Search results for: smart beta

Authors: C. Iraklis, G. Evmiridis, A. Iraklis

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Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.

Keywords: congestion, distribution networks, loss reduction, particle swarm optimization, smart grid

Procedia PDF Downloads 445

Authors: Luz Hurtado, Rodrigo Rojas, Jaime Romero, Christopher Concha

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The culture of the marine fish red cusk eel Genypterus chilensis is currently considered a priority for Chilean aquaculture which is a Chilean native species of high gastronomic demand and market value. The microbiota was analyzed in terms of diversity and structure using massive Illumina sequencing. The analysis of alpha diversity was performed in samples of G. chilensis larvae of 6, 18 and 32 dph (days post-hatching) and it was observed that there were significant differences (P = 0.05) between the days of culture for the Chao1 index, being the larvae of 18 dph the one with the highest index followed by the larvae of 6 dph, The lowest value for this index was presented in larvae of 32 dph. There were no significant differences in larvae between the days of culture for the Shannon (P=0.0857) and Simpson (P=0.0714) indices. In general, the larvae of G. chilensis have high rates of diversity. When analyzing the beta diversity, a differentiation between the bacterial communities is observed depending on the day of the culture of the larvae. Considering the PCoA elaborated from the unweighted UniFrac statistic, the explained variance was 46.2% (PC1 29.2% and PC2 17.0%) and in the case of the PCoA elaborated with the weighted UniFrac statistic; the explained variance was 65.5% (PC1 41.8% and PC2 23.7%) these differences were significant based on the Permanova statistical analysis (P= 0.002 and 0.037 respectively). When analyzing the taxonomic composition of the microbiota of the larvae in the different days of culture it was observed that at the phyla level the most abundant in the larvae of 6 dph were Proteobacteria (57%) Verrucomicrobia (24%) and Firmicutes (14%), for the larvae of 18 dph the predominant phyla were Proteobacteria (90%), Dependientiae (5%), Actinobacteria (2%) and Plactomyces (2%), for the larvae of 32 dph the phyla that presented the highest relative abundance were Proteobacteria (57%), Firmicutes (29%), Verrucomicrobia (5%) and Actinobacteria (5%), when comparing the larvae between the days it was observed that the phylum Proteobacteria was the most abundant in the samples of larvae of 6, 18 and 32 dph being the larvae of 18 dph those that present the highest relative abundance, the larvae of 6 dph were those that presented the highest relative abundance for the phylum Verrucomicrobia and in the larvae of 32 dph was observed greater abundance of the phylum Firmicutes compared to the other days of larval culture. At the level of genera, those with the highest relative abundance in larvae of 6 dph were Rubritalea (30%), Psychrobacter (28%), staphylococcus (17%) and Ralstonia (10%), for the larvae of 18 dph the genera with the highest abundance were Psychrobacter (47%), Litoreibacter (13%), Nautella (9%) and Cohesibacter (8%), for the larvae of 32 dph the most abundant genera were Alloiococcus (25%), Dialister (14%), Neptunomonas (13%) and Piscirickettsia (11%). When observing the taxonomic composition of the larvae between the days of larval culture, it is observed that there are differences between them.

Keywords: microbiota, diversity, G. Chilensis, larvae

Procedia PDF Downloads 73

Authors: Harsh Sadawarti, Kamal Malik

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Humans are the unique and the most powerful creature on this planet just because of the high level of intelligence gifted by nature. Computational Intelligence is highly influenced by the term natural intelligence, neurosciences and mathematics. To deal with the in-depth study of computational intelligence and to utilize it in real-life applications, it is quite important to understand its simulation with the human brain. In this paper, the three important parts, Frontal Lobe, Occipital Lobe and Parietal Lobe of the human brain, are compared with the ANN(Artificial Neural Network), CNN(Convolutional Neural network), and RNN(Recurrent Neural Network), respectively. Intelligent computational systems are created by combining deductive reasoning, logical concepts and high-level algorithms with the simulation and study of the human brain. Human brain is a combination of Physiology, Psychology, emotions, calculations and many other parameters which are of utmost importance that determines the overall intelligence. To create intelligent algorithms, smart machines and to simulate the human brain in an effective manner, it is quite important to have an insight into the human brain and the basic concepts of biological neurosciences.

