Search results for: peak detection

Authors: Jason Blair, Adeboye Adebayo, Mohamed Saad, Jeannette M. Byrne, Fabien A. Basset

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Running economy is a key physiological parameter of an individual’s running efficacy and a valid tool for predicting performance outcomes. Of the many factors known to influence running economy (RE), footwear certainly plays a role owing to its characteristics that vary substantially from model to model. Although minimalist footwear is believed to enhance RE and thereby endurance performance, conclusive research reports are scarce. Indeed, debates remain as to which footwear characteristics most alter RE. The purposes of this study were, therefore, two-fold: (a) to determine whether wearing minimalist shoes results in better RE compared to shod and to identify relationships with kinematic and muscle activation patterns; (b) to determine whether changes in RE with minimalist shoes are still evident following a fatiguing bout of exercise. Well-trained male distance runners (n=10; 29.0 ± 7.5 yrs; 71.0 ± 4.8 kg; 176.3 ± 6.5 cm) partook first in a maximal O₂ uptake determination test (VO₂ₘₐₓ = 61.6 ± 7.3 ml min⁻¹ kg⁻¹) 7 days prior to the experimental sessions. Second, in a fully randomized fashion, an RE test consisting of three 8-min treadmill runs in shod and minimalist footwear were performed prior to and following exercise induced fatigue (EIF). The minimalist and shod conditions were tested with a minimum of 7-day wash-out period between conditions. The RE bouts, interspaced by 2-min rest periods, were run at 2.79, 3.33, and 3.89 m s⁻¹ with a 1% grade. EIF consisted of 7 times 1000 m at 94-97% VO₂ₘₐₓ interspaced with 3-min recovery. Cardiorespiratory, electromyography (EMG), kinematics, rate of perceived exertion (RPE) and blood lactate were measured throughout the experimental sessions. A significant main speed effect on RE (p=0.001) and stride frequency (SF) (p=0.001) was observed. The pairwise comparisons showed that running at 2.79 m s⁻¹ was less economic compared to 3.33, and 3.89 m s⁻¹ (3.56 ± 0.38, 3.41 ± 0.45, 3.40 ± 0.45 ml O₂ kg⁻¹ km⁻¹; respectively) and that SF increased as a function of speed (79 ± 5, 82 ± 5, 84 ± 5 strides min⁻¹). Further, EMG analyses revealed that root mean square EMG significantly increased as a function of speed for all muscles (Biceps femoris, Gluteus maximus, Gastrocnemius, Tibialis anterior, Vastus lateralis). During EIF, the statistical analysis revealed a significant main effect of time on lactate production (from 2.7 ± 5.7 to 11.2 ± 6.2 mmol L⁻¹), RPE scores (from 7.6 ± 4.0 to 18.4 ± 2.7) and peak HR (from 171 ± 30 to 181 ± 20 bpm), expect for the recovery period. Surprisingly, a significant main footwear effect was observed on running speed during intervals (p=0.041). Participants ran faster with minimalist shoes compared to shod (3:24 ± 0:44 min [95%CI: 3:14-3:34] vs. 3:30 ± 0:47 min [95%CI: 3:19-3:41]). Although EIF altered lactate production and RPE scores, no other effect was noticeable on RE, EMG, and SF pre- and post-EIF, except for the expected speed effect. The significant footwear effect on running speed during EIF was unforeseen but could be due to shoe mass and/or heel-toe-drop differences. We also cannot discard the effect of speed on foot-strike pattern and therefore, running performance.

Keywords: exercise-induced fatigue, interval training, minimalist footwear, running economy

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Authors: Amita Jain, Shantanu Prakash, Suruchi Shukla

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Introduction: Acute encephalitis syndrome (AES) is a complex multi etiology syndrome posing a great public health problem in the northern part of India. Japanese encephalitis (JE) virus is an established etiology of AES in this region. Recently, Scrub typhus (ST) is being recognized as an emerging aetiology of AES in JE endemic belt. This study was conducted to establish the direct evidence of Central nervous system invasion by Orientia tsutsugamushi leading to AES. Methodology: A total of 849 cases with clinical diagnosis of AES were enrolled from six districts (Deoria and its adjoining area) of the traditional north Indian Japanese encephalitis (JE) belt. Serum and Cerebrospinal fluid samples were collected and tested for major agent causing acute encephalitis. AES cases either positive for anti-ST IgM antibodies or negative for all tested etiologies were investigated for ST-DNA by real-time PCR. Results: Of these 505 cases, 250 patients were laboratory confirmed for O. tsutsugamushi infection either by anti-ST IgM antibodies positivity (n=206) on serum sample or by ST-DNA detection by real-time PCR assay on CSF sample (n=2) or by both (n=42).Total 29 isolate could be sequenced for 56KDa gene. Conclusion: All the strains were found to cluster with Gilliam strains. The majority of the isolates showed a 97–99% sequence similarity with Thailand and Cambodian strains. Gilliam strain of O.tsusugamushi is an emerging as one of the major aetiologies leading to AES in northern part of India.

Keywords: acute encephalitis syndrome, O. tsutsugamushi, Gilliam strain, North India, cerebrospinal fluid

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Authors: Saule Mussabekova

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Forensic investigation of human teeth plays an important role in detection of crime, particularly in cases of personal identification of dead bodies changed by putrefactive processes or skeletonized bodies as well as when finding bodies of unknown persons. 152 teeth have been investigated; 85 of them belonged to men and 67 belonged to women taken from alive people of different age. Teeth have been investigated after extraction. Two types of teeth have been investigated: teeth without integrity violation of dental crown and teeth with different degrees of its violation. Additionally, 517 teeth have been investigated that were collected from dead bodies, 252 of which belonged to women and 265 belonged to men, whatever the cause of death with death limitation from 1 month to 20 years. Isohemagglutinating serums and Coliclons of different series have been used for the research of tooth-group specificity by serological methods according to the AB0 system. Standard protocols of different techniques have been used for DNA purification from teeth (by reagent Chelex 100 produced by Bio-Rad using reagent kit 'DNA IQTM System' produced by Promega company (USA) and using columns 'QIAamp DNA Investigator Kit' produced by Qiagen company). Results of comparative forensic investigation of human teeth using serological and molecular genetic methods have shown that use of serological methods for forensic identification is sensible only in cases of preselection prior to the next molecular genetic investigation as well as in cases of impossibility of corresponding genetic investigation for different objective reasons. A number of advantages of methods of molecular genetics in the dental investigation have been marked, particularly in putrefactive changes, in personal identification. Key moments of modern condition of personal identification have been reflected according to dental state. Prospective directions of advance preparation of material have been emphasized for identification of teeth in forensic practice.

