Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing data collection for structure determination

# 2003 International Union of Crystallography Printed in Denmark ± all rights reserved The ultimate purpose of diffraction data collection is to produce a data set which will result in the required structural information about the molecule of interest. This usually entails collecting a complete and accurate set of re ̄ection intensities to as high a resolution as possible. In practice, the characteristics of the crystal and properties of the X-ray source can be limiting factors to the data-set quality that can be achieved and a careful strategy has to be used to extract the maximum amount of information from the data within the experimental constraints. In the particular case of data intended for phasing using anomalous dispersion, the synchrotron beamline properties are relevant to determine how many wavelengths (one or more) should be used for the experiment and what the wavelength values should be. This will in turn affect the detailed strategy for data collection, including decisions about the data-collection sequence and how much data to collect at each wavelength. Collection of multiwavelength anomalous dispersion (MAD) data at three different wavelengths can provide very accurate experimental phases. Two-wavelength MAD experiments may offer the best compromise between phase quality and minimizing the effects of radiation damage to the sample. However, MAD experiments are demanding in terms of beamline wavelength range, easy tunability, stability and reproducibility. When the beamline cannot ful®ll these demands, single-wavelength experiments may be a better option. Received 14 January 2003 Accepted 8 August 2003
Learning from Click Model and Latent Factor Model for Relevance Prediction Challenge

How to accurately interpret user click behaviour in search log is a key but challenging problem for search relevance. In this paper, we describe our solution to the relevance prediction challenge which achieves the first place among eligible teams. There are three stages in our solution: feature generation, feature augmentation and learning a ranking function. In the first stage, we extract features in relation to querydocument pairs as well as individual queries and documents from the click log data. In the second stage, we induce additional features by click model techniques and learning latent factor models to correct different biases and discover the correlations between different queries or documents respectively. In the final stage, we apply supervised learning models on the limited labelled data to induce a model for predicting relevance based on the features generated in the previous two stages.
Naringin ameliorates acetic acid induced colitis through modulation of endogenous oxido-nitrosative balance and DNA damage in rats

The aim of this study was to evaluate the effect of naringin on experimentally induced inflammatory bowel disease in rats. Naringin (20, 40 and 80 mg/kg) was given orally for 7 days to Wistar rats before induction of colitis by intrarectal instillation of 2 mL of 4% (v/v) acetic acid solution. The degree of colonic mucosal damage was analyzed by examining mucosal damage, ulcer area, ulcer index and stool consistency. Intrarectal administration of 4% acetic acid resulted in significant modulation of serum alkaline phosphatase, lactate dehydrogenase, superoxide dismutase (SOD), glutathione (GSH), malondialdehyde (MDA) and myeloperoxidase (MPO) content along with colonic nitric oxide (NO), xanthine oxidase (XO) level and protein carbonyl content in the colonic tissue as well as in blood. Naringin (40 and 80 mg/kg) exerted a dose dependent (P < 0.05) ameliorative effect, as it significantly increased hematological parameter as well as colonic SOD and GSH. There was a significant (P < 0.05) and dose dependant inhibition of macroscopical score, ulcer area along with colonic MDA, MPO activity by the 7 days of pretreatment of naringin (40 and 80 mg/kg). Biochemical studies revealed a significant (P < 0.05) dose dependant inhibition in serum alkaline phosphatase (ALP) and lactate dehydrogenase (LDH) levels by pretreatment of naringin. Increased levels of colonic NO, XO, protein carbonyl content and DNA damage were also significantly decreased by naringin pretreatment. The findings of the present investigation propose that naringin has an anti-inflammatory, anti-oxidant and anti-apoptotic potential effect at colorectal sites as it modulates the production and expression of oxidative mediators such as MDA, MPO, NO and XO, thus reducing DNA damage.
A distributed, self-adaptive model of hypermedia system

We discuss a distributed user model architecture suitable for hypermedia systems. In this architecture, the user knowledge is spread over a collection of autonomous actors, cooperating in a way which provides, through collaborative activities, a global, dynamic user model. Separate duties and knowledge, combined with asynchronous and concurrent processing, augment the adaptivity and the efficiency of the platform, avoiding the drawbacks of more traditional centralized approaches. Our goal was to enrich an existing hypermedia architecture with an appropriate user model activity, conceived and realized with the same design perspective of the underlying system, the actor-level design approach. The organizational structure has been defined by extending a previous hypermedia system model without redesigning the overall architecture. The prototype has been tested with success as an adaptive hypermedia interface in a logic object-oriented programming environment.
Early Events in the Pathogenesis of Foot-and-Mouth Disease in Pigs; Identification of Oropharyngeal Tonsils as Sites of Primary and Sustained Viral Replication

