Search results for: microorganisms detection

Authors: Lars Laußat, Manfred Helmus, Kamil Szczesny, Markus König

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As one result of the project “Reactive Construction Project Scheduling using Real Time Construction Logistic Data and Simulation”, a procedure for using data about uncertain resource availability assumptions in reactive scheduling processes has been developed. Prediction data about resource availability is generated in a formalized way using real-time monitoring data e.g. from auto-ID systems on the construction site and in the supply chains. The paper focuses on the formalization of the procedure for monitoring construction logistic processes, for the detection of disturbance and for generating of new and uncertain scheduling assumptions for the reactive resource constrained simulation procedure that is and will be further described in other papers.

Keywords: auto-ID, construction logistic, fuzzy, monitoring, RFID, scheduling

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Authors: Zorica Tomičić, Ružica Tomičić, Peter Raspor

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Growing resistance of pathogenic yeast Candida glabrata to many classes of antifungal drugs has stimulated efforts to discover new agents to combat a rising number of invasive C. glabrata infections, which deserves a great deal of concern due to the high mortality rate in immunocompromised populations. One promising strategy is the use of probiotic microorganisms, which, when administered in adequate amounts, confers a health benefit. A selected number of probiotic organisms, Saccharomyces boulardii among them, have been tested as potential biotherapeutic agents. The aim of this study was to investigate the effect of the probiotic yeast S. boulardii on the adhesion of clinical isolates of C. glabrata at different temperatures, pH values, and in the presence of three clinically important antifungal drugs, such as fluconazole, itraconazole and amphotericin B. The method used to assess adhesion was crystal violet staining. The selection of antimycotics concentrations used in the adhesion assay was based on minimum inhibitory concentrations (MICs) obtained by the preliminarily performed microdilution modification of the Reference method for broth dilution antifungal susceptibility testing of yeast (Clinical and Laboratory Standards Institute (CLSI), standard M27-A2). the results showed that despite the nonadhesiveness of S. boulardii cells, probiotic yeast significantly suppressed the adhesion of C. glabrata strains. Besides, at specific strain ratios, a slight stimulatory effect was observed in some C. glabrata strains, which highlights the importance of strain specificity and opens up further research interests. When environmental conditions are considered, temperature and pH significantly influenced co-culture adhesion of C. glabrata and S. boulardii. The adhesion of C. glabrata strains was relatively equally reduced over all tested temperature range (28°C, 37°C, 39°C and 42°C) in the presence of S. boulardii cells, while the adhesion of a few C. glabrata strains were significantly stimulated at 28°C and suppressed at 42°C. Further, the adhesion was highly dependent on pH, with the highest adherence at pH 4 and lowest at pH 8.5. It was observed that S. boulardii did not manage to suppress the adhesion of C. glabrata strains at high pH. Antimycotics on the other hand showed a greater impact, since S. boulardii failed to affect co-culture adhesion at higher antimycotics concentrations. As expected, exposure to various concentrations of amphotericin B significantly reduced the adherence ability of C.glabrata strains both in a single culture and co-culture with S. boulardii. Therefore, it can be speculated that S. boulardii could substitute the effect of antimycotics in a range concentrations and with specific type of strains. This would certainly change the view on the treatment of yeast infections in the future.

Keywords: adhesion, antimycotics, candida glabrata, saccharomyces boulardii

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Jijun Shi, Lichen Sun, Jianchao Zhao, Lizhi Sun, Enjun Liu, Chongwu Guo

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Because of the consistency of pressure direction, more short cycle, and high sensitivity, Charging-Vacuum helium mass spectrometer leak testing technology is the most popular leak testing technology for the seal testing of the spacecraft parts, especially the small and medium size ones. Usually, auxiliary pump was used, and the minimum detectable leak rate could reach 5E-9Pa•m3/s, even better on certain occasions. Relative error is more important when evaluating the results. How to choose the reference leak, the background level of helium, and record formats would affect the leak rate tested. In the linearity range of leak testing system, it would reduce 10% relative error if the reference leak with larger leak rate was used, and the relative error would reduce obviously if the background of helium was low efficiently, the record format of decimal was used, and the more stable data were recorded.

