Search results for: clinical trial optimization

Authors: Shekoufeh Behdad, Sahar Yadegari, Alireza Ghehrazad, Amirhossein Yadegari

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Background: In this study, we compared the effect of intravenous dexamethasone with placebo on hemodynamic variables and hypotension in patients undergoing cesarean section under spinal anesthesia. Materials and methods: This double-blind, randomized clinical trial was conducted with the approval of the university ethics committee. Written informed consent was obtained from all participating patients. Before spinal anesthesia, patients were randomly assigned to receive either dexamethasone (8 mg IV) or placebo (normal saline). Hemodynamic variables, including systolic, diastolic, and mean arterial blood pressures, as well as heart rate, were measured before drug administration and every 3 minutes until the birth of the neonate and then every 5 minutes until the end of surgery. Side effects such as hypotension, bradycardia, nausea, and vomiting were assessed and recorded for all the patients. Results: There were no significant differences in mean systolic, diastolic, and mean arterial blood pressures before and after administration of the studied drugs in both groups (P.Value>0.05), but heart rate and the incidence of hypotension in the dexamethasone group were less than placebo significantly. Conclusions: Intravenous administration of 8 mg dexamethasone before spinal anesthesia in females undergoing cesarean section can reduce the incidence of post-spinal hypotension without causing serious side effects.

Keywords: cesarean section, hypotension, spinal anesthesia, dexamethasone

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Authors: Essa Abrahim Abdulgader Saleem, Thien-My Dao

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The main objective of this paper is to optimize series-parallel system reliability using Genetic Algorithm (GA) and statistical analysis; considering system reliability constraints which involve the redundant numbers of selected components, total cost, and total weight. To perform this work, firstly the mathematical model which maximizes system reliability subject to maximum system cost and maximum system weight constraints is presented; secondly, a statistical analysis is used to optimize GA parameters, and thirdly GA is used to optimize series-parallel systems reliability. The objective is to determine the strategy choosing the redundancy level for each subsystem to maximize the overall system reliability subject to total cost and total weight constraints. Finally, the series-parallel system case study reliability optimization results are showed, and comparisons with the other previous results are presented to demonstrate the performance of our GA.

Keywords: reliability, optimization, meta-heuristic, genetic algorithm, redundancy

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Authors: E. Tandis, E. Assareh

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Designing the optimal shape of MW wind turbine blades is provided in a number of cases through evolutionary algorithms associated with mathematical modeling (Blade Element Momentum Theory). Evolutionary algorithms, among the optimization methods, enjoy many advantages, particularly in stability. However, they usually need a large number of function evaluations. Since there are a large number of local extremes, the optimization method has to find the global extreme accurately. The present paper introduces a new population-based hybrid algorithm called Genetic-Based Bees Algorithm (GBBA). This algorithm is meant to design the optimal shape for MW wind turbine blades. The current method employs crossover and neighborhood searching operators taken from the respective Genetic Algorithm (GA) and Bees Algorithm (BA) to provide a method with good performance in accuracy and speed convergence. Different blade designs, twenty-one to be exact, were considered based on the chord length, twist angle and tip speed ratio using GA results. They were compared with BA and GBBA optimum design results targeting the power coefficient and solidity. The results suggest that the final shape, obtained by the proposed hybrid algorithm, performs better compared to either BA or GA. Furthermore, the accuracy and speed convergence increases when the GBBA is employed

Keywords: Blade Design, Optimization, Genetic Algorithm, Bees Algorithm, Genetic-Based Bees Algorithm, Large Wind Turbine

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Authors: Ali Ramezani

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Balancing feeding system of plastic injection molding has overriding importance as it minimizes the process’s product defects such as weld line, shrinkage, sink marks and warpage. This article presents the difference between optimization of feeding system in identical multi-cavity molding and family molding using Moldflow Plastic Insight software. In this work, the effect of dimension, shape, position and type of gates and runners on the products quality was studied. The optimization was carried out by analyzing plastic injection molding process parameters, including melt temperature, mold temperature, cooling time, cooling temperature packing time and packing pressure. It was found that symmetrical feeding system is the most efficient shape for diminishing defects in identical multi-cavity molding. However, the same results were not concluded for family molding due to the differences between volume, mass, thickness and shape of cavities.

Keywords: balancing feeding system, family molding, multi-cavity, Moldflow, plastic injection

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Authors: Seyed Sadegh Naseralavi, Mohsen Khatibinia

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In structural optimizations through meta-heuristic algorithms, analyses of structures are performed for many times. For this reason, performing the analyses in a time saving way is precious. The importance of the point is more accentuated in time-history analyses which take much time. To this aim, peak picking methods also known as spectrum analyses are generally utilized. However, such methods do not have the required accuracy either done by square root of sum of squares (SRSS) or complete quadratic combination (CQC) rules. The paper presents an efficient technique for evaluating the dynamic responses during the optimization process with high speed and accuracy. In the method, first by using a static equivalent of the earthquake, an initial design is obtained. Then, the displacements in the modal coordinates are achieved. The displacements are herein called basic modal displacements (MBD). For each new design of the structure, the responses can be derived by well scaling each of the MBD along the time and amplitude and superposing them together using the corresponding modal matrices. To illustrate the efficiency of the method, an optimization problems is studied. The results show that the proposed approach is a suitable replacement for the conventional time history and spectrum analyses in such problems.

