Search results for: severity identification

Authors: Serge B. Provost, Yishan Zhang

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A moment-based adjustment to the saddlepoint approximation is introduced in the context of density estimation. First applied to univariate distributions, this methodology is extended to the bivariate case. It then entails estimating the density function associated with each marginal distribution by means of the saddlepoint approximation and applying a bivariate adjustment to the product of the resulting density estimates. The connection to the distribution of empirical copulas will be pointed out. As well, a novel approach is proposed for estimating the support of distribution. As these results solely rely on sample moments and empirical cumulant-generating functions, they are particularly well suited for modeling massive data sets. Several illustrative applications will be presented.

Keywords: empirical cumulant-generating function, endpoints identification, saddlepoint approximation, sample moments, density estimation

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Authors: Sara Hasani

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This research focuses on natural sudden onset disasters characterised as ‘occurring with little or no warning and often cause excessive injuries far surpassing the national response capacities’. Based on the panel analysis of the historic record of 4,252 natural onset disasters between 1980 to 2015, a predictive method was developed to predict the human impact of the disaster (fatality, injured, homeless) with less than 3% of errors. The geographical dispersion of the disasters includes every country where the data were available and cross-examined from various humanitarian sources. The records were then filtered into 4252 records of the disasters where the five predictive variables (disaster type, HDI, DRI, population, and population density) were clearly stated. The procedure was designed based on a combination of pattern recognition techniques and rule-based clustering for prediction and discrimination analysis to validate the results further. The result indicates that there is a relationship between the disaster human impact and the five socio-economic characteristics of the affected country mentioned above. As a result, a framework was put forward, which could predict the disaster’s human impact based on their severity rank in the early hours of disaster strike. The predictions in this model were outlined in two worst and best-case scenarios, which respectively inform the lower range and higher range of the prediction. A necessity to develop the predictive framework can be highlighted by noticing that despite the existing research in literature, a framework for predicting the human impact and estimating the needs at the time of the disaster is yet to be developed. This can further be used to allocate the resources at the response phase of the disaster where the data is scarce.

Keywords: disaster management, natural disaster, pattern recognition, prediction

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Authors: Haitham S. Hamza, Mohamed Maher, Shourok Alaa, Aya Khattab, Hadeal Ismail, Kamilia Hosny

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Radio Frequency Identification (RFID) has become a key technology in the margining concept of Internet of Things (IoT). Naturally, business applications would require the deployment of various RFID systems that are developed by different vendors and use various data formats. This heterogeneity poses a real challenge in developing large-scale IoT systems with RFID as integration is becoming very complex and challenging. Semantic integration is a key approach to deal with this challenge. To do so, ontology for RFID systems need to be developed in order to annotated semantically RFID systems, and hence, facilitate their integration. Accordingly, in this paper, we propose ontology for RFID systems. The proposed ontology can be used to semantically enrich RFID systems, and hence, improve their usage and reasoning. The usage of the proposed ontology is explained through a simple scenario in the health care domain.

Keywords: RFID, semantic technology, ontology, sparql query language, heterogeneity

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Authors: Chanada Aonsri, Wichai Eungpinichpong

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Stereotypical behavior is one of the learning and social skills development problems that affect children with autism. Previous studies found that traditional Thai massage (TTM) could reduce stereotypical behaviors in autistic children. However, the effects of TTM delivered by the parents of autistic children have not been explored. This pilot study investigated the effects of TTM by parents on stereotypical behaviors in children with autism. A one-group pretest-posttest design was applied for 15 children, aged 4-16 years, with their parents' permissions. They participated in the study at the Special Education program of the Special Education Center of Khon Kaen University, Thailand. After being trained in a specialized TTM for children, the parents delivered 50-minute TTM to children once a day, twice a week for eight weeks. The severity of autism and autistic behaviors were measured using the Childhood Autism Rating Scale (CARS), and the Autism Treatment Evaluation Checklist (ATEC), respectively. The functions of autonomic nervous systems were measured using Heart Rate Variability (HRV) to indicated physical and mental disorders such as stress. The data at baseline and the 8th week were analyzed using either an independent t-test or Wilcoxon signed-rank test. The study found that 16 sessions of TTM significantly improved measured data for autism in all children including the CARS (p<0.001), ATEC, speech/language/communication (p<0.001), sociability (p<0.001), sensory/cognitive awareness (p<0.001), health/physical/behavior (p < 0.001), and HRV (p<0.001). The results indicated that TTM performed by parents could be useful as an adjunct therapy for autistic children as it can reduce stereotypical behaviors and stress.

