Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality-aware swarm-based optimal multi-user video streaming rate capacity in congested wireless networks

Due to alarming increase in video traffic over wireless network, there is a dramatic need to optimally support real-time video applications in order to provide the quality-of-service (QoS) needed from different users and applications with different users requirement. A low complexity quality-aware swarm-based mathematical model has been formulated and developed which is aware of the time-varying channel condition to support video streaming. In this paper, a quality-aware swarm-based scheme is proposed to solve the video streaming rate optimization problem in a congested wireless network and it primarily uses the fundamental principle of particle swarm optimization (PSO). The optimal streaming rate scheme is used to dynamically adjust the resources based on the quality-aware algorithm to provide the necessary QoS among users. The proposed swarm-based optimal video streaming rate controlled algorithm outperforms rate distortion optimization (RDO) and traditional (conventional) approaches in terms of perceived video quality and ultimately it has been constantly maintained. The performance of the developed scheme has been verified using experimental simulation and its highly effective for streaming rate control application in congested wireless networks.
Evolution of Large‐Scale Magnetic Fields From Near‐Earth Space During the Last 11 Solar Cycles

We use hourly mean magnetic field measurements from 34 midlatitude geomagnetic observatories between 1900 and 2015 to investigate the long‐term evolution and driving mechanism of the large‐scale external magnetic field at ground. The Hourly Magnetospheric Currents index (HMC) is derived as a refinement of the Annual Magnetospheric Currents index (HMC, Pick & Korte, 2017, https://doi.org/10.1093/gji/ggx367). HMC requires an extensive revision of the observatory hourly means. It depends on three third party geomagnetic field models used to eliminate the core, the crustal, and the ionospheric solar‐quiet field contributions. We mitigate the dependency of HMC on the core field model by subtracting only nondipolar components of the model from the data. The separation of the residual (dipolar) signal into internal and external (HMC) parts is the main methodological challenge. Observatory crustal biases are updated with respect to AMC, and the solar‐quiet field estimation is extended to the past based on a reconstruction of solar radio flux (F10.7). We find that HMC has more power at low frequencies (periods ≥ 1 year) than the Dcx index, especially at periods relevant to the solar cycle. Most of the slow variations in HMC can be explained by the open solar magnetic flux. There is a weakly decreasing linear trend in absolute HMC from 1900 to present, which depends sensitively on the data rejection criteria at early years. HMC is well suited for studying long‐term variations of the geomagnetic field.
Differentiation between two‐state and multi‐state folding proteins based on sequence

Prediction of protein‐folding rates follows different rules in two‐state and multi‐state kinetics. The prerequisite for the prediction is to recognize the folding kinetic pathway of proteins. Here, we use the logistic regression and support vector machine to discriminate between two‐state and multi‐state folding proteins. We find that chain length is sufficient to accurately recognize multi‐state proteins. There is a transition boundary between two kinetic models. Protein folds with multi‐state kinetics, if its length is larger than 112 residues. The logistic prediction from amino acid composition shows that the kinetic pathway of folding is closely related to amino acid volume. Small amino acids make two‐state folding easier, and vice versa. However, cysteine, alanine, arginine, lysine, histidine, and methionine do not conform to this rule. Proteins 2008. © 2008 Wiley‐Liss, Inc.
Policy-compliant path diversity and bisection bandwidth

How many links can be cut before a network is bisected? What is the maximal bandwidth that can be pushed between two nodes of a network? These questions are closely related to network resilience, path choice for multipath routing or bisection bandwidth estimations in data centers. The answer is quantified using metrics such as the number of edge-disjoint paths between two network nodes and the cumulative bandwidth that can flow over these paths. In practice though, such calculations are far from simple due to the restrictive effect of network policies on path selection. Policies are set by network administrators to conform to service level agreements, protect valuable resources or optimize network performance. In this work, we introduce a general methodology for estimating lower and upper bounds for the policy-compliant path diversity and bisection bandwidth between two nodes of a network, effectively quantifying the effect of policies on these metrics. Exact values can be obtained if certain conditions hold. The approach is based on regular languages and can be applied in a variety of use cases.
Transportation Infrastructure , Economic Productivity , and Geographic Scale : Aggregate Growth versus Spatial Redistribution

