Miracle-dz/UniFAR-FTUs huggingface dataset:
Preclinical Efficacy and Safety of 1-Deoxygalactonojirimycin in Mice for Fabry Disease

Fabry disease is an inborn error of glycosphingolipid metabolism caused by deficiency of α-galactosidase A (α-Gal A) activity. It has been shown that protein misfolding is primarily responsible for the enzyme deficiency in a large proportion of mutations identified in Fabry patients with residual enzyme activity, and 1-deoxygalactonojirimycin (DGJ) can effectively increase the residual enzyme activity in cultured patient's cells. Herein, we demonstrate the preclinical efficacy and safety of DGJ in transgenic mice that express human mutant α-Gal A activity. α-Gal A activity in heart, kidney, spleen, and liver was increased dose- and time-dependently. The mutant α-Gal A was increased in cardiomyocytes and distal convoluted tubules of the transgenic mice in a null background after 2 weeks of DGJ treatment. Globotriaosylceramide storage was remarkably reduced in kidney of mice after a 4-week treatment at a dosage of approximately 3 mg/kg body weight/day. The half-life of DGJ was less than 1 day in all major issues and that of the enzyme synthesized during the DGJ treatment period was approximately 4 days. No abnormality of blood chemistry and pathological tissue damage was found in mice treated with DGJ at ∼30 mg/kg body weight/day for 9 weeks. Furthermore, no change was observed in appearance, growth, fertility, and life span in mice during a 2-year period of continuous administration of DGJ at the effective dosage. These preclinical results indicate that DGJ is effective in restoring mutant enzyme activity in tissues and reversing substrate storage in kidney and is well tolerated in mice.
A cost ontology for enterprise modelling

There is an urgent need to formalize activity-based costing (ABC) for the purposes of implementation and usage in enterprises so that enterprises have access to the critical element of global success, viz. strategic management accounting. To make this possible, the authors present a core cost ontology and micro-theory of costing for enterprise modelling that spans the knowledge representation of activity, status of activity, time, causality, and resources. This ensures that ABC may be generically deployed in any enterprise to achieve effective activity-based cost management, irrespective of the enterprise belonging to the manufacturing or service sectors. <<ETX>>
A randomized controlled trial to evaluate the effectiveness of a cognitive behavioural group approach to improve patient adherence to peritoneal dialysis fluid restrictions: a pilot study.

BACKGROUND Peritoneal dialysis (PD) requires patients to take an active role in their adherence to fluid restrictions. Although fluid non-adherence had been identified among this patient group, no specific interventions have been researched or published with in the PD population. The current study sought to investigate whether an applied cognitive behavioural therapy (CBT-based intervention) used among haemodialysis patients would improve fluid adherence among PD patients; utilizing clinical indicators used in practice. METHODS Fifteen PD patients identified as fluid non-adherent were randomly assigned to an intervention group (IG) or a deferred-entry control group (CG). The study ran for a total of 21 weeks, with five data collection points; at baseline, post-intervention and at three follow-up points; providing a RCT phase and a combined longitudinal analysis phase. The content of the group intervention encompassed educational, cognitive and behavioural components, aimed to assist patients' self-management of fluid. RESULTS No significant differences in weight (kg) reduction were found in either phase and undesirable changes in blood pressure (BP) were observed. However, in the longitudinal phase, a statistically significant difference in oedematous status was observed at 6-week follow-up; which may be indicative of fluid adherence. Positive and significant differences were observed in the desired direction for measures of psychological well-being, quality of life and health beliefs; areas correlated with enhanced fluid adherence in other research. CONCLUSIONS This study reveals encouraging and significant changes in predictors of fluid adherence. Although there were no significant changes in weight as a crude clinical measure of fluid intake, significant reductions in oedematous status were observed as a consequence of this CBT-based group intervention.
Investigating City Characteristics Based on Community Profiling in LBSNs

While the detection of social subgroups (i.e., communities) has always been a fundamental task in social network analysis, few efforts has been made to characterize the detected community. Meanwhile, to effectively facilitate applications based on the community structure, it is very important to understand the features of each community. Thereby, a systematic community profiling mechanism is needed. With the recent surge of location-based social networks (LBSNs, e.g., Foursquare, Facebook Places), huge amount of digital footprints about users' locations, profiles as well as their online social connections provide sufficient metadata for community profiling. Different from social networks (e.g., Flickr, Facebook) which have explicit groups for users to subscribe or join, LBSNs usually have no explicit community structure. In order to capitalize on the large number of potential users, quality community detection and profiling approaches are needed so as to enable applications such as direct marketing, group tracking, etc. In this paper, based on the user-venue check-in relationship and user/venue attributes, we come out with a novel community profiling framework. Specifically, we first adopt edge-clustering to simultaneously group both users and venues into communities, and then based on the rich metadata of users and venues we put forward a quantitative community profiling mechanism to indicate the preferences, interests and habits of a community. The efficacy of our approach is validated by intensive empirical evaluations using the collected Foursquare dataset of 266,838 users with 9,803,764 check-ins over 2,477,122 venues worldwide.
Integration vs . Segregation in Functional Brain Networks

