Miracle-dz/UniFAR-FTUs huggingface dataset:
[Risk factors on the recurrence of ischemic stroke and the establishment of a Cox's regression model].

OBJECTIVE To investigate the risk factors and establish the Cox's regression model on the recurrence of ischemic stroke. METHODS We retrospectively reviewed consecutive patients with ischemic stroke admitted to the Neurology Department of the Hebei United University Affiliated Hospital between January 1, 2008 and December 31, 2009. Cases had been followed since the onset of ischemic stroke. The follow-up program was finished in June 30, 2010. Kaplan-Meier methods were used to describe the recurrence rate. Monovariant and multivariate Cox's proportional hazard regression model were used to analyze the risk factors associated to the episodes of recurrence. And then, a recurrence model was set up. RESULTS During the period of follow-up program, 79 cases were relapsed, with the recurrence rates as 12.75% in one year and 18.87% in two years. Monovariant and multivariate Cox's proportional hazard regression model showed that the independent risk factors that were associated with the recurrence appeared to be age (X₁) (RR = 1.025, 95%CI: 1.003 - 1.048), history of hypertension (X₂) (RR = 1.976, 95%CI: 1.014 - 3.851), history of family strokes (X₃) (RR = 2.647, 95%CI: 1.175 - 5.961), total cholesterol amount (X₄) (RR = 1.485, 95%CI: 1.214 - 1.817), ESRS total scores (X₅) (RR = 1.327, 95%CI: 1.057 - 1.666) and progression of the disease (X₆) (RR = 1.889, 95%CI: 1.123 - 3.178). Personal prognosis index (PI) of the recurrence model was as follows: PI = 0. 025X₁ + 0. 681X₂ + 0. 973X₃ + 0. 395X₄ + 0. 283X₅ + 0. 636X₆. The smaller the personal prognosis index was, the lower the recurrence risk appeared, while the bigger the personal prognosis index was, the higher the recurrence risk appeared. CONCLUSION Age, history of hypertension, total cholesterol amount, total scores of ESRS, together with the disease progression were the independent risk factors associated with the recurrence episodes of ischemic stroke. Both recurrence model and the personal prognosis index equation were successful constructed.
Business Process Model and Business Rule Integration - Towards a Decision Framework

Information systems architectures are becoming increasingly complex and fragmented. As a result, organizations struggle to cope with change propagation, compliance management, and interoperability. Two major components in current information system architectures in terms of modeling business requirements are business processes and business rules. Although the need for business processes and business rules to be modeled in an integrated manner is well established, the body of knowledge on integrated modeling of the two is limited. To investigate in this topic, the Ph.D. project is divided into 4 studies. The first study aims to identify and evaluate what factors affect integrated vs separated modeling decisions. The second study aims to examine the effect of integrated modeling on process understanding. The third study aims to develop a decision framework that can guide business process modelers in making decisions about how to model a business rule.
Subsalt Steep Dip Imaging Study With 3D Acoustic Modeling

SUMMARY W e present a 3D acoustic wave equation modeling study with the objective of understanding imaging challenges for steep dips (faults and three-way closure) beneath allochthonous salt sheets. Narrowazimuth, wide-azimuth and full-azimuth surface acquisition configurations as well as a 3D vertical seismic profile (VSP), are simulated using a two-way acoustic finite-difference modeling algorithm and followed by reverse time migration (RTM). Modeling results show that even full-azimuth surface seismic is not able to image steeply dipping subsalt events associated with faults and three-way traps. Only a 3D VSP is able to image targeted subsalt steep dips by placing receivers below the salt. The imaging success of VSP in this study emphasizes its complementary role to surface seismic.
Robotic needle insertion: effects of friction and needle geometry

Two experiments were performed to determine the effects of friction and needle geometry during robotic needle insertion into soft tissues. In Experiment I, friction forces along the instrument axis were characterized during needle insertion into bovine liver under CT fluoroscopic imaging. Because the relative velocity of the tissue and needle affect viscous and Coulomb friction, the needle insertion process was segmented into several phases of relative motion: none, partial and complete. During the complete relative motion phase, it was found that Coulomb friction accounts for the majority of needle force. In Experiment II, insertion forces along and orthogonal to the needle axis were measured during insertion into a silicone rubber phantom with a consistency similar to liver. The effects of needle diameter and tip type (bevel, cone, and triangle) on insertion force were characterized. A bevel tip causes more needle bending and is more easily affected by tissue density variations. Forces for larger diameter needles are higher due to increased cutting and friction forces. These results may be used in the control of needle insertion for robot-assisted percutaneous therapies.
Multi-Grained Role Labeling Based on Multi-Modality Information for Real Customer Service Telephone Conversation

