Search results for: Zhang Cong

Authors: Zhang Xin

Abstract:

Barrier lakes are lakes formed by storing water in valleys, river valleys or riverbeds after being blocked by landslide, earthquake, debris flow, and other factors. They have great potential safety hazards. When the water is stored to a certain extent, it may burst in case of strong earthquake or rainstorm, and the lake water overflows, resulting in large-scale flood disasters. In order to ensure the safety of people's lives and property in the downstream, it is very necessary to monitor the barrier lake. However, it is very difficult and time-consuming to manually monitor the barrier lake in high altitude areas due to the harsh climate and steep terrain. With the development of earth observation technology, remote sensing monitoring has become one of the main ways to obtain observation data. Compared with a single satellite, multi-satellite remote sensing cooperative observation has more advantages; its spatial coverage is extensive, observation time is continuous, imaging types and bands are abundant, it can monitor and respond quickly to emergencies, and complete complex monitoring tasks. Monitoring with multi-temporal and multi-platform remote sensing satellites can obtain a variety of observation data in time, acquire key information such as water level and water storage capacity of the barrier lake, scientifically judge the situation of the barrier lake and reasonably predict its future development trend. In this study, The Sarez Lake, which formed on February 18, 1911, in the central part of the Pamir as a result of blockage of the Murgab River valley by a landslide triggered by a strong earthquake with magnitude of 7.4 and intensity of 9, is selected as the research area. Since the formation of Lake Sarez, it has aroused widespread international concern about its safety. At present, the use of mechanical methods in the international analysis of the safety of Lake Sarez is more common, and remote sensing methods are seldom used. This study combines remote sensing data with field observation data, and uses the 'space-air-ground' joint observation technology to study the changes in water level and water storage capacity of Lake Sarez in recent decades, and evaluate its safety. The situation of the collapse is simulated, and the future development trend of Lake Sarez is predicted. The results show that: 1) in recent decades, the water level of Lake Sarez has not changed much and remained at a stable level; 2) unless there is a strong earthquake or heavy rain, it is less likely that the Lake Sarez will be broken under normal conditions, 3) lake Sarez will remain stable in the future, but it is necessary to establish an early warning system in the Lake Sarez area for remote sensing of the area, 4) the coordinative remote sensing observation technology is feasible for the high altitude barrier lake of Sarez.

Keywords: coordinative observation, disaster, remote sensing, geographic information system, GIS

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Authors: Rania S. Hussein

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This research mainly focuses on examining engagement in social media brand communities. Engagement in social media has become a main focus in literature affirming that the role of social media in our daily lives is growing. (Akman and Mishra, 2017;Prado-Gascó et al., 2017). Social media has also become a key medium for brand communication and brand building relationships(Frimpong and McLean,2018;Dimitriu and Guesalaga, 2017). Engagement on social media has become a main focus of many researchers who tried to understand this concept further and draw a link between engagement and various social media activities (Cvijikj and Michahelles;2013), Andre,2015; Wang et al., 2015). According to Felix et al. (2017), the internet and social media have provided better digital resources to improve brand loyalty and customer interactions, thus leading to social media engagement within brand communities. The aim of this research is to highlight the importance of social media and why it is important to maintain engagement within social media. While the term ‘engagement’ is widely used in scholarly literature, there isn’t a common consensus about what the term exactly entails, according to Kidd, (2011). On one hand, it was seen as something that includes factors such as participation, activation, empowerment, devotion, trust, and productivity (Zhang et al, andBenyoucef, M. (2016), ). Other scholars held different viewpoints. For example, Lim et al. (2015) has chosen to break down engagement into three types: operational engagement, emotional engagement, and relational engagement. Chandler and Lusch (2015) further studied engagement as a means to measure commitment to a brand. Fernandes&Remelhe (2016) had a more technical view, measuring engagement through comments, following, subscribing, sharing, enjoying, writing, etc., in the social media context. ustomer engagement has become a research focus for understanding how consumer relationships are developed, retained, and improved within a digital context. Based on previous literature, it is evident that many customer engagement related studies are limited to the interaction between firms and consumers on social media. There is a clear gap in the literature regarding consumer-to-consumer interaction and user-generated content and its significance. While some researchers, such as Alversia et al. (2016), touched upon the importance of customer-based engagement, a gap still remains: there is no consistent and well-tested method for defining the factors that affect consumer interaction. Moreover, few scholarly research papers such as (Case, 2019; Riley, 2020;Habibi, 2014) provided to assist businesses understand their customers' interaction habits as well as the best ways to develop customer loyalty. Additionally, the majority of research on brand pages concentrated on the drivers of Consumer engagement, with just a few studies example, Lamberton, Cc(2016), Poorrezaei, (2016). (Jayasingh, 2019), looking into the implications. This study focuses on understanding the concept of engagement and its importance, specifically engagement within social media brand communities. It examines drivers as well as consequences of engagement, including brand knowledge, brand trust, entertainment, and brand page interactivity. Brand engagement is also expected to affect brand loyalty and word of the mouth.

Keywords: engagement, social media, brand communities, drivers

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Authors: Shiyi He, Yan Xia, Xiaoping Ouyang, Liang Chen, Zhongbing Zhang, Jinlu Ruan

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As the key system of the spacecraft, various propelling system have been developing rapidly, including ion thrust, laser thrust, solar sail and other micro-thrusters. However, there still are some shortages in these systems. The ion thruster requires the high-voltage or magnetic field to accelerate, resulting in extra system, heavy quantity and large volume. The laser thrust now is mostly ground-based and providing pulse thrust, restraint by the station distribution and the capacity of laser. The thrust direction of solar sail is limited to its relative position with the Sun, so it is hard to propel toward the Sun or adjust in the shadow.In this paper, a novel nuclear thruster based on alpha decay and spontaneous fission is proposed and the principle of this radiation-thrust with alpha particle has been expounded. Radioactive materials with different released energy, such as 210Po with 5.4MeV and 238Pu with 5.29MeV, attached to a metal film will provides various thrust among 0.02-5uN/cm2. With this repulsive force, radiation is able to be a power source. With the advantages of low system quantity, high accuracy and long active time, the radiation thrust is promising in the field of space debris removal, orbit control of nano-satellite array and deep space exploration. To do further study, a formula lead to the amplitude and direction of thrust by the released energy and decay coefficient is set up. With the initial formula, the alpha radiation elements with the half life period longer than a hundred days are calculated and listed. As the alpha particles emit continuously, the residual charge in metal film grows and affects the emitting energy distribution of alpha particles. With the residual charge or extra electromagnetic field, the emitting of alpha particles performs differently and is analyzed in this paper. Furthermore, three more complex situations are discussed. Radiation element generating alpha particles with several energies in different intensity, mixture of various radiation elements, and cascaded alpha decay are studied respectively. In combined way, it is more efficient and flexible to adjust the thrust amplitude. The propelling model of the spontaneous fission is similar with the one of alpha decay, which has a more complex angular distribution. A new quasi-sphere space propelling system based on the radiation-thrust has been introduced, as well as the collecting and processing system of excess charge and reaction heat. The energy and spatial angular distribution of emitting alpha particles on unit area and certain propelling system have been studied. As the alpha particles are easily losing energy and self-absorb, the distribution is not the simple stacking of each nuclide. With the change of the amplitude and angel of radiation-thrust, orbital variation strategy on space debris removal is shown and optimized.

Keywords: alpha decay, angular distribution, emitting energy, orbital variation, radiation-thruster

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Authors: Zhihao Peng, Qiong Zhang, Xiyao Li, Yongzhen Peng

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Nowadays, conventional nitrogen removal process (nitrification and denitrification) was adopted in most wastewater treatment plants, but many problems have occurred, such as: high aeration energy consumption, extra carbon sources dosage and high sludge treatment costs. The emergence of anammox has bring about the great revolution to the nitrogen removal technology, and only the ammonia and nitrite were required to remove nitrogen autotrophically, no demand for aeration and sludge treatment. However, there existed many challenges in anammox applications: difficulty of biomass retention, insufficiency of nitrite substrate, damage from complex organic etc. Much effort was put into the research in overcoming the above challenges, and the payment was rewarded. It was also imperative to establish an innovative process that can settle the above problems synchronously, after all any obstacle above mentioned can cause the collapse of anammox system. Therefore, in this study, a two-stage process was established that the sequencing batch reactor (SBR) and upflow anaerobic sludge blanket (UASB) were used in the pre-stage and post-stage, respectively. The domestic wastewater entered into the SBR first and went through anaerobic/aerobic/anoxic (An/O/A) mode, and the draining at the aerobic end of SBR was mixed with domestic wastewater, the mixture then entering to the UASB. In the long term, organic and nitrogen removal performance was evaluated. All along the operation, most COD was removed in pre-stage (COD removal efficiency > 64.1%), including some macromolecular organic matter, like: tryptophan, tyrosinase and fulvic acid, which could weaken the damage of organic matter to anammox. And the An/O/A operating mode of SBR was beneficial to the achievement and maintenance of partial nitrification (PN). Hence, sufficient and steady nitrite supply was another favorable condition to anammox enhancement. Besides, the flexible mixing ratio helped to gain a substrate ratio appropriate to anammox (1.32-1.46), which further enhance the anammox. Further, the UASB was used and gas recirculation strategy was adopted in the post-stage, aiming to achieve granulation by the selection pressure. As expected, the granules formed rapidly during 38 days, which increased from 153.3 to 354.3 μm. Based on bioactivity and gene measurement, the anammox metabolism and abundance level rose evidently, by 2.35 mgN/gVss·h and 5.3 x109. The anammox bacteria mainly distributed in the large granules (>1000 μm), while the biomass in the flocs (<200 μm) and microgranules (200-500 μm) barely displayed anammox bioactivity. Enhanced anammox promoted the advanced autotrophic nitrogen removal, which increased from 71.9% to 93.4%, even when the temperature was only 12.9 ℃. Therefore, it was feasible to enhance anammox in the multiple favorable conditions created, and the strategy extended the application of anammox to the full-scale mainstream, enhanced the understanding of anammox in the aspects of culturing conditions.

