LLukas22/scidocs huggingface dataset:
New strategy for the prenatal detection/exclusion of paternal cystic fibrosis mutations in maternal plasma.

BACKGROUND
Since the presence of fetal DNA was discovered in maternal blood, different investigations have focused on non-invasive prenatal diagnosis. The analysis of fetal DNA in maternal plasma may allow the diagnosis of fetuses at risk of cystic fibrosis (CF) without any risk of fetal loss. Here, we present a new strategy for the detection of fetal mutations causing CF in maternal plasma.


METHODS
We have used a mini-sequencing based method, the SNaPshot, for fetal genotyping of the paternal mutation in maternal blood from three pregnancies at risk of CF.


RESULTS
The paternal mutation was detected in the analysis of plasma samples from cases 1 and 3 but not in case 2. Results of a posterior conventional molecular analysis of chorionic biopsies were in full agreement with those obtained from analysis of the plasma samples.


CONCLUSIONS
The knowledge about the inheritance of the paternal mutation in a fetus may avoid the conventional prenatal diagnosis in some cases. The SNaPshot technique has been shown to be a sensitive and accurate method for the detection of fetal mutations in maternal plasma. Its ease handling, rapid and low cost makes it appropriate for a future routine clinical use in non-invasive prenatal diagnosis of cystic fibrosis.
Mutual information-based SVM-RFE for diagnostic classification of digitized mammograms

0167-8655/$ see front matter 2009 Elsevier B.V. A doi:10.1016/j.patrec.2009.06.012 * Corresponding author. Tel.: +82 2 705 8931; fax: E-mail addresses: sjyoon@sogang.ac.kr (S. Yoon), sa Computer aided diagnosis (CADx) systems for digitized mammograms solve the problem of classification between benign and malignant tissues while studies have shown that using only a subset of features generated from the mammograms can yield higher classification accuracy. To this end, we propose a mutual information-based Support Vector Machine Recursive Feature Elimination (SVM-RFE) as the classification method with feature selection in this paper. We have conducted extensive experiments on publicly available mammographic data and the obtained results indicate that the proposed method outperforms other SVM and SVM-RFE-based methods. 2009 Elsevier B.V. All rights reserved.
AIR SCORE ASSESSMENT FOR ACUTE APPENDICITIS

BACKGROUND
Acute appendicitis is the most common cause of acute abdomen. Approximately 7% of the population will be affected by this condition during full life. The development of AIR score may contribute to diagnosis associating easy clinical criteria and two simple laboratory tests.


AIM
To evaluate the score AIR (Appendicitis Inflammatory Response score) as a tool for the diagnosis and prediction of severity of acute appendicitis.


METHOD
Were evaluated all patients undergoing surgical appendectomy. From 273 patients, 126 were excluded due to exclusion criteria. All patients were submitted o AIR score.


RESULTS
The value of the C-reactive protein and the percentage of leukocytes segmented blood count showed a direct relationship with the phase of acute appendicitis.


CONCLUSION
As for the laboratory criteria, serum C-reactive protein and assessment of the percentage of the polymorphonuclear leukocytes count were important to diagnosis and disease stratification.
Primary stability and histomorphometric bone-implant contact of self-drilling and self-tapping orthodontic microimplants.

INTRODUCTION
The aim of this study was to evaluate the primary stability and the histomorphometric measurements of self-drilling and self-tapping orthodontic microimplants and the correlations between factors related to host, implant, and measuring technique.


METHODS
Seventy-two self-drilling and self-tapping implants were placed into bovine iliac crest blocks after computed tomography assessments. Insertion torque values, subjective assessments of stability, and Periotest (Medizintecknik Gulden, Modautal, Germany) measurements were performed for each implant. Twelve specimens of each group were assigned to histologic and histomorphometric assessments.


