Search results for: disease modeling

Authors: Daniela Magalhaes, Jorge Pedro, Pedro Souteiro, Joao S. Neves, Sofia Castro-Oliveira, Vanessa Guerreiro, Rita Bettencourt- Silva, Maria M. Costa, Ana Varela, Joana Queiros, Paula Freitas, Davide Carvalho

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Introduction: Obesity is an independent risk factor for renal dysfunction. Our aims were: (1) evaluate the impact of bariatric surgery (BS) on renal function; (2) clarify the factors determining the postoperative evolution of the glomerular filtration rate (GFR); (3) access the occurrence of oxalate-mediated renal complications. Methods: We investigated a cohort of 1448 obese patients who underwent bariatric surgery. Those with basal GFR (GFR0) < 30mL/min or without information about the GFR 2-year post-surgery (GFR2) were excluded. Results: We included 725 patients, of whom 647 (89.2%) women, with 41 (IQR 34-51) years, a median weight of 112.4 (IQR 103.0-125.0) kg and a median BMI of 43.4 (IQR 40.6-46.9) kg/m2. Of these, 459 (63.3%) performed gastric bypass (RYGB), 144 (19.9%) placed an adjustable gastric band (AGB) and 122 (16.8%) underwent vertical gastrectomy (VG). At 2-year post-surgery, excess weight loss (EWL) was 60.1 (IQR 43.7-72.4) %. There was a significant improve of metabolic and inflammatory status, as well as a significant decrease in the proportion of patients with diabetes, arterial hypertension and dyslipidemia (p < 0.0001). At baseline, 38 (5.2%) of subjects had hyperfiltration with a GFR0 ≥ 125mL/min/1.73m2, 492 (67.9%) had a GFR0 90-124 mL/min/1.73m2, 178 (24.6%) had a GFR0 60-89 mL/min/1.73m2, and 17 (2.3%) had a GFR0 < 60 mL/min/1.73m2. GFR decreased in 63.2% of patients with hyperfiltration (ΔGFR=-2.5±7.6), and increased in 96.6% (ΔGFR=22.2±12.0) and 82.4% (ΔGFR=24.3±30.0) of the subjects with GFR0 60-89 and < 60 mL/min/1.73m2, respectively ( p < 0.0001). This trend was maintained when adjustment was made for the type of surgery performed. Of 321 patients, 10 (3.3%) had a urinary albumin excretion (UAE) > 300 mg/dL (A3), 44 (14.6%) had a UAE 30-300 mg/dL (A2) and 247 (82.1%) has a UAE < 30 mg/dL (A1). Albuminuria decreased after surgery and at 2-year follow-up only 1 (0.3%) patient had A3, 17 (5.6%) had A2 and 283 (94%) had A1 (p < 0,0001). In multivariate analysis, the variables independently associated with ΔGFR were BMI (positively) and fasting plasma glucose (negatively). During the 2-year follow-up, only 57 of the 725 patients had transient urinary excretion of calcium oxalate crystals. None has records of oxalate-mediated renal complications at our center. Conclusions: The evolution of GFR after BS seems to depend on the initial renal function, as it decreases in subjects with hyperfiltration, but tends to increase in those with renal dysfunction. Our results suggest that BS is associated with improvement of renal outcomes, without significant increase of renal complications. So, apart the clear benefits in metabolic and inflammatory status, maybe obese adults with nondialysis-dependent CKD should be referred for bariatric surgery evaluation.

Keywords: albuminuria, bariatric surgery, glomerular filtration rate, renal function

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Authors: Kumar Shashvat, Amol P. Bhondekar

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In the midst of the five senses, odor is the most reminiscent and least understood. Odor testing has been mysterious and odor data fabled to most practitioners. The delinquent of recognition and classification of odor is important to achieve. The facility to smell and predict whether the artifact is of further use or it has become undesirable for consumption; the imitation of this problem hooked on a model is of consideration. The general industrial standard for this classification is color based anyhow; odor can be improved classifier than color based classification and if incorporated in machine will be awfully constructive. For cataloging of odor for peas, trees and cashews various discriminative approaches have been used Discriminative approaches offer good prognostic performance and have been widely used in many applications but are incapable to make effectual use of the unlabeled information. In such scenarios, generative approaches have better applicability, as they are able to knob glitches, such as in set-ups where variability in the series of possible input vectors is enormous. Generative models are integrated in machine learning for either modeling data directly or as a transitional step to form an indeterminate probability density function. The algorithms or models Linear Discriminant Analysis and Naive Bayes Classifier have been used for classification of the odor of cashews. Linear Discriminant Analysis is a method used in data classification, pattern recognition, and machine learning to discover a linear combination of features that typifies or divides two or more classes of objects or procedures. The Naive Bayes algorithm is a classification approach base on Bayes rule and a set of qualified independence theory. Naive Bayes classifiers are highly scalable, requiring a number of restraints linear in the number of variables (features/predictors) in a learning predicament. The main recompenses of using the generative models are generally a Generative Models make stronger assumptions about the data, specifically, about the distribution of predictors given the response variables. The Electronic instrument which is used for artificial odor sensing and classification is an electronic nose. This device is designed to imitate the anthropological sense of odor by providing an analysis of individual chemicals or chemical mixtures. The experimental results have been evaluated in the form of the performance measures i.e. are accuracy, precision and recall. The investigational results have proven that the overall performance of the Linear Discriminant Analysis was better in assessment to the Naive Bayes Classifier on cashew dataset.

Keywords: odor classification, generative models, naive bayes, linear discriminant analysis

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Authors: Huseyin Guler, Cigdem Kosar

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The aim of this study is to propose Bridge estimator for seasonal unit root tests. Seasonality is an important factor for many economic time series. Some variables may contain seasonal patterns and forecasts that ignore important seasonal patterns have a high variance. Therefore, it is very important to eliminate seasonality for seasonal macroeconomic data. There are some methods to eliminate the impacts of seasonality in time series. One of them is filtering the data. However, this method leads to undesired consequences in unit root tests, especially if the data is generated by a stochastic seasonal process. Another method to eliminate seasonality is using seasonal dummy variables. Some seasonal patterns may result from stationary seasonal processes, which are modelled using seasonal dummies but if there is a varying and changing seasonal pattern over time, so the seasonal process is non-stationary, deterministic seasonal dummies are inadequate to capture the seasonal process. It is not suitable to use seasonal dummies for modeling such seasonally nonstationary series. Instead of that, it is necessary to take seasonal difference if there are seasonal unit roots in the series. Different alternative methods are proposed in the literature to test seasonal unit roots, such as Dickey, Hazsa, Fuller (DHF) and Hylleberg, Engle, Granger, Yoo (HEGY) tests. HEGY test can be also used to test the seasonal unit root in different frequencies (monthly, quarterly, and semiannual). Another issue in unit root tests is the lag selection. Lagged dependent variables are added to the model in seasonal unit root tests as in the unit root tests to overcome the autocorrelation problem. In this case, it is necessary to choose the lag length and determine any deterministic components (i.e., a constant and trend) first, and then use the proper model to test for seasonal unit roots. However, this two-step procedure might lead size distortions and lack of power in seasonal unit root tests. Recent studies show that Bridge estimators are good in selecting optimal lag length while differentiating nonstationary versus stationary models for nonseasonal data. The advantage of this estimator is the elimination of the two-step nature of conventional unit root tests and this leads a gain in size and power. In this paper, the Bridge estimator is proposed to test seasonal unit roots in a HEGY model. A Monte-Carlo experiment is done to determine the efficiency of this approach and compare the size and power of this method with HEGY test. Since Bridge estimator performs well in model selection, our approach may lead to some gain in terms of size and power over HEGY test.

