Search results for: geographic information systems (GIS)

Authors: Zahra Soltani Shal

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Introduction: The COVID-19 pandemic marks an extraordinary global public health crisis unseen in the last century, with its rapid spread worldwide and associated mortality burden. Healthcare resilience during a pandemic is crucial not only for continuous and safe patients care but also for control of any outbreak. Aim: The present study was conducted to discover the organizational variables effective in increasing resilience and continuing the work of nurses in critical and stressful pandemic conditions. Method: The study population is nurses working in hospitals for patients with coronavirus. Sampling was done purposefully and information was collected from 15 nurses through In-depth semi-structured interviews. The interview was conducted to analyze the data using the framework analysis method consisting of five steps and is classified in the table. Results: According to the findings through semi-structural interviews, among organizational variables, organizational commitment (Affective commitment, continuous commitment, normative commitment) has played a prominent role in nurses' resilience. Discussion: despite the non-withdrawal of nurses and their resilience, due to the negative quality of their working life, the mentioned variable has affected their level of performance and ability and leads to fatigue and physical and mental exhaustion. Implications for practice: By equipping hospitals and improving the facilities of nurses, their organizational commitment can be increased and lead to their resilience in critical situations. Supervisors and senior officials at the hospitals should be responsible for nurses' health and safety. A clear and codified program in critical situations and comprehensive management is effective in improving the quality of the work-life of nurses. Creating an empathetic and interactive environment can help promote nurses' mental health.

Keywords: organizational commitment, quality of work life, nurses resilience, pandemic, coronavirus

Procedia PDF Downloads 169

Authors: Mauro Callejas-Cuervo, Andrea Catherine Alarcon-Aldana, Lorena Paola Castillo-Guerra

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The software industry requires highly-trained professionals, capable of developing the roles integrated in the cycle of software development. That is why a large part of the task is the responsibility of higher education institutions; often through a curriculum established to orientate the academic development of the students. It is so that nowadays there are different models that support proposals for the improvement of the curricula for the area of Software Engineering, such as ACM, IEEE, ABET, Swebok, of which the last stands out, given that it manages and organises the knowledge of Software Engineering and offers a vision of theoretical and practical aspects. Moreover, it has been applied by different universities in the pursuit of achieving coverage in delivering the different topics and increasing the professional quality of future graduates. This research presents the structure of teaching and learning guides from the objectives of training and methodological strategies immersed in the levels of learning of Bloom’s taxonomy with which it is intended to improve the delivery of the topics in the area of Requirements Engineering. Said guides were implemented and validated in a course of Requirements Engineering of the Systems and Computer Engineering programme in the Universidad Pedagógica y Tecnológica de Colombia (Pedagogical and Technological University of Colombia) using a four stage methodology: definition of the evaluation model, implementation of the guides, guide evaluation, and analysis of the results. After the collection and analysis of the data, the results show that in six out of the seven topics proposed in the Swebok guide, the percentage of students who obtained total marks within the 'High grade' level, that is between 4.0 and 4.6 (on a scale of 0.0 to 5.0), was higher than the percentage of students who obtained marks within the 'Acceptable' range of 3.0 to 3.9. In 86% of the topics and the strategies proposed, the teaching and learning guides facilitated the comprehension, analysis, and articulation of the concepts and processes of the students. In addition, they mainly indicate that the guides strengthened the argumentative and interpretative competencies, while the remaining 14% denotes the need to reinforce the strategies regarding the propositive competence, given that it presented the lowest average.

Keywords: pedagogic guide, pedagogic strategies, requirements engineering, Swebok, teaching-learning process

Procedia PDF Downloads 289

Authors: Esam Jassim

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Industries using conventional fossil fuels have an interest in better understanding the mechanism of particulate formation during combustion since such is responsible for emission of undesired inorganic elements that directly impact the atmospheric pollution level. Fine and ultrafine particulates have tendency to escape the flue gas cleaning devices to the atmosphere. They also preferentially collect on surfaces in power systems resulting in ascending in corrosion inclination, descending in the heat transfer thermal unit, and severe impact on human health. This adverseness manifests particularly in the regions of world where coal is the dominated source of energy for consumption. This study highlights the behavior of calcium transformation as mineral grains verses organically associated inorganic components during pulverized coal combustion. The influence of existing type of calcium on the coarse, fine and ultrafine mode formation mechanisms is also presented. The impact of two sub-bituminous coals on particle size and calcium composition evolution during combustion is to be assessed. Three mixed blends named Blends 1, 2, and 3 are selected according to the ration of coal A to coal B by weight. Calcium percentage in original coal increases as going from Blend 1 to 3. A mathematical model and a new approach of describing constituent distribution are proposed. Analysis of experiments of calcium distribution in ash is also modeled using Poisson distribution. A novel parameter, called elemental index λ, is introduced as a measuring factor of element distribution. Results show that calcium in ash that originally in coal as mineral grains has index of 17, whereas organically associated calcium transformed to fly ash shown to be best described when elemental index λ is 7. As an alkaline-earth element, calcium is considered the fundamental element responsible for boiler deficiency since it is the major player in the mechanism of ash slagging process. The mechanism of particle size distribution and mineral species of ash particles are presented using CCSEM and size-segregated ash characteristics. Conclusions are drawn from the analysis of pulverized coal ash generated from a utility-scale boiler.

