Miracle-dz/UniFAR-FTUs huggingface dataset:
Drug safety in pregnancy--monitoring congenital anomalies.

AIM This paper outlines research into the causes of congenital anomalies, and introduces a pan-European study. The potential roles of nurses and midwives in this area are illustrated by a case report. BACKGROUND Since the thalidomide disaster, use of drugs in pregnancy has been carefully monitored to prevent anything similar happening again. However, monitoring is incomplete and questions remain unanswered. KEY ISSUES Many medicines are essential for the health of pregnant women. However, drug use in pregnancy requires surveillance. Methods include spontaneous reporting of adverse events, cohort studies and case control studies. It is hoped that a Europe-wide study, combining data from several congenital anomaly registers, will provide a sufficiently large population to assess the impact of selected drugs on congenital anomalies. However, this work depends on the consistency of reporting by nurses and midwives. CONCLUSION Drug safety in pregnancy remains undetermined. Collaboration across Europe has the potential to provide a framework for safety evaluation. IMPLICATIONS FOR NURSING MANAGEMENT Prescribers should consider the possibility of pregnancy in women of child-bearing age. Careful review of maternal drug use in early pregnancy is essential. Midwives and nurses should be aware of adverse event drug reporting systems, including congenital anomaly registers.
AXIN1 Expression and Localization in Meningiomas and Association to Changes of APC and E-cadherin.

BACKGROUND/AIM Tumor suppressor gene AXIN1 is an inhibitor of Wnt signaling pathway. It down-regulates the pathway's main signaling effector molecule, beta-catenin, in an AXIN-based destruction complex. In the present study we investigated the involvement of AXIN1 in intracranial meningioma. MATERIALS AND METHODS Loss of heterozygosity and microsatellite instability analyses were performed. The consequences of genetic changes on protein expression levels were studied in the same patients by immunohistochemistry. RESULTS Allelic deletions of AXIN1 gene were found in 21.1% of meningiomas. Microsatellite instability was also observed in 5.3% of cases. Weak or lack of AXIN1 expression was found in 21.9% of meningiomas. We found strong statistical correlations between cytoplasmic localization of AXIN1 and its weak expression and also between the simultaneous cytoplasmic and nuclear localizations and moderate and strong expression levels (p<0.000). The findings on AXIN1 were compared to concomitant expression of APC, beta-catenin and E-cadherin in the same patients by Chi-Square tests and Pearson's correlations. Analysis revealed that AXIN1 genetic changes were significantly associated to lack of the expression of APC and presence of mutant APC proteins (p<0.018). Moderate and strong cytoplasmic and nuclear AXIN1 expressions were positively correlated to strong expression of E-cadherin (p<0.05). CONCLUSION Our findings on genetic changes and expression levels of AXIN1 bring novel data on its involvement in meningeal brain tumors and reveal AXIN1's relation to specific Wnt molecules.
Nitrogen Status Assessment for Variable Rate Fertilization in Maize through Hyperspectral Imagery

This paper presents a method for mapping the nitrogen (N) status in a maize field using hyperspectral remote sensing imagery. An airborne survey was conducted with an AISA Eagle hyperspectral sensor over an experimental farm where maize (Zea mays L.) was grown with two N fertilization levels (0 and 100 kg N ha−1) in four replicates. Leaf and canopy field data were collected during the flight. The nitrogen (N) status has been estimated in this work based on the Nitrogen Nutrition Index (NNI), defined as the ratio between the leaf actual N concentration (%Na) of the crop and the minimum N content required for the maximum biomass production (critical N concentration (%Nc)) calculated through the dry mass at the time of the flight (Wflight). The inputs required to calculate the NNI (i.e., %Na and Wflight) have been estimated through regression analyses between field data and remotely sensed vegetation indices. MCARI/MTVI2 (Modified Chlorophyll Absorption Ratio Index/Modified Triangular Vegetation Index 2) showed the best performances in estimating the %Na (R2 = 0.59) and MTVI2 in estimating the Wflight (R2 = 0.80). The %Na and the Wflight were then mapped and used to compute the NNI map over the entire field. The NNI map agreed with the NNI estimated using field data through traditional destructive measurements (R2 = 0.70) confirming the potential of using remotely sensed indices to assess the crop N condition. Finally, a method to derive a pixel based variable rate N fertilization map was proposed as the difference between the actual N content and the optimal N content. We think that the proposed operational methodology is promising for precision farming since it represents an innovative attempt to derive a variable rate N fertilization map based on the actual crop N status from an aerial hyperspectral image.
Hematological Manifestations of SLE at Initial Presentation: Is It Underestimated?

