Search results for: stochastic signals

Authors: Nicholas C. Rose, Christopher D. Spicer

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The regeneration of damaged or diseased tissues would provide an invaluable therapeutic tool in biological research and medicine. Cells must be provided with a number of different biochemical signals in order to form mature tissue through complex signaling networks that are difficult to recreate in synthetic materials. The ability to attach and detach bioactive proteins from material in an iterative and dynamic manner would therefore present a powerful way to mimic natural biochemical signaling cascades for tissue growth. We propose to reversibly attach these bioactive proteins using ortho-boronoimine (oBI) linkages and related derivatives formed by the reaction of an ortho-boronobenzaldehyde with a nucleophilic amine derivative. To enable the use of oBIs for biomaterial modification, we have studied binding and cleavage processes with precise detail in the context of small molecule models. A panel of oBI complexes has been synthesized and screened using a novel Förster resonance energy transfer (FRET) assay, using a cyanine dye FRET pair (Cy3 and Cy5), to identify the most reactive boron-aldehyde/amine nucleophile pairs. Upon conjugation of the dyes, FRET occurs under Cy3 excitation and the resultant ratio of Cy3:Cy5 emission directly correlates to conversion. Reaction kinetics and equilibria can be accurately quantified for reactive pairs, with dissociation constants of oBI derivatives in water (KD) found to span 9-orders of magnitude (10⁻²-10⁻¹¹ M). These studies have provided us with a better understanding of oBI linkages that we hope to exploit to reversibly attach bioconjugates to materials. The long-term aim of the project is to develop a modular biomaterial platform that can be used to help combat chronic diseases such as osteoarthritis, heart disease, and chronic wounds by providing cells with potent biological stimuli for tissue engineering.

Keywords: dynamic, bioconjugation, bornoimine, rapid, physiological

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Authors: Kaushik Sathupadi, Sandesh Achar

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Pervasive computing is a growing research field that aims to acknowledge human physical life routines (HPLR) based on body-worn sensors such as MEMS sensors-based technologies. The use of these technologies for human activity recognition is progressively increasing. On the other hand, personalizing human life routines using numerous machine-learning techniques has always been an intriguing topic. In contrast, various methods have demonstrated the ability to recognize basic movement patterns. However, it still needs to be improved to anticipate the dynamics of human living patterns. This study introduces state-of-the-art techniques for recognizing static and dy-namic patterns and forecasting those challenging activities from multi-fused sensors. Further-more, numerous MEMS signals are extracted from one self-annotated IM-WSHA dataset and two benchmarked datasets. First, we acquired raw data is filtered with z-normalization and denoiser methods. Then, we adopted statistical, local binary pattern, auto-regressive model, and intrinsic time scale decomposition major features for feature extraction from different domains. Next, the acquired features are optimized using maximum relevance and minimum redundancy (mRMR). Finally, the artificial neural network is applied to analyze the whole system's performance. As a result, we attained a 90.27% recognition rate for the self-annotated dataset, while the HARTH and KU-HAR achieved 83% on nine living activities and 90.94% on 18 static and dynamic routines. Thus, the proposed HPLR system outperformed other state-of-the-art systems when evaluated with other methods in the literature.

Keywords: artificial intelligence, machine learning, gait analysis, local binary pattern (LBP), statistical features, micro-electro-mechanical systems (MEMS), maximum relevance and minimum re-dundancy (MRMR)

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Authors: Dimitriya A. Mihaylova, Zlatka V. Valkova-Jarvis, Georgi L. Iliev

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One possible approach for maintaining the security of communication systems relies on Physical Layer Security mechanisms. However, in wireless time division duplex systems, where uplink and downlink channels are reciprocal, the channel estimate procedure is exposed to attacks known as pilot contamination, with the aim of having an enhanced data signal sent to the malicious user. The Shifted 2-N-PSK method involves two random legitimate pilots in the training phase, each of which belongs to a constellation, shifted from the original N-PSK symbols by certain degrees. In this paper, legitimate pilots’ offset values and their influence on the detection capabilities of the Shifted 2-N-PSK method are investigated. As the implementation of the technique depends on the relation between the shift angles rather than their specific values, the optimal interconnection between the two legitimate constellations is investigated. The results show that no regularity exists in the relation between the pilot contamination attacks (PCA) detection probability and the choice of offset values. Therefore, an adversary who aims to obtain the exact offset values can only employ a brute-force attack but the large number of possible combinations for the shifted constellations makes such a type of attack difficult to successfully mount. For this reason, the number of optimal shift value pairs is also studied for both 100% and 98% probabilities of detecting pilot contamination attacks. Although the Shifted 2-N-PSK method has been broadly studied in different signal-to-noise ratio scenarios, in multi-cell systems the interference from the signals in other cells should be also taken into account. Therefore, the inter-cell interference impact on the performance of the method is investigated by means of a large number of simulations. The results show that the detection probability of the Shifted 2-N-PSK decreases inversely to the signal-to-interference-plus-noise ratio.

Keywords: channel estimation, inter-cell interference, pilot contamination attacks, wireless communications

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Authors: Bliss Singhal

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Epilepsy is a prevalent neurological disorder affecting approximately 50 million individuals worldwide and 1.2 million Americans. There exist millions of pediatric patients with intractable epilepsy, a condition in which seizures fail to come under control. The occurrence of seizures can result in physical injury, disorientation, unconsciousness, and additional symptoms that could impede children's ability to participate in everyday tasks. Predicting seizures can help parents and healthcare providers take precautions, prevent risky situations, and mentally prepare children to minimize anxiety and nervousness associated with the uncertainty of a seizure. This research proposes a comprehensive framework to predict seizures in pediatric patients by evaluating machine learning algorithms on unimodal neuroimaging data consisting of electroencephalogram signals. The bandpass filtering and independent component analysis proved to be effective in reducing the noise and artifacts from the dataset. Various machine learning algorithms’ performance is evaluated on important metrics such as accuracy, precision, specificity, sensitivity, F1 score and MCC. The results show that the deep learning algorithms are more successful in predicting seizures than logistic Regression, and k nearest neighbors. The recurrent neural network (RNN) gave the highest precision and F1 Score, long short-term memory (LSTM) outperformed RNN in accuracy and convolutional neural network (CNN) resulted in the highest Specificity. This research has significant implications for healthcare providers in proactively managing seizure occurrence in pediatric patients, potentially transforming clinical practices, and improving pediatric care.

