Miracle-dz/UniFAR-FTUs huggingface dataset:
A Transfer Learning Approach for Automated Segmentation of Prostate Whole Gland and Transition Zone in Diffusion Weighted MRI

The segmentation of prostate whole gland and transition zone in Diffusion Weighted MRI (DWI) are the first step in designing computer-aided detection algorithms for prostate cancer. However, variations in MRI acquisition parameters and scanner manufacturing result in different appearances of prostate tissue in the images. Convolutional neural networks (CNNs) which have shown to be successful in various medical image analysis tasks including segmentation are typically sensitive to the variations in imaging parameters. This sensitivity leads to poor segmentation performance of CNNs trained on a source cohort and tested on a target cohort from a different scanner and hence, it limits the applicability of CNNs for cross-cohort training and testing. Contouring prostate whole gland and transition zone in DWI images are time-consuming and expensive. Thus, it is important to enable CNNs pretrained on images of source domain, to segment images of target domain with minimum requirement for manual segmentation of images from the target domain. In this work, we propose a transfer learning method based on a modified U-net architecture and loss function, for segmentation of prostate whole gland and transition zone in DWIs using a CNN pretrained on a source dataset and tested on the target dataset. We explore the effect of the size of subset of target dataset used for fine-tuning the pre-trained CNN on the overall segmentation accuracy. Our results show that with a fine-tuning data as few as 30 patients from the target domain, the proposed transfer learning-based algorithm can reach dice score coefficient of 0.80 for both prostate whole gland and transition zone segmentation. Using a fine-tuning data of 115 patients from the target domain, dice score coefficient of 0.85 and 0.84 are achieved for segmentation of whole gland and transition zone, respectively, in the target domain.
Inference for the stochastic block model with unknown number of blocks and non-conjugate edge models

The stochastic block model (SBM) is a popular model for capturing community structure and interaction within a network. There is increasingly a range of network data with non-binary edges becoming commonplace. However, existing methods for inferring parameters of an SBM are commonly restricted to models for edges which yield a conjugate prior distribution. This paper introduces an effective reversible jump Markov chain Monte Carlo sampler for estimating the parameters and the number of blocks for a general network model allowing for a non-conjugate prior distribution on the edge model.
Visual Orbits of Spectroscopic Binaries with the CHARA Array. II. The Eclipsing Binary HD 185912

We present the visual orbit of the double-lined eclipsing binary, HD 185912, from long baseline interferometry with the CHARA Array. We also obtain echelle spectra from the Apache Point observatory to update the spectroscopic orbital solution and analyze new photometry from Burggraaff et al. to model the eclipses. By combining the spectroscopic and visual orbital solutions, we find component masses of M1 = 1.361 ± 0.004 M⊙ and M2 = 1.331 ± 0.004 M⊙, and a distance of d = 40.75 ± 0.30 pc from orbital parallax. From the light-curve solution, we find component radii of R1 = 1.348 ± 0.016 R⊙ and R2 = 1.322 ± 0.016 R⊙. By comparing these observed parameters to stellar evolution models, we find that HD 185912 is a young system near the zero age main sequence with an estimated age of 500 Myr.
The Nature of Class I Sources: Periodic Variables in Orion

We present a quantitative, empirically based argument that at least some Class I sources are low-mass, pre-main-sequence stars surrounded by spatially extended envelopes of dusty gas. The source luminosity arises principally from stellar gravitational contraction, as in optically visible pre-main-sequence stars that lack such envelopes. We base our argument on the fact that some Class I sources in Orion and other star-forming regions have been observed by Spitzer to be periodic variables in the mid-infrared, and with periods consistent with T Tauri rotation rates. Using a radiative transfer code, we construct a variety of dust envelopes surrounding rotating, spotted stars, to see whether an envelope that produces a Class I spectral energy distribution at least broadly matches the observed modulations in luminosity. Acceptable envelopes can be either spherical or flattened and may or may not have polar cavities. The key requirement is that they have a modest equatorial optical depth at the Spitzer waveband of 3.6 μm, typically τ3.6 ≈ 0.6. The total envelope mass, based on this limited study, is at most about 0.1 M⊙, less than a typical stellar mass. Future studies should focus on the dynamics of the envelope, to determine whether material is actually falling onto the circumstellar disk.
A lower semicontinuity result for linearised elasto-plasticity coupled with damage in $W^{1,\gamma}$, $\gamma>1$

We prove the lower semicontinuity of functionals of the form \[ \int \limits_\Omega \! V(\alpha) \, \mathrm{d} |\mathrm{E} u| \, , \] with respect to the weak converge of $\alpha$ in $W^{1,\gamma}(\Omega)$, $\gamma > 1$, and the weak* convergence of $u$ in $BD(\Omega)$, where $\Omega \subset \mathbb{R}^n$. These functional arise in the variational modelling of linearised elasto-plasticity coupled with damage and their lower semicontinuity is crucial in the proof of existence of quasi-static evolutions. This is the first result achieved for subcritical exponents $\gamma < n$.
Natural Language Processing via LDA Topic Model in Recommendation Systems

