Search results for: performance assessment

Authors: Saqib Saleem Abdullah, Saima Masood, Hafsa Zaneb, Shela Gul Bokhari, Muti Ur Rehman, Jamil Akbar

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A 5- weeks feeding trial was carried out to determine the effectiveness of Bacterial Phytase (Phyzyme®) in broilers, at different dietary levels of Phosphorous. 140 d-old broilers (Hubbard) were randomly divided into 4 groups (n=4). Birds were fed corn-based basal diet or the same diet supplemented with 3 different levels of non Phytate Phosphorous (NPP) (0.45 %, 0.30 % and 0.15 %). Furthermore, the diets were supplemented with bacterial Phytase. Birds were fed ad libitum and kept under thermo neutral conditions. The parameters studied were; body weight gain (BWG), tibial bone characteristics (TBC), serum Calcium (Ca), Phosphorus (P) and Alkaline Phosphatase (AP) levels and tibia ash percentage (TAP). BWG of the broilers was calculated at weekly interval and remaining parameters were calculated after slaughtering the birds at 35thday. Results suggested that Phytase supplementation at 0.30% NPP (Non Phytate Phosphorus + Bacterial Phytase) increased (P < 0.05) the BWG, bone length, bone weight, tibiotarsal index, medullary canal diameter and diaphysis diameter however, rubosticity index was reduced to minimum (P < 0.05) at this dietary level of phosphorous when compared with other groups. Maximum (P < 0.05) rubosticity index was observed in control group with 0% Phytase. Furthermore, Phytase addition at 0.30 % NPP also improved (P < 0.05) Ca, P and AP levels in the blood. Phytase supplementation at lower phosphorus level (0.30%NPP) improved BWG and TBC including bone density and bone quality in broilers hence it can be concluded that addition of Phytase at 0.30% NPP may prove beneficial for bone and overall performance in broilers.

Keywords: diaphysis diameter, phytase, rubosticity index, tibia

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Authors: Esam El Gohary

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— The companies’ ability to survive and compete in the fierce competition is determined by its competitiveness level. With the spread of information technology use and appearance of online shopping, it became crucial for companies to adopt e-commerce system to increase its competitiveness. This paper was conducted with the purpose of determine how increasing the service value through e-commerce factors (competitive strategy, ICT infrastructures, logistics, security, human resources and innovation) can enhance companies' competitiveness. The problem of this paper is summarized in the absence of the thorough awareness of e-commerce benefits for business owners and customers, as well as how to reduce the intangibility attributes of e-commerce. For this purpose this paper describes the e-commerce in Egypt and its success factors (infrastructures, legal and regulatory environment, human resources and innovation), as well as displays the barriers of such factor, to investigate the significant of these factors on increasing service value and enhance companies' competitiveness. This paper revealed that e-commerce companies have many opportunities to enhance its competitiveness in Egypt, which is enhanced by several factors. The most important factors are “strong ICT infrastructure, qualified and skilled human resources, in addition to the distinctive logistics that distinguish Egypt due to its location, strong legal and regulatory environment and Innovation, as well as the competitive strategy. As well as, companies encounter several threats such as; the lack of infrastructures and logistics in rural areas, the absence of the inclusive understanding and awareness of e-commerce, fear from e-payment transactions and fraud, the ambiguity and burdensome of customs. Through the research findings several recommendations were introduced to both government and companies to overcome threats and exploit opportunities to improve performance and enhance companies' competitiveness.

Keywords: e-commerce competitiveness, e-commerce factors, e-commerce in Egypt, information technology

Procedia PDF Downloads 103

Authors: Nadia Belu, Laurenţiu Mihai Ionescu, Agnieszka Misztal

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The automotive industry is one of the most important industries in the world that concerns not only the economy, but also the world culture. In the present financial and economic context, this field faces new challenges posed by the current crisis, companies must maintain product quality, deliver on time and at a competitive price in order to achieve customer satisfaction. Two of the most recommended techniques of quality management by specific standards of the automotive industry, in the product development, are Failure Mode and Effects Analysis (FMEA) and Control Plan. FMEA is a methodology for risk management and quality improvement aimed at identifying potential causes of failure of products and processes, their quantification by risk assessment, ranking of the problems identified according to their importance, to the determination and implementation of corrective actions related. The companies use Control Plans realized using the results from FMEA to evaluate a process or product for strengths and weaknesses and to prevent problems before they occur. The Control Plans represent written descriptions of the systems used to control and minimize product and process variation. In addition Control Plans specify the process monitoring and control methods (for example Special Controls) used to control Special Characteristics. In this paper we propose a computer-aided solution with Genetic Algorithms in order to reduce the drafting of reports: FMEA analysis and Control Plan required in the manufacture of the product launch and improved knowledge development teams for future projects. The solution allows to the design team to introduce data entry required to FMEA. The actual analysis is performed using Genetic Algorithms to find optimum between RPN risk factor and cost of production. A feature of Genetic Algorithms is that they are used as a means of finding solutions for multi criteria optimization problems. In our case, along with three specific FMEA risk factors is considered and reduce production cost. Analysis tool will generate final reports for all FMEA processes. The data obtained in FMEA reports are automatically integrated with other entered parameters in Control Plan. Implementation of the solution is in the form of an application running in an intranet on two servers: one containing analysis and plan generation engine and the other containing the database where the initial parameters and results are stored. The results can then be used as starting solutions in the synthesis of other projects. The solution was applied to welding processes, laser cutting and bending to manufacture chassis for buses. Advantages of the solution are efficient elaboration of documents in the current project by automatically generating reports FMEA and Control Plan using multiple criteria optimization of production and build a solid knowledge base for future projects. The solution which we propose is a cheap alternative to other solutions on the market using Open Source tools in implementation.

