Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian inference, model selection and likelihood estimation using fast rejection sampling: the Conway-Maxwell-Poisson distribution

Bayesian inference for models with intractable likelihood functions represents a challenging suite of problems in modern statistics. In this work we analyse the Conway-Maxwell-Poisson (COM-Poisson) distribution, a two parameter generalisation of the Poisson distribution. COM-Poisson regression modelling allows the flexibility to model dispersed count data as part of a generalised linear model (GLM) with a COM-Poisson response, where exogenous covariates control the mean and dispersion level of the response. The major difficulty with COM-Poisson regression is that the likelihood function contains multiple intractable normalising constants and is not amenable to standard inference and MCMC techniques. Recent work by Chanialidis et al. (2017) has seen the development of a sampler to draw random variates from the COM-Poisson likelihood using a rejection sampling algorithm. We provide a new rejection sampler for the COM-Poisson distribution which significantly reduces the CPU time required to perform inference for COM-Poisson regression models. A novel extension of this work shows that for any intractable likelihood function with an associated rejection sampler it is possible to construct unbiased estimators of the intractable likelihood which proves useful for model selection or for use within pseudo-marginal MCMC algorithms (Andrieu and Roberts, 2009). We demonstrate all of these methods on a real-world dataset of takeover bids.
Flux-closure domains in high aspect ratio electroless-deposited CoNiB nanotubes

We report the imaging of magnetic domains in ferromagnetic CoNiB nanotubes with very long aspect ratio, fabricated by electroless plating. While axial magnetization is expected for long tubes made of soft magnetic materials, we evidence series of azimuthal domains. We tentatively explain these by the interplay of anisotropic strain and/or grain size, with magneto-elasticity and/or anisotropic interfacial magnetic anisotropy. This material could be interesting for dense data storage, as well as curvature-induced magnetic phenomena such as the non-reciprocity of spin-wave propagation.
Application of Fredholm integral equations inverse theory to the radial basis function approximation problem I

This paper reveals and examines the relationship between the solution and stability of Fredholm integral equations and radial basis function approximation or interpolation. The underlying system (kernel) matrices are shown to have a smoothing property which is dependent on the choice of kernel. Instead of using the condition number to describe the ill-conditioning, hence only looking at the largest and smallest singular values of the matrix, techniques from inverse theory, particularly the Picard condition, show that it is understanding the exponential decay of the singular values which is critical for interpreting and mitigating instability. Results on the spectra of certain classes of kernel matrices are reviewed, verifying the exponential decay of the singular values. Numerical results illustrating the application of integral equation inverse theory are also provided and demonstrate that interpolation weights may be regarded as samplings of a weighted solution of an integral equation. This is then relevant for mapping from one set of radial basis function centers to another set. Techniques for the solution of integral equations can be further exploited in future studies to find stable solutions and to reduce the impact of errors in the data.
Unveiling the Values Inculcation Model among Mathematics Teachers in Developing Country: A Conceptual Approach

The demand for valued-education particularly science education and mathematics education is increasing in light of the global technological advancement. However, research on the area of values associated with mathematics teaching and learning among mathematics teachers remains in its infancy in Nigeria. This study was conducted to unveil the effectiveness of the mathematical values inculcation model among secondary schools mathematics teachers in Nigeria. A sample of 509 mathematics teachers was drawn from the six states of the North Eastern Region of Nigeria. A self-constructed survey instrument was used to gather the data of the study. The independent variables of the study consist of ideological, attitudinal, sociological, computational and motivational mathematical values. Structural equation modeling technique and confirmatory factor analysis (CFA) were conducted. The findings of the study show that there is a significant covariant relationship among the latent constructs for values inculcation in mathematics teaching and learning. There is also adequate support of the values inculcation model among Nigerian mathematics teachers as the model fits the data.
New detections of H2O maser sources on the 13.7m radio telescope of Purple Mountain Observatory

