Miracle-dz/UniFAR-FTUs huggingface dataset:
Unusual stability of the Methanospirillum hungatei sheath

The proteinaceous sheath of Methanospirillum hungatei was isolated by lysing cells in 50 mM dithiothreitol, separating the sheath from other cellular material by discontinuous sucrose density centrifugation, and removing the "cell spacers" with dilute NaOH. The isolated sheath material consisted of hollow tubes which had a highly ordered surface array. The stability of the sheath to treatment with denaturants and to enzymatic digestion was examined by a turbidimetric assay in conjunction with electron microscopy and optical or electron diffraction. The sheath was resistant to a range of proteases and also was not digested by peptidoglycan-degrading enzymes, a lipase, a cellulase, a glucosidase, or Rhozyme (a mixture of galactosidases, acetylglucosaminidase, acetylgalactosaminidase, fucosidase, and mannosidases). In addition to being unaffected by common salts, thiol-reducing agents, and EDTA, the layer was resistant to powerful denaturants such as 6 M urea, 6 M guanidinium hydrochloride, 10 M LiSCN, cyanogen bromide, sodium periodate, and 1% sodium dodecyl sulfate. Strong bases, boiling 3 N HCl, and performic acid did attack the sheath; in these cases, the array was systematically disassembled in a progressive manner, which was followed by electron microscopy. The layer was slightly modified by N-bromosuccinimide in urea, but the array remained intact. The stability of the sheath was remarkable, not only as compared to other bacterial surface arrays, but also as compared to proteins generally, and possibly indicated the presence of covalent cross-links between protein subunits.
Evaluation of hotel quality attribute importance through fuzzy correlation coefficient

AbstractAn indirect method of calculation of the importance of attributes as the fuzzy correlation between the performance of attributes and the overall satisfaction was proposed in a recent paper. We apply the method to the results of a survey with respect to the quality of hotel services in Oradea (Romania). Different representations of the answers as triangular fuzzy numbers, as well as distinct analyzes to compare the hierarchies of the attributes with respect to the experience with the hotel and the motivation of the travel are considered.
The Contribution of Carbon and Water in Modulating Wood Formation in Black Spruce Saplings1

During wood formation, water availability is the most important factor for cell production, while carbon is more important to sustain the differentiation of living cells. Nonstructural carbohydrates (NSCs) play a crucial role in xylem formation and represent, with water, the main constraint to plant growth. We assessed the relationships between xylogenesis and NSCs in order to (1) verify the variance explained by NSCs and (2) determine the influence of intrinsic (tissue supplying carbon) and extrinsic (water availability and temperature) factors. During 2 years, wood formation was monitored in saplings of black spruce (Picea mariana) subjected to a dry period of about 1 month in June and exposed to different temperature treatments in a greenhouse. In parallel, NSC concentrations were determined by extracting the sugar compounds from two tissues (cambium and inner xylem), both potentially supplying carbon for wood formation. A mixed-effect model was used to assess and quantify the potential relationships. Total xylem cells, illustrating meristematic activity, were modeled as a function of water, sucrose, and d-pinitol (conditional r2 of 0.79). Water availability was ranked as the most important factor explaining total xylem cell production, while the contribution of carbon was lower. Cambium stopped dividing under water deficit, probably to limit the number of cells remaining in differentiation without an adequate amount of water. By contrast, carbon factors were ranked as most important in explaining the variation in living cells (conditional r2 of 0.49), highlighting the functional needs during xylem development, followed by the tissue supplying the NSCs (cambium) and water availability. This study precisely demonstrates the role of carbon and water in structural growth expressed as meristematic activity and tissue formation.
Measuring School Effectiveness in Memphis

New Leaders for New Schools, a nonprofit organization committed to training school principals, is heading an initiative that offers financial awards to effective educators. This report details the value-added model Mathematica developed to identify effective schools in the Memphis City school district during the first year of the project. The model estimates each schoolâ€™s effect on student performance across all tested grades and subjects, accounting for student mobility, observable differences in student demographics, and measurement error in test scores.
The Development and Diffusion of Business Incubation Capabilities in Five Emerging Markets in South America

Business incubation encourages new business formation and offers the potential to improve emerging market economies. Business incubation is a system of routines for creating and improving survival rates and growth of new businesses. Incubation originated in developed economies and is now spreading globally to emerging markets. Incubators are designed to reduce start-up costs and train entrepreneurs in business practices while connecting them to markets and assisting in securing financial backing for the new ventures. For this qualitative study I interviewed managers from business incubators, government agencies, nongovernmental organizations and entrepreneurship educators from Peru, Bolivia, Chile, Argentina, and Brazil. This study integrates incubation practices in these five countries with organizational learning and diffusion of innovation theories to propose a model of stages of development for incubation practices in emerging markets. The model describes how national systems of business incubation develop and differentiate due to unique cultural, political, and economic contexts.
Modulation Filter Learning Using Deep Variational Networks for Robust Speech Recognition

