Miracle-dz/UniFAR-FTUs huggingface dataset:
A new tool in C. elegans reveals changes in secretory protein metabolism in ire-1-deficient animals

We recently showed that the ire-1/xbp-1 arm of the UPR plays a crucial role in maintaining basic endoplasmic reticulum (ER) functions required for the metabolism of secreted proteins even during unstressed growth conditions. During these studies we realized that although C. elegans is a powerful system to study the genetics of many cellular processes; it lacks effective tools for tracking the metabolism of secreted proteins at the cell and organism levels. Here, we outline how genetic manipulations and expression analysis of a DAF-28::GFP translational fusion transgene can be combined to infer different steps in the life cycle of secretory proteins. We demonstrate how we have used this tool to reveal folding defects, clearance defects, and secretion defects in ire-1 and xbp-1 mutants. We believe that further studies using this tool will deepen the understanding of secretory protein metabolism.
The Epstein-Barr Virus Rta Protein Activates Lytic Cycle Genes and Can Disrupt Latency in B Lymphocytes

ABSTRACT The transition of Epstein-Barr virus (EBV) from latency into the lytic cycle is associated with the expression of two immediate-early viral genes, BZLF1 and BRLF1. Overexpression of ZEBRA, the product of BZLF1, is sufficient to disrupt latency in B lymphocytes and epithelial cells by stimulating expression of lytic cycle genes, including BRLF1. The BRLF1 product Rta functions as a transcriptional activator in both B lymphocytes and epithelial cells. However, Rta has recently been reported to disrupt latency in an epithelial specific manner (S. Zalani, E. Holley-Guthrie, and S. Kenney, Proc. Natl. Acad. Sci. USA 93:9194–9199, 1996). Here we demonstrate that expression of Rta is also sufficient for disruption of latency in a permissive B-cell line. In HH514-16 cells, transfection of Rta leads to synthesis of ZEBRA, viral DNA replication, and late gene expression. However, Rta by itself is less potent than ZEBRA in the ability to activate most early and late lytic cycle genes. In light of previous work implicating ZEBRA in the activation of Rta, we suggest a cooperative model for EBV entry into the lytic cycle. Expression of either BZLF1 or BRLF1 triggers expression of the other immediate-early factor, and together these activators act individually or in synergy on downstream targets to activate the viral lytic cycle.
Edge dedection application with FPGA based Sobel operator

Image processing can be defined as analysis of the images consists of the several steps. The edge detection process that is one of these steps can be performed using a variety of operators. Sobel edge detection operator, is a basic operator, is preferred to use with high noisy images because its corruption is insensible on images. The proposed work presents an edge detection algorithm using Sobel operator based on FPGA architecture. Proposed system is designed using IEEE 754-1985 floating-point standard and VHDL hardware description language. Design is synthesized for Xilinx Virtex-6 FPGA chip with 160 MHz operating frequency. The performance is decreed according chip statistics.
Iteration-complexity of a Rockafellar's proximal method of multipliers for convex programming based on second-order approximations

ABSTRACT This paper studies the iteration-complexity of a new primal-dual algorithm based on Rockafellar's proximal method of multipliers (PMM) for solving smooth convex programming problems with inequality constraints. In each step, either a step of Rockafellar's PMM for a second-order model of the problem is computed or a relaxed extragradient step is performed. The resulting algorithm is a (large-step) relaxed hybrid proximal extragradient (r-HPE) method of multipliers, which combines Rockafellar's PMM with the r-HPE method. We obtain pointwise and ergodic global convergence rates at the price of solving, at each iteration, quadratic quadratically constrained convex programming problems. These convergence rates are superior to the corresponding pointwise and ergodic currently known for standard proximal-point methods, thanks to the incorporation of second-order information. To the best of our knowledge, this is the first time that the above mentioned rates and results are obtained for solving the smooth convex programming problems with inequality constraints.
Secure and E?cient Use of Recon?gurable Hardware Devices in Symmetric Cryptography

