Miracle-dz/UniFAR-FTUs huggingface dataset:
Visualizing and quantifying cell phenotype using soft X‐ray tomography

Soft X‐ray tomography (SXT) is an imaging technique capable of characterizing and quantifying the structural phenotype of cells. In particular, SXT is used to visualize the internal architecture of fully hydrated, intact eukaryotic and prokaryotic cells at high spatial resolution (50 nm or better). Image contrast in SXT is derived from the biochemical composition of the cell, and obtained without the need to use potentially damaging contrast‐enhancing agents, such as heavy metals. The cells are simply cryopreserved prior to imaging, and are therefore imaged in a near‐native state. As a complement to structural imaging by SXT, the same specimen can now be imaged by correlated cryo‐light microscopy. By combining data from these two modalities specific molecules can be localized directly within the framework of a high‐resolution, three‐dimensional reconstruction of the cell. This combination of data types allows sophisticated analyses to be carried out on the impact of environmental and/or genetic factors on cell phenotypes.
IMGT, a system and an ontology that bridge biological and computational spheres in bioinformatics

IMGT, the international ImMunoGeneTics information system (http://imgt.cines.fr), is the reference in immunogenetics and immunoinformatics. IMGT standardizes and manages the complex immunogenetic data that include the immunoglobulins (IG) or antibodies, the T cell receptors (TR), the major histocompatibility complex (MHC) and the related proteins of the immune system (RPI), which belong to the immunoglobulin superfamily (IgSF) and the MHC superfamily (MhcSF). The accuracy and consistency of IMGT data and the coherence between the different IMGT components (databases, tools and Web resources) are based on IMGT-ONTOLOGY, the first ontology for immunogenetics and immunoinformatics. IMGT-ONTOLOGY manages the immunogenetics knowledge through diverse facets relying on seven axioms, 'IDENTIFICATION', 'DESCRIPTION', 'CLASSIFICATION', 'NUMEROTATION', 'LOCALIZATION', 'ORIENTATION' and 'OBTENTION', that postulate that objects, processes and relations have to be identified, described, classified, numerotated, localized, orientated, and that the way they are obtained has to be determined. These axioms constitute the Formal IMGT-ONTOLOGY, also designated as IMGT-Kaleidoscope. These axioms have been essential for the conceptualization of the molecular immunogenetics knowledge and for the creation of IMGT. Indeed all the components of the IMGT integrated system have been developed, based on standardized concepts and relations, thus allowing IMGT to bridge biological and computational spheres in bioinformatics. The same axioms can be used to generate concepts for multi-scale level approaches at the molecule, cell, tissue, organ, organism or population level, emphasizing the generalization of the application domain. In that way the Formal IMGT-ONTOLOGY represents a paradigm for the elaboration of ontologies in system biology.
The comparison of a dentin adhesive with calcium hydroxide as a pulp-capping agent on the exposed pulps of human and sheep teeth.

OBJECTIVE This study evaluated the biocompatibility of a one-step dentin bonding agent (Prime&Bond 2.1) in pulp capping compared with calcium hydroxide [Ca(OH)2]. METHOD AND MATERIALS Thirty sheep teeth and 20 intact human premolars were used. After cavity preparation, pulp exposure was achieved with a bur (#390). Adhesive pulp capping was performed in 25 teeth (15 sheep and 10 human). In the control group (12 sheep and 10 human teeth), pulps were capped with Ca(OH)2 and all of the cavities in both groups were sealed with resin composite. Three of the sheep teeth were used as intact controls. Teeth were extracted 7 or 90 days following treatment and prepared for histological examination and bacterial detection. RESULTS At 7 days, severe inflammatory responses underlying the bonding agent and in the coronal pulp were observed with soft tissue disorganization in both human and sheep teeth capped with Prime&Bond 2.1. All of the teeth capped with Ca(OH)2 exhibited mild inflammatory reactions limited with the perforation area. After 90 days with the bonding agent, in 3 of 9 sheep teeth, chronic inflammatory reactions were significant, while slight pulpal reactions were observed in the others and dentin bridge formation in all of the sheep teeth was found. However, in human pulps, persistent, unresolved inflammation with the lack of dentin bridge formation was observed. In the Ca(OH)2 group, pulp repair with dentin bridging was found in all of the teeth, both sheep and human. No correlation was found between the presence of inflammation and bacterial staining using Spearman rank correlation test (P > .05). CONCLUSION Prime&Bond 2.1 facilitates enhanced pulp healing and bridge formation in sheep teeth, but in human teeth it was not as successful as Ca(OH)2 as a pulp capping agent.
An Architecture for Customer Co-business Systems

