Search results for: Alexei De Bono

Authors: Gabriele Borg, Alexei De Bono, Charlie Abela

Abstract:

There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale.

Keywords: Big Data, vehicular traffic, traffic management, mobile data patterns

Procedia PDF Downloads 109

Authors: Luisa Mesquita Oliveira Ribeiro, Alexei Manso Correa Machado

Abstract:

Handwritten signature is a unique form for recognizing an individual, used to discern documents, carry out investigations in the criminal, legal, banking areas and other applications. Signature verification is based on large amounts of biometric data, as they are simple and easy to acquire, among other characteristics. Given this scenario, signature forgery is a worldwide recurring problem and fast and precise techniques are needed to prevent crimes of this nature from occurring. This article carried out a study on the efficiency of the Capsule Network in analyzing and recognizing signatures. The chosen architecture achieved an accuracy of 98.11% and 80.15% for the CEDAR and GPDS databases, respectively.

Keywords: biometrics, deep learning, handwriting, signature forgery

Procedia PDF Downloads 83

Authors: Fereshteh Ganjavi, Rachel Schaffer, Varsha Jorawar

Abstract:

Elena’s Light is a non-profit organization focused on building brighter futures for refugees, especially women and children. Our mission is to empower refugee women and children by addressing social, legal, and public health issues that predominantly concern them. Elena’s Light offers a range of services that support refugees from structural disadvantages, cultural and social stress, marginalization, and other stressors related to migration. Using a three-pronged approach, our programs focus on legal advocacy, English language acquisition, and health and wellness. Following the Afghan humanitarian crisis, Elena’s Light has developed and intensified advocacy efforts in the legal realm to address the influx of refugees who desperately need assistance. We developed and hosted a Know Your Rights presentation with local immigration lawyers and professionals in February 2022 on the Afghan Humanitarian Parole, which was very successful with over 100 attendees. Elena’s Light is hosting the second Know Your Rights session in early August 2022 on immigration options for Afghans, including Temporary Protected Status (TPS), asylum, Special Immigrant Visa (SIV), and humanitarian parole. Lastly, EL is also leading the local initiative to develop a pro-bono committee to respond to the overwhelming need for lawyers to work on legal cases for Afghan during this crisis. Furthermore, through our other services, we provide free, in-home customizable ESL tutoring sessions to refugee women with a focus on driver’s education, facilitating acculturation, and improving employment opportunities. We also provide in-home maternal, pediatric, and mental health education and wellness services that are aimed at addressing the explicit and implicit barriers to healthcare for refugee populations. Elena’s Light’s diverse community aims to counter the structural disadvantages and anxiety-inducing emotions and experiences related to being a refugee. We would like to join this International Conference on Refugee Law since protecting refugee rights is our mission. We would like to share what we have learned from our legal initiatives for refugee rights. We would also like to listen, learn from, and discuss with experts and researchers how to better understand and advocate for refugee rights. We hope to improve our understanding of how to provide better legal aid for our clients through this conference.

Keywords: legal, advocacy, Afghan humanitarian crisis, policy, pro-bono

Procedia PDF Downloads 134

Authors: Dmytro O. Plutenko, Alexei D. Kiselev, Mikhail V. Vasnetsov

Abstract:

We present the results of our analytical and computational study of Laguerre-Gaussian (LG) beams scattering by spherical homogeneous isotropic particles located on the axis of the beam. We consider different types of scatterers (dielectric, metallic and double negative metamaterials) and different polarizations of the LG beams. A possibility to generate photonic nanojets using metallic and double negative metamaterial Mie scatterers is shown. We have studied the properties of such nonclassical nanojets and discovered new types of the nanojets characterized by zero on-axes magnetic (or electric) field with the electric (or magnetic) field polarized along the z-axis.