We propose a new methodology to evaluate the balance between segregation and integration in functional brain networks by using Singular Value Decomposition techniques. By means of magnetoencephalography, we obtain the brain activity of a control group of nineteen individuals during a memory task. Next, we project the node-to-node correlations into a complex network which is analyzed from the perspective of its modular structure encoded in the contribution matrix. In this way, we are able to study the role that nodes play inside/outside its community and to identify connector and local hubs. At the mesoscale level, the analysis of the contribution matrix allows to measure the degree of overlapping between communities and quantify how far the functional networks are from the configuration that better balances the integrated and segregated activity.
Netlearning and Learning through Networks

Traditional non-computerized learning environments are typically founded on an understanding of learning as acquiring silence for an effective individual learning process. Recently, it has also been reported that the high expectations for the impact of computer-based technology on educational practice have not been realized. This paper sets out to challenge both the assumptions made about the requirements for effective learning environments by pointing in the direction of social creative learning processes, as well as the technologies for effective and creative learning processes by redirecting the focus from what has been labeled “traditional computer-based learning environments” towards user-driven learning networks. Thus, this paper proposes the concept of netlearning as a general label for the traditional use of computer-based learning environments as education tools and then, it suggests the concept of learning through networks as a challenging concept for addressing user-driven technologies that support social, collaborative and creative learning processes in, via, or outside typical educational settings. The paper is inspired by recent research into the interaction society and the Scandinavian tradition in system development that always have highlighted the importance of user-driven processes, users as creative social individuals, and a perspective on users as creative contributors to both the form, and content of new interaction technologies. The paper ends with a presentation of a participatory design project in which children developed their own computer-based tools for editing film and I present this technology followed by a discussion on user-driven design of learning technologies in which the technology is not just a container for something else, but instead, novel technologies as a tool that directly enable the children to do new things, i.e. to collectively learn through their computer-supported social network.
Designing information system task teams

A theoretical model is suggested for designing information systems task teams based on a contingency approach using characteristics of the task, the environment and types of people as contingency variables. A fourth variable, systems design phase, is also considered for suggesting differences in the staffing and operations of task teams. The basic assumption is that staffing, ways of operating, ways of reaching decisions, and measures of task team effectiveness will vary during the systems development process.
An approximation algorithm for the legal firing sequence problem of Petri nets

The paper proposes an approximation algorithm YWLFS for the legal firing sequence problem, LFS for short, of Petri nets. Solving LFS has wide application to various problems, including the scheduling problems, the minimum initial resource allocation problems and the Petri net reachability problems. As far as we know YWLFS is the only approximation algorithm for LFS, and experimental results show that YWLFS is promising. <<ETX>>
p45NF-E2 represses Gcm1 in trophoblast cells to regulate syncytium formation, placental vascularization and embryonic growth

Absence of the leucine zipper transcription factor p45NF-E2 results in thrombocytopenia, impaired placental vascularization and intrauterine growth restriction (IUGR) in mice. The mechanism underlying the p45NF-E2-dependent placental defect and IUGR remains unknown. Here, we show that the placental defect and IUGR of p45NF-E2 (Nfe2) null mouse embryos is unrelated to thrombocytopenia, establishing that embryonic platelets and platelet-released mediators are dispensable for placentation. Rather, p45NF-E2, which was hitherto thought to be specific to hematopoietic cells, is expressed in trophoblast cells, where it is required for normal syncytiotrophoblast formation, placental vascularization and embryonic growth. Expression of p45NF-E2 in labyrinthine trophoblast cells colocalizes with that of Gcm1, a transcription factor crucial for syncytiotrophoblast formation. In the absence of p45NF-E2, the width of syncytiotrophoblast layer 2 and the expression of Gcm1 and Gcm1-dependent genes (Synb and Cebpa) are increased. In vitro, p45NF-E2 deficiency results in spontaneous syncytiotrophoblast formation, which can be reversed by Gcm1 knockdown. Increased Gcm1 expression in the absence of p45NF-E2 is dependent on enhanced protein acetylation, including post-translational modification of Gcm1. Increasing and inhibiting acetylation in the placenta of wild-type control embryos phenocopies and corrects, respectively, the changes observed in p45NF-E2-deficient embryos. These studies identify a novel function of p45NF-E2 during placental development: in trophoblast cells, p45NF-E2 represses Gcm1 and syncytiotrophoblast formation via acetylation.
Genetic Manipulation of Mycobacterium tuberculosis

