Search results for: Gemma Hurst

Authors: Othmane Zarhali, Cécilia Aubrun, Emmanuel Bacry, Jean-Philippe Bouchaud, Jean-François Muzy

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The Nested factor model was introduced by Bouchaud and al., where the asset return fluctuations are explained by common factors representing the market economic sectors and residuals (noises) sharing with the factors a common dominant volatility mode in addition to the idiosyncratic mode proper to each residual. This construction infers that the factors-residuals log volatilities are correlated. Here, we consider the case of a single factor where the only dominant common mode is a S-fbm process (introduced by Peng, Bacry and Muzy) with Hurst exponent H around 0.11 and the residuals having in addition to the previous common mode idiosyncratic components with Hurst exponents H around 0. The reason for considering this configuration is twofold: preserve the Nested factor model’s characteristics introduced by Bouchaud and al. and propose a framework through which the stylized fact reported by Peng and al. is reproduced, where it has been observed that the Hurst exponents of stock indices are large as compared to those of individual stocks. In this work, we show that the Log S-fbm Nested factor model’s construction leads to a Hurst exponent of single stocks being the ones of the idiosyncratic volatility modes and the Hurst exponent of the index being the one of the common volatility modes. Furthermore, we propose a statistical procedure to estimate the Hurst factor exponent from the stock returns dynamics together with theoretical guarantees, with good results in the limit where the number of stocks N goes to infinity. Last but not least, we show that the factor can be seen as an index constructed from the single stocks weighted by specific coefficients.

Keywords: hurst exponent, log S-fbm model, nested factor model, small intermittency approximation

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Authors: Hania Pasandi

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Since its publication in 1856, Madame Bovary has established itself as one of the most adapted texts of French literature. Some eighteen film adaptations and twenty-seven rewritings of Madame Bovary in fiction to date shows a great enthusiasm for recreating Flaubert’s masterpiece in a variety of mediums. Posy Simmonds’ 1999 graphic novel, Gemma Bovery stands out among these adaptations as the graphic novel with its visual and narrative structure offers a new reading experience of Madame Bovary, while combining Emma Bovary’s elements with contemporary social, cultural, and artistic discourses. This paper studies the transposition of Flaubert’s Madame Bovary (1857) to late twentieth-century Britain in Posy Simmonds’ 1999 graphic novel, Gemma Bovery by exploring how it borrows the essential flaubertian themes, from its source text to incorporate it with contemporary cultural trends.

Keywords: graphic novel, Gemma Bovery, Madame Bovary, transposition

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Authors: Shreemoyee Sarkar, Vikhyat Chadha

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In this paper, the local fractal properties and chaotic properties of financial time series are investigated by calculating two exponents, the Local Hurst Exponent: LHE and Lyapunov Exponent in a moving time window of a financial series.y. For the purpose of this paper, the Dow Jones Industrial Average (DIJA) and S&P 500, two of the major indices of United States have been considered. The behaviour of the above-mentioned exponents prior to some major crashes (1998 and 2008 crashes in S&P 500 and 2002 and 2008 crashes in DIJA) is discussed. Also, the optimal length of the window for obtaining the best possible results is decided. Based on the outcomes of the above, an attempt is made to predict the crashes and accuracy of such an algorithm is decided.

Keywords: local hurst exponent, lyapunov exponent, market crash prediction, time series chaos, time series local fractal properties

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Authors: Marina Benito-Parejo, Raul Perez-Lopez, Miguel Herraiz, Carolina Guardiola-Albert, Cesar Martinez

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Persistency, long-term memory and randomness are intrinsic properties of time-series of earthquakes. The Rescaled Range Analysis (RS-Analysis) was introduced by Hurst in 1956 and modified by Mandelbrot and Wallis in 1964. This method represents a simple and elegant analysis which determines the range of variation of one natural property (the seismic energy released in this case) in a time interval. Despite the simplicity, there is complexity inherent in the property measured. The cumulative curve of the energy released in time is the well-known fractal geometry of a devil’s staircase. This geometry is used for determining the maximum and minimum value of the range, which is normalized by the standard deviation. The rescaled range obtained obeys a power-law with the time, and the exponent is the Hurst value. Depending on this value, time-series can be classified in long-term or short-term memory. Hence, an algorithm has been developed for compiling the RS-Analysis for time series of earthquakes by days. Completeness time distribution and locally stationarity of the time series are required. The interest of this analysis is their application for a complex seismic crisis where different earthquakes take place in clusters in a short period. Therefore, the Hurst exponent has been obtained for the seismic crisis of Alhoceima (Mediterranean Sea) of January-March, 2016, where at least five medium-sized earthquakes were triggered. According to the values obtained from the Hurst exponent for each cluster, a different mechanical origin can be detected, corroborated by the focal mechanisms calculated by the official institutions. Therefore, this type of analysis not only allows an approach to a greater understanding of a seismic series but also makes possible to discern different types of seismic origins.

