Search results for: damaged detection

Authors: Munenari Inoguchi, Keiko Tamura

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In Japan, we were suffered by earthquake, typhoon, and flood disaster in 2019. Especially, 38 of 47 prefectures were affected by typhoon #1919 occurred in October 2019. By this disaster, 99 people were dead, three people were missing, and 484 people were injured as human damage. Furthermore, 3,081 buildings were totally collapsed, 24,998 buildings were half-collapsed. Once disaster occurs, local responders have to inspect damage level of each building by themselves in order to certificate building damage for survivors for starting their life reconstruction process. At that disaster, the total number to be inspected was so high. Based on this situation, Cabinet Office of Japan approved the way to detect building damage level efficiently, that is collectively detection. However, they proposed a just guideline, and local responders had to establish the concrete and infallible method by themselves. Against this issue, we decided to establish the effective and efficient methodology to detect building damage level collectively with flood depth. Besides, we thought that the flood depth was relied on the land height, and we decided to utilize GIS (Geographic Information System) for analyzing the elevation spatially. We focused on the analyzing tool of spatial interpolation, which is utilized to survey the ground water level usually. In establishing the methodology, we considered 4 key-points: 1) how to satisfy the condition defined in the guideline approved by Cabinet Office for detecting building damage level, 2) how to satisfy survivors for the result of building damage level, 3) how to keep equitability and fairness because the detection of building damage level was executed by public institution, 4) how to reduce cost of time and human-resource because they do not have enough time and human-resource for disaster response. Then, we proposed a methodology for detecting building damage level collectively with flood depth utilizing GIS with five steps. First is to obtain the boundary of flooded area. Second is to collect the actual flood depth as sampling over flooded area. Third is to execute spatial analysis of interpolation with sampled flood depth to detect two-dimensional flood depth extent. Fourth is to divide to blocks by four categories of flood depth (non-flooded, over the floor to 100 cm, 100 cm to 180 cm and over 180 cm) following lines of roads for getting satisfaction from survivors. Fifth is to put flood depth level to each building. In Koriyama city of Fukushima prefecture, we proposed the methodology of collectively detection for building damage level as described above, and local responders decided to adopt our methodology at typhoon #1919 in 2019. Then, we and local responders detect building damage level collectively to over 1,000 buildings. We have received good feedback that the methodology was so simple, and it reduced cost of time and human-resources.

Keywords: building damage inspection, flood, geographic information system, spatial interpolation

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Authors: Okike Benjamin

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Terrorism is the use of violence and threat to intimidate or coerce a person, group, society or even government especially for political purposes. Terrorism may be a way of resisting government by some group who may feel marginalized. It could also be a way of expressing displeasure over the activities of government. On 26th December, 2009, US placed Nigeria as a terrorist nation. Recently, the occurrences of terrorism in Nigeria have increased considerably. In Jos, Plateau state, Nigeria, there was a bomb blast which claimed many lives on the eve of 2010 Christmas. Similarly, there was another bomb blast in Mugadishi (Sani Abacha) Barracks Mammy market on the eve of 2011 New Year. For some time now, it is no longer news that bomb exploded in some Northern part of Nigeria. About 25 years ago, stopping terrorism in America by the Americans relied on old-fashioned tools such as strict physical security at vulnerable places, intelligence gathering by government agents, or individuals, vigilance on the part of all citizens, and a sense of community in which citizens do what could be done to protect each other. Just as technology has virtually been used to better the way many other things are done, so also this powerful new weapon called computer technology can be used to detect and prevent terrorism not only in Nigeria, but all over the world. This paper will x-ray the possible causes and effects of bomb blast, which is an act of terrorism and suggest ways in which Explosive Detection Devices (EDDs) and computer software technology could be deployed to reduce the occurrences of terrorism in Nigeria. This become necessary with the abduction of over 200 schoolgirls in Chibok, Borno State from their hostel by members of Boko Haram sect members on 14th April, 2014. Presently, Barrack Obama and other world leaders have sent some of their military personnel to help rescue those innocent schoolgirls whose offence is simply seeking to acquire western education which the sect strongly believe is forbidden.

Keywords: terrorism, bomb blast, computer technology, explosive detection devices, Nigeria

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Authors: Kai-Fen Tu, Jenn-Wen Huang, Yao-Tung Lin

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Cucumber is a major economic crop in the world. The global production of cucumber in 2017 was more than 71 million tonnes. Nonetheless, downy mildew, caused by Pseudoperonospora cubensis, is a devastating and common disease on cucumber in around 80 countries and causes severe economic losses. The long-term usage of fungicide also leads to the occurrence of fungicide resistance and decreases host resistance. In this study, six types of oil (neem oil, moringa oil, soybean oil, cinnamon oil, clove oil, and camellia oil) were selected to synthesize micro/nano-sized emulsions, and the disease control efficacy of micro/nano-sized emulsions were evaluated. Moreover, oil concentrations (0.125% - 1%) and droplet size of emulsion were studied. Results showed cinnamon-type emulsion had the best efficacy among these oils. The disease control efficacy of these emulsions increased as the oil concentration increased. Both disease incidence and disease severity were measured by detached leaf and pot experiment, respectively. For the droplet size effect, results showed that the 114 nm of droplet size synthesized by 0.25% cinnamon oil emulsion had the lowest disease incidence (6.67%) and lowest disease severity (33.33%). The release of zoospore was inhibited (5.33%), and the sporangia germination was damaged. These results suggest that cinnamon oil emulsion will be a valuable and environmentally friendly alternative to control cucumber downy mildew. The economic loss caused by plant disease could also be reduced.

