Search results for: proxy server

Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Wee Tong Liaw, Elaine Wong Yee Sing

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Since 2001, many companies in Singapore have voluntarily participated in the bi-annual Singapore HEALTH Award initiated by the Health Promotion Board of Singapore (HPB). The Singapore HEALTH Award (SHA), is an industry wide award and assessment process. SHA assesses and recognizes employers in Singapore for implementing a comprehensive and sustainable health promotion programme at their workplaces. The rationale for implementing a sustained health promoting workplace and participating in SHA is obvious when company management is convinced that healthier employees, business productivity, and profitability are positively correlated. However, performing research or empirical studies on the impact of a sustained health promoting workplace on stock returns are not likely to yield any interests in the absence of a systematic and independent assessment on the comprehensiveness and sustainability of a health promoting workplace in most developed economies. The principles of diversification and mean-variance efficient portfolio in Modern Portfolio Theory developed by Markowitz (1952) laid the foundation for the works of many financial economists and researchers, and among others, the development of the Capital Asset Pricing Model from the work of Sharpe (1964), Lintner (1965) and Mossin (1966), and the Fama-French Three-Factor Model of Fama and French (1992). This research seeks to support the rationale by studying whether there is a significant relationship or impact of a sustained health promoting workplace on the performance of companies listed on the SGX. The research shall form and test hypotheses pertaining to the impact of a sustained health promoting workplace on company’s performances, including stock returns, of companies that participated in the SHA and companies that did not participate in the SHA. In doing so, the research would be able to determine whether corporate and fund manager should consider the significance of a sustained health promoting workplace as a risk factor to explain the stock returns of companies listed on the SGX. With respect to Singapore’s stock market, this research will test the significance and relevance of a health promoting workplace using the Singapore Health Award as a proxy for non-diversifiable risk factor to explain stock returns. This study will examine the significance of a health promoting workplace on a company’s performance and study its impact on stock price performance and beta and examine if it has higher explanatory power than the traditional single factor asset pricing model CAPM (Capital Asset Pricing Model). To study the significance there are three key questions pertinent to the research study. I) Given a choice, would an investor be better off investing in a listed company with a sustained health promoting workplace i.e. a Singapore Health Award’s recipient? II) The Singapore Health Award has four levels of award starting from Bronze, Silver, Gold to Platinum. Would an investor be indifferent to the level of award when investing in a listed company who is a Singapore Health Award’s recipient? III) Would an asset pricing model combining FAMA-French Three Factor Model and ‘Singapore Health Award’ factor be more accurate than single factor Capital Asset Pricing Model and the Three Factor Model itself?

Keywords: asset pricing model, company's performance, stock prices, sustained health promoting workplace

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Authors: Gary J. Pickering, Sarah Lucas, Catherine E. Klodnicki, Nicole J. Gaudette

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Two taste pheno types that are of interest in the study of habitual diet-related risk factors and disease are 6-n-propylthiouracil (PROP) responsiveness and thermal tasting. Individuals differ considerable in how intensely they experience the bitterness of PROP, which is partially explained by three major single nucleotide polymorphisms associated with the TAS2R38 gene. Importantly, this variable responsiveness is a useful proxy for general taste responsiveness, and links to diet-related disease risk, including body mass index, in some studies. Thermal tasting - a newly discovered taste phenotype independent of PROP responsiveness - refers to the capacity of many individuals to perceive phantom tastes in response to lingual thermal stimulation, and is linked with TRPM5 channels. Thermal tasters (TTs) also experience oral sensations more intensely than thermal non-tasters (TnTs), and this was shown to associate with differences in self-reported food preferences in a previous survey from our lab. Here we report on two related studies, where we sought to determine whether PROP responsiveness and thermal tasting would associate with perceptual differences in the oral sensations elicited by sampled energy-dense foods, and whether in turn this would influence liking. We hypothesized that hyper-tasters (thermal tasters and individuals who experience PROP intensely) would (a) rate sweet and high-fat foods more intensely than hypo-tasters, and (b) would differ from hypo-tasters in liking scores. (Liking has been proposed recently as a more accurate measure of actual food consumption). In Study 1, a range of energy-dense foods and beverages, including table cream and chocolate, was assessed by 25 TTs and 19 TnTs. Ratings of oral sensation intensity and overall liking were obtained using gVAS and gDOL scales, respectively. TTs and TnTs did not differ significantly in intensity ratings for most stimuli (ANOVA). In a 2nd study, 44 female participants sampled 22 foods and beverages, assessing them for intensity of oral sensations (gVAS) and overall liking (9-point hedonic scale). TTs (n=23) rated their overall liking of creaminess and milk products lower than did TnTs (n=21), and liked milk chocolate less. PROP responsiveness was negatively correlated with liking of food and beverages belonging to the sweet or sensory food grouping. No other differences in intensity or liking scores between hyper- and hypo-tasters were found. Taken overall, our results are somewhat unexpected, lending only modest support to the hypothesis that these taste phenotypes associate with energy-dense food liking and consumption through differences in the oral sensations they elicit. Reasons for this lack of concordance with expectations and some prior literature are discussed, and suggestions for future research are advanced.

Keywords: taste phenotypes, sensory evaluation, PROP, thermal tasting, diet-related health risk

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Authors: Pin Xiu Chen, Shang Liang Chen

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A virtualized software controller is developed in this research to replace traditional hardware control units. This virtualized software controller transfers motion interpolation calculations from the motion control units of end devices to edge computing platforms, thereby reducing the end devices' computational load and hardware requirements and making maintenance and updates easier. The study also applies the concept of microservices, dividing the control system into several small functional modules and then deploy into a cloud data server. This reduces the interdependency among modules and enhances the overall system's flexibility and scalability. Finally, with containerization technology, the system can be deployed and started in a matter of seconds, which is more efficient than traditional virtual machine deployment methods. Furthermore, this virtualized software controller communicates with end control devices via wireless networks, making the placement of production equipment or the redesign of processes more flexible and no longer limited by physical wiring. To handle the large data flow and maintain low-latency transmission, this study integrates 5G technology, fully utilizing its high speed, wide bandwidth, and low latency features to achieve rapid and stable remote machine control. An experimental setup is designed to verify the feasibility and test the performance of this framework. This study designs a smart manufacturing site with a 5G communication architecture, serving as a field for experimental data collection and performance testing. The smart manufacturing site includes one robotic arm, three Computer Numerical Control machine tools, several Input/Output ports, and an edge computing architecture. All machinery information is uploaded to edge computing servers and cloud servers via 5G communication and the Internet of Things framework. After analysis and computation, this information is converted into motion control commands, which are transmitted back to the relevant machinery for motion control through 5G communication. The communication time intervals at each stage are calculated using the C++ chrono library to measure the time difference for each command transmission. The relevant test results will be organized and displayed in the full-text.

Keywords: 5G, MEC, microservices, virtualized software controller, smart manufacturing

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Authors: Estelle Arbellay, Lori D. Daniels, Shawn D. Mansfield, Alice S. Chang

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Mountain pine beetle (MPB) outbreaks are currently devastating lodgepole pine forests in western North America, which are also widely disturbed by frequent wildfires. Both MPB and fire can leave scars on lodgepole pine trees, thereby diminishing their commercial value and possibly compromising their utilization in solid wood products. In order to fully exploit the affected resource, it is crucial to understand how wounding from these two disturbance agents impact wood properties. Moreover, previous research on lodgepole pine has focused solely on sound wood and stained wood resulting from the MPB-transmitted blue fungi. By means of a quantitative multi-proxy approach, we tested the hypotheses that (i) wounding (of either MPB or fire origin) caused significant changes in wood properties of lodgepole pine and that (ii) MPB-induced wound effects could differ from those induced by fire in type and magnitude. Pith-to-bark strips were extracted from 30 MPB scars and 30 fire scars. Strips were cut immediately adjacent to the wound margin and encompassed 12 rings from normal wood formed prior to wounding and 12 rings from wound wood formed after wounding. Wood properties evaluated within this 24-year window included ring width, relative wood density, cellulose crystallinity, fibre dimensions, and carbon and nitrogen concentrations. Methods used to measure these proxies at a (sub-)annual resolution included X-ray densitometry, X-ray diffraction, fibre quality analysis, and elemental analysis. Results showed a substantial growth release in wound wood compared to normal wood, as both earlywood and latewood width increased over a decade following wounding. Wound wood was also shown to have a significantly different latewood density than normal wood 4 years after wounding. Latewood density decreased in MPB scars while the opposite was true in fire scars. By contrast, earlywood density was presented only minor variations following wounding. Cellulose crystallinity decreased in wound wood compared to normal wood, being especially diminished in MPB scars the first year after wounding. Fibre dimensions also decreased following wounding. However, carbon and nitrogen concentrations did not substantially differ between wound wood and normal wood. Nevertheless, insect-feeding and fire-heating wounding were shown to significantly alter most wood properties of lodgepole pine, as demonstrated by the existence of several morphological anomalies in wound wood. MPB and fire generally elicited similar anomalies, with the major exception of latewood density. In addition to providing quantitative criteria for differentiating between biotic (MPB) and abiotic (fire) disturbances, this study provides the wood industry with fundamental information on the physiological response of lodgepole pine to wounding in order to evaluate the utilization of scarred trees in solid wood products.

