Search results for: patient dose optimization

Authors: Aouaouche Elmaouhab, Hassina Beggar

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Solving multi-objective discrete optimization applications has always been limited by the resources of one machine: By computing power or by memory, most often both. To speed up the calculations, the grid computing represents a primary solution for the treatment of these applications through the parallelization of these resolution methods. In this work, we are interested in the study of some methods for solving multiple objective integer linear programming problem based on Branch-and-Bound and the study of grid computing technology. This study allowed us to propose an implementation of the method of Abbas and Al on the grid by reducing the execution time. To enhance our contribution, the main results are presented.

Keywords: multi-objective optimization, integer linear programming, grid computing, parallel computing

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Authors: Jia Liu

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This article explores the shifting nature of physician-patient relationship in mainland China. Specifically, it takes the physician-patient relationship during the barefoot doctor program in 1968-1978, the marketization of healthcare services in 1978-2002, and the healthcare reform in 2003-2020 as three typical historical periods, illustrating how the nature of the physician-patient relationship has changed over time in mainland China. Drawing on recent jurisprudential literature that emphasizes the roles and functions done by and through obligation rather than right, it explores how the obligations of physicians and patients along with the implementation of informed consent, marketization of the healthcare system, and the basic healthcare reform have affected their relationship. One key feature of this article is that it analyzes the ways in which commodification and decommodification of healthcare have defined and in many different ways have determined the expectations and practices of physicians and patients, which illustrates how the trust between physicians and patients threatens to collapse and the bond between the citizen and the state fails to be firmly established in the mainland Chinese healthcare context. It also pays special attention to the role played by law and legal institutions—for instance, the implementation of informed consent and the liability law—in being complicit in facilitating the decoupling of the practices of physicians and patients from their ethical senses of obligation and undermining the bond (the trust relationship) between them.

Keywords: healthcare, marketization, physician-patient relationship, sense of obligation

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Matjaž Divjak, Simon Zelič, Aleš Holobar

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We present a dedicated video-based monitoring system for quantification of patient’s attention to visual feedback during robot assisted gait rehabilitation. Two different approaches for eye gaze and head pose tracking are tested and compared. Several metrics for assessment of patient’s attention are also presented. Experimental results with healthy volunteers demonstrate that unobtrusive video-based gaze tracking during the robot-assisted gait rehabilitation is possible and is sufficiently robust for quantification of patient’s attention and assessment of compliance with the rehabilitation therapy.

Keywords: video-based attention monitoring, gaze estimation, stroke rehabilitation, user compliance

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Authors: Sophia Shi

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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

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Authors: Ayse Gul Bilen

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Selective serotonin reuptake inhibitors (SSRIs) are commonly prescribed antidepressants that are used clinically for the treatment of anxiety disorders, obsessive-compulsive disorder (OCD), panic disorders and eating disorders. The first SSRI, fluoxetine (sold under the brand names Prozac and Sarafem among others), had an adverse effect profile better than any other available antidepressant when it was introduced because of its selectivity for serotonin receptors. They have been considered almost free of side effects and have become widely prescribed, however questions about the safety and tolerability of SSRIs have emerged with their continued use. Most SSRI side effects are dose-related and can be attributed to serotonergic effects such as nausea. Continuous use might trigger adverse effects such as hyponatremia, tremor, nausea, weight gain, sleep disturbance and sexual dysfunction. Moderate toxicity can be safely observed in the hospital for 24 hours, and mild cases can be safely discharged (if asymptomatic) from the emergency department once cleared by Psychiatry in cases of intentional overdose and after 6 to 8 hours of observation. Although fluoxetine is relatively safe in terms of overdose, it might still be cardiotoxic and inhibit platelet secretion, aggregation, and plug formation. There have been reported clinical cases of seizures, cardiac conduction abnormalities, and even fatalities associated with fluoxetine ingestions. While the medical literature strongly suggests that most fluoxetine overdoses are benign, emergency physicians need to remain cognizant that intentional, high-dose fluoxetine ingestions may induce seizures and can even be fatal due to cardiac arrhythmia. Our case is a 35-year old female patient who was sent to ER with symptoms of confusion, amnesia and loss of orientation for time and location after being found wandering in the streets unconsciously by police forces that informed 112. Upon laboratory examination, no pathological symptom was found except sinus tachycardia in the EKG and high levels of aspartate transaminase (AST) and alanine transaminase (ALT). Diffusion MRI and computed tomography (CT) of the brain all looked normal. Upon physical and sexual examination, no signs of abuse or trauma were found. Test results for narcotics, stimulants and alcohol were negative as well. There was a presence of dysrhythmia which required admission to the intensive care unit (ICU). The patient gained back her conscience after 24 hours. It was discovered from her story afterward that she had been using fluoxetine due to post-traumatic stress disorder (PTSD) for 6 months and that she had attempted suicide after taking 3 boxes of fluoxetine due to the loss of a parent. She was then transferred to the psychiatric clinic. Our study aims to highlight the need to consider toxicologic drug use, in particular, the abuse of selective serotonin reuptake inhibitors (SSRIs), which have been widely prescribed due to presumed safety and tolerability, for diagnosis of patients applying to the emergency room (ER).

