Search results for: cost of equity capital

Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Huimin Liu, Li Xiang, Yue Liu, Jing Wang

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Background: As one of typical case for the developing countries who are stepping into the aging times globally, more and more older people in China might face the problem of which they could not maintain normal life due to the functional disability. While the government take efforts to build long-term care system and further carry out related policies for the core concept, there is still lack of strong evidence to evaluating the profile of disability states in the elderly population and its transition rate. It has been proved that disability is a dynamic condition of the person rather than irreversible so it means possible to intervene timely on them who might be in a risk of severe disability. Objective: The aim of this study was to depict the picture of the disability transferring status of the older people in China, and then find out individual characteristics that change the state of disability to provide theory basis for disability prevention and early intervention among elderly people. Methods: Data for this study came from the 2011 baseline survey and the 2013 follow-up survey of the China Health and Retirement Longitudinal Study (CHARLS). Normal ADL function, 1~2 ADLs disability,3 or above ADLs disability and death were defined from state 1 to state 4. Multi-state Markov model was applied and the four-state homogeneous model with discrete states and discrete times from two visits follow-up data was constructed to explore factors for various progressive stages. We modeled the effect of explanatory variables on the rates of transition by using a proportional intensities model with covariate, such as gender. Result: In the total sample, state 2 constituent ratio is nearly about 17.0%, while state 3 proportion is blow the former, accounting for 8.5%. Moreover, ADL disability statistics difference is not obvious between two years. About half of the state 2 in 2011 improved to become normal in 2013 even though they get elder. However, state 3 transferred into the proportion of death increased obviously, closed to the proportion back to state 2 or normal functions. From the estimated intensities, we see the older people are eleven times as likely to develop at 1~2 ADLs disability than dying. After disability onset (state 2), progression to state 3 is 30% more likely than recovery. Once in state 3, a mean of 0.76 years is spent before death or recovery. In this model, a typical person in state 2 has a probability of 0.5 of disability-free one year from now while the moderate disabled or above has a probability of 0.14 being dead. Conclusion: On the long-term care cost considerations, preventive programs for delay the disability progression of the elderly could be adopted based on the current disabled state and main factors of each stage. And in general terms, those focusing elderly individuals who are moderate or above disabled should go first.

Keywords: Markov model, elderly people, disability, transition intensity

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Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

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This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

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Authors: P. D. Pedrosa, J. M. A. Rebello, M. P. Cindra Fonseca

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Duplex stainless steels (DSS) exhibit a biphasic microstructure consisting of austenite and delta ferrite. Their high resistance to oxidation, and corrosion, even in H2S containing environments, allied to low cost when compared to conventional stainless steel, are some properties which make this material very attractive for several industrial applications. However, several of these industrial applications imposes cyclic loading to the equipments and in consequence fatigue damage needs to be a concern. A well-known way of improving the fatigue life of a component is by introducing compressive residual stress in its surface. Shot peening is an industrial working process which brings the material directly beneath component surface in a high mechanical compressive state, so inhibiting fatigue crack initiation. However, one must take into account the fact that the cyclic loading itself can reduce and even suppress these residual stresses, thus having undesirable consequences in the process of improving fatigue life by the introduction of compressive residual stresses. In the present work, shot peening was used to introduce residual stresses in several DSS samples. These were thereafter submitted to three different fatigue regimes: low, medium and high cycle fatigue. The evolution of the residual stress during loading were then examined on both surface and subsurface of the samples. It was used the DSS UNS S31803, with microstructure composed of 49% austenite and 51% ferrite. The treatment of shot peening was accomplished by the application of blasting in two Almen intensities of 0.25 and 0.39A. The residual stresses were measured by X-ray diffraction using the double exposure method and a portable equipment with CrK radiation and the (211) diffracting plane for the austenite phase and the (220) plane for the ferrite phase. It is known that residual stresses may arise when two regions of the same material experienced different degrees of plastic deformation. When these regions are separated in respect to each other on a scale that is large compared to the material's microstructure they are called macro stresses. In contrast, microstresses can largely vary over distances which are small comparable to the scale of the material's microstructure and must balance zero between the phases present. In the present work, special attention will be paid to the measurement of residual microstresses. Residual stress measurements were carried out in test pieces submitted to low, medium and high-cycle fatigue, in both longitudinal and transverse direction of the test pieces. It was found that after shot peening, the residual microstress is tensile in the austenite and compressive in the ferrite phases. It was hypothesized that the hardening behavior of the austenite after shot peening was probably due to its higher nitrogen content. Fatigue cycling can effectively change this stress state but this effect was found to be dependent of the shot peening intensity was well as the fatigue range.

Keywords: residual stresses, fatigue, duplex steel, shot peening

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Authors: Zhihua Cao, Hongfei Zhao, Zhongneng Wu

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The development of polar-based agroforestry was necessary due to the influence of the timber market environment in China, which can promote the coordinated development of forestry and agriculture, and gain remarkable ecological, economic and social benefits. The main agroforestry models of the main poplar planting area in Huaibei plain and along the Yangtze River plain were carried out. 11 typical management models of poplar were selected to sum up: pure poplar forest, poplar-rape-soybean, poplar-wheat-soybean, poplar-rape-cotton, poplar-wheat, poplar-chicken, poplar-duck, poplar-sheep, poplar-Agaricus blazei, poplar-oil peony, poplar-fish, represented by M0-M10, respectively. 12 indexes related with economic, ecological and social benefits (annual average cost, net income, ratio of output to investment, payback period of investment, land utilization ratio, utilization ratio of light energy, improvement and system stability of ecological and production environment, product richness, labor capacity, cultural quality of labor force, sustainability) were screened out to carry on the comprehensive evaluation and analysis to 11 kinds of typical agroforestry models based on analytic hierarchy process (AHP). The results showed that the economic benefit of each agroforestry model was in the order of: M8 > M6 > M9 > M7 > M5 > M10 > M4 > M1 > M2 > M3 > M0. The economic benefit of poplar-A. blazei model was the highest (332, 800 RMB / hm²), followed by poplar-duck and poplar-oil peony model (109, 820RMB /hm², 5, 7226 RMB /hm²). The order of comprehensive benefit was: M8 > M4 > M9 > M6 > M1 > M2 > M3 > M7 > M5 > M10 > M0. The economic benefit and comprehensive benefit of each agroforestry model were higher than that of pure poplar forest. The comprehensive benefit of poplar-A. blazei model was the highest, and that of poplar-wheat model ranked second, while its economic benefit was not high. Next were poplar-oil peony and poplar-duck models. It was suggested that the model of poplar-wheat should be adopted in the plain along the Yangtze River, and the whole cycle mode of poplar-grain, popalr-A. blazei, or poplar-oil peony should be adopted in Huaibei plain, northern Anhui. Furthermore, wheat, rape, and soybean are the main crops before the stand was closed; the agroforestry model of edible fungus or Chinese herbal medicine can be carried out when the stand was closed in order to maximize the comprehensive benefit. The purpose of this paper is to provide a reference for forest farmers in the selection of poplar agroforestry model in the future and to provide the basic data for the sustainable and efficient study of poplar agroforestry in Anhui province, eastern China.

