Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Property Prices on Stock Prices in Hong Kong

This paper studies the extent to which real estate prices impact common stock prices in Hong Kong. Real estate-related firms account for over 30 percent of Hong Kong's stock market capitalization. The real estate markets are therefore major determinants of changes in common stock prices. This study, using data during the 1974-1998 period, not only supports empirically that both unexpected changes in residential and office property prices are important determinants of the change in stock prices for Hong Kong, it also finds that the property and stock price series are cointegrated. Impulse response function based on an error-correction VAR model is used to examine the dynamic relationships between real estate and common stock prices.
Generalized Soft-Output Layered Orthogonal Lattice Detector for Golden Code

The authors develop a generalized layered orthogonal lattice detector (G-LORD) for the golden code. G-LORD includes the previously developed LORD algorithm and exhaustive search ML detection as special cases, and is proved to achieve the perfect balance between error performance and complexity. Meanwhile, G-LORD is suitable for parallel implementations, and has a deterministic complexity as opposed to the sphere decoder approach. Thanks to the special structure of the golden code, G-LORD can implement the optimal ordering with very low complexity. Most importantly, G-LORD can efficiently generate bit soft-output metric when golden code is concatenated with outer channel code. The development of G-LORD boosts the practical application of the golden code.
SOX, compliance and power relationships: Tactics for the CIO

Chief Information Officers (CIOs) around the globe are being drawn into the implementation of Sarbanes Oxley (SOX) compliance. According to the Public Company Accounting Oversight Board (PCAOB) (www.pcaob-us.org) , 15,000 US companies, 1,200 non-US based companies and 1,423 accounting firms spread across 76 countries are affected by SOX. In particular, Section 404 (404), which deals with management’s assessment of internal controls, affects CIOs and information technology (IT) departments (Berghel 2005). With the widespread use of technology, internal controls are either fully automated by being embedded within information systems, or combine automated and manual controls. 404 therefore corrals a wide range of applications such as product accounting, general ledger, asset and inventory management, billing and accounts, receivables and payables, payroll, budgeting and other operational, tracking and reporting systems. These include not only the organization’s main systems, such as ERP systems, but also local databases and personal spreadsheets developed and used on an ad hoc basis. Consequently, compliance and regulatory issues are something that CIOs need to understand, address and certainly not neglect (see inset box).
A fast heuristic particle swarm optimization algorithm for circles packing problem with the equilibrium constraints

The packing problem with the behavioral constraints is difficult to solve due to its NP-hard nature. Particle swarm optimization (PSO) is quick in convergence, but likely to be premature at the initial stage. Considering its characteristics, a fast heuristic PSO algorithm for this problem is proposed, which employ the heuristic method to get the initial approximate position of global optimum by randomly arranging round existing circles in peripheral with counter-clockwise movement, and the refined search of improved PSO as a whole to plan large-scale space global search according to the fitness change, and to quicken convergence speed, avoid premature problem, economize computational expenses, and obtain global optimum. The proposed algorithm is tested and compared it with other published methods on constrained layout examples, demonstrated that the algorithm is superior to the exiting algorithms in performance.
Fusion pores and their control of neurotransmitter and hormone release

Ca2+-triggered exocytosis functions broadly in the secretion of chemical signals, enabling neurons to release neurotransmitters and endocrine cells to release hormones. The biological demands on this process can vary enormously. Although synapses often release neurotransmitter in a small fraction of a millisecond, hormone release can be orders of magnitude slower. Vesicles usually contain multiple signaling molecules that can be released selectively and conditionally. Cells are able to control the speed, concentration profile, and content selectivity of release by tuning and tailoring exocytosis to meet different biological demands. Much of this regulation depends on the fusion pore—the aqueous pathway by which molecules leave a vesicle and move out into the surrounding extracellular space. Studies of fusion pores have illuminated how cells regulate secretion. Furthermore, the formation and growth of fusion pores serve as a readout for the progress of exocytosis, thus revealing key kinetic stages that provide clues about the underlying mechanisms. Herein, we review the structure, composition, and dynamics of fusion pores and discuss the implications for molecular mechanisms as well as for the cellular regulation of neurotransmitter and hormone release.
Efficient Retrieval of the Top-k Most Relevant Spatial Web Objects

