Miracle-dz/UniFAR-FTUs huggingface dataset:
Sound change in Māori and the influence of New Zealand English

This article investigates sound change in the vowels of Māori, the indigenous language of New Zealand. It examines the relationship between sound changes in Māori and in New Zealand English, the more dominant language, with which Māori has been in close contact for nearly 200 years. We report on the analysis of three adult speaker groups whose birth dates span 100 years. All speakers were bilingual in Māori and New Zealand English. In total the speech of 31 men and 31 women was investigated. Analysis was done on the first and second formant values, extracted from the vowel targets. There has been considerable movement in the Māori vowel space. We find that the sound change in the Māori monophthongs can be directly attributed to the impact of New Zealand English, however the situation for the diphthongs is not so clear cut. There is some evidence that both New Zealand English monophthongs and diphthongs are impacting on the Māori diphthongs, but so too are the Māori monophthongs. We conclude that although New Zealand English has had a strong influence on Māori, there is very strong evidence that new generations of speakers of Māori are acquiring a phonemic system with its own internal parameters and consistencies.
Cross-layer carrier selection and power control for LTE-A uplink with Carrier Aggregation

Long Term Evolution-Advanced (LTE-A) standard with Carrier Aggregation (CA) is emerging as a promising technology for 4G mobile communication systems to fulfill tremendous growth of high-data-rate demand. However, in LTE-A systems with CA, the uplink Radio Resource Management (RRM) performance is greatly limited by the insufficient user transmission power and the infamous power offset effects. In this paper, we design a cross-layer carrier selection and power control strategy for LTE-A uplink with CA to improve the average user throughput, while dealing with the above limitations. Specifically, we first propose a novel estimation method to effectively predict the average bandwidth that a newly admitted user can obtain from each carrier. The time-variability of carrier load conditions is carefully taken into account. Then, an optimal carrier subset and power allocation values are determined for each arrived user to improve the average user throughput by solving a user-power-utilization maximization problem, with considering the user power constraints and offset effects. Extensive simulations validate the effectiveness of the estimation method and demonstrate that the proposed cross-layer strategy can achieve higher average user throughput compared with the existing approach.
Oral Health Knowledge of Periodontal Disease among University Students

Objectives. The aim of this study was to evaluate levels of oral health knowledge of periodontal disease among nondental university students. Materials and Methods. Two hundred and fifty university students (mean age 20.1 years ± 2.5) were recruited into this study. The participants completed a structured questionnaire during a personal interview. The questionnaire consisted of items to assess participants' personal data (age, gender, level of study, and specialty) and oral heath knowledge related to periodontal disease. Statistical significance was based on probability values of less than 0.05. Results. Participants showed poor knowledge of causes, signs, symptoms, and preventive measures of gum disease. The level of study had no relationship with students' knowledge of the initiating factors of periodontal disease (P < 0.05), but had a significant relationship with the knowledge of periodontal disease's signs, preventive measures, and relations to general health and systemic disease (P < 0.05). Students from scientific disciplines had more knowledge of periodontal disease's causes, preventive measures, and relations to general health and systemic disease (P < 0.05) than those from humanity disciplines. Conclusions. There were significant differences in oral health knowledge regarding periodontal disease between students from different levels of studies and different disciplines.
Clustered linear precoding for downlink network MIMO systems with partial CSI

Cell collaboration, also known as downlink network MIMO, has been proved to suppress the adverse effects of inter-cell interference (ICI), and as a result, to improve the performance of cell edge users. In this paper, we propose a novel clustered linear precoding scheme applicable to network MIMO systems using only partial channel state information (CSI) to enhance the quality of service and the edge user throughput. More specifically, by using a novel block diagonalization (BD) method, we first construct the precoding matrices that jointly eliminate ICI and maximize the sum-rate for a given input covariance matrix. Assuming per-BTS power constraints (PBPCs), optimal allocation schemes are further developed to optimize the sum-rate. Numerical results show that the proposed method can achieve a similar sum-rate to that of the BD with full CSI knowledge. More importantly, such a benefit can be obtained by using a small cluster size without the need of global optimization. The comparison in terms of the average signal-to-interference-plus-noise ratio (SINR) between the proposed technique using partial CSI and that with full CSI is also made. It is then revealed that there is no difference in SINR, and as a consequence, the BER performance, between the two schemes.
Monoclonal antibodies against rat brain protein kinase C and their application to immunocytochemistry in nervous tissues

