This study was conducted to check whether benzene is contained inside the petroleum-based cleaning agent used in the printing industry and measure whether it is actually exposed to the air. Benzene was analyzed inside the cleaning agent and air exposure evaluation was done by area sampling. Risk assessment was performed using the CHARM (Chemical Hazard Risk Management) technique. Most products contained benzene based on the results obtained from this study. As a result of collecting air samples and checking whether the workers were exposed to benzene actually, benzene was detected in three samples. As a result of the risk assessment, most of printing businesses scored more than four points. Benzene was detected in all petroleum-based cleaning products. In addition, benzene was detected in some of air samples. Considering the fact that even small exposure level of benzene is dangerous to worker health and most of the printing businesses in South Korea operate on a small scale with fewer than five employees so the health management system is poor, it is necessary to prepare appropriate measures to prevent work diseases provoked by benzene exposure.
We designed a rhodamine B‐based colorimetry chemosensor BHSO ((Z)‐3',6'‐bis(diethylamino)‐2‐(2‐(((8‐hydroxy‐2,3,6,7‐tetrahydro‐1H,5H‐pyrido[3,2,1‐ij]quinolin‐9‐yl)methylene)amino)ethyl)spiro[isoindoline‐1,9'‐xanthen]‐3‐one) for detecting Cu2+. In presence of Cu2+, BHSO caused a color variation from colorless to bright orange. Limit of detection for Cu2+ toward BHSO was 0.73 μM. Binding of BHSO to Cu2+ was analyzed as a 1:1 ratio through the Job plot and ESI‐mass. BHSO can detect readily Cu2+ with the test strip by colorimetry variation. The detecting process of Cu2+ by BHSO was represented by UV‐vis titration, ESI‐MS, 1H NMR titrations, Job plot, and DFT calculations.
In the current study, we investigated the effects of gender and regular physical activity (PA) on PA decision-making and speed of information processing. We enrolled 110 university students ( Mage = 20.91, SD =2.28 years) in an experiment involving two tasks and a questionnaire. One of the two tasks assessed how much participants agreed with presented PA words and phrases and the other task predicted behavior and responses to future situations. We collected and measured the participants’ choices and the time they took to make them. The questionnaire, the International Physical Activity Questionnaire (IPAQ), consisted of exercise self-schema and PA questions. We conducted a 2 (gender: male or female) ×2 (regular PA or not) multivariate analysis of variance (MANOVA) and found statistically significant differences between variables as a function of participants’ gender (λ = .66, p < .001) and regular PA engagement (λ = .51, p < .001). In a regression analysis, we also found gender differences [males showed relationships between agreement with PA information and information processing speed for decisions on future behavior ( R ² = .31, F = 12.50); females showed relationships between their exercise self-schema ( R ² = .26, F = 18.18) and regular PA such that, in the non-regular PA group, exercise self-schema was related to reaction time in making decisions on future behavior ( R ² = .29, F = 11.23), and in the regular PA group, agreement with PA information was related to reaction time for PA-related words, and agreement with non-PA information ( R ² = .29, F = 8.91)]. These results highlight the need to consider participant characteristics when designing exercise interventions, and we present supplementary data regarding exercise self-schemas, decision-making, and the speed of processing PA information.
A wireless identification system was developed in which visible light was simultaneously used for illumination and for transmitting an interrogating signal from a reader to a transponder. We used the Manchester code to modulate the visible light to ensure flicker-free lighting, and the duty factor of the Manchester code was utilized for dimming control. The average optical power of the light emitting diode (LED) array in the reader, and the solar cell current in the transponder, increased when the duty factor of the Manchester code was increased. In experiments, the capture range of the identification system was about 2.3 meters when the duty factor was 90%. This configuration can be useful in an automatic vehicle identification system for security checks or fare calculation, using an LED lamp installed at toll gates or parking places.
Objectives Interactive learning through interprofessional education enhances collaborative practice. This study aims to determine the attitude, perception, and readiness of Omani undergraduate health professions students toward interprofessional education and practice. Methods A total of 327 Omani undergraduates across different health fields participated in this cross-sectional study. Data was gathered via an online-based survey by using two previously validated and reliable tools: 1) the Student Perceptions of Interprofessional Clinical Education-revised (SPICE-R2) and 2) the Readiness for Interprofessional Education Scale-modified. Data were analysed using descriptive and inferential statistics. Results The overall mean score of the students' attitude and readiness toward interprofessional education was 56.77 (SD = 5.51). The overall mean score of the students' perception toward interprofessional education was 41.42 (SD = 4.56). The overall mean attitude and readiness score and perception score were higher for the pharmacy students than for the rest of the students; however, no statistically significant difference was noted in the scores of attitude and readiness (p > .05), and perception (p > .05). Conclusions Overall, the study revealed that all the health professionals in Oman, irrespective of the profession, disclosed a favourable attitude, a high state of readiness, and a positive perception toward interprofessional education and practice. Furthermore, all the health professionals considered teamwork and collaboration to be essential.
