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Local variations in the intergalactic medium (IGM) neutral hydrogen fraction will affect the Ly-? absorption signature of protoclusters identified in tomographic surveys. Using the IllustrisTNG simulations, we investigate how the AGN proximity effect and hot, collisionally ionised gas arising from gravitational infall and black hole feedback changes the Ly-? absorption associated with Mz = 0 ? 1014?M? protoclusters at z ? 2.4. We find that protocluster galaxy overdensities exhibit a weak anti-correlation with Ly-? transmission in IGM transmission maps, but local HI ionisation enhancements due to hot T>106K gas or nearby AGN can disrupt this relationship within individual protoclusters. On average, however, we find that strong reductions in the IGM neutral fraction are limited to within ? 5h?1?cMpc of the dark matter haloes. Local ionisation enhancements will therefore have a minimal impact on the completeness of protocluster identification in tomographic surveys if smoothing Ly-? transmission maps over scales of ?4h?1?cMpc, as is typically done in observations. However, if calibrating the relationship between the matter density and Ly-? transmission in tomographic maps using simple analytical models for the Ly-? forest opacity, the presence of hot gas around haloes can still result in systematically lower estimates of Mz = 0 for the most massive protoclusters.

Local variations in the intergalactic medium (IGM) neutral hydrogen fraction will affect the Ly-$��$ absorption signature of protoclusters identified in tomographic surveys. Using the IllustrisTNG simulations, we investigate how the AGN proximity effect and hot, collisionally ionised gas arising from gravitational infall and black hole feedback changes the Ly-$��$ absorption associated with $M_{z=0}\simeq10^{14}\,M_\odot$ protoclusters at $z\simeq2.4$. We find that protocluster galaxy overdensities exhibit a weak anti-correlation with Ly-$��$ transmission in IGM transmission maps, but local HI ionisation enhancements due to hot $T>10^{6}\rm\,K$ gas or nearby AGN can disrupt this relationship within individual protoclusters. On average, however, we find that strong reductions in the IGM neutral fraction are limited to within $\lesssim 5h^{-1}\,\textrm{cMpc}$ of the dark matter haloes. Local ionisation enhancements will therefore have a minimal impact on the completeness of protocluster identification in tomographic surveys if smoothing Ly-$��$ transmission maps over scales of $\sim4 h^{-1}\,\textrm{cMpc}$, as is typically done in observations. However, if calibrating the relationship between the matter density and Ly-$��$ transmission in tomographic maps using simple analytical models for the Ly-$��$ forest opacity, the presence of hot gas around haloes can still result in systematically lower estimates of $M_{z=0}$ for the most massive protoclusters., 14 pages (including 1 appendix), 5 figures (plus 2 in the appendix), 1 table. Accepted for publication in MNRAS

Copyright: © 2021 Havumaki et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. There is an emerging consensus that achieving global tuberculosis control targets will require more proactive case finding approaches than are currently used in high-incidence settings. Household contact tracing (HHCT), for which households of newly diagnosed cases are actively screened for additional infected individuals is a potentially efficient approach to finding new cases of tuberculosis, however randomized trials assessing the population-level effects of such interventions in settings with sustained community transmission have shown mixed results. One potential explanation for this is that household transmission is responsible for a variable proportion of population-level tuberculosis burden between settings. For example, transmission is more likely to occur in households in settings with a lower tuberculosis burden and where individuals mix preferentially in local areas, compared with settings with higher disease burden and more dispersed mixing. To better understand the relationship between endemic incidence levels, social mixing, and the impact of HHCT, we developed a spatially explicit model of coupled household and community transmission. We found that the impact of HHCT was robust across settings of varied incidence and community contact patterns. In contrast, we found that the effects of community contact tracing interventions were sensitive to community contact patterns. Our results suggest that the protective benefits of HHCT are robust and the benefits of this intervention are likely to be maintained across epidemiological settings.

Introduction Since its onset, the COVID-19 pandemic has caused significant morbidity and mortality worldwide, with particularly severe outcomes in healthcare institutions and congregate settings. To mitigate spread, healthcare systems have been cohorting patients to limit contacts between uninfected patients and potentially infected patients or healthcare workers (HCWs). A major challenge in managing the pandemic is the presence of currently asymptomatic/presymptomatic individuals capable of transmitting the virus, who could introduce COVID-19 into uninfected cohorts. The optimal combination of personal protective equipment (PPE), testing and other approaches to prevent these events is unclear, especially in light of ongoing limited resources. Methods Using stochastic simulations with a susceptible-exposed-infected-recovered dynamic model, we quantified and compared the impacts of PPE use, patient and HCWs surveillance testing and subcohorting strategies. Results In the base case without testing or PPE, the healthcare system was rapidly overwhelmed, and became a net contributor to the force of infection. We found that effective use of PPE by both HCWs and patients could prevent this scenario, while random testing of apparently asymptomatic/presymptomatic individuals on a weekly basis was less effective. We also found that even imperfect use of PPE could provide substantial protection by decreasing the force of infection. Importantly, we found that creating smaller patient/HCW-interaction subcohorts can provide additional resilience to outbreak development with limited resources. Conclusion These findings reinforce the importance of ensuring adequate PPE supplies even in the absence of testing and provide support for strict subcohorting regimens to reduce outbreak potential in healthcare institutions.

Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.

The contact structure of a population plays an important role in transmission of infection. Many ``structured models'' capture aspects of the contact structure through an underlying network or a mixing matrix. An important observation in such models, is that once a fraction $1-1/\mathcal{R}_0$ has been infected, the residual susceptible population can no longer sustain an epidemic. A recent observation of some structured models is that this threshold can be crossed with a smaller fraction of infected individuals, because the disease acts like a targeted vaccine, preferentially immunizing higher-risk individuals who play a greater role in transmission. Therefore, a limited ``first wave'' may leave behind a residual population that cannot support a second wave once interventions are lifted. In this paper, we systematically analyse a number of mean-field models for networks and other structured populations to address issues relevant to the Covid-19 pandemic. In particular, we consider herd-immunity under several scenarios. We confirm that, in networks with high degree heterogeneity, the first wave confers herd-immunity with significantly fewer infections than equivalent models with lower degree heterogeneity. However, if modelling the intervention as a change in the contact network, then this effect might become more subtle. Indeed, modifying the structure can shield highly connected nodes from becoming infected during the first wave and make the second wave more substantial. We confirm this finding by using an age-structured compartmental model parameterised with real data and comparing lockdown periods implemented either as a global scaling of the mixing matrix or age-specific structural changes. We find that results regarding herd immunity levels are strongly dependent on the model, the duration of lockdown and how lockdown is implemented., 25 pages, 9 figures, 1 Table

SARS-CoV-2 causing COVID-19 disease has moved rapidly around the globe, infecting millions and killing hundreds of thousands. The basic reproduction number, which has been widely used and misused to characterize the transmissibility of the virus, hides the fact that transmission is stochastic, is dominated by a small number of individuals, and is driven by super-spreading events (SSEs). The distinct transmission features, such as high stochasticity under low prevalence, and the central role played by SSEs on transmission dynamics, should not be overlooked. Many explosive SSEs have occurred in indoor settings stoking the pandemic and shaping its spread, such as long-term care facilities, prisons, meat-packing plants, fish factories, cruise ships, family gatherings, parties and night clubs. These SSEs demonstrate the urgent need to understand routes of transmission, while posing an opportunity that outbreak can be effectively contained with targeted interventions to eliminate SSEs. Here, we describe the potential types of SSEs, how they influence transmission, and give recommendations for control of SARS-CoV-2., 10 pages, 3 figures

© 2020 Althouse et al. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiological agent of the Coronavirus Disease 2019 (COVID-19) disease, has moved rapidly around the globe, infecting millions and killing hundreds of thousands. The basic reproduction number, which has been widely used appropriately and less appropriately to characterize the transmissibility of the virus, hides the fact that transmission is stochastic, often dominated by a small number of individuals, and heavily influenced by superspreading events (SSEs). The distinct transmission features of SARS-CoV-2, e.g., high stochasticity under low prevalence (as compared to other pathogens, such as influenza), and the central role played by SSEs on transmission dynamics cannot be overlooked. Many explosive SSEs have occurred in indoor settings, stoking the pandemic and shaping its spread, such as long-Term care facilities, prisons, meat-packing plants, produce processing facilities, fish factories, cruise ships, family gatherings, parties, and nightclubs. These SSEs demonstrate the urgent need to understand routes of transmission, while posing an opportunity to effectively contain outbreaks with targeted interventions to eliminate SSEs. Here, we describe the different types of SSEs, how they influence transmission, empirical evidence for their role in the COVID-19 pandemic, and give recommendations for control of SARS-CoV-2.

Supplemental material, Online_Apendix for Juvenile Probation Officer Decision-Making in a Reforming State: Assessing the Application of Evidence-Based Principles by Joel Miller and Krissinda Palmer in Criminal Justice and Behavior

We consider the spread of a Susceptible-Infected-Recovered (SIR) disease through finite populations and derive an expression for the final size distribution. Our derivation allows arbitrary distributions of the number of transmissions caused by an infected individual. We show how this calculation can be used to infer parameters of the infectious disease through observations in multiple small populations. The inference suffers from some identifiability difficulties, and it requires many observations to distinguish between parameter combinations that correspond to the same reproductive number.

