Search results for: bi-directional long and short-term memory networks

Authors: Kyunghee Oh, Dooho Choi

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Although there is no theoretical weakness in a cryptographic algorithm, Side Channel Analysis can find out some secret data from the physical implementation of a cryptosystem. The analysis is based on extra information such as timing information, power consumption, electromagnetic leaks or even sound which can be exploited to break the system. Differential Power Analysis is one of the most popular analyses, as computing the statistical correlations of the secret keys and power consumptions. It is usually necessary to calculate huge data and takes a long time. It may take several weeks for some devices with countermeasures. We suggest and evaluate the methods to shorten the time to analyze cryptosystems. Our methods include distributed computing and parallelized processing.

Keywords: DPA, distributed computing, parallelized processing, side channel analysis

Procedia PDF Downloads 428

Authors: Sukhbir Singh

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This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

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Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

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Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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Authors: Lawrence Ngalim

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The paucity of entrepreneurial finance in Sub-Saharan Africa (SSA) can plausibly be tied to her comparatively less-developed capital markets, which potentially hurts entrepreneurial activities. The high rate of informality in SSA worsens information asymmetry, which restricts the supply of funds in a heavily bank-led environment. In this paper, we ask whether the adoption of recent technological improvements in delivering financial services, such as crowdfunding, assists the financially excluded within Africa. Secondly, we investigate the individual determinants of crowdfunding, such as income, level of education, demographics, culture/trust, and the effects of crowdfunding on households’ usage of formal financial services. The paper discusses the long-term policy implications of this particular type of fintech in achieving financial inclusion within the regional bloc and its advantage for Africa-Agenda-2063.

Keywords: fintech, banks, entrepreneurship, regional integration

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Authors: Sombol Mokhles

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Tackling climate change requires expanding networking opportunities between a diverse range of cities to accelerate climate actions. Existing climate city networks have limitations in actively engaging “ordinary” cities in networking processes between cities, as they encourage a few powerful cities to be followed by the many “ordinary” cities. To reimagine the networking opportunities between cities beyond global cities, this paper incorporates “cosmopolitan comparison” to expand our knowledge of a diverse range of cities using a data-driven approach. Through a cosmopolitan perspective, a framework is presented on how to utilise large data to expand knowledge of cities beyond global cities to reimagine the existing hierarchical networking practices. The contribution of this framework is beyond urban climate governance but inclusive of different fields which strive for a more inclusive and cosmopolitan comparison attentive to the differences across cities.

Keywords: cosmopolitan city comparison, data-driven approach, climate city networking, urban climate governance

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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Authors: G. Petruzzelli, F. Pedron, M. Grifoni, A. Pera, I. Rosellini, B. Pezzarossa

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The addition of lime as Ca(OH)2 to sewage sludge to destroy pathogens (Escherichia coli), was evaluated also in relation to heavy metal bioavailability. The obtained results show that the use of calcium hydroxide at the dose of 3% effectively destroyed pathogens ensuring the stability at high pH values over long period and the duration of the sewage sludge stabilization. In general, lime addition decreased the total extractability of heavy metals indicating a reduced bioavailability of these elements. This is particularly important for a safe utilization in agricultural soils to reduce the possible transfer of heavy metals to the food chain.

Keywords: biological sludge, Ca(OH)2, copper, pathogens, sanitation, zinc

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Authors: Chico Horacio Jose Sambo

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Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

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Authors: Nikhil Kumar, Aparna Singh

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Microstructural development when annealed at different temperatures in a high aluminum and manganese light weight steel has been examined. The FCC matrix of the manganese (Mn)-rich and nickel (Ni)-rich areas in the studied Fe-Mn-Al-Ni-C-light weight steel have been found to contain anti phase domains. In the Mn-rich region short order range of domains manifested by the diffuse scattering in the electron diffraction patterns was observed. Domains in the Ni-rich region were found to be arranged periodically validated through lattice imaging. The nature of these domains can be tuned with annealing temperature resulting in profound influence in the mechanical properties.

