Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of the ingestion of a symbiotic yogurt on the bowel habits of women with functional constipation.

BACKGROUND/AIMS functional constipation is a prevalent problem within the western population. There is evidence supporting the fact that the inclusion of pre and probiotics in the diet can favorably modify the intestinal function. The present study evaluates the effect of the consumption of Activia, a yogurt containing 10(8) UFC/g of Bifidobacterium animalis (DN-173 010) and fructoligosaccharide, in women between the ages of 18 and 55 with and without functional constipation (Rome II criteria). METHODS after a stabilization and a basal period, women were randomized to receive 2 units/day of Activia or a lacteous dessert without probiotics (control) for a period of 14 days. Afterwards the groups were intercrossed for another 14 days. RESULTS of the 399 women who started the study, 378 were eligible for study participation. In the group of women with functional constipation (n=266), the consumption of the symbiotic was associated with a higher bowel evacuation rate (6.1+/-2.7 depositions/week with Activia vs. 5.0+/-2.6 dep./week in the control group; P<0.01), an improvement in the quality of the stools according to the Bristol scale (3.6+/-1.0 vs. 3.4+/-1.0; P<0.01), a reduced perception of straining effort (1.9+/-0.8 vs. 2.2+/-0.9; P<0.01) and a reduced perception of pain associated with defecation (0.1+/-0.2 vs. 0.2+/-0.3; P<0.01). In the group of women without constipation (n=112) there were statistically significant variations in equal sense but of smaller magnitude, with the exception of pain which, having a very low value in the basal period, did not experience changes. CONCLUSION the consumption of a symbiotic yogurt by women with functional constipation showed a significant improvement in the parameters related with bowel evacuation. The use of this symbiotic food can result in a useful and safe tool for managing constipation.
SIGNAL MODELING WITH SINUSOIDS PLUS NOISE

Preface This work has been carried out in the Signal Processing Laboratory of Tampere University of Technology, Finland. The working in the Audio Research Group of TUT has been very enjoyable, and I would like to thank Mr. Jari Yli-Hietanen and Mr. Anssi Klapuri for giving me this possibility. I also would like to thank my other colleagues for the refreshing atmosphere. I wish to thank Professor Jaakko Astola for his valuable advice, and Anssi Klapuri for all his guidance and encouragement in the first steps of my scientific career.
Usefulness of 7-day Holter monitoring for heart rate variability nonlinear dynamics evaluation

Although a number of studies have addressed the clinical usefulness of Heart Rate Variability (HRV) as a marker of the autonomic activity, there are few studies about the short-term day-to-day reproducibility of HRV nonlinear indices. A database of 31 7-Day Holters (7DH) from Chronic Heart Failure patients was used to analyze the reliability of nonlinear dynamics and to evaluate the usefulness of 7DH recordings against the 24-hour recordings. On the one hand, scaling exponents α1 and α2 from De-trended Fluctuations Analysis, and Sample Entropy, were compared at two randomly selected days; day and night periods were also analyzed separately. On the other hand, the values obtained for each single day were compared to the ones for the 7DH. Intraclass Correlation Coefficients showed strong correlation for the indices between two random days, specially in the night period, hence suggesting that this could be the more suitable period to perform the calculations in terms of reliability. Significant differences were found for every single day of the week compared to the 7DH for α2. Therefore, 7DH can improve the understanding of long-term fractal correlation properties given by nonlinear indices.
Escrow: A Large-Scale Web Vulnerability Assessment Tool

The reliance on Web applications has increased rapidly over the years. At the same time, the quantity and impact of application security vulnerabilities have grown as well. Amongst these vulnerabilities, SQL Injection has been classified as the most common, dangerous and prevalent web application flaw. In this paper, we propose Escrow, a large-scale SQL Injection detection tool with an exploitation module that is light-weight, fast and platform-independent. Escrow uses a custom search implementation together with a static code analysis module to find potential target web applications. Additionally, it provides a simple to use graphical user interface (GUI) to navigate through a vulnerable remote database. Escrow is implementation-agnostic, i.e. It can perform analysis on any web application regardless of the server-side implementation (PHP, ASP, etc.). Using our tool, we discovered that it is indeed possible to identify and exploit at least 100 databases per 100 minutes, without prior knowledge of their underlying implementation. We observed that for each query sent, we can scan and detect dozens of vulnerable web applications in a short space of time, while providing a means for exploitation. Finally, we provide recommendations for developers to defend against SQL injection and emphasise the need for proactive assessment and defensive coding practices.
What is the role of exemplars in speech comprehension

ionist models . 1 Exemplar models . 2 Hybrid models . 3 Research questions . 7 Outline . 7 Chapter 2: The nature and relevance of exemplars in spoken word recognition 1
A Method for Measuring Semantic Similarity of Documents

