Search results for: signal spectrum

Authors: Haohua Zong, Marios Kotsonis

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Plasma synthetic jet actuator (PSJA) is a new concept of zero net mass flow actuator which utilizes pulsed arc/spark discharge to rapidly pressurize gas in a small cavity under constant-volume conditions. The unique combination of high exit jet velocity (>400 m/s) and high actuation frequency (>5 kHz) provides a promising solution for high-speed high-Reynolds-number flow control. This paper focuses on the performance of PSJA in repetitive working mode which is more relevant to future flow control applications. A two-electrodes PSJA (cavity volume: 424 mm3, orifice diameter: 2 mm) together with a capacitive discharge circuit (discharge energy: 50 mJ-110 mJ) is designed to enable repetitive operation. Time-Resolved Particle Imaging Velocimetry (TR-PIV) system working at 10 kHz is exploited to investigate the influence of discharge frequency on performance of PSJA. In total, seven cases are tested, covering a wide range of discharge frequencies (20 Hz-560 Hz). The pertinent flow features (shock wave, vortex ring and jet) remain the same for single shot mode and repetitive working mode. Shock wave is issued prior to jet eruption. Two distinct vortex rings are formed in one cycle. The first one is produced by the starting jet whereas the second one is related with the shock wave reflection in cavity. A sudden pressure rise is induced at the throat inlet by the reflection of primary shock wave, promoting the shedding of second vortex ring. In one cycle, jet exit velocity first increases sharply, then decreases almost linearly. Afterwards, an alternate occurrence of multiple jet stages and refresh stages is observed. By monitoring the dynamic evolution of exit velocity in one cycle, some integral performance parameters of PSJA can be deduced. As frequency increases, the jet intensity in steady phase decreases monotonically. In the investigated frequency range, jet duration time drops from 250 µs to 210 µs and peak jet velocity decreases from 53 m/s to approximately 39 m/s. The jet impulse and the expelled gas mass (0.69 µN∙s and 0.027 mg at 20 Hz) decline by 48% and 40%, respectively. However, the electro-mechanical efficiency of PSJA defined by the ratio of jet mechanical energy to capacitor energy doesn’t show significant difference (o(0.01%)). Fourier transformation of the temporal exit velocity signal indicates two dominant frequencies. One corresponds to the discharge frequency, while the other accounts for the alternation frequency of jet stage and refresh stage in one cycle. The alternation period (300 µs approximately) is independent of discharge frequency, and possibly determined intrinsically by the actuator geometry. A simple analytical model is established to interpret the alternation of jet stage and refresh stage. Results show that the dynamic response of exit velocity to a small-scale disturbance (jump in cavity pressure) can be treated as a second-order under-damping system. Oscillation frequency of the exit velocity, namely alternation frequency, is positively proportional to exit area, but inversely proportional to cavity volume and throat length. Theoretical value of alternation period (305 µs) agrees well with the experimental value.

Keywords: plasma, synthetic jet, actuator, frequency effect

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Authors: E. Mosiniewicz-Szablewska, P. Suchocki, P. C. Morais

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Despite the significant progress in cancer treatment, there is a need to search for new therapeutic methods in order to minimize side effects. Chemotherapy, the main current method of treating cancer, is non-selective and has a number of limitations. Toxicity to healthy cells is undoubtedly the biggest problem limiting the use of many anticancer drugs. The problem of how to kill cancer without harming a patient can be solved by using organic selenium (IV) compounds. Organic selenium (IV) compounds are a new class of materials showing a strong anticancer activity. They are first organic compounds containing selenium at the +4 oxidation level and therefore they eliminate the multidrug-resistance for all tumor cell lines tested so far. These materials are capable of selectively killing cancer cells without damaging the healthy ones. They are obtained by the incorporation of selenous acid (H2SeO3) into molecules of fatty acids of sunflower oil and therefore, they are inexpensive to manufacture. Attaching these compounds to magnetic carriers enables their precise delivery directly to the tumor area and the simultaneous application of the magnetic hyperthermia, thus creating a huge opportunity to effectively get rid of the tumor without any side effects. Polylactic-co-glicolic acid (PLGA) nanocapsules loaded with maghemite (-Fe2O3) nanoparticles and organic selenium (IV) compounds are successfully prepared by nanoprecipitation method. In vitro antitumor activity of the nanocapsules were evidenced using murine melanoma (B16-F10), oral squamos carcinoma (OSCC) and murine (4T1) and human (MCF-7) breast lines. Further exposure of these cells to an alternating magnetic field increased the antitumor effect of nanocapsules. Moreover, the nanocapsules presented antitumor effect while not affecting normal cells. Magnetic properties of the nanocapsules were investigated by means of dc magnetization, ac susceptibility and electron spin resonance (ESR) measurements. The nanocapsules presented a typical superparamagnetic behavior around room temperature manifested itself by the split between zero field-cooled/field-cooled (ZFC/FC) magnetization curves and the absence of hysteresis on the field-dependent magnetization curve above the blocking temperature. Moreover, the blocking temperature decreased with increasing applied magnetic field. The superparamagnetic character of the nanocapsules was also confirmed by the occurrence of a maximum in temperature dependences of both real ′(T) and imaginary ′′ (T) components of the ac magnetic susceptibility, which shifted towards higher temperatures with increasing frequency. Additionally, upon decreasing the temperature the ESR signal shifted to lower fields and gradually broadened following closely the predictions for the ESR of superparamagnetoc nanoparticles. The observed superparamagnetic properties of nanocapsules enable their simple manipulation by means of magnetic field gradient, after introduction into the blood stream, which is a necessary condition for their use as magnetic drug carriers. The observed anticancer and superparamgnetic properties show that the magnetic nanocapsules loaded with organic selenium (IV) compounds should be considered as an effective material system for magnetic drug delivery and magnetohyperthermia inductor in antitumor therapy.

Keywords: cancer treatment, magnetic drug delivery system, nanomaterials, nanotechnology

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Authors: Patrick Cormier, Cesar Meylan, Matt Jensen, Dana Agar-Newman, Chloe Werle, Ming-Chang Tsai, Marc Klimstra

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Sprint-derived horizontal force-velocity-power (FVP) profiles can be developed with adequate validity and reliability with satellite (GPS/GNSS) systems. However, FVP metrics are sensitive to small nuances in data processing procedures such that minor differences in defining the onset and end of the sprint could result in different FVP metric outcomes. Furthermore, in team-sports, there is a requirement for rapid analysis and feedback of results from multiple athletes, therefore developing standardized and automated methods to improve the speed, efficiency and reliability of this process are warranted. Thus, the purpose of this study was to compare different methods of sprint end detection on the development of FVP profiles from 10Hz GPS/GNSS data through goodness-of-fit and intertrial reliability statistics. Seventeen national team female soccer players participated in the FVP protocol which consisted of 2x40m maximal sprints performed towards the end of a soccer specific warm-up in a training session (1020 hPa, wind = 0, temperature = 30°C) on an open grass field. Each player wore a 10Hz Catapult system unit (Vector S7, Catapult Innovations) inserted in a vest in a pouch between the scapulae. All data were analyzed following common procedures. Variables computed and assessed were the model parameters, estimated maximal sprint speed (MSS) and the acceleration constant τ, in addition to horizontal relative force (F₀), velocity at zero (V₀), and relative mechanical power (Pmax). The onset of the sprints was standardized with an acceleration threshold of 0.1 m/s². The sprint end detection methods were: 1. Time when peak velocity (MSS) was achieved (zero acceleration), 2. Time after peak velocity drops by -0.4 m/s, 3. Time after peak velocity drops by -0.6 m/s, and 4. When the integrated distance from the GPS/GNSS signal achieves 40-m. Goodness-of-fit of each sprint end detection method was determined using the residual sum of squares (RSS) to demonstrate the error of the FVP modeling with the sprint data from the GPS/GNSS system. Inter-trial reliability (from 2 trials) was assessed utilizing intraclass correlation coefficients (ICC). For goodness-of-fit results, the end detection technique that used the time when peak velocity was achieved (zero acceleration) had the lowest RSS values, followed by -0.4 and -0.6 velocity decay, and 40-m end had the highest RSS values. For intertrial reliability, the end of sprint detection techniques that were defined as the time at (method 1) or shortly after (method 2 and 3) when MSS was achieved had very large to near perfect ICC and the time at the 40 m integrated distance (method 4) had large to very large ICCs. Peak velocity was reached at 29.52 ± 4.02-m. Therefore, sport scientists should implement end of sprint detection either when peak velocity is determined or shortly after to improve goodness of fit to achieve reliable between trial FVP profile metrics. Although, more robust processing and modeling procedures should be developed in future research to improve sprint model fitting. This protocol was seamlessly integrated into the usual training which shows promise for sprint monitoring in the field with this technology.