SLE can present with hematological manifestations alone or along with features of other system involvement. With a low index of clinical suspicion or inadequate follow up the diagnosis may be delayed or missed at the time of presentation, in those with hematological abnormalities as the initial manifestation. An observational study was conducted among patients of SLE, in a tertiary referral centre of North Kerala, with the purpose of estimating the proportion of patients with hematological manifestations as the initial presentation of the disease and to study their nature. It was observed that 82% of the patients had hematological manifestations at presentation. It is the most common presenting manifestation of SLE in people of North Kerala. Autoimmune hypothyroidism was one of the common coexisting abnormalities in these patients, which is not included in the American College of Rheumatology (ACR) criteria for diagnosis. Arthritis was uncommon among those who presented with hematological manifestations. A significant number of patients do not satisfy the ACR criteria at the time of diagnosis but do so on follow up. The ACR criteria are weak to diagnose such patients and therefore need revision. We therefore propose an alternative to ACR criteria as “Kozhikode criteria for SLE”.
Simple Classification using Binary Data

Binary, or one-bit, representations of data arise naturally in many applications, and are appealing in both hardware implementations and algorithm design. In this work, we study the problem of data classification from binary data and propose a framework with low computation and resource costs. We illustrate the utility of the proposed approach through stylized and realistic numerical experiments, and provide a theoretical analysis for a simple case. We hope that our framework and analysis will serve as a foundation for studying similar types of approaches.
Panoramic 3D Reconstruction Using Rotational Stereo Camera with Simple Epipolar Constraints

In this paper, we propose a novel method for panoramic 3D scene recovery using rotational stereo cameras with simple epipolar constraints. By rotating two parallel stereo cameras about a vertical axis with a constant velocity, we acquire two sampled spacio-temporal volumes which are made of the sequential images captured by a uniform angular interval. The two spacio-temporal volumes can be resampled into a set of multi-perspective panoramas. We analyze the epipolar geometry among images (panoramas and original images) of two spacio-temporal volumes. The result shows that only three types of simple epipolar constraints (epipolar line is row or column of image) exist in the two spacio-temporal volumes. Then we compute a depth map from four image pairs using a multi-baseline algorithm with the three types of epipolar constraints; that is horizontal, vertical and combination of them. Experimental results using both synthetic and real images show that our approach produces high quality panoramic 3D reconstruction.
Update for nurse anesthetists Acupressure and postoperative nausea and vomiting

*AANA Journal Course No. 25: The American Association of Nurse Anesthetists is accredited as a provider of continuing education in nursing by the American Nurses Credentialing Center Commission on Accreditation. The AANA Journal course will consist of 6 successive articles, each with objectives for the reader and sources for additional reading. At the conclusion of the 6-part series, a final examination will be printed in the AANA Journal. Successful completion will yield the participant 6 CE credits (6 contact hours), code number: 27603, expiration date: July 31, 2006. Update for nurse anesthetists
Discrimination between Upstairs and Downstairs Based on Accelerometer

An algorithm for the discrimination between human upstairs and downstairs using a tri-axial accelerometer is presented in this paper, which consists of vertical acceleration calibration, extraction of two kinds of features (Interquartile Range and Wavelet Energy), effective feature subset selection with the wrapper approach, and SVM classification. The proposed algorithm can recognize upstairs and downstairs with 95.64% average accuracy for different sensor locations, i.e. located on the subject's waist belt, in the trousers pocket, and in the shirt pocket. Even for the mixed data from all sensor locations, the average recognition accuracy can reach 94.84%. Experimental results have successfully validated the effectiveness of the proposed method.
The Cost-Effectiveness of Professional Doula Care for a Woman's First Two Births: A Decision Analysis Model.

INTRODUCTION Multiple studies have demonstrated the benefits of intrapartum doula care, including lower risk for cesarean birth and shortened labor time for nulliparous women. However, analyses investigating the cost-effectiveness of doula care are limited. This study evaluated the potential cost-effectiveness of professional doula support during a woman's first birth in a theoretical population of US women, with all women having a second birth without doula care. METHODS A cost-effectiveness model was designed to compare outcomes in women with a professional doula versus no doula labor support. A theoretical cohort of 1.6 million women, the approximate number of annual low-risk, nulliparous, term, singleton births in the United States, was used. Outcomes included mode of birth, maternal death, uterine rupture, cesarean hysterectomy, costs, and quality-adjusted life years (QALYs). Probability estimates used in the model were derived from the literature, and a cost-effectiveness threshold was set at $100,000 per QALY. Sensitivity analyses were used to investigate the robustness of the results. RESULTS In this theoretical model, professional doula care during the first birth resulted in fewer cesarean births and improved QALYs. Additionally, doula support resulted in 202,538 fewer cesarean births, 46 fewer maternal deaths secondary to fewer cesarean births, 99 fewer uterine ruptures, and 26 fewer hysterectomies, with an additional cost of $185 million and 7617 increased QALYs for the first and subsequent births. Sensitivity analyses demonstrated a professional doula was potentially cost-saving up to $884 and cost-effective up to $1360 per doula. DISCUSSION Professional doula care during a woman's first birth may lead to improved outcomes and increased QALYs during her first and second births. Given the limitations of this analysis, the cost-effectiveness estimate is likely conservative, further supporting broader integration of professional doulas into the US maternity care system and highlighting the need for higher doula care reimbursement.
Upgrading domain ontology based on latent semantic analysis and group center similarity calculation

