nils-herrmann/clean_scirepeval huggingface dataset:
An Organizational Learning Framework : From Intuition to Institution Author ( s ) :

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The reliability of the McCabe score as a marker of co-morbidity in healthcare-associated infection point prevalence studies.

This study aimed to ascertain the reliability of the McCabe score in a healthcare-associated infection point prevalence survey.   A 10 European Union Member States survey in 20 hospitals (n = 1912) indicated that there was a moderate level of agreement (κ = 0.57) with the score. The reliability of the application of the score could be increased by training data collectors, particularly with reference to the ultimately fatal criteria. This is important if the score is to be used to risk adjust data to drive infection prevention and control interventions.
Affective computing in virtual reality: emotion recognition from brain and heartbeat dynamics using wearable sensors

Affective Computing has emerged as an important field of study that aims to develop systems that can automatically recognize emotions. Up to the present, elicitation has been carried out with non-immersive stimuli. This study, on the other hand, aims to develop an emotion recognition system for affective states evoked through Immersive Virtual Environments. Four alternative virtual rooms were designed to elicit four possible arousal-valence combinations, as described in each quadrant of the Circumplex Model of Affects. An experiment involving the recording of the electroencephalography (EEG) and electrocardiography (ECG) of sixty participants was carried out. A set of features was extracted from these signals using various state-of-the-art metrics that quantify brain and cardiovascular linear and nonlinear dynamics, which were input into a Support Vector Machine classifier to predict the subject’s arousal and valence perception. The model’s accuracy was 75.00% along the arousal dimension and 71.21% along the valence dimension. Our findings validate the use of Immersive Virtual Environments to elicit and automatically recognize different emotional states from neural and cardiac dynamics; this development could have novel applications in fields as diverse as Architecture, Health, Education and Videogames.
Challenges in Infective Endocarditis.

Infective endocarditis is defined by a focus of infection within the heart and is a feared disease across the field of cardiology. It is frequently acquired in the health care setting, and more than one-half of cases now occur in patients without known heart disease. Despite optimal care, mortality approaches 30% at 1 year. The challenges posed by infective endocarditis are significant. It is heterogeneous in etiology, clinical manifestations, and course. Staphylococcus aureus, which has become the predominant causative organism in the developed world, leads to an aggressive form of the disease, often in vulnerable or elderly patient populations. There is a lack of research infrastructure and funding, with few randomized controlled trials to guide practice. Longstanding controversies such as the timing of surgery or the role of antibiotic prophylaxis have not been resolved. The present article reviews the challenges posed by infective endocarditis and outlines current and future strategies to limit its impact.
SQL- and Operator-centric Data Analytics in Relational Main-Memory Databases

Data volume and complexity continue to increase, as does the need for insight into data. Today, data management and data analytics are most often conducted in separate systems: database systems and dedicated analytics systems. This separation leads to timeand resource-consuming data transfer, stale data, and complex IT architectures. In this paper we show that relational main-memory database systems are capable of executing analytical algorithms in a fully transactional environment while still exceeding performance of state-of-the-art analytical systems rendering the division of data management and data analytics unnecessary. We classify and assess multiple ways of integrating data analytics in database systems. Based on this assessment, we extend SQL with a non-appending iteration construct that provides an important building block for analytical algorithms while retaining the high expressiveness of the original language. Furthermore, we propose the integration of analytics operators directly into the database core, where algorithms can be highly tuned for modern hardware. These operators can be parameterized with our novel user-defined lambda expressions. As we integrate lambda expressions into SQL instead of proposing a new proprietary query language, we ensure usability for diverse groups of users. Additionally, we carry out an extensive experimental evaluation of our approaches in HyPer, our full-fledged SQL main-memory database system, and show their superior performance in comparison to dedicated solutions.
The Differentiation Stage of Transplanted Stem Cells Modulates Nerve Regeneration

In regenerative medicine applications, the differentiation stage of implanted stem cells must be optimized to control cell fate and enhance therapeutic efficacy. We investigated the therapeutic potential of human induced pluripotent stem cell (iPSC)-derived cells at two differentiation stages on peripheral nerve regeneration. Neural crest stem cells (NCSCs) and Schwann cells (NCSC-SCs) derived from iPSCs were used to construct a tissue-engineered nerve conduit that was applied to bridge injured nerves in a rat sciatic nerve transection model. Upon nerve conduit implantation, the NCSC group showed significantly higher electrophysiological recovery at 1 month as well as better gastrocnemius muscle recovery at 5 months than the acellular group, but the NCSC-SC group didn’t. Both transplanted NCSCs and NCSC-SCs interacted with newly-growing host axons, while NCSCs showed better survival rate and distribution. The transplanted NCSCs mainly differentiated into Schwann cells with no teratoma formation, and they secreted higher concentrations of brain-derived neurotrophic factor and nerve growth factor than NCSC-SCs. In conclusion, transplantation of iPSC-NCSCs accelerated functional nerve recovery with the involvement of stem cell differentiation and paracrine signaling. This study unravels the in vivo performance of stem cells during tissue regeneration, and provides a rationale of using appropriate stem cells for regenerative medicine.
[Skew deviation. Strabismological diagnosis and treatment alternatives].