Keywords: agroforestry, analytic hierarchy process (AHP), comprehensive benefit, model, poplar

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Authors: Meng Xu, Alexis K. H. Lau, Ming Xu, Bill Barron, Narges Shahraki

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As an emerging unconventional energy, shale gas has been an economically viable step towards a cleaner energy future in U.S. China also has shale resources that are estimated to be potentially the largest in the world. In addition, China has enormous unmet for a clean alternative to substitute coal. Nonetheless, the geological complexity of China’s shale basins and issues of water scarcity potentially impose serious constraints on shale gas development in China. Further, even if China could replicate to a significant degree the U.S. shale gas boom, China faces the problem of transporting the gas efficiently overland with its limited pipeline network throughput capacity and coverage. The aim of this study is to identify the potential bottlenecks in China’s gas transmission network, as well as to examine the shale gas development affecting particular supply locations and demand centers. We examine this through application of three scenarios with projecting domestic shale gas supply by 2020: optimistic, medium and conservative shale gas supply, taking references from the International Energy Agency’s (IEA’s) projections and China’s shale gas development plans. Separately we project the gas demand at provincial level, since shale gas will have more significant impact regionally than nationally. To quantitatively assess each shale gas development scenario, we formulated a gas pipeline optimization model. We used ArcGIS to generate the connectivity parameters and pipeline segment length. Other parameters are collected from provincial “twelfth-five year” plans and “China Oil and Gas Pipeline Atlas”. The multi-objective optimization model uses GAMs and Matlab. It aims to minimize the demands that are unable to be met, while simultaneously seeking to minimize total gas supply and transmission costs. The results indicate that, even if the primary objective is to meet the projected gas demand rather than cost minimization, there’s a shortfall of 9% in meeting total demand under the medium scenario. Comparing the results between the optimistic and medium supply of shale gas scenarios, almost half of the shale gas produced in Sichuan province and Chongqing won’t be able to be transmitted out by pipeline. On the demand side, the Henan province and Shanghai gas demand gap could be filled as much as 82% and 39% respectively, with increased shale gas supply. To conclude, the pipeline network in China is currently not sufficient in meeting the projected natural gas demand in 2020 under medium and optimistic scenarios, indicating the need for substantial pipeline capacity expansion for some of the existing network, and the importance of constructing new pipelines from particular supply to demand sites. If the pipeline constraint is overcame, Beijing, Shanghai, Jiangsu and Henan’s gas demand gap could potentially be filled, and China could thereby reduce almost 25% its dependency on LNG imports under the optimistic scenario.

Keywords: energy policy, energy systematic analysis, scenario analysis, shale gas in China

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Authors: Aneeqa Suhail, Shabana Naveed

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The public sector (in both developed and developing countries) has gone through various waves of radical reforms in recent decades. In Pakistan, under the influence of New Public Management(NPM) Reforms; best practices of private sector are introduced in the public sector to modernize public organizations. Human Resource Information System (HRIS) has been popular in the private sector and proven to be a successful system, therefore it is being adopted in the public sector too. However, implementation of private business practices in public organizations us very challenging due to differences in context. This implementation gets further critical in Pakistan due to a centralizing tendency and lack of autonomy in public organizations. Adoption of HRIS by public organizations in Pakistan raises several questions: What challenges are faced by public organizations in implementation of HRIS? Are benefits of HRIS such as efficiency, process integration and cost reduction achieved? How is the previous system improved with this change and what are the impacts? Yet, it is an under-researched topic, especially in public enterprises. This study contributes to the existing body of knowledge by empirically exploring benefits and challenges of implementation of HRIS in public organizations. The research adopts a case study approach and uses qualitative data based on in-depth interviews conducted at various levels in the hierarchy including top management, departmental heads and employees. The unit of analysis is LESCO, the Lahore Electric Supply Company, a state-owned entity that generates, transmits and distributes electricity to 4 big cities in Punjab, Pakistan. The findings of the study show that LESCO has not achieved the benefits of HRIS as established in literature. The implementation process remained quite slow and costly. Various functions of HR are still in isolation and integration is a big challenge for the organization. Although the data is automated, the previous system of manually record maintenance and paperwork is still in work, resulting in the presence of parallel practices. The findings also identified resistance to change from top management and labor workforce, lack of commitment and technical knowledge, and costly vendors as major barriers that affect the effective implementation of HRIS. The paper suggests some potential actions to overcome these barriers and to enhance effective implementation of HR-technology. The findings are explained in light of an institutional logics perspective. HRIS’ new logic of automated and integrated HR system is in sharp contrast with the prevailing logic of process-oriented manual data maintenance, leading to resistance to change and deadlock.

Keywords: human resource information system, technological changes, state-owned enterprise, implementation challenges

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Authors: T. Kuchukhidze, N. Jalagonia, T. Archuadze, G. Bokuchava

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The growing scientific-technological progress in modern civilization causes actuality of producing construction materials which can successfully work in conditions of high temperature, radiation, pressure, speed, and chemically aggressive environment. Such extreme conditions can withstand very few types of materials and among them, ceramic materials are in the first place. Corundum ceramics is the most useful material for creation of constructive nodes and products of various purposes for its low cost, easy accessibility to raw materials and good combination of physical-chemical properties. However, ceramic composite materials have one disadvantage; they are less plastics and have lower toughness. In order to increase the plasticity, the ceramics are reinforced by various dopants, that reduces the growth of the cracks. It is shown, that adding of even small amount of carbon fibers and carbon nanotubes (CNT) as reinforcing material significantly improves mechanical properties of the products, keeping at the same time advantages of alundum ceramics. Graphene in composite material acts in the same way as inorganic dopants (MgO, ZrO2, SiC and others) and performs the role of aluminum oxide inhibitor, as it creates shell, that gives possibility to reduce sintering temperature and at the same time it acts as damper, because scattering of a shock wave takes place on carbon structures. Application of different structural modification of carbon (graphene, nanotube and others) as reinforced material, gives possibility to create multi-purpose highly requested composite materials based on alundum ceramics. In the present work offers simplified technology for obtaining of aluminum oxide ceramics, reinforced with carbon nanostructures, during which chemical modification with doping carbon nanostructures will be implemented in the process of synthesis of final powdery composite – Alumina. In charge doping carbon nanostructures connected to matrix substance with C-O-Al bonds, that provide their homogeneous spatial distribution. In ceramic obtained as a result of consolidation of such powders carbon fragments equally distributed in the entire matrix of aluminum oxide, that cause increase of bending strength and crack-resistance. The proposed way to prepare the charge simplifies the technological process, decreases energy consumption, synthesis duration and therefore requires less financial expenses. In the implementation of this work, modern instrumental methods were used: electronic and optical microscopy, X-ray structural and granulometric analysis, UV, IR, and Raman spectroscopy.

Keywords: ceramic materials, α-Al₂O₃, carbon nanostructures, composites, characterization, hot-pressing

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Authors: Pantea Salehizadeh, Martin P. Bucknall, Robert Driscoll, Jayashree Arcot, George Srzednicki

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Banana is one of the most important crops produced in large quantities in tropical and sub-tropical countries. Of the total plant material grown, approximately 40% is considered waste and left in the field to decay. This practice allows fungal diseases such as Sigatoka Leaf Spot to develop, limiting plant growth and spreading spores in the air that can cause respiratory problems in the surrounding population. The pseudostem is considered a waste residue of production (60 to 80 tonnes/ha/year), although it is a good source of dietary fiber and volatile organic compounds (VOC’s). Strategies to process banana pseudostem into palatable, nutritious and marketable food materials could provide significant social and economic benefits. Extraction of VOC’s with desirable odor from dried and fresh pseudostem could improve the smell of products from the confectionary and bakery industries. Incorporation of banana pseudostem flour into bakery products could provide cost savings and improve nutritional value. The aim of this study was to determine the effects of drying methods and different banana species on the profile of volatile aroma compounds in dried banana pseudostem. The banana species analyzed were Musa acuminata and Musa balbisiana. Fresh banana pseudostem samples were processed by either freeze-drying (FD) or heat pump drying (HPD). The extraction of VOC’s was performed at ambient temperature using vacuum distillation and the resulting, mostly aqueous, distillates were analyzed using headspace solid phase microextraction (SPME) gas chromatography – mass spectrometry (GC-MS). Optimal SPME adsorption conditions were 50 °C for 60 min using a Supelco 65 μm PDMS/DVB Stableflex fiber1. Compounds were identified by comparison of their electron impact mass spectra with those from the Wiley 9 / NIST 2011 combined mass spectral library. The results showed that the two species have notably different VOC profiles. Both species contained VOC’s that have been established in literature to have pleasant appetizing aromas. These included l-Menthone, D-Limonene, trans-linlool oxide, 1-Nonanol, CIS 6 Nonen-1ol, 2,6 Nonadien-1-ol, Benzenemethanol, 4-methyl, 1-Butanol, 3-methyl, hexanal, 1-Propanol, 2-methyl- acid، 2-Methyl-2-butanol. Results show banana pseudostem VOC’s are better preserved by FD than by HPD. This study is still in progress and should lead to the optimization of processing techniques that would promote the utilization of banana pseudostem in the food industry.

