Miracle-dz/UniFAR-FTUs huggingface dataset:
Iron-Nicotianamine Transporters Are Required for Proper Long Distance Iron Signaling1[OPEN]

Loss of iron-nicotianamine transporters causes mislocalization of iron in Arabidopsis leaves that leads to profound defects in the long-distance signaling of iron status to roots. The mechanisms of root iron uptake and the transcriptional networks that control root-level regulation of iron uptake have been well studied, but the mechanisms by which shoots signal iron status to the roots remain opaque. Here, we characterize an Arabidopsis (Arabidopsis thaliana) double mutant, yellow stripe1-like yellow stripe3-like (ysl1ysl3), which has lost the ability to properly regulate iron deficiency-influenced gene expression in both roots and shoots. In spite of markedly low tissue levels of iron, the double mutant does not up- and down-regulate iron deficiency-induced and -repressed genes. We have used grafting experiments to show that wild-type roots grafted to ysl1ysl3 shoots do not initiate iron deficiency-induced gene expression, indicating that the ysl1ysl3 shoots fail to send an appropriate long-distance signal of shoot iron status to the roots. We present a model to explain how impaired iron localization in leaf veins results in incorrect signals of iron sufficiency being sent to roots and affecting gene expression there. Improved understanding of the mechanism of long-distance iron signaling will allow improved strategies for the engineering of staple crops to accumulate additional bioavailable iron in edible parts, thus improving the iron nutrition of the billions of people worldwide whose inadequate diet causes iron deficiency anemia.
Fluorocarbons Enhance Intracellular Delivery of Short STAT3-sensors and Enable Specific Imaging

Short oligonucleotide sequences are now being widely investigated for their potential therapeutic properties. The modification of oligonucleotide termini with short fluorinated residues is capable of drastically altering their behavior in complex in vitro and in vivo systems, and thus may serve to greatly enhance their therapeutic potential. The main goals of our work were to explore: 1) how modification of STAT3 transcription factor-binding oligodeoxynucleotide (ODN) duplexes (ODND) with one or two short fluorocarbon (FC)-based residues would change their properties in vitro and in vivo, and if so, how this would affect their intracellular uptake by cancer cells, and 2) the ability of such modified ODND to form non-covalent complexes with FC-modified carrier macromolecule. The latter has an inherent advantage of producing a 19F-specific magnetic resonance (MR) imaging signature. Thus, we also tested the ability of such copolymers to generate 19F-MR signals. Materials and Methods. Fluorinated nucleic acid residues were incorporated into ODN by using automated synthesis or via activated esters on ODN 5'-ends. To quantify ODND uptake by the cells and to track their stability, we covalently labeled ODN with fluorophores using internucleoside linker technology; the FC-modified carrier was synthesized by acylation of pegylated polylysine graft copolymer with perfluoroundecanoic acid (M5-gPLL-PFUDA). Results. ODN with a single FC group exhibited a tendency to form duplexes with higher melting points and with increased stability against degradation when compared to control non-modified ODNs. ODND carrying fluorinated residues showed complex formation with M5-gPLL-PFUDA as predicted by molecular dynamics simulations. Moreover, FC groups modulated the specificity of ODND binding to the STAT3 target. Finally, FC modification resulted in greater cell uptake (2 to 4 fold higher) when compared to the uptake of non-modified ODND as determined by quantitative confocal fluorescence imaging of A431 and INS-1 cells. Conclusion. ODND modification with FC residues enables fine-tuning of protein binding specificity to double-strand binding motifs and results in an increased internalization by A431 and INS-1 cells in culture. Our results show that modification of ODN termini with FC residues is both a feasible and powerful strategy for developing more efficient nucleic acid-based therapies with the added benefit of allowing for non-invasive MR imaging of ODND therapeutic targeting and response.
Hypoxia-Induced Mitogenic Factor (HIMF/FIZZ1/RELMα) Increases Lung Inflammation and Activates Pulmonary Microvascular Endothelial Cells via an IL-4–Dependent Mechanism

