Miracle-dz/UniFAR-FTUs huggingface dataset:
A local regulatory network around three NAC transcription factors in stress responses and senescence in Arabidopsis leaves

Summary A model is presented describing the gene regulatory network surrounding three similar NAC transcription factors that have roles in Arabidopsis leaf senescence and stress responses. ANAC019, ANAC055 and ANAC072 belong to the same clade of NAC domain genes and have overlapping expression patterns. A combination of promoter DNA/protein interactions identified using yeast 1-hybrid analysis and modelling using gene expression time course data has been applied to predict the regulatory network upstream of these genes. Similarities and divergence in regulation during a variety of stress responses are predicted by different combinations of upstream transcription factors binding and also by the modelling. Mutant analysis with potential upstream genes was used to test and confirm some of the predicted interactions. Gene expression analysis in mutants of ANAC019 and ANAC055 at different times during leaf senescence has revealed a distinctly different role for each of these genes. Yeast 1-hybrid analysis is shown to be a valuable tool that can distinguish clades of binding proteins and be used to test and quantify protein binding to predicted promoter motifs.
Enabling commodity environmental sensor networks using multi-attribute combinatorial marketplaces

Large scale distributed e-infrastructures are emerging as commodity resource platforms. The next generation of commodity e-infrastructures will encapsulate the physical or tangible world by integrating ubiquitous sensors. Cheap environmental and physiological sensors are being increasingly deployed by many commercial organisations. The process of discovering and accessing commercially available resources requires a market for providers and consumers to trade these resources. This paper argues that developing a market will encourage the commoditisation of environmental sensor networks. It presents an overall architecture and adopts algorithms to support the trading of commodity environmental sensor networks.
Transductive Learning over Graphs : Incremental Assessment

Graphs constitute a most natural way to represent problems involving finite or countable universes. This might be especially so in the context of bio-informatics (e.g. for protein-interaction graphs), collaborative filtering, the analysis of social networks and citation graphs, and to various problems in operations research in the context of incomplete information. A further argument for using graphs for characterizing learning problems was found in the connection it makes to the literature on network flow algorithms and other deep results of combinatorial optimization problems.
Changes in heart rate circadian rhythm following exercise in middle-aged men

Aerobic fitness and exercise have been associated with improved cardiovascular health. Health effects of exercise may be associated with the circadian rhythm of the heart and may specifically reduced the risk of heart attacks during high-risk periods over the 24 hours. Linear and nonlinear heart rate variability (HRV) measures indicate the degree of heart rate modulation by the parasympathetic and sympathetic branches of the autonomic nervous system. Twenty-one sedentary middle-aged men underwent an 8-week moderate-volume exercise program and 24-hour heart rate recordings were obtained prior and following the exercise period. Temporal dynamic changes over the 24-hour period were calculated using the complex correlation measure (CCM) derived from the Poincaré Plot and analyzed in 1-hour intervals. The maximum significant differences between pre and post moderate-volume exercise were between the morning hours of 8.30 to 9.30 AM (p= 0.011) and in the afternoon between 4.00 and 5.00 PM (p=0.021). In the morning the temporal dynamics (mean ± sd) increased from 0.1±0.02 to 0.15±0.06. In the afternoon period the increase was from 0.11±0.04 to 0.14±0.05. An increase in CCM indicates a more complex temporal dynamics of the heart rate and an improved parasympathetic influence.
Obesity Affects Mitochondrial Citrate Synthase in Human Omental Adipose Tissue

The activities of some key enzymes in mitochondria from 135 human omental adipose tissue samples of obese and nonobese patients were analyzed for potential association with the patients' state of obesity. The activities of respiratory complexes I and II as well as citrate synthase in isolated mitochondria were measured using spectrophotometric enzyme assays. ATP generation of mitochondria was determined with a bioluminescence assay. Protein levels of citrate synthase were quantified by western blot. The rates of ATP generation and the enzymatic activities of complexes I and II did not display associations with age, gender, obesity, or diabetes. By contrast, the enzymatic activities of citrate synthase and its protein levels were significantly reduced in obesity as compared to controls. In diabetic patients, protein levels but not enzymatic activities of citrate synthase were elevated. Thus, this investigation based on enzymatic assay and determination of protein levels revealed that the development of obesity is associated with a significant impact on citrate synthase in mitochondria of human omental adipose tissue. The state of obesity appears to affect mitochondrial function in human omental adipose tissue by limiting this key enzyme of the tricarboxylic acid cycle rather than by limiting the activities of respiratory chain enzymes.
On the relationships between user profiles and navigation sessions in virtual communities: A data-mining approach

