Search results for: advanced electrochemical oxidation

Authors: Shabnam Abdi, Behzad Toosi

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Background: Melanoma is the most lethal type of malignant skin cancer in humans and dogs since it spreads rapidly throughout the body. Despite significant advances in treatment, cancer at an advanced stage has a poor prognosis. Hence, more effective treatments are needed to enhance outcomes with fewer side effects. Erythropoietin-producing hepatocellular receptors are the largest family of receptor tyrosine kinases and are divided into two subfamilies, EphA and EphB, both of which play a significant role in disease, especially cancer. Due to their association with proliferation and invasion in many aggressive types of cancer, Eph receptor tyrosine kinases (Eph RTKs) are promising cancer therapy molecules. Because these receptors have not been studied in canine melanoma, we investigated how EphA2 influences survival and tumorigenicity of melanoma cells. Methods: Expression of EphA2 protein in canine melanoma cell lines and human melanoma cell line was evaluated by Western blot. Melanoma cells were transduced with lentiviral particles encoding Eph-targeting shRNAs or non-silencing shRNAs (control) for silencing the expression of EphA2 receptor, and silencing was confirmed by Western blotting and immunofluorescence. The effect of siRNA treatment on cellular proliferation, colony formation, tumorsphere assay, invasion was analyzed by Resazurin assay Matrigel invasion assay, respectively. Results: Expression of EphA2 was detected in canine and human melanoma cell lines. Moreover, stably silencing EphA2 by specific shRNAs significantly and consistently decreased the expression of EphA2 protein in both human and canine melanoma cells. Proliferation, colony formation, tumorsphere and invasion of melanoma cells were significantly decreased in EphA2 siRNA-treated cells compared to control. Conclusion: Our data provide the first functional evidence that the EphA2 receptor plays a critical role in the malignant cellular behavior of melanoma in both human and dogs.

Keywords: ephA2, targeting, melanoma, human, canine

Procedia PDF Downloads 60

Authors: Basit Aftab, Zhichao Wang, Feng Zhongke

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Land Use and Land Cover Change (LULCC) is a critical environmental issue that has significant effects on biodiversity, ecosystem services, and climate change. This study examines the spatiotemporal dynamics of land use and land cover (LULC) across a three-decade period (1992–2022) in a district area. The goal is to support sustainable land management and urban planning by utilizing the combination of remote sensing, GIS data, and observations from Landsat satellites 5 and 8 to provide precise predictions of the trajectory of urban sprawl. In order to forecast the LULCC patterns, this study suggests a hybrid strategy that combines the Random Forest method with Multilayer Perceptron (MLP) and Markov Chain analysis. To predict the dynamics of LULC change for the year 2035, a hybrid technique based on multilayer Perceptron and Markov Chain Model Analysis (MLP-MCA) was employed. The area of developed land has increased significantly, while the amount of bare land, vegetation, and forest cover have all decreased. This is because the principal land types have changed due to population growth and economic expansion. The study also discovered that between 1998 and 2023, the built-up area increased by 468 km² as a result of the replacement of natural resources. It is estimated that 25.04% of the study area's urbanization will be increased by 2035. The performance of the model was confirmed with an overall accuracy of 90% and a kappa coefficient of around 0.89. It is important to use advanced predictive models to guide sustainable urban development strategies. It provides valuable insights for policymakers, land managers, and researchers to support sustainable land use planning, conservation efforts, and climate change mitigation strategies.

Keywords: land use land cover, Markov chain model, multi-layer perceptron, random forest, sustainable land, remote sensing.

Procedia PDF Downloads 33

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 80

Authors: Mayandi Ramanathan

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Gas turbine blades see the most aggressive thermal stress conditions within the engine, due to Turbine Entry Temperatures in the range of 1500 to 1600°C, but in synchronization with other functional components, they must readily deliver efficient performance, whilst incurring minimal overhaul and repair costs during its service life up to 5 million flying miles. The blades rotate at very high rotation rates and remove significant amount of thermal power from the gas stream. At high temperatures the major component failure mechanism is creep. During its service over time under high temperatures and loads, the blade will deform, lengthen and rupture. High strength and stiffness in the longitudinal direction up to elevated service temperatures are certainly the most needed properties of turbine blades. The proposed advanced Ti alloy material needs a process that provides strategic orientation of metallic ordering, uniformity in composition and high metallic strength. 25% Ta/(Al+Ta) ratio ensures TaAl3 phase formation, where as 51% Al/(Al+Ti) ratio ensures formation of α-Ti3Al and γ-TiAl mixed phases fand the three phase combination ensures minimal Al excess (~1.4% Al excess), unlike Ti-47Al-2Cr-2Nb which has significant excess Al (~5% Al excess) that could affect the service life of turbine blades. This presentation will involve the summary of additive manufacturing and heat treatment process conditions to fabricate turbine blade with Ti-43Al matrix alloyed with optimized amount of refractory Ta metal. Summary of thermo-mechanical test results such as high temperature tensile strength, creep strain rate, thermal expansion coefficient and fracture toughness will be presented. Improvement in service temperature of the turbine blades and corrosion resistance dependence on coercivity of the alloy material will be reported. Phase compositions will be quantified, and a summary of its correlation with creep strain rate will be presented.

Keywords: gas turbine, aerospace, specific strength, creep, high temperature materials, alloys, phase optimization

Procedia PDF Downloads 181

Authors: Nishaben Desai Dholakiya, Anirban Roy, Ranjan Dey

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Understanding ocean thermodynamics has become increasingly critical as Earth's oceans serve as the primary planetary heat regulator, absorbing approximately 93% of excess heat energy from anthropogenic greenhouse gas emissions. This investigation presents a comprehensive analysis of Arabian Sea surface seawater thermodynamics, focusing specifically on heat capacity (Cp) and thermal expansion coefficient (α) - parameters fundamental to global heat distribution patterns. Through high-precision experimental measurements of ultrasonic velocity and density across varying temperature (293.15-318.15K) and salinity (0.5-35 ppt) conditions, it characterize critical thermophysical parameters including specific heat capacity, thermal expansion, and isobaric and isothermal compressibility coefficients in natural seawater systems. The study employs advanced machine learning frameworks - Random Forest, Gradient Booster, Stacked Ensemble Machine Learning (SEML), and AdaBoost - with SEML achieving exceptional accuracy (R² > 0.99) in heat capacity predictions. the findings reveal significant temperature-dependent molecular restructuring: enhanced thermal energy disrupts hydrogen-bonded networks and ion-water interactions, manifesting as decreased heat capacity with increasing temperature (negative ∂Cp/∂T). This mechanism creates a positive feedback loop where reduced heat absorption capacity potentially accelerates oceanic warming cycles. These quantitative insights into seawater thermodynamics provide crucial parametric inputs for climate models and evidence-based environmental policy formulation, particularly addressing the critical knowledge gap in thermal expansion behavior of seawater under varying temperature-salinity conditions.