Observations of H2O maser sources on the 13.7 m radio telescope of Purple Mountain Observatory from 1990 Aug. to 1994 Jan. are summarized. For searching new water masers, the total number of search candidates is about 360, with 110 objects detected. Among them are 96 new detections. A list of the new detections and their spectra are presented.
A vibrant data placement approach for map reduce in diverse environments

Map reduce assumes that the computing capacity is same for each node in a cluster. Each node is assigned to the same load in homogeneous environment, hence it fully use the resources in the cluster. In such a cluster, there is likely to be various speciﬁcations of PCs or servers, which causes the abilities of the nodes to differ. If such a heterogeneous environment still uses the original Hadoop strategy that distributes data blocks into each node equally and the load is also evenly distributed to each node, then the overall performance of Ha-doop may be reduced. The major reason is that different computing capacities between nodes cause the task execution time to differ so that the faster executionrate nodes processing local data blocks faster than other slower nodes do.The required data should be transferred from another node through the network. Because waiting for the data transmission time increases the task execution time, it causes the entire job execution time to become prolonged.
Self-Employed or Employing Others? Pre-Entry Capabilities, Entrepreneurial Action, and the Learned Resourcefulness of Microcredit Firm Founders

We survey 612 entrepreneurs who are members of microcredit programs across three developing countries to examine the determinants of firm employment. We find that for opportunity-motivated entrepreneurs, a greater number of employees are predicted by pre-entry means (managerial skill, pre-planning, and business expertise) with these relationships mediated by differentiation-related innovation. We find that necessity-motivated entrepreneurs do not seek innovation as a means to growth. Rather their efforts to increase firm employment are enhanced by a set of learned repertoires which we identify as resourcefulness. Specifically, we find behavioral resourcefulness and social resourcefulness increased the likelihood of higher firm employment for necessity-motivated entrepreneurs while financial resourcefulness was not significant.
A modified Ising model for the thermodynamic properties of local and global protein folding–unfolding observed by circular dichroism and small-angle X-ray scattering

Based on the mean-field approximation, we have applied a modified Ising model to describe general protein unfolding behavior at thermodynamic equilibrium with the free energy contributed by the subgroup units (amino acids or peptide bonds) of the protein. With the thermodynamic properties of the protein, this model can associate the stepwise change of an unfolding fraction ratio profile with the local and global conformation unfolding. Taking cytochrome c (cyt c) as a model protein, we have observed, using small-angle X-ray scattering and circular dichroism (CD), the global and local structure changes for the protein in three kinds of denaturant environments: acid, urea and guanidine hydrochloride. The small-angle X-ray scattering and CD results are mapped to the unfolding fractions as a function of the pH value or denaturant concentration, from which we have extracted local and global unfolding free energies of cyt c in different denaturant environments using a modified Ising model. Based on the characteristics of the thermodynamic properties deduced from the local and global protein folding–unfolding, we discuss the thermodynamic stabilities of the protein in the three denaturant environments, and the possible correlation between the global conformation change of the protein and the local unfolding activities of the S—Fe bond in the Met80-heme and the α-helices.
Analysis of finite element methods for coupled Hydro-Mechanical problems

This work is concerned with the analysis of a non-stationary Hydro-Mechanical problem. The well-posedness of the continuous, time semi-discretized and fully discretized problems is addressed. An a posteriori error analysis is performed, leading to a family of space-time error indicators. The reliability of this family, i.e. a global upper bound of the error using the error indicators, is proved.
The effects of inward and outward FDI on domestic investment: evidence using panel data of ASEAN–8 countries

In view of the changing FDI landscape, in particular, a drastic increase in out-ward FDI from developing and transition economies in recent years, this paper attempts to explore the possible impacts of outward FDI other than domestic savings and inward foreign direct investment on domestic investment. The major contribution of this study is that it is the first effort to empirically analyse the short- and long-run effects of the outward FDI using panel data of ASEAN–8 countries, which could provide useful policy implications for governments at both regional and international levels to achieve inclusive growth and sustainable development. Using pool mean group analysis, this paper finds that the gross domestic saving, inward FDI and outward FDI have a positive long-run impact on the gross domestic investment even though their long-run estimates are inelastic. The empirical study reveals that both inward FDI and outward FDI, to some extent, are complementary to the gross domestic investment.
Strip Steel Surface Defect Classification Method Based on Enhanced Twin Support Vector Machine

