Search results for: identification of emotions

Authors: Andreas Aceranti, Simonetta Vernocchi, Marco Colorato, Daniel Zaccariello

Abstract:

Our study explores the usefulness of implementing facial expression recognition capabilities and using the Facial Action Coding System (FACS) in contexts where the other person is wearing a mask. In the communication process, the subjects use a plurality of distinct and autonomous reporting systems. Among them, the system of mimicking facial movements is worthy of attention. Basic emotion theorists have identified the existence of specific and universal patterns of facial expressions related to seven basic emotions -anger, disgust, contempt, fear, sadness, surprise, and happiness- that would distinguish one emotion from another. However, due to the COVID-19 pandemic, we have come up against the problem of having the lower half of the face covered and, therefore, not investigable due to the masks. Facial-emotional behavior is a good starting point for understanding: (1) the affective state (such as emotions), (2) cognitive activity (perplexity, concentration, boredom), (3) temperament and personality traits (hostility, sociability, shyness), (4) psychopathology (such as diagnostic information relevant to depression, mania, schizophrenia, and less severe disorders), (5) psychopathological processes that occur during social interactions patient and analyst. There are numerous methods to measure facial movements resulting from the action of muscles, see for example, the measurement of visible facial actions using coding systems (non-intrusive systems that require the presence of an observer who encodes and categorizes behaviors) and the measurement of electrical "discharges" of contracting muscles (facial electromyography; EMG). However, the measuring system invented by Ekman and Friesen (2002) - "Facial Action Coding System - FACS" is the most comprehensive, complete, and versatile. Our study, carried out on about 1,500 subjects over three years of work, allowed us to highlight how the movements of the hands and upper part of the face change depending on whether the subject wears a mask or not. We have been able to identify specific alterations to the subjects’ hand movement patterns and their upper face expressions while wearing masks compared to when not wearing them. We believe that finding correlations between how body language changes when our facial expressions are impaired can provide a better understanding of the link between the face and body non-verbal language.

Keywords: facial action coding system, COVID-19, masks, facial analysis

Procedia PDF Downloads 75

Authors: Maria Hopkins, Sarah Koch, Fred Biasini

Abstract:

Autism is lifelong disorder that affects one out of every 110 Americans. The deficits that accompany Autism Spectrum Disorders (ASD), such as abnormal behaviors and social incompetence, often make it extremely difficult for these individuals to gain functional independence from caregivers. These long-term implications necessitate an immediate effort to improve social skills among children with an ASD. Any technology that could teach individuals with ASD necessary social skills would not only be invaluable for the individuals affected, but could also effect a massive saving to society in treatment programs. The overall purpose of the first study was to develop, implement, and evaluate an avatar tutor for social skills training in children with ASD. “Face Say” was developed as a colorful computer program that contains several different activities designed to teach children specific social skills, such as eye gaze, joint attention, and facial recognition. The children with ASD were asked to attend to FaceSay or a control painting computer game for six weeks. Children with ASD who received the training had an increase in emotion recognition, F(1, 48) = 23.04, p < 0.001 (adjusted Ms 8.70 and 6.79, respectively) compared to the control group. In addition, children who received the FaceSay training had higher post-test scored in facial recognition, F(1, 48) = 5.09, p < 0.05 (adjusted Ms: 38.11 and 33.37, respectively) compared to controls. The findings provide information about the benefits of computer-based training for children with ASD. Recent research suggests the value of also using socially assistive robots with children who have an ASD. Researchers investigating robots as tools for therapy in ASD have reported increased engagement, increased levels of attention, and novel social behaviors when robots are part of the social interaction. The overall goal of the second study was to develop a social robot designed to teach children specific social skills such as emotion recognition. The robot is approachable, with both an animal-like appearance and features of a human face (i.e., eyes, eyebrows, mouth). The feasibility of the robot is being investigated in children ages 7-12 to explore whether the social robot is capable of forming different facial expressions to accurately display emotions similar to those observed in the human face. The findings of this study will be used to create a potentially effective and cost efficient therapy for improving the cognitive-emotional skills of children with autism. Implications and study findings using the robot as an intervention tool will be discussed.

Keywords: autism, intervention, technology, emotions

Procedia PDF Downloads 380

Authors: Muneeb Ullah, Daishihan, Xiadong Young

Abstract:

Deep learning plays a crucial role in identifying COVID-19 and preventing its spread. To improve the accuracy of COVID-19 diagnoses, it is important to have access to a sufficient number of training images of CXRs (chest X-rays) depicting the disease. However, there is currently a shortage of such images. To address this issue, this paper introduces COVID-19 GAN, a model that uses generative adversarial networks (GANs) to generate realistic CXR images of COVID-19, which can be used to train identification models. Initially, a generator model is created that uses digressive channels to generate images of CXR scans for COVID-19. To differentiate between real and fake disease images, an efficient discriminator is developed by combining the dense connectivity strategy and instance normalization. This approach makes use of their feature extraction capabilities on CXR hazy areas. Lastly, the deep regret gradient penalty technique is utilized to ensure stable training of the model. With the use of 4,062 grape leaf disease images, the Leaf GAN model successfully produces 8,124 COVID-19 CXR images. The COVID-19 GAN model produces COVID-19 CXR images that outperform DCGAN and WGAN in terms of the Fréchet inception distance. Experimental findings suggest that the COVID-19 GAN-generated CXR images possess noticeable haziness, offering a promising approach to address the limited training data available for COVID-19 model training. When the dataset was expanded, CNN-based classification models outperformed other models, yielding higher accuracy rates than those of the initial dataset and other augmentation techniques. Among these models, ImagNet exhibited the best recognition accuracy of 99.70% on the testing set. These findings suggest that the proposed augmentation method is a solution to address overfitting issues in disease identification and can enhance identification accuracy effectively.

Keywords: classification, deep learning, medical images, CXR, GAN.

