Search results for: robustness against disturbance

Authors: Eliane G. Tótoli, Hérida Regina N. Salgado

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Daptomycin is an important antimicrobial agent used in clinical practice nowadays, since it is very active against some Gram-positive bacteria that are particularly challenges for the medicine, such as methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE). The importance of environmental preservation has receiving special attention since last years. Considering the evident need to protect the natural environment and the introduction of strict quality requirements regarding analytical procedures used in pharmaceutical analysis, the industries must seek environmentally friendly alternatives in relation to the analytical methods and other processes that they follow in their routine. In view of these factors, green analytical chemistry is prevalent and encouraged nowadays. In this context, infrared spectroscopy stands out. This is a method that does not use organic solvents and, although it is formally accepted for the identification of individual compounds, also allows the quantitation of substances. Considering that there are few green analytical methods described in literature for the analysis of daptomycin, the aim of this work was the development and validation of a green analytical method for the quantification of this drug in lyophilized powder for injectable solution, by Fourier-transform infrared spectroscopy (FT-IR). Method: Translucent potassium bromide pellets containing predetermined amounts of the drug were prepared and subjected to spectrophotometric analysis in the mid-infrared region. After obtaining the infrared spectrum and with the assistance of the IR Solution software, quantitative analysis was carried out in the spectral region between 1575 and 1700 cm-1, related to a carbonyl band of the daptomycin molecule, and this band had its height analyzed in terms of absorbance. The method was validated according to ICH guidelines regarding linearity, precision (repeatability and intermediate precision), accuracy and robustness. Results and discussion: The method showed to be linear (r = 0.9999), precise (RSD% < 2.0), accurate and robust, over a concentration range from 0.2 to 0.6 mg/pellet. In addition, this technique does not use organic solvents, which is one great advantage over the most common analytical methods. This fact contributes to minimize the generation of organic solvent waste by the industry and thereby reduces the impact of its activities on the environment. Conclusion: The validated method proved to be adequate to quantify daptomycin in lyophilized powder for injectable solution and can be used for its routine analysis in quality control. In addition, the proposed method is environmentally friendly, which is in line with the global trend.

Keywords: daptomycin, Fourier-transform infrared spectroscopy, green analytical chemistry, quality control, spectrometry in IR region

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Authors: Jose CanIzares

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In the last decades, resilience has received much attention in relation to understanding and managing new forms of risk, especially in the context of urban adaptation to climate change. There are abundant concerns, however, on how to best interpret resilience and related ideas, and on whether they can guide ethically appropriate risk-related or adaptation efforts. Narrative creation and framing are critical steps in shaping public discussion and policy in large-scale interventions, since they favor or inhibit early decision and interpretation habits, which can be morally sensitive and then become persistent on time. This article adds to such framing process by contesting a conventional narrative on resilience and offering an alternative one. Conventionally, present ideas on resilience are traced to the work of ecologist C. S. Holling, especially to his article Resilience and Stability in Ecosystems. This article is usually portrayed as a contribution of complex systems thinking to theoretical ecology, where Holling appeals to resilience in order to challenge received views on ecosystem stability and the diversity-stability hypothesis. In this regard, resilience is construed as a “purely scientific”, precise and descriptive concept, denoting a complex property that allows ecosystems to persist, or to maintain functions, after disturbance. Yet, these formal features of resilience supposedly changed with Holling’s later work in the 90s, where, it is argued, Holling begun to use resilience as a more pragmatic “boundary term”, aimed at unifying transdisciplinary research about risks, ecological or otherwise, and at articulating public debate and governance strategies on the issue. In the conventional story, increased vagueness and degrees of normativity are the price to pay for this conceptual shift, which has made the term more widely usable, but also incompatible with scientific purposes and morally problematic (if not completely objectionable). This paper builds on a detailed analysis of Holling’s early work to propose an alternative narrative. The study will show that the “complexity turn” has often entangled theoretical and pragmatic aims. Accordingly, Holling’s primary aim was to fight what he termed “pathologies of natural resource management” or “pathologies of command and control management”, and so, the terms of his reform of ecosystem science are partly subordinate to the details of his proposal for reforming the management sciences. As regards resilience, Holling used it as a polysemous, ambiguous and normative term: sometimes, as an instrumental value that is closely related to various stability concepts; other times, and more crucially, as an intrinsic value and a tool for attacking efficiency and instrumentalism in management. This narrative reveals the limitations of its conventional alternative and has several practical advantages. It captures well the structure and purposes of Holling’s project, and the various roles of resilience in it. It helps to link Holling’s early work with other philosophical and ideological shifts at work in the 70s. It highlights the currency of Holling’s early work for present research and action in fields such as risk and climate adaptation. And it draws attention to morally relevant aspects of resilience that the conventional narrative neglects.

Keywords: resilience, complexity turn, risk management, positivistic, framing

Procedia PDF Downloads 141

Authors: Muhammad Waqas Baqai, Noman Shahzad, Rehman Alvi

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Communication among health care givers is the essence of quality patient care and any compromise results in errors and inefficiency leading to cumbersome outcomes. The use of smartphone among health professionals has increased tremendously. Almost every health professional carries it and majority of them uses a third party communication software called whatsApp for work related communications. It gives instant access to the person responsible for any particular query and therefore helps in efficient and timely decision making. It is also an easy way of sharing medical documents, multimedia and provides platform for consensual decision making through group discussions. However clinical communication through whatsApp has some demerits too including reduction in verbal communication, worsening professional relations, unprofessional behavior, risk of confidentiality breach and threats from cyber-attacks. On the other hand the traditional pager device being used in many health care systems is a unidirectional communication that lacks the ability to convey any information other than the number to which the receiver has to respond. Our study focused on these two widely used modalities of communication among doctors of the largest tertiary care center of Pakistan i.e. The Aga Khan University Hospital. Our aim was to note which modality is considered better and has fewer threats to medical data. Approval from ethical review committee of the institute was taken prior to conduction of this study. We submitted an online survey form to all the interns and residents working at our institute and collected their response in a month’s time. 162 submissions were recorded and analyzed using descriptive statistics. Only 20% of them were comfortable with using pagers exclusively, 52% with whatsApp and 28% with both. 65% think that whatsApp is time-saving and quicker than pager. 54% of them considered whatsApp to be causing nuisance from work related notifications in their off-work hours. 60% think that they are more likely to miss information through pager system because of the unidirectional nature. Almost all (96%) of residents and interns found whatsApp to be useful in terms of saving information for future reference. For urgent issues, majority (70%) preferred pager over whatsApp and also pager was considered more valid in terms of hospital policies and legal issues. Among major advantages of whatsApp as listed by them were; easy mass communication, sharing of clinical pictures, universal access and no need of carrying additional device. However the major drawback of using whatsApp for clinical communication that everyone shared was threat to patients’ confidentiality as clinicians usually share pictures of wounds, clinical documents etc. Lastly we asked them if they think there is a need of a separate application for instant communication dedicated to clinical communication only and 90% responded positively. Therefore, we concluded that both modalities have their merits and demerits but the greatest drawback with whatsApp is the risk of breach in patients’ confidentiality and off-work disturbance. Hence, we recommend a more secure, institute-run application for all intra hospital communications where they can share documents, pictures etc. easily under a controlled environment.

Keywords: WhatsApp, pager, clinical communication, confidentiality

Procedia PDF Downloads 119

Authors: Farnaz Farhangi

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Many people in New Zealand believe that the access to water is inexhaustible, and it comes from a history of virtually unrestricted access to it. For the region like Hamilton which is one of New Zealand’s fastest growing cities, it is crucial for policy makers to know about the future water consumption and implementation of rules and regulation such as universal water metering. Hamilton residents use water freely and they do not have any idea about how much water they use. Hence, one of proposed objectives of this research is focusing on forecasting water consumption using different methods. Residential water consumption time series exhibits seasonal and trend variations. Seasonality is the pattern caused by repeating events such as weather conditions in summer and winter, public holidays, etc. The problem with this seasonal fluctuation is that, it dominates other time series components and makes difficulties in determining other variations (such as educational campaign’s effect, regulation, etc.) in time series. Apart from seasonality, a stochastic trend is also combined with seasonality and makes different effects on results of forecasting. According to the forecasting literature, preprocessing (de-trending and de-seasonalization) is essential to have more performed forecasting results, while some other researchers mention that seasonally non-adjusted data should be used. Hence, I answer the question that is pre-processing essential? A wide range of forecasting methods exists with different pros and cons. In this research, I apply double seasonal ARIMA and Artificial Neural Network (ANN), considering diverse elements such as seasonality and calendar effects (public and school holidays) and combine their results to find the best predicted values. My hypothesis is the examination the results of combined method (hybrid model) and individual methods and comparing the accuracy and robustness. In order to use ARIMA, the data should be stationary. Also, ANN has successful forecasting applications in terms of forecasting seasonal and trend time series. Using a hybrid model is a way to improve the accuracy of the methods. Due to the fact that water demand is dominated by different seasonality, in order to find their sensitivity to weather conditions or calendar effects or other seasonal patterns, I combine different methods. The advantage of this combination is reduction of errors by averaging of each individual model. It is also useful when we are not sure about the accuracy of each forecasting model and it can ease the problem of model selection. Using daily residential water consumption data from January 2000 to July 2015 in Hamilton, I indicate how prediction by different methods varies. ANN has more accurate forecasting results than other method and preprocessing is essential when we use seasonal time series. Using hybrid model reduces forecasting average errors and increases the performance.

