Miracle-dz/UniFAR-FTUs huggingface dataset:
A literature-based economic evaluation of healthcare preventable adverse events in Europe

Purpose To establish from the literature, cost of preventable adverse events (PAEs) to member states of the Joint Action European Union Network for Patient Safety and Quality of Care. Data sources We searched MEDLINE, EMBASE and CINAHL for studies in Europe estimating cost of adverse events (AEs) and PAEs (2000-March 2016). Using data from the literature, we estimated PAE costs based on national 2013 total health expenditure (THE) data reported by World Health Organization and converted to 2015 Euros. Study selection/Data extraction Information on type, frequency and incremental cost per episode or estimated cost of AEs was extracted. Total annual disability-adjusted life years (DALYs) resulting from PAEs in 30 EU nations were calculated using an estimate from a published study and adjusted for the percentage of AEs considered preventable. Result of data synthesis Published estimates of costs of AEs and PAEs vary based on the care setting, methodology, population and year conducted. Only one study was from primary care, the majority were conducted in acute care. Nine studies estimated percentage of THE caused by AEs, 13 studies calculated attributable length of stay. We estimated the annual cost of PAEs to the 30 nations in 2015 to be in the range of 17-38 billion Euros, total DALYs lost from AEs as 3.5 million, of which 1.5 million DALYs were likely due to PAEs. Conclusion The economic burden of AEs and PAEs is substantial. However, whether patient safety interventions will be 'cost saving' depends on the effectiveness and costs of the interventions.
A Low Noise Amplifier for Neural Spike Recording Interfaces

This paper presents a Low Noise Amplifier (LNA) for neural spike recording applications. The proposed topology, based on a capacitive feedback network using a two-stage OTA, efficiently solves the triple trade-off between power, area and noise. Additionally, this work introduces a novel transistor-level synthesis methodology for LNAs tailored for the minimization of their noise efficiency factor under area and noise constraints. The proposed LNA has been implemented in a 130 nm CMOS technology and occupies 0.053 mm-sq. Experimental results show that the LNA offers a noise efficiency factor of 2.16 and an input referred noise of 3.8 μVrms for 1.2 V power supply. It provides a gain of 46 dB over a nominal bandwidth of 192 Hz–7.4 kHz and consumes 1.92 μW. The performance of the proposed LNA has been validated through in vivo experiments with animal models.
Protein , malnutrition and wasting disorders The impact of malnutrition on quality of life in patients with systemic sclerosis

Background/objectives Our objective was to investigate the prevalence of malnutrition in patients with systemic sclerosis (SSc) and its impact on their quality of life (QoL). Subjects/methods One hundred and twenty-nine patients with SSc underwent clinical evaluation and were screened with the Malnutrition Universal Screening Tool (MUST). Malnutrition was defined as MUST score ≥2.To investigate QoL, all patients completed the Short Form 36 Questionnaire and the Scleroderma Health Assessment Questionnaire. The data were analyzed with IBM SPSS Statistics by using χ/Fisher's test, Mann–Whitney U test, correlation, and linear regression analysis. Results One hundred and twenty-nine patients were included in this study (mean age was 59.1 ± 13.8 years, 90.7% women). The prevalence of malnutrition was 10.9%. Age and disease duration were not significantly different between malnourished and well-nourished patients. All QoL scores (except bodily pain and self-reported health) were significantly impaired in malnourished patients. Furthermore, the Scleroderma Health Assessment Score score which assesses disease-specific QoL was significantly higher in the malnourished patients (1.6 ± 0.73 compared to 0.91 ± 0.61 in well-nourished patients; p= 0.001), reflecting a lower QoL due to disease-specific impairments. Conclusions Severe malnutrition in SSc patients is associated with reduced QoL. Standardized nutritional screening should routinely be conducted to identify the risk of malnutrition in order to enable an intervention with multimodal treatment and avoid the serious consequences associated with severe malnutrition.
Naturally Acquired Human Antibodies Against Reticulocyte-Binding Domains of Plasmodium vivax Proteins, PvRBP2c and PvRBP1a, Exhibit Binding-Inhibitory Activity

