nils-herrmann/clean_scirepeval huggingface dataset:
Clinical Nurse Leader Integrated Care Delivery to Improve Care Quality: Factors Influencing Perceived Success.

Clinical nurse leader(TM) (CNL)-integrated care delivery is a new model for organizing master's-level nursing clinical leadership at the microsystem level. While there is growing evidence of improved patient care quality and safety outcomes associated with CNL practice, organizational and implementation characteristics that influence CNL success are not well characterized. The purpose of this study was to identify organization and implementation factors associated with perceived success of CNL integration into microsystem care delivery models.



A survey was developed and administered to a nationwide sample of certified CNLs and managers, leaders, educators, clinicians, and change agents involved in planning or integrating CNLs into a health system's nursing care delivery model. Items addressed organizational and implementation characteristics and perceived level of CNL initiative success. Generalized linear modeling was used to analyze data.



The final sample included 585 respondents. The final model accounted for 35% of variance in perceived CNL initiative success, and included five variables: phase of CNL initiative, CNL practice consistency, CNL instructor or preceptor involvement, CNL reporting structure, and CNL setting ownership status.



CNL initiative success is associated with modifiable organizational and implementation factors.



Study findings can be used to inform the development of successful implementation strategies for CNL practice integration into care delivery models to improve care quality outcomes.
Time dependent decision-making; dynamic priorities in the AHP/ANP: Generalizing from points to functions and from real to complex variables

The subject of time-dependent priorities is a new and potentially useful development in the AHP/ANP literature. It involves making paired comparisons not only of relative dominance of magnitudes as a starting point, but also of rates of change. Dealing with the future of human interaction and decisionmaking is very uncertain and confounding subject. We need caution in developing the subject if it is to work out to our advantage. This paper is mainly concerned with the theory of the subject. Examples are given to illustrate the method and detailed discussion is provided about how to derive time dependent priorities analytically for matrices of order up to four and numerically for matrices of all order. A brief representation and synthesis of time dependent neural firing and its hypermatrix is given.
Size dependency of nanocrystalline TiO 2 on its optical property and photocatalytic reactivity exemplified by 2-chlorophenol

Anatase TiO2 nanocrystallines (17–29 nm) were successfully synthesized by the metal–organic chemical vapor deposition method (MOCVD). Moderate manipulation of system parameters of MOCVD can control the particle size. The electro-optical and photocatalytic properties of the synthesized TiO2 nanoparticles were studied along with several commercially available ultra-fine TiO2 particles (e.g., 3.8–5.7 nm). The band gap of the TiO2 crystallines was determined using the transformed diffuse reflectance technique according to the Kubelka–Munk theory. Results showed that the band gap of TiO2 monotonically decreased from 3.239 to 3.173 eV when the particle size decreased from 29 to 17 nm and then increased from 3.173 to 3.289 eV as the particle size decreased from 17 to 3.8 nm. The results of band gap change as a function of particle size agreed well with what was predicted by the Brus’ equation, i.e., the effective mass model (EMM). However, results of the photocatalytic oxidation of 2-chlorophenol (2-CP), showed that the smaller the particle size, the faster the degradation rate. This is attributed in part to the combined effect of band gap change relative to the spectrum of the light source and the specific surface area (or particle size) of the photocatalysts. The change of band gap due to particle size represents only a small optical absorption window with respect to the total spectrum of the light source, i.e., from 380 to 400 nm versus>280 nm. Consequently, the gain in optical property of the larger particles was severely compromised by their decrease in specific surface area. Our results clearly indicated the importance of specific surface area in controlling the photocatalytic reactivity of photocatalysts. Results also showed that the secondary particle size grew with time due mainly to particle aggregation. The photocatalytic rate constants decreased exponentially with increase in primary particle size. Primary particle size alone is able to predict the photocatalytic rate as it is closely related to the electro-optical properties of photocatalysts.
Object-Extraction and Question-Parsing using CCG

Accurate dependency recovery has recently been reported for a number of wide-coverage statistical parsers using Combinatory Categorial Grammar (CCG). However, overall figures give no indication of a parser’s performance on specific constructions, nor how suitable a parser is for specific applications. In this paper we give a detailed evaluation of a CCG parser on object extraction dependencies found in WSJ text. We also show how the parser can be used to parse questions for Question Answering. The accuracy of the original parser on questions is very poor, and we propose a novel technique for porting the parser to a new domain, by creating new labelled data at the lexical category level only. Using a supertagger to assign categories to words, trained on the new data, leads to a dramatic increase in question parsing accuracy.
Global Software Development