This unit includes protocols for the genetic manipulation of Mycobacterium tuberculosis, including nucleic acid extraction (plasmid DNA, genomic DNA, and mRNA), and methods for electroporation (transformation), transduction (including allelic exchange), and transposon mutagenesis. Considerations for working with M. tuberculosis at Biosafety Level 3 containment are also discussed. Curr. Protoc. Microbiol. 6:10A.2. 1‐10A.2. 21. © 2007 by John Wiley & Sons, Inc.
A Modified Shell Element Model Combined with Yld91 Yield Function in Simulating Aluminum Alloy Applied Hydroforming

Hydroforming has been used widely across many industrial fields. Large applied pressure during hydroforming makes it necessary to consider the influence of normal stress in the thickness direction, while in FE simulation, the use of traditional shell element based upon plane-stress assumption is not appropriate in such cases. Here, the traditional shell element is modified by changing the constitutive relation which took into account the normal stress in the thickness direction, and the modified shell element formula is combined with Yld91 yield function to simulate the forming process of Aluminium alloy. Then the element formulation and material model is implemented into the FE code Ls-Dyna by means of USER interface. Two examples are carried out and good correlations are obtained when compared to the traditional shell element and solid element.
The Role of Asserted Resolution in Entity Identity Information Management

– This paper introduces the concept of asserted resolution as a technique for entity resolution. In asserted resolution trusted information sources are used to force the equivalence (or non-equivalence) of entity references and identity structures regardless of matching conditions. The paper proposes five specific forms of assertion to support entity identity information management, the process of storing and maintaining identity information in an information system so that references to an entity can be recognized and labeled with the same identifier over time. The paper also gives a description of the way in which asserted resolution is being implemented in the OYSTER open source entity resolution system.
In Vitro Ischemia Promotes Glutamate-Mediated Free Radical Generation and Intracellular Calcium Accumulation in Hippocampal Pyramidal Neurons

Ischemia-induced cell damage studies have revealed a complex mechanism that is thought to involve glutamate excitotoxicity, intracellular calcium increase, and free radical production. We provide direct evidence that free radical generation occurs in rat CA1 pyramidal neurons of organotypic slices subjected to a hypoxic–hypoglycemic insult. The production of free radicals is temporally correlated with intracellular calcium elevation, as measured by injection of fluo-3 in individual pyramidal cells, using patch electrodes. Free radical production (measured as changes in the fluorescence emission of dihydrorhodamine 123) peaked during reoxygenation and paralleled rising intracellular calcium. Electrophysiological whole-cell recordings revealed membrane potential depolarization and decreased input resistance during the ischemic insult. Glutamate receptor blockade resulted in decreased free radical production and markedly diminished intracellular calcium accumulation, and prevented neuronal depolarization and input resistance decrease during the ischemic episode. These results provide evidence for a direct involvement of glutamate in oxidative damage resulting from ischemic episodes.
Effect of Negative Intrathoracic Pressure on Left Ventricular Outflow Tract Obstruction in Muscular Subaortic Stenosis

To study the effect of respiration and negative intrathoracic pressure on the left ventricular outflow tract gradient in patients with muscular subaortic stenosis, we studied nine patients using various respiratory maneuvers at the time of cardiac catheterization. Deep inspiration decreased the left ventricular outflow tract gradient from 60 ± 11 to 34 ± 6 mm Hg (p < 0.01) and decreased the left ventricular ejection time (corrected for heart rate) from 0.42 ± 0.01 to 0.38 ± 0.01 second (p < 0.001). The Muller maneuver decreased the left ventricular outflow tract gradient from 69 ± 13 to 7 ± 3 mm Hg (p < 0.001) and decreased the corrected left ventricular ejection time from 0.42 ± 0.02 to 0.34 ± 0.01 second (p < 0.01). In keeping with this amelioration of left ventricular outflow tract obstruction, echocardiography showed a reduction or abolition of the systolic anterior motion of the anterior mitral leaflet, and auscultatory and phonocardiographic studies revealed a decrease or abolition of the apical systolic murmur. These findings indicate that negative intrathoracic pressure reduced the left ventricular outflow tract gradient in muscular subaortic stenosis. We believe that negative intrathoracic pressure produced these changes by increasing left ventricular afterload through an increase in left ventricular transmural pressure, resulting in a decrease in the left ventricular outflow tract obstruction. These observations provide an explanation for the decrease in pressure gradient that occurs on inspiration in patients with muscular subaortic stenosis.
Multivariate Zero-Inflated Poisson Models and Their Applications

