Miracle-dz/UniFAR-FTUs huggingface dataset:
Tonometry in Keratoconic Eyes before and after Riboflavin/UVA Corneal Collagen Crosslinking Using Three Different Tonometers

Purpose To evaluate the Goldmann applanation tonometer (GAT), the Pascal dynamic contour tonometer (PDCT), and the ocular response analyzer (ORA) tonometer in measuring intraocular pressure (IOP) in keratoconic eyes before and after riboflavin/ultraviolet A corneal collagen crosslinking (CXL), to assess agreement among devices and to analyze the impact of some ocular parameters on their measurements. Methods Fifty keratoconic eyes were included. Intraocular pressure was measured with GAT, PDCT, and ORA before and after CXL. Fifty nonkeratoconic eyes served as controls. Device agreements were calculated by Bland-Altman analysis. The effect of some ocular characteristics on IOP measurement differences between tonometers was determined. Results Between the 2 groups, there were statistically significant differences in all examined parameters. Preoperatively, in both groups a statistically significant difference was found in IOP measurements among devices (p<0.05). Bland-Altman analysis showed a bias among devices. On average, PDCT overread GAT and ORA. The IOP measurement differences were better predicted by corneal resistance factor. Postoperatively, in keratoconus eyes, there was no statistically significant difference in IOP measurements among the 3 tonometers (p>0.05). The IOP readings with all tonometers after treatment were higher than those obtained preoperatively; however, not to a statistically significant level, with the exception of PDCT and ORA readings at the first month postoperatively. Corneal resistance factor measurements have no significant change after CXL. Conclusions Pascal dynamic contour tonometer could provide more consistent and closer to the true IOP readings than GAT and ORA in healthy eyes with corneal thickness outside the 520-550 μm range, in keratoconus patients and after CXL. Corneal resistance factor was associated significantly with agreement among devices.
Persistent microbial translocation and immune activation in HIV-1-infected South Africans receiving combination antiretroviral therapy.

BACKGROUND Microbial translocation contributes to immune activation and disease progression during chronic human immunodeficiency virus type 1 (HIV-1) infection. However, its role in the African AIDS epidemic remains controversial. Here, we investigated the relationship between markers of monocyte activation, plasma lipopolysaccharide (LPS), and HIV-1 RNA in South Africans prioritized to receive combination antiretroviral therapy (cART). METHODS Ten HIV-1-negative African controls and 80 HIV-1-infected patients with CD4 T cell counts <200 cells/microL were sampled prior to (n=60) or during (n=20) receipt of effective cART. Viral load was measured by Nuclisens; LPS by the Limulus amoebocyte lysate assay; monocyte and T cell subsets by flow cytometry; and soluble CD14, cytokines, and chemokines by enzyme-linked immunosorbent assay and customized Bio-Plex plates. RESULTS Three distinct sets of markers were identified. CCL2, CXCL10, and CD14(+)CD16(+) monocyte levels were positively correlated with HIV-1 viremia. This finding, together with cART-induced normalization of these markers, suggests that their upregulation was driven by HIV-1. Plasma interleukin-6 was associated with the presence of opportunistic coinfections. Soluble CD14 and tumor necrosis factor were linked to plasma LPS levels and, as observed for LPS, remained elevated in patients receiving effective cART. CONCLUSIONS Microbial translocation is a major force driving chronic inflammation in HIV-infected Africans receiving cART. Prevention of monocyte activation may be especially effective at enhancing therapeutic outcomes.
Effect of various drying methods on texture and color of tomato halves.