Keywords: leak testing, spacecraft parts, relative error, error control

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Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

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This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling

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Authors: Zh. Karaulova, D. Baizhigitov

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At the Aktogay deposit, the oxidized ore section has been developed since 2015; by now, the reserves of easily enriched ore are decreasing, and a large number of copper-poor, difficult-to-enrich ores has been accumulated in the dumps of the KAZ Minerals Aktogay deposit, which is unprofitable to mine using the traditional mining methods. Hence, another technology needs to be implemented, which will significantly expand the raw material base of copper production in Kazakhstan and ensure the efficient use of natural resources. Heap and dump bacterial recovery are the most acceptable technologies for processing low-grade secondary copper sulfide ores. Test objects were the copper ores of Aktogay deposit and chemolithotrophic bacteria Leptospirillum ferrooxidans (L.f.), Acidithiobacillus caldus (A.c.), Sulfobacillus Acidophilus (S.a.), which are mixed cultures were both used in bacterial oxidation systems. They can stay active in the 20-400C temperature range. These bacteria were the most extensively studied and widely used in sulfide mineral recovery technology. Biocatalytic acceleration was achieved as a result of bacteria oxidizing iron sulfides to form iron sulfate, which subsequently underwent chemical oxidation to become sulfate oxide. The following results have been achieved at the initial stage: the goal was to grow and maintain the life activity of bacterial cultures under laboratory conditions. These bacteria grew the best within the pH 1,2-1,8 range with light stirring and in an aerated environment. The optimal growth temperature was 30-33оC. The growth rate decreased by one-half for each 4-5°C fall in temperature from 30°C. At best, the number of bacteria doubled every 24 hours. Typically, the maximum concentration of cells that can be grown in ferrous solution is about 107/ml. A further step researched in this case was the adaptation of microorganisms to the environment of certain metals. This was followed by mass production of inoculum and maintenance for their further cultivation on a factory scale. This was done by adding sulfide concentrate, allowing the bacteria to convert the ferrous sulfate as indicated by the Eh (>600 mV), then diluting to double the volume and adding concentrate to achieve the same metal level. This process was repeated until the desired metal level and volumes were achieved. The final stage of bacterial recovery was the transportation and irrigation of secondary sulfide copper ores of the oxidized ore section. In conclusion, the project was implemented at the Aktogay mine since the bioleaching process was prolonged. Besides, the method of bacterial recovery might compete well with existing non-biological methods of extraction of metals from ores.

Keywords: bacterial recovery, copper ore, bioleaching, bacterial inoculum

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Authors: Umberto Cerasani, Luca Cerasani

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Methods for earthquakes forecasting have been intensively investigated in the last decades, but there is still no universal solution agreed by seismologists. Rock failure is most often preceded by a tiny elastic movement in the failure area and by the appearance of micro-cracks. These micro-cracks could be detected at the soil surface and represent useful earth-quakes precursors. The aim of this study was to verify whether tiny raw acceleration signals (in the 10⁻¹ to 10⁻⁴ cm/s² range) prior to the arrival of main primary-waves could be exploitable and related to earthquakes magnitude. Mathematical tools such as Fast Fourier Transform (FFT), moving average and wavelets have been applied on raw acceleration data available on the ITACA web site, and the study focused on one of the most unpredictable earth-quakes, i.e., the August 24th, 2016 at 01H36 one that occurred in the central Italy area. It appeared that these tiny acceleration signals preceding main P-waves have different patterns both on frequency and time domains for high magnitude earthquakes compared to lower ones.

Keywords: earthquake, accelerometer, earthquake forecasting, seism

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Authors: Surita Maini, Sanjay Dhanka

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Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

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Authors: Masood Ahmad, Ataul Aziz Ikram, Ishtiaq Wahid

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Wireless sensor network (WSN) is the interconnection of mobile wireless nodes with limited energy and memory. These networks can be deployed formany critical applications like military operations, rescue management, fire detection and so on. In flat routing structure, every node plays an equal role of sensor and router. The topology may change very frequently due to the mobile nature of nodes in WSNs. The topology maintenance may produce more overhead messages. To avoid topology maintenance overhead messages, an optimized cluster based mobile wireless sensor network using memetic algorithm is proposed in this paper. The nodes in this network are first divided into clusters. The cluster leaders then transmit data to that base station. The network is validated through extensive simulation study. The results show that the proposed technique has superior results compared to existing techniques.

