Search results for: neural signal recording

Authors: Vanessa Kummer, Maik Meusel

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Real estate demand estimates are typically derived from transaction data. However, in regions with excess demand, transactions are driven by supply and therefore do not indicate what people are actually looking for. To estimate the demand for housing in Switzerland, search subscriptions from all important Swiss real estate platforms are used. These data do, however, suffer from missing information—for example, many users do not specify how many rooms they would like or what price they would be willing to pay. In economic analyses, it is often the case that only complete data is used. Usually, however, the proportion of complete data is rather small which leads to most information being neglected. Also, the data might have a strong distortion if it is complete. In addition, the reason that data is missing might itself also contain information, which is however ignored with that approach. An interesting issue is, therefore, if for economic analyses such as the one at hand, there is an added value by using the whole data set with the imputed missing values compared to using the usually small percentage of complete data (baseline). Also, it is interesting to see how different algorithms affect that result. The imputation of the missing data is done using unsupervised learning. Out of the numerous unsupervised learning approaches, the most common ones, such as clustering, principal component analysis, or neural networks techniques are applied. By training the model iteratively on the imputed data and, thereby, including the information of all data into the model, the distortion of the first training set—the complete data—vanishes. In a next step, the performances of the algorithms are measured. This is done by randomly creating missing values in subsets of the data, estimating those values with the relevant algorithms and several parameter combinations, and comparing the estimates to the actual data. After having found the optimal parameter set for each algorithm, the missing values are being imputed. Using the resulting data sets, the next step is to estimate the willingness to pay for real estate. This is done by fitting price distributions for real estate properties with certain characteristics, such as the region or the number of rooms. Based on these distributions, survival functions are computed to obtain the functional relationship between characteristics and selling probabilities. Comparing the survival functions shows that estimates which are based on imputed data sets do not differ significantly from each other; however, the demand estimate that is derived from the baseline data does. This indicates that the baseline data set does not include all available information and is therefore not representative for the entire sample. Also, demand estimates derived from the whole data set are much more accurate than the baseline estimation. Thus, in order to obtain optimal results, it is important to make use of all available data, even though it involves additional procedures such as data imputation.

Keywords: demand estimate, missing-data imputation, real estate, unsupervised learning

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Authors: Win Zaw Hein, Khin Sandar Linn, Su Su Yi Mon, Yoshitaka Goto

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The Earth ionosphere is located at the altitude of about 70 km to several 100 km from the ground, and it is composed of ions and electrons called plasma. In the ionosphere, these plasma makes delay in GPS (Global Positioning System) signals and reflect in radio waves. The delay along the signal path from the satellite to the receiver is directly proportional to the total electron content (TEC) of plasma, and this delay is the largest error factor in satellite positioning and navigation. Sounding observation from the top and bottom of the ionosphere was popular to investigate such ionospheric plasma for a long time. Recently, continuous monitoring of the TEC using networks of GNSS (Global Navigation Satellite System) observation stations, which are basically built for land survey, has been conducted in several countries. However, in these stations, multi-frequency support receivers are installed to estimate the effect of plasma delay using their frequency dependence and the cost of multi-frequency support receivers are much higher than single frequency support GPS receiver. In this research, single frequency GPS receiver was used instead of expensive multi-frequency GNSS receivers to measure the ionospheric plasma variation such as vertical TEC distribution. In this measurement, single-frequency support ublox GPS receiver was used to probe ionospheric TEC. The location of observation was assigned at Mandalay Technological University in Myanmar. In the method, the ionospheric TEC distribution is represented by polynomial functions for latitude and longitude, and parameters of the functions are determined by least-squares fitting on pseudorange data obtained at a known location under an assumption of thin layer ionosphere. The validity of the method was evaluated by measurements obtained by the Japanese GNSS observation network called GEONET. The performance of measurement results using single-frequency of GPS receiver was compared with the results by dual-frequency measurement.

Keywords: ionosphere, global positioning system, GPS, ionospheric delay, total electron content, TEC

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Authors: Mapatsakon Sarapat, Mongkol Ketwongsa, Somchat Sonasang, Preecha Yupapin

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The designed and performed preliminary tests on a space-time control circuit using a two-level system circuit with a 4-5 cm diameter microstrip for realistic teleportation have been demonstrated. It begins by calculating the parameters that allow a circuit that uses the alternative current (AC) at a specified frequency as the input signal. A method that causes electrons to move along the circuit perimeter starting at the speed of light, which found satisfaction based on the wave-particle duality. It is able to establish the supersonic speed (faster than light) for the electron cloud in the middle of the circuit, creating a timeline and propulsive force as well. The timeline is formed by the stretching and shrinking time cancellation in the relativistic regime, in which the absolute time has vanished. In fact, both black holes and white holes are created from time signals at the beginning, where the speed of electrons travels close to the speed of light. They entangle together like a capsule until they reach the point where they collapse and cancel each other out, which is controlled by the frequency of the circuit. Therefore, we can apply this method to large-scale circuits such as potassium, from which the same method can be applied to form the system to teleport living things. In fact, the black hole is a hibernation system environment that allows living things to live and travel to the destination of teleportation, which can be controlled from position and time relative to the speed of light. When the capsule reaches its destination, it increases the frequency of the black holes and white holes canceling each other out to a balanced environment. Therefore, life can safely teleport to the destination. Therefore, there must be the same system at the origin and destination, which could be a network. Moreover, it can also be applied to space travel as well. The design system will be tested on a small system using a microstrip circuit system that we can create in the laboratory on a limited budget that can be used in both wired and wireless systems.