Keywords: coal combustion, inorganic element, calcium evolution, fluid dynamics

Procedia PDF Downloads 340

Authors: Tooba Sabir, Asima Jaffar, Namra Sabir, Mohammad Amjad Sabir

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Ecocriticism is the study of relationship between human and environment which has been represented in literature since the very beginning in pastoral tradition. However, the analysis of such representation is new as compared to the other critical evaluations like Psychoanalysis, Marxism, Post-colonialism, Modernism and many others. Ecocritics seek to find information like anthropocentrism, ecocentrism, ecofeminism, eco-Marxism, representation of environment and environmental concept and several other topics. In the current study the representation of environmental concepts, were ecocritically analyzed in Paulo Coelho’s The Alchemist, one of the most read novels throughout the world, having been translated into many languages. Analysis of the text revealed, the representations of environmental ideas like landscapes and tourism, biodiversity, land-sea displacement, environmental disasters and warfare, desert winds and sand dunes. 'This desert was once a sea' throws light on different theories of land-sea displacement, one being the plate-tectonic theory which proposes Earth’s lithosphere to be divided into different large and small plates, continuously moving toward, away from or parallel to each other, resulting in land-sea displacement. Another theory is the continental drift theory which holds onto the belief that one large landmass—Pangea, broke down into smaller pieces of land that moved relative to each other and formed continents of the present time. The cause of desertification may, however, be natural i.e. climate change or artificial i.e. by human activities. Imagery of the environmental concepts, at some instances in the novel, is detailed and at other instances, is not as striking, but still is capable of arousing readers’ imagination. The study suggests that ecocritical justifications of environmental concepts in the text will increase the interactions between literature and environment which should be encouraged in order to induce environmental awareness among the readers.

Keywords: biodiversity, ecocritical analysis, ecocriticism, environmental disasters, landscapes

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Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

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This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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Authors: Virginia Martin Torrejon, Binjie Wu

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Gelatine is a protein biopolymer obtained from the partial hydrolysis of animal tissues which contain collagen, the primary structural component in connective tissue. Gelatine hydrogels have attracted considerable research in recent years as an alternative to synthetic materials due to their outstanding gelling properties, biocompatibility and compostability. Surfactants, such as sodium dodecyl sulfate (SDS), are often used in hydrogels solutions as surface modifiers or solubility enhancers, and their incorporation can influence the hydrogel’s viscoelastic properties and, in turn, its processing and applications. Literature usually focuses on studying the impact of formulation parameters (e.g., gelatine content, gelatine strength, additives incorporation) on gelatine hydrogels properties, but processing parameters, such as curing temperature, are commonly overlooked. For example, some authors have reported a decrease in gel strength at lower curing temperatures, but there is a lack of research on systematic viscoelastic characterisation of high strength gelatine and gelatine-SDS systems at a wide range of curing temperatures. This knowledge is essential to meet and adjust the technological requirements for different applications (e.g., viscosity, setting time, gel strength or melting/gelling temperature). This work investigated the effect of curing temperature (10, 15, 20, 23 and 25 and 30°C) on the elastic modulus (G’) and melting temperature of high strength gelatine-SDS hydrogels, at 10 wt% and 20 wt% gelatine contents, by small-amplitude oscillatory shear rheology coupled with Fourier Transform Infrared Spectroscopy. It also correlates the gel strength obtained by rheological measurements with the gel strength measured by texture analysis. Gelatine and gelatine-SDS hydrogels’ rheological behaviour strongly depended on the curing temperature, and its gel strength and melting temperature can be slightly modified to adjust it to given processing and applications needs. Lower curing temperatures led to gelatine and gelatine-SDS hydrogels with considerably higher storage modulus. However, their melting temperature was lower than those gels cured at higher temperatures and lower gel strength. This effect was more considerable at longer timescales. This behaviour is attributed to the development of thermal-resistant structures in the lower strength gels cured at higher temperatures.

Keywords: gelatine gelation kinetics, gelatine-SDS interactions, gelatine-surfactant hydrogels, melting and gelling temperature of gelatine gels, rheology of gelatine hydrogels

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Authors: Babina Aryal

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Background: The diagnosis of pancreatitis is generally based on clinical and laboratory findings; however, Computed Tomography (CT) is an imaging technique of choice specially Contrast Enhanced Computed Tomography (CECT) shows morphological characteristic findings that allow for establishing the diagnosis of pancreatitis and determining the extent of disease severity which is done along with the administration of appropriate contrast medium. The purpose of this study was to compare Computed Tomography Dose Index (CTDI), Dose Length Product (DLP) and Effective Dose (ED) among male and female patients from Contrast Enhanced Computed Tomography (CECT) Pancreatitis Protocol. Methods: This retrospective study involved data collection based on clinical/laboratory/ultrasonography diagnosis of Pancreatitis and has undergone CECT Abdomen pancreatitis protocol. data collection involved detailed information about a patient's Age and Gender, Clinical history, Individual Computed Tomography Dose Index and Dose Length Product and effective dose. Results: We have retrospectively collected dose data from 150 among which 127 were males and 23 were females. The values obtained from the display of the CT screen were measured, calculated and compared to determine whether the CTDI, DLP and ED values were similar or not. CTDI for females was more as compared to males. The differences in CTDI values for females and males were 32.2087 and 37.1609 respectively. DLP values and Effective dose for both the genders did not show significant differences. Conclusion: This study concluded that there were no more significant changes in the DLP and ED values among both the genders however we noticed that female patients had more CTDI than males.

Keywords: computed tomography, contrast enhanced computed tomography, computed tomography dose index, dose length product, effective dose

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Authors: Khadijat Olabisi Abdulwahab, Mohammad Azad Malik, Paul O'Brien, Grigore Timco, Floriana Tuna

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The synthesis of spinel ferrite nanoparticles with a narrow size distribution is very crucial in their numerous applications including information storage, hyperthermia treatment, drug delivery, contrast agent in magnetic resonance imaging, catalysis, sensors, and environmental remediation. Ferrites have the general formula MFe₂O₄ (M = Fe, Co, Mn, Ni, Zn e.t.c) and possess remarkable electrical and magnetic properties which depend on the cations, method of preparation, size and their site occupancies. To the best of our knowledge, there are no reports on the use of a single source precursor to synthesise quaternary ferrite nanoparticles. Here in, we demonstrated the use of trimetallic iron pivalate cluster [CrCoFeO(O₂CᵗBu)₆(HO₂CᵗBu)₃] as a single source precursor to synthesise monodisperse cobalt chromium ferrite (FeCoCrO₄) nanoparticles by the hot injection thermolysis method. The precursor was thermolysed in oleylamine, oleic acid, with diphenyl ether as solvent at 260 °C. The effect of reaction time on the stoichiometry, phases or morphology of the nanoparticles was studied. The p-XRD patterns of the nanoparticles obtained after one hour was pure phase of cubic iron cobalt chromium ferrite (FeCoCrO₄). TEM showed that a more monodispersed spherical ferrite nanoparticles were obtained after one hour. Magnetic measurements revealed that the ferrite particles are superparamagnetic at room temperature. The nanoparticles were characterised by Powder X-ray Diffraction (p-XRD), Transmission Electron Microscopy (TEM), Energy Dispersive Spectroscopy (EDS) and Super Conducting Quantum Interference Device (SQUID).

