Search results for: Complex fuzzy evolution equations

Authors: Renato Morbidelli, Carla Saltalippi, Alessia Flammini, Marco Cifrodelli, Corrado Corradini

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The trend of magnitude and frequency of extreme rainfalls seems to be different depending on the investigated area of the world. In this work, the impact of climate change on extreme rainfalls in Umbria, an inland region of central Italy, is examined using data recorded during the period 1921-2015 by 10 representative rain gauge stations. The study area is characterized by a complex orography, with altitude ranging from 200 to more than 2000 m asl. The climate is very different from zone to zone, with mean annual rainfall ranging from 650 to 1450 mm and mean annual air temperature from 3.3 to 14.2°C. Over the past 15 years, this region has been affected by four significant droughts as well as by six dangerous flood events, all with very large impact in economic terms. A least-squares linear trend analysis of annual maximums over 60 time series selected considering 6 different durations (1 h, 3 h, 6 h, 12 h, 24 h, 48 h) showed about 50% of positive and 50% of negative cases. For the same time series the non-parametrical Mann-Kendall test with a significance level 0.05 evidenced only 3% of cases characterized by a negative trend and no positive case. Further investigations have also demonstrated that the variance and covariance of each time series can be considered almost stationary. Therefore, the analysis on the magnitude of extreme rainfalls supplies the indication that an evident trend in the change of values in the Umbria region does not exist. However, also the frequency of rainfall events, with particularly high rainfall depths values, occurred during a fixed period has also to be considered. For all selected stations the 2-day rainfall events that exceed 50 mm were counted for each year, starting from the first monitored year to the end of 2015. Also, this analysis did not show predominant trends. Specifically, for all selected rain gauge stations the annual number of 2-day rainfall events that exceed the threshold value (50 mm) was slowly decreasing in time, while the annual cumulated rainfall depths corresponding to the same events evidenced trends that were not statistically significant. Overall, by using a wide available dataset and adopting simple methods, the influence of climate change on the heavy rainfalls in the Umbria region is not detected.

Keywords: climate changes, rainfall extremes, rainfall magnitude and frequency, central Italy

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Authors: Linjie Zhang, Baifen Ren, Xi Zhang, Genwang Liu

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Ship detection is of great significance for both military and civilian applications. Synthetic aperture radar (SAR) with all-day, all-weather, ultra-long-range characteristics, has been used widely. In view of the low time resolution of low orbit SAR and the needs for high time resolution SAR data, GEO (Geosynchronous orbit) SAR is getting more and more attention. Since GEO SAR has short revisiting period and large coverage area, it is expected to be well utilized in marine ship targets monitoring. However, the height of the orbit increases the time of integration by almost two orders of magnitude. For moving marine vessels, the utility and efficacy of GEO SAR are still not sure. This paper attempts to find the feasibility of GEO SAR by giving a GEO SAR simulator of moving ships. This presented GEO SAR simulator is a kind of geometrical-based radar imaging simulator, which focus on geometrical quality rather than high radiometric. Inputs of this simulator are 3D ship model (.obj format, produced by most 3D design software, such as 3D Max), ship's velocity, and the parameters of satellite orbit and SAR platform. Its outputs are simulated GEO SAR raw signal data and SAR image. This simulating process is accomplished by the following four steps. (1) Reading 3D model, including the ship rotations (pitch, yaw, and roll) and velocity (speed and direction) parameters, extract information of those little primitives (triangles) which is visible from the SAR platform. (2) Computing the radar scattering from the ship with physical optics (PO) method. In this step, the vessel is sliced into many little rectangles primitives along the azimuth. The radiometric calculation of each primitive is carried out separately. Since this simulator only focuses on the complex structure of ships, only single-bounce reflection and double-bounce reflection are considered. (3) Generating the raw data with GEO SAR signal modeling. Since the normal ‘stop and go’ model is not available for GEO SAR, the range model should be reconsidered. (4) At last, generating GEO SAR image with improved Range Doppler method. Numerical simulation of fishing boat and cargo ship will be given. GEO SAR images of different posture, velocity, satellite orbit, and SAR platform will be simulated. By analyzing these simulated results, the effectiveness of GEO SAR for the detection of marine moving vessels is evaluated.

Keywords: GEO SAR, radar, simulation, ship

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Authors: Farhaz Amyn Rajabali, Collins Odour

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Mathematics has been there for over 4000 years and has been one of the very first educational topics explored by human civilization. Throughout the years, it has become a complex study and has derived so many other subjects. With advancements in ICT, most of the computation in mathematics is done using powerful computers. In many different countries, the children in primary and secondary schools face difficulties in learning mathematics, and this has many reasons behind it, one being the students don’t engage much with the mathematical concepts hence failing to understand them deeply. The objective of this system is to help the students understand this mathematical concept interactively, which in return will encourage the love for learning and increase thorough understanding of many concepts. Research was conducted among a group of samples and about 50% of respondents replied that they had never used an augmented reality application before. This means that the chances for this system to be accepted in the market are high due to its innovative idea. Around 60% of people did recommend the use of this system to learn mathematics. The study also showed several challenges in an educational system, including but not limited to lack of resources which was chosen by 30% of respondents, the challenge to read from textbooks (34.6%) and how hard it is to visualize concepts (46.2%). The survey question asked what benefits the users see using augmented reality to learn mathematics. The responses that were picked the most were increased student engagement and using real-world examples to understand concepts, both being 65.4% and followed by easy access to learning material at 61.5%, and increased knowledge retention at 50%. This shows that there are plenty of issues with an education system that can be addressed by software applications; now that the newer generation is so enthusiastic about electronic devices, it can actually be used to deliver good knowledge and skills to the upcoming students and mitigate most of the challenges faced currently. The study concludes that the implementation of the system is a best practice for the educational system especially leveraging a new technology that has the ability to attract the attention of many young students and use it to deliver information. It will also give rise to awareness of new technology and on multiple ways it can be implemented. Addressing the educational sector in developing countries using information technology is an imperative task since these kids studying now is the future of the country and will use what they learn and understand during their childhood will help them to make decisions about their lives in the future which will not only affect them personally but also affect the whole society in general.

Keywords: AR, mathematics, system development, augmented reality

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Authors: F. Argurio, F. G. Vaccaro

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In a global environment defined by ever-increasing health issues, in spite of the progress made by modern medicine, this paper seeks to readdress the question of global health in an international relations perspective. The research hypothesis is: the lower the security environment, the higher the spread of communicable diseases. This question will be channeled by re-scaling the connotation of 'global' and 'international' dimension through the theoretical lens of glocalization, a theory by Bauman that starts its analysis from simple systems to get to the most complex ones. Glocalization theory will be operationalized by analyzing health in an armed-conflict context. In this respect, the independent variable 'low security environment' translates into the cases of Syria and Yemen, which provide a clear example of the all-encompassing nature of conflict on national health and the effects on regional development. In fact, Syria and Yemen have been affected by poliomyelitis and cholera outbreaks respectively. The dependent variable will be constructed on said communicable diseases which belong to the families of sanitation-related and vaccine-preventable diseases. The research will be both qualitative and quantitative, based on primary (interviews) and secondary (WHO and other NGO’s reports) sources. The methodology is based on the assessment of the vaccine coverage and case-analysis in time and space using epidemiological data. Moreover, local health facilities’ functioning and efficiency will be studied. The article posits that the intervention and cooperation of international organizations with the local authorities becomes crucial to provide the local populations with their primary health needs. In Yemen, the majority of fatal cholera cases were in the regions controlled by the Houthi rebels, not officially accredited by the International Community. Similarly, the polio outbreak in Syria primarily affected the areas not controlled by the Syrian Arab Republic forces, recognized as the leading interlocutor by the WHO. The jeopardized possibilities to access these countries have been pivotal to the determining the problem in controlling sanitation-related and vaccine preventable diseases. This represents a potential threat to global health.

