Search results for: space-time resilience enhancement

Authors: Priyanka Bharti

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Decades ago designs were based on common sense and tradition, but after an enhancement in visualization technology and research, we are now able to comprehend the cognitive ability involved in the decoding of the visual information. However, many fields in visuals need intense research to deliver an efficient explanation for the events. Visuals are an information representation mode through images, symbols and graphics. It plays an impactful role in decision making by facilitating quick recognition, comprehension, and analysis of a situation. They enhance problem-solving capabilities by enabling the processing of more data without overloading the decision maker. As research proves that, visuals offer an improved learning environment by a factor of 400 compared to textual information. Visual information engages learners at a cognitive level and triggers the imagination, which enables the user to process the information faster (visuals are processed 60,000 times faster in the brain than text). Appropriate information, visualization, and its presentation are known to aid and intensify the decision-making process for the users. However, most literature discusses the role of visual aids in comprehension and decision making during normal conditions alone. Unlike emergencies, in a normal situation (e.g. our day to day life) users are neither exposed to stringent time constraints nor face the anxiety of survival and have sufficient time to evaluate various alternatives before making any decision. An emergency is an unexpected probably fatal real-life situation which may inflict serious ramifications on both human life and material possessions unless corrective measures are taken instantly. The situation demands the exposed user to negotiate in a dynamic and unstable scenario in the absence or lack of any preparation, but still, take swift and appropriate decisions to save life/lives or possessions. But the resulting stress and anxiety restricts cue sampling, decreases vigilance, reduces the capacity of working memory, causes premature closure in evaluating alternative options, and results in task shedding. Limited time, uncertainty, high stakes and vague goals negatively affect cognitive abilities to take appropriate decisions. More so, theory of natural decision making by experts has been understood with far more depth than that of an ordinary user. Therefore, in this study, the author aims to understand the role of visual aids in supporting rapid comprehension to take appropriate decisions during an emergency situation.

Keywords: cognition, visual, decision making, graphics, recognition

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Authors: Dmitry V. Pasynkov, Ivan A. Egoshin, Alexey A. Kolchev, Ivan V. Kliouchkin

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In most cases, typical cysts are easily recognized at ultrasonography. The specificity of this method for typical cysts reaches 98%, and it is usually considered as gold standard for typical cyst diagnosis. However, it is necessary to have all the following features to conclude the typical cyst: clear margin, the absence of internal echoes and dorsal acoustic enhancement. At the same time, not every breast cyst is typical. It is especially characteristic for protein-contained cysts that may have significant internal echoes. On the other hand, some solid lesions (predominantly malignant) may have cystic appearance and may be falsely accepted as cysts. Therefore we tried to develop the automatic method of cystic and solid breast lesions differentiation. Materials and methods. The input data were the ultrasonography digital images with the 256-gradations of gray color (Medison SA8000SE, Siemens X150, Esaote MyLab C). Identification of the lesion on these images was performed in two steps. On the first one, the region of interest (or contour of lesion) was searched and selected. Selection of such region is carried out using the sigmoid filter where the threshold is calculated according to the empirical distribution function of the image brightness and, if necessary, it was corrected according to the average brightness of the image points which have the highest gradient of brightness. At the second step, the identification of the selected region to one of lesion groups by its statistical characteristics of brightness distribution was made. The following characteristics were used: entropy, coefficients of the linear and polynomial regression, quantiles of different orders, an average gradient of brightness, etc. For determination of decisive criterion of belonging to one of lesion groups (cystic or solid) the training set of these characteristics of brightness distribution separately for benign and malignant lesions were received. To test our approach we used a set of 217 ultrasonic images of 107 cystic (including 53 atypical, difficult for bare eye differentiation) and 110 solid lesions. All lesions were cytologically and/or histologically confirmed. Visual identification was performed by trained specialist in breast ultrasonography. Results. Our system correctly distinguished all (107, 100%) typical cysts, 107 of 110 (97.3%) solid lesions and 50 of 53 (94.3%) atypical cysts. On the contrary, with the bare eye it was possible to identify correctly all (107, 100%) typical cysts, 96 of 110 (87.3%) solid lesions and 32 of 53 (60.4%) atypical cysts. Conclusion. Automatic approach significantly surpasses the visual assessment performed by trained specialist. The difference is especially large for atypical cysts and hypoechoic solid lesions with the clear margin. This data may have a clinical significance.

Keywords: breast cyst, breast solid lesion, differentiation, ultrasonography

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Authors: Nelomi Anandagoda, Leanne J. Eveson

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During the COVID-19 pandemic, the surge in in-patient admissions across the medical directorate of a district general hospital necessitated the implementation of an incident rota. Conscious of the impact on training and professional development, the idea of developing a virtual teaching programme was conceived. The programme initially aimed to provide junior doctors, specialist nurses, pharmacists, and allied healthcare professionals from medical specialties and those re-deployed from other specialties (e.g., ophthalmology, GP, surgery, psychiatry) the knowledge and skills to manage the deteriorating patient with COVID-19. The programme was later developed to incorporate the general internal medicine curriculum. To facilitate continuing medical education whilst maintaining social distancing during this period, a virtual platform was used to deliver teaching to junior doctors across two large district general hospitals and two community hospitals. Teaching sessions were recorded and uploaded to a common platform, providing a resource for participants to catch up on and re-watch teaching sessions, making strides towards reducing discrimination against the professional development of less than full-time trainees. Thus, creating a learning environment, which is inclusive and accessible to adult learners in a self-directed manner. The negative impact of the pandemic on the well-being of healthcare professionals is well documented. To support the multi-disciplinary team, the virtual teaching programme evolved to included sessions on well-being, resilience, and work-life balance. Providing teaching for learners across the multi-disciplinary team (MDT) has been an eye-opening experience. By challenging the concept that learners should only be taught within their own peer groups, the authors have fostered a greater appreciation of the strengths of the MDT and showcased the immense wealth of expertise available within the trust. The inclusive nature of the teaching and the ease of joining a virtual teaching session has facilitated the dissemination of knowledge across the MDT, thus improving patient care on the frontline. The weekly teaching programme has been running for over eight months, with ongoing engagement, interest, and participation. As described above, the teaching programme has evolved to accommodate the needs of its learners. It has received excellent feedback with an appreciation of its inclusive, multi-disciplinary, and holistic nature. The COVID-19 pandemic provided a catalyst to rapidly develop novel methods of working and training and widened access/exposure to the virtual technologies available to large organisations. By merging pedagogical expertise and technology, the authors have created an effective online learning environment. Although the authors do not propose to replace face-to-face teaching altogether, this model of virtual multidisciplinary team, cross-site teaching has proven to be a great leveler. It has made high-quality teaching accessible to learners of different confidence levels, grades, specialties, and working patterns.

