Investigating the performance of transport infrastructure using real-time data and a scalable multi-modal agent based model

The idea that including more information in more dynamic and iterative ways is central to the promise of the big data paradigm. The hope is that via new data sources, such as remote sensors and mobile phones, the reliance on heavily simplified generalised functions for model inputs will be erased. This trade between idealised and actual empirical data will be matched with dynamic models which consider complexity at a fundamental level, inherently mirroring the systems they are attempting to replicate. Cloud computing brings the possibility of doing all of this, in less time than the simplified macro models of the past, thus enabling better answers and at the time of critical decision making junctures. This research was task driven - the question of high speed rail versus aviation led to an investigation into the simplifications and assumptions that back up many of the commonly held beliefs on the sustainability of different modes of transport. The literature ultimately highlighted the need for context specific information; actual load factors, actual journey times considering traffic/engineering works and so on. Thus, rather than being explicitly an exercise in answering a specific question, a specific question was used to drive the development of a tool which may hold promise for answering a range of transportation related questions. The original contributions of this work are, firstly the use of real-time data sources to quantify temporally and spatially dynamic network performance metrics (eg. journey times on different transport models) and secondly to organise these data sources in a framework which can handle the volume and type of the data and organise the data in a way so that it is useful for the dynamic agent based modelling of future scenarios.EPSRC I Case Studentship with Ove Arup & Partner

Influential Article Review - Maximizing Smart Home Energy Management With Geodesic Acceleration and LevMar

This paper examines using artificial neural networks to optimize energy management in smart homes. We present insights from a highly influential paper. Here are the highlights from this paper: Home energy optimization is increasing in research interest as smart technologies in appliances and other home devices are increasing in popularity, particularly as manufacturers move to produce appliances and devices which work in conjunction with the Internet. Home energy optimization has the potential to reduce energy consumption through “smart energy management” of appliances. Information and communications technologies (ICTs) help achieve energy savings with the goal of reducing greenhouse gas emissions and attaining effective environmental protection in several contexts including electricity generation and distribution. This “smart energy management” is utilized at the residential customer level through “smart homes.” This paper compares two artificial neural networks (ANN) used to support home energy management (HEM) systems based on Bluetooth low energy, called BluHEMS. The purpose of the algorithms is to optimize energy use in a typical residential home. The first ANN uses the LevenbergMarquardt algorithm and the second uses the Levenberg-Marquardt algorithm enhanced by a second order correction known as geodesic acceleration. For our overseas readers, we then present the insights from this paper in Spanish, French and German

The 300km/s stellar stream near Segue 1: Insights From high-resolution spectroscopy of its brightest star

We present a chemical abundance analysis of 300S-1, the brightest likely member star of the 300 km/s stream near the faint satellite galaxy Segue 1. From a high-resolution Magellan/MIKE spectrum we determine a metallicity of [Fe/H] = -1.46 +- 0.05 +- 0.23 (random and systematic uncertainties) for star 300S-1, and find an abundance pattern similar to typical halo stars at this metallicity. Comparing our stellar parameters to theoretical isochrones, we estimate a distance of 18 +- 7 kpc. Both the metallicity and distance estimates are in good agreement with what can be inferred from comparing the SDSS photometric data of the stream stars to globular cluster sequences. While several other structures overlap with the stream in this part of the sky, the combination of kinematic, chemical and distance information makes it unlikely that these stars are associated with either the Segue 1 galaxy, the Sagittarius stream or the Orphan stream. Streams with halo-like abundance signatures, such as the 300 km/s stream, present another observational piece for understanding the accretion history of the Galactic halo.Comment: 13 pages, emulateapj, accepted for publication in Ap

Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs

<p>Abstract</p> <p>Background</p> <p>Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks.</p> <p>Results</p> <p>We examined triplet motifs in a network of quantitative epistatic genetic relationships, and found a non-random distribution of particular motif classes. Individual motif classes were found to be associated with different functional properties, suggestive of an underlying biological significance. These associations were apparent not only for motif classes, but for individual positions within the motifs. As expected, NNN (all negative) motifs were strongly associated with previously reported genetic (i.e. synthetic lethal) interactions, while PPP (all positive) motifs were associated with protein complexes. The two other motif classes (NNP: a positive interaction spanned by two negative interactions, and NPP: a negative spanned by two positives) showed very distinct functional associations, with physical interactions dominating for the former but alternative enrichments, typical of biochemical pathways, dominating for the latter.</p> <p>Conclusion</p> <p>We present a model showing how NNP motifs can be used to recognize supportive relationships between protein complexes, while NPP motifs often identify opposing or regulatory behaviour between a gene and an associated pathway. The ability to use motifs to point toward underlying biological organizational themes is likely to be increasingly important as more extensive epistasis mapping projects in higher organisms begin.</p

Measuring transport-associated urban inequalities: Where are we and where do we go from here?

