Miracle-dz/UniFAR-FTUs huggingface dataset:
Control of microtubule dynamics and length by cyclin A- and cyclin B- dependent kinases in Xenopus egg extracts

In eukaryotic cells, the onset of mitosis involves cyclin molecules which interact with proteins of the cdc2 family to produce active kinases. In vertebrate cells, cyclin A dependent kinases become active in S- and pro-phases, whereas a cyclin B-dependent kinase is mostly active in metaphase. It has recently been shown that, when added to Xenopus egg extracts, bacterially produced A- and B-type cyclins associate predominantly with the same kinase catalytic subunit, namely p34cdc2, and induce its histone H1 kinase activity with different kinetics. Here, we show that in the same cell free system, both the addition of cyclin A and cyclin B changes microtubule behavior. However, the cyclin A-dependent kinase does not induce a dramatic shortening of centrosome-nucleated microtubules whereas the cyclin B- dependent kinase does, as previously reported. Analysis of the parameters of microtubule dynamics by fluorescence video microscopy shows that the dramatic shortening induced by the cyclin B-dependent kinase is correlated with a several fold increase in catastrophe frequency, an effect not observed with the cyclin A-dependent kinase. Using a simple mathematical model, we show how the length distributions of centrosome-nucleated microtubules relate to the four parameters that describe microtubule dynamics. These four parameters define a threshold between unlimited microtubule growth and the establishment of steady- state dynamics, which implies that well defined steady-state length distributions can be produced by regulating precisely the respective values of the dynamical parameters. Moreover, the dynamical model predicts that increasing catastrophe frequency is more efficient than decreasing the rescue frequency to reduce the average steady state length of microtubules. These theoretical results are quantitatively confirmed by the experimental data.
Variation in body size and trophic morphology within and among genetically differentiated populations of the cichlid fish, Metriaclima zebra, from Lake Malawi

SUMMARY 1. The cichlid fish Metriaclima zebra, common in Lake Malawi, feeds by filtering plankton from the water and by brushing items from sediment covered substrata. It inhabits isolated rocky reefs among which community structure, resource availability and gene pools are likely to differ. We speculated that body size and trophic morphology of M. zebra might vary concomitantly. 2. We quantified the extent of genetic, body size and trophic variation within and between populations of M. zebra from southern Lake Malawi. Specifically, we tested the hypotheses that: (i) local populations are genetically differentiated, (ii) local populations differ in jaw morphology, dentition and standard length (SL), and (iii) variation in size is correlated with variation in trophic morphology. 3. Local populations of M. zebra differed in mean SL and were genetically differentiated. Moreover, populations exhibited dissimilar oral jaw morphologies and dentitions, perhaps related to differences in feeding biology. Variation in jaw shape was largely restricted to the curvature of the distal tip of the dentary. Populations were characterised by individuals with oblique, upward or downward directed gapes. Dental patterns differed in the proportion of unicuspid teeth in all rows of each jaw (dentaries and premaxillae) and the spacing of teeth in affected rows. 4. Within populations, jaw and tooth shapes were correlated with body size. Smaller individuals possessed upward curving jaws and closely packed multicusped teeth, while larger individuals exhibited relatively downward-directed jaws with increasing numbers of widely spaced unicuspid teeth. 5. Metriaclima zebra populations have increased in mean SL over the last decade, in contrast to a decline among Lake Malawi pelagic cichlids. Differences in size may contribute to variation in trophic morphology and may track local environmental dynamics in this lacustrine system.
Predictive and Prognostic Value of sPRR in Patients with Primary Epithelial Ovarian Cancer

Aim. The purpose of the present study was to analyze the predictive and prognostic role of soluble (pro)renin receptor (sPRR) as a biomarker for clinicopathological outcome in patients with primary epithelial ovarian cancer (EOC). As part of the renin-angiotensin system (RAS) whose activity is known to increase in ovarian cancer patients, the relation of sPRR and ovarian cancer should be further investigated. Patients and Methods. In this study 197 patients with primary EOC in our institution from 2000 to 2011 were included. sPRR was determined by enzyme-linked immunosorbent assay (ELISA) in preoperative taken blood sera. Associations with clinicopathological outcome were analyzed and serum levels of sPRR in patients have been compared to those in healthy specimen. Kaplan-Meier and logistic/Cox regression assessed the impact of the markers on progression-free survival (PFS) and overall survival (OS). Results. There have been no correlations proved of sPRR levels with neither clinicopathological factors nor prognostic data. Also the distribution of sPRR in patients and controls was normal. Conclusion. sPRR seems to have no predictive, prognostic, or diagnostic value in EOC. As several factors of the RAS which might indicate cancer events have been shown, sPRR seems not to be affected.
Protein Structure Prediction by Fusion, Bayesian Methods