Keywords: Alhoceima crisis, earthquake time series, Hurst exponent, rescaled range analysis

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Authors: Lauren Currell, Gemma Hurst

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Introduction: The present study experimentally investigated the impact of attractive Instagram images on female’s body image. It also examined whether physical appearance perfectionism and cognitive coping predicted body image following upward comparisons to idealised bodies on Instagram. Methods: One-hundred and fifty-eight females (mean age 24.35 years) were randomly assigned to an experimental (where they compared their bodies to those of Instagram models) or control condition (where they critiqued landscape painting). All participants completed measures on physical appearance perfectionism, cognitive coping, and pre- and post-measures of body image. Results: Comparing one’s body to idealised bodies on Instagram resulted in increased appearance and weight dissatisfaction and decreased confidence, compared to the control condition. Physical appearance perfectionism and cognitive coping both predicted body image outcomes for the experimental condition. Discussion: Clinical implications, such as the prevention and treatment of body dissatisfaction, are discussed. Strengths and limitations of the current study are also noted, and suggestions for future research are provided.

Keywords: perfectionism, cognitive coping, body image, social media

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Authors: Hamidreza Namazi

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Fractal analysis is assessing fractal characteristics of data. It consists of several methods to assign fractal characteristics to a dataset which may be a theoretical dataset or a pattern or signal extracted from phenomena including natural geometric objects, sound, market fluctuations, heart rates, digital images, molecular motion, networks, etc. Fractal analysis is now widely used in all areas of science. An important limitation of fractal analysis is that arriving at an empirically determined fractal dimension does not necessarily prove that a pattern is fractal; rather, other essential characteristics have to be considered. For this purpose a Visual C++ based software called FRATSAN (FRActal Time Series ANalyser) was developed which extract information from signals through three measures. These measures are Fractal Dimensions, Jeffrey’s Measure and Hurst Exponent. After computing these measures, the software plots the graphs for each measure. Besides computing three measures the software can classify whether the signal is fractal or no. In fact, the software uses a dynamic method of analysis for all the measures. A sliding window is selected with a value equal to 10% of the total number of data entries. This sliding window is moved one data entry at a time to obtain all the measures. This makes the computation very sensitive to slight changes in data, thereby giving the user an acute analysis of the data. In order to test the performance of this software a set of EEG signals was given as input and the results were computed and plotted. This software is useful not only for fundamental fractal analysis of signals but can be used for other purposes. For instance by analyzing the Hurst exponent plot of a given EEG signal in patients with epilepsy the onset of seizure can be predicted by noticing the sudden changes in the plot.

Keywords: EEG signals, fractal analysis, fractal dimension, hurst exponent, Jeffrey’s measure

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Authors: Massimiliano Frezza, Sergio Bianchi, Augusto Pianese

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The relation between stock price volatility and trading volume represents a controversial issue which has received a remarkable attention over the past decades. In fact, an extensive literature shows a positive relation between price volatility and trading volume in the financial markets, but the causal relationship which originates such association is an open question, from both a theoretical and empirical point of view. In this regard, various models, which can be considered as complementary rather than competitive, have been introduced to explain this relationship. They include the long debated Mixture of Distributions Hypothesis (MDH); the Sequential Arrival of Information Hypothesis (SAIH); the Dispersion of Beliefs Hypothesis (DBH); the Noise Trader Hypothesis (NTH). In this work, we analyze whether stock market efficiency can explain the diversity of results achieved during the years. For this purpose, we propose an alternative measure of market efficiency, based on the pointwise regularity of a stochastic process, which is the Hurst–H¨older dynamic exponent. In particular, we model the stock market by means of the multifractional Brownian motion (mBm) that displays the property of a time-changing regularity. Mostly, such models have in common the fact that they locally behave as a fractional Brownian motion, in the sense that their local regularity at time t0 (measured by the local Hurst–H¨older exponent in a neighborhood of t0 equals the exponent of a fractional Brownian motion of parameter H(t0)). Assuming that the stock price follows an mBm, we introduce and theoretically justify the Hurst–H¨older dynamical exponent as a measure of market efficiency. This allows to measure, at any time t, markets’ departures from the martingale property, i.e. from efficiency as stated by the Efficient Market Hypothesis. This approach is applied to financial markets; using data for the SP500 index from 1978 to 2017, on the one hand we find that when efficiency is not accounted for, a positive contemporaneous relationship emerges and is stable over time. Conversely, it disappears as soon as efficiency is taken into account. In particular, this association is more pronounced during time frames of high volatility and tends to disappear when market becomes fully efficient.

Keywords: volume–volatility relationship, efficient market hypothesis, martingale model, Hurst–Hölder exponent

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Authors: H. Namazi, H. T. N. Kuan

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Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to visual stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeffrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to visual stimuli but provide us with very good recommendations for clinical purposes.

Keywords: visual stimuli, brain response, EEG signal, fractal dimension, hurst exponent, Jeffrey’s measure

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Authors: H. Namazi, H. T. N. Kuan

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Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to auditory stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeffrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to auditory stimuli but provide us with very good recommendations for clinical purposes.

Keywords: auditory stimuli, brain response, EEG signal, fractal dimension, hurst exponent, Jeffrey’s measure

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Authors: Valeria Bondarenko

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In this paper, we propose two problems related to fractal Brownian motion. First problem is simultaneous estimation of two parameters, Hurst exponent and the volatility, that describe this random process. Numerical tests for the simulated fBm provided an efficient method. Second problem is approximation of the increments of the observed time series by a power function by increments from the fractional Brownian motion. Approximation and estimation are shown on the example of real data, daily deposit interest rates.

