Search results for: drivers of deforestation and forest degradation

Authors: Petra Hofmann, Dana Koniel, Jussi Luukkanen, Walter Nieminen, Lea Hannola, Ilkka Donoghue

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The Covid-19 pandemic forced people to isolate and become physically less connected. The pandemic has not only reshaped people’s behaviours and needs but also accelerated digital transformation (DT). DT of cities has become an imperative with the outlook of converting them into smart cities in the future. Embedding digital infrastructure and smart city initiatives as part of normal design, construction, and operation of cities provides a unique opportunity to improve the connection between people. The Internet of Things (IoT) is an emerging technology and one of the drivers in DT. It has disrupted many industries by introducing different services and business models, and IoT solutions are being applied in multiple fields, including smart cities. As IoT and data are fundamentally linked together, IoT solutions can only create value if the data generated by the IoT devices is analysed properly. Extracting relevant conclusions and actionable insights by using established techniques, data analytics contributes significantly to the growth and success of IoT applications and investments. Companies must grasp DT and be prepared to redesign their offerings and business models to remain competitive in today’s marketplace. As there are many IoT solutions available today, the amount of data is tremendous. The challenge for companies is to understand what solutions to focus on and how to prioritise and which data to differentiate from the competition. This paper explains how IoT and data analytics can impact competitive advantage and how companies should approach IoT and data analytics to translate them into concrete offerings and solutions in the smart city context. The study was carried out as a qualitative, literature-based research. A case study is provided to validate the preservation of company’s competitive advantage through smart city solutions. The results of the research contribution provide insights into the different factors and considerations related to creating competitive advantage through IoT and data analytics deployment in the smart city context. Furthermore, this paper proposes a framework that merges the factors and considerations with examples of offerings and solutions in smart cities. The data collected through IoT devices, and the intelligent use of it, can create competitive advantage to companies operating in smart city business. Companies should take into consideration the five forces of competition that shape industries and pay attention to the technological, organisational, and external contexts which define factors for consideration of competitive advantages in the field of IoT and data analytics. Companies that can utilise these key assets in their businesses will most likely conquer the markets and have a strong foothold in the smart city business.

Keywords: data analytics, smart cities, competitive advantage, internet of things

Procedia PDF Downloads 130

Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

Procedia PDF Downloads 102

Authors: Mirco Tarozzi, Giacomo Pignagnoli, Andrea Benedetti

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Structural systems are often subjected to degradation processes due to different kind of phenomena like unexpected loadings, ageing of the materials and fatigue cycles. This is true especially for bridges, in which their safety evaluation is crucial for the purpose of a design of planning maintenance. This paper discusses the experimental evaluation of the stiffness reduction from frequency changes due to uniform damage scenario. For this purpose, a 1:4 scaled bridge has been built in the laboratory of the University of Bologna. It is made of concrete and its cross section is composed by a slab linked to four beams. This concrete deck is 6 m long and 3 m wide, and its natural frequencies have been identified dynamically by exciting it with an impact hammer, a dropping weight, or by walking on it randomly. After that, a set of loading cycles has been applied to this bridge in order to produce a uniformly distributed crack pattern. During the loading phase, either cracking moment and yielding moment has been reached. In order to define the relationship between frequency variation and loss in stiffness, the identification of the natural frequencies of the bridge has been performed, before and after the occurrence of the damage, corresponding to each load step. The behavior of breathing cracks and its effect on the natural frequencies has been taken into account in the analytical calculations. By using a sort of exponential function given from the study of lot of experimental tests in the literature, it has been possible to predict the stiffness reduction through the frequency variation measurements. During the load test also crack opening and middle span vertical displacement has been monitored.

Keywords: concrete bridge, damage detection, dynamic test, frequency shifts, operational modal analysis

Procedia PDF Downloads 180

Authors: I. Agboola Julius, Christopher A. Kumolu-Johnson, O. Kolade Rafiu, A. Saba Abdulwakil

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This work elucidates on mangrove diversity, trends of change, factors responsible for loss over the years and implications for sustainable livelihoods of locals in four villages (Ajido (L1), Tarkwa bay (L2), University of Lagos (L3), and Ikosi (L4)) along the coast of Lagos, Nigeria. Primary data were collected through field survey, questionnaires, interviews, and review of existing literature. Field observation and data analysis reveals mangrove diversity as low and varied on a spatial scale, where Margalef’s Diversity Index (D) was 0.368, 0.269, 0.326, and 0.333, respectively for L1, L2, L3, and L4. Shannon Weiner’s Index (H) was estimated to be 1.003, 1.460, 1.160, 1.046, and Specie Richness (E) 0.913, 0.907, 0.858, and 0.015, respectively, for the four villages. Also, The Simpson’s index of diversity was analyzed to be 0.632, 0. 731, 0.647, 0.667, and Simpson’s reciprocal index 2.717, 3.717, 3.060, and 3.003, respectively, for the four villages. Chi-square test was used to analyze the impact of mangrove loss on the sustainable livelihood of coastal communities. Calculated Chi-square (X2) value (5) was higher than tabulated value (4.30), suggesting that loss of mangrove wetlands impacted on local communities’ livelihood at the four villages. Analyses of causes and trends of mangrove wetland loss over the years suggest that urbanization, fuel wood and agricultural activities are major causes. Current degradation observed in mangrove wetlands on the Lagos coast suggest a reduction in mangroves biodiversity and associated fauna with potential cascading effects on higher trophic levels such as fisheries. Low yield in fish catch, reduction in income and increasing cases of natural disaster has culminated in threats to sustainable livelihoods of local communities along the coast of Lagos.

