Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Application of Artificial Neural Network for the Solution of Inverse Kinematics Controls of Robotic Manipulators

In robotic applications and research, inverse kinematics is one of the most important problems in terms of robot kinematics and control. Consequently, finding the solution of Inverse Kinematics in now days is considered as one of the most important problems in robot kinematics and control. As the intricacy of robot manipulator increases, obtaining the mathematical, statistical solutions of inverse kinematics are difficult and computationally expensive. For that reason, now soft-computing based highly intelligent based model applications should be adopted to getting appropriate solution for inverse kinematics. In this paper, a novel application of artificial neural network is used for controlling a robotic manipulator. The proposed methods are based on the establishments of the non- linear mapping between Cartesian and joint coordinates using multi layer perceptron and functional link artificial neural network.
Power Electronics Reliability Comparison of Grid Connected Small Wind Energy Conversion Systems

This work presents a power electronics reliability comparison of the power conditioning system for both the Permanent Magnet Generator (PMG) and Wound Rotor Induction Generator (WRIG)-based small Wind Energy Conversion Systems (WECS). The power conditioning system for grid connection of the PMG-based system requires a rectifier, boost converter and a grid-tie inverter, while the WRIG-based system employs a rectifier, a switch and an external resistor in the rotor side with the stator directly connected to the grid. Reliability of the power conditioning system is analyzed for the worst case scenario of maximum conversion losses at a predetermined wind speed. The analysis reveals that the Mean Time Between Failures (MTBF) of the power conditioning system of a WRIG-based small wind turbine is much higher than the MTBF of the power conditioning system of a PMG-based small wind turbine. The investigation is extended to identify the least reliable component within the power conditioning system for both systems. It is shown that the inverter has the dominant effect on the system reliability for the PMG-based system, while the rectifier is the least reliable for the WRIG-based system. This research indicates that the WRIG-based small wind turbine with a simple power conditioning system is a much better option for small wind energy conversion system.
The Development And Application Of A Simple Methodology For Recording Rock Art Using Consumer‐Grade Digital Cameras

A simple methodology for recording rock art has been recently developed in Australia and tested on Aboriginal rock art, including both petroglyphs and pictographs (engraved and painted images, respectively). The approach was based on commercial photogrammetric software and consumer‐grade digital cameras, because it was believed that archaeologists, conservators and site managers need simple and cost‐effective methods to record and document rock art. This methodology has been adopted subsequently by the Northumberland and Durham Rock Art Project working in conjunction with English Heritage, to assist in recording 1500 prehistoric engraved panels located across the north‐east of England. Significantly, the fieldwork was carried out by enthusiastic volunteers, willing to sacrifice their weekends to capture imagery suitable for digital photogrammetry.
Compression Artifact Removal by Deep Residual Networks

We propose a method for learned compression artifact removal by post-processing of BPG compressed images. We trained three networks of different sizes. We encoded input images using BPG with different QP values. We submitted the best combination of test images, encoded with different QP and post-processed by one of three networks, which satisfy the file size and decode time constraints imposed by the Challenge. The selection of the best combination is posed as an integer programming problem. Although the visual improvements in image quality is impressive, the average PSNR improvement for the results is about 0.5 dB.
Individualisation in Swedish Adult Education and the Shaping of Neo-liberal Subjectivities

ABSTRACT In this article we have analysed the ways a discourse on individualisation is taking shape within adult education in Sweden, how it operates, and what effects it has in terms of shaping student subjectivity. Drawing on a post-structural theorisation we analyse interviews with teachers and students in municipal adult education and folk high schools (FHS). The analysis illustrates how both institutions contribute to the shaping of individualised subjectivities, although differently. At the end, a general question is raised about what happens with the democratic function of adult education in general when a discourse on individualisation operates in the ways described and, more specifically, asks what is happening to FHS as an educational practice that upholds its self-image as a last bastion of a collective notion of learning and subjectivity and nurturing an educational practice of learning democracy?
Inverse isolation of dissolved inorganic nitrogen yield for individual land-uses from mosaic land-use patterns within a watershed