Keywords: quantum teleportation, black-white hole, time, timeline, relativistic electronics

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: Soultana Konstantinidou, Tiziana Schmidt, Elena Landi, Alessandro De Carli, Giovanni Maltinti, Darius Witt, Alicja Dziadosz, Agnieszka Lindstaedt, Michele Lai, Mauro Pistello, Valentina Cappello, Luciana Dente, Chiara Gabellini, Piotr Barski, Vittoria Raffa

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CRISPR/Cas9 technology has gained the interest of researchers in the field of biotechnology for genome editing. Since its discovery as a microbial adaptive immune defense, this system has been widely adopted and is acknowledged for having a variety of applications. However, critical barriers related to safety and delivery are persisting. Here, we propose a new concept of genome engineering, which is based on a nano-formulation of Cas9. The Cas9 enzyme was conjugated to a gold nanoparticle (AuNP-Cas9). The AuNP-Cas9 maintained its cleavage efficiency in vitro, to the same extent as the ribonucleoprotein, including non-conjugated Cas9 enzyme, and showed high gene editing efficiency in vivo in zebrafish embryos. Since CRISPR/Cas9 technology is extensively used in cancer research, melanoma was selected as a validation target. Cell studies were performed in A375 human melanoma cells. Particles per se had no impact on cell metabolism and proliferation. Intriguingly, the AuNP-Cas9 internalized spontaneously in cells and localized as a single particle in the cytoplasm and organelles. More importantly, the AuNP-Cas9 showed a high nuclear localization signal. The AuNP-Cas9, overcoming the delivery difficulties of Cas9, could be used in cellular biology and localization studies. Taking advantage of the plasmonic properties of gold nanoparticles, this technology could potentially be a bio-tool for combining gene editing and photothermal therapy in cancer cells. Further work will be focused on intracellular interactions of the nano-formulation and characterization of the optical properties.

Keywords: CRISPR/Cas9, gene editing, gold nanoparticles, nanotechnology

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Authors: Kamila Weissova, Jitka Skrabalova, Katerina Skalova, Jana Koprivova, Zdenka Bendova

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Any Arctic visitor has to deal with extreme conditions, including constant light during the summer season or constant darkness during winter time. Light/dark cycle is the most powerful synchronizing signal for biological clock and the absence of daily dark period during the polar day can significantly alter the functional state of the internal clock. However, the inner clock can be synchronized by other zeitgebers such as physical activity, food intake or social interactions. Here, we investigated the effect of polar day on circadian clock of 10 researchers attending the polar base station in the Svalbard region during July. The data obtained on Svalbard were compared with the data obtained before the researchers left for the expedition (in the Czech Republic). To determine the state of circadian clock we used wrist actigraphy followed by sleep diaries, saliva, and buccal mucosa samples, both collected every 4 hours during 24h-interval to detect melatonin by radioimmunoassay and clock gene (PER1, BMAL1, NR1D1, DBP) mRNA levels by RT-qPCR. The clock gene expression was analyzed using cosinor analysis. From our results, it is apparent that the constant sunlight delayed melatonin onset and postponed the physical activity in the same order. Nevertheless, the clock gene expression displayed higher amplitude on Svalbard compared to the amplitude detected in the Czech Republic. These results have suggested that the common daily schedule at the Svalbard expedition can strengthen circadian rhythm in the environment that is lacking light/dark cycle. In conclusion, the constant sunlight delays melatonin onset, but it still maintains its rhythmic secretion. The effect of constant sunlight on circadian clock can be minimalized by common daily scheduled activity.

Keywords: actighraph, clock genes, human, melatonin, polar day

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Authors: Valentina Marutyan

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Healthcare data mining is a rapidly developing field at the intersection of technology and medicine that has the potential to change our understanding and approach to providing healthcare. Healthcare and data mining is the process of examining huge amounts of data to extract useful information that can be applied in order to improve patient care, treatment effectiveness, and overall healthcare delivery. This field looks for patterns, trends, and correlations in a variety of healthcare datasets, such as electronic health records (EHRs), medical imaging, patient demographics, and treatment histories. To accomplish this, it uses advanced analytical approaches. Predictive analysis using historical patient data is a major area of interest in healthcare data mining. This enables doctors to get involved early to prevent problems or improve results for patients. It also assists in early disease detection and customized treatment planning for every person. Doctors can customize a patient's care by looking at their medical history, genetic profile, current and previous therapies. In this way, treatments can be more effective and have fewer negative consequences. Moreover, helping patients, it improves the efficiency of hospitals. It helps them determine the number of beds or doctors they require in regard to the number of patients they expect. In this project are used models like logistic regression, random forests, and neural networks for predicting diseases and analyzing medical images. Patients were helped by algorithms such as k-means, and connections between treatments and patient responses were identified by association rule mining. Time series techniques helped in resource management by predicting patient admissions. These methods improved healthcare decision-making and personalized treatment. Also, healthcare data mining must deal with difficulties such as bad data quality, privacy challenges, managing large and complicated datasets, ensuring the reliability of models, managing biases, limited data sharing, and regulatory compliance. Finally, secret code of data mining in healthcare helps medical professionals and hospitals make better decisions, treat patients more efficiently, and work more efficiently. It ultimately comes down to using data to improve treatment, make better choices, and simplify hospital operations for all patients.

Keywords: data mining, healthcare, big data, large amounts of data

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Authors: Kavian Khosravinia, Mohd Khair Hassan, Ribhan Zafira Abdul Rahman, Syed Abdul Rahman Al-Haddad

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The CAN (controller area network) bus is introduced as a multi-master, message broadcast system. The messages sent on the CAN are used to communicate state information, referred as a signal between different ECUs, which provides data consistency in every node of the system. OBD-II Dongles that are based on request and response method is the wide-spread solution for extracting sensor data from cars among researchers. Unfortunately, most of the past researches do not consider resolution and quantity of their input data extracted through OBD-II technology. The maximum feasible scan rate is only 9 queries per second which provide 8 data points per second with using ELM327 as well-known OBD-II dongle. This study aims to develop and design a programmable, and latency-sensitive vehicle data acquisition system that improves the modularity and flexibility to extract exact, trustworthy, and fresh car sensor data with higher frequency rates. Furthermore, the researcher must break apart, thoroughly inspect, and observe the internal network of the vehicle, which may cause severe damages to the expensive ECUs of the vehicle due to intrinsic vulnerabilities of the CAN bus during initial research. Desired sensors data were collected from various vehicles utilizing Raspberry Pi3 as computing and processing unit with using OBD (request-response) and direct CAN method at the same time. Two types of data were collected for this study. The first, CAN bus frame data that illustrates data collected for each line of hex data sent from an ECU and the second type is the OBD data that represents some limited data that is requested from ECU under standard condition. The proposed system is reconfigurable, human-readable and multi-task telematics device that can be fitted into any vehicle with minimum effort and minimum time lag in the data extraction process. The standard operational procedure experimental vehicle network test bench is developed and can be used for future vehicle network testing experiment.

