Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolutionary Consequences of Asymmetric Dispersal Rates

We study the consequences of asymmetric dispersal rates (e.g., due to wind or current) for adaptive evolution in a system of two habitat patches. Asymmetric dispersal rates can lead to overcrowding of the “downstream” habitat, resulting in a source‐sink population structure in the absence of intrinsic quality differences between habitats or can even cause an intrinsically better habitat to function as a sink. Source‐sink population structure due to asymmetric dispersal rates has similar consequences for adaptive evolution as a source‐sink structure due to habitat quality differences: natural selection tends to be biased toward the source habitat. We demonstrate this for two models of adaptive evolution: invasion of a rare allele that improves fitness in one habitat but reduces it in the other and antagonistic selection on a quantitative trait determined by five additive loci. If a habitat can sustain a population without immigration, the conditions for adaptation to that habitat are most favorable if there is little or no immigration from the other habitat; the influence of emigration depends on the magnitude of the allelic effects involved and other parameters. If, however, the population is initially unable to persist in a given habitat without immigration, our model predicts that the population will be most likely to adapt to that habitat if the dispersal rates in both directions are high. Our results highlight the general message that the effect of gene flow upon local adaptation should depend profoundly on the demographic context of selection.
Towards an Adaptive Transport Protocol for Efficient Media Delivery over Wireless Networks

The past decade has seen tremendous research, development and usage of local and wide area wireless networks. There is now a high penetration of cell-phone usage along with the evolution of powerful new mobile platforms, smaller wireless devices, and micro-browsers for small handhelds. Many important wireless data communication standards such as 802.11 for LANs and GPRS, 3G for WANs have also materialized. With this accelerated evolution of high-speed wireless data networks, the next generation “killer applications” are expected to be multimedia based.
A broadband optical local network based on multiple wavelength and multiple RF subcarriers

The authors propose a multiwavelength local-access optical network that is capable of supporting multiple services with diverse requirements. Integral to the network is an acousto-optic tunable filter that can select multiple nonadjacent wavelengths simultaneously. The use of multiwavelength selectivity, together with subcarrier multiplexing in the electronic domain, results in simple solutions to many transmission and switching problems in a multiservice setting. An important conclusion is that multiwavelength selectivity can be used to implement many networking functions not easily realized otherwise. <<ETX>>
A Cooperative Approach for Distributed Task Execution in Autonomic Clouds

Virtualization and distributed computing are two key pillars that guarantee scalability of applications deployed in the Cloud. In Autonomous Cooperative Cloud-based Platforms, autonomous computing nodes cooperate to offer a PaaS Cloud for the deployment of user applications. Each node must allocate the necessary resources for applications to be executed with certain QoS guarantees. If the QoS of an application cannot be guaranteed a node has mainly two options: to allocate more resources (if it is possible) or to rely on the collaboration of other nodes. Making a decision is not trivial since it involves many factors (e.g. the cost of setting up virtual machines, migrating applications, discovering collaborators). In this paper we present a model of such scenarios and experimental results validating the convenience of cooperative strategies over selfish ones, where nodes do not help each other. We describe the architecture of the platform of autonomous clouds and the main features of the model, which has been implemented and evaluated in the DEUS discrete-event simulator. From the experimental evaluation, based on workload data from the Google Cloud Backend, we can conclude that (modulo our assumptions and simplifications) the performance of a volunteer cloud can be compared to that of a Google Cluster.
Classical Special Functions and Lie Groups

The classical orthogonal functions of mathematical physics are closely related to Lie groups. Specifically, they are matrix elements of, or basis vectors for, unitary irreducible representations of lowdimensional Lie groups. We illustrate this connection for: The Wigner functions, spherical harmonics, and Legendre polynomials; the Bessel functions; and the Hermite polynomials. These functions are associated with the Lie groups: the rotation group SO(3) in three-space and its covering group SU(2); the Euclidean group in the plane E(2) or ISO(2); and the Heisenberg group H4.
The Causal Relationship between Trade and FDI: Implication for India and East Asian Countries

This study tries to find the causal relationship between bilateral trade and FDI in India and East Asian countries using macroeconomic data and derive policy implications for regional integration. Since the late 2000s, Korea, Japan and Singapore’s trade and FDI with India have been rapidly increasing, but the causal relationship between trade and FDI could not be found, contrary to expectations. The relationship between trade and FDI in the US, the UK and Germany with India showed one-way or two-way causality, respectively. The estimation suggests that the causal relationship between trade and FDI in both countries could be formed by long-term economic exchange rather than a short-term surge in scale.
Heuristics for HTN Planning As Satisfiability

