LLukas22/scidocs huggingface dataset:
Edad, escolarización y tareas de Fluencia Verbal para el screening de pacientes con Enfermedad de Alzheimer

Resumen: Introducción. Las pruebas de Fluencia Verbal (FV) Semántica (FVS) y Fonológica (FVF) son muy empleadas en la práctica clínica. Disponer de diferentes pruebas alternativas que además tengan en cuenta el efecto de variables sociodemográficas mejorarían su uso como tests de cribado, permitiendo diferenciar a personas con y sin Enfermedad de Alzheimer (EA). Objetivos. Comparar la capacidad discriminativa de las tareas de FVS “cosas en una casa” y “alimentos” frente a la tarea “animales” entre pacientes con EA (n = 50) y sujetos sanos (n = 50); comparar el uso de los fonemas “P”-“M”-“R” como tarea alternativa y/o paralela a los fonemas “F”-“A”-“S”; y valorar el uso combinado de ambos tipos de tareas junto con el de variables sociodemográficas para la discriminación de pacientes con EA y sujetos sanos. Resultados. Tanto la categoría semántica como fonológica muestran resultados semejantes, una alta correlación, mantienen la validez de criterio y permiten su utilización de forma paralela. El modelo de predicción que logra discriminar correctamente al 91% de los sujetos evaluados es el que incluye las tareas “cosas en una casa”, los fonemas “A” “S” y las variables edad y años de escolarización. Conclusiones. La utilización paralela de pruebas de FVS y FVF, junto con variables sociodemográficas mejora la capacidad discriminativa de las pruebas de FV. Palabras-clave: Demencia; enfermedad de Alzheimer; cribado; exploración neuropsicológica; fluidez verbal; fluidez semántica; fluencia fonológica. Title: Age, schooling and Verbal Fluency tasks for the screening of Alzheimer ́s disease patients. Abstract: Introduction. The Verbal (VF), Semantic (SF) and Phonemic Fluency (PF) tests are commonly used in clinical practice. Having different alternative tests, that could also allow for the effect of demographic variables, would improve their use as screening tests, making it possible to differentiate patients with or without Alzheimer ́s disease (AD). Aims. (1) To compare the discriminatory ability of the SF tasks “things in a house” and “food” versus the task “animals” among patients with the AD (n = 50) and healthy subjects (n = 50). (2) To compare the use of the phonemes such as “P”, “M” and “R” as an alternative and/or parallel task to the phonemes “F”, “A” and “S”. (3) To assess the combined use of both tasks with the demographic variables for the screening of AD patients and the healthy ones. Results. Both semantic and phonemic categories indicate similar results, high correlation, support the criteria validity and allow for their use in a parallel way. Among all the different roles assessed, the most successful in screening correctly 91% of the evaluated subjects is the one that includes tasks such as “things in a house”, the phonemes “A” and “S” and the age and schooling time variables. Conclusion. The parallel use of VF and PF, plus the demographic variables improve the discriminatory ability of the VF tests.
Education and training of young engineers in the light of industrial needs

The field of design and manufacture is suffering a dearth of able recruits. This is a direct consequence of the orientation of both students and teachers away from the real world of engineering towards a stylized science which is neither scholarship nor useful art. A solution to this problem that satisfies both the requirements of scholarship and industrial needs is difficult but must be achieved if we are to prosper and survive as a civilization
Perceptual audio loss function for deep learning

PESQ, Perceptual Evaluation of Speech Quality [5], and POLQA, Perceptual Objective Listening Quality Assessment [1] , are standards comprising a test methodology for automated assessment of voice quality of speech as experienced by human beings. The predictions of those objective measures should come as close as possible to subjective quality scores as obtained in subjective listening tests, usually, a Mean Opinion Score (MOS) is predicted. Wavenet [6] is a deep neural network originally developed as a deep generative model of raw audio waveforms. Wavenet architecture is based on dilated causal convolutions, which exhibit very large receptive fields. In this short paper we suggest using the Wavenet architecture, in particular its large receptive filed in order to mimic PESQ algorithm. By doing so we can use it as a differentiable loss function for speech enhancement. 1 Problem formulation and related work In statistics, the Mean Squared Error (MSE) or Peak Signal to Noise Ratio (PSNR) of an estimator are widely used objective measures and are good distortion indicators (loss functions) between the estimators output and the size that we want to estimate. those loss functions are used for many reconstruction tasks. However, PSNR and MSE do not have good correlation with reliable subjective methods such as Mean Opinion Score (MOS) obtained from expert listeners. A more suitable speech quality assessment can by achieved by using tests that aim to achieve high correlation with MOS tests such as PEAQ or POLQA. However those algorithms are hard to represent as a differentiable function such as MSE moreover, as opposed to MSE that measures the average
Price discounts significantly enhance fruit and vegetable purchases when combined with nutrition education: a randomized controlled supermarket trial.