Keywords: cross-site, cross-speciality, inter-disciplinary, multidisciplinary, virtual teaching

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Authors: Qinke Sun, Liang Zhou

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The ‘Dragon-Elephant Debate’ between China and India is an important manifestation of global multipolarity in the 21st century. The two rising powers have carried out economic reforms one after another in the interval of more than ten years, becoming the fastest growing developing country and emerging economy in the world. At the same time, the development differences between China and India have gradually attracted wide attention of scholars. Based on the continuous annual night light data (DMSP-OLS) from 1992 to 2012, this paper systematically compares and analyses the regional development differences between China and India by Gini coefficient, coefficient of variation, comprehensive night light index (CNLI) and hot spot analysis. The results show that: (1) China's overall expansion from 1992 to 2012 is 1.84 times that of India, in which China's change is 2.6 times and India's change is 2 times. The percentage of lights in unlighted areas in China dropped from 92% to 82%, while that in India from 71% to 50%. (2) China's new growth-oriented cities appear in Hohhot, Inner Mongolia, Ordos, and Urumqi in the west, and the declining cities are concentrated in Liaoning Province and Jilin Province in the northeast; India's new growth-oriented cities are concentrated in Chhattisgarh in the north, while the declining areas are distributed in Uttar Pradesh. (3) China's differences on different scales are lower than India's, and regional inequality of development is gradually narrowing. Gini coefficients at the regional and provincial levels have decreased from 0.29, 0.44 to 0.24 and 0.38, respectively, while regional inequality in India has slowly improved and regional differences are gradually widening, with Gini coefficients rising from 0.28 to 0.32. The provincial Gini coefficient decreased slightly from 0.64 to 0.63. (4) The spatial pattern of China's regional development is mainly east-west difference, which shows the difference between coastal and inland areas; while the spatial pattern of India's regional development is mainly north-south difference, but because the southern states are sea-dependent, it also reflects the coastal inland difference to a certain extent. (5) Beijing and Shanghai present a multi-core outward expansion model, with an average annual CNLI higher than 0.01, while New Delhi and Mumbai present the main core enhancement expansion model, with an average annual CNLI lower than 0.01, of which the average annual CNLI in Shanghai is about five times that in Mumbai.

Keywords: spatial pattern, spatial difference, DMSP-OLS, China, India

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Authors: E. Loffi Borghese

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In this comprehensive study, we delve into the intricate dynamics of the big tech oligopoly, focusing particularly on Apple as a case study. The core objective is to scrutinize the evolving relationship between a firm's commitment to positive social impact as its primary purpose and its resilience in the face of disruptive innovations within the big tech market. Our exploration begins with a theoretical framework, emphasizing the significance of distinguishing between corporate social responsibility and social impact as a primary purpose. Drawing on insights from Drumwright and Bartkus and Glassman, we underscore the transformative potential when a firm aligns its core business with a social mission, transcending mere side activities. Examining successful firms, such as Apple, we adopt Sinek's perspective on inspirational leadership and the "golden circle." This framework sheds light on why some organizations, like Apple, succeed in making positive social impact their primary purpose. Apple's early-stage life cycle is dissected, revealing a profound commitment to challenging the status quo and promoting simpler alternatives that resonate with its users' lives. The study then navigates through industry life cycles, drawing on Klepper's stages and Christensen's disruptive innovations. Apple's dominance in the big tech oligopoly is contrasted with companies like Harley Davidson and Polaroid, illustrating the consequences of failing to adapt to disruptive innovations. The data and methods employed encompass a qualitative approach, leveraging sources like ECB, Forbes, World in Data, and scientific articles. A secondary data analysis probes Apple's market evolution within the big tech oligopoly, emphasizing the shifts in market context and innovation trends that demand strategic adaptations. The subsequent sections scrutinize Apple's present innovation strategies, highlighting its diversified product portfolio and intensified focus on big data. We examine the implications of these shifts on Apple's capacity to maintain positive social impact as its primary purpose, pondering potential consequences on its brand perception. The study culminates in a reflection on the broader implications of the big tech oligopoly's dominance. It contemplates the diminishing competitiveness in the market and the potential sidelining of positive social impact as a competitive advantage. The expansion of tech firms into diverse sectors raises concerns about negative societal impacts, prompting a call for increased regulatory attention and awareness. In conclusion, this research serves as a catalyst for heightened awareness and discussion on the intricate interplay between firms' social impact goals, disruptive innovations, and the broader societal implications within the evolving landscape of the big tech oligopoly. Despite limitations, this study aims to stimulate further research, urging a conscious and responsible approach to shaping the future economic system.

Keywords: innovation trends, market dynamics, social impact, tech oligopoly

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Authors: Saif Alomari

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The paper aims at giving physical and mathematical descriptions of how the structural parameters of a resonant tunnelling diode (RTD) affect its output characteristics. Specifically, the value of the peak voltage, peak current, peak to valley current ratio (PVCR), and the difference between peak and valley voltages and currents ΔV and ΔI. A simulation-based approach using the Non-Equilibrium Green Function (NEGF) formalism based on the Silvaco ATLAS simulator is employed to conduct a series of designed experiments. These experiments show how the doping concentration in the emitter and collector layers, their thicknesses, and the width of the barriers and the quantum well influence the above-mentioned output characteristics. Each of these parameters was systematically changed while holding others fixed in each set of experiments. Factorial experiments are outside the scope of this work and will be investigated in future. The physics involved in the operation of the device is thoroughly explained and mathematical models based on curve fitting and underlaying physical principles are deduced. The models can be used to design devices with predictable output characteristics. These models were found absent in the literature that the author acanned. Results show that the doping concentration in each region has an effect on the value of the peak voltage. It is found that increasing the carrier concentration in the collector region shifts the peak to lower values, whereas increasing it in the emitter shifts the peak to higher values. In the collector’s case, the shift is either controlled by the built-in potential resulting from the concentration gradient or the conductivity enhancement in the collector. The shift to higher voltages is found to be also related to the location of the Fermi-level. The thicknesses of these layers play a role in the location of the peak as well. It was found that increasing the thickness of each region shifts the peak to higher values until a specific characteristic length, afterwards the peak becomes independent of the thickness. Finally, it is shown that the thickness of the barriers can be optimized for a particular well width to produce the highest PVCR or the highest ΔV and ΔI. The location of the peak voltage is important in optoelectronic applications of RTDs where the operating point of the device is usually the peak voltage point. Furthermore, the PVCR, ΔV, and ΔI are of great importance for building RTD-based oscillators as they affect the frequency response and output power of the oscillator.

Keywords: peak to valley ratio, peak voltage shift, resonant tunneling diodes, structural parameters

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Authors: Huayuan Lu, Chunfang Yang, Ma Zhu, Baojun Qi, Yaqiong Qiao, Jiangqian Xu

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Image geolocalization has great application prospects in fields such as autonomous driving and virtual/augmented reality. In practical application scenarios, the size of the image to be located is not fixed; it is impractical to train different networks for all possible sizes. When its size does not match the size of the input of the descriptor extraction model, existing image geolocalization methods usually directly scale or crop the image in some common ways. This will result in the loss of some information important to the geolocalization task, thus affecting the performance of the image geolocalization method. For example, excessive down-sampling can lead to blurred building contour, and inappropriate cropping can lead to the loss of key semantic elements, resulting in incorrect geolocation results. To address this problem, this paper designs a learnable image resizer and proposes an arbitrary-sized image geolocation method. (1) The designed learnable image resizer employs the self-attention mechanism to enhance the geometric features of the resized image. Firstly, it applies bilinear interpolation to the input image and its feature maps to obtain the initial resized image and the resized feature maps. Then, SKNet (selective kernel net) is used to approximate the best receptive field, thus keeping the geometric shapes as the original image. And SENet (squeeze and extraction net) is used to automatically select the feature maps with strong contour information, enhancing the geometric features. Finally, the enhanced geometric features are fused with the initial resized image, to obtain the final resized images. (2) The proposed image geolocalization method embeds the above image resizer as a fronting layer of the descriptor extraction network. It not only enables the network to be compatible with arbitrary-sized input images but also enhances the geometric features that are crucial to the image geolocalization task. Moreover, the triplet attention mechanism is added after the first convolutional layer of the backbone network to optimize the utilization of geometric elements extracted by the first convolutional layer. Finally, the local features extracted by the backbone network are aggregated to form image descriptors for image geolocalization. The proposed method was evaluated on several mainstream datasets, such as Pittsburgh30K, Tokyo24/7, and Places365. The results show that the proposed method has excellent size compatibility and compares favorably to recently mainstream geolocalization methods.