Keywords: Anti-phase domain boundaries, BCC, FCC, Light Weight Steel

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Authors: You-Lin Wu, Yi-Hsing Sung, Shih-Hung Lin, Jing-Jenn Lin

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Performance improvement in optoelectronic devices such as solar cells and photodetectors has been reported when a polymer/ZnO nanorods stack is used. Resistance switching of polymer/ZnO nanocrystals (or nanorods) hybrid has also gained a lot of research interests recently. It has been reported that high- and low-resistance states of a metal/insulator/metal (MIM) structure diode with a polystyrene (PS) and ZnO hybrid as the insulator layer can be switched by applied bias after a high-voltage forming process, while the same device structure merely with a PS layer does not show any forming behavior. In this work, we investigated the current-voltage (I-V) characteristics of an MIM device with a PS/ZnO nanorods stack deposited on fluorine-doped tin oxide (FTO) glass substrate. The ZnO nanorods were grown by a hydrothermal method using a mixture of zinc nitrate, hexamethylenetetramine, and DI water. Following that, a PS layer was deposited by spin coating. Finally, the device with a structure of Ti/ PS/ZnO nanorods/FTO was completed by e-gun evaporated Ti layer on top of the PS layer. Semiconductor parameters analyzer Agilent 4156C was then used to measure the I-V characteristics of the device by applying linear ramp sweep voltage with sweep sequence of 0V → 4V → 0V → 3V → 0V → 2V → 0V → 1V → 0V in both positive and negative directions. It is interesting to find that the I-V characteristics are bias dependent and hysteretic, indicating that the device Ti/PS/ZnO nanorods/FTO structure has ferroelectricity. Our results also show that the maximum hysteresis loop height of the I-V characteristics as well as the voltage at which the maximum hysteresis loop height of each scan occurs increase with increasing maximum sweep voltage. It should be noticed that, although ferroelectricity has been found in ZnO at its melting temperature (1975℃) and in Li- or Co-doped ZnO, neither PS nor ZnO has ferroelectricity at room temperature. Using the same structure but with a PS or ZnO layer only as the insulator does not give and hysteretic I-V characteristics. It is believed that a charge polarization layer is induced near the PS/ZnO nanorods stack interface and thus causes the ferroelectricity in the device with Ti/PS/ZnO nanorods/FTO structure. Our results show that the PS/ZnO stack can find a potential application in a resistive switching memory device with MIM structure.

Keywords: ferroelectricity, hysteresis, polystyrene, resistance switching, ZnO nanorods

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Authors: Hassan Nour, Nouh Mounadi, Oussama Abchir, Belaidi Salah, Samir Chtita

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Cholinesterase enzymes are biological catalysts essential for the transformation of acetylcholine, which is a neurotransmitter implicated in memory and learning, into acetic acid and choline, altering the neurotransmission process in Alzheimer’s disease patients. Therefore, inhibition of cholinesterase enzymes is a relevant strategy for the symptomatic treatment of Alzheimer’s disease. The current investigation aims to explore potential Cholinesterase (ChE) inhibitors through a comprehensive computational approach. Forty-nine phytoconstituents extracted from Cannabis sativa L were in-silico screened using molecular docking, pharmacokinetic and toxicological analysis to evaluate their possible inhibitory effect towards the cholinesterase enzymes. Two phytoconstituents belonging to cannabinoid derivatives were revealed to be promising candidates for Alzheimer therapy by acting as cholinesterase inhibitors. They have exhibited high binding affinities towards the cholinesterase enzymes and showed their ability to interact with key residues involved in cholinesterase enzymatic activity. In addition, they presented good ADMET profiles allowing them to be promising oral drug candidates. Furthermore, molecular dynamics (MD) simulations were executed to explore their interactions stability under mimetic biological conditions and thus support our findings. To corroborate the docking results, the binding free energy corresponding to the more stable ligand-ChE complexes was re-estimated by applying the MM-PBSA method. MD and MM-PBSA studies affirmed that the ligand-ChE recognition is spontaneous reaction leading to stable complexes. The conducted investigations have led to great findings that would strongly guide the pharmaceutical industries towards the rational development of potent anti-Alzheimer agents.