Keywords: elemental analysis, fibre quality analysis, lodgepole pine, wood properties, wounding, X-ray densitometry, X-ray diffraction

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Authors: M. V. Shivaani, P. K. Jain, Surendra S. Yadav

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Risk management has been gaining extensive focus from international organizations like Committee of Sponsoring Organizations and Financial Stability Board, and, the foundation of such an effective and efficient risk management system lies in a strong risk governance structure. In view of this, an attempt (perhaps a first of its kind) has been made to develop a risk governance index, which could be used as proxy for quality of risk governance structures. The index (normative framework) is based on eleven variables, namely, size of board, board diversity in terms of gender, proportion of executive directors, executive/non-executive status of chairperson, proportion of independent directors, CEO duality, chief risk officer (CRO), risk management committee, mandatory committees, voluntary committees and existence/non-existence of whistle blower policy. These variables are scored on a scale of 1 to 5 with the exception of the variables, namely, status of chairperson and CEO duality (which have been scored on a dichotomous scale with the score of 3 or 5). In case there is a legal/statutory requirement in respect of above-mentioned variables and there is a non-compliance with such requirement a score of one has been envisaged. Though there is no legal requirement, for the larger part of study, in context of CRO, risk management committee and whistle blower policy, still a score of 1 has been assigned in the event of their non-existence. Recognizing the importance of these variables in context of risk governance structure and the fact that the study basically focuses on risk governance, the absence of these variables has been equated to non-compliance with a legal/statutory requirement. Therefore, based on this the minimum score is 15 and the maximum possible is 55. In addition, an attempt has been made to explore the determinants of this index. For this purpose, the sample consists of non-financial companies (429) that constitute S&P CNX500 index. The study covers a 10 years period from April 1, 2005 to March 31, 2015. Given the panel nature of data, Hausman test was applied, and it suggested that fixed effects regression would be appropriate. The results indicate that age and size of firms have significant positive impact on its risk governance structures. Further, post-recession period (2009-2015) has witnessed significant improvement in quality of governance structures. In contrast, profitability (positive relationship), leverage (negative relationship) and growth (negative relationship) do not have significant impact on quality of risk governance structures. The value of rho indicates that about 77.74% variation in risk governance structures is due to firm specific factors. Given the fact that each firm is unique in terms of its risk exposure, risk culture, risk appetite, and risk tolerance levels, it appears reasonable to assume that the specific conditions and circumstances that a company is beset with, could be the biggest determinants of its risk governance structures. Given the recommendations put forth in the paper (particularly for regulators and companies), the study is expected to be of immense utility in an important yet neglected aspect of risk management.

Keywords: corporate governance, ERM, risk governance, risk management

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Authors: Pratap Chandra Pati, Prabina Rajib, Parama Barai

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The traditional finance theory neglects the role of sentiment factor in asset pricing. However, the behavioral approach to asset-pricing based on noise trader model and limit to arbitrage includes investor sentiment as a priced risk factor in the assist pricing model. Investor sentiment affects stock more that are vulnerable to speculation, hard to value and risky to arbitrage. It includes small stocks, high volatility stocks, growth stocks, distressed stocks, young stocks and non-dividend-paying stocks. Since the introduction of Chicago Board Options Exchange (CBOE) volatility index (VIX) in 1993, it is used as a measure of future volatility in the stock market and also as a measure of investor sentiment. CBOE VIX index, in particular, is often referred to as the ‘investors’ fear gauge’ by public media and prior literature. The upward spikes in the volatility index are associated with bouts of market turmoil and uncertainty. High levels of the volatility index indicate fear, anxiety and pessimistic expectations of investors about the stock market. On the contrary, low levels of the volatility index reflect confident and optimistic attitude of investors. Based on the above discussions, we investigate whether market-wide fear levels measured volatility index is priced factor in the standard asset pricing model for the Indian stock market. First, we investigate the performance and validity of Fama and French three-factor model and Carhart four-factor model in the Indian stock market. Second, we explore whether India volatility index as a proxy for fearful market-based sentiment indicators affect the cross section of stock returns after controlling for well-established risk factors such as market excess return, size, book-to-market, and momentum. Asset pricing tests are performed using monthly data on CNX 500 index constituent stocks listed on the National stock exchange of India Limited (NSE) over the sample period that extends from January 2008 to March 2017. To examine whether India volatility index, as an indicator of fear sentiment, is a priced risk factor, changes in India VIX is included as an explanatory variable in the Fama-French three-factor model as well as Carhart four-factor model. For the empirical testing, we use three different sets of test portfolios used as the dependent variable in the in asset pricing regressions. The first portfolio set is the 4x4 sorts on the size and B/M ratio. The second portfolio set is the 4x4 sort on the size and sensitivity beta of change in IVIX. The third portfolio set is the 2x3x2 independent triple-sorting on size, B/M and sensitivity beta of change in IVIX. We find evidence that size, value and momentum factors continue to exist in Indian stock market. However, VIX index does not constitute a priced risk factor in the cross-section of returns. The inseparability of volatility and jump risk in the VIX is a possible explanation of the current findings in the study.

Keywords: India VIX, Fama-French model, Carhart four-factor model, asset pricing

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Authors: Sahraoui Halima, Dahani Ameur, Tigrine Abedelkader

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DigiMesh technology represents a pioneering advancement in wireless networking, offering cost-effective and energy-efficient capabilities. Its inherent simplicity and adaptability facilitate the seamless transfer of data between network nodes, extending the range and ensuring robust connectivity through autonomous self-healing mechanisms. In light of these advantages, this study introduces a medical platform harnessed with DigiMesh wireless network technology characterized by low power consumption, immunity to interference, and user-friendly operation. The primary application of this platform is the real-time, long-distance monitoring of Electrocardiogram (ECG) signals, with the added capacity for simultaneous monitoring of ECG signals from multiple patients. The experimental setup comprises key components such as Raspberry Pi, E-Health Sensor Shield, and Xbee DigiMesh modules. The platform is composed of multiple ECG acquisition devices labeled as Sensor Node 1 and Sensor Node 2, with a Raspberry Pi serving as the central hub (Sink Node). Two communication approaches are proposed: Single-hop and multi-hop. In the Single-hop approach, ECG signals are directly transmitted from a sensor node to the sink node through the XBee3 DigiMesh RF Module, establishing peer-to-peer connections. This approach was tested in the first experiment to assess the feasibility of deploying wireless sensor networks (WSN). In the multi-hop approach, two sensor nodes communicate with the server (Sink Node) in a star configuration. This setup was tested in the second experiment. The primary objective of this research is to evaluate the performance of both Single-hop and multi-hop approaches in diverse scenarios, including open areas and obstructed environments. Experimental results indicate the DigiMesh network's effectiveness in Single-hop mode, with reliable communication over distances of approximately 300 meters in open areas. In the multi-hop configuration, the network demonstrated robust performance across approximately three floors, even in the presence of obstacles, without the need for additional router devices. This study offers valuable insights into the capabilities of DigiMesh wireless technology for real-time ECG monitoring in healthcare applications, demonstrating its potential for use in diverse medical scenarios.