Large-scale customer service call records include lots of valuable information for business intelligence. However, the analysis of those records has not utilized in the big data era before. There are two fundamental problems before mining and analyses: 1) The telephone conversation is mixed with words of agents and users which have to be recognized before analysis; 2) The speakers in conversation are not in a pre-defined set. These problems are new challenges which have not been well studied in the previous work. In this paper, we propose a four-phase framework for role labeling in real customer service telephone conversation, with the benefit of integrating multi-modality features, i.e., both low-level acoustic features and semantic-level textual features. Firstly, we conduct ΔBayesian Information Criterion (ΔBIC) based speaker diarization to get two segments clusters from an audio stream. Secondly, the segments are transferred into text in an Automatic Speech Recognition (ASR) phase with a deep learning model DNN-HMM. Thirdly, by intergrating acoustic and textual features, dialog level role labeling is proposed to map the two clusters into the agent and the user. Finally, sentence level role correction is designed in order to label results correctly in a fine-grained notion, which reduces the errors made in previous phases. The proposed framework is tested on two real datasets: mobile and bank customer service calls datasets. The precision of dialog level labeling is over 99.0%. On the sentense level, the accuracy of labeling reaches 90.4%, greatly outperforming traditional acoustic features based method which achieves only 78.5% in accuracy.
High Resolution Range Profile Recognition Using Robust Kernel Neighborhood Preserving Projection

A new manifold learning algorithm, called robust kernel neighborhood preserving projection (RKNPP), is presented and applied to radar target recognition based on high resolution range profiles. RKNPP attempts to map the high-dimensional data into such a low-dimensional space where points belonging to the same class are close to each other while points belonging to different classes are far away from each other, while preserving the main geometric structure of the original data. A sophisticated distance metric is utilized to construct the neighborhood graph of the input data, which has several good properties that are helpful to limit the effect of noise, and thus make RKNPP a robust classification method for real-world data. Moreover, in RKNPP, a simple technique of eigenvalue decomposition is applied to deal with the small sample size problem, to which not much attention has been paid in many manifold learning algorithms. Experimental results on measured data demonstrate the promising performance of the proposed method.
Sigma lenses: focus-context transitions combining space, time and translucence

Focus + context techniques such as fisheye lenses are used to navigate and manipulate objects in multi-scale worlds. They provide in-place magnification of a region without requiring users to zoom the whole representation and consequently lose context. Their adoption is however hindered by usability problems mostly due to the nature of the transition between focus and context. Existing transitions are often based on a physical metaphor (magnifying glass, fisheye, rubber sheet), and are almost always achieved through a single dimension: space. We investigate how other dimensions, namely time and translucence, can be used to achieve more efficient transitions. We present an extension to Carpendale's framework for unifying presentation space accommodating these new dimensions. We define new lenses in that space, called Sigma lenses, and compare them to existing lenses through experiments based on a generic task: focus targeting. Results show that one new lens, the Speed-coupled flattening lens, significantly outperforms all others.
A comparison of HoNOS with the Social Behaviour Schedule in three settings

The need for short methods of assessment are often in conflict with the desire for comprehensiveness. This study compared two assessment instruments, the recently developed Health of the Nation Outcome Scale (HoNOS) and the Social Behaviour Schedule (SBS) to investigate their ability to discriminate levels of disability. Three long-stay patient groups in different settings were assessed. Data were compared across groups selected on the basis of likelihood for discharge. The SBS, but not HoNOS, was found to discriminate between the patient group with the least likelihood for discharge from the two patient groups with less severe difficulties. HoNOS, but not the SBS, discriminated between the two less severe groups. Although HoNOS has many advantages with regard to brevity it may lack sufficient discriminatory power for certain patient groups.
Monitoring Recovery of Cognitive Function Following Severe Traumatic Brain Injury

Abstract We report on the development of a new assessment tool to monitor recovery after severe traumatic brain injury (TBI). Although a number of scales exist to identify such recovery, most are limited if one is interested in monitoring small changes or in setting goals for rehabilitation. This is due to the fact that items are too broad, they may cross more than one dimension (e.g. cognition and motor functioning) and there is a danger that recording of responses may be too subjective. The Wessex Head Injury Matrix (WHIM) was developed to avoid these problems. We observed 88 people with severe TBI. These were consecutive admissions to two hospitals. Mean coma duration was 14 days and mean duration of post traumatic amnesia (PTA) was 56 days. Of 145 behaviours observed, we selected 62 and each behaviour was compared to every other behaviour to determine a likely order of recovery. The resulting WHIM is an observational tool to assess and monitor cognitive recovery after severe head injury. It can be used with patients who are in coma, just out of coma or who are minimally conscious. Two case examples are provided.
Margin-Based Discriminative Training for String Recognition

