Miracle-dz/UniFAR-FTUs huggingface dataset:
DERIVATION OF EQUIVALENT KERNEL FOR GENERALSPLINE SMOOTHING : A SYSTEMATIC APPROACHFelix Abramovich

We consider rst the spline smoothing nonparametric estimation with variable smoothing parameter and arbitrary design density function and show that the corresponding equivalent kernel can be approximated by the Green's function of a certain linear diierential operator. Furthermore, we propose to use the standard (in applied mathematics and engineering) method for asymptotic solution of linear diierential equations, known as the WKB-method, for systematic derivation of asymptotically equivalent kernel in this general case. The corresponding results for polynomial splines are a special case of the general solution. Then, we show how these ideas can be directly extended to the very general L-spline smoothing.
BURC : Bootstrapping Using ResearchCyc

The goal of this research is to expand the knowledge in a large ontology called ResearchCyc by using existing knowledge in that ontology to extract knowledge for later use in that same system. In this way the system can be said to bootstrap, expanding its own knowledge through reading text, hopefully in a manner that will improve future knowledge acquisition. The system processes large quantities of texts using the CMU Link Grammar Parser, and using the individual links coupled with ResearchCyc, existing knowledge can generate new assertions about relationships implied to be possible, normal or commonplace in the world. This is possible by aggregating information from a large number of parse links over a large corpus
Node Localization Method for Wireless Sensor Networks Based on HybridOptimization of Differential Evolution and Particle Swarm Algorithm

Regarding the node localization problems for wireless sensor network, a hybrid optimization method was pro- posed accordingly on differential evolution(DE) algorithm and particle swarm optimization(PSO) algorithm. Firstly, the position and velocity of the initial population were randomly generated by PSO, and the fitness function was constructed according to the mean square error of estimated and measured distance between the unknown nodes and their adjacent an- chor node. Secondly, the mutation and selection operation of DE algorithm were executed to find out the optimum posi- tion of the population. Lastly, the current velocities and positions of all particles of the population were updated, and the crossover operation and selection operation of DE algorithm were executed to update the current global optimum position of the whole population. Population global optimum solution of iterative search algorithm is the position coordinate of the unknown node. Simulation results indicate that the proposed localization method has smaller average localization error and higher localization accuracy than that of DE algorithm and PSO algorithm in the same environment.
Field-based scattering-matrix extraction scheme for the FVTD method exploiting a flux-splitting algorithm

This paper introduces a novel field-based scheme for the extraction of a generalized-scattering matrix. A flux-splitting (FS) algorithm that separates the total electromagnetic field into an incident and a reflected part is used for a new definition of power waves. This flux-separation scheme, based on a plane-wave approach of the split waves, originates from finite-volume techniques. However, it can be applied locally in any numerical scheme that uses a volume discretization. To yield correct S-parameters, the FS matrix needs to be adapted through introduction of modified wave velocities to match the plane-wave condition. The introduced extraction scheme is applied to the finite-volume time-domain method and compared successfully to reference solutions for TEM and non-TEM structures, both with homogeneous and inhomogeneous cross sections.
HLA Antibody Specification Using Single-Antigen Beads—A Technical Solution for the Prozone Effect

Background. Substantial progress in human leukocyte antigen antibody specification has been made by the introduction of Luminex single-antigen bead (SAB) assays. This progress was impaired when it turned out that this method is prone to a prozone effect leading to false-negative results in the case of high antibody titers. Testing serum and ethylenediaminetetraacetic acid (EDTA) plasma of one patient in parallel, we observed the prozone effect with the serum sample only. This led us to investigate complement component 1 (C1) as the cause of the prozone in SAB testing. We also found an easy way to overcome the prozone effect. Methods. Sera with a prozone effect were tested in the SAB assay, applying different methods of serum pretreatment to explore the parameters leading to the prozone. Results. The prozone was not observed when EDTA plasma or serum with EDTA added were tested. Further, addition of dithiothreitol, addition of C1 inhibitor, or heat inactivation of the sera abolished the prozone effect. Adding fresh nonimmune serum to heat-inactivated sera restored the prozone effect. Only beads showing a prozone were found to be covered with C1q. Conclusion. Our observations are consistent with the hypothesis that dissociation or destruction of complement C1 eliminates the prozone effect. Addition of EDTA to serum of highly immunized patients is the easiest way to avoid false-negative results in SAB testing caused by a prozone effect.
Fast Moving Sampling Designs in Temporal Networks