Keywords: CAN bus, OBD-II, vehicle data acquisition, connected cars, telemetry, Raspberry Pi3

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Authors: Arushi Singh, Anjana Jain, Prakash Vyavahare

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Recently, Li-Fi(light-fiedelity) has been launched based on VLC(visible light communication) technique, 100 times faster than WiFi. Now 5G mobile communication system is proposed to use VLC-OFDM as the transmission technique. The VLC system focused on visible rays, is considered for efficient spectrum use and easy intensity modulation through LEDs. The reason of high speed in VLC is LED, as they flicker incredibly fast(order of MHz). Another advantage of employing LED is-it acts as low pass filter results no out-of-band emission. The VLC system falls under the category of ‘green technology’ for utilizing LEDs. In present scenario, OFDM is used for high data-rates, interference immunity and high spectral efficiency. Inspite of the advantages OFDM suffers from large PAPR, ICI among carriers and frequency offset errors. Since, the data transmission technique used in VLC system is OFDM, the system suffers the drawbacks of OFDM as well as VLC, the non-linearity dues to non-linear characteristics of LED and PAPR of OFDM due to which the high power amplifier enters in non-linear region. The proposed paper focuses on reduction of PAPR in VLC-OFDM systems. Many techniques are applied to reduce PAPR such as-clipping-introduces distortion in the carrier; selective mapping technique-suffers wastage of bandwidth; partial transmit sequence-very complex due to exponentially increased number of sub-blocks. The paper discusses three companding techniques namely- µ-law, A-law and advance A-law companding technique. The analysis shows that the advance A-law companding techniques reduces the PAPR of the signal by adjusting the companding parameter within the range. VLC-OFDM systems are the future of the wireless communication but non-linearity in VLC-OFDM is a severe issue. The proposed paper discusses the techniques to reduce PAPR, one of the non-linearities of the system. The companding techniques mentioned in this paper provides better results without increasing the complexity of the system.

Keywords: non-linear companding techniques, peak to average power ratio (PAPR), visible light communication (VLC), VLC-OFDM

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Authors: Neeraj Neeraj, Soumen Basu, Banibrata Maity

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Glutathione (GSH) is one of the most important biomolecules having small molecular weight, which helps in various cellular functions like regulation of gene, xenobiotic metabolism, preservation of intracellular redox activities, signal transduction, etc. Therefore, the detection of GSH requires huge attention by using extremely selective and sensitive techniques. Herein, a rapid fluorometric nanosensor is designed by combining carbon dots (Cdots) and MnO₂ nanoparticles of different sizes for the detection of GSH. The bottom-up approach, i.e., microwave method, was used for the preparation of the water soluble and greatly fluorescent Cdots by using ascorbic acid as a precursor. MnO₂ nanospheres of different sizes (large, medium, and small) were prepared by varying the ratio of concentration of methionine and KMnO₄ at room temperature, which was confirmed by HRTEM analysis. The successive addition of MnO₂ nanospheres in Cdots results fluorescence quenching. From the fluorescence intensity data, Stern-Volmer quenching constant values (KS-V) were evaluated. From the fluorescence intensity and lifetime analysis, it was found that the degree of fluorescence quenching of Cdots followed the order: large > medium > small. Moreover, fluorescence recovery studies were also performed in the presence of GSH. Fluorescence restoration studies also show the order of turn on follows the same order, i.e., large > medium > small, which was also confirmed by quantum yield and lifetime studies. The limits of detection (LOD) of GSH in presence of Cdots@different sized MnO₂ nanospheres were also evaluated. It was observed thatLOD values were in μM region and lowest in case of large MnO₂ nanospheres. The separation distance (d) between Cdots and the surface of different MnO₂ nanospheres was determined. The d values increase with increase in the size of the MnO₂ nanospheres. In summary, the synthesized Cdots@MnO₂ nanocomposites acted as a rapid, simple, economical as well as environmental-friendly nanosensor for the detection of GSH.

Keywords: carbon dots, fluorescence, glutathione, MnO₂ nanospheres, turn off-on

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Authors: Celeste De Kock, Bruce Anderson, Corneile Minnaar

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Geographic variation in the floral morphology of a flower species has often been assumed to result from co-variation in the availability of regionally-specific functional pollinator types, giving rise to plant ecotypes that are adapted to the morphology of the main pollinator types in that area. Wachendorfia paniculata is a geographically variable enantiostylous (handed) flower with preliminary observations suggesting that differences in pollinator community composition might be driving differences in the degree of herkogamy (spatial separation of the stigma and anthers on the same flower) across its geographic range. This study aimed to determine if pollinator-related variables such as visitation rate and pollinator type could explain differences in floral morphology seen in different populations. To assess pollinator community compositions, pollinator visitation rates, and the degree of herkogamy and flower size, flowers from 13 populations were observed and measured across the Western Cape, South Africa. Multiple regression analyses indicated that pollinator-related variables had no significant effect on the degree of herkogamy between sites. However, the degree of herkogamy was strongly negatively associated with the time of measurement. It remains possible that pollinators have had an effect on the development of herkogamy throughout the evolutionary timeline of different W. paniculata populations, but not necessarily to the fine-scale degree, as was predicted for this study. Annual fluctuations in pollinator community composition, paired with recent disturbances such as urbanization and the overabundance of artificially introduced honeybee hives, might also result in the signal of pollinator adaptation getting lost. Surprisingly, differences in herkogamy between populations could largely be explained by the time of day at which flowers were measured, suggesting a significant narrowing of the distance between reproductive parts throughout the day. We propose that this floral movement could possibly be an adaptation to ensure pollination if pollinator visitation to a flower was not sufficient earlier in the day, and will be explored in subsequent studies.