Typical training criteria for string recognition like for example minimum phone error (MPE) and maximum mutual information (MMI) in speech recognition are based on a (regularized) loss function. In contrast, large-margin classifiers-the de-facto standard in machine learning-maximize the separation margin. An additional loss term penalizes misclassified samples. This paper shows how typical training criteria like for example MPE or MMI can be extended to incorporate the margin concept, and that such modified training criteria are smooth approximations to support vector machines with the respective loss function. The proposed approach takes advantage of the generalization bounds of large-margin classifiers while keeping the efficient framework for conventional discriminative training. This allows us to directly evaluate the utility of the margin term for string recognition. Experimental results are presented using the proposed modified training criteria for different tasks from speech recognition (including large-vocabulary continuous speech recognition tasks trained on up to 1500-h audio data), part-of-speech tagging, and handwriting recognition.
A Comparison of PNN and SVM for Stock Market Trend Prediction using Economic and Technical Information

Neural Networks (PNN) and Support vector machines (SVM) are employed to predict stock market daily trends: ups and downs. The purpose is to examine the effect of macroeconomic information and technical analysis indicators on the accuracy of the classifiers. In addition, the study aims to study their joint effect on the classification performance when used together. First, Granger tests were performed to identify causal relationships between the input variables and the predicted stock returns. Then, lagged returns to be considered in the input space are identified by use of autocorrelation function. Finally, the hit ratio of predictions by P N N a n d SVM were compared. It is found that macroeconomic information is suitable to predict stock market trends than the use of technical indicators. In addition, the combination of the two sets of predictive inputs does not improve the forecasting accuracy. Furthermore, the prediction accuracy improves when trading strategies are considered.
The Research on Real-Time Map-Matching Algorithm

This paper presents a compatible map-matching algorithm for intersection: multi-weight probability of real-time map-matching algorithm. The map-matching algorithm divides in three different stages: the initial matching stage, the cross region matching stage, the determining location stage in the matching road. The algorithm takes different procedures for the three stages to improve the matching and displaying accuracy. The results of simulation in Matlab platform show that comparing with the present existing algorithms. The multi-algorithm does not introduce complex operations, but significantly reduces the matching errors of vehicles along road directions and the probability of wrong matching junction regions. Meanwhile, it helps to improve the display for intersection region matching.
The Effects of School Quality and Family Functioning on Youth Math Scores: A Canadian Longitudinal Analysis

This paper tries to disentangle the relative importance of family and school inputs on a child's cognitive achievement as measured by her percentile score on a mathematics test. We replicate a study by Todd and Wolpin (2007) in the United States with Canadian data. In contrast to their work that uses state-level indicators of school quality, we estimate our model with data from Statistics Canada's National Longitudinal Survey of Children and Youth (NLSCY) which provides micro-level information on the family and school history of the child. The sample used for the analysis is based on the 7- to 15-year-old longitudinal children who have completed at least two consecutive math tests. As in Todd and Wolpin, we conclude that cognitive outcomes are determined by current and past family inputs. Contrary to them, who find no impact of school inputs, we find that the quality of schools has a positive impact on achievement in mathematics.
Ball Catching Performance in Children With Developmental Coordination Disorder

The aim of this study was to compare the quality of ball catching performance of children with DCD to the performance of younger typically developing children. The outcome measures used were a modified ball catching item of the Test of Gross Motor Development and the number of grasping errors in a ball catching test. In the study, children with DCD were matched with younger typically developing children according to gender and the number of caught balls in the ball catching test. Children with DCD made significantly more grasping errors and scored significantly lower on the modified TGMD-item. Children with DCD were not only delayed in ball catching but they also seemed to use different movement strategies compared to younger typically developing children.
TOXICOKINETICS OF 2-METHYLIMIDAZOLE IN MALE AND FEMALE F344 RATS

The toxicokinetics of 2-methylimidazole (2-MI) were studied in male and female Fischer 344 rats after a single iv dose of 10 mg/kg or gavage dose of 25, 50, or 100 mg/kg. The 2-MI was formulated in 0.05 M phosphate-buffered saline (pH 7.4). The iv profiles could be best described by a two-compartment model with first-order elimination. The terminal elimination half-life, volume of distribution at steady state, and clearance values were 0.78 and 0.85 h -1 , 1.5 and 1.9 L, and 4.97 and 12.0 L/h/kg for males and females, respectively. After a gavage dose, the plasma concentration time profiles could be best described by a one-compartment model, no lag phase, and first-order absorption and elimination. The peak 2-MI plasma concentrations increased proportionately with dose and were reached within 35 to 50 min ( T max ) for all groups. The estimated half-life value for 2-MI was about 1 h for the iv group and the male 25-, 50-, or 100-mg/kg groups and female 25-mg/kg groups. Clearance increased for the male 100- and female 50- and 100- mg/kg groups. For a given dose group, clearance was also two to three times greater for female rats when compared to male rats. Absolute bioavailability for 2-MI was estimated to approach 97%. The results of this study indicated that 2-MI was (1) rapidly and completely absorbed, (2) quickly eliminated, (3) cleared differently for females than for males, (4) affected somewhat by dose for females, and (5) unlikely to undergo tissue accumulation following repeated exposure.
A Study of Occasional and Intensive Weapon Carrying Among Adolescents Using a Nationally Representative Sample

