Search results for: molecular techniques

Authors: A. Monika, Manu Sharma, Hong Boo Lee, Richa Dhingra, Neelima Dhingra

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Nuclear factor-κappa B serve as a molecular lynchpin that links persistent infections and chronic inflammation to increased cancer risk. Inflammation has been recognized as a hallmark and cause of cancer. Natural products present a privileged source of inspiration for chemical probe and drug design. Herbal remedies were the first medicines used by humans due to the many pharmacologically active secondary metabolites produced by plants. Some of the metabolites like Lantadene (pentacyclic triterpenoids) from the weed Lantana camara has been known to inhibit cell division and showed anti-antitumor potential. The C-3 aromatic esters of lantadenes were synthesized, characterized and evaluated for cytotoxicity and inhibitory potential against Tumor necrosis factor alpha-induced activation of Nuclear factor-κappa B in lung cancer cell line A549. The 3-methoxybenzoyloxy substituted lead analogue inhibited kinase activity of the inhibitor of nuclear factor-kappa B kinase in a single-digit micromolar concentration. At the same time, the lead compound showed promising cytotoxicity against A549 lung cancer cells with IC50 ( half maximal inhibitory concentration) of 0.98l µM. Further, molecular docking of 3-methoxybenzoyloxy substituted analogue against Inhibitor of nuclear factor-kappa B kinase (Protein data bank ID: 3QA8) showed hydrogen bonding interaction involving oxygen atom of 3-methoxybenzoyloxy with the Arginine-31 and Glutamine-110. Encouraging results indicate the Lantadene’s potential to be developed as anticancer agents.

Keywords: anticancer, lantadenes, pentacyclic triterpenoids, weed

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Authors: Maryam Beiranvand, Sajad Yaghoubi

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Background: Some microbes can colonize plants’ inner tissues without causing obvious damage and can even produce useful bioactive substances. In the present study, the diversity of the endophytic bacteria associated with medicinal plants from Iran was investigated by culturing techniques, molecular gene identification, as well as measuring them for antibacterial activity. Results: In the spring season from 2013 to 2014, 35 herb pharmacology samples were collected, sterilized, meshed, and then cultured on selective media culture. A total of 199 endophytic bacteria were successfully isolated from 35 tissue cultures of medical plants, and sixty-seven out of 199 bacterial isolates were subjected to identification by the 16S rRNA gene sequence analysis method. Based on the sequence similarity gene and phylogenetic analyses, these isolates were grouped into five classes, fourteen orders, seventeen families, twenty-one genera, and forty strains. The most abundant group of endophytic bacteria was actinobacterial, consisting of thirty-two (47%) out of 67 bacterial isolates. Ten (22.3%) out of 67 bacterial isolates remained unidentified and classified at the genus level. The signature of the 16S rRNA gene formed a distinct line in a phylogenetic tree showing that they might be new species of bacteria. One (5.2%) out of 67 bacterial isolates was still not well categorized. Forty-two out of 67 strains were candidates for antimicrobial activity tests. Nineteen (45%) out of 42 strains showed antimicrobial activity multidrug-resistance (MDR); thirteen (68%) out of 19 strains were allocated to classes actinobacteria. Four (21%) out of 19 strains belonged to the Bacillaceae family, one (5.2%) out of 19 strains was the Paenibacillaceae family, and one (5.2%) out of 19 strains belonged to the Pseudomonadaceae family. The other twenty-three strains did not show inhibitory activities. Conclusions: Our research showed a high-level phylogenetic diversity and the intoxicating antibiotic activity of endophytic bacteria in the herb pharmacology of Iran.

Keywords: medical plant, endophytic bacteria, antimicrobial activity, whole genome sequencing analysis

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Authors: Serhat Tuzun, Tufan Demirel

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Multi-Criteria Decision Making (MCDM) is the modelling of real-life to solve problems we encounter. It is a discipline that aids decision makers who are faced with conflicting alternatives to make an optimal decision. MCDM problems can be classified into two main categories: Multi-Attribute Decision Making (MADM) and Multi-Objective Decision Making (MODM), based on the different purposes and different data types. Although various MADM techniques were developed for the problems encountered, their methodology is limited in modelling real-life. Moreover, objective results are hard to obtain, and the findings are generally derived from subjective data. Although, new and modified techniques are developed by presenting new approaches such as fuzzy logic; comprehensive techniques, even though they are better in modelling real-life, could not find a place in real world applications for being hard to apply due to its complex structure. These constraints restrict the development of MADM. This study aims to conduct a comprehensive analysis of preference methods in MADM and propose an approach based on information. For this purpose, a detailed literature review has been conducted, current approaches with their advantages and disadvantages have been analyzed. Then, the approach has been introduced. In this approach, performance values of the criteria are calculated in two steps: first by determining the distribution of each attribute and standardizing them, then calculating the information of each attribute as informational energy.