Keywords: alzheimer’s disease, molecular docking, cannabis sativa l, cholinesterase inhibitors

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: V. K. Banga

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Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques.

Keywords: artificial intelligence, kinematics, robotic arm, neural networks, fuzzy logic

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Authors: Monisha Isaac

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Use of molecular markers for selecting plants with desired traits has been started long back. Due to their heritable characteristics, they are useful for identification and characterization of specific genotypes. The study involves various types of molecular markers used to select multiple desired characters in plants, their properties, and advantages to improve crop productivity in adverse climatological conditions for the purpose of providing food security to fast-growing global population. The study shows that genetic similarities obtained from molecular markers provide more accurate information and the genetic diversity can be better estimated from the genetic relationship obtained from the dendrogram. The information obtained from markers assisted characterization is more suitable for the crops of economic importance like sugarcane.

Keywords: molecular markers, crop productivity, genetic diversity, genotype

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Authors: Fekri Shawtari

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The banking sector plays a very crucial role in the economic development of the country. As a financial intermediary, it has assigned a great role in the economic growth and stability. This paper aims to examine the empirically the relationship between banking industry and economic growth in state of Qatar. We adopt the VAR vector error correction model (VECM) along with Granger causality to address the issue over the long-run and short-run between the banking sector and economic growth. It is expected that the results will give policy directions to the policymakers to make strategies that are conducive toward boosting development to achieve the targeted economic growth in current situation.

Keywords: economic growth, banking sector, Qatar, vector error correction model, VECM

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Authors: Thomas Prevenslik

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Weakly Interacting Massive Particle (WIMP) experiments suggesting dark matter does not exist are consistent with the argument that the long-standing galaxy rotation problem may be resolved without the need for dark matter if the redshift measurements giving the higher than expected galaxy velocities are corrected for the redshift in cosmic dust. Because of the ubiquity of cosmic dust, all velocity measurements in astronomy based on redshift are most likely overstated, e.g., an accelerating Universe expansion need not exist if data showing supernovae brighter than expected based on the redshift/distance relation is corrected for the redshift in dust. Extensions of redshift corrections for cosmic dust to other historical astronomical observations are briefly discussed.

Keywords: alternative theories, cosmic dust redshift, doppler effect, quantum mechanics, quantum electrodynamics

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Authors: Jens Ehm

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Manufacturing in supply chains requires an efficient organisation of production and transport processes in order to guarantee the supply of all partners within the chain with the material that is needed for the reliable fulfilment of tasks. If one partner is not able to supply products for a certain period, these products might be missing as the working material for the customer to perform the next manufacturing step, potentially as supply for further manufacturing steps. This way, local disruptions can influence the whole supply chain. In order to avoid material shortages, an efficient scheduling of tasks is necessary. However, the occurrence of unexpected disruptions cannot be eliminated, so that a modification of the schedule should be arranged as fast as possible. This paper discusses the challenges for the implementation of real-time scheduling and control methods and presents a graph-based approach that enables the integrated scheduling of production and transport processes for multiple supply chain partners and offers the potential for quick adaptations to parts of the initial schedule.

