nils-herrmann/clean_scirepeval huggingface dataset:
Modern Small Satellites-Changing the Economics of Space

Earth orbiting satellites come in a wide range of shapes and sizes to meet a diverse variety of uses and applications. Large satellites with masses over 1000 kg support high-resolution remote sensing of the Earth, high bandwidth communications services, and world-class scientific studies but take lengthy developments and are costly to build and launch. The advent of commercially available, high-volume, and hence low-cost microelectronics has enabled a different approach through miniaturization. This results in physically far smaller satellites that dramatically reduce timescales and costs and that are able to provide operational and commercially viable services. This paper charts the evolution and rise of small satellites from being an early curiosity with limited utility through to the present where small satellites are a key element of modern space capabilities.
Learning a visuomotor controller for real world robotic grasping using simulated depth images

We want to build robots that are useful in unstructured real world applications, such as doing work in the household. Grasping in particular is an important skill in this domain, yet it remains a challenge. One of the key hurdles is handling unexpected changes or motion in the objects being grasped and kinematic noise or other errors in the robot. This paper proposes an approach to learning a closed-loop controller for robotic grasping that dynamically guides the gripper to the object. We use a wrist-mounted sensor to acquire depth images in front of the gripper and train a convolutional neural network to learn a distance function to true grasps for grasp configurations over an image. The training sensor data is generated in simulation, a major advantage over previous work that uses real robot experience, which is costly to obtain. Despite being trained in simulation, our approach works well on real noisy sensor images. We compare our controller in simulated and real robot experiments to a strong baseline for grasp pose detection, and find that our approach significantly outperforms the baseline in the presence of kinematic noise, perceptual errors and disturbances of the object during grasping.
Ontology visualization methods - a survey

Ontologies, as sets of concepts and their interrelations in a specific domain, have proven to be a useful tool in the areas of digital libraries, the semantic web, and personalized information management. As a result, there is a growing need for effective ontology visualization for design, management and browsing. There exist several ontology visualization methods and also a number of techniques used in other contexts that could be adapted for ontology representation. The purpose of this article is to present these techniques and categorize their characteristics and features in order to assist method selection and promote future research in the area of ontology visualization.
Characterization of a triple DNA polymerase replisome.

The replicase of all cells is thought to utilize two DNA polymerases for coordinated synthesis of leading and lagging strands. The DNA polymerases are held to DNA by circular sliding clamps. We demonstrate here that the E. coli DNA polymerase III holoenzyme assembles into a particle that contains three DNA polymerases. The three polymerases appear capable of simultaneous activity. Furthermore, the trimeric replicase is fully functional at a replication fork with helicase, primase, and sliding clamps; it produces slightly shorter Okazaki fragments than replisomes containing two DNA polymerases. We propose that two polymerases can function on the lagging strand and that the third DNA polymerase can act as a reserve enzyme to overcome certain types of obstacles to the replication fork.
The Future of Traditional Grocery Stores

Grocery stores are required to sign leases many years before the space will be utilized, or renew the already existing leases and thereby tie-up the space for a lot of years. In order for grocers to know exactly what they want in terms of store requirements in the future, they need to know how people will purchase their groceries in that specific time. The complexity is reinforced by new trends and technological developments within the industry. For instance, e-commerce within the food industry is growing markedly and is predicted to continue to grow. The purpose of this report is to investigate how the grocery industry will develop in order to investigate the eventual change in traditional grocery stores’ area requirements. Further, the parameters affecting the requirements are analysed in regards to impact, time horizon and geographical areas in Sweden. Applying the theory behind diffusion of innovation, retail change theory and customer behaviour the purpose is met. In parallel, the trends affecting the research area, such as convenience and technology innovations was investigated. Data was gathered from interviews with industry experts as well as literature and reports. The conclusion of the study is that due to e-commerce and new store concepts, the overall area requirement can increase in certain areas and decrease in others. The largest cities in Sweden are likely to find a solution in order to be able to offer home deliveries. This solution might be a central warehouse, which would decrease the sales area in the physical store. The stores already owning a certain area will most probably redesign the store and utilize the trend of coexistence. Together with the trend of convenience, the new stores will be built in the natural flow of people, which means that the big cities will have more stores with smaller areas in general. For geographical areas with lower population density, the e-commerce is more likely to be of the click & collect alternative. Consequently, the storage section of the store will need to increase in size. In the rural areas, the adoption of e-commerce will not be as fast since the profitability for the companies will not be as high in these areas. The interior changes could mean that the stores will be redesigned, but will not affect the area requirements namely, leaving the area requirements in these areas more or less the same.  Area requirements, forecasting, e-commerce and grocery store development
The Impact of Annotation Guidelines and Annotated Data on Extracting App Features from App Reviews

