Miracle-dz/UniFAR-FTUs huggingface dataset:
Urban land value, Accessibility and Night Light Data: A Case Study in China

In this paper, we use night light imagery data at two scales – the city and within the city. Since many of the urban characteristics of cities including traffic and paved area are correlated with each other we derive components for our sample of 286 cities in China. We then correlate these measures for average DN values from night light imagery at the center and periphery of the city (using buffers of 5km and 20km). We also test at four points of time in the period 2002-2012 to assess changes over time if any. We then focus on Beijing and assess the correlation between night light imagery derived DN values, land price and an accessibility indicator. In deriving spatial accessibility we use micro scale indicators such as time distance to the city center, and employment centers by transit and automobile. We use spatial regression and Geographically Weighted Regression (GWR) models. _______________________________________________________ S. Srinivasan (Corresponding author) China Project, School of Engineering and Applied Sciences, Harvard University, Cambridge, MA Email: sumeeta@seas.harvard. edu D. Yu Institute of Geographical Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing, China, Email: rain00788@163.com CUPUM 2015 309-Paper
Developing Resources for Swedish Bio-Medical Text Mining

Collection and annotation of corpora in specialized fields, such as medicine, and particularly for lesser-spoken languages, than for instance English, is an important enterprise for the continuous development and growth of language technology research, for resource development and for the implementation of practical applications for these languages. In this paper, we describe our ongoing efforts to build a large Swedish medical corpus, the MEDLEX Corpus, how we combine generic named entity and terminology recognition for the detailed annotation of the corpus, and how these annotations are further utilized by an annotations-aware cascaded finite-state parser.
Statistical properties of the capacity of multipath fading channels

It is well known that a frequency-nonselective multipath fading channel can be modeled by a sum of complex sinusoids, also called sum-of-cisoids (SOC). By using the SOC, we can efficiently model the scattered component of the received signal in non-isotropic scattering environments. Such SOC-based multipath channel models provide the flexibility of having correlated in-phase and quadrature phase components of the received signal. This paper presents the derivation and analysis of the statistical properties of the capacity of multipath fading channels under LOS conditions. As an appropriate stochastic model for the multipath fading channel, we have adopted the SOC model. We have derived the exact analytical expressions for the probability density function (PDF), cumulative distribution function (CDF), level-crossing rate (LCR), and average duration of fades (ADF) of the channel capacity. The statistical behavior of the channel capacity is studied for different values of the number of multipaths (cisoids) in the SOC model and the results are compared with the reference model which can be obtained by using an infinite number of cisoids. It is shown that the SOC model with ten cisoids produces results very close to the reference model. The validity of all the theoretical expressions is tested with the help of simulations.
Robust and Efficient Distributed Compression for Cloud Radio Access Networks

This paper studies distributed compression for the uplink of a cloud radio access network where multiple multiantenna base stations (BSs) are connected to a central unit, which is also referred to as a cloud decoder, via capacity-constrained backhaul links. Since the signals received at different BSs are correlated, distributed source coding strategies are potentially beneficial. However, they require each BS to have information about the joint statistics of the received signals across the BSs, and they are generally sensitive to uncertainties regarding such information. Motivated by this observation, a robust compression method is proposed to cope with uncertainties on the correlation of the received signals. The problem is formulated using a deterministic worst case approach, and an algorithm is proposed that achieves a stationary point for the problem. Then, BS selection is addressed with the aim of reducing the number of active BSs, thus enhancing the energy efficiency of the network. An optimization problem is formulated in which compression and BS selection are performed jointly by introducing a sparsity-inducing term into the objective function. An iterative algorithm is proposed that is shown to converge to a locally optimal point. From numerical results, it is observed that the proposed robust compression scheme compensates for a large fraction of the performance loss induced by the imperfect statistical information. Moreover, the proposed BS selection algorithm is seen to perform close to the more complex exhaustive search solution.
Smooth and efficient crowd transformation