Keywords: Mangroves, lagos coast, fisheries, management

Procedia PDF Downloads 641

Authors: Philippe Gugler

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The aim of this study is to investigate how home country patterns may influence the competitiveness of EMNEs in international markets and more specifically their ability to invest abroad. The study examines the dynamic relationship between home country specific advantage and firms’ competitiveness. Are EMNEs still driven by strong country specific advantages or are EMNEs increasingly relying on their own firm specific competitiveness? EMNEs are not commonly recognized as a ‘homogeneous group’. Therefore, the approaches to these questions need to be specific while still attempting to extract some common evidence. The aim of the study is to elaborate a framework to investigate this issue in a dynamic context of international business’s strategies. The study focuses on two major research questions. The first one relates to the role of the home-base context in the internationalization process of EMNEs and more specifically the home-base assets’ influence on EMNEs competitiveness. Another question is to investigate the interactions among home-base context, recipient country context and EMNEs competitiveness. The evolution of EMNEs’ competitiveness is shaped by the evolution of the home country’s business environment. The nature of the home-based components in EMNEs’ specific advantages has changed over time due to the increased integration of emerging countries in the world market and the inherent changes related to their institutional, structural and regulatory patterns. The home country offers not only inherited assets but also a productive business environment, allowing firms to innovate, be more productive, create unique value for customers and finally, to face international competition successfully. The more sophisticated the home business environment is, the more opportunities there are for firms to developed exclusive and unique competitive assets. The international expansion of EMNEs is a fascinating but challenging issue. Among the numerous questions raised by the involvement of EMNEs in international competition is the evolving role of the home market. The purpose of this study is to examine some of the theoretical ideas and empirical evidence to allow us to deepen our understanding of the role of emerging home countries in the internationalization process of their domestic firms and more specifically in their ability to compete successfully abroad. How much do home specific assets still influence EMNEs’ foreign investment? Which home country assets provide the main competitive drivers to invest and compete abroad? How do EMNEs combine home country assets and host country assets to strengthen their competitive advantages? These questions as well as various others deserve further examination by the scientific community.

Keywords: competitiveness, emerging countries' multinational enterprises, foreign direct investments, international business

Procedia PDF Downloads 263

Authors: Zh. Saffari, A. Naeimi, M. S. Ekrami-Kakhki, F. Hamidi

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Fe3O4 is one of the important magnetic oxides with spinel structure; it has exhibited unique electric and magnetic properties based on the electron transfer between Fe2+ and Fe3+ in the octahedral sites. Fe3O4 has received considerable attention in various areas such as cancer therapy, drug targeting, enzyme immobilization catalysis, magnetic cell separation, magnetic refrigeration systems and super-paramagnetic materials Fe3O4–TiO2 nanostructures were synthesized by simple, effective and new co-precipitation method assisted by ultrasonic reaction at room temperatures with organic surfactant. The effect of various parameters such as temperature, time, and power on the size and morphology of the product was investigated. Alternating gradient force magnetometer shows that Fe3O4 nanoparticles exhibit super-paramagnetic behaviour at room temperature. For preparation of nanocomposite, 1 g of TiO2 nanostructures were dispersed in 100 mL of ethanol. 0.25 g of Fe(NO3)2 and 2 mL of octanoic acid was added to the solution as a surfactant. Then, NaOH solution (1.5 M) was slowly added into the solution until the pH of the mixture was 7–8. After complete precipitation, the solution placed under the ultrasonic irradiation for 30 min. The product was centrifuged, washed with distilled water and dried in an oven at 100 °C for 3 h. The resulting red powder was calcinated at 800 °C for 3 h to remove any organic residue. The photocatalytic behaviour of Fe3O4–TiO2 nanoparticles was evaluated using the degradation of a Methyl Violet (MV) aqueous solution under ultraviolet light irradiation. As time increased, more and more MV was adsorbed on the nanoparticles catalyst, until the absorption peak vanish. The MV concentration decreased rapidly with increasing UV-irradiation time

Keywords: magnetic, methyl violet, nanocomposite, photocatalytic

Procedia PDF Downloads 252

Authors: A. Bensaid, T. Mostephaoui, R. Nedjai

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A considerable area of Algerian lands is threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mecheria department generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of LANDSAT images (5, 7, and 8) of three scenes 197/37, 198/36 and 198/37 for the year 2020. As a second step, we prospect the use of geospatial techniques to monitor the progression of sand dunes on developed (urban) lands as well as on the formation of sandy accumulations (dune, dunes fields, nebkha, barkhane, etc.). For this purpose, this study made use of the semi-automatic processing method for the dynamic segmentation of images with very high spatial resolution (SENTINEL-2 and Google Earth). This study was able to demonstrate that urban lands under current conditions are located in sand transit zones that are mobilized by the winds from the northwest and southwest directions.

Keywords: land development, GIS, segmentation, remote sensing

Procedia PDF Downloads 149

Authors: Ekere E. Kokonne, Isimi C. Yetunde, Okoh E. Judith, Okafor E. Ijeoma, Ajeh J. Isaac, Olobayo O. Kunle, Emeje O. Martins

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NIPRIMAL® is a mono herbal formulation of Nauclea latifolia used in the treatment of malaria. The stability of extracts made from plant material is essential to ensure the quality, safety and efficacy of the finished product. This study assessed the stability of the formulation under three different storage conditions; normal room temperature, infrared and under refrigeration. Differential Scanning Calorimetry (DSC) and Thin Layer Chromatography (TLC) were used to monitor the formulations. The DSC analysis was done from 0oC to 350oC under the three storage conditions. Results obtained indicate that NIPRIMAL® was stable at all the storage conditions investigated. Thin layer chromatography (TLC) after 6 months showed there was no significant difference between retention factor (RF) values for the various storage conditions. The reference sample had four spots with RF values of 0.47, 0.68, 0.76, 0.82 respectively and these spots were retained in the test formulations with corresponding RF values were after 6 months at room temperature and refrigerated temperature been 0.56, 0.73, 0.80, 0.92 and 0.47, 0.68, 0.76, 0.82 respectively. On the other hand, the RF values (0.55, 0.74, 0.77, 0.93) obtained under infrared after 1 month varied slightly from the reference. The sample exposed to infrared had a lower heat capacity compared to that stored under room temperature or refrigeration. A combination of TLC and DSC measurements has been applied for assessing the stability of NIPRIMAL®. Both methods were found to be rapid, sensitive and reliable in determining its stability. It is concluded that NIPRIMAL® can be stored under any of the tested conditions without degradation. This study is a major contribution towards developing appropriate stability monitoring parameters for herbal products.