Prediction of protein secondary structure (alpha-helix, beta-sheet, coil) from primary sequence of amino acids is a very challenging and difficult task, and the problem has been approached from several angles. A protein is a sequence of amino acid residues and can thus be considered as a one dimensional chain of ‘beads’ where each bead correspond to one of the 20 different amino acid residues known to occur in proteins. The length of most protein sequence ranges from 50 residues to about 1000 residues but longer proteins are also known, e.g. myosin, the major protein of muscle fibers, consists of 1800 residues (Altschul et al. 1997). Many techniques were used many researchers to predict the protein secondary structure, but the most commonly used technique for protein secondary structure prediction is the neural network (Qian et al. 1988). This chapter discusses a new method combining profile-based neural networks (Rost et al. 1993b), Simulated Annealing (SA) (Akkaladevi et al. 2005; Simons et al. 1997), Genetic algorithm (GA) (Akkaladevi et al. 2005) and the decision fusion algorithms (Akkaladevi et al. 2005). Researchers used the neural network (Hopfield 1982) combined with GA and SA algorithms, and then applied the two decision fusion methods; committee method and the correlation methods and obtained improved results on the prediction accuracy (Akkaladevi et al. 2005). Sequence profiles of amino acids are fed as input to the profile-based neural network. The two decision fusion methods improved the prediction accuracy, but noticeably one method worked better in some cases and the other method for some other sequence profiles of amino acids as input (Akkaladevi et al. 2005). Instead of compromising on some of the good solutions that could have generated from either approach, a combination of these two approaches is used for obtaining better prediction accuracy. This criterion is the basis for the Bayesian inference method (Anandalingam et al. 1989; Schmidler et al. 2000; Simons et al. 1997). The results obtained show that the prediction accuracy improves by more than 2% using the combination of the decision fusion approach and the Bayesian inference method.
Performance Analysis of OpenVPN on a Consumer Grade Router

Virtual Private Networks (VPNs) offer an alternative solution using Internet Protocol (IP) tunnels to create secure, encrypted communication between geographically distant networks using a common shared medium such as the Internet. They use tunneling to establish end-to-end connectivity. OpenVPN is a cross-platform, secure, highly configurable VPN solution. Security in OpenVPN is handled by the OpenSSL cryptographic library which provides strong security over a Secure Socket Layer (SSL) using standard algorithms such as Advanced Encryption Standard (AES), Blowfish, or Triple DES (3DES). The Linksys WRT54GL router is a consumer-grade router made by Linksys, a division of Cisco Systems, capable of running under Linux. The Linux-based DD-WRT open-source router firmware can run OpenVPN on the Linksys WRT54GL router. For this case study, the performance of OpenVPN is measured and analyzed using a 2k-p fractional factorial design for 5 minus 1 factors where k = 5 and p = 1. The results show that the throughput is mainly limited by the encryption cipher used, and that the round-trip time (RTT) is mostly dependent on the transport protocol selected.
Oxidative Stress: A Pathogenic Mechanism for Niemann-Pick Type C Disease

Niemann-Pick type C (NPC) disease is a neurovisceral atypical lipid storage disorder involving the accumulation of cholesterol and other lipids in the late endocytic pathway. The pathogenic mechanism that links the accumulation of intracellular cholesterol with cell death in NPC disease in both the CNS and the liver is currently unknown. Oxidative stress has been observed in the livers and brains of NPC mice and in different NPC cellular models. Moreover, there is evidence of an elevation of oxidative stress markers in the serumof NPC patients. Recent evidence strongly suggests that mitochondrial dysfunction plays an important role in NPC pathogenesis and that mitochondria could be a significant source of oxidative stress in this disease. In this context, the accumulation of vitamin E in the late endosomal/lysosomal compartments in NPC could lead to a potential decrease of its bioavailability and could be another possible cause of oxidative damage. Another possible source of reactive species in NPC is the diminished activity of different antioxidant enzymes. Moreover, because NPC is mainly caused by the accumulation of free cholesterol, oxidized cholesterol derivatives produced by oxidative stress may contribute to the pathogenesis of the disease.
An unsupervised GVF snake approach for white blood cell segmentation based on nucleus

Segmentation accuracy, as the first step in an image analysis system, impacts on whole system efficiency. In normal human blood microscopic image, which contains white and red blood cells, because of high accumulation of red cells, there exist touch and overlap between these cells. They are two difficult issues in image segmentation which common segmentation algorithms cannot overcome them. We have employed GVF snake to segment white cells which are clinically more important than red cells. In spite of traditional snakes, in GVF snakes it is not necessary to localize initial snake near the desired boundaries. On the other hand, nucleus which is laid inside white cell is the darkest part of image which can be localized by an adaptive histogram analysis. In this paper, we have proposed to use the convex hull of the boundary of nucleus as initial contour to detect white cell and separate it from touching red cells. Thus, initial contour is determined via an unsupervised method. Additionally, edges of nucleus are eliminated from edge map of the image and improve the efficiency of GVF snake a lot. Experimental Results show that our approach is very efficient
Suppression of Vortex Shedding from a Circular Cylinder by using a Suction Flow Control Method