Keywords: automated, biomechanics, team-sports, sprint

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Authors: Viktor D. Dubrovin, Masoud Mollaee, Jie Zong, Xiushan Zhu, Nasser Peyghambarian

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Glasses doped with high rare-earth (RE) elements concentration attracted considerable attention since the middle of the 20th century due to their particular magneto-optical properties. Such glasses exhibit the Faraday effect in which the polarization plane of a linearly polarized light beam is rotated by the interaction between the incident light and the magneto-optical material. That effect found application in optical isolators that are useful for laser systems, which can prevent back reflection of light into lasers or optical amplifiers and reduce signal instability and noise. Glasses are of particular interest since they are cost-effective and can be formed into fibers, thus breaking the limits of traditional bulk optics requiring optical coupling for use with fiber-optic systems. The advent of high-power fiber lasers operating near 2µm revealed a necessity in the development of all fiber isolators for this region. Ce³⁺, Pr³⁺, Dy³⁺, and Tb³⁺ ions provide the biggest contribution to the Verdet constant value of optical materials among the RE. It is known that Pr³⁺ and Tb³⁺ ions have strong absorption bands near 2 µm, thus making Dy³⁺ and Ce³⁺ the only prospective candidates for fiber isolator operating in that region. Due to the high tendency of Ce³⁺ ions pass to Ce⁴⁺ during the synthesis, glasses with high cerium content usually suffers from Ce⁴⁺ ions absorption extending from visible to IR. Additionally, Dy³⁺ (₆H¹⁵/²) same as Ho³⁺ (⁵I₈) ions, have the largest effective magnetic moment (µeff = 10.6 µB) among the RE ions that starts to play the key role if the operating region is far from 4fⁿ→ 4fⁿ⁻¹5 d¹ electric-dipole transition relevant to the Faraday Effect. Considering the high effective magnetic moment value of Er³⁺ ions (µeff = 9.6 µB) that is 3rd after Dy³⁺/ Ho³⁺ and Tb³⁺, it is possible to assume that Er³⁺ doped glasses should exhibit Verdet constant value near 2µm that is comparable with one of Dy doped glasses. Thus, partial replacement of Dy³⁺ on Er³⁺ ions has been performed, keeping the overall concentration of Re₂O₃ equal to 70 wt.% (30.6 mol.%). Al₂O₃-B₂O₃-SiO₂-30.6RE₂O₃ (RE= Er, Dy) glasses had been synthesized, and their thermal, spectral, optical, structural, and magneto-optical properties had been studied. Glasses synthesis had been conducted in Pt crucibles for 3h at 1500 °C. The obtained melt was poured into preheated up to 400 °C mold and annealed from 800 oC to room temperature for 12h with 1h dwell. The mass of obtained glass samples was about 200g. Shown that the difference between crystallization and glass transition temperature is about 150 oC, even taking into account the fact that high content of RE₂O₃ leads to glass network depolymerization. Verdet constant of Al₂O₃-B₂O₃-SiO₂-30.6RE₂O₃ glasses for wavelength 1950 nm can reach more than 5.9 rad/(T*m), which is among the highest number reported for a paramagnetic glass at this wavelength. The refractive index value was found to be equal to 1.7545 at 633 nm. Our experimental results show that Al₂O₃-B₂O₃-SiO₂-30.6RE₂O₃ glasses with high Dy₂O₃ content are expected to be promising material for use as highly effective Faraday isolators and modulators of electromagnetic radiation in the 2μm region.

Keywords: oxide glass, magneto-optical, dysprosium, erbium, Faraday rotator, boron-aluminosilicate system

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Authors: Yi Li, Rui Lu, Lianjun Wang

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With the rapid development of chemical industry, the consumption of volatile organic compounds (VOCs) has increased extensively. In the process of VOCs production and application, plenty of them have been transferred to environment. As a result, it has led to pollution problems not only in soil and ground water but also to human beings. Thus, it is important to develop a sensitive and cost-effective analytical method for trace VOCs detection in environment. Surface-enhanced Raman Spectroscopy (SERS), as one of the most sensitive optical analytical technique with rapid response, pinpoint accuracy and noninvasive detection, has been widely used for ultratrace analysis. Based on the plasmon resonance on the nanoscale metallic surface, SERS technology can even detect single molecule due to abundant nanogaps (i.e. 'hot spots') on the nanosubstrate. In this work, a self-supported flexible silver nitrate (AgNO3)/ethylene-propylene copolymer (EPM) hybrid nanofibers was fabricated by electrospinning. After an in-situ chemical reduction using ice-cold sodium borohydride as reduction agent, numerous silver nanoparticles were formed on the nanofiber surface. By adjusting the reduction time and AgNO3 content, the morphology and dimension of silver nanoparticles could be controlled. According to the principles of solid-phase extraction, the hydrophobic substance is more likely to partition into the hydrophobic EPM membrane in an aqueous environment while water and other polar components are excluded from the analytes. By the enrichment of EPM fibers, the number of hydrophobic molecules located on the 'hot spots' generated from criss-crossed nanofibers is greatly increased, which further enhances SERS signal intensity. The as-prepared Ag/EPM hybrid nanofibers were first employed to detect common SERS probe molecule (p-aminothiophenol) with the detection limit down to 10-12 M, which demonstrated an excellent SERS performance. To further study the application of the fabricated substrate for monitoring hydrophobic substance in water, several typical VOCs, such as benzene, toluene and p-xylene, were selected as model compounds. The results showed that the characteristic peaks of these target analytes in the mixed aqueous solution could be distinguished even at a concentration of 10-6 M after multi-peaks gaussian fitting process, including C-H bending (850 cm-1), C-C ring stretching (1581 cm-1, 1600 cm-1) of benzene, C-H bending (844 cm-1 ,1151 cm-1), C-C ring stretching (1001 cm-1), CH3 bending vibration (1377 cm-1) of toluene, C-H bending (829 cm-1), C-C stretching (1614 cm-1) of p-xylene. The SERS substrate has remarkable advantages which combine the enrichment capacity from EPM and the Raman enhancement of Ag nanoparticles. Meanwhile, the huge specific surface area resulted from electrospinning is benificial to increase the number of adsoption sites and promotes 'hot spots' formation. In summary, this work provides powerful potential in rapid, on-site and accurate detection of trace VOCs using a portable Raman.

Keywords: electrospinning, ethylene-propylene copolymer, silver nanoparticles, SERS, VOCs

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Authors: Daniel Rowe, Christopher R. Vogel, Richard H. J. Willden

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The University of Oxford’s recirculating water flume is a combined wave and current test tank with a 1 m depth, 1.1 m width, and 10 m long working section, and is capable of flow speeds up to 1 ms−1 . This study documents the hydrodynamic characteristics of the facility in preparation for experimental testing of horizontal axis tidal stream turbine models. The turbine to be tested has a rotor diameter of 0.6 m and is a modified version of one of two model-scale turbines tested in previous experimental campaigns. An Acoustic Doppler Velocimeter (ADV) was used to measure the flow at high temporal resolution at various locations throughout the flume, enabling the spatial uniformity and turbulence flow parameters to be investigated. The mean velocity profiles exhibited high levels of spatial uniformity at the design speed of the flume, 0.6 ms−1 , with variations in the three-dimensional velocity components on the order of ±1% at the 95% confidence level, along with a modest streamwise acceleration through the measurement domain, a target 5 m working section of the flume. A high degree of uniformity was also apparent for the turbulence intensity, with values ranging between 1-2% across the intended swept area of the turbine rotor. The integral scales of turbulence exhibited a far higher degree of variation throughout the water column, particularly in the streamwise and vertical scales. This behaviour is believed to be due to the high signal noise content leading to decorrelation in the sampling records. To achieve more realistic levels of vertical velocity shear in the flume, a simple procedure to practically generate target vertical shear profiles in open-channel flows is described. Here, the authors arranged a series of non-uniformly spaced parallel bars placed across the width of the flume and normal to the onset flow. By adjusting the resistance grading across the height of the working section, the downstream profiles could be modified accordingly, characterised by changes in the velocity profile power law exponent, 1/n. Considering the significant temporal variation in a tidal channel, the choice of the exponent denominator, n = 6 and n = 9, effectively provides an achievable range around the much-cited value of n = 7 observed at many tidal sites. The resulting flow profiles, which we intend to use in future turbine tests, have been characterised in detail. The results indicate non-uniform vertical shear across the survey area and reveal substantial corner flows, arising from the differential shear between the target vertical and cross-stream shear profiles throughout the measurement domain. In vertically sheared flow, the rotor-equivalent turbulence intensity ranges between 3.0-3.8% throughout the measurement domain for both bar arrangements, while the streamwise integral length scale grows from a characteristic dimension on the order of the bar width, similar to the flow downstream of a turbulence-generating grid. The experimental tests are well-defined and repeatable and serve as a reference for other researchers who wish to undertake similar investigations.

Keywords: acoustic doppler Velocimeter, experimental hydrodynamics, open-channel flow, shear profiles, tidal stream turbines

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Authors: Mariam Khaled, Noha Farag, Ghada Mohamed Abdel Salam, Khaled Abu-Aisha, Mohamed El-Azizi

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Gastric and colorectal cancers are among the most frequent causes of cancer-associated mortalities in Africa. They have been considered as a global public health concern, as nearly one million new cases are reported per year. IL-1β is a pro-inflammatory cytokine-produced by activated macrophages and monocytes- and a member of the IL-1 family. The inactive IL-1β precursor is cleaved and activated by caspase-1 enzyme, which itself is activated by the assembly of intracellular structures defined as NLRP3 (Nod Like receptor P3) inflammasomes. Activated IL-1β stimulates the Interleukin-1 receptor type-1 (IL-1R1), which is responsible for the initiation of a signal transduction pathway leading to cell proliferation. It has been proven that the IL-1β gene is a highly polymorphic gene in which single nucleotide polymorphisms (SNPs) may affect its expression. It has been previously reported that SNPs including base transitions between C and T at positions, -511 (C-T; dbSNP: rs16944) and -31 (C-T; dbSNP: rs1143627), from the transcriptional start site, contribute to the pathogenesis of gastric and colorectal cancers by affecting IL-1β levels. Altered production of IL-1β due to such polymorphisms is suspected to stimulate an amplified inflammatory response and promote Epithelial Mesenchymal Transition leading to malignancy. Allele frequency distribution of the IL-1β-31 and -511 SNPs, in different populations, and their correlation to the incidence of gastric and colorectal cancers, has been intriguing to researchers worldwide. The current study aims to investigate allele distributions of the IL-1β SNPs among gastric and colorectal cancers Egyptian patients. In order to achieve to that, 89 Biopsy and surgical specimens from the antrum and corpus mucosa of chronic gastritis subjects and gastric and colorectal carcinoma patients was collected for DNA extraction followed by restriction fragment length polymorphism polymerase chain reaction (RFLP-PCR). The amplified PCR products of IL-1β-31C > T and IL-1β-511T > C were digested by incubation with the restriction endonuclease enzymes ALu1 and Ava1. Statistical analysis was carried out to determine the allele frequency distribution in the three studied groups. Also, the effect of the IL-1β -31 and -511 SNPs on nuclear factor binding was analyzed using Fluorescence Electrophoretic Mobility Shift Assay (EMSA), preceded by nuclear factor extraction from gastric and colorectal tissue samples and LPS stimulated monocytes. The results of this study showed that a significantly higher percentage of Egyptian gastric cancer patients have a homozygous CC genotype at the IL-1β-31 position and a heterozygous TC genotype at the IL-1β-511 position. Moreover, a significantly higher percentage of the colorectal cancer patients have a homozygous CC genotype at the IL-1β-31 and -511 positions as compared to the control group. In addition, the EMSA results showed that IL-1β-31C/T and IL-1β-511T/C SNPs do not affect nuclear factor binding. Results of this study suggest that the IL-1β-31 C/T and IL-1β-511 T/C may be correlated to the incidence of gastric cancer in Egyptian patients; however, similar findings couldn’t be proven in the colorectal cancer patients group for the IL-1β-511 T/C SNP. This is the first study to investigate IL-1β -31 and -511 SNPs in the Egyptian population.

