Search results for: Taylor Series Method

Authors: Deyadeen Ali Alshibani

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In the literature, the multi-armed bandit problem as a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time. There are several different algorithms models and their applications on this problem. In this paper, we evaluate the Regret-regression through comparing with Q-learning method. A simulation on determination of optimal treatment regime is presented in detail.

Keywords: optimal, bandit problem, optimization, dynamic programming

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Authors: Jamal Ahmad

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The Sanctuary of the Kafirs is a sanctified place for the people of Kalash which contain the sacred remains of their culture. The existence of the cultural Sanctuary is not limited up to boundaries of culture but its canopy also contain the spiritual attachments in terms of religion, rituals, introspections, myths, customs and living standards. Culture is the manifestation of the human intellectual achievement in a qualitative phenomenon of a place. The ethnic people of Hindu Kush (Kalash) are an indigenous group that practices Animism. They believe in Animistic Symbology i-e the material universe has high spiritual power. The Animism in their living standard comes from the high spiritualized and sacred sacrifices of animals goats, sheep etc. in their festivals which is the symbol of purity. Similarly certain cultural and religious phenomena make its behavior, its living pattern, its fairy tales, its birth and even its death unique. The scattered and the vanishing fragments of the Kafiristan, demands the phenomenal solution which molds all these factors into preserving standards. It demands a place of belief where, their unique culture, religion, festivals and life style make a sincere base for future existence, and such phenomena of place will consciously or unconsciously molds these ideas into building fabric. The Sanctuary contains ancient vandalized cemetery, the qaliq* the mujnatikeen*, the jastaks*, dewadoor* an amphitheater for dancing and ritual performances, an herbal garden and a profile sanctuary of the blood line of Kalash. The Case-Analysis provokes a new architecture of place, as the Phenomenological Architecture, which requires a place and phenomenon to take place. The Animistic Symbology and Phenomenology both are the part of their life but needs to reveal its hidden meaning and existence i-e (The Balamain, the alpine meadows, the sacred river). The Architectural work is strengthened by the philosophies of Animism and Phenomenology which make it easy to understand. The Scope of work is to reincarnate the ethical boundaries between the neighboring tribes and the Kafirs, by a series of dwellings, cultural and religious communal buildings and spaces, gardens and streets layout under the umbrella of ethical beliefs of Kalash community. So we conclude to build the Sanctuary of the Kafirs, in Bamboret valley of Kalash.

Keywords: Qaliq, Mujnatikeen, Dewadoor, Jastaks

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Authors: S. M. Javad Davoodi, Mojtaba Shourian

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Groundwater table close to the ground surface causes major problems in construction and mining operation. One of the methods to control groundwater in such cases is using pumping wells. These pumping wells remove excess water from the site project and lower the water table to a desirable value. Although the efficiency of this method is acceptable, it needs high expenses to apply. It means even small improvement in a design of pumping wells can lead to substantial cost savings. In order to minimize the total cost in the method of pumping wells, a simulation-optimization approach is applied. The proposed model integrates MODFLOW as the simulation model with Firefly as the optimization algorithm. In fact, MODFLOW computes the drawdown due to pumping in an aquifer and the Firefly algorithm defines the optimum value of design parameters which are numbers, pumping rates and layout of the designing wells. The developed Firefly-MODFLOW model is applied to minimize the cost of the dewatering project for the ancient mosque of Kerman city in Iran. Repetitive runs of the Firefly-MODFLOW model indicates that drilling two wells with the total rate of pumping 5503 m3/day is the result of the minimization problem. Results show that implementing the proposed solution leads to at least 1.5 m drawdown in the aquifer beneath mosque region. Also, the subsidence due to groundwater depletion is less than 80 mm. Sensitivity analyses indicate that desirable groundwater depletion has an enormous impact on total cost of the project. Besides, in a hypothetical aquifer decreasing the hydraulic conductivity contributes to decrease in total water extraction for dewatering.

Keywords: groundwater dewatering, pumping wells, simulation-optimization, MODFLOW, firefly algorithm

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Authors: Cynthia G. Esquerre, Amparo Iris Zavaleta

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Extremophiles constitute a potentially valuable source of proteases for the development of biotechnological processes; however, the number of available studies in the literature is limited compared to mesophilic counterparts. Therefore, in this study, Peruvian halophilic microorganisms were characterized to select suitable proteolytic strains that produce active proteases under exigent conditions. Proteolysis was screened using the streak plate method with gelatin or skim milk as substrates. After that, proteolytic microorganisms were selected for phenotypic characterization and screened by a semi-quantitative proteolytic test using a modified method of diffusion agar. Finally, proteolysis was evaluated using partially purified extracts by ice-cold ethanol precipitation and dialysis. All analyses were carried out over a wide range of NaCl concentrations, pH, temperature and substrates. Of a total of 60 strains, 21 proteolytic strains were selected, of these 19 were extreme halophiles and 2 were moderates. Most proteolytic strains demonstrated differences in their biochemical patterns, particularly in sugar fermentation. A total of 14 microorganisms produced extracellular proteases, 13 were neutral, and one was alkaline showing activity up to pH 9.0. Proteases hydrolyzed gelatin as the most specific substrate. In general, catalytic activity was efficient under a wide range of NaCl (1 to 4 M NaCl), temperature (37 to 55 °C) and after an ethanol exposition performed at -20 °C for 24 hours. In conclusion, this study reported 14 candidates extremely halophiles producing extracellular proteases capable of being stable and active on a wide range of NaCl, temperature and even long lasting ethanol exposition.

