Miracle-dz/UniFAR-FTUs huggingface dataset:
A MAP6-Related Protein Is Present in Protozoa and Is Involved in Flagellum Motility

In vertebrates the microtubule-associated proteins MAP6 and MAP6d1 stabilize cold-resistant microtubules. Cilia and flagella have cold-stable microtubules but MAP6 proteins have not been identified in these organelles. Here, we describe TbSAXO as the first MAP6-related protein to be identified in a protozoan, Trypanosoma brucei. Using a heterologous expression system, we show that TbSAXO is a microtubule stabilizing protein. Furthermore we identify the domains of the protein responsible for microtubule binding and stabilizing and show that they share homologies with the microtubule-stabilizing Mn domains of the MAP6 proteins. We demonstrate, in the flagellated parasite, that TbSAXO is an axonemal protein that plays a role in flagellum motility. Lastly we provide evidence that TbSAXO belongs to a group of MAP6-related proteins (SAXO proteins) present only in ciliated or flagellated organisms ranging from protozoa to mammals. We discuss the potential roles of the SAXO proteins in cilia and flagella function.
Pleurotus sajor-caju and Pleurotus florida Mushrooms Improve Some Extent of the Antioxidant Systems in the Liver of Hypercholesterolemic Rats

Objectives: There is evidence that the antioxidant systems are imbalanced in hypercholesterolemic rats due to oxidative stress. Dietary supplementation of Pleurotus sajor-caju and P. florida are anti-hypercholesterolemic in rats. In this study, it was investigated whether these mushrooms have any effects on the antioxidant systems in hypercholesterolemic rat liver, which are altered. Methods: Twenty young Long-Evans rats were randomly divided into 4 groups: control (fed basal diet), HC (fed 1% cholesterol with basal diet), HC+PS (fed 5% P. sajor-caju powder with 1% cholesterol and basal diet) and HC+PF (fed 5% P. florida powder with 1% cholesterol and basal diet). Rats were fed for 40 days, and then after sacrifice livers were collected, washed and homogenized. The content of reduced glutathione (GSH), thiobarbituric acid reactive substance (TBARS), and the activity of superoxide dismutase (SOD), catalase, glutathione peroxidase (GPx) in homogenate were measured. Results: All the studied parameters were altered in hypercholesterolemic rats significantly in comparison with control group, except catalase (non-significant). Feeding of P. florida protected liver lipid peroxidation in hypercholesterolemic rat, as TBARS was significantly lower (by 34.5%) in HC+PF group than in HC group. Feeding of both mushrooms showed significant improvement in the activity of GPx in liver of hypercholesterolemic rats (in HC+PS and HC+PF, the activity was higher by 50% and 80%, respectively than in HC group). However, mushroom feeding showed no significant effect on GSH level, SOD and catalase activity in hypercholesterolemic rats. Conclusion: This investigation confirms the antioxidant activities of P. sajor-caju and P. florida to some extent in hypercholesterolemic rats in addition to their anti-hypercholesterolemic activity.
Trader Type Effects on the Volatility-Volume Relationship: Evidence from the KOSPI 200 Index Futures Market

We investigate whether the trading activity generated by investors with different access to information and trading motives has positive or negative impact on index futures volatility. Surprises in non‐member institutional, individual and foreign investors' trading volume are positively associated with volatility in most of the cases. For member institutional investors, unexpected trading volume is positively related to volatility. Long‐run changes in the trading activity also affect volatility differently across trader types. Finally, allowing for time‐to‐maturity effects, surprises in open interest are associated with more volatility towards contract expiration, contrary to the negative effect we find during normal times.
The TF-IDF and Neural Networks Approach for Translation Initiation Site Prediction

The precise prediction of translation initiation site is an important task for the analysis of genomic sequence. This study aims to increase the accuracy for the prediction of translation initiation site using a TF-IDF-NN-TIS model (TF-IDF and Neural Networks Approach for Translation Initiation Site Prediction). This study creates feature using 1-gram and 2-gram techniques for both upstream and downstream. Determining feature value uses TF-IDF approach and feature selection by correlation-based feature selection method. Evaluation prediction results use 10-fold cross validation. This study performed experiments on three different datasets that are Vertebrate, Arabidopsis thaliana, and TIS+50. The results of the study indicate that the proposed model gives highest accuracy with less processing time.
Intelligent data mining systems by generalized multiple kernel machines on graph based subspace

