Miracle-dz/UniFAR-FTUs huggingface dataset:
Do More Hospital Beds Lead to Higher Hospitalization Rates? A Spatial Examination of Roemer’s Law

Background Roemer’s Law, a widely cited principle in health care policy, states that hospital beds that are built tend to be used. This simple but powerful expression has been invoked to justify Certificate of Need regulation of hospital beds in an effort to contain health care costs. Despite its influence, a surprisingly small body of empirical evidence supports its content. Furthermore, known geographic factors influencing health services use and the spatial structure of the relationship between hospital bed availability and hospitalization rates have not been sufficiently explored in past examinations of Roemer’s Law. We pose the question, “Accounting for space in health care access and use, is there an observable association between the availability of hospital beds and hospital utilization? ” Methods We employ an ecological research design based upon the Anderson behavioral model of health care utilization. This conceptual model is implemented in an explicitly spatial context. The effect of hospital bed availability on the utilization of hospital services is evaluated, accounting for spatial structure and controlling for other known determinants of hospital utilization. The stability of this relationship is explored by testing across numerous geographic scales of analysis. The case study comprises an entire state system of hospitals and population, evaluating over one million inpatient admissions. Results We find compelling evidence that a positive, statistically significant relationship exists between hospital bed availability and inpatient hospitalization rates. Additionally, the observed relationship is invariant with changes in the geographic scale of analysis. Conclusions This study provides evidence for the effects of Roemer’s Law, thus suggesting that variations in hospitalization rates have origins in the availability of hospital beds. This relationship is found to be robust across geographic scales of analysis. These findings suggest continued regulation of hospital bed supply to assist in controlling hospital utilization is justified.
Mapping the Binding and Calmodulin-Dependent Activation of Nitric Oxide Synthase Isozymes

Calmodulin (CaM) is a ubiquitous cytosolic Ca 2+ -binding protein that can bind and activate numerous intracellular target proteins including the nitric oxide synthase (NOS) enzymes. There are three different isoforms of NOS found in mammals - neuronal NOS (nNOS), endothelial NOS (eNOS), and inducible NOS (iNOS) - with all three isozymes capable of producing the free radical, nitric oxide (•NO). At elevated cellular Ca 2+ concentrations, CaM is able to bind and activate nNOS and eNOS. In contrast, the iNOS isozyme is transcriptionally regulated and binds to CaM in the absence of Ca 2+ . To further investigate the differences in the association of CaM to the Ca 2+ -dependent and Ca 2+ - independent NOS isoforms, a variety of CaM mutants were employed. These included CaM-troponin C chimeras, CaM EF hand pair proteins, CaM mutants incapable of binding to Ca 2+ , methionine oxidized CaM mutants, phosphomimetic CaM mutants and central linker CaM mutants. By characterizing these CaM proteins using a variety of biochemical techniques, we have mapped the binding and the CaM-dependent activation of the NOS enzymes to study their effect on the different electron transfer steps within the NOS enzymes. In addition, fluorescence and Forster resonance energy transfer (FRET) were used to monitor the orientation and conformation of CaM when bound to the NOS peptides and enzymes. Combining these cumulative results, a working model describing the CaM-dependent regulation of iNOS is proposed.
Multiple parameter estimation with quantized channel output

We present a general problem formulation for optimal parameter estimation based on quantized observations, with application to antenna array communication and processing (channel estimation, time-of-arrival (TOA) and direction-of-arrival (DOA) estimation). The work is of interest in the case when low resolution A/D-converters (ADCs) have to be used to enable higher sampling rate and to simplify the hardware. An Expectation-Maximization (EM) based algorithm is proposed for solving this problem in a general setting. Besides, we derive the Cramér-Rao Bound (CRB) and discuss the effects of quantization and the optimal choice of the ADC characteristic. Numerical and analytical analysis reveals that reliable estimation may still be possible even when the quantization is very coarse.
Fractional Delay Based Repetitive Control with Application to PWM DC/AC Converters

In repetitive control system, the period of exogenous signals must be the integer number of sampling points. However, it can not be always satisfied in real applications. In this paper, a systematic approach for non-integer delay repetitive control system with fixed sampling rate is proposed. The proposed fractional delay based repetitive control scheme employs the design techniques in digital signal processing theory and two different implementation structures are presented. One is easy to design and the other has optimized performance. Application of the proposed method to PWM DC/AC converter systems is studied to illustrate the design procedure and performance. Experimental results demonstrate the effectiveness of the proposed approach.
Reasons Not to Cheat, Academic-Integrity Responsibility, and Frequency of Cheating