A time-course study was performed to elucidate the early events of foot-and-mouth disease virus (FMDV) infection in pigs subsequent to simulated natural, intra-oropharyngeal, inoculation. The earliest detectable event was primary infection in the lingual and paraepiglottic tonsils at 6 hours post inoculation (hpi) characterized by regional localization of viral RNA, viral antigen, and infectious virus. At this time FMDV antigen was localized in cytokeratin-positive epithelial cells and CD172a-expressing leukocytes of the crypt epithelium of the paraepiglottic tonsils. De novo replication of FMDV was first detected in oropharyngeal swab samples at 12 hpi and viremia occurred at 18–24 hpi, approximately 24 hours prior to the appearance of vesicular lesions. From 12 through 78 hpi, microscopic detection of FMDV was consistently localized to cytokeratin-positive cells within morphologically characteristic segments of oropharyngeal tonsil crypt epithelium. During this period, leukocyte populations expressing CD172a, SLA-DQ class II and/or CD8 were found in close proximity to infected epithelial cells, but with little or no co-localization with viral proteins. Similarly, M-cells expressing cytokeratin-18 did not co-localize with FMDV proteins. Intra-epithelial micro-vesicles composed of acantholytic epithelial cells expressing large amounts of structural and non-structural FMDV proteins were present within crypts of the tonsil of the soft palate during peak clinical infection. These findings inculpate the paraepiglottic tonsils as the primary site of FMDV infection in pigs exposed via the gastrointestinal tract. Furthermore, the continuing replication of FMDV in the oropharyngeal tonsils during viremia and peak clinical infection with no concurrent amplification of virus occurring in the lower respiratory tract indicates that these sites are the major source of shedding of FMDV from pigs.
Motion control of a spherical mobile robot by feedback linearization

BYQ-III is a spherical mobile robot. This paper deals with the problem of its simple motion control in a fixed motion mode. The robot BYQ-III is designed to be partially self-contained. A simplified dynamic model of the rotation motion in the median sagital plane is derived under some assumptions. A full-state linear feedback controller for the dynamic model and a PI controller are designed to implement the motion control in the median coronal plane and the sagital plane respectively. The model and the controllers were validated through a set of experiments. Experimental trajectories for a circle of the robot on the plane were found to agree to a reasonable accuracy. The overall design, actuator mechanism, control system, and initial results are presented in this paper.
Mortality in Adult Offspring of Immigrants: A Swedish National Cohort Study

Background Higher risks of psychiatric disorders and lower-than-average subjective health in adulthood have been demonstrated in offspring of immigrants in Sweden compared with offspring of native Swedes, and linked to relative socioeconomic disadvantage. The present study investigated mortality rates in relation to this inequity from a gender perspective. Methods We used data from national registers covering the entire Swedish population aged 18-65 years. Offspring of foreign-born parents who were either Swedish born or had received residency in Sweden before school age (<7 years) were defined as “offspring of immigrants. ” We used Cox regression models to examine the association between parental country of birth and mortality between 1990 and 2008, with adjustment for education, income, age and family type. Results Male offspring of immigrants from the Middle East (HR:2.00, CI:1.66-2.26), other non-European countries (HR:1.80, CI:1.36-2.36) and Finland (HR:1.56, CI:1.48-1.65) showed an age-adjusted excess mortality risk from all causes of death when compared to offspring with Swedish-born parents. Income, but not education, greatly attenuated these increased mortality risks. No excess mortality rates were found among female offspring of immigrants, with the exception of external cause of death among offspring of Finnish immigrants. Conclusion The study demonstrates high mortality rates in male offspring of immigrants from Finland and non-European countries that are associated with economic, but not educational, disadvantage. No increased mortality rates were found among female offspring of immigrants. Future studies are needed to explain this gender differential and why income, but not education, predicts mortality in male offspring of immigrants.
FPGA-based Real-Time Object Tracking Using a Particle Filter with Stream Architecture

This paper deals with the real-time FPGA implementation of the posterior system state estimation in dynamic state-space models using a particle filter. The system is constructed by parallel resampling (FO-resampling) algorithm on a stream-based architecture. In particular, the system consists of three steps: prediction, likelihood calculation and resampling. Since the resampling is accomplished in a synchronized area, our approach enhances the object tracking system especially efficiency and performance. The result shows that the amount of FPGA resource utilizes for the simulation of red-color soccer ball tracking compared with the available usage. Moreover, we evaluate the tracker detection rate and the accuracy of object tracking with the calculation of average and maximum tracking errors.
Eurographics/ Acm Siggraph Symposium on Computer Animation (2007) Face Poser: Interactive Modeling of 3d Facial Expressions Using Model Priors

