Miracle-dz/UniFAR-FTUs huggingface dataset:
Turkish folk medicinal plants, X: Ürgüp (Nevşehir)

Bu calisma Urgup (Nevsehir) yoresinde geleneksel olarak kullanilan halk ilaci bitkilerini belirlemek amaciyla yapilmistir. Arastirma esnasinda yoredeki toplam 24 yerlesim merkezinin (20 koy dahil) hepsine gidilmis ve Haziran 2009-Haziran 2010 tarihleri arasinda mayis, haziran ve temmuz aylarinda toplam 32 gun suren arazi calismalari yapilmistir. Halk ilaci olarak kullanilan bitkilerden ornekler toplanmis ve bu bitkilerin yoresel adlari, yararlanilan kisimlari, tedavi edici etkileri, bitkisel halk ilaclari ile tedavi edilen hastaliklar ve saglik sorunlari, ilacin hazirlanis ve uygulanis yontemi, dozu, uygulama suresi hakkinda bilgiler derlenmistir. Toplanan bu ornekler Marmara Universitesi Eczacilik Fakultesi Herbaryumu’ nda (MARE) bulunmaktadir. 116 bitki orneginin teshisi sonucunda 67 turden geleneksel halk ilaci olarak yararlanildigi saptanmistir. Bunlardan da 52’ si yabani, 15’ i ise kultur bitkisidir. Bu bitkiler ve bunlarin tedavideki kullanilislari metin icinde tablo halinde sunulmustur. Urgup yoresinde kaydedilen bitkilerden en cok seker hastaligi, kalp-damar hastaliklari, oksuruk, yara, astim, mide hastaliklari ve yuksek kolesterol tedavisinde yararlanilmaktadir.
ExtensionSticker: A Proposal for a Striped Pattern Sticker to Extend Touch Interfaces and its Assessment

In this study, we propose a striped pattern sticker called ExtensionSticker that allows a touch input to be transferred from an external source by simply attaching the sticker to a touch panel. This allows the user to input touches or continuous scrolling actions by touching a sticker printed with stripes of conductive ink, without directly touching the touch panel. This method could be applied to the sides or back of a touch panel, or even the surface upon which a device is located as a touch interface, allowing us to freely construct interfaces in shapes matching the demands of the user. This paper also reports the results of evaluation experiments conducted to assess the recognition accuracy of scroll and tap actions using the proposed method.
Evaluation of salivary gland scintigraphy, magnetic resonance and diffusion-weighted imaging in clinical diagnosis of Sjgrens Syndrome

To assess diagnostic effectiveness of Sjogren’s syndrome (SS), salivary gland scintigraphy (SGS), magnetic resonance (MR) and diffusion-weighted imaging (DWI) were performed in 54 patients (primary SS, secondary SS and connective tissue disease (CTD) but without SS). Results showed that SGS and diffusion-weighted magnetic resonance imaging (MRI) provided high-resolution images of the parotid glands that enabled apparent diffusion coefficient (ADC) measurements. After overall analysis, all of the oral activity indices, the maximum accumulation (MA) and uptake rate (UR) of the parotid gland clearly decreased asclinical severity progressed, and statistically significant differences were observed. Our technique may prove helpful in diagnosing the progression of SS beyond its early stages. Key words: Diffusion-weighted imaging, salivary gland scintigraphy, Sjogren’s syndrome, receiver operating characteristic curve.
Purification and Characterization of A Novel Chitinase Isozyme from Yam Tuber.

