Miracle-dz/UniFAR-FTUs huggingface dataset:
Flux balance impact degree: a new definition of impact degree to properly treat reversible reactions in metabolic networks

Motivation: Metabolic pathways are complex systems of chemical reactions taking place in every living cell to degrade substrates and synthesize molecules needed for life. Modeling the robustness of these networks with respect to the dysfunction of one or several reactions is important to understand the basic principles of biological network organization, and to identify new drug targets. While several approaches have been proposed for that purpose, they are computationally too intensive to analyze large networks, and do not properly handle reversible reactions. Results: We propose a new model—the flux balance impact degree—to model the robustness of large metabolic networks with respect to gene knock-out. We formulate the computation of the impact of one or several reaction blocking as linear programs, and propose efficient strategies to solve them. We show that the proposed method better predicts the phenotypic impact of single gene deletions on Escherichia coli than existing methods. Availability: https://sunflower.kuicr.kyoto-u.ac. jp/∼tyoyo/fbid/index.html Contact: takutsu@kuicr.kyoto-u.ac. jp or Jean-Philippe.Vert@mines.org Supplementary information: Supplementary data are available at Bioinformatics online.
Towards the Framework of the File Systems Performance Evaluation Techniques and the Taxonomy of Replay Traces

This is the era of High Performance Computing (HPC). There is a great demand of the best performance evaluation techniques for the file and storage systems. The task of evaluation is both necessary and hard. It gives in depth analysis of the target system and that becomes the decision points for the users. That is also helpful for the inventors or developers to find out the bottleneck in their systems. In this paper many performance evaluation techniques are described for file and storage system evaluation and the main stress is given on the important one that is replay traces. A survey has been done for the performance evaluation techniques used by the researchers and on the replay traces. And the taxonomy of the replay traces is described. The some of the popular replay traces are just like, Tracefs [1], //Trace [2], Replayfs [3] and VFS Interceptor [12]. At last we have concluded all the features that must be considered when we are going to develop the new tool for the replay traces. The complete work of this paper shows that the storage system developers must care about all the techniques which can be used for the performance evaluation of the file systems. So they can develop highly efficient future file and storage systems.
C-SPADE: a web-tool for interactive analysis and visualization of drug screening experiments through compound-specific bioactivity dendrograms

Abstract The advent of polypharmacology paradigm in drug discovery calls for novel chemoinformatic tools for analyzing compounds’ multi-targeting activities. Such tools should provide an intuitive representation of the chemical space through capturing and visualizing underlying patterns of compound similarities linked to their polypharmacological effects. Most of the existing compound-centric chemoinformatics tools lack interactive options and user interfaces that are critical for the real-time needs of chemical biologists carrying out compound screening experiments. Toward that end, we introduce C-SPADE, an open-source exploratory web-tool for interactive analysis and visualization of drug profiling assays (biochemical, cell-based or cell-free) using compound-centric similarity clustering. C-SPADE allows the users to visually map the chemical diversity of a screening panel, explore investigational compounds in terms of their similarity to the screening panel, perform polypharmacological analyses and guide drug-target interaction predictions. C-SPADE requires only the raw drug profiling data as input, and it automatically retrieves the structural information and constructs the compound clusters in real-time, thereby reducing the time required for manual analysis in drug development or repurposing applications. The web-tool provides a customizable visual workspace that can either be downloaded as figure or Newick tree file or shared as a hyperlink with other users. C-SPADE is freely available at http://cspade.fimm. fi/.
Mice deficient in Ext2 lack heparan sulfate and develop exostoses

Hereditary multiple exostoses (HME) is a genetically heterogeneous human disease characterized by the development of bony outgrowths near the ends of long bones. HME results from mutations in EXT1 and EXT2, genes that encode glycosyltransferases that synthesize heparan sulfate chains. To study the relationship of the disease to mutations in these genes, we generated Ext2-null mice by gene targeting. Homozygous mutant embryos developed normally until embryonic day 6.0, when they became growth arrested and failed to gastrulate, pointing to the early essential role for heparan sulfate in developing embryos. Heterozygotes had a normal lifespan and were fertile; however, analysis of their skeletons showed that about one-third of the animals formed one or more ectopic bone growths (exostoses). Significantly, all of the mice showed multiple abnormalities in cartilage differentiation, including disorganization of chondrocytes in long bones and premature hypertrophy in costochondral cartilage. These changes were not attributable to a defect in hedgehog signaling, suggesting that they arise from deficiencies in other heparan sulfate-dependent pathways. The finding that haploinsufficiency triggers abnormal cartilage differentiation gives insight into the complex molecular mechanisms underlying the development of exostoses.
The Knowledge Management Strategy of Agile Software Development