Keywords: artificial neural network (ANN), double seasonal ARIMA, forecasting, hybrid model

Procedia PDF Downloads 300

Authors: Muhammad Shahzad Hussain

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Two major problems are facing generally by conventional poultry farming that is disease outbreaks and poor performance, which results due to improper management. To enhance the growth performance and efficiency of feed and reduce disease outbreaks, antibiotic growth promoters (AGPs) which are antibiotics at sub-therapeutic levels, are extensively used in the poultry industry. European Union has banned the use of antibiotics due to their presence in poultry products, development of antibiotic-resistant pathogens, and disturbance of normal gut microbial ecology. These residues cause serious health concerns and produce antibiotic resistance in pathogenic microbes in human beings. These issues strengthen the need for the withdrawal of AGPs from poultry feed. Nowadays, global warming is a major issue, and it is more critical in tropical areas like Pakistan, where heat stress is already a major problem. Heat stress leads to poor production performance, high mortality, immuno-suppression, and concomitant diseases outbreak. The poultry feed industry in Pakistan, like other countries of the world, has been facing shortages and high prices of local as well as imported feed ingredients. Prebiotics are potential replacer for AGP as prebiotics has properties to enhance the production potential and reduce the growth of harmful bacteria as well as stimulate the growth/activity of beneficial bacteria. The most commonly used prebiotics in poultry includes mannan oligosaccharide (MOS). MOS is an essential component of the yeast cell wall (YCW) (Saccharomyces cerevisiae); therefore, the YCW wall possesses prebiotic properties. The use of distillery yeast wall (YCW) has the potential to replace conventional AGPs and to reduce mortality due to heat stress as well as to bind toxins in the feed. The dietary addition of YCW has not only positive effects on production performance in poultry during normal conditions but during stressful conditions. A total of 168-day-old broilers were divided into 6 groups, each of which has 28 birds with 4 replicates (n=7).Yeast cell wall (YCW) supplementation @ 0%, 1%, 1.5%, 2%, 2.5%, 3% from day 0 to 35. Heat stress was exposed from day 21 to 35 at 30±1.1ᵒC with relative humidity 65±5%. Zootechnical parameters like body weight, FCR, Organ development, and histomorphometric parameters were studied. A significant weight gain was observed at group C supplemented @ 1.5% YCW during the fifth week. Significant organ weight gain of Gizzard, spleen, small intestine, and cecum was observed at group C supplemented @ 1.5% YCW. According to morphometric indices Duodenum, Jejunum, and Ileum has significant villus height, while Jejunum and Ileum have also significant villus surface area in the group supplemented with 1.5% YCW. IEL count was only decreased in 1.5% YCW-fed group in jejunum and ileum, not in duodenum, that was less in 2% YCW-supplemented group. Dietary yeast cell wall of saccharomyces cerevisiae partially reduced the effects of high ambient temperature in terms of better growth and modified gut histology and components of mucosal immune response to better withstand heat stress in broilers.

Keywords: antibiotics, AGPs, broilers, MOS, prebiotics, YCW

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Authors: Loris Franchi, Daniele Calvi, Sabrina Corpino

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This paper presents a design methodology in which stakeholders are assisted with the exploration of a so-called negotiation space, aiming to the maximization of both group social welfare and single stakeholder’s perceived utility. The outcome results in less design iterations needed for design convergence while obtaining a higher solution effectiveness. During the early stage of a space project, not only the knowledge about the system but also the decision outcomes often are unknown. The scenario is exacerbated by the fact that decisions taken in this stage imply delayed costs associated with them. Hence, it is necessary to have a clear definition of the problem under analysis, especially in the initial definition. This can be obtained thanks to a robust generation and exploration of design alternatives. This process must consider that design usually involves various individuals, who take decisions affecting one another. An effective coordination among these decision-makers is critical. Finding mutual agreement solution will reduce the iterations involved in the design process. To handle this scenario, the paper proposes a design methodology which, aims to speed-up the process of pushing the mission’s concept maturity level. This push up is obtained thanks to a guided negotiation space exploration, which involves autonomously exploration and optimization of trade opportunities among stakeholders via Artificial Intelligence algorithms. The negotiation space is generated via a multidisciplinary collaborative optimization method, infused by game theory and multi-attribute utility theory. In particular, game theory is able to model the negotiation process to reach the equilibria among stakeholder needs. Because of the huge dimension of the negotiation space, a collaborative optimization framework with evolutionary algorithm has been integrated in order to guide the game process to efficiently and rapidly searching for the Pareto equilibria among stakeholders. At last, the concept of utility constituted the mechanism to bridge the language barrier between experts of different backgrounds and differing needs, using the elicited and modeled needs to evaluate a multitude of alternatives. To highlight the benefits of the proposed methodology, the paper presents the design of a CubeSat mission for the observation of lunar radiation environment. The derived solution results able to balance all stakeholders needs and guaranteeing the effectiveness of the selection mission concept thanks to its robustness in valuable changeability. The benefits provided by the proposed design methodology are highlighted, and further development proposed.

Keywords: concurrent engineering, artificial intelligence, negotiation in engineering design, multidisciplinary optimization

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Authors: Haohua Zong, Marios Kotsonis

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Plasma synthetic jet actuator (PSJA) is a new concept of zero net mass flow actuator which utilizes pulsed arc/spark discharge to rapidly pressurize gas in a small cavity under constant-volume conditions. The unique combination of high exit jet velocity (>400 m/s) and high actuation frequency (>5 kHz) provides a promising solution for high-speed high-Reynolds-number flow control. This paper focuses on the performance of PSJA in repetitive working mode which is more relevant to future flow control applications. A two-electrodes PSJA (cavity volume: 424 mm3, orifice diameter: 2 mm) together with a capacitive discharge circuit (discharge energy: 50 mJ-110 mJ) is designed to enable repetitive operation. Time-Resolved Particle Imaging Velocimetry (TR-PIV) system working at 10 kHz is exploited to investigate the influence of discharge frequency on performance of PSJA. In total, seven cases are tested, covering a wide range of discharge frequencies (20 Hz-560 Hz). The pertinent flow features (shock wave, vortex ring and jet) remain the same for single shot mode and repetitive working mode. Shock wave is issued prior to jet eruption. Two distinct vortex rings are formed in one cycle. The first one is produced by the starting jet whereas the second one is related with the shock wave reflection in cavity. A sudden pressure rise is induced at the throat inlet by the reflection of primary shock wave, promoting the shedding of second vortex ring. In one cycle, jet exit velocity first increases sharply, then decreases almost linearly. Afterwards, an alternate occurrence of multiple jet stages and refresh stages is observed. By monitoring the dynamic evolution of exit velocity in one cycle, some integral performance parameters of PSJA can be deduced. As frequency increases, the jet intensity in steady phase decreases monotonically. In the investigated frequency range, jet duration time drops from 250 µs to 210 µs and peak jet velocity decreases from 53 m/s to approximately 39 m/s. The jet impulse and the expelled gas mass (0.69 µN∙s and 0.027 mg at 20 Hz) decline by 48% and 40%, respectively. However, the electro-mechanical efficiency of PSJA defined by the ratio of jet mechanical energy to capacitor energy doesn’t show significant difference (o(0.01%)). Fourier transformation of the temporal exit velocity signal indicates two dominant frequencies. One corresponds to the discharge frequency, while the other accounts for the alternation frequency of jet stage and refresh stage in one cycle. The alternation period (300 µs approximately) is independent of discharge frequency, and possibly determined intrinsically by the actuator geometry. A simple analytical model is established to interpret the alternation of jet stage and refresh stage. Results show that the dynamic response of exit velocity to a small-scale disturbance (jump in cavity pressure) can be treated as a second-order under-damping system. Oscillation frequency of the exit velocity, namely alternation frequency, is positively proportional to exit area, but inversely proportional to cavity volume and throat length. Theoretical value of alternation period (305 µs) agrees well with the experimental value.

