nils-herrmann/clean_scirepeval huggingface dataset:
An agent-based approach to knowledge management

Traditional approaches to knowledge management are essentially limited to document management. However, much knowledge in organizations or communities resides in an informal social network and may be accessed only by asking the right people. This paper describes MARS, a multiagent referral system for knowledge management. MARS assigns a software agent to each user. The agents facilitate their users' interactions and help manage their personal social networks. Moreover, the agents cooperate with one another by giving and taking referrals to help their users find the right parties to contact for a specific knowledge need.
RF chain and user selection for multiuser MIMO systems under random data arrival

Multiuser Multiple input multiple output (MIMO) systems are now having more and more radio frequency (RF) chains, with larger capacity and at the same time higher energy consumption. With random data arrival, it is desired to turn off RF chains to save energy according to the traffic variations. In this paper a low-complexity traffic-aware scheme is proposed, whereby RF chains and users are selected at each frame based on the channel quality and the data queue-length. Particularly, the number of active RF chains is determined by comparing the current queue-length to the predefined thresholds, the values of which are able to control the tradeoff between the energy saving and quality of service, i.e., delay. Simulation results show that the proposed scheme saves more energy compared with conventional schemes which is designed regardless the traffic variations, and the saving gain increases when the average traffic load decreases.
Stationary and mobile battery energy storage systems for smart grids

Renewable energy is a key technology in reducing global carbon dioxide emissions. Currently, penetration of intermittent renewable energies in most power grids is low, such that the impact of renewable energy's intermittency on grid stability is controllable. Utility scale energy storage systems can enhance stability of power grids with increasing share of intermittent renewable energies. With the grid communication network in smart grids, mobile battery systems in battery electric vehicles and plug-in hybrid electric vehicles can also be used for energy storage and ancillary services in smart grids. This paper will review the stationary and mobile battery systems for grid voltage and frequency stability control in smart grids with increasing shares of intermittent renewable energies. An optimization algorithm on vehicle-to-grid operation will also be presented.
Early predictors of adolescent aggression and adult violence.

The Cambridge Study in Delinquent Development is a prospective longitudinal survey of 411 London males from ages 8 years old to 32 years old. This article investigates the prediction of adolescent aggression (ages 12-14 years old), teenage violence (ages 16-18 years old), adult violence (age 32 years old), and convictions for violence. Generally, the best predictors were measures of economic deprivation, family criminality, poor child-rearing, school failure, hyperactivity-impulsivity-attention deficit, and antisocial child behavior. Similar predictors applied to all four measures of aggression and violence. It is concluded that aggression and violence are elements of a more general antisocial tendency, and that the predictors of aggression and violence are similar to the predictors of antisocial and criminal behavior in general.
Human adipose tissue is a source of multipotent stem cells.

Much of the work conducted on adult stem cells has focused on mesenchymal stem cells (MSCs) found within the bone marrow stroma. Adipose tissue, like bone marrow, is derived from the embryonic mesenchyme and contains a stroma that is easily isolated. Preliminary studies have recently identified a putative stem cell population within the adipose stromal compartment. This cell population, termed processed lipoaspirate (PLA) cells, can be isolated from human lipoaspirates and, like MSCs, differentiate toward the osteogenic, adipogenic, myogenic, and chondrogenic lineages. To confirm whether adipose tissue contains stem cells, the PLA population and multiple clonal isolates were analyzed using several molecular and biochemical approaches. PLA cells expressed multiple CD marker antigens similar to those observed on MSCs. Mesodermal lineage induction of PLA cells and clones resulted in the expression of multiple lineage-specific genes and proteins. Furthermore, biochemical analysis also confirmed lineage-specific activity. In addition to mesodermal capacity, PLA cells and clones differentiated into putative neurogenic cells, exhibiting a neuronal-like morphology and expressing several proteins consistent with the neuronal phenotype. Finally, PLA cells exhibited unique characteristics distinct from those seen in MSCs, including differences in CD marker profile and gene expression.
Physiological Stresses Related to Hypercapnia during Patrols on Submarines