Keywords: bridge estimators, HEGY test, model selection, seasonal unit root

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Authors: Stephanie Remedios, Linda Veronica Rios

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Background. Pediatric obesity is a serious health problem linked to multiple physical diseases and ailments, including diabetes, heart disease, and joint issues. While research has shown pediatric obesity can bring about an array of physical illnesses, it is less known how such a condition can affect children’s cognitive development. With childhood overweight and obesity prevalence rates on the rise, it is essential to understand the scope of their cognitive consequences. The present review of the literature tested the hypothesis that poor physical health, such as childhood obesity or malnutrition, negatively impacts a child’s cognitive development. Methodology. A systematic review was conducted to determine the relationship between poor physical health and lower cognitive functioning in children ages 4-16. Electronic databases were searched for studies dating back to ten years. The following databases were used: Science Direct, FIU Libraries, and Google Scholar. Inclusion criteria consisted of peer-reviewed academic articles written in English from 2012 to 2022 that analyzed the relationship between childhood malnutrition and obesity on cognitive development. A total of 17,000 articles were obtained, of which 16,987 were excluded for not addressing the cognitive implications exclusively. Of the acquired articles, 13 were retained. Results. Research suggested a significant connection between diet and cognitive development. Both diet and physical activity are strongly correlated with higher cognitive functioning. Cognitive domains explored in this work included learning, memory, attention, inhibition, and impulsivity. IQ scores were also considered objective representations of overall cognitive performance. Studies showed physical activity benefits cognitive development, primarily for executive functioning and language development. Additionally, children suffering from pediatric obesity or malnutrition were found to score 3-10 points lower in IQ scores when compared to healthy, same-aged children. Conclusion. This review provides evidence that the presence of physical activity and overall physical health, including appropriate diet and nutritional intake, has beneficial effects on cognitive outcomes. The primary conclusion from this research is that childhood obesity and malnutrition show detrimental effects on cognitive development in children, primarily with learning outcomes. Assuming childhood obesity and malnutrition rates continue their current trade, it is essential to understand the complete physical and psychological implications of obesity and malnutrition in pediatric populations. Given the limitations encountered through our research, further studies are needed to evaluate the areas of cognition affected during childhood.

Keywords: childhood malnutrition, childhood obesity, cognitive development, cognitive functioning

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Authors: Ibrahim Umar, Ashiru Rajab, Sumayya Chindo, Emmanuel Olashore

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INTRODUCTION: Kano is the most populous state in Nigeria and one of the two states with the highest TB burden in the country. The state notifies an average of 8,000+ TB cases quarterly and has the highest yearly notification of all the states in Nigeria from 2020 to 2022. The contribution of the state TB program to the National TB notification varies from 9% to 10% quarterly between the first quarter of 2022 and second quarter of 2023. The Kano State TB Situation Room is an innovative platform for timely data collection, collation and analysis for informed decision in health system. During the 2023 second National TB Testing week (NTBTW) Kano TB program aimed at early TB detection, prevention and treatment. The state TB Situation room provided avenue to the state for coordination and surveillance through real time data reporting, review, analysis and use during the NTBTW. OBJECTIVES: To assess the role of innovative information and communication technology platform for real-time TB reporting during second National TB Testing week in Nigeria 2023. To showcase the NTBTW data cascade analysis using TSR as innovative ICT platform. METHODOLOGY: The State TB deployed a real-time virtual dashboard for NTBTW reporting, analysis and feedback. A data room team was set up who received realtime data using google link. Data received was analyzed using power BI analytic tool with statistical alpha level of significance of <0.05. RESULTS: At the end of the week-long activity and using the real-time dashboard with onsite mentorship of the field workers, the state TB program was able to screen a total of 52,054 people were screened for TB from 72,112 individuals eligible for screening (72% screening rate). A total of 9,910 presumptive TB clients were identified and evaluated for TB leading to diagnosis of 445 TB patients with TB (5% yield from presumptives) and placement of 435 TB patients on treatment (98% percentage enrolment). CONCLUSION: The TB Situation Room (TBSR) has been a great asset to Kano State TB Control Program in meeting up with the growing demand for timely data reporting in TB and other global health responses. The use of real time surveillance data during the 2023 NTBTW has in no small measure improved the TB response and feedback in Kano State. Scaling up this intervention to other disease areas, states and nations is a positive step in the right direction towards global TB eradication.

Keywords: tuberculosis (tb), national tb testing week (ntbtw), tb situation rom (tsr), information communication technology (ict)

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Armana Huq, Wahidur Rahman, Sanwar Kader

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Inland waterways in Bangladesh play an important role in providing comfortable and low-cost transportation. However, a maritime accident takes away many lives and creates unwanted hazards every year. This article deals with a comprehensive review of inland waterway accidents in Bangladesh. Additionally, it includes a comparative study between international and local inland research studies based on maritime accidents. Articles from inland waterway areas are analyzed in-depth to make a comprehensive overview of the nature of the academic work, accident and risk management process and different statistical analyses. It is found that empirical analysis based on the available statistical data dominates the research domain. For this study, major maritime accident-related works in the last four decades in Bangladesh (1981-2020) are being analyzed for preparing a bibliometric analysis. A study of maritime accidents of passenger's vessels during (1995-2005) indicates that the predominant causes of accidents in the inland waterways of Bangladesh are collision and adverse weather (77%), out of which collision due to human error alone stands (56%) of all accidents. Another study refers that the major causes of waterway accidents are the collision (60.3%) during 2005-2015. About 92% of this collision occurs due to direct contact with another vessel during this period. Rest 8% of the collision occurs by contact with permanent obstruction on waterway roots. The overall analysis of another study from the last 25 years (1995-2019) shows that one of the main types of accidents is collisions, with about 50.3% of accidents being caused by collisions. The other accident types are cyclone or storm (17%), overload (11.3%), physical failure (10.3%), excessive waves (5.1%), and others (6%). Very few notable works are available in testing or comparing the methods, proposing new methods for risk management, modeling, uncertainty treatment. The purpose of this paper is to provide an overview of the evolution of marine accident-related research domain regarding inland waterway of Bangladesh and attempts to introduce new ideas and methods to abridge the gap between international and national inland maritime-related work domain which can be a catalyst for a safer and sustainable water transportation system in Bangladesh. Another fundamental objective of this paper is to navigate various national maritime authorities and international organizations to implement risk management processes for shipping accident prevention in waterway areas.

Keywords: inland waterways, safety, bibliometric analysis, risk management, accidents

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Authors: Sugandha Asthana, Geetika Vajpayee, Pratibha Kumari, Shanthy Sundaram

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An economically important disease of wheat in North Western region of India is Karnal Bunt caused by smut fungus Tilletia indica. This fungal pathogen spreads by air, soil and seed borne sporodia at the time of flowering, which ultimately leads to partial bunting of wheat kernels with fishy odor and taste to wheat flour. It has very serious effects due to quarantine measures which have to be applied for grain exports. Chemical fungicides such as mercurial compounds and Propiconazole applied to the control of Karnal bunt have been only partially successful. Considering the harmful effects of chemical fungicides on man as well as environment, many countries are developing biological control as the superior substitute to chemical control. Repeated use of fungicides can be responsible for the development of resistance in fungal pathogens against certain chemical compounds. The present investigation is based on the isolation and evaluation of antifungal properties of some isolated (from natural manure) and commercial bacterial strains against Tilletia indica. Total 23 bacterial isolates were obtained and antagonistic activity of all isolates and commercial bacterial strains (Bacillus subtilis MTCC8601, Bacillus pumilus MTCC 8743, Pseudomonas aeruginosa) were tested against T. indica by dual culture plate assay (pour plate and streak plate). Test for the production of antifungal volatile organic compounds (VOCs) by antagonistic bacteria was done by sealed plate method. Amongst all s1, s3, s5, and B. subtilis showed more than 80% inhibition. Production of extracellular hydrolytic enzymes such as protease, beta 1, 4 glucanase, HCN and ammonia was studied for confirmation of antifungal activity. s1, s3, s5 and B. subtilis were found to be the best for protease activity and s5 and B. subtilis for beta 1, 4 glucanase activity. Bacillus subtilis was significantly effective for HCN whereas s3, s5 and Bacillus subtilis for ammonia production. Isolates were identified as Pseudomonas aeruginosa (s1) and B. licheniformis (s3, s5) by various biochemical assays and confirmed by16s rRNA sequencing. Use of microorganisms or their secretions as biocontrol agents to avoid plant diseases is ecologically safe and may offer long term of protection to crop. The above study reports the promising effects of these strains in better pathogen free crop production and quality maintenance as well as prevention of the excessive use of synthetic fungicides.

