Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantification of carnitine and acylcarnitines in biological matrices by HPLC electrospray ionization-mass spectrometry.

BACKGROUND Analysis of carnitine and acylcarnitines by tandem mass spectrometry (MS/MS) has limitations. First, preparation of butyl esters partially hydrolyzes acylcarnitines. Second, isobaric nonacylcarnitine compounds yield false-positive results in acylcarnitine tests. Third, acylcarnitine constitutional isomers cannot be distinguished. METHODS Carnitine and acylcarnitines were isolated by ion-exchange solid-phase extraction, derivatized with pentafluorophenacyl trifluoromethanesulfonate, separated by HPLC, and detected with an ion trap mass spectrometer. Carnitine was quantified with d(3)-carnitine as the internal standard. Acylcarnitines were quantified with 42 synthesized calibrators. The internal standards used were d(6)-acetyl-, d(3)-propionyl-, undecanoyl-, undecanedioyl-, and heptadecanoylcarnitine. RESULTS Example recoveries [mean (SD)] were 69.4% (3.9%) for total carnitine, 83.1% (5.9%) for free carnitine, 102.2% (9.8%) for acetylcarnitine, and 107.2% (8.9%) for palmitoylcarnitine. Example imprecision results [mean (SD)] within runs (n = 6) and between runs (n = 18) were, respectively: total carnitine, 58.0 (0.9) and 57.4 (1.7) micromol/L; free carnitine, 44.6 (1.5) and 44.3 (1.2) micromol/L; acetylcarnitine, 7.74 (0.51) and 7.85 (0.69) micromol/L; and palmitoylcarnitine, 0.12 (0.01) and 0.11 (0.02) micromol/L. Standard-addition slopes and linear regression coefficients were 1.00 and 0.9998, respectively, for total carnitine added to plasma, 0.99 and 0.9997 for free carnitine added to plasma, 1.04 and 0.9972 for octanoylcarnitine added to skeletal muscle, and 1.05 and 0.9913 for palmitoylcarnitine added to skeletal muscle. Reference intervals for plasma, urine, and skeletal muscle are provided. CONCLUSIONS This method for analysis of carnitine and acylcarnitines overcomes the observed limitations of MS/MS methods.
Four Encounters with System Identification

Model-based engineering becomes more and more important in industrial practice. System identification is a vital technology for producing the necessary models, and has been an active area of research and applications in the automatic control community during half a century. At the same time, increasing demands require the area to constantly develop and sharpen its tools. This paper deals with how system identification does that by amalgamating concepts, features and methods from other fields. It describes encounters with four areas in systems theory and engineering: Networked Systems, Particle Filtering Techniques, Sparsity and Compressed Sensing, and Machine Learning. The impacts on System Identification methodology by these encounters are described and illustrated.
Querying semantic web data with SPARQL

The Semantic Web is the initiative of the W3C to make information on the Web readable not only by humans but also by machines. RDF is the data model for Semantic Web data, and SPARQL is the standard query language for this data model. In the last ten years, we have witnessed a constant growth in the amount of RDF data available on the Web, which have motivated the theoretical study of some fundamental aspects of SPARQL and the development of efficient mechanisms for implementing this query language. Some of the distinctive features of RDF have made the study and implementation of SPARQL challenging. First, as opposed to usual database applications, the semantics of RDF is open world, making RDF databases inherently incomplete. Thus, one usually obtains partial answers when querying RDF with SPARQL, and the possibility of adding optional information if present is a crucial feature of SPARQL. Second, RDF databases have a graph structure and are interlinked, thus making graph navigational capabilities a necessary component of SPARQL. Last, but not least, SPARQL has to work at Web scale! RDF and SPARQL have attracted interest from the database community. However, we think that this community has much more to say about these technologies, and, in particular, about the fundamental database problems that need to be solved in order to provide solid foundations for the development of these technologies. In this paper, we survey some of the main results about the theory of RDF and SPARQL putting emphasis on some research opportunities for the database community.
Cloning and Expression of Two Novel Hemin Binding Protein Genes from Treponema denticola

