Search results for: supersonic stage

Authors: Aksana N. Popel, Volha A. Sujayeva, Olga V. Kоshlataja, Irеna S. Karpava

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Introduction: It is a known fact that cardiovascular pathology and its complications cause a more severe course and worse prognosis in patients with comorbid kidney pathology. Chronic kidney disease (CKD) is associated with inflammation, endothelial dysfunction, and increased activity of the sympathoadrenal system. This circumstance increases the risk of cardiovascular diseases and the progression of kidney pathology. The above determines the need to identify cardiorenal changes at early stages to reduce the risks of cardiovascular complications and the progression of CKD. Objective: To identify risk factors (RF) for the development of CKD in elderly patients with chronic ischemic heart disease (CIHD). Methods: The study included 64 patients (40 women and 24 men) with a mean age of 74.4±4.5 years with coronary heart disease, without a history of structural kidney pathology and CKD. All patients underwent transthoracic echocardiography (TTE) and kidney ultrasound (KU) using GE Vivid 9 equipment (GE HealthCare, USA), and cardiac computed tomography (CCT) using Siemens Somatom Force equipment (Siemens Healthineers AG, Germany) in 3 months and in 1 year. Data obtained were analyzed using multiple regression analysis and nonparametric Mann-Whitney test. Statistical analysis was performed using the STATISTICA 12.0 program (StatSoft Inc.). Results: Initially, CKD was not diagnosed in all patients. In 3 months, CKD was diagnosed: stage C1 had 11 people (18%), stage C2 had 4 people (6%), stage C3A had 11 people (18%), stage C3B had 2 people (3%). After 1 year, CKD was diagnosed: stage C1 had 22 people (35%), stage C2 had 5 people (8%), stage C3A had 17 people (27%), stage C3B had 10 people (15%). In 3 months, statistically significant (p<0.05) risk factors were: 1) according to TTE: mitral peak E-wave velocity (U=678, p=0.039), mitral E-velocity DT (U=514, p=0.0168), mitral peak A-wave velocity (U=682, p=0.013). In 1 year, statistically significant (p<0.05) risk factors were: according to TTE: left ventricular (LV) end-systolic volume in B-mode (U=134, p=0.006), LV end-diastolic volume in B-mode (U=177, p=0.04), LV ejection fraction in B-mode (U=135, p=0.006), left atrial volume (U=178, p=0.021), LV hypertrophy (U=294, p=0.04), mitral valve (MV) fibrosis (U=328, p=0.01); according CCT: epicardial fat thickness (EFT) on the right ventricle (U=8, p=0.015); according to KU: interlobar renal artery resistance index (RI) (U=224, p=0.02), segmental renal artery RI (U=409, p=0.016). Conclusions: Both TTE and KU are very informative methods to determine the additional risk factors of CKD development and progression. The most informative risk factors were LV global systolic and diastolic functions, LV and LA volumes. LV hypertrophy, MV fibrosis, interlobar renal artery and segmental renal artery RIs, EFT.

Keywords: chronic kidney disease, ischemic heart disease, prognosis, risk factors

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Authors: Sumita Srivastava

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Despite several measures taken by the Government of India, entrepreneurship is still not perceived as a viable career option by the young generation. Although the rate of startups has improved a little after the penetration of e portals as business platforms, still the numbers are not very significant. It is also important to note that entrepreneurial initiatives are mostly taken up by graduates of premier institutions of India like Indian Institute of Technology (IITs) and Indian Institute of Management (IIMs). The scenario is not very satisfactory amongst the masses graduating from mainstream universities of the country. Indian youth at large are not attracted towards entrepreneurship as a career choice. The reason probably lies in the social fabric of the country and inappropriate education system which does not support the entrepreneurship at large amongst youth in the country. Education is critical to the development of an economy from the poverty level to the level of self-sustenance and development. The current curriculum in the majority of business schools in India prepares the average graduate to become employed by the available firms or business owners in society. For graduates in other streams, employment opportunities are very limited. The aim of this study was to identify and design entrepreneurship education contents to encourage undergraduates to pursue entrepreneurship as a career choice. This comprehensive study was conducted in multiple stages. Extensive research was conducted at each stage with an appropriate methodology. These stages of the project study were interconnected with each other, and each preceding stage provided inputs for the following stage of the study. In the first stage of the study, an empirical analysis was conducted to understand the current state of entrepreneurial intentions of undergraduates of Agra city. Various stakeholders were contacted at the stage, including students (n = 500), entrepreneurs (n = 20) and academicians and field experts (n = 10). At the second stage of the project study, a systems science technique, Nominal Group Technique (NGT) was used to identify the critical elements of entrepreneurship education in India based upon the findings of stage 1. The application of the Nominal Group Technique involved a workshop format; 15 domain experts participated in the workshop. Throughout the process, a democratic process was followed to avoid individual dominance and premature focusing on a single idea. The study obtained 63 responses from experts for effective entrepreneurship education in India. The responses were reduced to seven elements after a few thematic iterations. These elements were then segregated into content (knowledge, skills and attitude) and learning interaction on the basis of experts’ responses. After identifying critical elements of entrepreneurship education in the previous stage, the course was designed and validated at stage 3 of the project. Scientific methods were used at this stage to validate the curriculum contents and training interventions experimentally. The educational and training interventions designed through this study would not only help in developing entrepreneurial intentions but also creating skills relevant to the local entrepreneurial opportunities in the vicinity.