Keywords: image geolocalization, self-attention mechanism, image resizer, geometric feature

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Authors: Kaushal Kishore, Suman Mukhopadhyay, Susovan Das, Manashi Adhikary, Sandip Bhattacharyya

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In integrated steel plants, conveyor belts are widely used for transferring raw materials from one location to another. An output pin bush coupling attached with a conveyor transferring iron ore fines and fluxes failed after two years of service life. This led to an operational delay of approximately 15 hours. This study is focused on failure analysis of the coupling and recommending counter-measures to prevent any such failures in the future. Investigation consisted of careful visual observation, checking of operating parameters, stress calculation and analysis, macro and micro-fractography, material characterizations like chemical and metallurgical analysis and tensile and impact testings. The fracture occurred from an unusually sharp double step. There were multiple corrosion pits near the step that aggravated the situation. Inner contact surface of the coupling revealed differential abrasion that created a macroscopic difference in the height of the component. This pointed towards misalignment of the coupling beyond a threshold limit. In addition to these design and installation issues, material of the coupling did not meet the quality standards. These were made up of grey cast iron having graphite morphology intermediate between random distribution (Type A) and rosette pattern (Type B). This manifested as a marked reduction in impact toughness and tensile strength of the component. These findings corroborated well with the brittle mode of fracture that might have occurred during minor impact loading while loading of conveyor belt with raw materials from height. Simulated study was conducted to examine the effect of corrosion pits on tensile and impact toughness of grey cast iron. It was observed that pitting marginally reduced tensile strength and ductility. However, there was marked (up to 45%) reduction in impact toughness due to pitting. Thus, it became evident that failure of the coupling occurred due to combination of factors like inferior material, misalignment, poor step design and corrosion pitting. Recommendation for life enhancement of coupling included the use of tougher SG 500/7 grade, incorporation of proper fillet radius for the step, correction of alignment and application of corrosion resistant organic coating to prevent pitting.

Keywords: brittle fracture, cast iron, coupling, double step, pitting, simulated impact tests

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Authors: Vinay Kumar Vanjakula, Frank Adam, Nils Goseberg, Christian Windt

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When a structure is installed on a seabed, the presence of the structure will influence the flow field around it. The changes in the flow field include, formation of vortices, turbulence generation, waves or currents flow breaking and pressure differentials around the seabed sediment. These changes allow the local seabed sediment to be carried off and results in Scour (erosion). These are a threat to the structure's stability. In recent decades, rapid developments of research work and the knowledge of scour On fixed structures (bridges and Monopiles) in rivers and oceans has been carried out, and very limited research work on scour and liquefaction for gravity anchors, particularly for floating Tension Leg Platform (TLP) substructures. Due to its importance and need for enhancement of knowledge in scour and liquefaction around marine structures, the MarTERA funded a three-year (2020-2023) research program called NuLIMAS (Numerical Modeling of Liquefaction Around Marine Structures). It’s a group consists of European institutions (Universities, laboratories, and consulting companies). The objective of this study is to build a numerical model that replicates the reality, which indeed helps to simulate (predict) underwater flow conditions and to study different marine scour and Liquefication situations. It helps to design a heavyweight anchor for the TLP substructure and to minimize the time and expenditure on experiments. And also, the achieved results and the numerical model will be a basis for the development of other design and concepts For marine structures. The Computational Fluid Dynamics (CFD) numerical model will build in OpenFOAM. A conceptual design of heavyweight anchor for TLP substructure is designed through taking considerations of available state-of-the-art knowledge on scour and Liquefication concepts and references to Previous existing designs. These conceptual designs are validated with the available similar experimental benchmark data and also with the CFD numerical benchmark standards (CFD quality assurance study). CFD optimization model/tool is designed as to minimize the effect of fluid flow, scour, and Liquefication. A parameterized model is also developed to automate the calculation process to reduce user interactions. The parameters such as anchor Lowering Process, flow optimized outer contours, seabed interaction study, and FSSI (Fluid-Structure-Seabed Interactions) are investigated and used to carve the model as to build an optimized anchor.

Keywords: gravity anchor, liquefaction, scour, computational fluid dynamics

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Authors: Nikou Javadi, Uğur Dağlı

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The importance of culture and tourism in the attractiveness and competitiveness of the countries is central, and many regions are evidencing their cultural assets, tangible and intangible, as a means to create comparative advantages in tourism and produce a distinctive place in response to the pressures of globalization. Culture and tourism are interlinked because of their obvious combination and growth potential. Cultural tourism is a crucial global tourism market with fast growing. Regions can develop significant relations between culture and tourism to increase their attractiveness as places to visit, live and invest, increasing their competitiveness. Accordingly, having new and creative approach to historical areas as cultural value-based destinations can improve their conditions to promote tourism. Furthermore, in 21st century, media become the most important factor affecting the development of urban cities, including public places. As a result of the digital revolution, re-imaging and re-linkage public places by media are essential to create more interactions between public spaces and users, interaction media display, and urban screens, one of the most important defined media. This interaction can transform the urban space from being neglected to be more interactive space with users, especially the pedestrians. The paper focuses on The Walled City of Famagusta. As many other historic quarters elsewhere in the world, is in a process, of decay and deterioration, and its functionally distinctive areas are severely threatened by physical, functional, locational, and image obsolescence at varying degrees. So the focus on the future development of this area through tourism promotion can be an appropriate decision for the monument enhancement of the spatial quality in Walled City of Famagusta. In this paper, it is aimed to identify the effects of these new digital factors to transform public spaces especially in historic urban areas to promote creative tourism. Accordingly, two different analysis methods are used as well as a theoretical review. The first is case study on site and the second is Close ended questionnaire, test many concepts raised in this paper. The physical analysis on site carried out in order to evaluate the walled city restoration for touristic purpose. Besides, theoretical review is done in order to provide background to the subject and cleared Factors to attract tourists.

Keywords: historical areas, media façade, sustainable tourism, Walled city of Famagusta

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Authors: Eliza Torrigue, Efrelyn Iellamo

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Maternal death is one of the rising health issues in the Philippines. It is alarming to know that in every hour of each day, a mother gives birth to a child who may not live to see the next day. Statistics shows that intrapartum period and third stage of labor are the very crucial periods for the expectant mother, as well as the first six hours of life for the newborn. To address the issue, The Essential Intrapartum Newborn Care (EINC) was developed. Through this, Obstetric Delivery Room (OB-DR) Nurses shall be updated with the evidence-based maternal and newborn care to ensure patient safety, thus, reducing maternal and child mortality. This study aims to describe the compliance of hospitals, especially of OB-DR nurses, to the EINC Protocols. The researcher aims to link the profile variables of the respondents in terms of age, length of service and formal training to their compliance on the EINC Protocols. The outcome of the study is geared towards the development of appropriate training program for OB-DR Nurses assigned in the delivery room of the hospitals based on the study’s results to sustain the EINC standards. A descriptive correlational method was used. The sample consists of 75 Obstetric Delivery Room (OB-DR) Nurses from three government hospitals in the City of Manila namely, Ospital ng Maynila Medical Center, Tondo Medical Center, and Gat Andres Bonifacio Memorial Medical Center. Data were collected using an evaluative checklist. Ranking, weighted mean, Chi-square and Pearson’s R were used to analyze data. The level of compliance to the EINC Protocols by the respondents was evaluated with an overall mean score of 4.768 implying that OB-DR Nurses have a high regard in complying with the step by step procedure of the EINC. Furthermore, data shows that formal training on EINC have a significant relationship with OB-DR Nurses’ level of compliance during cord care, AMTSL, and immediate newborn care until the first ninety minutes to six hours of life. However, the respondents’ age and length of service do not have a significant relationship with the compliance of OB-DR Nurses on EINC Protocols. In the pursuit of decreasing the maternal mortality in the Philippines, EINC Protocols have been widely implemented in the country especially in the government hospitals where most of the deliveries happen. In this study, it was found out that OB-DR Nurses adhere and are highly compliant to the standards in order to assure that optimum level of care is delivered to the mother and newborn. Formal training on EINC, on the other hand, create the most impact on the compliance of nurses. It is therefore recommended that there must be a structured enhancement training program to plan, implement and evaluate the EINC protocols in these government hospitals.