Keywords: antagonistic, antifungal, biocontrol, Karnal bunt

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Authors: A. Schuchter, M. Promegger

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The outbreak of the COVID-19 pandemic has shown us that online education is so much more than just a cool feature for teachers – it is an essential part of modern teaching. In online math teaching, it is common to use tools to share screens, compute and calculate mathematical examples, while the students can watch the process. On the other hand, flipped classroom models are on the rise, with their focus on how students can gather knowledge by watching videos and on the teacher’s use of technological tools for information transfer. This paper proposes a co-educational teaching approach for coding and engineering subjects with the help of drone-building to spark interest in technology and create a platform for knowledge transfer. The project combines aspects from mathematics (matrices, vectors, shaders, trigonometry), physics (force, pressure and rotation) and coding (computational thinking, block-based programming, JavaScript and Python) and makes use of collaborative-shared 3D Modeling with clara.io, where students create mathematics knowhow. The instructor follows a problem-based learning approach and encourages their students to find solutions in their own time and in their own way, which will help them develop new skills intuitively and boost logically structured thinking. The collaborative aspect of working in groups will help the students develop communication skills as well as structural and computational thinking. Students are not just listeners as in traditional classroom settings, but play an active part in creating content together by compiling a Handbook of Knowledge (called “open book”) with examples and solutions. Before students start calculating, they have to write down all their ideas and working steps in full sentences so other students can easily follow their train of thought. Therefore, students will learn to formulate goals, solve problems, and create a ready-to use product with the help of “reverse engineering”, cross-referencing and creative thinking. The work on drones gives the students the opportunity to create a real-life application with a practical purpose, while going through all stages of product development.

Keywords: flipped classroom, co-creational education, coding, making, drones, co-education, ARCS-model, problem-based learning

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Authors: Aparecida De Fatima Dutra, Freddie Avant, Wilma Cordova

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People living with HIV/AIDS (PLWHA) have benefited from advances in treatment. Medical costs are a challenge for some, but the real challenge is the stigma and discrimination PLWHA continue to face, even though the disease has festered for the last four decades. Few studies regarding stigma and discrimination give voice to those affected by these practices. This study provides a voice to PLWHA in Brazil and in the US as to how they perceive stigma and discrimination, as well as services they access. The methodology of this study was designed based on phenomenological research, which is a research that aims to identify what individuals facing the same situation have to share about their experiences. Qualitative research using in- depth interviews was used in order to gather participants’ perceptions about services they access, and stigma and discrimination they experience as PLWHA (hypothesis). The target population was a minority group of 13 Afro-descendant men, mean age of 48.3, residents in East Texas, United States and Salvador, Brazil. Our findings indicate that in both countries, overall, participants have reasonable access to medication and qualified services, except for some specialties, such as dentistry. With regard to stigma and discrimination the majority of participants have not disclosed their diagnosis. They state they prefer not to disclose for fear of being ostracized and rejected. Participants who did reveal their status indicate that stigma and discrimination is a daily occurrence. These experiences tend to occur within their own families, neighborhoods, and in public health agencies where HIV/AIDS is not the focus. Participants who did offer suggestions for social change indicated they would have to reveal their status even if it means being stigmatized and discriminated against. Other factors contributing to this discrimination include skin color and poverty. This study concludes that even after decades since the spread of this epidemic, nothing has changed regarding stigma and discrimination towards PLWHA. Lack of awareness, empathy and education continue to be a major challenge, not only at a local level but across the globe. In conclusion, as documented in previous studies while stigma and discrimination towards this population prevail, negative attitudes will continue to jeopardize all individuals from receiving equal access to prevention, treatment and care. It is crucial to face stigma and discrimination not only as individual experiences, but as social practices that violate and restrict human rights and that as a result, reinforce inequality and social exclusion. Policies should be at the forefront to eliminate the stigma and discrimination PLWHA experience. Health professionals and societies must take a stand in order to promote mindfulness about the negative effect of oppression towards individuals living with HIV/AIDS and the potential global impact of these practices.

Keywords: discrimination, HIV/AIDS, human rights, stigma

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Authors: Catherine Peyrols Wu

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Intercultural interactions are becoming increasingly common in organizations and life. These interactions are often the stage of miscommunication and conflict. In management research, these problems are commonly attributed to cultural differences in values and interactional norms. As a result, the notion that intercultural competence can minimize these challenges is widely accepted. Cultural differences, however, are not the only source of a challenge during intercultural interactions. The need to rely on a lingua franca – or common language between people who have different mother tongues – is another important one. In theory, a lingua franca can improve communication and ease coordination. In practice however, disparities in people’s ability and confidence to communicate in the language can exacerbate tensions and generate inefficiencies. In this study, we draw on power theory to develop a model of disparities in language competence and conflict in a multicultural work context. Specifically, we hypothesized that differences in language competence between interaction partners would be positively related to conflict such that people would report greater conflict with partners who have more dissimilar levels of language competence and lesser conflict with partners with more similar levels of language competence. Furthermore, we proposed that cultural intelligence (CQ) an intercultural competence that denotes an individual’s capability to be effective in intercultural situations, would weaken the relationship between disparities in language competence and conflict such that people would report less conflict with partners who have more dissimilar levels of language competence when the interaction partner has high CQ and more conflict when the partner has low CQ. We tested this model with a sample of 135 undergraduate students working in multicultural teams for 13 weeks. We used a round-robin design to examine conflict in 646 dyads nested within 21 teams. Results of analyses using social relations modeling provided support for our hypotheses. Specifically, we found that in intercultural dyads with large disparities in language competence, partners with the lowest level of language competence would report higher levels of interpersonal conflict. However, this relationship disappeared when the partner with higher language competence was also high in CQ. These findings suggest that communication in a lingua franca can be a source of conflict in intercultural collaboration when partners differ in their level of language competence and that CQ can alleviate these effects during collaboration with partners who have relatively lower levels of language competence. Theoretically, this study underscores the benefits of CQ as a complement to language competence for intercultural effectiveness. Practically, these results further attest to the benefits of investing resources to develop language competence and CQ in employees engaged in multicultural work.

Keywords: cultural intelligence, intercultural interactions, language competence, multicultural teamwork

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Authors: Fikret Yalcinkaya, Hamza Unsal

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To understand how neurons work, it is required to combine experimental studies on neural science with numerical simulations of neuron models in a computer environment. In this regard, the simplicity and applicability of spiking neuron modeling functions have been of great interest in computational neuron science and numerical neuroscience in recent years. Spiking neuron models can be classified by exhibiting various neuronal behaviors, such as spiking and bursting. These classifications are important for researchers working on theoretical neuroscience. In this paper, three different spiking neuron models; Izhikevich, Adaptive Exponential Integrate Fire (AEIF) and Hindmarsh Rose (HR), which are based on first order differential equations, are discussed and compared. First, the physical meanings, derivatives, and differential equations of each model are provided and simulated in the Matlab environment. Then, by selecting appropriate parameters, the models were visually examined in the Matlab environment and it was aimed to demonstrate which model can simulate well-known biological neuron behaviours such as Tonic Spiking, Tonic Bursting, Mixed Mode Firing, Spike Frequency Adaptation, Resonator and Integrator. As a result, the Izhikevich model has been shown to perform Regular Spiking, Continuous Explosion, Intrinsically Bursting, Thalmo Cortical, Low-Threshold Spiking and Resonator. The Adaptive Exponential Integrate Fire model has been able to produce firing patterns such as Regular Ignition, Adaptive Ignition, Initially Explosive Ignition, Regular Explosive Ignition, Delayed Ignition, Delayed Regular Explosive Ignition, Temporary Ignition and Irregular Ignition. The Hindmarsh Rose model showed three different dynamic neuron behaviours; Spike, Burst and Chaotic. From these results, the Izhikevich cell model may be preferred due to its ability to reflect the true behavior of the nerve cell, the ability to produce different types of spikes, and the suitability for use in larger scale brain models. The most important reason for choosing the Adaptive Exponential Integrate Fire model is that it can create rich ignition patterns with fewer parameters. The chaotic behaviours of the Hindmarsh Rose neuron model, like some chaotic systems, is thought to be used in many scientific and engineering applications such as physics, secure communication and signal processing.

