Miracle-dz/UniFAR-FTUs huggingface dataset:
Typed Versus Voice Recognition for Data Entry in Electronic Health Records: Emergency Physician Time Use and Interruptions

Introduction Use of electronic health record (EHR) systems can place a considerable data entry burden upon the emergency department (ED) physician. Voice recognition data entry has been proposed as one mechanism to mitigate some of this burden; however, no reports are available specifically comparing emergency physician (EP) time use or number of interruptions between typed and voice recognition data entry-based EHRs. We designed this study to compare physician time use and interruptions between an EHR system using typed data entry versus an EHR with voice recognition. Methods We collected prospective observational data at 2 academic teaching hospital EDs, one using an EHR with typed data entry and the other with voice recognition capabilities. Independent raters observed EP activities during regular shifts. Tasks each physician performed were noted and logged in 30 second intervals. We compared time allocated to charting, direct patient care, and change in tasks leading to interruptions between sites. Results We logged 4,140 minutes of observation for this study. We detected no statistically significant differences in the time spent by EPs charting (29.4% typed; 27.5% voice) or the time allocated to direct patient care (30.7%; 30.8%). Significantly more interruptions per hour were seen with typed data entry versus voice recognition data entry (5.33 vs. 3.47; p=0.0165). Conclusion The use of a voice recognition data entry system versus typed data entry did not appear to alter the amount of time physicians spend charting or performing direct patient care in an ED setting. However, we did observe a lower number of workflow interruptions with the voice recognition data entry EHR. Additional research is needed to further evaluate the data entry burden in the ED and examine alternative mechanisms for chart entry as EHR systems continue to evolve.
Feasibility of targeted early detection for melanoma: a population-based screening study

The feasibility of targeted screening for cutaneous malignant melanoma in the UK using a postal questionnaire and invitation to screening by a consultant dermatologist was investigated in a population based cross-sectional survey. A total of 1600 people aged 25–69 years, stratified by the social deprivation score of wards within one general practice, were randomly selected from a population of 8000.1227 (77%) returned the questionnaire and 896 (56%) attended the screening clinic. Uptake was lower for men (P< 0.001), those aged under 50 (P< 0.001), people from deprived areas (P< 0.001) and skin types III and IV (men only, P< 0.001). Twenty per cent of women and 10% of men felt nervous about attending the clinic, but only 4% were worried by the questionnaire. The level of agreement between the self- and dermatologist’s assessments of risk factors was best for hair colour (Kappa = 0.67, sensitivity 73% and specificity 98%). People tended to under-report their level of risk. Over 95% knew about at least one major sign, but 54% reported incorrect signs of melanoma. Targeted screening for melanoma in the UK will be hampered by difficulties in accurately identifying the target population. Strategies to improve skin self-awareness rather than screening should be developed and evaluated. © 2000 Cancer Research Campaign
Migration to Open-Standard Interorganizational Systems: Network Effects, Switching Costs, and Path Dependency

Migration to Open-Standard Interorganizational Systems: Network Effects, Switching Costs and Path Dependency RESEARCH PROJECT REPORT June 2005 KEVIN ZHU The Paul Merage School of Business, and CRITO University of California, Irvine 949.824. 2619 Tel. kzhu@uci.edu KENNETH L. KRAEMER The Center for Research on Information Technology and Organizations (CRITO) The Paul Merage School of Business University of California, Irvine 949.824. 5246 Tel. kkraemer@uci.edu VIJAY GURBAXANI The CRITO Consortium The Paul Merage School of Business University of California, Irvine 949.824. 5215 Tel. vgurbaxa@uci.edu SEAN XU The Paul Merage School of Business, and CRITO University of California, Irvine sxu00@uci.edu This research has been supported by grants from the CISE/IIS/CSS Division of the U.S. National Science Foundation and the NSF Industry/University Cooperative Research Center (CISE/EEC) to the Center for Research on Information Technology and Organizations (CRITO) at the University of California, Irvine. Industry sponsors include: The Boeing Company, IBM, IDC, Intel, Microsoft, and the U.S. Department of Defense. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Pointing lenses: facilitating stylus input through visual-and motor-space magnification

Using a stylus on a tablet computer to acquire small targets can be challenging. In this paper we present pointing lenses -- interaction techniques that help users acquire and select targets by presenting them with an enlarged visual and interaction area. We present and study three pointing lenses for pen-based systems and find that our proposed Pressure-Activated Lens is the top overall performer in terms of speed, accuracy and user preference. In addition, our experimental results not only show that participants find all pointing lenses beneficial for targets smaller than 5 pixels, but they also suggest that this benefit may extend to larger targets as well.
A Universal Expression/Silencing Vector in Plants[C][OA]

