Search results for: opposition based learning

Authors: Chloe E. Edwards, Yasaman Shahtaheri

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Risk management plays a fundamental role in project planning and delivery. The purpose of incorporating risk management into project management practices is to identify and address uncertainties related to key project-related activities. The uncertainties, known as risk events, can relate to project deliverables that are quantifiable and are often measured by impact to project schedule, cost, or environmental impact. Risk management should be incorporated as an iterative practice throughout the planning, execution, and commissioning phases of a project. This paper specifically examines how risk management contributes to effective project planning and delivery through a case study of a transportation project. This case study focused solely on impacts to project schedule regarding three milestones: readiness for delivery, readiness for testing and commissioning, and completion of the facility. The case study followed the ISO 31000: Risk Management – Guidelines. The key factors that are outlined by these guidelines include understanding the scope and context of the project, conducting a risk assessment including identification, analysis, and evaluation, and lastly, risk treatment through mitigation measures. This process requires continuous consultation with subject matter experts and monitoring to iteratively update the risks accordingly. The risk identification process led to a total of fourteen risks related to design, permitting, construction, and commissioning. The analysis involved running 1,000 Monte Carlo simulations through @RISK 8.0 Industrial software to determine potential milestone completion dates based on the project baseline schedule. These dates include the best case, most likely case, and worst case to provide an estimated delay for each milestone. Evaluation of these results provided insight into which risks were the highest contributors to the projected milestone completion dates. Based on the analysis results, the risk management team was able to provide recommendations for mitigation measures to reduce the likelihood of risks occurring. The risk management team also provided recommendations for managing the identified risks and project activities moving forward to meet the most likely or best-case milestone completion dates.

Keywords: construction management, monte carlo simulation, project delivery, risk assessment, transportation engineering

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Authors: Leah Wright, Trevor Townsend

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Mode choice models are crucial instruments in the analysis of travel behaviour. These models show the relationship between an individual’s choice of transportation mode for a given O-D pair and the individual’s socioeconomic characteristics such as household size and income level, age and/or gender, and the features of the transportation system. The most popular functional forms of these models are based on Utility-Based Choice Theory, which addresses the uncertainty in the decision-making process with the use of an error term. However, with the development of artificial intelligence, many researchers have started to take a different approach to travel demand modelling. In recent times, researchers have looked at using neural networks, fuzzy logic and rough set theory to develop improved mode choice formulas. The concept of cloud theory has recently been introduced to model decision-making under uncertainty. Unlike the previously mentioned theories, cloud theory recognises a relationship between randomness and fuzziness, two of the most common types of uncertainty. This research aims to investigate the use of cloud theory in mode choice models. This paper highlights the conceptual framework of the mode choice model using cloud theory. Merging decision-making under uncertainty and mode choice models is state of the art. The cloud theory model is expected to address the issues and concerns with the nested logit and improve the design of mode choice models and their use in travel demand.

Keywords: Cloud theory, decision-making, mode choice models, travel behaviour, uncertainty

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Authors: Khalil Ibrahim, Ahmed Ramadan, Mohamed Fanni, Yo Kobayashi, Ahmed Abo-Ismail, Masakatus G. Fujie

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This paper deals with the design process and the dynamic control simulation of a new type of 4-DOFs parallel mechanism that can be used as an endoscopic surgical manipulator. The proposed mechanism, 2-PUU_2-PUS, is designed based on the screw theory and the parallel virtual chain type synthesis method. Based on the structure analysis of the 4-DOF parallel mechanism, the inverse position equation is studied using the inverse analysis theory of kinematics. The design and the stress analysis of the mechanism are investigated using SolidWorks software. The virtual prototype of the parallel mechanism is constructed, and the dynamic simulation is performed using ADAMS TM software. The system model utilizing PID and PI controllers has been built using MATLAB software. A more realistic simulation in accordance with a given bending angle and point to point control is implemented by the use of both ADAMS/MATLAB software. The simulation results showed that this control method has solved the coordinate control for the 4-DOF parallel manipulator so that each output is feedback to the four driving rods. From the results, the tracking performance is achieved. Other control techniques, such as intelligent ones, are recommended to improve the tracking performance and reduce the numerical truncation error.

Keywords: parallel mechanisms, medical robotics, tracjectory control, virtual chain type synthesis method

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Authors: Dewi Hapsari Ratna Muninggar, M. Rizal Martua Damanik

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The purpose of this study was to develop a formulation of instant Indonesian traditional pancake (Surabi) based on composite rice and soybean flour and supplemented with Torbangun (Coleus amboinicus Lour) powder as an alternative snack for ADHD (Attention Deficit Hyperactivity Disorder) children. Completely randomised factorial design by two factors which were the ratio of composite rice and soybean flour (75:25; 70:30; 65:35) as well as the addition of Torbangun powder (3%; 5%; 7%) was used in this study. This study revealed that the best formula was instant surabi with 65:35 composite rice and soybean flour and 5% addition of Torbangun powder by considering hedonic test result, functional aspect and nutrients contribution. Then, both chemical and physical characteristics from the best formula of instant surabi were measured. Nutrients content of the chosen instant surabi per 100 g wet basis were 62.68 g moisture, 1.30 g ash, 6.81 g protein, 0.75 g fat, 28.47 g carbohydrate, 88.62 mg calcium, 4.14 mg iron, and 144 kcal energy while physical characteristics, such as water activity, cohesiveness, and hardness were 0.97, 0.569, 5582.2 g force consecutively. The results of this research suggested that instant surabi which can be possibly beneficial for ADHD children had 65:35 for rice and soybean flour ratio as well as 5% for the addition of Torbangun powder.

