Search results for: adaptive threshold

Authors: J. Hash, J. Converse, L. Gibson

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Plant medicines are of growing interest for addressing mental health concerns. Ayahuasca, a traditional plant-based medicine, has established itself as a powerful way of processing trauma and precipitating healing and mood stabilization. Eye Movement Desensitization and Reprocessing (EMDR) is another treatment modality that aids in the rapid processing and resolution of trauma. We investigated group EMDR therapy, G-TEP, as a preparatory practice before Ayahuasca ceremonies to determine if the combination of these modalities supports participants in their journeys of letting go of past experiences negatively impacting mental health, thereby accentuating the healing of the plant medicine. We surveyed 96 participants (51 experimental G-TEP, 45 control grounding prior to their ceremony; age M=38.6, SD=9.1; F=57, M=34; white=39, Hispanic/Latinx=23, multiracial=11, Asian/Pacific Islander=10, other=7) in a pre-post, mixed methods design. Participants were surveyed for demographic characteristics, symptoms of PTSD and cPTSD (International Trauma Questionnaire (ITQ), depression (Beck Depression Inventory, BDI), and stress (Perceived Stress Scale, PSS) before the ceremony and at the end of the ceremony weekend. Open-ended questions also inquired about their expectations of the ceremony and results at the end. No baseline differences existed between the control and experimental participants. Overall, participants reported a decrease in meeting the threshold for PTSD symptoms (p<0.01); surprisingly, the control group reported significantly fewer thresholds met for symptoms of affective dysregulation, 2(1)=6.776, p<.01, negative self-concept, 2 (1)=7.122, p<.01, and disturbance in relationships, 2 (1)=9.804, p<.01, on subscales of the ITQ as compared to the experimental group. All participants also experienced a significant decrease in scores on the BDI, t(94)=8.995, p<.001, and PSS, t(91)=6.892, p<.001. Similar to patterns of PTSD symptoms, the control group reported significantly lower scores on the BDI, t(65.115)=-2.587, p<.01, and a trend toward lower PSS, t(90)=-1.775, p=.079 (this was significant with a one-sided test at p<.05), compared to the experimental group following the ceremony. Qualitative interviews among participants revealed a potential explanation for these relatively higher levels of depression and stress in the experimental group following the ceremony. Many participants reported needing more time to process their experience to gain an understanding of the effects of the Ayahuasca medicine. Others reported a sense of hopefulness and understanding of the sources of their trauma and the necessary steps to heal moving forward. This suggests increased introspection and openness to processing trauma, therefore making them more receptive to their emotions. The integration process of an Ayahuasca ceremony is a week- to months-long process that was not accessible in this stage of research, yet it is an integral process to understanding the full effects of the Ayahuasca medicine following the closure of a ceremony. Our future research aims to assess participants weeks into their integration process to determine the effectiveness of EMDR, and if the higher levels of depression and stress indicate the initial reaction to greater awareness of trauma and receptivity to healing.

Keywords: ayahuasca, EMDR, PTSD, mental health

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Authors: Nupur A. D., Miah M. S., Moniruzzaman S. K.

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Autism is a neurobiological disorder that affects physical, social, and language skills of a person. A child with autism feels difficulty for processing, integrating, and responding to sensory stimuli. Current estimates have shown that 45% to 96 % of children with Autism Spectrum Disorder demonstrate sensory difficulties. As autism is a worldwide burning issue, it has become a highly prioritized and important service provision in Bangladesh. The sensory deficit does not only hamper the normal development of a child, it also hampers the learning process and functional independency. The purpose of this study was to find out the prevalence of sensory dysfunction among children with autism and recognize common patterns of sensory dysfunction. A cross-sectional study design was chosen to carry out this research work. This study enrolled eighty children with autism and their parents by using the systematic sampling method. In this study, data were collected through the Short Sensory Profile (SSP) assessment tool, which consists of 38 items in the questionnaire, and qualified graduate Occupational Therapists were directly involved in interviewing parents as well as observing child responses to sensory related activities of the children with autism from four selected autism centers in Dhaka, Bangladesh. All item analyses were conducted to identify items yielding or resulting in the highest reported sensory processing dysfunction among those children through using SSP and Statistical Package for Social Sciences (SPSS) version 21.0 for data analysis. This study revealed that almost 78.25% of children with autism had significant sensory processing dysfunction based on their sensory response to relevant activities. Under-responsive sensory seeking and auditory filtering were the least common problems among them. On the other hand, most of them (95%) represented that they had definite to probable differences in sensory processing, including under-response or sensory seeking, auditory filtering, and tactile sensitivity. Besides, the result also shows that the definite difference in sensory processing among 64 children was within 100%; it means those children with autism suffered from sensory difficulties, and thus it drew a great impact on the children’s Daily Living Activities (ADLs) as well as social interaction with others. Almost 95% of children with autism require intervention to overcome or normalize the problem. The result gives insight regarding types of sensory processing dysfunction to consider during diagnosis and ascertaining the treatment. So, early sensory problem identification is very important and thus will help to provide appropriate sensory input to minimize the maladaptive behavior and enhance to reach the normal range of adaptive behavior.

Keywords: autism, sensory processing difficulties, sensory profile, occupational therapy

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Authors: L. Raczynski, P. Moskal, P. Kowalski, W. Wislicki, T. Bednarski, P. Bialas, E. Czerwinski, A. Gajos, L. Kaplon, A. Kochanowski, G. Korcyl, J. Kowal, T. Kozik, W. Krzemien, E. Kubicz, Sz. Niedzwiecki, M. Palka, Z. Rudy, O. Rundel, P. Salabura, N.G. Sharma, M. Silarski, A. Slomski, J. Smyrski, A. Strzelecki, A. Wieczorek, M. Zielinski, N. Zon

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The J-PET scanner, which allows for single bed imaging of the whole human body, is currently under development at the Jagiellonian University. The J-PET detector improves the TOF resolution due to the use of fast plastic scintillators. Since registration of the waveform of signals with duration times of few nanoseconds is not feasible, a novel front-end electronics allowing for sampling in a voltage domain at four thresholds was developed. To take fully advantage of these fast signals a novel scheme of recovery of the waveform of the signal, based on ideas from the Tikhonov regularization (TR) and Compressive Sensing methods, is presented. The prior distribution of sparse representation is evaluated based on the linear transformation of the training set of waveform of the signals by using the Principal Component Analysis (PCA) decomposition. Beside the advantage of including the additional information from training signals, a further benefit of the TR approach is that the problem of signal recovery has an optimal solution which can be determined explicitly. Moreover, from the Bayes theory the properties of regularized solution, especially its covariance matrix, may be easily derived. This step is crucial to introduce and prove the formula for calculations of the signal recovery error. It has been proven that an average recovery error is approximately inversely proportional to the number of samples at voltage levels. The method is tested using signals registered by means of the single detection module of the J-PET detector built out from the 30 cm long BC-420 plastic scintillator strip. It is demonstrated that the experimental and theoretical functions describing the recovery errors in the J-PET scenario are largely consistent. The specificity and limitations of the signal recovery method in this application are discussed. It is shown that the PCA basis offers high level of information compression and an accurate recovery with just eight samples, from four voltage levels, for each signal waveform. Moreover, it is demonstrated that using the recovered waveform of the signals, instead of samples at four voltage levels alone, improves the spatial resolution of the hit position reconstruction. The experiment shows that spatial resolution evaluated based on information from four voltage levels, without a recovery of the waveform of the signal, is equal to 1.05 cm. After the application of an information from four voltage levels to the recovery of the signal waveform, the spatial resolution is improved to 0.94 cm. Moreover, the obtained result is only slightly worse than the one evaluated using the original raw-signal. The spatial resolution calculated under these conditions is equal to 0.93 cm. It is very important information since, limiting the number of threshold levels in the electronic devices to four, leads to significant reduction of the overall cost of the scanner. The developed recovery scheme is general and may be incorporated in any other investigation where a prior knowledge about the signals of interest may be utilized.

