Spatial Impact Network Exposure Model (SINEM) with Integration of Traffic Characteristics and Air Pollution Concentration

The State of Qatar has undergone rapid economic growth and urbanization during the last few decades. This has resulted in an increase in the number of motor vehicles in the country. Therefore, it is vital to monitor and manage the air pollution level in Qatar. Trafficrelated air pollutants generally have a significant contribution to air pollution especially in urban areas and they also have an adverse impact on the commuters and abutting street population. Limited study has been carried out in this area and particularly in the context of Qatar. The purpose of this research is to establish a relationship between air pollution concentration and a set of parameters related to traffic and network characteristics; such as traffic volume, speed, VCR, etc. This study aims to develop an area-wide Spatial Impact Network Exposure Model (SINEM) using Geographic Information System (GIS). The SINEM shall be developed to assess the area-wide spatial impact of trafficrelated air pollution exposure based on an aggregated approach. This model helps to predict the surrounding network exposure index which helps in the decision-making process. Interestingly, this model also has the potential to scale up as well as convert into a real-time model. It will assist relevant authorities and decision-makers to identify and initialize policy measures to reduce the exposure impact, setting up building regulations, FAR implementation and sustainable master plan development

Of cattle, sand flies and men : a systematic review of risk factor analyses for South Asian visceral leishmaniasis and implications for elimination

Background: Studies performed over the past decade have identified fairly consistent epidemiological patterns of risk factors for visceral leishmaniasis (VL) in the Indian subcontinent. Methods and Principal Findings: To inform the current regional VL elimination effort and identify key gaps in knowledge, we performed a systematic review of the literature, with a special emphasis on data regarding the role of cattle because primary risk factor studies have yielded apparently contradictory results. Because humans form the sole infection reservoir, clustering of kala-azar cases is a prominent epidemiological feature, both at the household level and on a larger scale. Subclinical infection also tends to show clustering around kala-azar cases. Within villages, areas become saturated over a period of several years; kala-azar incidence then decreases while neighboring areas see increases. More recently, post kalaazar dermal leishmaniasis (PKDL) cases have followed kala-azar peaks. Mud walls, palpable dampness in houses, and peridomestic vegetation may increase infection risk through enhanced density and prolonged survival of the sand fly vector. Bed net use, sleeping on a cot and indoor residual spraying are generally associated with decreased risk. Poor micronutrient status increases the risk of progression to kala-azar. The presence of cattle is associated with increased risk in some studies and decreased risk in others, reflecting the complexity of the effect of bovines on sand fly abundance, aggregation, feeding behavior and leishmanial infection rates. Poverty is an overarching theme, interacting with individual risk factors on multiple levels. Conclusions: Carefully designed demonstration projects, taking into account the complex web of interconnected risk factors, are needed to provide direct proof of principle for elimination and to identify the most effective maintenance activities to prevent a rapid resurgence when interventions are scaled back. More effective, short-course treatment regimens for PKDL are urgently needed to enable the elimination initiative to succeed

MOLA: a bootable, self-configuring system for virtual screening using AutoDock4/Vina on computer clusters

<p>Abstract</p> <p>Background</p> <p>Virtual screening of small molecules using molecular docking has become an important tool in drug discovery. However, large scale virtual screening is time demanding and usually requires dedicated computer clusters. There are a number of software tools that perform virtual screening using AutoDock4 but they require access to dedicated Linux computer clusters. Also no software is available for performing virtual screening with Vina using computer clusters. In this paper we present MOLA, an easy-to-use graphical user interface tool that automates parallel virtual screening using AutoDock4 and/or Vina in bootable non-dedicated computer clusters.</p> <p>Implementation</p> <p>MOLA automates several tasks including: ligand preparation, parallel AutoDock4/Vina jobs distribution and result analysis. When the virtual screening project finishes, an open-office spreadsheet file opens with the ligands ranked by binding energy and distance to the active site. All results files can automatically be recorded on an USB-flash drive or on the hard-disk drive using VirtualBox. MOLA works inside a customized Live CD GNU/Linux operating system, developed by us, that bypass the original operating system installed on the computers used in the cluster. This operating system boots from a CD on the master node and then clusters other computers as slave nodes via ethernet connections.</p> <p>Conclusion</p> <p>MOLA is an ideal virtual screening tool for non-experienced users, with a limited number of multi-platform heterogeneous computers available and no access to dedicated Linux computer clusters. When a virtual screening project finishes, the computers can just be restarted to their original operating system. The originality of MOLA lies on the fact that, any platform-independent computer available can he added to the cluster, without ever using the computer hard-disk drive and without interfering with the installed operating system. With a cluster of 10 processors, and a potential maximum speed-up of 10x, the parallel algorithm of MOLA performed with a speed-up of 8,64× using AutoDock4 and 8,60× using Vina.</p