Keywords: abuse, amnesia, fluoxetine, intoxication, SSRI

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Authors: Bale Baidi Blaise, Gilles Marckmann, Liman Kaoye, Talaka Dya, Moustapha Bachirou, Gambo Betchewe, Tibi Beda

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This work highlights the capabilities of particles swarm optimization (PSO) method to identify parameters of hyperelastic models. The study compares this method with Genetic Algorithm (GA) method, Least Squares (LS) method, Pattern Search Algorithm (PSA) method, Beda-Chevalier (BC) method and the Levenberg-Marquardt (LM) method. Four classic hyperelastic models are used to test the different methods through parameters identification. Then, the study compares the ability of these models to reproduce experimental Treloar data in simple tension, biaxial tension and pure shear.

Keywords: particle swarm optimization, identification, hyperelastic, model

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Authors: O. Benaziz, A. Dorbane, S. Djeraba

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The objective of this work is to formulate a dry dispersible form of furosemide in the context of pediatric dose adjustment. To achieve this, we have produced a set of formulas that will be tested in process and after compression. The formula with the best results will be improved to optimize the final shape of the product. Furosemide is the most widely used pediatric diuretic because of its low toxicity. The manufacturing process was chosen taking into account all the data relating to the active ingredient and the excipients used and complying with the specifications and requirements of dispersible tablets. The process used to prepare these tablets was wet granulation. Different excipients were used: lactose, maize starch, magnesium stearate and two superdisintegrants. The mode of incorporation of super-disintegrant changes with each formula. The use of super-disintegrant in the formula allowed optimization of the disintegration time. Prepared tablets were evaluated for weight, content uniformity, hardness, disintegration time, friability and in vitro dissolution test. 

Keywords: formulation, dispersible tablets, wet granulation, superdisintegrants, disintegration

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Authors: Chee Sun Won

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This paper presents the size reduction of images for machine-to-machine communications. Here, the salient image regions to be preserved include the image patches of the key-points such as corners and blobs. Based on a saliency image map from the key-points and their image patches, an axis-aligned grid-size optimization is proposed for the reduction of image size. To increase the size-reduction efficiency the aspect ratio constraint is relaxed in the constraint optimization framework. The proposed method yields higher matching accuracy after the size reduction than the conventional content-aware image size-reduction methods.

Keywords: image compression, image matching, key-point detection and description, machine-to-machine communication

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Authors: Mark Andrew Tu, Raymond Olazo, Cybele Abad

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Cryptococcosis is an invasive infection most commonly found in patients who are immuno compromised. However, patients with this infection usually present with meningitis and rarely pulmonary infection in isolation. We present a case of a Filipino HIV patient who developed cryptococcal pneumonia without meningitis.