Keywords: plasma, synthetic jet, actuator, frequency effect

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Authors: Hussain Bohra, Pradyuman Sharma

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This study highlights the significance of Balance Sheet Indicators on the corporate performance in the case of Indian manufacturing companies. Balance sheet indicators show the actual financial health of the company and it helps to the external investors to choose the right company for their investment and it also help to external financing agency to give easy finance to the manufacturing companies. The period of study is 2000 to 2014 for 813 manufacturing companies for which the continuous data is available throughout the study period. The data is collected from PROWESS data base maintained by Centre for Monitoring Indian Economy Pvt. Ltd. Panel data methods like fixed effect and random effect methods are used for the analysis. The Likelihood Ratio test, Lagrange Multiplier test and Hausman test results proof the suitability of the fixed effect model for the estimation. Return on assets (ROA) is used as the proxy to measure corporate performance. ROA is the best proxy to measure corporate performance as it already used by the most of the authors who worked on the corporate performance. ROA shows return on long term investment projects of firms. Different ratios like Current Ratio, Debt-equity ratio, Receivable turnover ratio, solvency ratio have been used as the proxies for the Balance Sheet Indicators. Other firm specific variable like firm size, and sales as the control variables in the model. From the empirical analysis, it was found that all selected financial ratios have significant and positive impact on the corporate performance. Firm sales and firm size also found significant and positive impact on the corporate performance. To check the robustness of results, the sample was divided on the basis of different ratio like firm having high debt equity ratio and low debt equity ratio, firms having high current ratio and low current ratio, firms having high receivable turnover and low receivable ratio and solvency ratio in the form of firms having high solving ratio and low solvency ratio. We find that the results are robust to all types of companies having different form of selected balance sheet indicators ratio. The results for other variables are also in the same line as for the whole sample. These findings confirm that Balance sheet indicators play as significant role on the corporate performance in India. The findings of this study have the implications for the corporate managers to focus different ratio to maintain the minimum expected level of performance. Apart from that, they should also maintain adequate sales and total assets to improve corporate performance.

Keywords: balance sheet, corporate performance, current ratio, panel data method

Procedia PDF Downloads 237

Authors: T. Thein, S. Kalyar Myo

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Human uses visual information for understanding the speech contents in noisy conditions or in situations where the audio signal is not available. The primary advantage of visual information is that it is not affected by the acoustic noise and cross talk among speakers. Using visual information from the lip movements can improve the accuracy and robustness of automatic speech recognition. However, a major challenge with most automatic lip reading system is to find a robust and efficient method for extracting the linguistically relevant speech information from a lip image sequence. This is a difficult task due to variation caused by different speakers, illumination, camera setting and the inherent low luminance and chrominance contrast between lip and non-lip region. Several researchers have been developing methods to overcome these problems; the one is lip reading. Moreover, it is well known that visual information about speech through lip reading is very useful for human speech recognition system. Lip reading is the technique of a comprehensive understanding of underlying speech by processing on the movement of lips. Therefore, lip reading system is one of the different supportive technologies for hearing impaired or elderly people, and it is an active research area. The need for lip reading system is ever increasing for every language. This research aims to develop a visual teaching method system for the hearing impaired persons in Myanmar, how to pronounce words precisely by identifying the features of lip movement. The proposed research will work a lip reading system for Myanmar Consonants, one syllable consonants (င (Nga)၊ ည (Nya)၊ မ (Ma)၊ လ (La)၊ ၀ (Wa)၊ သ (Tha)၊ ဟ (Ha)၊ အ (Ah) ) and two syllable consonants ( က(Ka Gyi)၊ ခ (Kha Gway)၊ ဂ (Ga Nge)၊ ဃ (Ga Gyi)၊ စ (Sa Lone)၊ ဆ (Sa Lain)၊ ဇ (Za Gwe) ၊ ဒ (Da Dway)၊ ဏ (Na Gyi)၊ န (Na Nge)၊ ပ (Pa Saug)၊ ဘ (Ba Gone)၊ ရ (Ya Gaug)၊ ဠ (La Gyi) ). In the proposed system, there are three subsystems, the first one is the lip localization system, which localizes the lips in the digital inputs. The next one is the feature extraction system, which extracts features of lip movement suitable for visual speech recognition. And the final one is the classification system. In the proposed research, Two Dimensional Discrete Cosine Transform (2D-DCT) and Linear Discriminant Analysis (LDA) with Active Contour Model (ACM) will be used for lip movement features extraction. Support Vector Machine (SVM) classifier is used for finding class parameter and class number in training set and testing set. Then, experiments will be carried out for the recognition accuracy of Myanmar consonants using the only visual information on lip movements which are useful for visual speech of Myanmar languages. The result will show the effectiveness of the lip movement recognition for Myanmar Consonants. This system will help the hearing impaired persons to use as the language learning application. This system can also be useful for normal hearing persons in noisy environments or conditions where they can find out what was said by other people without hearing voice.

Keywords: feature extraction, lip reading, lip localization, Active Contour Model (ACM), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Two Dimensional Discrete Cosine Transform (2D-DCT)

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Authors: Sophio Kobauri, Temur Kantaria, Nina Kulikova, David Tugushi, Ramaz Katsarava

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The elaboration of effective drug delivery vehicles is still topical nowadays since targeted drug delivery is one of the most important challenges of the modern nanomedicine. The last decade has witnessed enormous research focused on synthetic cationic polymers (CPs) due to their flexible properties, in particular as non-viral gene delivery systems, facile synthesis, robustness, not oncogenic and proven gene delivery efficiency. However, the toxicity is still an obstacle to the application in pharmacotherapy. For overcoming the problem, creation of new cationic compounds including the polymeric nano-size particles – nano-containers (NCs) loading with different pharmaceuticals and biologicals is still relevant. In this regard, a variety of NCs-based drug delivery systems have been developed. We have found that amino acid-based biodegradable polymers called as pseudo-proteins (PPs), which can be cleared from the body after the fulfillment of their function are highly suitable for designing pharmaceutical NCs. Among them, one of the most promising are NCs made of biodegradable Cationic PPs (CPPs). For preparing new cationic NCs (CNCs), we used CPPs composed of positively charged amino acid L-arginine (R). The CNCs were fabricated by two approaches using: (1) R-based homo-CPPs; (2) Blends of R-based CPPs with regular (neutral) PPs. According to the first approach NCs we prepared from CPPs 8R3 (composed of R, sebacic acid and 1,3-propanediol) and 8R6 (composed of R, sebacic acid and 1,6-hexanediol). The NCs prepared from these CPPs were 72-101 nm in size with zeta potential within +30 ÷ +35 mV at a concentration 6 mg/mL. According to the second approach, CPPs 8R6 was blended in organic phase with neutral PPs 8L6 (composed of leucine, sebacic acid and 1,6-hexanediol). The NCs prepared from the blends were 130-140 nm in size with zeta potential within +20 ÷ +28 mV depending on 8R6/8L6 ratio. The stability studies of fabricated NCs showed that no substantial change of the particle size and distribution and no big particles’ formation is observed after three months storage. In vitro biocompatibility study of the obtained NPs with four different stable cell lines: A549 (human), U-937 (human), RAW264.7 (murine), Hepa 1-6 (murine) showed both type cathionic NCs are biocompatible. The obtained data allow concluding that the obtained CNCs are promising for the application as biodegradable drug delivery vehicles. This work was supported by the joint grant from the Science and Technology Center in Ukraine and Shota Rustaveli National Science Foundation of Georgia #6298 'New biodegradable cationic polymers composed of arginine and spermine-versatile biomaterials for various biomedical applications'.