The performance of a typical speech recognition system is degraded in the presence of extrinsic sources like noise and due to the recording artifacts like reverberation. The principle of modulation filtering attempts to remove the spectro-temporal modulations of the speech signal that are more susceptible to noise while preserving the key modulations for speech recognition. While traditional approaches use modulation filters that are hand-crafted, we propose a novel method for modulation filter learning using deep variational models in this paper. Specifically, we pose the filter learning problem in a deep unsupervised generative modeling framework where the convolutional filters in the variational autoencoder capture the important speech modulations. The two-dimensional modulation filters, learned using the deep variational networks in the joint spectro-temporal domain, are used to process the spectrogram features for speech recognition task. Several speech recognition experiments are performed on a set of tasks consisting of additive noise with channel artifacts (Aurora-4), reverberation (REVERB Challenge), and additive noise with reverberation (CHiME-3). In these experiments, the proposed modulation filter learning framework shows significant improvements over the baseline features as well as various other noise robust front-ends (average relative improvements of 7.5% and 20% over the baseline features on the Aurora-4 and CHiME-3 databases respectively). Furthermore, the proposed method is also shown to be of considerable benefit for semi-supervised automatic speech recognition applications. For example, on Aurora-4 database we observe an average relative improvement of 25% over the baseline system using 30% labeled training data.
Mandibular implant-supported overdentures: attachment systems, and number and locations of implants--Part II.

The use of dental implants in replacing missing teeth is an integral part of restorative dental treatment. Use of conventional complete dentures is associated with several problems such as lack of denture stability, support and retention. However, when mandibular complete dentures were used with two or more implants, an improvement in the patients' psychological and social well-being could be seen. There is general consensus that removable implant-supported overdentures (RISOs) with two implants should be considered as the first-choice standard of care for an edentulous mandible. This treatment option necessitates the use of attachment systems that connect the complete denture to the implant. Nevertheless, each attachment system has its inherent advantages and disadvantages, which should be considered when choosing a system. The first part of this article provides an overview on options available to restore the mandibular edentulous arch with dental implants. Different types of attachment systems, their features and drawbacks are also reviewed.
A Geometrical Representation of Balance of Payments Policy

IN my paper on "National Income, National Expenditure and the Balance of Payments " in the Economic Journal for December, 1948, and March, 1949, I attempted to show algebraically certain " multiplier" relationships between Income, Expenditure, Imports and Exports on the assumption that all prices were constant. In this paper' I intend to use the geometric technique to introduce certain changes in price relationships into the general structure used in my Economic Journal paper. But this technique will be used in this paper for the sole and limited purpose of comparing Exchange Rate variation and Commercial Policy (e.g., Import Restrictions or. Export Subsidies) as a means of removing an existing balance of payments disequilibrium between two countries both of which, in the terminology of my Economic Journal paper, are adopting policies for Internal Balance. We assume (i) that there are only two countries A and B, of which one may, of course, represent the rest of the world; (ii) that A produces only one product which we will call Wheat, and B only one product which we will call Machinery or, more realistically, that the prices of A's various products do not vary in relation to each other so that we can think unambiguously of a representative A product, and similarly with B; (iii) that both A and B adopt domestic fiscal or monetary policies for the maintenance of what I have called Internal Balance or, in other words, that the authorities in each country take steps to cause such an inflation or deflation of its Domestic Expenditure (i.e., of its total money expenditure on goods and services for final use at home, whether these be home-produced or imported products) as to maintain constant the total demand for its own product and so for its own labour; (iv) that the money wage-rate and so (with constant employment and output) the money price of the product of each country in terms of the currency of that country is constant; and (v) that imports of Wheat from A into B and of Machinery from B into A are the only elements in the balance of payments except where the contrary is expressly stated. We have left room in the above assumptions for two important types of price change. First, we do not assume a constant rate of exchange between A's money which we will call dollars and B's money which we will call pounds. The pound price of B's Machinery and the dollar price of A's Wheat are fixed (see assumption iv); but as
Comparison of Non-Parametric Bayesian Mixture Models for Syllable Clustering and Zero-Resource Speech Processing