Keywords: intractable epilepsy, seizure, deep learning, prediction, electroencephalogram channels

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Authors: Smita Chaudhary

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Traffic in India are observed uncontrolled, and are characterized by chaotic (not follows the lane discipline) traffic situation. Bus Rapid Transit (BRT) has emerged as a viable option to enhance transportation capacity and provide increased levels of mobility and accessibility. At present in Ahmadabad there are as many intersections which face the congestion and delay at signalized intersection due to transit (BRT) lanes. Most of the intersection in spite of being signalized is operated manually due to the conflict between BRT buses and heterogeneous traffic. Though BRTS in Ahmadabad has an exclusive lane of its own but with this comes certain limitations which Ahmadabad is facing right now. At many intersections in Ahmadabad due to these conflicts, interference, and congestion both heterogeneous traffic as well as transit buses suffer traffic delays of remarkable 3-4 minutes at each intersection which has a become an issue of great concern. There is no provision of BRT bus priority due to which existing signals have their least role to play in managing the traffic that ultimately call for manual operation. There is an immense decrement in the daily ridership of BRTS because people are finding this transit mode no more time saving in their routine, there is an immense fall in ridership ultimately leading to increased number of private vehicles, idling of vehicles at intersection cause air and noise pollution. In order to bring back these commuters’ transit facilities need to be improvised. Classified volume count survey, travel time delay survey was conducted and revised signal design was done for whole study stretch having three intersections and one roundabout, later one intersection was simulated in order to see the effect of giving priority to BRT on side street queue length and travel time for heterogeneous traffic. This paper aims at suggesting the recommendations in signal cycle, introduction of intermittent priority for transit buses, simulation of intersection in study stretch with proposed signal cycle using VISSIM in order to make this transit amenity feasible and attracting for commuters in Ahmadabad.

Keywords: BRT, priority, Ridership, Signal, VISSIM

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Authors: Imran Dayan, Ashiqul Khan

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Internal corporate fraud, which is fraud carried out by internal stakeholders of a company, affects the well-being of the organisation just like its external counterpart. Even if such an act is carried out for the short-term benefit of a corporation, the act is ultimately harmful to the entity in the long run. Internal fraud is often carried out by relying upon aberrations from usual business processes. Business processes are the lifeblood of a company in modern managerial context. Such processes are developed and fine-tuned over time as a corporation grows through its life stages. Modern corporations have embraced technological innovations into their business processes, and Enterprise Resource Planning (ERP) systems being at the heart of such business processes is a testimony to that. Since ERP systems record a huge amount of data in their event logs, the logs are a treasure trove for anyone trying to detect any sort of fraudulent activities hidden within the day-to-day business operations and processes. This research utilises the ERP systems in place within corporations to assess the likelihood of prospective internal fraud through developing a framework for measuring the risks of fraud through Process Mining techniques and hence finds risky designs and loose ends within these business processes. This framework helps not only in identifying existing cases of fraud in the records of the event log, but also signals the overall riskiness of certain business processes, and hence draws attention for carrying out a redesign of such processes to reduce the chance of future internal fraud while improving internal control within the organisation. The research adds value by applying the concepts of Process Mining into the analysis of data from modern day applications of business process records, which is the ERP event logs, and develops a framework that should be useful to internal stakeholders for strengthening internal control as well as provide external auditors with a tool of use in case of suspicion. The research proves its usefulness through a few case studies conducted with respect to big corporations with complex business processes and an ERP in place.

Keywords: enterprise resource planning, fraud risk framework, internal corporate fraud, process mining

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Authors: Lucas Paganin, Viliam Makis

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With the advent of globalization, the market competition has become a major issue for most companies. One of the main strategies to overcome this situation is the quality improvement of the product at a lower cost to meet customers’ expectations. In order to achieve the desired quality of products, it is important to control the process to meet the specifications, and to implement the optimal maintenance policy for the machines and the production lines. Thus, the overall objective is to reduce process variation and the production and maintenance costs. In this paper, an integrated model involving Statistical Process Control (SPC) and maintenance is developed to achieve this goal. Therefore, the main focus of this paper is to develop the jointly optimal maintenance and statistical process control policy minimizing the total long run expected average cost per unit time. In our model, the production process can go out of control due to either the deterioration of equipment or other assignable causes. The equipment is also subject to failures in any of the operating states due to deterioration and aging. Hence, the process mean is controlled by an Xbar control chart using equidistant sampling epochs. We assume that the machine inspection epochs are the times when the control chart signals an out-of-control condition, considering both true and false alarms. At these times, the production process will be stopped, and an investigation will be conducted not only to determine whether it is a true or false alarm, but also to identify the causes of the true alarm, whether it was caused by the change in the machine setting, by other assignable causes, or by both. If the system is out of control, the proper actions will be taken to bring it back to the in-control state. At these epochs, a maintenance action can be taken, which can be no action, or preventive replacement of the unit. When the equipment is in the failure state, a corrective maintenance action is performed, which can be minimal repair or replacement of the machine and the process is brought to the in-control state. SMDP framework is used to formulate and solve the joint control problem. Numerical example is developed to demonstrate the effectiveness of the control policy.

Keywords: maintenance, semi-Markov decision process, statistical process control, Xbar control chart

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Authors: Hala Alioua, Alberic Tellier

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This paper is designed to spotlight the research on corporate strategic planning, by emphasizing the role of middle manager of SBU’s and related issues such as the context of vision change. Previous research on strategic vision has been focused principally at the SME, with relatively limited consideration given to the role of middle managers SBU’s in the context of change. This project of research has been done by using a single case study. We formulated through our immersion for 2.5 years on the ground and by a qualitative method and abduction approach. This entity that we analyze is a subsidiary of multinational companies headquartered in Germany, specialized in manufacturing automotive equipment. The "Delta Company" is a French manufacturing plant that has undergone numerous changes over the past three years. The two major strategic changes that have a significant impact on the Delta plant are the strengths of its core business through « lead plant strategy» in 2011 and the implementation of a new strategic vision in 2014. These consecutive changes impact the purpose of the mission of the middle managers. The plant managers ask the following questions: How the middle managers make sense of the corporate strategic planning imposed by the parent company? How they appropriate the new vision and decline it into actions on the ground? We chose the individual interview technique through open-ended questions as the source of data collection. We first of all carried out an exploratory approach by interviewing 8 members of the Management committee’s decision and 19 heads of services. The first findings and results show that exist a divergence of opinion and interpretations of the corporate strategic planning among organization members and there are difficulties to make sense and interpretations of the signals of the environment. The lead plant strategy enables new projects which insure the workload of Delta Company. Nevertheless, it creates a tension and stress among the middle managers because its provoke lack of resources to the detriment of their main jobs as manufacturer plant. The middle managers does not have a clear vision and they are wondering if the new strategic vision means more autonomy and less support from the group.

