Miracle-dz/UniFAR-FTUs huggingface dataset:
Differentiation of Micromonospora Isolates from a Coastal Sediment in Wales on the Basis of Fourier Transform Infrared Spectroscopy, 16S rRNA Sequence Analysis, and the Amplified Fragment Length Polymorphism Technique

ABSTRACT A number of actinomycetes isolates were recovered from coastal sediments in Aberystwyth (Wales, United Kingdom) with standard isolation techniques. Most of them were putatively assigned to the genera Streptomyces and Micromonospora on the basis of their morphological characteristics, and there appeared to be no difference whether the isolation media contained distilled water or seawater. A group of 20 Micromonospora isolates was selected to undergo further polyphasic taxonomic investigation. Three approaches were used to analyze the diversity of these isolates, 16S rDNA sequencing, fluorescent amplified fragment length polymorphism (AFLP), and Fourier transform infrared spectroscopy (FT-IR). The 16S rDNA sequence analysis confirmed that all of these isolates should be classified to the genus Micromonospora, and they were analyzed with a group of other Micromonospora 16S rDNA sequences available from the Ribosomal Database Project. The relationships of the 20 isolates were observed after hierarchical clustering, and almost identical clusters were obtained with these three techniques. This has obvious implications for high-throughput screening for novel actinomycetes because FT-IR spectroscopy, which is a rapid and reliable whole-organism fingerprinting method, can be applied as a very useful dereplication tool to indicate which environmental isolates have been cultured previously.
Improving Classification by Improving Labelling: Introducing Probabilistic Multi-Label Object Interaction Recognition

This work deviates from easy-to-define class boundaries for object interactions. For the task of object interaction recognition, often captured using an egocentric view, we show that semantic ambiguities in verbs and recognising sub-interactions along with concurrent interactions result in legitimate class overlaps (Figure 1). We thus aim to model the mapping between observations and interaction classes, as well as class overlaps, towards a probabilistic multi-label classifier that emulates human annotators. Given a video segment containing an object interaction, we model the probability for a verb, out of a list of possible verbs, to be used to annotate that interaction. The proba- bility is learnt from crowdsourced annotations, and is tested on two public datasets, comprising 1405 video sequences for which we provide annotations on 90 verbs. We outper- form conventional single-label classification by 11% and 6% on the two datasets respectively, and show that learning from annotation probabilities outperforms majority voting and enables discovery of co-occurring labels.
Pareto Upper Confidence Bounds algorithms: An empirical study

Many real-world stochastic environments are inherently multi-objective environments with conflicting objectives. The multi-objective multi-armed bandits (MOMAB) are extensions of the classical, i.e. single objective, multi-armed bandits to reward vectors and multi-objective optimisation techniques are often required to design mechanisms with an efficient exploration / exploitation trade-off. In this paper, we propose the improved Pareto Upper Confidence Bound (iPUCB) algorithm that straightforwardly extends the single objective improved UCB algorithm to reward vectors by deleting the suboptimal arms. The goal of the improved Pareto UCB algorithm, i.e. iPUCB, is to identify the set of best arms, or the Pareto front, in a fixed budget of arm pulls. We experimentally compare the performance of the proposed Pareto upper confidence bound algorithm with the Pareto UCB1 algorithm and the Hoeffding race on a bi-objective example coming from an industrial control applications, i.e. the engagement of wet clutches. We propose a new regret metric based on the Kullback-Leibler divergence to measure the performance of a multi-objective multi-armed bandit algorithm. We show that iPUCB outperforms the other two tested algorithms on the given multi-objective environment.
Flexible transparent conductive films on PET substrates with an AZO/AgNW/AZO sandwich structure

