Search results for: artificial kidney

Authors: Yuji Kageyama, Shin Nagata, Tatsuya Takino, Izuru Nomura, Hiroyuki Kamata

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In previous study, technique to estimate a self-location by using a lunar image is proposed. We consider the improvement of the conventional method in consideration of FPGA implementation in this paper. Specifically, we introduce Artificial Bee Colony algorithm for reduction of search time. In addition, we use fixed point arithmetic to enable high-speed operation on FPGA.

Keywords: SLIM, Artificial Bee Colony Algorithm, location estimate, evolutional triangle similarity

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Authors: Nabila Daly, Hamdi Ellouzi, Hela Ltifi

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In last year’s, several recent researches’ that focus on e-learning approaches having as goal to improve pedagogy and student’s academy level assessment. E-learning-related works have become an important research file nowadays due to several problems that make it impossible for students join classrooms, especially in last year’s. Among those problems, we note the current epidemic problems in the word case of Covid-19. For those reasons, several e-learning-related works based on Artificial Intelligence techniques are proposed to improve distant education targets. In the current paper, we will present a short survey of the most relevant e-learning based on Artificial Intelligence techniques giving birth to newly developed e-learning tools that rely on new technologies.

Keywords: artificial intelligence techniques, decision, e-learning, support system, survey

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Authors: Hitoshi Minakuchi, Izumi Takei, Shu Wakino, Koichi Hayashi, Hiroshi Itoh

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Objectives: Among type 2 diabetics, patients with CKD(chronic kidney disease), insulin resistance, impaired glyconeogenesis in kidney and reduced degradation of insulin are recognized, and we observed different fluctuational patterns of blood sugar between CKD patients and non-CKD patients. On the other hand, non-dipper type blood pressure change is the risk of organ damage and mortality. We performed cross-sectional study to elucidate the characteristic of the fluctuation of blood glucose and blood pressure at insulin-treated diabetic patients with chronic kidney disease. Methods: From March 2011 to April 2013, at the Ichikawa General Hospital of Tokyo Dental College, we recruited 20 outpatients. All participants are insulin-treated type 2 diabetes with CKD. We collected serum samples, urine samples for several hormone measurements, and performed CGMS(Continuous glucose measurement system), ABPM (ambulatory blood pressure monitoring), brain computed tomography, carotid artery thickness, ankle brachial index, PWV, CVR-R, and analyzed these data statistically. Results: Among all 20 participants, hypoglycemia was decided blood glucose 70mg/dl by CGMS of 9 participants (45.0%). The event of hypoglycemia was recognized lower eGFR (29.8±6.2ml/min：41.3±8.5ml/min, P<0.05), lower HbA1c (6.44±0.57%：7.53±0.49%), higher PWV (1858±97.3cm/s：1665±109.2cm/s), higher serum glucagon (194.2±34.8pg/ml：117.0±37.1pg/ml), higher free cortisol of urine (53.8±12.8μg/day：34.8±7.1μg/day), and higher metanephrin of urine (0.162±0.031mg/day：0.076±0.029mg/day). Non-dipper type blood pressure change in ABPM was detected 8 among 9 participants with hypoglycemia (88.9%), 4 among 11 participants (36.4%) without hypoglycemia. Multiplex logistic-regression analysis revealed that the event of hypoglycemia is the independent factor of non-dipper type blood pressure change. Conclusions: Among insulin-treated type 2 diabetic patients with CKD, the events of hypoglycemia were frequently detected, and can associate with the organ derangements through the medium of non-dipper type blood pressure change.

Keywords: chronic kidney disease, hypoglycemia, non-dipper type blood pressure change, diabetic patients

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Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

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Authors: Hakan Duger, Alparslan Ersoy, Canan Ersoy