Mining high-dimensional business data is a challenging problem. This paper proposes a novel approach to address the problems including (1) the curse of dimensionality and (2) the meaningfulness of the similarity measure in the high dimension space. The solution of this study is to build a generalized multiple kernel machine (GMKM) on a low-dimensional subspace. The representative subspace is created by the locally consistent matrix factorization (an improved variation of non-negative matrix factorization). The strengths of our system are two-fold: (1) GMKM takes products of kernels-corresponding to a tensor product of feature spaces. This leads to a richer and much higher dimensional feature representation, which is powerful in identifying relevant features and their apposite kernel representation. (2) Locally consistent matrix factorization finds a compact low-dimensional representation for data, which uncovers underlying information and simultaneously respects the intrinsic geometric structure of data manifold. Our system robustly outperforms traditional multiple kernel machines, and dimensionality reduction methods.
Distributed Target Tracking with Imperfect Binary Sensor Networks

We study target tracking with wireless sensor networks in its most basic form, assuming a binary sensing model in which each sensor can return only 1-bit information regarding target's presence or absence in its sensing range. A novel, real-time and distributed target tracking algorithm for imperfect binary sensing models is proposed, which is an extension of our previous work on the ideal binary sensing model. The algorithm estimates target's location, velocity and trajectory in a distributed and asynchronous manner. Extensive simulations show that our algorithm achieves high performance and outperforms other algorithms in terms of accuracy of the estimation of target's location, velocity and trajectory.
NavOptim Coding: Supporting Website Navigation Optimisation using Effort Minimisation

Web applications have rapidly become critical to the interaction that organisations have with their external stakeholders. A major factor in the effectiveness of this interaction is the ease with which navigation within the application can occur, and especially the extent to which users can locate information and functionality which they are seeking. Effective design is however complicated by the multiple purposes and users which Web applications typically support. Despite the fact that this implies that navigation design is inherently an optimisation problem, few optimisation techniques have been applied in this domain - with most design techniques being based on intuition, general heuristics, or experimental refinement. In this paper we discuss this problem, and propose a navigation representation which can become the basis for optimisation techniques.
Human body auto-extraction using graph cuts

Grabcut is an Interactive segmentation algorithm, which is employed to extract the foreground of an image, but it works wrong frequently when the pixels around the foreground are similar to the pixels of the background. We advance a new cost function to correct the mistake after we analyze the reason why it works wrong. Experimental results show that the new cost function outperforms the original one. Moreover, based on the new cost function we propose, we advance an algorithm of human body auto-extraction, which can be used to extract human body from background without interaction of user.
Natural image database and its use for scene illuminant estimation

This paper describes a database collecting natural color images, called the Natural Image Database, and shows how it is used for illuminant estimation problems. First, we present significant features of the database. This database is not only a collection of color images of natural scenes, but also includes scene illuminant spectra and camera calibration data. Because these data sets are available via the Internet at http://www.osakac. ac.jp/labs/shoji, the database can be used as the calibrated common test data for evalu- ating the performance of illuminant estimation algorithms. Second, we focus on two illuminant estimation methods, the subspace method for estimating scene illuminant spectra and the sensor cor- relation method for classifying illuminant color temperature. The al- gorithms are briefly described. The former is based on the linear model representation of possible illuminant spectra, and the latter is based on correlation computation between an observed image and the reference illuminant gamuts. The performance of these algo- rithms is evaluated using the database. © 2002 SPIE and IS&T.
H.263 based video codec for real-time visual communications over wireless radio networks

With the emergence of the International Telecommunication Union's (ITU) H.263 video coding standard, real-time visual communications over low-bandwidth, low-error-rate wired telephone networks is now possible. Unfortunately, because of the nature of the algorithms employed within this compression standard and due to the inherent limitations of the radio environment, the H.263 coded video performs pearly when employed over bandwidth-limited, error-prone wireless channels. We propose an intuitive, low-complexity, pre-compression scheme that improves the performance of H.263 coded video over radio channels. In our scheme video frames are spacially segmented into regions of different perceptual importance before being compressed independently with the H.263 encoder. This allows us to apply unequal error protection and prioritized transmission to achieve at least a minimum temporal resolution at the receiver. Additionally, with this technique, both spatial and temporal error propagation is limited and through intra-frame statistical multiplexing transmission bandwidth is utilized optimally. The results demonstrate that in the presence of severe error conditions and severe bandwidth constraints, our modified H.263 video codec exhibits better error concealment, better temporal resolution, and better bandwidth utilization properties than the original H.263 video codec.
Mandibular Distraction Osteogenesis in Pierre Robin Sequence: Application of a New Internal Single-Stage Resorbable Device

Pierre Robin sequence may result in physiologically significant obstructive apnea in the neonatal and infant period. This may be life threatening and is most often treated by tracheostomy. To avoid tracheostomy or allow for early decannulation in severely affected infants and children, the authors have developed a new class of neonatal and infant mandibular bone distraction devices. These devices require a single operative procedure for placement and no operative removal is necessary. Fifteen infants (aged 7 days to 11 months; mean age, 3 months) and five children (aged 2 to 8 years; mean age, 5.5 years), 10 boys and 10 girls, with severe obstructive apnea and Pierre Robin sequence were treated with the mandibular infant devices over a 24-month period. Tracheostomy was avoided in 14 patients, whereas five of six patients who had previous tracheostomy were decannulated after mandibular distraction. The final tracheostomy status in one patient will be determined after surgery for gastroesophageal reflux. There were no major complications and no structural device failures.
Advancing coordinated care in four provincial healthcare systems: evaluating a knowledge-exchange intervention.

