Miracle-dz/UniFAR-FTUs huggingface dataset:
Diltiazem suppresses collagen synthesis and IL-1beta-induced TGF-beta1 production on human peritoneal mesothelial cells.

BACKGROUND After long-term treatment with continuous ambulatory peritoneal dialysis (CAPD), some patients may develop peritoneal fibrosis. Peritoneal mesothelial cells (PMCs) participate in the inflammatory reactions in the peritoneal cavity, and transforming growth factor-beta1 (TGF-beta1) and interleukin-1beta (IL-1beta) are involved in peritoneal fibrosis. Diltiazem is used frequently in patients with CAPD to treat hypertension. The objectives of this study were to examine the effects of diltiazem on collagen- and IL-1beta-induced TGF-beta1 production on human PMCs and the signalling pathway of diltiazem in this induction. METHODS Human PMCs were cultured from the enzymatic disaggregation of human omentum. Collagen synthesis was measured by [3H]proline incorporation into pepsin-resistant, salt-precipitated collagen. The expression of collagen I and III, and TGF-beta1 mRNA was evaluated by northern blotting. The production of TGF-beta1 by human PMCs was measured by immunoassay. The changes of intracellular calcium level after adding Fura-2-AM were measured by fluorescence spectrophotometry. Western blotting was used to assess mitogen-activated protein kinase (MAPK) signalling proteins. RESULTS We found that diltiazem (<0.2 mM) inhibited collagen I and III mRNA expression and collagen syntheses on a dose-dependent basis. Diltiazem (0.2 mM) suppressed IL-1beta- (5 ng/ml) induced TGF-beta1 production on human PMCs at both the protein and mRNA levels. Diltiazem (0.2 mM) also inhibited IL-1beta- (5 ng/ml) induced collagen I and III mRNA expression. Intracellular calcium levels did not change after the treatment with diltiazem, IL-1beta or both. The IL-1beta-treated human PMCs increased phospho-JNK (stress-activated c-Jun N-terminal kinase) and phospho-p38 MAPK expression, while diltiazem could suppress this phenomenon. CONCLUSIONS Diltiazem suppressed collagen synthesis of human PMCs and inhibited IL-1beta-induced TGF-beta1 production on human PMCs. This signalling transduction may be through p38 MAPK and JNK pathways instead of intracellular calcium. These results suggest diltiazem to be a potential therapeutic regimen in preventing peritoneal fibrosis and support further in vivo studies.
The application of computer communication technology in the information age

This article can clearly and intuitively understand the use of computer communication technology in the information age. In the past society, people only used pictures and other characters to transmit information, and the traffic was inconvenient. With the acceleration of economic development, computer communication technology has emerged in the current 21st century. The continuous development of this technology has made the network become popular in people's lives. People can use computers and other electronic devices to transmit information. Great convenience for people's daily lives. Computer communication technology is a close combination of computer and communication equipment, and it plays a big role in the process of people's living standards. Based on this, this paper focuses on thinking and exploring from the application of computer communication technology in the information age. By analyzing the concept and characteristics of computer communication technology, it is for people. Future life development points to a new path.
A study of top-k measures for discrimination discovery

Data mining approaches for discrimination discovery unveil contexts of possible discrimination against protected-by-law groups by extracting classification rules from a dataset of historical decision records. Rules are ranked according to some legally-grounded contrast measure defined over a 4-fold contingency table, including risk difference, risk ratio, odds ratio, and a few others. Due to time and cost constraints, however, only the top-k ranked rules are taken into further consideration by an anti-discrimination analyst. In this paper, we study to what extent the sets of top-k ranked rules with respect to any two pairs of measures agree.
Empirical investigations on parallel competent genetic algorithms

This paper empirically investigates parallel competent genetic algorithms (cGAs) [4]. cGAs, such as BOA [21], LINCGA [15], D5-GA [28], can solve GA-difficult problems by automatically learning problem structure as gene linkage. Parallel implementation of cGAs can reduce computational cost due to the linkage learning and give us problem solving environments for a wide spectrum of real-world problems. Although some parallel cGAs have been proposed [16, 18, 19], the effect of the parallelizations has not been investigated enough. This paper empirically discusses the applicability and property of parallel cGAs, including a new parallel cGA, parallel D5-GA.
A Fractal Model for Power Smart Grids

Smart grid technology is the future of electricity ordered by computers. This article presents the characteristics of the new technological developments in this area and reveals the fractal nature of this architecture, leading to a holonic structure which presents smart grid as a system bottom-up organized from autonomous entities that are recursively clustered at various aggregation layers. Taking into account the novelty of the subject, this paper should bring new opportunities to explore and develop this domain.
Worker Personality and Its Association with Spatially Structured Division of Labor