Keywords: literature review, multi-attribute decision making, operations research, preference method, informational energy

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Authors: Michael Dare Asemoloye, Segun Gbolagade Jonathan, Rafiq Ahmad, Odunayo Joseph Olawuyi, D. O. Adejoye

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Fungi have potentials for degrading hydrocarbons through the secretion of different enzymes. Crude oil tolerance and degradation by Trichoderma harzianum was investigated in this study with its ability to produce peroxidase enzymes (LiP and MnP). Many fungal strains were isolated from rhizosphere of grasses growing on a crude oil spilled site, and the most frequent strain based on percentage incidence was further characterized using morphological and molecular characteristics. Molecular characterization was done through the amplification of Ribosomal-RNA regions of 18s (1609-1627) and 28s (287-266) using ITS1 and ITS4 combinations and it was identified using NCBI BLAST tool. The selected fungus was also subjected to an in-vitro tolerance test at crude oil concentrations of 5, 10, 15, 20 and 25% while 0% served as control. In addition, lignin peroxidase genes (lig1-6) and manganese peroxidase gene (mnp) were detected and expressed in this strain using RT-PCR technique, its peroxidase producing activities was also studied in aliquots (U/ml). This strain had highest incidence of 80%, it was registered in NCBI as Trichoderma harzianum asemoJ KY488466. The strain KY488466 responded to crude oil concentrations as it increase, the dose inhibition response percentage (DIRP) increased from 41.67 to 95.41 at 5 to 25 % crude oil concentrations. All the peroxidase genes are present in KY488466, and expressed with amplified 900-1000 bp through RT-PCR technique. In this strain, lig2, lig4 and mnp genes were over-expressed, lig 6 was moderately expressed, while none of the genes was under-expressed. The strain also produced 90±0.87 U/ml lignin peroxidase and 120±1.23 U/mil manganese peroxidase enzymes in aliquots. These results imply that KY488466 can tolerate and survive high crude oil concentration and could be exploited for bioremediation of oil-spilled soils, the produced peroxidase enzymes could also be exploited for other biotechnological experiments.

Keywords: crude oil, enzymes, expression, peroxidase genes, tolerance, Trichoderma harzianum

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Authors: Ahmed Ali Torad

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Background: Breast feeding maintains the maternal fetal immunological link, favours the transmission of immune-competence from the mother to her infant and is considered an important contributory factor to the neo natal immune defense system. Purpose: This study was conducted to investigate the effect of relaxation techniques on immunological properties of breast milk. Subjects and Methods: Thirty breast feeding mothers with a single, mature infant without any complications participated in the study. Subjects will be recruited from outpatient clinic of obstetric department of El Kasr El-Aini university hospital in Cairo. Mothers were randomly divided into two equal groups using coin toss method: Group (A) (relaxation training group) (experimental group): It will be composed of 15 women who received relaxation training program in addition to breast feeding and nutritional advices and Group (B) (control group): It will be composed of 15 women who received breast feeding and nutritional advices only. Results: The results showed that mean mother’s age was 28.4 ± 3.68 and 28.07 ± 4.09 for group A and B respectively, there were statistically significant differences between pre and post values regarding cortisol level, IgA level, leucocyte count and infant’s weight and height and there is only statistically significant differences between both groups regarding post values of all immunological variables (cortisol – IgA – leucocyte count). Conclusion: We could conclude that there is a statistically significant effect of relaxation techniques on immunological properties of breast milk.

Keywords: relaxation, breast, milk, immunology, lactation

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Authors: M. Doumi, A. Miloudi, A. G. Aissaoui, K. Tahir, C. Belfedal, S. Tahir

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The studies on the photovoltaic system are extensively increasing because of a large, secure, essentially exhaustible and broadly available resource as a future energy supply. However, the output power induced in the photovoltaic modules is influenced by an intensity of solar cell radiation, temperature of the solar cells and so on. Therefore, to maximize the efficiency of the photovoltaic system, it is necessary to track the maximum power point of the PV array, for this Maximum Power Point Tracking (MPPT) technique is used. Some MPPT techniques are available in that perturbation and observation (P&O) and Fuzzy logic controller (FLC). The fuzzy control method has been compared with perturb and observe (P&O) method as one of the most widely conventional method used in this area. Both techniques have been analyzed and simulated. MPPT using fuzzy logic shows superior performance and more reliable control with respect to the P&O technique for this application.