Tomatoes were pretreated with osmotic solutions (NaCl and sucrose) at different concentrations and then dried using hot air (75C, 1.5 m/s), a vacuum (55C, 75 kPa) or hot-air drying followed by microwave treatment (400 W, 10 s). The effects of pretreatment and drying method on the drying kinetics were examined. A puncture test and scanning electron microscopy were used to analyze the effects of these processes on texture and microstructure. Hunter values (L, a, b) were used to measure color. Measurements showed that two osmotic solutions, S3 (40% sucrose, 5% NaCl) and S4 (40% sucrose, 10% NaCl), performed better, reducing drying times and having a positive effect on microstructure, but an adverse effect on hardness. Apart from the type of process, dehydration reduced firmness and collapsed the structure of tomato halves. The subsequent microwave treatment then caused further damage, especially on the surface of the dried samples, but enhanced their color when combined with appropriate osmotic treatment. PRACTICAL APPLICATIONS This study shows that the color and structural changes of tomato during drying can be reduced using appropriate procedure. This may find application in the production of dried tomato with better appearance and lower drying cost.
Synergistic effects of expandable graphite with magnesium hydroxide on the flame retardancy and thermal properties of polypropylene

In this study, the flammability characterization and synergistic effects of different particle size of expandable graphite (EG) with modified magnesium hydroxide (MH) in flame-retardant polypropylene (PP) composites were studied by limiting oxygen index (LOI), UL-94 test, thermogravimetric analysis (TGA), and fourier transform infrared (FTIR) spectroscopy. The results showed that the particle size of EG had a great effect on the flammability of the PP/MH/EG composites. The EG2 with smaller particle size could apparently increase the LOI value and improved the UL-94 flammability properties rating of the PP composites. The data obtained from the TGA and FTIR curves indicated that the thermo-oxidative stability of PP/MH/EG composites increased with decreasing particle size of EG. And the smaller the particle size of EG, the higher the residues of the composite. POLYM. ENG. SCI., 47:1756–1760, 2007. © 2007 Society of Plastics Engineers
Reality = Relevance? Insights from Spontaneous Modulations of the Brain's Default Network when Telling Apart Reality from Fiction

Background Although human beings regularly experience fictional worlds through activities such as reading novels and watching movies, little is known about what mechanisms underlie our implicit knowledge of the distinction between reality and fiction. The first neuroimaging study to address this issue revealed that the mere exposure to contexts involving real entities compared to fictional characters led to engagement of regions in the anterior medial prefrontal and posterior cingulate cortices (amPFC, PCC). As these core regions of the brain's default network are involved during self-referential processing and autobiographical memory retrieval, it was hypothesized that real entities may be conceptually coded as being more personally relevant to us than fictional characters. Methodology/Principal Findings In the present functional magnetic resonance imaging (fMRI) study, we directly test the hypothesis that entity-associated personal relevance is the critical factor underlying the differential engagement of these brain regions by comparing the brain's response when processing contexts involving family or friends (high relevance), famous people (medium relevance), or fictional characters (low relevance). In line with predictions, a gradient pattern of activation was observed such that higher entity-associated personal relevance was associated with stronger activation in the amPFC and the PCC. Conclusions/Significance The results of the study have several important implications. Firstly, they provide informed grounds for characterizing the dynamics of reality-fiction distinction. Secondly, they provide further insights into the functions of the amPFC and the PCC. Thirdly, in view of the current debate related to the functional relevance and specificity of brain's default network, they reveal a novel approach by which the functions of this network can be further explored.
A Specialized Search Engine for Web Service Discovery

Web service discovery on the web is not a trivial task as the number of available web service descriptions continuously increases, and global UDDI registries are no longer available. As discovery through conventional, general-purpose search engines does not yield satisfactory results, a more promising alternative should be explored through specialized search engines. This paper explores the design and implementation of such a framework, resulting in WESS, a search engine targeted to discovering and retrieving web service descriptions. The presented system features an adaptive web service description collection process, through specialized and directed crawling, as well as an enhanced indexing and retrieval mechanism, which handles description documents as semi-structured text, separating actual information from tags and annotations. The paper also presents experiments and use cases regarding different search scenarios, in addition to performance results.
An Effective Semantic Event Matching System in the Internet of Things (IoT) Environment

