Search results for: detect

Authors: Jannis Kountouras, Nikolaos Kapetanakis, Stergios A. Polyzos, Apostolis Papaeftymiou, Panagiotis Katsinelos, Ioannis Venizelos, Christina Nikolaidou, Christos Zavos, Iordanis Romiopoulos, Elena Tsiaousi, Evangelos Kazakos, Michael Doulberis

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Background & Aims: Helicobacter pylori infection (Hp-I) has been recognized as a substantial risk agent involved in gastrointestinal (GI) tract oncogenesis by stimulating cancer stem cells (CSCs), oncogenes, immune surveillance processes, and triggering GI microbiota dysbiosis. We aimed to investigate the possible involvement of active Hp-I in the sequence: chronic inflammation–adenoma–colorectal cancer (CRC) development. Methods: Four pillars were investigated: (i) endoscopic and conventional histological examinations of patients with CRC, colorectal adenomas (CRA) versus controls to detect the presence of active Hp-I; (ii) immunohistochemical determination of the presence of Hp; expression of CD44, an indicator of CSCs and/or bone marrow-derived stem cells (BMDSCs); expressions of oncogene Ki67 and anti-apoptotic Bcl-2 protein; (iii) expression of CD45, indicator of immune surveillance locally (assessing mainly T and B lymphocytes locally); and (iv) correlation of the studied parameters with the presence or absence of Hp-I. Results: Among 50 patients with CRC, 25 with CRA, and 10 controls, a significantly higher presence of Hp-I in the CRA (68%) and CRC group (84%) were found compared with controls (30%). The presence of Hp-I with accompanying immunohistochemical expression of CD44 in biopsy specimens was revealed in a high proportion of patients with CRA associated with moderate/severe dysplasia (88%) and CRC patients with moderate/severe degree of malignancy (91%). Comparable results were also obtained for Ki67, Bcl-2, and CD45 immunohistochemical expressions. Concluding Remarks: Hp-I seems to be involved in the sequence: CRA – dysplasia – CRC, similarly to the upper GI tract oncogenesis, by several pathways such as the following: Beyond Hp-I associated insulin resistance, the major underlying mechanism responsible for the metabolic syndrome (MetS) that increase the risk of colorectal neoplasms, as implied by other Hp-I related MetS pathologies, such as non-alcoholic fatty liver disease and upper GI cancer, the disturbance of the normal GI microbiota (i.e., dysbiosis) and the formation of an irritative biofilm could contribute to a perpetual inflammatory upper GIT and colon mucosal damage, stimulating CSCs or recruiting BMDSCs and affecting oncogenes and immune surveillance processes. Further large-scale relative studies with a pathophysiological perspective are necessary to demonstrate in-depth this relationship.

Keywords: Helicobacter pylori, colorectal cancer, colorectal adenomas, gastrointestinal oncogenesis

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Authors: B. T. Naveen Kumar, Anuj Tyagi, Niraj Kumar Singh, Visanu Boonyawiwat, A. H. Shanthanagouda, Orawan Boodde, K. M. Shankar, Prakash Patil, Shubhkaramjeet Kaur

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Early mortality syndrome (EMS)/Acute Hepatopancreatic Necrosis Disease (AHPND) has emerged as a major obstacle for the shrimp farming around the world. It is caused by a strain of Vibrio parahaemolyticus. The possible preventive and control measure is, early and rapid detection of the pathogen in the broodstock, post-larvae and monitoring the shrimp during the culture period. Polymerase chain reaction (PCR) based early detection methods are good, but they are costly, time taking and requires a sophisticated laboratory. The present study was conducted to develop a simple, sensitive and rapid diagnostic farmer level kit for the reliable detection of AHPND in shrimp. A panel of monoclonal antibodies (MAbs) were raised against the recombinant Pir B protein (rPirB). First, an immunodot was developed by using MAbs G3B8 and Mab G3H2 which showed specific reactivity to purified r-PirB protein with no cross-reactivity to other shrimp bacterial pathogens (AHPND free Vibrio parahaemolyticus (Indian strains), V. anguillarum, WSSV, Aeromonas hydrophila, and Aphanomyces invadans). Immunodot developed using Mab G3B8 is more sensitive than that with the Mab G3H2. However, immunodot takes almost 2.5 hours to complete with several hands-on steps. Therefore, the flow-through assay (FTA) was developed by using a plastic cassette containing the nitrocellulose membrane with absorbing pads below. The sample was dotted in the test zone on the nitrocellulose membrane followed by continuos addition of five solutions in the order of i) blocking buffer (BSA) ii) primary antibody (MAb) iii) washing Solution iv) secondary antibody and v) chromogen substrate (TMB) clear purple dots against a white background were considered as positive reactions. The FTA developed using MAbG3B8 is more sensitive than that with MAb G3H2. In FTA the two MAbs showed specific reactivity to purified r-PirB protein and not to other shrimp bacterial pathogens. The FTA is simple to farmer/field level, sensitive and rapid requiring only 8-10 min for completion. Tests can be developed to kits, which will be ideal for use in biosecurity, for the first line of screening (at the port or pond site) and during monitoring and surveillance programmes overall for the good management practices to reduce the risk of the disease.

Keywords: acute hepatopancreatic necrosis disease, AHPND, flow-through assay, FTA, farmer level, immunodot, pond site, shrimp

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Authors: N. Demertzis, J. L. Bowen

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Sepsis is a complex and rapidly evolving condition, resulting from uncontrolled prolonged activation of host immune system due to pathogenic insult. The aim of this study is the development of a multiplex electrochemical sensing platform, capable of detecting both pathogen associated and host immune markers to enable the rapid and definitive diagnosis of sepsis. A combination of aptamers and molecular imprinting approaches have been employed to generate sensing systems for lipopolysaccharide (LPS), c-reactive protein (CRP) and procalcitonin (PCT). Gold working electrodes were mechanically polished and electrochemically cleaned with 0.1 M sulphuric acid using cyclic voltammetry (CV). Following activation, a self-assembled monolayer (SAM) was generated, by incubating the electrodes with a thiolated anti-LPS aptamer / dithiodibutiric acid (DTBA) mixture (1:20). 3-aminophenylboronic acid (3-APBA) in combination with the anti-LPS aptamer was used for the development of the hybrid molecularly imprinted sensor (apta-MIP). Aptasensors, targeting PCT and CRP were also fabricated, following the same approach as in the case of LPS, with mercaptohexanol (MCH) replacing DTBA. In the case of the CRP aptasensor, the SAM was formed following incubation of a 1:1 aptamer: MCH mixture. However, in the case of PCT, the SAM was formed with the aptamer itself, with subsequent backfilling with 1 μM MCH. The binding performance of all systems has been evaluated using electrochemical impedance spectroscopy. The apta-MIP’s polymer thickness is controlled by varying the number of electropolymerisation cycles. In the ideal number of polymerisation cycles, the polymer must cover the electrode surface and create a binding pocket around LPS and its aptamer binding site. Less polymerisation cycles will create a hybrid system which resembles an aptasensor, while more cycles will be able to cover the complex and demonstrate a bulk polymer-like behaviour. Both aptasensor and apta-MIP were challenged with LPS and compared to conventional imprinted (absence of aptamer from the binding site, polymer formed in presence of LPS) and non-imprinted polymers (NIPS, absence of LPS whilst hybrid polymer is formed). A stable LPS aptasensor, capable of detecting down to 5 pg/ml of LPS was generated. The apparent Kd of the system was estimated at 17 pM, with a Bmax of approximately 50 pM. The aptasensor demonstrated high specificity to LPS. The apta-MIP demonstrated superior recognition properties with a limit of detection of 1 fg/ml and a Bmax of 100 pg/ml. The CRP and PCT aptasensors were both able to detect down to 5 pg/ml. Whilst full binding performance is currently being evaluated, there is none of the sensors demonstrate cross-reactivity towards LPS, CRP or PCT. In conclusion, stable aptasensors capable of detecting LPS, PCT and CRP at low concentrations have been generated. The realisation of a multiplex panel such as described herein, will effectively contribute to the rapid, personalised diagnosis of sepsis.

