Miracle-dz/UniFAR-FTUs huggingface dataset:
FORMATION OF ULTRACOMPACT X-RAY BINARIES THROUGH CIRCUMBINARY DISK-DRIVEN MASS TRANSFER

The formation of ultracompact X-ray binaries (UCXBs) has not been well understood. Previous works show that ultrashort orbital periods (less than 1 hr) may be reached through mass transfer driven by magnetic braking in normal low/intermediate-mass X-ray binaries (L/IMXBs) only for an extremely small range of initial binary parameters, which makes it difficult to account for the rather large population of UCXBs. In this paper, we report the calculated results on mass transfer processes in L/IMXBs with a circumbinary (CB) disk. We show that when the orbital angular momentum loss due to a CB disk is included, ultrashort orbital periods could be reached for a relatively wide range of initial binary parameters. The results of our binary models suggest an alternative formation channel for UCXBs.
Function Optimization using Guided Local Search

In this report, we examine the potential use of Guided Local Search (GLS) for function optimization. In order to apply GLS, the function to be minimized is augmented with a set of penalty terms that enable local search to escape from local minima. The function F6 is used to demonstrate the proposed technique.
The effects of smoking on periodontal disease: An evidence-based comprehensive literature review

The direct link between smoking, lung diseases, cancer, cardiovascular disease and poor pregnancy outcomes, such as miscarriage and low birth weight, has been extensively studied. In the past three decades, there has also been an increasing awareness of the impact of smoking on periodontal disease. Smoking is considered the major environmental risk factor in the prevalence, extent and severity of periodontal disease. This review article will attempt to build on previous studies in the periodontal literature in order to present an evidence-based comprehensive literature review on the effects of smoking on periodontal disease.
K+a galaxies in the zCOSMOS survey - physical properties of systems in their post-starburst phase

The identities of the main processes triggering and quenching star-formation in galaxies remain unclear. A key stage in evolution, however, appears to be represented by post-starburst galaxies. To investigate their impact on galaxy evolution, we initiated a multiwavelength study of galaxies with k+a spectral features in the COSMOS field. We examine a mass-selected sample of k+a galaxies at z=0.48-1.2 using the spectroscopic zCOSMOS sample. K+a galaxies occupy the brightest tail of the luminosity distribution. They are as massive as quiescent galaxies and populate the green valley in the colour versus luminosity (or stellar mass) distribution. A small percentage (<8%) of these galaxies have radio and/or X-ray counterparts (implying an upper limit to the SFR of ~8Msun/yr). Over the entire redshift range explored, the class of k+a galaxies is morphologically a heterogeneous population with a similar incidence of bulge-dominated and disky galaxies. This distribution does not vary with the strength of the Hdelta absorption line but instead with stellar mass in a way reminiscent of the well-known mass-morphology relation. Although k+a galaxies are also found in underdense regions, they appear to reside typically in a similarly rich environment as quiescent galaxies on a physical scale of ~2-8Mpc, and in groups they show a morphological early-to-late type ratio similar to the quiescent galaxy class. With the current data set, we do not find evidence of statistical significant evolution in either the number/mass density of k+a galaxies at intermediate redshift with respect to the local values, or the spectral properties. Those galaxies, which are affected by a sudden quenching of their star-formation activity, may increase the stellar mass of the red-sequence by up to a non-negligible level of ~10%.
Plant Biology Databases: A Needs Assessment

We review the anticipated needs of the plant genome research community for long-lived data collections. We find that there is an increasing need for such repositories, and offer guidelines for balancing the funding of data production projects with those aimed to manage and integrate the data. In particular, we find that there is a pressing need to develop a trained cadre of skilled knowledge workers who are able to curate complex biological data, and to provide this cadre with a system of stable funding that enables data repositories to be established and maintained over extended periods of time. We note approvingly the current trend of species-specific databases to expand into comparative genomics-minded clade-oriented databases, but caution that new technologies are needed to facilitate the transparent integration of data among these databases. Conclusions and specific recommendations begin on page 34.
Structure, dynamics, and thermodynamics of passivated gold nanocrystallites and their assemblies

