Search results for: traditional rehabilitation exercises

Authors: Esther Van Andel, Stefanie C. Lange, Maarten M. J. Smulders, Han Zuilhof

Abstract:

False outcomes of diagnostic tests are a major concern in medical health care. To improve the reliability of surface-based diagnostic tests, it is of crucial importance to diminish background signals that arise from the non-specific binding of biomolecules, a process called fouling. The aim is to create surfaces that repel all biomolecules except the molecule of interest. This can be achieved by incorporating antifouling protein repellent coatings in between the sensor surface and it’s recognition elements (e.g. antibodies, sugars, aptamers). Zwitterionic polymer brushes are considered excellent antifouling materials, however, to be able to bind the molecule of interest, the polymer brushes have to be functionalized and so far this was only achieved at the expense of either antifouling or binding capacity. To overcome this limitation, we combined both features into one single monomer: a zwitterionic sulfobetaine, ensuring antifouling capabilities, equipped with a clickable azide moiety which allows for further functionalization. By copolymerizing this monomer together with a standard sulfobetaine, the number of azides (and with that the number of recognition elements) can be tuned depending on the application. First, the clickable azido-monomer was synthesized and characterized, followed by copolymerizing this monomer to yield functionalizable antifouling brushes. The brushes were fully characterized using surface characterization techniques like XPS, contact angle measurements, G-ATR-FTIR and XRR. As a proof of principle, the brushes were subsequently functionalized with biotin via strain-promoted alkyne azide click reactions, which yielded a fully zwitterionic biotin-containing 3D-functionalized coating. The sensing capacity was evaluated by reflectometry using avidin and fibrinogen containing protein solutions. The surfaces showed excellent antifouling properties as illustrated by the complete absence of non-specific fibrinogen binding, while at the same time clear responses were seen for the specific binding of avidin. A great increase in signal-to-noise ratio was observed, even when the amount of functional groups was lowered to 1%, compared to traditional modification of sulfobetaine brushes that rely on a 2D-approach in which only the top-layer can be functionalized. This study was performed on stoichiometric silicon nitride surfaces for future microring resonator based assays, however, this methodology can be transferred to other biosensor platforms which are currently being investigated. The approach presented herein enables a highly efficient strategy for selective binding with retained antifouling properties for improved signal-to-noise ratios in binding assays. The number of recognition units can be adjusted to a specific need, e.g. depending on the size of the analyte to be bound, widening the scope of these functionalizable surface coatings.

Keywords: antifouling, signal-to-noise ratio, surface functionalization, zwitterionic polymer brushes

Procedia PDF Downloads 306

Authors: Denisa Denglerova, Radim Sip

Abstract:

Academic sources as well as international agreements and national documents define inclusion in terms of several criteria: equal opportunities, fulfilling individual needs, development of human resources, community participation. In order for these criteria to be met, the community must be cohesive. Community cohesion, which is a relatively new concept, is not determined by homogeneity, but by the acceptance of diversity among the community members and utilisation of its positive potential. This brings us to a central category of inclusion - appreciating diversity and using it to a positive effect. However, school diversity is a real phenomenon, which schools need to tackle more and more often. This is also indicated by the number of publications focused on diversity in schools. These sources present recent analyses of using identity as a tool of coping with the demands of a diversified society. The aim of this study is to identify and describe in detail the processes taking place in selected schools, which contribute to their pro-inclusive character. The research is designed around a multiple case study of three pro-inclusive schools. Paradigmatically speaking, the research is rooted in situational epistemology. This is also related to the overall framework of interpretation, for which we are going to use innovative methods of situational analysis. In terms of specific research outcomes this will manifest itself in replacing the idea of “objective theory” by the idea of “detailed cartography of a social world”. The cartographic approach directs both the logic of data collection and the choice of methods of their analysis and interpretation. The research results include detection of the following sensitive concepts: Key persons. All participants can contribute to promoting an inclusion-friendly environment; however, some do so with greater motivation than others. These could include school management, teachers with a strong vision of equality, or school counsellors. They have a significant effect on the transformation of the school, and are themselves deeply convinced that inclusion is necessary. Accordingly, they select suitable co-workers; they also inspire some of the other co-workers to make changes, leading by example. Employees with strongly opposing views gradually leave the school, and new members of staff are introduced to the concept of inclusion and openness from the beginning. Manifestations of school openness in working with diversity on all important levels. By this we mean positive manipulation with diversity both in the relationships between “traditional” school participants (directors, teachers, pupils) and school-parent relationships, or relationships between schools and the broader community, in terms of teaching methods as well as ways how the school culture affects the school environment. Other important detected concepts significantly helping to form a pro-inclusive environment in the school are individual and parallel classes; freedom and responsibility of both pupils and teachers, manifested on the didactic level by tendencies towards an open curriculum; ways of asserting discipline in the school environment.

Keywords: inclusion, diversity, education, sensitive concept, situational analysis

Procedia PDF Downloads 199

Authors: Ismene Ithai Bras-Ruiz

Abstract:

Learning Analytics (LA) is employed by universities not only as a tool but as a specialized ground to enhance students and professors. However, not all the academic programs apply LA with the same goal and use the same tools. In fact, LA is formed by five main fields of study (academic analytics, action research, educational data mining, recommender systems, and personalized systems). These fields can help not just to inform academic authorities about the situation of the program, but also can detect risk students, professors with needs, or general problems. The highest level applies Artificial Intelligence techniques to support learning practices. LA has adopted different techniques: statistics, ethnography, data visualization, machine learning, natural language process, and data mining. Is expected that any academic program decided what field wants to utilize on the basis of his academic interest but also his capacities related to professors, administrators, systems, logistics, data analyst, and the academic goals. The Open and Distance University System (SUAYED in Spanish) of the University National Autonomous of Mexico (UNAM), has been working for forty years as an alternative to traditional programs; one of their main supports has been the employ of new information and communications technologies (ICT). Today, UNAM has one of the largest network higher education programs, twenty-six academic programs in different faculties. This situation means that every faculty works with heterogeneous populations and academic problems. In this sense, every program has developed its own Learning Analytic techniques to improve academic issues. In this context, an investigation was carried out to know the situation of the application of LA in all the academic programs in the different faculties. The premise of the study it was that not all the faculties have utilized advanced LA techniques and it is probable that they do not know what field of study is closer to their program goals. In consequence, not all the programs know about LA but, this does not mean they do not work with LA in a veiled or, less clear sense. It is very important to know the grade of knowledge about LA for two reasons: 1) This allows to appreciate the work of the administration to improve the quality of the teaching and, 2) if it is possible to improve others LA techniques. For this purpose, it was designed three instruments to determinate the experience and knowledge in LA. These were applied to ten faculty coordinators and his personnel; thirty members were consulted (academic secretary, systems manager, or data analyst, and coordinator of the program). The final report allowed to understand that almost all the programs work with basic statistics tools and techniques, this helps the administration only to know what is happening inside de academic program, but they are not ready to move up to the next level, this means applying Artificial Intelligence or Recommender Systems to reach a personalized learning system. This situation is not related to the knowledge of LA, but the clarity of the long-term goals.

Keywords: academic improvements, analytical techniques, learning analytics, personnel expertise

Procedia PDF Downloads 128

Authors: Ojas Chaudhari, Ali Nejad Ghafar, Giedrius Zirgulis, Marjan Mousavi, Tommy Ellison, Sandra Pousette, Patrick Fontana

Abstract:

In Swedish tunnel construction, a critical issue that has been repeatedly acknowledged is corrosion and, consequently, failure of the rock bolts in rock support systems. The defective installation of rock bolts results in the formation of cavities in the cement mortar that is regularly used to fill the area under the dome plates. These voids allow for water-ingress to the rock bolt assembly, which results in corrosion of rock bolt components and eventually failure. In addition, the current installation technique consists of several manual steps with intense labor works that are usually done in uncomfortable and exhausting conditions, e.g., under the roof of the tunnels. Such intense tasks also lead to a considerable waste of materials and execution errors. Moreover, adequate quality control of the execution is hardly possible with the current technique. To overcome these issues, a non-shrinking/expansive cement-based mortar filled in the paper packaging has been developed in this study which properly fills the area under the dome plates without or with the least remaining cavities, ultimately that diminishes the potential of corrosion. This article summarizes the development process and the experimental evaluation of this technique for the installation of rock bolts. In the development process, the cementitious mortar was first developed using specific cement and shrinkage reducing/expansive additives. The mechanical and flow properties of the mortar were then evaluated using compressive strength, density, and slump flow measurement methods. In addition, isothermal calorimetry and shrinkage/expansion measurements were used to elucidate the hydration and durability attributes of the mortar. After obtaining the desired properties in both fresh and hardened conditions, the developed dry mortar was filled in specific permeable paper packaging and then submerged in water bath for specific intervals before the installation. The tests were enhanced progressively by optimizing different parameters such as shape and size of the packaging, characteristics of the paper used, immersion time in water and even some minor characteristics of the mortar. Finally, the developed prototype was tested in a lab-scale rock bolt assembly with various angles to analyze the efficiency of the method in real life scenario. The results showed that the new technique improves the performance of the rock bolts by reducing the material wastage, improving environmental performance, facilitating and accelerating the labor works, and finally enhancing the durability of the whole system. Accordingly, this approach provides an efficient alternative for the traditional way of tunnel bolt installation with considerable advantages for the Swedish tunneling industry.