A universal vector (IL-60 and auxiliary constructs), expressing or silencing genes in every plant tested to date, is described. Plants that have been successfully manipulated by the IL-60 system include hard-to-manipulate species such as wheat (Triticum duram), pepper (Capsicum annuum), grapevine (Vitis vinifera), citrus, and olive (Olea europaea). Expression or silencing develops within a few days in tomato (Solanum lycopersicum), wheat, and most herbaceous plants and in up to 3 weeks in woody trees. Expression, as tested in tomato, is durable and persists throughout the life span of the plant. The vector is, in fact, a disarmed form of Tomato yellow leaf curl virus, which is applied as a double-stranded DNA and replicates as such. However, the disarmed virus does not support rolling-circle replication, and therefore viral progeny single-stranded DNA is not produced. IL-60 does not integrate into the plant's genome, and the construct, including the expressed gene, is not heritable. IL-60 is not transmitted by the Tomato yellow leaf curl virus's natural insect vector. In addition, artificial satellites were constructed that require a helper virus for replication, movement, and expression. With IL-60 as the disarmed helper “virus,” transactivation occurs, resulting in an inducible expressing/silencing system. The system's potential is demonstrated by IL-60-derived suppression of a viral-silencing suppressor of Grapevine virus A, resulting in Grapevine virus A-resistant/tolerant plants.
Staying FIT: Efficient Load Shedding Techniques for Distributed Stream Processing

In distributed stream processing environments, large numbers of continuous queries are distributed onto multiple servers. When one or more of these servers become overloaded due to bursty data arrival, excessive load needs to be shed in order to preserve low latency for the query results. Because of the load dependencies among the servers, load shedding decisions on these servers must be well-coordinated to achieve end-to-end control on the output quality. In this paper, we model the distributed load shedding problem as a linear optimization problem, for which we propose two alternative solution approaches: a solver-based centralized approach, and a distributed approach based on metadata aggregation and propagation, whose centralized implementation is also available. Both of our solutions are based on generating a series of load shedding plans in advance, to be used under certain input load conditions. We have implemented our techniques as part of the Borealis distributed stream processing system. We present experimental results from our prototype implementation showing the performance of these techniques under different input and query workloads.
HOMED: a peer-to-peer overlay architecture for large-scale content-based publish/subscribe system

Content-based publish/subscrbe systems provide an useful alternative to traditional address-based communication due to their ability to decouple communication between participants. It has remained a challenge to design a scalable overlay supporting the complexity of content-based networks, while satisfying the desirable properties large distributed systems should have. This paper presents a new peer-to-peer overlay called HOMED for distributed publish/subscribe systems. It can construct a flexible and efficient event dissemination tree by organizing participants based on their interest. The delivery depth of an event as well as subscribing/unsubscribing overhead scales logarithmically with the number of participating nodes.
GPCR-GRAPA-LIB-a refined library of hidden Markov Models for annotating GPCRs

GPCR-GRAPA-LIB is a library of HMMs describing G protein coupled receptor families. These families are initially defined by class of receptor ligand, with divergent families divided into subfamilies using phylogenic analysis and knowledge of GPCR function. Protein sequences are applied to the models with the GRAPA curve-based selection criteria. RefSeq sequences for Homo sapiens, Drosophila melanogaster, and Caenorhabditis elegans have been annotated using this approach.
A conceptual model with empirical verification for constructing non-profit organization Web sites

A module-based Web site design model containing various functions was proposed with corresponding guidelines and suggestions, for non-profit organizations (NPOs) to construct, maintain, and re-design their Web sites. By adopting this model, NPOs will be able to clearly re-examine their Web site operations and select more suitable information and mechanisms to provide on their Web sites. It was also suggested in our model to take advantage of standardized interfaces and mechanisms (such as open standards and reusable components) for achieving the goal of efficiently and effectively constructing and operating NPO Web sites. In addition, for the purpose of verification, and under an unexpected time constrain, we quickly developed a Web site prototype fully based on our model, and submitted it to a charity-related contest. During a relatively short five-day period, we were able to succeed with a "second highest votes" ranked result, which surprisingly showed us the potentials and feasibility of this model. This model could also be applied to other NPOs as a valuable reference for their management and e-commerce project teams to successfully design and implement their e-commerce initiatives.
Semi-automatic error analysis for large-scale statistical machine translation

This paper presents a general framework for semi-automatic error analysis in large-scale statistical machine translation (SMT) systems. The main objective is to relate characteristics of input documents (which can be either in text or audio form) to the system's overall translation performance and thus identify particularly problematic input characteristics (e.g. source, genre, dialect, etc.). Various measurements of these factors are extracted from the input, either automatically or by human annotation, and are related to translation performance scores by means of mutual information. We apply this analysis to a state-of-the-art large-scale SMT system operating on Chinese and Arabic text and audio documents, and demonstrate how the proposed error analysis can help identify system weaknesses.
Estimating Causal Effects by Bounding Confounding