Keywords: biotechnological processes, ethanol exposition, extracellular proteases, extremophiles

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Authors: Tibor Ajtai, Noémi Utry, Máté Pintér, Gábor Szabó, Zoltán Bozóki

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Beyond its climate and health related issues ambient light absorbing carbonaceous particulate matter (LAC) has also become a great scientific interest in terms of its regulations recently. It has been experimentally demonstrated in recent studies, that LAC is dominantly composed of traffic and wood burning aerosol particularly under wintertime urban conditions, when the photochemical and biological activities are negligible. Several methods have been introduced to quantitatively apportion aerosol fractions emitted by wood burning and traffic but most of them require costly and time consuming off-line chemical analysis. As opposed to chemical features, the microphysical properties of airborne particles such as optical absorption and size distribution can be easily measured on-line, with high accuracy and sensitivity, especially under highly polluted urban conditions. Recently a new method has been proposed for the apportionment of wood burning and traffic aerosols based on the spectral dependence of their absorption quantified by the Aerosol Angström Exponent (AAE). In this approach the absorption coefficient is deduced from transmission measurement on a filter accumulated aerosol sample and the conversion factor between the measured optical absorption and the corresponding mass concentration (the specific absorption cross section) are determined by on-site chemical analysis. The recently developed multi-wavelength photoacoustic instruments provide novel, in-situ approach towards the reliable and quantitative characterization of carbonaceous particulate matter. Therefore, it also opens up novel possibilities on the source apportionment through the measurement of light absorption. In this study, we demonstrate an in-situ spectral characterization method of the ambient carbon fraction based on light absorption and size distribution measurements using our state-of-the-art multi-wavelength photoacoustic instrument (4λ-PAS) and Single Mobility Particle Sizer (SMPS) The carbonaceous particulate selective source apportionment study was performed for ambient particulate matter in the city center of Szeged, Hungary where the dominance of traffic and wood burning aerosol has been experimentally demonstrated earlier. The proposed model is based on the parallel, in-situ measurement of optical absorption and size distribution. AAEff and AAEwb were deduced from the measured data using the defined correlation between the AOC(1064nm)/AOC(266nm) and N100/N20 ratios. σff(λ) and σwb(λ) were determined with the help of the independently measured temporal mass concentrations in the PM1 mode. Furthermore, the proposed optical source apportionment is based on the assumption that the light absorbing fraction of PM is exclusively related to traffic and wood burning. This assumption is indirectly confirmed here by the fact that the measured size distribution is composed of two unimodal size distributions identified to correspond to traffic and wood burning aerosols. The method offers the possibility of replacing laborious chemical analysis with simple in-situ measurement of aerosol size distribution data. The results by the proposed novel optical absorption based source apportionment method prove its applicability whenever measurements are performed at an urban site where traffic and wood burning are the dominant carbonaceous sources of emission.

Keywords: absorption, size distribution, source apportionment, wood burning, traffic aerosol

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Authors: Serges Mendomo Meye, Li Guowei, Shen Zhenzhong, Gan Lei, Xu Liqun

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Due to the characteristics of high-heap and large-volume, the complex layers of waste and the high-water level of leachate, environmental pollution, and slope instability are easily produced. It is therefore of great significance to research the heterogeneous seepage field and stability of landfills. This paper focuses on the heterogeneous characteristics of the landfill piles and analyzes the seepage field and slope stability of the landfill using statistical and numerical analysis methods. The calculated results are compared with the field measurement and literature research data to verify the reliability of the model, which may provide the basis for the design, safe, and eco-friendly operation of the landfill. The main innovations are as follows: (1) The saturated-unsaturated seepage equation of heterogeneous soil is derived theoretically. The heterogeneous landfill is regarded as composed of infinite layers of homogeneous waste, and a method for establishing the heterogeneous seepage model is proposed. Then the formation law of the stagnant water level of heterogeneous landfills is studied. It is found that the maximum stagnant water level of landfills is higher when considering the heterogeneous seepage characteristics, which harms the stability of landfills. (2) Considering the heterogeneity weight and strength characteristics of waste, a method of establishing a heterogeneous stability model is proposed, and it is extended to the three-dimensional stability study. It is found that the distribution of heterogeneous characteristics has a great influence on the stability of landfill slope. During the operation and management of the landfill, the reservoir bank should also be considered while considering the capacity of the landfill.

Keywords: heterogeneous characteristics, leachate levels, saturated-unsaturated seepage, seepage field, slope stability

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Authors: Guncel Ozturk

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Background: Rhinoplasty is the most commonly performed cosmetic operations in plastic surgery. Maneuvers used in rhinoplasty lead to a firm and stiff nasal tip in the early postoperative months. This unnatural stability of the nose may easily cause distortion in the reshaped nose after severe trauma. Moreover, a firm nasal tip may cause difficulties in performing activities such as touching, hugging, or kissing. Decreasing the stability and increasing the mobility of the nasal tip would help rhinoplasty patients to avoid these small but relatively important problems. Methods: We use delivery approach with closed rhinoplasty and changed positions of intranasal incisions to reach a dynamic and mobile nose. A total of 203 patients who had undergone primary closed rhinoplasty in private practice were inspected retrospectively. Posterior strut flap that was connected with connective tissues in the caudal of septum and the medial crurals were formed. Cartilage of the posterior strut graft was left 2 mm thick in the distal part of septum, it was cut vertically, and the connective tissue in the distal part was preserved. Results: The median patient age was 24 (range 17-42) years. The median follow-up period was15.2 (range12-26) months. Patient satisfaction was assessed with the 'Rhinoplasty Outcome Evaluation' (ROE) questionnaire. Twelve months after surgeries, 87.5% of patients reported excellent outcomes, according to ROE. Conclusion: The soft tissue connections between that segment and surrounding structures should be preserved to save the support of the tip while having a mobile tip at the same time with this method. These modifications would access to a mobile, non-stiff, and dynamic nasal tip in the early postoperative months. Further and prospective studies should be performed for supporting this method.

Keywords: closed rhinoplasty, dynamic, mobile, tip

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: Martina I. Reinhold, Theresa Bacon-Baguley

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A core challenge of physician assistant education is preparing professionals for lifelong learning. While this conventionally has encompassed scientific advances, students must also embrace new care delivery models and technologies. Telemedicine, the provision of care via two-way audio and video, is an example of a technological advance reforming health care. During a three-semester sequence of Hospital Community Experiences, physician assistant students were assigned experiences with Answer Health on Demand, a telemedicine collaborative. Preceding the experiences, the agency lectured on the application of telemedicine. Students were then introduced to the technology and partnered with a provider. Prior to observing the patient-provider interaction, patient consent was obtained. Afterwards, students completed a reflection paper on lessons learned and the potential impact of telemedicine on their careers. Thematic analysis was completed on the students’ reflection papers (n=13). Preceding the lecture and experience, over 75% of students (10/13) were unaware of telemedicine. Several stated they were 'skeptical' about the effectiveness of 'impersonal' health care appointments. After the experience, all students remarked that telemedicine will play a large role in the future of healthcare and will provide benefits by improving access in rural areas, decreasing wait time, and saving cost. More importantly, 30% of students (4/13) commented that telemedicine is a technology they can see themselves using in their future practice. Initial results indicate that collaborative interaction between students and telemedicine providers enhanced student learning and exposed students to technological advances in the delivery of care. Further, results indicate that students perceived telemedicine more favorably as a viable delivery method after the experience.

