nils-herrmann/clean_scirepeval huggingface dataset:
Inter-app Communication in Android: Developer Challenges

The Android platform is designed to support mutually untrusted third-party apps, which run as isolated processes but may interact via platform-controlled mechanisms, called Intents. Interactions among third-party apps are intended and can contribute to a rich user experience, for example, the ability to share pictures from one app with another. The Android platform presents an interesting point in a design space of module systems that is biased toward isolation, extensibility, and untrusted contributions. The Intent mechanism essentially provides message channels among modules, in which the set of message types is extensible. However, the module system has design limitations including the lack of consistent mechanisms to document message types, very limited checking that a message conforms to its specifications, the inability to explicitly declare dependencies on other modules, and the lack of checks for backward compatibility as message types evolve over time. In order to understand the degree to which these design limitations result in real issues, we studied a broad corpus of apps and cross-validated our results against app documentation and Android support forums. Our findings suggest that design limitations do indeed cause development problems. Based on our results, we outline further research questions and propose possible mitigation strategies.
Potential Role of Tc-99m DTPA Diuretic Renal Scan in the Diagnosis of Calyceal Diverticulum in Children

The aim of the study was to assess the usefulness of Technetium-99m diethylene triamine pentaacetic acid (Tc-99m DTPA) diuretic scan to diagnose calyceal diverticulum (CD). From January 2000 to June 2014, children with evidence of renal cystic lesions of undetermined diagnosis on ultrasound were enrolled. Computed tomography urography (CTU) and Tc-99m DTPA diuretic scan were performed to characterize the precise anatomy. The diagnosis of CD depended on visualization of a renal cystic lesion with filling of contrast material or radiotracer from the collecting system on CTU or diuretic renal scan. Children who had positive findings of CD on 1 or both imaging studies were selected and analyzed. Both CTU and Tc-99m DTPA diuretic renal scan were performed in 39 children. A total of 9 (23.1 %) children with CD were diagnosed. All 9 children had positive diagnosis of CD on diuretic renal scan. Only 6 (66.7%) children could be diagnosed by CTU, and CD was missed by CTU in 3 subjects. The differential renal functions in patients with CD were 46% to 55%. The time of radiotracer appearance in the CD ranged from the 8th to the 24th minute. Seven patients had persistent accumulation of radiotracer in their CD at the end of the study. Tc-99m DTPA diuretic renal scan seems to be more sensitive than CTU in diagnosing CD. The possible reasons of higher sensitivity are discussed. Additional advantages that Tc-99m DTPA diuretic renal scan provides include the following: continuous monitoring, less radiation doses, and information on renal function, making it an attractive alternative to CTU for diagnosis of CD.
HUMANISM IN THE RENAISSANCE

In a letter to Paul of Middleburg in 1492 Marsilio Ficino, Renaissance philosopher, philologist and physician, referred to his own times as ‘a golden age which has restored to light the liberal arts which were almost extinct’. History has not successfully refuted his claim. The term ‘La Rinascita’ or ‘rebirth’ was coined by Giorgio Vasari (1511-74), painter, architect and art historian, in his Vite (Lives of the Artists, 1550) to describe developments from 14th to 16th century Italy in the visual arts that brought art closer to nature.
Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data

A brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI) is presented which allows human subjects to observe and control changes of their own blood oxygen level-dependent (BOLD) response. This BCI performs data preprocessing (including linear trend removal, 3D motion correction) and statistical analysis on-line. Local BOLD signals are continuously fed back to the subject in the magnetic resonance scanner with a delay of less than 2 s from image acquisition. The mean signal of a region of interest is plotted as a time-series superimposed on color-coded stripes which indicate the task, i.e., to increase or decrease the BOLD signal. We exemplify the presented BCI with one volunteer intending to control the signal of the rostral-ventral and dorsal part of the anterior cingulate cortex (ACC). The subject achieved significant changes of local BOLD responses as revealed by region of interest analysis and statistical parametric maps. The percent signal change increased across fMRI-feedback sessions suggesting a learning effect with training. This methodology of fMRI-feedback can assess voluntary control of circumscribed brain areas. As a further extension, behavioral effects of local self-regulation become accessible as a new field of research.
Tourism e-commerce recommender system based on web data mining

Recommender system based on web data mining is widely used in e-commerce for it generates more accurate and objective recommendation results and provides personalized service for web users. This paper makes analysis on some major recommendation methods based on web data mining such as Collaborative Filtering and Association Rules mining, and discusses the practical application of these methods in the tourism e-commerce, and then presents a design of web mining based tourism e-commerce recommender system with offline and online modules.
Expression of Stem Cell Markers in Primo Vessel of Rat