For enterprises, customer relationships are critical to succeed their business. To enhance them, we present in this paper a discussion, namely Customer Co-Business Systems (CCBS), about collaborative business between customers and enterprises where customers can benefit from collaboration with enterprises by providing services to interested customers. The discussion figures out a CCBS architecture with necessary components and management mechanisms to help customers collaborate with enterprises to devise services.
Role for NOD2 in Mycobacterium tuberculosis‐induced iNOS expression and NO production in human macrophages

M.tb, which causes TB, is a host‐adapted intracellular pathogen of macrophages. Macrophage intracellular PRRs, such as NOD proteins, regulate proinflammatory cytokine production in response to various pathogenic organisms. We demonstrated previously that NOD2 plays an important role in controlling the inflammatory response and viability of M.tb and Mycobacterium bovis BCG in human macrophages. Various inflammatory mediators, such as cytokines, ROS, and RNS, such as NO, can mediate this control. iNOS (or NOS2) is a key enzyme for NO production and M.tb control during infection of mouse macrophages; however, the role of NO during infection of human macrophages remains unclear, in part, as a result of the low amounts of NO produced in these cells. Here, we tested the hypothesis that activation of NOD2 by its ligands (MDP and GMDP, the latter from M.tb) plays an important role in the expression and activity of iNOS and NO production in human macrophages. We demonstrate that M.tb or M. bovis BCG infection enhances iNOS expression in human macrophages. The M.tb‐induced iNOS expression and NO production are dependent on NOD2 expression during M.tb infection. Finally, NF‐κB activation is required for NOD2‐dependent expression of iNOS in human macrophages. Our data provide evidence for a new molecular pathway that links activation of NOD2, an important intracellular PRR, and iNOS expression and activity during M.tb infection of human macrophages.
The management information requirements of heads of university departments: a critical success factors approach

This paper examines the problems of developing management information systems in universities, with particu lar attention to the information needs of Heads of Depart ments. The context of university work is explored and needs are uncovered using the critical success factors methodology In using CSF it was found that senior managers intuitively understand and accept their use and that the methodology can take account of the unique characteristics of university management. Further advantages of the method are that all information is considered, whether or not it is easy to collect, and the critical success factors point to priorities for develop ment. The conclusions include suggestions for future research, hypotheses on critical success factors and information needs of Heads of departments and recommendations on informa tion acquisition, analysis and dissemination.
Persistent predecessor search and orthogonal point location on the word RAM

We answer a basic data structuring question (for example, raised by Dietz and Raman back in SODA 1991): can van Emde Boas trees be made persistent, without changing their asymptotic query/update time? We present a (partially) persistent data structure that supports predecessor search in a set of integers in {1,. ,U} under an arbitrary sequence of n insertions and deletions, with O(log log U) expected query time and expected amortized update time, and O(n) space. The query bound is optimal in U for linear-space structures and improves previous near-O((log log U)2) methods. The same method solves a fundamental problem from computational geometry: point location in orthogonal planar subdivisions (where edges are vertical or horizontal). We obtain the first static data structure achieving O(log log U) worst-case query time and linear space. This result is again optimal in U for linear-space structures and improves the previous O((log log U)2) method by de Berg, Snoeyink, and van Kreveld (1992). The same result also holds for higher-dimensional subdivisions that are orthogonal binary space partitions, and for certain nonorthogonal planar subdivisions such as triangulations without small angles. Many geometric applications follow, including improved query times for orthogonal range reporting for dimensions ≥ 3 on the RAM. Our key technique is an interesting new van-Emde-Boas-style recursion that alternates between two strategies, both quite simple.
Backcalculation of subgrade stiffness under rubblised PCC slabs using multilevel FWD loads