Procedia PDF Downloads 95

Authors: Dipak Sonawane, Sudarshan Daga, Somesh Gupta

Abstract:

Quantitative risk assessment (QRA) is a very precise and consistent approach to defining the likelihood, consequence and severity of a major incident/accident. A variety of hazardous cargoes in bulk, such as hydrocarbons and flammable/toxic chemicals, are handled at various ports. It is well known that most of the operations are hazardous, having the potential of damaging property, causing injury/loss of life and, in some cases, the threat of environmental damage. In order to ensure adequate safety towards life, environment and property, the application of scientific methods such as QRA is inevitable. By means of these methods, comprehensive hazard identification, risk assessment and appropriate implementation of Risk Control measures can be carried out. In this paper, the authors, based on their extensive experience in Risk Analysis for ports and harbors, have exhibited how QRA can be used in practice to minimize and contain risk to tolerable levels. A specific case involving the operation for unloading of hydrocarbon at a port is presented. The exercise provides confidence that the method of QRA, as proposed by the authors, can be used appropriately for the identification of hazards and risk assessment of Ports and Terminals.

Keywords: quantitative risk assessment, hazard assessment, consequence analysis, individual risk, societal risk

Procedia PDF Downloads 79

Authors: David Ugalde, Arturo Castillo, Leopoldo Breschi

Abstract:

The Tuned Mass Dampers (TMDs) are an effective system for mitigating vibrations in building structures. These dampers have traditionally focused on the protection of high-rise buildings against earthquakes and wind loads. The Camara Chilena de la Construction (CChC) building, built in 2018 in Santiago, Chile, is a 21-story RC wall building equipped with a 150-ton TMD and instrumented with six permanent accelerometers, offering an opportunity to monitor the dynamic response of this damped structure. This paper presents the system identification of the CChC building using power spectral density plots of ambient vibration and two seismic events (5.5 Mw and 6.7 Mw). Linear models of the building with and without the TMD are used to compute the theoretical natural periods through modal analysis and simulate the response of the building through response history analysis. Results show that natural periods obtained from both ambient vibrations and earthquake records are quite similar to the theoretical periods given by the modal analysis of the building model. Some of the experimental periods are noticeable by simple inspection of the earthquake records. The accelerometers in the first story better captured the modes related to the building podium while the upper accelerometers clearly captured the modes related to the tower. The earthquake simulation showed smaller accelerations in the model with TMD that are similar to that measured by the accelerometers. It is concluded that the system identification through power spectral density shows consistency with the expected dynamic properties. The structural health monitoring of the CChC building confirms the advantages of seismic protection technologies such as TMDs in seismic prone areas.

Keywords: system identification, tuned mass damper, wall buildings, seismic protection

Procedia PDF Downloads 123

Authors: Karthick Gopalan, Selvamohan Thankiah

Abstract:

Biosurfactants are lipid compounds produced by microbes, which are amphipathic molecules consisting of hydrophophic and hydrophilic domains. In the present investigation, ten bacterial strains were isolated from petroleum oil contaminated sites near petrol bunk. Oil collapsing test, haemolytic activity were used as a criteria for primary isolation of biosurfactant producing bacteria. In this study, all the bacterial strains gave positive results. Among the ten strains, two were observed as good biosurfactant producers, they utilize the diesel as a sole carbon source. Optimization of biosurfactant producing bacteria isolated from petroleum oil contaminated sites was carried out using different parameters such as, temperature (20ºC, 25ºC, 30ºC, 37ºC and 45ºC), pH (5,6,7,8 & 9) and nitrogen sources (ammonium chloride, ammonium carbonate and sodium nitrate). Biosurfactants produced by bacteria were extracted, dried and quantified. As a result of optimization of parameters the suitable values for the production of more amount of biosurfactant by the isolated bacterial species was observed as 30ºC (0.543 gm/lt) in the pH 7 (0.537 gm/lt) with ammonium nitrate (0.431 gm/lt) as sole carbon source.

Keywords: isolation and identification, biosurfactant, microorganism, bioaugmentation

Procedia PDF Downloads 346

Authors: John Onolame Unuofin, Uchechukuw U. Nwodo, Anthony I. Okoh

Abstract:

Laccase is constantly gaining status as important biocatalyst in biotechnology. The illimitable potential of its industrial applications and the corresponding aggressive need for phenomenal volumes of extracellularly secreted laccases have called for its interminable production from sources which are able to meet this demand within a relatively short period of time, preferably bacteria. In response to this call, this study was designed to source for laccase-producing bacteria from different environmental matrices. Three sampling environments were chosen such as wastewater treatment plants, University of Fort Hare vicinity and the Hogback woodland, all within the Eastern Cape, South Africa. Samples such as effluents, sediments, leaf litters, degrading wood and rock scrapings were selectively enriched with some model aromatic compounds and were further screened qualitatively and quantitatively on five phenolic substrates ABTS (2,2’-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid), Guaiacol, 1-Naphthol, Potassium Ferric Cyanide and Syringaldazine). Basis for selection was their ability to elicit a colour change on at least three of the above mentioned agar based assay substrates. The choice isolates were further identified based on 16S rRNA molecular identification techniques. 33 isolates were screened out of the 40 representative distinct colonies during the qualitative plate screens, while quantitative screens selected out 11 bacterial isolates. They were, based on molecular identification, desginated as members of the genera Pseudomonas, Stenotrophomonas and Citrobacter of the gammaproteobacteria and Bordetalla and Achromobacter of the betaproteobacteria respectively. We therefore conclude based on our outcomes that we may have isolated efficient laccase-producing bacteria, which might be of beneficial significance in catalysis and biotechnology.

Keywords: beta proteobacteria, catalysis, gammaproteobacteria, laccase

Procedia PDF Downloads 173

Authors: Chao Yu, Qing-Guo Wang, Dan Zhang

Abstract:

The outlier detection problem for dynamic systems is formulated as a matrix decomposition problem with low-rank, sparse matrices and further recast as a semidefinite programming (SDP) problem. A fast algorithm is presented to solve the resulting problem while keeping the solution matrix structure and it can greatly reduce the computational cost over the standard interior-point method. The computational burden is further reduced by proper construction of subsets of the raw data without violating low rank property of the involved matrix. The proposed method can make exact detection of outliers in case of no or little noise in output observations. In case of significant noise, a novel approach based on under-sampling with averaging is developed to denoise while retaining the saliency of outliers and so-filtered data enables successful outlier detection with the proposed method while the existing filtering methods fail. Use of recovered “clean” data from the proposed method can give much better parameter estimation compared with that based on the raw data.