Recent cross-state studies of public infrastructure suggest that infrastructure is not economically productive. Yet it is possible that public capital influences economic activity Iargely by shifting that activity from one location to another. If that is the case, infrastructure can be productive at small geographic scales but not productive over large areas. This paper tests that hypothesis with a production function study of highway and road capital in California counties for the years 1969 through 1988. The results show that county output is positively associated with highway capital in the county, but negatively associated with kighway capital in neighboring counties. This suggests that the productive effects of highway capital are largely a shift in economic activity from one county to another. Acknowledgments: Gene Kim and Inha Yoon provided outstanding research assistance. John Greerdees, Douglas Holtz-Eakin, and Alicia Munnell provided data on private capital for California which were used to obtain estimates of county private capital within California. This research was supported by a grant from the U.S. and California Departments of Transpor/ation, administered through the University of California Transportation Center. I alone am responsibIe for any errors or shortcomings in the research presented here.
Improving the Simulation Accuracy of the Net Ecosystem Productivity of Subtropical Forests in China: Sensitivity Analysis and Parameter Calibration Based on the BIOME-BGC Model

Subtropical forests have strong carbon sequestration potential; however, the spatiotemporal patterns of their carbon sink are unclear. The BIOME-BGC model is a powerful tool for forest carbon sink estimation while the numerous parameters, as well as the localization, limit their application. This study takes three typical subtropical forests (evergreen broadleaf forest, EBF; evergreen needleleaf forest, ENF; and bamboo forest, BF) in China as examples, assesses the sensitivity of 43 ecophysiological parameters in the BIOME-BGC model both by the Morris method and the extended Fourier amplitude sensitivity test (EFAST), and then evaluates the net ecosystem productivity (NEP) estimation accuracy based on the dataset of the fiveFi long-term carbon flux sites of those three typical forests from 2000 to 2015. The results showed that (1) both sensitivity analysis methods can effectively screen out important parameters affecting NEP simulation while the Morris method is more computationally efficient and the EFAST is better in the quantitative evaluation of sensitivity. (2) The highly sensitive parameters obtained using the two methods are basically the same; however, their importance varies across sites and vegetation types, e.g., the most sensitive parameters are k for the EBF and ENF and Ract25 for the BF, respectively. (3) The optimized parameters successfully improved the NEP simulation accuracy in subtropical forests, with average correlation coefficients increased by 25.19% and normalized root mean square error reduced by 21.74% compared with those simulated by original parameters. This study provides a theoretical basis for the optimization of process model parameters and important technical support for accurate NEP simulations of subtropical forest ecosystems.
First-Order Optimality Conditions for Elliptic Mathematical Programs with Equilibrium Constraints via Variational Analysis

Mathematical programs in which the constraint set is partially defined by the solutions of an elliptic variational inequality, so-called “elliptic MPECs,” are formulated in reflexive Banach spaces. With the goal of deriving explicit first-order optimality conditions amenable to the development of numerical procedures, variational analytic concepts are both applied and further developed. The paper is split into two main parts. The first part concerns the derivation of conditions in which the (lower-level) state constraints are assumed to be polyhedric sets. This part is then completed by two examples, the latter of which involves pointwise bilateral bounds on the gradient of the state. The second part focuses on an important nonpolyhedric example, namely, when the lower-level state constraints are presented by pointwise bounds on the Euclidean norm of the gradient of the state. A formula for the second-order (Mosco) epiderivative of the indicator function for this convex set is derived. This result is then used to demonstrate the (Hadamard) directional differentiability of the solution mapping of the variational inequality, which then leads to the derivation of explicit strong stationarity conditions for this problem.
Anselmo Rubiralta Center for Globalization and Strategy Working Paper

Small firms are thought to encounter various difficulties implementing strategic alliances. Due to these problems, they may be less able to reap the benefits of alliance adaptation, and the changes that occur in alliances over time often will not coincide with the small firm’s interests. The evidence we present on contractual renegotiations in alliances suggests that small firms are no more or less likely to experience contractual changes in general. However, small firms tend to bear inefficiencies of two kinds in their collaborations. They are less likely to adapt alliances in the presence of governance misalignments. Furthermore, they are prone to make greater transaction-specific investments without commensurate contractual safeguards, which can lead to ex post hold-up in the form of contractual renegotiations.
Issues in Informing Science and Information Technology Persistf: a Transparent Persistence Framework with Architecture Applying Design Patterns

