nils-herrmann/clean_scirepeval huggingface dataset:
Robotic versus Open Partial Nephrectomy: A Systematic Review and Meta-Analysis

To critically review the currently available evidence of studies comparing robotic partial nephrectomy (RPN) and open partial nephrectomy (OPN).



A comprehensive review of the literature from Pubmed, Web of Science and Scopus was performed in October 2013. All relevant studies comparing RPN with OPN were included for further screening. A cumulative meta-analysis of all comparative studies was performed and publication bias was assessed by a funnel plot.



Eight studies were included for the analysis, including a total of 3418 patients (757 patients in the robotic group and 2661 patients in the open group). Although RPN procedures had a longer operative time (weighted mean difference [WMD]: 40.89; 95% confidence interval [CI], 14.39-67.40; p = 0.002), patients in this group benefited from a lower perioperative complication rate (19.3% for RPN and 29.5% for OPN; odds ratio [OR]: 0.53; 95%CI, 0.42-0.67; p<0.00001), shorter hospital stay (WMD: -2.78; 95%CI, -3.36 to -1.92; p<0.00001), less estimated blood loss(WMD: -106.83; 95%CI, -176.4 to -37.27; p = 0.003). Transfusions, conversion to radical nephrectomy, ischemia time and estimated GFR change, margin status, and overall cost were comparable between the two techniques. The main limitation of the present meta-analysis is the non-randomization of all included studies.



RPN appears to be an efficient alternative to OPN with the advantages of a lower rate of perioperative complications, shorter length of hospital stay and less blood loss. Nevertheless, high quality prospective randomized studies with longer follow-up period are needed to confirm these findings.
Automatic contrast enhancement of complex low-contrast images

The problem of operative (in real-time) contrast enhancement of complex monochrome images in the automatic mode is considered. A new method of contrast enhancement by statistical non-inertial transformation of image is proposed on the basis of an analysis of the values of integral image contrast for all possible values of adaptation level. A comparative analysis of the effectiveness of the proposed and known histogram-based methods of automatic contrast enhancement for a series of low-contrast monochrome images with a complex structure with using the known no-reference contrast metrics is carried out.
Conventions and Commitments in Distributed CSCW Groups

Conventions are necessary to establish in any recurrentcooperative arrangement. In electronic work, they are importantso as to regulate the use of shared objects. Based on empiricalresults from a long-term study of a group cooperating inelectronic work, I present examples showing that the group failedto develop normative convention behavior. These difficulties informing conventions can be attributed to a long list of factors:the lack of clear precedents, different perspectives among groupmembers, a flexible cooperation media, limited communication, thedesign process, and discontinuous cooperation. Further, I arguethat commitments to the conventions were difficult, due to theconventions not reaching an acceptance threshold, uneven payoffs,and weak social influences. The empirical results call for aspecific set of awareness information requirements to promoteactive learning about the group activity in order to support thearticulation of conventions. The requirements focus on the roleof feedback as a powerful mechanism for shaping and learningabout group behavior.
IEEE 802.22: An Introduction to the First Wireless Standard based on Cognitive Radios

In November/2004, we witnessed the formation of the first worldwide effort to define a novel wireless air interface (i.e., MAC and PHY) standard based on Cognitive Radios (CRs): the IEEE 802.22 Working Group (WG). The IEEE 802.22 WG is chartered with the development of a CR-based Wireless Regional Area Network (WRAN) Physical (PHY) and Medium Access Control (MAC) layers for use by license-exempt devices in the spectrum that is currently allocated to the Television (TV) service. Since 802.22 is required to reuse the fallow TV spectrum without causing any harmful interference to incumbents (i.e., the TV receivers), cognitive radio techniques are of primary importance in order to sense and measure the spectrum and detect the presence/absence of incumbent signals. On top of that, other advanced techniques that facilitate coexistence such as dynamic spectrum management and radio environment characterization could be designed. In this paper, we provide a detailed overview of the 802.22 draft specification, its architecture, requirements, applications, and coexistence considerations. These not only form the basis for the definition of this groundbreaking wireless air interface standard, but will also serve as foundation for future research in the promising area of CRs. Index Terms – Cognitive radio, incumbent, sensing, spectrum agility, IEEE 802.22, coexistence.
Neural representations for object perception: structure, category, and adaptive coding.