Three monoclonal antibodies were prepared against rat brain soluble protein kinase C. Two of the antibodies, CKI-97 (IgG2b subclass) and CKII-90 (IgG1 subclass), showed weak binding to native protein kinase C. The third antibody, CKI-33 (IgG2b subclass), showed no binding. However, the mixture of CKI-97, CKII-90, and CKI-33 exhibited much stronger binding activity to this protein kinase than any of the antibodies alone. Although none of these antibodies showed protein kinase C-neutralizing activity, Western blot analysis indicated that these antibodies reacted specifically with protein kinase C, presumably its subspecies, that is present predominantly in nervous tissues. Immunocytochemical studies shows that these antibodies can be used for identification of this enzyme in nervous tissues. In rat Purkinje cells, the immunoreactive material was present throughout the cytoplasm, including dendrites and axons, but was poorly represented in the cell nucleus. In cerebellum, the localization of protein kinase C appears to be very similar to that of cGMP-dependent protein kinase.
Pitx3‐CreER mice showing restricted Cre expression in developing ocular lens and skeletal muscles

To generate temporally controlled inactivation or activation of interested genes in Pitx3‐expressing cells, the tamoxifen‐inducible form of Cre, CreERT2, was inserted into the Pitx3 locus of a mouse BAC clone. Following a single dose of tamoxifen, Cre activity in Pitx3‐CreERT2 transgenic mice was observed in the ocular lens and skeletal muscles but not in the central nervous system at various embryonic stages. This mouse line provides a reagent for driving inducible Cre‐dependent recombination in the lens and skeletal muscles during embryonic development. genesis 46:324–328, 2008. © 2008 Wiley‐Liss, Inc.
Facial Contour Extraction Based on Level Set and Grey Prediction in Sequence Images

To improve the real-time performance of the level set algorithm for facial contour extraction in dynamic image sequence, a new facial contour extraction method is purposed in this paper which combines the level set and GM (1,1) model. With this method, firstly, the rough facial contour of a moving body is detected while it enters into the camera scope using the human motion information with the human skin-color model. Then the improved level set algorithm is used to accurately extract the facial contour. According to the integrity of facial contour motion, the centroid displacement of facial contour is predicted with GM(1,1) model so that the motion law of the facial contour can be estimated, which then can be taken as the iteration basis for the level set algorithm. In the same way, the extracted centroid of facial contour is taken as the prediction basis of the next frame GM(1,1) model. Experimental results show that this method can extract the motion facial contour with strong real-time performance and good robustness.
Thickness histogram and statistical harmonic representation for 3D model retrieval

Similarity measuring is a key problem for 3D model retrieval. We propose a novel shape descriptor "thickness histogram" (TH) by uniformly estimating thickness of a model using statistical methods. It is translation and rotation-invariant, discriminative to different shapes, and very efficient to compute with the shape distribution (SD) proposed by Osada etc. For high performance of the retrieval, we propose a robust method for translating the directional form of the statistical distribution to the harmonic representation. By summing up energies at different frequencies, a matrix shape signature is formed to provide an exhaustive characterization of 3D geometry. Experiments show that the performance of the statistical harmonic representation is among the top ones of existing shape descriptors.
A Shallow Approach for Answer Selection based on Dependency Trees and Term Density

This paper describes the experiments performed for the QA@CLEF-2006 within the joint participation of the eLing Division at VEng and the Language Technologies Laboratory at INAOE. This year our laboratories have participated in the Spanish monolingual task, continue with their previous work described in [Perez-Coutino et al., 2005]. The aim of these experiments was to observe and quantify the possible improvement at the final step of the Question Answering prototype when some syntactic features were taken into the decision process. In order to reach this goal, a shallow approach to answer ranking based on the term density measure has been included. This measure weighs the number of question terms which have a syntactic dependency to one candidate answer within a relevant passage to the given question. Once the term density has been computed for each candidate answer, their weights along to the weights gathered in the previous steps are merged by a lineal combination to gather the final weight for each candidate answer. Finally, the answer selection process arranges candidate answers based on their weights, selecting the top-n as the Question Answering system answers. The approach described has shown a small but interesting improvement against the same Question Answering prototype without this module. Nevertheless, there are many variables to consider for a substantial improvement of the whole Question Answering system, and particularly at the initial steps, where passage retrieval and candidate answer selection are determinant for the improvement of system’s recall.
Analyzing the Aftermath of the McColo Shutdown

This paper examines how spam behavior was impacted by the shutdown of McColo, a service provider known for its lax security enforcement. Since the shutdown, a variety of sources have reported significant changes to global spam patterns. In an effort to clarify how spam has changed, we examine reputation data provided by a leading security vendor and present an analysis of spam before and after the McColo shutdown. We show that the actual number of spammers has decreased. We also examine the distribution of spammers both geographically and across the IP space. Our results show that 87% spam sending regions suffered some reductions. Despite this however, the number of sources identified as spammers is still monotonically increasing and the spam volume has recovered to its pre-shutdown levels.
Adaptive Index Deletion in XML Document Based on Tree Traversal Order