Keywords: production, logistics, integrated scheduling, real-time scheduling

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Authors: Fleura Shkëmbi, Sevim Mustafa, Naim Fanaj

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Hypnosis, often known as cognitive therapy, is a sort of mind-body psychotherapy. A professional and certified hypnotist or hypnotherapist guides the patient into this extreme level of focus and relaxation during the session by utilizing verbal cues, repetition, and imagery. In recent years, hypnotherapy has gained popularity in the treatment of a variety of disorders, including anxiety and particular phobias. The term "phobia" is commonly used to define fear of a certain trigger. When faced with potentially hazardous situations, the brain naturally experiences dread. While a little dread here and there may keep us safe, phobias can drastically reduce our quality of life. In summary, persons who suffer from anxiety are considered to see particular environmental situations as dangerous, but those who do not suffer from anxiety do not. Hypnosis is essential in the treatment of anxiety disorders. Hypnosis can help patients minimize their anxiety symptoms. This broad concept has aided in the development of models and therapies for anxiety disorders such as generalized anxiety disorder, panic attacks, hypochondria, and obsessional disorders. Hypnosis techniques are supposed to be attentive and mental pictures, which is conceivable; this is why they're associated with improved working memory and visuospatial abilities. In this sense, the purpose of this study is to determine how effectively specific therapeutic methods perform in treating persons with anxiety and phobias. In addition to cognitive-behavioral therapy and other therapies, the approaches emphasized the use of therapeutic hypnosis. This study looks at the use of hypnosis and related psychotherapy procedures in the treatment of anxiety disorders. Following a discussion of the evolution of hypnosis as a therapeutic tool, neurobiological research is used to demonstrate the influence of hypnosis on the change of perception in the brain. The use of hypnosis in the treatment of phobias, stressful situations, and posttraumatic stress disorder is examined, as well as similarities between the hypnotic state and dissociative reactions to trauma. Through an extensive literature evaluation, this study will introduce hypnotherapy procedures that result in more successful anxiety and phobia treatment.

Keywords: anxiety, hypnosis, hypnotherapy, phobia, technique, state

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Authors: Zuzana Poborilova, Anna B. Ohlsson, Torkel Berglund, Anna Vildova, Petr Babula

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Lawsone is a pigment that occurs naturally in plants. It has been used as a skin and hair dye for a long time. Moreover, its different biological activities have been reported. The present study focused on the effect of lawsone on a plant cell model represented by tobacco BY-2 cell suspension culture, which is used as a model comparable with the HeLa cells. It has been shown that lawsone inhibits the cell growth in the concentration-dependent manner. In addition, changes in DNA methylation level have been determined. We observed decreasing level of DNA methylation in the presence of increasing concentrations of lawsone. These results were accompanied with overproduction of reactive oxygen species (ROS). Since epigenetic modifications can be caused by different stress factors, there could be a connection between the changes in the level of DNA methylation and ROS production caused by lawsone.

Keywords: DNA methylation, lawsone, naphthoquinone, reactive oxygen species

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Authors: Proud Arunrangsiwed, Sarinya Kongtieng

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Teachers and university lecturers face an unsolved problem, which is students’ multitasking behaviors during class time, such as texting or playing a game. It is important to examine the most powerful predictor that can result in students’ educational performances. Meta-analysis was used to analyze the research articles, which were published with the keywords, multitasking, class performance, and texting. We selected 14 research articles published during 2008-2013 from online databases, and four articles met the predetermined inclusion criteria. Effect size of each pair of variables was used as the dependent variable. The findings revealed that the students’ expectancy and value on SNSs usages is the best significant predictor of their educational performances, followed by their motivation and ability in using SNSs, prior educational performances, usage behaviors of SNSs in class, and their personal characteristics, respectively. Future study should conduct a longitudinal design to better understand the effect of multitasking in the classroom.