Keywords: DigiMesh protocol, ECG signal, real-time monitoring, medical platform

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Authors: Jialin Ma, Jia Meng

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Genomic features, the genome-based coordinates, are commonly used for the representation of biological features such as genes, RNA transcripts and transcription factor binding sites. For the analysis of RNA-related genomic features, such as RNA modification sites, a common task is to correlate these features with transcript components (5'UTR, CDS, 3'UTR) to explore their distribution characteristics in terms of transcriptomic coordinates, e.g., to examine whether a specific type of biological feature is enriched near transcription start sites. Existing approaches for performing these tasks involve the manipulation of a gene database, conversion from genome-based coordinate to transcript-based coordinate, and visualization methods that are capable of showing RNA transcript components and distribution of the features. These steps are complicated and time consuming, and this is especially true for researchers who are not familiar with relevant tools. To overcome this obstacle, we develop a dedicated web app TARF, which represents web toolkit for annotating RNA-related genomic features. TARF web tool intends to provide a web-based way to easily annotate and visualize RNA-related genomic features. Once a user has uploaded the features with BED format and specified a built-in transcript database or uploaded a customized gene database with GTF format, the tool could fulfill its three main functions. First, it adds annotation on gene and RNA transcript components. For every features provided by the user, the overlapping with RNA transcript components are identified, and the information is combined in one table which is available for copy and download. Summary statistics about ambiguous belongings are also carried out. Second, the tool provides a convenient visualization method of the features on single gene/transcript level. For the selected gene, the tool shows the features with gene model on genome-based view, and also maps the features to transcript-based coordinate and show the distribution against one single spliced RNA transcript. Third, a global transcriptomic view of the genomic features is generated utilizing the Guitar R/Bioconductor package. The distribution of features on RNA transcripts are normalized with respect to RNA transcript landmarks and the enrichment of the features on different RNA transcript components is demonstrated. We tested the newly developed TARF toolkit with 3 different types of genomics features related to chromatin H3K4me3, RNA N6-methyladenosine (m6A) and RNA 5-methylcytosine (m5C), which are obtained from ChIP-Seq, MeRIP-Seq and RNA BS-Seq data, respectively. TARF successfully revealed their respective distribution characteristics, i.e. H3K4me3, m6A and m5C are enriched near transcription starting sites, stop codons and 5’UTRs, respectively. Overall, TARF is a useful web toolkit for annotation and visualization of RNA-related genomic features, and should help simplify the analysis of various RNA-related genomic features, especially those related RNA modifications.

Keywords: RNA-related genomic features, annotation, visualization, web server

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Authors: Kanika Gupta, Ashok Kumar

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Biofilms are dense, highly hydrated cell clusters that are irreversibly attached to a substratum, to an interface or to each other, and are embedded in a self-produced gelatinous matrix composed of extracellular polymeric substances. Research in biofilm field has become very significant, as biofilm has shown high mechanical resilience and resistance to antibiotic treatment and constituted as a significant problem in both healthcare and other industry related to microorganisms. The massive information both stated and hidden in the biofilm literature are growing exponentially therefore it is not possible for researchers and practitioners to automatically extract and relate information from different written resources. So, the current work proposes and discusses the use of text mining techniques for the extraction of information from biofilm literature corpora containing 34306 documents. It is very difficult and expensive to obtain annotated material for biomedical literature as the literature is unstructured i.e. free-text. Therefore, we considered unsupervised approach, where no annotated training is necessary and using this approach we developed a system that will classify the text on the basis of growth and development, drug effects, radiation effects, classification and physiology of biofilms. For this, a two-step structure was used where the first step is to extract keywords from the biofilm literature using a metathesaurus and standard natural language processing tools like Rapid Miner_v5.3 and the second step is to discover relations between the genes extracted from the whole set of biofilm literature using pubmed.mineR_v1.0.11. We used unsupervised approach, which is the machine learning task of inferring a function to describe hidden structure from 'unlabeled' data, in the above-extracted datasets to develop classifiers using WinPython-64 bit_v3.5.4.0Qt5 and R studio_v0.99.467 packages which will automatically classify the text by using the mentioned sets. The developed classifiers were tested on a large data set of biofilm literature which showed that the unsupervised approach proposed is promising as well as suited for a semi-automatic labeling of the extracted relations. The entire information was stored in the relational database which was hosted locally on the server. The generated biofilm vocabulary and genes relations will be significant for researchers dealing with biofilm research, making their search easy and efficient as the keywords and genes could be directly mapped with the documents used for database development.

Keywords: biofilms literature, classifiers development, text mining, unsupervised learning approach, unstructured data, relational database

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Authors: Athanasios Raftopoulos

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In this paper, an attempt is made to explain the evolution or development of human’s representational arsenal from its humble beginnings to its modern abstract symbols. Representations are physical entities that represent something else. To represent a thing (in a general sense of “thing”) means to use in the mind or in an external medium a sign that stands for it. The sign can be used as a proxy of the represented thing when the thing is absent. Representations come in many varieties, from signs that perceptually resemble their representative to abstract symbols that are related to their representata through conventions. Relying the distinction among indices, icons, and symbols, it is explained how symbolic representations gradually emerged from indices and icons. To understand the development or evolution of our representational arsenal, the development of the cognitive capacities that enabled the gradual emergence of representations of increasing complexity and expressive capability should be examined. The examination of these factors should rely on a careful assessment of the available empirical neuroscientific and paleo-anthropological evidence. These pieces of evidence should be synthesized to produce arguments whose conclusions provide clues concerning the developmental process of our representational capabilities. The analysis of the empirical findings in this paper shows that Homo Erectus was able to use both icons and symbols. Icons were used as external representations, while symbols were used in language. The first step in the emergence of representations is that a sensory-motor purely causal schema involved in indices is decoupled from its normal causal sensory-motor functions and serves as a representation of the object that initially called it into play. Sensory-motor schemes are tied to specific contexts of the organism-environment interactions and are activated only within these contexts. For a representation of an object to be possible, this scheme must be de-contextualized so that the same object can be represented in different contexts; a decoupled schema loses its direct ties to reality and becomes mental content. The analysis suggests that symbols emerged due to selection pressures of the social environment. The need to establish and maintain social relationships in ever-enlarging groups that would benefit the group was a sufficient environmental pressure to lead to the appearance of the symbolic capacity. Symbols could serve this need because they can express abstract relationships, such as marriage or monogamy. Icons, by being firmly attached to what can be observed, could not go beyond surface properties to express abstract relations. The cognitive capacities that are required for having iconic and then symbolic representations were present in Homo Erectus, which had a language that started without syntactic rules but was structured so as to mirror the structure of the world. This language became increasingly complex, and grammatical rules started to appear to allow for the construction of more complex expressions required to keep up with the increasing complexity of social niches. This created evolutionary pressures that eventually led to increasing cranial size and restructuring of the brain that allowed more complex representational systems to emerge.

Keywords: mental representations, iconic representations, symbols, human evolution

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Authors: Najeebullah Soomro, Habib Noorbhai, Mariam Soomro, Ross Sanders

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The demands on cricketers are increasing with more matches being played in a shorter period of time with a greater intensity. A ten year report on injury incidence for Australian elite cricketers between the 2000- 2011 seasons revealed an injury incidence rate of 17.4%.1. In the 2009–10 season, 24 % of Australian fast bowlers missed matches through injury. 1 Injury rates are even higher in junior cricketers with an injury incidence of 25% or 2.9 injuries per 100 player hours reported. 2 Traditionally, injury surveillance has relied on the use of paper based forms or complex computer software. 3,4 This makes injury reporting laborious for the staff involved. The purpose of this presentation is to describe a smartphone based mobile application as a means of improving injury surveillance in cricket. Methods: The researchers developed CricPredict mobile App for the Android platforms, the world’s most widely used smartphone platform. It uses Qt SDK (Software Development Kit) as IDE (Integrated Development Environment). C++ was used as the programming language with the Qt framework, which provides us with cross-platform abilities that will allow this app to be ported to other operating systems (iOS, Mac, Windows) in the future. The wireframes (graphic user interface) were developed using Justinmind Prototyper Pro Edition Version (Ver. 6.1.0). CricPredict enables recording of injury and training status conveniently and immediately. When an injury is reported automated follow-up questions include site of injury, nature of injury, mechanism of injury, initial treatment, referral and action taken after injury. Direct communication with the player then enables assessment of severity and diagnosis. CricPredict also allows the coach to maintain and track each player’s attendance at matches and training session. Workload data can also be recorded by either the player or coach by recording the number of balls bowled or played in a day. This is helpful in formulating injury rates and time lost due to injuries. All the data are stored at a secured password protected data server. Outcomes and Significance: Use of CricPredit offers a simple, user friendly tool for the coaching or medical staff associated with teams to predict, record and report injuries. This system will assist teams to capture injury data with ease thus allowing better understanding of injuries associated with cricket and potentially optimize the performance of such cricketers.

