Search results for: artificial kidney

Authors: Bahar Tunctan, Sefika Pinar Kucukkavruk, Meryem Temiz-Resitoglu, Demet Sinem Guden, Ayse Nihal Sari, Seyhan Sahan-Firat, Mahesh P. Paudyal, John R. Falck, Kafait U. Malik

Abstract:

We hypothesized that 20-hydroxyeicosatetraenoic acid (20-HETE) mimetics such as N-(20-hydroxyeicosa-5[Z],14[Z]-dienoyl)glycine (5,14-HEDGE) may be beneficial for preventing mortality due to inflammation induced by lipopolysaccharide (LPS). This study aims to assess the effect of 5,14-HEDGE on the LPS-induced changes in nucleotide binding domain and leucine-rich repeat protein 3 (NLRP3)/apoptosis-associated speck-like protein containing a caspase activation and recruitment domain (ASC)/pro-caspase-1 inflammasome. Rats were injected with saline (4 ml/kg) or LPS (10 mg/kg) at time 0. Blood pressure and heart rate were measured using a tail-cuff device. 5,14-HEDGE (30 mg/kg) was administered to rats 1 h after injection of saline or LPS. The rats were sacrificed 4 h after saline or LPS injection and kidney, heart, thoracic aorta, and superior mesenteric artery were isolated for measurement of caspase-1/11 p20, NLRP3, ASC, and β-actin proteins as well as interleukin-1β (IL-1β) levels. Blood pressure decreased by 33 mmHg and heart rate increased by 63 bpm in the LPS-treated rats. In the LPS-treated rats, tissue protein expression of caspase-1/11 p20, NLRP3, and ASC in addition to IL-1β levels were increased. 5,14-HEDGE prevented the LPS-induced changes. Our findings suggest that inhibition of renal, cardiac, and vascular formation/activity of NLRP3/ASC/pro-caspase-1 inflammasome involved in the protective effect of 5,14-HEDGE on LPS-induced septic shock in rats. This work was financially supported by the Mersin University (2015-AP3-1343) and USPHS NIH (PO1 HL034300).

Keywords: 5, 14-HEDGE, lipopolysaccharide, NLRP3, inflammasome, septic shock

Procedia PDF Downloads 289

Authors: Melanie Macgregor-Ramiasa, Isabel Hopp, Patricia Murray, Krasimir Vasilev

Abstract:

Stem cells based therapies are one of the greatest promises of new-age medicine due to their potential to help curing most dreaded conditions such as cancer, diabetes and even auto-immune disease. However, establishing suitable in vitro culture materials allowing to control the fate of stem cells remain a challenge. Amongst the factor influencing stem cell behavior, substrate chemistry and nanotopogaphy are particularly critical. In this work, we used plasma assisted surface modification methods to produce model substrates with tailored nanotopography and controlled chemistry. Three different sizes of gold nanoparticles were bound to amine rich plasma polymer layers to produce homogeneous and gradient surface nanotopographies. The outer chemistry of the substrate was kept constant for all substrates by depositing a thin layer of our patented biocompatible polyoxazoline plasma polymer on top of the nanofeatures. For the first time, protein adsorption and stem cell behaviour (mouse kidney stem cells and mesenchymal stem cells) were evaluated on nanorough plasma deposited polyoxazoline thin films. Compared to other nitrogen rich coatings, polyoxazoline plasma polymer supports the covalent binding of proteins. Moderate surface nanoroughness, in both size and density, triggers cell proliferation. In association with polyoxazoline coating, cell proliferation is further enhanced on nanorough substrates. Results are discussed in term of substrates wetting properties. These findings provide valuable insights on the mechanisms governing the interactions between stem cells and their growth support.

Keywords: nanotopography, stem cells, differentiation, plasma polymer, oxazoline, gold nanoparticles

Procedia PDF Downloads 270

Authors: Mehrdad Nouri Khajavi, Gollamhassan Payganeh, Mohsen Fallah Tafti

Abstract:

Fault diagnosis is an important aspect of maintaining rotating machinery health and increasing productivity. Many researches has been done in this regards. Many faults such as unbalance, misalignment, looseness, bearing faults, etc. have been considered and diagnosed with different techniques. Most of the researches in fault diagnosis of rotating machinery deal with single fault. Where as in reality faults usually occur simultaneously and it is, therefore, necessary to recognize them at the same time. In this research, two of the most common faults namely unbalance and misalignment have been considered simultaneously with different intensity and then identified and classified with the use of Multi-Layer Perception Neural Network (MLPNN). Processed Vibration signals are used as the input to the MLPNN, and the class of mixed unbalancy, and misalignment is the output of the NN.

