The impact of economic and supply chain trends on British warehousing

Purpose: Warehouses are key nodes in many supply chains and typically represent over 20% of logistics costs. However, other than property market studies, there has been relatively little research on warehousing, particularly as regards how trends in warehouses may relate to changes in such parameters as wider economic and supply chain factors. The purpose of this paper is to examine this area in order to explore how trends in warehousing may relate to existing warehousing and supply chain theory so as to facilitate further research into the relationship between warehousing and "smarter" logistics strategies and efficient supply chain performance. Research approach: The paper is based on a longitudinal study examining the take-up (i.e. occupation) of new large warehouses in Great Britain over the past 16 years covering some 700 records. For the purposes of this study, large warehouses are classified as those over 100,000 square feet (9,290 square metres) in area. These trends, together with those of total warehouse stock, are then related to national statistics, warehouse surveys, supply chain changes and other relevant data over that period. Findings and Originality: This is a rare longitudinal study of this subject. It is found that, until the recent recession, the total warehouse stock, as well as the take-up of large warehouses, has been increasing and this can be associated with such factors as economic growth, retail spending and globalisation. Both the footprint and height of large warehouses has been rising and this may be due to such factors as network economies and warehouse technology. The locations of warehouses are becoming more dispersed, possibly due to the growth in e-commerce and port-centric logistics. In addition, it was found that large warehouses have been increasingly taken up by retailers and manufacturers rather than logistics companies. Research impact: This paper examines the possible influence of economic and supply chain trends on warehousing in Great Britain. As well as testing existing theories, the data provides a sound foundation for future research. For example, there have been conflicting evidence in previous research regarding economies and diseconomies of scale and this discussion can now be set against trends in warehouse footprint and height. Practical impact: The paper provides a better understanding and basis for decision making by planners, developers, funding corporations, operators and end users. For example, topics such as size and height of buildings are examined, as well as trends in port-centric logistics, rail connections and e-fulfilment. The changing nature of warehouse designs in terms of wider economic and supply chain trends is particularly important for practitioners as warehousing costs are to a large extent determined at the design phase and have a major impact on the effectiveness of the overall supply chain of which they are a part

Rising Inequality and the Financial Crises of 1929 and 2008

Inequality increased dramatically in the decades leading up to the financial crises of both 1929 and 2008. Yet students of both crises have largely ignored any role that rising inequality might have played in rendering the financial sector more vulnerable to systemic dysfunction. This study draws upon the work of Thorstein Veblen, Michal Kalecki, and Karl Marx to clarify the manner in which growing inequality prior to both crises made U.S. financial markets more prone to systemic dysfunction. Greater inequality generated three dynamics that heightened conditions in which these financial crises might occur. The first is that greater inequality meant that individuals were forced to struggle harder to find ways to consume more to maintain their relative social status, thereby reducing their savings and increasing their indebtedness. The second is that holding ever greater income and wealth, the elite flooded financial markets with credit, helping keep interest rates low and encouraging the creation of new credit instruments. The third dynamic is that, as the rich took larger shares of income and wealth, they gained more command over ideology and hence politics. Reducing the size of government, tax cuts for the rich, deregulating the economy, and failing to regulate newly evolving credit instruments flowed out of this ideology.

Increasing Inequality, Status Insecurity, Ideology, and the Financial Crisis of 2008

The current financial crisis has been blamed on inadequate regulation stemming from laissez-faire ideology, combined with low interest rates. But beneath these widely-acknowledged causal factors lies a deeper underlying determining cause that has received less notice: the dramatic increase in inequality in the U.S. over the preceding 35 years. This rise in inequality generated three phenomena that heightened conditions in which this crisis could occur. The first is that greater inequality meant that individuals were forced to struggle harder to find ways to consume more to maintain their relative social status. The consequence was that over the preceding three decades household saving rates plummeted, workers worked longer hours, and households took on ever-greater debt. The second phenomenon is that, flush with ever greater income and wealth, the elite were able to flood financial markets with credit, helping keep interest rates low and encouraging the creation of new credit instruments. The third phenomenon is that, as the rich took larger shares of income and wealth, they gained relatively more command over everything, including ideology. Reducing the size of government, deregulating the economy, and failing to regulate newly evolving credit instruments flowed out of this ideology.deregulation, real estate boom, credit, conspicuous consumption, social respectability

Rising Inequality and the Financial Crises of 1929 and 2008

The most widely embraced explanations of the financial crisis of 2008 have centered upon inadequate regulation stemming from laissez-faire ideology, combined with low interest rates. Although these widely-acknowledged causal factors are true, beneath them lies a deeper determining force that has received less notice: the dramatic increase in inequality in the U.S. over the preceding 35 years. Heightened inequality generated three dynamics that made the economy vulnerable to systemic dysfunction. The first is that inequality constrained consumption, reducing profitable investment potential in the real economy, and thereby encouraging an every wealthier elite to flood financial markets with credit, helping keep interest rates low, encouraging the creation of new credit instruments, and fueling speculation. The second dynamic is that greater inequality meant that individuals were forced to struggle harder to find ways to consume more to maintain their relative social status. The consequence was that over the preceding three decades household saving rates plummeted, households took on evergreater debt, and workers worked longer hours. The third dynamic is that, as the rich took larger shares of income and wealth, they gained more command over ideology and hence politics. Reducing the size of government, cutting taxes on the rich and reducing welfare for the poor, deregulating the economy, and failing to regulate newly evolving credit instruments flowed out of this ideology.Underconsumption, deregulation, speculation, real estate boom, credit, conspicuous consumption, social respectability