Keywords: Izhikevich, adaptive exponential integrate fire, Hindmarsh Rose, biological neuron behaviours, spiking neuron models

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Authors: Najeh Lakhoua

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Introduction: Scientific developments and techniques for the systemic approach generate several names to the systemic approach: systems analysis, systems analysis, structural analysis. The main purpose of these reflections is to find a multi-disciplinary approach which organizes knowledge, creates universal language design and controls complex sets. In fact, system analysis is structured sequentially by steps: the observation of the system by various observers in various aspects, the analysis of interactions and regulatory chains, the modeling that takes into account the evolution of the system, the simulation and the real tests in order to obtain the consensus. Thus the system approach allows two types of analysis according to the structure and the function of the system. The purpose of this paper is to present an application of system analysis of Unmanned Aerial Vehicle (UAV) components in order to represent the architecture of this system. Method: There are various analysis methods which are proposed, in the literature, in to carry out actions of global analysis and different points of view as SADT method (Structured Analysis and Design Technique), Petri Network. The methodology adopted in order to contribute to the system analysis of an Unmanned Aerial Vehicle has been proposed in this paper and it is based on the use of SADT. In fact, we present a functional analysis based on the SADT method of UAV components Body, power supply and platform, computing, sensors, actuators, software, loop principles, flight controls and communications). Results: In this part, we present the application of SADT method for the functional analysis of the UAV components. This SADT model will be composed exclusively of actigrams. It starts with the main function ‘To analysis of the UAV components’. Then, this function is broken into sub-functions and this process is developed until the last decomposition level has been reached (levels A1, A2, A3 and A4). Recall that SADT techniques are semi-formal; however, for the same subject, different correct models can be built without having to know with certitude which model is the good or, at least, the best. In fact, this kind of model allows users a sufficient freedom in its construction and so the subjective factor introduces a supplementary dimension for its validation. That is why the validation step on the whole necessitates the confrontation of different points of views. Conclusion: In this paper, we presented an application of system analysis of Unmanned Aerial Vehicle components. In fact, this application of system analysis is based on SADT method (Structured Analysis Design Technique). This functional analysis proved the useful use of SADT method and its ability of describing complex dynamic systems.

Keywords: system analysis, unmanned aerial vehicle, functional analysis, architecture

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Authors: Yi-Tung Lin

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Researchers commonly assess implicit self-esteem with the Implicit Association Test (IAT). The IAT’s measure, often referred to as the IAT effect, indicates the strengths of automatic preferences for the self relative to others, which is often considered an index of implicit self-esteem. However, based on the Dual-process theory, the IAT does not rely entirely on the automatic process; it is also influenced by a controlled process. The present study, therefore, analyzed the IAT data with the Quad model, separating four processes on the IAT performance: the likelihood that automatic association is activated by the stimulus in the trial (AC); that a correct response is discriminated in the trial (D); that the automatic bias is overcome in favor of a deliberate response (OB); and that when the association is not activated, and the individual fails to discriminate a correct answer, there is a guessing or response bias drives the response (G). The AC and G processes are automatic, while the D and OB processes are controlled. The AC parameter is considered as the strength of the association activated by the stimulus, which reflects what implicit measures of social cognition aim to assess. The stronger the automatic association between self and positive valence, the more likely it will be activated by a relevant stimulus. Therefore, the AC parameter was used as the index of implicit self-esteem in the present study. Meanwhile, the relationship between implicit self-esteem and depression is not fully investigated. In the cognitive theory of depression, it is assumed that the negative self-schema is crucial in depression. Based on this point of view, implicit self-esteem would be negatively associated with depression. However, the results among empirical studies are inconsistent. The aims of the present study were to examine the psychometric properties of the AC (i.e., test-retest reliability and its correlations with explicit self-esteem and depression) and compare it with that of the IAT effect. The present study had 105 patients with depressive disorders completing the Rosenberg Self-Esteem Scale, Beck Depression Inventory-II and the IAT on the pretest. After at least 3 weeks, the participants completed the second IAT. The data were analyzed by the latent-trait multinomial processing tree model (latent-trait MPT) with the TreeBUGS package in R. The result showed that the latent-trait MPT had a satisfactory model fit. The effect size of test-retest reliability of the AC and the IAT effect were medium (r = .43, p < .0001) and small (r = .29, p < .01) respectively. Only the AC showed a significant correlation with explicit self-esteem (r = .19, p < .05). Neither of the two indexes was correlated with depression. Collectively, the AC parameter was a satisfactory index of implicit self-esteem compared with the IAT effect. Also, the present study supported the results that implicit self-esteem was not correlated with depression.

Keywords: cognitive modeling, implicit association test, implicit self-esteem, quad model

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Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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Authors: Imran Aziz Tunio

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Islamkot is an underdeveloped sub-district (Taluka) in the Tharparkar district Sindh province of Pakistan located between latitude 24°25'19.79"N to 24°47'59.92"N and longitude 70° 1'13.95"E to 70°32'15.11"E. The Islamkot has an arid desert climate and the region is generally devoid of perennial rivers, canals, and streams. It is highly dependent on rainfall which is not considered a reliable surface water source and groundwater is the only key source of water for many centuries. To assess groundwater’s potential, an electrical resistivity survey (ERS) was conducted in Islamkot Taluka. Groundwater investigations for 128 Vertical Electrical Sounding (VES) were collected to determine the groundwater potential and obtain qualitatively and quantitatively layered resistivity parameters. The PASI Model 16 GL-N Resistivity Meter was used by employing a Schlumberger electrode configuration, with half current electrode spacing (AB/2) ranging from 1.5 to 100 m and the potential electrode spacing (MN/2) from 0.5 to 10 m. The data was acquired with a maximum current electrode spacing of 200 m. The data processing for the delineation of dune sand aquifers involved the technique of data inversion, and the interpretation of the inversion results was aided by the use of forward modeling. The measured geo-electrical parameters were examined by Interpex IX1D software, and apparent resistivity curves and synthetic model layered parameters were mapped in the ArcGIS environment using the inverse Distance Weighting (IDW) interpolation technique. Qualitative interpretation of vertical electrical sounding (VES) data shows the number of geo-electrical layers in the area varies from three to four with different resistivity values detected. Out of 128 VES model curves, 42 nos. are 3 layered, and 86 nos. are 4 layered. The resistivity of the first subsurface layers (Loose surface sand) varied from 16.13 Ωm to 3353.3 Ωm and thickness varied from 0.046 m to 17.52m. The resistivity of the second subsurface layer (Semi-consolidated sand) varied from 1.10 Ωm to 7442.8 Ωm and thickness varied from 0.30 m to 56.27 m. The resistivity of the third subsurface layer (Consolidated sand) varied from 0.00001 Ωm to 3190.8 Ωm and thickness varied from 3.26 m to 86.66 m. The resistivity of the fourth subsurface layer (Silt and Clay) varied from 0.0013 Ωm to 16264 Ωm and thickness varied from 13.50 m to 87.68 m. The Dar Zarrouk parameters, i.e. longitudinal unit conductance S is from 0.00024 to 19.91 mho; transverse unit resistance T from 7.34 to 40080.63 Ωm2; longitudinal resistance RS is from 1.22 to 3137.10 Ωm and transverse resistivity RT from 5.84 to 3138.54 Ωm. ERS data and Dar Zarrouk parameters were mapped which revealed that the study area has groundwater potential in the subsurface.