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Diabetes mellitus is the most common etiology of end-stage renal disease (ESRD). Also, diabetic nephropathy is the etiology of ESRD in approximately 23% of kidney transplant recipients. A successful kidney transplant improves the quality of life and reduces the mortality risk for most patients. However, patients require close follow-up after transplantation due to medical complications. Diabetes mellitus can affect patient morbidity and mortality due to possible effects of immunosuppressive therapy on glucose metabolism. We compared the frequency of medical complications and the outcomes in diabetic and non-diabetic kidney transplant recipients. Materials and Methods: This retrospective study conducted in 498 patients who underwent kidney transplant surgery at our center in 10-year periods. The patients were divided into two groups: diabetics (46 ± 10 year, 26 males, 16 females) and non-diabetics (39 ± 12 year, 259 males, 197 females). The medical complications, graft functions, causes of graft loss and death were obtained from medical records. Results: There was no significant difference between recipient age, duration of dialysis, body mass index, gender, donor type, donor age, dialysis type, histories of HBV, HCV and coronary artery disease between two groups. The history of hypertension in diabetics was higher (69% vs. 36%, p < 0.001). The ratios of hypertension (50.1% vs. 57.1%), pneumonia (21.9% vs. 20%), urinary infection (16.9% vs. 20%), transaminase elevation (11.5% vs. 20%), hyperpotasemia (14.7% vs. 17.1%), hyponatremia (9.7% vs. 20%), hypotension (7.1% vs. 7.9%), hypocalcemia (1.4% vs. 0%), thrombocytopenia (8.6% vs. 8.6%), hypoglycemia (0.7% vs. 0%) and neutropenia (1.8% vs. 0%) were comparable in non-diabetic and diabetic groups, respectively. The frequency of hyperglycaemia in diabetics was higher (8.6% vs. 54.3%, p < 0.001). After transplantation, primary non-function (3.4% vs. 2.6%), delayed graft function (25.1% vs. 34.2%) and acute rejection (7.3% vs. 10.5%) ratios of in non-diabetic and diabetic groups were similar, respectively. Hospitalization durations in non-diabetics and diabetics were 22.5 ± 17.5 and 18.7 ± 13 day (p=0.094). Mean serum creatinine levels in non-diabetics and diabetics were 1.54 ± 0.74 and 1.52 ± 0.62 mg/dL at 6th month. Forty patients had graft loss. The ratios of graft loss and death in non-diabetic and diabetic groups were 8.2% vs. 7.1% and 7.1% vs. 2.6% (p > 0.05). There was no significant relationship between graft and patient survivals with the development of medical complication. Conclusion: As a result, medical complications are common in the early period. Hyperglycaemia was frequently seen following transplantation due to the effects of immunosuppressant regimens. However, the frequency of other medical complications in diabetic patients did not differ from non-diabetic one. The most important cause of death is still infections. The development of medical complications during the first 6 months did not significantly affect transplant outcomes.

Keywords: kidney transplantation, diabetes mellitus, complication, graft function

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Authors: Amal Yamani, Jaber Elgtou, Aziz Mohammed, Lazaar Jamila, Elachouri Mostafa

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Peganum harmala used traditionally as an emenagogue and abortifacient agent in Morocco phytotherapy. Even thought its benefits effects, Peganum harmala remained severely toxic for the organism especially in strong doses. The present study was initiated to evaluate the nephrotoxic effects of aqueous extract of Peganum harmala seeds (PHS). The solution containing aqueous extract of PHS was administered orally by gavage at the dose of 2g/kg body weight during twenty days. Rats were used in this study, two groups were considered, a treated group received an extract of PHS at dose 2g/kg bodyweight and control group received an amount of tap water equivalent to the volume of the vehicle used for the dose of PHS extract. The data we collected showed that aqueous extracts of PHS administered during twenty days induced a significant changes in renal function expressed in decreases of diuresis (from 10 ± 0,58 to 5,33 ± 0,33 ml/24 hours) and the same profile for mean arterial blood pressure (from 125 ± 2,89 to 96,67 ± 6,01 mmHg). The histopathological study showed an alteration of kidney cells in treated group with regard the control group which is not affected. In conclusion: our results indicate that the aqueous extract of PHS induces toxicity may affect severely kidney function and causes renal histopathology.

Keywords: peganum harmala seeds, nephrotoxic, diuresi, histpathology, kidney

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Authors: M. Naidoo

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The concept of moral personhood extending from the moral status of an artificial intelligence system has been explored – but predominantly from a Western conception of personhood. African personhood, however, is distinctly different from Western personhood in that communitarianism is central to the underpinnings of personhood - rather than Western individualism. Personhood in the African context is not an inherent property that a human is born with; rather, it is an ontological journey that one goes on in his or her life with the hopes of attaining personhood. Given the decolonization, projects happening in Africa, and the law-making that is happening in this space within South Africa, it is of paramount importance to consider these views.

Keywords: artificial intelligence, bioethics, law, legal personality

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Authors: Mahmoudi Marwa, Bahim Nadhem, Aydi Abdelwaheb, Issaoui Wissal, S. Najet

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This work represents a coupling between the geographic information system (GIS) and the multicriteria analysis aiming at the selection of an artificial recharge site by the treated wastewater for the Ariana governorate. On regional characteristics, bibliography and available data on artificial recharge, 13 constraints and 5 factors were hierarchically structured for the adequacy of an artificial recharge. The factors are subdivided into two main groups: environmental factors and economic factors. The adopted methodology allows a preliminary assessment of a recharge site, the weighted linear combination (WLC) and the analytical hierarchy process (AHP) in a GIS. The standardization of the criteria is carried out by the application of the different membership functions. The form and control points of the latter are defined by the consultation of the experts. The weighting of the selected criteria is allocated according to relative importance using the AHP methodology. The weighted linear combination (WLC) integrates the different criteria and factors to delineate the most suitable areas for artificial recharge site selection by treated wastewater. The results of this study showed three potential candidate sites that appear when environmental factors are more important than economic factors. These sites are ranked in descending order using the ELECTRE III method. Nevertheless, decision making for the selection of an artificial recharge site will depend on the decision makers in force.

