Search results for: statistical distribution

Authors: Rajkumar Ghosh

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Earthquakes are natural disasters that pose a significant risk to human life and infrastructure. Effective earthquake mitigation measures require a thorough understanding of the dynamics of seismic occurrences, including thrust movement. Traditionally, estimating thrust movement has relied on typical techniques that may not capture the full complexity of these events. Therefore, investigating alternative approaches, such as incorporating out-of-sequence thrust movement data, could enhance earthquake mitigation strategies. This review aims to provide an overview of the applications of out-of-sequence thrust movement in earthquake mitigation. By examining existing research and studies, the objective is to understand how precise estimation of thrust movement can contribute to improving structural design, analyzing infrastructure risk, and developing early warning systems. The study demonstrates how to estimate out-of-sequence thrust movement using multiple data sources, including GPS measurements, satellite imagery, and seismic recordings. By analyzing and synthesizing these diverse datasets, researchers can gain a more comprehensive understanding of thrust movement dynamics during seismic occurrences. The review identifies potential advantages of incorporating out-of-sequence data in earthquake mitigation techniques. These include improving the efficiency of structural design, enhancing infrastructure risk analysis, and developing more accurate early warning systems. By considering out-of-sequence thrust movement estimates, researchers and policymakers can make informed decisions to mitigate the impact of earthquakes. This study contributes to the field of seismic monitoring and earthquake risk assessment by highlighting the benefits of incorporating out-of-sequence thrust movement data. By broadening the scope of analysis beyond traditional techniques, researchers can enhance their knowledge of earthquake dynamics and improve the effectiveness of mitigation measures. The study collects data from various sources, including GPS measurements, satellite imagery, and seismic recordings. These datasets are then analyzed using appropriate statistical and computational techniques to estimate out-of-sequence thrust movement. The review integrates findings from multiple studies to provide a comprehensive assessment of the topic. The study concludes that incorporating out-of-sequence thrust movement data can significantly enhance earthquake mitigation measures. By utilizing diverse data sources, researchers and policymakers can gain a more comprehensive understanding of seismic dynamics and make informed decisions. However, challenges exist, such as data quality difficulties, modelling uncertainties, and computational complications. To address these obstacles and improve the accuracy of estimates, further research and advancements in methodology are recommended. Overall, this review serves as a valuable resource for researchers, engineers, and policymakers involved in earthquake mitigation, as it encourages the development of innovative strategies based on a better understanding of thrust movement dynamics.

Keywords: earthquake, out-of-sequence thrust, disaster, human life

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Authors: M. Cardenas-Garcia, P. P. Gonzalez-Perez

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Intercellular communication is a necessary condition for cellular functions and it allows a group of cells to survive as a population. Throughout this interaction, the cells work in a coordinated and collaborative way which facilitates their survival. In the case of cancerous cells, these take advantage of intercellular communication to preserve their malignancy, since through these physical unions they can send signs of malignancy. The Wnt/β-catenin signaling pathway plays an important role in the formation of intercellular communications, being also involved in a large number of cellular processes such as proliferation, differentiation, adhesion, cell survival, and cell death. The modeling and simulation of cellular signaling systems have found valuable support in a wide range of modeling approaches, which cover a wide spectrum ranging from mathematical models; e.g., ordinary differential equations, statistical methods, and numerical methods– to computational models; e.g., process algebra for modeling behavior and variation in molecular systems. Based on these models, different simulation tools have been developed from mathematical ones to computational ones. Regarding cellular and molecular processes in cancer, its study has also found a valuable support in different simulation tools that, covering a spectrum as mentioned above, have allowed the in silico experimentation of this phenomenon at the cellular and molecular level. In this work, we simulate and explore the complex interaction patterns of intercellular communication in cancer cells using the Cellulat bioinformatics tool, a computational simulation tool developed by us and motivated by two key elements: 1) a biochemically inspired model of self-organizing coordination in tuple spaces, and 2) the Gillespie’s algorithm, a stochastic simulation algorithm typically used to mimic systems of chemical/biochemical reactions in an efficient and accurate way. The main idea behind the Cellulat simulation tool is to provide an in silico experimentation environment that complements and guides in vitro experimentation in intra and intercellular signaling networks. Unlike most of the cell signaling simulation tools, such as E-Cell, BetaWB and Cell Illustrator which provides abstractions to model only intracellular behavior, Cellulat is appropriate for modeling both intracellular signaling and intercellular communication, providing the abstractions required to model –and as a result, simulate– the interaction mechanisms that involve two or more cells, that is essential in the scenario discussed in this work. During the development of this work we made evident the application of our computational simulation tool (Cellulat) for the modeling and simulation of intercellular communication between normal and cancerous cells, and in this way, propose key molecules that may prevent the arrival of malignant signals to the cells that surround the tumor cells. In this manner, we could identify the significant role that has the Wnt/β-catenin signaling pathway in cellular communication, and therefore, in the dissemination of cancer cells. We verified, using in silico experiments, how the inhibition of this signaling pathway prevents that the cells that surround a cancerous cell are transformed.

Keywords: cancer cells, in silico approach, intercellular communication, key molecules, modeling and simulation

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

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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

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Authors: Tom Turner

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The recent financial crisis in 2008 and the growing inequality in developed industrial societies would appear to present significant challenges to capitalism and the free market. Yet there have been few substantial mainstream political or economic challenges to the dominant capitalist and market paradigm to-date. There is no dearth of critical and theoretical (academic) analyses regarding the prevailing systems failures. Yet despite the growing inequality in the developed industrial societies and the financial crisis in 2008 few commentators have advocated the comprehensive socialization or state ownership of the means of production to our knowledge – a core principle of radical Marxism in the 19th and early part of the 20th century. Undoubtedly the experience in the Soviet Union and satellite countries in the 20th century has cast a dark shadow over the notion of centrally controlled economies and state ownership of the means of production. In this paper, we explore the history of a doctrine advocating the socialization or state ownership of the means of production that was central to Marxism and socialism generally. Indeed this doctrine provoked an intense and often acrimonious debate especially for left-wing parties throughout the 20th century. The debate within the political economy tradition has historically tended to divide into a radical and a revisionist approach to changing or reforming capitalism. The radical perspective views the conflict of interest between capital and labor as a persistent and insoluble feature of a capitalist society and advocates the public or state ownership of the means of production. Alternatively, the revisionist perspective focuses on issues of distribution rather than production and emphasizes the possibility of compromise between capital and labor in capitalist societies. Over the 20th century, the radical perspective has faded and even the social democratic revisionist tradition has declined in recent years. We conclude with the major challenges that confront both the radical and revisionist perspectives in the development of viable policy agendas in mature developed democratic societies. Additionally, we consider whether state ownership of the means of production still has relevance in the 21st century and to what extent state ownership is off the agenda as a political issue in the political mainstream in developed industrial societies. A central argument in the paper is that state ownership of the means of production is unlikely to feature as either a practical or theoretical solution to the problems of capitalism post the financial crisis among mainstream political parties of the left. Although the focus here is solely on the shifting views of the radical and revisionist socialist perspectives in the western European tradition the analysis has relevance for the wider socialist movement.

Keywords: sate ownership, ownership means of production, radicals, revisionists

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Authors: Jaroslav Kraus

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Spatial information about demographic processes are a standard part of outputs in the Czech Republic. That was also the case of Population and Housing Census which was held on 2011. This is a starting point for a follow up study devoted to two basic types of households: single person households and households of one completed family. Single person households and one family households create more than 80 percent of all households, but the share and spatial structure is in long-term changing. The increase of single households is results of long-term fertility decrease and divorce increase, but also possibility of separate living. There are regions in the Czech Republic with traditional demographic behavior, and regions like capital Prague and some others with changing pattern. Population census is based - according to international standards - on the concept of currently living population. Three types of geospatial approaches will be used for analysis: (i) firstly measures of geographic distribution, (ii) secondly mapping clusters to identify the locations of statistically significant hot spots, cold spots, spatial outliers, and similar features and (iii) finally analyzing pattern approach as a starting point for more in-depth analyses (geospatial regression) in the future will be also applied. For analysis of this type of data, number of households by types should be distinct objects. All events in a meaningful delimited study region (e.g. municipalities) will be included in an analysis. Commonly produced measures of central tendency and spread will include: identification of the location of the center of the point set (by NUTS3 level); identification of the median center and standard distance, weighted standard distance and standard deviational ellipses will be also used. Identifying that clustering exists in census households datasets does not provide a detailed picture of the nature and pattern of clustering but will be helpful to apply simple hot-spot (and cold spot) identification techniques to such datasets. Once the spatial structure of households will be determined, any particular measure of autocorrelation can be constructed by defining a way of measuring the difference between location attribute values. The most widely used measure is Moran’s I that will be applied to municipal units where numerical ratio is calculated. Local statistics arise naturally out of any of the methods for measuring spatial autocorrelation and will be applied to development of localized variants of almost any standard summary statistic. Local Moran’s I will give an indication of household data homogeneity and diversity on a municipal level.