Division of labor is a defining characteristic of social insects and fundamental to their ecological success. Many of the numerous tasks essential for the survival of the colony must be performed at a specific location. Consequently, spatial organization is an integral aspect of division of labor. The mechanisms organizing the spatial distribution of workers, separating inside and outside workers without central control, is an essential, but so far neglected aspect of division of labor. In this study, we investigate the behavioral mechanisms governing the spatial distribution of individual workers and its physiological underpinning in the ant Myrmica rubra. By investigating worker personalities we uncover position-associated behavioral syndromes. This context-independent and temporally stable set of correlated behaviors (positive association between movements and attraction towards light) could promote the basic separation between inside (brood tenders) and outside workers (foragers). These position-associated behavior syndromes are coupled with a high probability to perform tasks, located at the defined position, and a characteristic cuticular hydrocarbon profile. We discuss the potentially physiological causes for the observed behavioral syndromes and highlight how the study of animal personalities can provide new insights for the study of division of labor and self-organized processes in general.
Bridge Centrality: A Network Approach to Understanding Comorbidity

Abstract Recently, researchers in clinical psychology have endeavored to create network models of the relationships between symptoms, both within and across mental disorders. Symptoms that connect two mental disorders are called "bridge symptoms. " Unfortunately, no formal quantitative methods for identifying these bridge symptoms exist. Accordingly, we developed four network statistics to identify bridge symptoms: bridge strength, bridge betweenness, bridge closeness, and bridge expected influence. These statistics are nonspecific to the type of network estimated, making them potentially useful in individual-level psychometric networks, group-level psychometric networks, and networks outside the field of psychopathology such as social networks. We first tested the fidelity of our statistics in predicting bridge nodes in a series of simulations. Averaged across all conditions, the statistics achieved a sensitivity of 92.7% and a specificity of 84.9%. By simulating datasets of varying sample sizes, we tested the robustness of our statistics, confirming their suitability for network psychometrics. Furthermore, we simulated the contagion of one mental disorder to another, showing that deactivating bridge nodes prevents the spread of comorbidity (i.e., one disorder activating another). Eliminating nodes based on bridge statistics was more effective than eliminating nodes high on traditional centrality statistics in preventing comorbidity. Finally, we applied our algorithms to 18 group-level empirical comorbidity networks from published studies and discussed the implications of this analysis.
Decoupling of multi-channels RF coil and its application to intraoperative MR-guided focused ultrasound device

Decoupling between different elements is the key technology in the design of the RF coil. The electrical decoupling circuits should vary with different arrangement of the elements. A novel method of decoupling for the RF coil used in the intraoperative MR-guided focused ultrasound system was reported in the paper. The prototype RF coil was made according to the proposed decoupling method. The bench test of the coil showed that the performance of the decoupling of the coil was excellent. The images in vivo were acquired with the designed prototype RF coil.
Automatic annotation of protein function based on family identification

Although genomes are being sequenced at an impressive rate, the information generated tells us little about protein function, which is slow to characterize by traditional methods. Automatic protein function annotation based on computational methods has alleviated this imbalance. The most powerful current approach for inferring the function of new proteins is by studying the annotations of their homologues, since their common origin is assumed to be reflected in their structure and function. Unfortunately, as proteins evolve they acquire new functions, so annotation based on homology must be carried out in the context of orthologues or subfamilies. Evolution adds new complications through domain shuffling: homology (or orthology) frequently corresponds to domains rather than complete proteins. Moreover, the function of a protein may be seen as the result of combining the functions of its domains. Additionally, automatic annotation has to deal with problems related to the annotations in the databases: errors (which are likely to be propagated), inconsistencies, or different degrees of function specification. We describe a method that addresses these difficulties for the annotation of protein function. Sequence relationships are detected and measured to obtain a map of the sequence space, which is searched for differentiated groups of proteins (similar to islands on the map), which are expected to have a common function and correspond to groups of orthologues or subfamilies. This mapmaking is done by applying a clustering algorithm based on Normalized cuts in graphs. The domain problem is addressed in a simple way: pairwise local alignments are analyzed to determine the extent to which they cover the entire sequence lengths of the two proteins. This analysis determines both what homologues are preferred for functional inheritance and the level of confidence of the annotation. To alleviate the problems associated with database annotations, the information on all the homologues that are grouped together with the query protein are taken into account to select the most representative functional descriptors. This method has been applied for the annotation of the genome of Buchnera aphidicola (specific host Baizongia pistaciae). Human inspection of the annotations allowed an estimation of accuracy of 94%; the different kinds of error that may appear when using this approach are described. Results can be accessed at http://www.pdg. cnb.uam. es/funcut.html. The programs are available upon request, although installation in other systems may be complicated. Proteins 2003;53:000–000. © 2003 Wiley‐Liss, Inc.
Ecological Applications, 6(3), 1996, pp