Keywords: basic modal displacements, earthquake, optimization, spectrum

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Authors: Manoj Kumar Reddy Pulim, Lakshmi Muthukrishnan, Geetha Jayapathy, Radhika Raman

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Introduction: In the past two decades, noninvasive positive pressure ventilation (NIPPV) emerged as one of the most important advances in the management of both acute and chronic respiratory failure in children. In the acute setting, it is an alternative to intubation with a goal to preserve normal physiologic functions, decrease airway injury, and prevent respiratory tract infections. There is a need to determine the clinical profile and parameters which point towards the need for NIV in the pediatric emergency setting. Objectives: i) To study the clinical profile of children who required non invasive ventilation and invasive ventilation, ii) To study the clinical parameters common to children who required non invasive ventilation. Methods: All children between one month to 18 years, who were intubated in the pediatric emergency department and those for whom decision to commence Non Invasive Ventilation was made in Emergency Room were included in the study. Children were transferred to the Paediatric Intensive Care Unit and started on Non Invasive Ventilation as per our hospital policy and followed up in the Paediatric Intensive Care Unit. Clinical profile of all children which included age, gender, diagnosis and indication for intubation were documented. Clinical parameters such as respiratory rate, heart rate, saturation, grunting were documented. Parameters obtained were subject to statistical analysis. Observations: Airway disease (Bronchiolitis 25%, Viral induced wheeze 22%) was a common diagnosis in 32 children who required Non Invasive Ventilation. Neuromuscular disorder was the common diagnosis in 27 children (78%) who were Intubated. 17 children commenced on Non Invasive Ventilation who later needed invasive ventilation had Neuromuscular disease. High frequency nasal cannula was used in 32, and mask ventilation in 17 children. Clinical parameters common to the Non Invasive Ventilation group were age < 1 year (17), tachycardia n = 7 (22%), tachypnea n = 23 (72%) and severe respiratory distress n = 9 (28%), grunt n = 7 (22%), SPO2 (80% to 90%) n = 16. Children in the Non Invasive Ventilation + INTUBATION group were > 3 years (9), had tachycardia 7 (41%), tachypnea 9(53%) with a male predominance n = 9. In statistical comparison among 3 groups,'p' value was significant for pH, saturation, and use of Ionotrope. Conclusion: Invasive ventilation can be avoided in the paediatric Emergency Department in children with airway disease, by commencing Non Invasive Ventilation early. Intubation in the pediatric emergency department has a higher association with neuromuscular disorders.

Keywords: clinical parameters, indications, non invasive ventilation, paediatric emergency room

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Authors: Akalu Banbeta, Emmanuel Lesaffre, Reynaldo Martina, Joost Van Rosmalen

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Including data from previous studies (historical data) in the analysis of the current study may reduce the sample size requirement and/or increase the power of analysis. The most common example is incorporating historical control data in the analysis of a current clinical trial. However, this only applies when the historical control dataare similar enough to the current control data. Recently, several Bayesian approaches for incorporating historical data have been proposed, such as the meta-analytic-predictive (MAP) prior and the modified power prior (MPP) both for single control as well as for multiple historical control arms. Here, we examine the performance of the MAP and the MPP approaches for the analysis of (over-dispersed) count data. To this end, we propose a computational method for the MPP approach for the Poisson and the negative binomial models. We conducted an extensive simulation study to assess the performance of Bayesian approaches. Additionally, we illustrate our approaches on an overactive bladder data set. For similar data across the control arms, the MPP approach outperformed the MAP approach with respect to thestatistical power. When the means across the control arms are different, the MPP yielded a slightly inflated type I error (TIE) rate, whereas the MAP did not. In contrast, when the dispersion parameters are different, the MAP gave an inflated TIE rate, whereas the MPP did not.We conclude that the MPP approach is more promising than the MAP approach for incorporating historical count data.