Assessing the causal effect of a treatment variable X on an outcome variable Y is usually difficult due to the existence of unobserved common causes. Without further assumptions, observed dependences do not even prove the existence of a causal effect from X to Y. It is intuitively clear that strong statistical dependences between X and Y do provide evidence for X influencing Y if the influence of common causes is known to be weak. We propose a framework that formalizes effect versus confounding in various ways and derive upper/lower bounds on the effect in terms of a priori given bounds on confounding. The formalization includes information theoretic quantities like information flow and causal strength, as well as other common notions like effect of treatment on the treated (ETT). We discuss several scenarios where upper bounds on the strength of confounding can be derived. This justifies to some extent human intuition which assumes the presence of causal effect when strong (e.g. close to deterministic) statistical relations are observed.
Flexible labour supply and the preference for random wages

An individual who responds flexibly to wage changes may benefit from random wages. A necessary condition for a preference for wage risk is that the labour supply curve slopes up. Jointly sufficient conditions for wage risk to be preferred are that the individual is neutral to full income risk and the substitution effect of a wage change is at least twice the size of the total income effect. The conditions are applied to the cases of homothetic preferences, Cobb-Douglas utility when there is positive non-labour income, and quasi-linear utility. JEL classification: J22; D81
Mutual Information-based Intrusion Detection Model for Industrial Internet

High dimension, redundancy attributes and high computing cost issues usually exist in the industrial Internet intrusion detection ﬁeld. For solving these problems, the mutual information-based intrusion detection model for industrial Internet was proposed. Firstly, by using features selection method based on mutual information, the attributes set was reduced and traﬃc characteristics vector was established. Secondly, the normal and abnormal traﬃc characteristics maps were obtained via the traﬃc characteristics map technology based on multi correlation analysis. Finally, with the using of discrete cosine transform and nonnegative matrix factorization, we can produce normal and abnormal hash digest, which were used to produce intrusion detection rules. To verify the eﬀec-tiveness of this model, we adopt NSL-KDD data as the experimental data. The experimental results show that, by using the features selection approach based on mutual information, the proposed model has good classiﬁcation accuracy and gets good detection performance.
On the Convergence of Multiplicative Update Algorithms for Nonnegative Matrix Factorization

Nonnegative matrix factorization (NMF) is useful to find basis information of nonnegative data. Currently, multiplicative updates are a simple and popular way to find the factorization. However, for the common NMF approach of minimizing the Euclidean distance between approximate and true values, no proof has shown that multiplicative updates converge to a stationary point of the NMF optimization problem. Stationarity is important as it is a necessary condition of a local minimum. This paper discusses the difficulty of proving the convergence. We propose slight modifications of existing updates and prove their convergence. Techniques invented in this paper may be applied to prove the convergence for other bound-constrained optimization problems.
Probabilistic Guarantees of Execution Duration for Amazon Spot Instances

In this paper we propose DRAFTS – a methodology for implementing probabilistic guarantees of instance reliability in the Amazon Spot tier. Amazon offers “unreliable” virtual machine instances (ones that may be terminated at any time) at a potentially large discount relative to “reliable” On-demand and Reserved instances. Our method predicts the “bid values” that users can specify to provision Spot instances which ensure at least a fixed duration of execution with a given probability. We illustrate the method and test its validity using Spot pricing data post facto, both randomly and using real-world workload traces. We also test the efficacy of the method experimentally by using it to launch Spot instances and then observing the instance termination rate. Our results indicate that it is possible to obtain the same level of reliability from unreliable instances that the Amazon service level agreement guarantees for reliable instances with a greatly reduced cost. CCS CONCEPTS • Networks → Cloud computing; • General and reference → Reliability; • Applied computing → Forecasting;
High resolution 3-T MR imaging in the evaluation of the trigeminal nerve course.

BACKGROUND The evaluation of the trigeminal course and his anatomical relationships with surrounding structures, is important for the assessment of the injury that may occur in tumors and several orofacial trauma and for avoiding the damage during surgeries. AIM The aim of this retrospective study was to assess the use of 3-T MRI in the evaluation of the course of the four segments of the trigeminal nerve: cisternal and Meckels's cave, cavernous sinus, skull base and mandibular extracranial segments. PATIENTS AND METHODS 78 patients were studied, for a total of 156 trigeminal nerves examined. T2-weighted 3D Fast imaging employing steady-state acquisition and T1-weighted Fast spoiled gradient recalled echo sequences were used. Two radiologists (reader A and B), independently, evaluated the course of the four segments of the trigeminal nerve according to a qualitative scale. The Intraclass correlation coefficient (ICC) and Pearson correlation coefficient were used to assess the intraobserver and interobserver variability in the nerve course evaluation. RESULTS Reader A evaluated 47 trigeminal nerves excellent, 94 good, 12 fair and 3 poor. Reader B rated 43 trigeminal nerves excellent, 92 good, 16 fair and 5 poor. The intraobserver variability was ICC = 0.937 in reader A and ICC = 0.894 in reader B. The interobserver variability was 0.734 (p ≤ 0.01). CONCLUSIONS High resolution 3-T MRI imaging allows an accurate study of the trigeminal nerve and especially of its mandibular branch. The knowledge of the course and of the anatomic relationships of these nerve bundles with surrounding structures, as well as of the anatomical variants, allow oral and maxillofacial surgical plannings thus reducing the risk of nerve damage.
Improving A Simple Bigram HMM Part-of-Speech Tagger by Latent Annotation and Self-Training