Keywords: corrosion, durability, mortar, rock bolt

Procedia PDF Downloads 112

Authors: Ampe Mohottige Sachinthi Sandaruwani Amarasiri, Anoja Priyadarshani Attanayake, Kamani Ayoma Perera Wijewardana Jayatilaka, Lakmini Kumari Boralugoda Mudduwa

Abstract:

The search for alternative pharmacological therapies based on natural extracts for renal failure has become an urgent need, due to paucity of effective pharmacotherapy. The current study was undertaken to evaluate the acute nephroprotective effect of aqueous leaf extract of Plectranthus amboinicus (Roxb.) (Family: Lamiaceae), a medicinal plant used in traditional Ayurvedic medicine for the management of renal diseases in Sri Lanka. The study was performed in adriamycin (ADR) induced nephrotoxic in Wistar rats. Wistar rats were randomly divided into four groups each with six rats. A single dose of ADR (20 mg/kg body wt., ip) was used for the induction of nephrotoxicity in all groups of rats except group one. The treatments were started 24 hours after induction of nephrotoxicity and continued for three days. Group one and two served as healthy and nephrotoxic control rats and were administered equivalent volumes of normal saline (0.9% NaCl) orally. Group three and four nephrotoxic rats were administered the lyophilized powder of the aqueous extract of P. amboinicus (400 mg/ kg body wt.; equivalent human therapeutic dose) and the standard drug, fosinopril sodium (0.09 mg/ kg body wt.) respectively. Urine and blood samples were collected from rats in each group at the end of the period of intervention for the estimation of selected renal parameters. H and E stained sections of the kidney tissues were examined for histopathological changes. Rats treated with the plant extract showed significant improvement in biochemical parameters and histopathological changes compared to ADR induced nephrotoxic group. The elevation of serum concentrations of creatinine and β2-microglobulin were decreased by 38%, and 66% in plant extract treated nephrotoxic rats respectively (p < 0.05). In addition, serum concentrations of total protein and albumin were significantly increased by 25% and 14% in rats treated with P. amboinicus respectively (p < 0.05). The results of β2 –microglobulin and serum total protein demonstrated a significant reduction in the elevated values in rats administered with the plant extract (400 mg/kg) compared to that of fosinopril (0.09 mg/kg). Urinary protein loss in 24hr urine samples was significantly decreased in rats treated with both fosinopril (86%) and P. ambonicus (56%) at the end of the intervention (p < 0.01). Accordingly, an attenuation of morphological destruction was observed in the H and E stained sections of the kidney with the treatments of plant extract and fosinopril. The results of the present study revealed that the aqueous leaf extract of P. amboinicus possesses significant nephroprotective activity at the equivalent therapeutic dose of 400 mg/ kg against adriamycin induced acute nephrotoxicity.

Keywords: biochemical assessment, histopathological assessment, nephroprotective activity, Plectranthus amboinicus

Procedia PDF Downloads 146

Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

Abstract:

Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

Procedia PDF Downloads 66

Authors: Web Huei Chou, Li Yi Chun, Wenwe Yu, Han Teng Weng, H. Yuan, T. Yang

Abstract:

The prevalence of dementia is estimated to rise to 78 million by 2030 and 139 million by 2050. Among those affected, Alzheimer's disease is the most common form of dementia, contributing to 60–70% of cases. Addressing this growing challenge is crucial, especially considering the impact on older individuals and their caregivers. To reduce the behavioral and psychological symptoms of dementia, people with dementia use a variety of pharmaceutical and non-pharmacological treatments, and some studies have found the use of non-pharmacological interventions. Treatment of depression, cognitive function, and social activities has potential benefits. Butler developed reminiscence therapy as a method of treating dementia. Through ‘life review,’ individuals can recall their past events, activities, and experiences, which can reduce the depression of the elderly and improve their Quality of life to help give meaning to their lives and help them live independently. The life review process uses a variety of memory triggers, such as household items, past objects, photos, and music, and can be conducted collectively or individually and structured or unstructured. However, despite the advantages of nostalgia therapy, past research has always pointed out that current research lacks rigorous experimental evaluation and cannot describe clear research results and generalizability. Therefore, this study aims to study physiological sensing experiments to find a feasible experimental and verification method to provide clearer design and design specifications for reminiscence therapy and to provide a more widespread application for healthy aging. This study is an ongoing research project, a collaboration between the School of Design at Yunlin University of Science and Technology in Taiwan and the Department of Medical Engineering at Chiba University in Japan. We use traditional rice dishes from Taiwan and Japan as nostalgic content to construct a narrative structure for the elderly in the two countries respectively for life review activities, providing an easy-to-carry nostalgic therapy game with an intuitive interactive design. This experiment is expected to be completed in 36 months. The design team constructed and designed the game after conducting literary and historical data surveys and interviews with elders to confirm the nostalgic historical data in Taiwan and Japan. The Japanese team planned the Electrodermal Activity (EDA) and Blood Volume Pulse (BVP) experimental environments and Data calculation model, and then after conducting experiments on elderly people in two places, the research results were analyzed and discussed together. The research has completed the first 24 months of pre-study, design work, and pre-study and has entered the project acceptance stage.

Keywords: reminiscence therapy, aging health, design research, life review

Procedia PDF Downloads 33

Authors: S. Jimenez, R.Duarte, J.Sanchez-Choliz, I. Villanua

Abstract:

There is a certain consensus in economic literature about the factors that have influenced in historical differences in growth rates observed between developed and developing countries. However, it is less clear what elements have marked different paths of growth in developed economies in recent decades. R&D has always been seen as one of the major sources of technological progress, and productivity growth, which is directly influenced by technological developments. Following recent literature, we can say that ‘innovation pushes the technological frontier forward’ as well as encourage future innovation through the creation of externalities. In other words, productivity benefits from innovation are not fully appropriated by innovators, but it also spread through the rest of the economies encouraging absorptive capacities, what have become especially important in a context of increasing fragmentation of production This paper aims to contribute to this literature in two ways, first, exploring alternative indexes of R&D flows embodied in inter-country, inter-sectorial flows of good and services (as approximation to technology spillovers) capturing structural and technological characteristic of countries and, second, analyzing the impact of direct and embodied R&D on the evolution of labor productivity at the country/sector level in recent decades. The traditional way of calculation through a multiregional input-output framework assumes that all countries have the same capabilities to absorb technology, but it is not, each one has different structural features and, this implies, different capabilities as part of literature, claim. In order to capture these differences, we propose to use a weight based on specialization structure indexes; one related with the specialization of countries in high-tech sectors and the other one based on a dispersion index. We propose these two measures because, as far as we understood, country capabilities can be captured through different ways; countries specialization in knowledge-intensive sectors, such as Chemicals or Electrical Equipment, or an intermediate technology effort across different sectors. Results suggest the increasing importance of country capabilities while increasing the trade openness. Besides, if we focus in the country rankings, we can observe that with high-tech weighted R&D embodied countries as China, Taiwan and Germany arose the top five despite not having the highest intensities of R&D expenditure, showing the importance of country capabilities. Additionally, through a fixed effects panel data model we show that, in fact, R&D embodied is important to explain labor productivity increases, in fact, even more that direct R&D investments. This is reflecting that globalization is more important than has been said until now. However, it is true that almost all analysis done in relation with that consider the effect of t-1 direct R&D intensity over economic growth. Nevertheless, from our point of view R&D evolve as a delayed flow and it is necessary some time to be able to see its effects on the economy, as some authors have already claimed. Our estimations tend to corroborate this hypothesis obtaining a gap between 4-5 years.

