Search results for: extraction wound

Authors: Abderrahim Cheriguene, Fatiha Arioui

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The experimental study focuses on the extraction of pectin, whey protein and gelatin, and the study of their functional properties. Microbiological, physicochemical and sensory approach integrated has been implanted to study the effect of the incorporation of these natural food additives in the matrix of a fermented milk type set yogurt, to study the stability of the product during the periods of fermentation and post-acidification over a period of 21 days at 4°C. Pectin was extracted in hot HCl solution. Thermo-precipitation was carried out to obtain the whey proteins while the gelatin was extracted by hydrolysis of the collagen from bovine ossein. The fermented milk was prepared by varying the concentration of the incorporated additives. The measures and controls carried performed periodically on fermented milk experimental tests were carried out: pH, acidity, viscosity, the enumeration of Streptococcus thermophilus, cohesiveness, adhesiveness, taste, aftertaste, whey exudation, and odor. It appears that the acidity, viscosity, and number of Streptococcus thermophilus increased with increasing concentration of additive added in the experimental tests. Indeed, it seems clear that the quality of fermented milk and storability is more improved than the incorporation rate is high. The products showed a better test and a firmer texture limiting the whey exudation.

Keywords: fermented milk, pectin, gelatin, whey proteins, functional properties, quality, conservation, valorization

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Authors: Elham Allahmoradi, Bahman Allahmoradi, Ali Bonyadi Naeini

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Complex systems have many aspects. A variety of methods have been developed to analyze these systems. The most efficient of these methods should not only be simple, but also provide useful and comprehensive information about many aspects of the system. Matrix methods are considered the most commonly methods used to analyze and design systems. Each matrix method can examine a particular aspect of the system. If these methods are combined, managers can access to more comprehensive and broader information about the system. This study was conducted in four steps. In the first step, a process model of a real project has been extracted through IDEF3. In the second step, activity levels have been attained by writing a process model in the form of a design structure matrix (DSM) and sorting it through triangulation algorithm (TA). In the third step, sub-processes have been obtained by writing the process model in the form of an interface structure matrix (ISM) and clustering it through cluster identification algorithm (CIA). In the fourth step, a mixed model has been developed to provide a unified picture of the project structure through the simultaneous presentation of activities and sub-processes. Finally, the paper is completed with a conclusion.

Keywords: integrated definition for process description capture (IDEF3) method, design structure matrix (DSM), interface structure matrix (ism), mixed matrix model, activity level, sub-process

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Authors: Mohammad Abotalib, Hamid Alhamadi

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In Kuwait, electricity is generated from two primary sources that are heavy fuel combustion and natural gas combustion. As Kuwait relies mainly on petroleum-based products for electricity generation, identifying and understanding the environmental trade-off of such operations should be carefully investigated. The life cycle assessment (LCA) tool is applied to identify the potential environmental impact of electricity generation under three scenarios by considering the material flow in various stages involved, such as raw-material extraction, transportation, operations, and waste disposal. The three scenarios investigated represent current and futuristic electricity grid mixes. The analysis targets six environmental impact categories: (1) global warming potential (GWP), (2) acidification potential (AP), (3) water depletion (WD), (4) acidification potential (AP), (4) eutrophication potential (EP), (5) human health particulate matter (HHPM), and (6) smog air (SA) per one kWh of electricity generated. Results indicate that one kWh of electricity generated would have a GWP (881-1030) g CO₂-eq, mainly from the fuel combustion process, water depletion (0.07-0.1) m³ of water, about 68% from cooling processes, AP (15.3-17.9) g SO₂-eq, EP (0.12-0.14) g N eq., HHPA (1.13- 1.33)g PM₂.₅ eq., and SA (64.8-75.8) g O₃ eq. The variation in results depend on the scenario investigated. It can be observed from the analysis that introducing solar photovoltaic and wind to the electricity grid mix improves the performance of scenarios 2 and 3 where 15% of the electricity comes from renewables correspond to a further decrease in LCA results.

Keywords: energy, functional uni, global warming potential, life cycle assessment, energy, functional unit

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Authors: Sayanti Kar, Amitava Ghosh, Pritam Aitch, Gupinath Bhandari

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An extensive seasonal analysis of wastewater had been done from outfalls of river Ganga in Howrah, Hooghly, 24 PGS (N) District, West Bengal, India during 2017. The morphological parameters of Bitter gourd (Momordica charantia L.) were estimated under wastewater treatment. An approach to study the activity within the range of low molecular weight peptide 3-0.5 kDa were taken through its extraction and purification by ion exchange resin column, cation, and anion exchanger. HPLC analysis had been done for both in wastewater treated and untreated plants. The antioxidant activity by using DPPH and germination percentage in control and treated plants were also determined in relation to wastewater effect. The inhibition of growth and its parameters were maximum in pre-monsoon in comparing to post-monsoon and monsoon season. The study also helped to explore the effect of wastewater on the peptidome of Bitter gourd (Momordica charantia L.). Some of these low molecular weight peptide(s) (3-0.5 kDa) also inhibited during wastewater treatment. Expression of particular peptide(s) or absence of some peptide(s) in chromatogram indicated the adverse effects on plants which may be the indication of stressful condition. Pre monsoon waste water was found to create more impact than other two.

