Miracle-dz/UniFAR-FTUs huggingface dataset:
Trends in Ambulatory Prescribing of Antiplatelet Therapy among US Ischemic Stroke Patients: 2000–2007

Objective. Study objectives were to assess temporal trends and identify patient- and practice-level predictors of the prescription of antiplatelet medications in a national sample of ischemic stroke (IS) patients seeking ambulatory care. Methods. IS-related outpatient visits by adults were identified using the National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey for the years 2000–2007. We assessed prescribing of antiplatelet medications using the generic drug code and drug entry codes in these data. Temporal trends in antiplatelet prescribing were assessed using the Cochran-Mantel-Haenszel test for trend. Results. We identified 9.5 million IS-related ambulatory visits. Antiplatelet medications were prescribed at 35.5% of visits. Physician office prescribing of the clopidogrel-aspirin combination increased significantly from 0.5% in 2000 to 22.0% in 2007 (P = 0.05), whereas prescribing of aspirin decreased from 17.9% to 7.0% (P = 0.50) during the same period. Conclusion. We observed a continued increase in prescription of the aspirin-clopidogrel combination from 2000 to 2007. Clinical trial evidence suggests that the aspirin-clopidogrel combination does not provide any additional benefit compared with clopidogrel alone; however, our study findings indicate that even with lack of adequate clinical evidence physician prescribing of this combination has increased in real-world community settings.
Diversité taxonomique et fonctionnelle de la communauté bactérienne d'une lagune côtière aux Îles-de-la-Madeleine, Golfe du Saint-Laurent, Canada

v Table des matières . vii Liste des tableaux . xi Liste des figures . xiii Liste des abréviations et des sigles . xv Remerciements . xix Avant-propos . xxi 1 Chapitre
A Current-Steering DAC Architecture with Novel Switching Scheme for GPON Burst-Mode Laser Drivers

SUMMARY This paper describes a current-steering Digital-to-Analog Converter (IDAC) architecture with a novel switching scheme, designed for GPON Burst Mode Laser Drivers (BMLD) and realized in a 0.35 µ mS iGe BiCMOS technology with 3.3 V power supply. The (4+6) segmented architecture of the proposed 10-bit IDAC is optimized for minimum DNL (Differential Nonlinearity). It combines a 4-bit MSBs (Most Significant Bits) unit-element sub-DAC and a 6-bit LSBs (Least Significant Bits) binaryweighted sub-DAC. A switching scheme based on this dedicated architecture yields a high monotony and a fast settling time. The linearity errors caused by systematic influences and random variations are reduced by the 2-D double centroid symmetrical architecture. Experimental results show that the DNL is below ± 0.5 LSB and that the settling time after the output current mirror is below 12 ns. Although the proposed IDAC architecture was designed for a BMLD chip, the design concept is generic and can be applied for developing other monotonic high-speed current-mode DACs.
Cohort profile: the Leicester respiratory cohorts.

Institution and country of all co-authors (1) Swiss Paediatric Respiratory Research Group, Department of Social and Preventive Medicine, University of Berne, Switzerland (2) The Leicester Children's Asthma Centre, Division of Child Health, Department of Infection, Immunity & Inflammation, University of Leicester, Leicester, LE2 7LX, UK (3) Specialist Community Child Health Services, Leicester City PCT, Bridge Park Plaza, Thurmaston, Leicester, LE4 8PQ, UK
Nonlinear Control of Two-Link Planar Manipulator Using Unstable Property of Zerodynamics

In this paper, a control method for an underactuated two-link planar manipulator using a partial linearization method, which is a one of the nonlinear control method based on structure theory, is proposed. In proposed method, for controlling of 2nd link, sliding-mode type partial linearization method is used, and for 1st link, the unstable property of Zerodynamics(it is dynamics of 1st link) is used, respectively. By analyzing a relationship between behavior of Zerodynamics and desired value of 2nd link, we find the property of Zerodynamics is changing by desired value of 2nd link. Therefore, the control of both links is able to achieve by single control input by deciding the desired value of 2nd link based on behavior of Zerodynamics. Finally, numerical simulations are performed to show the effectiveness of the proposed method.
Long-Term Effects of Musical Training and Functional Plasticity in Salience System