Schaefer, K. E. 1979. Physiological stresses related to hypercapnia during patrols on submarines. Undersea Biomed. S47.—Physiological studies on hypercapnic effects carried out on 13 Polaris patrols are summarized. The average C02 concentrations ranged from 0.7-1% C02; C02 was identified as the only environmental contaminant of the submarine atmosphere that has a direct effect on respiration in the concentration range found in the submarine atmosphere. A comparison has been made of physiological effects produced during 42 days of exposure to 1.5% C02 during laboratory studies (L.S.) with those observed during 50 to 60 days of exposure to 0.7-1% C02 on patrols (P.S.). A close similarity was found in the effects on respiration and blood electrolytes under both conditions. Respiratory minute volume was elevated by 40-63% because of increased tidal volume. The physiological dead space increased 60%. Vital capacity showed a trend toward a decrease. Studies of acid-base balance carried out during patrols demonstrated cyclic changes in blood pH and bicarbonate; pH and blood bicarbonate fell during the first 17 days of exposure, rose during the subsequent 20 days, and decreased again after 40 days. These cycles cannot be explained on the basis of known renal regulations in C02-induced acidosis and were not found during exposure to 1.5% C02. The hypothesis is advanced that these changes in acid-base balance are caused by cycles in C02 uptake and release in bones. The time constants of the bone C02 stores fit the observed length of cycles in acid-base balance. Correlation with cycles of calcium metabolism provides further support for this uypotnesis. Red cell electrolytes showed similar changes under 1.5% C02 (L.S.) and 0.7-1% C02 (P.S.). Red cell sodium increased and potassium decreased. Moreover, red cell calcium also increased under both conditions. The significance of these red cell electrolyte changes in regard to changes in permeability and active transport remains to be clarified. An increased gastric acidity was found during patrol (exposure to 0.80.95% C02). The changes observed during patrols disappeared during the recovery periods.
Fast and robust hand tracking using detection-guided optimization

Markerless tracking of hands and fingers is a promising enabler for human-computer interaction. However, adoption has been limited because of tracking inaccuracies, incomplete coverage of motions, low framerate, complex camera setups, and high computational requirements. In this paper, we present a fast method for accurately tracking rapid and complex articulations of the hand using a single depth camera. Our algorithm uses a novel detectionguided optimization strategy that increases the robustness and speed of pose estimation. In the detection step, a randomized decision forest classifies pixels into parts of the hand. In the optimization step, a novel objective function combines the detected part labels and a Gaussian mixture representation of the depth to estimate a pose that best fits the depth. Our approach needs comparably less computational resources which makes it extremely fast (50 fps without GPU support). The approach also supports varying static, or moving, camera-to-scene arrangements. We show the benefits of our method by evaluating on public datasets and comparing against previous work.
Effects of home-based exercise intervention on health-related quality of life for patients with ankylosing spondylitis: a meta-analysis

The objective of this paper was to objectively evaluate the effectiveness of home-based exercise interventions for improving health-related quality of life in patients with ankylosing spondylitis (AS). Databases including PubMed, Web of Science, EMBASE, Ovid-Medline, and The Cochrane Library were electronically searched published from inception through October 2014 involving home-based exercise intervention in AS patients. Studies that measured the Bath Ankylosing Spondylitis Functional Index (BASFI), the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), depression and pain as outcomes were included. Studies involving patients with multiple diseases or received combinations of other interventions were excluded. Two independent investigators screened the identified articles, extracted the data, and assessed the methodological quality of the included studies. Qualitative descriptions were conducted, and quantitative analysis was performed with RevMan software (version 5.2). A total of six studies comprising 1098 participants were included in the study. Meta-analyses showed that home-based exercise interventions significantly reduced the BASFI scores (MD = −0.39, 95 % CI −0.57, −0.20, p = 0.001), BASDAI scores (MD = −0.50, 95 % CI −0.99, −0.02, p = 0.04), depression scores (MD = −2.31, 95 % CI −3.33, −1.30, p = 0.001), and for pain scores because of different evaluation methods among these studies; therefore, a subgroup analysis should be conducted for comparison. The results show that home-based exercise interventions can effectively improve the health-related quality of life in patients with AS. The benefit and clinical performance of home-based exercise care requires further investigation by a series of multicenter, large-sample size randomized controlled trails.
Muscle size and strength are increased following walk training with restricted venous blood flow from the leg muscle, Kaatsu-walk training.

Previous studies have shown that low-intensity resistance training with restricted muscular venous blood flow (Kaatsu) causes muscle hypertrophy and strength gain. To investigate the effects of daily physical activity combined with Kaatsu, we examined the acute and chronic effects of walk training with and without Kaatsu on MRI-measured muscle size and maximum dynamic (one repetition maximum) and isometric strength, along with blood hormonal parameters. Nine men performed Kaatsu-walk training, and nine men performed walk training alone (control-walk). Training was conducted two times a day, 6 days/wk, for 3 wk using five sets of 2-min bouts (treadmill speed at 50 m/min), with a 1-min rest between bouts. Mean oxygen uptake during Kaatsu-walk and control-walk exercise was 19.5 (SD 3.6) and 17.2 % (SD 3.1) of treadmill-determined maximum oxygen uptake, respectively. Serum growth hormone was elevated (P < 0.01) after acute Kaatsu-walk exercise but not in control-walk exercise. MRI-measured thigh muscle cross-sectional area and muscle volume increased by 4-7%, and one repetition maximum and maximum isometric strength increased by 8-10% in the Kaatsu-walk group. There was no change in muscle size and dynamic and isometric strength in the control-walk group. Indicators of muscle damage (creatine kinase and myoglobin) and resting anabolic hormones did not change in both groups. The results suggest that the combination of leg muscle blood flow restriction with slow-walk training induces muscle hypertrophy and strength gain, despite the minimal level of exercise intensity. Kaatsu-walk training may be a potentially useful method for promoting muscle hypertrophy, covering a wide range of the population, including the frail and elderly.
Visualizing Geospatial Information Uncertainty: What We Know and What We Need to Know