Keywords: differential scanning calorimetry, formulation, NIPRIMAL®, stability, thin layer hromatography

Procedia PDF Downloads 254

Authors: Matjaž Šraml, Marko Renčelj, Tomaž Tollazzi, Chiara Gruden

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Road safety is a worldwide issue with numerous and heterogeneous factors influencing it. On the side, driver state – comprising distraction/inattention, fatigue, drowsiness, extreme emotions, and socio-cultural factors highly affect road safety. On the other side, the vehicle state has an important role in mitigating (or not) the road risk. Finally, the road environment is still one of the main determinants of road safety, defining driving task complexity. At the same time, thanks to technological development, a lot of detailed data is easily available, creating opportunities for the detection of driver state, vehicle characteristics and road conditions and, consequently, for the design of ad hoc interventions aimed at improving driver performance, increase awareness and mitigate road risks. This is the challenge faced by the i-DREAMS project. i-DREAMS, which stands for a smart Driver and Road Environment Assessment and Monitoring System, is a 3-year project funded by the European Union’s Horizon 2020 research and innovation program. It aims to set up a platform to define, develop, test and validate a ‘Safety Tolerance Zone’ to prevent drivers from getting too close to the boundaries of unsafe operation by mitigating risks in real-time and after the trip. After the definition and development of the Safety Tolerance Zone concept and the concretization of the same in an Advanced driver-assistance system (ADAS) platform, the system was tested firstly for 2 months in a driving simulator environment in 5 different countries. After that, naturalistic driving studies started for a 10-month period (comprising a 1-month pilot study, 3-month baseline study and 6 months study implementing interventions). Currently, the project team has approved a common evaluation approach, and it is developing the assessment of the usage and outcomes of the i-DREAMS system, which is turning positive insights. The i-DREAMS consortium consists of 13 partners, 7 engineering universities and research groups, 4 industry partners and 2 partners (European Transport Safety Council - ETSC - and POLIS cities and regions for transport innovation) closely linked to transport safety stakeholders, covering 8 different countries altogether.

Keywords: advanced driver assistant systems, driving simulator, safety tolerance zone, traffic safety

Procedia PDF Downloads 62

Authors: Emmanuel Iyamuremye, Edouard Singirankabo, Alexis Habineza, Yunvirusaba Nelson

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Temperature is one of the most important climatic factors for crop production. However, severe temperatures cause drought, feverish and cold spells that have various consequences for human life, agriculture, and the environment in general. It is necessary to provide reliable information related to the incidents and the probability of such extreme events occurring. In the 21st century, the world faces a huge number of threats, especially from climate change, due to global warming and environmental degradation. The rise in temperature has a direct effect on the decrease in rainfall. This has an impact on crop growth and development, which in turn decreases crop yield and quality. Countries that are heavily dependent on agriculture use to suffer a lot and need to take preventive steps to overcome these challenges. The main objective of this study is to model the statistical behaviour of extreme maximum temperature values in Rwanda. To achieve such an objective, the daily temperature data spanned the period from January 2000 to December 2017 recorded at nine weather stations collected from the Rwanda Meteorological Agency were used. The two methods, namely the block maxima (BM) method and the Peaks Over Threshold (POT), were applied to model and analyse extreme temperature. Model parameters were estimated, while the extreme temperature return periods and confidence intervals were predicted. The model fit suggests Gumbel and Beta distributions to be the most appropriate models for the annual maximum of daily temperature. The results show that the temperature will continue to increase, as shown by estimated return levels.

Keywords: climate change, global warming, extreme value theory, rwanda, temperature, generalised extreme value distribution, generalised pareto distribution

Procedia PDF Downloads 175

Authors: Mwehe Mathenge, Ben G. J. S. Sonneveld, Jacqueline E. W. Broerse

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Smallholder farmers are important drivers of agriculture productivity, food security, and poverty reduction in Sub-Saharan Africa. However, they are faced with myriad challenges in their efforts at participating in agribusiness markets. How the geographic explicit factors existing at the local level interact to impede smallholder farmers' decision to participates (or not) in agribusiness markets is not well understood. Deconstructing the spatial complexity of the local environment could provide a deeper insight into how geographically explicit determinants promote or impede resource-poor smallholder farmers from participating in agribusiness. This paper’s objective was to identify, map, and analyze local spatial autocorrelation in factors that impede poor smallholders from participating in agribusiness markets. Data were collected using geocoded researcher-administered survey questionnaires from 392 households in Western Kenya. Three spatial statistics methods in geographic information system (GIS) were used to analyze data -Global Moran’s I, Cluster and Outliers Analysis (Anselin Local Moran’s I), and geographically weighted regression. The results of Global Moran’s I reveal the presence of spatial patterns in the dataset that was not caused by spatial randomness of data. Subsequently, Anselin Local Moran’s I result identified spatially and statistically significant local spatial clustering (hot spots and cold spots) in factors hindering smallholder participation. Finally, the geographically weighted regression results unearthed those specific geographic explicit factors impeding market participation in the study area. The results confirm that geographically explicit factors are indispensable in influencing the smallholder farming decisions, and policymakers should take cognizance of them. Additionally, this research demonstrated how geospatial explicit analysis conducted at the local level, using geographically disaggregated data, could help in identifying households and localities where the most impoverished and resource-poor smallholder households reside. In designing spatially targeted interventions, policymakers could benefit from geospatial analysis methods in understanding complex geographic factors and processes that interact to influence smallholder farmers' decision-making processes and choices.

Keywords: agribusiness markets, GIS, smallholder farmers, spatial statistics, disaggregated spatial data

Procedia PDF Downloads 136

Authors: Q. Rzina, M. Lahrouni, S. Rida, N. Saadaoui, Y. Almossaid, K. Oufdou, K. Fares

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Many organic solid wastes are produced in the world. Poultry manure (PM), municipal organic wastes (MOW) and sugar beet lime sludge (LS) are produced in large quantities in Morocco. The co-composting of these organic wastes was investigated. The recycling and the valorization of such wastes is environmentally and economically beneficial especially for PM which is known source of bacterial pathogens. The aerobic biodegradation process was carried out by using three windrows of variable compositions: C1 prepared without LS (only MOW were composted with PM), C2 prepared from MOW plus PM and10% LS; and the last one C3 from MOW plus PM and 20% LS. The main process physico-chemical parameters (temperature, pH, humidity and C/N) and microbiological populations (mesophilic and thermophilic flora, total coliform, fecal coliform, Streptococci, Staphylococcus aureus and mesophilic fungi) were monitored over three months to ascertain the compost maturity and to ensure the compost hygienic aspect. The final products were characterized by their relatively high organic matter content, and low C/N ratio of 10.6-10.9. The organic matter degradation was reached approximately 59% for C2 and C3. In addition, the monitoring of the microbial population showed that the produced composts are mature and hygienic. The agronomic valorization of the final composts was tested on radish plant with tree level of composts and poultry manure without composting. The primary results of field trial showed a growth of radish plant biomass and root development without any phytotoxicity detected which reflects the quality of the composts produced. As for poultry manure it allowed to have a better results than other composts because of its readily available nitrogen.