RESULTS
The differences between insertion torque values, most Periotest values, and subjective assessments of stability scores were insignificant (P >0.05). The bone-implant contact percentage of the self-drilling group (87.60%) was higher than that of the self-tapping group (80.73%) (P <0.05). Positive correlations were found between insertion torque value, cortical bone thickness, and density in both groups (P <0.05). Negative correlations between insertion torque values and Periotest values were mostly observed in the self-drilling group (P <0.05). Positive correlations were found between bone-implant contact percentages, cortical bone densities, and insertion torque values in both groups (P <0.05). The differences between insertion torque values and corresponding subjective assessments of stability scores were different in both groups (P <0.05).


CONCLUSIONS
The differences in insertion torque values, Periotest values, and subjective assessments of stability scores of self-drilling and self-tapping implants were insignificant. Self-drilling implants had higher bone-implant contact percentages than did self-tapping implants. Significant correlations were found between parameters influencing the primary stability of the implants.
Internal Validation of Predictive Logistic Regression Models for Decision-Making in Wildlife Management

Predictive logistic regression models are commonly used to make informed decisions related to wildlife management and conservation, such as predicting favourable wildlife habitat for land conservation objectives and predicting vital rates for use in population models. Frequently, models are developed for use in the same population from which sample data were obtained, and thus, they are intended for internal use within the same population. Before predictions from logistic regression models are used to make management decisions, predictive ability should be validated. We describe a process for conducting an internal model validation, and we illustrate the process of internal validation using logistic regression models for predicting the number of successfully breeding wolf packs in six areas in the US northern Rocky Mountains. We start by defining the major components of accuracy for binary predictions as calibration and discrimination, and we describe methods for quantifying the calibration and discrimination abilities of a logistic regression model. We also describe methods for correcting problems of calibration and future predictive accuracy in a logistic regression model. We then show how bootstrap simulations can be used to obtain unbiased estimates of prediction accuracy when models are calibrated and evaluated within the same population from which they were developed. We also show how bootstrapping can be used to assess coverage rates and recalibrate the endpoints of confidence intervals for predictions from a logistic regression model, to achieve nominal coverage rates. Using the data on successfully breeding wolf packs in the northern Rocky Mountains, we validate that predictions from a model developed with data specific to each of six analysis areas are better calibrated to each population than a global model developed using all data simultaneously. We then use shrinkage of model coefficients to improve calibration and future predictive accuracy for the area-specific model, and recalibrate confidence interval endpoints to provide better coverage properties. Following this validation, managers can be confident that logistic regression predictions will be reliable in this situation, and thus that management decisions will be based on accurate predictions.
Linear scaling electronic structure methods in chemistry and physics

Scientists have known the nonrelativistic equations of quantum mechanics since 1926, when Austrian physicist Erwin Schrödinger published a series of papers on quantum mechanics. As Paul Dirac pointed out in 1929, questions in quantum mechanics are in principle just questions in applied mathematics. In practice, however, solving these equations has proved challenging. In spite of the impressive computer power at our disposal, solving the basic equation of quantum mechanics—the many-electron Schrödinger equation, which rules the quantum mechanical behavior of molecules and materials at the atomic level and determines their basic properties—remains a difficult task, and will require the interplay of physics, chemistry, mathematics, and computational science. Developing new methods for electronic structure calculations is more than just developing new algorithms: it requires a deep physical and chemical understanding of many-electron systems. Combining this understanding with modern mathematical concepts leads to algorithms that exploit the peculiarities of electronic systems to yield powerful new electronic structure methods. Adapting these methods for modern computer architectures will result in powerful programs to aid the research of many scientists. In this drive for better methods, algorithms in which computing time increases linearly with respect to the number of atoms in the system are the ultimate goal. Most physical quantities are extensive—that is, they grow linearly with system size. We might therefore expect that the computational effort will grow linearly with system size as well. An even slower increase in computing time is certainly not possible unless we ignore the basic physics of the electronic system. In this article, we review the physical principles and algorithms behind the quest for electronic structure computational methods that scale linearly with respect to system size.
Reinforcement learning: The Good, The Bad and The Ugly

Reinforcement learning provides both qualitative and quantitative frameworks for understanding and modeling adaptive decision-making in the face of rewards and punishments. Here we review the latest dispatches from the forefront of this field, and map out some of the territories where lie monsters.
Debriefing after failed paediatric resuscitation: a survey of current UK practice.