Keywords: computational intelligence, neurosciences, convolutional neural network, recurrent neural network, artificial neural network, frontal lobe, occipital lobe, parietal lobe

Procedia PDF Downloads 111

Authors: David Pinzauti, Simon De Jaegher, Maria D'Aguano, Manuele Biazzo

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The COVID-19 pandemic has left an indelible mark on global health, leading to a pressing need for understanding the intricate interactions between the virus and the human microbiome. This study focuses on characterizing the nasal microbiota of patients affected by COVID-19, with a specific emphasis on the comparison with unaffected individuals, to shed light on the crucial role of the microbiome in the development of this viral disease. To achieve this objective, Nanopore technology was employed to analyze the bacterial 16s rRNA full-length gene present in nasal swabs collected in Malta between January 2021 and August 2022. A comprehensive dataset consisting of 268 samples (126 SARS-negative samples and 142 SARS-positive samples) was subjected to a comparative analysis using an in-house, custom pipeline. The findings from this study revealed that individuals affected by COVID-19 possess a nasal microbiota that is significantly less diverse, as evidenced by lower α diversity, and is characterized by distinct microbial communities compared to unaffected individuals. The beta diversity analyses were carried out at different taxonomic resolutions. At the phylum level, Bacteroidota was found to be more prevalent in SARS-negative samples, suggesting a potential decrease during the course of viral infection. At the species level, the identification of several specific biomarkers further underscores the critical role of the nasal microbiota in COVID-19 pathogenesis. Notably, species such as Finegoldia magna, Moraxella catarrhalis, and others exhibited relative abundance in SARS-positive samples, potentially serving as significant indicators of the disease. This study presents valuable insights into the relationship between COVID-19 and the nasal microbiota. The identification of distinct microbial communities and potential biomarkers associated with the disease offers promising avenues for further research and therapeutic interventions aimed at enhancing public health outcomes in the context of COVID-19.

Keywords: COVID-19, nasal microbiota, nanopore technology, 16s rRNA gene, biomarkers

Procedia PDF Downloads 68

Authors: Iftikhar A. Tayubi, Aabdulrahman Alsubhi, Abdullah Althrwi

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The deoxyribonucleic acid text provides a single source of high-quality Cryptography about Deoxyribonucleic acid sequence for structural biologists. We will provide an intuitive, well-organized and user-friendly web interface that allows users to encrypt and decrypt Deoxy Ribonucleic Acid sequence text. It includes complex, securing by using Algorithm to encrypt and decrypt Deoxy Ribonucleic Acid sequence. The utility of this Deoxy Ribonucleic Acid Sequence Text is that, it can provide a user-friendly interface for users to Encrypt and Decrypt store the information about Deoxy Ribonucleic Acid sequence. These interfaces created in this project will satisfy the demands of the scientific community by providing fully encrypt of Deoxy Ribonucleic Acid sequence during this website. We have adopted a methodology by using C# and Active Server Page.NET for programming which is smart and secure. Deoxy Ribonucleic Acid sequence text is a wonderful piece of equipment for encrypting large quantities of data, efficiently. The users can thus navigate from one encoding and store orange text, depending on the field for user’s interest. Algorithm classification allows a user to Protect the deoxy ribonucleic acid sequence from change, whether an alteration or error occurred during the Deoxy Ribonucleic Acid sequence data transfer. It will check the integrity of the Deoxy Ribonucleic Acid sequence data during the access.

Keywords: algorithm, ASP.NET, DNA, encrypt, decrypt

Procedia PDF Downloads 234

Authors: A. Calabrese, V. F. Uricchio, D. di Noia, S. Favale, C. Caiati, G. P. Maggi, G. Donvito, D. Diacono, S. Tangaro, A. Italiano, E. Riezzo, M. Zippitelli, M. Toriello, E. Celiberti, D. Festa, A. Colaianni

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Climate change has a severe impact on human health. There is a vast literature demonstrating temperature increase is causally related to cardiovascular problem and represents a high risk for human health, but there are not study that improve a solution. In this work, it is studied how the clime influenced the human parameter through the analysis of climatic conditions in an area of the Apulia Region: Capurso Municipality. At the same time, medical personnel involved identified a set of variables useful to define an index describing health condition. These scientific studies are the base of an innovative alert system, IPPOCRATE, whose aim is to asses climate risk and share information to population at risk to support prevention and mitigation actions. IPPOCRATE is an e-health system, it is designed to provide technological support to analysis of health risk related to climate and provide tools for prevention and management of critical events. It is the first integrated system of prevention of human risk caused by climate change. IPPOCRATE calculates risk weighting meteorological data with the vulnerability of monitored subjects and uses mobile and cloud technologies to acquire and share information on different data channels. It is composed of four components: Multichannel Hub. Multichannel Hub is the ICT infrastructure used to feed IPPOCRATE cloud with a different type of data coming from remote monitoring devices, or imported from meteorological databases. Such data are ingested, transformed and elaborated in order to be dispatched towards mobile app and VoIP phone systems. IPPOCRATE Multichannel Hub uses open communication protocols to create a set of APIs useful to interface IPPOCRATE with 3rd party applications. Internally, it uses non-relational paradigm to create flexible and highly scalable database. WeHeart and Smart Application The wearable device WeHeart is equipped with sensors designed to measure following biometric variables: heart rate, systolic blood pressure and diastolic blood pressure, blood oxygen saturation, body temperature and blood glucose for diabetic subjects. WeHeart is designed to be easy of use and non-invasive. For data acquisition, users need only to wear it and connect it to Smart Application by Bluetooth protocol. Easy Box was designed to take advantage from new technologies related to e-health care. EasyBox allows user to fully exploit all IPPOCRATE features. Its name, Easy Box, reveals its purpose of container for various devices that may be included depending on user needs. Territorial Registry is the IPPOCRATE web module reserved to medical personnel for monitoring, research and analysis activities. Territorial Registry allows to access to all information gathered by IPPOCRATE using GIS system in order to execute spatial analysis combining geographical data (climatological information and monitored data) with information regarding the clinical history of users and their personal details. Territorial Registry was designed for different type of users: control rooms managed by wide area health facilities, single health care center or single doctor. Territorial registry manages such hierarchy diversifying the access to system functionalities. IPPOCRATE is the first e-Health system focused on climate risk prevention.