Keywords: double negative metamaterial, Laguerre-Gaussian beam, Mie scattering, optical vortices, photonic nanojets

Procedia PDF Downloads 221

Authors: Francesco Morgan Bono, Simone Cinquemani

Abstract:

This research aims to enhance bridge monitoring by employing innovative techniques that incorporate exogenous factors into the modeling of sensor signals, thereby improving long-term predictability beyond traditional static methods. Using real datasets from two different bridges equipped with Linear Variable Displacement Transducer (LVDT) sensors, the study investigates the fundamental principles governing sensor behavior for more precise long-term forecasts. Additionally, the research evaluates performance on noisy and synthetically damaged data, proposing a residual-based alarm system to detect anomalies in the bridge. In summary, this novel approach combines advanced modeling, exogenous factors, and anomaly detection to extend prediction horizons and improve preemptive damage recognition, significantly advancing structural health monitoring practices.

Keywords: structural health monitoring, dynamic models, sindy, railway bridges

Procedia PDF Downloads 38

Authors: Sariah Abang, S. M. Anisuzzaman, Awang Bono, D. Krishnaiah, S. Rasmih

Abstract:

Biodiesel is a potential renewable energy due to biodegradable and non-toxic. The challenge of its commercialization is associated with high production cost due to its feedstock also useful in various food products. Non-competitive feedstock such as waste cooking oils normally contains a large amount of free fatty acids (FFAs). Large amount of fatty acid degrades the alkaline catalyst in the biodiesel production, thereby decreasing the biodiesel production rate. Generally, biodiesel production processes including esterification and trans-esterification are conducting in a mixed system, in which the hydrodynamic effect on the reaction could not be completely defined. The aim of this study was to investigate the effect of variation rate constant and activation energy on energy consumption of biodiesel production. Usually, the changes of rate constant and activation energy depend on the operating temperature and the degradation of catalyst. By varying the activation energy and kinetic rate constant, the effects can be seen on the energy consumption of biodiesel production. The result showed that the energy consumption of biodiesel is dependent on the changes of rate constant and activation energy. Furthermore, this study was simulated using Aspen HYSYS.

Keywords: methanol, palm oil, simulation, transesterification, triolein

Procedia PDF Downloads 320

Authors: Gabriele Borg, Alexei Debono, Charlie Abela

Abstract:

There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale. Furthermore, a series of traffic prediction graph neural network models are conducted to compare MalTra to large-scale traffic datasets.

Keywords: graph neural networks, traffic management, big data, mobile data patterns

Procedia PDF Downloads 128

Authors: Dmitry Dikarev, Ajit Nimbalker, Alexei Davydov

Abstract:

Polar coding is a novel example of error correcting codes, which can achieve Shannon limit at block length N→∞ with log-linear complexity. Active research is being carried to adopt this theoretical concept for using in practical applications such as 5th generation wireless communication systems. Cyclic redundancy check (CRC) error detection code is broadly used in conjunction with successive cancellation list (SCL) decoding algorithm to improve finite-length polar code performance. However, there are two issues: increase of code block payload overhead by CRC bits and decrease of CRC error-detection capability. This paper proposes a method to control CRC overhead and false alarm rate of polar decoding. As shown in the computer simulations results, the proposed method provides the ability to use any set of CRC polynomials with any list size while maintaining the desired level of false alarm rate. This level of flexibility allows using polar codes in 5G New Radio standard.

Keywords: 5G New Radio, channel coding, cyclic redundancy check, list decoding, polar codes

Procedia PDF Downloads 238

Authors: Kamel A. Abd-Elsalam, Alexei R. Khokhlov

Abstract:

Studies on bioefficacy (in vitro and in vivo) and mode of action of the nanocides against the most important plant diseases in Egypt and Russia might assist in the goal of sustainable agriculture. To our knowledge, few researchers have evaluated the combined antimicrobial effect of inorganic nanoparticles (NPs) with bioorganic pesticides for controlling plant pathogens in the greenhouse and open field, decontrol investigated synergistic effect. In the current project, we will develop eco-friendly alternative management strategies including the use of heavy nanometal-tolerant Trichoderma strains and the main effective material in conventional fungicides (curpic, sulfur, phosphorus and zinc) for controlling plant diseases. Studies on bioefficacy and the mechanism of the nanocides against the most important plant diseases in Egypt were evaluated. There is a growing need to establish mechanisms of action for nano bio and/or fungicides to assist the design of new compounds or combinations of compounds, in order to understand resistance mechanisms and to provide a focus for toxicological attention. Nanofungicides represent an emerging technological development that could offer a range of benefits including increased efficacy, durability, and a reduction in the amounts of active ingredients that need to be used.

