Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular Analysis of mtDNA Types in Exploited Populations of Spinner Dolphins ( Stenella longirostris )

Stock structure of geographic forms of the spinner dolphin (Srenellu longirosrris) in the eastern tropical Pacific (ETP) is a conservation issue. These animals are incidentally killed during yellow fin tuna purse seining by US and international fleets, and mortality quotas apportioned by stock have been established by legislative act. Four management stocks of spinner dolphins in the ETP are currently defined on the basis of morphology and geographical distribution. However, recent work proposes that two of the stocks (the northern and southern 'whitebelly' spinners) comprise a broad zone of hybridisation or clinal integration between the neighbouring endemic 'eastern' spinner and the more typical spinners residing to the west and around the world in the tropics. I f this hypothesis is true. evidence of current or recent gene flow between the neighbouring 'stocks' should be apparent. To investigate this, we conducted a molecular analysis of mitochondrial DNA (mtDNA) extracted from livers of 151 spinner dolphins from the ETP and 13 spinner dolphins from the Timor Sea. We also analysed mtDNA from 10 spotted dolphins from the ETP. Liver mtDNA from each animal was digested with six restriction enzymes to deduce the individual mtDNA haplotypes. Genetic distances were then inferred within the sample pool by comparison of the individual mtDNA haplotypes in a pair-wise fashion. The results suggest the following three points: (1) The morphologically defined neighbouring eastern forms of ETP whitebelly spinners are not genetically distinct at the level of resolution of our analysis. We found no concordance of mtDNA haplotype with either the stock type of the school or individual morphology. The mean between-form distance was not significantly different from the two mean within-form distances. Thus, introgression is likely occurring (or has recently occurred) and significant genetic interchange can be inferred. (2) Mean within-school mtDNA diversity varied from school to school. and no clustering of certain haplotypes within specific schools was detected. (3) Timor Sea spinner and the spotted dolphins have unique mitochondrial genotypes likely characteristic of their geographic and genetic separation in the case of the spinner dolphins and their speeics-level separation in the case of the spotted dolphins. These findings reinforce the morphologically-based hypothesis of non-uniqueness of the whitebelly form and suggest that relatively more emphasis should be placed on conservation of the endemic and presumably locally adapted eastern form.
Movement Matters: How a Robot Becomes Body

This paper explores movement and its capacity for meaning-making and eliciting affect in human-robot interaction. Bringing together creative robotics, dance and machine learning, our research project develops a novel relational approach that harnesses dancers' movement expertise to design a non-anthropomorphic robot, its potential to move and capacity to learn. The project challenges the common assumption that robots need to appear human or animal-like to enable people to form connections with them. Our performative body-mapping (PBM) approach, in contrast, embraces the difference of machinic embodiment and places movement and its connection-making, knowledge-generating potential at the center of our social encounters. The paper discusses the first stage of the project, in which we collaborated with dancers to study how movement propels the becoming-body of a robot, and outlines our embodied approach to machine learning, grounded in the robot's performative capacity.
Effect of Foot Massage on Pain Responses to Heel Stick in Preterm Infants