Persistence is the term used in computer science to describe a capability to store data structures in non-volatile storage such as a file system or a relational database (Wikipedia, 2003). There is a growing need to simplify the interactions among separate systems and to build complex software systems that are made out of components with well-defined services. At the base-level of such complex systems lies a persistence framework – a set of classes tailored to save, retrieve, update and delete objects to and from their persistence stores, such as databases and flat files. This paper presents the design, and implementation of the transparent persistence framework called PersistF. have been widely accepted in the software engineering community as the recommended approach to developing software. Part of the research effort of this work included the application of well-known design patterns in order to build the framework. We present how consistent application of design patterns allowed us to build a fully working persistence framework. In order to support development of modern complex applications, some recent application development environments for different programming languages are built in with some kind of persistence framework. To use these frameworks in target applications, the developer often must go through a steep learning curve as each framework is specific in some way, but namely in respect of configuring the framework's runtime engine with enough information about the domain application. This configuration is often time consuming and error prone. Most of the existing frameworks require complicated configuration steps that are imposed onto the developer. Our aim with this work was to present a framework that will not require such complicated configuration steps and would provide its service to the target application with virtually no configuration of the framework's handling of domain classes.
Use of Twitter for Analysis of Public Sentiment for Improvement of Local Government Service

Active collaboration with the public is the key to improving the administrative services of local government, and social media is an essential tool for understanding public sentiment. In this paper, we propose a method to gauge public sentiment for local government by using Twitter. We conducted an operational test with local government officers and found that our proposal was effective in revealing sentiments that were meaningful for the public, such as avoiding full parking lots, finding potholes in the road, or attracting favorable comments or suggestions to improve festival events.
Adaptive Pseudo Dilation for Gestalt Edge Grouping and Contour Detection

We consider the problem of detecting object contours in natural images. In many cases, local luminance changes turn out to be stronger in textured areas than on object contours. Therefore, local edge features, which only look at a small neighborhood of each pixel, cannot be reliable indicators of the presence of a contour, and some global analysis is needed. We introduce a new morphological operator, called adaptive pseudo-dilation (APD), which uses context dependent structuring elements in order to identify long curvilinear structure in the edge map. We show that grouping edge pixels as the connected components of the output of APD results in a good agreement with the Gestalt law of good continuation. The novelty of this operator is that dilation is limited to the Voronoi cell of each edge pixel. An efficient implementation of APD is presented. The grouping algorithm is then embedded in a multithreshold contour detector. At each threshold level, small groups of edges are removed, and contours are completed by means of a generalized reconstruction from markers. The use of different thresholds makes the algorithm much less sensitive to the values of the input parameters. Both qualitative and quantitative comparison with existing approaches prove the superiority of the proposed contour detector in terms of larger amount of suppressed texture and more effective detection of low-contrast contours.
Tendon Graft Healing in Multiligament Reconstructed Knee Detected by FDG-PET/CT: A Pilot Study

Background and Aims: The detection of graft viability is challenging in the multiligament reconstructed knee. Magnetic resonance imaging gives structural information but lacks the capability to assess biological activity of the grafts. 18F-labeled fluorodeoxyglucose positron emission tomography combined with computer tomography is shown to be a sensitive method for imaging tissue metabolism and viability. The aim of the present study was to evaluate the feasibility of fluorodeoxyglucose positron emission tomography combined with computer tomography imaging in the detection of the replacement graft metabolism in multiligament reconstructed knees. Materials and Methods: Seven patients (17–44 years) with multiligament reconstructed knee underwent fluorodeoxyglucose positron emission tomography combined with computer tomography to evaluate the biological activity of replacement grafts. The degree of fluorodeoxyglucose uptake reported as standard uptake values from the region of interest was analyzed 3–24 months postoperatively. Results: In all patients, the fluorodeoxyglucose positron emission tomography combined with computer tomography showed increased fluorodeoxyglucose uptake in all replacement grafts at different follow-up time points. Furthermore, fluorodeoxyglucose was higher at femoral condyles of operated knees compared to contralateral reference values. Conclusion: This pilot study shows a significant increase in tendon graft metabolism during two first years of postoperative healing. The fluorodeoxyglucose positron emission tomography combined with computer tomography imaging seems to be adequate method of assessment of graft metabolism and viability during postoperative healing. The clinical value of fluorodeoxyglucose positron emission tomography combined with computer tomography imaging, however, warrants further evaluation with longitudinal studies with a larger patient population.
Two-way writing on dirty paper in the presence of noise-dependent interference

In this paper, we characterize the capacity regions of the Gaussian doubly dirty two-way channel (DD-TWC) in the presence of noise-dependent interference as well as input-dependent interference, and thereby we quantify the impact of such dependencies on the capacity region of the Gaussian DD-TWC. We also show that for the Gaussian DD-TWC with noise/input-dependent interference, adaptation (the use of formerly received signals in encoding process) is useless from a capacity point of view. The above-mentioned claims are proved by obtaining a capacity outer bound in the adaptive mode which is coincided with capacity inner bound derived in the non-adaptive mode.
Association of Tyrosine-phosphorylated c-Src with the Cytoskeleton of Hypertrophying Myocardium*