Keywords: economic growth, embodied, input-output, technology

Procedia PDF Downloads 124

Authors: Mohammad Lemar Zalmai, Osman Hurol Turkakin, Cemil Akcay, Ekrem Manisali

Abstract:

In public construction projects, determining the contract period in the award phase is one of the most important factors. The contract period establishes the baseline for creating the cash flow curve and progress payment planning in the post-award phase. If overestimated, project duration causes losses for both the owner and the contractor. Therefore, it is essential to base construction project duration on reliable forecasting. In Turkey, schedules are usually built using the bar chart (Gantt) schedule, especially for governmental construction agencies. The usage of these schedules is limited for bidding purposes. Although the bar-chart schedule is useful in some cases, it lacks logical connections between activities; it would be harder to obtain the activities that have more effects than others on the project's total duration, especially in large complex projects. In this study, a construction schedule is prepared with Critical Path Method (CPM) that addresses the above-mentioned discrepancies. CPM is a simple and effective method that displays project time and critical paths, showing results of forward and backward calculations with considering the logic relationships between activities; it is a powerful tool for planning and managing all kinds of construction projects and is a very convenient method for the construction industry. CPM provides a much more useful and precise approach than traditional bar-chart diagrams that form the basis of construction planning and control. CPM has two main application utilities in the construction field; the first one is obtaining project duration, which is called an as-planned schedule that includes as-planned activity durations with relationships between subsequent activities. Another utility is during the project execution; each activity is tracked, and their durations are recorded in order to obtain as-built schedule, which is named as a black box of the project. The latter is more useful for delay analysis, and conflict resolutions. These features of CPM have been popular around the world. However, it has not been yet extensively used in Turkey. In this study, a real construction project is investigated as a case study; CPM-based scheduling is used for establishing both of as-built and as-planned schedules. Problems that emerged during the construction phase are identified and categorized. Subsequently, solutions are suggested. Two scenarios were considered. In the first scenario, project progress was monitored based as CPM was used to track and manage progress; this was carried out based on real-time data. In the second scenario, project progress was supposedly tracked based on the assumption that the Gantt chart was used. The S-curves of the two scenarios are plotted and interpreted. Comparing the results, possible faults of the latter scenario are highlighted, and solutions are suggested. The importance of CPM implementation has been emphasized and it has been proposed to make it mandatory for preparation of construction schedule based on CPM for public construction projects contracts.

Keywords: as-built, case-study, critical path method, Turkish government sector projects

Procedia PDF Downloads 119

Authors: Thomas Turner

Abstract:

Due to the Covid-19 pandemic alternative ways of delivering dental education were required. As a result, many institutions moved teaching online. The impact of this is poorly understood. Is online problem-based learning (PBL) and case-based learning (CBL) effective and is it suitable in the post-pandemic era? PBL and CBL are both types of interactive, group-based learning which are growing in popularity within many dental schools. PBL was first introduced in the 1960’s and can be defined as learning which occurs from collaborative work to resolve a problem. Whereas CBL encourages learning from clinical cases, encourages application of knowledge and helps prepare learners for clinical practice. To evaluate the use of online PBL and CBL. A literature search was conducted using the CINAHL, Embase, PubMed and Web of Science databases. Literature was also identified from reference lists. Studies were only included from dental education. Seven suitable studies were identified. One of the studies found a high learner and facilitator satisfaction rate with online CBL. Interestingly one study found learners preferred CBL over PBL within an online format. A study also found, that within the context of distance learning, learners preferred a hybrid curriculum including PBL over a traditional approach. A further study pointed to the limitations of PBL within an online format, such as reduced interaction, potentially hindering the development of communication skills and the increased time and technology support required. An audience response system was also developed for use within CBL and had a high satisfaction rate. Interestingly one study found achievement of learning outcomes was correlated with the number of student and staff inputs within an online format. Whereas another study found the quantity of learner interactions were important to group performance, however the quantity of facilitator interactions was not. This review identified generally favourable evidence for the benefits of online PBL and CBL. However, there is limited high quality evidence evaluating these teaching methods within dental education and there appears to be limited evidence comparing online and faceto-face versions of these sessions. The importance of the quantity of learner interactions is evident, however the importance of the quantity of facilitator interactions appears to be questionable. An element to this may be down to the quality of interactions, rather than just quantity. Limitations of online learning regarding technological issues and time required for a session are also highlighted, however as learners and facilitators get familiar with online formats, these may become less of an issue. It is also important learners are encouraged to interact and communicate during these sessions, to allow for the development of communication skills. Interestingly CBL appeared to be preferred to PBL in an online format. This may reflect the simpler nature of CBL, however further research is required to explore this finding. Online CBL and PBL appear promising, however further research is required before online formats of these sessions are widely adopted in the post-pandemic era.

Keywords: case-based learning, online, problem-based learning, remote, virtual

Procedia PDF Downloads 77

Authors: Saikat Majumdar, D. C. Kalita

Abstract:

The Agriculture sector plays an important role in the rural economy of India. It is the backbone of our Indian economy and is the dominant sector in terms of employment and livelihood. Agriculture still contributes significantly to export earnings and is an important source of raw materials as well as of demand for many industrial products particularly fertilizers, pesticides, agricultural implements and a variety of consumer goods, etc. The performance of the agricultural sector influences the growth of Indian economy. According to the 2011 Agricultural Census of India, an estimated 61.5 percentage of rural populations are dependent on agriculture. Proper Agricultural infrastructure has the potential to transform the existing traditional agriculture into a most modern, commercial and dynamic farming system in India through its diffusion of technology. The rate of adoption of modern technology reflects the progress of development in agricultural sector. The adoption of any improved agricultural technology is also dependent on the development of road infrastructure or road network. The present study was consisting of 300 sample farmers out which 150 samples was taken from the developed area and rest 150 samples was taken from underdeveloped area. The samples farmers under develop and underdeveloped areas were collected by using Multistage Random Sampling procedure. In the first stage, North 24 Parganas District have been selected purposively. Then from the district, one developed and one underdeveloped block was selected randomly. In the third phase, 10 villages have been selected randomly from each block. Finally, from each village 15 sample farmers was selected randomly. The extents of adoption of technology in different areas were calculated through various parameters. These are percentage area under High Yielding Variety Cereals, percentage area under High Yielding Variety pulses, area under hybrids vegetables, irrigated area, mechanically operated area, amount spent on fertilizer and pesticides, etc. in both developed and underdeveloped areas of North 24 Parganas District, West Bengal. The percentage area under High Yielding Variety Cereals in the developed and underdeveloped areas was 34.86 and 22.59. 42.07 percentages and 31.46 percentages for High Yielding Variety pulses respectively. In the case the area under irrigation it was 57.66 and 35.71 percent while for the mechanically operated area it was 10.60 and 3.13 percent respectively in developed and underdeveloped areas of North 24 Parganas district, West Bengal. It clearly showed that the extent of adoption of technology was significantly higher in the developed area over underdeveloped area. Better road network system helps the farmers in increasing his farm income, farm assets, cropping intensity, marketed surplus and the rate of adoption of new technology. With this background, an attempt is made in this paper to study the impact of Agricultural Infrastructure on the adoption of modern technology in agriculture in North 24 Parganas District, West Bengal.