Keywords: automotive industry, FMEA, control plan, automotive technology

Procedia PDF Downloads 406

Authors: Muhammad Bilal Qadir, Danish Umer, Amir Shahzad

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The use of conductive materials in smart and interactive textiles is gaining significant importance for creating value addition, innovation, and functional product development. These products find their potential applications in health monitoring, military, protection, communication, sensing, monitoring, actuation, fashion, and lifestyles. The materials which are most commonly employed in such type of interactive textile include intrinsically conducting polymers, conductive inks, and metallic coating on textile fabrics and inherently conducting metallic fibre yarns. In this study, silver coated polyester filament yarn is explored for the development of multifunctional interactive gloves. The composite yarn was developed by covering the silver coated polyester filament around the polyester spun yarn using hollow spindle technique. The electrical and tensile properties of the yarn were studied. This novel yarn was used to manufacture a smart glove to explore the antibacterial, functional, and interactive properties of the yarn. The change in electrical resistance due to finger movement at different bending positions and antimicrobial properties were studied. This glove was also found useful as an interactive tool to operate the commonly used touch screen devices due to its conductive nature. The yarn can also be used to develop the sensing elements like stretch, strain, and piezoresistive sensors. Such sensor can be effectively used in medical and sports textile for performance monitoring, vital signs monitoring and development of antibacterial textile for healthcare and hygiene.

Keywords: conductive yarn, interactive textiles, piezoresistive sensors, smart gloves

Procedia PDF Downloads 243

Authors: Mustafa Dagbasi, Olusola Bamisile, Adii Chinedum

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The objective of this work is to examine and compare the economic and environmental feasibility of 40MW photovoltaic (PV) power plant and 40MW parabolic trough (PT) power plant to be installed in two different cities, namely Nicosia and Famagusta in Turkish Republic of Northern Cyprus (TRNC). The need for using solar power technology around the world is also emphasized. Solar radiation and sunshine data for Nicosia and Famagusta are considered and analyzed to assess the distribution of solar radiation, sunshine duration, and air temperature. Also, these two different technologies with same rated power of 40MW will be compared with the performance of the proposed Solar Power Plant at Bari, Italy. The project viability analysis is performed using System Advisor Model (SAM) through Annual Energy Production and economic parameters for both cities. It is found that for the two cities; Nicosia and Famagusta, the investment is feasible for both 40MW PV power plant and 40MW PT power plant. From the techno-economic analysis of these two different solar power technologies having same rated power and under the same environmental conditions, PT plants produce more energy than PV plant. It is also seen that if a PT plant is installed near an existing steam turbine power plant, the steam from the PT system can be used to run this turbine which makes it more feasible to invest. The high temperatures that are used to produce steam for the turbines in the PT plant system can be supplemented with a secondary plant based on natural gas or other biofuels and can be used as backup. Although the initial investment of PT plant is higher, it has higher economic return and occupies smaller area compared to PV plant of the same capacity.

Keywords: solar power, photovoltaic plant, parabolic trough plant, techno-economic analysis

Procedia PDF Downloads 283

Authors: Temidayo Otunniyi

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This paper presents a low computational channelization algorithm for the multi-standards platform using poly phase implementation of a critically sampled hybrid Trigonometry generalized Discrete Fourier Transform, (HGDFT). An HGDFT channelization algorithm exploits the orthogonality of two trigonometry Fourier functions, together with the properties of Quadrature Mirror Filter Bank (QMFB) and Exponential Modulated filter Bank (EMFB), respectively. HGDFT shows improvement in its implementation in terms of high reconfigurability, lower filter length, parallelism, and medium computational activities. Type 1 and type 111 poly phase structures are derived for real-valued HGDFT modulation. The design specifications are decimated critically and over-sampled for both single and multi standards receiver platforms. Evaluating the performance of oversampled single standard receiver channels, the HGDFT algorithm achieved 40% complexity reduction, compared to 34% and 38% reduction in the Discrete Fourier Transform (DFT) and tree quadrature mirror filter (TQMF) algorithm. The parallel generalized discrete Fourier transform (PGDFT) and recombined generalized discrete Fourier transform (RGDFT) had 41% complexity reduction and HGDFT had a 46% reduction in oversampling multi-standards mode. While in the critically sampled multi-standard receiver channels, HGDFT had complexity reduction of 70% while both PGDFT and RGDFT had a 34% reduction.

Keywords: software defined radio, channelization, critical sample rate, over-sample rate

Procedia PDF Downloads 148

Authors: Ghazi R. Reda Mahmoud Reda

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Among the metal that forms hydride´s, Mg and Ti are known as the most lightweight materials; however, they are covered with a passive layer of oxides and hydroxides and require activation treatment under high temperature ( > 300 C ) and hydrogen pressure ( > 3 MPa) before being used for storage and transport applications. It is well known that small graphite addition to Ti or Mg, lead to a dramatic change in the kinetics of mechanically induced hydrogen sorption ( uptake) and significantly stimulate the Ti-Hydrogen interaction. Many explanations were given by different authors to explain the effect of graphite addition on the performance of Ti as material for hydrogen storage. Not only graphite but also the addition of a polycyclic aromatic compound will also improve the hydrogen absorption kinetics. It will be shown that the function of carbon addition is two-fold. First carbon acts as a vacuum cleaner, which scavenges out all the interstitial oxygen that can poison or slow down hydrogen absorption. It is also important to note that oxygen favors the chemisorption of hydrogen, which is not desirable for hydrogen storage. Second, during scavenging of the interstitial oxygen, the carbon reacts with oxygen in the nano and microchannel through a highly exothermic reaction to produce carbon dioxide and monoxide which provide the necessary heat for activation and thus in the presence of carbon lower heat of activation for hydrogen absorption which is observed experimentally. Furthermore, the product of the reaction of hydrogen with the carbon oxide will produce water which due to ball milling hydrolyze to produce the linear H5O2 + this will reconstruct the primary structure of the nanocarbon to form secondary structure, where the primary structure (a sheet of carbon) are connected through hydrogen bonding. It is the space between these sheets where physisorption or defect mediated sorption occurs.