Given the central position of the focal adhesion complex, both physically in coupling integrins to the interstitium and biochemically in providing an upstream site for anabolic signal generation, we asked whether the recruitment of non-receptor tyrosine kinases to the cytoskeleton might be a mechanism whereby cellular loading could activate growth regulatory signals responsible for cardiac hypertrophy. Analysis revealed cytoskeletal association of c-Src, FAK, and β3-integrin, but no Fyn, in the pressure-overloaded right ventricle. This association was seen as early as 4 h after right ventricular pressure overloading, increased through 48 h, and reverted to normal in 1 week. Cytoskeletal binding of non-receptor tyrosine kinases was synchronous with tyrosine phosphorylation of several cytoskeletal proteins, including c-Src. Examination of cytoskeleton-bound c-Src revealed that a significant portion of the tyrosine phosphorylation was not at the Tyr-527 site and therefore presumably was at the Tyr-416 site. Thus, these studies strongly suggest that non-receptor tyrosine kinases, in particular c-Src, may play a critical role in hypertrophic growth regulation by their association with cytoskeletal structures, possibly via load activation of integrin-mediated signaling.
A Survey on Sequential Pattern Mining Algorithms

- Sequential pattern mining is a very important mining technique with broad applications. It found very useful in various domain like natural disaster, sales record analysis, marketing strategy, shopping sequences , medical treatment and DNA sequences etc. It discovers the subsequence’s and frequent relevant pattern from the given sequences. That we have provided the sequence database having sequences, in which each sequence is a list of the transactions ordered by the transaction time. Each transaction consists of the number of the items. The problem is to discover the all sequential pattern who satisfy the user specified constraint, from the given sequence database. There are various sequential pattern mining algorithms proposed earlier, some of them are GSP, SPADE, SPAM and Prefixspan. They are proposed to find the relevant frequent pattern from the sequences. In above algorithms the old dataset is deleted while some other dataset are updated. In these algorithm the timestamp is an important attribute of each dataset, and also it is important in the process of data mining for giving the more accurate and useful information. The detail survey of these entire algorithms is presented in this paper. The survey of all these algorithms done with various research perspectives. First we categorized these algorithms by their used approaches to solve the mining problem and then we have compared each one with another by their various provided features and performance point of view.
Design, construction and a compliant gait of “ModPod”: A modular hexpod robot

In this paper we describe the mechanical design, gait and control for a modular hexapod robot which makes it compliant to terrain while climbing slopes up and down. The robot uses a unique electronically actuated 2DOF universal spine similar to the spine of the Snake and the four legged animals like leopard, tiger etc. By controlling the amount of stiffness of the spine we were able to make the robot compliant to the surface. To our knowledge this is the first modular hexapod robot which achieves controllable compliance by both mechanical design and electronically actuating the robots spinal backbone. This design was biologically inspired based on the structure of a caterpillar with legs. Also we present the hardware and software architecture of the robot in this paper
RMDAP: A Versatile, Ready-To-Use Toolbox for Multigene Genetic Transformation

Background The use of transgenes to improve complex traits in crops has challenged current genetic transformation technology for multigene transfer. Therefore, a multigene transformation strategy for use in plant molecular biology and plant genetic breeding is thus needed. Methodology/Principal Findings Here we describe a versatile, ready-to-use multigene genetic transformation method, named the Recombination-assisted Multifunctional DNA Assembly Platform (RMDAP), which combines many of the useful features of existing plant transformation systems. This platform incorporates three widely-used recombination systems, namely, Gateway technology, in vivo Cre/loxP and recombineering into a highly efficient and reliable approach for gene assembly. RMDAP proposes a strategy for gene stacking and contains a wide range of flexible, modular vectors offering a series of functionally validated genetic elements to manipulate transgene overexpression or gene silencing involved in a metabolic pathway. In particular, the ability to construct a multigene marker-free vector is another attractive feature. The built-in flexibility of original vectors has greatly increased the expansibility and applicability of the system. A proof-of-principle experiment was confirmed by successfully transferring several heterologous genes into the plant genome. Conclusions/Significance This platform is a ready-to-use toolbox for full exploitation of the potential for coordinate regulation of metabolic pathways and molecular breeding, and will eventually achieve the aim of what we call “one-stop breeding. ”