Keywords: health in conflict-affected areas, cholera, polio, Yemen, Syria, glocalization

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Authors: Rajeshwari Balasubramanian, Margit Van Wessel, Nandini Deo

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The participation of women in local bodies witnessed a rise after the implementation of 73rd and 74th Amendments to the Indian Constitution which created quotas for women representatives. However, even when participation increased, it did not translate into meaningful contributions by women in local bodies. This led some civil society organisations (CSOs) to begin working with women panchayat representatives in various states to build their capacity for political participation. The focus of this paper is to study capacity building training by CSOs in Jharkhand. The paper maps how the training helps women elected representatives to negotiate their autonomy at multiple levels. The paper describes the capacity building program conducted by an international feminist organisation along with its seven local partners in Jharkhand. The central question that the study asks is: How does capacity building training by CSOs in Jharkhand impact the autonomy of elected women representatives? It uses a qualitative research methodology based on empirical data gathered through field visits in four districts of Jharkhand (Chatra, Hazaribagh, East Singhbum and Ranchi) where the program was implemented for three years. The study found that women elected representatives had to develop strategies to negotiate their choice to move out of their homes and attend the training conducted by CSOs. The ability to participate in the training programs itself was a significant achievement of personal autonomy for many women. The training provided them a platform to voice their opinion and appreciate their own value as panchayat leaders. This realization allowed them to negotiate their presence and a space for themselves in Gram panchayats. A Foucauldian approach to analyze capacity building workshops might lead us to see them as systems in which CSOs impose a form of governmentality on rural elected representatives. Instead, what we see here is a much more complex negotiation of agency in which the CSO creates spaces and practices that allow women to achieve their own forms of autonomy. The study concludes that the impact of the training on the autonomy of these women is based on their everyday negotiations of time, space and mobility. Autonomy for these elected women representatives is also contextual and relative, as they seem to realize it during the training process. The training allows the women to not only negotiate their participation in panchayats but also challenge everyday practices that are rooted in patriarchy.

Keywords: autonomy, feminist organization, local bodies, political participation

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Authors: Hassan Wajid, Syed T. Ahmed, Syed G. Haider Jr., Razia Latif, Ahsan Ali, Maira Anam

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The phenomenon of Metamorphosis can be associated with any object, organism, or structure gradually and progressively going through the change of systemic or morphological form. This phenomenon can be integrated while teaching drawing to architecture students. In architectural drawings, metamorphosis’s main focus and purpose are not to completely imitate any object. In the process of drawing, the changes in systemic or morphological form happen until the complete process, and the visuals of the complete process change the drawing, opening up possibilities for the imagination of the perceivers. Metamorphosis in architectural drawings begins with an initial form and, through various noticeable stages, ends up final form or manifestation. How much of the initial form is manifested in the final form and progressively among various intermediate stages becomes an indication of the nature of metamorphosis as a phenomenon. It is important at this stage to clarify that the term metamorphosis is presently being coopted from its original domain, usually in life sciences. In this current exercise, the architectural drawings are to act as an operative analog process transforming one image of art and/or architecture in its broadest sense. That composition is claimed to have come from one source (individual work, a cultural artifact, civilizational remain). It dialectically meets, opposes, or confronts some carefully chosen alien opposites from a different domain. As an example, the layers of a detailed drawing of a Turkish prayer rug of 5 x 7 ratio over a detailed architectural plan of a religious, historical complex can be observed such that the two drawings, though at markedly different scales could dialectically converse with one another and through their mutual congruencies. In the final stage, the idea concludes contradictions across the scales to initiate the analogous roles of metamorphosed third reality, which suggests the previous un-acknowledged architectural or artistic identity. The proposed paper explores the trajectory of reproduction by analyzing drawings through detailed drawing stages and analyzes challenges as well as opportunities in the discovered realm of imagination. This description further aims at identifying factors influencing creativity and innovation in producing architectural drawings through the process of observing drawings from inception to the concluding stage.

Keywords: architectural drawings, metamorphosis, perceptions, discovery

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Authors: K. P. Valdés García, E. I. Rodríguez Fonseca, L. G. Juárez Cantú

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Suicide is a global, multidimensional and dynamic problem of mental health, which requires a constant study for its understanding and prevention. When research of this phenomenon is done, it is necessary to consider the different characteristics it may have because of the individual and sociocultural variables, the importance of this consideration is related to the generation of effective treatments and interventions. Adolescents are a vulnerable population due to the characteristics of the development stage. The investigation was carried out with the objective of identifying and describing the conceptualization of adolescents of suicide, and in this process, we find possible differences between men and women. The study was carried out in Saltillo, Coahuila, Mexico. The sample was composed of 418 volunteer students aged between 11 and 18 years. The ethical aspects of the research were reviewed and considered in all the processes of the investigation with the participants, their parents and the schools to which they belonged, psychological attention was offered to the participants and preventive workshops were carried in the educational institutions. Natural semantic networks were the instrument used, since this hybrid method allows to find and analyze the social concept of a phenomenon; in this case, the word suicide was used as an evocative stimulus and participants were asked to evoke at least five words and a maximum 10 that they thought were related to suicide, and then hierarchize them according to the closeness with the construct. The subsequent analysis was carried with Excel, yielding the semantic weights, affective loads and the distances between each of the semantic fields established according to the words reported by the subjects. The results showed similarities in the conceptualization of suicide in adolescents, men and women. Seven semantic fields were generated; the words were related in the discourse analysis: 1) death, 2) possible triggering factors, 3) associated moods, 4) methods used to carry it out, 5) psychological symptomatology that could affect, 6) words associated with a rejection of suicide, and finally, 7) specific objects to carry it out. One of the necessary aspects to consider in the investigations of complex issues such as suicide is to have a diversity of instruments and techniques that adjust to the characteristics of the population and that allow to understand the phenomena from the social constructs and not only theoretical. The constant study of suicide is a pressing need, the loss of a life from emotional difficulties that can be solved through psychiatry and psychological methods requires governments and professionals to pay attention and work with the risk population.

Keywords: adolescents, psychological construct, semantic networks, suicide

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Authors: Sergio Celaschi, Henrique Canavarro de Alencar, Claaudecir Biazoli

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Effluent quality is of the highest priority for compliance with the permit limits of environmental protection agencies and ensures the protection of their local water system. Of the pollutants monitored, the biochemical oxygen demand (BOD) posed one of the greatest challenges. This work presents a solution for wastewater treatment plants - WWTP’s ability to react to different situations and meet treatment goals. Delayed BOD5 results from the lab take 7 to 8 analysis days, hindered the WWTP’s ability to react to different situations and meet treatment goals. Reducing BOD turnaround time from days to hours is our quest. Such a solution is based on a system of two BOD bioreactors associated with Digital Twin (DT) and Machine Learning (ML) methodologies via an Internet of Things (IoT) platform to monitor and control a WWTP to support decision making. DT is a virtual and dynamic replica of a production process. DT requires the ability to collect and store real-time sensor data related to the operating environment. Furthermore, it integrates and organizes the data on a digital platform and applies analytical models allowing a deeper understanding of the real process to catch sooner anomalies. In our system of continuous time monitoring of the BOD suppressed by the effluent treatment process, the DT algorithm for analyzing the data uses ML on a chemical kinetic parameterized model. The continuous BOD monitoring system, capable of providing results in a fraction of the time required by BOD5 analysis, is composed of two thermally isolated batch bioreactors. Each bioreactor contains input/output access to wastewater sample (influent and effluent), hydraulic conduction tubes, pumps, and valves for batch sample and dilution water, air supply for dissolved oxygen (DO) saturation, cooler/heater for sample thermal stability, optical ODO sensor based on fluorescence quenching, pH, ORP, temperature, and atmospheric pressure sensors, local PLC/CPU for TCP/IP data transmission interface. The dynamic BOD system monitoring range covers 2 mg/L < BOD < 2,000 mg/L. In addition to the BOD monitoring system, there are many other operational WWTP sensors. The CPU data is transmitted/received to/from the digital platform, which in turn performs analyses at periodic intervals, aiming to feed the learning process. BOD bulletins and their credibility intervals are made available in 12-hour intervals to web users. The chemical kinetics ML algorithm is composed of a coupled system of four first-order ordinary differential equations for the molar masses of DO, organic material present in the sample, biomass, and products (CO₂ and H₂O) of the reaction. This system is solved numerically linked to its initial conditions: DO (saturated) and initial products of the kinetic oxidation process; CO₂ = H₂0 = 0. The initial values for organic matter and biomass are estimated by the method of minimization of the mean square deviations. A real case of continuous monitoring of BOD wastewater effluent quality is being conducted by deploying an IoT application on a large wastewater purification system located in S. Paulo, Brazil.