Keywords: anammox, granules, nitrite accumulation, nitrogen removal efficiency

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Authors: Dian Zhang, Brendan Heery, Maria O’Neill, Ciprian Briciu-Burghina, Noel E. O’Connor, Fiona Regan

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Recent developments in sensors, wireless data communication and the cloud computing have brought the sensor web to a whole new generation. The introduction of the concept of ‘Internet of Thing (IoT)’ has brought the sensor research into a new level, which involves the developing of long lasting, low cost, environment friendly and smart sensors; new wireless data communication technologies; big data analytics algorithms and cloud based solutions that are tailored to large scale smart sensor network. The next generation of smart sensor network consists of several layers: physical layer, where all the smart sensors resident and data pre-processes occur, either on the sensor itself or field gateway; data transmission layer, where data and instructions exchanges happen; the data process layer, where meaningful information is extracted and organized from the pre-process data stream. There are many definitions of smart sensor, however, to summarize all these definitions, a smart sensor must be Intelligent and Adaptable. In future large scale sensor network, collected data are far too large for traditional applications to send, store or process. The sensor unit must be intelligent that pre-processes collected data locally on board (this process may occur on field gateway depends on the sensor network structure). In this case study, three smart sensing methods, corresponding to simple thresholding, statistical model and machine learning based MoPBAS method, are introduced and their strength and weakness are discussed as an introduction to the smart sensing concept. Data fusion, the integration of data and knowledge from multiple sources, are key components of the next generation smart sensor network. For example, in the water level monitoring system, weather forecast can be extracted from external sources and if a heavy rainfall is expected, the server can send instructions to the sensor notes to, for instance, increase the sampling rate or switch on the sleeping mode vice versa. In this paper, we describe the deployment of 11 affordable water level sensors in the Dublin catchment. The objective of this paper is to use the deployed river level sensor network at the Dodder catchment in Dublin, Ireland as a case study to give a vision of the next generation of a smart sensor network for flood monitoring to assist agencies in making decisions about deploying resources in the case of a severe flood event. Some of the deployed sensors are located alongside traditional water level sensors for validation purposes. Using the 11 deployed river level sensors in a network as a case study, a vision of the next generation of smart sensor network is proposed. Each key component of the smart sensor network is discussed, which hopefully inspires the researchers who are working in the sensor research domain.

Keywords: smart sensing, internet of things, water level sensor, flooding

Procedia PDF Downloads 381

Authors: Rongrong Liu, Li Wang, Hui Xu, Jianpei Fang, Sixi Liu, Xiaolin Yin, Junbin Liang, Gaohui Yan, Yaoyun Li, Yali Zhou, Xinyu Li, Yue Li, Lei Shi, Yongrong Lai, Junjiu Huang, Xinhua Zhang

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Background: Beta-Thalassemia is caused by reduced (β+) or absent (β0) synthesis of the β-globin chains of hemoglobin. Transfusions and oral iron chelation therapy have improved the quality of life for patients with Transfusion-Dependent thalassemia (TDT). Recent advances in genome editing platforms of CRISPR-Cas9 have paved the way for induction of HbF by reactivating expression of γ-chain.Aims: We performed CRISPR-Cas9-mediated genome editing of hematopoietic stem cells to mutate HBG1/HBG2 promoter sequence, thereby representing a naturally occurring HPFH-liked mutation, producing RM-001. Here, we present an initial assessment of safety and efficacy of RM-001 in patients with TDT. Methods: Patients (6–35 y of age) with TDT receiving packed red blood cell (pRBC) transfusions of ≥100 mL/kg/y or ≥10 units/y in the previous 2 y were eligible. CD34+ cells were edited with CRISPR-Cas9 using a guide RNA specific for the binding site of BCL11A on the HBG1/2 promoter. Prior to RM-001 product infusion (day 0), patients received myeloablative conditioning with Busulfan from day-7 to day-4. Patients were monitored for AEs Hb expression.Results: Data cut as of 28 Feb 2024, 16 TDT patients have been treated with RM-001 and followed ≥3 months. 5 of these 16 patients had finished their 24 months follow up. Eleven patients have β0/β0 genotype and five patients have β0/β+ genotype. In addition to β-thalassemia, two patients had α- deletion with the genotype of --/αα. Efficacy:All patients received a single dose intravenous infusion of RM-001 cells. 5 of them had been followed 24 months or longer. All patients achieved transfusion-independent (TI, total Hb continued ≥ 9g/dL) (Figure1). Patients demonstrated sustained and clinically meaningful increases in HbF levels since 4 month post-RM-001 infusion (Figure.2). Total hemoglobin in all patients was stable at 10-12g/dL during the follow-up period. Safety:The adverse events observed after RM-001 infusion were consistent with those that are typical of Busulfan-based myeloablation. The allelic editing analysis at 6-month visit showed that the on-target allelic editing frequency in bone marrow cells was 73.44% (64.65% to 84.6%, n=13).Summary/Conclusion: This interim analysis, in which all the 19 patients age from 7.9 to 25yo met the success criteria for the trial with respect to transfusion independence, showed that autologous HBG1/2 promoter-modified CD34+ HSPCs gene therapy resulted in an adequate amount of HbF as early as 2 months after infusion led to near-normal hemoglobin levels, remained transfusion-free through the reported period without product related SAE. After RM-001 infusion, high levels of HbF proportion and on-target editing in bone marrow cells were maintained. Submitted on behalf of the RM-001 Investigators.

Keywords: thalassemian, genetherapy, CRISPR/Cas9, HbF

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Authors: Chang Liu, Hanwen Zhang, Vikash Sharma, Don Eliseo Lucerno-Prisno III, Emmanuel Yujuico, Maulik Chokshi, Prashanthi Krishnakumar, Bach Xuan Tran, Giang Thu Vu, Kamilla Anna Pinter, Shenglan Tang

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Background and Aims: Globally, many health systems focus on hospital-based healthcare models targeting acute care and disease treatment, which are not effective in addressing the challenges of ageing populations, chronic conditions, multi-morbidities, and increasingly unhealthy lifestyles. Recently, integrated care programs on chronic diseases have been developed, piloted, and implemented to meet such challenges. However, integrated care programs in the Asia-Pacific region vary in the levels of integration from linkage to coordination to full integration. This study aims to identify and analyze existing cases of integrated care in the Asia-Pacific region and identify the facilitators and barriers in order to improve existing cases and inform future cases. Methods: The study is a comparative study, with a combination approach of desk-based research and key informant interviews. The selected countries included in this study represent a good mix of lower-middle income countries (the Philippines, India, Vietnam, and Fiji), upper-middle income country (China), and high-income country (Singapore) in the Asia-Pacific region. Existing integrated care programs were identified through the scoping review approach. Trigger, history, general design, beneficiaries, and objectors were summarized with barriers and facilitators of integrated care based on key informant interviews. Representative case(s) in each country were selected and comprehensively analyzed through deep-dive case studies. Results: A total of 87 existing integrated care programs on chronic diseases were found in all countries, with 44 in China, 21 in Singapore, 12 in India, 5 in Vietnam, 4 in the Philippines, and 1 in Fiji. 9 representative cases of integrated care were selected for in-depth description and analysis, with 2 in China, the Philippines, and Vietnam, and 1 in Singapore, India, and Fiji. Population aging and the rising chronic disease burden have been identified as key drivers for almost all the six countries. Among the six countries, Singapore has the longest history of integrated care, followed by Fiji, the Philippines, and China, while India and Vietnam have a shorter history of integrated care. Incentives, technologies, education, and performance evaluation would be crucial for developing strategies for implementing future programs and improve already existing programs. Conclusion: Integrated care is important for addressing challenges surrounding the delivery of long-term care. To date, there is an increasing trend of integrated care programs on chronic diseases in the Asia-Pacific region, and all six countries in our study set integrated care as a direction for their health systems transformation.

Keywords: integrated healthcare, integrated care delivery, chronic diseases, Asia-Pacific region

Procedia PDF Downloads 134

Authors: Jie Lin, Yiwen Pan, Li Zhang, Zhangyong Xia

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Atherosclerosis is a chronic inflammatory disease characterized by the accumulation of lipids, immune cells, and extracellular matrix in the arterial walls. This pathological process can lead to the formation of plaques that can obstruct blood flow and trigger various cardiovascular diseases such as heart attack and stroke. The underlying molecular mechanisms still remain unclear, although many studies revealed the dysfunction of endothelial cells, recruitment and activation of monocytes and macrophages, and the production of pro-inflammatory cytokines and chemokines in atherosclerosis. This study aimed to identify hub genes involved in the progression of atherosclerosis and to analyze their biological function in silico, thereby enhancing our understanding of the disease’s molecular mechanisms. Through the analysis of microarray data, we examined the gene expression in media and neo-intima from plaques, as well as distant macroscopically intact tissue, across a cohort of 32 hypertensive patients. Initially, 112 differentially expressed genes (DEGs) were identified. Subsequent immune infiltration analysis indicated a predominant presence of 27 immune cell types in the atherosclerosis group, particularly noting an increase in monocytes and macrophages. In the Weighted gene co-expression network analysis (WGCNA), 10 modules with a minimum of 30 genes were defined as key modules, with blue, dark, Oliver green and sky-blue modules being the most significant. These modules corresponded respectively to monocyte, activated B cell, and activated CD4 T cell gene patterns, revealing a strong morphological-genetic correlation. From these three gene patterns (modules morphology), a total of 2509 key genes (Gene Significance >0.2, module membership>0.8) were extracted. Six hub genes (CD36, DPP4, HMOX1, PLA2G7, PLN2, and ACADL) were then identified by intersecting 2509 key genes, 102 DEGs with lipid-related genes from the Genecard database. The bio-functional analysis of six hub genes was estimated by a robust classifier with an area under the curve (AUC) of 0.873 in the ROC plot, indicating excellent efficacy in differentiating between the disease and control group. Moreover, PCA visualization demonstrated clear separation between the groups based on these six hub genes, suggesting their potential utility as classification features in predictive models. Protein-protein interaction (PPI) analysis highlighted DPP4 as the most interconnected gene. Within the constructed key gene-drug network, 462 drugs were predicted, with ursodeoxycholic acid (UDCA) being identified as a potential therapeutic agent for modulating DPP4 expression. In summary, our study identified critical hub genes implicated in the progression of atherosclerosis through comprehensive bioinformatic analyses. These findings not only advance our understanding of the disease but also pave the way for applying similar analytical frameworks and predictive models to other diseases, thereby broadening the potential for clinical applications and therapeutic discoveries.

