Miracle-dz/UniFAR-FTUs huggingface dataset:
Raman-scattered O VI λ6825 and the Accretion Disk Emission Model in the Symbiotic Stars V1016 Cygni and HM Sagittae

We present the high-resolution spectra of the D-type symbiotic stars V1016 Cygni and HM Sagittae obtained with the Bohyunsan Optical Echelle Spectrograph (BOES) and investigate the double-peaked asymmetric profiles of the Raman scattered O VI λ6825 formed through Raman scattering of O VI λ1032 by atomic hydrogen. By adopting a wind accretion disk model, the O VI emission region is described by a Keplerian thin disk. The Raman scattering occurs in a neutral region near the giant, part of which is ionized by the strong UV radiation from the hot white dwarf. A Monte Carlo technique is used to compute the line profiles that are modulated by the slow spherical stellar wind from the giant component with the ionization front approximated by a hyperboloid. In order to account for the asymmetry and the central dip in the profiles, we add an O VI resonance scattering region between the hot white dwarf and the giant which hinders the incidence of slightly blue O VI photons upon the H I region. Overall good fits to the observed data are obtained from our model, which lends support to the accretion disk emission model. The best-fitting parameters for V1016 Cyg are vo = 30 km s-1, v∞ = 11 km s-1, and vc = 10 km s-1, where vo, v∞, and vc are the velocity of the outer disk rim, the terminal velocity of the giant wind, and the velocity component of the resonance scattering O VI region along the binary axis, respectively. Similar fitting parameters vo = 26 km s-1, v∞ = 10 km s-1, and vc = 7 km s-1 are obtained for HM Sge.
Decomposing Centralized Multiagent Policies

Using or extending Markov decision processes (MDPs) or partially observable Markov decision processes (POMDPs) to model multiagent decision problems has become an important trend. Generally speaking, there are two types of models: centralized ones and decentralized. The centralized ones focus on finding the best joint action given any global state, while the decentralied ones try to find out for each agent, what is the best local action given all the partial information available in that agent. Although decentralized models better capture the nature of decentralization in multiagent systems, they are much harder to solve compared to centralized models. In this paper, we show that, by studying the communication needs of the centralized models, we can establish a connection between the two models, and the solutions to centralized models (i.e. centralized policies) can be used to derive solutions to decentralized models (i.e. decentralized policies) – a process we call plan decomposition. We show that the amount of communication needed could be greatly reduced during the decomposition, and there are techniques that could be applied to produce a set of decentralized policies based on the same centralized policy. While this method does not solve decentralized models optimally, it does offer a great deal of flexibility and allows us to tradeoff the quality of the policies with the amount of communication needed, and gives us better insights about the need and timing for effective coordination in multiagent planning.
Workload characterization of biometric applications on Pentium 4 microarchitecture

Biometric computing is a technique that uses physiological and behavioral characteristics of persons to identify and authenticate individuals. Due to the increasing demand on security, privacy and anti-terrorism, biometric applications represent the rapidly growing computing workloads. However, very few results on the execution characteristics of these applications on the state-of-the-art microprocessor and memory systems have been published so far. This paper proposes a suite of biometric applications and reports the results of a biometric workload characterization effort, focusing on various architecture features. To understand the impacts and implications of biometric workloads on the processor and memory architecture design, we contrast the characteristics of biometric workloads and the widely used SPEC 2000 integer benchmarks. Our experiments show that biometric applications typically show small instruction footprint that can fit in the L1 instruction cache. The loads and stores account for more than 50% of the dynamic instructions. This indicates that biometric applications are data-centric in nature. Although biometric applications work across large-scale datasets to identify matched patterns, the active working sets of these workloads are usually small. As a result, prefetching and large L2 cache effectively handle the data footprints of a majority of the studied benchmarks. Branch misprediction rate is less than 4% on all studied workloads. The IPC of the studied benchmarks ranges from 0.13 to 0.77 indicates that out-of-order superscalar execution is not quite efficient. The developed biometric benchmark suite (BMW) and input data sets are freely available and can be downloaded from http://www.ideal. ece.ufl. edu/BMW.
Fetal origins of adult disease: epidemiology and mechanisms