Hybrid transparent conductive films (TCFs) with a sandwich structure composed of aluminum-doped zinc oxide (AZO) and Ag nanowires (AgNWs) were deposited on polyethylene terephthalate (PET) substrates. The AZO layers were prepared at room temperature by RF magnetron sputtering. The AgNWs were synthesized by a modified polyol method and inserted into the AZO layers. The optical properties and conductivity can be modified by the number of spin-coating cycles of an AgNWs suspension. Typically, an AZO/AgNW/AZO hybrid film exhibited an optical transmittance of 80.5%, a sheet resistance of 27.6 Ω sq−1 and an optical haze of 14.9%. The increase in optical haze caused by the silver nanowires may be beneficial for applications in solar cells. The hybrid films presented excellent flexible stability, showing only minor resistance changes and no surface cracks compared with pure AZO films. The AZO layers acted as the protecting layers that enhanced the adhesive and thermal stability of the hybrid films. The resulting hybrid TCFs with an AZO/AgNW/AZO sandwich structure show potential applications in flexible electronics, energy storage and photovoltaic devices.
Sharpness estimation for document and scene images

Images of document pages have different characteristics than images of natural scenes, and so the sharpness measures developed for natural scene images do not necessarily extend to document images primarily composed of text. We present an efficient and simple method for effectively estimating the sharp-ness/blurriness of document images that also performs well on natural scenes. Our method can be used to predict the sharpness in scenarios where images are blurred due to camera-motion (or hand-shake), defocus, or inherent properties of the imaging system. The proposed method outperforms the perceptually-based, no-reference sharpness work of [1] and [4], which was shown to perform better than 14 other no-reference sharpness measures on the LIVE dataset.
Trapping light in polymer photodiodes with soft embossed gratings

sur-face-pressure sensor and nanopure water (supplied by a Barnstead Nano-pure water system, 18.3 M (cid:87) ) as the subphase. A solution (0.08 mM) of the fractionated particles was prepared in hexane while TBBTwas dissolved in chloroform to make a concentration of ca. 2.4 mM. The calculated amount of the solutions was cast dropwise onto the water surface using a Hamilton microliter syringe. At least 20 min was allowed for evaporation prior to isotherm measurement and between compressions. Two particle layers were deposited onto both sides of a cleaned glass slide at a surface pressure (cid:112) = 13 mN/m. Optical measurements were carried out with a Unicam ATI UV-4 spectrometer with a resolution of 2 nm. The surface-plasmon band positions were determined by the second-order derivatives of the spectra. The TEM study was carried out with a Hitachi H7100 microscope (75 keV). Typically phase-contrast micro-images were captured at 300 K to 400 K magnification.
Cytoplasmic Relocalization of TAR DNA-Binding Protein 43 Is Not Sufficient to Reproduce Cellular Pathologies Associated with ALS In vitro

Mutations in the gene TARDBP, which encodes TAR DNA-binding protein 43 (TDP-43), are a rare cause of familial forms of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). While the majority of mutations are found in the C-terminal glycine-rich domain, an alanine to valine amino acid change at position 90 (A90V) in the bipartite nuclear localization signal (NLS) of TDP-43 has been described. This sequence variant has previously been shown to cause cytoplasmic mislocalization of TDP-43 and decrease protein solubility, leading to the formation of insoluble aggregates. Since the A90V mutation has been described both in patients as well as healthy controls, its pathogenic potential in ALS and FTD remains unclear. Here we compare properties of overexpressed A90V to the highly pathogenic M337V mutation. Though both mutations drive mislocalization of the protein to the cytoplasm to the same extent, M337V produces more significant damage in terms of protein solubility, levels of pathogenic phosphorylation, and formation of C-terminal truncated protein species. Furthermore, the M337V, but not the A90V mutant, leads to a downregulation of histone deacetylase 6 and Ras GTPase-activating protein-binding protein. We conclude that in the absence of another genetic or environmental ‘hit’ the A90V variant is not sufficient to cause the deleterious phenotypes associated with ALS and FTD, despite prominent cytoplasmic protein relocalization of TDP-43.
Classification Rules in Methods of Clustering

