Miracle-dz/UniFAR-FTUs huggingface dataset:
1 ECO-EPIDEMIOLOGICAL ENQUIRY UNDER GLOBAL ECOLOGICAL CHANGE : AN INTEGRATED ASSESSMENT TOOLKIT FOR BEGINNERS

of Alberta) for their valuable conceptual and editorial input. Abbreviations: AIDS acquired immunodeficiency syndrome BAU business as usual EF ecological footprint EFA eclogical footprint analysis EKCs Environmental Kuznets Curves GDP gross domestic product 3 HEADLAMP Linkage Methods for Environment and Health Analysis, HEADLAMP Project HIV human immunodeficiency virus IA integrated assessment I=PAT impact equals the product of population, affluence, and technology PLCA product life-cycle analysis SARS Severe Acute Respiratory Syndrome Introduction Global change and population health: complexities and urgency From the Newtonian to the complexity paradigm The broader context of population health Integrated assessment: a systems-based research approach Participatory methods Promising tools for eco-epidemiology Conclusions References Table Total paper word count: 12,135 5 ABSTRACT Eco-epidemiology is a sub-specialty of epidemiology, focusing on the relationships between human health and the dynamics of global ecological change. Under escalating global change, new conceptual and analytical tools are needed if we are to contribute to the development of prevention and adaptation strategies for reducing negative health effects of changing ecosystems. This paper provides an overview of methodological approaches and tools for advancing eco-epidemiological research. Several Integrated Assessment methods are discussed (integrated modeling, scenario analysis, and participatory methods), each combining knowledge elements from various disciplines into an analytical framework for identifying the cross-linkages and interactions among different contextual circumstances and processes underlying complex (eco-epidemiological) phenomena that we are facing today. Building on environmental (impact) studies, we additionally discuss some promising tools that can support more systematic approaches: conventional and disaggregated Ecological Footprint analysis, the DPSEEA-framework, Product Life-Cycle Analysis, the I = PAT identity, and Environmental Kuznets Curves. We argue that the methods and tools discussed can help to advance our understanding of the complex pathways among socioeconomic and environmental determinants of health, improving the exploration and modeling of human health under global ecological change. They help us to focus research attention on key features of complex systems to improve our understanding of systemic (" upstream ") drivers, and to facilitate a more complete characterization of proximate (" downstream ") exposures and their effects. Their application in problem-oriented transdisciplinary research encourages the adaptation and adoption of formerly discipline-specific methods into other disciplines; new, conceptual frameworks then emerge. Their continued employment and evaluation are encouraged.
Cofilin: a redox sensitive mediator of actin dynamics during T-cell activation and migration

Cofilin is an actin‐binding protein that depolymerizes and/or severs actin filaments. This dual function of cofilin makes it one of the major regulators of actin dynamics important for T‐cell activation and migration. The activity of cofilin is spatio‐temporally regulated. Its main control mechanisms comprise a molecular toolbox of phospho‐, phospholipid, and redox regulation. Phosphorylated cofilin is inactive and represents the dominant cofilin fraction in the cytoplasm of resting human T cells. A fraction of dephosphorylated cofilin is kept inactive at the plasma membrane by binding to phosphatidylinositol 4,5‐bisphosphate. Costimulation via the T‐cell receptor/CD3 complex (signal 1) together with accessory receptors (signal 2) or triggering through the chemokine SDF1α (stromal cell‐derived factor 1α) induce Ras‐dependent dephosphorylation of cofilin, which is important for immune synapse formation, T‐cell activation, and T‐cell migration. Recently, it became evident that cofilin is also highly sensitive for microenvironmental changes, particularly for alterations in the redox milieu. Cofilin is inactivated by oxidation, provoking T‐cell hyporesponsiveness or necrotic‐like programmed cell death. In contrast, in a reducing environment, even phosphatidylinositol 4,5‐bisphosphate ‐bound cofilin becomes active, leading to actin dynamics in the vicinity of the plasma membrane. In addition to the well‐established three signals for T‐cell activation, this microenvironmental control of cofilin delivers a modulating signal for T‐cell‐dependent immune reactions. This fourth modulating signal highly impacts both initial T‐cell activation and the effector phase of T‐cell‐mediated immune responses.
Slide Over Here: The Various Adjacencies of Co-borrowed Ebooks