Keywords: downy mildew, emulsion, oil droplet size, plant protectant

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Authors: Ogbuagu Josephat Okechukwu, Okeke Abuchi Princewill, Arinze Rosemary Uche, Tabugbo Ifeyinwa Blessing, Ogbuagu Adaora Stellamaris

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Phthalates or Phthalate esters (PAEs), categorized as an endocrine disruptor and persistent organic pollutants, are known for their environmental contamination and toxicological effects. In this study, the concentration of selected phthalates was determined across the sampling site to investigate their occurrence and the ecological and health risk assessment they pose to the environment. Water and sediment samples were collected following standard procedures. Solid phase and ultrasonic methods were used to extract seven different PAEs, which were analyzed by Gas Chromatography with Mass Detector (GCMS). The analytical average recovery was found to be within the range of 83.4% ± 2.3%. The results showed that PAEs were detected in six out of seven samples with a high percentage of detection rate in water. Di-n-butyl phthalate (DPB) and disobutyl phthalates (DiBP) showed a greater detection rate compared to other PAE monomers. The concentration of PEs was found to be higher in sediment samples compared to water samples due to the fact that sediments serve as a sink for most persistent organic pollutants. The concentrations of PAEs in water samples and sediments ranged from 0.00 to 0.23 mg/kg and 0.00 to 0.028 mg/l, respectively. Ecological risk assessment using the risk quotient method (RQ) reveals that the estimated environmental risk caused by phthalates lies within the moderate level as RQ ranges from 0.1 to 1.0, whereas the health risk assessment caused by phthalates on estimating the average daily dose reveals that the ingestion of phthalates was found to be approaching permissible limit which can cause serious carcinogenic occurrence in the human system with time due to excess accumulation.

Keywords: phthalates, endocrine disruptor, risk assessment, ecological risk, health risk

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Authors: R. K. Yadav, S. Baral, H. R. Paudel, R. Basnet

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The Public-Private Mix (PPM) approach is a strategic initiative that involves engaging all private and public healthcare providers in the fight against tuberculosis using international healthcare standards. For tuberculosis control in Nepal, the PPM approach could be a milestone. This study aimed to explore the barriers to a public-private mix approach in the management of tuberculosis cases in Nepal. A total of 20 respondents participated in the study. Barriers to PPM were identified in the following three themes: 1) Obstacles related to TB case detection, 2) Obstacles related to patients, and 3) Obstacles related to the healthcare system. PPM implementation was challenged by following subthemes that included staff turnover, low private sector participation in workshops, a lack of training, poor recording and reporting, insufficient joint monitoring and supervision, poor financial benefit, lack of coordination and collaboration, and non-supportive TB-related policies and strategies. The study concludes that numerous barriers exist in the way of effective implementation of the PPM approach, including TB cases detection barriers such as knowledge of TB diagnosis and treatment, HW attitude, workload, patient-related barriers such as knowledge of TB, self-medication practice, stigma and discrimination, financial status, and health system-related barriers such as staff turnover and poor engagement of the private sector in workshops, training, recording, and re-evaluation. Government stakeholders must work together with private sector stakeholders to perform joint monitoring and supervision. Private practitioners should receive training and orientation, and presumptive TB patients should be given adequate time and counseling as well as motivation to visit a government health facility.

Keywords: barrier, tuberculosis, case finding, PPM, nepal

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Authors: Rahmat Ali, Amjad Naseer, Abid A. Shah

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This paper is an attempt to presents the performance of building observed during 26th Oct, 2015 earthquake in District Swat and Shangla region. Most of the buildings in the earthquake hit areas were built with Rubble stone masonry, dress Stone Masonry, brick masonry with and without RC column, Brick masonry with RC beams and column, Block Masonry with and without RC column. It was found that most of the buildings were built without proper supervision and without following any codes. A majority of load bearing masonry walls were highly affected during the earthquake. The load bearing walls built with rubble stone masonry were collapsed resulting huge damages and loss of property and life. Load bearing bricks masonry walls were also affected in most of the region. In some residential buildings the bricks were crushed in a single brick walls. Severe cracks were also found in double brick masonry walls. In RC frame structure beams and columns were also seriously affected. A majority of building structures were non-engineered. Some buildings designed by unskilled local consultants were also affected during the earthquake. Several architectural and structural mistakes were also found in various buildings designed by local consultant. It was found that the structures were collapsed prematurely either because of unskillful labor and using substandard materials or avoiding delicate repair, maintenance, and health monitoring activities because of lack of available sophisticated technology in our country.

Keywords: cracks, collapse, earthquake, masonry, repair

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Authors: Adesuyi Ayodeji Steve, Zahn Munch

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This study investigates the use of MODIS NDVI to identify agricultural land cover change areas on an annual time step (2007 - 2012) and characterize the trend in the study area. An ISODATA classification was performed on the MODIS imagery to select only the agricultural class producing 3 class groups namely: agriculture, agriculture/semi-natural, and semi-natural. NDVI signatures were created for the time series to identify areas dominated by cereals and vineyards with the aid of ancillary, pictometry and field sample data. The NDVI signature curve and training samples aided in creating a decision tree model in WEKA 3.6.9. From the training samples two classification models were built in WEKA using decision tree classifier (J48) algorithm; Model 1 included ISODATA classification and Model 2 without, both having accuracies of 90.7% and 88.3% respectively. The two models were used to classify the whole study area, thus producing two land cover maps with Model 1 and 2 having classification accuracies of 77% and 80% respectively. Model 2 was used to create change detection maps for all the other years. Subtle changes and areas of consistency (unchanged) were observed in the agricultural classes and crop practices over the years as predicted by the land cover classification. 41% of the catchment comprises of cereals with 35% possibly following a crop rotation system. Vineyard largely remained constant over the years, with some conversion to vineyard (1%) from other land cover classes. Some of the changes might be as a result of misclassification and crop rotation system.