Keywords: curriculum design, entrepreneurial intention, entrepreneuship education, nominal group technique

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Authors: Dawood Al Chanti, Alice Caplier

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Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

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Authors: S. Neelima, P. S. Subramanyam

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The major tool for distribution planning is load forecasting, which is the anticipation of the load in advance. Artificial neural networks have found wide applications in load forecasting to obtain an efficient strategy for planning and management. In this paper, the application of neural networks to study the design of short term load forecasting (STLF) Systems was explored. Our work presents a pragmatic methodology for short term load forecasting (STLF) using proposed two-stage model of wavelet transform (WT) and artificial neural network (ANN). It is a two-stage prediction system which involves wavelet decomposition of input data at the first stage and the decomposed data with another input is trained using a separate neural network to forecast the load. The forecasted load is obtained by reconstruction of the decomposed data. The hybrid model has been trained and validated using load data from Telangana State Electricity Board.

Keywords: electrical distribution systems, wavelet transform (WT), short term load forecasting (STLF), artificial neural network (ANN)

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Authors: Wong Yat Cheung Maggie

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Occupational Safety and Health Ordinance (OS&HO) (Chap 509) was enacted in 1997, OHS in HK should be growing and maturing, with a holistic approach to occupational health and safety in the workplace including physical, mental, social and spiritual well-being. The question is “How effective are OHSPs in meeting the current needs of HK health workers?” This study was designed to explore the issue for the first time, to empirically analyse the views of those who work in the system. The study employed a mixed method approach to collect various data from Occupational Health Service Providers (OHSPs), Occupational Health Service Consumers (OHSC): Registered nurses working in the hospital setting. This study was designed in two phases and two stages. Phase I Stage I was a paper survey to collect the data on OHSP. Then Phase I Stage II was a follow-up interview. Phase II Stage I was a paper survey to collect the data on OHSC. Then Phase II Stage II was a follow-up focus group study on OHSC for further clarification of the Phase II and Stage I result. The Phase I result reflects HK OHSPs point of view and their experience in the existing OHS practice in the local hospitals. It reflects various styles of reporting systems, staff profiles background and resource in providing OHS in HK hospitals. However, the basic OHS concern is similar between hospitals. In general, the OHS policies and procedures are available on site even though they may have different foci. The Phase II result is reflecting the HKs OHSCs echoes the OHSP feedback at providing of OHS, OHS concern and related policies and procedure are available on site. However, the most significant feedback from the OHSC at Phase II Stage II shows, nurses experienced various OHS concern most commonly work stress, workplace harassment and back strain without formal or official report to the related parties. The lack of reporting was due to the management handling attitude, stakeholders’ compliance and term of definition still have room to be improved even the related policies and procedures are available on site.

Keywords: occupational health service, registered nurse, Hong Kong hospital, mixed method

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Authors: Jesus Ruano, Asensi Oliva

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The hydrodynamic field generated by a jet expansion is computed via three dimensional compressible Large Eddy Simulation (LES). Finite Volume Method (FVM) will be the discretization used during this simulation as well as hybrid schemes based on Kinetic Energy Preserving (KEP) schemes and up-winding Godunov based schemes with instabilities detectors. Velocity and pressure fields will be stored at different surfaces near the jet, but far enough to enclose all the fluctuations, in order to use them as input for the acoustic solver. The acoustic field is obtained in the far-field region at several locations by means of a hybrid method based on Ffowcs-Williams and Hawkings (FWH) equation. This equation will be formulated in the spectral domain, via Fourier Transform of the acoustic sources, which are modeled from the results of the initial simulation. The obtained results will allow the study of the broadband noise generated as well as sound directivities.

Keywords: far-field noise, Ffowcs-Williams and Hawkings, finite volume method, large eddy simulation, jet noise

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Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

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Authors: Farid Risheq, M. Zaid Alrisheq, Shuaa Al-Sadoon, Karim Al-Faqih, Mays Abdulazeez