One of the major failings of ebook collections is the lack of readily available browsing mechanisms particularly in academic libraries. This stands in sharp contrast to the library shelves, and is bemoaned by readers as a reason to avoid the use of ebooks. Nonetheless earlier work has identified limited ebook co-borrowing; in this paper we address the relationships between these ebooks with a view to understanding how readers accessed them in a single session.
Multisite Ion Model in Concentrated Solutions of Divalent Cations (MgCl2 and CaCl2): Osmotic Pressure Calculations

Accurate force field parameters for ions are essential for meaningful simulation studies of proteins and nucleic acids. Currently accepted models of ions, especially for divalent ions, do not necessarily reproduce the right physiological behavior of Ca2+ and Mg2+ ions. Saxena and Sept (J. Chem. Theor. Comput.2013, 9, 3538–3542) described a model, called the multisite-ion model, where instead of treating the ions as an isolated sphere, the charge was split into multiple sites with partial charge. This model provided accurate inner shell coordination of the ion with biomolecules and predicted better free energies for proteins and nucleic acids. Here, we expand and refine the multisite model to describe the behavior of divalent ions in concentrated MgCl2 and CaCl2 electrolyte solutions, eliminating the unusual ion–ion pairing and clustering of ions which occurred in the original model. We calibrate and improve the parameters of the multisite model by matching the osmotic pressure of concentrated solutions of MgCl2 to the experimental values and then use these parameters to test the behavior of CaCl2 solutions. We find that the concentrated solutions of both divalent ions exhibit the experimentally observed behavior with correct osmotic pressure, the presence of solvent separated ion pairs instead of direct ion pairs, and no aggregation of ions. The improved multisite model for (Mg2+ and Ca2+) can be used in classical simulations of biomolecules at physiologically relevant salt concentrations.
Principles of Compositional Multi-Agent System Development

A dedicated development method for multi-agent systems requires adequate means to describe the characteristics of agents and multi-agent systems. Compositional multi-agent system development is based on the principles process and knowledge abstraction, compositionality, reuse, specification and verification. Although the paper addreses these principles of compositional multi-agent system development from a generic perspective, some of the examples used to illustrate the notions discussed are taken from the compositional development method DESIRE.
Estimation of Distributed Fermat-Point Location for Wireless Sensor Networking

This work presents a localization scheme for use in wireless sensor networks (WSNs) that is based on a proposed connectivity-based RF localization strategy called the distributed Fermat-point location estimation algorithm (DFPLE). DFPLE applies triangle area of location estimation formed by intersections of three neighboring beacon nodes. The Fermat point is determined as the shortest path from three vertices of the triangle. The area of estimated location then refined using Fermat point to achieve minimum error in estimating sensor nodes location. DFPLE solves problems of large errors and poor performance encountered by localization schemes that are based on a bounding box algorithm. Performance analysis of a 200-node development environment reveals that, when the number of sensor nodes is below 150, the mean error decreases rapidly as the node density increases, and when the number of sensor nodes exceeds 170, the mean error remains below 1% as the node density increases. Second, when the number of beacon nodes is less than 60, normal nodes lack sufficient beacon nodes to enable their locations to be estimated. However, the mean error changes slightly as the number of beacon nodes increases above 60. Simulation results revealed that the proposed algorithm for estimating sensor positions is more accurate than existing algorithms, and improves upon conventional bounding box strategies.
Environmental Effect on Dominance in Young Great Tits Parus major: A Cross-Fostering Experiment