Keywords: ADHD children, instant surabi, soybean, torbangun

Procedia PDF Downloads 134

Authors: Shih-Wen Hsiao, Rong-Qi Chen, Chien-Yu Lin

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The topic of surface flattening plays a vital role in the field of computer aided design and manufacture. Surface flattening enables the production of 2D patterns and it can be used in design and manufacturing for developing a 3D surface to a 2D platform, especially in fashion design. This study describes surface flattening based on minimum energy methods according to the property of different fabrics. Firstly, through the geometric feature of a 3D surface, the less transformed area can be flattened on a 2D platform by geodesic. Then, strain energy that has accumulated in mesh can be stably released by an approximate implicit method and revised error function. In some cases, cutting mesh to further release the energy is a common way to fix the situation and enhance the accuracy of the surface flattening, and this makes the obtained 2D pattern naturally generate significant cracks. When this methodology is applied to a 3D mannequin constructed with feature lines, it enhances the level of computer-aided fashion design. Besides, when different fabrics are applied to fashion design, it is necessary to revise the shape of a 2D pattern according to the properties of the fabric. With this model, the outline of 2D patterns can be revised by distributing the strain energy with different results according to different fabric properties. Finally, this research uses some common design cases to illustrate and verify the feasibility of this methodology.

Keywords: surface flattening, strain energy, minimum energy, approximate implicit method, fashion design

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Authors: Arpita Saha, Satish Chandra, Indrajit Ghosh

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Delay implicates the time loss of a traveler while crossing an intersection. Efficiency of traffic operation at signalized intersections is assessed in terms of delay caused to an individual vehicle. Highway Capacity Manual (HCM) method and Webster’s method are the most widely used in India for delay estimation purpose. However, in India, traffic is highly heterogeneous in nature with extremely poor lane discipline. Therefore, to explore best delay estimation technique for Indian condition, a comparison was made. In this study, seven signalized intersections from three different cities where chosen. Data was collected for both during morning and evening peak hours. Only under saturated cycles were considered for this study. Delay was estimated based on the field data. With the help of Simpson’s 1/3 rd rule, delay of under saturated cycles was estimated by measuring the area under the curve of queue length and cycle time. Moreover, the field observed delay was compared with the delay estimated using HCM, Webster, Probabilistic, Taylor’s expansion and Regression methods. The drawbacks of the existing delay estimation methods to be use in Indian heterogeneous traffic conditions were figured out, and best method was proposed. It was observed that direct estimation of delay using field measured data is more accurate than existing conventional and modified methods.

Keywords: delay estimation technique, field delay, heterogeneous traffic, signalised intersection

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Authors: Wilayat Ali, Li Sheng, Waleed Ahmed

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The ability of the robot to make simultaneously map of the environment and localize itself with respect to that environment is the most important element of mobile robots. To solve SLAM many algorithms could be utilized to build up the SLAM process and SLAM is a developing area in Robotics research. Robot Operating System (ROS) is one of the frameworks which provide multiple algorithm nodes to work with and provide a transmission layer to robots. Manyof these algorithms extensively in use are Hector SLAM, Gmapping and Cartographer SLAM. This paper describes a ROS-based Simultaneous localization and mapping (SLAM) library Google Cartographer mapping, which is open-source algorithm. The algorithm was applied to create a map using laser and pose data from 2d Lidar that was placed on a mobile robot. The model robot uses the gazebo package and simulated in Rviz. Our research work's primary goal is to obtain mapping through Cartographer SLAM algorithm in a static indoor environment. From our research, it is shown that for indoor environments cartographer is an applicable algorithm to generate 2d maps with LIDAR placed on mobile robot because it uses both odometry and poses estimation. The algorithm has been evaluated and maps are constructed against the SLAM algorithms presented by Turtlebot2 in the static indoor environment.

Keywords: SLAM, ROS, navigation, localization and mapping, gazebo, Rviz, Turtlebot2, slam algorithms, 2d indoor environment, cartographer

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Authors: Lamzira Ebralidze, Aleksandre Tsertsvadze, Dali Berashvili, Aliosha Bakuridze

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Nowadays, there is an increasing demand for biologically active substances from vegetable, animal, and mineral resources. In terms of the use of natural compounds, pharmaceutical, cosmetic, and nutrition industry has big interest. The biggest drawback of conventional extraction methods is the need to use a large volume of organic extragents. The removal of the organic solvent is a multi-stage process. And their absolute removal cannot be achieved, and they still appear in the final product as impurities. A large amount of waste containing organic solvent damages not only human health but also has the harmful effects of the environment. Accordingly, researchers are focused on improving the extraction methods, which aims to minimize the use of organic solvents and energy sources, using alternate solvents and renewable raw materials. In this context, green extraction principles were formed. Green Extraction is a need of today’s environment. Green Extraction is the concept, and it totally corresponds to the challenges of the 21st century. The extraction of biologically active compounds based on green extraction principles is vital from the view of preservation and maintaining biodiversity. Novel technologies of green extraction are known, such as "cold methods" because during the extraction process, the temperature is relatively lower, and it doesn’t have a negative impact on the stability of plant compounds. Novel technologies provide great opportunities to reduce or replace the use of organic toxic solvents, the efficiency of the process, enhance excretion yield, and improve the quality of the final product. The objective of the research is the development of green technologies of flavonoids containing preparations. Methodology: At the first stage of the research, flavonoids containing preparations (Tincture Herba Leonuri, flamine, rutine) were prepared based on conventional extraction methods: maceration, bismaceration, percolation, repercolation. At the same time, the same preparations were prepared based on green technologies, microwave-assisted, UV extraction methods. Product quality characteristics were evaluated by pharmacopeia methods. At the next stage of the research technological - economic characteristics and cost efficiency of products prepared based on conventional and novel technologies were determined. For the extraction of flavonoids, water is used as extragent. Surface-active substances are used as co-solvent in order to reduce surface tension, which significantly increases the solubility of polyphenols in water. Different concentrations of water-glycerol mixture, cyclodextrin, ionic solvent were used for the extraction process. In vitro antioxidant activity will be studied by the spectrophotometric method, using DPPH (2,2-diphenyl-1- picrylhydrazyl) as an antioxidant assay. The advantage of green extraction methods is also the possibility of obtaining higher yield in case of low temperature, limitation extraction process of undesirable compounds. That is especially important for the extraction of thermosensitive compounds and maintaining their stability.