Zero-resource speech processing (ZS) systems aim to learn structural representations of speech without access to labeled data. A starting point for these systems is the extraction of syllable tokens utilizing the rhythmic structure of a speech signal. Several recent ZS systems have therefore focused on clustering such syllable tokens into linguistically meaningful units. These systems have so far used heuristically set number of clusters, which can, however, be highly dataset dependent and cannot be optimized in actual unsupervised settings. This paper focuses on improving the flexibility of ZS systems using Bayesian non-parametric (BNP) mixture models that are capable of simultaneously learning the cluster models as well as their number based on the properties of the dataset. We also compare different model design choices, namely priors over the weights and the cluster component models, as the impact of these choices is rarely reported in the previous studies. Experiments are conducted using conversational speech from several languages. The models are first evaluated in a separate syllable clustering task and then as a part of a full ZS system in order to examine the potential of BNP methods and illuminate the relative importance of different model design choices.
Detecting Information Waste on Websites

With the rapid growth of the internet, the amount of information waste is growing as well. However, it is not clear how much of this information waste is caused by websites. This paper describes a model using known and validated metrics. To make an estimate on the amount of information waste on the internet, this paper describes a proof of concept to show how data mining techniques can be used to estimate the amount of information waste on the internet caused by websites.
Implementation of particle swarm optimization algorithm for course scheduling (Case study: Universitas Multimedia Nusantara)

In a college, a scheduling is one of the most important aspects in teaching and learning activities, because every lecturers and students' activity depends on the schedule. This is the main reason why a schedule must be compiled properly, and be reviewed by the academy staff after every academic year, so that the activities can go well. An application that implements particle swarm optimization algorithm, which is built by using C# programming language and MySQL database, aims to generate a scheduling system which will not clash with each other. The methods used include literature studies, diagrams design, implementation, as well as testing and evaluation. The research results shown that non-lab regular classes scheduling, had been scheduled quite well with minimum schedule clashes (although still not free from clash).
Tuz Stresi Altında Yetiştirilen Patlıcan Bitkilerinde Klorofil, Yaprak Su Potansiyeli ve Bazı Meyve Özellikleri Üzerine Aşılı Bitki Kullanımının Etkisi

Tuzluluga bagli verim ve kalite kaybi diger sebzelerde oldugu gibi patlican icin de onemli bir sorundur. Patlican (Solanum melongena L.), tuza karsi orta derecede hassas bir bitkidir. Tuzluluk stresinin neden oldugu, verim kaybini ortadan kaldirmak veya azaltmak icin kullanilan onemli yontemlerden biri asilamadir. Arastirmada Vista, AGR703 (S. aethiopicum), Koksal F1, Yula F1, Vista (S. incanum x S. melongena hybrids) ve Hawk (S. torvum) ile tuza ve kuraga tolerant oldugu bilinen Mardin ve Burdur islah hatlari (S. melongena L.) anac olarak; tuza hassas Artvin yerel genotipi ile Naomi F1 cesidi kalem olarak kullanilmistir. Kalem olarak kullanilan cesitler ile asisiz, kendi uzerine ve anaclar uzerine asilanarak 18 anac/kalem kombinasyonu olusturulmustur. Bitkilerin yetistirilmesinde damla sulama yontemi kullanilarak, EC 1.8-2.0 dS/m-1 ve pH 5-6 ozelligindeki su ile (kontrol suyu) sulanma yapilmistir. Bitkiler ciceklenme ve meyve tutumu asamasina geldiginde 3 bin litrelik PE (polietilen) depo icine 8.76 kg NaCl (90 mM) ilave edilmis (EC 6-7 dS/m-1) ve bu depodan stres grubu bitkilere bir gun tuzlu su, bir gun kontrol suyu verilmistir. Arastirma sonucunda; klorofil icerigi, toplam verim, ortalama meyve agirligi, meyve suyu pH degeri, toplam suda cozunebilir madde miktari, titre edilebilir asit miktari ve meyvelerde renk olcumu degerleri bakimindan uygulama cesit interaksiyonu istatistiki olarak onemli bulunmustur. Bununla birlikte ortalama meyve capi degerleri bakimindan kombinasyon ve uygulamalar arasi, yaprak su potansiyeli degerleri bakimindan uygulamalar arasi farklilik onemli bulunmustur. Kalem olarak kullanilan Naomi F1 ticari cesidi, Artvin yerel genotipine gore daha iyi sonuclar verdigi, anac olarak kullanilan ticari cesitler icinde Koksal F1 ve Vista F1 cesitlerinin one ciktigi belirlenmistir. Sonuc olarak anac olarak kullanilan Burdur islah hattinin anac islahinda kullanilabilecek bir genotip oldugu tespit edilmistir.
Spiritual Care Training Provided to Healthcare Professionals: A Systematic Review