In this paper the analysis and Data-Mining of a large data-set related to a very popular Italian Virtual Community is presented. The Community is constituted by more than half-million registered users, each characterized by a unique nickname and a personal "profile" filled during a registration procedure, on a voluntary basis. Two data-sets have been considered: the Data-Base of the Users (nicknames and profiles), and the log-file of the server hosting the Community web-site. This work is constituted by three main parts: 1) analysis and clustering of the User Data-Base; 2) sessionization of the log-file and clustering of the navigation session database; 3) correlation of User clusters and navigation session clusters. This analysis provides a complete and full-rounded picture of the Virtual Community.
Pre‐synaptic and post‐synaptic neuronal activity supports the axon development of callosal projection neurons during different post‐natal periods in the mouse cerebral cortex

Callosal projection neurons, one of the major types of projection neurons in the mammalian cerebral cortex, require neuronal activity for their axonal projections [H. Mizuno et al. (2007) J. Neurosci. , 27, 6760–6770; C. L. Wang et al. (2007) J. Neurosci. , 27, 11334–11342]. Here we established a method to label a few callosal axons with enhanced green fluorescent protein in the mouse cerebral cortex and examined the effect of pre‐synaptic/post‐synaptic neuron silencing on the morphology of individual callosal axons. Pre‐synaptic/post‐synaptic neurons were electrically silenced by Kir2.1 potassium channel overexpression. Single axon tracing showed that, after reaching the cortical innervation area, green fluorescent protein‐labeled callosal axons underwent successive developmental stages: axon growth, branching, layer‐specific targeting and arbor formation between post‐natal day (P)5 and P9, and the subsequent elaboration of axon arbors between P9 and P15. Reducing pre‐synaptic neuronal activity disturbed axon growth and branching before P9, as well as arbor elaboration afterwards. In contrast, silencing post‐synaptic neurons disturbed axon arbor elaboration between P9 and P15. Thus, pre‐synaptic neuron silencing affected significantly earlier stages of callosal projection neuron axon development than post‐synaptic neuron silencing. Silencing both pre‐synaptic and post‐synaptic neurons impaired callosal axon projections, suggesting that certain levels of firing activity in pre‐synaptic and post‐synaptic neurons are required for callosal axon development. Our findings provide in‐vivo evidence that pre‐synaptic and post‐synaptic neuronal activities play critical, and presumably differential, roles in axon growth, branching, arbor formation and elaboration during cortical axon development.
Interdisciplinary Journal of E-learning and Learning Objects Formerly the Interdisciplinary Journal of Knowledge and Learning Objects towards a Comprehensive Learning Object Metadata: Incorporation of Context to Stipulate Meaningful Learning and Enhance Learning Object Reusability

In recent years, the learning object (LO) concept has been introduced to allow sharing of smaller and portable learning materials on the Internet. Its features, concept, components, and other related matters have been fairly debated among researchers and practitioners. Attempts have been made to derive definition, model, and its working application. However, the failure to embed learning context and pedagogical instructional role within metadata has contributed to the significance of LO educational values. Despite the efforts taken by various research groups and researchers to propose metadata that exhibit the LO pedagogical role, the accomplishment of these works is geared towards specific education environments or institutions. Therefore, it is desirable to attain new metadata elements that will capture the LO context and pedagogical aspects and increase the reusability features applicable to any education setting or environment. It is the intention of this paper to describe the work done in providing a new metadata element based on theoretical analysis.
A Biomedical Information Retrieval System based on Clustering for Mobile Devices