Keywords: meta-regression analysis, social networking sites, academic Performances, multitasking, motivation

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Authors: A. Mulry, C. Kealey, D. B. Brady

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Planktonic bacteria can form biofilms which are microbial aggregates embedded within a matrix of extracellular polymeric substances (EPS). They can be found attached to abiotic or biotic surfaces. Biofilms are responsible for oral diseases such as dental caries, gingivitis and the progression of periodontal disease. Biofilms can resist 500 to 1000 times the concentration of biocides and antibiotics used to kill planktonic bacteria. Biofilm development on oral surfaces involves four stages, initial attachment, early development, maturation and dispersal of planktonic cells. The Minimum Inhibitory Concentration (MIC) was determined using a range of saturated and unsaturated fatty acids using the resazurin assay, followed by serial dilution and spot plating on BHI agar plates to establish the Minimum Bactericidal Concentration (MBC). Log reduction of bacteria was also evaluated for each fatty acid. The Minimum Biofilm Inhibition Concentration (MBIC) was determined using crystal violet assay in 96 well plates on forming and pre-formed S. mutans biofilms using BHI supplemented with 1% sucrose. Saturated medium-chain fatty acids Octanoic (C8.0), Decanoic (C10.0) and Undecanoic acid (C11.0) do not display strong antibiofilm properties; however, Lauric (C12.0) and Myristic (C14.0) display moderate antibiofilm properties with 97.83% and 97.5% biofilm inhibition with 1000 µM respectively. Monounsaturated, Oleic acid (C18.1) and polyunsaturated large chain fatty acids, Linoleic acid (C18.2) display potent antibiofilm properties with biofilm inhibition of 99.73% at 125 µM and 100% at 65.5 µM, respectively. Long-chain polyunsaturated Omega-3 fatty acids α-Linoleic (C18.3), Eicosapentaenoic Acid (EPA) (C20.5), Docosahexaenoic Acid (DHA) (C22.6) have displayed strong antibiofilm efficacy from concentrations ranging from 31.25-250µg/ml. DHA is the most promising antibiofilm agent with an MBIC of 99.73% with 15.625µg/ml. This may be due to the presence of six double bonds and the structural orientation of the fatty acid. To conclude, fatty acids displaying the most antimicrobial activity appear to be medium or long-chain unsaturated fatty acids containing one or more double bonds. Most promising agents include Omega-3-fatty acids Linoleic, α-Linoleic, EPA and DHA, as well as Omega-9 fatty acid Oleic acid. These results indicate that fatty acids have the potential to be used as antimicrobials and antibiofilm agents against S. mutans. Future work involves further screening of the most potent fatty acids against a range of bacteria, including Gram-positive and Gram-negative oral pathogens. Future work will involve incorporating the most effective fatty acids onto dental implant devices to prevent biofilm formation.

Keywords: antibiofilm, biofilm, fatty acids, S. mutans

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Authors: Nadia Sghaier

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In this paper, we examine the influence of the COVID-19 pandemic on the performance of the Tunisian stock market and 12 sectors over a recent period from 23 March 2020 to 18 August 2021, including several waves and the introduction of vaccination. The empirical study is conducted using cointegration techniques which allows for long and short-run relationships. The obtained results indicate that both daily growth in confirmed cases and deaths have a negative and significant effect on the stock market returns. In particular, this effect differs across sectors. It seems more pronounced in financial, consumer goods and industrials sectors. These findings have important implications for investors to predict the behavior of the stock market or sectors returns and to implement hedging strategies during the COVID-19 pandemic.

Keywords: Tunisian stock market, sectors, COVID-19 pandemic, cointegration techniques

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Authors: Neelam Chhetry, Indranil Dutta

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The present study accounts for the fundamental frequency (f0) perturbations of stop types in Nepali spoken in the Maram region of Manipur, India. Two different experiments were performed on the speech of the native speakers of Nepali in order to investigate if the f0 perturbation following the stop types would be affected due to contact with tonal language, Maram. We found that the Nepali speakers maintained four way stop contrast: voiceless stop (VS), voiceless aspirated stop (VLAS), voiced stop (VS) and voiced aspirated stop (VAS) despite being in contact with Maramfor a very long time. We also found that the F0 range was greater for VAS leading to F0 compression for speakers with high level of proficiency (LOP) in Maram due to extensive language contact.