With the documents increasing amount available in local or Web repositories, the comparison methods have to analyze large documents sets with different types and terminologies to obtain a response with minimum documents and with as much useful content to the user. For large documents sets where each document can contain many pages, it is impossible to compute the similarity using the entire document, to require creating solutions to analyze a few meaningful terms, in summary form. This article presents TextSSimily, a method that compares documents semantically considering only short text for comparison (text summary), using semantics to improve the set of responses and summaries to improve time to obtain results for large sets of documents. General Terms Semantic Retrieval, Documents Comparison.
Generation and Analysis of a Mouse Intestinal Metatranscriptome through Illumina Based RNA-Sequencing

With the advent of high through-put sequencing (HTS), the emerging science of metagenomics is transforming our understanding of the relationships of microbial communities with their environments. While metagenomics aims to catalogue the genes present in a sample through assessing which genes are actively expressed, metatranscriptomics can provide a mechanistic understanding of community inter-relationships. To achieve these goals, several challenges need to be addressed from sample preparation to sequence processing, statistical analysis and functional annotation. Here we use an inbred non-obese diabetic (NOD) mouse model in which germ-free animals were colonized with a defined mixture of eight commensal bacteria, to explore methods of RNA extraction and to develop a pipeline for the generation and analysis of metatranscriptomic data. Applying the Illumina HTS platform, we sequenced 12 NOD cecal samples prepared using multiple RNA-extraction protocols. The absence of a complete set of reference genomes necessitated a peptide-based search strategy. Up to 16% of sequence reads could be matched to a known bacterial gene. Phylogenetic analysis of the mapped ORFs revealed a distribution consistent with ribosomal RNA, the majority from Bacteroides or Clostridium species. To place these HTS data within a systems context, we mapped the relative abundance of corresponding Escherichia coli homologs onto metabolic and protein-protein interaction networks. These maps identified bacterial processes with components that were well-represented in the datasets. In summary this study highlights the potential of exploiting the economy of HTS platforms for metatranscriptomics.
NADPH Oxidase Contributes to Angiotensin II Signaling in the Nucleus Tractus Solitarius

Angiotensin II (AngII), acting through angiotensin type 1 (AT1) receptors, exerts powerful effects on central autonomic networks regulating cardiovascular homeostasis and fluid balance; however, the mechanisms of AngII signaling in functionally defined central autonomic neurons have not been fully elucidated. In vascular cells, reactive oxygen species (ROS) generated by the enzyme NADPH oxidase play a major role in AngII signaling. Thus, we sought to determine whether NADPH oxidase is present in central autonomic neurons and, if so, whether NADPH oxidase-derived ROS are involved in the effects of AngII on these neurons. The present studies focused on the intermediate dorsomedial nucleus of the solitary tract (dmNTS) because this region receives autonomic afferents via the vagus nerve and is an important site of AngII actions. Using double-label immunoelectron microscopy, we found that the essential NADPH oxidase subunit gp91phox is present in somatodendric and axonal profiles containing AT1 receptors. The gp91phox-labeled dendrites received inputs from large axon terminals resembling vagal afferents. In parallel experiments using patch clamp of dissociated NTS neurons anterogradely labeled via the vagus, we found that AngII potentiates the L-type Ca2+ currents, an effect mediated by AT1 receptors and abolished by the ROS scavenger Mn(III) tetrakis (4-benzoic acid) porphyrin chloride. The NADPH oxidase assembly inhibitor apocynin and the peptide inhibitor gp91phox docking sequence, but not its scrambled version, also blocked the potentiation. The results provide evidence that NADPH oxidase-derived ROS are involved in the effects of AngII on Ca2+ influx in NTS neurons receiving vagal afferents and support the notion that ROS are important signaling molecules in central autonomic networks.
Novel Techniques for the Detection of ON and OFF States of Appliances for Power Estimation in Non-Intrusive Load Monitoring

Non-Intrusive Load Monitoring (NILM) is a method of extracting appliance-level power consumption information from aggregate circuit-level data with the goal of giving users feedback regarding their energy consumption so they can take control of their consumption habits. In this paper, we present a novel algorithm for classification of on and off states of appliances. We compare the performance of our algorithm in on state detection with a pervious paper that evaluated the same dataset and show that it performs up to 13% better. We also present the results of a case study where we collected data for different modes of a cooktop, microwave and dishwasher and used our algorithms to perform power estimation. The error on ten different setups in the test bed ranges from 1% to 32%. We discuss our results and lay out ideas for future work.
Comparison of Characteristics of Myosin Heavy Chain-based Fiber and Meat Quality among Four Bovine Skeletal Muscles