Keywords: heat pump drying, freeze drying, SPME, vacuum distillation, VOC analysis

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Authors: Minji Seo

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Fashion stakeholders are becoming increasingly aware of technological innovation in manufacturing. In 2020, the COVID-19 pandemic caused transformations in working patterns, such as working remotely rather thancommuting. To enable smooth remote working, 3D fashion design software is being adoptedas the latest trend in design and production. The majority of fashion designers, however, are still resistantto this change. Previous studies on 3D fashion design software solely highlighted the beneficial and detrimental factors of adopting design innovations. They lacked research on the relationship between resistance factors and the adoption of innovation. These studies also fell short of exploringthe perspectives of users of these innovations. This paper aims to investigate the key drivers and barriers of employing 3D fashion design software as wellas to explore the challenges faced by designers.It also toucheson the governmental support for digital manufacturing in Seoul, South Korea, and London, the United Kingdom. By conceptualising local support, this study aims to provide a new path for industrial clusters to optimise digital apparel manufacturing. The study uses a mixture of quantitative and qualitative approaches. Initially, it reflects a survey of 350 samples, fashion designers, on innovation resistance factors of 3D fashion design software and the effectiveness of local support. In-depth interviews with 30 participants provide a better understanding of designers’ aspects of the benefits and obstacles of employing 3D fashion design software. The key findings of this research are the main barriers to employing 3D fashion design software in fashion production. The cultural characteristics and interviews resultsare used to interpret the survey results. The findings of quantitative data examine the main resistance factors to adopting design innovations. The dominant obstacles are: the cost of software and its complexity; lack of customers’ interest in innovation; lack of qualified personnel, and lack of knowledge. The main difference between Seoul and London is the attitudes towards government support. Compared to the UK’s fashion designers, South Korean designers emphasise that government support is highly relevant to employing 3D fashion design software. The top-down and bottom-up policy implementation approach distinguishes the perception of government support. Compared to top-down policy approaches in South Korea, British fashion designers based on employing bottom-up approaches are reluctant to receive government support. The findings of this research will contribute to generating solutions for local government and the optimisation of use of 3D fashion design software in fashion industrial clusters.

Keywords: digital apparel production, industrial clusters, innovation resistance, 3D fashion design software, manufacturing, innovation, technology, digital manufacturing, innovative fashion design process

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Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper discusses the recent advances and future prospects of spacecraft position and attitude control using Model Predictive Control (MPC). First, the challenges of the space missions are summarized, in particular, taking into account the errors, uncertainties, and constraints imposed by the mission, spacecraft and, onboard processing capabilities. The summary of space mission errors and uncertainties provided in categories; initial condition errors, unmodeled disturbances, sensor, and actuator errors. These previous constraints are classified into two categories: physical and geometric constraints. Last, real-time implementation capability is discussed regarding the required computation time and the impact of sensor and actuator errors based on the Hardware-In-The-Loop (HIL) experiments. The rationales behind the scenarios’ are also presented in the scope of space applications as formation flying, attitude control, rendezvous and docking, rover steering, and precision landing. The objectives of these missions are explained, and the generic constrained MPC problem formulations are summarized. Three key design elements used in MPC design: the prediction model, the constraints formulation and the objective cost function are discussed. The prediction models can be linear time invariant or time varying depending on the geometry of the orbit, whether it is circular or elliptic. The constraints can be given as linear inequalities for input or output constraints, which can be written in the same form. Moreover, the recent convexification techniques for the non-convex geometrical constraints (i.e., plume impingement, Field-of-View (FOV)) are presented in detail. Next, different objectives are provided in a mathematical framework and explained accordingly. Thirdly, because MPC implementation relies on finding in real-time the solution to constrained optimization problems, computational aspects are also examined. In particular, high-speed implementation capabilities and HIL challenges are presented towards representative space avionics. This covers an analysis of future space processors as well as the requirements of sensors and actuators on the HIL experiments outputs. The HIL tests are investigated for kinematic and dynamic tests where robotic arms and floating robots are used respectively. Eventually, the proposed algorithms and experimental setups are introduced and compared with the authors' previous work and future plans. The paper concludes with a conjecture that MPC paradigm is a promising framework at the crossroads of space applications while could be further advanced based on the challenges mentioned throughout the paper and the unaddressed gap.

Keywords: convex optimization, model predictive control, rendezvous and docking, spacecraft autonomy

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Authors: Jiro Takagi

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Approximately 90 percent of the casualties in the near-fault-type Kobe earthquake in 1995 resulted from the collapse of wooden houses, although a limited number of collapses of this type of building were reported in the more recent off-shore-type Tohoku Earthquake in 2011 (excluding direct damage by the Tsunami). Kumamoto earthquake in 2016 also revealed the vulnerability of old wooden houses in Japan. There are approximately 24.5 million wooden houses in Japan and roughly 40 percent of them are considered to have the inadequate seismic-resisting capacity. Therefore, seismic strengthening of these wooden houses is an urgent task. However, it has not been quickly done for various reasons, including cost and inconvenience during the reinforcing work. Residents typically spend their money on improvements that more directly affect their daily housing environment (such as interior renovation, equipment renewal, and placement of thermal insulation) rather than on strengthening against extremely rare events such as large earthquakes. Considering this tendency of residents, a new approach to developing a seismic strengthening method for wooden houses is needed. The seismic reinforcement method developed in this research uses folded galvanized thin steel plates as both shear walls and the new exterior architectural finish. The existing finish is not removed. Because galvanized steel plates are aesthetic and durable, they are commonly used in modern Japanese buildings on roofs and walls. Residents could feel a physical change through the reinforcement, covering existing exterior walls with steel plates. Also, this exterior reinforcement can be installed with only outdoor work, thereby reducing inconvenience for residents since they would not be required to move out temporarily during construction. The Durability of the exterior is enhanced, and the reinforcing work can be done efficiently since perfect water protection is not required for the new finish. In this method, the entire exterior surface would function as shear walls and thus the pull-out force induced by seismic lateral load would be significantly reduced as compared with a typical reinforcement scheme of adding braces in selected frames. Consequently, reinforcing details of anchors to the foundations would be less difficult. In order to attach the exterior galvanized thin steel plates to the houses, new wooden beams are placed next to the existing beams. In this research, steel connections between the existing and new beams are developed, which contain a gap for the existing finish between the two beams. The thin steel plates are screwed to the new beams and the connecting vertical members. The seismic-resisting performance of the shear walls with thin steel plates is experimentally verified both for the frames and connections. It is confirmed that the performance is high enough for bracing general wooden houses.

