Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of a Polyketide Synthase Required for Alternariol (AOH) and Alternariol-9-Methyl Ether (AME) Formation in Alternaria alternata

Alternaria alternata produces more than 60 secondary metabolites, among which alternariol (AOH) and alternariol-9-methyl ether (AME) are important mycotoxins. Whereas the toxicology of these two polyketide-based compounds has been studied, nothing is known about the genetics of their biosynthesis. One of the postulated core enzymes in the biosynthesis of AOH and AME is polyketide synthase (PKS). In a draft genome sequence of A. alternata we identified 10 putative PKS-encoding genes. The timing of the expression of two PKS genes, pksJ and pksH, correlated with the production of AOH and AME. The PksJ and PksH proteins are predicted to be 2222 and 2821 amino acids in length, respectively. They are both iterative type I reducing polyketide synthases. PksJ harbors a peroxisomal targeting sequence at the C-terminus, suggesting that the biosynthesis occurs at least partly in these organelles. In the vicinity of pksJ we found a transcriptional regulator, altR, involved in pksJ induction and a putative methyl transferase, possibly responsible for AME formation. Downregulation of pksJ and altR caused a large decrease of alternariol formation, suggesting that PksJ is the polyketide synthase required for the postulated Claisen condensations during the biosynthesis. No other enzymes appeared to be required. PksH downregulation affected pksJ expression and thus caused an indirect effect on AOH production.
Texture-based ancient porcelain shards classifications using Gabor transform

In this paper, based on analysis of gabor-filters parameters, it selects filters which have multi-scale and multi-orientation parameters, extract texture features from the convolution results that use these filters and Ancient porcelain shards Images, and reduce feature-data¿s dimensions based on principal component analysis (PCA). At last, use nearest neighbor method classifies shards, automatically classify and recognize these ancient shards are realized.
Sequencing and functional analysis of styrene catabolism genes from Pseudomonas fluorescens ST

The nucleotide sequence of the 4,377-bp chromosomal region of Pseudomonas fluorescens ST that codes for the oxidation of styrene to phenylacetic acid was determined. Four open reading frames, named styA, styB, styC, and styD, were identified in this region. Sequence analysis and biotransformation assays, performed with batch and continuous cultures, allowed us to identify the functions of the sequenced genes. styA and styB encode a styrene monooxygenase responsible for the transformation of styrene to epoxystyrene; styC codes for the second enzyme of the pathway, an epoxystyrene isomerase that converts epoxystyrene to phenylacetaldehyde; and the styD gene produces a phenylacetaldehyde dehydrogenase that oxidizes phenylacetaldehyde to phenylacetic acid. StyA, 415-amino-acids long, was found to be weakly homologous to p-hydroxybenzoate hydroxylase from both P. fluorescens and P. aeruginosa and to salicylate hydroxylase from P. putida, suggesting that it might be a flavin adenine dinucleotide-binding monooxygenase. StyB was found to be partially homologous to the carboxyterminal part of the 2,4-dichlorophenol-6-monooxygenase encoded by plasmid pJP4, while the styC product did not share significant homology with any known proteins. The fourth open reading frame, styD, could encode a protein of 502 amino acids and was strongly homologous to several eukaryotic and prokaryotic aldehyde dehydrogenases. The order of the genes corresponds to that of the catabolic steps. The previously suggested presence of the gene for epoxystyrene reductase, which directly converts epoxystyrene to 2-phenylethanol (A.M. Marconi, F. Beltrametti, G. Bestetti, F. Solinas, M. Ruzzi, E. Galli, and E. Zennaro, Appl. Environ. Microbiol. 61:121-127, 1996), has not been confirmed by sequencing and by biotransformation assays performed in continuous cultures. A copy of the insertion sequence ISI162, belonging to the IS21-like family of elements, was identified immediately downstream of the styrene catabolic genes.
An extended multi-layered blackboard approach for the optimization of world-spanning query execution plans

New application domains ranging from the area of computational science (e.g. CERN Datagrid) to international business processes (e.g. Wal-Mart logistics) demand ever increasing storage capacities on a global scale. Therefore the ability to query and access data efficiently is one of the major challenges that drive research and development in the area of wide distributed data management. Due to the situation of a huge variety of underlying heterogeneous and homogenous infrastructures, where each showing specific hard- and software resources and a number of possible data sources, the optimization of the access process to the desired data is a challenging task. Hence, this paper introduces a novel heuristic approach for the optimization of query execution plans (QEP) on a global scale based on an extended multi-layered blackboard mechanism to determine which available (1) data, (2) resources, and (3) operations to use. The proposed method is illustrated by an application scenario of finding an optimal QEP for the retrieval of music information from an online music store.
On Weighted Distributions and Mean Advantage Over Inferiors Functions

