Proper Signal Research Articles

Issue Cover (April 2021)

Journal of NeurochemistryVolume 157, Issue 2 Issue CoverFree Access Issue Cover (April 2021) First published: 17 April 2021 https://doi.org/10.1111/jnc.15060 Read the full article: ‘Preface to the Special Issue “Presynaptic Dysfunction and Diseaseˮ ’ K. J. Smillie, M. A. Cousin, S. L. Gordon (J. Neurochem. 2021, vol. 157 (2), pp. 102–106) on doi:10.1111/jnc.15319 AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Graphical Abstract Front cover: The fundamental principle underlying brain communication is the tightly controlled release of chemical neurotransmitter in response to action potential stimulation. Neurotransmitter release occurs at presynaptic terminals. Proper presynaptic function is therefore critical for proper signal transduction, and dysfunction can cause pathophysiology. The current special issue presents summaries and updates on relevant aspects of presynaptic (dys-)function in healthy homeostatis and disease. Image Content: Depicted are primary cultures of hippocampal neurons that have been transduced with a EGFP (green) expressing virus and then immunolabelled with both vGLUT (magenta) and PSD95 (cyan) to mark presynaptic and postsynaptic sites respectively. Read the full article ‘Preface to the Special Issue “Presynaptic Dysfunction and Diseaseˮ ’ K. J. Smillie, M. A. Cousin, S. L. Gordon (J. Neurochem. 2021, vol. 157 (2), pp. 102–106) on doi:10.1111/jnc.15319 Volume157, Issue2Special Issue: Presynaptic DysfunctionApril 2021 RelatedInformation

ANALISA KOORDINASI SINYAL ANTAR SIMPANG PADA RUAS JALAN RADEN PANJI SUROSO KOTA MALANG

There are two adjacent intersections on Jl. Raden Panji Suroso get stopped at two intersections. It is a need to provide a proper traffic signal coordination aiming at improving the performance of those two intersections and managing the vehicle operating cost efficiently. The data were taken from the estimation of geometric shape at every intersection and the intersection capacity at the peak hours. The data, then, were integrated with the Indonesian Highway Capacity Manual (MKJI) methodology. Signal coordination makes the vehicles does not need to stop at every intersection. Increased adjacent performance with 0.813 degree of saturation from 0.814; 79,222m queue from 132,00m, and 39,919 seconds delay from 377,855; service level index from F into D; IDR . 2.850.274/ 1,000 km operating cost reduction for vehicle class I; IDR 4.236.430/1,000 km for vehicle class IIA; and IDR 5.385.889/1,000 km for vehicle class IIB respectively

Every Detail Matters. That Is, How the Interaction between Gα Proteins and Membrane Affects Their Function.

In highly organized multicellular organisms such as humans, the functions of an individual cell are dependent on signal transduction through G protein-coupled receptors (GPCRs) and subsequently heterotrimeric G proteins. As most of the elements belonging to the signal transduction system are bound to lipid membranes, researchers are showing increasing interest in studying the accompanying protein–lipid interactions, which have been demonstrated to not only provide the environment but also regulate proper and efficient signal transduction. The mode of interaction between the cell membrane and G proteins is well known. Despite this, the recognition mechanisms at the molecular level and how the individual G protein-membrane attachment signals are interrelated in the process of the complex control of membrane targeting of G proteins remain unelucidated. This review focuses on the mechanisms by which mammalian Gα subunits of G proteins interact with lipids and the factors responsible for the specificity of membrane association. We summarize recent data on how these signaling proteins are precisely targeted to a specific site in the membrane region by introducing well-defined modifications as well as through the presence of polybasic regions within these proteins and interactions with other components of the heterocomplex.