Keywords: extraction, green technologies, natural resources, flavonoids

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Authors: Yang Zhou, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is a fundamental problem in urban environment, facilitating the smart management of various businesses, such as taxi dispatching, bike relocation, and stampede alert. Most earlier methods rely on identifying the intrinsic spatial-temporal correlation to forecast. However, the complex nature of this problem entails a more sophisticated solution that can simultaneously capture the mutual influence of both adjacent and far-flung areas, with the information of time-dimension also incorporated seamlessly. To tackle this difficulty, we propose a new multi-phase architecture, DSTDS (Dual Spatial-Temporal Data Scheme for traffic prediction), that aims to reveal the underlying relationship that determines future traffic trend. First, a graph-based neural network with an attention mechanism is devised to obtain the static features of the road network. Then, a multi-granularity recurrent neural network is built in conjunction with the knowledge from a grid-based model. Subsequently, the preceding output is fed into a spatial-temporal super-resolution module. With this 3-phase structure, we carry out extensive experiments on several real-world datasets to demonstrate the effectiveness of our approach, which surpasses several state-of-the-art methods.

Keywords: traffic prediction, spatial-temporal, recurrent neural network, dual data scheme

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Authors: Amr AbdelAzim Ali, G. A. Elsheikh, Moutaz M. Hegazy

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Reaction wheels (RWs) are generally used as main actuator in the attitude control system (ACS) of spacecraft (SC) for fast orientation and high pointing accuracy. In order to achieve the required accuracy for the RWs model, the main characteristics of the RWs that necessitate analysis during the ACS design phase include: technical features, sequence of operating and RW control logic are included in function (behavior) model. A mathematical model is developed including the various errors source. The errors in control torque including relative, absolute, and error due to time delay. While the errors in angular velocity due to differences between average and real speed, resolution error, loose in installation of angular sensor, and synchronization errors. The friction torque is presented in the model include the different feature of friction phenomena: steady velocity friction, static friction and break-away torque, and frictional lag. The model response is compared with the experimental torque and frequency-response characteristics of tested RWs. Based on the created RW model, some criteria of optimization based control torque allocation problem can be recommended like: avoiding the zero speed crossing, bias angular velocity, or preventing wheel from running on the same angular velocity.

Keywords: friction torque, reaction wheels modeling, software in the loop, spacecraft attitude control

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Authors: Shabina Khan, Rukhsana Tabassum Syeda

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Islamic banking is a finance system based on the principles of Shariah law. Charging interest is prohibited in Islam. Instead of charging interest the lender shares some part of profit or loss with the borrower, there is a great need for Islamic banking after the collapse of leading Wall Street institutions notably Lehman Brothers and other global finance institution, economic recession, Islamic banking have emerged as an alternative to conventional banking. Islamic banking is growing at the rate of more than 15% not only in Muslim countries, but also in secular and modern industrialized countries like U.K. Japan, France, Singapore, Hongkong. India with a total population of about 184 million about $ 1.5% Muslim deposit interest is lying unclaimed in different Indian banks, as there are no banks based on shariah laws approved by the RBI. When we take the example of Kerala state in India, almost 26.2% population is Muslim. Thus thousands of crore of rupees earned in interest is suspended accounts. In Kerala alone Rs. 40,000 crore and in Jammu and Kashmir Rs. 50,000 crore as interest earned on deposit of Muslim are lying unclaimed. By 2050, Indian Muslim population would be the largest in the world. It will surpass Indonesia. The Muslim population is likely to exceed 18% i.e. 310 mn. Muslim population will increase four percentage points from 14% to 18%. This paper studies the problems and prospects of Islamic banking in India. India has 29 states and Maharashtra is one of them. In the Maharashtra state is Aurangabad district. According to census 2011, Aurangabad city population is 51.07% is Hindu .Muslim is the second most popular religion with approximately 30.79. There are branches of Islamic banking run by Anjuman e Islam in many parts of India by the name of Al- Khair Baitul Mal which is a nongovernment organization. Its branch is in Aurangabad. The main objectives of this study are: 1. To find the scope of Islamic banking. 2. To study and analyze the prospects and problems of such organizations in Aurangabad district. 3. To create awareness about Islamic banking. 4. To study the functions of the organizations based on Islamic banking rules. 5. To encourage non-Muslims to invest in Islamic banking. The methodology used will be primary as well as secondary data. This is helping the weaker section of the society to obtain sources for trade and business. This paper finds that there is sufficient scope of Islamic banking in the region.

Keywords: Aurangabad, conventional banking, Islamic banking, Riba (interest)

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Authors: Jae-Hyung Jin, Kyung-Tae Lee, Yee-Seul So, Eunji Jeong, Yeonseon Lee, Dongpil Lee, Dong-Gi Lee, Yong-Sun Bahn

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Cryptococcus neoformans causes cryptococcal meningoencephalitis mainly in immunocompromised patients as well as immunocompetent people. But therapeutic options are limited to treat cryptococcosis. Some signaling pathways including cyclic AMP pathway, MAPK pathway, and calcineurin pathway play a central role in the regulation of the growth, differentiation, and virulence of C. neoformans. To understand signaling networks regulating the virulence of C. neoformans, we selected the 114 putative phosphatase genes, one of the major components of signaling networks, in the genome of C. neoformans. We identified putative phosphatases based on annotation in C. neoformans var. grubii genome database provided by the Broad Institute and National Center for Biotechnology Information (NCBI) and performed a BLAST search of phosphatases of Saccharomyces cerevisiae, Aspergillus nidulans, Candida albicans and Fusarium graminearum to Cryptococcus neoformans. We classified putative phosphatases into 14 groups based on InterPro phosphatase domain annotation. Here, we constructed 170 signature-tagged gene-deletion strains through homologous recombination methods for 91 putative phosphatases. We examined their phenotypic traits under 30 different in vitro conditions, including growth, differentiation, stress response, antifungal resistance and virulence-factor production.