Background: Foot massage could inhibit the transmission of pain by 'closing the gate' or by activating the endogenous opioid pathway to decrease nociceptive transmission of pain associated with heel stick. Aim of the Study: To evaluate effect of foot massage on pain responses to heel stick in preterm infants. Material and Method: A quasi-experimental (time-series) design was utilized on a convenient sample of sixty preterm infants less than thirty seven weeks of gestation at two NICUs of Beni-Suif University Hospital and Beni-Suif Health Insurance Hospital in Beni-Suif City. A neonatal assessment sheet about characteristics of both neonates and heel stick sampling, and Premature Infant Pain Profile (PIPP) scale were used to collect data from October 2014 to May 2015. After written consent from parents, infants received no massage on the first sampling, and a 15-minuts. Massage of the foot prior to heel stick on the next sampling (1-3 days) later. One of the researchers applied the foot massage, measured PIPP, heart rate, and oxygen saturation 5min prior to heel stick, during and after heel stick immediately. Results: The current study revealed that preterm infants birth weight ranged from (900-2800gm), massage increased heart rate significantly before heel stick in study group while it decreased significantly after heel stick. Preterm infants who received foot massage prior to heel stick had statistically significant stabled behavioral state than who did not receive. Mean PIPP score had lowered significantly for preterm infants who received foot massage during and after heel stick than who did not received. Duration of sampling was decreased significantly for study than control group. Conclusion: Foot massage improved physiological and behavioral stability and lowered the severity of pain responses to heel stick in preterm infants, as well as decreasing the sampling duration. Recommendations: Foot massage must be involved in the routine care for preterm infants prior heel stick.
PROTEIN EXPRESSION AFTER NACL TREATMENT IN TWO TOMATO CULTIVARS DIFFERING IN SALT TOLERANCE

SDS-PAGE electrophoresis was used to study the effect of NaCl on protein expression in two cultivars of tomato (Solanum lycopersicum L.): Edkawi (salt-tolerant) and Castle rock (salt-sensitive). Five-day-old seedlings were grown on MS agar media supplemented with 0, 50, 100, 150, 200 and 300 mM NaCl. Two days after treatment the seedlings were examined to determine the effect of salt on their growth and to relate that to protein banding variations. Gel analysis showed differences in at least 4 protein bands with molecular weights at 20, 25, 45 and 65 kDa. These proteins were induced in the 50 mM NaCl treatment in the salt-sensitive cultivar, then decreasing to undetectability at higher concentrations. In the salt-tolerant cultivar, most of the proteins exhibited a more or less steady expression pattern and maintained expression through the 200 mM NaCl treatment. All proteins gave weak or no expression signals at 300 mM NaCl, the treatment that proved lethal. Differentially expressed bands were identified using MALDI-TOF mass spectrometry. The putative function of each identified protein in relation to salt stress is discussed.
Blockchain Analytics : A Bitcoin Perspective

Bitcoin is the first implementation of what has become known as a ‘public permissionless’ blockchain. Guaranteeing security and protocol conformity through its elegant combination of cryptographic assurances and game theoretic economic incentives, it permits censorship resistant public read-write access to its append-only blockchain database without the need for any mediating central authority. Not until its advent has such a trusted, transparent, comprehensive and granular data set of digital economic behaviours been available for public network analysis. In this article, by translating the cumbersome binary data structure of the Bitcoin blockchain into a high fidelity graph model, we demonstrate through various analyses the often overlooked social and econometric benefits of employing such a novel open data architecture. Specifically we show (a) how repeated patterns of transaction behaviours can be revealed to link user activity across the blockchain; (b) how newly mined bitcoin can be associated to demonstrate individual accumulations of wealth; (c) through application of the naïve quantity theory of money that Bitcoin’s disinflationary properties can be revealed and measured; and (d) how the user community can develop coordinated defences against repeated denial of service attacks on the network. All of the aforementioned being exemplary benefits that would be lost with the closed data models of the ‘private permissioned’ distributed ledger architectures that are dominating enterprise level development due to existing blockchain issues of governance, scalability and confidentiality.
Effective dielectric constant of periodic composite materials

We presentcomputer simulation data for the effective permittivity ~in the quasistatic limit ! of a system composed of discrete inhomogeneities of permittivity e1, embedded in a three-dimensional homogeneous matrix of permittivity e2. The primary purpose of this paper is to study the related issue of the effect of the geometric shape of the components on the dielectric properties of the medium. The secondary purpose is to analyse how the spatial arrangement in these two-phase materials affects the effective permittivity. The structures considered are periodic lattices of inhomogeneities. The numerical method proceeds by an algorithm based upon the resolution of boundary integral equations. Finally, we compare the prediction of our numerical simulation with the effective medium approach and with results of previous analytical works and numerical experiments.
Testing for convergence from the micro level