Keywords: biohybrids, biocides, bioagent, plant pathogenic fungi

Procedia PDF Downloads 255

Authors: Giorgio Visentin, Inna S. Kalinina, Alexei A. Buchachenko

Abstract:

In the ambit of intermolecular interactions, a combination rule is defined as a relation linking a potential parameter for the interaction of two unlike species with the same parameters for interaction pairs of like species. Some of their most exemplificative applications cover the construction of molecular dynamics force fields and dispersion-corrected density functionals. Here, an extended combination rule is proposed, relating the dipole-dipole dispersion coefficients for the interaction of like target species to the same coefficients for the interaction of the target and a set of partner species. The rule can be devised in two different ways, either by uniform discretization of the Casimir-Polder integral on a Gauss-Legendre quadrature or by relating the dynamic polarizabilities of the target and the partner species. Both methods return the same system of linear equations, which requires the knowledge of the dispersion coefficients for interaction between the partner species to be solved. The test examples show a high accuracy for dispersion coefficients (better than 1% in the pristine test for the interaction of Yb atom with rare gases and alkaline-earth metal atoms). In contrast, the rule does not ensure correct monotonic behavior of the dynamic polarizability of the target species. Acknowledgment: The work is supported by Russian Science Foundation grant # 17-13-01466.

Keywords: combination rule, dipole-dipole dispersion coefficient, Casimir-Polder integral, Gauss-Legendre quadrature

Procedia PDF Downloads 178

Authors: Adam Ahmed Hosney

Abstract:

The existence of a culture of corruption within an institution, such as the police, could be a sign of failure from various angles. There is a general perception among Ghanaians that the most corrupt institution is the police service. The purpose of this study is to formulate and analyze a nonlinear mathematical model to investigate corruption as an epidemic within the Ghana police service, this study revealed the basic reproduction number for corruption extinction and corruption survival. The threshold conditions for all kinds of equilibrium points are obtained using linearization methods and Lyapunov functional methods, and they demonstrate local asymptotic stability for both corrupt endemic and corrupt free equilibrium states. The model was analyzed qualitatively, and the solution was derived. The model appears to be positively invariant and attractive. Therefore, the region exhibits positive invariance. Thus, it is adequate to think about the dynamics of the model. For the purpose of illustrating the solution, the graphic result was presented and discussed. Results show that corruption will die out within the police service if the government shows no tolerance for those involved in corrupt practices. Study findings indicate that leaders should be trustworthy, demonstrate a complete and viable commitment to addressing corruption, and make it a priority to provide mass education to all citizens as well as using religious leaders to fight corruption since most Ghanaians are religious and trust their leaders.

Keywords: mathematical model, differential equation, dynamical system, simulation

Procedia PDF Downloads 26

Authors: S. M. Anisuzzaman, Sariah Abang, Awang Bono, D. Krishnaiah, N. M. Ismail, G. B. Sandrison

Abstract:

Wax and asphaltene are high molecular weighted compounds that contribute to the stability of crude oil at a dispersed state. Transportation of crude oil along pipelines from the oil rig to the refineries causes fluctuation of temperature which will lead to the coagulation of wax and flocculation of asphaltenes. This paper focuses on the prevention of wax and asphaltene precipitate deposition on the inner surface of the pipelines by using a wax inhibitor and an asphaltene dispersant. The novelty of this prevention method is the combination of three substances; a wax inhibitor dissolved in a wax inhibitor solvent and an asphaltene solvent, namely, ethylene-vinyl acetate (EVA) copolymer dissolved in methylcyclohexane (MCH) and toluene (TOL) to inhibit the precipitation and deposition of wax and asphaltene. The objective of this paper was to optimize the percentage composition of each component in this inhibitor which can maximize the viscosity reduction of crude oil. The optimization was divided into two stages which are the laboratory experimental stage in which the viscosity of crude oil samples containing inhibitor of different component compositions is tested at decreasing temperatures and the data optimization stage using response surface methodology (RSM) to design an optimizing model. The results of experiment proved that the combination of 50% EVA + 25% MCH + 25% TOL gave a maximum viscosity reduction of 67% while the RSM model proved that the combination of 57% EVA + 20.5% MCH + 22.5% TOL gave a maximum viscosity reduction of up to 61%.

Keywords: asphaltene, ethylene-vinyl acetate, methylcyclohexane, toluene, wax

Procedia PDF Downloads 415

Authors: Saroj Poudel, Joshua Mancini, Douglas Pike, Jennifer Timm, Alexei Tyryshkin, Vikas Nanda, Paul Falkowski

Abstract:

On the early Earth, protein-metal complexes likely harvested energy from a reduced environment. These complexes would have been precursors to the metabolic enzymes of ancient organisms. Hydrogenase is an essential enzyme in most anaerobic organisms for the reduction and oxidation of hydrogen in the environment and is likely one of the earliest evolved enzymes. To attempt to reinvent a precursor to modern hydrogenase, we computationally designed a short thirteen amino acid peptide that binds the often-required catalytic transition metal Nickel in hydrogenase. This simple complex can achieve hundreds of hydrogen evolution cycles using light energy in a broad range of temperature and pH. Biophysical and structural investigations strongly indicate the peptide forms a di-nickel active site analogous to Acetyl-CoA synthase, an ancient protein central to carbon reduction in the Wood-Ljungdahl pathway and capable of hydrogen evolution. This work demonstrates that prior to the complex evolution of multidomain enzymes, early peptide-metal complexes could have catalyzed energy transfer from the environment on the early Earth and enabled the evolution of modern metabolism

Keywords: hydrogenase, prebiotic enzyme, metalloenzyme, computational design

Procedia PDF Downloads 216

Authors: Viknesh Kasthuri, Victoria Angenent-Mari, Jade Wexler

Abstract:

The COVID-19 pandemic dramatically altered the landscape of asylum medicine. Brown Human Rights Asylum Clinic (BHRAC) is a medical-student-run asylum clinic that provides pro-bono medical evaluations and forensic affidavits for individuals seeking asylum in New England. After the outbreak of COVID-19 in March 2020, BHRAC experienced numerous changes both in the number of clients requesting services as well as in the resource needs of these clients. Uniquely, BHRAC assesses the needs of clients during their affidavit interview and seeks to address these needs by connecting clients to local community organizations and resources. Data regarding the specific needs of clients range from 2019-present day. Analysis of internal BHRAC’s internal data suggested a small increase in requests for assistance with light and gas (from 5% of total resource requests pre-COVID to 11%), as well as a decrease in requests for mental health services (from 20% of resources pre-COVID to 13% post-COVID). Furthermore, BHRAC witnessed a decline in clinic volume during the second half of 2020. In short, our data suggest that the pandemic affected asylum seekers' access to medico-legal services and the resources they need. Future research with larger sample sizes and in other geographic locations is required to determine the holistic impact of the COVID-19 pandemic on asylum seekers.