Keywords: census, geo-demography, households, the Czech Republic

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Authors: Austin P. Hopkins, R. Daren Harmel, Jim A Ippolito, P. J. A. Kleinman, D. Sahoo

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Field-scale runoff and water quality data are critical to understanding the fate and transport of nutrients applied to agricultural lands and minimizing their off-site transport because it is at that scale that agricultural management decisions are typically made based on hydrologic, soil, and land use factors. However, regional influences such as precipitation, temperature, and prevailing cropping systems and land use patterns also impact nutrient runoff. In the present study, the recently-updated MANAGE (Measured Annual Nutrient loads from Agricultural Environments) database was used to conduct an ecoregion-level analysis of nitrogen and phosphorus runoff from agricultural lands in the North America. Specifically, annual N and P runoff loads for cropland and grasslands in North American Level II EPA ecoregions were presented, and the impact of factors such as land use, tillage, and fertilizer timing and placement on N and P runoff were analyzed. Specifically we compiled annual N and P runoff load data (i.e., dissolved, particulate, and total N and P, kg/ha/yr) for each Level 2 EPA ecoregion and for various agricultural management practices (i.e., land use, tillage, fertilizer timing, fertilizer placement) within each ecoregion to showcase the analyses possible with the data in MANAGE. Potential differences in N and P runoff loads were evaluated between and within ecoregions with statistical and graphical approaches. Non-parametric analyses, mainly Mann-Whitney tests were conducted on median values weighted by the site years of data utilizing R because the data were not normally distributed, and we used Dunn tests and box and whisker plots to visually and statistically evaluate significant differences. Out of the 50 total North American Ecoregions, 11 were found that had significant data and site years to be utilized in the analysis. When examining ecoregions alone, it was observed that ER 9.2 temperate prairies had a significantly higher total N at 11.7 kg/ha/yr than ER 9.4 South Central Semi Arid Prairies with a total N of 2.4. When examining total P it was observed that ER 8.5 Mississippi Alluvial and Southeast USA Coastal Plains had a higher load at 3.0 kg/ha/yr than ER 8.2 Southeastern USA Plains with a load of 0.25 kg/ha/yr. Tillage and Land Use had severe impacts on nutrient loads. In ER 9.2 Temperate Prairies, conventional tillage had a total N load of 36.0 kg/ha/yr while conservation tillage had a total N load of 4.8 kg/ha/yr. In all relevant ecoregions, when corn was the predominant land use, total N levels significantly increased compared to grassland or other grains. In ER 8.4 Ozark-Ouachita, Corn had a total N of 22.1 kg/ha/yr while grazed grassland had a total N of 2.9 kg/ha/yr. There are further intricacies of the interactions that agricultural management practices have on one another combined with ecological conditions and their impacts on the continental aquatic nutrient loads that still need to be explored. This research provides a stepping stone to further understanding of land and resource stewardship and best management practices.

Keywords: water quality, ecoregions, nitrogen, phosphorus, agriculture, best management practices, land use

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Authors: Maja Martinovic, Valentina Zarkovic, Hrvoje Maljak

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Europe is one of the most popular tourist destinations in the world, in which tourism occupies a significant place among the most relevant economic activities, and this applies to the Republic of Croatia as well. Based on this study, the authors intended to encourage and support the creation of an effective tourism policy in Croatia that would be based on the profiling of certain target groups. Another objective was to compare the results obtained from the customer analysis with the market analysis of the tourism industry in Croatia. The objective is to adapt the current tourist offer according to the identified needs and expectations of a particular tourist group in order to increase the attractiveness of Croatia as a tourist destination and motivate greater attendance of the targeted tourist groups. The current research was oriented towards the Russian market as the target group. Therefore, the authors wanted to encourage a discussion on how to attract more Russian guests. Consequently, the intention of the research was a detailed analysis of Russian tourists, in order to gain a better understanding of their travelling motives and tendencies. Furthermore, attention was paid to the expectations of Russian customers and to compare them with the Croatian tourist offer, and to determine whether there is a possibility for an overlap. The method used to obtain the information required was a survey conducted among Russian citizens about their travelling habits. The research was carried out on the basis of 166 participants of different age, gender, profession and income group. The sampling and distribution of the survey took place between May and July 2016. The results provided from the research indicate that Croatian tourism has certain unrealized potential considering the popularization of Croatia as a tourist destination, and there is a capacity for increasing the revenues within the group of Russian tourists. Such a conclusion is based on the fact that the Croatian tourist offer and the preferences of the Russian guests are compatible, i.e. they overlap in many aspects. The results demonstrate that beautiful nature, cultural and historical heritage as well as the sun and sea, play a leading role in attracting more Russian tourists. It is precisely these elements that form the three pillars of the Croatian tourist offer. On the other hand, the profiling revealed that the most desirable destinations for the Russian guests are Italy and Spain, both of which provide the same main tourist attractions as Croatia. Therefore, the focus of the strategic ideas given in the paper shifted to other tourism segments, such as type of accommodation, sales channels, travel motives, additional offer and seasonality etc., in order to gain advantage in the Russian market, the Mediterranean region and tourism in general. The purpose of the research is to serve as a foundation for analysing the attractiveness of the other tourist destinations in the Russian market, as well as to be a general basis for a more detailed profiling of the various specific target groups of the Russian and other tourist groups.

Keywords: Croatia, Russian market, target groups, tourism, tourist destination

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Authors: Tsedekech Gebremeskel Weldmichael, Tamas Szegi, Lubangakene Denish, Ravi Kumar Gangwar, Erika Micheli, Barbara Simon

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Following the 1992 Earth Summit in Rio de Janeiro, soil biodiversity has been recognized globally as a crucial player in guaranteeing the functioning of soil and a provider of several ecosystem services essential for human well-being. The microbial fraction of the soil is a vital component of soil fertility as soil microbes play key roles in soil aggregate formation, nutrient cycling, humification, and degradation of pollutants. Soil fauna, such as earthworms, have huge impacts on soil organic matter dynamics, nutrient cycling, and infiltration and distribution of water in the soil. Currently, land-use change has been a global concern as evidence accumulates that it adversely affects soil biodiversity and the associated ecosystem goods and services. In this study, we examined the patterns of soil microbial respiration (SMR) and earthworm (abundance, biomass, and species richness) across three land-use types (grassland, arable land, and forest) in Hungary. The objectives were i) to investigate whether there is a significant difference in SMR and earthworm (abundance, biomass, and species richness) among land-use types. ii) to determine the key soil properties that best predict the variation in SMR and earthworm communities. Soil samples, to a depth of 25 cm, were collected from the surrounding areas of seven soil profiles. For physicochemical parameters, soil organic matter (SOM), pH, CaCO₃, E₄/E₆, available nitrogen (NH₄⁺-N and NO₃⁻-N), potassium (K₂O), phosphorus (P₂O₅), exchangeable Ca²⁺, Mg²⁺, soil moisture content (MC) and bulk density were measured. The analysis of SMR was determined by basal respiration method, and the extraction of earthworms was carried out by hand sorting method as described by ISO guideline. The results showed that there was no statistically significant difference among land-use types in SMR (p > 0.05). However, the highest SMR was observed in grassland soils (11.77 mgCO₂ 50g⁻¹ soil 10 days⁻¹) and lowest in forest soils (8.61 mgCO₂ 50g⁻¹ soil 10 days⁻¹). SMR had strong positive correlations with exchangeable Ca²⁺ (r = 0.80), MC (r = 0.72), and exchangeable Mg²⁺(r = 0.69). We found a pronounced variation in SMR among soil texture classes (p < 0.001), where the highest value in silty clay loam soils and the lowest in sandy soils. This study provides evidence that agricultural activities can negatively influence earthworm communities, in which the arable land had significantly lower earthworm communities compared to forest and grassland respectively. Overall, in our study, land use type had minimal effects on SMR whereas, earthworm communities were profoundly influenced by land-use type particularly agricultural activities related to tillage. Exchangeable Ca²⁺, MC, and texture were found to be the key drivers of the variation in SMR.