OBJECTIVES
Debriefing is a form of psychological "first aid" with origins in the military. It moved into the spotlight in 1983, when Mitchell described the technique of critical incident stress debriefing. To date little work has been carried out relating to the effectiveness of debriefing hospital staff after critical incidents. The aim of this study was to survey current UK practice in order to develop some "best practice" guidelines.


METHODS
This study was a descriptive evaluation based on a structured questionnaire survey of 180 lead paediatric and emergency medicine consultants and nurses, selected from 50 UK trusts. Questions collected data about trust policy and events and also about individuals' personal experience of debrief. Free text comments were analyzed using the framework method described for qualitative data.


RESULTS
Overall, the response rate was 80%. 62% said a debrief would occur most of the time. 85% reported that the main aim was to resolve both medical and psychological and emotional issues. Nearly all involve both doctors and nurses (88%); in over half (62%) other healthcare workers would be invited, eg, paramedics, students. Sessions are usually led by someone who was involved in the resuscitation attempt (76%). This was a doctor in 80%, but only 18% of responders said that a specifically trained person had led the session. Individuals' psychological issues would be discussed further on a one-to-one basis and the person directed to appropriate agencies. Any strategic working problems highlighted would be discussed with a senior member of staff and resolved via clinical governance pathways.


CONCLUSIONS
Little is currently known about the benefits of debriefing hospital staff after critical incidents such as failed resuscitation. Debriefing is, however, widely practised and the results of this study have been used to formulate some best practice guidelines while awaiting evidence from further studies.
Clarification Questions with Feedback

In this paper, we investigate how people construct clarification questions. Our goal is to develop similar strategies for handling errors in automatic spoken dialogue systems in order to make error recovery strategies more efficient. Using a crowd-sourcing tool [7], we collect a dataset of user responses to clarification questions when presented with sentences in which some words are missing. We find that, in over 60% of cases, users choose to continue the conversation without asking a clarification question. However, when users do ask a question, our findings support earlier research showing that users are more likely to ask a targeted clarification question than a generic question. Using the dataset we have collected, we are exploring machine learning approaches for determining which system responses are most appropriate in different contexts and developing strategies for constructing clarification questions.1
A randomized, double-blind, placebo-controlled study of the efficacy and safety of 2 doses of vortioxetine in adults with major depressive disorder.

BACKGROUND
This 8-week, randomized, double-blind, placebo-controlled study, conducted August 2010-May 2012 in the United States, evaluated the safety and efficacy of vortioxetine 10 mg and 15 mg in patients with major depressive disorder (MDD). The mechanism of action of vortioxetine is thought to be related to direct modulation of serotonin (5-HT) receptor activity and inhibition of the serotonin transporter.


METHOD
Adults aged 18-75 years with MDD (DSM-IV-TR) and Montgomery-Asberg Depression Rating Scale (MADRS) total score ≥ 26 were randomized (1:1:1) to receive vortioxetine 10 mg or 15 mg or placebo once daily, with the primary efficacy end point being change from baseline at week 8 in MADRS analyzed by mixed model for repeated measures. Adverse events were recorded during the study, suicidal ideation and behavior were assessed using the Columbia-Suicide Severity Rating Scale (C-SSRS), and sexual dysfunction was assessed using the Arizona Sexual Experience (ASEX) scale.


RESULTS
Of the 1,111 subjects screened, 469 subjects were randomized: 160 to placebo, 157 to vortioxetine 10 mg, and 152 to vortioxetine 15 mg. Differences from placebo in the primary efficacy end point were not statistically significant for vortioxetine 10 mg or vortioxetine 15 mg. Nausea, headache, dry mouth, constipation, diarrhea, vomiting, dizziness, and flatulence were reported in ≥ 5% of subjects receiving vortioxetine. Discontinuation due to adverse events occurred in 7 subjects (4.4%) in the placebo group, 8 (5.2%) in the vortioxetine 10 mg group, and 12 (7.9%) in the vortioxetine 15 mg group. ASEX total scores were similar across groups. There were no clinically significant trends within or between treatment groups on the C-SSRS, laboratory values, electrocardiogram, or vital sign parameters.