Background Crucial gaps in our understanding of Plasmodium vivax reticulocyte invasion and protective immunity have hampered development of vivax vaccines. P. vivax exclusively invades reticulocytes that is mediated by the P. vivax reticulocyte-binding proteins (PvRBPs) specifically PvRBP2c and PvRBP1a. Vivax infections in Duffy-null individuals have suggested the evolution of alternate invasion pathways that may be mediated by the PvRBPs. Thus, PvRBPs appear as potential targets for efficacious P. vivax neutralization. However, there are limited data validating their vaccine efficacy. In the absence of vivax invasion assays, binding-inhibitory activity of antibodies has been reported to be associated with protection and a measure of vaccine potential. Methods -based analysis was performed of the PvRBP reticulocyte-binding properties and binding-inhibitory activity of specific anti-PvRBP2c/PvRBP1a human antibodies. Results PvRBP2c and PvRBP1a displayed a distinct reticulocyte-binding specificity, and their specific reticulocyte-binding domains were mapped within their N-terminal regions. Importantly, naturally acquired antibodies against the reticulocyte-binding domains efficaciously blocked reticulocyte binding of native PvRBPs, suggesting that the human immune system produced functional binding-inhibitory antibodies through exposure to vivax malaria. Conclusions Reticulocyte-binding domains of PvRBP2c/PvRBP1a are targets of naturally acquired binding-inhibitory antibodies, substantiating their promise as candidate antigens against which vaccine-inducible immunity could potentially be boosted through natural infections.
OF COMPRESSIVE SENSING OVER WIRELESS FADING CHANNELS

Wireless fading channels exist mixed noise, the most common noises are gaussian noise and impulse noise, to ensure the quality of the received signal, removing the noise in the channel is very important and necessary. WSDN (wavelet soft-threshold de-noising) can suppress low-intensity gaussian noise well; unfortunately, the denoising effect in removing impulse noise using WSDN is not obvious, especially when noise intensity is relatively high. BPDN (Basis Pursuit Denoising) which is a reconstruction algorithm of compressive sensing can control high-intensity gaussian noise in the channels well preceding WSDN, but also the effect of BPDN denoising the common impulse noise is not obvious, to denoise impulse noise, we adopt IBPDN (Improved Basis Pursuit Denoising) that changes L2 form to noise to L1 form, which was proposed in 2006 by Guosheng Bing. The experimental data show that IBPDN has good anti-noise ability to both gaussian noise and impulse noise; furthermore, more satisfactory results are obtained using IBPDN to mixed noise than those with BPDN.
Associations of Brain Structure With Adiposity and Changes in Adiposity in a Middle-Aged and Older Biracial Population

Background Studies of adiposity and brain pathology in African Americans (AA) are sparse despite higher rates of obesity, dementia, and dementia-associated brain pathology in AA. This study examined relations of adiposity to white matter hyperintensities (WMH) and total brain volume (TBV) in AA and non-Hispanic whites (NHW). Methods Waist circumference (WC) and body mass index (BMI) were measured in the Genetic Epidemiology Network of Arteriopathy study at Visits 1 (mean age 57 [±11]) and 2 (mean age 61 [±10], mean 5.2 years later). Brain MRIs were obtained shortly after Visit 2 in 1,702 participants (64% women, 48% AA). Multilevel linear regression using generalized estimating equation estimated associations of adiposity (cross-sectional) or adiposity changes with WMH (accounting for intracranial size) or TBV adjusting for demographics, cardiovascular risk factors, and incorporating adiposity-by-race interactions. Adiposity-by-age interactions were examined. Results Concurrent TBV was inversely associated with BMI (β = -2.76 [95% confidence interval (CI): -4.99, -0.53]) and WC (β = -2.19 [CI: -4.04, -0.34]). Concurrent WMH were negatively associated with BMI (β = -0.04 [CI: -0.06, -0.01]) and, among NHW, with WC (β = -0.04 [CI: -0.06, -0.02]) but not with changes in BMI or WC. BMI increases were associated with lower TBV (β = -16.20, [CI: -30.34, -2.06]) in AA but not in NHW (β = -2.76 [CI: -14.02, 8.51]), although race-by-adiposity interactions were not supported. WC increases were not associated with MRI outcomes. Conclusion Greater measures of obesity and increases in measures of obesity, which are common in mid-life, could be detrimental to brain health, particularly in AA.
Semantic summary automatic generation in news event