In this paper, we will propose a domain ontology extensible method which can insert new keywords into the corresponding constructed domain ontology. The novel method uses TF-IDF (Term Frequency - Inverse Document Frequency) and LSA (Latent Semantic Analysis) to strengthen the semantic characteristic of keywords and transform the LSA matrix into a high dimensional space based on collected web pages. The similarity between keywords and concepts is evaluated by comparing the keywords on high dimensional matrix to the corresponding constructed ontology group center and individual concept. The keyword which has the highest similarity with the domain concept will be inserted into the offspring of the concept on the domain ontology and will become a new domain concept. The primary experiment uses the existing Chinese basketball ontology to examine its precision and the experimental results indicate that our proposed method has 73% accuracy.
Beyond binary relevance: preferences, diversity, and set-level judgments

In most information retrieval or filtering applications, assessor judgments form the cornerstone of system evaluation. These judgments are critical when comparing systems or training ranking algorithms. Other “judgments” such as clicks, relevance feedback or ratings are also used for tuning and selection of ranking algorithms, and more broadly for user modeling, evaluating presentation techniques, etc. However, most judgment types (including binary or graded relevance judgments, ratings, and explicit feedback) are for an individual document independent of other documents. The past several years have seen a growing interest in the use of relative judgments or preferences (Is document A better than document B? ), diversity judgments (Is a retrieved set of results diverse? ), novelty judgments (Is this document novel when added to a set? ), and implicit preferences from clicks that require considering multiple items. At the same time, there has been a surge in the development of machine learning methods for “structured learning”. These methods are capable of optimizing more complex interactions in both input features and output values as well as directly optimizing for more complex performance measures (e.g., MAP, ROC area, ranking, predicting parse trees, etc.). The SIGIR 2008 Workshop on Beyond Binary Relevance: Preferences, Diversity, and SetLevel judgments, held in conjunction with the 31st Annual International ACM SIGIR Conference, explored research challenges at the intersection of novel measures of relevance, novel learning methods, and core evaluation issues. The goal of the workshop was to examine how the type of response elicited from assessors and users influences the evaluation and analysis of retrieval and filtering applications. For example, research suggests that asking people which of two results they prefer is faster and more reliable than asking them to make absolute judgments about the relevance of each result. Similarly, many researchers are using implicit measures, such as clicks, to evaluate systems. New methods like preference judgments or usage data require learning methods,
A rigorous exposition of the LEMMA method for analog and mixed-signal testing

The linear error-mechanism modeling technique is an effective tool for testing analog and mixed-signal devices which minimizes the number of measurements required to characterize the static transfer function of a circuit by determining a small number of parameters of a linear error model and then predicting the entire response error. This work focuses on optimizing the linear error-mechanism model algorithm (LEMMA), introducing novel refinements which are shown to improve its performance significantly. We outline the implementation of the algorithm in a tutorial manner, paying due consideration to the underlying theory where required.
Simulation driven development — Validation of requirements in the early design stages of complex systems — The example of the German toll system

Looking at the end-to-end processing, typical software-intensive systems are built as a system-of-systems where each sub-system specializes according to both the business and technology perspective. One challenge is the integration of all systems into a single system — crossing technological and organizational boundaries as well as functional domains. To facilitate the successful integration we propose the use of simulation models in parallel to the existing software engineering procedures. As an example we look at the German tolling system for heavy goods vehicles (HGVs) — a liability-critical system consisting of some 60 sub-systems including a fleet of more than 1000 000 onboard units deployed in the HGVs. Since its start in 2005 the system regularly undergoes changes and updates. To mitigate the associated costs and risks we developed a microscopic discrete event simulation (DES) model of the tolling system and use it to support both the design of planned changes and the monitoring of the day-to-day operations. The model includes the dynamic aspects of the tolling system and HGVs interacting with the system. In the article we discuss the use of realistic simulation models as part of the system design process. Since simulations are heavily used by the design process it is called Simulation Driven Development (SDD).
The apical (hPepT1) and basolateral peptide transport systems of Caco-2 cells are regulated by AMP-activated protein kinase