Biodiversity mapping (e.g., the Gap Analysis Program [GAP]), in which vegetative features and categories of land use are mapped at coarse spatial scales, has been proposed as a reliable tool for land use decisions (e.g., reserve identification, selection, and design). This implicitly assumes that species richness data collected at coarse spatiotemporal scales provide a first-order approximation to community and ecosystem representation and persistence. This assumption may be false because (1) species abundance distributions and species richness are poor surrogates for community/ecosystem processes, and are scale dependent; (2) species abundance and richness data are unreliable because of unequal and unknown sampling probabilities and species-habitat models of doubtful reliability; (3) mapped species richness data may be inherently resistant to "scaling up" or "scaling down"; and (4) decision-making based on mapped species richness patterns may be sensitive to errors from unreliable data and models, resulting in suboptimal conservation decisions. We suggest an approach in which mapped data are linked to management via demographic models, multiscale sampling, and decision theory. We use a numerical representation of a system in which vegetation data are assumed to be known and mapped without error, a simple model relating habitat to predicted species persistence, and statistical decision theory to illustrate use of mapped data in conservation decision-making and the impacts of uncertainty in data or models on the decision outcome.
The Soar Cognitive Architecture

In development for thirty years, Soar is a general cognitive architecture that integrates knowledge-intensive reasoning, reactive execution, hierarchical reasoning, planning, and learning from experience, with the goal of creating a general computational system that has the same cognitive abilities as humans. In contrast, most AI systems are designed to solve only one type of problem, such as playing chess, searching the Internet, or scheduling aircraft departures. Soar is both a software system for agent development and a theory of what computational structures are necessary to support human-level agents. Over the years, both software system and theory have evolved. This book offers the definitive presentation of Soar from theoretical and practical perspectives, providing comprehensive descriptions of fundamental aspects and new components. The current version of Soar features major extensions, adding reinforcement learning, semantic memory, episodic memory, mental imagery, and an appraisal-based model of emotion. This book describes details of Soar's component memories and processes and offers demonstrations of individual components, components working in combination, and real-world applications. Beyond these functional considerations, the book also proposes requirements for general cognitive architectures and explicitly evaluates how well Soar meets those requirements.
Practical FIR Filter Design in MATLAB

This tutorial white-paper illustrates practical aspects of FIR ﬁlter design and ﬁxed-point implementation along with the algorithms available in the Filter Design Toolbox and the Signal Processing Toolbox for this purpose. The emphasis is mostly on lowpass ﬁlters, but many of the results apply to other ﬁlter types as well. The tutorial focuses on practical aspects of ﬁlter design and implementation, and on the advantages and disadvantages of the different design algorithms. The theory behind the design algorithms is avoided except when needed to motivate them.
Appearance control by projector camera feedback for visually impaired

Visual impairment is a common problem for people worldwide. The projector-based AR technique has the ability to change the appearance of real objects, and it can help to improve visibility for the visually impaired. We propose a new framework for appearance enhancement with a projector camera system that employs a model predictive controller. This framework enables arbitrary image processing such as photo-retouch software in the real world and it helps to improve visibility for the visually impaired. In this article, we show the appearance enhancement results of Peli's method and Wolffshon's method for low vision, and Jefferson's method for color vision deficiencies. Through experimental results, the potential of our method to enhance the appearance for the visually impaired was confirmed to be the same as appearance enhancement for digital images and television viewing.
Microarray analysis yields candidate markers for rotation resistance in the western corn rootworm beetle, Diabrotica virgifera virgifera

As pest species may evolve resistance to chemical controls, they may also evolve resistance to cultural control methods. Yearly rotation of corn (Zea mays) with another crop interrupts the life cycle of the western corn rootworm beetle (Diabrotica virgifera virgifera, Coleoptera: Chrysomelidae), but behavioral resistance to crop rotation is now a major problem in the Midwest of the USA. Resistant adult females exhibit reduced fidelity to corn as a host and lay their eggs in the soil of both corn and soybean (Glycine max) fields. Behavioral assays suggest that the adaptation is related to increased locomotor activity, but finding molecular markers has been difficult. We used microarray analysis to search for gene expression differences between resistant and wild‐type beetles. Candidates validated with real‐time polymerase chain reaction exhibit predicted patterns from the microarray in independent samples across time and space. Many genes more highly expressed in the rotation‐resistant females have no matches to known proteins, and most genes that were more lowly expressed are involved in antimicrobial defense.
Automatic Detection of Pathologies in The Voice by HOS Based Parameters