Object perception is one of the most remarkable capacities of the primate brain. Owing to the large and indeterminate dimensionality of object space, the neural basis of object perception has been difficult to study and remains controversial. Recent work has provided a more precise picture of how 2D and 3D object structure is encoded in intermediate and higher-level visual cortices. Yet, other studies suggest that higher-level visual cortex represents categorical identity rather than structure. Furthermore, object responses are surprisingly adaptive to changes in environmental statistics, implying that learning through evolution, development, and also shorter-term experience during adulthood may optimize the object code. Future progress in reconciling these findings will depend on more effective sampling of the object domain and direct comparison of these competing hypotheses.
Mining product reputations on the Web

Knowing the reputations of your own and/or competitors' products is important for marketing and customer relationship management. It is, however, very costly to collect and analyze survey data manually. This paper presents a new framework for mining product reputations on the Internet. It automatically collects people's opinions about target products from Web pages, and it uses text mining techniques to obtain the reputations of those products.On the basis of human-test samples, we generate in advance syntactic and linguistic rules to determine whether any given statement is an opinion or not, as well as whether such any opinion is positive or negative in nature. We first collect statements regarding target products using a general search engine, and then, using the rules, extract opinions from among them and attach three labels to each opinion, labels indicating the positive/negative determination, the product name itself, and an numerical value expressing the degree of system confidence that the statement is, in fact, an opinion. The labeled opinions are then input into an opinion database.The mining of reputations, i.e., the finding of statistically meaningful information included in the database, is then conducted. We specify target categories using label values (such as positive opinions of product A) and perform four types of text mining: extraction of 1) characteristic words, 2) co-occurrence words, 3) typical sentences, for individual target categories, and 4) correspondence analysis among multiple target categories.Actual marketing data is used to demonstrate the validity and effectiveness of the framework, which offers a drastic reduction in the overall cost of reputation analysis over that of conventional survey approaches and supports the discovery of knowledge from the pool of opinions on the web.
Videos as Space-Time Region Graphs

How do humans recognize the action “opening a book”? We argue that there are two important cues: modeling temporal shape dynamics and modeling functional relationships between humans and objects. In this paper, we propose to represent videos as space-time region graphs which capture these two important cues. Our graph nodes are defined by the object region proposals from different frames in a long range video. These nodes are connected by two types of relations: (i) similarity relations capturing the long range dependencies between correlated objects and (ii) spatial-temporal relations capturing the interactions between nearby objects. We perform reasoning on this graph representation via Graph Convolutional Networks. We achieve state-of-the-art results on both Charades and Something-Something datasets. Especially for Charades, we obtain a huge 4.4% gain when our model is applied in complex environments.
Frame-by-frame language identification in short utterances using deep neural networks

This work addresses the use of deep neural networks (DNNs) in automatic language identification (LID) focused on short test utterances. Motivated by their recent success in acoustic modelling for speech recognition, we adapt DNNs to the problem of identifying the language in a given utterance from the short-term acoustic features. We show how DNNs are particularly suitable to perform LID in real-time applications, due to their capacity to emit a language identification posterior at each new frame of the test utterance. We then analyse different aspects of the system, such as the amount of required training data, the number of hidden layers, the relevance of contextual information and the effect of the test utterance duration. Finally, we propose several methods to combine frame-by-frame posteriors. Experiments are conducted on two different datasets: the public NIST Language Recognition Evaluation 2009 (3 s task) and a much larger corpus (of 5 million utterances) known as Google 5M LID, obtained from different Google Services. Reported results show relative improvements of DNNs versus the i-vector system of 40% in LRE09 3 second task and 76% in Google 5M LID.
Comprehensive analysis and comparative evaluation of the isolated true bridgeless Cuk single-phase PFC rectifier system

In the public low voltage mains the stress caused by harmonic currents is strongly increased due to the higher demand of electronic equipment in everyday use. Therefore, standards were created in order to limit the harmonic currents injected into the network, thus maintaining a high voltage quality of these networks. Hence, converter systems with active PFC are indispensable, where in general the compliance of the created directives for lower harmonics can be easily fulfilled. Typically, in single-phase systems, boost PFC converter topologies are used, which offer a wide input voltage range and a controlled output voltage. Depending on the underlying applications, a subsequent reduction and/or isolation of the output voltage based on a DC/DC-converter is needed. The major disadvantages of this converter cascading are the reduction of the overall efficiency, the large component count and the increasing control complexity. In comparison to the conventional two-stage PFC converter system, the true bridgeless Cuk PFC rectifier system can perform the PFC functionality and the galvanic isolation in a single-stage, thus eliminating the mentioned disadvantages. In this paper a comprehensive analysis of the operation, design and limits of the recently proposed single-stage Cuk concept is investigated. In addition, a comparative evaluation concerning efficiency and power density against a conventional two-stage approach based on bridgeless PFC rectifier and a subsequent LLC-resonant DC/DC-converter is presented.
A neural network students' performance prediction model (NNSPPM)