Crowd transformation has been an important research field due to its diverse range of applications that include film production, computer games, robotics and performance training. We propose a novel approach with continuous space and continuous time for smooth crowd transformation. Most algorithms simulating the transformation of crowds focus on the trajectories of individual participants. As a contrast, the approach we proposed here focuses on the balanced assignment to maintain the collective behavior of the full crowd. We use a bitmap-based recognition of the starting and final formations and quantify the performance of the transformation with the mutual information. We demonstrate that our method is computationally efficient for several group sizes and formations.
KD-Tree Based Clustering for Gene Expression Data

K-means is one of the widely researched clustering algorithms. But it is sensitive to the selection of initial cluster centers and estimation of the number of clusters. In this chapter, we propose a novel approach to find the efficient initial cluster centers using kd-tree and compute the number of clusters using joint distance function. We have carried out excessive experiments on various synthetic as well as gene expression data. Dunn validity index is used to examine the quality of the clusters in case of multi-dimensional gene expression data. The experimental results are compared with the existing techniques using the Dunn validity index and number of iterations.
Detection of Escherichia coli O157 and Escherichia coli O157:H7 by the immunomagnetic separation technique and stx1 and stx2 genes by multiplex PCR in slaughtered cattle in Samsun Province, Turkey

This study was conducted to investigate the presence of Escherichia (E.) coli O157 and E. coli O157:H7 and stx1 and stx2 genes on cattle carcasses and in rectal samples collected from Samsun Province of Turkey. A total of 200 samples collected from cattle carcasses and the rectal contents of 100 slaughtered cattle from two commercial abattoirs were tested using the immunomagnetic separation technique and multiplex PCR methods. E. coli O157 and E. coli O157:H7 were detected in 52 of the 200 samples (26%) tested. Of the positive samples, 49 were E. coli O157 and three were E. coli O157:H7. The E. coli O157 strain was isolated from 24 carcasses and 25 rectal samples, while E. coli O157:H7 was isolated from two carcasses and one rectal sample. Of the 49 samples positive for E. coli O157, 32 were from the rectal and carcass samples of the same animal, while two E. coli O157:H7 isolates were obtained from rectal swabs and carcasses of the same animal. The stx1 and stx2 genes were both detected in 35 E. coli O157 isolates and one E. coli O157:H7 isolate, but the stx2 gene was only detected alone in two E. coli O157 isolates. Overall, 16 carcasses tested positive for E. coli O157 and one carcass tested positive for E. coli O157:H7 based on both carcass and rectal samples. Overall, the results of this study indicate that cattle carcasses pose a potential risk to human health due to contamination by E. coli O157 and E. coli O157:H7 in the feces.
Tactical allocation in falling stocks: Combining momentum and solvency ratio signals

We identified 4500 US stocks with year ending losses of 50 percent or more during the 2001-2011 period. We screened our "falling knives" for financial strength to promote a greater likelihood of recovery and minimize any survivorship bias. We added the constraints of Altman Z-Scores, debt/equity ratio, and current ratio to our data set. We use GARCH-in-mean model to control the risk of the strategies. The results show consistent improvement of risk-standardized return profiles of the strategies in comparison with buy and hold strategy.
Synaptic activity and Alzheimer's disease: a critical update

Synapses have been known for many years to be the crucial target of pathology in different forms of dementia, in particular Alzheimer's disease (AD). Synapses and their appropriate activation or inhibition are fundamental for the proper brain function. Alterations in synaptic/neuronal activity and brain metabolism are considered among the earliest symptoms linked to the progression of AD, and lead to a central question in AD research: what is the role played by synaptic activity in AD pathogenesis? Intriguingly, in the last decade, important studies demonstrated that the state of activation of synapses affects the homeostasis of beta-amyloid (Aβ) and tau, both of which aggregate and accumulate during AD, and are involved in neuronal dysfunction. In this review we aim to summarize the up-to-date data linking synaptic/neuronal activity with Aβ and tau; moreover, we also intend to provide a critical overview on brain activity alterations in AD, and their role in the disease's pathophysiology.
SATELLITE DYNAMICS ON THE LAPLACE SURFACE