This study employed the National Longitudinal Study of Adolescents (Add Health) data, a nationally representative sample of adolescents. The focus of the study was to examine whether similar risk factors underlie both occasional and intensive adolescent weapon carrying. Multinomial logistic regression analyses revealed that the characteristics of the two types of weapon carriers are largely overlapping but with some disparities. In addition, this study revealed a strong effect of prior victimization on the probability of weapon carrying, employing a victimization measure that included only serious and violent victimization experiences.
Current and Past Strategies for Bacterial Culture in Clinical Microbiology

SUMMARY A pure bacterial culture remains essential for the study of its virulence, its antibiotic susceptibility, and its genome sequence in order to facilitate the understanding and treatment of caused diseases. The first culture conditions empirically varied incubation time, nutrients, atmosphere, and temperature; culture was then gradually abandoned in favor of molecular methods. The rebirth of culture in clinical microbiology was prompted by microbiologists specializing in intracellular bacteria. The shell vial procedure allowed the culture of new species of Rickettsia. The design of axenic media for growing fastidious bacteria such as Tropheryma whipplei and Coxiella burnetii and the ability of amoebal coculture to discover new bacteria constituted major advances. Strong efforts associating optimized culture media, detection methods, and a microaerophilic atmosphere allowed a dramatic decrease of the time of Mycobacterium tuberculosis culture. The use of a new versatile medium allowed an extension of the repertoire of archaea. Finally, to optimize the culture of anaerobes in routine bacteriology laboratories, the addition of antioxidants in culture media under an aerobic atmosphere allowed the growth of strictly anaerobic species. Nevertheless, among usual bacterial pathogens, the development of axenic media for the culture of Treponema pallidum or Mycobacterium leprae remains an important challenge that the patience and innovations of cultivators will enable them to overcome.
Organizational Narcissism Scale (ONS)

Narcissism is a kind of psychological case can be experienced by people or organizations with healthy or pathological dimensions. The goal of this work is to develop a scale for measuring organizational narcissism. This scale is developed in in two phases, and every dimension (leadership and authority, anticipation of recognition, grandiosity, self admiration and exhibition) of the scale strongly, positively correlates with the other dimensions, as well as with the scale as a whole. Test-retest process is used. To the first phase 762 managers and workers from small to mid-sized companies in various sectors have contributed to the second one the same group have participated and 718 of them answered. The validity and reliability analysis done by providing a reliable measurement tool, the scale will help determine whether organizational narcissism is healthy or pathological. It is ready to be used by the company managers who want to learn the narcissism level of their organizations.
Fetal cells in maternal blood

Fetal lymphocytes, trophoblasts, and nucleated red blood cells have each been separated from maternal blood by methods such as flow cytometry, magnetic cell sorting, and charge flow separation. The frequency of fetal cells among circulating maternal mononuclear cells remains to be ascertained. Current estimates range from about 10−5 to 10−7, but the numbers may be increased in women carrying aneuploid fetuses. Fetal cells separated from maternal blood have been studied by methods such as polymerase chain reaction and fluorescence in situ hybridization. Among fetal conditions so far identified are sex; human leukocyte antigen and Rh blood types; trisomy 13, 18 and 21; triploidy; and sickle cell anemia and thalassemia. Thus, fetal cell separation might one day be used for screening of the common aneuploidies and, ultimately, for prenatal diagnosis. Individual fetal erythroid precursors have been cultured after separation in some laboratories. Culturing and karyotyping of separated fetal cells might enable diagnosis of a spectrum of chromosomal and genetic disorders. Further development will be required, however, before regular clinical application of these methodologies.
Time Scales and Organizational Theory

A critical specification lacking from much theory and research on organizations is that of time scale. Specification of the relevant time scale is as critical as the specification of the appropriate level or unit of analysis, a concept to which it is related. We define and explore five types of time scales and consider their implications for both the social constructionist and positivist approaches. Using examples from strategy and organizational theory, we show how the choice of time scale has important implications for the development of theory.