Keywords: earthworm community, land use, soil biodiversity, soil microbial respiration, soil property

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Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

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Authors: Dino Carpentras, Paul Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is dedicated to modeling the dynamic evolution of people's opinions. Models in this field are based on a micro-dynamic rule, which determines how people update their opinion when interacting. Despite the high number of new models (many of them based on new rules), little research has been dedicated to experimentally validate the rule. A few studies started bridging this literature gap by experimentally testing the rule. However, in these studies, participants are forced to express their opinion as a number instead of using natural language. Furthermore, some of these studies average data from experimental questions, without testing if differences existed between them. Indeed, it is possible that different topics could show different dynamics. For example, people may be more prone to accepting someone's else opinion regarding less polarized topics. In this work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions using natural language ('agree' or 'disagree') and the certainty of their answer, expressed as a number between 1 and 10. To keep the interaction based on natural language, certainty was not shown to other participants. We then showed to the participant someone else's opinion on the same topic and, after a distraction task, we repeated the measurement. To produce data compatible with standard opinion dynamics models, we multiplied the opinion (encoded as agree=1 and disagree=-1) with the certainty to obtain a single 'continuous opinion' ranging from -10 to 10. By analyzing the topics independently, we observed that each one shows a different initial distribution. However, the dynamics (i.e., the properties of the opinion change) appear to be similar between all topics. This suggested that the same micro-dynamic rule could be applied to unpolarized topics. Another important result is that participants that change opinion tend to maintain similar levels of certainty. This is in contrast with typical micro-dynamics rules, where agents move to an average point instead of directly jumping to the opposite continuous opinion. As expected, in the data, we also observed the effect of social influence. This means that exposing someone with 'agree' or 'disagree' influenced participants to respectively higher or lower values of the continuous opinion. However, we also observed random variations whose effect was stronger than the social influence’s one. We even observed cases of people that changed from 'agree' to 'disagree,' even if they were exposed to 'agree.' This phenomenon is surprising, as, in the standard literature, the strength of the noise is usually smaller than the strength of social influence. Finally, we also built an opinion dynamics model from the data. The model was able to explain more than 80% of the data variance. Furthermore, by iterating the model, we were able to produce polarized states even starting from an unpolarized population. This experimental approach offers a way to test the micro-dynamic rule. This also allows us to build models which are directly grounded on experimental results.

Keywords: experimental validation, micro-dynamic rule, opinion dynamics, update rule

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Authors: Claudia Norambuena, Myissa Weiss, Maria Ruiz Maya, Matthew Straley, Elijah Hammond, Benjamin Chesebrough, David Grow

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The purpose of this project is to develop a low-cost, portable sensor device that can be used at home for long-term analysis of gait and balance abnormalities. One area of particular concern involves the asymmetries in movement and balance that can accompany certain types of injuries and/or the associated devices used in the repair and rehabilitation process (e.g. the use of splints and casts) which can often increase chances of falls and additional injuries. This device has the capacity to monitor a patient during the rehabilitation process after injury or operation, increasing the patient’s access to healthcare while decreasing the number of visits to the patient’s clinician. The sensor device may thereby improve the quality of the patient’s care, particularly in rural areas where access to the clinician could be limited, while simultaneously decreasing the overall cost associated with the patient’s care. The device consists of nine interconnected accelerometer/ gyroscope/compass chips (9-DOF IMU, Adafruit, New York, NY). The sensors attach to and are used to determine the orientation and acceleration of the patient’s lower abdomen, C7 vertebra (lower neck), L1 vertebra (middle back), anterior side of each thigh and tibia, and dorsal side of each foot. In addition, pressure sensors are embedded in shoe inserts with one sensor (ESS301, Tekscan, Boston, MA) beneath the heel and three sensors (Interlink 402, Interlink Electronics, Westlake Village, CA) beneath the metatarsal bones of each foot. These sensors measure the distribution of the weight applied to each foot as well as stride duration. A small microntroller (Arduino Mega, Arduino, Ivrea, Italy) is used to collect data from these sensors in a CSV file. MATLAB is then used to analyze the data and output the hip, knee, ankle, and trunk angles projected on the sagittal plane. An open-source program Processing is then used to generate an animation of the patient’s gait. The accuracy of the sensors was validated through comparison to goniometric measurements (±2° error). The sensor device was also shown to have sufficient sensitivity to observe various gait abnormalities. Several patients used the sensor device, and the data collected from each represented the patient’s movements. Further, the sensors were found to have the ability to observe gait abnormalities caused by the addition of a small amount of weight (4.5 - 9.1 kg) to one side of the patient. The user-friendly interface and portability of the sensor device will help to construct a bridge between patients and their clinicians with fewer necessary inpatient visits.

Keywords: biomedical sensing, gait analysis, outpatient, rehabilitation

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Authors: Stefano Iannello, Massimiliano Materazzi

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Fluidized bed reactor technologies are one of the most valuable pathways for thermochemical conversions of biogenic fuels due to their good operating flexibility. Nevertheless, there are still issues related to the mixing and separation of heterogeneous phases during operation with highly volatile feedstocks, including biomass and waste. At high temperatures, the volatile content of the feedstock is released in the form of the so-called endogenous bubbles, which generally exert a “lift” effect on the particle itself by dragging it up to the bed surface. Such phenomenon leads to high release of volatile matter into the freeboard and limited mass and heat transfer with particles of the bed inventory. The aim of this work is to get a better understanding of the behaviour of a single reacting particle in a hot fluidized bed reactor during the devolatilization stage. The analysis has been undertaken at different fluidization regimes and temperatures to closely mirror the operating conditions of waste-to-energy processes. Beechwood and polypropylene particles were used to resemble the biomass and plastic fractions present in waste materials, respectively. The non-invasive X-ray technique was coupled to particle tracking algorithms to characterize the motion of a single feedstock particle during the devolatilization with high resolution. A high-energy X-ray beam passes through the vessel where absorption occurs, depending on the distribution and amount of solids and fluids along the beam path. A high-speed video camera is synchronised to the beam and provides frame-by-frame imaging of the flow patterns of fluids and solids within the fluidized bed up to 72 fps (frames per second). A comprehensive mathematical model has been developed in order to validate the experimental results. Beech wood and polypropylene particles have shown a very different dynamic behaviour during the pyrolysis stage. When the feedstock is fed from the bottom, the plastic material tends to spend more time within the bed than the biomass. This behaviour can be attributed to the presence of the endogenous bubbles, which drag effect is more pronounced during the devolatilization of biomass, resulting in a lower residence time of the particle within the bed. At the typical operating temperatures of thermochemical conversions, the synthetic polymer softens and melts, and the bed particles attach on its outer surface, generating a wet plastic-sand agglomerate. Consequently, this additional layer of sand may hinder the rapid evolution of volatiles in the form of endogenous bubbles, and therefore the establishment of a poor drag effect acting on the feedstock itself. Information about the mixing and segregation of solid feedstock is of prime importance for the design and development of more efficient industrial-scale operations.