Hypoxia-induced mitogenic factor (HIMF), also known as found in inflammatory zone 1 and resistin-like molecule α, belongs to a novel class of cysteine-rich secreted proteins. It exhibits mitogenic and chemotactic properties during pulmonary hypertension-associated vascular remodeling, as well as fibrogenic properties during pulmonary fibrosis. HIMF expression in the lung was reported to be regulated by Th2 cytokines (IL-4 and IL-13) via the transcription factor STAT6 pathway in a bleomycin-induced pulmonary fibrosis model. However, in this study, we found that in the hypoxia-induced pulmonary hypertension model, lung HIMF expression is increased in IL-4 and STAT6 knockout (KO) mice to the same degree as in wild-type (WT) mice, suggesting that induction of HIMF expression does not require Th2 regulation in this model. We also found that HIMF-induced proliferative activity, hypertrophy, collagen, and extracellular matrix deposition in the pulmonary arteries are significantly less in IL-4 KO mice than in WT mice. In addition, HIMF-induced production of angiogenic factors/chemokines, such as vascular endothelial growth factor, MCP-1, and stromal-derived factor-1, in the lung resident cells, as well as macrophage infiltration, were significantly suppressed in the lungs of IL-4 KO mice. We also show that IL-4 was significantly increased in the lungs of HIMF-treated WT mice. Our in vitro studies using pulmonary microvascular endothelial cells revealed that HIMF stimulated cell proliferation, vascular endothelial growth factor expression, and MCP-1 production in a manner that is dependent on the IL-4/IL-4Rα system. These findings suggest that IL-4 signaling may play a significant role in HIMF-induced lung inflammation and vascular remodeling.
Influence of the Magnetic Field on the Graphene Conductivity

The transversal conductivity of the gap-modification of the graphene was studied in the cases of weak nonquatizing and quantizing magnetic field. In the case of nonquantizing magnetic field the expression of the current density was derived from the Boltzmann equation. The dependence of conductivity and Hall conductivity on the magnetic field intensity was investigated. In the case of quantizing magnetic field the expression for the graphene transversal magnetoconductivity taking into account the scattering on the acoustic phonons was derived in the Born approximation. The graphene conductivity dependence on the magnetic field intensity was investigated. The graphene conductivity was shown to have the oscillations when the magnetic field intensity changes. The features of the Shubnikov-de Haas oscillations in graphene superlattice are discussed.
An efficient gradient projection optimization scheme for a seven-degree-of-freedom redundant robot with spherical wrist

A computationally effective kinematic control scheme is presented for a seven-degree-of-freedom redundant robot with spherical wrist. This scheme uses a gradient projection optimization method, which eliminates the need to determine the generalized inverse of the Jacobian when solving for joint velocities for given Cartesian end-effector velocities. Closed-form solutions are obtained for joint velocities using this approach. The application of this scheme to the seven-degree-of-freedom manipulator at the Center for Engineering Systems Advanced Research (CESAR) is described. <<ETX>>
Partial loss-of-function alleles reveal a role for GNOM in auxin transport-related, post-embryonic development of Arabidopsis

The Arabidopsis GNOM gene encodes an ARF GDP/GTP exchange factor involved in embryonic axis formation and polar localisation of the auxin efflux regulator PIN1. To examine whether GNOM also plays a role in post-embryonic development and to clarify its involvement in auxin transport, we have characterised newly isolated weak gnom alleles as well as trans-heterozygotes of complementing strong alleles. These genotypes form a phenotypic series of GNOM activity in post-embryonic development, with auxin-related defects, especially in the maintenance of primary root meristem activity and in the initiation and organisation of lateral root primordia. Our results suggest a model for GNOM action mediating auxin transport in both embryogenesis and post-embryonic organ development.
Evaluation of a national reform in the Israeli child protection practice designed to improve children's participation in decision‐making

A national reform of child protection practice in Israel includes the ambition of strengthening children's participation in intervention decisions carried out in formal committees, called planning, intervention and evaluation committees. A qualitative study was conducted of how well this was being achieved by following 21 case studies of families referred to the committees over 6 months. Data were collected from interviews with social workers, field observations of the committees and a document review. A systems approach was undertaken as a conceptual framework in order to allow a whole-organizational understanding of what is happening in the field, and why. The key finding was a very limited realization of the reform's aim. Only seven children attended the committees, and they had little influence on decisions, which appears to have made them less co-operative in implementing them. Those who did not attend rarely had their views conveyed to the committee by their social workers. The reform's lack of success is explained by being ill suited to the organizational working environment and culture. The analysis identified a number of systemic factors influencing the failure to give greater priority to children's views, including lack of skill and time, organizational messages about practice priorities and paternalistic ideology.
Two-point estimate method for quantifying transfer capability uncertainty

