Miracle-dz/UniFAR-FTUs huggingface dataset:
On the stability of the production of bubbles in yield-stress fluid using flow-focusing and T-junction devices

We investigate experimentally the stability of bubble production in yield-stress fluids (YSF) and highly viscous silicone oil, using flow-focusing and T-junction devices. When the exit channel is initially pre-filled with the fluid and the gas is pressure-driven, the production is highly unstable, despite a regular frequency of bubble production in the junction. As observed for pressure-driven bubble trains in Newtonian fluids, we report that two mechanisms can explain these observations: (i) drastic reduction of the hydrodynamic pressure drop along the channel during the transient bubble production, which induces a rapid increase of the gas flow rate and (ii) thin film deposition resulting in a cascade of plug break-up and bubble coalescence. While the drastic reduction of the pressure drop is inevitable in such two-phase flows, we show that modifying the surfaces of the channel can help to stabilize the system when the continuous phase is a YSF. To do so, we measure the thickness of the film deposited o.
A Study On Nutritional Status And Dietary Habit Of School Children Associated With Socio Economic Status In Dhaka North City Corporation , Bangladesh

An improved intergeneration cycle of nutrition can eliminate the curse of malnutrition. The study aims to find out the current nutritional condition and dietary practices of the urban school children. A cross sectional study was conducted among 302 school children aged between 4-14 years in four private primary school of DNCC. Anthropometric measurements and socioeconomic condition were taken to assess nutritional status of the children. In addition dietary diversity score (HDDS) was calculated using FAO guideline 2006. Among total 302 children aged between 4-14 years 52.3% were boys and 47.7% were girls. 81.1% children had normal WAZ, while 87.8% attain normal HAZ and 91.7% had normal WHZ. 18.5% & 52.6% children respectively were normal (CDC & WHO BMI-for-age standards). About 52% of the participants had high HDDS. Whereas 89.7% children wash their hand before eating while 93.7% wash their hand after defecation among them 67% wash hand by soap and 40% brushes their teeth twice a day. BMI-for-age was found statistically significant (≥0.05) with family size & income, mothers’ education and HDDS. The nutritional status and dietary habit of children were visibly good. The overall reduction of stunting, wasting and underweight in Bangladesh has been properly reflected in the present study.
Are Profile Hidden Markov Models Identifiable?

Profile Hidden Markov Models (HMMs) are graphical models that can be used to produce finite length sequences from a distribution. In fact, although they were only introduced for bioinformatics 25 years ago (by Haussler et al., Hawaii International Conference on Systems Science 1993), they are arguably the most commonly used statistical model in bioinformatics, with multiple applications, including protein structure and function prediction, classifications of novel proteins into existing protein families and superfamilies, metagenomics, and multiple sequence alignment. The standard use of profile HMMs in bioinformatics has two steps: first a profile HMM is built for a collection of molecular sequences (which may not be in a multiple sequence alignment), and then the profile HMM is used in some subsequent analysis of new molecular sequences. The construction of the profile thus is itself a statistical estimation problem, since any given set of sequences might potentially fit more than one model well. Hence a basic question about profile HMMs is whether they are \em statistically identifiable, which means that no two profile HMMs can produce the same distribution on finite length sequences. Indeed, statistical identifiability is a fundamental aspect of any statistical model, and yet it is not known whether profile HMMs are statistically identifiable. In this paper, we report on preliminary results towards characterizing the statistical identifiability of profile HMMs in one of the standard forms used in bioinformatics.
Signal Processing of Multimodal Mobile Lifelogging Data Towards Detecting Stress in Real-World Driving