Analysis of kinematic features related to clinical assessment scales may qualitatively improve the evaluation of upper extremity movements of stroke patients. We aimed to investigate kinematic features that could correlate the change in the Fugl-Meyer Assessment (FMA) score of stroke survivors through upper extremity robotic rehabilitation. We also analyzed whether changes in kinematic features by active and active-assisted robotic rehabilitation correlated differently with changes in FMA scores. Fifteen stroke patients participated in the upper extremity robotic rehabilitation program, and nine kinematic features were calculated from reach tasks for assessment. Simple and multiple linear regression analyses were used to characterize correlations. Features representing movement speed were associated with changes in FMA scores for the group that used an active rehabilitation robot. In contrast, in the group that used an active-assisted rehabilitation robot, features representing movement smoothness were associated with changes in the FMA score. These estimates can be an important basis for kinematic analysis to complement clinical scales.
Neurotransmitter release occurs either synchronously with action potentials (evoked release) or spontaneously (spontaneous release). Whether the molecular mechanisms underlying evoked and spontaneous release are identical, especially whether voltage-gated calcium channels (VGCCs) can trigger spontaneous events, is still a matter of debate in glutamatergic synapses. To elucidate this issue, we characterized the VGCC dependence of miniature excitatory postsynaptic currents (mEPSCs) in various synapses with different coupling distances between VGCCs and synaptic vesicles, known as a critical factor in evoked release. We found that most of the extracellular calcium-dependent mEPSCs were attributable to VGCCs in cultured autaptic hippocampal neurons and the mature calyx of Held where VGCCs and vesicles were tightly coupled. Among loosely coupled synapses, mEPSCs were not VGCC-dependent at immature calyx of Held and CA1 pyramidal neuron synapses, whereas VGCCs contribution was significant at CA3 pyramidal neuron synapses. Interestingly, the contribution of VGCCs to spontaneous glutamate release in CA3 pyramidal neurons was abolished by a calmodulin antagonist, calmidazolium. These data suggest that coupling distance between VGCCs and vesicles determines VGCC dependence of spontaneous release at tightly coupled synapses, yet VGCC contribution can be achieved indirectly at loosely coupled synapses.
In this study, we propose an efficient sorting method for encrypted data using fully homomorphic encryption (FHE). The proposed method extends the existing 2-way sorting method by applying the k-way sorting network for any prime k to reduce the depth in terms of comparison operation from O(log <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> n) to O(klog <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> n), thereby improving performance for k slightly larger than 2, such as k=5. We apply this method to approximate FHE which is widely used due to its efficiency of homomorphic arithmetic operations. In order to build up the k-way sorting network, the k-sorter, which sorts k-numbers with a minimal comparison depth, is used as a building block. The approximate homomorphic comparison, which is the only type of comparison working on approximate FHE, cannot be used for the construction of the k-sorter as it is because the result of the comparison is not binary, unlike the comparison in conventional bit-wise FHEs. To overcome this problem, we propose an efficient k-sorter construction utilizing the features of approximate homomorphic comparison. Also, we propose an efficient construction of a k-way sorting network using cryptographic SIMD operations. To use the proposed method most efficiently, we propose an estimation formula that finds the appropriate k that is expected to reduce the total time cost when the parameters of the approximating comparisons and the performance of the operations provided by the approximate FHE are given. We also show the implementation results of the proposed method, and it shows that sorting 5 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sup> = 15625 data using 5-way sorting network can be about 23.3% faster than sorting 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">14</sup> = 16384 data using 2-way.
This paper proposes a disturbance observer-based robust model predictive control (MPC) for a voltage sensorless grid-connected inverter with an inductive-capacitive-inductive (LCL) filter. A full-state estimator and a grid voltage observer are designed to reduce the number of sensors. A lumped disturbance observer, considering the parameter mismatch along with the grid impedance variation, is also designed to eliminate the steady-state error. A cost function, which consists of the error state and control input, is employed in the MPC design. Based on the Lyapunov stability, the full-state observer, voltage estimation, lumped disturbance observer, and the robust controller gains are obtained by solving an optimization problem based on linear matrix inequality (LMI). A frequency response analysis of the entire system is conducted to verify the reference tracking and disturbance rejection outcomes. As a result, the state and grid voltage observer outcomes converge to the actual values as rapidly as possible. The effectiveness of the proposed control method is demonstrated in comparison with the proportional-integral (PI) approach and with a controller recently proposed in the literature. Simulation and experimental results are presented to verify the effectiveness of the proposed method under LCL parameter uncertainties and grid impedance variations.