An experimental study was conduct to suppress the vortex shedding from a circular cylinder by using a suction flow control method. The suction flow control was accomplished using two suction holes located on the test cylinder model at an angle of 90.0 degrees in relation to the oncoming flow direction. In addition to measuring the pressure distributions around the test model, a high-resolution digital particle image Velocimetry (PIV) system was used to conduct detailed flow field measurements to quantify the transient shedding behavior of the unsteady vortex and turbulent flow structures in the wake of the test cylinder model under different suction flow control conditions. The effectiveness of the vortex shedding suppression using the suction flow control method was evaluated based on the quantitative measurement results, which include the mean and fluctuating pressure coefficient distributions around the test cylinder model, the lift and drag coefficients of the test cylinder model with and without suction flow control, the instantaneous velocity and vorticity fields, the mean velocity and turbulence kinetic energy distributions around the cylinder model, and the mean velocity profiles in the wake of the test model under different suction flow control conditions. The measurement results of the present study revealed that the suction flow control method exhibited excellent performance in suppressing the alternative vortex shedding from the circular cylinder model (i.e., change the alternative vortex shedding mode into symmetric mode). As a result, the fluctuations of the lift coefficients and drag coefficients of the cylinder model were found to be reduced dramatically by using the suction flow control method.
Persepsi Lurah Tentang Keterlibatan Ayah dalam Pengasuhan dan Pendidikan Anak Usia Dini

Father's involvement in parenting and early childhood education and development (ECED) is a form of active participation in supporting child's development. Father does not often actively participated in parenting particularly in the community having patrilinial system. The study, conducted from October 2015 to March 2016 in Kupang, aimes at identifying father's involvement in parenting and ECE. Research design used was qualitative with interview as data collection method. Four heads of urban community participated in this reseatch. Thematic analysis was conducted.The result of the study indicates that fathers in Kupang city have involved themselves in parenting and ECED, but the involvement are limited to economic needs fulfillment while attention and emotional needs are less fulfilled. The study suggests to improve father's involvement through socializations, seminars or discussions.
A Petri Net and Extended Genetic Algorithm Combined Scheduling Method for Wafer Fabrication

As one of the most complicated manufacturing processes, semiconductor manufacturing consists of four steps, wafer sort, wafer fabrication, assembly, and testing. Among them, wafer fabrication is the most costly, complex, and time consuming step. Its operation management and optimization are challenging modeling and scheduling researchers. To address its modeling issue, a hierarchical colored timed Petri net (HCTPN) is proposed, which can be used to describe various states, behavior and substructures of a wafer fabrication system. To address its scheduling issue, intelligent algorithms are introduced to the proposed HCTPN. An extended genetic algorithm (EGA) embedded scheduling strategy over HCTPN is studied to optimize the combination of scheduling policies. The combined approach can conduct more efficient search with better scheduling performance. At last, a real case is presented to illustrate the results. Based on comparing simulation results of different scheduling strategies, the HCTPN and EGA combined scheduling is proved to be valid and efficient.
An Overview of Lambda-PROLOG

$\lambda$Prolog is a logic programming language that extends Prolog by incorporating notions of higher-order functions, $\lambda$-terms, higher-order unification, polymorphic types, and mechanisms for building modules and secure abstract data types. These new features are provided in a principled fashion by extending the classical first-order theory of Horn clauses to the intuitionistic higher-order theory of {\em hereditary Harrop} formulas. The justification for considering this extension a satisfactory logic programming language is provided through the proof-theoretic notion of a {\em uniform proof}. The correspondence between each extension to Prolog and the new features in the stronger logical theory is discussed. Also discussed are various aspects of an experimental implementation of $\lambda$Prolog.
Oscillatory patterns in sympathetic neural discharge and cardiovascular variables during orthostatic stimulus.