Keywords: metal forming hydrides, polar molecule impurities, titanium, phase diagram, hydrogen absorption

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Authors: Jiaqi XU, Qingru Sun

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Accent plays a crucial role in second language (L2) learners’ performance in the schooling context in the era of globalization, where English is adopted as a lingua franca (ELF). Previous studies found that Chinese mainland students prefer American English accents, whereas the young generations in Hong Kong prefer British accents. However, these studies neglect the non-native accents of English and fail to elaborate much about why the L2 learners differ in accent preferences between the two regions. Therefore, this research aims to bridge the research gap by 1) including both native and non-native varieties of English accents: American accent, British accent, Chinese Mandarin English accent, and Hong Kong English accent; and 2) uncovering and comparing the deeper reasons for the similar or/and different accent preferences between the Chinese mainland and Hong Kong speakers. This research designed a questionnaire including objective and subjective questions to investigate the students’ accent inclinations and the attitudes and reasons behind their linguistic choices. The questionnaire was distributed to eight participants (4 Chinese mainland students and 4 Hong Kong students) who were postgraduate students at a Hong Kong university. Based on the data collection, this research finds out one similarity and two differences between the Chinese mainland and Hong Kong students’ attitudes. The theories of identity construction and standard language ideology are further applied to analyze the reasons behind the similarities and differences and to evaluate how language attitudes intertwine with their identity construction and language ideology.

Keywords: accent, language attitudes, identity construction, language ideology, ELF communication

Procedia PDF Downloads 162

Authors: Bachir Redouane, Dib Nihel, Bedrane Sumeya, Blanco Ginesa, Calvino José Juan

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Furfural, a key biomass-derived platform compound, holds significant potential for biofuel production and the synthesis of high-value intermediates. This study investigates the hydrogenation-condensation reaction of furfural issued from lignocellulosique biomass with isopropyl alcohol to produce isopropylfurfuryl ether (iPFE), a next-generation synfuel with a high-octane number. iPFE’s water stability and resistance to methanol absorption make it a sustainable alternative to conventional gasoline additives, offering comparable performance. The catalyst used in this reaction is based on NiAl layered double hydroxides (LDH), with zirconium incorporated to enhance the distribution and structure of active sites. Gold (Au) was deposited on the NiAlZr-LDH support to improve selectivity and yield. The addition of Zr improved the thermal and mechanical stability of the catalyst, while the Au modification further increased selectivity toward iPFE. Extensive catalytic experiments were conducted to optimize reaction conditions, including temperature, hydrogen pressure, and Au loading, to maximize iPFE yield. The results demonstrate a high conversion rate of furfural, exceeding 90% under optimal conditions, with enhanced selectivity toward iPFE. Moreover, iPFE was shown to have a higher-octane number compared to traditional furfuryl ethers, making it a highly promising candidate for advanced fuel applications.

Keywords: Au-NiAlZr-LDH, biofuels, furfural, green chemistry, hydrogenation, isopropylfurfuryl ether, octane number.

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Authors: Shannon O’Donnell, Matthew Driller, Gregory Jacobson, Steve Bird

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Stress hormone levels in a competition vs. training setting are yet to be evaluated in elite female athletes. The effect that these levels of stress have on subsequent sleep quality and quantity is also yet to be investigated. The aim of the current study was to evaluate different psychophysiological stress markers in competition and training environments and the subsequent effect on sleep indices in an elite female athlete population. The study involved 10 elite female netball athletes (mean ± SD; age = 23 ± 6 yrs) providing multiple salivary hormone measures and having their sleep monitored on two occasions; a match day, and a training day. The training and match were performed at the same time of day and were matched for intensity and duration. Saliva samples were collected immediately pre (5:00 pm) and post session (7:15 pm), and at 10:00 pm and were analysed for cortisol concentrations. Sleep monitoring was performed using wrist actigraphy to assess total sleep time (TST), sleep efficiency (SE%) and sleep latency (SL). Cortisol levels were significantly higher (p < 0.01) immediately post the match vs post training (mean ± SD; 0.925 ± 0.341 μg/dL and 0.239 ± 0.284 μg/dL, respectively) and at 10:00pm (0.143 ± 0.085 μg/dL and 0.072 ± 0.064 μg/dL, respectively, p < 0.01). The difference between trials was associated with a very large effect (ES: 2.23) immediately post (7:15 pm) and a large effect (ES: 1.02) at 10:00 pm. There was a significant reduction in TST (mean ± SD; -117.9 ± 111.9 minutes, p < 0.01, ES: -1.89) and SE% (-7.7 ± 8.5%, p < 0.02, ES: -0.79) on the night following the netball match compared to the training session. Although not significant (p > 0.05), there was an increase in SL following the netball match v the training session (67.0 ± 51.9 minutes and 38.5 ± 29.3 minutes, respectively), which was associated with a moderate effect (ES: 0.80). The current study reports that cortisol levels are significantly higher and subsequent sleep quantity and quality is significantly reduced in elite female athletes following a match compared to a training session.

Keywords: cortisol, netball, performance, recovery

Procedia PDF Downloads 256

Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

Procedia PDF Downloads 134

Authors: Komal Kumar, Sreedevi Upadhyayula

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In this study, a two-stage process was established for the synthesis of HMF esters using ionic liquid acid catalyst. Ionic liquid catalyst with different strength of the Bronsted acidity was prepared in the laboratory and characterized using 1H NMR, FT-IR, and 13C NMR spectroscopy. Solid acid catalyst from the ionic liquid catalyst was prepared using the immobilization method. The acidity of the synthesized acid catalyst was measured using Hammett function and titration method. Catalytic performance was evaluated for the biomass conversion to 5-hydroxymethylfurfural (5-HMF) and levulinic acid (LA) in methyl isobutyl ketone (MIBK)-water biphasic system. A good yield of 5-HMF and LA was found at the different composition of MIBK: Water. In the case of MIBK: Water ratio 10:1, good yield of 5-HMF was observed at ambient temperature 150˚C. Upgrading of 5-HMF into monoesters from the reaction of 5-HMF and reactants using biomass-derived monoacid were performed. Ionic liquid catalyst with -SO₃H functional group was found to be best efficient in comparative of a solid acid catalyst for the esterification reaction and biomass conversion. A good yield of 5-HMF esters with high 5-HMF conversion was found to be at 105˚C using the best active catalyst. In this process, process A was the hydrothermal conversion of cellulose and monomer into 5-HMF and LA using acid catalyst. And the process B was the esterification followed by using similar acid catalyst. All monoesters of 5-HMF synthesized here can be used in chemical, cross linker for adhesive or coatings and pharmaceutical industry. A theoretical density functional theory (DFT) study for the optimization of the ionic liquid structure was performed using the Gaussian 09 program to find out the minimum energy configuration of ionic liquid catalyst.

