Miracle-dz/UniFAR-FTUs huggingface dataset:
Wavelet packet feature extraction for vibration monitoring

Condition monitoring of dynamic systems based on vibration signatures has generally relied upon Fourier based analysis as a means of translating vibration signals in time domain into the frequency domain. However, Fourier analysis provided a poor representation of signals well localized in time. The wavelet packet transform is introduced as an alternative means of extracting time-frequency information from vibration signature. Moreover, with the aid of statistical based feature selection criteria, a lot of feature components containing little discriminant information could be discarded resulting in a feature subset with reduced number of parameters. This significantly reduces the long training time that is often associated with neural network classifier and increases the generalization ability of the neural network classifier.
In vitro, ex vivo and in vivo anti-hypertensive activity of Chrysophyllum cainito L. extract.

Chrysophyllum cainito L. , a traditional herbal medicine, could have the potential for management of hypertension due to presence of polyphenolic compounds. The extracts and fractions of the pulp of plant were evaluated for in vitro (inhibition of angiotensin I converting enzyme/ACE assay), ex vivo (isolated aorta relaxation assay) and in vivo (salt induced hypertensive rat assay). The alcoholic and aqueous extract (ALE and AQE respectively) of fruit of plant C. cainito was having 14.8 and 9.2% yield respectively. The fractionation with ethyl alcohol (EAF) and butanol (BTF) yielded 2.52 & 2.17% respectively from ALE and 0.46 & 0.31% respectively from AQE with respect to fruit pulp dry weight. More phenolic content was found in ALE (3.75±0.15 mg gallic acid equivalent or GAE g(-1) of dry power of fruit pulp) compared to AQE and maximum in ethyl acetate fraction of ALE (ALE-EAF) (2.32±0.21 mg GAE g(-1) of dry power of fruit pulp) among all fractions. ACE inhibition activity was found to be maximum in ALE-EAF 62.5±7.34%. While ex vivo study using isolated tissue of aorta showed again showed maximum activity (62.82±6.19 and 46.47±8.32% relaxation with 50 µg mL(-1) and 10 µg mL(-1) GAE concentration respectively). ALE-EAF reduced the elevated arterial pressure of salt induced hypertensive rat significantly to the level of normotensive animal group. Results of ALE-EAF have shown its potential as a source for novel constituent for the treatment hypertension and should further be studied for isolation of specific constituent for more effectiveness.
An iterative splitting method via waveform relaxation

This paper explores a new numerical strategy for a closed formulation of iterative splitting methods and their embedding in classical waveform-relaxation methods. Since iterative splitting has been developed in several papers, an abstract framework that relates these methods to other classical splitting methods would be useful and is needed. Here, we present an embedding of the iterative splitting method in the waveform-relaxation and exponential splitting methods. While we can use the theoretical background of the classical schemes, a simpler iterative splitting analysis is obtained. This is achieved by basing the analysis on semigroup and fixpoint schemes. Our approach is illustrated with numerical results obtained on differential equations with constant and time-dependent coefficients.
MULTILAYER BIT ALLOCATION FOR VIDEO ENCODING Elavarasan . R 1 and Dr

Video compression approach removes spatial and temporal redundancy based on the signal statistical correlation. Bit allocation technique adopts a visual distortion model for a better rate visual distortion video coding. Visual distortion model uses both motion and the texture structures in the video sequences. The existing video coding mechanisms reduces the bit rate for video coding. However to get better video compression ratio there is a need for multilayer compression technique. In this paper we proposed a multilayer bit allocation video coding mechanism. The proposed model reduces the bit allocation for video coding by retaining the same video quality. The experimental results using the proposed model reduced the bit rate by 3% to 4%. The result are promising. Finally we conclude with conclusion and future work.
Advanced-Level Security in Network and Real-Time Applications Using Machine Learning Approaches