Keywords: cobalt chromium ferrite, colloidal, hot injection thermolysis, monodisperse, reaction time, single source precursor, quaternary ferrite nanoparticles

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Authors: Natalia Feruleva

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The goal of this paper is to develop the fraud risk assessment model basing on both relational and financial data and test the impact of the relationships between Russian non-public companies on the likelihood of financial fraud commitment. Relationships mean various linkages between companies such as parent-subsidiary relationship and person-related relationships. These linkages may provide additional opportunities for committing fraud. Person-related relationships appear when firms share a director, or the director owns another firm. The number of companies belongs to CEO and managed by CEO, the number of subsidiaries was calculated to measure the relationships. Moreover, the dummy variable describing the existence of parent company was also included in model. Control variables such as financial leverage and return on assets were also implemented because they describe the motivating factors of fraud. To check the hypotheses about the influence of the chosen parameters on the likelihood of financial fraud, information about person-related relationships between companies, existence of parent company and subsidiaries, profitability and the level of debt was collected. The resulting sample consists of 160 Russian non-public firms. The sample includes 80 fraudsters and 80 non-fraudsters operating in 2006-2017. The dependent variable is dichotomous, and it takes the value 1 if the firm is engaged in financial crime, otherwise 0. Employing probit model, it was revealed that the number of companies which belong to CEO of the firm or managed by CEO has significant impact on the likelihood of financial fraud. The results obtained indicate that the more companies are affiliated with the CEO, the higher the likelihood that the company will be involved in financial crime. The forecast accuracy of the model is about is 80%. Thus, the model basing on both relational and financial data gives high level of forecast accuracy.

Keywords: financial fraud, fraud prediction, non-public companies, regression analysis, relational data

Procedia PDF Downloads 126

Authors: Elucir Gir, Laelson Rochelle Milanês Sousa, Pedro Henrique Tertuliano Leoni, Carla Aparecida Arena Ventura, Ana Cristina de Oliveira e Silva, Renata Karina Reis

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Context and significance: Resilience is a protective agent for the physical and mental well-being of nursing professionals. Team members are constantly subjected to high levels of work stress that can negatively impact care performance and users of health services. Stress levels have been exacerbated with the COVID-19 pandemic. Objective: The aim of this study was to analyze the resilience of nursing professionals in Brazil during the COVID-19 pandemic. Method: Cross-sectional study with a quantitative approach carried out with professionals from nursing teams from all regions of Brazil. Data collection took place in the first year of the pandemic between October and December 2020. Data were obtained through an online questionnaire posted on social networks. The information collected included the sociodemographic characterization of the nursing professionals and the Brief Resilient Coping Scale was applied. Student's t-test for independent samples and analysis of variance (ANOVA) were used to compare resilience scores with sociodemographic variables. Results: 8,792 nursing professionals participated in the study, 5,767 (65.6%) were nurses, 7,437 (84.6%) were female and 2,643 (30.1%) were from the Northeast region of Brazil, 5,124 (58.8% ) had low levels of resilience. The results showed a statistically significant difference between the resilience score and the variables: professional category (p<0.001); sex (p = 0.003); age range (p<0.001); region of Brazil (p<0.001); marital status (p=0.029) and providing assistance in a field hospital (p<0.001). Conclusion: Participants in this study had, in general, low levels of resilience. There is an urgent need for actions aimed at promoting the psychological health of nursing professionals inserted in pandemic contexts. Descriptors: Psychological Resilience; Nursing professionals; COVID-19; SARSCoV-2.

Keywords: psychological resilience, nursing professionals, COVID-19, SARS-CoV-2

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Authors: Laurin Zemmrich, Nicolai Stickler

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With the ongoing debate over how to incorporate sustainability, resilience, and value creation into business strategies, many procurement departments are put under pressure by governments, consumers, non-governmental organizations, and other stakeholders to disclose more information about their supply chains. According to practitioners and experts, procurement benefits the supply chain by increasing transparency and accountability, recruiting new suppliers, and supporting sustainable and ethical sourcing strategies. While most procurement departments establish these objectives, the bulk of activities are not carried out or are not regularly monitored. With the full potential of targeted sourcing still to be realized, procurement executives, in particular, are seeking for short-term cost-cutting impacts to appease external shareholders. We overcome this limitation by using an abductive approach to research and integrating empirical data from a Gioia methodology study design with relevant literature. Our analysis demonstrates that the procurement department has six essential levers aligned with sustainability, resilience, and value creation objectives and contributes to developing a new intra- and interorganizational purpose within the supply chain. Three enablers are identified as having a value-creating effect on supply chain interactions. Additionally, we discovered two impacts that alter the power balance between buyers and suppliers during transactions and have a cost-cutting or cost-avoiding effect. While cost-cutting, cost-avoidance, and dependency-reduction impacts are desirable, redistributing power may also have negative consequences. The article establishes a first strategy framework for evaluating the influence of the procurement department on supply chain transactions, allowing managers to understand better and apply the sourcing function inside a supply chain and embed it throughout the business.