The structure, dynamics, and thermodynamics of gold nanocrystallites passivated by alkylthiolate monolayers were investigated, using molecular dynamics simulations, in different environmentsas isolated gas-phase clusters, when adsorbed on a graphite surface, and when assembled into three-dimensional superlattices. The packing arrangements and densities of the monolayers passivating the facets of the core gold nanocrystallites differ from those found on extended gold surfaces, exhibiting organization into molecular bundles of preferred orientations which upon heating undergo a reversible melting transition from the ordered bundled state to a uniform intermolecular orientational distribution. The equilibrium geometries of adsorbed nanocrystallites depend on the chain length of the passivating molecules which effectively lubricate the interface between the gold core and the graphite surface conferring high surface mobility to the crystallites, involving a collective slip-diffusion mechanism. The room-tempera.
Machine Learning and Its Application at Nooksack Falls Hydroelectric Station

Copyright © 2005, American Association for Artificial Intelligence (www.aaai.org). All rights reserved. The objective of this project is to control water delivery and distribution at Nooksack Falls Hydroelectric Station (NFHS) in order to maximize efficiency of the system, thereby increasing energy generation. Two machine learning algorithms will be applied. (1) Q-learning a reinforcement learning approach to obtain a set of roughly optimal configurations. (2) Recurrent Neural Network (RNN) rough configurations gathered by the Q-learning agent will be used to train the RNN. The RNN will refine these configurations as well as enabling lifelong learning. The significance of this project is to demonstrate the practical utility of the machine learning techniques described above when applied to realworld processes such as NFHS. Utility process control has advanced towards increasing productivity and reliability, while decreasing operating costs by replacing humans with automated systems. When NFHS began operation in 1906, it required 24-hour manned operation, a job shared by several men with families living on site. In the 1970s a system of electromechanical relays, DC positioning motors, and low pressure hydraulics were added, decreasing the need for operator attendance. In 2003 a more sophisticated set of controls were added including: high pressure hydraulics, a programmable logic controller (PLC), and a host of relay and analog sensors providing information on plant state. The evolved control configuration outlined above is typical of modern utility process control. Sensor inputs, along with a control scheme devised by plant operators and engineers are programmed into the PLC, which operates the plant according to adjustable set-points. This works well for static processes, those without a great variance of operating conditions. However, NFHS is a dynamic process. Fluctuating river flow conditions, waterborne debris, equipment wear, and mechanical problems are variables impacting NFHS's energy production. For the process to remain optimal, set-points should be adjusted accordingly.
Transcriptome sequencing using the Ion Proton TM System

Understanding the structure, function, and organization of information within genomes is central to basic and translational research. With the advent of deep-sequencing technologies, it has become increasingly evident that transcription is an intricate and dynamic process involving a variety of RNA species, including short RNAs, polyadenylated RNA, and nonadenylated transcripts. Transcriptome sequencing is the most complete yet most cost-efficient method for identifying and quantifying RNA from multiple types of starting material. With the choice of two chips, the Ion PITM Chip and the Ion PIITM Chip,* sequencing coverage depth can be adjusted to determine the sensitivity of detection for low-abundance transcripts and rare RNA types or to multiplex samples for differential gene expression studies (Table 1).
Underwater simultaneous localization and mapping based on EKF and point features

The paper describes a localization system for autonomous underwater vehicles (AUV). It uses a DVL (Doppler velocity log) sensor and AHRS (attitude and heading reference system) sensor to measure AUV's depth, attitude and velocities relative to the bottom. A mechanically scanning imaging sonar (MSIS) is employed to obtain acoustic images of objects in underwater environment. In order to estimate optimally AUV pose without a priori map of the environment, simultaneous localization and map building (SLAM), a prevailing method in the past decade, is presented based on point features extraction and EKF-based estimator. Use Fluvia Nautic marina data set we compare the proposed method with traditional dead-reckoning, results show that our solution can reduce estimation error significantly.
Assessing Professional Skills in a Multi-scale Environment by Means of Graph-Based Algorithms