Keywords: traditional Thai massage, stereotypical behaviors, Autistic children, parent

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Authors: David Kramsky, Barbora Vegrichtova

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The prison facility is generally considered as an environment having a corrective purpose. Besides the social sense of remedy, prison is also an environment that potentially determines and affects socially dangerous behavior. The authors, based on long-term empirical research, present the significant indicators that are directly related to the transformation of personality attitudes, motivations and behavior associating with a process of radicalization. One of the most significant symptoms of radicalization is a particular social moral decision making. Individuals in the radicalism process primarily prefer utilitarian manners of decision-making more than personal aspects like empathy for others. The authors will present the method of social moral profiling of the subject in radicalization process as an effective prevention system reducing security risks in society.

Keywords: indicators, moral decision, radicalism, social profile

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Authors: Muhammad Denny Abdillah, Mochammad Rasyid Poedjijanto

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Batu, East Java, Indonesia is located in highland about 680-1,200 meters above ocean surface and has temperature 15-19 degree Celsius. With this condition, so the main profession of people around is a farmer. But, along with era’s developing, now Batu is started to improve their development in tourism sector and show up them as an icon of tourism in Indonesia. Such as: playground, museum, and paralayang’s summit. That is made Batu in nowadays well known as the one of recommended city to visit. The change of the development from farming sector to tourism sector make people around prefer doing job in trade than engage in farming. That’s make authors want to observe about this social phenomenon which is happening in Batu, whereas from the beginning the primary profession is a farmer, now changed to be a trader around the tourism place.

Keywords: development, profession, tourism, Batu

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Authors: Chetna Tyagi, Ambuj Tripathi, Devesh Avasthi

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Graphene oxide consists of sp³ hybridization along with sp² hybridization due to the presence of different oxygen-containing functional groups on its edges and basal planes. However, its sp³ / sp² hybridization can be tuned by various methods to utilize it in different applications, like transistors, solar cells and biosensors. Ion beam irradiation can also be one of the methods to optimize sp² and sp³ hybridization ratio for its desirable properties. In this work, graphene oxide films were irradiated with 100 keV Argon ions at different fluences varying from 10¹³ to 10¹⁶ ions/cm². Synchrotron X-ray diffraction measurements showed an increase in crystallinity at the low fluence of 10¹³ ions/cm². Raman spectroscopy performed on irradiated samples determined the defects induced by the ion beam qualitatively. Also, identification of different groups and their removal with different fluences was done using Fourier infrared spectroscopy technique.

Keywords: graphene oxide, ion beam irradiation, spectroscopy, X-ray diffraction

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Authors: Rebeca V. Tholen, Elaine Bundy