A new chitinase isozyme (Chitinase A), which had only one optimum pH toward a long substrate, glycolchitin, was purified from the peel of yam tuber by CTAB (hexadecyl trimethyl ammonium bromide) treatment and ammonium sulfate fractionation, followed by column chromatography on DEAE-Cellulofine A-500, chromatofocusing, and gel filtration on Sephacryl S-100. The molecular weight was 28,000 by SDS-PAGE. The isoelectric point was 3.6. The optimum pH was 4.0 toward both a polymer substrate, glycolchitin, and an oligosaccharide substrate, GlcNAc5. The optimum temperature was 60°C. Chitinase A was stable between pH 6 and 11 and below 45°C. Kinetic analysis was done using a series of N-acetylchitooligosaccharides (GlcNAcn, n=2 to 6) and glycolchitin as the substrates. Chitinase A hydrolyzed N-acetylchitooligosaccharides in an endo/random fashion except the disaccharide, and released the monosaccharide from all hydrolyzed oligosaccharides. This enzyme preferred oligosaccharides with the longer chain lengths. Chitinase A was inhibited 76% by 55 μM allosamidin, which is known to be a specific inhibitor of insect chitinases.
SMiLer: A Semi-Lazy Time Series Prediction System for Sensors

It is useful to predict future values in time series data, for example when there are many sensors monitoring environments such as urban space. The Gaussian Process (GP) model is considered as a promising technique for this setting. However, the GP model requires too high a training cost to be tractable for large data. Though approximation methods have been proposed to improve GP's scalability, they usually can only capture global trends in the data and fail to preserve small-scale patterns, resulting in unsatisfactory performance. We propose a new method to apply the GP for sensor time series prediction. Instead of (eagerly) training GPs on entire datasets, we custom-build query-dependent GPs on small fractions of the data for each prediction request. Implementing this idea in practice at scale requires us to overcome two obstacles. On the one hand, a central challenge with such a semi-lazy learning model is the substantial model-building effort at kNN query time, which could lead to unacceptable latency. We propose a novel two-level inverted-like index to support kNN search using the DTW on the GPU, making such "just-in-time" query-dependent model construction feasible for real-time applications. On the other hand, several parameters should be tuned for each time series individually since different sensors have different data generating processes in diverse environments. Manually configuring the parameters is usually not feasible due to the large number of sensors. To address this, we devise an adaptive auto-tuning mechanism to automatically determine and dynamically adjust the parameters for each time series with little human assistance. Our method has the following strong points: (a) it can make prediction in real time without a training phase; (b) it can yield superior prediction accuracy; and (c) it can effectively estimate the analytical predictive uncertainty. To illustrate our points, we present SMiLer, a semi-lazy time series prediction system for sensors. Extensive experiments on real-world datasets demonstrate its effectiveness and efficiency. In particular, by devising a two-level inverted-like index on the GPU with an enhanced lower bound of the DTW, SMiLer accelerates the efficiency of kNN search by one order of magnitude over its baselines. The prediction accuracy of SMiLer is better than the state-of-the-art competitors (up to 10 competitors) with better estimation of predictive uncertainty.
An exploration of human immunodeficiency virus (HIV) knowledge gaps among male migrant workers in Singapore

The general objective of this study is to provide a rapid assessment of HIV knowledge gaps among male migrant workers (MMWs) in Singapore. A cross-sectional pilot study was conducted in June 2011, in Singapore. A 14 multiple choice closed question self-administered questionnaire was used to collect information on current HIV knowledge among MMWs. Sixty seven MMWs participated in the survey and a total of 58 valid questionnaires were collected. Findings are reported by grouping survey responses of current knowledge of HIV. Although 84.5% of respondents have an awareness of HIV/AIDS, participants generally scored poorly in the survey and beliefs about the causes of HIV and HIV prevention strategies. 30.7% of those surveyed responded correctly to questions on HIV/AIDS knowledge, whilst 31.7% responded incorrectly and 37.7% of participants were unsure how to respond. The results indicate that there are significant HIV/AIDS knowledge gaps among male migrant workers in Singapore. We recommend that further research is required which could lead to the development of culturally appropriate peer-based HIV prevention programs, which should aim at both equipping this vulnerable group of individuals with necessary knowledge about HIV/AIDS and correcting misconceptions and misunderstandings. Key words: Male migrant workers, HIV knowledge, self-administered questionnaire.
Influenza virus-like particle vaccines