Keywords: WSN, routing, cluster based, meme, memetic algorithm

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Authors: Ali N. Siyal, Saima Q. Memon, Latif Elçi, Aydan Elçi

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Polystyrene (PS) was extracted from Styrofoam (expanded polystyrene foam) waste, so called white pollutant. The PS was functionalized with N, N- Bis(2-aminobenzylidene)benzene-1,2-diamine (ABA) ligand through an azo spacer. The resin was characterized by FT-IR spectroscopy and elemental analysis. The PS-N=N-ABA resin was used for the enrichment and speciation of Cr(III)/Cr(VI) ions and total Cr determination in aqueous samples by Flame Atomic Absorption Spectrometry (FAAS). The separation of Cr(III)/Cr(VI) ions was achieved at pH 2. The recovery of Cr(VI) ions was achieved ≥ 95.0% at optimum parameters: pH 2; resin amount 300 mg; flow rates 2.0 mL min-1 of solution and 2.0 mL min-1 of eluent (2.0 mol L-1 HNO3). Total Cr was determined by oxidation of Cr(III) to Cr(VI) ions using H2O2. The limit of detection (LOD) and quantification (LOQ) of Cr(VI) were found to be 0.40 and 1.20 μg L-1, respectively with preconcentration factor of 250. Total saturation and breakthrough capacitates of the resin for Cr(IV) ions were found to be 0.181 and 0.531 mmol g-1, respectively. The proposed method was successfully applied for the preconcentration/speciation of Cr(III)/Cr(VI) ions and determination of total Cr in industrial effluents.

Keywords: styrofoam waste, polymeric resin, preconcentration, speciation, Cr(III)/Cr(VI) ions, FAAS

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Authors: Taru Singh, Shukla Das, V. G. Ramachandran

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Objectives: To develop SYBR green based real-time PCR assay to detect carbapenemases (NDM, IMP) genes in E. coli. Methods: A total of 40 E. coli from stool samples were tested. Six were previously characterized as resistant to carbapenems and documented by PCR. The remaining 34 isolates previously tested susceptible to carbapenems and were negative for these genes. Bacterial RNA was extracted using manual method. The real-time PCR was performed using the Light Cycler III 480 instrument (Roche) and specific primers for each carbapenemase target were used. Results: Each one of the two carbapenemase gene tested presented a different melting curve after PCR amplification. The melting temperature (Tm) analysis of the amplicons identified was as follows: blaIMP type (Tm 82.18°C), blaNDM-1 (Tm 78.8°C). No amplification was detected among the negative samples. The results showed 100% concordance with the genotypes previously identified. Conclusions: The new assay was able to detect the presence of two different carbapenemase gene type by real-time PCR.

Keywords: resistance, b-lactamases, E. coli, real-time PCR

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Authors: A. Ejah Umraeni Salam, M. Tola, M. Selintung, F. Maricar

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Clean water is an essential and fundamental human need. Therefore, its supply must be assured by maintaining the quality, quantity and water pressure. However the fact is, on its distribution system, leakage happens and becomes a common world issue. One of the technical causes of the leakage is a leaking pipe. The purpose of the research is how to use the Radial Basis Function Neural (RBFNN) model to detect the location and the magnitude of the pipeline leakage rapidly and efficiently. In this study the RBFNN are trained and tested on data from EPANET hydraulic modeling system. Method of Radial Basis Function Neural Network is proved capable to detect location and magnitude of pipeline leakage with of the accuracy of the prediction results based on the value of RMSE (Root Meant Square Error), comparison prediction and actual measurement approaches 0.000049 for the whole pipeline system.

Keywords: radial basis function neural network, leakage pipeline, EPANET, RMSE

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Authors: Raghad A. Altowairgi

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With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

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Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna

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The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.

Keywords: Hyperion, hyperspectral, sensor, Landsat-8

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Authors: Judit Perjessy, Zsolt Zalan, Ferenc Hegyi, Eniko Horvath-Szanics, Krisztina Takacs, Andras Nagy, Adel Klupacs, Erika Koppany-Szabo, Zhirong Wang, Kaituo Wang, Muying Du, Jianquan Kan