We undertook this study to analyze diagnostic and treatment alternatives in patients with skew deviation (SD).



This is a prospective, observational and longitudinal study of patients with SD. The study took place in a third-level medical center during the period from September 2007 to May 2008. Strabismological exploration, multidisciplinary diagnosis and treatment alternatives were analyzed.



Ten patients presenting SD were studied. Diagnoses were multiple sclerosis, arteriovenous malformation, epilepsy, hydrocephalus, ischemic encephalopathy, cortical atrophy, hypoplasia of corpus callosum and thalamic hemorrhage. Psychomotor retardation was present in 80%. Other diagnoses were Cogan apraxia, Parinaud syndrome, see-saw nystagmus, Foville syndrome, and hemiplegic alterations. Related strabismuses were exotropia (5), esotropia (3), hypertropia (2), and dissociated vertical deviation (1). Lesions of II, III and VII cranial nerves were found.



Complete strabological study allows a better diagnosis of the lesion and consequently relapsing disease in order to achieve a better treatment according to each patient. Optical rehabilitation and botulinum applications are especially indicated.
Augmented Reality Games for Upper-Limb Stroke Rehabilitation

Stroke is the number one cause of severe physical disability in the UK. Recent studies have shown that technologies such as virtual reality and imaging can provide an engaging and motivating tool for physical rehabilitation. In this paper we summarize previous work in our group using virtual reality technology and webcam-based games. We then present early work we are conducting in experimenting with desktop augmented reality (AR) for rehabilitation. AR allows the user to use real objects to interact with computer-generated environments. Markers attached to the real objects enable the system (via a webcam) to track the position and orientation of each object as it is moved. The system can then augment the captured image of the real environment with computer-generated graphics to present a variety of game or task-driven scenarios to the user. We discuss the development of rehabilitation prototypes using available AR libraries and express our thoughts on the potential of AR technology.
A constraint-based biometric scheme on ATM and swiping machine

In this modern scientific world, technologies are transforming rapidly but along with the ease and comfort they also bring in a big concern for security. Taking into account the physical security of the system to ensure access control and authentication of users, made us to switch to a new system of Biometric combined with ATM PIN as PIN can easily be guessed, stolen or misused. Biometric is added with the existing technology to double the security in order to reduce ATM frauds but it has also put forward several issues which include sensor durability and time consumption. This paper envelops two questions “Is it really worthy to go through the entire biometric process to just debit a low amount?” and “What could be the maximum amount one can lose if one's card is misused?” As an answer we propose a constraint on transactions by ATM involving biometric to improve the system performance and to solve the defined issues. The proposal is divided in two parts. The first part solves sensor performance issue by adding a limit on amount of cash and number of transactions is defined in such a way that if one need to withdraw a big amount OR attempts for multiple transactions by withdrawing small amount again and again, it shall be necessary to present biometric. On the other hand if one need to make only balance enquiry or the cash is low and the number of transactions in a day is less than defined attempts, biometric presentation is not mandatory. It may help users to save time and maintain sensor performance by not furnishing their biometric for few hundred apart from maintaining security. In the second part this paper explains how fingerprint verification is conducted if the claimant is allowed to access the system and what could be the measures to increase performance of fingerprint biometric system which could be added to our proposed system to enhance the overall system performance.
Correlation and Simple Linear Regression 1 In this tutorial

1 From the Department of Radiology, Brigham and Women’s Hospital (K.H.Z., K.T., S.G.S.) and Department of Health Care Policy (K.H.Z.), Harvard Medical School, 180 Longwood Ave, Boston, MA 02115.  2001; revision requested October 31; revision received December 26; accepted January 21, 2002. Address correspondence to K.H.Z. (e-mail: zou@bwh.harvard.edu).
A MID dipole antenna in LDS technology

Molded interconnect devices (MID) allow the realization of electronic circuits on injection molded thermoplastics. MID antennas can be manufactured as part of device casings without the need for additional printed circuit boards or attachment of antennas printed on foil. Baluns, matching networks, amplifiers and connectors can be placed on the polymer in the vicinity of the antenna. A MID dipole antenna for 1 GHz is designed, manufactured and measured. A prototype of the antenna is built with laser direct structuring (LDS) on a Xantar LDS 3720 substrate. Measured return loss and calibrated gain patterns are compared to simulation results.
Automatic vulnerability mining with abstract interpretation and static taint trace

