Deviation Error Research Articles

Evaluation of multiple digital elevation models for hypsometric analysis in the watersheds affected by the opening of the Red Sea

Climate change is increasingly affecting the Red Sea-related terrains in Egypt and Saudi Arabia with a notable increase in heavy precipitation events. This highly vulnerable region to flashfloods and other climate change-driven hazards encompasses rough terrains with more than 11,000 basins/subbasins, which necessitates the accurate estimation of their hydrological and geomorphological parameters among which the hypsometric analysis. In this regard, The study examines the accuracy of the hypsometric analysis extracted using open source SRTM-1, ASTER-GDEM, Copernicus-GLO30, ALOS-DEM against high-resolution Topo-1 m and Topo-2.8 m DEMs for Talat Hamdh basin in Egypt and Wadi El-Salwely basin in Saudi Arabia, respectively. Copernicus-GLO30 shows the highest accuracy among all DEMs with the root-mean-squared–error (RMSE), mean elevation error, standard deviation, maximum and minimum absolute errors of 3.03, 2.0, 2.3, 11.7 and 0.1 m, respectively for Talat Hamdh basin. The findings also show that, regardless of the geology and geomorphic evolution of the basin, the hypsometric analysis is sensitive to the DEM type rather than the spatial resolution as Copernicus DEM yields similar basin numbers (a single basin) and area (1.366 and 141.9 km2) compared to the reference DEMs (1.408 and 154.4 km2) for Talat Hamdh and Wadi El-Salwely basins, respectively. Contrariwise, other open source DEMs yield multiple basins and thus significantly smaller basin area. Given the DEM-type dependence of the hypsometric analysis, the study recommends that large-scale hydrological and geomorphological analyses should consider using a high-resolution reference DEM on a local-scale basin to examine the accuracy of open source DEMs prior to conducting the analysis.

Coverage Enhancement of Light-Emitting Diode Array in Underwater Internet of Things over Optical Channels

The construction of the underwater Internet of Things (UIoT) is crucial to marine resource development, environmental observation, and tactical surveillance. The underwater optical wireless communication (UOWC) system with its large bandwidth and wide coverage facilitates the high-capacity information interconnection within the UIoT networks over short and medium ranges. To enhance the coverage characteristics of the UOWC system, an optimized lemniscate-compensated layout of light-emitting diode (LED) array is proposed in this paper, which can ameliorate the received optical power and reliability at the receiving terminal. Compared with traditional circular and rectangular layouts, the received optical power and bit error rate (BER) performance of the proposed system are analyzed based on the Monte Carlo simulation method. The analysis results show that the proposed LED array achieves a smaller peak power deviation and mean square error of the received optical power under three typical seawater environments. Furthermore, the proposed LED-array scheme supports a better BER performance of the UOWC system. For example, in turbid seawater with a transmission depth of 9.5 m, the BER of the proposed LED array layout is 1 × 10−7, which is better than the BER of 3.5 × 10−6 and 1 × 10−4 under the other two traditional light source layouts.

AirBP: Monitor Your Blood Pressure with Millimeter-Wave in the Air

Blood pressure (BP), an important vital sign to assess human health, is expected to be monitored conveniently. The existing BP monitoring methods, either traditional cuff based or newly emerging wearable based, all require skin contact, which may cause unpleasant user experience and is even injurious to certain users. In this article, we explore contactless BP monitoring and propose airBP, which emits millimeter-wave signals toward a user’s wrist, and captures the reflected signal bounded off from the pulsating artery underlying the wrist. By analyzing the reflected signal strength of the signal, airBP generates the arterial pulse and further estimates BP by exploiting the relationship between the arterial pulse and BP. To realize airBP, we design a new beam-forming method to keep focusing on the tiny and hidden wrist artery, by leveraging the inherent periodicity of the arterial pulse. Moreover, we custom design a pre-training and neural network architecture, to combat the challenges from the arterial pulse sparsity and ambiguity, so as to estimate BP accurately. We prototype airBP using a coin-size commercial off-the-shelf millimeter-wave radar and perform extensive experiments on 41 subjects. The results demonstrate that airBP accurately estimates systolic and diastolic BP, with a mean error of –0.30 mmHg and –0.23 mmHg, as well as a standard deviation error of 4.80 mmHg and 3.79 mmHg (within the acceptable range regulated by the FDA’s AAMI protocol), respectively, at a distance up to 26 cm.

