Search results for: small signal model

Authors: Jennifer Hunter, Francisco Ramirez, Neil A. Nedley, Thania Solorio, Christian Freed, Erica Kinjo

Abstract:

People who have autoimmune disease are often at an increased risk for psychological disorders such as anxiety. Untreated psychological conditions can affect the development of disease and can affect one’s general quality of life. In this study, it was hypothesized that an educational community-based intervention would be useful in decreasing the anxiety levels of participants with autoimmune disease. Programs, 2-hours long each, were held weekly over a period of eight weeks. During every meeting, a 45-minute DVD presentation by a skilled physician was shown, a small group discussion was guided by trained facilitators, and weekly practical assignments were given to each participant. The focus of the program was to educate participants about healthy lifestyle behaviors such as exercise, nutrition, sleep hygiene, helpful thought patterns etc., and to provide a group environment in which each participant was supported. Participants were assessed pre-post program for anxiety using the Depression and Anxiety Assessment Test (registration TX 7-398-022), a validated mental health test based on DSM-5 criteria and demographics. Anxiety scores were classified according to the DSM-5 criteria into 4 categories: none (0-6), mild (7-10), moderate (11-19) or severe (20 or more). Out of the participants who participated in programs conducted in the manner explained above (n=431), the average age was 54.9 (SD 16.6) and 81.9% were female. At baseline, the mean group anxiety level was 9.4 (SD 5.4). Within the baseline group, anxiety levels were as follows: none (21.1%), mild (22.0%), moderate (27.1%) and severe (29.7%). After the program, mean group anxiety decreased to 4.7 (SD 4.0). Post-program anxiety levels were as follows: none (54.8%), mild (27.1%), moderate (12.5%), severe (5.6%). The decrease in overall anxiety levels was significant t(431)=19.3 p<.001, 95% CI [0.815, 1.041]. It was concluded that the eight-week intensive was beneficial in decreasing the anxiety levels of participants. A long-term follow-up study would be beneficial in determining how lasting such improvements are especially since autoimmune diseases are often chronic. Additionally, future studies that utilize a control group would aid in establishing whether the improvements seen are due to the use of this specific lifestyle-educational program.

Keywords: anxiety, auto-immune disease, community-based educational program, lifestyle

Procedia PDF Downloads 106

Authors: Alexander David Natanson

Abstract:

This paper focuses on the effect of Sanctuary and Immigration and Customs Enforcement (ICE) policies on local economies. "Sanctuary cities" refers to municipal jurisdictions that limit their cooperation with the federal government's efforts to enforce immigration. Using county-level data from the American Community Survey and ICE data on economic indicators from 2006 to 2018, this study isolates the effects of local immigration policies on U.S. counties. The investigation is accomplished by simultaneously studying the policies' effects in counties where immigrants' families are persecuted via collaboration with Immigration and Customs Enforcement (ICE), in contrast to counties that provide protections. The analysis includes a difference-in-difference & two-way fixed effect model. Results are robust to nearest-neighbor matching, after the random assignment of treatment, after running estimations using different cutoffs for immigration policies, and with a regression discontinuity model comparing bordering counties with opposite policies. Results are also robust after restricting the data to a single-year policy adoption, using the Sun and Abraham estimator, and with event-study estimation to deal with the staggered treatment issue. In addition, the study reverses the estimation to understand what drives the decision to choose policies to detect the presence of reverse causality biases in the estimated policy impact on economic factors. The evidence demonstrates that providing protections to undocumented immigrants increases economic activity. The estimates show gains in per capita income ranging from 3.1 to 7.2, median wages between 1.7 to 2.6, and GDP between 2.4 to 4.1 percent. Regarding labor, sanctuary counties saw increases in total employment between 2.3 to 4 percent, and the unemployment rate declined from 12 to 17 percent. The data further shows that ICE policies have no statistically significant effects on income, median wages, or GDP but adverse effects on total employment, with declines from 1 to 2 percent, mostly in rural counties, and an increase in unemployment of around 7 percent in urban counties. In addition, results show a decline in the foreign-born population in ICE counties but no changes in sanctuary counties. The study also finds similar results for sanctuary counties when separating the data between urban, rural, educational attainment, gender, ethnic groups, economic quintiles, and the number of business establishments. The takeaway from this study is that institutional inclusion creates the dynamic nature of an economy, as inclusion allows for economic expansion due to the extension of fundamental freedoms to newcomers. Inclusive policies show positive effects on economic outcomes with no evident increase in population. To make sense of these results, the hypothesis and theoretical model propose that inclusive immigration policies play an essential role in conditioning the effect of immigration by decreasing uncertainties and constraints for immigrants' interaction in their communities, decreasing the cost from fear of deportation or the constant fear of criminalization and optimize their human capital.

Keywords: inclusive and exclusive institutions, post matching, fixed effect, time trend, regression discontinuity, difference-in-difference, randomization inference and sun, Abraham estimator

Procedia PDF Downloads 76

Authors: C. P. Autry, A.W. Roscoe

Abstract:

Authentication protocols based on public key infrastructure (PKI) and trusted third party (TTP) are no longer adequate for industrial scale IoT networks thanks to issues such as low compute and power availability, the use of widely distributed and commercial off-the-shelf (COTS) systems, and the increasingly sophisticated attackers and attacks we now have to counter. For example, there is increasing concern about nation-state-based interference and future quantum computing capability. We have examined this space from first principles and have developed several approaches to group and point-to-point authentication for IoT that do not depend on the use of a centralised client-server model. We emphasise the use of quantum resistant primitives such as strong cryptographic hashing and the use multi-factor authentication.