Keywords: Cryptococcal Pneumonia, HIV, Filipino, immune system

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Authors: A. Kaeotawee, N. Bunmas, W. Chomthong

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Background: The cancellation of elective surgery is a major indicator of poor operating room efficiency. Furthermore, it is recognized as a major cause of emotional trauma to patients as well as their families. This study was carried out to assess the incidence and causes of elective surgery cancellation in our setting and to find the appropriate solutions for better quality management. Objective: To determine the incidence and causes of elective surgery cancellations in Songklanagarind Hospital. Material and Method: A prospective survey was conducted from September to November 2012. All patients who had their scheduled elective operations cancelled were assessed. Data was collected on the following 2 components: (1) patient demographics;(2) main reasons for cancellations, which were grouped into patient-related factors and organizational-related factors. Data are reported as a percentage of patients whose operations were cancelled. The association between cancellation status and patient demographics was assessed using univariate logistic regression. Results: 2,395 patients were scheduled for elective surgery and of these 343 (14.3%) had their operations cancelled. Cardiothoracic surgery had the highest rate of cancellations (28.7%) while the least number of cancellations occurred in ophthalmology (10.1%). The main reasons for cancellations were related to the unit's organization (53.6%), due to the surgeon (48.4%). Patient related causes (46.4%), due to non medical reasons (32.1%). The most common cause of cancellation by the surgeon was lack of theater time (21.3%), by patients due to the patient’s nonappearance (25.1%). Cancellation was significantly associated with type of patient, health insurance, type of anesthesia and specialties (p<0.05). Conclusion: Surgery cancellations by surgeons relating to a lack of theater time was a significant problem in our setting. Appropriate solutions for better quality improvement are needed.

Keywords: elective cases, surgery cancellation, quality management, appropriate solutions

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Authors: Muhammad Zaman, Guohua Fang, Muhammad Saifullah,

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The presented study emphasize at an optimal model to compare past and future optimal hydropower generation. In order to get maximum benefits from the Xin’anjiang hydropower station a model is developed. A Particle Swarm Optimization (PSO) has purposed and past and future water flow is used to get the maximum benefits from future water resources in this study. The results revealed that the future hydropower generation is more than the past generation. This paper gives us idea that what could we get in the past using optimal method of electricity generation and what can we get in the future using this technique.

Keywords: PSO, future water resources, optimization, Xin’anjiang,

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Authors: Mandeep Kumar, Hari Singh

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The effective optimization of machining process parameters affects dramatically the cost and production time of machined components as well as the quality of the final products. This paper presents the optimization aspects of a Wire Electrical Discharge Machining operation using Inconel X-750 as work material. The objective considered in this study is minimization of the dimensional deviation. Six input process parameters of WEDM namely spark gap voltage, pulse-on time, pulse-off time, wire feed rate, peak current and wire tension, were chosen as variables to study the process performance. Taguchi's design of experiments methodology has been used for planning and designing the experiments. The analysis of variance was carried out for raw data as well as for signal to noise ratio. Four input parameters and one two-factor interaction have been found to be statistically significant for their effects on the response of interest. The confirmation experiments were also performed for validating the predicted results.

Keywords: ANOVA, DOE, inconel, machining, optimization

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Authors: Yehya Abdellatif, Iyad M. Muslih, Azzah Alkhalailah, Abdallah Muslih

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Hybrid Optimization Model for Electric Renewable (HOMER) software was utilized to find the optimum design of a hybrid off-Grid system, by choosing the optimal solution depending on the cost analysis of energy based on different capacity shortage percentages. A complete study for the site conditions and load profile was done to optimize the design and implementation of a hybrid off-grid power station. In addition, the solution takes into consecration the ambient temperature effect on the efficiency of the power generation and the economical aspects of selection depending on real market price. From the analysis of the HOMER model results, the optimum hybrid power station was suggested, based on wind speed, and solar conditions. The optimization function objective is to minimize the Net Price Cost (NPC) and the Cost of Energy (COE) with zero and 10 percentage of capacity shortage.