Keywords: compliance, intrapartum, newborn care, nurses

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Authors: Jo Mitchell, Daniel Johnson

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MindMax is a digital community and learning platform built to maximise the wellbeing and resilience of AFL Players and Australian men. The MindMax application engages men, via their existing connection with sport and video games, in a range of wellbeing ideas, stories and actions, because we believe fit minds, kick goals. MindMax is an AFL Players Association led project, supported by a Movember Foundation grant, to improve the mental health of Australian males aged between 16-35 years. The key engagement and delivery strategy for the project was digital technology, sport (AFL) and video games, underpinned by evidenced based wellbeing science. The project commenced April 2015, and the expected completion date is March 2017. This paper describes the conceptual model underpinning product development, including progress, key learnings and challenges, as well as the research agenda. Evaluation of the MindMax project is a multi-pronged approach of qualitative and quantitative methods, including participatory design workshops, online reference groups, longitudinal survey methods, a naturalistic efficacy trial and evaluation of the social and economic return on investment. MindMax is focused on the wellness pathway and maximising our mind's capacity for fitness by sharing and promoting evidence-based actions that support this. A range of these ideas (from ACT, mindfulness and positive psychology) are already being implemented in AFL programs and services, mostly in face-to-face formats, with strong engagement by players. Player's experience features strongly as part of the product content. Wellbeing science is a discipline of psychology that explores what helps individuals and communities to flourish in life. Rather than ask questions about illness and poor functioning, wellbeing scientists and practitioners ask questions about wellness and optimal functioning. While illness and wellness are related, they operate as separate constructs and as such can be influenced through different pathways. The essential idea was to take the evidence-based wellbeing science around building psychological fitness to the places and spaces that men already frequent, namely sport and video games. There are 800 current senior AFL players, 5000+ past players, and 11 million boys and men that are interested in the lives of AFL Players; what they think and do to be their best both on and off field. AFL Players are also keen video gamers – using games as one way to de-stress, connect and build wellbeing. There are 9.5 million active gamers in Australia with 93% of households having a device for playing games. Video games in MindMax will be used as an engagement and learning tool. Gamers (including AFL players) can also share their personal experience of how games help build their mental fitness. Currently available games (i.e., we are not in the game creation business) will also be used to motivate and connect MindMax participants. The MindMax model is built with replication by other sport codes (e.g., Cricket) in mind. It is intended to not only support our current crop of athletes but also the community that surrounds them, so they can maximise their capacity for health and wellbeing.

Keywords: Australian football league, digital application, positive psychology, wellbeing

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Authors: Luminita Marin, Dalila Belei, Carmen Dumea

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Aggregation induced emission (AIE) is an intriguing optical phenomenon recently evidenced by Tang and his co-workers, for which aggregation works constructively in the improving of light emission. The AIE challenging phenomenon is quite opposite to the notorious aggregation caused quenching (ACQ) of light emission in the condensed phase, and comes in line with requirements of photonic and optoelectronic devices which need solid state emissive substrates. This paper reports a series of ten new aggregation induced emission (AIE) low molecular weight compounds based on triazole and pyridine-N-oxide heterocyclic units bonded by short flexible chains, obtained by a „click” chemistry reaction. The compounds present extremely weak luminescence in solution but strong light emission in solid state. To distinguish the influence of the crystallinity degree on the emission efficiency, the photophysical properties were explored by UV-vis and photoluminescence spectroscopy in solution, water suspension, amorphous and crystalline films. On the other hand, the compound morphology of the up mentioned states was monitored by dynamic light scattering, scanning electron microscopy, atomic force microscopy and polarized light microscopy methods. To further understand the structural design – photophysical properties relationship, single crystal X-ray diffraction on some understudy compounds was performed too. The UV-vis absorption spectra of the triazole water suspensions indicated a typical behaviour for nanoparticle formation, while the photoluminescence spectra revealed an emission intensity enhancement up to 921-fold higher of the crystalline films compared to solutions, clearly indicating an AIE behaviour. The compounds have the tendency to aggregate forming nano- and micro- crystals in shape of rose-like and fibres. The crystals integrity is kept due to the strong lateral intermolecular forces, while the absence of face-to-face forces explains the enhanced luminescence in crystalline state, in which the intramolecular rotations are restricted. The studied flexible triazoles draw attention to a new structural design in which small biologically friendly luminophore units are linked together by small flexible chains. This design enlarges the variety of the AIE luminogens to the flexible molecules, guiding further efforts in development of new AIE structures for appropriate applications, the biological ones being especially envisaged.

Keywords: aggregation induced emission, pyridine-N-oxide, triazole

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Authors: Achirawatt Tungsombatsanti, Toansakul Santiboon, Kamon Ponkham

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Strategies of the STEM education was aimed to prepare of an interdisciplinary and applied approach for the instructional of science, technology, engineering, and mathematics in an integrated students for enhancing engagement of their science skills to the Problem-Based Learning (PBL) method in Borabu School with a sample consists of 80 students in 2 classes at the 12th grade level of their learning achievements on electromagnetic issue. Research administrations were to separate on two different instructional model groups, the 40-experimental group was designed with the STEM instructional experimenting preparation and induction in a 40-student class and the controlling group using the PBL was designed to students identify what they already know, what they need to know, and how and where to access new information that may lead to the resolution of the problem in other class. The learning environment perceptions were obtained using the 35-item Physics Laboratory Environment Inventory (PLEI). Students’ creating attitude skills’ sustainable development toward physics were assessed with the Test Of Physics-Related Attitude (TOPRA) The term scaling was applied to the attempts to measure the attitude objectively with the TOPRA was used to assess students’ perceptions of their science attitude toward physics. Comparisons between pretest and posttest techniques were assessed students’ learning achievements on each their outcomes from each instructional model, differently. The results of these findings revealed that the efficiency of the PLB and the STEM based on criteria indicate that are higher than the standard level of the 80/80. Statistically, significant of students’ learning achievements to their later outcomes on the controlling and experimental physics class groups with the PLB and the STEM instructional designs were differentiated between groups at the .05 level, evidently. Comparisons between the averages mean scores of students’ responses to their instructional activities in the STEM education method are higher than the average mean scores of the PLB model. Associations between students’ perceptions of their physics classes to their attitudes toward physics, the predictive efficiency R2 values indicate that 77%, and 83% of the variances in students’ attitudes for the PLEI and the TOPRA in physics environment classes were attributable to their perceptions of their physics PLB and the STEM instructional design classes, consequently. An important of these findings was contributed to student understanding of scientific concepts, attitudes, and skills as evidence with STEM instructional ought to higher responding than PBL educational teaching. Statistically significant between students’ learning achievements were differentiated of pre and post assessments which overall on two instructional models.