Keywords: unbalance, parallel misalignment, combined faults, vibration signals

Procedia PDF Downloads 341

Authors: Judit Vilarmau

Abstract:

Generative AI is emerging rapidly and transforming higher education in many ways, occasioning new challenges and disrupting traditional models and methods. The studies and authors explored remark on the impact on the ethics, curriculum, and pedagogical methods. Students are increasingly using generative AI for study, as a virtual tutor, and as a resource for generating works and doing assignments. This point is crucial for educators to make sure that students are using generative AI with ethical considerations. Generative AI also has relevant benefits for educators and can help them personalize learning experiences and promote self-regulation. Educators must seek and explore tools like ChatGPT to innovate without forgetting an ethical and pedagogical perspective. Eighteen studies were systematically reviewed, and the findings provide implementation guidelines with pedagogical and ethical considerations.

Keywords: ethics, generative artificial intelligence, guidelines, higher education, pedagogy

Procedia PDF Downloads 70

Authors: Seham Elia Moussa Shenouda

Abstract:

The relationship between development and human rights has long been the subject of academic debate. To understand the dynamics between these two concepts, various principles are adopted, from the right to development to development-based human rights. Despite the initiatives taken, the relationship between development and human rights remains unclear. However, the overlap between these two views and the idea that efforts should be made in the field of human rights have increased in recent years. It is then evaluated whether the right to sustainable development is acceptable or not. The article concludes that the principles of sustainable development are directly or indirectly recognized in various human rights instruments, which is a good answer to the question posed above. This book therefore cites regional and international human rights agreements such as , as well as the jurisprudence and interpretative guidelines of human rights institutions, to prove this hypothesis.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

Procedia PDF Downloads 17

Authors: Monika Kallubai, Shreya Dubey, Rajagopal Subramanyam

Abstract:

Our study is all about the biological interactions of synthesized 5β-dihydrocortisol (Dhc) and 5β-dihydrocortisol acetate (DhcA) molecules with carrier protein Human Serum Albumin (HSA). The cytotoxic study was performed on breast cancer cell line (MCF-7) normal human embryonic kidney cell line (HEK293), the IC50 values for MCF-7 cells were 28 and 25 µM, respectively, whereas no toxicity in terms of cell viability was observed with HEK293 cell line. The further experiment proved that Dhc and DhcA induced 35.6% and 37.7% early apoptotic cells and 2.5%, 2.9% late apoptotic cells respectively. Morphological observation of cell death through TUNEL assay revealed that Dhc and DhcA induced apoptosis in MCF-7 cells. The complexes of HSA–Dhc and HSA–DhcA were observed as static quenching, and the binding constants (K) was 4.7±0.03×104 M-1 and 3.9±0.05×104 M-1, and their binding free energies were found to be -6.4 and -6.16 kcal/mol, respectively. The displacement studies confirmed that lidocaine 1.4±0.05×104 M-1 replaced Dhc, and phenylbutazone 1.5±0.05×104 M-1 replaced by DhcA, which explains domain I and domain II are the binding sites for Dhc and DhcA. Further, CD results revealed that the secondary structure of HSA was altered in the presence of Dhc and DhcA. Furthermore, the atomic force microscopy and transmission electron microscopy showed that the dimensions like height and molecular sizes of the HSA–Dhc and HSA–DhcA complex were larger compared to HSA alone. Detailed analysis through molecular dynamics simulations also supported the greater stability of HSA–Dhc and HSA–DhcA complexes, and root-mean-square-fluctuation interpreted the binding site of Dhc as domain IB and domain IIA for DhcA. This information is valuable for the further development of steroid derivatives with improved pharmacological significance as novel anti-cancer drugs.

Keywords: apoptosis, dihydrocortisol, fluorescence quenching, protein conformations

Procedia PDF Downloads 124

Authors: Rauza Sukma Rita, Katsuya Dezaki, Yuko Maejima, Toshihiko Yada

Abstract:

Oxytocin is a nine-amino acid peptide synthesized in the paraventricular nucleus (PVN) and supraoptic nucleus (SON) of the hypothalamus. Oxytocin promotes contraction of the uterus during birth and milk ejection during breast feeding. Although oxytocin receptors are found predominantly in the breasts and uterus of females, many tissues and organs express oxytocin receptors, including the pituitary, heart, kidney, thymus, vascular endothelium, adipocytes, osteoblasts, adrenal gland, pancreatic islets, and many cell lines. On the other hand, in pancreatic islets, oxytocin receptors are expressed in both α-cells and β-cells with stronger expression in α- cells. However, to our knowledge there are no reports yet about the effect of oxytocin on cytosolic calcium reaction on α and β-cell. This study aims to investigate the effect of oxytocin on α-cells and β-cells and its oscillation pattern. Islet of Langerhans from wild type mice were isolated by collagenase digestion. Isolated and dissociated single cells either α-cells or β-cells on coverslips were mounted in an open chamber and superfused in HKRB. Cytosolic concentration ([Ca2+]i) in single cells were measured by fura-2 microfluorimetry. After measurement of [Ca2+]i, α-cells were identified by subsequent immunocytochemical staining using an anti-glucagon antiserum. In β-cells, the [Ca2+]i increase in response to oxytocin was observed only under 8.3 mM glucose condition, whereas in α-cells, [Ca2+]i an increase induced by oxytocin was observed in both 2.8 mM and 8.3 mM glucose. The oscillation incidence was induced more frequently in β-cells compared to α-cells. In conclusion, the present study demonstrated that oxytocin directly interacts with both α-cells and β-cells and induces increase of [Ca2+]i and its specific patterns.

Keywords: α-cells, β-cells, cytosolic calcium concentration, oscillation, oxytocin

Procedia PDF Downloads 177

Authors: S. Tokuomi, K. Mori, Y. Tsuruzono

Abstract:

A concrete-wall-climbing testing robot, has been developed. This robot adheres and climbs concrete walls using two sets of suction cups, as well as being able to rotate by the use of the alternating motion of the suction cups. The maximum climbing speed is about 60 cm/min. Each suction cup has a pressure sensor, which monitors the adhesion of each suction cup. The impact acoustic method is used in testing concrete walls. This robot has an impact acoustic device and four microphones for the acquisition of the impact sound. The effectiveness of the impact acoustic system was tested by applying it to an inspection of specimens with artificial circular void defects. A circular void defect with a diameter of 200 mm at a depth of 50 mm was able to be detected. The weight and the dimensions of the robot are about 17 kg and 1.0 m by 1.3 m, respectively. The upper limit of testing is about 10 m above the ground due to the length of the power cable.

Keywords: concrete wall, nondestructive testing, climbing robot, impact acoustic method

Procedia PDF Downloads 649

Authors: Ahmed Hossam El Molla, Mohamed Hatem Saleh, Hamza Mostafa, Lara Mamdouh, Yassin Wael

Abstract:

Artificial intelligence (AI) is reshaping industries, and its potential to revolutionize renewable energy and data center operations is immense. By harnessing AI's capabilities, we can optimize energy consumption, predict fluctuations in renewable energy generation, and improve the efficiency of data center infrastructure. This convergence of technologies promises a future where energy is managed more intelligently, sustainably, and cost-effectively. The integration of AI into renewable energy systems unlocks a wealth of opportunities. Ma-chine learning algorithms can analyze vast amounts of data to forecast weather patterns, solar irradiance, and wind speeds, enabling more accurate energy production planning. AI-powered systems can optimize energy storage and grid management, ensuring a stable power supply even during intermittent renewable genera-tion. Moreover, AI can identify maintenance needs for renewable energy infrastructure, preventing costly breakdowns and maximizing system lifespan. Data centers, which consume substantial amounts of energy, are prime candidates for AI-driven optimization. AI can analyze energy consumption patterns, identify inefficien-cies, and recommend adjustments to cooling systems, server utilization, and power distribution. Predictive maintenance using AI can prevent equipment failures, reducing energy waste and downtime. Additionally, AI can optimize data placement and retrieval, minimizing energy consumption associated with data transfer. As AI transforms renewable energy and data center operations, new Key Performance Indicators (KPIs) will emerge. Traditional metrics like energy efficiency and cost-per-megawatt-hour will continue to be relevant, but additional KPIs focused on AI's impact will be essential. These might include AI-driven cost savings, predic-tive accuracy of energy generation and consumption, and the reduction of carbon emissions attributed to AI-optimized operations. By tracking these KPIs, organizations can measure the success of their AI initiatives and identify areas for improvement. Ultimately, the synergy between AI, renewable energy, and data centers holds the potential to create a more sustainable and resilient future. By embracing these technologies, we can build smarter, greener, and more efficient systems that benefit both the environment and the economy.