Today, Internet is one of the widest available media worldwide. Recommendation systems are increasingly being used in various applications such as movie recommendation, mobile recommendation, article recommendation and etc. Collaborative Filtering (CF) and Content-Based (CB) are Well-known techniques for building recommendation systems. Topic modeling based on LDA, is a powerful technique for semantic mining and perform topic extraction. In the past few years, many articles have been published based on LDA technique for building recommendation systems. In this paper, we present taxonomy of recommendation systems and applications based on LDA. In addition, we utilize LDA and Gibbs sampling algorithms to evaluate ISWC and WWW conference publications in computer science. Our study suggest that the recommendation systems based on LDA could be effective in building smart recommendation system in online communities.
Rate Control for Wireless-Powered Communication Network With Reliability and Delay Constraints

We consider a two-phase Wireless-Powered Communication Network under Nakagami-m fading, where a wireless energy transfer process first powers a sensor node that then uses such energy to transmit its data in the wireless information transmission phase. We explore a fixed transmit rate scheme designed to cope with the reliability and delay constraints of the system while attaining closed-form approximations for the optimum wireless energy transfer and wireless information transmission blocklength. Then, a more-elaborate rate control strategy exploiting the readily available battery charge information is proposed and the results evidence its outstanding performance when compared with the fixed transmit rate, for which no battery charge information is available. It even reaches an average rate performance close to that of an ideal scheme requiring full Channel State Information at transmitter side. Numerical results show the positive impact of a greater number of antennas at the destination, and evidence that the greater the reliability constraints, the smaller the message sizes on average, and the smaller the optimum information blocklengths. Finally, we corroborate the appropriateness of using the asymptotic blocklength formulation as an approximation of the non-asymptotic finite blocklength results.
Morphological Differentiation Between Isolated Populations of Caspian spirlin ( Alburnoides eichwaldii ) ( Pisces : Cyprinidae ) Affected by Dam

A 12-landmark morphometric truss network system and 12 meristic characters were used to investigate the hypothesis differentiation of Alburnoides eichwaldii populations in upstream and downstream of the Shahid-Rajaei dam on the Tajan River, one of the most important habitats for the species in the southern Caspian Sea region. Analysis of variance showed significant differences between the two groups of 16 out of 67standardized measurement in truss and 5 out of 16meristic. Discriminant function analysis, proportion of individuals was correctly classified into their original groups as 79% and 78.0% for truss and meristic, respectively. The spirlin populations occupied different areas on canonical variates analysis scatter plot. Cluster analysis based on Euclidean distances among groups of centroids using UPGMA did not separate the two populations. Principal Component analysis separated the groups into distinct populations; though there was moderate overlap between two localities. The results of this survey demonstrated that Shahid-Rajaee dam could effectively create two morphologically different populations upstream and downstream of the dam. Also, this differentiation showed higher in morphometric measurements than meristic traits.
THE INFLUENCE OF POTASSIUM ON CONTENT OF TOTAL POLYPHENOLS AND ANTIOXIDANT ACTIVITY OF ONION ( ALLIUM CEPA L . )

Potassium (K) is an essential plant nutrient which is influencing on plant metabolism, plant growth, development of the crops quality and crop yield. The present study was aimed to evaluate the influence of the potassium on the content of the total polyphenols and antioxidant activity on the onion (Allium cepa L.) variety Mundo. The content of the total polyphenols was determined by using the Folin-Ciocalteu reagent (FCR) according to Lachman et al. (2003), who was found that the content of polyphenols in his study were (273.51±21.00 to 722. 15±30.01 mg. kg). At the end of the study we concluded statistically that the addition potassium in soil had a positive effect between the content of the potassium in the soil and the content of the total polyphenols on the onion, which was led an increase total polyphenols (P-value=2. 17.10). On the other hand we found that an the addition the potassium in the soil had negative between the potassium content and values of antioxidant activity on the free radical (DPPH) for onion plant.
econstor Make Your Publications Visible . A Service of zbw

This paper examines how changes in radio station ownership have affected music variety and station listenership. A unique panel dataset of music radio airplay shows that a common owner of stations in the same local radio market and the same broad music category increases the degree of differentiation between these stations, consistent with only a common owner internalizing “business stealing” effects. The implied effect on playlists is quite large and is not captured by changes in stations’ formats. Common ownership of stations in the same category but different local markets results in, at most, a small degree of playlist homogenization. Panel data on station listenership provides further support for the business stealing explanation, as when stations in a local market become commonly owned their audiences tend to increase.
Pyramidal Objects and Comparing Objects Using Similarity Measures