Keywords: compost, municipal organic wastes, poultry manure, radish crop, sugar beet lime sludge

Procedia PDF Downloads 305

Authors: Mustapha Ouardouz, Mina Amharref, Abdessamed Bernoussi

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The future energy, for limited energy resources countries, goes through renewable energies (solar, wind etc.). The renewable energies constitute a major component of the energy strategy to cover a substantial part of the growing needs and contribute to environmental protection by replacing fossil fuels. Indeed, sustainable development involves the promotion of renewable energy and the preservation of the environment by the use of clean energy technologies to limit emissions of greenhouse gases and reducing the pressure exerted on the forest cover. So the impact studies, of the energy use on the environment and farm-related risks are necessary. For that, a global approach integrating all the various sectors involved in such project seems to be the best approach. In this paper we present an approach based on the multi criteria analysis and the realization of one pilot to achieve the development of an innovative geo-intelligent environmental platform. An implementation of this platform will collect, process, analyze and manage environmental data in connection with the nature of used energy in the studied region. As an application we consider a region in the north of Morocco characterized by intense agricultural and industrials activities and using diverse renewable energy. The strategic goals of this platform are; the decision support for better governance, improving the responsiveness of public and private companies connected by providing them in real time with reliable data, modeling and simulation possibilities of energy scenarios, the identification of socio-technical solutions to introduce renewable energies and estimate technical and implantable potential by socio-economic analyzes and the assessment of infrastructure for the region and the communities, the preservation and enhancement of natural resources for better citizenship governance through democratization of access to environmental information, the tool will also perform simulations integrating environmental impacts of natural disasters, particularly those linked to climate change. Indeed extreme cases such as floods, droughts and storms will be no longer rare and therefore should be integrated into such projects.

Keywords: renewable energies, decision aided tool, environment, simulation

Procedia PDF Downloads 456

Authors: Buğra Sinmez

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In some countries, such as China, Turkey, andseveralEuropeanUnionnations, the therailwaypavementstructuralsystem has recently undergonerapid growth as a vital element of the transportation infrastructure, particularlyfortheuse of high-speed trains. It is vitaltoconsiderthe High-SpeedInfrastructureDemandwhendevelopingandconstructingtherailwaypavementstructure. HSRL can create more substantial ldifficultiestotheballastorbaselayer of regularlyusedballastedrailwaypavementsthanstandardrailwaytrains. The deterioration of the theballastorbaselayermayleadtosubstructuredegradation, which might lead to safety concerns and catastrophicincidents. As a result, the efficiency of railways will be impactedbylargecargoesorhigh-speed trains. A railwaypavement construction can be strengthened using geosyntheticmaterials in theballastorfoundationlayer as a countermeasure. However, there is still a need in the literature to quantifytheinfluence of geosynthetic materials, particularlygeogrid, on the mechanical responses of railwaypavementstructuresto HSRL loads which is essential knowledge in supporting the selection of appropriate material and geogridinstallationposition. As a result, the purpose of this research is to see how a geogridreinforcementlayermayaffectthekeyfeatures of a ballastedrailwaypavementstructure, with a particular focus on the materialtypeandgeogridplacementpositionthatmayassistreducethe rate of degradation of the therailwaypavementstructuresystem. Thisstudyusesnumericalmodeling in a genuinerailwaycontexttovalidatethebenefit of geogrid reinforcement. The usage of geogrids in the railway system has been thoroughly researched in the technical literature. Three distinct types of geogrid installed at two distinct positions (i.e.,withintheballastlayer, betweentheballastandthesub-ballast layer) within a railwaypavementconstructionwereevaluatedunder a variety of verticalwheelloadsusing a three-dimensional (3D) finite element model. As a result, fouralternativegeogridreinforcementsystemsweremodeledtoreflectdifferentconditions in the ballastedrailwaysystems (G0: no reinforcement; G1: reinforcedwithgeogridhavingthelowestdensityandYoung'smodulus; G2: reinforcedwithgeogridhavingtheintermediateYoung'smodulusanddensity; G3: reinforcedwithgeogridhavingthegreatestdensityandYoung'smodulus). Themechanicalreactions of the railway, such as verticalsurfacedeflection, maximumprimarystressandstrain, andmaximumshearstress, werestudiedandcomparedbetweenthefourgeogridreinforcementscenariosandfourverticalwheelloadlevels (i.e., 75, 100, 150, and 200 kN). Differences in the mechanical reactions of railwaypavementconstructionsowingtotheuse of differentgeogridmaterialsdemonstratethebenefits of suchgeosynthetics in ballast. In comparison to a non-reinforcedrailwaypavementconstruction, thereinforcedconstructionsfeaturedecreasedverticalsurfacedeflection, maximum shear stress at the sleeper-ballast contact, and maximum main stress at the bottom of the ballast layer. As a result, addinggeogridtotheballastlayerandbetweentheballastandsub-ballast layer in a ballastedrailwaypavementconstruction has beenfoundtolowercriticalshearand main stresses as well as verticalsurfacedeflection.

Keywords: geosynthetics, geogrid, railway, transportation

Procedia PDF Downloads 171

Authors: Chun-Hao Lai, Yu-Fang Huang, Pei-Wei Wang, Meng-Han Lin, Mei-Lien Chen

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Nonylphenol (NP) is a degradation product of nonylphenol ethoxylates (NPEOs). It is a well-known endocrine disruptor which may cause estrogenic effects. The growing fetus and infants are more vulnerable to exposure to NP than adults. It is important to know the levels and influences of prenatal exposure to NP. The aims of this study were (1) to determine the levels of prenatal exposure among Taiwanese, (2) to evaluate the potential risk for the infants who were breastfed and exposed to NP through the milk. (3) To investigate the correlation between birth outcomes and prenatal exposure to NP. We analyzed thirty one pairs of maternal urines, placentas, first month’ breast milk by high-performance liquid chromatography coupling with fluorescence detector. The questionnaire included socio- demographics, lifestyle, delivery method, dietary and work history. Information about the birth outcomes were obtained from medical records. The daily intake of NP from breast milk was calculated using deterministic and probabilistic risk assessment methods. The geometric means and geometric standard deviation of NP levels in placenta, and breast milk in the first month were 31.2 (1.8) ng/g, 17.2 (1.6) ng/g, respectively. The medium of daily intake NP in breast milk was 1.33 μg/kg-bw/day in the first month. We found negative association between NP levels of placenta and birth height. And we observed negative correlation between maternal urine NP levels and birth weight. In this study, we could provide the NP exposure profile among Taiwan pregnant women and the daily intake of NP in Taiwan infants. Prenatal exposure to higher levels of NP may increase the risk of lower birth weight and shorter birth height.