Information overload caused by the increasing availability of online texts and publications of interest is a problem that increases when such information is necessary for decision making, as in the biomedical field. It is in this domain where we present an information retrieval system for mobile devices. Traditional indexing and search processes are enriched with the feature of returning the results in clusters according to their content.
Conscious and Unconscious Thought in Risky Choice: Testing the Capacity Principle and the Appropriate Weighting Principle of Unconscious Thought Theory

Daily we make decisions ranging from the mundane to the seemingly pivotal that shape our lives. Assuming rationality, all relevant information about one’s options should be thoroughly examined in order to make the best choice. However, some findings suggest that under specific circumstances thinking too much has disadvantageous effects on decision quality and that it might be best to let the unconscious do the busy work. In three studies we test the capacity assumption and the appropriate weighting principle of Unconscious Thought Theory using a classic risky choice paradigm and including a “deliberation with information” condition. Although we replicate an advantage for unconscious thought (UT) over “deliberation without information,” we find that “deliberation with information” equals or outperforms UT in risky choices. These results speak against the generality of the assumption that UT has a higher capacity for information integration and show that this capacity assumption does not hold in all domains. Furthermore, we show that “deliberate thought with information” leads to more differentiated knowledge compared to UT which speaks against the generality of the appropriate weighting assumption.
Chest radiographic findings in patients with HIV/AIDS and pulmonary tuberculosis

The study describes the main chest radiographic changes in people living with HIV/AIDS and pulmonary tuberculosis, confirmed by sputum culture. This was a descriptive study involving a total of 42 sputum tests from 42 people living with HIV/AIDS and a clinical suspicion of pulmonary tuberculosis. All patients attended two referral hospitals in Recife-PE, Brazil, between August 2009 and January 2012. The most common isolated radiological change was parenchymal consolidation, encountered in six (14.3%) patients, followed by patterns of interstitial infiltrate, diffuse micronodular (miliary), and an association between interstitial infiltrate and parenchymal consolidation, each being encountered in five (11.9%) patients. No statistically significant difference was observed between the radiological findings and CD4 T-cell counts, p = 0.680.
Omega-3 fatty acids and incident type 2 diabetes: a systematic review and meta-analysis

The relationship between omega-3 polyunsaturated fatty acids (n-3 PUFA) from seafood sources (eicosapentaenoic acid, EPA; docosahexaenoic acid, DHA) or plant sources (alpha-linolenic acid, ALA) and risk of type 2 diabetes mellitus (DM) remains unclear. We systematically searched multiple literature databases through June 2011 to identify prospective studies examining relations of dietary n-3 PUFA, dietary fish and/or seafood, and circulating n-3 PUFA biomarkers with incidence of DM. Data were independently extracted in duplicate by 2 investigators, including multivariate-adjusted relative risk (RR) estimates and corresponding 95 % CI. Generalized least-squares trend estimation was used to assess dose–response relationships, with pooled summary estimates calculated by both fixed-effect and random-effect models. From 288 identified abstracts, 16 studies met inclusion criteria, including 18 separate cohorts comprising 540 184 individuals and 25 670 cases of incident DM. Consumption of fish and/or seafood was not significantly associated with DM (n = 13 studies; RR per 100 g/d = 1·12, 95 % CI = 0·94, 1·34); nor were consumption of EPA+DHA (n = 16 cohorts; RR per 250 mg/d = 1·04, 95 % CI = 0·97, 1·10) nor circulating levels of EPA+DHA biomarkers (n = 5 cohorts; RR per 3 % of total fatty acids = 0·94, 95 % CI = 0·75, 1·17). Both dietary ALA (n = 7 studies; RR per 0·5 g/d = 0·93, 95 % CI = 0·83, 1·04) and circulating ALA biomarker levels (n = 6 studies; RR per 0·1 % of total fatty acid = 0·90, 95 % CI = 0·80, 1·00, P = 0·06) were associated with non-significant trend towards lower risk of DM. Substantial heterogeneity (I2~80 %) was observed among studies of fish/seafood or EPA+DHA and DM; moderate heterogeneity ( < 55 %) was seen for dietary and biomarker ALA and DM. In unadjusted meta-regressions, study location (Asia vs. North America/Europe), mean BMI, and duration of follow-up each modified the association between fish/seafood and EPA+DHA consumption and DM risk (P-interaction ≤ 0·02 each). We had limited statistical power to determine the independent effect of these sources of heterogeneity due to their high collinearity. The overall pooled findings do not support either major harms or benefits of fish/seafood or EPA+DHA on development of DM, and suggest that ALA may be associated with modestly lower risk. Reasons for potential heterogeneity of effects, which could include true biologic heterogeneity, publication bias, or chance, deserve further investigation.
A comparative study of predictive algorithms for business analytics and decision support systems: Finance as a case study