The quality of automatic app feature extraction from app reviews depends on various aspects, e.g. the feature extraction method, training and evaluation datasets, evaluation method etc. Annotation guidelines used to guide the annotation of training and evaluation datasets can have a considerable impact to the quality of the whole system but it is one of the aspects that has been commonly overlooked. In this study, we explore the effects of annotation guidelines to the quality of app feature extraction. As a main result, we propose several changes to the existing annotation guidelines with a goal of making the extracted app features more useful and informative to the app developers. We test the proposed changes via simulating the application of the new annotation guidelines and then evaluating the performance of the supervised machine learning models trained on datasets annotated with initial and simulated annotation guidelines. While the overall performance of automatic app feature extraction remains the same as compared to the model trained on the dataset with initial annotations, the features extracted by the model trained on the dataset with simulated new annotations are less noisy and more informative to the app developers. Secondly, we are interested in what kind of annotated training data is necessary for training an automatic app feature extraction model. In particular, we explore whether the training set should contain annotated app reviews from those apps/app categories on which the model is subsequently planned to be applied, or is it sufficient to have annotated app reviews from any app available for training, even when these apps are from very different categories compared to the test app. Our experiments show that having annotated training reviews from the test app is not necessary although including them into training set helps to improve recall. Furthermore, we test whether augmenting the training set with annotated product reviews helps to improve the performance of app feature extraction. We find that the models trained on augmented training set lead to improved recall but at the cost of the drop in precision.
Combined convolutional and recurrent neural networks for hierarchical classification of images

Deep learning models based on CNNs are predominantly used in image classification tasks. Such approaches, assuming independence of object categories, normally use a CNN as a feature learner and apply a flat classifier on top of it. Object classes in many settings have hierarchical relations, and classifiers exploiting these relations should perform better. We propose hierarchical classification models combining a CNN to extract hierarchical representations of images, and an RNN or sequence-to-sequence model to capture a hierarchical tree of classes. In addition, we apply residual learning to the RNN part in oder to facilitate training our compound model and improve generalization of the model. Experimental results on a real world proprietary dataset of images show that our hierarchical networks perform better than state-of-the-art CNNs.
Extended abdominoperineal resection with gluteus maximus flap reconstruction of the pelvic floor for rectal cancer.

Intraoperative tumour perforation, positive tumour margins, wound complications and local recurrence are frequent difficulties with conventional abdominoperineal resection (APR) for rectal cancer. An alternative technique is the extended posterior perineal approach with gluteus maximus flap reconstruction of the pelvic floor. The aim of this study was to report the technique and early experience of extended APR in a select cohort of patients.



The principles of operation are that the mesorectum is not dissected off the levator muscles, the perineal dissection is done in the prone position and the levator muscles are resected en bloc with the anus and lower rectum. The perineal defect is reconstructed with a gluteus maximus flap. Between 2001 and 2005, 28 patients with low rectal cancer were treated accordingly at the Karolinska Hospital.



Two patients had ypT0 tumours, 20 ypT3 and six ypT4 tumours. Bowel perforation occurred in one, the circumferential resection margin (CRM) was positive in two, and four patients had local perineal wound complications. Two patients developed local recurrence after a median follow-up of 16 months.



The extended posterior perineal approach with gluteus maximus flap reconstruction in APR has a low risk of bowel perforation, CRM involvement and local perineal wound complications. The rate of local recurrence may be lower than with conventional APR.
Joint angle estimation for floating base robots utilizing MEMS IMUs

This paper describes a novel motion estimation algorithm for floating base manipulators that utilizes low-cost inertial measurement units (IMUs) containing a three-axis gyroscope and a three-axis accelerometer. Four strap-down microelectromechanical system (MEMS) IMUs are mounted on each link to form a virtual IMU whose body's fixed frame is located at the center of the joint rotation.  The measured results obtained from the planar motion of a hydraulic arm show that the accuracy of the estimation of the joint angle is within ± 1 degree and that the root mean square error is less than 0.5 degree.
Electronic monitoring of treatment adherence and validation of alternative adherence measures in tuberculosis patients: a pilot study.

To assess adherence to community-based directly observed treatment (DOT) among Tanzanian tuberculosis patients using the Medication Event Monitoring System (MEMS) and to validate alternative adherence measures for resource-limited settings using MEMS as a gold standard.



This was a longitudinal pilot study of 50 patients recruited consecutively from one rural hospital, one urban hospital and two urban health centres. Treatment adherence was monitored with MEMS and the validity of the following adherence measures was assessed: isoniazid urine test, urine colour test, Morisky scale, Brief Medication Questionnaire, adapted AIDS Clinical Trials Group (ACTG) adherence questionnaire, pill counts and medication refill visits.



