Miracle-dz/UniFAR-FTUs huggingface dataset:
Simultaneous and integrated neutron-based techniques for material analysis of a metallic ancient flute

A metallic 19th century flute was studied by means of integrated and simultaneous neutron-based techniques: neutron diffraction, neutron radiative capture analysis and neutron radiography. This experiment follows benchmark measurements devoted to assessing the effectiveness of a multitask beamline concept for neutron-based investigation on materials. The aim of this study is to show the potential application of the approach using multiple and integrated neutron-based techniques for musical instruments. Such samples, in the broad scenario of cultural heritage, represent an exciting research field. They may represent an interesting link between different disciplines such as nuclear physics, metallurgy and acoustics.
On the structure of certain normal ideals

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The internationalization of family firms: a resource dependence perspective

Drawing on the resource dependence theory, we expect the degree of openness/closeness in the governance structure of family businesses to influence internationalization. We view family firms with an open governance structure as those with external owners, external CEO, external directors, and large TMTs. Longitudinal data from 330 family firms reveal that: 1) external ownership increases the scale and the scope of the firm’s international operations; 2) an external CEO and larger TMTs enhance the scale of a family firm’s international operations, but not the scope; and, 3) external directors increase the scope of international operations, but not the scale.
GENETIC VARIATION AND RELATIONSHIPS AMONG VISAYAN NATIVE CHICKEN GENETIC GROUPS BOHOLANO AND DARAG ( Gallus gallus L.)

The present study was conducted to evaluate the genetic diversity and relationships of two Visayan native chicken genetic groups (Boholano and Darag), the native chicken (Labuyo) and commercial breed layer chicken (Lohman). Thirteen microsatellite or simple sequence repeats (SSR) markers were used covering 8 linkage groups or chromosomes. Four to eight alleles per locus were detected across all the breeds. The highest PIC value (0.773) was detected in primer ADL0268 and the average across primers was 0.6114. The mean number of alleles per locus (MNA), the observed heterozygosity (Ho), expected heterozygosity (He) and the inbreeding coefficient (FIS) were obtained for the Boholano (5.08, 0.6859, 0.6433, and -0.0998 respectively), the Darag (5.61, 0.6667, 0.6646, and -0.0225 respectively), the Labuyo (4.46,0.5944, 0.6486, and 0.0711 respectively) and the Lohman (2.46, 0.5, 0.3943, and 0.0258 respectively). The degree of genetic distance of the Boholano was moderate from Darag but great from Labuyo; but close between Darag and Labuyo. These indicate that the Darag, but not the Boholano, may have originated from the Labuyo. The high MNA, Ho, He, negative inbreeding coefficient and high interpopulation genetic differentiation (FST) [D1] values between genetic groups shows the richness of our native chicken genetic resource in Bohol and Panay Islands. ” Key Words: Boholano, Darag, Labuyo, microsatellite, native chicken
LOW-COST DEPLOYMENT STRATEGY FOR SATELLITE CONSTELLATIONS

This work proposes a novel method for the deployment of a constellation of nano-satellites into Low Earth Orbit by using carrier vehicles to deliver the nano-satellites into the required orbit positions. The analytical solution presented allows for rapid exploration of the design space and a direct optimisation of the deployment strategy to minimise the time for complete constellation deployment. Traditionally, the deployment of satellite constellations requires numerous launches – at least one per orbital plane – which can be costly. Launching as a secondary payload may offer significant cost reductions, but this comes at the price of decreased control over the launch schedule and final orbit parameters. The analytical method presented here allows for the optimal positioning of the orbit planes of the constellation to be determined and the minimum time for deployment determined as a function of the manoeuvre ΔV. The effect of atmospheric drag on the manoeuvre propellant cost is also considered to ensure a realistic deployment scenario. A case study considering three constellation designs is presented which compares the cost of deployment using traditional launch methods with that of deploying the constellation using carrier vehicles. The results of this study show a significant reduction in cost when using the carrier vehicles on a dedicated launch, compared with launching the satellites individually. Most significantly, the launch cost when using carrier vehicles is primarily determined by the total number of satellites in the constellation, rather than the number of orbital planes. Thus, the carrier vehicle deployment strategy would allow for constellations with a large number of planes to be deployed for a fraction of the equivalent cost if traditional launch methods were used.
Video Description Using Learning Multiple Features

Generating descriptions for open-domain videos is a major challenge for computer vision due to the complex dynamics. In this paper, we propose a video description model based on multiple features. In the process of encoding, we exploit two complementary features. The spatial one is extracted from the raw frame by VGG-16 model. The temporal one is extracted from the SIFT flow image by a fine-tuned VGG-16 model. In the process of decoding, we further add the mean pooling feature which represents holistic feature of the video. For generating sentence of the video, we utilize two-layer LSTMs model to generate sentence about the video. We evaluate several variants of our model on the MSVD dataset for METEOR metrics. The experimental results show that our model can be beneficial for generating sequence about the video. Keywords—video description; SIFT flow; VGG-16; mean pooling; LSTM;
Environmental Effects and Gene-Environment Interactions: Air Pollution and Temperature Effects on Cardiovascular Risk Factors