Keywords: experiment, seismic reinforcement, thin steel plates, wooden houses

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Authors: Lina Wu

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The excessive discharge of nitrogen in sewage greatly intensifies the eutrophication of water bodies and poses a threat to water quality. Nitrogen pollution control has become a global concern. Currently, the problem of water pollution in China is still not optimistic. As a typical high ammonia nitrogen organic wastewater, landfill leachate is more difficult to treat than domestic sewage because of its complex water quality, high toxicity, and high concentration.Many studies have shown that the autotrophic anammox bacteria in nature can combine nitrous and ammonia nitrogen without carbon source through functional genes to achieve total nitrogen removal, which is very suitable for the removal of nitrogen from leachate. In addition, the process also saves a lot of aeration energy consumption than the traditional nitrogen removal process. Therefore, anammox plays an important role in nitrogen conversion and energy saving. The process composed of short-range nitrification and denitrification coupled an ammo ensures the removal of total nitrogen and improves the removal efficiency, meeting the needs of the society for an ecologically friendly and cost-effective nutrient removal treatment technology. Continuous flow process for treating late leachate [an up-flow anaerobic sludge blanket reactor (UASB), anoxic/oxic (A/O)–anaerobic ammonia oxidation reactor (ANAOR or anammox reactor)] has been developed to achieve autotrophic deep nitrogen removal. In this process, the optimal process parameters such as hydraulic retention time and nitrification flow rate have been obtained, and have been applied to the rapid start-up and stable operation of the process system and high removal efficiency. Besides, finding the characteristics of microbial community during the start-up of anammox process system and analyzing its microbial ecological mechanism provide a basis for the enrichment of anammox microbial community under high environmental stress. One research developed partial nitrification-Anammox (PN/A) using an internal circulation (IC) system and a biological aerated filter (BAF) biofilm reactor (IBBR), where the amount of water treated is closer to that of landfill leachate. However, new high-throughput sequencing technology is still required to be utilized to analyze the changes of microbial diversity of this system, related functional genera and functional genes under optimal conditions, providing theoretical and further practical basis for the engineering application of novel anammox system in biogas slurry treatment and resource utilization.

Keywords: nutrient removal and recovery, leachate, anammox, partial nitrification

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Authors: Saurabh Sharma, Yong Sun, Bruce Vernham

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Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O₂ concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO₂/NOx ratio etc.

Keywords: diesel engine, machine learning, NOₓ emission, semi-empirical

Procedia PDF Downloads 96

Authors: Peter Burggräf, Matthias Dannapfel, Hanno Voet, Patrick-Benjamin Bök, Jérôme Uelpenich, Julian Hoppe

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The increasing digitalization of value chains can help companies to handle rising complexity in their processes and thereby reduce the steadily increasing planning and control effort in order to raise performance limits. Due to technological advances, companies face the challenge of smart value chains for the purpose of improvements in productivity, handling the increasing time and cost pressure and the need of individualized production. Therefore, companies need to ensure quick and flexible decisions to create self-optimizing processes and, consequently, to make their production more efficient. Lean production, as the most commonly used paradigm for complexity reduction, reaches its limits when it comes to variant flexible production and constantly changing market and environmental conditions. To lift performance limits, which are inbuilt in current value chains, new methods and tools must be applied. Digitalization provides the potential to derive these new methods and tools. However, companies lack the experience to harmonize different digital technologies. There is no practicable framework, which instructs the transformation of current value chains into digital pervasive value chains. Current research shows that a connection between lean production and digitalization exists. This link is based on factors such as people, technology and organization. In this paper, the introduced method for the determination of digitally pervasive value chains takes the factors people, technology and organization into account and extends existing approaches by a new dimension. It is the first systematic approach for the digital transformation of lean production and consists of four steps: The first step of ‘target definition’ describes the target situation and defines the depth of the analysis with regards to the inspection area and the level of detail. The second step of ‘analysis of the value chain’ verifies the lean-ability of processes and lies in a special focus on the integration capacity of digital technologies in order to raise the limits of lean production. Furthermore, the ‘digital evaluation process’ ensures the usefulness of digital adaptions regarding their practicability and their integrability into the existing production system. Finally, the method defines actions to be performed based on the evaluation process and in accordance with the target situation. As a result, the validation and optimization of the proposed method in a German company from the electronics industry shows that the digital transformation of current value chains based on lean production achieves a raise of their inbuilt performance limits.

Keywords: digitalization, digital transformation, Industrie 4.0, lean production, value chain

Procedia PDF Downloads 290

Authors: Sahar Heidary

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Radiography and radiotherapy have emerged as crucial pillars of modern medical practice, revolutionizing diagnostics and treatment for a myriad of health conditions. This abstract highlights the pivotal role of radiography and radiotherapy in favor of healthcare and society. Radiography, a non-invasive imaging technique, has significantly advanced medical diagnostics by enabling the visualization of internal structures and abnormalities within the human body. With the advent of digital radiography, clinicians can obtain high-resolution images promptly, leading to faster diagnoses and informed treatment decisions. Radiography plays a pivotal role in detecting fractures, tumors, infections, and various other conditions, allowing for timely interventions and improved patient outcomes. Moreover, its widespread accessibility and cost-effectiveness make it an indispensable tool in healthcare settings worldwide. On the other hand, radiotherapy, a branch of medical science that utilizes high-energy radiation, has become an integral component of cancer treatment and management. By precisely targeting and damaging cancerous cells, radiotherapy offers a potent strategy to control tumor growth and, in many cases, leads to cancer eradication. Additionally, radiotherapy is often used in combination with surgery and chemotherapy, providing a multifaceted approach to combat cancer comprehensively. The continuous advancements in radiotherapy techniques, such as intensity-modulated radiotherapy and stereotactic radiosurgery, have further improved treatment precision while minimizing damage to surrounding healthy tissues. Furthermore, radiography and radiotherapy have demonstrated their worth beyond oncology. Radiography is instrumental in guiding various medical procedures, including catheter placement, joint injections, and dental evaluations, reducing complications and enhancing procedural accuracy. On the other hand, radiotherapy finds applications in non-cancerous conditions like benign tumors, vascular malformations, and certain neurological disorders, offering therapeutic options for patients who may not benefit from traditional surgical interventions. In conclusion, radiography and radiotherapy stand as indispensable tools in modern medicine, driving transformative improvements in patient care and treatment outcomes. Their ability to diagnose, treat, and manage a wide array of medical conditions underscores their favor in medical practice. As technology continues to advance, radiography and radiotherapy will undoubtedly play an ever more significant role in shaping the future of healthcare, ultimately saving lives and enhancing the quality of life for countless individuals worldwide.

Keywords: radiology, radiotherapy, medical imaging, cancer treatment

Procedia PDF Downloads 49

Authors: Archil Undilashvili, Ketevan Stvilia, Dustin Gilbreath, Giorgi Dzneladze, Gordon Charchward

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Introduction: In recent years, diverse types of wheelchairs, both local production and imported, have been made available on the Georgian market for wheelchair users. Some types of wheelchairs are sold together with a service package, while the others, including the State Program, Supported locally-produced ones, don’t provide adjustment and maintenance service packages to users. Within the USAID Physical Rehabilitation Project in Georgia, a study was conducted to assess the impact of the wheelchair service provision in line with the WHO guidelines on the health and overall satisfaction of wheelchair users in Georgia. Methodology: A cross-sectional survey was conducted in May 2021. A structured questionnaire was used for telephone interviews that, along with socio-demographic characteristics, included questions for assessment of accessibility, availability, timeliness, cost and quality of wheelchair services received. Out of 1060 individuals listed in the census of wheelchair users, 752 were available for interview, with an actual response rate of 73.4%. 552 wheelchair users (31%) or their caregivers (69%) agreed to participate in the survey. In addition to using descriptive statistics, the study used multivariate matching of wheelchair users who received wheelchair services and who did not (control group). In addition, to evaluate satisfaction with service provision, respondents were asked to assess services. Findings: The majority (67%) of wheelchair users included in the survey were male. The average age of participants was 43. The three most frequently named reasons for using a wheelchair were cerebral palsy (29%), followed by stroke (18%), and amputation (12%). Users have had their current chair for four years on average. Overall, 60% of respondents reported that they were assessed before providing a wheelchair, but only half of them reported that their preferences and needs were considered. Only 13% of respondents had services in line with WHO guidelines and only 22% of wheelchair users had training when they received their current chair. 16% of participants said they had follow-up services, and 41% received adjustment services after receiving the chair. A slight majority (56%) of participants were satisfied with the quality of service provision and the service provision overall. Similarly, 55% were satisfied with the accessibility of service provision. A slightly larger majority (61%) were satisfied with the timeliness of service provision. The matching analysis suggests that users that received services in line with WHO guidelines were more satisfied with their chairs (the difference 17 point/0-100 scale) and they were four percentage points less likely to have health problems attributed to the chair. The regression analysis provides a similar finding of a 21 point increase in satisfaction attributable to services. Conclusion: The provision of wheelchair services in line with WHO guidelines and with follow-up services is likely to have a positive impact on the daily lives of wheelchair users in Georgia. Wheelchair services should be institutionalized as a standard component of wheelchair provision in Georgia.