Keywords: biomass conversion, 5-HMF, Ionic liquid, HMF ester

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Authors: T. M. Tawfik, M. A. Badr, E. Y. El-Kady, O. E. Abdellatif

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Electric power shortage is a serious problem in remote rural communities in Egypt. Over the past few years, electrification of remote communities including efficient on-site energy resources utilization has achieved high progress. Remote communities usually fed from diesel generator (DG) networks because they need reliable energy and cheap fresh water. The main objective of this paper is to design an optimal economic power supply from hybrid standalone energy system (HSES) as alternative energy source. It covers energy requirements for reverse osmosis desalination unit (DU) located in National Research Centre farm in Noubarya, Egypt. The proposed system consists of PV panels, Wind Turbines (WT), Batteries, and DG as a backup for supplying DU load of 105.6 KWh/day rated power with 6.6 kW peak load operating 16 hours a day. Optimization of HSES objective is selecting the suitable size of each of the system components and control strategy that provide reliable, efficient, and cost-effective system using net present cost (NPC) as a criterion. The harmonization of different energy sources, energy storage, and load requirements are a difficult and challenging task. Thus, the performance of various available configurations is investigated economically and technically using iHOGA software that is based on genetic algorithm (GA). The achieved optimum configuration is further modified through optimizing the energy extracted from renewable sources. Effective minimization of energy charging the battery ensures that most of the generated energy directly supplies the demand, increasing the utilization of the generated energy.

Keywords: energy management, hybrid system, renewable energy, remote area, optimization

Procedia PDF Downloads 199

Authors: Sofina Faith C. Navarro, Luke V. Subala, Rica H. Gatus, Alfonzo Ramon DG. Burguete

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Roof tiles, as integral components of buildings, play a crucial role in protecting structures from many things. The study focuses on the production of sustainable roof tiles that address the waste disposal challenges associated with Manila clam shells and mitigate the environmental impact of conventional roof tile materials. Various concentrations of roof tiles are developed, incorporating different proportions of powdered clam shell that contains calcium carbonate and shredded raffia palm fiber. Subsequently, the roof tiles are cast using standard methods and transported to the University of the Philippines Institute of Civil Engineering (UP-ICE) for flexural strength testing. In conclusion, the research aimed to assess the flexural durability of concrete roof tiles with varying concentrations of Raffia Palm Fiber and Manila Clam Shells additives. The findings indicate notable differences in maximum load capacities among the specimens, with C3.1 emerging as the concentration with the highest load-bearing capacity at 313.59729 N. This concentration, with a flexural strength of 2.15214, is identified as the most durable option, with a slightly heavier weight of 1.10 kg. On the other hand, C2.2, with a flexural strength of 0.366 and a weight of 0.80 kg, is highlighted for its impressive durability performance while maintaining a lighter composition. Therefore, for the production of concrete roof tile, C3.1 is recommended for optimal durability, while C2.2 is suggested as a preferable option considering both durability and lightweight characteristics.

Keywords: raffia palm fiber, flexural strength, lightweightness, Manila Clam Shells

Procedia PDF Downloads 62

Authors: Alfonzo Ramon Burguete, Rica Gatus, Sofina Faith Navarro, Luke Subala

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Roof tiles, as integral components of buildings, play a crucial role in protecting structures from many things. The study focuses on the production of sustainable roof tiles that address the waste disposal challenges associated with Manila clam shells and mitigate the environmental impact of conventional roof tile materials. Various concentrations of roof tiles are developed, incorporating different proportions of powdered clam shell that contains calcium carbonate and shredded raffia palm fiber. Subsequently, the roof tiles are cast using standard methods and transported to the University of the Philippines Institute of Civil Engineering (UP-ICE) for flexural strength testing. In conclusion, the research aimed to assess the flexural durability of concrete roof tiles with varying concentrations of Raffia Palm Fiber and Manila Clam Shells additives. The findings indicate notable differences in maximum load capacities among the specimens, with C3.1 emerging as the concentration with the highest load-bearing capacity at 313.59729 N. This concentration, with a flexural strength of 2.15214, is identified as the most durable option, with a slightly heavier weight of 1.10 kg. On the other hand, C2.2, with a flexural strength of 0.366 and a weight of 0.80 kg, is highlighted for its impressive durability performance while maintaining a lighter composition. Therefore, for the production of concrete roof tile C3.1 is recommended for optimal durability, while C2.2 is suggested as a preferable option considering both durability and lightweight characteristics.