The orbital dynamics of most planetary satellites is governed by the quadrupole moment from the equatorial bulge of the host planet and the tidal field from the Sun. On the Laplace surface, the long-term orbital evolution driven by the combined effects of these forces is zero, so that orbits have a fixed orientation and shape. The “classical” Laplace surface is defined for circular orbits, and coincides with the planet's equator at small planetocentric distances and with its orbital plane at large distances. A dissipative circumplanetary disk should settle to this surface, and hence satellites formed from such a disk are likely to orbit in or near the classical Laplace surface. This paper studies the properties of Laplace surfaces. Our principal results are: (1) if the planetary obliquity exceeds 68. °875, there is a range of semimajor axes in which the classical Laplace surface is unstable; (2) at some obliquities and planetocentric distances, there is a distinct Laplace surface consisting of nested eccentric orbits, which bifurcates from the classical Laplace surface at the point where instability sets in; (3) there is also a “polar” Laplace surface perpendicular to the line of nodes of the planetary equator on the planetary orbit; (4) for circular orbits, the polar Laplace surface is stable at small planetocentric distances and unstable at large distances; (5) at the onset of instability, this polar Laplace surface bifurcates into two polar Laplace surfaces composed of nested eccentric orbits.
Power Is The Great Motivator

Most HBR articles on motivation speak to managers about the people whose work they oversee. Curiously, the writers assume that the motivation of managers themselves-that is to say, of our readers-is so well aligned with organizational goals that it needs no examination. David McClelland and his colleague David Burnham knew better. They found that managers fall into three motivational groups. Those in the first, affiliative managers, need to be liked more than they need to get things done. Their decisions are aimed at increasing their own popularity rather than promoting the goals of the organization. Managers motivated by the need to achieve-the second group-aren't worried about what people think of them. They focus on setting goals and reaching them, but they put their own achievement and recognition first. Those in the third group-institutional managers-are interested above all in power. Recognizing that you get things done inside organizations only if you can influence the people around you, they focus on building power through influence rather than through their own individual achievement. People in this third group are the most effective, and their direct reports have a greater sense of responsibility, see organizational goals more clearly, and exhibit more team spirit.
Apache hadoop performance-tuning methodologies and best practices

Apache Hadoop is a Java based distributed computing framework built for applications implemented using MapReduce programming model. In recent years, Hadoop technology has experienced an unprecedented growth in its adoption. From single-node clusters to clusters with well over thousands of nodes, Hadoop technology is being used to perform myriad of functions - search optimizations, data mining, click stream analytics, machine learning to name a few. Although setting up Hadoop clusters and building applications for Hadoop is a well understood area, tuning Hadoop clusters for optimal performance is still a black art. In this demo paper, we will attempt to provide the audience with a holistic approach of Hadoop performance tuning methodologies and best practices. We discuss hardware as well as software tuning techniques including BIOS, OS, JVM and Hadoop configuration parameters tuning.
Asymptotic analysis of large MIMO wire-tap channel via replica method

Security has been one of the most significant problems surrounding wireless communications, in large part due to the openness of wireless medium where eavesdropping can be easily accomplished. In this work, the prior results on secrecy capacity is extended to the Gaussian MIMO wire-tap channel, where the transmitter, the receiver and illegal wire-tapper all employ multiple antenna technique. A reasonable security criterion is firstly defined for the MIMO wire-tap channel in this paper. Next the secrecy capacity and the achievable rate-equivocation (R, d) region in this multiple antenna scenario are derived. Finally, the analyzed results are validated by the numerical simulations.
Vinblastine and sulfinpyrazone export by the multidrug resistance protein MRP2 is associated with glutathione export

