Miracle-dz/UniFAR-FTUs huggingface dataset:
Diet-induced obesity and hepatic gene expression alterations in C 57 BL / 6 J and ICAM-1-deficient mice

Gregoire, Francine M. , Qin Zhang, Steven J. Smith, Carmen Tong, David Ross, Henry Lopez, and David B. West. Diet-induced obesity and hepatic gene expression alterations in C57BL/6J and ICAM-1-deficient mice. Am J Physiol Endocrinol Metab 282: E703–E713, 2002. First published October 2, 2001; 10.1152/ajpendo.00072. 2001. —The effects of high-fat feeding on the development of obesity were evaluated in intercellular adhesion molecule-1 (ICAM-1) knockout and C57BL/6J (B6) male mice fed a high-fat diet for 50 days. Serum and tissues were collected at baseline and after 1, 11, and 50 days on the diet. After 11 days on the diet, ICAM-1-deficient, but not B6, mice developed fatty livers and showed a significant increase in inguinal fat pad weight. At day 50, ICAM-1-deficient mice weighed less, and their adiposity index and circulating leptin levels were significantly lower than those of B6 controls. To better understand the early differential response to the diet, liver gene expression was analyzed at three time points by use of Affymetrix GeneChips. In both strains, a similar pattern of gene expression was detected in response to the high-fat diet. However, sterol regulatory element-binding protein-1, apolipoprotein A4, and adipsin mRNAs were significantly induced in ICAM1-deficient livers, suggesting that these genes and their associated pathways may be involved in the acute diet response observed in the knockout mice.
Constraint-free Graphical Model with Fast Learning Algorithm

In this paper, we propose a simple, versatile model for learning the structure and parameters of multivariate distributions from a data set. Learning a Markov network from a given data set is not a simple problem, because Markov networks rigorously represent Markov properties, and this rigor imposes complex constraints on the design of the networks. Our proposed model removes these constraints, acquiring important aspects from the information geometry. The proposed parameter- and structure-learning algorithms are simple to execute as they are based solely on local computation at each node. Experiments demonstrate that our algorithms work appropriately.
Modeling Database Federations in Terms of Evolving Agents (cid:3)

For advanced information systems, the interoperation between heterogeneous database systems which autonomously manage their existing, independently developed databases is a fundamental issue. Thus, organization's data is virtually represented at the global level in a uniform way and transparent access to distributed and heterogeneous data sources becomes possible. In this paper, we present a formal agent-based approach to modeling federated database systems. We identify some fundamental properties of agents which act as mediators between di(cid:11)erent, possibly heterogeneous and autonomous database systems. Finally, we brie(cid:13)y sketch an agent speci(cid:12)cation framework which may provide the basis for specifying highly dynamic and scalable information systems based on database federations.
Issues in Informing Science and Information Technology Manufacturing Organizational Memory : Logged Conversation Thread Analysis

Though not especially media-rich, mailing lists remain in use and retain popularity for their builtin technological controls and their capability to “reply” to a message (“continuing a thread”). The motivation for extracting knowledge fragments from the unstructured text of mailing lists is compelling, though successes doing so may be considered only partial because it requires mental processing, or a certain cognitive effort, that complicates automation. Cognitive psychology distinguishes the Long Term Memory (LTM), which may be compared to text thread storage, from the Working Memory (WM), which initiates the retrieval of knowledge fragments stored in the LTM. Searching by subject, date, and time stamp ranges, and by keyword-inclusive fragments, constitutes the commonly used methods for executing sequential LTM retrieval. Retrieval can, however, be greatly enhanced by automatically gleaning certain classes of threads from the entire structure and displaying them alongside other properties. Here, we describe automatic “class” extraction and its effect on OM manufacturing and LTM retrieval.
Towards a Generic Control Architecture of Rescue Robot Systems

This paper proposes a generic control architecture for robot systems performing search and rescue operations. The multimodal attention is introduced as an important factor in the design and implementation of control architecture for robot systems. We also considered a reliable learning ability of robot system about an explored environment as another important aspect to increase the robustness of decision processes. These decision processes include safe navigation through cluttered environment, search for victims in complex scenarios and obtaining a map of targeted environment.
Beyond the refactoring browser: advanced tool support for software refactoring