Keywords: outlier detection, system identification, matrix decomposition, low-rank matrix, sparsity, semidefinite programming, interior-point methods, denoising

Procedia PDF Downloads 305

Authors: Ebrahim H. Kapeel, Ehab Safwat, Hossam Hendy, Ahmed M. Kamel, Yehia Z. Elhalwagy

Abstract:

Motivated by the problem of the availability of high-fidelity flight simulation models for small unmanned aerial vehicles (UAVs). This paper focuses on the geometric-mass inertia modeling and the actuation system modeling for the small fixed-wing UAVs. The UAV geometric parameters for the body, wing, horizontal and vertical tail are physically measured. Pendulum experiment with high-grade sensors and data analysis using MATLAB is used to estimate the airplane moment of inertia (MOI) model. Finally, UAV’s actuation system is modeled by estimating each servo transfer function by using the system identification, which uses experimental measurement for input and output angles through using field-programmable gate array (FPGA). Experimental results for the designed models are given to illustrate the effectiveness of the methodology. It also gives a very promising result to finalize the open-loop flight simulation model through modeling the propulsion system and the aerodynamic system.

Keywords: unmanned aerial vehicle, geometric-mass inertia model, system identification, Simulink

Procedia PDF Downloads 177

Authors: Reem Alajmi, Hind Al Harbi, Tahany Ayaad, Zainab Al Musawi

Abstract:

Hard ticks Hyalomma spp. (family: Ixodidae) are obligate ectoparasite in their all life stages on some domestic animals mainly camels and cattle. Ticks may lead to many economic and public health problems because of their blood feeding behavior. Also, they act as vectors for many bacterial, viral and protozoan agents which may cause serious diseases such as tick-born encephalitis, Rocky-mountain spotted fever, Q-fever and Lyme disease which can affect human and/or animals. In the present study, molecular identification of ticks that attack camels in Riyadh region, Saudi Arabia based on the partial sequence of mitochondrial 16s rRNA gene was applied. Also, the present study aims to detect natural infections of collected camel ticks with Rickessia spp. and Borelia spp. using PCR/hybridization of Citrate synthase encoding gene present in bacterial cells. Hard ticks infesting camels were collected from different camels located in a farm in Riyadh region, Saudi Arabia. Results of the present study showed that the collected specimens belong to two species: Hyalomma dromedari represent 99% of the identified specimens and Hyalomma marginatum which account for 1 % of identified ticks. The molecular identification was made through blasting the obtained sequence of this study with sequences already present and identified in GeneBank. All obtained sequences of H. dromedarii specimens showed 97-100% identity with the same gene sequence of the same species (Accession # L34306.1) which was used as a reference. Meanwhile, no intraspecific variations of H. marginatum mesured because only one specimen was collected. Results also had shown that the intraspecific variability between individuals of H. dromedarii obtained in 92 % of samples ranging from 0.2- 6.6%, while the remaining 7 % of the total samples of H. dromedarii showed about 10.3 % individual differences. However, the interspecific variability between H. dromedarii and H. marginatum was approximately 18.3 %. On the other hand, by using the technique of PCR/hybridization, we could detect natural infection of camel ticks with Rickettsia spp. and Borrelia spp. Results revealed the natural presence of both bacteria in collected ticks. Rickettsial spp. infection present in 29% of collected ticks, while 35% of collected specimen were infected with Borrelia spp. The valuable results obtained from the present study are a new record for the molecular identification of camel ticks in Riyadh, Saudi Arabia and their natural infection with both Rickettsia spp. and Borrelia spp. These results may help scientists to provide a good and direct control strategy of ticks in order to protect one of the most important economic animals which are camels. Also results of this project spotlight on the disease that might be transmitted by ticks to put out a direct protective plan to prevent spreading of these dangerous agents. Further molecular studies are needed to confirm the results of the present study by using other mitochondrial and nuclear genes for tick identification.

Keywords: Camel ticks, Rickessia spp. , Borelia spp. , mitochondrial 16s rRNA gene

Procedia PDF Downloads 276

Authors: Farzaneh Noori

Abstract:

Entrepreneurs face different sort of difficulties especially with customers, organizations and employees. Emotional intelligence which is the ability to understand and control the emotions is an important factor to help entrepreneurs end up challenges to the result they prefer. Thus, it is assumed that entrepreneurs especially those who have passed the first challenging years of starting a new business, have high emotional intelligence. In this study the Iranian established entrepreneurs have been surveyed. According to Iran Gem 2014 report the percentage of established entrepreneur in Iran is 10.92%. So by using Cochran sample formula (1%) 96 Iranian established entrepreneurs have been selected and Emotional intelligence appraisal questionnaire distributed to them. The SPSS19 result shows high emotional intelligence in Iranian established entrepreneurs.

Keywords: emotional intelligence, emotional intelligence appraisal questionnaire, entrepreneurs, Iran

Procedia PDF Downloads 441

Authors: Arun Kharate, Sarata Kumar Sahu, Susen Kumar Panda, Niranjan Sahoo, H. K. Panda

Abstract:

In the present study, an attempt has been made for isolation and identification of feline panleukopaenia virus (FPLV) from wild felids of Nandankanan zoo, Odisha, India, along with prevalence study of FPLV. Fecal samples collected from wild felids (26 tigers, 22 lions, 5 leopards, 3 hyenas, 1 jaguar, 2 foxes and 1 wild cat) were subjected to hemagglutinnation test and fluorescent antibody test. In hemagglutinnation test 13 (50%) samples from tiger, 14 (63.63%) samples from lions, 1 (20%) sample from leopards, 1 (50%) from fox, 3 (100%) samples from hyenas and 1 (100%) sample from wild cat were positive. On fluorescent antibody test (FAT), 15 (57.69%) samples from tiger, 18 (81.81%) from lions, 2 (40%) from leopards, 1 (50%) from fox, 3 (100%) from hyenas and 1 (100%) from wild cat were positive. FPLV was isolated using MDBK cell line and preliminary characterization was done on the basis of characteristic cytopathic effect. The virus samples were quantified through titration in MDBK cells. Serological confirmation of FPLV isolates was carried out by HI test, micro-SNT and indirect-ELISA. Physico-chemical characters like pH and temperature resistance along molecular identification using specific FPLV primers was carried out. Seroprevalence study of 36 serum samples employing HI test, micro SNT and indirect-ELISA revealed prevalence of 38.8, 44.4 and 72.2% respectively. During study period an adult tigress and a tiger cub died suspected of feline panleukopenia. The necropsy findings in both animals showed hemorrhagic gastroenteritis. The cytological examination revealed presence of intranuclear inclusion bodies in the intestinal epithelial cells. Spleen, mesenteric lymph node and intestine were positive for feline panleukopenia by FAT. The investigation revealed that feline panleukopenia was prevalent in wild felines of Nandankanan zoo.

Keywords: Feline panleukopenia, fluorescent antibody test, hemagglutination test, indirect-ELISA, Nandankanan zoo

Procedia PDF Downloads 325

Authors: Marianna Ciaccia, Gennaro Agrimi, Isabella Pisano, Maurizio Bettiga, Silvia Rapacioli, Giulia Mensa, Monica Marzagalli

Abstract:

Objective: Untargeted metabolomic analysis of extracellular metabolites is a powerful approach that focuses on comprehensively profiling in the extracellular space. In this study, we applied extracellular metabolomic analysis to investigate the metabolism of two probiotic microorganisms with health benefits that extend far beyond the digestive tract and the immune system. Methods: Analytical techniques employed in extracellular metabolomic analysis encompass various technologies, including mass spectrometry (MS), which enables the identification of metabolites present in the fermentation media, as well as the comparison of metabolic profiles under different experimental conditions. Multivariate statistical analysis techniques like principal component analysis (PCA) or partial least squares-discriminant analysis (PLS-DA) play a crucial role in uncovering metabolic signatures and understanding the dynamics of metabolic networks. Results: Different types of supernatants from fermentation processes, such as dairy-free, not dairy-free media and media with no cells or pasteurized, were subjected to metabolite profiling, which contained a complex mixture of metabolites, including substrates, intermediates, and end-products. This profiling provided insights into the metabolic activity of the microorganisms. The integration of advanced software tools has facilitated the identification and characterization of metabolites in different fermentation conditions and microorganism strains. Conclusions: In conclusion, untargeted extracellular metabolomic analysis, combined with software tools, allowed the study of the metabolites consumed and produced during the fermentation processes of probiotic microorganisms. Ongoing advancements in data analysis methods will further enhance the application of extracellular metabolomic analysis in fermentation research, leading to improved bioproduction and the advancement of sustainable manufacturing processes.

Keywords: biotechnology, metabolomics, lactic bacteria, probiotics, postbiotics

Procedia PDF Downloads 69

Authors: Peter Fedichev

Abstract:

We studied fundamental aspects of aging to develop a mathematical model of gene regulatory network. We show that aging manifests itself as an inherent instability of gene network leading to exponential accumulation of regulatory errors with age. To validate our approach we studied age-dependent omic data such as transcriptomes, metabolomes etc. of different model organisms and humans. We build a computational platform based on our model to identify the targets and biomarkers of aging to design new drugs against aging and age-related diseases. As biomarkers of aging, we choose the rate of aging and the biological age since they completely determine the state of the organism. Since rate of aging rapidly changes in response to an external stress, this kind of biomarker can be useful as a tool for quantitative efficacy assessment of drugs, their combinations, dose optimization, chronic toxicity estimate, personalized therapies selection, clinical endpoints achievement (within clinical research), and death risk assessments. According to our model, we propose a method for targets identification for further interventions against aging and age-related diseases. Being a biotech company, we offer a complete pipeline to develop an anti-aging drug-candidate.

Keywords: aging, longevity, biomarkers, senescence

Procedia PDF Downloads 272

Authors: Luis Enrique Bautista-Hinojosa, Luis A. Herrera, Cristian Arriaga-Canon

Abstract:

Text should be written in the third person. Please avoid using "I" “my” or the pronoun "one". It is best to say "It is believed..." rather than "I believe..." or "One believes...".

Keywords: transcriptomics, co-expression, cancer, biomarkers

Procedia PDF Downloads 71

Authors: Fuyuan Ma, Yuhan Wang, Junhe Zhang, Ying Wang

Abstract:

Identifying the sources of information dissemination is a pivotal task in the study of collective behaviors in networks, enabling us to discern and intercept the critical pathways through which information propagates from its origins. This allows for the control of the information’s dissemination impact in its early stages. Numerous methods for source detection rely on pre-existing, underlying propagation models as prior knowledge. Current models that eschew prior knowledge attempt to harness label propagation algorithms to model the statistical characteristics of propagation states or employ Graph Neural Networks (GNNs) for deep reverse modeling of the diffusion process. These approaches are either deficient in modeling the propagation patterns of information or are constrained by the over-smoothing problem inherent in GNNs, which limits the stacking of sufficient model depth to excavate global propagation patterns. Consequently, we introduce the ODESI model. Initially, the model employs a label propagation algorithm to delineate the distribution density of infected states within a graph structure and extends the representation of infected states from integers to state vectors, which serve as the initial states of nodes. Subsequently, the model constructs a deep architecture based on GNNs-coupled Ordinary Differential Equations (ODEs) to model the global propagation patterns of continuous propagation processes. Addressing the challenges associated with solving ODEs on graphs, we approximate the analytical solutions to reduce computational costs. Finally, we conduct simulation experiments on two real-world social network datasets, and the results affirm the efficacy of our proposed ODESI model in source identification tasks.