Stock market prediction is regarded as a challenging task of financial time-series prediction. There have been many studies using machine learning techniques in this area. A large number of successful applications have shown that regression algorithms can be very useful tools for time-series modelling and forecasting. In this paper we run a comparative study of three of these algorithms: Multiple Linear Regression, Support Vector Regression and Decision Tree Regression in order to determine their performances in term of implementing financial time series forecasts. To assess the performance of these algorithms, we have conducted experiments using L'Oréal financial dataset. The results exhibit that support vector regression produced the best forecasts.
Tight Bounds For Distributed MST Verification

This paper establishes tight bounds for the Minimum-weight Spanning Tree (MST) verification problem in the distributed setting. Specifically, we provide an MST verification algorithm that achieves simultaneously tilde ~O(|E|) messages and $tilde O(sqrt{n} + D) time, where |E| is the number of edges in the given graph G and D is G's diameter. On the negative side, we show that any MST verification algorithm must send Omega(|E|) messages and incur ~Omega(sqrt{n} + D) time in worst case. Our upper bound result appears to indicate that the verification of an MST may be easier than its construction, since for MST construction, both lower bounds of Omega(|E|) messages and Omega(sqrt{n} + D) time hold, but at the moment there is no known distributed algorithm that constructs an MST and achieves simultaneously tilde O(|E|) messages and ´~O(sqrt{n} + D) time. Specifically, the best known time-optimal algorithm (using ~O(sqrt{n} + D) time) requires O(|E|+n^{3/2}) messages, and the best known message-optimal algorithm (using ~O(|E|) messages) requires O(n) time. On the other hand, our lower bound results indicate that the verification of an MST is not significantly easier than its construction.
Performance Analysis of Dynamic Finite Versioning Schemes: Storage Cost vs. Obsolescence

Dynamic finite versioning (DFV) schemes are an effective approach to concurrent transaction and query processing, where a finite number of consistent, but maybe slightly out-of-date, logical snapshots of the database can be dynamically derived for query access. In DFV, the storage overhead for keeping additional versions of changed data to support the logical snapshots and the amount of obsolescence faced by queries are two major performance issues. We analyze the performance of DFV, with emphasis on the trade-offs between the storage cost and obsolescence. We develop analytical models based on a renewal process approximation to evaluate the performance of DFV using M/spl ges/2 snapshots. Asymptotic closed form results for high query arrival rates are given for the case of two snapshots. Simulation is used to validate the analytical models and to evaluate the tradeoffs between various strategies for advancing snapshots when M>2. The results show that (1) the analytical models match closely with simulation; (2) storage cost and obsolescence are sensitive to the snapshot advancing strategies, and (3) usually, increasing the number of snapshots demonstrates a trade-off between storage overhead and query obsolescence. For cases with skewed accessor low update rates, a small increase in the number of snapshots beyond two can substantially reduce the obsolescence. Such a reduction in obsolescence is more significant as the coefficient of variation of the query length distribution becomes larger. Moreover, for very low update rates, a large number of snapshots can be used to reduce the obsolescence to almost zero without increasing the storage overhead.
Review of interference avoidance schemes in femtocell networks