High-resolution concentration measurement in water/n-butanol binary system by means of high-frequency electrical impedance method

Chemical composition measurement technologies for binary systems are needed in many industrial and research applications for monitoring fluid composition in pipes and sample analysis. Except for spectroscopy technology, composition measurement is retrieved by monitoring fluid properties as refractive index, density, electrical conductivity or fluid sound velocity. Demanding applications are those where optical access to the fluid is not easy or available, very local or/and fast measurements are required, and where space limitations dictate the use of sub-millimeter non-intrusive sensors. Combination of all the above constraints in one application makes it extremely difficult to cope with. The latter is the motivation for the present work where a novel diagnostic method, based on I-VED (In-Vivo Embolic Detector) patented technology used in humans for the diagnosis of Coronary Artery Disease and Decompression Sickness, is implemented to determine the concentration of a binary mixture using high frequency impedance measurements. At first, the technology allows tuning over a range of excitation frequencies to identify a proper signal where the fluid attains chiefly an ohmic behavior. Then it retrieves chemical composition of the binary system through calibration curves with respect to resistance and temperature. Adaptation of the I-VED as concentration sensor has been driven by the necessity to integrate such a diagnostic in setups where available solutions in literature cannot be applied. Further to satisfying the aforementioned constraints, I-VED offers also other advantages compared to existing technologies as it provides high-scale resolution, it is not sensitive to electromagnetic interference (EMI) and it retrieves an integrated signal of the liquid between the electrodes, so localization of the measuring volume can be controlled. The proposed method has been tested in aqueous solutions of alcohol and its dependence on temperature and alcohol concentration has been investigated at an existing experimental setup named SELENE (SELf-rewetting fluid for ENErgy management), developed for heat transfer research applications.

Vibration-based synchronous sampling and its application in wind-turbine drive-train-condition monitoring

Abstract Utilizing shaft-speed information to analyse vibration signals is an important method for fault diagnosis and condition monitoring of rotating machineries, especially for those running at variable speeds. However, in many cases, shaft-speed information is not always available, for a variety of reasons. Fortunately, in most of the measurements, the shaft-speed information is embedded in the vibration response in many different forms, such as in the format of the fundamental shaft-rotation-frequency response and its harmonics, and the gear-meshing-frequency response and its harmonics, etc. Proper signal processing can be used to extract the shaft instantaneous speed from the measured vibration responses. In existing instantaneous shaft-speed-identification methods, a narrow-bandpass filtering technique is used explicitly or implicitly. In a complex gearbox system, such as that used in a wind turbine, the gear-meshing-response component could be modulated by many other shaft speeds, due to the configuration of the gearbox or due to the existence of component damage. As a result, it is very difficult to isolate a single vibration-response component for instantaneous shaft-speed detection. In this paper, an innovative approach is presented. The instantaneous shaft speed is extracted based on maxima tracking from the vibration-response spectrogram. A numerical integration scheme is employed to obtain the shaft instantaneous phase. Digital-domain synchronous resampling is then applied to the vibration data by using the instantaneous phase information. Due to the nature of noise suppression in the numerical integration, the accuracy of synchronous sampling is greatly improved. This proposed approach demonstrates the feasibility and engineering applicability through a controlled laboratory test case and two field wind-turbine cases. More detailed results and conclusions of this research are presented at the end of this paper.

Dual Two-Level Voltage Source Inverter Virtual Inertia Emulation: A Comparative Study

In this paper, the virtual synchronous generator (VSG) concept is utilized in the controller of the grid-connected dual two-level voltage source inverter (DTL VSI). First, the topology of the VSG and the DTL VSI are presented. Then, the state-space equations of the DTL VSI and the grid-connected two-level voltage source inverter (TL VSI), regarding the presence of the phase-locked loop (PLL) and the VSG, are given. Next, the small-signal modeling of the DTL VSI and the TL VSI is realized. Eventually, the stability enhancement in the DTL VSI compared with the TL VSI is demonstrated. In the TL VSI, large values of virtual inertia could result in oscillations in the power system. However, the ability of the DTL VSI in damping oscillations is deduced. Furthermore, in the presence of nonlinear loads, the potentiality of the DTL VSI in reducing grid current Total Harmonic Distortion (THD) is evaluated. Finally, by using a proper reference current command signal, the abilities of the DTL VSI and the TL VSI in supplying nonlinear loads and providing virtual inertia are assessed simultaneously. The simulation results prove the advantages of the DTL VSI compared with the TL VSI in virtual inertia emulation and oscillation damping, which are realized by small-signal analysis.