Keywords: fluidized bed, pyrolysis, waste feedstock, X-ray

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Authors: Josef Drahorad, Milos Beran, Ondrej Vltavsky, Marian Urban, Martin Fronek, Jiri Sova

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Engineering efforts of researchers of the Food research institute Prague and the Czech Technical University in spray drying technologies led to the introduction of a demonstrator ATOMIZER and a new technology of Carbon Dioxide-Assisted Spray Nebulization Drying (CASND). The equipment combines the spray drying technology, when the liquid to be dried is atomized by a rotary atomizer, with Carbon Dioxide Assisted Nebulization - Bubble Dryer (CAN-BD) process in an original way. A solution, emulsion or suspension is saturated by carbon dioxide at pressure up to 80 bar before the drying process. The atomization process takes place in two steps. In the first step, primary droplets are produced at the outlet of the rotary atomizer of special construction. In the second step, the primary droplets are divided in secondary droplets by the CO2 expansion from the inside of primary droplets. The secondary droplets, usually in the form of microbubbles, are rapidly dried by warm air stream at temperatures up to 60ºC and solid particles are formed in a drying chamber. Powder particles are separated from the drying air stream in a high efficiency fine powder separator. The product is frequently in the form of submicron hollow spheres. The CASND technology has been used to produce microparticulated protein concentrates for human nutrition from alternative plant sources - hemp and canola seed filtration cakes. Alkali extraction was used to extract the proteins from the filtration cakes. The protein solutions after the alkali extractions were dried with the demonstrator ATOMIZER. Aerosol particle size distribution and concentration in the draying chamber were determined by two different on-line aerosol spectrometers SMPS (Scanning Mobility Particle Sizer) and APS (Aerodynamic Particle Sizer). The protein powders were in form of hollow spheres with average particle diameter about 600 nm. The particles were characterized by the SEM method. The functional properties of the microparticulated protein concentrates were compared with the same protein concentrates dried by the conventional spray drying process. Microparticulated protein has been proven to have improved foaming and emulsifying properties, water and oil absorption capacities and formed long-term stable water dispersions. This work was supported by the research grants TH03010019 of the Technology Agency of the Czech Republic.

Keywords: carbon dioxide-assisted spray nebulization drying, canola seed, hemp seed, microparticulated proteins

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Authors: Sara Qandil, Harriet Bothwell, Lowri Evans, Kevin Jones, Simon Collin

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Background: Uganda suffers from high rates of HIV. Misconceptions around HIV are known to be prevalent in Sub-Saharan Africa (SSA). Two of the most common misconceptions in Uganda are that HIV can be transmitted by mosquito bites or from sharing food. The aim of this project was to establish the local misconceptions around HIV in a Central Ugandan population, and identify if there is a role for patient education leaflets. This project was undertaken as a student selected component (SSC) offered by Swindon Academy, based at the Great Western Hospital, to medical students in their fourth year of the undergraduate programme. Methods: The study was conducted at Villa Maria Hospital; a private, rural hospital in Kalungu District, Central Uganda. 36 patients, 23 from the hospital clinic and 13 from the community were interviewed regarding their understanding of HIV and by what channels they had obtained this understanding. Interviews were conducted using local student nurses as translators. Verbal responses were translated and then transcribed by the researcher. The same 36 patients then undertook a 'misconception' test consisting of 35 questions. Quantitative data was analysed using descriptive statistics and results were scored based on three components of 'transmission knowledge', 'prevention knowledge' and 'misconception rejection'. Each correct response to a question was scored one point, otherwise zero e.g. correctly rejecting a misconception scored one point, but answering ‘yes’ or ‘don’t know’ scored zero. Scores ≤ 27 (the average score) were classified as having ‘poor understanding’. Mean scores were compared between participants seen at the HIV clinic and in the community, and p-values (including Fisher’s exact test) were calculated using Stata 2015. Level of significance was set at 0.05. Interviews with 7 members of staff working in the HIV clinic were undertaken to establish what methods of communication are used to educate patients. Interviews were transcribed and thematic analysis undertaken. Results: The commonest misconceptions which failed to be rejected included transmission of HIV by kissing (78%), mosquitoes (69%) and touching (36%). 33% believed HIV may be prevented by praying. The overall mean scores for transmission knowledge (87.5%) and prevention knowledge (81.1%) were better than misconception rejection scores (69.3%). HIV clinic respondents did tend to have higher scores, i.e. fewer misconceptions, although there was statistical evidence of a significant difference only for prevention knowledge (p=0.03). Analysis of the qualitative data is ongoing but several patients expressed concerns about not being able to read and therefore leaflets not having a helpful role. Conclusions: Results from this paper identified that a high proportion of the population studied held misconceptions about HIV. Qualitative data suggests that there may be a role for patient education leaflets, if pictorial-based and suitable for those with low literacy skill.

Keywords: HIV, human immunodeficiency virus, misconceptions, patient education, Sub-Saharan Africa, Uganda

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Authors: Njoku, Joy

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The re-calibration of the Campanian to Maastritchian of some parts Anambra basin was carried outusing samples from two exploration wells (Amama-1 and Bara-1), Amama-1 (219M–1829M) and Bara-1 (317M-1594M). Palynological and Paleontological analyses werecarried out on 100 ditch cutting samples. The faunal and floral succession were of terrestrialand marine origin as described and logged. The well penetrated four stratigraphic units inAnambra Basin (the Nkporo, Mamu, Ajali and Nsukka) the wells yielded well preservedformanifera and palynormorphs. The well yielded 53 species of foram and 69 species ofpalynomorphs, with 12 genera Bara-1 (25 Species of foram and 101 species of palynormorphs). Amama-1permitted the recognition of 21 genera with 31 formainiferal assemblage zones, 32 pollen and 37 sporesassemblage zones, and dinoflagellate cyst, biozonation, ranging from late Campanian – earlyPaleocene. Bara-1 yielded (60 pollen, 41 spore assemblage zone and 18 dinoflagellate cyst).The zones, in stratigraphically ascending order for the foraminifera and palynomorphs are asfollows. AmamaBiozone A-Globotruncanellahavanensis zone: Late Campanian –Maastrichtian (695 – 1829m) Biozone B-Morozovellavelascoensis zone: Early Paleocene(165–695m) Bara-1 Biozone A-Globotruncanellahavanensis zone: Late Campanian(1512m) Biozone B-Bolivinaafra, B. explicate zone: Maastrichtian (634–1204m) BiozoneC- Indeterminate (305 – 634m) Palynological Amama-1 A.Ctenolophoniditescostatus zone:Early Maastrichtian (1829m) B-Retidiporitesminiporatus Zone: Late Maastrichtian (1274m)Constructipollenitesineffectus Zone: Early Paleocene(695m) Bara-1 Droseriditessenonicus Zone: Late Campanian (994– 1600m) B. Ctenolophoniditescostatus Zone: EarlyMaastrichtian (713–994m) C. Retidiporitesminiporatus Zone: Late Maastrichtian (305 –713m) The paleo – environment of deposition were determined to range from non-marine toouter netritic. A detailed categorization of the palynormorphs into terrestrially derivedpalynormorphs and marine derived palynormorphs based on the distribution of three broadvegetation types; mangrove, fresh water swamps and hinther land communities were used toevaluate sea level fluctuations with respect to sediments deposited in the basins and linkedwith a particular depositional system tract. Amama-1 recorded 4 maximum flooding surface(MFS) at depth 165-1829, dated b/w 61ma-76ma and three sequence boundary(SB) at depth1048m-1533m and 1581 dated b/w 634m-1387m, dated 69.5ma-82ma and four sequenceboundary(SB) at 552m-876m, dated 68ma-77.5ma respectively. The application ofecostratigraphic description is characterised by the prominent expansion of the hinterlandcomponent consisting of the Mangrove to Lowland Rainforest and Afromontane – Savannah vegetation.