In this paper, we describe and evaluate a bigram part-of-speech (POS) tagger that uses latent annotations and then investigate using additional genre-matched unlabeled data for self-training the tagger. The use of latent annotations substantially improves the performance of a baseline HMM bigram tagger, outperforming a trigram HMM tagger with sophisticated smoothing. The performance of the latent tagger is further enhanced by self-training with a large set of unlabeled data, even in situations where standard bigram or trigram taggers do not benefit from self-training when trained on greater amounts of labeled training data. Our best model obtains a state-of-the-art Chinese tagging accuracy of 94.78% when evaluated on a representative test set of the Penn Chinese Treebank 6.0.
Synthesis and characterization of chitosan quaternary ammonium salt and its application as drug carrier for ribavirin

Abstract N-(2-hydroxyl) propyl-3-trimethyl ammonium chitosan chloride (HTCC) is hydro-soluble chitosan (CS) derivative, which can be obtained by the reaction between epoxypropyl trimethyl ammonium chloride (ETA) and CS. The preparation parameters for the synthesis of HTCC were optimized by orthogonal experimental design. ETA was successfully grafted into the free amino group of CS. Grafting of ETA with CS had great effect on the crystal structure of HTCC, which was confirmed by the XRD results. HTCC displayed higher capability to form nanoparticles by crosslinking with negatively charged sodium tripolyphosphate (TPP). Ribavrin- (RIV-) loaded HTCC nanoparticles were positively charged and were spherical in shape with average particle size of 200 nm. More efficient drug encapsulation efficiency and loading capacity were obtained for HTCC in comparison with CS, however, HTCC nanoparticles displayed faster release rate due to its hydro-soluble properties. The results suggest that HTCC is a promising CS derivative for the encapsulation of hydrophilic drugs in obtaining sustained release of drugs.
Probabilistic load flow computation using the method of combined cumulants and Gram-Charlier expansion

Open access transmission has created a deregulated power market and brought new challenges to system planning. This paper proposes a new method to compute a probabilistic load flow in extensive power systems for the purpose of using it as a quick screening tool to determine the major investment on improving transmission system inadequacy. This innovative method combines the concept of Cumulants and Gram-Charlier expansion theory to obtain probabilistic distribution functions of transmission line flows. It has significantly reduced the computational time while maintaining a high degree of accuracy. This enables probabilistic analysis of power flow problems to be treated objectively and allows quantitative assessment of system reliability.
Tracking social and biological experiences: the social etiology of cardiovascular disease.

The social gradient in cardiovascular disease (CVD) is well known. There are literally scores of studies showing that men and women who are socially disadvantaged are at increased risk of developing CVD and have a worse prognosis once they develop the disease.1 During the last 40 years, in most industrialized countries, a clear pattern has emerged showing that each increase in socioeconomic position confers a decreased risk in cardiovascular morbidity and mortality. Men between the ages of 25 and 64 who are the most disadvantaged have an ≈2.5-fold risk of dying of CVD. For women, the risks are even greater (3.4-fold risk). 2 Similar trends are seen for risk-related disorders, including hypertension and diabetes. The causes and mediating pathways by which this occurs are not nearly as well characterized, however. Identifying the biological and behavioral mechanisms that link economic and social disadvantage to cardiovascular morbidity and mortality provides valuable insights into the causes of CVD and information about where along the spectrum of disease development we may effectively intervene to improve outcomes in disadvantaged populations. There is little debate about the social patterning and distribution of CVD. There is, however, ongoing debate about the reason for the observed patterns. See p 3071 Much of the social gradient was attributed originally to the uneven distribution of a number of health behaviors related to diet, tobacco consumption, physical inactivity, compliance with therapeutic regimens, and differential access to high-quality medical care. As the story goes, as better educated, economically advantaged men and women learned about the risks that are related to tobacco, obesity, and inactivity, they changed their behaviors and subsequently reduced their cardiovascular risks, often giving rise to even greater disparities in coronary heart disease (CHD). We now know that differences in health behaviors account for a part of the disparities …