The conventional Internet is acquiring a geo-spatial dimension. Web documents are being geo-tagged, and geo-referenced objects such as points of interest are being associated with descriptive text documents. The resulting fusion of geo-location and documents enables a new kind of top-k query that takes into account both location proximity and text relevancy. To our knowledge, only naive techniques exist that are capable of computing a general web information retrieval query while also taking location into account. This paper proposes a new indexing framework for location-aware top-k text retrieval. The framework leverages the inverted file for text retrieval and the R-tree for spatial proximity querying. Several indexing approaches are explored within the framework. The framework encompasses algorithms that utilize the proposed indexes for computing the top-k query, thus taking into account both text relevancy and location proximity to prune the search space. Results of empirical studies with an implementation of the framework demonstrate that the paper's proposal offers scalability and is capable of excellent performance.
A Hierarchical Super Peer Network for Distributed Software Development

The approach presented in this paper is the construction of a peer-to-peer based network for distributed software development, which maps the structures of open source projects in a natural way. Distributed teams, in particular for open source projects, can be considered as peerto- peer systems themselves. A hierarchical super peer network is being designed to support the formation of new developer groups and projects and to allow a flexible self-organisation of the organisational units and their relationships. Distributed resources like version control systems as well as local devices can be integrated into the network. Basic synchronous and asynchronous communication with the possibility to use external CSCW systems for intensive coordination and cooperation enhance the network.
Voter Specialization in Local Elections

The established literature on voter behavior suggests that voting typologies can be generally defined as follows: (1) voters participating in all elections, (2) voters participating in state and federal elections only, (3) voters participating only in federal elections, and (4) voters participating only in presidential elections. My thesis investigates whether there are some voters who fall outside of these established voting typologies and focus their civic efforts towards nonpartisan or local issues elections. Utilizing data from the Ohio Secretary of State, I used Q methodology factor analysis to distinguish voter types. While I was unable to establish a local-specialist voter type, I was able to find groups of biennial federal specialists and habitual voters. Using hypotheses for the characteristics local specialists might have in common, I performed multivariate regression analysis to explain the difference between these federal specialists and the habitual voters who participated in local elections. I found that the habitual voters tend to be less partisan and from more rural counties, and turnout more often when elections have tax issues on the ballot and less often when elections have bond issues on the ballot. I found no indications that these habitual voters tend to be older or have specializations in local or miscellaneous issues (as defined by the Ohio Secretary of State).
Human Face Feature Extraction and Recognition Base on SIFT

An important algorithm SIFT, which has been successfully applied in image matching, is employed in face recognition. Firstly, the main region of a face is detected from background images by AdaBoost. Secondly, face features are extracted by using SIFT. Then, face recognition is conducted by the comparing real extracted features with training sets. Experiment shows that, in the ORAL face DB, this scheme can reserve the advantages of SIFT, and have a high robustness in face description.
Does Structural Inequality Begin with a Bank Account? Creating a Financial Stake in College: Report II of IV.

“Creating a Financial Stake in College” is a four-part series of reports that focuses on the relationship between children‖s savings and improving college success. This series examines: (1) why policymakers should care about savings, (2) the relationship between inequality and bank account ownership, (3) the connections between savings and college attendance, and (4) recommendations to refine children‖s savings account proposals. This series of reports presents evidence from a set of empirical studies conducted by Elliott and colleagues on children‖s savings research, with an emphasis on low-income children, relevant to large-scale policy proposals. One such proposal, The ASPIRE Act, would encourage savings by opening an account for every newborn child, seeding the account with an initial deposit and progressively matching contributions, and designating accumulated resources to support post-secondary education or other targeted uses such as homeownership or retirement. Collectively, these reports build on the compelling observation that children with savings in their name are given a stake in their future. As such, they are more inclined to take control over their educational experience and feel more empowered to attend college and persist through graduation.
Low Pressure Radio-Frequency Oxygen Plasma Induced Oxidation of Titanium – Surface Characteristics and Biological Effects