Keywords: source identification, ordinary differential equations, label propagation, complex networks

Procedia PDF Downloads 18

Authors: Zarine Avetisyan

Abstract:

Concepts are part and parcel of everyday text and talk. Their ubiquity predetermines the topicality of the given research which aims at the semantic decomposition of concepts in general and the concept of joy in particular, as well as the study of lexico-semantic variants as means of realization of a certain concept in different “semantic settings”, namely in a certain context. To achieve the stated aim, the given research departs from the methods of componential and contextual analysis, studying lexico-semantic variants /LSVs/ of the concept of joy and the semantic signs embedded in those LSVs, such as the semantic sign of intensity, supporting emotions, etc. in the context of Modern English fiction.

Keywords: concept, context, lexico-semantic variant, semantic sign

Procedia PDF Downloads 352

Authors: Pingping Lin, Xudong Luo

Abstract:

Natural language often conveys emotions of speakers. Therefore, sentiment analysis on what people say is prevalent in the field of natural language process and has great application value in many practical problems. Thus, to help people understand its application value, in this paper, we survey various applications of sentiment analysis, including the ones in online business and offline business as well as other types of its applications. In particular, we give some application examples in intelligent customer service systems in China. Besides, we compare the applications of sentiment analysis on Twitter, Weibo, Taobao and Facebook, and discuss some challenges. Finally, we point out the challenges faced in the applications of sentiment analysis and the work that is worth being studied in the future.

Keywords: application, natural language processing, online comments, sentiment analysis

Procedia PDF Downloads 257

Authors: Yu Chen Su

Abstract:

Introduction: Gestational diabetes mellitus (GDM) refers to impaired glucose tolerance in pregnant women, impacting both the mother and newborn with short and long-term effects. It increases risks of preeclampsia, hypertension, type 2 diabetes, cesarean section, and preterm birth. GDM is associated with fetal macrosomia, shoulder dystocia, neonatal hypoglycemia, and future type 2 diabetes risk. A study on 6,421 pregnant women found 12% experienced high stress, linked to maladaptive coping and depressive emotions. Women with high-risk pregnancies may experience greater stress and depression. Research suggests GDM increases depression prevalence. A study on 632 Hispanic women with GDM showed severe stress and depression tendencies. Involving 95 women with GDM, 33.4% exhibited depression symptoms. Another study compared 180 GDM women to 186 with normal glucose levels, revealing higher depression levels in GDM women. They found GDM women were 1.85 times more likely to receive antidepressants during pregnancy and 1.69 times more likely to experience postpartum depression. Maternal stress and depressive symptoms during pregnancy are significant factors. Early identification by healthcare professionals can greatly benefit GDM women, their infants, and their families. Objectives: The purpose of this study was to investigate the association between gestational diabetes mellitus (GDM) and the risk of depression. Methods: This study reviewed and analyzed relevant literature on gestational diabetes mellitus (GDM) and depression in 6,876 patients. The literature search followed PRISMA guidelines and included databases like Embase, PubMed, MEDLINE, CINAHL, and Cochrane Library. Prospective or retrospective studies with relevant risk ratios and estimates were included, using a random-effects model for the analysis of depression risk correlation. Studies without depression data or relevant risks were excluded. The search period extended until October 2022. Results: Systematic review of 7 studies (6,876 participants) found a significant association (OR = 8.77, CI: 7.98-9.64, p < 0.05) between gestational diabetes mellitus (GDM) and higher depression risk compared to healthy pregnant women. Conclusions: Pregnancy is a significant life transition involving physiological, psychological, and social changes. Gestational diabetes poses challenges to women's physical and mental well-being. Sensitive healthcare professionals identifying issues early can greatly benefit women, babies, and the family.

Keywords: gestational diabetes, depression, systematic review, neta-analysis

Procedia PDF Downloads 72

Authors: Payling Harn

Abstract:

LEGO® SERIOUS PLAY® is a kind of facilitated workshop of thinking and problem-solving approach. Participants built symbolic and metaphorical brick models in response to tasks given by the facilitator and presented these models to other participants. LEGO® SERIOUS PLAY® applied the positive psychological mechanism of Flow and positive emotions to help participants perceiving self-experience and unknown fact and increasing the happiness of life by building bricks and narrating story. At present, LEGO® SERIOUS PLAY® is often utilized for facilitating professional identity and strategy development to assist workers in career development. The researcher desires to apply LEGO® SERIOUS PLAY® to the career courses of college students in order to promote their career ability. This study aimed to use the facilitative method of LEGO® SERIOUS PLAY® to develop the career courses of college students, then explore the effects of Taiwanese college students' positive and negative emotions, career adaptabilities, and career sense of hope by LEGO® SERIOUS PLAY® career courses. The researcher regarded strength as the core concept and use the facilitative mode of LEGO® SERIOUS PLAY® to develop the 8 weeks’ career courses, which including ‘emotion of college life’ ‘career highlights’, ‘career strengths’, ‘professional identity’, ‘business model’, ‘career coping’, ‘strength guiding principles’, ‘career visions’,’ career hope’, etc. The researcher will adopt problem-oriented teaching method to give tasks which according to the weekly theme, use the facilitative mode of LEGO® SERIOUS PLAY® to guide participants to respond tasks by building bricks. Then participants will conduct group discussions, reports, and writing reflection journals weekly. Participants will be 24 second-grade college students. They will attend LEGO® SERIOUS PLAY® career courses for 2 hours a week. The researcher used’ ‘Career Adaptability Scale’ and ‘Career Hope Scale’ to conduct pre-test and post-test. The time points of implementation testing will be one week before courses starting, one day after courses ending respectively. Then the researcher will adopt repeated measures one-way ANOVA for analyzing data. The results revealed that the participants significantly presented immediate positive effect in career adaptability and career hope. The researcher hopes to construct the mode of LEGO® SERIOUS PLAY® career courses by this study and to make a substantial contribution to the future career teaching and researches of LEGO® SERIOUS PLAY®.