Keywords: electrical resistivity survey, GIS & RS, groundwater potential, environmental assessment, VES

Procedia PDF Downloads 81

Authors: Esra Yuce, Isil D. S. Yamaner, Murude Yazan

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Aims and objective: Antiresorptive agents including bisphosphonates and denosumab as strong suppressors of osteoclasts are the most commonly used antiresorptive medications for the treatment of osteoporosis which counteract the negative quantitative alteration of trabecular and cortical bone by inhibition of bone turnover. Oral bisphosphonate therapy for the treatment of osteopenia, osteoporosis or Paget's disease is associated with the low-grade risk of osteonecrosis of the jaw, while higher-grade risk is associated with receiving intravenous bisphosphonates therapy in the treatment of multiple myeloma and bone metastases. On the other hand, there has been a remarkable increase in incidences of antiresorptive related osteonecrosis of the jaw (ARONJ) in oral bisphosphonate users. This clinical presentation will evaluate the healing outcomes via piezoelectric bone surgery under the irrigation of PVP-I solution irrigation in patients received bisphosphonate therapy. Material-Method: The study involved 8 female and 5 male patients that have been treated for ARONJ. Among 13 necrotic sites, 9 were in the mandible and 4 were in the maxilla. All of these 13 patients treated with surgical debridement via piezoelectric bone surgery under irrigation by solution with 3% PVP-I concentration in combination with long-term antibiotic therapy and 5 also underwent removal of mobile segments of bony sequestrum. All removable prosthesis in 8 patients were relined with soft liners during the healing periods in order to eliminate chronic minor traumas. Results: All patients were on oral bisphosphonate therapy for at least 2 years and 5 of which had received intravenous bisphosphonates up to 1 year before therapy with oral bisphosphonates was started. According to the AAOMS staging system, four cases were stage II, eight cases were stage I, and one case was stage III. The majority of lesions were identified at sites of dental prostheses (38%) and dental extractions (62%). All patients diagnosed with ARONJ stage I had used unadjusted removable prostheses. No recurrence of the symptoms was observed during the present follow-up (9–37 months). Conclusion: Despite their confirmed effectiveness, the prevention and treatment of osteonecrosis of the jaw secondary to oral bisphosphonate therapy remain major medical challenges. Treatment with piezoelectric bone surgery with irrigation of povidone-iodine solution was effective for management of bisphosphonate-related osteonecrosis of the jaw. Taking precautions for patients treated with oral bisphosphonates, especially also denture users, may allow for a reduction in the rate of developing osteonecrosis of the maxillofacial region.

Keywords: antiresorptive drug related osteonecrosis, bisphosphonate therapy, piezoelectric bone surgery, povidone iodine

Procedia PDF Downloads 253

Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Gundula Bartzke, Hans-Peter Piepho

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Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available, making it necessary to predict rainfall values for particular locations through time. Predicting rainfall in space and time can be a complex and challenging task, especially where the rain gauge network is sparse and measurements are not recorded consistently for all rain gauges, leading to many missing values. Here, we develop a flexible Bayesian model for predicting rainfall in space and time and apply it to Narok County, situated in southwestern Kenya, using data collected at 23 rain gauges from 1965 to 2015. Narok County encompasses the Maasai Mara ecosystem, the northern-most section of the Mara-Serengeti ecosystem, famous for its diverse and abundant large mammal populations and spectacular migration of enormous herds of wildebeest, zebra and Thomson's gazelle. The model incorporates geographical and meteorological predictor variables, including elevation, distance to Lake Victoria and minimum temperature. We assess the efficiency of the model by comparing it empirically with the established Gaussian process, Kriging, simple linear and Bayesian linear models. We use the model to predict total monthly rainfall and its standard error for all 5 * 5 km grid cells in Narok County. Using the Monte Carlo integration method, we estimate seasonal and annual rainfall and their standard errors for 29 sub-regions in Narok. Finally, we use the predicted rainfall to predict large herbivore biomass in the Maasai Mara ecosystem on a 5 * 5 km grid for both the wet and dry seasons. We show that herbivore biomass increases with rainfall in both seasons. The model can handle data from a sparse network of observations with many missing values and performs at least as well as or better than four established and widely used models, on the Narok data set. The model produces rainfall predictions consistent with expectation and in good agreement with the blended station and satellite rainfall values. The predictions are precise enough for most practical purposes. The model is very general and applicable to other variables besides rainfall.

Keywords: non-stationary covariance function, gaussian process, ungulate biomass, MCMC, maasai mara ecosystem

Procedia PDF Downloads 283

Authors: Aloke Bapli, Debabrata Seth

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Graphene oxide (GO) is the two-dimensional (2D) nanoscale allotrope of carbon having several physiochemical properties such as high mechanical strength, high surface area, strong thermal and electrical conductivity makes it an important candidate in various modern applications such as drug delivery, supercapacitors, sensors etc. GO has been used in the photothermal treatment of cancers and Alzheimer’s disease etc. The main idea to choose GO in our work is that it is a surface active molecule, it has a large number of hydrophilic functional groups such as carboxylic acid, hydroxyl, epoxide on its surface and in basal plane. So it can easily interact with organic fluorophores through hydrogen bonding or any other kind of interaction and easily modulate the photophysics of the probe molecules. We have used different spectroscopic techniques for our work. The Ground-state absorption spectra and steady-state fluorescence emission spectra were measured by using UV-Vis spectrophotometer from Shimadzu (model-UV-2550) and spectrofluorometer from Horiba Jobin Yvon (model-Fluoromax 4P) respectively. All the fluorescence lifetime and anisotropy decays were collected by using time-correlated single photon counting (TCSPC) setup from Edinburgh instrument (model: LifeSpec-II, U.K.). Herein, we described the photophysics of a hydrophilic molecule 7-(n,n׀-diethylamino) coumarin-3-carboxylic acid (7-DCCA) in the reverse micelles containing GO. It was observed that photophysics of dye is modulated in the presence of GO compared to photophysics of dye in the absence of GO inside the reverse micelles. Here we have reported the solvent relaxation and rotational relaxation time in GO containing reverse micelle and compare our work with normal reverse micelle system by using 7-DCCA molecule. Normal reverse micelle means reverse micelle in the absence of GO. The absorption maxima of 7-DCCA were blue shifted and emission maxima were red shifted in GO containing reverse micelle compared to normal reverse micelle. The rotational relaxation time in GO containing reverse micelle is always faster compare to normal reverse micelle. Solvent relaxation time, at lower w₀ values, is always slower in GO containing reverse micelle compare to normal reverse micelle and at higher w₀ solvent relaxation time of GO containing reverse micelle becomes almost equal to normal reverse micelle. Here emission maximum of 7-DCCA exhibit bathochromic shift in GO containing reverse micelles compared to that in normal reverse micelles because in presence of GO the polarity of the system increases, as polarity increases the emission maxima was red shifted an average decay time of GO containing reverse micelle is less than that of the normal reverse micelle. In GO containing reverse micelle quantum yield, decay time, rotational relaxation time, solvent relaxation time at λₑₓ=375 nm is always higher than λₑₓ=405 nm, shows the excitation wavelength dependent photophysics of 7-DCCA in GO containing reverse micelles.