Keywords: effluent treatment, biochemical oxygen demand, continuous monitoring, IoT, machine learning

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Authors: Pritha Niraj Arya

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Education plays a crucial role in societal evolution by promoting economic expansion and creativity. The varied demands of students in India’s higher education setting signify inclusive and efficient teaching methods. The present study examined how teaching styles, self-efficacy, and personality traits interact among Indian higher education faculty members and how these factors collectively affect pedagogical practices. Specifically, the research explored differences in personality traits -agreeableness, conscientiousness, neuroticism, openness, and extraversion- between teachers with high and low self-efficacy and examined how these traits shape teaching strategies, either student-focused or teacher-focused. Data collection took place for three months, ensuring confidentiality and ethical compliance. 268 faculty members from Indian higher education institutions participated in this comparative study. An online questionnaire was used to gather data in which participants completed three well-established tools: the approaches to teaching inventory, which measures teaching styles; the teacher self-efficacy questionnaire, which measures self-efficacy levels; and the big five inventory, which measures personality traits. The results showed that while teachers with low self-efficacy had higher levels of neuroticism, those with high self-efficacy scored much higher on traits such as agreeableness, conscientiousness, openness, and extraversion. Despite the traditional belief that high self-efficacy is only associated with student-focused teaching, the findings suggest that teachers with high self-efficacy have cognitive flexibility, which enables them to skillfully use both teacher-focused and student-focused approaches to cater to a wide range of classroom needs. Teachers with low self-efficacy, on the other hand, are less flexible and adopt fewer different strategies in their teaching practice. The findings challenge simplistic associations between self-efficacy and teaching strategies, emphasising that high self-efficacy promotes adaptability rather than a fixed preference for specific teaching methods. This adaptability is crucial in India’s diverse educational settings, where teachers must balance standardised curricula with the varied learning needs of students. This study highlights the importance of integrating personality traits and self-efficacy into teacher training programs. By promoting self-efficacy and tailoring professional development to consider individual personality traits, institutions can enhance teachers’ teaching flexibility, hence improving student engagement and learning outcomes. These findings have practical implications for teacher education, suggesting that adopting cognitive flexibility among teachers can improve instructional quality and classroom dynamics. To gain a deeper knowledge of how personality traits and self-efficacy impact teaching practices over time, future research should investigate causal relationships using longitudinal studies. Examining external factors like institutional policies, availability of resources, and cultural settings will help to clarify the dynamics at play. Furthermore, this study emphasises the need to strike a balance between teacher-focused and student-focused approaches to provide a comprehensive education that covers both conceptual understanding and the delivery of key information. This study offers insights into how the Indian educational system is changing and how, to achieve global standards, effective teaching techniques are becoming increasingly important. This study promotes the larger objective of educational excellence by exploring the interaction of internal and external factors impacting teaching styles and providing practical policy and practice recommendations.

Keywords: higher education, personality traits, self-efficacy, teaching styles

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Authors: Francesca Maria Melucci, Marco Panettieri, Rocco Roma

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Cities are at the forefront of achieving the sustainable development goals set out in the Sustainable Development Goals of Agenda 2030. For these reasons, increasing attention has been given to the creation of resilient, sustainable, inclusive and green cities and finding solutions to these problems is one of the greatest challenges faced by researchers today. In particular urban green infrastructures, including green roofs, play a key role in tackling environmental, social and economic problems. The starting point was an extensive literature review on 1. research developments on the benefits (environmental, economic and social) and implications of green roofs; 2. sustainability assessment and applied methodologies; 3. specific indicators to measure impacts on urban sustainability. Through this review, the appropriate qualitative and quantitative characteristics that are part of the complex 'green roof' system were identified, as studies that holistically capture its multifunctional nature are still lacking. So, this paper aims to find a method to improve community participation in green roof initiatives and support local governance processes in developing efficient proposals to achieve better sustainability and resilience of cities. To this aim, the multidimensional indicator-based framework, presented by Tapia in 2021, has been tested for the first time in the case of a green roof in the city of Madrid. The framework's set of indicators was implemented with other indicators such as those of waste management and circularity (OECD Inventory of Circular Economy indicators) and sustainability performance. The specific indicators to be used in the case study were decided after a consultation phase with relevant stakeholders. Data on the community's willingness to participate in green roof implementation initiatives were collected through interviews and online surveys with a heterogeneous sample of citizens. The results of the application of the framework suggest how the different aspects of sustainability influence the choice of a green roof and provide input on the main mechanisms involved in citizens' willingness to participate in such initiatives.

Keywords: urban agriculture, green roof, urban sustainability, indicators, multi-criteria analysis

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Authors: Chatrabhuti Pipop, Visessri Supattra, Charinpanitkul Tawatchai

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Durian is one of the top agricultural products exported by Thailand. There is the massive market potential for the durian industry. While the global demand for Thai durians, especially the demand from China, is very high, Thailand's durian supply is far from satisfying strong demand. Poor agricultural practices result in low yields and poor quality of fruit. Most irrigation systems currently used by the farmers are fixed schedule or fixed rates that ignore actual weather conditions and crop water requirements. In addition, the technologies emerging are too difficult and complex and prices are too high for the farmers to adopt and afford. Many farmers leave the durian trees to grow naturally. With improper irrigation and nutrient management system, durians are vulnerable to a variety of issues, including stunted growth, not flowering, diseases, and death. Technical development or research for durian is much needed to support the wellbeing of the farmers and the economic development of the country. However, there are a limited number of studies or development projects for durian because durian is a perennial crop requiring a long time to obtain the results to report. This study, therefore, aims to address the problem of durian production by developing an autonomous and precision irrigation system. The system is designed and equipped with an industrial programmable controller, a weather station, and a digital flow meter. Daily water requirements are computed based on weather data such as rainfall and evapotranspiration for daily irrigation with variable flow rates. A prediction model is also designed as a part of the system to enhance the irrigation schedule. Before the system was installed in the field, a simulation model was built and tested in a laboratory setting to ensure its accuracy. Water consumption was measured daily before and after the experiment for further analysis. With this system, the crop water requirement is precisely estimated and optimized based on the data from the weather station. Durian will be irrigated at the right amount and at the right time, offering the opportunity for higher yield and higher income to the farmers.

Keywords: Durian, precision irrigation, precision agriculture, smart farm

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Authors: Mary Isobelle Mullaney

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The maxim "an unexamined life is not worth living," attributed to Socrates, prompts a contemplative reflection spanning over 32 years as a teacher educator in the Republic of Ireland. Taking time to contemplate the changes that have occurred and the current landscape provides valuable insights into the dynamic terrain of teacher preparation. The reflective journey traverses the impacts of global and societal shifts, responding to challenges, embracing advancements, and navigating the delicate balance between responsiveness to the world and the active shaping of it. The transformative events of the COVID-19 pandemic spotlighted the indispensable role of teachers in Ireland, reinforcing the critical nature of education for the well-being of pupils. Research solidifies the understanding that teachers matter and so it is worth exploring the pivotal role of the teacher educator. This reflective piece examines the changes in teacher education and explores the juxtapositions that have emerged in response to three decades of profound change. The attractiveness of teaching as a career is juxtaposed against the reality of the demands of the job, with conditions for public servants in Ireland undergoing a shift. High-level strategic discussions about increasing teacher numbers now contrast with a previous oversupply. The delicate balance between the imperative to increase enrolment (getting "bums on seats") and the gatekeeper role of teacher educators is explored, raising questions about maintaining high standards amid changing student profiles. Another poignant dichotomy involves the high demand for teachers versus the hurdles candidates face in becoming teachers. The rising cost and duration of teacher education courses raise concerns about attracting quality candidates. The perceived attractiveness of teaching as a career contends with the reality of increased demands on educators. One notable juxtaposition centres around the rapid evolution of Irish initial teacher education versus the potential risk of change overload. The Teaching Council of Ireland has spearheaded considerable changes, raising questions about the timing and evaluation of these changes. This reflection contemplates the vision of a professional teaching council versus its evolving reality and the challenges posed by the value placed on school placement in teacher preparation. The juxtapositions extend to the classroom, where theory may not seamlessly align with the lived experience. Inconsistencies between college expectations and the classroom reality prompt reflection on the effectiveness of teacher preparation programs. Addressing the changing demographic landscape of society and schools, there is a persistent incongruity between the diversity of Irish society and the profile of second-level teachers. As education undergoes a digital revolution, the enduring philosophies of education confront technological advances. This reflection highlights the tension between established practices and contemporary demands, acknowledging the irreplaceable value of face-to-face interaction while integrating technology into teacher training programs. In conclusion, this reflective journey encapsulates the intricate web of juxtapositions in Irish Initial Teacher Education. It emphasises the enduring commitment to fostering education, recognising the profound influence educators wield, and acknowledging the challenges and gratifications inherent in shaping the minds and futures of generations to come.