Keywords: agricultural infrastructure, adoption of technology, farm income, road network

Procedia PDF Downloads 101

Authors: Yilei Yu

Abstract:

Modernism, emerging in the Western world of the 20th century, attempted to create a universal international style, which pulled the architectural and social systems created by classicism back to an initial pure state. However, out of the introspection of the Modernism, Regionalism attempted to restore a humanistic environment and create flexible buildings during the 1950s. Meanwhile, as the first generation of architects came back, the wind of the Regionalism blew to Taiwan. However, with the increasing of political influence and the tightening of free creative space, from the second half of the 1950s to the 1980s, the "real" Regional Architecture, which should have taken roots in Taiwan, becomes the "fake" Regional Architecture filled with the oriental charm. Through the Comparative Method, which includes description, interpretation, juxtaposition, and comparison, this study analyses the difference of the style of the Modernist Chinese Architecture between the period before the 1980s and the after. The paper aims at exploring the development of Regionalism Architecture in Taiwan, which includes three parts. First, the burgeoning period of the "modernist Chinese architecture" in Taiwan was the beginning of the Chinese Nationalist Party's coming to Taiwan to consolidate political power. The architecture of the "Ming and Qing Dynasty Palace Revival Style" dominated the architectural circles in Taiwan. These superficial "regional buildings" have nearly no combination with the local customs of Taiwan, which is difficult to evoke the social identity. Second, in the late 1970s, the second generation of architects headed by Baode Han began focusing on the research and preservation of traditional Taiwanese architecture, and creating buildings combined the terroirs of Taiwan through the imitation of styles. However, some scholars have expressed regret that very few regionalist architectural works that appeared in the 1980s can respond specifically to regional conditions and forms of construction. Instead, most of them are vocabulary-led representations. Third, during the 1990s, by the end of the period of martial law, community building gradually emerged, which made the object of Taiwan's architectural concern gradually extended to the folk and ethnic groups. In the Yilan area, there are many architects who care about the local environment, such as the Field office Architects. Compared with the hollow regionality of the passionate national spirits that emerged during the martial law period, the local practice of the architect team in Yilan can better link the real local environmental life and reflect the true regionality. In conclusion, with the local practice case of the huge construction team in Yilan area, this paper focuses on the Spatial Practice by the Field office Architects to explore the spatial representation of the space and the practical enlightenment in the process of modernist Chinese architecture development in Taiwan.

Keywords: regionalism, modernism, Chinese architecture, political landscape, spatial representation

Procedia PDF Downloads 129

Authors: Prince Kumar, Shamseer Kulangara Kandi, Diwan S. Rawat, Kasturi Mukhopadhyay

Abstract:

Staphylococcus aureus is the most pathogenic of all staphylococci, a major cause of nosocomial infections, and known for acquiring resistance towards various commonly used antibiotics. Due to the widespread use of synthetic drugs, clinicians are now facing a serious threat in healthcare. The increasing resistance in staphylococci has created a need for alternatives to these synthetic drugs. One of the alternatives is a natural plant-based medicine for both disease prevention as well as the treatment of chronic diseases. Among such natural compounds, curcumin is one of the most studied molecules and has been an integral part of traditional medicines and Ayurveda from ancient times. It is a natural polyphenolic compound with diverse pharmacological effects, including anti-inflammatory, antioxidant, anti-cancerous and antibacterial activities. In spite of its efficacy and potential, curcumin has not been approved as a therapeutic agent yet, because of its low solubility, low bioavailability, and rapid metabolism in vivo. The presence of central β-diketone moiety in curcumin is responsible for its rapid metabolism. To overcome this, in the present study, curcuminoids were designed by modifying the central β-diketone moiety of curcumin into mono carbonyl moiety and their antibacterial potency against S. aureus ATCC 29213 was determined. Further, the mode of action and hemolytic activity of the most potent curcuminoids were studied. Minimum inhibitory concentration (MIC) and in vitro killing kinetics were used to study the antibacterial activity of the designed curcuminoids. For hemolytic assay, mouse Red blood cells were incubated with curcuminoids and hemoglobin release was measured spectrophotometrically. The mode of action of curcuminoids was analysed by membrane depolarization assay using membrane potential sensitive dye 3,3’-dipropylthiacarbocyanine iodide (DiSC3(5)) through spectrofluorimetry and membrane permeabilization assay using calcein-AM through flow cytometry. Antibacterial screening of the designed library (61 curcuminoids) revealed excellent in vitro potency of six compounds against S. aureus (MIC 8 to 32 µg/ml). Moreover, these six compounds were found to be non-hemolytic up to 225 µg/ml that is much higher than their corresponding MIC values. The in vitro killing kinetics data showed five of these lead compounds to be bactericidal causing >3 log reduction in the viable cell count within 4 hrs at 5 × MIC while the sixth compound was found to be bacteriostatic. Depolarization assay revealed that all the six curcuminoids caused depolarization in their corresponding MIC range. Further, the membrane permeabilization assay showed that all the six curcuminoids caused permeabilization at 5 × MIC in 2 hrs. This membrane depolarization and permeabilization caused by curcuminoids found to be in correlation with their corresponding killing efficacy. Both these assays point out that membrane perturbations might be a primary mode of action for these curcuminoids. Overall, the present study leads us six water soluble, non-hemolytic, membrane-active curcuminoids and provided an impetus for further research on therapeutic use of these lead curcuminoids against S. aureus.

Keywords: antibacterial, curcumin, minimum inhibitory concentration , Staphylococcus aureus

Procedia PDF Downloads 170

Authors: Selin Küçük

Abstract:

Pre-industrial architecture is integration of natural and subsequent properties by intelligence and experience. Since various settlements relatively industrialized or non-industrialized at any time, ‘pre-industrial’ term does not refer to a definite time. Natural properties, which are existent conditions and materials in natural local environment, are climate, geomorphology and local materials. Subsequent properties, which are all anthropological comparatives, are culture of societies, requirements of people and construction techniques that people use. Yet, after industrialization, technology took technique’s place, cultural effects are manipulated, requirements are changed and local/natural properties are almost disappeared in architecture. Technology is universal, global and expands simply; conversely technique is time and experience dependent and should has a considerable cultural background. This research is about construction techniques according to natural properties of a region and classification of these techniques. Understanding local architecture is only possible by searching its background which is hard to reach. There are always changes in positive and negative in architectural techniques through the time. Archaeological layers of a region sometimes give more accurate information about transformation of architecture. However, natural properties of any region are the most helpful elements to perceive construction techniques. Many international sources from different cultures are interested in local architecture by mentioning natural properties separately. Unfortunately, there is no literature deals with this subject as far as systematically in the correct way. This research aims to improve a clear perspective of local architecture existence by categorizing archetypes according to natural properties. The ultimate goal of this research is generating a clear classification of local architecture independent from subsequent (anthropological) properties over the world such like a handbook. Since local architecture is the most sustainable architecture with refer to its economic, ecologic and sociological properties, there should be an excessive information about construction techniques to be learned from. Constructing the same buildings in all over the world is one of the main criticism of modern architectural system. While this critics going on, the same buildings without identity increase incrementally. In post-industrial term, technology widely took technique’s place, yet cultural effects are manipulated, requirements are changed and natural local properties are almost disappeared in architecture. These study does not offer architects to use local techniques, but it indicates the progress of pre-industrial architectural evolution which is healthier, cheaper and natural. Immigration from rural areas to developing/developed cities should be prohibited, thus culture and construction techniques can be preserved. Since big cities have psychological, sensational and sociological impact on people, rural settlers can be convinced to not to immigrate by providing new buildings designed according to natural properties and maintaining their settlements. Improving rural conditions would remove the economical and sociological gulf between cities and rural. What result desired to arrived in, is if there is no deformation (adaptation process of another traditional buildings because of immigration) or assimilation in a climatic region, there should be very similar solutions in the same climatic regions of the world even if there is no relationship (trade, communication etc.) among them.