Keywords: biodegradable polymers, cationic pseudo-proteins, nano-containers, drug delivery vehicles

Procedia PDF Downloads 128

Authors: Martin Pellon Consunji

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Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

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Authors: M. Qamarul Islam, Ergun Dogan, Mehmet Yazici

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There is a growing body of evidence that non-normal data is more prevalent in nature than the normal one. Examples can be quoted from, but not restricted to, the areas of Economics, Finance and Actuarial Science. The non-normality considered here is expressed in terms of fat-tailedness and asymmetry of the relevant distribution. In this study a skew t distribution that can be used to model a data that exhibit inherent non-normal behavior is considered. This distribution has tails fatter than a normal distribution and it also exhibits skewness. Although maximum likelihood estimates can be obtained by solving iteratively the likelihood equations that are non-linear in form, this can be problematic in terms of convergence and in many other respects as well. Therefore, it is preferred to use the method of modified maximum likelihood in which the likelihood estimates are derived by expressing the intractable non-linear likelihood equations in terms of standardized ordered variates and replacing the intractable terms by their linear approximations obtained from the first two terms of a Taylor series expansion about the quantiles of the distribution. These estimates, called modified maximum likelihood estimates, are obtained in closed form. Hence, they are easy to compute and to manipulate analytically. In fact the modified maximum likelihood estimates are equivalent to maximum likelihood estimates, asymptotically. Even in small samples the modified maximum likelihood estimates are found to be approximately the same as maximum likelihood estimates that are obtained iteratively. It is shown in this study that the modified maximum likelihood estimates are not only unbiased but substantially more efficient than the commonly used moment estimates or the least square estimates that are known to be biased and inefficient in such cases. Furthermore, in conventional regression analysis, it is assumed that the error terms are distributed normally and, hence, the well-known least square method is considered to be a suitable and preferred method for making the relevant statistical inferences. However, a number of empirical researches have shown that non-normal errors are more prevalent. Even transforming and/or filtering techniques may not produce normally distributed residuals. Here, a study is done for multiple linear regression models with random error having non-normal pattern. Through an extensive simulation it is shown that the modified maximum likelihood estimates of regression parameters are plausibly robust to the distributional assumptions and to various data anomalies as compared to the widely used least square estimates. Relevant tests of hypothesis are developed and are explored for desirable properties in terms of their size and power. The tests based upon modified maximum likelihood estimates are found to be substantially more powerful than the tests based upon least square estimates. Several examples are provided from the areas of Economics and Finance where such distributions are interpretable in terms of efficient market hypothesis with respect to asset pricing, portfolio selection, risk measurement and capital allocation, etc.

Keywords: least square estimates, linear regression, maximum likelihood estimates, modified maximum likelihood method, non-normality, robustness

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Authors: Pedro Felgueiras, Ana Miguel, Nélson Almeida, Raquel Silva

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Objective: Through the study of a clinical case of delusional somatic disorder secondary to phantogeusia, we aim to highlight the importance of considering psychosomatic conditions in differential diagnosis, as well as to emphasize the complexity of its comprehension, treatment, and respective impact on patients’ functioning. Methods: Bearing this in mind, we conducted a critical analysis of a case series based on patient observations, clinical data, and complementary diagnostic methods, as well as a non-systematic review of the literature on the subject. Results: A 61-year-old female patient with no history of psychiatric conditions. Family psychiatric history of mood disorder (depression), with psychotic features found in her mother. Medical history of many comorbidities affecting different organ systems (endocrine, gastrointestinal, genitourinary, ophthalmological). Documented neuroticism traits of personality. The patient’s family described a persistent concern about several physical symptoms across her life, with a continuous effort to obtain explanations about any sensation out of her normal perception. Since being subjected to endoscopy in 2018, she started complaints of persistent phantogeusia (acid taste) and developed excessive thoughts, feelings, and behaviors associated with this somatic symptom. The patient was evaluated by several medical specialties, and an extensive panel of medical exams was carried out, excluding any disease. Besides all the investigation and with no evidence of disease signs, acute anxiety, time, and energy dispended to this symptom culminated in severe psychosocial impairment. The patient was admitted to a psychiatric ward for investigation and treatment of this clinical picture, leading to the diagnosis of the delusional somatic disorder. In order to exclude the acute organic etiology of this psychotic disorder, an analytic panel was carried out with no abnormal results. In the context of a psychotic clinical picture, a CT scan was performed, which revealed a right cortical vascular lesion. Neuropsychological evaluation was made, with the description of cognitive functioning being globally normative. During treatment with an antipsychotic (pimozide), a complete remission of the somatic delusion was associated with the disappearance of gustative perception disturbance. In follow-up, a relapse of gustative sensation was documented, and her thoughts and speech were dominated by concerns about multiple somatic symptoms. Conclusion: In terms of abnormal bodily sensations, the oral cavity is one of the frequent sites of delusional disorder. Patients with these gustatory perception distortions complain about unusual sensations without corresponding abnormal findings in the oral area. Its pathophysiology has not been fully elucidated yet. In terms of its comprehensive psychopathology, this case was hypothesized as a paranoid development of a delusional somatic disorder triggered by a post-invasive procedure phantogeusia (which is described as a possible side effect of an endoscopy) in a patient with an anankastic personality. This case presents interesting psychopathology, reinforcing the complexity of psychosomatic disorders in terms of their etiopathogenesis, clinical treatment, and long-term prognosis.

Keywords: psychosomatics, delusional somatic disorder, phantogeusia, paranoid development

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Authors: Omer Zvi Shaked, Amir Tirosh

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Type 1 Diabetes (T1DM) is an incurable chronic illness with no known preventive measures. Excess to insulin therapy can lead to hypoglycemia with neuro-glycogenic symptoms such as shakiness, nausea, sweating, irritability, fatigue, excessive thirst or hunger, weakness, seizure, and coma. Severe Hypoglycemia (SH) is also considered a most aversive event since it may put patients at risk for injury and death, which matches the criteria of a traumatic event. SH has a ranging prevalence of 20%, which makes it a primary medical Issue. One of the results of SH is an intense emotional fear reaction resembling the form of post-traumatic stress symptoms (PTS), causing many patients to avoid insulin therapy and social activities in order to avoid the possibility of hypoglycemia. As a result, they are at risk for irreversible health deterioration and medical complications. Fear of Hypoglycemia (FOH) is, therefore, a major disturbance for T1DM patients. FOH differs from prevalent post-traumatic stress reactions to other forms of traumatic events since the threat to life continuously exists in the patient's body. That is, it is highly probable that orthodox interventions may not be sufficient for helping patients after SH to regain healthy social function and proper medical treatment. Accordingly, the current presentation will demonstrate the results of a study conducted among T1DM patients after SH. The study was designed in two stages. First, a preliminary qualitative phenomenological study among ten patients after SH was conducted. Analysis revealed that after SH, patients confuse between stress symptoms and Hypoglycemia symptoms, divide life before and after the event, report a constant sense of fear, a loss of freedom, a significant decrease in social functioning, a catastrophic thinking pattern, a dichotomous split between the self and the body, and internalization of illness identity, a loss of internal locus of control, a damaged self-representation, and severe loneliness for never being understood by others. The second stage was a two steps study of intervention among five patients after SH. The first part of the intervention included three months of therapeutic 3rd wave CBT therapy. The contents of the therapeutic process were: acceptance of fear and tolerance to stress; cognitive de-fusion combined with emotional self-regulation; the adoption of an active position relying on personal values; and self-compassion. Then, the intervention included a one-week practical real-time 24/7 support by trained medical personnel, alongside a gradual exposure to increased insulin therapy in a protected environment. The results of the intervention are a decrease in stress symptoms, increased social functioning, increased well-being, and decreased avoidance of medical treatment. The presentation will discuss the unique emotional state of T1DM patients after SH. Then, the presentation will discuss the effectiveness of the intervention for patients with chronic conditions after a traumatic event. The presentation will make evident the unique situation of illness-related PTSD. The presentation will also demonstrate the requirement for multi-professional collaboration between social work and medical care for populations with chronic medical conditions. Limitations of the study and recommendations for further research will be discussed.

Keywords: type 1 diabetes, chronic illness, post-traumatic stress, illness-related PTSD

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Authors: Bikash Ranjan Mishra, Lopamudra D. Satpathy

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In the wake of the phenomenal surge in international business in the last decades or more, both the developed and developing economies around the world are in massive competition to attract more and more FDI flows. While the developed countries have marched ahead in the race, the developing countries, especially those of Asian economies, have followed them at a rapid pace. While most of the previous studies have analysed the role of institutional quality in the promotion of FDI flows in developing countries, very few studies have taken an integrated approach of examining the comprehensive impact of institutional quality, globalization pattern and domestic financial development on FDI flows. In this context, the paper contributes to the literature in two important ways. Firstly, two composite indices of institutional quality and domestic financial development for the Asian countries are constructed in comparison to earlier studies that resort to a single variable for indicating the institutional quality and domestic financial development. Secondly, the impact of these variables on FDI flows through their interaction with geographical region is investigated. The study uses panel data covering the time period of 1996 to 2012 by selecting twenty Asian developing countries by emphasizing the quality of institutions from the geographical regions of eastern, south-eastern, southern and western Asia. Control of corruption, better rule of law, regulatory quality, effectiveness of the government, political stability and voice and accountability are used as indicators of institutional quality. Besides these, the study takes into account the domestic credits in the hands of public, private sectors and in stock markets as domestic financial indicators. First in the specification of model, a factor analysis is performed to reduce the vast determinants, which are highly correlated with each other, to a manageable size. Afterwards, a reduced version of the model is estimated with the extracted factors in the form of index as independent variables along with a set of control variables. It is found that the institutional quality index and index of globalization exert a significant effect on FDI inflows of the host countries; in contrast, the domestic financial index does not seem to play much worthy role. Finally, some robustness tests are performed to make sure that the results are not sensitive to temporal and spatial unobserved heterogeneity. On the basis of the above study, one general inference can be drawn from the policy prescription point of view that the government of these developing countries should strengthen their domestic institution, both financial and non-financial. In addition to these, welfare policies should also target for rapid globalization. If the financial and non-financial institutions of these developing countries become sound and grow more globalized in the economic, social and political domain, then they can appeal to more amounts of FDI inflows that will subsequently result in advancement of these economies.

