Miracle-dz/UniFAR-FTUs huggingface dataset:
Aromatase inhibition affects testosterone-induced masculinization of song and the neural song system in female canaries.

Songbirds have a specialized steroid-sensitive network of brain nuclei, the song system, for controlling song. Most nuclei of the song system express androgen receptors, and the sensory-motor integration nucleus High Vocal Center (HVC) alone also expresses estrogen receptors. Apart from expressing estrogen receptors in the vocal control system, songbirds are unique among birds because they have high concentrations of the estrogen-synthesizing enzyme aromatase in the neostriatum surrounding HVC. However, the role of estrogen in controlling the development of the song structure has been scarcely investigated. In this work, we show that blocking the production of estrogen during testosterone-induced song motor development in adult female canaries alters the song pattern compared to control females treated with testosterone only. These effects were correlated with inhibition of the expression of estrogen-sensitive genes, such as brain-derived nerve growth factor, in HVC. The expression of the ATP-synthase gene, an indicator of cell activity, in HVC, and the size of HVC, were not affected by the treatment. Our results provide the first example of estrogen-sensitive mechanisms controlling the structural features of adult birdsong.
Adaptive Multi-path Telecommunications Solutions for ITS

Intelligent Transport Services (ITS) applications require availability of the wireless seamless secure communications solutions with selectable services quality and wide-area coverage. There are available both public as well as private wireless data services, however, dominantly in case of public services no guaranteed data service quality is offered. Principal improvement of the service quality can be reached by dynamical selection of the best possible alternative from the available portfolio of relevant services. Efficient decision processes must be implemented in the appropriate flexible seamless routing/switching structures. Generally recommended solution has been described in series of documents generated by ISO/CEN known as CALM family of standards. In accordance to our understanding CALM architecture represents very complex attitude, however, it is demanding solution for less ambitious implementations. On the other hand CALM decision processes are limited to approach based on the Policy-based Management (PBM) principles with limited functionality and adaptability. Authors present L3 alternative solution with adaptive classifications processes applied instead of PBM ones. Such approach can be efficiently implemented specifically if there is available deep understanding of applied technologies. Requirements on the representative system performance indicators and their tolerance range should be so carefully identified. Paper includes results of authors’ laboratory study of three most widely spread data services which can be understood as basis for the “CALM ideas” based system implementations.
Title Jmjd 5 , an H 3 K 36 me 2 histone demethylase , modulates embryonic cellproliferation through the regulation of Cdkn 1 a expression . Author (

*KURAに登録されているコンテンツの利用については,著作権法に規定されている私的使用や引用などの範囲内で行ってください。 *著作権法に規定されている私的使用や引用などの範囲を超える利用を行う場合には,著作権者の許諾を得てください。 ただし,著作権者 から著作権等管理事業者(学術著作権協会,日本著作出版権管理システムなど)に権利委託されているコンテンツの利用手続については ,各著作権等管理事業者に確認してください。 Title Jmjd5, an H3K36me2 histone demethylase, modulates embryonic cell proliferation through the regulation of Cdkn1a expression. Author(s) Ishimura, Akihiko; Minehata, Ken-ichi; Terashima, Minoru; Kondoh, Gen; Hara, Takahiko; Suzuki, Takeshi Citation Development, 139: 749-759
Towards Runtime Monitoring in Real-Time Systems

In this paper we present the state of our work on runtime monitoring for real-time systems: a way to observe system behavior online without unpredictably disturbing real-time properties. We discuss generic requirements to achieve these properties wherefrom we deduce our monitoring framework architecture. We describe this architecture in detail and discuss several challenges for our implementation called Ferret. We also explain why common operating system primitives, such as message passing or system calls, should not be used for monitoring in the general case and propose a very low-intrusive alternative. We also propose a way of measuring the intrusiveness caused by monitoring. We applied our technique in different scenarios ranging from simple temporal debugging, resource requirement estimation, gaining behavioral information of peripheral hardware devices to build timing models for providing real-time capable service on top of them, up to whole-system views, such as the interaction between concurrently running system threads. Our research platform also contains a para-virtualized version of Linux that we use to run legacy applications. We discuss how to apply our framework to these components with real-time requirements being only one of several important aspects. We also show how to compare the behavior of our para-virtualized Linux kernel with the behavior of the native variant. In this work, we demonstrate how to gain a continuous whole-system view by using only Ferret sensors in all layers of our system, starting from the underlying microkernel, basic microkernel programs, real-time applications, and the para-virtualized Linux kernel, as well as Linux user-space applications.
Supercloud