With the expansion of software scale, effective approaches for automatic vulnerability mining have been in badly needed. This paper presents a novel approach which can generate test cases of high pertinence and reachability. Unlike standard fuzzing techniques which explore the test space blindly, our approach utilizes abstract interpretation based on intervals to locate the Frail-Points of program which may cause buffer over-flow in some special conditions and the technique of static taint trace to build mappings between the Frail-Points and program inputs. Moreover, acquire path constraints of each Frail-Point through symbolic execution. Finally, combine information of mappings and path constraints to propose a policy for guiding test case generation.
Appropriate endpoints for evaluation of new antibiotic therapies for severe infections: a perspective from COMBACTE’s STAT-Net

In this era of rising antimicrobial resistance, slowly refilling antibiotic development pipelines, and an aging population, we need to ensure that randomized clinical trials (RCTs) determine the added benefit of new antibiotic agents effectively and in a valid way, especially for severely ill patients. Unfortunately, universally accepted endpoints for the evaluation of new drugs in severe infections are lacking. We review and discuss the current practices and challenges regarding endpoints in RCTs in this field and propose novel approaches. Usual endpoints actually recommended for drug development suffer from important flaws. Mortality requires large sample size and only partly related to the infectious process. Clinical cure rate is highly subjective in critically ill patients where symptoms may be related to other intercurrent events. Currently, composite endpoints, hierarchical nested designs, and competing risks analysis seem to be the most promising new tools for designing and analyzing clinical trials in this area, although they require further validation. Regulatory authorities, pharmaceutical companies, and clinicians need to agree on the most appropriate clinical endpoints for severe infections to ensure efficient approval of new, effective antibiotic agents.
Towards Analogy-based Recommendation: Benchmarking of Perceived Analogy Semantics

Requests for recommendation can be seen as a form of query for candidate items, ranked by relevance. Users are however oen unable to crisply dene what they are looking for. One of the core concepts of natural communication for describing and explaining complex information needs in an intuitive fashion are analogies: e.g., “What is to Christopher Nolan as is 2001: A Space Odyssey to Stanley Kubrick?”. Analogies allow users to explore the item space by formulating queries in terms of items rather than explicitly specifying the properties that they nd aractive. One of the core challenges which hamper research on analogy-enabled queries is that analogy semantics rely on consensus on human perception, which is not well represented in current benchmark data sets. erefore, in this paper we introduce a new benchmark dataset focusing on the human aspects for analogy semantics. Furthermore, we evaluate a popular technique for analogy semantics (word2vec neuronal embeddings) using our dataset. e results show that current word embedding approaches are still not not suitable to suciently deal with deeper analogy semantics. We discuss future directions including hybrid algorithms also incorporating structural or crowd-based approaches, and the potential for analogy-based explanations.
Coping with uncertainty: police strategies for resilient decision-making and action implementation

This study uses a hostage negotiation setting to demonstrate how a team of strategic police officers can utilize specific coping strategies to minimize uncertainty at different stages of their decision-making in order to foster resilient decision-making to effectively manage a high-risk critical incident. The presented model extends the existing research on coping with uncertainty by (1) applying the RAWFS heuristic (Lipshitz and Strauss in Organ Behav Human Decis Process 69:149–163, 1997) of individual decision-making under uncertainty to a team critical incident decision-making domain; (2) testing the use of various coping strategies during “in situ” team decision-making by using a live simulated hostage negotiation exercise; and (3) including an additional coping strategy (“reflection-in-action”; Schön in The reflective practitioner: how professionals think in action. Temple Smith, London, 1983) that aids naturalistic team decision-making. The data for this study were derived from a videoed strategic command meeting held within a simulated live hostage training event; these video data were coded along three themes: (1) decision phase; (2) uncertainty management strategy; and (3) decision implemented or omitted. Results illustrate that, when assessing dynamic and high-risk situations, teams of police officers cope with uncertainty by relying on “reduction” strategies to seek additional information and iteratively update these assessments using “reflection-in-action” (Schön 1983) based on previous experience. They subsequently progress to a plan formulation phase and use “assumption-based reasoning” techniques in order to mentally simulate their intended courses of action (Klein et al. 2007), and identify a preferred formulated strategy through “weighing the pros and cons” of each option. In the unlikely event that uncertainty persists to the plan execution phase, it is managed by “reduction” in the form of relying on plans and standard operating procedures or by “forestalling” and intentionally deferring the decision while contingency planning for worst-case scenarios.
Discovering Newsworthy Themes from Sequenced Data: A Step Towards Computational Journalism