Keywords: manila clam shells, raffia palm fiber, flexural strength, lightweightness

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Authors: Omolola Ojetayo, Emmanuel Garuba, Obinna Ajunwa, Abiodun A. Onilude

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Introduction: Biofilm is a functional community of microorganisms that are associated with a surface or an interface. These adherent cells become embedded within an extracellular matrix composed of polymeric substances, i.e., biofilms refer to biological deposits consisting of both microbes and their extracellular products on biotic and abiotic surfaces. Despite their detrimental effects in medicine, biofilms as natural cell immobilization have found several applications in biotechnology, such as in the treatment of wastewater, bioremediation and biodegradation, desulfurization of gas, and conversion of agro-derived materials into alcohols and organic acids. The means of enhancing immobilized cells have been chemical-inductive, and this affects the medium composition and final product. Physical factors including electrical, magnetic, and electromagnetic flux have shown potential for enhancing biofilms depending on the bacterial species, nature, and intensity of emitted signals, the duration of exposure, and substratum used. However, the concept of cell immobilisation by electrical and magnetic induction is still underexplored. Methods: To assess the effects of physical factors on biofilm formation, six American typed culture collection (Acetobacter aceti ATCC15973, Pseudomonas aeruginosa ATCC9027, Serratia marcescens ATCC14756, Gluconobacter oxydans ATCC19357, Rhodobacter sphaeroides ATCC17023, and Bacillus subtilis ATCC6633) were used. Standard culture techniques for bacterial cells were adopted. Natural autoimmobilisation potentials of test bacteria were carried out by simple biofilms ring formation on tubes, while crystal violet binding assay techniques were adopted in the characterisation of biofilm quantity. Electroinduction of bacterial cells by direct current (DC) application in cell broth, static magnetic field exposure, and electromagnetic flux were carried out, and autoimmobilisation of cells in a biofilm pattern was determined on various substrata tested, including wood, glass, steel, polyvinylchloride (PVC) and polyethylene terephthalate. Biot Savart law was used in quantifying magnetic field intensity, and statistical analyses of data obtained were carried out using the analyses of variance (ANOVA) as well as other statistical tools. Results: Biofilm formation by the selected test bacteria was enhanced by the physical factors applied. Electromagnetic induction had the greatest effect on biofilm formation, with magnetic induction producing the least effect across all substrata used. Microbial cell-cell communication could be a possible means via which physical signals affected the cells in a polarisable manner. Conclusion: The enhancement of biofilm formation by bacteria using physical factors has shown that their inherent capability as a cell immobilization method can be further optimised for industrial applications. A possible relationship between the presence of voltage-dependent channels, mechanosensitive channels, and bacterial biofilms could shed more light on this phenomenon.

Keywords: bacteria, biofilm, cell immobilization, electromagnetic induction, substrata

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Authors: Hoda Manafian, Stephen Holland

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Problem statement: Rural areas in Iran are one of the most popular tourism destinations. Abyaneh Village is one of them with a long history behind it (more than 1500 years) which is a national heritage site and also is nominated as a world heritage site in UNESCO tentative list from 2007. There is a considerable foundation of religious-cultural heritage and also agricultural history and activities. However, this heritage site suffers from mass tourism which is beyond its social and physical carrying capacity, since the annual number of tourists exceed 500,000. While there are four adjacent villages around Abyaneh which can benefit from advantages of tourism. Local managers also can at the same time prorate the tourists’ flux of Abyaneh on those other villages especially in high-season. The other villages have some cultural and natural tourism attractions as well. Goal: The main goal of this study is to identify a feasible development strategy according to the current strengths, weaknesses, opportunities and threats of rural tourism in this area (Abyaneh Village and four adjacent villages). This development strategy can lead to sustainable management of these destinations. Method: To this end, we used SWOT analysis as a well-established tool for conducting a situational analysis to define a sustainable development strategy. The procedures included following steps: 1) Extracting variables of SWOT chart based on interviewing tourism experts (n=13), local elites (n=17) and personal observations of researcher. 2) Ranking the extracted variables from 1-5 by 13 tourism experts in Isfahan Cultural Heritage, Handcrafts and Tourism Organization (ICHTO). 3) Assigning weights to the ranked variables using Expert Choice Software and the method of Analytical Hierarchical Process (AHP). 4) Defining the Total Weighted Score (TWS) for each part of SWOT chart. 5) Identifying the strategic position according to the TWS 6) Selecting the best development strategy based on the defined position using the Strategic Position and Action Evaluation (SPACE) matrix. 7) Assessing the Probability of Strategic Success (PSS) for the preferred strategy using relevant formulas. 8) Defining two feasible alternatives for sustainable development. Results and recommendations: Cultural heritage attractions were first-ranked variable in strength chart and also lack of sufficient amenities for one-day tourists (catering, restrooms, parking, and accommodation) was firs-ranked weakness. The strategic position was in ST (Strength-Threat) quadrant which is a maxi-mini position. According this position we would suggest ‘Competitive Strategy’ as a development strategy which means relying on strengths in order to neutralization threats. The result of Probability of Strategic Success assessment which was 0.6 shows that this strategy could be successful. The preferred approach for competitive strategy could be rebranding the market of tourism in this area. Rebranding the market can be achieved by two main alternatives which are based on the current strengths and threats: 1) Defining a ‘Heritage Corridor’ from first adjacent village to Abyaneh as a final destination. 2) Focus on ‘educational tourism’ versus mass tourism and also green tourism by developing agritourism in that corridor.

Keywords: Abyaneh village, rural tourism, SWOT analysis, sustainable strategies

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Authors: Peng Zhang, Cai Liang

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The non-biodegradable plastic wastes have posed severe environmental and ecological contaminations. Numerous technologies, such as pyrolysis, incineration, and landfilling, have already been employed for the treatment of plastic waste. Compared with conventional methods, microwave has displayed unique advantages in the rapid production of hydrogen from plastic wastes. Understanding the interaction between microwave radiation and materials would promote the optimization of several parameters for the microwave reaction system. In this work, various carbon materials have been investigated to reveal microwave heating performance and the ensuing catalytic activity. Results showed that the diversity in the heating characteristic was mainly due to the dielectric properties and the individual microstructures. Furthermore, the gaps and steps among the surface of carbon materials would lead to the distortion of the electromagnetic field, which correspondingly induced plasma discharging. The intensity and location of local plasma were also studied. For high-yield H₂ production, iron nanoparticles were selected as the active sites, and a series of iron/carbon bifunctional catalysts were synthesized. Apart from the high catalytic activity, the iron particles in nano-size close to the microwave skin depth would transfer microwave irradiation to the heat, intensifying the decomposition of plastics. Under microwave radiation, iron is supported on activated carbon material with 10wt.% loading exhibited the best catalytic activity for H₂ production. Specifically, the plastics were rapidly heated up and subsequently converted into H₂ with a hydrogen efficiency of 85%. This work demonstrated a deep understanding of microwave reaction systems and provided the optimization for plastic treatment.