Keywords: human fungal pathogen, phosphatase, deletion library, functional genomics

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Authors: Al Huuskonen, Clio Lake, K. M. Naude, Polina Petlitsyna, Sorsha Henning, Julia Wimmers-Klick

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This project presents the outcomes of a community-based participatory action initiative aimed at advocating for equitable healthcare and human rights for trans, two-spirit, and gender-diverse individuals, building upon the University of British Columbia (UBC) Trans Coalition's ongoing efforts. Participatory Action Research (PAR) was chosen as the research method with the goal of improving trans rights on the UBC campus, particularly regarding equitable access to healthcare. PAR involves active community contribution throughout the research process, which in this case was done by way of liaising with student resource groups and advocacy leaders. The goals of this project were as follows: a) identify gaps in gender-affirming healthcare for UBC students by consulting the community and collaborating with UBC services, b) develop an information package outlining provincial and university-based health insurance for gender-affirming care (including hormone therapy and surgeries), FAQs, and resources for UBC's trans students, c) make this package available to UBC students and other national transgender advocacy organizations. The initiative successfully expanded the UBC AMS Student Health and Dental Plan to include gender-affirming procedural coverage, developed a care access guide for students, and advocated for improved health records inclusivity, mechanisms for trans students to report negative care experiences, and increased access to gender-affirming primary care through the on-campus health clinic. Collaboration with other universities' pride organizations and Trans Care BC yielded positive outcomes through broader coalition building and resource sharing. Ongoing efforts are underway to update provincial policies, particularly through expanding coverage under fair pharma care and addressing the compounding effects of the primary care crisis for trans individuals. The project's tangible results include improved trans rights on campus, especially in terms of healthcare access. Expanding healthcare coverage through student care benefits thousands of students, making the ability to undergo important affirming procedures more affordable. Providing students with information on extended coverage options and communication with their doctors further removes barriers to care and positively impacts student wellbeing. This initiative demonstrates the effectiveness of community-based participatory action in advancing equitable healthcare for trans and gender-diverse individuals and serves as a model for other institutions and organizations striving to promote inclusivity and advocate for marginalized populations' rights.

Keywords: equitable healthcare, trans and gender-diverse individuals, inclusivity, participatory action research project

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Authors: N. Mansouri, A. Asadi

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Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.

Keywords: data grid, data replication, simulation, replica selection, replica placement

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Authors: Aarnav Singh, Jatin Moolchandani

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The proposed research work aims to build a query-based AI chatbot that can answer any question related to any topic. A chatbot is software that converses with users via text messages. In the proposed system, we aim to build a chatbot that generates a response based on the user’s query. For this, we use natural language processing to analyze the query and some set of texts to form a concise answer. The texts are obtained through web-scrapping and filtering all the credible sources from a web search. The objective of this project is to provide a chatbot that is able to provide simple and accurate answers without the user having to read through a large number of articles and websites. Creating an AI chatbot that can answer a variety of user questions on a variety of topics is the goal of the proposed research project. This chatbot uses natural language processing to comprehend user inquiries and provides succinct responses by examining a collection of writings that were scraped from the internet. The texts are carefully selected from reliable websites that are found via internet searches. This project aims to provide users with a chatbot that provides clear and precise responses, removing the need to go through several articles and web pages in great detail. In addition to exploring the reasons for their broad acceptance and their usefulness across many industries, this article offers an overview of the interest in chatbots throughout the world.

Keywords: Chatbot, Artificial Intelligence, natural language processing, web scrapping

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Authors: Hossain A., Chowdhury S. I.

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Introduction: The use of a gamma camera is a standard procedure in nuclear medicine facilities or hospitals to diagnose chronic kidney disease (CKD), but the gamma camera does not precisely stage the disease. The authors sought to determine whether they could use an artificial neural network to determine whether CKD was in normal or abnormal stages based on GFR values (ANN). Method: The 250 kidney patients (Training 188, Testing 62) who underwent an ultrasonography test to diagnose a renal test in our nuclear medical center were scanned using a gamma camera. Before the scanning procedure, the patients received an injection of ⁹⁹ᵐTc-DTPA. The gamma camera computes the pre- and post-syringe radioactive counts after the injection has been pushed into the patient's vein. The artificial neural network uses the softmax function with cross-entropy loss to determine whether CKD is normal or abnormal based on the GFR value in the output layer. Results: The proposed ANN model had a 99.20 % accuracy according to K-fold cross-validation. The sensitivity and specificity were 99.10 and 99.20 %, respectively. AUC was 0.994. Conclusion: The proposed model can distinguish between normal and abnormal stages of CKD by using an artificial neural network. The gamma camera could be upgraded to diagnose normal or abnormal stages of CKD with an appropriate GFR value following the clinical application of the proposed model.