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Background: Liver transplantation (LT) is considered the only curative treatment for end-stage liver disease Background: Liver transplantation (LT) is considered the only curative treatment for end-stage liver disease (ESLD). The effects of alcoholism can cause irreversible liver damage, cirrhosis and subsequent liver failure. Alcohol relapse after transplant occurs in 20-50% of patients and increases the risk for recurrent cirrhosis, organ rejection, and graft failure. Alcohol relapse after transplant has been identified as a problem among liver transplant recipients at a large urban academic transplant center in the United States. Transplantation will reverse the complications of ESLD, but it does not treat underlying alcoholism or reduce the risk of relapse after transplant. The purpose of this quality improvement project is to implement and evaluate the effectiveness of a High-Risk Alcoholism Relapse (HRAR) Scale to screen and identify patients at high-risk for alcohol relapse after receiving an LT. Methods: The HRAR Scale is a predictive tool designed to determine the severity of alcoholism and risk of relapse after transplant. The scale consists of three variables identified as having the highest predictive power for early relapse including, daily number of drinks, history of previous inpatient treatment for alcoholism, and the number of years of heavy drinking. All adult liver transplant recipients at a large urban transplant center were screened with the HRAR Scale prior to hospital discharge. A zero to two ordinal score is ranked for each variable, and the total score ranges from zero to six. High-risk scores are between three to six. Results: Descriptive statistics revealed 25 patients were newly transplanted and discharged from the hospital during an 8-week period. 40% of patients (n=10) were identified as being high-risk for relapse and 60% low-risk (n=15). The daily number of drinks were determined by alcohol content (1 drink = 15g of ethanol) and number of drinks per day. 60% of patients reported drinking 9-17 drinks per day, and 40% reported ≤ 9 drinks. 50% of high-risk patients reported drinking ≥ 25 years, 40% for 11-25 years, and 10% ≤ 11 years. For number of inpatient treatments for alcoholism, 50% received inpatient treatment one time, 20% ≥ 1, and 30% reported never receiving inpatient treatment. Findings reveal the importance and value of a validated screening tool as a more efficient method than other screening methods alone. Integration of a structured clinical tool will help guide the drinking history portion of the psychosocial assessment. Targeted interventions can be implemented for all high-risk patients. Conclusions: Our findings validate the effectiveness of utilizing the HRAR scale to screen and identify patients who are a high-risk for alcohol relapse post-LT. Recommendations to help maintain post-transplant sobriety include starting a transplant support group within the organization for all high-risk patients. (ESLD). The effects of alcoholism can cause irreversible liver damage, cirrhosis and subsequent liver failure. Alcohol relapse after transplant occurs in 20-50% of patients, and increases the risk for recurrent cirrhosis, organ rejection, and graft failure. Alcohol relapse after transplant has been identified as a problem among liver transplant recipients at a large urban academic transplant center in the United States. Transplantation will reverse the complications of ESLD, but it does not treat underlying alcoholism or reduce the risk of relapse after transplant. The purpose of this quality improvement project is to implement and evaluate the effectiveness of a High-Risk Alcoholism Relapse (HRAR) Scale to screen and identify patients at high-risk for alcohol relapse after receiving a LT. Methods: The HRAR Scale is a predictive tool designed to determine severity of alcoholism and risk of relapse after transplant. The scale consists of three variables identified as having the highest predictive power for early relapse including, daily number of drinks, history of previous inpatient treatment for alcoholism, and the number of years of heavy drinking. All adult liver transplant recipients at a large urban transplant center were screened with the HRAR Scale prior to hospital discharge. A zero to two ordinal score is ranked for each variable, and the total score ranges from zero to six. High-risk scores are between three to six. Results: Descriptive statistics revealed 25 patients were newly transplanted and discharged from the hospital during an 8-week period. 40% of patients (n=10) were identified as being high-risk for relapse and 60% low-risk (n=15). The daily number of drinks were determined by alcohol content (1 drink = 15g of ethanol) and number of drinks per day. 60% of patients reported drinking 9-17 drinks per day, and 40% reported ≤ 9 drinks. 50% of high-risk patients reported drinking ≥ 25 years, 40% for 11-25 years, and 10% ≤ 11 years. For number of inpatient treatments for alcoholism, 50% received inpatient treatment one time, 20% ≥ 1, and 30% reported never receiving inpatient treatment. Findings reveal the importance and value of a validated screening tool as a more efficient method than other screening methods alone. Integration of a structured clinical tool will help guide the drinking history portion of the psychosocial assessment. Targeted interventions can be implemented for all high-risk patients. Conclusions: Our findings validate the effectiveness of utilizing the HRAR scale to screen and identify patients who are a high-risk for alcohol relapse post-LT. Recommendations to help maintain post-transplant sobriety include starting a transplant support group within the organization for all high-risk patients.

Keywords: alcoholism, liver transplant, quality improvement, substance abuse

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Authors: S. K. Ashiquer Rahman

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This paper presents a knowledge mediation platform, “ePLANETe Blue” that addresses the challenge of building knowledge partnerships for higher education. The purpose is to present, as an institutional perception, the ‘ePLANETe' idea and functionalities as a practical and pedagogical innovation program contributing to the collaborative learning goals in higher education. In consequence, the set of functionalities now amalgamated in ‘ePLANETe’ can be seen as an investigation of the challenges of “Collaborative Learning Digital Process.” It can exploit the system to facilitate collaborative education, research and student learning in higher education. Moreover, the platform is projected to support the identification of best practices at explicit levels of action and to inspire knowledge interactions in a “virtual community” and thus to advance in deliberation and learning evaluation of higher education through the engagement of collaborative activities of different sorts.

Keywords: mediation, collaboration, deliberation, evaluation

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Authors: Arezoo Fallahi

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Introduction: Exposure to second-hand smoke is an important global health problem and threatens the health of people, especially children and women. The aim of this study was to determine the effect of education based on the Health Belief Model on preventive behaviors of exposure to secondhand smoke in women. Materials and Methods: This experimental study was performed in 2023in Sanandaj, west of Iran. Seventy-four people were selected by simple random sampling and divided into an intervention group (37 people) and a control group (37 people). Data collection tools included demographic characteristics and a second-hand smoke exposure questionnaire based on the Health Beliefs Model. The training in the intervention group was conducted in three one-hour sessions in the comprehensive health service centers in the form of lectures, pamphlets, and group discussions. Data were analyzed using SPSS software version 21 and statistical tests such as correlation, paired t-test, and independent t-test. Results: The intervention and control groups were homogeneous before education. They were similar in terms of mean scores of the Health Belief Model. However, after an educational intervention, some of the scores increased, including the mean perceived sensitivity score (from 17.62±2.86 to 19.75±1.23), perceived severity score (28.40±4.45 to 31.64±2), perceived benefits score (27.27±4.89 to 31.94±2.17), practice score (32.64±4.68 to 36.91±2.32) perceived barriers from 26.62±5.16 to 31.29±3.34, guide for external action (from 17.70±3.99 to 22/89 ±1.67), guide for internal action from (16.59±2.95 to 1.03±18.75), and self-efficacy (from 19.83 ±3.99 to 23.37±1.43) (P <0.05). Conclusion: The educational intervention designed based on the Health Belief Model in women was effective in performing preventive behaviors against exposure to secondhand smoke.

