Miracle-dz/UniFAR-FTUs huggingface dataset:
Nurse Leader Initiatives to Decrease Job Stress on the Acute Care Unit

Nurses are expected to provide high quality, safe healthcare in working environments where limited resources and increasing responsibilities are common. An imbalance between providing high quality care and managing or minimizing the assault of stressors can lead to increased job stress. Nurses on the Acute Care Unit (ACU) of a Midwestern, rural hospital utilized the Nursing Stress Scale (NSS) developed by Gray-Toft & Anderson (1981) to analyze aggregated mean data self-reported scores for job stressors before and after focused change initiatives. Nurses selected and led change initiatives for the top five scoring stressors that nurses concurred were modifiable using interprofessional interventions. Multidisciplinary teams collaborated to choose educational sessions, updated resources, and revised communication tools in an attempt to decrease job stress on the unit. The results of the second NSS when compared to the first survey overall demonstrated decreased stress mean scores in six of the seven subscales. The specific nurse led unit initiatives decreased self-reported job stress in four of the five areas. This project found encouraging results in decreasing job stress by implementing nurse led change initiates on the ACU. Keywords: nursing, job stress, leadership, change initiatives
The Elusive Metric for Low-Power Architecture Research

The Energy-Delay product or ED product was proposed as a metric to gauge design ee ctiveness. This metric is widely used in the area of low-power architecture research, however it is also often improperly used when reporting a new architecture design that addresses energy-performance effectiveness. In this paper, we discuss two common fallacies from the literature: (1) the way the ED product is calculated, and (2) issues of introducing additional hardware structures to reduce dynamic switching activities. When using the ED product without meticulous consideration, a seemingly energy-ecient design could turn out to be a more energy-consuming one.
Gap-weighted subsequences for automatic cognate identification and phylogenetic inference

In this paper, we describe the problem of cognate identification and its relation to phylogenetic inference. We introduce subsequence based features for discriminating cognates from non-cognates. We show that subsequence based features perform better than the state-of-the-art string similarity measures for the purpose of cognate identification. We use the cognate judgments for the purpose of phylogenetic inference and observe that these classifiers infer a tree which is close to the gold standard tree. The contribution of this paper is the use of subsequence features for cognate identification and to employ the cognate judgments for phylogenetic inference.
Novel Half-Bridge Inductive DC–DC Isolated Converters for Fuel Cell Applications

This paper proposes a new class of converters based on the inductive input converters for the design of a power electronic interface for fuel cell (FC) applications. After studying the half-bridge structure, two soft-switching dc-dc converters are analyzed: one operating in zero-voltage-switching (ZVS) mode and the other in zero-current-switching (ZCS) mode. The ZVS converter can overcome the drawbacks of the original structure but is more complicated. The ZCS converter cannot operate at duty cycles below 0.5, but is simpler and more suitable for FC applications. Flexible choice of components, low losses, high efficiency, and modular converter possibility are all interesting characteristics of these converters. Their operation principle and characteristics are presented in this paper. Experimental results on 2 kW converters of each structure validate the theoretical analysis.
Preference for Curvature: A Historical and Conceptual Framework

That people find curved contours and lines more pleasurable than straight ones is a recurrent observation in the aesthetic literature. Although such observation has been tested sporadically throughout the history of scientific psychology, only during the last decade has it been the object of systematic research. Recent studies lend support to the idea that human preference for curved contours is biologically determined. However, it has also been argued that this preference is a cultural phenomenon. In this article, we review the available evidence, together with different attempts to explain the nature of preference for curvature: sensoriomotor-based and valuation-based approaches. We also argue that the lack of a unifying framework and clearly defined concepts might be undermining our efforts towards a better understanding of the nature of preference for curvature. Finally, we point to a series of unresolved matters as the starting point to further develop a consistent research program.
Robust sheet metal bend sequencing method based on A-star algorithm

the bending stage is the most critical part in manufacturing sheet metal workpieces. Moreover, the automatic bend sequencing is a necessity for process planning. A robust method for sheet metal bend sequencing is presented in this paper, in which hard reject criteria and the preclusion method of complex bending model are both concerned. A set of solution methods in bend sequencing based on A-star algorithm is also developed accordingly. Finally, an application example of complex bending model is used to verify the presented bend sequencing method. And a CNC bending machine process planning software is developed based on it.
The Determinants of Global Bank Credit-Default-Swap Spreads