In a study related to this one I set up a temporal network simulation environment for evaluating network intervention strategies. A network intervention strategy consists of a sampling design to select nodes in the network. An intervention is applied to nodes in the sample for the purpose of changing the wider network in some desired way. The network intervention strategies can represent natural agents such as viruses that spread in the network, programs to prevent or reduce the virus spread, and the agency of individual nodes, such as people, in forming and dissolving the links that create, maintain or change the network. The present paper examines idealized versions of the sampling designs used to that study. The purpose is to better understand the natural and human network designs in real situations and to provide a simple inference of design-based properties that in turn measure properties of the time-changing network. The designs use link tracing and sometimes other probabilistic procedures to add units to the sample and have an ongoing attrition process by which units are removed from the sample.
The impact of collaborative work climate on knowledge sharing intention

The current study investigated the relationship between collaborative work climate and intention to share knowledge in Fars Regional Power Distribution Company (FRPDC), Iran. Using stratified random sampling method, a sample of 214 employees were selected for further analysis. The analysis of the data showed that the relationship between the perception of collaborative work climate and intention to share knowledge is significant and positive. The results also indicated that there are significant relationships between dimensions of collaborative work climate (work group support, immediate supervisor support, business unit culture and employees attitude) and intention to share knowledge. The values of R2 also indicated that workgroup support, business unit culture, immediate supervisor and employees’ attitudes have moderate, moderate to high, low and moderate impact on intention to share knowledge respectively. Key words: Collaborative work climate, knowledge, knowledge sharing, climate.
Characterization of Toll-like receptors in the female reproductive tract in humans.

BACKGROUND Rapid innate immune defences against infection involve the recognition of invading pathogens by specific pattern recognition receptors recently attributed to the family of Toll-like receptors (TLR). Little is known about the in vivo protein expression or distribution of TLR in the female reproductive tract in humans. It is likely that TLR distribution in the female reproductive tract reflects the immunological tolerance to the commensal organisms in lower parts of the tract (vagina, ectocervix and, partially, endocervix) and the intolerance to commensal microbial flora in the upper tract (the uterus and uterine tubes). METHODS Using immunohistochemistry techniques, distribution of TLR1-6 was studied in surgical sections from the vagina, ecto- and endocervix, endometrium and uterine tubes, obtained from patients undergoing abdominal hysterectomy for benign gynaecological conditions. RESULTS TLR1, 2, 3, 5 and 6 were present in the epithelia of different regions of female reproductive tract. However, TLR4 was only present in the endocervix, endometrium and uterine tubes and absent in vagina and ectocervix. In addition, a secretory form of TLR4 seems to be produced by the endocervical glands. CONCLUSION TLR4 may play an important role in modulation of immunological tolerance in the lower parts of the female reproductive tract, and in host defence against ascending infection.
Beyond induction variables

Induction variable detection is usually closely tied to the strength reduction optimization. This paper studies induction variable analysis from a different perspective, that of finding induction variables for data dependence analysis. While classical induction variable analysis techniques have been used successfully up to now, we have found a simple algorithm based on the Static Single Assignment form of a program that finds all linear induction variables in a loop. Moreover, this algorithm is easily extended to find induction variables in multiple nested loops, to find nonlinear induction variables, and to classify other integer scalar assignments in loops, such as monotonic, periodic and wrap-around variables. Some of these other variables are now classified using ad hoc pattern recognition, while others are not analyzed by current compilers. Giving a unified approach improves the speed of compilers and allows a more general classification scheme. We also show how to use these variables in data dependence testing.
The Use of Family History in Primary Health Care: A Qualitative Study

The aim of this study is to describe how Belgian family physicians register and use the family history data of their patients in daily practice. Qualitative in-depth semistructured one-to-one interviews were conducted including 16 family physicians in Belgium. These interviews were recorded, transcribed, and analysed. Recurring themes were identified and compared with findings from the existing literature. All interviewed family physicians considered the family history as an important part of the medical records. Half of the surveyed physicians confirmed knowing the family history of at least 50% of their patients. The data on family history were mainly collected during the first consultations with the patient. The majority of physicians did not use a standardised questionnaire or form to collect and to record the family history. To estimate the impact of a family history, physicians seldom use official guidance or resources. Physicians perceived a lack of time and unreliable information provided by their patients as obstacles to collect and interpret the family history. Solutions that foster the use of family history data were identified at the level of the physician and also included the development of specific instruments integrated within the electronic medical record.
Specification for the : WISHBONE System-On-Chip ( SoC ) Interconnection Architecture for Portable IP Cores

This document shows changes to the WISHBONE specification that are recommended or under review by the Steward. The purpose of this document is to convey all known issues that need to be addressed during the next revision of the specification. This is a working document that is subject to change without notice. All changes shown herein are NOT APPROVED, and are presented for informational purposes only.
nRobotic: A platform for managing robots with different capabilities