Keywords: nonylphenol, mother, fetus, placenta, breast milk, urine

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Authors: Adeshina Fadeyibi

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Application of pure thermoplastic film in food packaging is greatly limited because of its poor service performance, often enhanced by the addition of organic or inorganic particles in the range of 1–100 nm. Thus, this study was conducted to develop cassava starch zinc-nanocomposite films for applications in food packaging. Three blending ratios of 1000 g cassava starch, 45–55 % (w/w) glycerol and 0–2 % (w/w) zinc nanoparticles were formulated, mixed and mechanically homogenized to form the nanocomposite. Thermoplastic were prepared, from a dispersed mixture of 24 g of the nanocomposite and 600 ml of distilled water, and heated to 90oC for 30 minutes. Plastic molds of 350 ×180 mm dimension and 8, 10 and 12 mm depths were used for film casting and drying at 60oC and 80 % RH for 24 hour. The average thicknesses of the dried films were found to be 15, 16 and 17 µm. The films were characterized based on their barrier, thermal, mechanical and structural properties. The results show that the oxygen and water vapor barrier properties increased with glycerol concentration and decreased with thickness; but the full width at half maximum (FWHM) and d- spacing increased with thickness. The higher degree of d- spacing obtained is a consequence of higher polymer intercalation and exfoliation. Also, only 2 % weight degradation was observed when the films were exposed to temperature between 30–60oC; indicating that they are thermally stable and can be used for packaging applications in the tropics. The mechanical properties of the film were higher than that of the pure thermoplastic but comparable with the LDPE films. The information on the characterized attributes and optimization of the cassava starch zinc-nanocomposite films justifies their alternative application to pure thermoplastic and conventional films for food packaging.

Keywords: synthesis, characterization, casaava Starch, nanocomposite film, packaging

Procedia PDF Downloads 116

Authors: Petra Hofmann, Dana Koniel, Jussi Luukkanen, Walter Nieminen, Lea Hannola, Ilkka Donoghue

Abstract:

The Covid-19 pandemic forced people to isolate and become physically less connected. The pandemic hasnot only reshaped people’s behaviours and needs but also accelerated digital transformation (DT). DT of cities has become an imperative with the outlook of converting them into smart cities in the future. Embedding digital infrastructure and smart city initiatives as part of the normal design, construction, and operation of cities provides a unique opportunity to improve connection between people. Internet of Things (IoT) is an emerging technology and one of the drivers in DT. It has disrupted many industries by introducing different services and business models, and IoT solutions are being applied in multiple fields, including smart cities. As IoT and data are fundamentally linked together, IoT solutions can only create value if the data generated by the IoT devices is analysed properly. Extracting relevant conclusions and actionable insights by using established techniques, data analytics contributes significantly to the growth and success of IoT applications and investments. Companies must grasp DT and be prepared to redesign their offerings and business models to remain competitive in today’s marketplace. As there are many IoT solutions available today, the amount of data is tremendous. The challenge for companies is to understand what solutions to focus on and how to prioritise and which data to differentiate from the competition. This paper explains how IoT and data analytics can impact competitive advantage and how companies should approach IoT and data analytics to translate them into concrete offerings and solutions in the smart city context. The study was carried out as a qualitative, literature-based research. A case study is provided to validate the preservation of company’s competitive advantage through smart city solutions. The results of the researchcontribution provide insights into the different factors and considerations related to creating competitive advantage through IoT and data analytics deployment in the smart city context. Furthermore, this paper proposes a framework that merges the factors and considerations with examples of offerings and solutions in smart cities. The data collected through IoT devices, and the intelligent use of it, can create a competitive advantage to companies operating in smart city business. Companies should take into consideration the five forces of competition that shape industries and pay attention to the technological, organisational, and external contexts which define factors for consideration of competitive advantages in the field of IoT and data analytics. Companies that can utilise these key assets in their businesses will most likely conquer the markets and have a strong foothold in the smart city business.

Keywords: internet of things, data analytics, smart cities, competitive advantage

Procedia PDF Downloads 92

Authors: Rahul Jarariya

Abstract:

The textile industry uses various types of dyes and discharges a lot of highly coloured wastewater. It impacts the environment like allergic reaction, respiratory, skin problems, irritation to a mucous membrane, the upper respiratory tract has to the fore, Intoxicated dye discharges 40 to 50,000 tons with great concern. Spinel ferrites gained a lot of attention due to their wide application area from biomedical to wastewater treatment. Generally, spinel ferrite is known as M-Fe2O4. Spinel type nanoparticles possess high suspension stability. The synthesis method of Microwave solution combustion (MC) method is effective for nanoscale materials, including oxides, metals, alloys, and sulfides, works as fast and energy-efficient during the process. The review focuses on controlling, nanostructure and doping. The influence of the fuel concentration and the post-treatment temperature on the structural and magnetic properties. The effects of amounts of fuel and phase changes, particle size and shape, and magnetic properties can be characterized by various techniques. Urea is the most commonly used fuel. Ethanol or n-butanol is apt for removing impurities. As a result of the materials gives fine purity. Photocatalysis phenomena act with catalyst dosage to degrade dye from wastewater. Visible light responsive produces a large amount of hydroxyl (•OH) radical made the degradation efficiency of Rh21 type dye. It develops a narrow bandgap to make it suitable for enhanced photocatalytic activity.