Current refactoring tools only provide support for performing selected refactorings. We show how tool support can be provided for the preparatory phases of refactoring as well, by determining when a software application should be refactored and which refactoring(s) in particular should be applied. We implemented a tool to detect bad smells and to propose adequate refactorings based on these smells, and validated this tool by carrying out experiments in three concrete case studies: the Soul application, the Smalltalk collection hierarchy, and the HotDraw application framework. We also show how our tool complements the Smalltalk refactoring browser.
The heat‐shock protein/chaperone network and multiple stress resistance

Summary Crop yield has been greatly enhanced during the last century. However, most elite cultivars are adapted to temperate climates and are not well suited to more stressful conditions. In the context of climate change, stress resistance is a major concern. To overcome these difficulties, scientists may help breeders by providing genetic markers associated with stress resistance. However, multistress resistance cannot be obtained from the simple addition of single stress resistance traits. In the field, stresses are unpredictable and several may occur at once. Consequently, the use of single stress resistance traits is often inadequate. Although it has been historically linked with the heat stress response, the heat‐shock protein (HSP)/chaperone network is a major component of multiple stress responses. Among the HSP/chaperone ‘client proteins’, many are primary metabolism enzymes and signal transduction components with essential roles for the proper functioning of a cell. HSPs/chaperones are controlled by the action of diverse heat‐shock factors, which are recruited under stress conditions. In this review, we give an overview of the regulation of the HSP/chaperone network with a focus on Arabidopsis thaliana. We illustrate the role of HSPs/chaperones in regulating diverse signalling pathways and discuss several basic principles that should be considered for engineering multiple stress resistance in crops through the HSP/chaperone network.
Dysregulation of Complement System and CD4+ T Cell Activation Pathways Implicated in Allergic Response

Allergy is a complex disease that is likely to involve dysregulated CD4+ T cell activation. Here we propose a novel methodology to gain insight into how coordinated behaviour emerges between disease-dysregulated pathways in response to pathophysiological stimuli. Using peripheral blood mononuclear cells of allergic rhinitis patients and controls cultured with and without pollen allergens, we integrate CD4+ T cell gene expression from microarray data and genetic markers of allergic sensitisation from GWAS data at the pathway level using enrichment analysis; implicating the complement system in both cellular and systemic response to pollen allergens. We delineate a novel disease network linking T cell activation to the complement system that is significantly enriched for genes exhibiting correlated gene expression and protein-protein interactions, suggesting a tight biological coordination that is dysregulated in the disease state in response to pollen allergen but not to diluent. This novel disease network has high predictive power for the gene and protein expression of the Th2 cytokine profile (IL-4, IL-5, IL-10, IL-13) and of the Th2 master regulator (GATA3), suggesting its involvement in the early stages of CD4+ T cell differentiation. Dissection of the complement system gene expression identifies 7 genes specifically associated with atopic response to pollen, including C1QR1, CFD, CFP, ITGB2, ITGAX and confirms the role of C3AR1 and C5AR1. Two of these genes (ITGB2 and C3AR1) are also implicated in the network linking complement system to T cell activation, which comprises 6 differentially expressed genes. C3AR1 is also significantly associated with allergic sensitisation in GWAS data.
LSHTM Research Online