Keywords: aptamer, electrochemical impedance spectroscopy, molecularly imprinted polymers, sepsis

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

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Authors: Clara Tramuta, Floris Irene, Daniela Manila Bianchi, Monica Pitti, Giulia Federica Cazzaniga, Lucia Decastelli

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This work presents the results obtained by the Regional Reference Centre for Salmonella Typing (CeRTiS) in a retrospective study aimed to investigate, through Pulsed-field Gel Electrophoresis (PFGE) analysis, the genetic relatedness of emerging Salmonella serotypes of human origin circulating in North-West of Italy. Furthermore, the goal of this work was to create a Regional database to facilitate foodborne outbreak investigation and to monitor them at an earlier stage. A total of 112 strains, isolated from 2016 to 2018 in hospital laboratories, were included in this study. The isolates were previously identified as Salmonella according to standard microbiological techniques and serotyping was performed according to ISO 6579-3 and the Kaufmann-White scheme using O and H antisera (Statens Serum Institut®). All strains were characterized by PFGE: analysis was conducted according to a standardized PulseNet protocol. The restriction enzyme XbaI was used to generate several distinguishable genomic fragments on the agarose gel. PFGE was performed on a CHEF Mapper system, separating large fragments and generating comparable genetic patterns. The agarose gel was then stained with GelRed® and photographed under ultraviolet transillumination. The PFGE patterns obtained from the 112 strains were compared using Bionumerics version 7.6 software with the Dice coefficient with 2% band tolerance and 2% optimization. For each serotype, the data obtained with the PFGE were compared according to the geographical origin and the year in which they were isolated. Salmonella strains were identified as follow: S. Derby n. 34; S. Infantis n. 38; S. Napoli n. 40. All the isolates had appreciable restricted digestion patterns ranging from approximately 40 to 1100 kb. In general, a fairly heterogeneous distribution of pulsotypes has emerged in the different provinces. Cluster analysis indicated high genetic similarity (≥ 83%) among strains of S. Derby (n. 30; 88%), S. Infantis (n. 36; 95%) and S. Napoli (n. 38; 95%) circulating in north-western Italy. The study underlines the genomic similarities shared by the emerging Salmonella strains in Northwest Italy and allowed to create a database to detect outbreaks in an early stage. Therefore, the results confirmed that PFGE is a powerful and discriminatory tool to investigate the genetic relationships among strains in order to monitoring and control Salmonellosis outbreak spread. Pulsed-field gel electrophoresis (PFGE) still represents one of the most suitable approaches to characterize strains, in particular for the laboratories for which NGS techniques are not available.

Keywords: emerging Salmonella serotypes, genetic characterization, human strains, PFGE

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Authors: Afnan Al-Romi, Iman Al-Momani

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

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

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Authors: S. H. Gasa, L. Singh, B. Pillay, A. O. Olaniran

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Wastewater treatment plants (WWTPs) have been implicated as the leading reservoir for antibiotic resistant bacteria (ARB), including Enterococci spp. and antibiotic resistance genes (ARGs), worldwide. Enterococci are a group of clinically significant bacteria that have gained much attention as a result of their antibiotic resistance. They play a significant role as the principal cause of nosocomial infections and dissemination of antimicrobial resistance genes in the environment. The main objective of this study was to ascertain the role of WWTPs in Durban, South Africa as potential reservoirs for antibiotic resistant Enterococci (ARE) and their related ARGs. Furthermore, the antibiogram and resistance gene profile of Enterococci species recovered from treated wastewater effluent and receiving surface water in Durban were also investigated. Using membrane filtration technique, Enterococcus selective agar and selected antibiotics, ARE were enumerated in samples (influent, activated sludge, before chlorination and final effluent) collected from two WWTPs, as well as from upstream and downstream of the receiving surface water. Two hundred Enterococcus isolates recovered from the treated effluent and receiving surface water were identified by biochemical and PCR-based methods, and their antibiotic resistance profiles determined by the Kirby-Bauer disc diffusion assay, while PCR-based assays were used to detect the presence of resistance and virulence genes. High prevalence of ARE was obtained at both WWTPs, with values reaching a maximum of 40%. The influent and activated sludge samples contained the greatest prevalence of ARE with lower values observed in the before and after chlorination samples. Of the 44 vancomycin and high-level gentamicin-resistant isolates, 11 were identified as E. faecium, 18 as E. faecalis, 4 as E. hirae while 11 are classified as “other” Enterococci species. High-level aminoglycoside resistance for gentamicin (39%) and vancomycin (61%) was recorded in species tested. The most commonly detected virulence gene was the gelE (44%), followed by asa1 (40%), while cylA and esp were detected in only 2% of the isolates. The most prevalent aminoglycoside resistance genes were aac(6')-Ie-aph(2''), aph(3')-IIIa, and ant(6')-Ia detected in 43%, 45% and 41% of the isolates, respectively. Positive correlation was observed between resistant phenotypes to high levels of aminoglycosides and presence of all aminoglycoside resistance genes. Resistance genes for glycopeptide: vanB (37%) and vanC-1 (25%), and macrolide: ermB (11%) and ermC (54%) were detected in the isolates. These results show the need for more efficient wastewater treatment and disposal in order to prevent the release of virulent and antibiotic resistant Enterococci species and safeguard public health.

Keywords: antibiogram, enterococci, gentamicin, vancomycin, virulence signatures

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Authors: Marina Bubalo, Davor Romić, Stjepan Husnjak, Helena Bakić

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Even though European Council Directive 91/676/EEC known as Nitrates Directive was adopted in 1991, the issue of water quality preservation in areas of intensive agricultural production still persist all over Europe. High nitrate nitrogen concentrations in surface and groundwater originating from diffuse sources are one of the most important environmental problems in modern intensive agriculture. The fate of nitrogen in soil, surface and groundwater in agricultural area is mostly affected by anthropogenic activity (i.e. agricultural practice) and hydrological and climatological conditions. The aim of this study was to identify impact of land use, soil type, soil vulnerability to pollutant percolation, and natural aquifer vulnerability to nitrate occurrence in surface and groundwater within an intensive agricultural area. The study was set in Varaždin County (northern Croatia), which is under significant influence of the large rivers Drava and Mura and due to that entire area is dominated by alluvial soil with shallow active profile mainly on gravel base. Negative agricultural impact on water quality in this area is evident therefore the half of selected county is a part of delineated nitrate vulnerable zones (NVZ). Data on water quality were collected from 7 surface and 8 groundwater monitoring stations in the County. Also, recent study of the area implied detailed inventory of agricultural production and fertilizers use with the aim to produce new agricultural land use database as one of dominant parameters. The analysis of this database done using ArcGIS 10.1 showed that 52,7% of total County area is agricultural land and 59,2% of agricultural land is used for intensive agricultural production. On the other hand, 56% of soil within the county is classified as soil vulnerable to pollutant percolation. The situation is similar with natural aquifer vulnerability; northern part of the county ranges from high to very high aquifer vulnerability. Statistical analysis of water quality data is done using SPSS 13.0. Cluster analysis group both surface and groundwater stations in two groups according to nitrate nitrogen concentrations. Mean nitrate nitrogen concentration in surface water – group 1 ranges from 4,2 to 5,5 mg/l and in surface water – group 2 from 24 to 42 mg/l. The results are similar, but evidently higher, in groundwater samples; mean nitrate nitrogen concentration in group 1 ranges from 3,9 to 17 mg/l and in group 2 from 36 to 96 mg/l. ANOVA analysis confirmed statistical significance between stations that are classified in the same group. The previously listed parameters (land use, soil type, etc.) were used in factorial correspondence analysis (FCA) to detect importance of each stated parameter in local water quality. Since stated parameters mostly cannot be altered, there is obvious necessity for more precise and more adapted land management in such conditions.

Keywords: agricultural area, nitrate, factorial correspondence analysis, water quality

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Authors: In-Tsang Lin, Chiching Wei

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Reading order is an important task in many digitization scenarios involving the preservation of the logical structure of a document. From the paper survey, it finds that the state-of-the-art algorithm could not fulfill to get the accurate reading order in the portable document format (PDF) files with rich formats, diverse layout arrangement. In recent years, most of the studies on the analysis of reading order have targeted the specific problem of associating layout components with logical labels, while less attention has been paid to the problem of extracting relationships the problem of detecting the reading order relationship between logical components, such as cross-references. Over 3 years of development, the company Foxit has demonstrated the layout recognition (LR) engine in revision 20601 to eager for the accuracy of the reading order. The bounding box of each paragraph can be obtained correctly by the Foxit LR engine, but the result of reading-order is not always correct for single-column, and two-column layout format due to the table issue, formula issue, and multiple mini separated bounding box and footer issue. Thus, the algorithm is developed to improve the accuracy of the reading order based on the Foxit LR structure. In this paper, a creative observation method (Here called the MESH method) is provided here to open a new chance in the research of the reading-order field. Here two important parameters are introduced, one parameter is the number of the bounding box on the right side of the present bounding box (NRight), and another parameter is the number of the bounding box under the present bounding box (Nunder). And the normalized x-value (x/the whole width), the normalized y-value (y/the whole height) of each bounding box, the x-, and y- position of each bounding box were also put into consideration. Initial experimental results of single column layout format demonstrate a 19.33% absolute improvement in accuracy of the reading-order over 7 PDF files (total 150 pages) using our proposed method based on the LR structure over the baseline method using the LR structure in 20601 revision, which its accuracy of the reading-order is 72%. And for two-column layout format, the preliminary results demonstrate a 44.44% absolute improvement in accuracy of the reading-order over 2 PDF files (total 18 pages) using our proposed method based on the LR structure over the baseline method using the LR structure in 20601 revision, which its accuracy of the reading-order is 0%. Until now, the footer issue and a part of multiple mini separated bounding box issue can be solved by using the MESH method. However, there are still three issues that cannot be solved, such as the table issue, formula issue, and the random multiple mini separated bounding boxes. But the detection of the table position and the recognition of the table structure are out of the scope in this paper, and there is needed another research. In the future, the tasks are chosen- how to detect the table position in the page and to extract the content of the table.