Keywords: atherosclerosis, hub genes, drug prediction, bioinformatics

Procedia PDF Downloads 66

Authors: Xiaoying Zhang

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Forest school – an outdoor educational experience that is undertaken in an outdoor environment with trees – becomes an emerging field of early childhood education recently. In China, the benefits of natural outdoor education to children and young people’s wellness have raised attention. Although different types of outdoor-based activities have been involved in some pre-school of China, few study and practice have been conducted in terms of the notion of forest school. To comprehend the impact of forest school for children and young people, this study aims to systematically review articles on the topic of forest school in preschool education from an ecological perspective, i.e. from individual level (e.g., behavior and mental health) to microsystem level (e.g., the relationship between teachers and children) to ecosystem level. Based on PRISMA framework flow, using the key words of “Forest School” and “Early Childhood Education” for searching in Web-of-science database, a total of 33 articles were identified. Sample participants of 13 studies were not preschool children, five studies were not on forest school theme, and two literature review articles were excluded for further analysis. Finally, 13 articles were eligible for thematic analysis. According to Bronfenbrenner's ecological systems theory, there are some fingdings, on the individual level, current forest school studies are concerned about the children behavioral experience in forest school, how these experience may relate to their achievement or to develop children’s wellbeing/wellness, and how this type of learning experience may enhance children’s self-awareness on risk and safety issues. On the microsystem/mesosystem level, this review indicated that pedagogical development for forest school, risk perception from teachers and parents, social development between peers, and adult’s role in the participation of forest school were concerned, explored and discussed most frequently. On the macrosystem, the conceptualization of forest school is the key theme. Different forms of presentation in various countries with diverse cultures could provide various models of forest school education. However, there was no study investigating forest school on an ecosystem level. As for the potential benefits of physical health and mental wellness that results from forest school, it informs us to reflect the system of preschool education from the ecological perspective for Chinese children. For instance, most Chinese kindergartens ignored the significance of natural outdoor activities for children. Preschool education in China is strongly oriented by primary school system, which means pre-school children are expected to be trained as primary school students to do different subjects, such as math. Hardly any kindergarteners provide the opportunities for children and young people to take risks in a natural environment like forest school does. However, merely copying forest school model for a Chinese preschool education system will be less effective. This review of different level concerns could inform us that the localization the idea of forest school to adapt to a Chinese political, educational and cultural background. More detailed results and profound discussions will be presented in the full paper.

Keywords: early childhood education, ecological system, education development prospects in China, forest school

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Authors: Alastair Hales, Xi Jiang, Siming Zhang

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Numerical methods are used to generate vortices in a domain. Through considered design, two counter-rotating vortices may interact and effectively drive one another downstream. This phenomenon is comparable to the vortex interaction that occurs in a region immediately downstream from two counter-oscillating piezoelectric (PE) fan blades. PE fans are small blades clamped at one end and driven to oscillate at their first natural frequency by an extremely low powered actuator. In operation, the high oscillation amplitude and frequency generate sufficient blade tip speed through the surrounding air to create downstream air flow. PE fans are considered an ideal solution for low power hot spot cooling in a range of small electronic devices, but a single blade does not typically induce enough air flow to be considered a direct alternative to conventional air movers, such as axial fans. The development of face-to-face PE fan arrays containing multiple blades oscillating in counter-phase to one another is essential for expanding the range of potential PE fan applications regarding the cooling of power electronics. Even in an unoptimised state, these arrays are capable of moving air volumes comparable to axial fans with less than 50% of the power demand. Replicating the airflow generated by face-to-face PE fan arrays without including the actual blades in the model reduces the process’s computational demands and enhances the rate of innovation and development in the field. Vortices are generated at a defined inlet using a time-dependent velocity profile function, which pulsates the inlet air velocity magnitude. This induces vortex generation in the considered domain, and these vortices are shown to separate and propagate downstream in a regular manner. The generation and propagation of a single vortex are compared to an equivalent vortex generated from a PE fan blade in a previous experimental investigation. Vortex separation is found to be accurately replicated in the present numerical model. Additionally, the downstream trajectory of the vortices’ centres vary by just 10.5%, and size and strength of the vortices differ by a maximum of 10.6%. Through non-dimensionalisation, the numerical method is shown to be valid for PE fan blades with differing parameters to the specific case investigated. The thorough validation methods presented verify that the numerical model may be used to replicate vortex formation from an oscillating PE fans blade. An investigation is carried out to evaluate the effects of varying the distance between two PE fan blade, pitch. At small pitch, the vorticity in the domain is maximised, along with turbulence in the near vicinity of the inlet zones. It is proposed that face-to-face PE fan arrays, oscillating in counter-phase, should have a minimal pitch to optimally cool nearby heat sources. On the other hand, downstream airflow is maximised at a larger pitch, where the vortices can fully form and effectively drive one another downstream. As such, this should be implemented when bulk airflow generation is the desired result.

Keywords: piezoelectric fans, low energy cooling, vortex formation, computational fluid dynamics

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Authors: Yu Zhang, Jie Wu, Li Dong

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Rural tourism is the service industry which regards the agricultural production, rural life, rural nature and cultural landscape as the tourist attraction. It aims to meet the needs of the city tourists such as country sightseeing, vacation, and leisure. According to the difference of the tourist resources, the rural settlements can be divided into different types: The type of tourism resources, scenic spot, and peri-urban. In the past ten years, the rural tourism has promoted the industrial transformation and economic growth in rural areas of China. And it is conducive to the coordinated development of urban and rural areas and has greatly improved the ecological environment and the standard of living for farmers in rural areas. At the same time, a large number of buildings and sites are built in the countryside in order to enhance the tourist attraction and the ability of tourist reception and also to increase the travel comfort and convenience, which has significant influence on the spatial evolution of the village settlement. This article takes the XiangYing Subdistrict, which is in JinPu District of Dalian in China as the exemplification and uses the technology of Remote Sensing (RS), Geographic Information System (GIS) and the technology of Landscape Spatial Analysis to study the influence of the rural tourism development in the rural settlement spaces in four steps. First, acquiring the remote sensing image data at different times of 8 administrative villages in the XiangYing Subdistrict, by using the remote sensing application EDRAS8.6; second, vectoring basic maps of XiangYing Subdistrict including its land-use map with the application of ArcGIS 9.3, associating with social and economic attribute data of rural settlements and analyzing on the rural evolution visually; third, quantifying the comparison of these patches in rural settlements by using the landscape spatial calculation application Fragstats 3.3 and analyzing on the evolution of the spatial structure of settlement in macro and medium scale; finally, summarizing the evolution characteristics and internal reasons of tourism-oriented rural settlements. The main findings of this article include: first of all, there is difference in the evolution of the spatial structure between the developing rural settlements and undeveloped rural settlements among the eight administrative villages; secondly, the villages relying on the surrounding tourist attractions, the villages developing agricultural ecological garden and the villages with natural or historical and cultural resources have different laws of development; then, the rural settlements whose tourism development in germination period, development period and mature period have different characteristics of spatial evolution; finally, the different evolution modes of the tourism-oriented rural settlement space have different influences on the protection and inheritance of the village scene. The development of tourism has a significant impact on the spatial evolution of rural settlement. The intensive use of rural land and natural resources is the fundamental principle to protect the rural cultural landscape and ecological environment as well as the critical way to improve the attraction of rural tourism and promote the sustainable development of countryside.

Keywords: landscape pattern, rural settlement, spatial evolution, tourism-oriented, Xiangying Subdistrict

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Authors: David X. Dong, Qingming Zhang, Meng Lu

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Nitrites enter waterways as runoff from croplands and are discharged from many industrial sites. Excessive nitrite inputs to water bodies lead to eutrophication. On-site rapid detection of nitrite is of increasing interest for managing fertilizer application and monitoring water source quality. Existing methods for detecting nitrites use spectrophotometry, ion chromatography, electrochemical sensors, ion-selective electrodes, chemiluminescence, and colorimetric methods. However, these methods either suffer from high cost or provide low measurement accuracy due to their poor selectivity to nitrites. Therefore, it is desired to develop an accurate and economical method to monitor nitrites in environments. We report a low-cost optical sensor, in conjunction with a machine learning (ML) approach to enable high-accuracy detection of nitrites in water sources. The sensor works under the principle of measuring molecular absorptions of nitrites at three narrowband wavelengths (295 nm, 310 nm, and 357 nm) in the ultraviolet (UV) region. These wavelengths are chosen because they have relatively high sensitivity to nitrites; low-cost light-emitting devices (LEDs) and photodetectors are also available at these wavelengths. A regression model is built, trained, and utilized to minimize cross-sensitivities of these wavelengths to the same analyte, thus achieving precise and reliable measurements with various interference ions. The measured absorbance data is input to the trained model that can provide nitrite concentration prediction for the sample. The sensor is built with i) a miniature quartz cuvette as the test cell that contains a liquid sample under test, ii) three low-cost UV LEDs placed on one side of the cell as light sources, with each LED providing a narrowband light, and iii) a photodetector with a built-in amplifier and an analog-to-digital converter placed on the other side of the test cell to measure the power of transmitted light. This simple optical design allows measuring the absorbance data of the sample at the three wavelengths. To train the regression model, absorbances of nitrite ions and their combination with various interference ions are first obtained at the three UV wavelengths using a conventional spectrophotometer. Then, the spectrophotometric data are inputs to different regression algorithm models for training and evaluating high-accuracy nitrite concentration prediction. Our experimental results show that the proposed approach enables instantaneous nitrite detection within several seconds. The sensor hardware costs about one hundred dollars, which is much cheaper than a commercial spectrophotometer. The ML algorithm helps to reduce the average relative errors to below 3.5% over a concentration range from 0.1 ppm to 100 ppm of nitrites. The sensor has been validated to measure nitrites at three sites in Ames, Iowa, USA. This work demonstrates an economical and effective approach to the rapid, reagent-free determination of nitrites with high accuracy. The integration of the low-cost optical sensor and ML data processing can find a wide range of applications in environmental monitoring and management.