Keywords: LEGO® SERIOUS PLAY®, career courses, strength, positive and negative affect, career hope

Procedia PDF Downloads 251

Authors: Satender Saraswat, Dharmendra Prasad Singh, Rajesh Kumar Verma, Swati Sarswat

Abstract:

Background and Purpose: The predominant cause of candidiasis was Candida albicans which has shifted towards non-Candida albicans Candida (NCAC) (Candida species other than the C. albicans). NCAC, earlier considered non-pathogenic or minimally virulent, are now considered a primary cause of morbidity and mortality in immunocompromised. With the NCAC spp. gaining weightage in the clinical cases, this study was conducted to determine the prevalence of NCAC spp. in different clinical specimens and to assess a few of their virulence factors. Material and Methods: Routine samples for bacterial culture and sensitivity, showing colony characteristics like Candida on Blood Agar and microscopic features resembling Candida spp. were processed further. Candida isolates were tested for chlamydospore formation, biochemical tests including sugar fermentation and sugar assimilation tests, and growth at 42oC, colony colour on HiCrome™ Candida Differential Agar, HiCandida Identification Kit and VITEK-2 Compact. Virulence factors like adherence to buccal epithelial cells (ABEC), biofilm formation, hemolytic activity, and production of coagulase enzyme were also tested. Results: Mean age of the patients was 38.46 with a male-female ratio of 1.36:1. 137 Candida isolates were recovered. 45.3% isolates were isolated from urine, 19.7% from vaginal swabs and 13.9% from oropharyngeal swabs. 55 (40.1%) isolates of C. albicans and 82 (59.9%) of NCAC spp. were identified, with C. tropicalis (23.4%) in NCAC. C. albicans (3; 50%) was the commonest species in cases of candidemia. Haemolysin production (85.5%) and ABEC (78.2%) were the major virulence factors in C. albicans. C. tropicalis (59.4%) and C. dubliniensis (50%) showed maximum ABEC. Biofilm forming capacity was higher in C. tropicalis (78.1%) than C. albicans (67%). Conclusion: This study suggests varied prevalence and virulence based on geographical locations, even within a subcontinent. It clearly demarcates the emergence of NCAC and their predominance in different body fluids. Identification of Candida to species level should become a routine in all the laboratories.

Keywords: ABEC, NCAC, non-Candida albicans Candida, Vitek-2TM compact

Procedia PDF Downloads 129

Authors: P. Maheshwari, M. Brindavan

Abstract:

The present research aimed to study the level of socio-emotional skills and perceived self-efficacy of children with learning disability. The study further investigated the relationship between the levels of socio-emotional skills, perceived self-efficacy and academic achievement of children with learning disability. The sample comprised of 40 children with learning disability as their primary condition, belonging to middle or upper middle class, living with both the parents, residing in Mumbai. Purposive or Judgmental and snowball sampling technique was used to select the sample for the study. Proformas in the form of questionnaires were used to obtain the background information of the children with learning disability. A self-constructed Child’s Perceived Self-Efficacy Assessment Scale and Child’s Social and Emotional Skills Assessment Scale was used to measure the level of child’s perceived self-efficacy and their level of social and emotional skill respectively. Academic scores of the child were collected from the child’s parents or teachers and were converted into a percentage. The data was analyzed quantitatively using SPSS. Spearman rho or Pearson Product Moment correlation was used to ascertain the multiple relationships between child’s perceived self-efficacy, child’s social and emotional skills and child’s academic achievement. The findings revealed majority (27) of the children with learning disability perceived themselves having above average level of social and emotional skills while 13 out of 40 perceived their level of social and emotional skills at an average level. Domain wise analyses revealed that, in the domain of self- management (26) and relationship skills (22) more number of the children perceived themselves as having average or below average level of social and emotional skills indicating that they perceived themselves as having average or below average skills in regulating their emotions, thoughts, and behaviors effectively in different situations, establishing and maintaining healthy and rewarding relationships with diverse groups and individuals. With regard to perceived self-efficacy, the majority of the children with learning disability perceived themselves as having above average level of self-efficacy. Looking at the data domain wise it was found that, in the domains of self-regulated learning and emotional self-efficacy, 50% of the children perceived themselves at average or below average level, indicating that they perceived themselves as average on competencies like organizing academic activities, structuring environment to make it conducive for learning, expressing emotions in a socially acceptable manner. Further, the correlations were computed, and significant positive correlations were found between children’s social and emotional skills and academic achievement (r=.378, p < .01), and between children’s social and emotional skills and child’s perceived self-efficacy (r = .724, p < .01) and a positive significant correlation was also found between children’s perceived self-efficacy and academic achievement (r=.332, p < .05). Results of the study emphasize on planning intervention for children with learning disability focusing on improving self-management and relationship skills, self-regulated learning and emotional self-efficacy.

Keywords: learning disability, social and emotional skills, perceived self-efficacy, academic achievement

Procedia PDF Downloads 240

Authors: Mourad Bakouka, Abdelaziz Rabehi

Abstract:

Companies need to have logistics and transportation in place that can adapt to the changing nature of construction sites. This ensures they can react quickly when needed. A study was conducted to develop a way to locate and track materials on construction sites. The system is an RFID/GPS integration that's required to pull off this feat. The study also reports how the platform has been used in construction. They found many advantages to using it, including reductions in both time and costs as well as improved management of materials orders. . For example, the time in which a project could start up was shortened from two weeks to three days with just a single digital order. As of now, the technology is still limited in its widespread adoption due largely to overall lack of awareness and difficulty connecting to it. However, as more and more companies embrace it in construction, the technology is expected to become ubiquitous. The developed platform provides contractors and construction managers with real-time information about the status of materials and work, allowing them to better manage the workflow in a project. The study sheds new light on this subject, which is essential to know. This work is becoming increasingly aware of the use of smart tools in constructing buildings.