Keywords: change, middle managers, vision, sensemaking

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Authors: S. Ben-Shabat, T. Turgeman, O. Leubinski, N. Roth-Bejerano, V. Kagan-Zur, Y. Sitrit

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The ectomycorrhizal (ECM) desert truffle Terfezia boudieri produces edible fruit bodies and forms symbiosis with its host plant Helianthemum sessiliflorum (Cistaceae) in the Negev desert of Israel. The symbiosis is vital for both partners' survival under desert conditions. Under desert habitat conditions, ECMs must form symbiosis before entering the dry season. To secure a successful encounter, in the course of evolution, both partners have responded by evolving special signals exchange that facilitates recognition. Members of the Cistaceae family serve as host plants for many important truffles. Conceivably, during evolution a common molecule present in Cistaceae plants was recruited to facilitate successful encounter with ectomycorrhizas. Arbuscular vesicular fungi (AM) are promiscuous in host preferences, in contrast, ECM fungi show specificity to host plants. Accordingly, we hypothesize that H. sessiliflorum secretes a chemotrophic-signaling, which is common to plants hosting ECM fungi belonging to the Pezizales. However, thus far no signaling molecules have been identified in ECM fungi. We developed a bioassay for chemotrophic activity. Fractionation of root exudates revealed a substance with chemotrophic activity and molecular mass of 534. Following the above concept, screening the transcriptome of Terfezia, grown under chemoattraction, discovered genes showing high homology to G proteins-coupled receptors of plant pathogens involved in positive chemotaxis and chemotaxis suppression. This study aimed to identify the active molecule using analytical methods (LC-MS, NMR etc.). This should contribute to our understanding of how ECM fungi communicate with their hosts in the rhizosphere. In line with the ability of Terfezia to form also endomycorrhizal symbiosis like AM fungi, analysis of the mechanisms may likewise be applicable to AM fungi. Developing methods to manipulate fungal growth by the chemoattractant can open new ways to improve inoculation of plants.

Keywords: chemotrophic signal, Helianthemum sessiliflorum, Terfezia boudieri, ECM

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Authors: Adel Salem Bahakeem, Ahmad Jamal, Mir Md. Maruf Morshed, Elwaleed Awad Khidir

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Direct Current (DC) servo motors, or simply DC motors, play an important role in many industrial applications such as manufacturing of plastics, precise positioning of the equipment, and operating computer-controlled systems where speed of feed control, maintaining the position, and ensuring to have a constantly desired output is very critical. These parameters can be controlled with the help of control systems such as the Proportional Integral Derivative (PID) controller. The aim of the current work is to investigate the effects of Proportional (P) and Integral (I) controllers on the steady state and transient response of the DC motor. The controller gains are varied to observe their effects on the error, damping, and stability of the steady and transient motor response. The current investigation is conducted experimentally on a servo trainer CE 110 using analog PI controller CE 120 and theoretically using Simulink in MATLAB. Both experimental and theoretical work involves varying integral controller gain to obtain the response to a steady-state input, varying, individually, the proportional and integral controller gains to obtain the response to a step input function at a certain frequency, and theoretically obtaining the proportional and integral controller gains for desired values of damping ratio and response frequency. Results reveal that a proportional controller helps reduce the steady-state and transient error between the input signal and output response and makes the system more stable. In addition, it also speeds up the response of the system. On the other hand, the integral controller eliminates the error but tends to make the system unstable with induced oscillations and slow response to eliminate the error. From the current work, it is desired to achieve a stable response of the servo motor in terms of its angular velocity subjected to steady-state and transient input signals by utilizing the strengths of both P and I controllers.

Keywords: DC servo motor, proportional controller, integral controller, controller gain optimization, Simulink

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Authors: Kana Matsuyanagi

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Anorexia Nervosa (AN) is a psychiatric disorder characterized by a relentless pursuit of thinness and strict restriction of food. The current therapeutic approaches for AN predominantly revolve around outpatient psychotherapies, which create significant financial barriers for the majority of affected patients, hindering their access to treatment. Nonetheless, AN exhibit one of the highest mortality and relapse rates among psychological disorders, underscoring the urgent need to provide patients with an affordable self-treatment tool, enabling those unable to access conventional medical intervention to address their condition autonomously. To this end, a neurofeedback software, termed RelaxNeuron, was developed with the objective of providing an economical and portable means to aid individuals in self-managing AN. Electroencephalography (EEG) was chosen as the preferred modality for RelaxNeuron, as it aligns with the study's goal of supplying a cost-effective and convenient solution for addressing AN. The primary aim of the software is to ameliorate the negative emotional responses towards food stimuli and the accompanying aberrant eye-tracking patterns observed in AN patient, ultimately alleviating the profound fear towards food an elemental symptom and, conceivably, the fundamental etiology of AN. The core functionality of RelaxNeuron hinges on the acquisition and analysis of EEG signals, alongside an electrocardiogram (ECG) signal, to infer the user's emotional state while viewing dynamic food-related imagery on the screen. Moreover, the software quantifies the user's performance in accurately tracking the moving food image. Subsequently, these two parameters undergo further processing in the subsequent algorithm, informing the delivery of either negative or positive feedback to the user. Preliminary test results have exhibited promising outcomes, suggesting the potential advantages of employing RelaxNeuron in the treatment of AN, as evidenced by its capacity to enhance emotional regulation and attentional processing through repetitive and persistent therapeutic interventions.

Keywords: Anorexia Nervosa, fear conditioning, neurofeedback, BCI

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Authors: Nicholas Pearce, Eun-jin Kim

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Pathologies of the cardiovascular (CV) system remain a serious and deadly health problem for human society. Computational modelling provides a relatively accessible tool for diagnosis, treatment, and research into CV disorders. However, numerical models of the CV system have largely focused on the function of the ventricles, frequently overlooking the behaviour of the atria. Furthermore, in the study of the pressure-volume relationship of the heart, which is a key diagnosis of cardiac vascular pathologies, previous works often evoke popular yet questionable time-varying elastance (TVE) method that imposes the pressure-volume relationship instead of calculating it consistently. Despite the convenience of the TVE method, there have been various indications of its limitations and the need for checking its validity in different scenarios. A model of the combined left ventricle (LV) and left atrium (LA) is presented, which consistently considers various feedback mechanisms in the heart without having to use the TVE method. Specifically, a synergistic model of the left ventricle is extended and modified to include the function of the LA. The synergy of the original model is preserved by modelling the electro-mechanical and chemical functions of the micro-scale myofiber for the LA and integrating it with the microscale and macro-organ-scale heart dynamics of the left ventricle and CV circulation. The atrioventricular node function is included and forms the conduction pathway for electrical signals between the atria and ventricle. The model reproduces the essential features of LA behaviour, such as the two-phase pressure-volume relationship and the classic figure of eight pressure-volume loops. Using this model, disorders in the internal cardiac electrical signalling are investigated by recreating the mechano-electric feedback (MEF), which is impossible where the time-varying elastance method is used. The effects of AV node block and slow conduction are then investigated in the presence of an atrial arrhythmia. It is found that electrical disorders and arrhythmia in the LA degrade the CV system by reducing the cardiac output, power, and heart rate.