Intelligent Control of Solar LED Street Lamp Based on Adaptive Fuzzy PI Control

As road traffic develops, energy-saving and efficient street lights have become a key research field for relevant professionals. To reduce street lights energy consumption, a fireworks algorithm is used to optimize the membership function parameters of fuzzy control and the initial parameters of PI control. A fireworks algorithm improved adaptive fuzzy PI solar LED street light control system is designed. The results showed that in the calculation of Root-mean-square deviation and Mean absolute error, the Root-mean-square deviation of the adaptive fuzzy PI control system improved by the fireworks algorithm was 0.213, 0.258, 0.243, 0.220, and the Mean absolute error was 0.143, 0.152, 0.154, 0.139, respectively, which proved that the prediction accuracy was high and the stability was good. In the calculation of the 1-day power consumption of the solar LED intelligent control system, the average power consumption of the designed solar LED intelligent control system was about 2000W, which was 25.9%, 47.4%, and 42.9% lower than the other three control methods, respectively. This proves that its energy consumption is low, and its heat generation is low, and the battery service life is long. The research and design of an adaptive fuzzy PI control solar LED street light intelligent control system has good performance, which can effectively achieve intelligent management and energy conservation and emission reduction in smart cities.

The way to induce asset‐backed securities participation in eco‐compensation

AbstractBy establishing an ecology compensation asset securitization project, market mechanisms can be used to regulate the interests of stakeholders in ecological conservation. Previous studies have shown that combining asset securitization with environmental protection can effectively promote the sustainable development of both economy and environment. However, there is still a lack of research on the stable mechanisms and impact of integrating ecology compensation and asset securitization. In this study, we propose a comprehensive operating model for ecology compensation asset securitization and a specific valuation framework supported by a multi‐period, multi‐state Markov model for ecology compensation asset securitization. If the project's net present value is positive, it can effectively reduce the risks of ecology compensation projects and increase the return rate of ecology compensation asset securitization projects. By employing the case study of ZhongHang ShouGang Green Energy (SZ:180801) and implementing the asset pool valuation using the multi‐state Markov model, the deviation error is 0.89%, validating the effectiveness of the model. Additionally, sensitivity analysis from simulation results indicates that changes in interest rates and default probabilities are the main factors influencing the valuation of the asset pool. After summarizing the research conclusions, relevant policy recommendations and future prospects are presented. This research aims to provide reference for the development and application of ecology compensation asset securitization.

Prediction of Q-Band Rain Attenuation Statistics Using Frequency Scaling Models for Temperate Location, Vigo, Spain

The prediction of yearly rain attenuation statistics at Q-band is made from Ka-band measurement for a temperate location, Vigo, Spain, using different frequency scaling models. The validity of the different frequency scaling models is tested for the present location by graphical comparison between measurement and prediction and also in terms of mean, standard deviation, and root mean square errors (RMSE). The Battesti model performs better compared to other existing frequency scaling models, RMSE is only 4.16% and 5.52% for the periods July 2016 to June 2017 and July 2017 to June 2018 respectively. The proposed new power law model increases the accuracy of the prediction for which the RMSE error is 1.09% and 2.17% less compared to the Battesti model for the periods July 2016 to June 2017 and July 2017 to June 2018, respectively. In predicting monthly statistics, the proposed model performs better compared to the Battesti model for all the months except December, January, and February. While predicting monthly statistics, for the proposed model, the maximum and minimum prediction errors are 18.50% and 0.39%, respectively. For the prediction of diurnal statistics, the proposed model performs better compared to the Battesti model with a very small prediction error, less than 4% for both days. The present study can be useful in the design and planning of satellite communication links in present or similar climatic regions for estimating rain attenuation at Q band or above, for which the experimental setup's cost is very high and requires a large receiver margin.