The multidrug resistance proteins MRP1 and MRP2 are members of the same subfamily of ATP-binding cassette transporters. Besides organic molecules conjugated to negatively charged ligands, these proteins also transport cytotoxic drugs for which no negatively charged conjugates are known to exist. In polarized MDCKII cells, MRP1 routes to the lateral plasma membrane, and MRP2 to the apical plasma membrane. In these cells MRP1 transports daunorubicin, and MRP2 vinblastine; both transporters export reduced glutathione (GSH) into the medium. We demonstrate that glutathione transport in MDCKII-MRP1 cells is inhibited by the inhibitors of organic anion transporters sulfinpyrazone, indomethacin, probenecid and benzbromarone. In MDCKII-MRP2 cells, GSH export is stimulated by low concentrations of sulfinpyrazone or indomethacin, whereas export is inhibited down to control levels at high concentrations. We find that unmodified sulfinpyrazone is a substrate for MRP2, also at concentrations where GSH export is inhibited. We also show that GSH export in MDCKII-MRP2 cells increases in the presence of vinblastine, and that the stochiometry between drug and GSH exported is between two and three. Our data indicate that transport of sulfinpyrazone and vinblastine is associated with GSH export. However, at high sulfinpyrazone concentrations this compound is transported without GSH. Models of MRP action are discussed that could explain these results. © 2000 Cancer Research Campaign
The EUDICO Project, Multi Media Annotation over the Internet

In this paper we dsecribe a software environment that facilitates media annotation and analysis of media related corpora over the internet. We will describe the general architecture of this environment and we will introduce our Abstract Corpus Model with which we isolate corpora specific formats from the annotation and analysis tools. The main set of tools is described by giving examples of their usage. Finally we will discuss features regarding the distributed character of this environment.
Neurexin-1 and Frontal Lobe White Matter: An Overlapping Intermediate Phenotype for Schizophrenia and Autism Spectrum Disorders

Background Structural variation in the neurexin-1 (NRXN1) gene increases risk for both autism spectrum disorders (ASD) and schizophrenia. However, the manner in which NRXN1 gene variation may be related to brain morphology to confer risk for ASD or schizophrenia is unknown. Method/Principal Findings 53 healthy individuals between 18–59 years of age were genotyped at 11 single nucleotide polymorphisms of the NRXN1 gene. All subjects received structural MRI scans, which were processed to determine cortical gray and white matter lobar volumes, and volumes of striatal and thalamic structures. Each subject's sensorimotor function was also assessed. The general linear model was used to calculate the influence of genetic variation on neural and cognitive phenotypes. Finally, in silico analysis was conducted to assess potential functional relevance of any polymorphisms associated with brain measures. A polymorphism located in the 3′ untranslated region of NRXN1 significantly influenced white matter volumes in whole brain and frontal lobes after correcting for total brain volume, age and multiple comparisons. Follow-up in silico analysis revealed that this SNP is a putative microRNA binding site that may be of functional significance in regulating NRXN1 expression. This variant also influenced sensorimotor performance, a neurocognitive function impaired in both ASD and schizophrenia. Conclusions Our findings demonstrate that the NRXN1 gene, a vulnerability gene for SCZ and ASD, influences brain structure and cognitive function susceptible in both disorders. In conjunction with our in silico results, our findings provide evidence for a neural and cognitive susceptibility mechanism by which the NRXN1 gene confers risk for both schizophrenia and ASD.
Performance comparison of commercial VMM: ESXI, XEN, HYPER-V & KVM

