Search results for: fracture detection

Authors: Deepak Jugran, Rajesh Gill

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Purpose: To study the demographic, sociological, gender and clinical profile of the children presented for childhood cataract at a public sector tertiary eye care centre in India. Methodology: The design of the study is retrospective, and hospital-based data is available with the Central Registration Department of the PGIMER, Chandigarh. The majority of the childhood cataract cases are being reported in this hospital, yet not each and every case of childhood cataract approaches PGI, Chandigarh. Nevertheless, this study is going to be pioneering research in India, covering five-year data of the childhood cataract patients who visited the Advanced Eye Centre, PGIMER, Chandigarh, from 1.1.2015 to 31.12.2019. The SPSS version 23 was used for all statistical calculations. Results: A Total of 354 children were presented for childhood cataract from 1.1.2015 to 31.12.2019. Out of 354 children, 248 (70%) were male, and 106 (30%) were female. In-spite of 2 flagship programmes, namely the National Programme for Control of Blindness (NPCB) and Aayushman Bharat (PM JAY) for eradication of cataract, no children received any financial assistance from these two programmes. A whopping 99% of these children belong to the poor families. In most of these families, the mothers were house-wives and did not employ anywhere. These interim results will soon be conveyed to the Govt. of India so that a suitable mechanism can be evolved to address this pertinent issue. Further, the disproportionate ratio of male and female children in this study is an area of concern as we don’t know whether the prevalence of childhood cataract is lower in female children or they are not being presented on time in the hospital by the families. Conclusion: The World Health Organization (WHO) has categorized Childhood blindness resulting from cataract as a priority area and urged all member countries to develop institutionalized mechanisms for its early detection, diagnosis and management. The childhood cataract is an emerging and major cause of preventable and avoidable childhood blindness, especially in low and middle-income countries. In the formative years, the children require a sound physical, mental and emotional state, and in the absence of either one of them, it can severely dent their future growth. The recent estimate suggests that India could suffer an economic loss of US$12 billion (Rs. 88,000 Crores) due to blindness, and almost 35% of cases of blindness are preventable and avoidable if detected at an early age. Besides reporting these results to the policy makers, synchronized efforts are needed for early detection and management of avoidable causes of childhood blindness such as childhood cataract.

Keywords: childhood blindness, cataract, Who, Npcb

Procedia PDF Downloads 92

Authors: P. Leo, E. Cerri, L. Fratini, G. Buffa

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The Friction Stir Welding process uses an inert rotating mandrel and a force on the mandrel normal to the plane of the sheets to generate the frictional heat. The heat and the stirring action of the mandrel create a bond between the two sheets without melting the base metal. As matter of fact, the use of a solid state welding process limits the insurgence of defects, due to the presence of gas in melting bath, and avoids the negative effects of materials metallurgical transformation strictly connected with the change of phase. The industrial importance of Ti-6Al-4V alloy is well known. It provides an exceptional good balance of strength, ductility, fatigue and fracture properties together with good corrosion resistance and good metallurgical stability. In this paper, the authors analyze the microstructure of friction stir welded joints of Ti-6Al-4V processed at the same travel speed (35 mm/min) but at different rotation speeds (300-500 rpm). The microstructure of base material (BM), as result from both optical microscope and scanning electron microscope analysis is not homogenous. It is characterized by distorted α/β lamellar microstructure together with smashed zone of fragmented β layer and β retained grain boundary phase. The BM has been welded in the-as received state, without any previous heat treatment. Even the microstructure of the transverse and longitudinal sections of joints is not homogeneous. Close to the top of weld cross sections a much finer microstructure than the initial condition has been observed, while in the center of the joints the microstructure is less refined. Along longitudinal sections, the microstructure is characterized by equiaxed grains and lamellae. Both the length and area fraction of lamellas increases with distance from longitudinal axis. The hardness of joints is higher than that of BM. As the process temperature increases the average microhardness slightly decreases.