Disability is a key social identity or social category that is associated with significant social disadvantage. For men, having a disability can be discordant with their masculine identity. Self-reliance is one component of masculinity that is known to be important to men with disabilities, however it is also known to be associated with adverse mental health outcomes in the broader adult male population. Intersectionality approaches offer a means of examining the way that the effect of self-reliance on mental health might vary between those with and without a disability. Among a sample of 12,052 men aged 18–55 years from the Ten-to-Men study, we used effect measure modification (EMM) to examine the way that self-reliance modifies the relationship between disability and depressive symptoms. Disability was assessed using the Washington Group Short Set of questions, which capture functional limitations. Results showed that men with disabilities who reported higher conformity to self- reliance norms had much worse mental health than non-disabled men with low conformity to self-reliance, as measured in terms of depressive symptoms (PRR: 9.40, 95%CI 7.88, 11.22, p-value<0.001). We found evidence of positive EMM of depressive symptoms by conformity to self-reliance on the additive scale (RERI: 2.84, 95%CI 1.26, 4.42, p-value<0.001). These results provide evidence that high conformity to self-reliance norms exerts a particularly damaging effect on the mental health of men with disabilities. Given that men with disabilities are more likely to rely on help and support from others, these results provide important insights for the delivery of services to men with disability.
Analysis of Socio-Economic Conditions Influencing Adoption of Agroforestry Practices

Recent years have witnessed a significant imp rovement in the adoption and promotion of agroforestry technologies among s mallholder farmers world-wide and in particu lar, developing countries. This paper examines the main socio-economic factors related to farmers' decision to adopt and pro mote agroforestry practices. While environ mental factors such as topography, soil types and climat ic factors affect plant growth and development, findings suggest that the main socio-economic factors that determine the actual occurrence of agroforestry are household security, access to capital and incentives, labour, gender, land tenure, farm size and knowledge for management. Sustainable development through agroforestry can be achieved through genuine and continuous involvement of farmers in agroforestry activities. Recognizing and addressing fundamental factors that determine involvement of people in develop mental activ ities predisposes an agroforestry project to genuine local participat ion.
Altered blood pressure during sleep in normotensive subjects with type I diabetes.

This study was designed to examine the circadian pattern of blood pressure in children and young adults with type I diabetes who were completely normotensive by standard criteria. Forty-five patients and the same number of age- and sex-matched control subjects were studied. In diabetic children of 10-14 years of age, the nocturnal fall in systolic and diastolic blood pressures was intact. In diabetics of 15-20 years of age, the fall in systolic blood pressure was blunted; in diabetics of 21-37 years of age, the fall in both systolic and diastolic blood pressures during sleep was blunted. When data from all diabetic subjects were pooled and analyzed in a multiple linear regression model, mean blood pressure during sleep correlated best with urinary albumin excretion (r = 0.60). On the basis of this finding, we subdivided our patients into two groups: a microalbuminuric group (urinary albumin excretion > 30 mg per 24 hours; mean, 160.3 +/- 29.7; n = 11) and a normoalbuminuric group (urinary albumin excretion < 30 mg per 24 hours; mean, 6.6 +/- 6.5; n = 34). Both systolic and diastolic blood pressures during sleep were higher in microalbuminuric (121.1 +/- 3.3 and 69.3 +/- 2.5 mm Hg, respectively) than in normoalbuminuric diabetics (114.2 +/- 1.8 and 60.1 +/- 1.2 mm Hg, p < 0.05) or control subjects (113.3 +/- 1.2 and 60.1 +/- 1.2 mm Hg, p < 0.05). (ABSTRACT TRUNCATED AT 250 WORDS)
COMPARISON OF THE HEMODYNAMIC CHANGES AS SEEN IN PATIENTS UNDERGOING CESAREAN SECTION WITH HYPERBARIC BUPIVACAINE VERSUS ISOBARIC

