Search Results (12,802)

This paper introduces a novel capacitive sensor array designed for tactile perception applications. Utilizing an all-in-one inkjet deposition printing process, the sensor array exhibited exceptional flexibility and accuracy. With a resolution of up to 32.7 dpi, the sensor array was capable of capturing the fine details of touch inputs, making it suitable for applications requiring high spatial resolution. The design incorporates two multiplexers to achieve a scanning rate of 100 Hz, ensuring the rapid and responsive data acquisition that is essential for real-time feedback in interactive applications, such as gesture recognition and haptic interfaces. To evaluate the performance of the capacitive sensor array, an experiment that involved handwritten number recognition was conducted. The results demonstrated that the sensor accurately captured fingertip inputs with a high precision. When combined with an Auxiliary Classifier Generative Adversarial Network (ACGAN) algorithm, the sensor system achieved a recognition accuracy of 98% for various handwritten numbers from “0” to “9”. These results show the potential of the capacitive sensor array for advanced human–computer interaction applications. Full article

We focus on dual-user operation, where two users control a single remote robot equipped with a force sensor using haptic interface devices. We employ a cooperative work in which the two users control the remote robot to collaborate with remote robot systems with force feedback to carry an object. By measuring the force acting upon the object, we aim to better understand the underlying mechanisms by which the user with lower network latency can help the other user, as observed in our previous work. We notice that with increasing network delays, the force exerted on the object tends to intensify, indicating that it becomes more challenging for users to operate the remote robot effectively as network delays increase. We also measure the force applied to the object by changing the network delays between the remote robot and the two users to clarify why the user with the lower network delay can assist the other user. We find that when the total network delay is the same, the average force magnitude and the average maximum force magnitude remain nearly identical. This is because, despite the challenges faced by the user with the larger network delay, the user with the smaller delay can operate the remote robot more easily and assist the other user. In order to reduce the force acting upon the object, we propose an enhancement method for the robot position control, which determines the position of the remote robot arm while accounting for network delay, and investigate the effects by experiment. Experimental results demonstrate that our proposed method is effective and can reduce the applied force. This is because the proposed method adjusts the ratio between the user with the lower delay and the user with the higher delay. The user with the lower delay can operate the remote robot more easily and respond to it more quickly. Our findings and proposed method can be useful in improving work accuracy and operability when designing a remote robot system with force feedback for applications. Full article

The Arabic language has gained significant global recognition, with a growing number of non-Arab individuals learning it as a second language. Despite this trend, learners of Arabic face various challenges that have not been thoroughly examined. This study aimed to investigate the challenges encountered by learners of the Arabic language and to determine the factors that contribute to effective language learning and use. Data from 444 non-native speakers learning Arabic as a second language were analyzed with SPSS 27using a descriptive approach. The results indicated that Arabic instructors should focus on improving feedback practices, developing customized curricula, and incorporating technology and multimedia resources into their teaching methods. Furthermore, this study highlights the importance of integrating cultural components and accommodating diverse learners in the classroom. To improve speaking proficiency, learners can engage in activities such as listening to radio broadcasts, collaborating with classmates, and building relationships with Arabic-speaking friends. The results of this research provide insights that can assist instructors of Arabic as a second language in supporting learners, improving their abilities to learn and communicate in Arabic. Full article

Growth-factor-induced cell signaling plays a crucial role in development; however, negative regulation of this signaling pathway is important for sustaining homeostasis and preventing diseases. SPROUTY2 (SPRY2) is a potent negative regulator of receptor tyrosine kinase (RTK) signaling that binds to GRB2 during RTK activation and inhibits the GRB2-SOS complex, which inhibits RAS activation and attenuates the downstream RAS/ERK signaling cascade. SPRY was formerly discovered in Drosophila but was later discovered in higher eukaryotes and was found to be connected to many developmental abnormalities. In several experimental scenarios, increased SPRY2 protein levels have been observed to be involved in both peripheral and central nervous system neuronal regeneration and degeneration. SPRY2 is a desirable pharmaceutical target for improving intracellular signaling activity, particularly in the RAS/ERK pathway, in targeted cells because of its increased expression under pathological conditions. However, the role of SPRY2 in brain-derived neurotrophic factor (BDNF) signaling, a major signaling pathway involved in nervous system development, has not been well studied yet. Recent research using a variety of small-animal models suggests that SPRY2 has substantial therapeutic promise for treating a range of neurological conditions. This is explained by its function as an intracellular ERK signaling pathway inhibitor, which is connected to a variety of neuronal activities. By modifying this route, SPRY2 may open the door to novel therapeutic approaches for these difficult-to-treat illnesses. This review integrates an in-depth analysis of the structure of SPRY2, the role of its major interactive partners in RTK signaling cascades, and their possible mechanisms of action. Furthermore, this review highlights the possible role of SPRY2 in neurodevelopmental disorders, as well as its future therapeutic implications. Full article