Machine learning is a field that is developed out of artificial intelligence (AI). Applying AI, we needed to manufacture better and keen machines. Be that as it may, aside from a couple of simple errands, for example, finding the briefest way between two points, it isn't to program more mind boggling and continually developing difficulties. There was an acknowledgment that the best way to have the capacity to accomplish this undertaking was to give machines a chance to gain from itself. This sounds like a youngster learning from itself. So, machine learning was produced as another capacity for computers. Also, machine learning is available in such huge numbers of sections of technology that we don't understand it while utilizing it. This chapter explores advanced-level security in network and real-time applications using machine learning.
The BOLD Response in the Rat Hippocampus Depends Rather on Local Processing of Signals than on the Input or Output Activity. A Combined Functional MRI and Electrophysiological Study

Functional magnetic resonance imaging (fMRI) of the human brain is widely used in neuroscience, but the exact relationship between measured fMRI response and the underlying changes in neuronal activity is still elusive. To obtain further information about the specific roles of synaptic (input) and spiking activity (output) for the generation of fMRI-related signals, we used an approach that combines electrophysiological and MRI measurements in the anatomically and physiologically well defined rat hippocampus. Direct electrical stimulation of the perforant pathway enabled us to control synchronized input activity to the dentate gyrus, whereas recorded population spikes from the granular cell layer indicated the dentate output activity. The perforant pathway was first stimulated with 15 identical pulse trains (10 Hz for 8 s), and evoked blood oxygenation level-dependent (BOLD) responses and population spikes were measured for each individual stimulus train. Spatial and magnitude aspects of the elicited BOLD responses differentially changed in the dentate gyrus and hippocampus from early to late stimulus trains together with population spike latencies in the dentate indicating delayed inhibitory network processing. Furthermore, the same number of stimuli presented in different patterns within trains (i.e., bursts of 10 stimuli at 50, 100, or 200 Hz) clearly altered the BOLD responses. Similarly, variations in the BOLD response also occurred when different stimulus patterns were chosen that caused the same number of population spikes. The results indicate that neuronal network activity including inhibitory interneurons rather than exclusively the input or spiking activity of the principal neurons determine a BOLD response to repetitive stimuli.
Assessing the Potential of Climate Change Mitigation Actions in Three Different City Types in Finland

As the effects of global warming have become more evident, ambitious short-term greenhouse gas emission reduction targets have been set in recent years. Many cities worldwide have adopted an active approach to climate change mitigation, but policy makers are not always knowledgeable of the true effects of their planned mitigation action. The purpose of this paper is to evaluate the effectiveness of different mitigation strategies in achieving low-carbon urban communities. The assessment is conducted via means of consumption based hybrid life-cycle assessment, which allows the reduction potential to be analyzed from the perspective of an individual resident of the urban community. The assessed actions represent strategies that are both adopted by the case cities and possible to implement with current best practices in Finland. The four assessed actions comprise: (1) dense urban structure with less private driving; (2) the use of energy production based on renewable sources; (3) new low-energy residential construction; and (4) improving the energy efficiency of existing buildings. The findings show that the effectiveness depends greatly on the type of city, although in absolute terms the most significant reduction potential lies with lowering the fossil fuel dependence of the local energy production.
GENOTYPE‐ENVIRONMENT INTERACTION FOR CLIMATE AND COMPETITION IN A NATURAL POPULATION OF FLOUR BEETLES, TRIBOLIUM CASTANEUM