In software development the most important asset is knowledge. Much of this knowledge is tacit, and given its elusive nature, this creates a challenge for organisations. In practice most organisational KM strategies are codification strategies or personalisation strategies. We use this distinction to guide a review of typical practices in agile software development that address knowledge management. Based on this survey we conclude that agile software development implies a personalisation strategy.
Lifetime Maximization in Wireless Sensor Networks

One of the fundamental requirements in wireless sensor networks WSNs is to prolong the lifetime of sensor nodes by minimizing the energy consumption. The information about the energy status of sensor nodes can be used to notify the base station about energy depletion in any part of the network. An energy map of WSN can be constructed with available remaining energy at sensor nodes. The energy map can increase the lifetime of sensor networks by adaptive clustering, energy centric routing, data aggregation, and so forth. In this paper, the authors describe use of energy map techniques for WSNs and summarize the applications in routing, aggregation, clustering, data dissemination, and so forth. The authors also present an energy map construction algorithm that is based on prediction.
Whole program data dependence profiling to unveil parallel regions in the dynamic execution

As application programs become large and complex year by year, mapping these programs into highly parallelized hardware resources by understanding all of the program structures across an application is becoming harder and harder for programmers. In this paper, we present an advanced technique that can extract dynamic memory dataflow across whole program execution to provide programmers with hints for program parallelization and acceleration. Using a pre-compiled executable binary code as the input, we monitor data dependencies via memory references together with dynamic loop- and call-contexts. We implement our mechanism on a dynamic binary translation system and evaluate it using productive benchmark suites. From these results, we confirm that we can successfully keep track of data dependencies among function calls, loops and their iterations using LCCT+M (Loop-Call Context Tree with Memory Dataflow) representation within reasonable time and memory space overheads. We also demonstrate our profiling can help programmers to identify loop-, task- and pipeline-parallelisms in its actual dynamic execution.
Push vs. Pull-Based Loop Fusion in Query Engines

Database query engines use pull-based or push-based approaches to avoid the materialization of data across query operators. In this paper, we study these two types of query engines in depth and present the limitations and advantages of each engine. Similarly, the programming languages community has developed loop fusion techniques to remove intermediate collections in the context of collection programming. We draw parallels between the DB and PL communities by demonstrating the connection between pipelined query engines and loop fusion techniques. Based on this connection, we propose a new type of pull-based engine, inspired by a loop fusion technique, which combines the benefits of both approaches. Then we experimentally evaluate the various engines, in the context of query compilation, for the first time in a fair environment, eliminating the biasing impact of ancillary optimizations that have traditionally only been used with one of the approaches. We show that for realistic analytical workloads, there is no considerable advantage for either form of pipelined query engine, as opposed to what recent research suggests. Also, by using microbenchmarks we show that our proposed engine dominates the existing engines by combining the benefits of both.
Modelling the Structure and Dynamics of Biological Pathways

There is a need for formalised diagrams that both summarise current biological pathway knowledge and support modelling approaches that explain and predict their behaviour. Here, we present a new, freely available modelling framework that includes a biologist-friendly pathway modelling language (mEPN), a simple but sophisticated method to support model parameterisation using available biological information; a stochastic flow algorithm that simulates the dynamics of pathway activity; and a 3-D visualisation engine that aids understanding of the complexities of a system’s dynamics. We present example pathway models that illustrate of the power of approach to depict a diverse range of systems.
CloudRand : Building Heterogeneous and Moving-target Port Interfaces for Networked Systems

Some fundamental reasons why our networked systems are still vulnerable to network attacks are: (1) they are more open than necessary; (2) they are homogeneous, i.e., the same way to exploit a vulnerability on one machine is easily applicable to many other machines (which is particularly a severe concern in cloud computing environments when virtual machines images are heavily reused/cloned); (3) current networked services are merely static targets, i.e., they are easily predictable and do not change. While network authentication and access control mechanisms such as firewall and VPN can help reduce the openness (mostly at network perimeter level), they do not help much on the latter two factors. To bridge the gap and greatly complement existing network authentication/access control mechanisms, we propose CloudRand, a new framework to make networked systems/services heterogeneous (every host has a different networking interface) and moving targets (such interfaces keep changing and they are unpredictable to untrusted entities). Inspired by the previous work on hostlevel (memory or instruction) Address Space Randomization (ASR), we build a lightweight solution to randomize network service port interfaces. Thus, even derived from the same image, each virtual machine can have very different run-time network service interfaces and they keep changing to further reduce the attack surface. CloudRand is an application-agnostic, hypervisorlevel security service, orthogonal to existing application/network security mechanisms such as authentication, encryption, and access control. Our extensive evaluation shows that this solution has low overhead, and it can significantly reduce network attack surface and successfully defeat malware epidemic attacks.
Institutional Investors and the Development of IT Capability: Evidence from Publicly Listed Companies