Rubblisation is an effective rehabilitation method for deteriorated Portland cement concrete (PCC) pavements due to its low initial costs, minimal traffic disruption and ability to minimise reflective cracking in asphalt overlays. However, the loss of strength in the PCC slab due to rubblisation creates the demand for a subgrade that is strong enough to handle traffic after rubblisation. This paper presents a research effort to develop an analysis method that allows the realistic estimation of subgrade stiffness after rubblisation from deflection measurements on intact PCC slabs before rubblisation. As a forward model, stress- and strain-dependent nonlinear subgrade models are incorporated into a finite element analysis (FEA). Based on the synthetic database generated from the FEA, different methodologies are developed to predict the coefficients in the nonlinear subgrade model from deflections under multilevel falling weight deflectometer loads.
Source influence on emission pathways and ambient PM2.5 pollution over India (2015–2050)

India is currently experiencing degraded air quality, and future economic development will lead to challenges for air quality management. Scenarios of sectoral emissions of fine particulate matter and its precursors were developed and evaluated for 2015–2050, under specific pathways of diffusion of cleaner and more energy-efficient technologies. The impacts of individual source sectors on PM2.5 concentrations were assessed through systematic simulations of spatially and temporally resolved particulate matter concentrations, using the GEOS-Chem model, followed by population-weighted aggregation to national and state levels. We find that PM2.5 pollution is a pan-India problem, with a regional character, and is not limited to urban areas or megacities. Under present-day emissions, levels in most states exceeded the national PM2.5 annual standard (40 μg m−3). Sources related to human activities were responsible for the largest proportion of the present-day population exposure to PM2.5 in India. About 60 % of India’s mean population-weighted PM2.5 concentrations come from anthropogenic source sectors, while the remainder are from “other” sources, windblown dust and extra-regional sources. Leading contributors are residential biomass combustion, power plant and industrial coal combustion and anthropogenic dust (including coal fly ash, fugitive road dust and waste burning). Transportation, brick production and distributed diesel were other contributors to PM2.5. Future evolution of emissions under regulations set at current levels and promulgated levels caused further deterioration of air quality in 2030 and 2050. Under an ambitious prospective policy scenario, promoting very large shifts away from traditional biomass technologies and coal-based electricity generation, significant reductions in PM2.5 levels are achievable in 2030 and 2050. Effective mitigation of future air pollution in India requires adoption of aggressive prospective regulation, currently not formulated, for a three-pronged switch away from (i) biomass-fuelled traditional technologies, (ii) industrial coal-burning and (iii) open burning of agricultural residue. Future air pollution is dominated by industrial process emissions, reflecting larger expansion in industrial, rather than residential energy demand. However, even under the most active reductions envisioned, the 2050 mean exposure, excluding any impact from windblown mineral dust, is estimated to be nearly 3 times higher than the WHO Air Quality Guideline.
1-2-tree: Semantic Modeling and Editing of Trees

In computer graphics, procedural methods and Lsystems are common approaches to model complex botanical trees. In contrast to previous tree modeling systems, we propose linking rules, parameters and geometry to semantic entities. This has the avantage that when an entity is clicked in the viewport, its parameters can be displayed immediately, and viewport editing operations can be reflected in the parameter set. Furthermore, we store the entities in a hierarchical data structure and allow the user to activate recursive traversal via selection options for all editing operations. Therefore, viewport or parameter changes can be applied to a single entity or many entities at once, and only the geometry for the affected entities needs to be updated. The proposed user interface aims at simplifying the modeling process.
Dense Gaussian Sensor Networks: Minimum Achievable Distortion and the Order Optimality of Separation