Keywords: authentication, enterprise IoT cybersecurity, PKI/TTP, IoT space

Procedia PDF Downloads 159

Authors: Nada Mohamed, Abdel Aziz Mohamed

Abstract:

Climate change in coastal areas is a global issue that can be felt on local scale and will be around for decades and centuries to come to an end; it also has critical risks on the city’s economy, communities, and the natural environment. One of these changes that cause a huge risk on coastal cities is the sea level rise (SLR). SLR is a result of scarcity and reduction in global environmental system. The main cause of climate change and global warming is the countries with high development index (HDI) as Japan and Germany while the medium and low HDI countries as Egypt does not have enough awareness and advanced tactics to adapt with this changes that destroy urban areas and cause loss in land and economy. This is why Climate Resilience is one of the UN sustainable development goals 2030, which is calling for actions to strengthen climate change resilience through mitigation and adaptation. For many reasons, adaptation has received less attention than mitigation and it is only recently that adaptation has become a focal global point of attention. This adaption can be achieved through some actions such as upgrading the use and the design of the land, adjusting business and activities of people, and increasing community understanding of climate risks. To reach the adaption goals, and we have to apply a strategic pathway to Climate Resilience, which is the Urban Bioregionalism Paradigm. Resiliency has been framed as persistence, adaptation, and transformation. Climate Resilience decision support system includes a visualization platform where ecological, social, and economic information can be viewed alongside with specific geographies that's why Urban Bioregionalism is a socio-ecological system which is defined as a paradigm that has potential to help move social attitudes toward environmental understanding and deepen human-environment connections within ecological development. The research aim is to achieve an adaptive integrated urban development model throughout the analyses of tactics and strategies that can be used to adapt urban areas and coastal communities to the challenges of climate changes especially SLR and also simulation model using advanced technological software for a coastal city corridor to elaborates the suitable strategy to apply.

Keywords: climate resilience, sea level rise, SLR, coastal resilience, adaptive development simulation

Procedia PDF Downloads 130

Authors: Ashutosh Saxena, Kumar Pallav, Ramji Dwivedi

Abstract:

The present study estimates the seismicity parameter 'b' and maximum possible magnitude of an earthquake (Mmax) for Gujarat region with three well-established methods viz. Kijiko parametric model (KP), Kijiko-Sellevol-Bayern (KSB) and Tapered Gutenberg-Richter (TGR), as a combined seismic source regime. The earthquake catalogue is prepared for a period of 1330 to 2013 in the region Latitudes 20o N to 250 N and Longitudinally extending from 680 to 750 E for earthquake moment magnitude (Mw) ≥4.0. The ’a’ and 'b' value estimated for the region as 4.68 and 0.58. Further, Mmax estimated as 8.54 (± 0.29), 8.69 (± 0.48), and 8.12 with KP, KSB, and TGR, respectively.

Keywords: Mmax, seismicity parameter, Gujarat, Tapered Gutenberg-Richter

Procedia PDF Downloads 533

Authors: Rebecca S. Hock, Cyralene P. Bryce, Kevin Williams, Arielle G. Rabinowitz, Janina R. Galler

Abstract:

Background: Findings have been mixed regarding whether offspring of parents who were abused or neglected as children have a greater risk of experiencing abuse or neglect themselves. In addition, many studies on this topic are restricted to physical abuse and take place in a limited number of countries, representing a small segment of the world's population. Methods: We examined relationships between childhood maltreatment history assessed in a subset (N=68) of the original longitudinal birth cohort (G1) of the Barbados Nutrition Study and their now-adult offspring (G2) (N=111) using the Childhood Trauma Questionnaire-Short Form (CTQ-SF). We used Pearson correlations to assess relationships between parent and offspring CTQ-SF total and subscale scores (physical, emotional, and sexual abuse; physical and emotional neglect). Next, we ran multiple regression analyses, using the parental CTQ-SF total score and the parental Sexual Abuse score as primary predictors separately in our models of G2 CTQ-SF (total and subscale scores). Results: G1 total CTQ-SF scores were correlated with G2 offspring Emotional Neglect and total scores. G1 Sexual Abuse history was significantly correlated with G2 Emotional Abuse, Sexual Abuse, Emotional Neglect, and Total Score. In fully-adjusted regression models, parental (G1) total CTQ-SF scores remained significantly associated with G2 offspring reports of Emotional Neglect, and parental (G1) Sexual Abuse was associated with offspring (G2) reports of Emotional Abuse, Physical Abuse, Emotional Neglect, and overall CTQ-SF scores. Conclusions: Our findings support a link between parental exposure to childhood maltreatment and their offspring's self-reported exposure to childhood maltreatment. Of note, there was not an exact correspondence between the subcategory of maltreatment experienced from one generation to the next. Compared with other subcategories, G1 Sexual Abuse history was the most likely to predict G2 offspring maltreatment. Further studies are needed to delineate underlying mechanisms and to develop intervention strategies aimed at preventing intergenerational transmission.