Abstract. This study combines the observed riverine DIN (dissolved inorganic nitrogen) export and the controlling factors (land-use, population and discharge) to inversely estimate the effective DIN yield factors for individual land-use and DIN per capita loading. A total of 16 sub-catchments, with different land-use compositions on the Danshui River of Taiwan, were used in this study. Observed riverine DIN concentrations and yields varied from 20–450 μM and 400–10 000 kg N km −2 yr −1 corresponding to the increase of urbanization gradient (e.g. building and population). Meanwhile, the transport behaviors changed from hydrological enhancement to dilution with increasing urbanization as well. Our method shows that the DIN yield factors, independent of discharge, are 12.7, 63.9, and 1381.0 μM, for forest, agriculture, and building, respectively, which equals to 444.5, 2236.5, 48 335 kg N km −2 yr −1 at the given annual runoff of 2500 mm. The agriculture DIN yield only accounts for 10% of fertilizer application indicating the complicated N cascade and possible over fertilization. The DIN per capita loading (~0.49 kg N capita −1 yr −1 ) which is lower than the documented human N emission (1.6–5.5 kg N capita −1 yr −1 ) can be regarded as an effective export coefficient after treatment or retention. A conducted scenario experiment supports the observations demonstrating the capability for assessment. We therefore, can extrapolate all possible combinations of land-use, discharge, and population density for evaluation. This can provide a strong basis for watershed management and supplementary estimation for regional to global study.
Wake-Up-Word Feature Extraction on FPGA

Wake-Up-Word Speech Recognition task (WUW-SR) is a computationally very demand, particularly the stage of feature extraction which is decoded with corresponding Hidden Markov Models (HMMs) in the back-end stage of the WUW-SR. The state of the art WUW-SR system is based on three different sets of features: Mel-Frequency Cepstral Coefficients (MFCC), Linear Predictive Coding Coefficients (LPC), and Enhanced Mel-Frequency Cepstral Coefficients (ENH_MFCC). In (front-end of Wake-Up-Word Speech Recognition System Design on FPGA) [1], we presented an experimental FPGA design and implementation of a novel architecture of a real-time spectrogram extraction processor that generates MFCC, LPC, and ENH_MFCC spectrograms simultaneously. In this paper, the details of converting the three sets of spectrograms 1) Mel-Frequency Cepstral Coefficients (MFCC), 2) Linear Predictive Coding Coefficients (LPC), and 3) Enhanced Mel-Frequency Cepstral Coefficients (ENH_MFCC) to their equivalent features are presented. In the WUW- SR system, the recognizer’s frontend is located at the terminal which is typically connected over a data network to remote back-end recognition (e.g., server). The WUW-SR is shown in Figure 1. The three sets of speech features are extracted at the front-end. These extracted features are then compressed and transmitted to the server via a dedicated channel, where subsequently they are decoded.
Piecewise linear fitting and trend changing points of climate parameters

Finding an overall linear trend is a common method in scientific studies. It is almost a requirement when one intends to study variability. Nevertheless, when dealing with long climate temporal series, fitting a straight line only seldom has a relevant meaning. This paper proposes and describes a new methodology for finding overall trends, and, simultaneously, for computing a new set of climate parameters: the breakpoints between periods with significantly different trends. The proposed methodology uses a least‐squares approach to compute the best continuous set of straight lines that fit a given time series, subject to a number of constraints on the minimum distance between breakpoints and on the minimum trend change at each breakpoint. The method is tested with three climate time series.
Optimal Monetary Policy with In‡ation-Conditional Macroeconomic Volatility

This paper develops an econometric model of the US macroeconomy that is potentially heteroskedastic and uses it to analyze optimal monetary policy. This model allows the variance structure to depend in a linear or quadratic way on a lagged endogenous variable such as the in‡ation or interest rate, consistent with the Okun (1971) and Friedman (1977) conjecture that macroeconomic volatility depends upon the underlying rate of in‡ation. The linear speci.cation is the analogue of the Cox, Ingersoll, and Ross (1985) ‘square root’ volatility speci.cation found in the term structure literature, but the quadratic speci.cation is novel. Both models . t nicely into the linear-quadratic framework used in the optimal control literature. Theoretically, the quadratic component makes policy more responsive to in‡ation shocks in the same way that an increase in the welfare weight attached to in‡ation does, while the linear component reduces the steady state rate of in‡ation. Empirical results for the period 1961-2009 underline the statistical signi.cance of in‡ation-dependent US macroeconomic volatility revealed by research on the term structure. Analysis of the welfare losses associated with in‡ation and macroeconomic volatility shows that the conventional homoskedastic model seriously underestimates the potential welfare gains from policy optimization.
Multiple-scales analysis of photonic crystal waveguides