While classification rules are essential in supervised classification methods, they are not noticed well in methods of clustering. Nevertheless, some clustering techniques have clear rules of classification, while they are not obvious in other methods. This paper discusses classification rules or classification functions in the former class including K-means, fuzzy c-means, and the mixture of distributions, and shows theoretical properties that exhibit the nature of a method in this class. In contrast, linkage methods of agglomerative hierarchical clustering do not appear to have classification rules. We show, however, the single linkage method has the rule of nearest neighbor classification, while other linkage methods not. An advanced method using positive-definite kernels is also discussed.
Distribution of FMR1 and FMR2 Repeats in Argentinean Patients with Primary Ovarian Insufficiency

The premutation state of FMR1 (Fragile X Mental Retardation 1) has been associated with primary ovarian insufficiency (POI), and is the most common known genetic cause for 46,XX patients. Nevertheless, very few studies have analyzed its frequency in Latin American populations. Additionally, a relationship between alleles carrying a cryptic microdeletion in the 5’UTR of FMR2 and the onset of POI has only been studied in one population. Our aim was to analyze the incidence of FMR1 premutations and putative microdeletions in exon 1 of FMR2 in a cohort of Argentinean women with POI. We studied 133 patients and 84 controls. Fluorescent PCR was performed, and the FMR2 exon 1 was further sequenced in samples presenting less than 11 repeats. We found the frequency of FMR1 premutations to be 6.7% and 2.9% for familial and sporadic patients, respectively. Among controls, 1/84 women presented a premutation. In addition, although we did not find microdeletions in FMR2, we observed a change (T >C) adjacent to the repeats in two sisters with POI. Given the repetitive nature of the sequence involved, we could not ascertain whether this represents a single nucleotide polymorphism (SNP) or a deletion. Therefore, a relationship between FMR2 and POI could not be established for our population.
PRISM User ’ s Manual ( Version 1 . 10 )

Preface The past few years have witnessed a tremendous interest in logic-based probabilistic learning as testified by the number of formalisms and systems and their applications. Logic-based proba-bilistic learning is a multidisciplinary research area that integrates relational or logic formalisms, probabilistic reasoning mechanisms, and machine learning and data mining principles. Logic-based probabilistic learning has found its way into many application areas including bioinfor-matics, diagnosis and troubleshooting, stochastic language processing, information retrieval, linkage analysis and discovery, robot control, and probabilistic constraint solving. PRISM (PRogramming In Statistical Modeling) is a logic-based language that integrates logic programming and probabilistic reasoning including parameter learning. It allows for the description of independent probabilistic choices and their consequences in general logic programs. PRISM supports parameter learning, i.e. for a given set of possibly incomplete observed data, PRISM can estimate the probability distributions to best explain the data. This power is suitable for applications such as learning parameters of stochastic grammars, training stochastic models for gene sequence analysis, game record analysis, user modeling, and obtaining prob-abilistic information for tuning systems performance. PRISM offers incomparable flexibility compared with specific statistical tools such as hidden Markov models (HMMs) [2, 14], proba-bilistic context free grammars (PCFGs) [2] and discrete Bayesian networks. PRISM employs a proof-theoretic approach to learning. It conducts learning in two phases: the first phase searches for all the explanations for the observed data, and the second phase estimates the probability distributions by using the EM algorithm. Learning from flat explanations can be exponential in both space and time. To speed up learning, the authors proposed learning from explanation graphs and using tabling to reduce redundancy in the construction of explanation graphs. The PRISM programming system is implemented on top of B-Prolog (http://www.probp.com/), a constraint logic programming system that provides an efficient tabling system called linear tabling [29]. Tabling shares the same idea as dynamic programming in that both approaches make full use of intermediate results of computations. Using tabling in constructing explanation graphs resembles using dynamic programming in the Baum-Welch algorithm for HMMs and the Inside-Outside algorithm for PCFGs. Thanks to the good efficiency of the tabling system and the EM learner adopted in PRISM, PRISM is comparable in performance to specific statistical tools on relatively large amounts of data. The theoretical side of PRISM is comprehensively described in [23]. For an implementational view, please refer to [30]. This document describes the PRISM language, its programming system, …
Who moderates the moderators?: crowdsourcing abuse detection in user-generated content