Developing reliable methods for representing and managing information uncertainty remains a persistent and relevant challenge to GIScience. Information uncertainty is an intricate idea, and recent examinations of this concept have generated many perspectives on its representation and visualization, with perspectives emerging from a wide range of disciplines and application contexts. In this paper, we review and assess progress toward visual tools and methods to help analysts manage and understand information uncertainty. Specifically, we report on efforts to conceptualize uncertainty, decision making with uncertainty, frameworks for representing uncertainty, visual representation and user control of displays of information uncertainty, and evaluative efforts to assess the use and usability of visual methods of uncertainty. We conclude by identifying seven key research challenges in visualizing information uncertainty, particularly as it applies to decision making and analysis.
Building Empathy: Scaling User Research for Organizational Impact

Building user empathy in a tech organization is crucial to ensure that products are designed with an eye toward user needs and experiences. The Pokerface program is a Google internal user empathy campaign with 26 researchers that helped more than 1500 employees-including engineers, product managers, designers, analysts, and program managers across more than 15 sites-have first-hand experiences with their users. Here, we discuss the goals of the Pokerface program, some challenges that we have faced during execution, and the impact we have measured thus far.
Pole-Like Road Object Detection From Mobile Lidar System Using a Coarse-to-Fine Approach

The requirements of three-dimensional (3-D) road objects have increased for various applications, such as geographic information systems and intelligent transportation systems. The use of mobile lidar systems (MLSs) running along road corridors is an effective way to collect accurate road inventories, but MLS feature extraction is challenged by the blind scanning characteristics of lidar systems and the huge amount of data involved; therefore, an automatic process for MLS data is required to improve efficiency of feature extraction. This study developed a coarse-to-fine approach for the extraction of pole-like road objects from MLS data. The major work consists of data preprocessing, coarse-to-fine segmentation, and detection. In data preprocessing, points from different trajectories were reorganized into road parts, and building facades alongside road corridors were removed to reduce their influence. Then, a coarse-to-fine computational framework for the detection of pole-like objects that segments point clouds was proposed. The results show that the pole-like object detection rate for the proposed method was about 90%, and the proposed coarse-to-fine framework was more efficient than the single-scale framework. These results indicate that the proposed method can be used to effectively extract pole-like road objects from MLS data.
Scalable and Efficient Probabilistic Topic Model Inference for Textual Data

Probabilistic topic models have proven to be an extremely versatile class of mixed-membership models for discovering the thematic structure of text collections. There are many possible applications, covering a broad range of areas of study: technology, natural science, social science and the humanities. In this thesis, a new efficient parallel Markov Chain Monte Carlo inference algorithm is proposed for Bayesian inference in large topic models. The proposed methods scale well with the corpus size and can be used for other probabilistic topic models and other natural language processing applications. The proposed methods are fast, efficient, scalable, and will converge to the true posterior distribution. In addition, in this thesis a supervised topic model for high-dimensional text classification is also proposed, with emphasis on interpretable document prediction using the horseshoe shrinkage prior in supervised topic models. Finally, we develop a model and inference algorithm that can model agenda and framing of political speeches over time with a priori defined topics. We apply the approach to analyze the evolution of immigration discourse in the Swedish parliament by combining theory from political science and communication science with a probabilistic topic model.
Preschool Drawing and School Mathematics: The Nature of the Association.