OBJECTIVE: The purpose of the study is to compare and assess the hemodynamic and associated changes that occur in the patient population operated for a lower segment cesarean section (LSCS), when they are given 0.5% hyperbaric bupivacaine versus 0.5% isobaric bupivacaine. METHOD: The method of study is a prospective double blind randomized trial of 60 patients belonging to the ASA 1 and ASA 2 category, who underwent a lower segment cesarean section, and comparative analysis of the efficacy and associated hemodynamic changes of hyperbaric with isobaric bupivacaine. The patient population was segmented into two groups, group A receiving hyperbaric bupivacaine 0.5% as 2.5ml ( 12.5mg dose ) and the second group designated as, group B receiving isobaric bupivacaine 0.5% as 2.5ml ( 12.5mg dose) intrathecally. The resultant sensory and motor blockade was determined using pin prick and bromage scale respectively. RESULTS: There was a significant difference found among the two groups under study, when compared at 3min interval regarding the sensory blockade. The level of T6 block was reached in 37% (n=10) patients belonging to group A and 77% (n= 17) patients in group B. It was observed that there was no significant change among the two groups at 5min interval regarding sensory and motor blockade respectively. The immediate sensory blockade with isobaric bupivacaine in group B produced greater decrease in the systolic and mean arterial blood pressure when contrasted with hyperbaric bupivacaine in group A at 5min interval, but after time interval of 45min there was no statistically significant change observed. CONCLUSION: According to our study the effects of isobaric bupivacaine were more significantly predictable, hence have a higher efficacy, when contrasted against hyperbaric bupivacaine in lower section cesarean section spinal anesthesia. Quick sensory blockade with isobaric bupivacaine was associated with more decrease in blood pressures when contrasted with the hyperbaric bupivacaine, but this result is not statistically significant.
ENTRA: Whole-Systems Energy Transparency

Promoting energy efficiency to a first class system design goal is an important research challenge. Although more energy-efficient hardware can be designed, it is software that controls the hardware; for a given system the potential for energy savings is likely to be much greater at the higher levels of abstraction in the system stack. Thus the greatest savings are expected from energy-aware software development, which is the vision of the EU ENTRA project. This article presents the concept of energy transparency as a foundation for energyaware software development. We show how energy modelling of hardware is combined with static analysis to allow the programmer to understand the energy consumption of a program without executing it, thus enabling exploration of the design space taking energy into consideration. The paper concludes by summarising the current and future challenges identified in the ENTRA project.
I/o-eecient Scientiic Computation Using Tpie I/o-eecient Scientiic Computation Using Tpie

In recent years, I/O-eecient algorithms for a wide variety of problems have appeared in the literature. Thus far, however, systems speciically designed to assist programmers in implementing such algorithms have remained scarce. TPIE is a system designed to ll this void. It supports I/O-eecient paradigms for problems from a variety of domains, including computational geometry, graph algorithms, and scientiic computation. The TPIE interface frees programmers from having to deal not only of explicit read and write calls, but also the complex memory management that must be performed for I/O-eecient computation. In this paper, we discuss applications of TPIE to problems in scientiic computation. We discuss algorithmic issues underlying the design and implementation of the relevant components of TPIE and present performance results of programs written to solve a series of benchmark problems using our current TPIE prototype. Some of the benchmarks we present are based on the NAS parallel benchmarks 5], while others are of our own creation. We demonstrate that the CPU overhead required to manage I/O is small and that even with just a single disk the I/O overhead of I/O-eecient computation ranges from negligible to the same order of magnitude as CPU time. We conjecture that if we use a number of disks in parallel this overhead can be all but eliminated.
LPM: A Systematic Methodology for Concurrent Data Access Pattern Optimization from a Matching Perspective

As applications become increasingly data intensive, conventional computing systems become increasingly inefficient due to data access performance bottlenecks. While intensive efforts have been made in developing new memory technologies and in designing special purpose machines, there is a lack of solutions for evaluating and utilizing recent hardware advancements to address the memory-wall problem in a systematic way. In this study, we present the memory Layered Performance Matching (LPM) methodology to provide a systematic approach for data access performance optimization. LPM uniquely presents and utilizes the data access concurrency, in addition to data access locality, in a memory hierarchical system. The LPM methodology consists of models and algorithms, and is supported with a series of analytic results for its correctness. The rationale of LPM is to reduce the overall data access delay through the matching of data request rate and data supply rate at each layer of a memory hierarchy, with a balanced consideration of data locality, data concurrency, and latency hiding of data flow. Extensive experimentations on both physical platforms and software simulators confirm our theoretical findings, and they show that the LPM approach can be applied in diverse computing platforms and can effectively guide performance optimization of memory systems.
(3S)-1,2,3,4-Tetrahydro-β-carboline-3-carboxylic Acid from Cichorium endivia. L Induces Apoptosis of Human Colorectal Cancer HCT-8 Cells