Keywords: photovoltaic system, MPPT, perturb and observe, fuzzy logic

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Authors: Eman I. Raslan, Haitham S. Hamza, Reda A. El-Khoribi

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Fiber-Wireless (FiWi) networks are a promising candidate for future broadband access networks. These networks combine the optical network as the back end where different passive optical network (PON) technologies are realized and the wireless network as the front end where different wireless technologies are adopted, e.g. LTE, WiMAX, Wi-Fi, and Wireless Mesh Networks (WMNs). The convergence of both optical and wireless technologies requires designing architectures with robust efficient and effective bandwidth allocation schemes. Different bandwidth allocation algorithms have been proposed in FiWi networks aiming to enhance the different segments of FiWi networks including wireless and optical subnetworks. In this survey, we focus on the differentiating between the different bandwidth allocation algorithms according to their enhancement segment of FiWi networks. We classify these techniques into wireless, optical and Hybrid bandwidth allocation techniques.

Keywords: fiber-wireless (FiWi), dynamic bandwidth allocation (DBA), passive optical networks (PON), media access control (MAC)

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Authors: Abdulkader Helwan

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Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

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Authors: Jose Flores, Nadia Gamboa

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A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.

Keywords: PCA, HCA, Jequetepeque, multivariate statistical

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Authors: Shanshan Zhu, Mohammad Nasim

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Financial fraud continues to be a major threat to financial institutions across the world, causing colossal money losses and undermining public trust. Fraud prevention techniques, based on hard rules, have become ineffective due to evolving patterns of fraud in recent times. Against such a background, the present study probes into distinct methodologies that exploit emergent AI-driven techniques to further strengthen fraud detection. We would like to compare the performance of generative adversarial networks and graph neural networks with other popular techniques, like gradient boosting, random forests, and neural networks. To this end, we would recommend integrating all these state-of-the-art models into one robust, flexible, and smart system for real-time anomaly and fraud detection. To overcome the challenge, we designed synthetic data and then conducted pattern recognition and unsupervised and supervised learning analyses on the transaction data to identify which activities were fishy. With the use of actual financial statistics, we compare the performance of our model in accuracy, speed, and adaptability versus conventional models. The results of this study illustrate a strong signal and need to integrate state-of-the-art, AI-driven fraud detection solutions into frameworks that are highly relevant to the financial domain. It alerts one to the great urgency that banks and related financial institutions must rapidly implement these most advanced technologies to continue to have a high level of security.

Keywords: AI-driven fraud detection, financial security, machine learning, anomaly detection, real-time fraud detection

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Authors: Delia Enyedi

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Throughout film history, the regular return of 3D cinema has been discussed in connection to crises caused by the advent of television or the competition of the Internet. In addition, the three waves of stereoscopic 3D (from 1952 up to 1983) and its current digital version have been blamed for adding a challenging technical distraction to the viewing experience. By discussing the films Dial M for Murder (1954) and Goodbye to Language (2014), the paper aims to analyze the response of recognized auteurs to the use of 3D techniques in filmmaking. For Alfred Hitchcock, the solution to attaining perceptual immersion paradoxically resided in restraining the signature effect of 3D, namely protrusion. In Jean-Luc Godard’s vision, 3D techniques allowed him to explore perceptual absorption by means of depth of field, for which he had long advocated as being central to cinema. Thus, both directors contribute to the foundation of an auteur aesthetic in 3D filmmaking.

Keywords: Alfred Hitchcock, authorship, 3D filmmaking, Jean-Luc Godard, perceptual absorption, perceptual immersion

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Authors: Jesmin Akter, Chang Hyuk Ahn, Ilho Kim, Jaiyeop Lee

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Global pandemic coronavirus disease (COVID-19) caused by Severe acute respiratory syndrome SARS-CoV-2, to control the spread of the COVID-19 pandemic, wastewater surveillance has been used to monitor SARS-CoV2 prevalence in the community. The challenging part is establishing wastewater surveillance; there is a need for a well-equipped laboratory for wastewater sample analysis. According to many previous studies, reverse transcription-polymerase chain reaction (RT-PCR) based molecular tests are the most widely used and popular detection method worldwide. However, the RT-qPCR based approaches for the detection or quantification of SARS-CoV-2 genetic fragments ribonucleic acid (RNA) from wastewater require a specialized laboratory, skilled personnel, expensive instruments, and a workflow that typically requires 6 to 8 hours to provide results for just minimum samples. Rapid and reliable alternative detection methods are needed to enable less-well-qualified practitioners to set up and provide sensitive detection of SARS-CoV-2 within wastewater at less-specialized regional laboratories. Therefore, scientists and researchers are conducting experiments for rapid detection methods of COVID-19; in some cases, the structural and molecular characteristics of SARS-CoV-2 are unknown, and various strategies for the correct diagnosis of COVID-19 have been proposed by research laboratories, which are presented in the present study. The ongoing research and development of these highly sensitive and rapid technologies, namely RT-LAMP, ELISA, Biosensors, GeneXpert, allows a wide range of potential options not only for SARS-CoV-2 detection but also for other viruses as well. The effort of this study is to discuss the above effective and regional rapid detection and quantification methods in community wastewater as an essential step in advancing scientific goals.