The mean adherence rate in the study population was 96.3% (standard deviation, SD: 7.7). Adherence was less than 100% in 70% of the patients, less than 95% in 21% of them, and less than 80% in 2%. The ACTG adherence questionnaire and urine colour test had the highest sensitivities but lowest specificities. The Morisky scale and refill visits had the highest specificities but lowest sensitivities. Pill counts and refill visits combined, used in routine practice, yielded moderate sensitivity and specificity, but sensitivity improved when the ACTG adherence questionnaire was added.



Patients on community-based DOT showed good adherence in this study. The combination of pill counts, refill visits and the ACTG adherence questionnaire could be used to monitor adherence in settings where MEMS is not affordable. The findings with regard to adherence and to the validity of simple adherence measures should be confirmed in larger populations with wider variability in adherence rates.
Webs of Five-Branes and N = 2 Superconformal Field Theories

We describe configurations of 5-branes and 7-branes which realize, when compactified on a circle, new isolated four-dimensional N = 2 superconformal field theories recently constructed by Gaiotto. Our diagrammatic method allows to easily count the dimensions of Coulomb and Higgs branches, with the help of a generalized s-rule. We furthermore show that superconformal field theories with E 6,7,8 flavor symmetry can be analyzed in a uniform manner in this framework; in particular we realize these theories at infinitely strongly-coupled limits of quiver theories with SU gauge groups.
A 25 dBm Digitally Modulated CMOS Power Amplifier for WCDMA/EDGE/OFDM With Adaptive Digital Predistortion and Efficient Power Control

A digitally modulated power amplifier (DPA) in 1.2 V 0.13 mum SOI CMOS is presented, to be used as a building block in multi-standard, multi-band polar transmitters. It performs direct amplitude modulation of an input RF carrier by digitally controlling an array of 127 unary-weighted and three binary-weighted elementary gain cells. The DPA is based on a novel two-stage topology, which allows seamless operation from 800 MHz through 2 GHz, with a full-power efficiency larger than 40% and a 25.2 dBm maximum envelope power. Adaptive digital predistortion is exploited for DPA linearization. The circuit is thus able to reconstruct 21.7 dBm WCDMA/EDGE signals at 1.9 GHz with 38% efficiency and a higher than 10 dB margin on all spectral specifications. As a result of the digital modulation technique, a higher than 20.1 % efficiency is guaranteed for WCDMA signals with a peak-to-average power ratio as high as 10.8 dB. Furthermore, a 15.3 dBm, 5 MHz WiMAX OFDM signal is successfully reconstructed with a 22% efficiency and 1.53% rms EVM. A high 10-bit nominal resolution enables a wide-range TX power control strategy to be implemented, which greatly minimizes the quiescent consumption down to 10 mW. A 16.4% CDMA average efficiency is thus obtained across a > 70 dB power control range, while complying with all the spectral specifications.
Reuleaux: Robot Base Placement by Reachability Analysis

Before beginning any robot task, users must position the robot's base, a task that now depends entirely on user intuition. While slight perturbation is tolerable for robots with moveable bases, correcting the problem is imperative for fixed- base robots if some essential task sections are out of reach. For mobile manipulation robots, it is necessary to decide on a specific base position before beginning manipulation tasks. This paper presents Reuleaux, an open source library for robot reachability analyses and base placement. It reduces the amount of extra repositioning and removes the manual work of identifying potential base locations. Based on the reachability map, base placement locations of a whole robot or only the arm can be efficiently determined. This can be applied to both statically mounted robots, where the position of the robot and workpiece ensure the maximum amount of work performed, and to mobile robots, where the maximum amount of workable area can be reached. The methods were tested on different robots of different specifications and evaluated for tasks in simulation and real world environment. Evaluation results indicate that Reuleaux had significantly improved performance than prior existing methods in terms of time-efficiency and range of applicability.
Mate-selection and the Dark Triad: Facilitating a short-term mating strategy and creating a volatile environment

The current study (N = 242) seeks to establish the relationship between traits known collectively as the Dark Triad – narcissism, psychopathy, Machiavellianism – and mating standards and preferences. Using a budget-allocation task, we correlated scores on the Dark Triad traits with mate preferences for a longterm and short-term mate. Men scoring high on the Dark Triad may be more indiscriminate than most when selecting for short-term mates in order to widen their prospects. Furthermore, those high on the Dark Triad – psychopathy in particular – tend to select for mates based on self-interest, assortative mating, or a predilection for volatile environments. We assessed these correlations when controlling for the Big Five and the sex of the participant. We also tested for moderation by the sex of the participant and mating context. Ramifications and future directions are considered.
Exploring the mechanisms behind the assessment of usefulness of restaurant reviews