ABSTRACT Treponema denticola does not appear to produce siderophores, so it must acquire iron by other pathways. Indeed,T. denticola has been shown to have an iron-regulated 44-kDa outer membrane protein (HbpA) with hemin binding ability. To characterize the HbpA protein, its gene was cloned from genomic DNA libraries of T. denticola. Sequence analysis of thehbpA open reading frame indicated that it encoded a 42.8-kDa protein with a 23-amino-acid signal peptide. HbpA has no significant homology to any proteins in the databases. Southern blot analysis demonstrated that hbpA is present in severalT. denticola ATCC strains and clinical isolates, but not inTreponema pectinovorum, Treponema socranskii, orEscherichia coli. HbpA, expressed as a recombinant protein in E. coli and purified by antibody affinity chromatography, has hemin binding activity as determined by lithium dodecyl sulfate-polyacrylamide gel electrophoresis with tetramethylbenzidine staining. Northern blot analysis showed that there were two hbpA-containing transcripts, of approximately 1.3 and 2.6 kb, and that the RNA levels were low-iron induced. Interestingly, the 2.6-kb mRNA also encoded a second protein with significant homology to hbpA. This downstream gene, calledhbpB, was cloned and sequenced and its product was expressed as a fusion protein in E. coli. ThehbpB gene product is 49% identical to HbpA and binds hemin. Thus, T. denticola has two novel hemin binding proteins which may be part of a previously unrecognized iron acquisition pathway.
Classification Model Disease Risk Areas Endemicity Dengue Fever Outbreak based Prediction of Patients, Death, IR and CFR using Forecasting Techniques

model time series data becomes a process of model use to create prediction (forecast) to an event in the future based on past event which is known as data. The data gives benefit to the interrelatedness among factors that can be the predictor variables. Deep investigation to time series data will give information to find out the data pattern. One of the examples of data series is dengue fever phenomena. Dengue fever is a contagious disease which can become an endemic. The spread of dengue fever needs a particular supervision from related party under the supervision of health department. Dengue fever control is used to avoid the disease to stop spreading. It is done to give important information, so the society can know endemic area from a particular social environment. The research is aimed to do improvisation toward dengue fever surveillance system by conducting a forecast of dengue fever occurrences in a particular area. Forecast technique was conducted with three (3) algorithm approaches. The test of three algorithm forecasting was done to predict dengue fever occurrences in 12 months and to help the activity to control spreading cases of dengue fever to stop spreading in the area of Yogyakarta. Forecast experiment approach from three methods in which linear regression, multilayer perceptron, and sequential minimal optimization regression (SMOreg) showed that linear regression had better accuracy compared to sequential minimal optimization regression (SMOreg) and multilayer perceptron.
MFI-tree: An effective multi-feature index structure for weighted query application

Multi-Feature Index Tree (MFI-Tree), a new indexing structure, is proposed to index multiple high-dimensional features of video data for video retrieval through example. MFI-Tree employs tree structure which is beneficial for the browsing application, and retrieves the last level cluster nodes in retrieval application to improve the performance. Aggressive Decided Distance for kNN (ADD-kNN) search algorithm is designed because it can effectively reduce the distance to prune the search space. Experimental results demonstrate that the MFITree and ADD-kNN algorithm have the advantages over sequential scan in performance.
Vegetation Greening Trends at Two Sites in the Canadian Arctic: 1984–2015

ABSTRACT This study examined vegetation greening at two arctic sites: the Apex River Watershed (ARW), Baffin Island, Nunavut (a Low Arctic site) and the Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, Nunavut (a High Arctic site). The vegetation at both study sites was characterized using a supervised land-cover classification approach using high spatial resolution satellite remote sensing data (i.e., IKONOS [4 m] and WorldView-2 [2 m]). Meanwhile, Normalized Difference Vegetation Index (NDVI) data spanning the past 30 years were derived from intermediate spatial resolution data (i.e., Landsat TM/ETM/OLI [30 m]). The land-cover classifications were used to partition the Landsat NDVI time series by vegetation type. Climate variables (i.e., temperature, precipitation, and growing season length [GSL]) were examined to explore potential relationships of NDVI to climate warming trends. The results of the land-cover classifications demonstrated inherent trends of vegetation types along elevation and moisture gradients. The NDVI time series for the CBAWO (1985–2015) demonstrated an overall significant increase in greening, specifically in the dry and mesic vegetation types. Conversely, similar greening (overall or by vegetation type) was not observed for the ARW (1984–2015). Based on climate data from the nearest permanent weather station (Mould Bay, Nunavut), the overall increase in NDVI at the CBAWO was largely attributed to a significant increase in July temperatures and GSL.
Multi-channel i-vector combination for robust speaker verification in multi-room domestic environments

