To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure email@example.com
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
In recent years, the discovery of massive quasars at
has provided a striking challenge to our understanding of the origin and growth of supermassive black holes in the early Universe. Mounting observational and theoretical evidence indicates the viability of massive seeds, formed by the collapse of supermassive stars, as a progenitor model for such early, massive accreting black holes. Although considerable progress has been made in our theoretical understanding, many questions remain regarding how (and how often) such objects may form, how they live and die, and how next generation observatories may yield new insight into the origin of these primordial titans. This review focusses on our present understanding of this remarkable formation scenario, based on the discussions held at the Monash Prato Centre from November 20 to 24, 2017, during the workshop ‘Titans of the Early Universe: The Origin of the First Supermassive Black Holes’.
Effective treatment of maternal antenatal depression may ameliorate adverse neurodevelopmental outcomes in offspring. We performed two follow-up rounds of children at age 2 and age 5 whose mothers had received either specialized cognitive-behavioural therapy or routine care for depression while pregnant. Of the original cohort of 54 women, renewed consent was given by 28 women for 2-year follow-up and by 24 women for 5-year follow-up. Child assessments at the 2-year follow-up included the Parenting Stress Index (PSI), Bayley Scales of Infant Development (BSID-III) and the Child Behaviour Checklist (CBCL). The 5-year follow-up included the Wechsler Preschool and Primary Scales of Intelligence (WPPSI-III) and again the CBCL. Treatment during pregnancy showed significant benefits for children’s development at age 2, but not at age 5. At 2 years, intervention effects were found with lower scores on the PSI Total score, Parent Domain and Child domain (d=1.44, 1.47, 0.96 respectively). A non-significant trend favoured the intervention group on most subscales of the CBCL and the BSID-III (most notably motor development: d =0.52). In contrast, at 5-year follow-up, no intervention effects were found. Also, irrespective of treatment allocation, higher depression or anxiety during pregnancy was associated with higher CBCL and lower WPPSI-III scores at 5 years. This is one of the first controlled studies to evaluate the long-term effect of antenatal depression treatment on infant neurodevelopmental outcomes, showing some benefit. Nevertheless, caution should be taken interpreting the results because of a small sample size, and larger studies are warranted.
The importance of parasites as a selective force in host evolution is a topic of current interest. However, short-term ecological studies of host–parasite systems, on which such studies are usually based, provide only snap-shots of what may be dynamic systems. We report here on four surveys, carried out over a period of 12 years, of helminths of spiny mice (Acomys dimidiatus), the numerically dominant rodents inhabiting dry montane wadis in the Sinai Peninsula. With host age (age-dependent effects on prevalence and abundance were prominent) and sex (female bias in abundance in helminth diversity and in several taxa including Cestoda) taken into consideration, we focus on the relative importance of temporal and spatial effects on helminth infracommunities. We show that site of capture is the major determinant of prevalence and abundance of species (and higher taxa) contributing to helminth community structure, the only exceptions being Streptopharaus spp. and Dentostomella kuntzi. We provide evidence that most (notably the Spiruroidea, Protospirura muricola, Mastophorus muris and Gongylonema aegypti, but with exceptions among the Oxyuroidae, e.g. Syphacia minuta), show elements of temporal-site stability, with a rank order of measures among sites remaining similar over successive surveys. Hence, there are some elements of predictability in these systems.
Recent findings highlight that there are prenatal risks for affective disorders that are mediated by glucocorticoid mechanisms, and may be specific to females. There is also evidence of sex differences in prenatal programming mechanisms and developmental psychopathology, whereby effects are in opposite directions in males and females. As birth weight is a risk for affective disorders, we sought to investigate whether maternal prenatal cortisol may have sex-specific effects on fetal growth. Participants were 241 mothers selected from the Wirral Child Health and Development Study (WCHADS) cohort (n=1233) using a psychosocial risk stratifier, so that responses could be weighted back to the general population. Mothers provided saliva samples, which were assayed for cortisol, at home over 2 days at 32 weeks gestation (on waking, 30-min post-waking and during the evening). Measures of infant birth weight (corrected for gestational age) were taken from hospital records. General population estimates of associations between variables were obtained using inverse probability weights. Maternal log of the area under the curve cortisol predicted infant birth weight in a sex-dependent manner (interaction term P=0.029). There was a positive and statistically significant association between prenatal cortisol in males, and a negative association in females that was not statistically significant. A sex interaction in the same direction was evident when using the waking (P=0.015), and 30-min post-waking (P=0.013) cortisol, but not the evening measure. There was no interaction between prenatal cortisol and sex to predict gestational age. Our findings add to an emerging literature that suggests that there may be sex-specific mechanisms that underpin fetal programming.