Using a sample of 161 global banks in 23 countries, we examine the applicability of market-based structural models and accounting-based bank fundamentals to price global bank credit risk. First, we find that variables predicted by structural models are significantly associated with bank CDS spreads. Second, some CAMELS indicators contain incremental information for bank CDS prices. We find no evidence in favor of one model over the other, while the combined structural and CAMELS model performs better than each individual model. Moreover, leverage and asset quality have had a stronger impact on bank CDS since the onset of the recent financial crisis. Banks in countries with lower stock market volatility, fewer entry barriers, and/or more financial conglomerate restrictions tend to have lower credit risk. Deposit insurance appears to have an adverse effect on bank CDS spreads, indicating a moral hazard problem.
Robust Texture Recognition Using Credal Classifiers

Texture classification is used for many vision systems; in this paper we focus on improving the reliability of the classification through the so-called imprecise (or credal) classifiers, which suspend the judgment on the doubtful instances by returning a set of classes instead of a single class. Our view is that on critical instances it is more sensible to return a reliable set of classes rather than an unreliable single class. We compare the traditional naive Bayes classifier (NBC) against its imprecise counterpart, the naive credal classifier (NCC); we consider a standard classification dataset, when the problem is made progressively harder by introducing different image degradations or by providing smaller training sets. Experiments show that on the instances for which NCC returns more classes, NBC issues in fact unreliable classifications; the indeterminate classifications of NCC preserve reliability but at the same time also convey significant information, reducing the set of possible classes (on most critical instances) from 24 to some 2-3.
Data-driven Natural Language Generation: Making Machines Talk Like Humans Using Natural Corpora

With the significant improvements that have been seen in speech applications, the long-held goal of building machines that can have humanlike conversations has begun to seem more reachable; there exist spoken dialog systems which can now be used effectively by much of the general public. Despite these improvements, however, applications are still frequently limited by their unnatural spoken language generation. This thesis discusses the problem of human-like spoken language generation: how to make machine-generated speech more like natural human speech. The scope of this problem is large, with issues in speech synthesis, natural language generation, and spoken dialog, among other areas. The work in this thesis is primarily focused on natural language generation, with some discussion of the issues related to speech synthesis and the intersection between synthesis and language generation. In particular, we discuss a method that uses signal modifications of the synthesized waveforms to emulate what humans do when trying to be understood better while speaking in noisy conditions. One of the main differences between humanand machineproduced speech is in understandability; natural human speech is typically easier to understand. We describe a general framework, which we call uGloss, designed to improve the understandability of spoken generation of complex information. The uGloss framework employs a set of tactical generation strategies that attempt to take the expected capability of the human listener into account; by staying within those abilities the resulting spoken output is typically more easily understood. Though uGloss can improve understandability, it is not a complete solution to machine-generated human-like speech. In many other fields, from speech recognition and synthesis, to parsing and understanding, using corpus-based statistical knowledge has led to improved systems. We propose a similar data-driven approach intended to improve language generation systems, specifically for speech and dialog applications. Our proposed approach – the MOUNTAIN language generation system – is a fully-automatic approach which uses machine translation techniques to generate novel examples from a natural corpus. This system is designed to be a domain-independent method for training a generator that can produce human-like language in speech applications, by translating the machine’s internal representation of
A Hox-Eya-Pax Complex Regulates Early Kidney Developmental Gene Expression