The norm of reaction, the set of average phenotypes produced by a genotype in different environments, can be affected by spatial variation in natural selection especially when there exists genotype‐environment interaction. In subdivided populations, the greater the genotype‐environment interaction variance and the lower the migration rate, the more independent are the possible evolutionary trajectories for local adaptation. I examined genotype‐environment interaction in the rate of population increase for lineages randomly derived from a wild population of Tribolium castaneum across a series of ecologically important environments. The lineages were derived from an outbred, wild‐caught population by 14 generations of random genetic drift, during which the effective size of each lineage was approximately 22 breeding adults. The environments studied were the classic temperate‐wet and cold‐dry climates of Park (1954) in factorial combination with two genetic strains of a congeneric competitor, T. confusum. Much among‐lineage genetic variation for rate of population increase was found for each of these ecologically important environments of climate and competition. Genotype‐environment interaction accounted for 40.5% of the total among‐lineage variance in rate of population increase signifying that the performance of a lineage in one environment is not necessarily a good predictor of its performance in another. Changing the genetic identity of the competitor changed the rate of increase of some lineages as much or more than changing the climatic conditions of temperature and humidity. This is the first empirical study to characterize the genotype‐environment interaction variance associated with genetic variation in a competing congeneric species. This competitor‐specific genetic variation in competitive ability may play an important role in coevolution in subdivided populations.
The potential effects of changing HIV treatment policy on tuberculosis outcomes in South Africa: results from three tuberculosis-HIV transmission models

Objective(s):Many countries are considering expanding HIV treatment following recent findings emphasizing the effects of antiretroviral therapy (ART) on reducing HIV transmission in addition to already established survival benefits. Given the close interaction of tuberculosis (TB) and HIV epidemics, ART expansion could have important ramifications for TB burden. Previous studies suggest a wide range of possible TB impacts following ART expansion. We used three independently developed TB-HIV models to estimate the TB-related impact of expanding ART in South Africa. Design:We considered two dimensions of ART expansion – improving coverage of pre-ART and ART services, and expanding CD4-based ART eligibility criteria (from CD4 <350 to CD4 <500 or all HIV-positive). Methods:Three independent mathematical models were calibrated to the same data pertaining to the South African HIV–TB epidemic, and used to assess standardized ART policy changes. Key TB impact indictors were projected from 2014 to 2033. Results:Compared with current eligibility and coverage, cumulative TB incidence was projected to decline by 6–30% over the period 2014-2033 if ART eligibility were expanded to all HIV positive individuals, and by 28–37% if effective ART coverage were additionally increased to 80%. Overall, expanding ART was estimated to avert one TB case for each 10–13 additional person-years of ART. All models showed that TB incidence and mortality reductions would grow over time, but would stabilize towards the end of the projection period. Conclusion:ART expansion could substantially reduce TB incidence and mortality in South Africa and could provide a platform for collaborative HIV-TB programs to effectively halt HIV-associated TB.
Signal Modulation Recognizer Based on Method of Artificial Neural Networks

Communication signals travelling in space with different modulation types and different frequencies fall in a very wide band. Usually, it is required to identify and monitor these signals for many applications. Some of these applications are in civilian purposes such as signal confirmation, interference identification and spectrum management. this paper described the new original configuration of subsystems for the automatic modulation recognition of digital and analog signals. The signal recognizer being developed consists of five subsystems: (1) adaptive antenna arrays, (2) pre-processing of EM signals, (3) key features extraction, (4) modulation recognizer and (5) output stage. The choice of maximum value of spectral power density of the normalized-centred amplitude, standard deviation of the absolute value of the centred non-linear component of the instantaneous phase, standard deviation of the absolute value of the normalized-centred instantaneous amplitude, standard deviation of the absolute value of the normalized-centred instantaneous frequency, spectrum symmetry measure as key features for the digital and analogue modulation recognizer based on the artificial neural networks (ANNs). The new original structure of the recognizer of digital and analogue signals is described. The modulation recognizer uses two ANNs with two hidden layers. The results are summarized for real EM signals.
Small area estimation from the American Community Survey using a hierarchical logistic model of persons and housing units