The present paper introduces a study of different techniques to assess professional skills in social networks and to align those user skills with existing multi-scale knowledge classifications. Currently both job seekers and talent hunters are looking for new and innovative techniques to filter jobs and candidates as well as candidates are also trying to improve and make more attractive their profiles. In this environment it is necessary to provide new techniques to assess the quality of professional skills depending on user’s activity and to compare with existing scales. To do so some relevant graph-based techniques such as the HITS and the SPEAR algorithms have been used for calculating the confidence of a certain user in a particular skill. Moreover a new re-interpretation of the SPEAR algorithm, called Skillrank, is introduced to take advantage of user’s behavior and history. A major outcome of this approach is that expertise and experts can be detected, verified and ranked using a suited trust metric. The paper also presents a validation of the Skillrank accuracy by means of a sound qualitative and quantitative comparison with existing approaches based on the opinions of a panel of experts (3) on a real dataset (created using the Linkedin API) and two different scales. Although results show in general low values of accuracy (close to 50% of correct classified skills), the Skillrank technique is more accurate than other techniques to align a user skill in a certain scale of knowledge. Finally some discussion, conclusions and future work are also outlined. Keywords— Graph-based algorithms; professional competence; hybrid methods; LinkedIn; Skills; Social Networks.
Analytic approximations for solar cell open circuit voltage, short circuit current and fill factor

For a detailed understanding of solar cell operation and optimization it is necessary to know how the main performance parameters (open circuit voltage, short circuit current and fill factor) depend on material and structural parameters. In this work, we give analytic formulas for the case of solar cells consisting of a single layer absorber, derived from the drift-diffusion model under some simplifying assumptions. We provide insight into the dependency of these parameters on mobility, light intensity, contact workfunctions and recombination coefficients, and we derive simple formulas for limiting cases.
The Application of Optimized Particle Swarm Algorithm in Non-paper Examination

To deal with non-paper test composition algorithm impact on exam quality, we proposed the test-sheet composition algorithms. By comparing a variety of existing intelligent algorithms in the application of test-sheet composition, we identify the shortcomings of existing algorithms, such as the "premature" of algorithm due to the poor local search ability and the low convergence rate, etc. PSO algorithm has no crossover, mutation operators. It directly provides the speed, position update formula, and completes the assessment with the help of the fitness function of iterations. The principles and mechanisms of algorithm are simpler. On the basis of standard PSO algorithm, we proposed a Binary Particle Swarm Optimize (BPSO) algorithm based on probability. Bayes formula was used to overcome the human factors impacting on algorithm convergence speed. The algorithm validity has been shown in the simulation experiment with Java.
Party members and activists

Membership of political parties is diverse. Not everyone participates and those who do, do not participate in the same way. This book engages with the debate over the significance and future of political parties as membership organisations and presents the first broad comparative analysis of party membership and activism. It is based on membership surveys which have been administered, gathered and collated by a group of prominent party scholars from across Europe, Canada and Israel. Utilizing this rich data source together with the insights of party scholars, the book investigates what party membership means in advanced industrial democracies. In doing so, it provides a clearer picture of who joins political parties, why they do it, the character of their political activism, how they engage with their parties, and what opinions they hold. This text will be of interest to scholars and students of comparative politics, particularly to those interested in representation, participation, political parties and elections.
Labor Supply and Taxation in France