Keywords: artificial neural network, glomerular filtration rate, stages of the kidney, gamma camera

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Authors: Chinasa U. Imo, Queen Chikwendu, Jonathan Ajuma, Mario Banuelos

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Background: Sociocultural norms primarily influence the health-seeking behavior of populations in rural communities. In the Nkporo community, Abia State, Nigeria, their sociocultural perception of diseases runs counter to biomedical definitions, wherein they rely heavily on traditional medicine and practices. In a state where birth asphyxia and sepsis account for the significant causes of death for neonates, malaria leads to the causes of other mortalities, followed by common preventable diseases such as diarrhea, pneumonia, acute respiratory tract infection, malnutrition, and HIV/AIDS. Most local mothers attribute their health conditions and that of their children to witchcraft attacks, the hand of God, and ancestral underlining. This influences how they see antenatal and postnatal care, choice of place of accessing care and birth delivery, response to children's illnesses, immunization, and nutrition. Method: To implement a community health improvement program, we adopted an asset-based community development model to address health's normative and social determinants. The first step was to use a qualitative approach to conduct a community health needs baseline assessment, involving focus group discussions with twenty-five (25) youths aged 18-25, semi-structured interviews with ten (10) officers-in-charge of primary health centers, eight (8) ward health committee members, and nine (9) community leaders. Secondly, we designed an intervention program. Going forward, we will proceed with implementing and evaluating this program. Result: The priority needs identified by the communities were malaria, lack of clean drinking water, and the need for behavioral change information. The study also highlighted the significant influence of youths on their peers, family, and community as caregivers and information interpreters. Based on the findings, the NGO SieDi-Hub collaborated with the Abia State Ministry of Health, the State Primary Healthcare Agency, and Empower Next Generations to design a one-year "Community Health Youth Champions Pilot Program." Twenty (20) youths in the community were trained and equipped to champion a participatory approach to bridging the gap between access and delivery of primary healthcare, to adjust sociocultural norms to improve health equity for people in Nkporo community – with limited education, lack of access to health information, and quality healthcare facilities using an innovative community-led improvement approach. Conclusion: Youths play a vital role in achieving health equity, being a vulnerable population with significant influence. To ensure effective primary healthcare, strategies must include cultural humility. The asset-based community development model offers valuable tools, and this article will share ongoing lessons from the intervention's behavioral change strategies with young people.

Keywords: asset-based community development, community health, primary health systems strengthening, youth empowerment

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Authors: Septiawan A. Saputro, Purnami Widyaningsih, Sutanto Sastraredja

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Measles is a disease which can spread caused by a virus and has been a priority’s Ministry of Health in Indonesia to be solved. Each infected person can be recovered and get immunity so that the spread of the disease can be constructed with susceptible infected recovered (SIR). To prevent the spread of measles transmission, the Ministry of Health holds vaccinations program. The aims of the research are to derive susceptible vaccinated infected recovered (SVIR) model, to determine the patterns of disease spread with SVIR model, and also to apply the SVIR model on the spread of measles in Indonesia. Based on the article, it can be concluded that the spread model of measles with vaccinations, that is SVIR model. It is a first-order differential equation system. The patterns of disease spread is determined by solution of the model. Based on that model Indonesia will be a measles-free nation in 2186 with the average of vaccinations scope about 88% and the average score of vaccinations failure about 4.9%. If it is simulated as Ministry of Health new programs with the average of vaccinations scope about 95% and the average score of vaccinations failure about 3%, then Indonesia will be a measles-free nation in 2184. Even with the average of vaccinations scope about 100% and no failure of vaccinations, Indonesia will be a measles-free nation in 2183. Indonesia’s target as a measles-free nation in 2020 has not been reached.

Keywords: measles, vaccination, susceptible infected recovered (SIR), susceptible vaccinated infected recovered (SVIR)

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Authors: Abigail Parra Parra, Jorge L. Morelos Hernandez, Pedro A. Marquez Agilar, Marina Vlasova, Jesus Colin De La Cruz

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Carbothermal reduction of metal oxides is widely used both in metallurgical processes and in the production of oxygen-free refractory ceramics. As a rule, crushed coke and graphite are used as a reducing agent. The products of carbonization of organic compounds are among the innovative reducing agents. The aim of this work was to study the process of reduction of iron oxide (hematite) down to iron by waste active sludge (WAS) carbonization products. WAS was chosen due to the accumulation of a large amount of this type of waste, soil pollution, and the relevance of the development of technologies for its disposal. The studies have shown that the temperature treatment of mixtures WAS-Fe₂O₃ in the temperature range 900-1000 ºC for 1-5 hours under oxygen deficiency is described by the following scheme: WAS + Fe₂O₃→ C,CO + Fe₂O₃→ C + FexO → Fe (amorphous and crystalline). During the heat treatment of the mixtures, strong samples are formed. The study of the electrical conductive properties of such samples showed that, depending on the ratio of the components in the initial mixtures, it is possible to change the values of electrical resistivity from 5.6 Ω‧m to 151.6 Ω‧m When a current is passed through the samples, they are heated from 240 to 378ºC. Thus, based on WAS-Fe₂O₃ mixtures, heating elements can be created that can be used to heat ceramics and concrete.

Keywords: Fe₂O₃, reduction, waste activate sludge, electroconductivity

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Authors: Masoud Shahmanzari

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The aim of this paper is to present a Variable Neighborhood Search (VNS) with Tabu Search (TS) conditions for the Roaming Salesman Problem (RSP). The RSP is a special case of the well-known traveling salesman problem (TSP) where a set of cities with time-dependent rewards and a set of campaign days are given. Each city can be visited on any day and a subset of cities can be visited multiple times. The goal is to determine an optimal campaign schedule consist of daily open/closed tours that visit some cities and maximizes the total net benefit while respecting daily maximum tour duration constraints and the necessity to return campaign base frequently. This problem arises in several real-life applications and particularly in election logistics where depots are not fixed. We formulate the problem as a mixed integer linear programming (MILP), in which we capture as many real-world aspects of the RSP as possible. We also present a hybrid metaheuristic algorithm based on a VNS with TS conditions. The initial feasible solution is constructed via a new matheuristc approach based on the decomposition of the original problem. Next, this solution is improved in terms of the collected rewards using the proposed local search procedure. We consider a set of 81 cities in Turkey and a campaign of 30 days as our largest instance. Computational results on real-world instances show that the developed algorithm could find near-optimal solutions effectively.