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Breast cancer is the most frequently diagnosed cancer worldwide, and a common cause of death among women. Various conventional anatomical imaging tools are utilized for diagnosis, histological assessment and TNM (Tumor, Node, Metastases) staging of breast cancer. Biopsy of sentinel lymph node is becoming an alternative to the axillary lymph node dissection. Advances in 18-Fluoro-Deoxi-Glucose Positron Emission Tomography/Computed Tomography (18FDG-PET/CT) imaging have facilitated breast cancer diagnosis utilizing biological trapping of 18FDG inside lesion cells, expressed as Standardized Uptake Value (SUVmax). Objective: To present the utility of 18FDG uptake PET/CT scans in detecting active extra lymph nodes and distant occult metastases for breast cancer staging. Subjects and Methods: Four female patients were presented with initially classified TNM stages of breast cancer based on conventional anatomical diagnostic techniques. 18FDG-PET/CT scans were performed one hour post 18FDG intra-venous injection of (300-370) MBq, and (7-8) bed/130sec. Transverse, sagittal, and coronal views; fused PET/CT and MIP modality were reconstructed for each patient. Results: A total of twenty four lesions in breast, extended lesions to lung, liver, bone and active extra lymph nodes were detected among patients. The initial TNM stage was significantly changed post 18FDG-PET/CT scan for each patient, as follows: Patient-1: Initial TNM-stage: T1N1M0-(stage I). Finding: Two lesions in right breast (3.2cm2, SUVmax=10.2), (1.8cm2, SUVmax=6.7), associated with metastases to two right axillary lymph nodes. Final TNM-stage: T1N2M0-(stage II). Patient-2: Initial TNM-stage: T2N2M0-(stage III). Finding: Right breast lesion (6.1cm2, SUVmax=15.2), associated with metastases to right internal mammary lymph node, two right axillary lymph nodes, and sclerotic lesions in right scapula. Final TNM-stage: T2N3M1-(stage IV). Patient-3: Initial TNM-stage: T2N0M1-(stage III). Finding: Left breast lesion (11.1cm2, SUVmax=18.8), associated with metastases to two lymph nodes in left hilum, and three lesions in both lungs. Final TNM-stage: T2N2M1-(stage IV). Patient-4: Initial TNM-stage: T4N1M1-(stage III). Finding: Four lesions in upper outer quadrant area of right breast (largest: 12.7cm2, SUVmax=18.6), in addition to one lesion in left breast (4.8cm2, SUVmax=7.1), associated with metastases to multiple lesions in liver (largest: 11.4cm2, SUV=8.0), and two bony-lytic lesions in left scapula and cervicle-1. No evidence of regional or distant lymph node involvement. Final TNM-stage: T4N0M2-(stage IV). Conclusions: Our results demonstrated that 18FDG-PET/CT scans had significantly changed the TNM stages of breast cancer patients. While the T factor was unchanged, N and M factors showed significant variations. A single session of PET/CT scan was effective in detecting active extra lymph nodes and distant occult metastases, which were not identified by conventional diagnostic techniques, and might advantageously replace bone scan, and contrast enhanced CT of chest, abdomen and pelvis. Applying 18FDG-PET/CT scan early in the investigation, might shorten diagnosis time, helps deciding adequate treatment protocol, and could improve patients’ quality of life and survival. Trapping of 18FDG in malignant lesion cells, after a PET/CT scan, increases the retention index (RI%) for a considerable time, which might help localize sentinel lymph node for biopsy using a hand held gamma probe detector. Future work is required to demonstrate its utility.

Keywords: axillary lymph nodes, breast cancer staging, fluorodeoxyglucose positron emission tomography/computed tomography, lymph nodes

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Authors: William Li

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Lane-change path planning is a crucial and yet complex task in autonomous driving. The traditional path planning approach based on a system of carefully-crafted rules to cover various driving scenarios becomes unwieldy as more and more rules are added to deal with exceptions and corner cases. This paper proposes to divide the entire path planning to two stages. In the first stage the ego vehicle travels longitudinally in the source lane to reach a safe state. In the second stage the ego vehicle makes lateral lane-change maneuver to the target lane. The paper derives the safe state conditions based on lateral lane-change maneuver calculation to ensure collision free in the second stage. To determine the acceleration sequence that minimizes the time to reach a safe state in the first stage, the paper proposes three schemes, namely, kinetic model based optimization, deep reinforcement learning, and 5G vehicle-to-vehicle (V2V) communications. The paper investigates these schemes via simulation. The model-based optimization is sensitive to the model assumptions. The deep reinforcement learning is more flexible in handling scenarios beyond the model assumed by the optimization. The 5G V2V eliminates uncertainty in predicting future behaviors of surrounding vehicles by sharing driving intents and enabling cooperative driving.

Keywords: lane change, path planning, autonomous driving, deep reinforcement learning, 5G, V2V communications, connected vehicles

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Authors: Armin Shirbazo, Mohammad Vahab, Hamed Lamei Ramandi, Jalal Fahimpour

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One of the most effective ways for increasing production in wells that are faced with problems such as pressure depletion and low rate is hydraulic fracturing. Hydraulic fracturing is creating a high permeable path through the reservoir and simulated area around the wellbore. This is very important for low permeability reservoirs, which their production is uneconomical. In this study, the influence of the fracturing pattern in multi-stage fractured horizontal wells is analyzed for a tight, heavy oil reservoir to explore the impact of fracturing patterns on improving oil recovery. The horizontal well has five transverse fractures with the same fracture length, width, height, and conductivity properties. The fracture patterns are divided into four distinct shapes: uniform shape, diamond shape, U shape, and W shape. The results show that different fracturing patterns produce various cumulative production after ten years, and the best pattern can be selected based on the most cumulative production. The result also illustrates that optimum design in fracturing can boost the production up to 3% through the permeability distribution around the wellbore and reservoir.

Keywords: multi-stage fracturing, horizontal well, fracture patterns, fracture length, number of stages

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Authors: T. S. Sidhu

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Amongst the existing coatings methods, the cold spray is new upcoming process to deposit coatings. As from the name itself, the cold spray coating takes place at very low temperature as compare to other thermal spray coatings. In all other thermal spray coating process the partial melting of the coating powder particles takes place before deposition, but cold spray process takes place in solid state. In cold spray process, the bonding of coating power with substrate is not metallurgical as in other thermal spray processes. Due to supersonic speed and less temperature of spray particles, solid state, dense, and oxide free coatings are produced. Due to these characteristics, the cold spray coatings have been used to protect the materials against hot corrosion. In the present study, the cold spray process, cold spray fundaments, its types, and its applications for high temperatures are discussed in the light of presently available literature. In addition, the assessment of cold spray with the competitive technologies has been conferred with available literature.