Keywords: microwave solution combustion method, normal spinel, doped spinels, magnetic property, Rb21

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Authors: Carlos Rios Llamas

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Urban health challenges, like the obesity epidemic, need to be studied from a dialogue between different disciplines and geographical conditions. Public health uses quantitative analysis and local samples, but qualitative data and multisite analysis would help to better understand how obesity has become a health problem. In the last decades, obesity rates have increased in most of the countries, especially in the Western World. Concerned about the problem, the American Medical Association has recently voted obesity as a disease. Suddenly, a ‘war on obesity’ attracted scientists from different disciplines to explore various ways to control and even reverse the trends. Medical sciences have taken the advance with quantitative methodologies focused on individual behaviors. Only a few scientist have extended their studies to the environment where obesity is produced as social risk, and less of them have taken into consideration the political and cultural aspects. This paper presents a multisite ethnography in South Bronx, USA, La Courneuve, France, and Lomas del Sur, Mexico, where obesity rates are as relevant as urban degradation. The comparative ethnography offers a possibility to unveil the mechanisms producing health risks from the urban tissue. The analysis considers three main categories: 1) built environment and access to food and physical activity, 2) biocultural construction of the healthy body, 3) urban inequalities related to health and body size. Major findings from a comparative ethnography on obesogenic environments, refer to the anthropological values related to food and body image, as well as the multidimensional oppression expressed in fat people who live in stigmatized urban zones. At the end, obesity, like many other diseases, is the result of political and cultural constructions structured in urbanization processes.

Keywords: comparative ethnography, urban health, obesogenic cities, biopolitics

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Authors: Gyati Shilakari Asthana, Abhay Asthana, Dharm Veer Kohli, Suresh Prasad Vyas

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Purpose: The therapeutic potential of oligonucleotide (ODN) is primarily dependent upon its safe and efficient delivery to specific cells overcoming degradation and maximizing cellular uptake in vivo. The present study is focused to design low molecular weight chitosan nanoconstructs to meet the requirements of safe and effectual delivery of ODNs. LMW-chitosan is a biodegradable, water soluble, biocompatible polymer and is useful as a non-viral vector for gene delivery due to its better stability in water. Methods: LMW chitosan ODN nanoparticles (CHODN NPs) were formulated by self-assembled method using various N/P ratios (moles ratio of amine groups of CH to phosphate moieties of ODNs; 0.5:1, 1:1, 3:1, 5:1, and 7:1) of CH to ODN. The developed CHODN NPs were evaluated with respect to gel retardation assay, particle size, zeta potential and cytotoxicity and transfection efficiency. Results: Complete complexation of CH/ODN was achieved at the charge ratio of 0.5:1 or above and CHODN NPs displayed resistance against DNase I. On increasing the N/P ratio of CH/ODN, the particle size of the NPs decreased whereas zeta potential (ZV) value increased. No significant toxicity was observed at all CH concentrations. The transfection efficiency was increased on increasing N/P ratio from 1:1 to 3:1, whereas it was decreased with further increment in N/P ratio upto 7:1. Maximum transfection of CHODN NPs with both the cell lines (Raw 267.4 cells and Hela cells) was achieved at N/P ratio of 3:1. The results suggest that transfection efficiency of CHODN NPs is dependent on N/P ratio. Conclusion: Thus the present study states that LMW chitosan nanoparticulate carriers would be acceptable choice to improve transfection efficiency in vitro as well as in vivo delivery of oligonucleotide.

Keywords: LMW-chitosan, chitosan nanoparticles, biocompatibility, cytotoxicity study, transfection efficiency, oligonucleotide

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Authors: Abdalraheem Huwaysh, Khalil Al Samarrai, Yasmin ElAhmar

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Water quality is an important factor that determines its usage for domestic, agricultural and industrial uses. This study was carried out through the Tajoura Area, Jifarah Plain, Northwest Libya. Chemical and physical parameters were measured and analyzed for groundwater samples collected in 2021 from twenty-six wells distributed throughout the investigation area. Overexploitation of groundwater caused considerable deterioration in the water quality, especially at Tajoura Town (20 Km east of Tripoli). The aquifer shows an increase in salinization, which has reached an alarming level in many places during the past 25 years as a result of the seawater intrusion. The chemical composition of the water samples was compared with the drinking water standards of WHO and Libyan Standards. Groundwater from this area was not suitable to be a source for direct drinking based on Total Dissolved Solids. The dominant cation is sodium, while the dominant anion is chloride. Based on the Piper trilinear diagram, most of the groundwater samples (90%) were identified as sodium chloride type. The best groundwater quality exists at the southern part of the study area. Serious degradation in the water quality, expressed in salinity increase, occurs as we go towards the coastline. The abundance of NaCl waters is strong evidence to attribute the successive deterioration of the water quality to the seawater intrusion. Considering the values of Cl- concentration and the ratio of Cl-/HCO3-, about 70% of the groundwater samples were strongly affected by the saline water. Car wash stations in the study area as well as the unlined disposal pond used for the collection of untreated wastewater, contribute significantly to the deterioration of water quality. The water quality in this area needs to be monitored regularly and it is crucial to treat the water before consumption.

Keywords: Tajoura, groundwater, seawater intrusion, water quality

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Authors: Neha Verma, Manik Rakhra

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Statement of the Problem: Nowadays, a tremendous increase in population and advanced industrialization augment the problems related to air and water pollutions. Growing industries promoting environmental danger, which is an alarming threat to the ecosystem. For safeguard, the environment, detection of perilous gases and release of colored wastewater is required for eutrophication pollution. Researchers around the globe are trying their best efforts to save the environment. For this remediation advanced oxidation process is used for potential applications. ZnO is an important semiconductor photocatalyst with high photocatalytic and gas sensing activities. For efficient photocatalytic and gas sensing properties, it is necessary to prepare a doped/co-doped ZnO compound to decrease the electron-hole recombination rates. However, lanthanide doped and co-doped metal oxide is seldom studied for photocatalytic and gas sensing applications. The purpose of this study is to describe the best photocatalyst for the photodegradation of dyes and gas sensing properties. Methodology & Theoretical Orientation: Economical framework has to be used for the synthesis of ZnO. In the depth literature survey, a simple combustion method is utilized for gas sensing and photocatalytic activities. Findings: Rare earth doped and co-doped ZnO nanoparticles were the best photocatalysts for photodegradation of organic dyes and different gas sensing applications by varying various factors such as pH, aging time, and different concentrations of doping and codoping metals in ZnO. Complete degradation of dye was observed only in min. Gas sensing nanodevice showed a better response and quick recovery time for doped/co-doped ZnO. Conclusion & Significance: In order to prevent air and water pollution, well crystalline ZnO nanoparticles were synthesized by rapid and economic method, which is used as photocatalyst for photodegradation of organic dyes and gas sensing applications to sense the release of hazardous gases from the environment.