Keywords: injury, cricket, surveillance, smartphones, mobile

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Authors: Md. Fazlul Karim, Ashik Sharfaraz, Aysha Ferdoushi

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Background: Computational medicinal chemistry approaches are used for designing and identifying new drug-like molecules, predicting properties and pharmacological activities, and optimizing lead compounds in drug development. SIRT7, a nicotinamide adenine dinucleotide (NAD+)-dependent deacylase which regulates aging, is an emerging target for cancer therapy with mounting evidence that SIRT7 downregulation plays important roles in reversing cancer phenotypes and suppressing tumor growth. Activation or altered expression of SIRT7 is associated with the progression and invasion of various cancers, including liver, breast, gastric, prostate, and non-small cell lung cancer. Objectives: The goal of this work was to identify potent and selective bioactive candidate inhibitors of SIRT7 by in silico screening of small molecule compounds obtained from Nigella sativa (N. sativa). Methods: SIRT7 structure was retrieved from The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), and its active site was identified using CASTp and metaPocket. Molecular docking simulation was performed with PyRx 0.8 virtual screening software. Drug-likeness properties were tested using SwissADME and pkCSM. In silico toxicity was evaluated by Osiris Property Explorer. Bioactivity was predicted by Molinspiration software. Antitumor activity was screened for Prediction of Activity Spectra for Substances (PASS) using Way2Drug web server. Molecular dynamics (MD) simulation was carried out by Desmond v3.6 package. Results: A total of 159 bioactive compounds from the N. Sativa were screened against the SIRT7 enzyme. Five bioactive compounds: chrysin (CID:5281607), pinocembrin (CID:68071), nigellidine (CID:136828302), nigellicine (CID:11402337), and epicatechin (CID:72276) were identified as potent SIRT7 anti-cancer candidates after docking score evaluation and applying Lipinski's Rule of Five. Finally, MD simulation identified Chrysin as the top SIRT7 anti-cancer candidate molecule. Conclusion: Chrysin, which shows a potential inhibitory effect against SIRT7, can act as a possible anti-cancer drug candidate. This inhibitor warrants further evaluation to check its pharmacokinetics and pharmacodynamics properties both in vitro and in vivo.

Keywords: SIRT7, antitumor, molecular docking, molecular dynamics simulation

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Authors: Luisa Kynast

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It is obvious that buildings and infrastructure are highly impacted by climate change (CC). Both, design and material of buildings need to be resilient to weather events in order to shelter humans, animals, or goods. As well as buildings and infrastructure are exposed to weather events, the construction process itself is generally carried out outdoors without being protected from extreme temperatures, heavy rain, or storms. The production process is restricted by technical limitations for processing materials with machines and physical limitations due to human beings (“outdoor-worker”). In future due to CC, average weather patterns are expected to change as well as extreme weather events are expected to occur more frequently and more intense and therefore have a greater impact on production processes and on the construction businesses itself. This research aims to examine this impact by analyzing an association between responses to CC and financial performance of businesses within the construction industry. After having embedded the above depicted field of research into the resource dependency theory, a literature review was conducted to expound the state of research concerning a contingent relation between climate change adaptation measures (CCAM) and corporate financial performance for construction businesses. The examined studies prove that this field is rarely investigated, especially for construction businesses. Therefore, reports of the Carbon Disclosure Project (CDP) were analyzed by applying content analysis using the software tool MAXQDA. 58 construction companies – located worldwide – could be examined. To proceed even more systematically a coding scheme analogous to findings in literature was adopted. Out of qualitative analysis, data was quantified and a regression analysis containing corporate financial data was conducted. The results gained stress adaptation measures as a response to CC as a crucial proxy to handle climate change impacts (CCI) by mitigating risks and exploiting opportunities. In CDP reports the majority of answers stated increasing costs/expenses as a result of implemented measures. A link to sales/revenue was rarely drawn. Though, CCAM were connected to increasing sales/revenues. Nevertheless, this presumption is supported by the results of the regression analysis where a positive effect of implemented CCAM on construction businesses´ financial performance in the short-run was ascertained. These findings do refer to appropriate responses in terms of the implemented number of CCAM. Anyhow, still businesses show a reluctant attitude for implementing CCAM, which was confirmed by findings in literature as well as by findings in CDP reports. Businesses mainly associate CCAM with costs and expenses rather than with an effect on their corporate financial performance. Mostly companies underrate the effect of CCI and overrate the costs and expenditures for the implementation of CCAM and completely neglect the pay-off. Therefore, this research shall create a basis for bringing CC to the (financial) attention of corporate decision-makers, especially within the construction industry.

Keywords: climate change adaptation measures, construction businesses, financial implication, resource dependency theory

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Authors: Echo Wang, Andrew Li

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Transparency could be defined as the voluntary release of information by institutions that is relevant to their own evaluation. Transparency based on information disclosure is recognised to be vital for the Third Sector, as civil society organisations are under pressure to become more transparent to answer the call for accountability. The growing importance of social enterprises as hybrid organisations emerging from the nexus of the public, the private and the Third Sector makes their transparency a topic worth exploring. However, transparency for social enterprises has not yet been studied: as a new form of organisation that combines non-profit missions with commercial means, it is unclear to both the practical and the academic world if the shift in operational logics from non-profit motives to for-profit pursuits has significantly altered their transparency. This is especially so in China, where informational governance and practices of information disclosure by local governments, industries and civil society are notably different from other countries. This study investigates the transparency-seeking behaviour of social enterprises in Greater China to understand what factors at the organisational level may affect their transparency, measured by their willingness to disclose financial information. We make use of the Survey on the Models and Development Status of Social Enterprises in the Greater China Region (MDSSGCR) conducted in 2015-2016. The sample consists of more than 300 social enterprises from the Mainland, Hong Kong and Taiwan. While most respondents have provided complete answers to most of the questions, there is tremendous variation in the respondents’ demonstrated level of transparency in answering those questions related to the financial aspects of their organisations, such as total revenue, net profit, source of revenue and expense. This has led to a lot of missing data on such variables. In this study, we take missing data as data. Specifically, we use missing values as a proxy for an organisation’s level of transparency. Our dependent variables are constructed from missing data on total revenue, net profit, source of revenue and cost breakdown. In addition, we also take into consideration the quality of answers in coding the dependent variables. For example, to be coded as being transparent, an organization must report the sources of at least 50% of its revenue. We have four groups of predictors of transparency, namely nature of organization, decision making body, funding channel and field of concentration. Furthermore, we control for an organisation’s stage of development, self-identity and region. The results show that social enterprises that are at their later stages of organisational development and are funded by financial means are significantly more transparent than others. There is also some evidence that social enterprises located in the Northeast region in China are less transparent than those located in other regions probably because of local political economy features. On the other hand, the nature of the organisation, the decision-making body and field of concentration do not systematically affect the level of transparency. This study provides in-depth empirical insights into the information disclosure behaviour of social enterprises under specific social context. It does not only reveal important characteristics of Third Sector development in China, but also contributes to the general understanding of hybrid institutions.

Keywords: China, information transparency, organisational behaviour, social enterprise

Procedia PDF Downloads 185

Authors: Agnieszka H. Ludwig-Slomczynska, Michal T. Seweryn, Przemyslaw Kapusta, Ewelina Pitera, Katarzyna Cyganek, Urszula Mantaj, Lucja Dobrucka, Ewa Wender-Ozegowska, Maciej T. Malecki, Pawel Wolkow

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Obesity results from an imbalance between energy intake and its expenditure. Genome-Wide Association Study (GWAS) analyses have led to discovery of only about 100 variants influencing body mass index (BMI), which explain only a small portion of genetic variability. Analysis of gene epistasis gives a chance to discover another part. Since it was shown that interaction and communication between nuclear and mitochondrial genome are indispensable for normal cell function, we have looked for epistatic interactions between the two genomes to find their correlation with BMI. Methods: The analysis was performed on 366 T1DM patients using Illumina Infinium OmniExpressExome-8 chip and followed by imputation on Michigan Imputation Server. Only genes which influence mitochondrial functioning (listed in Human MitoCarta 2.0) were included in the analysis – variants of nuclear origin (MAF > 5%) in 1140 genes and 42 mitochondrial variants (MAF > 1%). Gene expression analysis was performed on GTex data. Association analysis between genetic variants and BMI was performed with the use of Linear Mixed Models as implemented in the package 'GENESIS' in R. Analysis of association between mRNA expression and BMI was performed with the use of linear models and standard significance tests in R. Results: Among variants involved in epistasis between mitochondria and nucleus we have identified one in mitochondrial transcription factor, TFB2M (rs6701836). It interacted with mitochondrial variants localized to MT-RNR1 (p=0.0004, MAF=15%), MT-ND2 (p=0.07, MAF=5%) and MT-ND4 (p=0.01, MAF=1.1%). Analysis of the interaction between nuclear variant rs6701836 (nuc) and rs3021088 localized to MT-ND2 mitochondrial gene (mito) has shown that the combination of the two led to BMI decrease (p=0.024). Each of the variants on its own does not correlate with higher BMI [p(nuc)=0.856, p(mito)=0.116)]. Although rs6701836 is intronic, it influences gene expression in the thyroid (p=0.000037). rs3021088 is a missense variant that leads to alanine to threonine substitution in the MT-ND2 gene which belongs to complex I of the electron transport chain. The analysis of the influence of genetic variants on gene expression has confirmed the trend explained above – the interaction of the two genes leads to BMI decrease (p=0.0308). Each of the mRNAs on its own is associated with higher BMI (p(mito)=0.0244 and p(nuc)=0.0269). Conclusıons: Our results show that nuclear-mitochondrial epistasis can influence BMI in T1DM patients. The correlation between transcription factor expression and mitochondrial genetic variants will be subject to further analysis.