Keywords: learning instructional managements, problem-based learning, STEM education, method, enhancement, students learning achievements, science attitude, physics classes

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Authors: Jing Jiang, Wenhuan XU, Lei Zhang, Shiyi Zhang, Tongli Wang

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Climate data quality significantly affects the reliability of ecological modeling. In the Asia Pacific (AP) region, low-quality climate data hinders ecological modeling. ClimateAP, a software developed in 2017, generates high-quality climate data for the AP region, benefiting researchers in forestry and agriculture. However, its adoption remains limited. This study aims to confirm the validity of biologically relevant variable data generated by ClimateAP during the normal climate period through comparison with the currently available gridded data. Climate data from 2,366 weather stations were used to evaluate the prediction accuracy of ClimateAP in comparison with the commonly used gridded data from WorldClim1.4. Univariate regressions were applied to 48 monthly biologically relevant variables, and the relationship between the observational data and the predictions made by ClimateAP and WorldClim was evaluated using Adjusted R-Squared and Root Mean Squared Error (RMSE). Locations were categorized into mountainous and flat landforms, considering elevation, slope, ruggedness, and Topographic Position Index. Univariate regressions were then applied to all biologically relevant variables for each landform category. Random Forest (RF) models were implemented for the climatic niche modeling of Cunninghamia lanceolata. A comparative analysis of the prediction accuracies of RF models constructed with distinct climate data sources was conducted to evaluate their relative effectiveness. Biologically relevant variables were obtained from three unpublished Chinese meteorological datasets. ClimateAPv3.0 and WorldClim predictions were obtained from weather station coordinates and WorldClim1.4 rasters, respectively, for the normal climate period of 1961-1990. Occurrence data for Cunninghamia lanceolata came from integrated biodiversity databases with 3,745 unique points. ClimateAP explains a minimum of 94.74%, 97.77%, 96.89%, and 94.40% of monthly maximum, minimum, average temperature, and precipitation variances, respectively. It outperforms WorldClim in 37 biologically relevant variables with lower RMSE values. ClimateAP achieves higher R-squared values for the 12 monthly minimum temperature variables and consistently higher Adjusted R-squared values across all landforms for precipitation. ClimateAP's temperature data yields lower Adjusted R-squared values than gridded data in high-elevation, rugged, and mountainous areas but achieves higher values in mid-slope drainages, plains, open slopes, and upper slopes. Using ClimateAP improves the prediction accuracy of tree occurrence from 77.90% to 82.77%. The biologically relevant climate data produced by ClimateAP is validated based on evaluations using observations from weather stations. The use of ClimateAP leads to an improvement in data quality, especially in non-mountainous regions. The results also suggest that using biologically relevant variables generated by ClimateAP can slightly enhance climatic niche modeling for tree species, offering a better understanding of tree species adaptation and resilience compared to using gridded data.

Keywords: climate data validation, data quality, Asia pacific climate, climatic niche modeling, random forest models, tree species

Procedia PDF Downloads 67

Authors: Daniel Manaye Kabtamu, Anteneh Wodaje Bayeh

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With the development and utilization of new energy technology, people’s demand for large-scale energy storage system has become increasingly urgent. Vanadium redox flow battery (VRFB) is one of the most promising technologies for grid-scale energy storage applications because of numerous attractive features, such as long cycle life, high safety, and flexible design. However, the relatively low energy efficiency and high production cost of the VRFB still limit its practical implementations. It is of great attention to enhance its energy efficiency and reduce its cost. One of the main components of VRFB that can impressively impact the efficiency and final cost is the electrode materials, which provide the reactions sites for redox couples (V₂₊/V³⁺ and VO²⁺/VO₂⁺). Graphite felt (GF) is a typical carbon-based material commonly employed as electrode for VRFB due to low-cost, good chemical and mechanical stability. However, pristine GF exhibits insufficient wettability, low specific surface area, and poor kinetics reversibility, leading to low energy efficiency of the battery. Therefore, it is crucial to further modify the GF electrode to improve its electrochemical performance towards VRFB by employing active electrocatalysts, such as less expensive metal oxides. This study successfully fabricates low-cost plate-like bismuth vanadate (BiVO₄) material through a simple one-step hydrothermal route, employed as an electrocatalyst to adorn the GF for use as the negative electrode in VRFB. The experimental results show that BiVO₄-3h exhibits the optimal electrocatalytic activity and reversibility for the vanadium redox couples among all samples. The energy efficiency of the VRFB cell assembled with BiVO₄-decorated GF as the negative electrode is found to be 75.42% at 100 mA cm−2, which is about 10.24% more efficient than that of the cell assembled with heat-treated graphite felt (HT-GF) electrode. The possible reasons for the activity enhancement can be ascribed to the existence of oxygen vacancies in the BiVO₄ lattice structure and the relatively high surface area of BiVO₄, which provide more active sites for facilitating the vanadium redox reactions. Furthermore, the BiVO₄-GF electrode obstructs the competitive irreversible hydrogen evolution reaction on the negative side of the cell, and it also has better wettability. Impressively, BiVO₄-GF as the negative electrode shows good stability over 100 cycles. Thus, BiVO₄-GF is a promising negative electrode candidate for practical VRFB applications.

Keywords: BiVO₄ electrocatalyst, electrochemical energy storage, graphite felt, vanadium redox flow battery

Procedia PDF Downloads 1571

Authors: Dibyendu Rakshit, Santosh K. Sarkar

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The study illustrates a comprehensive account of large-scale changes plankton community structure in relevance to water quality characteristics due to anthropogenic stresses, mainly concerned for Annual Gangasagar Festival (AGF) at the southern tip of Sagar Island of Indian Sundarban wetland for 3-year duration (2012-2014; n=36). This prograding, vulnerable and tide-dominated megadelta has been formed in the estuarine phase of the Hooghly Estuary infested by largest continuous tract of luxurious mangrove forest, enriched with high native flora and fauna. The sampling strategy was designed to characterize the changes in plankton community and water quality considering three diverse phases, namely during festival period (January) and its pre - (December) as well as post (February) events. Surface water samples were collected for estimation of different environmental variables as well as for phytoplankton and microzooplankton biodiversity measurement. The preservation and identification techniques of both biotic and abiotic parameters were carried out by standard chemical and biological methods. The intensive human activities lead to sharp ecological changes in the context of poor water quality index (WQI) due to high turbidity (14.02±2.34 NTU) coupled with low chlorophyll a (1.02±0.21 mg m-3) and dissolved oxygen (3.94±1.1 mg l-1), comparing to pre- and post-festival periods. Sharp reduction in abundance (4140 to 2997 cells l-1) and diversity (H′=2.72 to 1.33) of phytoplankton and microzooplankton tintinnids (450 to 328 ind l-1; H′=4.31 to 2.21) was very much pronounced. The small size tintinnid (average lorica length=29.4 µm; average LOD=10.5 µm) composed of Tintinnopsis minuta, T. lobiancoi, T. nucula, T. gracilis are predominant and reached some of the greatest abundances during the festival period. Results of ANOVA revealed a significant variation in different festival periods with phytoplankton (F= 1.77; p=0.006) and tintinnid abundance (F= 2.41; P=0.022). RELATE analyses revealed a significant correlation between the variations of planktonic communities with the environmental data (R= 0.107; p= 0.005). Three distinct groups were delineated from principal component analysis, in which a set of hydrological parameters acted as the causative factor(s) for maintaining diversity and distribution of the planktonic organisms. The pronounced adverse impact of anthropogenic stresses on plankton community could lead to environmental deterioration, disrupting the productivity of benthic and pelagic ecosystems as well as fishery potentialities which directly related to livelihood services. The festival can be considered as multiple drivers of changes in relevance to beach erosion, shoreline changes, pollution from discarded plastic and electronic wastes and destruction of natural habitats resulting loss of biodiversity. In addition, deterioration in water quality was also evident from immersion of idols, causing detrimental effects on aquatic biota. The authors strongly recommend for adopting integrated scientific and administrative strategies for resilience, sustainability and conservation of this megadelta.