Stress is a negative emotion that is part of everyday life. However, frequent episodes or prolonged periods of stress can be detrimental to long-term health. Nevertheless, developing self-awareness is an important aspect of fostering effective ways to self-regulate these experiences. Mobile lifelogging systems provide an ideal platform to support self-regulation of stress by raising awareness of negative emotional states via continuous recording of psychophysiological and behavioral data. However, obtaining meaningful information from large volumes of raw data represents a significant challenge because these data must be accurately quantified and processed before stress can be detected. This work describes a set of algorithms designed to process multiple streams of lifelogging data for stress detection in the context of real world driving. Two data collection exercises have been performed where multimodal data, including raw cardiovascular activity and driving information, were collected from 21 people during daily commuter journeys. Our approach enabled us to 1) pre-process raw physiological data to calculate valid measures of heart rate variability, a significant marker of stress, 2) identify/correct artefacts in the raw physiological data, and 3) provide a comparison between several classifiers for detecting stress. Results were positive and ensemble classification models provided a maximum accuracy of 86.9 percent for binary detection of stress in the real-world.
Phenotypic and Genotypic Identification of Methicillin-Resistant Coagulase Negative Staphylococcus spp. Isolated from Bovine Mastitis

India ranks first in the world in milk production and dairying in India are a classic example of production by masses rather than mass production. Among the different food sectors, the growth in dairy sector has been commendable. The rate of growth in milk production in India is also substantially higher (3.60 %) than the world average of 1.50 per cent. However, the total projected demand of milk by the year 2030 would be about 200 million tonnes, depending on assumptions about income, population, urban growth, and expenditure elasticity parameters, which would imply an annual increase of around 4 million tonnes during the next two decades (N.D.R.I., 2011). Among the several barriers in achieving the production targets, mastitis continues to remain as a challenging impediment, since the affected quarters may have 30.00 per cent less productivity and dairy animals may lose about 15.00 per cent production (Radostitis et al., 2007). In India, the overall economic loss due to mastitis is estimated to be Rs. 7165.51 crores (Bansal and Gupta, 2009). Despite intense research and control programmes, bovine mastitis has remained a major economic problem of the dairy industry (Denis et al., 2009). International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 7 Number 03 (2018) Journal homepage: http://www.ijcmas. com
A GENE EXPRESSION PROGRAMMING SYSTEM FOR TIME SERIES MODELING

This paper presents a heuristic method for time series modeling. The method is based on gene expression programming, a recently proposed evolutionary computation technique. We explain in details the method and the system we developed, named EGIPSYS. We consider time series modeling as a particular problem of symbolic regression. Five different series found in the literature were modeled, including river flows, sunspots and financial data. Performance was measured using the correlation coefficient, the coefficient of variation and the normalized mean square error. For each data series, a training set was used to find a suitable model, and an evaluation set was used to access its forecast performance. Results show that the heuristic method here proposed is appropriate for modeling time series and, also, that it can display a fair performance for one-step and multistep forecasting.
Bacterial Whole Cell Biotransformations: In Vivo Reactions Under In Vitro Conditions

Wild and recombinant bacterial strains are able of carrying out biocatalysis and biotransformation processes involving multi-step metabolic pathways with co-factor regeneration. Bacterial cell tolerance and adaptation to organic solvents, ionic liquids and other nonconventional conditions, have allowed the biotransformation of low water soluble substrates and the production of high valued compounds. The recent developments in single cell monitoring, namely by fluorescence microscopy and flow cytometry, have resulted in increased yields and extended operation of processes for the biotransformation of toxic compounds. In this review, the utilisation of wild and recombinant strains will be discussed as well as the recent developments in metabolic engineering of bioconversion processes. The application of cells in non-conventional media and its repercussion in process design will be reviewed and the importance of studying cell viability will be presented. _____________________________________________________________________________________________________________
Dex-Net as a Service (DNaaS): A Cloud-Based Robust Robot Grasp Planning System

Accessing software resources via the Cloud has become increasingly popular as a means to configure and manage automation systems with reduced infrastructure overhead. Dex-Net as a Service (DNaaS) is a cloud-based grasp planning system for parallel-jaw grippers that provides a graphical user interface and API access to Dex-Net 1.0, a robust grasp planning system based on wrench mechanics and stochastic sampling. DNaaS allows anyone online to compute parallel-jaw grasps on triangular meshes and visualize the results. This paper presents system architecture, examples of generated grasps, and timing data for DNaaS. DNaaS takes under 75 seconds on average to process grasp requests. DNaaS is available at http://automation.berkeley. edu/dex-net.
Analysis of Response Time Distributions: An Example Using the Stroop Task