AbstractAmultivariate binomial/multinomial modelisproposedforestimatingpoverty and housing-unit characteristics of small areas. It is demon-strated that the model is in concordance with the design in that themodel can reproduce within small area design-based estimates of vari-ance. The methodology for producing estimates is presented, alongwith several evaluations using data from the American CommunitySurvey. Itis concludedthat this approach can bea viableway to makesmall area estimates without needing to assume that the design-basedestimates of variance are xed (as in most area-level models). Keywords: Hierarchical Model, Logistic parameterization, Unit levelSmall Area Model, Full Bayesian Analysis 1 Introduction In an e ort to provide accurate estimates for census-type aggregations suchas tracts, on a yearly basis from the American Community Survey (ACS),small area methods can be employed. A hierarchical logistic model of bothpersons and housing units within tracts is proposed for making tract levelestimates. This approachdirectly accounts forthe uncertainty ofwithin tractvariability, a component whose estimate is often regarded as xed in othersmall area estimation methods. Since within-tract variability is a componentthat a ects borrowing strength, this approach automatically accounts for theadditional uncertainty of unknown within-tract variability in the magnitudeof borrowing strength.A typical assumption used in small area estimation is that the directsmall area estimates are normally distributed with unknown mean but withthe corresponding estimated variance treated as xed and known (e.g. seeRao (1999), eq 2.2). A model linking the unknown small area means togetheris then used to produce nal estimates. Due to small sample sizes in a smallarea, variance estimates of the direct estimates may be imprecise and, in thatcase, should not be treated as known. In addition, the direct estimates may1
Predicting early renal allograft function using clinical variables.

BACKGROUND Suboptimal early graft function following renal transplantation remains a significant challenge. It is suggested that clinical variables (or scoring systems based thereon) may predict the occurrence of delayed graft function (DGF), defined as post-operative dialysis requirement. However, data is conflicting, and suboptimal renal function not requiring dialysis has been little investigated. This study tested the ability of clinical variables to predict suboptimal early function variably assessed by: (i) DGF (dialysis requirement during the first week); (ii) DGF duration; (iii) slow graft function (creatinine>3 mg/dl on day 5); (iv) creatinine reduction ratio on day 2. METHODS Details on 217 consecutive renal transplant recipients were collected. All received ciclosporin-based immunosuppression. Multiple regression analysis was used to assess the association between individual clinical variables and suboptimal early graft function. Also tested were three scoring systems incorporating clinical variables [US Renal Database System (USRDS score), deceased donor score (DDS) and expanded criteria donor kidneys]. Receiver operated-characteristic curve analysis was used to assess the predictive power of clinical variables and scoring systems. RESULTS Early graft function was associated with donor age, donor body mass index, donor hypertension, donation following cardiac death, black recipient ethnicity, recipient weight and cold ischaemic time (P<or=0.05 for all). All scoring systems showed associations with early graft function, although only USRDS score remained in the multiple regression model. The overall utility of the USRDS score in predicting DGF was moderate at best, although improved at extreme scores (specificity: 95%; positive predictive value: 73%; for USRDS score>or=150). CONCLUSIONS Clinical variables and scores have moderate predictive ability for early graft function and although of potential use in clinical practice, caution should be exercised before altering patient management based solely on them.
Influence of Location, Population, and Climate on Building Damage and Fatalities due to Australian Bushfire: 1925–2009

Abstract This study reevaluates the history of building damage and loss of life due to bushfire (wildfire) in Australia since 1925 in light of the 2009 Black Saturday fires in Victoria in which 173 people lost their lives and 2298 homes were destroyed along with many other structures. Historical records are normalized to estimate building damage and fatalities had events occurred under the societal conditions of 2008/09. There are relationships between normalized building damage and the El Nino–Southern Oscillation and Indian Ocean dipole phenomena, but there is no discernable evidence that the normalized data are being influenced by climatic change due to the emission of greenhouse gases. The 2009 Black Saturday fires rank second in terms of normalized fatalities and fourth in terms of normalized building damage. The public safety concern is that, of the 10 years with the highest normalized building damage, the 2008/09 bushfire season ranks third, behind the 1925/26 and 1938/39 seasons, in terms of the r.
Comparing Scores Intended for Ranking