CONCLUSIONS
In this study, vortioxetine did not differ significantly from placebo on MADRS total score after 8 weeks of treatment in MDD subjects.


TRIAL REGISTRATION
ClinicalTrials.gov identifier: NCT01179516.
Determinants of modern contraceptive utilization among married women of reproductive age group in North Shoa Zone, Amhara Region, Ethiopia

BACKGROUND
Ethiopia is the second most populous country in Africa with high fertility and fast population growth rate. It is also one of the countries with high maternal and child mortality rate in sub-Saharan Africa Family planning is a crucial strategy to halt the fast population growth, to reduce child mortality and improve maternal health (Millennium Development Goal 4 and 5). Therefore, this study aimed to assess the prevalence and determinants of modern contraceptive utilization among married women of reproductive age group.


METHODS
A community based cross-sectional study was conducted from August 15 to September 1, 2010 among married women aged 15-49 years in Debre Birhan District. Multistage sampling technique was used to select a total of 851 study participants. A pre-tested structured questionnaire was used for gathering data. Bivariate and multivariate logistic regression analyses were performed using SPSS version 16.0 statistical package.


RESULTS
Modern contraceptive prevalence rate among currently married women was 46.9%. Injectable contraceptives were the most frequently used methods (62.9%), followed by intrauterine device (16.8%), pills (14%), norplant (4.3%), male condom (1.2%) and female sterilization (0.8%). Multiple logistic regression model revealed that the need for more children (AOR 9.27, 95% CI 5.43-15.84), husband approve (AOR 2.82, 95% CI 1.67-4.80), couple's discussion about family planning issues (AOR 7.32, 95% CI 3.60-14.86). Similarly, monthly family income and number of living children were significantly associated with the use of modern contraceptives.


CONCLUSION
Modern contraceptive use was high in the district. Couple's discussion and husband approval of contraceptives use were significantly associated with the use of modern contraceptives. Therefore, district health office and concerned stakeholders should focus on couples to encourage communication and male involvement for family planning.
Interproximal gingivitis and plaque reduction by four interdental products.

OBJECTIVE
The study was conducted to compare the performance of three interdental products to dental floss in the control and removal of plaque, and in the reduction of gingivitis.


METHODOLOGY
One-hundred and twenty subjects were screened for the presence of interproximal sites of a size suitable for a GUMO Go-Betweens cleaner, and for being in compliance with inclusion and exclusion criteria. They were then assessed with the Plaque, Gingivitis, and Eastman Interdental Bleeding Indices (EIBI) at baseline, given a prophylaxis, randomly assigned to one of four products (Glide dental floss, Butler flossers, GUM Go-Betweens cleaners, and GUM Soft-Picks cleaners), and given product use instructions. Subjects returned at three weeks for a compliance review and at six weeks for a final visit. Plaque was assessed at the final visit before and after using the assigned products. Plaque, gingivitis, and bleeding scores were evaluated by analysis of covariance using the baseline measurements as the covariate.


RESULTS
All four interdental products significantly reduced interdental plaque from baseline to before-use at the final visit (after six weeks) employing baseline plaque as a covariate. Reductions were 16% to 24%. Similarly, use of the products at the final visit resulted in 26% to 31% reductions in plaque with the before-use plaque as a covariate. Interdental gingivitis scores showed a reduction both lingually and buccally, with reductions ranging from 27% to 36% for the former and 34% to 53% for the latter (baseline was the covariate). No statistical differences were found between the products on the lingual interdental sites. The Go-Betweens cleaners showed a statistically greater reduction in the Gingival Index score buccally than the other three products. No differences were noted among the products for the EIBI.