Keywords: body mass index, epistasis, mitochondria, type 1 diabetes

Procedia PDF Downloads 175

Authors: Michela Del Vicario, Walter Quattrociocchi, Antonio Scala, Ana Lucía Schmidt, Fabiana Zollo

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Information, rumors, and debates may shape and impact public opinion heavily. In the latest years, several concerns have been expressed about social influence on the Internet and the outcome that online debates might have on real-world processes. Indeed, on online social networks users tend to select information that is coherent to their system of beliefs and to form groups of like-minded people –i.e., echo chambers– where they reinforce and polarize their opinions. In this way, the potential benefits coming from the exposure to different points of view may be reduced dramatically, and individuals' views may become more and more extreme. Such a context fosters misinformation spreading, which has always represented a socio-political and economic risk. The persistence of unsubstantiated rumors –e.g., the hypothetical and hazardous link between vaccines and autism– suggests that social media do have the power to misinform, manipulate, or control public opinion. As an example, current approaches such as debunking efforts or algorithmic-driven solutions based on the reputation of the source seem to prove ineffective against collective superstition. Indeed, experimental evidence shows that confirmatory information gets accepted even when containing deliberately false claims while dissenting information is mainly ignored, influences users’ emotions negatively and may even increase group polarization. Moreover, confirmation bias has been shown to play a pivotal role in information cascades, posing serious warnings about the efficacy of current debunking efforts. Nevertheless, mitigation strategies have to be adopted. To generalize the problem and to better understand social dynamics behind information spreading, in this work we rely on a tight quantitative analysis to investigate the behavior of more than 300M users w.r.t. news consumption on Facebook over a time span of six years (2010-2015). Through a massive analysis on 920 news outlets pages, we are able to characterize the anatomy of news consumption on a global and international scale. We show that users tend to focus on a limited set of pages (selective exposure) eliciting a sharp and polarized community structure among news outlets. Moreover, we find similar patterns around the Brexit –the British referendum to leave the European Union– debate, where we observe the spontaneous emergence of two well segregated and polarized groups of users around news outlets. Our findings provide interesting insights into the determinants of polarization and the evolution of core narratives on online debating. Our main aim is to understand and map the information space on online social media by identifying non-trivial proxies for the early detection of massive informational cascades. Furthermore, by combining users traces, we are finally able to draft the main concepts and beliefs of the core narrative of an echo chamber and its related perceptions.

Keywords: information spreading, misinformation, narratives, online social networks, polarization

Procedia PDF Downloads 292

Authors: Rebecca Zahra, Joseph G. Vella, Ernest Cachia

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The notion of cloud computing is rapidly gaining ground in the IT industry and is appealing mostly due to making computing more adaptable and expedient whilst diminishing the total cost of ownership. This paper focuses on the software as a service (SaaS) architecture of cloud computing which is used for the outsourcing of databases with their associated business processes. One approach for offering SaaS is basing the system’s architecture on multi-tenancy. Multi-tenancy allows multiple tenants (users) to make use of the same single application instance. Their requests and configurations might then differ according to specific requirements met through tenant customisation through the software. Despite the known advantages, companies still feel uneasy to opt for the multi-tenancy with data security being a principle concern. The fact that multiple tenants, possibly competitors, would have their data located on the same server process and share the same database tables heighten the fear of unauthorised access. Security is a vital aspect which needs to be considered by application developers, database administrators, data owners and end users. This is further complicated in cloud-based multi-tenant system where boundaries must be established between tenants and additional access control models must be in place to prevent unauthorised cross-tenant access to data. Moreover, when altering the database state, the transactions need to strictly adhere to the tenant’s known business processes. This paper focuses on the fact that security in cloud databases should not be considered as an isolated issue. Rather it should be included in the initial phases of the database design and monitored continuously throughout the whole development process. This paper aims to identify a number of the most common security risks and threats specifically in the area of multi-tenant cloud systems. Issues and bottlenecks relating to security risks in cloud databases are surveyed. Some techniques which might be utilised to overcome them are then listed and evaluated. After a description and evaluation of the main security threats, this paper produces a list of software requirements to ensure that proper security policies are implemented by a software development team when designing and implementing a multi-tenant based SaaS. This would then assist the cloud service providers to define, implement, and manage security policies as per tenant customisation requirements whilst assuring security for the customers’ data.

Keywords: cloud computing, data management, multi-tenancy, requirements, security

Procedia PDF Downloads 157

Authors: Vijay Marisetty, Poonam Singh

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Research on the effect of director's network connections on investor welfare is inconclusive. Some studies suggest that directors' connections are beneficial, in terms of, improving earnings information, firms valuation for new investors. On the other hand, adverse effects of directorial networks are also reported, in terms of higher earnings management, options back dating fraud, reduction in firm performance, lower board monitoring. From regulatory perspective, the role of directorial networks on corporate welfare is crucial. Cognizant of the possible ill effects associated with directorial networks, large investors, for better representation on the boards, are building their own database of prospective directors who are highly qualified, however, sourced from outside the highly connected directorial labor market. For instance, following Dodd-Frank Reform Act, California Public Employees' Retirement Systems (CalPERs) has initiated a database for registering aspiring and highly qualified directors to nominate them for board seats (proxy access). Our paper stems from this background and tries to explore the chances of outside directors getting directorships who lack established network connections. The paper is able to identify such aspiring directors' information by accessing a unique Indian data sourced from an online portal that aims to match the supply of registered aspirants with the growing demand for outside directors in India. The online portal's tie-up with stock exchanges ensures firms to access the new pool of directors. Such direct access to the background details of aspiring directors over a period of 10 years, allows us to examine the chances of aspiring directors without corporate network, to enter directorial network. Using this resume data of 16105 aspiring corporate directors in India, who have no prior board experience in the directorial labor market, the paper analyses the entry dynamics in corporate directors' labor market. The database also allows us to investigate the value of corporate network by comparing non-network new entrants with incumbent networked directors. The study develops measures of network centrality and network degree based on merit, i.e. network of individuals belonging to elite educational institutions, like Indian Institute of Management (IIM) or Indian Institute of Technology (IIT) and based on job or company, i.e. network of individuals serving in the same company. The paper then measures the impact of these networks on the appointment of first time directors and subsequent appointment of directors. The paper reports the following main results: 1. The likelihood of becoming a corporate director, without corporate network strength, is only 1 out 100 aspirants. This is inspite of comparable educational background and similar duration of corporate experience; 2. Aspiring non-network directors' elite educational ties help them to secure directorships. However, for post-board appointments, their newly acquired corporate network strength overtakes as their main determinant for subsequent board appointments and compensation. The results thus highlight the limitations in increasing board diversity.

Keywords: aspiring corporate directors, board diversity, director labor market, director networks

Procedia PDF Downloads 313

Authors: Jessica Vasil'chuk, Elena Ivanova, Pavel Krechetov, Vladimir Litvinsky, Nadine Budantseva, Julia Chizhova, Yurij Vasil'chuk

