Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Inheritance of Female and Male Morphotypes in Giant Freshwater Prawn Macrobrachium rosenbergii

Giant freshwater prawn (GFP) Macrobrachium rosenbergii is unique with males categorized in five different morphotypes (small claw, orange claw, blue claw, old blue claw and no claw males) and females in three reproductive statuses (mature ovary, berried and spawned females). In the present study we examined genetic inheritance of female and male morphotypes, their body weights and genetic associations between morphotypes and body traits. Restricted maximum likelihood fitting a multi-trait animal model was performed on a total of 21,459 body records collected over five generations in a GFP population selected for high growth rate. The estimates of variance components showed that there were substantial differences in additive genetic variance in body weight between male morphotypes. The low and significantly different from one genetic correlations between the expressions of body weight in male morphotypes also suggest that these traits should be treated as genetically different traits in selective breeding programs. By contrast, body weights of female types are essentially the same characters as indicated by the high genetic correlations between homologous trait expressions. In addition to body weight, male morphotypes and female reproductive statuses were treated as traits in themselves and were analysed as binary observations using animal and sire linear mixed models, and logit and probit threshold models. The estimates of heritability back-transformed from the liability scale were in good agreement with those obtained from linear mixed models, ranging from 0.02 to 0.43 for male morphotypes and 0.06 to 0.10 for female types. The genetic correlations among male morphoptypes were generally favourable. Body weight showed negative genetic associations with SM (−0.96), whereas those of body weight with other male morphotypes were positive (0.25 to 0.76). Our results showed that there is existence of heritable (additive genetic) component for male morphotypes, giving prospects for genetic selection to change population structure of GFP.
The Price Premium for Organic Wines: Estimating a Hedonic Farm-Gate Price Equation*

Abstract Organic wines are increasingly produced and appreciated. Because organic production is more costly, a crucial question is whether they benefit from a price premium. We estimate hedonic price functions for Piedmont organic and conventional wines. We use data on the production side in addition to variables of interest to consumers. Our results show that, along with characteristics of interest to consumers, some farm and producer characteristics not directly relevant for consumers do significantly affect wine prices. We find that organic wine tends to obtain higher prices than conventional wine. The price premium is not simply an addition to other price components; organic quality modifies the impact of the other variables on price. (JEL Classification: C21, D49, L11, Q12)
Interleaved entropy coders

The ANS family of arithmetic coders developed by Jarek Duda has the unique property that encoder and decoder are completely symmetric in the sense that a decoder reading bits will be in the exact same state that the encoder was in when writing those bits---all "buffering" of information is explicitly part of the coder state and identical between encoder and decoder. As a consequence, the output from multiple ABS/ANS coders can be interleaved into the same bitstream without any additional metadata. This allows for very efficient encoding and decoding on CPUs supporting superscalar execution or SIMD instructions, as well as GPU implementations. We also show how interleaving without additional metadata can be implemented for any entropy coder, at some increase in encoder complexity.
Using Kohonen's Self-Organizing Feature Map to Uncover Automobile Bodily Injury Claims Fraud

Claims fraud is an increasingly vexing problem confronting the insurance industry. In this empirical study, we apply Kohonen's Self-Organizing Feature Map to classify automobile bodily injury (BI) claims by the degree of fraud suspicion. Feed forward neural networks and a back propagation algorithm are used to investigate the validity of the Feature Map approach. Comparative experiments illustrate the potential usefulness of the proposed methodology. We show that this technique performs better than both an insurance adjuster's fraud assessment and an insurance investigator's fraud assessment with respect to consistency and reliability.
Atrial fibrillation detection using photo-plethysmography and acceleration data at the wrist