The past 10 years have provided unequivocal evidence that there are associations between birth size measures and future development of adult diseases, such as type 2 diabetes and coronary artery disease. Despite initial concern that bias or residual confounding in the analyses had produced these rather bizarre associations, the findings have now been reproduced in different cohorts by independent investigators from many parts of the world. The challenge for the next decade must be to discover the cellular and molecular mechanisms giving rise to these associations. If this aim is accomplished, it might be possible to devise strategies to reduce the impact of these disabling, chronic, and expensive diseases. The purpose of this review is to describe some of the relevant, important, and more recent epidemiological studies, and also to discuss potential mechanisms underpinning the associations.J Clin Pathol(J Clin Pathol 2000;53:822–828)
A survey: Verification of family relationship from parents and child facial images

Verification of Family Relationship from facial images is a challenging problem in computer vision, and there are very few attempts on tackling this problem in the literature. We present a survey on how to verify family relation by a various metric learning method, probabilistic framework and several methods which can extract critical points on a face using both location and texture information such as lip corners, eye corners and nose tip. These are critical points in a human face, and centre of the mouth of each face. Motivated by the fact that interclass samples (without kinship relations) with higher similarity usually lie in a neighborhood and are more easily misclassified than those with lower similarity, we aim to learn a distance metric under which the interclass samples (with kinship relations) are pushed as close as possible and interclass samples lying in a neighborhood are repulsed and pulled as far as possible, simultaneously, such that more discriminative information can be exploited for verification. To make better use of multiple feature descriptors to further improve the verification performance it is necessary to develop a method to extract the salient familial traits in face images for kinship recognition. If this idea works, an instrument may be invented to measure familial relationships. This computational kinship measurement might have a large impact in real applications, such as child adoptions, trafficking/smuggling of children, and finding missing children, identifying relatives from a photo collection. We can collect Dataset of young parent and old parent face images from Internet. In our research work verification has to be performed by measuring the number of image pairs available for training and testing along with images of their parents and children frontal images. These images are taken as kinship so as to maintain relationship between two persons who are biologically related with overlapping genes.
Building Bridges to the Community: The Kirkham Family Connectors (KFC) Prison Programme

Families represent a form of social capital that can influence effective reintegration depending on the strength of the bond, and the nature of the relationship. An innovative training programme delivered at HMP Kirkham was designed to mobilise the strengths of prisoners, in the period prior to their release, by engaging family members as bridges to community resources and by a shared planning process designed to build stronger bonds between prisoners and their families. The conceptual framework for the Kirkham Family Connectors (KFC) project is based on the principles of Asset Based Community Development (ABCD) and Assertive Linkage (assisting individuals in engaging with such assets). The project aimed to build prisoner resettlement capital by identifying what each prisoner’s skills and strengths were, what enthused and engaged them, and to create partnerships with family members to establish accessible pathways to related resources in the communities to which they would be returning on their release. Evaluation data show that the programme generated hope and a sense of partnership among participants and key lessons for a strengths-based intervention to support the prison-community transition. All three of the participating groups – staff, prisoners, and families – reported positive engagement and an emerging sense of hope, and group cohesion through shared goals. There is considerable scope for both peer and probation staff delivery of the programme in the future, and for extending the scale and the scope of the project.
Support Vector Machine Approach for Classification of Cancerous Prostate Regions