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Carbonate minerals’ isotopic composition is widely used as a proxy for environmental parameters of the past. Pedogenic carbonate coatings on lower surfaces of coarse rock fragments are studied in order to indicate the climatic conditions and predominant vegetation under which they were formed. The purpose of the research is to characterize the isotopic composition of carbonate pedofeatures in soils of Minusink Hollow and estimate its correlation with isotopic composition of soil pore water, precipitation, vegetation and parent material. The samples of pedogenic carbonates, vegetation, carbonate parent material, soil water and precipitation water were analyzed using the Delta-V mass spectrometer with options of a gas bench and element analyser. The soils we studied are mainly Kastanozems that are poorly moisturized, therefore soil pore water was extracted by ethanol. Oxygen and carbon isotopic composition of pedogenic carbonates was analyzed in 3 key sites. Kazanovka Khakass state national reserve, Hankul salt lake, region of Sayanogorsk aluminum smelter. Vegetation photosynthetic pathway in the region is mainly C3. δ18O values of carbonate coatings in soils of Kazanovka vary in a range from −7.49 to −10.5‰ (vs V-PDB), and the smallest value −13.9‰ corresponds the coatings found between two buried soil horizons which 14C dates are 4.6 and 5.2 kyr BP. That may indicate cooler conditions of late Holocene than nowadays. In Sayanogorsk carbonates’ δ18O range is from −8.3 to −11.1‰ and near the Hankul Lake is from −9.0 to −10.2‰ all ranges are quite similar and may indicate coatings’ uniform formation conditions. δ13C values of carbonate coatings in Kazanovka vary from −2.5 to −6.7‰, the highest values correspond to the soils of Askiz and Syglygkug rivers former floodplains. For Sayanogorsk the range is from −4.9 to −6.8‰ and for Hankul from −2.3 to −5.7‰, where the highest value is for the modern salt crust. δ13C values of coatings strongly decrease from inner (older) to outer (younger) layers of coatings, that can indicate differences connected with the diffusion of organic material. Carbonate parent material δ18O value in the region vary from −11.1 to −12.0‰ and δ13C values vary from −4.9 to −5.7‰. Soil pore water δ18O values that determine the oxygen isotope composition of carbonates vary due to the processes of transpiration and mixing in the studied sites in a wide range of −2.0 to −13.5‰ (vs V-SMOW). Precipitation waters show δ18O values from -6.6‰ in May and -19.0‰ in January (snow) due to the temperature difference. The main conclusions are as follows: pedogenic carbonates δ13C values (−7…−2,5‰) show no correlation with modern C3 vegetation δ13C values (−30…−26‰), expected values under such vegetation are (−19…−15‰) but are closer to C4 vegetation. Late Holocene climate for the Minusinsk Hollow according to obtained data on isotope composition of carbonates and soil pore water chemical composition was dryer and cooler than present, that does not contradict with paleocarpology data obtained for the region. The research was supported by Russian Science Foundation (grant №14-27-00083).

Keywords: carbon, oxygen, pedogenic carbonates, South Siberia, stable isotopes

Procedia PDF Downloads 297

Authors: Omair Anas

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The Persian Gulf has been in turmoil for a long time since the colonial administration has handed over the role to the small and weak kings and emirs who were assured of protection in return of many economic and security promises to them. The regional order, Saudi Arabia evolved was a rentier regional order secured by an expansion of rentier economy and taking responsibility for much of the expenses of the regional order on behalf of relatively poor countries. The two oil booms helped the Saudi state to expand the 'rentier order' driven stability and bring the countries like Egypt, Jordan, Syria, and Palestine under its tutelage. The disruptive misadventure, however, came with Iran's proclamation of the Islamic Revolution in 1979 which it wanted to be exported to its 'un-Islamic and American puppet' Arab neighbours. For Saudi Arabia, even the challenge presented by the socialist-nationalist Arab dictators like Gamal Abdul Nasser and Hafez Al-Assad was not that much threatening to the Saudi Arabia’s then-defensive realism. In the Arab uprisings, the Gulf monarchies saw a wave of insecurity and Iran found it an opportune time to complete the revolutionary process it could not complete after 1979. An alliance of convenience and ideology between Iran and Islamist groups had the real potential to challenge both Saudi Arabia’s own security and its leadership in the region. The disruptive threat appeared at a time when the Saudi state had already sensed an impending crisis originating from the shifts in the energy markets. Low energy prices, declining global demands, and huge investments in alternative energy resources required Saudi Arabia to rationalize its economy according to changing the global political economy. The domestic Saudi reforms remained gradual until the death of King Abdullah in 2015. What is happening now in the region, the Qatar crisis, the Lebanon crisis and the Saudi-Iranian proxy war in Iraq, Syria, and Yemen has combined three immediate objectives, rationalising Saudi economy and most importantly, the resetting the Saudi royal power for Saudi Arabia’s longest-serving future King Mohammad bin Salman. The Saudi King perhaps has no time to wait and watch the power vacuum appearing because of Iran’s expansionist foreign policy. The Saudis appear to be employing an offensive realism by advancing a pro-active regional policy to counter Iran’s threatening influence amid disappearing Western security from the region. As the Syrian civil war is coming to a compromised end with ceding much ground to Iran-controlled militias, Hezbollah and Al-Hashad, the Saudi state has lost much ground in these years and the threat from Iranian proxies is more than a reality, more clearly in Bahrain, Iraq, Syria, and Yemen. This paper attempts to analyse the changing Saudi behaviour in the region, which, the author understands, is shaped by an offensive-realist approach towards finding a favourable security environment for the Saudi-led regional order, a post-rentier order perhaps.

Keywords: terrorism, Saudi Arabia, Rentier State, gulf crisis

Procedia PDF Downloads 138

Authors: África Vicario, Fernando J. Álvarez, Felipe Parralejo, Fernando Aranda

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The irrigation systems of traditional agriculture, such as gravity-fed irrigation, produce a great waste of water because, generally, there is no control over the amount of water supplied in relation to the water needed. The AIRON Project tries to solve this problem by implementing an IoT-based system to sensor the irrigation plots so that the state of the crops and the amount of water used for irrigation can be known remotely. The IoT system consists of a sensor network that measures the humidity of the soil, the weather conditions (temperature, relative humidity, wind and solar radiation) and the irrigation water flow. The communication between this network and a central gateway is conducted by means of long-range wireless communication that depends on the characteristics of the irrigation plot. The main objective of the AIRON project is to deploy an IoT sensor network in two different plots of the irrigation community of Aranjuez in the Spanish region of Madrid. The first plot is 2 km away from the central gateway, so LoRa has been used as the base communication technology. The problem with this plot is the absence of mains electric power, so devices with energy-saving modes have had to be used to maximize the external batteries' use time. An ESP32 SOC board with a LoRa module is employed in this case to gather data from the sensor network and send them to a gateway consisting of a Raspberry Pi with a LoRa hat. The second plot is located 18 km away from the gateway, a range that hampers the use of LoRa technology. In order to establish reliable communication in this case, the long-term evolution (LTE) standard is used, which makes it possible to reach much greater distances by using the cellular network. As mains electric power is available in this plot, a Raspberry Pi has been used instead of the ESP32 board to collect sensor data. All data received from the two plots are stored on a proprietary server located at the irrigation management company's headquarters. The analysis of these data by means of machine learning algorithms that are currently under development should allow a short-term prediction of the irrigation water demand that would significantly reduce the waste of this increasingly valuable natural resource. The major finding of this work is the real possibility of deploying a remote sensing system for irrigated plots by using Commercial-Off-The-Shelf (COTS) devices, easily scalable and adaptable to design requirements such as the distance to the control center or the availability of mains electrical power at the site.

Keywords: internet of things, irrigation water control, LoRa, LTE, smart farming

Procedia PDF Downloads 87

Authors: Muhammad Zia Ullah Baig, Atiq Uz Zama

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The motivation of the project is to facilitate the governance body, as well as the common man in his/her daily life consuming product rates, to easily monitor the expense, to control the budget with the help of single SMS (message), e-mail facility, and to manage governance body by task management system. The system will also be capable of finding irregularities being done by the concerned department in mitigating the complaints generated by the customer and also provide a solution to overcome problems. We are building a system that easily controls the price control system of any country, we will feeling proud to give this system free of cost to Indian Government also. The system is able to easily manage and control the price control department of government all over the country. Price control department run in different cities under City District Government, so the system easily run in different cities with different SMS Code and decentralize Database ensure the non-functional requirement of system (scalability, reliability, availability, security, safety). The customer request for the government official price list with respect to his/her city SMS code (price list of all city available on website or application), the server will forward the price list through a SMS, if the product is not available according to the price list the customer generate a complaint through an SMS or using website/smartphone application, complaint is registered in complaint database and forward to inspection department when the complaint is entertained, the inspection department will forward a message about the complaint to customer. Inspection department physically checks the seller who does not follow the price list, but the major issue of the system is corruption, may be inspection officer will take a bribe and resolve the complaint (complaint is fake) in that case the customer will not use the system. The major issue of the system is to distinguish the fake and real complain and fight for corruption in the department. To counter the corruption, our strategy is to rank the complain if the same type of complaint is generated the complaint is in high rank and the higher authority will also notify about that complain, now the higher authority of department have reviewed the complaint and its history, the officer who resolve that complaint in past and the action against the complaint, these data will help in decision-making process, if the complaint was resolved because the officer takes bribe, the higher authority will take action against that officer. When the price of any good is decided the market/former representative is also there, with the mutual understanding of both party the price is decided, the system facilitate the decision-making process. The system shows the price history of any goods, inflation rate, available supply, demand, and the gap between supply and demand, these data will help to allot for the decision-making process.