Keywords: dental state, forensic identification, molecular genetic analysis, teeth

Procedia PDF Downloads 141

Authors: Eman M. Morgan, Hayam M. Lotfy, Yasmin M. Fayez, Mohamed Abdelkawy, Engy Shokry

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Two simple, selective, economic, safe, accurate, precise and environmentally friendly methods were developed and validated for the quantitative determination of valaciclovir (VAL) in the presence of its related substances R1 (acyclovir), R2 (guanine) in bulk powder and in the commercial pharmaceutical product containing the drug. Method A is a colorimetric method where VAL selectively reacts with ferric hydroxamate and the developed color was measured at 490 nm over a concentration range of 0.4-2 mg/mL with percentage recovery 100.05 ± 0.58 and correlation coefficient 0.9999. Method B is a reversed phase ultra performance liquid chromatographic technique (UPLC) which is considered superior in technology to the high-performance liquid chromatography with respect to speed, resolution, solvent consumption, time, and cost of analysis. Efficient separation was achieved on Agilent Zorbax CN column using ammonium acetate (0.1%) and acetonitrile as a mobile phase in a linear gradient program. Elution time for the separation was less than 5 min and ultraviolet detection was carried out at 256 nm over a concentration range of 2-50 μg/mL with mean percentage recovery 100.11±0.55 and correlation coefficient 0.9999. The proposed methods were fully validated as per International Conference on Harmonization specifications and effectively applied for the analysis of valaciclovir in pure form and tablets dosage form. Statistical comparison of the results obtained by the proposed and official or reported methods revealed no significant difference in the performance of these methods regarding the accuracy and precision respectively.

Keywords: hydroxamic acid, related substances, UPLC, valaciclovir

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Authors: Bhavana Gulaty, Arshia Chaudhri

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Great civic projects contribute integrally to a city, and every city undergoes a recurring cycle of urban transformations and regeneration by their insertion. The M.I.C.E. (Meetings, Incentives, Convention and Exhibitions) industry is the forbearer of one category of such catalytic civic projects. Through a specific focus on M.I.C.E. destinations, this paper illustrates the multifarious dimensions that urban catalysts impact the city on S.P.U.R. (Seed. Profile. Urbane. Reflections), the theoretical framework of this paper aims to unearth these dimensions in the realm of the COEX (Convention & Exhibition) biosphere. The ‘COEX Biosphere’ is the filter of such catalysts being ecosystems unto themselves. Like a ripple in water, the impact of these strategic interventions focusing on art, culture, trade, and promotion expands right from the trigger; the immediate context to the region and subsequently impacts the global scale. These ripples are known to bring about significant economic, social, and political and network changes. The COEX inventory in the Asian context has one such prominent addition; the proposed India International Convention and Exhibition Centre (IICC) at New Delhi. It is envisioned to be the largest facility in Asia currently and would position India on the global M.I.C.E map. With the first phase of the project scheduled to open for use in the end of 2019, this flagship project of the Government of India is projected to cater to a peak daily footfall of 3,20,000 visitors and estimated to generate 5,00,000 jobs. While the economic benefits are yet to manifest in real time and ‘Good design is good business’ holds true, for the urban transformation to be meaningful, the benefits have to go beyond just a balance sheet for the city’s exchequer. This aspect has been found relatively unexplored in research on these developments. The methodology for investigation will comprise of two steps. The first will be establishing an inventory of the global success stories and associated benefits of COEX projects over the past decade. The rationale for capping the timeframe is the significant paradigm shift that has been observed in their recent conceptualization; for instance ‘Innovation Districts’ conceptualised in the city of Albuquerque that converges into the global economy. The second step would entail a comparative benchmarking of the projected transformations by IICC through a toolkit of parameters. This is posited to yield a matrix that can form the test bed for mapping the catalytic trajectory for projects in the pipeline globally. As a ready reckoner, it purports to be a catalyst to substantiate decision making in the planning stage itself for future projects in similar contexts.

Keywords: catalysts, COEX, M.I.C.E., urban transformations

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Authors: Abdul Kadir, L. Meily Kurniawidjaja

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Batik Madura workers are exposed to many Musculoskeletal Disorders risk factors, particularly Low Back Pain (LBP). This study was conducted as an early detection of ergonomic risk level on Workers Industrial Sentra Batik Madura in Dusun Banyumas, Klampar Subdistrict, Proppo Pamekasan, Madura, East Java. This study includes 12 workers who 11 workers had pain in the upper and lower part of the neck, back, wrist right hand, also 10 workers had pain in the right shoulder. This is a descriptive observational study with cross-sectional approach. Qualitative research by observing workers activity such as draw and putting the wax motif, fabric dyeing, fabric painting, discoloration, washing, and drying. The results are workers have identified ergonomic hazards such as awkward postures, twisting movements, repetitive, and static work postures. Using the method of REBA and QEC, the results get a very high-risk level of activity in each of Madura batik making process is the draw and putting the wax motif, coloring, painting, discoloration, washing, and drying. The level of risk can be reduced by improvement of work equipment include the provision of seats, strut fabric, high settings furnaces, drums, coloring basin, and washing tub.