Keywords: optical sensor, regression model, nitrites, water quality

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Authors: Yuli Hou, Jianping Sun, Mengdan Gao, Hui Liu, Ling Qin, Ang Li, Dongfu Li, Yonghong Zhang, Yan Zhao

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Background and Aims: Interferon-induced transmembrane protein 3 (IFITM3) is a component of ISG (Interferon-Stimulated Gene) family. IFITM3 has been recognized as a key signal molecule regulating cell growth in some tumors. However, the function of IFITM3 rs12252-CC genotype in the hepatocellular carcinoma (HCC) remains unknown to author’s best knowledge. A cohort study was employed to clarify the relationship between IFITM3 rs12252-CC genotype and HCC progression, and cellular experiments were used to investigate the correlation of function of IFITM3 and the progress of HCC. Methods: 336 candidates were enrolled in study, including 156 with HBV related HCC and 180 with chronic Hepatitis B infections or liver cirrhosis. Polymerase chain reaction (PCR) was employed to determine the gene polymorphism of IFITM3. The functions of IFITM3 were detected in PLC/PRF/5 cell with different treated:LV-IFITM3 transfected with lentivirus to knockdown the expression of IFITM3 and LV-NC transfected with empty lentivirus as negative control. The IFITM3 expression, proliferation and migration were detected by Quantitative reverse transcription polymerase chain reaction (qRT-PCR), QuantiGene Plex 2.0 assay, western blotting, immunohistochemistry, Cell Counting Kit(CCK)-8 and wound healing respectively. Six samples (three infected with empty lentiviral as control; three infected with LV-IFITM3 vector lentiviral as experimental group ) of PLC/PRF/5 were sequenced at BGI (Beijing Genomics Institute, Shenzhen,China) using RNA-seq technology to identify the IFITM3-related signaling pathways and chose PI3K/AKT pathway as related signaling to verify. Results: The patients with HCC had a significantly higher proportion of IFITM3 rs12252-CC compared with the patients with chronic HBV infection or liver cirrhosis. The distribution of CC genotype in HCC patients with low differentiation was significantly higher than that in those with high differentiation. Patients with CC genotype found with bigger tumor size, higher percentage of vascular thrombosis, higher distribution of low differentiation and higher 5-year relapse rate than those with CT/TT genotypes. The expression of IFITM3 was higher in HCC tissues than adjacent normal tissues, and the level of IFITM3 was higher in HCC tissues with low differentiation and metastatic than high/medium differentiation and without metastatic. Higher RNA level of IFITM3 was found in CC genotype than TT genotype. In PLC/PRF/5 cell with knockdown, the ability of cell proliferation and migration was inhibited. Analysis RNA sequencing and verification of RT-PCR found out the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin(PI3K/AKT/mTOR) pathway was associated with knockdown IFITM3.With the inhibition of IFITM3, the expression of PI3K/AKT/mTOR signaling pathway was blocked and the expression of vimentin was decreased. Conclusions: IFITM3 rs12252-CC with the higher expression plays a vital role in the progress of HCC by regulating HCC cell proliferation and migration. These effects are associated with PI3K/AKT/mTOR signaling pathway.

Keywords: IFITM3, interferon-induced transmembrane protein 3, HCC, hepatocellular carcinoma, PI3K/ AKT/mTOR, phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin

Procedia PDF Downloads 124

Authors: Linmin Zhang

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Entrained-flow gasification technology is considered the most promising gasification technology because of its clean and efficient utilization characteristics. The stable fluidity of slag at high temperatures is the key to affecting the long-period operation of the gasifier. The diversity and differences of coal ash-slag systems make it difficult to meet the requirements for stable slagging in entrained-flow gasifiers. Therefore, coal blending or adding fluxes has been used in industry for a long time to improve the flow behavior of coal ash. As a by-product of the indirect coal liquefaction process, indirect coal liquefaction residue (ICLR) is a kind of industrial solid waste that is usually disposed of by stacking or landfilling. However, this disposal method will not only occupy land resources but also cause serious pollution to soil and water bodies by leachate containing toxic and harmful metals. As a carbon-containing matrix, ICLR is not only a kind of waste but also a kind of energy substance. Utilizing existing industrial gasifiers to blend combustion ICLR can not only transform industrial solid waste into fuel but also save coal resources. Moreover, the ICLR usually contains a unique ash chemical composition different from coal, which will affect the slagging performance of the gasifier. Therefore, exploring the effect of the ash addition in ICLR on the coal ash flow behavior can not only improve the slagging performance and gasification efficiency of entrained-flow gasifier by using the unique ash chemical composition of ICLR but also provide some theoretical support for the large-scale consumption of industrial solid waste. Combining molecular dynamics simulation with Raman spectroscopy experiment, the effect of ICLR addition on slag structure and fluidity was explained, and the relationship between the evolution law of slag short/medium range microstructure and macroscopic flow behavior was discussed. The research found that the high silicon and aluminum content in coal ash led to the formation of complex [SiO₄]⁴- tetrahedron and [AlO₄]⁵- tetrahedron structures at high temperature, and the [SiO₄]⁴- tetrahedron and [AlO₄]⁵- tetrahedron were connected by oxygen atoms to form a multi-membered ring structure with high polymerization degree. Due to the action of the multi-membered ring structure, the internal friction in the slag increased, and the viscosity value was higher on the macro-level. As a network-modified ion, Fe2+ could replace Si4+ and Al3+ in the multi-membered ring structure and combine with O2-, which will destroy the bridge oxygen (BO) structure and transform more complex tri cluster oxygen (TO) and bridge oxygen (BO) into simple non-bridge oxygen (NBO) structure. As a result, a large number of multi-membered rings with high polymerization degrees were depolymerized into low-membered rings with low polymerization degrees. The evolution of oxygen types and ring structures in slag reduced the structure complexity and polymerization degree of coal ash slag, resulting in a decrease in the viscosity of coal ash slag.

Keywords: ash slag, coal gasification, fluidity, industrial solid waste, slag structure

Procedia PDF Downloads 29

Authors: Zhuang Ma, Zihan Zhang, Yu Li

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Environmental concerns from stakeholders (e.g., governments & customers) have pushed firms to integrate environmental management systems into business processes such as R&D, manufacturing, and marketing. Environmental systems include managing environmental risks and pollution control (e.g., air pollution control, waste-water treatment, noise control, energy recycling & solid waste treatment) through raw material management, the elimination and reduction of contaminants, recycling, and reuse in firms' operational processes. Despite increasing studies on firms' proactive adoption of environmental management, their focus is primarily on large corporations operating in developed economies. Investigations in the environmental management efforts of small and medium-sized enterprises (SMEs) are scarce. This is problematic for SMEs because, unlike large corporations, SMEs have limited awareness, resources, capabilities to adapt their operational routines to address environmental impacts. The purpose of this study is to explore how SMEs develop organizational capabilities through interactions with business partners (e.g., environmental management specialists & customers). Drawing on the resource-based view (RBV) and an organizational capabilities perspective, this study investigates the interactively developed capabilities that allow SMEs to adopt environmental management systems. Using an exploratory approach, the study includes 12 semi-structured interviews with senior managers from four SMEs, two environmental management specialists, and two customers in the pharmaceutical sector in Chongqing, China. Findings of this study include four key organizational capabilities: 1) ‘dynamic marketing’ capability, which allows SMEs to recoup the investments in environmental management systems by developing environmentally friendly products to address customers' ever-changing needs; 2) ‘process improvement’ capability, which allows SMEs to select and adopt the latest technologies from biology, chemistry, new material, and new energy sectors into the production system for improved environmental performance and cost-reductions; and 3) ‘relationship management’ capability which allows SMEs to improve corporate image among the public, social media, government agencies, and customers, who in turn help SMEs to overcome their competitive disadvantages. These interactively developed capabilities help SMEs to address larger competitors' foothold in the local market, reduce market constraints, and exploit competitive advantages in other regions (e.g., Guangdong & Jiangsu) of China. These findings extend the RBV and organizational capabilities perspective; that is, SMEs can develop the essential resources and capabilities required for environmental management through interactions with upstream and downstream business partners. While a limited number of studies did highlight the importance of interactions among SMEs, customers, suppliers, NGOs, industrial associations, and consulting firms, they failed to explore the specific capabilities developed through these interactions. Additionally, the findings can explain how a proactive adoption of environmental management systems could help some SMEs to overcome the institutional and market restraints on their products, thereby springboarding into larger, more environmentally demanding, yet more profitable markets compared with their existing market.