Keywords: Irish post primary teaching, juxtapositions, reflection, teacher education

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Authors: Hesham Hamdy Abdelmohsen, Ahmed Shawky Abdul Azizb, Mona Fawzy Aldaghma

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Helical piles have earned considerable attention as an effective deep foundation alternative due to their rapid installation process and their dual purpose in compression and tension. These piles find common uses as foundations for structures like solar panels, wind turbines, offshore platforms, and some kinds of retaining walls. These structures usually transfer different combinations of loads to their helical-pile foundations in the form of axial and lateral loads. Extensive research has been conducted to investigate and understand the behavior of these piles under the influence of either axial or lateral loads. However, the impacts of loading patterns that may act on the helical piles as combinations of axial compression and lateral loads still need more efforts of research work. This paper presents the results of an experimental (Lab tests) and numerical (PLAXIS-3D) study performed on vertical helical-pile groups under the action of combined loads as axial compression (bearing loads), acting successively with lateral (horizontal) loads. The study aims to clarify the effects of key factors, like helix location and direction of lateral load, on the lateral capacity of helical-pile groups and, consequently, on group efficiency. Besides the variation of helix location and lateral load direction, three patterns of successive bearing combined loads were considered, in which the axial vertical compression load was either zero, V1 or V2, whereas the lateral horizontal loads were varied under each vertical compression load. The study concluded that the lateral capacity of the helical-pile group is significantly affected by helix location within the length of the pile shaft. The optimal lateral performance is achieved with helices at a depth ratio of H/L = 0.4. Furthermore, groups of rectangular plan distribution exhibit greater lateral capacity if subjected to lateral horizontal load in the direction of its long axis. Additionally, the research emphasizes that the presence of vertical compression loading can enhance the lateral capacity of the group. This enhancement depends on the value of the vertical compression load, lateral load direction, and helix location, which highlights the complex interaction effect of these factors on the efficiency of helical-pile groups.

Keywords: helical piles, experimental, numerical, lateral loading, group efficiency

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Authors: Ali R. Alshawawreh, Francisco Liébana-Cabanillas, Francisco J. Blanco-Encomienda

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Collaboration between marketing and business intelligence (BI) is crucial in today's ever-evolving business landscape. These two domains play pivotal roles in molding customers' experiential knowledge. Marketing insights offer valuable information regarding customer needs, preferences, and behaviors. Conversely, BI facilitates data-driven decision-making, leading to heightened operational efficiency, product quality, and customer satisfaction. Customer experiential knowledge (CEK) encompasses customers' implicit comprehension of consumption experiences influenced by diverse factors, including social and cultural influences. This study primarily focuses on telecommunications companies in Jordan, scrutinizing how experiential customer knowledge mediates the relationship between marketing intelligence and business intelligence. Drawing on theoretical frameworks such as the resource-based view (RBV) and service-dominant logic (SDL), the research aims to comprehend how organizations utilize their resources, particularly knowledge, to foster Evolution. Employing a quantitative research approach, the study collected and analyzed primary data to explore hypotheses. Structural equation modeling (SEM) facilitated by Smart PLS software evaluated the relationships between the constructs, followed by mediation analysis to assess the indirect associations in the model. The study findings offer insights into the intricate dynamics of organizational Creation, uncovering the interconnected relationships between business intelligence, customer experiential knowledge-based innovation (CEK-DI), marketing intelligence (MI), and product and service innovation (PSI), underscoring the pivotal role of advanced intelligence capabilities in developing innovative practices rooted in a profound understanding of customer experiences. Furthermore, the positive impact of BI on PSI reaffirms the significance of data-driven decision-making in shaping the innovation landscape. The significant impact of CEK-DI on PSI highlights the critical role of customer experiences in driving an organization. Companies that actively integrate customer insights into their opportunity creation processes are more likely to create offerings that match customer expectations, which drives higher levels of product and service sophistication. Additionally, the positive and significant impact of MI on CEK-DI underscores the critical role of market insights in shaping evolutionary strategies. While the relationship between MI and PSI is positive, the slightly weaker significance level indicates a subtle association, suggesting that while MI contributes to the development of ideas, In conclusion, the study emphasizes the fundamental role of intelligence capabilities, especially artificial intelligence, emphasizing the need for organizations to leverage market and customer intelligence to achieve effective and competitive innovation practices. Collaborative efforts between marketing and business intelligence serve as pivotal drivers of development, influencing customer experiential knowledge and shaping organizational strategies and practices. Future research could adopt longitudinal designs and gather data from various sectors to offer broader insights. Additionally, the study focuses on the effects of marketing intelligence, business intelligence, customer experiential knowledge, and innovation, but other unexamined variables may also influence innovation processes. Future studies could investigate additional factors, mediators, or moderators, including the role of emerging technologies like AI and machine learning in driving innovation.

Keywords: marketing intelligence, business intelligence, product, customer experiential knowledge-driven innovation

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Authors: Tobias Schmithuesen, Johannes Henrich Schleifenbaum

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The additive manufacturing process laser powder bed fusion offers many advantages over conventional manufacturing processes. For example, almost any complex part can be produced, such as topologically optimized lightweight parts, which would be inconceivable with conventional manufacturing processes. A major challenge posed by the LPBF process, however, is, in most cases, the need to use and remove support structures on critically inclined part surfaces (α < 45 ° regarding substrate plate). These are mainly used for dimensionally accurate mapping of part contours and to reduce distortion by absorbing process-related internal stresses. Furthermore, they serve to transfer the process heat to the substrate plate and are, therefore, indispensable for the LPBF process. A major challenge for the economical use of the LPBF process in industrial process chains is currently still the high manual effort involved in removing support structures. According to the state of the art (SoA), the parts are usually treated by simple hand tools (e.g., pliers, chisels) or by machining (e.g., milling, turning). New automatable approaches are the removal of support structures by means of wet chemical ablation and thermal deburring. According to the state of the art, the support structures are essentially adapted to the LPBF process and not to potential post-processing steps. The aim of this study is the determination of support structure designs that are adapted to the mentioned post-processing approaches. In the first step, the essential boundary conditions for complete removal by means of the respective approaches are identified. Afterward, a representative demonstrator part with various macroscopic support structure designs will be LPBF-manufactured and tested with regard to a complete powder and support removability. Finally, based on the results, potentially suitable support structure designs for the respective approaches will be derived. The investigations are carried out on the example of the aluminum alloy AlSi10Mg.