In this paper we propose a platform for interconnecting robots that are different in terms of capabilities, hardware, and software. We define a software representation for a robot and for a mission and we discuss possible implementations for three types of robots. The platform exposes a service through which other applications can control different types of robots through a unified interface.
A Study of Redundant Metrics in Defect Prediction Datasets

Defect prediction models can help Software Quality Assurance (SQA) teams understand their past pitfalls that lead to defective modules. However, the conclusions that are derived from defect prediction models without mitigating redundant metrics issues may be misleading. In this paper, we set out to investigate if redundant metrics issues are affecting defect prediction studies, and its degree and causes of redundancy. Through a case study of 101 publicly-available defect datasets of systems that span both proprietary and open source domains, we observe that (1) 10%-67% of metrics of the studied defect datasets are redundant, and (2) the redundancy of metrics has to do with the aggregation functions of metrics. These findings suggest that researchers should be aware of redundant metrics prior to constructing a defect prediction model in order to maximize internal validity of their studies.
Semantic-level fusion of heterogenous sensor network and other sources based on Bayesian network

Information fusion systems that involve the use of heterogeneous sensor networks often face the problems of loss of data and uncertainty in data caused by vulnerability of networks where sensor nodes may be attacked or break down, limited bandwidth which may cause network congestion, and urban environments which may affect the sensor measurements. In this paper, we propose to address the above mentioned problem by employing information from other sources (e.g., textual situation reports, open-source web information, news reports and social media etc.) to augment estimation from physical sensors (e.g., video, acoustic, seismic, radar and multispectral data). A semantic-level information fusion (SELF) framework is developed based on Bayesian network, which is capable of (i) integrating information of different types (hard and soft data); (ii) incorporating contextual information and prior knowledge into the process; and (iii) dealing with loss of data and uncertainties inherent in all data sources. An adversarial event detection problem is used as an example to illustrate the effectiveness of the proposed system.
Changes in frequency of premature complexes and heart rate variability related to shift work

OBJECTIVES To investigate whether an increased risk of cardiovascular disease might be caused by increased arrhythmogeneity and by unfavourable changes in autonomic cardiac control the changes in the occurrence of premature complexes (PVCs) and in heart rate variability (HRV) were studied in subjects who started to work in shifts. METHODS 1 Year changes in frequency of PVCs and HRV were measured in 49 shift workers and 22 control subjects working in daytime. All respondents were starting in a new job in integrated circuit or waste incinerator plants. RESULTS The incidence of PVC increased significantly in shift workers over the 1 year follow up, compared with daytime workers. The frequency of ventricular extrasystoles increased in 48.9% of the shift workers, and in 27.3% of the daytime workers. The Spearman correlation coefficient between the number of nights worked and the change in PVCs was 0.33 (p=0.004). A small non-significant unfavourable change in HRV was found in both the shift and daytime workers. CONCLUSIONS A change in arrhythmogeneity, but not in cardiac autonomic control, might explain the increased risk of cardiovascular disease in shift workers.
Place of residence affects routine dental care in the intellectually and developmentally disabled adult population on Medicaid.

OBJECTIVE To compare the likelihood of intellectually and developmentally disabled (ID/DD) adults receiving a dental cleaning across places of residence. DATA SOURCES Medicaid and Minnesota's Medicaid Management Information System (MMIS) databases. STUDY DESIGN All adults with DD assessments in MMIS in 2001-2002. DATA EXTRACTION METHODS All completed DD assessments in 2001-2002 linked to Medicaid utilization data for same recipients for same years. CONCLUSIONS The most disabled individuals are generally least likely to receive a dental cleaning. Individuals living in their own or a family home are less likely to receive the procedure than those living in ICF/MRs or a group home, even after controlling for disability, with those living in a group home falling in between ICF/MR and own/family home residents. The level of preventive dental care that ID/DD adults receive in community settings may be inadequate, particularly for persons living in own homes or with family.
Rough set based system for effective E-learning

To achieve intelligence over the web is underlying research topic and continuous efforts have been made in this direction. The results of these efforts in its practical form of applications have been achieved using modern tools & techniques. Artificial Intelligence (AI) has evolved as one of the promising technology for achieving intelligence over web. To facilitate quality education, the identification & selection of various factors that may influence a students' academic performance is very important. Knowing these factors is important for parents & teachers working positively on these factors may improve the performance of the student. In this paper we propose an approach of decision rule induction to induce knowledge that can facilitate the proper decision making process. The approach for rule induction process is based on AI based rough set theory. The proposed system may be seen as a helping hand to creators of contents, educators and teachers of the course.
Chronic Treatment of Methimazole Alters Expression of Serotonin Receptors in Raphe Nuclei and Limbic System

