The potential of Hudson Valley glacial floods to drive abrupt climate change

The periodic input of meltwater into the ocean from a retreating Laurentide Ice Sheet is often hypothesized to have weakened the Atlantic meridional overturning circulation (AMOC) and triggered several cold periods during the last deglaciation (21,000 to 8,000 years before present). Here, we use a numerical model to investigate whether the Intra-Allerød Cold Period was triggered by the drainage of Glacial Lake Iroquois, ~13,300 years ago. Performing a large suite of experiments with various combinations of single and successive, short (1 month) and long (1 year) duration flood events, we were unable to find any significant weakening of the AMOC. This result suggests that although the Hudson Valley floods occurred close to the beginning of the Intra-Allerød Cold Period, they were unlikely the sole cause. Our results have implications for re-evaluating the relationship of meltwater flood events (past and future) to periods of climatic cooling, particularly with regards to flood input location, volume, frequency, and duration.

Categorizing Touch-Input Locations from Touchscreen Device Interfaces via On-Board Mechano-Acoustic Transducers

Many mobile electronics devices, including smartphones and tablets, require the user to interact physically with the device via tapping the touchscreen. Conveniently, these compact devices are also equipped with high-precision transducers such as accelerometers and microphones, integrated mechanically and designed on-board to support a range of user functionalities. However, unintended access to these transducer signals (bypassing normal on-board data access controls) may allow sensitive user interaction information to be detected and thereby exploited. In this study, we show that acoustic features extracted from the on-board microphone signals, supported with accelerometer and gyroscope signals, may be used together with machine learning techniques to successfully determine the user’s touch input location on a touchscreen: our ensemble model, namely the random forest model, predicts touch input location with up to 86% accuracy in a realistic scenario. Accordingly, we present the approach and techniques used, the performance of the model developed, and also discuss limitations and possible mitigation methods to thwart possible exploitation of such unintended signal channels.

The impact of location variables on the modelling and forecasting of capital expenditure for hyperscale datacenters

The digital age and the growth of the internet is increasing exponentially each year, this has created a need for facilities to house and store the data generated. Examples of the data generated are such items such as images, film libraries such as Netflix and Prime Video along withinternet search data. The facility to house this information is a data center. A data centeris a building (or self-contained unit within a building) used to house computing equipment such as servers along with associated components such as telecommunications, network and storage systems. This growth in demand has required data centerproviders to expand into new countries, often at very short notice. Research Design The research design will likely use a positivist paradigm with a deductive approach, combining predictive theory and action research theory using a multivariate linear regression technique. The Data will be collected using closed questionnaires, publicly available data and industry data analysed in a quantitative method with a cross sectional timeline. Research Findings Variables will be established and analysed to understand the weighting of each variable and its impact on capital expenditure. Research Conclusions The conclusion is expected to be a model where input location variables are used to predict the capital expenditure for the construction of hyperscale data centers. This will benefit data centerowners, developers and fund providers when assessing the value of capital expenditure required as a decision for investment in selecting a site location fora hyperscale data center.

Effects of Spatial Location of Auditory Tones on Pitch Discrimination

Pitch discrimination accuracy has been found to be affected by many factors, including handedness, musical training, interfering stimuli, and spatial location of the auditory stimulus. Separating the stimulus input location of interference tones from initial (reference) and final (comparison) tones leads to more accurate pitch discrimination, but the effects of spatial location relationships between the reference, interference, and comparison tones have not been fully explored. This study examined the impact of stimulus spatial location in 24 young, nonmusician females. Participants determined whether the pitch of reference and comparison tones were the same or different in 20 pitch discrimination conditions with varied interference, spatial relationships, and frequencies. Findings revealed that pitch discrimination accuracy was significantly better when (a) there was no interference, (b) the comparison tone was presented to the contralateral brain hemisphere from reference and interference tones, and (c) the comparison tone was presented to the left ear. We discussed the implications of these findings for therapy programs to strengthen pitch discrimination abilities.

Decoding the locational information in the orb web vibrations of Araneus diadematus and Zygiella x-notata

A spider's web is a multifunctional structure that captures prey and provides an information platform that transmits vibrational information. Many physical factors interact to influence web vibration and information content, from vibration source properties and input location, to web physical properties and geometry. The aim of the study was to test whether orb web vibration contains information about the location of the source of vibration. We used finite-element analysis model webs to control and vary major physical factors, investigating webs where spiders use a direct or remote monitoring strategy. When monitoring with eight sensors (legs) at the web centre, a comparison of longitudinal and transverse wave amplitude between the sensors gave sufficient information to determine source direction and distance, respectively. These localization cues were robust to changes in source amplitude, input angle and location, with increased accuracy at lower source amplitudes. When remotely monitoring the web using a single thread connected to the web's hub (a signal thread), we found that locational information was not available when the angle of the source input was unknown. Furthermore, a free sector and a stiff hub were physical mechanisms to aid information transfer, which provides insights for bioinspired fibre networks for sensing technologies.

An analytical perspective about structural damage identification based on transmissibility function

Transmissibility functions have been widely applied into the field of structural health monitoring, especially for damage detection. However, due to the existence of few analytical research works to conceive the significance of damage onset, the inherent mechanism of damage identification based on transmissibility function has not yet been clearly and deeply evaluated. In this article, an analytical approach has been investigated to demonstrate how to localize damage components caused by mass and stiffness change in terms of multiple-degree-of-freedom mass–spring–damper system, based on the inherent analysis between the transmissibility functions for any two consecutive masses. This study also points out the importance of the system input: various input location may lead to different recognized damage regions. Related simulation case studies and laboratory activities are carried out, proving the effectiveness and accuracy of the proposed approach.

A Spatial, Temporal Complexity Metric for Tactical Air Traffic Control

Tactical monitoring and controlling of air traffic is becoming increasingly difficult to manage for Air Traffic Controllers (ATCOs) owing to an increasingly complex traffic flow. A dynamic tactical complexity model, herein known as Conflict Activity Level (CAL), has been developed and is presented in this paper. This can be achieved either by establishing an overall score for an entire region or sub-regions of interest as specified by user's input location and time. This is done by evaluating the likely aircraft flight shape profile based on its current and projected position and trajectory. From the flight shape profile, CAL values are computed based on instantaneous existing traffic numbers in the overall region or sub-regions of interest. The proposed complexity approach shows good agreement with other methods in terms of ranking the order of complexity of various air traffic scenarios and the key influencing factors contributing to conflict.