In the paper the problems of objects similarity measures and detection of similarity of objects are addressed. Currently, when using the object-based representation and object oriented approaches we frequently meet the problem of object similarity. This problem spans many different application domains in which it is necessary to apply decision making process. Given a pair of objects, it is of interest to know how they are related to each other. Similarity measures can be used in many types of data retrieval, data mining and many analysis tasks. Very often we can group the objects of a given application into clusters based on their similarity values. Sophisticated methods use multiple levels of objects in the frame of one task and different types of similarity: attribute, correlation or behaviour based similarity measures. Keywords—Associated objects, pyramidal objects, object-based representation, similarity measures.
Bioluminescent and fluorescent reporters in circadian rhythm studies

Various organisms create fascinating “glow-in-the-dark” proteins in nature. Scientists introduce these special proteins into organisms that they study and use the emitted light to report where, when, and how much genes or proteins of interest are expressed. Two major kinds of reporters, luciferases and fluorescent proteins, are often confused with each other because they have common characteristics: (1) they can be used to make it easy to track the expression of genes or proteins of interest by fusing a reporter gene to a gene of interest (genetically encoded reporters), and (2) they glow in the dark. However, there are fundamental differences between these reporters. Generally, luciferases, which catalyze a reaction with a substrate luciferin and generate light as a product (bioluminescence), are dim, but highly quantitative reporters and suitable to measure how much and when a gene or protein is expressed. Fluorescent proteins, which require an external light source to stimulate emission of a different wavelength of light, are bright reporters and suitable to locate in which cells a gene is activated or where in a cell a protein is expressed. In this review, we introduce basic mechanisms of bioluminescence and fluorescence, and how they are used in circadian rhythm research. Entry Level Intermediate Level Advanced Level Mechanisms to glow in the dark As you study biological science, you encounter experiments using “bioluminescence” and “fluorescence. ” Both bioluminescence and fluorescence appear as specimens glowing in the dark. However, the light is generated by different mechanisms. Bioluminescence is generated by chemical reactions, whereas fluorescence is the re-emission of transformed light that was absorbed by a substance at a different wavelength. In other words, bioluminescence can glow by itself like stars, but fluorescence needs an external light source to glow, like the moon needs the sun to shine. In this section, we will introduce the mechanisms that generate bioluminescence and fluorescence.
Learning segmentations that balance latency versus quality in spoken language translation

Segmentation of the incoming speech stream and translating segments incrementally is a commonly used technique that improves latency in spoken language translation. Previous work (Oda et al. 2014) [1] has explored creating training data for segmentation by finding segments that maximize translation quality with a user-defined bound on segment length. In this work, we provide a new algorithm, using Pareto-optimality, for finding good segment boundaries that can balance the trade-off between latency versus translation quality. We compare against the state-of-the-art greedy algorithm from (Oda et al. 2014) [1]. Our experimental results show that we can improve latency by up to 12% without harming the BLEU score for the same average segment length. Another benefit is that for any segment size, Paretooptimal segments maximize latency and translation quality.
Productivity and Efficiency Change in the Australian Broadacre Agriculture : Nonparametric Estimates

This paper uses distance functions estimation methods to compute and decompose FärePrimont indexes of total factor productivity of Australian broadacre agriculture. FärePrimont indexes have some distinguishing features that make them more superior than others. First, they satisfy all basic index number axioms that are economically relevant. Secondly, they can be exhaustively decomposed into different meaningful measures of technical change and efficiency change without having any residual effects. Third, quantities data only can be used to compute the indexes, i.e. price data are not mandatory to compute the indexes. Using state level data from 1990 to 2011, this study provides few useful insights into estimates of productivity and efficiency change in broadacre agriculture. This study finds decline in technical possibilities as the main drivers of low productivity in broadacre agriculture in Australia. It also finds that the states are highly technically efficient. As a result, the scale and mix efficiency change has become the main driver of efficiency improvement. Kew Words: Total Factor Productivity; Färe-Primont Index; Technical Efficiency; Mix Efficiency; Scale Efficiency; Distance Function; Broadacre Agriculture; Australia
COMPARISON OF SATURATED-UNSATURATED SHEAR STRENGTH AND HYDRAULIC CONDUCTIVITY BEHAVIOR OF A COMPACTED SANDY-CLAY TILL

Compacted fine-grained soils are commonly used in the construction of soil structures. Several factors such as void ratio, soil structure (aggregation), “initial” moulding water content, and stress state influence the properties of these saturated and unsaturated soils. Test results of statically compacted specimens of a fine-grained soil at three different “initial” water contents are presented. The data include saturated shear strength parameters, saturated coefficient of permeability, and soil-water characteristic curves. The coefficient of permeability and shear strength of the soil in its unsaturated state are predicted using the saturated soil properties and the soil-water characteristic curve. The parameters influencing the behavior of the saturatedunsaturated soil with respect to the coefficient of permeability and shear strength are presented and discussed in this paper.
Embedded System for a Sailing Robot based on FPGA Sonali .