The effect of 5-aminoimidazole-4-carboxamide-ribonucleoside (AICAR) activation of the AMP-activated protein kinase (AMPK) on the transport of the model radiolabeled dipeptide [3H]-D-Phe-L-Gln was investigated in the human epithelial colon cancer cell line Caco-2. Uptake and transepithelial fluxes of [3H]-D-Phe-L-Gln were carried out in differentiated Caco-2 cell monolayers, and hPepT1 and glucose transporter 2 (GLUT2) protein levels were quantified by immunogold electron microscopy. AICAR treatment of Caco-2 cells significantly inhibited apical [3H]-D-Phe-L-Gln uptake, matched by a decrease in brush-border membrane hPepT1 protein but with a concomitant increase in the facilitated glucose transporter GLUT2. A restructuring of the apical brush-border membrane was seen by electron microscopy. The hPepT1-mediated transepithelial (A-to-B) peptide flux across the Caco-2 monolayers showed no significant alteration in AICAR-treated cells. The electrical resistance in the AICAR-treated monolayers was significantly higher compared with control cells. Inhibition of the sodium/hydrogen exchanger 3 (NHE3) had an additive effect to AICAR, suggesting that the AMPK effect is not via NHE3. Fluorescence measurement of intracellular pH showed no reduction in the proton gradient driving PepT1-mediated apical uptake. The reduction in apical hPepT1 protein and dipeptide uptake after AICAR treatment in Caco-2 cells demonstrates a regulatory effect of AMPK on hPepT1, along with an influence on both the microvilli and tight junction structures. The absence of an associated reduction in transepithelial peptide movement implies an additional stimulatory effect of AICAR on the basolateral peptide transport system in these cells. These results provide a link between the hPepT1 transporter and the metabolic state of this model enterocyte.
An Evaluation of HMM-Based Techniques for the Recognition of Screen Rendered Text

Segmentation and recognition of screen rendered text is a challenging task due to its low resolution (72 or 96 ppi) and use of antialiased rendering. This paper evaluates Hidden Markov Model (HMM) techniques for OCR of low resolution text -- both on screen rendered isolated characters and screen rendered text-lines -- and compares it with the performance of other commercial and open source OCR systems. Results show that HMM-based methods reach the performance of other methods on screen rendered text and yield above 98% character level accuracies on both screen rendered text-lines and characters.
Spatial learning induces predominant downregulation of cytosolic proteins in the rat hippocampus

Spatial learning is known to depend on protein synthesis in the hippocampus. Whereas the role of the hippocampus in spatial memory is established, the biochemical and molecular mechanisms underlying this process are poorly understood. To comprehend the complex pattern of protein expression induced by spatial learning, we analyzed alterations in the rat hippocampus proteome after 7 days of spatial learning in the Morris water maze. Forty Wistar rats were randomized into two groups. Animals of group A learned to localize a hidden platform in the water maze. Animals of group B served as controls and spent exactly the same time in the water maze as animals of group A. However, no platform was used in this test and the rats could not learn to localize the target. After the last trial, hydrophilic proteins from the hippocampus were isolated. A proteome‐wide study was performed, based on two‐dimensional gel electrophoresis and mass spectrometry. Compared with non‐learning animals, 53 (70%) proteins were downregulated and 23 (30%) proteins were upregulated after 7 days in rats with spatial learning. The overall changes in protein expression, as quantified by the induction factor, ranged from −1.62 (downregulation to 62%) to 2.10 (upregulation by 110%) compared with controls (100%). Most identified proteins exhibit known functions in vesicle transport, cytoskeletal architecture, and metabolism as well as neurogenesis. These findings indicate that learning in the Morris water maze has a morphological correlate on the proteome level in the hippocampus.
On using mixed-initiative control: A perspective for managing large-scale robotic teams

Prior work suggests that the potential benefits of mixed initiative management of multiple robots are mitigated by situational factors, including workload and operator expertise. In this paper, we present an experiment where allowing a supervisor and group of searchers to jointly decide the correct level of autonomy for a given situation (“mixed initiative”) results in better overall performance than giving an agent exclusive control over their level of autonomy (“adaptive autonomy”) or giving a supervisor exclusive control over the agent's level of autonomy (“adjustable autonomy”), regardless of the supervisor's expertise or workload. In light of prior work, we identify two elements of our experiment that appear to be requirements for effective mixed initiative control of large-scale robotic teams: (a) Agents must be capable of making progress toward a goal without having to wait for human input in most circumstances. (b) The operator control interface must help the human to rapidly understand and modify the progress and intent of several agents.
Implementing First Class Relationships in Java

Relationships have been an essential component of OO design since the 90s but OO languages still do not support firstclass relationships. Hence, programmers must implement relationships in an ad-hoc fashion which results in unnecessarily complex code. We have developed a new model for relationships in OO which distinguishes tuples and relationships (mutable sets of tuples) and supports both as first-class constructs. This paper describes the design of a library for Java which provides this model.