Keywords: document processing, reading order, observation method, layout recognition

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Authors: Shams Khaled Abdelrahman Abdallah Elbaz, Alaa Aldeen Abd Al Hakeem Balbaa

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Purpose: The purpose of this study was to compare the effects of Positional Release Technique versus Kinesio Tape on pain level, pressure pain threshold level and functional disability in patients with back myofascial pain syndrome at iliocostalis lumborum. Backgrounds/significance: Myofascial Pain Syndrome is a common muscular pain syndrome that arises from trigger points which are hyperirritable, painful and tender points within a taut band of skeletal muscle. In more recent literature, about 75% of patients with musculoskeletal pain presenting to a community medical centres suffer from myofascial pain syndrome.Iliocostalis lumborum are most likely to develop active trigger points. Subjects: Thirty patients diagnosed as back myofascial pain syndrome with active trigger points in iliocostalis lumborum muscle bilaterally had participated in this study. Methods and materials: Patients were randomly distributed into two groups. The first group consisted of 15 patients (8 males and 7 females) with mean age 30.6 (±3.08) years, they received positional release technique which was applied 3 times per session, 3/week every other day for 2 weeks. The second group consisted of 15 patients(5 males, 10 females) with a mean age 30.4 (±3.35) years, they received kinesio tape which was applied and changed every 3 days with one day off for a total 3 times in 2 weeks. Both techniques were applied over trigger points of the iliocostalis lumborum bilaterally. Patients were evaluated pretreatment and posttreatment program for Pain intensity (Visual analogue scale), pressure pain threshold (digital pressure algometry), and functional disability (The Oswestry Disability Index). Analyses: Repeated measures MANOVA was used to detect differences within and between groups pre and post treatment. Then the univariate ANOVA test was conducted for the analysis of each dependant variable within and between groups. All statistical analyses were done using SPSS. with significance level set at p<0.05 throughout all analyses. Results: The results revealed that there was no significant difference between positional release technique and kinesio tape technique on pain level, pressure pain threshold and functional activities (p > 0.05). Both groups of patients showed significant improvement in all the measured variables (p < 0.05) evident by significant reduction of both pain intensity and functional disability as well as significant increase of pressure pain threshold Conclusions : Both positional release technique and kinesio taping technique are effective in reducing pain level, improving pressure pain threshold and improving function in treating patients who suffering from back myofascial pain syndrome at iliocostalis lumborum. As there was no statistically significant difference was proven between both of them.

Keywords: positional release technique, kinesio tape, myofascial pain syndrome, Iliocostalis lumborum

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Authors: Tomas Makaras, Gintaras Svecevičius

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Landfill waste is a common problem as it has an economic and environmental impact even if it is closed. Landfill waste contains a high density of various persistent compounds such as heavy metals, organic and inorganic materials. As persistent compounds are slowly-degradable or even non-degradable in the environment, they often produce sublethal or even lethal effects on aquatic organisms. The aims of the present study were to estimate sublethal effects of the Kairiai landfill (WGS: 55°55‘46.74“, 23°23‘28.4“) leachate on the locomotor activity of rainbow trout Oncorhynchus mykiss juveniles using the original system package developed in our laboratory for automated monitoring, recording and analysis of aquatic organisms’ activity, and to determine patterns of fish behavioral response to sublethal effects of leachate. Four different concentrations of leachate were chosen: 0.125; 0.25; 0.5 and 1.0 mL/L (0.0025; 0.005; 0.01 and 0.002 as part of 96-hour LC50, respectively). Locomotor activity was measured after 5, 10 and 30 minutes of exposure during 1-minute test-periods of each fish (7 fish per treatment). The threshold-effect-concentration amounted to 0.18 mL/L (0.0036 parts of 96-hour LC50). This concentration was found to be even 2.8-fold lower than the concentration generally assumed to be “safe” for fish. At higher concentrations, the landfill leachate solution elicited behavioral response of test fish to sublethal levels of pollutants. The ability of the rainbow trout to detect and avoid contaminants occurred after 5 minutes of exposure. The intensity of locomotor activity reached a peak within 10 minutes, evidently decreasing after 30 minutes. This could be explained by the physiological and biochemical adaptation of fish to altered environmental conditions. It has been established that the locomotor activity of juvenile trout depends on leachate concentration and exposure duration. Modeling of these parameters showed that the activity of juveniles increased at higher leachate concentrations, but slightly decreased with the increasing exposure duration. Experiment results confirm that the behavior of rainbow trout juveniles is a sensitive and rapid biomarker that can be used in combination with the system for fish behavior monitoring, registration and analysis to determine sublethal concentrations of pollutants in ambient water. Further research should be focused on software improvement aimed to include more parameters of aquatic organisms’ behavior and to investigate the most rapid and appropriate behavioral responses in different species. In practice, this study could be the basis for the development and creation of biological early-warning systems (BEWS).

Keywords: fish behavior biomarker, landfill leachate, locomotor activity, rainbow trout juveniles, sublethal effects

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Authors: Seyed Hamed Mousavi, Juha M. Hijmans, Reza Rajabi, Ron Diercks, Johannes Zwerver, Henk van der Worp

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Introduction: Running is one of the most popular sports activity among people. Improper sagittal plane ankle, knee and hip kinematics are considered to be associated with the increase of injury risk in runners. Motion assessing smart-phone applications are increasingly used to measure kinematics both in the field and laboratory setting, as they are cheaper, more portable, accessible, and easier to use relative to 3D motion analysis system. The aims of this study are 1) to compare the results of 3D gait analysis system and CE; 2) to evaluate the test-retest and intra-rater reliability of coach’s eye (CE) app for the sagittal plane hip, knee, and ankle angles in the touchdown and toe-off while running. Method: Twenty subjects participated in this study. Sixteen reflective markers and cluster markers were attached to the subject’s body. Subjects were asked to run at a self-selected speed on a treadmill. Twenty-five seconds of running were collected for analyzing kinematics of interest. To measure sagittal plane hip, knee and ankle joint angles at touchdown (TD) and toe off (TO), the mean of first ten acceptable consecutive strides was calculated for each angle. A smartphone (Samsung Note5, android) was placed on the right side of the subject so that whole body was simultaneously filmed with 3D gait system during running. All subjects repeated the task with the same running speed after a short interval of 5 minutes in between. The CE app, installed on the smartphone, was used to measure the sagittal plane hip, knee and ankle joint angles at touchdown and toe off the stance phase. Results: Intraclass correlation coefficient (ICC) was used to assess test-retest and intra-rater reliability. To analyze the agreement between 3D and 2D outcomes, the Bland and Altman plot was used. The values of ICC were for Ankle at TD (TRR=0.8,IRR=0.94), ankle at TO (TRR=0.9,IRR=0.97), knee at TD (TRR=0.78,IRR=0.98), knee at TO (TRR=0.9,IRR=0.96), hip at TD (TRR=0.75,IRR=0.97), hip at TO (TRR=0.87,IRR=0.98). The Bland and Altman plots displaying a mean difference (MD) and ±2 standard deviation of MD (2SDMD) of 3D and 2D outcomes were for Ankle at TD (MD=3.71,+2SDMD=8.19, -2SDMD=-0.77), ankle at TO (MD=-1.27, +2SDMD=6.22, -2SDMD=-8.76), knee at TD (MD=1.48, +2SDMD=8.21, -2SDMD=-5.25), knee at TO (MD=-6.63, +2SDMD=3.94, -2SDMD=-17.19), hip at TD (MD=1.51, +2SDMD=9.05, -2SDMD=-6.03), hip at TO (MD=-0.18, +2SDMD=12.22, -2SDMD=-12.59). Discussion: The ability that the measurements are accurately reproduced is valuable in the performance and clinical assessment of outcomes of joint angles. The results of this study showed that the intra-rater and test-retest reliability of CE app for all kinematics measured are excellent (ICC ≥ 0.75). The Bland and Altman plots display that there are high differences of values for ankle at TD and knee at TO. Measuring ankle at TD by 2D gait analysis depends on the plane of movement. Since ankle at TD mostly occurs in the none-sagittal plane, the measurements can be different as foot progression angle at TD increases during running. The difference in values of the knee at TD can depend on how 3D and the rater detect the TO during the stance phase of running.