Keywords: climate zones, geomorphology, local architecture, local materials

Procedia PDF Downloads 429

Authors: Oluwagbemi Victor Aladeokin

Abstract:

In the last decade, the global peanut cultivation has seen increased demand, which is attributed to their health benefits, rising to ~ 41.4 MMT in 2019/2020. Peanut and other nutshells are considered as waste in various parts of the world and are usually used for their fuel value. However, this agricultural by-product can be converted to a higher value product such as activated carbon. For many years, due to the highly porous structure of activated carbon, it has been widely and effectively used as an adsorbent in the purification and separation of gases and liquids. Those used for commercial purposes are primarily made from a range of precursors such as wood, coconut shell, coal, bones, etc. However, due to difficulty in regeneration and high cost, various agricultural residues such as rice husk, corn stalks, apricot stones, almond shells, coffee beans, etc, have been explored to produce activated carbons. In the present study, the potential of peanut shells as precursors in the production of activated carbon and their adsorption capacity is investigated. Usually, precursors used to produce activated carbon have carbon content above 45 %. A typical raw peanut shell has 42 wt.% carbon content. To increase the yield, this study has employed chemical activation method using zinc chloride. Zinc chloride is well known for its effectiveness in increasing porosity of porous carbonaceous materials. In chemical activation, activation temperature and impregnation ratio are parameters commonly reported to be the most significant, however, this study has also studied the influence of activation time on the development of activated carbon from peanut shells. Activated carbons are applied for different purposes, however, as the application of activated carbon becomes more specific, an understanding of the influence of activation variables to have a better control of the quality of the final product becomes paramount. A traditional approach to experimentally investigate the influence of the activation parameters, involves varying each parameter at a time. However, a more efficient way to reduce the number of experimental runs is to apply design of experiment. One of the objectives of this study is to optimize the activation variables. Thus, this work has employed response surface methodology of design of experiment to study the interactions between the activation parameters and consequently optimize the activation parameters (temperature, impregnation ratio, and activation time). The optimum activation conditions found were 485 °C, 15 min and 1.7, temperature, activation time, and impregnation ratio respectively. The optimum conditions resulted in an activated carbon with relatively high surface area ca. 1700 m2/g, 47 % yield, relatively high density, low ash, and high fixed carbon content. Impregnation ratio and temperature were found to mostly influence the final characteristics of the produced activated carbon from peanut shells. The results of this study, using response surface methodology technique, have revealed the potential and the most significant parameters that influence the chemical activation process, of peanut shells to produce activated carbon which can find its use in both liquid and gas phase adsorption applications.

Keywords: chemical activation, fixed carbon, impregnation ratio, optimum, surface area

Procedia PDF Downloads 145

Authors: Matthew Yeager, Christopher Willy, John Bischoff

Abstract:

The conceptualization and design phases of a system lifecycle consume a significant amount of the lifecycle budget in the form of direct tasking and capital, as well as the implicit costs associated with unforeseeable design errors that are only realized during downstream phases. Ad hoc or iterative approaches to generating system requirements oftentimes fail to consider the full array of feasible systems or product designs for a variety of reasons, including, but not limited to: initial conceptualization that oftentimes incorporates a priori or legacy features; the inability to capture, communicate and accommodate stakeholder preferences; inadequate technical designs and/or feasibility studies; and locally-, but not globally-, optimized subsystems and components. These design pitfalls can beget unanticipated developmental or system alterations with added costs, risks and support activities, heightening the risk for suboptimal system performance, premature obsolescence or forgone development. Supported by rapid advances in learning algorithms and hardware technology, sensors and sensor systems have become commonplace in both commercial and industrial products. The evolving array of hardware components (i.e. sensors, CPUs, modular / auxiliary access, etc…) as well as recognition, data fusion and communication protocols have all become increasingly complex and critical for design engineers during both concpetualization and implementation. This work seeks to develop and utilize a non-deterministic approach for sensor system design within the multi-attribute tradespace exploration (MATE) paradigm, a technique that incorporates decision theory into model-based techniques in order to explore complex design environments and discover better system designs. Developed to address the inherent design constraints in complex aerospace systems, MATE techniques enable project engineers to examine all viable system designs, assess attribute utility and system performance, and better align with stakeholder requirements. Whereas such previous work has been focused on aerospace systems and conducted in a deterministic fashion, this study addresses a wider array of system design elements by incorporating both traditional tradespace elements (e.g. hardware components) as well as popular multi-sensor data fusion models and techniques. Furthermore, statistical performance features to this model-based MATE approach will enable non-deterministic techniques for various commercial systems that range in application, complexity and system behavior, demonstrating a significant utility within the realm of formal systems decision-making.

Keywords: multi-attribute tradespace exploration, data fusion, sensors, systems engineering, system design

Procedia PDF Downloads 183

Authors: Roberto de Lieto Vollaro, Emanuele de Lieto Vollaro, Gianluca Coltrinari

Abstract:

The building sector is responsible, in many industrialized countries, for about 40% of the total energy requirements, so it seems necessary to devote some efforts in this area in order to achieve a significant reduction of energy consumption and of greenhouse gases emissions. The paper presents a study aiming at providing a design methodology able to identify the best configuration of the system building/plant, from a technical, economic and environmentally point of view. Normally, the classical approach involves a building's energy loads analysis under steady state conditions, and subsequent selection of measures aimed at improving the energy performance, based on previous experience made by architects and engineers in the design team. Instead, the proposed approach uses a sequence of two well known scientifically validated calculation methods (TRNSYS and RETScreen), that allow quite a detailed feasibility analysis. To assess the validity of the calculation model, an existing, historical building in Central Italy, that will be the object of restoration and preservative redevelopment, was selected as a case-study. The building is made of a basement and three floors, with a total floor area of about 3,000 square meters. The first step has been the determination of the heating and cooling energy loads of the building in a dynamic regime by means of TRNSYS, which allows to simulate the real energy needs of the building in function of its use. Traditional methodologies, based as they are on steady-state conditions, cannot faithfully reproduce the effects of varying climatic conditions and of inertial properties of the structure. With TRNSYS it is possible to obtain quite accurate and reliable results, that allow to identify effective combinations building-HVAC system. The second step has consisted of using output data obtained with TRNSYS as input to the calculation model RETScreen, which enables to compare different system configurations from the energy, environmental and financial point of view, with an analysis of investment, and operation and maintenance costs, so allowing to determine the economic benefit of possible interventions. The classical methodology often leads to the choice of conventional plant systems, while RETScreen provides a financial-economic assessment for innovative energy systems and low environmental impact. Computational analysis can help in the design phase, particularly in the case of complex structures with centralized plant systems, by comparing the data returned by the calculation model RETScreen for different design options. For example, the analysis performed on the building, taken as a case study, found that the most suitable plant solution, taking into account technical, economic and environmental aspects, is the one based on a CCHP system (Combined Cooling, Heating, and Power) using an internal combustion engine.

Keywords: energy, system, building, cooling, electrical

Procedia PDF Downloads 573

Authors: Vineeta Sirohi

Abstract:

The development of critical skills and competencies becomes imperative for young people to cope with the unpredicted challenges of the time and prepare for work and life. Recognizing that education has a critical role in reaching sustainability goals as emphasized by 2030 agenda for sustainability development, educating youth in global competence, meta-cognitive competencies, and skills from the initial stages of formal education are vital. Further, educating for global competence would help in developing work readiness and boost employability. Vocational education and training in India as envisaged in various policy documents remain marginalized in practice as compared to general education. The country is still far away from the national policy goal of tracking 25% of the secondary students at grade eleven and twelve under the vocational stream. In recent years, the importance of skill development has been recognized in the present context of globalization and change in the demographic structure of the Indian population. As a result, it has become a national policy priority and taken up with renewed focus by the government, which has set the target of skilling 500 million people by 2022. This paper provides an overview of the policies, practices, and current status of vocational education and training in India supported by statistics from the National Sample Survey, the official statistics of India. The national policy documents and annual reports of the organizations actively involved in vocational education and training have also been examined to capture relevant data and information. It has also highlighted major initiatives taken by the government to promote skill development. The data indicates that in the age group 15-59 years, only 2.2 percent reported having received formal vocational training, and 8.6 percent have received non-formal vocational training, whereas 88.3 percent did not receive any vocational training. At present, the coverage of vocational education is abysmal as less than 5 percent of the students are covered by the vocational education programme. Besides, launching various schemes to address the mismatch of skills supply and demand, the government through its National Policy on Skill Development and Entrepreneurship 2015 proposes to bring about inclusivity by bridging the gender, social and sectoral divide, ensuring that the skilling needs of socially disadvantaged and marginalized groups are appropriately addressed. It is fundamental that the curriculum is aligned with the demands of the labor market, incorporating more of the entrepreneur skills. Creating nonfarm employment opportunities for educated youth will be a challenge for the country in the near future. Hence, there is a need to formulate specific skill development programs for this sector and also programs for upgrading their skills to enhance their employability. There is a need to promote female participation in work and in non-traditional courses. Moreover, rigorous research and development of a robust information base for skills are required to inform policy decisions on vocational education and training.