Keywords: climate change, arabian sea, thermodynamics, machine learning

Procedia PDF Downloads 4

Authors: Helen Coronel, Will Brewer, Peggy Bergeron, Clarissa Hall, Victoria Casson

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Simulation-based training provides the nurse practitioner (NP) student with a safe and controlled environment in which they can practice a real-life scenario. This type of learning fosters critical thinking skills essential to practice. The expectation of this study was that students would have an increase in their competency and confidence after performing the simulation. Approximately 8.4% of Americans suffer from depression. The state of Alabama is ranked 47th out of 50 for access to mental health care. As a result of this significant shortage of mental health providers, primary care providers are frequently put in the position of screening for and treating mental health conditions, such as depression. Family nurse practitioners are often utilized as primary care providers, making their ability to assess, diagnose and treat these disorders a necessary skill. The expected outcome of this simulation is an increase in confidence, competency and the empowerment of the nurse practitioner student’s ability to assess, diagnose and treat a common mood disorder they may encounter in practice. The Kirkpatrick Module was applied for this study. A non-experimental design using descriptive statistical analysis was utilized. The simulation was based on a common psychiatric mood disorder frequently observed in primary care and mental health clinics. Students were asked to watch a voiceover power point presentation prior to their on-campus simulation. The presentation included training on the assessment, diagnosis, and treatment of a patient with depression. Prior to the simulation, the students completed a pre-test, then participated in the simulation, and completed a post-test when done. Apple iPads were utilized to access a simulated health record. Major findings of the study support an increase in students’ competency and confidence when assessing, diagnosing, and treating an adult patient with depression.

Keywords: advanced practice, nurse practitioner, simulation, primary care, depression

Procedia PDF Downloads 95

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

Abstract:

Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should evaluate properly their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, neural networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable of offering an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 70

Authors: Sereen Itani

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As the world aspires for technological innovation, Innovative Robotics Technology-Supported Pedagogic Models in STEAM Education (Science, Technology, Engineering, Arts, and Mathematics) are critical in our global education system to build and enhance the next generation 21st century skills. Thus, diverse international schools endeavor in attempts to construct an integrated robotics and technology enhanced curriculum based on interdisciplinary subjects. Accordingly, it is vital that the globe remains resilient in STEAM fields by equipping the future learners and educators with Innovative Technology Experiences through robotics to support such fields. A variety of advanced teaching methods is employed to learn about Robotics Technology-integrated pedagogic models. Therefore, it is only when STEAM and innovations in Robotic Technology becomes integrated with real-world applications that transformational learning can occur. Robotics STEAM education implementation faces major challenges globally. Moreover, STEAM skills and concepts are communicated in separation from the real world. Instilling the passion for robotics and STEAM subjects and educators’ preparation could lead to the students’ majoring in such fields by acquiring enough knowledge to make vital contributions to the global STEAM industries. Thus, this necessitates the establishment of Pedagogic models such as Innovative Robotics Technologies to enhance STEAM education and develop students’ 21st-century skills. Moreover, an ICT innovative supported robotics classroom will help educators empower and assess students academically. Globally, the Robotics Design System and platforms are developing in schools and university labs creating a suitable environment for the robotics cross-discipline STEAM learning. Accordingly, the research aims at raising awareness about the importance of robotics design systems and methodologies of effective employment of robotics innovative technology-supported pedagogic models to enhance and develop (STEAM) education globally and enhance the next generation 21st century skills.

Keywords: education, robotics, STEAM (Science, Technology, Engineering, Arts and Mathematics Education), challenges

Procedia PDF Downloads 384

Authors: Mehmet Halkaci, Ekrem Öztürk, Mevlüt Türköz, H. Selçuk Halkacı

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Hydromechanical deep drawing (HMD) process is an advanced manufacturing process used to form deep parts with only one forming step. In this process, sheet metal blank can be drawn deeper by means of fluid pressure acting on sheet surface in the opposite direction of punch movement. High limiting drawing ratio, good surface quality, less springback characteristic and high dimensional accuracy are some of the advantages of this process. The performance of the HMD process is affected by various process parameters such as fluid pressure, blank holder force, punch-die radius, pre-bulging pressure and height, punch diameter, friction between sheet-die and sheet-punch. The fluid pressure and bank older force are the main loading parameters and affect the formability of HMD process significantly. The punch diameter also influences the limiting drawing ratio (the ratio of initial sheet diameter to punch diameter) of the sheet metal blank. In this research, optimal loading (fluid pressure and blank holder force) profiles were determined for AA 5754-O sheet material through fuzzy control algorithm developed in previous study using LS-DYNA finite element analysis (FEA) software. In the preceding study, the fuzzy control algorithm was developed utilizing geometrical criteria such as thinning and wrinkling. In order to obtain the final desired part with the developed algorithm in terms of the punch diameter requested, the effect of punch diameter, which is the one of the process parameters, on loading profiles was investigated separately using blank thickness of 1 mm. Thus, the practicality of the previously developed fuzzy control algorithm with different punch diameters was clarified. Also, thickness distributions of the sheet metal blank along a curvilinear distance were compared for the FEA in which different punch diameters were used. Consequently, it was found that the use of different punch diameters did not affect the optimal loading profiles too much.

Keywords: Finite Element Analysis (FEA), fuzzy control, hydromechanical deep drawing, optimal loading profiles, punch diameter

Procedia PDF Downloads 431

Authors: Abderrazak Bannari

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Acid Mine Drainage (AMD) from mine wastes and contaminations of soils and water with metals are considered as a major environmental problem in mining areas. It is produced by interactions of water, air, and sulphidic mine wastes. This environment problem results from a series of chemical and biochemical oxidation reactions of sulfide minerals e.g. pyrite and pyrrhotite. These reactions lead to acidity as well as the dissolution of toxic and heavy metals (Fe, Mn, Cu, etc.) from tailings waste rock piles, and open pits. Soil and aquatic ecosystems could be contaminated and, consequently, human health and wildlife will be affected. Furthermore, secondary minerals, typically formed during weathering of mine waste storage areas when the concentration of soluble constituents exceeds the corresponding solubility product, are also important. The most common secondary mineral compositions are hydrous iron oxide (goethite, etc.) and hydrated iron sulfate (jarosite, etc.). The objectives of this study focus on the detection and mapping of MIOP in the soil using Hyperion EO-1 (Earth Observing - 1) hyperspectral data and constrained linear spectral mixture analysis (CLSMA) algorithm. The abandoned Kettara mine, located approximately 35 km northwest of Marrakech city (Morocco) was chosen as study area. During 44 years (from 1938 to 1981) this mine was exploited for iron oxide and iron sulphide minerals. Previous studies have shown that Kettara surrounding soils are contaminated by heavy metals (Fe, Cu, etc.) as well as by secondary minerals. To achieve our objectives, several soil samples representing different MIOP classes have been resampled and located using accurate GPS ( ≤ ± 30 cm). Then, endmembers spectra were acquired over each sample using an Analytical Spectral Device (ASD) covering the spectral domain from 350 to 2500 nm. Considering each soil sample separately, the average of forty spectra was resampled and convolved using Gaussian response profiles to match the bandwidths and the band centers of the Hyperion sensor. Moreover, the MIOP content in each sample was estimated by geochemical analyses in the laboratory, and a ground truth map was generated using simple Kriging in GIS environment for validation purposes. The acquired and used Hyperion data were corrected for a spatial shift between the VNIR and SWIR detectors, striping, dead column, noise, and gain and offset errors. Then, atmospherically corrected using the MODTRAN 4.2 radiative transfer code, and transformed to surface reflectance, corrected for sensor smile (1-3 nm shift in VNIR and SWIR), and post-processed to remove residual errors. Finally, geometric distortions and relief displacement effects were corrected using a digital elevation model. The MIOP fraction map was extracted using CLSMA considering the entire spectral range (427-2355 nm), and validated by reference to the ground truth map generated by Kriging. The obtained results show the promising potential of the proposed methodology for the detection and mapping of mine iron oxide pollution in the soil.