We use state of the art hydrodyamical simulations from the Sherwood, EAGLE and Illustris projects to examine the signature of $M_{\rm z=0}\simeq 10^{14}M_{\odot}$ protoclusters observed in Ly-$��$ absorption at $z\simeq 2.4$. We find there is a weak correlation between the mass overdensity, $��_{\rm m}$, and the Ly-$��$ effective optical depth relative to the mean, $��_{��_\textrm{eff}}$, averaged over $15~h^{-1}\rm\,cMpc$ scales, although scatter in the $��_{\rm m}$--$��_{��_\textrm{eff}}$ plane means it is not possible to uniquely identify large scale overdensities with strong Ly-$��$ absorption. Although all protoclusters are associated with large scale mass overdensities, most sight lines through protoclusters in a $\sim 10^{6}$ $\rm cMpc^{3}$ volume probe the low column density Ly-$��$ forest. A small subset of sight lines that pass through protoclusters exhibit coherent, strong Ly-$��$ absorption on $15h^{-1}\rm\,cMpc$ scales, although these correspond to a wide range in mass overdensity. Assuming perfect removal of contamination by Ly-$��$ absorbers with damping wings, more than half of the remaining sight lines with $��_{��_{\rm eff}}>3.5$ trace protoclusters. It is furthermore possible to identify a model dependent $��_{��_{\rm eff}}$ threshold that selects only protoclusters. However, such regions are rare: excluding absorption caused by damped systems, less than 0.1 per cent of sight lines that pass through a protocluster have $��_{��_{\rm eff}}>3.5$, meaning that any protocluster sample selected in this manner will also be highly incomplete. On the other hand, coherent regions of Ly-$��$ absorption also provide a promising route for identifying and studying filamentary environments at high redshift., 18 pages, 18 figures, 3 tables; accepted for publication in MNRAS

Pairwise models are used widely to model epidemic spread on networks. These include the modelling of susceptible-infected-removed (SIR) epidemics on regular networks and extensions to SIS dynamics and contact tracing on more exotic networks exhibiting degree heterogeneity, directed and/or weighted links and clustering. However, extra features of the disease dynamics or of the network lead to an increase in system size and analytical tractability becomes problematic. Various `closures' can be used to keep the system tractable. Focusing on SIR epidemics on regular but clustered networks, we show that even for the most complex closure we can determine the epidemic threshold as an asymptotic expansion in terms of the clustering coefficient.We do this by exploiting the presence of a system of fast variables, specified by the correlation structure of the epidemic, whose steady state determines the epidemic threshold. While we do not find the steady state analytically, we create an elegant asymptotic expansion of it. We validate this new threshold by comparing it to the numerical solution of the full system and find excellent agreement over a wide range of values of the clustering coefficient, transmission rate and average degree of the network. The technique carries over to pairwise models with other closures [1] and we note that the epidemic threshold will be model dependent. This emphasises the importance of model choice when dealing with realistic outbreaks., 12 pages, 9 figures. arXiv admin note: substantial text overlap with arXiv:1806.06135

El presente trabajo investigativo de seminario de graduación está referido la valoración de instrumentos financieros a largo plazo, puesto que existe una considerable cantidad de personas que desconocen esta temática, se decidió abordar un caso práctico que explicara la valoración de instrumentos financieros a largo plazo de renta fija (bonos) . En este caso hemos valorado el precio de un Bono de la Republica de Nicaragua aplicando el método de valoración por costo amortizado. Para mejorar eficaz mete la comprensión acerca del tema en cuestión se decidió por comenzar describiendo conceptos claves como son: Mercados de capital, bolsa de valores, instrumentos financieros, método de valoración, bonos, BRN emitidos por el MHCP entre otros. Una vez presentados todos los conceptos básicos se valoró el instrumento en cuestión y se determinó la tabla de amortización donde se detallaba el costo amortizado de cada período. Mediante el procedimiento de valoración por costo amortizado obtuvimos datos relevantes mismos que nos sirvieron para la aplicación de los tres indicadores financieros básicos de una inversión para su posterior análisis de rentabilidad. Tras valorar dicho instrumento de inversión (BRN) se logró conocer que la inversión en bonos de la republica de Nicaragua es libre de riesgos ya que está respaldada por las reservas del tesoro de Nicaragua, así mismo determinamos que es rentable para personas que buscan una rentabilidad aproximadamente del 9.95% de su inversión a largo plazo. Este trabajo de seminario de graduación es de carácter documental ya que se recopilo, seleccionó, analizó y presentó información pertinente para la explicación de los contenidos abordados mismos que fueron abordados para el entendimiento del caso práctico, pues fueron consultadas fuentes de información tales como: revistas, documentos, libros y artículos de páginas web debidamente revisados y fundamentados.

Random network models play a prominent role in modeling, analyzing and understanding complex phenomena on real-life networks. However, a key property of networks is often neglected: many real-world networks exhibit spatial structure, the tendency of a node to select neighbors with a probability depending on physical distance. Here, we introduce a class of random spatial networks (RSNs) which generalizes many existing random network models but adds spatial structure. In these networks, nodes are placed randomly in space and joined in edges with a probability depending on their distance and their individual expected degrees, in a manner that crucially remains analytically tractable. We use this network class to propose a new generalization of small-world networks, where the average shortest path lengths in the graph are small, as in classical Watts-Strogatz small-world networks, but with close spatial proximity of nodes that are neighbors in the network playing the role of large clustering. Small-world effects are demonstrated on these spatial small-world networks without clustering. We are able to derive partial integro-differential equations governing susceptible-infectious-recovered disease spreading through an RSN, and we demonstrate the existence of traveling wave solutions. If the distance kernel governing edge placement decays slower than exponential, the population-scale dynamics are dominated by long-range hops followed by local spread of traveling waves. This provides a theoretical modeling framework for recent observations of how epidemics like Ebola evolve in modern connected societies, with long-range connections seeding new focal points from which the epidemic locally spreads in a wavelike manner.