Grâce a une experimentation d'elevage croise (adoption), l'importance relative des facteurs genetiques et environnementaux sur le statut social des jeunes de Parus major est examinee. La dominance est examine dans le cadre de la competition alimentaire. L'origine des animaux utilisees est soit une foret de coniferes soit une foret a arbres a feuilles caduques
Honeypot through Web (Honeyd@WEB): The Emerging of Security Application Integration

This paper discusses on the development of the Honeyd@WEB. Honeyd@WEB is a system that can deploy low-interaction, production, dynamic and manageable virtual honeypots via a web interface. It runs open source programs, such as P0f (a passive fingerprinting tool) and Honeyd (a low-interaction honeypot). Honeyd@WEB can automatically determine; how many honeypots to deploy, how to deploy them, and what they should look like to blend in with the environment. The first part of this paper highlights the basic security concepts of honeypot and honeynet. The second part of this paper explains the Honeyd@WEB system. Finally, the strengths and the weaknesses of the system are discussed.
PDE 7 Inhibitors: New Potential Drugs for the Therapy of Spinal Cord Injury

Background Primary traumatic mechanical injury to the spinal cord (SCI) causes the death of a number of neurons that to date can neither be recovered nor regenerated. During the last years our group has been involved in the design, synthesis and evaluation of PDE7 inhibitors as new innovative drugs for several neurological disorders. Our working hypothesis is based on two different facts. Firstly, neuroinflammation is modulated by cAMP levels, thus the key role for phosphodiesterases (PDEs), which hydrolyze cAMP, is undoubtedly demonstrated. On the other hand, PDE7 is expressed simultaneously on leukocytes and on the brain, highlighting the potential crucial role of PDE7 as drug target for neuroinflammation. Methodology/Principal Findings Here we present two chemically diverse families of PDE7 inhibitors, designed using computational techniques such as virtual screening and neuronal networks. We report their biological profile and their efficacy in an experimental SCI model induced by the application of vascular clips (force of 24 g) to the dura via a four-level T5–T8 laminectomy. We have selected two candidates, namely S14 and VP1.15, as PDE7 inhibitors. These compounds increase cAMP production both in macrophage and neuronal cell lines. Regarding drug-like properties, compounds were able to cross the blood brain barrier using parallel artificial membranes (PAMPA) methodology. SCI in mice resulted in severe trauma characterized by edema, neutrophil infiltration, and production of a range of inflammatory mediators, tissue damage, and apoptosis. Treatment of the mice with S14 and VP1.15, two PDE7 inhibitors, significantly reduced the degree of spinal cord inflammation, tissue injury (histological score), and TNF-α, IL-6, COX-2 and iNOS expression. Conclusions/Significance All these data together led us to propose PDE7 inhibitors, and specifically S14 and VP1.15, as potential drug candidates to be further studied for the treatment of SCI.
Examination of the antiproliferative activity of iron chelators: multiple cellular targets and the different mechanism of action of triapine compared with desferrioxamine and the potent pyridoxal isonicotinoyl hydrazone analogue 311.