Keywords: hyperion eo-1, hyperspectral, mine iron oxide pollution, environmental impact, unmixing

Procedia PDF Downloads 228

Authors: Aidan Battison, Neliswa Mama

Abstract:

Environmental pollution by ionic species has been identified as one of the biggest challenges to the sustainable development of communities. The widespread use of organic and inorganic chemical products and the release of toxic chemical species from industrial waste have resulted in a need for advanced monitoring technologies for environment protection, remediation and restoration. Some of the disadvantages of conventional sensing methods include expensive instrumentation, well-controlled experimental conditions, time-consuming procedures and sometimes complicated sample preparation. On the contrary, the development of fluorescent chemosensors for biological and environmental detection of metal ions has attracted a great deal of attention due to their simplicity, high selectivity, eidetic recognition, rapid response and real-life monitoring. Coumarin derivatives S1 and S2 (Scheme 1) containing 1,2,3-triazole moieties at position -3- have been designed and synthesized from azide and alkyne derivatives by CuAAC “click” reactions for the detection of metal ions. These compounds displayed a strong preference for Fe3+ ions with complexation resulting in fluorescent quenching through photo-induced electron transfer (PET) by the “sphere of action” static quenching model. The tested metal ions included Cd2+, Pb2+, Ag+, Na+, Ca2+, Cr3+, Fe3+, Al3+, Cd2+, Ba2+, Cu2+, Co2+, Hg2+, Zn2+ and Ni2+. The detection limits of S1 and S2 were determined to be 4.1 and 5.1 uM, respectively. Compound S1 displayed the greatest selectivity towards Fe3+ in the presence of competing for metal cations. S1 could also be used for the detection of Fe3+ in a mixture of CH3CN/H¬2¬O. Binding stoichiometry between S1 and Fe3+ was determined by using both Jobs-plot and Benesi-Hildebrand analysis. The binding was shown to occur in a 1:1 ratio between the sensor and a metal cation. Reversibility studies between S1 and Fe3+ were conducted by using EDTA. The binding site of Fe3+ to S1 was determined by using 13 C NMR and Molecular Modelling studies. Complexation was suggested to occur between the lone-pair of electrons from the coumarin-carbonyl and the triazole-carbon double bond.

Keywords: chemosensor, "click" chemistry, coumarin, fluorescence, static quenching, triazole

Procedia PDF Downloads 163

Authors: Vivek Anand, Rainer Naegele

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Industry 4.0 is a global mega-trend revolutionizing the world of advanced manufacturing, but also bringing up challenges for SMEs. In response, many regional, as well as digital Industry 4.0 Platforms, have been set up to boost the competencies of established enterprises as well as SMEs. The concept of 'Clusters' is a policy tool that aims to be a starting point to establish sustainable and self-supporting structures in industries of a region by identifying competencies and supporting cluster actors with services that match their growth needs. This paper is motivated by the idea that Clusters have the potential to enable firms, particularly SMEs, to accelerate the innovation process and transition to digital technologies. In this research, the efficacy of Industry 4.0 platforms as Cluster ecosystems is evaluated, especially for SMEs. Focusing on the Baden Wurttemberg region in Germany, an action research method is employed to study how SMEs leverage other actors on Industry 4.0 Platforms to further their Industry 4.0 journeys. The aim is to evaluate how such Industry 4.0 platforms stimulate innovation, cooperation and competitiveness. Additionally, the barriers to these platforms fulfilling their promise to serve as capacity building cluster ecosystems for SMEs in a region will also be identified. The findings will be helpful for academicians and policymakers alike, who can leverage a ‘cluster policy’ to enable Industry 4.0 ecosystems in their regions. Furthermore, relevant management and policy implications stem from the analysis. This will also be of interest to the various players in a cluster ecosystem - like SMEs and service providers - who benefit from the cooperation and competition. The paper will improve the understanding of how a dialogue orientation, a bottom-up approach and active integration of all involved cluster actors enhance the potential of Industry 4.0 Platforms. A strong collaborative culture is a key driver of digital transformation and technology adoption across sectors, value chains and supply chains; and will position Industry 4.0 Platforms at the forefront of the industrial renaissance. Motivated by this argument and based on the results of the qualitative research, a roadmap will be proposed to position Industry 4.0 Platforms as effective clusters ecosystems to support Industry 4.0 adoption in a region.

Keywords: cluster policy, digital transformation, industry 4.0, innovation clusters, innovation policy, SMEs and startups

Procedia PDF Downloads 222

Authors: Balasooriya B. M. C. M., Sujeeva N., Thowfeek Z., Siddiqa Omo, Liyanagunawardana J. E., Jayawardana Saiu, Manathunga S. S., Katulanda G. W.

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Introduction and objectives: Adrenal venous sampling (AVS) is the gold standard to discriminate unilateral primary aldosteronism (UPA) from bilateral disease (BPA). AVS is technically demanding and only performed in a limited number of centers worldwide. To the best of our knowledge, Except for one study conducted in India, no other research studies on this area have been conducted in South Asia. This study aimed to evaluate the effectiveness of AVS in the management of primary aldosteronism. Methods: A total of 32 patients who underwent AVS at the National Hospital of Sri Lanka from April 2021 to April 2023 were enrolled. Demographic, clinical and laboratory data were obtained retrospectively. A procedure was considered successful when adequate cannulation of both adrenal veins was demonstrated. Cortisol gradient across the adrenal vein (AV) and the peripheral vein was used to establish the success of venous cannulation. Lateralization was determined by the aldosterone gradient between the two sides. Continuous and categorical variables were summarized with mean, SD, and proportions, respectively. The mean and standard deviation of the contralateral suppression index (CSI) were estimated with an intercept-only Bayesian inference model. Results: Of the 32 patients, the average age was 52.47 +26.14 and 19 (59.4%) were males. Both AVs were successfully cannulated in 12 (37.5%). Among them, lateralization was demonstrated in 11(91.7%), and one was diagnosed as a bilateral disease. There were no total failures. Right AV cannulation was unsuccessful in 18 (56.25%), of which lateralization was demonstrated in 9 (50%), and others were inconclusive. Left AV cannulation was unsuccessful only in 2 (6.25%); one was lateralized, and the other remained inconclusive. The estimated mean of the CSI was 0.33 (89% credible interval 0.11-0.86). Seven patients underwent unilateral adrenalectomy and demonstrated significant improvement in blood pressure during follow-up. Two patients await surgery. Others were treated medically. Conclusions: Despite failure due to procedural difficulties, AVS remained useful in the management of patients with PA. Moreover, the success of the procedure needs experienced hands and advanced equipment to achieve optimal outcomes in PA.