Keywords: photophysics, reverse micelle, rotational relaxation, solvent relaxation

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Authors: George Pavlidis, Ana Vivas

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The demographic change into an aging population has stimulated the examination of seniors’ mental health and ability to live independently. The corresponding literature depicts the relation between cognitive decline and everyday functionality with aging, focusing largely in individuals that are reaching or have bridged the threshold of various forms of neuropathology and disability. In this context, recent meta-analysis depicts a moderate relation between cognitive performance and everyday functionality in AD sufferers. However, there has not been an analogous effort for the examination of this relation in the healthy spectrum of aging (i.e, in samples that are not challenged from a neurodegenerative disease). There is a consensus that the assessment tools designed to detect neuropathology with those that assess cognitive performance in healthy adults are distinct, thus their universal use in cognitively challenged and in healthy adults is not always valid. The same accounts for the assessment of everyday functionality. In addition, it is argued that everyday functionality should be examined with cultural adjusted assessment tools, since many vital everyday tasks are heterotypical among distinct cultures. Therefore, this study was set out to examine the relation between cognitive performance and everyday functionality a) in the healthy spectrum of aging and b) by adjusting the everyday functionality tools EPT and OTDL-R in the Greek cultural context. In Greece, 107 cognitively healthy seniors ( Mage = 62.24) completed a battery of neuropsychological tests and everyday functionality tests. Both were carefully chosen to be sensitive in fluctuations of performance in the healthy spectrum of cognitive performance and everyday functionality. The everyday functionality assessment tools were modified to reflect the local cultural context (i.e., EPT-G and OTDL-G). The results depicted that performance in all everyday functionality measures decline with age (.197 < r > .509). Statistically significant correlations emerged between cognitive performance and everyday functionality assessments that range from r =0.202 to r=0.510. A series of independent regression analysis including the scores of cognitive assessments has yield statistical significant models that explained 20.9 < AR2 > 32.4 of the variance in everyday functionality scored indexes. All everyday functionality measures were independently predicted by the TMT B-A index, and indicator of executive function. Stepwise regression analyses depicted that TMT B-A and age were statistically significant independent predictors of EPT-G and OTDL-G. It was concluded that everyday functionality is declining with age and that cognitive performance and everyday functional may be related in the healthy spectrum of aging. Age seems not to be the sole contributing factor in everyday functionality decline, rather executive control as well. Moreover, it was concluded that the EPT-G and OTDL-G are valuable tools to assess everyday functionality in Greek seniors that are not cognitively challenged, especially for research purposes. Future research should examine the contributing factors of a better cognitive vitality especially in executive control, as vital for the maintenance of independent living capacity with aging.

Keywords: cognition, everyday functionality, aging, cognitive decline, healthy aging, Greece

Procedia PDF Downloads 515

Authors: Tatsuya Yamazaki, Kazuya Miyakawa, Tomohiko Sugiyama, Toshitaka Iwatani

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The introduction of sensor technologies into agriculture is a necessary step to realize Precision Agriculture. Although sensing methodologies themselves have been prevailing owing to miniaturization and reduction in costs of sensors, there are some difficulties to analyze and understand the sensing data. Targeting at pears ’Le Lectier’, which is particular to Niigata in Japan, cultivation environmental data have been collected at pear fields by eight sorts of sensors: field temperature, field humidity, rain gauge, soil water potential, soil temperature, soil moisture, inner-bag temperature, and inner-bag humidity sensors. With regard to the inner-bag temperature and humidity sensors, they are used to measure the environment inside the fruit bag used for pre-harvest bagging of pears. In this experiment, three kinds of fruit bags were used for the pre-harvest bagging. After over 100 days continuous measurement, volumes of sensing data have been collected. Firstly, correlation analysis among sensing data measured by respective sensors reveals that one sensor can replace another sensor so that more efficient and cost-saving sensing systems can be proposed to pear farmers. Secondly, differences in characteristic and performance of the three kinds of fruit bags are clarified by the measurement results by the inner-bag environmental sensing. It is found that characteristic and performance of the inner-bags significantly differ from each other by statistical analysis. Lastly, a relational model between the sensing data and the pear outlook quality is established by use of Structural Equation Model (SEM). Here, the pear outlook quality is related with existence of stain, blob, scratch, and so on caused by physiological impair or diseases. Conceptually SEM is a combination of exploratory factor analysis and multiple regression. By using SEM, a model is constructed to connect independent and dependent variables. The proposed SEM model relates the measured sensing data and the pear outlook quality determined on the basis of farmer judgement. In particularly, it is found that the inner-bag humidity variable relatively affects the pear outlook quality. Therefore, inner-bag humidity sensing might help the farmers to control the pear outlook quality. These results are supported by a large quantity of inner-bag humidity data measured over the years 2014, 2015, and 2016. The experimental and analytical results in this research contribute to spreading Precision Agriculture technologies among the farmers growing ’Le Lectier’.

Keywords: precision agriculture, pre-harvest bagging, sensor fusion, structural equation model

Procedia PDF Downloads 298

Authors: Josiah Damisa, Michelle Louise Richardson, Morenike Adewuyi

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Lower back pain is a significant cause of disability worldwide and associated with great implications in terms of the well-being of affected individuals and society as a whole due to its undeniable socio-economic impact. With its prevalence on the increase as a result of an aging global population, the need for novel forms of pain management is ever paramount. This review aims to provide further insight into current research regarding a role for the endocannabinoid signaling pathway as a target in the treatment of chronic pain, with particular emphasis on its potential use as part of the treatment of lower back pain. Potential advantages and limitations of cannabis-based medicines over other forms of analgesia currently licensed for medical use are discussed in addition to areas that require ongoing consideration and research. To evaluate the efficacy of cannabis-based medicines in chronic pain, studies pertaining to the role of medical cannabis in chronic disease were reviewed. Standard searches of PubMed, Google Scholar and Web of Science databases were undertaken with peer-reviewed journal articles reviewed based on the indication for pain management, cannabis treatment modality used and study outcomes. Multiple studies suggest an emerging role for cannabis-based medicines as therapeutic agents in the treatment of chronic back pain. A potential synergistic effect has also been purported if these medicines are co-administered with opiate analgesia due to the similarity of the opiate and endocannabinoid signaling pathways. However, whilst recent changes to legislation in the United Kingdom mean that cannabis is now licensed for medicinal use on NHS prescription for a number of chronic health conditions, concerns remain as to the efficacy and safety of cannabis-based medicines. Research is lacking into both their side effect profiles and the long-term effects of cannabis use. Legal and ethical considerations to the use of these products in standardized medical practice also persist due to the notoriety of cannabis as a drug of abuse. Despite this, cannabis is beginning to gain traction as an alternative or even complementary drug to opiates, with some preclinical studies showing opiate-sparing effects. Whilst there is a paucity of clinical trials in this field, there is scope for cannabinoids to be successful anti-nociceptive agents in managing chronic back pain. The ultimate aim would be to utilize cannabis-based medicines as alternative or complementary therapies, thereby reducing opiate over-reliance and providing hope to individuals who have exhausted all other forms of standard treatment.

Keywords: endocannabinoids, cannabis-based medicines, chronic pain, lower back pain

