Miracle-dz/UniFAR-FTUs huggingface dataset:
ltrafast FRET at fiber tips : Potential applications in sensitive remote ensing of molecular interaction

Förster resonance energy transfer (FRET) strategy is well adopted in fiber-optics for efficient sensor design. However, resonance type energy transfer from one molecule (donor) to other (acceptor) should meet few key properties including donor to acceptor energy migration in non-radiative way, which is hard to conclude from simply emission quenching of the donor, rather needs careful investigation of excited state lifetime of the donor molecule. In the present study, we have shown that the evanescent field of an optical fiber can be coupled to covalently attached donor (dansyl) molecules at the fiber tip. By using picosecond resolved time correlated single photon counting (TCSPC) we have demonstrated that dansyl at the fiber tip transfers energy to a well known DNA-intercalating dye ethidium upon surface adsorption of DNA at the fiber tip. Our ultrafast detection scheme selectively distinguishes the probe (dansyl) emission from the intrinsic emission of the fiber. The validation of the energy transfer mechanism to be of resonance type (FRET), allows us to estimate the distance between the probe dansyl and the surface adsorbed DNA. ovalently sensitized fiber tip We have also used the setup for the remote sensing of the dielectric constant (polarity) of an environment as the excited state lifetime of the probe dansyl heavily depends on the polarity of the immediate host environment. FRET signal from a used fiber tip immediately after adsorption of DNA reveals stepwise surface desorption of the biomolecule in saline solution. The reusability of the fiber tip for sensing has also been demonstrated. © 2015 Elsevier B.V. All rights reserved.
Occurrence of multidrug-resistant Acinetobacter baumannii and Escherichia coli in veterinary healthcare facilities in Klang Valley, Malaysia

Multidrug-resistant organisms (MDROs) such as multidrug-resistant (MDR) Acinetobacter baumannii and Escherichia coli are important pathogens associated with nosocomial infections in both human and animal health care facilities. Surfaces of inanimate objects in health care facilities can serve as sources of infection. However, studies on prevalence of these pathogens in veterinary settings are lacking in the country. Therefore, the objectives of this study were to determine the occurrence of A. baumannii and E. coli and the occurrence of MDR isolates on surfaces of inanimate objects in veterinary health care facilities in Klang Valley, Malaysia. In this study, swab samples were taken from 65 surfaces of inanimate objects that included door knobs, examination tables, labcoats, stethoscopes and weighing scales. The swab samples were cultured and all isolates were subjected to antibiotic susceptibility test. The study revealed that the occurrence of A. baumannii was 9.23% and 5 out of 6 (83.33%) A. baumannii isolates were classified as MDR. However, no E. coli was isolated. In conclusion, surfaces of inanimate objects can be a source of MDR A. baumannii in veterinary health care facilities that is of animal and public health concern.
Difficult Intubation: Prospective observational study to evaluate it's key predictors

Introduction: Airway assessment to identify the predictors of difficult intubation (DI) during general anaesthesia is very important to maintain patient safety and prevent untoward events like hypoxia and brain damage. The aim of our study is to evaluate the occurrence of difficult tracheal intubation during general anaesthesia in elective surgeries and to find out the key predictors of difficult intubation. Materials and Method: A prospective study was conducted in 450 patients posted for elective general surgeries requiring general anaesthesia over a one year period. The screening tests for difficult intubation included the following: Mallampati classification (MPC), inter-incisor gap (IG), thyromental distance (TMD), subluxation of mandible (slux) and restricted neck movements (RNM). Risk factors assessed included obesity, neck circumference, short neck, buck teeth and poor dentition (loose / missing). Difficult intubation was defined when any one or more of these criteria were present: > 2 attempts at intubation; > 5-minutes duration of laryngoscopy; Cormack Lehane grade 3 or 4; use of intubating aids like McCoy laryngoscope and Frova (tracheal introducer). Multivariate analysis using a binary logistic regression was performed for the ten predictors. Predictive accuracy was assessed using sensitivity, specificity and positive predictive values. Result: Incidence of DI was 20.8%. It had strong correlation with MPC, RNM, TMD and poor dentition with an odds ratio of 9.2, 5.2, 4.8, and 2.58 respectively. TMD is most sensitive predictor (55.32%) and RNM is most specific predictor (97.2%). MPC, RNM, TMD are the key independent predictors of difficult intubation. Keywords: Predictor, Difficult intubation, Laryngoscopic view
Detection and mitigation of hypothetical bias in contingent valuation with an application to curbside recycling