Keywords: count data, meta-analytic prior, negative binomial, poisson

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Authors: Bao Li, Aike Qiao, Gaoyang Li, Youjun Liu

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Background: Lumped parameter model (LPM) is a common numerical model for hemodynamic calculation. LPM uses circuit elements to simulate the human blood circulatory system. Physiological indicators and characteristics can be acquired through the model. However, due to the different physiological indicators of each individual, parameters in LPM should be personalized in order for convincing calculated results, which can reflect the individual physiological information. This study aimed to develop an automatic and effective optimization method to personalize the parameters in LPM of the blood circulatory system, which is of great significance to the numerical simulation of individual hemodynamics. Methods: A closed-loop LPM of the human blood circulatory system that is applicable for most persons were established based on the anatomical structures and physiological parameters. The patient-specific physiological data of 5 volunteers were non-invasively collected as personalized objectives of individual LPM. In this study, the blood pressure and flow rate of heart, brain, and limbs were the main concerns. The collected systolic blood pressure, diastolic blood pressure, cardiac output, and heart rate were set as objective data, and the waveforms of carotid artery flow and ankle pressure were set as objective waveforms. Aiming at the collected data and waveforms, sensitivity analysis of each parameter in LPM was conducted to determine the sensitive parameters that have an obvious influence on the objectives. Simulated annealing was adopted to iteratively optimize the sensitive parameters, and the objective function during optimization was the root mean square error between the collected waveforms and data and simulated waveforms and data. Each parameter in LPM was optimized 500 times. Results: In this study, the sensitive parameters in LPM were optimized according to the collected data of 5 individuals. Results show a slight error between collected and simulated data. The average relative root mean square error of all optimization objectives of 5 samples were 2.21%, 3.59%, 4.75%, 4.24%, and 3.56%, respectively. Conclusions: Slight error demonstrated good effects of optimization. The individual modeling algorithm developed in this study can effectively achieve the individualization of LPM for the blood circulatory system. LPM with individual parameters can output the individual physiological indicators after optimization, which are applicable for the numerical simulation of patient-specific hemodynamics.

Keywords: blood circulatory system, individual physiological indicators, lumped parameter model, optimization algorithm

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Authors: Abdelghani Choucha, Lakhdar Chaib, Salem Arif

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This paper treated the problem of power system stability with the aid of Static Synchronous Series Compensator (SSSC) installed in the transmission line of single machine infinite bus (SMIB) power system. A fractional order PID (FOPID) controller has been applied as a robust controller for optimal SSSC design to control the power system characteristics. Additionally, the SSSC based FOPID parameters are smoothly tuned using Invasive Weed Optimization algorithm (IWO). To verify the strength of the proposed controller, SSSC based FOPID controller is validated in a wide range of operating condition and compared with the conventional scheme SSSC-POD controller. The main purpose of the proposed process is greatly enhanced the dynamic states of the tested system. Simulation results clearly prove the superiority and performance of the proposed controller design.

Keywords: SSSC-FOPID, SSSC-POD, SMIB power system, invasive weed optimization algorithm

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Authors: Daly M. J, Condron C, Mulhall C, Eppich W, O'Neill J.

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Introduction: In contemporary clinical cardiology, comprehensive and holistic bedside evaluation including accurate cardiac auscultation is in decline despite having positive effects on patients and their outcomes. Methods: Scripted histories and scoring checklists for three clinical scenarios in cardiology were co-created and refined through iterative consensus by a panel of clinical experts; these were then paired with recordings of auscultatory findings from three actual patients with known valvular heart disease. A wearable vest with embedded pressure-sensitive panel speakers was developed to transmit these recordings when examined at the standard auscultation points. RCSI medical students volunteered for a series of three formative long case examinations in cardiology (LC1 – LC3) using this hybrid simulation. Participants were randomised into two groups: Group 1 received individual teaching from an expert trainer between LC1 and LC2; Group 2 received the same intervention between LC2 and LC3. Each participant’s long case examination performance was recorded and blindly scored by two peer participants and two RCSI examiners. Results: Sixty-eight participants were included in the study (age 27.6 ± 0.1 years; 74% female) and randomised into two groups; there were no significant differences in baseline characteristics between groups. Overall, the median total faculty examiner score was 39.8% (35.8 – 44.6%) in LC1 and increased to 63.3% (56.9 – 66.4%) in LC3, with those in Group 1 showing a greater improvement in LC2 total score than that observed in Group 2 (p < .001). Using the novel checklist, intraclass correlation coefficients (ICC) were excellent between examiners in all cases: ICC .994 – .997 (p < .001); correlation between peers and examiners improved in LC2 following peer grading of LC1 performances: ICC .857 – .867 (p < .001). Conclusion: Hybrid simulation and quantitative grading improve learning, standardisation of assessment, and direct comparisons of both performance and acumen in clinical cardiology.