The objective of this paper, is to apply support vector machine (SVM) approach for the classification of cancerous and normal regions of prostate images. Three kinds of textural features are extracted and used for the analysis: parameters of the GaussMarkov random field (GMRF), correlation function and relative entropy. Prostate images are acquired by the system consisting of a microscope, video camera and a digitizing board. Cross-validated classification over a database of 46 images is implemented to evaluate the performance. In SVM classification, sensitivity and specificity of 96.2% and 97.0% are achieved for the 32x32 pixel block sized data, respectively, with an overall accuracy of 96.6%. Classification performance is compared with artificial neural network and k-nearest neighbor classifiers. Experimental results demonstrate that the SVM approach gives the best performance. Keywords—Computer-aided diagnosis, support vector machines, Gauss-Markov random fields, texture classification.
Experimental Activity on Cooperative Mobile Positioning in Indoor Environments

Traditional localization systems are based on the information obtained from some fixed reference points (e.g., Access Points (APs)) to Mobile Station (MS) links; typically for short-range, Received Signal Strength Difference (RSSD) or Received Signal Strength (RSS) measurements are used. In order to enhance the accuracy of localization systems indoors, the innovative solution presented in this paper considers also the information obtained from MS-MS links. A proof of concept in a real scenario is implemented in an indoor environment by using a Wireless Local Area Network (WLAN), and the results show that the accuracy is enhanced with respect to non-cooperative schemes. Non-Linear Least Square (NLLS) and Extended Kalman Filter (EKF) are used as data fusion algorithms to combine RSSD measurements from AP-MS links and RSS measurements from MS-MS links.
Enhanced Excitatory Synaptic Connectivity in Layer V Pyramidal Neurons of Chronically Injured Epileptogenic Neocortex in Rats

Formation of new recurrent excitatory circuits after brain injuries has been hypothesized as a major factor contributing to epileptogenesis. Increases in total axonal length and the density of synaptic boutons are present in layer V pyramidal neurons of chronic partial isolations of rat neocortex, a model of posttraumatic epileptogenesis. To explore the functional consequences of these changes, we used laser-scanning photostimulation combined with whole-cell patch-clamp recording from neurons in layer V of somatosensory cortex to map changes in excitatory synaptic connectivity after injury. Coronal slices were submerged in artificial CSF (23°C) containing 100 μm caged glutamate, APV (2-amino-5-phosphonovaleric acid), and high divalent cation concentration to block polysynaptic responses. Focal uncaging of glutamate, accomplished by switching a pulsed UV laser to give a 200–400 μs light stimulus, evoked single- or multiple-component composite EPSCs. In neurons of the partially isolated cortex, there were significant increases in the fraction of uncaging sites from which EPSCs could be evoked (“hot spots”) and a decrease in the mean amplitude of individual elements in the composite EPSC. When plotted along the cortical depth, the changes in EPSCs took place mainly between 150 and 200 μm above and below the somata, suggesting a specific enhancement of recurrent excitatory connectivity among layer V pyramidal neurons of the undercut neocortex. These changes may shift the balance within cortical circuits toward increased synaptic excitation and contribute to epileptogenesis.
Datastructuring—Organizing and curating digital traces into action

Digital transformations and processes of “datafication” fundamentally reshape how information is produced, circulated and given meaning. In this article, we provide a concept of “datastructuring” which seeks to capture this reshaping as both a product of and productive of social activity. To do this we focus on (1) how new forms of social action map onto and are enabled by technological changes related to datafication, and (2) how new forms of datafied social action constitute a form of knowledge production which becomes embedded in technologies themselves. We illustrate the potential of the datastructuring concept with empirical examples which also serve to highlight some new avenues for research and some empirical questions to explore further. We suggest a focus on datastructuring can ignite scholarly debates across disciplines that may share an interest in the technological configurations, sorting activities, and other socio-material forces that shape digital spaces, but which are rarely brought together. Such cross-disciplinary conceptualizations may give more attention to how information is structured and organized, becomes “algorithmically recognizable”, and emerges as (in)visible in digital, datafied spaces. Such a concept, we suggest, may help us better understand the novel ways in which “backstage datawork” and “data sorting processes” gain traction in political interventions, commercial processes, and social ordering.
An Approach to Computing Multidimensional Isotonic Regressions