A two-point estimate method is proposed in this paper to assess the power transfer capability uncertainty. This paper assumes that the uncertainty of the line parameters and bus injections involved in transfer capability calculations can be estimated or measured and shows how to estimate the corresponding uncertainty in the transfer capability. Instead of using a large number of simulations as required in the Monte Carlo approach, for a system with n uncertain parameters, the two-point estimate method uses 2n calculations of transfer capability to quantify the uncertainty. The proposed method uses a numerical method to calculate the moments of the transfer capability. The moments are then used in the probability distribution fitting. Using the obtained transfer capability uncertainty information and a desired level of reliability, an adequate transmission reliability margin can be determined for each transmission service. The proposed method can be used directly with a deterministic computer program and it does not require derivatives of the transfer capability. Test results of the proposed method are compared with those obtained from the Monte Carlo simulations and a truncated Taylor series expansion method.
Towards a Compiler for Reals

Numerical software, common in scientific computing or embedded systems, inevitably uses a finite-precision approximation of the real arithmetic in which most algorithms are designed. In many applications, the roundoff errors introduced by finite-precision arithmetic are not the only source of inaccuracy, and measurement and other input errors further increase the uncertainty of the computed results. Adequate tools are needed to help users select suitable data types and evaluate the provided accuracy, especially for safety-critical applications. We present a source-to-source compiler called Rosa that takes as input a real-valued program with error specifications and synthesizes code over an appropriate floating-point or fixed-point data type. The main challenge of such a compiler is a fully automated, sound, and yet accurate-enough numerical error estimation. We introduce a unified technique for bounding roundoff errors from floating-point and fixed-point arithmetic of various precisions. The technique can handle nonlinear arithmetic, determine closed-form symbolic invariants for unbounded loops, and quantify the effects of discontinuities on numerical errors. We evaluate Rosa on a number of benchmarks from scientific computing and embedded systems and, comparing it to the state of the art in automated error estimation, show that it presents an interesting tradeoff between accuracy and performance.
Application-layer anomaly detection based on application-layer protocols' keywords

Nowadays most network-based attacks are based on application-layer protocols and don't present significant difference in network traffic. Observed from the network-layer and transport-layer, these attacks may not contain significant malicious activities, and generate abnormal network traffic. So it is difficult for existing methods to effectively detect such application-layer attacks without special techniques. In theory, application-layer anomaly detection can detect the known, unknown and novel attacks happened on application-layer, therefore the research of application-layer anomaly detection is very important. This paper presents an application-layer anomaly detection method based on application-layer protocols' keywords. In this method, the keywords of an application-layer protocol and their inter-arrival times are used as the observations, a hidden semi-Markov model is used to describe the behaviors of a normal user who is using the application-layer protocol. The experimental results show that this method has high detection accuracy and low false positive ratio.
CLEANSING A prelude to knowledge discovery

This chapter analyzes the problem of data cleansing and the identification of potential errors in data sets. The differing views of data cleansing are surveyed and reviewed and a brief overview of existing data cleansing tools is given. A general framework of the data cleansing process is presented as well as a set of general methods that can be used to address the problem. The applicable methods include statistical outlier detection, pattern matching, clustering, and data mining techniques. The experimental results of applying these methods to a real world data set are also given. Finally, research directions necessary to further address the data cleansing problem are discussed.
Surprise in the GRID

This paper analyses surprise in the framework of the GRID paradigm as part of a research project on the meaning of emotion words across languages and cultures. Based on psychological component theories of emotion, an online instrument was designed to rate the meaning of 24 emotion terms on 142 features of emotion. Data was collected for 23 languages in 27 countries. The mean rates within and across languages offer a semantic profile of the emotion terms. Results are presented on the meaning of “surprise” across languages and in English and French. The data also indicate four dimensions are necessary to describe the emotion space: valence, power, arousal and novelty. Novelty captures variation in suddenness and expectedness and differentiates surprise from other emotions, as well as types of emotion within a family, revealing itself as a relevant aspect of emotion universally encoded in our affective lexicons.
Distinguished Scholar Invited Essay

This article reviews goal-setting theory in terms of the causal relationships it specifies, the boundary conditions within which the causal relationships occur, and the mediators that explain the causal relationships. Three types of goals are described: performance, behavioral, and learning. Emphasis in the article is placed on findings regarding the beneficial effect of setting a specific, difficult learning goal.
Role Breadth and Role Performance: An Empirical Investigation

Based on role theory, the present study examines theoretically meaningful, yet infrequently studied relationship between organization identification, autonomy orientation and competence mobilization in predicting role breadth and role performance. Data collected from employees (n = 178) and supervisors (n = 67) working in a large information technology (IT) company based in India was analyzed using hierarchical regression to test the hypotheses. Results show that organization identification, autonomy orientation and competence mobilization were positively related to role breadth. Specifically, role breadth mediates the relationship between organization identification, autonomy orientation and competence mobilization and role performance. Discussion shows insights into theoretical and practical perspectives.
Sparse Modeling with Universal Priors and Learned Incoherent Dictionaries(PREPRINT)