Accumulating line of evidence support that adult tissues contain a rare population of pluripotent stem cells (PSCs), which differentiate into all types of cells in our body. Bonghan microcell (primo microcells (PMCs)) discovered in 1960s was reported to have a pluripotency like a stem cell in vivo as well as in vitro condition. Here, we describe the detailed morphology and molecular features of PMCs. PMCs reside in Bonghan duct (primo vessel (PV)) reported as a corresponding structure of acupuncture points and meridian system. We found that PMCs were frequently observed in the liver surface of the rat between 300 g and 400 g from April to June, suggesting that the their detection frequency depends on the weight, the season, and the organ of rat. As reported, PMCs freshly isolated from PVs were spherical ~1-2  μ m microsized cells. In contrast, a unique bithread or budding-shaped PMCs emerged during tissue culture around 8 days. RT-PCR analysis demonstrated that PVs-derived cells express the Oct4, the most important PSCs gene, in addition to several PSCs markers (Sox2, Stella, Rex1, and Klf4). Thus, we for the first time provide the evidence about Oct4-expressing stem-like characteristics for cells resident in PVs, a possible novel stem cell enriched niche.
Automated Regularization Parameter Selection in Multi-Scale Total Variation Models for Image Restoration

Multi-scale total variation models for image restoration are introduced. The models utilize a spatially dependent regularization parameter in order to enhance image regions containing details while still sufficiently smoothing homogeneous features. The fully automated adjustment strategy of the regularization parameter is based on local variance estimators. For robustness reasons, the decision on the acceptance or rejection of a local parameter value relies on a confidence interval technique based on the expected maximal local variance estimate. In order to improve the performance of the initial algorithm a generalized hierarchical decomposition of the restored image is used. The corresponding subproblems are solved by a superlinearly convergent algorithm based on Fenchel-duality and inexact semismooth Newton techniques. The paper ends by a report on numerical tests, a qualitative study of the proposed adjustment scheme and a comparison with popular total variation based restoration methods.
Sad but true ?-How induced emotional states differentially bias self-rated Big Five personality traits

The Big Five are seen as stable personality traits. This study hypothesized that their measurement via self-ratings is differentially biased by participants’ emotions. The relationship between habitual emotions and personality should be mirrored in a patterned influence of emotional states upon personality scores.  We experimentally induced emotional states and compared baseline Big Five scores of ninety-eight German participants (67 female; mean age 22.2) to their scores after the induction of happiness or sadness. Manipulation checks included the induced emotion’s intensity and durability.  The expected differential effect could be detected for neuroticism and extraversion and as a trend for agreeableness. Post-hoc analyses showed that only sadness led to increased neuroticism and decreased extraversion scores. Oppositely, happiness did not decrease neuroticism, but there was a trend for an elevation on extraversion scores.  Results suggest a specific effect of sadness on self-reported personality traits, particularly on neuroticism. Sadness may trigger different self-concepts in susceptible people, biasing perceived personality. This bias could be minimised by tracking participants’ emotional states prior to personality measurement.
Cybersecurity as an Application Domain for Multiagent Systems

The science of cybersecurity has recently been garnering much attention among researchers and practitioners dissatisfied with the ad hoc nature of much of the existing work on cybersecurity. Cybersecurity offers a great opportunity for multiagent systems research. We motivate cybersecurity as an application area for multiagent systems with an emphasis on normative multiagent systems. First, we describe ways in which multiagent systems could help advance our understanding of cybersecurity and provide a set of principles that could serve as a foundation for a new science of cybersecurity. Second, we argue how paying close attention to the challenges of cybersecurity could expose the limitations of current research in multiagent systems, especially with respect to dealing with considerations of autonomy and interdependence.
Microsurgical replantation for child total scalp avulsion.

Total scalp avulsion is an intractable problem in clinical practice. It often occurs in female adults, but rarely in children. In this article, we described the replantation of 2 scalp segments in a 4-year-old girl. The right segment involved the hairy scalp merely, whereas the left one involved the hairy scalp, forehead, eyelid, ear, and part of the face. Warm ischemia time was about 28 hours, and operation time was 13 hours. Although an explorative operation was performed, the left segment survived partly. A relatively satisfactory aesthetic result was obtained by transplanting split skin from the abdomen and part of the survived right avulsed scalp. According to our experience, every effort should be undertaken to save the avulsed scalp, even in severely damaged and juvenile cases.
Regulation of parkinsonian motor behaviours by optogenetic control of basal ganglia circuitry