In the growth literature, researchers are typically concerned with macro convergence. However, to the extent that macro dynamics result from the underlying microeconomic relations, convergence should also be investigated at the micro-level. In this paper, we suggest an approach that allows exploiting large micro panels to test for convergence. Compared to the traditional convergence analysis, this approach allows obtaining, at the same time, β and σ like convergence parameters for both the micro and the macro level of interest. We provide a practical example that analyzes productivity convergence in Italy across firms and provinces using a large sample of Italian firms.
A quantum transport approach to the calculation of gate tunnelling current in Nano-scale FD SOI MOSFETs

As integrated circuits (ICs) become more densely packed with transistors, the conventional MOSFETs approach their physical limits of operation. Thus many novel device structures are being extensively explored. As a substitute Ultra thin Nano scale MOSFETs are one of the potential candidates. It is very attractive one-dimensional material and is useful for future nanoelectronic applications. We have used quantum transport to investigate the effect of scattering due to coupling of the gate contact on the gate tunnelling current. We have developed a proper self energy term which is included within the Hamiltonian formalism for the Poisson Schrödinger solver. It will manifest the coupling of scattering parameter on the gate tunnelling current.
Nearest Neighbor Search Applications for the Terasys Massively Parallel Workstation.

Abstract : The Terasys workstation is a massively parallel computer developed at IDA's Center for Computing Sciences. This report, based on a project conducted in IDA's Computer and Software Engineering Division, presents an overview of the Terasys workstation and discusses how the Terasys could be applied to the task of nearest neighbor search. The report discusses a number of areas where Terasys based nearest neighbor search could potentially be applied including nearest neighbor classification, pattern recognition, and estimating intrinsic dimensionality. One area where the use of Terasys-based nearest neighbor search seems particularly promising is in the development of new neighbor classifiers. The report includes experimental results showing that a Terasys with 32,768 processors can perform a particular nearest neighbor search problem up to 69 times faster than a Sun Microsystems 61 MHz Sparcstation-20. To illustrate how the Terasys could be applied to the kinds of government work conducted by IDA divisions outside of the Center for Computing Sciences, the report examines three possible applications of Terasys-based nearest neighbor search to an ongoing radar evaluation project in IDA's Science and Technology Division.
Extending the Rash model to a multiclass parametric network model

Marianna Bolla and Ahmed Elbanna Institute of Mathematics Technical University of Budapest Bolla: also at the Center for Telecommunication and Informatics, Debrecen University (Research supported by the TAMOP-4.2.2.B-10/1-2010-0009 project) Elbanna: also at the MTA-BME Stochastic Research Group marib@math.bme. hu, ahmed@math.bme. hu 1st International Conference on Future RFID Technologies, Eger November 6, 2014
Is economics scientific discipline loyal to its own starting points and fundamental principles?

The article argues that the economic scientific community, by disregarding the importance of freedom which was essential for its emancipation and market as its key criterion of choice, is disloyal to its own starting points and fundamental principles. By dictating strict methodological rules the neoclassical school has consolidated its monopoly position within economics. The article highlights that this methodological normativism is substantially reducing the diversity of methodological approaches and that such restriction of freedom has become a source of subordination within economic community. The author argues that today a new emancipation is needed, with a strong emphasis on the freedom to forge new approaches and acute awareness of the fact that no theoretical platform can persist without adequate demand for its findings in the science market.
Design of Doubly Complementary Stator-PM Machine With High Magnet Utilization Factor for Low-Cost Applications