Keywords: Gangasagar festival, phytoplankton, Sundarban megadelta, tintinnid

Procedia PDF Downloads 231

Authors: Alejandra G. Barbón, José Vila, Dania Vazquez

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This study seeks to contribute to the advancement of library and archival sciences in the areas of records management, knowledge organization, and information architecture, particularly focusing on the enhancement of bibliographical description through the incorporation of visual interactive designs aimed to enrich the library users’ experience. In an era of heightened awareness about the legacy of hiddenness across special and rare collections in libraries and archives, along with the need for inclusivity in academia, the University of Miami Libraries has embarked on an innovative project that intersects the realms of print culture, decolonization, and digital technology. This proposal presents an exciting initiative to revitalize the study of Artists’ Books collections by employing digital visual representations to decolonize bibliographic records of some of the most unique materials and foster a more holistic understanding of cultural heritage. Artists' Books, a dynamic and interdisciplinary art form, challenge conventional bibliographic classification systems, making them ripe for the exploration of alternative approaches. This project involves the creation of a digital platform that combines multimedia elements for digital representations, interactive information retrieval systems, innovative information architecture, trending bibliographic cataloging and metadata initiatives, and collaborative curation to transform how we engage with and understand these collections. By embracing the potential of technology, we aim to transcend traditional constraints and address the historical biases that have influenced bibliographic practices. In essence, this study showcases a groundbreaking endeavor at the University of Miami Libraries that seeks to not only enhance bibliographic practices but also confront the legacy of hiddenness across special and rare collections in libraries and archives while strengthening conventional bibliographic description. By embracing digital visualizations, we aim to provide new pathways for understanding Artists' Books collections in a manner that is more inclusive, dynamic, and forward-looking. This project exemplifies the University’s dedication to fostering critical engagement, embracing technological innovation, and promoting diverse and equitable classifications and representations of cultural heritage.

Keywords: decolonizing bibliographic cataloging frameworks, digital visualizations information architecture platforms, collaborative curation and inclusivity for records management, engagement and accessibility increasing interaction design and user experience

Procedia PDF Downloads 71

Authors: Jeh Patel, Chandrahas Paidi, Ahmed Hambaba

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Traditional methods for analyzing athlete movement often lack the detail and immediacy required for optimal training. This project aims to address this limitation by developing a Real-time human pose estimation system specifically designed to enhance athlete training across various sports. This system leverages the power of convolutional neural networks (CNNs) to provide a comprehensive and immediate analysis of an athlete’s movement patterns during training sessions. The core architecture utilizes dilated convolutions to capture crucial long-range dependencies within video frames. Combining this with the robust encoder-decoder architecture to further refine pose estimation accuracy. This capability is essential for precise joint localization across the diverse range of athletic poses encountered in different sports. Furthermore, by quantifying movement efficiency, power output, and range of motion, the system provides data-driven insights that can be used to optimize training programs. Pose estimation data analysis can also be used to develop personalized training plans that target specific weaknesses identified in an athlete’s movement patterns. To overcome the limitations posed by outdoor environments, the project employs strategies such as multi-camera configurations or depth sensing techniques. These approaches can enhance pose estimation accuracy in challenging lighting and occlusion scenarios, where pose estimation accuracy in challenging lighting and occlusion scenarios. A dataset is collected From the labs of Martin Luther King at San Jose State University. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing different poses, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced pose detection model and lays the groundwork for future innovations in assistive enhancement technologies.

Keywords: computer vision, deep learning, human pose estimation, U-NET, CNN

Procedia PDF Downloads 49

Authors: Shubham Gogri, Lucia Florescu

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Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

Procedia PDF Downloads 158

Authors: S. S. Sharma, P. R. Prabhu, K. Jagannath, Achutha Kini U., Gowri Shankar M. C.

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In present global scenario, aluminum alloys are coining the attention of many innovators as competing structural materials for automotive and space applications. Comparing to other challenging alloys, especially, 7xxx series aluminum alloys have been studied seriously because of their benefits such as moderate strength; better deforming characteristics, excellent chemical decay resistance, and affordable cost. 7075 Al-alloys have been used in the transportation industry for the fabrication of several types of automobile parts, such as wheel covers, panels and structures. It is expected that substitution of such aluminum alloys for steels will result in great improvements in energy economy, durability and recyclability. However, it is necessary to improve the strength and the formability levels at low temperatures in aluminium alloys for still better applications. Aluminum–Zinc–Magnesium with or without other wetting agent denoted as 7XXX series alloys are medium strength heat treatable alloys. Cu, Mn and Si are the other solute elements which contribute for the improvement in mechanical properties achievable by selecting and tailoring the suitable heat treatment process. On subjecting to suitable treatments like age hardening or cold deformation assisted heat treatments, known as low temperature thermomechanical treatments (LTMT) the challenging properties might be incorporated. T6 is the age hardening or precipitation hardening process with artificial aging cycle whereas T8 comprises of LTMT treatment aged artificially with X% cold deformation. When the cold deformation is provided after solution treatment, there is increase in hardness related properties such as wear resistance, yield and ultimate strength, toughness with the expense of ductility. During precipitation hardening both hardness and strength of the samples are increasing. Decreasing peak hardness value with increasing aging temperature is the well-known behavior of age hardenable alloys. The peak hardness value is further increasing when room temperature deformation is positively supported with age hardening known as thermomechanical treatment. Considering these aspects, it is intended to perform heat treatment and evaluate hardness, tensile strength, wear resistance and distribution pattern of reinforcement in the matrix. 2 to 2.5 and 3 to 3.5 times increase in hardness is reported in age hardening and LTMT treatments respectively as compared to as-cast composite. There was better distribution of reinforcements in the matrix, nearly two fold increase in strength levels and upto 5 times increase in wear resistance are also observed in the present study.

Keywords: reinforcement, precipitation, thermomechanical, dislocation, strain hardening

Procedia PDF Downloads 309

Authors: Ashima Sharma, Tapan K. Chaudhuri

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Human Serum Albumin (HSA) is one of the most demanded therapeutic protein with immense biotechnological applications. The current source of HSA is human blood plasma. Blood is a limited and an unsafe source as it possesses the risk of contamination by various blood derived pathogens. This issue led to exploitation of various hosts with the aim to obtain an alternative source for the production of the rHSA. But, till now no host has been proven to be effective commercially for rHSA production because of their respective limitations. Thus, there exists an indispensable need to promote non-animal derived rHSA production. Of all the host systems, Escherichia coli is one of the most convenient hosts which has contributed in the production of more than 30% of the FDA approved recombinant pharmaceuticals. E. coli grows rapidly and its culture reaches high cell density using inexpensive and simple substrates. The fermentation batch turnaround number for E. coli culture is 300 per year, which is far greater than any of the host systems available. Therefore, E. coli derived recombinant products have more economical potential as fermentation processes are cheaper compared to the other expression hosts available. Despite of all the mentioned advantages, E. coli had not been successfully adopted as a host for rHSA production. The major bottleneck in exploiting E. coli as a host for rHSA production was aggregation i.e. majority of the expressed recombinant protein was forming inclusion bodies (more than 90% of the total expressed rHSA) in the E. coli cytosol. Recovery of functional rHSA form inclusion body is not preferred because it is tedious, time consuming, laborious and expensive. Because of this limitation, E. coli host system was neglected for rHSA production for last few decades. Considering the advantages of E. coli as a host, the present work has targeted E. coli as an alternate host for rHSA production through resolving the major issue of inclusion body formation associated with it. In the present study, we have developed a novel and innovative method for enhanced soluble and functional production of rHSA in E.coli (~60% of the total expressed rHSA in the soluble fraction) through modulation of the cellular growth, folding and environmental parameters, thereby leading to significantly improved and enhanced -expression levels as well as the functional and soluble proportion of the total expressed rHSA in the cytosolic fraction of the host. Therefore, in the present case we have filled in the gap in the literature, by exploiting the most well studied host system Escherichia coli which is of low cost, fast growing, scalable and ‘yet neglected’, for the enhancement of functional production of HSA- one of the most crucial biomolecule for clinical and biotechnological applications.