Keywords: capabilities, environmental management systems, interactions, SMEs

Procedia PDF Downloads 180

Authors: Akeel A. Shah, Tong Zhang

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Computational approaches to learning the properties of materials are commonplace, motivated by the need to screen or design materials for a given application, e.g., semiconductors and energy storage. Experimental approaches can be both time consuming and costly. Unfortunately, computational approaches such as ab-initio electronic structure calculations and classical or ab-initio molecular dynamics are themselves can be too slow for the rapid evaluation of materials, often involving thousands to hundreds of thousands of candidates. Machine learning assisted approaches have been developed to overcome the time limitations of purely physics-based approaches. These approaches, on the other hand, require large volumes of data for training (hundreds of thousands on many standard data sets such as QM7b). This means that they are limited by how quickly such a large data set of physics-based simulations can be established. At high fidelity, such as configuration interaction, composite methods such as G4, and coupled cluster theory, gathering such a large data set can become infeasible, which can compromise the accuracy of the predictions - many applications require high accuracy, for example band structures and energy levels in semiconductor materials and the energetics of charge transfer in energy storage materials. In order to circumvent this problem, multi-fidelity approaches can be adopted, for example the Δ-ML method, which learns a high-fidelity output from a low-fidelity result such as Hartree-Fock or density functional theory (DFT). The general strategy is to learn a map between the low and high fidelity outputs, so that the high-fidelity output is obtained a simple sum of the physics-based low-fidelity and correction, Although this requires a low-fidelity calculation, it typically requires far fewer high-fidelity results to learn the correction map, and furthermore, the low-fidelity result, such as Hartree-Fock or semi-empirical ZINDO, is typically quick to obtain, For high-fidelity outputs the result can be an order of magnitude or more in speed up. In this work, a new multi-fidelity approach is developed, based on a graph convolutional network (GCN) combined with semi-supervised learning. The GCN allows for the material or molecule to be represented as a graph, which is known to improve accuracy, for example SchNet and MEGNET. The graph incorporates information regarding the numbers of, types and properties of atoms; the types of bonds; and bond angles. They key to the accuracy in multi-fidelity methods, however, is the incorporation of low-fidelity output to learn the high-fidelity equivalent, in this case by learning their difference. Semi-supervised learning is employed to allow for different numbers of low and high-fidelity training points, by using an additional GCN-based low-fidelity map to predict high fidelity outputs. It is shown on 4 different data sets that a significant (at least one order of magnitude) increase in accuracy is obtained, using one to two orders of magnitude fewer low and high fidelity training points. One of the data sets is developed in this work, pertaining to 1000 simulations of quinone molecules (up to 24 atoms) at 5 different levels of fidelity, furnishing the energy, dipole moment and HOMO/LUMO.

Keywords: .materials screening, computational materials, machine learning, multi-fidelity, graph convolutional network, semi-supervised learning

Procedia PDF Downloads 39

Authors: Jing Zhang, Yvonne Reinwald, Nick Poulson, Alicia El Haj, Chung See, Mike Somekh, Melissa Mather

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Biomedical imaging of native tissue using light offers the potential to obtain excellent structural and functional information in a non-invasive manner with good temporal resolution. Image contrast can be derived from intrinsic absorption, fluorescence, or scatter, or through the use of extrinsic contrast. A major challenge in applying optical microscopy to in vivo tissue imaging is the effects of light attenuation which limits light penetration depth and achievable imaging resolution. Recently Selective Plane Illumination Microscopy (SPIM) has been used to map the 3D distribution of fluorophores dispersed in biological structures. In this approach, a focused sheet of light is used to illuminate the sample from the side to excite fluorophores within the sample of interest. Images are formed based on detection of fluorescence emission orthogonal to the illumination axis. By scanning the sample along the detection axis and acquiring a stack of images, 3D volumes can be obtained. The combination of rapid image acquisition speeds with the low photon dose to samples optical sectioning provides SPIM is an attractive approach for imaging biological samples in 3D. To date all implementations of SPIM rely on the use of fluorescence reporters be that endogenous or exogenous. This approach has the disadvantage that in the case of exogenous probes the specimens are altered from their native stage rendering them unsuitable for in vivo studies and in general fluorescence emission is weak and transient. Here we present for the first time to our knowledge a label-free implementation of SPIM that has downstream applications in the clinical setting. The experimental set up used in this work incorporates both label-free and fluorescent illumination arms in addition to a high specification camera that can be partitioned for simultaneous imaging of both fluorescent emission and scattered light from intrinsic sources of optical contrast in the sample being studied. This work first involved calibration of the imaging system and validation of the label-free method with well characterised fluorescent microbeads embedded in agarose gel. 3D constructs of mammalian cells cultured in agarose gel with varying cell concentrations were then imaged. A time course study to track cell proliferation in the 3D construct was also carried out and finally a native tissue sample was imaged. For each sample multiple images were obtained by scanning the sample along the axis of detection and 3D maps reconstructed. The results obtained validated label-free SPIM as a viable approach for imaging cells in a 3D gel construct and native tissue. This technique has the potential use in a near-patient environment that can provide results quickly and be implemented in an easy to use manner to provide more information with improved spatial resolution and depth penetration than current approaches.

Keywords: bioimaging, optics, selective plane illumination microscopy, tissue imaging

Procedia PDF Downloads 247

Authors: Desmond Appiah, Fan Zhang, Shouqi Yuan, Wei Xueyuan, Stephen N. Asomani

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The side channel pump has distinctive hydraulic performance characteristics over other vane pumps because of its generation of high pressure heads in only one impeller revolution. Hence, there is soaring utilization and application in the fields of petrochemical, food processing fields, automotive and aerospace fuel pumping where high heads are required at low flows. The side channel pump is characterized by unstable flow because after fluid flows into the impeller passage, it moves into the side channel and comes back to the impeller again and then moves to the next circulation. Consequently, the flow leaves the side channel pump following a helical path. However, the pressure fluctuation exhibited in the flow greatly contributes to the unwanted noise and vibration which is associated with the flow. In this paper, a side channel pump prototype was examined thoroughly through numerical calculations based on SST k-ω turbulence model to ascertain the pressure fluctuation behavior. The pressure fluctuation intensity of the 3D unstable flow dynamics were carefully investigated under different working conditions 0.8QBEP, 1.0 QBEP and 1.2QBEP. The results showed that the pressure fluctuation distribution around the pressure side of the blade is greater than the suction side at the impeller and side channel interface (z=0) for all three operating conditions. Part-load condition 0.8QBEP recorded the highest pressure fluctuation distribution because of the high circulation velocity thus causing an intense exchanged flow between the impeller and side channel. Time and frequency domains spectra of the pressure fluctuation patterns in the impeller and the side channel were also analyzed under the best efficiency point value, QBEP using the solution from the numerical calculations. It was observed from the time-domain analysis that the pressure fluctuation characteristics in the impeller flow passage increased steadily until the flow reached the interrupter which separates low-pressure at the inflow from high pressure at the outflow. The pressure fluctuation amplitudes in the frequency domain spectrum at the different monitoring points depicted a gentle decreasing trend of the pressure amplitudes which was common among the operating conditions. The frequency domain also revealed that the main excitation frequencies occurred at 600Hz, 1200Hz, and 1800Hz and continued in the integers of the rotating shaft frequency. Also, the mass flow exchange plots indicated that the side channel pump is characterized with many vortex flows. Operating conditions 0.8QBEP, 1.0 QBEP depicted less and similar vortex flow while 1.2Q recorded many vortex flows around the inflow, middle and outflow regions. The results of the numerical calculations were finally verified experimentally. The performance characteristics curves from the simulated results showed that 0.8QBEP working condition recorded a head increase of 43.03% and efficiency decrease of 6.73% compared to 1.0QBEP. It can be concluded that for industrial applications where the high heads are mostly required, the side channel pump can be designed to operate at part-load conditions. This paper can serve as a source of information in order to optimize a reliable performance and widen the applications of the side channel pumps.

Keywords: exchanged flow, pressure fluctuation, numerical simulation, side channel pump

Procedia PDF Downloads 136

Authors: Fei Jia, Xingjian Bai, Xiaowei Zhang, Wenjie Yan, Ruitong Dai, Xingmin Li, Jozef Kokini

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Pseudomonas aeruginosa is a Gram-negative, aerobic, opportunistic human pathogen that is present in the soil, water, and food. This microbe has been recognized as a representative food-borne spoilage bacterium that can lead to many types of infections. Considering the casualties and property loss caused by P. aeruginosa, the development of a rapid and reliable technique for the detection of P. aeruginosa is crucial. The whole-cell aptasensor, an emerging biosensor using aptamer as a capture probe to bind to the whole cell, for food-borne pathogens detection has attracted much attention due to its convenience and high sensitivity. Here, a low-field magnetic resonance imaging (LF-MRI) aptasensor for the rapid detection of P. aeruginosa was developed. The basic detection principle of the magnetic relaxation switch (MRSw) nanosensor lies on the ‘T₂-shortening’ effect of magnetic nanoparticles in NMR measurements. Briefly speaking, the transverse relaxation time (T₂) of neighboring water protons get shortened when magnetic nanoparticles are clustered due to the cross-linking upon the recognition and binding of biological targets, or simply when the concentration of the magnetic nanoparticles increased. Such shortening is related to both the state change (aggregation or dissociation) and the concentration change of magnetic nanoparticles and can be detected using NMR relaxometry or MRI scanners. In this work, two different sizes of magnetic nanoparticles, which are 10 nm (MN₁₀) and 400 nm (MN₄₀₀) in diameter, were first immobilized with anti- P. aeruginosa aptamer through 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC)/N-hydroxysuccinimide (NHS) chemistry separately, to capture and enrich the P. aeruginosa cells. When incubating with the target, a ‘sandwich’ (MN₁₀-bacteria-MN₄₀₀) complex are formed driven by the bonding of MN400 with P. aeruginosa through aptamer recognition, as well as the conjugate aggregation of MN₁₀ on the surface of P. aeruginosa. Due to the different magnetic performance of the MN₁₀ and MN₄₀₀ in the magnetic field caused by their different saturation magnetization, the MN₁₀-bacteria-MN₄₀₀ complex, as well as the unreacted MN₄₀₀ in the solution, can be quickly removed by magnetic separation, and as a result, only unreacted MN₁₀ remain in the solution. The remaining MN₁₀, which are superparamagnetic and stable in low field magnetic field, work as a signal readout for T₂ measurement. Under the optimum condition, the LF-MRI platform provides both image analysis and quantitative detection of P. aeruginosa, with the detection limit as low as 100 cfu/mL. The feasibility and specificity of the aptasensor are demonstrated in detecting real food samples and validated by using plate counting methods. Only two steps and less than 2 hours needed for the detection procedure, this robust aptasensor can detect P. aeruginosa with a wide linear range from 3.1 ×10² cfu/mL to 3.1 ×10⁷ cfu/mL, which is superior to conventional plate counting method and other molecular biology testing assay. Moreover, the aptasensor has a potential to detect other bacteria or toxins by changing suitable aptamers. Considering the excellent accuracy, feasibility, and practicality, the whole-cell aptasensor provides a promising platform for a quick, direct and accurate determination of food-borne pathogens at cell-level.