Keywords: fractional Brownian motion, Gausssian processes, approximation, time series, estimation of properties of the model

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Authors: Valeria Bondarenko

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We proposed algorithms for: estimation of parameters fBm (volatility and Hurst exponent) and for the approximation of random time series by functional of fBm. We proved the consistency of the estimators, which constitute the above algorithms, and proved the optimal forecast of approximated time series. The adequacy of estimation algorithms, approximation, and forecasting is proved by numerical experiment. During the process of creating software, the system has been created, which is displayed by the hierarchical structure. The comparative analysis of proposed algorithms with the other methods gives evidence of the advantage of approximation method. The results can be used to develop methods for the analysis and modeling of time series describing the economic, physical, biological and other processes.

Keywords: mathematical model, random process, Wiener process, fractional Brownian motion

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Authors: Sania Ashraf

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The paper focuses on the prevalence of informational efficiency and integration of GCC Shariah Equity market for the period of 01st January 2010 to 31st June 2015 with daily equity returns of Kuwait, Oman, Qatar, Bahrain, Saudi Arabia and United Arab Emirates. The study employs traditional as well as the modern approach of tracing out the efficiency and integration in the return series. From the results of efficiency it was observed that the market lacked efficiency in terms of its past information. The results of integration test clearly indicates that there was a long memory in the returns of GCC Shariah during the study period. Hence it was concluded and proved that the returns of all GCC Equity Shariah were not informationally efficient but fractionally integrated during the study period.

Keywords: efficiency, Fama, GCC shariah, hurst exponent, integration, serial correlation

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Authors: Gemma Garcia Lopez

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The goal of this study is to perform an emotional analysis of the hooks used in Facebook by three of the most important daily newspapers in the USA. These hook texts are used to get the user's attention and invite him to read the news and linked contents. Thanks to the emotional analysis in text, made with the tool of IBM, Tone Analyzer, we discovered that more than 30% of the hooks can be classified emotionally as joy, sadness, anger or fear. This study gathered the publications made by The New York Times, USA Today and The Washington Post during a random day. The results show that the choice of words by the journalist, can expose the reader to different emotions before clicking on the content. In the three cases analyzed, the absence of emotions in some cases, and the presence of emotions in text in others, appear in very similar percentages. Therefore, beyond the objectivity and veracity of the content, a new factor could come into play: the emotional influence on the reader as a mediatic manipulation tool.

Keywords: emotional analysis of newspapers hooks, emotions on Facebook, newspaper hooks on Facebook, news publication on Facebook

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Authors: Tushnik Sarkar, Mofazzal H. Khondekar, Subrata Banerjee

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This paper investigates the nature of the fluctuation of the daily average Solar wind speed time series collected over a period of 2492 days, from 1^st January, 1997 to 28^th October, 2003. The degree of self-similarity and scalability of the Solar Wind Speed signal has been explored to characterise the signal fluctuation. Multi-fractal Detrended Fluctuation Analysis (MFDFA) method has been implemented on the signal which is under investigation to perform this task. Furthermore, the singularity spectra of the signals have been also obtained to gauge the extent of the multifractality of the time series signal.

Keywords: detrended fluctuation analysis, generalized hurst exponent, holder exponents, multifractal exponent, multifractal spectrum, singularity spectrum, time series analysis

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Authors: Jamal Choudhry, Roland Larsson, Andreas Almqvist

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A multi-scale flash temperature model has been developed and validated against existing work. The core strength of the proposed model is that it can be adapted to predict flash contact temperatures occurring in various types of sliding systems. In this paper, it is used to investigate how different surface roughness parameters affect the flash temperatures. The results show that for decreasing Hurst exponents as well as increasing values of the high-frequency cut-off, the maximum flash temperature increases. It was also shown that the effect of surface roughness does not influence the average interface temperature. The model predictions were validated against data from an experiment conducted in a pin-on-disc machine. This also showed the importance of including a wear model when simulating flash temperature development in a sliding system.

Keywords: multiscale, pin-on-disc, finite element method, flash temperature, surface roughness

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Authors: Gemma García López

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The goal of this study is to analyze if search queries carried out in search engines such as Google, can offer emotional information about the user that performs them. Knowing the emotional state in which the Internet user is located can be a key to achieve the maximum personalization of content and the detection of worrying behaviors. For this, two studies were carried out using tools with advanced natural language processing techniques. The first study determines if a query can be classified as positive, negative or neutral, while the second study extracts emotional content from words and applies the categorical and dimensional models for the representation of emotions. In addition, we use search queries in Spanish and English to establish similarities and differences between two languages. The results revealed that text search queries performed by users on the Internet can be classified emotionally. This allows us to better understand the emotional state of the user at the time of the search, which could involve adapting the technology and personalizing the responses to different emotional states.