With the recent development of Internet of Things (IoT) in the next generation Cyber-Physical System (CPS) such as autonomous driving, there is a significant requirement of big data analysis with a high accuracy and a low latency. For efficient big data analysis, Deep Learning (DL) supports strong analytic capability; it has been applied at the cloud and edge layers by extensive research to provide accurate data analysis at low latency. However, existing researches failed to address certain challenges, such as centralized control, adversarial attacks, security, and privacy. To this end, we propose DeepBlockIoTNet, a secure DL approach with blockchain for the IoT network wherein the DL operation is carried out among the edge nodes at the edge layer in a decentralized, secure manner. The blockchain provides a secure DL operation and removes the control from a centralized authority. The experimental evaluation demonstrates that the proposed approach supports higher accuracy.
The aim of the study involves accelerating ultrafast electrochemical behavior of lithium‐ion batteries (LIBs) by proposing hierarchical core/shell heterostructure of carbon nanofiber (CNF)/3D interconnected hybrid network with nanocarbon and fluorine‐doped tin oxide (FTO) nanoparticles (NPs) via a one‐pot process of horizontal ultrasonic spray pyrolysis deposition. This is constructed via a pyrolysis reaction of ketjen black forming 3D interconnected FTO NPs covered with nanocarbon network on CNF. It offers fast electrical conductivity to the overall electrode with improved Li ion diffusion due to decreased size effect and relaxed structural variation of FTO NPs via nanocarbon network, leading to high discharge capacity (868.7 mAh g⁻¹ after 100 cycles) at 100 mA g⁻¹ and superior rate capability. Nevertheless, at extremely high current density (2000 mA g⁻¹), significant ultrafast electrochemical performances with reversible discharge capacity (444.4 mAh g⁻¹) and long‐term cycling retention (89.9% after 500 cycles) are noted. This is attributed to the novel effects of 3D interconnected hybrid network accelerating receptive capacity of Li ions into the FTO NPs via nanocarbon network, delivery of formed Li ions and electrons by hybrid network with FTO NP and nanocarbon, and prevention of FTO NP pulverization from CNFs via nanocarbon network. Therefore, the proposed heterostructure holds significant promise for effective development of ultrafast anode material for enhancing the practical applications of LIBs.
Chameleon tongue-like manipulators have the potential to be quite useful for mobile systems to overcome access issues by allowing them to reach distant targets in an instant. For example, a quadrotor with this manipulator will be able to snatch distant targets instead of hovering and picking up. In this letter, we present a chameleon-inspired shooting and rapidly retracting manipulator, which is lightweight, compact, and ultimately suitable for mobile systems. To make this possible, two design strategies are proposed: to use a wind-up spring as an energy source and to employ an active clutch to selectively distribute the energy. The wind-up spring enables the device to keep supplying the stored energy for a long time, compared to normal torsion springs. The active clutch controls the direction and the timing of the energy supply, which allows to deploy and retract the end-effector. Thanks to these design strategies, the device achieves snatching manipulation while maintaining compact and lightweight. In result, the Snatcher has a size of 120x85x85mm, weighs 117.48g, and brings a 30g mass located at 0.8m away within 600ms.
The topical delivery of siRNA‐based therapies has opened new avenues for the treatment of skin disorders. The use of siRNA as a therapeutic, however, is limited due to its rapid degradation and poor cellular uptake. Furthermore, the top layer of skin, the stratum corneum, is a major barrier to the delivery of topical agents. There is an unmet need for efficient topical formulations for delivering siRNA to the site of action. In this study, we used 1,2‐dioleoyl‐3‐trimethylammonium‐propane (DOTAP) or lipofectamine to prepare a nanocarrier for delivering siRNA against glyceraldehyde 3‐phosphate dehydrogenase (GAPDH); GAPDH expression was then evaluated at the cellular level. In addition, a dermal transport assay was designed and implemented to evaluate the penetration and delivery efficacy of siRNA in pig skin using lipid nanocarriers. The delivery of siRNA with the use of a lipid nanocarrier was significantly better than the delivery of siRNA without it. Thus, Our findings identify lipid nanocarriers as excellent candidates for the transdermal delivery of siRNA for gene silencing in the skin and thus for applications in related preclinical models.