A linear model-based simulation tool for estimating number of trials needed for upper limb stroke recovery in a given rehabilitation session

Traditional methods for assessing upper-limb functional outcomes in stroke patients often fail to estimate the number of trials required to achieve performance stability of a chosen kinematic metric. Limited non-model-based studies have attempted to tackle this issue. To bridge this gap, this study utilized an iterative learning algorithm (ILA) in MATLAB, employing linear models to represent the muscle dynamics and forearm extension of impaired patients. The reference task space trajectory was set as a straight-line point-point trajectory within a range of 0 - 0.2828m. By using the root mean square error (RMSE) as a metric for evaluating kinematic accuracy, a maximum kinematic deviation error of 0.01m was imposed with respect to the trajectory by the (ILA). Results indicate that over 16 trials, performance stability was obtained with improvement in deviation error from 0.0168m in the first trial to 0.0060 at sixteen trials. The result obtained is in line with similar non-model studies and our findings inform the potential of ILAs with linear models for estimation of trial numbers required to attain performance stability of a selected kinematic metric (i.e., kinematic accuracy).

Modeling the electrical properties of heterojunctions using ANFIS, ANFIS-GA and ANFIS-PSO Models

The present research introduces a theoretical study that aims to utilize ANFIS in estimating and predicting the electrical behavior of heterojunctions. For this purpose, five different heterojunctions were chosen. The experimental datasets that represent the electrical behavior of the chosen heterojunctions were extracted and employed in ANFIS as targets. To enhance the ANFIS performance two hybrid heuristic algorithms, genetic algorithm (GAs) and particle swarm optimization (PSO) were combined with ANFIS. The major contribution of the current research is to predict the electric characteristics of heterojunctions using ANFIS and increase the modeling accuracy of ANFIS by optimizing the premise and consequent parameters using (GAs) and (PSO). Also, compare the proportion of enhancement produced by using ANFIS-GA and ANFIS-PSO to decide which of them is more powerful under the study conditions. However, to the author’s knowledge, the presented goals have not been investigated before for heterojunctions. The mean squared error (MSE), the correlation coefficient (R2), and the standard deviation error (Std. error) were calculated for all trained models. The modeling errors of ANFIS-GA and ANFIS-PSO were compared to the error values produced by ANFIS. According to modeling results, simulation ANFIS outputs follow the experimental data patterns in excellent response. Predictions of electrical characteristics for heterojunctions using the trained models provide acceptable results where the MSE values obtained by training ANFIS-PSO are lower than their values obtained by ANFIS and ANFIS-GA models. The improvements in average percentages in ANFIS performance when combined with GA and PSO are equal to 2.2% and 3%, respectively. Consequently, the proposed ANFIS-PSO model is more accurate in predicting the electrical behavior of heterojunctions under the study conditions.

A Concentric Tube Steerable Drilling Robot for Minimally Invasive Spinal Fixation of Osteoporotic Vertebrae.

Spinal fixation with rigid pedicle screws have shown to be an effective treatment for many patients. However, this surgical option has been proved to be insufficient and will eventually fail for patients experiencing osteoporosis. This failure is mainly attributed to the lack of dexterity in the existing rigid drilling instruments and the complex anatomy of vertebrae, forcing surgeons to implant rigid pedicle screws within the osteoporotic regions of anatomy. To address this problem, in this paper, we present the design, fabrication, and evaluation of a unique flexible yet structurally strong concentric tube steerable drilling robot (CT-SDR). The CT-SDR is capable of drilling smooth and accurate curved trajectories through hard tissues without experiencing buckling and failure; thus enabling the use of novel flexible pedicle screws for the next generation of spinal fixation procedures. Particularly, by decoupling the control of bending and insertion degrees of freedom (DoF) of the CT-SDR, we present a robotic system that (i) is intuitive to steer as it does not require an on-the-fly control algorithm for the bending DoF, and (ii) is able to address the contradictory requirements of structural stiffness and dexterity of a flexible robot interacting with the hard tissue. The robust and repeatable performance of the proposed CT-SDR have been experimentally evaluated by conducting various drilling procedures on simulated bone materials and animal bone samples. Experimental results indicate drilling times as low as 35 seconds for curved trajectories with 41 mm length and remarkable steering accuracy with a maximum 2% deviation error.