Investors often influence the strategic decisions of their holdings, such as long-term orientation and investments in intangible assets. Investigating IT capability as a strategic asset, we examine the influence of institutional shareholders’ investment horizon and blockholdings on the development of organizational IT capability. We perform a panel data analysis of eleven years of archival data from publicly listed U.S. companies. Our findings show a positive relationship between a firm’s ownership structure and the development of its IT capability. In particular, we find that equity owners that remain invested over long periods of time increase firms’ likelihood of developing a continuous IT capability. In contrast, investors that can be classified as blockholders do not exert significant influence on their portfolio firms. By linking accounting research on firm ownership with ongoing IS research on IT capability, we provide new insides into the firm-level benefits of long-term oriented institutional investors on IT capability.
Evaluating the energy efficiency of LTE-Advanced relay and Picocell deployments

As wireless communications experience tremendous growth, energy consumption is becoming a crucial problem in the wireless industry. Energy saving mechanisms are important for supporting the mobility and extending the battery life of a user equipment, reducing the operation costs of a network operator, enhancing corporate image of operators and vendors alike, and providing a lower total energy consumption which reflects in a lower environmental impact. Herein, we evaluate the energy efficiency of different small node deployments, namely relay nodes and Picocells, within the 3GPP LTE-Advanced framework. The energy efficiency of small node deployments is considered on both the uplink and downlink of 3GPP-defined urban and suburban models. In specific, the work investigates the impact of deploying different numbers of small nodes on reducing area power consumption, or alternatively, on enhancing the throughput power consumption of access networks.
Toward Sustainability Assessment of Agricultural Ecosystem based on Thermodynamic Approach: A Case Study for Haenam Farmland in Korea

i TABLE OF CONTENTS . iii LIST OF TABLE . v LIST OF FIGURES . vii 1. Background of the Study . 1 1.1 Motivation . 1 1.2 Conceptual Framework . 4 1.3 Haenam Farmland in Korea (HFK) . 7 2. Material and Method . 11 2.1 Site Description . 11 2.2 Field Measurement and Flux Data Processing . 12 2.3 Theoretical Background . 14 2.3.1 Energy and Entropy Budget . 14 2.3. 2 Actual Evapotranspiration . 16 2.3. 3 The Budyko Curve . 16 2.3. 4 Reference Evapotranspiration . 19 2.3. 5 Crop Coefficient . 20 2.3. 6 Water Use Efficiency . 21 2.3. 7 Footprint Analysis . 23 3. Results and Discussion . 25 3.1 Climate Conditions . 25 3.1.1 Precipitation (P) . 25 3.1.2 Downward Shortwave Radiation (Rs) . 28
Decreased Intra- and Inter-Salience Network Functional Connectivity is Related to Trait Anxiety in Adolescents

Objective: Adolescence is a critical period for the vulnerability of anxiety. Imaging studies focusing on adolescents' susceptibility to anxiety suggest that the different development trajectories between the limbic system and the executive control system may play important roles in this phenomenon. However, few studies have explored the brain basis of this susceptibility from the perspective of functional networks. The salience network (SN) consists of a series of key limbic and prefrontal regions that are engaged in the development of anxiety, such as the amygdala, anterior insula (AI), and dorsal anterior cingulate cortex (dACC). Intra- and inter-network connections in this system play essential roles in bottom-up attention and top-down regulation of anxiety, nevertheless, little is known about whether the SN-centered connections are associated with trait anxiety (i.e., susceptibility to anxiety) in adolescents. Method: Here, we applied resting-state functional magnetic resonance imaging (fMRI) to explore the relationship between intra- and inter-network functional connectivity (FC) of the SN and trait anxiety in adolescents using the amygdala, AI and dACC as the regions of interest (ROI). Results: We found that trait anxiety levels were inversely associated with both characteristic AI-dACC FC in the SN and distributed inter-network FC between the SN and multiple functional systems, which included the default mode network and the executive control network. Conclusions: Our results indicate that weaker intra- and inter-network FC of the SN was linked to higher trait anxiety among adolescents, and it may underlie altered salience processing and cognitive regulation.
AGAMOUS-LIKE 24, a dosage-dependent mediator of the flowering signals