Keywords: adrenal venous sampling, lateralization, contralateral suppression index, primary aldosteronism

Procedia PDF Downloads 64

Authors: Makhan Maharjan, Mani Ulaganathan, Vanchiappan Aravindan, Srinivasan Madhavi, Jing-Yuan Wang, Tuti Mariana Lim

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The ever-increasing energy demand has made research to develop high performance energy storage systems that are able to fulfill energy needs. Supercapacitors have potential applications as portable energy storage devices. In recent years, there have been huge research interests to enhance the performances of supercapacitors via exploiting novel promising carbon precursors, tailoring textural properties of carbons, exploiting various electrolytes and device types. In this work, we employed orange peel (waste material) as the starting material and synthesized activated carbon by pyrolysis of KOH impregnated orange peel char at 800 °C in argon atmosphere. The resultant orange peel-derived activated carbon (OP-AC) exhibited BET surface area of 1,901 m² g-1, which is the highest surface area so far reported for the orange peel. The pore size distribution (PSD) curve exhibits the pores centered at 11.26 Å pore width, suggesting dominant microporosity. The high surface area OP-AC accommodates more ions in the electrodes and its well-developed porous structure facilitates fast diffusion of ions which subsequently enhance electrochemical performance. The OP-AC was studied as positive electrode in combination with different negative electrode materials, such as pre-lithiated graphite (LiC6) and Li4Ti5O12 for making hybrid capacitors. The lithium ion capacitor (LIC) fabricated using OP-AC with pre-lithiated graphite delivered high energy density of ~106 Wh kg–1. The energy density for OP-AC||Li4Ti5O12 capacitor was ~35 Wh kg⁻¹. For comparison purpose, configuration of OP-AC||OP-AC capacitors were studied in both aqueous (1M H2SO4) and organic (1M LiPF6 in EC-DMC) electrolytes, which delivered the energy density of 8.0 Wh kg⁻¹ and 16.3 Wh kg⁻¹, respectively. The cycling retentions obtained at current density of 1 A g⁻¹ were ~85.8, ~87.0 ~82.2 and ~58.8% after 2500 cycles for OP-AC||OP-AC (aqueous), OP-AC||OP-AC (organic), OP-AC||Li4Ti5O12 and OP-AC||LiC6 configurations, respectively. In addition, characterization studies were performed by elemental and proximate composition, thermogravimetry analysis, field emission-scanning electron microscopy, Raman spectra, X-ray diffraction (XRD) pattern, Fourier transform-infrared, X-ray photoelectron spectroscopy (XPS) and N2 sorption isotherms. The morphological features from FE-SEM exhibited well-developed porous structures. Two typical broad peaks observed in the XRD framework of the synthesized carbon implies amorphous graphitic structure. The ratio of 0.86 for ID/IG in Raman spectra infers high degree of graphitization in the sample. The band spectra of C 1s in XPS display the well resolved peaks related to carbon atoms in various chemical environments. The presence of functional groups is also corroborated from the FTIR spectroscopy. Characterization studies revealed the synthesized carbon to be promising electrode material towards the application for energy storage devices. Overall, the intriguing properties of OP-AC make it a new alternative promising electrode material for the development of high energy lithium ion capacitors from abundant, low-cost, renewable biomass waste. The authors gratefully acknowledge Agency for Science, Technology and Research (A*STAR)/ Singapore International Graduate Award (SINGA) and Nanyang Technological University (NTU), Singapore for funding support.

Keywords: energy storage, lithium-ion capacitors, orange peels, porous activated carbon

Procedia PDF Downloads 229

Authors: J. Shamash

Abstract:

The high-school curriculum in algebra deals mainly with the solution of different types of equations. However, modern algebra has a completely different viewpoint and is concerned with algebraic structures and operations. A question then arises: What might be the relevance and contribution of an abstract algebra course for developing expertise and mathematical perspective in secondary school mathematics instruction? This is the focus of this paper. The course Algebra: From Equations to Structures is a carefully designed abstract algebra course for Israeli secondary school mathematics teachers. The course provides an introduction to algebraic structures and modern abstract algebra, and links abstract algebra to the high-school curriculum in algebra. It follows the historical attempts of mathematicians to solve polynomial equations of higher degrees, attempts which resulted in the development of group theory and field theory by Galois and Abel. In other words, algebraic structures grew out of a need to solve certain problems, and proved to be a much more fruitful way of viewing them. This theorems in both group theory and field theory. Along the historical ‘journey’, many other major results in algebra in the past 150 years are introduced, and recent directions that current research in algebra is taking are highlighted. This course is part of a unique master’s program – the Rothschild-Weizmann Program – offered by the Weizmann Institute of Science, especially designed for practicing Israeli secondary school teachers. A major component of the program comprises mathematical studies tailored for the students at the program. The rationale and structure of the course Algebra: From Equations to Structures are described, and its relevance to teaching school algebra is examined by analyzing three kinds of data sources. The first are position papers written by the participating teachers regarding the relevance of advanced mathematics studies to expertise in classroom instruction. The second data source are didactic materials designed by the participating teachers in which they connected the mathematics learned in the mathematics courses to the school curriculum and teaching. The third date source are final projects carried out by the teachers based on material learned in the course.

Keywords: abstract algebra , linking abstract algebra and school mathematics, school algebra, secondary school mathematics, teacher professional development

Procedia PDF Downloads 146

Authors: Achitphol Chookaew, Paramee Thongsukhsai, Patamarerk Engsontia, Narongwit Nakwan, Pritsana Raugrut

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Lung cancer is one of the most common malignancies and primary cause of death due to cancer worldwide. Non-small cell lung cancer (NSCLC) is the main subtype in which majority of patients present with advanced-stage disease. Herein, we analyzed differentially expressed genes to find potential biomarkers for lung cancer diagnosis as well as prognostic markers. We used transcriptome data from our 2 NSCLC patients and public data (GSE81089) composing of 8 NSCLC and 10 normal lung tissues. Differentially expressed genes (DEGs) between NSCLC and normal tissue and between early-stage and late-stage NSCLC were analyzed by the DESeq2. Pairwise correlation was used to find the DEGs with false discovery rate (FDR) adjusted p-value £ 0.05 and |log2 fold change| ³ 4 for NSCLC versus normal and FDR adjusted p-value £ 0.05 with |log2 fold change| ³ 2 for early versus late-stage NSCLC. Bioinformatic tools were used for functional and pathway analysis. Moreover, the top ten genes in each comparison group were verified the expression and survival analysis via GEPIA. We found 150 up-regulated and 45 down-regulated genes in NSCLC compared to normal tissues. Many immnunoglobulin-related genes e.g., IGHV4-4, IGHV5-10-1, IGHV4-31, IGHV4-61, and IGHV1-69D were significantly up-regulated. 22 genes were up-regulated, and five genes were down-regulated in late-stage compared to early-stage NSCLC. The top five DEGs genes were KRT6B, SPRR1A, KRT13, KRT6A and KRT5. Keratin 6B (KRT6B) was the most significantly increased gene in the late-stage NSCLC. From GEPIA analysis, we concluded that IGHV4-31 and IGKV1-9 might be used as diagnostic biomarkers, while KRT6B and KRT6A might be used as prognostic biomarkers. However, further clinical validation is needed.