In the current panorama the conclusive identification of a laryngeal pathology relies inevitably on the observation of the vocal folds by means of laryngoscopical techniques. This inspection technique is inconvenient for a number of reasons, such as its high cost, the duration of the inspection, and, above all, the fact that it is an invasive technique. This paper looks into the possibility of measuring the quality of a voice starting from an audio recording. The existing parameters in current literature (“classic parameters”) which allow quantifying the quality of a voice have been studied, and the parameters that present better results have been selected. Also, seven new high order statistics (HOS) based parameters are proposed to parameterize the voice signal. On the other hand, a software package has been developed which carries out the automatic detection of dysfunction in phonation. A success rate of 98.3% has been obtained by using both the classic and the HOS based proposed parameters.
Scene Recognition through Visual Attention and Image Features: A Comparison between SIFT and SURF Approaches

In this work we study how we can use a novel model of spatial saliency (visual attention) combined with image features to significantly accelerate a scene recognition application and, at the same time, preserve recognition performance. To do so, we use a mobile robotlike application where scene recognition is carried out through the use of image features to characterize the different scenarios, and the Nearest Neighbor rule to carry out the classification. SIFT and SURF are two recent and competitive alternatives to image local featuring that we compare through extensive experimental work. Results from the experiments show that SIFT features perform significantly better than SURF features achieving important reductions in the size of the database of prototypes without significant losses in recognition performance, and thus, accelerating scene recognition. Also, from the experiments it is concluded that SURF features are less distinctive when using very large databases of interest points, as it occurs in the present case. Visual attention is the process by which the Human Visual System (HVS) is able to select from a given scene regions of interest that contain salient information, and thus, reduce the amount of information to be processed (Treisman, 1980; Koch, 1985). In the last decade, several computational models biologically motivated have been released to implement visual attention in image and video processing (Itti, 2000; Garcia-Diaz, 2008). Visual attention has also been used to improve object recognition and scene analysis (Bonaiuto, 2005; Walther, 2005). In this chapter, we study the utility of using a novel model of spatial saliency to improve a scene recognition application by reducing the amount of prototypes needed to carry out the classification task. The application is based on mobile robot-like video sequences taken in indoor facilities formed by several rooms and halls. The aim is to recognize the different scenarios in order to provide the mobile robot system with general location data. The visual attention approach is a novel model of bottom-up saliency that uses local phase information of the input data where the statistic information of second order is deleted to achieve a Retinoptical map of saliency. The proposed approach joints computational mechanisms of the two hypotheses largely accepted in early vision: first, the efficient coding
Heterogeneous response of different tumor cell lines to methotrexate-coupled nanoparticles in presence of hyperthermia

Today, the therapeutic efficacy of cancer is restricted by the heterogeneity of the response of tumor cells to chemotherapeutic drugs. Since those therapies are also associated with severe side effects in nontarget organs, the application of drugs in combination with nanocarriers for targeted therapy has been suggested. Here, we sought to assess whether the coupling of methotrexate (MTX) to magnetic nanoparticles (MNP) could serve as a valuable tool to circumvent the heterogeneity of tumor cell response to MTX by the combined treatment with hyperthermia. To this end, we investigated five breast cancer cell lines of different origin and with different mutational statuses, as well as a bladder cancer cell line in terms of their response to exposure to MTX as a free drug or after its coupling to MNP as well as in presence/absence of hyperthermia. We also assessed whether the effects could be connected to the cell line-specific expression of proteins related to the uptake and efflux of MTX and MNP. Our results revealed a very heterogeneous and cell line-dependent response to an exposure with MTX-coupled MNP (MTX–MNP), which was almost comparable to the efficacy of free MTX in the same cell line. Moreover, a cell line-specific and preferential uptake of MTX–MNP compared with MNP alone was found (probably by receptor-mediated endocytosis), agreeing with the observed cytotoxic effects. Opposed to this, the expression pattern of several cell membrane transport proteins noted for MTX uptake and efflux was only by tendency in agreement with the cellular toxicity of MTX–MNP in different cell lines. Higher cytotoxic effects were achieved by exposing cells to a combination of MTX–MNP and hyperthermal treatment, compared with MTX or thermo-therapy alone. However, the heterogeneity in the response of the tumor cell lines to MTX could not be completely abolished – even after its combination with MNP and/or hyperthermia – and the application of higher thermal dosages might be necessary.