Infrastructure-as-a-Service (IaaS) cloud providers hide available interfaces for virtual machine (VM) placement and migration, CPU capping, memory ballooning, page sharing, and I/O throttling, limiting the ways in which applications can optimally configure resources or respond to dynamically shifting workloads. Given these interfaces, applications could migrate VMs in response to diurnal workloads or changing prices, adjust resources in response to load changes, and so on. This article proposes a new abstraction that we call a Library Cloud and that allows users to customize the diverse available cloud resources to best serve their applications. We built a prototype of a Library Cloud that we call the Supercloud. The Supercloud encapsulates applications in a virtual cloud under users’ full control and can incorporate one or more availability zones within a cloud provider or across different providers. The Supercloud provides virtual machine, storage, and networking complete with a full set of management operations, allowing applications to optimize performance. In this article, we demonstrate various innovations enabled by the Library Cloud.
Organization learning through effective knowledge sharing in SME's: A conceptual model

The purpose of this paper is to describe the impact of individual knowledge sharing and organizational learning capability to organizational learning outcomes. Despite its major contribution to national economy, SME still faced a lot of problem that make them have a low survival rate. In this rapid changing situation, become a learning organization through effective knowledge sharing activities is a key factor in organization's survival. SME, with its unique characteristics, need a specific and suitable strategy to maintain its sustainability using knowledge sharing activity. This research proposed a conceptual model for promoting organizational learning process through effective knowledge sharing in SME's.
A systematic approximation to the neural motor control of forward, backward and lateral toe-tapping in children and adults

Title of thesis: A SYSTEMATIC APPROXIMATION TO THE NEURAL MOTOR CONTROL OF FORWARD, BACKWARD AND LATERAL TOE-TAPPING IN CHILDREN AND ADULTS Mohammad Ehsanul Karim Master of Arts in Kinesiology, 2014 Thesis directed by: Professor Jane E. Clark, Ph.D. Department of Kinesiology The neural motor control of forward, backward and lateral toe-tapping of typically developing adults, 6and 10-year-old children was investigated using the uncontrolled manifold technique. Our results indicate that the central nervous system (CNS) controls or stabilizes three functional variables (center of mass, toe and head position) by organizing the overall joint variability structure, more than the individual joints. Results reveal: (1) children control forward and backward stepping more than adults, and (2) adults’ forward stepping is more controlled than backward or lateral stepping. The relative ranking defining the approximate neural motor control of toe-tapping is: center of mass, toe and head position; indicating the CNS focuses on balance and foot placement. The observed invariance of this structure across movement phase, tap direction, and age, reinforces the idea that the CNS controls multi-directional toe-tap motion using similar neural control strategy. A SYSTEMATIC APPROXIMATION TO THE NEURAL MOTOR CONTROL OF FORWARD, BACKWARD AND LATERAL TOE-TAPPING IN CHILDREN AND ADULTS
A Local Search Algorithm for Resource Allocation for Underlaying Device-to-Device Communications