Keywords: bitter gourd (Momordica charantia l.), low molecular weight peptide, river ganga, waste water

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Authors: Maíra O. Palm, Cintia Marangoni, Ozair Souza, Noeli Sellin

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Wastes from a vegetal extracts industry (cocoa, oak, Guarana and mate) were characterized by particle size, proximate and ultimate analysis, lignocellulosic fractions, high heating value, thermal analysis (Thermogravimetric analysis – TGA, and Differential thermal analysis - DTA) and energy density to evaluate their potential as biomass in the form of briquettes for power generation. All wastes presented adequate particle sizes to briquettes production. The wastes showed high moisture content, requiring previous drying for use as briquettes. Cocoa and oak wastes had the highest volatile matter contents with maximum mass loss at 310 ºC and 450 ºC, respectively. The solvents used in the aroma extraction process influenced in the moisture content of the wastes, which was higher for mate due to water has been used as solvent. All wastes showed an insignificant loss mass after 565 °C, hence resulting in low ash content. High carbon and hydrogen contents and low sulfur and nitrogen contents were observed ensuring a low generation of sulfur and nitrous oxides. Mate and cocoa exhibited the highest carbon and lignin content, and high heating value. The dried wastes had high heating value, from 17.1 MJ/kg to 20.8 MJ/kg. The results indicate the energy potential of wastes for use as fuel in power generation.

Keywords: agro-industrial waste, biomass, briquettes, combustion

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Authors: Mirjana Dragas, Marli Gonan Bozac, Morena Paulisic

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Corporate social responsibility (CSR) is a balance between strategic and financial goals of companies, as well as social needs. The integration of competitive strategy and CSR in food and beverage industry has allowed companies to find new sources of competitive advantage. The paper discusses the fact that socially responsible companies encourage co-operation with socially responsible suppliers in order to strengthen market competitiveness. In addition to the descriptive interpretation of the results obtained by a questionnaire, factor analysis was used, while principal components analysis was applied as a factor extraction method. The research results based on two multiple regression analyses show that: (1) selecting the CSR supplier explains a statistically significant part of the variance of the results on the scale of financial aspects of competitiveness (as much as 44.7% of the explained variance); and (2) selecting the CSR supplier is a significant predictor of non-financial aspects of competitiveness (explains 43.9% of the variance of the results on the scale of non-financial aspects of competitiveness). A successful competitive strategy must ultimately support the growth strategy. This implies an analytical approach to finding factors that influence competitiveness through socially sustainable solutions and satisfactory top management decisions.

Keywords: competitiveness, corporate social responsibility, food and beverage industry, supply chain decision making

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Authors: Rupinder Kaur, Parmjit S. Panesar, Ram S. Singh

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Whey is the lactose rich by-product of the dairy industry, having good amount of nutrient reservoir. Most abundant nutrients are lactose, soluble proteins, lipids and mineral salts. Disposing of whey by most of milk plants which do not have proper pre-treatment system is the major issue. As a result of which, there can be significant loss of potential food and energy source. Thus, whey has been explored as the substrate for the synthesis of different value added products such as enzymes. β-galactosidase is one of the important enzymes and has become the major focus of research due to its ability to catalyze both hydrolytic as well as transgalactosylation reaction simultaneously. The enzyme is widely used in dairy industry as it catalyzes the transformation of lactose to glucose and galactose, making it suitable for the lactose intolerant people. The enzyme is intracellular in both bacteria and yeast, whereas for molds, it has an extracellular location. The present work was carried to utilize the whey for the production of β-galactosidase enzyme using both yeast and fungal cultures. The yeast isolate Kluyveromyces marxianus WIG2 and various fungal strains have been used in the present study. Different disruption techniques have also been investigated for the extraction of the enzyme produced intracellularly from yeast cells. Among the different methods tested for the disruption of yeast cells, SDS-chloroform showed the maximum β-galactosidase activity. In case of the tested fungal cultures, Aureobasidium pullulans NCIM 1050, was observed to be the maximum extracellular enzyme producer.