Keywords: collaboration, physician assistant education, teaching innovative health care delivery method, telemedicine

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Authors: Lijuan Zhou, Mengqi Wu, Changyong Niu

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Attributed graph clustering can utilize the graph topology and node attributes to uncover hidden community structures and patterns in complex networks, aiding in the understanding and analysis of complex systems. Utilizing contrastive learning for attributed graph clustering can effectively exploit meaningful implicit relationships between data. However, existing attributed graph clustering methods based on contrastive learning suffer from the following drawbacks: 1) Complex data augmentation increases computational cost, and inappropriate data augmentation may lead to semantic drift. 2) The selection of positive and negative samples neglects the intrinsic cluster structure learned from graph topology and node attributes. Therefore, this paper proposes a method called self-supervised Attributed Graph Clustering with Dual Contrastive Loss constraints (AGC-DCL). Firstly, Siamese Multilayer Perceptron (MLP) encoders are employed to generate two views separately to avoid complex data augmentation. Secondly, the neighborhood contrastive loss is introduced to constrain node representation using local topological structure while effectively embedding attribute information through attribute reconstruction. Additionally, clustering-oriented contrastive loss is applied to fully utilize clustering information in global semantics for discriminative node representations, regarding the cluster centers from two views as negative samples to fully leverage effective clustering information from different views. Comparative clustering results with existing attributed graph clustering algorithms on six datasets demonstrate the superiority of the proposed method.

Keywords: attributed graph clustering, contrastive learning, clustering-oriented, self-supervised learning

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Authors: Kubra Dogan, Fatih Tornuk

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Due to increasing consumer demand for the high-quality food products and awareness regarding the health benefits of different nutrients in food minimal processing becomes more popular in modern food preservation. To date, heat treatment is often used for inactivation of spoilage microorganisms in foods. However, it may cause significant changes in the quality and nutritional properties of food. In order to overcome the detrimental effects of heat treatment, several alternatives of non-thermal microbial inactivation processes have been investigated. Ultraviolet (UV) inactivation is a promising and feasible method for better quality and longer shelf life as an alternative to heat treatment, which aims to inhibit spoilage and pathogenic microorganisms and to inactivate the enzymes in vegetable juice production. UV-C is a sub-class of UV treatment which shows the highest microcidal effect between 250-270 nm. The wavelength of 254 nm is used for the surface disinfection of certain liquid food products such as vegetable juice. Effects of UV-C treatment on microbiological load and quality parameter of vegetable juice which is a mix of celery, carrot, lemon and orange was investigated. Our results showed that storing of UV-C applied vegetable juice for three months, reduced the count of TMAB by 3.5 log cfu/g and yeast-mold by 2 log cfu/g compared to control sample. Total phenolic content was found to be 514.3 ± 0.6 mg gallic acid equivalent/L, and there wasn’t a significant difference compared to control. The present work suggests that UV-C treatment is an alternative method for disinfection of vegetable juice since it enables adequate microbial inactivation, longer shelf life and has minimal effect on degradation of quality parameters of vegetable juice.

Keywords: heat treatment, phenolic content, shelf life, ultraviolet (UV-C), vegetable juice

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Authors: Weichen Chang

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To create a guided teaching method for AI generative drawing design, this paper develops a set of teaching models for AI generative drawing (DCAI), which combines learning modes such as problem-solving, thematic inquiry, phenomenon-based, task-oriented, and DFC . Through the information security AI picture book learning guided programs and content, the application of participatory action research (PAR) and interview methods to explore the dual knowledge of Context and ChatGPT (DCAI) for AI to guide the development of students' AI learning skills. In the interviews, the students highlighted five main learning outcomes (self-study, critical thinking, knowledge generation, cognitive development, and presentation of work) as well as the challenges of implementing the model. Through the use of DCAI, students will enhance their consensus awareness of generative mapping analysis and group cooperation, and they will have knowledge that can enhance AI capabilities in DCAI inquiry and future life. From this paper, it is found that the conclusions are (1) The good use of DCAI can assist students in exploring the value of their knowledge through the power of stories and finding the meaning of knowledge communication; (2) Analyze the transformation power of the integrity and coherence of the story through the context so as to achieve the tension of ‘starting and ending’; (3) Use ChatGPT to extract inspiration, arrange story compositions, and make prompts that can communicate with people and convey emotions. Therefore, new knowledge construction methods will be one of the effective methods for AI learning in the face of artificial intelligence, providing new thinking and new expressions for interdisciplinary design and design education practice.

Keywords: artificial intelligence, task-oriented, contextualization, design education

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Authors: Juan Huang, Hugo Ninanya

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Oil has been used as a source of energy and supply to make materials, such as asphalt or rubber for many years. This is the reason why new technologies have been implemented through time. However, research still needs to continue increasing due to new challenges engineers face every day, just like unconventional reservoirs. Various numerical methodologies have been applied in petroleum engineering as tools in order to optimize the production of reservoirs before drilling a wellbore, although not all of these have the same efficiency when talking about studying fracture propagation. Analytical methods like those based on linear elastic fractures mechanics fail to give a reasonable prediction when simulating fracture propagation in ductile materials whereas numerical methods based on the cohesive zone method (CZM) allow to represent the elastoplastic behavior in a reservoir based on a constitutive model; therefore, predictions in terms of displacements and pressure will be more reliable. In this work, a hydro-geomechanical coupled model of horizontal wells in fractured rock was developed using ABAQUS; both extended element method and cohesive elements were used to represent predefined fractures in a model (2-D). A power law for representing the rheological behavior of fluid (shear-thinning, power index <1) through fractures and leak-off rate permeating to the matrix was considered. Results have been showed in terms of aperture and length of the fracture, pressure within fracture and fluid loss. It was showed a high infiltration rate to the matrix as power index decreases. A sensitivity analysis is conclusively performed to identify the most influential factor of fluid loss.