Classical planning is the problem of synthesizing a sequence of actions to reach the goal state starting from the initial state. Hierarchical task networks (HTNs) have been used as a guidance for solving planning problems where tasks are decomposed into subtasks. Recently, both action-based planning as well as HTNbased planning have been east as SAT. The performance of planning as SAT has been hitherto remark
An Empirical Research into Metadata of Business Intelligence Systems

The ultimate goal of Business Intelligence (BI) initiative is to deliver data in the most appropriate way for making informed business decisions. To attain this goal, metadata for end users plays a critical role in understanding the data provided by a BI system. However, there has been little empirical research about the metadata issues impacting the implementation of BI systems. In particular, such critical questions as „why does BI need metadata? ‟ and „What metadata does BI need? ‟ have not been investigated in depth. Answers to these questions are explored in an action research undertaken in a large university in Australia. The findings of semistructured interviews show that success of a BI system relies more on the metadata for business users than on technical metadata. As a result, a business-users-oriented metadata solution on object and element level has been developed to improve the users‟ satisfaction. The main issues that were found during the implementation process are also discussed. The research findings in conjunction with the conclusion of the study may help BI stakeholders in identifying the critical metadata needs required for a more optimised BI deployment. It also may assist BI vendors in improving the business-side metadata which are crucial for a successful BI endeavour.
Family Protective Factors as the Basis for Helping Children With Special Needs Increasing Resilience

The number of children with special needs which tend to increase have not been followed by the enhancement on people's knowledge and understanding on their developmental characteristics. Discrimination upon these children come not only from other people in their environment but also often from their own families. In this stressful situation, they are possibly having a lot of difficulties in following educational program and enhancing their academic, social and other life skills. The important aspect that makes some of them adaptive in facing adversity or stressful condition is resilience. The aim of this study was describing family protective factors that can be used as the basis for helping children with special needs increasing their resilience. This study used qualitative approach. Participants consist of four families that have child with special needs. All of those families reside in Surabaya. Data were collected through interview with each family member, observation with general guidance and field notes. Thematic analysis was used as data analysis technique. Eight protective factors found as the result of this study: (1) Family independence; (2) Patience and sincerity in experiencing the problems; (3) The persistence; (4) Positive communication; (5) Togetherness and support among family member; (6) Other social support; (7) Activeness in accessing information and openness to situational changes; (8) Similarity positive respond between parents. The paper concludes with a discussion of these findings, as well as explanation about steps that can be taken by parents in strengthening the protective factors, which will support childrens with special needs to increase their resilience.
Dynamically variable negative stiffness structures

A novel active structure supports loads while dynamically and continuously changing stiffness by more than 100× in less than 10 ms. Variable stiffness structures that enable a wide range of efficient load-bearing and dexterous activity are ubiquitous in mammalian musculoskeletal systems but are rare in engineered systems because of their complexity, power, and cost. We present a new negative stiffness–based load-bearing structure with dynamically tunable stiffness. Negative stiffness, traditionally used to achieve novel response from passive structures, is a powerful tool to achieve dynamic stiffness changes when configured with an active component. Using relatively simple hardware and low-power, low-frequency actuation, we show an assembly capable of fast (<10 ms) and useful (>100×) dynamic stiffness control. This approach mitigates limitations of conventional tunable stiffness structures that exhibit either small (<30%) stiffness change, high friction, poor load/torque transmission at low stiffness, or high power active control at the frequencies of interest. We experimentally demonstrate actively tunable vibration isolation and stiffness tuning independent of supported loads, enhancing applications such as humanoid robotic limbs and lightweight adaptive vibration isolators.
MEMS Gyro Denoising Based on Second Generation Wavelet Transform

In order to improve the precision of MEMS gyro, the MEMS gyro denoising method based on second generation wavelet transform is investigated in this paper. After introducing the principles and establishment of the second generation wavelet transform, a wavelet thresholding de-noising method based on the lifting scheme wavelet transform is used to remove the random drift of three axis MEMS gyro. The denoisng method we used showed good performance in speed and a little better precision compared to conventional wavelet thresholding schemes. The experimental results and analysis indicate that the lifting denoising can effectively reduce the random drift error of MEMS gyro and can be used in real time system.
SHEF-Multimodal: Grounding Machine Translation on Images

This paper describes the University of Sheffield’s submission for the WMT16 Multimodal Machine Translation shared task, where we participated in Task 1 to develop German-to-English and Englishto-German statistical machine translation (SMT) systems in the domain of image descriptions. Our proposed systems are standard phrase-based SMT systems based on the Moses decoder, trained only on the provided data. We investigate how image features can be used to re-rank the n-best list produced by the SMT model, with the aim of improving performance by grounding the translations on images. Our submissions are able to outperform the strong, text-only baseline system for both directions
Neuromorphic analogue VLSI.