Keywords: colorectal cancer, Egyptian patients, gastric cancer, interleukin-1β, single nucleotide polymorphisms

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Francisco Julio Batle Lorente

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The present paper aims at presenting a new category of role for academia: proactive creator/promoter of communities of practice in emerging areas of innovation. It is based in research among practitioners in three different areas: social entrepreneurship, alumni engaged in entrepreneurship and innovation, and digital nomads. The concept of CoP is related to an intentionally created space to share experiences and collectively reflect on the cases arising from practice. Such an endeavour is not contemplated in the literature on academic roles in an explicit way. The goal of the paper is providing a framework for this function and throw some light on the perception and priorities of members of emerging communities (78 alumni, 154 social entrepreneurs, and 231 digital nomads) regarding community, learning, engagement, and networking, areas in which the university can help and, by doing so, contributing to signal the emerging area and creating new opportunities for the academia. The research methodology was based in Survey research. It is a specific type of field study that involves the collection of data from a sample of elements drawn from a well-defined population through the use of a questionnaire. It was considered that survey research might be valuable to the present project and help outline the utility of various study designs and future projects with the emerging communities that are the object of the investigation. Open questions were used for different topics, as well as critical incident technique. It was used a standard technique for survey sampling and questionnaire design. Finally, it was defined a procedure for pretesting questionnaires and for data collection. The questionnaire was channelled by means of google forms. The results indicate that the members of emerging, innovative CoPs and learning such the ones that were selected for this investigation lack cohesion, inspiration, networking, opportunities for creation of social capital, opportunities for collaboration beyond their existing and close network. The opportunity that arises for the academia from proactively helping articulate CoP (and Communities of learning) are related to key elements of any CoP/ CoL: community construction approaches, technological infrastructure, benefits, participation issues and urgent challenges, trust, networking, technical ability/training/development and collaboration. Beyond training, other three areas (networking, collaboration and urgent challenges) were the ones in which the contribution of universities to the communities were considered more interesting and workable to practitioners. The analysis of the responses for the open questions related to perception of the universities offer options for terra incognita to be explored for universities (signalling new areas, establishing broader collaborations with research, government, media and corporations, attracting investment). Based on the findings from this research, there is some evidence that CoPs can offer a formal and informal method of professional and interprofessional development for member of any emerging and innovative community and can decrease social and professional isolation. The opportunity that it offers to academia can increase the entrepreneurial and engaged university identity. It also moves to academia into a realm of civic confrontation of present and future challenges in a more proactive way.

Keywords: social innovation, new roles of academia, community of learning, community of practice

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Authors: Sabrina S. W. Chan, Emily Schwartzman, Nicholas O. Rule

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Past literature showed mixed findings on how smiling affects a person’s chance of getting hired. On one hand, smiling suggests enthusiasm, cooperativeness, and enthusiasm, which can elicit positive impressions. On the other hand, smiling can suggest weaker professionalism or a filler to hide nervousness, which can lower a candidate’s perceived competence. Emotion expressions can also be perceived differently depending on the person’s gender and can activate certain gender stereotypes. Women especially face a double bind with respect to hiring decisions and smiling. Because women are socially expected to smile more, those who do not smile will be considered stereotype incongruent. This becomes a noisy signal to employers and may lower their chance of being hired. However, women’s smiling as a formality may also be an obstacle. They are more likely to put on fake smiles; but if they do, they are also likely to be perceived as inauthentic and over-expressive. This paper sought to investigate how smiling affects hiring decisions, and whether this relationship is moderated by gender. In Study 1, participants were shown a series of smiling and emotionally neutral face images, incorporated into fabricated LinkedIn profiles. Participants were asked to rate how hireable they thought that candidate was. Results showed that participants rated smiling candidates as more hireable than nonsmiling candidates, and that there was no difference in gender. Moreover, individuals who did not study business were more biased in their perceptions than those who did. Since results showed a trending favoritism over female targets, in suspect of desirability bias, a second study was conducted to collect implicit measures behind the decision-making process. In Study 2, a mouse-tracking design was adopted to explore whether participants’ implicit attitudes were different from their explicit responses on hiring. Participants asked to respond whether they would offer an interview to a candidate. Findings from Study 1 was replicated in that smiling candidates received more offers than neutral-faced candidates. Results also showed that female candidates received significantly more offers than male candidates but was associated with higher attractiveness ratings. There were no significant findings in reaction time or change of decisions. However, stronger hesitation was detected for responses made towards neutral targets when participants perceived the given position as masculine, implying a conscious attempt of making situational judgments (e.g., considering candidate’s personality and job fit) to override automatic processing (evaluations based on attractiveness). Future studies would look at how these findings differ for positions which are stereotypically masculine (e.g., surgeons) and stereotypically feminine (e.g., kindergarten teachers). Current findings have strong implications for developing bias-free hiring policies in workplace, especially for organizations who maintain online/hybrid working arrangements in the post-pandemic era. This also bridges the literature gap between face perception and gender discrimination, highlighting how engendered facial cues can affect individual’s career development and organization’s success in diversity and inclusion.

Keywords: engendered facial cues, face perception, gender stereotypes, hiring decisions, smiling, workplace discrimination

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

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

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

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Authors: Yi-Hao Wong, Li-Li Chan, Chee-Onn Leong, Stephen Ambu, Joon-Wah Mak, Priyasashi Sahu

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Background: Acanthamoeba is a genus of amoebae which lives as a free-living in nature or as a human pathogen that causes severe brain and eye infections. Virulence potential of Acanthamoeba is not constant and can change with growth conditions. DNA methylation, an epigenetic process which adds methyl groups to DNA, is used by eukaryotic cells, including several human parasites to control their gene expression. We used qPCR, siRNA gene silencing, and RNA sequencing (RNA-Seq) to study DNA-methyltransferase gene family (DNMT) in order to indicate the possibility of its involvement in programming Acanthamoeba virulence potential. Methods: A virulence-attenuated Acanthamoeba isolate (designation: ATCC; original isolate: ATCC 50492) was subjected to mouse passages to restore its pathogenicity; a virulence-reactivated isolate (designation: AC/5) was generated. Several established factors associated with Acanthamoeba virulence phenotype were examined to confirm the succession of reactivation process. Differential gene expression of DNMT between ATCC and AC/5 isolates was performed by qPCR. Silencing on DNMT gene expression in AC/5 isolate was achieved by siRNA duplex. Total RNAs extracted from ATCC, AC/5, and siRNA-treated (designation: si-146) were subjected to RNA-Seq for comparative transcriptomic analysis in order to identify the genome-wide effect of DNMT in regulating Acanthamoeba gene expression. qPCR was performed to validate the RNA-Seq results. Results: Physiological and cytophatic assays demonstrated an increased in virulence potential of AC/5 isolate after mouse passages. DNMT gene expression was significantly higher in AC/5 compared to ATCC isolate (p ≤ 0.01) by qPCR. si-146 duplex reduced DNMT gene expression in AC/5 isolate by 30%. Comparative transcriptome analysis identified the differentially expressed genes, with 3768 genes in AC/5 vs ATCC isolate; 2102 genes in si-146 vs AC/5 isolate and 3422 genes in si-146 vs ATCC isolate, respectively (fold-change of ≥ 2 or ≤ 0.5, p-value adjusted (padj) < 0.05). Of these, 840 and 1262 genes were upregulated and downregulated, respectively, in si-146 vs AC/5 isolate. Eukaryotic orthologous group (KOG) assignments revealed a higher percentage of downregulated gene expression in si-146 compared to AC/5 isolate, were related to posttranslational modification, signal transduction and energy production. Gene Ontology (GO) terms for those downregulated genes shown were associated with transport activity, oxidation-reduction process, and metabolic process. Among these downregulated genes were putative genes encoded for heat shock proteins, transporters, ubiquitin-related proteins, proteins for vesicular trafficking (small GTPases), and oxidoreductases. Functional analysis of similar predicted proteins had been described in other parasitic protozoa for their survival and pathogenicity. Decreased expression of these genes in si146-treated isolate may account in part for Acanthamoeba reduced pathogenicity. qPCR on 6 selected genes upregulated in AC/5 compared to ATCC isolate corroborated the RNA sequencing findings, indicating a good concordance between these two analyses. Conclusion: To the best of our knowledge, this study represents the first genome-wide analysis of DNA methylation and its effects on gene expression in Acanthamoeba spp. The present data indicate that DNA methylation has substantial effect on global gene expression, allowing further dissection of the genome-wide effects of DNA-methyltransferase gene in regulating Acanthamoeba pathogenicity.