Keywords: F0, sociophonetic, F0 range, sociophonetic

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Authors: Joanna Cabaj, Sylwia Baluta, Karol Malecha, Kamila Drzozga

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Catecholamines are the principal neurotransmitters that mediate a variety of the central nervous system functions, such as motor control, cognition, emotion, memory processing, and endocrine modulation. Dysfunctions in catecholamine neurotransmission are induced in some neurologic and neuropsychiatric diseases. Changeable neurotransmitters level in biological fluids can be a marker of several neurological disorders. Because of its significance in analytical techniques and diagnostics, sensitive and selective detection of neurotransmitters is increasingly attracting a lot of attention in different areas of bio-analysis or biomedical research. Recently, fluorescent techniques for detection of catecholamines have attracted interests due to their reasonable cost, convenient control, as well as maneuverability in biological environments. Nevertheless, with the observed need for a sensitive and selective catecholamines sensor, the development of a convenient method for this neurotransmitter is still at its basic level. The manipulation of nanostructured materials in conjunction with biological molecules has led to the development of a new class of hybrid modified biosensors in which both enhancement of charge transport and biological activity preservation may be obtained. Immobilization of biomaterials on electrode surfaces is the crucial step in fabricating electrochemical as well as optical biosensors and bioelectronic devices. Continuing systematic investigation in the manufacturing of enzyme–conducting sensitive systems, here is presented a convenient fluorescence sensing strategy for catecholamines detection based on FRET (fluorescence resonance energy transfer) phenomena observed for, i.e., complexes of Fe²⁺ and epinephrine. The biosensor was constructed using low temperature co-fired ceramics technology (LTCC). This sensing system used the catalytical oxidation of catecholamines and quench of the strong luminescence of obtained complexes due to FRET. The detection process was based on the oxidation of substrate in the presence of the enzyme–laccase/tyrosinase.

Keywords: biosensor, conducting polymer, enzyme, FRET, LTCC

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Authors: Ruining Wu, Na Song

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Paper-cut, as one of the Chinese traditional folk decoration art, has become a unique visual aesthetic characteristics of the Chinese nation in the long-term evolution of cultural symbols. Chinese paper-cut art is the treasure-house for product design in natural resources. This paper first analyzed Chinese folk art of historical origin, cultural background, cultural values, aesthetic value, style features of Chinese paper cut art, then analyzed the design thought and design cases of paper-cut art application in different areas, such as clothing design, logo design and product design areas. Through the research of Chinese paper-cut art culture and design elements, this paper aims to build a household product design concept of Chinese traditional culture.

Keywords: paper-cut art, culture, household products, design

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Authors: Elissar Mansour, Emily Chen, Tracee Fernandez, Mariam Basheti, Christopher Gordon, Bandana Saini

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Sleep is an essential process for the maintenance of several neurobiological processes such as memory consolidation, mood, and metabolic processes. It is known that sleep patterns vary with age and is affected by multiple factors. While non-pharmacological strategies are generally considered first-line, sedatives are excessively used in the older population. This study aimed to explore the management of sleep in residential aged care facilities (RACFs) by nurse professionals and to identify the key factors that impact provision of optimal sleep health care. An inductive thematic qualitative research method was employed to analyse the data collected from semi-structured interviews with registered nurses working in RACF. Seventeen interviews were conducted, and the data yielded three themes: 1) the nurses’ observations and knowledge of sleep health, 2) the strategies employed in RACF for the management of sleep disturbances, 3) the organizational barriers to evidence-based sleep health management. Nurse participants reported the use of both non-pharmacological and pharmacological interventions. Sedatives were commonly prescribed due to their fast action and accessibility despite the guidelines indicating their use in later stages. Although benzodiazepines are known for their many side effects, such as drowsiness and oversedation, temazepam was the most commonly administered drug. Sleep in RACF was affected by several factors such as aging and comorbidities (e.g., dementia, pain, anxiety). However, the were also many modifiable factors that negatively impacted sleep management in RACF. These include staffing ratios, nursing duties, medication side effects, and lack of training and involvement of allied health professionals. This study highlighted the importance of involving a multidisciplinary team and the urge to develop guidelines and training programs for healthcare professionals to improve sleep health management in RACF.