Objective This research was designed to investigate the effects of low pressure radio-frequency (RF) oxygen plasma treatment (OPT) on the surface of commercially pure titanium (CP-Ti) and Ti6Al4V. Surface topography, elemental composition, water contact angle, cell viability, and cell morphology were surveyed to evaluate the biocompatibility of titanium samples with different lengths of OP treating time. Materials and Methods CP-Ti and Ti6Al4V discs were both classified into 4 groups: untreated, treated with OP generated by using oxygen (99.98%) for 5, 10, and 30 min, respectively. After OPT on CP-Ti and Ti6Al4V samples, scanning probe microscopy, X-ray photoelectron spectrometry (XPS), and contact angle tests were conducted to determine the surface topography, elemental composition and hydrophilicity, respectively. The change of surface morphology was further studied using sputtered titanium on silicon wafers. 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (MTT) assay and F-actin immunofluorescence stain were performed to investigate the viability and spreading behavior of cultivated MG-63 cells on the samples. Results The surface roughness was most prominent after 5 min OPT in both CP-Ti and Ti6Al4V, and the surface morphology of sputtered Ti sharpened after the 5 min treatment. From the XPS results, the intensity of Ti°, Ti2+, and Ti3+ of the samples’ surface decreased indicating the oxidation of titanium after OPT. The water contact angles of both CP-Ti and Ti6Al4V were increased after 5 min OPT. The results of MTT assay demonstrated MG-63 cells proliferated best on the 5 min OP treated titanium sample. The F-actin immunofluorescence stain revealed the cultivated cell number of 5 min treated CP-Ti/Ti6Al4V was greater than other groups and most of the cultivated cells were spindle-shaped. Conclusions Low pressure RF oxygen plasma modified both the composition and the morphology of titanium samples’ surface. The CP-Ti/Ti6Al4V treated with 5 min OPT displayed the roughest surface, sharpest surface profile and best biocompatibility.
A Computation Offloading Framework for Soft Real-Time Embedded Systems

Recent developments in embedded hardware have empowered human experiences through pervasive computing. While embedded systems are becoming more powerful, they still fall short when faced with users' growing desire for running more resource-demanding applications. To bridge this gap, one solution is to leverage powerful resources residing at remote sites by performing computation offloading. Unfortunately, the state-of-the-art offloading frameworks cannot be applied in many embedded systems supporting applications with soft real-time (SRT) constraints or high delay sensitivity, as they typically optimize response times on a "best-effort" basis using heuristics. This paper establishes a soft real-time offloading framework that optimizes the resource utilization of the embedded system while analytically guaranteeing SRT schedulability. The key idea behind the proposed framework is to view offloading-induced delays as suspensions occurring at the local embedded system side, which allows a task being offloaded to be modelled as a suspending task and thus existing SRT suspension-aware scheduling and analysis techniques to be leveraged. Based on this idea, we propose an offloading algorithm, namely Real-time Offloading Decision-making Algorithm (RODA), to make offloading decisions such that SRT schedulability of the task system can be ensured. The optimality properties of RODA have been proved on both uniprocessors and multiprocessors. We conducted extensive simulations on evaluating schedulability and implemented a case study offloading system on top of real hardware to test runtime response time performance. Results demonstrated that RODA is superior to existing performance-driven offloading algorithms, particularly under heavy workloads.
Knowledge management implementation frameworks: a review

One reason why many organizations are still struggling with knowledge management (KM) and failing in their endeavours to realize its full potential is that they lack the support of a strong theoretical foundation to guide them in its implementation. A sound KM implementation framework helps to fulfil this need by providing important guiding principles and directions. However, developing such a framework can be a challenging task for managers and practitioners as they may lack the knowledge of what characteristics, elements and constructs should be included in it. Implementation frameworks that do not have the necessary elements in place can paint an incomplete picture of KM and its implementation process, thus providing a suboptimal guidance for conducting KM. This paper reviews the existing KM implementation frameworks presented in the literature in order to determine and propose a set of guidelines for constructing them. By utilizing these guidelines to develop a KM implementation framework, it is hoped that a stronger theoretical foundation can be constructed, thus facilitating the accomplishment of KM. Copyright © 2004 John Wiley & Sons, Ltd.
A Game Theoretical Approach to Modeling Information Dissemination in Social Networks

One major function of social networks (e.g., massive online social networks) is the dissemination of information such as scientific knowledge, news, and rumors. Information can be propagated by the users of the network via natural connections in written, oral or electronic form. The information passing from a sender to a receiver intrinsically involves both of them considering their self-perceived knowledge, reputation, and popularity, which further determine their decisions of whether or not to forward the information and whether or not to provide feedback. To understand such human aspects of the information dissemination, we propose a game theoretical model of the information forwarding and feedback mechanisms in a social network that take into account the personalities of the sender and the receiver (including their perceived knowledgeability, reputation, and desire for popularity) and the global characteristics of the network.
Efficacy and safety of canagliflozin in subjects with type 2 diabetes and chronic kidney disease