In this paper, we use a unique curbside-recycling data set to test the effectiveness of “cheap talk” and “preference uncertainty” in mitigating hypothetical bias in contingent valuation. The sample includes two types of ouseholds—those located in communities with curbside recycling programs (mandatory or voluntary) and those in communities without curbside recycling. Using stated and revealed preference data, detect significant hypothetical bias. Cheap talk and preference-uncertainty controls are partially effective in mitigating the bias.
A Gamification Approach for Experiential Education of Inventory Control

In this educational research project, game-based in-class and after-class learning activities are developed to teach selected inventory control strategies to undergraduate and graduate students. Students from Supply Chain Management and System Simulation courses are targeted, who are taught by different instructors. The activities include teaching the inventory control policies to students in a regular class setting, then providing an overview on a game developed on MS Excel. In the game, the lead time and customer demand variables are defined uncertain, and not given to students, which make the assignment an ill-structured problem. A 12-month planning and execution period is given to students with qualitative and quantitative information about 3 products. The students are given a 1-week period to play the game. The game simulates selected inventory control strategies with reorder point and order quantity parameters for 12 months. The learning outcomes of the course related to inventory control, and students’ experience with the game are surveyed. Survey results are statistically and visually analyzed. Overall results indicated that the proposed gamification approach is found to have positive impact in learning effectiveness in the majority of evaluation categories. In addition, the contribution of the proposed gamification approach was found to be effectively supporting the learning outcomes of the course.
A compact model for flicker noise in MOS transistors for analog circuit design

Designers need accurate models to estimate 1/f noise in MOS transistors as a function of their size, bias point, and technology. Conventional models present limitations; they usually do not consistently represent the series-parallel associations of transistors and may not provide adequate results for all the operating regions, particularly moderate inversion. In this brief, we present a consistent, physics-based, one-equation-all-regions model for flicker noise developed with the aid of a one-equation-all-regions dc model of the MOS transistor.
Current Approaches for Enhanced Expression of Secondary Metabolites as Bioactive Compounds in Plants for Agronomic and Human Health Purposes – a Review

The study of secondary metabolism in plants is an important source for the discovery of bioactive compounds with a wide range of applications. Today these bioactive compounds derived from plants are important drugs such as antibiotics, and agrochemicals substitutes, they also have been economically important as flavors and fragrances, dyes and pigments, and food preservatives. Many of the drugs sold today are synthetic modifications of naturally obtained substances. There is no rigid scheme for classifying secondary metabolites, but they can be divided into different groups based on their chemical components, function and biosynthesis: terpenoids and steroids, fatty acid-derived substances and polyketides, alkaloids, phenolic compounds, non-ribosomal polypeptides and enzyme cofactors. The increasing commercial importance of these chemical compounds has resulted in a great interest in secondary metabolism, particularly the possibility of altering the production of bioactive plant metabolites by means of tissue culture technology and metabolomics. In today’s world the use of bioactive compounds derived from plants plays an important role in pharmaceutical applications. This review presents information about these metabolites and their applications as well as their importance in agronomy and bioactive effects on human health as nutraceuticals. This review includes also the new tendencies to produce these bioactive compounds under different stresses conditions such as biotic and abiotic stress that could be included in production systems.
EFFECTS OF RESYNCHRONIZATION ON FERTILITY & ECONOMICS