Keywords: rapid detection, SARS-CoV-2, sensitive detection, wastewater surveillance

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Authors: Jonathan Iworiso

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Forecasting the equity premium out-of-sample is a major concern to researchers in finance and emerging markets. The quest for a superior model that can forecast the equity premium with significant economic gains has resulted in several controversies on the choice of variables and suitable techniques among scholars. This research focuses mainly on the application of Regression Training (RT) techniques to forecast monthly equity premium out-of-sample recursively with an expanding window method. A broad category of sophisticated regression models involving model complexity was employed. The RT models include Ridge, Forward-Backward (FOBA) Ridge, Least Absolute Shrinkage and Selection Operator (LASSO), Relaxed LASSO, Elastic Net, and Least Angle Regression were trained and used to forecast the equity premium out-of-sample. In this study, the empirical investigation of the RT models demonstrates significant evidence of equity premium predictability both statistically and economically relative to the benchmark historical average, delivering significant utility gains. They seek to provide meaningful economic information on mean-variance portfolio investment for investors who are timing the market to earn future gains at minimal risk. Thus, the forecasting models appeared to guarantee an investor in a market setting who optimally reallocates a monthly portfolio between equities and risk-free treasury bills using equity premium forecasts at minimal risk.

Keywords: regression training, out-of-sample forecasts, expanding window, statistical predictability, economic significance, utility gains

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Authors: İsmail İnce, Osman Günaydin, Fatma Özer

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Stones used in the construction of historical structures are exposed to various direct or indirect atmospheric effects depending on climatic conditions. Building stones deteriorate partially or fully as a result of this exposure. The historic structures are important symbols of any cultural heritage. Therefore, it is important to protect and restore these historical structures. The aim of this study is to determine the weathering conditions at the Kilistra ancient city. It is located in the southwest of the Konya city, Central Anatolia, and was built by carving into pyroclastic rocks during the Byzantine Era. For this purpose, the petrographic and mechanical properties of the pyroclastic rocks were determined. In the assessment of weathering of structures in the ancient city, in-situ non-destructive testing (i.e., Schmidt hardness rebound value, relative humidity measurement) methods were applied.

Keywords: cultural heritage, Kilistra ancient city, non-destructive techniques, weathering

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Authors: Luigi Delle Rose, Oliver Fischer, Ahmed Hammad

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In this article, we study the prospects of the proposed Large Hadron electron Collider (LHeC) in the search for heavy neutral scalar particles. We consider a minimal model with one additional complex scalar singlet that interacts with the Standard Model (SM) via mixing with the Higgs doublet, giving rise to an SM-like Higgs boson and a heavy scalar particle. Both scalar particles are produced via vector boson fusion and can be tested via their decays into pairs of SM particles, analogously to the SM Higgs boson. Using multivariate techniques, we show that the LHeC is sensitive to heavy scalars with masses between 200 and 800 GeV down to scalar mixing of order 0.01.

Keywords: beyond the standard model, large hadron electron collider, multivariate analysis, scalar singlet

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Authors: Rodrigo Antunes, Olga Borisevich, David Demange

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The Tritium Laboratory Karlsruhe (TLK) has identified zeolite membranes as most promising for tritium processes in the future fusion reactors. Tritium diluted in purge gases or gaseous effluents, and present in both molecular and oxidized forms, can be pre-concentrated by a stage of zeolite membranes followed by a main downstream recovery stage (e.g., catalytic membrane reactor). Since 2011 several membrane zeolite samples have been tested to measure the membrane performances in the separation of hydrogen and water vapor from helium streams. These experiments were carried out in the ZIMT (Zeolite Inorganic Membranes for Tritium) facility where mass spectrometry and cold traps were used to measure the membranes’ performances. The membranes were tested at temperatures ranging from 25 °C up to 130 °C, at feed pressures between 1 and 3 bar, and typical feed flows of 2 l/min. During this experimental campaign, several zeolite-type membranes were studied: a hollow-fiber MFI nanocomposite membrane purchased from IRCELYON (France), and tubular MFI-ZSM5, NaA and H-SOD membranes purchased from Institute for Ceramic Technologies and Systems (IKTS, Germany). Among these membranes, only the MFI-based showed relevant performances for the H2/He separation, with rather high permeances (~0.5 – 0.7 μmol/sm2Pa for H2 at 25 °C for MFI-ZSM5), however with a limited ideal selectivity of around 2 for H2/He regardless of the feed concentration. Both MFI and NaA showed higher separation performances when water vapor was used instead; for example, at 30 °C, the separation factor for MFI-ZSM5 is approximately 10 and 38 for 0.2% and 10% H2O/He, respectively. The H-SOD evidenced to be considerably defective and therefore not considered for further experiments. In this contribution, a comprehensive analysis of the experimental methods and results obtained for the separation performance of different zeolite membranes during the past four years in inactive environment is given. These results are encouraging for the experimental campaign with molecular and oxidized tritium that will follow in 2017.