Keywords: plastic scintillators, positron emission tomography, statistical analysis, tikhonov regularization

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Authors: Faye Cosgrove, Donna Peacock

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This paper examines current state strategies for dealing with vulnerable people in police custody and identifies the underpinning discourses and practices which inform these strategies. It has previously been argued that the state has utilised contradictory and conflicting responses to the control of crime, by employing opposing strategies of denial and adaptation in order to simultaneously both display sovereignty and disclaim responsibility. This paper argues that these contradictory strategies are still being employed in contemporary criminal justice, although the focus and the purpose have now shifted. The focus is upon the ‘vulnerable’ suspect, whose social identity is as incongruous, complex and contradictory as his social environment, and the purpose is to redirect attention away from negative state practices, whilst simultaneously displaying a compassionate and benevolent countenance in order to appeal to the voting public. The findings presented here result from intensive qualitative research with police officers, with health care professionals, and with civilian volunteers who work within police custodial environments. The data has been gathered over a three-year period and includes observational and interview data which has been thematically analysed to expose the underpinning mechanisms from which the properties of the system emerge. What is revealed is evidence of contemporary state practices of denial relating to the harms of austerity and the structural relations of vulnerability, whilst simultaneously adapting through processes of ‘othering’ of the vulnerable, ‘responsibilisation’ of citizens, defining deviance down through diversionary practices, and managing success through redefining the aims of the system. The ‘vulnerable’ suspect is subject to individual pathologising, and yet the nature of risk is aggregated. ‘Vulnerable’ suspects are supported in police custody by private citizens, by multi-agency partnerships, and by for-profit organisations, while the state seeks to collate and control services, and thereby to retain a veneer of control. Late modern ambivalence to crime control and the associated contradictory practices of abjuration and adjustment have extended to state responses to vulnerable suspects. The support available in the custody environment operates to control and minimise operational and procedural risk, rather than for the welfare of the detained person, and in fact, the support available is discovered to be detrimental to the very people that it claims to benefit. The ‘vulnerable’ suspect is now subject to the bifurcated logics employed at the new limits of the sovereign state.

Keywords: custody, policing, sovereign state, vulnerability

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Authors: A. Delimitsou, C. Gouedard, E. Konstanta, A. Koletis, S. Patera, E. Manou, K. Spaho, S. Murray

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Background: There remains a lack of International Standard Control Reference materials for Next Generation Sequencing-based approaches or device calibration. We have designed and validated dsDNA biomimetic reference materials for targeted such approaches incorporating proprietary motifs (patent pending) for device/test calibration. They enable internal single-sample calibration, alleviating sample comparisons to pooled historical population-based data assembly or statistical modelling approaches. We have validated such an approach for BRCA Copy Number Variation analytics using iQRS™-CNVSUITE versus Mixed Ligation-dependent Probe Amplification. Methods: Standard BRCA Copy Number Variation analysis was compared between mixed ligation-dependent probe amplification and next generation sequencing using a cohort of 198 breast/ovarian cancer patients. Next generation sequencing based copy number variation analysis of samples spiked with iQRS™ dsDNA biomimetics were analysed using proprietary CNVSUITE software. Mixed ligation-dependent probe amplification analyses were performed on an ABI-3130 Sequencer and analysed with Coffalyser software. Results: Concordance of BRCA – copy number variation events for mixed ligation-dependent probe amplification and CNVSUITE indicated an overall sensitivity of 99.88% and specificity of 100% for iQRS™-CNVSUITE. The negative predictive value of iQRS-CNVSUITE™ for BRCA was 100%, allowing for accurate exclusion of any event. The positive predictive value was 99.88%, with no discrepancy between mixed ligation-dependent probe amplification and iQRS™-CNVSUITE. For device calibration purposes, precision was 100%, spiking of patient DNA demonstrated linearity to 1% (±2.5%) and range from 100 copies. Traditional training was supplemented by predefining the calibrator to sample cut-off (lock-down) for amplicon gain or loss based upon a relative ratio threshold, following training of iQRS™-CNVSUITE using spiked iQRS™ calibrator and control mocks. BRCA copy number variation analysis using iQRS™-CNVSUITE™ was successfully validated and ISO15189 accredited and now enters CE-IVD performance evaluation. Conclusions: The inclusion of a reference control competitor (iQRS™ dsDNA mimetic) to next generation sequencing-based sequencing offers a more robust sample-independent approach for the assessment of copy number variation events compared to mixed ligation-dependent probe amplification. The approach simplifies data analyses, improves independent sample data analyses, and allows for direct comparison to an internal reference control for sample-specific quantification. Our iQRS™ biomimetic reference materials allow for single sample copy number variation analytics and further decentralisation of diagnostics to single patient sample assessment.

Keywords: validation, diagnostics, oncology, copy number variation, reference material, calibration

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Authors: Dicle Aydın, Süheyla Büyükşahin Sıramkaya

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Conservation concept gained importance especially in 19th century, it found value with the change and developments lived globally. Basic values in the essence of the concept are important in the continuity of historical and cultural fabrics which have character special to them. Reuse of settlements and spaces carrying historical and cultural values in the frame of socio-cultural and socio-economic conditions is related with functional value. Functional dimension of reuse signifies interrogation of the usage potential of the building with a different aim other than its determined aim. If a building carrying historical and cultural values cannot be used with its own function because of environmental, economical, structural and functional reasons, it is advantageous to maintain its reuse from the point of environmental ecology. By giving a new function both a requirement of the society is fulfilled and a culture entity is conserved because of its functional value. In this study, functional dimension of reuse is exemplified in Antalya Kaleiçi where has a special location and importance with its natural, cultural and historical heritage characteristics. Antayla Kaleiçi settlement preserves its liveliness as a touristic urban fabric with its almost fifty thousand years of past, traditional urban form, civil architectural examples of 18th–19th century reflecting the life style of the region and monumental buildings. The civil architectural examples in the fabric have a special character formed according to Mediterranean climate with their outer sofa (open or closed), one, two or three storey, courtyards and oriels. In the study reuse of five civil architectural examples as boutique hotel by forming a whole with their environmental arrangements is investigated, it is analyzed how the spatial requirements of a boutique hotel are fulfilled in traditional dwellings. Usage of a cultural entity as a boutique hotel is evaluated under the headlines of i.functional requirement, ii.satisfactoriness of spatial dimensions, iii.functional organization. There are closed and open restaurant, kitchen, pub, lobby, administrative offices in the hotel with 70 bed capacity and 28 rooms in total. There are expansions to urban areas on second and third floors by the means of oriels in the hotel surrounded by narrow streets in three directions. This boutique hotel, formed by unique five different dwellings having similar plan scheme in traditional fabric, is different with its structure opened to outside and connected to each other by the means of courtyards, and its outside spaces which gained mobility because of the elevation differences in courtyards.

Keywords: reuse, adaptive reuse, functional dimension of reuse, traditional dwellings

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Authors: Shengnan Chen, Shuhua Wang

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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

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Authors: Giulia Colonna, Jocelyn Hoye, Bart de Laat, Gelsina Stanley, Jose Key, Alaaddin Ibrahimy, Sule Tinaz, Evan D. Morris