2012 Dairy Cattle Reproduction Conference 63 Sacramento, CA EFFECTS OF RESYNCHRONIZATION ON FERTILITY & ECONOMICS Todd R. Bilby, Ph.D.; Ricardo C. Chebel, D.V.M.; and Julio Giordano, Ph.D. Texas A&M AgriLife Research and Extension, Stephenville; Department of Veterinary Population Medicine, University of Minnesota, St. Paul; Department of Animal Science, Cornell University, Ithaca, NY Email: trbilby@ag.tamu. edu
Tree Clustering

This project investigates the methods for clustering of tree data structures. Clustering is an important method of unsupervised learning that allows to discover new properties and patterns within data. Tree clustering plays an important role for the scientific areas which use tree structures to describe observations, e.g. computational biology, structured text databases, natural language processing, web mining, image analysis and computer vision, pattern recognition as well as compiler optimisation [3,9,14,24]. This work illustrates the application of tree clustering on set of experimental observations of stem cell differentiation. The main contribution of this work is the development of the methods for finding mean trees in a set of unordered labelled trees. The traditional methods, i.e. calculation of median graph [11], are not as flexible in the terms of using different similarity metrics, as well as would lead to infeasible centroid trees. To the best of our knowledge this project presents the first study of this approach. The related works for different algorithms used in the project are reviewed in the corresponding sections. The remain of this script starts with the description of different methods to establish a distance between two tree structures in Section 2. This allows to define a metric on a tree space, which is necessary for the correctness of centroid search and clustering algorithms discussed in Sections 3 and 4. The experimental part of this script in Section 7 begins with evaluation of different metrics and clustering algorithms using artificial data, following by application on the real-world data of biological experiments. The running time evaluation of algorithms used in this project as well as some methods for optimisation and parallelisation are discussed in Section 8. The last section of this script summarises the results and gives an overview of possible topics for further research.
Tissue Doppler in Ischemic Heart Disease

Tissue Doppler Echocardiography was introduced in the 1960s (Yoshida et al., 1961), and enabled the quantitative assessment of myocardial motion and deformation. The wide use of tissue Doppler as a research tool halted, however, until the early 1990s (Hatle & Sutherland, 2000). Tissue Doppler is now available for high frame rates, wide sector angles and in combination with 2-dimiensional data acquisition. Although widely used in cardiovascular research, the clinical use is limited, probably due to the time consumption associated with special imaging protocols and tedious post processing. Nevertheless, tissue Doppler echocardiography has contributed to most of the available knowledge on the pathophysiology involved in myocardial contraction deficiency. The experienced cardiologist can easily identify large myocardial infarcts by visual analysis of echocardiograms, but identification of a small MI may be challenging due to the modest changes in tissue properties. In ischemic tissue, the contractility is reduced and reduced deformation and deformation rate is observed. Due to differences in contractility among ischemic and adjacent healthy myocardium, the ischemic myocardium has a characteristic deformation pattern with stretch in early systole, reduced systolic shortening, and a delayed (postsystolic) shortening when the ventricular pressure decays. This early stretch and post systolic shortening pattern has been described both experimentally (Edvardsen, T. et al., 2002; Skulstad et al., 2002) and clinically (Gjesdal et al., 2008; Jamal et al., 1999; Voigt et al., 2004).
Preliminary phytochemical and antimicrobial evaluations of the methanolic leaf extract of Ochna kibbiensis Hutz and Dalz ( Ochnaceae )