The multiple-scales method is used to derive a scalar differential equation that describes the envelopes of photonic crystal waveguide modes. For a photonic crystal heterostructure waveguide and an air core photonic crystal waveguide, the mode frequencies calculated from the envelope approximation and full numerical simulations agree to 9% in the worst case when compared to the frequency difference of the band edges. The single-mode and cutoff width conditions for a photonic crystal waveguide are predicted and verified.
A comparative study of fluorescence resonance energy transfer fret in solution phase and in hybrid films prepared by LB and LBL techniques

Fluorescence resonance energy transfer (FRET) between two dyes acriflavine (Acf) and rhodamine B (RhB) were investigated in solution and layer-by-layer (LbL) self assembled films in presence and absence of clay mineral laponite. UV–Vis absorption and fluorescence spectroscopy studies suggest both the dyes present mainly as monomer in solution and films. Energy transfer occurred from Acf to RhB in solution and LbL films. The energy transfer efficiency increases in presence of clay laponite and the maximum efficiency were 92.50% and 55.71% in clay dispersion and in LbL films respectively. Presence of laponite eywords: luorescence resonance energy transfer yes lay aponite particles onto LbL film was confirmed by atomic force microscopy investigations with a surface coverage of more than 75%. Energy transfer efficiency was pH sensitive and the energy transfer efficiency varies from 4.5% to 44.45% in mixed dye solution for a change in pH from 3.0 to 12.0. With proper calibration it is possible to use the present system under investigation to sense pH over a wide range of pH from 3.0 to 12.0. ayer-by-layer
Deposition of calcium carbonate in karst caves: role of bacteria in Stiffe's Cave

Bacteria make a significant contribution to the accumulation of carbonate in several natural habitats where large amounts of carbonates are deposited. However, the role played by microbial communities in speleothem formation (stalactites, stalagmites etc.) in caves is still unclear. In bacteria carbonate is formed by autotrophic pathways, which deplete CO2 from the environment, and by heterotrophic pathways, leading to active or passive precipitation. We isolated cultivable heterotrophic microbial strains, able to induce CaC03 precipitation in vitro, from samples taken from speleothems in the galleries of Stiffe's cave, L' Aquila, Italy. We found a large number of bacteria in the calcite formations (I x 10 to 5 X 10 cells g\ Microscopic examination, in laboratory conditions at different temperatures, showed that most of the isolates were able to form calcium carbonate microcrystals. The most crystalline precipitates were observed at 32T. No precipitation was detected in un-inoculated controls media or in media that had been inoculated with autoclaved bacterial cells. X-ray diffraction (XRD) analysis showed that most of the carbonate crystals produced were calcite. Bacillus strains were the most common calcifying isolates collected from Stiffe's Cave. Analysis of carbonate-solubilization capability revealed that the non-calcifying bacteria were carbonate solubilizers.
ubstrate binding pocket residues of human lkyladenine-DNA glycosylase critical for ethylating agent survival