Keywords: additive manufacturing, laser powder bed fusion, laser beam melting, selective laser melting, post processing, tool-free, wet chemical ablation, thermal deburring, aluminum alloy, AlSi10Mg

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Authors: Naomi Nathan

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Introduction Digitalization of medical education can revolutionize how medical students learn and interact with the medical curriculum across contexts. With the increasing availability of the internet and mobile connectivity in LMICs, online medical education platforms and digital learning tools are becoming more widely available, providing new opportunities for learners to access high-quality medical education and training. However, the adoption and integration of digital technologies in medical education in LMICs is a complex process influenced by various factors, including learners' perceptions and attitudes toward digital learning. In Ethiopia, the adoption of digital platforms for medical education has been slow, with traditional face-to-face teaching methods still being the norm. However, as access to technology improves and more universities adopt digital platforms, it is crucial to understand how medical students perceive this shift. Methodology This study investigated medical students' perception of the digitalization of medical education in relation to their access to the Lecturio Digital Medical Education Platform through a capacity-building project. 740 medical students from over 20 medical universities participated in the study. The students were surveyed using a questionnaire that included their attitudes toward the digitalization of medical education, their frequency of use of the digital platform, and their perceived benefits and challenges. Results The study results showed that most medical students had a positive attitude toward digitalizing medical education. The most commonly cited benefit was the convenience and flexibility of accessing course material/curriculum online. Many students also reported that they found the platform more interactive and engaging, leading to a more meaningful learning experience. The study also identified several challenges medical students faced when using the platform. The most commonly reported challenge was the need for more reliable internet access, which made it difficult for students to access content consistently. Overall, the results of this study suggest that medical students in Ethiopia have a positive perception of the digitalization of medical education. Over 97% of students continuously expressed a need for access to the Lecturio platform throughout their studies. Conclusion Significant challenges still need to be addressed to fully realize the Lecturio digital platform's benefits. Universities, relevant ministries, and various stakeholders must work together to address these challenges to ensure that medical students fully participate in and benefit from digitalized medical education - sustainably and effectively.

Keywords: digital medical education, EdTech, LMICs, e-learning

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Authors: Rutuja Upadhyay, Anurag Mehra

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Solid food foams/cellular foods are colloidal systems which impart structure, texture and mouthfeel to many food products such as bread, cakes, ice-cream, meringues, etc. Their heterogeneous morphology makes the quantification of structure/mechanical relationships complex. The porous structure of solid food foams is highly influenced by the processing conditions, ingredient composition, and their interactions. Sensory perceptions of food foams are dependent on bubble size, shape, orientation, quantity and distribution and determines the texture of foamed foods. The state and structure of the solid matrix control the deformation behavior of the food, such as elasticity/plasticity or fracture, which in turn has an effect on the force-deformation curves. The obvious step in obtaining the relationship between the mechanical properties and the porous structure is to quantify them simultaneously. Here, we attempt to research food foams such as bread dough, baked bread and steamed rice cakes to determine the link between ingredients and the corresponding effect of each of them on the rheology, microstructure, bubble size and texture of the final product. Dynamic rheometry (SAOS), confocal laser scanning microscopy, flatbed scanning, image analysis and texture profile analysis (TPA) has been used to characterize the foods studied. In all the above systems, there was a common observation that when the mean bubble diameter is smaller, the product becomes harder as evidenced by the increase in storage and loss modulus (G′, G″), whereas when the mean bubble diameter is large the product is softer with decrease in moduli values (G′, G″). Also, the bubble size distribution affects texture of foods. It was found that bread doughs with hydrocolloids (xanthan gum, alginate) aid a more uniform bubble size distribution. Bread baking experiments were done to study the rheological changes and mechanisms involved in the structural transition of dough to crumb. Steamed rice cakes with xanthan gum (XG) addition at 0.1% concentration resulted in lower hardness with a narrower pore size distribution and larger mean pore diameter. Thus, control of bubble size could be an important parameter defining final food texture.

Keywords: food foams, rheology, microstructure, texture

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Authors: Ahmad Haidar

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Modern economic systems are characterized by growing complexity, and addressing their challenges requires innovative approaches. This study examines the implications of artificial intelligence (AI) on unemployment in Europe from a macroeconomic perspective, employing data modeling techniques to understand the relationship between AI integration and labor market dynamics. To understand the AI-unemployment nexus comprehensively, this research considers factors such as sector-specific AI adoption, skill requirements, workforce demographics, and geographical disparities. The study utilizes a panel data model, incorporating data from European countries over the last two decades, to explore the potential short-term and long-term effects of AI implementation on unemployment rates. In addition to investigating the direct impact of AI on unemployment, the study also delves into the potential indirect effects and spillover consequences. It considers how AI-driven productivity improvements and cost reductions might influence economic growth and, in turn, labor market outcomes. Furthermore, it assesses the potential for AI-induced changes in industrial structures to affect job displacement and creation. The research also highlights the importance of policy responses in mitigating potential negative consequences of AI adoption on unemployment. It emphasizes the need for targeted interventions such as skill development programs, labor market regulations, and social safety nets to enable a smooth transition for workers affected by AI-related job displacement. Additionally, the study explores the potential role of AI in informing and transforming policy-making to ensure more effective and agile responses to labor market challenges. In conclusion, this study provides a comprehensive analysis of the macroeconomic implications of AI on unemployment in Europe, highlighting the importance of understanding the nuanced relationships between AI adoption, economic growth, and labor market outcomes. By shedding light on these relationships, the study contributes valuable insights for policymakers, educators, and researchers, enabling them to make informed decisions in navigating the complex landscape of AI-driven economic transformation.

Keywords: artificial intelligence, unemployment, macroeconomic analysis, european labor market

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Authors: Tugba Altin

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In an era marked by pronounced climate change consequences, communities are observed to confront traumatic events that yield both tangible and intangible repercussions. Such events not only cause discernible damage to the landscape but also deeply affect the intangible aspects, including emotional distress and disruptions to cultural landscapes. The Lytton Creek Fire of 2021 serves as a case in point. Beyond the visible destruction, the less overt but profoundly impactful disturbance to place attachment (PA) is scrutinized. PA, representing the emotional and cognitive bonds individuals establish with their environments, is crucial for understanding how such events impact cultural identity and connection to the land. The study underscores the significance of addressing both tangible and intangible traumas for holistic community recovery. As communities renegotiate their affiliations with altered environments, the cultural landscape emerges as instrumental in shaping place-based identities. This renewed understanding is pivotal for reshaping adaptation planning. The research advocates for adaptation strategies rooted in the lived experiences and testimonies of the affected populations. By incorporating both the tangible and intangible facets of trauma, planning efforts are suggested to be more culturally attuned and emotionally insightful, fostering true resonance with the affected communities. Through such a comprehensive lens, this study contributes enriching the climate change discourse, emphasizing the intertwined nature of tangible recovery and the imperative of emotional and cultural healing after environmental disasters. Following the pronounced aftermath of the Lytton Creek Fire in 2021, research aims to deeply understand its impact on place attachment (PA), encompassing the emotional and cognitive bonds individuals form with their environments. The interpretive phenomenological approach, enriched by a hermeneutic framework, is adopted, emphasizing the experiences of the Lytton community and co-researchers. Phenomenology informed the understanding of 'place' as the focal point of attachment, providing insights into its formation and evolution after traumatic events. Data collection departs from conventional methods. Instead of traditional interviews, walking audio sessions and photo elicitation methods are utilized. These allow co-researchers to immerse themselves in the environment, re-experience, and articulate memories and feelings in real-time. Walking audio facilitates reflections on spatial narratives post-trauma, while photo voices captured intangible emotions, enabling the visualization of place-based experiences. The analysis is collaborative, ensuring the co-researchers' experiences and interpretations are central. Emphasizing their agency in knowledge production, the process is rigorous, facilitated by the harmonious blend of interpretive phenomenology and hermeneutic insights. The findings underscore the need for adaptation and recovery efforts to address emotional traumas alongside tangible damages. By exploring PA post-disaster, the research not only fills a significant gap but advocates for an inclusive approach to community recovery. Furthermore, the participatory methodologies employed challenge traditional research paradigms, heralding potential shifts in qualitative research norms.