Keywords: β-galactosidase, fungus, yeast, whey

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Authors: Svetlana Ignatjeva, Jelena Slesareva

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The aim of the study is development and adaptation of the method to analyze and quantify the indicators characterizing the relationship between a company and its employees. Diagnostics of such indicators is one of the most complex and actual issues in psychology of labour. The offered method is based on the questionnaire; its indicators reflect cognitive, affective and connotative components of socio-psychological attitude of employees to be as efficient as possible in their professional activities. This approach allows measure not only the selected factors but also such parameters as cognitive and behavioural dissonances. Adaptation of the questionnaire includes factor structure analysis and suitability analysis of phenomena indicators measured in terms of internal consistency of individual factors. Structural validity of the questionnaire was tested by exploratory factor analysis. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor analysis allows reduce dimension of the phenomena moving from the indicators to aggregative indexes and latent variables. Aggregative indexes are obtained as the sum of relevant indicators followed by standardization. The coefficient Cronbach's Alpha was used to assess the reliability-consistency of the questionnaire items. The two-step cluster analysis in the space of allocated factors allows classify employees according to their attitude to work in the company. The results of psychometric testing indicate possibility of using the developed technique for the analysis of employees’ attitude towards their work in companies and development of recommendations on their optimization.

Keywords: involved in the organization, loyalty, organizations, method

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Authors: Monika Szymańska-Czerwińsk, Kinga Zaręba-Marchewka, Krzysztof Niemczuk

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Chlamydiaceae are Gram-negative bacteria distributed worldwide in animals and humans. One of them is Chlamydia gallinacea recently discovered. Available data show that C. gallinacea is dominant chlamydial agent found in poultry in European and Asian countries. The aim of the studies was screening of poultry flocks in order to evaluate frequency of C. gallinacea shedding and genetic diversity. Sampling was conducted in different regions of Poland in 2019-2020. Overall, 1466 cloacal/oral swabs were collected in duplicate from 146 apparently healthy poultry flocks including chickens, turkeys, ducks, geese and quails. Dry swabs were used for DNA extraction. DNA extracts were screened using a Chlamydiaceae 23S rRNA real-time PCR assay. To identify Chlamydia species, specific real-time PCR assays were performed. Furthermore, selected samples were used for sequencing based on ompA gene fragments and variable domains (VD1-2, VD3-4). In total, 10.3% of the tested flocks were Chlamydiaceae-positive (15/146 farms). The presence of Chlamydiaceae was confirmed mainly in chickens (13/92 farms) but also in turkey (1/19 farms) and goose (1/26 farms) flocks. Eleven flocks were identified as C. gallinacea-positive while four flocks remained unclassified. Phylogenetic analysis revealed at least 16 genetic variants of C. gallinacea. Research showed that Chlamydiaceae occur in a poultry flock in Poland. The strains of C. gallinacea as dominant species show genetic variability.

Keywords: C. gallinacea, emerging agent, poultry, real-time PCR

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Authors: M. Eckert, D. Mendes, J P. Gonçalves, C. Moço, M. Oliveira

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The intensive extraction of natural aggregates leads to both depletion of natural resources and unwanted environmental impacts. On the other hand, uncontrolled disposal of Construction and Demolition Wastes (C&DW) causes the lifetime reduction of landfills. It is known that the European Union produces, each year, about 850 million tons of C&DW. For all the member States of the European Union, one of the milestones to be reached by 2020, according to the Resource Efficiency Roadmap (COM (2011) 571) of the European Commission, is to recycle 70% of the C&DW. In this work, properties of different types of recycled C&DW aggregates and natural aggregates were compared. Assays were performed according to European Standards (EN 13285; EN 13242+A1; EN 12457-4; EN 12620; EN 13139) for the characterization of there: physical, mechanical and chemical properties. Not standardized tests such as water absorption over time, mass stability and post compaction sieve analysis were also carried out. The tested recycled C&DW aggregates were classified according to the requirements of the European Standards regarding there potential use in concrete, mortar, unbound layers of road pavements and embankments. The results of the physical and mechanical properties of recycled C&DW aggregates indicated, in general, lower quality properties when compared to natural aggregates, particularly, for concrete preparation and unbound layers of road pavements. The results of the chemical properties attested that the C&DW aggregates constitute no environmental risk. It was concluded that recycled aggregates produced from C&DW have the potential to be used in many applications.