In this note, some fundamental results including relationship between weighted distribution functions and mean advantage over inferiors functions are established. Ordering of reliability and/or distribution functions via mean advantage over inferiors functions and related functions for parent and weighted reliability functions are presented. Some applications and examples are given. Mathematics Subject Classifications (2010): 62E15, 62F03
Situation awareness and mental workload of navigator in ship maneuvering simulator

Evading navigation in heavy marine traffic area required high navigation skill for navigator. Ship maneuvering simulator training was effective to improve their navigation skill. For the effective training, it was important that subject appropriately recognized ships that had collision risk. In order to measure navigator's situation awareness in simulator training, situation awareness global assessment technique was useful. However, in the case of ship maneuvering simulator training, accuracy of the measured data was insufficient. In order to clarify the reason for insufficient accuracy, this study measured navigator's situation awareness and mental workload in ship maneuvering simulator. As a result, this paper indicated that subjects who got appropriate tension during the simulation run had appropriate situation awareness.
The geometric error for homography Ondřej Chum Tomáš Pajdla

In this paper, an exact computation of the geometric error for homography is derived. We assume the Gaussian noise model for the perturbation of image coordinates and formulate the problem as a least squares minimization. This paper shows how to compute accurate geometric error through solving a polynomial of degree eight. This approach avoids falling into local minima that may occur when iterative methods are used. An application where this method can improve accuracy is discussed. Experiments comparing the geometric error with its approximation by the Sampson error are presented.
K-12 School Diversity and Social Cohesion: Evidence in Support of a Compelling State Interest

Despite existing research that demonstrates the benefits of racial diversity in education, the Court has become increasingly disinclined to allow the use of race or ethnicity in education policy targeted to increase race/ethnic diversity, absent a compelling state interest. The debate over the merits of educational diversity has almost exclusively focused on individual-level outcomes, ignoring consequences for society at large. We argue that this restricted conception of the goals of diversity may limit our understanding of how diverse learning opportunities represent compelling societal interests. Using macro-level data of 29 U.S. metropolitan areas, we examine the societal impact of K-12 diversity on an important societal attribute, intergroup social cohesion. This research has the potential to inform education policy and judicial sentiment about diversity as a compelling state interest in an increasingly diverse society.
Node Vulnerability under Finite Perturbations in Complex Networks

A measure to quantify vulnerability under perturbations (attacks, failures, large fluctuations) in ensembles (networks) of coupled dynamical systems is proposed. Rather than addressing the issue of how the network properties change upon removal of elements of the graph (the strategy followed by most of the existing methods for studying the vulnerability of a network based on its topology), here a dynamical definition of vulnerability is introduced, referring to the robustness of a collective dynamical state to perturbing events occurring over a fixed topology. In particular, we study how the collective (synchronized) dynamics of a network of chaotic units is disrupted under the action of a finite size perturbation on one of its nodes. Illustrative examples are provided for three systems of identical chaotic oscillators coupled according to three distinct well-known network topologies. A quantitative comparison between the obtained vulnerability rankings and the classical connectivity/centrality rankings is made that yields conclusive results. Possible applications of the proposed strategy and conclusions are also discussed.
Context-Aware Factorization for Personalized Student ' s Task Recommendation

Collaborative filtering one of the recommendation techniques has been applied for e-learning recently. This techniqu e makes an assumption that each user rates for an item once. However, in educa tional environment, each student may perform a task (problem) several times. Thus, applying original collaborative filtering for student's task recommen dation may produce unsatisfied results. We propose using context-aware models to utilize all interactions (performances) of the given student-ta sk pairs. This approach can be applied not only for personalized learning envir onment (e.g., recommending tasks to students) but also for predicting student performance. Evaluation results show that the proposed approach works bette r than the none-context method, which only uses one recent performance.
Bees_ Ants Based Routing Algorithm

In this paper we propose a novel routing algorithm called Bees Ants algorithm. This algorithm is a combination of Ant colony based Routing Algorithm (ARA) and BeeHive based Routing Algorithm. The proposed routing algorithm depends on splitting the network into two parts; one is a fixed network and the other is a mobile ad hoc network (MANET), then applying the Ant colony based Routing Algorithm on the mobile part and the BeeHive based Routing Algorithm on the fixed one. After comparing the proposed algorithm with the ARA algorithm, it shows promising results in terms of propagation delay, queue delay, and number of hops.
Interleukin-1 receptor antagonist gene (IL-1RN) polymorphism is a predictive factor of clinical pregnancy after IVF.