Investigating the level of Safety Considerations in Radiology Centers (North of Iran): Cross –Sectional Study

Background and Purpose Providing health care is the basic right of people(1). Diagnostic radiology is one of the main procedures in health care services and proper benefiting from this technology is brought only under well planning and management(1). Supervision of the available condition and its comparison with the recommended standards is a key role in assessing assurance from the benefit of these instruments (2). Data show that more than 80% of patients referring to these hospitals need radiology image (3).Improper service causes repetition of radiography and even wrong diagnosis, as a results threatening health of the patients (3) lack of protective barrier leads to the exposure of the staff to X-ray which is obviously carcinogen us (4). It happens that the instruments are not working properly, like of symmetry in X-ray field, defects in collimators, lack of adjusting ray field and X-ray, low quality or defective developing machine, lack of proper protective barrier, using low quality film and drugs, lack of protective barrier for children, all of which cause severe hazards for the patients and staff (4). Materials and Methods The crucial aim of medical services is to provide the public with their needs which are very important. The sensitivity of such services is to such an extent that in case of lack of care, the hazards are too high. In evaluation of health services, the first thing is to evaluate the device used. Methods, efficiency, profits and their combination for prevention and eradication of diseases are also important. Therefore to gain this goal, it is necessary the obtain results comparable with recommended standards. The purpose of this study was to access the conditions of radiology units at Mazandaran University hospitals and compare them with the standards of ICRU NCRP and ICRP. Radiology unit is the most expensive section of any hospital for its instruments, manpower and space provided. In a study conducted in 51centers on radiology staff, radiography room and protective barrier, ray leakage, the outcome were 89%, 82%, 77% and 37% respectively. It was found that the condition of these centers regarding the protective barriers is very unsuitable due to unawareness of the leakage (5, 6).Considering the mentioned necessities, in this study, the condition of radiography centers affiliated to the Mazandaran University of Medical Sciences was studied for the type and the rate of problem, in order to provide a proper solving method. Results Data were collected through, observation, interviewing and filling questionnaire. Results show that, the situations of the radiology units are for from international standard, to such an extent that it is matched clout 50%. Conclusion The results showed that, none of the dark rooms are standard, and do not have proper alarm signal. In 63% of these units there no tiling system about staff protection from radiation. Defects in radiography room, protective barrier and lack looking rays were 60%, 51% and 47% respectively. Referring to the obtained data, periodic supervision, and obeying of the standards are necessary.

WITHDRAWN: DESD-CAT inspired algorithm for establishing trusted connection in energy efficient FoG-BAN networks

Abstract Advanced technology utilization in medical field is emerging filed to reduce workload and time by providing earlier disease diagnosis and provide quality treatment. In this field to establish trusted connection from the attackers and providing secure data transfer among the interconnected sensors are challenging tasks. To overcome these problems, an attack identification scheme is required in trustable intra Body Area Network. Existing Trust-BAN networks are framed based on residual energy, Nodes distance, Cooperative communication and nodes behavior strategy. In this category nearest sensor nodes gathered all such nature details, based on that untrusted nodes are identified. But this is not suitable always in realistic situations. So an intelligent adaptive solution is needed in FoG computing based Body Area environment to identify malignant nodes. Hence proposed trust-based model, trustable nodes are identified using proper handshaking techniques which are happened in internal wireless Body Area Nodes, based on node id, Sensor localization, Channel Id ,Residual Energy, Delay and original sensor informations. This work also explaining about trust based energy efficient model for classifying malicious nodes from authorized sensor nodes. After classifying malicious nodes the remaining nodes in the WBAN form a trusted-cluster in order to provide proper handshaking signals among them. In every group the cluster head is selected based on the CAT inspired intelligent algorithm. By utilizing a Chaos based encryption techniques and adaptive fitness functions biomedical datas are encrypted in FoG server for further analysis and maintaining Integrity of data. The experimental results clearly explains that the proposed work achieve good performance in terms of precision, recall, throughput ,delay and other network centric performance measures compare to the firefly algorithm.