Reducing urban inequalities is at the forefront of the global sustainable development agenda, as well as national and local policies. While existing measures of inequality are mostly focused on income and wealth, it is widely recognised that non-monetary disparities such as in health, education, and housing play a crucial role in creating and reinforcing inequalities. Transport plays a central role in mitigating inequalities by enhancing access to employment, education, and essential services. It is also directly and indirectly related to disparities in housing, neighbourhoods, and health. Policymakers increasingly recognize the potential of transport policies in addressing inequalities; however, the effects of interventions need to be understood beyond the transport sector only and should consider wider impacts. In this review, we concentrate on three interlinked sectors – housing, land-use, and transportation – where local governments possess some capacity to influence the processes by which inequalities are created and exacerbated. Currently, empirical research on inequalities within these domains is fragmented. Models and datasets used for scenario testing, planning, and intervention evaluation are often disjointed, sector-focused, and rarely consider distributional effects. Our aim is to critically review the literature across different disciplines and perspectives and propose future interdisciplinary directions towards better measurement and modelling of transport-associated inequalities

Malaria Diagnosis Using a Mobile Phone Polarized Microscope

Malaria remains a major global health burden, and new methods for low-cost, high-sensitivity, diagnosis are essential, particularly in remote areas with low-resource around the world. In this paper, a cost effective, optical cell-phone based transmission polarized light microscope system is presented for imaging the malaria pigment known as hemozoin. It can be difficult to determine the presence of the pigment from background and other artifacts, even for skilled microscopy technicians. The pigment is much easier to observe using polarized light microscopy. However, implementation of polarized light microscopy lacks widespread adoption because the existing commercial devices have complicated designs, require sophisticated maintenance, tend to be bulky, can be expensive, and would require re-training for existing microscopy technicians. To this end, a high fidelity and high optical resolution cell-phone based polarized light microscopy system is presented which is comparable to larger bench-top polarized microscopy systems but at much lower cost and complexity. The detection of malaria in fixed and stained blood smears is presented using both, a conventional polarized microscope and our cell-phone based system. The cell-phone based polarimetric microscopy design shows the potential to have both the resolution and specificity to detect malaria in a low-cost, easy-to-use, modular platform

The 300 km s -1 stellar stream near Segue 1: Insights from high-resolution spectroscopy of its brightest star

We present a chemical abundance analysis of 300S-1, the brightest likely member star of the 300 km s-1 stream near the faint satellite galaxy Segue 1. From a high-resolution Magellan/MIKE spectrum, we determine a metallicity of [Fe/H] = -1.46 ± 0.05 ±

The Relationship Between Components of the Vegetarian Diet and Perceived Stress and Mental Distress

Recent evidence suggests that dietary patterns have an impact on mental health. However, little is known about how dietary patterns may impact the stress response. The purpose of this study was to investigate how components of a vegetarian diet relate to stress and mental distress. An anonymous survey was distributed primarily through social media targeting participants from diverse backgrounds. This study analyzed a total of 585 responses from adults 18 years old or older. Spearman’s rho correlation and principal component analysis were used to assess how dietary patterns and consumption of various foods and food groups relate to perceived stress and mental distress levels. The data was analyzed in SPSS version 25.0. Our results reveal a negative correlation between stress and whole grains (⍴= -0.103), dark green leafy vegetables (⍴= -0.154), and beans (⍴= -0.102). Mental distress was a negatively correlated with whole grains (⍴= -.147), nuts and flaxseed (⍴= -0.116), dark green leafy vegetables (⍴= -0.153), yogurt (⍴= -0.084), eggs (⍴= -0.108) and raw oats (⍴= -.101). These results indicate that multiple components of the vegetarian diet are inversely associated with stress, which explains the negative association with mental distress. Our results suggest that vegetarian items improve the stress response, which eventually improves mental health.https://orb.binghamton.edu/research_days_posters_2021/1101/thumbnail.jp

High Performance Computing for City-Scale Modelling and Simulations

The 21st Century is witnessing a rapid rise of urbanization both in the developed and the developing world. Cities increasingly need to be able to do more with less in order to provide for the well-being of their citizens in a sustainable way. The promise of Smart City is an emerging ability to understand, to respond to, and to shape human activity at urban population and geographic scales so that a more agile, adaptive, and sustainable urban environment can be created (see Batty et al., 2012; Caragliu et al., 2011; Chourabi et al., 2012; Su et al., 2011 for early adoption of Smart City). To be effective, this requires the predictive power of data-driven modelling and city-scale computational simulations. Recently city-scale simulations are becoming possible thanks to a surge of development in the high-performance computing (HPC) domain including advanced hardware, computational and algorithmic techniques such as domain decomposition across multi-GPUs and multigrid techniques. Advanced high performance computing systems (a billion billion calculations per second) are now becoming available to performance city-scale simulations with micro-scale models of an individual objective (structure, people, vehicle, etc.) (e.g. Sánchez-Medina et al., 2010; Hori, 2011; Zia et al., 2012; Wijerathne et al., 2013; Pijanowski et al., 2014; Yoshimura et al., 2016; Johansen et al., 2017; Lu and Guan., 2017