Keywords: asylum clinic, asylum medicine, COVID, social determinants of health

Procedia PDF Downloads 103

Authors: Nicholas Agyepong, Paul Gyan

Abstract:

Inappropriate prescribing of antibiotic is a common healthcare concern globally resulted in an increased risk of adverse reactions and the emergence of antimicrobial resistance. The wrong antibiotic prescribing habits may lead to ineffective and unsafe treatment, worsening of disease condition, and thus increase in health care costs. The study was to examine the antibiotic prescribing pattern and associated risk factors at Regional Hospital in the Bono region of Ghana. A retrospective cross-sectional study was conducted to describe the current prescribing practices at the Hospital from January 2014 to December, 2021. A systematic random sampling method was used to select the participants for the study. STATA version 16 software was used for data management and analysis. Descriptive statistics and logistic regression analysis were used to analyze the data. Statistical significance set at p<0.05. Antibiotic consumption was equivalent to 11 per 1000 inhabitants consuming 1 DDD per day. Most common prescribed antibiotic was amoxicillin/clavulanic acid (14.39%) followed by erythromycin (11.44%), and ciprofloxacin (11.36%). Antibiotics prescription have been steadily increased over the past eight years (2014: n=59,280 to 2021: n=190,320). Prescribers above the age of 35 were more likely to prescribe antibiotics than those between the ages of 20 and 25 (COR=21.00; 95% CI: 1.78 – 48.10; p=0.016). Prescribers with at least 6 years of experience were also significantly more likely to prescribe antibiotics than those with at most 5 years of experience (COR=14.17; 95% CI: 2.39 – 84.07; p=0.004). Thus, the establishment of an antibiotic stewardship program in the hospitals is imperative, and further studies need to be conducted in other facilities to establish the national antibiotic prescription guideline.

Keywords: antibiotic, antimicrobial resistance, prescription, prescribers

Procedia PDF Downloads 46

Authors: Giorgio Visentin, Alexei A. Buchachenko

Abstract:

Recent proposals to use Yb dimer as an optical clock and as a sensor for non-Newtonian gravity imply the knowledge of its interaction potential. Here, the ground-state Born-Oppenheimer Yb₂ potential energy curve is represented by a semi-analytical function, consisting of short- and long-range contributions. For the former, the systematic ab initio all-electron exact 2-component scalar-relativistic CCSD(T) calculations are carried out. Special care is taken to saturate diffuse basis set component with the atom- and bond-centered primitives and reach the complete basis set limit through n = D, T, Q sequence of the correlation-consistent polarized n-zeta basis sets. Similar approaches are used to the long-range dipole and quadrupole dispersion terms by implementing the CCSD(3) polarization propagator method for dynamic polarizabilities. Dispersion coefficients are then computed through Casimir-Polder integration. The semiclassical constraint on the number of the bound vibrational levels known for the ¹⁷⁴Yb isotope is used to scale the potential function. The scaling, based on the most accurate ab initio results, bounds the interaction energy of two Yb atoms within the narrow 734 ± 4 cm⁻¹ range, in reasonable agreement with the previous ab initio-based estimations. The resulting potentials can be used as the reference for more sophisticated models that go beyond the Born-Oppenheimer approximation and provide the means of their uncertainty estimations. The work is supported by Russian Science Foundation grant # 17-13-01466.

Keywords: ab initio coupled cluster methods, interaction potential, semi-analytical function, ytterbium dimer

Procedia PDF Downloads 151

Authors: Mahmood Alsaadi, Alexei Lisitsa

Abstract:

Nowadays, medical devices rely completely on software whether as whole software or as embedded software, therefore, the organization that develops medical device software can benefit from adopting agile practices. Using agile practices in healthcare software development industries would bring benefits such as producing a product of a high-quality with low cost and in short period. However, medical device software development companies faced challenges in adopting agile practices. These due to the gaps that exist between agile practices and the requirements of healthcare regulations such as documentation, traceability, and formality. This research paper will conduct a study to investigate the adoption rate of agile practice in medical device software development, and they will extract and outline the requirements of healthcare regulations such as Food and Drug Administration (FDA), Health Insurance Portability and Accountability Act (HIPAA), and Medical Device Directive (MDD) that affect directly or indirectly on software development life cycle. Moreover, this research paper will evaluate the suitability of using agile practices in healthcare industries by analyzing the most popular agile practices such as eXtream Programming (XP), Scrum, and Feature-Driven Development (FDD) from healthcare industry point of view and in comparison with the requirements of healthcare regulations. Finally, the authors propose an agile mixture model that consists of different practices from different agile methods. As result, the adoption rate of agile practices in healthcare industries still low and agile practices should enhance with regard to requirements of the healthcare regulations in order to be used in healthcare software development organizations. Therefore, the proposed agile mixture model may assist in minimizing the gaps existing between healthcare regulations and agile practices and increase the adoption rate in the healthcare industry. As this research paper part of the ongoing project, an evaluation of agile mixture model will be conducted in the near future.