Musicians undergoing long-term musical training show improved emotional and cognitive function, which suggests the presence of neuroplasticity. The structural and functional impacts of the human brain have been observed in musicians. In this study, we used data-driven functional connectivity analysis to map local and distant functional connectivity in resting-state functional magnetic resonance imaging data from 28 professional musicians and 28 nonmusicians. Compared with nonmusicians, musicians exhibited significantly greater local functional connectivity density in 10 regions, including the bilateral dorsal anterior cingulate cortex, anterior insula, and anterior temporoparietal junction. A distant functional connectivity analysis demonstrated that most of these regions were included in salience system, which is associated with high-level cognitive control and fundamental attentional process. Additionally, musicians had significantly greater functional integration in this system, especially for connections to the left insula. Increased functional connectivity between the left insula and right temporoparietal junction may be a response to long-term musical training. Our findings indicate that the improvement of salience network is involved in musical training. The salience system may represent a new avenue for exploration regarding the underlying foundations of enhanced higher-level cognitive processes in musicians.
Generalized Spatial Regression with Differential Penalization

We propose a novel method for the analysis of spatially distributed data from an exponential family distribution, able to efficiently treat data occurring over irregularly shaped domains. We consider a generalized linear framework and extend the work of Sangalli et al. (2013) to distributions other than the Gaussian. In particular, we can handle all distributions within the exponential family, including binomial, Poisson and Gamma outcomes , hence leading to a very broad applicability of the proposed model. We maximize a penalized log-likelihood function. The roughness penalty term involves a suitable differential operator of the spatial field over the domain of interest. This maximization is done via a penalized iterative least square approach (see Wood (2006)). Covariate information can also be included in the model in a semi-parametric setting. The proposed models exploit advanced scientific computing techniques and specifically make use of the Finite Element Method, that provides a basis for piecewise polynomial surfaces and allows to impose boundary conditions on the space distribution of the probability. Finally, we extend theoretically the model to deal with data occurring on a two dimensional manifold. 3 Thanks. I'm very grateful to Professor Victor Panaretos who gave me the chance to make a very interesting master thesis. I also would thank Dr. Kjell Konis who made me like computational statistics being my mentor with R. 1 1 in La Bible liturgique, Association episcopale liturgique des pays francophones (AELF), 1980
SimBac: simulation of whole bacterial genomes with homologous recombination

Bacteria can exchange genetic material, or acquire genes found in the environment. This process, generally known as bacterial recombination, can have a strong impact on the evolution and phenotype of bacteria, for example causing the spread of antibiotic resistance across clades and species, but can also disrupt phylogenetic and transmission inferences. With the increasing affordability of whole genome sequencing, the need has emerged for an efficient simulator of bacterial evolution to test and compare methods for phylogenetic and population genetic inference, and for simulation-based estimation. We present SimBac, a whole-genome bacterial evolution simulator that is roughly two orders of magnitude faster than previous software and includes a more general model of bacterial evolution, allowing both within- and between-species homologous recombination. Since methods modelling bacterial recombination generally focus on only one of these two modes of recombination, the possibility to simulate both allows for a general and fair benchmarking. SimBac is available from https://github.com/tbrown91/SimBac and is distributed as open source under the terms of the GNU General Public Licence.
Augmenting reality with geo-referenced information for environmental management

When interacting with natural or urban environments there are many situations where the ability to access data in real time becomes relevant. Augmented Reality (AR) technologies allow real time superimposition of synthetic objects on real images, providing an augmented knowledge about the surrounding world. Using a Head Mounted Display, the user of an AR system can visualize the exterior world with additional virtual information that is generated in real time and in a contextual way.This paper presents ANTS (Augmented Environments), an AR project for providing geo-referenced environmental information. The project uses a flexible client-server approach that allows to move more or less components to the client, depending on processing power and application requirements. The geo-referenced database and 3D model for user positioning are located in the server and the presentation component, for image composition and display, is the most fundamental part of the client. The applications for environmental management, include monitoring water quality using models of the pollutant transport, the visualization of the temporal evolution of physical structures and the evolution of subsoil structures, such as phone and power supply networks.
A Communication Network Preserves the Privacy of the user using Unique IDs

An algorithm for anonymous sharing of private data among parties is developed. This technique is used to assign these n ID numbers ranging from 1 to N.The popularity of internet as a communication medium whether for personal or business use depends in part on its support for anonymous communication. Businesses engage in anonymous communication and avoid the consequences of identity revelation. Existing and new algorithms for assigning anonymous IDs are examined with respect to tradeoffs between communication and computational requirements. Keywords— Privacy Preservation, File Sharing, data sharing, key-aggregate encryption,Secure sum.
Numerical analysis for steady boundary layer flow of Maxwell fluid over a stretching surface embedded in a porous medium with viscous dissipation using the spectral relaxation method

In the current paper, a theoretical analysis is laid out to explore the features of flow, heat and mass transfer characteristics of Maxwell fluid over a stretching sheet, which can be embedded in a porous medium with viscous dissipation. To get the numerical solution a powerful numerical technique, spectral relaxation method, is applied for the set of transformed equations derived from the physical model of the flow. Thereafter, numerical outcomes are computed to discuss the convergence and accuracy of the proposed technique. The impacts of different flow controlling parameters, which are experienced in the problem, are resolved. All the obtained outcomes from the above numerical procedure are displayed through graphs and tables to discuss various resulting parameters. The main notable observations are an increment in surface shear stress and decrement in heat and mass transfer rates for the increase in the strength of the porous medium.
Precision radial velocities of 15 M5-M9 dwarfs