Keywords: Asian developing economies, FDI, institutional quality, panel data

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Authors: D. Madhushanka, Y. Liu, H. C. Fernando

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Fires are one of the foremost factors of land surface disturbance in diverse ecosystems, causing soil erosion and land-cover changes and atmospheric effects affecting people's lives and properties. Generally, the severity of the fire is calculated as the Normalized Burn Ratio (NBR) index. This is performed manually by comparing two images obtained afterward. Then by using the bitemporal difference of the preprocessed satellite images, the dNBR is calculated. The burnt area is then classified as either unburnt (dNBR<0.1) or burnt (dNBR>= 0.1). Furthermore, Wildfire Severity Assessment (WSA) classifies burnt areas and unburnt areas using classification levels proposed by USGS and comprises seven classes. This procedure generates a burn severity report for the area chosen by the user manually. This study is carried out with the objective of producing an automated tool for the above-mentioned process, namely the World Wildfire Severity Assessment Tool (WWSAT). It is implemented in Google Earth Engine (GEE), which is a free cloud-computing platform for satellite data processing, with several data catalogs at different resolutions (notably Landsat, Sentinel-2, and MODIS) and planetary-scale analysis capabilities. Sentinel-2 MSI is chosen to obtain regular processes related to burnt area severity mapping using a medium spatial resolution sensor (15m). This tool uses machine learning classification techniques to identify burnt areas using NBR and to classify their severity over the user-selected extent and period automatically. Cloud coverage is one of the biggest concerns when fire severity mapping is performed. In WWSAT based on GEE, we present a fully automatic workflow to aggregate cloud-free Sentinel-2 images for both pre-fire and post-fire image compositing. The parallel processing capabilities and preloaded geospatial datasets of GEE facilitated the production of this tool. This tool consists of a Graphical User Interface (GUI) to make it user-friendly. The advantage of this tool is the ability to obtain burn area severity over a large extent and more extended temporal periods. Two case studies were carried out to demonstrate the performance of this tool. The Blue Mountain national park forest affected by the Australian fire season between 2019 and 2020 is used to describe the workflow of the WWSAT. This site detected more than 7809 km2, using Sentinel-2 data, giving an error below 6.5% when compared with the area detected on the field. Furthermore, 86.77% of the detected area was recognized as fully burnt out, of which high severity (17.29%), moderate-high severity (19.63%), moderate-low severity (22.35%), and low severity (27.51%). The Arapaho and Roosevelt National Forest Park, California, the USA, which is affected by the Cameron peak fire in 2020, is chosen for the second case study. It was found that around 983 km2 had burned out, of which high severity (2.73%), moderate-high severity (1.57%), moderate-low severity (1.18%), and low severity (5.45%). These spots also can be detected through the visual inspection made possible by cloud-free images generated by WWSAT. This tool is cost-effective in calculating the burnt area since satellite images are free and the cost of field surveys is avoided.

Keywords: burnt area, burnt severity, fires, google earth engine (GEE), sentinel-2

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Authors: Zuzana Tatarkova, Ivana Pilchova, Michal Cibulka, Martin Kolisek, Peter Racay, Peter Kaplan

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Introduction: Normal functioning of mitochondria is crucial for cardiac performance. Mitochondria undergo mitophagy and biogenesis, and mitochondrial proteins are subject to extensive post-translational modifications. The state of mitochondrial homeostasis reflects overall cellular fitness and longevity. Perturbed mitochondria produce less ATP, release greater amounts of reactive molecules, and are more prone to apoptosis. Therefore mitochondrial turnover is an integral aspect of quality control in which dysfunctional mitochondria are selectively eliminated through mitophagy. Currently, the progressive deterioration of physiological functions is seen as accumulation of modified/damaged proteins with limiting regenerative ability and disturbance of such affected protein-protein communication throughout aging in myocardial cells. Methodologies: For our study was used immunohistochemistry, biochemical methods: spectrophotometry, western blotting, immunodetection as well as more sophisticated 2D electrophoresis and mass spectrometry for evaluation protein-protein interactions and specific post-translational modification. Results and Discussion: Mitochondrial stress response to reactive species was evaluated as electron transport chain (ETC) complexes, redox-active molecules, and their possible communication. Protein-protein interactions revealed a strong linkage between age and ETC protein subunits. Redox state was strongly affected in senescent mitochondria with shift in favor of more pro-oxidizing condition within cardiomyocytes. Acute myocardial ischemia and ischemia-reperfusion (IR) injury affected ETC complexes I, II and IV with no change in complex III. Ischemia induced decrease in total antioxidant capacity, MnSOD, GSH and catalase activity with recovery in some extent during reperfusion. While MnSOD protein content was higher in IR group, activity returned to 95% of control. Nitric oxide is one of the biological molecules that can out compete MnSOD for superoxide and produce peroxynitrite. This process is faster than dismutation and led to the 10-fold higher production of nitrotyrosine after IR injury in adult with higher protection in senescent ones. 2D protein profiling revealed 140 mitochondrial proteins, 12 of them with significant changes after IR injury and 36 individual nitrotyrosine-modified proteins further identified by mass spectrometry. Linking these two groups, 5 proteins were altered after IR as well as nitrated, but only one showed massive nitration per lowering content of protein after IR injury in adult. Conclusions: Senescent cells have greater proportion of protein content, which might be modulated by several post-translational modifications. If these protein modifications are connected to functional consequences and protein-protein interactions are revealed, link may lead to the solution. Assume all together, dysfunctional proteostasis can play a causative role and restoration of protein homeostasis machinery is protective against aging and possibly age-related disorders. This work was supported by the project VEGA 1/0018/18 and by project 'Competence Center for Research and Development in the field of Diagnostics and Therapy of Oncological diseases', ITMS: 26220220153, co-financed from EU sources.

Keywords: aging heart, mitochondria, proteomics, redox state

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: Amal Balila, Maria Vahdati

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Earth is a green building material with very low embodied energy and almost zero greenhouse gas emissions. However, it lacks strength and durability in its natural state. By responsibly sourcing stabilisers, it's possible to enhance its strength. This research draws inspiration from the robustness of termite mounds, where termites incorporate glycoproteins from their saliva during construction. Biomimicry explores the potential of these termite stabilisers in producing bio-inspired adobe bricks. The meat industry generates significant waste during slaughter, including blood, skin, bones, tendons, gastrointestinal contents, and internal organs. While abundant, many meat by-products raise concerns regarding human consumption, religious orders, cultural and ethical beliefs, and also heavily contribute to environmental pollution. Extracting and utilising proteins from this waste is vital for reducing pollution and increasing profitability. Exploring the untapped potential of meat industry waste, this research investigates how glycoproteins could revolutionize adobe brick construction. Bovine serum albumin (BSA) from cows' blood and mucin from porcine stomachs were the chosen glycoproteins used as stabilisers for adobe brick production. Despite their wide usage across various fields, they have very limited utilisation in food processing. Thus, both were identified as potential stabilisers for adobe brick production in this study. Two soil types were utilised to prepare adobe bricks for testing, comparing controlled unstabilised bricks with glycoprotein-stabilised ones. All bricks underwent testing for unconfined compressive strength and erosion resistance. The primary finding of this study is the efficacy of BSA, a glycoprotein derived from cows' blood and a by-product of the beef industry, as an earth construction stabiliser. Adding 0.5% by weight of BSA resulted in a 17% and 41% increase in the unconfined compressive strength for British and Sudanese adobe bricks, respectively. Further, adding 5% by weight of BSA led to a 202% and 97% increase in the unconfined compressive strength for British and Sudanese adobe bricks, respectively. Moreover, using 0.1%, 0.2%, and 0.5% by weight of BSA resulted in erosion rate reductions of 30%, 48%, and 70% for British adobe bricks, respectively, with a 97% reduction observed for Sudanese adobe bricks at 0.5% by weight of BSA. However, mucin from the porcine stomach did not significantly improve the unconfined compressive strength of adobe bricks. Nevertheless, employing 0.1% and 0.2% by weight of mucin resulted in erosion rate reductions of 28% and 55% for British adobe bricks, respectively. These findings underscore BSA's efficiency as an earth construction stabiliser for wall construction and mucin's efficacy for wall render, showcasing their potential for sustainable and durable building practices.