Keywords: policy, skill, training, vocational education

Procedia PDF Downloads 153

Authors: Nawal Alawad, Passent Ibrahim Tantawi, Mohamed Abdel Salam Ragheb

Abstract:

Providing customers with quality experiences has been confirmed to be a sustainable, competitive advantage with a distinct financial impact for companies. The success of service providers now relies on their ability to provide customer-centric services. The importance of perceived service quality and customer experience is widely recognized. The focus of this research is in the area of mobile and fixed broadband services. This study is of dual importance both academically and practically. Academically, this research applies a new model investigating the impact of customer experience quality on loyalty based on modifying the multiple-item scale for measuring customers’ service experience in a new area and did not depend on the traditional models. The integrated scale embraces four dimensions: service experience, outcome focus, moments of truth and peace of mind. In addition, it gives a scientific explanation for this relationship so this research fill the gap in such relations in which no one correlate or give explanations for these relations before using such integrated model and this is the first time to apply such modified and integrated new model in telecom field. Practically, this research gives insights to marketers and practitioners to improve customer loyalty through evolving the experience quality of broadband customers which is interpreted to suggested outcomes: purchase, commitment, repeat purchase and word-of-mouth, this approach is one of the emerging topics in service marketing. Data were collected through 412 questionnaires and analyzed by using structural equation modeling.Findings revealed that both outcome focus and moments of truth have a significant impact on loyalty while both service experience and peace of mind have insignificant impact on loyalty.In addition, it was found that 72% of the variation occurring in loyalty is explained by the model. The researcher also measured the net prompters score and gave explanation for the results. Furthermore, assessed customer’s priorities of broadband services. The researcher recommends that the findings of this research will extend to be considered in the future plans of Telecom Egypt Group. In addition, to be applied in the same industry especially in the developing countries that have the same circumstances with similar service settings. This research is a positive contribution in service marketing, particularly in telecom industry for making marketing more reliable as managers can relate investments in service experience directly with the performance closest to income for instance, repurchasing behavior, positive word of mouth and, commitment. Finally, the researcher recommends that future studies should consider this model to explain significant marketing outcomes such as share of wallet and ultimately profitability.

Keywords: broadband services, customer experience quality, loyalty, net promoters score

Procedia PDF Downloads 267

Authors: Stefano Pelaggi

Abstract:

The research is focused on youth labor and mobility in Berlin. Mobility has become a common denominator in our daily lives but it does not primarily move according to monetary incentives. Labor, knowledge and leisure overlap on this point as cities are trying to attract people who could participate in production of the innovations while the new migrants are experiencing the lifestyle of the host cities. The research will present the project of empirical study focused on Italian workers in the digital industry in Berlin, trying to underline the connection between pleasure, leisure with the choice of life abroad. Berlin has become the epicenter of the European Internet start-up scene, but people suitable to work for digital industries are not moving in Berlin to make a career, most of them are attracted to the city for different reasons. This point makes a clear exception to traditional migration flows, which are always originated from a specific search of employment opportunities or strong ties, usually families, in a place that could guarantee success in finding a job. Even the skilled migration has always been originated from a specific need, finding the right path for a successful professional life. In a society where the lack of free time in our calendar seems to be something to be ashamed, the actors of youth mobility incorporate some categories of experiential tourism within their own life path. Professional aspirations, lifestyle choices of the protagonists of youth mobility are geared towards meeting the desires and aspirations that define leisure. While most of creative work places, in particular digital industries, uses the category of fun as a primary element of corporate policy, virtually extending the time to work for the whole day; more and more people around the world are deciding their path in life, career choices on the basis of indicators linked to the realization of the self, which may include factors like a warm climate, cultural environment. All indicators that are usually eradicated from the hegemonic approach to labor. The interpretative framework commonly used seems to be mostly focused on a dualism between Florida's theories and those who highlight the absence of conflict in his studies. While the flexibility of the new creative industries is minimizing leisure, incorporating elements of leisure itself in work activities, more people choose their own path of life by placing great importance to basic needs, through a gaze on pleasure that is only partially driven by consumption. The multi localism is the co-existence of different identities and cultures that do not conflict because they reject the bind on territory. Local loses its strength of opposition to global, with an attenuation of the whole concept of citizenship, territory and even integration. A similar perspective could be useful to search a new approach to all the studies dedicated to the gentrification process, while studying the new migrations flow.

Keywords: brain drain, digital industry, leisure and gentrification, multi localism

Procedia PDF Downloads 243

Authors: Rajkumar Ghosh

Abstract:

Earthquakes pose significant risks to human life and infrastructure, highlighting the importance of effective earthquake mitigation strategies. Traditional earthquake modelling and mitigation efforts have largely focused on the primary fault segments and their slip behaviour. However, earthquakes can exhibit complex rupture dynamics, including out-of-sequence thrust (OOST) events, which occur on secondary or subsidiary faults. This abstract examines the impact of OOST dynamics on earthquake mitigation strategies and their implications for hazard assessment and disaster planning. OOST events challenge conventional seismic hazard assessments by introducing additional fault segments and potential rupture scenarios that were previously unrecognized or underestimated. Consequently, these events may increase the overall seismic hazard in affected regions. The study reviews recent case studies and research findings that illustrate the occurrence and characteristics of OOST events. It explores the factors contributing to OOST dynamics, such as stress interactions between fault segments, fault geometry, and mechanical properties of fault materials. Moreover, it investigates the potential triggers and precursory signals associated with OOST events to enhance early warning systems and emergency response preparedness. The abstract also highlights the significance of incorporating OOST dynamics into seismic hazard assessment methodologies. It discusses the challenges associated with accurately modelling OOST events, including the need for improved understanding of fault interactions, stress transfer mechanisms, and rupture propagation patterns. Additionally, the abstract explores the potential for advanced geophysical techniques, such as high-resolution imaging and seismic monitoring networks, to detect and characterize OOST events. Furthermore, the abstract emphasizes the practical implications of OOST dynamics for earthquake mitigation strategies and urban planning. It addresses the need for revising building codes, land-use regulations, and infrastructure designs to account for the increased seismic hazard associated with OOST events. It also underscores the importance of public awareness campaigns to educate communities about the potential risks and safety measures specific to OOST-induced earthquakes. This sheds light on the impact of out-of-sequence thrust dynamics in earthquake mitigation. By recognizing and understanding OOST events, researchers, engineers, and policymakers can improve hazard assessment methodologies, enhance early warning systems, and implement effective mitigation measures. By integrating knowledge of OOST dynamics into urban planning and infrastructure development, societies can strive for greater resilience in the face of earthquakes, ultimately minimizing the potential for loss of life and infrastructure damage.

Keywords: earthquake mitigation, out-of-sequence thrust, seismic, satellite imagery

Procedia PDF Downloads 88

Authors: Muhammmad Riandhy Anindika Yudhy, Harry Patria, Ramadhani Santoso

Abstract:

Loss of containment is the primary hazard that process safety management is concerned within the oil and gas industry. Escalation to more serious consequences all begins with the loss of containment, starting with oil and gas release from leakage or spillage from primary containment resulting in pool fire, jet fire and even explosion when reacted with various ignition sources in the operations. Therefore, the heart of process safety management is avoiding loss of containment and mitigating its impact through the implementation of safeguards. The most effective safeguard for the case is an early detection system to alert Operations to take action prior to a potential case of loss of containment. The detection system value increases when applied to a long surface pipeline that is naturally difficult to monitor at all times and is exposed to multiple causes of loss of containment, from natural corrosion to illegal tapping. Based on prior researches and studies, detecting loss of containment accurately in the surface pipeline is difficult. The trade-off between cost-effectiveness and high accuracy has been the main issue when selecting the traditional detection method. The current best-performing method, Real-Time Transient Model (RTTM), requires analysis of closely positioned pressure, flow and temperature (PVT) points in the pipeline to be accurate. Having multiple adjacent PVT sensors along the pipeline is expensive, hence generally not a viable alternative from an economic standpoint.A conceptual approach to combine mathematical modeling using computational fluid dynamics and a supervised machine learning model has shown promising results to predict leakage in the pipeline. Mathematical modeling is used to generate simulation data where this data is used to train the leak detection and localization models. Mathematical models and simulation software have also been shown to provide comparable results with experimental data with very high levels of accuracy. While the supervised machine learning model requires a large training dataset for the development of accurate models, mathematical modeling has been shown to be able to generate the required datasets to justify the application of data analytics for the development of model-based leak detection systems for petroleum pipelines. This paper presents a review of key leak detection strategies for oil and gas pipelines, with a specific focus on crude oil applications, and presents the opportunities for the use of data analytics tools and mathematical modeling for the development of robust real-time leak detection and localization system for surface pipelines. A case study is also presented.