Keywords: data center, artificial intelligence (AI), renewable energy, energy efficiency, sustainability, optimization, predictive analytics, energy consumption, energy storage, grid management, data center optimization, key performance indicators (KPIs), carbon emissions, resiliency

Procedia PDF Downloads 4

Authors: Meriem Mossaddek, El Mehdi Laadissi, El Mehdi Loualid, Chouaib Ennawaoui, Sohaib Bouzaid, Abdelowahed Hajjaji

Abstract:

An electrochemical system is a subset of mechatronic systems that includes a wide variety of batteries and nickel-cadmium, lead-acid batteries, and lithium-ion. Those structures have several non-linear behaviors and uncertainties in their running range. This paper studies an effective technique for modeling Lithium-Ion (Li-Ion) batteries using a Nonlinear Auto-Regressive model with exogenous input (NARX). The Artificial Neural Network (ANN) is trained to employ the data collected from the battery testing process. The proposed model is implemented on a Li-Ion battery cell. Simulation of this model in MATLAB shows good accuracy of the proposed model.

Keywords: lithium-ion battery, neural network, energy storage, battery model, nonlinear models

Procedia PDF Downloads 95

Authors: Fenni Sim

Abstract:

Background: The application of systemic family therapy approaches to community health cases have not gathered traction. In National Kidney Foundation, Singapore, the belief is that community support has great potential in helping End Stage Renal Failure (ESRF) patients manage the demands of their treatment regime, whether Hemodialysis (HD) or Peritoneal Dialysis(PD) and sustain them on the treatment. However, the current community support does not include family interventions and is largely nursing based. Although nursing support is well provided to patients, and their family members in issues related to treatment and compliance, complex family issues and dynamics arising from caregiver strain or pre-dialysis relationship strain might deter efforts in managing the challenges of the treatment. Objective: The objective of the study is to understand the potential scope of work provided by a social worker who is trained in systemic family therapy and the effects of these interventions. Methodology: 3 families on HD and 3 families on PD who have been receiving family intervention for the past 6 months would be chosen for the study. A qualitative interview would be conducted to review the effectiveness for the family. Scales such as SCORE-15, PHQ-9, and Zarit Burden were used to measure family functioning, depression, and caregiver’s burden for the families. Results: The research is still in preliminary phase. Conclusion: The study highlights the importance of family intervention for families with multiple stressors on different treatment modalities who might have different needs and challenges. Nursing support needs to be complemented with family-based support to manage complex family issues in order to achieve better health outcomes and improved family coping.

Keywords: complementing nursing support, end stage renal failure, healthcare, systemic approaches

Procedia PDF Downloads 192

Authors: Michał Rogala, Jakub Gajewski

Abstract:

As the automotive industry develops, passive safety is becoming an increasingly important aspect when designing motor vehicles. A commonly used solution is energy absorption by thin-walled construction. One such structure is a closed thin-walled profile fixed to the vehicle stringers. The article presents numerical tests of conical thin-walled profiles filled with aluminum foam. The columns were loaded axially with constant energy. On the basis of the results obtained, efficiency indicators were calculated. The efficiency of the foam filling was evaluated. Artificial neural networks were used for data analysis. The application of regression analysis was used as a tool to study the relationship between the quantities characteristic of the dynamic crush.

Keywords: aluminium foam, crashworthiness, neural networks, thin-walled structure

Procedia PDF Downloads 133

Authors: K. E. Ch. Vidyasagar, M. Moghavvemi, T. S. S. T. Prabhat

Abstract:

Epilepsy is a global problem, and with seizures eluding even the smartest of diagnoses a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Among a multitude of methods for automatic epilepsy detection, one should find the best method out, based on accuracy, for classification. This paper reasons out, and rationalizes, the best methods for classification. Accuracy is based on the classifier, and thus this paper discusses classifiers like quadratic discriminant analysis (QDA), classification and regression tree (CART), support vector machine (SVM), naive Bayes classifier (NBC), linear discriminant analysis (LDA), K-nearest neighbor (KNN) and artificial neural networks (ANN). Results show that ANN is the most accurate of all the above stated classifiers with 97.7% accuracy, 97.25% specificity and 98.28% sensitivity in its merit. This is followed closely by SVM with 1% variation in result. These results would certainly help researchers choose the best classifier for detection of epilepsy.

Keywords: classification, seizure, KNN, SVM, LDA, ANN, epilepsy

Procedia PDF Downloads 503

Authors: Pierre Tize Mha, Mohammad Jahazi, Amèvi Togne, Olivier Pantalé

Abstract:

Large-size forged blocks made of medium carbon high-strength steels are extensively used in the automotive industry as dies for the production of bumpers and dashboards through the plastic injection process. The manufacturing process of the large blocks starts with ingot casting, followed by open die forging and a quench and temper heat treatment process to achieve the desired mechanical properties and numerical simulation is widely used nowadays to predict these properties before the experiment. But the temperature gradient inside the specimen remains challenging in the sense that the temperature before loading inside the material is not the same, but during the simulation, constant temperature is used to simulate the experiment because it is assumed that temperature is homogenized after some holding time. Therefore to be close to the experiment, real distribution of the temperature through the specimen is needed before the mechanical loading. Thus, We present here a robust algorithm that allows the calculation of the temperature gradient within the specimen, thus representing a real temperature distribution within the specimen before deformation. Indeed, most numerical simulations consider a uniform temperature gradient which is not really the case because the surface and core temperatures of the specimen are not identical. Another feature that influences the mechanical properties of the specimen is recrystallization which strongly depends on the deformation conditions and the type of deformation like Upsetting, Cogging...etc. Indeed, Upsetting and Cogging are the stages where the greatest deformations are observed, and a lot of microstructural phenomena can be observed, like recrystallization, which requires in-depth characterization. Complete dynamic recrystallization plays an important role in the final grain size during the process and therefore helps to increase the mechanical properties of the final product. Thus, the identification of the conditions for the initiation of dynamic recrystallization is still relevant. Also, the temperature distribution within the sample and strain rate influence the recrystallization initiation. So the development of a technique allowing to predict the initiation of this recrystallization remains challenging. In this perspective, we propose here, in addition to the algorithm allowing to get the temperature distribution before the loading stage, an analytical model leading to determine the initiation of this recrystallization. These two techniques are implemented into the Abaqus finite element software via the UAMP and VUHARD subroutines for comparison with a simulation where an isothermal temperature is imposed. The Artificial Neural Network (ANN) model to describe the plastic behavior of the material is also implemented via the VUHARD subroutine. From the simulation, the temperature distribution inside the material and recrystallization initiation is properly predicted and compared to the literature models.

Keywords: dynamic recrystallization, finite element modeling, artificial neural network, numerical implementation

Procedia PDF Downloads 74

Authors: Sulyman Abdulhakeem Olarewaju, S. O. Malomo, M. T. Yakubu, J. O. Akolade

Abstract:

The ameliorative effect of Celosia argentea var. cristata leaf extract against cadmium (Cd) induced oxidative stress and toxicity in selected tissues of rats was investigated. Toxicity coupled with oxidative stress was induced in rats by oral administration of Cd (8 mg/kg b. wt). Preliminary quantitative phytochemical and in vitro antioxidant analyses showed that the methanolic extract of C. argentea leaves was constituted by polyphenols (5.72%), saponins (3.20%), tannins (0.65%) and cadenolides (0.006%). IC50 of 9800, 7406, and 45.04 μg/ml were recorded for inhibition of linoleic acid oxidation, 2, 2-diphenyl-1-picrylhydrazyl and hydrogen peroxide radicals respectively. Simultaneous administration of C. argentea leaf extract with Cd significantly attenuated Cd-induced elevation of serum enzyme markers such as aspartate and alanine transaminase, alkaline and acid phosphatase as well as γ-glutaryltransferase in a dose-dependent fashion, while their reduced level in the liver were significantly increased. Higher levels of enzymatic antioxidants; superoxide dismutase and catalase activities were observed in the liver, brain, kidney and testes of the Cd-induced rats treated with C. argentea extract, while lipid peroxidation expressed in malondialdehyde concentrations were lower when compared to values in rats administered Cd only. Other Cd-induced toxicity and stress markers in the serum viz. reduced uric acid and albumin levels as well as elevated total and unconjugated bilirubin were attenuated by the extract and their values compared favorably with those animals co-administered cadmium with ascorbic acid. Data from the study showed that oral administration of extract from the leaf C. argentea may ameliorate Cd-induced oxidative stress and toxicity in rats.

Keywords: toxicity, cadmium, celosia, antioxidants, oxidative stress

Procedia PDF Downloads 330

Authors: Bola George Asaad Bekledas

Abstract:

Relationship between development and human rights has long been the subject of academic debate. To understand the dynamics between these two concepts, various principles are adopted, from the right to development to development-based human rights. Despite the initiatives taken, the relationship between development and human rights remains unclear. However, the compatibility between these two concepts and the idea that these efforts should be made to respect human rights guarantees have gained momentum in recent years. It is then evaluated whether the right to sustainable development is acceptable or not. The article concludes that the principles of sustainable development are directly or indirectly recognized in various human rights instruments, which is a good answer to the question posed above. This study, therefore, cites regional and international human rights agreements such as, as well as the jurisprudence and interpretative guidelines of human rights institutions, to prove this hypothesis.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security.

Procedia PDF Downloads 34

Authors: Cedric Leong, Parth Desai, Parth Patel

Abstract:

The purpose of this project was to develop a neural network based on qualitative team data to predict alliance scores to determine winners of matches in the FIRST Robotics Competition (FRC). The game for the competition changes every year with different objectives and game objects, however the idea was to create a prediction system which can be reused year by year using some of the statistics that are constant through different games, making our system adaptable to future games as well. Aerial Assist is the FRC game for 2014, and is played in alliances of 3 teams going against one another, namely the Red and Blue alliances. This application takes any 6 teams paired into 2 alliances of 3 teams and generates the prediction for the final score between them.