How to generate summary with more novel and rich semantics is a challenging issue in the area of multi‐document automatic summary. In this paper, a core semantics extraction model (CSEM) is proposed to improve the novel and rich semantics of multi‐document summary. Firstly, for improving the rich semantics, semantic units, which are a group of association relations of keywords, are used to express texts' semantics. Secondly, for improving the novel semantics, an attenuation function is introduced to adjust the importance of semantic units according to the appearing times that semantic units in the candidate of summary sentences. Thirdly, in order to maximize the novel and rich semantics of summary, the generating process of summary is converted into the optimization process on how to find a set of sentences with a higher importance. Finally, CSEM extracts the least number of sentences to cover the most core semantics in corpus as summary. Experimental results on the benchmark DUC 2004 show that our model outperforms the state‐of‐art approaches (eg, OCCAMS_V, JS‐Gen‐2) under official metric. Especially, the recall of our model in ROUGE‐1 is 40.684%, which is better than other approaches (eg, OCCAMS_V 38.497% and JS‐Gen‐2 36.739%).
Validation of Photoplethysmography-Based Sleep Staging Compared With Polysomnography in Healthy Middle-Aged Adults

Study Objectives To compare the accuracy of automatic sleep staging based on heart rate variability measured from photoplethysmography (PPG) combined with body movements measured with an accelerometer, with polysomnography (PSG) and actigraphy. Methods Using wrist-worn PPG to analyze heart rate variability and an accelerometer to measure body movements, sleep stages and sleep statistics were automatically computed from overnight recordings. Sleep-wake, 4-class (wake/N1 + N2/N3/REM) and 3-class (wake/NREM/REM) classifiers were trained on 135 simultaneously recorded PSG and PPG recordings of 101 healthy participants and validated on 80 recordings of 51 healthy middle-aged adults. Epoch-by-epoch agreement and sleep statistics were compared with actigraphy for a subset of the validation set. Results The sleep-wake classifier obtained an epoch-by-epoch Cohen's κ between PPG and PSG sleep stages of 0.55 ± 0.14, sensitivity to wake of 58.2 ± 17.3%, and accuracy of 91.5 ± 5.1%. κ and sensitivity were significantly higher than with actigraphy (0.40 ± 0.15 and 45.5 ± 19.3%, respectively). The 3-class classifier achieved a κ of 0.46 ± 0.15 and accuracy of 72.9 ± 8.3%, and the 4-class classifier, a κ of 0.42 ± 0.12 and accuracy of 59.3 ± 8.5%. Conclusions The moderate epoch-by-epoch agreement and, in particular, the good agreement in terms of sleep statistics suggest that this technique is promising for long-term sleep monitoring, although more evidence is needed to understand whether it can complement PSG in clinical practice. It also offers an improvement in sleep/wake detection over actigraphy for healthy individuals, although this must be confirmed on a larger, clinical population.
Diarrhea, Stimulation and Growth Predict Neurodevelopment in Young North Indian Children

Background and Objective Infants and young children in low to middle-income countries are at risk for adverse neurodevelopment due to multiple risk factors. In this study, we sought to identify stimulation and learning opportunities, growth, and burden of respiratory infections and diarrhea as predictors for neurodevelopment. Methods We visited 422 North Indian children 6 to 30 months old weekly for six months. Childhood illnesses were assessed biweekly. At end study, we assessed neurodevelopment using the Ages and Stages Questionnaire 3rd ed. (ASQ-3) and gathered information on stimulation and learning opportunities. We identified predictors for ASQ-3 scores in multiple linear and logistic regression models. Results We were able to explain 30.5% of the variation in the total ASQ-3 score by the identified predictors. When adjusting for child characteristics and annual family income, stimulation and learning opportunities explained most of the variation by 25.1%. Height for age (standardized beta: 0.12, p<.05) and weight for height z-scores (std. beta: 0.09, p<.05) were positively associated with the total ASQ-3 score, while number of days with diarrhea was negatively associated with these scores (std. beta: -0.13, p<0.01). Conclusion Our results support the importance of early child stimulation and general nutrition for child development. Our study also suggests that diarrhea is an additional risk factor for adverse neurodevelopment in vulnerable children.
Comparison of conservation metrics in a case study of lemurs

