Miracle-dz/UniFAR-FTUs huggingface dataset:
A model for music complexity applied to music preprocessing for cochlear implants

Music appreciation remains challenging for cochlear implant users. In previous studies a strong negative correlation was found with cochlear implant subjects between music appreciation and music complexity. In this paper, music features that contribute to music complexity are investigated and related to a music preprocessing scheme for cochlear implants, in which a complexity reduction is achieved in an attempt to increase music appreciation. First, a complexity rating experiment is performed with pop/rock music excerpts and a linear regression model is developed to describe this (subjective) music complexity based on different music features. Subsequently, this model is used to validate the complexity reduction in the music preprocessing scheme and to provide an indication for the preferred setting for the balance between vocals/bass/drums and the other instruments for cochlear implant subjects.
Nutrition in the critically ill patient

Purpose of review To summarize recent relevant studies regarding nutrition during critical illness and provide recommendations for clinical practice. Recent findings Recently acquired knowledge regarding nutritional status and risk assessment, body composition, gastric residual volume, prokinetics, tube positioning, enteral vs parenteral nutrition, nutritional dose and timing of initiation, pharmaconutrition, dysbiosis and probiotics are discussed. Summary Body composition especially lean body mass is associated with clinical outcomes. The modified NUTrition Risk in the Critically ill score was validated for nutritional risk assessment and identifies patients that benefit from higher nutritional intake; however, caloric restriction decreases mortality in refeeding syndrome. Gastric residual volume monitoring is debated, as abandoning its application doesn’t worsen outcome. There is no consensus regarding benefits of gastric vs postpyloric tube placement. Current prokinetics temporarily reduce feeding intolerance, new prokinetics are developed. Enteral remains preferable over parenteral nutrition, although no inferiority of parenteral nutrition is reported in recent studies. Studies imply no harm of hypocaloric feeding when protein requirements are met. Optimal protein provision may be more important than caloric adequacy. Pharmaconutrition confers no superior outcomes and may even confer harm. Dysbiosis is frequently encountered and associated with worse outcomes. Probiotics reduce infectious complications, but not mortality, and may contribute to earlier recovery of gut function.
Performance comparison of different STBC codes in the presence of IQ imbalances in mobile communications

In receivers, IQ imbalances have significant effects on the performance of data transmission. Comparison of the performance of different types of orthogonal space-time block codes (OSTBC) in the presence of IQ imbalances show that different codes donpsilat have a same behavior. Although most codes have an acceptable performance in low imbalances, they canpsilat work properly in the presence of intensive non-idealities. Despite this general similarity, there are some differences in the behavior of the codes against non-idealities. Such differences make them suitable for different situations.
Nonlocal vibration of a piezoelectric polymeric nanoplate carrying nanoparticle via Mindlin plate theory

This paper is concerned with the vibration characteristics of an embedded nanoplate-based nanoelectromechanical sensor made of polyvinylidene fluoride (PVDF) carrying a nanoparticle with different masses at any position. The nanoplate is surrounded by elastic medium which is simulated as Pasternak foundation. The PVDF nanoplate is subjected to an applied voltage in the thickness direction. In order to satisfy the Maxwell equation, electric potential distribution is assumed as a combination of a half-cosine and linear variation. Adopting the nonlocal Mindlin plate theory, the governing equations are derived based on the energy method and Hamilton’s principle which are then solved by Galerkin method to obtain the natural frequency of the nanoplate. A detailed parametric study is conducted to elucidate the influences of the nonlocal parameter, external electric voltage, position and mass of nanoparticle, temperature changes and dimension of nanoplate and elastic medium. Results indicate that the frequency is increased as the nanoparticle comes closer to the center of the nanoplate; also increasing mass of the nanoparticle decreases the frequency of the system. This study might be useful for the design of PVDF nanoplate-based resonator as nanoelectromechanical sensor.
Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure

Fuzzy c-means clustering (FCM) with spatial constraints (FCM/spl I.bar/S) is an effective algorithm suitable for image segmentation. Its effectiveness contributes not only to the introduction of fuzziness for belongingness of each pixel but also to exploitation of spatial contextual information. Although the contextual information can raise its insensitivity to noise to some extent, FCM/spl I.bar/S still lacks enough robustness to noise and outliers and is not suitable for revealing non-Euclidean structure of the input data due to the use of Euclidean distance (L/sub 2/ norm). In this paper, to overcome the above problems, we first propose two variants, FCM/spl I.bar/S/sub 1/ and FCM/spl I.bar/S/sub 2/, of FCM/spl I.bar/S to aim at simplifying its computation and then extend them, including FCM/spl I.bar/S, to corresponding robust kernelized versions KFCM/spl I.bar/S, KFCM/spl I.bar/S/sub 1/ and KFCM/spl I.bar/S/sub 2/ by the kernel methods. Our main motives of using the kernel methods consist in: inducing a class of robust non-Euclidean distance measures for the original data space to derive new objective functions and thus clustering the non-Euclidean structures in data; enhancing robustness of the original clustering algorithms to noise and outliers, and still retaining computational simplicity. The experiments on the artificial and real-world datasets show that our proposed algorithms, especially with spatial constraints, are more effective.
Unbalanced Expander Based Compressive Data Gathering in Clustered Wireless Sensor Networks

Conventional compressive sensing-based data gathering (CS-DG) algorithms require a large number of sensors for each compressive sensing measurement, thereby resulting in high energy consumption in clustered wireless sensor networks (WSNs). To solve this problem, we propose a novel energy-efficient CS-DG algorithm, which exploits the better reconstruction accuracy of the adjacency matrix of an unbalanced expander graph. In the proposed CS-DG algorithm, each measurement is the sum of a few sensory data, which are jointly determined by random sampling and random walks. Through theoretical analysis, we prove that the constructed <inline-formula> <tex-math notation="LaTeX">${M\times N}$ </tex-math></inline-formula> sparse binary sensing matrix is the adjacency matrix of a <inline-formula> <tex-math notation="LaTeX">$(k,\varepsilon )$ </tex-math></inline-formula> unbalanced expander graph when <inline-formula> <tex-math notation="LaTeX">${M=O\left ({k\log {N / k}}\right )}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">${t = O\left ({ {{N_{c} / {\left ({ {kq} }\right )}}} }\right )}$ </tex-math></inline-formula> for WSNs with <inline-formula> <tex-math notation="LaTeX">$N_{c}$ </tex-math></inline-formula> clusters, where <inline-formula> <tex-math notation="LaTeX">${0\leq q\leq 1}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">${N_{c}>k}$ </tex-math></inline-formula>. Simulation results show our proposed CS-DG has better performance than existing algorithms in terms of reconstruction accuracy and energy consumption. When hybrid energy-efficient distributed clustering algorithm is used, to achieve the same reconstruction accuracy, our proposed CS-DG can save energy by at least 27.8%.
Characterization of delayed liquid gastric emptying in children by the 13C-acetate breath test

The 13C-acetate breath test represents a potential alternative to conventional scintigraphy to measure liquid gastric emptying (GE). The purpose of this study was to compare the 13C-acetate breath test to gastric scintigraphy in children with functional dyspepsia. Simultaneous assessment of GE was performed in 28 children (9–17 years of age) using a liquid test meal that was double labeled with 13C-acetate and 99 mTechnetium. 13CO2 versus time profiles were fit using traditional pharmacokinetic analyses. For each subject, GE half-life determined by scintigraphy was plotted against parameters determined from the 13C-acetate breath test. Linear regression was used to explore the associations between the tests. Complete 13CO2 versus time profiles were available for 25 subjects. There was no association between the scintigraphy GE T½ and the13CO2 half-exhalation time. However, significant associations were observed between the gastric half-emptying time as determined by scintigraphy and two of the breath test parameters: the enrichment of 13CO2 present in breath samples at 60 min (DOB60) (r = −0.52, p = 0.01) and the area under the curve from 0 to 60 min (AUC0-60 min) (r = −0.54; p < 0.01). The 13C-acetate breath test has the potential to serve as a rapid, technically simple and inexpensive means to assess liquid GE in children with functional dyspepsia and possibly serve as a pharmacodynamic surrogate in studies of prokinetic drugs in children.
Prevalence of Cardiovascular Disease Risk Factor Clustering Among the Adult Population of China: Results From the International Collaborative Study of Cardiovascular Disease in Asia (InterAsia)