Keywords: trauma, family, adolescents, intergenerational trauma, child abuse, child neglect, global mental health, North America

Procedia PDF Downloads 79

Authors: Safdar Muhammad Usman, Youji Kohda, Katsuhiro Umemoto

Abstract:

Electronic market place plays an important intermediary role for connecting dealers and retail customers. The main aim of this paper is to design a value co-creation model in used-car auctions. More specifically, the study has been designed in order to describe the process of value co-creation in used-car auctions, to explore the co-created values in used-car auctions, and finally conclude the paper indicating the future research directions. Our analysis shows that economic values as well as non-economic values are co-created in used-car auctions. In addition, this paper contributes to the academic society broadening the view of value co-creation in service science.

Keywords: value co-creation, used-car auctions, non-financial values, service science

Procedia PDF Downloads 349

Authors: Tia Kristian Tajnšek, Matjaž Mazaj, Nataša Zabukovec Logar

Abstract:

Metal-organic frameworks (MOFs) with their specific properties and the possibility of tuning the structure represent excellent candidates for use in the biomedical field. Their advantage lies in large pore surfaces and volumes, as well as the possibility of using bio-friendly or bioactive constituents. So-called bioMOFs are representatives of MOFs, which are constructed from at least one biomolecule (metal, a small bioactive molecule in metal clusters and/or linker) and are intended for bio-application (usually in the field of medicine; most commonly drug delivery). When designing a bioMOF for biomedical applications, we should adhere to some guidelines for an improved toxicological profile of the material. Such as (i) choosing an endogenous/nontoxic metal, (ii) GRAS (generally recognized as safe) linker, and (iii) nontoxic solvents. Design and synthesis of bioNICS-1 (bioMOF of National Institute of Chemistry Slovenia – 1) consider all these guidelines. Zinc (Zn) was chosen as an endogenous metal with an agreeable recommended daily intake (RDI) and LD50 value, and ascorbic acid (Vitamin C) was chosen as a GRAS and active linker. With these building blocks, we have synthesized a bioNICS-1 material. The synthesis was done in ethanol using a solvothermal method. The synthesis protocol was further optimized in three separate ways. Optimization of (i) synthesis parameters to improve the yield of the synthesis, (ii) input reactant ratio and addition of specific modulators for production of larger crystals, and (iii) differing of the heating source (conventional, microwave and ultrasound) to produce nano-crystals. With optimization strategies, the synthesis yield was increased. Larger crystals were prepared for structural analysis with the use of a proper species and amount of modulator. Synthesis protocol was adjusted to different heating sources, resulting in the production of nano-crystals of bioNICS-1 material. BioNICS-1 was further activated in ethanol and structurally characterized, resolving the crystal structure of new material.

Keywords: ascorbic acid, bioMOF, MOF, optimization, synthesis, zinc ascorbate

Procedia PDF Downloads 134

Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

Abstract:

Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

Procedia PDF Downloads 270

Authors: J. W. Choi, S. Y. Cho, H. J. Lee, W. Z. Oh, S. J. Choi

Abstract:

Ionic liquids (ILs), which is alternative to conventional organic solvent, were used for extraction of Cs ions. ILs, as useful environment friendly green solvents, have been recently applied as replacement for traditional volatile organic compounds (VOCs) in liquid/liquid extraction of heavy metal ions as well as organic and inorganic species and pollutants. Thus, Ionic liquids were used for extraction of Cs ions from the liquid radioactive waste. In most cases, Cs ions present in radioactive wastes in very low concentration, approximately less than 1ppm. Therefore, unlike established extraction system the required amount of ILs as extractant is comparatively very small. This extraction method involves cation exchange mechanism in which Cs ion transfers to the organic phase and binds to one crown ether by chelation in exchange of single ILs cation, IL_cation+, transfer to the aqueous phase. In this extraction system showed solid-liquid separation in which the Ionic liquid 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonly)imide (C2mimTf2N) and the crown ether Dicyclohexano-18-crown-6 (DCH18C6) both were used here in very little amount as solvent and as extractant, respectively. 30 mM of CsNO3 was used as simulated waste solution cesium ions. Generally, in liquid-liquid extraction, the molar ratio of CE:Cs+:ILs was 1:5~10:>100, while our applied molar ratio of CE:Cs+:ILs was 1:2:1~10. The quantity of CE and Cs ions were fixed to 0.6 and 1.2 mmol, respectively. The phenomenon of precipitation showed two kinds of separation: solid-liquid separation in the ratio of 1:2:1 and 1:2:2; solid-liquid-liquid separation (3 phase) in the ratio of 1:2:5 and 1:2:10. In the last system, 3 phases were precipitate-ionic liquids-aqueous. The precipitate was verified to consist of Cs+, DCH18C6, Tf2N- based on the cation exchange mechanism. We analyzed precipitate using scanning electron microscopy with X-ray microanalysis (SEM-EDS), an elemental analyser, Fourier transform infrared spectroscopy (FT-IR) and differential scanning calorimetry (DSC). The experimental results showed an easy extraction method and confirmed the composition of solid precipitate. We also obtained information that complex formation ratio of Cs+ to DCH18C6 is 0.88:1 regardless of C2mimTf2N quantities.