Keywords: magnetic resonance imaging, meat spoilage, P. aeruginosa, transverse relaxation time

Procedia PDF Downloads 152

Authors: Zhenyu Zhang, Hsi-Hsien Wei

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Highway network systems play a vital role in disaster response for disaster-damaged areas. Damaged bridges in such network systems can impede disaster response by disrupting transportation of rescue teams or humanitarian supplies. Therefore, emergency inspection and repair of bridges to quickly collect damage information of bridges and recover the functionality of highway networks is of paramount importance to disaster response. A widely used measure of a network’s capability to recover from disasters is resilience. To enhance highway network resilience, plenty of studies have developed various repair scheduling methods for the prioritization of bridge-repair tasks. These methods assume that repair activities are performed after the damage to a highway network is fully understood via inspection, although inspecting all bridges in a regional highway network may take days, leading to the significant delay in repairing bridges. In reality, emergency repair activities can be commenced as soon as the damage data of some bridges that are crucial to emergency response are obtained. Given that emergency bridge inspection and repair (EBIR) activities are executed simultaneously in the response phase, the real-time interactions between these activities can occur – the blockage of highways due to repair activities can affect inspection routes which in turn have an impact on emergency repair scheduling by providing real-time information on bridge damages. However, the impact of such interactions on the optimal emergency inspection routes (EIR) and emergency repair schedules (ERS) has not been discussed in prior studies. To overcome the aforementioned deficiencies, this study develops a routing and scheduling model for EBIR while accounting for real-time inspection-repair interactions to maximize highway network resilience. A stochastic, time-dependent integer program is proposed for the complex and real-time interacting EBIR problem given multiple inspection and repair teams at locations as set post-disaster. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. Computational tests are performed using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that the simultaneous implementation of bridge inspection and repair activities can significantly improve the highway network resilience. Moreover, the deployment of inspection and repair teams should match each other, and the network resilience will not be improved once the unilateral increase in inspection teams or repair teams exceeds a certain level. This study contributes to both knowledge and practice. First, the developed mathematical model makes it possible for capturing the impact of real-time inspection-repair interactions on inspection routing and repair scheduling and efficiently deriving optimal EIR and ERS on a large and complex highway network. Moreover, this study contributes to the organizational dimension of highway network resilience by providing optimal strategies for highway bridge management. With the decision support tool, disaster managers are able to identify the most critical bridges for disaster management and make decisions on proper inspection and repair strategies to improve highway network resilience.

Keywords: disaster management, emergency bridge inspection and repair, highway network, resilience, uncertainty

Procedia PDF Downloads 109

Authors: Jinlu Ruan, Liang Chen, Bo Liu, Xiaoping Ouyang, Zhichao Zhu, Zhongbing Zhang, Shiyi He, Mengxuan Xu

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Plastic scintillators play an important role in the measurement of a mixed neutron/gamma pulsed radiation, neutron radiography and pulse shape discrimination technology. In some research, these luminescent properties are necessary that photons produced by the interactions between a plastic scintillator and radiations can be detected as much as possible by the photoelectric detectors and more photons can be emitted from the scintillators along a specific direction where detectors are located. Unfortunately, a majority of these photons produced are trapped in the plastic scintillators due to the total internal reflection (TIR), because there is a significant light-trapping effect when the incident angle of internal scintillation light is larger than the critical angle. Some of these photons trapped in the scintillator may be absorbed by the scintillator itself and the others are emitted from the edges of the scintillator. This makes the light extraction of plastic scintillators very low. Moreover, only a small portion of the photons emitted from the scintillator easily can be detected by detectors effectively, because the distribution of the emission directions of this portion of photons exhibits approximate Lambertian angular profile following a cosine emission law. Therefore, enhancing the light extraction efficiency and adjusting the emission angular profile become the keys for improving the number of photons detected by the detectors. In recent years, photonic crystal structures have been covered on inorganic scintillators to enhance the light extraction efficiency and adjust the angular profile of scintillation light successfully. However, that, preparation methods of photonic crystals will deteriorate performance of plastic scintillators and even destroy the plastic scintillators, makes the investigation on preparation methods of photonic crystals for plastic scintillators and luminescent properties of plastic scintillators with photonic crystal structures inadequate. Although we have successfully made photonic crystal structures covered on the surface of plastic scintillators by a modified self-assembly technique and achieved a great enhance of light extraction efficiency without evident angular-dependence for the angular profile of scintillation light, the preparation of photonic crystal structures with large area (the diameter is larger than 6cm) and perfect periodic structure is still difficult. In this paper, large area photonic crystals on the surface of scintillators were prepared by nanoimprint lithography firstly, and then a conformal layer with material of high refractive index on the surface of photonic crystal by atomic layer deposition technique in order to enhance the stability of photonic crystal structures and increase the number of leaky modes for improving the light extraction efficiency. The luminescent properties of the plastic scintillator with photonic crystals prepared by the mentioned method are compared with those of the plastic scintillator without photonic crystal. The results indicate that the number of photons detected by detectors is increased by the enhanced light extraction efficiency and the angular profile of scintillation light exhibits evident angular-dependence for the scintillator with photonic crystals. The mentioned preparation of photonic crystals is beneficial to scintillation detection applications and lays an important technique foundation for the plastic scintillators to meet special requirements under different application backgrounds.

Keywords: angular profile, atomic layer deposition, light extraction efficiency, plastic scintillator, photonic crystal

Procedia PDF Downloads 200

Authors: Yan Zhang

Abstract:

Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

Procedia PDF Downloads 386

Authors: Ruolan Zhang, Ryo Imai, Naoko Senda, Tomoyuki Sakai

Abstract:

Enzymes have attracted increasing attentions in industrial manufacturing for their applicability in catalyzing complex chemical reactions under mild conditions. Directed evolution has become a powerful approach to optimize enzymes and exploit their full potentials under the circumstance of insufficient structure-function knowledge. With the incorporation of cell-free synthetic biotechnology, rapid enzyme synthesis can be realized because no cloning procedure such as transfection is needed. Its open environment also enables direct enzyme measurement. These properties of cell-free biotechnology lead to excellent throughput of enzymes generation. However, the capabilities of current screening methods have limitations. Fluorescence-based assay needs applicable fluorescent label, and the reliability of acquired enzymatic activity is influenced by fluorescent label’s binding affinity and photostability. To acquire the natural activity of an enzyme, another method is to combine pre-screening step and high-performance liquid chromatography (HPLC) measurement. But its throughput is limited by necessary time investment. Hundreds of variants are selected from libraries, and their enzymatic activities are then identified one by one by HPLC. The turn-around-time is 30 minutes for one sample by HPLC, which limits the acquirable enzyme improvement within reasonable time. To achieve the real high-throughput enzyme screening, i.e., obtain reliable enzyme improvement within reasonable time, a widely applicable high-throughput measurement of enzymatic reactions is highly demanded. Here, a high-throughput screening method using broadband coherent anti-Stokes Raman spectroscopy (CARS) was proposed. CARS is one of coherent Raman spectroscopy, which can identify label-free chemical components specifically from their inherent molecular vibration. These characteristic vibrational signals are generated from different vibrational modes of chemical bonds. With the broadband CARS, chemicals in one sample can be identified from their signals in one broadband CARS spectrum. Moreover, it can magnify the signal levels to several orders of magnitude greater than spontaneous Raman systems, and therefore has the potential to evaluate chemical's concentration rapidly. As a demonstration of screening with CARS, alcohol dehydrogenase, which converts ethanol and nicotinamide adenine dinucleotide oxidized form (NAD+) to acetaldehyde and nicotinamide adenine dinucleotide reduced form (NADH), was used. The signal of NADH at 1660 cm⁻¹, which is generated from nicotinamide in NADH, was utilized to measure the concentration of it. The evaluation time for CARS signal of NADH was determined to be as short as 0.33 seconds while having a system sensitivity of 2.5 mM. The time course of alcohol dehydrogenase reaction was successfully measured from increasing signal intensity of NADH. This measurement result of CARS was consistent with the result of a conventional method, UV-Vis. CARS is expected to have application in high-throughput enzyme screening and realize more reliable enzyme improvement within reasonable time.