Schizophrenia (SZ) is a severe neuropsychiatric disorder associated with disrupted connectivity within the thalamic-cortico-cerebellar network. Resting-state functional connectivity studies have reported thalamic hypoconnectivity with the cerebellum and prefrontal cortex as well as thalamic hyperconnectivity with sensory cortical regions in SZ patients compared with healthy comparison participants (HCs). However, fundamental questions remain regarding the clinical significance of these connectivity abnormalities.
Resting state seed-based functional connectivity was used to investigate thalamus to whole brain connectivity using multi-site data including 183 SZ patients and 178 matched HCs. Statistical significance was based on a voxel-level FWE-corrected height threshold of p < 0.001. The relationships between positive and negative symptoms of SZ and regions of the brain demonstrating group differences in thalamic connectivity were examined.
HC and SZ participants both demonstrated widespread positive connectivity between the thalamus and cortical regions. Compared with HCs, SZ patients had reduced thalamic connectivity with bilateral cerebellum and anterior cingulate cortex. In contrast, SZ patients had greater thalamic connectivity with multiple sensory-motor regions, including bilateral pre- and post-central gyrus, middle/inferior occipital gyrus, and middle/superior temporal gyrus. Thalamus to middle temporal gyrus connectivity was positively correlated with hallucinations and delusions, while thalamus to cerebellar connectivity was negatively correlated with delusions and bizarre behavior.
Thalamic hyperconnectivity with sensory regions and hypoconnectivity with cerebellar regions in combination with their relationship to clinical features of SZ suggest that thalamic dysconnectivity may be a core neurobiological feature of SZ that underpins positive symptoms.
Although the environmental benefits of recycling plastics are well established and most geographic locations within the U.S. offer some plastic recycling, recycling rates are often low. Low recycling rates are often observed in conventional centralized recycling plants due to the challenge of collection and transportation for high-volume low-weight polymers. The recycling rates decline further when low population density, rural and relatively isolated communities are investigated because of the distance to recycling centers makes recycling difficult and both economically and energetically inefficient. The recent development of a class of open source hardware tools (e.g. RecycleBots) able to convert post-consumer plastic waste to polymer filament for 3-D printing offer a means to increase recycling rates by enabling distributed recycling. In addition, to reducing the amount of plastic disposed of in landfills, distributed recycling may also provide low-income families a means to supplement their income with domestic production of small plastic goods. This study investigates the environmental impacts of polymer recycling. A life-cycle analysis (LCA) for centralized plastic recycling is compared to the implementation of distributed recycling in rural areas. Environmental impact of both recycling scenarios is quantified in terms of energy use per unit mass of recycled plastic. A sensitivity analysis is used to determine the environmental impacts of both systems as a function of distance to recycling centers. The results of this LCA study indicate that distributed recycling of HDPE for rural regions is energetically favorable to either using virgin resin or conventional recycling processes. This study indicates that the technical progress in solar photovoltaic devices, open-source 3-D printing and polymer filament extrusion have made distributed polymer recycling and upcycling technically viable.
We have analyzed the distributions of CO and temperature in a large suite of simulated
molecular clouds, in order to help us understand how to interpret CO line emission from
real molecular clouds. We find that most of the CO is located at densities over
103cm-3 where the temperature is roughly 10–20 K independently of
the mean density, metallicity and UV field strength. Although, most of the volume is in
warmer and thinner regions where CO abundance is small. On that account, CO observations
alone give a misleading view of the physical conditions in the clouds.
So far in our models the physical characteristics of velocity and diffusivity have been specified or “hard-wired” into the calculations. The next step to consider is allowing them to respond to changing conditions. In this chapter, we will be developing and exploring a class of models aimed at simulating the seasonal behavior of the upper ocean in response to changing atmospheric forcing. We subsequently will extend this model to simulate the response of dissolved gases in the upper ocean. This approach can be more generally applied to other shallow water column properties (including bio-optical modeling, particle dynamics, etc.) with very minor modifications. What we're trying to show you here is not just how to design, build, and extend the model, but more importantly how to figure out what the model is actually doing, and how to compare its performance quantitatively with actual observations.
There are two general types of upper ocean models (although there are hybrids of these two as well). There are the bulk mixed layer models which, as the name suggests, treat the mixed layer as a homogeneous, well-mixed box, within which properties including chemical species, temperature, salinity, and physical momentum are uniformly distributed.
What is art but life upon the larger scale, the higher. When, graduating up in a spiral line of still expanding and ascending gyres, it pushes toward the intense significance of all things, hungry for the infinite?
Elizabeth Barrett Browning
Onward to the next dimension
Although one-dimensional models provide useful insight into basic biogeochemical processes, we are forced to admit that the world is made of more than one spatial dimension. The addition of an extra dimension to a model often does more than “fill space”, but rather imbues the model with behavior that is qualitatively different from its lower-dimensional analogue. The opportunity presented by the extra dimension is that more interesting, and perhaps more “realistic” phenomena may be modeled. This opportunity brings with it challenges, however, that are not just computational in nature. The choices of model geometry, circulation scheme, and boundary conditions become more complicated. Seemingly innocuous choices can have subtle or profound effects on how your model behaves. Moreover, matching model results to observations often requires decisions about whether features result from intrinsic processes of interest, or are mere artifacts of the choices made in model configuration.