Keywords: emotion classification, text search queries, emotional analysis, sentiment analysis in text, natural language processing

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Authors: Gemma A. Gruyal

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Plants can contain a wide variety of substances with antioxidative properties which are associated to important health benefits. These positive health effects are of great importance at a time when the environment is laden with many toxic substances. Five selected herbal plants namely, Mimosa pudica, Phyllanthus niruri, Ceiba pentandra, Eleusine polydactyla and Trema amboinensis, were chosen for the experiment to investigate their total phenolics content and antioxidant activities using ABTS radical cation decolorization power, and ferric reducing antioxidant power. The total phenolic content of each herbal plants ranges from 0.84 to 42.59 mg gallic acid equivalent/g. The antioxidant activity in the ABTS radical cation decolorization power varies from 0.005 to 0.362 mg trolox equivalent/g and the FRAP ranges from 0.30 to 28.42 mg gallic acid equivalent/g. Among the five medicinal plants, Mimosa pudica has been an excellent performer in terms of the 3 parameters measured; it is followed by Phyllanthus niruri. The five herbal plants do not have equivalent antioxidant power. The relative high values for M. pudica and P. niruri supports the medicinal value of both plants. The total phenolics, ABTS and FRAP correlate strongly with one another.

Keywords: ABTS, FRAP, Leaf extracts, phenol

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Authors: Ceren Vardar Acar, Mine Caglar

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In finance, the price of a volatile asset can be modeled using fractional Brownian motion (fBm) with Hurst parameter H>1/2. The Black-Scholes model for the values of returns of an asset using fBm is given as, 〖Y_t=Y_0 e^((r+μ)t+σB)〗_t^H, 0≤t≤T where Y_0 is the initial value, r is constant interest rate, μ is constant drift and σ is constant diffusion coefficient of fBm, which is denoted by B_t^H where t≥0. Black-Scholes model can be constructed with some Markov processes such as Brownian motion. The advantage of modeling with fBm to Markov processes is its capability of exposing the dependence between returns. The real life data for a volatile asset display long-range dependence property. For this reason, using fBm is a more realistic model compared to Markov processes. Investors would be interested in any kind of information on the risk in order to manage it or hedge it. The maximum possible loss is one way to measure highest possible risk. Therefore, it is an important variable for investors. In our study, we give some theoretical bounds on the distribution of maximum possible loss of fBm. We provide both asymptotical and strong estimates for the tail probability of maximum loss of standard fBm and fBm with drift and diffusion coefficients. In the investment point of view, these results explain, how large values of possible loss behave and its bounds.

Keywords: maximum drawdown, maximum loss, fractional brownian motion, large deviation, Gaussian process

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Authors: Fergus Wade, Jasmine Makker, Matthew Jankinson, Aminah Qamar, Gemma Morrelli, Shayan Shah

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Background: Ambulance offload delays (AODs) affect patient outcomes. At baseline, the average AOD at Princess Royal University Hospital (PRUH) was 41 minutes, in breach of the 15-minute target. Aims: By February 2023, we aimed to reduce: the average AOD to 30 minutes percentage of AOD >30 minutes (PA30) to 25% and >60 minutes (PA60) to 10% Methods: Following a root-cause analysis, we implemented 2 Plan, Do, Study, Act (PDSA) cycles. PDSA-1 ‘Drop-and-run’: ambulances waiting >15 minutes for a handover left the patients in the Emergency Department (ED) and returned to the community. PDSA-2: Booking in the patients before the handover, allowing direct updates to online records, eliminating the need for handwritten notes. Outcome measures: AOD, PA30, and PA60, and process measures: total ambulances and patients in the ED were recorded for 16 weeks. Results: In PDSA-1, all parameters increased slightly despite unvarying ED crowding. In PDSA-2, two shifts in data were seen: initially, a sharp increase in the outcome measures consistent with increased ED crowding, followed by a downward shift when crowding returned to baseline (p<0.01). Within this interval, the AOD reduced to 29.9 minutes, and PA30 and PA60 were 31.2% and 9.2% respectively. Discussion/conclusion: PDSA-1 didn’t result in any significant changes; lack of compliance was a key cause. The initial upward shift in PDSA-2 is likely associated with NHS staff strikes. However, during the second interval, the AOD and the PA60 met our targets of 30 minutes and 10%, respectively, improving patient flow in the ED. This was sustained without further input and if maintained, saves 2 paramedic shifts every 3 days.

Keywords: ambulance offload, district general hospital, handover, quality improvement

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Authors: Gemma Postil, Claire Zanin, Michael Halpin, Caroline Ritter

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Illness experience research typically focuses on people that are living with a medical condition; however, the broad consequences of the COVID-19 pandemic are impacting those without the virus itself, as many experienced extensive lockdowns, social isolation, and distress. Drawing on conceptual work in the illness experience literature, we argue that policy and social changes tied to COVID-19 produce biographical disruptions. In this sense, we argue that the COVID-19 pandemic produces illness experience without illness, as the pandemic comprehensively impacts health and biography. This paper draws on 30 in-depth interviews with young adults living in Prince Edward Island (PEI), which were conducted as part of a larger project to understand how young adults navigate compliance with the COVID-19 pandemic. We then inductively analyzed the interviews with a constructivist grounded theory approach. Specifically, we demonstrate that young adults living in PEI during the COVID-19 pandemic experienced biographical disruptions throughout the pandemic despite not contracting the virus. First, we detail how some participants experience biographical acceleration, with the pandemic accelerating relationships, home buying, and career planning. Second, we demonstrate biographical stagnation, wherein participants report being unable to pursue major life milestones. Lastly, we describe biographical regression, wherein participants feel they are losing ground during the pandemic and are actively falling behind their peers. These findings provide the novel application of illness experience concepts to the context of the COVID-19 pandemic, contribute to work on illness experience and ambiguity, and extend Bury’s conceptualization of biographical disruption. In conclusion, we demonstrate that young adults experienced the biographical disruption expected from having COVID-19 without having an illness, highlighting the depth to which the pandemic affected young adults.