The study examined the etiology of individual differences in early drawing and of its longitudinal association with school mathematics. Participants (N = 14,760), members of the Twins Early Development Study, were assessed on their ability to draw a human figure, including number of features, symmetry, and proportionality. Human figure drawing was moderately stable across 6 months (average r = .40). Individual differences in drawing at age 4½ were influenced by genetic (.21), shared environmental (.30), and nonshared environmental (.49) factors. Drawing was related to later (age 12) mathematical ability (average r = .24). This association was explained by genetic and shared environmental factors that also influenced general intelligence. Some genetic factors, unrelated to intelligence, also contributed to individual differences in drawing.
A Current-mode ADC with Current Exchanging and Averaging Capabilities by Switching the Currents and Calculating Data in the Digital Domain

A 2 V, 25 MS/s, current-mode and pipelined analog-to-digital converter (ADC) which realizes a 1.5-bit bit-block architecture and uses a front-end current-mode sample-and-hold (S/H) circuit is described. In order to obtain the precise output current without suffering from poor current mismatch in a bit-block, the input and output currents in a current-mirror circuit are exchanged at every clock period. This produces signal currents at the output of a bit-block with positive and negative mismatch errors in turn. Since the analog-to-digital (A-D) converted digital codes of a bit-block contain these positive and negative mismatch errors, the errors are canceled out by taking the average of the consecutive digital codes at the output part of the ADC. A current-mode ADC using this proposed scheme has been fabricated by using 0.25 mum CMOS devices. The results show that the effective number of bits (ENOB) is 7.6, that the spurious-free dynamic range (SFDR) is 48 dB, with a 20 MHz clock from a 2 V supply voltage.
An overview of the saturn project

We present an overview of the Saturn program analysis system, including a rationale for three major design decisions: the use of function-at-a-time, or summary-based, analysis, the use of constraints, and the use of a logic programming language to express program analysis algorithms. We argue that the combination of summaries and constraints allows Saturn to achieve both great scalability and great precision, while the use of a logic programming language with constraints allows for succinct, high-level expression of program analyses.
Minimal Invasive Percutaneous Fixation of Thoracic and Lumbar Spine Fractures

We studied 122 patients with 163 fractures of the thoracic and lumbar spine undergoing the surgical treatment by percutaneous transpedicular fixation and stabilization with minimally invasive technique. Patient followup ranged from 6 to 72 months (mean 38 months), and the patients were assessed by clinical and radiographic evaluation. The results show that percutaneous transpedicular fixation and stabilization with minimally invasive technique is an adequate and satisfactory procedure to be used in specific type of the thoracolumbar and lumbar spine fractures.
Towards seamless interaction between physical and virtual locations for asymmetric collaboration

Virtual Reality allows rapid prototyping and simulation of physical artefacts, which would be difficult and expensive to perform otherwise. On the other hand, when the design process is complex and involves multiple stakeholders, decisions are taken in meetings hosted in the physical world. In the case of aerospace industrial designs, the process is accelerated by having asymmetric collaboration between the two locations: experts discuss the possibilities in a meeting room while a technician immersed in VR tests the selected alternatives. According to experts, the current approach is not without limitations, and in this work, we present prototypes designed to tackle them. The described artefacts were created to address the main issues: awareness of the remote location, remote interaction and manipulation, and navigation between locations. First feedback from experts regarding the prototypes is also presented. The resulting design considerations can be used in other asymmetric collaborative scenarios.
A Controlled Natural Language Interface for Semantic Media Wiki Using the Rabbit Language

Despite of their potential value as collaborative knowledge editing systems, semantic wikis present a number of usability challenges. In particular, there are several mismatches between the simple user interaction mechanisms of wikis (which are the key to the success of wikis) and the need for users to create, edit and understand structured knowledge content (e.g., in the form of RDF or OWL ontologies). In this paper, we present a Controlled Natural Language (CNL) approach to support collaborative ontology development on Semantic MediaWiki (SMW). In order to support the expressivity required for OWL ontology development we were obliged to extend the representational substructure of the SMW system with an OWL meta model using a template-based mechanism. To improve usability, we provided a guided input interface based on semantic forms and output several CNL verbalisers including Rabbit English, Rabbit Chinese (Yayan) and Ace English. As such, this work may provide a potentially effective mechanism for encouraging the largescale collaborative creation of semantically-enriched online content.
Android mobile app for real-time bilateral Arabic sign language translation using leap motion controller

This paper introduces an android mobile App for real-time bilateral Arabic sign language translation. The system is designed to operate on isolated sign language words. The mobile App has four main components; sign language capture for training, sign language capture for translation, voice to sign language translation and a sign language quiz game. Therefore, the Mobile App can be used for bilateral communication with the deaf community. Acquisition of sign language words is performed using a portable Leap Motion Controller that is connected to the USB of the mobile phone through an OTG adapter. We use simple feature extraction approaches based on statistical features such as mean, variance and covariance. We also use simple classification approach based on the minimum distance classifier. Classification results performed using 15 different sign language words revealed that excellent classification results are achieved. In comparison to a similar system that uses data gloves, our system has the advantage of higher accuracy and the advantage of real-time processing using a mobile App.