Keywords: climate change, health risk, new technological system

Procedia PDF Downloads 867

Authors: Chiung-Hui Chen

Abstract:

The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: behavior, big data, hierarchical hidden Markov model, intelligent object

Procedia PDF Downloads 233

Authors: Jude A. Mbanasor, Chigozirim N. Onwusiribe

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The enigma climate change is no longer an illusion but a reality. In the recent years, the Nigeria climate has changed and the changes are shown by the changing patterns of rainfall, the sunshine, increasing level carbon and nitrous emission as well as deforestation. This study analyzed the behavioural response of bee keepers to variations in the climate and the adaptation techniques developed in response to the climate variation. Beekeeping is a viable economic activity for the alleviation of poverty as the products include honey, wax, pollen, propolis, royal jelly, venom, queens, bees and their larvae and are all marketable. The study adopted the multistage sampling technique to select 120 beekeepers from the five states of Southeast Nigeria. Well-structured questionnaires and focus group discussions were adopted to collect the required data. Statistical tools like the Principal component analysis, data envelopment models, graphs, and charts were used for the data analysis. Changing patterns of rainfall and sunshine with the increasing rate of deforestation had a negative effect on the habitat of the bees. The bee keepers have adopted the Kenya Top bar and Langstroth hives and they establish the bee hives on fallow farmland close to the cultivated communal farms with more flowering crops.

Keywords: climate, farmer, response, smart

Procedia PDF Downloads 133

Authors: Junichi Hosoi

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Epidermal Langerhans cells reside in upper layer of epidermis and play a role in immune surveillance. The finding of the close association of nerve endings to Langerhans cells triggered the research on systemic regulation of Langerhans cells. They disappear from epidermis after exposure to environmental and internal stimuli and reappear about a week later. Myeloid progenitor cells are assumed to be one of the sources of Langerhans cells. We examined the effects of cortisol on the reappearance of Langerhans cells in vitro. Cord-blood derived CD34-positive cells were cultured in the medium supplemented with stem cell factor/Flt3 ligand/granulocyte macrophage-colony stimulating factor/tumor necrosis factor alpha/bone morphologic protein 7/transforming growth factor beta in the presence or absence of cortisol. Cells were analyzed by flow cytometry for CD1a (cluster differentiation 1a), a marker of Langerhans cells and dermal dendritic cells, and CD39 (cluster differentiation factor 39), extracellular adenosine triphosphatase. Both CD1a-positive cells and CD39-positive cells were decreased by treatment with cortisol (suppression by 35% and 22% compared to no stress hormone, respectively). Differentiated Langerhans cells are attracted to epidermis by chemokines that are secreted from keratinocytes. Epidermal keratinocytes were cultured in the presence or absence of cortisol and analyzed for the expression of CCL2 (C-C motif chemokine ligand 2) and CCL20 (C-C motif chemokine ligand 20), which are typical attractants of Langerhans cells, by quantitative reverse transcriptase polymerase chain reaction. The expression of both chemokines, CCL2 and CCL20, were suppressed by treatment with cortisol (suppression by 38% and 48% compared to no stress hormone, respectively). We examined the possible regulation of the suppression by cortisol with plant extracts. The extracts of Ganoderma lucidum and Iris protected the suppression of the differentiation to CD39-positive cells and also the suppression of the gene expression of LC-chemoattractants. These results suggest that cortisol, which is either systemic or locally produced, blocks the supply of epidermal Langerhans cells at 2 steps, differentiation from the precursor and attraction to epidermis. The suppression is possibly blocked by some plant extracts.