Keywords: illness experience, lived experience, biographical disruption, COVID-19, young adults

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Authors: Massimiliano Frezza, Sergio Bianchi, Augusto Pianese

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Introduced by Shannon in 1948 in the field of information theory as the average rate at which information is produced by a stochastic set of data, the concept of entropy has gained much attention as a measure of uncertainty and unpredictability associated with a dynamical system, eventually depicted by a stochastic process. In particular, the Shannon entropy measures the degree of order/disorder of a given signal and provides useful information about the underlying dynamical process. It has found widespread application in a variety of fields, such as, for example, cryptography, statistical physics and finance. In this regard, many contributions have employed different measures of entropy in an attempt to characterize the financial time series in terms of market efficiency, market crashes and/or financial crises. The Shannon entropy has also been considered as a measure of the risk of a portfolio or as a tool in asset pricing. This work investigates the theoretical link between the Shannon entropy and the multifractional Brownian motion (mBm), stochastic process which recently is the focus of a renewed interest in finance as a driving model of stochastic volatility. In particular, after exploring the current state of research in this area and highlighting some of the key results and open questions that remain, we show a well-defined relationship between the Shannon (log)entropy and the memory function H(t) of the mBm. In details, we allow both the length of time series and time scale to change over analysis to study how the relation modify itself. On the one hand, applications are developed after generating surrogates of mBm trajectories based on different memory functions; on the other hand, an empirical analysis of several international stock indexes, which confirms the previous results, concludes the work.

Keywords: Shannon entropy, multifractional Brownian motion, Hurst–Holder exponent, stock indexes

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Authors: Pinna Beatrice., Laini Alex, Negro Giovanni, Burgazzi Gemma, Viaroli Pierluigi, Vezza Paolo

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Habitat models rarely consider macroinvertebrates as ecological targets in rivers. Available approaches mainly focus on single macroinvertebrate species, not addressing the ecological needs and functionality of the entire community. This research aimed to provide an approach to model the habitat of the macroinvertebrate community. The approach is based on the recently developed Flow-T index, together with a Random Forest (RF) regression, which is employed to apply the Flow-T index at the meso-habitat scale. Using different datasets gathered from both field data collection and 2D hydrodynamic simulations, the model has been calibrated in the Trebbia river (2019 campaign), and then validated in the Trebbia, Taro, and Enza rivers (2020 campaign). The three rivers are characterized by a braiding morphology, gravel riverbeds, and summer low flows. The RF model selected 12 mesohabitat descriptors as important for the macroinvertebrate community. These descriptors belong to different frequency classes of water depth, flow velocity, substrate grain size, and connectivity to the main river channel. The cross-validation R² coefficient (R²𝒸ᵥ) of the training dataset is 0.71 for the Trebbia River (2019), whereas the R² coefficient for the validation datasets (Trebbia, Taro, and Enza Rivers 2020) is 0.63. The agreement between the simulated results and the experimental data shows sufficient accuracy and reliability. The outcomes of the study reveal that the model can identify the ecological response of the macroinvertebrate community to possible flow regime alterations and to possible river morphological modifications. Lastly, the proposed approach allows extending the MesoHABSIM methodology, widely used for the fish habitat assessment, to a different ecological target community. Further applications of the approach can be related to flow design in both perennial and non-perennial rivers, including river reaches in which fish fauna is absent.

Keywords: ecological flows, macroinvertebrate community, mesohabitat, river habitat modeling

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Authors: Marie Sams, Kate Barnett-Richards, Jacqui Speculand, Gemma Tombs

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Business education in the United Kingdom has seen a number of improvements over the years in moving from delivering traditional chalk and talk lectures to using digital technologies and inviting guest lectures from industry to deliver sessions for students. Engaging topical industry talks to enhance course delivery is generally seen as a positive aspect of enhancing curriculum, however it is acknowledged that perhaps there are better ways in which industry can contribute to the quality of business programmes. Additionally, there is a consensus amongst UK industry managers that a bigger involvement in designing and inputting into business curriculum will have a greater impact on the quality of business ready graduates. Funded by the Disruptive Media Learning Lab at Coventry University in the UK, a project (SOPI - Student Online Projects with Industry) was initiated to enable students to work in project teams to respond and engage with real problems and challenges faced by five managers in various industries including retail, events and manufacturing. Over a semester, approximately 200 students were given the opportunity to develop their management, facilitation, problem solving and reflective skills, whilst having some exposure to real challenges in industry with a focus on supply chain and project management. Face to face seminars were re-designed to enable students to work on live issues in a competitive environment, and were guided to consider the theoretical aspects of their module delivery to underpin the solutions that they were generating. Dialogue between student groups and managers took place using Google+ community; an online social media tool which enables private discussions to take place and can be accessed on mobile devices. Results of the project will be shared in how this development has added value to students experience and understanding of the two subject areas. Student reflections will be analysed and evaluated to assess how the project has contributed to their perception of how the theoretical nature of these two business subjects are applied in practical situations.