Keywords: differentially expressed genes, early and late-stages, gene ontology, non-small cell lung cancer transcriptomics

Procedia PDF Downloads 114

Authors: Jane E. Souyave, Judith Bower

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This study is an ongoing collaborative project between the University of Central Lancashire and the Alzheimer’s Society to design and test the idea of using interactive tools for a person living with dementia and their carers. It is hoped that the tools will fulfill the possible needs of engagement and interaction as dementia progresses, therefore enhancing wellbeing and improving quality of life for the person with dementia and their carers. The project was informed by Kitwood’s five psychological needs for producing wellbeing and explored evidence that fidgeting is often seen as a form of agitation and a negative symptom of dementia. Although therapy for agitation may be well established, there is a lack of appropriate items aimed at people in the later stage of dementia, that are not childlike or medical in their aesthetic. Individuals may fidget in a particular way and the tools in the Fidget Widget Toolkit have been designed to encourage repetitive movements of the hand, specifically to address the abilities of people with relatively advanced dementia. As an intervention, these tools provided a new approach that had not been tested in dementia care. Prototypes were created through an iterative design process and tested with a number of people with dementia and their carers, using quantitative and qualitative methods. Dementia Care Mapping was used to evaluate the impact of the intervention in group settings. Cohen Mansfield’s Agitation Inventory was used to record the daily use and interest of the intervention for people in their usual place of residence. The results informed the design of a new set of devices to promote safe, stigma free fidgeting as a positive experience, meaningful activity and enhance wellbeing for people in the later stage of dementia. The outcomes addressed the needs of individuals by reducing agitation and restlessness through helping them to connect, engage and act independently, providing the means of doing something for themselves that they were able to do. The next stage will be to explore the commercial feasibility of the Fidget Widget Toolkit so that it can be introduced as good practice and innovation in dementia care. It could be used by care homes, with carers and their families to support wellbeing and lead the way in providing some positive experiences and person-centred approaches that are lacking in the later stage of dementia.

Keywords: dementia, design, fidgeting, healthcare, positive moments, quality of life, wellbeing

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Authors: Pelin Balcik Ercin

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Introduction: ZEB transcription factor family member ZEB2, has a role in epithelial to mesenchymal transition during development and metastasis. The altered circulating extracellular miRNAs expression is observed in diseases, and extracellular miRNAs have an important role in cancer cell microenvironment. In ChIP-Seq study, the expression of miR-2110 was found to be regulated by ZEB2. In this study, the effects of miR2110 on cell proliferation and migration of hepatocellular carcinoma (HCC) cells were examined. Material and Methods: SNU398 cells transfected with mimic miR2110 (20nM) (HMI0375, Sigma-Aldrich) and negative control miR (HMC0002, Sigma-Aldrich). MicroRNA isolation was accomplished with miRVANA isolation kit according to manufacturer instructions. cDNA synthesis was performed expression, respectively, and calibrated with Ct of controls. The real-time quantitative PCR (RT-qPCR) reaction was performed using the TaqMan Fast Advanced Master Mix (Thermo Sci.). Ct values of miR2110 were normalized to miR-186-5p and miR16-5p for the intracellular gene. Cell proliferation analysis was analyzed with the xCELLigence RTCA System. Wound healing assay was analyzed with the ImageJ program and relative fold change calculated. Results: The mimic-miR-2110 transfected SNU398 cells nearly nine-fold (log2) more miR-2110 expressed compared to negative control transfected cells. The mimic-miR-2110 transfected HCC cell proliferation significantly inhibited compared to the negative control cells. Furthermore, miR-2110-SNU398 cell migration capacity was relatively four-fold decreased compared to negative control-miR-SNU398 cells. Conclusion: Our results suggest the miR-2110 inhibited cell proliferation and also miR-2110 negatively affect cell migration compared to control groups in HCC cells. These data suggest the complexity of microRNA EMT transcription factors regulation. These initial results are pointed out the predictive biomarker capacity of miR-2110 in HCC.

Keywords: epithelial to mesenchymal transition, EMT, hepatocellular carcinoma cells, micro-RNA-2110, ZEB2

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Authors: Sergio Celaschi, Henrique Canavarro de Alencar, Claaudecir Biazoli

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Effluent quality is of the highest priority for compliance with the permit limits of environmental protection agencies and ensures the protection of their local water system. Of the pollutants monitored, the biochemical oxygen demand (BOD) posed one of the greatest challenges. This work presents a solution for wastewater treatment plants - WWTP’s ability to react to different situations and meet treatment goals. Delayed BOD5 results from the lab take 7 to 8 analysis days, hindered the WWTP’s ability to react to different situations and meet treatment goals. Reducing BOD turnaround time from days to hours is our quest. Such a solution is based on a system of two BOD bioreactors associated with Digital Twin (DT) and Machine Learning (ML) methodologies via an Internet of Things (IoT) platform to monitor and control a WWTP to support decision making. DT is a virtual and dynamic replica of a production process. DT requires the ability to collect and store real-time sensor data related to the operating environment. Furthermore, it integrates and organizes the data on a digital platform and applies analytical models allowing a deeper understanding of the real process to catch sooner anomalies. In our system of continuous time monitoring of the BOD suppressed by the effluent treatment process, the DT algorithm for analyzing the data uses ML on a chemical kinetic parameterized model. The continuous BOD monitoring system, capable of providing results in a fraction of the time required by BOD5 analysis, is composed of two thermally isolated batch bioreactors. Each bioreactor contains input/output access to wastewater sample (influent and effluent), hydraulic conduction tubes, pumps, and valves for batch sample and dilution water, air supply for dissolved oxygen (DO) saturation, cooler/heater for sample thermal stability, optical ODO sensor based on fluorescence quenching, pH, ORP, temperature, and atmospheric pressure sensors, local PLC/CPU for TCP/IP data transmission interface. The dynamic BOD system monitoring range covers 2 mg/L < BOD < 2,000 mg/L. In addition to the BOD monitoring system, there are many other operational WWTP sensors. The CPU data is transmitted/received to/from the digital platform, which in turn performs analyses at periodic intervals, aiming to feed the learning process. BOD bulletins and their credibility intervals are made available in 12-hour intervals to web users. The chemical kinetics ML algorithm is composed of a coupled system of four first-order ordinary differential equations for the molar masses of DO, organic material present in the sample, biomass, and products (CO₂ and H₂O) of the reaction. This system is solved numerically linked to its initial conditions: DO (saturated) and initial products of the kinetic oxidation process; CO₂ = H₂0 = 0. The initial values for organic matter and biomass are estimated by the method of minimization of the mean square deviations. A real case of continuous monitoring of BOD wastewater effluent quality is being conducted by deploying an IoT application on a large wastewater purification system located in S. Paulo, Brazil.