Keywords: gas separation, nuclear fusion, tritium processes, zeolite membranes

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Authors: Chowduru Ramachandra Sharma, Shatunjay Rawat

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A false positive state is when the IDS/IPS identifies an activity as an attack, but the activity is acceptable behavior in the system. False positives in a Network Intrusion Detection System ( NIDS ) is an issue because they desensitize the administrator. It wastes computational power and valuable resources when rules are not tuned properly, which is the main issue with anomaly NIDS. Furthermore, most false positives reduction techniques are not performed during the real-time of attempted intrusions; instead, they have applied afterward on collected traffic data and generate alerts. Of course, false positives detection in ‘offline mode’ is tremendously valuable. Nevertheless, there is room for improvement here; automated techniques still need to reduce False Positives in real-time. This paper uses the Snort signature detection model to redirect the alerted attacks to Honeypots and verify attacks.

Keywords: honeypot, TPOT, snort, NIDS, honeybird, iptables, netfilter, redirection, attack detection, docker, snare, tanner

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Authors: Rami Faraj, Cezary Graczykowski, Błażej Popławski, Grzegorz Mikułowski, Rafał Wiszowaty

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Progress in the field of sensors, electronics and computing results in more and more often applications of adaptive techniques for dynamic response mitigation. When it comes to systems excited with mechanical impacts, the control system has to take into account the significant limitations of actuators responsible for system adaptation. The paper provides a comprehensive discussion of the problem of appropriate design and implementation of adaptation techniques and mechanisms. Two case studies are presented in order to compare completely different adaptation schemes. The first example concerns a double-chamber pneumatic shock absorber with a fast piezo-electric valve and parameters corresponding to the suspension of a small unmanned aerial vehicle, whereas the second considered system is a safety air cushion applied for evacuation of people from heights during a fire. For both systems, it is possible to ensure adaptive performance, but a realization of the system’s adaptation is completely different. The reason for this is technical limitations corresponding to specific types of shock-absorbing devices and their parameters. Impact mitigation using a pneumatic shock absorber corresponds to much higher pressures and small mass flow rates, which can be achieved with minimal change of valve opening. In turn, mass flow rates in safety air cushions relate to gas release areas counted in thousands of sq. cm. Because of these facts, both shock-absorbing systems are controlled based on completely different approaches. Pneumatic shock-absorber takes advantage of real-time control with valve opening recalculated at least every millisecond. In contrast, safety air cushion is controlled using the semi-passive technique, where adaptation is provided using prediction of the entire impact mitigation process. Similarities of both approaches, including applied models, algorithms and equipment, are discussed. The entire study is supported by numerical simulations and experimental tests, which prove the effectiveness of both adaptive impact mitigation techniques.

Keywords: adaptive control, adaptive system, impact mitigation, pneumatic system, shock-absorber

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Authors: Mattea Carmen Castrovilli, Antonella Cartoni

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Electrospray ionisation (ESI), a well-established technique widely used to produce ion beams of biomolecules in mass spectrometry (ESI-MS), can be used for ambient soft landing of enzymes on a specific substrate. In this work, we show how the ambient electrospray deposition (ESD) technique can be successfully exploited for manufacturing a promising, green-friendly electrochemical amperometric laccase-based biosensor with unprecedented reuse and storage performance. These biosensors have been manufactured by spraying a laccase solution of 2μg/μL at 20% of methanol on a commercial carbon screen printed electrode (C-SPE) using a custom ESD set-up. The laccase-based ESD biosensor has been tested against catechol compounds in the linear range 2-100 μM, with a limit of detection of 1.7 μM, without interference from cadmium, chrome, arsenic, and zinc and without any memory effects, but showing a matrix effect in lake and well water. The ESD biosensor shows enhanced performances compared to the ones fabricated with other immobilization methods, like drop-casting. Indeed, it retains 100% activity up to two months of storage at ambient conditions without any special care and working stability up to 63 measurements on the same electrode just prepared and 20 on a one-year-old electrode subjected to redeposition together with a 100% resistance to use of the same electrode in subsequent days. The ESD method is a one-step, environmentally friendly method that allows the deposition of the bio-recognition layer without using any additional chemicals. The promising results in terms of storage and working stability also obtained with the more fragile lactate oxidase enzyme suggest these improvements should be attributed to the ESD technique rather than to the bioreceptor, highlighting how the ESD could be useful in reducing pollution from disposable devices. Acknowledgment: The understanding at the molecular level of this promising biosensor by using different spectroscopies, microscopies and analytical techniques is the subject of our PRIN 2022 project ESILARANTE.