How to rapidly delete the XML index item to improve the query efficiently has received many attentions in resent research. However, the deletion maintenance of the index on the XML document is important also in dynamic application, which may limit efficiency when the scale of modification operation is high because the index maintenances need lots of I/Os and CPU time. In this paper we introduce a tree traversal deletion order on the XML index, this algorithms build the sub-tree of the deletion index nodes before the nodes are deleted from the index to avoid the repeat traversal on the index tree. Experimental results from our prototype system implementation highlight the correctness and efficiency of our solution. Keywords-Tree Travesal Order; Node Order; Index deletion;
Learning to Control an Octopus Arm with Gaussian Process Temporal Difference Methods

The Octopus arm is a highly versatile and complex limb. How the Octopus controls such a hyper-redundant arm (not to mention eight of them! ) is as yet unknown. Robotic arms based on the same mechanical principles may render present day robotic arms obsolete. In this paper, we tackle this control problem using an online reinforcement learning algorithm, based on a Bayesian approach to policy evaluation known as Gaussian process temporal difference (GPTD) learning. Our substitute for the real arm is a computer simulation of a 2-dimensional model of an Octopus arm. Even with the simplifications inherent to this model, the state space we face is a high-dimensional one. We apply a GPTD-based algorithm to this domain, and demonstrate its operation on several learning tasks of varying degrees of difficulty.
Problem investigation of min-max method for RSSI based indoor localization

This paper evaluates the performance of min-max and trilateration methods for RSSI-based indoor localization by a real test. Our experiments have been carried out in a laboratory room in the Department of Electrical Engineering, Prince of Songkla University, Thailand. An LPC2103F microcontroller interfacing with a CC2500 radio transceiver which was developed by our research team is used as a wireless node. The experimental result from a given scenario demonstrates that the min-max method significantly gives the better performance than the trilateration method; an average estimated position is closer to a real target position, and an average error distance is smaller. For the RSSI-based min-max method, we also summarize its limitations as found during the experiment; our finding can be used as information for researchers to further develop the min-max method.
Shape Measurement System of Foot Sole Surface from Flatbed Scanner Image

We present a system to measure 3D shape of sole surface of human foot using flatbed scanner. Our goal is to build a low cost system for reconstructing sole surface of human foot using flatbed scanner for mak- ing tailored shoes. There are two main phases in our system: a photometric parameter estimation and a re- construction phase. The photometric parameter esti- mation calculates the position of the light source in the scanner. The reconstruction phase uses iterative algo- rithm to calculate normal vector and the depth informa- tion. First, we implement photometric parameter esti- mation by scanning some white paper in several slant and rotation angles. We conducted some experiments to obtain the best slant and rotation angle combination for calculating light source position of the scanner. We also propose a new method for estimating light source position of the scanner using foot model. Next, we con- duct reconstruction phase by scanning user's foot. We then apply median filter with 5×5 mask sizes to remove the noise in scanned image. By using the calculated light source position from the previous step and pixel in- tensity of scanned image, depth and normal vector are calculated iteratively. We acquire more accurate light source position by comparing albedo ratio and finally we acquire the 3D shape which average error compared with ground truth data is up to 0.97mm.
A STOCHASTIC APPROACH FOR CREATING DYNAMIC CONTEXT-AWARE SERVICES IN SMART HOME ENVIRONMENT

Context-aware service platforms aim at providing users with dynamic services that adapt to changeful environment. Though various toolkits have been developed, it is still not easy for end-users to program their own personalized services. In this paper, we present a context-aware service platform called Synapse that can adequately relate users’ contexts and services, and automatically generate context-aware services based on users’ habits. By exploiting the recorded histories of contexts and services, Synapse can learn different users’ habits. Then Synapse can predict the most relevant services that users will use in current situation based on their habits, and provide services in different modes. As learning and predicting mechanisms are on the basis of a stochastic approach – Bayesian Networks [5], Synapse can absorb various uncertainties arising from sensor data and provide truly personalized services.
Highly E cient and Encapsulated Re-use of Synchronization Code in Concurrent Object-Oriented Languages

Re-use of synchronization code in concurrent OOlanguages has been considered di cult due to inheritance anomaly, which we minimize with our new proposal. Designed with high practicality in mind, we propose language primitives (plus their implementation) with the following characteristics: (1) it allows multiple synchronization schemes|the language schemes for programming synchronization|to coexist and be integrated, (2) re-use of synchronization code is done similarly to sequential OO-languages for user familiarity, (3) it o ers high degree of encapsulation|even synchronization schemes could be encapsulated in superclasses in many cases, and (4) it can be e ciently implemented on conventional MPPs. We demonstrate the e ectiveness of our proposal with solutions to the example inheritance anomaly cases from [16]. We also give an overview of the implementation architecture, along with preliminary benchmarks. The proposed language primitives are being incorporated into our ABCL/onAP1000 running on Fujitsu's 512-node MPP, AP1000.
FUSE Observations of Cooling-Flow Gas in the Galaxy Clusters A1795 and A2597