Keywords: cardiovascular system, left atrium, numerical model, MEF

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Authors: Nicole Ramlachan, Samuel Mark West

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Lung cancer is the leading cause of cancer-associated deaths in North America, with the vast majority being non-small cell lung cancer (NSCLC), with a five-year survival rate of only 24%. Non-invasive discovery of biomarkers associated with early-diagnosis of NSCLC can enable precision oncology efforts using liquid biopsy-based multiomics profiling of plasma. Although tissue biopsies are currently the gold standard for tumor profiling, this method presents many limitations since these are invasive, risky, and sometimes hard to obtain as well as only giving a limited tumor profile. Blood-based tests provides a less-invasive, more robust approach to interrogate both tumor- and non-tumor-derived signals. We intend to examine 30 stage III-IV NSCLC patients pre-surgery and collect plasma samples.Cell-free DNA (cfDNA) will be extracted from plasma, and next-generation sequencing (NGS) performed. Through the analysis of tumor-specific alterations, including single nucleotide variants (SNVs), insertions, deletions, copy number variations (CNVs), and methylation alterations, we intend to identify tumor-derived DNA—ctDNA among the total pool of cfDNA. This would generate data to be used as an accurate form of cancer genotyping for diagnostic purposes. Using liquid biopsies offer opportunities to improve the surveillance of cancer patients during treatment and would supplement current diagnosis and tumor profiling strategies previously not readily available in Trinidad and Tobago. It would be useful and advantageous to use this in diagnosis and tumour profiling as well as to monitor cancer patients, providing early information regarding disease evolution and treatment efficacy, and reorient treatment strategies in, timethereby improving clinical oncology outcomes.

Keywords: genomics, multiomics, clinical genetics, genotyping, oncology, diagnostics

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Authors: Shahid Hussain Abro, Siamak Zohari, Lena H. M. Renström, Désirée S. Jansson, Faruk Otman, Karin Ullman, Claudia Baule

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Infectious bronchitis is an acute, highly contagious respiratory, nephropathogenic and reproductive disease of poultry that is caused by infectious bronchitis virus (IBV). The present study used a large data set of structural gene sequences, including newly generated ones and sequences available in the GenBank database to further analyze the diversity and to identify selective pressures and recombination spots. There were some deletions or insertions in the analyzed regions in isolates of the Italy-02 and D274 genotypes. Whereas, there were no insertions or deletions observed in the isolates of the Massachusetts and 4/91 genotype. The hypervariable nucleotide sequence regions spanned positions 152–239, 554–582, 686–737 and 802–912 in the S1 sub-unit of the all analyzed genotypes. The nucleotide sequence data of the E gene showed that this gene was comparatively unstable and subjected to a high frequency of mutations. The M gene showed substitutions consistently distributed except for a region between nucleotide positions 250–680 that remained conserved. The lowest variation in the nucleotide sequences of ORF5a was observed in the isolates of the D274 genotype. While, ORF5b and N gene sequences showed highly conserved regions and were less subjected to variation. Genes ORF3a, ORF3b, M, ORF5a, ORF5b and N presented negative selective pressure among the analyzed isolates. However, some regions of the ORFs showed favorable selective pressure(s). The S1 and E proteins were subjected to a high rate of mutational substitutions and non-synonymous amino acids. Strong signals of recombination breakpoints and ending break point were observed in the S and N genes. Overall, the results of this study revealed that very likely the strong selective pressures in E, M and the high frequency of substitutions in the S gene can probably be considered the main determinants in the evolution of IBV.

Keywords: IBV, avian infectious bronchitis, structural genes, genotypes, genetic diversity

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Authors: Ana Breda, Catarina Cruz

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Daily, we face unpredictable events, often attributed to chance, as there is no justification for such an occurrence. Chance, understood as a source of uncertainty, is present in several aspects of human life, such as weather forecasts, dice rolling, and lottery. Surprisingly, humans and some animals can quickly adjust their behavior to handle efficiently doubly stochastic processes (random events with two layers of randomness, like unpredictable weather affecting dice rolling). This adjustment ability suggests that the human brain has built-in mechanisms for perceiving, understanding, and responding to simple probabilities. It also explains why current trends in mathematics education include probability concepts in official curriculum programs, starting from the third year of primary education onwards. In the first years of schooling, children learn to use a certain type of (specific) vocabulary, such as never, always, rarely, perhaps, likely, and unlikely, to help them to perceive and understand the probability of some events. These are keywords of crucial importance for their perception and understanding of probabilities. The development of the probabilistic concepts comes from facts and cause-effect sequences resulting from the subject's actions, as well as the notion of chance and intuitive estimates based on everyday experiences. As part of a junior summer school program, which took place at a Portuguese university, a non-formal learning experiment was carried out with 18 children in the 5th and 6th grades. This experience was designed to be implemented in a dynamic of a serious ice-breaking game, to assess their levels of probabilistic, critical, and creative thinking in understanding impossible, certain, equally probable, likely, and unlikely events, and also to gain insight into how the non-formal learning context influenced their achievements. The criteria used to evaluate probabilistic thinking included the creative ability to conceive events classified in the specified categories, the ability to properly justify the categorization, the ability to critically assess the events classified by other children, and the ability to make predictions based on a given probability. The data analysis employs a qualitative, descriptive, and interpretative-methods approach based on students' written productions, audio recordings, and researchers' field notes. This methodology allowed us to conclude that such an approach is an appropriate and helpful formative assessment tool. The promising results of this initial exploratory study require a future research study with children from these levels of education, from different regions, attending public or private schools, to validate and expand our findings.