Keywords: business, education, industry, projects

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Authors: Pablo González Álvarez, Anna Vinaixa Vergés, Paula Sol Ventura, Paula Fernández, Mercè Redorta, Gemma Ginovart Galiana, Maria Méndez Hernández

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Context: The use of music therapy is gaining popularity worldwide, and it has shown positive effects in neonatology. Hospital Germans Trias i Pujol has recently established a music therapy unit and initiated a project in their neonatal intensive care unit (NICU). Research Aim: The aim of this study is to measure the effect of a music therapy intervention in the NICU of Hospital Germans Trias i Pujol in Spain. Methodology: The study will be an observational analytical case-control study. All newborns admitted to the neonatology unit, both term and preterm, and their parents will be offered a session of music therapy. Data will be collected from families who receive at least two music therapy sessions. Maternal and paternal anxiety levels will be measured through a pre- and post-intervention test. Findings: The study aims to demonstrate the benefits and acceptance of music therapy by patients, parents, and healthcare workers in the neonatal unit. The findings are expected to show a reduction in maternal and paternal anxiety levels following the music therapy sessions. Theoretical Importance: This study contributes to the growing body of literature on the effectiveness of music therapy in neonatal care. It will provide evidence of the acceptance and potential benefits of music therapy in reducing anxiety levels in both parents and babies in the NICU setting. Data Collection: Data will be collected from families who receive at least two music therapy sessions. This will include pre- and post-intervention test results to measure anxiety levels. Analysis Procedures: The collected data will be analyzed using appropriate statistical methods to determine the impact of music therapy on reducing anxiety levels in parents. Questions Addressed: - What is the effect of music therapy on maternal anxiety levels? - What is the effect of music therapy on paternal anxiety levels? - What is the acceptability and perceived benefits of music therapy among patients and healthcare workers in the NICU? Conclusion: The study aims to provide evidence supporting the value of music therapy in the neonatal intensive care unit. It seeks to demonstrate the positive effect of music therapy on reducing anxiety levels among parents.

Keywords: neonatology, music therapy, neonatal intensive care unit, babies, parents

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Authors: Shankha Sanyal, Archi Banerjee, Sayan Biswas, Sourya Sengupta, Sayan Nag, Ranjan Sengupta, Dipak Ghosh

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The term ‘gestalt’ has been widely used in the field of psychology which defined the perception of human mind to group any object not in part but as a 'unified' whole. Music, in general, is polyphonic - i.e. a combination of a number of pure tones (frequencies) mixed together in a manner that sounds harmonious. The study of human brain response due to different frequency groups of the acoustic signal can give us an excellent insight regarding the neural and functional architecture of brain functions. Hence, the study of music cognition using neuro-biosensors is becoming a rapidly emerging field of research. In this work, we have tried to analyze the effect of different frequency bands of music on the various frequency rhythms of human brain obtained from EEG data. Four widely popular Rabindrasangeet clips were subjected to Wavelet Transform method for extracting five resonant frequency bands from the original music signal. These frequency bands were initially analyzed with Detrended/Adaptive Fractal analysis (DFA/AFA) methods. A listening test was conducted on a pool of 100 respondents to assess the frequency band in which the music becomes non-recognizable. Next, these resonant frequency bands were presented to 20 subjects as auditory stimulus and EEG signals recorded simultaneously in 19 different locations of the brain. The recorded EEG signals were noise cleaned and subjected again to DFA/AFA technique on the alpha, theta and gamma frequency range. Thus, we obtained the scaling exponents from the two methods in alpha, theta and gamma EEG rhythms corresponding to different frequency bands of music. From the analysis of music signal, it is seen that loss of recognition is proportional to the loss of long range correlation in the signal. From the EEG signal analysis, we obtain frequency specific arousal based response in different lobes of brain as well as in specific EEG bands corresponding to musical stimuli. In this way, we look to identify a specific frequency band beyond which the music becomes non-recognizable and below which in spite of the absence of other bands the music is perceivable to the audience. This revelation can be of immense importance when it comes to the field of cognitive music therapy and researchers of creativity.

Keywords: AFA, DFA, EEG, gestalt in music, Hurst exponent

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Authors: Matthew J. I. Woolley, Gemma J. M. Read, Paul M. Salmon, Natassia Goode

Abstract:

The significance of high consequence, workplace failures within construction continues to resonate with a combined average of 12 fatal incidents occurring daily throughout Australia, the United Kingdom, and the United States. Within the Australian construction domain, more than 35 serious, compensable injury incidents are reported daily. These alarming figures, in conjunction with the continued occurrence of fatal and serious, occupational injury incidents globally suggest existing approaches to incident analysis may not be achieving required injury prevention outcomes. One reason may be that, incident analysis methods used in construction have not kept pace with advances in the field of safety science and are not uncovering the full range system-wide contributory factors that are required to achieve optimal levels of construction safety performance. Another reason underpinning this global issue may also be the absence of information surrounding the construction operating and project delivery system. For example, it is not clear who shares the responsibility for construction safety in different contexts. To respond to this issue, to the author’s best knowledge, a first of its kind, control structure model of the construction industry is presented and then used to analyse a fatal construction incident. The model was developed by applying and extending the Systems Theoretic and Incident Model and Process method to hierarchically represent the actors, constraints, feedback mechanisms, and relationships that are involved in managing construction safety performance. The Causal Analysis based on Systems Theory (CAST) method was then used to identify the control and feedback failures involved in the fatal incident. The conclusions from the Coronial investigation into the event are compared with the findings stemming from the CAST analysis. The CAST analysis highlighted additional issues across the construction system that were not identified in the coroner’s recommendations, suggested there is a potential benefit in applying a systems theory approach to incident analysis in construction. The findings demonstrate the utility applying systems theory-based methods to the analysis of construction incidents. Specifically, this study shows the utility of the construction control structure and the potential benefits for project leaders, construction entities, regulators, and construction clients in controlling construction performance.