Resource allocation for Device-to-Device (D2D) communication underlaying cellular network poses new challenges in terms of interference while at the same time provides increased system sum rate. In this paper, we propose a local search based resource allocation algorithm (LORA) for allocating resource blocks to D2D devices that are shared with Long Term Evolution (LTE) cellular users. We first formulate the problem of downlink resource block (RB) allocation to D2D users from cellular users as a computationally expensive mixed integer nonlinear programming (MINLP) problem. However, as the optimal solution of an MINLP can take exponential time to compute, we propose a local search based algorithm to compute a locally optimal solution based on an initial feasible solution. We compare the obtained system sum rate from this local search algorithm with a well-known greedy heuristic based resource allocation algorithm and a random resource allocation algorithm. The simulation results show that LORA achieves an overall better system sum rate compared to the other algorithms for RB allocation while maintaining the signal quality at the cellular users and the D2D receivers.
New Bounds on the Size of Optimal Meshes

The theory of optimal size meshes gives a method for analyzing the output size (number of simplices) of a Delaunay refinement mesh in terms of the integral of a sizing function over the input domain. The input points define a maximal such sizing function called the feature size. This paper presents a way to bound the feature size integral in terms of an easy to compute property of a suitable ordering of the point set. The key idea is to consider the pacing of an ordered point set, a measure of the rate of change in the feature size as points are added one at a time. In previous work, Miller et al. showed that if an ordered point set has pacing ϕ, then the number of vertices in an optimal mesh will be O(ϕdn), where d is the input dimension. We give a new analysis of this integral showing that the output size is only θ(n+nlogϕ). The new analysis tightens bounds from several previous results and provides matching lower bounds. Moreover, it precisely characterizes inputs that yield outputs of size O(n).
Revisiting the Delta IC approach to component recovery

Component recovery supports program understanding, architecture recovery and reuse. Among the best known techniques for detection of reusable objects (related global variables and their accessor functions) is Delta-IC (Canfora et al., 1996). This paper re-visits the original approach and extends it in different ways. It describes a variant of Delta-IC suitable for reverse engineering that omits the slicing step of the original approach. The underlying metric of Delta-IC is extended toward types integrating ideas of the Internal Access technique (Yeh et al., 1995) such that abstract data types can also be detected. Furthermore, the connectivity metric of Delta-IC is combined with a cohesion metric based on vertex connectivity. The new metrics and the new algorithm for reverse engineering are quantitatively evaluated using the framework proposed in (Koschke and Eisenbarth, 2000) as a standard evaluation of clustering techniques for component recovery.
GeneSigDB: a manually curated database and resource for analysis of gene expression signatures

GeneSigDB (http://www.genesigdb.org or http://compbio.dfci.harvard.edu/genesigdb/) is a database of gene signatures that have been extracted and manually curated from the published literature. It provides a standardized resource of published prognostic, diagnostic and other gene signatures of cancer and related disease to the community so they can compare the predictive power of gene signatures or use these in gene set enrichment analysis. Since GeneSigDB release 1.0, we have expanded from 575 to 3515 gene signatures, which were collected and transcribed from 1604 published articles largely focused on gene expression in cancer, stem cells, immune cells, development and lung disease. We have made substantial upgrades to the GeneSigDB website to improve accessibility and usability, including adding a tag cloud browse function, facetted navigation and a ‘basket’ feature to store genes or gene signatures of interest. Users can analyze GeneSigDB gene signatures, or upload their own gene list, to identify gene signatures with significant gene overlap and results can be viewed on a dynamic editable heatmap that can be downloaded as a publication quality image. All data in GeneSigDB can be downloaded in numerous formats including . gmt file format for gene set enrichment analysis or as a R/Bioconductor data file. GeneSigDB is available from http://www.genesigdb. org.
Classification of fetal heart rate during labour using hidden Markov models

Intrapartum electronic fetal monitoring (EFM) is an indispensable means for fetal surveillance. However, the early enthusiasm was followed by scepticism, since the introduction of EFM in every day practise resulted in an increase in operative deliveries. Nevertheless the drawbacks of EFM relate not so much to the technique itself but more to the difficulties in reading and interpreting the fetal heart rate (FHR). In an attempt to develop more objective means to analyse the FHR recordings and compensate for the different levels of expertise among clinicians, computerized systems have been developed during the last 2 decades. In this work, we present an approach to automatic classification of FHR tracings belonging to hypoxic and normal newborns. The classification is performed using a set of parameters extracted from the FHR signal and two hidden Markov models (one for each class). The results are satisfactory indicating that the FHR convey much more information than what is conventionally used.
Chapter 14: Cancer Genome Analysis