Keywords: wildfire recovery, place attachment, trauma recovery, cultural landscape, visual methodologies

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Authors: Abisha Isaac Mohanlal

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Amidst all suspicions and cynicism raised by the legal fraternity, Artificial Intelligence has found its way into the legal system and has revolutionized the conventional forms of legal services delivery. Be it legal argumentation and research or resolution of complex legal disputes; artificial intelligence has crept into all legs of modern day legal services. Its impact has been largely felt by way of big data, legal expert systems, prediction tools, e-lawyering, automated mediation, etc., and lawyers around the world are forced to upgrade themselves and their firms to stay in line with the growth of technology in law. Researchers predict that the future of legal services would belong to artificial intelligence and that the age of human lawyers will soon rust. But as far as the Judiciary is concerned, even in the developed countries, the system has not fully drifted away from the orthodoxy of preferring Natural Intelligence over Artificial Intelligence. Since Judicial decision-making involves a lot of unstructured and rather unprecedented situations which have no single correct answer, and looming questions of legal interpretation arise in most of the cases, discretion and Emotional Intelligence play an unavoidable role. Added to that, there are several ethical, moral and policy issues to be confronted before permitting the intrusion of Artificial Intelligence into the judicial system. As of today, the human judge is the unrivalled master of most of the judicial systems around the globe. Yet, scientists of Artificial Intelligence claim that robot judges can replace human judges irrespective of how daunting the complexity of issues is and how sophisticated the cognitive competence required is. They go on to contend that even if the system is too rigid to allow robot judges to substitute human judges in the recent future, Artificial Intelligence may still aid in other judicial tasks such as drafting judicial documents, intelligent document assembly, case retrieval, etc., and also promote overall flexibility, efficiency, and accuracy in the disposal of cases. By deconstructing the major challenges that Artificial Intelligence has to overcome in order to successfully invade the human- dominated judicial sphere, and critically evaluating the potential differences it would make in the system of justice delivery, the author tries to argue that penetration of Artificial Intelligence into the Judiciary could surely be enhancive and reparative, if not fully transformative.

Keywords: artificial intelligence, judicial decision making, judicial systems, legal services delivery

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Authors: Catherine Wheatley, Emma L. Davies, Helen Dawes

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The health benefits of exercise are widely recognised, but numerous interventions have failed to halt a sharp decline in physical activity during early adolescence. Many such projects are underpinned by the Theory of Planned Behaviour, yet this model of rational decision-making leaves variance in behavior unexplained. This study investigated whether the Prototype Willingness Model, which proposes a second, reactive decision-making path to account for spontaneous responses to the social environment, has potential to improve understanding of adolescent exercise behaviour in school by exploring constructs in the model with young people. PE teachers in 4 Oxfordshire schools each nominated 6 pupils who were active in school, and 6 who were inactive, to participate in the study. Of these, 45 (22 male) aged 12-13 took part in 8 focus group discussions. These were transcribed and subjected to deductive thematic analysis to search for themes relating to the prototype willingness model. Participants appeared to make rational decisions about commuting to school or attending sports clubs, but spontaneous choices to be inactive during both break and PE. These reactive decisions seemed influenced by a social context described as more ‘judgmental’ than primary school, characterised by anxiety about physical competence, negative peer evaluation and inactive playground norms. Participants described their images of typical active and inactive adolescents: active images included negative social characteristics including ‘show-off’. There was little concern about the long-term risks of inactivity, although participants seemed to recognise that physical activity is healthy. The Prototype Willingness Model might more fully explain young adolescents’ physical activity in school than rational behavioural models, indicating potential for physical activity interventions that target social anxieties in response to the changing playground environment. Images of active types could be more complex than earlier research has suggested, and their negative characteristics might influence willingness to be active.

Keywords: adolescence, physical activity, prototype willingness model, school

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Authors: Elisabeth Maidl

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The interdependence of climate change and natural hazard goes along with large uncertainties regarding future risks. Regional stakeholders, experts in natural hazards management and scientists have specific knowledge, resp. mental models on such risks. This diversity of views makes it difficult to find common and broadly accepted prevention measures. If the specific knowledge of these types of actors is shared in an interactive knowledge production process, this enables a broader and common understanding of complex risks and allows to agree on long-term solution strategies. Previous studies on mental models confirm that actors with specific vulnerabilities perceive different aspects of a topic and accordingly prefer different measures. In bringing these perspectives together, there is the potential to reduce uncertainty and to close blind spots in solution finding. However, studies that examine the mental models of regional actors on future concrete mass movement risks are lacking so far. The project tests and evaluates the feasibility of knowledge co-creation for the anticipatory prevention of climate change-induced mass movement risks in the Alps. As a key element, mental models of the three included groups of actors are compared. Being integrated into the research program Climate Change Impacts on Alpine Mass Movements (CCAMM2), this project is carried out in two Swiss mountain regions. The project is structured in four phases: 1) the preparatory phase, in which the participants are identified, 2) the baseline phase, in which qualitative interviews and a quantitative pre-survey are conducted with actors 3) the knowledge-co-creation phase, in which actors have a moderated exchange meeting, and a participatory modelling workshop on specific risks in the region, and 4) finally a public information event. Results show that participants' mental models are based on the place of origin, profession, believes, values, which results in narratives on climate change and hazard risks. Further, the more intensively participants interact with each other, the more likely is that they change their views. This provides empirical evidence on how changes in opinions and mindsets can be induced and fostered.

Keywords: climate change, knowledge-co-creation, participatory process, natural hazard risks

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Authors: Shraddha Acharya, Sharad Kumar Sharma, Ratna Bhattarai, Bhagwan Maharjan, Deepak Dahal, Serpahine Kaminsa

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Background: Drug-resistant (DR) tuberculosis (TB) continues to be a threat in Nepal, with an estimated 2800 new cases every year. The treatment of DR-TB with second line TB drugs is complex and takes longer time with comparatively lower treatment success rate than drug-susceptible TB. Delay in treatment initiation for DR-TB patients might further result in unfavorable treatment outcomes and increased transmission. This study thus aims to determine median time taken to initiate second-line treatment among Rifampicin Resistant (RR) diagnosed TB patients and to assess the proportion of treatment delays among various type of DR-TB cases. Method: A retrospective cohort study was done using national routine electronic data (DRTB and TB Laboratory Patient Tracking System-DHIS2) on drug resistant tuberculosis patients between January 2020 and December 2022. The time taken for treatment initiation was computed as– days from first diagnosis as RR TB through Xpert MTB/Rif test to enrollment on second-line treatment. The treatment delay (>7 days after diagnosis) was calculated. Results: Among total RR TB cases (N=954) diagnosed via Xpert nationwide, 61.4% were enrolled under shorter-treatment regimen (STR), 33.0% under longer treatment regimen (LTR), 5.1% for Pre-extensively drug resistant TB (Pre-XDR) and 0.4% for Extensively drug resistant TB (XDR) treatment. Among these cases, it was found that the median time from diagnosis to treatment initiation was 6 days (IQR:2-15.8). The median time was 5 days (IQR:2.0-13.3) among STR, 6 days (IQR:3.0-15.0) among LTR, 30 days (IQR:5.5-66.8) among Pre-XDR and 4 days (IQR:2.5-9.0) among XDR TB cases. The overall treatment delay (>7 days after diagnosis) was observed in 42.4% of the patients, among which, cases enrolled under Pre-XDR contributed substantially to treatment delay (72.0%), followed by LTR (43.6%), STR (39.1%) and XDR (33.3%). Conclusion: Timely diagnosis and prompt treatment initiation remain fundamental focus of the National TB program. The findings of the study, however suggest gaps in timeliness of treatment initiation for the drug-resistant TB patients, which could bring adverse treatment outcomes. Moreover, there is an alarming delay in second line treatment initiation for the Pre-XDR TB patients. Therefore, this study generates evidence to identify existing gaps in treatment initiation and highlights need for formulating specific policies and intervention in creating effective linkage between the RR TB diagnosis and enrollment on second line TB treatment with intensified efforts from health providers for follow-ups and expansion of more decentralized, adequate, and accessible diagnostic and treatment services for DR-TB, especially Pre-XDR TB cases, due to the observed long treatment delays.