Numerical analysis of the heat exchange model with the ground on the example of a complex of industrial halls

This paper describes the process of validation of the numerical model and its calibration, based on long-term field studies that were carried out at a growing tunnel system for Agaricus bisporus in southern Poland. A verification of uncertainty indices was undertaken, based on which the applicability of the model for further research and analysis was assessed according to commonly used guidelines. WUFI®plus software was applied based on the numerical elementary balance method (EBM). The HVAC system was also simulated in order to reflect actual conditions as accurately as possible. The correctness of the model was assessed by means of uncertainty indicators in the form of the normalised mean deviation error (NMBE) and the Coefficient of Variation of the Root Mean Square Error CV (RMSE). The analysis provided an opportunity to highlight the validity of the calculations, considered reliable under the criteria adopted. It also pointed out some limitations of the model applied, resulting in negative calibration results for a small number of selected measurement monitors. Using the validated calculation model, heat flows from the ground to the building and the other way around were estimated. The specifics of the building contributed to the occurrence of heat gain from the ground being 20 times larger compared to energy losses to the ground. This opens up a potential path for extending the numerical analysis to optimise energy management for the investigated facility and to determine the thermal interaction between buildings in the surveyed area.

Analisis Perilaku Moral Hazard dan Adverse Selection pada Agency Problem di Pembiayaan Musyarakah PT. Bank Sumut KCPSY Binjai

This study aims to determine the form of behavior and how to handle agency problems caused by moral hazard behavior and adverse selection in musyarakah financing at PT. Bank Sumut KCPSY Binjai. The agency problem is the agency problem in the musyarakah product scheme. This type of research is field research with qualitative methods. Sources of data in this study include two categories, namely primary data and secondary data. The subjects in this study were employees of PT. Bank Sumut KCPSY Binjai in the management section that is competent in the field of musyarakah financing. The research results show that the form of moral hazard and adverse selection behavior at PT. Bank Sumut KCPSY Binjai namely the difficulty of banks assessing the true character of customers, errors in analysis, ethical deviations and lack of supervision (monitoring) carried out by banks. PT. Bank Sumut KCPSY Binjai Office made various efforts from screening, verification to monitoring. Furthermore, if the problem of moral hazard and adverse selection has occurred, the bank will handle it in two ways, namely saving financing in the form of first rescheduling, reconditioning, restructuring and solving problem financing by means of billing. lawsuits, execution of mortgage auctions, and WO

Evaluation of collum angle of maxillary incisors on impacted vs non impacted canine Side: A CBCT analysis

The angle which is formed between the crown axis and root axis of an upper central incisor is called collum angle and this angle serves as an important morphological feature for normal development of the dentition and plays a vital role during diagnosis and treatment planning and may vary in different malocclusions i.e; skeletal and dental malocclusions. To quantify and compare the collum angle (crown root angulation) of maxillary incisors (central and lateral incisor) in subjects with unilateral permanent maxillary canine impaction between the impacted and non impacted side using Cone Beam Computed Tomography (CBCT). Thirty subjects with unilateral permanent maxillary canine impaction who had to undergo fixed orthodontic treatment were selected and their CBCT images were analysed. The collum angle of maxillary central and lateral incisor on impaction and non impaction side was measured using CBCT imaging. Descriptive statistical analysis was carried out and the mean±standard deviation was calculated and comparison between two sides was made by using paired t-test and a p value of less <0.05 was considered as statistically significant. The collum angle of central and lateral incisor between impacted and non impacted side were averaged. Thus, the mean±standard deviation and standard error of the collum angle (n-30) were calculated for maxillary central incisor and lateral incisor on both sides. The mean±sd of the collum angle of maxillary central incisor on impacted and non impacted side was 1.39±7.16 and 2.33±5.86 respectively with a p value of 0.282, while as the mean±sd of the collum angle of maxillary lateral incisor on impacted and non impacted side was 3.09±6.26 and 5.24±5.28 respectively with a p value of 0.060 which was considered as statistically insignificant between the two sides. A decrease in collum angle was found on impaction side with a more decreased value for lateral incisor when comparison was made with non impaction side, but no statistically significant difference was found.