Keywords: plastic waste, recycling, hydrogen, microwave

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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: Laleh Boroumand, Muhammad Shiraz, Abdullah Gani, Rashid Hafeez Khokhar

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Cloud computing being the use of hardware and software that are delivered as a service over a network has its application in the area of health care. Due to the emergency cases reported in most of the medical centers, prompt for an efficient scheme to make health data available with less response time. To this end, we propose a mobile global healthcare village (MGHV) model that combines the components of three deployment model which include country, continent and global health cloud to help in solving the problem mentioned above. In the creation of continent model, two (2) data centers are created of which one is local and the other is global. The local replay the request of residence within the continent, whereas the global replay the requirements of others. With the methods adopted, there is an assurance of the availability of relevant medical data to patients, specialists, and emergency staffs regardless of locations and time. From our intensive experiment using the simulation approach, it was observed that, broker policy scheme with respect to optimized response time, yields a very good performance in terms of reduction in response time. Though, our results are comparable to others when there is an increase in the number of virtual machines (80-640 virtual machines). The proportionality in increase of response time is within 9%. The results gotten from our simulation experiments shows that utilizing MGHV leads to the reduction of health care expenditures and helps in solving the problems of unqualified medical staffs faced by both developed and developing countries.

Keywords: cloud computing (MCC), e-healthcare, availability, response time, service broker policy

Procedia PDF Downloads 377

Authors: Diego R. Boiarski, Camila M. Toigo, Thais M. Sobjak, Andrey F. P. Santos, Silvia Romao, Ana T. B. Guimaraes

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Anthropogenic activities promote changes in the community’s structures and decrease the species abundance of amphibians. Biological communities of fluvial systems are assemblies of organisms that have adapted to regional conditions, including the physical environment and food resources, and are further refined through interactions with other species. The aim of this study was to assess neurotoxic alterations and in the antioxidant system on tadpoles of Lithobates catesbeianus exposed to waters from Cascavel River, in the south of Brazil. A total of 420 L of water was collected from the Cascavel River, 140 L from each of the three different locations: Site 1 – headwater; Site 2 – stretch of the stream that runs through an urbanized area; Site 3 – a stretch from the rural area. Twelve tadpoles were acclimated in each aquarium (100 L of water) for seven days. The water from each aquarium was replaced with the ones sampled from the river, except the one from the control aquarium. After seven days, a portion of the liver was removed and conditioned for ChE, SOD, CAT and LPO analysis; other part of the tissue was conditioned for histological analysis. The statistical analysis performed was one-way ANOVA, followed by post-hoc Tukey-HSD test, and the multivariate principal components analysis. It was not observed any neurotoxic effect, but a slight increase in SOD activity and elevation of CAT activity in both urban and rural environment. A decrease in LPO reaction was detected, mainly among the tadpoles exposed to the waters from the rural area. The results of the present study demonstrate the alteration of the antioxidant system, as well as liver histopathologies in tadpoles exposed mainly to waters collected in urban and rural environments. These alterations may cause the reduction in the velocity of the metamorphosis process from the tadpoles. Further, were observed histological alterations, highlighting necrotic areas mainly among the animals exposed to urban waters. Those damages can lead to metabolic dysfunction, interfering with survival capacity, diminishing not only individual fitness but for the whole population. In the interpretation synthesis of all biomarkers, the cellular damage gradient is perceptible, characterized by the variables related to the antioxidant system, due to the flow direction of the stream. This result is indicative that along the course of the creek occurs dumping of organic material, which promoted an acute response upon tadpoles of L. catesbeianus. and it was also observed the difference in tissue damage between the experimental groups and the control group, the latter presenting histological alterations, but to a lesser degree than the animals exposed to the waters of the Cascavel river. These damages, caused by reactive oxygen species possibly resulting from the contamination by organic compounds, can lead the animals to a series of metabolic dysfunctions, interfering with its metamorphosis capacity. Interruption of metamorphosis may affect survival, which may impair its growth, development and reproduction, diminishing not only the fitness of each individual but in a long-term, to the entire population.

Keywords: American bullfrog, histopathology, oxidative stress, urban creeks pollution

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Authors: Abdisalam Hassan Muse, Samuel Mwalili, Oscar Ngesa

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A generalized log-logistic distribution with variable shapes of the hazard rate was introduced and studied, extending the log-logistic distribution by adding an extra parameter to the classical distribution, leading to greater flexibility in analysing and modeling various data types. The proposed distribution has a large number of well-known lifetime special sub-models such as; Weibull, log-logistic, exponential, and Burr XII distributions. Its basic mathematical and statistical properties were derived. The method of maximum likelihood was adopted for estimating the unknown parameters of the proposed distribution, and a Monte Carlo simulation study is carried out to assess the behavior of the estimators. The importance of this distribution is that its tendency to model both monotone (increasing and decreasing) and non-monotone (unimodal and bathtub shape) or reversed “bathtub” shape hazard rate functions which are quite common in survival and reliability data analysis. Furthermore, the flexibility and usefulness of the proposed distribution are illustrated in a real-life data set and compared to its sub-models; Weibull, log-logistic, and BurrXII distributions and other parametric survival distributions with 3-parmaeters; like the exponentiated Weibull distribution, the 3-parameter lognormal distribution, the 3- parameter gamma distribution, the 3-parameter Weibull distribution, and the 3-parameter log-logistic (also known as shifted log-logistic) distribution. The proposed distribution provided a better fit than all of the competitive distributions based on the goodness-of-fit tests, the log-likelihood, and information criterion values. Finally, Bayesian analysis and performance of Gibbs sampling for the data set are also carried out.