Keywords: price control, goods, government, inspection, department, customer, employees

Procedia PDF Downloads 412

Authors: Ahmed Hossam ElMolla, Mohamed Hatem Saleh, Hamza Mostafa, Lara Mamdouh, Yassin Wael

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Artificial intelligence (AI) is reshaping industries, and its potential to revolutionize renewable energy and data center operations is immense. By harnessing AI's capabilities, we can optimize energy consumption, predict fluctuations in renewable energy generation, and improve the efficiency of data center infrastructure. This convergence of technologies promises a future where energy is managed more intelligently, sustainably, and cost-effectively. The integration of AI into renewable energy systems unlocks a wealth of opportunities. Machine learning algorithms can analyze vast amounts of data to forecast weather patterns, solar irradiance, and wind speeds, enabling more accurate energy production planning. AI-powered systems can optimize energy storage and grid management, ensuring a stable power supply even during intermittent renewable generation. Moreover, AI can identify maintenance needs for renewable energy infrastructure, preventing costly breakdowns and maximizing system lifespan. Data centers, which consume substantial amounts of energy, are prime candidates for AI-driven optimization. AI can analyze energy consumption patterns, identify inefficiencies, and recommend adjustments to cooling systems, server utilization, and power distribution. Predictive maintenance using AI can prevent equipment failures, reducing energy waste and downtime. Additionally, AI can optimize data placement and retrieval, minimizing energy consumption associated with data transfer. As AI transforms renewable energy and data center operations, modified Key Performance Indicators (KPIs) will emerge. Traditional metrics like energy efficiency and cost-per-megawatt-hour will continue to be relevant, but additional KPIs focused on AI's impact will be essential. These might include AI-driven cost savings, predictive accuracy of energy generation and consumption, and the reduction of carbon emissions attributed to AI-optimized operations. By tracking these KPIs, organizations can measure the success of their AI initiatives and identify areas for improvement. Ultimately, the synergy between AI, renewable energy, and data centers holds the potential to create a more sustainable and resilient future. By embracing these technologies, we can build smarter, greener, and more efficient systems that benefit both the environment and the economy.

Keywords: data center, artificial intelligence, renewable energy, energy efficiency, sustainability, optimization, predictive analytics, energy consumption, energy storage, grid management, data center optimization, key performance indicators, carbon emissions, resiliency

Procedia PDF Downloads 36

Authors: D. Serero, L. Couton, J. D. Parisse, R. Leroy

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In urban planning, an increasing number of cities require wind analysis to verify comfort of public spaces and around buildings. These studies are made using computer fluid dynamic simulation (CFD). However, this technique is often based on wind information taken from meteorological stations located at several kilometers of the spot of analysis. The approximated input data on project surroundings produces unprecise results for this type of analysis. They can only be used to get general behavior of wind in a zone but not to evaluate precise wind speed. This paper presents another approach to this problem, based on collecting wind data and generating an urban wind cartography using connected ultrasound anemometers. They are wireless devices that send immediate data on wind to a remote server. Assembled in array, these devices generate geo-localized data on wind such as speed, temperature, pressure and allow us to compare wind behavior on a specific site or building. These Netatmo-type anemometers communicate by wifi with central equipment, which shares data acquired by a wide variety of devices such as wind speed, indoor and outdoor temperature, rainfall, and sunshine. Beside its precision, this method extracts geo-localized data on any type of site that can be feedback looped in the architectural design of a building or a public place. Furthermore, this method allows a precise calibration of a virtual wind tunnel using numerical aeraulic simulations (like STAR CCM + software) and then to develop the complete volumetric model of wind behavior over a roof area or an entire city block. The paper showcases connected ultrasonic anemometers, which were implanted for an 18 months survey on four study sites in the Grand Paris region. This case study focuses on Paris as an urban environment with multiple historical layers whose diversity of typology and buildings allows considering different ways of capturing wind energy. The objective of this approach is to categorize the different types of wind in urban areas. This, particularly the identification of the minimum and maximum wind spectrum, helps define the choice and performance of wind energy capturing devices that could be implanted there. The localization on the roof of a building, the type of wind, the altimetry of the device in relation to the levels of the roofs, the potential nuisances generated. The method allows identifying the characteristics of wind turbines in order to maximize their performance in an urban site with turbulent wind.

Keywords: computer fluid dynamic simulation in urban environment, wind energy harvesting devices, net-zero energy building, urban wind behavior simulation, advanced building skin design methodology

Procedia PDF Downloads 103

Authors: Wisam H. Benamer, Ehab A. Elfallah, Mohamed A. Elshaari, Farag A. Elshaari

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A challenge for laboratories is to provide bacterial identification and antibiotic sensitivity results within a short time. Hence, advancement in the required technology is desirable to improve timing, accuracy and quality. Even with the current advances in methods used for both phenotypic and genotypic identification of bacteria the need is there to develop method(s) that enhance the outcome of bacteriology laboratories in accuracy and time. The hypothesis introduced here is based on the assumption that the chromosome of any bacteria contains unique sequences that can be used for its identification and typing. The outcome of a pilot study designed to test this hypothesis is reported in this manuscript. Methods: The complete chromosome sequences of several bacterial species were downloaded to use as search targets for unique sequences. Visual basic and SQL server (2014) were used to generate a complete set of 18-base long primers, a process started with reverse translation of randomly chosen 6 amino acids to limit the number of the generated primers. In addition, the software used to scan the downloaded chromosomes using the generated primers for similarities was designed, and the resulting hits were classified according to the number of similar chromosomal sequences, i.e., unique or otherwise. Results: All primers that had identical/similar sequences in the selected genome sequence(s) were classified according to the number of hits in the chromosomes search. Those that were identical to a single site on a single bacterial chromosome were referred to as unique. On the other hand, most generated primers sequences were identical to multiple sites on a single or multiple chromosomes. Following scanning, the generated primers were classified based on ability to differentiate between medically important bacterial and the initial results looks promising. Conclusion: A simple strategy that started by generating primers was introduced; the primers were used to screen bacterial genomes for match. Primer(s) that were uniquely identical to specific DNA sequence on a specific bacterial chromosome were selected. The identified unique sequence can be used in different molecular diagnostic techniques, possibly to identify bacteria. In addition, a single primer that can identify multiple sites in a single chromosome can be exploited for region or genome identification. Although genomes sequences draft of isolates of organism DNA enable high throughput primer design using alignment strategy, and this enhances diagnostic performance in comparison to traditional molecular assays. In this method the generated primers can be used to identify an organism before the draft sequence is completed. In addition, the generated primers can be used to build a bank for easy access of the primers that can be used to identify bacteria.

Keywords: bacteria chromosome, bacterial identification, sequence, primer generation

Procedia PDF Downloads 193

Authors: Stephanie Giordano, Rosa Plasencia

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In the USA, in 2013, public service systems such as Medicaid, aging, and disability systems undertook an effort to measure the quality of service delivery by examining the experiences and outcomes of those receiving public services. The goal of this effort was to develop a survey to measure the experiences and outcomes of those receiving public services, with the goal of measuring system performance for quality improvement. The performance indicators were developed through with input from directors of state aging and disability service systems, along with experts and stakeholders in the field across the United States. This effort, National Core Indicators –Aging and Disabilities (NCI-AD), grew out of National Core Indicators –Intellectual and Developmental Disabilities, an effort to measure developmental disability (DD) systems across the States. The survey tool and administration protocol underwent multiple rounds of testing and revision between 2013 and 2015. The measures in the final tool – called the Adult Consumer Survey (ACS) – emphasize not just important indicators of healthcare access and personal safety but also includes indicators of system quality based on person-centered outcomes. These measures indicate whether service systems support older adults and people with disabilities to live where they want, maintain relationships and engage in their communities and have choice and control in their everyday lives. Launched in 2015, the NCI-AD Adult Consumer Survey is now used in 23 states in the US. Surveys are conducted by NCI-AD trained surveyors via direct conversation with a person receiving public long-term services and supports (LTSS). Until 2020, surveys were only conducted in person. However, after a pilot to test the reliability of videoconference and telephone survey modes, these modes were adopted as an acceptable practice. The nature of the survey is that of a “guided conversation” survey administration allows for surveyor to use wording and terminology that is best understand by the person surveyed. The survey includes a subset of questions that may be answered by a proxy respondent who knows the person well if the person is receiving services in unable to provide valid responses on their own. Surveyors undergo a standardized training on survey administration to ensure the fidelity of survey administration. In addition to the main survey section, a Background Information section collects data on personal and service-related characteristics of the person receiving services; these data are typically collected through state administrative record. This information is helps provide greater context around the characteristics of people receiving services. It has also been used in conjunction with outcomes measures to look at disparity (including by race and ethnicity, gender, disability, and living arrangements). These measures of quality are critical for public service delivery systems to understand the unique needs of the population of older adults and improving the lives of older adults as well as people with disabilities. Participating states may use these data to identify areas for quality improvement within their service delivery systems, to advocate for specific policy change, and to better understand the experiences of specific populations of people served.