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Parkinson’s disease (PD) is the second most common neurodegenerative disease and affects approximately 1% of the world’s population. Increasing evidence suggests that aerobic physical exercise can be beneficial in mitigating both motor and non-motor symptoms of the disease. In a recent pilot study of the role of exercise on PD, we sought to confirm exercise intensity by monitoring heart rate (HR). For this purpose, we asked participants to wear a chest strap heart rate monitor (Polar Electro Oy, Kempele). The device sometimes proved uncomfortable. Looking forward to larger clinical trials, it would be convenient to employ a more comfortable and user friendly device. The Fitbit Charge 4 (Fitbit Inc) is a potentially comfortable, user-friendly solution since it is a wrist-worn heart rate monitor. Polar H10 has been used in large trials, and for our purposes, we treated it as the gold standard for the beat-to-beat period (R-R interval) assessment. In previous literature, it has been shown that Fitbit Charge 4 has comparable accuracy to Polar H10 in healthy subjects. It has yet to be determined if the Fitbit is as accurate as the Polar H10 in subjects with PD or in clinical populations, generally. Goal: To compare the Fitbit Charge 4 to the Polar H10 for monitoring HR in PD subjects engaging in an intensive exercise program. Methods: A total of 596 exercise sessions from 11 subjects (6 males) were collected simultaneously by both devices. Subjects with early-stage PD (Hoehn & Yahr <=2) were enrolled in a 6 months exercise training program designed for PD patients. Subjects participated in 3 one-hour exercise sessions per week. They wore both Fitbit and Polar H10 during each session. Sessions included rest, warm-up, intensive exercise, and cool-down periods. We calculated the bias in the HR via Fitbit under rest (5min) and intensive exercise (20min) by comparing the mean HR during each of the periods to the respective means measured by the Polar (HRFitbit – HRPolar). We also measured the sensitivity and specificity of Fitbit for detecting HRs that exceed the threshold for intensive exercise, defined as 70% of an individual’s theoretical maximum HR. Different types of correlation between the two devices were investigated. Results: The mean bias was 1.68 bpm at rest and 6.29 bpm during high intensity exercise, with an overestimation by Fitbit in both conditions. The mean bias of Fitbit across both rest and intensive exercise periods was 3.98 bpm. The sensitivity of the device in identifying high intensity exercise sessions was 97.14 %. The correlation between the two devices was non-linear, suggesting a saturation tendency of Fitbit to saturate at high values of HR. Conclusion: The performance of Fitbit Charge 4 is comparable to Polar H10 for assessing exercise intensity in a cohort of PD subjects. The device should be considered a reasonable replacement for the more cumbersome chest strap technology in future similar studies of clinical populations.

Keywords: fitbit, heart rate measurements, parkinson’s disease, wrist-wearable devices

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Authors: Mai Abdul Latif, Yuntian Feng

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Applied Element Method (AEM) is a method that was developed to aid in the analysis of the collapse of structures. Current available methods cannot deal with structural collapse accurately; however, AEM can simulate the behavior of a structure from an initial state of no loading until collapse of the structure. The elements in AEM are connected with sets of normal and shear springs along the edges of the elements, that represent the stresses and strains of the element in that region. The elements are rigid, and the material properties are introduced through the spring stiffness. Nonlinear dynamic analysis has been widely modelled using the finite element method for analysis of progressive collapse of structures; however, difficulties in the analysis were found at the presence of excessively deformed elements with cracking or crushing, as well as having a high computational cost, and difficulties on choosing the appropriate material models for analysis. The Applied Element method is developed and coded to significantly improve the accuracy and also reduce the computational costs of the method. The scheme works for both linear elastic, and nonlinear cases, including elasto-plastic materials. This paper will focus on elastic and elasto-plastic material behaviour, where the number of springs required for an accurate analysis is tested. A steel cantilever beam is used as the structural element for the analysis. The first modification of the method is based on the Gaussian Quadrature to distribute the springs. Usually, the springs are equally distributed along the face of the element, but it was found that using Gaussian springs, only up to 2 springs were required for perfectly elastic cases, while with equal springs at least 5 springs were required. The method runs on a Newton-Raphson iteration scheme, and quadratic convergence was obtained. The second modification is based on adapting the number of springs required depending on the elasticity of the material. After the first Newton Raphson iteration, Von Mises stress conditions were used to calculate the stresses in the springs, and the springs are classified as elastic or plastic. Then transition springs, springs located exactly between the elastic and plastic region, are interpolated between regions to strictly identify the elastic and plastic regions in the cross section. Since a rectangular cross-section was analyzed, there were two plastic regions (top and bottom), and one elastic region (middle). The results of the present study show that elasto-plastic cases require only 2 springs for the elastic region, and 2 springs for the plastic region. This showed to improve the computational cost, reducing the minimum number of springs in elasto-plastic cases to only 6 springs. All the work is done using MATLAB and the results will be compared to models of structural elements using the finite element method in ANSYS.

Keywords: applied element method, elasto-plastic, Gaussian springs, nonlinear

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Authors: Mireille Canal-Raffin, Nadege Lepage, Antoine Villa

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Context: Most antineoplastic drugs (AD) have a potential carcinogenic, mutagenic and/or reprotoxic effect and are classified as 'hazardous to handle' by National Institute for Occupational Safety and Health Their handling increases with the increase of cancer incidence. AD contamination from workers who handle AD and/or care for treated patients is, therefore, a major concern for occupational physicians. As part of the process of evaluation and prevention of chemical risks for professionals exposed to AD, Biological Monitoring of Occupational Exposure (BMOE) is the tool of choice. BMOE allows identification of at-risk groups, monitoring of exposures, assessment of poorly controlled exposures and the effectiveness and/or wearing of protective equipment, and documenting occupational exposure incidents to AD. This work aims to make proposals for the practical implementation of the BMOE for AD. The proposed strategy is based on the French good practice recommendations for BMOE, issued in 2016 by 3 French learned societies. These recommendations have been adapted to occupational exposure to AD. Results: AD contamination of professionals is a sensitive topic, and the BMOE requires the establishment of a working group and information meetings within the concerned health establishment to explain the approach, objectives, and purpose of monitoring. Occupational exposure to AD is often discontinuous and 2 steps are essential upstream: a study of the nature and frequency of AD used to select the Biological Exposure Indice(s) (BEI) most representative of the activity; a study of AD path in the institution to target exposed professionals and to adapt medico-professional information sheet (MPIS). The MPIS is essential to gather the necessary elements for results interpretation. Currently, 28 urinary specific BEIs of AD exposure have been identified, and corresponding analytical methods have been published: 11 BEIs were AD metabolites, and 17 were AD. Results interpretation is performed by groups of homogeneous exposure (GHE). There is no threshold biological limit value of interpretation. Contamination is established when an AD is detected in trace concentration or in a urine concentration equal or greater than the limit of quantification (LOQ) of the analytical method. Results can only be compared to LOQs of these methods, which must be as low as possible. For 8 of the 17 AD BEIs, the LOQ is very low with values between 0.01 to 0.05µg/l. For the other BEIs, the LOQ values were higher between 0.1 to 30µg/l. Results restitution by occupational physicians to workers should be individual and collective. Faced with AD dangerousness, in cases of workers contamination, it is necessary to put in place corrective measures. In addition, the implementation of prevention and awareness measures for those exposed to this risk is a priority. Conclusion: This work is a help for occupational physicians engaging in a process of prevention of occupational risks related to AD exposure. With the current analytical tools, effective and available, the (BMOE) to the AD should now be possible to develop in routine occupational physician practice. The BMOE may be complemented by surface sampling to determine workers' contamination modalities.

Keywords: antineoplastic drugs, urine, occupational exposure, biological monitoring of occupational exposure, biological exposure indice

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Authors: Gerhard Gritsch, Ana Skupch, Manfred Hartmann, Wolfgang Frühwirt, Hannes Perko, Dieter Grossegger, Tilmann Kluge

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Rehabilitation of stroke patients is dominated by classical physiotherapy. Nowadays, a field of research is the application of neurofeedback techniques in order to help stroke patients to get rid of their motor impairments. Especially, if a certain limb is completely paralyzed, neurofeedback is often the last option to cure the patient. Certain exercises, like the imagination of the impaired motor function, have to be performed to stimulate the neuroplasticity of the brain, such that in the neighboring parts of the injured cortex the corresponding activity takes place. During the exercises, it is very important to keep the motivation of the patient at a high level. For this reason, the missing natural feedback due to a movement of the effected limb may be replaced by a synthetic feedback based on the motor-related brain function. To generate such a synthetic feedback a system is needed which measures, detects, localizes and visualizes the motor related µ-rhythm. Fast therapeutic success can only be achieved if the feedback features high specificity, comes in real-time and without large delay. We describe such an approach that offers a 3D visualization of µ-rhythms in real time with a delay of 500ms. This is accomplished by combining smart EEG preprocessing in the frequency domain with source localization techniques. The algorithm first selects the EEG channel featuring the most prominent rhythm in the alpha frequency band from a so-called motor channel set (C4, CZ, C3; CP6, CP4, CP2, CP1, CP3, CP5). If the amplitude in the alpha frequency band of this certain electrode exceeds a threshold, a µ-rhythm is detected. To prevent detection of a mixture of posterior alpha activity and µ-activity, the amplitudes in the alpha band outside the motor channel set are not allowed to be in the same range as the main channel. The EEG signal of the main channel is used as template for calculating the spatial distribution of the µ - rhythm over all electrodes. This spatial distribution is the input for a inverse method which provides the 3D distribution of the µ - activity within the brain which is visualized in 3D as color coded activity map. This approach mitigates the influence of lid artifacts on the localization performance. The first results of several healthy subjects show that the system is capable of detecting and localizing the rarely appearing µ-rhythm. In most cases the results match with findings from visual EEG analysis. Frequent eye-lid artifacts have no influence on the system performance. Furthermore, the system will be able to run in real-time. Due to the design of the frequency transformation the processing delay is 500ms. First results are promising and we plan to extend the test data set to further evaluate the performance of the system. The relevance of the system with respect to the therapy of stroke patients has to be shown in studies with real patients after CE certification of the system. This work was performed within the project ‘LiveSolo’ funded by the Austrian Research Promotion Agency (FFG) (project number: 853263).