IoT sensors use the publish/subscribe model for communication to benefit from its decoupled nature with respect to space, time, and synchronization. Because of the heterogeneity of communicating parties, semantic decoupling is added as a fourth dimension. The added semantic decoupling complicates the matching process and reduces its efficiency. Our proposed algorithm clusters subscriptions and events according to topic and performs the matching process within these clusters, which increases the throughput by reducing the matching time from the range of 16–18 ms to 2–4 ms. Moreover, the accuracy of matching is improved when subscriptions must be fully approximated, as demonstrated by an over 40% increase in F-score results. This work shows the benefit of clustering, as well as the improvement in the matching accuracy and efficiency achieved using this approach.
Discrete minimum ratio curves and surfaces

Graph cuts have proven useful for image segmentation and for volumetric reconstruction in multiple view stereo. However, solutions are biased: the cost function tends to favour either a short boundary (in 2D) or a boundary with a small area (in 3D). This bias can be avoided by instead minimising the cut ratio, which normalises the cost by a measure of the boundary size. This paper uses ideas from discrete differential geometry to develop a linear programming formulation for finding a minimum ratio cut in arbitrary dimension, which allows constraints on the solution to be specified in a natural manner, and which admits an efficient and globally optimal solution. Results are shown for 2D segmentation and for 3D volumetric reconstruction.
In Vivo Mapping of Vascular Inflammation Using Multimodal Imaging

Background Plaque vulnerability to rupture has emerged as a critical correlate to risk of adverse coronary events but there is as yet no clinical method to assess plaque stability in vivo. In the search to identify biomarkers of vulnerable plaques an association has been found between macrophages and plaque stability—the density and pattern of macrophage localization in lesions is indicative of probability to rupture. In very unstable plaques, macrophages are found in high densities and concentrated in the plaque shoulders. Therefore, the ability to map macrophages in plaques could allow noninvasive assessment of plaque stability. We use a multimodality imaging approach to noninvasively map the distribution of macrophages in vivo. The use of multiple modalities allows us to combine the complementary strengths of each modality to better visualize features of interest. Our combined use of Positron Emission Tomography and Magnetic Resonance Imaging (PET/MRI) allows high sensitivity PET screening to identify putative lesions in a whole body view, and high resolution MRI for detailed mapping of biomarker expression in the lesions. Methodology/Principal Findings Macromolecular and nanoparticle contrast agents targeted to macrophages were developed and tested in three different mouse and rat models of atherosclerosis in which inflamed vascular plaques form spontaneously and/or are induced by injury. For multimodal detection, the probes were designed to contain gadolinium (T1 MRI) or iron oxide (T2 MRI), and Cu-64 (PET). PET imaging was utilized to identify regions of macrophage accumulation; these regions were further probed by MRI to visualize macrophage distribution at high resolution. In both PET and MR images the probes enhanced contrast at sites of vascular inflammation, but not in normal vessel walls. MRI was able to identify discrete sites of inflammation that were blurred together at the low resolution of PET. Macrophage content in the lesions was confirmed by histology. Conclusions/Significance The multimodal imaging approach allowed high-sensitivity and high-resolution mapping of biomarker distribution and may lead to a clinical method to predict plaque probability to rupture.
Characterization of seizure‐induced syncopes: EEG, ECG, and clinical features

Ictal bradycardia and ictal asystole (IA) are rare but severe complications of epileptic seizures. They are difficult to recognize within a seizure and their consequences remain unclear. Herein we aimed to extend the description of electrical and clinical features of seizures with IA and/or syncope.
Use of estimated evolutionary strength at the codon level improves the prediction of disease‐related protein mutations in humans