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The post-harvest diseases cause great economic losses in the fruit and vegetables; the prevention of these deterioration has great importance. Against the fungi, which cause most of the diseases, are extensively used the fungicides. However, there are increasing consumer concerns over the presence of pesticide residues in food. An alternative and in recent years, increasingly studied method for the prevention of the diseases is biocontrol, where antagonistic microorganisms are used for the control of fungi. The genera of Lactobacillus is well known and extensively studied, but its applicability as biocontrol agents in post-harvest preservation of fruit and vegetables is poorly investigated. However these bacteria can be found on the surface of the plants and have great antimicrobial activity. In our study we have investigated the chitinase activity, the antifungal effect and the applicability of several Lactobacillus strains to select potential biocontrol agents. We investigated the determination of the environmental parameters of a gene (encoding chitinase) expression and we also investigated the relationship between actual antifungal activity and potential chitinase activity. Mixed cultures were also developed to enhance the antifungal activity and determined the optimal mold spore and bacteria concentration ratio for the appropriate efficacy. Five Lactobacillus strains (L. acidophilus N2, L. delbrueckii subsp. bulgaricus B397, L. sp. 2231, L. sake subsp. sake 2471, L. buchneri 1145) possess chitinase-coding gene from the 43 investigated Lactobacillus strains. Proteins with similar molecular weight and separation properties like bacterial chitinases were detected from these strains, which also possess chitin-binding property. Nevertheless, they were inactive, lacks the chitinolytic activity. In point of the cumulative activity of inhibition, our results showed that certain strains were statistically significant in a positive direction compared to other strains, e.g., L. rhamnosus VT1 and L. Casey 154 have shown great general antifungal effect against 11 molds from the genera Penicillium and Botrytis and isolated from spoiled fruit and vegetables. Also, some mixed cultures (L. rhamnosus VT1 - L. Plantarum 299v) showed significant antifungal effects against the indigenous molds on the surface of apple fruit during the industrial storage experiment. Thus, they could be promising for post-harvest biopreservation.

Keywords: biocontrol, chitinase, Lactobacillus, post-harvest

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Authors: Neelamshobha Nirala, R. Periyasamy, Awanish Kumar

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Diabetes is a metabolic disorder and with the increase of global prevalence of diabetes, cardiovascular diseases and mortality related to diabetes has also increased. Diabetes causes the increase of arterial stiffness by elusive hormonal and metabolic abnormalities. We used photoplethysmograph (PPG), a simple non-invasive method to study the change in arterial stiffness due to diabetes. Toe PPG signals were taken from 29 diabetic subjects with mean age of (65±8.4) years and 21 non-diabetic subjects of mean age of (49±14) years. Mean duration of diabetes is 12±8 years for diabetic group. Rise-time (RT) and area under rise time (AUR) were calculated from the PPG signal of each subject and Welch’s t-test is used to find the significant difference between two groups. We obtained a significant difference of (p-value) 0.0005 and 0.03 for RT and AUR respectively between diabetic and non-diabetic subjects. Average value of RT and AUR is 0.298±0.003 msec and 14.4±4.2 arbitrary units respectively for diabetic subject compared to 0.277±0.0005 msec and 13.66±2.3 a.u respectively for non-diabetic subjects. In conclusion, this study support that arterial stiffness is increased in diabetes and can be detected early using PPG.

Keywords: area under rise-time, AUR, arterial stiffness, diabetes, photoplethysmograph, PPG, rise-time (RT)

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Authors: P. S. Surya Meghana, K. Lingeshwaran, C. Kannan, V. Raghavendran, C. Priya

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One of the most basic and powerful tools in all of science and medicine is the light microscope, the fundamental device for laboratory as well as research purposes. With the improving technology, the need for portable, economic and user-friendly instruments is in high demand. The conventional microscope fails to live up to the emerging trend. Also, adequate access to healthcare is not widely available, especially in developing countries. The most basic step towards the curing of a malady is the diagnosis of the disease itself. The main aim of this paper is to diagnose Malaria with the most common device, cell phones, which prove to be the immediate solution for most of the modern day needs with the development of wireless infrastructure allowing to compute and communicate on the move. This opened up the opportunity to develop novel imaging, sensing, and diagnostics platforms using mobile phones as an underlying platform to address the global demand for accurate, sensitive, cost-effective, and field-portable measurement devices for use in remote and resource-limited settings around the world.

Keywords: cellular, hand-held, health care, image processing, malarial parasites, microscope

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Authors: Morello Sara, Pederiva Sabina, Bianchi Manila, Martucci Francesca, Marchis Daniela, Decastelli Lucia