Background and Objective Air temperature changes are associated with increased cardiovascular and respiratory risk, but the roles of inflammatory and coagulation markers are not well understood. We investigated the associations between temperature and several blood markers in patients with coronary heart disease (CHD) and pulmonary disease (PD). Methods Two studies were conducted in Erfurt, Germany, over two successive winters. 578 and 381 repeated blood measurements were collected from 57 CHD and 38 PD patients, respectively. Data on patient characteristics and disease history were gathered at baseline. Meteorological data were collected from existing networks. Associations were analysed using additive mixed models with random patient effects. Effect modification by diabetes status was investigated only in CHD patients, as only two PD patients had diabetes. Results Mean daily air temperature varied between 138C and 168C in both study periods. A 108C decrease in the 5-day temperature average before blood withdrawal led to an increase in platelet counts (% change from the mean: 3.0%, 95% CI 0.6% to 5.5%) and fibrinogen (5.5%, 1.3% to 9.7%), no change in C-reactive protein in PD patients, and a decrease in C-reactive protein in CHD patients. A 2-day delayed increase in factor VII associated with temperature decrease was seen in CHD patients (4.9%; 0.7% to 9.2%), while PD patients showed no effect. ‘Effects in CHD patients without diabetes’ into ‘Effects on factor VII in CHD patients without diabetes’. Conclusions This study suggests that temperature decrease is associated with change in several blood parameters. The complex interplay of blood markers at low temperature may contribute to the observed association between cold and cardiovascular mortality
Does Prey Availability Determine Seasonal Patterns of Habitat Selection in Texas Ratsnakes

Abstract An animal's requirements (e.g., food vs. shelter) from its environment are likely to vary seasonally and, therefore, so too should habitat selection. Here, we test the hypothesis that Texas Ratsnakes (Elaphe obsoleta) choose habitats based on prey availability during their active season and on cover during winter. We examined snake habitat selection at three spatial scales and compared that to abundance of small mammals and nesting birds, which we confirmed by diet analysis to be the snakes' principal prey. Small mammal trapping and avian point counts showed that overall prey abundance was higher on mesas and slopes compared to savannahs. Compared to availability of habitats within the entire study area, snakes selected home ranges with a high proportion of slope habitat. Within home ranges, however, selection for slopes was exhibited only during winter when foraging is at a minimum and snakes are relatively inactive. Snakes did not use habitat within home ranges selectively during the active season or during the avian breeding season. The latter result suggests that ratsnakes are effective avian nest predators despite preying on birds opportunistically. However, it is also possible that some individual ratsnakes specialize on birds, whereas the majority preys on mammals. Microhabitat analysis comparing winter and active season sites showed that snakes preferentially used areas of high canopy cover and rock ground cover during winter. Collectively these results provide limited support for the hypothesis that ratsnakes use habitats based on prey availability but do indicate that ratsnakes select winter habitat based on cover availability.
Choice of DNA extraction method affects DNA metabarcoding of unsorted invertebrate bulk samples

Characterisation of freshwater benthic biodiversity using DNA metabarcoding may allow more cost-effective environmental assessments than the current morphological-based assessment methods. DNA metabarcoding methods where sorting or pre-sorting of samples are avoided altogether are especially interesting, since the time between sampling and taxonomic identification is reduced. Due to the presence of non-target material like plants and sediments in crude samples, DNA extraction protocols become important for maximising DNA recovery and sample replicability. We sampled freshwater invertebrates from six river and lake sites and extracted DNA from homogenised bulk samples in quadruplicate subsamples, using a published method and two commercially available kits: HotSHOT approach, Qiagen DNeasy Blood & Tissue Kit and Qiagen DNeasy PowerPlant Pro Kit. The performance of the selected extraction methods was evaluated by measuring DNA yield and applying DNA metabarcoding to see if the choice of DNA extraction method affects DNA yield and metazoan diversity results. The PowerPlant Kit extractions resulted in the highest DNA yield and a strong significant correlation between sample weight and DNA yield, while the DNA yields of the Blood & Tissue Kit and HotSHOT method did not correlate with the sample weights. Metazoan diversity measures were more repeatable in samples extracted with the PowerPlant Kit compared to those extracted with the HotSHOT method or the Blood & Tissue Kit. Subsampling using Blood & Tissue Kit and HotSHOT extraction failed to describe the same community in the lake samples. Our study exemplifies that the choice of DNA extraction protocol influences the DNA yield as well as the subsequent community analysis. Based on our results, low specimen abundance samples will likely provide more stable results if specimens are sorted prior to DNA extraction and DNA metabarcoding, but the repeatability of the DNA extraction and DNA metabarcoding results was close to ideal in high specimen abundance samples.
A unified approach to estimation of nonlinear mixed effects and Berkson measurement error models