Keywords: reliability, running, sagittal plane, two dimensional

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Authors: David Oluigbo, Erik Hemberg, Nathan Shwatal, Wenqi Ding, Yin Yuan, Susanna Mierau

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Introduction: Calcium imaging is an established technique in neuroscience research for detecting activity in neural networks. Bursts of action potentials in neurons lead to transient increases in intracellular calcium visualized with fluorescent indicators. Manual identification of cell bodies and their contours by experts typically takes 10-20 minutes per calcium imaging recording. Our aim, therefore, was to design an automated pipeline to facilitate and optimize calcium imaging data analysis. Our pipeline aims to accelerate cell body and contour identification and production of graphical representations reflecting changes in neuronal calcium-based fluorescence. Methods: We created a Python-based pipeline that uses OpenCV (a computer vision Python package) to accurately (1) detect neuron contours, (2) extract the mean fluorescence within the contour, and (3) identify transient changes in the fluorescence due to neuronal activity. The pipeline consisted of 3 Python scripts that could both be easily accessed through a Python Jupyter notebook. In total, we tested this pipeline on ten separate calcium imaging datasets from murine dissociate cortical cultures. We next compared our automated pipeline outputs with the outputs of manually labeled data for neuronal cell location and corresponding fluorescent times series generated by an expert neuroscientist. Results: Our results show that our automated pipeline efficiently pinpoints neuronal cell body location and neuronal contours and provides a graphical representation of neural network metrics accurately reflecting changes in neuronal calcium-based fluorescence. The pipeline detected the shape, area, and location of most neuronal cell body contours by using binary thresholding and grayscale image conversion to allow computer vision to better distinguish between cells and non-cells. Its results were also comparable to manually analyzed results but with significantly reduced result acquisition times of 2-5 minutes per recording versus 10-20 minutes per recording. Based on these findings, our next step is to precisely measure the specificity and sensitivity of the automated pipeline’s cell body and contour detection to extract more robust neural network metrics and dynamics. Conclusion: Our Python-based pipeline performed automated computer vision-based analysis of calcium image recordings from neuronal cell bodies in neuronal cell cultures. Our new goal is to improve cell body and contour detection to produce more robust, accurate neural network metrics and dynamic graphs.

Keywords: calcium imaging, computer vision, neural activity, neural networks

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Authors: Minghui Zhang, Sirine Fkaier, Sabri Fernana, Svetlana Kiseleva, Denis Kiselev

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The real-time identification of bacteria and fungi is difficult because they emit much weaker signals than pollen. In 2020, Plair developed Rapid-E+, which extends abilities of Rapid-E to detect smaller bioaerosols such as bacteria and fungal spores with diameters down to 0.3 µm, while keeping the similar or even better capability for measurements of large bioaerosols like pollen. Rapid-E+ enables simultaneous measurements of (1) time-resolved, polarization and angle dependent Mie scattering patterns, (2) fluorescence spectra resolved in 16 channels, and (3) fluorescence lifetime of individual particles. Moreover, (4) it provides 2D Mie scattering images which give the full information on particle morphology. The parameters of every single bioaerosol aspired into the instrument are subsequently analysed by machine learning. Firstly, pure species of microbes, e.g., Bacillus subtilis (a species of bacteria), and Penicillium chrysogenum (a species of fungal spores), were aerosolized in a bioaerosol chamber for Rapid-E+ training. Afterwards, we tested microbes under different concentrations. We used several steps of data analysis to classify and identify microbes. All single particles were analysed by the parameters of light scattering and fluorescence in the following steps. (1) They were treated with a smart filter block to get rid of non-microbes. (2) By classification algorithm, we verified the filtered particles were microbes based on the calibration data. (3) The probability threshold (defined by the user) step provides the probability of being microbes ranging from 0 to 100%. We demonstrate how Rapid-E+ identified simultaneously microbes based on the results of Bacillus subtilis (bacteria) and Penicillium chrysogenum (fungal spores). By using machine learning, Rapid-E+ achieved identification precision of 99% against the background. The further classification suggests the precision of 87% and 89% for Bacillus subtilis and Penicillium chrysogenum, respectively. The developed algorithm was subsequently used to evaluate the performance of microbe classification and quantification in real-time. The bacteria and fungi were aerosolized again in the chamber with different concentrations. Rapid-E+ can classify different types of microbes and then quantify them in real-time. Rapid-E+ enables classifying different types of microbes and quantifying them in real-time. Rapid-E+ can identify pollen down to species with similar or even better performance than the previous version (Rapid-E). Therefore, Rapid-E+ is an all-in-one instrument which classifies and quantifies not only pollen, but also bacteria and fungi. Based on the machine learning platform, the user can further develop proprietary algorithms for specific microbes (e.g., virus aerosols) and other aerosols (e.g., combustion-related particles that contain polycyclic aromatic hydrocarbons).

Keywords: bioaerosols, laser-induced fluorescence, Mie-scattering, microorganisms

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Authors: Suman Som, Abhijit Maity, Sunil B. Daschakraborty, Sujit Chaudhuri, Manik Pradhan

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Background: Helicobacter pylori is a common and important human pathogen and the primary cause of peptic ulcer disease and gastric cancer. Currently H. pylori infection is detected by both invasive and non-invasive way but the diagnostic accuracy is not up to the mark. Aim: To set up an optimal diagnostic cut-off value of 13C-Urea Breath Test to detect H. pylori infection and evaluate a novel c-PDR methodology to overcome of inconclusive grey zone. Materials and Methods: All 83 subjects first underwent upper-gastrointestinal endoscopy followed by rapid urease test and histopathology and depending on these results; we classified 49 subjects as H. pylori positive and 34 negative. After an overnight, fast patients are taken 4 gm of citric acid in 200 ml water solution and 10 minute after ingestion of the test meal, a baseline exhaled breath sample was collected. Thereafter an oral dose of 75 mg 13C-Urea dissolved in 50 ml water was given and breath samples were collected upto 90 minute for 15 minute intervals and analysed by laser based high precisional cavity enhanced spectroscopy. Results: We studied the excretion kinetics of 13C isotope enrichment (expressed as δDOB13C ‰) of exhaled breath samples and found maximum enrichment around 30 minute of H. pylori positive patients, it is due to the acid mediated stimulated urease enzyme activity and maximum acidification happened within 30 minute but no such significant isotopic enrichment observed for H. pylori negative individuals. Using Receiver Operating Characteristic (ROC) curve an optimal diagnostic cut-off value, δDOB13C ‰ = 3.14 was determined at 30 minute exhibiting 89.16% accuracy. Now to overcome grey zone problem we explore percentage dose of 13C recovered per hour, i.e. 13C-PDR (%/hr) and cumulative percentage dose of 13C recovered, i.e. c-PDR (%) in exhaled breath samples for the present 13C-UBT. We further explored the diagnostic accuracy of 13C-UBT by constructing ROC curve using c-PDR (%) values and an optimal cut-off value was estimated to be c-PDR = 1.47 (%) at 60 minute, exhibiting 100 % diagnostic sensitivity , 100 % specificity and 100 % accuracy of 13C-UBT for detection of H. pylori infection. We also elucidate the gastric emptying process of present 13C-UBT for H. pylori positive patients. The maximal emptying rate found at 36 minute and half empting time of present 13C-UBT was found at 45 minute. Conclusions: The present study exhibiting the importance of c-PDR methodology to overcome of grey zone problem in 13C-UBT for accurate determination of infection without any risk of diagnostic errors and making it sufficiently robust and novel method for an accurate and fast non-invasive diagnosis of H. pylori infection for large scale screening purposes.