Keywords: extraction, precipitation, solid-liquid seperation, ionic liquid, precipitate

Procedia PDF Downloads 412

Authors: Man-Yun Liu, Emily Chia-Yu Su

Abstract:

Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

Procedia PDF Downloads 315

Authors: Kemal Efe Eseller, Göktuğ Yazici

Abstract:

Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

Procedia PDF Downloads 83

Authors: Feleke Tsegaye

Abstract:

The work in this thesis mainly focuses on trajectory tracking of fixed wing unmanned aerial vehicle (FWUAV) by using fuzzy based sliding mode controller(FSMC) for surveillance applications. Unmanned Aerial Vehicles (UAVs) are general-purpose aircraft built to fly autonomously. This technology is applied in a variety of sectors, including the military, to improve defense, surveillance, and logistics. The model of FWUAV is complex due to its high non-linearity and coupling effect. In this thesis, input decoupling is done through extracting the dominant inputs during the design of the controller and considering the remaining inputs as uncertainty. The proper and steady flight maneuvering of UAVs under uncertain and unstable circumstances is the most critical problem for researchers studying UAVs. A FSMC technique was suggested to tackle the complexity of FWUAV systems. The trajectory tracking control algorithm primarily uses the sliding-mode (SM) variable structure control method to address the system’s control issue. In the SM control, a fuzzy logic control(FLC) algorithm is utilized in place of the discontinuous phase of the SM controller to reduce the chattering impact. In the reaching and sliding stages of SM control, Lyapunov theory is used to assure finite-time convergence. A comparison between the conventional SM controller and the suggested controller is done in relation to the chattering effect as well as tracking performance. It is evident that the chattering is effectively reduced, the suggested controller provides a quick response with a minimum steady-state error, and the controller is robust in the face of unknown disturbances. The designed control strategy is simulated with the nonlinear model of FWUAV using the MATLAB® / Simulink® environments. The simulation result shows the suggested controller operates effectively, maintains an aircraft’s stability, and will hold the aircraft’s targeted flight path despite the presence of uncertainty and disturbances.

Keywords: fixed-wing UAVs, sliding mode controller, fuzzy logic controller, chattering, coupling effect, surveillance, finite-time convergence, Lyapunov theory, flight path

Procedia PDF Downloads 51

Authors: Babak Forouraghi

Abstract:

A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

Procedia PDF Downloads 54

Authors: Sofya Komarova, Frashia Ndungu, Alessia Gavazzoli, Roberta Mineo

Abstract:

Modern society requires people to be flexible and to develop innovative solutions to unexpected situations. Creativity refers to the “interaction among aptitude, process, and the environment by which an individual or group produces a perceptible product that is both novel and useful as defined within a social context”. It allows humans to produce novel ideas, generate new solutions, and express themselves uniquely. Only a few scientific studies have examined group dynamics' influence on individuals' creativity. There exist some gaps in the research on creative thinking, such as the fact that collaborative effort frequently results in the enhanced production of new information and knowledge. Therefore, it is critical to evaluate creativity via social settings. The study aimed at exploring the group dynamics of young adults in small group settings and the influence of these dynamics on their creativity. The study included 30 participants aged 20 to 25 who were attending university after completing a bachelor's degree. The participants were divided into groups of three, in gender homogenous and heterogeneous groups. The groups’ creative task was tied to the Lego mosaic created for the Scintillae laboratory at the Reggio Children Foundation. Group dynamics were operationalized into patterns of behaviors classified into three major categories: 1) Social Interactions, 2) Play, and 3) Distraction. Data were collected through audio and video recording and observation. The qualitative data were converted into quantitative data using the observational coding system; then, they were analyzed, revealing correlations between behaviors using median points and averages. For each participant and group, the percentages of represented behavior signals were computed. The findings revealed a link between social interaction, creative thinking, and creative activities. Other findings revealed that the more intense the social interaction, the lower the amount of creativity demonstrated. This study bridges the research gap between group dynamics and creativity. The approach calls for further research on the relationship between creativity and social interaction.

Keywords: group dynamics, creative thinking, creative action, social interactions, group play

Procedia PDF Downloads 118

Authors: Sibani Bisoyi, Ute Zschieschang, Alexander Hoyer, Hagen Klauk

Abstract:

Abstract— Organic thin-film transistors (TFTs) have great potential to be used for various applications such as flexible displays or sensors. For some of these applications, the TFTs must be able to withstand temperatures in excess of 100 °C, for example to permit the integration with devices or components that require high process temperatures, or to make it possible that the devices can be subjected to the standard sterilization protocols required for biomedical applications. In this work, we have investigated how the thermal stability of low-voltage small-molecule semiconductor dinaphtho[2,3-b:2’,3’-f]thieno[3,2-b]thiophene (DNTT) TFTs is affected by the encapsulation of the TFTs and by the ambient in which the thermal stress is performed. We also studied to which extent the thermal stability of the TFTs depends on the channel length. Some of the TFTs were encapsulated with a layer of vacuum-deposited Teflon, while others were left without encapsulation, and the thermal stress was performed either in nitrogen or in air. We found that the encapsulation with Teflon has virtually no effect on the thermal stability of our TFTs. In contrast, the ambient in which the thermal stress is conducted was found to have a measurable effect, but in a surprising way: When the thermal stress is carried out in nitrogen, the mobility drops to 70% of its initial value at a temperature of 160 °C and to close to zero at 170 °C, whereas when the stress is performed in air, the mobility remains at 75% of its initial value up to a temperature of 160 °C and at 60% up to 180 °C. To understand this behavior, we studied the effect of the thermal stress on the semiconductor thin-film morphology by scanning electron microscopy. While the DNTT films remain continuous and conducting when the heating is carried out in air, the semiconductor morphology undergoes a dramatic change, including the formation of large, thick crystals of DNTT and a complete loss of percolation, when the heating is conducted in nitrogen. We also found that when the TFTs are heated to a temperature of 200 °C in air, all TFTs with a channel length greater than 50 µm are destroyed, while TFTs with a channel length of less than 50 µm survive, whereas when the TFTs are heated to the same temperature (200 °C) in nitrogen, only the TFTs with a channel smaller than 8 µm survive. This result is also linked to the thermally induced changes in the semiconductor morphology.