Improving the Prediction of Grain Protein Content in Winter Wheat at the County Level with Multisource Data: A Case Study in Jiangsu Province of China

Wheat is an important food crop in China. The quality of wheat affects the development of the agricultural economy. However, the high-quality wheat produced in China cannot meet the demand, so it would be an important direction for research to develop high-quality wheat. Grain protein content (GPC) is an important criterion for the quality of winter wheat and its content directly affects the quality of wheat. Studying the spatial heterogeneity of wheat grain proteins is beneficial to the prediction of wheat quality, and it plays a guiding role in the identification, grading, and processing of wheat quality. Due to the complexity and variability of wheat quality, conventional evaluation methods have shortcomings such as low accuracy and poor applicability. To better predict the GPC, geographically weighted regression (GWR) models, multiple linear regression, random forest (RF), BP neural networks, support vector machine, and long-and-short-term memory algorithms were used to analyze the meteorological data and soil data of Jiangsu Province from March to May in 2019–2022. It was found that the winter wheat GPC rises by 0.17% with every 0.1° increase in north latitude at the county level in Jiangsu. Comparison of the prediction accuracy of the coefficient of determination, mean deviation error, root mean square error, and mean absolute error by analyzing multiple algorithms showed that the GWR model was the most accurate, followed by the RF model. The regression coefficient of precipitation in April showed the smallest range of variation among all factors, indicating that precipitation in April had a more stable effect on GPC in the study area than the other meteorological factors. Therefore, consideration of spatial information might be beneficial in predicting county-level winter wheat GPC. GWR models based on meteorological and soil factors enrich the studies regarding the prediction of wheat GPC based on environmental data. It might be applied to predict winter wheat GPC and improve wheat quality to better guide large-scale production and processing.

Error-insensitive preparation of entangled states between a Josephson qubit and microwave photons via invariant-based shortcuts

Optimal preparation of quantum entanglement is of significance to information processing and state engineering. In this paper, an efficient scheme is proposed to implement error-insensitive generation of entangled states between a Josephson qubit and microwave photons by the technique of invariant-based shortcuts to adiabaticity. A superconducting qubit is dispersively coupled to a quantized cavity field of one-dimensional transmission line resonator. Within a considered subspace spanned by three composite states, we deal with an effective interaction of the composite system with two classical drivings. A maximally entangled qubit-photon state can be deterministically induced using a splitting-like quantum state transfer. To nullify the deviation errors of Rabi coupling and frequency detuning, we optimize the driving parameters and then make the entanglement creation insusceptible to these control imperfections. Thanks to the mitigation of deviation effects, robustness against the residual noisy environment could be obtained numerically. The proposed strategy could provide a promising avenue towards fast and robust information processing with superconducting circuit quantum electrodynamics.

A Novel Extensible Continuum Robot with Growing Motion Capability Inspired by Plant Growth for Path-Following in Transoral Laryngeal Surgery.

This article presents a novel extensible continuum robot (ECR) with growing motion capability for improved flexible access in transoral laryngeal procedures. The robot uses an extensible continuum joint with a staggered V-shaped notched structure as the backbone, driven by the pushing and pulling of superelastic Nitinol rods. The notched structure is optimized to achieve a wide range of extension/contraction and bending motion for the continuum joint. The successive and uniform deflection of the notches provides the continuum joint with excellent constant curvature bending characteristics. The bidirectional rod-driven approach expands the robot's extension capabilities with both pushing and pulling operations, and the superelasticity of the driving rods preserves the robot's bending performance. The ECR significantly increases motion dexterity and reachability through its variable length, which facilitates collision-free access to deep lesions by following the anatomy. To further exploit the advantages of the ECR in path-following for flexible access, a growing motion approach inspired by the plant growth process has been proposed to minimize the path deviation error. Characterization experiments are conducted to verify the performances of the proposed ECR. The extension ratio achieves up to 225.92%, and the average distal positioning error and hysteresis error values are 2.87% and 0.51% within the ±120° bending range. Compared with the typical continuum robot with a fixed length, the path-following deviation of this robot is reduced by more than 58.30%, effectively reducing the risk of collision during access. Phantom experiments validate the feasibility of the proposed concept in flexible access procedures.