Keywords: recycled aggregate, sustainability, aggregate properties, European Standard Classification

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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Authors: Ali Mirtaghavi, Andy Baldwin, Rajendarn Muthuraj, Jack Luo

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Recent advances in biomaterials have led to utilizing biopolymers to develop 3D scaffolds in tissue regeneration. One of the major challenges of designing biomaterials for 3D scaffolds is to mimic the building blocks similar to the extracellular matrix (ECM) of the native tissues. Biopolymer based aerogels obtained by freeze-drying have shown to provide structural similarities to the ECM owing to their 3D format and a highly porous structure with interconnected pores, similar to the ECM. Gelatin (GEL) is known to be a promising biomaterial with inherent regenerative characteristics owing to its chemical similarities to the ECM in native tissue, biocompatibility abundance, cost-effectiveness and accessible functional groups, which makes it facile for chemical modifications with other biomaterials to form biocomposites. Despite such advantages, gelatin offers poor mechanical properties, sensitive enzymatic degradation and high viscosity at room temperature which limits its application and encourages its use to develop biocomposites. Hydrophilic biomass-based cellulose nanofibrous (CNF) has been explored to use as suspension for biocomposite aerogels for the development of 3D porous structures with excellent mechanical properties, biocompatibility and slow enzymatic degradation. In this work, CNF biocomposite aerogels with various ratios of CNF:GEL) (90:10, 70:30 and 50:50) were prepared by freeze-drying technique, and their properties were investigated in terms of physicochemical, mechanical and biological characteristics. Epichlorohydrin (EPH) was used to investigate the effect of chemical crosslinking on the molecular interaction of CNF: GEL, and its effects on physicochemical, mechanical and biological properties of the biocomposite aerogels. Ultimately, chemical crosslinking helped to improve the mechanical resilience of the resulting aerogels. Amongst all the CNF-GEL composites, the crosslinked CNF: GEL (70:30) biocomposite was found to be favourable for cell attachment and viability. It possessed highly porous structure (porosity of ~93%) with pore sizes ranging from 16-110 µm, adequate mechanical properties (compression modulus of ~47 kPa) and optimal biocompatibility both in-vitro and in-vivo, as well as controlled enzymatic biodegradation, high water penetration, which could be considered a suitable option for wound healing application. In-vivo experiments showed improvement on inflammation and foreign giant body cell reaction for the crosslinked CNF: GEL (70:30) compared to the other samples. This could be due to the superior interaction of CNF with gelatin through chemical crosslinking, resulting in more optimal in-vivo improvement. In-vitro cell culture investigation on human dermal fibroblasts showed satisfactory 3D cell attachment over time. Overall, it has been observed that the developed CNF: GEL aerogel can be considered as a potential scaffold for soft tissue regeneration application.

Keywords: 3D scaffolds, aerogels, Biocomposites , tissue engineering

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Authors: V. C. Santos-Ebinuma, J. F. B. Pereira, M. F. S. Teixeira, A. Pessoa Jr., P. Jauregi

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There is worldwide interest in process development for colorants production from natural sources. Microorganisms provide an alternative source of natural colorants which can be produced by cultivation technology and extracted from fermented broth. The aim of the present work was to study the recovery of red colorants from fermented broth of Penicillium purpurogenum DPUA 1275 using the technique of Colloidal Gas Aphrons (CGA); CGA are surfactant-stabilized microbubbles generated by intense stirring of a surfactant solution. CGA were generated by the cationic, hexadecyl trimethyl ammonium bromide (CTAB) surfactant. Firstly, experiments were carried out at different surfactant/fermented broth volumetric ratios (VCGA/VFB, VRATIO) varying between 3 and 18 at pH 6.9. Secondly, the experiments were carried out at VRATIO of 6 and 12 in different pH, namely, 6.9, 8.0, 9.0 and 10.0. The first results of recovery showed that an increase in the VRATIO from 3 to 6 and 12 promoted an increase as recovery as partition coefficient. However, at VRATIO of 18 the lowest partition coefficient was obtained. The best results were achieved at VRATIO of 6 and 12, namely recovery, Re, around 60% and partition coefficient, K, of 2.5 and 3.0 to 6 and 12 VRATIO, respectively. The second set of experiments showed that the pH 9.0 promoted the best results at VRATIO of 12 as follow: Re=70%, K=5.39, proteins and sugar selectivity (SePROT, 3.75 and SeSUGAR, 7.20, respectively). These results indicate that with CTAB the recovery is mainly driven by electrostatic interactions. In conclusion, the results above show that CGA employing a cationic surfactant is a promissory technique and it can be used as the first step of purification to recovery red colorants from fermented broth.

Keywords: liquid-liquid extraction, colloidal gas aphrons, recovery, natural colorants

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Authors: Hao Wang, Shengchun Wang, Weidong Wang

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On the influence of train vibration and environmental noise on the measurement of track wear, we proposed a method for automatic extraction of circular arc on the inner or outer side of the rail waist and achieved the high-precision registration of rail profile. Firstly, a polynomial fitting method based on truncated residual histogram was proposed to find the optimal fitting curve of the profile and reduce the influence of noise on profile curve fitting. Then, based on the curvature distribution characteristics of the fitting curve, the interval search algorithm based on dynamic window’s maximum curvature entropy was proposed to realize the automatic segmentation of small circular arc. At last, we fit two circle centers as matching reference points based on small circular arcs on both sides and realized the alignment from the measured profile to the standard designed profile. The static experimental results show that the mean and standard deviation of the method are controlled within 0.01mm with small measurement errors and high repeatability. The dynamic test also verified the repeatability of the method in the train-running environment, and the dynamic measurement deviation of rail wear is within 0.2mm with high repeatability.