OBJECTIVES This research project created and evaluated a knowledge-exchange intervention designed to facilitate an increase in organizational readiness for implementing coordinated stroke care in four primarily rural provincial healthcare systems. INTERVENTION Knowledge brokers were linked to networks within, across and outside the provinces to support, inform and disseminate best practice recommendations for coordinated stroke care within the provincial healthcare systems. FINDINGS The intervention increased awareness and dissemination of recommendations, which stimulated the implementation of coordinated stroke care. Similar knowledge-exchange interventions might work in other healthcare jurisdictions with similar demographics, to promote evidence-informed improvements in healthcare.
Teaching Religious Education: The Ethics and Religious Culture Program as Case Study

Responding to religious diversity and the new reality of schooling, the Ethics and Religious Culture (ERC) Program was introduced as a mandatory subject for all students in Quebec, Canada. Now in it's tenth year, the ERC has faced both challenges and successes in it's implementation. Though many studies have been written around the wider concepts of religious education and religious literacy in the public system, few studies have included voices from educators. Jafralie and Zaver's qualitative research study examines the potentials and struggles of the ERC Program, and by doing so, raise important considerations around the effective teaching of religion. The findings point to several consistent themes that teachers grapple with in regards to curriculum and pedagogy and highlights that in-service teachers are not thoroughly prepared to teach about religion, nor are teacher education programs effectively preparing pre-service teachers entering the field to deal with the complexities of teaching about religion in a secular setting. The authors suggest avenues in which teacher education for ERC teachers, and all religious education teachers, can look like in order for students and teachers to engage meaningfully with religious diversity.
A putative lipase gene EXTRA GLUME1 regulates both empty-glume fate and spikelet development in rice

Recent studies have shown that molecular control of inner floral organ identity appears to be largely conserved between monocots and dicots, but little is known regarding the molecular mechanism underlying development of the monocot outer floral organ, a unique floral structure in grasses. In this study, we report the cloning of the rice EXTRA GLUME1 (EG1) gene, a putative lipase gene that specifies empty-glume fate and floral meristem determinacy. In addition to affecting the identity and number of empty glumes, mutations in EG1 caused ectopic floral organs to be formed at each organ whorl or in extra ectopic whorls. Iterative glume-like structures or new floral organ primordia were formed in the presumptive region of the carpel, resulting in an indeterminate floral meristem. EG1 is expressed strongly in inflorescence primordia and weakly in developing floral primordia. We also found that the floral meristem and organ identity gene OsLHS1 showed altered expression with respect to both pattern and levels in the eg1 mutant, and is probably responsible for the pleiotropic floral defects in eg1. As a putative class III lipase that functionally differs from any known plant lipase, EG1 reveals a novel pathway that regulates rice empty-glume fate and spikelet development.
A Summariser based on Human Memory Limitations and Lexical Competition

Kintsch and van Dijk proposed a model of human comprehension and summarisation which is based on the idea of processing propositions on a sentence-bysentence basis, detecting argument overlap, and creating a summary on the basis of the best connected propositions. We present an implementation of that model, which gets around the problem of identifying concepts in text by applying coreference resolution, named entity detection, and semantic similarity detection, implemented as a two-step competition. We evaluate the resulting summariser against two commonly used extractive summarisers using ROUGE, with encouraging results.
Anomaly detection on traffic videos based on trajectory simplification

Detecting anomalies in the Traffic Control Systems (TCS) could be very useful for the accident analysis, fault detection and other traffic-related topics. In this article we propose a general framework for the trajectory-based anomaly detection, which is fast and reliable. Experimental results show that the system could be used on a vast variety of camera types and configurations. We have used a semi-supervised anomaly detection in the framework which learns from the trajectories of “normal” movements and detects the trajectories that does not fit on the trained model. The trajectories are simplified using a line simplification algorithm to improve the performance while increasing robustness on the noisy inputs.
Esscher transforms and the minimal entropy martingale measure for exponential Lévy models