Keywords: critical and creative thinking, non-formal mathematics learning, probabilistic thinking, serious game

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Authors: Abderrahmane Soufi

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The building sector is the largest consumer of energy in France, accounting for 44% of French consumption. To reduce energy consumption and improve energy efficiency, France implemented an energy transition law targeting 40% energy savings by 2030 in the tertiary building sector. Building simulation tools are used to predict the energy performance of buildings but the reliability of these tools is hampered by discrepancies between the real and simulated energy performance of a building. This performance gap lies in the simplified assumptions of certain factors, such as the behavior of occupants on air conditioning and heating, which is considered deterministic when setting a fixed operating schedule and a fixed interior comfort temperature. However, the behavior of occupants on air conditioning and heating is stochastic, diverse, and complex because it can be affected by many factors. Probabilistic models are an alternative to deterministic models. These models are usually derived from statistical data and express occupant behavior by assuming a probabilistic relationship to one or more variables. In the literature, logistic regression has been used to model the behavior of occupants with regard to heating and air conditioning systems by considering univariate logistic models in residential buildings; however, few studies have developed multivariate models for higher education and vocational training buildings in a Mediterranean climate. Therefore, in this study, occupant behavior on heating and air conditioning systems was modeled using logistic regression. Occupant behavior related to the turn-on heating and air conditioning systems was studied through experimental measurements collected over a period of one year (June 2023–June 2024) in three classrooms occupied by several groups of students in engineering schools and professional training. Instrumentation was provided to collect indoor temperature and indoor relative humidity in 10-min intervals. Furthermore, the state of the heating/air conditioning system (off or on) and the set point were determined. The outdoor air temperature, relative humidity, and wind speed were collected as weather data. The number of occupants, age, and sex were also considered. Logistic regression was used for modeling an occupant turning on the heating and air conditioning systems. The results yielded a proposed model that can be used in building simulation tools to predict the energy performance of teaching buildings. Based on the first months (summer and early autumn) of the investigations, the results illustrate that the occupant behavior of the air conditioning systems is affected by the indoor relative humidity and temperature in June, July, and August and by the indoor relative humidity, temperature, and number of occupants in September and October. Occupant behavior was analyzed monthly, and univariate and multivariate models were developed.

Keywords: occupant behavior, logistic regression, behavior model, mediterranean climate, air conditioning, heating

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

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

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

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Authors: Maftunakhon Latipova, Feruza Khaydarova

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Obesity is considered a chronic metabolic disease that occurs at any age. Regulation of body weight in the body is carried out through complex interaction of a complex of interrelated systems that control the body's energy system. Energy imbalance is the cause of obesity and overweight, in which the supply of energy from food exceeds the energy needs of the body. Obesity is closely related to impaired appetite regulation, and a hypothalamus is a key place for neural regulation of food consumption. The nucleus of the hypothalamus is connected and interdependent on receiving, integrating and sending hunger signals to regulate appetite. Purpose of the study: to identify markers of food behavior. Materials and methods: The screening was carried out to identify eating disorders in 200 men and women aged 18 to 35 years with overweight and obesity and to check the effects of Orexin A and Neuropeptide Y markers. A questionnaire and questionnaires were conducted with over 200 people aged 18 to 35 years. Questionnaires were for eating disorders and hidden depression (on the Zang scale). Anthropometry is measured by OT, OB, BMI, Weight, and Height. Based on the results of the collected data, 3 groups were divided: People with obesity, People with overweight, Control Group of Healthy People. Results: Of the 200 analysed persons, 86% had eating disorders. Of these, 60% of eating disorders were associated with childhood. According to the Zang test result: Normal condition was about 37%, mild depressive disorder 20%, moderate depressive disorder 25% and 18% of people suffered from severe depressive disorder without knowing it. One group of people with obesity had eating disorders and moderate and severe depressive disorder, and group 2 was overweight with mild depressive disorder. According to laboratory data, the first group had the lowest concentration of Orexin A and Neuropeptide U in blood serum. Conclusions: Being overweight and obese are the first signal of many diseases, and prevention and detection of these disorders will prevent various diseases, including type 2 diabetes. Obesity etiology is associated with eating disorders and signal transmission of the orexinorghetic system of the hypothalamus.

Keywords: obesity, endocrinology, hypothalamus, overweight

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Authors: Anna Siegler

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Bullying among peers is not uncommon; however, adults can notice only a fragment of the cases of harassment during everyday life. The systemic approaches of bullying investigation put the whole school community in the focus of attention and propose that the solution should emerge from the culture of the school. Bystanders are essential in the prevention and intervention processes as an active agent rather than passive. For combating exclusion, stigmatization and harassment, it is important that the bystanders have to realize they have the power to take action. To prevent the escalation of violence, victims must believe that students and teachers will help them and their environment is able to provide safety. The study based on scientific narrative psychological approach, and focuses on the examination of the different perspectives of students, how peers are mentalizing with each other in case of bullying. The data collection contained responses of students (N = 138) from three schools in Hungary, and from three different area of the country (Budapest, Martfű and Barcs). The test battery include Bullying Prevalence Questionnaire, Interpersonal Reactivity Index and an instruction to get narratives about bullying, which effectiveness was tested during a pilot test. The obtained results are in line with the findings of previous bullying research: the victims are mentalizing less with their peers and experience greater personal distress when they are in identity threatening situations, thus focusing on their own difficulties rather than social signals. This isolation is an adaptive response in short-term although it seems to lead to a deficit in social skills later in life and makes it difficult for students to become socially integrated to society. In addition the results also show that students use more mental state attribution when they report verbal bullying than in case of physical abuse. Those who witness physical harassment also witness concrete answers to the problem from teachers, in contrast verbal abuse often stays without consequences. According to the results students mentalizing more in these stories because they have less normative explanation to what happened. To expanding bullying literature, this research helps to find ways to reduce school violence through community development.

Keywords: bullying, mentalization, narrative, school culture

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Authors: J. Das, T. S. Mahule, V. V. Srinivasu