Combining Soft with Hard Condensed Matter for Circular Polarized Light Sensing and Logic Operations

AbstractThe study shows the incorporation of chiral nematic photonic cellulose nanocrystal (CNC) films, well known for their adaptive character of selective reflection of circular polarized light (CPL), and silicon‐based thin‐film photodiodes, thus achieving a light sensor capable of discriminating right‐ from left‐handed CPL. The circular polarization (CP) response is maximum for specific wavelengths in the green‐to‐red region. When subjected to these wavelengths, they produce photocurrents that are over 50% distinct between the two CP states. Proper signal processing, thus, yields a binary output depending on the handedness of the light. Through the addition of monovalent salt to the initial CNC suspension, a blueshift to the photonic band gap is induced, enabling a larger wavelength gamut and application possibilities. The measured results are then used as a basis for electromagnetic simulations that show remarkable consistency with the experimental results, thus defining a new tool that can be used to efficiently optimize the devices’ response. Fast transient responses to CPL are shown with possible logic operations, as well as humidity sensing. The developed devices are, thus, applicable in areas as diverse as imaging, CPL sensing, optoelectronic counterfeiting, and information processing with logic states that depend solely on the handedness of the incident light.

Comprehensive Detection of Pseudogenes Transcribed by Readthrough.

Transcription termination is a critical stage for the production of legitimate mRNAs, and consequently functional proteins. However, the transcription machinery can ignore the stop signs and continue elongating beyond gene boundaries, invading downstream neighboring genes. Such phenomenon, designated transcription readthrough, can trigger the expression of pseudogenes usually silenced or lacking the proper regulatory signals. Due to the sequence similarity to parental genes, readthrough transcribed pseudogenes can regulate relevant protein-coding genes and impact biological functions. Here, we describe a computational pipeline that employs already existent bioinformatic tools to detect readthrough transcribed pseudogenes from expression profiles. We also unveil that combining strand-specific transcriptome data and epigenetic profiles can enhance and corroborate the results. By applying such approach to renal cancer biopsies, we show that pseudogenes can be readthrough transcribed as part of unspliced transcripts or processed RNA chimeras. Overall, our pipeline allows us to scrutinize transcriptome profiles to detect a diversity of readthrough events leading to expression of pseudogenes.

Thermal Compensation Method for Piezoresistive Pressure Transducer

Piezoresistive pressure sensors are employed in a wide range of applications, but their output signal shows a substantial dependence on the working temperature. Usually, there is a need for an additional component to ensure a proper temperature-compensated signal for the sensors. In this article, we describe a method for the sensor thermal compensation that uses only the electrical signal produced by the pressure sensors themselves, without the need of additional measurements. The method proved to be effective while also ensuring a significant reduction in the measurement error.

Bi-LSTM based deep learning method for 5G signal detection and channel estimation

<abstract> <p>The advanced neural network methods solve significant signal estimation and channel characterization difficulties in the next-generation 5G wireless communication systems. The number of transmitted signal copies received through multiple paths at the receiver leads to delay spread, which intern causes interference in communication. These adverse effects of the interference can be mitigated with the orthogonal frequency division modulation (OFDM) technique. Furthermore, the proper signal detection methods optimal channel estimation enhances the performance of the multicarrier wireless communication system. In this paper, bi-directional long short-term memory (Bi-LSTM) based deep learning method is implemented to estimate the channel in different multipath scenarios. The impact of the pilots and cyclic prefix on the performance of Bi LSTM algorithm is analyzed. It is evident from the symbol-error rate (SER) results that the Bi-LSTM algorithm performs better than the state of art channel estimation methods known as the Minimum Mean Square and Error (MMSE) estimation method.</p> </abstract>

Time Line Correlative Spectral Processing for Stratification of Blood Pressure using Adaptive Signal Conditioning

Stratification of Blood Pressure is essential input in most of the cardiovascular diseases detection and prediction and is also a great aid to medical practitioners in dealing with Hypertension. Denoising based on spectral coding is developed based on frequency spectral decomposition and a spectral correlative approach based on wavelet transform. The existing approaches perform a standard deviation and mean of peak correlation in signal conditioning. The artifact filtrations were developed based on thresholding. Filtration of coefficients has an impact on accuracy of estimation and hence proper signal conditioning is a primal need. Wherein threshold is measured with discrete monitoring, time line observation could improve the accuracy of filtration efficiency under varying interference condition. Dynamic interference due to capturing or processing source results in jitter type noises which are short period deviations with varying frequency component. Hence a time-frequency analysis for filtration is adapted for filtration. This paper presents an approach of spectral correlation approach for signal condition in stratification of blood pressure under cuff less monitoring. This presented approach operates on the spectral distribution of finer resolution bands for monitoring signal in denoising and decision making. Existing approaches lacks the capability of loss-less denoising which is efficiently worked out in this paper.