Keywords: optimization, routing, election logistics, heuristics

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Authors: Hyun-Ju Oh, Soon-Rim Suh, Mihan Kim

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The steady and rapid increase of the older population is a global phenomenon. Chronic diseases and disabilities are increased due to aging. In general, exercise has been known to be most effective in preventing and managing chronic back pain. However, it is hard for the older women to initiate and maintain the exercise. Transtheoretical model (TTM) is one of the theories explain behavioral changes such as exercise. The application of the program considering the stage of behavior change is effective for the elderly woman to start and maintain the exercise. The purpose of this study was to develop TTM based exercise program and to examine its effect for elderly women with chronic back-pain. For the program evaluation, the non-equivalent control pre-posttest design was applied. The independent variable of this study is exercise intervention program. The contents of the program were constructed considering the characteristics of the elderly women with chronic low back pain, focusing on the process of change, the stage of change by the previous studies. The developed exercise program was applied to the elderly women with chronic low back pain in the planning stage and the preparation stage. The subjects were 50 older women over 65 years of age with chronic back-pain who did not practice regular exercise. The experimental group (n=25) received the 8weeks TTM based exercise program. The control group received the book which named low back pain management. Data were collected at three times: before the exercise intervention, right after the intervention, and 4weeks after the intervention. The dependent variables were the processes of change, decisional balance, exercise self-efficacy, back-pain, depression and muscle strength. The results of this study were as follows. Processes of change (<.001), pros of decisional balance (<.001), exercise self-efficacy (<.001), back pain (<.001), depression (<.001), muscle strength (<.001) were higher in the experimental group than in the control group right after the program and 4weeks after the programs. The results of this study show that applying the TTM based exercise program increases the use of the change process, increases the exercise self-efficacy, increases the stage of changing the exercise behavior and strengthens the muscular strength by lowering the degree of pain and depression Respectively. The significance of the study was to confirm the effect of continuous exercise by maintaining regular exercise habits by applying exercise program of the transtheoretical model to the chronic low back pain elderly with exercise intention.

Keywords: chronic back pain, elderly, exercise, women

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Authors: Cory B. Portner, Julie A. Grauert, Lisa M. Stromme, Shelby D. Anderson, Franji H. Mayes

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Introduction: WASHINGTON state in the Pacific Northwest of the United States is internationally known for its technology industry, fisheries, agriculture, and vistas. On January 21, 2020, Washington state also became known as the first state with a confirmed COVID-19 case in the United States, thrusting the state into the international spotlight as the world came to grips with the global threat of this disease presented. Tourism is Washington state’s fourth-largest industry. Tourism to the state generates over 1.8 billion dollars (USD) in local and state tax revenue and employs over 180,000 people. Communicating with residents, stakeholders, and visitors on the status of disease activity, prevention measures, and response updates was vital to stopping the pandemic and increasing compliance and awareness. Significance: In order to communicate vital public health updates, guidance implementation, and safety measures to the public, the Washington State Department of Health established routine live virtual media briefings to reach audiences via social media, internet television, and broadcast television. Through close partnership with regional broadcast news stations and the state public affairs news network, the Washington State Department of Health hosted 95 media briefings from January 2020 through September 2022 and continues to regularly host live virtual media briefings to accommodate the needs of the public and media. Methods: Our methods quickly evolved from hosting briefings in the cement closet of a military base to being able to produce and stream the briefings live from any home-office location. The content was tailored to the hot topic of the day and to the reporter's questions and needs. Virtual media briefings hosted through inexpensive or free platforms online are extremely cost-effective: the only mandatory components are WiFi, a laptop, and a monitor. There is no longer a need for a fancy studio or expensive production software to achieve the goal of communicating credible, reliable information promptly. With minimal investment and a small learning curve, facilitators and panelists are able to host highly produced and engaging media availabilities from their living rooms. Results: The briefings quickly developed a reputation as the best source for local and national journalists to get the latest and most factually accurate information about the pandemic. In the height of the COVID-19 response, 135 unique media outlets logged on to participate in the briefing. The briefings typically featured 4-5 panelists, with as many as 9 experts in attendance to provide information and respond to media questions. Preparation was always a priority: Public Affairs staff for the Washington State Department of Health produced over 170 presenter remarks, including guidance on talking points for 63 expert guest panelists. Implication For Practice: Information is today’s most valuable currency. The ability to disseminate correct information urgently and on a wide scale is the most effective tool in crisis communication. Due to our role as the first state with a confirmed COVID-19 case, we were forced to develop the most accurate and effective way to get life-saving information to the public. The cost-effective, web-based methods we developed can be applied in any crisis to educate and protect communities under threat, ultimately saving lives from a laptop.