Keywords: effluent treatment, biochemical oxygen demand, continuous monitoring, IoT, machine learning

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Authors: Azizah M. Nahari, Peter Doerner

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Phosphate (Pi) is one of the essential macronutrients in plant growth and development, and it plays a central role in metabolic processes in plants, particularly photosynthesis and respiration. Limitation of crop productivity by Pi is widespread and is likely to increase in the future. Applications of Pi fertilizers have improved soil Pi fertility and crop production; however, they have also caused environmental damage. Therefore, in order to reduce dependence on unsustainable Pi fertilizers, a better understanding of phosphate use efficiency (PUE) is required for engineering nutrient-efficient crop plants. Enhanced Pi efficiency can be achieved by improved productivity per unit Pi taken up. We aim to identify, by using association mapping, general features of the most important loci that contribute to increased PUE to allow us to delineate the physiological pathways involved in defining this trait in the model plant Arabidopsis. As PUE is in part determined by the efficiency of uptake, we designed a hydroponic system to avoid confounding effects due to differences in root system architecture leading to differences in Pi uptake. In this system, 18 parental lines and 217 lines of the MAGIC population (a Multiparent Advanced Generation Inter-Cross) grown in high and low Pi availability conditions. The results showed revealed a large variation of PUE in the parental lines, indicating that the MAGIC population was well suited to identify PUE loci and pathways. 2 of 18 parental lines had the highest PUE in low Pi while some lines responded strongly and increased PUE with increased Pi. Having examined the 217 MAGIC population, considerable variance in PUE was found. A general feature was the trend of most lines to exhibit higher PUE when grown in low Pi conditions. Association mapping is currently in progress, but initial observations indicate that a wide variety of physiological processes are involved in influencing PUE in Arabidopsis. The combination of hydroponic growth methods and genome-wide association mapping is a powerful tool to identify the physiological pathways underpinning complex quantitative traits in plants.

Keywords: hydroponic system growth, phosphate use efficiency (PUE), Genome-wide association mapping, MAGIC population

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Authors: F. Polito, M. Cucinotta, A. Conti, C. Lo Giudice, C. Tomasello, F. Angileri, D. La Torre, M. Aguennouz

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Glioblastoma multiforme (GBM) is the most aggressive form of brain tumors, with an extremely poor prognosis. Telomeres lenght is associated with tumor progression in several type of human cancers and telomere elongation is a common molecular feature of advanced malignancies. Among the telomeric shelterin proteins PTOP is required for telomeric protein complex assembly, telomerase recruitment and activity, and telomere length regulation through a PTOP-telomerase interaction. Previous studies suggest that PTOP upregulation is involved in radioresistance and telomere lengthening in colorectal cancer cells. Moreover, in human osteosarcoma cells PTOP deletion led to telomere shortening, increased apoptosis and radiation sensitivity enhancement. However, to date, little is known about the role of PTOP in progression of glioma cancers. In light of this background aim of the study is to investigate the expression of PTOP in different grades of human glioma and its correlation with the pathological grade of gliomas, grades of malignancy, proliferative activity and apoptosis. Fifteen Low Grade Astrocytomas (LGA), 18 Anaplastic Astrocytomas (AA) and 26 Glioblastoma Multiforme (GBM) samples were analyzed. Three samples of normal brain tissue (NBT) were used as controls. The expression levels of PTOP, h-TERT, BIRC1 and cyclin D1 were determined by real time PCR and/or western blot. Results obtained shows that PTOP expression in glioma tissues is tightly correlated with clinical grade ( p < 0.01 ). No correlation was found between PTOP expression and other clinicopathologic parameters. The expression of PTOP was positively correlated with the expression of hTERT and TERF1. Furthermore PTOP positively correlates with cyclin D1 and negatively correlates with the expression of BIRC1. Our findings indicate that PTOP might play key role in the progression of glioma regulating telomerase activity and likely through regulation of cell cycle and apoptosis. In conclusion results obtained prompted us to speculate that PTOP might represents a potential molecular bio marker and a therapeutic target for the treatment of glioblastoma tumors.

Keywords: glioblastoma, PTOP, telomere, brain tumors

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Authors: Khadija Refouh

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Culture bound-expressions have been a bottleneck for Natural Language Processing (NLP) and comprehension, especially in the case of machine translation (MT). In the last decade, the field of machine translation has greatly advanced. Neural machine translation NMT has recently achieved considerable development in the quality of translation that outperformed previous traditional translation systems in many language pairs. Neural machine translation NMT is an Artificial Intelligence AI and deep neural networks applied to language processing. Despite this development, there remain some serious challenges that face neural machine translation NMT when translating culture bounded-expressions, especially for low resources language pairs such as Arabic-English and Arabic-French, which is not the case with well-established language pairs such as English-French. Machine translation of opaque idioms from English into French are likely to be more accurate than translating them from English into Arabic. For example, Google Translate Application translated the sentence “What a bad weather! It runs cats and dogs.” to “يا له من طقس سيء! تمطر القطط والكلاب” into the target language Arabic which is an inaccurate literal translation. The translation of the same sentence into the target language French was “Quel mauvais temps! Il pleut des cordes.” where Google Translate Application used the accurate French corresponding idioms. This paper aims to perform NMT experiments towards better translation of opaque idioms using high quality clean multilingual corpus. This Corpus will be collected analytically from human generated idiom translation. AutoML translation, a Google Neural Machine Translation Platform, is used as a custom translation model to improve the translation of opaque idioms. The automatic evaluation of the custom model will be compared to the Google NMT using Bilingual Evaluation Understudy Score BLEU. BLEU is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Human evaluation is integrated to test the reliability of the Blue Score. The researcher will examine syntactical, lexical, and semantic features using Halliday's functional theory.

Keywords: multilingual corpora, natural language processing (NLP), neural machine translation (NMT), opaque idioms

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Authors: Bruno Nascimento, Cristina Wanzeller, Jorge Silva, João A. Dias, André Barbosa, José Ribeiro

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The increasing complexity of logistics operations stems from evolving business needs, such as the shift from mass production to mass customization, which demands greater efficiency and flexibility. In response, Industry 4.0 and 5.0 technologies provide improved solutions to enhance operational agility and better meet market demands. The management of kitting zones, combined with the use of Autonomous Mobile Robots, faces challenges related to coordination, resource optimization, and rapid response to customer demand fluctuations. Additionally, implementing lean manufacturing practices in this context must be carefully orchestrated by intelligent systems and human operators to maximize efficiency without sacrificing the agility required in an advanced production environment. This paper proposes and implements a microservices-based architecture integrating principles from Industry 4.0 and 5.0 with lean manufacturing practices. The architecture enhances communication and coordination between autonomous vehicles and kitting management systems, allowing more efficient resource utilization and increased scalability. The proposed architecture focuses on the modularity and flexibility of operations, enabling seamless flexibility to change demands and the efficient allocation of resources in realtime. Conducting this approach is expected to significantly improve logistics operations’ efficiency and scalability by reducing waste and optimizing resource use while improving responsiveness to demand changes. The implementation of this architecture provides a robust foundation for the continuous evolution of kitting management and process optimization. It is designed to adapt to dynamic environments marked by rapid shifts in production demands and real-time decision-making. It also ensures seamless integration with automated systems, aligning with Industry 4.0 and 5.0 needs while reinforcing Lean Manufacturing principles.