Keywords: friction stir welding, microhardness, microstructure, Ti-6Al-4V

Procedia PDF Downloads 367

Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

Procedia PDF Downloads 64

Authors: Kashima Arora, Monika Tomar, Vinay Gupta

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Biosensors have found potential applications ranging from environmental testing and biowarfare agent detection to clinical testing, health care, and cell analysis. This is driven in part by the desire to decrease the cost of health care and to obtain precise information more quickly about the health status of patient by the development of various biosensors, which has become increasingly prevalent in clinical testing and point of care testing for a wide range of biological elements. Uric acid is an important byproduct in human body and a number of pathological disorders are related to its high concentration in human body. In past few years, rapid growth in the development of new materials and improvements in sensing techniques have led to the evolution of advanced biosensors. In this context, metal oxide thin film based matrices due to their bio compatible nature, strong adsorption ability, high isoelectric point (IEP) and abundance in nature have become the materials of choice for recent technological advances in biotechnology. In the past few years, wide band-gap metal oxide semiconductors including ZnO, SnO₂ and CeO₂ have gained much attention as a matrix for immobilization of various biomolecules. Tin oxide (SnO₂), wide band gap semiconductor (Eg =3.87 eV), despite having multifunctional properties for broad range of applications including transparent electronics, gas sensors, acoustic devices, UV photodetectors, etc., it has not been explored much for biosensing purpose. To realize a high performance miniaturized biomolecular electronic device, rf sputtering technique is considered to be the most promising for the reproducible growth of good quality thin films, controlled surface morphology and desired film crystallization with improved electron transfer property. Recently, iron oxide and its composites have been widely used as matrix for biosensing application which exploits the electron communication feature of Fe, for the detection of various analytes using urea, hemoglobin, glucose, phenol, L-lactate, H₂O₂, etc. However, to the authors’ knowledge, no work is being reported on modifying the electronic properties of SnO₂ by implanting with suitable metal (Fe) to induce the redox couple in it and utilizing it for reagentless detection of uric acid. In present study, Fe implanted SnO₂ based matrix has been utilized for reagentless uric acid biosensor. Implantation of Fe into SnO₂ matrix is confirmed by energy-dispersive X-Ray spectroscopy (EDX) analysis. Electrochemical techniques have been used to study the response characteristics of Fe modified SnO₂ matrix before and after uricase immobilization. The developed uric acid biosensor exhibits a high sensitivity to about 0.21 mA/mM and a linear variation in current response over concentration range from 0.05 to 1.0 mM of uric acid besides high shelf life (~20 weeks). The Michaelis-Menten kinetic parameter (Km) is found to be relatively very low (0.23 mM), which indicates high affinity of the fabricated bioelectrode towards uric acid (analyte). Also, the presence of other interferents present in human serum has negligible effect on the performance of biosensor. Hence, obtained results highlight the importance of implanted Fe:SnO₂ thin film as an attractive matrix for realization of reagentless biosensors towards uric acid.

Keywords: Fe implanted tin oxide, reagentless uric acid biosensor, rf sputtering, thin film

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Authors: Attila Kiss, Erzsébet Némedi, Zoltán Naár

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As natural prebiotic (non-digestible) carbohydrates stimulate the growth of colon microflora and contribute to maintain the health of the host, analytical studies aiming at revealing the chemical behavior of these beneficial food components came to the forefront of interest. Food processing (especially baking) may lead to a significant conversion of the parent compounds, hence it is of utmost importance to characterize the transformation patterns and the plausible decomposition products formed by thermal degradation. The relevance of this work is confirmed by the wide-spread use of these carbohydrates (fructo-oligosaccharides, cyclodextrins, raffinose and resistant starch) in the food industry. More and more functional foodstuffs are being developed based on prebiotics as bioactive components. 12 different types of oligosaccharides have been investigated in order to reveal their thermal degradation characteristics. Different carbohydrate derivatives (D-fructose and D-glucose oligomers and polymers) have been exposed to elevated temperatures (150 °C 170 °C, 190 °C, 210 °C, and 220 °C) for 10 min. An advanced HPLC method was developed and used to identify the decomposition products of carbohydrates formed as a consequence of thermal treatment. Gradient elution was applied with binary solvent elution (acetonitrile, water) through amine based carbohydrate column. Evaporative light scattering (ELS) proved to be suitable for the reliable detection of the UV/VIS inactive carbohydrate degradation products. These experimental conditions and applied advanced techniques made it possible to survey all the formed intermediers. Change in oligomer distribution was established in cases of all studied prebiotics throughout the thermal treatments. The obtained results indicate increased extent of chain degradation of the carbohydrate moiety at elevated temperatures. Prevalence of oligomers with shorter chain length and even the formation of monomer sugars (D-glucose and D-fructose) might be observed at higher temperatures. Unique oligomer distributions, which have not been described previously are revealed in the case of each studied, specific carbohydrate, which might result in various prebiotic activities. Resistant starches exhibited high stability when being thermal treated. The degradation process has been modeled by a plausible reaction mechanism, in which proton catalyzed degradation and chain cleavage take place.

Keywords: prebiotics, thermal degradation, fructo-oligosaccharide, HPLC, ELS detection

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Authors: Kushal Gowda Jayaram, Joseph Huret, Jonathan Quibel, Walter-John Chitty, Gilbert Henaff

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Thermal aging is one of the concerns for the long-term operation of nuclear power plants. Indeed, components in the primary circuit undergo thermal aging while exposed to the chemically active environment of Pressurized Water Reactors (PWRs) over time. Among the materials used in the reactor components, Alloy 690 can be found in some critical components for nuclear safety. Despite its importance, research on the effect of thermal aging on the microstructural changes and low cycle fatigue (LCF) behavior of Alloy 690 remains limited. This study aims to assess the impact of thermal aging on the fatigue life of Alloy 690. The as-received sample underwent aging at 420°C for 4000 hours, representing the equivalent aging of 60 years in reactor working conditions. First, the characterization of the area and density of intergranular and intragranular precipitates was performed to understand the microstructural changes in the aged specimen. Then, low cycle fatigue tests were conducted on the as received and aged samples at varying strain amplitudes. To investigate the influence of thermal aging on the fatigue behavior of Alloy 690, fracture surfaces were analyzed to estimate fatigue crack growth rates based on striation spacing measurements. Additionally, the axially cut fractured samples have undergone analysis using Electron Backscatter Diffraction (EBSD) to understand the effect of aging on strain localization near the crack path. Results indicate that while the characterization of the area and density of intergranular precipitates in the aged specimen (for 2000 hours, approximately 30 years) showed no significant changes, there was a slight increase in the area and density of intragranular precipitates under the same conditions.