0 7 4 0 7 4 5 9 / 0 1 / $ 1 0 . 0 0 © 2 0 0 1 I E E E Software engineers have recognized the profound influence of business globalization for some time, generating alarmist reactions in some quarters and moving others to try to capture and emulate models that have met with success. More recently, attention has turned toward trying to understand the factors that enable multinationals and virtual corporations to operate successfully across geographic and cultural boundaries.
Caricature synthesis with feature deviation matching under example-based framework

Example-based caricature synthesis techniques have been attracting large attentions for being able to generate attractive caricatures of various styles. This paper proposes a new example-based caricature synthesis system using a feature deviation matching method as a cross-modal distance metric. It employs the deviation values from average features across different feature spaces rather than the values of features themselves to search for similar components from caricature examples directly. Compared with traditional example-based systems, the proposed system can generate various styles of caricatures without requiring paired photograph–caricature example databases. The newly designed features can effectively capture visual characteristics of the hairstyles and facial components in input portrait images. In addition, this system can control the exaggeration of individual facial components and provide several similarity-based candidates to satisfy users’ different preferences. Experiments are conducted to prove the above ideas.
Detecting object affordances with Convolutional Neural Networks

We present a novel and real-time method to detect object affordances from RGB-D images. Our method trains a deep Convolutional Neural Network (CNN) to learn deep features from the input data in an end-to-end manner. The CNN has an encoder-decoder architecture in order to obtain smooth label predictions. The input data are represented as multiple modalities to let the network learn the features more effectively. Our method sets a new benchmark on detecting object affordances, improving the accuracy by 20% in comparison with the state-of-the-art methods that use hand-designed geometric features. Furthermore, we apply our detection method on a full-size humanoid robot (WALK-MAN) to demonstrate that the robot is able to perform grasps after efficiently detecting the object affordances.
High Ringxiety: Attachment Anxiety Predicts Experiences of Phantom Cell Phone Ringing

Mobile cell phone users have reported experiencing ringing and/or vibrations associated with incoming calls and messages, only to find that no call or message had actually registered. We believe this phenomenon can be understood as a human signal detection issue, with potentially important influences from psychological attributes. We hypothesized that individuals higher in attachment anxiety would report more frequent phantom cell phone experiences, whereas individuals higher in attachment avoidance would report less frequent experiences. If these experiences are primarily psychologically related to attributes of interpersonal relationships, associations with attachment style should be stronger than for general sensation seeking. We also predicted that certain contexts would interact with attachment style to increase or decrease the likelihood of experiencing phantom cell phone calls and messages. Attachment anxiety directly predicted the frequency of phantom ringing and notification experiences, whereas attachment avoidance and sensation seeking did not directly predict frequency. Attachment anxiety and attachment avoidance interacted with contextual factors (expectations for a call or message and concerned about an issue that one may be contacted about) in the expected directions for predicting phantom cell phone experiences.
Can Invisible Watermarks Resolve Rightful Ownerships?

Digital watermarks have been proposed in recent literature as the means for copyright protection of multimedia data. In this paper we address the capability of invisible watermarking schemes to resolve copyright ownerships. We will show that rightful ownerships cannot be resolved by current watermarking schemes alone. In addition, in the absence of standardization of watermarking procedures, anyone can claim ownership of any watermarked image. Specifically, we provide counterfeit watermarking schemes that can be performed on a watermarked image to allow multiple claims of rightful ownerships. We also propose non-invertible watermarking schemes in this paper and discuss in general the usefulness of digital watermarks in identifying the rightful copyright owners. The results, coupled with the recent attacks on some image watermarks, further imply that we have to carefully re-think our approaches to invisible watermarking of images, and re-evaluate the promises, applications and limitations of such digital means of copyright protection.
The gut microbiota shapes intestinal immune responses during health and disease

Immunological dysregulation is the cause of many non-infectious human diseases such as autoimmunity, allergy and cancer. The gastrointestinal tract is the primary site of interaction between the host immune system and microorganisms, both symbiotic and pathogenic. In this Review we discuss findings indicating that developmental aspects of the adaptive immune system are influenced by bacterial colonization of the gut. We also highlight the molecular pathways that mediate host–symbiont interactions that regulate proper immune function. Finally, we present recent evidence to support that disturbances in the bacterial microbiota result in dysregulation of adaptive immune cells, and this may underlie disorders such as inflammatory bowel disease. This raises the possibility that the mammalian immune system, which seems to be designed to control microorganisms, is in fact controlled by microorganisms.
Assessing coping strategies: a theoretically based approach.