Local online reviews such as Yelp have become large repositories of information, thus making it difficult for readers to find the most useful content. Our work investigates the factors that influence the readers' judgment of usefulness of restaurant reviews. We focus on assessing the mechanism behind the users' assessment of usefulness of reviews, particularly with respect to reviews provided by reviewers with local knowledge. We collected 160 manual annotations of 36 unique restaurant reviews and we interviewed ten participants. Our results show that users are able to detect reviews written by knowledgeable locals, and they perceive reviews provided by locals more useful not because they provide more valuable content but because local knowledge results in higher trust. We discuss design implications of these findings for helping readers to overcome information overload in local systems.
Quitty: using technology to persuade smokers to quit

Health is an important topic in HCI research with an increasing amount of health risks surrounding individuals and society at large. It is well known that smoking cigarettes can have serious health implications. The importance of this problem motivates investigation into the use of technology to encourage behavior change. Our study was designed to gather empirical knowledge about the role a "quitting app" can play in persuading people to quit smoking. Our purpose-built app Quitty introduces different content types from different content sources to study how they are perceived and motivate health behavior change. Findings from our field study show that tailored content and push-messages are considered the most important for persuading people to stop smoking. Based on our empirical findings, we propose six guidelines on how to design mobile applications to persuade smokers to quit.
Cotranscriptional Set 2 Methylation of Histone H 3 Lysine 36 Recruits a Repressive Rpd 3 Complex

Michael-Christopher Keogh,1 Siavash K. Kurdistani,2 Stephanie A. Morris,3 Seong Hoon Ahn,1,7 Vladimir Podolny,1 Sean R. Collins,4 Maya Schuldiner,4 Kayu Chin,5 Thanuja Punna,5 Natalie J. Thompson,5 Charles Boone,5,6 Andrew Emili,5,6 Jonathan S. Weissman,4 Timothy R. Hughes,5,6 Brian D. Strahl,3 Michael Grunstein,2 Jack F. Greenblatt,5,6,* Stephen Buratowski,1,* and Nevan J. Krogan5,6,8 1Department of Biological Chemistry and Molecular Pharmacology Harvard Medical School 240 Longwood Avenue Boston, Massachusetts 02115 2Department of Biological Chemistry David Geffen School of Medicine University of California, Los Angeles Los Angeles, California 90095 3Department of Biochemistry and Biophysics University of North Carolina School of Medicine Chapel Hill, North Carolina 27599 4Howard Hughes Medical Institute Department of Cellular and Molecular Pharmacology University of California, San Francisco Genentech Hall S472C 600 16th Street San Francisco, California 94143 5Banting and Best Department of Medical Research University of Toronto 112 College Street Toronto, Ontario M5G 1L6 Canada 6Department of Medical Genetics and Microbiology University of Toronto 1 Kings College Circle Toronto, Ontario M5S 1A8 Canada
An ontology for context-aware pervasive computing environments

This document describes COBRA-ONT, an ontology for supporting pervasive context-aware systems. COBRA-ONT, expressed in the Web Ontology Language OWL, is a collection of ontologies for describing places, agents and events and their associated properties in an intelligent meeting-room domain. This ontology is developed as a part of the Context Broker Architecture (CoBrA), a broker-centric agent architecture that provides knowledge sharing, context reasoning and privacy protection supports for pervasive context-aware systems. We also describe an inference engine for reasoning with information expressed using the COBRA-ONT ontology and the ongoing research in using the DAML-Time ontology for context reasoning.
Benefits and challenges of three cloud computing service models

Cloud computing can be defined as the use of new or existing computing hardware and virtualization technologies to form a shared infrastructure that enables web-based value added services. The three predominant service models are infrastructure, platform, and software-asa-service. Infrastructure-as-a-Service (IaaS) can be defined as the use of servers, storage, and virtualization to enable utility like services for users. Security is a big concern within IaaS, especially considering that the rest of the cloud service models run on top of the infrastructure and related layers. Platform-as-a-Service (PaaS) providers offer access to APIs, programming languages and development middleware which allows subscribers to develop custom applications without installing or configuring the development environment. Software-as-a-Service (SaaS) gives subscribed or pay-peruse users access to software or services which reside in the cloud and not on the user's device. Understanding the cloud service models is critical in determining if cloud services or hosting are an appropriate business solution, and if so, which model best balances the level of control required versus reduced hardware, configuration, and maintenance costs. Cloud computing offers many benefits to organizations; it has enabled collaboration amongst disparate communities and workgroups, and has overcome challenges that have plagued existing business solutions. However, the security, privacy, and integrity of the cloud are of prime importance and there are many challenges that exist. At the present time there seems to be a lot of momentum behind the adoption of cloud computing despite these. This may simply be a trend, an indication that society truly wants their data to be available whenever from anywhere, or a sign that few understand the associated risks.