Keywords: alloy 690, thermal aging, low cycle fatigue, precipitates

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Authors: Alicja Starczewska, Aleksander Nawrat, Krzysztof Daniec, Jarosław Homa, Kacper Hołda

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Border Gateway Protocol is the main routing protocol that enables routing establishment between all autonomous systems, which are the basic administrative units of the internet. Due to the poor protection of BGP, it is important to use additional BGP security systems. Many solutions to this problem have been proposed over the years, but none of them have been implemented on a global scale. This article describes a system capable of building images of real-time BGP network topology in order to detect BGP anomalies. Our proposal performs a detailed analysis of BGP messages that come into local network cards supplemented by information collected by remote collectors in different localizations.

Keywords: BGP, BGP hijacking, cybersecurity, detection

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Authors: Kamrun N. Keya, Nasrin A. Kona, Ruhul A. Khan

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Pineapple leaf fiber (PALF) reinforced polypropylene (PP) based composites were fabricated by a conventional compression molding technique. In this investigation, PALF composites were manufactured using different percentages of fiber, which were varying from 25-50% on the total weight of the composites. To fabricate the PALF/PP composites, untreated and treated fibers were selected. A systematic study was done to observe the physical, mechanical and interfacial behavior of the composites. In this study, mechanical properties of the composites such as tensile, impact and bending properties were observed precisely. It was found that 45wt% of fiber composites showed better mechanical properties than others. Maximum tensile strength (TS) and bending strength (BS) was observed, 65 MPa and 50 MPa respectively, whereas the highest tensile modulus (TM) and bending modulus (BM) was examined, 1.7 GPa and 0.85 GPa respectively. The PALF/PP based composites were treated with irradiated under gamma radiation (the source strength 50 kCi Cobalt-60) of various doses (2.5 kGy to 10 kGy). The effect of gamma radiation on the composites was also investigated, and it found that the effect of 5.0 kGy (i.e. units for radiation measurement is 'gray', kGy=kilogray ) gamma dose showed better mechanical properties than other doses. The values of TS, BS, TM, and BM of the irradiated (5.0 kGy) composites were found to improve by 19%, 23%, 17% and 25 % over non-irradiated composites. After flexural testing, fracture sides of the untreated and treated both composites were studied by scanning electron microscope (SEM). SEM results of the treated PALF/PP based composites showed better fiber-matrix adhesion and interfacial bonding than untreated PALF/PP based composites. Water uptake and soil degradation tests of untreated and treated composites were also investigated.

Keywords: PALF, polypropylene, compression molding technique, gamma radiation, mechanical properties, scanning electron microscope

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Authors: Mihail Nagea, Olivera Lupescu, Nicolae Ciurea, Alexandru Dimitriu, Alina Grosu

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Introduction: As severe open injuries are more and more frequent in modern traumatology, threatening not only the integrity of the affected limb but even the life of the patients, new methods desired to cope with the consequences of these traumas were described. Vacuum therapy is one such method which has been described as enhancing healing in trauma with extensive soft-tissue injuries, included those with septic complications. Material and methods: Authors prospectively analyze 15 patients with severe lower limb trauma with MESS less than 6, with considerable soft tissue loss following initial debridement and fracture fixation. The patients needed serial debridements and vacuum therapy was applied after delayed healing due to initial severity of the trauma, for an average period of 12 days (7 - 23 days).In 7 cases vacuum therapy was applied for septic complications. Results: Within the study group, there were no local complications; secondary debridements were performed for all the patients and vacuum system was re-installed after these debridements. No amputations were needed. Medical records were reviewed in order to compare the outcome of the patients: the hospital stay, anti-microbial therapy, time to healing of the bone and soft tissues (there is no standard group to be compared with) and the result showed considerable improvements in the outcome of the patients. Conclusion: Vacuum therapy improves healing of the soft tissues, including those infected; hospital stay and the number of secondary necessary procedures are reduced. Therefore it is considered a valuable support in treating trauma of the limbs with severe soft tissue injuries.

