Miracle-dz/UniFAR-FTUs huggingface dataset:
Altered secondary myogenesis in transgenic animals expressing the neural cell adhesion molecule under the control of a skeletal muscle alpha-actin promoter

The majority of skeletal muscle fibers are generated through the process of secondary myogenesis. Cell adhesion molecules such as NCAM are thought to be intricately involved in the cell-cell interactions between developing secondary and primary myotubes. During secondary myogenesis, the expression of NCAM in skeletal muscle is under strict spatial and temporal control. To investigate the role of NCAM in the regulation of primary-secondary myotube interactions and muscle fusion in vivo, we have examined muscle development in transgenic mice expressing the 125-kD muscle-specific, glycosylphosphatidylinositol- anchored isoform of human NCAM, under the control of a human skeletal muscle alpha-actin promoter that is active from about embryonic day 15 onward. Analysis of developing muscle from transgenic animals revealed a significantly lower number of myofibers encased by basal lamina at postnatal day 1 compared with nontransgenic littermates, although the total number of developing myofibers was similar. An increase in muscle fiber size and decreased numbers of VCAM-1-positive secondary myoblasts at postnatal day 1 was also found, indicating enhanced secondary myoblast fusion in the transgenic animals. There was also a significant decrease in myofiber number but no increase in overall muscle size in adult transgenic animals; other measurements such as the number of nuclei per fiber and the size of individual muscle fibers were significantly increased, again suggesting increased secondary myoblast fusion. Thus the level of NCAM in the sarcolemma is a key regulator of cell-cell interactions occurring during secondary myogenesis in vivo and fulfills the prediction derived from transfection studies in vitro that the 125-kD NCAM isoform can enhance myoblast fusion.
A causality based dynamic message ordering for DVEs on Wide Area Network

Due to the large message transmission latency in Distributed Virtual Environments(DVEs) on Wide Area Net-work(WAN), the effectiveness of causality consistency control of message ordering is determined by not only causal order of messages but also the real-timeness. If merely causal order is considered, the real-time property of DVEs may not be ensured because of the unlimited waiting time for the delayed messages. While if only real-timeness is emphasized, there may be too many delayed messages, which have to be discarded, to maintain the quality of causal message ordering. Therefore, a trade-off between the quality of causal order delivery and real-timeness is necessary for DVEs. In this article, a novel causality based message ordering approach is presented. In general, this new approach dynamically balances the demands of causal order delivery and real-timeness. Experiment results demonstrate the approach can enhance the quality of causality, while simultaneously keep the real-time property of DVEs.
Internet use and expatriate adjustment: understanding the degree of isolation experienced in kingdom of Saudi Arabia

Expatriate research has indicated that expatriate adjustment is a complex problem given that factors such as the influence of the spouse, cultural training/understanding, fluency in the host language and personality or emotional readiness of the expatriate are key. Considering these challenges in a culturally diverse environment such as Kingdom of Saudi Arabia (KSA) provides a setting for an interesting study. The on-going PhD study concerning how expatriates use the Internet to adapt to KSA has proposed a theoretical model derived by following Glaser's Grounded Theory Methodology (GTM). This paper will report on a specific aspect of this proposed model namely the substantive category "degree of isolation" that references the expatriates the most. In line with the principles of the GTM extant literature were surveyed when the proposed theory reached maturity. This paper describes how the theory of Sense of Community (SOC) was chosen and applied to explain how expatriates, living in compounds in KSA, make sense of the degree of isolation experienced as it addressed the multifaceted nature of isolation as defined by this study.
A Network Mechanism for the Determination of Shape-from-Texture

We propose a computational model for how the cortex discriminates shape and depth from texture. The model consists of four stages: (1) extraction of local spatial frequency, (2) frequency characterization, (3) detection of texture compression by normalization, and (4) integration of the normalized frequency over space. The model accounts for a number of psychophysical observations including experiments based on novel random textures. These textures are generated from white noise and manipulated in Fourier domain in order to produce specific frequency spectra. Simulations with a range of stimuli, including real images, show qualitative and quantitative agreement with human perception.
Real-Time Global Illumination for VR Applications

Real-time global illumination in VR systems enhances scene realism by incorporating soft shadows, reflections of objects in the scene, and color bleeding. The virtual light field (VLF) method enables real-time global illumination rendering in VR. The VLF has been integrated with the extreme VR system for real-time GPU-based rendering in a cave automatic virtual environment.
Robust Scheduling of Scientific Workflows with Deadline and Budget Constraints in Clouds