Keywords: energy modeling, HOMER, off-grid system, optimization

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Authors: Ines Zemni, Maher Slimane, Jamel Ben Hassouna, Khaled Rahal

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Background: Neurofibromatosis type 1 (NF1) is a genetic disease, which is associated with an increased risk of developing different malignancies including breast cancer. The association between NF1 band breast sarcoma is a rare entity. Herein we present a 25-year-old woman with NF1 who had fibrosarcoma of the left breast. Case presentation: The patient has multiple thoraco-abdominal 'café au lait' spots. Clinical examination showed a lump of the left breast measuring 9 cm of diameter, which was noticed for 6 months. There was a left inguinal mass of 6 cm of diameter. The patient underwent first a left lumpectomy. Histopathological exam revealed a high-grade fibrosarcoma of the left breast measuring 7.5 cm. Three months later, the patient underwent a left mastectomy and excision of the inguinal mass, which was a neurofibroma. An adjuvant chemotherapy and radiation therapy were indicated, but not applied because of the timeout. The patient is now alive after a follow up of 6 years, with no loco-regional recurrence or metastasis. Conclusion: The relationship between NF1 and breast cancer need to be more clarified by further studies. Establishing a specific screening program of these patients may help to make an earlier diagnosis of breast cancer.

Keywords: neurofibromatosis, breast, sarcoma, cancer

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Authors: Yong Cang

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RJV001 is a subcutaneous injection containing mutated recombinant Collagenase H (ColH), leading to disruption of collagen matrix in adipose tissue and programmed cell death of adipocytes. Here we reported our clinical investigation of the safety, tolerance and pharmacodynamics of localized RJV001 injection into healthy human abdominal fat tissues (NCT04821648, Arizona Research Center). Investigate the safety, tolerance and clinical pharmacodynamics of subcutaneous RJV001 in humans. In the dose-escalating study, 18 subjects completed the study, 100% female, 78% white, with a mean age of 42[±9.9]. All three tested dose (0.05, 0.075 and 0.15 mg/injection), up to 30 injections, were safe and well-tolerated. Bruising and tenderness to palpation, mild to moderate, were the most frequent local skin reactions but nearly all resolved within 30 days. Additionally, physician-monitored ultrasound measurement showed that a reduction in abdominal fat tissue thickness was consistently observed in Cohort C (0.075, 0.15 mg/injection, 30injections), with a mean reduction of 7.37 [± 2.020] mm. Based on this clinical study, RJV001 has been advanced to phase II clinical studies. In the dose-escalating study, subcutaneously administered RJV001 was safe and well-tolerated in healthy adults up to 0.15 mg/injection, 30 injections. Fat reduction and adipocytolysis were observed by ultrasound measurements and histological analysis for exploratory purposes.

Keywords: fat reduction, mutant collagenase, clinical trial, subcutaneous injection

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Authors: Muhammad Umar Kiani, Muhammad Shahbaz

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Performance of any vehicle can be predicted by its design/modeling and optimization. Design optimization leads to efficient performance. Followed by horizontal launch, the air launch re-entry vehicle undergoes a launch maneuver by introducing a carefully selected angle of attack profile. This angle of attack profile is the basic element to complete a specified mission. Flight program of said vehicle is optimized under the constraints of the maximum allowed angle of attack, lateral and axial loads and with the objective of reaching maximum altitude. The main focus of this study is the endo-atmospheric phase of the ascent trajectory. A three degrees of freedom trajectory model is simulated in MATLAB. The optimization process uses evolutionary algorithm, because of its robustness and efficient capacity to explore the design space in search of the global optimum. Evolutionary Algorithm based trajectory optimization also offers the added benefit of being a generalized method that may work with continuous, discontinuous, linear, and non-linear performance matrix. It also eliminates the requirement of a starting solution. Optimization is particularly beneficial to achieve maximum advantage without increasing the computational cost and affecting the output of the system. For the case of launch vehicles we are immensely anxious to achieve maximum performance and efficiency under different constraints. In a launch vehicle, flight program means the prescribed variation of vehicle pitching angle during the flight which has substantial influence reachable altitude and accuracy of orbit insertion and aerodynamic loading. Results reveal that the angle of attack profile significantly affects the performance of the vehicle.