Keywords: Langerhans cell, stress, CD39, chemokine

Procedia PDF Downloads 186

Authors: Raluca Ionela Maxim

Abstract:

Designing a gender responsive Science, Technology, Engineering and Mathematics (STEM) mobile game based learning solution (mGBL) is a challenge in terms of content, gamification level and equal engagement of girls and boys. The goal of this case study was to research and create a high-fidelity prototype design of a mobile game that contains role-models as avatars that guide and expose girls and boys to STEM learning content. For this research purpose it was applied the methodology of design sprint with five-phase process that combines design thinking principles. The technique of this methodology comprises smart interviews with STEM experts, mind-map creation, sketching, prototyping and usability testing of the interactive prototype of the gender responsive STEM mGBL. The results have shown that the effect of the avatar/role model had a positive impact. Therefore, by exposing students (boys and girls) to STEM role models in an mGBL tool is helpful for the decreasing of the gender inequalities in STEM fields.

Keywords: design thinking, design sprint, gender-responsive STEM education, mobile game based learning, role-models

Procedia PDF Downloads 135

Authors: Minh Nguyen

Abstract:

Today, QR or Quick Response Codes are prevalent, and mobile/smart devices can efficiently read and understand them. Therefore, we can see their appearance in many areas, such as storing web pages/websites, business phone numbers, redirecting to an app download, business location, social media. The popularity of the QR Code is mainly because of its many advantages, such as it can hold a good amount of information, is small, easy to scan and read by a general RGB camera, and it can still work with some damages on its surface. However, there are still some issues. For instance, some areas needed to be kept untouched for its successful decode (e.g., the “Finder Patterns,” the “Quiet Zone,” etc.), the capability of built-in auto-correction is not robust enough, and it is not flexible enough for many application such as Augment Reality (AR). We proposed a new Colour Quick Response Code that has several advantages over the original ones: (1) there is no untouchable area, (2) it allows up to 40% of the entire code area to be damaged, (3) it is more beneficial for Augmented Reality applications, and (4) it is back-compatible and readable by available QR Code scanners such as Pyzbar. From our experience, our Colour Quick Response Code is significantly more flexible on damage compared to the original QR Code. Our code is believed to be suitable in situations where standard 2D Barcodes fail to work, such as curved and shiny surfaces, for instance, medical blood test sample tubes and syringes.

Keywords: QR code, computer vision, image processing, 2D barcode

Procedia PDF Downloads 118

Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: crime prediction, machine learning, public safety, smart city

Procedia PDF Downloads 111

Authors: Sara Rankohi, Lloyd Waugh

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Construction sites are information saturated. Digitalization is hitting construction sites to meet the incredible demand of knowledge sharing and information documentations. From flying drones, 3D Lasers scanners, pocket mobile applications, to augmented reality glasses and smart helmet, visualization technologies help real-time information imposed straight onto construction professional’s field of vision. Although these technologies are very applicable and can have the direct impact on project cost and productivity, experience shows that only a minority of construction professionals quickly adapt themselves to benefit from them in practice. The majority of construction managers still tend to apply traditional construction management methods. This paper investigates a) current applications of visualization technologies in construction projects management, b) the direct effect of these technologies on productivity improvement and cost saving of a multi-residential building project via a case study on Mac Taggart Senior Care project located in Edmonton, Alberta. The research shows the imaged based technologies have a direct impact on improving project productivity and cost savings.

Keywords: image-based technologies, project management, cost, productivity improvement

Procedia PDF Downloads 360

Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

Procedia PDF Downloads 58

Authors: Olivia Bory Devisme, Denis Genon-Catalot, Frederic Alicalapa, Pierre-Olivier Lucas De Peslouan, Jean-Pierre Chabriat

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In the context of climate change, it is essential that island territories gain energy autonomy. Currently mostly dependent on fossil fuels, the island of Reunion lo- cated in the Indian Ocean nevertheless has a high potential for solar energy. As the market for photovoltaic panels has been growing in recent years, the issues of energy losses linked to the multiple conversions from direct current to alternating current are emerging. In order to quantify these advantages and disadvantages by a comparative study, this document present the measurements carried out on a direct current test bench, particularly for lighting, ventilation, air condi- tioning and office equipment for the tertiary sector. All equipment is supplied with DC power from energy produced by photovoltaic panels. A weather sta- tion, environmental indoor sensors, and drivers are also used to control energy. Self-consumption is encouraged in order to manage different priorities between user consumption and energy storage in a lithium iron phosphate battery. The measurements are compared to a conventional electrical architecture (DC-AC- DC) for energy consumption, equipment overheating, cost, and life cycle analysis.