The CaseCrawler is a lightweight and low-profile movable platform with a high payload capacity; it is capable of crawling around carrying a smartphone. The body of the robot resembles a phone case but it has crawling legs stored in its back. It is designed with a deployable, in-plane transmission that is capable of crawling locomotion. The CaseCrawler's leg structure has a knee joint that can passively bend only in one direction; this allows it to sustain a load in the other direction. This anisotropic leg allows a crank slider to be used as the main transmission for generating the crawling motion; the crank slider generates a motion only within a 2D plane. The crank slider deploys the leg when the slider is pushed and retracts it when pulled; this enables a low-profile case that can fully retract the legs flat. Furthermore, by being restricted to swinging within a plane, the hip joint is highly resistant to off-axis deformation, this results in a high payload capacity. As a result, the CaseCrawler has a body thickness of 16mm (the transmission without the gearbox is only 1.5mm) and a total weight of 22.7g; however, it can carry a load of over 300g, which is 13 times its own weight. To show the feasibility of the robot for use in real-world applications, in this study, the CaseCrawler was employed as a movable platform that carries a 190g mass, including a smartphone and its cover. This robot can crawl around with the smartphone to enable the phone to charge itself on a wireless charging station. In the future, if appropriate sensing and control functions are implemented, the robot will be able to collect data or return to the owner when needed.
This paper describes flat yarn‐based polyethylene terephthalate (PET) fabrics as substrates for screen printing conductive inks. We investigate the effect of the screen‐printing parameters such as the screen mesh size (70 or 120 pixels/inch) and the number of printing cycles. The uniformity of the screen‐printed layers and their electrical properties are directly related to the yarn shape, substrate roughness, and printing conditions. Minimum average sheet resistance of 16 ± 3 mΩ/sq is achieved on the flat‐yarn PET fabrics, and there is little change in the electrical performance after 1,000 bending cycles. To demonstrate the impact of yarn shape on an E‐textile application, we fabricate wearable antennas using the screen‐printed PET fabrics. The antenna was designed to operate at 2.4 GHz, which is a widely used unlicensed frequency for public wireless LAN services, Bluetooth, and radio frequency identification (RFID) services. We analyze the effects of the uniformity and conductivity of the printed layers on the antenna performance. In open‐area field tests, the textile antennas show better performance than commercial antennas. The results of this study will help improve the understanding of how the ink/substrate interface affects the screen‐printing process and to advance the manufacturing technology for conductive patterns. This article is protected by copyright. All rights reserved.
Knee injuries at risk of post-traumatic knee osteoarthritis (PTOA) and knee osteoarthritis (OA) are closely associated with knee transverse plane and/or frontal plane instability and excessive loading. However, most existing training and rehabilitation devices involve mainly movements in the sagittal plane. An offaxis elliptical training system was developed to train and evaluate neuromuscular control about the off-axes (knee varus/valgus and tibial rotation) as well as the main flexion/extension axis (sagittal movements). Effects of the offaxis elliptical training systemin improving either transverse or frontal neuromuscular control depending on subjects’ need (Pivoting group, Sliding group) were demonstrated through 6 week subject-specific neuromuscular training on subjects with knee injuries at risk of PTOA or medial knee osteoarthritis. The combined pivoting and sliding group, named as offxis group demonstrated significant reduction in pivoting instability, minimum pivoting angle, and sliding instability. The pivoting group showed more reduction in pivoting instability, maximum and minimum pivoting angle than the sliding group. On the other hand, the sliding group showed more reduction in sliding instability, maximum and minimum sliding distance than the pivoting group. Based on these findings, the offaxis elliptical trainer system can potentially be used as a therapeutic and research tool to train human subjects for plane-dependent improvements for their neuromuscular control during functional weight-bearing stepping movements.