Keywords: formanifera, palynomorphs. campanian, maastritchian, ecostratigraphic anambra

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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

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Authors: Anastasios Zopiatis, Antonis L. Theocharous

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In the midst of a fierce war for talent, the hospitality industry is seeking new and innovative ways to enrich its image as an employer of choice and not a necessity. Historically, the industry’s professions are portrayed as ‘unattractive’ due to their repetitious nature, long and unsocial working schedules, below average remunerations, and the mental and physical demands of the job. Aligning with the industry, hospitality and tourism scholars embarked on a journey to investigate pertinent topics with the aim of enhancing our conceptual understanding of the elements that influence employees at the hospitality world of work. Topics such as job involvement, commitment, job and career satisfaction, and turnover intentions became the focal points in a multitude of relevant empirical and conceptual investigations. Nevertheless, gaps or inconsistencies in existing theories, as a result of both the volatile complexity of the relationships governing human behavior in the hospitality workplace, and the academic community’s unopposed acceptance of theoretical frameworks mainly propounded in the United States and United Kingdom years ago, necessitate our continuous vigilance. Thus, in an effort to enhance and enrich the discourse, we set out to investigate the relationship between intrinsic and extrinsic job satisfaction traits and the individual’s career satisfaction, and subsequent intention to remain in the hospitality industry. Reflecting on existing literature, a quantitative survey was developed and administered, face-to-face, to 650 individuals working as full-time employees in 4- and 5- star hotel establishments in Cyprus, whereas a multivariate statistical analysis method, namely Structural Equation Modeling (SEM), was utilized to determine whether relationships existed between constructs as a means to either accept or reject the hypothesized theory. Findings, of interest to both industry stakeholders and academic scholars, suggest that the individual’s future intention to remain within the industry is primarily associated with extrinsic job traits. Our findings revealed that positive associations exist between extrinsic job traits, and both career satisfaction and future intention. In contrast, when investigating the relationship of intrinsic traits, a positive association was revealed only with career satisfaction. Apparently, the local industry’s environmental factors of seasonality, excessive turnover, overdependence on seasonal, and part-time migrant workers, prohibit industry stakeholders in effectively investing the time and resources in the development and professional growth of their employees. Consequently intrinsic job satisfaction factors such as advancement, growth, and achievement, take backstage to the more materialistic extrinsic factors. Findings from the subsequent mediation analysis support the notion that intrinsic traits can positively influence future intentions indirectly only through career satisfaction, whereas extrinsic traits can positively impact both career satisfaction and future intention both directly and indirectly.

Keywords: career satisfaction, Cyprus, hotel employees, structural equation modeling, SEM

Procedia PDF Downloads 276

Authors: Asad Hanif, Pavithra Parthasarathy, Zongjin Li

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Thermal insulating composites help to reduce the total power consumption in a building by creating a barrier between external and internal environment. Such composites can be used in the roofing tiles or wall panels for exterior surfaces. This study purposes to develop lightweight cement-based composites for thermal insulating applications. Waste materials like silica fume (an industrial by-product) and fly ash cenosphere (FAC) (hollow micro-spherical shells obtained as a waste residue from coal fired power plants) were used as partial replacement of cement and lightweight filler, respectively. Moreover, aerogel, a nano-porous material made of silica, was also used in different dosages for improved thermal insulating behavior, while poly vinyl alcohol (PVA) fibers were added for enhanced toughness. The raw materials including binders and fillers were characterized by X-Ray Diffraction (XRD), X-Ray Fluorescence spectroscopy (XRF), and Brunauer–Emmett–Teller (BET) analysis techniques in which various physical and chemical properties of the raw materials were evaluated like specific surface area, chemical composition (oxide form), and pore size distribution (if any). Ultra-lightweight cementitious composites were developed by varying the amounts of FAC and aerogel with 28-day unit weight ranging from 1551.28 kg/m³ to 1027.85 kg/m³. Excellent mechanical and thermal insulating properties of the resulting composites were obtained ranging from 53.62 MPa to 8.66 MPa compressive strength, 9.77 MPa to 3.98 MPa flexural strength, and 0.3025 W/m-K to 0.2009 W/m-K as thermal conductivity coefficient (QTM-500). The composites were also tested for peak temperature difference between outer and inner surfaces when subjected to heating (in a specially designed experimental set-up) by a 275W infrared lamp. The temperature difference up to 16.78 ^oC was achieved, which indicated outstanding properties of the developed composites to act as a thermal barrier for building envelopes. Microstructural studies were carried out by Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) for characterizing the inner structure of the composite specimen. Also, the hydration products were quantified using the surface area mapping and line scale technique in EDS. The microstructural analyses indicated excellent bonding of FAC and aerogel in the cementitious system. Also, selective reactivity of FAC was ascertained from the SEM imagery where the partially consumed FAC shells were observed. All in all, the lightweight fillers, FAC, and aerogel helped to produce the lightweight composites due to their physical characteristics, while exceptional mechanical properties, owing to FAC partial reactivity, were achieved.

Keywords: aerogel, cement-based, composite, fly ash cenosphere, lightweight, sustainable development, thermal conductivity

Procedia PDF Downloads 217

Authors: Maryam Ziaee, Himanshu Shee, Amrik Sohal

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Big Data Analytics (BDA) in supply chain management has recently drawn the attention of academics and practitioners. Big data refers to a massive amount of data from different sources, in different formats, generated at high speed through transactions in business environments and supply chain networks. Traditional statistical tools and techniques find it difficult to analyse this massive data. BDA can assist organisations to capture, store, and analyse data specifically in the field of supply chain. Currently, there is a paucity of research on BDA in the pharmaceutical supply chain context. In this research, the Australian pharmaceutical supply chain was selected as the case study. This industry is highly significant since the right medicine must reach the right patients, at the right time, in right quantity, in good condition, and at the right price to save lives. However, drug shortages remain a substantial problem for hospitals across Australia with implications on patient care, staff resourcing, and expenditure. Furthermore, a massive volume and variety of data is generated at fast speed from multiple sources in pharmaceutical supply chain, which needs to be captured and analysed to benefit operational decisions at every stage of supply chain processes. As the pharmaceutical industry lags behind other industries in using BDA, it raises the question of whether the use of BDA can improve transparency among pharmaceutical supply chain by enabling the partners to make informed-decisions across their operational activities. This presentation explores the impacts of BDA on supply chain management. An exploratory qualitative approach was adopted to analyse data collected through interviews. This study also explores the BDA potential in the whole pharmaceutical supply chain rather than focusing on a single entity. Twenty semi-structured interviews were undertaken with top managers in fifteen organisations (five pharmaceutical manufacturers, five wholesalers/distributors, and five public hospital pharmacies) to investigate their views on the use of BDA. The findings revealed that BDA can enable pharmaceutical entities to have improved visibility over the whole supply chain and also the market; it enables entities, especially manufacturers, to monitor consumption and the demand rate in real-time and make accurate demand forecasts which reduce drug shortages. Timely and precise decision-making can allow the entities to source and manage their stocks more effectively. This can likely address the drug demand at hospitals and respond to unanticipated issues such as drug shortages. Earlier studies explore BDA in the context of clinical healthcare; however, this presentation investigates the benefits of BDA in the Australian pharmaceutical supply chain. Furthermore, this research enhances managers’ insight into the potentials of BDA at every stage of supply chain processes and helps to improve decision-making in their supply chain operations. The findings will turn the rhetoric of data-driven decision into a reality where the managers may opt for analytics for improved decision-making in the supply chain processes.

Keywords: big data analytics, data-driven decision, pharmaceutical industry, supply chain management

Procedia PDF Downloads 102

Authors: Manali Chakraborty

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In the developing countries the most prevalent pathological state is malnutrition and under nutrition due to deficiency of essential nutrients. This condition is more seen between the woman population, especially in the adolescent girls. It is causing childhood deaths along with others cognitive, degenerative diseases. Born of low weight babies and stillbirth are also major problems associated with the malnutrition. Along with the increased level of population, people not only should concern about their quantity of food but also for the quality of the food to be healthy. Lethargy, depression caused due to iron deficiency often quoted as normal or unimportant issues. Children of malnourished women are more likely associated with cognitive impairment, immune dysfunction leading to a higher risk of being attacked by diseases. Malnourishment also affects the productivity of women. Low social status, lack of proper nutritional education is an important cause of this nutrient deficiency among women. Iron deficiency and anemia are mostly famous nutritional deficiencies among women worldwide. Mostly women from below poverty lined area are anemic due to less consumption of iron-rich foods or having foods that might inhibit the iron absorption. Growing females like adolescents or lactating females need more iron supply. Less supplement causes iron deficiency. Though malaria also might cause anemia, it is more likely endemic one in some specific areas. Folate deficiency in females also may cause neurological defects in the infants. Other Vitamin B, A deficiencies along with low iodine level is also noted in malnourished women. According to tradition, still in some areas in developing countries females have their food at the end. According to some survey and collected data, these females are often into the risk zone of being malnourished. Regularly they have the very lesser amount, or food sometimes may start to lose its nutrients. Women are the one who maintains the responsibility to cook foods in the home. Lack of proper nutritional education and proper food preparation not only make those foods lose the nutrients leading to impairment in proper nutrient intake of the family members but also impairing own nutritional status. Formulation and development of food products from iron or other nutrient affluent sources viz., traditional herbs can be helpful in the prevention of such malnutrition condition in females. Keeping low cost and smooth maintenance of the food product development from the natural sources like pulses, cereals or other vegetation also can be beneficial to sustain socio-economic condition. Consumption of such kind of foodstuff is much healthier rather than taking continuous supplements like capsules. Utilization of proper scientific and cost-effective techniques for this food product development and their distribution among rural women population might be an enormous initiative.