Keywords: organic thin-film transistors, encapsulation, thermal stability, thin-film morphology

Procedia PDF Downloads 340

Authors: Soumaya Mrabet, Taieb Ach, Imen Akkari, Amira Atig, Neirouz Ghannouchi, Koussay Ach, Elhem Ben Jazia

Abstract:

Introduction: Celiac disease (CD) is an immune-mediated small intestinal disorder that occurs in genetically susceptible people. It is significantly associated with other autoimmune disorders represented mainly by type 1 diabetes and autoimmune dysthyroidism. The aim of our study is to determine the prevalence and the type of the various autoimmune diseases associated with CD in adult patients. Material and methods: This is a retrospective study including patients diagnosed with CD, explored in Internal Medicine, Gastroenterology and Endocrinology and Diabetology Departments of the Farhat Hached University Hospital, between January 2005 and January 2016. The diagnosis of CD was confirmed by serological tests and duodenal biopsy. The screening of autoimmune diseases was based on physical examination, biological and serological tests. Results: Sixty five patients with a female predominance were included, 48women (73.8%) and 17 men (26.2%). The mean age was 31.8 years (17-75). A family history of CD or other autoimmune diseases was present in 5 and 10 patients respectively. Clinical presentation of CD was made by recurrent abdominal pain in 49 cases, diarrhea in 29 cases, bloating in 17 cases, constipation in 25 cases and vomiting in 8 cases. Autoimmune diseases associated with CD were found in 30 cases (46.1%): type 1 diabetes in 15 patients attested by the positivity of anti-GAD antibodies in 11 cases and anti-IA2 in 4 cases, Hashimoto thyroiditis in 8 cases confirmed by the positivity of anti-TPO antibodies, Addison's disease in 2 patients, Anemia of Biermer in 2 patients, autoimmune hepatitis, Systemic erythematosus lupus, Gougerot Sjögren syndrome, rheumatoid arthritis, Vitiligo and antiphospholipid syndrome in one patient each. CD was associated with more than one autoimmune disease defining multiple autoimmune syndrome in 2 female patients. The first patient had Basedow disease, Addison disease and type 1 diabetes. The second patient had systemic erythematosus lupus and Gougerot Sjögren syndrome. Conclusion: In our study autoimmune diseases were associated with CD in 46.1% of cases and were dominated by diabetes and dysthroidism. After establishing the diagnosis of CD the search of associated autoimmune diseases is necessary in order to avoid any therapeutic delay which can alter the prognosis of the patient.

Keywords: association, autoimmune thyroiditis, celiac disease, diabetes

Procedia PDF Downloads 274

Authors: Dorra Gherib

Abstract:

This article explores in depth the technological innovations by the Top Managements of banks in the Tunisian banking sector. The framework of this research is based on an amalgamation of four theories related to the decision of adopting technological innovations: The Theory of Reasoned Action (TRA), the Theory of Planned Behaviour (TPB), Technology Acceptance Model (TAM), and Diffusion of Innovation (DI). The result of our qualitative study highlights four variables which influence the attitude of the Top Managements towards the adoption of internet banking: Relative advantage, Perceived Ease of Use, compatibility and Perceived risk.

Keywords: top management, attitude, internet banking, TRA, TAM, TPB, DI

Procedia PDF Downloads 466

Authors: Fazli Idris, Jihad Mohammad

Abstract:

The study aims to determine the impact of technology and service operations flexibility, which is divided into external flexibility and internal robustness, on operations costs. A mediation model is proposed that links technology to operations costs via operation flexibility. Drawing on a sample of 475 of operations managers of various service sectors in Malaysia and South Africa, Structural Equation Modeling (SEM) was employed to test the relationship using Smart-PLS procedures. It was found that a significant relationship was established between technologies to operations costs via both operations flexibility dimensions. Theoretical and managerial implications are offered to explain the results.

Keywords: Operations flexibility, technology, costs, mediation

Procedia PDF Downloads 606

Authors: Matheus Nunes, Rafael Mendes, Taygoara Felamingo Oliveira, Antonio Brasil Junior

Abstract:

Wind tunnel experiments of horizontal axis propeller hydrokinetic turbines model were carried out, in order to determine the performance behavior for different configurations and operational range. The present experiments introduce the use of two different geometries of rear diffusers to enhance the performance of the free flow machine. The present paper reports an increase of the power coefficient about 50%-80%. It represents an important feature that has to be taken into account in the design of this kind of machine.

Keywords: diffuser-enhanced turbines, hydrokinetic turbine, wind tunnel experiments, micro hydro

Procedia PDF Downloads 266

Authors: Nadjette Belhamra, Abdelouahed Chala, Ibrahim Guasmi

Abstract:

Titanium nitride coatings have been extensively used in industry, such as in cutting tools. TiN coating were deposited by chemical vapour deposition (CVD) on carbide insert at a temperature between 850°C and 1100°C, which often exceeds the hardening treatment temperature of the metals. The objective of this work is to realize, to characterize of TiN coating and to apply it in the turning of steel 42CrMo4 under lubrification. Various experimental techniques were employed for the microstructural characterization of the coatings, e. g., X-ray diffraction (XRD), scanning electron microscope (SEM) model JOEL JSM-5900 LV, equipped with energy dispersive X-ray (EDX). The results show that TiN-coated demonstrate a good wear resistance.