The most dramatic phase change in plants is the transition from vegetative to reproductive growth. This flowering process is regulated by several interacting pathways that monitor both the developmental state of the plants and environmental cues such as light and temperature. The flowering-time genes FLOWERING LOCUS T (FT) and SUPPRESSOR OF OVEREXPRESSION OF CO1 (SOC1), together with the floral meristem identity gene LEAFY (LFY), are three essential regulators integrating floral signals from multiple pathways in Arabidopsis thaliana. Part of the crosstalk among these genes is mediated by a putative transcription factor, AGAMOUS-LIKE 24 (AGL24). This gene is gradually activated in shoot apical meristems during the floral transition and later located in the whole zone of both inflorescence and floral meristems. Loss and reduction of AGL24 activity by double-stranded RNA-mediated interference result in late flowering, whereas constitutive overexpression of AGL24 causes precocious flowering. The correlation between the level of AGL24 accumulation and the alteration of flowering time suggests that AGL24 is a dosage-dependent flowering promoter. Analysis of AGL24 expression in various flowering-time mutants shows that it is regulated in several floral inductive pathways. Further genetic analyses of epistasis indicate that AGL24 may act downstream of SOC1 and upstream of LFY.
Cosegmentation of Image Pairs by Histogram Matching - Incorporating a Global Constraint into MRFs

We introduce the term cosegmentation which denotes the task of segmenting simultaneously the common parts of an image pair. A generative model for cosegmentation is presented. Inference in the model leads to minimizing an energy with an MRF term encoding spatial coherency and a global constraint which attempts to match the appearance histograms of the common parts. This energy has not been proposed previously and its optimization is challenging and NP-hard. For this problem a novel optimization scheme which we call trust region graph cuts is presented. We demonstrate that this framework has the potential to improve a wide range of research: Object driven image retrieval, video tracking and segmentation, and interactive image editing. The power of the framework lies in its generality, the common part can be a rigid/non-rigid object (or scene), observed from different viewpoints or even similar objects of the same class.
Bioinformatic Requirements for Protein Database Searching Using Predicted Epitopes from Disease-associated Antibodies*

We describe a new approach to identify proteins involved in disease pathogenesis. The technology, Epitope-Mediated Antigen Prediction (E-MAP), leverages the specificity of patients’ immune responses to disease-relevant targets and requires no prior knowledge about the protein. E-MAP links pathologic antibodies of unknown specificity, isolated from patient sera, to their cognate antigens in the protein database. The E-MAP process first involves reconstruction of a predicted epitope using a peptide combinatorial library. We then search the protein database for closely matching amino acid sequences. Previously published attempts to identify unknown antibody targets in this manner have largely been unsuccessful for two reasons: 1) short predicted epitopes yield too many irrelevant matches from a database search and 2) the epitopes may not accurately represent the native antigen with sufficient fidelity. Using an in silico model, we demonstrate the critical threshold requirements for epitope length and epitope fidelity. We find that epitopes generally need to have at least seven amino acids, with an overall accuracy of >70% to the native protein, in order to correctly identify the protein in a nonredundant protein database search. We then confirmed these findings experimentally, using the predicted epitopes for four monoclonal antibodies. Since many predicted epitopes often fail to achieve the seven amino acid threshold, we demonstrate the efficacy of paired epitope searches. This is the first systematic analysis of the computational framework to make this approach viable, coupled with experimental validation.
Biological Cycling of Mineral Nutrients in a Temperate Forested Shale Catchment

Biological pumping of mineral elements (root uptake from the soil and concentration at the surface via litterfall) may be an important mechanism influencing their loss from terrestrial ecosystems by accelerating transport in runoff, though few estimates exist to assess this. In the Susquehanna Shale Hills Critical Zone Observatory (a temperate forested watershed in central Pennsylvania), we compared two independent methods (litterfall‐based and transpiration flow‐based) for estimating the total uptake of elements (Ca, K, Mg, Mn, Si, Sr, and Al) by canopy trees. Elemental concentrations were measured monthly in leaf tissue and xylem sap of dominant species Quercus rubra (chestnut oak), Q. prinus (red oak), and Acer saccharum (sugar maple) for two growing seasons. Species‐specific litterfall and transpiration (estimated by eddy covariance) were used to scale concentrations to annual fluxes. For most elements, both methods generated comparable gross fluxes in the range of 53–85 (Ca), 9–19 (Mg), 14–28 (Mn), 0.2–0.6 (Al), and 0.1–0.3 (Sr) kg·ha−1·year−1. For K, litterfall‐based methods generated substantially lower estimates than transpiration, though neither accounted comprehensively for leaching from live foliage, resorption, or potential recycling within the growing season. For most elements, uptake rates were similar in magnitude to stream losses, implying a low degree of recycling. For K and Mn however, biological uptake exceeded losses by 1–2 orders of magnitude, suggesting a biological role in ecosystem retention. We conclude that litter‐ and transpiration‐based methods can be combined to broadly estimate the magnitude of biological pumping, with additional measures of wood‐/root‐based turnover necessary for more accurate budgets.