The effect of selected variables on carcass traits of beef

Seven hundred and twenty-two carcasses from Shorthorn, Angus, Hereford, Charolais and Other Breeds (predominately Simmental X Hereford or Angus) were utilized in an eight year (1968-75) study of breed and year variation in beef carcass yield traits. These steers were entered in the Bristol Junior Steer Show by 4-H and FFA members of East Tennessee and Southwest Virginia. The calves consisted of 15 Shorthorn, 284 Angus, 316 Hereford, 75 Charolais and 32 Other Breeds steers ranging from 360 to 575 days of age. Data collected relative to performance traits (live weight, carcass weight and weight per day of age) indicated a significant (P \u3c .05) advantage of Other Breeds and Charolais carcasses when com-pared to Shorthorn carcasses. There was no significant difference when Other Breeds, Charolais, or Shorthorn were compared to Hereford and Angus. Shorthorn cattle performed lowest in these traits. Angus cattle had the highest mean carcass grade of 12.50 or Low Choice. Other Breeds followed with a 12.10 or Low Choice. Hereford steer carcasses were significantly (P \u3c .05) lower in quality grade than any other of the breed groups. The mean carcass quality grade was 11.88 or High Good for all years and breeds. Carcasses of 1971 cattle were significantly (P \u3c .05) higher with a score of 12.92 or approaching Average Choice. Angus steer carcasses had an average marbling score of 57.10 (Modest Minus) which was significantly (P \u3c .05) higher than the Other Breed groups. Hereford and Charolais steer carcasses had the lowest marbling scores. Although a correlation of 0.87 existed between carcass quality grade and USDA marbling score, the year 1970 had the highest signifi-cant (P \u3c ,05) marbling score. Steers measured an average of 0.44 inches of external fat thick-ness over the twelfth rib. Charolais fat thickness was significantly (P \u3c .05) smaller than the British Breed carcasses. Other Breeds were intermediate in measurements. Cattle slaughtered in 1971, 1972 and 1975 had significantly (P \u3c .05) less external fat thickness. A significant (P \u3c .05) negative correlation of 0.87 existed between carcass fat thickness and percent retail cuts. Ribeye area studies showed that Charolais and Other Breeds had a significant (P \u3c .05) advantage. Shorthorn steers had significantly (P \u3c .05) smaller ribeye area. Year had no significant (P \u3c .05) effect. The estimated overall mean for percent retail cuts was 50.35. Other Breeds and Charolais steers yielded the highest significant (P \u3c .05) percent. Shorthorn steers were predicted (P \u3c .05) to yield the lowest. Live grade with respect to breed and year was not significant. The overall mean live grade was 12.67 compared to an overall mean carcass grade of 11.88 almost one-third higher than actual

Linear generators for direct drive marine renewable energy converters

This thesis is concerned with the development of linear generators for use as the power take off mechanism in marine renewable energy converters. Delivering significant power at the low velocities demanded by wave and tidal stream energy converters requires a large force, which must be reacted by an electrical machine in a direct drive system. Attention is focused on the development of two novel topology linear permanent magnet machines suitable for use in this application. For each topology, models are presented that are capable of predicting the force characteristics and dynamic generator performance. The models, which are verified experimentally, reveal significant behavioural differences between the two topologies. The designer is thus provided with an interesting choice when considering a direct drive power take off strategy. In short, a variable reluctance machine is shown to develop a high shear force in its airgap, offering the potential of a compact generator, yet its performance is hindered by a poor power factor and the presence of significant airgap closure forces. The second machine, an air cored stator encompassing a permanent magnet translator, is shown to lend itself favourably as a generator, but only at the expense of requiring a large quantity of magnetic material and developing a significantly lower shear stress. Mechanical issues involved in the direct integration of linear electrical machines into the marine environment are examined. Details of two existing marine renewable energy devices are used to hypothesise about the characteristics of realistic sized generators of both the topologies investigated. Direct drive power take off is shown to represent a feasible alternative to the complex systems frequently proposed in these applications

Exploring Audio Sensing in Detecting Social Interactions Using Smartphone Devices