Keywords: enantiostyly, floral movement, geographic variation, ecotypes

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Authors: Christian Fercher, Jiaul Islam, Simon R. Corrie

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Fluorescence-based immunodiagnostics are an emerging field in biosensor development and exhibit several advantages over traditional detection methods. While various affinity biosensors have been developed to generate a fluorescence signal upon sensing varying concentrations of analytes, reagentless, reversible, and continuous monitoring of complex biological samples remains challenging. Here, we aimed to genetically engineer biosensors based on single-chain antibody fragments (scFv) that are site-specifically labeled with environmentally sensitive fluorescent unnatural amino acids (UAA). A rational design approach resulted in quantifiable analyte-dependent changes in peak fluorescence emission wavelength and enabled antigen detection in vitro. Incorporation of a polarity indicator within the topological neighborhood of the antigen-binding interface generated a titratable wavelength blueshift with nanomolar detection limits. In order to ensure continuous analyte monitoring, scFv candidates with fast binding and dissociation kinetics were selected from a genetic library employing a high-throughput phage display and affinity screening approach. Initial rankings were further refined towards rapid dissociation kinetics using bio-layer interferometry (BLI) and surface plasmon resonance (SPR). The most promising candidates were expressed, purified to homogeneity, and tested for their potential to detect biomarkers in a continuous microfluidic-based assay. Variations of dissociation kinetics within an order of magnitude were achieved without compromising the specificity of the antibody fragments. This approach is generally applicable to numerous antibody/antigen combinations and currently awaits integration in a wide range of assay platforms for one-step protein quantification.

Keywords: antibody engineering, biosensor, phage display, unnatural amino acids

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Authors: Binh T. T. Nguyen, Zhenyu Li, Eric Yap, Yi Zhang, Ai-Qun Liu

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Silicon-photonic-sensor system is an emerging class of analytical technologies that use evanescent field wave to sensitively measure the slight difference in the surrounding environment. The wavelength shift induced by local refractive index change is used as an indicator in the system. These devices can be served as sensors for a wide variety of chemical or biomolecular detection in clinical and environmental fields. In our study, a system including a silicon-based micro-ring resonator, microfluidic channel, and optical processing is designed, fabricated for biomolecule detection. The system is demonstrated to detect Clostridium botulinum type A neurotoxin (BoNT) in different water sources. BoNT is one of the most toxic substances known and relatively easily obtained from a cultured bacteria source. The toxin is extremely lethal with LD50 of about 0.1µg/70kg intravenously, 1µg/ 70 kg by inhalation, and 70µg/kg orally. These factors make botulinum neurotoxins primary candidates as bioterrorism or biothreat agents. It is required to have a sensing system which can detect BoNT in a short time, high sensitive and automatic. For BoNT detection, silicon-based micro-ring resonator is modified with a linker for the immobilization of the anti-botulinum capture antibody. The enzymatic reaction is employed to increase the signal hence gains sensitivity. As a result, a detection limit to 30 pg/mL is achieved by our silicon-photonic sensor within a short period of 80 min. The sensor also shows high specificity versus the other type of botulinum. In the future, by designing the multifunctional waveguide array with fully automatic control system, it is simple to simultaneously detect multi-biomaterials at a low concentration within a short period. The system has a great potential to apply for online, real-time and high sensitivity for the label-free bimolecular rapid detection.

Keywords: biotoxin, photonic, ring resonator, sensor

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Authors: J. Ritonja, R. Brezovnik, M. Petrun, B. Polajžer

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Many modern synchronous generators in power systems are extremely weakly damped. The reasons are cost optimization of the machine building and introduction of the additional control equipment into power systems. Oscillations of the synchronous generators and related stability problems of the power systems are harmful and can lead to failures in operation and to damages. The only useful solution to increase damping of the unwanted oscillations represents the implementation of the power system stabilizers. Power system stabilizers generate the additional control signal which changes synchronous generator field excitation voltage. Modern power system stabilizers are integrated into static excitation systems of the synchronous generators. Available commercial power system stabilizers are based on linear control theory. Due to the nonlinear dynamics of the synchronous generator, current stabilizers do not assure optimal damping of the synchronous generator’s oscillations in the entire operating range. For that reason the use of the robust power system stabilizers which are convenient for the entire operating range is reasonable. There are numerous robust techniques applicable for the power system stabilizers. In this paper the use of sliding mode control for synchronous generator stability improvement is studied. On the basis of the sliding mode theory, the robust power system stabilizer was developed. The main advantages of the sliding mode controller are simple realization of the control algorithm, robustness to parameter variations and elimination of disturbances. The advantage of the proposed sliding mode controller against conventional linear controller was tested for damping of the synchronous generator oscillations in the entire operating range. Obtained results show the improved damping in the entire operating range of the synchronous generator and the increase of the power system stability. The proposed study contributes to the progress in the development of the advanced stabilizer, which will replace conventional linear stabilizers and improve damping of the synchronous generators.

Keywords: control theory, power system stabilizer, robust control, sliding mode control, stability, synchronous generator

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Authors: Yong-Kian Lim, Khan Cheung, Xin Dang, Steven Roberts, Xiaotong Wang, Vengatesen Thiyagarajan

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Unprecedented rate of increased CO₂ level in the ocean and the subsequent changes in carbonate system including decreased pH, known as ocean acidification (OA), is predicted to disrupt not only the calcification process but also several other physiological and developmental processes in a variety of marine organisms, including edible oysters. Nonetheless, not all species are vulnerable to those OA threats, e.g., some species may be able to cope with OA stress using environmentally induced modifications on gene and protein expressions. For example, external environmental stressors, including OA, can influence the addition and removal of methyl groups through epigenetic modification (e.g., DNA methylation) process to turn gene expression “on or off” as part of a rapid adaptive mechanism to cope with OA. In this study, the above hypothesis was tested through testing the effect of OA, using decreased pH 7.4 as a proxy, on the DNA methylation pattern of an endemic and a commercially important estuary oyster species, Crassostrea hongkongensis, at the time of larval habitat selection and metamorphosis. Larval growth rate did not differ between control pH 8.1 and treatment pH 7.4. The metamorphosis rate of the pediveliger larvae was higher at pH 7.4 than those in control pH 8.1; however, over one-third of the larvae raised at pH 7.4 failed to attach to an optimal substrate as defined by biofilm presence. During larval development, a total of 130 genes were differentially methylated across the two treatments. The differential methylation in the larval genes may have partially accounted for the higher metamorphosis success rate under decreased pH 7.4 but with poor substratum selection ability. Differentially methylated loci were concentrated in the exon regions and appear to be associated with cytoskeletal and signal transduction, oxidative stress, metabolic processes, and larval metamorphosis, which implies the high potential of C. hongkongensis larvae to acclimate and adapt through non-genetic ways to OA threats within a single generation.