Permission to make digital or hard copies of part or all of this wor k for per sonal or classr oom use is granted without fee provided that copies are not made or distributed for commer cial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this wor k owned by other s than ACM must be honored. Abstracting with cr edit is permitted. To copy other wise, to republish, to post on ser ver s, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions Dept, ACM Abstract In this paper, we present an intuitive interface for interactively posing 3D facial expressions. The user can create and edit facial expressions by drawing freeform strokes, or by directly dragging facial points in 2D screen space. Designing such an interface for face modeling and editing is challenging because many unnatural facial expressions might be consistent with the ambiguous user input. The system automatically learns a model prior from a prerecorded facial expression database and uses it to remove the ambiguity. We formulate the problem in a maximum a posteriori (MAP) framework by combining the prior with user-defined constraints. Maximizing the posterior allows us to generate an optimal and natural facial expression that satisfies the user-defined constraints. Our system is interactive; it is also simple and easy to use. A first-time user can learn to use the system and start creating a variety of natural face models within minutes. We evaluate the performance of our approach with cross validation tests, and by comparing with alternative techniques.
Robust output feedback control for a class of nonlinear systems

This paper investigates the problem of robust output feedback stabilization for a family of uncertain nonlinear systems. The proposed method contemplates uncertainties and results in asymptotic stability of system errors. The proposed method relaxes the debility of existing researches where the system nonlinearities are assumed to be bounded by a function of system output. In this note, the system nonlinearities under consideration are required to be bounded by a known function of state (not the system output), additionally no restrictive assumption is made on the system uncertainties. As some examples, the method is applied to two different control systems: the output feedback control of an atomic force microscopy as an example of chaotic systems; and the speed control of DC motors with only measurements of the armature current (not the shaft speed).
Managing cultural diversity in healthcare partnerships: the case of LIFT.

PURPOSE The National Health Service (NHS) Local Improvement Finance Trust (LIFT) programme was launched in 2001 as an innovative public-private partnership to address the historical under-investment in local primary care facilities in England. The organisations from the public and private sector that comprise a local LIFT partnership each have their own distinctive norms of behaviour and acceptable working practices - ultimately different organisational cultures. The purpose of this article is to assess the role of organisational culture in facilitating (or impeding) LIFT partnerships and to contribute to an understanding of how cultural diversity in public-private partnerships is managed at the local level. DESIGN/METHODOLOGY/APPROACH The approach taken was qualitative case studies, with data gathering comprising interviews and a review of background documentation in three LIFT companies purposefully sampled to represent a range of background factors. Elite interviews were also conducted with senior policy makers responsible for implementing LIFT policy at the national level. FINDINGS Interpreting the data against a conceptual framework designed to assess approaches to managing strategic alliances, the authors identified a number of key differences in the values, working practices and cultures in public and private organisations that influenced the quality of joint working. On the whole, however, partners in the three LIFT companies appeared to be working well together, with neither side dominating the development of strategy. Differences in culture were being managed and accommodated as partnerships matured. RESEARCH LIMITATIONS/IMPLICATIONS As LIFT develops and becomes the primary source of investment for managing, developing and channelling funding into regenerating the primary care infrastructure, further longitudinal work might examine how ongoing partnerships are working, and how changes in the cultures of public and private partners impact upon wider relationships within local health economies and shape the delivery of patient care. ORIGINALITY/VALUE To the authors' knowledge this is the first study of the role of culture in mediating LIFT partnerships and the findings add to the evidence on public-private partnerships in the NHS.
Expression of CD34 and L-selectin on human corneal keratocytes.

PURPOSE To investigate the expression of CD34, a hematopoietic stem cell marker and an adhesion molecule, and its ligand L-selectin in the human cornea. METHODS Seventeen normal adult human corneal specimens were studied by immunohistochemistry using a panel of monoclonal antibodies against all three classes of the hematopoietic stem cell marker CD34 and its ligand L-selectin. An additional six corneal specimens were used for protein extraction and analysis by Western blotting, using the CD34 and L-selectin antibodies. PCR was used to determine expression of mRNA for CD34 and L-selectin in the corneal specimens. RESULTS Only corneal keratocytes showed positive immunostaining for all three classes of CD34. Western blotting confirmed the expression of CD34 by these cells and mRNA expression for CD34 in the corneal stroma was demonstrated by PCR. For L-selectin, positive staining around keratocytes was noted on immunohistochemistry but L-selectin could not be detected either by Western blotting or PCR. CONCLUSIONS Normal human corneal keratocytes express all three classes of CD34. The expression of this adhesion molecule on corneal keratocytes suggests that it may have a role in keeping the keratocytes anchored in their microniche, between the collagen lamellae. The positive staining for L-selectin found by immunohistochemistry but not by Western blotting or PCR would indicate the presence of either another ligand from the selectin family or a cross-reactive epitope on corneal keratocytes.
Consecutive and simultaneous interpreting