The antimicrobial effect of the crude methanol leaf xtract of Ochna kibbiensis obtained through macer tion technique was evaluated against pathogenic microorg anisms which include Staphylococcus aureus, Methici llin Resistant Staphylococcus aureus (MRSA), Vancomycin Resistant Enterococci, Listeria monocytogenes, Heli cobacter pylori, Campylobacter fetus, Proteus vulgaris, Pseu domonas flourescens, Candida tropicalis and Candida stellatoidea. Agar Disc diffusion and Nutrient Brot h dilution techniques were employed. Susceptibility test results showed that the extract (400μg) inhibited the growt h of all the test organisms (bacteria and fungi) wi th a mean zone of inhibition range of 18-27mm, with the exception of Methicillin Resistant Staphylococcus aureus, Hel icobacter pylori and Pseudomonas flourescens. The standard an tibacterial drug, Sparfloxacin (5ug/ml) had inhibit ory activity against all the organisms except H. pylori, P. flou rescens, C. tropicalis and C. stellatoidea while Fl uconazole, the standard anti-fungal drug showed activity only on t he wo fungi species tested C. tropicalis and C. st ellatoidea. The Minimum Inhibitory Concentration (MIC) and the Mini mum Bactericidal/Fungicidal Concentration (MBC) ran ge for the extract was 5-20mg/ml and 10-40mg/ml, respe ctiv ly. Preliminary phytochemical screening reveal ed the presence of flavonoids, steroids/terpenes, saponins , glycosides and alkaloids in the extract. The resu lts of this study suggest that the leaves extract of the plant O. kib biensis contains bioactive constituent(s) with good antibacterial and antifungal activity and, lends credence to its folkloric use in wound healing and other microbial infections.
Extrema based unwarping for time-varying pitch estimation

We present an extrema based unwarping technique for signals with time-varying periodicity. We show that for arbitrary variation of pitch periodicity in speech signal,the unwarping technique maps the signals to periodic signals which enable eficient estimation of periodicity. We demonstrate the e�ectiveness of the new technique using both synthetic and real speech signals.
Querying Key-Value Stores Under Simple Semantic Constraints : Rewriting and Parallelization

We propose to demonstrate a system for accessing Key-Value stores in the presence of semantic constraints, as considered in the setting of ontology-mediated query answering. The constraints we study are expressed in a native rule language for JSON records and their purpose is to establish a high level view over a collection of legacy and possibly heterogenous Key-Value stores. To ensure correct and complete data access, constraints are taken into account via query rewriting techniques tailored for MongoDB queries. The nature of queries and constraints also enable the deployment of parallelization techniques for optimizing query rewriting and therefore the whole data access task. During the demonstration, attendees will first be able to query JSON datasets in the presence of rules thereby illustrating how semantic constraints bring novel and pertinent answers to queries. Then, it will be possible to make a detailed analysis of query rewriting and compare the parallel version of the reformulation algorithm with the baseline centralized one.
Does nonlinear econometrics confirm the macroeconomic models of consumption

This article aims at checking whether the macroeconomic models of consumption are always verified to reproduce the dynamics of consumption habits. We show that even if the Keynesian theory of consumption is still checked as the disposable income is a significant explanatory variable of household consumption, the dynamics of consumption cannot be reproduced anymore through the Post-Keynesian models like that of Brown (1952). While introducing nonlinearity and using the recent developments of Smooth Transition Regression (STR) models, we propose an extension for Brown's model and develop a Nonlinear Macroeconometric Model of Consumption (NMMC). Nonlinearity is justified by the structural breaks induced by habit formation and the irregularity in the evolution of the saving ratio since the seventies. Based on American and French data, our empirical results show that our model is statistically appropriate and leads to better performance than the usual macroeconomic specification of Brown.
Soil organic carbon sequestration rates by tillage and crop rotation : A global data analysis