Keywords: adaptive plasticity, DNA methylation, larval metamorphosis, ocean acidification

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Authors: Rajapaksha Gedara Prasad Tharanga Jayasooriya, Matharage Gayani Dilshara, Yung Hyun Choi, Gi-Young Kim

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Camptothecin (CPT) is a quinolone alkaloid which inhibits DNA topoisomerase I that induces cytotoxicity in a variety of cancer cell lines. We previously showed that CPT effectively inhibited invasion of prostate cancer cells and also combined treatment with subtoxic doses of CPT and TNF-related apoptosis-inducing ligand (TRAIL) potentially enhanced apoptosis in a caspase-dependent manner in hepatoma cancer cells. Here, we found that treatment with CPT caused an irreversible cell cycle arrest in the G2/M phase. CPT-induced cell cycle arrest was associated with a decrease in protein levels of cell division cycle 25C (Cdc25C) and increased the level of cyclin B and p21. The CPT-induced decrease in Cdc25C was blocked in the presence of proteasome inhibitor MG132, thus reversed the cell cycle arrest. In addition to that treatment of CPT-increased phosphorylation of Cdc25C was the resulted of activation of checkpoint kinase 2 (Chk2), which was associated with phosphorylation of ataxia telangiectasia-mutated. Interestingly CPT induced G2/M phase of the cell cycle arrest is reactive oxygen species (ROS) dependent where ROS inhibitors NAC and GSH reversed the CPT-induced cell cycle arrest. These results further confirm by using transient knockdown of nuclear factor-erythroid 2-related factor 2 (Nrf2) since it regulates the production of ROS. Our data reveal that treatment of siNrf2 increased the ROS level as well as further increased the CPT induce G2/M phase cell cycle arrest. Our data also indicate CPT-enhanced cell cycle arrest through the extracellular signal-regulated kinase (ERK) and the c-Jun N-terminal kinase (JNK) pathway. Inhibitors of ERK and JNK more decreased the Cdc25C expression and protein expression of p21 and cyclin B. These findings indicate that Chk2-mediated phosphorylation of Cdc25C plays a major role in G2/M arrest by CPT.

Keywords: camptothecin, cell cycle, checkpoint kinase 2, nuclear factor-erythroid 2-related factor 2, reactive oxygen species

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Authors: Arda Ozkurt, Ozlem Bozkurt

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Brain-computer interfaces (BCIs) are devices that output commands by interpreting the data collected from the brain. Electroencephalography (EEG) is a non-invasive method to measure the brain's electrical activity. Since it was invented by Hans Berger in 1929, it has led to many neurological discoveries and has become one of the essential components of non-invasive measuring methods. Despite the fact that it has a low spatial resolution -meaning it is able to detect when a group of neurons fires at the same time-, it is a non-invasive method, making it easy to use without possessing any risks. In EEG, electrodes are placed on the scalp, and the voltage difference between a minimum of two electrodes is recorded, which is then used to accomplish the intended task. The recordings of EEGs include, but are not limited to, the currents along dendrites from synapses to the soma, the action potentials along the axons connecting neurons, and the currents through the synaptic clefts connecting axons with dendrites. However, there are some sources of noise that may affect the reliability of the EEG signals as it is a non-invasive method. For instance, the noise from the EEG equipment, the leads, and the signals coming from the subject -such as the activity of the heart or muscle movements- affect the signals detected by the electrodes of the EEG. However, new techniques have been developed to differentiate between those signals and the intended ones. Furthermore, an EEG device is not enough to analyze the data from the brain to be used by the BCI implication. Because the EEG signal is very complex, to analyze it, artificial intelligence algorithms are required. These algorithms convert complex data into meaningful and useful information for neuroscientists to use the data to design BCI devices. Even though for neurological diseases which require highly precise data, invasive BCIs are needed; non-invasive BCIs - such as EEGs - are used in many cases to help disabled people's lives or even to ease people's lives by helping them with basic tasks. For example, EEG is used to detect before a seizure occurs in epilepsy patients, which can then prevent the seizure with the help of a BCI device. Overall, EEG is a commonly used non-invasive BCI technique that has helped develop BCIs and will continue to be used to detect data to ease people's lives as more BCI techniques will be developed in the future.

Keywords: BCI, EEG, non-invasive, spatial resolution

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Authors: Husain Rajib, T. H. Sheikh, D. G. Jewel

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Background: Amblyopia is a frequent cause of monocular blindness in children. It can be unilateral or bilateral reduction of best corrected visual acuity associated with decrement in visual processing, accomodation, motility, spatial perception or spatial projection. Anisometropia is an important risk factor for amblyopia that develops when unequal refractive error causes the image to be blurred in the critical developmental period and central inhibition of the visual signal originating from the affected eye associated with significant visual problems including anisokonia, strabismus, and reduced stereopsis. Methods: It is a prospective hospital based study of newly diagnosed of amblyopia seen at the pediatric clinic of Chittagong Eye Infirmary & Training Complex. There were 50 anisometropic amblyopia subjects were examined & questionnaire was piloted. Included were all patients diagnosed with refractive amblyopia between 3 to 13 years, without previous amblyopia treatment, and whose parents were interested to participate in the study. Patients diagnosed with strabismic amblyopia were excluded. Patients were first corrected with the best correction for a month. When the VA in the amblyopic eye did not improve over month, then occlusion treatment was started. Occlusion was done daily for 6-8 hours (full time) together with vision therapy. The occlusion was carried out for 3 months. Results: In this study about 8% subjects had anisometropia from myopia, 18% from hyperopia, 74% from astigmatism. The initial mean visual acuity was 0.74 ± 0.39 Log MAR and after intervention of amblyopia therapy with active vision therapy mean visual acuity was 0.34 ± 0.26 Log MAR. About 94% of subjects were improving at least two lines. The depth of amblyopia associated with type of anisometropic refractive error and magnitude of Anisometropia (p<0.005). By doing this study 10% mild amblyopia, 64% moderate and 26% severe amblyopia were found. Binocular function also decreases with magnitude of Anisometropia. Conclusion: Anisometropic amblyopia is a most important factor in pediatric age group because it can lead to visual impairment. Occlusion therapy with at least one instructed hour of active visual activity practiced out of school hours was effective in anisometropic amblyopes who were diagnosed at the age of 8 years and older, and the patients complied well with the treatment.