A large fraction of user-generated content on the Web, such as posts or comments on popular online forums, consists of abuse or spam. Due to the volume of contributions on popular sites, a few trusted moderators cannot identify all such abusive content, so viewer ratings of contributions must be used for moderation. But not all viewers who rate content are trustworthy and accurate. What is a principled approach to assigning trust and aggregating user ratings, in order to accurately identify abusive content? In this paper, we introduce a framework to address the problem of moderating online content using crowdsourced ratings. Our framework encompasses users who are untrustworthy or inaccurate to an unknown extent --- that is, both the content and the raters are of unknown quality. With no knowledge whatsoever about the raters, it is impossible to do better than a random estimate. We present efficient algorithms to accurately detect abuse that only require knowledge about the identity of a single 'good' agent, who rates contributions accurately more than half the time. We prove that our algorithm can infer the quality of contributions with error that rapidly converges to zero as the number of observations increases; we also numerically demonstrate that the algorithm has very high accuracy for much fewer observations. Finally, we analyze the robustness of our algorithms to manipulation by adversarial or strategic raters, an important issue in moderating online content, and quantify how the performance of the algorithm degrades with the number of manipulating agents.
Study protocol for a single-blind, placebo-controlled randomised trial of Tianjiu effects in patients with intradialytic hypotension

Introduction Intradialytic hypotension (IDH) is the most frequent complication of haemodialysis (HD) and may contribute to cardiovascular events and high mortality. The aetiology of IDH is multifactorial; therefore, it remains a challenging problem in the management of patients with HD. Since the application of Tianjiu at specific points can influence haemodynamics, we hypothesise that Tianjiu therapy at the traditionally used meridian points will reduce the severity of hypotension in patients who undergo HD. Methods/analysis In this clinical trial, eligible patients with IDH will be divided randomly and equally into a Tianjiu group and a control group for 4 weeks. In the Tianjiu group, the patients will have Tianjiu applied at three points (conception vessel 4, and bilateral kidney 1) during each HD session. In the control group, patients will have clay patches applied in the same way as those in the Tianjiu treatment group. Both groups will be followed up for 2 weeks. The primary outcome measure will be the percentage of target ultrafiltration achieved, defined as the actual ultrafiltration volume divided by the target ultrafiltration volume. Secondary outcome measures, including frequency of IDH episodes and number of nursing interventions during HD sessions, predialysis and postdialysis blood pressure (BP), patient's participative assessment of the degree of fatigue after dialysis (scale from 0, not at all, to 10, extremely), and recovery time from fatigue after dialysis will be recorded at the 0th and 4th weeks. Ethics/dissemination This trial has undergone ethical scrutiny and been approved by the ethics review board of Chang Gung Memorial Hospital (Permission number: 102-4749A3 and 104-3156C). The pre-results of this trial will help to determine whether Tianjiu is an effective and safe treatment for IDH, and, if so, whether it is a therapeutic effect rather than a placebo effect. Trial registration number NCT02210377; Pre-results.
BasisGraph: Combining Storage and Structure Index for Similarity Search in Graph DB

Graph databases supporting retrieval based on structural similarity utilize structure indexes. A structure index is a data structure that indexes dierent structural features of member graphs. These features are typically extracted at insertion time. However, as the extraction of structural features may suer from combinatorial explosion, the structure index takes long insertion time and large disk space. The member graphs cannot be modified, since even a simple structural modification may require re-extraction of structural features. The depth to which structural features were extracted during insertion, forms a hard limit on query precision, which cannot be changed at query time. In order to address these issues, a new model is introduced that combines the database graph storage and the structure index into one data structure. There is no need to extract structural features at insertion time, no hard limit on query refinement and graph modifications are supported naturally.
Auditory External Representations: Exploring and Evaluating the Design and Learnability of an Auditory UML Diagram