Human alkyladenine-DNA glycosylase (AAG) initiates base excision repair (BER) of alkylated and deaminated bases in DNA. Here, we assessed the mutability of the AAG substrate binding pocket, and the essentiality of individual binding pocket amino acids for survival of methylation damage. We used oligonucleotide-directed mutagenesis to randomize 19 amino acids, 8 of which interact with substrate bases, and created more than 4.5 million variants. We expressed the mutant AAGs in repair-deficient Escherichia coli and selected for protection against the cytotoxicity of either methylmethane sulfonate (MMS) or methyllexitropsin (Me-lex), an agent that produces 3-methyladenine as the predominant base lesion. Sequence analysis of 116 methylation-resistant mutants revealed no substitutions for highly conserved Tyr127and His136. In contrast, one mutation, L180F, was greatly enriched in both the MMSand Me-lex-resistant libraries. Expression of the L180F single mutant conferred 4.4-fold enhanced survival at the high dose of MMS used for selection. The homogeneous L180F mutant enzyme exhibited 2.2-fold reduced excision of 3-methyladenine and 7.3-fold reduced excision of 7-methylguanine from methylated calf thymus DNA. Decreased excision of methylated bases by the mutant glycosylase could promote survival at high MMS concentrations, where the capacity of downstream enzymes to process toxic BER intermediates may be saturated. The mutant also displayed 6.6and 3.0-fold reduced excision of 1,N6-ethenoadenine and hypoxanthine from oligonucleotide substrates, respectively, and a 1.7-fold increase in binding to abasic site-containing DNA. Our work provides in vivo evidence for the substrate binding mechanism deduced from crystal structures, illuminates the function of Leu180 in wild-type human AAG, and is consistent with a role for balanced expression of BER enzymes in damage survival. Please cite this article in press as: C. -Y. Chen, et al., Substrate binding p methylating agent survival, DNA Repair (2008), doi:10.1016/j.dnarep. 2008.0 ∗ Corresponding author. Tel. : +1 206 543 6015; fax: +1 206 543 3967. E-mail addresses: laloeb@u.washington. edu, pocow@u.washington. 568-7864/$ – see front matter © 2008 Elsevier B.V. All rights reserved. oi:10.1016/j.dnarep. 2008.06.019 ocket residues of human alkyladenine-DNA glycosylase critical for 6.019 © 2008 Elsevier B.V. All rights reserved.
Differentiable Training for Hardware Efficient LightNNs

To reduce runtime and resource utilization of Deep Neural Networks (DNNs) on customized hardware, LightNN has been proposed by constraining the weights of DNNs to be a sum of a limited number (denoted as k ∈ {1, 2}) of powers of 2. LightNNs can therefore replace the multiplication between activations and weights with a shift operation or two shifts and an add operation. To provide a more continuous Pareto-optimal curve of accuracy and runtime so that hardware designers can have more flexible options of DNN configurations, one can customize the k for each convolutional filter. In this paper, we formulate the selection of k to be differentiable, and train the model weights and per-filter k in an end-to-end fashion. Since flexible-k LightNNs (FLightNNs) fully utilize the hardware resources on Field Programmable Gate Arrays (FPGAs), our experimental results show that FLightNN can achieve 2× speedup on FPGAs when compared to LightNN-2, with only 0.1% accuracy degradation. In addition, compared to a 4-bit fixed-point quantization, FLightNN can achieve slightly higher accuracy and 1.4× speedup, due to its lightweight shift operations.
Unsupervised online learning of condition-invariant images for place recognition

This paper presents an online, unsupervised training algorithm enabling vision-based place recognition across a wide range of changing environmental conditions such as those caused by weather, seasons, and day-night cycles. The technique applies principal component analysis to distinguish between aspects of a location’s appearance that are condition-dependent and those that are condition-invariant. Removing the dimensions associated with environmental conditions produces condition-invariant images that can be used by appearance-based place recognition methods. This approach has a unique benefit – it requires training images from only one type of environmental condition, unlike existing data-driven methods that require training images with labelled frame correspondences from two or more environmental conditions. The method is applied to two benchmark variable condition datasets. Performance is equivalent or superior to the current state of the art despite the lesser training requirements, and is demonstrated to generalise to previously unseen locations.
Neuropsychology of music : a rapidly growing branch of psychology

Relationship between brain and music is of interest to musicians, psychologists and neuroscientists. In recent years no other area of psychology of music has seen as much advancement as neuropsychology of music. The aim of the article is to present some main issues in the neuropsychology of music abroad and in Slovenia, to classify research studies into larger categories and to predict the future development of this field. There are different levels of inquiry into the neuropsychology of music: (1) the analysis of normal and abnormal psychological and physiological functions to determine the principles and modes by which the human brain processes, codifies, stores, and produces music, and (2) a description of the clinical deficits in music perception or performance resulting from localized or diffuse damage to the nervous system. Main topics that occupy neuropsychology of music are neuropsychological models of musical processing, functional imaging of musical perception and cognition, and the use of music as a therapeutic and clinical tool. Although some important studies have already been conducted since the year 2003, in Slovenia we faced a "formal" turning point in acknowledging the importance of the connection between music, mind and brain with the Sinapsa's Week of the brain 2009 under the title Brain and music.
Migration of an insulating particle under the action of uniform ambient electric and magnetic fields. Part 2. Boundary formulation and ellipsoidal particles