Keywords: change detection, land cover, modis, NDVI

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Authors: Emin Z. Mahmud

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This paper presents the observations from a series of shaking-table tests done on a 1:1 scaled confined masonry wall model, with opening for a door – specimens CMDuS (confined masonry wall with opening for a door before strengthening) and CMDS (confined masonry wall with opening for a door after strengthening). Frequency and stiffness changes before and after GFRP (Glass Fiber Reinforced Plastic) wall strengthening are analyzed. Definition of dynamic properties of the models was the first step of the experimental testing, which enabled acquiring important information about the achieved stiffness (natural frequencies) of the model. The natural frequency was defined in the Y direction of the model by applying resonant frequency search tests. It is important to mention that both specimens CMDuS and CMDS are subjected to the same effects. The tests are realized in the laboratory of the Institute of Earthquake Engineering and Engineering Seismology (IZIIS), Skopje. The specimens were examined separately on the shaking table, with uniaxial, in-plane excitation. After testing, samples were strengthened with GFRP and re-tested. The initial frequency of the undamaged model CMDuS is 13.55 Hz, while at the end of the testing, the frequency decreased to 6.38 Hz. This emphasizes the reduction of the initial stiffness of the model due to damage, especially in the masonry and tie-beam to tie-column connection. After strengthening of the damaged wall, the natural frequency increases to 10.89 Hz. This highlights the beneficial effect of the strengthening. After completion of dynamic testing at CMDS, the natural frequency is reduced to 6.66 Hz.

Keywords: behaviour of masonry structures, Eurocode, frequency, masonry, shaking table test, strengthening

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Authors: Aanh Eduardo Dimate-Garcia, Diana Carolina Rodriguez-Romero, Edna Yuliana Gonzalez Rincon, Diana Marcela Pardo Lopez, Yessica Garibello Cubillos

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Musculoskeletal disorders (MD) are the new epidemic of chronic diseases, are multifactorial and affect the different productive sectors. Although there are multiple instruments to evaluate the static and dynamic load, the method of repetitive occupational action (OCRA) seems to be an attractive option. Objective: It is aimed to analyze the use of the OCRA method and the prevalence of MD in workers of various productive sectors according to the literature (2007-2018). Materials and Methods: A literature review (following the PRISMA statement) of studies aimed at assessing the level of biomechanical risk (OCRA) and the prevalence of MD in the databases Scielo, Science Direct, Scopus, ProQuest, Gale, PubMed, Lilacs and Ebsco was realized; 7 studies met the selection criteria; the majority are quantitative (cross section). Results: it was evidenced (gardening and flower-growers) in this review that 79% of the conditions related to the task require physical requirements and involve repetitive movements. In addition, of the high appearance of DM in the high-low back, upper and lower extremities that are produced by the frequency of the activities carried out (footwear production). Likewise, there was evidence of 'very high risks' of developing MD (salmon industry) and a medium index (OCRA) for repetitive movements that require special care (U-Assembly line). Conclusions: the review showed the limited use of the OCRA method for the detection of MD in workers from different sectors, and this method can be used for the detection of biomechanical risk and the appearance of MD.

Keywords: checklist, cumulative trauma disorders, musculoskeletal diseases, repetitive movements

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Authors: Swathi Gopakumar, Sruthi Krishna, Shivasubramani Krishnamoorthy

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Contactless, painless and radiation-free thermal imaging technology is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer-aided diagnosis of breast cancer. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: (I) marker-controlled, Level-set segmentation of anisotropic diffusion filtered preprocessed image versus (II) Segmentation using marker-controlled level-set on a Gaussian-filtered image. Gaussian-filtering processes the image uniformly, whereas anisotropic filtering processes only in specific areas of a thermographic image. The pre-processed (Gaussian-filtered and anisotropic-filtered) images of breast samples were then applied for segmentation. The segmentation of breast starts with initial level-set function. In this study, marker refers to the position of the image to which initial level-set function is applied. The markers are generally placed on the left and right side of the breast, which may vary with the breast size. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer-aided diagnosis of breast cancer.

Keywords: anisotropic diffusion, breast, Gaussian, level-set, thermograms

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Authors: Abeer A. Aljohani

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COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred to as coronavirus, which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. This research aims to predict COVID-19 disease in its initial stage to reduce the death count. Machine learning (ML) is nowadays used in almost every area. Numerous COVID-19 cases have produced a huge burden on the hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease is based on the symptoms and medical history of the patient. This research presents a unique architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard UCI dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques to the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and the principal component analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, receiver operating characteristic (ROC), and area under curve (AUC). The results depict that decision tree, random forest, and neural networks outperform all other state-of-the-art ML techniques. This achieved result can help effectively in identifying COVID-19 infection cases.

Keywords: supervised machine learning, COVID-19 prediction, healthcare analytics, random forest, neural network

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Authors: Şeyma Özçirak Ergün, Ergün Şakalar, Emrah Yalazi̇, Nebahat Şahi̇n

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Food irradiation is a usage of exposing food to ionising radiation (IR) such as gamma rays. IR has been used to decrease the number of harmful microorganisms in the food such as spices. Excessive usage of IR can cause damage to both food and people who consuming food. And also it causes to damages on food DNA. Generally, IR detection techniques were utilized in literature for spices are Electron Spin Resonance (ESR), Thermos Luminescence (TL). Storage creates negative effect on IR detection method then analyses of samples have been performed without storage in general. In the experimental part, red pepper (Capsicum annuum) and mint (Mentha piperita) as spices were exposed to 0, 0.272, 0.497, 1.06, 3.64, 8.82, and 17.42 kGy ionize radiation. ESR was applied to samples irradiated. DNA isolation from irradiated samples was performed using GIDAGEN Multi Fast DNA isolation kit. The DNA concentration was measured using a microplate reader spectrophotometer (Infinite® 200 PRO-Life Science–Tecan). The concentration of each DNA was adjusted to 50 ng/µL. Genomic DNA was imaged by UV transilluminator (Gel Doc XR System, Bio-Rad) for the estimation of genomic DNA bp-fragment size after IR. Thus, agarose gel profiles of irradiated spices were obtained to determine the change of band profiles. Besides, samples were examined at three different time periods (0, 3, 6 months storage) to show the feasibility of developed method. Results of gel electrophoresis showed especially degradation of DNA of irradiated samples. In conclusion, this study with gel electrophoresis can be used as a basis for the identification of the dose of irradiation by looking at degradation profiles at specific amounts of irradiation. Agarose gel results of irradiated samples were confirmed with ESR analysis. This method can be applied widely to not only food products but also all biological materials containing DNA to predict radiation-induced damage of DNA.