Keywords: adoption of agile, agile gaps, agile mixture model, agile practices, healthcare regulations

Procedia PDF Downloads 236

Authors: Alessandra Rossodivita, Alexei Tikhomirov, Andrey Trufanov, Nikolay Kinash, Olga Berestneva, Svetlana Nikitina, Fabio Casati, Alessandro Visconti, Tommaso Saporito

Abstract:

It is well known that world and national societies are exposed to diverse threats: anthropogenic, technological, and natural. Anthropogenic ones are of greater risks and, thus, attract special interest to researchers within wide spectrum of disciplines in efforts to lower the pertinent risks. Some researchers showed by means of multilayered, complex network models how media promotes the prevention of disease spread. To go further, not only are mass-media sources included in scope the paper suggests but also personificated social bots (socbots) linked according to reflexive theory. The novel scope considers information spread over conscious and unconscious agents while counteracting both natural and man-made threats, i.e., infections and terrorist hazards. Contrary to numerous publications on misinformation disseminated by ‘bad’ bots within social networks, this study focuses on ‘good’ bots, which should be mobilized to counter the former ones. These social bots deployed mixture with real social actors that are engaged in concerted actions at spreading, receiving and analyzing information. All the contemporary complex network platforms (multiplexes, interdependent networks, combined stem networks et al.) are comprised to describe and test socbots activities within competing information sharing tools, namely mass-media hubs, social networks, messengers, and e-mail at all phases of disasters. The scope and concomitant techniques present evidence that embedding such socbots into information sharing process crucially change the network topology of actor interactions. The change might improve or impair robustness of social network environment: it depends on who and how controls the socbots. It is demonstrated that the topological approach elucidates techno-social processes within the field and outline the roadmap to a safer world.

Keywords: complex network platform, counterterrorism, information sharing topology, social bots

Procedia PDF Downloads 162

Authors: Parminder Kaur Heer, Alexei Lapkin

Abstract:

Due to global challenges of increased competition and demand for more sustainable products/processes, there is a rising pressure on the industry to develop innovative processes. Through Process Intensification (PI) the existing and new processes may be able to attain higher efficiency. However, very few PI options are generally considered. This is because processes are typically analysed at a unit operation level, thus limiting the search space for potential process options. PI performed at more detailed levels of a process can increase the size of the search space. The different levels at which PI can be achieved is unit operations, functional and phenomena level. Physical/chemical phenomena form the lowest level of aggregation and thus, are expected to give the highest impact because all the intensification options can be described by their enhancement. The objective of the current work is thus, generation of numerous process alternatives based on phenomena, and development of their corresponding computer aided models. The methodology comprises: a) automated generation of process options, and b) automated generation of process models. The process under investigation is disintegrated into functions viz. reaction, separation etc., and these functions are further broken down into the phenomena required to perform them. E.g., separation may be performed via vapour-liquid or liquid-liquid equilibrium. A list of phenomena for the process is formed and new phenomena, which can overcome the difficulties/drawbacks of the current process or can enhance the effectiveness of the process, are added to the list. For instance, catalyst separation issue can be handled by using solid catalysts; the corresponding phenomena are identified and added. The phenomena are then combined to generate all possible combinations. However, not all combinations make sense and, hence, screening is carried out to discard the combinations that are meaningless. For example, phase change phenomena need the co-presence of the energy transfer phenomena. Feasible combinations of phenomena are then assigned to the functions they execute. A combination may accomplish a single or multiple functions, i.e. it might perform reaction or reaction with separation. The combinations are then allotted to the functions needed for the process. This creates a series of options for carrying out each function. Combination of these options for different functions in the process leads to the generation of superstructure of process options. These process options, which are formed by a list of phenomena for each function, are passed to the model generation algorithm in the form of binaries (1, 0). The algorithm gathers the active phenomena and couples them to generate the model. A series of models is generated for the functions, which are combined to get the process model. The most promising process options are then chosen subjected to a performance criterion, for example purity of product, or via a multi-objective Pareto optimisation. The methodology was applied to a two-step process and the best route was determined based on the higher product yield. The current methodology can identify, produce and evaluate process intensification options from which the optimal process can be determined. It can be applied to any chemical/biochemical process because of its generic nature.