Keywords: Acanthamoeba, DNA methylation, RNA sequencing, virulence

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Authors: Irina Mizeva, Elena Potapova, Viktor Dremin, Mikhail Mezentsev, Valeri Shupletsov

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The local tissue perfusion is regulated by the microvascular tone which is under the control of a number of physiological mechanisms. Laser Doppler flowmetry (LDF) together with wavelet analyses is the most commonly used technique to study the regulatory mechanisms of cutaneous microcirculation. External factors such as temperature, local pressure of the probe on the skin, etc. influence on the blood flow characteristics and are used as physiological tests to evaluate microvascular regulatory mechanisms. Local probe pressure influences on the microcirculation parameters measured by optical methods: diffuse reflectance spectroscopy, fluorescence spectroscopy, and LDF. Therefore, further study of probe pressure effects can be useful to improve the reliability of optical measurement. During pressure tests variation of the mean perfusion measured by means of LDF usually is estimated. An additional information concerning the physiological mechanisms of the vascular tone regulation system in response to local pressure can be obtained using spectral analyses of LDF samples. The aim of the present work was to develop protocol and algorithm of data processing appropriate for study physiological response to the local pressure test. Involving 6 subjects (20±2 years) and providing 5 measurements for every subject we estimated intersubject and-inter group variability of response of both averaged and oscillating parts of the LDF sample on external surface pressure. The final purpose of the work was to find special features which further can be used in wider clinic studies. The cutaneous perfusion measurements were carried out by LAKK-02 (SPE LAZMA Ltd., Russia), the skin loading was provided by the originally designed device which allows one to distribute the pressure around the LDF probe. The probe was installed on the dorsal part of the distal finger of the index figure. We collected measurements continuously for one hour and varied loading from 0 to 180mmHg stepwise with a step duration of 10 minutes. Further, we post-processed the samples using the wavelet transform and traced the energy of oscillations in five frequency bands over time. Weak loading leads to pressure-induced vasodilation, so one should take into account that the perfusion measured under pressure conditions will be overestimated. On the other hand, we revealed a decrease in endothelial associated fluctuations. Further loading (88 mmHg) induces amplification of pulsations in all frequency bands. We assume that such loading leads to a higher number of closed capillaries, higher input of arterioles in the LDF signal and as a consequence more vivid oscillations which mainly are formed in arterioles. External pressure higher than 144 mmHg leads to the decrease of oscillating components, after removing the loading very rapid restore of the tissue perfusion takes place. In this work, we have demonstrated that local skin loading influence on the microcirculation parameters measured by optic technique; this should be taken into account while developing portable electronic devices. The proposed protocol of local loading allows one to evaluate PIV as far as to trace dynamic of blood flow oscillations. This study was supported by the Russian Science Foundation under project N 18-15-00201.

Keywords: blood microcirculation, laser Doppler flowmetry, pressure-induced vasodilation, wavelet analyses blood

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Authors: Philipp Wenger, Michael Beltle, Stefan Tenbohlen, Uwe Riechert

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The integration of renewable energy introduces new challenges to the transmission grid, as the power generation is located far from load centers. The associated necessary long-range power transmission increases the demand for high voltage direct current (HVDC) transmission lines and DC distribution grids. HVDC gas-insulated switchgears (GIS) are considered being a key technology, due to the combination of the DC technology and the long operation experiences of AC-GIS. To ensure long-term reliability of such systems, insulation defects must be detected in an early stage. Operational experience with AC systems has proven evidence, that most failures, which can be attributed to breakdowns of the insulation system, can be detected and identified via partial discharge (PD) measurements beforehand. In AC systems the identification of defects relies on the phase resolved partial discharge pattern (PRPD). Since there is no phase information within DC systems this method cannot be transferred to DC PD diagnostic. Furthermore, the behaviour of e.g. free-moving particles differs significantly at DC: Under the influence of a constant direct electric field, charge carriers can accumulate on particles’ surfaces. As a result, a particle can lift-off, oscillate between the inner conductor and the enclosure or rapidly bounces at just one electrode, which is known as firefly motion. Depending on the motion and the relative position of the particle to the electrodes, broadband electromagnetic PD pulses are emitted, which can be recorded by ultra-high frequency (UHF) measuring methods. PDs are often accompanied by light emissions at the particle’s tip which enables optical detection. This contribution investigates PD characteristics of free moving metallic particles in a commercially available 300 kV SF6-insulated HVDC-GIS. The influences of various defect parameters on the particle motion and the PD characteristic are evaluated experimentally. Several particle geometries, such as cylinder, lamella, spiral and sphere with different length, diameter and weight are determined. The applied DC voltage is increased stepwise from inception voltage up to UDC = ± 400 kV. Different physical detection methods are used simultaneously in a time-synchronized setup. Firstly, the electromagnetic waves emitted by the particle are recorded by an UHF measuring system. Secondly, a photomultiplier tube (PMT) detects light emission with a wavelength in the range of λ = 185…870 nm. Thirdly, a high-speed camera (HSC) tracks the particle’s motion trajectory with high accuracy. Furthermore, an electrically insulated electrode is attached to the grounded enclosure and connected to a current shunt in order to detect low frequency ion currents: The shunt measuring system’s sensitivity is in the range of 10 nA at a measuring bandwidth of bw = DC…1 MHz. Currents of charge carriers, which are generated at the particle’s tip migrate through the gas gap to the electrode and can be recorded by the current shunt. All recorded PD signals are analyzed in order to identify characteristic properties of different particles. This includes e.g. repetition rates and amplitudes of successive pulses, characteristic frequency ranges and detected signal energy of single PD pulses. Concluding, an advanced understanding of underlying physical phenomena particle motion in direct electric field can be derived.

Keywords: current shunt, free moving particles, high-speed imaging, HVDC-GIS, UHF

Procedia PDF Downloads 132

Authors: Maria João Ferreira, Natalia Sierra-Garcia, Javier Cremades, Carla António, Ana M. Rodrigues, Helena Silva, Ângela Cunha

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Salicornia ramosissima, a halophyte that grows naturally in coastal areas of the northern hemisphere, is often considered the most promising halophyte candidate for extensive crop cultivation and saline agriculture practices. The expanding interest in this plant surpasses its use as gourmet food and includes their potential application as a source of bioactive compounds for the pharmaceutical industry. Despite growing well in saline soils, sustainable and ecologically friendly techniques to enhance crop production and the nutritional value of this plant are still needed. The root microbiome of S. ramosissima proved to be a source of taxonomically diverse plant growth-promoting bacteria (PGPB). Halotolerant strains of Bacillus, Salinicola, Pseudomonas, and Brevibacterium, among other genera, exhibit a broad spectrum of plant-growth promotion traits [e.g., 3-indole acetic acid (IAA), 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase, siderophores, phosphate solubilization, Nitrogen fixation] and express a wide range of extracellular enzyme activities. In this work, three plant growth-promoting bacteria strains (Brevibacterium casei EB3, Pseudomonas oryzihabitans RL18, and Bacillus aryabhattai SP20) isolated from the rhizosphere and the endosphere of S. ramosissima roots from different saltmarshes along the Portuguese coast were inoculated in S. ramosissima seeds. Plants germinated from inoculated seeds were grown for three months in pots filled with a mixture of perlite and estuarine sediment (1:1) in greenhouse conditions and later transferred to a growth chamber, where they were maintained two months with controlled photoperiod, temperature, and humidity. Pots were placed on trays containing the irrigation solution (Hoagland’s solution 20% added with 10‰ marine salt). Before reaching the flowering stage, plants were collected, and the fresh and dry weight of aerial parts was determined. Non-inoculated seeds were used as a negative control. Selected dried stems from the most promising treatments were later analyzed by GC-TOF-MS for primary metabolite composition. The efficiency of inoculation and persistence of the inoculum was assessed by Next Generation Sequencing. Inoculations with single strain EB3 and co-inoculations with EB3+RL18 and EB3+RL18+SP20 (All treatment) resulted in significantly higher biomass production (fresh and dry weight) compared to non-inoculated plants. Considering fresh weight alone, inoculation with isolates SP20 and RL18 also caused a significant positive effect. Combined inoculation with the consortia SP20+EB3 or SP20+RL18 did not significantly improve biomass production. The analysis of the profile of primary metabolites will provide clues on the mechanisms by which the growth-enhancement effect of the inoculants operates in the plants. These results sustain promising prospects for the use of rhizospheric and endophytic PGPB as biofertilizers, reducing environmental impacts and operational costs of agrochemicals and contributing to the sustainability and cost-effectiveness of saline agriculture. Acknowledgments: This work was supported by project Rhizomis PTDC/BIA-MIC/29736/2017 financed by Fundação para a Ciência e Tecnologia (FCT) through the Regional Operational Program of the Center (02/SAICT/2017) with FEDER funds (European Regional Development Fund, FNR, and OE) and by FCT through CESAM (UIDP/50017/2020 + UIDB/50017/2020), LAQV-REQUIMTE (UIDB/50006/2020). We also acknowledge FCT/FSE for the financial support to Maria João Ferreira through a PhD grant (PD/BD/150363/2019). We are grateful to Horta dos Peixinhos for their help and support during sampling and seed collection. We also thank Glória Pinto for her collaboration providing us the use of the growth chambers during the final months of the experiment and Enrique Mateos-Naranjo and Jennifer Mesa-Marín of the Departamento de Biología Vegetal y Ecología, the University of Sevilla for their advice regarding the growth of salicornia plants in greenhouse conditions.