We revisit the size distribution of finite components in infinite Configuration Model networks. We provide an elementary combinatorial proof about the sizes of birth-death trees which is more intuitive than previous proofs. We use this to rederive the component size distribution for Configuration Model networks. Our derivation provides a more intuitive interpretation of the formula as contrasted with the previous derivation based on contour integrations. We demonstrate that the formula performs well, even on networks with heavy tails which violate assumptions of the derivation. We explain why the result should remain robust for these networks., Comment: [just updating a few minor typos and obvious little issues. No change to main argument]

Organic semiconductors find increasing importance in spin transport devices due to the modulation and control of their properties through chemical synthetic versatility. The organic materials are used as interlayers between two ferromagnet (FM) electrodes in organic spin valves (OSV), as well as for magnetic spin manipulation of metal-organic complexes at the molecular level. In the latter, specifically, the substrate-induced magnetic switching in a paramagnetic molecule has been evoked extensively, but studied by delicate surface spectroscopies. Here we present evidence of the substantial magnetic switching in a nanosized thin film of the paramagnetic molecule, tris(8-hydroxyquinoline)iron(III) (Feq3) deposited on a FM substrate, using the magnetoresistance response of electrical spin-injection in an OSV structure, and the inverse-spin-Hall effect induced by state-of-art pulsed microwave spin-pumping. We show that interfacial spin control at the molecular level may lead to a macroscopic organic spin transport device, thus, bridging the gap between organic spintronics and molecular spintronics.

Around the world, police departments, policy makers, and communities have struggled to develop best practices that ensure the delivery of both fair and effective policing. Recently, five police departments in Spain undertook an ambitious reform program intended to reduce ethnic profiling and increase the effectiveness and fairness of police stops and searches. Their collective experience shows that change is possible—while also illustrating the challenges and resources required to make change sustainable. Through a series of steps outlined in this report, police agencies reduced the ethnic disproportionality of their stops, increased the effectiveness of stops, while reducing the total number of people stopped, and improved relations with ethnic minority communities. This report, produced by the Open Society Justice Initiative and the Plataforma por la Gestión Policial de la Diversidad, is both a description of reform efforts and a prescription—grounded in day-to-day experience—for how police departments can carry out reforms and what can be achieved. By combining a narrative account of how the reforms were implemented with data on the impact of the reforms, Fair and Effective Police Stops provides a roadmap for any police service seeking to improve the fairness and effectiveness of its work.

A complex contagion is an infectious process in which individuals may require multiple transmissions before changing state. These are used to model behaviors if an individual only adopts a particular behavior after perceiving a consensus among others. We may think of individuals as beginning inactive and becoming active after contact with a sufficient number of active partners. These have been studied in a number of cases, but analytic models for the dynamic spread of complex contagions are typically complex. Here we study the dynamics of the Watts Threshold Model (WTM) assuming transmission occurs in continuous time as a Poisson process, or in discrete time where individuals transmit to all partners in the time step following their activation. We adapt techniques developed for infectious disease modeling to develop and analyze analytic models for the dynamics of the WTM in Configuration Model networks and a class of random clustered (triangle-based) networks. The resulting model is relatively simple and compact. We use it to gain insights into the contagion dynamics. In the infinite population limit, we derive conditions under which cascades happen with an arbitrarily small initial proportion active, confirming a hypothesis of Watts for this case. We also observe hybrid phase transitions when cascades are not possible for small initial conditions, but occur for large enough initial conditions. We derive sufficient conditions for this hybrid phase transition to occur. We show that in many cases, if the hybrid phase transition occurs, all individuals eventually become active. Finally, we discuss the role clustering plays in facilitating or impeding the spread and find that the hypothesis of Watts that was confirmed in Configuration Model networks does not hold in general. This approach allows us to unify many existing disparate observations and derive new results., key words: Watts Threshold Model, Cascades, Hybrid Bifurcation, Complex Contagion, Dynamic Model

This dissertation is concerned with the theoretical study of the stability of viscoelastic shear flows. It is divided into two parts: part I studies inertialess coextrusion flows at large Weissenberg number where the instabilities are due to discontinuities in the elastic properties, and part II studies the effect of elasticity on the well-known inertial instabilities of inviscid flows with inflection points. We begin part I with a previously known short-wave instability of Upper Convected Maxwell and Oldroyd–B fluids at zero Reynolds number in Couette flow. We show that if the Weissenberg number is large, the instability persists with the same growth rate when the wavelength is longer than the channel width. Intriguingly, surface tension does not modify the growth rate. Previous explanations of elastic interfacial instabilities based on the jump in normal stress at the interface cannot apply to this instability. These results are confirmed both numerically and with asymptotic methods. We then consider Poiseuille flow and show that a new class of instability exists if the interface is close to the center-line. We analyse the scalings and show that it results from a change in the boundary layer structure of the Couette instability. The growth rates can be large, and the wavespeed can be faster than the base flow advection. We are unable to simplify the equations significantly, and asymptotic results are not available, so we use numerics to verify the results. In studying these instabilities we encounter some others which we mention, but do not analyse in detail. In part II we study the effect of elasticity on the inertial instability of flows with inflection points. We show that the elasticity modifies the development of cat’s eyes. The presence of extensional flow complicates the analysis. Consequently we use the FENE–CR equations.