We developed a multidimensional coping inventory to assess the different ways in which people respond to stress. Five scales (of four items each) measure conceptually distinct aspects of problem-focused coping (active coping, planning, suppression of competing activities, restraint coping, seeking of instrumental social support); five scales measure aspects of what might be viewed as emotional-focused coping (seeking of emotional social support, positive reinterpretation, acceptance, denial, turning to religion); and three scales measure coping responses that arguably are less useful (focus on and venting of emotions, behavioral disengagement, mental disengagement). Study 1 reports the development of scale items. Study 2 reports correlations between the various coping scales and several theoretically relevant personality measures in an effort to provide preliminary information about the inventory's convergent and discriminant validity. Study 3 uses the inventory to assess coping responses among a group of undergraduates who were attempting to cope with a specific stressful episode. This study also allowed an initial examination of associations between dispositional and situational coping tendencies.
Visfer: Camera-based visual data transfer for cross-device visualization

Going beyond the desktop to leverage novel devices—such as smartphones, tablets, or large displays—for visual sensemaking typically requires supporting extraneous operations for device discovery, interaction sharing, and view management. Such operations can be time-consuming and tedious, and distract the user from the actual analysis. Embodied interaction models in these multi-device environments can take advantage of the natural interaction and physicality afforded by multimodal devices and help effectively carry out these operations in visual sensemaking. In this paper, we present cross-device interaction models for visualization spaces, that are embodied in nature, by conducting a user study to elicit actions from participants that could trigger a portrayed effect of sharing visualizations (and therefore information) across devices. We then explore one common interaction style from this design elicitation called Visfer, a technique for effortlessly sharing visualizations across devices using the visual medium. More specifically, this technique involves taking pictures of visualizations, or rather the QR codes augmenting them, on a display using the built-in camera on a handheld device. Our contributions include a conceptual framework for cross-device interaction and the Visfer technique itself, as well as transformation guidelines to exploit the capabilities of each specific device and a web framework for encoding visualization components into animated QR codes, which capture multiple frames of QR codes to embed more information. Beyond this, we also present the results from a performance evaluation for the visual data transfer enabled by Visfer. We end the paper by presenting the application examples of our Visfer framework.
FACTO: a fact lookup engine based on web tables

Recently answers for fact lookup queries have appeared on major search engines. For example, for the query Barack Obama date of birth Google directly shows "4 August 1961" above its regular results. In this paper, we describe FACTO, an end-to-end system for answering fact lookup queries for web search. FACTO extracts structured data from tables on the web, aggregates and cleans such data and stores them in a database. Given a web search query, FACTO will decide if it asks for facts in this database, and provides the most confident answer when possible. FACTO achieves higher precision and comparable coverage comparing with the fact lookup engines by Google and Ask.com, although FACTO is developed by a very small team. We present the challenges and our solutions in developing every component of FACTO. Some solutions are based on existing technologies, and many others are novel approaches proposed by us.
An Empirical Analysis of Deep Network Loss Surfaces

The training of deep neural networks is a high-dimension optimization problem with respect to the loss function of a model. Unfortunately, these functions are of high dimension and non-convex and hence difficult to characterize. In this paper, we empirically investigate the geometry of the loss functions for state-of-the-art networks with multiple stochastic optimization methods. We do this through several experiments that are visualized on polygons to understand how and when these stochastic optimization methods find local minima.
Model-free, Model-based, and General Intelligence

During the 60s and 70s, AI researchers explored intuitions about intelligence by writing programs that displayed intelligent behavior. Many good ideas came out from this work but programs written by hand were not robust or general. After the 80s, research increasingly shifted to the development of learners capable of inferring behavior and functions from experience and data, and solvers capable of tackling well-defined but intractable models like SAT, classical planning, Bayesian networks, and POMDPs. The learning approach has achieved considerable success but results in black boxes that do not have the flexibility, transparency, and generality of their model-based counterparts. Modelbased approaches, on the other hand, require models and scalable algorithms. Model-free learners and model-based solvers have close parallels with Systems 1 and 2 in current theories of the human mind: the first, a fast, opaque, and inflexible intuitive mind; the second, a slow, transparent, and flexible analytical mind. In this paper, I review developments in AI and draw on these theories to discuss the gap between model-free learners and model-based solvers, a gap that needs to be bridged in order to have intelligent systems that are robust and general.
Ee364a: Convex Optimization I Final Exam