Keywords: real-time EEG neuroimaging, neurofeedback, stroke, EEG–signal processing, rehabilitation

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Authors: Khan Farhan Rafat, Riaz Ahmed

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Renowned offshore organizations are drifting towards collaborative exertion to win and implement international projects for business gains. However, devoid of financial constraints, with the availability of skilled professionals, and despite improved project management practices through state-of-the-art tools and techniques, project delays have become a norm these days. This situation calls for exploring the factor(s) affecting the bonding between project management performance and project success. In the context of the well-known 3M’s of project management (that is, manpower, machinery, and materials), machinery and materials are dependent upon manpower. Because the body of knowledge inveterate on the influence of national culture on men, hence, the realization of the impact on the link between project management performance and project success need to be investigated in detail to arrive at the possible cause(s) of project delays. This research initiative was, therefore, undertaken to fill the research gap. The unit of analysis for the proposed research excretion was the individuals who had worked on skyscraper construction projects. In reverent studies, project management is best described using construction examples. It is due to this reason that the project oriented city of Dubai was chosen to reconnoiter on causes of project delays. A structured questionnaire survey was disseminated online with the courtesy of the Project Management Institute local chapter to carry out the cross-sectional study. The Construction Industry Institute, Austin, of the United States of America along with 23 high-rise builders in Dubai were also contacted by email requesting for their contribution to the study and providing them with the online link to the survey questionnaire. The reliability of the instrument was warranted using Cronbach’s alpha coefficient of 0.70. The appropriateness of sampling adequacy and homogeneity in variance was ensured by keeping Kaiser–Meyer–Olkin (KMO) and Bartlett’s test of sphericity in the range ≥ 0.60 and < 0.05, respectively. Factor analysis was used to verify construct validity. During exploratory factor analysis, all items were loaded using a threshold of 0.4. Four hundred and seventeen respondents, including members from top management, project managers, and project staff, contributed to the study. The link between project management performance and project success was significant at 0.01 level (2-tailed), and 0.05 level (2-tailed) for Pearson’s correlation. Before initiating the moderator analysis test for linearity, multicollinearity, outliers, leverage points and influential cases, test for homoscedasticity and normality were carried out which are prerequisites for conducting moderator review. The moderator analysis, using a macro named PROCESS, was performed to verify the hypothesis that national culture has an influence on the said link. The empirical findings, when compared with Hofstede's results, showed high power distance as the cause of construction project delays in Dubai. The research outcome calls for the project sponsors and top management to reshape their project management strategy and allow for low power distance between management and project personnel for timely completion of projects.

Keywords: causes of construction project delays, construction industry, construction management, power distance

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Authors: Muhammad Awais Kiani

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The field of electronics engineering plays a vital role in the marketing of smart materials. Smart materials are innovative, adaptive materials that can respond to external stimuli, such as temperature, light, or pressure, in order to enhance performance or functionality. As the demand for smart materials continues to grow, it is crucial to understand how electronics engineering can contribute to their marketing strategies. This abstract presents an overview of the role of electronics engineering in the marketing of smart materials. It explores the various ways in which electronics engineering enables the development and integration of smart features within materials, enhancing their marketability. Firstly, electronics engineering facilitates the design and development of sensing and actuating systems for smart materials. These systems enable the detection and response to external stimuli, providing valuable data and feedback to users. By integrating sensors and actuators into materials, their functionality and performance can be significantly enhanced, making them more appealing to potential customers. Secondly, electronics engineering enables the creation of smart materials with wireless communication capabilities. By incorporating wireless technologies such as Bluetooth or Wi-Fi, smart materials can seamlessly interact with other devices, providing real-time data and enabling remote control and monitoring. This connectivity enhances the marketability of smart materials by offering convenience, efficiency, and improved user experience. Furthermore, electronics engineering plays a crucial role in power management for smart materials. Implementing energy-efficient systems and power harvesting techniques ensures that smart materials can operate autonomously for extended periods. This aspect not only increases their market appeal but also reduces the need for constant maintenance or battery replacements, thus enhancing customer satisfaction. Lastly, electronics engineering contributes to the marketing of smart materials through innovative user interfaces and intuitive control mechanisms. By designing user-friendly interfaces and integrating advanced control systems, smart materials become more accessible to a broader range of users. Clear and intuitive controls enhance the user experience and encourage wider adoption of smart materials in various industries. In conclusion, electronics engineering significantly influences the marketing of smart materials by enabling the design of sensing and actuating systems, wireless connectivity, efficient power management, and user-friendly interfaces. The integration of electronics engineering principles enhances the functionality, performance, and marketability of smart materials, making them more adaptable to the growing demand for innovative and connected materials in diverse industries.

Keywords: electronics engineering, smart materials, marketing, power management

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Authors: Abdulkadir Sarauta

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Almost every type of industrial process involves the release of trace quantity of toxic organic and inorganic compound that up in receiving water bodies, this study was aimed at assessing the Persistent Organic Pollutant Level in Challawa River Basin of Kano State, Nigeria. And the research formed the basis of identifying the presence of PCBs and PAHs in receiving water bodies in the study area, assessing the PCBs and PAHs concentration in receiving water body of Challawa system, evaluate the concentration level of PCBs and PAHs in fishes in the study area, determine the concentration level of PCBs and PAHs in crops irrigated in the study area as well as compare the concentration of PCBs and PAHs with the acceptable limit set by Nigerian, EU, U.S and WHO standard. Data were collected using reconnaissance survey, site inspection, field survey, laboratory experiment as well as secondary data source. A total of 78 samples were collected through stratified systematic random sampling (i.e., 26 samples for each of water, crops and fish) three sampling points were chosen and designated A, B and C along the stretch of the river (i.e. up, middle, and downstream) from Yan Danko Bridge to Tambirawa bridge. The result shows that the Polychlorinated biphenyls (PCBs) was not detected while, polycyclic aromatic hydrocarbons (PAHs) was detected in the whole samples analysed at the trench of Challawa River basin in order to assess the contribution of human activities to global environmental pollution. The total concentrations of ΣPAH and ΣPCB ranges between 0.001 to 0.087mg/l and 0.00 to 0.00mg/l of water samples While, crops samples ranges between 2.0ppb to 8.1ppb and fish samples ranges from 2.0 to 6.7ppb.The whole samples are polluted because most of the parameters analyzed exceed the threshold limits set by WHO, Nigerian, U.S and EU standard. The analytical results revealed that some chemicals are present in water, crops and fishes are significantly very high at Zamawa village which is very close to Challawa industrial estate and also is main effluent discharge point and drinking water around study area is not potable for consumption. Analysis of Variance was obtained by Bartlett’s test performance. There is only significant difference in water because the P < 0.05 level of significant, But there is no difference in crops concentration they have the same performance, likes wise in the fishes. It is said to be of concern to health hazard which will increase incidence of tumor related diseases such as skin, lungs, bladder, gastrointestinal cancer, this show there is high failure of pollution abatement measures in the area. In conclusion, it can be said that industrial activities and effluent has impact on Challawa River basin and its environs especially those that are living in the immediate surroundings. Arising from the findings of this research some recommendations were made the industries should treat their liquid properly by installing modern treatment plants.

