Miracle-dz/UniFAR-FTUs huggingface dataset:
C-reactive protein, interleukin-6, and procalcitonin in the immediate postnatal period: influence of illness severity, risk status, antenatal and perinatal complications, and infection.

BACKGROUND Studies of the diagnostic accuracy of most laboratory tests for early-onset neonatal sepsis have yielded variable results. We investigated whether some of this variation might be attributable to differences in population baseline severity and risk status as well as to specific ante- and perinatal variables, independent of the presence of neonatal infection. METHODS The Score for Neonatal Acute Physiology (SNAP) was used to define illness severity, with SNAP Perinatal Extension (SNAP-PE) used to define the combined physiologic and perinatal mortality risk. A total of 134 ill newborns (19 with early-onset infection and 115 with no infection) were available for simultaneous analysis of the association of SNAP, SNAP-PE, and maternal and perinatal variables with C-reactive protein (CRP), interleukin-6 (IL-6), and procalcitonin (PCT) concentrations at birth and at 24 and 48 h of life. RESULTS Early-onset neonatal infection was associated with significant increases in CRP, IL-6, and PCT concentrations at all three time points, independent of illness severity. However, among babies without infection, higher SNAP and SNAP-PE scores were associated with higher IL-6 concentrations at birth. Certain maternal or perinatal variables altered IL-6 and PCT values in the infected as well as in the uninfected neonates. However, if different cutoff points were used at any of the three neonatal ages, PCT sensitivity and specificity were greater than those of CRP or IL-6. CONCLUSIONS Illness severity and risk status are unlikely to interfere with the use of CRP and PCT for detection of early-onset neonatal sepsis. In contrast, the diagnostic value of IL-6 at birth may be altered by physiologic severity and risk indexes. The reliability of CRP, IL-6, and PCT for the diagnosis of early-onset neonatal infection requires specific cutoff values for each evaluation time point over the first 48 h of life.
Predicting the Influence of Microvascular Structure On Tumor Response to Radiotherapy

Objective: The purpose of this study is to investigate how theoretical predictions of tumor response to radiotherapy (RT) depend on the morphology and spatial representation of the microvascular network. Methods: A hybrid multiscale model, which couples a cellular automaton model of tumor growth with a model for oxygen transport from blood vessels, is used to predict the viable fraction of cells following one week of simulated RT. Both artificial and biologically derived three-dimensional (3-D) vessel networks of well vascularized tumors are considered and predictions compared with 2-D descriptions. Results: For literature-derived values of the cellular oxygen consumption rate there is little difference in predicted viable fraction when 3-D network representations of biological or artificial vessel networks are employed. Different 2-D representations are shown to either over- or under-estimate viable fractions relative to the 3-D cases, with predictions based on point-wise descriptions shown to have greater sensitivity to vessel network morphology. Conclusion: The predicted RT response is relatively insensitive to the morphology of the microvessel network when 3-D representations are adopted, however, sensitivity is greater in certain 2-D representations. Significance: By using realistic 3-D vessel network geometries this study shows that real and artificial network descriptions and assumptions of spatially uniform oxygen distributions lead to similar RT response predictions in relatively small tissue volumes. This suggests that either a more detailed description of oxygen transport in the microvasculature is required or that the oxygen enhancement ratio used in the well known linear-quadratic RT response model is relatively insensitive to microvascular structure.
Piracy and the Legitimate Demand for Recorded Music

Abstract Publishers of computer software and music claimed losses of over $17.6 billion to piracy in 2002. Theoretically, however, piracy may raise legitimate demand through positive demand-side externalities, sampling, and sharing. Accordingly, the actual impact of piracy on the legitimate demand is an empirical issue. Addressing this issue in the context of recorded music, we develop and test hypotheses from theoretical models of piracy on international data for music CDs over the period 1994-98. Empirically, we find that the demand for music CDs decreased with piracy, suggesting that "theft" outweighed the "positive" effects of piracy. However, the impact of piracy on CD sales was considerably less than estimated by industry. We estimated that, in 1998, actual losses amounted to about 6.6% of sales, or 42% of industry estimates. But, we found evidence that publishers would have raised prices in the absence of piracy, suggesting that the actual revenue loss would have been higher.
Re-envisioning Social Studies with the Community School Model of Elsie Ripley Clapp

Given the current marginalization of social studies education in schools, this paper explores the social studies centered community-school model of Elsie Ripley Clapp, who was a significant educator, scholar, and leader within progressive education. A former graduate assistant of John Dewey, Clapp put progressive pedagogical ideology into practice in the 1920s and 1930s through her curriculum development and administrative leadership in rural schools such as: the Ballard School in Kentucky and the Arthurdale Schools in West Virginia. She developed a social studies focused, experiential curriculum rooted in her vision of schools as democratic spaces. First, biographical information about Clapp’s life, educational experiences, and commitment to social justice is provided. Second, Clapp’s community school model at the Ballard School is explored. The model, which united people across social class and centered on local history, geography, and economics, provides implications for how we might re-envision our current approaches to social studies education.
Investigation of the feasibility of a superconducting “self-healing” DC grid on a LNG carrier