Keywords: activities of Madura's batik, ergonomic risk level, equipment, QEC (Quick Exposure Checklist), REBA (Rapid Entire Body Assessment)

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Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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Authors: Mahmoud M. S. Farrag, Alaa A. K. Elhaweet, El-Sayed Kh. A. Akel, Mohsen A. Moustafa

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The present work aimed to study the reproductive strategy of the common lessepsian puffer fish Lagocephalus sceleratus (Gmelin, 1879) from the Egyptian Mediterranean Waters. It is a famous migratory species plays an important role in the field of fisheries and ecology of aquatic ecosystem. The specimens were collected monthly from the landing centers along the Egyptian Mediterranean coast during 2012. Six maturity stages were recorded: (I) Thread like stage, (II) Immature stage (Virgin stage), (III) Maturing stage (Developing Virgin and recovering spent), (IV) Nearly ripe stage, (V) Fully ripe, (VI) Spawning stage, (VII) Spent stage. According to sex ratio, males exhibited higher number than females representing 52.44 % of the total fishes with sex ratio 1: 0.91. Fish length corresponding to 50% maturation was 38.5 cm for males and 41 cm for females. The corresponding ages (age at first maturity) are equal to 2.14 and 2.27 years for male and female respectively. The ova diameter ranged from 0.02mm to 0.85mm, the mature ova ranged from 0.16mm to 0.85mm and showed progressive increase from April towards September. Also, the presences of ova diameter in one peak of mature and ripe eggs in the ovaries were observed during spawning period. The relationship between gutted weight and absolute fecundity indicated that that fecundity increased as the fish grew in weight. The absolute fecundity ranged from 260288 to 2372931 for fish weight ranged from 698 to 3285 cm with an average of 1449522±720975. The relative fecundity ranged from 373 to 722 for fish weight ranged from 698 to 3285 cm with an average of 776±231. The spawning season of L. sceleratus was investigated from the data of gonado-somatic index and monthly distribution of maturity stages along the year as well as sequence of ova diameter for mature stages and exhibited a relatively prolong spawning season extending from April for both sexes and ends in August for male while ends in September for female. Fish releases its ripe ova in one batch during the spawning season. Histologically, the ovarian cycle of L. sceleratus was classified into six stages and the testicular cycle into five stages. Histological characters of gonads of L. sceleratus during the year of study had confirmed the previous results of distribution of maturity stages, gonado-somatic index and ova diameter, indicating this fish species has prolonged spawning season from April to September. This species is considered totally or uni spawner with synchronous group as it contained one to two developmental stages at the same gonad.

Keywords: Lagocephalus sceleratus, reproductive biology, oogenesis, histology

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Authors: Estefania Ponce-Amaya, Ana Lidia Arellano-Ortiz, Cecilia Diaz-Hernandez, Jose Alberto Lopez-Diaz, Antonio De La Mora-Covarrubias, Claudia Lucia Vargas-Requena, Mauricio Salcedo-Vargas, Florinda Jimenez-Vega

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Cervical Cancer (CC) is the second leading cause of death among women worldwide and it had been associated with a persistent infection of human papillomavirus (HPV). The goal of the current study was to identify the prevalence of HPV infection in women with abnormal Pap smear who were attended at Dysplasia Clinic of Ciudad Juarez, Mexico. Methods: Cervical samples from 146 patients, who attended the Colposcopy Clinic at Sanitary Jurisdiction II of Cd Juarez, were collected for histopathology and molecular study. DNA was isolated for the HPV detection by Polymerase Chain Reaction (PCR) using MY09/011 and GP5/6 primers. The associated risk factors were assessed by a questionnaire. The statistical analysis was performed by ANOVA, using EpiINFO V7 software. Results: HPV infection was present in 142 patients (97.3 %). The prevalence of HPV infection was distributed in a 96% of all evaluated groups, low-grade squamous intraepithelial lesion (LSIL), high-grade squamous intraepithelial lesion (HISIL) and CC. We found a statistical significance (α = <0.05) between gestation and number of births as risk factors. The median values showed an ascending tend according with the lesion progression. However, CC showed a statistically significant difference with respect to the pre-carcinogenic stages. Conclusions: In these Mexican patients exists a high prevalence of HPV infection, and for that reason, we are studying the most prevalent HPV genotypes in this population.

Keywords: cervical cancer, HPV, prevalence hpv, squamous intraepithelial lesion

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Authors: M. Kowalski, M. Brodowski, K. Dziabowska, E. Czaczyk, W. Bialobrzeska, N. Malinowska, S. Zoledowska, R. Bogdanowicz, D. Nidzworski

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Boron-doped-carbon nanowall (BCNW) electrodes are recently in much interest among scientists. BCNWs are good candidates for biosensor purposes as they possess interesting electrochemical characteristics like a wide potential range and the low difference between redox peaks. Moreover, from technical parameters, they are mechanically resistant and very tough. The production process of the microwave plasma-enhanced chemical vapor deposition (MPECVD) allows boron to build into the structure of the diamond being formed. The effect is the formation of flat, long structures with sharp ends. The potential of these electrodes was checked in the biosensing field. The procedure of simple carbon electrodes modification by antibodies was adopted to BCNW for specific antigen recognition. Surface protein D deriving from H. influenzae pathogenic bacteria was chosen as a target analyte. The electrode was first modified with the aminobenzoic acid diazonium salt by electrografting (electrochemical reduction), next anti-protein D antibodies were linked via 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride/N-hydroxysuccinimide (EDC/NHS) chemistry, and free sites were blocked by BSA. Cyclic voltammetry measurements confirmed the proper electrode modification. Electrochemical impedance spectroscopy records indicated protein detection. The sensor was proven to detect protein D in femtograms. This work was supported by the National Centre for Research and Development (NCBR) TECHMATSTRATEG 1/347324/12/NCBR/ 2017.

Keywords: anti-protein D antibodies, boron-doped carbon nanowall, impedance spectroscopy, Haemophilus influenzae.