A rotary hydraulic motor including a stator having a central cylindrical cavity with radial slots communicating with the cavity and containing reciprocable sealing rollers, a cam rotor in the cavity with a peripheral cam surface including a plurality of cam lobes with intervening lows engaging the sealing rollers to form displacement chambers, a pair of port plates secured to opposite sides of the rotor for rotation therewith including outwardly disposed portions slidably engaging the sides of the stator adjacent the roller slots, an annular array of alternate inlet and outlet ports in each port plate adjacent the roller slots in the stator, and a pair of pressure plates disposed against the surfaces of the port plates remote from the rotor and the stator. Pressure chambers around the periphery of the port plates reduce deflection of the plates, and pressure chambers behind each pressure plate seal the port plates in the housing. The rotor is constructed with passages communicating the inlet ports in the two port plates and passages communicating the outlet ports in the two port plates. Provision is made for supplying pressure acting in the outer ends of the slots to urge the rollers toward the cam.
Behavior Analysis in Social Media

W ith the rise of social media, information sharing has been democratized. As a result, users are given opportunities to exhibit different behaviors such as sharing, posting, liking, commenting, and befriending conveniently and on a daily basis. By analyzing behaviors observed on social media, we can categorize these behaviors into individual and collective behavior. Individual behavior is exhibited by a single user, whereas collective behavior is observed when a group of users behave together. For instance, users using the same hashtag on Twitter or migrating to another social media site are examples of collective behavior. User activities on social media generate behavioral data, which is massive, expansive, and indicative of user preferences, interests, opinions, and relationships. This behavioral data provides a new lens through which we can observe and analyze individual and collective behaviors of users. The emergence of this new type of data presents behavior analysis on social media with new challenges. We detail first what individual and collective behavior analysis is, and then outline novel challenges with future work.
Pengaruh Debt to Equity Ratio, Earning per Share dan Net Profit Margin Terhadap Return Saham Perusahaan (Pada Perusahaan Perbankan yang Listing di BEI Tahun 2008-2010)

Pasar modal sebagai sarana untuk memobilisasi dana yang bersumber dari masyarakat ke berbagai sektor yang melaksanakan investasi. Syarat utama yang diinginkan oleh para investor untuk bersedia menyalurkan dananya melalui pasar modal adalah perasaan aman akan investasinya. Para investor yang akan melakukan investasi dengan membeli saham di pasar modal akan menganalisis kondisi perusahaan terlebih dahulu agar investasi yang dilakukannya dapat memberikan keuntungan (return). Memperoleh return (keuntungan) merupakan tujuan utama dari aktivitas perdagangan para investor di pasar modal. Penelitian ini bertujuan untuk mengetahui pengaruh pengaruh debt to equity ratio, earning per share dan net profit margin secara parsial maupun simultan terhadap return saham pada perusahaan perbankan yang listing di BEI tahun 2008-2010. Populasi dalam penelitian ini adalah semua perusahaan perbankan yang terdaftar di Bursa Efek Indonesia. Teknik pengambilan sampel menggunakan purposive sampling. Dimana dari teknik purposive sampling tersebut diperoleh sampel sebanyak 22 perusahaan. Variabel dalam penelitian ini terdiri dari debt to equity ratio (X1), earning per share (X2), net profit margin (X3) dan return saham (Y). Metode pengumpulan data dengan menggunakan metode dokumentasi. Metode analisis data menggunakan analisis regresi linier berganda dengan program SPSS 16. Besarnya pengaruh debt to equity ratio, earning per share dan net profit margin secara simultan terhadap return saham adalah 24,3 % dan sisanya sebesar 74,7% dipengaruhi oleh variabel lain yang tidak masuk dalam penelitian ini. Besarnya pengaruh secara parsial debt to equity ratio kualitas terhadap return saham adalah 8,07%. Besarnya pengaruh secara parsial earning per share terhadap return saham adalah 16,08%. Sedangkan net profit margin secara parsial tidak berpengaruh terhadap return saham. Persamaan regresi yang dihasilkan adalah Y= 0,222 - 0,012X1 + 0,001X2 + 0,004X3. Berdasarkan hasil penelitian diketahui bahwa secara simultan terdapat pengaruh debt to equity ratio, earning per share dan net profit margin terhadap return saham. Secara parsial debt to equity ratio dan earning per share berpengaruh terhadap return saham. Namun secara parsial net profit margin tidak berpengaruh signifikan terhadap return saham. Saran yang dapat peneliti berikan adalah kepada calon investor sebaikanya lebih memperhatikan faktor-faktor fundamental seperti tingkat DER, EPS dan NPM perusahaan perbankan sebelum memutuskan untuk membeli saham melalui Bursa Efek Indonesia.
Performance analysis of propagation models in different terrain conditions for IEEE standard 802.16e WiMAX