Keywords: hard coating TiN, carbide inserts, machining, turning, wear

Procedia PDF Downloads 544

Authors: Brennan Lodge

Abstract:

Amidst a complex regulatory landscape, Retrieval Augmented Generation (RAG) emerges as a transformative tool for Governance Risk and Compliance (GRC) officers. This paper details the application of RAG in synthesizing Large Language Models (LLMs) with external knowledge bases, offering GRC professionals an advanced means to adapt to rapid changes in compliance requirements. While the development for standalone LLM’s (Large Language Models) is exciting, such models do have their downsides. LLM’s cannot easily expand or revise their memory, and they can’t straightforwardly provide insight into their predictions, and may produce “hallucinations.” Leveraging a pre-trained seq2seq transformer and a dense vector index of domain-specific data, this approach integrates real-time data retrieval into the generative process, enabling gap analysis and the dynamic generation of compliance and risk management content. We delve into the mechanics of RAG, focusing on its dual structure that pairs parametric knowledge contained within the transformer model with non-parametric data extracted from an updatable corpus. This hybrid model enhances decision-making through context-rich insights, drawing from the most current and relevant information, thereby enabling GRC officers to maintain a proactive compliance stance. Our methodology aligns with the latest advances in neural network fine-tuning, providing a granular, token-level application of retrieved information to inform and generate compliance narratives. By employing RAG, we exhibit a scalable solution that can adapt to novel regulatory challenges and cybersecurity threats, offering GRC officers a robust, predictive tool that augments their expertise. The granular application of RAG’s dual structure not only improves compliance and risk management protocols but also informs the development of compliance narratives with pinpoint accuracy. It underscores AI’s emerging role in strategic risk mitigation and proactive policy formation, positioning GRC officers to anticipate and navigate the complexities of regulatory evolution confidently.

Keywords: cybersecurity, gen AI, retrieval augmented generation, cybersecurity defense strategies

Procedia PDF Downloads 86

Authors: R. Horchani

Abstract:

Optical pumping technique with laser fields combined with photo-association of ultra-cold atoms leads to control on demand the vibrational and/or the rotational population of molecules. Here, we review the basic concepts and main steps should be followed, including the excitation schemes and detection techniques we use to achieve the ro-vibrational cooling of Cs2 molecules. We also discuss the extension of this technique to other molecules. In addition, we present a theoretical model used to support the experiment. These simulations can be widely used for the preparation of various experiments since they allow the optimization of several important experimental parameters.

Keywords: cold molecule, photo-association, optical pumping, vibrational and rotational cooling

Procedia PDF Downloads 294

Authors: Nihal Kartaltepe Behram, Göksel Ataman, Dila Okçu

Abstract:

With the development of foreign direct investments, the social, cultural, political and economic interactions between countries and institutions have become visible and they have become determining factors for the strategic structuring and market goals. In this context the purpose of this study is to investigate the effects of cultural distance and institutions on foreign direct investment choices in terms of location and investment model. For international establishments, the concept of culture, as well as the concept of cultural distance, is taken specifically into consideration, especially in the selection of methods for entering the market. In the researches and empirical studies conducted, a direct relationship between cultural distance and foreign direct investments is set and institutions and effective variable factors are examined at the level of defining the investment types. When the detailed calculation strategies and empirical researches and studies are taken into consideration, the most common methods for determining the direct investment model, considering the cultural distances, are full-ownership enterprises and joint ventures. Also, when all of the factors affecting the investments are taken into consideration, it was seen that the effect of institutions such as Government Intervention, Intellectual Property Rights, Corruption and Contract Enforcements is very important. Furthermore agglomeration is more intense and effective on the investment, compared to other factors. China has been selected as the target country, due to its effectiveness in world economy and its contributions to developing countries, which has commercial relationships with. Qualitative research methods are used for this study conducted, to measure the effects of determinative variable factors in the hypotheses of study, on the direct foreign investors and to evaluate the findings. In this study in-depth interview is used as a data collection method and the data analysis is made through descriptive analysis. Foreign Direct Investments are so reactive to institutions and cultural distance is identified by all interviews and analysis. On the other hand, agglomeration is the most strong determiner factor on foreign direct investors in Chinese Market. The reason of this factors, which comprise the sectorial aggregate, are not the strongest factors as agglomeration that the most important finding. We expect that this study became a beneficial guideline for developed and developing countries and local and national institutions’ strategic plans.