Keywords: cold spray coating, hot corrosion, thermal spray coating, high-temperature materials

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Authors: Moses C. Siame, Kazutoshi Haga, Atsushi Shibayama

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This study investigates the removal of silica, alumina and phosphorus as impurities from Sanje iron ore using wet high-intensity magnetic separation (WHIMS). Sanje iron ore contains low-grade hematite ore found in Nampundwe area of Zambia from which iron is to be used as the feed in the steelmaking process. The chemical composition analysis using X-ray Florence spectrometer showed that Sanje low-grade ore contains 48.90 mass% of hematite (Fe₂O₃) with 34.18 mass% as an iron grade. The ore also contains silica (SiO₂) and alumina (Al₂O₃) of 31.10 mass% and 7.65 mass% respectively. The mineralogical analysis using X-ray diffraction spectrometer showed hematite and silica as the major mineral components of the ore while magnetite and alumina exist as minor mineral components. Mineral particle distribution analysis was done using scanning electron microscope with an X-ray energy dispersion spectrometry (SEM-EDS) and images showed that the average mineral size distribution of alumina-silicate gangue particles is in order of 100 μm and exists as iron-bearing interlocked particles. Magnetic separation was done using series L model 4 Magnetic Separator. The effect of various magnetic separation parameters such as magnetic flux density, particle size, and pulp density of the feed was studied during magnetic separation experiments. The ore with average particle size of 25 µm and pulp density of 2.5% was concentrated using pulp flow of 7 L/min. The results showed that 10 T was optimal magnetic flux density which enhanced the recovery of 93.08% of iron with 53.22 mass% grade. The gangue mineral particles containing 12 mass% silica and 3.94 mass% alumna remained in the concentrate, therefore the concentrate was further treated in the second stage WHIMS using the same parameters from the first stage. The second stage process recovered 83.41% of iron with 67.07 mass% grade. Silica was reduced to 2.14 mass% and alumina to 1.30 mass%. Accordingly, phosphorus was also reduced to 0.02 mass%. Therefore, the two stage magnetic separation process was established using these results.

Keywords: Sanje iron ore, magnetic separation, silica, alumina, recovery

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Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: Henri El Zakhem, Anthony Dahdah, Lara Frangieh, Jessica Koura

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Nowadays, the removal of whey produced in the dairy processes has been the most important problem in the dairy industry. Every year, about 47% of the 115 million tons of whey produced world-wide are disposed in the environment. Whey is a nutritious liquid, containing whey proteins (β-lactoglobulin, α-lactalbumin, immunoglobulin-G, proteose pepton), lactose, vitamins (B5, B2, C, and B6), minerals (Calcium, Magnesium, Phosphorous, Potassium, Chloride, and Sodium), and trace elements (Zinc, Iron, Iodine, and Copper). The first objective was to increase the economical and commercial value of whey which is considered as by-product. The second objective of this study was to formulate a new baby food with good nutritional, sensory and storage properties and acceptable to consumers using the cheese whey. The creation of the new product must pass through the following stages: idea stage, development stage which includes the business planning and the product development prototype, packaging stage, production stage, test marketing stage, quality control/sanitation. Three types of whey-based food were selected and prepared by mixing whey and apple, whey and banana as well as whey, apple, and banana.To compile with the recommended dietary allowances (RDA) and adequate intakes (AI) for vitamins and minerals, each sample is formed from 114g of sliced and smashed fruits mixed with 8 mL of whey. Mixtures are heated to 72oC for 15 seconds, and filled in pasteurized jars. Jars were conserved at 4oC. Following the experimental part, sensory evaluation made by an experienced panel took place. Hedonic tests results show that the mixture of whey, apple, and banana has the most delicious and sweetness taste followed by the mixture of whey and banana, and finally the mixture of whey and apple. This study was concluded with a managerial and engineering study that reveals that the project is economically profitable to be executed in Lebanon.

Keywords: baby food, by-product, cheese whey, formulation

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Authors: Shangqing Song, Bin Xu, Yajun Cheng, Zhong Wang

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miRNAs derived from exosomes exist in a body fluid such as urine were regarded as potential biomarkers for various human cancers diagnosis and prognosis, as mature miRNAs can be steadily preserved by exosomes. However, its potential value in clear cell renal cell carcinoma (ccRCC) diagnosis and prognosis remains unclear. In the present study, differentially expressed miRNAs from urinal exosomes were identified by next-generation sequencing (NGS) technology. The 16 differentially expressed miRNAs were identified between ccRCC patients and healthy donors. To explore the specific diagnosis biomarker of ccRCC, we validated these urinary exosomes from 70 early-stage renal cancer patients, 30 healthy people and other urinary system cancers, including 30 early-stage prostate cancer patients and 30 early-stage bladder cancer patients by qRT-PCR. The results showed that urinary exosome miR-30c-5p could be stably amplified and meanwhile the expression of miR-30c-5p has no significant difference between other urinary system cancers and healthy control, however, expression level of miR-30c-5p in urinary exosomal of ccRCC patients was lower than healthy people and receiver operation characterization (ROC) curve showed that the area under the curve (AUC) values was 0.8192 (95% confidence interval was 0.7388-0.8996, P= 0.0000). In addition, up-regulating miR-30c-5p expression could inhibit renal cell carcinoma cells growth. Lastly, HSP5A was found as a direct target gene of miR-30c-5p. HSP5A depletion reversed the promoting effect of ccRCC growth casued by miR-30c-5p inhibitor, respectively. In conclusion, this study demonstrated that urinary exosomal miR-30c-5p is readily accessible as diagnosis biomarker of early-stage ccRCC, and miR-30c-5p might modulate the expression of HSPA5, which correlated with the progression of ccRCC.