Keywords: refractive error, anisometropia, amblyopia, strabismic amblyopia

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Alexander E. Hramov, Vadim V. Grubov, Alexey A. Koronovskii, Maria K. Kurovskaуa, Anastasija E. Runnova

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The perception of visual signals in the brain was among the first issues discussed in terms of multistability which has been introduced to provide mechanisms for information processing in biological neural systems. In this work the influence of the cognitive noise on the visual perception of multistable pictures has been investigated. The study includes an experiment with the bistable Necker cube illusion and the theoretical background explaining the obtained experimental results. In our experiments Necker cubes with different wireframe contrast were demonstrated repeatedly to different people and the probability of the choice of one of the cubes projection was calculated for each picture. The Necker cube was placed at the middle of a computer screen as black lines on a white background. The contrast of the three middle lines centered in the left middle corner was used as one of the control parameter. Between two successive demonstrations of Necker cubes another picture was shown to distract attention and to make a perception of next Necker cube more independent from the previous one. Eleven subjects, male and female, of the ages 20 through 45 were studied. The choice of the Necker cube projection was detected with the Electroencephalograph-recorder Encephalan-EEGR-19/26, Medicom MTD. To treat the experimental results we carried out theoretical consideration using the simplest double-well potential model with the presence of noise that led to the Fokker-Planck equation for the probability density of the stochastic process. At the first time an analytical solution for the probability of the selection of one of the Necker cube projection for different values of wireframe contrast have been obtained. Furthermore, having used the results of the experimental measurements with the help of the method of least squares we have calculated the value of the parameter corresponding to the cognitive noise of the person being studied. The range of cognitive noise parameter values for studied subjects turned to be [0.08; 0.55]. It should be noted, that experimental results have a good reproducibility, the same person being studied repeatedly another day produces very similar data with very close levels of cognitive noise. We found an excellent agreement between analytically deduced probability and the results obtained in the experiment. A good qualitative agreement between theoretical and experimental results indicates that even such a simple model allows simulating brain cognitive dynamics and estimating important cognitive characteristic of the brain, such as brain noise.

Keywords: bistability, brain, noise, perception, stochastic processes

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Authors: Kun Hua O., Dong Woon Kim, Won Hyung Lee

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Introduction: Neuropathic pain induced by spinal or peripheral nerve injury is highly resistant to common painkillers, nerve blocks, and other pain management approaches. Recently, several new therapeutic drug candidates have been developed to control neuropathic pain. In this study, we used the spinal nerve L5 ligation (SNL) model to investigate the ability of intrathecal or intravenous Evans blue to decrease pain behavior and to study the relationship between Evans blue and the neural structure of pain transmission. Method: Neuropathic pain (allodynia) of the left hind paw was induced by unilateral SNL in Sprague-Dawley rats(n=10) in each group. Evans blue (5, 15, 50μg/10μl) or phosphate buffer saline(PBS,10μl) was injected intrathecally at 3days post-ligation or intravenously(1mg/200 μl) 3days and 5days post-ligation . Mechanical sensitivity was assessed using Von Frey filaments at 3 days post-ligation and at 2 hours, days 1, 2, 3, 5,7 after intrathecal Evans blue injection, and on days 2, 4, 7, and 11 at 14 days after intravenous injection. In the intrathecal group, microglia and glutaminergic neurons in the dorsal horn and VNUT(vesicular nucleotide transporter) in the dorsal root ganglia were tested to evaluate co-staining with Evans blue. The experimental procedures were performed in accordance with the animal care guideline of the Korean Academy of Medical Science(Animal ethic committee of Chungnam National University Hospital: CNUH-014-A0005-1). Results: Tight ligation of the L5 spinal nerve induced allodynia in the left hind paw 3 days post-ligation. Intrathecal Evans blue most significantly(P＜0.001) alleviated allodynia at 2 days after intrathecal, but not an intravenous injection. Glutaminergic neurons in the dorsal horn and VNUT in the dorsal root ganglia were co-stained with Evans blue. On the other hand, microglia in the dorsal horn were partially co-stained with Evans blue. Conclusion: We confirmed that Evans blue might have an analgesic effect through the central nervous system, not another system in neuropathic pain of the SNL animal model. These results suggest Evans blue may be a potential new drug for the treatment of chronic pain. This research was supported by the National Research Foundation of Korea (NRF-2020R1A2C100757512), funded by the Ministry of Education.

Keywords: neuropathic pain, Evas blue, intrathecal, intravenous

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Authors: Hwang Ahreum, Kang Taejoon, Kim Bongsoo

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Nanosensors for high sensitive detection of diseases have been widely studied to improve the quality of life. Here, we suggest robust nano-plasmonic diagnostic sensor using cysteine tagged protein G (Cys3-protein G) and ultraflat, ultraclean and single-crystalline Au nanoplates. Protein G formed on an ultraflat Au surface provides ideal background for dense and uniform immobilization of antibodies. The Au is highly stable in diverse biochemical environment and can immobilize antibodies easily through Au-S bonding, having been widely used for various biosensing applications. Especially, atomically smooth single-crystalline Au nanomaterials synthesized using chemical vapor transport (CVT) method are very suitable to fabricate reproducible sensitive sensors. As the C-reactive protein (CRP) is a nonspecific biomarker of inflammation and infection, it can be used as a predictive or prognostic marker for various cardiovascular diseases. Cys3-protein G immobilized uniformly on the Au nanoplate enable CRP antibody (anti-CRP) to be ordered in a correct orientation, making their binding capacity be maximized for CRP detection. Immobilization condition for the Cys3-protein G and anti-CRP on the Au nanoplate is optimized visually by AFM analysis. Au nanoparticle - Au nanoplate (NPs-on-Au nanoplate) assembly fabricated from sandwich immunoassay for CRP can reduce zero-signal extremely caused by nonspecific bindings, providing a distinct surface-enhanced Raman scattering (SERS) enhancement still in 10-18 M of CRP concentration. Moreover, the NP-on-Au nanoplate sensor shows an excellent selectivity against non-target proteins with high concentration. In addition, comparing with control experiments employing a Au film fabricated by e-beam assisted deposition and linker molecule, we validate clearly contribution of the Au nanoplate for the attomolar sensitive detection of CRP. We expect that the devised platform employing the complex of single-crystalline Au nanoplates and Cys3-protein G can be applied for detection of many other cancer biomarkers.