Dynamic resource provisioning and the notion of seemingly unlimited resources are attracting scientific workflows rapidly into Cloud computing. Existing works on workflow scheduling in the context of Clouds are either on deadline or cost optimization, ignoring the necessity for robustness. Robust scheduling that handles performance variations of Cloud resources and failures in the environment is essential in the context of Clouds. In this paper, we present a robust scheduling algorithm with resource allocation policies that schedule workflow tasks on heterogeneous Cloud resources while trying to minimize the total elapsed time (make span) and the cost. Our results show that the proposed resource allocation policies provide robust and fault-tolerant schedule while minimizing make span. The results also show that with the increase in budget, our policies increase the robustness of the schedule.
Information-Centric Multiaccess P2P Networks

This paper explores the performance benefits of an information-centric network which capitalizes on overlapping multiaccess for content distribution. We present our architecture which uses an enhanced BitTorrent protocol, supports multiple network accesses simultaneously, and localizes information retrieval. We employ simulation to show the gains, on one hand, in individual node performance and, and on the other, in reduced load on the inter-operator traffic. Our simulation results indicate that download durations can be reduced, on median, by 33%. More importantly, upload throughput can increase significantly by 63%, on median. Finally, we show that our system can limit inter-domain traffic through hierarchical information-centric name resolution. The evidence we present indicates that an information-centric approach can be beneficial for both end users retrieving content such as files or video streaming, and for network opera-tors.
SWIFT beginnings – exploring the effectiveness and transformative character of a Summer Writing Institute For Teachers (SWIFT)

Abstract The purpose of this article is to describe, examine, and make a case for the value of a Continuing Professional Development week-long summer institute offered to teachers from across the education continuum – from early childhood, through primary, secondary, further and higher education. At the institute participants could meet, learn and share good practice about their own writing and the teaching of writing. The institute was inspired by the United States National Writing Project model and was designed by staff of the Maynooth University Writing Centre, in partnership with the Bay Area Writing Project, University of California Berkeley, and in consultation with a range of Irish teaching and learning networks. This paper presents the background to and rationale for the institute, considers its effectiveness in terms of the model, the ‘personality’ and the impact of the summer institute, and suggests how the summer institute is transformative for participants.
Approximate Smoothing Spline Methods for Large DataSets in the Binary

We consider the use of smoothing splines in generalized additive models with binary responses in the large data set situation. Xiang and Wahba (1996) proposed using the Generalized Approximate Cross Validation (GACV) function as a method to choose (multiple) smoothing parameters in the binary data case and demonstrated through simulation that the GACV method compares well to existing iterative methods, as judged by the Kullback-Leibler distance of the estimate to the true function being tted. However, the calculation of the GACV function involves solving an n by n linear system, where n is the sample size. As the sample size increases, the calculation becomes numerically unstable and infeasible. To reduce these computational problems we propose a randomized version of the GACV function, which is numerically stable. Furthermore, we use a clustering algorithm to choose a set of basis functions with which to approximate the exact additive smoothing spline estimate, which has a basis function for every data point. Combining these two approaches, we are able to extend smoothing spline methods in the binary response case to much larger data sets without sacriicing much accuracy.
Simulation of Forest Carbon Fluxes Using Model Incorporation and Data Assimilation

This study improved simulation of forest carbon fluxes in the Changbai Mountains with a process-based model (Biome-BGC) using incorporation and data assimilation. Firstly, the original remote sensing-based MODIS MOD_17 GPP (MOD_17) model was optimized using refined input data and biome-specific parameters. The key ecophysiological parameters of the Biome-BGC model were determined through the Extended Fourier Amplitude Sensitivity Test (EFAST) sensitivity analysis. Then the optimized MOD_17 model was used to calibrate the Biome-BGC model by adjusting the sensitive ecophysiological parameters. Once the best match was found for the 10 selected forest plots for the 8-day GPP estimates from the optimized MOD_17 and from the Biome-BGC, the values of sensitive ecophysiological parameters were determined. The calibrated Biome-BGC model agreed better with the eddy covariance (EC) measurements (R2 = 0.87, RMSE = 1.583 gC·m−2·d−1) than the original model did (R2 = 0.72, RMSE = 2.419 gC·m−2·d−1). To provide a best estimate of the true state of the model, the Ensemble Kalman Filter (EnKF) was used to assimilate five years (of eight-day periods between 2003 and 2007) of Global LAnd Surface Satellite (GLASS) LAI products into the calibrated Biome-BGC model. The results indicated that LAI simulated through the assimilated Biome-BGC agreed well with GLASS LAI. GPP performances obtained from the assimilated Biome-BGC were further improved and verified by EC measurements at the Changbai Mountains forest flux site (R2 = 0.92, RMSE = 1.261 gC·m−2·d−1).
Optimality under noise: higher memory strategies for the alternating prisoner's dilemma.