Keywords: 13C-Urea breath test, c-PDR methodology, grey zone, Helicobacter pylori

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Authors: Ibrahim Rassoul, A. Serir, E-K. Si Ahmed, J. Legrand

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The acronym PEM refers to Proton Exchange Membrane or alternatively Polymer Electrolyte Membrane. Due to its high efficiency, low operating temperature (30–80 °C), and rapid evolution over the past decade, PEMFCs are increasingly emerging as a viable alternative clean power source for automobile and stationary applications. Before PEMFCs can be employed to power automobiles and homes, several key technical challenges must be properly addressed. One technical challenge is elucidating the mechanisms underlying water transport in and removal from PEMFCs. On one hand, sufficient water is needed in the polymer electrolyte membrane or PEM to maintain sufficiently high proton conductivity. On the other hand, too much liquid water present in the cathode can cause “flooding” (that is, pore space is filled with excessive liquid water) and hinder the transport of the oxygen reactant from the gas flow channel (GFC) to the three-phase reaction sites. The experimental transparent fuel cell used in this work was designed to represent actual full scale of fuel cell geometry. According to the operating conditions, a number of flow regimes may appear in the microchannel: droplet flow, blockage water liquid bridge /plug (concave and convex forms), slug/plug flow and film flow. Some of flow patterns are new, while others have been already observed in PEMFC microchannels. An algorithm in MATLAB was developed to automatically determine the flow structure (e.g. slug, droplet, plug, and film) of detected liquid water in the test microchannels and yield information pertaining to the distribution of water among the different flow structures. A video processing algorithm was developed to automatically detect dynamic and static liquid water present in the gas channels and generate relevant quantitative information. The potential benefit of this software allows the user to obtain a more precise and systematic way to obtain measurements from images of small objects. The void fractions are also determined based on images analysis. The aim of this work is to provide a comprehensive characterization of two-phase flow in an operating fuel cell which can be used towards the optimization of water management and informs design guidelines for gas delivery microchannels for fuel cells and its essential in the design and control of diverse applications. The approach will combine numerical modeling with experimental visualization and measurements.

Keywords: polymer electrolyte fuel cell, air-water two phase flow, gas diffusion layer, microchannels, advancing contact angle, receding contact angle, void fraction, surface tension, image processing

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Authors: Bander Alzahrani, Mohammed Alreshoodi

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Information-centric networking (ICN) using architectures such as the Publish-Subscribe Internet Technology (PURSUIT) has been proposed as a new networking model that aims at replacing the current used end-centric networking model of the Internet. This emerged model focuses on what is being exchanged rather than which network entities are exchanging information, which gives the control plane functions such as routing and host location the ability to be specified according to the content items. The forwarding plane of the PURSUIT ICN architecture uses a simple and light mechanism based on Bloom filter technologies to forward the packets. Although this forwarding scheme solve many problems of the today’s Internet such as the growth of the routing table and the scalability issues, it is vulnerable to brute force attacks which are starting point to distributed- denial-of-service (DDoS) attacks. In this work, we design and analyze a novel source-routing and information delivery technique that keeps the simplicity of using Bloom filter-based forwarding while being able to deter different attacks such as denial of service attacks at the ingress of the network. To achieve this, special forwarding nodes called Edge-FW are directly attached to end user nodes and used to perform a security test for malicious injected random packets at the ingress of the path to prevent any possible attack brute force attacks at early stage. In this technique, a core entity of the PURSUIT ICN architecture called topology manager, that is responsible for finding shortest path and creating a forwarding identifiers (FId), uses a cryptographically secure hash function to create a 64-bit hash, h, over the formed FId for authentication purpose to be included in the packet. Our proposal restricts the attacker from injecting packets carrying random FIds with a high amount of filling factor ρ, by optimizing and reducing the maximum allowed filling factor ρm in the network. We optimize the FId to the minimum possible filling factor where ρ ≤ ρm, while it supports longer delivery trees, so the network scalability is not affected by the chosen ρm. With this scheme, the filling factor of any legitimate FId never exceeds the ρm while the filling factor of illegitimate FIds cannot exceed the chosen small value of ρm. Therefore, injecting a packet containing an FId with a large value of filling factor, to achieve higher attack probability, is not possible anymore. The preliminary analysis of this proposal indicates that with the designed scheme, the forwarding function can detect and prevent malicious activities such DDoS attacks at early stage and with very high probability.

Keywords: forwarding identifier, filling factor, information centric network, topology manager

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Authors: Manal M. Kame, Hanan G. El-Baz, Zeinab A.Demerdash, Engy M. Abd El-Moneem, Mohamed A. Hendawy, Ibrahim R. Bayoumi

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There is a constant need to improve the performance of current diagnostic assays of schistosomiasis as well as develop innovative testing strategies to meet new testing challenges. This study aims at increasing the diagnostic efficiency of monoclonal antibody (MAb)-based antigen detection assays through gold nanoparticles conjugated with specific anti-Schistosoma mansoni monoclonal antibodies. In this study, several hybidoma cell lines secreting MAbs against adult worm tegumental Schistosoma antigen (AWTA) were produced at Immunology Department of Theodor Bilharz Research Institute and preserved in liquid nitrogen. One MAb (6D/6F) was chosen for this study due to its high reactivity to schistosome antigens with highest optical density (OD) values. Gold nanoparticles (AuNPs) were functionalized and conjugated with MAb (6D/6F). The study was conducted on serum samples of 116 subjects: 71 patients with S. mansoni eggs in their stool samples group (gp 1), 25 with other parasites (gp2) and 20 negative healthy controls (gp3). Patients in gp1 were further subdivided according to egg count in their stool samples into Light infection {≤ 50 egg per gram(epg) (n= 17)}, moderate {51-100 epg (n= 33)} and severe infection {>100 epg(n= 21)}. Sandwich ELISA was performed using (AuNPs -MAb) for detection of circulating schistosomal antigen (CSA) levels in serum samples of all groups and the results were compared with that after using MAb/ sandwich ELISA system. Results Gold- MAb/ ELISA system reached a lower detection limit of 10 ng/ml compared to 85 ng/ml on using MAb/ ELISA and the optimal concentrations of AuNPs -MAb were found to be 12 folds less than that of MAb/ ELISA system for detection of CSA. The sensitivity and specificity of sandwich ELISA for detection of CSA levels using AuNPs -MAb were 100% & 97.8 % respectively compared to 87.3% &93.38% respectively on using MAb/ ELISA system. It was found that CSA was detected in 9 out of 71 S.mansoni infected patients on using AuNPs - MAb/ ELISA system and was not detected by MAb/ ELISA system. All those patients (9) was found to have an egg count below 50 epg feces (patients with light infections). ROC curve analyses revealed that sandwich ELISA using gold-MAb was an excellent diagnostic investigator that could differentiate Schistosoma patients from healthy controls, on the other hand it revealed that sandwich ELISA using MAb was not accurate enough as it could not recognize nine out of 71 patients with light infections. Conclusion Our data demonstrated that: Loading gold nanoparticles with MAb (6D/6F) increases the sensitivity and specificity of sandwich ELISA for detection of CSA, thus active (early) and light infections could be easily detected. Moreover this binding will decrease the amount of MAb consumed in the assay and lower the coast. The significant positive correlation that was detected between ova count (intensity of infection) and OD reading in sandwich ELISA using gold- MAb enables its use to detect the severity of infections and follow up patients after treatment for monitoring of cure.

Keywords: Schistosomiasis, nanoparticles, gold, monoclonal antibodies, ELISA

Procedia PDF Downloads 342

Authors: Atchara Sankom, Warapa Mahakarnchanakul, Ronnarit Rittiron, Tanaboon Sajjaanantakul, Thammasak Thongket