Keywords: women, health behaviour, smoke, belive

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Authors: K. Jarmkom, P. Eakwaropas, W. Khobjai, S. Techaeoi

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Ancient Thai perfumed powder was used as a fragrance for clothing, food, and the body. Plant-based natural Thai perfume products are known as Pang-Rum. The objective of this study was to evaluate the stability of essential oils after six months of incubation. The chemical compositions were determined by gas chromatography-mass spectrometry (GC-MS), in terms of the qualitative composition of the isolated essential oil. The isolation of the essential oil of natural products by incubate sample for 5 min at 40 ºC is described. The volatile components were identified by percentage of total peak areas comparing their retention times of GC chromatograph with NIST mass spectral library. The results show no significant difference in the seven chromatograms of perfumed powder (Pang-Rum) both with binder and without binder. Further identification was done by GC-MS. Some components of Pang-Rum with/without binder were changed by temperature and time.

Keywords: GC-MS analysis, essential oils, stability, Pang-Rum

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Authors: Magdi. M. Nabi, Ding-Li Yu

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Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based on the identification of the plant and self-learning capability of RBFNN. A PID controller is used in the feedback control to regulate the actual temperature by compensating the neural network inverse model output. Simulation results show that the proposed control has strong adaptability, robustness and satisfactory control performance and the nonlinear system is achieved.

Keywords: Chylla-Haase polymerization reactor, RBF neural networks, feed-forward, feedback control

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Authors: Parisa Mansour

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Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

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Authors: Lauren McGillivray, Michelle Torok, Alison Calear

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Suicide is the leading cause of death for Australians aged 15-24 years, with rates increasing over the past decade. As young people can be particularly vulnerable to mental health problems and suicidal behavior, they are an essential and obvious target for suicide prevention efforts. This study investigates the effectiveness of the universal mental health promotion and suicide prevention program, Youth Aware of Mental Health (YAM), to reduce suicidal ideation and attempts and increase help-seeking in young people. This trial took place in Australian schools across four regions in New South Wales that form part of LifeSpan, a larger multilevel suicide prevention research trial. The YAM program was delivered to Year 9 students in up to 78 schools over two years (from January 2017 to December 2019). All schools were invited to participate in YAM's evaluation, which included completing a student questionnaire at three time-points: baseline, 3-month post-intervention, and 6-month follow-up. The primary outcome is suicidal ideation severity. Secondary outcomes are new reports of suicide attempts, stigma towards suicide, knowledge about suicide, help-seeking intentions and behaviors, and depressive symptoms. Results from pre-post and follow-up data will be presented. These research findings are promising and will contribute to the evidence-based for YAM and suicide prevention programs in Australian schools. These findings are also expected to promote YAM's value and sustainability to be more widely delivered in Australian secondary schools.

Keywords: adolescent mental health, suicidal ideation, suicide prevention, universal program

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Authors: André Jesus, Yanjie Zhu, Irwanda Laory