Keywords: enhanced functional production of rHSA in E. coli, recombinant human serum albumin, recombinant protein expression, recombinant protein processing

Procedia PDF Downloads 345

Authors: Monalisa Halder, Amit K. Das, Ajit K. Meikap

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Polymer nanocomposites are very significant materials both in academia and industry for diverse potential applicability in electronics. Polymer plays the role of matrix element which has low density, flexibility, good mechanical strength and electrical properties. Use of nanosized multiferroic filler in the polymer matrix is suitable to achieve nanocomposites with enhanced magneto-dielectric effect and good mechanical properties both at the same time. Multiferroic terbium manganate (TbMnO₃) nanoparticles have been synthesized by sol-gel method using chloride precursors. Terbium manganate-polyvinyl alcohol (TbMnO₃-PVA) nanocomposite film has been prepared by solution casting method. Crystallite size of TbMnO₃ nanoparticle has been calculated to be ~ 40 nm from XRD analysis. Morphological study of the samples has been done by scanning electron microscopy and a well dispersion of the nanoparticles in the PVA matrix has been found. Thermogravimetric analysis (TGA) exhibits enhancement of thermal stability of the nanocomposite film with the inclusion of TbMnO₃ nanofiller in PVA matrix. The electrical transport properties of the nanocomposite film sample have been studied in the frequency range 20Hz - 2MHz at and above room temperature. The frequency dependent variation of ac conductivity follows universal dielectric response (UDR) obeying Jhonscher’s sublinear power law. Correlated barrier hopping (CBH) mechanism is the dominant charge transport mechanism with maximum barrier height 19 meV above room temperature. The variation of dielectric constant of the sample with frequency has been studied at different temperatures. Real part of dielectric constant at 1 KHz frequency at room temperature of the sample is found to be ~ 8 which is higher than that of the pure PVA film sample (~ 6). Dielectric constant decreases with the increase in frequency. Relaxation peaks have been observed in the variation of imaginary part of electric modulus with frequency. The relaxation peaks shift towards higher frequency as temperature increases probably due to the existence of interfacial polarization in the sample in presence of applied electric field. The current-voltage (I-V) characteristics of the nanocomposite film have been studied under ±40 V applied at different temperatures. I-V characteristic exhibits temperature dependent rectifying nature indicating the formation of Schottky barrier diode (SBD) with barrier height 23 meV. In conclusion, using multiferroic TbMnO₃ nanofiller in PVA matrix, enhanced thermal stability and electrical properties can be achieved.

Keywords: correlated barrier hopping, nanocomposite, schottky diode, TbMnO₃, TGA

Procedia PDF Downloads 126

Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

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Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

Procedia PDF Downloads 86

Authors: Miroslav Premrov, Andrej Štrukelj, Erika Kozem Šilih

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The utilization of prefabricated timber-wall elements with double glazing, called as double-skin façade element (DSF), represents an innovative structural approach in the context of new high-rise timber construction, simultaneously combining sustainable solutions with improved energy efficiency and living quality. In addition to the minimum energy needs of buildings, the design of modern buildings is also increasingly focused on the optimal indoor comfort, in particular on sufficient natural light indoors. An optimally energy-designed building with an optimal layout of glazed areas around the building envelope represents a great potential in modern timber construction. Usually, all these transparent façade elements, because of energy benefits, are primary asymmetrical oriented and if they are considered as non-resisting against a horizontal load impact, a strong torsion effects in the building can appear. The problem of structural stability against a strong horizontal load impact of such modern timber buildings especially increase in a case of high-rise structures where additional bracing elements have to be used. In such a case, special diagonal bracing systems or other bracing solutions with common timber wall elements have to be incorporated into the structure of the building to satisfy all prescribed resisting requirements given by the standards. However, all such structural solutions are usually not environmentally friendly and also not contribute to an improved living comfort, or they are not accepted by the architects at all. Consequently, it is a special need to develop innovative load-bearing timber-glass wall elements which are in the same time environmentally friendly, can increase internal comfort in the building, but are also load-bearing. The new developed load-bearing DSF elements can be a good answer on all these requirements. Timber-glass façade elements DSF wall elements consist of two transparent layers, thermal-insulated three-layered glass pane on the internal side and an additional single-layered glass pane on the external side of the wall. The both panes are separated by an air channel which can be of any dimensions and can have a significant influence on the thermal insulation or acoustic response of such a wall element. Most already published studies on DSF elements primarily deal only with energy and LCA solutions and do not address any structural problems. In previous studies according to experimental analysis and mathematical modeling it was already presented a possible benefit of such load-bearing DSF elements, especially comparing with previously developed load-bearing single-skin timber wall elements, but they were not applicate yet in any high-rise timber structure. Therefore, in the presented study specially selected 10-storey prefabricated timber building constructed in a cross-laminated timber (CLT) structural wall system is analyzed using the developed DSF elements in a sense to increase a structural lateral stability of the whole building. The results evidently highlight the importance the load-bearing DSF elements, as their incorporation can have a significant impact on the overall behavior of the structure through their influence on the stiffness properties. Taking these considerations into account is crucial to ensure compliance with seismic design codes and to improve the structural resilience of high-rise timber buildings.

Keywords: glass, high-rise buildings, numerical analysis, timber

Procedia PDF Downloads 44

Authors: Rajasekhar Reddy Poonuru, Anusha Parnem

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Purpose: To formulate proliposome powder of agomelatine, an antipsychotic drug, and to evaluate physicochemical, in vitro characters and effect of surface charge on ex vivo intestinal permeation. Methods: Film deposition technique was employed to develop proliposomal powders of agomelatin with varying molar ratios of lipid Hydro Soy PC L-α-phosphatidylcholine (HSPC) and cholesterol with fixed sum of drug. With the aim to derive free flowing and stable proliposome powder, fluid retention potential of various carriers was examined. Liposome formation and number of vesicles formed for per mm3 up on hydration, vesicle size, and entrapment efficiency was assessed to deduce an optimized formulation. Sodium cholate added to optimized formulation to induce surface charge on formed vesicles. Solid-state characterization (FTIR, DSC, and XRD) was performed with the intention to assess native crystalline and chemical behavior of drug. The in vitro dissolution test of optimized formulation along with pure drug was evaluated to estimate dissolution efficiency (DE) and relative dissolution rate (RDR). Effective permeability co-efficient (Peff(rat)) in rat and enhancement ratio (ER) of drug from formulation and pure drug dispersion were calculated from ex vivo permeation studies in rat ileum. Results: Proliposomal powder formulated with equimolar ratio of HSPC and cholesterol ensued in higher no. of vesicles (3.95) with 90% drug entrapment up on hydration. Neusilin UFL2 was elected as carrier because of its high fluid retention potential (4.5) and good flow properties. Proliposome powder exhibited augmentation in DE (60.3 ±3.34) and RDR (21.2±01.02) of agomelation over pure drug. Solid state characterization studies demonstrated the transformation of native crystalline form of drug to amorphous and/or molecular state, which was in correlation with results obtained from in vitro dissolution test. The elevated Peff(rat) of 46.5×10-4 cm/sec and ER of 2.65 of drug from charge induced proliposome formulation with respect to pure drug dispersion was assessed from ex vivo intestinal permeation studies executed in ileum of wistar rats. Conclusion: Improved physicochemical characters and ex vivo intestinal permeation of drug from charge induced proliposome powder with Neusilin UFL2 unravels the potentiality of this system in enhancing oral delivery of agomelatin.