Keywords: quality of life, long term services and supports, person-centered practices, aging and disability research, survey methodology

Procedia PDF Downloads 122

Authors: Sakshi Piplani, Ajit Kumar

Abstract:

Valproic acid (VPA) is the first synthetic therapeutic agent used to treat epileptic disorders, which account for affecting nearly 1% world population. Teratogenicity caused by VPA has prompted the search for next generation drug with better efficacy and lower side effects. Recent studies have posed HDAC8 as direct target of VPA that causes the teratogenic effect in foetus. We have employed molecular dynamics (MD) and docking simulations to understand the binding mode of VPA and their analogues onto HDAC8. A total of twenty 3D-structures of human HDAC8 isoforms were selected using BLAST-P search against PDB. Multiple sequence alignment was carried out using ClustalW and PDB-3F07 having least missing and mutated regions was selected for study. The missing residues of loop region were constructed using MODELLER and energy was minimized. A set of 216 structural analogues (>90% identity) of VPA were obtained from Pubchem and ZINC database and their energy was optimized with Chemsketch software using 3-D CHARMM-type force field. Four major neurotransmitters (GABAt, SSADH, α-KGDH, GAD) involved in anticonvulsant activity were docked with VPA and its analogues. Out of 216 analogues, 75 were selected on the basis of lower binding energy and inhibition constant as compared to VPA, thus predicted to have anti-convulsant activity. Selected hHDAC8 structure was then subjected to MD Simulation using licenced version YASARA with AMBER99SB force field. The structure was solvated in rectangular box of TIP3P. The simulation was carried out with periodic boundary conditions and electrostatic interactions and treated with Particle mesh Ewald algorithm. pH of system was set to 7.4, temperature 323K and pressure 1atm respectively. Simulation snapshots were stored every 25ps. The MD simulation was carried out for 20ns and pdb file of HDAC8 structure was saved every 2ns. The structures were analysed using castP and UCSF Chimera and most stabilized structure (20ns) was used for docking study. Molecular docking of 75 selected VPA-analogues with PDB-3F07 was performed using AUTODOCK4.2.6. Lamarckian Genetic Algorithm was used to generate conformations of docked ligand and structure. The docking study revealed that VPA and its analogues have more affinity towards ‘hydrophobic active site channel’, due to its hydrophobic properties and allows VPA and their analogues to take part in van der Waal interactions with TYR24, HIS42, VAL41, TYR20, SER138, TRP137 while TRP137 and SER138 showed hydrogen bonding interaction with VPA-analogues. 14 analogues showed better binding affinity than VPA. ADMET SAR server was used to predict the ADMET properties of selected VPA analogues for predicting their druggability. On the basis of ADMET screening, 09 molecules were selected and are being used for in-vivo evaluation using Danio rerio model.

Keywords: HDAC8, docking, molecular dynamics simulation, valproic acid

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Authors: Paulo Roberto Vasconcellos-Silva

Abstract:

The "Janeiro Roxo" (Purple January) campaign in Brazil aims to promote awareness of leprosy and its early symptoms. The COVID-19 pandemic has adversely affected institutional campaigns, mostly considering leprosy a neglected disease by the media. Google Trends (GT) is a tool that tracks user searches on Google, providing insights into the popularity of specific search terms. Our prior research has categorized online searches into two types: "Reactive searches," driven by transient campaign-related stimuli, and "Proactive searches," driven by personal interest in early symptoms and self-diagnosis. Using GT we studied: (i) the impact of "Janeiro Roxo" on public interest in leprosy (assessed through reactive searches) and its early symptoms (evaluated through proactive searches) over the past five years; (ii) changes in public interest during and after the COVID-19 pandemic; (iii) patterns in the dynamics of reactive and proactive searches Methods: We used GT's "Relative Search Volume" (RSV) to gauge public interest on a scale from 0 to 100. "HANSENÍASE" (HAN) was a proxy for reactive searches, and "HANSENÍASE SINTOMAS" (leprosy symptoms) (H.SIN) for proactive searches (interest in leprosy or in self-diagnosis). We analyzed 261 weeks of data from 2018 to 2023, using polynomial trend lines to model trends over this period. Analysis of Variance (ANOVA) was used to compare weekly RSV, monthly (MM) and annual means (AM). Results: Over a span of 261 weeks, there was consistently higher Relative Search Volume (RSV) for HAN compared to H.SIN. Both search terms exhibited their highest (MM) in January months during all periods. COVID-19 pandemic: a decline was observed during the pandemic years (2020-2021). There was a 24% decrease in RSV for HAN and a 32.5% decrease for H.SIN. Both HAN and H.SIN regained their pre-pandemic search levels in January 2022-2023. Breakpoints indicated abrupt changes - in the 26th week (February 2019), 55th and 213th weeks (September 2019 and 2022) related to September regional campaigns (interrupted in 2020-2021). Trend lines for HAN exhibited an upward curve between 33rd-45th week (April to June 2019), a pandemic-related downward trend between 120th-136th week (December 2020 to March 2021), and an upward trend between 220th-240th week (November 2022 to March 2023). Conclusion: The "Janeiro Roxo" campaign, along with other media-driven activities, exerts a notable influence on both reactive and proactive searches related to leprosy topics. Reactive searches, driven by campaign stimuli, significantly outnumber proactive searches. Despite the interruption of the campaign due to the pandemic, there was a subsequent resurgence in both types of searches. The recovery observed in reactive and proactive searches post-campaign interruption underscores the effectiveness of such initiatives, particularly at the national level. This suggests that regional campaigns aimed at leprosy awareness can be considered highly successful in stimulating proactive public engagement. The evaluation of internet-based campaign programs proves valuable not only for assessing their impact but also for identifying the needs of vulnerable regions. These programs can play a crucial role in integrating regions and highlighting their needs for assistance services in the context of leprosy awareness.

Keywords: health communication, leprosy, health campaigns, information seeking behavior, Google Trends, reactive searches, proactive searches, leprosy early identification

Procedia PDF Downloads 63

Authors: Dian Zhang, Brendan Heery, Maria O’Neill, Ciprian Briciu-Burghina, Noel E. O’Connor, Fiona Regan

Abstract:

Recent developments in sensors, wireless data communication and the cloud computing have brought the sensor web to a whole new generation. The introduction of the concept of ‘Internet of Thing (IoT)’ has brought the sensor research into a new level, which involves the developing of long lasting, low cost, environment friendly and smart sensors; new wireless data communication technologies; big data analytics algorithms and cloud based solutions that are tailored to large scale smart sensor network. The next generation of smart sensor network consists of several layers: physical layer, where all the smart sensors resident and data pre-processes occur, either on the sensor itself or field gateway; data transmission layer, where data and instructions exchanges happen; the data process layer, where meaningful information is extracted and organized from the pre-process data stream. There are many definitions of smart sensor, however, to summarize all these definitions, a smart sensor must be Intelligent and Adaptable. In future large scale sensor network, collected data are far too large for traditional applications to send, store or process. The sensor unit must be intelligent that pre-processes collected data locally on board (this process may occur on field gateway depends on the sensor network structure). In this case study, three smart sensing methods, corresponding to simple thresholding, statistical model and machine learning based MoPBAS method, are introduced and their strength and weakness are discussed as an introduction to the smart sensing concept. Data fusion, the integration of data and knowledge from multiple sources, are key components of the next generation smart sensor network. For example, in the water level monitoring system, weather forecast can be extracted from external sources and if a heavy rainfall is expected, the server can send instructions to the sensor notes to, for instance, increase the sampling rate or switch on the sleeping mode vice versa. In this paper, we describe the deployment of 11 affordable water level sensors in the Dublin catchment. The objective of this paper is to use the deployed river level sensor network at the Dodder catchment in Dublin, Ireland as a case study to give a vision of the next generation of a smart sensor network for flood monitoring to assist agencies in making decisions about deploying resources in the case of a severe flood event. Some of the deployed sensors are located alongside traditional water level sensors for validation purposes. Using the 11 deployed river level sensors in a network as a case study, a vision of the next generation of smart sensor network is proposed. Each key component of the smart sensor network is discussed, which hopefully inspires the researchers who are working in the sensor research domain.

Keywords: smart sensing, internet of things, water level sensor, flooding

Procedia PDF Downloads 383