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Authors: Bhawana, Roshan Kamal Topno, Maneesh Kumar, Major Madhukar, Krishna Pandey, Ganesh Chandra Sahoo, Manas Ranjan Dikhit, Surya Suman, Devendra Prasad Yadav, Rishikesh Kumar, Pradeep Das

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Viral co-infection is now very common across taxa and environments that are involved in congenital infections. Herpes simplex virus (HSV) and Rubella are the two serious viral infections, well categorized in TORCH Syndrome. Here we had endeavoured the seroprevalence of co-infection of HSV and Rubella. Systematic tests have been performed to check the virulence pattern of the co-infection. The study was conducted at Department of Virology, Rajendra Memorial Research Institute of Medical Sciences (ICMR), Patna, Bihar, India during January 2018-July 2018. 299 newly cases were attended with the sign and symptoms of HSV and Rubella. After taking written consent forms from all the subjects, blood samples were collected for serological detection. ELISA was performed to detect the presence of IgM antibody level. 12 patients were found to be IgM positive from each HSV and Rubella infection. The findings of our study showed that 6 patients were positive for both HSV and rubella and hence were co-infected. Such co-infection causes severe health problems as it leads to the mortality rate of the patients during viral infectivity. Epidemiologically, proper screening should be needed to check any chance of occurrence of such co-infection in the affected regions in large scale and take suitable preventive approach to decrease the case totality. Concern has to be given to aid proper diagnosis and treatment in order to decrease the spread of HSV and Rubella co-infection.

Keywords: HSV, Rubella, seroprevalence, co-infection, ELISA, viral infectivity

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Authors: Zheng Yi

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Among the attempts made worldwide to foster urban and transport sustainability, transit-oriented development certainly is one of the most successful. Residents' travel behavior is a concern in the researches about the impacts of transit-oriented development. The study takes 620 English journal papers in the core collection database of Web of Science as the study objects; the paper tries to map out the scientific knowledge mapping in the field and draw the basic conditions by co-citation analysis, co-word analysis, a total of citation network analysis and visualization techniques. This study teases out the research hotspots and evolution of the relationship between urban rail transit and resident's travel behavior from 1999 to 2019. According to the results of the analysis of the time-zone view and burst-detection, the paper discusses the trend of the next stage of international study. The results show that in the past 20 years, the research focuses on these keywords: land use, behavior, model, built environment, impact, travel behavior, walking, physical activity, smart card, big data, simulation, perception. According to different research contents, the key literature is further divided into these topics: the attributes of the built environment, land use, transportation network, transportation policies. The results of this paper can help to understand the related researches and achievements systematically. These results can also provide a reference for identifying the main challenges that relevant researches need to address in the future.

Keywords: urban rail transit, travel behavior, knowledge map, evolution of researches

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Authors: Saad M. Howladar

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Although, there are a little data on the use of littoral plants as heavy metals bioaccumulators over large areas of the wetlands environment. So, soil samples and biomass of the five plant species: Pluchea dioscroides, Pulicaria crispa, Lavandula pubescens, Tarchononthus comporatus and Argemone ochroleuca were collected from two different sites (basin and mouth) of four dams at Baha province, KSA. Nutrients and heavy metals were extracted from plant samples (leaves and stems) for analyzing elements (Na, K, Ca, P and N) and heavy metals (Pb, Cu and Ni). The soils of the mouth of the dam had the highest concentrations of all elements, while that of basin had the highest ones of most heavy metals except Pb. The soil elements in relation to the two sites arranged as: Ca > K > P > Na > N; and the heavy metals as: Cu > Ni > Pb. The present study indicated that Pluchea dioscroides had the highest values of most elements and heavy metals, while Lavandula pubescens had the lowest. In general, leaves attain the highest concentrations of all nutrients and heavy metals in most studied species as compared with stem. It was indicated that Pluchea dioscroides showed a high transfer factor for almost elements and heavy metals such as K, Na, Cu, Ni and Pb, while Pulicaria crispa showed the highest translocation factor of N, P, Ca-Na ratio and Cu. All studied species growing in the basin had almost the highest concentrations of elements and heavy metals as compared with that in the mouth of dam except K in Pluchea dioscroides, Tarchononthus comporatus and Argemone ochroleuca tissues. Otherwise tissues of Tarchononthus comporatus growing in the basin had the lowest concentrations of K and Ni, while that growing in the mouth had the highest of P and N.

Keywords: Baha Region, bioindicators, plant, pollution, dams, heavy metals

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Authors: Suvarna Kumar Gogula, Sandhya Devi Gogula, P. Chanakya

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Augmented reality is defined as the collection of the digital (or) computer generated information like images, audio, video, 3d models, etc. and overlay them over the real time environment. Augmented reality can be thought as a blend between completely synthetic and completely real. Augmented reality provides scope in a wide range of industries like manufacturing, retail, gaming, advertisement, tourism, etc. and brings out new dimensions in the modern digital world. As it overlays the content, it makes the users enhance the knowledge by providing the content blended with real world. In this application, we integrated augmented reality with data analytics and integrated with cloud so the virtual content will be generated on the basis of the data present in the database and we used marker based augmented reality where every marker will be stored in the database with corresponding unique ID. This application can be used in wide range of industries for different business processes, but in this paper, we mainly focus on the marketing industry which helps the customer in gaining the knowledge about the products in the market which mainly focus on their prices, customer feedback, quality, and other benefits. This application also focuses on providing better market strategy information for marketing managers who obtain the data about the stocks, sales, customer response about the product, etc. In this paper, we also included the reports from the feedback got from different people after the demonstration, and finally, we presented the future scope of Augmented Reality in different business processes by integrating with new technologies like cloud, big data, artificial intelligence, etc.

Keywords: augmented reality, data analytics, catch room, marketing and sales

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Authors: S. S. Adamu, H. S. Muhammad, D. S. Shuaibu

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Poor power quality in electrical power systems can lead to medical equipment at healthcare centres to malfunction and present wrong medical diagnosis. Equipment such as X-rays, computerized axial tomography, etc. can pollute the system due to their high level of harmonics production, which may cause a number of undesirable effects like heating, equipment damages and electromagnetic interferences. The conventional approach of mitigation uses passive inductor/capacitor (LC) filters, which has some drawbacks such as, large sizes, resonance problems and fixed compensation behaviours. The current trends of solutions generally employ active power filters using suitable control algorithms. This work focuses on assessing the level of Total Harmonic Distortion (THD) on medical facilities and various ways of mitigation, using radiology unit of an existing hospital as a case study. The measurement of the harmonics is conducted with a power quality analyzer at the point of common coupling (PCC). The levels of measured THD are found to be higher than the IEEE 519-1992 standard limits. The system is then modelled as a harmonic current source using MATLAB/SIMULINK. To mitigate the unwanted harmonic currents a shunt active filter is developed using synchronous detection algorithm to extract the fundamental component of the source currents. Fuzzy logic controller is then developed to control the filter. The THD without the active power filter are validated using the measured values. The THD with the developed filter show that the harmonics are now within the recommended limits.