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Vegetables represent an integral part of a healthy diet due to their valuable nutritional properties and the growth in consumer demand in recent years is particularly remarkable for a diet rich in vitamins and micronutrients. However, plant-based products are involved in several food outbreaks connected to various sources of contamination and quite often, bacteria responsible for side effects showed high resistance to antibiotics. The abuse of antibiotics can be one of the main mechanisms responsible for increasing antibiotic resistance (AR). Plants grown for food use can be contaminated directly by spraying antibiotics on crops or indirectly by treatments with antibiotics due to the use of manure, which may contain both antibiotics and genes of antibiotic resistance (ARG). Antibiotic residues could represent a potential way of human health risk due to exposure through the consumption of plant-based foods. The presence of antibiotic-resistant bacteria might pose a particular risk to consumers. The present work aims to investigate through a multidisciplinary approach the occurrence of ARG by means of a biomolecular approach (PCR) and the prevalence of antibiotic residues using a multi residues LC-MS/MS method, both in different plant-based products. During the period from July 2020 to October 2021, a total of 74 plant samples (33 lettuces and 41 tomatoes) were collected from 57 farms located throughout the Piedmont area, and18 out of 74 samples (11 lettuces and 7 tomatoes) were selected to LC-MS/MS analyses. DNA extracted (ExtractME, Blirt, Poland) from plants used on crops and isolated bacteria were analyzed with 6 sets of end-point multiplex PCR (Qiagen, Germany) to detect the presence of resistance genes of the main antibiotic families, such as tet genes (tetracyclines), bla (β-lactams) and mcr (colistin). Simultaneous detection of 43 molecules of antibiotics belonging to 10 different classes (tetracyclines, sulphonamides, quinolones, penicillins, amphenicols, macrolides, pleuromotilines, lincosamides, diaminopyrimidines) was performed using Exion LC system AB SCIEX coupled to a triple quadrupole mass spectrometer QTRAP 5500 from AB SCIEX. The PCR assays showed the presence of ARG in 57% (n=42): tetB (4.8%; n=2), tetA (9.5%; n=4), tetE (2.4%; n=1), tetL (12%; n=5), tetM (26%; n=11), blaSHV (21.5%; n=9), blaTEM (4.8%; n =2) and blaCTX-M (19%; n=8). In none of the analyzed samples was the mcr gene responsible for colistin resistance detected. Results obtained from LC-MS/MS analyses showed that none of the tested antibiotics appear to exceed the LOQ (100 ppb). Data obtained confirmed the presence of bacterial populations containing antibiotic resistance determinants such as tet gene (tetracycline) and bla genes (beta-lactams), widely used in human medicine, which can join the food chain and represent a risk for consumers, especially with raw products. The presence of traces of antibiotic residues in vegetables, in concentration below the LOQ of the LC-MS/MS method applied, cannot be excluded. In conclusion, traces of antibiotic residues could be a health risk to the consumer due to potential involvement in the spread of AR. PCR represents a useful and effective approach to characterize and monitor AR carried by bacteria from the entire food chain.

Keywords: plant-based products, ARG, PCR, antibiotic residues

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Authors: Santi Maneewatchararangsri, Wanpen Chaicumpa, Patcharin Saengjaruk, Urai Chaisri

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Leptospirosis is a globally neglected disease that continues to be a significant public health and veterinary burden, with millions of cases reported each year. Early and accurate differential diagnosis of leptospirosis from other febrile illnesses and the development of a broad spectrum of leptospirosis vaccines are needed. The LipL32 outer membrane lipoprotein is a member of Leptospira adhesive matrices and has been found to exert hemolytic activity to erythrocytes in vitro. Therefore, LipL32 is regarded as a potential target for diagnosis, broad-spectrum leptospirosis vaccines, and for passive immunotherapy. In this study, we established LipL32-specific mouse monoclonal antibodies, mAbLPF1 and mAbLPF2, and their respective mouse- and humanized-engineered single chain variable fragment (ScFv). Their antibodies’ neutralizing activities against Leptospira-mediated hemolysis in vitro, and the therapeutic efficacy of mAbs against heterologous Leptospira infected hamsters were demonstrated. The epitope peptide of mAb LPF1 was mapped to a non-contiguous carboxy-terminal β-turn and amphipathic α-helix of LipL32 structure contributing to phospholipid/host cell adhesion and membrane insertion. We found that the mAbLPF2 epitope was located on the interacting loop of peptide binding groove of the LipL32 molecule responsible for interactions with host constituents. Epitope sequences are highly conserved among Leptospira spp. and are absent from the LipL32 superfamily of other microorganisms. Both epitopes are surface-exposed, readily accessible by mAbs, and immunogenic. However, they are less dominant when revealed by LipL32-specific immunoglobulins from leptospirosis-patient sera and rabbit hyperimmune serum raised by whole Leptospira. Our study also demonstrated an adhesion inhibitory activity of LipL32 protein to host membrane components and cells mediated by mAbs as well as an anti-hemolytic activity of the respective antibodies. The therapeutic antibodies, particularly the humanized-ScFv, have a potential for further development as non-drug therapeutic agent for human leptospirosis, especially in subjects allergic to antibiotics. The epitope peptides recognized by two therapeutic mAbs have potential use as tools for structure-function studies. Finally, protective peptides may be used as a target for epitope-based vaccines for control of leptospirosis.