Keywords: China, cultural distance, Foreign Direct Investments, institutions

Procedia PDF Downloads 413

Authors: Mir Ahmad Lashteh Neshaei, Hamed Afsoos Biria, Ata Ghabraei, Mir Abdolhamid Mehrdad

Abstract:

Awareness of effective land using issues in coastal area including protection of natural ecosystems and coastal environment due to the increasing of human life along the coast is of great importance. There are numerous valuable structures and heritages which are located in defence sites and waterfront area. Marine structures such as groins, sea walls and detached breakwaters are constructed in coast to improve the coast stability against bed erosion due to changing wave and climate pattern. Marine mechanisms and interaction with the shore protection structures need to be intensively studied. Groins are one of the most prominent structures that are used in shore protection to create a safe environment for coastal area by maintaining the land against progressive coastal erosion. The main structural function of a groin is to control the long shore current and littoral sediment transport. This structure can be submerged and provide the necessary beach protection without negative environmental impact. However, for submerged structures adopted for beach protection, the shoreline response to these structures is not well understood at present. Nowadays, modelling and computer simulation are used to assess beach morphology in the vicinity of marine structures to reduce their environmental impact. The objective of this study is to predict the beach morphology in the vicinity of submerged groins and comparison with non-submerged groins with focus on a part of the coast located in Dahane sar Sefidrood, Guilan province, Iran where serious coast erosion has occurred recently. The simulations were obtained using a one-line model which can be used as a first approximation of shoreline prediction in the vicinity of groins. The results of the proposed model are compared with field measurements to determine the shape of the coast. Finally, the results of the present study show that using submerged groins can have a good efficiency to control the beach erosion without causing severe environmental impact to the coast. The important outcome from this study can be employed in optimum designing of defence sites in the coastal cities to improve their efficiency in terms of re-using the heritage lands.

Keywords: submerged structures, groin, shore protective structures, coastal cities

Procedia PDF Downloads 311

Authors: David W. Hill, Linda W. Glass, Jakob L. Vingren

Abstract:

Maximal accumulated oxygen deficit (MAOD), the gold standard measure of anaerobic capacity, is the difference between the oxygen cost of exhaustive severe intensity exercise and the accumulated oxygen consumption (O2; mL·kg–1). In theory, MAOD can be estimated as the sum of independent estimates of the phosphocreatine and glycolysis contributions, which we refer to as PCr+glycolysis. Purpose: The purpose was to test the hypothesis that PCr+glycolysis provides a valid measure of anaerobic capacity in cycling and running. Methods: The participants were 27 women (mean ± SD, age 22 ±1 y, height 165 ± 7 cm, weight 63.4 ± 9.7 kg) and 25 men (age 22 ± 1 y, height 179 ± 6 cm, weight 80.8 ± 14.8 kg). They performed two exhaustive cycling and running tests, at speeds and work rates that were tolerable for ~5 min. The rate of oxygen consumption (VO2; mL·kg–1·min–1) was measured in warmups, in the tests, and during 7 min of recovery. Fingerprick blood samples obtained after exercise were analysed to determine peak blood lactate concentration (PeakLac). The VO2 response in exercise was fitted to a model, with a fast ‘primary’ phase followed by a delayed ‘slow’ component, from which was calculated the accumulated O2 and the excess O2 attributable to the slow component. The VO2 response in recovery was fitted to a model with a fast phase and slow component, sharing a common time delay. Oxygen demand (in mL·kg–1·min–1) was determined by extrapolation from steady-state VO2 in warmups; the total oxygen cost (in mL·kg–1) was determined by multiplying this demand by time to exhaustion and adding the excess O2; then, MAOD was calculated as total oxygen cost minus accumulated O2. The phosphocreatine contribution (area under the fast phase of the post-exercise VO2) and the glycolytic contribution (converted from PeakLac) were summed to give PCr+glycolysis. There was not an interaction effect involving sex, so values for anaerobic capacity were examined using a two-way ANOVA, with repeated measures across method (PCr+glycolysis vs MAOD) and mode (cycling vs running). Results: There was a significant effect only for exercise mode. There was no difference between MAOD and PCr+glycolysis: values were 59 ± 6 mL·kg–1 and 61 ± 8 mL·kg–1 in cycling and 78 ± 7 mL·kg–1 and 75 ± 8 mL·kg–1 in running. Discussion: PCr+glycolysis is a valid measure of anaerobic capacity in cycling and running, and it is as valid for women as for men.

Keywords: alactic, anaerobic, cycling, ergometer, glycolysis, lactic, lactate, oxygen deficit, phosphocreatine, running, treadmill

Procedia PDF Downloads 129

Authors: Adriano Losso, Birgit Dämon, Stefan Mayr

Abstract:

In vascular plants, water flows from roots to leaves in a metastable state, and even a small perturbation of the system can lead a sudden transition from the liquid to the vapor phase, resulting in xylem embolism (cavitation). Xylem embolism, induced by drought stress and/or freezing stress is caused by the aspiration of gaseous bubbles into xylem conduits from adjacent gas-filled compartments through pit membrane pores (‘air seeding’). At water potentials less negative than the threshold for air seeding, the surface tension (γ) stabilizes the air-water interface and thus prevents air from passing the pit pores. This hold is probably also true for conifers, where this effect occurs at the edge of the sealed torus. Accordingly, it was experimentally demonstrated that γ influences air seeding, but information on the relevance of this effect under field conditions is missing. In this study, we analyzed seasonal changes in γ of the xylem sap in two conifers growing at the alpine timberline (Picea abies and Pinus mugo). In addition, cut branches were perfused (40 min perfusion at 0.004 MPa) with different γ solutions (i.e. distilled and degassed water, 2, 5 and 15% (v/v) ethanol-water solution corresponding to a γ of 74, 65, 55 and 45 mN m-1, respectively) and their vulnerability to drought-induced embolism analyzed via the centrifuge technique (Cavitron). In both species, xylem sap γ changed considerably (ca. 53-67 and ca. 50-68 mN m-1 in P. abies and P. cembra, respectively) over the season. Branches perfused with low γ solutions showed reduced resistance against drought-induced embolism in both species. A significant linear relationship (P < 0.001) between P12, P50 and P88 (i.e. water potential at 12, 50 and 88% of the loss of conductivity) and xylem sap γ was found. Based on this correlation, a variation in P50 between -3.10 and -3.83 MPa (P. abies) and between -3.21 and -4.11 MPa (P. mugo) over the season could be estimated. Results demonstrate that changes in γ of the xylem sap can considerably influence a tree´s resistance to drought-induced embolism. They indicate that vulnerability analyses, normally conducted at a γ near that of pure water, might often underestimate vulnerabilities under field conditions. For studied timberline conifers, seasonal changes in γ might be especially relevant in winter, when frost drought and freezing stress can lead to an excessive embolism.