The purpose of this work is to investigate the implementation of superconducting (SC) Direct Current Power Distribution on the power grid of a LNG Carrier. In the first part of the paper, the state of the art in High Temperature Superconductor technology is reviewed and an analytical approach of Superconducting DC Power Distribution on a power system is provided. In the second part, a simulation of a SC distribution line is performed during the transmission from superconducting to normal state regarding power losses and the operation of the line as a fault current limiter.
Convergence acceleration techniques for the stochastic unit commitment problem

This paper proposes a two-stage stochastic mix-integer programming formulation that addresses a unit commitment (UC) problem in a probabilistic manner. The objective of this problem is to minimize the expected operating cost for the decision time horizon under load uncertainty. The problem is solved using a standard L-shaped algorithm. We then propose some acceleration techniques to improve convergence behavior. These techniques are tested on a 9-bus system to determine computing efficiency. Results show that the proposed acceleration techniques reduce number of iterations as well as the algorithm convergence time.
Orbifolds and finite group representations

We present our recent understanding on resolutions of Gorenstein orbifolds, which involves the finite group representation theory. We concern only the quotient singularity of hypersurface type. The abelian group Ar(n) for A-type hypersurface quotient singularity of dimension n is introduced. For n=4, the structure of Hilbert scheme of group orbits and crepant resolutions of Ar(4)-singularity are obtained. The flop procedure of 4-folds is explicitly constructed through the process.
Energy efficient design in AF relay networks with bidirectional asymmetric traffic

This paper focuses on energy efficient transmission in Amplify-and-Forward (AF) relay networks with bidirectional asymmetric traffic. A joint relay selection and power allocation scheme is designed to minimize the energy consumed per bit transmitted for both one-way and two-way relay networks. Through theoretical analysis, close-form solutions for energy efficient power allocation are derived at each relay. Then the direct transmission mode or the relay consuming the least energy is chosen by the sources according to the feedback of each relay. Simulation results present the considerable energy saving ability of the proposed scheme compared with the extended best worse channel relay selection and uniform power allocation (PA) schemes.
Streaming video over variable bit-rate wireless channels

We consider streaming of video sequences over both constant and variable bit-rate (VBR) channels. Our goal is to enable decoding of each video unit before exceeding its displaying deadline and, hence, to guarantee successful sequence presentation even if the media rate does not match the channel rate. In this work, we show that the separation between a delay jitter buffer and a decoder buffer is in general suboptimal for VBR video transmitted over VBR channels. We specify the minimum initial delay and the minimum required buffer for a given video stream and a deterministic VBR channel. In addition, we provide some probabilistic statements in case that we observe a random behavior of the channel bit rate. A specific example tailored to wireless video streaming is discussed in greater detail and bounds are derived which allow guaranteeing a certain quality-of-service even for random VBR channels in a wireless environment. Simulation results validate the findings.
Improving object classification using semantic attributes

This paper shows how semantic attribute features can be used to improve object classification performance. The semantic attributes used fall into five groups: scene (e.g. ‘road’), colour (e.g. ‘green’), part (e.g. ‘face’), shape (e.g. ‘box’), and material (e.g. ‘wood’). We train classifiers from representative images for 60 semantic attributes. We first assess the accuracy of the individual classifiers, and show that they can be used to predict semantic annotations for test images. We then use output from the set of trained classifiers to create a new low-dimensional image representation. Experiments on data from the PASCAL VOC challenge show that the semantic attribute features achieve an object classification performance close to that of high-dimensional bag-of-words features, and that using a combination of semantic attribute features and bag-of-words features gives a better classification performance than using either feature set alone.
RF Transconductor Linearization Robust to Process, Voltage and Temperature Variations

Software-defined radio receivers increasingly exploit linear RF V-I conversion, instead of RF voltage gain, to improve interference robustness. Unfortunately, the linearity of CMOS inverters, which are often used to implement V-I conversion, is highly sensitive to Process, Voltage and Temperature variations. This paper proposes a more robust technique based on resistive degeneration. To mitigate third-order IM3 distortion induced by the quadratic MOSFET I-V characteristic, a new linearization technique is proposed which exploits a floating battery by-pass circuit and replica biasing to improve IIP3 in a robust way. This paper explains the concept and analyzes linearity improvement. To demonstrate operation, an LNTA with current domain mixer is implemented in a 45 nm CMOS process. Compared to a conventional inverter based LNTA with the same transconductance, it improves IIP3 from 2 dBm to a robust P IIP3 of 8 dBm at the cost of 67% increase in power consumption.
Product Line Variability Refactoring Tool