In this work we address the speaker veriﬁcation task in domestic environments where multiple rooms are monitored by a set of distributed microphones. In particular, we focus on the mismatch between the training of the total variability feature extraction hyper-parameters, the enrolment stage, which occurs at a ﬁxed position in the home, and the test phase which could happen in any location of the apartment. Building upon a previous work, where a position independent multi-channel veriﬁcation system was introduced, we investigate different i-vector combination strategies to attenuate the effects of the above mentioned mismatch sources. The proposed methods implicitly select the microphones in the room where the speaker is, without any knowledge about the speaker position. An experimental analysis on a simulated multi-channel multi-room reverberant data-set shows that the proposed solutions are robust against changes in the speaker position and orientation, achieving performance close to an upper-bound based on knowledge about the speaker location.
Adenosine Monophosphate-Activated Protein Kinase Suppresses Vascular Smooth Muscle Cell Proliferation Through the Inhibition of Cell Cycle Progression

Vascular smooth muscle cell (VSMC) proliferation is a critical event in the development and progression of vascular diseases, including atherosclerosis. We investigated whether the activation of adenosine monophosphate-activated protein kinase (AMPK) could suppress VSMC proliferation and inhibit cell cycle progression. Treatment of human aortic smooth muscle cells (HASMCs) or isolated rabbit aortas with the AMPK activator 5-Aminoimidazole-4-carboxamide ribonucleoside (AICAR) induced phosphorylation of AMPK and acetyl Co-A carboxylase. AICAR significantly inhibited HASMC proliferation induced by both platelet-derived growth factor-BB (PDGF-BB) and fetal calf serum (FCS). Treatment with AICAR inhibited the phosphorylation of retinoblastoma gene product (Rb) induced by PDGF-BB or FCS, and increased the expression of cyclin-dependent kinase inhibitor p21CIP but not that of p27KIP. Pharmacological inhibition of AMPK or overexpression of dominant negative-AMPK inhibited both the suppressive effect of AICAR on cell proliferation and the phosphorylation of Rb, suggesting that the effect of AICAR is mediated through the activation of AMPK. Cell cycle analysis in HASMCs showed that AICAR significantly increased cell population in G0/G1-phase and reduced that in S- and G2/M-phase, suggesting AICAR induced cell cycle arrest. AICAR increased both p53 protein and Ser-15 phosphorylated p53 in HASMCs, which were blocked by inhibition of AMPK. In isolated rabbit aortas, AICAR also increased Ser-15 phosphorylation and protein expression of p53 and inhibited Rb phosphorylation induced by FCS. These data suggest for the first time that AMPK suppresses VSMC proliferation via cell cycle regulation by p53 upregulation. Therefore, AMPK activation in VSMCs may be a therapoietic target for the prevention of vascular diseases.
Cancer in relation to occupational exposure to trichloroethylene.

Accepted 3 September 1995 Trichloroethylene (TCE), C2HC13, has been produced commercially for more than 80 years. For the past few decades it has been used primarily for metal degreasing, and as a solvent for oils and resins. Chronic high dose exposure to TCE increases the incidence of some forms of cancer in some species of rodents. Malignant tumours of the liver occur with increased frequency in Swiss and B6C3F, mice of both sexes, after either respiratory' or oral2 exposure to TCE, but not in some other strains of mice nor in rats or hamsters.3 6 Chronic exposure to TCE increases the incidence of adenocarcinomas of the lung in female ICR and B6C3F, mice,' 7 but other strains of mice and rats that have been tested did not develop lung tumours. ' Small increases in the occurrence of kidney tubular cell carcinomas and testicular tumours also have occurred after TCE in some (but not all) species of male rats. 2 5 The occurrence of cancer has been monitored in several employed groups in whom specific exposure to TCE could be identified. Four of these cohort studies8-" have tabulated the rates of individual types of cancer. The purpose of this article is to review the results of the four cohort studies (augmented, for several of the
Reciprocal translocations: tracing their meiotic behavior