For instructional purposes, we'll stick to a genre called gyre models which, as you might guess, are characterized by a quasi-circular flow on a plane. Such models have utility in the subtropics – at least that's where we'll be dwelling here – but can be used in many other parts of the ocean.
‘From a drop of water,’ said the writer, ‘a logician could infer the possibility of an Atlantic or a Niagara without having seen or heard of one or the other. So all life is a great chain, the nature of which is known whenever we are shown a single link of it.’
Sir Arthur Conan Doyle
Suppose you're looking for patterns or relationships in your data. For example, you may be trying to quantify the presence and distribution of certain water masses in a hydrographic section, or you may be looking for evidence and patterns of nitrogen fixation or denitrification in some nutrient data. Perhaps you're trying to find the best way to account for interferences from other elements (“matrix effects”) in your ICPMS data. You've gathered your data, maybe obtained from a cleverly designed experiment, or extracted from a hydrographic atlas or a collection of cruise data. The information you require lies within the relationships or correlations between the different properties or variables in your data set. But where (and how) do you look? If instinct leads you to look at the data covariance matrix, then your instinct is right! In this chapter we'll show you some techniques for extracting and analyzing this structure. We will start with some underlying basics that you'll need to understand these techniques, and we'll mention a few relatively intuitive approaches for analyzing data structure.
If you are a student of science in the twenty-first century, but are not using computers, then you are probably not doing science. A little harsh, perhaps, and tendentious, undoubtedly. But this bugle-call over-simplification gets to the very heart of the reason that we wrote this book. Over the years we noticed, with increasing alarm, very gifted students entering our graduate program in marine chemistry and geochemistry with very little understanding of the applied mathematics and numerical modeling they would be required to know over the course of their careers. So this book, like many before it, started as a course – in this case, a course in modeling, data analysis, and numerical techniques for geochemistry that we teach every other year in Woods Hole. As the course popularity and web pages grew, we realized our efforts should be set down in a more formal fashion.
We wrote this book first and foremost with the graduate and advanced undergraduate student in mind. In particular, we have aimed the material at the student still in the stages of formulating their Ph.D. or B.Sc. thesis. We feel that the student armed with the knowledge of what will be required of them when they synthesize their data and write their thesis will do a much better job at collecting the data in the first place. Nevertheless, we have found that many students beyond these first years find this book useful as a reference.
To those devoid of imagination, a blank place on the map is a useless waste; to others, the most valuable part.
Most of you are familiar with topographic contour maps. Those squiggly lines represent locations on the map of equal elevation. Many of you have probably seen a similar mode of presentation for scientific data, contour plots with isolines of constant property values (e.g. isotherms and isopycnals). What many of you are probably not familiar with are the mathematics that lie behind the creation of those “maps” and their uses beyond visualization.
Contouring and gridding concepts
This chapter covers the question: “What do you do when your data are not on a regular grid?” This question comes up frequently with ocean field data, which are rarely sampled at exactly equal intervals of space or time. The grid dimensions could be latitude–longitude, like the familiar topographic map, or involve other dimensions such as time, depth, or even property values (e.g. temperature, oxygen, chlorophyll). Mathematical gridding is common in visualization because computers can only draw contour lines if they know where to draw them. Often, a contouring package will first grid your data using a default method, and this may be acceptable. But there is more to it than making pretty pictures.
People don't understand the earth, but they want to, so they build a model, and then they have two things they don't understand.
So far, we have introduced many of the elements of ocean modeling but in simplified situations with reduced dimensionality (i.e. box models, vertical 1D models, 2D gyre models). Here we pull all of the elements together, introducing the topic of 3D ocean general circulation models (GCMs). As you might expect, the topic is complex, and our GCM tour will be necessarily brief and focused. While you probably won't be able to construct your own GCM, you should at least be able to understand the conversation and perhaps even utilize 3D GCM output. Several good review articles and books have been written on ocean GCMs that the reader can refer to for more details (e.g. Haidvogel and Beckmann, 1999; Griffies et al., 2000; Griffies, 2004). While our emphasis is on marine systems, most of the fundamental concepts about GCMs are applicable to a wide range of environmental fluid systems, from the atmosphere to mantle convection to groundwaters.
Several themes emerge when considering ocean GCMs. First, no matter how fast technology develops, the cutting edge of ocean modeling is always “compute bound”, which is why you won't be able to build a decent GCM using MATLAB. Ocean GCM development is linked to the evolution of supercomputers, and in fact GCMs are commonly used to test new supercomputers.