The Alternating Prisoner's Dilemma is a variant of the iterated Prisoner's Dilemma in which the players alternate in the roles of actor and recipient. We searched for strategies which are "optimal" in the Alternating Prisoner's Dilemma with noise (a non-zero probability that a player's decision will be transmitted incorrectly). In order to achieve success against a variety of other strategies, a strategy must be "self-cooperating" (able to achieve mutual cooperation with its clone), "C-exploiting" (able to exploit unconditional cooperators), and "D-unexploitable" (able to resist exploitation by defectors). It must also have high evolutionary "dominance", a general measure of evolutionary performance which considers both resistance to invasion and the ability to invade other strategies. A strategy which meets these optimality criteria can evolve cooperation by invading a population of defectors and establishing a stable cooperative society. Most of the strategies commonly discussed in the Alternating Prisoner's Dilemma literature are low-memory strategies such as Tit For Tat, Pavlov, and Firm But Fair, but none of these strategies can simultaneously meet all of the optimality criteria. However, we discovered a class of higher memory "Firm Pavlov" strategies, which not only meet our stringent optimality criteria, but also achieve remarkable success in round-robin tournaments and evolutionary interactions. These higher memory strategies are friendly enough to cooperate with their clone, pragmatic enough to exploit unconditional cooperators, and wary enough to resist exploitation by defectors: they are truly "optimal under noise" in the Alternating Prisoner's Dilemma.
Training Ternary Neural Networks with Exact Proximal Operator

In this paper, we propose a stochastic proximal gradient method to train ternary weight neural networks (TNN). The proposed method features weight ternarization via an exact formula of proximal operator. Our experiments show that our trained TNN are able to preserve the state-of-the-art performance on MNIST and CIFAR10 benchmark datesets.
PROXIMUS: a framework for analyzing very high dimensional discrete-attributed datasets

This paper presents an efficient framework for error-bounded compression of high-dimensional discrete attributed datasets. Such datasets, which frequently arise in a wide variety of applications, pose some of the most significant challenges in data analysis. Subsampling and compression are two key technologies for analyzing these datasets. PROXIMUS provides a technique for reducing large datasets into a much smaller set of representative patterns, on which traditional (expensive) analysis algorithms can be applied with minimal loss of accuracy. We show desirable properties of PROXIMUS in terms of runtime, scalability to large datasets, and performance in terms of capability to represent data in a compact form. We also demonstrate applications of PROXIMUS in association rule mining. In doing so, we establish PROXIMUS as a tool for preprocessing data before applying computationally expensive algorithms or as a tool for directly extracting correlated patterns. Our experimental results show that use of the compressed data for association rule mining provides excellent precision and recall values (near 100%) across a range of support thresholds while reducing the time required for association rule mining drastically.
Exploring the similarity space

Ranked queries are used to locate relevant documents in text databases. In a ranked query a list of terms is specified, then the documents that most closely match the query are returned---in decreasing order of similarity---as answers. Crucial to the efficacy of ranked querying is the use of a similarity heuristic, a mechanism that assigns a numeric score indicating how closely a document and the query match. In this note we explore and categorise a range of similarity heuristics described in the literature. We have implemented all of these measures in a structured way, and have carried out retrieval experiments with a substantial subset of these measures.Our purpose with this work is threefold: first, in enumerating the various measures in an orthogonal framework we make it straightforward for other researchers to describe and discuss similarity measures; second, by experimenting with a wide range of the measures, we hope to observe which features yield good retrieval behaviour in a variety of retrieval environments; and third, by describing our results so far, to gather feedback on the issues we have uncovered. We demonstrate that it is surprisingly difficult to identify which techniques work best, and comment on the experimental methodology required to support any claims as to the superiority of one method over another.
Efficient Banking under Interstate Branching

Nationally chartered banks will be allowed to branch across state lines beginning June 1, 1997. Whether they will depends on their assessment of the profitability of such a delivery system for their services and on their preferences regarding risk and return. The authors investigate the probable effect of interstate branching on banks' risk-return trade-off, accounting for the endogeneity of deposit volatility. If interstate branching improves the risk-return trade-off banks face, then banks that branch across state lines may choose a higher level of risk in return for higher profits. The authors find efficiency gains due to geographic diversity. Coauthors are William Lang, Loretta J. Mester, and Choon-Geol Moon. Copyright 1996 by Ohio State University Press.
The Beta Workbench: a computational tool to study the dynamics of biological systems

We introduce the Beta Workbench (BWB), a scalable tool built on top of the newly defined BlenX language to model, simulate and analyse biological systems. We show the features and the incremental modelling process supported by the BWB on a running example based on the mitogen-activated kinase pathway. Finally, we provide a comparison with related approaches and some hints for future extensions.
ECG compression using multiscale recurrent patterns with period normalization