Keywords: complex injuries, negative pressure, open fractures, wound therapy

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Authors: Yahya Asanoglu, Celaletdin Ergun

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Ceramic-matrix composites (CMC) have significant prominence in various engineering applications because of their heat resistance associated with an ability to withstand the brittle type of catastrophic failure. In this study, specific raw materials have been chosen for the purpose of having suitable CMC material for high-temperature dielectric applications. CMC material will be manufactured through the polymer infiltration and pyrolysis (PIP) method. During the manufacturing process, vacuum infiltration and autoclave will be applied so as to decrease porosity and obtain higher mechanical properties, although this advantage leads to a decrease in the electrical performance of the material. Time and temperature adjustment in pyrolysis parameters provide a significant difference in the properties of the resulting material. The mechanical and thermal properties will be investigated in addition to the measurement of dielectric constant and tangent loss values within the spectrum of Ku-band (12 to 18 GHz). Also, XRD, TGA/PTA analyses will be employed to prove the transition of precursor to ceramic phases and to detect critical transition temperatures. Additionally, SEM analysis on the fracture surfaces will be performed to see failure mechanism whether there is fiber pull-out, crack deflection and others which lead to ductility and toughness in the material. In this research, the cost-effectiveness and applicability of the PIP method will be proven in the manufacture of CMC materials while optimization of pyrolysis time, temperature and cycle for specific materials is detected by experiment. Also, several resins will be shown to be a potential raw material for CMC radome and antenna applications. This research will be distinguished from previous related papers due to the fact that in this research, the combination of different precursors and fabrics will be experimented with to specify the unique cons and pros of each combination. In this way, this is an experimental sum of previous works with unique PIP parameters and a guide to the manufacture of CMC radome and antenna.

Keywords: CMC, PIP, precursor, quartz

Procedia PDF Downloads 149

Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: Amal Saafan, Kareem Al Sofy, Sameh AbdelGhani, Magdy Amin

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Background: Acinetobacter spp. resistance towards β-lactam antibiotics is mediated mainly by different classes of β-lactamases production; detection of some genes responsible for production of β-lactamases is the objective of the study. Methods: One hundred fifty bacterial isolates were recovered from blood, sputum, and urine specimens from different hospitals in Egypt. Sixty-nine isolate were identified as Acinetobacter baumannii using traditional biochemical tests, CHROM agar, MicroScan and PCR amplification of blaoxa-51like gene. Acinetobacterbaumannii isolates were grouped into carbapenem resistant group (GP1), cefotaxime, ceftazidime and cefoxitin resistant group (GP2) and carbapenem and cephalosporin non-resistant group (GP3). Carbapenemase activity was screened using modified Hodge test (MHT) for GP1.Metallo-β-lactamases screening was performed for MHT positive isolates using double disk synergy test (DDST) and combined disk test (CDT). Amp C activity was screened using Amp C disk test with Tris-EDTA, DDST, and CDT for GP2. Finally, PCR amplification of blaoxa-51like, blaoxa-23like, blaIMP-like, blaVIM-like, and blaADC-like genes was performed for isolates that showed, at least, two positive results of three for both AmpC and carbapenemases phenotypic screening tests (obvious activity), in addition to GP3 (for comparison). Detection of blaoxa-51like and blaADC-like genes preceded by ISAba1 was also performed. Results: Antibiogram of 69 pure Acinetobacter baumannii isolates resulted in 57, 64, and 2 isolates enrolled into GP1, GP2, and GP3, respectively. Carbapenemase activity was shown by 49(85.9%) isolate using MHT. Metallo-β-lactamases screening revealed 32(65.3%) and 35(71.4%) using DDST and CDT, respectively.AmpC activity was shown by 43(67.2%) and 50 (78.1%) isolates using AmpC disk test with Tris-EDTA, and both DDST and CDT, respectively. Twenty-seven isolates showed obvious activity, all of them (100%) were harboring blaoxa-51like and blaADC-like genes, while blaoxa-23like, blaIMP-like andblaVIM-like genes were harbored by 23(85.2%), 9 (33.%) and no isolate respectively. Only 12 (44.4%) isolates harbored blaoxa-51like and blaADC-like genes preceded by ISAba1. GP3 isolates showed only positive blaoxa-51like and blaADC-like genes. Conclusion: It is not possible to correlate resistance with presence of blaoxa-51like and blaADC-like genes and presence of ISAba1 was immediate as transcriptional promoter. A blaoxa-23like gene played an important role in carbapenem resistance when compared with blaIMP-like and blaVIM-like gene.

Keywords: acinetobacter, beta-lactams, resistance, antimicrobial agents

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Authors: Heungsu Lee, Youngseok Kim, Jonghwa Yi, Chul Park

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A landing pier is subjected to safety assessment by visual inspection and design data, but it is difficult to check the damage in real-time. In this study, real - time damage detection and safety evaluation methods were studied. As a result of structural analysis of the arbitrary landing pier structure, the inflection point of deformation and moment occurred at 10%, 50%, and 90% of pile length. The critical value of Fiber Bragg Grating (FBG) sensor was set according to the safety factor, and the FBG sensor application method for real - time safety evaluation was derived.

Keywords: FBG sensor, harbor structure, maintenance, safety evaluation system

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Authors: Laura Boschis, Elena D. Ozzello, Enzo Mastromatteo

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Point of care diagnostic finds growing interest in medicine and agri-food because of faster intervention and prevention. EliChip is a microfluidic platform to perform Point of Care immunoenzymatic assay based on ready-to-use kits and a portable instrument to manage fluidics and read reliable quantitative results. Thanks to miniaturization, analyses are faster and more sensible than conventional ELISA. EliChip is one of the crucial assets of the Europen-founded Flamingo project for in-line measuring inflammatory markers.