Femtocell is a solution to increase the system capacity and coverage to meet the high demand of the next generation of services on broadband wireless access. However, the deployment of a new femtocell layer may have an undesired impact on the performance of the macrocell layer. The allocation of spectrum resources and the avoidance of electromagnetic interference are some of the more urgent challenges that operators face before femtocells become widely deployed. In this paper different interference avoidance schemes are described and compared. Special attention is paid to the use of uplink and downlink power control and self-configuration and self-optimization techniques for the avoidance of interference. From the review, we conclude that frequency planning is suitable for interference avoidance schemes for unplanned location of femtocells deployment.
An Evolutionarily Conserved Innate Immunity Protein Interaction Network*

Background: Innate immunity affects infectious and inflammatory diseases. Results: Using RNAi and proteomic data, we identified a novel evolutionarily conserved protein network that modulates innate immunity. Conclusion: Studies using mutant C. elegans and mice demonstrate the utility of this network for disease investigation. Significance: This innate immunity network provides a novel set of targets for future innate immunity disease studies. The innate immune response plays a critical role in fighting infection; however, innate immunity also can affect the pathogenesis of a variety of diseases, including sepsis, asthma, cancer, and atherosclerosis. To identify novel regulators of innate immunity, we performed comparative genomics RNA interference screens in the nematode Caenorhabditis elegans and mouse macrophages. These screens have uncovered many candidate regulators of the response to lipopolysaccharide (LPS), several of which interact physically in multiple species to form an innate immunity protein interaction network. This protein interaction network contains several proteins in the canonical LPS-responsive TLR4 pathway as well as many novel interacting proteins. Using RNAi and overexpression studies, we show that almost every gene in this network can modulate the innate immune response in mouse cell lines. We validate the importance of this network in innate immunity regulation in vivo using available mutants in C. elegans and mice.
Three novel CFTR polymorphic repeats improve segregation analysis for cystic fibrosis.

BACKGROUND Molecular diagnosis for cystic fibrosis (CF) is based on the direct identification of mutations in the CFTR gene [cystic fibrosis transmembrane conductance regulator (ATP-binding cassette sub-family C, member 7)] (detection rate about 90% with scanning procedures) and on segregation analysis of intragenic polymorphisms for carrier and prenatal diagnosis in about 20% of CF families in which 1 or both causal mutations are unknown. METHODS We identified 3 novel intragenic polymorphic repeats (IVS3polyA, IVS4polyA, and IVS10CA repeats) in the CFTR gene and developed and validated a procedure based on the PCR followed by capillary electrophoresis for large-scale analysis of these polymorphisms and the 4 previously identified microsatellites (IVS1CA, IVS8CA, IVS17bTA, and IVS17bCA repeats) in a single run. We validated the procedure for both single- and 2-cell samples (for a possible use in preimplantation diagnosis), and on a large number of CF patients bearing different genotypes and non-CF controls. RESULTS The allelic distribution and heterozygosity results suggest that the 3 novel polymorphisms strongly contribute to carrier and prenatal diagnosis of CF in families in which 1 or both causal mutations have not been identified. At least 1 of the 4 previously identified microsatellites was informative in 78 of 100 unrelated CF families; at least 1 of all 7 polymorphisms was informative in 98 of the families. Finally, the analysis of haplotypes for the 7 polymorphisms revealed that most CF mutations are associated with different haplotypes, suggesting multiple slippage events but a single origin for most CFTR mutations. CONCLUSIONS The analysis of the 7 polymorphisms is a rapid and efficient tool for routine carrier, prenatal, and preimplantation diagnosis of CF.
N OVEL 3D M ATCHING S ELF -L OCALISATION A LGORITHM

A new and fast methodology is discussed as a solution to pinpointing the location of a robot called RobVigil, in a robust way, without environment preparation, even in dynamic scenarios. This solution does not require a high computational power. Firstly, the EKF-SLAM is used to find the location of the vehicle, allowing to map the surrounding area in the 3D space. Afterwards, the constructed map is used in a 3D matching algorithm during the normal operation of the vehicle to pinpoint its location. The 3D matching algorithm uses data from a tilting Laser Range Finder. Experimental results on the performance and accuracy of the proposed method are presented in this paper.