Neural circuits of the basal ganglia are critical for motor planning and action selection. Two parallel basal ganglia pathways have been described, and have been proposed to exert opposing influences on motor function. According to this classical model, activation of the ‘direct’ pathway facilitates movement and activation of the ‘indirect’ pathway inhibits movement. However, more recent anatomical and functional evidence has called into question the validity of this hypothesis. Because this model has never been empirically tested, the specific function of these circuits in behaving animals remains unknown. Here we report direct activation of basal ganglia circuitry in vivo, using optogenetic control of direct- and indirect-pathway medium spiny projection neurons (MSNs), achieved through Cre-dependent viral expression of channelrhodopsin-2 in the striatum of bacterial artificial chromosome transgenic mice expressing Cre recombinase under control of regulatory elements for the dopamine D1 or D2 receptor. Bilateral excitation of indirect-pathway MSNs elicited a parkinsonian state, distinguished by increased freezing, bradykinesia and decreased locomotor initiations. In contrast, activation of direct-pathway MSNs reduced freezing and increased locomotion. In a mouse model of Parkinson’s disease, direct-pathway activation completely rescued deficits in freezing, bradykinesia and locomotor initiation. Taken together, our findings establish a critical role for basal ganglia circuitry in the bidirectional regulation of motor behaviour and indicate that modulation of direct-pathway circuitry may represent an effective therapeutic strategy for ameliorating parkinsonian motor deficits.
Three-phase current source GTO rectifier adopting new PWM control techniques

A three-phase current source gate turn-off (GTO) thyristor rectifier is described with a high power factor, low line current distortion, and a simple main circuit. It adopts pulse-width modulation (PWM) control techniques obtained by analyzing the PWM patterns of three-phase current source rectifiers/inverters, and it uses a method of generating such patterns. In addition, by using an optimum set-up of the circuit constants, the GTO switching frequency is reduced to 500 Hz. This rectifier is suitable for large power conversion, because it can reduce GTO switching loss and its snubber loss.<<ETX>>
Bringing Modern Hierarchical Memory Systems Into Focus: A study of architecture and workload factors on system performance

The increasing size of workloads has led to the development of new technologies and architectures that are intended to help address the capacity limitations of DRAM main memories. The proposed solutions fall into two categories: those that re-engineer Flash-based SSDs to further improve storage system performance and those that incorporate non-volatile technology into a Hybrid main memory system. These developments have blurred the line between the storage and memory systems. In this paper, we examine the differences between these two approaches to gain insight into the types of applications and memory technologies that benefit the most from these different architectural approaches.
 In particular this work utilizes full system simulation to examine the impact of workload randomness on system performance, the impact of backing store latency on system performance, and how the different implementations utilize system resources differently. We find that the software overhead incurred by storage based implementations can account for almost 50% of the overall access latency. As a result, backing store technologies that have an access latency up to 25 microseconds tend to perform better when implemented as part of the main memory system. We also see that high degrees of random access can exacerbate the software overhead problem and lead to large performance advantages for the Hybrid main memory approach. Meanwhile, the page replacement algorithm utilized by the OS in the storage approach results in considerably better performance on highly sequential workloads at the cost of greater pressure on the cache.
Nonlinear Distributional Gradient Temporal-Difference Learning

We devise a distributional variant of gradient temporal-difference (TD) learning. Distributional reinforcement learning has been demonstrated to outperform the regular one in the recent study (Bellemare et al., 2017a). In the policy evaluation setting, we design two new algorithms called distributional GTD2 and distributional TDC using the Cramér distance on the distributional version of the Bellman error objective function, which inherits advantages of both the nonlinear gradient TD algorithms and the distributional RL approach. In the control setting, we propose the distributional Greedy-GQ using the similar derivation. We prove the asymptotic almost-sure convergence of distributional GTD2 and TDC to a local optimal solution for general smooth function approximators, which includes neural networks that have been widely used in recent study to solve the real-life RL problems. In each step, the computational complexities of above three algorithms are linear w.r.t. the number of the parameters of the function approximator, thus can be implemented efficiently for neural networks.
Plasticity from muscle to brain

Recognition that the entire central nervous system (CNS) is highly plastic, and that it changes continually throughout life, is a relatively new development. Until very recently, neuroscience has been dominated by the belief that the nervous system is hardwired and changes at only a few selected sites and by only a few mechanisms. Thus, it is particularly remarkable that Sir John Eccles, almost from the start of his long career nearly 80 years ago, focused repeatedly and productively on plasticity of many different kinds and in many different locations. He began with muscles, exploring their developmental plasticity and the functional effects of the level of motor unit activity and of cross-reinnervation. He moved into the spinal cord to study the effects of axotomy on motoneuron properties and the immediate and persistent functional effects of repetitive afferent stimulation. In work that combined these two areas, Eccles explored the influences of motoneurons and their muscle fibers on one another. He studied extensively simple spinal reflexes, especially stretch reflexes, exploring plasticity in these reflex pathways during development and in response to experimental manipulations of activity and innervation. In subsequent decades, Eccles focused on plasticity at central synapses in hippocampus, cerebellum, and neocortex. His endeavors extended from the plasticity associated with CNS lesions to the mechanisms responsible for the most complex and as yet mysterious products of neuronal plasticity, the substrates underlying learning and memory. At multiple levels, Eccles' work anticipated and helped shape present-day hypotheses and experiments. He provided novel observations that introduced new problems, and he produced insights that continue to be the foundation of ongoing basic and clinical research. This article reviews Eccles' experimental and theoretical contributions and their relationships to current endeavors and concepts. It emphasizes aspects of his contributions that are less well known at present and yet are directly relevant to contemporary issues.
Improving the speed of neural networks on CPUs