Keywords: crisis communications, public relations, media management, news media

Procedia PDF Downloads 168

Authors: Ling-Lang Huang, Yih-Jer Wu

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Empathy is crucial for a patient-physician relationship and medical professionalism. Internet activity, gaming, or even addiction, have been more and more common among medical students. However, there’s been no report showing whether internet behavior has a substantial impact on empathy in medical students to our best knowledge. All year-2 medical students taking the optional course 'Narrative, Comprehension, and Communication' were enrolled. Internet behaviors are divided into two groups, 'internet users without online gaming (IU)' and 'internet users with online gaming (IG)', each group was further divided into 3 groups according to their average online retention time each day (< 2, 2 - 6, > 6 hours). Empathy was evaluated by the scores of the reports and humanities reflection after watching indicated movies, and by self-measured empathy questionnaire. All students taking the year-2 optional course 'Narrative, Comprehension, and Communication' were enrolled. As compared with students in the IU group, those in the IG group had significantly lower scores for the reports (81.3 ± 3.7 vs. 86.4 ± 5.1, P = 0.014). If further dividing the students into 5 groups (IU < 2, IU 2-6, IG < 2, IG 2 - 6, and IG > 6 hours), the scores were significantly and negatively correlated to online gaming with longer hours (r = -0.556, P = 0.006). However, there was no significant difference between IU and IG groups (33.0 ± 5.4 vs. 34.8 ± 3.2, P = n.s.), in terms of scores in the self-measured empathy questionnaire, neither was there any significant trend of scores along with longer online hours across the 5 groups (r = -0.164, P = n.s.). To date, there has been no evidence showing whether different internet behaviors (with or without online gaming) have distinct impacts on empathy. Although all of the medical students had a similarly good self-perception for empathy, our data suggested that online gaming did have a negative impact on their actual expression of empathy. Our observation has brought up an important issue for pondering: May IT- or gaming-assisted medical learning actually harm students’ empathy? In conclusion, this data suggests that long hours of online gaming harms expression of empathy, though all medics think themselves a person of high empathy.

Keywords: empathy. Internet, medical students, online gaming

Procedia PDF Downloads 121

Authors: Ghebremedhin Tsegay, Weldu Tesfagaber, Yuanmao Zhu, Xijun He, Wan Wang, Zhenjiang Zhang, Encheng Sun, Jinya Zhang, Yuntao Guan, Fang Li, Renqiang Liu, Zhigao Bu, Dongming Zhao*

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African swine fever (ASF) is a highly infectious viral disease of pigs, resulting in significant economic loss worldwide. As there is no approved vaccines and treatments, the control of ASF entirely depends on early diagnosis and culling of infected pigs. Thus, highly specific and sensitive diagnostic assays are required for accurate and early diagnosis of ASF virus (ASFV). Currently, only a few recombinant proteins have been tested and validated for use as reagents in ASF diagnostic assays. The most promising ones for ASFV antibody detection were p72, p30, p54, and pp62. So far, three ELISA kits based on these recombinant proteins have been commercialized. Due to the complex nature of the virus and variety forms of the disease, robust serodiagnostic assays are still required. ASFV p22 protein, encoded by KP177R gene, is located in the inner membrane of viral particle and appeared transiently in the plasma membrane early after virus infection. The p22 protein interacts with numerous cellular proteins, involved in processes of phagocytosis and endocytosis through different cellular pathways. However, p22 does not seem to be involved in virus replication or swine pathogenicity. In this study, E.coli expressed recombinant p22 protein was used to generate a monoclonal antibody (mAb), and its potential use for the development of blocking ELISA (bELISA) was evaluated. A total of 806 pig serum samples were tested to evaluate the bELISA. Acording the ROC (Reciever operating chracteristic) analysis, 100% sensitivity and 98.10% of specificity was recorded when the PI cut-off value was set at 47%. The novel assay was able to detect the antibodies as early as 9 days post infection. Finaly, a highly sensitive, specific and rapid novel p22-mAb based bELISA assay was developed, and optimized for detection of antibodies against genotype I and II ASFVs. It is a promising candidate for an early and acurate detection of the antibodies and is highly expected to have a valuable role in the containment and prevention of ASF.

Keywords: ASFV, blocking ELISA, diagnosis, monoclonal antibodies, sensitivity, specificity

Procedia PDF Downloads 67

Authors: Schnell Zsuzsanna

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Background: The interpretation of written texts, language processing in the visual domain, in other words, atypical reading abilities, also known as dyslexia, is an ever-growing phenomenon in today’s societies and educational communities. The much-researched problem affects cognitive abilities and, coupled with normal intelligence normally manifests difficulties in the differentiation of sounds and orthography and in the holistic processing of written words. The factors of susceptibility are varied: social, cognitive psychological, and linguistic factors interact with each other. Methods: The research will explain the psycholinguistics of dyslexia on the basis of several empirical experiments and demonstrate how domain-general abilities of inhibition, retrieval from the mental lexicon, priming, phonological processing, and visual modality transfer affect successful language processing and interpretation. Interpretation of visual stimuli is hindered, and the problem seems to be embedded in a sociocultural, psycholinguistic, and cognitive background. This makes the picture even more complex, suggesting that the understanding and resolving of the issues of dyslexia has to be interdisciplinary, aided by several disciplines in the field of humanities and social sciences, and should be researched from an empirical approach, where the practical, educational corollaries can be analyzed on an applied basis. Aim and applicability: The lecture sheds light on the applied, cognitive aspects of interpretation, social cognitive traits of language processing, the mental underpinnings of cognitive interpretation strategies in different languages (namely, Hungarian and English), offering solutions with a few applied techniques for success in foreign language learning that can be useful advice for the developers of testing methodologies and measures across ESL teaching and testing platforms.

Keywords: dyslexia, social cognition, transparency, modalities

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Authors: Sevde D. Karayel, Ediz Atmaca

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Supplier selection subject is vital because of development competitiveness and performance of firms which have right, rapid and with low cost procurement. Considering the fact that competition between firms is no longer on their supply chains, hence it is very clear that performance of the firms’ not only depend on their own success but also success of all departments in supply chain. For this purpose, firms want to work with suppliers which are cost effective, flexible in terms of demand and high quality level for customer satisfaction. However, diversification and redundancy of their expectations from suppliers, supplier selection problems need to be solved as a hard problem. In this study, supplier selection problem is discussed for critical piece, which is using almost all production of products in and has troubles with lead time from supplier, in a firm that produces medical devices. Analyzing policy in the current situation of the firm in the supplier selection indicates that supplier selection is made based on the purchasing department experience and other authorized persons’ general judgments. Because selection do not make based on the analytical methods, it is caused disruptions in production, lateness and extra cost. To solve the problem, AHP and TOPSIS which are multi-criteria decision making techniques, which are effective, easy to implement and can analyze many criteria simultaneously, are used to make a selection among alternative suppliers.