Studies in the field of interpretation and translation have offered various models with which to explore the nature of the interpreting process, whether using simultaneous or consecutive interpreting. This chapter examines both simultaneous and consecutive interpreting, particularly as they relate to American Sign Language (ASL)-English interpreters, and argues for the increased use of consecutive interpreting. One of the unique features of working between ASL and English is that the languages are produced in different language modalities, one signed and one spoken, which has created a long-held view that because there is no auditory interference, as is the case with interpreting between two spoken languages, there is no need to work consecutively. Here we explore the role of consecutive interpreting in the education of ASL-English interpreters in North America, highlight some of the perceptions and myths held by interpreters and by consumers of interpreting services, and discuss the impact of choosing simultaneous or consecutive interpreting on the accuracy of the work. While the studies described in this chapter are largely based in Canada and the United States, the principles discussed will apply to interpreters working in other signed languages throughout the world.
ADAPTIVE BEAMPATTERN CONTROL USING QUADRATIC CONSTRAINTS FOR CIRCULAR ARRAY STAP

A general framework for adaptive and non-adaptive spacetime beampattern synthesis using quadratic beampattern constraints with minimum mean-square error (MMSE) and linearly constrained minimum variance (LCMV) beamforming is presented. Main beam and sidelobe pattern control is achieved by imposing a set of inequality constraints on the weighted mean-square error between the adaptive pattern and a desired beampattern over a set of angle-Doppler regions. An iterative procedure for satisfying the constraints is developed which can be applied as post-processing to standard MMSE or LCMV beamformers. The algorithm is used to synthesize a nearly uniform sidelobe level quiescent pattern for the circular UHF Electronically Scanned Array (UESA), and to control sidelobe levels for the same array in an adaptive manner. Performance results using data provided by Lincoln Lab show that under low sample support conditions, sidelobes can be effectively suppressed while maintaining high signalto-interference plus noise ratio, and deep nulls on clutter and interferers.
Intrusion Detection Using PCA Based Modular Neural Network

Most of current intrusion detection systems are based on machine learning methods but very few till now use clustering algorithms as a preprocessing layer to reduce the high dimensionality of data, which is difficult to analyze. In this paper we introduce Modular Neural Network for intrusion detection, which apply Principal Component Analysis (PCA) as preprocessing layer for reducing huge information quantity presented in knowledge discovery and data mining (KDD99) data set. PCA significantly reduce the high dimensionality of data set without loss of information. Then this preprocess data in the form of principal component is presented to Batch Backpropagation Neural Network for efficient intrusion detection. We rely on some experiments to calculate Root Mean Square Error (RMSE) using Modular Neural Network on KDD 99 data set. Our experimental results show improvement in the learning time due to the reduction of high dimensions of data. Also we have obtained low RMSE during training, which is below the acceptance range of 0.1. Proposed Modular Neural Network has capability to efficiently and accurately classify data into attack and normal.
Temporal Difference Learning and the Neural MoveMap Heuristic in the Game of Lines of Action

This paper investigates to what extent learning methods are beneficial for the Lines of Action tournament program MIA. We focus on two components of the program: (1) the evaluation function and (2) the move ordering. Using temporal difference learning the evaluation function was improved by tuning the weights. We found substantial improvements for three weights. The move ordering was enhanced by the Neural MoveMap (NMM) heuristic, which is based on learning. The two learning techniques improved both the playing quality and the speed of the program. Test results are given. The new evaluation function improved the program with a winning ratio of 1.68. The speed up of the NMM heuristic is 17 percent.
Improving M/EEG source localizationwith an inter-condition sparse prior

The inverse problem with distributed dipoles models in M/EEG is strongly ill-posed requiring to set priors on the solution. Most common priors are based on a convenient ℓ2 norm. However such methods are known to smear the estimated distribution of cortical currents. In order to provide sparser solutions, other norms than ℓ2 have been proposed in the literature, but they often do not pass the test of real data. Here we propose to perform the inverse problem on multiple experimental conditions simultaneously and to constrain the corresponding active regions to be different, while preserving the robust ℓ2 prior over space and time. This approach is based on a mixed norm that sets a ℓ1 prior between conditions. The optimization is performed with an efficient iterative algorithm able to handle highly sampled distributed models. The method is evaluated on two synthetic datasets reproducing the organization of the primary somatosensory cortex (S1) and the primary visual cortex (V1), and validated with MEG somatosensory data.