Keywords: anemia, food supplements, malnutrition, rural places, women population

Procedia PDF Downloads 116

Authors: Clara Tramuta, Floris Irene, Daniela Manila Bianchi, Monica Pitti, Giulia Federica Cazzaniga, Lucia Decastelli

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This work presents the results obtained by the Regional Reference Centre for Salmonella Typing (CeRTiS) in a retrospective study aimed to investigate, through Pulsed-field Gel Electrophoresis (PFGE) analysis, the genetic relatedness of emerging Salmonella serotypes of human origin circulating in North-West of Italy. Furthermore, the goal of this work was to create a Regional database to facilitate foodborne outbreak investigation and to monitor them at an earlier stage. A total of 112 strains, isolated from 2016 to 2018 in hospital laboratories, were included in this study. The isolates were previously identified as Salmonella according to standard microbiological techniques and serotyping was performed according to ISO 6579-3 and the Kaufmann-White scheme using O and H antisera (Statens Serum Institut®). All strains were characterized by PFGE: analysis was conducted according to a standardized PulseNet protocol. The restriction enzyme XbaI was used to generate several distinguishable genomic fragments on the agarose gel. PFGE was performed on a CHEF Mapper system, separating large fragments and generating comparable genetic patterns. The agarose gel was then stained with GelRed® and photographed under ultraviolet transillumination. The PFGE patterns obtained from the 112 strains were compared using Bionumerics version 7.6 software with the Dice coefficient with 2% band tolerance and 2% optimization. For each serotype, the data obtained with the PFGE were compared according to the geographical origin and the year in which they were isolated. Salmonella strains were identified as follow: S. Derby n. 34; S. Infantis n. 38; S. Napoli n. 40. All the isolates had appreciable restricted digestion patterns ranging from approximately 40 to 1100 kb. In general, a fairly heterogeneous distribution of pulsotypes has emerged in the different provinces. Cluster analysis indicated high genetic similarity (≥ 83%) among strains of S. Derby (n. 30; 88%), S. Infantis (n. 36; 95%) and S. Napoli (n. 38; 95%) circulating in north-western Italy. The study underlines the genomic similarities shared by the emerging Salmonella strains in Northwest Italy and allowed to create a database to detect outbreaks in an early stage. Therefore, the results confirmed that PFGE is a powerful and discriminatory tool to investigate the genetic relationships among strains in order to monitoring and control Salmonellosis outbreak spread. Pulsed-field gel electrophoresis (PFGE) still represents one of the most suitable approaches to characterize strains, in particular for the laboratories for which NGS techniques are not available.

Keywords: emerging Salmonella serotypes, genetic characterization, human strains, PFGE

Procedia PDF Downloads 99

Authors: Chu-Tzu Chen, Angela S. Huang, Yu-Min Chou, Chin-Hui Yang

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Dengue is a major public health concern throughout tropical and sub-tropical regions. Taiwan is located in the Pacific Ocean and overlying the tropical and subtropical zones. The island remains humid throughout the year and receives abundant rainfall, and the temperature is very hot in summer at southern Taiwan. It is ideal for the growth of dengue vectors and would be increasing the risk on dengue outbreaks. During the first half of the 20th century, there were three island-wide dengue outbreaks (1915, 1931, and 1942). After almost forty years of dormancy, a DEN-2 outbreak occurred in Liuchiu Township, Pingtung County in 1981. Thereafter, more dengue outbreaks occurred with different scales in southern Taiwan. However, there were more than ten thousands of dengue cases in 2014 and in 2015. It did not only affect human health, but also caused widespread social disruption and economic losses. The study would like to reveal the epidemiology of dengue on Taiwan, especially the severe outbreak in 2015, and try to find the effective interventions in dengue control including dengue vaccine development for the elderly. Methods: The study applied the Notifiable Diseases Surveillance System database of the Taiwan Centers for Disease Control as data source. All cases were reported with the uniform case definition and confirmed by NS1 rapid diagnosis/laboratory diagnosis. Results: In 2014, Taiwan experienced a serious DEN-1 outbreak with 15,492 locally-acquired cases, including 136 cases of dengue hemorrhagic fever (DHF) which caused 21 deaths. However, a more serious DEN-2 outbreak occurred with 43,419 locally-acquired cases in 2015. The epidemic occurred mainly at Tainan City (22,760 cases) and Kaohsiung City (19,723 cases) in southern Taiwan. The age distribution for the cases were mainly adults. There were 228 deaths due to dengue infection, and the case fatality rate was 5.25 ‰. The average age of them was 73.66 years (range 29-96) and 86.84% of them were older than 60 years. Most of them were comorbidities. To review the clinical manifestations of the 228 death cases, 38.16% (N=87) of them were reported with warning signs, while 51.75% (N=118) were reported without warning signs. Among the 87 death cases reported to dengue with warning signs, 89.53% were diagnosed sever dengue and 84% needed the intensive care. Conclusion: The year 2015 was characterized by large dengue outbreaks worldwide. The risk of serious dengue outbreak may increase significantly in the future, and the elderly is the vulnerable group in Taiwan. However, a dengue vaccine has been licensed for use in people 9-45 years of age living in endemic settings at the end of 2015. In addition to carry out the research to find out new interventions in dengue control, developing the dengue vaccine for the elderly is very important to prevent severe dengue and deaths.

Keywords: case fatality rate, dengue, dengue vaccine, the elderly

Procedia PDF Downloads 277

Authors: Afnan Al-Romi, Iman Al-Momani

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The urge of applying the Software Engineering (SE) processes is both of vital importance and a key feature in critical, complex large-scale systems, for example, safety systems, security service systems, and network systems. Inevitably, associated with this are risks, such as system vulnerabilities and security threats. The probability of those risks increases in unsecured environments, such as wireless networks in general and in Wireless Sensor Networks (WSNs) in particular. WSN is a self-organizing network of sensor nodes connected by wireless links. WSNs consist of hundreds to thousands of low-power, low-cost, multi-function sensor nodes that are small in size and communicate over short-ranges. The distribution of sensor nodes in an open environment that could be unattended in addition to the resource constraints in terms of processing, storage and power, make such networks in stringent limitations such as lifetime (i.e. period of operation) and security. The importance of WSN applications that could be found in many militaries and civilian aspects has drawn the attention of many researchers to consider its security. To address this important issue and overcome one of the main challenges of WSNs, security solution systems have been developed by researchers. Those solutions are software-based network Intrusion Detection Systems (IDSs). However, it has been witnessed, that those developed IDSs are neither secure enough nor accurate to detect all malicious behaviours of attacks. Thus, the problem is the lack of coverage of all malicious behaviours in proposed IDSs, leading to unpleasant results, such as delays in the detection process, low detection accuracy, or even worse, leading to detection failure, as illustrated in the previous studies. Also, another problem is energy consumption in WSNs caused by IDS. So, in other words, not all requirements are implemented then traced. Moreover, neither all requirements are identified nor satisfied, as for some requirements have been compromised. The drawbacks in the current IDS are due to not following structured software development processes by researches and developers when developing IDS. Consequently, they resulted in inadequate requirement management, process, validation, and verification of requirements quality. Unfortunately, WSN and SE research communities have been mostly impermeable to each other. Integrating SE and WSNs is a real subject that will be expanded as technology evolves and spreads in industrial applications. Therefore, this paper will study the importance of Requirement Engineering when developing IDSs. Also, it will study a set of existed IDSs and illustrate the absence of Requirement Engineering and its effect. Then conclusions are drawn in regard of applying requirement engineering to systems to deliver the required functionalities, with respect to operational constraints, within an acceptable level of performance, accuracy and reliability.