The shape of a response time (RT) distribution can be described by a 3-parameter model consisting of the convolution of the normal and exponential distributions, the ex-Gaussian. Analyses based on mean RT do not take the distributions shape into account and, for that reason, may obscure aspects of performance. To illustrate the point, the ex-Gaussian model was applied to data obtained from a Stroop task. Mean RT revealed strong interference but no facilitation, whereas the analysis based on the ex-Gaussian model showed both interference and facilitation. In short, analyses that do not take the shape of RT distributions into account can mislead and, therefore, should be avoided. Response time (RT) distributions typically have a positively skewed unimodal shape that contains information that cannot be derived from the distributions mean and variance. A number of studies using a variety of tasks have exploited the extra information to test models (Hacker, 1980; Hockley, 1984; Ratcliff, 1978, 1979). A distributional analysis was used, for instance, to reject the class of models for recognition memory that assumes serial processing at a constant rate: Such models predict mean RT (MRr) but do not account for the shape of the distribution in both the study-test and prememorized-list paradigms (Hockley & CorbaUis, 1982; Ratcliff& Murdock, 1976). In spite of its proven utility, however, the literature appears to treat a distributional analysis as an esoteric supplement to the traditional analysis, namely, the analysis of MRr. In this article, we argue that a distributional analysis should not be treated as a supplementary technique. Rather, we contend that RT measures should always be analyzed using a distributional analysis and that the traditional analysis of MRr risks serious misinterpretation of the data. We start by describing difficulties associated with an analysis of MRr. Next, we discuss
Morphological Characteristics of Vegetative and Reproductive Growth of Senna sophera (L.) Roxb. (Caesalpiniaceae)

In this study, morphological information is produced as evidence for proper delimitation of Senna sophera (L.) Roxb. taxonomy. The field work was carried out during the growing season of 2008 in order to follow up the morphology of vegetative and reproductive growth of studied species throughout the successive stages of its entire life span. Germination of seeds and yield components at harvest time were also taken in consideration. Such knowledge may fulfill information acquisition in this concern. The morphology of vegetative growth includes: plant height, length and diameter of the main stem, number of internodes of the main stem, number of primary branches developed on the main stem, lengths of primary branches at maturity, fresh weight of leafless shoot per plant, total number of leaves per plant, total leaf area per plant and fresh weight of leaves per plant. Moreover, keen observations and descriptive morphology of the root and the shoot were under consideration. The morphology of reproductive growth includes: flower bud differentiation, full blooming, fruit set and maturity. In addition, the yield characters at harvest time were investigated; i.e., number of matured dry pods per plant, number of seeds per pod, number of seeds per plant, yield of matured dry seeds per plant and specific weight of seeds.
Dermoscopic Findings of Hair and Scalp Diseases

Background: Hair and scalp dermoscopy, known as trichoscopy, has recently been used frequently in order to both diagnose and distinguish in various hair and scalp disorders as well as melanocytic lesions. This non-invasive, modern and comfortable method enables us for evaluating hair shafts such as broken hairs, tapering hairs, short vellus hairs, comma hairs, corkscrew hairs, and congenital hair shaft abnormalities; follicular and interfollicular epidermal changes such as yellow dots, black dots, white dots, peripilar sign, follicular openings; and vascular structures such as red dots and globules, twisted red loops, glomerular vessels, arborizing vessels and atypical red vessels. While yellow dots are more important features for alopecia areata, hair diameter variability is very specific for androgenetic alopecia. Comma hairs and corkscrew hairs were reported in patients with tinea capitis. Red dots and globules and twisted red loops are frequently seen in patients with scalp psoriasis, but not seborrheic dermatitis. Thanks to these dermoscopic features, as we can increase our likelihood of correct diagnosis, we can reduce the number of unnecessary scalp biopsies. Furthermore, we can use dermoscopy to evaluate follow-up treatment in diseases such as pediculosis capitis and tinea capitis. Consequently, hair and scalp dermoscopy is very simple, useful and timesaving method that can be easily used in daily practice.
Key Inference from Irish Traditional Music Scores and Recordings