This is a 24 hour take-home final. Please turn it in at Bytes Cafe in the Packard building, 24 hours after you pick it up. You may use any books, notes, or computer programs, but you may not discuss the exam with anyone until March 16, after everyone has taken the exam. The only exception is that you can ask us for clarification, via the course staff email address. We've tried pretty hard to make the exam unambiguous and clear, so we're unlikely to say much. Please make a copy of your exam, or scan it, before handing it in. Please attach the cover page to the front of your exam. Assemble your solutions in order (problem 1, problem 2, problem 3,. . .), starting a new page for each problem. Put everything associated with each problem (e.g., text, code, plots) together; do not attach code or plots at the end of the final. We will deduct points from long needlessly complex solutions, even if they are correct. Our solutions are not long, so if you find that your solution to a problem goes on and on for many pages, you should try to figure out a simpler one. We expect neat, legible exams from everyone, including those enrolled Cr/N. When a problem involves computation you must give all of the following: a clear discussion and justification of exactly what you did, the source code that produces the result, and the final numerical results or plots. Files containing problem data can be found in the usual place, Please respect the honor code. Although we allow you to work on homework assignments in small groups, you cannot discuss the final with anyone, at least until everyone has taken it. All problems have equal weight. Some are easy. Others, not so much. Be sure you are using the most recent version of CVX, CVXPY, or Convex,jl. Check your email often during the exam, just in case we need to send out an important announcement. Some problems involve applications. But you do not need to know anything about the problem area to solve the problem; the problem statement contains everything you need.
Automatic Labelling of Tabla Signals

Most of the recent developments in the field of music indexing and music information retrieval are focused on western music. In this paper, we present an automatic music transcription system dedicated to Tabla a North Indian percussion instrument. Our approach is based on three main steps: firstly, the audio signal is segmented in adjacent segments where each segment represents a single stroke. Secondly, rhythmic information such as relative durations are calculated using beat detection techniques. Finally, the transcription (recognition of the strokes) is performed by means of a statistical model based on Hidden Markov Model (HMM). The structure of this model is designed in order to represent the time dependencies between successives strokes and to take into account the specificities of the tabla score notation (transcription symbols may be context dependent). Realtime transcription of Tabla soli (or performances) with an error rate of 6.5% is made possible with this transcriber. The transcription system, along with some additional features such as sound synthesis or phrase correction, are integrated in a user-friendly environment called Tablascope.
MRI-Compatibility of a Manipulator using a Spherical Ultrasonic Motor

We report the development of a manipulator using a spherical ultrasonic motor (SUSM) and the magnetic resonance imaging (MRI)-compatibility of the SUSM. The SUSM is constructed of three ring-shaped stators and a spherical rotor and has two or three degrees of freedom (DOF). In the present study, a novel SUSM composed of non-magnetic materials has been constructed. In an MRI-compatibility test of the SUSM in a 1.5 T MRI, the noise effects on MRI images of driving SUSM and not driving SUSM were observed. The results have shown a sharp image, though the quality of the image reduced. Terrible noise and deformation were not observed. On the other hand, the solution by a shield cloth was attempted. The results show some knowledge.
Optimal Cell Load and Throughput in Green Small Cell Networks With Generalized Cell Association

This paper thoroughly explores the fundamental interactions between cell association, cell load, and throughput in a green (energy-efficient) small cell network in which all base stations form a homogeneous Poisson point process (PPP) of intensity λB and all users form another independent PPP of intensity λ∪. Cell voidness, usually disregarded due to rarity in cellular network modeling, is first theoretically analyzed under generalized (channel-aware) cell association (GCA). We show that the void cell probability cannot be neglected any more since it is bounded above by exp(-λ∪/λB) that is typically not small in a small cell network. The accurate expression of the void cell probability for GCA is characterized and it is used to derive the average cell and user throughputs. We learn that cell association and cell load λ∪/λB significantly affect these two throughputs. According to the average cell and user throughputs, the green cell and user throughputs are defined respectively to reflect whether the energy of a base station is efficiently used to transmit information or not. In order to achieve satisfactory throughput with certain level of greenness, cell load should be properly determined. We present the theoretical solutions of the optimal cell loads that maximize the green cell and user throughputs, respectively, and verify their correctness by simulation.
Identity Aging: Efficient Blockchain Consensus

Decentralized currencies and similar blockchain applications require consensus. Bitcoin achieves eventual consensus in a fullydecentralized seing, but provides very low throughput and high latency with excessive energy consumption. In this paper, we propose identity aging as a novel and more ecient consensus approach. Our main idea is to establish reliable, long-term identities and choose the oldest identity as the miner on each round. Based on this approach, we design two blockchain systems. Our rst system, Scifer, leverages Intel’s SGX aestation for identity bootstrapping in a partially-decentralized seing, where blockchain is permissionless, but we trust Intel for aestation. Our second system, Difer, creates new identities through a novel mining mechanism and provides consensus in a fully-decentralized seing, similar to Bitcoin. One of the main benets of identity aging is that it does not require constant computation. Our analysis and experiments show that identity aging provides signicant performance improvements over Bitcoin with strong security guarantees.