The strip steel surface defect classification belongs to multi-class classification. It demands high classification accuracy and efficiency. However, traditional methods are not fit for abnormal datasets, such as the large-scale, sparse, unbalanced and corrupted dataset. So a novel classification method is proposed in this paper based on enhanced twin support vector machine (TWSVM) and binary tree. According to the density information, the large-scale dataset is pruned, the sparse dataset is added with unlabeled samples, and TWSVM is improved to multi-density TWSVM (MDTWSVM) which has efficient successive overrelaxation (SOR) algorithm. Finally, MDTWSVM and binary tree are combined together to realize multiclass classification. Some experiments are done on the strip steel surface defect datasets with the proposed algorithm. Experimental results show that MDTWSVM has higher accuracy and efficiency than the other methods of multi-class classification for the strip steel surface defect.
Teaching Dining Skills to Students with Emotional and Behavior Disorders.

Children with emotional and behavior disorders often have difficulties understanding social cues, responding appropriately in social situations, and initiating age-appropriate interactions with peers and adults. A real-life social activity that is often neglected in social skills training is dining. Dining involves dining etiquette, personal hygiene, mathematics, and social skills. Dining skills can be taught using a direct model approach that include introduction and instruction of the skill, modeling, peer involvement, role-playing, feedback, and reinforcement of desired social behaviors. Providing social skills training and real-life dining experiences for students with emotional and behavior disorders can provide many opportunities for students to learn appropriate interaction with peers and authority figures, recognize social cues, and learn social competence.
Artificial Neural Networks in Construction Engineering and Management

: Artiﬁcial Neural Networks has gained considerable application in construction engineering and management in recent time. Over 100 resources published in refereed journals and conference proceedings were screened and reviewed with the view to exploring the trend and new directions of the applications of diﬀerent ANN algorithms. The study revealed successful applications of ANNs in cost prediction, optimization and scheduling, risk assessment, claims and dispute resolution outcomes and decision making. It was observed that ANN have been applied to problems that are diﬃcult to solve with traditional mathematical and statistical methods. The integration of ANN with other soft computing methods like Genetic Algorithm, Fuzzy Logic, Ant Colony Optimization, Artiﬁcial Bee Colony and Particle Swarm Optimization were also explored which generally indicated better results when compared with conventional ANNs. The study provides comprehensive repute of ANN in construction engineering and management for application in diﬀerent areas for improved accuracy and reliable predictions.
Data search and discovery process for financial statement fraud

Financial fraud in the form of significant public interest, media, investors, financial community and legislators to get oneself and for several large companies such as Enron fraud is known, Lucent and WorldCom have occurred in the past years. Fraudulent financial reporting in more than declarative through asset sales and profits and low self liabilities, costs and losses occur (Yue et al., 2007). Fraud, an important reason for the failure of many companies and particularly damaging to capital markets because investors, creditors and financial analysts in their decisions on the financial statements available to the public, they rely on and trust. Detect fraud in financial statements, it is difficult and complex issues discovered (Yue et al., 2007). The main objective of this paper is to provide an overview of data mining processes used to detect financial fraud, particularly fraud in the financial statements. Keywords : Mining, fraud, financial statements, forecasting, regression, artificial neural networks
Modeling and forecasting regional tourism demand using the Bayesian GVAR (BGVAR) model

Increasing levels of global and regional integration have led to tourist flows between countries becoming closely linked. These links should be considered when modeling and forecasting international tourism demand within a region. This study introduces a comprehensive and accurate systematic approach to tourism demand analysis, based on a Bayesian global vector autoregressive (BGVAR) model. An empirical study of international tourist flows in nine countries in Southeast Asia demonstrates the ability of the BGVAR model to capture the spillover effects of international tourism demand in this region. The study provides clear evidence that the BGVAR model consistently outperforms three other alternative VAR model versions throughout oneto four-quarters-ahead forecasting horizons. The potential of the BGVAR model in future applications is demonstrated by its superiority in both modeling and forecasting tourism demand.
Picophytoplankton diversity and photoacclimation in the Strait of Sicily (Mediterranean Sea) in summer. I. Mesoscale variations