Keywords: Challawa River Basin, organic, persistent, pollutant

Procedia PDF Downloads 555

Authors: Tatiana G. Smirnova, Stan G. Benjamin

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Rapid Update Cycle (RUC) land surface model (LSM) was a land-surface component in several generations of operational weather prediction models at the National Center for Environment Prediction (NCEP) at the National Oceanic and Atmospheric Administration (NOAA). It was designed for short-range weather predictions with an emphasis on severe weather and originally was intentionally simple to avoid uncertainties from poorly known parameters. Nevertheless, the RUC LSM, when coupled with the hourly-assimilating atmospheric model, can produce a realistic evolution of time-varying soil moisture and temperature, as well as the evolution of snow cover on the ground surface. This result is possible only if the soil/vegetation/snow component of the coupled weather prediction model has sufficient skill to avoid long-term drift. RUC LSM was first implemented in the operational NCEP Rapid Update Cycle (RUC) weather model in 1998 and later in the Weather Research Forecasting Model (WRF)-based Rapid Refresh (RAP) and High-resolution Rapid Refresh (HRRR). Being available to the international WRF community, it was implemented in operational weather models in Austria, New Zealand, and Switzerland. Based on the feedback from the US weather service offices and the international WRF community and also based on our own validation, RUC LSM has matured over the years. Also, a sea-ice module was added to RUC LSM for surface predictions over the Arctic sea-ice. Other modifications include refinements to the snow model and a more accurate specification of albedo, roughness length, and other surface properties. At present, RUC LSM is being tested in the regional application of the Unified Forecast System (UFS). The next generation UFS-based regional Rapid Refresh FV3 Standalone (RRFS) model will replace operational RAP and HRRR at NCEP. Over time, RUC LSM participated in several international model intercomparison projects to verify its skill using observed atmospheric forcing. The ESM-SnowMIP was the last of these experiments focused on the verification of snow models for open and forested regions. The simulations were performed for ten sites located in different climatic zones of the world forced with observed atmospheric conditions. While most of the 26 participating models have more sophisticated snow parameterizations than in RUC, RUC LSM got a high ranking in simulations of both snow water equivalent and surface temperature. However, ESM-SnowMIP experiment also revealed some issues in the RUC snow model, which will be addressed in this paper. One of them is the treatment of grid cells partially covered with snow. RUC snow module computes energy and moisture budgets of snow-covered and snow-free areas separately by aggregating the solutions at the end of each time step. Such treatment elevates the importance of computing in the model snow cover fraction. Improvements to the original simplistic threshold-based approach have been implemented and tested both offline and in the coupled weather model. The detailed description of changes to the snow cover fraction and other modifications to RUC soil and snow parameterizations will be described in this paper.

Keywords: land-surface models, weather prediction, hydrology, boundary-layer processes

Procedia PDF Downloads 65

Authors: Nasser S. Shebka

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Fuzzy logic is used in complex adaptive systems where classical tools of representing knowledge are unproductive. Nevertheless, the incorporation of fuzzy logic, as it’s the case with all artificial intelligence tools, raised some inconsistencies and limitations in dealing with increased complexity systems and rules that apply to real-life situations and hinders the ability of the inference process of such systems, but it also faces some inconsistencies between inferences generated fuzzy rules of complex or imprecise knowledge-based systems. The use of fuzzy logic enhanced the capability of knowledge representation in such applications that requires fuzzy representation of truth values or similar multi-value constant parameters derived from multi-valued logic, which set the basis for the three t-norms and their based connectives which are actually continuous functions and any other continuous t-norm can be described as an ordinal sum of these three basic ones. However, some of the attempts to solve this dilemma were an alteration to fuzzy logic by means of non-monotonic logic, which is used to deal with the defeasible inference of expert systems reasoning, for example, to allow for inference retraction upon additional data. However, even the introduction of non-monotonic fuzzy reasoning faces a major issue of conflict resolution for which many principles were introduced, such as; the specificity principle and the weakest link principle. The aim of our work is to improve the logical representation and functional modelling of AI systems by presenting a method of resolving existing and potential rule conflicts by representing temporal modalities within defeasible inference rule-based systems. Our paper investigates the possibility of resolving fuzzy rules conflict in a non-monotonic fuzzy reasoning-based system by introducing temporal modalities and Kripke's general weak modal logic operators in order to expand its knowledge representation capabilities by means of flexibility in classifying newly generated rules, and hence, resolving potential conflicts between these fuzzy rules. We were able to address the aforementioned problem of our investigation by restructuring the inference process of the fuzzy rule-based system. This is achieved by using time-branching temporal logic in combination with restricted first-order logic quantifiers, as well as propositional logic to represent classical temporal modality operators. The resulting findings not only enhance the flexibility of complex rule-base systems inference process but contributes to the fundamental methods of building rule bases in such a manner that will allow for a wider range of applicable real-life situations derived from a quantitative and qualitative knowledge representational perspective.

Keywords: fuzzy rule-based systems, fuzzy tense inference, intelligent systems, temporal modalities

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Authors: Jared Beard, Ali Baheri

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As autonomous systems become more prominent in society, ensuring their safe application becomes increasingly important. This is clearly demonstrated with autonomous cars traveling through a crowded city or robots traversing a warehouse with heavy equipment. Human environments can be complex, having high dimensional state and action spaces. This gives rise to two problems. One being that analytic solutions may not be possible. The other is that in simulation based approaches, searching the entirety of the problem space could be computationally intractable, ruling out formal methods. To overcome this, approximate solutions may seek to find failures or estimate their likelihood of occurrence. One such approach is adaptive stress testing (AST) which uses reinforcement learning to induce failures in the system. The premise of which is that a learned model can be used to help find new failure scenarios, making better use of simulations. In spite of these failures AST fails to find particularly sparse failures and can be inclined to find similar solutions to those found previously. To help overcome this, multi-fidelity learning can be used to alleviate this overuse of information. That is, information in lower fidelity can simulations can be used to build up samples less expensively, and more effectively cover the solution space to find a broader set of failures. Recent work in multi-fidelity learning has passed information bidirectionally using “knows what it knows” (KWIK) reinforcement learners to minimize the number of samples in high fidelity simulators (thereby reducing computation time and load). The contribution of this work, then, is development of the bidirectional multi-fidelity AST framework. Such an algorithm, uses multi-fidelity KWIK learners in an adversarial context to find failure modes. Thus far, a KWIK learner has been used to train an adversary in a grid world to prevent an agent from reaching its goal; thus demonstrating the utility of KWIK learners in an AST framework. The next step is implementation of the bidirectional multi-fidelity AST framework described. Testing will be conducted in a grid world containing an agent attempting to reach a goal position and adversary tasked with intercepting the agent as demonstrated previously. Fidelities will be modified by adjusting the size of a time-step, with higher-fidelity effectively allowing for more responsive closed loop feedback. Results will compare the single KWIK AST learner with the multi-fidelity algorithm with respect to number of samples, distinct failure modes found, and relative effect of learning after a number of trials.

Keywords: multi-fidelity reinforcement learning, multi-fidelity simulation, safety validation, falsification

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Authors: Iulianna Taritsa, Kuldeep Neote, Eric Fossel

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Lysosome-induced immunogenic cell death (LIICD) is a powerful mechanism of targeting cancer cells that kills circulating malignant cells and primes the host’s immune cells against future remission. Current immunotherapies for cancer are limited in preventing recurrence – a gap that can be bridged by training the immune system to recognize cancer neoantigens. Lysosomal leakage can be induced therapeutically to traffic antigens from dying cells to dendritic cells, which can later present those tumorigenic antigens to T cells. Previous research has shown that oxidative agents administered in the tumor microenvironment can initiate LIICD. We generated a fusion protein between an oxidative agent known as xanthine oxidase (XO) and a mini-antibody specific for EGFR/HER2-sensitive breast tumor cells. The anti-EGFR single domain antibody fragment is uniquely sourced from llama, which is functional without the presence of a light chain. These llama micro-antibodies have been shown to be better able to penetrate tissues and have improved physicochemical stability as compared to traditional monoclonal antibodies. We demonstrate that the fusion protein created is stable and can induce early markers of immunogenic cell death in an in vitro human breast cancer cell line (SkBr3). Specifically, we measured overall cell death, as well as surface-expressed calreticulin, extracellular ATP release, and HMGB1 production. These markers are consensus indicators of ICD. Flow cytometry, luminescence assays, and ELISA were used respectively to quantify biomarker levels between treated versus untreated cells. We also included a positive control group of SkBr3 cells dosed with doxorubicin (a known inducer of LIICD) and a negative control dosed with cisplatin (a known inducer of cell death, but not of the immunogenic variety). We looked at each marker at various time points after cancer cells were treated with the XO/antibody fusion protein, doxorubicin, and cisplatin. Upregulated biomarkers after treatment with the fusion protein indicate an immunogenic response. We thus show the potential for this fusion protein to induce an anticancer effect paired with an adaptive immune response against EGFR/HER2+ cells. Our research in human cell lines here provides evidence for the success of the same therapeutic method for patients and serves as the gateway to developing a new treatment approach against breast cancer.