Background—The prevalence of cardiovascular disease (CVD) risk factors has been increasing in China. Methods and Results—We examined the prevalence of CVD risk factor clustering among Chinese adults aged 35 to 74 years with data from the International Collaborative Study of Cardiovascular Disease in Asia (InterAsia), a cross-sectional survey of a nationally representative sample (n=14 690) conducted during 2000 to 2001 and compared these data with those of US adults from the National Health and Nutrition Examination Survey of 1999 to 2000. Overall, 80.5%, 45.9%, and 17.2% of Chinese adults had ≥1, ≥2, and ≥3 modifiable CVD risk factors (dyslipidemia, hypertension, diabetes, cigarette smoking, and overweight), respectively. By comparison, 93.1%, 73.0%, and 35.9% of US adults had ≥1, ≥2, and ≥3 of these risk factors, respectively. In a multivariate model including age, sex, and area of residence, the odds ratio (95% confidence interval [CI]) of having ≥1, ≥2, and ≥3 CVD risk factors versus none of the studied risk factors was 2.61 (95% CI, 2.09 to 3.27), 3.55 (95% CI, 2.77 to 4.54), and 4.97 (95% CI, 3.67 to 6.74), respectively, for Chinese adults 65 to 74 years old versus 35 to 44 years old; 3.65 (95% CI, 3.21 to 4.15), 4.67 (95% CI, 4.06 to 5.38), and 5.60 (95% CI, 4.70 to 6.67), respectively, for men compared with women; 1.18 (95% CI, 1.07 to 1.30), 1.34 (95% CI, 1.21 to 1.50), and 1.84 (95% CI, 1.60 to 2.12), respectively, for urban compared with rural residents; and 1.98 (95% CI, 1.76 to 2.22), 2.75 (95% CI, 2.42 to 3.13), and 4.36 (95% CI, 3.68 to 5.18), respectively, for residents of northern compared with southern China. Conclusions—Clustering of CVD risk factors is common in China. Prevention, detection, and treatment of CVD risk factor clustering should be an important component of a national strategy to reduce the increasing burden of CVD in China.
L-GRAAL: Lagrangian graphlet-based network aligner

Motivation: Discovering and understanding patterns in networks of protein–protein interactions (PPIs) is a central problem in systems biology. Alignments between these networks aid functional understanding as they uncover important information, such as evolutionary conserved pathways, protein complexes and functional orthologs. A few methods have been proposed for global PPI network alignments, but because of NP-completeness of underlying sub-graph isomorphism problem, producing topologically and biologically accurate alignments remains a challenge. Results: We introduce a novel global network alignment tool, Lagrangian GRAphlet-based ALigner (L-GRAAL), which directly optimizes both the protein and the interaction functional conservations, using a novel alignment search heuristic based on integer programming and Lagrangian relaxation. We compare L-GRAAL with the state-of-the-art network aligners on the largest available PPI networks from BioGRID and observe that L-GRAAL uncovers the largest common sub-graphs between the networks, as measured by edge-correctness and symmetric sub-structures scores, which allow transferring more functional information across networks. We assess the biological quality of the protein mappings using the semantic similarity of their Gene Ontology annotations and observe that L-GRAAL best uncovers functionally conserved proteins. Furthermore, we introduce for the first time a measure of the semantic similarity of the mapped interactions and show that L-GRAAL also uncovers best functionally conserved interactions. In addition, we illustrate on the PPI networks of baker's yeast and human the ability of L-GRAAL to predict new PPIs. Finally, L-GRAAL's results are the first to show that topological information is more important than sequence information for uncovering functionally conserved interactions. Availability and implementation: L-GRAAL is coded in C++. Software is available at: http://bio-nets.doc. ic.ac. uk/L-GRAAL/. Contact: n.malod-dognin@imperial.ac. uk Supplementary information: Supplementary data are available at Bioinformatics online.
Statistical methods for the analysis of high-throughput metabolomics data