Keywords: supply chain management, resilience, sustainability, value creation, purpose

Procedia PDF Downloads 122

Authors: Karan Bhandari

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Almost quarter region of Indian terrain is covered by grasslands. Grass being a low maintenance perennial crop is in abundance. Farmers are well acquainted with its nature, yield and storage. The aim of this paper is to study and identify the applicability of grass as a source of bio fuel. Anaerobic break down is a well-recognized technology. This process is vital for harnessing bio fuel from grass. Grass is a lignocellulosic material which is fibrous and can readily cause problems with parts in motion. Further, it also has a tendency to float. This paper also deals with the ideal digester configuration for biogas generation from grass. Intensive analysis of the literature is studied on the optimum production of grass storage in accordance with bio digester specifications. Subsequent to this two different digester systems were designed, fabricated, analyzed. The first setup was a double stage wet continuous arrangement usually known as a Continuously Stirred Tank Reactor (CSTR). The next was a double stage, double phase system implementing Sequentially Fed Leach Beds using an Upflow Anaerobic Sludge Blanket (SLBR-UASB). The above methodologies were carried for the same feedstock acquired from the same field. Examination of grass silage was undertaken using Biomethane Potential values. The outcomes portrayed that the Continuously Stirred Tank Reactor system produced about 450 liters of methane per Kg of volatile solids, at a detention period of 48 days. The second method involving Leach Beds produced about 340 liters of methane per Kg of volatile solids with a detention period of 28 days. The results showcased that CSTR when designed exclusively for grass proved to be extremely efficient in methane production. The SLBR-UASB has significant potential to allow for lower detention times with significant levels of methane production. This technology has immense future for research and development in India in terms utilizing of grass crop as a non-conventional source of fuel.

Keywords: biomethane potential values, bio digester specifications, continuously stirred tank reactor, upflow anaerobic sludge blanket

Procedia PDF Downloads 248

Authors: Faruk Aras, Melih Inal, Tansel Cinar

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The coordination of airport staff especially in the operations and maintenance departments is important for the airport operation. As a result, this coordination will increase the efficiency in all operation. Therefore, a Collaborative Decision-Making (CDM) system targets on improving the overall productivity of all operations by optimizing the use of resources and improving the predictability of actions. Enlarged productivity can be of major benefit for all airport operations. It also increases cost-efficiency. This study explains how predictive maintenance using IoT (Internet of Things), predictive operations and the statistical data such as Mean Time To Failure (MTTF) improves airport terminal operations and utilize airport terminal equipment in collaboration with collaborative decision making system/Airport Operation Control Center (AOCC). Data generated by the predictive maintenance methods is retrieved and analyzed by maintenance managers to predict when a problem is about to occur. With that information, maintenance can be scheduled when needed. As an example, AOCC operator would have chance to assign a new gate that towards to this gate all the equipment such as travellator, elevator, escalator etc. are operational if the maintenance team is in collaboration with AOCC since maintenance team is aware of the health of the equipment because of predictive maintenance methods. Applying predictive maintenance methods based on analyzing the health of airport terminal equipment dramatically reduces the risk of downtime by on time repairs. We can classify the categories as high priority calls for urgent repair action, as medium priority requires repair at the earliest opportunity, and low priority allows maintenance to be scheduled when convenient. In all cases, identifying potential problems early resulted in better allocation airport terminal resources by AOCC.

Keywords: airport, predictive maintenance, collaborative decision-making system, Airport Operation Control Center (AOCC)

Procedia PDF Downloads 367

Authors: Christin Koch, Andreas Winkel, Martin Kahlmeyer, Stefan Böhm

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Due to environmental regulations on greenhouse gas emissions and the depletion of fossil fuels, there is an increasing interest in electric vehicles.To maximize their driving range, batteries with high storage capacities are needed. In most electric cars, rechargeable lithium-ion batteries are used because of their high energy density. However, it has to be taken into account that these batteries generate a large amount of heat during the charge and discharge processes. This leads to a decrease in a lifetime and damage to the battery cells when the temperature exceeds the defined operating range. To ensure an efficient performance of the battery cells, reliable thermal management is required. Currently, the cooling is achieved by heat sinks (e.g., cooling plates) bonded to the battery cells with a thermally conductive adhesive (TCA) that directs the heat away from the components. Especially when large amounts of heat have to be dissipated spontaneously due to peak loads, the principle of heat conduction is not sufficient, so attention must be paid to the mechanism of heat storage. An efficient method to store thermal energy is the use of phase change materials (PCM). Through an isothermal phase change, PCM can briefly absorb or release thermal energy at a constant temperature. If the phase change takes place in the transition from solid to liquid, heat is stored during melting and is released to the ambient during the freezing process upon cooling. The presented work displays the great potential of thermally conductive adhesives filled with microencapsulated PCM to limit peak temperatures in battery systems. The encapsulation of the PCM avoids the effects of aging (e.g., migration) and chemical reactions between the PCM and the adhesive matrix components. In this study, microencapsulation has been carried out by in situ polymerization. The microencapsulated PCM was characterized by FT-IR spectroscopy, and the thermal properties were measured by DSC and laser flash method. The mechanical properties, electrical and thermal conductivity, and adhesive toughness of the TCA/PCM composite were also investigated.

Keywords: phase change material, microencapsulation, adhesive bonding, thermal management

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Authors: Amjad Alsulami, Farah Albishri, Kholod Alzubidi, Lama Almehemadi, Salma Elhag

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Food allergy is a common and rising problem among children. Many students have their first allergic reaction at school, one of these is anaphylaxis, which can be fatal. This study discovered that several schools' processes lacked safety regulations and information on how to handle allergy issues and chronic diseases like diabetes where students were not supervised or monitored during the cafeteria purchasing process. There is no obvious prevention or effort in academic institutions when purchasing food containing allergens or negatively impacting the health status of students who suffer from chronic diseases. Students must always be stable to reflect positively on their educational development process. To address this issue, this paper uses a business reengineering process to propose the automation of the whole food-purchasing process, which will aid in detecting and avoiding allergic occurrences and preventing any side effects from eating foods that are conflicting with students' health. This may be achieved by designing a smart card with an embedded QR code that reveals which foods cause an allergic reaction in a student. A survey was distributed to determine and examine how the cafeteria will handle allergic children and whether any management or policy is applied in the school. Also, the survey findings indicate that the integration of QR technology into the food purchasing process would improve health condition detection. The suggested system would be beneficial to all parties, the family agreed, as they would ensure that their children didn't eat foods that were bad for their health. Moreover, by analyzing and simulating the as-is process and the suggested process the results demonstrate that there is an improvement in quality and time.