J. R. Barnes, 'Precision radial velocities of 15 M5-M9 dwarfs', Monthly Notices of the Royal Astronomical Society, Vol. 439 (3): 3094 - 3113, first published online 20 February 2014. The version of record is available online at doi: 10.1093/mnras/stu172 © 2014 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society.
Constrained Nonnegative Tensor Factorization for Clustering

Constrained clustering through matrix factorization has been shown to largely improve clustering accuracy by incorporating prior knowledge into the factorization process. Although it has been well studied, none of them deal with constrained multi-way data factorization. Multi-way data or Tensors are encoded as high-order data structures. They can be seen as the generalization of matrices. One typical tensor is multiple two-way data/matrices in different time periods. To the best of our knowledge, this paper is the first work developing two general formulation of constrained nonnegative tensor factorization. An extensive experiment conducts a comparative study on the proposed constrained nonnegative tensor factorization and other state-of-the-art algorithms.
The stability modeling of ripple-based constant on-time control schemes used in the converters operating in DCM

Ripple-based constant on-time (RBCOT) control schemes have recently received much attention for the DC converters used in many applications mainly due to its high efficiency feature under light-load condition. There are control models reported for such schemes for the continuous conduction mode (CCM) operation but not for the discontinuous mode (DCM). Since the converter is usually operated in DCM under light-load condition, an effort to investigate the RBCOT schemes under DCM is practically important. Two RBCOT schemes are considered in this paper, the basic RBCOT and the RBCOT with virtual inductor current (VIC). A describing function approach and a time-domain approach are used for the investigation of the feedback stability issue of the control schemes in DCM. It is proved that it is always stable for the basic RBCOT converter operating in DCM, but that is not the case for the VICRBCOT converters. Proper VIC signal must be used to maintain stability for both the CCM and the DCM operation. The analysis results are verified with experiments.
Design of a circuit to provide scanning power supply to a sensor array to reduce the number of wires for data acquisition

This research aims at the design of a circuit to provide power supply to every element in a sensor array in a scanning style for the data acquisition with very few wires. It is useful in data acquisition when there is a need of large amount of wires, but without enough space to hold these wires. It will make a sensing system practical by considerably reducing the number of the wires, especially for the application to a tubular-shape force sensor array on a long tubular device such as a colonoscope due to very limited available space for running too many wires. In the application of the designed circuit to a sensor array of 16 columns and 445 rows in a colonoscope, it has been achieved that only 19 wires were used for the data acquisition for all the 7120 sensing elements. Without this circuit, at least 461 wires are needed as explained in the paper. In this paper, the design of the circuit was explained first. Then the outputs of the circuit were simulated using a software package and experimentally verified using PCB boards. Two of the PCB boards has been built and tested on a sensor array with graphical display of the applied force. One of the final goals of this project is to be used in a skin sensor array for colonoscope to avoid bowel perforation which is a life threatening complication during a colonoscopy.
Truth or Tale? How Construal Level and Judgment Mode Affect Confidence and Accuracy in Deception Detection

Abstract Previous research has indicated that individuals typically perform quite poorly in discerning truths from lies, and that confidence in judged veracity is not predictive of objective accuracy. In this experiment, we investigated the joint influence of construal level and judgment mode on detection accuracy and confidence. Participants (N = 161) watched eight videotaped true and false statements while adopting a high or low level of construal, and received instructions to detect the deceptiveness of the statements either before (online judgments) or after (offline judgments) watching the videos. Contrary to our predictions, construal level and judgment mode did not influence detection accuracy independently or interactively. However, low level participants were less confident when making judgments offline as opposed to online, whereas the confidence of high level participants was unaffected by judgment mode. Implications for deception detection research and practice are discussed.
Just How Easy is it to Cheat a Linear Regression ?