Thyroid hormones play an essential and critical role for metabolism, growth, and tissue differentiation in chordate. Thyroid dysfunction such as hypothyroidism is a frequent disease in adults, leading to neurological symptoms and emotional disease including depression. The interaction between thyroid hormones and serotonin of central nervous system may account for it. The present study was aimed to determine the expression level of serotonin receptors including 5HT_(1A), 5HT_(2A), 5HT_(2C), 5HT_(3A), and serotonin transporter (SERT) in hippocampus, amygdala, raphe nuclei, and medial prefrontal cortex in the rat after chronic treatment of methimazole (MMI) by using real time PCR. Results showed the mRNA level of 5-HT_(1A) was increased in raphe nuclei and hippocampus of the MMI-treated animals. The mRNA of 5-HT_(2A) receptor was elevated in raphe nuclei, and the mRNA of 5-HT_(2C) receptor and SERT were increased in hippocampus. In conclusion, we found that chronic administration of MMI changes expression of serotonin receptors in the raphe nuclei and limbic system, and could be the reason due to depression.
Chromosomal Rearrangements in Post-Chernobyl Papillary Thyroid Carcinomas: Evaluation by Spectral Karyotyping and Automated Interphase FISH

Structural genomic rearrangements are frequent findings in human cancers. Therefore, papillary thyroid carcinomas (PTCs) were investigated for chromosomal aberrations and rearrangements of the RET proto-oncogene. For this purpose, primary cultures from 23 PTC have been established and metaphase preparations were analysed by spectral karyotyping (SKY). In addition, interphase cell preparations of the same cases were investigated by fluorescence in situ hybridisation (FISH) for the presence of RET/PTC rearrangements using RET-specific DNA probes. SKY analysis of PTC revealed structural aberrations of chromosome 11 and several numerical aberrations with frequent loss of chromosomes 20, 21, and 22. FISH analysis for RET/PTC rearrangements showed prevalence of this rearrangement in 72% (16 out of 22) of cases. However, only subpopulations of tumour cells exhibited this rearrangement indicating genetic heterogeneity. The comparison of visual and automated scoring of FISH signals revealed concordant results in 19 out of 22 cases (87%) indicating reliable scoring results using the optimised scoring parameter for RET/PTC with the automated Metafer4 system. It can be concluded from this study that genomic rearrangements are frequent in PTC and therefore important events in thyroid carcinogenesis.
Malleability of Students' Perceptions of an Affect-Sensitive Tutor and Its Influence on Learning

We evaluated an affect-sensitive version of AutoTutor, a dialogue based ITS that simulates human tutors. While the original AutoTutor is sensitive to students’ cognitive states, the affect-sensitive tutor (Supportive tutor) also responds to students’ affective states (boredom, confusion, and frustration) with empathetic, encouraging, and motivational dialogue moves that are accompanied by appropriate emotional expressions. We conducted an experiment that compared the Supportive and Regular (non-affective) tutors over two 30-minute learning sessions with respect to perceived effectiveness, fidelity of cognitive and emotional feedback, engagement, and enjoyment. The results indicated that, irrespective of tutor, students’ ratings of engagement, enjoyment, and perceived learning decreased across sessions, but these ratings were not correlated with actual learning gains. In contrast, students’ perceptions of how closely the computer tutors resembled human tutors increased across learning sessions, was related to the quality of tutor feedback, the increase was greater for the Supportive tutor, and was a powerful predictor of learning. Implications of our findings for the design of affect-sensitive ITSs are discussed.
Fast Imaging Technique for fMRI: Consecutive Multishot Echo Planar Imaging Accelerated with GRAPPA Technique

This study was to evaluate the proposed consecutive multishot echo planar imaging (cmsEPI) combined with a parallel imaging technique in terms of signal-to-noise ratio (SNR) and acceleration for a functional imaging study. We developed cmsEPI sequence using both consecutively acquired multishot EPI segments and variable flip angles to minimize the delay between segments and to maximize the SNR, respectively. We also combined cmsEPI with the generalized autocalibrating partially parallel acquisitions (GRAPPA) method. Temporal SNRs were measured at different acceleration factors and number of segments for functional sensitivity evaluation. We also examined the geometric distortions, which inherently occurred in EPI sequence. The practical acceleration factors, R = 2 or R = 3, of the proposed technique improved the temporal SNR by maximally 18% in phantom test and by averagely 8.2% in in vivo experiment, compared to cmsEPI without parallel imaging. The data collection time was decreased in inverse proportion to the acceleration factor as well. The improved temporal SNR resulted in better statistical power when evaluated on the functional response of the brain. In this study, we demonstrated that the combination of cmsEPI with the parallel imaging technique could provide the improved functional sensitivity for functional imaging study, compensating for the lower SNR by cmsEPI.