Keywords: reuse, storage performance, immobilization, electrospray deposition, biosensor, laccase, catechol detection, green chemistry

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Authors: Malika Ourabia

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A new and efficient method is presented for the analysis of arbitrarily shaped discontinuities. The discontinuities is characterized using a hybrid spectral/numerical technique. This structure presents an arbitrary number of ports, each one with different orientation and dimensions. This article presents a hybrid method based on multimode contour integral and mode matching techniques. The process is based on segmentation and dividing the structure into key building blocks. We use the multimode contour integral method to analyze the blocks including irregular shape discontinuities. Finally, the multimode scattering matrix of the whole structure can be found by cascading the blocks. Therefore, the new method is suitable for analysis of a wide range of waveguide problems. Therefore, the present approach can be applied easily to the analysis of any multiport junctions and cascade blocks. The accuracy of the method is validated comparing with results for several complex problems found in the literature. CPU times are also included to show the efficiency of the new method proposed.

Keywords: segmentation, s parameters, simulation, optimization

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Authors: J. Chandrasekhar Rao, B. G. Naidu, G. J. Naga Raju, P. Sarita

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Particle Induced X-ray Emission (PIXE) and Inductively Coupled Plasma Mass Spectroscopy (ICP-MS) techniques have been employed in this work to determine the elements present in the root of Cyperus rotundus medicinal plant used in the treatment of rheumatoid arthritis. The elements V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Rb, and Sr were commonly identified and quantified by both PIXE and ICP-MS whereas the elements Li, Be, Al, As, Se, Ag, Cd, Ba, Tl, Pb and U were determined by ICP-MS and Cl, K, Ca, Ti and Br were determined by PIXE. The regional variation of elemental content has also been studied by analyzing the same plant collected from different geographical locations. Information on the elemental content of the medicinal plant would be helpful in correlating its ability in the treatment of rheumatoid arthritis and also in deciding the dosage of this herbal medicine from the metal toxicity point of view. Principal component analysis and cluster analysis were also applied to the data matrix to understand the correlation among the elements.

Keywords: PIXE, CP-MS, elements, Cyperus rotundus, rheumatoid arthritis

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Authors: Kien Xuan Ngo

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Cassiicolin (Cas), a toxin produced by Corynespora cassiicola, is responsible for corynespora leaf fall (CLF) disease in rubber trees. Currently, the molecular mechanism of the cytotoxicity of Cas isoforms (i.e., Cas1, Cas2) on rubber leaves and its host selectivity have not been fully elucidated. This study analyzed the binding of Cas1 and Cas2 to membranes consisting of different plant lipids and their membrane-disruption activities. Using high-speed atomic force microscopy and confocal microscopy, this study reveals that the binding and disruption activities of Cas1 and Cas2 on lipid membranes are strongly dependent on the specific plant lipids. The negative phospholipids, glycerolipids, and sterols are more susceptible to membrane damage caused by Cas1 and Cas2 than neutral phospholipids and betaine lipids. In summary, This study unveils that (i) Cas1 and Cas2 directly damage and cause necrosis in the leaves of specific rubber clones; (ii) Cas1 and Cas2 can form biofilm-like structures on specific lipid membranes (negative phospholipids, glycerolipids, and sterols). The biofilm-like formation of Cas toxin plays an important role in selective disruption on lipid membranes; (iii) Vulnerability of the specific cytoplasmic membranes to the selective Cas toxin is the most remarkable feature of cytotoxicity of Cas toxin on plant cells. Finally, researcher’s exploration is crucial to understand the basic molecular mechanism underlying the host-selective toxic interaction of Cas toxin with cytoplasmic membranes in plant cells.