As of late, the validity of much academic research has come into question. While many studies have been retracted for outright falsification of data, perhaps more common is inappropriate statistical methodology. In particular, this paper focuses on data dredging in the case of balanced design with two groups and classical linear regression. While it is well-known data dredging has pernicious e↵ects, few have attempted to quantify these e↵ects, and little is known about both the number of covariates needed to induce statistical significance and data dredging’s e↵ect on statistical power and e↵ect size. I have explored its e↵ect mathematically and through computer simulation. First, I prove that in the extreme case that the researcher can obtain any desired result by collecting nonsense data if there is no limit on how much data he or she collects. In practice, there are limits, so secondly, by computer simulation, I demonstrate that with a modest amount of e↵ort a researcher can find a small number of covariates to achieve statistical significance both when the treatment and response are independent as well as when they are weakly correlated. Moreover, I show that such practices lead not only to Type I errors but also result in an exaggerated e↵ect size. These findings emphasize the importance of reproducibility and following best practice statistics.
The Linkages between Mindfulness and Social Information Processing Theory on the Usage of Whatsapp Media Groups

The objective of the research was to find the linkages between mindfulness and social information processing theory on the use of WhatsApp group of Elementary school Principals in District Cilandak Region III for the distribution of various information and instructions. Through the concept of mindfulness and Social Information Processing theory approach (SIP), this research would explore the causes of the frequent emergence of noise, misunderstanding, and even tangency to the WA group that was carried on the meeting of headmaster meetings and relationships between members. The research problem was why WA group still causing issues among the Principals. By using the qualitative approach, data collection techniques used in this research were the interview, observation, and literature study. It is found that technological sophistication does not go parallel with maturity in communicating using media technologies. Lack of mindfulness in the WA group is a form of organizational communication that is simply transferred into the form of text communication on mobile phones that is being the main cause. Also, the organizational structure is still inherent in it and only serves as a bridge/form of interim communication because the main form of communication is still in the form of correspondence and face-to-face meetings.
Awakened Hatred and Heightened Fears: “The Trump Effect” on the Lives of Mixed-Status Families

The rise of the Trump regime has sparked xenophobic sentiments directed toward and heightened fears experienced by mixed-status immigrant families living in the United States. Using the Southern Poverty Law Center’s concept of “The Trump Effect”—how the election of Donald Trump has had a damaging impact on undocumented immigrants—the researchers reveal how the lives of 12 mixed-status families (16 youth and 16 of their parents/guardians) have been transformed. Implications of this investigation are significant given the current social and political landscapes and continual fear mixed-status families undergo in their plight for daily survival.
Automatic medical image segmentation based on finite skew gaussian mixture model

A novel methodology for segmenting the brain Magnetic Resonance Imaging (MRI) images using the finite skew Gaussian mixture model has been proposed for improving the effectiveness of the segmentation process. This model includes Gaussian mixture model as a limiting case and we believe does more effective segmentation of both symmetric and asymmetric nature of brain tissues as compared to the existing models. The segmentation is carried out by identifying the initial parameters and utilizing the Expectation-Maximization (EM) algorithm for fine tuning the parameters. For effective segmentation, hierarchical clustering technique is utilized. The proposed model has been evaluated on the brain images extracted from the brain web image database using 8sub-images of 2 brain images. The segmentation evaluation is carried out using objective evaluation criterion viz. Jacquard Coefficient (JC) and Volumetric Similarity (VS). The performance evaluation of reconstructed images is carried out using image quality metrics. The experimentation is carried out using T1 weighted images and the results are presented. We infer from the results that the proposed model achieves good segmentation results when used in brain image processing.
Contextual Richness and Word Learning: Context Enhances Comprehension but Retrieval Enhances Retention.

Learning new vocabulary from context typically requires multiple encounters during which word meaning can be retrieved from memory or inferred from context. We compared the effect of memory retrieval and context inferences on short- and long-term retention in three experiments. Participants studied novel words and then practiced the words either in an uninformative context that required the retrieval of word meaning from memory ("I need the funguo") or in an informative context from which word meaning could be inferred ("I want to unlock the door: I need the funguo"). The informative context facilitated word comprehension during practice. However, later recall of word form and meaning and word recognition in a new context were better after successful retrieval practice and retrieval practice with feedback than after context-inference practice. These findings suggest benefits of retrieval during contextualized vocabulary learning whereby the uninformative context enhanced word retention by triggering memory retrieval.
Analysis of the residue variation of the circadian clock protein KaiA

Regulation of daily physiological functions with approximate a 24-hour periodicity, or circadian rhythms, is a characteristic of eukaryotes. So far, cyanobacteria are only known prokaryotes reported to possess circadian rhythmicity. The circadian system in cyanobacteria comprises both a post-translational oscillator (PTO) and a transcriptional/translational feedback loop (TTFL). The PTO can be reconstituted in vitro with three purified proteins (KaiA, KaiB, and KaiC) with the existence of ATP. Phase of the nanoclockwork has been associated with the phosphorylation states of KaiC, with KaiA promoting the phosphorylation of KaiC, and KaiB dephosphorylating KaiC. Here we studied the sequence variation of 65 KaiA proteins in evolution, and determined some key residues in KaiA by analyzing the site variation rates of the protein sequences. These key residues could be used to study the key interactions of KaiA with KaiB and KaiC.