Keywords: fracture, hydro-geomechanical model, non-Newtonian fluid, numerical analysis, sensitivity analysis

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Authors: Niharika Kaushal, Minni Singh

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Citrus fruits contain an abundance of phytochemicals that can promote health. A substantial amount of agrowaste is produced from the juice processing industries, primarily peels and seeds. This leftover agrowaste is a reservoir of nutraceuticals, particularly bioflavonoids which render it antioxidant and potentially anticancerous. It is, therefore, favorable to utilize this biomass and contribute towards sustainability in a manner that value-added products may be derived from them, nutraceuticals, in this study. However, the pre-systemic metabolism of flavonoids in the gastric phase limits the effectiveness of these bioflavonoids derived from mandarin biomass. In this study, ‘kinnow’ mandarin (Citrus nobilis X Citrus deliciosa) biomass was explored for its flavonoid profile. This work entails supercritical fluid extraction and identification of bioflavonoids from mandarin biomass. Furthermore, to overcome the limitations of these flavonoids in the gastrointestinal tract, a double-layered vehicular mechanism comprising the fabrication of nanoconjugates and edible hydrogels was adopted. Total flavonoids in the mandarin peel extract were estimated by the aluminum chloride complexation method and were found to be 47.3±1.06 mg/ml rutin equivalents as total flavonoids. Mass spectral analysis revealed the abundance of polymethoxyflavones (PMFs), nobiletin and tangeretin as the major flavonoids in the extract, followed by hesperetin and naringenin. Furthermore, the antioxidant potential was analyzed by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method, which showed an IC50 of 0.55μg/ml. Nanoconjugates were fabricated via the solvent evaporation method, which was further impregnated into hydrogels. Additionally, the release characteristics of nanoconjugate-laden hydrogels in a simulated gastrointestinal environment were studied. The PLGA-PMFs nanoconjugates exhibited a particle size between 200-250nm having a smooth and spherical shape as revealed by FE-SEM. The impregnated alginate hydrogels offered a dense network that ensured the holding of PLGA-PMF nanoconjugates, as confirmed by Cryo-SEM images. Rheological studies revealed the shear-thinning behavior of hydrogels and their high resistance to deformation. Gastrointestinal studies showed a negligible 4.0% release of flavonoids in the gastric phase, followed by a sustained release over the next hours in the intestinal environment. Therefore, based on the enormous potential of recovering nutraceuticals from agro-processing wastes, further augmented by nanotechnological interventions for enhancing the bioefficacy of these compounds, lays the foundation for exploring the path towards the development of value-added products, thereby contributing towards the sustainable use of agrowaste.

Keywords: agrowaste, gastrointestinal, hydrogel, nutraceuticals

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Authors: Abdullah Al Mamoon, Niels E. Joergensen, Ataur Rahman, Hassan Qasem

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Intergovernmental Panel for Climate Change (IPCC) in its fourth Assessment Report AR4 predicts a more extreme climate towards the end of the century, which is likely to impact the design of engineering infrastructure projects with a long design life. A recent study in 2013 developed new design rainfall for Qatar, which provides an improved design basis of drainage infrastructure for the State of Qatar under the current climate. The current design standards in Qatar do not consider increased rainfall intensity caused by climate change. The focus of this paper is to update recently developed design rainfalls in Qatar under the changing climatic conditions based on IPCC's AR4 allowing a later revision to the proposed design standards, relevant for projects with a longer design life. The future climate has been investigated based on the climate models released by IPCC’s AR4 and A2 story line of emission scenarios (SRES) using a stationary approach. Annual maximum series (AMS) of predicted 24 hours rainfall data for both wet (NCAR-CCSM) scenario and dry (CSIRO-MK3.5) scenario for the Qatari grid points in the climate models have been extracted for three periods, current climate 2010-2039, medium term climate (2040-2069) and end of century climate (2070-2099). A homogeneous region of the Qatari grid points has been formed and L-Moments based regional frequency approach is adopted to derive design rainfalls. The results indicate no significant changes in the design rainfall on the short term 2040-2069, but significant changes are expected towards the end of the century (2070-2099). New design rainfalls have been developed taking into account climate change for 2070-2099 scenario and by averaging results from the two scenarios. IPCC’s AR4 predicts that the rainfall intensity for a 5-year return period rain with duration of 1 to 2 hours will increase by 11% in 2070-2099 compared to current climate. Similarly, the rainfall intensity for more extreme rainfall, with a return period of 100 years and duration of 1 to 2 hours will increase by 71% in 2070-2099 compared to current climate. Infrastructure with a design life exceeding 60 years should add safety factors taking the predicted effects from climate change into due consideration.

Keywords: climate change, design rainfalls, IDF, Qatar

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Authors: Rajeev Ravindran, Amit K. Jaiswal

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Waste from the food-processing industry is produced in large amount and contains high levels of lignocellulose. Due to continuous accumulation throughout the year in large quantities, it creates a major environmental problem worldwide. The chemical composition of these wastes (up to 75% of its composition is contributed by polysaccharide) makes it inexpensive raw material for the production of value-added products such as biofuel, bio-solvents, nanocrystalline cellulose and enzymes. In order to use lignocellulose as the raw material for the microbial fermentation, the substrate is subjected to enzymatic treatment, which leads to the release of reducing sugars such as glucose and xylose. However, the inherent properties of lignocellulose such as presence of lignin, pectin, acetyl groups and the presence of crystalline cellulose contribute to recalcitrance. This leads to poor sugar yields upon enzymatic hydrolysis of lignocellulose. A pre-treatment method is generally applied before enzymatic treatment of lignocellulose that essentially removes recalcitrant components in biomass through structural breakdown. Present study is carried out to find out the best pre-treatment method for the maximum liberation of reducing sugars from spent coffee waste (SPW). SPW was subjected to a range of physical, chemical and physico-chemical pre-treatment followed by a sequential, combinatorial pre-treatment strategy is also applied on to attain maximum sugar yield by combining two or more pre-treatments. All the pre-treated samples were analysed for total reducing sugar followed by identification and quantification of individual sugar by HPLC coupled with RI detector. Besides, generation of any inhibitory compounds such furfural, hydroxymethyl furfural (HMF) which can hinder microbial growth and enzyme activity is also monitored. Results showed that ultrasound treatment (31.06 mg/L) proved to be the best pre-treatment method based on total reducing content followed by dilute acid hydrolysis (10.03 mg/L) while galactose was found to be the major monosaccharide present in the pre-treated SPW. Finally, the results obtained from the study were used to design a sequential lignocellulose pre-treatment protocol to decrease the formation of enzyme inhibitors and increase sugar yield on enzymatic hydrolysis by employing cellulase-hemicellulase consortium. Sequential, combinatorial treatment was found better in terms of total reducing yield and low content of the inhibitory compounds formation, which could be due to the fact that this mode of pre-treatment combines several mild treatment methods rather than formulating a single one. It eliminates the need for a detoxification step and potential application in the valorisation of lignocellulosic food waste.