Often, ranking is performed on the the basis of some scores available for each item. The existing practice for comparing scoring functions is to compare the induced rankings by one of the multitude of rank comparison methods available in the literature. We suggest that it may be better to compare the underlying scores themselves. To this end, a generalized Kendall distance is defined, which takes into consideration not only the final ordering that the two schemes produce, but also at the spacing between pairs of scores. This is shown to be equivalent to comparing the scores after fusing with another set of scores, making it theoretically interesting. A top k version of the score comparison methodology is also provided. Experimental results clearly show the advantages score comparison has over rank comparison.
Two Efficient Algorithms for Linear Time Suffix Array Construction

We present, in this paper, two efficient algorithms for linear time suffix array construction. These two algorithms achieve their linear time complexities, using the techniques of divide-and-conquer, and recursion. What distinguish the proposed algorithms from other linear time suffix array construction algorithms (SACAs) are the variable-length leftmost S-type (LMS) substrings and the fixed-length d-critical substrings sampled for problem reduction, and the simple algorithms for sorting these sampled substrings: the induced sorting algorithm for the variable-length LMS substrings and the radix sorting algorithm for the fixed-length d-critical substrings. The very simple sorting mechanisms render our algorithms an elegant design framework, and, in turn, the surprisingly succinct implementations. The fully functional sample implementations of our proposed algorithms require only around 100 lines of C code for each, which is only 1/10 of the implementation of the KA algorithm and comparable to that of the KS algorithm. The experimental results demonstrate that these two newly proposed algorithms yield the best time and space efficiencies among all the existing linear time SACAs.
DATA DISTRIBUTION MANAGEMENT IN THE HLA Multidimensional Regions and Physically Correct Filtering

The goal of HLA Data Distribution Management (DDM) services is to limit the messages received by federates in large distributed federations to those messages of interest in order to reduce (1) the data set required to be processed by the receiving federate and (2) the message traffic over the network. If this functionality is provided in a manner that is efficient, it can significantly improve the performance and scalability of large distributed federations. We provide an overview of the fundamental DDM mechanisms, routing spaces with update and subscription regions, and show how DDM services interoperate with other HLA services to allow federates to discover objects and attributes of interest. We proceed to derive strategies for implementing physically correct filters to account for network latencies and object movement in the virtual environment. These strategies rely on mathematically derived extensions of update and subscription regions to optimize filter efficiency.
Use of a centrifugal bioreactor for cartilaginous tissue formation from isolated chondrocytes

Although a centrifugal bioreactor (CCBR) supports high‐density mammalian suspension cell cultures by balancing drag, buoyancy, and centrifugal forces, to date anchorage‐dependent cultures have not been tried. Also, steady or intermittent hydrostatic pressures of 8 to 500 kPa, and shears of 0.02 to 1.4 N/m2 can be simultaneously applied in the CCBR. This article demonstrates the use of a CCBR to stimulate chondrogenesis in a high‐density culture. At 3 weeks, histological results show even distribution of glycosaminoglycan (GAG) and collagen, with 1,890 ± 270 cells/mm2 cell densities that exceed those of 1,470 ± 270 in pellet cultures. Analysis of collagen content reveals similar levels for all treatment groups; 6.8 ± 3.5 and 5.0 ± 0.4 μg collagen/μg DNA for 0.07 and 0.26 MPa CCBR cultures, respectively, in contrast to 6.6 ± 1.9 values for control pellet cultures. GAG levels of 5.6 ± 1.5 and 4.1 ± 0.9 μg GAG /μg DNA are present for cultures stressed at 0.07 and 0.26 MPa, respectively, in comparison to control pellet cultures at the 8.4 ± 0.9 level. Although results to date have not revealed mechanical stress combinations that stimulate chondrogenesis over unstressed controls, system advantages include continuous culture at cell densities above those in the pellet, precise medium control, the ability to independently vary multiple mechanical stresses over a broad range, and the flexibility for integration of scaffold features for future chondrogenesis stimulation studies. © 2011 American Institute of Chemical Engineers Biotechnol. Prog. , 2011