BACKGROUND Only 25% of IVF transfer cycles lead to a clinical pregnancy, calling for continued technical progress but also more in depth analysis of patients' individual characteristics. The interleukin-1 (IL-1) system and matrix metalloproteinases (MMPs) are strongly implicated in embryo implantation. The genes coding for IL-1Ra (gene symbol IL-1RN), IL-1beta, MMP2 and MMP9 bear functional polymorphisms. We analysed the maternal genetic profile at these polymorphic sites in IVF patients, to determine possible correlations with IVF outcome. METHODS One hundred and sixty women undergoing an IVF cycle were enrolled and a buccal smear was obtained. The presence of IL-1RN variable number of tandem repeats and IL-1B + 3953, MMP2-1306 and MMP9-1562 single nucleotide substitutions were determined. Patients were divided into pregnancy failures (119), biochemical pregnancies (8) and clinical pregnancies (33). RESULTS There was a 40% decrease in IL-1RN*2 allele frequency (P = 0.024) and a 45% decrease in IL-1RN*2 carrier status in the clinical pregnancy group as compared to the pregnancy failure group (P = 0.017). This decrease was still statistically significant after a multivariate logistic regression analysis. The likelihood of a clinical pregnancy was decreased accordingly in IL-1RN*2 carriers: odds ratio = 0.349, 95% confidence interval = 0.2-0.8, P = 0.017. The IL-1B, MMP2 and MMP9 polymorphisms showed no correlation with IVF outcome. CONCLUSIONS IL-1RN*2 allele carriage is associated with a poor prognosis of achieving a pregnancy after IVF.
Bayesian Analysis of Stock Index Return Volatility

The stochastic volatility is a universal phenomenon in financial time series, and an important issue in risk management research. In this paper, through the statistical structure of the standard stochastic volatility model, we infer the SV model's likelihood function, design the parameters' conjugate prior distribution, obtain the corresponding model parameter according to the Bayesian theorem, and examine their condition distribution. Furthermore, in order to obtain the model parameter estimation and their confidence intervals, we use Gibbs sampling to devise an MCMC computational procedure, and carry out an empirical analysis using the Shanghai composite index and the Shenzhen component index data. The results indicate that the Bayesian method is an effective tool to explore the financial time series data.
Detection of Adeno-Associated Virus Viremia in Hematopoietic Cell Transplant Recipients

Abstract Adeno-associated virus (AAV) is widely considered to be nonpathogenic, but the clinical epidemiology of this virus is limited. By use of polymerase chain reaction assays, we investigated the incidence and clinical significance of AAV viremia in a population of consecutive recipients of a hematopoietic cell transplant (HCT). Four (2.8%) of 145 patients developed AAV viremia after HCT. Viremia was low level and transient in all patients. Two patients were admitted to the hospital and died in proximity to AAV viremia (<7 weeks between diagnosis and death); however, AAV was not detected in tissue specimens obtained at autopsy. Thus, AAV does not appear to play a pathogenic role in organ-specific illness, even in a highly immunocompromised population.
Clinical improvisation in music therapy: theory, practice, research and training

Clinical improvisation is widely used in music therapeutic settings. This roundtable will reflect the use and innovated research of clinical improvisation in music therapy practice from an international, multi-theoretical perspective.Six music therapists from three different countries will provide a comprehensive presentation about innovated theoretical perspectives, clinical uses of improvisation with various classifications of psychiatric and medical populations, as well as provide relevant information on improvisational analysis (manual and computational), on how to assess the emotional impact of improvisations through heart rate variability measurements, on conducting various types of research in improvisation and also on advanced training in improvisation.
A new species of Agaricus section Minores from China

Agaricus gemloides sp. nov. is characterised by its reddish brown fibrillose squamose on the pileus, relatively slender basidiome and broader basidiospores. In this article, it is introduced based on its distinguished morphological features and molecular phylogenetic position.
Joint Action Segmentation and Classification by an Extended Hidden Markov Model

Hidden Markov models (HMMs) provide joint segmentation and classification of sequential data by efficient inference algorithms and have therefore been employed in fields as diverse as speech recognition, document processing, and genomics. However, conventional HMMs do not suit action segmentation in video due to the nature of the measurements which are often irregular in space and time, high dimensional and affected by outliers. For this reason, in this paper we present a joint action segmentation and classification approach based on an extended model: the hidden Markov model for multiple, irregular observations (HMM-MIO). Experiments performed over a concatenated version of the popular KTH action dataset and the challenging CMU multi-modal activity dataset (CMU-MMAC) report accuracies comparable to or higher than those of a bag-of-features approach, showing the usefulness of improved sequential models for joint action segmentation and classification tasks.
Connection establishment in high-speed networks

Protocols for establishing, maintaining, and terminating connections in packet-switched networks have been studied, and numerous standards have been developed to address this problem. The authors reexamine connection establishment in the context of a high-speed packet network, introduce a protocol for connection establishment/takedown that is appropriate for such a network, and explain its advantages over previously proposed protocols. The main features of the proposed protocol are: fast bandwidth reservation in order to avoid as much as possible reservation conflicts, guaranteed release of the reserved bandwidth even under modal and link failures, and soft recovery from processor failures, which allows the maintenance of existing connections under processor failure provided the switch and links do not fail. The underlying model that is used is the PARIS/plaNET network, but the protocol can be adapted to other fast packet networking architectures as well. >
Multi-class learning using data driven ECOC with deep search and re-balancing