Abstract : Sparse data models have gained considerable attention in recent years, and their use has led to state-of-the-art results in many signal and image processing tasks. The learning of sparse models has been mostly concerned with adapting the dictionary to tasks such as classification and reconstruction, optimizing extrinsic properties of the trained dictionaries. In this work, we first propose a learning method aimed at enhancing both extrinsic and intrinsic properties of the dictionaries, such as the mutual and cumulative coherence and the Gram matrix norm, characteristics known to improve the efficiency and performance of sparse coding algorithms. We then use tools from information theory to propose a sparsity regularization term which has several desirable theoretical and practical advantages over the more standard `0 or `1 ones. These new sparse modeling components lead to improved coding performance and accuracy in reconstruction tasks.
Conversation Map: An Interface for Very Large-Scale Conversations

Very large-scale conversation (VLSC) involves the exchange of thousands of electronic mail (e-mail) messages among hundreds or thousands of people. Usenet newsgroups are good examples (but not the only examples) of online sites where VLSCs take place. Tofacilitate understanding of the social and semantic structure of VLSCs, two tools from the social sciences-social networks and semantic networks-have been extended for the purposes of interface design. As interface devices, social and semantic networks need to be flexible, layered representations that are useful as a means for summarizing, exploring, and cross-indexing the large volumes of messages that constitute the archives of VLSCs. This paper discusses the design criteria necessary for transforming these social scientific representations into interface devices. The discussion is illustrated with the description of the Conversation Map system, an implemented system for browsing and navigating VLSCs.
Doing Well by Doing Good

A complete understanding of the financial impact of patient safety interventions must consider the economic incentives of both payers and providers within the current fee-for-service payment model. This study evaluated the impact of a central line–associated bloodstream infection (CLABSI) initiative on costs, reimbursements, and margins for 1 Hawaii hospital and its payers. Intensive care unit patients (January 2009-December 2011) who developed a CLABSI were compared to matched controls. Mean hospital cost, reimbursement, and margin was $222 692 versus $80 144 (P = .01), $259 433 versus $72 543 (P < .01), and $54 906 versus $6506 (P < .01), respectively. Although hospitals and payers reduce costs by preventing CLABSIs, hospitals also would decrease their margins, which creates a perverse incentive to have more line infections. An optimal reimbursement system must reward hospitals and payers for preventing harm rather than treating illness. This study highlights the critical role that health care payers have as patient safety advocates, financial sponsors, and facilitators.
User Satisfaction of the Website for National Center for Health Communication and Education in Vietnam: An Application of IS Success Model

Website of National Center for Health Communication and Education (CHCE), Vietnam, has been designed and used from July 2006. The website is an important information channel which provides quickly, accurately and timely information on food safety, hygiene, and disease prevention, and also provides necessary documents, data and information for managers, policy makers and researchers in the health sector. This study aimed to assess the satisfaction of the CHCE website users and propose solutions to improve the quality of the website to meet the needs of users. For this purpose, this study built a research model by applying IS Success Model, and conducted a survey by delivering questionnaires to the users from CHCE in 9 provinces and one Institute of MOH in Vietnam. The results show that three factors (information quality, system quality, system design quality) have positive effect on user satisfaction of using CHCE website. Moreover, users care more about quality systems and quality information. In other words, users are more interested in what information and knowledge the website provides, and how good is its information quality; e.g., reliable or useful, for organization management or for people's everyday life.
A survey of current trends in computational drug repositioning

Computational drug repositioning or repurposing is a promising and efficient tool for discovering new uses from existing drugs and holds the great potential for precision medicine in the age of big data. The explosive growth of large-scale genomic and phenotypic data, as well as data of small molecular compounds with granted regulatory approval, is enabling new developments for computational repositioning. To achieve the shortest path toward new drug indications, advanced data processing and analysis strategies are critical for making sense of these heterogeneous molecular measurements. In this review, we show recent advancements in the critical areas of computational drug repositioning from multiple aspects. First, we summarize available data sources and the corresponding computational repositioning strategies. Second, we characterize the commonly used computational techniques. Third, we discuss validation strategies for repositioning studies, including both computational and experimental methods. Finally, we highlight potential opportunities and use-cases, including a few target areas such as cancers. We conclude with a brief discussion of the remaining challenges in computational drug repositioning.