Keywords: curvature entropy, profile registration, rail wear, structured light, train-running

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Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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Authors: Emma Carr, Jennifer Morrison, Peter Walker

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Background: Due to COVID-19, there was a significant reduction in the number of children being treated under general anaesthetic (GA) within the health board, which led to a backlog of referrals. The referrals were being triaged and added to a waiting list in order of priority -determined by the information given. By implementing a checklist, it is anticipated that at least 70% of referrals will have the majority of the information required to effectively prioritise patients. The gold standard, as defined in ‘Guidelines For The Management Of Children Referred For Dental Extractions Under General Anaesthesia’, indicates that all referrals should mention: (i) Inability of the child to cooperate, (ii) Previously tried anxiety management techniques, (iii) Existence of psychological disorders, (iv) Presence of acute dental infection, (v) Requirement for extractions in multiple quadrants. Method: 130 referrals were examined over three months and compared to the recommended standard. A letter was emailed to referring dentists within Ayrshire & Arran outlining the recommended information to be included within the referral. The second round of data collection was then carried out, which involved an examination of 105 referrals. Results: The first round revealed that only 28% of referrals mentioned at least four defined standards outlined above. Following issuing a checklist to all dentists, this increased to 72%. Conclusion: As many of the children referred for extractions under GA have suffered pain and infection because of dental caries, it is important that delay of treatment is minimised, where possible. The implementation of a standardised checklist has enabled more effective prioritisation of patients.

Keywords: caries, dentistry, general anaesthetic, paediatrics

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: Babak Azari, Afshin Pourahmad, Babak Sadeghi, Masuod Mokhtari

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In this work, Equisetnm arvense plant extract was used for preparing amorphous SiO₂. For preparing of SiO₂/zeolitic imidazolate framework-8 (ZIF-8) nanocomposite by solvothermal method, the synthesized SiO₂ was added to the synthesis mixture ZIF-8. The nanocomposite was characterized using a range of techniques. The photocatalytic activity of SiO₂/ZIF-8 was investigated systematically by degrading crystal violet as a cationic dye under Ultraviolet light irradiation. Among synthesized samples (SiO₂, ZIF-8 and SiO₂/ZIF-8), the SiO₂/ZIF-8 exhibited the highest photocatalytic activity and improved stability compared to pure SiO₂ and ZIF-8. As evidenced by Scanning Electron Microscopy and Transmission electron microscopy images, ZIF-8 particles without aggregation are located over SiO₂. The SiO₂ not only provides structured support for ZIF-8 but also prevents the aggregation of ZIF-8 Metal-organic framework in comparison to the isolated ZIF-8. The superior activity of this photocatalyst was attributed to the synergistic effects from SiO₂ owing to (I) an electron acceptor (from ZIF-8) and an electron donor (to O₂ molecules), (II) preventing recombination of electron-hole in ZIF-8, and (III) maximum interfacial contact ZIF-8 with the SiO₂ surface without aggregation or prevent the accumulation of ZIF-8. The results demonstrate that holes (h+) and •O₂- are primary reactive species involved in the photocatalytic oxidation process. Moreover, the SiO₂/ZIF-8 photocatalyst did not show any obvious loss of photocatalytic activity during five-cycle tests, which indicates that the heterostructured photocatalyst was highly stable and could be used repeatedly.

Keywords: nano, zeolit, potocatalist, nanocomposite

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Authors: Nastaran Hemmati, Farhad Nikkhahi, Amir Javadi, Sahar Eskandarion, Seyed Mahmuod Amin Marashi

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Neisseria meningitidis, Escherichia coli K, Streptococcus agalactiae, and Streptococcus pneumoniae cause 90% of bacterial meningitis. Almost all infected people die or have irreversible neurological complications. Therefore, it is essential to have a diagnostic kit with the ability to quickly detect these fatal infections. The project involved 212 patients from whom cerebrospinal fluid samples were obtained. After total genome extraction and performing multiplex quantitative polymerase chain reaction (qPCR), the presence or absence of each infectious factor was determined by comparing with standard strains. The specificity, sensitivity, positive predictive value, and negative predictive value calculated were 100%, 92.9%, 50%, and 100%, respectively. So, due to the high specificity and sensitivity of the designed primers, they can be used instead of bacterial culture that takes at least 24 to 48 hours. The remarkable benefit of this method is associated with the speed (up to 3 hours) at which the procedure could be completed. It is also worth noting that this method can reduce the personnel unintentional errors which may occur in the laboratory. On the other hand, as this method simultaneously identifies four common factors that cause bacterial meningitis, it could be used as an auxiliary method diagnostic technique in laboratories particularly in cases of emergency medicine.