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Structural health monitoring is one of the most promising technologies concerning aversion of structural risk and economic savings. Analysts often have to deal with a considerable variety of uncertainties that arise during a monitoring process. Namely the widespread application of numerical models (model-based) is accompanied by a widespread concern about quantifying the uncertainties prevailing in their use. Some of these uncertainties are related with the deterministic nature of the model (code uncertainty) others with the variability of its inputs (parameter uncertainty) and the discrepancy between a model/experiment (systematic uncertainty). The actual process always exhibits a random behaviour (observation error) even when conditions are set identically (residual variation). Bayesian inference assumes that parameters of a model are random variables with an associated PDF, which can be inferred from experimental data. However in many Bayesian methods the determination of systematic uncertainty can be problematic. In this work systematic uncertainty is associated with a discrepancy function. The numerical model and discrepancy function are approximated by Gaussian processes (surrogate model). Finally, to avoid the computational burden of a fully Bayesian approach the parameters that characterise the Gaussian processes were estimated in a four stage process (modular Bayesian approach). The proposed methodology has been successfully applied on fields such as geoscience, biomedics, particle physics but never on the SHM context. This approach considerably reduces the computational burden; although the extent of the considered uncertainties is lower (second order effects are neglected). To successfully identify the considered uncertainties this formulation was extended to consider multiple responses. The efficiency of the algorithm has been tested on a small scale aluminium bridge structure, subjected to a thermal expansion due to infrared heaters. Comparison of its performance with responses measured at different points of the structure and associated degrees of identifiability is also carried out. A numerical FEM model of the structure was developed and the stiffness from its supports is considered as a parameter to calibrate. Results show that the modular Bayesian approach performed best when responses of the same type had the lowest spatial correlation. Based on previous literature, using different types of responses (strain, acceleration, and displacement) should also improve the identifiability problem. Uncertainties due to parametric variability, observation error, residual variability, code variability and systematic uncertainty were all recovered. For this example the algorithm performance was stable and considerably quicker than Bayesian methods that account for the full extent of uncertainties. Future research with real-life examples is required to fully access the advantages and limitations of the proposed methodology.

Keywords: bayesian, calibration, numerical model, system identification, systematic uncertainty, Gaussian process

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Authors: Jurijs Salijevs, Katrina Bolocko

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The integration of artificial intelligence and neural networks has significantly changed full-body imaging and high-resolution 3D mapping systems, and this paper reviews research in these areas. With an emphasis on their use in the early identification of melanoma and other disorders, the goal is to give a wide perspective on the current status and potential future of these medical imaging technologies. Authors also examine methodologies such as machine learning and deep learning, seeking to identify efficient procedures that enhance diagnostic capabilities through the analysis of 3D body scans. This work aims to encourage further research and technological development to harness the full potential of AI in disease diagnosis.

Keywords: artificial intelligence, neural networks, 3D scan, body scan, 3D mapping system, healthcare

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Authors: Yasin I. Tayem, Jamil Ahmed, Mahmood Bahzad, Abdullah Alnama, Fahad Al Asfoor, Mahmood A. Jalil, Mohammed Radhi, Ahmed Alenezi, Khalid A. J. Al-Khaja

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Drug-drug interactions (DDIs) represent a significant cause of patient’s morbidity and mortality. The rate of DDIs is rapidly increasing worldwide with the increasing proportion of ageing population and frequent requirement of polypharmacy-prescription of multiple drugs to treat comorbidities. Prescribing physicians are responsible for checking their prescriptions for the presence and severity of DDIs. However, since a large number of new drugs are approved and marketed every year, new interactions between medications are increasingly reported. Consequently, it is no longer practical for physicians to rely only upon their previous knowledge of medicine to avoid potential DDIs. The aim of this study was to explore the perceptions of physicians working at primary healthcare centers in Bahrain towards DDIs and how they manage them during their practice. Methodology: In this cross-sectional study, physicians working at all governmental primary healthcare centers in Bahrain were invited to voluntarily, privately and anonymously respond to a self-administered questionnaire. The questionnaire aims to assess their self-reported knowledge of DDIs and how they check for them in their practice. The participants were requested to provide socio demographic data and information related to their attitudes towards DDIs including strategies they employ for detecting and managing them, and their awareness of drugs which commonly cause DDIs. At the end of the questionnaire, an open-ended item was added to allow participants to further add any comment. Findings and Conclusions: The study is going on currently, and the results and conclusions will be presented at the conference.

Keywords: awareness, drug interactions, health centres, physicians

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Authors: David Pettitt, Benjamin Davies, Georg Holländer, David Brindley

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Cellular based therapies, whose origins can be traced from the intertwined concepts of tissue engineering and regenerative medicine, have the potential to transform the current medical landscape and offer an approach to managing what were once considered untreatable diseases. However, despite a large increase in basic science activity in the cell therapy arena alongside a growing portfolio of cell therapy trials, the number of industry products available for widespread clinical use correlates poorly with such a magnitude of activity, with the number of cell-based therapeutics in mainstream use remaining comparatively low. This research serves to quantitatively assess the barriers to the clinical adoption of cell-based therapeutics through identification of unique barriers, specific challenges and opportunities facing the development and adoption of such therapies.