Keywords: halophytes, PGPB, rhizosphere engineering, biofertilizers, primary metabolite profiling, plant inoculation, Salicornia ramosissima

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Authors: Jawaad Saleem, Hannah Wright, Peter Sommerville, Adrian Hopper

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Introduction: Inpatient falls are the most commonly reported patient safety incidents, and carry a significant burden on resources, morbidity, and mortality. Ensuring adequate post falls management of patients by staff is therefore paramount to maintaining patient safety especially in out of hours and resource stretched settings. Aims: This quality improvement project aims to improve the current practice of falls management at Guys St Thomas Hospital, London as compared to our 2016 Quality Improvement Project findings. Furthermore, it looks to increase current junior doctors confidence in managing falls and their use of new guidance protocols. Methods: Multifaceted Interventions implemented included: the development of new trust wide guidelines detailing management pathways for patients post falls, available for intranet access. Furthermore, the production of 2000 lanyard cards distributed amongst junior doctors and staff which summarised these guidelines. Additionally, a ‘safety signal’ email was sent from the Trust chief medical officer to all staff raising awareness of falls and the guidelines. Formal falls teaching was also implemented for new doctors at induction. Using an established incident database, 189 consecutive falls in 2017were retrospectively analysed electronically to assess and compared to the variables measured in 2016 post interventions. A separate serious incident database was used to analyse 50 falls from May 2015 to March 2018 to ascertain the statistical significance of the impact of our interventions on serious incidents. A similar questionnaire for the 2017 cohort of foundation year one (FY1) doctors was performed and compared to 2016 results. Results: Questionnaire data demonstrated improved awareness and utility of guidelines and increased confidence as well as an increase in training. 97% of FY1 trainees felt that the interventions had increased their awareness of the impact of falls on patients in the trust. Data from the incident database demonstrated the time to review patients post fall had decreased from an average of 130 to 86 minutes. Improvement was also demonstrated in the reduced time to order and schedule X-ray and CT imaging, 3 and 5 hours respectively. Data from the serious incident database show that ‘the time from fall until harm was detected’ was statistically significantly lower (P = 0.044) post intervention. We also showed the incidence of significant delays in detecting harm ( > 10 hours) reduced post intervention. Conclusions: Our interventions have helped to significantly reduce the average time to assess, order and schedule appropriate imaging post falls. Delays of over ten hours to detect serious injuries after falls were commonplace; since the intervention, their frequency has markedly reduced. We suggest this will lead to identifying patient harm sooner, reduced clinical incidents relating to falls and thus improve overall patient safety. Our interventions have also helped increase clinical staff confidence, management, and awareness of falls in the trust. Next steps include expanding teaching sessions, improving multidisciplinary team involvement to aid this improvement.

Keywords: patient safety, quality improvement, serious incidents, falls, clinical care

Procedia PDF Downloads 101

Authors: Damien Mouratille, Antonio R. Hidalgo-Muñoz, Nadine Matton, Yves Rouillard, Mickael Causse, Radouane El Yagoubi

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Background: The monitoring of the physiological activity related to mental workload (MW) on pilots will be useful to improve aviation safety by anticipating human performance degradation. The electrocardiogram (ECG) can reveal MW fluctuations due to either cognitive workload or/and emotional state since this measure exhibits autonomic nervous system modulations. Arguably, heart rate (HR) is one of its most intuitive and reliable parameters. It would be particularly interesting to analyze the interaction between cognitive requirements and emotion in ecologic sets such as a flight simulator. This study aims to explore by means of HR the relation between cognitive demands and emotional activation. Presumably, the effects of cognition and emotion overloads are not necessarily cumulative. Methodology: Eight healthy volunteers in possession of the Private Pilot License were recruited (male; 20.8±3.2 years). ECG signal was recorded along the whole experiment by placing two electrodes on the clavicle and left pectoral of the participants. The HR was computed within 4 minutes segments. NASA-TLX and Big Five inventories were used to assess subjective workload and to consider the influence of individual personality differences. The experiment consisted in completing two dual-tasks of approximately 30 minutes of duration into a flight simulator AL50. Each dual-task required the simultaneous accomplishment of both a pre-established flight plan and an additional task based on target stimulus discrimination inserted between Air Traffic Control instructions. This secondary task allowed us to vary the cognitive workload from low (LC) to high (HC) levels, by combining auditory and visual numerical stimuli to respond to meeting specific criteria. Regarding emotional condition, the two dual-tasks were designed to assure analogous difficulty in terms of solicited cognitive demands. The former was realized by the pilot alone, i.e. Low Arousal (LA) condition. In contrast, the latter generates a high arousal (HA), since the pilot was supervised by two evaluators, filmed and involved into a mock competition with the rest of the participants. Results: Performance for the secondary task showed significant faster reaction times (RT) for HA compared to LA condition (p=.003). Moreover, faster RT was found for LC compared to HC (p < .001) condition. No interaction was found. Concerning HR measure, despite the lack of main effects an interaction between emotion and cognition is evidenced (p=.028). Post hoc analysis showed smaller HR for HA compared to LA condition only for LC (p=.049). Conclusion. The control of an aircraft is a very complex task including strong cognitive demands and depends on the emotional state of pilots. According to the behavioral data, the experimental set has permitted to generate satisfactorily different emotional and cognitive levels. As suggested by the interaction found in HR measure, these two factors do not seem to have a cumulative impact on the sympathetic nervous system. Apparently, low cognitive workload makes pilots more sensitive to emotional variations. These results hint the independency between data processing and emotional regulation. Further physiological data are necessary to confirm and disentangle this relation. This procedure may be useful for monitoring objectively pilot’s mental workload.

Keywords: cognitive demands, emotion, flight simulator, heart rate, mental workload

Procedia PDF Downloads 247

Authors: Shuo Li, Yannick Coffinier, Chann Lagadec, Fabrizio Cleri, Katsuhiko Nishiguchi, Akira Fujiwara, Soo Hyeon Kim, Nicolas Clément

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The need for single cell detection and analysis techniques has increased in the past decades because of the heterogeneity of individual living cells, which increases the complexity of the pathogenesis of malignant tumors. In the search for early cancer detection, high-precision medicine and therapy, the technologies most used today for sensitive detection of target analytes and monitoring the variation of these species are mainly including two types. One is based on the identification of molecular differences at the single-cell level, such as flow cytometry, fluorescence-activated cell sorting, next generation proteomics, lipidomic studies, another is based on capturing or detecting single tumor cells from fresh or fixed primary tumors and metastatic tissues, and rare circulating tumors cells (CTCs) from blood or bone marrow, for example, dielectrophoresis technique, microfluidic based microposts chip, electrochemical (EC) approach. Compared to other methods, EC sensors have the merits of easy operation, high sensitivity, and portability. However, despite various demonstrations of low limits of detection (LOD), including aptamer sensors, arrayed EC sensors for detecting single-cell have not been demonstrated. In this work, a new technique based on 20-nm-thick nanopillars array to support cells and keep them at ideal recognition distance for redox-labeled aptamers grafted on the surface. The key advantages of this technology are not only to suppress the false positive signal arising from the pressure exerted by all (including non-target) cells pushing on the aptamers by downward force but also to stabilize the aptamer at the ideal hairpin configuration thanks to a confinement effect. With the first implementation of this technique, a LOD of 13 cells (with5.4 μL of cell suspension) was estimated. In further, the nanosupported cell technology using redox-labeled aptasensors has been pushed forward and fully integrated into a single-cell electrochemical aptasensor array. To reach this goal, the LOD has been reduced by more than one order of magnitude by suppressing parasitic capacitive electrochemical signals by minimizing the sensor area and localizing the cells. Statistical analysis at the single-cell level is demonstrated for the recognition of cancer cells. The future of this technology is discussed, and the potential for scaling over millions of electrodes, thus pushing further integration at sub-cellular level, is highlighted. Despite several demonstrations of electrochemical devices with LOD of 1 cell/mL, the implementation of single-cell bioelectrochemical sensor arrays has remained elusive due to their challenging implementation at a large scale. Here, the introduced nanopillar array technology combined with redox-labeled aptamers targeting epithelial cell adhesion molecule (EpCAM) is perfectly suited for such implementation. Combining nanopillar arrays with microwells determined for single cell trapping directly on the sensor surface, single target cells are successfully detected and analyzed. This first implementation of a single-cell electrochemical aptasensor array based on Brownian-fluctuating redox species opens new opportunities for large-scale implementation and statistical analysis of early cancer diagnosis and cancer therapy in clinical settings.

Keywords: bioelectrochemistry, aptasensors, single-cell, nanopillars

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Authors: Paul Licina, Emma M. Johnston, David Lisle, Mark Young, Chris Brady

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Background: Lumbar pars pathology is a common cause of pain in the growing spine. It can be seen in young athletes participating in at-risk sports and can affect sporting performance and long-term health due to its resistance to traditional management. There is a current lack of consensus of classification and treatment for pars injuries. Previous systems used CT to stage pars defects but could not assess early stress reactions. A modified classification is proposed that considers findings on MRI, significantly improving early treatment guidance. The treatment protocol is designed for patients aged 5 to 19 years. Method: Clinical screening identifies patients with a low, medium, or high index of suspicion for lumbar pars injury using patient age, sport participation and pain characteristics. MRI of the at-risk cohort enables augmentation of existing CT-based classification while avoiding ionising radiation. Patients are classified into five categories based on MRI findings. A type 0 lesion (stress reaction) is present when CT is normal and MRI shows high signal change (HSC) in the pars/pedicle on T2 images. A type 1 lesion represents the ‘early defect’ CT classification. The group previously referred to as a 'progressive stage' defect on CT can be split into 2A and 2B categories. 2As have HSC on MRI, whereas 2Bs do not. This distinction is important with regard to healing potential. Type 3 lesions are terminal stage defects on CT, characterised by pseudarthrosis. MRI shows no HSC. Results: Stress reactions (type 0) and acute fractures (1 and 2a) can heal and are treated in a custom-made hard brace for 12 weeks. It is initially worn 23 hours per day. At three weeks, patients commence basic core rehabilitation. At six weeks, in the absence of pain, the brace is removed for sleeping. Exercises are progressed to positions of daily living. Patients with continued pain remain braced 23 hours per day without exercise progression until becoming symptom-free. At nine weeks, patients commence supervised exercises out of the brace for 30 minutes each day. This allows them to re-learn muscular control without rigid support of the brace. At 12 weeks, bracing ceases and MRI is repeated. For patients with near or complete resolution of bony oedema and healing of any cortical defect, rehabilitation is focused on strength and conditioning and sport-specific exercise for the full return to activity. The length of this final stage is approximately nine weeks but depends on factors such as development and level of sports participation. If significant HSC remains on MRI, CT scan is considered to definitively assess cortical defect healing. For these patients, return to high-risk sports is delayed for up to three months. Chronic defects (2b and 3) cannot heal and are not braced, and rehabilitation follows traditional protocols. Conclusion: Appropriate clinical screening and imaging with MRI can identify pars pathology early. In those with potential for healing, we propose hard bracing and appropriate rehabilitation as part of a multidisciplinary management protocol. The validity of this protocol will be tested in future studies.