Keywords: drug-resistant, tuberculosis, treatment initiation, Nepal, treatment delay

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Authors: Jose A. Alvarez Aldegunde, Adrian Fernandez Sanchez, Matthew D. Menden, Bernardo Vila Rodriguez

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Up to five statistical pre-processings have been carried out considering the pollutant records of the stations present in Cartagena de Indias, Colombia, also taking into account the childhood asthma incidence surveys conducted in hospitals in the city by the Health Ministry of Colombia for this study. These pre-processings have consisted of different techniques such as the determination of the quality of data collection, determination of the quality of the registration network, identification and debugging of errors in data collection, completion of missing data and purified data, as well as the improvement of the time scale of records. The characterization of the quality of the data has been conducted by means of density analysis of the pollutant registration stations using ArcGis Software and through mass balance techniques, making it possible to determine inconsistencies in the records relating the registration data between stations following the linear regression. The results obtained in this process have highlighted the positive quality in the pollutant registration process. Consequently, debugging of errors has allowed us to identify certain data as statistically non-significant in the incidence and series of contamination. This data, together with certain missing records in the series recorded by the measuring stations, have been completed by statistical imputation equations. Following the application of these prior processes, the basic series of incidence data for respiratory disease and pollutant records have allowed the characterization of the influence of pollutants on respiratory diseases such as, for example, childhood asthma. This characterization has been carried out using statistical correlation methods, including visual correlation, simple linear regression correlation and spectral analysis with PAST Software which identifies maximum periodicity cycles and minimums under the formula of the Lomb periodgram. In relation to part of the results obtained, up to eleven maximums and minimums considered contemporary between the incidence records and the particles have been identified taking into account the visual comparison. The spectral analyses that have been performed on the incidence and the PM2.5 have returned a series of similar maximum periods in both registers, which are at a maximum during a period of one year and another every 25 days (0.9 and 0.07 years). The bivariate analysis has managed to characterize the variable "Daily Vehicular Flow" in the ninth position of importance of a total of 55 variables. However, the statistical correlation has not obtained a favorable result, having obtained a low value of the R2 coefficient. The series of analyses conducted has demonstrated the importance of the influence of pollutants such as PM2.5 in the development of childhood asthma in Cartagena. The quantification of the influence of the variables has been able to determine that there is a 56% probability of dependence between PM2.5 and childhood respiratory asthma in Cartagena. Considering this justification, the study could be completed through the application of the BenMap Software, throwing a series of spatial results of interpolated values of the pollutant contamination records that exceeded the established legal limits (represented by homogeneous units up to the neighborhood level) and results of the impact on the exacerbation of pediatric asthma. As a final result, an economic estimate (in Colombian Pesos) of the monthly and individual savings derived from the percentage reduction of the influence of pollutants in relation to visits to the Hospital Emergency Room due to asthma exacerbation in pediatric patients has been granted.

Keywords: Asthma Incidence, BenMap, PM2.5, Statistical Analysis

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Authors: Jaan-Willem Simon, Bertram Stier, Brett Bednarcyk, Evan Pineda, Stefanie Reese

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Textile composites, in which the reinforcing fibers are woven or braided, have become very popular in numerous applications in aerospace, automotive, and maritime industry. These textile composites are advantageous due to their ease of manufacture, damage tolerance, and relatively low cost. However, physics-based modeling of the mechanical behavior of textile composites is challenging. Compared to their unidirectional counterparts, textile composites introduce additional geometric complexities, which cause significant local stress and strain concentrations. Since these internal concentrations are primary drivers of nonlinearity, damage, and failure within textile composites, they must be taken into account in order for the models to be predictive. The macro-scale approach to modeling textile-reinforced composites treats the whole composite as an effective, homogenized material. This approach is very computationally efficient, but it cannot be considered predictive beyond the elastic regime because the complex microstructural geometry is not considered. Further, this approach can, at best, offer a phenomenological treatment of nonlinear deformation and failure. In contrast, the mesoscale approach to modeling textile composites explicitly considers the internal geometry of the reinforcing tows, and thus, their interaction, and the effects of their curved paths can be modeled. The tows are treated as effective (homogenized) materials, requiring the use of anisotropic material models to capture their behavior. Finally, the micro-scale approach goes one level lower, modeling the individual filaments that constitute the tows. This paper will compare meso- and micro-scale approaches to modeling the deformation, damage, and failure of textile-reinforced polymer matrix composites. For the mesoscale approach, the woven composite architecture will be modeled using the finite element method, and an anisotropic damage model for the tows will be employed to capture the local nonlinear behavior. For the micro-scale, two different models will be used, the one being based on the finite element method, whereas the other one makes use of an embedded semi-analytical approach. The goal will be the comparison and evaluation of these approaches to modeling textile-reinforced composites in terms of accuracy, efficiency, and utility.

Keywords: multiscale modeling, continuum damage model, damage interaction, textile composites

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Authors: Sakshi Gupta, Seema Joshi

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Thiosemicarbazones (TSCs) have garnered significant attention in coordination chemistry due to their versatile coordination modes and pharmacological properties. Mixed ligand complexes of TSCs represent a promising area of research, offering enhanced antimicrobial activities compared to their parent compounds. This review provides an overview of the synthesis, characterization, and antimicrobial properties of mixed ligand complexes incorporating thiosemicarbazones. The synthesis of mixed ligand complexes typically involves the reaction of a metal salt with TSC ligands and additional ligands, such as nitrogen- or oxygen-based ligands. Various transition metals, including copper, nickel, and cobalt, have been employed to form mixed ligand complexes with TSCs. Characterization techniques such as spectroscopy, X-ray crystallography, and elemental analysis are commonly utilized to confirm the structures of these complexes. One of the key advantages of mixed ligand complexes is their enhanced antimicrobial activity compared to pure TSC compounds. The synergistic effect between the TSC ligands and additional ligands contributes to increased efficacy, possibly through improved metal-ligand interactions or enhanced membrane permeability. Furthermore, mixed ligand complexes offer the potential for selective targeting of microbial species while minimizing toxicity to mammalian cells. This selectivity arises from the specific interactions between the metal center, TSC ligands, and biological targets within microbial cells. Such targeted antimicrobial activity is crucial for developing effective treatments with minimal side effects. Moreover, the versatility of mixed ligand complexes allows for the design of tailored antimicrobial agents with optimized properties. By varying the metal ion, TSC ligands, and additional ligands, researchers can fine-tune the physicochemical properties and biological activities of these complexes. This tunability opens avenues for the development of novel antimicrobial agents with improved efficacy and reduced resistance. In conclusion, mixed ligand complexes of thiosemicarbazones represent a promising class of compounds with potent antimicrobial activities. Further research in this field holds great potential for the development of novel therapeutic agents to combat microbial infections effectively.

Keywords: metal complex, thiosemicarbazones, mixed ligand, selective targeting, antimicrobial activity

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Authors: Xianghong Lu, Yuejun Wang, Chengshi Gan, Xin Qian

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The North Sulawesi Arc, located on the east of Indonesia and to the south of the Celebes Sea, is the north part of the K-shape of Sulawesi Island and has a complex tectonic history since the Cenozoic due to the convergence of three plates (Eurasia, India-Australia and Pacific plates). Published rock records contain less precise chronology, mostly using K-Ar dating, and rare geochemistry data, which limit the understanding of the regional tectonic setting. This study presents detailed zircon U-Pb geochronological and Hf-O isotope and whole-rock geochemical analyses for the Na-rich granites from the North Sulawesi Arc. Zircon U-Pb geochronological analyses of three representative samples yield weighted mean ages of 30.4 ± 0.4 Ma, 29.5 ± 0.2 Ma, and 27.3 ± 0.4 Ma, respectively, revealing the Oligocene magmatism in the North Sulawesi Arc. The samples have high Na₂O and low K₂O contents with high Na₂O/K₂O ratios, belonging to Low-K tholeiitic Na-rich granites. The Na-rich granites are characterized by high SiO₂ contents (75.05-79.38 wt.%) and low MgO contents (0.07-0.91 wt.%) and show arc-like trace elemental signatures. They have low (⁸⁷Sr/⁸⁶Sr)i ratios (0.7044-0.7046), high εNd(t) values (from +5.1 to +6.6), high zircon εHf(t) values (from +10.1 to +18.8) and low zircon δ18O values (3.65-5.02). They show an Indian-Ocean affinity of Pb isotopic compositions with ²⁰⁶Pb/²⁰⁴Pb ratio of 18.16-18.37, ²⁰⁷Pb/²⁰⁴Pb ratio of 15.56-15.62, and ²⁰⁸Pb/²⁰⁴Pb ratio of 38.20-38.66. These geochemical signatures suggest that the Oligocene Na-rich granites from the North Sulawesi Arc formed by partial melting of the juvenile oceanic crust with sediment-derived fluid-related metasomatism in a subducting setting and support an intra-oceanic arc origin. Combined with the published study, the emergence of extensive calc-alkaline felsic arc magmatism can be traced back to the Early Oligocene period, subsequent to the Eocene back-arc basalts (BAB) that share similarity with the Celebes Sea basement. Since the opening of the Celebes Sea started from the Eocene (42~47 Ma) and stopped by the Early Oligocene (~32 Ma), the geodynamical mechanism of the formation of the Na-rich granites from the North Sulawesi Arc during the Oligocene might relate to the subduction of the Indian Ocean.