Enhancing Accessibility: Assistive Devices Pairing Mobile Apps for Visually Impaired People

Vision impairment and blindness are significant health conditions that affect a considerable portion of the global population and have significant consequences, particularly in developed nations. Its harmful consequences can have a negative influence on a person's personal quality of life, as well as limit their ability to live independently. Navigation plays a crucial role in the activities that are impacted by vision loss. This is because it is almost impossible for the individual to move safely and independently. The goal of this project is to improve mobility for visually impaired people by employing Light Detection and Ranging (LiDAR) sensors to identify obstacles and alert users via haptic feedback if there are potential obstacles in their way. In addition, this study compares two sensors, LiDAR and ultrasonic sensors, besides the implementation of the Internet of Things (IoT), which was integrated into the small, portable robot by pairing a mobile phone. This is to ensure the user may be securely guided to their destination. I-Walk is a mobile app with a voice user interface (VUI) for GPS navigation systems and emergency calling. This app has been developed to allow users safe and independent travel. The simulation result shows that even though ultrasonic sensors are cheaper and serve the same function as LiDAR, their huge standard deviation and percentage error shown in this study cannot equal LiDAR's accuracy in which LiDAR has an average error of 0.63%. In contrast, ultrasonic sensors have an average error of 2.39%. Overall, this obstacle detection and navigation system comprises robust hardware and software to assist visually impaired people effectively.Keywords: Assistive technology, blind, mini guider robot, obstacle detection, navigation, IoT

Influence of switching sequences on the neutral point voltage balance in a three-level voltage source invertor

BACKGROUND:Ensuring the voltage balance of the neutral point of the DC link within acceptable limits is one of the mandatory requirements during the operation of a three-level autonomous neutral point clamped voltage source inverter. It is known that neutral point voltage imbalance can adversely affect the operation of the inverter and the load at all, lead to the failure of both power switches and capacitors in the DC link. Neutral point voltage imbalance mostly often occurs due to the asymmetry of the nominal values of DC capacitors, inconsistent properties of switching devices, asymmetric three-phase load, and also due to the imperfection of the converter control algorithm.
 AIMS:Selection of the optimal switching sequence that ensures the smallest deviation of the neutral point voltage and the number of switching of power switches in a three-level voltage source inverter.
 METHODS:For an objective comparison of the considered switching sequences and their influence on the neutral point voltage balance, a simulation model of a three-level neutral point clamped voltage source inverter was developed in theMATLAB/Simulinksoftware. To control this inverter, a space vector modulation method was used with three different switching sequences: five-segment, seven-segment and standard.
 RESULTS:The topology of a three-level neutral point clamped voltage source inverter is presented. The experimental dependencies of the neutral point voltage deviation error was taken with a change in the modulation coefficient, the frequency of the fundamental harmonic at the inverter output, and load characteristics for three different switching sequences.
 CONCLUSIONS:In this paper, the influence of the basic vectors and the influence of switching sequences on the neutral point voltage balance are studied. Combinations of states of large and zero basic vectors do not affect the neutral point voltage. For the medium basic vectors, the neutral point voltage can increase or decrease depending on the operating conditions of the inverter. The small basic vectors significantly affect the neutral point voltage. Considering the abovementioned, the seven-segment sequence that ensures both the optimal balance of the neutral point voltage and the level of switching losses should be considered as the best switching sequence for a three-level inverter.

Accuracy of intraoral scan with prefabricated aids and stereophotogrammetry compared with open tray impressions for complete-arch implant-supported prosthesis: A clinical study.