With the growing academic and industrial interest in Software Product Lines (SPL), one area demanding special attention is tool support development, which is a pre-requisite for widespread SPL practices adoption. In this paper, we present FLiPEx, a code refactoring tool that can be used for extraction of product variations in the context of developing mobile game SPLs.
A dose‐finding study of once‐daily oral telbivudine in HBeAg‐positive patients with chronic hepatitis B virus infection

Current therapy for chronic hepatitis B is suboptimal as a result of limited durable response rates, cumulative viral resistance, and/or poor tolerability. Telbivudine has potent antiviral activity against hepatitis B virus (HBV) in vitro and in the woodchuck model and has a promising preclinical safety profile. In this first clinical study of telbivudine, safety, antiviral activity, and pharmacokinetics were assessed in 43 adults with hepatitis B e antigen–positive chronic hepatitis B. This placebo‐controlled dose‐escalation trial investigated 6 telbivudine daily dosing levels (25, 50, 100, 200, 400, and 800 mg/d); treatment was given for 4 weeks, with 12 weeks' follow‐up. Serum HBV DNA levels were monitored via quantitative polymerase chain reaction. The results indicate that telbivudine was well tolerated at all dosing levels, with no dose‐related or treatment‐related clinical or laboratory adverse events. telbivudine plasma pharmacokinetics were dose‐proportional within the studied dose range. Marked dose‐related antiviral activity was evident, with a maximum at telbivudine doses of 400 mg/d or more. In the 800mg/d cohort, the mean HBV DNA reduction was 3.75 log10 copies/mL at week 4, comprising a 99.98% reduction in serum viral load. Correspondingly, posttreatment return of viral load was slowest in the high‐dose groups. Viral dynamic analyses suggested a high degree of efficiency of inhibition of HBV replication by telbivudine and helped refine selection of the optimal dose. In conclusion, these results support expanded clinical studies of this new agent for the treatment of hepatitis B. (HEPATOLOGY 2004;40:719–726.)
The study of neural estimator structure influence on the estimation quality of selected state variables of the complex mechanical part of electrical drive

This paper presents results of simulation research of off-line trained, feedforward neural-network-based state estimator. The investigated system is the mechanical part of electrical drive characterized by elastic coupling with working machine, modeled as dual-mass system. The aim of the research was to find a set of neural networks structures giving useful and repeatable results of the estimation. Mechanical resonance frequency of the system has been adopted at the level of 9.3 Hz to 10.3 Hz. Selected state variables of the mechanical system are load speed and stiffness torque of the shaft.
Analysis of the Literature on Cervical Spine Fractures in Ankylosing Spinal Disorders

Study Design: Narrative literature review. Objective: The numbers of low-energy cervical fractures seen in patients suffering from ankylosing spondylitis (also known as Bechterew disease) or diffuse idiopathic skeletal hyperostosis (also known as Forestier disease) have greatly increased over recent decades. These fractures tend to be particularly overlooked, leading to delayed diagnosis and secondary neurological deterioration. The aim of the present evaluation was to summarize current knowledge on cervical fractures in patients with ankylosing spinal disorders (ASDs). Methods: The literature was analyzed through an extensive PubMed search focusing on cervical fractures, especially with delayed diagnosis. Results: In ASDs, it was mainly the cervical spine that was found to be affected by fractures. Fifty percent of ASD patients had neurological deficits at admission, with a high probability of secondary deterioration due to an initially missed diagnosis. Multislice high-resolution imaging techniques should be the radiological standard of care if a vertebral fracture is suspected. Nevertheless, many of these spinal fractures are overlooked, leading to feared secondary deterioration of existing unstable fractures. Long posterior instrumentations were found to be the treatment of choice, followed by anterior and combined anterior-posterior instrumentations. Conclusions: Delayed diagnosis of cervical fractures in ASDs contributes to initially misinterpreted clinical symptoms, inadequate imaging techniques, and a lack of knowledge about this disease entity due to its peculiarities. Thorough assessment of the patients’ neurological morbidity at admission might reduce the occurrence of the associated fractures. The biomechanical behavior of ASD fractures is completely different from that of non-ASD fractures, so that the treatment strategy for these patients should be at least surgical, in combination with long dorsal instrumentations or combined anterior-posterior approaches.
Motor imagery EEG detection by empirical mode decomposition