Keywords: QR code, smart card, food allergies, business process reengineering, health condition detection

Procedia PDF Downloads 81

Authors: Ibrahim Magaji

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WhatsApp messaging platform brings about new opportunities for users to participate in unique storytelling experiences and audience engagement, particularly to Students of Mass communication who receive training to report events and issues accurately and objectively in accordance with official controls. Also, the complex nature of society today made it possible to use the WhatsApp platform that revolutionizes the means of sharing information, ideas, and experiences. This paper examined the WhatsApp messaging platform and how it influenced the academic performance of students in the Department of Mass Communication, Abdu Gusau Polytechnic, Talata Mafara. It used in-depth interview techniques and focus group discussion with students, as well as the use of published materials as well as unpublished materials to gather related and relevant data. Also, the paper used procedures involved to analyze long interview content. This procedure includes observation of a useful utterance, development of expanded observation, the examination of the interconnection of observed comments, collective scrutiny of observation for patterns and themes, and review and analysis of the themes across all interviews for development of the thesis. The result revealed that the majority of students used WhatsApp messenger for making friends and chatting. Also, the students experienced negative effects such as poor grammar and spelling, less study time, and poor academic performance because of active participation in the use of WhatsApp messaging platform. Surprisingly, there was a high addiction rate among students in the usage of WhatsApp messenger. However, other students experienced an improvement in their readings skills as a result of participation in the use of the platform. Also, students shared ideas, discussed, and shared examination questions among themselves on WhatsApp messenger.

Keywords: WhatsApp messenger, students, participation, group

Procedia PDF Downloads 136

Authors: Kumiko Inagaki

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In recent, years, Japanese universities have begun to face a dilemma: more than half of all high school graduates go on to attend an institution of higher learning, overwhelming Japanese universities accustomed to small student bodies. These universities have been forced to embrace qualitative changes to accommodate the increased number and diversity of students who enter their establishments, students who differ in their motivations for learning, their levels of eagerness to learn, and their perspectives on the future. One of these changes is an increase in awareness among Japanese educators of the importance of active learning, which deepens students’ understanding of course material through a range of activities, including writing, speaking, thinking, and presenting, in addition to conventional “passive learning” methods such as listening to a one-way lecture. 　The purpose of this study is to examine the effectiveness of the teaching method adapted to improve active learning. A teaching method designed to promote active learning was implemented in a social science course at one of the most popular universities in Japan. A questionnaire using a five-point response format was given to students in 2,305 courses throughout the university to evaluate the effectiveness of the method based on the following measures: ① the ratio of students who were motivated to attend the classes, ② the rate at which students learned new information, and ③ the teaching method adopted in the classes. The results of this study show that the percentage of students who attended the active learning course eagerly, and the rate of new knowledge acquired through the course, both exceeded the average for the university, the department, and the subject area of social science. In addition, there are strong correlations between teaching method and student motivation and between teaching method and knowledge acquisition rate. These results indicate that the active learning teaching method was effectively implemented and that it may improve student eagerness to attend class and motivation to learn.

Keywords: active learning, Japanese university, teaching method, university education

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Authors: Oksana Razina, Shakeel Ahmad, Jessie Qun Ren, Olufemi Isiaq

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The modern life of businesses is categorically reliant on their established position online, where digital (and particularly website) content plays a significant role as the first point of information. Digital content, therefore, becomes essential – from making the first impression to the building and development of client relationships. Despite a number of valuable papers suggesting a strategic approach when dealing with digital data, other sources often do not view or accept the approach to digital content as a holistic or continuous process. Associations are frequently made with merely a one-off marketing campaign or similar. The challenge is to establish an agreed definition for the notion of Digital Content Strategy, which currently does not exist, as DCS is viewed from an excessive number of different angles. A strategic approach to content, nonetheless, is required, both practically and contextually. The researchers, therefore, aimed at attempting to identify the key content components comprising a digital content strategy to ensure all the aspects were covered and strategically applied – from the company’s understanding of the content value to the ability to display flexibility of content and advances in technology. This conceptual project evaluated existing literature on the topic of Digital Content Strategy (DCS) and related aspects, using the PRISMA Systematic Review Method, Document Analysis, Inclusion and Exclusion Criteria, Scoping Review, Snow-Balling Technique and Thematic Analysis. The data was collected from academic and statistical sources, government and relevant trade publications. Based on the suggestions from academics and trading sources related to the issues discussed, the researchers revealed the key actions for content creation and attempted to define the notion of DCS. The major finding of the study presented Key Content Components of Digital Content Strategy and can be considered for implementation in a business retail setting.

Keywords: digital content strategy, key content components, websites, digital marketing strategy

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Authors: Raquel Vianna Duarte Cardoso, Eduarda Lobato Faria, José Jorge Boueri

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Rapid urbanization has transformed the global landscape, presenting significant challenges to public health. This article delves into the impact of urbanization on the spread of infectious diseases in cities and identifies crucial strategies to enhance urban community resilience. Massive urbanization over recent decades has created conducive environments for the rapid spread of diseases due to population density, mobility, and unequal living conditions. Urbanization has been observed to increase exposure to pathogens and foster conditions conducive to disease outbreaks, including seasonal flu, vector-borne diseases, and respiratory infections. In order to tackle these issues, a range of cross-disciplinary approaches are suggested. These encompass the enhancement of urban healthcare infrastructure, emphasizing the need for robust investments in hospitals, clinics, and healthcare systems to keep pace with the burgeoning healthcare requirements in urban environments. Moreover, the establishment of disease monitoring and surveillance mechanisms is indispensable, as it allows for the timely detection of outbreaks, enabling swift responses. Additionally, community engagement and education play a pivotal role in advocating for personal hygiene, vaccination, and preventive measures, thus playing a pivotal role in diminishing disease transmission. Lastly, the promotion of sustainable urban planning, which includes the creation of cities with green spaces, access to clean water, and proper sanitation, can significantly mitigate the risks associated with waterborne and vector-borne diseases. The article is based on a review of scientific literature, and it offers a comprehensive insight into the complexities of the relationship between urbanization and health. It places a strong emphasis on the urgent need for integrated approaches to improve urban resilience in the face of health challenges.