Purpose: Segregation and interchromosomal effect studies have been performed in reciprocal translocation carriers by sperm-fluorescent in situ hybridization reporting a great heterogeneity. The divergences have been attributed to the particular cytogenetic characteristics of each rearrangement. Nevertheless, there is no consensus in the factors that are responsible for such variability. The purpose of this study was to determine which cytogenetic features influence in the segregation and interchromosomal effect outcome.Methods: Segregation and interchromosomal effects analyses were performed in 14 reciprocal translocation carriers, selected because they presented very different cytogenetic features regarding the tetravalent pairing geometry. In each segregation study, a customized combination of probes was used to identify all the segregation products. In the interchromosomal effect study, we used a triple-color fluorescent in situ hybridization for chromosomes X, Y, and 18.Results: A preferential segregation pattern with a gradually decreasing production of Alternate, Adjacent I, Adjacent II, and 3:1 segregation was observed in the segregation analysis. Some specific features have been observed to influence this distribution: size of the translocated and centric segments and the presence of centromeres from acrocentric chromosomes in the center of the cross. Aneuploidy/diploidy screening revealed increased frequencies of numerical anomalies in seven carriers.Conclusions: Our data suggest that reciprocal translocations display a more homogeneous behavior than described in the literature. The interchromosomal effects represent an additional source of imbalances in these carriers.
Fructose: A Dietary Sugar in Crosstalk with Microbiota Contributing to the Development and Progression of Non-Alcoholic Liver Disease

Fructose is one of the key dietary catalysts in the development of non-alcoholic fatty liver disease (NAFLD). NAFLD comprises a complex disease spectrum, including steatosis (fatty liver), non-alcoholic steatohepatitis, hepatocyte injury, inflammation, and fibrosis. It is also the hepatic manifestation of the metabolic syndrome, which covers abdominal obesity, insulin resistance, dyslipidemia, glucose intolerance, or type 2 diabetes mellitus. Commensal bacteria modulate the host immune system, protect against exogenous pathogens, and are gatekeepers in intestinal barrier function and maturation. Dysbalanced intestinal microbiota composition influences a variety of NAFLD-associated clinical conditions. Conversely, nutritional supplementation with probiotics and preobiotics impacting composition of gut microbiota can improve the outcome of NAFLD. In crosstalk with the host immune system, the gut microbiota is able to modulate inflammation, insulin resistance, and intestinal permeability. Moreover, the composition of microbiota of an individual is a kind of fingerprint highly influenced by diet. In addition, not only the microbiota itself but also its metabolites influence the metabolism and host immune system. The gut microbiota can produce vitamins and a variety of nutrients including short-chain fatty acids. Holding a healthy balance of the microbiota is therefore highly important. In the present review, we discuss the impact of long-term intake of fructose on the composition of the intestinal microbiota and its biological consequences in regard to liver homeostasis and disease. In particular, we will refer about fructose-induced alterations of the tight junction proteins affecting the gut permeability, leading to the translocation of bacteria and bacterial endotoxins into the blood circulation.
“You Stupid Tin Box” - Children Interacting with the AIBO Robot: A Cross-linguistic Emotional Speech Corpus

This paper deals with databases that combine different aspects: children's speech, emotional speech, human-robot communication, cross-linguistics, and read vs. spontaneous speech: in a Wizard-of-Oz scenario, German and English children had to instruct Sony's AIBO robot to fulfil specific tasks. In one experimental condition, strictly parallel for German and English, the AIBO behaved `disobedient' by following it's own script irrespective of the child's commands. By that, reactions of different children to the same sequence of AIBO's actions could be obtained. In addition, both the German and the English children were recorded reading texts. The data are transliterated orthographically; emotional user states and some other phenomena will be annotated. We report preliminary word recognition rates and classification results.
Scoring Systems in Assessing Survival of Critically Ill ICU Patients