Role of actin cytoskeleton in the organization and function of ionotropic glutamate receptors.

Neural networks with precise connection are compulsory for learning and memory. Various cellular events occur during the genesis of dendritic spines to their maturation, synapse formation, stabilization of the synapse, and proper signal transmission. The cortical actin cytoskeleton and its multiple regulatory proteins are crucial for the above cellular events. The different types of ionotropic glutamate receptors (iGluRs) present on the postsynaptic density (PSD) are also essential for learning and memory. Interaction of the iGluRs in association of their auxiliary proteins with actin cytoskeleton regulated by actin-binding proteins (ABPs) are required for precise long-term potentiation (LTP) and long-term depression (LTD). There has been a quest to understand the mechanistic detail of synapse function involving these receptors with dynamic actin cytoskeleton. A major, emerging area of investigation is the relationship between ABPs and iGluRs in synapse development. In this review we have summarized the current understanding of iGluRs functioning with respect to the actin cytoskeleton, scaffolding proteins, and their regulators. The AMPA, NMDA, Delta and Kainate receptors need the stable underlying actin cytoskeleton to anchor through synaptic proteins for precise synapse formation. The different types of ABPs present in neurons play a critical role in dynamizing/stabilizing the actin cytoskeleton needed for iGluRs function.

Determination of the Amount of Grain in Silos With Deep Learning Methods Based on Radar Spectrogram Data

Since the grain is a crucial food source, the determination of the quantity of stored grain in silos is inevitable in terms of commercial and correct inventory planning. In this study, a convolutional neural network (CNN) is developed to determine grain quantity using the spectrograms of the radar backscattering data. The radar backscattering signals of different amounts of grain for different grain surface condition types are collected using a stepped frequency continuous-wave radar system. In the scaled model silo, a total of 5681 measurements are carried out for grain stacks with different surface patterns and different weights (0-20 kg). Then, the dataset is constituted by using the spectrograms of these radar measurements. Randomly selected 4261 data corresponding to 75% of the dataset are used for training and the remaining 1420 data are used for testing. The proposed method is compared with pretrained CNN. Accuracy of the methods is given with metric parameters for both classification and regression. The classification task results of the proposed method are obtained as 98.45% accuracy, 98.15% sensitivity, 99.07% specitivity, 98.77% precision, 98.45% F1-Score, and 97.62% Matthews correlation coefficient. The regression task results are calculated as 0.3228 mean absolute error, 0.5150 mean absolute percentage error (MAPE), 0.9649 mean squared error, and 0.9823 root-mean-squared error. The proposed method is also compared with previous studies in the literature (with 3.29 MAPE) and its superiority is demonstrated with metric parameters. The results point out that, if CNN is properly modeled and trained, the combination of CNN and proper signal processing can provide effective results in the quantity measurement applications of the grain stacks.

Adaptive Compensation for Actuation Sign Faults of Flexible Spacecraft

This article develops a multiple-model-based adaptive control scheme to compensate for actuation sign faults of the flexible spacecraft using an error transformation. Multiple control signals are designed based on multiple estimators and an error transformation among estimation errors, tracking errors of estimators, and a virtual control error. A switching mechanism is established using a group of cost functions to choose the most proper control signal that can guarantee the desired system stability and asymptotic tracking performance.

The effect of loan granted factor on peer-to-peer lending (funded loan) in Indonesia

This study aims to determine whether the loan granted factor can affect peer-to-peer lending in Indonesia. The factors investigated in this research are the loan amount, loan period, interest rate, gender, and loan history using the data from registered and licensed peer-to-peer lending by the Financial Services Authority or Otoritas Jasa Keuangan (OJK) on November 2019. By examining 1,006 loans, the analytical method used is binary logistic regression with a significance level of alpha 0.05. The results of this research are loan amount, loan period, and loan history have the strongest impact on borrowers’ loan funding decision, suggesting that these loan characteristics can signal information that standard measures are used for loan funding. However, interest rate and gender have no significant effect on loan granted. Overall, loan funding decisions are based on proper and relevant signals given by loan characteristics.