Keywords: registered nurses, residential aged care facilities, sedative use, sleep

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Authors: Jeroen Rotteveel, Zeger De Groot

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The small satellite community is more and more aware of the need to start operating responsibly and sustainably in order to secure the use of outer space in the long run. On the technical side, many debris mitigation techniques have been investigated and demonstrated on board small satellites, showing that technically, a lot of things can be done to curb the growth of space debris and operate more responsible. However, in the absence of strict laws and constraints, one cannot help but wonder what the incentive is to incur significant costs (paying for debris mitigation systems and the launch mass of these systems) and to lose performance onboard resource limited small satellites (mass, volume, power)? Many small satellite developers are operating under tight budgets, either from their sponsors (in case of academic and research projects) or from their investors (in case of startups). As long as it is not mandatory to act more responsibly, we might need to consider the implementation of incentives to stimulate developers to accommodate deorbiting modules, etc. ISISPACE joined the NetZeroSpace initiative in 2021 with the aim to play its role in secure the use of low earth orbit for the next decades by facilitating more sustainable use of space. The company is in a good position as both a satellite builder, a rideshare launch provider, and a technology development company. ISISPACE operates under one of the stricter space laws in the world in terms of maximum orbital lifetime and has been active in various debris mitigation and debris removal in-orbit demonstration missions in the past 10 years. ISISPACE proposes to introduce together with launch partners and regulators an incentive scheme for CubeSat developers to baseline debris mitigation systems on board their CubeSats in such a way that is does not impose too many additional costs to the project. Much like incentives to switch to electric cars or install solar panels on your house, such an incentive can help to increase market uptake of behavior or solutions prior to legislation or bans of certain practices. This can be achieved by: Introducing an extended launch volume in CubeSat deployers to accommodate debris mitigation systems without compromising available payload space for the payload of the main mission Not charging the fee for the launch mass for the additional debris mitigation module Whenever possible, find ways to further co-fund the purchase price, or otherwise reduce the cost of flying debris mitigation modules onboard the CubeSats. The paper will outline the framework of such an incentive scheme and provides ISISPACE’s way forward to make this happen in the near future.

Keywords: netZerospace, cubesats, debris mitigation, small satellite community

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Authors: Peter David Reiss

Abstract:

The concept of the psychosis prodrome has allowed for the identification of adolescent and young adult patients who have a significantly elevated risk of developing schizophrenia spectrum disorders. A number of different interventions have been tested in order to prevent or delay progression of symptoms. To date, there has been no consistent meta-analytical evidence to support efficacy of antipsychotic treatment for patients in the prodromal state, and their use remains therefore inconclusive. Although antipsychotics may manage symptoms transiently, they have not been found to prevent or delay onset of psychotic disorders. Furthermore, pharmacological intervention in high-risk individuals remains controversial, because of the antipsychotic side effect profile in a population in which only about 20 to 35 percent will eventually convert to psychosis over a two-year period, with even after two years conversion rates not exceeding 30 to 40 percent. This general estimate is additionally problematic, in that it ignores the fact that there is significant variation in individual risk among clinical high-risk cases. The current lack of reliable tests for at-risk patients makes it difficult to justify individual treatment decisions. Preventive treatment should ideally be dictated by an individual’s risk while minimizing potentially harmful medication exposure. This requires more accurate predictive assessments by using valid and accessible prognostic markers. The following will compare prediction and risk modification potential of behavioral biomarkers such as disturbances of basic sense of self and emotion awareness, neurocognitive biomarkers such as attention, working and declarative memory, and neurophysiological biomarkers such as glutamatergic abnormalities and NMDA receptor dysfunction. Identification of robust biomarkers could therefore not only provide more reliable means of psychosis prediction, but also help test and develop new clinical interventions targeted at the prodromal state.