ABSTRACT During embryonic development, the anterior-posterior body axis is specified in part by the combinatorial activities of Hox genes. Given the poor DNA binding specificity of Hox proteins, their interaction with cofactors to regulate target genes is critical. However, few regulatory partners or downstream target genes have been identified. Herein, we demonstrate that Hox11 paralogous proteins form a complex with Pax2 and Eya1 to directly activate expression of Six2 and Gdnf in the metanephric mesenchyme. We have identified the binding site within the Six2 enhancer necessary for Hox11-Eya1-Pax2-mediated activation and demonstrate that this site is essential for Six2 expression in vivo. Furthermore, genetic interactions between Hox11 and Eya1 are consistent with their participation in the same pathway. Thus, anterior-posterior-patterning Hox proteins interact with Pax2 and Eya1, factors important for nephrogenic mesoderm specification, to directly regulate the activation of downstream target genes during early kidney development.
Current status of atopic dermatitis in Japan

Atopic dermatitis (AD) is a common, chronic or chronically relapsing, severely pruritic, eczematous skin disease. AD is the second most frequently observed skin disease in dermatology clinics in Japan. Prevalence of childhood AD is 12-13% in mainland Japan; however, it is only half that (about 6%) in children from Ishigaki Island, Okinawa. Topical steroids and tacrolimus are the mainstay of treatment. However, the adverse effects and emotional fear of long-term use of topical steroids have induced a "topical steroid phobia" in patients throughout the world. Undertreatment can exacerbate facial/periocular lesions and lead to the development of atopic cataract and retinal detachment due to repeated scratching/rubbing/patting. Overcoming topical steroid phobia is a key issue for the successful treatment of AD through education, understanding and cooperation of patients and their guardians.
Nitro: A Fast, Scalable In-Memory Storage Engine for NoSQL Global Secondary Index

We present Nitro, a high-performance in-memory key-value storage engine used in Couchbase 4.5 Global Secondary Indexes. The Nitro storage engine is well suited for the recent hardware trends like large amounts of memory and many CPU cores. The storage engine leverages latch-free data structures and tries to achieve linear scalability for the index read-write operations. The Nitro storage engine offers concurrent readers and writers, lightweight database snapshots, stable scan, backup and recovery operations. We integrated Nitro into the Couchbase Global Secondary Indexes (GSI) and observed significant improvement in performance compared to our disk oriented storage engine configured with the same amount of memory for buffer cache. On a 32 core machine, we observed an end-to-end GSI server insertion throughput of 1,650,000 entries/sec and index update throughput of 822,000 entries/sec. A single instance of Nitro data structure running on a 40 core machine achieved a peak insertion throughput of 4 million index entries/sec and entry lookup throughput of 10 million lookups/sec.
Proposed Algorithm for Edge Detection in Biomedical Images based Numerical Approach

In this paper we present a new algorithm for detection the edge in biomedical images depends on least square approximation method which considered one of the types of the numerical methods. Biomedical image processing has been undergoing rapid changes driven by better hardware and software. Much of the software is based on new methods. It is useful to base biomedical engineering principles on rigorous mathematical foundations for the development of software methods to be integrated into therapy systems. We focus edge detection task in biomedical images which is a key problem. We will show how proposed method can detection on the edge in images with high efficiency compare with standard methods. General Terms Biomedical Informatics, Image Processing.
Prevalence of respiratory symptoms at two time points in a population of children in Manchester—a cohort study