Keywords: cardiology, clinical skills, long case examination, hybrid simulation, checklist

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Authors: Jui-Chien Hsieh

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Background:12-lead electrocardiography(ECG) is one of frequently-used tools to detect atrial fibrillation (AF), which might degenerate into life-threaten stroke, in clinical Practice. Based on this study, the AF detection by the clinically-used 12-lead ECG device has only 0.73~0.77 positive predictive value (ppv). Objective: It is on great demand to develop a new algorithm to improve the precision of AF detection using 12-lead ECG. Due to the progress on artificial intelligence (AI), we develop an ECG deep model that has the ability to recognize AF patterns and reduce false-positive errors. Methods: In this study, (1) 570-sample 12-lead ECG reports whose computer interpretation by the ECG device was AF were collected as the training dataset. The ECG reports were interpreted by 2 senior cardiologists, and confirmed that the precision of AF detection by the ECG device is 0.73.; (2) 88 12-lead ECG reports whose computer interpretation generated by the ECG device was AF were used as test dataset. Cardiologist confirmed that 68 cases of 88 reports were AF, and others were not AF. The precision of AF detection by ECG device is about 0.77; (3) A parallel 4-layer 1 dimensional convolutional neural network (CNN) was developed to identify AF based on limb-lead ECGs and chest-lead ECGs. Results: The results indicated that this model has better performance on AF detection than traditional computer interpretation of the ECG device in 88 test samples with 0.94 ppv, 0.98 sensitivity, 0.80 specificity. Conclusions: As compared to the clinical ECG device, this AI ECG model promotes the precision of AF detection from 0.77 to 0.94, and can generate impacts on clinical applications.

Keywords: 12-lead ECG, atrial fibrillation, deep learning, convolutional neural network

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Authors: Felix Lankester, Alicia Davis, Safari Kinung'hi, Catherine Bunga, Shayo Alkara, Imam Mzimbiri, Jonathan Yoder, Sarah Cleaveland, Guy H. Palmer

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Achieving the London Declaration goal of a 90% reduction in neglected tropical diseases (NTDs) by 2030 requires cost-effective strategies that attain high and comprehensive coverage. The first objective of this trial was to assess the impact on cost and coverage of employing a novel integrative One Health approach linking two NTD control programs: mass drug administration (MDA) for soil-transmitted helminths in humans (STH) and mass dog rabies vaccination (MDRV). The second objective was to compare the coverage achieved by the MDA, a community-wide deworming intervention, with that of the existing national primary school-based deworming program (NSDP), with particular focus on the proportion of primary school-age children reached and their school enrolment status. Our approach was unconventional because, in line with the One Health approach to disease control, it coupled the responsibilities and resources of the Ministries responsible for human and animal health into one program with the shared aim of preventing multiple NTDs. The trial was carried out in hard-to-reach pastoral communities comprising 24 villages of the Ngorongoro District, Tanzania, randomly allocated to either Arm A (MDA and MDRV), Arm B (MDA only) or Arm C (MDRV only). Objective one: The percentage of people in each target village that received treatment through MDA in Arms A and B was 63% and 65%, respectively (χ2 = 1, p = 0.32). The percentage of dogs vaccinated in Arm A and C was 70% and 81%, respectively (χ2 =9, p = 0.003). It took 33% less time for a single person and a dog to attend the integrated delivery than two separate events. Cost per dose (including delivery) was lower under the integrated strategy, with delivery of deworming and rabies vaccination reduced by $0.13 (54%) and $0.85 (19%) per dose, respectively. Despite a slight reduction in the proportion of village dogs vaccinated in the integrated event, both the integrated and non-integrated strategies achieved the target threshold of 70% required to eliminate rabies. Objective two: The percentages of primary school age children enrolled in school that was reached by this trial (73%) and the existing NSDP (80%) were not significantly different (F = 0.9, p = 0.36). However, of the primary school age children treated in this trial, 46% were not enrolled in school. Furthermore, 86% of the people treated would have been outside the reach of the NSDP because they were not primary school age or were primary school age children not enrolled in school. The comparable reach, the substantial reductions in cost per dose delivered and the decrease in participants’ time support this integrated One Health approach to control multiple NTDs. Further, the recorded level of non-enrolment at primary school suggests that, in remote areas, school-based delivery strategies could miss a large fraction of school-age children and that programs that focus delivery solely at the level of the primary school will miss a substantial proportion of both primary school age children as well as other individuals from the community. We have shown that these populations can be effectively reached through extramural programs.

Keywords: canine mediated human rabies, integrated health interventions, mass drug administration, neglected tropical disease, One Health, soil-transmitted helminths

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Authors: Abdul Halim Abdul Razik, Ali Elkamel, Leonardo Simon

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Wheat straw is one of the alternative feedstocks that may be utilized for bioethanol production especially when sustainability criteria are the major concerns. To increase market competitiveness, optimal supply chain plays an important role since wheat straw is a seasonal agricultural residue. In designing the supply chain optimization model, economic profitability of the thermochemical and biochemical conversion routes options were considered. It was found that torrefied pelletization with gasification route to be the most profitable option to produce bioethanol from the lignocellulosic source of wheat straw.