Carbon-carbon (CC) bonding is a key essence of organic and biochemistry. The length of a CC bond, i.e. 1.54 Å found in the diamond allotrope of carbon and ethane, is among the essential information learned by all chemistry students. This is the length of a single bond () between sp3-hybridized carbons and is the longest of all common CC bonds. Our studies of the [TCNE]22- (TCNE = tetracyanoethylene) dimers reveal that 2.89 ± 0.05 Å 2 electron/4 center (2e-/4c) CC bonds are present. Structural, spectroscopic, magnetic, and computational data supporting this multicenter formulation will be presented. These unusual bonds lead to unusual physical properties that will be discussed, as will what is a chemical bond? Furthermore, examples of long, multicenter C-C bonds existing for other dianions, e.g., [cyanil]22-, as well as dications, e.g., [TTF]22+ (TTF = tetrathiafulvalene), and homo-, e.g., [tri-t-butylphenalenyl]2, and zwitterionic heterodimers e.g., TTF+•••´TCNE-( ~ 0.5), will be discussed. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.

Epidemic spreading phenomena are ubiquitous in nature and society. Examples include the spreading of diseases, information, and computer viruses. Epidemics can spread by local spreading, where infected nodes can only infect a limited set of direct target nodes and global spreading, where an infected node can infect every other node. In reality, many epidemics spread using a hybrid mixture of both types of spreading. In this study we develop a theoretical framework for studying hybrid epidemics, and examine the optimum balance between spreading mechanisms in terms of achieving the maximum outbreak size. We show the existence of critically hybrid epidemics where neither spreading mechanism alone can cause a noticeable spread but a combination of the two spreading mechanisms would produce an enormous outbreak. Our results provide new strategies for maximising beneficial epidemics and estimating the worst outcome of damaging hybrid epidemics.

The ger districts, so named for the traditional felt tents that are still prevalent in the domestic landscape of Ulaanbaatar, Mongolia, retain a connection to their nomadic heritage. But those who dwell here are now removed from the pastoral production systems of the countryside as they struggle to establish a place for themselves at the edge of the city. This dissertation first locates the place of the ger districts between the countryside and the city, then delves into how land within the ger districts is subdivided for settlement. With the nature of access to land established, the investigation turns to ethnographic methods of participant-observation and semi-structured interviews combined with architecturally-based research into the visual and material culture of the built environment. The aim is to better understand residents' quotidian practices of constructing and inhabiting peri-urban neighborhoods of informal housing. Conclusions find that ger district residents are finding their own way forward through strategies that transform domesticity into economic and social participation. The transmutation of mobility, from a nomadic past toward an urban future provides a unique model for academic understanding of self-built housing areas as well as the more generalizable practices and policies concerning settlements in an increasingly urbanized world.

The primary tool for predicting infectious disease spread and intervention effectiveness is the mass action Susceptible-Infected-Recovered model of Kermack and McKendrick. Its usefulness derives largely from its conceptual and mathematical simplicity; however, it incorrectly assumes all individuals have the same contact rate and contacts are fleeting. This paper is the first of three investigating edge-based compartmental modeling, a technique eliminating these assumptions. In this paper, we derive simple ordinary differential equation models capturing social heterogeneity (heterogeneous contact rates) while explicitly considering the impact of contact duration. We introduce a graphical interpretation allowing for easy derivation and communication of the model. This paper focuses on the technique and how to apply it in different contexts. The companion papers investigate choosing the appropriate level of complexity for a model and how to apply edge-based compartmental modeling to populations with various sub-structures.

We consider the edge-based compartmental models for infectious disease spread introduced in Part I. These models allow us to consider standard SIR diseases spreading in random populations. In this paper we show how to handle deviations of the disease or population from the simplistic assumptions of Part I. We allow the population to have structure due to effects such as demographic detail or multiple types of risk behavior the disease to have more complicated natural history. We introduce these modifications in the static network context, though it is straightforward to incorporate them into dynamic networks. We also consider serosorting, which requires using the dynamic network models. The basic methods we use to derive these generalizations are widely applicable, and so it is straightforward to introduce many other generalizations not considered here.