Keywords: apoptosis, breast cancer, immunogenic cell death, lysosome

Procedia PDF Downloads 179

Authors: Wilai Masanga, Chirapha Tannanonta, Sangutid Thongsawad, Sasikarn Chamchod, Todsaporn Fuangrod

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The major factors of radiotherapy for head and neck (HN) cancers include patient’s anatomical changes and tumour shrinkage. These changes can significantly affect the planned dose distribution that causes the treatment plan deterioration. A measured transit EPID images compared to a predicted EPID images using gamma analysis has been clinically implemented to verify the dose accuracy as part of adaptive radiotherapy protocol. However, a global gamma analysis dose not sensitive to some critical organ changes as the entire treatment field is compared. The objective of this feasibility study is to evaluate the dosimetric response to patient anatomical changes during the treatment course in HN IMRT (Head and Neck Intensity-Modulated Radiation Therapy) using a novel comparison method; organ-of-interest gamma analysis. This method provides more sensitive to specific organ change detection. Random replanned 5 HN IMRT patients with causes of tumour shrinkage and patient weight loss that critically affect to the parotid size changes were selected and evaluated its transit dosimetry. A comprehensive physics-based model was used to generate a series of predicted transit EPID images for each gantry angle from original computed tomography (CT) and replan CT datasets. The patient structures; including left and right parotid, spinal cord, and planning target volume (PTV56) were projected to EPID level. The agreement between the transit images generated from original CT and replanned CT was quantified using gamma analysis with 3%, 3mm criteria. Moreover, only gamma pass-rate is calculated within each projected structure. The gamma pass-rate in right parotid and PTV56 between predicted transit of original CT and replan CT were 42.8%( ± 17.2%) and 54.7%( ± 21.5%). The gamma pass-rate for other projected organs were greater than 80%. Additionally, the results of organ-of-interest gamma analysis were compared with 3-dimensional cone-beam computed tomography (3D-CBCT) and the rational of replan by radiation oncologists. It showed that using only registration of 3D-CBCT to original CT does not provide the dosimetric impact of anatomical changes. Using transit EPID images with organ-of-interest gamma analysis can provide additional information for treatment plan suitability assessment.

Keywords: re-plan, anatomical change, transit electronic portal imaging device, EPID, head, and neck

Procedia PDF Downloads 198

Authors: Anila Hayat

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Pakistan is one of those developing countries that are least involved in emissions but has the most vulnerable environmental conditions. Pakistan is ranked 8th in most affected countries by climate change on the climate risk index 1992-2011. Pakistan is facing severe water shortages and flooding as a result of changes in rainfall patterns, specifically in the least developed areas such as Tharparkar. Nagarparkar, once an attractive tourist spot located in Tharparkar because of its tropical desert climate, is now facing severe drought conditions for the last few decades. This study investigates the present socio-economic situation of local communities, major impacts of droughts and their underlying causes and current mitigation strategies adopted by local communities. The study uses both secondary (quantitative in nature) and primary (qualitative in nature) methods to understand the impacts and explore causes on the socio-economic life of local communities of the study area. The relevant data has been collected through household surveys using structured questionnaires, focus groups and in-depth interviews of key personnel from local and international NGOs to explore the sensitivity of impacts and adaptation to droughts in the study area. This investigation is limited to four rural communities of union council Pilu of Nagarparkar district, including Bheel, BhojaBhoon, Mohd Rahan Ji Dhani and Yaqub Ji Dhani villages. The results indicate that drought has caused significant economic and social hardships for the local communities as more than 60% of the overall population is dependent on rainfall which has been disturbed by irregular rainfall patterns. The decline in Crop yields has forced the local community to migrate to nearby areas in search of livelihood opportunities. Communities have not undertaken any appropriate adaptive actions to counteract the adverse effect of drought; they are completely dependent on support from the government and external aid for survival. Respondents also reported that poverty is a major cause of their vulnerability to drought. An increase in population, limited livelihood opportunities, caste system, lack of interest from the government sector, unawareness shaped their vulnerability to drought and other social issues. Based on the findings of this study, it is recommended that the local authorities shall create awareness about drought hazards and improve the resilience of communities against drought. It is further suggested to develop, introduce and implement water harvesting practices at the community level to promote drought-resistant crops.

Keywords: migration, vulnerability, awareness, Drought

Procedia PDF Downloads 112

Authors: Nejmeddine Ouhichi, Fethi Lachaal, Radhouane Hamdi, Olivier Grunberger

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Located in Cap Bon peninsula (Tunisia), the Lebna dam was built in 1987 to balance local water salt intrusion taking place in the coastal aquifer of Korba. The first intention was to reduce coastal groundwater over-pumping by supplying surface water to a large irrigation system. The unpredicted beneficial effect was recorded with the occurrence of a direct localized recharge to the coastal aquifer by leakage through the geological material of the southern bank of the lake. The hydrological balance of the reservoir dam gave an estimation of the annual leakage volume, but dynamic processes and sound quantification of recharge inputs are still required to understand the localized effect of the recharge in terms of piezometry and quality. Present work focused on simulating the recharge process to confirm the hypothesis, and established a sound quantification of the water supply to the coastal aquifer and extend it to multi-annual effects. A spatial frame of 30km² was used for modeling. Intensive outcrops and geophysical surveys based on 68 electrical resistivity soundings were used to characterize the aquifer 3D geometry and the limit of the Plio-quaternary geological material concerned by the underground flow paths. Permeabilities were determined using 17 pumping tests on wells and piezometers. Six seasonal piezometric surveys on 71 wells around southern reservoir dam banks were performed during the 2019-2021 period. Eight monitoring boreholes of high frequency (15min) piezometric data were used to examine dynamical aspects. Model boundary conditions were specified using the geophysics interpretations coupled with the piezometric maps. The dam-groundwater flow model was performed using Visual MODFLOW software. Firstly, permanent state calibration based on the first piezometric map of February 2019 was established to estimate the permanent flow related to the different reservoir levels. Secondly, piezometric data for the 2019-2021 period were used for transient state calibration and to confirm the robustness of the model. Preliminary results confirmed the temporal link between the reservoir level and the localized recharge flow with a strong threshold effect for levels below 16 m.a.s.l. The good agreement of computed flow through recharge cells on the southern banks and hydrological budget of the reservoir open the path to future simulation scenarios of the dilution plume imposed by the localized recharge. The dam reservoir-groundwater flow-model simulation results approve a potential for storage of up to 17mm/year in existing wells, under gravity-feed conditions during level increases on the reservoir into the three years of operation. The Lebna dam groundwater flow model characterized a spatiotemporal relation between groundwater and surface water.