Enveloped virus-like particle (VLP) vaccines containing influenza hemagglutinin (HA) and neuraminidase (NA) antigens are produced easily in insect or mammalian cells via the simultaneous expression of HA and NA along with a viral core protein, such as influenza matrix (M1) or a retroviral Gag protein. The size and shape of the resulting particles are dictated by the choice of the core component, but M1- and Gag-based VLPs are strongly immunogenic and protective in seasonal and highly pathogenic influenza challenge models. Current data are consistent with the hypothesis that influenza VLP vaccine efficacy is related to the particulate, multivalent composition coupled with the presence of correctly folded antigens with intact biological activities. This new influenza vaccine paradigm offers potential advantages over the conventional egg-based, split-vaccine platform in terms of enhanced immunogenicity and better breadth of protection.
Partition Crossover for Pseudo-Boolean Optimization

A partition crossover operator is introduced for use with NK landscapes, MAX-kSAT and for all k-bounded pseudo-Boolean functions. By definition, these problems use a bit representation. Under partition crossover, the evaluation of offspring can be directly obtained from partial evaluations of substrings found in the parents. Partition crossover explores the variable interaction graph of the pseudo-Boolean functions in order to partition the variables of the solution vector. Proofs are presented showing that if the differing variable assignments found in the two parents can be partitioned into q non-interacting sets, partition crossover can be used to find the best of 2q possible offspring. Proofs are presented which show that parents that are locally optimal will always generate offspring that are locally optimal with respect to a (more restricted) hyperplane subspace. Empirical experiments show that parents that are locally optimal generate offspring that are locally optimal in the full search space more than 80 percent of the time. Experimental results also show the effectiveness of the proposed crossover when used in combination with a hybrid genetic algorithm.
Misbehavior in Bitcoin: A Study of Double-Spending and Accountability

Bitcoin is a decentralized payment system that relies on Proof-of-Work (PoW) to resist double-spending through a distributed timestamping service. To ensure the operation and security of Bitcoin, it is essential that all transactions and their order of execution are available to all Bitcoin users. Unavoidably, in such a setting, the security of transactions comes at odds with transaction privacy. Motivated by the fact that transaction confirmation in Bitcoin requires tens of minutes, we analyze the conditions for performing successful double-spending attacks against fast payments in Bitcoin, where the time between the exchange of currency and goods is short (in the order of a minute). We show that unless new detection techniques are integrated in the Bitcoin implementation, double-spending attacks on fast payments succeed with considerable probability and can be mounted at low cost. We propose a new and lightweight countermeasure that enables the detection of double-spending attacks in fast transactions. In light of such misbehavior, accountability becomes crucial. We show that in the specific case of Bitcoin, accountability complements privacy. To illustrate this tension, we provide accountability and privacy definition for Bitcoin, and we investigate analytically and empirically the privacy and accountability provisions in Bitcoin.
Creating a virtual "global community of learners" in radiation medicine through sound educational principles †

The International Atomic Energy Agency (IAEA), comprising 154 Member States, is an internationally recognised repository of knowledge in the radiation medicine domain (nuclear medicine, diagnostic radiology, radiation oncology, and medical radiation physics), as delivered through its Department of Nuclear Sciences and Applications-Division of Human Health (NAHU). This paper discusses the goal and implementation strategy adopted by NAHU towards realising its educational vision, namely, to create a virtual global community of learners for radiation medicine professionals in IAEA’s Member States. The virtual community refers to a distance learning platform and resource made available to the IAEA’s Member States. Since 2008, NAHU has been explicitly integrating sound educational principles into the Division’s education and training programmes to accomplish this educational vision. To translate the above educational vision into action, content, process, and information technology experts at NAHU have been involved in a collective effort to progressively focus on developing strategies for “ref lective practice” by employing educational processes based on a continuous quality improvement philosophy: Plan-Do-Check-Act. This paper describes an ongoing effort in this direction, which entails several developmental stages utilising a set of awareness-raising and internally planned capacity building activities. NAHU functions as a “learning organisation” that encourages a collaborative learning environment. NAHU also emphasises the development of ref lective practice, critical thinking, and knowledge building through a virtual learning environment. By incorporating the practices of a learning organisation, this transformative strategy can prepare NAHU’s professional staff to build capacity in radiation medicine across the globe with the aim of minimising the gap in radiation medicine between the developed and developing countries.
Development and application of ‘phosphoflow’ as a tool for immunomonitoring