To determine the performance of positron emission mammography (PEM), as compared with magnetic resonance (MR) imaging, including the effect on surgical management, in ipsilateral breasts with cancer.Four hundred seventy-two women with newly diagnosed breast cancer who were offered breast-conserving surgery consented from September 2006 to November 2008 to participate in a multicenter institutional review board-approved, HIPAA-compliant protocol. Participants underwent contrast material-enhanced MR imaging and fluorine 18 fluorodeoxyglucose PEM in randomized order; resultant images were interpreted independently. Added biopsies and changes in surgical procedure for the ipsilateral breast were correlated with histopathologic findings. Performance characteristics were compared by using the McNemar test and generalized estimating equations.Three hundred eighty-eight women (median age, 58 years; age range, 26-93 years; median estimated tumor size, 1.5 cm) completed the study. Additional cancers were found in 82 (21%) women (82 ipsilateral breasts; median tumor size, 0.7 cm). Twenty-eight (34%) of the 82 breasts were identified with both PEM and MR imaging; 21 (26%) breasts, with MR imaging only; 14 (17%) breasts, with PEM only; and seven (8.5%) breasts, with mammography and ultrasonography. Twelve (15%) cases of additional cancer were missed at all imaging examinations. Integration of PEM and MR imaging increased cancer detection-to 61 (74%) of 82 breasts versus 49 (60%) of 82 breasts identified with MR imaging alone (P.001). Of 306 breasts without additional cancer, 279 (91.2%) were correctly assessed with PEM compared with 264 (86.3%) that were correctly assessed with MR imaging (P = .03). The positive predictive value of biopsy prompted by PEM findings (47 [66%] of 71 cases) was higher than that of biopsy prompted by MR findings (61 [53%] of 116 cases) (P = .016). Of 116 additional cancers, 61 (53%) were depicted by MR imaging and 47 (41%) were depicted by PEM (P = .043). Fifty-six (14%) of the 388 women required mastectomy: 40 (71%) of these women were identified with MR imaging, and 20 (36%) were identified with PEM (P.001). Eleven (2.8%) women underwent unnecessary mastectomy, which was prompted by only MR findings in five women, by only PEM findings in one, and by PEM and MR findings in five. Thirty-three (8.5%) women required wider excision: 24 (73%) of these women were identified with MR imaging, and 22 (67%) were identified with PEM.PEM and MR imaging had comparable breast-level sensitivity, although MR imaging had greater lesion-level sensitivity and more accurately depicted the need for mastectomy. PEM had greater specificity at the breast and lesion levels. Eighty-nine (23%) participants required more extensive surgery: 61 (69%) of these women were identified with MR imaging, and 41 (46%) were identified with PEM (P = .003). Fourteen (3.6%) women had tumors seen only at PEM.

We consider the edge-based compartmental models for epidemic spread developed in Part I. We show conditions under which simpler models may be substituted for more detailed models, and in so doing we define a hierarchy of epidemic models. In particular we provide conditions under which it is appropriate to use the standard mass action SIR model, and we show what happens when these conditions fail. Using our hierarchy, we provide a procedure leading to the choice of the appropriate model for a given population. Our result about the convergence of models to the Mass Action model gives clear, rigorous conditions under which the Mass Action model is accurate.

Study Objective: Laryngeal mask airways (LMAs) are often used as airway rescue devices where laryngoscopy is difficult. The LMA does not protect the airway and is preferably replaced with a cuffed endotracheal tube. There are reports of cases where an Eschmann tracheal tube introducer (ETTI) was successfully used to bridge between a standard LMA and an endotracheal tube. This project was designed to determine whether an Eschmann stylet can reliably be passed through an LMA into the trachea as a means of rescue intubation. Methods: Nineteen emergency medicine residents and attending physicians, who were participants in a cadaveric airway course, placed and inflated a size 4 LMA (The Laryngeal Mask Company Ltd., San Diego, CA) on each of six unembalmed human cadavers in the usual fashion. They then attempted to pass a lubricated, 15 Fr, reusable, coude-tipped ETTI (Portex, Smiths Medical, Keene, NH)) through the airspace/handle of the inflated LMA. The LMA was then deflated and removed while the ETTI was held in place. Investigators then determined the location of the ETTI by laryngoscopy. Results: Of 114 attempts at the rescue procedure, 59 resulted in placement of the bougie into the trachea, yielding an overall success rate of 52% (95% CI 48%-56%). There were no significant differences in performance based on level of training of residents or years of experience of attending physicians. Conclusions: While not a primary difficult airway option, the use of a ETTI as a bridge device between LMA and endotracheal tube was successful about 50% of the time. [West J Emerg Med. 2010;11:16-19.]

The social networks that infectious diseases spread along are typically clustered. Because of the close relation between percolation and epidemic spread, the behavior of percolation in such networks gives insight into infectious disease dynamics. A number of authors have studied clustered networks, but the networks often contain preferential mixing between high degree nodes. We introduce a class of random clustered networks and another class of random unclustered networks with the same preferential mixing. We analytically show that percolation in the clustered networks reduces the component sizes and increases the epidemic threshold compared to the unclustered networks., The first version is being separated into multiple papers. This is the first of these to be submitted

Recent work by Erik Volz [arXiv:0705.2092] has shown how to calculate the growth and eventual decay of an SIR epidemic on a static random network, assuming infection and recovery each happen at constant rates. This calculation allows us to account for effects due to heterogeneity in degree that are neglected in the standard mass-action SIR equations. In this note we offer an alternate derivation which arrives at a simpler -- though equivalent -- system of governing equations to that of Volz. This new derivation is more closely connected to the underlying physical processes, and the resulting equations are of comparable complexity to the mass-action SIR equations. We further show that earlier derivations of the final size of epidemics on networks can be reproduced using the same approach, thereby providing a common framework for calculating both the dynamics and the final size of an epidemic spreading on a random network., Comment: compared to earlier drafts, have simplified the analysis and rearranged some sections. The equations are now simpler than earlier drafts