Keywords: leptospira lipl32-specific antibodies, therapeutic epitopes, epitopes characterization, immunotherapy

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Authors: Raghuveer Kaur, Kartikay Sharma, Ashu Khanna

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Earnings management has been present from times immemorial. The recent downfall of giant enterprises like Enron, Satyam and WorldCom has brought a lot of focus on the study and detection of earnings management. The present study is an attempt to study earnings management in one of the fastest emerging economy - India. The study makes an attempt to understand earnings management in different sectors of the economy. The paper first tests a hypothesis to check whether different sectors of India are engaged in earnings management or not. In the later section the paper aims to study the level of earnings management in 6 popular sectors of India: IT&BPO, Retail, Telecom, Biotech, Hotels and coffee. To measure earnings management two popular techniques of detecting earnings management has been employed: Modified Jones Model and Beniesh M Score. A total of 332 companies were studied. Publicly available data from Capitaline database has been used. The paper also classifies the top and bottom five performers on the basis of sales turnover in each sector and identifies whether they manage their earnings or not.

Keywords: earnings management, India, modified Jones model, Beneish M score

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Authors: Norah Mohammed Alshahrani, Abdulaziz Almaleh

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Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD and they are Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then Feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by the Support Vector Machine (SVM), achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: autism spectrum disorder, machine learning, feature selection, support vector machine

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Authors: Jyun-Guo You, Wei-Lung Tseng

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Herein, this study represents a synthetic route for producing highly luminescent AuNCs based on the integration of two concepts, including thiol-induced luminescence enhancement of ligand-insufficient GSH-AuNCs and Ce3+-induced aggregation of GSH-AuNCs. The synthesis of GSH-AuNCs was conducted by modifying the previously reported procedure. To produce more Au(I)-GSH complexes on the surface of ligand-insufficient GSH-AuNCs, the extra GSH is added to attach onto the AuNC surface. The formed ligand-sufficient GSH-AuNCs (LS-GSH-AuNCs) emit relatively strong luminescence. The luminescence of LS-GSH-AuNCs is further enhanced by the coordination of two carboxylic groups (pKa1 = 2 and pKa2 = 3.5) of GSH and lanthanide ions, which induce the self-assembly of LS-GSH-AuNCs. As a result, the quantum yield of the self-assembled LS-GSH-AuNCs (SA-AuNCs) was improved to be 13%. Interestingly, the SA-AuNCs were dissembled into LS-GSH-AuNCs in the presence of adenosine triphosphate (ATP) because of the formation of the ATP- lanthanide ion complexes. Our assay was employed to detect alkaline phosphatase (ALP) activity over the range of 0.1−10 U/mL with a limit of detection (LOD) of 0.03 U/mL.

Keywords: self-assembly, lanthanide ion, adenosine triphosphate, alkaline phosphatase

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Authors: Raphael C. Zero, Marita V. Cardozo, Thiago A. S. S. Rocha, Mariana T. Kihara, Fernando A. Ávila, Fabrício S. Oliveira

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There are several fixative and preservative solutions for use on cadavers, many of them using formaldehyde as the fixative or anatomical part preservative. In some countries, such as Brazil, this toxic agent has been increasingly restricted. The objective of this study was to microbiologically identify and quantify the key agents in tanks containing 96GL ethanol or sodium chloride solutions, used respectively as fixatives and preservatives of cat cadavers. Eight adult cat corpses, three females and five males, with an average weight of 4.3 kg, were used. After injection via the external common carotid artery (120 ml/kg, 95% 96GL ethyl alcohol and 5% pure glycerin), the cadavers were fixed in a plastic tank with 96GL ethanol for 60 days. After fixing, they were stored in a 30% sodium chloride aqueous solution for 120 days in a similar tank. Samples were collected at the start of the experiment - before the animals were placed in the ethanol tanks, and monthly thereafter. The bacterial count was performed by Pour Plate Method in BHI agar (Brain Heart Infusion) and the plates were incubated aerobically and anaerobically for 24h at 37ºC. MacConkey agar, SPS agar (Sulfite Polymyxin Sulfadizine) and MYP Agar Base were used to isolate the microorganisms. There was no microbial growth in the samples prior to alcohol fixation. After 30 days of fixation in the alcohol solution, total aerobic and anaerobic (<1.0 x 10 CFU/ml) were found and Pseudomonas sp., Staphylococcus sp., Clostridium sp. were the identified agents. After 60 days in the alcohol fixation solution, total aerobes (<1.0 x 10 CFU/ml) and total anaerobes (<2.2 x 10 CFU/mL) were found, and the identified agents were the same. After 30 days of storage in the aqueous solution of 30% sodium chloride, total aerobic (<5.2 x 10 CFU/ml) and total anaerobes (<3.7 x 10 CFU/mL) were found and the agents identified were Staphylococcus sp., Clostridium sp., and fungi. After 60 days of sodium chloride storage, total aerobic (<3.0 x 10 CFU / ml) and total anaerobes (<7.0 x 10 CFU/mL) were found and the identified agents remained the same: Staphylococcus sp., Clostridium sp., and fungi. The microbiological count was low and visual inspection did not reveal signs of contamination in the tanks. There was no strong odor or purification, which proved the technique to be microbiologically effective in fixing and preserving the cat cadavers for the four-month period in which they are provided to undergraduate students of University of Veterinary Medicine for surgery practice. All experimental procedures were approved by the Municipal Legal Department (protocol 02.2014.000027-1). The project was funded by FAPESP (protocol 2015-08259-9).