Influence of rocuronium on achieving optimal vagal stimulation during intraoperative nerve monitoring in thyroid surgery

BackgroundIn the present study we determine the feasibility of intraoperative neuromonitoring following the administration of a nondepolarizing neuromuscular blocking agent during thyroid operations, as well as the influence of rocuronium on the achievement of optimal vagal stimulation during intraoperative neuromonitoring in thyroid surgery. We further investigate whether accelerometry is a reliable approach to obtaining an ipsilateral vagus signal prior to recurrent laryngeal nerve dissection. MethodsIncluded in the study were 61 thyroidectomized patients whose demographic data, indications, type of surgery, vagus, and recurrent nerve values before and after resection were obtained. We created five groups of patients based on the twitch values recorded during ipsilateral vagus stimulation prior to the recurrent laryngeal nerve dissection: (1) <10%, (2) 11–25%, (3) 26–50%, (4) 51–75% and (5) >75%. ResultsThe average electromyography amplitudes of the vagus nerve prior to the determination of the recurrent laryngeal nerve for each group were 552 μV, 463 μV, 543 μV, 513 μV and 551 μV, respectively. No difference between the groups was observed in this regard (p > 0.05). ConclusionIt can be expected that as soon as the effects of neuromuscular blockers on the peripheral muscles begin to abate, it will be possible to obtain the ipsilateral vagus signal prior to recurrent laryngeal nerve dissection at the desired levels. It can be concluded from this study that accelerometry using the pollicis muscle is an unreliable tool for the interpretation of the proper electromyography signals of the vagus nerve prior to the determination of the recurrent laryngeal nerve.

Real Time Optimal Tuning of Quadcopter Attitude Controller Using Particle Swarm Optimization

A real-time novel algorithm for proportional, integral and derivative (PID) controller tuning for quadcopters is introduced. The particle swarm optimization (PSO) method is utilized to search the quadcopter solution space to find the best PID controller parameters. A fuzzy logic (FL) controller is used to provide proper velocity reference signals to serve as tracking set points to be achieved by the PID controller. This nested loop design is proposed for stabilizing the quadcopter, where the fuzzy logic controller (FL) is used in the stable loop (i.e. outer loop) to control the desired angle, while the PID controller is used for the rate loop (i.e. inner loop). Finally, the optimum generated PID parameters were achieved in real time using the PSO search algorithm. The generated parameters were tested successfully using an experimental quadcopter setup at the University of Jordan.

A Comprehensive Study on Light Signals of Opportunity for Subdecimetre Unmodulated Visible Light Positioning

Currently, visible light positioning (VLP) enabling an illumination infrastructure requires a costly retrofit. Intensity modulation systems not only necessitate changes to the internal LED driving module, but decrease the LEDs’ radiant flux as well. This hinders the infrastructure’s ability to meet the maintained illuminance standards. Ideally, the LEDs could be left unmodulated, i.e., unmodulated VLP (uVLP). uVLP systems, inherently low-cost, exploit the characteristics of the light signals of opportunity (LSOOP) to infer a position. In this paper, it is shown that proper signal processing allows using the LED’s characteristic frequency (CF) as a discriminative feature in photodiode (PD)-based received signal strength (RSS) uVLP. This manuscript investigates and compares the aptitude of (future) RSS-based uVLP and VLP systems in terms of their feasibility, cost and accuracy. It demonstrates that CF-based uVLP exhibits an acceptable loss of accuracy compared to (regular) VLP. For point source-like LEDs, uVLP only worsens the trilateration-based median and 90th percentile root-mean-square error from to (+50%) and from to (+62%), in the × room under consideration. A large experimental validation shows that employing a robust model-based fingerprinting localisation procedure, instead of trilateration, further boosts uVLP’s and accuracy to and . When collating with VLP’s and , uVLP exhibits a comparable positioning performance at a significantly lower cost and at a higher maintained illuminance, all of which underline uVLP’s high adoption potential. With this work, a significant step is taken towards the development of an accurate and low-cost tracking system.