Keywords: agomelatin, proliposome, sodium cholate, neusilin

Procedia PDF Downloads 134

Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes

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Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.

Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology

Procedia PDF Downloads 77

Authors: Hanna Mamo Ergando

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Climate change is already having a severe influence on agriculture, affecting crop yields, the nutritional content of main grains, and livestock productivity. Significant adaptation investments will be necessary to sustain existing yields and enhance production and food quality to fulfill demand. Climate-smart agriculture (CSA) provides numerous potentials in this regard, combining a focus on enhancing agricultural output and incomes while also strengthening resilience and responding to climate change. To improve agriculture production and productivity, the Ethiopian government has adopted and implemented a series of strategies, including the recent agricultural cluster farming that is practiced as an effort to change, improve, and transform subsistence farming to modern, productive, market-oriented, and climate-smart approach through farmers production cluster. Besides, greater attention and focus have been given to wheat production and productivity by the government, and wheat is the major crop grown in cluster farming. Therefore, the objective of this assessment was to examine various opportunities and challenges farmers face in a cluster farming system. A qualitative research approach was used to generate primary and secondary data. Respondents were chosen using the purposeful sampling technique. Accordingly, experts from the Federal Ministry of Agriculture, the Ethiopian Agricultural Transformation Institute, the Ethiopian Agricultural Research Institute, and the Ethiopian Environment Protection Authority were interviewed. The assessment result revealed that farming in clusters is an economically viable technique for sustaining small, resource-limited, and socially disadvantaged farmers' agricultural businesses. The method assists farmers in consolidating their products and delivering them in bulk to save on transportation costs while increasing income. Smallholders' negotiating power has improved as a result of cluster membership, as has knowledge and information spillover. The key challenges, on the other hand, were identified as a lack of timely provision of modern inputs, insufficient access to credit services, conflict of interest in crop selection, and a lack of output market for agro-processing firms. Furthermore, farmers in the cluster farming approach grow wheat year after year without crop rotation or diversification techniques. Mono-cropping has disadvantages because it raises the likelihood of disease and insect outbreaks. This practice may result in long-term consequences, including soil degradation, reduced biodiversity, and economic risk for farmers. Therefore, the government must devote more resources to addressing the issue of environmental sustainability. Farmers' access to complementary services that promote production and marketing efficiencies through infrastructure and institutional services has to be improved. In general, the assessment begins with some hint that leads to a deeper study into the efficiency of the strategy implementation, upholding existing policy, and scaling up good practices in a sustainable and environmentally viable manner.

Keywords: cluster farming, smallholder farmers, wheat, challenges, opportunities

Procedia PDF Downloads 216

Authors: Roberta Mugellesi Dow

Abstract:

As the climate crisis becomes unignorable, it is imperative that new services are developed addressing not only the needs of customers but also taking into account its impact on the environment. The Telecommunication and Integrated Application (TIA) Directorate of ESA is supporting the green transition with particular attention to the sustainable mobility.“Accelerating the shift to sustainable and smart mobility” is at the core of the European Green Deal strategy, which seeks a 90% reduction in related emissions by 2050 . Transforming the way that people and goods move is essential to increasing mobility while decreasing environmental impact, and transport must be considered holistically to produce a shared vision of green intermodal mobility. The use of space technologies, integrated with terrestrial technologies, is an enabler of smarter traffic management and increased transport efficiency for automated and connected multimodal mobility. Satellite connectivity, including future 5G networks, and digital technologies such as Digital Twin, AI, Machine Learning, and cloud-based applications are key enablers of sustainable mobility.SatCom is essential to ensure that connectivity is ubiquitously available, even in remote and rural areas, or in case of a failure, by the convergence of terrestrial and SatCom connectivity networks, This is especially crucial when there are risks of network failures or cyber-attacks targeting terrestrial communication. SatCom ensures communication network robustness and resilience. The combination of terrestrial and satellite communication networks is making possible intelligent and ubiquitous V2X systems and PNT services with significantly enhanced reliability and security, hyper-fast wireless access, as well as much seamless communication coverage. SatNav is essential in providing accurate tracking and tracing capabilities for automated vehicles and in guiding them to target locations. SatNav can also enable location-based services like car sharing applications, parking assistance, and fare payment. In addition to GNSS receivers, wireless connections, radar, lidar, and other installed sensors can enable automated vehicles to monitor surroundings, to ‘talk to each other’ and with infrastructure in real-time, and to respond to changes instantaneously. SatEO can be used to provide the maps required by the traffic management, as well as evaluate the conditions on the ground, assess changes and provide key data for monitoring and forecasting air pollution and other important parameters. Earth Observation derived data are used to provide meteorological information such as wind speed and direction, humidity, and others that must be considered into models contributing to traffic management services. The paper will provide examples of services and applications that have been developed aiming to identify innovative solutions and new business models that are allowed by new digital technologies engaging space and non space ecosystem together to deliver value and providing innovative, greener solutions in the mobility sector. Examples include Connected Autonomous Vehicles, electric vehicles, green logistics, and others. For the technologies relevant are the hybrid satcom and 5G providing ubiquitous coverage, IoT integration with non space technologies, as well as navigation, PNT technology, and other space data.

Keywords: sustainability, connectivity, mobility, satellites

Procedia PDF Downloads 132

Authors: Amit Gill, Lalith Wijerathne, Sebastian Poledna

Abstract:

This research presents the details of the implementation of high performance computing (HPC) extension of agent-based economic models (ABEMs) to simulate hundreds of millions of heterogeneous agents. ABEMs offer an alternative approach to study the economy as a dynamic system of interacting heterogeneous agents, and are gaining popularity as an alternative to standard economic models. Over the last decade, ABEMs have been increasingly applied to study various problems related to monetary policy, bank regulations, etc. When it comes to predicting the effects of local economic disruptions, like major disasters, changes in policies, exogenous shocks, etc., on the economy of the country or the region, it is pertinent to study how the disruptions cascade through every single economic entity affecting its decisions and interactions, and eventually affect the economic macro parameters. However, such simulations with hundreds of millions of agents are hindered by the lack of HPC enhanced ABEMs. In order to address this, a scalable Distributed Memory Parallel (DMP) implementation of ABEMs has been developed using message passing interface (MPI). A balanced distribution of computational load among MPI-processes (i.e. CPU cores) of computer clusters while taking all the interactions among agents into account is a major challenge for scalable DMP implementations. Economic agents interact on several random graphs, some of which are centralized (e.g. credit networks, etc.) whereas others are dense with random links (e.g. consumption markets, etc.). The agents are partitioned into mutually-exclusive subsets based on a representative employer-employee interaction graph, while the remaining graphs are made available at a minimum communication cost. To minimize the number of communications among MPI processes, real-life solutions like the introduction of recruitment agencies, sales outlets, local banks, and local branches of government in each MPI-process, are adopted. Efficient communication among MPI-processes is achieved by combining MPI derived data types with the new features of the latest MPI functions. Most of the communications are overlapped with computations, thereby significantly reducing the communication overhead. The current implementation is capable of simulating a small open economy. As an example, a single time step of a 1:1 scale model of Austria (i.e. about 9 million inhabitants and 600,000 businesses) can be simulated in 15 seconds. The implementation is further being enhanced to simulate 1:1 model of Euro-zone (i.e. 322 million agents).

Keywords: agent-based economic model, high performance computing, MPI-communication, MPI-process

Procedia PDF Downloads 127