Keywords: Phenomena, Process intensification, Process models , Process options

Procedia PDF Downloads 232

Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

Abstract:

Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

Procedia PDF Downloads 177

Authors: Dace Grauda, Inta Belogrudova, Alexei Katashev, Linda Lancere, Isaak Rashal

Abstract:

The goal of study was the elaboration of easy applicable flow cytometry method for detection of influence of abiotic stress factors on plants, which could be useful for detection of environmental stresses in urban areas. The lime tree Tillia vulgaris H. is a popular tree species used for urban landscaping in Europe and is one of the main species of street greenery in Riga, Latvia. Tree decline and low vitality has observed in the central part of Riga. For this reason lime trees were select as a model object for the investigation. During the period of end of June and beginning of July 12 samples from different urban environment locations as well as plant material from a greenhouse were collected. BD FACSJazz® cell sorter (BD Biosciences, USA) with flow cytometer function was used to test viability of plant cells. The method was based on changes of relative fluorescence intensity of cells in blue laser (488 nm) after influence of stress factors. SpheroTM rainbow calibration particles (3.0–3.4 μm, BD Biosciences, USA) in phosphate buffered saline (PBS) were used for calibration of flow cytometer. BD PharmingenTM PBS (BD Biosciences, USA) was used for flow cytometry assays. The mean fluorescence intensity information from the purified cell suspension samples was recorded. Preliminary, multiple gate sizes and shapes were tested to find one with the lowest CV. It was found that low CV can be obtained if only the densest part of plant cells forward scatter/side scatter profile is analysed because in this case plant cells are most similar in size and shape. The young pollen cells in one nucleus stage were found as the best for detection of influence of abiotic stress. For experiments only fresh plant material was used– the buds of Tillia vulgaris with diameter 2 mm. For the cell suspension (in vitro culture) establishment modified protocol of microspore culture was applied. The cells were suspended in the MS (Murashige and Skoog) medium. For imitation of dust of urban area SiO2 nanoparticles with concentration 0.001 g/ml were dissolved in distilled water. Into 10 ml of cell suspension 1 ml of SiO2 nanoparticles suspension was added, then cells were incubated in speed shaking regime for 1 and 3 hours. As a stress factor the irradiation of cells for 20 min by UV was used (Hamamatsu light source L9566-02A, L10852 lamp, A10014-50-0110), maximum relative intensity (100%) at 365 nm and at ~310 nm (75%). Before UV irradiation the suspension of cells were placed onto a thin layer on a filter paper disk (diameter 45 mm) in a Petri dish with solid MS media. Cells without treatment were used as a control. Experiments were performed at room temperature (23-25 °C). Using flow cytometer BS FACS Software cells plot was created to determine the densest part, which was later gated using oval-shaped gate. Gate included from 95 to 99% of all cells. To determine relative fluorescence of cells logarithmic fluorescence scale in arbitrary fluorescence units were used. 3x103 gated cells were analysed from the each sample. The significant differences were found among relative fluorescence of cells from different trees after treatment with SiO2 nanoparticles and UV irradiation in comparison with the control.

Keywords: flow cytometry, fluorescence, SiO2 nanoparticles, UV irradiation

Procedia PDF Downloads 412