Keywords: materials management, internet of things (IoT), radio frequency identification (RFID), construction site, supply chain management

Procedia PDF Downloads 79

Authors: Liat Shamri-Zeevi, Neta Ram-Vlasov

Abstract:

Today the world as a whole is attempting to cope with the COVID-19, which has affected all facets of personal and social life from country-wide confinement to maintaining social distance and taking protective measures to maintain hygiene. One of the populations faced with the most severe restrictions is seniors. Various studies have shown that creativity plays a crucial role in dealing with crisis events. Painting - regardless of media - allows for emotional and cognitive processing of these situations, and enables the expression of experiences in a tangible creative way that conveys and endows meaning to the artwork. The current study was conducted in Israel immediately after a 6-week lockdown. It was designed to specifically examine the impact of the COVID-19 pandemic on the quality of life of elderly women as reflected in their artworks. The sample was composed of 21 Israeli women aged 60-90, in good mental health (without diagnosed dementia or Alzheimer's), all of whom were Hebrew-speaking, and retired with an extended family, who indicated that they painted and had engaged in artwork on an ongoing basis throughout the lockdown (from March 12 to May 30, 2020). The participants' artworks were collected, and a semi-structured in-depth interview was conducted that lasted one to two hours. The participants were asked about their feelings during the pandemic and the artworks they produced during this time, and completed a questionnaire on well-being and mental health. The initial analysis of the interviews and artworks revealed themes related to the specific role of each piece of artwork. The first theme included notions that the artwork was an activity and a framework for doing, which supported positive emotions, and provided a sense of vitality during the closure. Most of the participants painted images of nature and growth which were ascribed concrete and symbolic meaning. The second theme was that the artwork enabled the processing of difficult and /or conflicting emotions related to the situation, including anxiety about death and loneliness that were symbolically expressed in the artworks, such as images of the Corona virus and the respiratory machines. The third theme suggested that the time and space prompted by the lockdown gave the participants time for a gathering together of the self, and freed up time for creative activities. Many participants stated that they painted more and more frequently during the Corona lockdown. At the conference, additional themes and findings will be presented.

Keywords: Corona virus, artwork, quality of life of elderly

Procedia PDF Downloads 141

Authors: Shaimaa Alobaidi

Abstract:

The presentation examines how urbanization opens possibilities for American Indian characters like Zits in Alexie’s Flightto explore new definitionsoftheirtribal self-identification. Zits travels in time and views the world from different bodies, ages, and races; his journeys end with different perspectives on the idea of nationhood as an American Indian. He is an example of Vine Deloria’s statementthat “urban Indians have become the cutting edge of the new Indian nationalism” (248). Flight is chosen because the momentZits leaves the real world for time-traveling adventures is very critical; it is a moment of rage that ends in the mass murder of many Anglo-Americans. The paper focus on the turning point when he returns into his body with new opportunities towards his existence among the majority of anglo-Americans who cannot help but see him American Indian minority in need of help and assistance. Characters, such as Zits, attempt to outlive alienation, and Alexie gives new definitionsof their ethnic nationhood. Futuristicdoes not mean the very far unpredictable future; it is rather a nearpotential future for teenagers of American Indians, like Zits, Arnold, andCoyoteSprings- the band in ReservationBlues; all revolutionary personalitiesin Alexie’s works. They will be analyzed as Gerald Vizenor’s “postindianwarriors” who have the ability to identify Indigenous nationalism in a post-colonial context.

Keywords: alienation, self-identification, nationhood, urbanization, postindian

Procedia PDF Downloads 165

Authors: Stepan Papacek, Jiri Jablonsky, Radek Kana, Ctirad Matonoha, Stefan Kindermann

Abstract:

FRAP (Fluorescence Recovery After Photobleaching) is a widely used measurement technique to determine the mobility of fluorescent molecules within living cells. While the experimental setup and protocol for FRAP experiments are usually fixed, data processing part is still under development. In this paper, we formulate and solve the problem of data selection which enhances the processing of FRAP images. We introduce the concept of the irrelevant data set, i.e., the data which are almost not reducing the confidence interval of the estimated parameters and thus could be neglected. Based on sensitivity analysis, we both solve the problem of the optimal data space selection and we find specific conditions for optimizing an important experimental design factor, e.g., the radius of bleach spot. Finally, a theorem announcing less precision of the integrated data approach compared to the full data case is proven; i.e., we claim that the data set represented by the FRAP recovery curve lead to a larger confidence interval compared to the spatio-temporal (full) data.

Keywords: FRAP, inverse problem, parameter identification, sensitivity analysis, optimal experimental design

Procedia PDF Downloads 276

Authors: Ezgi Şendil

Abstract:

Information extracted from social media has received great attention since it has become an effective alternative for collecting people’s opinions and emotions based on specific experiences in a faster and easier way. The paper aims to put data in a meaningful way to analyze users’ posts and get a result in terms of the experiences and opinions of the users during and after natural disasters. The posts collected from Reddit are classified into nine different categories, including injured/dead people, infrastructure and utility damage, missing/found people, donation needs/offers, caution/advice, and emotional support, identified by using labelled Twitter data and four different machine learning (ML) classifiers.

Keywords: disaster, NLP, postdisaster management, sentiment analysis

Procedia PDF Downloads 74

Authors: Ogundele Lasun Tunde, Ayeku Oluwagbemiga Patrick

Abstract:

Heavy metals are released into the sediments in aquatic environment from both natural and anthropogenic sources and they are considered as worldwide issue due to their deleterious ecological risks and food chain disruption. In this study, sediments samples were collected at three major sites (Awoye, Abereke and Ayetoro) along Ondo coastal area using VanVeen grab sampler. The concentrations of As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, V and Zn were determined by employing Atomic Absorption Spectroscopy (AAS). The combined concentrations data were subjected to Positive Matrix Factorization (PMF) receptor approach for source identification and apportionment. The probable risks that might be posed by heavy metals in the sediment were estimated by potential and integrated ecological risks indices. Among the measured heavy metals, Fe had the average concentrations of 20.38 ± 2.86, 23.56 ± 4.16 and 25.32 ± 4.83 lg/g at Abereke, Awoye and Ayetoro sites, respectively. The PMF resulted in identification of four sources of heavy metals in the sediments. The resolved sources and their percentage contributions were oil exploration (39%), industrial waste/sludge (35%), detrital process (18%) and Mn-sources (8%). Oil exploration activities and industrial wastes are the major sources that contribute heavy metals into the coastal sediments. The major pollutants that posed ecological risks to the local aquatic ecosystem are As, Pb, Cr and Cd (40 B Ei ≤ 80) classifying the sites as moderate risk. The integrate risks values of Awoye, Abereke and Ayetoro are 231.2, 234.0 and 236.4, respectively suggesting that the study areas had a moderate ecological risk. The study showed the suitability of PMF receptor model for source identification of heavy metals in the sediments. Also, the intensive anthropogenic activities and natural sources could largely discharge heavy metals into the study area, which may increase the heavy metal contents of the sediments and further contribute to the associated ecological risk, thus affecting the local aquatic ecosystem.