Keywords: DC microgrids, solar energy, smart buildings, storage

Procedia PDF Downloads 162

Authors: S. Ibrahim, D. Salilew-Wondim, M. Hoelker, C. Looft, E. Tholen, C. Grosse-Brinkhaus, K. Schellander, C. Neuhoff, D. Tesfaye

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Bovine endometrial cells appear to have a key role in innate immune defense of the female genital tract. A better understanding of molecular changes in microRNAs (miRNAs) and their target genes expression may identify reliable prognostic indicators for cows that will resolve inflammation and resume cyclicity. In the current study, we hypothesized that let-7 miRNAs family has a primary role in the innate immune defence of the endometrium tissue against bacterial infection, which is partly achieved via regulating mRNA stability of pro-inflammatory cytokines at the post-transcriptional level. Therefore, we conducted two experiments. In the first experiment, primary bovine endometrial cells were challenged with clinical (3.0 μg/ml) and sub-clinical (0.5 μg/ml) doses of lipopolysaccharide (LPS) for 24h. In the 2nd experiment, we have investigated the potential role of let-7 miRNAs (let-7a and let-7f) using gain and loss of function approaches. Additionally, tumor necrosis factor alpha (TNFα), transforming growth factor beta 1 induced transcript 1 (TGFB1I1) and serum deprivation response (SDPR) genes were validated using reporter assay. Here we addressed for the first time that let-7 miRNAs have a precise role in bovine endometrium, where LPS dysregulated let-7 miRNAs family expression was associated with an increased pro-inflammatory cytokine level by directly/indirectly targeting the TNFα, interleukin 6 (IL6), nuclear factor kappa-light-chain enhancer of activated B cells (NFκB), TGFβ1I1 and SDPR genes. To our knowledge, this is the first study showing that TNFα, TGFβ1I1 and SDPR were identified and validated as novel let-7 miRNAs targets and could have a distinct role in inflammatory immune response of LPS challenged bovine endometrial cells. Our data represent a new finding by which uterine homeostasis is maintained through functional regulation of let-7a by down-regulation of pro-inflammatory cytokines expression (TNFα and IL6) at the mRNA and protein levels. These findings suggest that LPS serves as a negative regulator of let-7 miRNAs expression and provides a mechanism for the persistent pro-inflammatory phenotype, which is a hallmark of bovine subclinical endometritis.

Keywords: bovine endometrial cells, let-7, lipopolysaccharide, pro-inflammatory cytokines

Procedia PDF Downloads 380

Authors: Stuti Modi, Aditi Kambli

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This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

Procedia PDF Downloads 186

Authors: Malihe Motiei, Nor Hidayati Zakaria, Davide Aloini

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This study aims to present a method to develop the failure measurement model for ERP post-implementation. To achieve this outcome, the study firstly evaluates the suitability of Technology-Organization-Environment framework for the proposed conceptual model. This study explains how to discover the constructs and subsequently to design and evaluate the constructs as formative or reflective. Constructs are used including reflective and purely formative. Then, the risk dimensions are investigated to determine the instruments to examine the impact of risk on ERP failure after implementation. Two construct as formative constructs consist inadequate implementation and poor organizational decision making. Subsequently six construct as reflective construct include technical risks, operational risks, managerial risks, top management risks, lack of external risks, and user’s inefficiency risks. A survey was conducted among Iranian industries to collect data. 69 data were collected from manufacturing sectors and the data were analyzed by Smart PLS software. The results indicated that all measurements included 39 critical risk factors were acceptable for the ERP post-implementation failure model.

Keywords: critical risk factors (CRFs), ERP projects, ERP post-implementation, measurement instruments, ERP system failure measurement model

Procedia PDF Downloads 363

Authors: Mazharuddin Syed Ahmed

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This research presents a framework used to develop The Ara Polytechnic College of Architecture Studies building “Kahukura” which is Green Building certified. This framework integrates the development of a smart building digital twin by utilizing Building Information Modelling (BIM) and its BIM maturity levels, including Levels of Development (LOD), eight dimensions of BIM, Heritage-BIM (H-BIM) and Facility Management BIM (FM BIM). The research also outlines a structured approach to building performance analysis and integration with the circular economy, encapsulated within a five-level digital twin framework. Starting with Level 1, the Descriptive Twin provides a live, editable visual replica of the built asset, allowing for specific data inclusion and extraction. Advancing to Level 2, the Informative Twin integrates operational and sensory data, enhancing data verification and system integration. At Level 3, the Predictive Twin utilizes operational data to generate insights and proactive management suggestions. Progressing to Level 4, the Comprehensive Twin simulates future scenarios, enabling robust “what-if” analyses. Finally, Level 5, the Autonomous Twin, represents the pinnacle of digital twin evolution, capable of learning and autonomously acting on behalf of users.

Keywords: building information modelling, circular economy integration, digital twin, predictive analytics

Procedia PDF Downloads 43

Authors: Reynaldo Esquivel, Pedro Hernandez, Aaron Martinez-Higareda, Sergio Tena-Cano, Enrique Alvarez-Ramos, Armando Lucero-Acuna

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Stimuli-responsive nanomaterials play an essential role in loading, transporting and well-distribution of anti-cancer compounds in the cellular surroundings. The outstanding properties as the Lower Critical Solution Temperature (LCST), hydrolytic cleavage and protonation/deprotonation cycle, govern the release and delivery mechanisms of payloads. In this contribution, we experimentally determine the load efficiency and release of antineoplastic Vincristine Sulfate into PNIPAM-Interpenetrated-Chitosan (PIntC) nanoparticles. Structural analysis was performed by Fourier Transform Infrared Spectroscopy (FT-IR) and Proton Nuclear Magnetic Resonance (1HNMR). ζ-Potential (ζ) and Hydrodynamic diameter (DH) measurements were monitored by Electrophoretic Mobility (EM) and Dynamic Light scattering (DLS) respectively. Mathematical analysis of the release pharmacokinetics reveals a three-phase model above LCST, while a monophasic of Vincristine release model was observed at 32 °C. Cytotoxic essays reveal a noticeable enhancement of Vincristine effectiveness at low drug concentration on HeLa cervix cancer and MDA-MB-231 breast cancer.