Keywords: cell therapy, clinical adoption, commercialization, translation

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Authors: Rahy Farooq, Maria Ahmad Khan, Ayesha Isani Majeed

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Objective: The main aim of this research is to assess the knowledge, attitude and practices of female nursing staff and nursing students regarding breast cancer, to provide a baseline for monitoring trends of breast cancer awareness in them. Background: Healthcare professionals are a direct source of information for the patients and the general public as a whole. It is, therefore, essential that the information they convey be accurate and helps in building additional awareness. However, clinical experience does not influence the knowledge, attitude and practices regarding breast cancer. Nurses, being the prime part of the healthcare professionals, play a significant role and hence, their awareness regarding this pressing issue is pertinent. Lack of awareness regarding common presenting symptoms or breast cancer risk factors translates to poor breast cancer screening practices and late diagnosis. Methodology: A cross-sectional study of 280 female nurses was conducted at a tertiary care hospital in Islamabad, Pakistan. A pre-tested structured questionnaire with additional variables like cultural barriers to seeking medical help was used. The scores for outcome variables including knowledge, attitude and practices were pre-defined. Data was analyzed using SPSSv23. Results: Of the 280 participants with a mean age of 28.99±9.98 years, 142 (50.7%) were married, and 138 (49.3%) were unmarried. Mean scores were computed to be 6.14±2.93 (out of 12), 0.30±0.7 (out of 3) and 9.53±1.92 (out of 16) for knowledge, attitude and practice respectively. Using independent sample T-test, a statistically significant correlation was found when means for the score of Attitude was compared with age. With a p-value of 0.018, 117 nurses of age more than 30 years, faced more practical, financial, emotional and service barriers as compared to 163 women younger than 30 years of age. Knowledge of age-related lifetime risks was also significantly poor more in single women; with a p-value of 0.006 for identification of correct age as a risk factor and a p-value of 0.005 for correct identification of risk for development of breast cancer in the lifetime of women. By application of Chi-square test, there was a significant correlation between marital status and cultural barriers to seeking medical help, showing that single women (58.7%) shy away from talking about breast cancer considering it a taboo (p-value 0.028) whereas, more married nurses (59.2%) were apprehensive that they might be considered at fault by the society, as compared to 40.8% of single nurses. (p-value 0.038). Conclusion: Owing to the scarcity of awareness among nurses, this study recognizes the need for delivering effective information to the female nurses regarding breast cancer. Educating patients is likely to be effective if the female nurses play their part and have correct attitudes towards breast cancer practices. A better understanding of the knowledge and practices regarding breast cancer among the nursing population will enable high-risk patients to be recognized early. Therefore, we recommend arrangement of special courses and seminars for all healthcare professionals including the nursing staff.

Keywords: breast cancer, cultural barriers, kap, nurses

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Authors: Rajesh A. Rane, Shital S. Naphade, Rajshekhar Karpoormath

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Thiozolidin-4-one, a mimic of thiazolobenzimidazole (TBZ) has drawn many attentions due to its potent and selective inhibition against the HIV-1 and low toxicity by binding to the allosteric site of the reverse transcriptase (RT) as a non-nucleoside RT inhibitor (NNRTI). Similarly, marine bromopyrrole alkaloids are well known for their diverse array of anti-infective properties. Hence, we have reported synthesis and in vitro HIV-1 RT inhibitory activity of a series of 4-thiazolidinone-bromopyrrole alkaloid hybrids tethered with amide linker. The results of in vitro HIV-1 RT kit assay showed that some of the compounds, such as 4c, 4d, and 4i could effectively inhibit RT activity. Among them, compounds 4c having 4-chlorophenyl substituted 4-thiazolidione ring was the best one with the IC50 value of 0.26 µM. The sturdy emerges with key structure-activity relationship that pyrrole-NH-free core benefited inhibition against HIV-1 RT inhibition. This study identified conjugate 4c with potent activity and selectivity as promising compound for further drug development to HIV.

Keywords: antiviral drugs, bromopyrrole alkaloids, HIV-1 RT inhibition, 4-thiazolidinone

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Authors: A. K. Sarathe, N. P. Patidar

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The Indian automobile sector is comprised of independent manufacturers and joint ventures with their foreign counterpart companies by making use of the Foreign Direct Investment policy of the Government of India. These manufacturers started capturing the hearts of Indian customers with their choice of technological and innovative product features, with quality and reliability. This transformed the automobile scene from a “sellers market to buyers market”. The potential benefits from the auto sector have been recognized by the planners, managers, and administrators of both the sectors –government and private. Generation of employment for the readily available technical workforce has been achieved not only through the manufacturers, but also through the growing ancillaries and service providers of the auto industries. The main purpose of this paper is to come up with the identification of possible working areas and associated job functions of mechanical and automobile diploma holders having employment opportunities in auto sector of India.