Keywords: microservices, event-driven, kitting, AMR, lean manufacturing, industry 4.0, industry 5.0

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Authors: Dar-Bin Shieh, Gwo-Bin Lee, Chen-Ming Chang, Chen Sheng Yeh, Chih-Chia Huang, Tsung-Ju Li

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Mitochondrial defects have a significant impact in many human diseases and aging associated phenotypes. The pathogenic mitochondrial DNA (mtDNA) mutations are diverse and usually present as heteroplasmic. mtDNA 4977bps deletion is one of the common mtDNA defects, and the ratio of mutated versus normal copy is significantly associated with clinical symptoms thus their quantitative detection has become an important unmet needs for advanced disease diagnosis and therapeutic guidelines. This study revealed a Micro-electro-mechanical-system (MEMS) enabled automatic microfluidic chip that only required minimal sample. The system integrated multiple laboratory operation steps into a Lab-on-a-Chip for high-sensitive and prompt measurement. The entire process including magnetic nanoparticle based mtDNA extraction in chip, mutation selective photonic DNA cleavage, and nanoparticle accelerated photonic quantitative polymerase chain reaction (qPCR). All subsystems were packed inside a miniature three-dimensional micro structured system and operated in an automatic manner. Integration of magnetic beads with microfluidic transportation could promptly extract and enrich the specific mtDNA. The near infrared responsive magnetic nanoparticles enabled micro-PCR to be operated by pulse-width-modulation controlled laser pulsing to amplify the desired mtDNA while quantified by fluorescence intensity captured by a complementary metal oxide system array detector. The proportions of pathogenic mtDNA in total DNA were thus obtained. Micro capillary electrophoresis module was used to analyze the amplicone products. In conclusion, this study demonstrated a new magnetophotonic based qPCR MEMS system that successfully detects and quantify specific disease related DNA mutations thus provides a promising future for rapid diagnosis of mitochondria diseases.

Keywords: mitochondrial DNA, micro-electro-mechanical-system, magnetophotonics, PCR

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Authors: Ben Main Piotr Ozieranski

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State government spending on pharmaceuticals stands at 1 trillion USD globally, promoting criticism of the pharmaceutical industry's monetization of drug efficacy, product cost overvaluation, and health injustice. This paper elucidates the mechanisms behind a state-institutional response to this problem through the sociological lens of the strategic relational approach to state power. To do so, 30 expert interviews, legal and policy documents are drawn on to explain how state elites in New Zealand have successfully contested a 30-year “pharmaceutical spending containment policy”. Proceeding from Jessop's notion of strategic “selectivity”, encompassing analyses of the enabling features of state actors' ability to harness state structures, a theoretical explanation is advanced. First, a strategic context is described that consists of dynamics around pharmaceutical dealmaking between the state bureaucracy, pharmaceutical pricing strategies (and their effects), and the industry. Centrally, the pricing strategy of "bundling" -deals for packages of drugs that combine older and newer patented products- reflect how state managers have instigated an “incentivization game” that is played by state and industry actors, including HTA professionals, over pharmaceutical products (both current and in development). Second, a protective context is described that is comprised of successive legislative-judicial responses to the strategic context and characterized by the regulation and the societalisation of commercial law. Third, within the policy, the achievement of increased pharmaceutical coverage (pharmaceutical “mix”) alongside contained spending is conceptualized as a state defence of a "social profit". As such, in contrast to scholarly expectations that political and economic cultures of neo-liberalism drive pharmaceutical policy-making processes, New Zealand's state elites' approach is shown to be antipathetic to neo-liberals within an overall capitalist economy. The paper contributes an analysis of state pricing strategies and how they are embedded in state regulatory structures. Additionally, through an analysis of the interconnections of state power and pharmaceutical value Abrahams's neo-liberal corporate bias model for pharmaceutical policy analysis is problematised.

Keywords: pharmaceutical governance, pharmaceutical bureaucracy, pricing strategies, state power, value theory

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Authors: Nadia Naseem, Farwa Batool, Nasir Mehmood, AbdulHannan Nagi

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Background: The incidence and mortality of breast cancer vary significantly in geographically distinct populations. In Pakistan, breast cancer has shown an increase in incidence in young females and is characterized by more aggressive behavior. The tumor suppressor TP53 gene is a crucial genetic factor that plays a significant role in breast carcinogenesis. This study investigated the TP53 mutations in molecular subtypes of both nodes negative and positive breast cancer in young Pakistani patients. Material and Methods: p53, Estrogen Receptor (ER), Progesterone Receptor (PR), Her-2 neu and Ki 67 expressions were analyzed immunohistochemically in a series of 75 node negative (A) and 75 node positive (B) young (aged: 19-40 years) breast cancer patients diagnosed between 2014 to 2017 at two leading hospitals of Punjab, Pakistan. Tumor tissue specimens and peripheral blood samples were examined for TP53 mutations by direct sequencing of the gene (exons 4-9). The relation of TP53 mutations to these markers and clinicopathological data was investigated. Results: Mean age of the patients was 32.4 + 9.1 SD. Invasive breast carcinoma was the most frequent histological variant (A=92%, B=94.6%). Grade 3 carcinoma was the commonest grade (A=72%, B=81.3%). Triple negative cases (ER-, PR-, Her-2) formed most of the molecular subtypes (A=44%, B=50.6%). A total of 17.2% (A: 6.6%, B: 10.6%) patients showed TP53 mutations. Mutations were significantly more frequent in triple negative cases (A: 74.8%, B: 62.2%) compared to HER2-positive patients (P < 0.0001). In the multivariate analysis of the whole patient group, the independent prognosticator were triple negative cases (P=0.021), TP53 overexpression by IHC (P=0.001) and advanced-stage disease (P=0.007). No statistically significant correlation between TP53 mutations and clinicopathological parameters was found (P < 0.05). Conclusions: It is concluded that TP53 mutations are infrequently present in breast carcinoma of young Pakistani population and there was no significant correlation between p53 mutation and early onset disease. Immunohistochemically detected TP53 expression in our resource-constrained to set up can be beneficial in predicting mutations at the younger age in our population.