Virtualization enables us to strengthen IT resources into single unit so that they can be shared over a network and fulfill the shrinking resources and growing business needs. It adds and subtracts different computing resources to present or past operating environments with different sort of methods like hardware and software aggregation, machine simulation, emulation and many others. Virtualization is integral part of cloud computing as it supports multiple Virtual Machines with different hosting environments. Cloud platform not only manages the resources of the cloud infrastructure but also benefits customer on-demand requirements and task scheduling on virtual machines. In this paper authors have chosen KVM, Xen, Hyper-V and ESXi as hypervisors for the performance evaluation. The aspiration of the paper is to provide the qualitative comparison of the hypervisor under different workloads and their point of saturation. The performance variation on different applications and workloads of the hypervisors has been noticed under different test conditions.
Constructing Graphical Models via the Focused Information Criterion

A focused information criterion is developed to estimate undirected graphical models where for each node in the graph a generalized linear model is put forward conditioned upon the other nodes in the graph. The proposed method selects a graph with a small estimated mean squared error for a user-specified focus, which is a function of the parameters in the generalized linear models, by selecting an appropriate model at each node. For situations where the number of nodes is large in comparison with the number of cases, the procedure performs penalized estimation with quadratic approximations to several popular penalties. To show the procedure’s applicability and usefulness we have applied it to two datasets involving voting behavior of U.S. senators and to a clinical dataset on psychopathology.
The Extreme Compact Starburst in MRK 273

Images of neutral Hydrogen 21cm absorption and radio continuum emission at 1.4 GHz from Mrk 273 were made using the Very Long Baseline Array and Very Large Array. These images reveal a gas disk associated with the northern nuclear region with a diameter of 0.5 ′′ (370 pc), at an inclination angle of 53 o. The radio continuum emission is composed of a diffuse component plus a number of compact sources. This morphology resembles those of nearby, lower luminosity starburst galaxies. These images provide strong support for the hypothesis that the luminosity of the northern source is dominated by an extreme compact starburst. The HI 21cm absorption shows an east-west gradient in velocity of 450 km s −1 across 0.3 ′′ (220 pc), implying an enclosed mass of 2×10 9 M ⊙ , comparable to the molecular gas mass. The brightest of the compact sources may indicate radio emission from an active nucleus (AGN), but this source contributes only 3.8% to the total flux density of the northern nuclear region. The HI 21cm absorption toward the southeast radio nucleus suggests infall at 200 km s −1 on scales ≤ 40 pc, and the southwest near IR nucleus is not detected in high resolution radio continuum images.
Collaborative Work on Indonesian WordNet through Asian WordNet (AWN)

This paper describes collaborative work on developing Indonesian WordNet in the AsianWordNet (AWN). We will describe the method to develop for collaborative editing to review and complete the translation of synset. This paper aims to create linkage among Asian languages by adopting the concept of semantic relations and synset expressed in Word-Net.
Towards synergy in multiperspective management: An American–Chinese case

This paper presents a comparative study of two multiperspective approaches to management, one developed and applied mainly in the United States, the other in China and East Asia. The contentions of the two approaches are briefly outlined, commonality and differences analysed, cultural traditions surfaced, and the ways the two approaches inform and learn from each other reported. It is suggested that the recent development of multiperspective approaches world-wide is not accidental, but can be seen as an outcome of humankind’s common search for responses to the increasingly challenging multidimensional complexity in human systems management. Systems/management scientists in both the West and the East can do better in dealing with the complexity if we consciously open to, inform and learn from each other.
Identification of Software System Components using Semantic Models and Graph Slicing

In this paper, we present an implementation of part of a process for automatically decomposing a legacy software system into a loosely coupled Service Oriented Architecture. We present the Relationship Modelling Framework (RMF), which, when coupled with the appropriate components, can generate and maintain a semantic model of a software system, showing at various levels of abstraction the elements that make up a software system, including (but not limited to) source code entities, database tables, and configuration resources, and the relationships between these elements. We present a technique called graph slicing, derived from program slicing, which can be used to identify the dependencies of selected elements. IBM independently verifies the performance of the model generation process, and the accuracy of the graph slicing process, using a prototypical implementation of RMF. The validation is performed against a real-world software suite produced by IBM.