PURPOSE Tumors are sensitive to iron (Fe) chelation therapy with the clinically used chelator desferrioxamine (DFO). Recently, the potent inhibitor of ribonucleotide reductase, Triapine, has entered clinical trials as an anticancer agent. This compound is a potential Fe chelator, but despite this, no investigations have examined its effect on cellular Fe metabolism. This is essential for understanding its mechanism of action and clinical effects. EXPERIMENTAL DESIGN We compared the effect of Triapine with DFO, and also with the novel Fe chelator, 311, which shows marked antiproliferative activity. This latter ligand was relevant to compare, because it is tridentate like Triapine and shares structural similarity. We assessed the effects of chelators on proliferation, Fe uptake, Fe efflux, the expression of cell cycle control molecules, and iron-regulatory protein-RNA-binding activity. Redox activity was determined by ascorbate oxidation, benzoate hydroxylation, plasmid DNA degradation, and the precipitation of cellular DNA. These studies have been performed using several neuroepithelioma and neuroblastoma cell lines and a variety of normal cell types including fibroblasts, umbilical vein endothelial cells, skeletal muscle cells, monocyte-derived macrophages, and bone marrow stem cells. RESULTS Triapine was twice as effective as DFO at mobilizing (59)Fe from prelabeled cells but was much less efficient than 311. In terms of preventing (59)Fe uptake from Tf, Triapine and DFO had similar activity, having far less efficacy than 311. All three of the chelators showed greater activity against the proliferation of neoplastic than of normal cells, the effect of 311 and Triapine being similar and these two chelators being significantly (P < 0.0001) more active than DFO. Complexation of Triapine with Fe had no appreciable effect on its antiproliferative activity, whereas addition of Fe totally inhibited the effects of DFO and 311. Furthermore, the Triapine Fe complex was shown to be redox active. CONCLUSION The cytotoxic mechanism of action of Triapine was different from that of DFO and 311, with the combined action of Fe chelation and free radical generation being involved.
Publisher mobility support in content centric networks

As the high speed Internet and the smart devices become prevalent, it is expected that the traffic volume of the video conferencing/broadcasting on the mobile devices is increasing explosively. One of the promising solutions for the traffic explosion problem is the content centric networking (CCN), which solves the problem by focusing on the content instead of the location. Even though CCN can provide better delivery efficiency, robustness, security, and native subscriber mobility, little attention is paid to the publisher mobility problem, where the mobile devices produce the real-time traffic. In this paper, we propose PMC, a publisher mobility support protocol in CCN. By introducing two names and corresponding operations at the routers, PMC supports publisher mobility for the mobile video conferencing and broadcasting without violating the original CCN architecture. We believe that PMC is a validated and secured scheme following the philosophy of the CCN architecture to support mobile publisher.
A SVM ensemble approach combining pixel-based and object-based features for the classification of high resolution remotely sensed imagery

According to the `salt and pepper' effect of pixel-based multi-feature classification and over-smoothing of ground details of object-based image analysis, in this paper, an approach, which fuses pixel-based features and multi-scale object-based features is proposed to improve the accuracy of image classification. (1) Firstly, mean shift algorithm is used to segment the image to obtain over-segmentation regions. Multi-scale segmentation results are obtained by merging the over-segmentation results. The relation between segmentation scales and classification accuracy on each scale is analyzed, and an optimal scale is found. (2)Secondly, objects' spectral features of the optimal scale, pixel-based spectral features and objects' spectral features of initialization segmentation scale are normalized. (3)Finally, the classification method based on pixel-based and object-based features is implemented by means of support vector machine ( SVM ). The experiment results demonstrate that our method can not only effectively reduce the `salt and pepper' effect of pixel-based algorithm, but also maintain the integrity of the ground objects and preserve details. The classification accuracy of categories that are easily confused (e.g. shadow vs. streets) is also improved.
Investor Protection, Diversification, Investment, and Tobin's Q

We develop a dynamic incomplete-markets model where an entrenched insider, facing imperfect investor protection and non-diversifiable illiquid business risk, makes interdependent consumption, portfolio choice, expropriation, corporate investment, ownership, and business exit decisions. Unlike in the frst-best, the insider's tradeoff between under-diversification costs and private benefits leads to the following results: (1) the firm either over- or underinvests, depending on firm size; (2) the insider's private valuation fundamentally differs from diversified investors valuation;(3) conditional CAPM holds for outside equity; (4) the insider demands an additional idiosyncratic risk premium; (5) the exit option and ownership dynamics are important for the insider to manage business risk.
Resource and performance prediction at high utilization for N-Tier cloud-based service systems