Objective Although the prevalence of asthma and atopy has been noted to have increased in recent decades, patterns of asthma prevalence have, traditionally, been difficult to track. Most reports on trends in childhood asthma have been cross-sectional measuring the prevalence in cohorts of similar aged children at different time points. The aim of this paper is to report on the prevalence of symptoms in the same cohort at two separate time points. Design Retrospective cohort study. Setting Community-based study, Central Manchester. Participants MANCAS1, study n=5086, participation n=2414. MANCAS2, study n=6338, participation n=1608. Children born in a hospital in Manchester within specified dates and still living or attending a school in Central Manchester were eligible for inclusion. Children on an ‘at-risk’ register or living with short-term carers were excluded. Outcome measures Data on respiratory symptoms were collected at two separate time points using parent completed questionnaires. Results Response rate for MANCAS1 was 47.5% and 25.4% for MANCAS2. There were 801 individuals for whom a response to both studies was received. There was a significant reduction in the prevalence of night cough (29.5% vs 18.3%, McNemar <0.01) and antibiotic use for respiratory infections (9.1% vs 4.3%, McNemar <0.01) between the two study time points. The prevalence of hay fever/eczema increased (41.6% vs 46.9%, McNemar <0.01) between the two studies. There was no significant difference in the prevalence of wheeze, exercise-induced wheeze or asthma medication. Conclusions Although this report of respiratory symptom prevalence in the same population at two time points over a 7-year period shows a constant burden of asthma symptoms, there is some suggestion of variability in asthma symptom prevalence within the cohort as the children matured while the burden of allergy symptoms increased.
Hierarchical p2p overlays for DVE: An Additively Weighted Voronoi based approach

This paper presents a support for the development of Distributed Virtual Environments (DVEs) on P2P architectures. A hierarchical overlay is defined by pairing each peer with a weight which is proportional to its networking bandwidth. Peers characterized by higher weights are assigned a greater workload, in terms of connections with other peers and of number of passive objects they manage, and can act as superpeers that offer a set of services to peers characterized by lower bandwidth. Additively Weighted Voronoi (AWV) Diagrams are exploited to define a partition of the DVE that assigns to each peer a region whose size is dependent on the peer's weight. Superpeers are modeled by sites of the tessellation that have absorbed at least the Voronoi region of another site. A set of experimental results shows that this approach can be a load balancing mechanism for peer-to-peer networks, that does not impair usual properties of Voronoi-based peer-to-peer networks.
Consistency Management in the EROS Kernel

EROS is a persistent operating system targeted towards managing resources with great longevity. The system provides a persistent single level store supporting two fundamental object types: nodes and pages. All primary objects, including memory segments and protection domains, are constructed out of these fundamental objects, and inherit their persistence. EROS is a pure capability system: access to objects is provided exclusively through the invocation of kernel enforced, secure capabilities. This paper describes the EROS Abstract Machine and the mechanisms used to achieve efficient consistency management within the system. The implementation, including all primary objects, a low overhead checkpoint/migration subsystem, and an efficient interprocess communication mechanism, requires less than 64 Kbytes of supervisor code (prior to size tuning). Comments University of Pennsylvania Department of Computer and Information Science Technical Report No.MSCIS-96-06. This technical report is available at ScholarlyCommons: http://repository.upenn. edu/cis_reports/185 Consistency Management in the EROS Kernel Jonathan S. Shapiro David J. Farber Jonathan M. Smith University of Pennsylvania School of Engineering and Applied Science Computer and Information Science Department Philadelphia, PA 19104-6389 Consist eiicy Ma ol t hIS-CIS-96-06
High-Sensitivity Troponin T and Copeptin in Non-ST Acute Coronary Syndromes: Implications for Prognosis and Role of hsTnT and Copeptin in Non-STEACS