Keywords: artifical neural network, prediction system, qualitative team data, FIRST Robotics Competition (FRC)

Procedia PDF Downloads 496

Authors: Precious Ehiomogue, Ifechukwude Israel Ahuchaogu, Isiguzo Edwin Ahaneku

Abstract:

Vermicompost is the product of the decomposition process using various species of worms, to create a mixture of decomposing vegetable or food waste, bedding materials, and vemicast. This process is called vermicomposting, while the rearing of worms for this purpose is called vermiculture. Several works have verified the adsorption of toxic metals using vermicompost but the application is still scarce for the retention of organic compounds. This research brings to knowledge the effectiveness of earthworm waste (vermicompost) for the remediation of crude oil contaminated soils. The remediation methods adopted in this study were two soil washing methods namely, batch and column process which represent laboratory and in-situ remediation. Characterization of the vermicompost and crude oil contaminated soil were performed before and after the soil washing using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), X-ray fluorescence (XRF), X-ray diffraction (XRD) and Atomic adsorption spectrometry (AAS). The optimization of washing parameters, using response surface methodology (RSM) based on Box-Behnken Design was performed on the response from the laboratory experimental results. This study also investigated the application of machine learning models [Artificial neural network (ANN), Adaptive neuro fuzzy inference system (ANFIS). ANN and ANFIS were evaluated using the coefficient of determination (R²) and mean square error (MSE)]. Removal efficiency obtained from the Box-Behnken design experiment ranged from 29% to 98.9% for batch process remediation. Optimization of the experimental factors carried out using numerical optimization techniques by applying desirability function method of the response surface methodology (RSM) produce the highest removal efficiency of 98.9% at absorbent dosage of 34.53 grams, adsorbate concentration of 69.11 (g/ml), contact time of 25.96 (min), and pH value of 7.71, respectively. Removal efficiency obtained from the multilevel general factorial design experiment ranged from 56% to 92% for column process remediation. The coefficient of determination (R²) for ANN was (0.9974) and (0.9852) for batch and column process, respectively, showing the agreement between experimental and predicted results. For batch and column precess, respectively, the coefficient of determination (R²) for RSM was (0.9712) and (0.9614), which also demonstrates agreement between experimental and projected findings. For the batch and column processes, the ANFIS coefficient of determination was (0.7115) and (0.9978), respectively. It can be concluded that machine learning models can predict the removal of crude oil from polluted soil using vermicompost. Therefore, it is recommended to use machines learning models to predict the removal of crude oil from contaminated soil using vermicompost.

Keywords: ANFIS, ANN, crude-oil, contaminated soil, remediation and vermicompost

Procedia PDF Downloads 98

Authors: Noof Eid Al Shammari

Abstract:

Background: Living with haemodialysis (HD) can impose several physical and social restrictions on the lives of individuals. Usually, the patient has three dialysis sessions per week that each run for three to four hours. This limits the social life of patients and causes a lower quality of life, in conjunction with the fact that people with chronic kidney disease must follow strict fluid and food regimens and use multiple medications. Given these factors, patients undergoing HD generally need psychological support. Objective: This scoping review study aims to evaluate the effectiveness of physical and breathing exercises on quality of life (QOL) and psychophysical status in patients undergoing HD. Methodology: Searches for relevant studies were performed in four databases (MEDLINE, CINAHL, Google Scholar, and PubMed) for articles published between 2011 and 2021. Out of all the searched literature, ten studies met the inclusion criteria (8 randomised controlled trials, one quasi-experimental study, and one pilot study), with a total of 588 patients. Different types of physical and breathing exercises were used (breathing, cardiopulmonary, and physical exercises). Results: All included studies in this scoping review revealed that most of the aerobic or anaerobic exercises, as well as breathing exercises, had a positive effect and significantly improved patients’ QOL, physical functioning, and psychological status. Conclusions: In this review, most of the articles demonstrated a positive effect of physical and breathing exercises on the QOL and psychophysical status of HD patients. Based on the findings of these studies, physical and breathing exercises were shown to improve muscle strength and other health-related aspects of QOL, including sexual, social, cognitive, and physical functions. However, more studies will need to be conducted with a larger sample to determine the best intervention that could be implemented and standardised in nursing care for patients undergoing HD.