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Electron spin resonance (ESR) study at 9.45 GHz and a field modulation frequency of 100Hz was performed on bulk polycrystalline samples of Mn:TM (Fe/Ni) and Mn:RE (Gd/Sm) co doped ZnO samples with composition Zn1-xMn:TM/RE)xO synthesised by solid state reaction route and sintered at 500 0C temperature. The room temperature microwave absorption data collected by sweeping the DC magnetic field from -500 to 9500 G for the Mn:Fe and Mn:Ni co doped ZnO samples exhibit a rarely reported non resonant low field absorption (NRLFA) in addition to a strong absorption at around 3350G, usually associated with ferromagnetic resonance (FMR) satisfying Larmor’s relation due to absorption in the full saturation state. Observed low field absorption is distinct to ferromagnetic resonance even at low temperature and shows hysteresis. Interestingly, it shows a phase opposite with respect to the main ESR signal of the samples, which indicates that the low field absorption has a minimum value at zero magnetic field whereas the ESR signal has a maximum value. The major resonance peak as well as the peak corresponding to low field absorption exhibit asymmetric nature indicating magnetic anisotropy in the sample normally associated with intrinsic ferromagnetism. Anisotropy parameter for Mn:Ni codoped ZnO sample is noticed to be quite higher. The g values also support the presence of oxygen vacancies and clusters in the samples. These samples have shown room temperature ferromagnetism in the SQUID measurement. However, in rare earth (RE) co doped samples (Zn1-x (Mn: Gd/Sm)xO), which show paramagnetic behavior at room temperature, the low field microwave signals are not observed. As microwave currents due to itinerary electrons can lead to ohmic losses inside the sample, we speculate that more delocalized 3d electrons contributed from the TM dopants facilitate such microwave currents leading to the loss and hence absorption at the low field which is also supported by the increase in current with increased micro wave power. Besides, since Fe and Ni has intrinsic spin polarization with polarisability of around 45%, doping of Fe and Ni is expected to enhance the spin polarization related effect in ZnO. We emphasize that in this case Fe and Ni doping contribute to polarized current which interacts with the magnetization (spin) vector and get scattered giving rise to the absorption loss.

Keywords: co-doping, electron spin resonance, hysteresis, non-resonant microwave absorption

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Authors: Zhenyu Zhang, Hsi-Hsien Wei

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Highway networks play a vital role in post-disaster recovery for disaster-damaged areas. Damaged bridges in such networks can disrupt the recovery activities by impeding the transportation of people, cargo, and reconstruction resources. Therefore, rapid restoration of damaged bridges is of paramount importance to long-term disaster recovery. In the post-disaster recovery phase, the key to restoration scheduling for a highway network is prioritization of bridge-repair tasks. Resilience is widely used as a measure of the ability to recover with which a network can return to its pre-disaster level of functionality. In practice, highways will be temporarily blocked during the downtime of bridge restoration, leading to the decrease of highway-network functionality. The failure to take downtime effects into account can lead to overestimation of network resilience. Additionally, post-disaster recovery of highway networks is generally divided into emergency bridge repair (EBR) in the response phase and long-term bridge repair (LBR) in the recovery phase, and both of EBR and LBR are different in terms of restoration objectives, restoration duration, budget, etc. Distinguish these two phases are important to precisely quantify highway network resilience and generate suitable restoration schedules for highway networks in the recovery phase. To address the above issues, this study proposes a novel resilience quantification method for the optimization of long-term bridge repair schedules (LBRS) taking into account the impact of EBR activities and restoration downtime on a highway network’s functionality. A time-dependent integer program with recursive functions is formulated for optimally scheduling LBR activities. Moreover, since uncertainty always exists in the LBRS problem, this paper extends the optimization model from the deterministic case to the stochastic case. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. The proposed methods are tested using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that, in this case, neglecting the bridge restoration downtime can lead to approximately 15% overestimation of highway network resilience. Moreover, accounting for the impact of EBR on network functionality can help to generate a more specific and reasonable LBRS. The theoretical and practical values are as follows. First, the proposed network recovery curve contributes to comprehensive quantification of highway network resilience by accounting for the impact of both restoration downtime and EBR activities on the recovery curves. Moreover, this study can improve the highway network resilience from the organizational dimension by providing bridge managers with optimal LBR strategies.

Keywords: disaster management, highway network, long-term bridge repair schedule, resilience, restoration downtime

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Authors: Ioannis Iglezakis, Theodoros D. Trokanas, Panagiota Kiortsi

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This paper aims to explore major legal issues arising from the collection and processing of Health Big Data in the light of the new European secondary legislation for the protection of personal data of natural persons, placing emphasis on the General Data Protection Regulation 679/2016. Whether Big Health Data can be characterised as ‘personal data’ or not is really the crux of the matter. The legal ambiguity is compounded by the fact that, even though the processing of Big Health Data is premised on the de-identification of the data subject, the possibility of a combination of Big Health Data with other data circulating freely on the web or from other data files cannot be excluded. Another key point is that the application of some provisions of GPDR to Big Health Data may both absolve the data controller of his legal obligations and deprive the data subject of his rights (e.g., the right to be informed), ultimately undermining the fundamental right to the protection of personal data of natural persons. Moreover, data subject’s rights (e.g., the right not to be subject to a decision based solely on automated processing) are heavily impacted by the use of AI, algorithms, and technologies that reclaim health data for further use, resulting in sometimes ambiguous results that have a substantial impact on individuals. On the other hand, as the COVID-19 pandemic has revealed, Big Data analytics can offer crucial sources of information. In this respect, this paper identifies and systematises the legal provisions concerned, offering interpretative solutions that tackle dangers concerning data subject’s rights while embracing the opportunities that Big Health Data has to offer. In addition, particular attention is attached to the scope of ‘consent’ as a legal basis in the collection and processing of Big Health Data, as the application of data analytics in Big Health Data signals the construction of new data and subject’s profiles. Finally, the paper addresses the knotty problem of role assignment (i.e., distinguishing between controller and processor/joint controllers and joint processors) in an era of extensive Big Health data sharing. The findings are the fruit of a current research project conducted by a three-member research team at the Faculty of Law of the Aristotle University of Thessaloniki and funded by the Greek Ministry of Education and Religious Affairs.

Keywords: big health data, data subject rights, GDPR, pandemic

Procedia PDF Downloads 129

Authors: Rreze Gecaj, Corina Schanzenbach, Benedikt Kirchner, Michael Pfaffl, Bajram Berisha

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The maintenance of corpus lutem (CL) during early pregnancy in cattle is a critical and multifarious process. A luteotrophic mechanism originating from the embryo is widely accepted as the triggering signal for the CL maintenance. In the cattle, it is the interferon-tau (IFNT) secretion form conceptus that prevents CL regression and ensures progesterone production for the establishment of pregnancy. In addition to endocrine and paracrine signals, microRNA (miRNA) can also support CL sustainability during early pregnancy. MiRNA are small non-coding nucleic acids that regulate gene expression post-transcriptionally and are shown to be involved in the modulation of CL function. However, the examination of miRNAs in corpus luteum function at the early pregnancy still remains largely uncovered. This study aims at profiling the expression of miRNA in CL during the early pregnancy in cattle by comparing it with the CL form late cycle and with the regressed CL. Corpora lutea were assigned in two different groups during the cycle (C13 group, late CL: days 13-18 and C18, regressed CL group: day >18) and during the early pregnancy (group P: 1-2 month). The estrous cycle was determined by macroscopic examination and to age the fetus crown-rump length measurement was applied. A total of 9 corpora lutea from individual animals were included in the study, three corpora lutea for each group. MiRNAs population was profiled using small RNA next-generation sequencing and biologically significant miRNAs were evaluated for their differential expression using the DESeq2-methodology. We show that 6 differentially expressed miRNAs (bta-mir-2890, -2332, -2441-3p, -148b, -1248 and -29c) are common to both comparisons, P vs C13 and P vs C18. While for each stage individually we have identified unique miRNAs differentially expressed only for the given comparison. bta-miR-23a and -769 were unique miRNAs differentially expressed in P vs C13, whereas forty-four unique miRNAs were identified as differentially expressed in P vs C18. These data confirm that miRNAs are highly abundant in luteal tissue during early pregnancy and potentially regulate the CL maintenance at this stage of fetus development.