Keywords: DNA, electrophoresis, gel electrophoresis, ionizeradiation

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Authors: Abdul Khalique Baloch, Ali Okatan

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The quality analysis of food and vegetable from image is hot topic now a day, where researchers make them better then pervious findings through different technique and methods. In this research we have review the literature, and find gape from them, and suggest better proposed approach, design the algorithm, developed a software to measure the quality from images, where accuracy of image show better results, and compare the results with Perouse work done so for. The Application we uses an open-source dataset and python language with tensor flow lite framework. In this research we focus to sort food and vegetable from image, in the images, the application can sorts and make them grading after process the images, it could create less errors them human base sorting errors by manual grading. Digital pictures datasets were created. The collected images arranged by classes. The classification accuracy of the system was about 94%. As fruits and vegetables play main role in day-to-day life, the quality of fruits and vegetables is necessary in evaluating agricultural produce, the customer always buy good quality fruits and vegetables. This document is about quality detection of fruit and vegetables using images. Most of customers suffering due to unhealthy foods and vegetables by suppliers, so there is no proper quality measurement level followed by hotel managements. it have developed software to measure the quality of the fruits and vegetables by using images, it will tell you how is your fruits and vegetables are fresh or rotten. Some algorithms reviewed in this thesis including digital images, ResNet, VGG16, CNN and Transfer Learning grading feature extraction. This application used an open source dataset of images and language used python, and designs a framework of system.

Keywords: deep learning, computer vision, image processing, rotten fruit detection, fruits quality criteria, vegetables quality criteria

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Authors: Nadia El Alami El Hassani, Soukaina Motia, Benachir Bouchikhi, Nezha El Bari

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Doxycycline (DXy) is a cycline antibiotic, most frequently prescribed to treat bacterial infections in veterinary medicine. However, its broad antimicrobial activity and low cost, lead to an intensive use, which can seriously affect human health. Therefore, its spread in the food products has to be monitored. The scope of this work was to synthetize a sensitive and very selective molecularly imprinted polymer (MIP) for DXy detection in honey samples. Firstly, the synthesis of this biosensor was performed by casting a layer of carboxylate polyvinyl chloride (PVC-COOH) on the working surface of a gold screen-printed electrode (Au-SPE) in order to bind covalently the analyte under mild conditions. Secondly, DXy as a template molecule was bounded to the activated carboxylic groups, and the formation of MIP was performed by a biocompatible polymer by the mean of polyacrylamide matrix. Then, DXy was detected by measurements of differential pulse voltammetry (DPV). A non-imprinted polymer (NIP) prepared in the same conditions and without the use of template molecule was also performed. We have noticed that the elaborated biosensor exhibits a high sensitivity and a linear behavior between the regenerated current and the logarithmic concentrations of DXy from 0.1 pg.mL⁻¹ to 1000 pg.mL⁻¹. This technic was successfully applied to determine DXy residues in honey samples with a limit of detection (LOD) of 0.1 pg.mL⁻¹ and an excellent selectivity when compared to the results of oxytetracycline (OXy) as analogous interfering compound. The proposed method is cheap, sensitive, selective, simple, and is applied successfully to detect DXy in honey with the recoveries of 87% and 95%. Considering these advantages, this system provides a further perspective for food quality control in industrial fields.

Keywords: doxycycline, electrochemical sensor, food control, gold nanoparticles, honey, molecular imprinted polymer

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Authors: Dylan Treger, Lujia Zhang, Xiaoxiao Jia, Jessica H. Hui, Munkh-Amgalan Gantumur, Mizhou Hui, Li Liu

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Hyaluronic acid (HA) is involved in wound healing via inflammation, granulation, and re-epithelialization mechanisms. The poor physical properties of natural high-molecular-weight polymers limit their direct use in the medical field. In this clinical study, we investigated whether the local injection of a tissue-permeable 35 kDa HA fragment (HA35) could favor the healing process in patients with chronic wounds accompanied by neuropathic pain. The HA35 fragments were freshly manufactured by degradation of high-molecular-weight HA with bovine testis-derived hyaluronidase PH20. Twenty patients in this study had nonhealing wounds and wound-related pain for more than 3 months. Freshly produced HA35 was locally injected into healthy skin immediately surrounding chronic wounds once a day for 10 days. Wound-associated pain and the degree of wound healing were evaluated. The injection of HA35 relieved the pain associated with chronic wounds in 24 hours. HA35 treatment significantly promoted the healing of chronic wounds, including expanded fresh granulation tissue on the wounds; reduced darkness or redness, dryness, and damaged areas on the surface of the skin surrounding the wounds; and decreased the size of the wound area. It can be concluded that the topical injection of tissue-permeable HA35 around chronic wounds has great potential to promote wound healing.