Keywords: infectious diseases dissemination, public health, urbanization impacts, urban resilience

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Authors: Archana Gupta, Rajesh Kumar

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The chemistry of chalcones has generated intensive scientific studies throughout the world. Especially, interest has been focused on the synthesis and biodynamic activities of chalcones. The blue light transmittance, excellent crystallizability and the two planar rings connected through a conjugated double bond show that chalcone derivatives are superior nonlinear organic compounds. 3-(2-Chloro-6-fluoro¬phen¬yl)-1-(2-thien¬yl) prop-2-en-1-one, 3-(2, 4- Dichlorophenyl) – 1 - (4-methylphenyl) – prop -2-en-1-one, (2E)-3-[4-(methylsulfanyl) phenyl]-1-(4-nitrophenyl) prop-2-en-1-one are some chalcone derivatives exhibiting non linear optical (NLO) properties. NLO materials have been extensively investigated in recent years as they are the key elements for photonic technologies of optical communication, optical interconnect oscillator, amplifier, frequency converter etc. Due to their high molecular hyperpolarizabilities, organic materials display a number of significant NLO properties. Experimental measurements and theoretical calculations on molecular hyperpolarizability β have become one of the key factors in the design of second order NLO materials. Theoretical determination of hyperpolarizability is quite useful both in understanding the relationship between the molecular structure and NLO properties. It also provides a guideline to experimentalists for the design and synthesis of organic NLO materials. Quantum-chemical calculations have made an important contribution to the understanding of the electronic polarization underlying the molecular NLO processes and the establishment of structure–property relationships. In the present investigation, the detailed vibrational analysis of some chalcone derivatives is taken up to understand the correlation of the charge transfer interaction and the NLO activity of the molecules based on density functional theory calculations. The vibrational modes contributing toward the NLO activity have been identified and analyzed. Rather large hyperpolarizability derived by theoretical calculations suggests the possible future use of these compounds for non-linear optical applications. The study suggests the importance of π - conjugated systems for non-linear optical properties and the possibility of charge transfer interactions. We hope that the results of the present study of chalcone derivatives are of assistance in development of new efficient materials for technological applications.

Keywords: hyperpolarizability, molecular structure, NLO material, quantum chemical calculations

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Authors: Chan Hui-Ya, Ding Shin-Tan

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Background and Aim: The discharge planning is considered helpful to reduce the hospital length of stay and readmission rate, and then increased satisfaction with healthcare for patients and professionals. In order to decrease the waiting time of long-term care and boost the care quality of patients after discharge from the hospital, the Ministry of Health and Welfare department in Taiwan initiates a program “discharge planning connects with long-term care 2.0 services” in 2017. The purpose of this study is to investigate the outcome of the pilot of this program in a medical center. Methods: By purpose sampling, the study chose five wards in a medical center as pilot units. The researchers compared the beds of service, the numbers of cases which were transferred to the long-term care center and transferred rates per month between the pilot units and the other units, and analyze the basic data, the long-term care service needs and the approval service items of cases transfer to the long-term care center in pilot units. Results: From June to September 2017, a total of 92 referrals were made, and 51 patients were enrolled into the pilot program. There is a significant difference of transferring rate between the pilot units and the other units (χ = 702.6683, p < 0.001). Only 20 cases (39.2% success rate) were approved to accept the parts of service items of long-term care in the pilot units. The most approval item was respite care service (n = 13; 65%), while it was third at needs ranking of service lists during linking services process. Among the reasons of patients who cancelled the request, 38.71% reasons were related to the services which could not match the patients’ needs and expectation. Conclusion: The results indicate there is a requirement to modify the long-term care services to fit the needs of cases. The researchers suggest estimating the potential cases by screening data from hospital informatics systems and to hire more case manager according the service time of potential cases. Meanwhile, the strategies shortened the assessment scale and authorized hospital case managers to approve some items of long-term care should be considered.

Keywords: discharge planning, long-term care, case manager, patient care

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Authors: Nadeem Munawar, Iftikhar Hussain, Tariq Mahmood

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The lesser bandicoot rat (Bandicota bengalensis) is widely distributed and a serious agricultural pest in Pakistan. It has wide adaptation with rice-wheat-sugarcane cropping systems of Punjab, Sindh and Khyber Pakhtunkhwa and wheat-groundnut cropping system of Pothwar area, thus inflicting heavy losses to these crops. Comparative efficacies of four food baits (onion, guava, potato and peanut butter smeared bread/Chapatti) were tested in multiple feeding tests for kill trapping of this rat species in the Pothwar Plateau between October 2013 to July 2014 at the sowing, tilling, flowering and maturity stages of wheat, groundnut and millet crops. The results revealed that guava was the most preferred bait as compared to the rest of three, presumably due to particular taste and smell of the guava. The relative efficacies of all four tested baits guava also scoring the highest trapping success of 16.94 ± 1.42 percent, followed by peanut butter, potato, and onion with trapping successes of 10.52 ± 1.30, 7.82 ± 1.21 and 4.5 ± 1.10 percent, respectively. In various crop stages and season-wise the highest trapping success was achieved at maturity stages of the crops, presumably due to higher surface activity of the rat because of favorable climatic conditions, good shelter, and food abundance. Moreover, the maturity stage of wheat crop coincided with spring breeding season and maturity stages of millet and groundnut match with monsoon/autumn breeding peak of the lesser bandicoot rat in Pothwar area. The preferred order among four baits tested was guava > peanut butter > potato > onion. The study recommends that the farmers should periodically carry out rodent trapping at the beginning of each crop season and during non-breeding seasons of this rodent pest when the populations are low in numbers and restricted under crop boundary vegetation, particularly during very hot and cold months.

Keywords: Bandicota bengalensis, efficacy, food baits, Pothwar

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Authors: Z. B. Ibrahim, N. Ismail, K. I. Othman

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Fuzzy Differential Equations (FDEs) play an important role in modelling many real life phenomena. The FDEs are used to model the behaviour of the problems that are subjected to uncertainty, vague or imprecise information that constantly arise in mathematical models in various branches of science and engineering. These uncertainties have to be taken into account in order to obtain a more realistic model and many of these models are often difficult and sometimes impossible to obtain the analytic solutions. Thus, many authors have attempted to extend or modified the existing numerical methods developed for solving Ordinary Differential Equations (ODEs) into fuzzy version in order to suit for solving the FDEs. Therefore, in this paper, we proposed the development of a fuzzy version of three-point block method based on Block Backward Differentiation Formulas (FBBDF) for the numerical solution of first order FDEs. The three-point block FBBDF method are implemented in uniform step size produces three new approximations simultaneously at each integration step using the same back values. Newton iteration of the FBBDF is formulated and the implementation is based on the predictor and corrector formulas in the PECE mode. For greater efficiency of the block method, the coefficients of the FBBDF are stored at the start of the program. The proposed FBBDF is validated through numerical results on some standard problems found in the literature and comparisons are made with the existing fuzzy version of the Modified Simpson and Euler methods in terms of the accuracy of the approximated solutions. The numerical results show that the FBBDF method performs better in terms of accuracy when compared to the Euler method when solving the FDEs.