Atrial fibrillation (AF) is a pathological cardiac condition leading to increased risk for embolic stroke. Screening for AF is challenging due to the paroxysmal and asymptomatic nature of the condition. We aimed to investigate whether an unobtrusive wrist-wearable device equipped with a photo-plethysmographic (PPG) and acceleration sensor could detect AF. Sixteen patients with suspected AF were monitoredfor 24 hours in an outpatient setting using a Holter ECG. Simultaneously, PPG and acceleration data were collected at the wrist. PPG data was processed to determine the timing of heartbeats and inter-beat-interval (IBI). Wrist acceleration and PPG morphology were used to discard IBIs in presence of motion artefacts. An ECG validated first-order Markov model was used to assess the probability of irregular rhythm due to AF using PPG-derived IBIs. The AF detection algorithm was compared with clinical adjudications of AF episodes after review of the ECG records. AF detection was achieved with 97 ± 2% sensitivity and 99 ± 3% specificity. Due to motion artefacts, the algorithm did not provide AF classification for an average of 36 ± 9% of the 24 hours monitoring. We concluded that a wrist-wearable device equipped with a PPG and acceleration sensor can accurately detect rhythm irregularities caused by AF in daily life.
Supervised learning on graphs of spatio-temporal similarity in satellite image sequences

High resolution satellite image sequences are multidimensional signals composed of spatio-temporal patterns associated to numerous and various phenomena. Bayesian methods have been previously proposed in (Heas and Datcu, 2005) to code the information contained in satellite image sequences in a graph representation using Bayesian methods. Based on such a representation, this paper further presents a supervised learning methodology of semantics associated to spatio-temporal patterns occurring in satellite image sequences. It enables the recognition and the probabilistic retrieval of similar events. Indeed, graphs are attached to statistical models for spatio-temporal processes, which at their turn describe physical changes in the observed scene. Therefore, we adjust a parametric model evaluating similarity types between graph patterns in order to represent user-specific semantics attached to spatio-temporal phenomena. The learning step is performed by the incremental definition of similarity types via user-provided spatio-temporal pattern examples attached to positive or/and negative semantics. From these examples, probabilities are inferred using a Bayesian network and a Dirichlet model. This enables to links user interest to a specific similarity model between graph patterns. According to the current state of learning, semantic posterior probabilities are updated for all possible graph patterns so that similar spatio-temporal phenomena can be recognized and retrieved from the image sequence. Few experiments performed on a multi-spectral SPOT image sequence illustrate the proposed spatio-temporal recognition method.
Statistical analysis of amplitude fluctuations in EPSCs evoked in rat CA1 pyramidal neurones in vitro.

1. EPSCs were evoked in CA1 pyramidal neurones of young rats in vitro by extracellular stimulation of axons in a restricted stratum radiatum field, and were recorded using the whole‐cell technique. 2. Quantal fluctuations in EPSC amplitude could be demonstrated for nineteen of fifty EPSCs analysed. Quantal currents (at the soma) ranged from 2.6 to 9.5 pA (after correction for the access resistance) with a mean of 4.0 +/‐ 2.0 pA. 3. Quantal variance was negligible for the majority (13/19) of the EPSCs. However, a large quantal variance (with a coefficient of variation > 0.4) is one possible reason why a large number of the EPSCs (29/50) could not be shown to have quantal fluctuations. 4. The statistical pattern of fluctuations in the amplitude of the majority of the quantal EPSCs (18/19) could not be described by conventional models of transmitter release. 5. The time course of the EPSC and a compartmental model of CA1 pyramidal neurones were used to calculate synaptic location. The quantal current (at the soma) was independent of the electrotonic location of the synapse at which it was evoked. The peak quantal conductance generating each quantal current ranged from 0.5 to 6.8 nS (mean 1.3 +/‐ 1.4 nS), its magnitude increasing with distance from the soma. The mean peak conductance is likely to be generated by the opening of at least 60‐160 AMPA channels.
Node connectivity index as mobility metric for GA based QoS routing in MANET