Keywords: biomimicry, earth construction, industrial waste management, sustainable building materials, termite mounds.

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Authors: Simon Grossemy, Peggy P. Y. Chan, Pauline M. Doran

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Nerve tissue engineering is the main field of research aimed at finding an alternative to autografts as a treatment for nerve injuries. Scaffolds are used as a support to enhance nerve regeneration. In order to successfully design novel scaffolds and in vitro cell culture systems, a deep understanding of the factors affecting nerve regeneration processes is needed. Physical and biological parameters associated with the culture environment have been identified as potentially influential in nerve cell differentiation, including electrical stimulation, exposure to extracellular-matrix (ECM) proteins, dynamic medium conditions and co-culture with glial cells. The mechanisms involved in driving the cell to differentiation in the presence of these factors are poorly understood; the complexity of each of them raises the possibility that they may strongly influence each other. Some questions that arise in investigating nerve regeneration include: What are the best protein coatings to promote neural cell attachment? Is the scaffold design suitable for providing all the required factors combined? What is the influence of dynamic stimulation on cell viability and differentiation? In order to study these effects, scaffolds adaptable to bioreactor culture conditions were designed to allow electrical stimulation of cells exposed to ECM proteins, all within a dynamic medium environment. Gold coatings were used to make the surface of viscose rayon microfiber scaffolds (VRMS) conductive, and poly-L-lysine (PLL) and laminin (LN) surface coatings were used to mimic the ECM environment and allow the attachment of rat PC12 neural cells. The robustness of the coatings was analyzed by surface resistivity measurements, scanning electron microscope (SEM) observation and immunocytochemistry. Cell attachment to protein coatings of PLL, LN and PLL+LN was studied using DNA quantification with Hoechst. The double coating of PLL+LN was selected based on high levels of PC12 cell attachment and the reported advantages of laminin for neural differentiation. The underlying gold coatings were shown to be biocompatible using cell proliferation and live/dead staining assays. Coatings exhibiting stable properties over time under dynamic fluid conditions were developed; indeed, cell attachment and the conductive power of the scaffolds were maintained over 2 weeks of bioreactor operation. These scaffolds are promising research tools for understanding complex neural cell behavior. They have been used to investigate major factors in the physical culture environment that affect nerve cell viability and differentiation, including electrical stimulation, bioreactor hydrodynamic conditions, and combinations of these parameters. The cell and tissue differentiation response was evaluated using DNA quantification, immunocytochemistry, RT-qPCR and functional analyses.

Keywords: bioreactor, electrical stimulation, nerve differentiation, PC12 cells, scaffold

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Authors: Eva Masson, Andrea Kübler

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Anxiety disorders (AD) are the most prevalent psychological disorders. However, far from most affected individuals are diagnosed and receive treatment. This gap is probably due to the diagnosis criteria, relying on symptoms (according to the DSM-5 definition) with no objective biomarker. Approach-avoidance conflict tasks are one common approach to simulate such disorders in a lab setting, with most of the paradigms focusing on the relationships between behavior and neurophysiology. Approach-avoidance conflict tasks typically place participants in a situation where they have to make a decision that leads to both positive and negative outcomes, thereby sending conflicting signals that trigger the Behavioral Inhibition System (BIS). Furthermore, behavioral validation of such paradigms adds credibility to the tasks – with overt conflict behavior, it is safer to assume that the task actually induced a conflict. Some of those tasks have linked asymmetrical frontal brain activity to induced conflicts and the BIS. However, there is currently no consensus for the direction of the frontal activation. The authors present here a modified version of the T-Maze paradigm, a motivational conflict desktop task, in which behavior is recorded simultaneously to the recording of high-density EEG (HD-EEG). Methods: In this within-subject design, HD-EEG and behavior of 35 healthy participants was recorded. EEG data was collected with a 128 channels sponge-based system. The motivational conflict desktop task consisted of three blocks of repeated trials. Each block was designed to record a slightly different behavioral pattern, to increase the chances of eliciting conflict. This variety of behavioral patterns was however similar enough to allow comparison of the number of trials categorized as ‘overt conflict’ between the blocks. Results: Overt conflict behavior was exhibited in all blocks, but always for under 10% of the trials, in average, in each block. However, changing the order of the paradigms successfully introduced a ‘reset’ of the conflict process, therefore providing more trials for analysis. As for the EEG correlates, the authors expect a different pattern for trials categorized as conflict, compared to the other ones. More specifically, we expect an elevated alpha frequency power in the left frontal electrodes at around 200ms post-cueing, compared to the right one (relative higher right frontal activity), followed by an inversion around 600ms later. Conclusion: With this comprehensive approach of a psychological mechanism, new evidence would be brought to the frontal asymmetry discussion, and its relationship with the BIS. Furthermore, with the present task focusing on a very particular type of motivational approach-avoidance conflict, it would open the door to further variations of the paradigm to introduce different kinds of conflicts involved in AD. Even though its application as a potential biomarker sounds difficult, because of the individual reliability of both the task and peak frequency in the alpha range, we hope to open the discussion for task robustness for neuromodulation and neurofeedback future applications.

Keywords: anxiety, approach-avoidance conflict, behavioral inhibition system, EEG

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Authors: Jacqueline Y. Thompson, Sam Watson, Lee Middleton, Karla Hemming

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Introduction: The odds ratio (estimated via logistic regression) is a well-established and common approach for estimating covariate-adjusted binary treatment effects when comparing a treatment and control group with dichotomous outcomes. Its popularity is primarily because of its stability and robustness to model misspecification. However, the situation is different for the relative risk and risk difference, which are arguably easier to interpret and better suited to specific designs such as non-inferiority studies. So far, there is no equivalent, widely acceptable approach to estimate an adjusted relative risk and risk difference when conducting clinical trials. This is partly due to the lack of a comprehensive evaluation of available candidate methods. Methods/Approach: A simulation study is designed to evaluate the performance of relevant candidate methods to estimate relative risks to represent conditional and marginal estimation approaches. We consider the log-binomial, generalised linear models (GLM) with iteratively weighted least-squares (IWLS) and model-based standard errors (SE); log-binomial GLM with convex optimisation and model-based SEs; log-binomial GLM with convex optimisation and permutation tests; modified-Poisson GLM IWLS and robust SEs; log-binomial generalised estimation equations (GEE) and robust SEs; marginal standardisation and delta method SEs; and marginal standardisation and permutation test SEs. Independent and identically distributed datasets are simulated from a randomised controlled trial to evaluate these candidate methods. Simulations are replicated 10000 times for each scenario across all possible combinations of sample sizes (200, 1000, and 5000), outcomes (10%, 50%, and 80%), and covariates (ranging from -0.05 to 0.7) representing weak, moderate or strong relationships. Treatment effects (ranging from 0, -0.5, 1; on the log-scale) will consider null (H0) and alternative (H1) hypotheses to evaluate coverage and power in realistic scenarios. Performance measures (bias, mean square error (MSE), relative efficiency, and convergence rates) are evaluated across scenarios covering a range of sample sizes, event rates, covariate prognostic strength, and model misspecifications. Potential Results, Relevance & Impact: There are several methods for estimating unadjusted and adjusted relative risks. However, it is unclear which method(s) is the most efficient, preserves type-I error rate, is robust to model misspecification, or is the most powerful when adjusting for non-prognostic and prognostic covariates. GEE estimations may be biased when the outcome distributions are not from marginal binary data. Also, it seems that marginal standardisation and convex optimisation may perform better than GLM IWLS log-binomial.

Keywords: binary outcomes, statistical methods, clinical trials, simulation study

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Authors: Soumava Boral, Sanjay K. Chaturvedi, Ian Howard, Kristoffer McKee, V. N. A. Naikan

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Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach.