Keywords: nanoparticles, vincristine, drug delivery, PNIPAM

Procedia PDF Downloads 156

Authors: A. Kherraf, M. Bouziane, L. Azzouzi, R. Habbal

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Introduction: Hypocalcaemia is a rare cause of heart failure. We report the clinical case of a young patient with reversible dilated cardiomyopathy secondary to hypocalcaemia in the context of hyperparathyroidism. Clinical case: We report the clinical case of a 23-year-old patient with a history of thyroidectomy for papillary thyroid carcinoma 3 years previously, who presented to the emergency room with a progressive onset dyspnea and edema of the lower limbs. Clinical examination showed hypotension at 90/70 mmHg, tachycardia at 102 bpm, and edema of the lower limbs. The ECG showed a regular sinus rhythm with a prolonged corrected QT interval to 520ms. The chest x-ray showed cardiomegaly. Echocardiography revealed dilated cardiomyopathy with biventricular dysfunction and a left ventricular ejection fraction of 45%, as well as moderate mitral insufficiency by restriction of the posterior mitral leaflet, moderate tricuspid insufficiency, and a dilated inferior vena cava with a pulmonary arterial pressure estimated at 46 mmHg. Blood tests revealed severe hypocalcemia at 38 mg / l with normal albumin and thyroxine levels, as well as hyperphosphatemia and increased TSH. The patient received calcium intake and vitamin D supplementation and was treated with beta blockers, ACE inhibitors, and diuretics with good progress and progressive normalization of cardiac function. Discussion: The cardiovascular manifestations of hypocalcaemia usually appear with deeply low serum calcium levels. This can lead to hypotension, arrhythmias, ventricular fibrillation, prolonged QT interval, or even heart failure. Heart failure is a rare and serious complication of hypocalcemia but most often characterized by complete normalization of myocardial function after treatment. The etiology of the hypocalcaemia, in this case, was probably related to accidental parathyroid removal during thyroidectomy. This is why careful monitoring of calcium levels is recommended after surgery. Conclusion: Hypocalcemic heart failure is rare but reversible heart disease. Systematic monitoring of serum calcium should be performed in all patients after thyroid surgery to avoid any complications related to hypoparathyroidism.

Keywords: hypocalcemia, heart failure, thyroid surgery, hypoparathyroidism

Procedia PDF Downloads 143

Authors: Salina Yahya Saddick

Abstract:

Ovarian cancer remains the most lethal gynecological malignancy due to the lack of highly sensitive and specific screening tools for detection of early-stage disease. The OSE provides the progenitor cells for 90% of human ovarian cancers. Recent morphologic, immunohistochemical and molecular genetic studies have led to the development of a new paradigm for the pathogenesis and origin of epithelial ovarian cancer (EOC) based on a ualistic model of carcinogenesis that divides EOC into two broad categories designated Types I and II which are characterized by specific mutations, including KRAS, BRAF, ERBB2, CTNNB1, PTEN PIK3CA, ARID1A, and PPPR1A, which target specific cell signaling pathways. Type 1 tumors rarely harbor TP53. type I tumors are relatively genetically stable and typically display a variety of somatic sequence mutations that include KRAS, BRAF, PTEN, PIK3CA CTNNB1 (the gene encoding beta catenin), ARID1A and PPP2R1A but very rarely TP53 . The cancer stem cell (CSC) hypothesis postulates that the tumorigenic potential of CSCs is confined to a very small subset of tumor cells and is defined by their ability to self-renew and differentiate leading to the formation of a tumor mass. Potential protein biomarker miRNA, are promising biomarkers as they are remarkably stable to allow isolation and analysis from tissues and from blood in which they can be found as free circulating nucleic acids and in mononuclear cells. Recently, genomic anaylsis have identified biomarkers and potential therapeutic targets for ovarian cancer namely, FGF18 which plays an active role in controlling migration, invasion, and tumorigenicity of ovarian cancer cells through NF-κB activation, which increased the production of oncogenic cytokines and chemokines. This review summarizes update information on epithelial ovarian cancers and point out to the most recent ongoing research.