Keywords: lab on chip, point of care, immunoenzymatic analysis, synovial arthritis

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Authors: Selman Cagman

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A detailed analysis is made within an organized industrial zone (OIZ) that has 1165 production facilities such as manufacturing of furniture, fabricated metal products (machinery and equipment), food products, plastic and rubber products, machinery and equipment, non-metallic mineral products, electrical equipment, textile products, and manufacture of wood and cork products. In this OIZ, a field study is done by choosing some facilities that can represent the whole OIZ sectoral distribution. In this manner, there are 207 facilities included to the site visit, and there is a 17 questioned survey carried out with each of them to assess their inputs, outputs, and waste amounts during manufacturing processes. The survey result identify that MDF/Particleboard and chipboard particles, textile, food, foam rubber, sludge (treatment sludge, phosphate-paint sludge, etc.), plastic, paper and packaging, scrap metal (aluminum shavings, steel shavings, iron scrap, profile scrap, etc.), slag (coal slag), ceramic fracture, ash from the fluidized bed are the wastes come from these facilities. As a result, there are 5 industrial symbiosis projects established with this study. One of the projects is a 2.840 kW capacity Integrated Biomass Based Waste Incineration-Energy Production Facility running on 35.000 tons/year of MDF particles and chipboard waste. Another project is a biogas plant with 225 tons/year whey, 100 tons/year of sesame husk, 40 tons/year of burnt wafer dough, and 2.000 tons/year biscuit waste. These two plants investment costs and operational costs are given in detail. The payback time of the 2.840 kW plant is almost 4 years and the biogas plant is around 6 years.

Keywords: industrial symbiosis, energy, biogas, waste to incineration

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Authors: Sang Koo Jeon, Seung Hoon Nahm, Oh Heon Kwon

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The unit cell of solid oxide fuel cell (SOFC) must be stacked as several layers type to obtain the high power. The most of researcher have concerned about the performance of stacked SOFC rather than the structural stability of stacked SOFC and especially interested how to design for reducing the electrical loss and improving the high efficiency. Consequently, the stacked SOFC able to produce the electrical high power and related parts like as manifold, gas seal, bipolar plate were developed to optimize the stack design. However, the unit cell of SOFC was just layered on the interconnector without the adhesion and the hydrogen and oxygen were injected to the interfacial layer in the high temperature. On the operating condition, the interfacial layer can be the one of the weak point in the stacked SOFC. Therefore the evaluation of the structural safety for the failure is essentially needed. In this study, interfacial adhesion between SOFC and metal adhesive was estimated in the high temperature environment. The metal adhesive was used to strongly connect the unit cell of SOFC with interconnector and provide the electrical conductivity between them. The four point bending test was performed to measure the interfacial adhesion. The unit cell of SOFC and SiO2 wafer were diced and then attached by metal adhesive. The SiO2 wafer had the center notch to initiate a crack from the tip of the notch. The modified stereomicroscope combined with the CCD camera and system for measuring the length was used to observe the fracture behavior. Additionally, the interfacial adhesion was evaluated in the high temperature condition because the metal adhesive was affected by high temperature. Also the specimen was exposed in the furnace during several hours and then the interfacial adhesion was evaluated. Finally, the interfacial adhesion energy was quantitatively determined and compared in the each condition.

Keywords: solid oxide fuel cell (SOFC), metal adhesive, adhesion, high temperature

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Authors: Giovanni Gonzalez Araujo, Michael Kyrilov, Angelo Kyrilov

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STEAMplug is a web-based innovative educational platform which makes teaching easier and learning more effective. It requires no setup, eliminating the barriers to entry, allowing students to focus on their learning throughreal-world development environments. The student-centric tools enable easy collaboration between peers and teachers. Analyzing user interactions with the system enables us to predict student performance and identify at-risk students, allowing early instructor intervention.

Keywords: plagiarism detection, identifying at-Risk Students, education technology, e-learning system, collaborative development, learning and teaching with technology

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Authors: Hye Kyung Kim, Myung-Gyou Kim, Kang-Hyun Leem

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Postmenopausal osteoporosis is characterized by low bone density which leads to increased bone fragility and greater susceptibility to fracture. Current treatments for osteoporosis are dominated by drugs that inhibit bone resorption although they also suppress bone formation that may contribute to pathogenesis of osteonecrosis. To restore the extensive bone loss, there is a great need for anabolic treatments that induce osteoblasts to build new bone. Pre-osteoblastic cells produce proteins of the extra-cellular matrix, including type I collagen at first, and then to successively produce alkaline phosphatase (ALP) and osteocalcin during differentiation to osteoblasts. Finally, osteoblasts deposit calcium. Present study investigated the effects of egg yolk peptide (EYP) on osteogenic activities and bone matrix gene expressions in human osteoblastic MG-63 cells. The effects of EYP on cell proliferation, alkaline phosphatase (ALP) activity, collagen synthesis, and mineralization were measured. The expression of osteogenic genes including COL1A1 (collagen, type I, alpha 1), ALP, BGLAP (osteocalcin), and SPP1 (secreted phosphoprotein 1, osteopontin) were measured by quantitative realtime PCR. EYP dose-dependently increased MG-63 cell proliferation, ALP activity, collagen synthesis, and calcium deposition. Furthermore, COL1A1, ALP, and SPP1 gene expressions were increased by EYP treatment. Present study suggested that EYP treatment enhanced osteogenic activities and increased bone matrix osteogenicgenes. These results could provide a mechanistic explanation for the bone-strengthening effects of EYP.