To fulfill the end-users demand for access to the Internet “anywhere-anytime” and ensure quality of service, is the WiMAX (Worldwide Interoperability for Microwave Access) technology standardized based on IEEE 802.16 that provides efficient packet radio interface enabling transmission of high data rates. WiMAX network became popular and receives growing acceptance as a Broadband Wireless Access (BWA) system which is the solution of “last mile” wireless broadband. WiMAX has potential success and is gaining hike all over the world for deployment of the network in its line-of-sight (LOS) and non-line-of-sight (NLOS) conditions for both fixed operation below 11GHz and Mobile operation below 6 GHz frequency range. In the first step of cell planning and deployment of wireless network, estimation of path loss is very important in turn to get better signal strength to access Internet. In this work, we have used well-structured propagation models for analysis and comparison at different terrain areas, the models are - COST231 Hata model, COST231 Walfisch-Ikegami model, ECC-33 model, Ericsson model, and SUI model for SIMO (Single-input Multiple-output) channels. Using environmental parameters and some correction factors path loss is calculated for all terrain (urban, suburban, and rural) conditions. This provides guidelines for cell planning of mobile WiMAX at cellular frequency between 2-6 GHz.
A Tight BER Upper Bound for Bit-Interleaved Coded Modulation with Square QAM and Gray Labeling

Bit-interleaved coded modulation (BICM) is a bandwidth-efficient coded system with diversity order higher than that of Ungerboeck's trellis-coded modulation on fading channels. In this paper, we investigate the BER (bit error rate) performance of BICM in the additive white Gaussian and Rayleigh fading channels. A new upper bound is given for the square QAM constellation with gray labeling, which constitutes a large portion of practical applications of BICM systems. The new upper bound is tighter than the well-known BICM union bound proposed in G. Caire et al. (1998)
Quiet-Sun Magnetic Field Measurements Based on Lines with Hyperfine Structure

The Zeeman pattern of Mn I lines is sensitive to hyperfine structure (HFS), and because of this, they respond to hectogauss magnetic field strengths differently than the lines commonly used in solar magnetometry. This peculiarity has been employed to measure magnetic field strengths in quiet-Sun regions, assuming the magnetic field to be constant over a resolution element. This assumption is clearly insufficient, biasing the measurements. The diagnostic potential of Mn I lines can be fully exploited only after one understands the sense and magnitude of such bias. We present the first syntheses of Mn I lines in realistic quiet-Sun model atmospheres. The Mn I lines weaken with increasing field strength. In particular, kilogauss magnetic concentrations produce Mn I λ5538 circular polarization signals (Stokes V) that can be up to 2 orders of magnitude smaller than what the weak magnetic field approximation predicts. The polarization emerging from an atmosphere having weak and strong fields is biased toward the weak fields, and HFS features characteristic of weak fields show up even when the magnetic flux and energy are dominated by kilogauss fields. For the HFS feature of Mn I λ5538 to disappear, the filling factor of kilogauss fields has to be larger than the filling factor of subkilogauss fields. Since the Mn I lines are usually weak, Stokes V depends on magnetic field inclination according to the simple cosine law. Atmospheres with unresolved velocities produce very asymmetric line profiles, which cannot be reproduced by simple one-component model atmospheres. Using the HFS constants available in the literature, we reproduce the observed line profiles of nine lines with varied HFS patterns.
Prediction of the Location of the Pyramidal Tract in Patients with Thalamic or Basal Ganglia Tumors