The authors investigated the relations among reasons students gave for why they would not cheat in response to a cheating vignette, self-reported cheating, and the extent to which students take responsibility for promoting academic integrity. The authors surveyed 1,086 graduate and undergraduate students. Students who said they would not cheat because of punitive consequences were more likely to report that they cheated in classes and took less responsibility for promoting academic integrity. Students whose reasons related to the value of learning, personal character, and/or it being simply not right reported less cheating and took more responsibility for academic integrity. Academic-integrity responsibility correlated with less cheating. Results are discussed in terms of the effectiveness of punishment and the significance of internalizing integrity standards.
Maternal and environmental factors in early cloned embryo development

Cloning by somatic cell nuclear transfer (SCNT) in mammals has revealed the remarkable ability of an oocyte to reprogram somatic cell nuclei and induce them to recapitulate the developmental program. Despite the success, cloning remains very inefficient. This review summarizes recent observations from cloning in mice that reveal some of the likely causes for the present inefficiency. One cause appears to be the slow pace of reprogramming combined with the early onset of genome transcription, which together cause cloned embryos to elaborate many somatic cell characteristics even before the first cleavage division. The altered phenotypes of cloned embryos render standard embryo culture conditions grossly sub-optimum. Another cause appears to be a hitherto unappreciated contribution of spindle-associated factors to early embryo development. As current procedures remove the spindle and associated factors, cloned embryos lack these factors. These observations are providing new insight into basic mammalian embryology. They also reveal possible changes to protocols that could improve the overall success of cloning.
A syllable based continuous speech recognizer for Tamil

This paper presents a novel technique for building a syllable based continuous speech recognizer when unannotated transcribed train data is available. We present two different segmentation algorithms to segment the speech and the corresponding text into comparable syllable like units. A group delay based two level segmentation algorithm is proposed to extract accurate syllable units from the speech data. A rule based text segmentation algorithm is used to automatically annotate the text corresponding to the speech into syllable units. Isolated style syllable models are built using multiple frame size (MFS) and multiple frame rate (MFR) for all unique syllables by collecting examples from annotated speech. Experiments performed on Tamil language show that the recognition performance is comparable to recognizers built using manually segmented train data. These experiments suggest that system development cost can be reduced by using minimum manual effort if sentence level transcription of the speech data is available. Index Terms: syllable based speech recognition, acoustic group delay segmentation, text segmentation, annotation.
Relationship between coronary plaque formation and NAD(P)H oxidase-derived reactive oxygen species - comparison of intravascular ultrasound finding of atherosclerotic lesions with histochemical characteristics-.

BACKGROUND Oxidative stress induced by reactive oxygen species (ROS) in the vessel wall plays an essential role in atherogenesis. Recently, we demonstrated that the generation of ROS via NAD(P)H oxidase was correlated with plaque instability using coronary specimens obtained by directional coronary atherectomy (DCA). In this study, the relation between plaque formation and ROS generation was studied based on pre-interventional examination with intravascular ultrasound (IVUS) and histological analysis of the corresponding DCA specimens. METHODS Pre-interventional IVUS images of 29 patients were analyzed. Vessel cross-sectional area (CSA), lumen CSA, plaque CSA and % plaque area were obtained at the minimal lumen site. ROS generation and expression of NAD(P)H oxidase p22phox in DCA specimens were evaluated by the dihydroethidium method and immunohistochemistry as the ratio of positive area versus total surface area in each specimen. RESULTS ROS positive area ratio in DCA specimens was correlated positively with vessel CSA, plaque CSA, and % plaque area (r = 0.51, p = 0.0046; r = 0.62, p = 0.0004; r = 0.60, p = 0.0006, respectively). Further, p22phox positive area ratio in DCA specimens was also correlated with vessel CSA and plaque CSA (r = 0.47, p = 0.0095; r = 0.47, p = 0.0103, respectively). CONCLUSIONS This in vivo study clearly demonstrates that NAD(P)H oxidase-derived ROS plays a significant role in the development of atherosclerosis.
Sequence-based control for networked control systems based on virtual control inputs

In this paper, we address the problem of controlling a system over an unreliable UDP-like network that is affected by time-varying delays and randomly occurring packet losses. A major challenge of this setup is that the controller just has uncertain information about the control inputs actually applied by the actuator. The key idea of this work is to model the uncertain control inputs by random variables, the so-called virtual control inputs, which are characterized by discrete probability density functions. Subject to this probabilistic description, a novel, easy to implement sequence-based control approach is proposed that extends any given state feedback controller designed without consideration of the network-induced disturbances. The high performance of the proposed controller is demonstrated by means of Monte Carlo simulation runs with an inverted pendulum on a cart.
Analysing of M-AHIDS with Future States on DARPA and KDD99 Benchmarks