We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. The overall goal of the sensor network is to take measurements from an underlying random process, code and transmit those measurement samples to a collector node in a cooperative multiple access channel with potential feedback, and reconstruct the entire random process at the collector node. We provide lower and upper bounds for the minimum achievable expected distortion when the underlying random process is Gaussian. When the Gaussian random process satisfies some general conditions, we evaluate the lower and upper bounds explicitly, and show that they are of the same order for a wide range of power constraints. Thus, for these random processes, under these power constraints, we express the minimum achievable expected distortion as a function of the power constraint. Further, we show that the achievability scheme that achieves the lower bound on the distortion is a separation-based scheme that is composed of multi-terminal rate-distortion coding and amplify-and-forward channel coding. Therefore, we conclude that separation is order-optimal for the dense Gaussian sensor network scenario under consideration, when the underlying random process satisfies some general conditions.
A unified approach to content-based and fault tolerant music identification

In this paper we propose a unified approach to content-based search in different kinds of music data. Our approach is based on a general algorithmic framework for searching patterns of complex objects in large databases. In particular we describe how this approach may be used to allow for polyphonic search in polyphonic scores as well as for the identification of PCM audio material. We give an overview on the various aspects of our technology including fault tolerant search methods. Several areas of application are suggested. We give an overview on several prototypic systems we developed for those applications including the notify! and the audentify! systems.
Breast border extraction and pectoral muscle removal in MLO mammogram images

In this paper, we propose a new method for breast border extraction, artifact removal and removal of annotations typically found in the background of mammograms. The proposed method uses adaptive local thresholding to create an initial binary mask for an image. This is followed by the use of morphological operations to remove background artifacts. Then an adaptive algorithm is proposed to automatically detect and remove the pectoral muscle depending on the gray-level intensity values. Preliminary results of experiments conducted on the Mini-MIAS database (Mammographic Image Analysis Society, London, U.K.) show that the proposed method achieves a near 100% success rate for breast contour extraction and the proposed method for pectoral muscle removal achieves nearly 89% accuracy. More importantly, the proposed pre-processing techniques improved the mammogram classification results when compared to using previous pre-processing methods.
Enabling self-adaptivity in component-based streaming applications

Self-adaptivity is the capability of a system to adapt itself dynamically to achieve its goals. By means of this mechanism the system is able to autonomously modify its behavior or the way in which applications are run and implemented to achieve the goals set. In this paper we propose a framework that uses a componentbased approach to implement self-adaptivity at application level. By using this mechanism, the framework provides the ability to perform both adaptation on the structure of the application (i.e., how the components are connected together) and on internal parameters of each component. At application level, there is a mechanism to monitor different parameters and to check whether the system is meeting the assigned goals or not. A controller drives adaptations when goals are not met.
Multiple index combination for Japanese spoken term detection with optimum index selection based on OOV-region classifier

In this paper, a novel index combination method for spoken term detection is proposed. In our method, outputs from four different recognizers (word, syllable, word-syllable, and fragment recognizer) are combined into one confusion network. A novel index-selection method for the multiple index-combination method is then used to suppress the increase of the index size. Two methods are proposed to reduce index size: (1) arc selection and (2) unit selection, both of which are based on an OOV-region classifier score. Experimental results with 39 hours of Japanese lecture recordings showed that the index-selection method achieved a 22% reduction of index size of the best confusion network while maintaining its high accuracy. Compared with the best phoneme-based index from a single recognizer, the proposed method achieved a 25.0% and 14.8% relative error reduction for IV and OOV queries without increasing the index size.
Energy determination of corn co-products in finishing pigs and the use of an in vitro organic matter digestibility assay to predict in vivo energy