BACKGROUND
Reducing fruit and vegetable (F&V) prices is a frequently considered policy to improve dietary habits in the context of health promotion. However, evidence on the effectiveness of this intervention is limited.


OBJECTIVE
The objective was to examine the effects of a 50% price discount on F&Vs or nutrition education or a combination of both on supermarket purchases.


DESIGN
A 6-mo randomized controlled trial within Dutch supermarkets was conducted. Regular supermarket shoppers were randomly assigned to 1 of 4 conditions: 50% price discounts on F&Vs, nutrition education, 50% price discounts plus nutrition education, or no intervention. A total of 199 participants provided baseline data; 151 (76%) were included in the final analysis. F&V purchases were measured by using supermarket register receipts at baseline, at 1 mo after the start of the intervention, at 3 mo, at 6 mo (end of the intervention period), and 3 mo after the intervention ended (9 mo).


RESULTS
Adjusted multilevel models showed significantly higher F&V purchases (per household/2 wk) as a result of the price discount (+3.9 kg; 95% CI: 1.5, 6.3 kg) and the discount plus education intervention (+5.6 kg; 95% CI: 3.2, 7.9 kg) at 6 mo compared with control. Moreover, the percentage of participants who consumed recommended amounts of F&Vs (≥400 g/d) increased from 42.5% at baseline to 61.3% at 6 mo in both discount groups (P = 0.03). Education alone had no significant effect.


CONCLUSIONS
Discounting F&Vs is a promising intervention strategy because it resulted in substantially higher F&V purchases, and no adverse effects were observed. Therefore, pricing strategies form an important focus for future interventions or policy. However, the long-term effects and the ultimate health outcomes require further investigation. This trial was registered at the ISRCTN Trial Register as number ISRCTN56596945 and at the Dutch Trial Register (http://www.trialregister.nl/trialreg/index.asp) as number NL22568.029.08.
Fospropofol: a new sedative-hypnotic agent for monitored anesthesia care.

OBJECTIVE
To summarize the published clinical data on fospropofol, critically review the safety and efficacy information, and provide pertinent information for formulary review.


DATA SOURCES
Data were collected from searches of MEDLINE (1966-June 30, 2009), EMBASE (1974-June 30, 2009), bibliographies of manuscripts, and www.fda.gov. Key search terms included fospropofol, Lusedra, Aquavan, sedative-hypnotic, and monitored anesthesia care.


STUDY SELECTION AND DATA EXTRACTION
All Phase 1, Phase 2, and Phase 3 clinical trials studying the safety and efficacy of fospropofol were reviewed.


DATA SYNTHESIS
Fospropofol is a water-soluble prodrug of propofol, a potent sedative-hypnotic agent. Propofol is highly lipophilic and is formulated in lipid-containing solvents, which have known disadvantages, including pain on injection, narrow therapeutic window with the potential to cause deep sedation, high lipid intake during long-term sedation, and risk of infection resulting from bacterial contamination. Due to its water solubility, fospropofol eliminates some of the known lipid emulsion-associated disadvantages of propofol and provides a more predictable peak onset of activity and more gradual recovery to a full state of consciousness. The pharmacokinetic and pharmacodynamic profiles of fospropofol make it an attractive agent for sedation for procedures of short duration. Unfortunately, the number of patients studied has been relatively small and the amount of safety data is limited. Of concern are reports of hypoxemia and hypotension; these reports are limited in number, but the episodes are serious and may require acute intervention. Although fospropofol holds promise for procedural sedation, due to limited safety data, the Food and Drug Administration has limited approval of fospropofol to monitored anesthesia care in patients undergoing diagnostic or therapeutic procedures.