Keywords: adolescents, MRI classification, pars interticularis, treatment protocol

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Authors: Marco Frieslaar, Bing Chu, Eric Rogers

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Stroke is a devastating illness that is the second biggest cause of death in the world (after heart disease). Where it does not kill, it leaves survivors with debilitating sensory and physical impairments that not only seriously harm their quality of life, but also cause a high incidence of severe depression. It is widely accepted that early intervention is essential for recovery, but current rehabilitation techniques largely favor hospital-based therapies which have restricted access, expensive and specialist equipment and tend to side-step the emotional challenges. In addition, there is insufficient funding available to provide the long-term assistance that is required. As a consequence, recovery rates are poor. The relatively unexplored solution is to develop therapies that can be harnessed in the home and are formulated from technologies that already exist in everyday life. This would empower individuals to take control of their own improvement and provide choice in terms of when and where they feel best able to undertake their own healing. This research seeks to identify how effective post-stroke, rehabilitation therapy can be applied to upper limb mobility, within the physical context of a home rather than a hospital. This is being achieved through the design and construction of an automation scheme, based on iterative learning control and the Riener muscle model, that has the ability to adapt to the user and react to their level of fatigue and provide tangible physical recovery. It utilizes a SMART Phone and laptop to construct an iterative learning control (ILC) system, that monitors upper arm movement in three dimensions, as a series of exercises are undertaken. The equipment generates functional electrical stimulation to assist in muscle activation and thus improve directional accuracy. In addition, it monitors speed, accuracy, areas of motion weakness and similar parameters to create a performance index that can be compared over time and extrapolated to establish an independent and objective assessment scheme, plus an approximate estimation of predicted final outcome. To further extend its assessment capabilities, nerve conduction velocity readings are taken by the software, between the shoulder and hand muscles. This is utilized to measure the speed of response of neuron signal transfer along the arm and over time, an online indication of regeneration levels can be obtained. This will prove whether or not sufficient training intensity is being achieved even before perceivable movement dexterity is observed. The device also provides the option to connect to other users, via the internet, so that the patient can avoid feelings of isolation and can undertake movement exercises together with others in a similar position. This should create benefits not only for the encouragement of rehabilitation participation, but also an emotional support network potential. It is intended that this approach will extend the availability of stroke recovery options, enable ease of access at a low cost, reduce susceptibility to depression and through these endeavors, enhance the overall recovery success rate.

Keywords: home-based therapy, iterative learning control, Riener muscle model, SMART phone, stroke rehabilitation

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Authors: Anita Conti, Riccardo Ossanna, Lindsey A. Quintero, Giamaica Conti, Andrea Sbarbati

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Ischemia/reperfusion (IR) injury induces muscle fiber atrophy and skeletal muscle fiber death with subsequently functionality loss. The heterogeneous pool of cells, especially mesenchymal stem cells, contained in the stromal vascular fraction (SVF) of adipose tissue could promote muscle fiber regeneration. To prevent SVF dispersion, it has been proposed the use of injectable biopolymers that work as cells carrier. A significant element of the extracellular matrix is hyaluronic acid (HA), which has been widely used in regenerative medicine as a cell scaffold given its biocompatibility, degradability, and the possibility of chemical functionalization. Connective tissue micro-fragments enriched with SVF obtained from mechanical disaggregation of adipose tissue were evaluated for IR muscle injury regeneration using low molecular weight HA as a scaffold. IR induction. Hindlimb ischemia was induced in 9 athymic nude mice through the clamping of the right quadriceps using a plastic band. Reperfusion was induced by cutting the plastic band after 3 hours of ischemic period. Contralateral (left) muscular tissue was used as healthy control. Treatment. Twenty-four hours after the IR induction, animals (n=3) were intramuscularly injected with 100 µl of SVF mixed with HA (SVF-HA). Animals treated with 100 µl of HA (n=3) and 100 µl saline solution (n=3) were used as control. Treatment monitoring. All animals were in vivo monitored by magnetic resonance imaging (MRI) at 5, 7, 14 and 18 days post-injury (dpi). High-resolution morphological T2 weighed, quantitative T2 map and Dynamic Contrast-Enhanced (DCE) images were acquired in order to assess the regenerative potential of SVF-HA treatment. Ex vivo evaluation. After 18 days from IR induction, animals were sacrificed, and the muscles were harvested for histological examination. At 5 dpi T2 high-resolution MR images clearly reveal the presence of an extensive edematous area due to IR damage for all groups identifiable as an increase of signal intensity (SI) of muscular and surrounding tissue. At 7 dpi, animals of the SVF-HA group showed a reduction of SI, and the T2relaxation time of muscle tissue of the HA-SVF group was 29±0.5ms, comparable with the T2relaxation time of contralateral muscular tissue (30±0.7ms). These suggest a reduction of edematous overflow and swelling. The T2relaxation time at 7dpi of HA and saline groups were 84±2ms and 90±5ms, respectively, which remained elevated during the rest of the study. The evaluation of vascular regeneration showed similar results. Indeed, DCE-MRI analysis revealed a complete recovery of muscular tissue perfusion after 14 dpi for the SVF-HA group, while for the saline and HA group, controls remained in a damaged state. Finally, the histological examination of SVF-HA treated animals exhibited well-defined and organized fibers morphology with a lateralized nucleus, similar to contralateral healthy muscular tissue. On the contrary, HA and saline-treated animals presented inflammatory infiltrates, with HA slightly improving the diameter of the fibers and less degenerated tissue. Our findings show that connective tissue micro-fragments enriched with SVF induce higher muscle homeostasis and perfusion restoration in contrast to control groups.

Keywords: ischemia/reperfusion injury, regenerative medicine, resonance imaging, stromal vascular fraction

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Authors: Judy M. Obliosca, Olivia Vest, Sandra Poulos, Kelsi Smith, Tammy Ferguson, Abigail Powers Lott, Alicia K. Smith, Yang Xu, Christopher K. Tison

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Post-Traumatic Stress Disorder (PTSD) is a mental health problem that people may develop after experiencing traumatic events such as combat, natural disasters, and major emotional challenges. Tragically, the number of military personnel with PTSD correlates directly with the number of veterans who attempt suicide, with the highest rate in the Army. Research has shown epigenetic risks in those who are prone to several psychiatric dysfunctions, particularly PTSD. Once initiated in response to trauma, epigenetic alterations in particular, the DNA methylation in the form of 5-methylcytosine (5mC) alters chromatin structure and represses gene expression. Current methods to detect DNA methylation, such as bisulfite-based genomic sequencing techniques, are laborious and have massive analysis workflow while still having high error rates. A faster and simpler detection method of high sensitivity and precision would be useful in a clinical setting to confirm potential PTSD etiologies, prevent other psychiatric disorders, and improve military health. A nano-enhanced Surface Plasmon Resonance imaging (SPRi)-based assay that simultaneously detects site-specific 5mC base (termed as PTSD base) in methylated genes related to PTSD is being developed. The arrays on a sensing chip were first constructed for parallel detection of PTSD bases using synthetic and genomic DNA (gDNA) samples. For the gDNA sample extracted from the whole blood of a PTSD patient, the sample was first digested using specific restriction enzymes, and fragments were denatured to obtain single-stranded methylated target genes (ssDNA). The resulting mixture of ssDNA was then injected into the assay platform, where targets were captured by specific DNA aptamer probes previously immobilized on the surface of a sensing chip. The PTSD bases in targets were detected by anti-5-methylcytosine antibody (anti-5mC), and the resulting signals were then enhanced by the universal nanoenhancer. Preliminary results showed successful detection of a PTSD base in a gDNA sample. Brighter spot images and higher delta values (control-subtracted reflectivity signal) relative to those of the control were observed. We also implemented the in-house surface activation system for detection and developed SPRi disposable chips. Multiplexed PTSD base detection of target methylated genes in blood DNA from PTSD patients of severity conditions (asymptomatic and severe) was conducted. This diagnostic capability being developed is a platform technology, and upon successful implementation for PTSD, it could be reconfigured for the study of a wide variety of neurological disorders such as traumatic brain injury, Alzheimer’s disease, schizophrenia, and Huntington's disease and can be extended to the analyses of other sample matrices such as urine and saliva.

Keywords: epigenetic assay, DNA methylation, PTSD, whole blood, multiplexing

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Authors: Thanthrige Thiunuwan Priyathilaka, Don Anushka Sandaruwan Elvitigala, Bong-Soo Lim, Hyung-Bok Jeong, Jehee Lee

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Toll like receptors (TLRs) are a phylogeneticaly conserved family of pattern recognition receptors, which participates in the host immune responses against various pathogens and pathogen derived mitogen. TLR21, a non-mammalian type, is almost restricted to the fish species even though those can be identified rarely in avians and amphibians. Herein, this study was carried out to identify and characterize TLR21 from rock bream (Oplegnathus fasciatus) designated as RbTLR21, at transcriptional and genomic level. In this study, the full length cDNA and genomic sequence of RbTLR21 was identified using previously constructed cDNA sequence database and BAC library, respectively. Identified RbTLR21 sequence was characterized using several bioinformatics tools. The quantitative real time PCR (qPCR) experiment was conducted to determine tissue specific expressional distribution of RbTLR21. Further, transcriptional modulation of RbTLR21 upon the stimulation with Streptococcus iniae (S. iniae), rock bream iridovirus (RBIV) and Edwardsiella tarda (E. tarda) was analyzed in spleen tissues. The complete coding sequence of RbTLR21 was 2919 bp in length which can encode a protein consisting of 973 amino acid residues with molecular mass of 112 kDa and theoretical isoelectric point of 8.6. The anticipated protein sequence resembled a typical TLR domain architecture including C-terminal ectodomain with 16 leucine rich repeats, a transmembrane domain, cytoplasmic TIR domain and signal peptide with 23 amino acid residues. Moreover, protein folding pattern prediction of RbTLR21 exhibited well-structured and folded ectodomain, transmembrane domain and cytoplasmc TIR domain. According to the pair wise sequence analysis data, RbTLR21 showed closest homology with orange-spotted grouper (Epinephelus coioides) TLR21with 76.9% amino acid identity. Furthermore, our phylogenetic analysis revealed that RbTLR21 shows a close evolutionary relationship with its ortholog from Danio rerio. Genomic structure of RbTLR21 consisted of single exon similar to its ortholog of zebra fish. Sevaral putative transcription factor binding sites were also identified in 5ʹ flanking region of RbTLR21. The RBTLR 21 was ubiquitously expressed in all the tissues we tested. Relatively, high expression levels were found in spleen, liver and blood tissues. Upon induction with rock bream iridovirus, RbTLR21 expression was upregulated at the early phase of post induction period even though RbTLR21 expression level was fluctuated at the latter phase of post induction period. Post Edwardsiella tarda injection, RbTLR transcripts were upregulated throughout the experiment. Similarly, Streptococcus iniae induction exhibited significant upregulations of RbTLR21 mRNA expression in the spleen tissues. Collectively, our findings suggest that RbTLR21 is indeed a homolog of TLR21 family members and RbTLR21 may be involved in host immune responses against bacterial and DNA viral infections.