Keywords: construction project management, construction performance, incident analysis, systems thinking

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Authors: Jeffrey L. Hurst, Sarah M. Coyne

Abstract:

With the growth of technology and media, teens are increasingly exposed to media such as pornography and engaging in risky media use such as sexting. Parental media mediation strategies including controlling or autonomy supporting strategies can be an important protective factor against risky media uses. The purpose of this study is to examine how parental media mediation around media, influence adolescents’ behaviors including frequency of pornography use and sexting. We also examine the effects of parental media mediation on adolescents disclosing pornography use to parents and the amount of secrets that adolescents keep about pornography use. We hypothesize that controlling media mediation will result in more sexting, more frequency pornography use, more secrets about pornography and less disclosure to parents. We also predict that autonomy supportive media mediation will show the opposite pattern. Data for this study came from a nationally representative research project, Project M.E.D.I.A. Participants included 783 adolescents. 49% of the participants were male, and the mean age for boys was 15.44 years (SD= 3.34) and for girls was 15.3 years (SD=2.93). Parental media mediation was assessed using an eight-item measure with subscales of controlling and autonomy supporting media mediation. Participants were also asked if they have ever viewed pornography. If they answered yes, they were asked about the frequency of pornography use as well as if they have ever kept secrets from their parents about it and if they had ever disclosed their pornography use to their parents. The data analysis strategy for this study was a multiple group path analysis. Frequency of pornography use, sexting, secrets from parents and disclosure to parents were predicted by controlling and autonomy supporting parental media mediation, frequency of parents warning against pornography use, income and ethnicity. Groups were distinguished by boys and girls, allowing for sex differences. After running the model in MPLUS, we found partial support for our hypotheses. Autonomy supportive media mediation resulted in less sexting for boys (β= -.15, p < .05) and girls ( β= -.13, p < .05). Autonomy supportive media mediation also predicted keeping fewer secrets for girls (β=-.27, p < .01) but had no effect for boys. Controlling media mediation predicted more disclosure about pornography to parents for boys (β=.16, p < .05) and less disclosure to parents about pornography for girls (β=-.14, p < .05). Frequency of pornography was not predicted by any of the predictors in the model. Autonomy supportive media mediation was a very strong predictor of less sexting for both boys and girls. Parents should approach media mediation with this supportive and understanding mindset. Parental autonomy support allows adolescents to explore and develop their own moral beliefs without feeling guilt or shame from their parents. This need to have autonomy is also shown by girls disclosing less pornography use to their parents when parents are really controlling about media use. Interestingly, boys disclosed more to their parents when their parents were controlling. Further research is needed on why this is. Further research should also look at the effects that disclosing pornography use to parents has on future pornography use.

Keywords: media, moral development, parental mediation, pornography, sexting

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Authors: Gemma Reynolds, Deborah Bailey Rodriguez, Maria Paula Valdivieso Rueda

Abstract:

In recent years, the mental health of Higher Education (HE) students has been a growing concern. This has been further exacerbated by the stresses associated with the Covid-19 pandemic, placing students at even greater risk of developing mental health issues. Support available to students in HE tends to follow an established and traditional route. The demands for counselling services have grown, not only with the increase in student numbers but with the number of students seeking support for mental health issues. One way of improving well-being and mental health in HE students is through the use of brief interventions, such as expressive writing (EW). This intervention involves encouraging individuals to write continuously for at least 15-20 minutes for three to five sessions (often on consecutive days) about their deepest thoughts and feelings to explore significant personal experiences in a meaningful way. Given the brevity, simplicity and cost-effectiveness of EW, this intervention has considerable potential as an intervention for HE populations. The current study, therefore, employed a mixed-methods design to explore the effectiveness of EW in reducing anxiety, general stress, academic stress and depression in HE students while improving well-being. HE students at MDX were randomly assigned to one of three conditions: (1) The UniExp-EW group were required to write about their emotions and thoughts about any stressors they have faced that are directly relevant to their university experience (2) The NonUniExp-EW group were required to write about their emotions and thoughts about any stressors that are NOT directly relevant to their university experience, and (3) The Control group were required to write about how they spent their weekend, with no reference to thoughts or emotions, and without thinking about university. Participants were required to carry out the EW intervention for 15minutes per day for four consecutive days. Baseline mental health and wellbeing measures were taken before the intervention via a battery of standardised questionnaires. Following completion of the intervention on day four, participants were required to complete the questionnaires a second time and again one week later. Participants were also invited to attend focus groups to discuss their experience of the intervention. This will allow an in-depth investigation into students’ perceptions of EW as an effective intervention to determine whether they would choose to use this intervention in the future. The quantitative findings will be discussed at the conference as well as a discussion of the important implications of the findings. The study is fundamental because if EW is an effective intervention for improving mental health and well-being in HE students, its brevity and simplicity means it can be easily implemented and can be freely-available to students. Improving the mental health and well-being of HE students can have knock-on implications for improving academic skills and career development.