In recent years, the fast proliferation of smartphones devices has provided powerful and portable methodologies for integrating sensing systems which can run continuously and provide feedback in real-time. The mobile crowd-sensing of human behaviour is an emerging computing paradigm that offers a challenge of sensing everyday social interactions performed by people who carry smartphone devices upon themselves. Typical smartphone sensors and the mobile crowd-sensing paradigm compose a process where the sensors present, such as the microphone, are used to infer social relationships between people in diverse social settings, where environmental factors can be dynamic and the infrastructure of buildings can vary. The typical approaches in detecting social interactions between people consider the use of co-location as a proxy for real-world interactions. Such approaches can under-perform in challenging situations where multiple social interactions can occur within close proximity to each other, for example when people are in a queue at the supermarket but not a part of the same social interaction. Other approaches involve a limitation where all participants of a social interaction must carry a smartphone device with themselves at all times and each smartphone must have the sensing app installed. The problem here is the feasibility of the sensing system, which relies heavily on each participant's smartphone acting as nodes within a social graph, connected together with weighted edges of proximity between the devices; when users uninstall the app or disable background sensing, the system is unable to accurately determine the correct number of participants. In this thesis, we present two novel approaches to detecting co-located social interac- tions using smartphones. The first relies on the use of WiFi signals and audio signals to distinguish social groups interacting within a few meters from each other with 88% precision. We orchestrated preliminary experiments using WiFi as a proxy for co-location between people who are socially interacting. Initial results showed that in more challenging scenarios, WiFi is not accurate enough to determine if people are socially interacting within the same social group. We then made use of audio as a second modality to capture the sound patterns of conversations to identify and segment social groups within close proximity to each other. Through a range of real-world experiments (social interactions in meeting scenarios, coffee shop scenarios, conference scenarios), we demonstrate a technique that utilises WiFi fingerprinting, along with sound fingerprinting to identify these social groups. We built a system which performs well, and then optimized the power consumption and improved the performance to 88% precision in the most challenging scenarios using duty cycling and data averaging techniques. The second approach explores the feasibility of detecting social interactions without the need of all social contacts to carry a social sensing device. This work explores the use of supervised and unsupervised Deep Learning techniques before concluding on the use of an Autoencoder model to perform a Speaker Identification task. We demonstrate how machine learning can be used with the audio data collected from a singular device as a speaker identification framework. Speech from people is used as the input to our Autoencoder model and then classified against a list of "social contacts" to determine if the user has spoken a person before or not. By doing this, the system can count the number of social contacts belonging to the user, and develop a database of common social contacts. Through the use 100 randomly-generated social conversations and the use of state-of-the-art Deep Learning techniques, we demonstrate how this system can accurately distinguish new and existing speakers from a data set of voices, to count the number of daily social interactions a user encounters with a precision of 75%. We then optimize the model using Hyperparameter Optimization to ensure that the model is most optimal for the task. Unlike most systems in the literature, this approach would work without the need to modify the existing infrastructure of a building, and without all participants needing to install the same ap

Kinetically stable high-energy isomers of C14H12 and C12H10N2 derived from cis-stilbene and cis-azobenzene

Following on from our recent enforced geometry optimization (EGO) investigation of isomerization in cis-stilbene (J Comput Chem, in press) we report the discovery of two interesting new, symmetrical “fused sandwich” isomers of both cis-stilbene and the related cis-azobenzene. The isomers were obtained by applying external forces to pairs of carbon atoms from each of the benzene rings in cis-stilbene and cis-azobenzene simultaneously, and are all at least 100 kcal mol-1 higher in energy than the starting material. Each new structure was characterized as a minimum by vibrational analysis. Despite their high energy, all of the new isomers appear to be kinetically stable with respect to rearrangement back to cis-stilbene or cis-azobenzene, respectively

Are life-extending treatments for terminal illnesses a special case? Exploring choices and societal viewpoints

Criteria used by the National Institute for Health and Care Excellence (NICE) to assess life-extending, end-of-life (EoL) treatments imply that health gains from such treatments are valued more than other health gains. Despite claims that the policy is supported by societal values, evidence from preference elicitation studies is mixed and in-depth research has shown there are different societal viewpoints. Few studies elicit preferences for policies directly or combine different approaches to understand preferences.Survey questions were designed to investigate support for NICE EoL guidance at national and regional levels. These ‘Decision Rule’ and ‘Treatment Choice’ questions were administered to an online sample of 1496 UK respondents in May 2014. The same respondents answered questions designed to elicit their agreement with three viewpoints (previously identified and described) in relation to provision of EoL treatments for terminally ill patients. We report the findings of these choice questions and examine how they relate to each other and respondents' viewpoints.The Decision Rule questions described three policies: DA – a standard ‘value for money’ test, applied to all health technologies; DB – giving special consideration to all treatments for terminal illnesses; and DC – giving special consideration to specific categories of treatments for terminal illnesses e.g. life extension (as in NICE EoL guidance) or those that improve quality-of-life (QoL). Three Treatment Choices were presented: TA – improving QoL for patients with a non-terminal illness; TB – extending life for EoL patients; and TC – improving QoL at the EoL.DC received most support (45%) with most respondents giving special consideration to EoL only when treatments improved QoL. The most commonly preferred treatment choices were TA (51%) and TC (43%). Overall, this study challenges claims about public support for NICE's EoL guidance and the focus on life extension at EoL and substantiates existing evidence of plurality in societal values