Keywords: rock bream, toll like receptor 21 (TLR21), pattern recognition receptor, genomic characterization

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Authors: Komal K., Cleary F., Wells J S.G., Bennett L

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Smart fabric garments enable various monitoring applications across sectors such as healthcare, sports and fitness, and the military. Healthcare smart garments monitoring EEG, EMG, and ECG rely on the use of electrodes (dry or wet). However, such electrodes, when used for long-term monitoring, can cause discomfort and skin irritation for the wearer because of their inflexible structure and weight. Ongoing research has been investigating textile-based electrodes (textrodes) in order to provide more comfortable and usable fabric-based electrodes capable of providing intuitive biopotential monitoring. Progress has been made in this space, but they still face a critical design challenge in maintaining consistent skin contact, which directly impacts signal quality. Furthermore, there is a lack of an ISO-based testing framework to validate the electrode design and assess its ability to achieve enhanced performance, strength, usability, and durability. This study proposes the development and evaluation of an ISO-compliant testing framework for standard 2D and advanced 3D embroidered textrodes designs that have a unique structure in order to establish enhanced skin contact for the wearer. This testing framework leverages ISO standards: ISO 13934-1:2013 for tensile and zone-wise strength tests; ISO 13937-2 for tear tests; and ISO 6330 for washing, validating the textrode's performance, a necessity for wearables health parameter monitoring applications. Five textrodes (C1-C5) were designed using EPC win digitization software. Varying patterns such as running stitches, lock stitches, back-to-back stitches, and moss stitches were used to create various embroidered tetrodes samples using Madeira HC12 conductive thread with a resistivity of 100 ohm/m. The textrode designs were then fabricated using a ZSK technical embroidery machine. A comparative analysis was conducted based on a series of laboratory tests adhering to ISO compliance requirements. Tests focusing on the application of strain were applied to the textrodes, and these included: (1) analysis of the electrode's overall surface area strength; (2) assessment of the robustness of the textrodes boundaries; and (3) the assignment of fault test zones to each textrode, where vertical and horizontal slits of 3mm were applied to evaluate the performance of textrodes and its durability. Specific ISO-compliant tests linked to washing were conducted multiple times on each textrode sample to assess both mechanical and chemical damage. Additionally, abrasion and pilling tests were performed to evaluate mechanical damage on the surface of the textrodes and to compare it with the washing test. Finally, the textrodes were assessed based on morphological and surface resistance changes. Results demonstrate that textrode C4, featuring a 3-D layered structure consisting of foam, fabric, and conductive thread layers, significantly enhances skin-electrode contact for biopotential recording. The inclusion of a 3D foam layer was particularly effective in maintaining the shape of the electrode during strain tests, making it the top-performing textrode sample. Therefore, the layered 3D design structure of textrode C4 ranks highest when tested for durability, reusability, and washability. The ISO testing framework established in this study will support future research, validating the durability and reliability of textrodes for a wide range of applications.

Keywords: smart fabric, textrodes, testing framework, ISO compliant

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Authors: Vishal Kumar, Soumitra Satapathi

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Föster Resonance Energy Transfer (FRET) is a powerful technique used to probe close-range molecular interactions. Physically, the FRET phenomenon manifests as a dipole–dipole interaction between closely juxtaposed fluorescent molecules (10–100 Å). Our effort is to employ this FRET technique to make a prototype device for highly sensitive detection of environment pollutant. Among the most common environmental pollutants, nitroaromatic compounds (NACs) are of particular interest because of their durability and toxicity. That’s why, sensitive and selective detection of small amounts of nitroaromatic explosives, in particular, 2,4,6-trinitrophenol (TNP), 2,4-dinitrotoluene (DNT) and 2,4,6-trinitrotoluene (TNT) has been a critical challenge due to the increasing threat of explosive-based terrorism and the need of environmental monitoring of drinking and waste water. In addition, the excessive utilization of TNP in several other areas such as burn ointment, pesticides, glass and the leather industry resulted in environmental accumulation, and is eventually contaminating the soil and aquatic systems. To the date, high number of elegant methods, including fluorimetry, gas chromatography, mass, ion-mobility and Raman spectrometry have been successfully applied for explosive detection. Among these efforts, fluorescence-quenching methods based on the mechanism of FRET show good assembly flexibility, high selectivity and sensitivity. Here, we report a FRET-based sensor system for the highly selective detection of NACs, such as TNP, DNT and TNT. The sensor system is composed of a copolymer Poly [(N,N-dimethylacrylamide)-co-(Boc-Trp-EMA)] (RP) bearing tryptophan derivative in the side chain as donor and dansyl tagged copolymer P(MMA-co-Dansyl-Ala-HEMA) (DCP) as an acceptor. Initially, the inherent fluorescence of RP copolymer is quenched by non-radiative energy transfer to DCP which only happens once the two molecules are within Förster critical distance (R0). The excellent spectral overlap (Jλ= 6.08×10¹⁴ nm⁴M⁻¹cm⁻¹) between donors’ (RP) emission profile and acceptors’ (DCP) absorption profile makes them an exciting and efficient FRET pair i.e. further confirmed by the high rate of energy transfer from RP to DCP i.e. 0.87 ns⁻¹ and lifetime measurement by time correlated single photon counting (TCSPC) to validate the 64% FRET efficiency. This FRET pair exhibited a specific fluorescence response to NACs such as DNT, TNT and TNP with 5.4, 2.3 and 0.4 µM LODs, respectively. The detection of NACs occurs with high sensitivity by photoluminescence quenching of FRET signal induced by photo-induced electron transfer (PET) from electron-rich FRET pair to electron-deficient NAC molecules. The estimated stern-volmer constant (KSV) values for DNT, TNT and TNP are 6.9 × 10³, 7.0 × 10³ and 1.6 × 104 M⁻¹, respectively. The mechanistic details of molecular interactions are established by time-resolved fluorescence, steady-state fluorescence and absorption spectroscopy confirmed that the sensing process is of mixed type, i.e. both dynamic and static quenching as lifetime of FRET system (0.73 ns) is reduced to 0.55, 0.57 and 0.61 ns DNT, TNT and TNP, respectively. In summary, the simplicity and sensitivity of this novel FRET sensor opens up the possibility of designing optical sensor of various NACs in one single platform for developing multimodal sensor for environmental monitoring and future field based study.

Keywords: FRET, nitroaromatic, stern-Volmer constant, tryptophan and dansyl tagged copolymer

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Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

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This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

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Authors: Adriana Muñoz-Talavera, Ana Rosa Rincón-Sánchez, Abraham Escobedo-Moratilla, María Cristina Islas-Carbajal, Miguel Ángel Gómez-Lim

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The highest rates of diabetes incidence and prevalence worldwide will increase the number of diabetic patients requiring insulin or insulin analogues. Then, current production systems would not be sufficient to meet the future market demands. Therefore, developing efficient expression systems for insulin and insulin analogues are needed. In addition, insulin analogues with better pharmacokinetics and pharmacodynamics properties and without mitogenic potential will be required. SCI-57 (single chain insulin-57) is an insulin analogue having 10 times greater affinity to the insulin receptor, higher resistance to thermal degradation than insulin, native mitogenicity and biological effect. Plants as expression platforms have been used to produce recombinant proteins because of their advantages such as cost-effectiveness, posttranslational modifications, absence of human pathogens and high quality. Immunoglobulin production with a yield of 50% has been achieved by transient expression in Nicotiana benthamiana (Nb). The aim of this study is to produce SCI-57 by transient expression in Nb. Methodology: DNA sequence encoding SCI-57 was cloned in pICH31070. This construction was introduced into Agrobacterium tumefaciens by electroporation. The resulting strain was used to infiltrate leaves of Nb. In order to isolate SCI-57, leaves from transformed plants were incubated 3 hours with the extraction buffer therefore filtrated to remove solid material. The resultant protein solution was subjected to anion exchange chromatography on an FPLC system and ultrafiltration to purify SCI-57. Detection of SCI-57 was made by electrophoresis pattern (SDS-PAGE). Protein band was digested with trypsin and the peptides were analyzed by Liquid chromatography tandem-mass spectrometry (LC-MS/MS). A purified protein sample (20µM) was analyzed by ESI-Q-TOF-MS to obtain the ionization pattern and the exact molecular weight determination. Chromatography pattern and impurities detection were performed using RP-HPLC using recombinant insulin as standard. The identity of the SCI-57 was confirmed by anti-insulin ELISA. The total soluble protein concentration was quantified by Bradford assay. Results: The expression cassette was verified by restriction mapping (5393 bp fragment). The SDS-PAGE of crude leaf extract (CLE) of transformed plants, revealed a protein of about 6.4 kDa, non-present in CLE of untransformed plants. The LC-MS/MS results displayed one peptide with a high score that matches SCI-57 amino acid sequence in the sample, confirming the identity of SCI-57. From the purified SCI-57 sample (PSCI-57) the most intense charge state was 1069 m/z (+6) on the displayed ionization pattern corresponding to the molecular weight of SCI-57 (6412.6554 Da). The RP-HPLC of the PSCI-57 shows the presence of a peak with similar retention time (rt) and UV spectroscopic profile to the insulin standard (SCI-57 rt=12.96 and insulin rt=12.70 min). The collected SCI-57 peak had ELISA signal. The total protein amount in CLE from transformed plants was higher compared to untransformed plants. Conclusions: Our results suggest the feasibility to produce insulin analogue SCI-57 by transient expression in Nicotiana benthamiana. Further work is being undertaken to evaluate the biological activity by glucose uptake by insulin-sensitive and insulin-resistant murine and human cultured adipocytes.