Keywords: artificial recharge site, treated wastewater, analytical hierarchy process, ELECTRE III

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Authors: Iman Abu-Rub

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This research paper examines if Artificial Intelligence is, in fact, racist or not. Different studies from all around the world, and covering different communities were analyzed to further understand AI’s true implications over different communities. The black community, Asian community, and Muslim community were all analyzed and discussed in the paper to figure out if AI is biased or unbiased towards these specific communities. It was found that the biggest problem AI faces is the biased distribution of data collection. Most of the data inserted and coded into AI are of a white male, which significantly affects the other communities in terms of reliable cultural, political, or medical research. Nonetheless, there are various research was done that help increase awareness of this issue, but also solve it completely if done correctly. Governments and big corporations are able to implement different strategies into their AI inventions to avoid any racist results, which could cause hatred culturally but also unreliable data, medically, for example. Overall, Artificial Intelligence is not racist per se, but the data implementation and current racist culture online manipulate AI to become racist.

Keywords: social media, artificial intelligence, racism, discrimination

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Authors: Magdalena Barbara Kaziuk, Waldemar Kosiba, Marek Jan Kuzniewski

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Introduction: Vitamin D3 has a proven pleiotropic effect, not only responsible for calcium and phosphate management, but also influencing normal functioning of the whole body. Aim: Evaluation of vitamin D3 resources and its effect on a nutritional status, obesity type and glomerular filtration in kidney transplant recipients. Methods: Group of 152 (81 women and 71 men, average age 47.8 ± 11.6 years) patients with a functioning renal transplant their body composition was assessed using the bioimpendance method (BIA) and anthropometric measurements more than 3 months after the transplant. The nutritional status and the obesity type were determined with the Waist to Height Ratio (WHtR) and the Waist to Hip Ratio (WHR). 25- Hydroxyvitamin D3 (25 (OH)D3) was determined, together with its correlation with the obesity type and the glomerular filtration rate (eGFR) calculated with the MDRD formula. Results: The mean 25 (OH)D3 level was 20.4 ng/ml. 30ng/ml was considered as a minimum correct level 22,7% of patients from the study group were classified to be a correct body weight, 56,7% of participants had an android type and 20,6% had a gynoid type. Significant correlation was observed between 25 (OH)D3 deficiency and abdominal obesity (p < 0.005) in patients. Furthermore, a statistically significant relationship was demonstrated between the 25 (OH)D3 levels and eGFR in patients after a kidney transplant. Patients with an android body type had lower eGFR versus those with the gynoid body type (p=0.004). Conclusions: Correct diet in patients after a kidney transplant determines minimum recommended serum levels of vitamin D3. Excessive fatty tissue, low levels of 25 (OH)D3), may be a predictor for android obesity and renal injury; therefore, correct diet and pharmacological management together with physical activities adapted to the physical fitness level of a patient are necessary.

Keywords: kidney transplantation, glomerular filtration rate, obesity, vitamin D3

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Authors: Hakan Duger, Alparslan Ersoy, Canan Ersoy

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The improvement of surgical techniques in recent years has reduced the frequency of postoperative complications in kidney transplant recipients. Novel immunosuppressive agents have reduced rates of graft loss due to acute rejection to less than 1%. However, surgical complications may still lead graft loss and morbidity in recipients. Because of potent immunosuppression, impaired wound healing and complications are frequent after transplantation. We compared the frequency of post-operative surgical complications in diabetic and non-diabetic patients after kidney transplantation. Materials and Methods: This retrospective study conducted in consecutive patients (213 females, 285 males, median age 39 years) who underwent kidney transplant surgery at our center between December 2005 and October 2015. The patients were divided into two groups: diabetics (46 ± 10 year, 26 males, 16 females) and non-diabetics (39 ± 12 year, 259 males, 197 females). Characteristics of both groups were obtained from medical records. Results: We performed 225 living and 273 deceased donor transplantations. Renal replacement type was hemodialysis in 60.8%, peritoneal dialysis in 17.3% and preemptive in 12%. The mean body mass indexes of the recipients were 24 ± 4.6 kg/m², donor age was 48.6 ± 14.3 years, cold ischemic time was 11.3 ± 6.1 hours, surgery time was 4.9 ± 1.2 hours, and recovery time was 54±31 min. The mean hospitalization duration was 19.1 ± 13.5 days. The frequency of postoperative surgical complications was 43.8%. There was no significant difference between the ratios of post-operative surgical complications in non-diabetic (43.5%) and diabetic (47.4%) groups (p=0.648). Post-operative surgical complications were lymphocele (24.6% vs. 23.7%), delayed wound healing (13.2% vs. 7.6%), hematoma (7.8% vs.15.8 %), urinary leak (4.6% vs. 5.3%), hemorrhage (5.1% vs. 0%), hydronephrosis (2.2% vs. 0%), renal artery thrombosis (1.5% vs. 0%), renal vein thrombosis (1% vs. 2.6%), urinoma (0.7% vs. 0%), urinary obstruction (0.5% vs. 0%), ureteral stenosis (0.5% vs. 0%) and ureteral reflux (0.2% vs. 0%) in non-diabetic and diabetic groups, respectively (p > 0.05). Mean serum creatinine levels in non-diabetics and diabetics were 1.43 ± 0.81 and 1.61 ± 0.96 mg/dL at 1st month (p=0.198). At the 6th month, the mean graft and patient survival times in patients with post-operative surgical complications were significantly lower than in those who did not (162.9 ± 3.4 vs. 175.6 ± 1.5 days, p=0.008, and 171 ± 2.9 vs. 176.1 ± 1.6 days, p=0.047, respectively). However, patient survival durations of non-diabetic (173 ± 27) and diabetic (177 ± 13 day) groups were comparable (p=0.396). Conclusion: As a result, we concluded that surgical complications such as lymphocele and delayed wound healing were common and that frequency of these complications in diabetic recipients did not differ from non-diabetic one. All persons involved in the postoperative care of kidney transplant recipients be aware of the potential surgical complications for rapid diagnosis and treatment.