Phytoplankton dynamics were investigated at the mesoscale in the northern part of the Strait of Sicily in July-August 1997 on fractionated samples ( 3 μm) using HPLC pigment analysis and flow cytometry. Distribution, diversity and photoacclimation varied within the different water masses and features present at the time of sampling, including a surface filament of deep, cold water. Picophytoplankton ( 3 μm) appeared to respond to different cues. Chlorophyll pigment content per cell of Synechococcus spp. , Prochlorococcus spp. or picoeukaryotes was estimated by coupling pigment data with flow cytometric counts. In Prochlorococcus spp. , we found an average of 0.44 and 1.56 fg divinyl-chlorophyll a (dvchl a) cell -1 in surface and DCM layers, respectively. In contrast, chl a content in the picoeukaryote group ranged between 17 and 168 fg chl a cell -1 , depending upon depth and water mass, which suggested strong photoacclimation and photoadaptation with depth. The relative contribution of each eukaryote pigment to one size class or the other changed through the water column, and reflected size segregation within single taxonomic groups.
Martin boundary points of a John domain and unions of convex sets

We show that a John domain has finitely many minimal Martin boundary points at each Euclidean boundary point. The number of minimal Martin boundary points is estimated in terms of the John constant. In particular, if the John constant is bigger than $\sqrt3/2$ , then there are at most two minimal Martin boundary points at each Euclidean boundary point. For a class of John domains represented as the union of convex sets we give a sufficient condition for the Martin boundary and the Euclidean boundary to coincide.
Comparison of Three Methods for the Quantification of Sediment Organic Carbon in Salt Marshes of the Rubicon Estuary, Tasmania, Australia

With the increasing need to accurately quantify carbon sinks of coastal wetlands, this study compares three methods in use. Sediment cores (n = 4) were collected from three salt marsh sites of the Rubicon Estuary, Tasmania Australia and analysed for organic carbon using three methods for measuring soil C concentration. The first method of elemental analysis quantified carbon using a Thermo Finnigan EA 1112 Series Flash Elemental Analyser. The second method used the loss on ignition technique at 550°C for 4 hours and applied a standard carbon conversion. The third method used loss on ignition technique at 450°C for 8 hours and applied a standard carbon conversion. Results from each method found significantly different quantities of carbon in replicate samples, however each method differentiated similar carbon trends within datasets. Each methodology investigated was found to have a useful application in carbon science, including the broad scale use of the standard carbon conversion and the accuracy of the elemental analysis method. The application of the standard carbon conversion in this study showed an underestimate of carbon stores in salt marsh sediment. Wetlands are well known to be among the most carbon rich ecosystems of the world, however this study highlights that in some cases those carbon stores may have been underestimated, and verification may further increase the value of wetlands as carbon sinks.
PHMM: Stemming on Persian Texts using Statistical Stemmer Based on Hidden Markov ModelPHMM: Stemming on Persian Texts using Statistical Stemmer Based on Hidden Markov Model

Stemming is the process of finding the main morpheme of a word andit is used in natural language processing, text mining and informationretrieval systems. A stemmer extracts the stem of the words. We can classifyPersian stemmers in to three main classes: structural stemmers, dictionarybased stemmers and statistical stemmers.The precision of structural stemmers is low and the expenses of dictionary basedstemmers is high, so the main goal of this research is to design and implementa statistical stemmer based on hidden markov model with high precision which can reduce the sizeof indexed file and increase the speedof information retrieval systems. Our proposed stemmer, finds the prefixes and suffixes of a word and removethem, so the rest of the word is the stem. But there are some exceptions inPersian words which lead to stem those words by mistakes. So we collect a dictionaryof Persian stemmers. Our proposed stemmers, search a word in the dictionary, if it is not there , itfinds the stem of it by hmm based stemmer. This stemmer is tested in Bijankhancorpus and Hamshahri test collection. The results show increment in meanaverage precision and recall. The speed of the Information retrieval system isincreased and the size of indexed filesis decreased by the algorithm.
SATELLITE AND UNMANNED AERIAL VEHICLE DATA FOR THE CLASSIFICATION OF SAND DUNE VEGETATION