Keywords: endo-atmospheric, evolutionary algorithm, efficient performance, optimization process

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Authors: Arias Fernando, Juan Bojórquez, Edén Bojórquez, Alfredo Reyes-Salazar, Fernando de J. Velarde, Robespierre Chávez, J. Martin Leal, Victor Baca

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The present study focuses on the optimization of different structural systems employed in tall steel buildings, with a specific focus on the city of Acapulco, Guerrero, a region known for its high seismic activity. Using the spectral modal method, analyses were conducted to assess the ability of these buildings to withstand seismic forces and other external loads. After performing a detailed analysis of various models, the results were compared based on various engineering parameters, including maximum interstory drift, base shear, displacements, and the total weight of the structures, the latter being considered as an estimate of the cost of the proposed systems. The findings of this study indicate that steel frames stand out as a viable option for tall buildings in question. However, areas of potential improvement were identified, suggesting opportunities for further optimization of the design and seismic resistance of these structures. This study provides a deep and insightful perspective on the optimization of structural systems in tall steel buildings, offering valuable information for engineers and professionals in the field involved in similar projects.

Keywords: high seismic zone, irregular buildings, optimization design, steel buildings

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Authors: Mehdi Jalalpour, Mazdak Tootkaboni

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We present a computationally efficient method for reliability-based topology optimization under material properties uncertainty, which is assumed to be lognormally distributed and correlated within the domain. Computational efficiency is achieved through estimating the response statistics with stochastic perturbation of second order, using these statistics to fit an appropriate distribution that follows the empirical distribution of the response, and employing an efficient gradient-based optimizer. The proposed algorithm is utilized for design of new structures and the changes in the optimized topology is discussed for various levels of target reliability and correlation strength. Predictions were verified thorough comparison with results obtained using Monte Carlo simulation.

Keywords: material uncertainty, stochastic perturbation, structural reliability, topology optimization

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Authors: P. Gunnasegaran, M. Z. Abdullah, M. Z. Yusoff, Nur Irmawati

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This study presents experimental and optimization of nanoparticle mass concentration and heat input based on the total thermal resistance (Rth) of loop heat pipe (LHP), employed for PC-CPU cooling. In this study, silica nanoparticles (SiO2) in water with particle mass concentration ranged from 0% (pure water) to 1% is considered as the working fluid within the LHP. The experimental design and optimization is accomplished by the design of the experimental tool, Response Surface Methodology (RSM). The results show that the nanoparticle mass concentration and the heat input have a significant effect on the Rth of LHP. For a given heat input, the Rth is found to decrease with the increase of the nanoparticle mass concentration up to 0.5% and increased thereafter. It is also found that the Rth is decreased when the heat input is increased from 20W to 60W. The results are optimized with the objective of minimizing the Rt, using Design-Expert software, and the optimized nanoparticle mass concentration and heat input are 0.48% and 59.97W, respectively, the minimum thermal resistance being 2.66(ºC/W).

Keywords: loop heat pipe, nanofluid, optimization, thermal resistance

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Authors: Vladimir Zobov, Nail Nazarov, Alexandra Vyshtakalyuk, Vyacheslav Semenov, Irina Galyametdinova, Vladimir Reznik

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The aim of this study was to investigate hepatoprotective properties of the Xymedon derivative L-ascorbate 1- (2-hydroxyethyl)-4,6-dimethyl-1,2-dihydropyrimidine-2-one (XD), which exhibits high efficiency as actoprotector. The study was carried out on 68 male albino rats weighing 250-400 g using preventive exposure to the test preparation. Effectiveness of XD win comparison with effectiveness of Xymedon (original substance) after administration of the compounds in identical doses. Maximum dose was 20 mg/kg. The animals orally received Xymedon or its derivative in doses of 10 and 20 mg/kg over 4 days. In 1-1.5 h after drug administration, CCl4 in vegetable oil (1:1) in a dose of 2 ml/kg. Controls received CCl4 but without hepatoprotectors. Intact control group consisted of rats, not receiving CCl4 or other compounds. The next day after the last administration of CCl4 and compounds under study animals were dehematized under ether anesthesia, blood and liver samples were taken for biochemical and histological analysis. Xymedon and XD administered according to the preventice scheme, exerted hepatoprotective effects: Xymedon — in the dose of 20 mg/kg, XD — in doses of 10 and 20 mg/kg. The drugs under study had different effects on liver condition, affected by induction with CCl4. Xymedon had a more pronounced effect both on the ALT level, which can be elevated not only due to destructive changes in hepatocytes, but also as a cholestasis manifestation, and on the serum total protein level, which reflects protein synthesis in liver. XD had a more pronounced effect on AST level, which is one of the markers of hepatocyte damage. Lower effective dose of XD — 10 mg/kg, compared to Xymedon effective according to, and its pronounced effect on AST, the hepatocyte cytolysis marker, is indicative of its higher preventive effectiveness, compared to Xymedon. This work was performed with the financial support of Russian Science Foundation (grant No: 14-50-00014).