Keywords: physical rehabilitation, wheelchair users, persons with disabilities, wheelchair production

Procedia PDF Downloads 86

Authors: Honey Bryant, Elvina Chu

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Stroke is the leading cause of disability in adults in Canada and directly related to depression, anxiety, and sleep disorders; with an estimated annual cost of $50 billion in health care. Strokes not only impact the individual but society as a whole. Current stroke rehabilitation does not include Music Therapy, although it has success in clinical research in the use of stroke rehabilitation. This study examines the use of neurologic music therapy (NMT) in conjunction with stroke rehabilitation to improve sleep quality, reduce stress levels, and promote neurogenesis. Existing research on NMT in stroke is limited, which means any conclusive information gathered during this study will be significant. My novel hypotheses are a.) stroke patients will become less depressed and less anxious with improved sleep following NMT. b.) NMT will reduce stress levels and promote neurogenesis in stroke patients admitted for rehabilitation. c.) Beneficial effects of NMT will be sustained at least short-term following treatment. Participants were recruited from the in-patient stroke rehabilitation program at Providence Care Hospital in Kingston, Ontario, Canada. All participants-maintained stroke rehabilitation treatment as normal. The study was spilt into two groups, the first being Passive Music Listening (PML) and the second Neurologic Music Therapy (NMT). Each group underwent 10 sessions of intensive music therapy lasting 45 minutes for 10 consecutive days, excluding weekends. Psychiatric Assessments, Epworth Sleepiness Scale (ESS), Hospital Anxiety & Depression Rating Scale (HADS), and Music Engagement Questionnaire (MusEQ), were completed, followed by a general feedback interview. Physiological markers of stress were measured through blood pressure measurements and heart rate variability. Serum collections reviewed neurogenesis via Brain-derived neurotrophic factor (BDNF) and stress markers of cortisol levels. As this study is still on-going, a formal analysis of data has not been fully completed, although trends are following our hypotheses. A decrease in sleepiness and anxiety is seen upon the first cohort of PML. Feedback interviews have indicated most participants subjectively felt more relaxed and thought PML was useful in their recovery. If the hypothesis is supported, larger external funding which will allow for greater investigation of the use of NMT in stroke rehabilitation. As we know, NMT is not covered under Ontario Health Insurance Plan (OHIP), so there is limited scientific data surrounding its uses as a clinical tool. This research will provide detailed findings of the treatment of neuropsychiatric aspects of stroke. Concurrently, a passive music listening study is being designed to further review the use of PML in rehabilitation as well.

Keywords: music therapy, psychotherapy, neurologic music therapy, passive music listening, neuropsychiatry, counselling, behavioural, stroke, stroke rehabilitation, rehabilitation, neuroscience

Procedia PDF Downloads 90

Authors: Enrico Dorigatti

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The growing pile of hazardous e-waste produced especially by those developed and wealthy countries gets relentlessly bigger, composed of the EEDs (Electric and Electronic Device) that are often thrown away although still well functioning, mainly due to (programmed) obsolescence. As a consequence, e-waste has taken, over the last years, the shape of a frightful, uncontrollable, and unstoppable phenomenon, mainly fuelled by market policies aiming to maximize sales—and thus profits—at any cost. Against it, governments and organizations put some efforts in developing ambitious frameworks and policies aiming to regulate, in some cases, the whole lifecycle of EEDs—from the design to the recycling. Incidentally, however, such regulations sometimes make the disposal of the devices economically unprofitable, which often translates into growing illegal e-waste trafficking—an activity usually undertaken by criminal organizations. It seems that nothing, at least in the near future, can stop the phenomenon of e-waste production and accumulation. But while, from a practical standpoint, a solution seems hard to find, much can be done regarding people's education, which translates into informing and promoting good practices such as reusing and repurposing. This research argues that circuit bending—an activity rooted in neo-materialist philosophy and post-digital aesthetic, and based on repurposing EEDs into novel music instruments and sound generators—could have a great potential in this. In particular, it asserts that circuit bending could expose ecological, environmental, and social criticalities related to the current market policies and economic model. Not only thanks to its practical side (e.g., sourcing and repurposing devices) but also to the artistic one (e.g., employing bent instruments for ecological-aware installations, performances). Currently, relevant literature and debate lack interest and information about the ecological aspects and implications of the practical and artistic sides of circuit bending. This research, therefore, although still at an early stage, aims to fill in this gap by investigating, on the one side, the ecologic potential of circuit bending and, on the other side, its capacity of sensitizing people, through artistic practice, about e-waste-related issues. The methodology will articulate in three main steps. Firstly, field research will be undertaken—with the purpose of understanding where and how to source, in an ecologic and sustainable way, (discarded) EEDs for circuit bending. Secondly, artistic installations and performances will be organized—to sensitize the audience about environmental concerns through sound art and music derived from bent instruments. Data, such as audiences' feedback, will be collected at this stage. The last step will consist in realising workshops to spread an ecologically-aware circuit bending practice. Additionally, all the data and findings collected will be made available and disseminated as resources.

Keywords: circuit bending, ecology, sound art, sustainability

Procedia PDF Downloads 147

Authors: Milos Beran, Josef Drahorad, Ondrej Vltavsky, Martin Fronek, Jiri Sova

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While most nanofibers are produced using electrospinning, this technique suffers from several drawbacks, such as the requirement for specialized equipment, high electrical potential, and electrically conductive targets. Consequently, recent years have seen the increasing emergence of novel strategies in generating nanofibers in a larger scale and higher throughput manner. The centrifugal spinning is simple, cheap and highly productive technology for nanofiber production. In principle, the drawing of solution filament into nanofibers using centrifugal spinning is achieved through the controlled manipulation of centrifugal force, viscoelasticity, and mass transfer characteristics of the spinning solutions. Engineering efforts of researches of the Food research institute Prague and the Czech Technical University in the field the centrifugal nozzleless spinning led to introduction of a pilot plant demonstrator NANOCENT. The main advantages of the demonstrator are lower investment cost - thanks to simpler construction compared to widely used electrospinning equipments, higher production speed, new application possibilities and easy maintenance. The centrifugal nozzleless spinning is especially suitable to produce submicron fibers from polymeric solutions in highly volatile solvents, such as chloroform, DCM, THF, or acetone. To date, submicron fibers have been prepared from PS, PUR and biodegradable polyesters, such as PHB, PLA, PCL, or PBS. The products are in form of 3D structures or nanofiber membranes. Unique self-supporting nanofiber membranes were prepared from the biodegradable polyesters in different mixtures. The nanofiber membranes have been tested for different applications. Filtration efficiencies for water solutions and aerosols in air were evaluated. Different active inserts were added to the solutions before the spinning process, such as inorganic nanoparticles, organic precursors of metal oxides, antimicrobial and wound healing compounds or photocatalytic phthalocyanines. Sintering can be subsequently carried out to remove the polymeric material and transfer the organic precursors to metal oxides, such as Si02, or photocatalytic Zn02 and Ti02, to obtain inorganic nanofibers. Electrospinning is more suitable technology to produce membranes for the filtration applications than the centrifugal nozzleless spinning, because of the formation of more homogenous nanofiber layers and fibers with smaller diameters. The self-supporting nanofiber membranes prepared from the biodegradable polyesters are especially suitable for medical applications, such as wound or burn healing dressings or tissue engineering scaffolds. This work was supported by the research grants TH03020466 of the Technology Agency of the Czech Republic.