Keywords: lignocellulose, enzymatic hydrolysis, pre-treatment, ultrasound

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Authors: Alexa Rakoski, Yun Suk Eo, Cagliyan Kurdak, Priscila F. S. Rosa, Zachary Fisk, Monica Ciomaga Hatnean, Geetha Balakrishnan, Boyoun Kang, Myungsuk Song, Byungki Cho

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Samarium hexaboride (SmB6) is a strongly correlated mixed valence material and Kondo insulator. In the resistance-temperature curve, SmB6 exhibits activated behavior from 4-40 K after the Kondo gap forms. However, below 4 K, the resistivity is temperature independent or weakly temperature dependent due to the appearance of a topologically protected surface state. Current research suggests that the surface of SmB6 is conductive while the bulk is truly insulating, different from conventional 3D TIs (Topological Insulators) like Bi₂Se₃ which are plagued by bulk conduction due to impurities. To better understand why the bulk of SmB6 is so different from conventional TIs, this study employed a new method, called inverted resistance, to explore the lowest temperatures, as well as standard Hall measurements for the rest of the temperature range. In the inverted resistance method, current flows from an inner contact to an outer ring, and voltage is measured outside of this outer ring. This geometry confines the surface current and allows for measurement of the bulk resistivity even when the conductive surface dominates transport (below 4 K). The results confirm that the bulk of SmB6 is truly insulating down to 2 K. Hall measurements on a number of samples show consistent bulk behavior from 4-40 K, but widely varying behavior among samples above 40 K. This is attributed to a combination of the growth process and purity of the starting material, and the relationship between the high and low temperature behaviors is still being explored.

Keywords: bulk transport, Hall effect, inverted resistance, Kondo insulator, samarium hexaboride, topological insulator

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Authors: Luh Eka Suryani, Purhadi

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Poisson regression is a non-linear regression model with response variable in the form of count data that follows Poisson distribution. Modeling for a pair of count data that show high correlation can be analyzed by Poisson Bivariate Regression. Data, the number of infant mortality and maternal mortality, are count data that can be analyzed by Poisson Bivariate Regression. The Poisson regression assumption is an equidispersion where the mean and variance values are equal. However, the actual count data has a variance value which can be greater or less than the mean value (overdispersion and underdispersion). Violations of this assumption can be overcome by applying Generalized Poisson Regression. Characteristics of each regency can affect the number of cases occurred. This issue can be overcome by spatial analysis called geographically weighted regression. This study analyzes the number of infant mortality and maternal mortality based on conditions in East Java in 2016 using Geographically Weighted Bivariate Generalized Poisson Regression (GWBGPR) method. Modeling is done with adaptive bisquare Kernel weighting which produces 3 regency groups based on infant mortality rate and 5 regency groups based on maternal mortality rate. Variables that significantly influence the number of infant and maternal mortality are the percentages of pregnant women visit health workers at least 4 times during pregnancy, pregnant women get Fe3 tablets, obstetric complication handled, clean household and healthy behavior, and married women with the first marriage age under 18 years.

Keywords: adaptive bisquare kernel, GWBGPR, infant mortality, maternal mortality, overdispersion

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Authors: Ramin Mansouri

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Due to the contrast of rivers discharge regime with water demands, one of the best ways to use water resources is to regulate the natural flow of the rivers and supplying water needs to construct dams. Optimal utilization of reservoirs, consideration of multiple important goals together at the same is of very high importance. To study about analyzing this method, statistical data of Bakhtiari and Roudbar dam over 46 years (1955 until 2001) is used. Initially an appropriate objective function was specified and using DE algorithm, the rule curve was developed. In continue, operation policy using rule curves was compared to standard comparative operation policy. The proposed method distributed the lack to the whole year and lowest damage was inflicted to the system. The standard deviation of monthly shortfall of each year with the proposed algorithm was less deviated than the other two methods. The Results show that median values for the coefficients of F and Cr provide the optimum situation and cause DE algorithm not to be trapped in local optimum. The most optimal answer for coefficients are 0.6 and 0.5 for F and Cr coefficients, respectively. After finding the best combination of coefficients values F and CR, algorithms for solving the independent populations were examined. For this purpose, the population of 4, 25, 50, 100, 500 and 1000 members were studied in two generations (G=50 and 100). result indicates that the generation number 200 is suitable for optimizing. The increase in time per the number of population has almost a linear trend, which indicates the effect of population in the runtime algorithm. Hence specifying suitable population to obtain an optimal results is very important. Standard operation policy had better reversibility percentage, but inflicts severe vulnerability to the system. The results obtained in years of low rainfall had very good results compared to other comparative methods.