Keywords: North Sulawesi Arc, oligocene, Na-rich granites, in-situ zircon Hf–O analysis, intra-oceanic origin

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Authors: Saeidreza Radpour, Md. Ahiduzzaman, Amit Kumar

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Alberta’s mining sector consumed 871.3 PJ in 2012, which is 67.1% of the energy consumed in the industry sector and about 40% of all the energy consumed in the province of Alberta. Natural gas, petroleum products, and electricity supplied 55.9%, 20.8%, and 7.7%, respectively, of the total energy use in this sector. Oil sands mining and upgrading to crude oil make up most of the mining energy sector activities in Alberta. Crude oil is produced from the oil sands either by in situ methods or by the mining and extraction of bitumen from oil sands ore. In this research, the factors affecting oil sands production have been assessed and a framework has been developed for market penetration of new efficient technologies in this sector. Oil sands production amount is a complex function of many different factors, broadly categorized into technical, economic, political, and global clusters. The results of developed and implemented statistical analysis in this research show that the importance of key factors affecting on oil sands production in Alberta is ranked as: Global energy consumption (94% consistency), Global crude oil price (86% consistency), and Crude oil export (80% consistency). A framework for modeling oil sands energy technologies’ market penetration (OSETMP) has been developed to cover related technical, economic and environmental factors in this sector. It has been assumed that the impact of political and social constraints is reflected in the model by changes of global oil price or crude oil price in Canada. The market share of novel in situ mining technologies with low energy and water use are assessed and calculated in the market penetration framework include: 1) Partial upgrading, 2) Liquid addition to steam to enhance recovery (LASER), 3) Solvent-assisted process (SAP), also called solvent-cyclic steam-assisted gravity drainage (SC-SAGD), 4) Cyclic solvent, 5) Heated solvent, 6) Wedge well, 7) Enhanced modified steam and Gas push (emsagp), 8) Electro-thermal dynamic stripping process (ET-DSP), 9) Harris electro-magnetic heating applications (EMHA), 10) Paraffin froth separation. The results of the study will show the penetration profile of these technologies over a long term planning horizon.

Keywords: appliances efficiency improvement, diffusion models, market penetration, residential sector

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Authors: Hao Yan, Xiaobing Zhang

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The working mechanism of miniaturized solid rocket motors (SRMs) is not yet fully understood. It is imperative to explore its unique features. However, there are many disadvantages to using common multi-objective evolutionary algorithms (MOEAs) in predicting the parameters of the miniaturized SRM during its conceptual design phase. Initially, the design variables and objectives are constrained in a lumped parameter model (LPM) of this SRM, which leads to local optima in MOEAs. In addition, MOEAs require a large number of calculations due to their population strategy. Although the calculation time for simulating an LPM just once is usually less than that of a CFD simulation, the number of function evaluations (NFEs) is usually large in MOEAs, which makes the total time cost unacceptably long. Moreover, the accuracy of the LPM is relatively low compared to that of a CFD model due to its assumptions. CFD simulations or experiments are required for comparison and verification of the optimal results obtained by MOEAs with an LPM. The conceptual design phase based on MOEAs is a lengthy process, and its results are not precise enough due to the above shortcomings. An artificial neural network (ANN) based parameter prediction is proposed as a way to reduce time costs and improve prediction accuracy. In this method, an ANN is used to build a surrogate model that is trained with a 3D numerical simulation. In design, the original LPM is replaced by a surrogate model. Each case uses the same MOEAs, in which the calculation time of the two models is compared, and their optimization results are compared with 3D simulation results. Using the surrogate model for the parameter prediction process of the miniaturized SRMs results in a significant increase in computational efficiency and an improvement in prediction accuracy. Thus, the ANN-based surrogate model does provide faster and more accurate parameter prediction for an initial design scheme. Moreover, even when the MOEAs converge to local optima, the time cost of the ANN-based surrogate model is much lower than that of the simplified physical model LPM. This means that designers can save a lot of time during code debugging and parameter tuning in a complex design process. Designers can reduce repeated calculation costs and obtain accurate optimal solutions by combining an ANN-based surrogate model with MOEAs.

Keywords: artificial neural network, solid rocket motor, multi-objective evolutionary algorithm, surrogate model

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Authors: Manuel I. Capel, Antonio Tomeu, Alberto Salguero

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Tumor growth from a transformed cancer-cell up to a clinically apparent mass spans through a range of spatial and temporal magnitudes. Through computer simulations, Cellular Automata (CA) can accurately describe the complexity of the development of tumors. Tumor development prognosis can now be made -without making patients undergo through annoying medical examinations or painful invasive procedures- if we develop appropriate CA-based software tools. In silico testing mainly refers to Computational Biology research studies of application to clinical actions in Medicine. To establish sound computer-based models of cellular behavior, certainly reduces costs and saves precious time with respect to carrying out experiments in vitro at labs or in vivo with living cells and organisms. These aim to produce scientifically relevant results compared to traditional in vitro testing, which is slow, expensive, and does not generally have acceptable reproducibility under the same conditions. For speeding up computer simulations of cellular models, specific literature shows recent proposals based on the CA approach that include advanced techniques, such the clever use of supporting efficient data structures when modeling with deterministic stochastic cellular automata. Multiparadigm and multiscale simulation of tumor dynamics is just beginning to be developed by the concerned research community. The use of stochastic cellular automata (SCA), whose parallel programming implementations are open to yield a high computational performance, are of much interest to be explored up to their computational limits. There have been some approaches based on optimizations to advance in multiparadigm models of tumor growth, which mainly pursuit to improve performance of these models through efficient memory accesses guarantee, or considering the dynamic evolution of the memory space (grids, trees,…) that holds crucial data in simulations. In our opinion, the different optimizations mentioned above are not decisive enough to achieve the high performance computing power that cell-behavior simulation programs actually need. The possibility of using multicore and GPU parallelism as a promising multiplatform and framework to develop new programming techniques to speed-up the computation time of simulations is just starting to be explored in the few last years. This paper presents a model that incorporates parallel processing, identifying the synchronization necessary for speeding up tumor growth simulations implemented in Java and C++ programming environments. The speed up improvement that specific parallel syntactic constructs, such as executors (thread pools) in Java, are studied. The new tumor growth parallel model is proved using implementations with Java and C++ languages on two different platforms: chipset Intel core i-X and a HPC cluster of processors at our university. The parallelization of Polesczuk and Enderling model (normally used by researchers in mathematical oncology) proposed here is analyzed with respect to performance gain. We intend to apply the model and overall parallelization technique presented here to solid tumors of specific affiliation such as prostate, breast, or colon. Our final objective is to set up a multiparadigm model capable of modelling angiogenesis, or the growth inhibition induced by chemotaxis, as well as the effect of therapies based on the presence of cytotoxic/cytostatic drugs.

Keywords: cellular automaton, tumor growth model, simulation, multicore and manycore programming, parallel programming, high performance computing, speed up

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