Keywords: automobile sector, diploma holder, employment, job description

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Authors: Nelson Igaba, C. Onaga, S. Hlongwane

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Background: Medical Male Circumcision (MMC) is part of a comprehensive HIV prevention strategy. The quality of MMC done at Right To Care (RtC) sites is maintained by Continuous Quality Improvement (CQI) based on findings of assessments by internal and independent external assessors who evaluate such parameters as the quality of the surgical procedure, infection control, etc. There are 12 RtC MMC teams in Mpumalanga, two of which are headed by Medical Officers and 10 by Clinical Associates (Clin A). Objectives: To compare the quality (i) of care rendered at doctor headed sites (DHS) versus Clin A headed sites (CHS); (ii) of CQI assessments (external versus internal). Methodology: A retrospective review of data from RightMax™ (a novel RtC data management system) and CQI reports (external and internal) was done. CQI assessment scores of October 2015 and October 2016 were taken as the baseline and latest respectively. Four sites with 745-810 circumcisions per annum were purposively selected; the two DHS (group A) and two CHS (group B). Statistical analyses were conducted using R (2017 version). Results: There were no significant difference in latest CQI scores between the two groups (DHS and CHS) (Anova, F = 1.97, df = 1, P = 0.165); between internal and external CQI assessment scores (Anova, F = 2.251, df = 1, P = 0.139) or among the individual sites (Anova, F = 1.095, df = 2, P = 0.341). Of the total of 16 adverse events reported by the four sites in the 12 months reviewed (all were infections), there was no statistical evidence that the documented severity of the infection was different for DHS and CHS (Fisher’s exact test, p-value = 0.269). Conclusion: At RtC VMMC sites in Mpumalanga, internal and external/independent CQI assessments are comparable, and quality of care of VMMC is standardized with the performance of well-supervised clinical associates comparing well with those of medical officers.

Keywords: adverse events, Right to Care, male medical circumcision, continuous quality improvement

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Authors: Jaiden X. Schraut

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Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

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Authors: Lovepreet Kaur Dhugga, Dwijendra P. Singh

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Calcium copper titanate (CCTO) was synthesized via the sol-gel auto-combustion method. The precursor was calcined at 800°C and 1000°C for 6 hours providing brown-coloured powders, which were pelletized and sintered at 1000°C for 12 hrs to determine their dielectric behaviour in the frequency range (100Hz-10MHz) at room temperature. The dielectric constant(εr) and loss tangent (tanδ) has been found to be ~ 6153 and 0.5 for 800°C and ~ 5504 and 0.2 for 1000°C respectively, at frequency 1kHz. Microstructure study revealed maximum grain growth occurs in sample calcined at 800°C, responsible for its high dielectric constant. Phase identification of CaCu₃Ti₄O₁₂ has been carried out through X-ray diffraction. It can be used in various electronic applications as it shows large εᵣ and low tanδ values over a wide frequency spectrum, including energy storage devices, microwave shielding, and sensors.

Keywords: calcium copper titanate, dielectric behaviour, microstructure, X-ray diffraction

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Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long

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In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.

Keywords: agricultural object detection, deep learning, machine vision, YOLO family

Procedia PDF Downloads 193

Authors: V. A. Doss, R. Sowndarya, K. Juila Rose Mary

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Objective: Amino acid neurotransmitter system dysfunction plays a major role in the pathophysiology of depression. The objective of the present study was to identify the amino acids as possible metabolite biomarkers for depression using GCMS (Gas Chromatography Mass Spectrometry) before and after exercise regimen in brain samples of depression induced animal models. Methods: Depression-like behaviour was induced by Chronic Unpredictable mild stress (CUMS). Severity of depression was measured by forced swim test (FST) and sucrose consumption test (SCT). Swimming protocol was followed for 4 weeks of exercise treatment. Brain obtained from depressed and exercise treated rats were used for the metabolite analysis by GCMS. Subsequent statistical analysis obtained by ANOVA followed by post hoc test revealed significant metabolic changes. Results: Amino acids such as alanine, glycine, serine, glutamate, homocysteine, proline and branched chain aminoacids (BCAs) Leucine, Isoleucine, Valine were determined in brain samples of control, depressed and exercised groups. Among these amino acids, the levels of D-Serine and branched chain amino acids were found to be decreased in depression induced rats. After four weeks of swimming exercise regimen, there were improvements in the levels of serine and Branched chain amino acids. Conclusion: We suggest that Serine and BCAs may be investigated as potential metabolite markers using GCMS and their beneficial metabolic changes in Exercise.