Flow cytometry has revolutionized our ability to monitor immune responses by allowing us to simultaneously track a variety of cell surface and intracellular markers in discrete cell subsets in a highly sensitive and reproducible manner. This is especially critical in this new era of vaccinology trying to tackle the growing problems of chronic viral infections and cancer that not only evade host immune responses, but can negatively manipulate vaccine-induced immune responses. Thus, understanding how lymphocyte signaling is altered under normal and pathological conditions has become more critical. Over the last decade, a new flow cytometry technology called ‘phosphoflow’ (also sometimes called ‘phosflow’), is rapidly developing for tracking multiple intracellular signaling molecules in the immune system at a single-cell level. Antibodies and reagents for tracking both tyrosine-phosphorylated and serine/threonine-phosphorylated signaling intermediaries in key immune signaling pathways have been developed, and phosphoflow is now starting to be applied to a wide variety of both preclinical and clinical studies on lymphocyte responses, as well as the functioning of cancer cells and virally infected cells. Here, we review the development of phosphoflow technology, its modern applications in the field of immunomonitoring and its current limitations. We then provide a perspective on the future of phosphoflow and a vision of how it can be applied to emerging critical questions in human vaccinology and public health.
Explaining Risk Attitude in Framing Tasks by Regulatory Focus: A Verbal Protocol Analysis and a Simulation Using Fuzzy Logic

We investigate the role of salient regulatory focus for risk attitude in framed gambles. In Experiment 1 we measured regulatory focus by collecting verbal protocols and found that people avoided risk under prevention focus and preferred risk under promotion focus. In Experiment 2 the same result was found when measuring people's regulatory focus with a questionnaire. Finally, the questionnaire data were used as inputs for simulating the choices of our participants by a fuzzy-logic decision generator. The findings show that regulatory focus has a strong effect on risk attitude and that risk attitude in framing tasks can be successfully modeled as some form of fuzzy processing.
Phasor Imaging

In correlation-based time-of-flight (C-ToF) imaging systems, light sources with temporally varying intensities illuminate the scene. Due to global illumination, the temporally varying radiance received at the sensor is a combination of light received along multiple paths. Recovering scene properties (e.g., scene depths) from the received radiance requires separating these contributions, which is challenging due to the complexity of global illumination and the additional temporal dimension of the radiance. We propose phasor imaging, a framework for performing fast inverse light transport analysis using C-ToF sensors. Phasor imaging is based on the idea that, by representing light transport quantities as phasors and light transport events as phasor transformations, light transport analysis can be simplified in the temporal frequency domain. We study the effect of temporal illumination frequencies on light transport and show that, for a broad range of scenes, global radiance (inter-reflections and volumetric scattering) vanishes for frequencies higher than a scene-dependent threshold. We use this observation for developing two novel scene recovery techniques. First, we present micro-ToF imaging, a ToF-based shape recovery technique that is robust to errors due to inter-reflections (multipath interference) and volumetric scattering. Second, we present a technique for separating the direct and global components of radiance. Both techniques require capturing as few as 3--4 images and minimal computations. We demonstrate the validity of the presented techniques via simulations and experiments performed with our hardware prototype.
The practitioner’s experience and conception of evidence based library and information practice: an exploratory analysis