The objective of this paper is to propose a unique connectivity index, nci which indicates the quality of route when nodes move randomly. The most reliable route is then chosen using GA route selection mechanism. The node mobility model is introduced and shows that there exists upper bound for velocity in order to achieve reliable wireless communication. The nci is then derived based on contraction and expansion model. It is then utilized as one of the fitness variable in our multi objectives GA-based QOS Routing protocol. It has been observed that the performances of our protocol QOSRGA on velocity scenario are better than the BE-DSR routing protocol.
Automatic Abduction of Qualitative Models

We describe a method of automatically abducing qualitative models from descriptions of behaviors. We generate, from either quantitative or qualitative data, models in the form of qualitative differential equations suitable for use by QSIM. Constraints are generated and filtered both by comparison with the input behaviors and by dimensional analysis. If the user provides complete information on the input behaviors and the dimensions of the input variables, the resulting model is unique, maximally constrained, and guaranteed to reproduce the input behaviors. If the user provides incomplete information, our method will still generate a model which reproduces the input behaviors, but the model may no longer be unique. Incompleteness can take several forms: missing dimensions, values of variables, or entire variables.
Humidity‐dependent bending recovery and relaxation of human hair

The time-dependent bending recovery of human hair fibers was investigated for a variety of relative humidities and aging times. The data were analyzed on the basis of a viscoelastic filament/matrix model and the Denby-equation, containing the parameter K as the ratio of the elastic bending rigidities of the matrix and the filaments and the Kohlrausch-Williams-Watts (KWW) function as relaxation function. The first stage of the analysis ascertained that the recovery curves shift with aging time on the time scale with the expected aging rate of μ ≈ 1. The second stage showed that the shape factor of the KWW function exhibits a mean value across the aging and humidity range of m = 0.28, which is close to the “universal” value of 1/3. On this basis, it was found that virtually no change occurs for the modulus ratio for low water contents up to about 10%, being constant at K0= 6 . 1, while linearly decreasing beyond this threshold. The reduced, characteristic relaxation time drops on the log-time scale from logτr(0) = 0.47 for the dry fiber linearly with water content, covering about two thirds of a decade for 0–20% water content. With the pronounced humidity dependence of the parameters, hair shows what is termed hydro-rheologically complex (HRC) in analogy to thermo-rheologically complex behavior. Using the HRC approach, the dynamical mechanical performance of hair (1 Hz) was calculated for a range of water contents and aging times and found to be in good general agreement with experimental data. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009
Failure Assessment Diagram for Brazed 304 Stainless Steel Joints

*- Brush and Wellman trade name for 62%Be 38%Al metal matrix composite FAILURE ASSESSMENT DIAGRAM FOR BRAZED 304 STAINLESS STEEL JOINTS ABSTRACT Interaction equations were proposed earlier to predict failure in Albemet 162* brazed joints. Based on the test results of this study, it was determined that the same interaction equations can be used for lower bound estimate of the failure criterion in 304 stainless steel joints brazed with silver-based filler metals as well as for construction of the Failure Assessment Diagrams (FAD). 1.0 INTRODUCTION Prediction of failure in brazed joints subjected to complex loading conditions continues to challenge designers and structural analysts attempting to estimate margins of safety in critical assemblies fabricated by brazing. Despite the fact that brazed components and structures are extensively used in the aerospace industry, literature is lacking simple engineering procedures or guidelines for failure assessment of brazed joints. Earlier work [1] demonstrated that interaction equations could be used for failure assessment of Albemet 162 joints brazed with AWS BAlSi-4 (88%Al,12%Si) filler metal. In the current effort, different base / filler metal combinations consisting of 304 SS brazed with pure silver and AWS BAg8 (78%Ag, 28%Cu eutectic) filler metals were evaluated. This memorandum provides information on specimen design, fabrication and testing performed by the Materials Engineering Branch to verify that interaction equations used earlier could also be applied for failure assessment of other brazed systems. 2.0 APPROACH This effort consisted of two parts. In first part design values of tensile
Generation of a monoclonal antibody to the carboxy‐terminal domain of tau by immunization with the amino‐terminal domain of the amyloid precursor protein