The paper investigates the possibility of using empirical mode decomposition (EMD) method to detect the mu rhythm of motor imagery EEG signal. Recently the mu rhythm by motor imagination has been used as a reliable EEG pattern for brain-computer interface (BCI) system. Considering the non-stationary characteristics of the motor imagery EEG, the EMD method is proposed to detect the mu rhythm during left and right hand movement imagination. By analyzing the instantaneous amplitude and instantaneous frequency of the intrinsic mode functions (IMFs), the mu rhythm can be detected. And by Hilbert marginal spectrum, the ERD/ERS phenomenon of mu rhythm can be found. The results in this paper demonstrate that the EMD method is a effective time-frequency analysis tool for non-stationary EEG signal.
Psychological well‐being among mothers of children with cerebral palsy

Little is known about the proportion of mothers of children with cerebral palsy (CP) who experience distress, particularly in terms of depressed and anxious moods. The present study aimed to address this issue by examining the level of maternal anxious and depressed moods. The associations between maternal psychological well‐being and self‐efficacy and perception of children’s eating, sleeping and mobility were also examined. The sample comprised 78 mothers (mean age, 37 years; standard deviation, 7.91) of children with CP aged < 16 years of age. Data were collected by self‐administered questionnaires based on standard measures of anxious and depressed moods that were mailed to mothers. Results showed 29.8%, 26% and 11.7% of mothers were at low, moderate, and high risk of clinically anxious mood compared with population female norms of 23%, 13%, and 3%, respectively. A total of 22.1% and 19.5% of mothers were at low and moderate risk of clinically depressed mood compared with norms of 9% and 4%, respectively. Anxious and depressed moods were inversely associated with generalised self‐efficacy (p = 0.001) and anxious mood was inversely associated with children’s sleeping difficulties. In conclusion, levels of maternal psychological well‐being are a cause for concern and warrant exploration of interventions that will reduce maternal distress, and increase self‐efficacy.
Potential risk of exposure to selected xenobiotic residues and their fate in the food chain--part I: classification of xenobiotics.

Consumers are exposed to a diversity of chemicals in all areas of life. Air, water, soil and food are all unavoidable components of the human environment. Each of those elements influences the quality of human life, and each of them may be contaminated. We are exposed to toxic or potentially toxic compounds in many ways in our daily lives and toxicology is clearly a subject of great importance for society. This becomes apparent when we look at the types of poisons and the ways in which we are exposed to them. Indeed, the categories cover virtually all the chemicals one might expect to encounter in the environment. After consideration of this, one might well ask "Are all chemicals toxic? " Phrase as an answer: "There are no safe chemicals, only their safe use". Xenobiotics are defined here as those compounds, both organic and inorganic, produced by human beings and introduced into the environment, as well as into the food chain at concentrations that cause undesirable effects. Xenobiotics in the food chain are monitored in two forms: by testing--the objective of which is to discover unsuitable foodstuffs in the consumer`s network, and by monitoring--to obtain objective information about environmental components contamination and to harmlessness health of available foodstuffs.
Effects of Talent Management on Employees Retention: The Mediate Effect of Organizational Trust

Talent management is found to be important for modern organizations because of the advent of the Modern economy, new generations entering the human resource and the need for businesses to become more strategic and competitive, which implies new ways of managing resource and human capital. In this research, the relationship between Talent management, employee Retention and organizational trust is investigated. The aim of the article is to examine the effect of Talent management on employee Retention through organizational trust among staffs of Isfahan University in Iran. The research method is a descriptive survey. The statistical population consists of staffs of Isfahan University in Iran. The sample included 280 employees, which were selected randomly. Data have been collected by a researcher-developed questionnaire and sampling has been done through census and analyzed using SPSS and AMOS software. The validity of the instrument was achieved through content validity and the reliability through Cronbach Alpha. The results of hypothesis testing indicate that there is a significant relationship between Talent management, employee Retention and organizational trust. The study is significant in that it draws attention to the effects of talent management on organizational trust and employees Retention in organization.
Within the Framework of Course-assisted Creation, an Incremental Method to Extract Relevant Information from the Web and Integrate it in a Course Draft

Within the framework of course-assisted creation, we are developing a prototype whose goal will be to enrich an ontology of teaching concepts. To do that, we automatically query search engines with key words extracted from pages that were previously analysed (beginning with an ontology which treats on a hierarchical basis the first keywords). This analysis (lexical, syntactic and semantic), targeted towards the extraction of definitions ("this concept-X is a .etc.") and of specializations ("this concept-X comes in .etc."), is based on the exploitation of a base of syntactic templates automatically learned from the analysis of definitions of several on-line dictionaries, and from a minimal dictionary (in particular to treat synonymies). The ontology thus created finally generates a course draft that must be "finalized" manually, in spite of the use of a few subroutines for knowledge synthesis (for the moment our work is mainly focused on the enrichment of the ontology). We illustrate this method with the creation of a course on "multi-tier architectures" for which we suppose only the bases initially known.