When an infectious disease strikes a population, the number of newly reported cases is often the only available information that one can obtain during early stages of the outbreak. An important goal of early outbreak analysis is to obtain a reliable estimate for the basic reproduction number, $R_{0}$, from the limited information available. We present a novel method that enables us to make a reliable real-time estimate of the reproduction number at a much earlier stage compared to other available methods. Our method takes into account the possibility that a disease has a wide distribution of infectious period and that the degree distribution of the contact network is heterogeneous. We validate our analytical framework with numerical simulations., Comment: 29 pages, 13 Figures

We analytically address disease outbreaks in large, random networks with heterogeneous infectivity and susceptibility. The transmissibility $T_{uv}$ (the probability that infection of $u$ causes infection of $v$) depends on the infectivity of $u$ and the susceptibility of $v$. Initially a single node is infected, following which a large-scale epidemic may or may not occur. We use a generating function approach to study how heterogeneity affects the probability that an epidemic occurs and, if one occurs, its attack rate (the fraction infected). For fixed average transmissibility, we find upper and lower bounds on these. An epidemic is most likely if infectivity is homogeneous and least likely if the variance of infectivity is maximized. Similarly, the attack rate is largest if susceptibility is homogeneous and smallest if the variance is maximized. We further show that heterogeneity in infectious period is important, contrary to assumptions of previous studies. We confirm our theoretical predictions by simulation. Our results have implications for control strategy design and identification of populations at higher risk from an epidemic., Comment: 5 pages, 3 figures. Submitted to Physical Review Letters

Molecules involving tetracyanoethylene (TCNE) and transition or rare earth compounds have been found to exhibit magnetic properties at low temperature. One compound, however, with V and TCNE has been found to have an ordering temperature above 300 K. A compound with Fe and TCNE has shown to exhibit 32% more magnetization in molecules than iron metal. Molecular magnet compounds can be dissolved in a solvent, added to a matrix such as a polymer, and do not require metallurgical processing. Since magnetism is a very basic science, application possibilities for molecular magnets are broad, stretching from nanotechnology to high density information storage.

This thesis develops a theoretical framework for explaining offending among young male offenders, and generates provisional insights and hypotheses about ethnic differences among this group. The study involves qualitative interviews with 51 young male offenders under sentence in Young Offender Institutions: 19 white, 14 Black-Caribbean, 8 Black-Mixed, and 10 Asian. The framework highlights how young males become offenders because of range of 'criminogenic constraints' in their backgrounds, consistent with strain, subcultural, control and psychological theories. However, it also highlights how individuals become offenders in part resulting from their own volition. That is, offenders help create some of the criminogenic constraints which contribute to their downfall, and must ultimately choose, actively, to pursue crime, over and above these constraints. This requires that they embrace certain motivations to develop into offenders. Such motivations are not simply reducible to the criminogenic constraints they experience, and draw potentially on wider cultural influences. Furthermore, these motivations play an important role in shaping the extent of their offending and the offences they carry out. The framework provides a basis for comparing ethnic groups. Importantly, the research suggests that there is much commonality among young male offenders from different ethnic groups. This being said, insights into possible ethnic differences were identified, which could be used to provide hypotheses for further research. White offenders appeared to have more psychological problems, serious drugs or alcohol problems and be more disposed towards burglaries and car crime. Black-Caribbean offenders appear to have fewer of these types of problems, appear more highly motivated by offending to spend on consumption-oriented lifestyles, and more often involved in robbery. Asian offenders appear to have the least difficulties in their backgrounds, but also appear least developed in their offending.

A 25-year database including daily temperatures and precipitation is analyzed for distributions, variations, trends and predictability for 17 counties on the Southern High Plains (SHP). Both minimum and maximum temperatures increase from north to south. However, diurnal temperature spread is distributed in a distinctly west to east fashion: a greater spread is noted in the west than in the eastern counties. In this region of interest, precipitation in terms of volume exhibits uniformity within the central and Southern counties. In the northern counties precipitation increases from west to east. As expected with a data set of this size, no precipitation or temperature trends are noted. A logarithmic distribution is shown to provide a primitive fit to wet-day and dry-day spells. Finally, Markov chain and gamma distribution models are used to describe and predict regional precipitation.