Although there is great promise in the benefits to be obtained by analyzing cancer genomes, numerous challenges hinder different stages of the process, from the problem of sample preparation and the validation of the experimental techniques, to the interpretation of the results. This chapter specifically focuses on the technical issues associated with the bioinformatics analysis of cancer genome data. The main issues addressed are the use of database and software resources, the use of analysis workflows and the presentation of clinically relevant action items. We attempt to aid new developers in the field by describing the different stages of analysis and discussing current approaches, as well as by providing practical advice on how to access and use resources, and how to implement recommendations. Real cases from cancer genome projects are used as examples.
Direct requirement for Xmus101 in ATR-mediated phosphorylation of Claspin bound Chk1 during checkpoint signaling

TopBP1-like proteins, which include Xenopus laevis Xmus101, are required for DNA replication and have been linked to replication checkpoint control. A direct role for TopBP1/Mus101 in checkpoint control has been difficult to prove, however, because of the requirement for replication in generating the DNA structures that activate the checkpoint. Checkpoint activation occurs in X. laevis egg extracts upon addition of an oligonucleotide duplex (AT70). We show that AT70 bypasses the requirement for replication in checkpoint activation. We take advantage of this replication-independent checkpoint system to determine the role of Xmus101 in the checkpoint. We find that Xmus101 is essential for AT70-mediated checkpoint signaling and that it functions to promote phosphorylation of Claspin bound Chk1 by the ataxia-telangiectasia and Rad-3–related (ATR) protein kinase. We also identify a separation-of-function mutant of Xmus101. In extracts expressing this mutant, replication of sperm chromatin occurs normally; however, the checkpoint response to stalled replication forks fails. These data demonstrate that Xmus101 functions directly during signal relay from ATR to Chk1.
Reconstruction of Stellar Orbits Close to Sagittarius A*: Possibilities for Testing General Relativity

We have reconstructed possible orbits for a collection of stars located within 0. ″5 of Sgr A*. These orbits are constrained by observed stellar positions and angular proper motions. The construction of such orbits serves as a baseline from which to search for possible deviations due to the unseen mass distribution in the central 1000 AU of the Galaxy. We also discuss the likelihood that some of these stars may eventually exhibit detectable relativistic effects, allowing for interesting tests of general relativity around the 2.6 × 106 M☉ central object.
Kinetic Analysis of Ligand-Receptor Complex Formation with the Aid of Computer Simulation

Cellular signal transduction is initiated by the binding of extracellular ligands to membrane receptors. However, the concentration of ligand required for cellular activation is often lower than that required for receptor binding; receptors are often expressed in excess. To elucidate the physiological significance of this phenomenon, we have developed a Monte Carlo simulation program for kinetic analysis of ligand-receptor formation. Our present simulation showed that an excess amount of the receptors was not required for signal activation when the dissociation constant (Kd) of the ligand-receptor complex (LR) was low (10~9 or less). However, a low Kd value caused delayed LR dissociation after clearance of ligand from the extracellular space; no signal shutdown took place. These data indicate that an excess amount of receptors with high Kd (10~8 or more) was required for prompt signal propagation at physiological ligand concentrations and rapid signal cessation following ligand clearance. Our simulations were conducted using a conventional personal computer with a CPU running at 2.6 GHz under Windows XP or 2000 operating systems, and single simulation runs typically took less than two hours. Our simulation program could be readily implemented for kinetic analysis of any signal transduction system with various parameters, and could be used by any investigator because special computing hardware and training are not required.
Somatosensory Processing of the Tongue in Humans