Keywords: software engineering, requirement engineering, Intrusion Detection System, IDS, Wireless Sensor Networks, WSN

Procedia PDF Downloads 318

Authors: Tony R. Walker, N. Devin MacAskill, Andrew Thalhiemer

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Sydney Harbour, Nova Scotia has long been subject to effluent and atmospheric inputs of metals, polycyclic aromatic hydrocarbons (PAHs), and polychlorinated biphenyls (PCBs) from a large coking operation and steel plant that operated in Sydney for nearly a century until closure in 1988. Contaminated effluents from the industrial site resulted in the creation of the Sydney Tar Ponds, one of Canada’s largest contaminated sites. Since its closure, there have been several attempts to remediate this former industrial site and finally, in 2004, the governments of Canada and Nova Scotia committed to remediate the site to reduce potential ecological and human health risks to the environment. The Sydney Tar Ponds and Coke Ovens cleanup project has become the most prominent remediation project in Canada today. As an integral part of remediation of the site (i.e., which consisted of solidification/stabilization and associated capping of the Tar Ponds), an extensive multiple media environmental effects program was implemented to assess what effects remediation had on the surrounding environment, and, in particular, harbour sediments. Additionally, longer-term natural sediment recovery rates of select contaminants predicted for the harbour sediments were compared to current conditions. During remediation, potential contributions to sediment quality, in addition to remedial efforts, were evaluated which included a significant harbour dredging project, propeller wash from harbour traffic, storm events, adjacent loading/unloading of coal and municipal wastewater treatment discharges. Two sediment sampling methodologies, sediment grab and gravity corer, were also compared to evaluate the detection of subtle changes in sediment quality. Results indicated that overall spatial distribution pattern of historical contaminants remains unchanged, although at much lower concentrations than previously reported, due to natural recovery. Measurements of sediment indicator parameter concentrations confirmed that natural recovery rates of Sydney Harbour sediments were in broad agreement with predicted concentrations, in spite of ongoing remediation activities. Overall, most measured parameters in sediments showed little temporal variability even when using different sampling methodologies, during three years of remediation compared to baseline, except for the detection of significant increases in total PAH concentrations noted during one year of remediation monitoring. The data confirmed the effectiveness of mitigation measures implemented during construction relative to harbour sediment quality, despite other anthropogenic activities and the dynamic nature of the harbour.

Keywords: contaminated sediment, monitoring, recovery, remediation

Procedia PDF Downloads 234

Authors: Hai L. Tran

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In the digital age, evidence-based reporting is touted as a best practice for seeking the truth and keeping the public well-informed. Journalists are expected to rely on evidence to demonstrate the validity of a factual statement and lend credence to an individual account. Evidence can be obtained from various sources, and due to a rich supply of evidence types available, the definition of this important concept varies semantically. To promote clarity and understanding, it is necessary to break down the various types of evidence and categorize them in a more coherent, systematic way. There is a wide array of devices that digital journalists deploy as proof to back up or refute a truth claim. Evidence can take various formats, including verbal and visual materials. Verbal evidence encompasses quotes, soundbites, talking heads, testimonies, voice recordings, anecdotes, and statistics communicated through written or spoken language. There are instances where evidence is simply non-verbal, such as when natural sounds are provided without any verbalized words. On the other hand, other language-free items exhibited in photos, video footage, data visualizations, infographics, and illustrations can serve as visual evidence. Moreover, there are different sources from which evidence can be cited. Supporting materials, such as public or leaked records and documents, data, research studies, surveys, polls, or reports compiled by governments, organizations, and other entities, are frequently included as informational evidence. Proof can also come from human sources via interviews, recorded conversations, public and private gatherings, or press conferences. Expert opinions, eye-witness insights, insider observations, and official statements are some of the common examples of testimonial evidence. Digital journalism studies tend to make broad references when comparing qualitative versus quantitative forms of evidence. Meanwhile, limited efforts are being undertaken to distinguish between sister terms, such as “data,” “statistical,” and “base-rate” on one side of the spectrum and “narrative,” “anecdotal,” and “exemplar” on the other. The present study seeks to develop the evidence taxonomy, which classifies evidence through the quantitative-qualitative juxtaposition and in a hierarchical order from broad to specific. According to this scheme, data, statistics, and base rate belong to the quantitative evidence group, whereas narrative, anecdote, and exemplar fall into the qualitative evidence group. Subsequently, the taxonomical classification arranges data versus narrative at the top of the hierarchy of types of evidence, followed by statistics versus anecdote and base rate versus exemplar. This research reiterates the central role of evidence in how journalists describe and explain social phenomena and issues. By defining the various types of evidence and delineating their logical connections it helps remove a significant degree of conceptual inconsistency, ambiguity, and confusion in digital journalism studies.

Keywords: evidence, evidence forms, evidence types, taxonomy

Procedia PDF Downloads 61

Authors: Augustus K. Lebechi, Kenneth I. Ozoemena

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Rechargeable zinc-air batteries (RZABs) have been described as one of the most viable next-generation ‘beyond-the-lithium-ion’ battery technologies with great potential for renewable energy storage. It is safe, with a high specific energy density (1086 Wh/kg), environmentally benign, and low-cost, especially in resource-limited African countries. For widespread commercialization, the sluggish oxygen reaction kinetics pose a major challenge that impedes the reversibility of the system. Hence, there is a need for low-cost and highly active bifunctional electrocatalysts. Manganese oxide catalysts on carbon conducting additives remain the best couple for the realization of such low-cost RZABs. In this work, hausmannite Mn₃O₄ nanoparticles were synthesized through the annealing method from commercial electrolytic manganese dioxide (EMD), multi-walled carbon nanotubes (MWCNTs) were synthesized via the chemical vapor deposition (CVD) method and carbon nanofibers (CNFs) were synthesized via the electrospinning process with subsequent carbonization. Both Mn₃O₄ catalysts and the carbon conducting additives (MWCNT and CNF) were thoroughly characterized using X-ray powder diffraction spectroscopy (XRD), scanning electron microscopy (SEM), thermogravimetry analysis (TGA) and X-ray photoelectron spectroscopy (XPS). Composite electrocatalysts (Mn₃O₄/CNT and Mn₃O₄/CNF) were investigated for oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) in an alkaline medium. Using the established electrocatalytic modalities for evaluating the electrocatalytic performance of materials (including double layer, electrochemical active surface area, roughness factor, specific current density, and catalytic stability), CNFs proved to be the most efficient conducting additive material for the Mn₃O₄ catalyst. From the DFT calculations, the higher performance of the CNFs over the MWCNTs is related to the ability of the CNFs to allow for a more favorable distribution of the d-electrons of the manganese (Mn) and enhanced synergistic effect with Mn₃O₄ for weaker adsorption energies of the oxygen intermediates (O*, OH* and OOH*). In a proof-of-concept, Mn₃O₄/CNF was investigated as the air cathode for rechargeable zinc-air battery (RZAB) in a micro-3D-printed cell configuration. The RZAB showed good performance in terms of open circuit voltage (1.77 V), maximum power density (177.5 mW cm-2), areal-discharge energy and cycling stability comparable to Pt/C (20 wt%) + IrO2. The findings here provide fresh physicochemical perspectives on the future design and utility of CNFs for developing manganese-based RZABs.

Keywords: bifunctional electrocatalyst, oxygen evolution reaction, oxygen reduction reactions, rechargeable zinc-air batteries.