In the academic industry, students' early performance prediction is important to academic communities so that strategic intervention can be planned before students reach the final semester. This paper presents a study on Artificial Neural Network (ANN) model development in predicting academic performance of engineering students. Cumulative Grade Point Average (CGPA) was used to measure the academic achievement at semester eight. The study was conducted at the Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM), Malaysia. Students' results for the fundamental subjects in the first semester were used as independent variables or input predictor variables while CGPA at semester eight was used as the output or the dependent variable. The study was done for two different entry points namely Matriculation and Diploma intakes. Performances of the models were measured using the coefficient of Correlation R and Mean Square Error (MSE). The outcomes from the study showed that fundamental subjects at semester one and three have strong influence in the final CGPA upon graduation.
Properties of cutaneous mechanoreceptors in the human hand-related to touch sensation

Recordings from single peripheral nerve fibres made it possible to analyse the functional properties of tactile afferent units supplying the glabrous skin of the human hand and to assess directly the relation between impulse discharge and perceptive experiences. The 17,000 tactile units in this skin area of the human hand are of four different types: two fast adapting types, FA I and FA I1 (formerly RA and PC), and two slowly adapting types, SA I and SA 11. The receptive field characteristics and the densities in the skin of the type I units (FA I and SA I) indicate that these account for the detailed spatial resolution that is of paramount importance for the motor skill and the explorative role of the hand. The relationship between the stimulus amplitude and perceived intensity during sustained skin indentations did not match the corresponding stimulus response functions of SA units suggesting non-linear transformations within the central nervous system. These transformations, in turn, appear to vary between subjects. A single impulse in a single FA I unit may be felt when originating from the most important tactile regions of the hand, indicating that the psychophysical detection may be set by the threshold of the sense organs. Moreover, no significant noise seems to be superimposed in the respective central sensory pathways.
Differential effects of mindful breathing, progressive muscle relaxation, and loving-kindness meditation on decentering and negative reactions to repetitive thoughts.

Decentering has been proposed as a potential mechanism of mindfulness-based interventions but has received limited empirical examination to date in experimental studies comparing mindfulness meditation to active comparison conditions. In the present study, we compared the immediate effects of mindful breathing (MB) to two alternative stress-management techniques: progressive muscle relaxation (PMR) and loving-kindness meditation (LKM) to test whether decentering is unique to mindfulness meditation or common across approaches. Novice meditators (190 female undergraduates) were randomly assigned to complete one of three 15-min stress-management exercises (MB, PMR, or LKM) presented by audio recording. Immediately after the exercise, participants completed measures of decentering, frequency of repetitive thoughts during the exercise, and degree of negative reaction to thoughts. As predicted, participants in the MB condition reported greater decentering relative to the other two conditions. The association between frequency of repetitive thought and negative reactions to thoughts was relatively weaker in the MB condition than in the PMR and LKM conditions, in which these two variables were strongly and positively correlated. Consistent with the construct of decentering, the relative independence between these two variables in the MB condition suggests that mindful breathing may help to reduce reactivity to repetitive thoughts. Taken together, results help to provide further evidence of decentering as a potential mechanism that distinguishes mindfulness practice from other credible stress-management approaches.
Pain: a review of three commonly used pain rating scales.

This review aims to explore the research available relating to three commonly used pain rating scales, the Visual Analogue Scale, the Verbal Rating Scale and the Numerical Rating Scale. The review provides information needed to understand the main properties of the scales.



Data generated from pain-rating scales can be easily misunderstood. This review can help clinicians to understand the main features of these tools and thus use them effectively.



A MedLine review via PubMed was carried out with no restriction of age of papers retrieved. Papers were examined for methodological soundness before being included. The search terms initially included pain rating scales, pain measurement, Visual Analogue Scale, VAS, Verbal Rating Scale, VRS, Numerical/numeric Rating Scale, NRS. The reference lists of retrieved articles were used to generate more papers and search terms. Only English Language papers were examined.



All three pain-rating scales are valid, reliable and appropriate for use in clinical practice, although the Visual Analogue Scale has more practical difficulties than the Verbal Rating Scale or the Numerical Rating Scale. For general purposes the Numerical Rating Scale has good sensitivity and generates data that can be statistically analysed for audit purposes. Patients who seek a sensitive pain-rating scale would probably choose this one. For simplicity patients prefer the Verbal Rating Scale, but it lacks sensitivity and the data it produces can be misunderstood.