Keywords: Fermatean fuzzy sets, Fermatean fuzzy MAIRCA, maintenance strategy selection, sustainable manufacturing, MCDM

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Authors: A. Saravanan, B. R. Huang, C. J. Yeh, K. C. Leou, I. N. Lin

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A new class of ultra-nano diamond-graphite nano-hybrid (DGH) composite materials containing nano-sized diamond needles was developed at low temperature process. Such kind of diamond- graphite nano-hybrid composite nanowires exhibit high electrical conductivity and excellent electron field emission (EFE) properties. Few earlier reports mention that addition of N2 gas to the growth plasma requires high growth temperature (800°C) to trigger the dopants to generate the conductivity in the films. High growth temperature is not familiar with the Si-based device fabrications. We have used a novel process such as bias-enhanced-grown (beg) MPECVD process to grow diamond films at low substrate temperature (450°C). We observed that the beg-N/UNCD films thus obtained possess high conductivity of σ=987 S/cm, ever reported for diamond films with excellent Electron field emission (EFE) properties. TEM investigation indicated that these films contain needle-like diamond grains about 5 nm in diameter and hundreds of nanometers in length. Each of the grains was encased in graphitic layers about tens of nano-meters in thickness. These materials properties suitable for more specific applications, such as high conductivity for electron field emitters, high robustness for microplasma cathodes and high electrochemical activity for electro-chemical sensing. Subsequently, other hand, the highly conducting DGH films were coated on vertically aligned ZnO nanorods, there is no prior nucleation or seeding process needed due to the use of BEG method. Such a composite structure provides significant enhancement in the field emission characteristics of the cold cathode was observed with ultralow turn on voltage 1.78 V/μm with high EFE current density of 3.68 mA/ cm2 (at 4.06V/μm) due to decoration of DGH material on ZnO nanorods. The DGH/ZNRs based device get stable emission for longer duration of 562min than bare ZNRs (104min) without any current degradation because the diamond coating protects the ZNRs from ion bombardment when they are used as the cathode for microplasma devices. The potential application of these materials is demonstrated by the plasma illumination measurements that ignited the plasma at the minimum voltage by 290 V. The photoresponse (Iphoto/Idark) behavior of the DGH/ZNRs based photodetectors exhibits a much higher photoresponse (1202) than bare ZNRs (229). During the process the electron transport is easy from ZNRs to DGH through graphitic layers, the EFE properties of these materials comparable to other primarily used field emitters like carbon nanotubes, graphene. The DGH/ZNRs composite also providing a possibility of their use in flat panel, microplasma and vacuum microelectronic devices.

Keywords: bias-enhanced nucleation and growth, ZnO nanorods, electrical conductivity, electron field emission, photo-detectors

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Authors: Yan Torres, Fernanda Simoes, Francisco Petrucci-Fonseca, Freddie-Jeanne Richard

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The non-invasive samples are an alternative of collecting genetic samples directly. Non-invasive samples are collected without the manipulation of the animal (e.g., scats, feathers and hairs). Nevertheless, the use of non-invasive samples has some limitations. The main issue is degraded DNA, leading to poorer extraction efficiency and genotyping. Those errors delayed for some years a widespread use of non-invasive genetic information. Possibilities to limit genotyping errors can be done using analysis methods that can assimilate the errors and singularities of non-invasive samples. Genotype matching and population estimation algorithms can be highlighted as important analysis tools that have been adapted to deal with those errors. Although, this recent development of analysis methods there is still a lack of empirical performance comparison of them. A comparison of methods with dataset different in size and structure can be useful for future studies since non-invasive samples are a powerful tool for getting information specially for endangered and rare populations. To compare the analysis methods, four different datasets used were obtained from the Dryad digital repository were used. Three different matching algorithms (Cervus, Colony and Error Tolerant Likelihood Matching - ETLM) are used for matching genotypes and two different ones for population estimation (Capwire and BayesN). The three matching algorithms showed different patterns of results. The ETLM produced less number of unique individuals and recaptures. A similarity in the matched genotypes between Colony and Cervus was observed. That is not a surprise since the similarity between those methods on the likelihood pairwise and clustering algorithms. The matching of ETLM showed almost no similarity with the genotypes that were matched with the other methods. The different cluster algorithm system and error model of ETLM seems to lead to a more criterious selection, although the processing time and interface friendly of ETLM were the worst between the compared methods. The population estimators performed differently regarding the datasets. There was a consensus between the different estimators only for the one dataset. The BayesN showed higher and lower estimations when compared with Capwire. The BayesN does not consider the total number of recaptures like Capwire only the recapture events. So, this makes the estimator sensitive to data heterogeneity. Heterogeneity in the sense means different capture rates between individuals. In those examples, the tolerance for homogeneity seems to be crucial for BayesN work properly. Both methods are user-friendly and have reasonable processing time. An amplified analysis with simulated genotype data can clarify the sensibility of the algorithms. The present comparison of the matching methods indicates that Colony seems to be more appropriated for general use considering a time/interface/robustness balance. The heterogeneity of the recaptures affected strongly the BayesN estimations, leading to over and underestimations population numbers. Capwire is then advisable to general use since it performs better in a wide range of situations.

Keywords: algorithms, genetics, matching, population

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Authors: Saul Estrin, Ute Stephan, Suncica Vujic

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Background and research question: Gender differences in pay are present at all organisational levels, including at the very top. One possible way for women to circumvent organizational norms and discrimination is to engage in entrepreneurship because, as CEOs of their own organizations, entrepreneurs largely determine their own pay. While commercial entrepreneurship plays an important role in job creation and economic growth, social entrepreneurship has come to prominence because of its promise of addressing societal challenges such as poverty, social exclusion, or environmental degradation through market-based rather than state-sponsored activities. This opens the research question whether social entrepreneurship might be a form of entrepreneurship in which the pay of men and women is the same, or at least more similar; that is to say there is little or no gender pay gap. If the gender gap in pay persists also at the top of social enterprises, what are the factors, which might explain these differences? Methodology: The Oaxaca-Blinder Decomposition (OBD) is the standard approach of decomposing the gender pay gap based on the linear regression model. The OBD divides the gender pay gap into the ‘explained’ part due to differences in labour market characteristics (education, work experience, tenure, etc.), and the ‘unexplained’ part due to differences in the returns to those characteristics. The latter part is often interpreted as ‘discrimination’. There are two issues with this approach. (i) In many countries there is a notable convergence in labour market characteristics across genders; hence the OBD method is no longer revealing, since the largest portion of the gap remains ‘unexplained’. (ii) Adding covariates to a base model sequentially either to test a particular coefficient’s ‘robustness’ or to account for the ‘effects’ on this coefficient of adding covariates might be problematic, due to sequence-sensitivity when added covariates are correlated. Gelbach’s decomposition (GD) addresses latter by using the omitted variables bias formula, which constructs a conditional decomposition thus accounting for sequence-sensitivity when added covariates are correlated. We use GD to decompose the differences in gaps of pay (annual and hourly salary), size of the organisation (revenues), effort (weekly hours of work), and sources of finances (fees and sales, grants and donations, microfinance and loans, and investors’ capital) between men and women leading social enterprises. Database: Our empirical work is made possible by our collection of a unique dataset using respondent driven sampling (RDS) methods to address the problem that there is as yet no information on the underlying population of social entrepreneurs. The countries that we focus on are the United Kingdom, Spain, Romania and Hungary. Findings and recommendations: We confirm the existence of a gender pay gap between men and women leading social enterprises. This gap can be explained by differences in the accumulation of human capital, psychological and social factors, as well as cross-country differences. The results of this study contribute to a more rounded perspective, highlighting that although social entrepreneurship may be a highly satisfying occupation, it also perpetuates gender pay inequalities.

Keywords: Gelbach’s decomposition, gender gap, returns to social entrepreneurship, values and preferences

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Authors: Alessandro Balbo, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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Hydrogen is expected to become an undisputed player in the ecological transition throughout the next decades. The decarbonization potential offered by this energy vector provides various opportunities for the so-called “hard-to-abate” sectors, including industrial production of iron and steel, glass, refineries and the heavy-duty transport. In this regard, Italy, in the framework of decarbonization plans for the whole European Union, has been considering a wider use of hydrogen to provide an alternative to fossil fuels in hard-to-abate sectors. This work aims to assess and compare different options concerning the pathway to be followed in the development of the future Italian energy system in order to meet decarbonization targets as established by the Paris Agreement and by the European Green Deal, and to infer a techno-economic analysis of the required asset alternatives to be used in that perspective. To accomplish this objective, the Energy System Optimization Model TEMOA-Italy is used, based on the open-source platform TEMOA and developed at PoliTo as a tool to be used for technology assessment and energy scenario analysis. The adopted assessment strategy includes two different scenarios to be compared with a business-as-usual one, which considers the application of current policies in a time horizon up to 2050. The studied scenarios are based on the up-to-date hydrogen-related targets and planned investments included in the National Hydrogen Strategy and in the Italian National Recovery and Resilience Plan, with the purpose of providing a critical assessment of what they propose. One scenario imposes decarbonization objectives for the years 2030, 2040 and 2050, without any other specific target. The second one (inspired to the national objectives on the development of the sector) promotes the deployment of the hydrogen value-chain. These scenarios provide feedback about the applications hydrogen could have in the Italian energy system, including transport, industry and synfuels production. Furthermore, the decarbonization scenario where hydrogen production is not imposed, will make use of this energy vector as well, showing the necessity of its exploitation in order to meet pledged targets by 2050. The distance of the planned policies from the optimal conditions for the achievement of Italian objectives is be clarified, revealing possible improvements of various steps of the decarbonization pathway, which seems to have as a fundamental element Carbon Capture and Utilization technologies for its accomplishment. In line with the European Commission open science guidelines, the transparency and the robustness of the presented results is ensured by the adoption of the open-source open-data model such as the TEMOA-Italy.