Keywords: egg yolk peptide, osteoblastic MG-63 cells, alkaline phosphatase, collagen synthesis, osteogenic genes, COL1A1, osteocalcin, osteopontin

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Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

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The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

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Authors: Amine Rezzoug, Selsabil Rokia Laraba, Mourad Ancer, Said Abdi

Abstract:

Composite materials are taking center stage in different fields thanks to their mechanical characteristics and their ease of preparation. Environmental constraints have led to the development of composite with natural reinforcements. The sandwich structure has the advantage to have good flexural proprieties for low density, which is why it was chosen in this work. The development of these materials is related to an energy saving strategy and environmental protection. The present work refers to the study of the development and characterization of sandwiches composites based on hybrids laminates with natural reinforcements (Alfa and Jute), a metal fabric was introduced into composite in order to have a compromise between weight and properties. We use different configurations of reinforcements (jute, metallic fabric) to develop laminates in order to use them as thin facings for sandwiches materials. While the core was an epoxy matrix reinforced with Alfa short fibers, a chemical treatment sodium hydroxide was cared to improve the adhesion of the Alfa fibers. The mechanical characterization of our materials was made by the tensile and bending test, to highlight the influence of jute and Alfa. After testing, the fracture surfaces are observed by scanning electron microscopy (SEM). Optical microscopy allowed us to calculate the degree of porosity and to observe the morphology of the individual layers. Laminates based on jute fabric have shown better results in tensile test as well as to bending, compared to those of the metallic fabric (100%, 65%). Sandwich Panels were also characterized in terms of bending test. Results we had provide, shows that this composite has sufficient properties for possible replacing conventional composite materials by considering the environmental factors.

Keywords: bending test, bio-composites, sandwiches, tensile test

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Authors: Roscoe McLean, Jared Padayachee, Glen Bright

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There is currently a gap in the technology covering the rapid establishment of control after a reconfiguration in a Reconfigurable Manufacturing System. This gap involves the detection of the factory floor state and the communication link between the factory floor and the high-level software. In this paper, a thin, hardware-supported Middleware Management System (MMS) is proposed and its design and implementation are discussed. The research found that a cost-effective localization technique can be combined with intelligent software to speed up the ramp-up of a reconfigured system. The MMS makes the process more intelligent, more efficient and less time-consuming, thus supporting the industrial implementation of the RMS paradigm.

Keywords: intelligent systems, middleware, reconfigurable manufacturing, management system

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Authors: H. Hotait, X. Chiementin, L. Rasolofondraibe

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This paper presents a continuous work to detect the abnormal state in the rolling bearing by studying the vibration signature analysis and calculation of the remaining useful life. To achieve these aims, two methods; the first method is the classification to detect the degradation state by the AOM-OPTICS (Acousto-Optic Modulator) method. The second one is the prediction of the degradation state using least-squares support vector regression and then compared with the linear degradation model. An experimental investigation on ball-bearing was conducted to see the effectiveness of the used method by applying the acquired vibration signals. The proposed model for predicting the state of bearing gives us accurate results with the experimental and numerical data.

Keywords: bearings, automatization, optimization, prognosis, classification, defect detection

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Authors: Justo Rodriguez, Daming Chen, Amador M. Guzman

Abstract:

The detection, treatment, and control of rapidly propagating, deadly viruses such as COVID-19, require the development of inexpensive, fast, and accurate devices to address the urgent needs of the population. Microfluidics-based sensors are amongst the different methods and techniques for detection that are easy to use. A micro analyzer is defined as a microfluidics-based sensor, composed of a network of microchannels with varying functions. Given their size, portability, and accuracy, they are proving to be more effective and convenient than other solutions. A micro analyzer based on the concept of “Lab on a Chip” presents advantages concerning other non-micro devices due to its smaller size, and it is having a better ratio between useful area and volume. The integration of multiple processes in a single microdevice reduces both the number of necessary samples and the analysis time, leading the next generation of analyzers for the health-sciences. In some applications, the flow of solution within the microchannels is originated by a pressure gradient, which can produce adverse effects on biological samples. A more efficient and less dangerous way of controlling the flow in a microchannel-based analyzer is applying an electric field to induce the fluid motion and either enhance or suppress the mixing process. Electrokinetic flows are characterized by no less than two non-dimensional parameters: the electric Rayleigh number and its geometrical aspect ratio. In this research, stable and unstable flows have been studied numerically (and when possible, will be experimental) in a T-shaped microchannel. Additionally, unstable electrokinetic flows for Rayleigh numbers higher than critical have been characterized. The flow mixing enhancement was quantified in relation to the stretching and folding that fluid particles undergo when they are subjected to supercritical electrokinetic flows. Computational simulations were carried out using a finite element-based program while working with the flow mixing concepts developed by Gollub and collaborators. Hundreds of seeded massless particles were tracked along the microchannel from the entrance to exit for both stable and unstable flows. After post-processing, their trajectories, the folding and stretching values for the different flows were found. Numerical results show that for supercritical electrokinetic flows, the enhancement effects of the folding and stretching processes become more apparent. Consequently, there is an improvement in the mixing process, ultimately leading to a more homogenous mixture.