Keywords: clear cell renal cell carcinoma, exosome, HSP5A, miR-30c-5p

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Authors: Loyce Nahwera, Joy Wachira, Edwin Kiptolo, Constance Nsibambi, Mshilla Maghanga, Timothy Makubuya

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Introduction: Hypertension is one of the most prominent risk factors for cardiovascular diseases globally, and it can be modified through lifestyle interventions such as exercise. The objective of this study was to investigate the effects of a 12-week aerobic dance programme on systolic blood pressure (SBP) in stage 1 hypertensive individuals. Methods: This study employed an experimental research design. A total of 36 stage 1 hypertensive individuals who were randomly assigned into experimental and control groups completed the study. Systolic BP was measured using a mercury sphygmomanometer at baseline, mid-point and after the program. The experimental group participants trained 3 days a week, 45 minutes per session, at a moderate intensity of 40-60% of maximum oxygen consumption (VO2max) monitored by Garmin heart rate monitors. Data were analyzed using SPSS version 20. The significance level was set at p<0.05. A paired sample t-test was used to compare mean differences within the groups. Results: Data from the 36 participants (22 males and 14 females) (experimental; n=18, control; n=18) show that the experimental group had a mean SBP of 143.83±6.382 mmHg at baseline while the control had a mean of 137.61±6.400 mmHg. Following the end of a 6-week aerobic dance, the mean SBP of the experimental group reduced to 138.06±9.539 mmHg while that of the control marginally decreased to 137.00±8.073 mmHg. At the completion of a 12-week program, the mean SBP of the experimental group reduced to 136.33±9.191 mmHg, while that of the control marginally increased to 139.56±9.954 mmHg. This implies that both the 6-week and 12-week aerobic dance program reduced the SBP of the experimental group by 5.77±7.133 mmHg and 7.50±8.487 mmHg, respectively, while the control group fast reduced marginally by 0.61 before ultimately increasing by 1.95±7.974 mmHg at 12-weeks. The changes were statistically significant (p<0.05) at both 6 and 12 weeks of an aerobic dance program. Conclusion: The study concluded that aerobic dance is an effective non-pharmacological method for managing SBP of stage 1 hypertensive individuals both in the short-term (6 weeks) and long-term (12 weeks).

Keywords: aerobic dance, blood pressure, stage 1 hypertension, systolic blood pressure.

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Authors: Eugene Kogan

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We analytically study the localized running waves in the discrete Josephson transmission lines (JTL), constructed from Josephson junctions (JJ) and capacitors. The quasi-continuum approximation reduces the calculation of the running wave properties to the problem of equilibrium of an elastic rod in the potential field. Making additional approximations, we reduce the problem to the motion of the fictitious Newtonian particle in the potential well. We show that there exist running waves in the form of supersonic kinks and solitons and calculate their velocities and profiles. We show that the nonstationary smooth waves, which are small perturbations on the homogeneous non-zero background, are described by Korteweg-de Vries equation, and those on zero background -by the modified Korteweg-de Vries equation. We also study the effect of dissipation on the running waves in JTL and find that in the presence of the resistors, shunting the JJ and/or in series with the ground capacitors, the only possible stationary running waves are the shock waves, whose profiles are also found.

Keywords: Josephson transmission line, shocks, solitary waves, nonlinear waves

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Authors: YuPei Chang

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In recent years, moral judgement tasks have served as an increasingly popular plot mechanism in digital gameplay. As a moral agency, the player's choice judgment in digital games is to shuttle between the real world and the game world. The purpose of the research is to explore the moral difficulties brewed by the interactive mechanism of the game and the moral choice of players. In the theoretical level, this research tries to combine moral disengagement, moral foundations theory, and gameplay as an aesthetic experience. And in the methodical level, this research tries to use methods that combine text analysis, diary method, and in-depth interviews. There are three research problems that will be solved in three stages. In the first stage, this project will explore how moral dilemmas are represented in game mechanics. In the second stage, this project will analyze the appearance and conflicts of moral dilemmas in game mechanics based on the five aspects of moral foundations theory. In the third stage, this project will try to understand the players' choices when they face the choices of moral dilemmas, as well as their explanations and reflections after making the decisions.

Keywords: morality, moral disengagement, moral foundations theory, PC game, gameplay, moral dilemmas, player

Procedia PDF Downloads 79

Authors: Amanda Abbott-Jones

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Adult students with dyslexia can receive support for cognitive needs but may also experience anxiety, which is less understood. This study aims to test the hypothesis that dyslexic learners in higher education have a higher prevalence of academic and social anxiety than their non-dyslexic peers and explores wider emotional consequences of studying with dyslexia and the ways that adults with dyslexia cope cognitively and emotionally. A mixed-method approach was used in two stages. Stage one compared survey responses from students with dyslexia (N = 102) and students without dyslexia (N = 72) after completion of an anxiety inventory. Stage two explored the emotional consequences of studying with dyslexia and the types of coping strategies used through semi-structured interviews with 20 dyslexic students. Results revealed a statistically significant effect for academic anxiety but not for social anxiety. Findings for stage two showed that: (1) students’ emotional consequences were characterised by a mixture of negative and positive responses, yet negative responses were more frequent in response to questions about academic tasks than positive responses; (2) participants had less to say on coping emotionally, than coping cognitively.