Predicting the functional impact of protein variation is one of the most challenging problems in bioinformatics. A rapidly growing number of genome‐scale studies provide large amounts of experimental data, allowing the application of rigorous statistical approaches for predicting whether a given single point mutation has an impact on human health. Up until now, existing methods have limited their source data to either protein or gene information. Novel in this work, we take advantage of both and focus on protein evolutionary information by using estimated selective pressures at the codon level. Here we introduce a new method (SeqProfCod) to predict the likelihood that a given protein variant is associated with human disease or not. Our method relies on a support vector machine (SVM) classifier trained using three sources of information: protein sequence, multiple protein sequence alignments, and the estimation of selective pressure at the codon level. SeqProfCod has been benchmarked with a large dataset of 8,987 single point mutations from 1,434 human proteins from SWISS‐PROT. It achieves 82% overall accuracy and a correlation coefficient of 0.59, indicating that the estimation of the selective pressure helps in predicting the functional impact of single‐point mutations. Moreover, this study demonstrates the synergic effect of combining two sources of information for predicting the functional effects of protein variants: protein sequence/profile‐based information and the evolutionary estimation of the selective pressures at the codon level. The results of large‐scale application of SeqProfCod over all annotated point mutations in SWISS‐PROT (available for download at http://sgu.bioinfo.cipf.es/services/Omidios/; last accessed: 24 August 2007), could be used to support clinical studies. Hum Mutat 29(1), 198–204, 2008. © 2007 Wiley‐Liss, Inc.
Spoken term detection using fast phonetic decoding

While spoken term detection (STD) systems based on word indices provide good accuracy, there are several practical applications where it is infeasible or too costly to employ an LVCSR engine. An STD system is presented, which is designed to incorporate a fast phonetic decoding front-end and be robust to decoding errors whilst still allowing for rapid search speeds. This goal is achieved through monophone open-loop decoding coupled with fast hierarchical phone lattice search. Results demonstrate that an STD system that is designed with the constraint of a fast and simple phonetic decoding front-end requires a compromise to be made between search speed and search accuracy.
Moderate to vigorous physical activity and sedentary time and cardiometabolic risk factors in children and adolescents.

CONTEXT Sparse data exist on the combined associations between physical activity and sedentary time with cardiometabolic risk factors in healthy children. OBJECTIVE To examine the independent and combined associations between objectively measured time in moderate- to vigorous-intensity physical activity (MVPA) and sedentary time with cardiometabolic risk factors. DESIGN, SETTING, AND PARTICIPANTS Pooled data from 14 studies between 1998 and 2009 comprising 20 871 children (aged 4-18 years) from the International Children's Accelerometry Database. Time spent in MVPA and sedentary time were measured using accelerometry after reanalyzing raw data. The independent associations between time in MVPA and sedentary time, with outcomes, were examined using meta-analysis. Participants were stratified by tertiles of MVPA and sedentary time. MAIN OUTCOME MEASURES Waist circumference, systolic blood pressure, fasting triglycerides, high-density lipoprotein cholesterol, and insulin. RESULTS Times (mean [SD] min/d) accumulated by children in MVPA and being sedentary were 30 (21) and 354 (96), respectively. Time in MVPA was significantly associated with all cardiometabolic outcomes independent of sex, age, monitor wear time, time spent sedentary, and waist circumference (when not the outcome). Sedentary time was not associated with any outcome independent of time in MVPA. In the combined analyses, higher levels of MVPA were associated with better cardiometabolic risk factors across tertiles of sedentary time. The differences in outcomes between higher and lower MVPA were greater with lower sedentary time. Mean differences in waist circumference between the bottom and top tertiles of MVPA were 5.6 cm (95% CI, 4.8-6.4 cm) for high sedentary time and 3.6 cm (95% CI, 2.8-4.3 cm) for low sedentary time. Mean differences in systolic blood pressure for high and low sedentary time were 0.7 mm Hg (95% CI, -0.07 to 1.6) and 2.5 mm Hg (95% CI, 1.7-3.3), and for high-density lipoprotein cholesterol, differences were -2.6 mg/dL (95% CI, -1.4 to -3.9) and -4.5 mg/dL (95% CI, -3.3 to -5.6), respectively. Geometric mean differences for insulin and triglycerides showed similar variation. Those in the top tertile of MVPA accumulated more than 35 minutes per day in this intensity level compared with fewer than 18 minutes per day for those in the bottom tertile. In prospective analyses (N = 6413 at 2.1 years' follow-up), MVPA and sedentary time were not associated with waist circumference at follow-up, but a higher waist circumference at baseline was associated with higher amounts of sedentary time at follow-up. CONCLUSION Higher MVPA time by children and adolescents was associated with better cardiometabolic risk factors regardless of the amount of sedentary time.
Tracing Gas Motions in the Centaurus Cluster