We review research on somatosensory (tactile) processing of the tongue based on data obtained using non-invasive neurophysiological and neuroimaging methods. Technical difficulties in stimulating the tongue, due to the noise elicited by the stimulator, the fixation of the stimulator, and the vomiting reflex, have necessitated the development of specialized devices. In this article, we show the brain activity relating to somatosensory processing of the tongue evoked by such devices. More recently, the postero-lateral part of the tongue has been stimulated, and the brain response compared with that on stimulation of the antero-lateral part of the tongue. It is likely that a difference existed in somatosensory processing of the tongue, particularly around primary somatosensory cortex, Brodmann area 40, and the anterior cingulate cortex.
A New Sparsity-Based Band Selection Method for Target Detection of Hyperspectral Image

Band selection (BS) plays an important role in the dimensionality reduction of hyperspectral data. However, as to the existing BS methods, few are specially designed for target detection. In this letter, we combine the target detection and BS process together and put forward a new BS method for target detection, named least absolute shrinkage and selection operator (LASSO)-based BS (LBS). Interestingly, by using a linear regression model with L1 regularization (LASSO model), LBS transforms the discrete BS problem into the continuous optimization problem, which cannot only avoid the complicated subset selection process but also evaluate the importance of all the bands simultaneously. The experiments on real hyperspectral data demonstrate that LBS is a very effective BS method for target detection.
An Architectural Modeling Approach with Symmetric Alignment of Multiple Concern Spaces

Architectural modeling identifies several concerns in problem domain and associates them with design decisions in solution domain. There is, however, no commonsense on how to localize problem domain concerns and relate them to the solution domain. This paper proposes a modeling approach to address the architectural concerns in multiple concern spaces both for problem and solution domains, and align them "symmetrically". This approach identifies the problem domain in multiple concern spaces by correlating the "architectural aspects" and "quality attributes". The solution domain is likewise identified in other multiple concern spaces by correlating the "multi-views" and "multi-tiers" of architectures. Symmetric alignment is used here for the correlation between separate concern spaces instead of mapping individual concerns from problem to solution domain. The paper claims that this alignment helps identifying architectural components, connectors and properties in the solution domain.
Tree Adaptive A

Incremental heuristic search algorithms can solve sequences of similar search problems potentially faster than heuristic search algorithms that solve each search problem from scratch. So far, there existed incremental heuristic search algorithms (such as Adaptive A*) that make the h-values of the current A* search more informed, which can speed up future A* searches, and incremental heuristic search algorithms (such as D* Lite) that change the search tree of the current A* search to the search tree of the next A* search, which can be faster than constructing it from scratch. In this paper, we present Tree Adaptive A*, which applies to goal-directed navigation in unknown terrain and builds on Adaptive A* but combines both classes of incremental heuristic search algorithms in a novel way. We demonstrate experimentally that it can run faster than Adaptive A*, Path Adaptive A* and D* Lite, the top incremental heuristic search algorithms in the context of goal-directed navigation in unknown grids.
A Microstrip Antenna Array for Indoor Wireless Dynamic Environments

A planar microstrip antenna array with a Butler matrix has been implemented to form a microstrip antenna array that has narrow beamwidth, circular polarization, and polarization diversity. This microstrip antenna array improves the system performance in indoor wireless dynamic environments. A circularly polarized microstrip antenna array is designed such that it consists of four identical linearly polarized patches. A 2 times 2 planar microstrip antenna array and a 4 times 4 Butler matrix have been designed and simulated using advanced design system and Matlab software. The measured results show that a combination of a planar microstrip antenna array and a 4 times 4 Butler matrix creates four beams; two of these beams have right-hand circular polarization and the other two have left-hand circular polarization.
KESAHAN DAN KEBOLEHPERCAYAAN DALAM KAJIAN KUALITATIF

Artikel ini akan menfokuskan kepada definisi kesahan dan kebolehpercayaan serta tujuan utama pelasaksanaan kedua-duanya dalam penyelidikan kualitatif. Seterusnya, tulisan ini akan menjelaskan bentuk-kesahan dan kebolehpercayaan yang boleh dilaksanakan dalam penyelidikan kualitatif dengan mengambil contoh daripada kajian terhadap guru yang dilakukan oleh penulis.