This paper proposed an embedded HW/SW implementation for the computing system of a small scale without human autonomous sailing boat. The system is integrated in a mono XILINX FPGA, and hosts a Microblaze soft processor surrounded with mixed, custom designed, control and processing modules than handle the interface with all the sensors, actuators and communication devices of the sailing boat. These interfacing modules implement tasks that have been decentralized from the master processor, thus alleviating its computational load and providing processing time for upper level software applications. Using FPGA to implement an integrated single-chip computing system, as an alternative to conventional processors, has proven to be a very flexible solution as it eases the migration of computation tasks between the hardware and software domains, and more importantly, allowing the rapid adaptation of the digital interfacing hardware in order to support additional peripheral devices required for an application mission. The software component of the boat’s control system runs on the top of the uClinux embedded operating system and is formed by various concurrent applications developed in C with the standard Linux libraries. Remote monitoring, configuration and operation of the sailing boat is done via a WiFi link, using a graphics interactive application that runs on a conventional PC. For this paper reference of paper "An FPGA-based Embedded System for a Sailing Robot" by José C. Alves and Nuno A. Cruz from Faculty of Engineering University of Porto Porto, Portugal is been taken.
Hyperrhiz: New Media Cultures

Human mental activities such as memories, reveries, and daydreams are important aspects of our experiences and literary productions. In the emerging area of computer-generated narratives, however, the subjects of preconscious and subconscious inner thought are rarely tackled because the subjective and affective natures of such phenomena are difficult, and perhaps not possible, to pin down in terms of traditional computer science and artificial intelligence (AI). This paper calls attention to underlying parallels and synergies between stream of consciousness literature, cognitive linguistics, and AI. In this historical moment, we propose that concerns of modernist writers regarding inner thought have been reinvigorated in light of these contemporary cognitive scientific developments regarding preconscious conceptualization. Specifically, we present our computational narrative project Memory, Reverie Machine (MRM), which explores how to generate stories about artificial memories, reveries, and daydreams with AI and conceptual blending techniques. Our work exemplifies a new form that can leverage AI technologies for expressive narrative without being burdened by their philosophical baggage or implicit aesthetic dictates.
Advances in Global Leadership Emerald Book Chapter: Understanding proactive leadership

This chapter discusses proactive leadership by elaborating the meaning of leaders’ proactivity, the required competencies of proactive leadership, and the potentially different evaluations of leaders’ proactivity by different observers, including leaders themselves, their supervisors, peers, and subordinates. Specifically, based on the goal generation – goal striving process view of proactivity, we define leaders’ proactivity as ‘‘generating and enacting self-initiated and future-focused leading actions that are persistently sustained to bring changes toward the environment. ’’ In line with the process view, we also propose the competency requirement of proactive leadership, by benchmarking against a scientifically developed, comprehensive competency dictionary, the Universal Competency Framework (UCF). Finally, we discuss the possibility that leaders’ proactivity can be observed and evaluated differently by raters at different positions. Overall, this chapter provides a conceptual analysis of proactive leadership and points to potential research directions subject to empirical investigation.
PATHFINDER: Graph-Based Itemset Embedding for Learning Course Recommendation and Beyond

We demonstrate a tool, named as PATHFINDER, that captures and visualizes rich latent relationships among courses as a graph, mines students' past course performance data, and recommends pathways or top-k courses most helpful to a given student, using an itemset embedding based learning model. With dedicated design for the asymmetric, non-additive and non-negative challenges specific to the problem, our model for helpfulness achieves the best performance among competing models. We demonstrate the visualization of four course relationships (e.g., mandatory, prerequisite, helpful, and top-k) in a graph. The PATHFINDER demo is publicly available at: http://140.82. 60.177:8000
The determinants of subjective measurement of performance : A longitudinal empirical study

The study examines the determinants of the implementation of a branch sales manager incentive system with multiple performance measures. We specifically examine the following question: What are the determinants of subjective measurement of performance in bonus determination? Our research examines these relationships with proprietary data from a Chinese manufacturer with 28 sales branches using a multi period experimental context (5 successive years of changes in the incentive scheme – 1998, 1999, 2000, 2001 and 2002). The results using a longitudinal method design provide a unique contribution to the management control literature. PDF created with pdfFactory Pro trial version www.pdffactory. com 1 The determinants of subjective measurement of performance: A longitudinal empirical study