Keywords: polymeric nanofibers, self-supporting nanofiber membranes, biodegradable polyesters, active inserts

Procedia PDF Downloads 151

Authors: Tessa E. Reid, Vanessa N. Kavamura, Maider Abadie, Adriana Torres-Ballesteros, Mark Pawlett, Ian M. Clark, Jim Harris, Tim Mauchline

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The deleterious effect of chemical fertilizer on rhizobacterial diversity has been well documented using 16S rRNA gene amplicon sequencing and predictive metagenomics. Biofertilization is a cost-effective and sustainable alternative; improving strategies depends on isolating beneficial soil microorganisms. Although culturing is widespread in biofertilization, it is unknown whether the composition of cultured isolates closely mirrors native beneficial rhizobacterial populations. This study aimed to determine the relative abundance of culturable plant growth-promoting rhizobacteria (PGPR) isolates within total soil DNA and how potential PGPR populations respond to chemical fertilization in a commercial wheat variety. It was hypothesized that PGPR will be reduced in fertilized relative to unfertilized wheat. Triticum aestivum cv. Cadenza seeds were sown in a nutrient depleted agricultural soil in pots treated with and without nitrogen-phosphorous-potassium (NPK) fertilizer. Rhizosphere and rhizoplane samples were collected at flowering stage (10 weeks) and analyzed by culture-independent (amplicon sequence variance (ASV) analysis of total rhizobacterial DNA) and -dependent (isolation using growth media) techniques. Rhizosphere- and rhizoplane-derived microbiota culture collections were tested for plant growth-promoting traits using functional bioassays. In general, fertilizer addition decreased the proportion of nutrient-solubilizing bacteria (nitrate, phosphate, potassium, iron and, zinc) isolated from rhizocompartments in wheat, whereas salt tolerant bacteria were not affected. A PGPR database was created from isolate 16S rRNA gene sequences and searched against total soil DNA, revealing that 1.52% of total community ASVs were identified as culturable PGPR isolates. Bioassays identified a higher proportion of PGPR in non-fertilized samples (rhizosphere (49%) and rhizoplane (91%)) compared to fertilized samples (rhizosphere (21%) and rhizoplane (19%)) which constituted approximately 1.95% and 1.25% in non-fertilized and fertilized total community DNA, respectively. The analyses of 16S rRNA genes and deduced functional profiles provide an in-depth understanding of the responses of bacterial communities to fertilizer; this study suggests that rhizobacteria, which potentially benefit plants by mobilizing insoluble nutrients in soil, are reduced by chemical fertilizer addition. This knowledge will benefit the development of more targeted biofertilization strategies.

Keywords: bacteria, fertilizer, microbiome, rhizoplane, rhizosphere

Procedia PDF Downloads 286

Authors: Sina Moradi, Christopher W. K. Chow, John Van Leeuwen, David Cook, Mary Drikas, Patrick Hayde, Rose Amal

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Chloramine is commonly used as a disinfectant in drinking water distribution systems (DWDSs), particularly in Australia and the USA. Maintaining a chloramine residual throughout the DWDS is important in ensuring microbiologically safe water is supplied at the customer’s tap. In order to simulate how chloramine behaves when it moves through the distribution system, a water quality network model (WQNM) can be applied. In this work, the WQNM was based on mono-chloramine decomposition reactions, which enabled prediction of mono-chloramine residual at different locations through a DWDS in Australia, using the Bentley commercial hydraulic package (Water GEMS). The accuracy of WQNM predictions is influenced by a number of water quality parameters. Optimization of these parameters in order to obtain the closest results in comparison with actual measured data in a real DWDS would result in both cost reduction as well as reduction in consumption of valuable resources such as energy and materials. In this work, the optimum operating conditions of water quality parameters (i.e. temperature, pH, and initial mono-chloramine concentration) to maximize the accuracy of mono-chloramine residual predictions for two water supply scenarios in an entire network were determined using response surface methodology (RSM). To obtain feasible and economical water quality parameters for highest model predictability, Design Expert 8.0 software (Stat-Ease, Inc.) was applied to conduct the optimization of three independent water quality parameters. High and low levels of the water quality parameters were considered, inevitably, as explicit constraints, in order to avoid extrapolation. The independent variables were pH, temperature and initial mono-chloramine concentration. The lower and upper limits of each variable for two water supply scenarios were defined and the experimental levels for each variable were selected based on the actual conditions in studied DWDS. It was found that at pH of 7.75, temperature of 34.16 ºC, and initial mono-chloramine concentration of 3.89 (mg/L) during peak water supply patterns, root mean square error (RMSE) of WQNM for the whole network would be minimized to 0.189, and the optimum conditions for averaged water supply occurred at pH of 7.71, temperature of 18.12 ºC, and initial mono-chloramine concentration of 4.60 (mg/L). The proposed methodology to predict mono-chloramine residual can have a great potential for water treatment plant operators in accurately estimating the mono-chloramine residual through a water distribution network. Additional studies from other water distribution systems are warranted to confirm the applicability of the proposed methodology for other water samples.

Keywords: chloramine decay, modelling, response surface methodology, water quality parameters

Procedia PDF Downloads 206

Authors: Debjit Ray

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Horizontal gene transfer (HGT) and recombination leads to the emergence of bacterial antibiotic resistance and pathogenic traits. HGT events can be identified by comparing a large number of fully sequenced genomes across a species or genus, define the phylogenetic range of HGT, and find potential sources of new resistance genes. In-depth comparative phylogenomics can also identify subtle genome or plasmid structural changes or mutations associated with phenotypic changes. Comparative phylogenomics requires that accurately sequenced, complete and properly annotated genomes of the organism. Assembling closed genomes requires additional mate-pair reads or “long read” sequencing data to accompany short-read paired-end data. To bring down the cost and time required of producing assembled genomes and annotating genome features that inform drug resistance and pathogenicity, we are analyzing the performance for genome assembly of data from the Illumina NextSeq, which has faster throughput than the Illumina HiSeq (~1-2 days versus ~1 week), and shorter reads (150bp paired-end versus 300bp paired end) but higher capacity (150-400M reads per run versus ~5-15M) compared to the Illumina MiSeq. Bioinformatics improvements are also needed to make rapid, routine production of complete genomes a reality. Modern assemblers such as SPAdes 3.6.0 running on a standard Linux blade are capable in a few hours of converting mixes of reads from different library preps into high-quality assemblies with only a few gaps. Remaining breaks in scaffolds are generally due to repeats (e.g., rRNA genes) are addressed by our software for gap closure techniques, that avoid custom PCR or targeted sequencing. Our goal is to improve the understanding of emergence of pathogenesis using sequencing, comparative genomics, and machine learning analysis of ~1000 pathogen genomes. Machine learning algorithms will be used to digest the diverse features (change in virulence genes, recombination, horizontal gene transfer, patient diagnostics). Temporal data and evolutionary models can thus determine whether the origin of a particular isolate is likely to have been from the environment (could it have evolved from previous isolates). It can be useful for comparing differences in virulence along or across the tree. More intriguing, it can test whether there is a direction to virulence strength. This would open new avenues in the prediction of uncharacterized clinical bugs and multidrug resistance evolution and pathogen emergence.