Keywords: AHP-TOPSIS methods, multi-criteria decision making, supplier selection problem, supply chain management

Procedia PDF Downloads 250

Authors: N. P. Patidar, J. Earnest, Laxmikant Nagar, Akshay Sharma

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This paper describes the diligence of a new input signal based fuzzy power system stabilizer in multi-machine power system. Instead of conventional input pairs like speed deviation (∆ω) and derivative of speed deviation i.e. acceleration (∆ω ̇) or speed deviation and accelerating power deviation of each machine, in this paper, deviation of active power through the tie line colligating two areas is used as one of the inputs to the fuzzy logic controller in concurrence with the speed deviation. Fuzzy Logic has the features of simple concept, easy effectuation, and computationally efficient. The advantage of this input is that, the same signal can be fed to each of the fuzzy logic controller connected with each machine. The simulated system comprises of two fully symmetrical areas coupled together by two 230 kV lines. Each area is equipped with two superposable generators rated 20 kV/900MVA and area-1 is exporting 413 MW to area-2. The effectiveness of the proposed control scheme has been assessed by performing small signal stability assessment and transient stability assessment. The proposed control scheme has been compared with a conventional PSS. Digital simulation is used to demonstrate the performance of fuzzy logic controller.

Keywords: Power System Stabilizer (PSS), small signal stability, inter-area oscillation, fuzzy logic controller, membership function, rule base

Procedia PDF Downloads 512

Authors: Dai Yizheng, Chen-Yang Zhang

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As station-city integration has been widely accepted as a strategy for mixed-use development, a quantitative analysis of the functional characteristics of urban complexes based on station-city integration is urgently needed. Taking 15 railway stations in European, North American, and East Asian cities as the research objects, this study analyzes their functional proportion, functional positioning, and functional correlation with respect to four categories of functional facilities for both railway passenger flow and subway passenger flow. We found that (1) the functional proportion of urban complexes was mainly concentrated in three models: complementary, dominant, and equilibrium. (2) The mathematical model affected by the functional proportion was created to evaluate the functional positioning of an urban complex at three scales: station area, city, and region. (3) The strength of the correlation between the functional area and passenger flow was revealed via data analysis using Pearson’s correlation coefficient. Finally, the findings of this study provide a valuable reference for research on similar topics in other countries that are developing station-city integration.

Keywords: urban complex, station-city integration, mixed-use, function, quantitative analysis

Procedia PDF Downloads 97

Authors: Agada N. Ihuoma, Nagata Yasunori

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Artificial intelligence (AI) techniques play a crucial role in predicting the expected energy outcome and its performance, analysis, modeling, and control of renewable energy. Renewable energy is becoming more popular for economic and environmental reasons. In the face of global energy consumption and increased depletion of most fossil fuels, the world is faced with the challenges of meeting the ever-increasing energy demands. Therefore, incorporating artificial intelligence to predict solar radiation outcomes from the intermittent sunlight is crucial to enable a balance between supply and demand of energy on loads, predict the performance and outcome of solar energy, enhance production planning and energy management, and ensure proper sizing of parameters when generating clean energy. However, one of the major problems of forecasting is the algorithms used to control, model, and predict performances of the energy systems, which are complicated and involves large computer power, differential equations, and time series. Also, having unreliable data (poor quality) for solar radiation over a geographical location as well as insufficient long series can be a bottleneck to actualization. To overcome these problems, this study employs the anaconda Navigator (Jupyter Notebook) for machine learning which can combine larger amounts of data with fast, iterative processing and intelligent algorithms allowing the software to learn automatically from patterns or features to predict the performance and outcome of Solar Energy which in turns enables the balance of supply and demand on loads as well as enhance production planning and energy management.

Keywords: artificial Intelligence, backward elimination, linear regression, solar energy

Procedia PDF Downloads 150

Authors: Danny Fraser, James Zhang

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Aim of the study: Our study aims to identify any statistically significant evidence as it relates to PROMs for mastectomy and implant-based reconstruction to guide future surgical management. Method: The demographic, pre and post-operative treatment and implant characteristics were collected of all patients at Basildon hospital who underwent breast reconstruction from 2017-2023. We used the Breast-Q psychosocial well-being, physical well-being, and satisfaction with breasts scales. An Independent t-test was conducted for each group, and linear regression of age and implant size. Results: 69 patients were contacted, and 39 PROMs returned. The mean age of patients was 57.6. 40% had smoked before, and 40.8% had BMI>30. 29 had pre-pectoral placement, and 40 had subpectoral placement. 17 had smooth implants, and 52 textured. Sub pectoral placement was associated with higher (75.7 vs. 61.9 p=0.046) psychosocial scores than pre pectoral, and textured implants were associated with a lower physical score than the smooth surface (34.7 VS 50.2 P=0.046). On linear regression, age was positively associated (p=0.007) with psychosocial score. Conclusion: We present a large cohort of patients who underwent breast reconstruction. Understanding the PROMs of these procedures can guide clinicians, patients and policy makers to be more informed of the course of rehabilitation of these operations. Significance: We have found that from a patient perspective subpectoral implant placement was associated with a statistically significant improvement in psychosocial scores.

Keywords: breast surgery, mastectomy, breast implants, oncology

Procedia PDF Downloads 45