This paper gives an approach for determining isotonic regre ssions for data at points in multidimensional space, with the ordering given by domination. Recent algori thmic advances for 2-dimensional isotonic regressions have made them useful for significantly larger d ata sets, and here we provide an advance for dimensions 3 and larger. Given a set V of n d-dimensional points, it is shown that an isotonic regressio n on V can be determined iñ Θ(n2), Θ̃(n3), andΘ̃(n) time for theL1, L2, andL∞ metrics, respectively. This improves upon previous results by a factor of Θ̃(n). The core of the approach is in extending the regression to a set of pointsV ′ ⊃ V where the domination ordering on V ′ can be represented with relatively few edges.
Under Consideration for Publication in Theory and Practice of Logic Programming the Impact of Disjunction on Reasoning under Existential Rules: Research Summary

Datalog ± is a Datalog-based language family enhanced with existential quantification in rule heads, equalities and negative constraints. Query answering over databases with respect to a Datalog ± theory is generally undecidable, however several syntactic restrictions have been proposed to remedy this fact. However, a useful and natural feature however is as of yet missing from Datalog ± : The ability to express uncertain knowledge, or choices, using disjunction. It is the precise objective of the doctoral thesis herein discussed, to investigate the impact on the complexity of query answering, of adding disjunction to well-known decidable Datalog ± fragments, namely guarded, sticky and weakly-acyclic Datalog ± theories. For guarded theories with disjunction, we obtain a strong 2EXP lower bound in the combined complexity, even for very restricted formalisms like fixed sets of (disjunctive) inclusion dependencies. For sticky theories, the query answering problem becomes undecidable, even in the data complexity, and for weakly-acyclic query answering we see a reasonable and expected increase in complexity.
A Dominant Mutation in mediator of paramutation2, One of Three Second-Largest Subunits of a Plant-Specific RNA Polymerase, Disrupts Multiple siRNA Silencing Processes

Paramutation involves homologous sequence communication that leads to meiotically heritable transcriptional silencing. We demonstrate that mop2 (mediator of paramutation2), which alters paramutation at multiple loci, encodes a gene similar to Arabidopsis NRPD2/E2, the second-largest subunit of plant-specific RNA polymerases IV and V. In Arabidopsis, Pol-IV and Pol-V play major roles in RNA–mediated silencing and a single second-largest subunit is shared between Pol-IV and Pol-V. Maize encodes three second-largest subunit genes: all three genes potentially encode full length proteins with highly conserved polymerase domains, and each are expressed in multiple overlapping tissues. The isolation of a recessive paramutation mutation in mop2 from a forward genetic screen suggests limited or no functional redundancy of these three genes. Potential alternative Pol-IV/Pol-V–like complexes could provide maize with a greater diversification of RNA–mediated transcriptional silencing machinery relative to Arabidopsis. Mop2-1 disrupts paramutation at multiple loci when heterozygous, whereas previously silenced alleles are only up-regulated when Mop2-1 is homozygous. The dramatic reduction in b1 tandem repeat siRNAs, but no disruption of silencing in Mop2-1 heterozygotes, suggests the major role for tandem repeat siRNAs is not to maintain silencing. Instead, we hypothesize the tandem repeat siRNAs mediate the establishment of the heritable silent state—a process fully disrupted in Mop2-1 heterozygotes. The dominant Mop2-1 mutation, which has a single nucleotide change in a domain highly conserved among all polymerases (E. coli to eukaryotes), disrupts both siRNA biogenesis (Pol-IV–like) and potentially processes downstream (Pol-V–like). These results suggest either the wild-type protein is a subunit in both complexes or the dominant mutant protein disrupts both complexes. Dominant mutations in the same domain in E. coli RNA polymerase suggest a model for Mop2-1 dominance: complexes containing Mop2-1 subunits are non-functional and compete with wild-type complexes.
Present and Future Potential Habitat Distribution of Carcharhinus falciformis and Canthidermis maculata By-Catch Species in the Tropical Tuna Purse-Seine Fishery under Climate Change