One of the key objectives of cloud computing systems is to meet the service level agreements (SLAs) under conditions of high resource utilization. Cloud service providers often need to design policies for resource sharing and performance optimization. As a result, being able to predict the performance and resource utilizations prior to implementing these policies is important to the dynamic provisioning of services by cloud providers. It is a significant and difficult challenge due to the fact that requests for resources often interact with each other in complex ways. Moreover, the dynamics of the cloud environment bring more problems to predicting the performance of a running query or workload. Hence, an accurate situation-aware model which can capture the complex interactions among resource requests is useful for addressing this challenge. To this end, we propose an efficient and highly accurate resource and performance prediction framework which takes into account the interactions among concurrently running resource requests for n-tier service systems. The proposed framework extends the Gaussian process and kernel canonical correlation analysis techniques and is able to dynamically adapt to variations in workload and physical resource usage. The proposed framework has been trained and evaluated extensively with a realistic multi-tier cloud application benchmark - the RUBiS benchmark system. The results demonstrate that the framework yields highly accurate performance and resource usage predictions, especially under high resource utilization conditions.
An investigation of interaural time difference fluctuations, part 1: the subjective spatial effect of fluctuations delivered over headphones

The subjective spatial effect of noise signals with sinusoidal ITD fluctuations was investigated. Both verbal and non-verbal elicitation experiments were carried out to examine the subjective effect of the ITD fluctuations with a number of fluctuation frequencies and fluctuation magnitudes. It was found that the predominant effect of increasing the fluctuation magnitude was an increase in the perceived width of the sound.
Supplementary Material : Description of database implementation

3DBG was devised to efficiently handle extremely large amounts of genomic data associated to fine-grained 3D models. Classical spatial indices such as R-Trees are inappropriate to our context, since they consider too many overlapping bounding boxes (and hence, too many distinct reads) when indexing complex 3D models and their associated metadata (see the database description section). Instead, we adapt our own, state-of-the-art TrajStore [1] spatial index to efficiently index arbitrary large amounts of genomic data and metadata along three dimensions. Our index has the three following desirable properties: it is i) sparse (i.e., it does not grow linearly as the indexed data grows), ii) non-overlapping (yielding limited index lookups event for 3D range queries on complex meshes) and iii) adaptive (i.e., it continuously adjusts to the local densities of the indexed data). Formally, our basic index structure is an adaptive 3D octree (i.e., a 3D multi-level grid, that can also be represented as a tree data structure in which each internal node has exactly eight children), where each cell (sub-cube) in the octree corresponds to a distinct entry in the chunk index (see below). Our octree index is always updated to yield the minimal query execution cost given a set of queries q ∈ W on the current indexed data points. In our Big Data context where potentially large amounts of data are scanned to answer the queries, the query execution cost is dominated by the cost of reading large chunks of data from the distributed filesystem holding the bulk of the data. State-of-the-art distributed filesystems (e.g., like the very popular HDFS[2]) organize data into large contiguous blocks (typically 64 MB) to amortize the cost of locating and reading data from the distributed infrastructure. Our goal in the following is to take advantage of those large blocks in order to regroup as much relevant data as possible in such chunks. Hence, we attempt to intelligently co-locate spatially adjacent data from the 3D space into the same 1D chunks on disk, in order to minimize the number of data chunks accessed through the filesystem to answer a given spatial query. We hence express the cost of a query as follows:
The Perspective Geometry of the Eye: Toward Image-Based Eye-Tracking

Eye-tracking applications are used in large variety of fields of research: neuro-science, psychology, human-computer interfaces, marketing and advertising, and computer science. The commonly known techniques are: contact lens method (Robinson, 1963), electro-oculography (Kaufman et al., 1993), limbus tracking with photo-resistors (Reulen et al., 1988; Stark et al., 1962), corneal reflection (Eizenman et al., 1984; Morimoto et al., 2000) and Purkinje image tracking (Cornsweet & Crane, 1973; Crane & Steele, 1978).