In this paper we offer a systematic survey and comparison of the Esscher martingale transform for linear processes, the Esscher martingale transform for exponential processes, and the minimal entropy martingale measure for exponential Lévy models, and present some new results in order to give a complete characterization of those classes of measures. We illustrate the results with several concrete examples in detail.
Privacy enabling technology for video surveillance

In this paper, we address the problem privacy in video surveillance. We propose an efficient solution based on transformdomain scrambling of regions of interest in a video sequence. More specifically, the sign of selected transform coefficients is flipped during encoding. We address more specifically the case of Motion JPEG 2000. Simulation results show that the technique can be successfully applied to conceal information in regions of interest in the scene while providing with a good level of security. Furthermore, the scrambling is flexible and allows adjusting the amount of distortion introduced. This is achieved with a small impact on coding performance and negligible computational complexity increase. In the proposed video surveillance system, heterogeneous clients can remotely access the system through the Internet or 2G/3G mobile phone network. Thanks to the inherently scalable Motion JPEG 2000 codestream, the server is able to adapt the resolution and bandwidth of the delivered video depending on the usage environment of the client.
Experimental evaluation of timing bounds for clustering protocols in wireless sensor networks

In recent years a flurry of research activity has produced many suggested schemes for clustering wireless sensor networks, but no hard numbers for real-world implementations. This lack of guidance for developers makes it very difficult to effectively and confidently build working networks. This paper partially addresses these concerns by deriving minimal timing bounds on the clustering process in a typical and recently suggested clustering schemes. This is achieved through low-level network simulation in NS –2. We present detailed results that provide insight to timings involved in different phases of cluster set up. Results show ideal clusters can be constructed within 0.5 s for expected node densities (≤ 0.04 nodes/m2).
A novel fractional autocorrelation based feature extraction approach for radar emitter signals

An effective approach to extract the features of ambiguity function main ridge (AFMR) slice of radar emitter signals is proposed, in which fractional autocorrelation is used to search the AFMR, and moment method is adopted to describe the distribution characteristics of AFMR slice. The results of theoretical analysis and simulation experiments show that, the extracted characteristics vector of AFMR slice clearly expresses the differences of waveform in different signals, and it has strong compactness within clusters and good ability to resist noise. So it can be served as the optional parameter of deinterleaving for complicated radar emitter signals.
Psychological Disorders among Iranian Infertile Couples Undergoing Assisted Reproductive Technology (ART)

Background: Worldwide, infertility affects 10%–15% of couples and most of them seek medical help including Assisted Reproductive Technology (ART) treatments. Undergoing ART treatments create many physical and emotional burdens. This study examined the psychological consequences of infertility in Iranian infertile males and females as well as their spouses, unlike previous studies that examined mainly females with infertility. Methods: Subjects in this descriptive analytical design were recruited from the IVF Department of Mirza Koochak Khan Hospital and the Rouyesh Infertility Treatment Center of Tehran, Iran between Aug 2014 and Sep 2015. Overall, 256 couples (64% response rate), consisting of 78 infertile male and their spouses and 50 infertile female and their spouses, were included in this research. The psychological disorders were measured by the Persian version of Symptoms Checklist-90-Revised and Cattle Inventory. Results: Psychological disorders of infertile couples are significantly associated with increasing age, higher education, longer duration of infertility and unemployment (P<0.05). Prevalence of anxiety, depression, hypochondriasis and paranoia in infertile females and spouses of infertile males were significantly higher than husbands of infertile females (P<0.05). Obsession was more sever in infertile females was significantly greater than infertile males (P=0.01). Depression was significantly lower in infertile males than their spouses (P=0.016). Conclusion: Iranian infertile females and spouses of infertile males experienced more psychological disorders than infertile males and spouses of infertile females. These results may be due to the impact of cultural beliefs and gender roles in Iranian society. Anxiety, depression, obsession, paranoia and hypochondriasis should be addressed before any ART treatments.
An Empirical Performance Evaluation of Distributed SQL Query Engines

Distributed SQL Query Engines (DSQEs) are increasingly used in variety of domains, but especially users in small companies with little expertise may face the challenge of selecting an appropriate engine for their specific applications. Although both industry and academia are attempting to come up with high level benchmarks, the performance of DSQEs has never been explored or compared in-depth. We propose an empirical method for evaluating the performance of DSQEs with representative metrics, datasets, and system configurations. We implement a micro-benchmarking suite of three classes of SQL queries for both a synthetic and a real world dataset and we report response time, resource utilization, and scalability. We use our micro-benchmarking suite to analyze and compare three state-of-the-art engines, viz. Shark, Impala, and Hive. We gain valuable insights for each engine and we present a comprehensive comparison of these DSQEs. We find that different query engines have widely varying performance: Hive is always being outperformed by the other engines, but whether Impala or Shark is the best performer highly depends on the query type.