Keywords: physical exercise, breathing exercises, quality of life, depression, hemodialysis

Procedia PDF Downloads 100

Authors: Chivon Choeung, Heng Tang, Panha Soth, Vichet Huy

Abstract:

This paper presents a robust control strategy for a single-phase DC-AC inverter with an output LC-filter. An all-pass filter is utilized to create an artificial β-signal so that the proposed controller can be simply used in dq-synchronous frame. The proposed robust controller utilizes a state feedback control with integral action in the dq-synchronous frame. A linear matrix inequality-based optimization scheme is used to determine stabilizing gains of the controllers to maximize the convergence rate to steady state in the presence of uncertainties. The uncertainties of the system are described as the potential variation range of the inductance and resistance in the LC-filter.

Keywords: single-phase inverter, linear matrix inequality, robust control, all-pass filter

Procedia PDF Downloads 127

Authors: S. S. Salehi, A. Shamloo

Abstract:

Poor ability of cartilage tissue when experiencing a damage leads scientists to use tissue engineering as a reliable and effective method for regenerating or replacing damaged tissues. An artificial tissue should have some features such as biocompatibility, biodegradation and, enough mechanical properties like the original tissue. In this work, a composite hydrogel is prepared by using natural and synthetic materials that has high porosity. Mechanical properties of different combinations of polymers such as modulus of elasticity were tested, and a hydrogel with good mechanical properties was selected. Bone marrow derived mesenchymal stem cells were also seeded into the pores of the sponge, and the results showed the adhesion and proliferation of cells within the hydrogel after one month. In comparison with previous works, this study offers a new and efficient procedure for the fabrication of cartilage like tissue and further cartilage repair.

Keywords: cartilage tissue engineering, hydrogel, mechanical strength, mesenchymal stem cell

Procedia PDF Downloads 286

Authors: Ji Eun Shin, Dong Hoon Lim

Abstract:

Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

Procedia PDF Downloads 419

Authors: A. Kabiri-Samani, M. J. Seddighi

Abstract:

There is no doubt that a key factor in the manifestation of architecture is the interaction of human and nature. Explaining the type of relationship defined by “the architect” between architecture and nature opens a window towards understanding the theoretical conceptions of the architect as the creator of “architecture”. Now, if these theoretical foundations are put under scrutiny from the viewpoint of Islam, and an architect considers the relationship of human and nature within the context of Islam, he would let nature to manifest itself in architecture. The reasons for such a relationship is explicable in terms of the degree and nature of knowledge of the architect about nature; while the way it comes to existence is explained by defining the force of nature – ruling the entire nature – and its acts. It is by the scientific command of the architect and his mastery in the hermetic force of nature that the material bodies of buildings evolve from artificial to natural. Additionally, the presence of nature creates hermetic architectural spaces for the spiritual development of humans while serving for living at different levels.

Keywords: nature, Islam, cognition, science, presence, elixir

Procedia PDF Downloads 473

Authors: Felib Ayman Shawky Salem

Abstract:

Experiential marketing means an unforgettable experience that remains deeply anchored in the customer's memory. Furthermore, customer satisfaction is defined as the emotional response to the experiences provided that relate to specific products or services purchased. Therefore, experiential marketing activities can influence the level of customer satisfaction and loyalty. In this context, the study aims to examine the relationship between experiential marketing, customer satisfaction and loyalty of beauty products in Konya. The results of this study showed that experiential marketing is an important indicator of customer satisfaction and loyalty and that experiential marketing has a significant positive impact on customer satisfaction and loyalty.

Keywords: sponsorship, marketing communication theories, marketing communication tools internet, marketing, tourism, tourism management corporate responsibility, employee organizational performance, internal marketing, internal customer experiential marketing, customer satisfaction, customer loyalty, social sciences.

Procedia PDF Downloads 55

Authors: Ioannis P. Panapakidis, Marios N. Moschakis

Abstract:

The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

Keywords: deregulated energy market, forecasting, machine learning, system marginal price

Procedia PDF Downloads 202

Authors: L. Parisi

Abstract:

Kinematic data wisely correlate vector quantities in space to scalar parameters in time to assess the degree of symmetry between the intact limb and the amputated limb with respect to a normal model derived from the gait of control group participants. Furthermore, these particular data allow a doctor to preliminarily evaluate the usefulness of a certain rehabilitation therapy. Kinetic curves allow the analysis of ground reaction forces (GRFs) to assess the appropriateness of human motion. Electromyography (EMG) allows the analysis of the fundamental lower limb force contributions to quantify the level of gait asymmetry. However, the use of this technological tool is expensive and requires patient’s hospitalization. This research work suggests overcoming the above limitations by applying artificial neural networks.