Second generation of Multi-agent heterogeneous intrusion detection system (M-AHIDS) is a prototype proposed to detect untrusted and unusual network behaviour. The M-AHIDS is based on online traffic statistics in sFlow format acquired by network device with the sFlow agent and is able to perform a real-time surveillance of the 10 Gb networks. However, after an immense reimplementation it is capable to process also offline data set from DARPA Intrusion Detection Evaluation Data Set and KDD99 Cup data set. Offline data sets are used for the correct comparison with another IDSs. The main contribution of the system is the integration of several anomaly detection techniques, new future state prognostic and new machinery of multi-agent temporal logic with hybrid argumentation. Every detection technique is represented by featuring a specific detection autonomous agent. At this stage, every agent determines the flow trustfulness from aggregated connection. The anomalies are used as an input for machinery of multi-agent temporal logic which is represented by the logical agent. M-AHIDS is already partially implemented, tested and modified accordingly for more than three years.
Detection of Low-Abundance KRAS Mutations in Colorectal Cancer Using Microfluidic Capillary Electrophoresis-Based Restriction Fragment Length Polymorphism Method with Optimized Assay Conditions

Constitutively active KRAS mutations have been found to be involved in various processes of cancer development, and render tumor cells resistant to EGFR-targeted therapies. Mutation detection methods with higher sensitivity will increase the possibility of choosing the correct individual therapy. Here, we established a highly sensitive and efficient microfluidic capillary electrophoresis-based restriction fragment length polymorphism (µCE-based RFLP) platform for low-abundance KRAS genotyping with the combination of µCE and RFLP techniques. By using our self-built sensitive laser induced fluorescence (LIF) detector and a new DNA intercalating dye YOYO-1, the separation conditions of µCE for ΦX174 HaeIII DNA marker were first optimized. Then, a Mav I digested 107-bp KRAS gene fragment was directly introduced into the microfluidic device and analyzed by µCE, in which field amplified sample stacking (FASS) technique was employed to obtain the enrichment of the RFLP digestion products and extremely improved the sensitivity. The accurate analysis of KRAS statuses in HT29, LS174T, CCL187, SW480, Clone A, and CX-1 colorectal cancer (CRC) cell lines by µCE-based RFLP were achieved in 5 min with picoliter-scale sample consumption, and as low as 0.01% of mutant KRAS could be identified from a large excess of wild-type genomic DNA (gDNA). In 98 paraffin-embedded CRC tissues, KRAS codon 12 mutations were discovered in 28 (28.6%), significantly higher than that obtained by direct sequencing (13, 13.3%). Clone sequencing confirmed these results and showed this system could detect at least 0.4% of the mutant KRAS in CRC tissue slides. Compared with direct sequencing, the new finding of the µCE-based RFLP platform was that KRAS mutations in codon 12 were correlated with the patient’s age. In conclusion, we established a sensitive, fast, and cost-effective screening method for KRAS mutations, and successfully detected low-abundance KRAS mutations in clinical samples, which will allow provision of more precise individualized cancer therapy.
Evaluating the severity of trust to identity- management-as-a-service

The benefits of a c loud service have been well documented as reduced cost in both staff and computing infrastructure, rapid deployment, and scalabilit y and location independence. Despite all these benefits, Identity-management-as- a-Service's (IdMaaS) is struggling to gain a market presence due to an array of factors one of which is trust. In IdMaaS, trust may either be borne within the relationships amongst the actors (relying party, identity manager, identity owner, or end user) or may be actor specific. This paper will focus on trust between the identity owner and the identi ty manager within the context of third party identity management. A great effort in identifying trust issues by other researchers is acknowledged, however they did not go to the ext ent of measuring th e severity of t rust specifically related to I dMaaS. Our research shows that availability of the identity management system and security of identities are more critical concerns when compared to the cost of managing identities and fear of vendor lock-in. Above all, the research revealed that trust in IdMaaS is less than 40% at a 95% level of con fidence. Establishing the severity of tru st and its trusting factors is a more valuable input to the refinement of the IdMaaS approach. The success of IdMaaS will add to the domain of anything-as-a-service (XaaS) at the same time opening up an additional entrepreneurial avenue.
Text classification with evolving label-sets

We introduce the evolving label-set problem encountered in building real-world text classification systems. This problem arises when a text classification system trained on a label-set encounters documents of unseen classes at deployment time. We design a class-detector module that monitors unlabeled data, detects new classes, and suggests them to the administrator for inclusion in the label-set. We propose abstractions that group together tokens under human understandable concepts and provide a mechanism of assigning importance to unseen terms. We present generative algorithms leveraging the notion of support of documents in a model for (1) selecting documents of proposed new classes, and (2) automatically triggering detection of new classes. Experiments on three real world taxonomies show that our methods select new class documents with high precision, and trigger emergence of new classes with low false-positive and false-negative rates.
From Society to Self (and Back) through Place: Habit in Transactional Context