Keywords: genomics, pathogens, genome assembly, superbugs

Procedia PDF Downloads 181

Authors: Afnan Al-Romi, Iman Al-Momani

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The urge of applying the Software Engineering (SE) processes is both of vital importance and a key feature in critical, complex large-scale systems, for example, safety systems, security service systems, and network systems. Inevitably, associated with this are risks, such as system vulnerabilities and security threats. The probability of those risks increases in unsecured environments, such as wireless networks in general and in Wireless Sensor Networks (WSNs) in particular. WSN is a self-organizing network of sensor nodes connected by wireless links. WSNs consist of hundreds to thousands of low-power, low-cost, multi-function sensor nodes that are small in size and communicate over short-ranges. The distribution of sensor nodes in an open environment that could be unattended in addition to the resource constraints in terms of processing, storage and power, make such networks in stringent limitations such as lifetime (i.e. period of operation) and security. The importance of WSN applications that could be found in many militaries and civilian aspects has drawn the attention of many researchers to consider its security. To address this important issue and overcome one of the main challenges of WSNs, security solution systems have been developed by researchers. Those solutions are software-based network Intrusion Detection Systems (IDSs). However, it has been witnessed, that those developed IDSs are neither secure enough nor accurate to detect all malicious behaviours of attacks. Thus, the problem is the lack of coverage of all malicious behaviours in proposed IDSs, leading to unpleasant results, such as delays in the detection process, low detection accuracy, or even worse, leading to detection failure, as illustrated in the previous studies. Also, another problem is energy consumption in WSNs caused by IDS. So, in other words, not all requirements are implemented then traced. Moreover, neither all requirements are identified nor satisfied, as for some requirements have been compromised. The drawbacks in the current IDS are due to not following structured software development processes by researches and developers when developing IDS. Consequently, they resulted in inadequate requirement management, process, validation, and verification of requirements quality. Unfortunately, WSN and SE research communities have been mostly impermeable to each other. Integrating SE and WSNs is a real subject that will be expanded as technology evolves and spreads in industrial applications. Therefore, this paper will study the importance of Requirement Engineering when developing IDSs. Also, it will study a set of existed IDSs and illustrate the absence of Requirement Engineering and its effect. Then conclusions are drawn in regard of applying requirement engineering to systems to deliver the required functionalities, with respect to operational constraints, within an acceptable level of performance, accuracy and reliability.

Keywords: software engineering, requirement engineering, Intrusion Detection System, IDS, Wireless Sensor Networks, WSN

Procedia PDF Downloads 304

Authors: Rabindranath Jana, Biswajit Maity, Keka Rana

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The most promising clean energy source is the fuel cell, since it does not generate toxic gases and other hazardous compounds. Again the direct methanol fuel cell (DMFC) is more user-friendly as it is easy to be miniaturized and suited as energy source for automobiles as well as domestic applications and portable devices. And unlike the hydrogen used for some fuel cells, methanol is a liquid that is easy to store and transport in conventional tanks. The most important part of a fuel cell is its membrane. Till now, an overall efficiency for a methanol fuel cell is reported to be about 20 ~ 25%. The lower efficiency of the cell may be due to the critical factors, e.g. slow reaction kinetics at the anode and methanol crossover. The oxidation of methanol is composed of a series of successive reactions creating formaldehyde and formic acid as intermediates that contribute to slow reaction rates and decreased cell voltage. Currently, the investigation of new anode catalysts to improve oxidation reaction rates is an active area of research as it applies to the methanol fuel cell. Surprisingly, there are very limited reports on nanostructured membranes, which are rather simple to manufacture with different tuneable compositions and are expected to allow only the proton permeation but not the methanol due to their molecular sizing effects and affinity to the membrane surface. We have developed a nanostructured fuel cell membrane from polydimethyl siloxane rubber (PDMS), ethylene methyl co-acrylate (EMA) and multi-walled carbon nanotubes (MWNTs). The effect of incorporating different proportions of f-MWNTs in polymer membrane has been studied. The introduction of f-MWNTs in polymer matrix modified the polymer structure, and therefore the properties of the device. The proton conductivity, measured by an AC impedance technique using open-frame and two-electrode cell and methanol permeability of the membranes was found to be dependent on the f-MWNTs loading. The proton conductivity of the membranes increases with increase in concentration of f-MWNTs concentration due to increased content of conductive materials. Measured methanol permeabilities at 60oC were found to be dependant on loading of f-MWNTs. The methanol permeability decreased from 1.5 x 10-6 cm²/s for pure film to 0.8 x 10-7 cm²/s for a membrane containing 0.5wt % f-MWNTs. This is due to increasing proportion of f-MWNTs, the matrix becomes more compact. From DSC melting curves it is clear that the polymer matrix with f-MWNTs is thermally stable. FT-IR studies show good interaction between EMA and f-MWNTs. XRD analysis shows good crystalline behavior of the prepared membranes. Significant cost savings can be achieved when using the blended films which contain less expensive polymers.

Keywords: fuel cell membrane, polydimethyl siloxane rubber, carbon nanotubes, proton conductivity, methanol permeability

Procedia PDF Downloads 399

Authors: Deborah Bailey-Rodriguez, Maria Paula Valdivieso Rueda, Gemma Reynolds

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In recent years, the mental health of Higher Education (HE) students has been a growing concern. This has been further exacerbated by the stresses associated with the Covid-19 pandemic, placing students at even greater risk of developing mental health issues. Support available to students in HE tends to follow an established and traditional route. The demands for counseling services have grown, not only with the increase in student numbers but with the number of students seeking support for mental health issues, with 94% of HE institutions recently reporting an increase in the need for counseling services. One way of improving the well-being and mental health of HE students is through the use of brief interventions, such as expressive writing (EW). This intervention involves encouraging individuals to write continuously for at least 15-20 minutes for three to five sessions (often on consecutive days) about their deepest thoughts and feelings to explore significant personal experiences in a meaningful way. Given the brevity, simplicity and cost-effectiveness of EW, this intervention has considerable potential as an intervention for HE populations. The current study, therefore, employed a mixed-methods design to explore the effectiveness of EW in reducing anxiety, general stress, academic stress and depression in HE students while improving well-being. HE students at MDX were randomly assigned to one of three conditions: (1) The UniExp-EW group was required to write about their emotions and thoughts about any stressors they have faced that are directly relevant to their university experience (2) The NonUniExp-EW group was required to write about their emotions and thoughts about any stressors that are NOT directly relevant to their university experience, and (3) The Control group were required to write about how they spent their weekend, with no reference to thoughts or emotions, and without thinking about university. Participants were required to carry out the EW intervention for 15 minutes per day for four consecutive days. Baseline mental health and well-being measures were taken before the intervention via a battery of standardized questionnaires. Following completion of the intervention on day four, participants were required to complete the questionnaires a second time and again one week later. Participants were also invited to attend focus groups to discuss their experience of the intervention. This will allow an in-depth investigation into students’ perceptions of EW as an effective intervention to determine whether they would choose to use this intervention in the future. Preliminary findings will be discussed at the conference as well as a discussion of the important implications of the findings. The study is fundamental because if EW is an effective intervention for improving mental health and well-being in HE students, its brevity and simplicity mean it can be easily implemented and can be freely available to students. Improving the mental health and well-being of HE students can have knock-on implications for improving academic skills and career development.