Keywords: bio-ethanol, optimization, supply chain, wheat straw

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Authors: Roberto Machado

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We conducted a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology, analyzing 2,996 studies and synthesizing 41 of them to explore the evolution of data science and its integration into geography. By employing optimization algorithms, we accelerated the review process, significantly enhancing the efficiency and precision of literature selection. Our findings indicate that data science has developed over five decades, facing challenges such as the diversified integration of data and the need for advanced statistical and computational skills. In geography, the integration of data science underscores the importance of interdisciplinary collaboration and methodological innovation. Techniques like large-scale spatial data analysis and predictive algorithms show promise in natural disaster management and transportation route optimization, enabling faster and more effective responses. These advancements highlight the transformative potential of data science in geography, providing tools and methodologies to address complex spatial problems. The relevance of this study lies in the use of optimization algorithms in systematic reviews and the demonstrated need for deeper integration of data science into geography. Key contributions include identifying specific challenges in combining diverse spatial data and the necessity for advanced computational skills. Examples of connections between these two fields encompass significant improvements in natural disaster management and transportation efficiency, promoting more effective and sustainable environmental solutions with a positive societal impact.

Keywords: data science, geography, systematic review, optimization algorithms, supervised learning

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Authors: A. Fordham, A. Hudson

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Background: Studies have suggested 16-25% of normotensive trauma patients with no clinical signs of shock have abnormal lactate and BD readings evidencing shock; a phenomenon known as occult hypoperfusion (OH). In light of the scarce quantity of evidence currently documenting OH, this study aimed to identify the prevalence of OH in the pre-hospital setting and explore ways to improve its identification and management. Methods: A quantitative retrospective data analysis was carried out on 75 sets of patient records for trauma patients treated by Kent Surrey Sussex Air Ambulance Trust between November 2013 and October 2014. The KSS HEMS notes and subsequent ED notes were collected. Trends between patients’ SBP on the scene, whether or not they received PRBCs on the scene as well as lactate and BD readings in the ED were assessed. Patients’ KSS HEMS notes written by the HEMS crew were also reviewed and recorded. Results: -Suspected OH was identified in 7% of the patients who did not receive PRBCs in the pre-hospital phase. -SBP heavily influences the physicians’ decision of whether or not to transfuse PRBCs in the pre-hospital phase. Preliminary conclusions: OH is an under-studied and underestimated phenomenon. We suggest a prospective trial is carried out to evaluate whether detecting trauma patients’ tissue perfusion status in the pre-hospital phase using portable devices capable of measuring serum BD and/or lactate could aid more accurate detection and management of all haemorrhaging trauma patients, including patients with OH.

Keywords: occult hypoperfusion, PRBC transfusion, point of care testing, pre-hospital emergency medicine, trauma

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Authors: Hany Mohamed Abdu, Mohamed Hassan Gadallah, El-Giushi Mokhtar, Yehia Mahmoud Ismail

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Laser beam cutting is one nontraditional machining process. This paper optimizes the parameters of Laser beam cutting machining parameters of Stainless steel (316L) by considering the effect of input parameters viz. power, oxygen pressure, frequency and cutting speed. Statistical design of experiments are carried in three different levels and process responses such as 'Average kerf taper (Ta)' and 'Surface Roughness (Ra)' are measured accordingly. A quadratic mathematical model (RSM) for each of the responses is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27 OA) are employed to search for an optimal parametric combination to achieve desired yield of the process. RSM models are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA) using MATLAB environment. Optimum solutions are compared with Taguchi Methodology results.

Keywords: optimization, laser cutting, robust design, kerf width, Taguchi method, RSM and DOE

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Authors: Onder Aldemir, Ercan Ceyhan

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The research was conducted to determine effects of salt concentrations on emergence and seedling development of chickpea genotypes. Trials were performed during the year of 2013 on the laboratory and greenhouse of Agricultural Faculty, Selcuk University. Emergency trial was set up according to ‘Randomized Plots Design’ by two factors and four replications; greenhouse trial was also set up according to ‘Randomized Plots Design’ by two factors with three replications. The chickpea genotypes; CA119, CA132, CA149, CA150, CA215, CA222, CA235, CA261, Bozkır and Gokce were used as material for both of the trials. Effects of the five doses of salt concentrations (control, 30 mM, 60 mM, 90 mM and 120 mM) on the ratio of emergency, speed of emergency, average time for emergency, index of sensibility, length of shoot and root, fresh weight of shoot and root, dry weight of shoot and root, index of salt tolerance were evaluated. Responses of the chickpea genotypes for salt concentrations were found different. Comparing to the control, all of the investigated characteristics on the chickpea genotypes showed significant reduction by depending on the increasing salt level. According to the effects of salt application, the chickpea genotypes Gokce, CA215 and CA222 were the most tolerant in respect to plant dry weights while the chickpea genotypes CA149 and CA150 were the most sensitive.