Keywords: hepatoprotectors, pyrimidine derivatives, toxic liver damage, xymedon

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Authors: Huang Wei-Yi

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Objective: This article explores the intensive care nursing experience of a terminal lung cancer patient who received palliative care after tracheal intubation. The patient was nearing death, and the family experienced sadness and grief as they faced the patient’s deteriorating condition and impending death. Methods: The patient was diagnosed with lung cancer in 2018 and received chemotherapy and radiation therapy with regular outpatient follow-ups. Due to brain metastasis and recent poor pain control and treatment outcomes, the patient was admitted to the intensive care unit (ICU), where the tracheal tube was removed, and palliative care was initiated. During the care period, a holistic assessment was conducted, addressing the physical, psychological, social, and spiritual aspects of care. Medical records were reviewed, interviews and family meetings were held, and a comprehensive assessment was carried out by the critical care team in collaboration with the palliative care team. The primary nursing issues identified included pain, ineffective breathing patterns, fear of death, and altered tissue perfusion. Results: Throughout the care process, the palliative care nurse, along with the family, utilized listening, caring, companionship, pain management, essential oil massage, distraction, and comfortable positioning to alleviate the patient’s pain and breathing difficulties. The use of Morphine 6mg in 0.9% N/S 50ml IV drip q6h reduced the FLACC pain score from 6 to 3. The patient’s respiratory rate improved from 28 breaths/min to 18-22 breaths/min, and sleep duration increased from 4 to 7 uninterrupted hours. The holistic palliative care approach, coupled with the involvement of the palliative care team, facilitated expressions of gratitude, apologies, and love between the patient and family. Visiting hours were extended, and with the nurse’s assistance, these moments were recorded and shared with the patient’s consent, providing cherished memories for the family. The patient’s end-of-life experience was thus improved, and the family was able to find peace. This case also served to promote the concept of palliative care, ensuring that more patients and families receive high-quality nursing care. Conclusion: When caring for terminal patients, collaboration with the palliative care team, including social workers, clergy, psychologists, and nutritionists, is essential. Involving the family in decision-making and providing opportunities for closeness and expressions of gratitude improve personalized care and enhance the patient's quality of life. Upon transferring to the ward, the patient’s hemodynamic stability was maintained, including SBP 110-130 mmHg, respiratory rate 20-22 breaths/min, and pain score <3. The patient was later discharged and transitioned to home hospice care for ongoing support.

Keywords: intensive care, lung cancer, palliative care, ICU

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Authors: Mefleh Hamideen

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In this investigation, the activity concentrations of ²²⁶Ra, ²³²Th, and ⁴⁰K, of some ceramic tile materials used in the local market of Jordan for interior decoration were determined by making use of High Purity Germanium (HPGe) detector. Twenty samples of the different countries of origin and sizes used in Jordan were analyzed. The concentration values of the last-mentioned radionuclides ranged from 30 Bq.kg⁻¹ (Sample from Jordan) to 98 Bq.kg⁻¹ (Sample from China) for ²²⁶Ra, 31 Bq.kg⁻¹ (Sample from Italy) to 98 Bq.kg⁻¹ (Sample from China) for ²³²Th, and 129 Bq.kg⁻¹ (Sample from Spain) to 679 Bq.kg⁻¹ (Sample from Italy) for ⁴⁰K. Based on the calculated activity concentrations, some radiological parameters have been calculated to test the radiation hazards in the ceramic tiles. In this work, the following parameters: Total absorbed dose rate (DR), Annual effective dose rate (HR), Radium equivalent activity (Raeq), Radon emanation coefficient F (%) and Radon mass exhalation rate (Em) were calculated for all ceramic tiles and listed in the body of the work. Fortunately, the average calculated values of all parameters are less than the recommended values for each parameter. Consequently, almost all the examined ceramic materials appear to have low radon emanation coefficients. As a result of that investigation, no problems on people can appear by using those ceramic tiles in Jordan.