The aim of this clinical study was to compare the accuracy of intraoral scan system (IOS) with prefabricated aids and stereophotogrammetry (SPG) compared with open tray implant impression (OI) for complete-arch implant-supported fixed dental prostheses (CIFDP). Patients needing CIFDP were enrolled in this study. OI, reference standard, IOS with prefabricated aids, and SPG were performed for each patient. Distance and angle deviations between all pairs of abutment analogs, root mean square (RMS) errors between the aligned test and reference model, and chairside time were measured. The effect of inter-abutment distance, jaw (maxilla or mandible), number of implants, and arch length on deviations was analyzed. The mixed effect model was applied to analyze deviations and RMS errors. Fifteen consecutive individuals (6 females and 9 males, 47-77 years old) with 22 arches (9 upper and 13 lower jaws) and 115 implants were included. There was no significant difference in distance deviation comparing SPG and IOS with OI (p > .05). IOS showed a significantly greater angle deviation and RMS errors than SPG (median 0.40° vs. 0.31°, 69 μm vs. 45 μm, p < .01). The inter-abutment distance was negatively correlated with the accuracy of SPG and IOS (p < .05). The chairside time for IOS, SPG, and OI was 10.49 ± 3.50, 14.71 ± 2.86, and 20.20 ± 3.01 min, respectively (p < .01). The accuracy of SPG and IOS with prefabricated aids was comparable. IOS was the most efficient workflow.

Taste Bud-Inspired Single-Drop Multitaste Sensing for Comprehensive Flavor Analysis with Deep Learning Algorithms.

The electronic tongue (E-tongue) system has emerged as a significant innovation, aiming to replicate the complexity of human taste perception. In spite of the advancements in E-tongue technologies, two primary challenges remain to be addressed. First, evaluating the actual taste is complex due to interactions between taste and substances, such as synergistic and suppressive effects. Second, ensuring reliable outcomes in dynamic conditions, particularly when faced with high deviation error data, presents a significant challenge. The present study introduces a bioinspired artificial E-tongue system that mimics the gustatory system by integrating multiple arrays of taste sensors to emulate taste buds in the human tongue and incorporating a customized deep-learning algorithm for taste interpretation. The developed E-tongue system is capable of detecting four distinct tastes in a single drop of dietary compounds, such as saltiness, sourness, astringency, and sweetness, demonstrating notable reversibility and selectivity. The taste profiles of six different wines are obtained by the E-tongue system and demonstrated similarities in taste trends between the E-tongue system and user reviews from online, although some disparities still exist. To mitigate these disparities, a prototype-based classifier with soft voting is devised and implemented for the artificial E-tongue system. The artificial E-tongue system achieved a high classification accuracy of ∼95% in distinguishing among six different wines and ∼90% accuracy even in an environment where more than 1/3 of the data contained errors. Moreover, by harnessing the capabilities of deep learning technology, a recommendation system was demonstrated to enhance the user experience.

Misperception of Visual Verticality Measured with a Virtual Reality Device in Patients with Fibromyalgia Syndrome: A Cross-Sectional Study

The objective of this study was to analyze the perception of visual verticality (VV) in subjects with Fibromyalgia Syndrome (FMS) and to correlate this with the symptoms of the disease and balance capacity. A cross-sectional study including 54 patients (51 female) was conducted. The evaluation of visual verticality was carried out with a virtual reality device by calculating the Mean Absolute Error (MAE) of degrees deviation in two tests: the Subjective Visual Vertical (SVV) test for the contribution of the vestibular system to the perception of verticality and the Rod and Frame test (RFT) for the contribution of the visual system. In total, 16 subjects (29.6%) presented good VV perception, 6 subjects (11.1%) presented an exclusive alteration of the SVV test, 19 subjects (35.2%) presented an exclusive alteration of the RFT and 13 subjects (24.1%) showed alteration in the two tests. The MAE in the SVV test showed medium correlations with several variables such as the Fibromyalgia Impact Questionnaire (FIQ) (Rho = 0.399, p = 0.003), the Pain Catastrophizing Scale (PCS) (Rho = 0.417, p = 0.002), the Dizziness Handicap Inventory (DHI) (Rho = 0.376, p = 0.005), and the Activities-Specific Balance Confidence Scale (ABC-16) (Rho = −0.367, p = 0.006). The MAE in the RFT showed medium correlations with the Instability Support Reduced (Rho = 0.327, p = 0.016) and Instability Gait Eyes Open (Rho = 0.312, p = 0.022) subscales of the JAEN (Joined Assessment of Equilibrium and Neuro-motor) Scale. Conclusions: Around 70% of the subjects with FMS showed some alteration in the perception of VV; 60% of these patients presented visual system dependence. The SVV test correlates with the impact and health status of FMS, and the RFT correlates with the alteration in the dynamic balance.