Muscle fiber characteristics account for meat quality and muscle fibers are mainly classified into three or more types according to their contractile and metabolic properties. However, the majority of previous studies on bovine skeletal muscle are based on myosin ATPase activity. In the present study, the differences in the characteristics of muscle fibers classified by the expression of myosin heavy chain (MHC) among four bovine skeletal muscles such as longissimus thoracis (LT), psoas major (PM), semimembranosus (SM) and semitendinosus (ST) and their relationships to beef quality were investigated. MHCs 2x, 2a and slow were identified by LC-MS/MS and IIX, IIA and I fiber types were classified. PM, which had the smallest size and highest density of fibers regardless of type, showed the highest myoglobin content, CIE L*, a*, b* and sarcomere length (p<0.05), whereas ST with the highest composition of IIX, showed high shear force and low sarcomere length (p<0.05). The correlation coefficients between muscle fiber characteristics and meat quality showed that type IIX is closely related to poor beef quality and that a high density of small-sized fibers is related to redness and tenderness. Therefore, the differences in meat quality between muscles can be explained by the differences in muscle fiber characteristics, and especially, the muscles with good quality are composed of more small-sized fibers regardless of fiber type.
GUIDING GOAL MODELLING USING SCENARIOS 1

Even though goal modelling is an effective approach to requirements engineering, it is known to present a number of difficulties in practice. The paper discusses these difficulties and proposes to couple goal modelling and scenario authoring to overcome them. Whereas existing techniques use scenarios to concretise goals, we use them to discover goals. Our proposal is to define enactable rules which form the basis of a software environment called L’Ecritoire to guide the requirements elicitation process through interleaved goal modelling and scenario authoring. The focus of the paper is on the discovery of goals from scenarios. The discovery process is centred around the notion of a Requirement Chunk (RC) which is a pair <Goal, Scenario>. The paper presents the notion of RC, the rules to support the discovery of RCs and illustrates the application of the approach within L’Ecritoire using the ATM example. It also evaluates the potential practical benefits expected from the use of the approach.
Patterns in Species Persistence and Biomass Production in Soil Microcosms Recovering from a Disturbance Reject a Neutral Hypothesis for Bacterial Community Assembly

The neutral theory of biodiversity has emerged as a major null hypothesis in community ecology. The neutral theory may sufficiently well explain the structuring of microbial communities as the extremely high microbial diversity has led to an expectation of high ecological equivalence among species. To address this possibility, we worked with microcosms of two soils; the microcosms were either exposed, or not, to a dilution disturbance which reduces community sizes and removes some very rare species. After incubation for recovery, changes in bacterial species composition in microcosms compared with the source soils were assessed by pyrosequencing of bacterial 16S rRNA genes. Our assays could detect species with a proportional abundance ≥ 0.0001 in each community, and changes in the abundances of these species should have occurred during the recovery growth, but not be caused by the disturbance per se. The undisturbed microcosms showed slight changes in bacterial species diversity and composition, with a small number of initially low-abundance species going extinct. In microcosms recovering from the disturbance, however, species diversity decreased dramatically (by > 50%); and in most cases there was not a positive relationship between species initial abundance and their chance of persistence. Furthermore, a positive relationship between species richness and community biomass was observed in microcosms of one soil, but not in those of the other soil. The results are not consistent with a neutral hypothesis that predicts a positive abundance-persistence relationship and a null effect of diversity on ecosystem functioning. Adaptation mechanisms, in particular those associated with species interactions including facilitation and predation, may provide better explanations.
Condiciones de cuidado domiciliario de las personas mayores de 65 años y las características de sus cuidadores. Manizales 2009

Enfermera; Especialista en Salud Pública; Magíster en Desarrollo Educativo y Social; Docente Investigadora de la Facultad de Ciencias de la Salud, Grupo de Investigación en Enfermería (GRIEN), de la Universidad Católica de Manizales. eugenietom@une.net. co Enfermera; Docente Investigadora de la Facultad de Ciencias de la Salud, Grupo de Investigación en Enfermería (GRIEN), de la Universidad Católica de Manizales.
Electronic Health Record Analysis via Deep Poisson Factor Models

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. Information from different modalities is shared via a deep hierarchy of common hidden units. Activation of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demonstrate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 16,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.
Cortical Inactivation by Cooling in Small Animals