Keywords: block, backward differentiation formulas, first order, fuzzy differential equations

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Authors: H. Abas Nejad, A. R. Teymoori

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Facial expression recognition is one of the open problems in computer vision. Robust neutral face recognition in real time is a major challenge for various supervised learning based facial expression recognition methods. This is due to the fact that supervised methods cannot accommodate all appearance variability across the faces with respect to race, pose, lighting, facial biases, etc. in the limited amount of training data. Moreover, processing each and every frame to classify emotions is not required, as the user stays neutral for the majority of the time in usual applications like video chat or photo album/web browsing. Detecting neutral state at an early stage, thereby bypassing those frames from emotion classification would save the computational power. In this work, we propose a light-weight neutral vs. emotion classification engine, which acts as a preprocessor to the traditional supervised emotion classification approaches. It dynamically learns neutral appearance at Key Emotion (KE) points using a textural statistical model, constructed by a set of reference neutral frames for each user. The proposed method is made robust to various types of user head motions by accounting for affine distortions based on a textural statistical model. Robustness to dynamic shift of KE points is achieved by evaluating the similarities on a subset of neighborhood patches around each KE point using the prior information regarding the directionality of specific facial action units acting on the respective KE point. The proposed method, as a result, improves ER accuracy and simultaneously reduces the computational complexity of ER system, as validated on multiple databases.

Keywords: neutral vs. emotion classification, Constrained Local Model, procrustes analysis, Local Binary Pattern Histogram, statistical model

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Authors: Khaled Al-Badani, Andrew Norbury, Essam Elmshawet, Glynn Rotwell, Ian Jenkinson , James Ren

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Micro welding procedures are widely used for joining materials, developing duplex components or functional surfaces, through various methods such as Micro Discharge Welding or Spot Welding process, which can be found in the engineering, aerospace, automotive, biochemical, biomedical and numerous other industries. The relationship between the material properties, structure and processing is very important to improve the structural integrity and the final performance of the welded joints. This includes controlling the shape and the size of the welding nugget, state of the heat affected zone, residual stress, etc. Nowadays, modern high volume productions require the welding of much versatile shapes/sizes and material systems that are suitable for various applications. Hence, an improved understanding of the micro welding process and the digital tools, which are based on computational numerical modelling linking key welding parameters, dimensional attributes and functional performance of the weldment, would directly benefit the industry in developing products that meet current and future market demands. This paper will introduce recent work on developing an integrated experimental and numerical modelling code for micro welding techniques. This includes similar and dissimilar materials for both ferrous and non-ferrous metals, at different scales. The paper will also produce a comparative study, concerning the differences between the micro discharge welding process and the spot welding technique, in regards to the size effect of the welding zone and the changes in the material structure. Numerical modelling method for the micro welding processes and its effects on the material properties, during melting and cooling progression at different scales, will also be presented. Finally, the applications of the integrated numerical modelling and the material development for the digital manufacturing of welding, is discussed with references to typical application cases such as sensors (thermocouples), energy (heat exchanger) and automotive structures (duplex steel structures).

Keywords: computer modelling, droplet formation, material distortion, materials forming, welding

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Authors: Muluken Biadgelegn Wollele, Mebratu Assaye Mengistu

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Nanotechnology has created new opportunities for improving industrial efficiency and performance. One of the proposed approaches to improving the effectiveness of temperature exchangers is the use of nanofluids to improve heat transfer performance. The thermal conductivity of nanoparticles, as well as their size, diameter, and volume concentration, all played a role in influencing the rate of heat transfer. Nanofluids are commonly used in automobiles, energy storage, electronic component cooling, solar absorbers, and nuclear reactors. Convective heat transfer must be improved when designing thermal systems in order to reduce heat exchanger size, weight, and cost. Using roughened surfaces to promote heat transfer has been tried several times. Thus, both active and passive heat transfer methods show potential in terms of heat transfer improvement. There will be an added advantage of enhanced heat transfer due to the two methods adopted; however, pressure drop must be considered during flow. Thus, the current research aims to increase heat transfer by adding a twisted tap insert in a plain tube using a working fluid hybrid nanofluid (Al₂O₃-Cu) with a base fluid of water. A circular duct with inserts, a tube length of 3 meters, a hydraulic diameter of 0.01 meters, and tube walls with a constant heat flux of 20 kW/m² and a twist ratio of 125 was used to investigate Al₂O₃-Cu/H₂O hybrid nanofluid with inserts. The temperature distribution is better than with conventional tube designs due to stronger tangential contact and swirls in the twisted tape. The Nusselt number values of plain twisted tape tubes are 1.5–2.0 percent higher than those of plain tubes. When twisted tape is used instead of plain tube, performance evaluation criteria improve by 1.01 times. A heat exchanger that is useful for a number of heat exchanger applications can be built utilizing a mixed flow of analysis that incorporates passive and active methodologies.