Aiming to improve permanent magnet (PM) utilization factor, suppress cogging torque, and reduce back-EMF harmonics in stator-PM machines, a new type of stator-PM doubly complementary machines (DCMs) are proposed in this paper. These machines employ two complementarities in the structure, as one exists in double rotors and the other exists in the units belonging to same phases. The first complementary characteristic supplies a consecutive switching path for PM exciting flux, so that shorted or open magnetic path could be avoided to reduce cogging torque and improve PM utilization. The second one is designed to reduce back electromotive force (EMF) harmonics and improve the torque density. The topology, operation principle, characteristics, and design methodology for DCMs are presented. Simulation and experiments are conducted for a 12/11(stator teeth/rotor teeth) DCM to evaluate its performance and verify this design methodology. It is revealed that this machine could obtain good sinusoidal back-EMF waveform, small torque ripple, and high PM utilization factor due to the doubly complementary characteristic.
Computational investigation into the phase transitions from AlPO4-H3

Molecular dynamics simulation approach has been used to investigate the phase transitions from aluminophosphate AlPO 4 -H 3 . Derived from AlPO 4 -H 3 , several hypothetical models of its high-temperature phases are designed through removing the bridged water molecules and changing the up-down connected sequences of T-sites in the 4-membered rings. Full geometry optimizations are performed to obtain structural parameters for the models that are compared to the reported data, and their structure features and thermodynamic stabilities have been discussed. The simulation study suggests that AlPO 4 -H 3 is energetically favored to transform to AlPO 4 -C, and then to AlPO 4 -D as well as to other novel hypothetical 3D open-frameworks.
Psychometric characteristics of the Personality Belief Questionnaire – Short Form

This study evaluated the psychometric properties of the Brazilian version of the Personality Belief Questionnaire – Short Form (PBQ-SF). A sample of 700 college students answered to the Brazilian version of the PBQ-SF. The results showed good estimates of reliability (Cronbach’s alpha) of the PBQ-SF scales, indi-cating a significant association between the beliefs of each of the scales. The results of factor analysis of the PBQ-SF were similar to its original version. Overall, the findings provide support for the existence of factorial validity for the Brazilian version of the PBQ-SF, suggesting that it is a practical tool for the mea-surement of dysfunctional beliefs related to personality disorders
Motives for inter-firm cooperation on R&D and innovation: empirical evidence from Argentine and Spain

Motives and determinants supporting inter-firm technological cooperation have been extensively investigated in developed countries but scarcely addressed in developing countries. This paper addresses these issues, investigating empirically several factors influencing the likelihood to cooperate on R&D and innovation between Argentine and Spanish firms, their strategic motives and firms characteristics which influence cooperation. We draw upon data collected through a survey of 104 firms and complementary information gathered from 19 in-depth interviews, combining both qualitative and quantitative methodology. Results of a multinomial regression and the interviews show that the probability to cooperate increases with the firm size and exportation activities and decrease with the firm age whereas, opposite to literature findings, technological intensity of the firm is a non-significant variable. While for Argentine firms the principal motives are cost reduction and the possibilities for improving learning and capabilities, access to new knowledge for technological development and the search for market opportunities are the principal motives for firms located in Spain. Results of interviews also indicates that firm-specific motives and expectations may differ considerably according the activity sector, with relevant implication for norms and regulation policies in each country.
articleComparative analysis of right element mutant lox sites on recombination efficiency in embryonic stem cells

Background: Cre-mediated site-specific integrative recombination in mouse embryonic stem (ES) cells is a useful tool for genome engineering, allowing precise and repeated site-specific integration. To promote the integrative reaction, a left element/right element (LE/RE) mutant strategy using a pair of lox sites with mutations in the LE or RE of the lox sequence has previously been developed. Recombination between LE and RE mutant lox produces a wild-type loxP site as well as an LE+RE double mutant lox site, which has mutations in both sides and less affinity to Cre, resulting in stable integration. We previously demonstrated successful integrative recombination using lox71 (an LE mutant) and lox66 (an RE mutant) in ES cells. Recently, other LE/RE mutant lox sites showing higher recombination efficiency in Escherichia coli have been reported. However, their recombination efficiency in mammalian cells remains to be
MULTIRATE ANALYSIS AND NEURAL NETWORK BASED CLASSIFICATION OF HUMAN EMOTIONS USING FACIAL ELECTROMYOGRAPHY SIGNALS