Keywords: positive matrix factorization, sediments, heavy metals, sources, ecological risks

Procedia PDF Downloads 20

Authors: Mariateresa Torchia, Helene Cristini, Hannele Kauppinen

Abstract:

Leadership plays a vital role in organizations. Leaders provide directions and facilitate the processes that enable organizations to achieve their goals and objectives. However, while productivity and financial objectives are often given the greatest emphasis, leaders also have the responsibility for instituting standards of ethical conduct and moral values that guide the behavior of employees. Leaders’ behaviors such as support, empowerment and a high-quality relationship with their employees might not only prevent stress, but also improve employees’ stress coping meanwhile contributing to their affective well-being. Stemming from Girard’s Mimetic Theory, this study aims at understanding how leaders can foster well-being in organizations. To do so, we explore which is the role leaders play in conflict management, resentment management and negative emotions dissipation. Furthermore, we examine whether and to what extent religiosity impacts the way in which leaders operate in relation to employees’ well-being. Indeed, given that organizational values are crucial to ethical behavior and firms’ values may be steeled by a deep sense of spirituality and religious identification, there is a need to take a closer look at the role religion and spirituality play in influencing the way leaders impact employees’ well-being. Thus, religion might work as an overarching logic that provides a set of principles guiding leaders’ everyday practices and relations with employees. We answer our research questions using a qualitative approach. We interviewed 27 Christian leaders (members of the Christian Entrepreneurs and Leaders Association – EDC, a non-profit organization created in 1926 including 3,000 French Christian Leaders & Entrepreneurs). Our results show that well-being can have a different meaning in relation to the type of companies, size, culture, country of analysis. Moreover the values and believes of leaders influence the way they see and foster well-being among employees. Furthermore, leaders can have both a positive or negative impact on well-being. Indeed on the one side, they could increase well-being in the company while on the other hand, they could be the source of resentment and conflicts among employees. Finally, we observed that Christian leaders possess characteristics that are sometimes missing in leaders (humility, inability to compare with others, attempt to be coherent with their values and beliefs, interest in the common good instead of the personal interest, having tougher dilemmas, collectively undertaking the firm). Moreover the Christian leader believes that the common good should come before personal interest. In other words, to them, not only short –termed profit shouldn’t guide strategical decisions but also leaders should feel responsible for their employees’ well-being. Last but not least, the study is not an apologia of Christian, yet it discusses the implications of these values through the light of Girard’s mimetic theory for both theory and practice.

Keywords: Christian leaders, employees well-being, leadership, mimetic theory

Procedia PDF Downloads 120

Authors: Joel Niklaus, Matthias Sturmer

Abstract:

The publication of judicial proceedings is a cornerstone of many democracies. It enables the court system to be made accountable by ensuring that justice is made in accordance with the laws. Equally important is privacy, as a fundamental human right (Article 12 in the Declaration of Human Rights). Therefore, it is important that the parties (especially minors, victims, or witnesses) involved in these court decisions be anonymized securely. Today, the anonymization of court decisions in Switzerland is performed either manually or semi-automatically using primitive software. While much research has been conducted on anonymization for tabular data, the literature on anonymization for unstructured text documents is thin and virtually non-existent for court decisions. In 2019, it has been shown that manual anonymization is not secure enough. In 21 of 25 attempted Swiss federal court decisions related to pharmaceutical companies, pharmaceuticals, and legal parties involved could be manually re-identified. This was achieved by linking the decisions with external databases using regular expressions. An automated re-identification system serves as an automated test for the safety of existing anonymizations and thus promotes the right to privacy. Manual anonymization is very expensive (recurring annual costs of over CHF 20M in Switzerland alone, according to an estimation). Consequently, many Swiss courts only publish a fraction of their decisions. An automated anonymization system reduces these costs substantially, further leading to more capacity for publishing court decisions much more comprehensively. For the re-identification system, topic modeling with latent dirichlet allocation is used to cluster an amount of over 500K Swiss court decisions into meaningful related categories. A comprehensive knowledge base with publicly available data (such as social media, newspapers, government documents, geographical information systems, business registers, online address books, obituary portal, web archive, etc.) is constructed to serve as an information hub for re-identifications. For the actual re-identification, a general-purpose language model is fine-tuned on the respective part of the knowledge base for each category of court decisions separately. The input to the model is the court decision to be re-identified, and the output is a probability distribution over named entities constituting possible re-identifications. For the anonymization system, named entity recognition (NER) is used to recognize the tokens that need to be anonymized. Since the focus lies on Swiss court decisions in German, a corpus for Swiss legal texts will be built for training the NER model. The recognized named entities are replaced by the category determined by the NER model and an identifier to preserve context. This work is part of an ongoing research project conducted by an interdisciplinary research consortium. Both a legal analysis and the implementation of the proposed system design ESRA will be performed within the next three years. This study introduces the system design of ESRA, an end-to-end system for re-identification and anonymization of Swiss court decisions. Firstly, the re-identification system tests the safety of existing anonymizations and thus promotes privacy. Secondly, the anonymization system substantially reduces the costs of manual anonymization of court decisions and thus introduces a more comprehensive publication practice.

Keywords: artificial intelligence, courts, legal tech, named entity recognition, natural language processing, ·privacy, topic modeling

Procedia PDF Downloads 147