Recently, the multidimensional multiscale parser (MMP), an algorithm based on multiscale recurrent patterns, has been used to successfully compress data from ECG signals. Their quasi-periodic nature makes them natural candidates for the use of recurrent patterns. However, as many diagnostic relevant signals are far from periodic, the characteristics of MMP are not fully exploited. We have dealt with this problem by interpolating the ECG signal so that the interval between successive heart beats becomes constant. Following that, the algorithm subtracts the average period from the interpolated signal. Simulation results show that these modifications increase the rate-distortion performance
2.12 Micron Molecular Hydrogen Emission from Circumstellar Disks Embedded in the Orion Nebula

We present narrowband images of two externally illuminated circumstellar disks embedded in the Orion Nebula. The images were taken with camera 2 of the Near-Infrared Camera and Multiobject Spectrometer (NICMOS) as part of the Hubble Space Telescope Early Release Observations program. Molecular hydrogen emission is confined to the silhouettes embedded in the objects HST 10 (182-413) and HST 17 (183-419). This emission appears to trace the surfaces of nearly edge-on circumstellar disks and is likely to be excited by the intense far-ultraviolet (FUV) radiation field produced by nearby O stars. The presence of this emission confirms that FUV radiation penetrates to the disk surface. The absence of H2 emission in the region between the ionization front and the disk surface provides evidence that this medium is predominantly atomic. Our observations constitute the first demonstration that the dense circumstellar disks embedded in the proplyds are predominately molecular. While the central star is marginally detected at 2.15 μm in HST 10, the central star of HST 17 is clearly detected.
Accelerating lemma learning using joins-DPLL ( t )

State-of-the-art satisfiability modulo theory solvers use a combination of the Davis-PutnamLogemann-Loveland (DPLL) procedure for performing Boolean search and an integration of theory solvers for identifying theory conflicts. Theory conflicts are presented as clauses over the propositional vocabulary that prune the DPLL search. This combination is often highly effective, as propositional reasoning is handled by state-of-the-art methods for propositional satisfiability, while theory solvers can be invoked incrementally as the DPLL core asserts literals. However, there are several cases where this integration misses short proofs if the short proofs require additional literals that are not part of the input. We present a method based on joins for identifying a sufficient basis of additional literals and lemmas that can speed up proof search for DPLL with theories exponentially. We then compare variants of the proposed methods with proof systems based on superposition and resolution. The theoretical result is that general formulations of joins are equivalent in succinctness to superposition and resolution.
The role of peace journalism in the deconstruction of elections and the “national question” in Nigeria

ABSTRACT Nigeria, a very fragile country, is constantly teetering towards dissolution. For several decades post-independence, the country has been plagued by protracted disputations among the diverse ethnic nationalities, which have been attributed to the inadvertent merger of the Northern and Southern protectorates in 1914 by the British colonialists. Since the merger, there has been intense unrest among the various ethnic groups with tensions for greater resource control and self-determination. The country has also witnessed the intense politicisation of religion in ways that have continued to aggravate the deepening antagonism between Christians and Muslims, further broadening already existing fault lines. The longdrawn-out bickering has led to calls for a renegotiation of the terms of cohabitation among the various ethnic nationalities; and this has given rise to the “national question”, a term used to describe the quest to review the dilemmas associated with accommodating multipleidentity communities within the framework of a single, integrated, national political system. This article argues that traditional media reportage of the “national question” in Nigeria has been more divisive than uniting. The article proposes the adoption of a peace journalism approach to reporting the “national question” to ensure that members of the various ethnic nationalities consider and value non-violent responses to conflict.
Novel Patch-Via-Spiral Resonators for the Development of Miniaturized Bandpass Filters With Transmission Zeros

A novel patch-via-spiral resonator based on the dual-metal-plane configuration is proposed and examined. With the microstrip patch on the top plane serving as a capacitor and linking to the quasi-lumped spiral inductor on the bottom plane through a connecting via, the proposed dual-plane resonator structure located on the opposite sides of the single substrate may form a miniaturized one in the printed-circuit board fabrication. By suitably combining the proposed patch-via-spiral resonators, useful coupled-resonator pairs may be constructed to simultaneously provide electric and magnetic couplings. Based on these coupled-resonator pairs, a second-order bandpass filter with multiple transmission zeros is realized without requiring either the cross-coupled path or the source-load coupling. For design purpose, the equivalent-circuit model is also derived and verified. In this study, a fourth-order patch-via-spiral bandpass filter with both good passband selectivity and miniaturized size of only 22.14 mm times5.08 mm (i.e., 0.188lambdag0times0.043lambdag0) is implemented, where lambdag0 denotes the guided wavelength of the 50-Omega microstrip line at center frequency