Keywords: power quality, total harmonics distortion, shunt active filters, fuzzy logic

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Authors: Maxime Merheb, Rachel Matar

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Retrieving ancient DNA sequences which in return permit the entire genome sequencing from fossils have extraordinarily improved in recent years, thanks to sequencing technology and other methodological advances. In any case, the quest to search for ancient DNA is still obstructed by the damage inflicted on DNA which accumulates after the death of a living organism. We can characterize this damage into three main categories: (i) Physical abnormalities such as strand breaks which lead to the presence of short DNA fragments. (ii) Modified bases (mainly cytosine deamination) which cause errors in the sequence due to an incorporation of a false nucleotide during DNA amplification. (iii) DNA modifications referred to as blocking lesions, will halt the PCR extension which in return will also affect the amplification and sequencing process. We can clearly see that the issues arising from breakage and coding errors were significantly decreased in recent years. Fast sequencing of short DNA fragments was empowered by platforms for high-throughput sequencing, most of the coding errors were uncovered to be the consequences of cytosine deamination which can be easily removed from the DNA using enzymatic treatment. The methodology to repair DNA sequences is still in development, it can be basically explained by the process of reintroducing cytosine rather than uracil. This technique is thus restricted to amplified DNA molecules. To eliminate any type of damage (particularly those that block PCR) is a process still pending the complete repair methodologies; DNA detection right after extraction is highly needed. Before using any resources into extensive, unreasonable and uncertain repair techniques, it is vital to distinguish between two possible hypotheses; (i) DNA is none existent to be amplified to begin with therefore completely un-repairable, (ii) the DNA is refractory to PCR and it is worth to be repaired and amplified. Hence, it is extremely important to develop a non-enzymatic technique to detect the most degraded DNA.

Keywords: ancient DNA, DNA barcodong, enzymatic repair, PCR

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Authors: Bliss Singhal

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Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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Authors: Majid Farsadrouh Rashti, Amir Shafiee Kisomi, Parisa Jahani

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The direct ethanol fuel cells (DEFCs) are contemplated as a promising energy source because, In addition to being used in portable electronic devices, it is also used for electric vehicles. The synthesis of bimetallic nanostructures due to their novel optical, catalytic and electronic characteristic which is precisely in contrast to their monometallic counterparts is attracting extensive attention. Galvanic replacement (sometimes is named to as cementation or immersion plating) is an uncomplicated and effective technique for making nanostructures (such as core-shell) of different metals, semiconductors, and their application in DEFCs. The replacement of galvanic does not need any external power supply compared to electrodeposition. In addition, it is different from electroless deposition because there is no need for a reducing agent to replace galvanizing. In this paper, a fast method for the palladium (Pd) wire nanostructures synthesis with the great surface area through galvanic replacement reaction utilizing copper nanowires (CuNWS) as a template by the assistance of ultrasound under room temperature condition is proposed. To evaluate the morphology and composition of Pd@ Copper nanowires/MultiWalled Carbon nanotubes-Chitosan, emission scanning electron microscopy, energy dispersive X-ray spectroscopy were applied. In order to measure the phase structure of the electrocatalysts were performed via room temperature X-ray powder diffraction (XRD) applying an X-ray diffractometer. Various electrochemical techniques including chronoamperometry and cyclic voltammetry were utilized for the electrocatalytic activity of ethanol electrooxidation and durability in basic solution. Pd@ Copper nanowires/MultiWalled Carbon nanotubes-Chitosan catalyst demonstrated substantially enhanced performance and long-term stability for ethanol electrooxidation in the basic solution in comparison to commercial Pd/C that demonstrated the potential in utilizing Pd@ Copper nanowires/MultiWalled Carbon nanotubes-Chitosan as efficient catalysts towards ethanol oxidation. Noticeably, the Pd@ Copper nanowires/MultiWalled Carbon nanotubes-Chitosan presented excellent catalytic activities with a peak current density of 320.73 mAcm² which was 9.5 times more than in comparison to Pd/C (34.2133 mAcm²). Additionally, activation energy thermodynamic and kinetic evaluations revealed that the Pd@ Copper nanowires/MultiWalled Carbon nanotubes-Chitosan catalyst has lower compared to Pd/C which leads to a lower energy barrier and an excellent charge transfer rate towards ethanol oxidation.

Keywords: core-shell structure, electrocatalyst, ethanol oxidation, galvanic replacement reaction

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Authors: Burçak Boztemur, Yue Xu, Laima Luo, M. Lütfi Öveçoğlu, Duygu Ağaoğulları