Keywords: conifers, Picea abies, Pinus mugo, timberline

Procedia PDF Downloads 284

Authors: Flavia Magliacani

Abstract:

The urbanization of the last decades and its resulting urban growth entail problems both for environmental and economic sustainability. From this perspective, sustainable settlement development requires a horizontal decrease in the existing urban structure in order to enhance its greater concentration. Hence, new stratifications of the city fabric and architectural strategies ensuring high-density settlement models are possible solutions. However, although increasing housing density is necessary, it is not sufficient. Guaranteeing the quality of living is, indeed, equally essential. In order to meet this objective, many other factors come to light, namely the relationship between private and public spaces, the proximity to services, the accessibility of public transport, the local lifestyle habits, and the social needs. Therefore, how to safeguard both quality and density in human habitats? The present paper attempts to answer the previous main research question by addressing several sub-questions: Which architectural types meet the dual need for urban density and housing quality? Which project criteria should be taken into consideration by good design practices? What principles are desirable for future planning? The research will analyse different architectural responses adopted in four European cities: Paris, Lion, Rotterdam, and Amsterdam. In particular, it will develop a qualitative and comparative study of two specific architectural solutions which integrate housing density and quality living. On the one hand, the so-called 'self-contained city' model, on the other hand, the French 'Habitat Dense Individualisé' one. The structure of the paper will be as follows: the first part will develop a qualitative evaluation of some case studies, emblematic examples of the two above said architectural models. The second part will focus on the comparison among the chosen case studies. Finally, some conclusions will be drawn. The methodological approach, therefore, combines qualitative and comparative research. Parameters will be defined in order to highlight potential and criticality of each model in light of an interdisciplinary view. In conclusion, the present paper aims at shading light on design approaches which ensure a right balance between density and quality of the urban living in contemporary European cities.

Keywords: density, future design, housing quality, human habitat

Procedia PDF Downloads 98

Authors: Kamila Dus-Szachniewicz, Artur Bednarkiewicz, Katarzyna Gdesz-Birula, Slawomir Drobczynski

Abstract:

In modern oncology hyperthermia (HT) is defined as a controlled tumor heating. HT treatment temperatures range between 40–48 °C and can selectively damage heat-sensitive cancer cells or limit their further growth, usually with minimal injury to healthy tissues. Despite many advantages, conventional whole-body and regional hyperthermia have clinically relevant side effects, including cardiac and vascular disorders. Additionally, the lack of accessibility of deep-seated tumor sites and impaired targeting micrometastases renders HT less effective. It is believed that above disadvantages can significantly overcome by the application of biofunctionalized microparticles, which can specifically target tumor sites and become activated by an external stimulus to provide a sufficient cellular response. In our research, the unique optical tweezers system have enabled capturing the silica microparticles, primary cells and tumor spheroids in highly controllable and reproducible environment to study the impact of localized heat stimulation on normal and pathological cell and within multicellular tumor spheroid. High throughput spheroid model was introduced to better mimic the response to HT treatment on tumors in vivo. Additionally, application of local heating of tumor spheroids was performed in strictly controlled conditions resembling tumor microenvironment (temperature, pH, hypoxia, etc.), in response to localized and nonhomogeneous hyperthermia in the extracellular matrix, which promotes tumor progression and metastatic spread. The lack of precise control over these well- defined parameters in basic research leads to discrepancies in the response of tumor cells to the new treatment strategy in preclinical animal testing. The developed approach enables also sorting out subclasses of cells, which exhibit partial or total resistance to therapy, in order to understand fundamental aspects of the resistance shown by given tumor cells in response to given therapy mode and conditions. This work was funded by the National Science Centre (NCN, Poland) under grant no. UMO-2017/27/B/ST7/01255.

Keywords: cancer spheroids, hyperthermia, microparticles, optical tweezers

Procedia PDF Downloads 128

Authors: Jeena R. S., Sukesh Kumar A.

Abstract:

Stroke is one of the major reasons of adult disability and morbidity in many of the developing countries like India. Early diagnosis of stroke is essential for timely prevention and cure. Various conventional statistical methods and computational intelligent models have been developed for predicting the risk and outcome of stroke. This research work focuses on a multilevel approach for predicting the occurrence of stroke based on various risk factors and invasive techniques like retinal imaging. This risk prediction model can aid in clinical decision making and help patients to have an improved and reliable risk prediction.

Keywords: prediction, retinal imaging, risk factors, stroke

Procedia PDF Downloads 294