In this thesis, I use large scale state-of-the-art hydrodynamical cosmological simulations to investigate the Ly-α absorption properties of protocluster regions at redshift z∼2.4. Using the IllustrisTNG simulations, I investigate how the AGNproximity effect and hot, collisionally ionised gas arising from gravitational infall and black hole feedback changes the Ly-α absorption associated with the z≃2.4 progenitors of M≥10^14 M_☉ clusters. Within these protoclusters, I find that galaxy overdensities exhibit a weak anti-correlation with Ly-α transmission in tomographic maps of the intergalactic medium (IGM), but local HI ionisation enhancements due to hot T>10^6 K gas or nearby AGN can disrupt this relationship within individual protoclusters. On average, however, I find that strong reductions in the IGM neutral fraction are limited to within ≲5 h^−1 cMpc of the dark matter haloes. Local ionisation enhancements will therefore have a limited impact on the completeness of protocluster identification in tomographic surveys if smoothing Ly-α transmission maps over scales of ∼4 h^−1 cMpc, as is typically done in observations. However, if calibrating the relationship between the matter density and Ly-α transmission in tomographic maps using simple analytical models for the Ly-α forest opacity, the presence of hot gas around haloes may result in systematically lower estimates of the z=0 descendant mass of the most massive protoclusters. \ud \ud I then use simulations from the Sherwood, EAGLE and Illustris projects to examine the Ly-α absorption signatures of z∼2.4 protoclusters with a descendant mass of M≥10^14 M_☉. I find there is a weak correlation between the mass overdensity, δ_m, and the Ly-α effective optical depth relative to the mean, δ_τeff, averaged over 15 h^−1 cMpc scales; however, the scatter in the δ_m–δ_τeff plane means it is not possible to uniquely identify large scale overdensities with strong Ly-α absorption. Assuming perfect removal of contamination by Ly-α absorbers with damping wings, more than half of the remaining sightlines with δ_τeff>3.5 (CoSLAs) trace protoclusters. It is furthermore possible to identify a model dependent δ_τeff threshold that eliminates the contamination from filamentary structure and Lyman-limit systems that are preferentially aligned along the line of sight. However, such regions are rare: excluding absorption caused by damped systems, less than 0.1% of sightlines that pass through a protocluster have δ_τeff>3.5, meaning that any protocluster sample selected in this manner will also be highly incomplete. \ud \ud Finally, I use the TNG300-1 simulation from the IllustrisTNG project to study the extent to which simulation box size—and the resulting presence of the most massive protoclusters—is responsible for the differences between the CoSLA populations observed in large N-body simulations and those in comparatively small hydrodynamical simulations. Using the better statistics afforded by the larger simulation volume, I confirm that CoSLAs are rare objects, finding a number of CoSLAs per unit redshift dn/dz∼1×10^−2 at redshift z=2.444. Furthermore, I find the δτeff–δm relation in a 205^3 h^−3 Mpc^3 volume is consistent with that for a smaller 75^3 h^−3 Mpc^3 box size, with systems with δ_m>1 existing over a wide range of δ_τeff values. I find the CoSLAs in TNG300-1 to have a median δ_m=0.45±0.05, which remains somewhat lower than the δ_m=0.64±0.38 previously found in larger N-body simulations. These findings suggest that the differences between the CoSLA populations in hydrodynamical and N-body simulations are not solely the result of the differing simulation box sizes. Instead I suggest that these discrepancies are caused by the modelling of the hot, collisionally ionised, gas that surrounds massive haloes in protocluster regions.

© 2020 Elsevier Inc. The ongoing Coronavirus Disease 2019 (COVID-19) pandemic threatens the health of humans and causes great economic losses. Predictive modeling and forecasting the epidemic trends are essential for developing countermeasures to mitigate this pandemic. We develop a network model, where each node represents an individual and the edges represent contacts between individuals where the infection can spread. The individuals are classified based on the number of contacts they have each day (their node degrees) and their infection status. The transmission network model was respectively fitted to the reported data for the COVID-19 epidemic in Wuhan (China), Toronto (Canada), and the Italian Republic using a Markov Chain Monte Carlo (MCMC) optimization algorithm. Our model fits all three regions well with narrow confidence intervals and could be adapted to simulate other megacities or regions. The model projections on the role of containment strategies can help inform public health authorities to plan control measures.

Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.

Algorithms such as Kleinberg's HITS algorithm, the PageRank algorithm of Brin and Page, and the SALSA algorithm of Lempel and Moran use the link structure of a network of web pages to assign weights to each page in the network. The weights can then be used to rank the pages as authoritative sources. These algorithms share a common underpinning; they find a dominant eigenvector of a nonnegative matrix that describes the link structure of the given network and use the entries of this eigenvector as the page weights. We use this commonality to give a unified treatment, proving the existence of the required eigenvector for the PageRank, HITS, and SALSA algorithms, the uniqueness of the PageRank eigenvector, and the convergence of the algorithms to these eigenvectors. However, we show that the HITS and SALSA eigenvectors need not be unique. We examine how the initialization of the algorithms affects the final weightings produced. We give examples of networks that lead the HITS and SALSA algorithms to return nonunique or nonintuitive rankings. We characterize all such networks in terms of the connectivity of the related HITS authority graph. We propose a modification, Exponentiated Input to HITS, to the adjacency matrix input to the HITS algorithm. We prove that Exponentiated Input to HITS returns a unique ranking, provided that the network is weakly connected. Our examples also show that SALSA can give inconsistent hub and authority weights, due to nonuniqueness. We also mention a small modification to the SALSA initialization which makes the hub and authority weights consistent.