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Tungsten (W) is used chiefly as plasma-facing material. However, it has some problems, such as brittleness after plasma exposure. High-entropy alloys (RHEAs) are a new opportunity for this deficiency. So, the neutron shielding behavior of WNbMoVTa and WNbMoVTaCr₀.₅Al compositions were examined against He⁺ irradiation in this study. The mechanical and irradiation properties of the WNbMoVTa base composition were investigated by adding the Al and Cr elements. The mechanical alloying (MA) for 6 hours was applied to obtain RHEA powders. According to the X-ray diffraction (XRD) method, the body-centered cubic (BCC) phase and NbTa phase with a small amount of WC impurity that comes from vials and balls were determined after 6 h MA. Also, RHEA powders were consolidated with the spark plasma sintering (SPS) method (1500 ºC, 30 MPa, and 10 min). After the SPS method, (Nb,Ta)C and W₂C₀.₈₅ phases were obtained with the decomposition of WC and stearic acid that is added during MA based on XRD results. Also, the BCC phase was obtained for both samples. While the Al₂O₃ phase with a small intensity was seen for the WNbMoVTaCr₀.₅Al sample, the Ta₂VO₆ phase was determined for the base sample. These phases were observed as three different regions according to scanning electron microscopy (SEM). All elements were distributed homogeneously on the white region by measuring an electron probe micro-analyzer (EPMA) coupled with a wavelength dispersive spectroscope (WDS). Also, the grey region of the WNbMoVTa sample was rich in Ta, V, and O elements. However, the amount of Al and O elements was higher for the grey region of the WNbMoVTaCr₀.₅Al sample. The high amount of Nb, Ta, and C elements were determined for both samples. Archimedes’ densities that were measured with alcohol media were closer to the theoretical densities of RHEAs. These values were important for the microhardness and irradiation resistance of compositions. While the Vickers microhardness value of the WNbMoVTa sample was measured as ~11 GPa, this value increased to nearly 13 GPa with the WNbMoVTaCr₀.₅Al sample. These values were compatible with the wear behavior. The wear volume loss was decreased to 0.16×10⁻⁴ from 1.25×10⁻⁴ mm³ by the addition of Al and Cr elements to the WNbMoVTa. The He⁺ irradiation was conducted on the samples to observe surface damage. After irradiation, the XRD patterns were shifted to the left because of defects and dislocations. He⁺ ions were infused under the surface, so they created the lattice expansion. The peak shifting of the WNbMoVTaCr₀.₅Al sample was less than the WNbMoVTa base sample, thanks to less impact. A small amount of fuzz was observed for the base sample. This structure was removed and transformed into a wavy structure with the addition of Cr and Al elements. Also, the deformation hardening was actualized after irradiation. A lower amount of hardening was obtained with the WNbMoVTaCr₀.₅Al sample based on the changing microhardness values. The surface deformation was decreased in the WNbMoVTaCr₀.₅Al sample.

Keywords: refractory high entropy alloy, microhardness, wear resistance, He⁺ irradiation

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Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

Abstract:

Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

Procedia PDF Downloads 138

Authors: Azhar Ulhaq, Zubair Yameen, Almas Anjum

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Frequency behaviour of self-excited induction generator (SEIG) wind turbines during control mode transition from grid connected to islanded mode is studied in detail. A robust control scheme for frequency regulation based on combined action of STATCOM, energy storage system (ESS) and pitch angle control for wind powered microgrid (MG) is proposed. Suggested STATCOM controller comprises a 3-phase voltage source converter (VSC) that contains insulated gate bipolar transistors (IGBTs) based pulse width modulation (PWM) inverters along with a capacitor bank. Energy storage system control consists of current controlled voltage source converter and battery bank. Both of them acting simultaneously after detection of island compensates for reactive and active power demands, thus regulating frequency at point of common coupling (PCC) and also improves load stability. STATCOM integrates at point of common coupling and ESS is connected to microgrids main bus. Results reveal that proposed control not only stabilizes frequency during transition duration but also minimizes sudden frequency imbalance caused by load variation or wind intermittencies in islanded operation. System is investigated with and without suggested control scheme. The efficacy of proposed strategy has been verified by simulation in MATLAB/Simulink.

Keywords: energy storage system, island, wind, STATCOM, self-excited induction generator, SEIG, transient

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Authors: Feleke Terefe Fanta

Abstract:

Background: The existence of heavy metals and coliform bacteria contaminants in aquatic system of Akaki river basin, a sub city of Addis Ababa, Ethiopia has become a public concern as human population increases and land development continues. Hence, it is the right time to design treatment technologies that can handle multiple pollutants. Results: In this study, we prepared a synthetic zeolites and copper doped zeolite composite adsorbents as cost effective and simple approach to simultaneously remove heavy metals and total coliforms from wastewater of Akaki river. The synthesized copper–zeolite X composite was obtained by ion exchange method of copper ions into zeolites frameworks. Iodine test, XRD, FTIR and autosorb IQ automated gas sorption analyzer were used to characterize the adsorbents. The mean concentrations of Cd, Cr, and Pb in untreated sample were 0.795, 0.654 and 0.7025 mg/L respectively. These concentrations decreased to Cd (0.005 mg/L), Cr (0.052 mg/L) and Pb (bellow detection limit, BDL) for sample treated with bare zeolite X while a further decrease in concentration of Cd (0.005 mg/L), Cr (BDL) and Pb (BDL) was observed for the sample treated with copper–zeolite composite. Zeolite X and copper-modified zeolite X showed complete elimination of total coliforms after 90 and 50 min contact time respectively. Conclusion: The results obtained in this study showed high antimicrobial disinfection and heavy metal removal efficiencies of the synthesized adsorbents. Furthermore, these sorbents are efficient in significantly reducing physical parameters such as electrical conductivity, turbidity, BOD and COD.

Keywords: WASTE WATER, COPPER DOPED ZEOITE X, ADSORPITION, HEAVY METAL, DISINFECTION, AKAKI RIVER

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Authors: Jixiang Lei, Alexander Fuchs, Franz Pernkopf, Katrin Ellermann

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Within the Space@Sea project, funded by the Horizon 2020 program, an island consisting of multiple platforms was designed. The platforms are connected by ropes and fenders. The connection is critical with respect to the safety of the whole system. Therefore, fault detection systems are investigated, which could detect early warning signs for a possible failure in the connection elements. Previously, a model-based method called Extended Kalman Filter was developed to detect the reduction of rope stiffness. This method detected several types of faults reliably, but some types of faults were much more difficult to detect. Furthermore, the model-based method is sensitive to environmental noise. When the wave height is low, a long time is needed to detect a fault and the accuracy is not always satisfactory. In this sense, it is necessary to develop a more accurate and robust technique that can detect all rope faults under a wide range of operational conditions. Inspired by this work on the Space at Sea design, we introduce a fault diagnosis method based on deep neural networks. Our method cannot only detect rope degradation by using the acceleration data from each platform but also estimate the contributions of the specific acceleration sensors using methods from explainable AI. In order to adapt to different operational conditions, the domain adaptation technique DANN is applied. The proposed model can accurately estimate rope degradation under a wide range of environmental conditions and help users understand the relationship between the output and the contributions of each acceleration sensor.