Procedia PDF Downloads 53

Authors: Indika Fernando, Jiangang Fei, Roger Stanely, Hossein Enshaei

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Ever increasing demand for quality fresh produce by the consumers, had increased the gravity on the post-harvest supply chains in multi-fold in the recent years. Mechanical injury to fresh produce was a critical factor for produce wastage, especially with the expansion of supply chains, physically extending to thousands of miles. The impact of vibration damages in transit was identified as a specific area of focus which results in wastage of significant portion of the fresh produce, at times ranging from 10% to 40% in some countries. Several studies were concentrated on quantifying the impact of vibration to fresh produce, and it was a challenge to collect vibration impact data continuously due to the limitations in battery life or the memory capacity in the devices. Therefore, the study samples were limited to a stretch of the transit passage or a limited time of the journey. This may or may not give an accurate understanding of the vibration impacts encountered throughout the transit passage, which limits the accuracy of the results. Consequently, an approach which can extend the capacity and ability of determining vibration signals in the transit passage would contribute to accurately analyze the vibration damage along the post-harvest supply chain. A mechanism was developed to address this challenge, which is capable of measuring the in transit vibration continuously through the transit passage subject to a minimum acceleration threshold (0.1g). A system, consisting six tri-axel vibration transducers installed in different locations inside the cargo (produce) pallets in the truck, transmits vibration signals through LORA (Long Range Radio) technology to a central device installed inside the container. The central device processes and records the vibration signals transmitted by the portable transducers, along with the GPS location. This method enables to utilize power consumption for the portable transducers to maximize the capability of measuring the vibration impacts in the transit passage extending to days in the distribution process. The trial tests conducted using the approach reveals that it is a reliable method to measure and quantify the in transit vibrations along the supply chain. The GPS capability enables to identify the locations in the supply chain where the significant vibration impacts were encountered. This method contributes to determining the causes, susceptibility and intensity of vibration impact damages to fresh produce in the post-harvest supply chain. Extensively, the approach could be used to determine the vibration impacts not limiting to fresh produce, but for products in supply chains, which may extend from few hours to several days in transit.

Keywords: post-harvest, supply chain, wireless transducers, LORA, fresh produce

Procedia PDF Downloads 261

Authors: Temitope L. Baiyegunhi, Christopher Baiyegunhi, Kuiwu Liu, Oswald Gwavava

Abstract:

Diagenesis is the most important factor that affects or impact the reservoir property. Despite the fact that published data gives a vast amount of information on the geology, sedimentology and lithostratigraphy of the Ecca Group in the Karoo Basin of South Africa, little is known of the diagenesis of the potentially feasible shales and sandstones of the Ecca Group. The study aims to provide a general account of the diagenesis of sandstones and mudstone of the Ecca Group. Twenty-five diagenetic textures and structures are identified and grouped into three regimes or stages that include eogenesis, mesogenesis and telogenesis. Clay minerals are the most common cementing materials in the Ecca sandstones and mudstones. Smectite, kaolinite and illite are the major clay minerals that act as pore lining rims and pore-filling cement. Most of the clay minerals and detrital grains were seriously attacked and replaced by calcite. Calcite precipitates locally in pore spaces and partly or completely replaced feldspar and quartz grains, mostly at their margins. Precipitation of cements and formation of pyrite and authigenic minerals as well as little lithification occurred during the eogenesis. This regime was followed by mesogenesis which brought about an increase in tightness of grain packing, loss of pore spaces and thinning of beds due to weight of overlying sediments and selective dissolution of framework grains. Compaction, mineral overgrowths, mineral replacement, clay-mineral authigenesis, deformation and pressure solution structures occurred during mesogenesis. During rocks were uplifted, weathered and unroofed by erosion, this resulted in additional grain fracturing, decementation and oxidation of iron-rich volcanic fragments and ferromagnesian minerals. The rocks of Ecca Group were subjected to moderate-intense mechanical and chemical compaction during its progressive burial. Intergranular pores, matrix micro pores, secondary intragranular, dissolution and fractured pores are the observed pores. The presence of fractured and dissolution pores tend to enhance reservoir quality. However, the isolated nature of the pores makes them unfavourable producers of hydrocarbons, which at best would require stimulation. The understanding of the space and time distribution of diagenetic processes in these rocks will allow the development of predictive models of their quality, which may contribute to the reduction of risks involved in their exploration.

Keywords: diagenesis, reservoir quality, Ecca Group, Karoo Supergroup

Procedia PDF Downloads 141

Authors: Ali H. Daraji, Jack M. Hale, Ye Jianqiao

Abstract:

With the extensive use of high specific strength structures to optimise the loading capacity and material cost in aerospace and most engineering applications, much effort has been expended to develop intelligent structures for active vibration reduction and structural health monitoring. These structures are highly flexible, inherently low internal damping and associated with large vibration and long decay time. The modification of such structures by adding lightweight piezoelectric sensors and actuators at efficient locations integrated with an optimal control scheme is considered an effective solution for structural vibration monitoring and controlling. The size and location of sensor and actuator are important research topics to investigate their effects on the level of vibration detection and reduction and the amount of energy provided by a controller. Several methodologies have been presented to determine the optimal location of a limited number of sensors and actuators for small-scale structures. However, these studies have tackled this problem directly, measuring the fitness function based on eigenvalues and eigenvectors achieved with numerous combinations of sensor/actuator pair locations and converging on an optimal set using heuristic optimisation techniques such as the genetic algorithms. This is computationally expensive for small- and large-scale structures subject to optimise a number of s/a pairs to suppress multiple vibration modes. This paper proposes an efficient method to determine optimal locations for a limited number of sensor/actuator pairs for active vibration reduction of a flexible structure based on finite element method and Hamilton’s principle. The current work takes the simplified approach of modelling a structure with sensors at all locations, subjecting it to an external force to excite the various modes of interest and noting the locations of sensors giving the largest average percentage sensors effectiveness measured by dividing all sensor output voltage over the maximum for each mode. The methodology was implemented for a cantilever plate under external force excitation to find the optimal distribution of six sensor/actuator pairs to suppress the first six modes of vibration. It is shown that the results of the optimal sensor locations give good agreement with published optimal locations, but with very much reduced computational effort and higher effectiveness. Furthermore, it is shown that collocated sensor/actuator pairs placed in these locations give very effective active vibration reduction using optimal linear quadratic control scheme.

Keywords: optimisation, plate, sensor effectiveness, vibration control

Procedia PDF Downloads 224

Authors: Farnaz Jafari

Abstract:

The surge in mass timber construction represents a pivotal moment in sustainable building practices, yet the lack of comprehensive education in construction management poses a challenge in harnessing this innovation effectively. This research endeavors to bridge this gap by developing a curriculum framework integrating mass timber construction into undergraduate and industry certificate programs. To optimize learning outcomes, the study explores the impact of two prototype formats -Virtual Reality (VR) simulations and physical mock-ups- on students' understanding and skill development. The curriculum framework aims to equip future construction managers with a holistic understanding of mass timber, covering its unique properties, construction methods, building codes, and sustainable advantages. The study adopts a mixed-methods approach, commencing with a systematic literature review and leveraging surveys and interviews with educators and industry professionals to identify existing educational gaps. The iterative development process involves incorporating stakeholder feedback into the curriculum. The evaluation of prototype impact employs pre- and post-tests administered to participants engaged in pilot programs. Through qualitative content analysis and quantitative statistical methods, the study seeks to compare the effectiveness of VR simulations and physical mock-ups in conveying knowledge and skills related to mass timber construction. The anticipated findings will illuminate the strengths and weaknesses of each approach, providing insights for future curriculum development. The curriculum's expected contribution to sustainable construction education lies in its emphasis on practical application, bridging the gap between theoretical knowledge and hands-on skills. The research also seeks to establish a standard for mass timber construction education, contributing to the field through a unique comparative analysis of VR simulations and physical mock-ups. The study's significance extends to the development of best practices and evidence-based recommendations for integrating technology and hands-on experiences in construction education. By addressing current educational gaps and offering a comparative analysis, this research aims to enrich the construction management education experience and pave the way for broader adoption of sustainable practices in the industry. The envisioned curriculum framework is designed for versatile integration, catering to undergraduate programs and industry training modules, thereby enhancing the educational landscape for aspiring construction professionals. Ultimately, this study underscores the importance of proactive educational strategies in preparing industry professionals for the evolving demands of the construction landscape, facilitating a seamless transition towards sustainable building practices.

Keywords: curriculum framework, mass timber construction, physical vs. virtual prototypes, sustainable building practices

Procedia PDF Downloads 60