CONCLUSIONS
Fospropofol is a viable addition to the class of sedative-hypnotic agents due to the minimization of unwanted adverse effects of propofol and maintenance of a favorable pharmacokinetic profile facilitating sedation, anxiolysis, and rapid recovery. However, there are limited safety data to justify its use without the presence of dedicated anesthesia personnel.
Molecular stressors underlying exercise training-induced improvements in K+ regulation during exercise and Na+ ,K+ -ATPase adaptation in human skeletal muscle.

Despite substantial progress made towards a better understanding of the importance of skeletal muscle K+ regulation for human physical function and its association with several disease states (eg type-II diabetes and hypertension), the molecular basis underpinning adaptations in K+ regulation to various stimuli, including exercise training, remains inadequately explored in humans. In this review, the molecular mechanisms essential for enhancing skeletal muscle K+ regulation and its key determinants, including Na+ ,K+ -ATPase function and expression, by exercise training are examined. Special attention is paid to the following molecular stressors and signaling proteins: oxygenation, redox balance, hypoxia, reactive oxygen species, antioxidant function, Na+ ,K+ , and Ca2+ concentrations, anaerobic ATP turnover, AMPK, lactate, and mRNA expression. On this basis, an update on the effects of different types of exercise training on K+ regulation in humans is provided, focusing on recent discoveries about the muscle fibre-type-dependent regulation of Na+ ,K+ -ATPase-isoform expression. Furthermore, with special emphasis on blood-flow-restricted exercise as an exemplary model to modulate the key molecular mechanisms identified, it is discussed how training interventions may be designed to maximize improvements in K+ regulation in humans. The novel insights gained from this review may help us to better understand how exercise training and other strategies, such as pharmacological interventions, may be best designed to enhance K+ regulation and thus the physical function in humans.
Identification of Hindi Dialects and Emotions using Spectral and Prosodic features of Speech

In this paper, we have explored speech features to identify Hindi dialects and emotions. A dialect is any distinguishable variety of a language spoken by a group of people. Emotions provide naturalness to speech. In this work, five prominent dialects of Hindi are considered for the identification task. They are Chattisgharhi (spoken in central India), Bengali (Bengali accented Hindi spoken in Eastern region), Marathi (Marathi accented Hindi spoken in Western region), General (Hindi spoken in Northern region) and Telugu (Telugu accented Hindi spoken in Southern region). Along with dialect identification, we have also carried out emotion recognition in this work. Speech database considered for dialect identification task consists of spontaneous speech spoken by male and female speakers. Indian Institute of Technology Kharagpur Simulated Emotion Hindi Speech Corpus (IITKGP-SEHSC) is used for conducting the emotion recognition studies. The emotions considered in this study are anger, disgust, fear, happy, neutral and sad. Prosodic and spectral features extracted from speech are used for discriminating the dialects and emotions. Spectral features are represented by Mel frequency cepstral coefficients (MFCC) and prosodic features are represented by durations of syllables, pitch and energy contours. Auto-associative neural network (AANN) models and Support Vector Machines (SVM) are explored for capturing the dialect specific and emotion specific information from the above specified features. AANN models are expected to capture the nonlinear relations specific to dialects or emotions through the distributions of feature vectors. SVMs perform dialect or emotion classification based on discriminative characteristics present among the dialects or emotions. Classification systems are developed separately for dialect classification and emotion classification. Recognition performance of the dialect identification and emotion recognition systems is found to be 81% and 78% respectively. Keywords— Auto-associative neural networks, Emotion recognition, Hindi dialect, Prosodic features, Spectral features, Support vector machines.
Canadian Advanced Nanospace Experiment 2: On-Orbit Experiences with a Three-Kilogram Satellite