CONCLUSION
In this study, dental floss, the recognized "gold standard" for gingivitis reduction, was matched in performance by flossers and an interdental cleaner with small elastomeric fingers, and surpassed by an interdental brush. All products performed comparably for plaque reduction and removal.
Effectiveness of Front-Of-Pack Nutrition Labels in French Adults: Results from the NutriNet-Santé Cohort Study

BACKGROUND
To date, no consensus has emerged on the most appropriate front-of-pack (FOP) nutrition label to help consumers in making informed choices. We aimed to compare the effectiveness of the label formats currently in use: nutrient-specific, graded and simple summary systems, in a large sample of adults.


METHODS
The FOP label effectiveness was assessed by measuring the label acceptability and understanding among 13,578 participants of the NutriNet-Santé cohort study, representative of the French adult population. Participants were exposed to five conditions, including four FOP labels: Guideline Daily Amounts (GDA), Multiple Traffic Lights (MTL), 5-Color Nutrition Label (5-CNL), Green Tick (Tick), and a "no label" condition. Acceptability was evaluated by several indicators: attractiveness, liking and perceived cognitive workload. Objective understanding was assessed by the percentage of correct answers when ranking three products according to their nutritional quality. Five different product categories were tested: prepared fish dishes, pizzas, dairy products, breakfast cereals, and appetizers. Differences among the label effectiveness were compared with chi-square tests.


RESULTS
The 5-CNL was viewed as the easiest label to identify and as the one requiring the lowest amount of effort and time to understand. GDA was considered as the least easy to identify and to understand, despite being the most attractive and liked label. All FOP labels were found to be effective in ranking products according to their nutritional quality compared with the "no label" situation, although they showed differing levels of effectiveness (p<0.0001). Globally, the 5-CNL performed best, followed by MTL, GDA and Tick labels.


CONCLUSIONS
The graded 5-CNL label was considered as easy to identify, simple and rapid to understand; it performed well when comparing the products' nutritional quality. Therefore, it is likely to present advantages in real shopping situations where choices are usually made quickly.
Why is "SXSW" trending? Exploring Multiple Text Sources for Twitter Topic Summarization

User-contributed content is creating a surge on the Internet. A list of “buzzing topics” can effectively monitor the surge and lead people to their topics of interest. Yet a topic phrase alone, such as “SXSW”, can rarely present the information clearly. In this paper, we propose to explore a variety of text sources for summarizing the Twitter topics, including the tweets, normalized tweets via a dedicated tweet normalization system, web contents linked from the tweets, as well as integration of different text sources. We employ the concept-based optimization framework for topic summarization, and conduct both automatic and human evaluation regarding the summary quality. Performance differences are observed for different input sources and types of topics. We also provide a comprehensive analysis regarding the task challenges.
Stability analysis of negative impedance converter

Negative Impedance Converter (NIC) have received much attention to improve the restriction of antenna gain-bandwidth tradeoff relationship. However, a significant problem with NIC is the potential instability of unwanted oscillation due to the presence of positive feedback. For solving this problem, we propose a NIC circuit technique which is stable and has wideband characteristics of negative impedance.
A two-warehouse inventory model for items with three-parameter Weibull distribution deterioration, shortages and linear trend in demand

Depending on the type of goods and storage facilities available, perishable goods decay in different manners in terms of the initial point and rate of deterioration. The three-parameter Weibull distribution is an excellent generalization of exponential decay, with the flexibility of modeling various types of deteriorations. Since inventory management of perishable goods involves expensive storage facilities, the retailer with small storage may have to rent a warehouse. In this paper, we discuss a two-warehouse inventory model where deteriorations in the two warehouses follow independent three-parameter Weibull distributions. Transfer of units is from the rented warehouse to the own warehouse, and incurs a positive cost per unit. Demand is a non-decreasing linear function of time, shortages are backlogged and replenishment is instantaneous. A solution procedure for obtaining optimal values of initial inventory level and cycle time is presented. Sensitivity analysis is carried out. The effect of using other related deterioration distributions is illustrated.