Classical kinetic energy, quantum fluctuation terms and kinetic-energy functionals

We employ a recently formulated dequantization procedure to obtain an exact expression for the kinetic energy which is applicable to all kinetic-energy functionals. We express the kinetic energy of an N-electron system as the sum of an N-electron classical kinetic energy and an N-electron purely quantum kinetic energy arising from the quantum fluctuations that turn the classical momentum into the quantum momentum. This leads to an interesting analogy with Nelson's stochastic approach to quantum mechanics, which we use to conceptually clarify the physical nature of part of the kinetic-energy functional in terms of statistical fluctuations and in direct correspondence with Fisher Information Theory. We show that the N-electron purely quantum kinetic energy can be written as the sum of the (one-electron) Weizsacker term and an (N-1)-electron kinetic correlation term. We further show that the Weizsacker term results from local fluctuations while the kinetic correlation term results from the nonlocal fluctuations. For one-electron orbitals (where kinetic correlation is neglected) we obtain an exact (albeit impractical) expression for the noninteracting kinetic energy as the sum of the classical kinetic energy and the Weizsacker term. The classical kinetic energy is seen to be explicitly dependent on the electron phase and this has implications for the development of accurate orbital-free kinetic-energy functionals. Also, there is a direct connection between the classical kinetic energy and the angular momentum and, across a row of the periodic table, the classical kinetic energy component of the noninteracting kinetic energy generally increases as Z increases.Comment: 10 pages, 1 figure. To appear in Theor Chem Ac

Studying strategies and types of players:Experiments, logics and cognitive models

How do people reason about their opponent in turn-taking games? Often, people do not make the decisions that game theory would prescribe. We present a logic that can play a key role in understanding how people make their decisions, by delineating all plausible reasoning strategies in a systematic manner. This in turn makes it possible to construct a corresponding set of computational models in a cognitive architecture. These models can be run and fitted to the participants’ data in terms of decisions, response times, and answers to questions. We validate these claims on the basis of an earlier game-theoretic experiment about the turn-taking game “Marble Drop with Surprising Opponent”, in which the opponent often starts with a seemingly irrational move. We explore two ways of segregating the participants into reasonable “player types”. The first way is based on latent class analysis, which divides the players into three classes according to their first decisions in the game: Random players, Learners, and Expected players, who make decisions consistent with forward induction. The second way is based on participants’ answers to a question about their opponent, classified according to levels of theory of mind: zero-order, first-order and second-order. It turns out that increasing levels of decisions and theory of mind both correspond to increasing success as measured by monetary awards and increasing decision times. Next, we use the logical language to express different kinds of strategies that people apply when reasoning about their opponent and making decisions in turn-taking games, as well as the ‘reasoning types’ reflected in their behavior. Then, we translate the logical formulas into computational cognitive models in the PRIMs architecture. Finally, we run two of the resulting models, corresponding to the strategy of only being interested in one’s own payoff and to the myopic strategy, in which one can only look ahead to a limited number of nodes. It turns out that the participant data fit to the own-payoff strategy, not the myopic one. The article closes the circle from experiments via logic and cognitive modelling back to predictions about new experiments

Determination of monolayer-protected gold nanoparticle ligand–shell morphology using NMR

It is accepted that the ligand shell morphology of nanoparticles coated with a monolayer of molecules can be partly responsible for important properties such as cell membrane penetration and wetting. When binary mixtures of molecules coat a nanoparticle, they can arrange randomly or separate into domains, for example, forming Janus, patchy or striped particles. To date, there is no straightforward method for the determination of such structures. Here we show that a combination of one-dimensional and two-dimensional NMR can be used to determine the ligand shell structure of a series of particles covered with aliphatic and aromatic ligands of varying composition. This approach is a powerful way to determine the ligand shell structure of patchy particles; it has the limitation of needing a whole series of compositions and ligands' combinations with NMR peaks well separated and whose shifts due to the surrounding environment can be large enough