This paper provides sequential labor supply estimates for French married men and women under specifications analogous to those used by Hausman to account for the effects of taxation upon the budget constraint. Results suggest that, even though labor force participation follows the expected pattern, work hours are quite rigid, most of the variation in the latter being attributed to measurement errors. The second part of the paper concentrates on the simultaneous estimation of male and female labor supply. Conditional maximum likelihood techniques are shown to permit the separate estimation of work hours for both spouses with an appropriate set of instruments aimed at correcting for the biases arising from simultaneity, selectivity, and the nonlinearity of the budget constraint. Although consistent, the resulting estimates apparently contradict the usual rationality restrictions on family labor supply behavior and seem to confirm the lack of flexibility in work hours.
Attribute expansion with sequential learning for object classification

Augmenting the semantic attribute representation with the discriminative features has been proved to be an effective method for improving the performance of object classification. However, how to make the expanded features more effective and discriminative is still an open problem. In this paper, we propose a Sequential Augmented features Learning method (SAL) to implement semantic attribute augmentation. In our SAL method, the augmented non-semantic features are learned one by one under a sequential error-correcting scheme so that we can obtain more discriminating power with very compact expanded features. Extensive experiments are conducted on a public dataset and the results show that our approach achieves encouraging performance.
Exploration and exploitation of homologous series of bis(acrylamido)alkanes containing pyridyl and phenyl groups: β-sheet versus two-dimensional layers in solid-state photochemical [2 + 2] reactions

Sixteen derivatives of the homologous series of bis(acrylamido)alkanes have been synthesized with the aim of systematic analysis of their crystal structures and their solid-state [2 + 2] reactivities. Seven out of the 16 found to have reactive alignments for solid-state [2 + 2] reactions yield dimers and polymers.
From co-emergence dynamics to human perceptual evolution: The role of neuroplasticity during mindfulness training

It is generally accepted that the aim of mindfulness training is to develop greater objectivity, acceptance and detachment with each experience. Using a standard delivery structure, daily practice of mindfulness meditation teaches the trainee to perceive thoughts merely as thoughts and body sensations as body sensations, with an attempt to not identify with the experience. The training promotes reliance on perceptual, rather than judgmental, appraisal of information, resulting in greater ability for experiential acceptance.
Essays on asymmetric information in the automobile insurance market

This dissertation is concerned with the consequences of asymmetric infor mation in the automobile insurance market. It consists of five separate and self contained essays that analyze information asymmetries in terms of risky traffic behavior. Three of the essays are based on a database of insurance contracts and traffic violations, while two essays provide theoretical analyses of how the problems of asymmetric information regarding traffic behavior may be alleviated.
Gaze-supported Interaction ( Demo )

Considering the increasing diversity of display arrangements including wall-sized screens and multidisplay setups, our eye gaze provides a particular high potential for implicit and seamless, as well as fast interactions. However, gaze-based interaction is often regarded as error-prone and unnatural, especially when restricting the input to gaze as a single modality. For this reason, we have developed several interaction techniques benefitting from gaze as an additional, implicit and fast pointing modality for roughly indicating a user’s visual attention in combination with common smartphones to make more explicit and precise specifications. In our demos, we showcase two examples for more natural and yet effective ways of incorporating a user’s gaze as a supporting input modality. The two application scenarios comprise (1) gaze-supported pan-and-zoom techniques using the example of GoogleEarth and (2) gaze-supported navigation and target selection in a virtual 3D scene.
Diagnosis of Helicobacter pylori infection by invasive and noninvasive tests