Keywords: dyslexia, higher education, anxiety, emotion

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Authors: K. Srujana, Vinay U. Rao, M. Sudhakar

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Isoniazide (INH) a freely water soluble and pyrazinamide (Z) a practically water insoluble first line anti tubercular (TB) drugs were identified as candidates for optimizing the Moisture Activated Dry Granulation (MADG) process. The work focuses on identifying the effect of binder type and concentration as well as the effect of magnesium stearate level on critical quality attributes of Disintegration time (DT) and in vitro dissolution test when the tablets are processed by the MADG process. Also, the level of the drug concentration, binder concentration and fluid addition during the agglomeration stage of the MADG process was evaluated and optimized. For INH, it was identified that for tablets with HPMC as binder at both 2% w/w and 5% w/w level and Magnesium stearate upto 1%w/w as lubrication the DT is within 1 minute and the dissolution rate is the fastest (> 80% in 15 minutes) as compared to when PVP or pregelatinized starch is used as binder. Regarding the process, fast disintegrating and rapidly dissolving tablets are obtained when the level of drug, binder and fluid uptake in agglomeration stage is 25% w/w 0% w/w binder and 0.033%. w/w. At the other 2 levels of these three ingredients, the DT is significantly impacted and dissolution is also slower. For pyrazinamide,it was identified that for the tablets with 2% w/w level of each of PVP as binder and Cross Caramellose Sodium disintegrant the DT is within 2 minutes and the dissolution rate is the fastest(>80 in 15 minutes)as compared to when HPMC or pregelatinized starch is used as binder. This may be attributed to the fact that PVP may be acting as a solubilizer for the practically insoluble Pyrazinamide. Regarding the process,fast dispersing and rapidly disintegrating tablets are obtained when the level of drug, binder and fluid uptake in agglomeration stage is 10% w/w,25% w/w binder and 1% w/w.At the other 2 levels of these three ingredients, the DT is significantly impacted and dissolution is comparatively slower and less complete.

Keywords: agglomeration stage, isoniazide, MADG, moisture distribution stage, pyrazinamide

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Authors: S. Sonkham, U. Pinsopon, W. Chatlatanagulchai

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This paper presents a method of sliding mode control (SMC) designing and developing for the servo system in a dual-stage actuator (DSA) hard disk drive. Mathematical modelling of hard disk drive actuators is obtained, extracted from measuring frequency response of the voice-coil motor (VCM) and PZT micro-actuator separately. Matlab software tools are used for mathematical model estimation and also for controller design and simulation. A model-reference approach for tracking requirement is selected as a proposed technique. The simulation results show that performance of a model-reference SMC controller design in DSA servo control can be satisfied in the tracking error, as well as keeping the positioning of the head within the boundary of +/-5% of track width under the presence of internal and external disturbance. The overall results of model-reference SMC design in DSA are met per requirement specifications and significant reduction in %off track is found when compared to the single-state actuator (SSA).

Keywords: hard disk drive, dual-stage actuator, track following, hdd servo control, sliding mode control, model-reference, tracking control

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Authors: Arvind Srivastav, Tarun Kanti Bhattacharyya

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The north-eastern, Himalayan, and Eastern Ghats Belt of India comprise of earthquake-prone, remote, and hilly terrains. Earthquakes have caused enormous damages in these regions in the past. A wireless sensor network based earthquake early warning system (EEWS) is being developed to mitigate the damages caused by earthquakes. It consists of sensor nodes, distributed over the region, that perform majority voting of the output of the seismic sensors in the vicinity, and relay a message to a base station to alert the residents when an earthquake is detected. At the heart of the EEWS is a low-power two-stage seismic sensor that continuously tracks seismic events from incoming three-axis accelerometer signal at the first-stage, and, in the presence of a seismic event, triggers the second-stage P-wave detector that detects the onset of P-wave in an earthquake event. The parameters of the P-wave detector have been optimized for minimizing detection time and maximizing the accuracy of detection.Working of the sensor scheme has been verified with seven earthquakes data retrieved from IRIS. In all test cases, the scheme detected the onset of P-wave accurately. Also, it has been established that the P-wave onset detection time reduces linearly with the sampling rate. It has been verified with test data; the detection time for data sampled at 10Hz was around 2 seconds which reduced to 0.3 second for the data sampled at 100Hz.

Keywords: earthquake early warning system, EEWS, STA/LTA, polarization, wavelet, event detector, P-wave detector

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Authors: Wafa Halfaoui Mbarek, Khir Tahar, Ben Brahim Ammar

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This study reports a comparison from an exergetic point of view between three configurations of vapor compression industrial refrigeration systems operating with R134a as working fluid. The performances of the different cycles are analyzed as function of several operating parameters such as condensing temperature and inter stage pressure. In addition, the contributions of component exergy destruction to the total exergy destruction are obtained for each system. The results are estimated to be used in the selection of the most advantageous configuration from an exergetic view point.