This argument extends the efforts of scholars of occupation and habit in several ways. It extends previous examinations of John Dewey's perspective on habit by bringing to the forefront his view of the social and moral dimensions of habit in the context of his larger metaphysical ground-map. That view suggests a habit process involving the transaction of the social and the individual, with habit as central to that transaction. Dewey's view is further enhanced with a portrayal of how it operates in the material experience of place and landscape. Examples from several scales of place are discussed to illustrate the essential role of material landscapes in this habit process. Using these analyses, the concept of rehabilitation is reconsidered.
HOO 2012 Error Recognition and Correction Shared Task: Cambridge University Submission Report

Previous work on automated error recognition and correction of texts written by learners of English as a Second Language has demonstrated experimentally that training classifiers on error-annotated ESL text generally outperforms training on native text alone and that adaptation of error correction models to the native language (L1) of the writer improves performance. Nevertheless, most extant models have poor precision, particularly when attempting error correction, and this limits their usefulness in practical applications requiring feedback. We experiment with various feature types, varying quantities of error-corrected data, and generic versus L1-specific adaptation to typical errors using Naive Bayes (NB) classifiers and develop one model which maximizes precision. We report and discuss the results for 8 models, 5 trained on the HOO data and 3 (partly) on the full error-coded Cambridge Learner Corpus, from which the HOO data is drawn.
Establishing the norms of scientific argumentation in classrooms

Basing its arguments in current perspectives on the nature of the scientific enterprise, which see argument and argumentative practice as a core activity of scientists, this article develops the case for the inclusion and central role of argument in science education. Beginning with a review of the nature of argument, it discusses the function and purpose of dialogic argument in the social construction of scientific knowledge and the interpretation of empirical data. The case is then advanced that any education about science, rather than education in science, must give the role of argument a high priority if it is to give a fair account of the social practice of science, and develop a knowledge and understanding of the evaluative criteria used to establish scientific theories. Such knowledge is essential to enhance the public understanding of science and improve scientific literacy. The existing literature, and work that has attempted to use argument within science education, is reviewed to show that classroom practice does provide the opportunity to develop young people's ability to construct argument. Furthermore, the case is advanced that the lack of opportunities for the practice of argument within science classrooms, and lack of teacher's pedagogical skills in organizing argumentative discourse within the classroom are significant impediments to progress in the field. © 2000 John Wiley & Sons, Inc. Sci Ed84:287–312, 2000.
The Keynesian multiplier, news and fiscal policy rules in a DSGE model

We extend the standard Smets-Wouters (2007) medium-sized DSGE model in two directions, namely to analyse the effects of news and the Keynesian multiplier, and secondly to incorporate a fiscal policy rule. We show that both the news channel and the government spending fiscal policy rule significantly improve the model fit to data. News shows up significantly, but most of its contribution comes from the fiscal rule as opposed to consumption. We then calculate the fiscal multipliers which appear more Keynesian (with a higher effect on output and a positive effect on consumption, more persistent) than argued in much preceding literature.
Linearly constrained RLS algorithm with variable forgetting factor for DS-CDMA system

In this paper we present a novel linearly constrained (LC) RLS algorithm with variable forgetting factor (VFF), and apply to the DS-CDMA system for suddenly joined narrowband interference suppression. Under Rayleigh fading channel environment, the VFF could be employed to improve the tracking capability compared with the conventional LC-RLS algorithm with fixed value of forgetting factor (FF). From computer simulation results, we verify that the proposed scheme outperforms the conventional optimal FF LC-RLS algorithm in terms of rapid tracking capability and strong narrow-band suppression.
Challenges of inter-organizational information and middleware system projects: Agility, complexity, success, and failure

There are two main ways to manage projects in business: The traditional and the agile. While the first has been historically the main Project Management methodology for businesses, the latter is gaining more support for projects involving Information Systems (IS) due to its fitting with the unpredictable nature of IS changes. To assess outcomes of projects, businesses have been using rational, narrative, organizational, and/or performative approaches. While each approach has its strengths and weaknesses, the jury is still out on which is more suitable for IS projects. More specifically, there is a lack of targeted research on which type of project management and which approach for project outcome evaluation are most relevant for Inter-Organizational Information Systems (IOIS) and Inter-Organizational Middleware System (IOMS). IOISs are automated ISs spanning across partnering organizations and aiming at synergizing their forces to increase competitiveness and cost efficiency. An Inter-Organizational Middleware System (IOMS) is the component inside IOIS that is responsible for bridging various partners' systems while holding part of the business intelligence. First, this paper collects and reviews existing project management methodologies; it then evaluates present approaches for assessing outcomes of IS projects, before it focuses on IOIS and IOMS projects, highlighting their unique characteristics and challenges. The paper concludes with a highlight of the research gap into IOIS and IOMS project management.