Keywords: Au nanoplate, biomarker, diagnostic sensor, protein G, SERS

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Authors: Michele M. Mahr

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The purpose of this study is to educate, inform, and facilitate scholarly conversation and discussion regarding the implementation of mindfulness techniques when working with individuals with substance use disorder (SUD) or addictive behaviors in mental health. Mindfulness can be recognized as the present moment, non-judgmental awareness, initiated by concentrated attention that is non-reactive and as openheartedly as possible. Individuals with SUD or addiction typically are challenged with triggers, environmental situations, cravings, or social pressures which may deter them from remaining abstinent from their drug of choice or addictive behavior. Also, mindfulness is recognized as one of the cognitive and behavioral treatment approaches and is both a physical and mental practice that encompasses individuals to become aware of internal situations and experiences with undivided attention. That said, mindfulness may be an effective strategy for individuals to employ during these experiences. This study will reveal how mental health practitioners and addiction counselors may find mindfulness to be an essential component of increasing wellness when working with individuals seeking mental health treatment. To this end, mindfulness is simply the ability individuals have to know what is actually happening as it is occurring and what they are experiencing at the moment. In the context of substance abuse and addiction, individuals may employ breathing techniques, meditation, and cognitive restructuring of the mind to become aware of present moment experiences. Furthermore, the notion of mindfulness has been directly connected to the development of neuropathways. The creation of the neural pathways then leads to creating thoughts which leads to developing new coping strategies and adaptive behaviors. Mindfulness strategies can assist individuals in connecting the mind with the body, allowing the individual to remain centered and focused. All of these mentioned above are vital components to recovery during substance abuse and addiction treatment. There are a variety of therapeutic modalities applying the key components of mindfulness, such as Mindfulness-Based Stress Reduction (MBSR) and Mindfulness-Based Cognitive Therapy for depression (MBCT). This study will provide an overview of both MBSR and MBCT in relation to treating individuals with substance abuse and addiction. The author will also provide strategies for readers to employ when working with clients. Lastly, the author will create and foster a safe space for discussion and engaging conversation among participants to ask questions, share perspectives, and be educated on the numerous benefits of mindfulness within wellness.

Keywords: mindfulness, wellness, substance abuse, mental health

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Authors: Abdelhalim. N. Mohammed, Mohammed. Y. Esmail

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In the course of recent decades, medical imaging has been dominated by the use of costly film media for review and archival of medical investigation, however due to developments in networks technologies and common acceptance of a standard digital imaging and communication in medicine (DICOM) another approach in light of World Wide Web was produced. Web technologies successfully used in telemedicine applications, the combination of web technologies together with DICOM used to design a web-based and open source DICOM viewer. The Web server allowance to inquiry and recovery of images and the images viewed/manipulated inside a Web browser without need for any preinstalling software. The dynamic site page for medical images visualization and processing created by using JavaScript and HTML5 advancements. The XAMPP ‘apache server’ is used to create a local web server for testing and deployment of the dynamic site. The web-based viewer connected to multiples devices through local area network (LAN) to distribute the images inside healthcare facilities. The system offers a few focal points over ordinary picture archiving and communication systems (PACS): easy to introduce, maintain and independently platforms that allow images to display and manipulated efficiently, the system also user-friendly and easy to integrate with an existing system that have already been making use of web technologies. The wavelet-based image compression technique on which 2-D discrete wavelet transform used to decompose the image then wavelet coefficients are transmitted by entropy encoding after threshold to decrease transmission time, stockpiling cost and capacity. The performance of compression was estimated by using images quality metrics such as mean square error ‘MSE’, peak signal to noise ratio ‘PSNR’ and compression ratio ‘CR’ that achieved (83.86%) when ‘coif3’ wavelet filter is used.

Keywords: DICOM, discrete wavelet transform, PACS, HIS, LAN

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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: Abbas Ali Husseini, Ali Mohammad Yazdani, Fatemeh Ghadiri, Alper Şişman

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We developed a microchip device that uses surface acoustic waves for rapid lysis of low level of cell samples. The device incorporates sharp-edge glass microparticles for improved performance. We optimized the lysis conditions for high efficiency and evaluated the device's feasibility for point-of-care applications. The microchip contains a 13-finger pair interdigital transducer with a 30-degree focused angle. It generates high-intensity acoustic beams that converge 6 mm away. The microchip operates at a frequency of 16 MHz, exciting Rayleigh waves with a 250 µm wavelength on the LiNbO3 substrate. Cell lysis occurs when Candida albicans cells and glass particles are placed within the focal area. The high-intensity surface acoustic waves induce centrifugal forces on the cells and glass particles, resulting in cell lysis through lateral forces from the sharp-edge glass particles. We conducted 42 pilot cell lysis experiments to optimize the surface acoustic wave-induced streaming. We varied electrical power, droplet volume, glass particle size, concentration, and lysis time. A regression machine-learning model determined the impact of each parameter on lysis efficiency. Based on these findings, we predicted optimal conditions: electrical signal of 2.5 W, sample volume of 20 µl, glass particle size below 10 µm, concentration of 0.2 µg, and a 5-minute lysis period. Downstream analysis successfully amplified a DNA target fragment directly from the lysate. The study presents an efficient microchip-based cell lysis method employing acoustic streaming and microparticle collisions within microdroplets. Integration of a surface acoustic wave-based lysis chip with an isothermal amplification method enables swift point-of-care applications.