This systematic review was conducted to assess the outcomes of spiritual care training. It outlines the training outcomes based on participants’ oral/written feedback, course evaluation and performance assessment. Intervention was defined as any form of spiritual care training provided to healthcare professionals studying/working in an academic and/or clinical setting. An online search was conducted in MEDLINE, EMBASE, CINAHL, Web of Science, ERIC, PsycINFO, ASSIA, CSA, ATLA and CENTRAL up to Week 27 of 2013 by two independent investigators to reduce errors in inclusion. Only peer-reviewed journal articles reporting on training outcomes were included. A primary keyword-driven search found 4912 articles; 46 articles were identified as relevant for final analysis. The narrative synthesis of findings outlines the following outcomes: (1) acknowledging spirituality on an individual level, (2) success in integrating spirituality in clinical practice, (3) positive changes in communication with patients. This study examines primarily pre/post-effects within a single cohort. Due to an average study quality, the reported findings in this review are to be seen as indicators at most. Nevertheless, this review makes evident that without attending to one’the repeliefs and needs, addressing spirituality in patients will not be forthcoming. It also demonstrates that spiritual care training may help to challenge the spiritual vacuum in healthcare institutions.
A pair of taxifolin-3-O-arabinofuranoside isomers from Juglans regia L.

Abstract Diaphragma juglandis Fructus has been known for its effect on tonifying kidney in traditional Uighur medicine. During our ongoing studies on the discovery of biologically active compounds from folk medicine, a pair of flavanonol glycoside isomers named (2S,3S)-taxifolin-3-O-α-d-arabinofuranoside (1) and (2S,3S)-taxifolin-3-O-α-l-arabinofuranoside (2) were isolated, among them, 1 was a new compound. It is the first report of taxifolin-3-O-arabinofuranosides in both α-d and α-l configuration forms in genus Juglans. Their structures were determined on the basis of spectroscopic analysis and chemical evidence, in combination with circular dichroism.
Do patient age and medical condition influence medical advice to stop smoking?

OBJECTIVE to determine whether the age and medical condition of a patient influences hospital-based doctors' decision making when advising patients to stop smoking cigarettes. METHODS we presented 142 doctors from four grades (consultant, registrar, senior house officer and house officer) and four specialities (medicine, surgery, psychiatry and anaesthetics), based in a Dublin teaching hospital, with 20 clinical vignettes. Each vignette described a patient from one of five age groups with one of four levels of health. The vignettes were randomly mixed. We asked doctors to say whether they would advise the patient in each case to quit smoking. RESULTS hospital-based doctors are significantly less likely to advise patients aged over 65 years than younger patients of the hazards of cigarette smoking, irrespective of the person's physical or mental health (P < 0.001). CONCLUSION the advice given to patients about their cigarette smoking habits by hospital doctors is strongly influenced not only by the patient's health, but also by the patient's chronological age.
Polymer chain statistics and conformational analysis of DNA molecules with bends or sections of different flexibility.

The worm-like chain model has often been employed to describe the average conformation of long, intrinsically straight polymer molecules, including DNA. The present study extends the applicability of the worm-like chain model to polymers containing bends or sections of different flexibility. Several cases have been explicitly considered: (i) polymers with a single bend; (ii) polymers with multiple coplanar bends; (iii) polymers with two non-coplanar bends; and (iv) polymers comprised of sections with different persistence lengths. Expressions describing the average conformation of such polymers in terms of the mean-square end-to-end distance have been derived for each case. For cases (i) and (iv), expressions for the projection of the end-to-end vector onto the initial orientation of the chain are presented. The expressions derived here have been used to investigate DNA molecules with sequence-induced bending (A-tracts). Mean-square end-to-end distance values determined from a large number of A-tract containing DNA molecules visualized by scanning force microscopy resulted in an average bend angle of 13.5 degrees per A-tract. A similar study was performed to characterize the flexibility of double-strandedDNA molecules containing a single-stranded region. Analysis of their mean-square end-to-end distance yielded a persistence length of 1.3 nm for single-stranded DNA.
Statistical learning for prediction of Type 1 Diabetes using clinical risk factors and omics data (Statistisches Lernen zur Vorhersage von Typ 1 Diabetes mithilfe von klinischen Risikofaktoren und omics Daten)

In this thesis we use statistical learning approaches to identify novel markers for the pathogenesis of type 1 diabetes (T1D) and to develop new risk models with reliable prediction accuracy and feature selection. For this we develop an algorithm for high-dimensional survival data using a repeated nested cross-validation approach to obtain a sparse set of features along with an unbiased prediction accuracy estimate. By adapting and applying this approach in a proteomics study, we establish two sets of biomarkers predicting a pre-T1D stage and the progression to T1D onset. Using transcriptomics data, we present an approach to identify gene expression differences in a heterogeneous, longitudinally measured, high-dimensional dataset with a tailored generalized additive mixed model. Here, we identify a coherent molecular pattern between a T1D risk factor, Cesarean section and the development of autoantibodies.