Twenty corn co-products from various wetand dry-grind ethanol plants were fed to finishing pigs to determine DE and ME and to generate equations to predict energy based upon each ingredient’s chemical analysis. Co-products included: DDGS (7), HP-DDG (3), bran (2), germ (2), gluten meal and feed, dehulled, degermed corn, dried solubles, starch, and corn oil. The control diet was based on corn (97.1%), limestone, dicalcium phosphate, salt, vitamins, and trace minerals. All but two test diets were formulated by mixing the control diet with 30% of a co-product. Dried solubles and oil were included at 20% and 10%, respectively. Eight groups of 24 finishing gilts (n=192, 112.7 final BW ± 7.9 kg) were randomly assigned to a test diet and each diet was fed to a total of 8 pigs. Gilts were placed in metabolism crates and fed an amount equivalent to 3% BW daily for 9 d followed by separately collecting feces and urine for 4 d. Ingredients were analyzed for moisture, GE, CP, crude fat (EE), crude fiber, NDF, ADF, total dietary fiber (TDF), and ash. Gross energy was determined on the feed, feces, and urine to calculate DE and ME for each ingredient. 1 Supported in part by grants from the National Pork Board (No. 08-107). The authors acknowledge Howard Tyler and Leo Timms, Associate Professors in the Department of Animal Science, Iowa State University, Ames 50011. We are also thankful for help from Tom Webber, Cheri Ziemer, Jennifer Cook, Erin Conrad, Kristin Hard, Tricia Wolfswinkle, Tonya Huenink, Chris Olsen, Joel Johnson, Brandy Jacobs, Alisha Hoffman and staff at the Iowa State University Swine Nutrition and Research Farm. 2 These authors contributed equally to the work. 3 Corresponding author: brian.kerr@ars.usda. gov
Prediction of relative solvent accessibility by support vector regression and best-first method

Since, it is believed that the native structure of most proteins is defined by their sequences, utilizing data mining methods to extract hidden knowledge from protein sequences, are unavoidable. A major difficulty in mining bioinformatics data is due to the size of the datasets which contain frequently large numbers of variables. In this study, a two-step procedure for prediction of relative solvent accessibility of proteins is presented. In a first “feature selection” step, a small subset of evolutionary information is identified on the basis of selected physicochemical properties. In the second step, support vector regression is used to real value prediction of protein solvent accessibility with these custom selected features of evolutionary information. The experiment results show that the proposed method is an improvement in average prediction accuracy and training time.
A joint analysis for cosmology and photometric redshift calibration using cross-correlations

We present a method of calibrating the properties of photometric redshift bins as part of a larger Markov Chain Monte Carlo (MCMC) analysis for the inference of cosmological parameters. The redshift bins are characterised by their mean and variance, which are varied as free parameters and marginalised over when obtaining the cosmological parameters. We demonstrate that the likelihood function for cross-correlations in an angular power spectrum framework tightly constrains the properties of bins such that they may be well determined, reducing their influence on cosmological parameters and avoiding the bias from poorly estimated redshift distributions. We demonstrate that even with only three photometric and three spectroscopic bins, we can recover accurate estimates of the mean redshift of a bin to within $\Delta\mu \approx 3-4 \times10^{-3}$ and the width of the bin to $\Delta\sigma \approx 1\times10^{-3}$ for galaxies near $z = 1$. This indicates that we may be able to bring down the photometric redshift errors to a level which is in line with the requirements for the next generation of cosmological experiments.
Transcriptional activity of the TFIIA four‐helix bundle in vivo

TFIIA contributes to transcription initiation by stabilizing the TBP–TATA interaction and by mediating the response to transcriptional activators and inhibitors. TFIIA contains a six‐stranded β‐sheet domain and a four‐helix bundle. The β‐domain makes functional contacts with DNA and TBP. The role of the four‐helix bundle was investigated using a structure‐based model of this domain (called 4HB). 4HB adopts a highly stable, helical fold, consistent with its structure in the context of TFIIA. Like TBP and other intact transcription factors, 4HB is able to activate transcription in vivo when artificially recruited to a promoter via a heterologous DNA‐binding domain. Thus, in addition to making important contacts with TBP and DNA via the β‐domain, TFIIA makes other specific, functional contacts with the transcriptional machinery via the four‐helix bundle. Proteins 2001;43:227–232. © 2001 Wiley‐Liss, Inc.