High-sensitivity TnT (hsTnT) has been proposed to improve the diagnosis and stratification in acute coronary syndromes. Copeptin has been proposed for a rapid and accurate rule out of acute myocardial infarction, but some doubts exist about its use out of the first hours from admission. Abnormalities of serum hsTnT and copeptin levels in non-STEACS and negative TnT, could have prognostic implications. Methods. We included 122 non-STEACS patients without raised TnT, 33 disease controls and 43 healthy controls. We measured hsTnT and copeptin levels. Clinical follow-up at 12 months was performed for adverse endpoints. Results. Non-STEACS patients had raised hsTnT compared with both control groups (P = 0.036 and P < 0.001). Copeptin levels were higher in non-STEACS patients than healthy controls (P = 0.021), without differences with disease controls. Raised levels of hs-TnT presented prognostic implications [HR 3.29 (95%CI: 1.33–7.49), P = 0.010]. hs-TnT could be used for invasive approach decision, as it shows prognostic relevance in conservative approach-patients whereas remains unrelevant for catheterized-patients. Copeptin levels were not associated with adverse events. Conclusion. hsTnT levels increased in non-STEACS, were predictive of adverse events and could be important for recommending an invasive management. We cannot confirm a predictive role of copeptin out of the first hours from admission.
QRKE: Resistance to Attacks using the Inverse of the Cosine Representation of Chebyshev Polynomials

We've been able to show recently that Permutable Chebyshev polynomials (T polynomials) defined over the field of real numbers can be used to create a Diffie-Hellman-like key exchange algorithm and certificates. The cryptosystem was theoretically proven to withstand attacks using quantum computers. We additionally prove that attacks based on the inverse of the cosine representation of T polynomials fail.
Two-dimensional Radiative Transfer in Protostellar Envelopes. II. An Evolutionary Sequence

We present model spectral energy distributions (SEDs), colors, polarization, and images for an evolutionary sequence of a low-mass protostar from the early collapse stage (Class 0) to the remnant disk stage (Class III). We find a substantial overlap in colors and SEDs between protostars embedded in envelopes (Class 0-I) and T Tauri disks (Class II), especially at mid-IR wavelengths. Edge-on Class I-II sources show double-peaked SEDs, with a short-wavelength hump due to scattered light and a long-wavelength hump due to thermal emission. These are the bluest sources in mid-IR color-color diagrams. Since Class 0 and I sources are diffuse, the size of the aperture over which fluxes are integrated has a substantial effect on the computed colors, with larger aperture results showing significantly bluer colors. Viewed through large apertures, the Class 0 colors fall in the same regions of mid-IR color-color diagrams as Class I sources and are even bluer than Class II-III sources in some colors. It is important to take this into account when comparing color-color diagrams of star formation regions at different distances or different sets of observations of the same region. However, the near-IR polarization of the Class 0 sources is much higher than the Class I-II sources, providing a means to separate these evolutionary states. We varied the grain properties in the circumstellar envelope, allowing for larger grains in the disk midplane and smaller grains in the envelope. In comparing with models with the same grain properties throughout, we find that the SED of the Class 0 source is sensitive to the grain properties of the envelope only—that is, grain growth in the disk in Class 0 sources cannot be detected from the SED. Grain growth in disks of Class I sources can be detected at wavelengths greater than 100 μm. Our image calculations predict that the diffuse emission from edge-on Class I and II sources should be detectable in the mid-IR with the Space Infrared Telescope Facility (SIRTF) in nearby star-forming regions (out to several hundred parsecs).
Dilute III-PBi and III-SbBi for IR applications

In this paper, I present recent progresses on epitaxial growth and material characterizations of novel dilute III-PBi and III-SbBi. High quality dilute bismide thin films can be epitaxially grown by molecular beam epitaxy in a narrow growth parameter window. Up to 13% and 4.3% Bi is incorporated in GaSbBi and InPBi, respectively, and majority Bi atoms are at the lattice position as confirmed by Rutherford backscattering spectroscopy. For the quaternary InGaPBi and InAlPBi, the strain can be tuned from tensile to compressive by increasing Bi concentration. The thin films also reveal strong and broad photoluminescence up to 2.7 μm and large band-gap reduction. Structural and chemical analysis indicates a non-uniform distribution of Bi, and various Bi related defects are directly imaged in scanning tunneling microscopy. Such defects are the origins for deep levels confirmed by deep level transient spectroscopy and have profound effect on photoluminescence spectra.