Keywords: chickpea, emergence, salt tolerant, seedling development

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Authors: Chao Hsing Yeh, Wei Chun Lin

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Background: Current management of aromatase inhibitor-induced arthralgia (AIA) in postmenopausal breast cancer survivors (PBCS) has limited effect. Method: In this prospective randomized clinical trial (RCT), a 4-week APA treatment was used to manage AIA. Twenty PBCS participated. After baseline data was collected, participants were waited for a month before they receive APA at a convenient time once a week for 4 weeks. Blood samples from participants in both groups were collected at baseline and after 4 weeks of treatment. The primary outcomes included: pain intensity, pain interference, stiffness, and physical function. Results: After the 4-week APA treatment, the pro-inflammatory cytokines and chemokines display a trend of mean percentage reduction (i.e., -22% in IL-1α, -4% in IL-1β, -1% in IL-2, -3% in IL-6, -19% in IL-12, -9% in Eotaxin, and -2% in MCP-1). The anti-inflammatory cytokine IL-10 and IL-13 (i.e., 5% in IL-10 and 29% in IL-13) increased from pre- to post-APA treatment. Significant positive correlation of percentage mean change was observed between symptom severity and eotaxin (ρ = 0.56; p < 0.01) & MCP-1 (ρ = 0.65; p < 0.01). Interference and chemokines (eotaxin & MIP-1) also shows positive correlation (ρ = 0.48; p < 0.01 & ρ = 0.39; p < 0.05). Another positive correlation was found between worst pain and chemokines (eotaxin, ρ = 0.48; p < 0.01 & MIP-1, ρ = 0.39; p < 0.05). Additionally, interference also shows positive correlation among IL-1α (ρ = 0.36; p < 0.05) and IL-β (ρ = 0.33; p < 0.05). Conclusion: These findings suggest that APA intervention may inhibit inflammation of AIA patients and chemokine could be one of the key factors of AIA symptom improvement.

Keywords: acupressure, cytokine, pain management, breast cancer survivors

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Authors: Xiao-Li Liu, Ling-Yun Zhao, Xing-Jie Liang, Hai-Ming Fan

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Owing to their unique properties, magnetic nanoparticles have been used as diagnostic and therapeutic agents for biomedical applications. Highly monodispersed magnetic nanoparticles with controlled particle size and surface coating have been successfully synthesized as a model system to investigate the effect of surface coating on the T2 relaxivity and specific absorption rate (SAR) under an alternating magnetic field, respectively. Amongst, by using mPEG-g-PEI to solubilize oleic-acid capped 6 nm magnetic nanoparticles, the T2 relaxivity could be significantly increased by up to 4-fold as compared to PEG coated nanoparticles. Moreover, it largely enhances the cell uptake with a T2 relaxivity of 92.6 mM-1s-1 for in vitro cell MRI. As for hyperthermia agent, SAR value increase with the decreased thickness of PEG surface coating. By elaborate optimization of surface coating and particle size, a significant increase of SAR (up to 74%) could be achieved with a minimal variation on the saturation magnetization (<5%). The 19 nm magnetic nanoparticles with 2000 Da PEG exhibited the highest SAR of 930 W•g-1 among the samples, which can be maintained in various simulated physiological conditions. This systematic work provides a general strategy for the optimization of surface coating of magnetic core for high performance MRI contrast agent and hyperthermia agent.

Keywords: magnetic nanoparticles, magnetic hyperthermia, magnetic resonance imaging, surface modification

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Authors: Marin Mandić, Elis Sutlović, Tonći Modrić, Luka Stanić

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With the restructuring and deregulation of the power system, storage owners, generation companies or private producers can offer their multiple services on various power markets and earn income in different types of markets, such as the day-ahead, real-time, ancillary services market, etc. During the COVID-19 pandemic, electricity prices, as well as ancillary services prices, increased significantly. The optimization of the energy storage operation was performed using a suitable model for simulating the operation of a pumped storage hydropower plant under market conditions. The objective function maximizes the income earned through energy arbitration, regulation-up, regulation-down and spinning reserve services. The optimization technique used for solving the objective function is mixed integer linear programming (MILP). In numerical examples, the pumped storage hydropower plant operation has been optimized considering the already achieved hourly electricity market prices from Nord Pool for the pre-pandemic (2019) and the pandemic (2020 and 2021) years. The impact of the electricity market prices during the COVID-19 pandemic on energy storage operation is shown through the analysis of income, operating hours, reserved capacity and consumed energy for each service. The results indicate the role of energy storage during a significant fluctuation in electricity and services prices.

Keywords: electrical market prices, electricity market, energy storage optimization, mixed integer linear programming (MILP) optimization

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Authors: Mahdi Fakoor, Seyed Mohammad Navid Ghoreishi

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Composite patching is a common way for reinforcing the cracked pipes and cylinders. The effects of composite patch reinforcement on fracture parameters of a cracked pipe depend on a variety of parameters such as number of layers, angle, thickness, and material of each layer. Therefore, stacking sequence optimization of composite patch becomes crucial for the applications of cracked pipes. In this study, in order to obtain the optimal stacking sequence for a composite patch that has minimum weight and maximum resistance in propagation of cracks, a coupled Multi-Objective Genetic Algorithm (MOGA) and Finite Element Method (FEM) process is proposed. This optimization process has done for longitudinal and transverse semi-elliptical cracks and optimal stacking sequences and Pareto’s front for each kind of cracks are presented. The proposed algorithm is validated against collected results from the existing literature.