Keywords: microchannel, stretching and folding, electro kinetic flow mixing, micro-analyzer

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Authors: Yunyong Guo, Man Wang, Bryan Guo, Nathan Guo

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This paper introduces an advanced security and privacy model tailored for Telehealth systems, emphasizing end-to-end protection across IoT, Fog, and Cloud components. The proposed model integrates encryption, key management, intrusion detection, and privacy-preserving measures to safeguard patient data. A comprehensive simulation study evaluates the model's effectiveness in scenarios such as unauthorized access, physical breaches, and insider threats. Results indicate notable success in detecting and mitigating threats yet underscore areas for refinement. The study contributes insights into the intricate balance between security and usability in Telehealth environments, setting the stage for continued advancements.

Keywords: cloud, enhancing security, fog, IoT, telehealth

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Authors: Chao-Ming Su, Pei-Sheng Wu, Yu-Chi Kuo, Yin-Chou Huang, Tan-Yueh Chen, Jefunnie Matahum, Tzong-Rong Ger

Abstract:

Application of magnetic particles (MPs) has been applied in biomedical field for many years. There are lots of advantages through this mediator including high biocompatibility and multi-diversified bio-applications. However, current techniques for evaluating the quantity of the magnetic-labeled sample assays are rare. In this paper, a Wheatstone bridge giant magnetoresistance (GMR) sensor integrated with a homemade detecting system was fabricated and used to quantify the concentration of MPs. The homemade detecting system has shown high detecting sensitivity of 10 μg/μl of MPs with optimized parameter vertical magnetic field 100 G, horizontal magnetic field 2 G and flow rate 0.4 ml/min.

Keywords: magnetic particles, magnetoresistive sensors, microfluidics, biosensor

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Authors: Samabia Tehsin, Sumaira Kausar

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Due to the vast increase in the multimedia data in recent years, efficient and robust retrieval techniques are needed to retrieve and index images/ videos. Text embedded in the images can serve as the strong retrieval tool for images. This is the reason that text extraction is an area of research with increasing attention. English text extraction is the focus of many researchers but very less work has been done on other languages like Urdu. This paper is focusing on Urdu text extraction from video frames. This paper presents a text detection feature set, which has the ability to deal up with most of the problems connected with the text extraction process. To test the validity of the method, it is tested on Urdu news dataset, which gives promising results.

Keywords: caption text, content-based image retrieval, document analysis, text extraction

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Authors: Alireza Akbari, Gelareh Babaee Khou

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Ground Penetrating Radar (GPR) is an important nondestructive remote sensing tool that has been used in both military and civilian fields. Recently, GPR imaging has attracted lots of attention in detection of subsurface shallow small targets such as landmines and unexploded ordnance and also imaging behind the wall for security applications. For the monostatic arrangement in the space-time GPR image, a single point target appears as a hyperbolic curve because of the different trip times of the EM wave when the radar moves along a synthetic aperture and collects reflectivity of the subsurface targets. With this hyperbolic curve, the resolution along the synthetic aperture direction shows undesired low resolution features owing to the tails of hyperbola. However, highly accurate information about the size, electromagnetic (EM) reflectivity, and depth of the buried objects is essential in most GPR applications. Therefore hyperbolic curve behavior in the space-time GPR image is often willing to be transformed to a focused pattern showing the object's true location and size together with its EM scattering. The common goal in a typical GPR image is to display the information of the spatial location and the reflectivity of an underground object. Therefore, the main challenge of GPR imaging technique is to devise an image reconstruction algorithm that provides high resolution and good suppression of strong artifacts and noise. In this paper, at first, the standard back-projection (BP) algorithm that was adapted to GPR imaging applications used for the image reconstruction. The standard BP algorithm was limited with against strong noise and a lot of artifacts, which have adverse effects on the following work like detection targets. Thus, an improved BP is based on cross-correlation between the receiving signals proposed for decreasing noises and suppression artifacts. To improve the quality of the results of proposed BP imaging algorithm, a weight factor was designed for each point in region imaging. Compared to a standard BP algorithm scheme, the improved algorithm produces images of higher quality and resolution. This proposed improved BP algorithm was applied on the simulation and the real GPR data and the results showed that the proposed improved BP imaging algorithm has a superior suppression artifacts and produces images with high quality and resolution. In order to quantitatively describe the imaging results on the effect of artifact suppression, focusing parameter was evaluated.