By-catch species from tropical tuna purse seine fishery have been affected by fishery pressures since the last century; however, the habitat distribution and the climate change impacts on these species are poorly known. With the objective of predicting the potential suitable habitat for a shark (Carcharhinus falciformis) and a teleost (Canthidermis maculata) in the Indian, Atlantic and Eastern Pacific Oceans, a MaxEnt species distribution model (SDM) was developed using data collected by observers in tuna purse seiners. The relative percentage of contribution of some environmental variables (depth, sea surface temperature, salinity and primary production) and the potential impact of climate change on species habitat by the end of the century under the A2 scenario (scenario with average concentrations of carbon dioxide of 856 ppm by 2100) were also evaluated. Results showed that by-catch species can be correctly modelled using observed occurrence records and few environmental variables with SDM. Results from projected maps showed that the equatorial band and some coastal upwelling regions were the most suitable areas for both by-catch species in the three oceans in concordance with the main fishing grounds. Sea surface temperature was the most important environmental variable which contributed to explain the habitat distribution of the two species in the three oceans in general. Under climate change scenarios, the largest change in present habitat suitability is observed in the Atlantic Ocean (around 16% of the present habitat suitability area of Carcharhinus falciformis and Canthidermis maculata, respectively) whereas the change is less in the Pacific (around 10% and 8%) and Indian Oceans (around 3% and 2 %). In some regions such as Somalia, the Atlantic equatorial band or Peru’s coastal upwelling areas, these species could lose potential habitat whereas in the south of the equator in the Indian Ocean, the Benguela System and in the Pacific coast of Central America, they could gain suitable habitat as consequence of global warming. This work presents new information about the present and future habitat distribution under climate change of both by-catch species which can contributes to the development of ecosystem-based fishery management and spatially driven management measures.
Release of Dengue Virus Genome Induced by a Peptide Inhibitor

Dengue virus infects approximately 100 million people annually, but there is no available therapeutic treatment. The mimetic peptide, DN59, consists of residues corresponding to the membrane interacting, amphipathic stem region of the dengue virus envelope (E) glycoprotein. This peptide is inhibitory to all four serotypes of dengue virus, as well as other flaviviruses. Cryo-electron microscopy image reconstruction of dengue virus particles incubated with DN59 showed that the virus particles were largely empty, concurrent with the formation of holes at the five-fold vertices. The release of RNA from the viral particle following incubation with DN59 was confirmed by increased sensitivity of the RNA genome to exogenous RNase and separation of the genome from the E protein in a tartrate density gradient. DN59 interacted strongly with synthetic lipid vesicles and caused membrane disruptions, but was found to be non-toxic to mammalian and insect cells. Thus DN59 inhibits flavivirus infectivity by interacting directly with virus particles resulting in release of the genomic RNA.
Comparative BER Performance Analysis of OFDM System Using M-PSK and M-QAM Modulation Schemes over AWGN Channel

Orthogonal frequency division multiplexing (OFDM) is becoming the chosen modulation technique for wireless communications. It can provide large data rates and is sufficiently robust in the face of radio channel impairments. Digital modulation techniques contribute to the evolution of our mobile wireless communications by increasing the capacity, speed and quality of wireless networks. In this paper, I concentrate on digital modulation schemes, such as M-PSK (M-ary Phase Shift keying) and M-QAM (M-ary Quadrature Amplitude Modulation) over an additive white Gaussian Noise (AWGN) channel to analyse the performance of an OFDM system in terms of bit error rate (BER). This is evaluated through a computer simulation, the results from which make it clear that, for high-capacity data rate transmission, the M-QAM modulation is better than the M-PSK modulation.