Changes in agricultural management can potentially increase the accumulation rate of soil organic C (SOC), thereby sequestering CO 2 from the atmosphere. This study was conducted to quantify potential soil C sequestration rates for different crops in response to decreasing tillage intensity or enhancing rotation complexity, and to estimate the duration of time over which sequestration may occur. Analyses of C sequestration rates were completed using a global database of 67 long-term agricultural experiments, consisting of 276 paired treatments. Results indicate, on average, that a change from conventional tillage (CT) to no-till (NT) can sequester 57 ± 14 g C m -2 yr -1 , excluding wheat (Triticum aestivum L.)-fallow systems which may not result in SOC accumulation with a change from CT to NT. Enhancing rotation complexity can sequester an average 20 ± 12 g C m -2 yr -1 , excluding a change from continuous corn (Zea mays L.) to corn-soybean (Glycine max L.) which may not result in a significant accumulation of SOC. Carbon sequestration rates, with a change from CT to NT, can be expected to peak in 5 to 10 yr with SOC reaching a new equilibrium in 15 to 20 yr. Following initiation of an enhancement in rotation complexity, SOC may reach a new equilibrium in approximately 40 to 60 yr. Carbon sequestration rates, estimated for a number of individual crops and crop rotations in this study, can be used in spatial modeling analyses to more accurately predict regional, national, and global C sequestration potentials.
Development, Optimization, and Twisted Adjustment of an Axial Flow Blood Pump for Fontan Patients

xiii Chapter 1 SIGNIFICANCE AND OBJECTIVES . 1 1.1 Single Ventricle Physiology.1 1.1.1 Therapeutic Option: Cavopulmonary Assist Devise . 6 1.2 Project Objectives.8 2 MATERIALS AND METHODS: DESIGN AND NUMERICAL SIMULATIONS.10 2.1.1 Standard Pump Design Equations . 11 2.1.2 Hemolysis and Thrombosis.12 2.1. 3 Design Specifications and Characteristics.12 2.2 Computational Fluid Dynamics: ANSYS CFX.14 2.2.1 BladeGen . 15 2.2.2 TurboGrid: Mesh Generator . 16
Developing a Computer Assisted Summary Writing Learning Model

 Abstract —Summary writing is a process of producing a more concise text through the process of selecting important information and deleting supporting and explanatory details from the source text. A good summary does not only depend on students ability to comprehend the source text, but also able to relate their prior knowledge in the process. Besides that, summarizing strategies are also crucial in summary writing. From a study conducted on Malaysian undergraduate students, it was found that majority of them were unable to write a good summary due to lack of prior knowledge and functional knowledge of summarizing strategies. This indicates that prior knowledge and summarizing strategies are important in summary writing. The aim of this research is to develop a summary writing learning model that incorporates prior knowledge, summarizing strategies and learning theories to enhance students’ ability to produce a good summary. The proposed Summary Writing Learning (SWL) model consists of three main components; Prior Knowledge Activation (PKA), Summarizing Strategies Learning (SSL), and Summarizing (SZ). An advanced organizer is used to activate students’ prior knowledge in PKA to comprehend the new text. The worked example instructional approach is used to instruct students in SSL. Moreover, a feedback sub-component is proposed in SZ to provide feedback to students on their summary strategies identification. The proposed SWL model will be a valuable contribution to educational technology specifically in summary writing.
Insights into capacity loss mechanisms of all-solid-state Li-ion batteries with Al anodes

The atomistic mechanism for lithiation/delithiation in all-solid-state batteries is still an open question, and the ‘holy grail’ to engineer devices with extended lifetime. Here, by combining real-time scanning electron microscopy in ultra-high vacuum with electrochemical cycling, we quantify the dynamic degradation of Al anodes in Li-ion all-solid-state batteries, a promising alternative for ultra lightweight devices. We find that AlLi alloy mounds are formed on the top surface of the Al anode and that degradation of battery capacity occurs because of Li trapped in them. Our approach establishes a new platform for probing the real-time degradation of electrodes, and can be expanded to other complex systems, allowing for high throughput characterization of batteries with nanoscale resolution.
Trade-off Study on Switched Capacitor Regulators for Implantable Medical Devices

This study presents the trade-offs when using a Switched capacitor (SC) DC-DC converter as the energy management device on a highly integrated implantable medical device. The efficiency of the Low Dropout Regulator (LDO) is presented and used as a reference point to determine the performance gain when using an SC converter. Also, the balance between load requirements and optimum parameters for implementing an SC converter is analyzed. The analysis presented can be used to determine when an SC converter is the best solution for energy management on an implantable device.