Keywords: mental health, wellbeing, higher education students, expressive writing

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Authors: Deborah Bailey-Rodriguez, Maria Paula Valdivieso Rueda, Gemma Reynolds

Abstract:

In recent years, the mental health of Higher Education (HE) students has been a growing concern. This has been further exacerbated by the stresses associated with the Covid-19 pandemic, placing students at even greater risk of developing mental health issues. Support available to students in HE tends to follow an established and traditional route. The demands for counseling services have grown, not only with the increase in student numbers but with the number of students seeking support for mental health issues, with 94% of HE institutions recently reporting an increase in the need for counseling services. One way of improving the well-being and mental health of HE students is through the use of brief interventions, such as expressive writing (EW). This intervention involves encouraging individuals to write continuously for at least 15-20 minutes for three to five sessions (often on consecutive days) about their deepest thoughts and feelings to explore significant personal experiences in a meaningful way. Given the brevity, simplicity and cost-effectiveness of EW, this intervention has considerable potential as an intervention for HE populations. The current study, therefore, employed a mixed-methods design to explore the effectiveness of EW in reducing anxiety, general stress, academic stress and depression in HE students while improving well-being. HE students at MDX were randomly assigned to one of three conditions: (1) The UniExp-EW group was required to write about their emotions and thoughts about any stressors they have faced that are directly relevant to their university experience (2) The NonUniExp-EW group was required to write about their emotions and thoughts about any stressors that are NOT directly relevant to their university experience, and (3) The Control group were required to write about how they spent their weekend, with no reference to thoughts or emotions, and without thinking about university. Participants were required to carry out the EW intervention for 15 minutes per day for four consecutive days. Baseline mental health and well-being measures were taken before the intervention via a battery of standardized questionnaires. Following completion of the intervention on day four, participants were required to complete the questionnaires a second time and again one week later. Participants were also invited to attend focus groups to discuss their experience of the intervention. This will allow an in-depth investigation into students’ perceptions of EW as an effective intervention to determine whether they would choose to use this intervention in the future. Preliminary findings will be discussed at the conference as well as a discussion of the important implications of the findings. The study is fundamental because if EW is an effective intervention for improving mental health and well-being in HE students, its brevity and simplicity mean it can be easily implemented and can be freely available to students. Improving the mental health and well-being of HE students can have knock-on implications for improving academic skills and career development.

Keywords: expressive writing, higher education, psychology in education, mixed-methods, mental health, academic stress

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Authors: Jessica Raven Gates, Gemma Wilson-Menzfeld, Professor Alison Steven

Abstract:

In 2019, the Primary Care system in the UK National Health Service (NHS) was subject to reform and restructuring. Primary Care Networks (PCNs) were established, which aligned with a trend towards integrated care both within the NHS and internationally. The introduction of PCNs brought groups of GP practices in a locality together, to operate as a network, build on existing services and collaborate at a larger scale. PCNs were expected to bring a range of benefits to patients and address some of the workforce pressures in the NHS, through an expanded and collaborative workforce. The early establishment of PCNs was disrupted by the emerging COVID-19 pandemic. This study, set in the context of the pandemic, aimed to explore experiences of the PCN workforce, and their perceptions of the establishment of PCNs. Specific objectives focussed on examining factors perceived as enabling or hindering the success of a PCN, the impact on day-to-day work, the approach to implementing change, and the influence of the COVID-19 pandemic upon PCN development. This study is part of a three-phase PhD project that utilized qualitative approaches and was underpinned by social constructionist philosophy. Phase 1: a systematic narrative review explored the provision of preventative healthcare services in UK primary settings and examined facilitators and barriers to delivery as experienced by the workforce. Phase 2: informed by the findings of phase 1, semi-structured interviews were conducted with fifteen participants (PCN workforce). Phase 3: follow-up interviews were conducted with original participants to examine any changes to their experiences and perceptions of PCNs. Three main themes span across phases 2 and 3 and were generated through a Framework Analysis approach: 1) working together at scale, 2) network infrastructure, and 3) PCN leadership. Findings suggest that through efforts to work together at scale and collaborate as a network, participants have broadly accepted the concept of PCNs. However, the workforce has been hampered by system design and system complexity. Operating against such barriers has led to a negative psychological impact on some PCN leaders and others in the PCN workforce. While the pandemic undeniably increased pressure on healthcare systems around the world, it also acted as a disruptor, offering a glimpse into how collaboration in primary care can work well. Through the integration of findings from all phases, a new theoretical model has been developed, which conceptualises the findings from this Ph.D. study and demonstrates how the workforce has experienced change associated with the establishment of PCNs. The model includes a contextual component of the COVID-19 pandemic and has been informed by concepts from Complex Adaptive Systems theory. This model is the original contribution to knowledge of the PhD project, alongside recommendations for practice, policy and future research. This study is significant in the realm of health services research, and while the setting for this study is the UK NHS, the findings will be of interest to an international audience as the research provides insight into how the healthcare workforce may experience imposed policy and service changes.

Keywords: health services research, qualitative research, NHS workforce, primary care

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