We present an approach that examines the design of auditory displays for accessing graphically represented information in terms of their roles as external representations. This approach describes how a cross-modal translation process should emphasise the semantics of the represented information rather than the structural features of the medium that presents it. We exemplify this by exploring the design of a hierarchical representation to organise relational information encoded in a UML class diagram, and describe two alternative presentation modes to auditorally communicate this structure. We report on an experiment that we conducted to assess the viability of our approach and describe a novel methodological analysis which extends existing evaluation techniques to formally examine how a group of users learn and develop interactive expertise when using this auditory display.
The Research on Shaft Center Position of Ultra-Supercritical Steam-Turbine Generator

The shaft center of steam-turbine generator, showing relative position of shaft and bearing bush, would changed when jacking oil pump or turning gear started, raising speed and loading carrying. The change of bear carrying, oil film rigidity and clearance variation in flow passage of steam-turbine generator could be deduced through measuring shaft center position and analyzing its variation to working conditions, which would be helpful for treating vibration malfunction cased by deficiency of oil film rigidity, steam flow exciting and rubbing.
Trajectory Tracking of a Tri-Rotor Aerial Vehicle Using an MRAC-Based Robust Hybrid Control Algorithm

In this paper, a novel Model Reference Adaptive Control (MRAC)-based hybrid control algorithm is presented for the trajectory tracking of a tri-rotor Unmanned Aerial Vehicle (UAV). The mathematical model of the tri-rotor is based on the Newton–Euler formula, whereas the MRAC-based hybrid controller consists of Fuzzy Proportional Integral Derivative (F-PID) and Fuzzy Proportional Derivative (F-PD) controllers. MRAC is used as the main controller for the dynamics, while the parameters of the adaptive controller are fine-tuned by the F-PD controller for the altitude control subsystem and the F-PID controller for the attitude control subsystem of the UAV. The stability of the system is ensured and proven by Lyapunov stability analysis. The proposed control algorithm is tested and verified using computer simulations for the trajectory tracking of the desired path as an input. The effectiveness of our proposed algorithm is compared with F-PID and the Fuzzy Logic Controller (FLC). Our proposed controller exhibits much less steady state error, quick error convergence in the presence of disturbance or noise, and model uncertainties.
The roughening transition of crystal surfaces. I: Static and dynamic renormalization theory, crystal shape and facet growth

The renormalization approach to the roughening transition is reconsidered, both in a static and in a dynamic picture. Earlier results based on an asymptotic approximation are corrected, especially as regards the interface mobility. For a tilted interface, or in the presence of an applied force F, a new length scale appears, which must be compared to the correlation length ξ. As a result, the roughening transition is blurred, the crossover occuring below T R . This crossover is approached from both ends, via a «stopped renormalization» technique on the rough side, within a «discrete step» picture in the faceted state. At this last stage, the discussion is mostly qualitative. Comparison with experiment is done elsewhere Approche de la transition par une technique de renormalisation bloquee du cote rugueux et dans un schema de marches discretes du cote facette
Noisy Bloom Filters for Multi-Set Membership Testing

This paper is on designing a compact data structure for multi-set membership testing allowing fast set querying. Multi-set membership testing is a fundamental operation for computing systems and networking applications. Most existing schemes for multi-set membership testing are built upon Bloom filter, and fall short in either storage space cost or query speed. To address this issue, in this paper we propose Noisy Bloom Filter (NBF) and Error Corrected Noisy Bloom Filter (NBF-E) for multi-set membership testing. For theoretical analysis, we optimize their classification failure rate and false positive rate, and present criteria for selection between NBF and NBF-E. The key novelty of NBF and NBF-E is to store set ID information in a compact but noisy way that allows fast recording and querying, and use denoising method for querying. Especially, NBF-E incorporates asymmetric error-correcting coding technique into NBF to enhance the resilience of query results to noise by revealing and leveraging the asymmetric error nature of query results. To evaluate NBF and NBF-E in comparison with prior art, we conducted experiments using real-world network traces. The results show that NBF and NBF-E significantly advance the state-of-the-art on multi-set membership testing.