Keywords: kidney transplantation, diabetes mellitus, surgery, complication

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Authors: Pei-Chann Chang, Jhen-Fu Liao, Chin-Hung Teng, Meng-Hui Chen

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This research combines artificial immune system with user and item based collaborative filtering to create an efficient and accurate recommendation system. By applying the characteristic of antibodies and antigens in the artificial immune system and using Pearson correlation coefficient as the affinity threshold to cluster the data, our collaborative filtering can effectively find useful users and items for rating prediction. This research uses MovieLens dataset as our testing target to evaluate the effectiveness of the algorithm developed in this study. The experimental results show that the algorithm can effectively and accurately predict the movie ratings. Compared to some state of the art collaborative filtering systems, our system outperforms them in terms of the mean absolute error on the MovieLens dataset.

Keywords: artificial immune system, collaborative filtering, recommendation system, similarity

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Authors: Aniekan Peter, ECS Naidu, Edidiong Akang, U. Offor, R. Kalhapure, A. A. Chuturgoon, T. Govender, O. O. Azu

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Introduction: Nano-drugs are novel innovations in the management of human immunodeficiency virus (HIV) pandemic, especially resistant strains of the virus in their sanctuary sites: testis and the brain. There are safety concerns to be addressed to achieve the full potential of this new drug delivery system. Aim of study: Our study was designed to investigate toxicity profile of Tenofovir Nanoparticle (TDF-N) synthesized by University of Kwazulu-Natal (UKZN) Nano-team for prevention and treatment of HIV infection. Methodology: Ten adult male Sprague-Dawley rats maintained at the Animal House of the Biomedical Resources Unit UKZN were used for the study. The animals were weighed and divided into two groups of 5 animal each. Control animals (A) were administered with normal saline. Therapeutic dose (4.3 mg/kg) of TDF-N was administered to group B. At the end of four weeks, animals were weighed and sacrificed. Liver and kidney were removed fixed in formal saline, processed and stained using H/E, PAS and MT stains for light microscopy. Serum was obtained for renal function test (RFT), liver function test (LFT) and full blood count (FBC) using appropriate analysers. Cellular measurements were done using ImageJ and Leica software 2.0. Data were analysed using graph pad 6, values < 0.05 were significant. Results: We reported no histological alterations in the liver, kidney, FBC, LFT and RFT between the TDF-N animals and saline control. There were no significant differences in weight, organo-somatic index and histological measurements in the treatment group when compared with saline control. Conclusion/recommendations: TDF-N is not toxic to the liver, kidney and blood cells in our study. More studies using human subjects is recommended.

Keywords: tenofovir nanoparticles, liver, kidney, blood cells

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Authors: Mehrzad Abdi Khalife, Iraj Mahdavi

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This paper presents the agile model for project management process. For project management process, the Project Management Body of Knowledge (PMBOK) guideline has been selected as platform. Combination of computational science and artificial intelligent methodology has been added to the guideline to transfer the standard to agile project management process. The model is the combination of practical standard, computational science and artificial intelligent. In this model, we present communication model and protocols to keep process agile. Here, we illustrate the collaboration man and machine in project management area with artificial intelligent approach.

Keywords: artificial intelligent, conceptual model, man-machine collaboration, project management, standard

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Authors: Kapila Warnakulasuriya, Walimuni Janaka Mendis

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In this study, an artificial intelligence-based approach is developed to diagnose abnormal tissues in human or animal bodies by analyzing magnetic resonance signals. As opposed to the conventional method of generating an image from the magnetic resonance signals, which are then evaluated by a radiologist for the diagnosis of abnormalities, in the discussed approach, the magnetic resonance signals are analyzed by an artificial intelligence algorithm without having to generate or analyze an image. The AI-based program compares magnetic resonance signals with millions of possible magnetic resonance waveforms which can be generated from various types of normal tissues. Waveforms generated by abnormal tissues are then identified, and images of the abnormal tissues are generated with the possible location of them in the body for further diagnostic tests.