Mixed effects models and Berkson measurement error models are widely used. They share features which the author uses to develop a unified estimation framework. He deals with models in which the random effects (or measurement errors) have a general parametric distribution, whereas the random regression coefficients (or unobserved predictor variables) and error terms have nonparametric distributions. He proposes a second‐order least squares estimator and a simulation‐based estimator based on the first two moments of the conditional response variable given the observed covariates. He shows that both estimators are consistent and asymptotically normally distributed under fairly general conditions. The author also reports Monte Carlo simulation studies showing that the proposed estimators perform satisfactorily for relatively small sample sizes. Compared to the likelihood approach, the proposed methods are computationally feasible and do not rely on the normality assumption for random effects or other variables in the model.
AN INVESTIGATION OF INFORMATION INTELLIGENCE RETRIEVAL MODEL IN LOCAL SEARCHING SYSTEMS

The process of building and learning neural networks requires considerable computational effort. Fortunately, nowadays there are many various systems with high computing power. Development of systems, algorithms, methods and their applications in machine learning has become a promising direction in science. The work is devoted to the investigation of information retrieval problems and the main problems associated with this task, constructing an overfit-safe neural network model for improving the local searching system quality on 49% using machine learning algorithms.
EFFECT OF COASTAL SEDIMENT TO NUTRIENT AVAILABILITY AND MAIZE PRODUCTIVITY ON ENTISOLS

Entisols had a great potential for maize planting area expansion in increasing its production. The low soil fertility could be improved by application of coastal sediment. This current research examined the effect of different amount of coastal sediment on nutrient availability and maize production on Entisols, West Kalimantan. The research was conducted from July to November, 2013 in green house, Faculty of Agriculture, Tanjungpura University, West Kalimantan. The treatment conducted was the application of coastal sediment at dosage of: 0 Mg ha -1 (L 0 ), 14 Mg ha -1 (L 1 ), 28 Mg ha -1 (L 2 ), 42 Mg ha -1 (L 3 ), 56 Mg ha -1 (L 4 ), 72 ton ha -1 (L 5 ), 86 Mg ha -1 (L 6 ) and 100 Mg ha -1 (L 7 ). The treatments were arranged by completely randomized design with 3 replications. Research results showed that 42 Mg ha -1 coastal sediment was the best treatment and able to increase soil nutrients availability and maize productivity. The provision of coastal sediment increased the availability of K, Ca, Mg and Na, also the availability of nutrients in accordance with the increase of the dosage of coastal sediment.
On Scale Functions for Spectrally Negative L evy Processes with Phase-type Jumps

1 8.37E-11 8.3E-09 8 0.00015 0.00202 7.18E-10 6.8E-08 9 0.00112 0.01003 5.56E-09 3.9E-07 10 0.00846 0.05704 4.27E-08 2.2E-06 11 0.05977 0.30605 3.27E-07 1.2E-05 12 0.30722 1.54606 2.50E-06 6.5E-05 13 0.53382 6.51607 1.92E-05 3.5E-04 14 0.08944 23.304(i) Weibull(0.6,0.665) (ii) Pareto(1.2,5)Table:Parameters of the hyperexponential distributions tted to (i) aWeibull distribution with c = 0:6and a = 0:665and (ii) a Paretodistribution with a = 1:2and b = 5(taken from Tables 3 and 9, respectively,ofFeldmann and Whitt (1998)).
1 H-NMR metabolic profiling of wines from three cultivans, three soil types and two contrasting vintages

Aims: Differences in wine flavour proceed primarily from grape quality. Environmental factors (climate, soil), cultivars and training systems modify many grape and wine quality traits. Metabolic profiling based on proton nuclear magnetic resonance (1H-NMR) spectra has been proved to be useful to study multifactorial effects of the vine environment on intricate grape quality traits. The capacity of this method to discriminate the environmental effects on wine has to be demonstrated.Methods and results: : 1H-NMR spectra were made from wines produced with grapes harvested at maturity of three cultivars (Cabernet-Sauvignon, Cabernet franc and Merlot) and three soil types (gravely, sandy and clayey) during two vintages (2002 and 2003). Data were analysed by multivariate statistical methods. Principal component analysis applied on the NMR spectra data were not always able to separate satisfactorily wines from the 3 soil types. Conversely, partial least square analysis separated clearly the 3 soil types independently of the vintage and cultivar.Conclusion: By comparing the NMR signals that contribute to the two first axes of the PCA and PLS analyses, a significant soil effect on NMR signals in wines is reported. However, the effect of the vintage on wine composition was greater then the effect of the soil type.Significance and impact of study: After validation on a larger number of wine samples this chemical profiling will be a useful new method to the qualify wines in relation to climate, soil, and cultivar effects which contribute to the terroir.
Measuring Performance in Rail Freight Transportation Companies