Keywords: hazard rate function, log-logistic distribution, maximum likelihood estimation, generalized log-logistic distribution, survival data, Monte Carlo simulation

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Authors: Hamed Rajabzadeh Gatabi, Soroush Dastgheibifard, Mahsa Asnafi

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There is no doubt that reinforced concrete is known as one of the most significant materials which is used in construction industry for many years. Although, some natural elements in dealing with environment can contribute to its corrosion or failure. One of which is bar or so-called reinforcement failure. So as to combat this problem, one of the oxidization prevention methods investigated was the barrier protection method implemented over the application of an organic coating, specifically fusion-bonded epoxy. In this study comparative method is prepared on two different kinds of covered bars (zinc-riches epoxy and polyamide epoxy coated bars) and also uncoated bar. With the aim of evaluate these reinforced concretes, the stickiness, toughness, thickness and corrosion performance of coatings were compared by some tools like Cu/CuSo4 electrodes, EIS and etc. Different types of concretes were exposed to the salty environment (NaCl 3.5%) and their durability was measured. As stated by the experiments in research and investigations, thick coatings (named epoxies) have acceptable stickiness and strength. Polyamide epoxy coatings stickiness to the bars was a bit better than that of zinc-rich epoxy coatings; nonetheless it was stiffer than the zinc rich epoxy coatings. Conversely, coated bars with zinc-rich epoxy showed more negative oxidization potentials, which take revenge protection of bars by zinc particles. On the whole, zinc-rich epoxy coverings is more corrosion-proof than polyamide epoxy coatings due to consuming zinc elements and some other parameters, additionally if the epoxy coatings without surface defects are applied on the rebar surface carefully, it can be said that the life of steel structures is subjected to increase dramatically.

Keywords: surface coating, epoxy polyamide, reinforce concrete bars, salty environment

Procedia PDF Downloads 289

Authors: Daniel Mueller, Melanie Breitbach, Stefan Cornelius, Sarah Pakulla-Dickel, Margaretha Koenig, Anke Prochnow, Mario Scherer

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The European STR standard set (ESS) of loci as well as the new expanded CODIS core loci set as recommended by the CODIS Core Loci Working Group, has led to a higher standardization and harmonization in STR analysis across borders. Various multiplex PCRs assays have since been developed for the analysis of these 17 ESS or 23 CODIS expansion STR markers that all meet high technical demands. However, forensic analysts are often faced with difficult STR results and the questions thereupon. What is the reason that no peaks are visible in the electropherogram? Did the PCR fail? Was the DNA concentration too low? QIAGEN’s newest Investigator STR kits contain a novel Quality Sensor (QS) that acts as internal performance control and gives useful information for evaluating the amplification efficiency of the PCR. QS indicates if the reaction has worked in general and furthermore allows discriminating between the presence of inhibitors or DNA degradation as a cause for the typical ski slope effect observed in STR profiles of such challenging samples. This information can be used to choose the most appropriate rework strategy.Based on the latest PCR chemistry called FRM 2.0, QIAGEN now provides the next technological generation for STR analysis, the Investigator ESSplex SE QS and Investigator 24plex QS Kits. The new PCR chemistry ensures robust and fast PCR amplification with improved inhibitor resistance and easy handling for a manual or automated setup. The short cycling time of 60 min reduces the duration of the total PCR analysis to make a whole workflow analysis in one day more likely. To facilitate the interpretation of STR results a smart primer design was applied for best possible marker distribution, highest concordance rates and a robust gender typing.

Keywords: PCR, QIAGEN, quality sensor, STR

Procedia PDF Downloads 496

Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

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Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

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Authors: Michael Karnes, Alper Yilmaz

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This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.

Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition

Procedia PDF Downloads 76

Authors: Banafsheh Nikmehr, Mohsen Bahrami, Yueqiang Song, Anuradha Koduru, Ayse K. Vuruskan, Hongkun Lu, Mallory Pitts, Tolga B. Mesen, Tamer M. Yalcinkaya

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The number of people who receive in vitro fertilization (IVF) treatment has increased on a startling trajectory over the past two decades. Despite advances in this field, particularly the introduction of intracytoplasmic sperm injection (ICSI) and the preimplantation genetic screening (PGS), the IVF success remains low. A major factor contributing to IVF failure is embryonic aneuploidy (abnormal chromosome content), which often results in miscarriage and birth defects. Although PGS is often used as the standard diagnostic tool to identify aneuploid embryos, it is an invasive approach that could affect the embryo development, and yet inaccessible to many patients due its high costs. As such, there is a clear need for a non-invasive cost-effective approach to identify euploid embryos for single embryo transfer (SET). The reported differences between morphokinetic behaviors of aneuploid and euploid embryos has shown promise to address this need. However, current literature is inconclusive and further research is urgently needed to translate current findings into clinical diagnostics. In this ongoing study, we found significant differences between morphokinetic behaviors of euploid and aneuploid embryos that provides important insights and reaffirms the promise of such behaviors for developing non-invasive methodologies. Methodology—A total of 242 embryos (euploid: 149, aneuploid: 93) from 74 patients who underwent IVF treatment in Carolinas Fertility Clinics in Winston-Salem, NC, were analyzed. All embryos were incubated in an EmbryoScope incubator. The patients were randomly selected from January 2019 to June 2021 with most patients having both euploid and aneuploid embryos. All embryos reached the blastocyst stage and had known PGS outcomes. The ploidy assessment was done by a third-party testing laboratory on day 5-7 embryo biopsies. The morphokinetic variables of each embryo were measured by the EmbryoViewer software (Uniesense FertiliTech) on time-lapse images using 7 focal depths. We compared the time to: pronuclei fading (tPNf), division to 2,3,…,9 cells (t2, t3,…,t9), start of embryo compaction (tSC), Morula formation (tM), start of blastocyst formation (tSC), blastocyst formation (tB), and blastocyst expansion (tEB), as well as intervals between them (e.g., c23 = t3 – t2). We used a mixed regression method for our statistical analyses to account for the correlation between multiple embryos per patient. Major Findings— The average age of the patients was 35.04 yrs. The average patient age associated with euploid and aneuploid embryos was not different (P = 0.6454). We found a significant difference in c45 = t5-t4 (P = 0.0298). Our results indicated this interval on average lasts significantly longer for aneuploid embryos - c45(aneuploid) = 11.93hr vs c45(euploid) = 7.97hr. In a separate analysis limited to embryos from the same patients (patients = 47, total embryos=200, euploid=112, aneuploid=88), we obtained the same results (P = 0.0316). The statistical power for this analysis exceeded 87%. No other variable was different between the two groups. Conclusion— Our results demonstrate the importance of morphokinetic variables as potential biomarkers that could aid in non-invasively characterizing euploid and aneuploid embryos. We seek to study a larger population of embryos and incorporate the embryo quality in future studies.