Keywords: 35 kDa hyaluronan fragment HA35, chronic wound, wound healing, tissue permeability

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Authors: Vaibhav Budhiraja, Chandra Mouli Pandey

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The ultrasonic synthesis of nanostructured conducting copolymer is an effective technique to synthesize polymer with desired chemical properties. This tailored nanostructure, shows tremendous improvement in sensitivity and stability to detect a variety of analytes. The present work reports ultrasonically synthesized nanostructured conducting poly(o-phenylenediamine)-co-poly(1-naphthylamine) (POPD-co-PNA). The synthesized material has been characterized using Fourier transform infrared spectroscopy (FTIR), ultraviolet-visible spectroscopy, transmission electron microscopy, X-ray diffraction and cyclic voltammetry. FTIR spectroscopy confirmed random copolymerization, while UV-visible studies reveal the variation in polaronic states upon copolymerization. High crystallinity was achieved via ultrasonic synthesis which was confirmed by X-ray diffraction, and the controlled morphology of the nanostructures was confirmed by transmission electron microscopy analysis. Cyclic voltammetry shows that POPD-co-PNA has rather high electrochemical activity. This behavior was explained on the basis of variable orientations adopted by the conducting polymer chains. The synthesized material was electrophoretically deposited at onto indium tin oxide coated glass substrate which is used as cathode and parallel platinum plate as the counter electrode. The fabricated bioelectrode was further used for detection of glucose by crosslinking of glucose oxidase in the PODP-co-PNA film. The bioelectrode shows a surface-controlled electrode reaction with the electron transfer coefficient (α) of 0.72, charge transfer rate constant (ks) of 21.77 s⁻¹ and diffusion coefficient 7.354 × 10⁻¹⁵ cm²s⁻¹.

Keywords: conducting, electrophoretic, glucose, poly (o-phenylenediamine), poly (1-naphthylamine), ultrasonic

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Authors: David Polcari, Samuel C. Perry, Loredano Pollegioni, Matthias Geissler, Janine Mauzeroll

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ᴅ-serine acts as an endogenous co-agonist for N-methyl-ᴅ-aspartate receptors in neuronal synapses. This makes it a key component in the development and function of a healthy brain, especially given its role in several neurodegenerative diseases such as Alzheimer’s disease and dementia. Despite such clear research motivations, the primary site and mechanism of ᴅ-serine release is still currently unclear. For this reason, we are developing a biosensor for the detection of ᴅ-serine utilizing a microelectrode in combination with a ᴅ-amino acid oxidase enzyme, which produces stoichiometric quantities of hydrogen peroxide in response to ᴅ-serine. For the fabrication of a biosensor with good selectivity, we use a permselective poly(meta-phenylenediamine) film to ensure only the target molecule is reacted, according to the size exclusion principle. In this work, we investigated the effect of the electrodeposition conditions used on the biosensor’s response time and selectivity. Careful optimization of the fabrication process allowed for enhanced biosensor response time. This allowed for the real time sensing of ᴅ-serine in a bulk solution, and also provided in means to map the efflux of ᴅ-serine in real time. This was done using scanning electrochemical microscopy (SECM) with the optimized biosensor to measure localized release of ᴅ-serine from an agar filled glass capillary sealed in an epoxy puck, which acted as a model system. The SECM area scan simultaneously provided information regarding the rate of ᴅ-serine flux from the model substrate, as well as the size of the substrate itself. This SECM methodology, which provides high spatial and temporal resolution, could be useful to investigate the primary site and mechanism of ᴅ-serine release in other biological samples.

Keywords: ᴅ-serine, enzymatic biosensor, microelectrode, scanning electrochemical microscopy

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Authors: Mohamed Ahmed Khali

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Numbers of deep well anode ground beds (GBs) have been retrieved due to un operated anode chains. New identical magnetite anode chains(MAC) have been installed at Raslanuf complex impressed current Cathodic protection(ICCP) system, distributed at different plants(Utility, ethylene and polyethylene). All problems associated with retrieving and installation of MACs have been discussed, rectified and presented. All GB associated severely corroded wellhead casings were well maintained and/ or replaced by new fabricated and modified ones. The main cause of wellhead casings internal corrosion was discussed, and the conducted remedy action to overcome future corrosion problem is presented. All GB connected anode junction boxes (AJBs) and shunts were closely inspected, maintained, and necessary replacement/and or modification were carried out on shunts. All damaged GB concrete foundations (CF) have been inspected and completely replaced. All GB associated Transformer-Rectifiers units (TRUs) were subjected to through inspection, and necessary maintenance has been performed on each individual TRU. After completion of all MACs and TRU maintenance activities, each cathodic protection station (CPS) has been re-operated. An alternative current (AC), direct current (DC), voltage and structure to soil potential (S/P) measurements have been conducted, recorded, and all obtained test results are presented. DC current outputs has been adjusted, and DC current outputs of each MAC has been recorded for each GB AJB.

Keywords: magnatite anode, deep well, ground bed, cathodic protection, transformer rectifies, impreced current, junction box

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Authors: Andrej Golowin, Viktor Denk, Axel Riepe

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Solid fan blades and discs in aero engines are subjected to high combined low and high cycle fatigue loads especially around the contact areas between blade and disc. Therefore, special coatings (e.g. dry film lubricant) and surface treatments (e.g. shot peening or laser shock peening) are applied to increase the strength with respect to combined cyclic fatigue and fretting fatigue, but also to improve damage tolerance capability. The traditional deterministic damage tolerance assessment based on fracture mechanics analysis, which treats service damage as an initial crack, often gives overly conservative results especially in the presence of vibratory stresses. A probabilistic damage tolerance methodology using crack initiation data has been developed for fan discs exposed to relatively high vibratory stresses in cross- and tail-wind conditions at certain resonance speeds for limited time periods. This Monte-Carlo based method uses a damage databank from similar designs, measured vibration levels at typical aircraft operations and wind conditions and experimental crack initiation data derived from testing of artificially damaged specimens with representative surface treatment under combined fatigue conditions. The proposed methodology leads to a more realistic prediction of the minimum damage tolerance life for the most critical locations applicable to modern fan disc designs.