Purpose: This paper presents a study that explores the way in which library and information science (LIS) practitioner’s experience and conceive evidence based library and information practice (EBLIP). Design: Semi-structured interviews were used for data collection. The interviews were designed and conducted using the phenomenographic approach. Phenomenography is an interpretive research approach that looks at the different ways people experience or conceive a range of phenomenon. The intent of phenomenographic research is to understand variation in the collective experience of a group or community in regards a particular phenomenon. Six participants took part in a 30-60 minute audio recorded interview. The goal of each interview was to understand the variation in each participant’s experience of EBLIP. Findings: The results suggest that LIS professionals have four different ways of experiencing evidence based practice. The four different ways or categories are (i) EBLIP is not relevant; (ii) EBLIP is learning from experience; (ii) EBLIP is service improvement; and (iv) EBLIP is all consuming. It should be noted that this framework is fluid and will evolve as the research project continues. Value: The study is significant because it provides the first model or rich description of EBLIP as understood by the library and information practitioner. This model can assist library educators, associations and others involved in supporting and preparing current and future evidence based professionals, so that an evidence based culture can be firmly established within the profession.
Effect of rosuvastatin as adjuvant therapy to methotrexate on hematological parameters in patients with moderately-highly active rheumatoid arthritis

Objective: Rheumatoid arthritis (RA) is a common inflammatory disease associated with many extra-articular features including anemia, leucocytosis and thrombocytosis. Rosuvastatin is an antidyslipidemic agent with anti-inflammatory activity. The aim of the study was to evaluate the effect of rosuvastation as adjuvant therapy to methotrexate on hematological parameters in Iraqi patients with moderately-highly active RA. Methods: A single center randomized double-blind placebo-controlled trial of 8 weeks duration was performed. Disease activity was measured via calculating the disease activity score in 28 joints using erythrocyte sedimentation rate (DAS28-ESR). 40 Patients who were using methotrexate (MTX) intramuscularly were randomly allocated to receive each day either rosuvastatin 10 mg tablet or capsules prefilled with glucose as placebo and were evaluated at baseline and at week 8 for hematological parameters. Results: Erythrocyte sedimentation rate (ESR) and platelet count were significantly more reduced in rosuvastatin group than placebo group after 8weeks. Non signiﬁcant changes were observed in the hemoglobin (Hb) amount and white blood cells (WBC) count between groups. No significant correlation was recorded between ESR and Hb in both groups. Conclusion: Low dose rosuvastatin adjuvant to MTX seem to be an effective method to lower ESR and platelet count in rheumatoid arthritis patients.
Extended Differential Grouping for Large Scale Global Optimization with Direct and Indirect Variable Interactions

Cooperative co-evolution is a framework that can be used to effectively solve large scale optimization problems. This approach employs a divide and conquer strategy, which decomposes the problem into sub-components that are optimized separately. However, solution quality relies heavily on the decomposition method used. Ideally, the interacting decision variables should be assigned to the same sub-component and the interdependency between sub-components should be kept to a minimum. Differential grouping, a recently proposed method, has high decomposition accuracy across a suite of benchmark functions. However, we show that differential grouping can only identify decision variables that interact directly. Subsequently, we propose an extension of differential grouping that is able to correctly identify decision variables that also interact indirectly. Empirical studies show that our extended differential grouping method achieves perfect decomposition on all of the benchmark functions investigated. Significantly, when our decomposition method is embedded in the cooperative co-evolution framework, it achieves comparable or better solution quality than the differential grouping method.
Individual Variability in Benefit from Fixed and Adaptive Directional Microphones

Abstract This study aimed to document improvements in speech recognition when listening through fixed or adaptive directional microphone arrays relative to listening through omnidirectional microphone arrays in a variety of near-field noise conditions. Twelve participants with mild to severe hearing loss were recruited. Data were analyzed in a manner to facilitate discussion of both group and individual performance. The activation of directional microphones significantly improved speech recognition in all listening conditions when compared to omnidirectional listening conditions. Significant differences in speech recognition performance were not observed between fixed and adaptive directional microphone conditions. Analysis of individual outcomes shows a wide range of both absolute speech recognition scores and directional benefit across treatment conditions.