The objective of the Canadian Advanced Nanospace eX periment (CanX) program is to develop highly capabl e “nanospacecraft,” or spacecraft under 10 kilograms, in hort timeframes of 2-3 years. CanX missions o ffer low-cost and rapid access to space for scientists, technolog y developers, and operationally responsive missions . The Space Flight Laboratory (SFL) at the University of Toront Institute for Aerospace Studies (UTIAS) has devel op d the Canadian Advanced Nanospace eXperiment 2 (CanX-2) n anosatellite that launched in April 2008. CanX-2, a 3.5-kg, 10 x 10 x 34 cm satellite, features a collection of scientific and engineering payloads that push the envelope of capability for this class of spacecraft. The prima ry mission of CanX-2 is to test and demonstrate sev eral enabling technologies for precise formation flight. These t echnologies include a custom cold-gas propulsion sy stem, a 30 mNms nanosatellite reaction wheel as part of a thre e-axis stabilized momentum-bias attitude control sy stem, and a commercially available GPS receiver. The secondary objective of CanX-2 is to fly a number of universi ty experiments including an atmospheric spectrometer. At the time of writing CanX-2 has been in orbit fo r three weeks and has performed very well during preliminar y commissioning. The mission, the engineering and s cientific payloads, and the preliminary on-orbit commissionin g experiences of CanX-2 are presented in this paper .
Survey on Frequent Pattern Mining

Frequent itemsets play an essential role in many data mining tasks that try to find interesting patterns from databases, such as association rules, correlations, sequences, episodes, classifiers, clusters and many more of which the mining of association rules is one of the most popular problems. The original motivation for searching association rules came from the need to analyze so called supermarket transaction data, that is, to examine customer behavior in terms of the purchased products. Association rules describe how often items are purchased together. For example, an association rule “beer ⇒ chips (80%)” states that four out of five customers that bought beer also bought chips. Such rules can be useful for decisions concerning product pricing, promotions, store layout and many others. Since their introduction in 1993 by Argawal et al. [3], the frequent itemset and association rule mining problems have received a great deal of attention. Within the past decade, hundreds of research papers have been published presenting new algorithms or improvements on existing algorithms to solve these mining problems more efficiently. In this chapter, we explain the basic frequent itemset and association rule mining problems. We describe the main techniques used to solve these problems and give a comprehensive survey of the most influential algorithms that were proposed during the last decade.
A validated prediction model for all forms of acute coronary syndrome: estimating the risk of 6-month postdischarge death in an international registry.

CONTEXT
Accurate estimation of risk for untoward outcomes after patients have been hospitalized for an acute coronary syndrome (ACS) may help clinicians guide the type and intensity of therapy.


OBJECTIVE
To develop a simple decision tool for bedside risk estimation of 6-month mortality in patients surviving admission for an ACS.


DESIGN, SETTING, AND PATIENTS
A multinational registry, involving 94 hospitals in 14 countries, that used data from the Global Registry of Acute Coronary Events (GRACE) to develop and validate a multivariable stepwise regression model for death during 6 months postdischarge. From 17,142 patients presenting with an ACS from April 1, 1999, to March 31, 2002, and discharged alive, 15,007 (87.5%) had complete 6-month follow-up and represented the development cohort for a model that was subsequently tested on a validation cohort of 7638 patients admitted from April 1, 2002, to December 31, 2003.


MAIN OUTCOME MEASURE
All-cause mortality during 6 months postdischarge after admission for an ACS.


RESULTS
The 6-month mortality rates were similar in the development (n = 717; 4.8%) and validation cohorts (n = 331; 4.7%). The risk-prediction tool for all forms of ACS identified 9 variables predictive of 6-month mortality: older age, history of myocardial infarction, history of heart failure, increased pulse rate at presentation, lower systolic blood pressure at presentation, elevated initial serum creatinine level, elevated initial serum cardiac biomarker levels, ST-segment depression on presenting electrocardiogram, and not having a percutaneous coronary intervention performed in hospital. The c statistics for the development and validation cohorts were 0.81 and 0.75, respectively.