Keywords: cassiicolin, corynespora leaf fall disease, high-speed AFM, giant liposome vesicles

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Authors: M. Doudi, M. H. Pazandeh, L. Rahimzadeh Torabi

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Bedsores are pressure ulcers that occur on the skin or tissue due to being immobile and lying in bed for extended periods. Bedsores have the potential to progress into open ulcers, increasing the possibility of variety of bacterial infection. Acinetobacter baumannii, a pathogen of considerable clinical importance, exhibited a significant correlation with Bedsores (pressure ulcers) infections, thereby manifesting a wide spectrum of antibiotic resistance. The emergence of drug resistance has led researchers to focus on alternative methods, particularly phage therapy, for tackling bacterial infections. Phage therapy has emerged as a novel therapeutic approach to regulate the activity of these agents. The management of bacterial infections greatly benefits from the clinical utilization of bacteriophages as a valuable antimicrobial intervention. The primary objective of this investigation consisted of isolating and discerning potent bacteriophage capable of targeting multi drug-resistant (MDR) and extensively drug-resistant (XDR) bacteria obtained from pressure ulcers. In present study, analyzed and isolated A. baumannii strains obtained from a cohort of patients suffering from pressure ulcers at Taleghani Hospital in Ahvaz, Iran. An approach that included biochemical and molecular identification techniques was used to determine the taxonomic classification of bacterial isolates at the genus and species levels. The molecular identification process was facilitated by using the 16S rRNA gene in combination with universal primers 27 F, and 1492 R. Bacteriophage was obtained through the isolation process conducted on treatment plant sewage located in Isfahan, Iran. The main goal of this study was to evaluate different characteristics of phage, such as their appearance, range of hosts they can infect, how quickly they can enter a host, their stability at varying temperatures and pH levels, their effectiveness in killing bacteria, the growth pattern of a single phage stage, mapping of enzymatic digestion, and identification of proteomics patterns. The findings demonstrated that an examination was conducted on a sample of 50 specimens, wherein 15 instances of A. baumannii were identified. These microorganisms are the predominant Gram-negative agents known to cause wound infections in individuals suffering from bedsores. The study's findings indicated a high prevalence of antibiotic resistance in the strains isolated from pressure ulcers, excluding the clinical strains that exhibited responsiveness to colistin.According to the findings obtained from assessments of host range and morphological characteristics of bacteriophage VbɸAB-1, it can be concluded that this phage possesses specificity towards A. Baumannii BAH_Glau1001 was classified as a member of the Plasmaviridae family. The bacteriophage mentioned earlier showed the strongest antibacterial effect at a temperature of 18 °C and a pH of 6.5. Through the utilization of sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis on protein fragments, it was established that the bacteriophage VbɸAB-1 exhibited a size range between 50 and 75 kilodaltons (KDa). The numerous research findings on the effectiveness of phages and the safety studies conducted suggest that the phages studied in this research can be considered as a practical solution and recommended approach for controlling and treating stubborn pathogens in burn wounds among hospitalized patients.

Keywords: acinetobacter baumannii, extremely drug- resistant, phage therapy, surgery wound

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Authors: Suganiya Rama Rao, Yoon-Yen Yow, Thor-Seng Liew, Shyamala Ratnayeke

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Invasive snails in the genus Pomacea have spread across Southeast Asia including Peninsular Malaysia. Apart from significant economic costs to wetland crops, very little is known about the snails’ effects on native species, and wetland function through their alteration of macrophyte communities. This study was conducted to establish diagnostic characteristics of Pomacea species in the Malaysian environment using genetic and morphological criteria. Snails were collected from eight localities in northern and central regions of Peninsular Malaysia. The mitochondrial COI gene of 52 adult snails was amplified and sequenced. Maximum likelihood analysis was used to analyse species identity and assess phylogenetic relationships among snails from different geographic locations. Shells of the two species were compared using geometric morphometric analysis and covariance analyses. Shell height accounted for most of the observed variation between P. canaliculata and P. maculata, with the latter possessing a smaller mean ratio of shell height: aperture height (p < 0.0001) and shell height to shell width (give p < 0.0001). Genomic and phylogenetic analysis demonstrated the presence of two monophyletic taxa, P. canaliculata and P. maculata, in Peninsular Malaysia samples. P. maculata co-occurred with P. canaliculata in 5 localities, but samples from 3 localities contained only P. canaliculata. This study is the first to confirm the presence of two of the most invasive species of Pomacea in Peninsular Malaysia using a genomic approach. P. canaliculata appears to be the more widespread species. Despite statistical differences, both quantitative and qualitative morphological characteristics demonstrate much interspecific overlap and intraspecific variability; thus morphology alone cannot reliably verify species identity. Molecular techniques for distinguishing between these two highly invasive Pomacea species are needed to understand their specific ecological niches and develop effective protocols for their management.