Conservation planning is important to protect species from going extinct now that natural habitats are decreasing owing to human activity and climate change. However, there is considerable controversy in choosing appropriate metrics to weigh the value of species and geographic regions. For example, the added value of phylogenetic conservation‐selection criteria remains disputed because high correlations between them and the nonphylogenetic criteria of species richness have been reported. We evaluated the commonly used conservation metrics species richness, endemism, phylogenetic diversity (PD), and phylogenetic endemism (PE) in a case study on lemurs of Madagascar. This enabled us to identify the conservation target of each metric and consider how they may be used in future conservation planning. We also devised a novel metric that uses a phylogeny scaled according to the rate of phenotypic evolution as a proxy for a species’ ability to adapt to change. High rates of evolution may indicate generalization or specialization. Both specialization and low rates of evolution may result in an inability to adapt to changing environments. We examined conservation priorities by using the inverse of the rate of body mass evolution to account for species with low rates of evolution. In line with previous work, we found high correlations among species richness and PD (r = 0.96), and endemism and PE (r = 0.82) in Malagasy lemurs. Phylogenetic endemism in combination with rates of evolution and their inverse prioritized grid cells containing highly endemic and specialized lemurs at risk of extinction, such as Avahi occidentalis and Lepilemur edwardsi, 2 endangered lemurs with high rates of phenotypic evolution and low‐quality diets, and Hapalemur aureus, a critically endangered species with a low rate of body mass evolution and a diet consisting of very high doses of cyanide.
Robust Bearing Angle Error Estimation for Mobile Robots With a Gimballed Ultrasonic Seeker

This paper deals with the bearing angle error (BAE) estimation problem associated with a one-axis gimballed ultrasonic seeker, which can be used as a low-cost sensor for mobile robot applications. Under the assumptions that the target has an ultrasonic transmitter and the gimbal control loops work properly, the moving target tracking reduces to an estimation problem of a piecewise constant BAE using real sinusoids measured by a receiver array mounted on the gimbal. To effectively cope with the real-time implementation issue, our estimation problem is formulated using linear robust state estimation and is resolved using the constrained robust weighted least squares method. Through experimental results obtained from a hardware-in-the-loop simulation (HILS) approach, it is demonstrated that the proposed scheme provides more reliable and consistent estimation performance than existing approaches.
Towards Automated Detection of Peer-to-Peer Botnets: On the Limits of Local Approaches

State-of-the-art approaches for the detection of peer-to-peer (P2P) botnets are on the one hand mostly local and on the other hand tailored to specific botnets involving a great amount of human time, effort, skill and creativity. Enhancing or even replacing this labor-intensive process with automated and, if possible, local network monitoring tools is clearly extremely desirable. To investigate the feasibility of automated and local monitoring, we present an experimental analysis of the traffic dispersion graph (TDG)--a key concept in P2P network detection--of P2P overlay maintenance and search traffic as seen at a single AS. We focus on a feasible scenario where an imaginary P2P botnet uses some basic P2P techniques to hide its overlay network. The simulations are carried out on an AS-level model of the Internet. We show that the visibility of P2P botnet traffic at any single AS (let alone a single router) can be very limited. While we strongly believe that the automated detection and mapping of complete P2P botnets is possible, our results imply that it cannot be achieved by a local approach: it will inevitably require very close cooperation among many different administrative domains and it will require state-of-the-art P2P algorithms as well.
Real-Time Viscosity Measurement for Condition-Based Monitoring Using Solid-State Viscosity Sensor