Keywords: magnetic resonance, artificial intelligence, magnetic waveform analysis, abnormal tissues

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Authors: Qi Liu, Jiqin Yao, Xiaohu Zhou, Bo Zheng

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The first artificial cell was produced by Thomas Chang in the 1950s when he was trying to make a mimic of red blood cells. Since then, many different types of artificial cells have been constructed from one of the two approaches: a so-called bottom-up approach, which aims to create a cell from scratch, and a top-down approach, in which genes are sequentially knocked out from organisms until only the minimal genome required for sustaining life remains. In this project, bottom-up approach was used to build a new cell-free expression system which mimics artificial cell that capable of protein expression and communicate with each other. The artificial cells constructed from the bottom-up approach are usually lipid vesicles, polymersomes, hydrogels or aqueous droplets containing the nucleic acids and transcription-translation machinery. However, lipid vesicles based artificial cells capable of communication present several issues in the cell communication research: (1) The lipid vesicles normally lose the important functions such as protein expression within a few hours. (2) The lipid membrane allows the permeation of only small molecules and limits the types of molecules that can be sensed and released to the surrounding environment for chemical communication; (3) The lipid vesicles are prone to rupture due to the imbalance of the osmotic pressure. To address these issues, the hydrogel-based artificial cells were constructed in this work. To construct the artificial cell, polyacrylamide hydrogel was functionalized with Acrylate PEG Succinimidyl Carboxymethyl Ester (ACLT-PEG2000-SCM) moiety on the polymer backbone. The proteinaceous factors can then be immobilized on the polymer backbone by the reaction between primary amines of proteins and N-hydroxysuccinimide esters (NHS esters) of ACLT-PEG2000-SCM, the plasmid template and ribosome were encapsulated inside the hydrogel particles. Because the artificial cell could continuously express protein with the supply of nutrients and energy, the artificial cell-artificial cell communication and artificial cell-natural cell communication could be achieved by combining the artificial cell vector with designed plasmids. The plasmids were designed referring to the quorum sensing (QS) system of bacteria, which largely relied on cognate acyl-homoserine lactone (AHL) / transcription pairs. In one communication pair, “sender” is the artificial cell or natural cell that can produce AHL signal molecule by synthesizing the corresponding signal synthase that catalyzed the conversion of S-adenosyl-L-methionine (SAM) into AHL, while the “receiver” is the artificial cell or natural cell that can sense the quorum sensing signaling molecule form “sender” and in turn express the gene of interest. In the experiment, GFP was first immobilized inside the hydrogel particle to prove that the functionalized hydrogel particles could be used for protein binding. After that, the successful communication between artificial cell-artificial cell and artificial cell-natural cell was demonstrated, the successful signal between artificial cell-artificial cell or artificial cell-natural cell could be observed by recording the fluorescence signal increase. The hydrogel-based artificial cell designed in this work can help to study the complex communication system in bacteria, it can also be further developed for therapeutic applications.

Keywords: artificial cell, cell-free system, gene circuit, synthetic biology

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Authors: Ng Liang Shen, Ngahzaifa Abdul Ghani

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This research aimed at developing an early warning system for pre-diabetic and diabetics by analyzing simple and easily determinable signs and symptoms of diabetes among the people living in Malaysia using Particle Swarm Optimized Artificial. With the skyrocketing prevalence of Type 2 diabetes in Malaysia, the system can be used to encourage affected people to seek further medical attention to prevent the onset of diabetes or start managing it early enough to avoid the associated complications. The study sought to find out the best predictive variables of Type 2 Diabetes Mellitus, developed a system to diagnose diabetes from the variables using Artificial Neural Networks and tested the system on accuracy to find out the patent generated from diabetes diagnosis result in machine learning algorithms even at primary or advanced stages.

Keywords: diabetes diagnosis, Artificial Neural Networks, artificial intelligence, soft computing, medical diagnosis

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Authors: Anita Kushwaha

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We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

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Authors: Lai Junzhe, Wang Lihao, Burra Venkata Durga Kumar

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In recent years, due to today's global technological advances, big data and artificial intelligence technologies have been widely used in various industries and fields, playing an important role in reducing costs and increasing efficiency. Among them, artificial intelligence has derived another branch in its own continuous progress and the continuous development of computer personnel, namely distributed artificial intelligence computing systems. Distributed AI is a method for solving complex learning, decision-making, and planning problems, characterized by the ability to take advantage of large-scale computation and the spatial distribution of resources, and accordingly, it can handle problems with large data sets. Nowadays, distributed AI is widely used in military, medical, and human daily life and brings great convenience and efficient operation to life. In this paper, we will discuss three areas of distributed AI computing systems in vision processing, blockchain, and smart home to introduce the performance of distributed systems and the role of AI in distributed systems.