Cichorium endivia. L, consumed either cooked or eaten raw in salads, is a popular kind of vegetable cultivated all around the World. Its components have been widely used in folk medicine in anti-inflammatory therapy. However, the anti-cancer activity of the components has never been reported. In this study, (3S)-1,2,3,4-tetrahydro-β-carboline-3-carboxylic acid (1), an amino acid isolated from C. endivia. L, was found for the first time to show cytotoxic activity in colorectal cancer cell line HCT-8. Compound 1 at concentrations of 0.5–4 μM induced apoptosis of HCT-8 cells in a dose-dependent manner. The compound 1-induced apoptosis in HCT-8 cells was accompanied by the loss of mitochondrial membrane potential, the activation of caspase-3, caspase-8 and caspase-9, the up-regulation of Bax and the down-regulation of Bcl-2. In addition, compound 1 suppressed the activation of NF-κB, which acts as an inhibitor of apoptosis. Taken together, these results suggested that compound 1 could significantly induce apoptosis of HCT-8 cells through the suppression of NF-κB signaling pathway, and thus can be considered as a potential candidate for developing chemotherapeutic drugs against cancer.
Query Snowball: A Co-occurrence-based Approach to Multi-document Summarization for Question Answering

We propose a new method for query-oriented extractive multi-document summarization. To enrich the information need representation of a given query, we build a co-occurrence graph to obtain words that augment the original query terms. We then formulate the summarization problem as a Maximum Coverage Problem with Knapsack Constraints based on word pairs rather than single words. Our experiments with the NTCIR ACLIA question answering test collections show that our method achieves a pyramid F3-score of up to 0.313, a 36% improvement over a baseline using Maximal Marginal Relevance.
Efficient and reliable schemes for nonlinear diffusion filtering

Nonlinear diffusion filtering in image processing is usually performed with explicit schemes. They are only stable for very small time steps, which leads to poor efficiency and limits their practical use. Based on a discrete nonlinear diffusion scale-space framework we present semi-implicit schemes which are stable for all time steps. These novel schemes use an additive operator splitting (AOS), which guarantees equal treatment of all coordinate axes. They can be implemented easily in arbitrary dimensions, have good rotational invariance and reveal a computational complexity and memory requirement which is linear in the number of pixels. Examples demonstrate that, under typical accuracy requirements, AOS schemes are at least ten times more efficient than the widely used explicit schemes.
Extracting Gene Regulation Networks Using Linear-Chain Conditional Random Fields and Rules

Published literature in molecular genetics may collectively provide much information on gene regulation networks. Dedicated computational approaches are required to sip through large volumes of text and infer gene interactions. We propose a novel sieve-based relation extraction system that uses linear-chain conditional random fields and rules. Also, we introduce a new skip-mention data representation to enable distant relation extraction using first-order models. To account for a variety of relation types, multiple models are inferred. The system was applied to the BioNLP 2013 Gene Regulation Network Shared Task. Our approach was ranked first of five, with a slot error rate of 0.73.
L’ALGORITHME DE METROPOLIS-HASTINGS, UN OUTIL PUISSANT POUR L’ESTIMATION DE MODELES ENVIRONNEMENTAUX. APPLICATION A LA MODÉLISATION DE DONNÉES DE DEMANDE BIOLOGIQUE EN OXYGENE

Environmental scientists often face situations where: (i) stimulus-response relationships are non-linear; (ii) data are rare or imprecise; (iii) facts are uncertain and stimulus-responses relationships are questionable. In this paper, we focus on the first two points. A powerful and easy-to-use statistical method, the Metropolis-Hastings algorithm, allows the quantification of the uncertainty attached to any model response. This stochastic simulation technique is able to reproduce the statistical joint distribution of the whole parameter set of any model. The Metropolis-Hastings algorithm is described and illustrated on a typical environmental model: the biochemical oxygen demand (BOD). The aim is to provide a helpful guideline for further, and ultimately more complex, models. As a first illustration, the MH-method is also applied to a simple regression example to demonstrate to the practitioner the ability of the algorithm to produce valid results.