Keywords: combined fatigue, damage tolerance, engine, surface treatment

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Authors: Salvatore Luongo, Carlo Luongo

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This paper discusses the implementation solutions to reduce the computational load for the Traffic Situational Awareness with Alerts (TSAA) application, based on Automatic Dependent Surveillance-Broadcast (ADS-B) technology. In 2008, there were 23 total mid-air collisions involving general aviation fixed-wing aircraft, 6 of which were fatal leading to 21 fatalities. These collisions occurred during visual meteorological conditions, indicating the limitations of the see-and-avoid concept for mid-air collision avoidance as defined in the Federal Aviation Administration’s (FAA). The commercial aviation aircraft are already equipped with collision avoidance system called TCAS, which is based on classic transponder technology. This system dramatically reduced the number of mid-air collisions involving air transport aircraft. In general aviation, the same reduction in mid-air collisions has not occurred, so this reduction is the main objective of the TSAA application. The major difference between the original conflict detection application and the TSAA application is that the conflict detection is focused on preventing loss of separation in en-route environments. Instead TSAA is devoted to reducing the probability of mid-air collision in all phases of flight. The TSAA application increases the flight crew traffic situation awareness providing alerts of traffic that are detected in conflict with ownship in support of the see-and-avoid responsibility. The relevant effort has been spent in the design process and the code generation in order to maximize the efficiency and performances in terms of computational load and memory consumption reduction. The TSAA architecture is divided into two high-level systems: the “Threats database” and the “Conflict detector”. The first one receives the traffic data from ADS-B device and provides the memorization of the target’s data history. Conflict detector module estimates ownship and targets trajectories in order to perform the detection of possible future loss of separation between ownship and each target. Finally, the alerts are verified by additional conflict verification logic, in order to prevent possible undesirable behaviors of the alert flag. In order to reduce the computational load, a pre-check evaluation module is used. This pre-check is only a computational optimization, so the performances of the conflict detector system are not modified in terms of number of alerts detected. The pre-check module uses analytical trajectories propagation for both target and ownship. This allows major accuracy and avoids the step-by-step propagation, which requests major computational load. Furthermore, the pre-check permits to exclude the target that is certainly not a threat, using an analytical and efficient geometrical approach, in order to decrease the computational load for the following modules. This software improvement is not suggested by FAA documents, and so it is the main innovation of this work. The efficiency and efficacy of this enhancement are verified using fast-time and real-time simulations and by the execution on a real device in several FAA scenarios. The final implementation also permits the FAA software certification in compliance with DO-178B standard. The computational load reduction allows the installation of TSAA application also on devices with multiple applications and/or low capacity in terms of available memory and computational capabilities

Keywords: traffic situation awareness, general aviation, aircraft conflict detection, computational load reduction, implementation solutions, software certification

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Authors: Eliza. E. Camaso, Guiller. B. Damian, Miguelito. F. Isip, Ronaldo T. Alberto

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Land-cover maps were important for many scientific, ecological and land management purposes and during the last decades, rapid decrease of soil fertility was observed to be due to land use practices such as rice cultivation. High-precision land-cover maps are not yet available in the area which is important in an economy management. To assure   accurate mapping of land cover to provide information, remote sensing is a very suitable tool to carry out this task and automatic land use and cover detection. The study did not only provide high precision land cover maps but it also provides estimates of rice production area that had undergone chemical degradation due to fertility decline. Land-cover were delineated and classified into pre-defined classes to achieve proper detection features. After generation of Land-cover map, of high intensity of rice cultivation, soil fertility degradation assessment in rice production area due to fertility decline was created to assess the impact of soils used in agricultural production. Using Simple spatial analysis functions and ArcGIS, the Land-cover map of Municipality of Quezon in Nueva Ecija, Philippines was overlaid to the fertility decline maps from Land Degradation Assessment Philippines- Bureau of Soils and Water Management (LADA-Philippines-BSWM) to determine the area of rice crops that were most likely where nitrogen, phosphorus, zinc and sulfur deficiencies were induced by high dosage of urea and imbalance N:P fertilization. The result found out that 80.00 % of fallow and 99.81% of rice production area has high soil fertility decline.

Keywords: aerial image, landcover, LiDAR, soil fertility degradation

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Authors: Kangujam Monika, Kiranbala Devi Thokchom, Soibam Sandhyarani Devi

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Earthquake is a major natural hazard in India. Manipur, located in the North-Eastern Region of India, is one of the most affected location in the region prone to earthquakes since it lies in an area where Indian and Eurasian tectonic plates meet and is in seismic Zone V which is the most severe intensity zone, according to IS Code. Some recent earthquakes recorded in Manipur are M 6.7 epicenter at Tamenglong (January 4, 2016), M 5.2 epicenter at Churachandpur (February 24, 2017) and most recent M 4.4 epicenter at Thoubal (June 19, 2017). In these recent earthquakes, some houses and buildings were damaged, landslides were also occurred. A field study was carried out. An overview of the various causal factors involved in triggering of earthquake in Manipur has been discussed. It is found that improper planning, poor design, negligence, structural irregularities, poor quality materials, construction of foundation without proper site soil investigation and non-implementation of remedial measures, etc., are possibly the main causal factors for damage in Manipur during earthquake. The study also suggests, though the proper design of structure and foundation along with soil investigation, ground improvement methods, use of modern techniques of construction, counseling with engineer, mass awareness, etc., might be effective solution to control the hazard in many locations. An overview on the analysis pertaining to earthquake in Manipur together with on-going detailed site specific geotechnical investigation were presented.