CONCLUSIONS
The GRACE 6-month postdischarge prediction model is a simple, robust tool for predicting mortality in patients with ACS. Clinicians may find it simple to use and applicable to clinical practice.
Proactive event processing in action: a case study on the proactive management of transport processes (industry article)

Proactive event processing constitutes the next phase in the evolution of complex event processing. Proactive event processing makes it possible to anticipate potential issues during process execution and thereby enables proactive process management. One industry domain that can expect relevant benefits from applying proactive event processing is transportation. Transportation companies face numerous stochastic issues when managing the shipment of goods. One such issue faced in airfreight is the exact volume, weight, and number of pieces that a shipper wants to have shipped. Because of the high cost of air shipments, discrepancies between what has been booked by a shipper and the actual volume that is delivered impose costs that create problems for all participants in a shipment. One potential approach to addressing this problem is to use real-time monitoring and proactive alerting to assist air freight companies in anticipating actual delivered weights, volumes, and piece counts. In this paper we address the issue of cargo shipments by leveraging real-time monitoring data collected from an industry-standard monitoring system of a large freight forwarding company. Our evidence indicates that by using a novel proactive event-driven software engine, prediction about the weight of shipments can be developed and used in a proactive manner to assist air freight planners in making better estimates and plans for the shipment of goods. We demonstrate that through the use of this proactive approach, predictions concerning over and under-weight loads can be made days in advance of a shipment, thus enabling the air freight planner to optimize their load plans and thus maximize the revenue that they generate from shipments.
Side-Channel Attacks on Everyday Applications : Distinguishing Inputs with F LUSH + R ELOAD

Side channel attacks are typically used to break implementations of cryptography. Recently, side-channel attacks are being discovered in more general settings that violate user privacy. We build on this work by showing that the FLUSH+RELOAD L3 cache side channel from Yuval Yarom and Katrina Falkner [33] can be used to distinguish between inputs to non-cryptographic programs on multi-user systems. We describe how input-distinguishing attacks can be discovered automatically (with human assistance) and we present three concrete attacks. Our first attack is against the Links command-line web browser. We show that an attacker can determine which of the top 100 Wikipedia pages the user visited (correct 94% of the time). Our second attack is against the Poppler PDF rendering library. We show that an attacker can determine which of a set of 127 PDFs were rendered by Poppler (correct 98% of the time). Finally, we show how an attacker can determine whether the TrueCrypt volume a user just mounted contained a hidden volume or not (correct above 80% of the time, but the attack only works on one of our two test systems).
Daily acyclovir to decrease herpes simplex virus type 2 (HSV-2) transmission from HSV-2/HIV-1 coinfected persons: a randomized controlled trial.

BACKGROUND
Daily suppressive therapy with valacyclovir reduces risk of sexual transmission of herpes simplex virus type 2 (HSV-2) in HSV-2-serodiscordant heterosexual couples by 48%. Whether suppressive therapy reduces HSV-2 transmission from persons coinfected with HSV-2 and human immunodeficiency virus type 1 (HIV-1) is unknown.


METHODS
Within a randomized trial of daily acyclovir 400 mg twice daily in African HIV-1 serodiscordant couples, in which the HIV-1-infected partner was HSV-2 seropositive, we identified partnerships in which HIV-1-susceptible partners were HSV-2 seronegative to estimate the effect of acyclovir on risk of HSV-2 transmission.


RESULTS
We randomly assigned 911 HSV-2/HIV-1-serodiscordant couples to daily receipt of acyclovir or placebo. We observed 68 HSV-2 seroconversions, 40 and 28 in acyclovir and placebo groups, respectively (HSV-2 incidence, 5.1 cases per 100 person-years; hazard ratio [HR], 1.35 [95% confidence interval, .83-2.20]; P = .22). Among HSV-2-susceptible women, vaginal drying practices (adjusted HR, 44.35; P = .004) and unprotected sex (adjusted HR, 9.91; P = .002) were significant risk factors for HSV-2 acquisition; having more children was protective (adjusted HR, 0.47 per additional child; P = .012). Among HSV-2-susceptible men, only age ≤30 years was associated with increased risk of HSV-2 acquisition (P = .016).


CONCLUSIONS
Treatment of African HSV-2/HIV-1-infected persons with daily suppressive acyclovir did not decrease risk of HSV-2 transmission to susceptible partners. More-effective prevention strategies to reduce HSV-2 transmission from HIV-1-infected persons are needed.