Keywords: metabolomics, depression, forced swim test, exercise, amino acid metabolites, GCMS, biomarker

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Authors: Lalita Panchal, Zulfiya Sheikh

Abstract:

Fluoride is essential for teeth and bones development not only for human beings but also for animals. But excess intake of fluoride causes harmful effects on health. Fluorosis is a worldwide health hazard and India is also one of the endemic countries. Udaipur district of Rajasthan is also prone to fluorosis and superphosphate industries are aggravating fluoride toxicity in this area. Grazing fields for animals in the close vicinity of the industries, fodder and water are fluoride contaminated. Fluoride toxicity in the form of dental fluorosis was observed in domestic animals, inhabiting industrial area near Udaipur, where superphosphate fertilizer plants are functioning and releasing fluoride and fumes and effluents into the surroundings. These fumes and gases directly affect the vegetation of grazing field, thus allowing entry of fluoride into the food chain. A survey was conducted in this area to assess the severity of fluorosis, in 2015-16. It was a house to house survey and animal owners were asked for their fodder and water supply. Anterior teeth of the animal were observed. Domestic animals exhibited mild to severe signs of dental fluorosis. Teeth showed deep brown staining, patches, lines and abrasions. Even immature animals were affected badly. Most of the domestic animals were affected, but goats of this area showed chronic symptoms of fluorosis. Due to abrasion of teeth and paining teeth their chewing or grazing capacity and appetite reduced. Eventually, it reduced the life span of animals and increased the mortality rate.

Keywords: domestic animals, fluoride toxicity, industrial fluorosis, superphosphate fertilizers

Procedia PDF Downloads 292

Authors: Najaf Hamadzadeh Arbabi

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Crime scene management is the first and most critical step in criminal investigations and all the criminal investigations are based on the ability of the crime scene investigation officers for diagnosing the importance and the role of physical evidence at the crime scene. According to the role of available physical evidence at the scene to prove the crime and identify the perpetrator and prove the innocence of those accused have been unduly and also impossible due to the rejection of these reasons, the maintenance and investigation of crime scene and collect evidence are very important in the crime scene. This research, by identifying the factors affecting the management of the crime scene, looking for presenting the effective and efficient indigenous pattern for managing of the crime scene in Iran. Method: This study is an applied and development research. Wilcoxon signed-rank test and the Friedman test for ranking, were used for analyzing the data and all hypotheses were tested at 95% confidence level. The target population is 50 judges and experts in Tehran.

Keywords: crime scene, identification, designation, individualization, reconstruction

Procedia PDF Downloads 275

Authors: Surekha Rathod

Abstract:

Sickle cell disease is a vascular disorder characterized by chronic, ongoing organ damage that is punctuated by episodes of acutely painful vascular complications.1 It is the most common genetic blood disorder in the United States, with about 2000 infants being identified through routine blood screenings annually, and an estimated 104,000-138,000 affected individuals living in the United States. Approximately 0.3%-1.3% of African American are affected by Sickle Cell Diseases (SCD).3 The aim of this paper is to present oral health status of patients with SCD. A total of 200 subjects of both sexes in the age group 18- 40 years were included in this study. The subjects were examined and the following indices were recorded • Oral hygiene index – Simplified (OHI-S). • Probing depths (PD). • Clinical Attachment Levels (CAL). • Gingival Index - Loe and Sillness. • Turesky Gillmore Glickman Modification of the Quigley Hein Plaque Index. (1970) • DMFT index. • Sickle Cell Disease Severity Index. A total of 1478 patients were screened of which 200 subjects were found to be diagnosed with SCD by electrophoresis. The study thus, included 200 subjects (111 females & 89 males) diagnosed with Sickle Cell Disease in the age group of 18-40 years. The probing pocket depths (PPD) were measured in millimeters. 36% had PPD in the range of 2-4mm, 48% had PPD in the range of 4-6mm while 16% had PPD of more than 6mm. Similar results were obtained for the Clinical Attachment Levels (CAL). 29.5 % subjects had CAL 2-4mm, 44.5% had 4-6mm & 26% had CAL 6mm & above. We can thus conclude that although oral health is not a priority for patients with SCD, it is supported by increased plaque accumulation. Because of the chronic anemic state of the patients with SCD, they should be encouraged to pay strict attention to oral hygiene instructions and practice.

Keywords: chronic, genetic, oral, sickle cell disease, vascular

Procedia PDF Downloads 396

Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

Abstract:

Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. That is why the need for automation of this task is urgent. A lot of studies have investigated the subject using different standard image processing descriptors and sometimes hand-crafted ones.In this work, we make a comparative study between classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN, Autoencoders, Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches

Keywords: pollens identification, features extraction, pollens classification, automated palynology

Procedia PDF Downloads 132