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Vegetables are frequently contaminated with pesticides residues resulting in the most food safety concern among agricultural products. The objective of this work was to develop a method to detect the organophosphate (OP) pesticides residues in vegetables using Near Infrared (NIR) spectroscopy technique. Low concentration (ppm) of OP pesticides in vegetables were investigated. The experiment was divided into 2 sections. In the first section, Chinese kale spiked with different concentrations of chlorpyrifos pesticide residues (0.5-100 ppm) was chosen as the sample model to demonstrate the appropriate conditions of sample preparation, both for a solution or solid sample. The spiked samples were extracted with acetone. The sample extracts were applied as solution samples, while the solid samples were prepared by the dry-extract system for infrared (DESIR) technique. The DESIR technique was performed by embedding the solution sample on filter paper (GF/A) and then drying. The NIR spectra were measured with the transflectance mode over wavenumber regions of 12,500-4000 cm⁻¹. The QuEChERS method followed by gas chromatography-mass spectrometry (GC-MS) was performed as the standard method. The results from the first section showed that the DESIR technique with NIR spectroscopy demonstrated good accurate calibration result with R² of 0.93 and RMSEP of 8.23 ppm. However, in the case of solution samples, the prediction regarding the NIR-PLSR (partial least squares regression) equation showed poor performance (R² = 0.16 and RMSEP = 23.70 ppm). In the second section, the DESIR technique coupled with NIR spectroscopy was applied to the detection of OP pesticides in vegetables. Vegetables (Chinese kale, cabbage and hot chili) were spiked with OP pesticides (chlorpyrifos ethion and profenofos) at different concentrations ranging from 0.5 to 100 ppm. Solid samples were prepared (based on the DESIR technique), then samples were scanned by NIR spectrophotometer at ambient temperature (25+2°C). The NIR spectra were measured as in the first section. The NIR- PLSR showed the best calibration equation for detecting low concentrations of chlorpyrifos residues in vegetables (Chinese kale, cabbage and hot chili) according to the prediction set of R2 and RMSEP of 0.85-0.93 and 8.23-11.20 ppm, respectively. For ethion residues, the best calibration equation of NIR-PLSR showed good indexes of R² and RMSEP of 0.88-0.94 and 7.68-11.20 ppm, respectively. As well as the results for profenofos pesticide, the NIR-PLSR also showed the best calibration equation for detecting the profenofos residues in vegetables according to the good index of R² and RMSEP of 0.88-0.97 and 5.25-11.00 ppm, respectively. Moreover, the calibration equation developed in this work could rapidly predict the concentrations of OP pesticides residues (0.5-100 ppm) in vegetables, and there was no significant difference between NIR-predicted values and actual values (data from GC-MS) at a confidence interval of 95%. In this work, the proposed method using NIR spectroscopy involving the DESIR technique has proved to be an efficient method for the screening detection of OP pesticides residues at low concentrations, and thus increases the food safety potential of vegetables for domestic and export markets.

Keywords: NIR spectroscopy, organophosphate pesticide, vegetable, food safety

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Authors: Benyam Zenebe, Tesfaye Sisay, Gurja Belay, Workabeba Abebe

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Background: The prevalence and antibiogram of pathogenic E. coli strains, which cause diarrhea vary from region to region, and even within countries in the same geographical area. In Ethiopia, diagnostic approaches to E. coli induced diarrhea in children less than five years of age are not standardized. The aim of this study was to determine the involvement of pathogenic E. coli strains in child diarrhea and determine the antibiograms of the isolates in children less than 5 years of age with diarrhea at Addis Ababa University College of Health Sciences TikurAnbessa Specialized Hospital, Addis Ababa, Ethiopia. Methods: A purposive study that included 98 diarrheic children less than five years of age was conducted at Addis Ababa University College of Health Sciences, TikurAnbessa Specialized Hospital, Addis Ababa, Ethiopia to detect pathogenic E. coli biotypes. Stool culture was used to identify presumptive E. coliisolates. Presumptive isolates were confirmed by biochemical tests, and antimicrobial susceptibility tests were performed on confirmed E. coli isolates by the disk diffusion method. DNA was extracted from confirmed isolates by a heating method and subjected to Polymerase Chain Reaction or the presence of virulence genes. Amplified PCR products were analyzed by agarose gel electrophoresis. Data were collected on child demographics and clinical conditions using administered questionnaires. The prevalence of E. coli strains from the total diarrheic children, and the prevalence of pathogenic strains from total E. coli isolates along with their susceptibility profiles; the distribution of pathogenic E.coli biotypes among different age groups and between the sexes were determined by using descriptive statistics. Result: Out of 98 stool specimens collected from diarrheic children less than 5 years of age, 75 presumptive E. coli isolates were identified by culture; further confirmation by biochemical tests showed that only 56 of the isolates were E. coli; 29 of the isolates were found in male children and 27 of them in female children. Out of the 58 isolates of E. coli, 25 pathotypes belonging to different classes of pathogenic strains: STEC, EPEC, EHEC, EAEC were detected by using the PCR technique. Pathogenic E. coli exhibited high rates of antibiotic resistance to many of the antibiotics tested. Moreover, they exhibited multiple drug resistance. Conclusion: This study found that the isolation rate of E. coli and the involvement of antibiotic-resistant pathogenic E. coli in diarrheic children is prominent, and hence focus should be given on the diagnosis and antimicrobial sensitivity testing of pathogenic E. coli at Addis Ababa University College of Health Sciences TikurAnbessa Specialized Hospital. Among antibiotics tested, Cefotitan could be a drug of choice to treat E. coli.

Keywords: antibiotic susceptibility profile, children, diarrhea, E. coli, pathogenic

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Authors: Simona Perga, Chiara Beltramo, Floriana Fruscione, Isabella Martini, Federica Cavallo, Federica Riccardo, Paolo Buracco, Selina Iussich, Elisabetta Razzuoli, Katia Varello, Lorella Maniscalco, Elena Bozzetta, Angelo Ferrari, Paola Modesto

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Introduction: Human and canine melanoma have common clinical, histologic characteristics making dogs a good model for comparative oncology. The identification of specific genes and a better understanding of the genetic landscape, signaling pathways, and tumor–microenvironmental interactions involved in the cancer onset and progression is essential for the development of therapeutic strategies against this tumor in both species. In the present study, the differential expression of genes in spontaneously occurring canine melanoma and in paired normal tissue was investigated by targeted RNAseq. Material and Methods: Total RNA was extracted from 17 canine malignant melanoma (CMM) samples and from five paired normal tissues stored in RNA-later. In order to capture the greater genetic variability, gene expression analysis was carried out using two panels (Qiagen): Human Immuno-Oncology (HIO) and Mouse-Immuno-Oncology (MIO) and the miSeq platform (Illumina). These kits allow the detection of the expression profile of 990 genes involved in the immune response against tumors in humans and mice. The data were analyzed through the CLCbio Genomics Workbench (Qiagen) software using the Canis lupus familiaris genome as a reference. Data analysis were carried out both comparing the biologic group (tumoral vs. healthy tissues) and comparing neoplastic tissue vs. paired healthy tissue; a Fold Change greater than two and a p-value less than 0.05 were set as the threshold to select interesting genes. Results and Discussion: Using HIO 63, down-regulated genes were detected; 13 of those were also down-regulated comparing neoplastic sample vs. paired healthy tissue. Eighteen genes were up-regulated, 14 of those were also down-regulated comparing neoplastic sample vs. paired healthy tissue. Using the MIO, 35 down regulated-genes were detected; only four of these were down-regulated, also comparing neoplastic sample vs. paired healthy tissue. Twelve genes were up-regulated in both types of analysis. Considering the two kits, the greatest variation in Fold Change was in up-regulated genes. Dogs displayed a greater genetic homology with humans than mice; moreover, the results have shown that the two kits are able to detect different genes. Most of these genes have specific cellular functions or belong to some enzymatic categories; some have already been described to be correlated to human melanoma and confirm the validity of the dog as a model for the study of molecular aspects of human melanoma.

Keywords: animal model, canine melanoma, gene expression, spontaneous tumors, targeted RNAseq

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Authors: Taurino S. R. Neto, Epitácio D. S. Neto, Flávio Signorelli, Gustavo G. M. Balbi, Alex H. Higashi, Mário Luiz R. Monteiro, Eloisa Bonfá, Danieli C. O. Andrade, Leandro C. Zacharias

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Purpose: To perform a multimodal evaluation, including the use of Optical Coherence Angiotomography (OCTA), in patients with primary antiphospholipid syndrome (PAPS) without ocular complaints and to compare them with healthy individuals. Methods: A complete structural and functional ophthalmological evaluation using OCTA and microperimetry (MP) exam in patients with PAPS, followed at a tertiary rheumatology outpatient clinic, was performed. All ophthalmologic manifestations were recorded and then statistical analysis was performed for comparative purposes; p <0.05 was considered statistically significant. Results: 104 eyes of 52 subjects (26 patients with PAPS without ocular complaints and 26 healthy individuals) were included. Among PAPS patients, 21 were female (80.8%) and 21 (80.8%) were Caucasians. Thrombotic PAPS was the main clinical criteria manifestation (100%); 65.4% had venous and 34.6% had arterial thrombosis. Obstetrical criteria were present in 34.6% of all thrombotic PAPS patients. Lupus anticoagulant was present in all patients. 19.2% of PAPS patients presented ophthalmologic findings against none of the healthy individuals. The most common retinal change was paracentral acute middle maculopathy (PAMM) (3 patients, 5 eyes), followed by drusen-like deposits (1 patient, 2 eyes) and pachychoroid pigment epitheliopathy (1 patient, 1 eye). Systemic hypertension and hyperlipidaemia were present in 100% of the PAPS patients with PAMM, while only six patients (26.1%) with PAPS without PAMM presented these two risk factors together. In the quantitative OCTA evaluation, we found significant differences between PAPS patients and controls in both the superficial vascular complex (SVC) and deep vascular complex (DVC) in the high-speed protocol, as well as in the SVC in the high-resolution protocol. In the analysis of the foveal avascular zone (FAZ) parameters, the PAPS group had a larger area of FAZ in the DVC using the high-speed method compared to the control group (p=0.047). In the quantitative analysis of the MP, the PAPS group had lower central (p=0.041) and global (p<0.001) retinal sensitivity compared to the control group, as well as in the sector analysis, with the exception of the inferior sector. In the quantitative evaluation of fixation stability, there was a trend towards worse stability in the PAPS subgroup with PAMM in both studied methods. Conclusions: PAMM was observed in 11.5% of PAPS patients with no previous ocular complaints. Systemic hypertension concomitant with hyperlipidemia was the most commonly associated risk factor for PAMM in patients with PAPS. PAPS patients present lower vascular density and retinal sensitivity compared to the control group, even in patients without PAMM.