Keywords: bovine, corpus luteum, microRNA, pregnancy, RNA-Seq

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Authors: Thais Cardoso Franco, Caio Nahuel Sousa Fagonde, Willer Gomes dos Santos

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Aurora Borealis is an optical phenomenon composed of luminous events observed in the night skies in the polar regions resulting from disturbances in the magnetosphere due to the impact of solar wind particles with the Earth's upper atmosphere, channeled by the Earth's magnetic field, which causes atmospheric molecules to become excited and emit electromagnetic spectrum, leading to the display of lights in the sky. However, there are still different implications of this phenomenon under study: high intensity auroras are often accompanied by geomagnetic storms that cause blackouts on Earth and impair the transmission of signals from the Global Navigation Satellite Systems (GNSS). Auroras are also known to occur on other planets and exoplanets, so the activity is an indication of active space weather conditions that can aid in learning about the planetary environment. In order to improve understanding of the phenomenon, this research aims to design a satellite formation flying solution for collecting and transmitting data for monitoring aurora borealis in northern hemisphere, an approach that allows studying the event with multipoint data collection in a reduced time interval, in order to allow analysis from the beginning of the phenomenon until its decline. To this end, the ideal number of satellites, the spacing between them, as well as the ideal topology to be used will be analyzed. From an orbital study, approaches from different altitudes, eccentricities and inclinations will also be considered. Given that at large relative distances between satellites in formation, controllers tend to fail, a study on the efficiency of nonlinear adaptive control methods from the point of view of position maintenance and propellant consumption will be carried out. The main orbital perturbations considered in the simulation: non-homogeneity terrestrial, atmospheric drag, gravitational action of the Sun and the Moon, accelerations due to solar radiation pressure and relativistic effects.

Keywords: formation flying, nonlinear adaptive control method, aurora borealis, adaptive SDRE method

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Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

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The U.S. Federal Emergency Management Agency (FEMA) developed flood maps based on experts’ experience and estimates of the probability of flooding. Current flood-risk models evaluate flood risk with regional and subjective measures without impact from torrential rain and nuisance flooding at the neighborhood level. Nuisance flooding occurs in small areas in the community, where a few streets or blocks are routinely impacted. This type of flooding event occurs when torrential rainstorm combined with high tide and sea level rise temporarily exceeds a given threshold. In South Florida, this threshold is 1.7 ft above Mean Higher High Water (MHHW). The National Weather Service defines torrential rain as rain deposition at a rate greater than 0.3-inches per hour or three inches in a single day. Data from the Florida Climate Center, 1970 to 2020, shows 371 events with more than 3-inches of rain in a day in 612 months. The purpose of this research is to develop a data-driven method to determine comprehensive analytical damage-avoidance criteria that account for nuisance flood events at the single-family home level. The method developed uses the Failure Mode and Effect Analysis (FMEA) method from the American Society of Quality (ASQ) to estimate the Damage Avoidance (DA) preparation for a 1-day 100-year storm. The Consequence of Nuisance Flooding (CoNF) is estimated from community mitigation efforts to prevent nuisance flooding damage. The Probability of Nuisance Flooding (PoNF) is derived from the frequency and duration of torrential rainfall causing delays and community disruptions to daily transportation, human illnesses, and property damage. Urbanization and population changes are related to the U.S. Census Bureau's annual population estimates. Data collected by the United States Department of Agriculture (USDA) Natural Resources Conservation Service’s National Resources Inventory (NRI) and locally by the South Florida Water Management District (SFWMD) track the development and land use/land cover changes with time. The intent is to include temporal trends in population density growth and the impact on land development. Results from this investigation provide the risk of nuisance flooding as a function of CoNF and PoNF for coastal areas of South Florida. The data-based criterion provides awareness to local municipalities on their flood-risk assessment and gives insight into flood management actions and watershed development.

Keywords: flood risk, nuisance flooding, urban flooding, FMEA

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Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

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Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

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Authors: Mirzet SeHo, Alaa Alaabed, Mansur Masih

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In theory, risk-sharing-based financing (RSF) is considered a corner stone of Islamic finance. It is argued to render Islamic banks more resilient to shocks. In practice, however, this feature of Islamic financial products is almost negligible. Instead, debt-based instruments, with conventional like features, have overwhelmed the nascent industry. In addition, the framework of present-day economic, regulatory and financial reality inevitably exposes Islamic banks in dual banking systems to problems of conventional banks. This includes, but is not limited to, interest rate risk. Empirical evidence has, thus far, confirmed such exposures, despite Islamic banks’ interest-free operations. This study applies system GMM in modeling the determinants of RSF, and finds that RSF is insensitive to changes in interest rates. Hence, our results provide support to the “stability” view of risk-sharing-based financing. This suggests RSF as the way forward for risk management at Islamic banks, in the absence of widely acceptable Shariah compliant hedging instruments. Further support to the stability view is given by evidence of counter-cyclicality. Unlike debt-based lending that inflates artificial asset bubbles through credit expansion during the upswing of business cycles, RSF is negatively related to GDP growth. Our results also imply a significantly strong relationship between risk-sharing deposits and RSF. However, the pass-through of these deposits to RSF is economically low. Only about 40% of risk-sharing deposits are channeled to risk-sharing financing. This raises questions on the validity of the industry’s claim that depositors accustomed to conventional banking shun away from risk sharing and signals potential for better balance sheet management at Islamic banks. Overall, our findings suggest that, on the one hand, Islamic banks can gain ‘independence’ from conventional banks and interest rates through risk-sharing products, the potential for which is enormous. On the other hand, RSF could enable policy makers to improve systemic stability and restrain excessive credit expansion through its countercyclical features.