Keywords: cerebrospinal fluid, meningitis, quantitative polymerase chain reaction, simultaneous detection, diagnosis testing

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Authors: Anjana Sagar

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Arsenic poisoned ground water is a major concern in South Asia. The arsenic enters the food chain not only through drinking but also by using arsenic polluted water for irrigation. Arsenic is highly toxic in its inorganic forms; however, organic forms of arsenic are comparatively less toxic. In terrestrial plants, inorganic form of arsenic is predominantly found; however, we found that significant proportion of organic arsenic was present in root and shoot of a staple legume, chickpea (Cicer arientinum L) plants. Chickpea plants were raised in pot culture on soils spiked with arsenic ranging from 0-70 mg arsenate per Kg soil. Total arsenic concentrations of chickpea shoots and roots were determined by inductively coupled plasma-mass-spectrometry (ICP-MS) ranging from 0.76 to 20.26, and 2.09 to 16.43 µg g⁻¹ dry weight, respectively. Information on arsenic species was acquired by methanol/water extraction method, with arsenic species being analyzed by high-performance liquid chromatography (HPLC) coupled with ICP-MS. Dimethylarsinic acid (DMA) was the only organic arsenic species found in amount from 0.02 to 3.16 % of total arsenic shoot concentration and 0 to 6.93 % of total arsenic root concentration, respectively. To investigate the source of the organic arsenic in chickpea plants, arsenic species in the rhizosphere of soils of plants were also examined. The absence of organic arsenic in soils would suggest the possibility of formation of DMA in plants. The present investigation provides useful information for better understanding of distribution of arsenic species in terrestrial legume plants.

Keywords: arsenic, arsenic speciation, dimethylarsinic acid, organoarsenic

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Authors: Mohammad Hajjartabar, Tahereh Kermani Ranjbar

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P. aeruginosa EF2 was isolated and identified from human infection sources before in our previous study. The present study was performed to determine the characteristics and activity role of bioflocculant produced by the bacterium in flocculation of the wastewater active sludge treatment. The bacterium was inoculated and then was grown in an orbital shaker at 250 rpm for 5 days at 35 °C under TSB and peptone water media. After incubation period, culture broths of the bacterial strain was collected and washed. The concentration of the bacteria was adjusted. For the extraction of the bacterial bioflocculant, culture was centrifuged at 6000 rpm for 20 min at 4 °C to remove bacterial cells. Supernatant was decanted and pellet containing bioflocculant was dried at 105 °C to a constant weight according to APHA, 2005. The chemical composition of the extracted bioflocculant from the bacterial sample was then analyzed. Wastewater active sludge sample obtained from aeration tank from one of wastewater treatment plants in Tehran, was first mixed thoroughly. After addition of bioflocculant, improvements in floc density were observed with an increase in bioflocculant. The results of this study strongly suggested that the extracted bioflucculant played a significant role in flocculation of the wastewater sample. The use of wild bacteria and nutrient regulation techniques instead of genetic manipulation opens wide investigation area in the future to improve wastewater treatment processes. Also this may put a new path in front of us to attain and improve the more effective bioflocculant using the purified microbial culture in wastewater treatment.

Keywords: wastewater treatment, P. aeruginosa, sludge treatment

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Authors: Ritesh K. Shukla

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Degradation of biological samples in terms of macromolecules (DNA, RNA, and protein) are the major challenges in the forensic investigation which misleads the result interpretation. Currently, there are no precise methods available to circumvent this problem. Therefore, at the preliminary level, some methods are urgently needed to solve this issue. In this order, Comet assay is one of the most versatile, rapid and sensitive molecular biology technique to assess the DNA degradation. This technique helps to assess DNA degradation even at very low amount of sample. Moreover, the expedient part of this method does not require any additional process of DNA extraction and isolation during DNA degradation assessment. Samples directly embedded on agarose pre-coated microscopic slide and electrophoresis perform on the same slide after lysis step. After electrophoresis microscopic slide stained by DNA binding dye and observed under fluorescent microscope equipped with Komet software. With the help of this technique extent of DNA degradation can be assessed which can help to screen the sample before DNA fingerprinting, whether it is appropriate for DNA analysis or not. This technique not only helps to assess degradation of DNA but many other challenges in forensic investigation such as time since deposition estimation of biological fluids, repair of genetic material from degraded biological sample and early time since death estimation could also be resolved. With the help of this study, an attempt was made to explore the application of well-known molecular biology technique that is Comet assay in the field of forensic science. This assay will open avenue in the field of forensic research and development.