Keywords: antiphospholipid syndrome, optical coherence angio tomography, optical coherence tomography, retina

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Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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Authors: Shrabani Ghosh

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Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: Ozlem Uguz, Ali Demirci, Hanzade Haykiri-Acma, Serdar Yaman

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Lignitic coal holds its position as Turkey’s most important indigenous energy source to generate energy in thermal power plants. Hence, efficient and environmental-friendly use of lignite in electricity generation is of great importance. Thus, clean coal technologies have been planned to mitigate emissions and provide more efficient burning in power plants. In this context, oxygen enriched combustion (oxy-combustion) is regarded as one of the clean coal technologies, which based on burning with oxygen concentrations higher than that in air. As it is known that the most of the Turkish coals are low rank with high mineral matter content, unburnt carbon trapped in ash is, unfortunately, high, and it leads significant losses in the overall efficiencies of the thermal plants. Besides, the necessity of burning huge amounts of these low calorific value lignites to get the desired amount of energy also results in the formation of large amounts of ash that is rich in unburnt carbon. Oxygen enriched combustion technology enables to increase the burning efficiency through the complete burning of almost all of the carbon content of the fuel. This also contributes to the protection of air quality and emission levels drop reasonably. The aim of this study is to investigate the unburnt carbon content and the burning reactivities of several different lignite samples under oxygen enriched conditions. For this reason, the combined effects of temperature and oxygen/nitrogen ratios in the burning atmosphere were investigated and interpreted. To do this, Turkish lignite samples from Adıyaman-Gölbaşı and Kütahya-Tunçbilek regions were characterized first by proximate and ultimate analyses and the burning profiles were derived using DTA (Differential Thermal Analysis) curves. Then, these lignites were subjected to slow burning process in a horizontal tube furnace at different temperatures (200ºC, 400ºC, 600ºC for Adıyaman-Gölbaşı lignite and 200ºC, 450ºC, 800ºC for Kütahya-Tunçbilek lignite) under atmospheres having O₂+N₂ proportions of 21%O₂+79%N₂, 30%O₂+70%N₂, 40%O₂+60%N₂, and 50%O₂+50%N₂. These burning temperatures were specified based on the burning profiles derived from the DTA curves. The residues obtained from these burning tests were also analyzed by proximate and ultimate analyses to detect the unburnt carbon content along with the unused energy potential. Reactivity of these lignites was calculated using several methodologies. Burning yield under air condition (21%O₂+79%N₂) was used a benchmark value to compare the effectiveness of oxygen enriched conditions. It was concluded that oxygen enriched combustion method enhanced the combustion efficiency and lowered the unburnt carbon content of ash. Combustion of low-rank coals under oxygen enriched conditions was found to be a promising way to improve the efficiency of the lignite-firing energy systems. However, cost-benefit analysis should be considered for a better justification of this method since the use of more oxygen brings an unignorable additional cost.

Keywords: coal, energy, oxygen enriched combustion, reactivity

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Authors: Mohamed Abo El Nasr, Mohamed Shoeib, Abdelhamid Abdelkhalik, Amro Serag

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Background: Early assessment of severity of chest trauma, either blunt or penetrating is of critical importance in prediction of patient outcome. Different trauma scoring systems are widely available and are based on anatomical or physiological parameters to expect patient morbidity or mortality. Up till now, there is no ideal, universally accepted trauma score that could be applied in all trauma centers and is suitable for assessment of severity of chest trauma patients. Aim: Our aim was to compare various trauma scoring systems regarding their predictability of morbidity and mortality in chest trauma patients. Patients and Methods: This study was a prospective study including 400 patients with chest trauma who were managed at Tanta University Emergency Hospital, Egypt during a period of 2 years (March 2014 until March 2016). The patients were divided into 2 groups according to the mode of trauma: blunt or penetrating. The collected data included age, sex, hemodynamic status on admission, intrathoracic injuries, and associated extra-thoracic injuries. The patients outcome including mortality, need of thoracotomy, need for ICU admission, need for mechanical ventilation, length of hospital stay and the development of acute respiratory distress syndrome were also recorded. The relevant data were used to calculate the following trauma scores: 1. Anatomical scores including abbreviated injury scale (AIS), Injury severity score (ISS), New injury severity score (NISS) and Chest wall injury scale (CWIS). 2. Physiological scores including revised trauma score (RTS), Acute physiology and chronic health evaluation II (APACHE II) score. 3. Combined score including Trauma and injury severity score (TRISS ) and 4. Chest-Specific score Thoracic trauma severity score (TTSS). All these scores were analyzed statistically to detect their sensitivity, specificity and compared regarding their predictive power of mortality and morbidity in blunt and penetrating chest trauma patients. Results: The incidence of mortality was 3.75% (15/400). Eleven patients (11/230) died in blunt chest trauma group, while (4/170) patients died in penetrating trauma group. The mortality rate increased more than three folds to reach 13% (13/100) in patients with severe chest trauma (ISS of >16). The physiological scores APACHE II and RTS had the highest predictive value for mortality in both blunt and penetrating chest injuries. The physiological score APACHE II followed by the combined score TRISS were more predictive for intensive care admission in penetrating injuries while RTS was more predictive in blunt trauma. Also, RTS had a higher predictive value for expectation of need for mechanical ventilation followed by the combined score TRISS. APACHE II score was more predictive for the need of thoracotomy in penetrating injuries and the Chest-Specific score TTSS was higher in blunt injuries. The anatomical score ISS and TTSS score were more predictive for prolonged hospital stay in penetrating and blunt injuries respectively. Conclusion: Trauma scores including physiological parameters have a higher predictive power for mortality in both blunt and penetrating chest trauma. They are more suitable for assessment of injury severity and prediction of patients outcome.

Keywords: chest trauma, trauma scores, blunt injuries, penetrating injuries

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Authors: Nokwethaba Makhanya, Babatunde J. Abiodun, Piotr Wolski

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Climate change possibly intensifies hydrological droughts and reduces water availability in river basins. Despite this, most research on climate change effects in southern Africa has focused exclusively on meteorological droughts. This thesis projects the potential impact of climate change on the future characteristics of hydrological droughts in the Limpopo River Basin (LRB). The study uses regional climate model (RCM) measurements (from the Coordinated Regional Climate Downscaling Experiment, CORDEX) and a combination of hydrological simulations (using the Soil and Water Assessment Tool Plus model, SWAT+) to predict the impacts at four global warming levels (GWLs: 1.5℃, 2.0℃, 2.5℃, and 3.0℃) under the RCP8.5 future climate scenario. The SWAT+ model was calibrated and validated with a streamflow dataset observed over the basin, and the sensitivity of model parameters was investigated. The performance of the SWAT+LRB model was verified using the Nash-Sutcliffe efficiency (NSE), Percent Bias (PBIAS), Root Mean Square Error (RMSE), and coefficient of determination (R²). The Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI) have been used to detect meteorological droughts. The Soil Water Index (SSI) has been used to define agricultural drought, while the Water Yield Drought Index (WYLDI), the Surface Run-off Index (SRI), and the Streamflow Index (SFI) have been used to characterise hydrological drought. The performance of the SWAT+ model simulations over LRB is sensitive to the parameters CN2 (initial SCS runoff curve number for moisture condition II) and ESCO (soil evaporation compensation factor). The best simulation generally performed better during the calibration period than the validation period. In calibration and validation periods, NSE is ≤ 0.8, while PBIAS is ≥ ﹣80.3%, RMSE ≥ 11.2 m³/s, and R² ≤ 0.9. The simulations project a future increase in temperature and potential evapotranspiration over the basin, but they do not project a significant future trend in precipitation and hydrological variables. However, the spatial distribution of precipitation reveals a projected increase in precipitation in the southern part of the basin and a decline in the northern part of the basin, with the region of reduced precipitation projected to increase with GWLs. A decrease in all hydrological variables is projected over most parts of the basin, especially over the eastern part of the basin. The simulations predict meteorological droughts (i.e., SPEI and SPI), agricultural droughts (i.e., SSI), and hydrological droughts (i.e., WYLDI, SRI) would become more intense and severe across the basin. SPEI-drought has a greater magnitude of increase than SPI-drought, and agricultural and hydrological droughts have a magnitude of increase between the two. As a result, this research suggests that future hydrological droughts over the LRB could be more severe than the SPI-drought projection predicts but less severe than the SPEI-drought projection. This research can be used to mitigate the effects of potential climate change on basin hydrological drought.