Keywords: Coherent Anti-Stokes Raman Spectroscopy, CARS, directed evolution, enzyme screening, Raman spectroscopy

Procedia PDF Downloads 141

Authors: Ting Wu, Feiting Hu, Xinyue Zhang, Shuxin Tang, Xiaoyun Xu

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As a by-product of yuba, processing wastewater of Yuba (PWY) contains many bioactive components such as soybean isoflavones, soybean polysaccharides and soybean oligosaccharides, which is a good source of prebiotics and has a potential of high value utilization. The use of Lactobacillus plantarum to ferment PWY can be considered as a potential biogenic element, which can regulate the balance of intestinal microbiota. In this study, firstly, Lactobacillus plantarum was used to ferment PWY to improve its content of active components and antioxidant activity. Then, the health effect of fermented processing wastewater of yuba (FPWY) was measured in vitro. Finally, microencapsulation technology was used applied to improve the sustained release of FPWY and reduce the loss of active components in the digestion process, as well as to improving the activity of FPWY. The main results are as follows: (1) FPWY presented a good antioxidant capacity with DPPH free radical scavenging ability (0.83 ± 0.01 mmol Trolox/L), ABTS free radical scavenging ability (7.47 ± 0.35 mmol Trolox/L) and iron ion reducing ability (1.11 ± 0.07 mmol Trolox/L). Compared with non-fermented processing wastewater of yuba (NFPWY), there was no significant difference in the content of total soybean isoflavones, but the content of glucoside soybean isoflavones decreased, and aglyconic soybean isoflavones increased significantly. After fermentation, PWY can effectively reduce the soluble monosaccharides, disaccharides and oligosaccharides, such as glucose, fructose, galactose, trehalose, stachyose, maltose, raffinose and sucrose. (2) FPWY can significantly enhance the growth of beneficial bacteria such as Bifidobacterium, Ruminococcus and Akkermansia, significantly inhibit the growth of harmful bacteria E.coli, regulate the structure of intestinal microbiota, and significantly increase the content of short-chain fatty acids such as acetic acid, propionic acid, butyric acid, isovaleric acid. Higher amount of lactic acid in the gut can be further broken down into short chain fatty acids. (3) In order to improve the stability of soybean isoflavones in FPWY during digestion, sodium alginate and chitosan were used as wall materials for embedding. The FPWY freeze-dried powder was embedded by the method of acute-coagulation bath. The results show that when the core wall ratio is 3:1, the concentration of chitosan is 1.5%, the concentration of sodium alginate is 2.0%, and the concentration of calcium is 3%, the embossing rate is 53.20%. In the simulated in vitro digestion stage, the release rate of microcapsules reached 59.36% at the end of gastric digestion and 82.90% at the end of intestinal digestion. Therefore, the core materials with good sustained-release performance of microcapsules were almost all released. The structural analysis results of FPWY microcapsules show that the microcapsules have good mechanical properties. Its hardness, springness, cohesiveness, gumminess, chewiness and resilience were 117.75± 0.21 g, 0.76±0.02, 0.54±0.01, 63.28±0.71 g·sec, 48.03±1.37 g·sec, 0.31±0.01, respectively. Compared with the unembedded FPWY, the infrared spectrum results showed that the microcapsules had embedded effect on the FPWY freeze-dried powder.

Keywords: processing wastewater of yuba, lactobacillus plantarum, intestinal microbiota, microcapsule

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Authors: Mingqian Zhang

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Tip-enhanced Raman spectroscopy (TERS) is a scanning probe technique for individual objects and structured surfaces investigation that provides a wealth of enhanced spectral information with nanoscale spatial resolution and high detection sensitivity. It has become a powerful and promising chemical and physical information detection method in the nanometer scale. The TERS technique uses a sharp metallic tip regulated in the near-field of a sample surface, which is illuminated with a certain incident beam meeting the excitation conditions of the wave-vector matching. The local electric field, and, consequently, the Raman scattering, from the sample in the vicinity of the tip apex are both greatly tip-enhanced owning to the excitation of localized surface plasmons and the lightning-rod effect. Typically, a TERS setup is composed of a scanning probe microscope, excitation and collection optical configurations, and a Raman spectroscope. In the illumination configuration, an objective lens or a parabolic mirror is always used as the most important component, in order to focus the incident beam on the tip apex for excitation. In this research, a novel TERS setup was built up by introducing a plasmonic lens to the excitation optics as a focusing device. A plasmonic lens with symmetry breaking semi-annular slits corrugated on gold film was designed for the purpose of generating concentrated sub-wavelength light spots with strong longitudinal electric field. Compared to conventional far-field optical components, the designed plasmonic lens not only focuses an incident beam to a sub-wavelength light spot, but also realizes a strong z-component that dominants the electric field illumination, which is ideal for the excitation of tip-enhancement. Therefore, using a PL in the illumination configuration of TERS contributes to improve the detection sensitivity by both reducing the far-field background and effectively exciting the localized electric field enhancement. The FDTD method was employed to investigate the optical near-field distribution resulting from the light-nanostructure interaction. And the optical field distribution was characterized using an scattering-type scanning near-field optical microscope to demonstrate the focusing performance of the lens. The experimental result is in agreement with the theoretically calculated one. It verifies the focusing performance of the plasmonic lens. The optical field distribution shows a bright elliptic spot in the lens center and several arc-like side-lobes on both sides. After the focusing performance was experimentally verified, the designed plasmonic lens was used as a focusing component in the excitation configuration of TERS setup to concentrate incident energy and generate a longitudinal optical field. A collimated linearly polarized laser beam, with along x-axis polarization, was incident from the bottom glass side on the plasmonic lens. The incident light focused by the plasmonic lens interacted with the silver-coated tip apex and enhanced the Raman signal of the sample locally. The scattered Raman signal was gathered by a parabolic mirror and detected with a Raman spectroscopy. Then, the plasmonic lens based setup was employed to investigate carbon nanotubes and TERS experiment was performed. Experimental results indicate that the Raman signal is considerably enhanced which proves that the novel TERS configuration is feasible and promising.

Keywords: longitudinal electric field, plasmonics, raman spectroscopy, tip-enhancement

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Authors: Lei Ye, Min Liu, Yong-Li Gao, Jun Zhang

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Purpose: The aims of the study are to investigate the status of health-promoting lifestyle and to compare the healthy lifestyle of emergency nurses in different levels of hospitals in Sichuan province, China. The investigation is mainly about the health-promoting lifestyle, including spiritual growth, health responsibility, physical activity, nutrition, interpersonal relations, stress management. Then the factors were analyzed influencing the health-promoting lifestyle of emergency nurses in hospitals of Sichuan province in order to find the relevant models to provide reference evidence for intervention. Study Design: A cross-sectional research method was adopted. Stratified cluster sampling, based on geographical location, was used to select the health facilities of 1389 emergency nurses in 54 hospitals from Sichuan province in China. Method: The 52-item, six-factor structure Health-Promoting Lifestyle Profile II (HPLP- II) instrument was used to explore participants’ self-reported health-promoting behaviors and measure the dimensions of health responsibility, physical activity, nutrition, interpersonal relations, spiritual growth, and stress management. Demographic characteristics, education, work duration, emergency nursing work duration and self-rated health status were documented. Analysis: Data were analyzed through SPSS software ver. 17.0. Frequency, percentage, mean ± standard deviation were used to describe the general information, while the Nonparametric Test was used to compare the constituent ratio of general data of different hospitals. One-way ANOVA was used to compare the scores of health-promoting lifestyle in different levels hospital. A multiple linear regression model was established. P values which were less than 0.05 determined statistical significance in all analyses. Result: The survey showed that the total score of health-promoting lifestyle of nurses at emergency departments in Sichuan Province was 120.49 ± 21.280. The relevant dimensions are ranked by scores in descending order: interpersonal relations, nutrition, health responsibility, physical activity, stress management, spiritual growth. The total scores of the three-A hospital were the highest (121.63 ± 0.724), followed by the senior class hospital (119.7 ± 1.362) and three-B hospital (117.80 ± 1.255). The difference was statistically significant (P=0.024). The general data of nurses was used as the independent variable which includes age, gender, marital status, living conditions, nursing income, hospital level, Length of Service in nursing, Length of Service in emergency, Professional Title, education background, and the average number of night shifts. The total score of health-promoting lifestyle was used as dependent variable; Multiple linear regression analysis method was adopted to establish the regression model. The regression equation F = 20.728, R2 = 0.061, P < 0.05, the age, gender, nursing income, turnover intention and status of coping stress affect the health-promoting lifestyle of nurses in emergency department, the result was statistically significant (P < 0.05 ). Conclusion: The results of the investigation indicate that it will help to develop health promoting interventions for emergency nurses in all levels of hospital in Sichuan Province through further research. Managers need to pay more attention to emergency nurses’ exercise, stress management, self-realization, and conduct intervention in nurse training programs.

Keywords: emergency nurse, health-promoting lifestyle profile II, health behaviors, lifestyle

Procedia PDF Downloads 282

Authors: Irene Carmagnola, Valeria Chiono, Sandra Pacharra, Jochen Salber, Sean McMahon, Chris Lovell, Pooja Basnett, Barbara Lukasiewicz, Ipsita Roy, Xiang Zhang, Gianluca Ciardelli

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Thrombosis and restenosis after stenting procedure can be prevented by promoting fast stent wall endothelialisation. It is well known that surface functionalisation with antifouling molecules combining with extracellular matrix proteins is a promising strategy to design biomimetic surfaces able to promote fast endothelialization. In particular, REDV has gained much attention for the ability to enhance rapid endothelialization due to its specific affinity with endothelial cells (ECs). In this work, a two-step plasma treatment was performed to polymerize a thin layer of acrylic acid, used to subsequently graft PEGylated-REDV and polyethylene glycol (PEG) at different molar ratio with the aim to selectively promote endothelial cell adhesion avoiding platelet activation. PEGylate-REDV was provided by Biomatik and it is formed by 6 PEG monomer repetitions (Chempep Inc.), with an NH2 terminal group. PEG polymers were purchased from Chempep Inc. with two different chain lengths: m-PEG6-NH2 (295.4 Da) with 6 monomer repetitions and m-PEG12-NH2 (559.7 Da) with 12 monomer repetitions. Plasma activation was obtained by operating at 50W power, 5 min of treatment and at an Ar flow rate of 20 sccm. Pure acrylic acid (99%, AAc) vapors were diluted in Ar (flow = 20 sccm) and polymerized by a pulsed plasma discharge applying a discharge RF power of 200 W, a duty cycle of 10% (on time = 10 ms, off time = 90 ms) for 10 min. After plasma treatment, samples were dipped into an 1-(3-dimethylaminopropyl)-3- ethylcarbodiimide (EDC)/N-hydroxysuccinimide (NHS) solution (ratio 4:1, pH 5.5) for 1 h at 4°C and subsequently dipped in PEGylate-REDV and PEGylate-REDV:PEG solutions at different molar ratio (100 μg/mL in PBS) for 20 h at room temperature. Surface modification was characterized through physico-chemical analyses and in vitro cell tests. PEGylated-REDV peptide and PEG were successfully bound to the carboxylic groups that are formed on the polymer surface after plasma reaction. FTIR-ATR spectroscopy, X -ray Photoelectron Spectroscopy (XPS) and contact angle measurement gave a clear indication of the presence of the grafted molecules. The use of PEG as a spacer allowed for an increase in wettability of the surface, and the effect was more evident by increasing the amount of PEG. Endothelial cells adhered and spread well on the surfaces functionalized with the REDV sequence. In conclusion, a selective coating able to promote a new endothelial cell layer on polymeric stent surface was developed. In particular, a thin AAc film was polymerised on the polymeric surface in order to expose –COOH groups, and PEGylate-REDV and PEG were successful grafted on the polymeric substrates. The REDV peptide demonstrated to encourage cell adhesion with a consequent, expected improvement of the hemocompatibility of these polymeric surfaces in vivo. Acknowledgements— This work was funded by the European Commission 7th Framework Programme under grant agreement number 604251- ReBioStent (Reinforced Bioresorbable Biomaterials for Therapeutic Drug Eluting Stents). The authors thank all the ReBioStent partners for their support in this work.