Digital Art as ‘Monetised Graphics:’ Enforcing Intellectual Property on the Blockchain

In a global economic landscape of hyper-commodification and financialisation, efforts to assimilate digital art into the high-stakes commercial art market have so far been rather unsuccessful, presumably because digital art works cannot easily assume the status of precious object worthy of collection. This essay explores the use of blockchain technologies in attempts to create proprietary digital art markets in which uncommodifiable digital art works are financialised as artificially scarce commodities. Using the decentralisation techniques and distributed database protocols underlying current cryptocurrency technologies, such efforts, exemplified here by the platform Monegraph, tend to be presented as concerns with the interest of digital artists and with shifting ontologies of the contemporary work of art. I challenge this characterisation, and argue, in a discussion that combines aesthetic theory, legal and philosophical theories of intellectual property, rhetorical analysis, and research in the political economy of new media, that the formation of proprietary digital art markets by emerging commercial platforms such as Monegraph constitutes a worrisome amplification of long-established, on-going efforts to fence in creative expression as private property. As I argue, the combination of blockchain-based protocols with established ambitions of intellectual property policy yields hybrid conceptual-computational financial technologies (such as self-enforcing smart contracts attached to digital artefacts) that are unlikely to empower artists, but which serve to financialise digital creative practices as a whole, curtailing the critical potential of the digital as an inherently dynamic and potentially uncommodifiable mode of production and artistic expression

The Role of IRE1α in the Degradation of Insulin mRNA in Pancreatic β-Cells

The endoplasmic reticulum (ER) is a cellular compartment for the biosynthesis and folding of newly synthesized secretory proteins such as insulin. Perturbations to ER homeostasis cause ER stress and subsequently activate cell signaling pathways, collectively known as the Unfolded Protein Response (UPR). IRE1α is a central component of the UPR. In pancreatic β-cells, IRE1α also functions in the regulation of insulin biosynthesis.Here we report that hyperactivation of IRE1α caused by chronic high glucose treatment or IRE1α overexpression leads to insulin mRNA degradation in pancreatic β-cells. Inhibition of IRE1α signaling using its dominant negative form prevents insulin mRNA degradation. Islets from mice heterozygous for IRE1α retain expression of more insulin mRNA after chronic high glucose treatment than do their wild-type littermates.These results reveal a role of IRE1α in insulin mRNA expression under ER stress conditions caused by chronic high glucose. The rapid degradation of insulin mRNA could provide immediate relief for the ER and free up the translocation machinery. Thus, this mechanism would preserve ER homeostasis and help ensure that the insulin already inside the ER can be properly folded and secreted. This adaptation may be crucial for the maintenance of β-cell homeostasis and may explain why the β-cells of type 2 diabetic patients with chronic hyperglycemia stop producing insulin in the absence of apoptosis. This mechanism may also be involved in suppression of the autoimmune type 1 diabetes by reducing the amount of misfolded insulin, which could be a source of “neo-autoantigens.

Foundations of Black Hole Accretion Disk Theory

This review covers the main aspects of black hole accretion disk theory. We begin with the view that one of the main goals of the theory is to better understand the nature of black holes themselves. In this light we discuss how accretion disks might reveal some of the unique signatures of strong gravity: the event horizon, the innermost stable circular orbit, and the ergosphere. We then review, from a first-principles perspective, the physical processes at play in accretion disks. This leads us to the four primary accretion disk models that we review: Polish doughnuts (thick disks), Shakura-Sunyaev (thin) disks, slim disks, and advection-dominated accretion flows (ADAFs). After presenting the models we discuss issues of stability, oscillations, and jets. Following our review of the analytic work, we take a parallel approach in reviewing numerical studies of black hole accretion disks. We finish with a few select applications that highlight particular astrophysical applications: measurements of black hole mass and spin, black hole vs. neutron star accretion disks, black hole accretion disk spectral states, and quasi-periodic oscillations (QPOs).Comment: 91 pages, 23 figures, final published version available at http://www.livingreviews.org/lrr-2013-