The zero-inflated Poisson (ZIP) distribution has been shown to be useful for modeling outcomes of manufacturing processes producing numerous defect-free products. When there are several types of defects, the multivariate ZIP (MZIP) model can be useful to detect specific process equipment problems and to reduce multiple types of defects simultaneously. This article proposes types of MZIP models and investigates distributional properties of an MZIP model. Finite-sample simulation studies show that, compared to the method of moments, the maximum likelihood method has smaller bias and variance, as well as more accurate coverage probability in estimating model parameters and zero-defect probability. Real-life examples from a major electronic equipment manufacturer illustrate how the proposed procedures are useful in a manufacturing environment for equipment-fault detection and for covariate effect studies.
Tensor decompositions, alternating least squares and other tales

This work was originally motivated by a classification of tensors proposed by Richard Harshman. In particular, we focus on simple and multiple ‘bottlenecks’, and on ‘swamps’. Existing theoretical results are surveyed, some numerical algorithms are described in details, and their numerical complexity is calculated. In particular, the interest in using the enhanced line search (ELS) enhancement in these algorithms is discussed. Computer simulations feed this discussion. Copyright © 2009 John Wiley & Sons, Ltd.
Graphite Web: web tool for gene set analysis exploiting pathway topology

Graphite web is a novel web tool for pathway analyses and network visualization for gene expression data of both microarray and RNA-seq experiments. Several pathway analyses have been proposed either in the univariate or in the global and multivariate context to tackle the complexity and the interpretation of expression results. These methods can be further divided into ‘topological’ and ‘non-topological’ methods according to their ability to gain power from pathway topology. Biological pathways are, in fact, not only gene lists but can be represented through a network where genes and connections are, respectively, nodes and edges. To this day, the most used approaches are non-topological and univariate although they miss the relationship among genes. On the contrary, topological and multivariate approaches are more powerful, but difficult to be used by researchers without bioinformatic skills. Here we present Graphite web, the first public web server for pathway analysis on gene expression data that combines topological and multivariate pathway analyses with an efficient system of interactive network visualizations for easy results interpretation. Specifically, Graphite web implements five different gene set analyses on three model organisms and two pathway databases. Graphite Web is freely available at http://graphiteweb.bio. unipd.it/.
Fuzzy logic based intelligent control of a variable speed cage machine wind generation system

The paper describes a variable speed wind generation system where fuzzy logic principles are used for efficiency optimization and performance enhancement control. A squirrel cage induction generator feeds the power to double-sided pulse width modulated converter system which pumps power to a utility grid or can supply to an autonomous system. The generation system has fuzzy logic control with vector control in the inner loops. A fuzzy controller tracks the generator speed with the wind velocity to extract the maximum power. A second fuzzy controller programs the machine flux for light load efficiency improvement, and a third fuzzy controller gives robust speed control against wind gust and turbine oscillatory torque. The complete control system has been developed, analysed, validated by simulation study, and then performances have been evaluated in detail. <<ETX>>
Management Accounting Theory Revisited: Seeking to Increase Research Relevance

Management accounting research has recently been suffering, as its relevance is being seriously questioned. For academic research output to be relevant it should gain scholars' attention and have an impact upon practice, and should address groups with interests beyond the managerial elite. For this a theoretical approach needs to be adopted that addresses the various societal elements that organisations should engage with, such as the environment and social aspects. The theory derives from existing theories used in accounting. However, to gain and maintain relevance with regard to practice, the theory needs to be built based on empirical input from practicing accountants. Thus, several mini- case studies of accountants in practice were undertaken in order inform the theoretical framework. The definitions of management accounting, theory and practice are revisited to discuss the diverse approaches to theories in management accounting. Recommendations for future research are to apply the framework in positivist and interpretive studies.
A Hybrid Recommendation Method with Reduced Data for Large-Scale Application

Most recommendation algorithms attempt to alleviate information overload by identifying which items a user will find worthwhile. Content-based (CB) filtering uses the features of items, whereas collaborative filtering (CF) relies on the opinions of similar customers to recommend items. In addition to these techniques, hybrid methods have also been suggested to improve the performance of recommendation algorithms. However, even though recent hybrid methods have helped to avoid certain limitations of CB and CF, scalability and sparsity are still major problems in large-scale recommendation systems. In order to overcome these problems, this paper proposes a novel hybrid recommendation algorithm HYRED, which combines CF using the modified Pearson's binary correlation coefficients with CB filtering using the generalized distance-to-boundary-based rating. In the proposed recommendation system, the nearest and farthest neighbors of a target customer are utilized to yield a reduced dataset of useful information by avoiding scalability and sparsity problem when confronted by tremendous volumes of data. The use of reduced datasets enables us not only to lessen the computing effort, but also to improve the performance of recommendations. In addition, a generalized method to combine CF and CB system into a hybrid recommendation system is proposed by developing on the normalization metric. We have used this HYRED algorithm to experiment with all possible combination of CF and statistical-learning-based CB filtering. These experiments have shown that the use of reduced datasets saves computational time, and neighbor information improves performance.