Keywords: epithelial ovarian cancers, somatic sequence mutations, cancer stem cell (CSC), potential protein, biomarker, genomic analysis, FGF18 biomarker

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Authors: M. Emmanouilidou

Abstract:

The Internet of Things (IoT) is a disruptive technological paradigm that is at the center of the digital evolution by integrating physical and virtual worlds leading to the creation of extended interconnected ecosystems that are characterized as smart environments. The concept of the IoT has a broad range of applications in different industries including the healthcare sector. The Internet of Healthcare Things (IoHT), a branch of the IoT, is expected to bring promising benefits to all involved stakeholders and accelerate the revolution of the healthcare sector through a transition towards preventive and personalized medicine. The socio-economic challenges that the healthcare sector is facing further emphasize the need for a radical transformation of healthcare systems in both developed and developing countries with the role of pervasive technological innovations, such as IoHT, recognized as key to counteract the relevant challenges. Besides the number of potential opportunities that IoHT presents, there are fundamental ethical concerns that need to be considered and addressed in relation to the application of IoHT. This paper contributes to the discussion of the emerging topic of IoHT by providing an overview of the role and potential of IoHT, highlighting the characteristics of the current and future healthcare landscape, reporting on the up-to-date status of IoHT in Europe and reflecting upon existing research in the ethics of IoHT by incorporating additional ethical dimensions that have been ignored which can provide pathways for future research in the field.

Keywords: ethics, Europe, healthcare, Internet of Things

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Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif

Abstract:

Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.

Keywords: beamforming, interference, mutual information, wireless communications

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Authors: Christo Nicholls

Abstract:

The National Electricity Grid (NEG) in South Africa has been under strain for the last five years. This overburden of the NEG led Eskom (the State-Owned Entity responsible for the NEG) to implement a blunt methodology to assist them in reducing the maximum demand (MD) on the NEG, when required, called Loadshedding. The challenge of this methodology is that not only does it lead to immense technical issues with the distribution network equipment, e.g., transformers, due to the frequent abrupt off and on switching, it also has a broader negative fiscal impact on the distributors, as their key consumers (commercial & industrial) are now grid defecting due to the lack of Electricity Security Provision (ESP). This paper provides a pragmatic alternative methodology utilizing specific functionalities embedded within direct-connect single and three-phase Advanced Meter Infrastructure (AMI) Solutions deployed within the distribution network, in conjunction with a Multi-Agent Systems Based AI implementation focused on Automated Negotiation Peer-2-Peer trading. The results of this research clearly illustrate, not only does methodology provide a factual percentage contribution towards the NEG MD at the point of consideration, it also allows the distributor to leverage the real-time MD data from key consumers to activate complex, yet impact-measurable Demand Response (DR) programs.

Keywords: AI, AMI, demand response, multi-agent

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Authors: Carles Ferré, Ferran Llopis, Javier Jacob, Jordi Giol, Xavier Palom, Ignasi Bardés

Abstract:

Objective: To analyze the characteristics of acute bacterial prostatitis (ABP) in elderly patients attended in the emergency department (ED). Methods: Observational and cohort study with prospective follow-up including patients with ABP presenting to the ED from January-December 2012. Data were collected for demographic variables, comorbidities, clinical and microbiological findings, treatment, outcome, and reconsultation at 30 days follow up. Findings were compared between patients ≥ 75 years (study group) and < 75 years (control group). Results: During the study period 241 episodes of ABP were included for analysis. Mean age was 62,9 ± 16 years, and 64 (26.5%) were ≥ 75 years old. A history of prostate adenoma was reported in 54 cases (22,4%), diabetes mellitus in 47 patients (19,5%) and prior manipulation of the lower urinary tract in 40 (17%). Mean symptoms duration was 3.38 ± 4.04 days, voiding symptoms were present in 176 cases (73%) and fever in 154 (64%). From 216 urine cultures, 128 were positive (59%) and 24 (17,6%) out of 136 blood cultures. Escherichia coli was the main pathogen in 58.6% of urine cultures and 64% of blood cultures (with resistant strains to fluoroquinolones in 27,7%, cotrimoxazole in 22,9% and amoxicillin/clavulanic in 27.7% of cases). Seventy patients (29%) were admitted to the hospital, and 3 died. At 30-day follow-up, 29 patients (12%) returned to the ED. In the bivariate analysis previous manipulation of the urinary tract, history of cancer, previous antibiotic treatment, resistant E. coli strains to amoxicillin-clavulanate and ciprofloxacin and extended spectrum beta-lactamase (ESBL) producers, renal impairment, and admission to the hospital were significantly more frequent (p < 0.05) among patients ≥ 75 years compared to those younger than 75 years. Conclusions: Ciprofloxacin and amoxicillin-clavulanate appear not to be good options for the empiric treatment of ABP for patients ≥ 75 years given the drug-resistance pattern in our series, and the proportion of ESBL-producing strains of E. coli should be taken into account. Awaiting bacteria identification and antibiogram from urine and/or blood cultures, treatment on an inpatient basis should be considered in older patients with ABP.