Keywords: anatomy, fixation, microbiology, small animal, surgery

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Authors: Asma Bashir, Neha Farid, Kashif Ali, Kiran Fatima

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Background: Bacteriocins are a subclass of antimicrobial peptides that are becoming extremely important in treatments. It is possible to utilise bacteriocins in place of or in addition to traditional antibiotics. It is possible to treat a variety of infections, including Vancomycin-Resistant Staphylococcus aureus (VRSA) and Methicillin-Resistant Staphylococcus aureus (MRSA), using the targeted spectrum of activity of these microorganisms. Method: This study aimed to examine the efficiency of antibiotics and bacteriocin against VRSA and MRSA. The effects of bacteriocins, such as enterocin KAE01, enterocin KAE03, enterocin KAE05, and enterocin KAE06 isolated from Enterococcus faecium strains, alone and in combination with vancomycin and methicillin antibiotics were examined. The selection technique utilized the minimum inhibitory concentrations (MICs) against Gram-positive indicator strain ATCC 6538 Methicillin-Resistant Staphylococcus aureus (MRSA) and indicator strain KSA 02 Vancomycin-Resistant Staphylococcus aureus (VRSA). Results: We report the isolation and identification of enterocins KAE01, KAE03, KAE05, and KAE06 from food isolates of Enterococcus faecium (KAE01, KAE03, KAE05, and KAE06). After isolating the protein, it was partially purified with ammonium sulphate precipitation and purified with fast protein liquid chromatography (FPLC) procedures. Combinations of enterocin KAE01, 1 citric acid, 1 lactic acid, and microcin J25, 1 reuterin, 1 citric acid, and microcin J25, 1 reuterin, 1 lactic acid shown synergistic benefits (FIC index = 0.5) against Vancomycin-Resistant Staphylococcus aureus (VRSA). In addition, a moderately synergistic (FIC index = 0.75) interaction was seen between pediocin PA-1, 1 citric acid, 1 lactic acid, and reuterin 1 citric acid, 1 lactic acid against L. ivanovii HPB28. In the presence of acids, nisin Z exhibited a modestly synergistic effect (FIC index = 0.625-0.75); however, it exhibited additive effects (FIC index = 1) when combined with reuterin or pediocin PA-1 against L. ivanovii HPB28. The efficacy of synergistic consortiums against Gram-positive bacteria was examined. Conclusion: Combining antimicrobials with various modes of action boosted efficacy and expanded the spectrum of inhibition, particularly against multidrug-resistant pathogens, according to our research.

Keywords: Enterococcus faecium, bacteriocin, antimicrobial resistance, antagonistic activity, vancomycin-resistant Staphylococcus aureus, methicillin-resistant Staphylococcus aureus

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: O. Ikpotokin

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In any production process, every product is aimed to attain a certain standard, but the presence of assignable cause of variability affects our process, thereby leading to low quality of product. The ability to identify and remove this type of variability reduces its overall effect, thereby improving the quality of the product. In case of a univariate control chart signal, it is easy to detect the problem and give a solution since it is related to a single quality characteristic. However, the problems involved in the use of multivariate control chart are the violation of multivariate normal assumption and the difficulty in identifying the quality characteristic(s) that resulted in the out of control signals. The purpose of this paper is to examine the use of non-parametric control chart (the bootstrap approach) for obtaining control limit to overcome the problem of multivariate distributional assumption and the p-value method for detecting out of control signals. Results from a performance study show that the proposed bootstrap method enables the setting of control limit that can enhance the detection of out of control signals when compared, while the p-value method also enhanced in identifying out of control variables.