Keywords: pipeline, leakage, detection, AI

Procedia PDF Downloads 191

Authors: Thi Thi Zin, Pyke Tin, Ikuo Kobayashi, Yoichiro Horii

Abstract:

Today dairy farm experts and farmers have well recognized the importance of dairy cow Body Condition Score (BCS) since these scores can be used to optimize milk production, managing feeding system and as an indicator for abnormality in health even can be utilized to manage for having healthy calving times and process. In tradition, BCS measures are done by animal experts or trained technicians based on visual observations focusing on pin bones, pin, thurl and hook area, tail heads shapes, hook angles and short and long ribs. Since the traditional technique is very manual and subjective, the results can lead to different scores as well as not cost effective. Thus this paper proposes an algebraic geometric imaging approach for an automatic dairy cow BCS system. The proposed system consists of three functional modules. In the first module, significant landmarks or anatomical points from the cow image region are automatically extracted by using image processing techniques. To be specific, there are 23 anatomical points in the regions of ribs, hook bones, pin bone, thurl and tail head. These points are extracted by using block region based vertical and horizontal histogram methods. According to animal experts, the body condition scores depend mainly on the shape structure these regions. Therefore the second module will investigate some algebraic and geometric properties of the extracted anatomical points. Specifically, the second order polynomial regression is employed to a subset of anatomical points to produce the regression coefficients which are to be utilized as a part of feature vector in scoring process. In addition, the angles at thurl, pin, tail head and hook bone area are computed to extend the feature vector. Finally, in the third module, the extracted feature vectors are trained by using Markov Classification process to assign BCS for individual cows. Then the assigned BCS are revised by using multiple regression method to produce the final BCS score for dairy cows. In order to confirm the validity of proposed method, a monitoring video camera is set up at the milk rotary parlor to take top view images of cows. The proposed method extracts the key anatomical points and the corresponding feature vectors for each individual cows. Then the multiple regression calculator and Markov Chain Classification process are utilized to produce the estimated body condition score for each cow. The experimental results tested on 100 dairy cows from self-collected dataset and public bench mark dataset show very promising with accuracy of 98%.

Keywords: algebraic geometric imaging approach, body condition score, Markov classification, polynomial regression

Procedia PDF Downloads 158

Authors: Aline V. Arroteia, Gustavo G. Do Amaral, Simone Z. Kikuti, Norberto C. S. Moura, Silvio B. Melhado

Abstract:

Despite the significant advances made by the construction industry in recent years, the crystalized absence of integration between the design and construction phases is still an evident and costly problem in building construction. Globally, the construction industry has sought to adopt collaborative practices through new technologies to mitigate impacts of this fragmented process and to optimize its production. In this new technological business environment, professionals are required to develop new methodologies based on the notion of collaboration and integration of information throughout the building lifecycle. This scenario also represents the industry’s reality in developing nations, and the increasing need for overall efficiency has demanded new educational alternatives at the undergraduate and post-graduate levels. In countries like Brazil, it is the common understanding that Architecture, Engineering and Building Construction educational programs are being required to review the traditional design pedagogical processes to promote a comprehensive notion about integration and simultaneity between the phases of the project. In this context, the coherent inclusion of computation design to all segments of the educational programs of construction related professionals represents a significant research topic that, in fact, can affect the industry practice. Thus, the main objective of the present study was to comparatively measure the effectiveness of the Building Information Modeling courses offered by the University of Sao Paulo, the most important academic institution in Brazil, at the Schools of Architecture and Civil Engineering and the courses offered in well recognized BIM research institutions, such as the School of Design in the College of Architecture of the Georgia Institute of Technology, USA, to evaluate the dissemination of BIM knowledge amongst students in post graduate level. The qualitative research methodology was developed based on the analysis of the program and activities proposed by two BIM courses offered in each of the above-mentioned institutions, which were used as case studies. The data collection instruments were a student questionnaire, semi-structured interviews, participatory evaluation and pedagogical practices. The found results have detected a broad heterogeneity of the students regarding their professional experience, hours dedicated to training, and especially in relation to their general knowledge of BIM technology and its applications. The research observed that BIM is mostly understood as an operational tool and not as methodological project development approach, relevant to the whole building life cycle. The present research offers in its conclusion an assessment about the importance of the incorporation of BIM, with efficiency and in its totality, as a teaching method in undergraduate and graduate courses in the Brazilian architecture, engineering and building construction schools.

Keywords: building information modeling (BIM), BIM education, BIM process, design teaching

Procedia PDF Downloads 154

Authors: Liliana Gomez Cardona, Mary McComber, Kristyn Brown, Arlene Laliberté, Outi Linnaranta

Abstract:

The history of colonialism and more contemporary political issues have resulted in the exposure of Kanien'kehá:ka: non (Kanien'kehá:ka of Kahnawake) to challenging and even traumatic experiences. Colonization, religious missions, residential schools as well as economic and political marginalization are the factors that have challenged the wellbeing and mental health of these populations. In psychiatry, screening for mental illness is often done using questionnaires with which the patient is expected to respond to how often he/she has certain symptoms. However, the Indigenous view of mental wellbeing may not fit well with this approach. Moreover, biomedical treatments do not always meet the needs of Indigenous people because they do not understand the culture and traditional healing methods that persist in many communities. Assess whether the questionnaires used to measure symptoms, commonly used in psychiatry are appropriate and culturally safe for the Mohawk in Quebec. Identify the most appropriate tool to assess and promote wellbeing and follow the process necessary to improve its cultural sensitivity and safety for the Mohawk population. Qualitative, collaborative, and participatory action research project which respects First Nations protocols and the principles of ownership, control, access, and possession (OCAP). Data collection based on five focus groups with stakeholders working with these populations and members of Indigenous communities. Thematic analysis of the data collected and emerging through an advisory group that led a revision of the content, use, and cultural and conceptual relevance of the instruments. The questionnaires measuring psychiatric symptoms face significant limitations in the local indigenous context. We present the factors that make these tools not relevant among Mohawks. Although the scale called Growth and Empowerment Measure (GEM) was originally developed among Indigenous in Australia, the Mohawk in Quebec found that this tool comprehends critical aspects of their mental health and wellbeing more respectfully and accurately than questionnaires focused on measuring symptoms. We document the process of cultural adaptation of this tool which was supported by community members to create a culturally safe tool that helps in growth and empowerment. The cultural adaptation of the GEM provides valuable information about the factors affecting wellbeing and contributes to mental health promotion. This process improves mental health services by giving health care providers useful information about the Mohawk population and their clients. We believe that integrating this tool in interventions can help create a bridge to improve communication between the Indigenous cultural perspective of the patient and the biomedical view of health care providers. Further work is needed to confirm the clinical utility of this tool in psychological and psychiatric intervention along with social and community services.

Keywords: cultural adaptation, cultural safety, empowerment, Mohawks, mental health, Quebec

Procedia PDF Downloads 153

Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

Abstract:

Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

Procedia PDF Downloads 100

Authors: Anishur Rahman, Maria Areias, Diogo Simões, Ana Figeuiredo, Filipa Figueiredo, João Nunes

Abstract:

The circular economy (CE) has gained increased awareness among academics, businesses, and decision-makers as it stimulates resource circularity in the production and consumption systems. A large epistemological study has explored the principles of CE, but scant attention eagerly focused on analysing how CE is evaluated, consented to, and enforced using economic metabolism data and business intelligent framework. Economic metabolism involves the ongoing exchange of materials and energy within and across socio-economic systems and requires the assessment of vast amounts of data to provide quantitative analysis related to effective resource management. Limited concern, the present work has focused on the regional flows pilot region from Portugal. By addressing this gap, this study aims to promote eco-innovation and sustainability in the regions of Intermunicipal Communities Região de Coimbra, Viseu Dão Lafões and Beiras e Serra da Estrela, using this data to find precise synergies in terms of material flows and give companies a competitive advantage in form of valuable waste destinations, access to new resources and new markets, cost reduction and risk sharing benefits. In our work, emphasis on applying artificial intelligence (AI) and, more specifically, on implementing state-of-the-art deep learning algorithms is placed, contributing to construction a business intelligent approach. With the emergence of new approaches generally highlighted under the sub-heading of AI and machine learning (ML), the methods for statistical analysis of complex and uncertain production systems are facing significant changes. Therefore, various definitions of AI and its differences from traditional statistics are presented, and furthermore, ML is introduced to identify its place in data science and the differences in topics such as big data analytics and in production problems that using AI and ML are identified. A lifecycle-based approach is then taken to analyse the use of different methods in each phase to identify the most useful technologies and unifying attributes of AI in manufacturing. Most of macroeconomic metabolisms models are mainly direct to contexts of large metropolis, neglecting rural territories, so within this project, a dynamic decision support model coupled with artificial intelligence tools and information platforms will be developed, focused on the reality of these transition zones between the rural and urban. Thus, a real decision support tool is under development, which will surpass the scientific developments carried out to date and will allow to overcome imitations related to the availability and reliability of data.