Background Locating the pyramidal tract (PT) is difficult in patients with thalamic or basal ganglia tumors, especially when the surrounding anatomical structures cannot be identified using computed tomography or magnetic resonance images. Hence, we objected to find a way to predict the location of the PT in patients with thalamic and basal ganglia tumors Methodology/Principal Findings In 59 patents with thalamic or basal ganglia tumors, the PTs were constructed by with diffusion tensor imaging (DTI)-based fiber tracking (FT). In axial slices crossing the foramen of Monro, the tumor position was classified according to three lines. Line 1 was vertical and crossed the vertex point of the anterior limbs of the internal capsule. Lines 2 and line 3 were horizontal and crossed the foramen of Monro and joint of the middle and lateral thirds of the posterior limbs, respectively. Six (10.17%) patients were diagnosed with type 1 tumor, six (10.17%) with type 2, seven (11.86%) with type 3a, five (8.47%) with type 3b, 17 (28.81%) with type 4a, six (10.17%) with type 4b, three (5.08%) with type 5, and nine (15.25%) with type 6. In type 1 tumors, the PTs were located at the 12 o'clock position of the tumor, type 2 at six o'clock, type 3a between nine and 12 o'clock, type 3 between six and nine o'clock, type 4a between 12 and three o'clock, type 4b at three o'clock, type 5 between six and nine o'clock, and type 6 between three and six o'clock. Conclusions/Significance The position of the PT relative to the tumor could be determined according to the tumor location. These results could prove helpful in determining the location of the PT preoperatively.
A Semantic Rule-Based Approach Towards Process Mining for Personalised Adaptive Learning

In recent years, automated learning systems are widely used for educational and training purposes within various organisations including, schools, universities and further education centres. A common challenge for automated learning approaches is the demand for an effectively well-designed and fit for purpose system that meets the requirements and needs of intended learners to achieve their learning goals. This paper proposes a novel approach for automated learning that is capable of detecting changing trends in learning behaviours and abilities through the use of process mining techniques. The goal is to discover user interaction patterns, and respond by making decisions based on adaptive rules centred on captured user profiles. The approach applies semantic annotation of activity logs within the learning process in order to discover patterns automatically by means of semantic reasoning. Therefore, our proposed approach is grounded on Semantic modelling and process mining techniques. To this end, it is possible to apply effective reasoning methods to make inferences over a Learning Process Knowledge-Base that leads to automated discovery of learning patterns or behaviour.
Photometric modelling of real-world objects

This paper presents a method to model the photometric properties of real-world objects from single-view and calibrated multiview image sets. Lights are modelled as point sources and reflection properties are modelled using the isotropic Ward reflectance model. Lighting and reflectance are simultaneously recovered using known geometry. Measured reflectance data and model results are presented along with rendered scenes generated using the photometric models. The rendered images compare closely to the original images with the colours, positions of shadows and highlights accurately reproduced.
A modular inspection robot platform for power plant applications

This paper presents a novel approach for a modular robotic platform to support power plant inspection. In a first part the paper gives an overview over the challenges and benefits of robotic inspection on power generation equipment. The industry requirements are presented and discussed on a general level. The second part of the paper focus on the modular platform itself. The overall modular architecture is described and the various robotic modules with the various design features are presented and discussed. Based on the modular architecture a local navigation and control system is introduced providing the details on the architecture, the sensors used and the different algorithms implemented. At the example of a volumetric non destructive inspection of steam turbine rotor shafts and the inspection of electro static precipitators the variety of possible system configurations is presented. The paper closes with a brief discussion of the results achieved.
EMPIRICAL INVESTIGATION ON COGNITIVE USER INTERFACE DIMENSIONS