For optimal condition-based monitoring the measurement of viscosity is essential. Consideration of the manufacturing sector renders laboratory approaches as unsuitable, due to the lag-time between sampling and results reporting. Therefore, the continuous measurement approach has been considered the most ideal, yielding instantaneous results reporting and quality control feedback. The historical design of viscometers has resulted in a complex, highly mechanical device associated with a high cost and selling price. Highly sensitive solid-state viscosity sensors in an online configuration will provide the benefits of fast results reporting, simple fluidics management, and advantageous cost/benefit relation. The sensor measures viscous damping of a surface shear wave on a quartz crystal to obtain the viscosity-density product of the sample. The sensor offers solid-state reliability, real-time response time, and is immune to flow conditions and vibration while designed for the challenging process control environments and for OEM applications.
Efficient Time Domain Deterministic-Stochastic Model of Spectrum Usage

For achieving an efficient spectrum sharing in a context of dynamic spectrum access, understanding the spectrum usage by licensed users [primary users (PUs)], is important for secondary users (SUs). Duty cycle (DC) has been used to express the deterministic and stochastic aspects of spectrum usage. Specifically, a deterministic model for the mean of the duty cycle (M-DC) has been proposed in a previous work. The deterministic aspect of M-DC is affected by social behavior, and common habits of users, which can be confirmed in cellular systems. On the other hand, the observed DC (O-DC) during short time duration has randomness and a stochastic model is more suitable, e.g. distribution of O-DC. In this paper, we extend the conventional approach, in which only either the deterministic or stochastic aspect is considered, to a combined deterministic-stochastic (DS) model, which represents both the deterministic and stochastic aspects at once. For the distribution of the O-DC, the beta distribution has been used as stochastic model, but we employ a mixture of beta distributions. The mixture-beta distribution can achieve higher accuracy but requires more capacity for data storage in spectrum usage measurements since it has a higher number of parameters than the beta distribution. For this issue, we employ regression analysis in DS-model since this approach can reduce the number of parameters while retaining the accuracy. We show the validity of DS-model based on exhaustive spectrum measurements in IEEE 802.11-based wireless local area networks and long-term evolution uplink.
EUCANEXT: an integrated database for the exploration of genomic and transcriptomic data from Eucalyptus species

Abstract Tree species of the genus Eucalyptus are the most valuable and widely planted hardwoods in the world. Given the economic importance of Eucalyptus trees, much effort has been made towards the generation of specimens with superior forestry properties that can deliver high-quality feedstocks, customized to the industrýs needs for both cellulosic (paper) and lignocellulosic biomass production. In line with these efforts, large sets of molecular data have been generated by several scientific groups, providing invaluable information that can be applied in the development of improved specimens. In order to fully explore the potential of available datasets, the development of a public database that provides integrated access to genomic and transcriptomic data from Eucalyptus is needed. EUCANEXT is a database that analyses and integrates publicly available Eucalyptus molecular data, such as the E. grandis genome assembly and predicted genes, ESTs from several species and digital gene expression from 26 RNA-Seq libraries. The database has been implemented in a Fedora Linux machine running MySQL and Apache, while Perl CGI was used for the web interfaces. EUCANEXT provides a user-friendly web interface for easy access and analysis of publicly available molecular data from Eucalyptus species. This integrated database allows for complex searches by gene name, keyword or sequence similarity and is publicly accessible at http://www.lge. ibi.unicamp. br/eucalyptusdb. Through EUCANEXT, users can perform complex analysis to identify genes related traits of interest using RNA-Seq libraries and tools for differential expression analysis. Moreover, all the bioinformatics pipeline here described, including the database schema and PERL scripts, are readily available and can be applied to any genomic and transcriptomic project, regardless of the organism. Database URL: http://www.lge. ibi.unicamp. br/eucalyptusdb
Contrast measurement for MRI images using histogram of second-order derivatives

The proposed method is a contrast measurement technique which makes use of the second-order derivatives of the pixels in MRI images. The technique utilizes the changes in the histogram of second-order derivatives for the image, specifically the region under a Laplacian curve which approximates the distribution of the pixel frequencies in the histogram. As gain is introduced, the region of the histogram under the curve changes. The standard deviation of the frequency differences between the histogram and the curve in the region is used as a measurement score. The objective of this method is to provide a way to include small details, such as small blood vessels, in the contrast measurement, compared to local average contrast and RMS contrast measurements which do not. The outcome is a scoring method which not only provides a measurement of contrast, but also indicates the loss of small details in MRI images.