Keywords: bootstrap control limit, p-value method, out-of-control signals, p-value, quality characteristics

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Authors: Zeid A. Alothman

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Silver nanoparticle (AgNP) has been synthesized using adrenaline. Adrenaline readily undergoes an autoxidation reaction in an alkaline medium with the dissolved oxygen to form adrenochrome, thus behaving as a mild reducing agent for the dissolved oxygen. This reducing behavior of adrenaline when employed to reduce Ag(+) ions yielded a large enhancement in the intensity of absorbance in the visible region. Transmission electron microscopy (TEM) and X-ray diffraction (XRD) studies have been performed to confirm the surface morphology of AgNPs. Further, the metallic nanoparticles with size greater than 2 nm caused a strong and broad absorption band in the UV-visible spectrum called surface plasmon band or Mie resonance. The formation of AgNPs caused the large enhancement in the absorbance values with λmax at 436 nm through the excitation of the surface plasmon band. The formation of AgNPs was adapted to for the quantitative assessment of adrenaline using spectrophotometry with lower detection limit and higher precision values.

Keywords: silver nanoparticle, adrenaline, XRD, TEM, analysis

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Authors: Claudio Lamilla, Andrés Santos, Vicente Llanquinao, Jocelyn Hermosilla, Leticia Barrientos

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The industry in general is very interested in improving and optimizing industrial processes in order to reduce the costs involved in obtaining raw materials and production. Thus, an interesting and cost-effective alternative is the incorporation of bioactive metabolites in such processes, being an example of this enzymes which catalyze efficiently a large number of enzymatic reactions of industrial and biotechnological interest. In the search for new sources of these active metabolites, Antarctica is one of the least explored places on our planet where the most drastic cold conditions, salinity, UVA-UVB and liquid water available are present, features that have shaped all life in this very harsh environment, especially bacteria that live in different Antarctic ecosystems, which have had to develop different strategies to adapt to these conditions, producing unique biochemical strategies. In this work the production of cellulolytic enzymes of seven bacterial strains isolated from marine sediments at different sites in the Antarctic was evaluated. Isolation of the strains was performed using serial dilutions in the culture medium at M115°C. The identification of the strains was performed using universal primers (27F and 1492R). The enzyme activity assays were performed on R2A medium, carboxy methyl cellulose (CMC)was added as substrate. Degradation of the substrate was revealed by adding Lugol. The results show that four of the tested strains produce enzymes which degrade CMC substrate. The molecular identifications, showed that these bacteria belong to the genus Streptomyces and Pseudoalteromonas, being Streptomyces strain who showed the highest activity. Only some bacteria in marine sediments have the ability to produce these enzymes, perhaps due to their greater adaptability to degrade at temperatures bordering zero degrees Celsius, some algae that are abundant in this environment and have cellulose as the main structure. The discovery of new enzymes adapted to cold is of great industrial interest, especially for paper, textiles, detergents, biofuels, food and agriculture. These enzymes represent 8% of industrial demand worldwide and is expected to increase their demand in the coming years. Mainly in the paper and food industry are required in extraction processes starch, protein and juices, as well as the animal feed industry where treating vegetables and grains helps improve the nutritional value of the food, all this clearly puts Antarctic microorganisms and their enzymes specifically as a potential contribution to industry and the novel biotechnological applications.

Keywords: antarctic, bacteria, biotechnological, cellulolytic enzymes

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Authors: Bong Keun Kang, Sung Suk Oh, Jeong-Woo Sohn, Jong-Ryul Choi, Young Ho Kim

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In this paper, we describe two-step micro-pattering by using laser cutting and wax printing. Wax printing is performed only on the bridges for hydrophobic barriers. We prepared 405nm blue-violet laser module and wax pencil module. And, this two modules combine x-y plot. The hollow microstructure formed by laser patterning define the hydrophilic flowing paths. However, bridges are essential to avoid the cutting area being the island. Through the support bridges, microfluidic solution spread out to the unnecessary areas. Chromatography blotting paper was purchased from Whatman. We used 20x20 cm and 46x57 cm of chromatography blotting paper. Axis moving speed of x-y plot was the main parameter of optimization. For aligning between the two patterning, the paper sheet was taped at the bottom. After the two-step patterning, temperature curing step was done at 110-130 °C. The resolution of the fabrication and the potential of the multiplex detection were investigated.

Keywords: µPADs, microfluidic, biosensor, mass-fabrication

Procedia PDF Downloads 464