Keywords: algorithm, back-projection, GPR, remote sensing

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Authors: Javad Khaligh, Aghileh Heydari, Ali Akbar Heydari

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Mathematical epidemiological models for the spread of disease through a population are used to predict the prevalence of a disease or to study the impacts of treatment or prevention measures. Initial conditions for these models are measured from statistical data collected from a population since these initial conditions can never be exact, the presence of chaos in mathematical models has serious implications for the accuracy of the models as well as how epidemiologists interpret their findings. This paper confirms the chaotic behavior of a model for dengue fever and SI by investigating sensitive dependence, bifurcation, and 0-1 test under a variety of initial conditions.

Keywords: epidemiological models, SEIR disease model, bifurcation, chaotic behavior, 0-1 test

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Authors: Yunha Ryu, Kyoungsik Kim

Abstract:

Raman spectroscopy is one of the most powerful techniques for chemical detection, but the low sensitivity originated from the extremely small cross-section of the Raman scattering limits the practical use of Raman spectroscopy. To overcome this problem, Surface Enhanced Raman Scattering (SERS) has been intensively studied for several decades. Because the SERS effect is mainly induced from strong electromagnetic near-field enhancement as a result of localized surface plasmon resonance of metallic nanostructures, it is important to design the plasmonic structures with high density of electromagnetic hot spots for SERS substrate. One of the useful fabrication methods is using porous nanomaterial as a template for metallic structure. Internal pores on a scale of tens of nanometers can be strong EM hotspots by confining the incident light. Also, porous structures can capture more target molecules than non-porous structures in a same detection spot thanks to the large surface area. Herein we report the facile fabrication method of porous SERS substrate by integrating solvent-assisted nanoimprint lithography and selective etching of block copolymer. We obtained nanostructures with high porosity via simple selective etching of the one microdomain of the diblock copolymer. Furthermore, we imprinted of the nanocone patterns into the spin-coated flat block copolymer film to make three-dimensional SERS substrate for the high density of SERS hot spots as well as large surface area. We used solvent-assisted nanoimprint lithography (SAIL) to reduce the fabrication time and cost for patterning BCP film by taking advantage of a solvent which dissolves both polystyrenre and poly(methyl methacrylate) domain of the block copolymer, and thus block copolymer film was molded under the low temperature and atmospheric pressure in a short time. After Ag deposition, we measured Raman intensity of dye molecules adsorbed on the fabricated structure. Compared to the Raman signals of Ag coated solid nanocone, porous nanocone showed 10 times higher Raman intensity at 1510 cm(-1) band. In conclusion, we fabricated porous metallic nanocone arrays with high density electromagnetic hotspots by templating nanoimprinted diblock copolymer with selective etching and demonstrated its capability as an effective SERS substrate.

Keywords: block copolymer, porous nanostructure, solvent-assisted nanoimprint, surface-enhanced Raman spectroscopy

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Authors: Faozia A. S. Abuhtana, Yahia S. Abujnah, Said O. Gnann

Abstract:

Ultra High Temperature (UHT) processed milk is widely distributed and preferred in numerous countries all over the world due its relatively high quality and long shelf life. Because of the notable high consumption rate of UHT in Libya in addition to negligible studies related to such product on the local level, this study was designed to assess the shelf life of locally produced as well as imported reconstituted sterilized whole milk samples marketed in Tripoli, Libya . Four locally produced vs. three imported brands were used in this study. All samples were stored at room temperature (25± 2C ) for 8 month long period, and subjected to physical, chemical, microbiological and sensory tests. These tests included : measurement of pH, specific gravity, percent acidity, and determination of fat, protein and melamine content. Microbiological tests included total aerobic count, total psychotropic bacteria, total spore forming bacteria and total coliform counts. Results indicated no detection of microbial growth of any type during the study period, in addition to no detection of melamine in all samples. On the other hand, a gradual decline in pH accompanied with gradual increase in % acidity of both locally produced and imported samples was observed. Such changes in both pH and % acidity reached their lowest and highest values respectively during the 24th week of storage. For instance pH values were (6.40, 6.55, 6.55, 6.15) and (6.30, 6.50, 6.20) for local and imported brands respectively. On the other hand, % acidity reached (0.185, 0181, 0170, 0183) and (0180, 0.180, 0.171) at the 24th week for local and imported brands respectively. Similar pattern of decline was also observed in specific gravity, fat and protein content in some local and imported samples especially at later stages of the study. In both cases, some of the recorded pH values, % acidity, sp. gravity and fat content were in violation of the accepted limits set by Libyan standard no. 356 for sterilized milk. Such changes in pH, % acidity and other UHT sterilized milk constituents during storage were coincided with a gradual decrease in the degree of acceptance of the stored milk samples of both types as shown by sensory scores recorded by the panelists. In either case degree of acceptance was significantly low at late stages of storage and most milk samples became relatively unacceptable after the 18th and 20th week for both untrained and trained panelists respectively.

Keywords: UHT milk, shelf life, quality, gravity, bacteria

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