Keywords: climate change, CORDEX, drought, hydrological modelling, Limpopo River Basin

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Authors: Evelyn Bilias-Lolis, Emily Louise Winter

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Schools have a responsibility to implement school-wide frameworks that actively prevent, detect, and support all aspects of child development and learning. Such efforts can range from individual or classroom-level supports to school-wide primary prevention practices for the school’s infrastructure or climate. This study assessed the perceptions of educators across a variety of disciplines in Connecticut (i.e., elementary and secondary education, special education, school psychology, and school social work) on the perceived impact of their beliefs, language, and behavior about food and body consciousness on student self-image and school climate. Participants (N=50) completed a short electronic questionnaire measuring perceptions of how their behavior can influence their students’ opinions about themselves, their emerging self-image, and the overall climate of the school community. Secondly, the beliefs that were directly assessed in the first portion of the survey were further measured through the use of applied social vignettes involving students directly or as bystanders. Preliminary findings are intriguing. When asked directly, 100% of the respondents reported that what they say to students directly could influence student opinions about themselves and 98% of participants further agreed that their behavior both to and in front of students could impact a student’s developing self-image. Likewise, 82% of the sample agreed that their personal language and behavior affect the overall climate of a school building. However, when the above beliefs were assessed via applied social vignettes depicting routine social exchanges, results were significantly more widespread (i.e., results were evenly dispersed among levels of agreement and disagreement across participants in all areas). These preliminary findings offer humble but critical implications for informing integrated school wellness frameworks that aim to create body-sensitive school communities. Research indicates that perceptions about body image, attitudes about eating, and the onset of disordered eating practices surface in school-aged years. Schools provide a natural setting for instilling foundations for child wellness as a natural extension of existing school climate reform efforts. These measures do not always need to be expansive or extreme. Rather, educators have a ripe opportunity to become champions for health and wellness through increased self-awareness and subtle shifts in language and behavior. Future psychological research needs to continue to explore this line of inquiry using larger and more varied samples of educators in order to identify needs in teacher training and development that can yield positive and preventative health outcomes for children.

Keywords: body-sensitive schools, integrated school health, school climate reform, teacher awareness

Procedia PDF Downloads 142

Authors: Narayana Bhat, Majda Khalil, Hamad Al-Mansour, Anitha Manuvel, Vimla Yeddu

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The aim of this study was to assess the antimicrobial and antioxidant potential and phytochemical composition of Peganum harmala L. For this purpose, powdered shoot, root, and seed samples were extracted in an accelerated solvent extractor (ASE) with methanol, ethanol, acetone, and dichloromethane. The residues were reconstituted in the above solvents and 10% dimethyl sulphoxide (DMSO). The antimicrobial activity of these extracts was tested against two bacterial (Escherichia coli E49 and Staphylococcus aureus CCUG 43507) and two fungi Candida albicans ATCC 24433, Candida glabrata ATCC 15545) strains using the well-diffusion method. The minimum inhibitory concentration (MIC) and growth pattern of these test strains were determined using microbroth dilution method, and the phospholipase assay was performed to detect tissue damage in the host cells. Results revealed that ethanolic, methanolic, and dichloromethane extracts of seeds exhibited significant antimicrobial activities against all tested strains, whereas the acetone extract of seeds was effective against E. coli only. Similarly, ethanolic and methanolic extracts of roots were effective against two bacterial strains only. One sixth of percent (0.6%) yield of methanol extract of seeds was found to be the MIC for Escherichia coli E49, Staphylococcus aureus CCUG 43507, and Candida glabrata ATCC 15545. Overall, seed extracts had greater antimicrobial activities compared to roots and shoot extracts. The original plant extract and MIC dilutions prevented phospholipase secretion in Staphylococcus aureus CCUG 43507 and Candida albicans ATCC 24433. The 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging assay revealed radical scavenging activities ranging from 71.80 ± 4.36% to 87.75 ± 1.70%. The main compound present in the root extract was 1-methyl-7-methoxy-beta-carboline (RT: 44.171), followed by norlapachol (3.62%), benzopyrazine (2.20%), palmitic acid (2.12%) and vasicinone (1.96%). In contrast, phenol,4-ethenyl-2-methoxy was in abundance in the methonolic extract of the shoot, whereas 1-methyl-7-methoxy-beta-carboline (79.59%), linoleic acid (9.05%), delta-tocopherol (5.02%), 9,12-octadecadienoic acid, methyl ester (2.65%), benzene, 1,1-1,2 ethanediyl bis 3,4dimethyl (1.15%), anthraquinone (0.58%), hexadecanoic acid, methyl ester (0.54%), palmitic acid (0.35%) and methyl stearate (0.18%) were present in the methanol extract of seeds. Major findings of this study, along with their relevance to developing effective, safe drugs, will be discussed in this presentation.

Keywords: medicinal plants, secondary metabolites, phytochemical screening, bioprospecting, radical scavenging

Procedia PDF Downloads 152

Authors: Riya Bose, Ashok Bera, Manas R. Parida, Anirudhha Adhikari, Basamat S. Shaheen, Erkki Alarousu, Jingya Sun, Tom Wu, Osman M. Bakr, Omar F. Mohammed

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This work reports visualization of charge carrier dynamics on the surface of copper indium gallium selenide (CIGSe) nanocrystals in real space and time using four-dimensional scanning ultrafast electron microscopy (4D S-UEM) and correlates it with the optoelectronic properties of the nanocrystals. The surface of the nanocrystals plays a key role in controlling their applicability for light emitting and light harvesting purposes. Typically for quaternary systems like CIGSe, which have many desirable attributes to be used for optoelectronic applications, relative abundance of surface trap states acting as non-radiative recombination centre for charge carriers remains as a major bottleneck preventing further advancements and commercial exploitation of these nanocrystals devices. Though ultrafast spectroscopic techniques allow determining the presence of picosecond carrier trapping channels, because of relative larger penetration depth of the laser beam, only information mainly from the bulk of the nanocrystals is obtained. Selective mapping of such ultrafast dynamical processes on the surfaces of nanocrystals remains as a key challenge, so far out of reach of purely optical probing time-resolved laser techniques. In S-UEM, the optical pulse generated from a femtosecond (fs) laser system is used to generate electron packets from the tip of the scanning electron microscope, instead of the continuous electron beam used in the conventional setup. This pulse is synchronized with another optical excitation pulse that initiates carrier dynamics in the sample. The principle of S-UEM is to detect the secondary electrons (SEs) generated in the sample, which is emitted from the first few nanometers of the top surface. Constructed at different time delays between the optical and electron pulses, these SE images give direct and precise information about the carrier dynamics on the surface of the material of interest. In this work, we report selective mapping of surface dynamics in real space and time of CIGSe nanocrystals applying 4D S-UEM. We show that the trap states can be considerably passivated by ZnS shelling of the nanocrystals, and the carrier dynamics can be significantly slowed down. We also compared and discussed the S-UEM kinetics with the carrier dynamics obtained from conventional ultrafast time-resolved techniques. Additionally, a direct effect of the state trap removal can be observed in the enhanced photoresponse of the nanocrystals after shelling. Direct observation of surface dynamics will not only provide a profound understanding of the photo-physical mechanisms on nanocrystals’ surfaces but also enable to unlock their full potential for light emitting and harvesting applications.

Keywords: 4D scanning ultrafast microscopy, charge carrier dynamics, nanocrystals, optoelectronics, surface passivation, trap states

Procedia PDF Downloads 270