Keywords: reservoirs, differential evolution, dam, Optimal operation

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Authors: Rose C.Anamezie, Mishack T. Gumbo

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Physics learners’ poor retention, which culminates in poor achievement due to teaching approaches that are unrelated to learners’ in non-Western cultures, warranted the study. The tenet of this study was to determine the effectiveness of the ethnoscience-based teaching (EBT) approach on learners’ retention in the Physics concept of Optics in the Awka Education zone of Anambra State- Nigeria. Two research questions and three null hypotheses tested at a 0.05 level of significance guided the study. The design adopted for the study was Quasi-experimental. Specifically, a non-equivalent control group design was adopted. The population for the study was 4,825 SS2 Physics learners in the zone. 160 SS2 learners were sampled using purposive and random sampling. The experimental group was taught rectilinear propagation of light (RPL) using the EBT approach, while the control group was taught the same topic using the lecture method. The instrument for data collection was the 50 Physics Retention Test (PRT) which was validated by three experts and tested for reliability using Kuder-Richardson’s formula-20, which yielded coefficients of 0.81. The data were analysed using mean, standard deviation and analysis of co-variance (p< .05). The results showed higher retention for the use of the EBT approach than the lecture method, while there was no significant gender-based factor in the learners’ retention in Physics. It was recommended that the EBT approach, which bridged the gender gap in Physics retention, be adopted in secondary school teaching and learning since it could transform science teaching, enhance learners’ construction of new science concepts based on their existing knowledge and bridge the gap between Western science and learners’ worldviews.

Keywords: Ethnoscience-based teaching, optics, rectilinear propagation of light, retention

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Authors: Asrat Agalu Abejew

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Background: Antimicrobial resistance (AMR) is a silent tsunami and one of the top global threats to health care and public health. It is one of the common agendas globally and in Ethiopia. Emerging AMR will be a double burden to Ethiopia, which is facing a series of problems from infectious disease morbidity and mortality. In Ethiopia, although there are attempts to document AMR in healthcare institutions, comprehensive and all-inclusive analysis is still lacking. Thus, this study is aimed to determine trends in AMR from 2016-2021. Methods: A retrospective analysis of secondary data recorded in the Amhara Public Health Institute (APHI) from 2016 to 2021 G.C was conducted. Blood, Urine, Stool, Swabs, Discharge, body effusions, and other Microbiological specimens were collected from each study participants, and Bacteria identification and Resistance tests were done using the standard microbiologic procedure. Data was extracted from excel in August 2022, Trends in AMR were analyzed, and the results were described. In addition, the chi-square (X2) test and binary logistic regression were used, and a P. value < 0.05 was used to determine a significant association. Results: During 6 years period, there were 25143 culture and susceptibility tests. Overall, 265 (46.2%) bacteria were resistant to 2-4 antibiotics, 253 (44.2%) to 5-7 antibiotics, and 56 (9.7%) to >=8 antibiotics. The gram-negative bacteria were 166 (43.9%), 155 (41.5%), and 55 (14.6%) resistant to 2-4, 5-7, and ≥8 antibiotics, respectively, whereas 99(50.8%), 96(49.2% and 1 (0.5%) of gram-positive bacteria were resistant to 2-4, 5-7 and ≥8 antibiotics respectively. K. pneumonia 3783 (15.67%) and E. coli 3199 (13.25%) were the most commonly isolated bacteria, and the overall prevalence of AMR was 2605 (59.9%), where K. pneumonia 743 (80.24%), E. cloacae 196 (74.81%), A. baumannii 213 (66.56%) being the most common resistant bacteria for antibiotics tested. Except for a slight decline during 2020 (6469 (25.4%)), the overall trend of AMR is rising from year to year, with a peak in 2019 (8480 (33.7%)) and in 2021 (7508 (29.9%). If left un-intervened, the trend in AMR will increase by 78% of variation from the study period, as explained by the differences in years (R2=0.7799). Ampicillin, Augmentin, ciprofloxacin, cotrimoxazole, tetracycline, and Tobramycin were almost resistant to common bacteria they were tested. Conclusion: AMR is linearly increasing during the last 6 years. If left as it is without appropriate intervention after 15 years (2030 E.C), AMR will increase by 338.7%. A growing number of multi-drug resistant bacteria is an alarm to awake policymakers and those who do have the concern to intervene before it is too late. This calls for a periodic, integrated, and continuous system to determine the prevalence of AMR in commonly used antibiotics.

Keywords: AMR, trend, pattern, MDR

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Authors: Ibrahim Sengor, Sumeyye Cesur, Ilyas Kartal, Faik Nuzhet Oktar, Nazmi Ekren, Ahmet Talat Inan, Oguzhan Gunduz

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In recent years, many researchers focused on nano-size fiber production. Nanofibers have been studied due to their different and superior physical, chemical and mechanical properties. Poly (lactic acid) (PLA), is a type of biodegradable thermoplastic polyester derived from renewable sources used in biomedical owing to its biocompatibility and biodegradability. In addition, zinc oxide is an antibacterial material and hazelnut shell powder is a filling material. In this study, nanofibers were obtained by adding of different ratio Zinc oxide, (ZnO) and hazelnut shell powder at different concentration into Poly (lactic acid) (PLA) by using electrospinning method which is the most common method to obtain nanofibers. After dissolving the granulated polylactic acids in % 1,% 2,% 3 and% 4 with chloroform solvent, they are homogenized by adding tween and hazelnut shell powder at different ratios and then by electrospinning, nanofibers are obtained. Scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FTIR), Differential scanning calorimeter (DSC) and physical analysis such as density, electrical conductivity, surface tension, viscosity measurement and antimicrobial test were carried out after production process. The resulting structures of the nanofiber possess antimicrobial and antiseptic properties, which are attractive for biomedical applications. The resulting structures of the nanofiber possess antimicrobial, non toxic, self-cleaning and rigid properties, which are attractive for biomedical applications.