In line to the introduction of the online museum, a user interface is a new medium to allow museum collections to be exhibited and promoted more effectively. For promoting purposes, this paper stresses on usability of the interface design. It is critical to pay attention to the cognitive design and ensure that the interface is usable in order to help users understand the displayed information. The user interface design for online museum has commanded significant attention from designers and researchers but lacks in the cognitive design perspective. In the effort to formalize the design, this paper is the extension of the initial work on a user interface design dimensions. The individual differences approach is adopted to explore possible user interface design elements. This study also validates the dimensions by conducting empirical investigation. The investigation is to test the hypotheses linkage between cognitive styles and user interface dimensions. The research method involves using Field Dependent and Field Independent as the case study and webbased survey on online museum visitors. The result of the analysis suggests cognitive styles do influence user interface dimensions. These design dimensions contain the implications for cognitive design of user interface development, and the identification of cognitive design of user interface for cultural website. The effort may contribute towards increasing the usability level of the website.
From Placenta to Polycystic Ovarian Syndrome: The Role of Adipokines

Adipokines are cytokines produced mainly by adipose tissue, besides many other tissues such as placenta, ovaries, peripheral-blood mononuclear cells, liver, muscle, kidney, heart, and bone marrow. Adipokines play a significant role in the metabolic syndrome and in cardiovascular diseases, have implications in regulating insulin sensitivity and inflammation, and have significant effects on growth and reproductive function. The objective of this review was to analyze the functions known today of adiponectin, leptin, resistin, and visfatin from placenta throughout childhood and adolescence. It is well known now that their serum concentrations during pregnancy and lactation have long-term effects beyond the fetus and newborn. With regard to puberty, adipokines are involved in the regulation of the relationship between nutritional status and normal physiology or disorders of puberty and altered gonadal function, as, for example, premature pubarche and polycystic ovarian syndrome (PCOS). Cytokines are involved in the maturation of oocytes and in the regular progression of puberty and pregnancy.
Identification of versions of the same musical composition by processing audio descriptions

Automatically making sense of digital information, and specially of music digital documents, is an important problem our modern society is facing. In fact, there are still many tasks that, although being easily performed by humans, cannot be effectively performed by a computer. In this work we focus on one of such tasks: the identification of musical piece versions (alternate renditions of the same musical composition like cover songs, live recordings, remixes, etc.). In particular, we adopt a computational approach solely based on the information provided by the audio signal. We propose a system for version identification that is robust to the main musical changes between versions, including timbre, tempo, key and structure changes. Such a system exploits nonlinear time series analysis tools and standard methods for quantitative music description, and it does not make use of a specific modeling strategy for data extracted from audio, i.e. it is a model-free system. We report remarkable accuracies for this system, both with our data and through an international evaluation framework. Indeed, according to this framework, our model-free approach achieves the highest accuracy among current version identification systems (up to the moment of writing this thesis). Model-based approaches are also investigated. For that we consider a number of linear and nonlinear time series models. We show that, although model-based approaches do not reach the highest accuracies, they present a number of advantages, specially with regard to computational complexity and parameter setting. In addition, we explore post-processing strategies for version identification systems, and show how unsupervised grouping algorithms allow the characterization and enhancement of the output of query-by-example systems such as the version identification ones. To this end, we build and study a complex network of versions and apply clustering and community detection algorithms. Overall, our work brings automatic version identification to an unprecedented stage where high accuracies are achieved and, at the same time, explores promising directions for future research. Although our steps are guided by the nature of the considered signals (music recordings) and the characteristics of the task at hand (version identification), we believe our methodology can be easily transferred to other contexts and domains.