Internet of Things (IoT) technology provides the basic infrastructure for a hyper connected society where all things are connected and exchange information through the Internet. IoT technology is fused with 5G and artificial intelligence (AI) technologies for use various fields such as the smart city and smart factory. As the demand for IoT technology increases, security threats against IoT infrastructure, applications, and devices have also increased. A variety of studies have been conducted on the detection of IoT malware to avoid the threats posed by malicious code. While existing models may accurately detect malicious IoT code identified through static analysis, detecting the new and variant IoT malware quickly being generated may become challenging. This paper proposes a dynamic analysis for IoT malware detection (DAIMD) to reduce damage to IoT devices by detecting both well-known IoT malware and new and variant IoT malware evolved intelligently. The DAIMD scheme learns IoT malware using the convolution neural network (CNN) model and analyzes IoT malware dynamically in nested cloud environment. DAIMD performs dynamic analysis on IoT malware in a nested cloud environment to extract behaviors related to memory, network, virtual file system, process, and system call. By converting the extracted and analyzed behavior data into images, the behavior images of IoT malware are classified and trained in the Convolution Neural Network (CNN). DAIMD can minimize the infection damage of IoT devices from malware by visualizing and learning the vast amount of behavior data generated through dynamic analysis.
The hybrid precoding and combining algorithms for mmWave massive multiple-input multiple-output (MIMO) systems must consider the trade-off between the complexity and performance of the system. Unfortunately, because of the unit-norm constraint imposed by the use of phase shifters, the optimization of the radio frequency (RF) precoder and combiner becomes a non-convex problem. As a consequence, the algorithm for hybrid precoding and combining design often incurs high complexity. This paper proposes a dictionary-constrained low-complexity algorithm for hybrid precoding and combining design. The proposed algorithm considers a decoupled optimization scheme between the RF and baseband domains for the spectral efficiency-maximization problem. In the RF domain, we propose an incremental successive selection method to find a subset of array response vectors from a dictionary, which forms the RF precoding/combining matrices. For the digital domain, we employ singular-value decomposition (SVD) of the low-dimensional effective channel matrix to generate the digital baseband precoder and combiner. Through numerical simulation, we show that the proposed algorithm achieves near-optimal performance while providing approximately up to 99% complexity reduction compared to the conventional hybrid precoding and combining algorithms.
Smart wearable electronics that are fabricated on light‐weight fabrics or flexible substrates are considered to be of next‐generation and portable electronic device systems. Ideal wearable and portable applications not only require the device to be integrated into various fiber form factors, but also desire self‐powered system in such a way that the devices can be continuously supplied with power as well as simultaneously save the acquired energy for their portability and sustainability. Nevertheless, most of all self‐powered wearable electronics requiring both the generation of the electricity and storing of the harvested energy, which have been developed so far, have employed externally connected individual energy generation and storage fiber devices using external circuits. In this work, for the first time, a hybrid smart fiber that exhibits a spontaneous energy generation and storage process within a single fiber device that does not need any external electric circuit/connection is introduced. This is achieved through the employment of asymmetry coaxial structure in an electrolyte system of the supercapacitor that creates potential difference upon the creation of the triboelectric charges. This development in the self‐charging technology provides great opportunities to establish a new device platform in fiber/textile‐based electronics. A self‐charging fiber‐based device is realized by coupling between triboelectric and electrochemical effects. This is attributed to the structural engineering of the fiber device, which leads to the inducing of the potential difference to ionize an electrolyte by harnessing surrounding mechanical energy. The self‐charging fiber device provides great opportunities to establish new generation wearable electronics.
The morphology of conjugated polymers has critical influences on electronic and optical properties of optoelectronic devices. Even though lots of techniques and methods are suggested to control the morphology of polymers, very few studies have been performed inducing high charge transport along out‐of‐plane direction. In this study, the self‐assembly of homo‐ and blended conjugated polymers which are confined in nanostructures is utilized. The resulting structures lead to high charge mobility along vertical direction for both homo‐ and blended conjugated polymers. Both semicrystalline and amorphous polymers show highly increased population of face‐on crystallite despite intrinsic crystallinity of polymers. They result in more than two orders of magnitude enhanced charge mobility along vertical direction revealed by nanoscale conductive scanning force microscopy and macroscale IV characteristic measurements. Moreover, blends of semicrystalline and amorphous polymers, which are known to show inferior optical and electrical properties due to their structural incompatibility, are formed into harmonious states by this approach. Assembly of blends of semicrystalline and amorphous polymers under nanoconfinement shows charge mobility in out‐of‐plane direction of 0.73 cm2 V−1 s−1 with wide range of absorption wavelength from 300 to 750 nm demonstrating the synergistic effects of two different polymers. Versatilility of nanoconfinement on homo‐ and blended semiconducting polymers is demonstrated. Significantly enhanced crystallinity with face‐on orientation leads to more than two magnitudes higher charge mobilities along vertical direction for both semicrystalline and amorphous polymers. Moreover, blends of polymers, which are known to show inferior optical and electrical properties due to their structural incompatibility, are formed into harmonious states.
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Seoul, South Korea