Keywords: distributed system, artificial intelligence, blockchain, IoT, visual information processing, smart home

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Authors: Justyna Minkiewicz

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Artificial Intelligence (AI) applied in the arts may influence the development of AI knowledge in other sectors and then also impact mutual collaboration with the artistic environment. Hence this collaboration may also impact the development of art projects. The paper will reflect the qualitative research outcomes based on in-depth (IDI) interviews within the marketing sector in Poland and desk research. Art is a reflection of the spirit of our times. Moreover, now we are experiencing a significant acceleration in the development of technologies and their use in various sectors. The leading technologies that contribute to the development of the economy, including the creative sector, embrace technologies such as artificial intelligence, blockchain, extended reality, voice processing, and virtual beings. Artificial intelligence is one of the leading technologies developed for several decades, which is currently reaching a high level of interest and use in various sectors. However, the conducted research has shown that there is still low awareness of artificial intelligence and its wide application in various sectors. The study will show how artists use artificial intelligence in their art projects and how it can be translated into practice within the business. At the same time, the paper will raise awareness of the need for businesses to be inspired by the artistic environment. The research proved that there is still a need to popularize knowledge about this technology which is crucial for many sectors. Art projects are tools to develop knowledge and awareness of society and also various sectors. At the same time, artists may benefit from such collaboration. The paper will include selected aspects of mutual relations, areas of possible inspiration, and possible transfers of technological solutions. Those are AI applications in creative industries such as advertising and film, image recognition in art, and projects from different sectors.

Keywords: artificial intelligence, business, art, creative industry, technology

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Authors: Sandeep Reddy, Sonia Allan, Simon Coghlan, Paul Cooper

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Artificial Intelligence (AI) and its application in medicine has generated ample interest amongst policymakers and clinicians. Successes with AI in medical imaging interpretation and clinical decision support are paving the way for its incorporation into routine healthcare delivery. While there has been a focus on the development of ethical principles to guide its application in healthcare, challenges of this application go beyond what ethics principles can address thus requiring robust governance frameworks. Also, while ethical challenges of medical artificial intelligence are being discussed, the ethics of deploying AI in lower-income countries receive less attention than in other developed economies. This creates an imperative not only for sound ethical guidelines but also for robust governance frameworks to regulate AI in medicine around the world. In this article, we discuss what components need to be considered in developing these governance frameworks and who should lead this worldwide effort.

Keywords: artificial intelligence, global health, governance, ethics

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Authors: Marwa Ahmed Abd El Hamied

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In this paper In this paper, a new technique based on Artificial Immunity System (AIS) technique has been developed to track Maximum Power Point (MPP). AIS system is implemented in a photovoltaic system that is subjected to variable temperature and insulation condition. The proposed novel is simulated using Mat Lab program. The results of simulation have been compared to those who are generated from Observation Controller. The proposed model shows promising results as it provide better accuracy comparing to classical model.

Keywords: component, artificial immunity technique, solar energy, perturbation and observation, power based methods

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Authors: Arezou Ghadi, Nasrollah Vahedi, Azam Sinkakarimi

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For determination of antibiotic residues in slaughtered cow carcasses of Amol city in Iran, sampling has done from 100 heads of cow. For this purpose, the microbiological F.P.T (Four-Plate Test) method was used. Basis of this method, a clear zone is creating around the leachate on the plate that already has cultured a uniform layer of under test bacteria on agar plate. In this study from 100 heads of cow carcasses, at least 75 cases (75%) in one of the tested organs (muscle-liver-kidney) have been antibiotic residues. Also, it has been found that kidney have the most positive cases (60%) than other organs (liver and muscle), then the liver (58%) and finally are muscles (51%).

Keywords: antibiotic residues, agar plate test, cow carcass

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Authors: Tarek Aboueldahab, Hanan Farag

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Parallel Job Shop Scheduling Problem (JSP) is a multi-objective and multi constrains NP- optimization problem. Traditional Artificial Intelligence techniques have been widely used; however, they could be trapped into the local minimum without reaching the optimum solution, so we propose a hybrid Artificial Intelligence model (AI) with Discrete Breeding Swarm (DBS) added to traditional Artificial Intelligence to avoid this trapping. This model is applied in the cost minimization of the Car Sequencing and Operator Allocation (CSOA) problem. The practical experiment shows that our model outperforms other techniques in cost minimization.