Neuromorphic systems emulate the organization and function of nervous systems. They are usually composed of analogue electronic circuits that are fabricated in the complementary metal-oxide-semiconductor (CMOS) medium using very large-scale integration (VLSI) technology. However, these neuromorphic systems are not another kind of digital computer in which abstract neural networks are simulated symbolically in terms of their mathematical behavior. Instead, they directly embody, in the physics of their CMOS circuits, analogues of the physical processes that underlie the computations of neural systems. The significance of neuromorphic systems is that they offer a method of exploring neural computation in a medium whose physical behavior is analogous to that of biological nervous systems and that operates in real time irrespective of size. The implications of this approach are both scientific and practical. The study of neuromorphic systems provides a bridge between levels of understanding. For example, it provides a link between the physical processes of neurons and their computational significance. In addition, the synthesis of neuromorphic systems transposes our knowledge of neuroscience into practical devices that can interact directly with the real world in the same way that biological nervous systems do.
Implementation of Sensor RFID: Carrying Sensor Information in the Modulation Frequency

An approach that can be used for exploiting the sensing capabilities of RF identification (RFID) is presented and formulated. In this approach, sensor information is carried through the modulation frequency of RFID. The aim of this work is to investigate the sensor concept and to characterize the sensor performance both theoretically and experimentally. Furthermore, the operation of the sensor RF parts and oscillator are described analytically, and the equations are verified by simulations and measurements. The concept is experimentally demonstrated at a single carrier frequency to test its suitability for ultra-high-frequency RFID applications, and shown to be feasible for implementing sensors that can be read across distances up to 14 m.
Photometric approach to surface reconstruction of artist paintings

We propose a method for surface reconstruction of artist paintings. In order to reproduce the appearance of a painting, including color, surface texture, and glossiness, it is essential to acquire the pixel-wise light reflection property and orientation of the surface and render an image under an arbitrary lighting condition. A photometric approach is used to estimate bidirectional reflectance distribution functions (BRDFs) and surface normals from a set of images photographed by a fixed camera with sparsely distributed point light sources. A robust and computationally less expensive nonlinear optimization algorithm is proposed that optimizes the small number of parameters to simultaneously determine all of the specular BRDF, diffuse albedo, and surface normal. The proposed method can be applied to moderately glossy surfaces without separating captured images into diffuse and specular reflections beforehand. Experiments were conducted using oil paintings with different surface glossiness. The effectiveness of the proposed method is validated by comparing captured and rendered images.
Capabilities of the UML Profile for Schedulability Performance and Time ( SPT )

The authors are performance specialists with experience in software engineering, and contributors to the definition of the performance sub-profile of the UML SPT Profile [6]. Our viewpoint is that the profile should be usable in everyday practice by software developers. We have used it in a dozen examples and have found it largely effective. Our domain is distributed systems for telecom and business, with variable (stochastic) workloads and statistical real-time performance requirements, such as a deadline for a stated percentile of response completions. However, we have also considered schedulability of more deterministic systems. Here we comment on the strengths of the Profile, and additional capabilities that could be added to the next version.
Cross layer optimization for scalable video multicast over 802.11 WLANs

Compared with unicast, video multicast over 802.11 WLANs should handle varying channel conditions of multiple users and user topology changes as well as scalability to achieve good quality for all users in the serving area. This paper analyzes error control strategies available in different layers of the network stack, including modulation and channel coding in physical layer, cross-packet Forward Error Correction (FEC), packet size optimization and scalable video coding in application layer. By combining and adapting these schemes jointly, an adaptive cross layer optimization algorithm is proposed for scalable video multicast over 802.11 WLANs. Based on a variety of criteria, improvement in overall video quality for all the targeted users can be achieved.
The contribution of C alpha-H...O hydrogen bonds to membrane protein stability depends on the position of the amide.

Structural analyses of membrane proteins reveal a large number of C(alpha)-H.O contacts between transmembrane helices, presumed to be hydrogen bonds. Recent experiments produced conflicting results for the contribution of such hydrogen bonds to membrane protein stability. An FTIR study estimated an energy of -0.88 kcal/mol for the G79-C(alpha)-H.I76-O hydrogen bond in glycophorin A, whereas a mutagenesis study showed that the A51-C(alpha)-H.T24-O(gamma) hydrogen bond does not stabilize bacteriorhodopsin. Here, we reconcile these results using molecular mechanics calculations and an implicit membrane model (IMM1). With explicit hydrogen atoms, the potential energy of the G79-C(alpha)-H.I76-O interaction in GpA ranges from -0.54 to -0.9 kcal/mol and its contribution to stability (effective energy) from -0.49 to -0.83 kcal/mol, depending on the structural model used. The average values of these quantities in GpA-like motifs are similar. In bR, the corresponding numbers for the A51-C(alpha)-H.T24-O(gamma) interaction are +0.15 and +0.32 kcal/mol. The difference results from the different arrangement of the interacting groups and specifically the position of the acceptor with respect to the C(alpha) and N atoms. This conclusion likely applies to soluble proteins as well.
Model Free Approach to Kinetic Analysis of Real-Time Hyperpolarized 13C Magnetic Resonance Spectroscopy Data