Canagliflozin is a sodium glucose co‐transporter 2 inhibitor in development for treatment of type 2 diabetes mellitus (T2DM). This study evaluated the efficacy and safety of canagliflozin in subjects with T2DM and stage 3 chronic kidney disease [CKD; estimated glomerular filtration rate (eGFR) ≥30 and <50 ml/min/1.73 m2].
Practical Free-form RTI Acquisition with Local Spot Lights

We present an automated light calibration pipeline for free-form acquisition of shape and reflectance of objects using common off-the-shelf illuminators, such as LED lights, that can be placed arbitrarily close to the objects. We acquire multiple digital photographs of the studied object shot from a stationary camera. In each photograph, a light is freely positioned around the object in order to cover a wide variety of illumination directions. While common free-form acquisition approaches are based on the simplifying assumptions that the light sources are either sufficiently far from the object that all incoming light can be modeled using parallel rays, or that lights are local points emitting uniformly in space, we use the more realistic model of a scene lit by a moving local spot light with exponential fall-off depending on the cosine of the angle between the spot light optical axis and the illumination direction, raised to the power of the spot exponent. We recover all spot light parameters using a multipass numerical method. First, light positions are determined using standard methods used in photometric stereo approaches. Then, we exploit measures taken on a Lambertian reference planar object to recover the spot light exponent and the per-image spot light optical axis; we minimize the difference between the observed reflectance and the reflectance synthesized by using the near-field Lambertian equation. The optimization is performed in two passes, first generating a starting solution and then refining it using a Levenberg-Marquardt iterative minimizer. We demonstrate the effectiveness of the method based on an error analysis performed on analytical datasets, as well as on real-world experiments.
Galaxy evolution in the high-redshift, colour-selected cluster RzCS 052 at z= 1.02

We present deep I and z' imaging of the colour-selected cluster RzCS 052 and study the colour-magnitude relation of this cluster, its scatter, the morphological distribution on the red sequence, the luminosity and stellar mass functions of red galaxies and the cluster blue fraction. We find that the stellar populations of early-type galaxies in this cluster are uniformly old and that their luminosity function does not show any sign of evolution other than the passive evolution of their stellar populations. We rule out a significant contribution from mergers in the build-up of the red sequence of RzCS 052. The cluster has a large (∼30 per cent) blue fraction and we infer that the evolution of the blue galaxies is faster than an exponentially declining star formation model and that these objects have probably experienced starburst episodes. Mergers are unlikely to be the driver of the observed colour evolution, because of the measured constancy of the mass function, as derived from near-infrared photometry of 32 clusters, including RzCS 052, presented in a related paper. Mechanisms with clustercentric radial dependent efficiencies are disfavoured as well, because of the observed constant blue fraction with clustercentric distance.
Network Topologies in Wireless Sensor Networks: A Review

In Wireless Sensor Networks (WSNs), sensor nodes have limited battery power, so energy consumption is essential issue. Every sensor node can obtain its location information from GPS or other positioning system and send data to sink at any time. In this paper, comparison of the dynamic network topologies in Wireless Sensor Networks has been done. The characteristic of this is to divide WSN into network based on Topologies i.e. Bus, Tree, Star, Ring, Mesh, Circular, Grid. Information of the position of nodes, and those nodes are organized within the network by the Topological way.
Comparing Clusterings Using Bertin's Idea

Classifying a set of objects into clusters can be done in numerous ways, producing different results. They can be visually compared using contingency tables [27], mosaicplots [13], fluctuation diagrams [15], tableplots [20] , (modified) parallel coordinates plots [28], Parallel Sets plots [18] or circos diagrams [19]. Unfortunately the interpretability of all these graphical displays decreases rapidly with the numbers of categories and clusterings. In his famous book A Semiology of Graphics [5] Bertin writes “the discovery of an ordered concept appears as the ultimate point in logical simplification since it permits reducing to a single instant the assimilation of series which previously required many instants of study”. Or in more everyday language, if you use good orderings you can see results immediately that with other orderings might take a lot of effort. This is also related to the idea of effect ordering [12], that data should be organised to reflect the effect you want to observe. This paper presents an efficient algorithm based on Bertin's idea and concepts related to Kendall's t [17], which finds informative joint orders for two or more nominal classification variables. We also show how these orderings improve the various displays and how groups of corresponding categories can be detected using a top-down partitioning algorithm. Different clusterings based on data on the environmental performance of cars sold in Germany are used for illustration. All presented methods are available in the R package extracat which is used to compute the optimized orderings for the example dataset.