Keywords: parallel job shop scheduling problem, artificial intelligence, discrete breeding swarm, car sequencing and operator allocation, cost minimization

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Authors: Latika Choudhary

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“The potential benefits of Artificial Intelligence are huge, So are the dangers.” - Dave Water. Artificial intelligence is one of the facet of Information technology domain which despite several attempts does not have a clear definition or ambit. However it can be understood as technology to solve problems via automated decisions and predictions. Artificial intelligence is essentially an algorithm based technology which analyses the large amounts of data and then solves problems by detecting useful patterns. Owing to its automated feature it will not be wrong to say that humans & AI have more utility than humans alone or computers alone.1 For many decades AI experienced enthusiasm as well as setbacks, yet it has today become part and parcel of our everyday life, making it convenient or at times problematic. AI and related technology encompass Intellectual Property in multiple ways, the most important being AI technology for management of Intellectual Property, IP for protecting AI and IP as a hindrance to the transparency of AI systems. Thus the relationship between the two is of reciprocity as IP influences AI and vice versa. While AI is a recent concept, the IP laws for protection or even dealing with its challenges are relatively older, raising the need for revision to keep up with the pace of technological advancements. This paper will analyze the relationship between AI and IP to determine how beneficial or conflictual the same is, address how the old concepts of IP are being stretched to its maximum limits so as to accommodate the unwanted consequences of the Artificial Intelligence and propose ways to mitigate the situation so that AI becomes the friend it is and not turn into a potential foe it appears to be.

Keywords: intellectual property rights, information technology, algorithm, artificial intelligence

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Authors: Widyani Fatwa Dewi, Subroto Athor

Abstract:

In a telecommunication service provider, quantity and interval of customer demand often difficult to predict due to high dependency on customer expansion strategy and technological development. Demand arrives when a customer needs to add capacity to an existing site or build a network in a new site. Because demand is uncertain for each period, and sometimes there is a null demand for several equipments, it is categorized as intermittent. This research aims to improve demand forecast quality in Indonesia's telecommunication service providers by using Artificial Neural Network. In Artificial Neural Network, the pattern or relationship within data will be analyzed using the training process, followed by the learning process as validation stage. Historical demand data for 36 periods is used to support this research. It is found that demand forecast by using Artificial Neural Network outperforms the existing method if it is reviewed on two criteria: the forecast accuracy, using Mean Absolute Deviation (MAD), Mean of the sum of the Squares of the Forecasting Error (MSE), Mean Error (ME) and service level which is shown through inventory cost. This research is expected to increase the reference for a telecommunication demand forecast, which is currently still limited.

Keywords: artificial neural network, demand forecast, forecast accuracy, intermittent, service level, telecommunication

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Authors: Maria Jędrzejczak, Patryk Pieniążek

Abstract:

The European legal reality is on the eve of significant change. In European Union law, there is talk of a “fourth industrial revolution”, which is driven by massive data resources linked to powerful algorithms and powerful computing capacity. The above is closely linked to technological developments in the area of artificial intelligence, which has prompted an analysis covering both the legal environment as well as the economic and social impact, also from an ethical perspective. The discussion on the regulation of artificial intelligence is one of the most serious yet widely held at both European Union and Member State level. The literature expects legal solutions to guarantee security for fundamental rights, including privacy, in artificial intelligence systems. There is no doubt that personal data have been increasingly processed in recent years. It would be impossible for artificial intelligence to function without processing large amounts of data (both personal and non-personal). The main driving force behind the current development of artificial intelligence is advances in computing, but also the increasing availability of data. High-quality data are crucial to the effectiveness of many artificial intelligence systems, particularly when using techniques involving model training. The use of computers and artificial intelligence technology allows for an increase in the speed and efficiency of the actions taken, but also creates security risks for the data processed of an unprecedented magnitude. The proposed regulation in the field of artificial intelligence requires analysis in terms of its impact on the regulation on personal data protection. It is necessary to determine what the mutual relationship between these regulations is and what areas are particularly important in the personal data protection regulation for processing personal data in artificial intelligence systems. The adopted axis of considerations is a preliminary assessment of two issues: 1) what principles of data protection should be applied in particular during processing personal data in artificial intelligence systems, 2) what regulation on liability for personal data breaches is in such systems. The need to change the regulations regarding the rights and obligations of data subjects and entities processing personal data cannot be excluded. It is possible that changes will be required in the provisions regarding the assignment of liability for a breach of personal data protection processed in artificial intelligence systems. The research process in this case concerns the identification of areas in the field of personal data protection that are particularly important (and may require re-regulation) due to the introduction of the proposed legal regulation regarding artificial intelligence. The main question that the authors want to answer is how the European Union regulation against data protection breaches in artificial intelligence systems is shaping up. The answer to this question will include examples to illustrate the practical implications of these legal regulations.