Real-time detection of the rates of metabolic flux, or exchange rates of endogenous enzymatic reactions, is now feasible in biological systems using Dynamic Nuclear Polarization Magnetic Resonance. Derivation of reaction rate kinetics from this technique typically requires multi-compartmental modeling of dynamic data, and results are therefore model-dependent and prone to misinterpretation. We present a model-free formulism based on the ratio of total areas under the curve (AUC) of the injected and product metabolite, for example pyruvate and lactate. A theoretical framework to support this novel analysis approach is described, and demonstrates that the AUC ratio is proportional to the forward rate constant k. We show that the model-free approach strongly correlates with k for whole cell in vitro experiments across a range of cancer cell lines, and detects response in cells treated with the pan-class I PI3K inhibitor GDC-0941 with comparable or greater sensitivity. The same result is seen in vivo with tumor xenograft-bearing mice, in control tumors and following drug treatment with dichloroacetate. An important finding is that the area under the curve is independent of both the input function and of any other metabolic pathways arising from the injected metabolite. This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized 13C metabolic imaging in humans, where measurement of the input function can be problematic.
Genetic Algorithm (GA) Implementation for Feature Selection in Manipuri POS Tagging

Feature selection is a major hurdle for the CRF and SVM based POS tagging. The features are of course listed which will have a very good impact with the identification of POS. Among the listed features, the feature selection is purely a manual effort with hit and trail methods among them. The best way for better output is to design a system where the system itself identifies the best combination of features. A Genetic Algorithm (GA) system is design so that the best possible combination can be sort out instead of a manual hit and trail method in feature selection. The system shows a Recall of 80.00% , Precision ( P ) of 90.43% and F-score ( F ) of 84.90% .
Multiple human tracking based on Daubechies Complex Wavelet Transform combined with histogram of templates features

In video processing, tracking objects that are in motion has attracted lot of interest of the researchers all over the world. In numerous computer vision applications, such as monitoring traffic, remote video surveillance automation, human tracking, etc, moving object detection in video sequence is the major step of knowledge extraction. In this paper, an effective human tracking system based on Daubechies Complex Wavelet Transform (DaubCxWT) combined with histogram of template is introduced. This transform is suitable to track a person in video sequences because of its approximate shift-invariance nature. Initially, DaubCxWT co-efficients associated to the person are computed. Then, in Daubechies complex wavelet domain, the energy of these co-efficients is compared to the neighbouring object, to carry out tracking in the consecutive frames. Histogram of template feature is used to extract the texture and gradient information for the human detected. Daubechies Complex Wavelet co-efficients and histogram of template features are combined to form feature vector. In order to build feature vector for every pixel in that area, the calculated co-efficients are utilised. Further, by making use of the generated feature vectors inside an adaptive search window, optimal search for the best match is performed. Search window adaption is employed to estimate the speed and direction of the person, in motion. This method has shown appreciable results.
Positive and Negative Regulation of Th17 Cell Differentiation: Evaluating The Impact of RORC2

Objective Th17 cells are known to be involved in some types of inflammations and autoimmune disorders. RORC2 is the key transcription factor coordinating Th17 cell differentiation. Thus, blocking RORC2 may be useful in suppressing Th17-dependent inflammatory processes. The aim was to silence RORC2 by specific siRNAs in naïve T cells differentiating to Th17. Time-dependent expression of RORC2 as well as IL-17 and IL-23R were considered before and after RORC2 silencing. Materials and Methods In this experimental study, naïve CD4+T cells were isolated from human cord blood samples. Cytokines TGFß plus IL-6 and IL-23 were used to polarize the naïve T cells to Th17 cells in X-VIVO 15 serum free medium. A mixture of three siRNAs specific for RORC2 was applied for blocking its expression. RORC2, IL-17 and IL-23R mRNA and protein levels were measured using qRT-PCR, ELISA and flow cytometry techniques. Pearson correlation and one-way ANOVA were used for statistical analyses. Results Significant correlations were obtained in time-dependent analysis of IL-17 and IL-23R expression in relation with RORC2 (R=0.87 and 0.89 respectively, p<0.05). Silencing of RORC2 was accompanied with almost complete suppression of IL-17 (99.3%; p<0.05) and significant decrease in IL-23R gene expression (77.2%, p<0.05). Conclusion Our results showed that RORC2 is the main and the primary trigger for upregulation of IL-17 and IL-23R genes in human Th17 cell differentiation. Moreover, we show that day 3 could be considered as the key day in the Th17 differentiation process.