Keywords: immunohistochemistry (IHC), invasive breast carcinoma (IBC), Pakistan, TP53

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Authors: Auwal Abubakar, Shazril Imran Shaukat, Noor Khairiah A. Karim, Mohammed Zakir Kassim, Gokula Kumar Appalanaido, Hafiz Mohd Zin

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Background: Voluntary deep inspiration breath-hold radiotherapy (vDIBH-RT) is an effective cardiac dose reduction technique during left breast radiotherapy. This study aimed to assess the accuracy of the implementation of the vDIBH technique among left breast cancer patients without the use of a special device such as a surface-guided imaging system. Methods: The vDIBH-RT technique was implemented among thirteen (13) left breast cancer patients at the Advanced Medical and Dental Institute (AMDI), Universiti Sains Malaysia. Breath-hold monitoring was performed based on breath-hold skin marks and laser light congruence observed on zoomed CCTV images from the control console during each delivery. The initial setup was verified using cone beam computed tomography (CBCT) during breath-hold. Each field was delivered using multiple beam segments to allow a delivery time of 20 seconds, which can be tolerated by patients in breath-hold. The data were analysed using an in-house developed MATLAB algorithm. PTV margin was computed based on van Herk's margin recipe. Results: The setup error analysed from CBCT shows that the population systematic error in lateral (x), longitudinal (y), and vertical (z) axes was 2.28 mm, 3.35 mm, and 3.10 mm, respectively. Based on the CBCT image guidance, the Planning target volume (PTV) margin that would be required for vDIBH-RT using CCTV/Laser monitoring technique is 7.77 mm, 10.85 mm, and 10.93 mm in x, y, and z axes, respectively. Conclusion: It is feasible to safely implement vDIBH-RT among left breast cancer patients without special equipment. The breath-hold monitoring technique is cost-effective, radiation-free, easy to implement, and allows real-time breath-hold monitoring.

Keywords: vDIBH, cone beam computed tomography, radiotherapy, left breast cancer

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Authors: Rafiqul Hasan, A. S. M. Tanim Anwar, Mohammad Azizul Hakim

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Background: Chronic kidney disease (CKD) is a major public health problem that continues to increase in prevalence globally. The prevalence of chronic kidney disease is increasing day by day in low to middle income countries (LMICs). People living in LMICs have the highest need for renal replacement therapy (RRT) despite they have lowest access to various modalities of treatment. As continuous ambulatory peritoneal dialysis (CAPD) does not require advanced technologies, very much infrastructure, dialysis staff support, it should be an ideal form of RRT in LMICs, particularly for those living in remote areas. To authors knowledge there was scarcity of data regarding CAPD performance in remote area of Bangladesh. This study was aimed to report the characteristics and outcomes of CAPD in ESRD patients lived in least developed area of Bangladesh. Methods: This prospective study was conducted in Cox’sbazar Medical College Hospital, Cox’sbazar and Parkview hospital Ltd, Chattogram, Bangladesh. Data were collected by questionnaire from the patients of any age with end-stage renal disease (ESRD) who underwent CAPD in 2018–2021. The baseline characteristics, PD-related complication as well as patient and technique survivals were analyzed. Results: Out of 31 patients who underwent CAPD, 18 (58%) were male on the age range of 15–79 years. The mean follow-up duration was 18 months. Mortality was inversely related with the EF of echocardiography. The peritonitis rate was 0.48 episodes per patient per year. The 1, 3 and 4-year patient survival rates were 64.34% (95% CI = 52.5–81.5), 23.79% (95% CI = 17.9 – 57.4) and 3.22% (95% CI = 31.2–77.5) respectively. Conclusions: In this study, CAPD performance was poorer than usual reference. Cardiac compromised patient and inappropriate dwell might be the main contributing factors behind this scenario. The peritonitis rate was nearly similar to that of developed countries. CAPD was cost effective than HD in remote area. Some accessible measures may be taken to make CAPD a more acceptable RRT modality with improved outcomes in poor socioeconomic backgrounds.

Keywords: dialysis cost, peritoneal dialysis, peritonitis, CAPD, least developed area, remote area, Bangladesh

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Authors: Bhawesh Kumar, A. P. Krishna

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There are continuous changes upon earth’s surface by a variety of natural and anthropogenic agents cut, carry away and depositing of minerals from land. Running water has higher capacity of erosion than other geomorphologic agents. This research work has been carried out on Ganga River, whose channel is continuously changing under the influence of geomorphic agents and human activities in the surrounding regions. The main focus is to study morphological characteristics and sand dynamics of Ganga River with particular emphasis on bank lines and width changes using remote sensing and GIS techniques. The advance remote sensing data and topographical data were interpreted for obtaining 52 years of changes. For this, remote sensing data of different years (LANDSAT TM 1975, 1988, 1993, ETM 2005 and ETM 2012) and toposheet of SOI for the year 1960 were used as base maps for this study. Sinuosity ratio, braiding index and migratory activity index were also established. It was found to be 1.16 in 1975 and in 1988, 1993, 2005 and 2005 it was 1.09, 1.11, 1.1, 1.09 respectively. The analysis also shows that the minimum value found in 1960 was in reach 1 and maximum value is 4.8806 in 2012 found in reach 4 which suggests creation of number of islands in reach 4 for the year 2012. Migratory activity index (MAI), which is a standardized function of both length and time, was computed for the 8 representative reaches. MAI shows that maximum migration was in 1975-1988 in reach 6 and 7 and minimum migration was in 1993-2005. From the channel change analysis, it was found that the shifting of bank line was cyclic and the river Ganges showed a trend of southward maximum values. The advanced remote sensing data and topographical data helped in obtaining 52 years changes in the river due to various natural and manmade activities like flood, water velocity and excavation, removal of vegetation cover and fertile soil excavation for the various purposes of surrounding regions.

Keywords: braided index, migratory activity index (MAI), Ganga river, river morphology

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Authors: Mohammad Mosaddik Rahman

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This study embarks on an exploratory journey to assess the pervasive issue of heavy metal contamination in the water bodies along Chittagong Coast, Bangladesh. Situated along the mesmerizing Bay of Bengal, known for its potential as an emerging tourist haven, economic zone, ship breaking yard, confronts significant environmental hurdles. The core of these challenges lies in the contamination from heavy metals such as lead, cadmium, chromium, and mercury, which detrimentally impact both the ecological integrity and public health of the region. This contamination primarily stems from industrial activities, particularly those involving metallurgical and chemical processes, which release these metals into the environment, leading to their accumulation in soil and water bodies. The study's primary aim is to conduct a thorough assessment of heavy metal pollution levels, alongside an analysis of nutrient variations, focusing on nitrates and nitrites. Methodologically, the study leverages systematic sampling and advanced analytical tools like the Hach 3900 spectrophotometer to ensure precise and reliable data collection. The implications of heavy metal presence are multifaceted, affecting microbial and aquatic life, and posing severe health risks to the local population, including respiratory problems, neurological disorders, and an increased risk of cancer. The results of this study highlight the urgent need for effective mitigation strategies and regulatory measures to address this critical issue. By providing a comprehensive understanding of the environmental and public health implications of heavy metal contamination in Chittagong Coast, this research endeavours to serve as a catalyst for change, emphasising the need for pollution control and advancements in water management policies. It is envisioned that the outcomes of this study will guide stakeholders in collaborating to develop and implement sustainable solutions, ultimately safeguarding the region’s environment and public health.

Keywords: heavy metal, environmental health, pollution control policies, shipbreaking yard

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