Abstract. Within coastal systems, sand dunes are the only natural barriers able to counteract erosive processes. Since their equilibrium is often threatened by human activities and high vulnerability of the coastal environment, dunes require increasing attention and specific monitoring. Located between the mainland and the sea, dunes are unique residue habitats for some plant and animal species. In particular, their vegetation is important because it has a consolidation function and promotes the vertical dune accretion. A georeferenced vegetation classification can be useful to define the advancements or erosion stage of the dune, usually based only on the geometric reconstruction. The proposed study aims to compare the classifications performed with some combinations of two of the last generation sensors and traditional image processing techniques. High spectral resolution satellite image (WorldView-2) and a multispectral orthophoto, obtained from data acquired by an unmanned aerial vehicle, were used. Objects and pixel algorithms were applied and the results were compared by a statistical test. Using the same bands, the findings show that both data are suitable for monitoring the evolutionary dune status. Specifically, the WorldView-2 pixel-based classification and UAV object-based classification provide the same accurate results.
Ruminal Behavior of Protein and Starch Free Organic Matter of Lupinus Albus and Vicia Faba in Dairy Cows

Faba beans (vicia faba) (FB) and lupin seeds (Lupinus Albus) (LS) were dry roasted at three temperatures (110, 130, 150°C) for 15, 30 or 45 min to determine the effects of dry roasting on rumen degradation of crude protein and starch free organic matter ( P S F OM). Rumen degradation characteristics of P S F OM were determined by the nylon bag incubation technique in dairy cows fed 60% hay and 40% concentrate. Measured characteristics of P S F OM were undegradable fraction (U), degradable fraction (D), soluble fraction (S), lag time (TO), and the rate of degradation (Kd). Based on the measured characteristics, rumen availability (RA P S F OM) and bypass P S F OM (B P S F OM) were calculated. Dry roasting did not have a greater impact on rumen degradation characteristics of P S F OM (p>0.05). S varied from 32.1 (raw) to 30.0, 27.8, 30.8% (LS) and 15.4 (raw) to 14.4, 20.8, 20.9% (FB); D varied from 65.4 (raw) to 66.3, 66.9, 55.9% (LS) and 54.9 (raw) to 55.0, 51.0, 64.7% (FB); U varied from 2.6 (raw) to 7.3, 7.0, 7.7% (LS) and 29.7 (raw) to 30.6, 28.2, 14.4% (FB); Kd varied from 6.0 (raw) to 7.3, 7.0, 7.7% (LS) and 22.4 (raw) to 24.4, 21.1, 7.9% (FB); B P S F OM varied from 35.5 (raw) to 33.8, 36.6, 38.2% (LS) and 41.3 (raw) to 41.5, 39.7, 47.6% (FB) at 110, 130 and 150°C, respectively. Therefore dry roasting did not significantly affect RA P S F OM, which were 353.7, 367.9, 349.6, 336.9 (g/kg DM) (LS) and 12.82, 127.0, 133.7, 117.1 (g/kg DM) (FB) at 110, 130 and 150°C, respectively. These results alone with our previously published reports indicate dry roasting had the differently affected pattern of rumen degradation characteristics of various components in LS and FB. It strongly increased bypass crude protein (BCP) and moderately increased starch (BST) with increasing temperature and time but least affected P S F OM. Such desirable degradation patterns in dry roasted LS and FB might be beneficial to the high yielding cows which could use more dry roasted P S F OM as an energy source for microbial protein synthesized in the rumen and absorb more amino acids and glucose in the small intestine.