 TO CLINICAL PRACTICE
In order to use pain-rating scales well clinicians need to appreciate the potential for error within the tools, and the potential they have to provide the required information. Interpretation of the data from a pain-rating scale is not as straightforward as it might first appear.
The restless engram: consolidations never end.

Memory consolidation is the hypothetical process in which an item in memory is transformed into a long-term form. It is commonly addressed at two complementary levels of description and analysis: the cellular/synaptic level (synaptic consolidation) and the brain systems level (systems consolidation). This article focuses on selected recent advances in consolidation research, including the reconsolidation of long-term memory items, the brain mechanisms of transformation of the content and of cue-dependency of memory items over time, as well as the role of rest and sleep in consolidating and shaping memories. Taken together, the picture that emerges is of dynamic engrams that are formed, modified, and remodified over time at the systems level by using synaptic consolidation mechanisms as subroutines. This implies that, contrary to interpretations that have dominated neuroscience for a while, but similar to long-standing cognitive concepts, consolidation of at least some items in long-term memory may never really come to an end.
SATIRE: a software architecture for smart AtTIRE

Personal instrumentation and monitoring services that collect and archive the physical activities of a user have recently been introduced for various medical, personal, safety, and entertainment purposes. A general software architecture is needed to support different categories of such monitoring services. This paper presents a software architecture, implementation, and preliminary evaluation of SATIRE, a wearable personal monitoring service transparently embedded in user garments. SATIRE records the owner's activity and location for subsequent automated uploading and archiving. The personal archive can later be searched for particular events to answer questions regarding past and present user activity, location, and behavior patterns. A short feasibility and usage study of a prototype based on MicaZ motes provides a proof of concept for the SATIRE architecture.
changepoint: An R Package for Changepoint Analysis

One of the key challenges in changepoint analysis is the ability to detect multiple changes within a given time series or sequence. The changepoint package has been developed to provide users with a choice of multiple changepoint search methods to use in conjunction with a given changepoint method and in particular provides an implementation of the recently proposed PELT algorithm. This article describes the search methods which are implemented in the package as well as some of the available test statistics whilst highlighting their application with simulated and practical examples. Particular emphasis is placed on the PELT algorithm and how results differ from the binary segmentation approach.
Tailoring graph-coloring register allocation for runtime compilation

Just-in-time compilers are invoked during application execution and therefore need to ensure fast compilation times. Consequently, runtime compiler designers are averse to implementing compile-time intensive optimization algorithms. Instead, they tend to select faster but less effective transformations. In this paper, we explore this trade-off for an important optimization - global register allocation. We present a graph-coloring register allocator that has been redesigned for runtime compilation. Compared to Chaitin- Briggs [7], a standard graph-coloring technique, the reformulated algorithm requires considerably less allocation time and produces allocations that are only marginally worse than those of Chaitin-Briggs. Our experimental results indicate that the allocator performs better than the linear-scan and Chaitin-Briggs allocators on most benchmarks in a runtime compilation environment. By increasing allocation efficiency and preserving optimization quality, the presented algorithm increases the suitability and profitability of a graph-coloring register allocation strategy for a runtime compiler.
Forecasting seasonal time series with computational intelligence: On recent methods and the potential of their combinations

Accurate time series forecasting is a key issue to support individual and organizational decision making. In this paper, we introduce novel methods for multi-step seasonal time series forecasting. All the presented methods stem from computational intelligence techniques: evolutionary artificial neural networks, support vector machines and genuine linguistic fuzzy rules. Performance of the suggested methods is experimentally justified on seasonal time series from distinct domains on three forecasting horizons. The most important contribution is the introduction of a new hybrid combination using linguistic fuzzy rules and the other computational intelligence methods. This hybrid combination presents competitive forecasts, when compared with the popular ARIMA method. Moreover, such hybrid model is more easy to interpret by decision-makers when modeling trended series.
Value of Information Systems and Products : Understanding the Users ’ Perspective and Values

Developers aim at providing value through their systems and products. However, value is not financial only, but depends on usage and users’ perceptions of value. In this paper, we clarify the concept of value from the users’ perspective and the role of user involvement in providing value. First, theories and approaches of psychology, marketing and human-computer interaction are reviewed. Secondly, the concept of ‘user values’ is suggested to clarify the concept of value from the user’s point of view and a category framework of user values is presented to make them more concrete and easier to identify. Thirdly, the activities and methods for adopting user values in development work are discussed. The analysis of the literature shows that value has been considered in multiple ways in development. However, users’ perspectives have received less attention. As a conclusion, we draw future research directions for value-centered design and propose that user involvement is essential in identifying user values, interpreting the practical meaning of the values and implementing them in development work.