A fusion protein between β‐Galactosidase and the amino‐terminal dimain fo amyloid precursor protein (APP) was used as an immunoghen for the production of monoclonal antibodies. One of these antibodies, the 5D12 mjonoclonal antibody, labeled the neurofibrillary tangles (NFT) by immunohistochemisty, as well as isolated paired helical filament (PHF) in electron microscopy. In immunoassay, the ascitic fluid produced by the 5D12 cline was demonstrated to contain a high titer of antibodies to heat‐stable micotubule associated proteins (MAPs). By immunoblotting, the proteins recognized in heat‐stable MAPs were found to corespond totau proteins. The 5D12 antibody recognized normal tau isolated from rat and hiuman brain homkogentes, and PHF‐tau isolated from th brain of patients with Alzheimer's disease (AD). By immunohlotting, the 5D12 antibody also recognized the full‐length recombinant recombibnat tau protein but not the fusion protein used as an immunogen. The immunoreactivity of the 5D12 antibody with tau was completely abolished when the half‐carboxy domain of tau, contaoining the tubulin‐binding repeats, was removex. This studydemonstrats that the use of the amino‐terminal domain of APP as an immunogen les to the generation of a monoclonal antiboidy to the half‐carboxy domain of tau. © 1996 Wiley‐Liss, Inc.
Comparing a TBL Tagger with an HMM Tagger : Time Efficiency , Accuracy , Unknown Words .

In this paper a transformation-based learning tagger is compared with a hidden Markov model tagger. For this comparison the Brill tagger and the TnT tagger are used. The Dutch Spoken Corpus (CGN), tagged with a medium-sized (72) tagstet, is used as training and testing material. The TnT tagger outperforms the Brill tagger on larger tagsets and when relatively small training-sets (around 10.000 sentences) are used. The results support the observation by Schneider and Volk that the unknownword handling of the Brill tagger is still unsatisfactory. While both taggers achieve around the same tagging speed the Brill-tagger takes a long time to train. The Brill tagger takes around 18 hours to train for a training-set of 100.000 sentences tagged with the 72-tags tagset; the TnT tagger takes slightly less than nine seconds for that and slightly less then a minute and a half to train on a set of 900.000 sentences. The best result for the Brill-tagger on the medium-sized tagset was an error-rate of 3.9% with an training-set of 100.000 sentences. The best result for the TnT-tagger on the medium-sized tagset was an error-rate of 2.7% with an training-set of 900.000 sentences.
Scala-AM: A Modular Static Analysis Framework

We present Scala-AM, a modular framework for static analysis based on systematic abstraction of abstract machines. Scala-AM achieves modularity by separating operational semantics, abstract values and machine abstraction concerns via actions, thus enabling language designers, static analysis developers and machine abstraction experts to combine their efforts. This modularity enables us to support semantics for multiple languages, and to include multiple machine abstractions in our framework. Different operational semantics and machine abstractions can then be combined with minimal effort. We evaluate our framework by demonstrating how it enables implementing machine abstractions independently of the operational semantics, and by instantiating the framework for a static taint analysis of Scheme.
OBS network model for OMNeT++: a performance evaluation

Optical Burst Switching (OBS) is an optical switching technology capable of supporting large demands for bandwidth in optical backbones with Wavelength Division Multiplexing (WDM). This paper presents an OBS simulation model for the discrete event simulator OMNeT++. The performance of this model is compared with the performance of the well-known INET simulation model for IP networks. Both models show similar performance results. The OBS model is faster but uses more dynamic memory.
Oligonucleotide and Parylene Surface Coating of Polystyrene and ePTFE for Improved Endothelial Cell Attachment and Hemocompatibility