Keywords: vapor compression, exergy, destruction, efficiency, R134a

Procedia PDF Downloads 385

Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya

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In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.

Keywords: cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis

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Authors: Shay Kee Tan, Kok Haur Ng, Jennifer So-Kuen Chan

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This paper extends the conditional autoregressive range (CARR) model to multivariate CARR (MCARR) model and further to the two-stage MCARR-return model to model and forecast volatilities, correlations and returns of multiple financial assets. The first stage model fits the scaled realised Parkinson volatility measures using individual series and their pairwise sums of indices to the MCARR model to obtain in-sample estimates and forecasts of volatilities for these individual and pairwise sum series. Then covariances are calculated to construct the fitted variance-covariance matrix of returns which are imputed into the stage-two return model to capture the heteroskedasticity of assets’ returns. We investigate different choices of mean functions to describe the volatility dynamics. Empirical applications are based on the Standard and Poor 500, Dow Jones Industrial Average and Dow Jones United States Financial Service Indices. Results show that the stage-one MCARR models using asymmetric mean functions give better in-sample model fits than those based on symmetric mean functions. They also provide better out-of-sample volatility forecasts than those using CARR models based on two robust loss functions with the scaled realised open-to-close volatility measure as the proxy for the unobserved true volatility. We also find that the stage-two return models with constant means and multivariate Student-t errors give better in-sample fits than the Baba, Engle, Kraft, and Kroner type of generalized autoregressive conditional heteroskedasticity (BEKK-GARCH) models. The estimates and forecasts of value-at-risk (VaR) and conditional VaR based on the best MCARR-return models for each asset are provided and tested using Kupiec test to confirm the accuracy of the VaR forecasts.

Keywords: range-based volatility, correlation, multivariate CARR-return model, value-at-risk, conditional value-at-risk

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Authors: Johnson Adafin, James O. B. Rotimi, Suzanne Wilkinson, Abimbola O. Windapo

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An aspect of client expenditure management that requires attention is the level of accuracy achievable in design-stage elemental cost planning. This has been a major concern for construction clients and practitioners in New Zealand (NZ). Pre-tender estimating inaccuracies are significantly influenced by the level of risk information available to estimators. Proper cost planning activities should ensure the production of a project’s likely construction costs (initial and final), and subsequent cost control activities should prevent unpleasant consequences of cost overruns, disputes and project abandonment. If risks were properly identified and priced at the design stage, observed variance between design-stage elemental cost plans (ECPs) and final tender sums (FTS) (initial contract sums) could be reduced. This study investigates the variations between design-stage ECPs and FTS of construction projects, with a view to identifying risk factors that are responsible for the observed variance. Data were sourced through interviews, and risk factors were identified by using thematic analysis. Access was obtained to project files from the records of study participants (consultant quantity surveyors), and document analysis was employed in complementing the responses from the interviews. Study findings revealed the discrepancies between ECPs and FTS in the region of -14% and +16%. It is opined in this study that the identified risk factors were responsible for the variability observed. The values obtained from the analysis would enable greater accuracy in the forecast of FTS by Quantity Surveyors. Further, whilst inherent risks in construction project developments are observed globally, these findings have important ramifications for construction projects by expanding existing knowledge on what is needed for reasonable budgetary performance and successful delivery of construction projects. The findings contribute significantly to the study by providing quantitative confirmation to justify the theoretical conclusions generated in the literature from around the world. This therefore adds to and consolidates existing knowledge.

Keywords: accuracy, design-stage, elemental cost plan, final tender sum

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Authors: Ajay Gogia, Svs Deo, Dn Sharma, Atul Batra, Ashutash Mishra

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Background and Aims: Breast cancer in women aged less than 25 years (defined as very young breast cancer, VYBC) is rare and accounts for 0.25% of all breast cancer in the West. There is no data available on VYBC from developing countries. The aim of this study was to analyze the clinical, pathological, and prognostic factors and outcomes in VYBC. Methods: This retrospective analysis was performed on 80 patients aged 25 years or less (screened 8000 files of female BC) who were registered at All India Institute of Medical Sciences (AIIMS), New Delhi, India, over a 15-year period between 2011 and 2023. Results: The median age was 21.5 years (range 16-25). A positive family history (siblings and parents) was elicited in 30% of cases, and breast cancer gene (BRCA1/2) mutation was found in 33% of cases patients. Ten patients (12.5%) patients have pregnancy-associated breast cancer (BC detected during pregnancy or 1 year after postpartum period). The TNM stage distribution was Stage I was 0, stage II -30%, stage III –60% and Stage IV -10 %patients. Seventy percent of tumors were high grade, and 90% had pathological node-positive disease. Estrogen, Progesterone, and human epidermal growth factor receptor 2 (HER2)/neu positivity were 25%,25% and 35%, respectively. Triple-negative breast cancer constituted 40% of patients. With a median follow-up of 42 months, 3 years, relapse-free survival (nonmetastatic disease), progression-free survival (metastatic disease) and overall survival were 30%, 15% and 50%, respectively. Conclusions: Very young women constituted 1% of all breast cancer cases. Advanced disease at presentation and high-risk pathological features result in poor outcomes. One-third of VYBCs are associated with BRCA mutation, which requires genetic counseling and risk reduction surgery if required. Due to the aggressive behavior of BC in this age group, need early diagnosis and prompt treatment