The aim of this paper is to present techniques and results for identifying the key of Irish traditional music melodies, or tunes . Several corpora are used, consisting of both symbolic and audio representations. Monophonic and hetero-phonic recordings are present in the audio datasets. Some particularities of Irish traditional music are discussed, notably its modal nature. New key-proﬁles are deﬁned, that are better suited to Irish music.
Protein Kinase C Enhances Electrical Synaptic Transmission by Acting on Junctional and Postsynaptic Ca 2 Currents X

By synchronizing neuronal activity, electrical transmission influences the coordination, pattern, and/or frequency of firing. In the hemaphroditic marine-snail, Aplysia calfornica, the neuroendocrine bag cell neurons use electrical synapses to synchronize a 30 min afterdischarge of action potentials for the release of reproductive hormone. During the afterdischarge, protein kinase C (PKC) is activated, although its impact on bag cell neuron electrical transmission is unknown. This was investigated here by monitoring electrical synapses between paired cultured bag cell neurons using dual whole-cell recording. Voltage clamp revealed a largely voltage-independent junctional current, which was enhanced by treating with a PKC activator, PMA, before recording. We also examined the transfer of presynaptic action potential-like waveforms (generated in voltage clamp) to the postsynaptic cell (measured in current clamp). For control pairs, the presynaptic spike-like waveforms mainly evoked electrotonic potentials; however, when PKC was triggered, these stimuli consistently produced postsynaptic action potentials. To assess whether this involved changes to postsynaptic responsiveness, single bag cell neurons were injected with junctional-like current mimicking that evoked by a presynaptic action potential. Unlike control neurons, which were less likely to spike, cells in PMA always fired action potentials to the junctional-like current. Furthermore, PKC activation increased a postsynaptic voltage-gated Ca 2 current, which was recruited even by modest depolarization associated with an electrotonic potential. Whereas PKC inhibits gap junctions in most systems, bag cell neurons are rather unique, as the kinase potentiates the electrical synapse; in turn, this synergizes with augmented postsynaptic Ca 2 current to promote synchronous firing.
A Retrospective Study of Statin Use and Its Effectiveness in Taiwanese

Background: Epidemiological and clinical studies have clearly established the link between low-density lipoprotein cholesterol (LDL-C) and atherosclerosis-related cardiovascular consequences. All treatment guidelines developed in different countries identify LDL-C as a causative factor for cardiovascular disease and as a target for lipid-lowering therapy. Although it has been a common practice for physicians to prescribe statins for patients with dyslipidemia, there is little data regarding the effectiveness of statin therapy in Taiwanese. At the same time, the pattern of statin prescription by Taiwanese physicians has been obscure. Methods: We conducted a retrospective study of dyslipidemic Taiwanese patients receiving statin treatment between Sep. 2002 and Dec. 2004. Clinical information and laboratory parameters were collected by reviewing the medical records. The objective was to evaluate the performance of lipid-lowering therapies with statins. Results: Atotal of 961 dyslipidemic patients receiving steady dose of statins were selected from 6468 patients. The most commonly prescribed statin was simvastatin (31.8, n = 306), and the most commonly used doses of different statins were medium potency such as atorvastatin 10 mg (93.4), fluvastatin 80 mg (96.7), lovostatin 20 mg (96.7), pravastatin 10 mg (84.1) and simvastatin 20 mg (84.3). Among the five statins examined, atorvastatin appeared to be the most effective in terms of lowering LDL-C levels across all CHD risk groups. The proportion of attainment of guideline treatment goal was inversely related to cardiovascular risk, with less likelihood in the high cardiovascular group. Only 13.5 and 31 of high-risk patients attained the treatment goals for total cholesterol and LDL-C level, respectively. Conclusion:Fromthis retrospective review, we conclude that despite the proven efficacy of statin in lipid-lowering therapy, there are still many patients not achieving their recommended LDL-C target levels. The percentage of successful lipid-lowering is lowest among the patients with highest risk (those with established cardiovascular disease or diabetes patients). There exists a big discrepancy between physicians’ perception and the true rate of successful lipid control in Taiwan.
Effect of PVP, PVA and POLE surfactants on the size of iridium nanoparticles