Recent advances in deep learning have made the use of large, deep neural networks with tens of millions of parameters suitable for a number of applications that require real-time processing. The sheer size of these networks can represent a challenging computational burden, even for modern CPUs. For this reason, GPUs are routinely used instead to train and run such networks. This paper is a tutorial for students and researchers on some of the techniques that can be used to reduce this computational cost considerably on modern x86 CPUs. We emphasize data layout, batching of the computation, the use of SSE2 instructions, and particularly leverage SSSE3 and SSE4 fixed-point instructions which provide a 3× improvement over an optimized floating-point baseline. We use speech recognition as an example task, and show that a real-time hybrid hidden Markov model / neural network (HMM/NN) large vocabulary system can be built with a 10× speedup over an unoptimized baseline and a 4× speedup over an aggressively optimized floating-point baseline at no cost in accuracy. The techniques described extend readily to neural network training and provide an effective alternative to the use of specialized hardware.
The Business Model Ecosystem

There is much knowledge about Business models (BM) (Zott 2009, Zott 2010, Zott 2011, Fielt 2011, Teece 2010, Lindgren 2013) but very little knowledge and research about Business Model Eco system (BMES) – those “ecosystems” where the BM’s really operates and works as value-adding mechanism – objects or “species”. How are these BMES actually constructed – How do they function – what are their characteristics and How can we really define these BMES? There are until now not an accepted language developed for BMES’s nor is the term BMES generally accepted in the BM Literature. This paper intends to commence the journey of building up such language on behalf of case studies within the Wind Mill, Health-, Agriculture-, and Fair line of BMES. A preliminary study of “AS IS” and “TO BE” BM’s related to these BMES present our first findings and preliminary understanding of BMES. The paper attempt to define what is a BMES and the dimensions and components of BMES. In this context we build upon a comprehensive review of academic business and BM literature together with an analogy study to ecological eco systems and ecosystem frameworks. We commence exploring the origin of the term business, BM and ecosystems and then relate this to a proposed BMES framework and the concept of the Multi BM framework (Lindgren 2013).
Scene Graph Parsing as Dependency Parsing

In this paper, we study the problem of parsing structured knowledge graphs from textual descriptions. In particular, we consider the scene graph representation (Johnson et al., 2015) that considers objects together with their attributes and relations: this representation has been proved useful across a variety of vision and language applications. We begin by introducing an alternative but equivalent edgecentric view of scene graphs that connect to dependency parses. Together with a careful redesign of label and action space, we combine the two-stage pipeline used in prior work (generic dependency parsing followed by simple post-processing) into one, enabling end-toend training. The scene graphs generated by our learned neural dependency parser achieve an F-score similarity of 49.67% to ground truth graphs on our evaluation set, surpassing best previous approaches by 5%. We further demonstrate the effectiveness of our learned parser on image retrieval
Design and Analysis of a Hardware CNN Accelerator

In recent years, Convolutional Neural Networks (CNNs) have revolutionized computer vision tasks. However, inference in current CNN designs is extremely computationally intensive. This has lead to an explosion of new accelerator architectures designed to reduce power consumption and latency [20]. In this paper, we design and implement a systolic array based architecture we call ConvAU to efficiently accelerate dense matrix multiplication operations in CNNs. We also train an 8-bit quantized version of Squeezenet[14] and evaluate our accelerator’s power consumption and throughput. Finally, we compare our results to the reported results for the K80 GPU and Google’s TPU. We find that ConvAU gives a 200x improvement in TOPs/W when compared to a NVIDIA K80 GPU and a 1.9x improvement when compared to the TPU.
Trace minerals in fish nutrition

The role of trace elements in biological systems has been described in several animals. However, the knowledge in fish is mainly limited to iron, copper, manganese, zinc and selenium as components of body fluids, cofactors in enzymatic reactions, structural units of non-enzymatic macromolecules, etc. Investigations in fish are comparatively complicated as both dietary intake and waterborne mineral uptake have to be considered in determining the mineral budgets. The importance of trace minerals as essential ingredients in diets, although in small quantities, is also evident in fish.