Although several invasive and noninvasive tests have been developed for the diagnosis of Helicobacter pylori infection, all of the tests have their limitations. We conducted a study to investigate and compare the suitability of rapid urease test (RUT), serology, histopathology and stool antigen tests with polymerase chain reaction (PCR) for detection of H. pylori, and correlate the diagnostic methods with PCR. Eighty nine patients (61 adults, 28 children) referred to the Firoozgar Hospital and Children Medical Center Hospital for diagnostic upper gastrointestinal endoscopy entered to the study and noninvasive tests such as immunoassay for serological antibodies against H. pylori and detection of its antigen in feces were measured. The biopsies were utilized for histological examination, RUT and PCR. The H. pylori statuses were evaluated by the positivity of ureC PCR in biopsy specimens and 53 subjects had H. pylori positive result. Histopathology showed high overall performance in adults and children with sensitivity and specificity 100% and 90%, respectively. Sensitivity, specificity, and accuracy for stool antigen test were 87.8%, 75% and 82%, respectively. Correlation of RUT, serology (IgG), histopathology and stool antigen tests with PCR were 0.82, 0.32, 0.91 and 0.63, respectively. In conclusion, the RUT and histopathology are as accurate as the PCR of biopsy and stool antigen test can consider as appropriate noninvasive test for detection of H. pylori infection.
Plk1-Dependent Recruitment of γ-Tubulin Complexes to Mitotic Centrosomes Involves Multiple PCM Components

The nucleation of microtubules requires protein complexes containing γ-tubulin, which are present in the cytoplasm and associate with the centrosome and with the mitotic spindle. We have previously shown that these interactions require the γ-tubulin targeting factor GCP-WD/NEDD1, which has an essential role in spindle formation. The recruitment of additional γ-tubulin to the centrosomes occurs during centrosome maturation at the G2/M transition and is regulated by the mitotic kinase Plk1. However, the molecular details of this important pathway are unknown and a Plk1 substrate that controls γ-tubulin recruitment has not been identified. Here we show that Plk1 associates with GCP-WD in mitosis and Plk1 activity contributes to phosphorylation of GCP-WD. Plk1 depletion or inhibition prevents accumulation of GCP-WD at mitotic centrosomes, but GCP-WD mutants that are defective in Plk1-binding and -phosphorylation still accumulate at mitotic centrosomes and recruit γ-tubulin. Moreover, Plk1 also controls the recruitment of other PCM proteins implicated in centrosomal γ-tubulin attachment (Cep192/hSPD2, pericentrin, Cep215/Cdk5Rap2). Our results support a model in which Plk1-dependent recruitment of γ-tubulin to mitotic centrosomes is regulated upstream of GCP-WD, involves multiple PCM proteins and therefore potentially multiple Plk1 substrates.
Microarray Comparative Genomic Hybridisation Analysis Incorporating Genomic Organisation, and Application to Enterobacterial Plant Pathogens

Microarray comparative genomic hybridisation (aCGH) provides an estimate of the relative abundance of genomic DNA (gDNA) taken from comparator and reference organisms by hybridisation to a microarray containing probes that represent sequences from the reference organism. The experimental method is used in a number of biological applications, including the detection of human chromosomal aberrations, and in comparative genomic analysis of bacterial strains, but optimisation of the analysis is desirable in each problem domain. We present a method for analysis of bacterial aCGH data that encodes spatial information from the reference genome in a hidden Markov model. This technique is the first such method to be validated in comparisons of sequenced bacteria that diverge at the strain and at the genus level: Pectobacterium atrosepticum SCRI1043 (Pba1043) and Dickeya dadantii 3937 (Dda3937); and Lactococcus lactis subsp. lactis IL1403 and L. lactis subsp. cremoris MG1363. In all cases our method is found to outperform common and widely used aCGH analysis methods that do not incorporate spatial information. This analysis is applied to comparisons between commercially important plant pathogenic soft-rotting enterobacteria (SRE) Pba1043, P. atrosepticum SCRI1039, P. carotovorum 193, and Dda3937. Our analysis indicates that it should not be assumed that hybridisation strength is a reliable proxy for sequence identity in aCGH experiments, and robustly extends the applicability of aCGH to bacterial comparisons at the genus level. Our results in the SRE further provide evidence for a dynamic, plastic ‘accessory’ genome, revealing major genomic islands encoding gene products that provide insight into, and may play a direct role in determining, variation amongst the SRE in terms of their environmental survival, host range and aetiology, such as phytotoxin synthesis, multidrug resistance, and nitrogen fixation.