Commonly transition metal nano particle are synthesized by physical, chemical or electrochemical methods. In the present work colloidal iridium nanoparticles were synthesized by chemical oxidation method with different surfactants like poly vinyl pyrrolidone (PVP), poly vinyl alcohol (PVA) and poly oxyethylene lauryl ether (POLE). It was found that shape and size of Ir-nano particles resulted were related to kind of capping agent (surfactant) used. The characterization of the synthesized nano particle has been carried out by UV-vis, X-ray diffraction (XRD), FT-IR, scanning electron microscopy (SEM) and transmission electron microscopic (TEM) techniques. UV-vis and FT-IR confirm the oxidation of IrCl3 into IrO2 while XRD confirms the amorphous nature of the iridium nanoparticles synthesized. The morphology and size of the particle were confirmed by TEM. The average particle size determined by Scherrer equation was about 4.12 nm to 4.23 nm with PVP, 2.74 to 3.36 nm with PVA and 20.41 to 42.25 nm with POLE. Poly oxyethylene lauryl ether particles were not further analyzed because of their large size and less stability. Further particle size was confirmed with TEM, which was 4.5 nm with PVP and 7.0 nm with PVA. The particles are spherical with no agglomeration tendency.
Estimation of the macro- and micronutrient status of raspberries grown in the Lublin region

Abstract Environmental monitoring was conducted in the Lublin region in 2009-2012 aimed at the assessment of the supply of several macro- and micronutrients in raspberries plants. The plantations studied were located in eight main regions for the growing of raspberries (Bełżyce, Chodel, Godziszów, Kraśnik, Lublin, Międzyrzec Podlaski, Opole Lubelskie and Urzędów). The contents of nitrogen (N), potassium (K), phosphorus (P), magnesium (Mg), calcium (Ca), iron (Fe), manganese (Mn), zinc (Zn), copper (Cu) and boron (B) were determined in raspberry leaves. Furthermore, the impact of select soil properties on the content of essential elements in the leaves was assessed. The results obtained revealed the suitable N, P, K, Mg, B, Zn and Cu supplies in the plants. However, the mean content of Mn greatly exceeded the optimal level recommended for this species. Also, the content of Fe in some regions was above the optimal value. The calculated correlation coefficients between soil properties and the content of the elements in raspberry leaves suggest that these variables were interdependent in only a few cases.
Finite Element Modeling of a Transient Functional Electrical Stimulation

Distribution of three-dimensional current and potential is very important for precise stimulation in functional electrical stimulation. Static models describe the effect of an amplitude change of the stimulation, but the result is the same for different pulse duration. We present the finite element model of a transient electrical stimulation on the upper arm. A standard Galerkin procedure was derived in order to obtain discrete finite element equations. Different tissue properties are defined by their conductive and dielectric properties. It is aimed to show that FE modeling of stimulation can give the spatial-temporal location and amplitude of the current to be dynamically configured. Two cases were modeled with the same geometry but with different input of the current pulse, electrode size, positions and tissue properties. The first model case was compared with experimental and numerical results form the literature. The second one was fitted to our own experimental investigations on a few volunteers. The fitting was performed on tissue parameters. Both cases have shown a strong effects of transient conditions and relative permittivity of the skin on the solutions. Our observation showed that dielectric tissue properties (permittivity) cannot be neglected and that the static approach in the electrical stimulation is not appropriate. Hence, the therapeutic strategy should take into account these effects during the functional electrical stimulation.