BACKGROUND We tested the hypothesis that a common oscillatory pattern might characterize the rhythmic discharge of muscle sympathetic nerve activity (MSNA) and the spontaneous variability of heart rate and systolic arterial pressure (SAP) during a physiological increase of sympathetic activity induced by the head-up tilt maneuver. METHODS AND RESULTS Ten healthy subjects underwent continuous recordings of ECG, intra-arterial pressure, respiratory activity, central venous pressure, and MSNA, both in the recumbent position and during 75 degrees head-up tilt. Venous samplings for catecholamine assessment were obtained at rest and during the fifth minute of tilt. Spectrum and cross-spectrum analyses of R-R interval, SAP, and MSNA variabilities and of respiratory activity provided the low (LF, 0.1 Hz) and high frequency (HF, 0.27 Hz) rhythmic components of each signal and assessed their linear relationships. Compared with the recumbent position, tilt reduced central venous pressure, but blood pressure was unchanged. Heart rate, MSNA, and plasma epinephrine and norepinephrine levels increased, suggesting a marked enhancement of overall sympathetic activity. During tilt, LF(MSNA) increased compared with the level in the supine position; this mirrored similar changes observed in the LF components of R-R interval and SAP variabilities. The increase of LF(MSNA) was proportional to the amount of the sympathetic discharge. The coupling between LF components of MSNA and R-R interval and SAP variabilities was enhanced during tilt compared with rest. CONCLUSIONS During the sympathetic activation induced by tilt, a similar oscillatory pattern based on an increased LF rhythmicity characterized the spontaneous variability of neural sympathetic discharge, R-R interval, and arterial pressure.
A Review Paper of 3D Surface Reconstruction of Coronary Arteries from Cardiovascular Angiography

This paper begins with a review of the coronary artery trees extraction techniques within different eras. Next, a review of 3D reconstruction of coronary artery trees approaches is presented in details. A well presentation of the center of gravity approaches is included within the 3D reconstruction review techniques. Finally, the paper discusses the surface reconstruction techniques throughout their development stages. Each stage of the review paper is concluded by a summary. This paper is concluded by a comprehensive summary which discussed the lack of a robust approach in each stage of it. The improvement of a new approach in each stage depends on the lack in that stage and the results which are expected from the work.
Semantic Workflow Adaption in Support of Workflow Diversity

The application of business process execution and guidance to environments with highly dynamic situations and workflow diversity is hindered by rigid predefined workflow models. Software engineering environments constitute an acute example where developers could benefit from automated workflow guidance if the workflows were made sufficiently concrete and conformant to actual situations. A context-aware software engineering environment was developed utilizing semantic processing and situational method engineering to automatically adapt workflows utilizing an adaptive process- aware information system. Workflows are constructed via context knowledge congruent to the current situation. Preliminary results suggest this technique can be beneficial in addressing high workflow diversity while providing useable guidance and reducing workflow modeling effort.
Role of vacuum fluctuation forces in thin metal film stability

Thin metal films are subject to the pressure caused by the zero-point oscillations of the electromagnetic field, which depends upon the film optical properties and, in case of deposition onto a substrate, upon the substrate reflectivity. It has been suggested that this force may be relevant in determining the stability of deposited pseudomorphic films with respect to buckling or island formation. We present a detailed analysis of its behavior as a function of the optical parameters and of the film thickness and we illustrate the conditions under which it may play some role. For free-standing films it turns out that the film stabilization is basically due to the surface stress, which largely overwhelms the vacuum force. For epilayers on metal substrate the vacuum force may be important, and we give stability diagrams and critical thicknesses for several cases, illustrating how the flat surface growth may depend upon the film parameters. The importance of including retardation effects into the theory for a realistic determination of the stability conditions is also discussed.
Space-time spreading for MIMO CDMA-based systems over fast-fading channels

In this paper, a transmit diversity scheme based on space-time spreading for code-division multiple-access (CDMA) systems in fast-fading channels is introduced. The proposed transmit diversity scheme employs orthogonal Walsh spreading codes to exploit the time diversity introduced by the channel, and hence achieves two-fold of the diversity order obtained using conventional space-time spreading schemes. A generalization of the proposed coding scheme to systems with different antenna configurations is also discussed. For slowly-fading channels, we show that the proposed transmit diversity scheme reduces to that of conventional transmit diversity schemes with no performance degradation. For nonorthogonal spreading codes, we propose a receiver structure that employs an interference cancellation scheme to compensate for signal interference. Our results show a large performance improvement when using such an interference cancellation scheme relative to the conventional matched filter receiver.
Self-informed neural network structure learning

We study the problem of large scale, multi-label visual recognition with a large number of possible classes. We propose a method for augmenting a trained neural network classifier with auxiliary capacity in a manner designed to significantly improve upon an already well-performing model, while minimally impacting its computational footprint. Using the predictions of the network itself as a descriptor for assessing visual similarity, we define a partitioning of the label space into groups of visually similar entities. We then augment the network with auxilliary hidden layer pathways with connectivity only to these groups of label units. We report a significant improvement in mean average precision on a large-scale object recognition task with the augmented model, while increasing the number of multiply-adds by less than 3%.