Keywords: data protection law, personal data, AI law, personal data breach

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Authors: Ali Khaleel Kareem, Shian Gao, Ahmed Qasim Ahmed

Abstract:

A numerical investigation of unsteady mixed convection heat transfer in a 3D moving top wall enclosure, which has a central rotating cylinder and uses either artificial roughness on the bottom hot plate or smooth bottom hot plate to study the heat transfer enhancement, is completed for fixed circular cylinder, and anticlockwise and clockwise rotational speeds, -1 ≤ Ω ≤ 1, at Reynolds number of 5000. The top lid-driven wall was cooled, while the other remaining walls that completed obstructed cubic were kept insulated and motionless. A standard k-ε model of Unsteady Reynolds-Averaged Navier-Stokes (URANS) method is involved to deal with turbulent flow. It has been clearly noted that artificial roughness can strongly control the thermal fields and fluid flow patterns. Ultimately, the heat transfer rate has been dramatically increased by involving artificial roughness on the heated bottom wall in the presence of rotating cylinder.

Keywords: artificial roughness, lid-driven cavity, mixed convection heat transfer, rotating cylinder, URANS method

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Authors: Alia Ali, Azeem Taj, Muhammed Joher Amin, Farrukh Iqbal, Zafar Iqbal

Abstract:

Background: Hypertension is commonly found in patients with Diabetic Kidney Disease (DKD). Microalbuminuria is the first clinical sign of involvement of kidneys in patients with type 2 diabetes. Uncontrolled hypertension induces a higher risk of cardiovascular events, including death, increasing proteinuria and progression to kidney disease. Objectives: To determine the correlation between microalbuminuria and hypertension and their association with other risk factors in type 2 diabetic patients. Methods: One hundred and thirteen type 2 diabetic patients were screened for microalbuminuria and raised blood pressure, attending the diabetic clinic of Shaikh Zayed Hospital, Lahore, Pakistan. The study was conducted from November 2012 to June 2013. Results: Patients were divided into two groups. Group 1, those with normoalbuminuria (n=63) and Group 2, those having microalbuminuria (n=50). Group 2 patients showed higher blood pressure values as compared to Group 1. The results were statistically significant and showed poor glycemic control as a contributing risk factor. Conclusion: The study concluded that there is high frequency of hypertension among type 2 diabetics but still much higher among those having microalbuminuria. So, early recognition of renal dysfunction through detection of microalbuminuria and to start treatment without any delay will confer future protection from end-stage renal disease as well as hypertension and its complications in type 2 diabetic patients.

Keywords: hypertension, microalbuminuria, diabetic kidney disease, type 2 Diabetes mellitus

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Authors: Ludmila A. Gavriliuc, Jerry McLarty, Heather E. Kleiner, J. Michael Mathis

Abstract:

Abstract -- Background: The citrus coumarine Auraptene (Aur) is an effective chemopreventive agent, as manifested in many models of diseases and cancer. Nuclear factor erythroid 2-related factor (Nrf2) is an important regulator of genes induced by oxidative stress, such as glutathione S-transferases, heme oxygenase-1, and peroxiredoxin 1, by activating the antioxidant response element (ARE). Genetic and biochemical evidence has demonstrated that glutathione (GSH) and glutathione-dependent enzymes, glutathione reductase (GR), glutathione peroxidases (GPs), glutathione S-transferases (GSTs) are responsible for the control of intracellular reduction-oxidation status and participate in cellular adaptation to oxidative stress. The effect of Aur on the activity of GR, GPs (Se-GP and Se-iGP), and content of GSH in the liver, kidney, and spleen is insufficiently explored. Aim: Our goal was the examination of the Aur influence on the redox-system of GSH in Nrf2 wild type and Nrf2 knockout mice via activation of Nrf2 and ARE. Methods: Twenty female mice, 10 Nrf2 wild-type (WT) and 10 Nrf2 (-/-) knockout (KO), were bred and genotyped for our study. The activity of GR, Se-GP, Se-iGP, GST, G6PD, CytP450 reductase, catalase (Cat), and content of GSH were analyzed in the liver, kidney, and spleen using Spectrophotometry methods. The results of the specific activity of enzymes and the amount of GSH were analyzed with ANOVA and Spearman statistical methods. Results: Aur (200 mg/kg) treatment induced hepatic GST, GR, Se-GP activity and inhibited their activity in the spleen of mice, most likely via activation of the ARE through Nrf2. Activation in kidney Se-GP and G6PD by Aur is also controlled, apparently through Nrf2. Results of the non-parametric Spearman correlation analysis indicated the strong positive correlation between GR and G6PD only in the liver in WT control mice (r=+0.972; p < 0.005) and in the kidney KO control mice (r=+0.958; p < 0.005). The observed low content of GSH in the liver of KO mice indicated an increase in its participation in the neutralization of toxic substances with the absence of induction of GSH-dependent enzymes, such as GST, GR, Se-GP, and Se-iGP. Activation of CytP450 in kidney and spleen and Cat in the liver in KO mice probably revealed another regulatory mechanism for these enzymes. Conclusion: Thereby, obtained results testify that Aur can modulate the activity of genes and antioxidant enzymatic redox-system of GSH, responsible for the control of intracellular reduction-oxidation status.

Keywords: auraptene, glutathione, GST, Nrf2

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