Keywords: Pomacea canaliculata, Pomacea maculata, invasive species, phylog enetic analysis, geometric morphometric analysis

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Authors: D. Glamowska, K. Szymkowska, K. Mojsiewicz- Pieńkowska, K. Cal, Z. Jankowski

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Introduction: The integrity of the outermost layer of skin (stratum corneum) is vital to the penetration of various compounds, including toxic substances. Barrier function of skin depends of its structure. The barrier function of the stratum corneum is provided by patterned lipid lamellae (binlayer). However, a lot of substances, including the low molecular methyl siloxanes (volatile methyl siloxanes, VMS) have an impact on alteration the skin barrier due to damage of stratum corneum structure. VMS belong to silicones. They are widely used in the pharmaceutical as well as cosmetic industry. Silicones fulfill the role of ingredient or excipient in medicinal products and the excipient in personal care products. Due to the significant human exposure to this group of compounds, an important aspect is toxicology of the compounds and safety assessment of products. Silicones in general opinion are considered as a non-toxic substances, but there are some data about their negative effect on living organisms through the inhaled or oral application. However, the transdermal route has not been described in the literature as a possible alternative route of penetration. The aim of the study was to verify the possibility of penetration of the stratum corneum, further permeation into the deeper layers of the skin (epidermis and dermis) as well as to the fluid acceptor by VMS. Methods: Research methodology was developed based on the OECD and WHO guidelines. In ex-vivo study, the fluorescence microscope and ATR FT-IR spectroscopy was used. The Franz- type diffusion cells were used to application of the VMS on the sample of human skin (A=0.65 cm) for 24h. The stratum corneum at the application site was tape-stripped. After separation of epidermis, relevant dyes: fluorescein, sulforhodamine B, rhodamine B hexyl ester were put on and observations were carried in the microscope. To confirm the penetration and permeation of the cyclic or linear VMS and thus the presence of silicone in the individual layers of the skin, spectra ATR FT-IR of the sample after application of silicone and H2O (control sample) were recorded. The research included comparison of the intesity of bands in characteristic positions for silicones (1263 cm-1, 1052 cm-1 and 800 cm-1). Results: and Conclusions The results present that cyclic and linear VMS are able to overcome the barrier of the skin. Influence of them on damage of corneocytes of the stratum corneum was observed. This phenomenon was due to distinct disturbances in the lipid structure of the stratum corneum. The presence of cyclic and linear VMS were identified in the stratum corneum, epidermis as well as in the dermis by both fluorescence microscope and ATR FT-IR spectroscopy. This confirms that the cyclic and linear VMS can penetrate to stratum corneum and permeate through the human skin layers. Apart from this they cause changes in the structure of the skin. Results show to possible absorption into the blood and lymphathic vessels by the VMS with linear and cyclic structure.

Keywords: low molecular methyl siloxanes, volatile methyl siloxanes, linear and cyclic siloxanes, skin penetration, skin permeation

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Authors: M. M. Wagh, V. V. Kulkarni

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The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.

Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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Authors: Rani Danavath, V. B. Narsimha

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Cloud computing is emerging as a new paradigm of large scale distributed computing. Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., three service models, and four deployment networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics models. Load balancing is one of the main challenges in cloud computing, which is required to distribute the dynamic workload across multiple nodes, to ensure that no single node is overloaded. It helps in optimal utilization of resources, enhancing the performance of the system. The goal of the load balancing is to minimize the resource consumption and carbon emission rate, that is the direct need of cloud computing. This determined the need of new metrics energy consumption and carbon emission for energy-efficiency load balancing techniques in cloud computing. Existing load balancing techniques mainly focuses on reducing overhead, services, response time and improving performance etc. In this paper we introduced a Technique for energy-efficiency, but none of the techniques have considered the energy consumption and carbon emission. Therefore, our proposed work will go towards energy – efficiency. So this energy-efficiency load balancing technique can be used to improve the performance of cloud computing by balancing the workload across all the nodes in the cloud with the minimum resource utilization, in turn, reducing energy consumption, and carbon emission to an extent, which will help to achieve green computing.

Keywords: cloud computing, distributed computing, energy efficiency, green computing, load balancing, energy consumption, carbon emission

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

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

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

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Authors: Javad Yarmahmoudi, Alireza Mirzaee

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Many active and passive structural health monitoring (SHM) techniques have been developed for detection of the defects of plates. Generally, riveted joints hold the plates together and their failure may create accidents. In this study, well known active and passive methods were modified for the evaluation of the health of the riveted joints between the plates. The active method generated Lamb waves and monitored their propagation by using lead zirconate titanate (PZT) disks. The signal was analyzed by using the wavelet transformations. The passive method used the Fiber Bragg Grating (FBG) sensors and evaluated the spectral characteristics of the signals by using Fast Fourier Transformation (FFT). The results indicated that the existing methods designed for the evaluation of the health of individual plates may be used for inspection of riveted joints with software modifications.

Keywords: structural health monitoring, SHM, active SHM, passive SHM, fiber bragg grating sensor, lead zirconate titanate, PZT

Procedia PDF Downloads 319