Keywords: cell lysis, surface acoustic wave, micro-glass particle, droplet

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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: Vakhtang Charaia, Mariam Lashkhi

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Foreign direct investment (FDI) plays a vital role in global business. It provides firms with new markets and advertising channels, cheaper production facilities, admission to new technology, products, skills and financing. FDI can provide a recipient country/company with a source of new technologies, capital, practice, products, management skills, and as such can be a powerful drive for economic development. It is one of the key elements of stable economic development in many countries, especially in developing ones. Therefore the size of FDI inflow is one of the most crustal factors for economic perfection in small economy countries (like, Georgia), while most of developed ones are net exporters of FDI. Since, FDI provides firms with new markets; admission to new technologies, products and management skills; marketing channels; cheaper production facilities, and financing opportunities. It plays a significant role in Georgian economic development. Increasing FDI inflows from all over the world to Georgia in last decade was achieved with the outstanding reforms managed by the Georgian government. However, such important phenomenon as world financial crisis and Georgian-Russian war put its consequence on the over amount of FDI inflow in Georgia in the last years. It is important to mention that the biggest investor region for Georgia is EU, which is interested in Georgia not only from the economic points of view but from political. The case studies from main EU investor countries show that Georgia has a big potential of investment in different areas, such as; financial sector, energy, construction, tourism industry, transport and communications. Moreover, signing of Association Agreement between Georgia and EU will further boost all the fields of economy in Georgia in both short and long terms. It will attract more investments from different countries and especially from EU. The last, but not least important issue is the calculation of annual FDI inflow to Georgia, which it is calculated differently by different organizations, based on different methodologies, but what is more important is that all of them show significant increase of FDI in last decade, which gives a positive signal to investors and underlines necessity of further improvement of investment climate in the same direction.

Keywords: foreign direct investment (FDI), Georgia, investment development path, investment climate

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Authors: O. Elkana, O Heyman, S. Hamdan, M. Franko, J. Vatine

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Objective: To investigate whether a direct link exists between perceived pain (PP) and executive functions (EF), above and beyond the influence of depression symptoms, in the context of medical rehabilitation. Design: Cross-sectional study. Setting: Rehabilitation Hospital. Participants: 125 medical records of hospitalized patients were screened for matching to our inclusion criteria. Only 60 patients were found fit and were asked to participate. 19 decline to participate on personal basis. The 41 neurologically intact patients (mean age 46, SD 14.96) that participated in this study were in their sub-acute stage of recovery, with fluent Hebrew, with intact upper limb (to neutralize influence on psychomotor performances) and without an organic brain damage. Main Outcome Measures: EF were assessed using the Wisconsin Card Sorting Test (WCST) and the Stop-Signal Test (SST). PP was measured using 3 well-known pain questionnaires: Pain Disability Index (PDI), The Short-Form McGill Questionnaire (SF-MPQ) and the Pain Catastrophizing Scale (PCS). Perceived pain index (PPI) was calculated by the mean score composite from the 3 pain questionnaires. Depression symptoms were assessed using the Patient Health Questionnaire (PHQ-9). Results: The results indicate that irrespective of the presence of depression symptoms, PP is directly correlated with response inhibition (SST partial correlation: r=0.5; p=0.001) and mental flexibility (WSCT partial correlation: r=-0.37; p=0.021), suggesting decreased performance in EF as PP severity increases. High correlations were found between the 3 pain measurements: SF-MPQ with PDI (r=0.62, p<0.001), SF-MPQ with PCS (r=0.58, p<0.001) and PDI with PCS (r=0.38, p=0.016) and each questionnaire alone was also significantly associated with EF; thus, no specific questionnaires ‘pulled’ the results obtained by the general index (PPI). Conclusion: Examining the direct association between PP and EF, beyond the contribution of depression symptoms, provides further clinical evidence suggesting that EF and PP share underlying mediating neuronal mechanisms. Clinically, the importance of assessing patients' EF abilities as well as PP severity during rehabilitation is underscored.

Keywords: depression, executive functions, mental-flexibility, neuropsychology, pain perception, perceived pain, response inhibition

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Authors: Sebastian Wójtowicz, Anna Mosiołek, Anna Słupik, Zbigniew Wroński, Dariusz Białoszewski

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Introduction: In whole-body vibration (WBV) high-frequency mechanical stimuli is generated by a vibration plate and is transferred through bone, muscle and connective tissues to the whole body. The research has shown that the implementation of a vibration plate training over a long period of time leads to improvement of neuromuscular facilitation, especially in afferent neural pathways, which are responsible for the conduction of vibration and proprioceptive stimuli, muscle function, balance, and proprioception. The vibration stimulus is suggested to briefly inhibit the conduction of afferent signals from proprioceptors and may hinder the maintenance of body balance. The purpose of this study was to evaluate the result of a single set of exercises connected with whole-body vibration on the proprioception. Material and Methods: The study enrolled 60 people aged 19-24 years. These individuals were divided into a test group (group A) and a control group (group B). Both groups consisted of 30 persons and performed the same set of exercises on a vibration plate. The following vibration parameters: frequency of 20Hz and amplitude of 3mm, were used in the group A. The vibration plate was turned off while the control group did their exercises. All participants performed six dynamic 30-seconds-long exercises with a 60-second resting period between them. Large muscle groups of the trunk, pelvis, and lower limbs were involved while taking the exercises. The results were measured before and immediately after the exercises. The proprioception of lower limbs was measured in a closed kinematic chain using a Humac 360®. Participants were instructed to perform three squats with biofeedback in a defined range of motion. Then they did three squats without biofeedback which were measured. The final result was the average of three measurements. Statistical analysis was performed using Statistica 10.0 PL software. Results: There were no significant differences between the groups, both before and after the exercise (p > 0.05). The proprioception did not change in both the group A and the group B. Conclusions: 1. Deterioration in proprioception was not observed immediately after the vibration stimulus. This suggests that vibration-induced blockage of proprioceptive stimuli conduction can only have a short-lasting effect occurring only in the presence of the vibration stimulus. 2. Short-term use of vibration seems to be safe for patients with proprioceptive impairment due to the fact that the treatment does not decrease proprioception. 3. There is a need for supplementing the results with evaluation of proprioception while vibration stimuli are being applied. Moreover, the effects of vibration parameters used in the exercises should be evaluated.

Keywords: joint position sense, proprioception, squat, whole body vibration

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