Keywords: kinetics, kinematics, cyclograms, neural networks, transtibial amputation

Procedia PDF Downloads 432

Authors: Dariush Jafari, Seyed Ali Jafari

Abstract:

The recommended limit for cadmium concentration in potable water is less than 0.005 mg/L. A continuous biosorption process using indigenous red seaweed, Gracilaria corticata, was performed to remove cadmium from the potable water. The process was conducted under fixed conditions and the breakthrough curves were achieved for three consecutive sorption-desorption cycles. A modeling based on Artificial Neural Network (ANN) was employed to fit the experimental breakthrough data. In addition, a simplified semi empirical model, Thomas, was employed for this purpose. It was found that ANN well described the experimental data (R2>0.99) while the Thomas prediction were a bit less successful with R2>0.97. The adjusted design parameters using the nonlinear form of Thomas model was in a good agreement with the experimentally obtained ones. The results approve the capability of ANN to predict the cadmium concentration in potable water.

Keywords: ANN, biosorption, cadmium, packed-bed, potable water

Procedia PDF Downloads 417

Authors: Bajraktarevic Adnan, Djukic Branka, Sporisevic Lutvo, Krdzalic Zecevic Belma, Uzicanin Sajra, Hadzimuratovic Admir, Hadzimuratovic Hadzipasic Emina, Abduzaimovic Alisa, Kustric Amer, Suljevic Ismet, Serafi Ismail, Tahmiscija Indira, Khatib Hakam, Semic Jusufagic Aida, Haas Helmut, Vladicic Aleksandra, Aplenc Richard, Kadic Deovic Aida

Abstract:

Introduction: Joubert syndrome has an autosomal recessive pattern of inheritance. It is referred as the brain malfunctioning and caused due to the underdevelopment of the cerebellar vermis. Associated conditions involving the eye, the kidney, and ocular disease are well described. Aims: Research helps us better understand this diseases, Joubert syndrome and can lead to advances in diagnosis and treatment. Methods: Different several conditions have been described in which the molar tooth sign and characteristics of Joubert syndrome in ten different places in the world. Carrier testing and diagnosis are available if one of these gene mutations has been identified in an affected family member. Results: Authors have described eleven cases during twenty years of Joubert syndrome. It is a clinically and genetically heterogeneous group of disorders characterized by hypoplasia of the cerebellar vermis with the characteristic neuroradiologic molar tooth sign, and accompanying neurologic symptoms, including dysregulation of breathing pattern and developmental delay. We made confirmation of diagnosis in twin sisters with Joubert syndrome with renal anomalies. Ocular symptoms have existed in seven cases (63.64%) from total eleven. Eleven cases were different sex, five boys (45.45%) and six girls (54.44%). Conclusions: Joubert syndrome is inherited as an autosomal recessive genetic disorder with several features of the disease.

Keywords: Joubert syndrome, cerebellooculorenal syndrome, autosomal recessive genetic disorder (ARGD), children

Procedia PDF Downloads 272

Authors: L. Mouzai, M. Bouhadef

Abstract:

Rills begin to be generated once overland flow shear capacity overcomes the soil surface resistance. This resistance depends on soil texture, the arrangement of soil particles and on chemical and physical properties. The rill density could affect soil erosion, especially when the distance between the rills (interrill) contributes to the variation of the rill characteristics, and consequently on sediment concentration. To investigate this point, agricultural sandy soil, a soil tray of 0.2x1x3m³ and a piece of hardwood rectangular in shape to build up rills were the base of this work. The results have shown that small lines have been developed between the rills and the flow acceleration increased in comparison to the flow on the flat surface (interrill). Sediment concentration increased with increasing rill number (density).

Keywords: artificial rainfall, experiments, rills, soil erosion, transport capacity

Procedia PDF Downloads 149

Authors: Bouchra Nadji, Elaid Bouchetob

Abstract:

PV systems are common in residential and industrial settings because of their low, upfront costs and operating costs throughout their lifetimes. Buck or boost converters are used in photovoltaic systems, regardless of whether the system is autonomous or connected to the grid. These converters became less appealing because of their low efficiency, inadequate power density, and use of silicon for their power components. Traditional devices based on Si are getting close to reaching their theoretical performance limits, which makes it more challenging to improve the performance and efficiency of these devices. GaN and SiC are the two types of WBG semiconductors with the most recent technological advancements and are available. Tolerance to high temperatures and switching frequencies can reduce active and passive component size. Utilizing high-efficiency dc-dc boost converters is the primary emphasis of this work. These converters are for photovoltaic systems that use wave energy.

Keywords: component, Artificial intelligence, PV System, ANN MPPT, DC-DC converter

Procedia PDF Downloads 48