Keywords: nanofluids, active method, passive method, Nusselt number, performance evaluation criteria

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Authors: Prem Bahadur Giri, Trilochana Pokhrel

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The nationalization of forest during early 1960s had become a counterproductive for the conservation of forest in Nepal. Realizing this fact, the Government of Nepal initiated a paradigm shift from government-controlled forestry system to people’s direct participation for managing forestry, conceptualizing community forest approach in the early 1980s. The community forestry approach is expected to promote sustainable forest management, restoring degraded forests for enhancing the forest condition on one hand, and on the other, improvement of livelihoods, particularly of low-income people and forest dependent communities, as well as promoting community ownership to forest. As a result, establishment of community forests started and had taken faster momentum in Nepal. Of the total land in Nepal, forest occupies 6.5 million hectares which is around 45 percent of the forest area. Of the total forest area 1.8 million hectarehas been handed-over to community management. A total of 19,361 ‘community forest users groups’ are already created to manage the community forest.Tostreamlinethe governance of community forest, the enactment of ‘Forest Act 1993’ provides a clear legal basis for managing community forest in Nepal. This article is based on an in-depth study taking a case of Tarpakha Community Forest (TCF) located in Siranchok Rural Municipality of Gorkha District in Nepal. It mainly discusses on to extent the TCF able to achieve twin objectives of this community forest for catalyzing socio-economic improvement of the targeted community and conservation of forest. The primary information was generated through in-depth interviews along with group discussion with members, management committee, and other relevant stakeholders. The findings reveal that there is significant improvement of regeneration of forest and also changes in the socio-economic status of local community. However, coordination with local municipality and forest governing entities is still weak.

Keywords: community forest, nepal, socio-economic benefit, sustainable forest management

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Authors: Franca De Sarno, Alfonso Maria Ponsiglione, Enza Torino

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Recent advances in diagnostic imaging technology have significantly contributed to a better understanding of specific changes associated with diseases progression. Among different imaging modalities, Magnetic Resonance Imaging (MRI) represents a noninvasive medical diagnostic technique, which shows low sensitivity and long acquisition time and it can discriminate between healthy and diseased tissues by providing 3D data. In order to improve the enhancement of MRI signals, some imaging exams require intravenous administration of contrast agents (CAs). Recently, emerging research reports a progressive deposition of these drugs, in particular, gadolinium-based contrast agents (GBCAs), in the body many years after multiple MRI scans. These discoveries confirm the need to have a biocompatible system able to boost a clinical relevant Gd-chelate. To this aim, several approaches based on engineered nanostructures have been proposed to overcome the common limitations of conventional CAs, such as the insufficient signal-to-noise ratios due to relaxivity and poor safety profile. In particular, nanocarriers, labeling or loading with CAs, capable of carrying high payloads of CAs have been developed. Currently, there’s no a comprehensive understanding of the thermodynamic contributions enable of boosting the efficacy of conventional CAs by using biopolymers matrix. Thus, considering the importance of MRI in diagnosing diseases, here it is reported a successful example of the next generation of these drugs where the commercial gadolinium chelate is incorporate into a biopolymer nanostructure, formed by cross-linked hyaluronic acid (HA), with improved relaxation properties. In addition, they are highlighted the basic principles ruling biopolymer-CA interactions in the perspective of their influence on the relaxometric properties of the CA by adopting a multidisciplinary experimental approach. On the basis of these discoveries, it is clear that the main point consists in increasing the rigidification of readily-available Gd-CAs within the biopolymer matrix by controlling the water dynamics, the physicochemical interactions, and the polymer conformations. In the end, the acquired knowledge about polymer-CA systems has been applied to develop of Gd-based HA nanoparticles with enhanced relaxometric properties.

Keywords: biopolymers, MRI, nanoparticles, contrast agent

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Authors: Aamir Hasan, Subhash Mishra

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The purpose of the study was to determine the key drivers which influence the shopping behavior of the customers in the retail store. In today‟s competitive world with increasing number of retail stores, the retailers need to be more customer oriented. Retail has changed and expanded in all lines of business, be it apparel,jewelry, footwear, groceries etc. The modern consumer is posing a challenging task for the Indian retailer. More aware, more confident and much more demanding, therefore the retailers are looking for ways to deliver better consumer value and to increase consumer purchase intention. Retailers tend to differentiate themselves by making their service easier to consumers. The study aims to study the key drivers that can influence shopping behavior in retail store. A survey (store intercept) method was employed to elicit primary information from 300 shoppers in different retail stores of Lucknow. The findings reveal the factors that play a greater role in influencing the shopping behavior of customers in retail store. As such, a survey of retail store customers‟ attitude towards reduced price, sales promotion, quality of the products, proximity to the home, customer service, store atmospherics were analyzed to identify the key drivers influencing shopping behavior in retail store. A questionnaire based on a five-item Likert scale, as well as random sampling, was employed for data collection. Data analysis was accomplished using SPSS software. The paper has found shopping experience, store image and value for money as three important variable out of which shopping experience emerged as a dominant factor which influences the consumer's shopping behavior in the retail store. Since the research has established empirical evidences in determining the key drivers which influences the shopping behavior of the customers in the retail store, it serves as a foundation for a deeper probe into the shopping behavior of the customers in the retail store research domain in the Indian context.

Keywords: retail, shopping, customers, questionnaire

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Authors: Lucilla Crosta, Anthony Edwards

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Companies and the market place nowadays struggle to find employees with adequate skills in relation to anticipated growth of their businesses. At least half of workers will need to undertake some form of up-skilling process in the next five years in order to remain aligned with the requests of the market . In order to meet these challenges, there is a clear need to explore the potential uses of AI (artificial Intelligence) based tools in assessing transversal skills (critical thinking, communication and soft skills of different types in general) of workers and adult students while empowering them to develop those same skills in a reliable trustworthy way. Companies seek workers with key transversal skills that can make a difference between workers now and in the future. However, critical thinking seems to be the one of the most imprtant skill, bringing unexplored ideas and company growth in business contexts. What employers have been reporting since years now, is that this skill is lacking in the majority of workers and adult students, and this is particularly visible trough their writing. This paper investigates how critical thinking and communication skills are currently developed in Higher Education environments through use of AI tools at postgraduate levels. It analyses the use of a branch of AI namely Machine Learning and Big Data and of Neural Network Analysis. It also examines the potential effect the acquisition of these skills through AI tools and what kind of effects this has on employability This paper will draw information from researchers and studies both at national (Italy & UK) and international level in Higher Education. The issues associated with the development and use of one specific AI tool Edulai, will be examined in details. Finally comparisons will be also made between these tools and the more recent phenomenon of Chat GPT and forthcomings and drawbacks will be analysed.

Keywords: critical thinking, artificial intelligence, higher education, soft skills, chat GPT

Procedia PDF Downloads 119