We present far-ultraviolet spectroscopy of the cores of the massive cooling-flow clusters Abell 1795 and 2597, obtained with the Far Ultraviolet Spectroscopic Explorer. As the intracluster gas cools through 3 × 105 K, it should emit strongly in the O VI λλ1032, 1038 resonance lines. We report the detection of O VI λ1032 emission in A2597, with a line flux of × 10-15 ergs cm-2 s-1, as well as detection of emission from C III λ977. A marginal detection of C III λ977 emission is also reported for A1795. These observations provide evidence for a direct link between the hot (107 K) cooling-flow gas and the cool (104 K) gas in the optical emission line filaments. Assuming simple cooling-flow models, the O VI line flux in A2597 corresponds to a mass deposition rate of ~40 M☉ yr-1 within the central 36 kpc. Emission from O VI λ1032 was not detected in A1795, with an upper limit of 1.5 × 10-15 ergs cm-2 s-1, corresponding to a limit on the mass cooling-flow rate of (28 kpc) < 28 M☉ yr-1. We have considered several explanations for the lack of detection of O VI emission in A1795 and the weaker than expected flux in A2597, including extinction by dust in the outer cluster and quenching of thermal conduction by magnetic fields. We conclude that a turbulent mixing model, with some dust extinction, could explain our O VI results while also accounting for the puzzling lack of emission by Fe XVII in cluster cooling flows.
A Secure , Peer-to-Peer File Locker System

We have built a secure, distributed, scalable, peer-to-peer file-locker system which enables users to mirror files of their choice in a decentralized "cloud" of individually untrusted commodity consumer computers, while still ensuring the integrity of replicated files by utilizing keyed-hash message authentication codes. Our system is cross-platform (it can be ported to any device which is capable of running the Java virtual machine) and utilizes standard TCP/IP networking to promote adoption and usage across the wider internet. Participants in the system are registered in a distributed hash table backed by the Chord algorithm, therefore saves and lookups in the system scale logarithmically in proportion to the number of participating clients.
DNA Targeting Sequence Improves Magnetic Nanoparticle-Based Plasmid DNA Transfection Efficiency in Model Neurons

Efficient non-viral plasmid DNA transfection of most stem cells, progenitor cells and primary cell lines currently presents an obstacle for many applications within gene therapy research. From a standpoint of efficiency and cell viability, magnetic nanoparticle-based DNA transfection is a promising gene vectoring technique because it has demonstrated rapid and improved transfection outcomes when compared to alternative non-viral methods. Recently, our research group introduced oscillating magnet arrays that resulted in further improvements to this novel plasmid DNA (pDNA) vectoring technology. Continued improvements to nanomagnetic transfection techniques have focused primarily on magnetic nanoparticle (MNP) functionalization and transfection parameter optimization: cell confluence, growth media, serum starvation, magnet oscillation parameters, etc. Noting that none of these parameters can assist in the nuclear translocation of delivered pDNA following MNP-pDNA complex dissociation in the cell’s cytoplasm, inclusion of a cassette feature for pDNA nuclear translocation is theoretically justified. In this study incorporation of a DNA targeting sequence (DTS) feature in the transfecting plasmid improved transfection efficiency in model neurons, presumably from increased nuclear translocation. This observation became most apparent when comparing the response of the dividing SH-SY5Y precursor cell to the non-dividing and differentiated SH-SY5Y neuroblastoma cells.
Y Comments on the Future of TEX and METAFONT 1

: : : specifically to identify, develop, operate, fund, support, promote and encourage charitable, educational and scientific programs and projects which will stimulate those who have an interest in systems for typesetting technical text and font design; to exchange information of same and associated use of computer peripheral equipment; to establish channels to facilitate the exchange of macro packages, etc., through publications and otherwise; and to develop, implement and sponsor educational programs, seminars and conferences in connection with the foregoing: : :
An Adaptive UKF Algorithm for Process Fault Prognostics

For standard unscented Kalman filters (UKF), the unknown covariance matrices of prior state estimate error, output prediction error and posterior state estimate error propagate recursively through fixed models, which does not consider the actual distribution information of errors. With respect to above problem, an adaptive UKF algorithm is proposed to improve the estimation of error covariance matrices. By introducing measurement innovation into the estimation of error covariance matrices, the proposed algorithm can compute the Kalman gain adaptively and make the future measurement innovation series uncorrelated. The adaptive UKF algorithm is then utilized for nonlinear process fault prognostics. Simulation results on a continuous stirred tank reactor demonstrate the effectiveness of the proposed algorithm.