Keywords: fault diagnosis, deep learning, domain adaptation, explainable AI

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Authors: J. Bravo, F. Cabrera Suárez, B. Vega, L. Román, M. Martel, F. Acosta

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Ciguatera fish poisoning (CFP) is the most common non-bacterial intoxication in the world caused by ingestion of fish with bio-accumulated ciguatoxins (CTXs). It is typical in tropical and subtropical areas, mainly affecting the Caribbean Sea, Polynesia and other areas in the Pacific and Indian Oceans. Interest in Europe by the CFP is increasing in recent years as more and more cases in European hospitals are appearing, usually by people who have consumed ciguatoxin imported fish or have travelled to areas of risk for this poisoning. Since 2004 a series of poisonings raised the question of a possible occurrence of ciguatoxin in Europe, especially in the area of Macaronesia in the East Atlantic temperate zone. Furthermore, some studies have identified the presence of Gambierdiscus spp. in waters surrounding the Canary Islands and Madeira, a toxic dinoflagellate related to this poisoning. The toxin accumulates and concentrates through the food chain and affects to the end of the chain, the human consumer. Fish were collected from the Canary Islands waters and the toxin has been extracted and purified by using acetone and liquid/liquid partition in order to eliminate the excess of fatty acids that may interfere with the detection of the toxin. The fish extracts were inoculated in Neuroblastoma (neuro-2a) cells. After 24-h cell viability was used as an endpoint for cytotoxic effects measurement. Since 2011 our laboratory is collecting data for species such Seriola spp., Epinephelus spp., Makaira spp., Pomatomus spp., Xiphias spp., and Acantocybium spp., from all islands and including the sports fishing and professional activities, we obtained a 8% of fish that have ciguatoxin in their muscle. With these results, we conclude that the island where fishing and fish size affects the probability of catching a fish with the ciguatoxin.

Keywords: Canary Islands, ciguatera fish poisoning, ciguatoxin, Europe

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Authors: Saikiran Subbagari, Avinash Malladhi

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Anti Money Laundering (AML) regulations are designed to prevent money laundering and terrorist financing activities worldwide. Financial institutions around the world are legally obligated to identify, assess and mitigate the risks associated with money laundering and report any suspicious transactions to governing authorities. With increasing volumes of data to analyze, financial institutions seek to automate their AML processes. In the rise of financial crimes, optical character recognition (OCR), in combination with machine learning (ML) algorithms, serves as a crucial tool for automating AML processes by extracting the data from documents and identifying suspicious transactions. In this paper, we examine the utilization of OCR for AML and delve into various OCR techniques employed in AML processes. These techniques encompass template-based, feature-based, neural network-based, natural language processing (NLP), hidden markov models (HMMs), conditional random fields (CRFs), binarizations, pattern matching and stroke width transform (SWT). We evaluate each technique, discussing their strengths and constraints. Also, we emphasize on how OCR can improve the accuracy of customer identity verification by comparing the extracted text with the office of foreign assets control (OFAC) watchlist. We will also discuss how OCR helps to overcome language barriers in AML compliance. We also address the implementation challenges that OCR-based AML systems may face and offer recommendations for financial institutions based on the data from previous research studies, which illustrate the effectiveness of OCR-based AML.

Keywords: anti-money laundering, compliance, financial crimes, fraud detection, machine learning, optical character recognition

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Authors: Asad Hanif, Pavithra Parthasarathy, Zongjin Li

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Thermal insulating composites help to reduce the total power consumption in a building by creating a barrier between external and internal environment. Such composites can be used in the roofing tiles or wall panels for exterior surfaces. This study purposes to develop lightweight cement-based composites for thermal insulating applications. Waste materials like silica fume (an industrial by-product) and fly ash cenosphere (FAC) (hollow micro-spherical shells obtained as a waste residue from coal fired power plants) were used as partial replacement of cement and lightweight filler, respectively. Moreover, aerogel, a nano-porous material made of silica, was also used in different dosages for improved thermal insulating behavior, while poly vinyl alcohol (PVA) fibers were added for enhanced toughness. The raw materials including binders and fillers were characterized by X-Ray Diffraction (XRD), X-Ray Fluorescence spectroscopy (XRF), and Brunauer–Emmett–Teller (BET) analysis techniques in which various physical and chemical properties of the raw materials were evaluated like specific surface area, chemical composition (oxide form), and pore size distribution (if any). Ultra-lightweight cementitious composites were developed by varying the amounts of FAC and aerogel with 28-day unit weight ranging from 1551.28 kg/m³ to 1027.85 kg/m³. Excellent mechanical and thermal insulating properties of the resulting composites were obtained ranging from 53.62 MPa to 8.66 MPa compressive strength, 9.77 MPa to 3.98 MPa flexural strength, and 0.3025 W/m-K to 0.2009 W/m-K as thermal conductivity coefficient (QTM-500). The composites were also tested for peak temperature difference between outer and inner surfaces when subjected to heating (in a specially designed experimental set-up) by a 275W infrared lamp. The temperature difference up to 16.78 ^oC was achieved, which indicated outstanding properties of the developed composites to act as a thermal barrier for building envelopes. Microstructural studies were carried out by Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) for characterizing the inner structure of the composite specimen. Also, the hydration products were quantified using the surface area mapping and line scale technique in EDS. The microstructural analyses indicated excellent bonding of FAC and aerogel in the cementitious system. Also, selective reactivity of FAC was ascertained from the SEM imagery where the partially consumed FAC shells were observed. All in all, the lightweight fillers, FAC, and aerogel helped to produce the lightweight composites due to their physical characteristics, while exceptional mechanical properties, owing to FAC partial reactivity, were achieved.