Keywords: insulin analogue, mass spectrometry, Nicotiana benthamiana, transient expression

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Authors: Wonil Nam, Xiang Ren, Inyoung Kim, Masoud Agah, Wei Zhou

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Despite its ultrasensitive detection capability, surface-enhanced Raman spectroscopy (SERS) faces challenges as a quantitative biochemical analysis tool due to the significant dependence of local field intensity in hotspots on nanoscale geometric variations of plasmonic nanostructures. Therefore, despite enormous progress in plasmonic nanoengineering of high-performance SERS devices, it is still challenging to quantitatively correlate the measured SERS signals with the actual molecule concentrations at hotspots. A significant effort has been devoted to developing SERS calibration methods by introducing internal standards. It has been achieved by placing Raman tags at plasmonic hotspots. Raman tags undergo similar SERS enhancement at the same hotspots, and ratiometric SERS signals for analytes of interest can be generated with reduced dependence on geometrical variations. However, using Raman tags still faces challenges for real-world applications, including spatial competition between the analyte and tags in hotspots, spectral interference, laser-induced degradation/desorption due to plasmon-enhanced photochemical/photothermal effects. We show that electronic Raman scattering (ERS) signals from metallic nanostructures at hotspots can serve as the internal calibration standard to enable quantitative SERS analysis and improve biostatistical analysis. We perform SERS with Au-SiO₂ multilayered metal-insulator-metal nano laminated plasmonic nanostructures. Since the ERS signal is proportional to the volume density of electron-hole occupation in hotspots, the ERS signals exponentially increase when the wavenumber is approaching the zero value. By a long-pass filter, generally used in backscattered SERS configurations, to chop the ERS background continuum, we can observe an ERS pseudo-peak, IERS. Both ERS and SERS processes experience the |E|⁴ local enhancements during the excitation and inelastic scattering transitions. We calibrated IMRS of 10 μM Rhodamine 6G in solution by IERS. The results show that ERS calibration generates a new analytical value, ISERS/IERS, insensitive to variations from different hotspots and thus can quantitatively reflect the molecular concentration information. Given the calibration capability of ERS signals, we performed label-free SERS analysis of living biological systems using four different breast normal and cancer cell lines cultured on nano-laminated SERS devices. 2D Raman mapping over 100 μm × 100 μm, containing several cells, was conducted. The SERS spectra were subsequently analyzed by multivariate analysis using partial least square discriminant analysis. Remarkably, after ERS calibration, MCF-10A and MCF-7 cells are further separated while the two triple-negative breast cancer cells (MDA-MB-231 and HCC-1806) are more overlapped, in good agreement with the well-known cancer categorization regarding the degree of malignancy. To assess the strength of ERS calibration, we further carried out a drug efficacy study using MDA-MB-231 and different concentrations of anti-cancer drug paclitaxel (PTX). After ERS calibration, we can more clearly segregate the control/low-dosage groups (0 and 1.5 nM), the middle-dosage group (5 nM), and the group treated with half-maximal inhibitory concentration (IC50, 15 nM). Therefore, we envision that ERS calibrated SERS can find crucial opportunities in label-free molecular profiling of complicated biological systems.

Keywords: cancer cell drug efficacy, plasmonics, surface-enhanced Raman spectroscopy (SERS), SERS calibration

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Authors: Meena Agrawal, Chaitanya P. Agrawal

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The power systems are transforming and becoming smarter with innovations in technologies to enable embark simultaneously upon the sustainable energy needs, rising environmental concerns, economic benefits and quality requirements. The advantages provided by inter-connection of renewable energy resources are becoming more viable and dependable with the smart controlling technologies. The limitation of most renewable resources have their diversity and intermittency causing problems in power quality, grid stability, reliability, security etc. is being cured by these efforts. A necessitate of optimal energy management by intelligent Micro-Grids at the distribution end of the power system has been accredited to accommodate sustainable renewable Distributed Energy Resources on large scale across the power grid. All over the world Smart Grids are emerging now as foremost concern infrastructure upgrade programs. The hardware setup includes NI cRIO 9022, Compact Reconfigurable Input Output microcontroller board connected to the PC on a LAN router with three hardware modules. The Real-Time Embedded Controller is reconfigurable controller device consisting of an embedded real-time processor controller for communication and processing, a reconfigurable chassis housing the user-programmable FPGA, Eight hot-swappable I/O modules, and graphical LabVIEW system design software. It has been employed for signal analysis, controls and acquisition and logging of the renewable sources with the LabVIEW Real-Time applications. The employed cRIO chassis controls the timing for the module and handles communication with the PC over the USB, Ethernet, or 802.11 Wi-Fi buses. It combines modular I/O, real-time processing, and NI LabVIEW programmable. In the presented setup, the Analog Input Module NI 9205 five channels have been used for input analog voltage signals from renewable energy sources and NI 9227 four channels have been used for input analog current signals of the renewable sources. For switching actions based on the programming logic developed in software, a module having Electromechanical Relays (single-pole single throw) with 4-Channels, electrically isolated and LED indicating the state of that channel have been used for isolating the renewable Sources on fault occurrence, which is decided by the logic in the program. The module for Ethernet based Data Acquisition Interface ENET 9163 Ethernet Carrier, which is connected on the LAN Router for data acquisition from a remote source over Ethernet also has the module NI 9229 installed. The LabVIEW platform has been employed for efficient data acquisition, monitoring and control. Control logic utilized in program for operation of the hardware switching Related to Fault Relays has been portrayed as a flowchart. A communication system has been successfully developed amongst the sources and loads connected on different computers using Hypertext transfer protocol, HTTP or Ethernet Local Stacked area Network TCP/IP protocol. There are two main I/O interfacing clients controlling the operation of the switching control of the renewable energy sources over internet or intranet. The paper presents experimental results of the briefed setup for intelligent control of the micro-grid for renewable energy sources, besides the control of Micro-Grid with data acquisition and control hardware based on a microcontroller with visual program developed in LabVIEW.

Keywords: data acquisition and control, LabVIEW, microcontroller cRIO, Smart Micro-Grid

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Authors: Katarzyna Lubecka, Kirsty Flower, Megan Beetch, Lucinda Kurzava, Hannah Buvala, Samer Gawrieh, Suthat Liangpunsakul, Tracy Gonzalez, George McCabe, Naga Chalasani, James M. Flanagan, Barbara Stefanska

Abstract:

Hepatocellular carcinoma (HCC), the most prevalent type of primary liver cancer, is the second leading cause of cancer death worldwide. Late onset of clinical symptoms in HCC results in late diagnosis and poor disease outcome. Approximately 85% of individuals with HCC have underlying liver cirrhosis. However, not all cirrhotic patients develop cancer. Reliable early detection biomarkers that can distinguish cirrhotic patients who will develop cancer from those who will not are urgently needed and could increase the cure rate from 5% to 80%. We used Illumina-450K microarray to test whether blood DNA, an easily accessible source of DNA, bear site-specific changes in DNA methylation in response to HCC before diagnosis with conventional tools (pre-diagnostic). Top 11 differentially methylated sites were selected for validation by pyrosequencing. The diagnostic potential of the 11 pyrosequenced probes was tested in blood samples from a prospective cohort of cirrhotic patients. We identified 971 differentially methylated CpG sites in pre-diagnostic HCC cases as compared with healthy controls (P < 0.05, paired Wilcoxon test, ICC ≥ 0.5). Nearly 76% of differentially methylated CpG sites showed lower levels of methylation in cases vs. controls (P = 2.973E-11, Wilcoxon test). Classification of the CpG sites according to their location relative to CpG islands and transcription start site revealed that those hypomethylated loci are located in regulatory regions important for gene transcription such as CpG island shores, promoters, and 5’UTR at higher frequency than hypermethylated sites. Among 735 CpG sites hypomethylated in cases vs. controls, 482 sites were assigned to gene coding regions whereas 236 hypermethylated sites corresponded to 160 genes. Bioinformatics analysis using GO, KEGG and DAVID knowledgebase indicate that differentially methylated CpG sites are located in genes associated with functions that are essential for gene transcription, cell adhesion, cell migration, and regulation of signal transduction pathways. Taking into account the magnitude of the difference, statistical significance, location, and consistency across the majority of matched pairs case-control, we selected 11 CpG loci corresponding to 10 genes for further validation by pyrosequencing. We established that methylation of CpG sites within 5 out of those 10 genes distinguish cirrhotic patients who subsequently developed HCC from those who stayed cancer free (cirrhotic controls), demonstrating potential as biomarkers of early detection in populations at risk. The best predictive value was detected for CpGs located within BARD1 (AUC=0.70, asymptotic significance ˂0.01). Using an additive logistic regression model, we further showed that 9 CpG loci within those 5 genes, that were covered in pyrosequenced probes, constitute a panel with high diagnostic accuracy (AUC=0.887; 95% CI:0.80-0.98). The panel was able to distinguish pre-diagnostic cases from cirrhotic controls free of cancer with 88% sensitivity at 70% specificity. Using blood as a minimally invasive material and pyrosequencing as a straightforward quantitative method, the established biomarker panel has high potential to be developed into a routine clinical test after validation in larger cohorts. This study was supported by Showalter Trust, American Cancer Society (IRG#14-190-56), and Purdue Center for Cancer Research (P30 CA023168) granted to BS.

Keywords: biomarker, DNA methylation, early detection, hepatocellular carcinoma

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