Keywords: IVF, embryo, euploidy, aneuploidy, morphokinteic

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Authors: Thanakorn Thanawat, Nomjit Nualnetr

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Background and Purpose: In Thailand, rice farmers have the most prevalence of low back pain when compared with other manual workers. Exercises have been suggested to be a principal part of treatment programs for low back pain. However, the programs should be tailored to an individual’s readiness to change categorized by a behavioral approach. This study aimed to evaluate a difference between the responses of rice farmers with chronic low back pain who received an exercise program integrated with the transtheoretical model of behavior change (TTM) and those of the comparison group regarding severity of pain and trunk muscle endurance. Materials and Methods: An 8-week exercise program was conducted to rice farmers with chronic low back pain who were randomized to either the TTM (n=62, 52 woman and 10 men, mean age ± SD 45.0±5.4 years) or non-TTM (n=64, 53 woman and 11 men, mean age ± SD 44.7±5.4 years) groups. All participants were tested for their severity of pain and trunk (abdominal and back) muscle endurance at baseline (week 0) and immediately after termination of the program (week 8). Data were analysed by using descriptive statistics and student’s t-tests. The results revealed that both TTM and non-TTM groups could decrease their severity of pain and improve trunk muscle endurance after participating in the 8-week exercise program. When compared with the non-TTM group, however, the TTM showed a significantly greater increase in abdominal muscle endurance than did the non-TTM (P=0.004, 95% CI -12.4 to -2.3). Conclusions and Clinical Relevance: An exercise program integrated with the TTM could provide benefits to rice farmers with chronic low back pain. Future studies with a longitudinal design and more outcome measures such as physical performance and quality of life are suggested to reveal further benefits of the program.

Keywords: chronic low back pain, transtheoretical model, rice farmers, exercise program

Procedia PDF Downloads 383

Authors: Min Jindong, Wang Mingxia

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With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

Procedia PDF Downloads 278

Authors: Jennifer Kehinde, Claire O'donnell, Annmarie Grealish

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Introduction: Breastfeeding has been shown to provide numerous health benefits for both infants and mothers. The decision to breastfeed is influenced by physiological, psychological, and emotional factors. However, the importance of equipping mothers with the necessary knowledge for successful breastfeeding practice cannot be ruled out. The decline in global breastfeeding rate can be linked to lack of adequate breastfeeding education during prenatal stage.This systematic review examined the effectiveness of prenatal breastfeeding education on breastfeeding uptake postpartum. Method: This review was undertaken and reported in conformity with the Preferred Reporting Items for Systemic Reviews and Meta-Analysis statement (PRISMA) and was registered on the international prospective register for systematic reviews (PROSPERO: CRD42020213853). A PICO analysis (population, intervention, comparison, outcome) was undertaken to inform the choice of keywords in the search strategy to formulate the review question which was aimed at determining the effectiveness of prenatal breastfeeding educational programs at improving breastfeeding uptake following birth. A systematic search of five databases (Cumulative Index to Nursing and Allied Health Literature, Medline, Psych INFO, and Applied Social Sciences Index and Abstracts) were searched between January 2014 until July 2021 to identify eligible studies. Quality assessment and narrative synthesis were subsequently undertaken. Results: Fourteen studies were included. All 14 studies used different types of breastfeeding programs; eight used a combination of curriculum based breastfeeding education program, group prenatal breastfeeding counselling and one-to-one breastfeeding educational programs which were all delivered in person; four studies used web-based learning platforms to deliver breastfeeding education prenatally which were both delivered online and face to face over a period of 3 weeks to 2 months with follow-up periods ranging from 3 weeks to 6 months; one study delivered breastfeeding educational intervention using mother-to-mother breastfeeding support groups in promoting exclusive breastfeeding and one study disseminated breastfeeding education to participants based on the theory of planned behaviour. The most effective interventions were those that included both theory and hands-on demonstrations. Results showed an increase in breastfeeding uptake, breastfeeding knowledge, increase in positive attitude to breastfeeding and an increase in maternal breastfeeding self-efficacy among mothers who participated in breastfeeding educational programs during prenatal care. Conclusion: Prenatal breastfeeding education increases women’s knowledge of breastfeeding. Mothers who are knowledgeable about breastfeeding and hold a positive approach towards breastfeeding have the tendency to initiate breastfeeding and continue for a lengthened period. Findings demonstrates a general correlation between prenatal breastfeeding education and increased breastfeeding uptake postpartum. The high level of positive breastfeeding outcome inherent in all the studies can be attributed to prenatal breastfeeding education. This review provides rigorous contemporary evidence that healthcare professionals and policymakers can apply when developing effective strategies to improve breastfeeding rates and ultimately improve the health outcomes of mothers and infants.

Keywords: breastfeeding, breastfeeding programs, breastfeeding self-efficacy, prenatal breastfeedng education

Procedia PDF Downloads 67