Keywords: aerogel, cement-based, composite, fly ash cenosphere, lightweight, sustainable development, thermal conductivity

Procedia PDF Downloads 224

Authors: Sina Moradi, Christopher W. K. Chow, John Van Leeuwen, David Cook, Mary Drikas, Patrick Hayde, Rose Amal

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Chloramine is commonly used as a disinfectant in drinking water distribution systems (DWDSs), particularly in Australia and the USA. Maintaining a chloramine residual throughout the DWDS is important in ensuring microbiologically safe water is supplied at the customer’s tap. In order to simulate how chloramine behaves when it moves through the distribution system, a water quality network model (WQNM) can be applied. In this work, the WQNM was based on mono-chloramine decomposition reactions, which enabled prediction of mono-chloramine residual at different locations through a DWDS in Australia, using the Bentley commercial hydraulic package (Water GEMS). The accuracy of WQNM predictions is influenced by a number of water quality parameters. Optimization of these parameters in order to obtain the closest results in comparison with actual measured data in a real DWDS would result in both cost reduction as well as reduction in consumption of valuable resources such as energy and materials. In this work, the optimum operating conditions of water quality parameters (i.e. temperature, pH, and initial mono-chloramine concentration) to maximize the accuracy of mono-chloramine residual predictions for two water supply scenarios in an entire network were determined using response surface methodology (RSM). To obtain feasible and economical water quality parameters for highest model predictability, Design Expert 8.0 software (Stat-Ease, Inc.) was applied to conduct the optimization of three independent water quality parameters. High and low levels of the water quality parameters were considered, inevitably, as explicit constraints, in order to avoid extrapolation. The independent variables were pH, temperature and initial mono-chloramine concentration. The lower and upper limits of each variable for two water supply scenarios were defined and the experimental levels for each variable were selected based on the actual conditions in studied DWDS. It was found that at pH of 7.75, temperature of 34.16 ºC, and initial mono-chloramine concentration of 3.89 (mg/L) during peak water supply patterns, root mean square error (RMSE) of WQNM for the whole network would be minimized to 0.189, and the optimum conditions for averaged water supply occurred at pH of 7.71, temperature of 18.12 ºC, and initial mono-chloramine concentration of 4.60 (mg/L). The proposed methodology to predict mono-chloramine residual can have a great potential for water treatment plant operators in accurately estimating the mono-chloramine residual through a water distribution network. Additional studies from other water distribution systems are warranted to confirm the applicability of the proposed methodology for other water samples.

Keywords: chloramine decay, modelling, response surface methodology, water quality parameters

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Authors: Sanan Raza, Tariq Abbas, Ahmad Yar Qamar, Muhammad Younus, Hamayun Khan, Mujahid Zafar

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Water Buffaloes contribute significantly in Asian agriculture. The objective of this study was to evaluate the efficacy of two synchronization protocols in enhancing pregnancy rate in 105 mixed parity buffaloes particularly in summer season. Buffaloes are seasonal breeders showing more fertility from October to January in subtropical environment of Pakistan. In current study 105 lactating buffaloes of mixed parity were used having normal estrous cycle, age ranging 5-9 years, weighing between 400-650 kg, BCS 4 ± 0.5 (1-5) and lactation varied from first to 5th. Experimental animals were divided into three groups based on corpus leteummorphometry. Morphometry of C.L was done using rectal population and ultrasonography. All animals were injected 25mg of PGi.m. (Cloprostenol). In Group-1 (n=35) hCG was administered at follicular size of 10mm having scanned after detection of heat. Similarly Group-2 (n=35) received 25 mg EB i.m (Estradiol Benzoate) after confirmation of follicular size of 10mm with ultrasound. Likewise, buffaloes of Group-3 (n=35) were administered normal saline respectively using as control. All buffaloes of three groups were inseminated after 12h of hCG, EB, and normal saline administration respectively. Pregnancy was assessed by ultrasound at 18th and 45th day post insemination. Pregnancy rates at 18th day were 38.2%, 34.5%, and 27.3% for G1, G2, and G3 respectively indicating that hCG and EB administered groups have no difference in results except control group having lower conception rate than both groups respectively. Similarly on 42nd day, these were 40.4%, 32.7% for G1 and G2 which are significantly higher than G3= 26.6 (control Group). Also, hCG and EB treated buffaloes have more probability of pregnancy than control group. Based on the findings of current study, it seems reasonable that the use of hCG and EB has been associated with improving pregnancy rates in non-breeding season of buffaloes.

Keywords: buffalo, hCG, EB, pregnancy rate, follicle, insemination

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Authors: A. Ferasat, S. Rostampour Yasouri

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Seasonal flu is a highly contagious infection caused by influenza viruses. These viruses undergo genetic changes that result in new epidemics across the globe. Medical attention is crucial in severe cases, particularly for the elderly, frail, and those with chronic illnesses, as their immune systems are often weaker. The purpose of this study was to detect new subtypes of the influenza A virus rapidly using a specific RT-PCR method based on the HA gene (hemagglutinin). In the winter and spring of 2022_2023, 120 embryonated egg samples were cultured, suspected of seasonal influenza. RNA synthesis, followed by cDNA synthesis, was performed. Finally, the PCR technique was applied using a pair of specific primers designed based on the HA gene. The PCR product was identified after purification, and the nucleotide sequence of purified PCR products was compared with the sequences in the gene bank. The results showed a high similarity between the sequence of the positive samples isolated from the patients and the sequence of the new strains isolated in recent years. This RT-PCR technique is entirely specific in this study, enabling the detection and multiplication of influenza and its subspecies from clinical samples. The RT-PCR technique based on the HA gene, along with sequencing, is a fast, specific, and sensitive diagnostic method for those infected with influenza viruses and its new subtypes. Rapid molecular diagnosis of influenza is essential for suspected people to control and prevent the spread of the disease to others. It also prevents the occurrence of secondary (sometimes fatal) pneumonia that results from influenza and pathogenic bacteria. The critical role of rapid diagnosis of new strains of influenza is to prepare a drug vaccine against the latest viruses that did not exist in the community last year and are entirely new viruses.

Keywords: influenza, molecular diagnosis, patients, RT-PCR technique

Procedia PDF Downloads 74

Authors: A. Shirazibeheshti, T. Radwan, A. Ettefaghian, G. Wilson, C. Luca, Farbod Khanizadeh

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Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature, which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on over 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. To further evaluate the performance of the model, any association between the average risk score within each group and other factors such as socioeconomic status (i.e., Index of Multiple Deprivation) and an index of health and disability were investigated. The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings also show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, indicating that females are more at risk from this kind of multiple medications. The risk may be monitored and controlled in well artificial intelligence-equipped healthcare management systems.

Keywords: anticholinergic medicines, clustering, deprivation, socioeconomic status

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