Identifying clustering at high redshift through actively star-forming galaxies

Identifying galaxy clustering at high redshift (i.e. z > 1) is essential to our understanding of the current cosmological model. However, at increasing redshift, clusters evolve considerably in star-formation activity and so are less likely to be identified using the widely-used red sequence method. Here we assess the viability of instead identifying high redshift clustering using actively star-forming galaxies (SMGs associated with over-densities of BzKs/LBGs). We perform both a 2- and 3-D clustering analysis to determine whether or not true (3D) clustering can be identified where only 2D data are available. As expected, we find that 2D clustering signals are weak at best and inferred results are method dependant. In our 3D analysis, we identify 12 SMGs associated with an over-density of galaxies coincident both spatially and in redshift - just 8% of SMGs with known redshifts in our sample. Where an SMG in our target fields lacks a known redshift, their sightline is no more likely to display clustering than blank sky fields; prior redshift information for the SMG is required to identify a true clustering signal. We find that the strength of clustering in the volume around typical SMGs, while identifiable, is not exceptional. However, we identify a small number of highly clustered regions, all associated with an SMG. The most notable of these, surrounding LESSJ033336.8-274401, potentially contains an SMG, a QSO and 36 star-forming galaxies (a > 20sig over-density) all at z~1.8. This region is highly likely to represent an actively star-forming cluster and illustrates the success of using star-forming galaxies to select sites of early clustering. Given the increasing number of deep fields with large volumes of spectroscopy, or high quality and reliable photometric redshifts, this opens a new avenue for cluster identification in the young Universe.Comment: 24 pages, 14 figures, accepted MNRA

Limits on dust emission from z~5 LBGs and their local environments

We present 1.2mm MAMBO-2 observations of a field which is over-dense in Lyman Break Galaxies (LBGs) at z~5. The field includes seven spectroscopically-confirmed LBGs contained within a narrow (z=4.95+/-0.08) redshift range and an eighth at z=5.2. We do not detect any individual source to a limit of 1.6 mJy/beam (2*rms). When stacking the flux from the positions of all eight galaxies, we obtain a limit to the average 1.2 mm flux of these sources of 0.6mJy/beam. This limit is consistent with FIR imaging in other fields which are over-dense in UV-bright galaxies at z~5. Independently and combined, these limits constrain the FIR luminosity (8-1000 micron) to a typical z~5 LBG of LFIR<~3x10^11 Lsun, implying a dust mass of Mdust<~10^8 Msun (both assuming a grey body at 30K). This LFIR limit is an order of magnitude fainter than the LFIR of lower redshift sub-mm sources (z~1-3). We see no emission from any other sources within the field at the above level. While this is not unexpected given millimetre source counts, the clustered LBGs trace significantly over-dense large scale structure in the field at z = 4.95. The lack of any such detection in either this or the previous work, implies that massive, obscured star-forming galaxies may not always trace the same structures as over-densities of LBGs, at least on the length scale probed here. We briefly discuss the implications of these results for future observations with ALMA.Comment: 10 pages, 6 figures, MNRAS Accepte

Study protocol to investigate the effect of a lifestyle intervention on body weight, psychological health status and risk factors associated with disease recurrence in women recovering from breast cancer treatment

Background Breast cancer survivors often encounter physiological and psychological problems related to their diagnosis and treatment that can influence long-term prognosis. The aim of this research is to investigate the effects of a lifestyle intervention on body weight and psychological well-being in women recovering from breast cancer treatment, and to determine the relationship between changes in these variables and biomarkers associated with disease recurrence and survival. Methods/design Following ethical approval, a total of 100 patients will be randomly assigned to a lifestyle intervention (incorporating dietary energy restriction in conjunction with aerobic exercise training) or normal care control group. Patients randomised to the dietary and exercise intervention will be given individualised healthy eating dietary advice and written information and attend moderate intensity aerobic exercise sessions on three to five days per week for a period of 24 weeks. The aim of this strategy is to induce a steady weight loss of up to 0.5 Kg each week. In addition, the overall quality of the diet will be examined with a view to (i) reducing the dietary intake of fat to ~25% of the total calories, (ii) eating at least 5 portions of fruit and vegetables a day, (iii) increasing the intake of fibre and reducing refined carbohydrates, and (iv) taking moderate amounts of alcohol. Outcome measures will include body weight and body composition, psychological health status (stress and depression), cardiorespiratory fitness and quality of life. In addition, biomarkers associated with disease recurrence, including stress hormones, estrogen status, inflammatory markers and indices of innate and adaptive immune function will be monitored. Discussion This research will provide valuable information on the effectiveness of a practical, easily implemented lifestyle intervention for evoking positive effects on body weight and psychological well-being, two important factors that can influence long-term prognosis in breast cancer survivors. However, the added value of the study is that it will also evaluate the effects of the lifestyle intervention on a range of biomarkers associated with disease recurrence and survival. Considered together, the results should improve our understanding of the potential role that lifestyle-modifiable factors could play in saving or prolonging lives