Keywords: comet assay, DNA degradation, forensic, molecular biology

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Authors: A. Degale Desta, Cheng Jian

Abstract:

Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

Abstract:

Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

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Authors: Chayan Gupta, Arun Prasad

Abstract:

The quick evolution of industrialization causes the scarcity of precious land. Thus, it is vital need to influence the R&D societies to achieve sustainable, economic and social benefits from huge utilization of waste for universal aids. The current study promotes the influence of steel industries waste i.e. ground granulated blast furnace slag (GGBS) in geotechnical properties of jarosite waste (solid waste residues produced from hydrometallurgy operations involved in extraction of Zinc). Numerous strengths tests (unconfined compression (qu) and splitting tensile strength (qt)) are conducted on jarosite-GGBS blends (GGBS, 10-30%) with different curing periods (7, 28 & 90 days). The results indicate that both qu and qt increase with the increase in GGBS content along with curing periods. The increased strength with the addition of GGBS is also observed from microstructural study, which illustrates the occurrence of larger agglomeration of jarosite-GGBS blend particles. The Freezing-Thawing (F-T) durability analysis is also conducted for all the jarosite-GGBS blends and found that the reduction in unconfined compressive strength after five successive F-T cycles enhanced from 62% (natural jarosite) to 48, 42 and 34% at 7, 14 and 28 days curing periods respectively for stabilized jarosite-GGBS samples containing 30% GGBS content. It can be concluded from this study that blending of cementing additives (GGBS) with jarosite waste resulted in a significant improvement in geotechnical characteristics.

Keywords: jarosite, GGBS, strength characteristics, microstructural study, durability analysis

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Authors: Senem Suna, Canan Ece Tamer, Ömer Utku Çopur

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In this research, dried linden (Tilia argentea) leaves and blossoms were used as a raw material for mineral enriched herbal tea beverage production. For this aim, %1 dried linden was infused with boiling water (100 °C) for 5 minutes. After cooling, sucrose, citric acid, ascorbic acid, natural lemon flavor and natural mineral water were added. Beverage samples were plate filtered, filled into 200-mL glass bottles, capped then pasteurized at 98 °C for 15 minutes. Water soluble dry matter, titratable acidity, ascorbic acid, pH, minerals (Fe, Ca, Mg, K, Na), color (L*, a*, b*), turbidity, bioaccessible phenolics and antioxidant capacity were analyzed. Water soluble dry matter, titratable acidity, and ascorbic were determined as 7.66±0.28 g/100 g, 0.13±0.00 g/100 mL, and 19.42±0.62 mg/100 mL, respectively. pH was measured as 3.69. Fe, Ca, Mg, K and Na contents of the beverage were determined as 0.12±0.00, 115.48±0.05, 34.72±0.14, 48.67±0.43 and 85.72±1.01 mg/L, respectively. Color was measured as 13.63±0.05, -4.33±0.05, and 3.06±0.05 for L*, a*, and b* values. Turbidity was determined as 0.69±0.07 NTU. Bioaccessible phenolics were determined as 312.82±5.91 mg GAE/100 mL. Antioxidant capacities of chemical (MetOH:H₂O:HCl) and physiological extracts (in vitro digestive enzymatic extraction) with DPPH (27.59±0.53 and 0.17±0.02 μmol trolox/mL), FRAP (21.01±0.97 and 13.27±0.19 μmol trolox/mL) and CUPRAC (44.71±9.42 and 2.80±0.64 μmol trolox/mL) methods were also evaluated. As a result, enrichment with natural mineral water was proposed for the development of functional and nutritional values together with a good potential for commercialization.

Keywords: linden, herbal tea beverage, bioaccessibility, antioxidant capacity

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Authors: Othman Elmahdy Othman

Abstract:

The objectives of this study were to identify polymorphisms in the STAT5A using Restriction Fragment Length Polymorphism and DGAT1 using Single-Strand Conformation Polymorphism genes among three Egyptian goat breeds (Barki, Zaraibi, and Damascus) as well as investigate the effect of their genotypes on milk composition traits of Zaraibi goats. One hundred and fifty blood samples were collected for DNA extraction, 60 from Zaraibi, 40 from Damascus and 50 from Barki breeds. Fat, protein and lactose percentages were determined in Zaraibi goat milk using an automatic milk analyzer. Two genotypes, CC and CT (for STAT5A) and C-C- and C-C+ (for DGAT1), were identified in the three Egyptian goat breeds with different frequencies. The associations between these genotypes and milk fat, protein and lactose were determined in Zaraibi breed. The results showed that the STAT5A genotypes had significant effects on milk yield, protein, fat and lactose with the superiority of CT genotype over CC. Regarding DGAT1 polymorphism, the result showed the only association between it with milk fat where the animals with C-C+ genotype had greater milk fat than animals possess C-C- genotype. The association of combined genotypes with milk trait declared that the does with heterozygous genotypes for both genes are preferred than does with homozygous genotypes where the animals with CTC-C+ have more milk yield, fat and protein than those with CCC-C- genotype. In conclusion, the result showed that C/T and C-/C+ SNPs of STAT5A and DGAT1 genes respectively may be useful markers for assisted selection programs to improve goat milk composition