We apply the stochastic model of iron transport developed by Rebusco et al. (2005) to the Centaurus cluster. Using this model, we find that an effective diffusion coefficient D in the range 2 x 10{sup 28} - 4 x 10{sup 28} cm{sup 2}s{sup -1} can approximately reproduce the observed abundance distribution. Reproducing the flat central profile and sharp drop around 30-70 kpc, however, requires a diffusion coefficient that drops rapidly with radius so that D > 4 x 10{sup 28} cm{sup 2}s{sup -1} only inside about 25 kpc. Assuming that all transport is due to fully-developed turbulence, which is also responsible for offsetting cooling in the cluster core, we calculate the length and velocity scales of energy injection. These length scales are found to be up to a factor of {approx} 10 larger than expected if the turbulence is due to the inflation and rising of a bubble. We also calculate the turbulent thermal conductivity and find it is unlikely to be significant in preventing cooling.
Treatment Course with Antidepressant Therapy in Late-life Depression

Objective: In order to assess the effect of gray matter volumes and cortical thickness on antidepressant treatment response in late-life depression, the authors examined the relationship between brain regions identified a priori and Montgomery-Åsberg Depression Rating Scale (MADRS) scores over the course of an antidepressant treatment trial. Method: In a nonrandomized prospective trial, 168 patients who were at least 60 years of age and met DSM-IV criteria for major depression underwent MRI and were enrolled in a 12-week treatment study. Exclusion criteria included cognitive impairment or severe medical disorders. The volumes or cortical thicknesses of regions of interest that differed between the depressed group and a comparison group (N=50) were determined. These regions of interest were used in analyses of the depressed group to predict antide-pressant treatment outcome. Mixed-model analyses adjusting for age, education, age at depression onset, race, baseline MADRS score, scanner, and interaction with time examined predictors of MADRS scores over time. Results: Smaller hippocampal volumes predicted a slower response to treatment. With the inclusion of white matter hyper-intensity severity and neuropsychological factor scores, the best model included hippocampal volume and cognitive processing speed to predict rate of response over time. A secondary analysis showed that hippocampal volume and frontal pole thickness differed between patients who achieved remission and those who did not. Conclusions: These data expand our understanding of the prediction of treatment course in late-life depression. The authors propose that the primary variables of hippocampal volume and cognitive processing speed, subsuming other contributing variables (episodic memory, executive function, language processing) predict an-tidepressant response. Lat e-life depression is a heterogeneous disorder that is associated with many adverse conditions, including decreased cognitive function (1–3) and an elevated risk for comorbid medical disorders such as vascular diseases (4, 5), as well as with an elevated mortality rate (1). The etiological factors contributing to late-life depression are not entirely understood, but the vascular depression hypothesis (6, 7) posits that cerebrovascular disease contributes to the development and severity of depression in older adults by causing ischemic white matter lesions of subcortical limbic structure projections to the frontal cortex or in frontal cortical white matter tracts; these interruptions cause alterations in mood regulation (5, 8) and cognition (9). Gray matter structural alterations are also implicated in late-life depression, especially the regions comprising the frontolimbic pathway, including the orbitofrontal cortex, anterior cingulate gyrus, basal ganglia, hippocampus, parahippocampus, and amygdala. Smaller volumes of the …
Asset Pricing with Limited Risk Sharing and Heterogeneous Agents

We solve a model with incomplete markets and heterogeneous agents that generates a large equity premium, while simultaneously matching stock market participation and individual asset holdings. The high risk premium is driven by incomplete risk sharing among stockholders, which results from the combination of aggregate uncertainty, borrowing constraints and a (realistically) calibrated life-cycle earnings profile subject to idiosyncratic shocks. We show that it is challenging to simultaneously match asset pricing moments and individual portfolio decisions, while limited participation has a negligible impact on the risk premium, contrary to the results of models where it is imposed exogenously.