Keywords: ZnO, photocatalyst, photodegradation of dye, gas sensor

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Authors: Amal A. Al-Kahlawy, Heba H. El-Maghrabi

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Due to the increasing need to environment protection in real time need to energize new materials are under extensive investigations. Between others, TiO2 nanotubes (TNTs) nanocomposite with iron oxide and silver carbonate, are promising alternatives as high-efficiency visible light photocatalyst due to their unique properties and their superior charge transport properties. Our efforts in this domain aim the construction of novel nanocomposite of TiO2NT/Fe2O3@Ag2CO3. The structure, surface morphology, chemical composition and optical properties were characterized by X-ray diffraction (XRD), Raman, Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy dispersive X-ray spectrometer (EDS), transmission electron microscopy (TEM), selected area electron diffraction (SAED) and UV–vis diffuse reflectance spectroscopy (DRS). XRD results confirm the interaction of TiO2-NT with iron oxide. This novel nanocomposite shows remarkably enhanced performance for phenol compounds photodegradation. The experimental data shows a promising photocatalytic activity. In particular, a maximum value of 450 mg/g was removed within 60 min at solar light irradiation with degradation efficiency of 99.5%. The high photocatalytic activity of the nanocomposite is found to be related to the increased adsorption toward chemical species, enhanced light absorption and efficient charge separation and transfer. Finally, the designed TiO2NT/Fe2O3@Ag2CO3 nanocomposite has a great degree of sustainability and could has a potential application for the industrial treatment of wastewater containing toxic organic materials.

Keywords: nanocomposite, photocatalyst, solar energy, titanium dioxide nanotubes

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Authors: Zainab Bibi, Afsheen Aman, Shah Ali Ul Qader

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Endo-β-1,4-xylanases [EC 3.2.1.8] are one of the major groups of enzymes that are involved in degradation process of xylan and have several applications in food, textile and paper processing industries. Due to broad utility of endo-β-1,4-xylanase, researchers are focusing to increase the productivity of this hydrolase from various microbial species. Harsh industrial condition, faster reaction rate and efficient hydrolysis of xylan with low risk of contamination are critical requirements of industry that can be fulfilled by synthesizing the enzyme with efficient properties. In the current study, a newly isolated thermophile Geobacillus stearothermophilus KIBGE-IB29 was used in order to attain the maximum production of endo-1,4-β-xylanase. Bacterial culture was isolated from soil, collected around the blast furnace site of a steel processing mill, Karachi. Optimization of various nutritional and physical factors resulted the maximum synthesis of endo-1,4-β-xylanase from a thermophile. High production yield was achieved at 60°C and pH-6.0 after 24 hours of incubation period. Various nitrogen sources viz. peptone, yeast extract and meat extract improved the enzyme synthesis with 0.5%, 0.2% and 0.1% optimum concentrations. Dipotassium hydrogen phosphate (0.25%), potassium dihydrogen phosphate (0.05%), ammonium sulfate (0.05%) and calcium chloride (0.01%) were noticed as valuable salts to improve the production of enzyme. The thermophilic nature of isolate, with its broad pH stability profile and reduced fermentation time indicates its importance for effective xylan saccharification and for large scale production of endo-1,4-β-xylanase.

Keywords: geobacillus, optimization, production, xylanase

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Authors: Naeim Akbari Shahkhosravi, Reza Kakavand, Helen M. S. Davies, Amin Komeili

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Equine locomotion and performance are significantly affected by hoof health. One of the most critical diseases of the hoof is laminitis, which can lead to horse lameness in a severe condition. This disease exhibits the mechanical properties degradation of the laminar junction tissue within the hoof. Therefore, it is essential to investigate the biomechanics of the hoof, focusing specifically on excessive and cumulatively accumulated stresses within the laminar junction tissue. For this aim, the current study generated a novel equine hoof Finite Element (FE) model under dynamic physiological loading conditions and employing a hyperelastic material model. Associated tissues of the equine hoof were segmented from computed tomography scans of an equine forelimb, including the navicular bone, third phalanx, sole, frog, laminar junction, digital cushion, and medial- dorsal- lateral wall areas. The inner tissues were connected based on the hoof anatomy, and the hoof was under a dynamic loading over cyclic strides at the trot. The strain distribution on the hoof wall of the model was compared with the published in vivo strain measurements to validate the model. Then the validated model was used to study the development of laminitis. The ultimate stress tolerated by the laminar junction before rupture was considered as a stress threshold. The tissue damage was simulated through iterative reduction of the tissue’s mechanical properties in the presence of excessive maximum principal stresses. The findings of this investigation revealed how damage initiates from the medial and lateral sides of the tissue and propagates through the hoof dorsal area.

Keywords: horse hoof, laminitis, finite element model, continuous damage

Procedia PDF Downloads 178

Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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Authors: Alon Cohen, Jeffrey Kantor, Shalom Levy

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Technology adoption models are extensively used in the literature to explore drivers and inhibitors affecting the adoption of Computer Assisted Audit Techniques and Tools (CAATTs). Further studies from recent years suggested additional factors that may affect technology adoption by CPA firms. However, the adoption of CAATTs by financial auditors differs from the adoption of technologies in other industries. This is a result of the unique characteristics of the auditing process, which are expressed in the audit risk elements and the risk-based auditing approach, as encoded in the auditing standards. Since these audit risk factors are not part of the existing models that are used to explain technology adoption, these models do not fully correspond to the specific needs and requirements of the auditing domain. The overarching objective of this qualitative research is to fill the gap in the literature, which exists as a result of using generic technology adoption models. Followed by a pretest and based on semi-structured in-depth interviews with 16 Israeli CPA firms of different sizes, this study aims to reveal determinants related to audit risk factors that influence the adoption of CAATTs in audits and proposes a new modeling approach for the successful adoption of CAATTs. The findings emphasize several important aspects: (1) while large CPA firms developed their own inner guidelines to assess the audit risk components, other CPA firms do not follow a formal and validated methodology to evaluate these risks; (2) large firms incorporate a variety of CAATTs, including self-developed advanced tools. On the other hand, small and mid-sized CPA firms incorporate standard CAATTs and still need to catch up to better understand what CAATTs can offer and how they can contribute to the quality of the audit; (3) the top management of mid-sized and small CPA firms should be more proactive and updated about CAATTs capabilities and contributions to audits; and (4) All CPA firms consider professionalism as a major challenge that must be constantly managed to ensure an optimal CAATTs operation. The study extends the existing knowledge of CAATTs adoption by looking at it from a risk-based auditing approach. It suggests a new model for CAATTs adoption by incorporating influencing audit risk factors that auditors should examine when considering CAATTs adoption. Since the model can be used in various audited scenarios and supports strategic, risk-based decisions, it maximizes the great potential of CAATTs on the quality of the audits. The results and insights can be useful to CPA firms, internal auditors, CAATTs developers and regulators. Moreover, it may motivate audit standard-setters to issue updated guidelines regarding CAATTs adoption in audits.