Keywords: leakage, MODFLOW, saltwater intrusion, surface water-groundwater interaction

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

Procedia PDF Downloads 391

Authors: Heribert R. Kaijage, Samuel N. A. Codjoe, Simon H. D. Mamuya, Mangi J. Ezekiel

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There is strong evidence that climate has changed significantly affecting various sectors including public health. The recommended feasible solution is adopting development trajectories which combine both mitigation and adaptation measures for improving resilience pathways. This approach demands a consideration for complex interactions between climate and social-ecological systems. While other sectors such as agriculture and water have developed climate resilience indices, the public health sector in Tanzania is still lagging behind. The aim of this study was to find out how can we use Demographic and Health Surveys (DHS) linked with Remote Sensing (RS) technology and metrological information as tools to inform climate change resilient development and evaluation for the health sector. Methodological review was conducted whereby a number of studies were content analyzed to find appropriate indicators and indices for climate resilience household and their integration approach. These indicators were critically reviewed, listed, filtered and their sources determined. Preliminary identification and ranking of indicators were conducted using participatory approach of pairwise weighting by selected national stakeholders from meeting/conferences on human health and climate change sciences in Tanzania. DHS datasets were retrieved from Measure Evaluation project, processed and critically analyzed for possible climate change indicators. Other sources for indicators of climate change exposure were also identified. For the purpose of preliminary reporting, operationalization of selected indicators was discussed to produce methodological approach to be used in resilience comparative analysis study. It was found that household climate resilient index depends on the combination of three indices namely Household Adaptive and Mitigation Capacity (HC), Household Health Sensitivity (HHS) and Household Exposure Status (HES). It was also found that, DHS alone cannot complement resilient evaluation unless integrated with other data sources notably flooding data as a measure of vulnerability, remote sensing image of Normalized Vegetation Index (NDVI) and Metrological data (deviation from rainfall pattern). It can be concluded that if these indices retrieved from DHS data sets are computed and scientifically integrated can produce single climate resilience index and resilience maps could be generated at different spatial and time scales to enhance targeted interventions for climate resilient development and evaluations. However, further studies are need to test for the sensitivity of index in resilience comparative analysis among selected regions.

Keywords: climate change, resilience, remote sensing, demographic and health surveys

Procedia PDF Downloads 140

Authors: Ibrahim Musa, Mohammed Abdul-Aziz Mabrouk, Yusuf Tanko

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Introduction: Long term physical training affect the performance of athletes especially the females. Soccer which is a team sport, played in an outdoor field, require adequate oxygen transport system for the maximal aerobic power during exercise in order to complete 90 minutes of competitive play. Suboptimal haematological status has often been recorded in athletes with intensive physical activity. It may be due to the iron depletion caused by hemolysis or haemodilution results from plasma volume expansion. There is lack of data regarding the dynamics of red blood cell variables, in male football players. We hypothesized that, a long competitive season involving frequent matches and intense training could influence red blood cell variables, as a consequence of applying repeated physical loads when compared with sedentary. Methods: This cross sectional study was carried on 40 adult males (20 athletes and 20 non athletes) between 18-25 years of age. The 20 apparently healthy male non athletes were taken as sedentary and 20 male footballers comprise the study group. The university institutional review board (ABUTH/HREC/TRG/36) gave approval for all procedures in accordance with the Declaration of Helsinki. Red blood cell (RBC) concentration, packed cell volume (PCV), and plasma volume were measured in fasting state and immediately after exercise. Statistical analysis was done by using SPSS/ win.20.0 for comparison within and between the groups, using student’s paired and unpaired “t” test respectively. Results: The finding from our study shows that, immediately after termination of exercise, the mean RBC counts and PCV significantly (p<0.005) decreased with significant increased (p<0.005) in plasma volume when compared with pre-exercised values in both group. In addition the post exercise RBC was significantly higher in untrained (261.10±8.5) when compared with trained (255.20±4.5). However, there was no significant differences in the post exercise hematocrit and plasma volume parameters between the sedentary and the footballers. Moreover, beside changes in pre-exercise values among the sedentary and the football players, the resting red blood cell counts and Plasma volume (PV %) was significantly (p < 0.05) higher in the sedentary group (306.30±10.05 x 104 /mm3; 58.40±0.54%) when compared with football players (293.70±4.65 x 104 /mm3; 55.60±1.18%). On the other hand, the sedentary group exhibited significant (p < 0.05) decrease in PCV (41.60±0.54%) when compared with the football players (44.40±1.18%). Conclusions: It is therefore proposed that the acute football exercise induced reduction in RBC and PCV is entirely due to plasma volume expansion, and not of red blood cell hemolysis. In addition, the training status also influenced haematological indices of male football players differently from the sedentary at rest due to adaptive response. This is novel.

Keywords: Haematological Indices, Performance Status, Sedentary, Male Football Players

Procedia PDF Downloads 236

Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

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This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

Procedia PDF Downloads 138

Authors: Vlad Andrei Raducanu, Mariana Lucia Angelescu, Ion Cinca, Vasile Danut Cojocaru, Doina Raducanu

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By using smart digital tools, such as generative design (GD) and digital fabrication (DF), problems of high actuality concerning resources optimization (materials, energy, time) can be solved and applications or products of free-form type can be created. In the new digital technology materials are active, designed in response to a set of performance requirements, which impose a total rethinking of old material practices. The article presents the design procedure key steps of a free-form architectural object - a column type one with connections to get an adaptive 3D surface, by using the parametric design methodology and by exploiting the properties of conventional metallic materials. In parametric design the form of the created object or space is shaped by varying the parameters values and relationships between the forms are described by mathematical equations. Digital parametric design is based on specific procedures, as shape grammars, Lindenmayer - systems, cellular automata, genetic algorithms or swarm intelligence, each of these procedures having limitations which make them applicable only in certain cases. In the paper the design process stages and the shape grammar type algorithm are presented. The generative design process relies on two basic principles: the modeling principle and the generative principle. The generative method is based on a form finding process, by creating many 3D spatial forms, using an algorithm conceived in order to apply its generating logic onto different input geometry. Once the algorithm is realized, it can be applied repeatedly to generate the geometry for a number of different input surfaces. The generated configurations are then analyzed through a technical or aesthetic selection criterion and finally the optimal solution is selected. Endless range of generative capacity of codes and algorithms used in digital design offers various conceptual possibilities and optimal solutions for both technical and environmental increasing demands of building industry and architecture. Constructions or spaces generated by parametric design can be specifically tuned, in order to meet certain technical or aesthetical requirements. The proposed approach has direct applicability in sustainable architecture, offering important potential economic advantages, a flexible design (which can be changed until the end of the design process) and unique geometric models of high performance.

Keywords: parametric design, algorithmic procedures, free-form architectural object, sustainable architecture

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Authors: Olubisi Friday Oluduro

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The Paris Agreement 2015, the result of negotiations under the United Nations Framework Convention on Climate Change (UNFCCC), after Kyoto Protocol expiration, sets a long-term goal of limiting the increase in the global average temperature to well below 2 degrees Celsius above pre-industrial levels, and of pursuing efforts to limiting this temperature increase to 1.5 degrees Celsius. An advancement on the erstwhile Kyoto Protocol which sets commitments to only a limited number of Parties to reduce their greenhouse gas (GHGs) emissions, it includes the goal to increase the ability to adapt to the adverse impacts of climate change and to make finance flows consistent with a pathway towards low GHGs emissions. For it achieve these goals, the Agreement requires all Parties to undertake efforts towards reaching global peaking of GHG emissions as soon as possible and towards achieving a balance between anthropogenic emissions by sources and removals by sinks in the second half of the twenty-first century. In addition to climate change mitigation, the Agreement aims at enhancing adaptive capacity, strengthening resilience and reducing the vulnerability to climate change in different parts of the world. It acknowledges the importance of addressing loss and damage associated with the adverse of climate change. The Agreement also contains comprehensive provisions on support to be provided to developing countries, which includes finance, technology transfer and capacity building. To ensure that such supports and actions are transparent, the Agreement contains a number reporting provisions, requiring parties to choose the efforts and measures that mostly suit them (Nationally Determined Contributions), providing for a mechanism of assessing progress and increasing global ambition over time by a regular global stocktake. Despite the somewhat global look of the Agreement, it has been fraught with manifold limitations threatening its very existential capability to produce any meaningful result. Considering these obvious limitations some of which were the very cause of the failure of its predecessor—the Kyoto Protocol—such as the non-participation of the United States, non-payment of funds into the various coffers for appropriate strategic purposes, among others. These have left the developing countries largely threatened eve the more, being more vulnerable than the developed countries, which are really responsible for the climate change scourge. The paper seeks to examine the mitigation and adaptation measures under the Paris Agreement 2015, appraise the present situation since the Agreement was concluded and ascertain whether the developing countries have been better or worse off since the Agreement was concluded, and examine why and how, while projecting a way forward in the present circumstance. It would conclude with recommendations towards ameliorating the situation.