Multi-class learning is an important task in Data Science. One of the ways to achieve good performance on this task is to use Error Correcting Output Codes (ECOC), which is a powerful ensemble learning method that transforms a multi-class problem into a series of binary classifiers which it uses indirectly to learn the original multi-class problem. A crucial component of ECOC is the design of the coding matrix, which determines which binary problems should be combined to achieve multi-class classification. There are two general ways of designing the coding matrix. One is rooted in information theory while the other is data driven. In this work, we investigate the data-driven approach which was previously shown to bear greater promise and propose a better search through the coding-matrix space, keeping in mind the tradeoff between efficiency and effectiveness, as well as considerations about class-imbalance issues in the underlying binary problems. After consolidating our hy! potheses with a study on artificial domains, we propose the Unsupervised Deep Search Algorithm (UDS) coupled with re-sampling, to address both concerns. Our results on real world domains show that our method outperforms traditional multi-class learning methods.
Relating a Model of Resolution of Arrested Anger to Outcome in Emotion-Focused Therapy of Depression

The present study explored essential client performances hypothesized to be involved in resolution of arrested anger for 32 clients engaged in EFT for depression, based on a previously proposed Model of Resolution of Arrested Anger in Depression (Tarba, 2007). Five components or predictors were investigated: (a) marker of arrested anger, (b) the expression of assertive anger, (c) empathic and insightful understanding of the other/selfcritic, (d) expression of primary adaptive sadness, and (e) letting go/forgiving the other/selfcritic. The Marker of Arrested Anger Rating Scale (MAARS) and The Resolution of Arrested Anger Components Scale (RAACS), two 5-point scales developed at the beginning of this study, were used to rate the presence and degree of manifestation of the hypothesized components. The average of "peak" ratings was used. Final outcome was assessed using change scores on three self-report measures: Beck Depression Inventory (BDI-II, depressive symptomatology), Global Severity Index (GSI, global symptomatology), and the Inventory of Interpersonal Problems (IIP, interpersonal difficulties). This study hypothesized a positive correlation between the peak intensity of markers of arrested anger and outcome measures at pre-treatment. As well, the components of resolution were expected to predict outcome at post-treatment, and anger expression was hypothesized to be an independent unique predictor, over and above the other components. Pearson’s product-moment correlations indicated a strong positive correlation (r = .78, p<.001) between the peak intensity of a marker of arrested anger and BDI-II pre-treatment scores, but not between the marker and other outcome measures (i.e., GSI and IIP). Regressions analyses showed that taken together, the components of resolution significantly predicted changes in BDI-II scores (64% of the overall variance explained), but not in GSI and IIP. Assertive anger expression is a
Establishing an Integrated Secure Wireless Sensor Network System: A New Approach

Wireless sensor networks (WSNs) are gaining a lot of popularity these days due to their application in a number of areas. WSN’s provide an easily implementable and cheaper solution for many real world problems like data gathering, surveillance, monitoring and control etc. However they are also used in a number of applications where security is a prime concern like military operations or other sensitive projects, whereby if the network is compromised then the outcomes can be disastrous. A lot of security schemes have been proposed which address different layers of protocol stack but none of them are fully integrated. In this paper a new approach is presented to establish a secure wireless sensor network. The proposed integrated approach addresses concerns like energy, and various security parameters like authenticity, confidentiality, integrity and requires lesser processing power.
Cognitive micro-foundations at work: how organizations resist change in work practice

Purpose The purpose of this paper is to explore the essence that is, the nature of organizational responses to efficiently resist enforced change in institutionalized work practice destined to address poor organizational performance. The micro-foundations of the cognitive logic that are activated when organizations face change are hereby conceptualized. Design/methodology/approach Using a case study design, the study focusses on narratives of a failure to implement a regulatory enforced change in work practice at a military academy established in the 1600s. The interviews are complemented by secondary data. Findings The analysis reveals a cognitive framework by which the members of the organization shaped their responses. By building on micro-foundations for mobilizing resistance (i.e. the essential substance at a micro level), this study shows how the cognitive logic is activated to respond to change. To show how the cognitive logic is used to mitigate and compensate for incongruences with the regulatory logic, this study outlines a set of strategic resistance maneuvers and cognitive resistance forces that restrict regulatory influence on change in work practice. This study thus provides insights into maneuvers and resistance forces that members may activate to resist change efficiently. Originality/value To the author’s knowledge, this is the first study to attempt to conceptualize the essence of the cognitive logic activated to resist organizational change.