Keywords: audit risk, CAATTs, financial auditing, information technology, technology adoption models

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Authors: A. Berraf-Tebbal, Z. Bouznad, , A.J.L. Phillips

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Phaeomoniella is a fungus genus in the mitosporic ascomycota which includes Phaeomoniella chlamydospora specie associated with two declining diseases on grapevine (Vitis vinifera) namely Petri disease and esca. Recent studies have shown that several Phaeomoniella species also cause disease on many other woody crops, such as forest trees and woody ornamentals. Two new species, Phaeomoniella zymoides and Phaeomoniella pinifoliorum H.B. Lee, J.Y. Park, R.C. Summerbell et H.S. Jung, were isolated from the needle surface of Pinus densiflora Sieb. et Zucc. in Korea. The identification of species in Phaeomoniella genus can be a difficult task if based solely on morphological and cultural characters. In this respect, the application of molecular methods, particularly PCR-based techniques, may provide an important contribution. MSP-PCR (microsatellite primed-PCR) fingerprinting has proven useful in the molecular typing of fungal strains. The high discriminatory potential of this method is particularly useful when dealing with closely related or cryptic species. In the present study, the application of PCR fingerprinting was performed using the micro satellite primer M13 for the purpose of species identification and strain typing of 84 Phaeomoniella -like isolates collected from grapevines with typical symptoms of dieback. The bands produced by MSP-PCR profiles divided the strains into 3 clusters and 5 singletons with a reproducibility level of 80%. Representative isolates from each group and, when possible, isolates from Eutypa dieback and esca symptoms were selected for sequencing of the ITS region. The ITS sequences for the 16 isolates selected from the MSP-PCR profiles were combined and aligned with sequences of 18 isolates retrieved from GenBank, representing a selection of all known Phaeomoniella species. DNA sequences were compared with those available in GenBank using Neighbor-joining (NJ) and Maximum-parsimony (MP) analyses. The phylogenetic trees of the ITS region revealed that the Phaeomoniella isolates clustered with Phaeomoniella chlamydospora reference sequences with a bootstrap support of 100 %. The complexity of the pathosystems vine-trunk diseases shows clearly the need to identify unambiguously the fungal component in order to allow a better understanding of the etiology of these diseases and justify the establishment of control strategies against these fungal agents.

Keywords: Genotyping, MSP-PCR, ITS, phylogeny, trunk diseases

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Authors: Erika Csanyi, Gyula Sandor

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In the course of the examination, we sought to answer the question of how and to what extent the home range and daily activity of a deer stag relocated from its habitual surroundings changes. We conducted the examination in two hunting areas in Hungary, about 50 km from one another. The control area was in the north of Somogy County, while the sample area was an area of similar features in terms of forest cover, tree stock, agricultural structure, altitude above sea level, climate, etc. in the south of Somogy County. Three middle-aged red deer stags were captured with rocket nets, immobilized and marked with GPS-Plus Collars manufactured by Vectronic Aerospace Gesellschaft mit beschränkter Haftung. One captured species was relocated. We monitored deer movements over 24-hour periods at 3 months. In the course of the examination, we analysed the behaviour of the relocated species and those that remained in their original habitat, as well as the temporal evolution of their behaviour. We examined the characteristics of the marked species’ daily activities and the hourly distance they covered. We intended to find out the difference between the behaviour of the species remaining in their original habitat and of those relocated to a more distant, but similar habitat. In summary, based on our findings, it can be established that such enforced relocations to a different habitat (e.g., game relocation) significantly increases the home range of the species in the months following relocation. Home ranges were calculated using the full data set and the minimum convex polygon (MCP) method. Relocation did not increase the nocturnal and diurnal movement activity of the animal in question. Our research found that the home range of the relocated species proved to be significantly higher than that of those species that were not relocated. The results have been presented in tabular form and have also been displayed on a map. Based on the results, it can be established that relocation inherently includes the risk of falling victim to poaching, vehicle collision. It was only in the third month following relocation that the home range of the relocated species subsided to the level of those species that were not relocated. It is advisable to take these observations into consideration in relocating red deer for nature conservation or game management purposes.

Keywords: Cervus elaphus, home range, relocation, red deer stag

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Authors: Adepoju Abiola Lydia, Adeyanju James Abiodun, Abioye A. O.

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Spray drying, an innovative and sustainable preservation method, is increasingly gaining recognition for its potential to enhance food security by extending the shelf life of fruits. This technique involves the atomization of fruit pulp into fine droplets, followed by rapid drying with hot air, resulting in a powdered product that retains much of the original fruit's nutritional value, flavor, and color. By encapsulating sensitive bioactive compounds within a dry matrix, spray drying mitigates nutrient degradation and extends product usability. This technology aligns with sustainability goals by reducing post-harvest losses, minimizing the need for preservatives, and lowering energy consumption compared to conventional drying methods. Furthermore, spray drying enables the use of imperfect or surplus fruits, contributing to waste reduction and providing a continuous supply of nutritious fruit-based ingredients regardless of seasonal variations. The powdered form enhances versatility, allowing incorporation into various food products, thus broadening the scope of fruit utilization. Innovations in spray drying, such as the use of novel carrier agents and optimization of processing parameters, enhance the quality and functionality of the final product. Moreover, the scalability of spray drying makes it suitable for both industrial applications and smaller-scale operations, supporting local economies and food systems. In conclusion, spray drying stands out as a key technology in enhancing food security by ensuring a stable supply of high-quality, nutritious food ingredients while fostering sustainable agricultural practices.

Keywords: spray drying, sustainable, process parameters, carrier agents, fruits

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