concentraron los peores indicadores en la propiedad de la tierra, la cobertura de servicios de infraestructura, el hacinamiento, los hogares con Necesidades Basicas Insatisfechas (NBI) la desocupacion, el analfabetismo y las viviendas irrecuperables. En los ultimos anos, la gestion municipal encaro diversas acciones tendientes a evitar nuevas ocupaciones masivas de tierras y a urbanizar los asentamientos informales generados desde 2006. La situacion actual es de una gran incertidumbre sobre el futuro de la ciudad de Rio Grande, pero en caso que las migraciones continuen, deberan atenderse algunos desafios fundamentales y encarar acciones sostenibles en el tiempo.