Keywords: at-risk mental state, biomarkers, glutamatergic system, NMDA receptor, psychosis prodrome, schizophrenia

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Authors: Mariyan Tomov

Abstract:

Bulgarian working class immigrants are increasingly concerned with UK’s recent immigration policies in the context of Brexit. The new ID system would exclude many people currently working in Britain and would break the usual immigrant travel patterns. Post-Brexit Britain would aim to repeal seasonal immigrants. Measures for keeping long-term and life-long immigrants have been implemented and migrants that aim to remain in Britain and establish a household there would be more privileged than temporary or seasonal workers. The results of such regulating mechanisms come at the expense of migrants’ longings for a ‘normal’ existence, especially for those coming from Central and Eastern Europe. Based on in-depth interviews with Bulgarian working class immigrants, the study found out that their major concerns following the decision of the UK to leave the EU are related with the freedom to travel, reside and work in the UK. Furthermore, many of the interviewed women are concerned that they could lose some of the EU's fundamental rights, such as maternity and protection of pregnant women from unlawful dismissal. The soar of commodity prices and university fees and the limited access to public services, healthcare and social benefits in the UK, are also subject to discussion in the paper. The most serious problem, according to the interview, is that the attitude towards Bulgarians and other immigrants in the UK is deteriorating. Both traditional and social media in the UK often portray the migrants negatively by claiming that they take British job positions while simultaneously abuse the welfare system. As a result, the Bulgarian migrants often face social exclusion, which might have negative influence on their health and welfare. In this sense, some of the interviewed stress on the fact that the most important changes after Brexit must take place in British society itself. The aim of the proposed study is to provide a better understanding of the Bulgarian migrants’ economic, health and sociocultural experience in the context of Brexit. Methodologically, the proposed paper leans on: 1. Analysing ethnographic materials dedicated to the pre- and post-migratory experiences of Bulgarian working class migrants, using SPSS. 2. Semi-structured interviews are conducted with more than 50 Bulgarian working class migrants [N > 50] in the UK, between 18 and 65 years. The communication with the interviewees was possible via Viber/Skype or face-to-face interaction. 3. The analysis is guided by theoretical frameworks. The paper has been developed within the framework of the research projects of the National Scientific Fund of Bulgaria: DCOST 01/25-20.02.2017 supporting COST Action CA16111 ‘International Ethnic and Immigrant Minorities Survey Data Network’.

Keywords: Bulgarian migrants in UK, economic experiences, sociocultural experiences, Brexit

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Authors: Wullapa Wongsinlatam

Abstract:

Back propagation algorithm (BP) is a widely used technique in artificial neural network and has been used as a tool for solving the time series problems, such as decreasing training time, maximizing the ability to fall into local minima, and optimizing sensitivity of the initial weights and bias. This paper proposes an improvement of a BP technique which is called IM-COH algorithm (IM-COH). By combining IM-COH algorithm with cuckoo search algorithm (CS), the result is cuckoo search improved control output hidden layer algorithm (CS-IM-COH). This new algorithm has a better ability in optimizing sensitivity of the initial weights and bias than the original BP algorithm. In this research, the algorithm of CS-IM-COH is compared with the original BP, the IM-COH, and the original BP with CS (CS-BP). Furthermore, the selected benchmarks, four time series samples, are shown in this research for illustration. The research shows that the CS-IM-COH algorithm give the best forecasting results compared with the selected samples.

Keywords: artificial neural networks, back propagation algorithm, time series, local minima problem, metaheuristic optimization

Procedia PDF Downloads 152