In vivo self-endothelialization by endothelial cell adhesion on cardiovascular implants is highly desirable. DNA-oligonucleotides are an intriguing coating material with nonimmunogenic characteristics and the feasibility of easy and rapid chemical fabrication. The objective of this study was the creation of cell adhesive DNA-oligonucleotide coatings on vascular implant surfaces. DNA-oligonucleotides immobilized by adsorption on parylene (poly(monoaminomethyl-para-xylene)) coated polystyrene and ePTFE were resistant to high shear stress (9.5 N/m2) and human blood serum for up to 96 h. Adhesion of murine endothelial progenitor cells, HUVECs and endothelial cells from human adult saphenous veins as well as viability over a period of 14 days of HUVECs on oligonucleotide coated samples under dynamic culture conditions was significantly enhanced (P < 0.05). Oligonucleotide-coated surfaces revealed low thrombogenicity and excellent hemocompatibility after incubation with human blood. These properties suggest the suitability of immobilization of DNA-oligonucleotides for biofunctionalization of blood vessel substitutes for improved in vivo endothelialization.
Automatic Viseme Vocabulary Construction to Enhance Continuous Lip-reading

Speech is the most common communication method between humans and involves the perception of both auditory and visual channels. Automatic speech recognition focuses on interpreting the audio signals, but it has been demonstrated that video can provide information that is complementary to the audio. Thus, the study of automatic lip-reading is important and is still an open problem. One of the key challenges is the definition of the visual elementary units (the visemes) and their vocabulary. Many researchers have analyzed the importance of the phoneme to viseme mapping and have proposed viseme vocabularies with lengths between 11 and 15 visemes. These viseme vocabularies have usually been manually defined by their linguistic properties and in some cases using decision trees or clustering techniques. In this work, we focus on the automatic construction of an optimal viseme vocabulary based on the association of phonemes with similar appearance. To this end, we construct an automatic system that uses local appearance descriptors to extract the main characteristics of the mouth region and HMMs to model the statistic relations of both viseme and phoneme sequences. To compare the performance of the system different descriptors (PCA, DCT and SIFT) are analyzed. We test our system in a Spanish corpus of continuous speech. Our results indicate that we are able to recognize approximately 58% of the visemes, 47% of the phonemes and 23% of the words in a continuous speech scenario and that the optimal viseme vocabulary for Spanish is composed by 20 visemes.
Monte Carlo simulations of electrical percolation in multicomponent thin films with nanofillers

We developed a 2D disk–stick percolation model to investigate the electrical percolation behavior of an insulating thin film reinforced with 1D and 2D conductive nanofillers via Monte Carlo simulation. Numerical predictions of the percolation threshold in single component thin films showed good agreement with the previous published work, validating our model for investigating the characteristics of the percolation phenomena. Parametric studies of size effect, i.e., length of 1D nanofiller and diameter of 2D nanofiller, were carried out to predict the electrical percolation threshold for hybrid systems. The relationships between the nanofillers in two hybrid systems was established, which showed differences from previous linear assumption. The effective electrical conductance was evaluated through Kirchhoff’s current law by transforming it into a resistor network. The equivalent resistance was obtained from the distribution of nodal voltages by solving a system of linear equations with a Gaussian elimination method. We examined the effects of stick length, relative concentration, and contact patterns of 1D/2D inclusions on electrical performance. One novel aspect of our study is its ability to investigate the effective conductance of nanocomposites as a function of relative concentrations, which shows there is a synergistic effect when nanofillers with different dimensionalities combine properly. Our work provides an important theoretical basis for designing the conductive networks and predicting the percolation properties of multicomponent nanocomposites.
Performance measurements of motes sensor networks

In this paper we investigate the performance of mica2 and mica2dot Berkeley motes by means of an extensive experimental analysis. This study is aimed at analyzing the main elements that characterize the performance of a sensor network, e.g., power consumption in different operating conditions, impact of weather conditions, interference between neighboring nodes, etc. Even if the analysis is related to a specific technology it provides some general useful information. Specifically, we found that the transmission range of mote sensor nodes decreases significantly in the presence of fog or rain. We also investigated the interference between neighboring nodes and, based on the experimental results, we propose a channel model for mote sensor nodes. This model is very similar to the channel model of IEEE 802.11 networks.