G. Charlyn Pushpa Latha and M. Mohana Priya Faculty of Engineering, Karpagam University, Coimbatore, India E-Mail: charlyn.latha@gmail.com ABSTRACT Facial electromyography is a modality for designing emotion recognition system which is gaining popularity as a human machine interface to control the devices. In this research, we analyse the Facial Electromyography (FEMG) signals for the six emotions namely anger, disgust, fear, happy, neutral and sad using the multirate features. Multirate signal processing is a technique which alters the rate of the discrete-time signals, either by adding or deleting a portion of the signal samples. The advantages of such multirate features are that it increases the processing efficiency and reduces DSP hardware requirements. Twenty subjects took part in this experimental study. Three multirate features are used to derive the significant features. Six emotions were identified by applying the multirate features as input to neural network models. Two network models namely Cascade Network and Fitting Network were used and compared to identify an efficient network for emotion identification. The performance of the networks identified the six emotions in the range of 78.56% to 98.72%.
A Framework for MRI Image Retrieval using Curvelet transform and Euclidean Distance

Content Based Image Retrieval (CBIR) system supports users to retrieve relevant medical images based on their features. Current content based image retrieval systems are incapable of providing exact results to the users. To address this problem a consistent feature extraction method is required for content based medical image retrieval system to extract similar features from the images. In this study discrete curvelet based feature extraction technique is proposed to retrieve similar images and the similarity distance is calculated by using Euclidean distance. The proposed method gives better precision and recall rate. Experimental results on a database of 200 MRI images.
A low-cost dual energy CT system with sparse data

Dual Energy CT (DECT) has recently gained significant research interest owing to its ability to discriminate materials, and hence is widely applied in the field of nuclear safety and security inspection. With the current technological developments, DECT can be typically realized by using two sets of detectors, one for detecting lower energy X-rays and another for detecting higher energy X-rays. This makes the imaging system expensive, limiting its practical implementation. In 2009, our group performed a preliminary study on a new low-cost system design, using only a complete data set for lower energy level and a sparse data set for the higher energy level. This could significantly reduce the cost of the system, as it contained much smaller number of detector elements. Reconstruction method is the key point of this system. In the present study, we further validated this system and proposed a robust method, involving three main steps: (1) estimation of the missing data iteratively with TV constraints; (2) use the reconstruction from the complete lower energy CT data set to form an initial estimation of the projection data for higher energy level; (3) use ordered views to accelerate the computation. Numerical simulations with different number of detector elements have also been examined. The results obtained in this study demonstrate that 1 + 14% CT data is sufficient enough to provide a rather good reconstruction of both the effective atomic number and electron density distributions of the scanned object, instead of 2 sets CT data.
The Study of Key Technology for Dynamic Resource Management in the Cloud Computing Environments

Storage resource scheduling is lack of flexibility, and user’ demand for different data is vary. In cloud computing storage resource scheduling process, these data files to be equally are irrational, so it needs a dynamic storage resource scheduling mechanism to distinguish requirements of different data. For the file hot issues that a surge request results in the copy number of the current file is difficult to meet the demand of Cloud computing, we presented a cloud storage resources dynamic scheduling mechanism based on Hadoop distributed file system and genetic algorithm. We used tree structure to encode and decode chromosomes, used the spanning tree algorithm to generate the initial population of virtual machines. We designed the corresponding fitness function evaluation program. And according to the changes in chromosome structure we designed selection operator, crossover operator and mutation operator. Experimental results show that the algorithm compared with traditional algorithms, convergence time is faster, while effectively reducing the number of virtual machine migration.