Keywords: Islamic banks, risk-sharing, financing, interest rate, dynamic system GMM

Procedia PDF Downloads 316

Authors: Yusuf Ulaş Kabukçu, Si̇nan Çeli̇k, Onur Salan, Mai̇de Altuntaş, Mert Can Dalkiran, Gökseni̇n Bozdağ, Metehan Bulut, Fati̇h Yaman

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This study presents a more compact implementation of the 2.4GHz MIT Coffee Can Doppler Radar for 2.6GHz operating frequency. The main difference of our prototype depends on the use of microstrip antennas which makes it possible to transport with a small robotic vehicle. We have designed our radar system with two different channels: Tx and Rx. The system mainly consists of Voltage Controlled Oscillator (VCO) source, low noise amplifiers, microstrip antennas, splitter, mixer, low pass filter, and necessary RF connectors with cables. The two microstrip antennas, one is element for transmitter and the other one is array for receiver channel, was designed, fabricated and verified by experiments. The system has two operation modes: speed detection and range detection. If the switch of the operation mode is ‘Off’, only CW signal transmitted for speed measurement. When the switch is ‘On’, CW is frequency-modulated and range detection is possible. In speed detection mode, high frequency (2.6 GHz) is generated by a VCO, and then amplified to reach a reasonable level of transmit power. Before transmitting the amplified signal through a microstrip patch antenna, a splitter used in order to compare the frequencies of transmitted and received signals. Half of amplified signal (LO) is forwarded to a mixer, which helps us to compare the frequencies of transmitted and received (RF) and has the IF output, or in other words information of Doppler frequency. Then, IF output is filtered and amplified to process the signal digitally. Filtered and amplified signal showing Doppler frequency is used as an input of audio input of a computer. After getting this data Doppler frequency is shown as a speed change on a figure via Matlab script. According to experimental field measurements the accuracy of speed measurement is approximately %90. In range detection mode, a chirp signal is used to form a FM chirp. This FM chirp helps to determine the range of the target since only Doppler frequency measured with CW is not enough for range detection. Such a FMCW Doppler radar may be used in border security of the countries since it is capable of both speed and range detection.

Keywords: doppler radar, FMCW, range detection, speed detection

Procedia PDF Downloads 398

Authors: Aya Al Masri, Naima Oubenali, Safoin Aktaou, Thibault Julien, Malorie Martin, Fouad Maaloul

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Introduction: The increased number of performed 'Computed Tomography (CT)' examinations raise public concerns regarding associated stochastic risk to patients. In its Publication 102, the ‘International Commission on Radiological Protection (ICRP)’ emphasized the importance of managing patient dose, particularly from repeated or multiple examinations. We developed a Dose Archiving and Communication System that gives multiple dose indexes (organ dose, effective dose, and skin-dose mapping) for patients undergoing radiological imaging exams. The aim of this study is to compare the organ dose values given by our software for patients undergoing CT exams with those of another software named "VirtualDose". Materials and methods: Our software uses Monte Carlo simulations to calculate organ doses for patients undergoing computed tomography examinations. The general calculation principle consists to simulate: (1) the scanner machine with all its technical specifications and associated irradiation cases (kVp, field collimation, mAs, pitch ...) (2) detailed geometric and compositional information of dozens of well identified organs of computational hybrid phantoms that contain the necessary anatomical data. The mass as well as the elemental composition of the tissues and organs that constitute our phantoms correspond to the recommendations of the international organizations (namely the ICRP and the ICRU). Their body dimensions correspond to reference data developed in the United States. Simulated data was verified by clinical measurement. To perform the comparison, 270 adult patients and 150 pediatric patients were used, whose data corresponds to exams carried out in France hospital centers. The comparison dataset of adult patients includes adult males and females for three different scanner machines and three different acquisition protocols (Head, Chest, and Chest-Abdomen-Pelvis). The comparison sample of pediatric patients includes the exams of thirty patients for each of the following age groups: new born, 1-2 years, 3-7 years, 8-12 years, and 13-16 years. The comparison for pediatric patients were performed on the “Head” protocol. The percentage of the dose difference were calculated for organs receiving a significant dose according to the acquisition protocol (80% of the maximal dose). Results: Adult patients: for organs that are completely covered by the scan range, the maximum percentage of dose difference between the two software is 27 %. However, there are three organs situated at the edges of the scan range that show a slightly higher dose difference. Pediatric patients: the percentage of dose difference between the two software does not exceed 30%. These dose differences may be due to the use of two different generations of hybrid phantoms by the two software. Conclusion: This study shows that our software provides a reliable dosimetric information for patients undergoing Computed Tomography exams.

Keywords: adult and pediatric patients, computed tomography, organ dose calculation, software comparison

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Authors: Kai Pai Huang

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Background: There are several types of plasma cell neoplasms including multiple myeloma, plasmacytoma, lymphoplasmacytic lymphoma, and monoclonal gammopathy of undetermined significance (MGUS) are found in our lab. Today, we want to compare with two cases using the method of capillary electrophoresis. Method: Serum is prepared and electrophoresis is performed at alkaline PH in a capillary using the Sebia® Capillary 2. Albumin and globulins are detected by the detector which is located in the cathode of the capillary and the signals are transformed to peaks. Serum was treated with beta-mercaptoethanol which reducing the polymerized immunoglobulin to monomer immunoglobulin to clarify two M-protein are secreted from the same plasma cell clone in bone marrow. Result: Case 1: A 78-year-old female presenting dysuria, oliguria and leg edema for several months. Laboratory data showed proteinuria, leukocytosis, results of high serum IgA and lambda light chain. A renal biopsy found amyloid fibrils in the glomerular mesangial area. Serum protein electrophoresis shows a major monoclonal peak in the β region and minor small peak in gamma region, and the immunotyping studies for serum showed two IgA/λ type. Case 2: A 55-year-old male presenting abdominal distension and low back pain for more than one month. Laboratory data showed T12 T8 compression fracture, results of high serum IgM and kappa light chain. Bone marrow aspiration showed the cells from the bone marrow are B cells with monotypic kappa chain expression. Bone marrow biopsy found this is lymphoplasmacytic lymphoma (Waldenstrom macroglobulin). Serum protein electrophoresis shows a monoclonal peak in the β region and the immunotyping studies for serum showed IgM/κ type. Conclusion: Plasma cell neoplasm can be diagnosed by many examinations. Among them, using capillary electrophoresis by a lab can separate several types of gammopathy and the quantification of a monoclonal peak can be used to evaluate the patients’ prognosis or treatment.

Keywords: plasma cell neoplasm, capillary electrophoresis, serum protein electrophoresis, immunotyping

Procedia PDF Downloads 146