Keywords: expressive writing, higher education, psychology in education, mixed-methods, mental health, academic stress

Procedia PDF Downloads 51

Authors: Manuel Branco

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This paper argues that mainstream economics is one of the reasons that can explain the difficulty in fully realizing human rights because its logic is intrinsically contradictory to human rights, most especially economic, social and cultural rights. First, its utilitarianism, both in its cardinal and ordinal understanding, contradicts human rights principles. Maximizing aggregate utility along the lines of cardinal utility is a theoretical exercise that consists in ensuring as much as possible that gains outweigh losses in society. In this process an individual may get worse off, though. If mainstream logic is comfortable with this, human rights' logic does not. Indeed, universality is a key principle in human rights and for this reason the maximization exercise should aim at satisfying all citizens’ requests when goods and services necessary to secure human rights are at stake. The ordinal version of utilitarianism, in turn, contradicts the human rights principle of indivisibility. Contrary to ordinal utility theory that ranks baskets of goods, human rights do not accept ranking when these goods and services are necessary to secure human rights. Second, by relying preferably on market logic to allocate goods and services, mainstream economics contradicts human rights because the intermediation of money prices and the purpose of profit may cause exclusion, thus compromising the principle of universality. Finally, mainstream economics sees human rights mainly as constraints to the development of its logic. According to this view securing human rights would, then, be considered a cost weighing on economic efficiency and, therefore, something to be minimized. Fully realizing human rights needs, therefore, a different approach. This paper discusses a human rights-based political economy. This political economy, among other characteristics should give up mainstream economics narrow utilitarian approach, give up its belief that market logic should guide all exchanges of goods and services between human beings, and finally give up its view of human rights as constraints on rational choice and consequently on good economic performance. Giving up mainstream’s narrow utilitarian approach means, first embracing procedural utility and human rights-aimed consequentialism. Second, a more radical break can be imagined; non-utilitarian, or even anti-utilitarian, approaches may emerge, then, as alternatives, these two standpoints being not necessarily mutually exclusive, though. Giving up market exclusivity means embracing decommodification. More specifically, this means an approach that takes into consideration the value produced outside the market and an allocation process no longer necessarily centered on money prices. Giving up the view of human rights as constraints means, finally, to consider human rights as an expression of wellbeing and a manifestation of choice. This means, in turn, an approach that uses indicators of economic performance other than growth at the macro level and profit at the micro level, because what we measure affects what we do.

Keywords: economic and social rights, political economy, economic theory, markets

Procedia PDF Downloads 134

Authors: J. Woźniak-Holecka, T. Holecki, S. Jaruga

Abstract:

Spa treatment is an important area of the health care system in Poland due to the increasing needs of the population and the context of historical conditions for this form of therapy. It extends the range of financing possibilities of the outlets and increases the potential of spa services, which is very important in the context of demographic and epidemiological changes. The main advantages of spa treatment services include its relatively wide availability, low risk of side effects, good patient tolerance, long-lasting curative effect and a relatively low cost. In addition, patients should be provided with a proper diet and enable participation in health education and health promotion classes aimed at health problems consistent with the treatment profile. Challenges for global health care systems include a sharp increase in spending on benefits, dynamic development of health technologies and growing social expectations. This requires extending the competences of health resort facilities for health promotion. Within each type of health resort institutions in Poland, nutritional education services are implemented, aimed at creating and consolidating proper eating habits. Choosing the right diet can speed up recovery or become one of the methods to alleviate the symptoms of chronic diseases. During spa treatment patient learns the principles of rational nutrition and adequate dietotherapy to his diseases. The aim of the project is to assess the frequency and quality of nutritional education provided to patients in health resort facilities in a nationwide perspective. The material for the study will be data obtained as part of an in-depth interview conducted among Heads of Nutrition Departments of selected institutions. The use of nutritional education in a health resort may be an important goal of implementing the state health policy as a useful tool to reduce the risk of diet-related diseases. Recognizing nutritional education in health resort institutions as a type of full-value health service can be effective system support for health policy, including seniors, due to demographic changes currently occurring in the Polish population. Furthermore, it is necessary to increase the interest and motivation of patients to follow the recommendations of nutritional education, because it will bring tangible benefits for the long-term effects of therapy and care should be taken for the form and methodology of nutrition education implemented in health resort institutions. Finally it is necessary to construct an educational offer in terms of selected groups of patients with the highest health needs: the elderly and the disabled. In conclusion, it can be said that the system of nutritional education implemented in polish health resort institutions should be subjected to global changes and strong systemic correction.

Keywords: health care system, nutritional education, public health, spa and treatment

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Authors: Maria Amaia Iza Padilla, Ibai Ostolozaga

Abstract:

The objective of this paper is to analyze how transportation costs between regions within a country can affect not only domestic trade but also the allocation of resources in a given region, aggregate productivity, and relative domestic prices (tradable versus non-tradable). On the one hand, there is a vast literature that analyzes the transportation costs faced by countries when trading with the rest of the world. However, this paper focuses on the effect of transportation costs on domestic trade. Countries differ in their domestic road infrastructure and transport quality. There is also some literature that focuses on the effect of road infrastructure on the price difference between regions but not on relative prices at the aggregate level. On the other hand, this work is also related to the literature on resource misallocation. Finally, the paper is also related to the literature analyzing the effect of trade on the development of the manufacturing sector. Using the World Bank Enterprise Survey database, it is observed cross-country differences in the proportion of firms that consider transportation as an obstacle. From the International Comparison Program, we obtain a significant negative correlation between GDP per worker and relative prices (manufacturing sector prices relative to the service sector). Furthermore, there is a significant negative correlation between a country’s transportation quality and the relative price of manufactured goods with respect to the price of services in that country. This is consistent with the empirical evidence of a negative correlation between transportation quality and GDP per worker, on the one hand, and the negative correlation between GDP per worker and domestic relative prices, on the other. It is also shown that in a country, the share of manufacturing firms whose main market is at the local (regional) level is negatively related to the quality of the transportation infrastructure within the country. Similarly, this index is positively related to the share of manufacturing firms whose main market is national or international. The data also shows that those countries with a higher proportion of manufacturing firms operating locally have higher relative prices. With this information in hand, the paper attempts to quantify the effects of the allocation of resources between and within sectors. The higher the trade barriers caused by transportation costs, the less efficient allocation, which causes lower aggregate productivity. Second, it is built a two-sector model where regions within a country trade with each other. On the one hand, it is found that with respect to the manufacturing sector, those countries with less trade between their regions will be characterized by a smaller variety of goods, less productive manufacturing firms on average, and higher relative prices for manufactured goods relative to service sector prices. Thus, the decline in the relative price of manufactured goods in more advanced countries could also be explained by the degree of trade between regions. This trade allows for efficient intra-industry allocation (traders are more productive, and resources are allocated more efficiently)).

Keywords: misallocation, relative prices, TFP, transportation cost

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Authors: Ali H. Daraji, Jack M. Hale, Ye Jianqiao

Abstract:

With the extensive use of high specific strength structures to optimise the loading capacity and material cost in aerospace and most engineering applications, much effort has been expended to develop intelligent structures for active vibration reduction and structural health monitoring. These structures are highly flexible, inherently low internal damping and associated with large vibration and long decay time. The modification of such structures by adding lightweight piezoelectric sensors and actuators at efficient locations integrated with an optimal control scheme is considered an effective solution for structural vibration monitoring and controlling. The size and location of sensor and actuator are important research topics to investigate their effects on the level of vibration detection and reduction and the amount of energy provided by a controller. Several methodologies have been presented to determine the optimal location of a limited number of sensors and actuators for small-scale structures. However, these studies have tackled this problem directly, measuring the fitness function based on eigenvalues and eigenvectors achieved with numerous combinations of sensor/actuator pair locations and converging on an optimal set using heuristic optimisation techniques such as the genetic algorithms. This is computationally expensive for small- and large-scale structures subject to optimise a number of s/a pairs to suppress multiple vibration modes. This paper proposes an efficient method to determine optimal locations for a limited number of sensor/actuator pairs for active vibration reduction of a flexible structure based on finite element method and Hamilton’s principle. The current work takes the simplified approach of modelling a structure with sensors at all locations, subjecting it to an external force to excite the various modes of interest and noting the locations of sensors giving the largest average percentage sensors effectiveness measured by dividing all sensor output voltage over the maximum for each mode. The methodology was implemented for a cantilever plate under external force excitation to find the optimal distribution of six sensor/actuator pairs to suppress the first six modes of vibration. It is shown that the results of the optimal sensor locations give good agreement with published optimal locations, but with very much reduced computational effort and higher effectiveness. Furthermore, it is shown that collocated sensor/actuator pairs placed in these locations give very effective active vibration reduction using optimal linear quadratic control scheme.

Keywords: optimisation, plate, sensor effectiveness, vibration control

Procedia PDF Downloads 212