Procedia PDF Downloads 189

Authors: Yuliya Huseva

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To investigate the contents of tears to determine latent blood. Methods: Tear samples from 72 women were studied with the microscopy of tears aspirated with a capillary and stained by Nocht and with a chemical method of test strips with chromogen. Statistical data processing was carried out using statistical packages Statistica 10.0 for Windows, calculation of Pearson's chi-square test, Yule association coefficient, the method of determining sensitivity and specificity. Results:, In 30.6% (22) of tear samples erythrocytes were revealed microscopically. Correlations between the presence of erythrocytes in the tear and the phase of the menstrual cycle has been discovered. In the follicular phase of the cycle, erythrocytes were found in 59.1% (13) people, which is significantly more (x2=4.2, p=0.041) compared to the luteal phase - in 40.9% (9) women. In the first seven days of the follicular phase of the menstrual cycle the erythrocytes were predominanted of in the tears of women examined testifies in favour of the vicarious bleeding from the mucous membranes of extragenital organs in sync with menstruation. Of the other cellular elements in tear samples with latent haemolacria, neutrophils prevailed - in 45.5% (10), while lymphocytes were less common - in 27.3% (6), because neutrophil exudation is accompanied by vasodilatation of the conjunctiva and the release of erythrocytes into the conjunctival cavity. It was found that the prognostic significance of the chemical method was 0.53 of the microscopic method. In contrast to microscopy, which detected blood in tear samples from 30.6% (22) of women, blood was detected chemically in tears of 16.7% (12). An association between latent haemolacria and endometriosis was found (k=0.75, p≤0.05). Microscopically, in the tears of patients with endometriosis, erythrocytes were detected in 70% of cases, while in healthy women without endometriosis - in 25% of cases. The proportion of women with erythrocytes in tears, determined by a chemical method, was 41.7% among patients with endometriosis, which is significantly more (x2=6.5, p=0.011) than 11.7% among women without endometriosis. The data obtained can be explained by the etiopathogenesis of the extragenital endometriosis which is caused by hematogenous spread of endometrial tissue into the orbit. In endometriosis, erythrocytes are found against the background of accumulations of epithelial cells. In the tear samples of 4 women with endometriosis, glandular cuboidal epithelial cells, morphologically similar to endometrial cells, were found, which may indicate a generalization of the disease. Conclusions: Single erythrocytes can normally be found in the tears, their number depends on the phase of the menstrual cycle, increasing in the follicular phase. Erythrocytes found in tears against the background of accumulations of epitheliocytes and their glandular atypia may indicate a manifestation of extragenital endometriosis. Both used methods (microscopic and chemical) are informative in revealing latent haemolacria. The microscopic method is more sensitive, reveals intact erythrocytes, and besides, it provides information about other cells. At the same time, the chemical method is faster and technically simpler, it determines the presence of haemoglobin and its metabolic products, and can be used as a screening.

Keywords: tear, blood, microscopy, epitheliocytes

Procedia PDF Downloads 113

Authors: Marlin Mubarak

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Background: Endometriosis is a complex disabling disease affecting young females in the reproductive period mainly. The aim of this project is to generate a diagnostic model to predict severity and stage of endometriosis prior to Laparoscopic surgery. This will help to improve the pre-operative diagnostic accuracy of stage 3 & 4 endometriosis and as a result, refer relevant women to a specialist centre for complex Laparoscopic surgery. The model is based on the British Society of Gynaecological Endoscopy (BSGE) pain questionnaire, clinical examination and ultrasound scan. Design: This is a prospective, observational, study, in which women completed the BSGE pain questionnaire, a BSGE requirement. Also, as part of the routine preoperative assessment patient had a routine ultrasound scan and when recto-vaginal and deep infiltrating endometriosis was suspected an MRI was performed. Setting: Luton & Dunstable University Hospital. Patients: Symptomatic women (n = 56) scheduled for laparoscopy due to pelvic pain. The age ranged between 17 – 52 years of age (mean 33.8 years, SD 8.7 years). Interventions: None outside the recognised and established endometriosis centre protocol set up by BSGE. Main Outcome Measure(s): Sensitivity and specificity of endometriosis diagnosis predicted by symptoms based on BSGE pain questionnaire, clinical examinations and imaging. Findings: The prevalence of diagnosed endometriosis was calculated to be 76.8% and the prevalence of advanced stage was 55.4%. Deep infiltrating endometriosis in various locations was diagnosed in 32/56 women (57.1%) and some had DIE involving several locations. Logistic regression analysis was performed on 36 clinical variables to create a simple clinical prediction model. After creating the scoring system using variables with P < 0.05, the model was applied to the whole dataset. The sensitivity was 83.87% and specificity 96%. The positive likelihood ratio was 20.97 and the negative likelihood ratio was 0.17, indicating that the model has a good predictive value and could be useful in predicting advanced stage endometriosis. Conclusions: This is a hypothesis-generating project with one operator, but future proposed research would provide validation of the model and establish its usefulness in the general setting. Predictive tools based on such model could help organise the appropriate investigation in clinical practice, reduce risks associated with surgery and improve outcome. It could be of value for future research to standardise the assessment of women presenting with pelvic pain. The model needs further testing in a general setting to assess if the initial results are reproducible.

Keywords: deep endometriosis, endometriosis, minimally invasive, MRI, ultrasound.

Procedia PDF Downloads 339

Authors: Farahnaz Amini, Woo Yun Kin, Lazwani Kolandaiveloo

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Availability of different genetic tests after completion of Human Genome Project increases the physicians’ responsibility to keep themselves update on the potential implementation of these genetic tests in their daily practice. However, due to numbers of barriers, still many of physicians are not either aware of these tests or are not willing to offer or refer their patients for genetic tests. This study was conducted an anonymous, cross-sectional, mailed-based survey to develop a primary data of Malaysian physicians’ level of knowledge and perception of gene profiling. Questionnaire had 29 questions. Total scores on selected questions were used to assess the level of knowledge. The highest possible score was 11. Descriptive statistics, one way ANOVA and chi-squared test was used for statistical analysis. Sixty three completed questionnaires was returned by 27 general practitioners (GPs) and 36 medical specialists. Responders’ age range from 24 to 55 years old (mean 30.2 ± 6.4). About 40% of the participants rated themselves as having poor level of knowledge in genetics in general whilst 60% believed that they have fair level of knowledge. However, almost half (46%) of the respondents felt that they were not knowledgeable about available genetic tests. A majority (94%) of the responders were not aware of any lab or company which is offering gene profiling services in Malaysia. Only 4% of participants were aware of using gene profiling for detection of dosage of some drugs. Respondents perceived greater utility of gene profiling for breast cancer (38%) compared to the colorectal familial cancer (3%). The score of knowledge ranged from 2 to 8 (mean 4.38 ± 1.67). Non-significant differences between score of knowledge of GPs and specialists were observed, with score of 4.19 and 4.58 respectively. There was no significant association between any demographic factors and level of knowledge. However, those who graduated between years 2001 to 2005 had higher level of knowledge. Overall, 83% of participants showed relatively high level of perception on value of gene profiling to detect patient’s risk of disease. However, low perception was observed for both statements of using gene profiling for general population in order to alter their lifestyle (25%) as well as having the full sequence of a patient genome for the purpose of determining a patient’s best match for treatment (18%). The lack of clinical guidelines, limited provider knowledge and awareness, lack of time and resources to educate patients, lack of evidence-based clinical information and cost of tests were the most barriers of ordering gene profiling mentioned by physicians. In conclusion Malaysian physicians who participate in this study had mediocre level of knowledge and awareness in gene profiling. The low exposure to the genetic questions and problems might be a key predictor of lack of awareness and knowledge on available genetic tests. Educational and training workshop might be useful in helping Malaysian physicians incorporate genetic profiling into practice for eligible patients.

Keywords: gene profiling, knowledge, Malaysia, physician

Procedia PDF Downloads 319

Authors: Dosun Shin, Assegid Kidane, Pavan Turaga

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According to the National Institute of Health, living a sedentary lifestyle leads to a number of health issues, including increased risk of cardiovascular dis-ease, type 2 diabetes, obesity, and certain types of cancers. This project brings together experts in multiple disciplines to bring product design, sensor design, algorithms, and health intervention studies to develop a product and system that helps reduce the amount of time sitting at the workplace. This paper illustrates ongoing improvements to prototypes the research team developed in initial research; including working prototypes with a software application, which were developed and demonstrated for users. Additional modifications were made to improve functionality, aesthetics, and ease of use, which will be discussed in this paper. Extending on the foundations created in the initial phase, our approach sought to further improve the product by conducting additional human factor research, studying deficiencies in competitive products, testing various materials/forms, developing working prototypes, and obtaining feedback from additional potential users. The solution consisted of an aesthetically pleasing seat cover cushion that easily attaches to common office chairs found in most workplaces, ensuring a wide variety of people can use the product. The product discreetly contains sensors that track when the user sits on their chair, sending information to a phone app that triggers reminders for users to stand up and move around after sitting for a set amount of time. This paper also presents the analyzed typical office aesthetics and selected materials, colors, and forms that complimented the working environment. Comfort and ease of use remained a high priority as the design team sought to provide a product and system that integrated into the workplace. As the research team continues to test, improve, and implement this solution for the sedentary workplace, the team seeks to create a viable product that acts as an impetus for a more active workday and lifestyle, further decreasing the proliferation of chronic disease and health issues for sedentary working people. This paper illustrates in detail the processes of engineering, product design, methodology, and testing results.