Keywords: circular economy, artificial intelligence, economic metabolisms, machine learning

Procedia PDF Downloads 73

Authors: Mirjana Dokmanovic

Abstract:

The main topic of this paper is the analysis of the presence of gender stereotypes in the media content in the Republic of Serbia with respect to the state commitments to eliminate discrimination against women. The research methodology included the analysis of the media content of six daily newspapers and two magazines on the date of 28 December 2015 and the analysis of the reality TV show programs in 2015 from gender perspective. The methods of the research has also included a desk research and a qualitative analysis of the available data, statistics, policy papers, studies, and reports produced by the government, the Ministry of Culture and Information, the Regulatory Body for Electronic Media, the Press Council, the associations of media professionals, the independent human rights bodies, and civil society organizations (CSOs). As a State Signatory to the Convention on the Elimination of All Forms of Discrimination against Women, the Republic of Serbia has adopted numerous measures in this field, including the Law on Equality between Sexes and the national gender equality strategies. Special attention has been paid to eliminating gender stereotypes and prejudices in the media content and portraying of women. This practice has been forbidden by the Law on Electronic Media, the Law on Public Information and Media, the Law on Public Service Broadcasting and the Bylaw on the Protection of Human Rights in the Provision of Media Services. Despite these commitments, there has not been achieved progress regarding eliminating gender stereotypes in the media content. The research indicates that the media perpetuate traditional gender roles and patriarchal patterns. Female politicians, entrepreneurs, academics, scientists, and engineers have been very rarely portrayed in the media. On the other side, women are in their focus as celebrities, singers, and actresses. Women are underrepresented in the pages related to politics and economy, while they are mostly present in the cover stories related to show-business, health care, family and household matters. Women are three times more than men identified on the basis of their family status, as mothers, wives, daughters, etc. Hate speech, misogyny, and violence against women are often present in the reality TV shows. The abuse of women and their bodies in advertising is still widely present. The cases of domestic violence are still presented with sensationalism, although there has been achieved progress in portraying victims of domestic violence with respect and dignity. The issues related to gender equality and the position of the vulnerable groups of women, such as Roma women or rural women, are not visible in the media. This research, as well as warnings of women’s CSOs and independent human rights bodies, indicates the necessity to implement legal and policy measures in this field consistently and with due diligence. The aim of the paper is to contribute eliminating gender stereotypes in the media content and advancing gender equality.

Keywords: discrimination against women, gender roles, gender stereotypes, media, misogyny, portraying women in the media, prejudices against women, Republic of Serbia

Procedia PDF Downloads 204

Authors: Ikram Mohamed Eltayeb Elsiddig, Yacouba Amina Djamila, Amna El Hassan Hamad

Abstract:

Hyperglycemia and diabetes have been treated with several medicinal plants for a long time, meanwhile reduce associated side effects than the synthetic ones. Therefore, the search for more effective and safer anti-diabetic agents derived from plants has become an interest area of active research. A. sativum, belonging to the Liliaceae family is well known for its medicinal uses in African traditional medicine, it used for treating of many human diseases mainly diabetes, high cholesterol, and high blood pressure. The present study was carried out to investigate the anti-hyperglycemic effect of the extracts of A. sativum bulb growing in Sudan on glucose-loaded Wistar albino rats. A. sativum bulbs were collected from local vegetable market at Khourtoum/ Sudan in a fresh form, identified and authenticated by taxonomist, then dried, and extracted with solvents of increasing polarity: petroleum ether, chloroform, ethyl acetate and methanol by using Soxhlet apparatus. The effect of the extracts on glucose uptake was evaluated by using the isolated rats hemidiaphgrams after loading the fasting rats with glucose, and the anti-hyperglycemic effect was investigated on glucose-loaded Wistar albino rats. Their effects were compared to control rats administered with the vehicle and to a standard group administered with Metformin standard drug. The most active extract was analyzed chemically using GC-MS analysis compared to NIST library. The results showed significant anti-diabetic effect of extracts of A. sativum bulb growing in Sudan. Addition to the hypoglycemic activity of A. sativum extracts was found to be decreased with increase in the polarity of the extraction solvent; this may explain the less polarity of substance responsible for the activity and their concentration decreased with polarity increase. The petroleum ether extract possess anti-hyperglycemic activity more significant than the other extracts and the Metformin standard drug with p-value 0.000** of 400mg/kg at 1 hour, 2 hour and four hour; and p-value 0.019*, 0.015* and 0.010* of 200mg/kg at 1 hour, 2 hour and four hour respectively. The GC-MS analysis of petroleum ether extract, with highest anti -diabetes activity showed the presence of Methyl linolate (42.75%), Hexadecanoic acid, methyl ester (10.54%), Methyl α-linolenate (8.36%), Dotriacontane (6.83), Tetrapentacontane (6.33), Methyl 18-methylnonadecanoate (4.8), Phenol,2,2’-methylenebis[6-(1,1-dimethylethyl)-4-methyl] (3.25), Methyl 20-methyl-heneicosanoate (2.70), Pentatriacontane (2.13) and many other minor compounds. The most of these compounds are well known for their anti-diabetic activity. The study concluded that A. sativum bulbs extracts were found to enhanced the reuptake of glucose in the isolated rat hemidiaphragm and have antihyperglycemic effect when evaluated on glucose-loaded albino rats with petroleum ether extract activity more significant than the Metformin standard drug.

Keywords: Allium, anti-hyperglycemic, bulbs, sativum

Procedia PDF Downloads 169

Authors: Diego Santibañez Oyarce, Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

Abstract:

The advent of high-throughput sequencing technologies has revolutionized genomics, generating vast amounts of genetic data that challenge traditional bioinformatics methods. Machine learning addresses these challenges by leveraging computational power to identify patterns and extract information from large datasets. However, biological sequence data, being symbolic and non-numeric, must be converted into numerical formats for machine learning algorithms to process effectively. So far, some encoding methods, such as one-hot encoding or k-mers, have been explored. This work proposes additional approaches for encoding DNA sequences in order to compare them with existing techniques and determine if they can provide improvements or if current methods offer superior results. Data from the 16S rRNA gene, a universal marker, was used to analyze eight bacterial groups that are significant in the pulmonary environment and have clinical implications. The bacterial genes included in this analysis are Prevotella, Abiotrophia, Acidovorax, Streptococcus, Neisseria, Veillonella, Mycobacterium, and Megasphaera. These data were downloaded from the NCBI database in Genbank file format, followed by a syntactic analysis to selectively extract relevant information from each file. For data encoding, a sequence normalization process was carried out as the first step. From approximately 22,000 initial data points, a subset was generated for testing purposes. Specifically, 55 sequences from each bacterial group met the length criteria, resulting in an initial sample of approximately 440 sequences. The sequences were encoded using different methods, including one-hot encoding, k-mers, Fourier transform, and Wavelet transform. Various machine learning algorithms, such as support vector machines, random forests, and neural networks, were trained to evaluate these encoding methods. The performance of these models was assessed using multiple metrics, including the confusion matrix, ROC curve, and F1 Score, providing a comprehensive evaluation of their classification capabilities. The results show that accuracies between encoding methods vary by up to approximately 15%, with the Fourier transform obtaining the best results for the evaluated machine learning algorithms. These findings, supported by the detailed analysis using the confusion matrix, ROC curve, and F1 Score, provide valuable insights into the effectiveness of different encoding methods and machine learning algorithms for genomic data analysis, potentially improving the accuracy and efficiency of bacterial classification and related genomic studies.

Keywords: DNA encoding, machine learning, Fourier transform, Fourier transformation

Procedia PDF Downloads 23