Keywords: radon emanation coefficient, radon mass exhalation rate, total annual effective dose, radon level

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Authors: Zakir Husain

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Main objective of a power transformer design optimization problem requires minimizing the total overall cost and/or mass of the winding and core material by satisfying all possible constraints obligatory by the standards and transformer user requirement. The constraints include appropriate limits on winding fill factor, temperature rise, efficiency, no-load current and voltage regulation. The design optimizations tasks are a constrained minimum cost and/or mass solution by optimally setting the parameters, geometry and require magnetic properties of the transformer. In this paper, present the above design problems have been formulated by using genetic algorithm (GA) and simulated annealing (SA) on the MATLAB platform. The importance of the presented approach is stems for two main features. First, proposed technique provides reliable and efficient solution for the problem of design optimization with several variables. Second, it guaranteed to obtained solution is global optimum. This paper includes a demonstration of the application of the genetic programming GP technique to transformer design.

Keywords: optimization, power transformer, genetic algorithm (GA), simulated annealing technique (SA)

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Authors: Reza Abbasi, Ahmad Hamidi Benam

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Shell structures have many geometrical variables that modify some of these parameters to improve the mechanical behavior of the shell. On the other hand, the behavior of such structures depends on their geometry rather than on mass. Optimization techniques are useful in finding the geometrical shape of shell structures to improve mechanical behavior, especially to prevent or reduce bending anchors. The overall objective of this research is to optimize the shape of concrete shells using the thickness and height parameters along the reference curve and the overall shape of this curve. To implement the proposed scheme, the geometry of the structure was formulated using nonlinear curves. Shell optimization was performed under equivalent static loading conditions using the modified bird community algorithm. The results of this optimization show that without disrupting the initial design and with slight changes in the shell geometry, the structural behavior is significantly improved.

Keywords: concrete shells, shape optimization, spinless curves, modified particle community algorithm

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Authors: Amber Elyse Corrigan, Alexander Smith, Anna Pennington, Ben Carter, Jonathan Hewitt

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Background and Purpose: Morbidity secondary to stroke is highly heterogeneous, but it is important to both patients and clinicians in post-stroke management and adjustment to life after stroke. The consideration of post-stroke morbidity clinically and from the patient perspective has been poorly measured. The patient-reported outcome measures (PROs) in morbidity assessment help improve this knowledge gap. The primary aim of this study was to consider the association between PRO outcomes and stroke predictors. Methods: A multicenter prospective cohort study assessed 549 stroke patients at 19 hospital sites across England and Wales during 2019. Following a stroke event, demographic, clinical, and PRO measures were collected. Prevalence of morbidity within PRO measures was calculated with associated 95% confidence intervals. Predictors of domain outcome were calculated using a multilevel generalized linear model. Associated P -values and 95% confidence intervals are reported. Results: Data were collected from 549 participants, 317 men (57.7%) and 232 women (42.3%) with ages ranging from 25 to 97 (mean 72.7). PRO morbidity was high post-stroke; 93.2% of the cohort report post-stroke PRO morbidity. Previous stroke, diabetes, and gender are associated with worse patient-reported outcomes across both the physical and cognitive domains. Conclusions: This large-scale multicenter cohort study illustrates the high proportion of morbidity in PRO measures. Further, we demonstrate key predictors of adverse outcomes (Diabetes, previous stroke, and gender) congruence with clinical predictors. The PRO has been demonstrated to be an informative and useful stroke when considering patient-reported outcomes and has wider implications for considerations of PROs in clinical management. Future longitudinal follow-up with PROs is needed to consider association of long-term morbidity.