Keywords: electrospinning, hazelnut shell powder, nanofibers, poly (lactic acid), zinc oxide

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Authors: Emma Nemishalyan

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It is believed that learners’ mother tongue (L1 hereafter) has a huge impact on their second language acquisition (L2 hereafter). This hypothesis has been exposed to both positive and negative criticism. Based on research results of a wide range of learners’ corpora (Chinese, Japanese, Spanish among others) the hypothesis has either been proved or disproved. However, no such study has been conducted on the Armenian learners. The aim of this paper is to understand the implication of the hypothesis on the Armenian learners’ corpus in terms of the use of the passive voice. To this end, the method of Contrastive Interlanguage Analysis (hereafter CIA) has been used on native speakers’ corpus (Louvain Corpus of Native English Essays (LOCNESS)) and Armenian learners’ corpus which has been compiled by me in compliance with International Corpus of Learner English (ICLE) guidelines. CIA compares the interlanguage (the language produced by learners) with the one produced by native speakers. With the help of this method, it is possible not only to highlight the mistakes that learners make, but also to underline the under or overuses. The choice of the grammar issue (passive voice) is conditioned by the fact that typologically Armenian and English are drastically different as they belong to different branches. Moreover, the passive voice is considered to be one of the most problematic grammar topics to be acquired by learners of the English language. Based on this difference, we hypothesized that Armenian learners would either overuse or underuse some types of the passive voice. With the help of Lancsbox software, we have identified the frequency rates of passive voice usage in LOCNESS and Armenian learners’ corpus to understand whether the latter have the same usage pattern of the passive voice as the native speakers. Secondly, we have identified the types of the passive voice used by the Armenian leaners trying to track down the reasons in their mother tongue. The results of the study showed that Armenian learners underused the passive voices in contrast to native speakers. Furthermore, the hypothesis that learners’ L1 has an impact on learners’ L2 acquisition and production was proved.

Keywords: corpus linguistics, applied linguistics, second language acquisition, corpus compilation

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Authors: Nurkhairul Bariyah Baharun, Afzan Adam, Reena Rahayu Md Zin

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Tumor microenvironment (TME) in breast cancer is mainly composed of cancer cells, immune cells, and stromal cells. The interaction between cancer cells and their microenvironment plays an important role in tumor development, progression, and treatment response. The TME in breast cancer includes tumor-infiltrating lymphocytes (TILs) that are implicated in killing tumor cells. TILs can be found in tumor stroma (sTILs) and within the tumor (iTILs). TILs in triple negative breast cancer (TNBC) have been demonstrated to have prognostic and potentially predictive value. The international Immune-Oncology Biomarker Working Group (TIL-WG) had developed a guideline focus on the assessment of sTILs using hematoxylin and eosin (H&E)-stained slides. According to the guideline, the pathologists use “eye balling” method on the H&E stained- slide for sTILs assessment. This method has low precision, poor interobserver reproducibility, and is time-consuming for a comprehensive evaluation, besides only counted sTILs in their assessment. The TIL-WG has therefore recommended that any algorithm for computational assessment of TILs utilizing the guidelines provided to overcome the limitations of manual assessment, thus providing highly accurate and reliable TILs detection and classification for reproducible and quantitative measurement. This study is carried out to develop a TNBC digital whole slide image (WSI) dataset from H&E-stained slides and IHC (CD4+ and CD8+) stained slides. TNBC cases were retrieved from the database of the Department of Pathology, Hospital Canselor Tuanku Muhriz (HCTM). TNBC cases diagnosed between the year 2010 and 2021 with no history of other cancer and available block tissue were included in the study (n=58). Tissue blocks were sectioned approximately 4 µm for H&E and IHC stain. The H&E staining was performed according to a well-established protocol. Indirect IHC stain was also performed on the tissue sections using protocol from Diagnostic BioSystems PolyVue™ Plus Kit, USA. The slides were stained with rabbit monoclonal, CD8 antibody (SP16) and Rabbit monoclonal, CD4 antibody (EP204). The selected and quality-checked slides were then scanned using a high-resolution whole slide scanner (Pannoramic DESK II DW- slide scanner) to digitalize the tissue image with a pixel resolution of 20x magnification. A manual TILs (sTILs and iTILs) assessment was then carried out by the appointed pathologist (2 pathologists) for manual TILs scoring from the digital WSIs following the guideline developed by TIL-WG 2014, and the result displayed as the percentage of sTILs and iTILs per mm² stromal and tumour area on the tissue. Following this, we aimed to develop an automated digital image scoring framework that incorporates key elements of manual guidelines (including both sTILs and iTILs) using manually annotated data for robust and objective quantification of TILs in TNBC. From the study, we have developed a digital dataset of TNBC H&E and IHC (CD4+ and CD8+) stained slides. We hope that an automated based scoring method can provide quantitative and interpretable TILs scoring, which correlates with the manual pathologist-derived sTILs and iTILs scoring and thus has potential prognostic implications.

Keywords: automated quantification, digital pathology, triple negative breast cancer, tumour infiltrating lymphocytes

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Authors: Sina Modares Ahmadi, Mohamad Reza Ghazavi, Mandana Sheikhzad

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Squeeze film damper systems (SFD) are often used in machines with high rotational speed to reduce non-periodic behavior by creating external damping. These types of systems are frequently used in aircraft gas turbine engines. There are some structural parameters which are of great importance in designing these kinds of systems, such as oil film thickness, C, and outer race mass, mo. Moreover, there is a crucial parameter associated with manufacturing process, under the title of waviness. Geometric imperfections are often called waviness if its wavelength is much longer than Hertzian contact width which is a considerable source of vibration in ball bearings. In this paper, a system of a flexible rotor and two ball bearings with floating ring squeeze film dampers and consideration of waviness has been modeled and solved by a numerical integration method, namely Runge-Kutta method to investigate the dynamic response of the system. The results show that by increasing the number of wave lobes, which is due to inappropriate manufacturing, non- periodic and chaotic behavior increases. This result reveals the importance of manufacturing accuracy. Moreover, as long as C< 1.5×10-4 m, by increasing the oil film thickness, unwanted vibrations and non-periodic behavior of the system have been reduced, On the other hand, when C>1.5×10-4 m, increasing the outer oil film thickness results in the increasing chaotic and non-periodic responses. This result shows that although the presence of oil film results in reduction the non-periodic and chaotic behaviors, but the oil film has an optimal thickness. In addition, with increasing mo, the disc displacement amplitude increases. This result reveals the importance of utilizing light materials in manufacturing the squeeze film dampers.