Keywords: mitigation, adaptation, climate change, Paris agreement 2015, framework

Procedia PDF Downloads 141

Authors: Eiji Nakamachi, Tsuyoshi Eguchi, Sayo Yamamoto, Yusuke Morita, H. Sakamoto

Abstract:

In this study, we aim to reveal the relationship between the meniscal tearing and the articular cartilage injury of knee joint by using the dynamic explicit finite element (FE) method. Meniscal injuries reduce its functional ability and consequently increase the load on the articular cartilage of knee joint. In order to prevent the induction of osteoarthritis (OA) caused by meniscal injuries, many medical treatment techniques, such as artificial meniscus replacement and meniscal regeneration, have been developed. However, it is reported that these treatments are not the comprehensive methods. In order to reveal the fundamental mechanism of OA induction, the mechanical characterization of meniscus under the condition of normal and injured states is carried out by using FE analyses. At first, a FE model of the human knee joint in the case of normal state – ‘intact’ - was constructed by using the magnetron resonance (MR) tomography images and the image construction code, Materialize Mimics. Next, two types of meniscal injury models with the radial tears of medial and lateral menisci were constructed. In FE analyses, the linear elastic constitutive law was adopted for the femur and tibia bones, the visco-hyperelastic constitutive law for the articular cartilage, and the visco-anisotropic hyperelastic constitutive law for the meniscus, respectively. Material properties of articular cartilage and meniscus were identified using the stress-strain curves obtained by our compressive and the tensile tests. The numerical results under the normal walking condition revealed how and where the maximum compressive stress occurred on the articular cartilage. The maximum compressive stress and its occurrence point were varied in the intact and two meniscal tear models. These compressive stress values can be used to establish the threshold value to cause the pathological change for the diagnosis. In this study, FE analyses of knee joint were carried out to reveal the influence of meniscal injuries on the cartilage injury. The following conclusions are obtained. 1. 3D FE model, which consists femur, tibia, articular cartilage and meniscus was constructed based on MR images of human knee joint. The image processing code, Materialize Mimics was used by using the tetrahedral FE elements. 2. Visco-anisotropic hyperelastic constitutive equation was formulated by adopting the generalized Kelvin model. The material properties of meniscus and articular cartilage were determined by curve fitting with experimental results. 3. Stresses on the articular cartilage and menisci were obtained in cases of the intact and two radial tears of medial and lateral menisci. Through comparison with the case of intact knee joint, two tear models show almost same stress value and higher value than the intact one. It was shown that both meniscal tears induce the stress localization in both medial and lateral regions. It is confirmed that our newly developed FE analysis code has a potential to be a new diagnostic system to evaluate the meniscal damage on the articular cartilage through the mechanical functional assessment.

Keywords: finite element analysis, hyperelastic constitutive law, knee joint injury, meniscal tear, stress concentration

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Authors: Carmela Nardelli, Laura Iaffaldano, Valentina Capobianco, Antonietta Tafuto, Maddalena Ferrigno, Angela Capone, Giuseppe Maria Maruotti, Maddalena Raia, Rosa Di Noto, Luigi Del Vecchio, Pasquale Martinelli, Lucio Pastore, Lucia Sacchetti

Abstract:

Maternal obesity and nutrient excess in utero increase the risk of future metabolic diseases in the adult life. The mechanisms underlying this process are probably based on genetic, epigenetic alterations and changes in foetal nutrient supply. In mammals, the placenta is the main interface between foetus and mother, it regulates intrauterine development, modulates adaptive responses to sub optimal in uterus conditions and it is also an important source of human amniotic mesenchymal stem cells (hA-MSCs). We previously highlighted a specific microRNA (miRNA) profiling in amnion from obese (Ob) pregnant women, here we compared the miRNA expression profile of hA-MSCs isolated from (Ob) and control (Co) women, aimed to search for any alterations in metabolic pathways that could predispose the new-born to the obese phenotype. Methods: We isolated, at delivery, hA-MSCs from amnion of 16 Ob- and 7 Co-women with pre-pregnancy body mass index (mean/SEM) 40.3/1.8 and 22.4/1.0 kg/m2, respectively. hA-MSCs were phenotyped by flow cytometry. Globally, 384 miRNAs were evaluated by the TaqMan Array Human MicroRNA Panel v 1.0 (Applied Biosystems). By the TargetScan program we selected the target genes of the miRNAs differently expressed in Ob- vs Co-hA-MSCs; further, by KEGG database, we selected the statistical significant biological pathways. Results: The immunophenotype characterization confirmed the mesenchymal origin of the isolated hA-MSCs. A large percentage of the tested miRNAs, about 61.4% (232/378), was expressed in hA-MSCs, whereas 38.6% (146/378) was not. Most of the expressed miRNAs (89.2%, 207/232) did not differ between Ob- and Co-hA-MSCs and were not further investigated. Conversely, 4.8% of miRNAs (11/232) was higher and 6.0% (14/232) was lower in Ob- vs Co-hA-MSCs. Interestingly, 7/232 miRNAs were obesity-specific, being expressed only in hA-MSCs isolated from obese women. Bioinformatics showed that these miRNAs significantly regulated (P<0.001) genes belonging to several metabolic pathways, i.e. MAPK signalling, actin cytoskeleton, focal adhesion, axon guidance, insulin signaling, etc. Conclusions: Our preliminary data highlight an altered miRNA profile in Ob- vs Co-hA-MSCs and suggest that an epigenetic miRNA-based mechanism of gene regulation could affect pathways involved in placental growth and function, thereby potentially increasing the newborn’s risk of metabolic diseases in the adult life.

Keywords: hA-MSCs, obesity, miRNA, biosystem

Procedia PDF Downloads 497

Authors: Abdulwakeel B. Raji

Abstract:

This paper introduces a concept of an intelligent virtual learning environment that involves communication between learners and an artificially intelligent teaching agent in an attempt to replicate classroom learning interactions. The benefits of this technology over current e-learning practices is that it creates a virtual classroom where real time adaptive learning interactions are made possible. This is a move away from the static learning practices currently being adopted by e-learning systems. Over the years, artificial intelligence has been applied to various fields, including and not limited to medicine, military applications, psychology, marketing etc. The purpose of e-learning applications is to ensure users are able to learn outside of the classroom, but a major limitation has been the inability to fully replicate classroom interactions between teacher and students. This study used comparative surveys to gain information and understanding of the current learning practices in Nigerian universities and how they compare to these practices compare to the use of a developed e-learning system. The study was conducted by attending several lectures and noting the interactions between lecturers and tutors and as an aftermath, a software has been developed that deploys the use of an artificial intelligent teaching-agent alongside an e-learning system to enhance user learning experience and attempt to create the similar learning interactions to those found in classroom and lecture hall settings. Dialogflow has been used to implement a teaching-agent, which has been developed using JSON, which serves as a virtual teacher. Course content has been created using HTML, CSS, PHP and JAVASCRIPT as a web-based application. This technology can run on handheld devices and Google based home technologies to give learners an access to the teaching agent at any time. This technology also implements the use of definite clause grammars and natural language processing to match user inputs and requests with defined rules to replicate learning interactions. This technology developed covers familiar classroom scenarios such as answering users’ questions, asking ‘do you understand’ at regular intervals and answering subsequent requests, taking advanced user queries to give feedbacks at other periods. This software technology uses deep learning techniques to learn user interactions and patterns to subsequently enhance user learning experience. A system testing has been undergone by undergraduate students in the UK and Nigeria on the course ‘Introduction to Database Development’. Test results and feedback from users shows that this study and developed software is a significant improvement on existing e-learning systems. Further experiments are to be run using the software with different students and more course contents.

Keywords: virtual learning, natural language processing, definite clause grammars, deep learning, artificial intelligence

Procedia PDF Downloads 112