Keywords: morbidity, patient-reported outcome, PRO, stroke

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Authors: Alireza Lavaei, Alireza Lohrasbi, Mohammadali M. Shahlaei

Abstract:

To reduce the overall time of structural optimization for earthquake loads two strategies are adopted. In the first strategy, a neural system consisting self-organizing map and radial basis function neural networks, is utilized to predict the time history responses. In this case, the input space is classified by employing a self-organizing map neural network. Then a distinct RBF neural network is trained in each class. In the second strategy, an improved genetic algorithm is employed to find the optimum design. A 72-bar space truss is designed for optimal weight using exact and approximate analysis for the El Centro (S-E 1940) earthquake loading. The numerical results demonstrate the computational advantages and effectiveness of the proposed method.

Keywords: optimization, genetic algorithm, neural networks, self-organizing map

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Authors: Xiaohua Zou, Yongxin Su

Abstract:

The reasonable operation of heating, ventilation, and air conditioning (HVAC) is of great significance in improving the security, stability, and economy of power system operation. However, the uncertainty of the operating environment, thermal comfort varies by users and rapid decision-making pose challenges for HVAC demand response optimization. In this regard, this paper proposes a reinforcement learning-based method for HVAC demand response optimization considering few-shot personalized thermal comfort (PTC). First, an HVAC DR optimization framework based on few-shot PTC model and DRL is designed, in which the output of few-shot PTC model is regarded as the input of DRL. Then, a few-shot PTC model that distinguishes between awake and asleep states is established, which has excellent engineering usability. Next, based on soft actor criticism, an HVAC DR optimization algorithm considering the user’s PTC is designed to deal with uncertainty and make decisions rapidly. Experiment results show that the proposed method can efficiently obtain use’s PTC temperature, reduce energy cost while ensuring user’s PTC, and achieve rapid decision-making under uncertainty.

Keywords: HVAC, few-shot personalized thermal comfort, deep reinforcement learning, demand response

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Authors: Shaikah Alsubayae, Gianluigi Casse, Carlos Chavez, Jon Taylor, Alan Taylor, Mohammad Alsulimane

Abstract:

Achieving precise radiotherapy through carbon therapy necessitates the accurate monitoring of radiation dose distribution within the patient's body. This process is pivotal for targeted tumor treatment, minimizing harm to healthy tissues, and enhancing overall treatment effectiveness while reducing the risk of side effects. In our investigation, we adopted a methodological approach to monitor secondary proton doses in carbon therapy using Monte Carlo (MC) simulations. Initially, Geant4 simulations were employed to extract the initial positions of secondary particles generated during interactions between carbon ions and water, including protons, gamma rays, alpha particles, neutrons, and tritons. Subsequently, we explored the relationship between the carbon ion beam and these secondary particles. Interaction vertex imaging (IVI) proves valuable for monitoring dose distribution during carbon therapy, providing information about secondary particle locations and abundances, particularly protons. The IVI method relies on charged particles produced during ion fragmentation to gather range information by reconstructing particle trajectories back to their point of origin, known as the vertex. In the context of carbon ion therapy, our simulation results indicated a strong correlation between some secondary particles and the range of carbon ions. However, challenges arose due to the unique elongated geometry of the target, hindering the straightforward transmission of forward-generated protons. Consequently, the limited protons that did emerge predominantly originated from points close to the target entrance. Fragment (protons) trajectories were approximated as straight lines, and a beam back-projection algorithm, utilizing interaction positions recorded in Si detectors, was developed to reconstruct vertices. The analysis revealed a correlation between the reconstructed and actual positions.

Keywords: radiotherapy, carbon therapy, monitor secondary proton doses, interaction vertex imaging

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Authors: Hai Huu Le, Paul Junor, Moshi Geso, Graeme O’Keefe

Abstract:

In this paper, the authors propose a personal wearable directionally-sensitive radiation dosimeter using multiple semiconductor CdZnTe detectors. The proposed dosimeter not only measures the real-time dose rate but also provide the direction of the radioactive source. A linear relationship between radioactive source direction and the radiation intensity measured by each detectors is established and an equation to determine the source direction is derived by the authors. The efficiency and accuracy of the proposed dosimeter is verified by simulation using Geant4 package. Results have indicated that in a measurement duration of about 7 seconds, the proposed dosimeter was able to estimate the direction of a 10μCi 137/55Cs radioactive source to within 2 degrees.

Keywords: dose rate, Geant4 package, radiation dosimeter, radioactive source direction

Procedia PDF Downloads 325