Background The aim of this study was to determine which of the most commonly used scoring systems for evaluation of critically ill patients in the ICU is the best and simplest to use in our hospital. Material/Methods This prospective study included 60 critically ill patients. After admittance to the ICU, APACHE II, SAPS II, and MPM II0 were calculated. During further treatment in the ICU, SOFA and MPM II were calculated at 24 h, 48 h, and 72 h and 7 days after admittance using laboratory and radiological measures. Results In comparison with survivors, non-survivors were older (p<0.01) and spent significantly more days on mechanical ventilation (p<0.01). ARDS was significantly more common in patients who survived compared to those who did not (chi-square=7.02, p<0.01), which is not the case with sepsis (chi-square=0.388, p=0.53). AUROC SAPS II was 0.690, and is only slightly higher than the other 2 AUROC incipient scoring systems, MPM II and APACHE II (0.654 and 0.623). The APACHE II has the highest specificity (81.8%) and MPM II the highest sensitivity (85.2%). MPM II7day AUROC (1.0) shows the best discrimination between patients who survived and those who did not. MPM II48 (0.836), SOFA72 (0.821) and MPM II72 (0.817) also had good discrimination scores. Conclusions APACHE II and SAPS II measured on admission to the ICU were significant predictors of complications. MPM II7day has the best discriminatory power, followed by SOFA7day and MPM II48. MPM II7day has the best calibration followed by SOFA7day and APACHE II.
Low Power and Low Complexity Compressor for Video Capsule Endoscopy

The main challenge in video capsule endoscopic system is to reduce the area and power consumption while maintaining acceptable video reconstruction. In this paper, a subsample-based data compressor for video endoscopy application is presented. The algorithm is developed around the special features of endoscopic images that consists of a differential pulse-coded modulation (DPCM) followed by Golomb-Rice coding. Based on the nature of endoscopic images, several subsampling schemes on the chrominance components are applied. This video compressor is designed in a way to work with any commercial low-power image sensors that outputs image pixels in a raster scan fashion, eliminating the need of memory buffer and temporary storage (as needed in transform coding schemes). An image corner clipping algorithm is also introduced. The reconstructed images have been verified by five medical doctors for acceptability. The proposed low-complexity design is implemented in a 0.18 μm CMOS technology and consumes 592 standard cells, 0.16 × 0.16 mm silicon area, and 42 μW of power. Compared to other algorithms targeted to video capsule endoscopy, the proposed raster-scan-based scheme performs strongly with a compression ratio of 80% and a very high reconstruction peak signal-to-noise ratio (over 48 dB).
Performance of pearl millet under agri-horti system as influenced by sowing methods and integrated nutrient management in Vindhyan region of Uttar Pradesh, India

An experiment involving three sowing methods and four integrated nutrient management practices was undertaken at Rajeev Gandhi South Campus, Banaras Hindu University in factorial randomized complete block design with three replications. The aim of the study was to assess the effects of sowing methods and integrated nutrients management practices on performance of pearl millet under agri-horti system. The sowing methods and integrated nutrient management practices significantly (P=0.05) influenced performance of pearl millet. Adoption of ridge and furrow sowing method recorded higher growth [plant height (147.7 cm), dry weight (72.7 g), and number of tillers plant-1 (2.0)], yield attributes [effective tillers hill-1 (1.77), panicle length (17.9 cm), grains panicle-1 (1508.3), grains weight panicle-1 (13.9), and test weight (9.23 g)], yields [ grain yield (1412 kg ha-1 ), and stover yield (3972 kg ha-1 )], and economics [net returns (Rs. 36371 ha-1 ), and B:C ratio (1.79) than broadcasting and raised bed. Application of 50% recommended dose of fertilizer + 50% poultry manure resulted higher growth [plant height (151.9 cm), dry weight (79.7 g), and number of tillers plant-1 (2.22)], yield attributes[effective tillers hill-1 (2.0), panicle length (18.8 cm), grains panicle-1 (1615.6), grains weight panicle-1 (14.5), and test weight (9.76 g)], yields [ grain yield (1552 kg ha-1 ), and stover yield (4360 kg ha-1 )] and economics [net returns (Rs. 38227 ha-1 ), and B:C ratio (1.77) than remaining integrated nutrient management practices. The combination of ridge and furrow and 50% recommended dose of fertilizer + 50% poultry manure was adjudged to be better for pearl millet performance.