Performance Measurement Systems - PMSs has become relevant for Organizations in the last years taking into consideration the broad approach and the strategic link which the current performance measurement is focused on. Brazilian railroad transportation has poor performance when compared with other similar countries. The rail transportation production has 25% of participation within total transportation matrix. Besides infrastructure aspects, management is the key for the improvement of this performance. A Performance Measurement System - PMS framework using Balanced Scorecard – BSC structure is proposed aiming to allow a more comprehensive and strategic performance measurement in railroad companies. A systematic approach was used for the literature review. Due to the lack in the literature related to the purpose of this paper a long period was considered for the search of references linked to performance measurement for railroads. Aiming to elaborate a PMS framework for railroad companies a case study method was applied in a large Brazilian railroad company. Semi-structured interviews and documental data collection were used in order to get evidences related to the processes, environment, customers and strategic objectives as perspectives needed to elaborate a PMS based on Balanced Scorecard. This case study applied in a large freight railroad company in Brazil allowed to understand typical strategic objectives as well as processes, customer’s requirements and environment related to this kind of business. Balanced Scorecard was suitable to the performance measurement needs of the railroad company operation. It can measure operations performance comprehensively and strategically in an effective way. This study brings up important contribution in terms of PMS literature and it can be used as a reference guide for future researches focused on this field. Also it can be worth for practitioners who desire implement PMS in Organizations, not limited for railroad companies, but also for other kind of operations. This framework proposed is unique taking into consideration that there is no comprehensive PMS for a railroad companies using Balanced Scorecard structure. This same structure can be applied in more field researches seeking better understandings about performance measurement in freight railroad companies. Some research questions in order to solve future issues related to this study are proposed at the end of this paper.
On model selection criteria in multimodel analysis

Hydrologic systems are open and complex, rendering them prone to multiple conceptualizations and mathematical descriptions. There has been a growing tendency to postulate several alternative hydrologic models for a site and use model selection criteria to (1) rank these models, (2) eliminate some of them, and/or (3) weigh and average predictions and statistics generated by multiple models. This has led to some debate among hydrogeologists about the merits and demerits of common model selection (also known as model discrimination or information) criteria such as AIC, AICc, BIC, and KIC and some lack of clarity about the proper interpretation and mathematical representation of each criterion. We examine the model selection literature to find that (1) all published rigorous derivations of AIC and AICc require that the (true) model having generated the observational data be in the set of candidate models; (2) though BIC and KIC were originally derived by assuming that such a model is in the set, BIC has been rederived by Cavanaugh and Neath (1999) without the need for such an assumption; and (3) KIC reduces to BIC as the number of observations becomes large relative to the number of adjustable model parameters, implying that it likewise does not require the existence of a true model in the set of alternatives. We explain why KIC is the only criterion accounting validly for the likelihood of prior parameter estimates, elucidate the unique role that the Fisher information matrix plays in KIC, and demonstrate through an example that it imbues KIC with desirable model selection properties not shared by AIC, AICc, or BIC. Our example appears to provide the first comprehensive test of how AIC, AICc, BIC, and KIC weigh and rank alternative models in light of the models' predictive performance under cross validation with real hydrologic data.
A generalization of Drygas functional equation

which can be reduced to the following equation (see [21], Remark 9.2, p.131)(1.1) f(x+y)+f(x−y)=2f(x)+f(y)+f(−y),x,y∈Rwhere R denotes the set of real numbers.This equation is known in the literature as Drygas equation and is ageneralization of the quadratic functional equation(1.2) f(x+y)+f(x−y)=2f(x)+2f(y),x,y∈R.The general solution of Drygas equation was given by Ebanks, Kannappanand Sahoo in [10]. It has the formf(x)=A(x)+Q(x),where A: R −→R is an additive function and Q: R −→R is a quadraticfunction, see also [17]. A set-valued version of Drygas equation was consid-ered by Smajdor in [23]. The Drygas functional equation on an arbitrarygroup G takes the form(1.3) f(xy)+f(xy
Career Concern and Tax Preparer Fraud

This paper focuses on the effects of career concern on fraud among tax return preparers. A two-stage model is built to ascertain whether the propensity of tax preparers to cooperate with taxpayers in underpaying tax can be decreased if the revealed fraud behavior increases the probability of being audited by the tax agency in the following period. After solving the unique SPNE, this effect is shown to exist.