Keywords: Manipur, earthquake, hazard, structure, soil

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Authors: Oumaima Khlifati, Khadija Baba

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Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

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Authors: Gaurav Bhanjana, Ganga Ram Chaudhary, Sandeep Kumar, Neeraj Dilbaghi

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Main sources of endocrine disrupting compounds in the ecosystem are hormones, pesticides, phthalates, flame retardants, dioxins, personal-care products, coplanar polychlorinated biphenyls (PCBs), bisphenol A, and parabens. These endocrine disrupting compounds are responsible for learning disabilities, brain development problems, deformations of the body, cancer, reproductive abnormalities in females and decreased sperm count in human males. Although discharge of these chemical compounds into the environment cannot be stopped, yet their amount can be retarded through proper evaluation and detection techniques. The available techniques for determination of these endocrine disrupting compounds mainly include high performance liquid chromatography (HPLC), mass spectroscopy (MS) and gas chromatography-mass spectrometry (GC–MS). These techniques are accurate and reliable but have certain limitations like need of skilled personnel, time consuming, interference and requirement of pretreatment steps. Moreover, these techniques are laboratory bound and sample is required in large amount for analysis. In view of above facts, new methods for detection of endocrine disrupting compounds should be devised that promise high specificity, ultra sensitivity, cost effective, efficient and easy-to-operate procedure. Nowadays, electrochemical sensors/biosensors modified with nanomaterials are gaining high attention among researchers. Bioelement present in this system makes the developed sensors selective towards analyte of interest. Nanomaterials provide large surface area, high electron communication feature, enhanced catalytic activity and possibilities of chemical modifications. In most of the cases, nanomaterials also serve as an electron mediator or electrocatalyst for some analytes.

Keywords: electrochemical, endocrine disruptors, microscopy, nanoparticles, sensors

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Authors: Mohamed Amine Ben Henni, Taher Hassaine Daouadji, Boussad Abbes, Yu Ming Li, Fazilay Abbes

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The reinforcement and repair of concrete structures by bonding composite materials have become relatively common operations. Different types of composite materials can be used: carbon fiber reinforced polymer (CFRP), glass fiber reinforced polymer (GFRP) as well as functionally graded material (FGM). The development of analytical and numerical models describing the mechanical behavior of structures in civil engineering reinforced by composite materials is necessary. These models will enable engineers to select, design, and size adequate reinforcements for the various types of damaged structures. This study focuses on the free vibration behavior of orthotropic laminated composite plates using a refined shear deformation theory. In these models, the distribution of transverse shear stresses is considered as parabolic satisfying the zero-shear stress condition on the top and bottom surfaces of the plates without using shear correction factors. In this analysis, the equation of motion for simply supported thick laminated rectangular plates is obtained by using the Hamilton’s principle. The accuracy of the developed model is demonstrated by comparing our results with solutions derived from other higher order models and with data found in the literature. Besides, a finite-element analysis is used to calculate the natural frequencies of laminated composite plates and is compared with those obtained by the analytical approach.

Keywords: composites materials, laminated composite plate, finite-element analysis, free vibration

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Authors: Emin Z. Mahmud

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Shaking table tests are planned in order to deepen the understanding of the behavior of confined masonry structures with or without openings. The tests are realized in the laboratory of the Institute of Earthquake Engineering and Engineering Seismology (IZIIS) – Skopje. The specimens were examined separately on the shaking table, with uniaxial, in-plane excitation. After testing, samples were strengthened with GFRP (Glass Fiber Reinforced Plastic) and re-tested. This paper presents the observations from a series of shaking-table tests done on a 1:1 scaled confined masonry wall model, with opening for a window – specimens CMWuS (before strengthening) and CMWS (after strengthening). Frequency and stiffness changes before and after GFRP wall strengthening are analyzed. Definition of dynamic properties of the models was the first step of the experimental testing, which enabled acquiring important information about the achieved stiffness (natural frequencies) of the model. The natural frequency was defined in the Y direction of the model by applying resonant frequency search tests. It is important to mention that both specimens CMWuS and CMWS are subjected to the same effects. The initial frequency of the undamaged model CMWuS is 18.79 Hz, while at the end of the testing, the frequency decreased to 12.96 Hz. This emphasizes the reduction of the initial stiffness of the model due to damage, especially in the masonry and tie-beam to tie-column connection. After strengthening the damaged wall, the natural frequency increases to 14.67 Hz. This highlights the beneficial effect of strengthening. After completion of dynamic testing at CMWS, the natural frequency is reduced to 10.75 Hz.

Keywords: behaviour of masonry structures, Eurocode, frequency, masonry, shaking table test, strengthening

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Authors: Parvaneh Eskandari, Rachel O'Reilly

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In the last years, controlling the self-assembly behavior of stimuli-responsive nano-objects, including micelles, vesicles, worm-like, etc., at different conditions is considered a pertinent challenge in the polymer community. The aim of the project was to synthesize aggregation-induced emission (AIE)-active stimuli-responsive polymeric nano-objects to control the self-assemblies morphologies of the prepared nano-objects. Two types of nanoobjects, micelle and vesicles, including PDMAEMA-b-P(BzMA-TPEMA) [PDMAEMA: poly(N,Ndimethylaminoethyl methacrylate); P(BzMA-TPEMA): poly[benzyl methacrylate-co- tetraphenylethene methacrylate]] were synthesized by using reversible addition−fragmentation chain-transfer (RAFT)- mediated polymerization-induced self-assembly (PISA), which combines polymerization and self-assembly in a single step. Transmission electron microscope and dynamic light scattering (DLS) analysis were used to confirm the formed self-assemblies morphologies. The controlled self-assemblies were applied as nitrophenolic compounds (NPCs) adsorbents from wastewater, thanks to their CO2-responsive part, PDMAEMA. Moreover, the fluorescence-active part of the prepared nano-objects, P(BzMA-TPEMA), played a key role in the detection of the NPCs at the aqueous solution. The optical properties of the prepared nano-objects were studied by UV/Vis and fluorescence spectroscopies. For responsivity investigations, the hydrodynamic diameter and Zeta-potential (ζ-potential) of the sample's aqueous solution were measured by DLS. In the end, the prepared nano-objects were used for the detection and adsorption of different NPCs.