This paper examines the low-Reynolds-number migration of an insulating and rigid particle that is freely suspended in a viscous liquid metal and subject to uniform ambient electric and magnetic fields $\hbox{\bf\itshape E}$ and $\hbox{\bf\itshape B}. $ Under the same physical assumptions as Part 1, a whole boundary formulation of the problem is established. It allows the determination of the particle rigid-body motion without calculating the modified electric field and the flow induced by the Lorentz body force in the fluid domain. The advocated boundary approach, well-adapted for future numerical implementation, makes it possible to obtain an analytical expression for the translational velocity of any ellipsoidal particle (the simplest case of non-spherical orthotropic particles). The behaviour of a spheroid is carefully investigated and discussed both without and with gravity. The migration of this simple non-spherical particle is found to depend on both its nature (prolate or oblate) and the ambient uniform fields $\hbox{\bf\itshape E}$ and $\hbox{\bf\itshape B}. $ The spheroid translates without rotation, and not necessarily parallel to $\hbox{\bf\itshape E}\wedge \hbox{\bf\itshape B}. $ For adequately selected fields $\hbox{\bf\itshape E}$ and $\hbox{\bf\itshape B},$ the spheroid may either migrate parallel or anti-parallel to a sphere and even be motionless.
Differential seed germination of a keystone palm (Euterpe edulis) dispersed by avian frugivores

The effectiveness of seed dispersal by vertebrates has been analysed by examining both quantitative and qualitative components (Jordano & Schupp 2000, Schupp et al. 2010). While the quantitative component is relatively easily assessed in the field (e.g. visitation rate, number of fruits eaten per visit), the qualitative component (e.g. fate of dispersed seeds, seed treatment in the digestive system of the disperser) is rarely studied under natural conditions, because it is difficult to measure the effects on seeds once ingested by the dispersers (Cortes et al. 2009).
AIRCRAFT SECURITY ENHANCEMENT : ROTATING MACHINERY FAULT DIAGNOSIS AND HEALTH ASSESSMENT USING MANIFOLD LEARNING AND DYNAMIC TIME WARPING

To enhance the ability of AHMS, a research on aircraft rotating machinery fault diagnosis and health assessment techniques is conduct, and an approach combining manifold learning and dynamic time warping (DTW) is present in this paper. First, the original nonlinear and nonstationary vibration signals are processed by wavelet packet decomposition, and the wavelet energies are extracted to act as fault features, which are high-dimensional. Then, manifold learning method is employed for dimensionality reduction to find the intrinsic fault features. Finally, based on the accurate fault features, DTW is introduced to determine the fault state and assess the heath degree. The results of fault diagnosis and health assessment for a self-priming centrifugal pump in the aircraft fuel injection system demonstrate the effectiveness of the proposed approach.
Establishment and validation of molecular predictive models for understanding survival and susceptibility of Vibrio parahaemolyticus in seafood stored at low temperature

ii Acknowledgments. iv List of Tables . vii List of Illustrations . viii List of Abbreviations . ix Chapter 1: Introduction . 1 Chapter 2: Literature review . 5 2.1 Characteristics of Vibrio parahaemolyticus . 6 2.2 Virulence factors of Vibrio parahaemolyticus . 7 2.2.1 Thermostable direct hemolysin (TDH) . 7 2.2.2 TDH-related hemolysin (TRH) . 8 2.2.3 Type III secretion systems (T3SSs) . 8 2.2.3.1 T3SS1 . 9 2.2.3.2 T3SS2 . 9 2.2. 4 Type VI secretion systems (T6SSs) . 10 2.3 Detection of Vibrio parahaemolyticus . 10 2.3.1 Thiosulphate citrate bile salts sucrose (TCBS) . 11 2.3.2 CHROMagar Vibrio . 11 2.3. 3 Most probable number (MPN) . 12