Keywords: DGAT1, genetic polymorphism, milk trait, STAT5A

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Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

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This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

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Authors: M. I. Tyletc, O. I. Podgornya, T. G. Shaposhnikova, S. V. Shabelnikov, A. G. Mittenberg, M. A. Daugavet

Abstract:

Ascidiacea is the most numerous class of the Tunicata subtype. These chordates' distinctive feature of the anatomical structure is a tunic consisting of cellulose fibrils, protein molecules, and single cells. The mechanisms of the tunic formation are not known in detail; tunic formation could be used as the model system for studying the interaction of cells with the extracellular matrix. Our model species is the ascidian Styela rustica, which is prevalent in benthic communities of the White Sea. As previously shown, the tunic formation involves morula blood cells, which contain the major 48 kDa protein p48. P48 participation in the tunic formation was proved using antibodies against the protein. The nature of the protein and its function remains unknown. The current research aims to determine the amino acid sequence of p48, as well as to clarify its role in the tunic formation. The peptides that make up the p48 amino acid sequence were determined by mass spectrometry. A search for peptides in protein sequence databases identified sequences homologous to p48 in Styela clava, Styela plicata, and Styela canopus. Based on sequence alignment, their level of similarity was determined as 81-87%. The correspondent sequence of ascidian Styela canopus was used for further analysis. The Styela rustica p48 sequence begins with a signal peptide, which could indicate that the protein is secretory. This is consistent with experimentally obtained data: the contents of morula cells secreted in the tunic matrix. The isoelectric point of p48 is 9.77, which is consistent with the experimental results of acid electrophoresis of morula cell proteins. However, the molecular weight of the amino acid sequence of ascidian Styela canopus is 103 kDa, so p48 of Styela rustica is a shorter homolog. The search for conservative functional domains revealed the presence of two Ca-binding EGF-like domains, thrombospondin (TSP1) and tyrosinase domains. The p48 peptides determined by mass spectrometry fall into the region of the sequence corresponding to the last two domains and have amino acid substitutions as compared to Styela canopus homolog. The tyrosinase domain (pfam00264) is known to be part of the phenoloxidase enzyme, which participates in melanization processes and the immune response. The thrombospondin domain (smart00209) interacts with a wide range of proteins, and is involved in several biological processes, including coagulation, cell adhesion, modulation of intercellular and cell-matrix interactions, angiogenesis, wound healing and tissue remodeling. It can be assumed that the tyrosinase domain in p48 plays the role of the phenoloxidase enzyme, and TSP1 provides a link between the extracellular matrix and cell surface receptors, and may also be responsible for the repair of the tunic. The results obtained are consistent with experimental data on p48. The domain organization of protein suggests that p48 is an enzyme involved in the tunic tunning and is an important regulator of the organization of the extracellular matrix.

Keywords: ascidian, p48, thrombospondin, tyrosinase, tunic, tunning

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Authors: Alicja Kot-Niewiadomska

Abstract:

Securing sustainable access to raw materials is vital for the growth of the European economy and for the goals laid down in Strategy Europe 2020. One of the most important sources of mineral raw materials are primary deposits. The efficient management of them, including extraction, will ensure competitiveness of the European economy. A critical element of this approach is mineral deposits safeguarding and the most important tool - spatial planning. The safeguarding of deposits should be understood as safeguarding of land access, and safeguarding of area against development, which may (potential) prevent the use of the deposit and the necessary mining activities. Many European Union countries successfully integrated their mineral policy and spatial policy, which has ensured the proper place of mineral deposits in their spatial planning systems. These, in turn, are widely recognized as the most important mineral deposit safeguarding tool, the essence of which is to ensure long-term access to its resources. The examples of Austria, Portugal, Slovakia, Czech Republic, Sweden, and the United Kingdom, discussed in the paper, are often mentioned as examples of good practices in this area. Although none of these countries managed to avoid cases of social and environmental conflicts related to mining activities, the solutions they implement certainly deserve special attention. And for many countries, including Poland, they can be a potential source of solutions aimed at improving the protection of mineral deposits.

Keywords: mineral deposits, land use planning, mineral deposit safeguarding, European practices

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