Keywords: acute bacterial prostatitits, antibiotic resistance, elderly patients, emergency

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Authors: Elisaveta Kirilova, Wilfried Becker, Jordanka Ivanova, Tatyana Petrova

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The study is a continuation of the research on the hygrothermal piezoelectric response of a smart patch/layer joint with undesirable interface defect (gap) at dynamic time harmonic mechanical and electrical load and environmental conditions. In order to find the axial displacements, shear stress and interface debond length in a closed analytical form for different positions of the interface gap, the 1D modified shear lag analysis is used. The debond length is represented as a function of many parameters (frequency, magnitude, electric displacement, moisture and temperature, joint geometry, position of the gap along the interface, etc.). Then the Genetic algorithm (GA) is implemented to find this position of the gap along the interface at which a vanishing/minimal debond length is ensured, e.g to find the most harmless position for the safe work of the structure. The illustrative example clearly shows that analytical shear-lag solutions and GA method can be combined successfully to give an effective prognosis of interface shear stress and interface delamination in patch/layer structure at combined loading with existing defects. To show the effect of the position of the interface gap, all obtained results are given in figures and discussed.

Keywords: genetic algorithm, minimal delamination, optimal gap position, shear lag solution

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Authors: Ahmadu Girgiri, Lawan Gana Ali, Mamman M. Baba

Abstract:

Environmental security clearly articulates the perfections and developments of various communities around the world irrespective of the region, culture, religion or social inclination. Although, the present state of insecurity has become serious issue devastating the peace, unity, stability and progress of man and his physical environment particularly in developing countries. Recently, measure of security and it management in Nigeria has been a bottle-neck to the effectiveness and advancement of various sectors that include; business, education, social relations, politics and above all an economy. Several measures have been considered on mitigating environment insecurity such as surveillance, demarcation, security personnel empowerment and the likes, but still the issue remains disturbing. In this paper, we present the application of new technology that contributes to the improvement of security surveillance known as “Wireless Sensor Network (WSN)”. The system is new, smart and emerging technology that provides monitoring, detection and aggregation of information using sensor nodes and wireless network. WSN detects, monitors and stores information or activities in the deployed area such as schools, environment, business centers, public squares, industries, and outskirts and transmit to end users. This will reduce the cost of security funding and eases security surveillance depending on the nature and the requirement of the deployment.

Keywords: application, environment, insecurity, sensor, wireless sensor network

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Authors: Davaanyam Surenjav, Chinzolboo Dandarbaatar, Ganbold Batkhuyag

Abstract:

Primate city induced rapid urbanization has been become one of the main challenges in sustainable development in Mongolia like other developing countries since transition to market economy in 1990. According due to statistical yearbook, population number of Ulaanbaatar city has increased from 0.5 million to 1.5 million for last 30 years and contains now almost half (47%) of total Mongolian population. Rural-Ulaanbaatar and local Cities-Ulaanbaatar city migration leads to social issues like uncontrolled urbanization, income inequality, poverty, overwork of public service, economic over cost for redevelopment and limitation of transport and environmental degradation including air, noise, water and soil pollution. Most thresholds of all of the sustainable urban development main and sub-indicators over exceeded from safety level to unsafety level in Ulaanbaatar. So, there is an urgent need to remove migration pull factors including some administrative and high education functions from Ulaanbaatar city to its satellite cities or secondary cities. Moreover, urban smart transport system and green and renewable energy technologies should be introduced to urban development master plan of Ulaanbaatar city.

Keywords: challenge for sustainable urban development, migration factors, primate city , urban safety thresholds

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Authors: Rajendra Kumar Isaac, Monisha Isaac

Abstract:

Climate variability and changes are the emerging challenges for Indian agriculture with the growing population to ensure national food security. A study was conducted to assess the Climatic Change effects in medium to low altitude areas of the Himalayan region causing changes in land use and cereal crop productivity with the various climatic parameters. The rainfall and temperature changes from 1951 to 2013 were studied at four locations of varying altitudes, namely Hardwar, Rudra Prayag, Uttar Kashi and Tehri Garwal. It was observed that there is noticeable increment in temperature on all the four locations. It was surprisingly observed that the mean rainfall intensity of 30 minutes duration has increased at the rate of 0.1 mm/hours since 2000. The study shows that the combined effect of increasing temperature, rainfall, runoff and urbanization at the mid-Himalayan region is causing an increase in various climatic disasters and changes in agriculture patterns. A noticeable change in cropping patterns, crop productivity and land use change was observed. Appropriate adaptation and mitigation strategies are necessary to ensure that sustainable and climate-resilient agriculture. Appropriate information is necessary for farmers, as well as planners and decision makers for developing, disseminating and adopting climate-smart technologies.

Keywords: climate variability, agriculture, land use, mitigation strategies

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