Assessing the importance of car meanings and attitudes in consumer evaluations of electric vehicles

This paper reports findings from a research study which assesses the importance of attitudinal constructs related to general car attitudes and the meanings attached to car ownership over evaluations of electric vehicles (EVs). The data are assessed using principal component analysis to evaluate the structure of the underlying attitudinal constructs. The identified constructs are then entered into a hierarchical regression analysis which uses either positive or negative evaluations of the instrumental capabilities of EVs as the dependent variable. Results show that attitudinal constructs offer additional predictive power over socioeconomic characteristics and that the symbolic and emotive meanings of car ownership are as, if not more, effective in explaining the assessment of EV instrumental capability as compared to issues of cost and environmental concern. Additionally, the more important an individual considers their car to be in their everyday life, the more negative their evaluations are of EVs whilst individuals who claim to be knowledgeable about cars in general and EVs in particular have a lower propensity for negative EV attitudes. However, positive and negative EV attitudes are related to different attitudinal constructs suggesting that it is possible for someone to hold both negative and positive assessments at the same time

Post-Translational Modifications and Age-Related Hearing Loss

Post-translational modifications (PTMs) affect nearly all systems of the human body due to their role in protein synthesis and functionality. These reversible and irreversible modifications control the structure, localization, activity, and properties of proteins. For this reason, PTMs are essential in regulating cellular processes and maintaining homeostasis. Diseases such as Alzheimer\u27s, cardiovascular disease, diabetes, cancer, and many others have been linked to dysfunctions of PTMs. Recent research has also shown that irregularities in PTMs can be linked to hearing loss, including age-related hearing loss (ARHL) – the number one communication disorder and one of the top neurodegenerative diseases in our aging population. So far, there has been no FDA approved treatment for ARHL; however, translational studies investigating PTMs involvement in ARHL show promising results. In this review, we summarize key findings for PTMs within the auditory system, the involvement of PTMs with aging and ARHL, and lastly discuss potential treatment options focusing on utilizing PTMs as biomarkers and therapeutic pathway components

Accounting for Endogeneity in Maintenance Decisions and Overlay Thickness in a Pavement-Roughness Deterioration Model

Pavement deterioration models are an important part of any pavement management system. Many of these models suffer from endogeneity bias because of the inclusion of independent variables correlated with unobserved factors, which are captured by the model's error terms. Examples of such endogenous variables include pavement overlay thickness and maintenance and rehabilitation activities, both of which are not randomly chosen but are in fact decision variables selected by pavement engineers based on field conditions. Inclusion of these variables in a pavement deterioration model can result in biased and inconsistent model parameter estimates, leading to incorrect insights. Previous research has shown that continuous endogenous variables, such as pavement overlay thickness, can be corrected using auxiliary models to replace the endogenous variable with an instrumented variable that has lower correlation with the unobserved error term. Discrete endogenous variables, such as the type of maintenance and rehabilitation activities, have been accounted for by modeling the likelihood of each potential outcome and developing individual deterioration models for each of the potential responses. This paper proposes an alternative approach to accommodate discrete endogenous variables-the selectivity correction method-that allows a single model to incorporate the impacts of all discrete choices. This approach is applied to develop a pavement-roughness progression model that incorporates both continuous and discrete endogenous variables using field data from Washington State. The result is a roughness progression model with consistent parameter estimates, which have more realistic values than those obtained in previous studies that used the same data

Engineering of Microcage Carbon Nanotube Architectures with Decoupled Multimodal Porosity and Amplified Catalytic Performance

New approaches for the engineering of the 3D microstructure, pore modality, and chemical functionality of hierarchically porous nanocarbon assemblies are key to develop the next generation of functional aerogel and membrane materials. Here, interfacially driven assembly of carbon nanotubes (CNT) is exploited to fabricate structurally directed aerogels with highly controlled internal architectures, composed of pseudo-monolayer, CNT microcages. CNT Pickering emulsions enable engineering at fundamentally different length scales, whereby the microporosity, mesoporosity, and macroporosity are decoupled and individually controlled through CNT type, CNT number density, and process energy, respectively. In addition, metal nanocatalysts (Cu, Pd, and Ru) are embedded within the architectures through an elegant sublimation and shock-decomposition approach; introducing the first approach that enables through-volume functionalization of intricate, pre-designed aerogels without microstructural degradation. Catalytic structure–function relationships are explored in a pharma-important amidation reaction; providing insights on how the engineered frameworks enhance catalyst activity. A sophisticated array of advanced tomographic, spectroscopic, and microscopic techniques reveal an intricate 3D assembly of CNT building-blocks and their influence on the functional properties of the enhanced nanocatalysts. These advances set a basis to modulate structure and chemistry of functional aerogel materials independently in a controlled fashion for a variety of applications, including energy conversion and storage, smart electronics, and (electro)catalysis