Keywords: aggregation-induced emission polymers, stimuli-responsive polymers, reversible addition−fragmentation chain-transfer polymerization, polymerization-induced self-assembly, wastewater treatment

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Authors: Vineeth Siripuram, Abhineet Nigam

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A bioreactor is an engineered system that supports a biologically active environment. Along the years, the advancements in bioreactors have been widely accepted all over the world for varied applications ranging from sewage treatment to tissue cloning. Driven by tissue and organ shortage, tissue engineering has emerged as an alternative to transplantation for the reconstruction of lost or damaged organs. In this study, Computational fluid dynamics (CFD) has been used to model porous medium flow in scaffolds (taken from the literature) with different flow patterns. A detailed analysis of different scaffold geometries and their influence on cell deposition in the perfusion system is been carried out using Computational fluid dynamics (CFD). Considering the fact that, the scaffold should mimic the organs or tissues structures in a three-dimensional manner, certain assumptions were made accordingly. The research on scaffolds has been extensively carried out in different bioreactors. However, there has been less focus on the morphology of the scaffolds and the flow patterns in which the perfusion system is laid upon. The objective of this paper is to employ a computational approach using CFD simulation to determine the optimal morphology and the anisotropic measurements of the various samples of scaffolds. Using predictive computational modelling approach, variables which exert dominant effects on the cell deposition within the scaffold were prioritised and corresponding changes in morphology of scaffold and flow patterns in the perfusion systems are made. A Eulerian approach was carried on in multiple CFD simulations, and it is observed that the morphological and topological changes in the scaffold perfusion system are of great importance in the commercial applications of scaffolds.

Keywords: cell seeding, CFD, flow patterns, modelling, perfusion systems, scaffold

Procedia PDF Downloads 161

Authors: Valeriy M. Kondratev, Ekaterina A. Vyacheslavova, Talgat Shugabaev, Alexander S. Gudovskikh, Alexey D. Bolshakov

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Modern sensorics imposes strict requirements on the biosensors characteristics, especially technological feasibility, and selectivity. There is a growing interest in the analysis of human health biological markers, which indirectly testifying the pathological processes in the body. Such markers are acids and alkalis produced by the human, in particular - ammonia and hydrochloric acid, which are found in human sweat, blood, and urine, as well as in gastric juice. Biosensors based on modern nanomaterials, especially low dimensional, can be used for this markers detection. Most classical adsorption sensors based on metal and silicon oxides are considered non-selective, because they identically change their electrical resistance (or impedance) under the action of adsorption of different target analytes. This work demonstrates a feasible frequency-resistive method of electrical impedance spectroscopy data analysis. The approach allows to obtain of selectivity in adsorption sensors of a resistive type. The method potential is demonstrated with analyzis of impedance spectra of silicon nanowires in the presence of NH3 and HCl vapors with concentrations of about 125 mmol/L (2 ppm) and water vapor. We demonstrate the possibility of unambiguous distinction of the sensory signal from NH3 and HCl adsorption. Moreover, the method is found applicable for analysis of the composition of ammonia and hydrochloric acid vapors mixture without water cross-sensitivity. Presented silicon sensor can be used to find diseases of the gastrointestinal tract by the qualitative and quantitative detection of ammonia and hydrochloric acid content in biological samples. The method of data analysis can be directly translated to other nanomaterials to analyze their applicability in the field of biosensory.

Keywords: electrical impedance spectroscopy, spectroscopy data analysis, selective adsorption sensor, nanotechnology

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Authors: Saleh Gorji, Sahil Gulati, Ana Pakzad

Abstract:

Continuous electron diffraction tomography, also known as microcrystal electron diffraction (MicroED) or three-dimensional electron diffraction (3DED), is a powerful technique, which in combination with cryo-electron microscopy (cryo-ED), can provide atomic-scale 3D information about the crystal structure and composition of different classes of crystalline materials such as proteins, peptides, and small molecules. Unlike the well-established X-ray crystallography method, 3DED does not require large single crystals and can collect accurate electron diffraction data from crystals as small as 50 – 100 nm. This is a critical advantage as growing larger crystals, as required by X-ray crystallography methods, is often very difficult, time-consuming, and expensive. In most cases, specimens studied via 3DED method are electron beam sensitive, which means there is a limitation on the maximum amount of electron dose one can use to collect the required data for a high-resolution structure determination. Therefore, collecting data using a conventional scintillator-based fiber coupled camera brings additional challenges. This is because of the inherent noise introduced during the electron-to-photon conversion in the scintillator and transfer of light via the fibers to the sensor, which results in a poor signal-to-noise ratio and requires a relatively higher and commonly specimen-damaging electron dose rates, especially for protein crystals. As in other cryo-EM techniques, damage to the specimen can be mitigated if a direct detection camera is used which provides a high signal-to-noise ratio at low electron doses. In this work, we have used two classes of such detectors from Gatan, namely the K3® camera (a monolithic active pixel sensor) and Stela™ (that utilizes DECTRIS hybrid-pixel technology), to address this problem. The K3 is an electron counting detector optimized for low-dose applications (like structural biology cryo-EM), and Stela is also a counting electron detector but optimized for diffraction applications with high speed and high dynamic range. Lastly, data collection workflows, including crystal screening, microscope optics setup (for imaging and diffraction), stage height adjustment at each crystal position, and tomogram acquisition, can be one of the other challenges of the 3DED technique. Traditionally this has been all done manually or in a partly automated fashion using open-source software and scripting, requiring long hours on the microscope (extra cost) and extensive user interaction with the system. We have recently introduced Latitude® D in DigitalMicrograph® software, which is compatible with all pre- and post-energy-filter Gatan cameras and enables 3DED data acquisition in an automated and optimized fashion. Higher quality 3DED data enables structure determination with higher confidence, while automated workflows allow these to be completed considerably faster than before. Using multiple examples, this work will demonstrate how to direct detection electron counting cameras enhance 3DED results (3 to better than 1 Angstrom) for protein and small molecule structure determination. We will also show how Latitude D software facilitates collecting such data in an integrated and fully automated user interface.

Keywords: continuous electron diffraction tomography, direct detection, diffraction, Latitude D, Digitalmicrograph, proteins, small molecules

Procedia PDF Downloads 107