Keywords: anti-sedentary work behavior, new product development, sensor design, health intervention studies

Procedia PDF Downloads 146

Authors: Michelle Rippy

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Medicolegal death investigation historically is a field that does not receive much research attention or advancement, as all of the subjects are deceased. Public health threats, drug epidemics and contagious diseases are typically recognized in decedents first, with thorough and accurate death investigations able to assist in epidemiology research and prevention programs. One vital component of medicolegal death investigation is determining the decedent’s time of death. An accurate time of death can assist in corroborating alibies, determining sequence of death in multiple casualty circumstances and provide vital facts in civil situations. Popular television portrays an unrealistic forensic ability to provide the exact time of death to the minute for someone found deceased with no witnesses present. The actuality of unattended decedent time of death determination can generally only be narrowed to a 4-6 hour window. In the mid- to late-20th century, liver temperatures were an invasive action taken by death investigators to determine the decedent’s core temperature. The core temperature was programmed into an equation to determine an approximate time of death. Due to many inconsistencies with the placement of the thermometer and other variables, the accuracy of the liver temperatures was dispelled and this once common place action lost scientific support. Currently, medicolegal death investigators utilize three major after death or post-mortem changes at a death scene. Many factors are considered in the subjective determination as to the time of death, including the cooling of the decedent, stiffness of the muscles, release of blood internally, clothing, ambient temperature, disease and recent exercise. Current research is utilizing non-invasive hospital grade tympanic thermometers to measure the temperature in the each of the decedent’s ears. This tool can be used at the scene and in conjunction with scene indicators may provide a more accurate time of death. The research is significant and important to investigations and can provide an area of accuracy to a historically inaccurate area, considerably improving criminal and civil death investigations. The goal of the research is to provide a scientific basis to unwitnessed deaths, instead of the art that the determination currently is. The research is currently in progress with expected termination in December 2018. There are currently 15 completed case studies with vital information including the ambient temperature, decedent height/weight/sex/age, layers of clothing, found position, if medical intervention occurred and if the death was witnessed. This data will be analyzed with the multiple variables studied and available for presentation in January 2019.

Keywords: algor mortis, forensic pathology, investigations, medicolegal, time of death, tympanic

Procedia PDF Downloads 107

Authors: Mballa Abanda Luc Aurelien Serge, Henda Gnakate Biba, Kuate Guemo Romaric, Akono Rufine Nicole, Zabotom Yaya Fadel Biba, Petfiang Sidonie, Bella Suzane Jenifer

Abstract:

The main hypotheses proposed around the definition of the syllable and of music, of the common origin of music and language, should lead the reader to reflect on the cross-cutting questions raised by the debate on the notion of universals in linguistics and musicology. These are objects of controversy, and there lies its interest: the debate raises questions that are at the heart of theories on language. It is an inventive, original, and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological, and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation, and the question of modeling in the human sciences: mathematics, computer science, translation automation, and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal, and random music. The experimentation confirming the theorization, I designed a semi-digital, semi-analog application that translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music, and deterministic and random music). To test this application, I use music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). The translation is done (from writing to writing, from writing to speech, and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz, and world music or variety, etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: language, music, sciences, quantum entenglement

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Authors: Ramin Mehdiabadi, Neda Menbari, Mohammad Nazir Menbari

Abstract:

As a pressing public health concern, breast cancer stands as the predominant oncological diagnosis and principal cause of cancer-related mortality among women globally, accounting for 11.7% of new cancer incidences and 6.9% of cancer-related deaths. The annual figures indicate that approximately 230,480 women are diagnosed with breast cancer in the United States alone, with 39,520 succumbing to the disease. While developed economies have reported a deceleration in both incidence and mortality rates across various forms of cancer, including breast cancer, emerging and low-income economies manifest a contrary escalation, largely attributable to lifestyle-mediated risk factors such as tobacco usage, physical inactivity, and high caloric intake. Breast cancer is distinctly characterized by molecular heterogeneity, manifesting in specific subtypes delineated by biomarkers—Estrogen Receptors (ER), Progesterone Receptors (PR), and Human Epidermal Growth Factor Receptor 2 (HER2). These subtypes, comprising Luminal A, Luminal B, HER2-enriched, triple-negative/basal-like, and normal-like, necessitate nuanced, subtype-specific therapeutic regimens, thereby challenging the applicability of generalized treatment protocols. Within this molecular complexity, the transcription factor Forkhead Box M1 (FoxM1) has garnered attention as a significant driver of cellular proliferation, tumorigenesis, metastatic progression, and treatment resistance in a spectrum of human malignancies, including breast cancer. Concurrently, microRNAs (miRs), specifically miR-216b-5p, have been identified as post-transcriptional gene expression regulators and potential tumor suppressors. The overarching objective of this academic investigation is to explicate the multifaceted interrelationship between FoxM1 and miR-216b-5p across the disparate molecular subtypes of breast cancer. Employing a methodologically rigorous, interdisciplinary research design that incorporates cutting-edge molecular biology techniques, sophisticated bioinformatics analytics, and exhaustive meta-analyses of extant clinical data, this scholarly endeavor aims to unveil novel biomarker-specific therapeutic pathways. By doing so, this research is positioned to make a seminal contribution to the advancement of personalized, efficacious, and minimally toxic treatment paradigms, thus profoundly impacting the global efforts to ameliorate the burden of breast cancer.

Keywords: breast cancer, fox m1, microRNAs, mir-216b-5p, gene expression

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Authors: Tzu-Ting Hu, Jung-Der Wang, Ming-Yeng Lin, Jin-Luh Chen, Perng-Jy Tsai

Abstract:

The vinyl chloride monomer (VCM) has been classified as group 1 (human) carcinogen by the IARC. Workers exposed to VCM are known associated with the development of the liver cancer and hence might cause economical and health losses. Particularly, for those work for the petrochemical industry have been seriously concerned in the environmental and occupational health field. Considering assessing workers’ health risks and their resultant economical and health losses requires the establishment of long-term VCM exposure data for any similar exposure group (SEG) of interest, the development of suitable technologies has become an urgent and important issue. In the present study, VCM exposures for petrochemical industry workers were determined firstly based on the database of the 'Workplace Environmental Monitoring Information Systems (WEMIS)' provided by Taiwan OSHA. Considering the existence of miss data, the reconstruction of historical exposure techniques were then used for completing the long-term exposure data for SEGs with routine operations. For SEGs with non-routine operations, exposure modeling techniques, together with their time/activity records, were adopted for determining their long-term exposure concentrations. The Bayesian decision analysis (BDA) was adopted for conducting exposure and health risk assessments for any given SEG in the petrochemical industry. The resultant excessive cancer risk was then used to determine the corresponding loss of quality-adjusted life expectancy (QALE). Results show that low average concentrations can be found for SEGs with routine operations (e.g., VCM rectification 0.0973 ppm, polymerization 0.306 ppm, reaction tank 0.33 ppm, VCM recovery 1.4 ppm, control room 0.14 ppm, VCM storage tanks 0.095 ppm and wastewater treatment 0.390 ppm), and the above values were much lower than that of the permissible exposure limit (PEL; 3 ppm) of VCM promulgated in Taiwan. For non-routine workers, though their high exposure concentrations, their low exposure time and frequencies result in low corresponding health risks. Through the consideration of exposure assessment results, health risk assessment results, and QALE results simultaneously, it is concluded that the proposed method was useful for prioritizing SEGs for conducting exposure abatement measurements. Particularly, the obtained QALE results further indicate the importance of reducing workers’ VCM exposures, though their exposures were low as in comparison with the PEL and the acceptable health risk.

Keywords: exposure assessment, health risk assessment, petrochemical industry, quality-adjusted life years, vinyl chloride monomer

Procedia PDF Downloads 183