Keywords: squeeze-film damper, waviness, ball bearing, bifurcation

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Authors: Joanna Smoluk-Sikorska, Władysława Łuczka

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Organic farming is an important element of sustainable agriculture. It has been developing very dynamically in Poland, especially since Poland’s accession to the EU. Nevertheless, properly functioning organic market is a necessary condition justifying development of organic agriculture. Despite significant improvement, this market in Poland is still in the initial stage of growth. An important element of the market is distribution, especially retail, which offers specified product range to consumers. Therefore, there is a need to investigate retail outlets offering organic food in order to improve functioning of this part of the market. The inquiry research conducted in three types of outlets offering organic food, between 2011 and 2012 in the 8 largest Polish cities, shows that the majority of outlets offer cereals, processed fruit and vegetables as well as spices and the least shops – meat and sausages. The distributors mostly indicate unsatisfactory product range of suppliers as the reason for this situation. The main providers of the outlets are wholesalers, particularly in case of processed products, and in fresh products – organic farms. A very important distribution obstacle is dispersion of producers, which generates high transportation costs and what follows that, high price of organics. In the investigated shops, the most often used price calculation method is a cost method. The majority of the groceries and specialist shops apply margins between 21 and 40%. The margin in specialist outlets is the highest, in regard to the qualified service and advice. In turn, most retail networks declare the margin between 0 and 20%, which is consistent with low-price strategy applied in these shops. Some lacks in the product range of organics and in particular high prices cause that the demand volume is rather low. Therefore there is a need to support certain market actions, e.g. on-farm processing or promotion.

Keywords: organic food, retail, product range, supply sources

Procedia PDF Downloads 285

Authors: B. Samuel Raj, Solomon R. D. Jebakumar

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Microbial fuel cells (MFCs) are an emerging and promising method for achieving sustainable energy since they can remove contaminated organic matter and simultaneously generate electricity. Our approach was driven in three different ways like Bacterial fuel cell, Soil Microbial fuel cell (Soil MFC) and Plant Microbial fuel cell (Plant MFC). Bacterial MFC: Sulphate reducing bacteria (SRB) were isolated and identified as the efficient electricigens which is able to produce ±2.5V (689mW/m2) and it has sustainable activity for 120 days. Experimental data with different MFC revealed that high electricity production harvested continuously for 90 days 1.45V (381mW/m2), 1.98V (456mW/m2) respectively. Biofilm formation was confirmed on the surface of the anode by high content screening (HCS) and scanning electron Microscopic analysis (SEM). Soil MFC: Soil MFC was constructed with low cost and standard Mudwatt soil MFC was purchased from keegotech (USA). Vermicompost soil (V1) produce high energy (± 3.5V for ± 400 days) compared to Agricultural soil (A1) (± 2V for ± 150 days). Biofilm formation was confirmed by HCS and SEM analysis. This finding provides a method for extracting energy from organic matter, but also suggests a strategy for promoting the bioremediation of organic contaminants in subsurface environments. Our Soil MFC were able to run successfully a 3.5V fan and three LED continuously for 150 days. Plant MFC: Amaranthus candatus (P1) and Triticum aestivium (P2) were used in Plant MFC to confirm the electricity production from plant associated microbes, four uniform size of Plant MFC were constructed and checked for energy production. P2 produce high energy (± 3.2V for 40 days) with harvesting interval of two times and P1 produces moderate energy without harvesting interval (±1.5V for 24 days). P2 is able run 3.5V fan continuously for 10days whereas P1 needs optimization of growth conditions to produce high energy.

Keywords: microbial fuel cell, biofilm, soil microbial fuel cell, plant microbial fuel cell

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Authors: Zain Ul Hassan, Muhammad Zain Ul Abadin, Muhammad Zubair Khan

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Unmanned aerial vehicles (UAVs) have now become of predominant importance for various operations, and an immense amount of work is going on in this specific category. The structural stability and life of these UAVs is key factor that should be considered while deploying them to different intelligent operations as their failure leads to loss of sensitive real-time data and cost. This paper presents an applied research on the development of a structural health monitoring system for a UAV designed and fabricated by deploying modular approach. Firstly, a modular UAV has been designed which allows to dismantle and to reassemble the components of the UAV without effecting the whole assembly of UAV. This novel approach makes the vehicle very sustainable and decreases its maintenance cost to a significant value by making possible to replace only the part leading to failure. Then the SHM for the designed architecture of the UAV had been specified as a combination of wings integrated with strain gauges, on-board data logger, bridge circuitry and the ground station. For the research purpose sensors have only been attached to the wings being the most load bearing part and as per analysis was done on ANSYS. On the basis of analysis of the load time spectrum obtained by the data logger during flight, fatigue life of the respective component has been predicted using fracture mechanics techniques of Rain Flow Method and Miner’s Rule. Thus allowing us to monitor the health of a specified component time to time aiding to avoid any failure.

Keywords: fracture mechanics, rain flow method, structural health monitoring system, unmanned aerial vehicle

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Authors: J.P. Henriques, E. R. Neto, G. Almeida, G. Ribeiro, J.V. Coutinho, A.B. Lugli

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Industry 4.0, or the Fourth Industrial Revolution, is transforming the relationship between people and machines. In this scenario, some technologies such as Cloud Computing, Internet of Things, Augmented Reality, Artificial Intelligence, Additive Manufacturing, among others, are making industries and devices increasingly intelligent. One of the most powerful technologies of this new revolution is the Digital Twin, which allows the virtualization of a real system or process. In this context, the present paper addresses the linear and nonlinear dynamic study of a didactic level plant using Digital Twin. In the first part of the work, the level plant is identified at a fixed point of operation, BY using the existing method of least squares means. The linearized model is embedded in a Digital Twin using Automation Studio® from Famous Technologies. Finally, in order to validate the usage of the Digital Twin in the linearized study of the plant, the dynamic response of the real system is compared to the Digital Twin. Furthermore, in order to develop the nonlinear model on a Digital Twin, the didactic level plant is identified by using the method proposed by Hammerstein. Different steps are applied to the plant, and from the Hammerstein algorithm, the nonlinear model is obtained for all operating ranges of the plant. As for the linear approach, the nonlinear model is embedded in the Digital Twin, and the dynamic response is compared to the real system in different points of operation. Finally, yet importantly, from the practical results obtained, one can conclude that the usage of Digital Twin to study the dynamic systems is extremely useful in the industrial environment, taking into account that it is possible to develop and tune controllers BY using the virtual model of the real systems.

Keywords: industry 4.0, digital twin, system identification, linear and nonlinear models

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