Keywords: very young, breast cancer, outcome, developing country, India

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Authors: Taha Anjamrooz, Sareh Rajabi, Salwa Bheiry

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Selection between the available projects in bidding processes for the contractor is one of the essential areas to concentrate on. It is important for the contractor to choose the right projects within its portfolio during the tendering stage based on certain criteria. It should align the bidding process with its origination strategies and goals as a screening process to have the right portfolio pool to start with. Secondly, it should set the proper framework and use a suitable technique in order to optimize its selection process for concertation purpose and higher efforts during the tender stage with goals of success and winning. In this research paper, a two steps framework proposed to increase the efficiency of the contractor’s bidding process and the winning chance of getting the new projects awarded. In this framework, initially, all the projects pass through the first stage screening process, in which the portfolio basket will be evaluated and adjusted in accordance with the organization strategies to the reduced version of the portfolio pool, which is in line with organization activities. In the second stage, the contractor uses linear programming to optimize the portfolio pool based on available resources such as manpower, light equipment, heavy equipment, financial capability, return on investment, and success rate of winning the bid. Therefore, this optimization model will assist the contractor in utilizing its internal resource to its maximum and increase its winning chance for the new project considering past experience with clients, built-relation between two parties, and complexity in the exertion of the projects. The objective of this research will be to increase the contractor's winning chance in the bidding process based on the success rate and expected return on investment.

Keywords: bidding process, internal resources, optimization, contracting portfolio management

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Authors: Renata Checiches, Thierry Coche, Nicolas F. Delahaye, Albert Linder, Fernando Ulloa Montoya, Olivier Gruselle, Karen Langfeld, An de Creus, Bart Spiessens, Vincent G. Brichard, Jamila Louahed, Frédéric F. Lehmann

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Background: The RNA-expression levels of cancer-testis antigens MAGE A3 and PRAME were determined in resected tissue from patients with primary non-small-cell lung cancer (NSCLC) and related to clinical outcome. EGFR, KRAS and BRAF mutation status was determined in a subset to investigate associations with MAGE A3 and PRAME expression. Methods: We conducted a single-centre, uncontrolled, retrospective study of 1260 tissue-bank samples from stage IA-III resected NSCLC. The prognostic value of antigen expression (qRT-PCR) was determined by hazard-ratio and Kaplan-Meier curves. Results: Thirty-seven percent (314/844) of tumours expressed MAGE-A3, 66% (723/1092) expressed PRAME and 31% (239/839) expressed both. Respective frequencies in squamous-cell tumours and adenocarcinomas were 43%/30% for MAGE A3 and 80%/44% for PRAME. No correlation with stage, tumour size or patient age was found. Overall, no prognostic value was identified for either antigen. A trend to poorer overall survival was associated with MAGE-A3 in stage IIIB and with PRAME in stage IB. EGFR and KRAS mutations were found in 10.1% (28/311) and 33.8% (97/311) of tumours, respectively. EGFR (but not KRAS) mutation status was negatively associated with PRAME expression. Conclusion: No clear prognostic value for either PRAME or MAGE A3 was observed in the overall population, although some observed trends may warrant further investigation.

Keywords: MAGE A3, PRAME, cancer-testis gene, NSCLC, survival, EGFR

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Authors: Deirdre Mc Grath, Joanne Reid

Abstract:

Background: Ovarian cancer is the leading cause of mortality among gynaecologic cancers in developed countries and the seventh most common cancer worldwide with nearly 240,000 women diagnosed each year. Although it is recognized engaging in exercise results in positive health care outcomes, women with ovarian cancer are reluctant to participate. No evidence currently exists focusing on how to successfully implement an exercise intervention program for patients with ovarian cancer, using a realist approach. There is a requirement for the implementation of exercise programmes within the oncology health care setting as engagement in such interventions has positive health care outcomes for women with ovarian cancer both during and following treatment. Aim: To co-design the implementation of an exercise intervention for women following treatment for ovarian cancer. Methods: This study is a realist evaluation using quantitative and qualitative methods of data collection and analysis. Realist evaluation is well-established within the health and social care setting and has in relation to this study enabled a flexible approach to investigate how to optimise implementation of an exercise intervention for this patient population. This single centre study incorporates three stages in order to identify the underlying contexts and mechanisms which lead to the successful implementation of an exercise intervention for women who have had treatment for ovarian cancer. Stage 1 - A realist literature review. Stage 2 -Co-design of the implementation of an exercise intervention with women following treatment for ovarian cancer, their carer’s, and health care professionals. Stage 3 –Implementation of an exercise intervention with women following treatment for ovarian cancer. Evaluation of the implementation of the intervention from the perspectives of the women who participated in the intervention, their informal carers, and health care professionals. The underlying program theory initially conceptualised before and during the realist review was developed further during the co-design stage. The evolving program theory in relation to how to successfully implement an exercise for these women is currently been refined and tested during the final stage of this realist evaluation which is the implementation and evaluation stage. Results: This realist evaluation highlights key issues in relation to the implementation of an exercise intervention within this patient population. The underlying contexts and mechanisms which influence recruitment, adherence, and retention rates of participants are identified. Conclusions: This study will inform future research on the implementation of exercise interventions for this patient population. It is anticipated that this intervention will be implemented into practice as part of standard care for this group of patients.

Keywords: ovarian cancer, exercise intervention, implementation, Co-design

Procedia PDF Downloads 186