Keywords: decarbonization, energy system optimization models, hydrogen, open-source modeling, TEMOA

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Authors: Atilola O. Abidemi-Iromini, Oluayo A. Bello-Olusoji, Immanuel A. Adebayo

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Ecological studies were carried out in Asejire Reservoir (AR) and Lagos Lagoon (LL), Southwest Nigeria from January 2012 to December 2013 to determine the health status of Chrysichthys nigrodigitatus (CN) and Oreochromis niloticus (ON). The fish species samples were collected every month, these were separated into sexes, and growth pattern {length, (cm); weight (g), Isometric index, condition factor} were measured. Heavy metals (lead (Pb), iron (Fe), zinc (Zn), copper (Cu), and chromium (Cr) in ppm concentrations were also determined while bacteria occurrence(s), (load and prevalence) on fish skins, gills and intestine in the two ecological zones were determined. The fish ratio collected is in range with normal aquatic (1: 1+) male: female ratio. Growth assessment determined revealed no significant difference in length and weight in O. niloticus between locations, but a significant difference in weight occurred in C. nigrodigitatus between locations, with a higher weight (196.06 ±0.16 g) from Lagos Lagoon. Highest condition factor (5.25) was recorded in Asejire Reservoir O. niloticus, (ARON); and lowest condition factor (1.64) was observed in Asejire Reservoir C. nigrodigitatus (ARCN); as this indicated a negative allometric value which is normal in Bagridae species because it increases more in Length to weight gain than for the Cichlidae growth status. Normal growth rate (K > 1) occurred between sexes, with the male species having higher K - factors than female species within locations, between locations, between species, and within species, except for female C. nigrodigitatus having higher condition factor (K = 1.75) than male C. nigrodigitatus (K = 1.54) in Asejire Reservoir. The highest isometric value (3.05) was recorded in Asejire Reservoir O. niloticus and lowest in Lagos Lagoon C. nigrodigitatus. Male O. niloticus from Asejire Reservoir had highest isometric value, and O. niloticus species had higher condition factor which ranged between isometric (b ≤ 3) and positive allometric (b > 3), hence, denoted robustness of fish to grow more in weight than in length; while C. nigrodigitatus fish has negative allometric (b < 3) indicating fish add more length than in weight on growth. The status of condition factors and isometric values obtained is species-specific, and environmental influence, food availability or reproduction factor may as well be contributing factors. The concentrations of heavy metals in fish flesh revealed that Zn (6.52 ±0.82) had the highest, while Cr (0.01±0.00) was ranked lowest; for O. niloticus in Asejire Reservoir. In Lagos Lagoon, heavy metals concentration level revealed that O. niloticus flesh had highest in Zn (4.71±0.25) and lowest in Pb (0.01±0.00). Lagos Lagoon C. nigrodigitatus heavy metal concentration level revealed Zn (9.56±0.96) had highest, while Cr (0.06±0.01) had lowest; and Asejire Reservoir C. nigrodigitatus heavy metal level revealed that Zn (8.26 ±0.74) had highest, and Cr (0.08±0.00) had lowest. In all, Zinc (Zn) was top-ranked in level among species.

Keywords: Oreochromis niloticus, growth status, Chrysichthys nigrodigitatus, environments, heavy metals

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Authors: Gema M. Rodado, Jose M. Olavarrieta

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Hydrogen fuel cell technologies have experienced a great boost in the last decades, significantly increasing the production of these devices for both stationary and portable (mainly automotive) applications; these are influenced by two main factors: environmental pollution and energy shortage. A fuel cell is an electrochemical device that converts chemical energy directly into electricity by using hydrogen and oxygen gases as reactive components and obtaining water and heat as byproducts of the chemical reaction. Fuel cells, specifically those of Proton Exchange Membrane (PEM) technology, are considered an alternative to internal combustion engines, mainly because of the low emissions they produce (almost zero), high efficiency and low operating temperatures (< 373 K). The introduction and use of fuel cells in the automotive market requires the development of standardized and validated procedures to test and evaluate their performance in different environmental conditions including vibrations and freeze-thaw cycles. These situations of vibration and extremely low/high temperatures can affect the physical integrity or even the excellent operation or performance of the fuel cell stack placed in a vehicle in circulation or in different climatic conditions. The main objective of this work is the development and validation of vibration and freeze-thaw cycling test procedures for fuel cell stacks that can be used in a vehicle in order to consolidate their safety, performance, and durability. In this context, different experimental tests were carried out at the facilities of the National Hydrogen Centre (CNH2). The experimental equipment used was: A vibration platform (shaker) for vibration test analysis on fuel cells in three axes directions with different vibration profiles. A walk-in climatic chamber to test the starting, operating, and stopping behavior of fuel cells under defined extreme conditions. A test station designed and developed by the CNH2 to test and characterize PEM fuel cell stacks up to 10 kWe. A 5 kWe PEM fuel cell stack in off-operation mode was used to carry out two independent experimental procedures. On the one hand, the fuel cell was subjected to a sinusoidal vibration test on the shaker in the three axes directions. It was defined by acceleration and amplitudes in the frequency range of 7 to 200 Hz for a total of three hours in each direction. On the other hand, the climatic chamber was used to simulate freeze-thaw cycles by defining a temperature range between +313 K and -243 K with an average relative humidity of 50% and a recommended ramp up and rump down of 1 K/min. The polarization curve and gas leakage rate were determined before and after the vibration and freeze-thaw tests at the fuel cell stack test station to evaluate the robustness of the stack. The results were very similar, which indicates that the tests did not affect the fuel cell stack structure and performance. The proposed procedures were verified and can be used as an initial point to perform other tests with different fuel cells.

Keywords: climatic chamber, freeze-thaw cycles, PEM fuel cell, shaker, vibration tests

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Authors: Konstantinos Kottikas, Vlasis Stathakopoulos, Ioannis G. Theodorakis, Efthymia Kottika

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Theorists have argued that Market Orientation is comprised of two facets, namely the Market Driven and the Market Driving components. The present theoretical paper centers on the latter, which to date has been notably under-investigated. The term Market Driving (MD) pertains to influencing the structure of the market, or the behavior of market players in a direction that enhances the competitive edge of the firm. Presently, the main objectives of the paper are the specification of key antecedents and outcomes of Market Driving behavior. Market Driving firms behave proactively, by leading their customers and changing the rules of the game rather than by responding passively to them. Leading scholars were the first to conceptually conceive the notion, followed by some qualitative studies and a limited number of quantitative publications. However, recently, academicians noted that research on the topic remains limited, expressing a strong necessity for further insights. Concerning the key antecedents, top management’s Transformational Leadership (i.e. the form of leadership which influences organizational members by aligning their values, goals and aspirations to facilitate value-consistent behaviors) is one of the key drivers of MD behavior. Moreover, scholars have linked the MD concept with Entrepreneurship. Finally, the role that Employee’s Creativity plays in the development of MD behavior has been theoretically exemplified by a stream of literature. With respect to the key outcomes, it has been demonstrated that MD Behavior positively triggers firm Performance, while theorists argue that it empowers the Competitive Advantage of the firm. Likewise, researchers explicate that MD Behavior produces Radical Innovation. In order to test the robustness of the proposed theoretical framework, a combination of qualitative and quantitative methods is proposed. In particular, the conduction of in-depth interviews with distinguished executives and academicians, accompanied with a large scale quantitative survey will be employed, in order to triangulate the empirical findings. Given that it triggers overall firm’s success, the MD concept is of high importance to managers. Managers can become aware that passively reacting to market conditions is no longer sufficient. On the contrary, behaving proactively, leading the market, and shaping its status quo are new innovative approaches that lead to a paramount competitive posture and Innovation outcomes. This study also exemplifies that managers can foster MD Behavior through Transformational Leadership, Entrepreneurship and recruitment of Creative Employees. To date, the majority of the publications on Market Orientation is unilaterally directed towards the responsive (i.e. the Market Driven) component. The present paper further builds on scholars’ exhortations, and investigates the Market Driving facet, ultimately aspiring to conceptually integrate the somehow fragmented scientific findings, in a holistic framework.

Keywords: entrepreneurial orientation, market driving behavior, market orientation

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