Metabolomics is a relatively new high-throughput technology that aims at measuring all endogenous metabolites within a biological sample in an unbiased fashion. The resulting metabolic profiles may be regarded as functional signatures of the physiological state, and have been shown to comprise effects of genetic regulation as well as environmental factors. This potential to connect genotypic to phenotypic information promises new insights and biomarkers for different research fields, including biomedical and pharmaceutical research. In the statistical analysis of metabolomics data, many techniques from other omics fields can be reused. However recently, a number of tools specific for metabolomics data have been developed as well. The focus of this mini review will be on recent advancements in the analysis of metabolomics data especially by utilizing Gaussian graphical models and independent component analysis.
Assessment of Still and Moving Images in the Diagnosis of Gastric Lesions Using Magnifying Narrow-Band Imaging in a Prospective Multicenter Trial

Objectives Magnifying narrow-band imaging (M-NBI) is more accurate than white-light imaging for diagnosing small gastric cancers. However, it is uncertain whether moving M-NBI images have additional effects in the diagnosis of gastric cancers compared with still images. Design A prospective multicenter cohort study. Methods To identify the additional benefits of moving M-NBI images by comparing the diagnostic accuracy of still images only with that of both still and moving images. Still and moving M-NBI images of 40 gastric lesions were obtained by an expert endoscopist prior to this prospective multicenter cohort study. Thirty-four endoscopists from ten different Japanese institutions participated in the prospective multicenter cohort study. Each study participant was first tested using only still M-NBI images (still image test), then tested 1 month later using both still and moving M-NBI images (moving image test). The main outcome was a difference in the diagnostic accuracy of cancerous versus noncancerous lesions between the still image test and the moving image test. Results Thirty-four endoscopists were analysed. There were no significant difference of cancerous versus noncancerous lesions between still and moving image tests in the diagnostic accuracy (59.9% versus 61.5%), sensitivity (53.4% versus 55.9%), and specificity (67.0% versus 67.6%). And there were no significant difference in the diagnostic accuracy between still and moving image tests of demarcation line (65.4% versus 65.5%), microvascular pattern (56.7% versus 56.9%), and microsurface pattern (48.1% versus 50.9%). Diagnostic accuracy showed no significant difference between the still and moving image tests in the subgroups of endoscopic findings of the lesions. Conclusions The addition of moving M-NBI images to still M-NBI images does not improve the diagnostic accuracy for gastric lesions. It is reasonable to concentrate on taking sharp still M-NBI images during endoscopic observation and use them for diagnosis. Trial registration Umin.ac. jp UMIN-CTR000008048
Nanotechnology application to local anaesthesia (LA)

Abstract Several advancements have been made on the exact release of local anaesthetics formulation and its efficiency at inducing motor and sensory block for an extended time has been harnessed in clinical practice. The use of sustained release formulations delivers analgesia for a lengthier period of time with one administration, thereby reducing complications that usually arise with administration of conventional analgesia. In addition, controlled release of an anaesthetic drug is said to prevent overdosing, reduced side effects, especially cardiotoxicity, neurotoxicity and tissue lesions. The use of nanotechnology knowledge via liposomal formulation has recorded high successful results in pain control and quick patient recovery.
An Approximate Nonmyopic Computation for Value of Information

Value-of-information analyses provide a straightforward means for selecting the best next observation to make, and for determining whether it is better to gather additional information or to act immediately. Determining the next best test to perform, given a state of uncertainty about the world, requires a consideration of the value of making all possible sequences of observations. In practice, decision analysts and expert-system designers have avoided the intractability of exact computation of the value of information by relying on a myopic approximation. Myopic analyses are based on the assumption that only one additional test will be performed, even when there is an opportunity to make a large number of observations. We present a nonmyopic approximation for value of information that bypasses the traditional myopic analyses by exploiting the statistical properties of large samples.
A virtual machine for sensor networks