Keywords: endothelialisation, plasma treatment, stent, surface functionalisation

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Authors: James Brown, Stella Kortekaas, Ian Finnie, George Zhang, Christine Devine, Neil Healy

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The use of GIS as an analysis tool for engineering decision making is now best practice in the offshore industry. GIS enables multidisciplinary data integration, analysis and visualisation which allows the presentation of large and intricate datasets in a simple map-interface accessible to all project stakeholders. Presenting integrated geoscience and geotechnical data in GIS enables decision makers to be well-informed. This paper is a successful case study of how GIS spatial analysis techniques were applied to help select the most favourable pipeline route. Routing a pipeline through any natural environment has numerous obstacles, whether they be topographical, geological, engineering or financial. Where the pipeline is subjected to external hydrostatic water pressure and is carrying pressurised hydrocarbons, the requirement to safely route the pipeline through hazardous terrain becomes absolutely paramount. This study illustrates how the application of modern, GIS-based pipeline routing techniques enabled the identification of a single most-favourable pipeline route crossing of a challenging seabed terrain. Conventional approaches to pipeline route determination focus on manual avoidance of primary constraints whilst endeavouring to minimise route length. Such an approach is qualitative, subjective and is liable to bias towards the discipline and expertise that is involved in the routing process. For very short routes traversing benign seabed topography in shallow water this approach may be sufficient, but for deepwater geohazardous sites, the need for an automated, multi-criteria, and quantitative approach is essential. This study combined multiple routing constraints using modern least-cost-routing algorithms deployed in GIS, hitherto unachievable with conventional approaches. The least-cost-routing procedure begins with the assignment of geocost across the study area. Geocost is defined as a numerical penalty score representing hazard posed by each routing constraint (e.g. slope angle, rugosity, vulnerability to debris flows) to the pipeline. All geocosted routing constraints are combined to generate a composite geocost map that is used to compute the least geocost route between two defined terminals. The analyses were applied to select the most favourable pipeline route for a potential gas development in deep water. The study area is geologically complex with a series of incised, potentially active, canyons carved into a steep escarpment, with evidence of extensive debris flows. A similar debris flow in the future could cause significant damage to a poorly-placed pipeline. Protruding inter-canyon spurs offer lower-gradient options for ascending an escarpment but the vulnerability of periodic failure of these spurs is not well understood. Close collaboration between geoscientists, pipeline engineers, geotechnical engineers and of course the gas export pipeline operator guided the analyses and assignment of geocosts. Shorter route length, less severe slope angles, and geohazard avoidance were the primary drivers in identifying the most favourable route.

Keywords: geocost, geohazard, pipeline route determination, pipeline route optimisation, spatial analysis

Procedia PDF Downloads 406

Authors: Kazuhiro Tateda, Elisa Gonzalez, Shuhei Ito, Kirstin Heinrich, Kevin Sweetland, Pingping Zhang, Catia Ferreira, Michael Pride, Jennifer Moisi, Sharon Gray, Bennett Lee, Fred Angulo

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Clostridium difficile (C. difficile) is the most common cause of antibiotic-associated diarrhea and infectious diarrhea in healthcare settings. Japan has an aging population; the elderly are at increased risk of hospitalization, antibiotic use, and C. difficile infection (CDI). Little is known about the population-based incidence and disease burden of CDI in Japan although limited hospital-based studies have reported a lower incidence than the United States. To understand CDI disease burden in Japan, CLOUD (Clostridium difficile Infection Burden of Disease in Adults in Japan) was developed. CLOUD will derive population-based incidence estimates of the number of CDI cases per 100,000 population per year in Ota-ku (population 723,341), one of the districts in Tokyo, Japan. CLOUD will include approximately 14 of the 28 Ota-ku hospitals including Toho University Hospital, which is a 1,000 bed tertiary care teaching hospital. During the 12-month patient enrollment period, which is scheduled to begin in November 2018, Ota-ku residents > 50 years of age who are hospitalized at a participating hospital with diarrhea ( > 3 unformed stools (Bristol Stool Chart 5-7) in 24 hours) will be actively ascertained, consented, and enrolled by study surveillance staff. A stool specimen will be collected from enrolled patients and tested at a local reference laboratory (LSI Medience, Tokyo) using QUIK CHEK COMPLETE® (Abbott Laboratories). which simultaneously tests specimens for the presence of glutamate dehydrogenase (GDH) and C. difficile toxins A and B. A frozen stool specimen will also be sent to the Pfizer Laboratory (Pearl River, United States) for analysis using a two-step diagnostic testing algorithm that is based on detection of C. difficile strains/spores harboring toxin B gene by PCR followed by detection of free toxins (A and B) using a proprietary cell cytotoxicity neutralization assay (CCNA) developed by Pfizer. Positive specimens will be anaerobically cultured, and C. difficile isolates will be characterized by ribotyping and whole genomic sequencing. CDI patients enrolled in CLOUD will be contacted weekly for 90 days following diarrhea onset to describe clinical outcomes including recurrence, reinfection, and mortality, and patient reported economic, clinical and humanistic outcomes (e.g., health-related quality of life, worsening of comorbidities, and patient and caregiver work absenteeism). Studies will also be undertaken to fully characterize the catchment area to enable population-based estimates. The 12-month active ascertainment of CDI cases among hospitalized Ota-ku residents with diarrhea in CLOUD, and the characterization of the Ota-ku catchment area, including estimation of the proportion of all hospitalizations of Ota-ku residents that occur in the CLOUD-participating hospitals, will yield CDI population-based incidence estimates, which can be stratified by age groups, risk groups, and source (hospital-acquired or community-acquired). These incidence estimates will be extrapolated, following age standardization using national census data, to yield CDI disease burden estimates for Japan. CLOUD also serves as a model for studies in other countries that can use the CLOUD protocol to estimate CDI disease burden.

Keywords: Clostridium difficile, disease burden, epidemiology, study protocol

Procedia PDF Downloads 261

Authors: Shuai Yuan, Minxia Shi, Xu Zhang, Jianzhi Yang, Kangqi Tian, Yuzheng Ma

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The precise measurement of muscle activities is essential for understanding the function of various body movements. This work aims to develop a muscle magnetic field signal detection system based on mathematical analysis. Medical research has underscored that early detection of muscle atrophy, coupled with lifestyle adjustments such as dietary control and increased exercise, can significantly enhance muscle-related diseases. Currently, surface electromyography (sEMG) is widely employed in research as an early predictor of muscle atrophy. Nonetheless, the primary limitation of using sEMG to forecast muscle strength is its inability to directly measure the signals generated by muscles. Challenges arise from potential skin-electrode contact issues due to perspiration, leading to inaccurate signals or even signal loss. Additionally, resistance and phase are significantly impacted by adipose layers. The recent emergence of optically pumped magnetometers introduces a fresh avenue for bio-magnetic field measurement techniques. These magnetometers possess high sensitivity and obviate the need for a cryogenic environment unlike superconducting quantum interference devices (SQUIDs). They detect muscle magnetic field signals in the range of tens to thousands of femtoteslas (fT). The utilization of magnetometers for capturing muscle magnetic field signals remains unaffected by issues of perspiration and adipose layers. Since their introduction, optically pumped atomic magnetometers have found extensive application in exploring the magnetic fields of organs such as cardiac and brain magnetism. The optimal operation of these magnetometers necessitates an environment with an ultra-weak magnetic field. To achieve such an environment, researchers usually utilize a combination of active magnetic compensation technology with passive magnetic shielding technology. Passive magnetic shielding technology uses a magnetic shielding device built with high permeability materials to attenuate the external magnetic field to a few nT. Compared with more layers, the coils that can generate a reverse magnetic field to precisely compensate for the residual magnetic fields are cheaper and more flexible. To attain even lower magnetic fields, compensation coils designed by Biot-Savart law are involved to generate a counteractive magnetic field to eliminate residual magnetic fields. By solving the magnetic field expression of discrete points in the target region, the parameters that determine the current density distribution on the plane can be obtained through the conventional target field method. The current density is obtained from the partial derivative of the stream function, which can be represented by the combination of trigonometric functions. Optimization algorithms in mathematics are introduced into coil design to obtain the optimal current density distribution. A one-dimensional linear regression analysis was performed on the collected data, obtaining a coefficient of determination R2 of 0.9349 with a p-value of 0. This statistical result indicates a stable relationship between the peak-to-peak value (PPV) of the muscle magnetic field signal and the magnitude of grip strength. This system is expected to be a widely used tool for healthcare professionals to gain deeper insights into the muscle health of their patients.

Keywords: muscle magnetic signal, magnetic shielding, compensation coils, trigonometric functions.

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