Keywords: multi objective optimization, pareto front, composite patch, cracked pipe

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Authors: Rizqi W. Romadhon, Nur Arifan

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Halal Tourism is a part of tourism industry which is based on Islamic Principle and addressed to the Muslim tourist. The potency of halal tourism is very broad to be developed, because the growth of Muslim populations is rapidly increasing. Indonesia is one of the biggest countries with Majority of its population is Muslim, therefore human resources and natural resources have very good potential to be part of the Halal tourism industry. But the fact is Indonesia can not optimize the potential of human resources and natural resources as well as neighboring countries carried out. This paper will discuss the reasons of the importance of developing Halal tourism, and the factors influencing the success of developing halal tourism in Indonesia, and also the optimization strategies which can be adopted by the government so that the Halal tourism industry in Indonesia has a sustainable competitive advantage. The existence of this research is expected to government, tourism agents and others can optimize the potency of Indonesia’s Human resources and natural resources for developing Halal tourism industry in Indonesia.

Keywords: halal tourism, Islamic principle, optimization, sustainable competitive advantage

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Authors: Tomoaki Hashimoto

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Recently, optimal control problems subject to probabilistic constraints have attracted much attention in many research field. Although probabilistic constraints are generally intractable in optimization problems, several methods haven been proposed to deal with probabilistic constraints. In most methods, probabilistic constraints are transformed to deterministic constraints that are tractable in optimization problems. This paper examines a method for transforming probabilistic constraints into deterministic constraints for a class of probabilistic constrained optimal control problems.

Keywords: optimal control, stochastic systems, discrete-time systems, probabilistic constraints

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Authors: D. S. Nagesh, G. L. Datta

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In the field of welding, various studies had been made by some of the previous investigators to predict as well as optimize weld bead geometric descriptors. Modeling of weld bead shape is important for predicting the quality of welds. In most of the cases, design of experiments technique to postulate multiple linear regression equations have been used. Nowadays, Genetic Algorithm (GA) an intelligent information treatment system with the characteristics of treating complex relationships as seen in welding processes used as a tool for inverse mapping/optimization of the process is attempted.

Keywords: smaw, genetic algorithm, bead geometry, optimization/inverse mapping

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Authors: D. S. Nagesh, G. L. Datta

Abstract:

In the field of welding, various studies had been made by some of the previous investigators to predict as well as optimize weld bead geometric descriptors. Modeling of weld bead shape is important for predicting the quality of welds. In most of the cases design of experiments technique to postulate multiple linear regression equations have been used. Nowadays Genetic Algorithm (GA) an intelligent information treatment system with the characteristics of treating complex relationships as seen in welding processes used as a tool for inverse mapping/optimization of the process is attempted.

Keywords: SMAW, genetic algorithm, bead geometry, optimization/inverse mapping

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Authors: Won Mog Choi, Seong Kyeong Hong, Seok Young Jeong

Abstract:

The stress on the buried pipeline under pavement is significantly affected by vehicle loads and elastic modulus of the soil surrounding the pipeline. The correct elastic modulus of soil has to be applied to the finite element model to investigate the effect of the vehicle loads on the buried pipeline using finite element analysis. The purpose of this study is to establish the approach to calculating the correct elastic modulus of soil using the optimization process. The optimal elastic modulus of soil, which minimizes the difference between the strain measured from vehicle driving test at the velocity of 35km/h and the strain calculated from finite element analyses, was calculated through the optimization process using multi-response surface methodology. Three elastic moduli of soil (road layer, original soil, dense sand) surrounding the pipeline were defined as the variables for the optimization. Further analyses with the optimal elastic modulus at the velocities of 4.27km/h, 15.47km/h, 24.18km/h were performed and compared to the test results to verify the applicability of multi-response surface methodology. The results indicated that the strain of the buried pipeline was mostly affected by the elastic modulus of original soil, followed by the dense sand and the load layer, as well as the results of further analyses with optimal elastic modulus of soil show good agreement with the test.

Keywords: pipeline, optimization, elastic modulus of soil, response surface methodology

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Authors: Niloufar Yadgari

Abstract:

GANs are a potent form of deep learning models that have found success in various fields. They are part of the larger group of generative techniques, which aim to produce authentic data using a probabilistic model that learns distributions from actual samples. In clinical settings, GANs have demonstrated improved abilities in capturing spatially intricate, nonlinear, and possibly subtle disease impacts in contrast to conventional generative techniques. This review critically evaluates the current research on how GANs are being used in imaging studies of different neurological conditions like Alzheimer's disease, brain tumors, aging of the brain, and multiple sclerosis. We offer a clear explanation of different GAN techniques for each use case in neuroimaging and delve into the key hurdles, unanswered queries, and potential advancements in utilizing GANs in this field. Our goal is to connect advanced deep learning techniques with neurology studies, showcasing how GANs can assist in clinical decision-making and enhance our comprehension of the structural and functional aspects of brain disorders.