Reversible inactivation of the cortex by surface cooling is a powerful method for studying the function of a particular area. Implanted cooling cryoloops have been used to study the role of individual cortical areas in auditory processing of awake-behaving cats. Cryoloops have also been used in rodents for reversible inactivation of the cortex, but recently there has been a concern that the cryoloop may also cool non-cortical structures either directly or via the perfusion of blood, cooled as it passed close to the cooling loop. In this study we have confirmed that the loop can inactivate most of the auditory cortex without causing a significant reduction in temperature of the auditory thalamus or other subcortical structures. We placed a cryoloop on the surface of the guinea pig cortex, cooled it to 2°C and measured thermal gradients across the neocortical surface. We found that the temperature dropped to 20–24°C among cells within a radius of about 2.5 mm away from the loop. This temperature drop was sufficient to reduce activity of most cortical cells and led to the inactivation of almost the entire auditory region. When the temperature of thalamus, midbrain, and middle ear were measured directly during cortical cooling, there was a small drop in temperature (about 4°C) but this was not sufficient to directly reduce neural activity. In an effort to visualize the extent of neural inactivation we measured the uptake of thallium ions following an intravenous injection. This confirmed that there was a large reduction of activity across much of the ipsilateral cortex and only a small reduction in subcortical structures.
Short-Term Forecasting for Empirical Economists. A Survey of the Recently Proposed Algorithms

Practitioners do not always use research findings, as the research is not always conducted in a manner relevant to real-world practice. This survey seeks to close the gap between research and practice in respect of short-term forecasting in real time. To this end, we review the most relevant recent contributions to the literature, examining their pros and cons, and we take the liberty of proposing some avenues of future research. We include bridge equations, MIDAS, VARs, factor models and Markov-switching factor models, all allowing for mixed-frequency and ragged ends. Using the four constituent monthly series of the Stock-Watson coincident index, industrial production, employment, income and sales, we evaluate their empirical performance to forecast quarterly US GDP growth rates in real time. Finally, we review the main results having regard to the number of predictors in factorbased forecasts and how the selection of the more informative or representative variables can be made.
STRONGER KEY DERIVATION VIA SEQUENTIAL MEMORY-HARD FUNCTIONS

We introduce the concepts of memory-hard algorithms and sequential memory-hard functions, and argue that in order for key derivation functions to be maximally secure against attacks using custom hardware, they should be constructed from sequential memory-hard functions. We present a family of key derivation functions which, under the random oracle model of cryptographic hash functions, are provably sequential memory-hard, and a variation which appears to be marginally stronger at the expense of lacking provable strength. Finally, we provide some estimates of the cost of performing brute force attacks on a variety of password strengths and key derivation functions.
Effects of Age and Body Mass Index on Thoracolumbar Spine X-Ray for Diagnosing Osteoporosis in Elderly Women: Tianliao Old People (TOP) Study 07

Purpose The aim of this study was to determine the effects of diagnostic discordance with or without a thoracolumbar spine lateral view X-ray in patients with osteoporosis. Methods We randomly enrolled 368 women over 65 years old (74.3 ± 6.0 years) from Tianliao Township in 2009 (response rate: 75.7%). A diagnosis of osteoporosis was confirmed using one of these criteria: (1) a history of non-traumatic fracture, (2) vertebral fractures based on a thoracolumbar spine lateral view X-ray, or (3) a bone mineral density T-score ≤ -2.5 for the total hip, the femoral neck, the lumbar spine, or all 3 sites. The prevalence of osteoporosis in three groups was compared based on Model I (criteria 1+2) vs. Model II (criteria 1+3) vs. Model III (criteria 1+2+3). The role of thoracolumbar X-ray reflected by the diagnostic discordance of osteoporosis between Models II and III was evaluated. Results The overall prevalence of osteoporosis was 78.3% (Model III, age-standardized 78.1%). The diagnostic discordance was 17.4% in the 368 participants. A logistic regression model showed that age was negatively associated with diagnostic discordance (odds ratio [OR] = 0.93, 95% confidence interval [CI]: 0.88–0.98, p < 0.05), but body mass index was positively associated (OR = 1.07, 95% CI: 1.00–1.15, p < 0.05). Conclusions A thoracolumbar spine lateral view X-ray should be added for women ≥ 65 years old or with a body mass index ≥ 25 kg/m2 to minimize the diagnostic discordance in osteoporosis, especially in highly endemic regions.
Load Balancing of Irregular System Area Networks through Multiple Roots

In recent years we have seen an increasing interest in irregular topologies in the interconnect communities. The predominant routing strategy for such networks is the up*/down* algorithm proposed in connection with Autonet. One problem with this algorithm is that it creates a configuration that is very prone to hot-spots near the root of the up*/down* tree. Previous methods for handling this problem are all based on minimal routing combined with escape paths in some form, but this solution requires functionality for adaptive routing to be implemented in the switches. Furthermore, technologies that require in-order delivery of packets, like the recent InfiniBand specification, cannot take advantage of such methods. In this paper we propose a simple method for load balancing that can be utilized for technologies with source routing or deterministic routing. Our simulation experiments show improvements in throughput of up to 85% in some cases.