Automatic discovery of newsworthy themes from sequenced data can relieve journalists from manually poring over a large amount of data in order to find interesting news. In this paper, we propose a novel <inline-formula> <tex-math notation="LaTeX">$k$</tex-math><alternatives><inline-graphic xlink:href="fan-ieq1-2685587.gif"/> </alternatives></inline-formula>-Sketch query that aims to find <inline-formula><tex-math notation="LaTeX"> $k$</tex-math><alternatives><inline-graphic xlink:href="fan-ieq2-2685587.gif"/></alternatives> </inline-formula> striking streaks to best summarize a subject. Our scoring function takes into account streak strikingness and streak coverage at the same time. We study the <inline-formula><tex-math notation="LaTeX"> $k$</tex-math><alternatives><inline-graphic xlink:href="fan-ieq3-2685587.gif"/></alternatives> </inline-formula>-Sketch query processing in both offline and online scenarios, and propose various streak-level pruning techniques to find striking candidates. Among those candidates, we then develop approximate methods to discover the <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives> <inline-graphic xlink:href="fan-ieq4-2685587.gif"/></alternatives></inline-formula> most representative streaks with theoretical bounds. We conduct experiments on four real datasets, and the results demonstrate the efficiency and effectiveness of our proposed algorithms: the running time achieves up to 500 times speedup and the quality of the generated summaries is endorsed by the anonymous users from Amazon Mechanical Turk.
A relative quantitative positive/negative ion switching method for untargeted lipidomics via high resolution LC-MS/MS from any biological source

Advances in high-resolution mass spectrometry have created renewed interest for studying global lipid biochemistry in disease and biological systems. Here, we present an untargeted 30 min. LC-MS/MS platform that utilizes positive/negative polarity switching to perform unbiased data dependent acquisitions (DDA) via higher energy collisional dissociation (HCD) fragmentation to profile more than 1000–1500 lipid ions mainly from methyl-tert-butyl ether (MTBE) or chloroform:methanol extractions. The platform uses C18 reversed-phase chromatography coupled to a hybrid QExactive Plus/HF Orbitrap mass spectrometer and the entire procedure takes ~10 h from lipid extraction to identification/quantification for a data set containing 12 samples (~4 h for a single sample). Lipids are identified by both accurate precursor ion mass and fragmentation features and quantified using LipidSearch and Elements software. Using this approach, we are able to profile intact lipid ions from up to 18 different main lipid classes and 66 subclasses. We show several studies from different biological sources, including cultured cancer cells, resected tissues from mice such as lung and breast tumors and biological fluids such as plasma and urine. Using mouse embryonic fibroblasts, we showed that TSC2−/− KD significantly abrogates lipid biosynthesis and that rapamycin can rescue triglyceride (TG) lipids and we show that SREBP−/− shuts down lipid biosynthesis significantly via mTORC1 signaling pathways. We show that in mouse EGFR driven lung tumors, a large number of TGs and phosphatidylmethanol (PMe) lipids are elevated while some phospholipids (PLs) show some of the largest decrease in lipid levels from ~ 2000 identified lipid ions. In addition, we identified more than 1500 unique lipid species from human blood plasma.
Modeling IoT-aware business processes

A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
Reducing children's television-viewing time: a qualitative study of parents and their children.

The American Academy of Pediatrics recommends that children over age 2 years spend < or = 2 hours per day with screen media, because excessive viewing has been linked to a plethora of physical, academic, and behavioral problems. The primary goal of this study was to qualitatively explore how a recommendation to limit television viewing might be received and responded to by a diverse sample of parents and their school-age children.



The study collected background data about media use, gathered a household media inventory, and conducted in-depth individual and small group interviews with 180 parents and children ages 6 to 13 years old.



Most of the children reported spending approximately 3 hours per day watching television. The average home in this sample had 4 television sets; nearly two thirds had a television in the child's bedroom, and nearly half had a television set in the kitchen or dining room. Although virtually all of the parents reported having guidelines for children's television viewing, few had rules restricting the time children spend watching television. Data from this exploratory study suggest several potential barriers to implementing a 2-hour limit, including: parents' need to use television as a safe and affordable distraction, parents' own heavy television viewing patterns, the role that television plays in the family's day-to-day routine, and a belief that children should spend their weekend leisure time as they wish. Interviews revealed that for many of these families there is a lack of concern that television viewing is a problem for their child, and there remains confusion about the boundaries of the recommendation of the American Academy of Pediatrics.



Parents in this study expressed interest in taking steps toward reducing children's television time but also uncertainty about how to go about doing so. Results suggest possible strategies to reduce the amount of time children spend in front of the screen.