Keywords: GAN, pathology, generative adversarial network, neuro imaging

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Authors: Avantika Vats, Kushal Thakur

Abstract:

This paper displays the point at issue, improvement, and utilization of a Monarch Butterfly Optimization (MBO) rather than a Genetic Algorithm (GA) in cognitive radio for the channel portion. This approach offers a satisfactory approach to get the accessible range of both the users, i.e., primary users (PUs) and secondary users (SUs). The proposed enhancement procedure depends on a nature-inspired metaheuristic algorithm. In MBO, all the monarch butterfly individuals are located in two distinct lands, viz. Southern Canada and the northern USA (land 1), and Mexico (Land 2). The positions of the monarch butterflies are modernizing in two ways. At first, the offsprings are generated (position updating) by the migration operator and can be adjusted by the migration ratio. It is trailed by tuning the positions for different butterflies by the methods for the butterfly adjusting operator. To keep the population unaltered and minimize fitness evaluations, the aggregate of the recently produced butterflies in these two ways stays equivalent to the first population. The outcomes obviously display the capacity of the MBO technique towards finding the upgraded work values on issues regarding the genetic algorithm.

Keywords: cognitive radio, channel allocation, monarch butterfly optimization, evolutionary, computation

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Authors: H. Zidoum, A. AlShareedah, S. Al Sawafi, A. Al-Ansari, B. Al Lawati

Abstract:

Systemic lupus erythematosus (SLE) is an autoimmune disease with genetic and environmental components. SLE is characterized by a wide variability of clinical manifestations and a course frequently subject to unpredictable flares. Despite recent progress in classification tools, the early diagnosis of SLE is still an unmet need for many patients. This study proposes an interpretable disease classification model that combines the high and efficient predictive performance of CatBoost and the model-agnostic interpretation tools of Shapley Additive exPlanations (SHAP). The CatBoost model was trained on a local cohort of 219 Omani patients with SLE as well as other control diseases. Furthermore, the SHAP library was used to generate individual explanations of the model's decisions as well as rank clinical features by contribution. Overall, we achieved an AUC score of 0.945, F1-score of 0.92 and identified four clinical features (alopecia, renal disorders, cutaneous lupus, and hemolytic anemia) along with the patient's age that was shown to have the greatest contribution on the prediction.

Keywords: feature selection, classification, systemic lupus erythematosus, model interpretation, SHAP, Catboost

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Authors: Jungbin Lim, Bohee Kang, Heelim Lee, Sunjin Kim, GeumHee Choi, Jae-Suk Jung, Suk Ji

Abstract:

Nonsurgical periodontal therapies have, for several decades, been the basis of periodontal treatment concepts. The aim of this paper is to investigate the effectiveness of non-surgical periodontal therapy according to the severity of periodontitis disease. Methods: Retrospective data of patients who visited Department of periodontics in Ajou University Medical Center from 2016 to 2022 were collected. Among the patients, those who took full mouth examination of clinical parameters and non-surgical periodontal therapy were chosen for this study. Selected patients were divided into initial, moderate, and severe periodontitis based on severity and complexity of management (2018 World Workshop EFP/AAP consensus). Recall visits with clinical periodontal examination were scheduled for 1,2,3 months or 1,3,6 months after the treatment. The results were evaluated by recordings of mean probing pocket depth (mean PD), mean clinical attachment levels (mean CAL), bleeding on probing (BOP%), mean gingival index (mean GI), mean regression, mean sulcus bleeding index (mean SBI), mean plaque scores (mean PI). All statistical analyses were performed with R software, version 4.3.0. A level of significance, P<0.05, was considered to be statistically significant. Results: A total of 92 patients were included in this study. 15 patients were diagnosed as initial periodontitis, 14 moderate periodontitis, and 63 severe periodontitis. The all parameters except for mean recession decreased over time in all groups. The amount of mean PD decreased were the greatest in severe periodontitis group followed by moderate and initial, which was found to be statistically significant. The changes of mean PD were 0.15±0.05 mm, 0.37±0.06 mm, and 1.01±0.07 mm (initial, moderate, and severe, respectively, P<0.001). When comparing before and after treatment, the reductions in BOP(%), mean GI, mean SBI, and mean PI were statistically significant. Conclusion: All patients who received non-surgical periodontal therapy showed periodontal healing in terms of improvements in clinical parameters, and it was greater in the severe group.

Keywords: periodontology, clinical periodontology, oral treatment, comprehensive preventive dentistry, non-surgical periodontal therapy

Procedia PDF Downloads 78