Sensor networks are increasingly being deployed for a wide variety of tasks. Today, in these networks, the development, deployment, and maintenance of applications are performed largely ad-hoc. Existing platforms help somewhat but also introduce implicit trade-offs. In one extreme, low-level programming platforms and languages make programming cumbersome and error-prone. In the other extreme, declarative approaches greatly facilitate programming but restrict what can be done. In both cases, additional limitations include lack of support for concurrency, difficulties in changing applications, and insufficient abstractions from low-level details. This paper presents SwissQM, a virtual machine designed to address all these limitations. SwissQM offers a platform-independent programming abstraction that is geared towards data acquisition and in-network data processing.
ParaLite: Supporting Collective Queries in Database System to Parallelize User-Defined Executable

This paper proposes extensions to parallel database systems called collective queries and User-Defined eXecutables (UDX). A collective query is an SQL query whose results are distributed to multiple clients and then processed by them in parallel, using arbitrary external programs (user-defined executables). The intended applications are data intensive work-flows, typically built out of various independently developed executables and scripts. Collective queries facilitate description of such workflows by making data parallel execution of external programs on big data easy and streamlined. It also provides the workflow developers with a familiar and powerful language SQL, for flexible data filtering and stereotypical data processing tasks. We implement this concept in a system "ParaLite", a parallel database system based on a popular lightweight database SQ Lite. It equips with data transfer optimization algorithms that distribute query results to multiple clients, taking both communication cost and compute loads into account. We verified the correctness and performance of Para Lite and the experimental results show that Para Lite has good performance on SQL processing and achieves good scalability for the parallelization of UDX.
Critical illness–related corticosteroid insufficiency after multiple traumas: A multicenter, prospective cohort study

BACKGROUND Given that the observed prevalence and time course of critical illness–related corticosteroid insufficiency (CIRCI) remain inconsistent in trauma patients, the present study was designed to investigate the prevalence, time course, and effect of CIRCI on the outcome of critically ill patients with multiple injuries. METHODS In this multicenter, prospective cohort study, patients with multiple injuries in seven intensive care units in China were enrolled. Adrenocorticotropic hormone (ACTH) stimulation tests were performed by administering intravenously 250 &mgr;g of synthetic ACTH on Days 1, 2, 3, 5, and 7 after traumatic injury. CIRCI was defined as baseline cortisol level of less than 10 &mgr;g/dL or a &Dgr;cortisol (difference baseline and highest cortisol level at 30 or 60 minutes after ACTH stimulation) less than 9 &mgr;g/dL. The incidence and time course of CIRCI and 28-day mortality were recorded. RESULTS CIRCI occurred in 54.3% (38 of 70) of the patients with multiple injuries, including 10 patients with total cortisol level of less than 10 &mgr;g/dL and 28 patients with &Dgr;cortisol of less than 9 &mgr;g/dL. Most (94.7%) diagnosis of CIRCI was made in the first 48 hours after traumatic injury. The CIRCI patients had significantly more severe illness on the day of admission. At each time point, the baseline cortisol level was comparable between the CIRCI and non-CIRCI patients, while &Dgr;cortisol in the CIRCI group was significantly lower compared with the non-CIRCI group. The CIRCI patients with a &Dgr;cortisol of less than 9 &mgr;g/dL had a significantly higher 28-day mortality (39.3%) compared with those with a baseline cortisol level of less than 10 &mgr;g/dL (10.0%) and non-CIRCI patients (6.3%). Only &Dgr;cortisol of less than 9 &mgr;g/dL but not baseline cortisol level of less than 10 &mgr;g/dL seemed to be an independent risk factor for death (odds ratio, 1.19; p = 0.023). CONCLUSION CIRCI is common in critically ill trauma population and usually occurs in the early stages. Only the results of the ACTH stimulation test but not baseline cortisol level was associated with poor prognosis. LEVEL OF EVIDENCE Prognostic study, level II.