This contribution examines the control problem for very large wind energy converters during shutdown operation and analyses the most important control approaches. The control methods make use of the built-in conventional control infrastructure, but control system reconfigurations are undertaken in order to meet the demands of the shutdown control operation. Hence, the torque controller as well as the collective pitch controller (CPC) are redesigned from their regulator functions to reference tracking control systems with constraints. In addition, the CPC is combined with a feedforward controller in order to gain responsiveness. Constraints in magnitude and rate are managed by a modified anti-windup mechanism. Simulations of a 20 MW reference wind turbine verify the performance of the approaches. Full article

There are ongoing debates globally regarding excessive executive compensation, the perceived weak link between pay and performance, and the widening inequality gap. The South African corporate governance code King IV’s Principle 14 addresses the need for fair, responsible, and transparent remuneration. At the same time, the newly enacted Companies Amendment Act No. 16 of 2024 in South Africa emphasizes transparency in compensation, shareholder voting, and responding to shareholder feedback. This study conducts a systematic literature review of 30 articles on the transparency of executive remuneration disclosures and their determinants by analyzing Scopus-indexed articles published between 2010 and 2023, selected through specific keyword searches. The findings suggest an increasing focus on research regarding the disclosure of executive compensation, predominantly conducted in the Global North and primarily framed through agency theory. Studies exploring the factors influencing executive remuneration and the relationship between pay and performance are prevalent, with mixed results generally indicating a positive connection. Firm size emerges as a key factor in transparency, and many studies employ binary scoring to evaluate whether executive compensation disclosure is present. This paper provides valuable insights for investors, analysts, and policymakers and adds to the current understanding of executive remuneration transparency. Full article

Educational chatbots (ECs) can offer instructional feedback to enhance learning. However, the effect of metacognitive feedback on science education has not been fully explored. This study focuses on the effect of the EC with metacognitive feedback on students’ knowledge retention, transfer, and intrinsic motivation in the field of biology science. A between-group experimental design with 62 college students was conducted. Students in the experiment group received metacognitive feedback, whereas students in the control group received no feedback. The results of the ANCOVA test showed that students in the experiment group demonstrated better knowledge retention and transfer than those in the control group (F = 13.11, p = 0.001; F = 14.39, p < 0.001). Further, students in the experiment group reported more learning interest and higher perceived competence and value than those in the control group (F = 3.72, p = 0.001; F = 1.91, p = 0.009; F = 2.70, p = 0.004). In addition, correlation analysis revealed that perceived competence in the metacognitive feedback group was positively related to knowledge transfer (r = 0.39, p = 0.032). However, there was no significant difference in perceived pressure between both groups (p = 0.203). This study highlights the potential of the EC with metacognitive feedback for science learning. Full article

Traditional Chinese medicinal herbs have strict environmental requirements and are highly susceptible to weed damage, while conventional herbicides can adversely affect their quality. Laser weeding has emerged as an effective method for managing weeds in precious medicinal herbs. This technique allows for precise weed removal without chemical residue and protects the surrounding ecosystem. To maximize the effectiveness of this technology, accurate detection and localization of weeds in the medicinal herb fields are crucial. This paper studied seven species of weeds in the field of Dictamnus dasycarpus, a traditional Chinese medicinal herb. We propose a lightweight YOLO-Riny weed-detection algorithm and develop a YOLO-Riny-ByteTrack Multiple Object Tracking method by combining it with the ByteTrack algorithm. This approach enables accurate detection and localization of weeds in medicinal fields. The YOLO-Riny weed-detection algorithm is based on the YOLOv7-tiny network, which utilizes the FasterNet lightweight structure as the backbone, incorporates a lightweight upsampling operator, and adds structure reparameterization to the detection network for precise and rapid weed detection. The YOLO-Riny-ByteTrack Multiple Object Tracking method provides quick and accurate feedback on weed identification and location, reducing redundant weeding and saving on laser weeding costs. The experimental results indicate that (1) YOLO-Riny improves detection accuracy for Digitaria sanguinalis and Acalypha australis, ultimately amounting to 5.4% and 10%, respectively, compared to the original network. It also diminishes the model size by 2 MB and inference time by 10 ms, making it more suitable for resource-constrained edge devices. (2) YOLO-Riny-ByteTrack enhances Multiple Object Tracking accuracy by 3%, reduces ID switching by 14 times, and improves overall tracking accuracy by 3.4%. The proposed weed-detection and localization method for Dictamnus dasycarpus offers fast detection speed, high localization accuracy, and stable tracking, supporting the implementation of laser weeding during the seedling stage of Dictamnus dasycarpus. Full article

Cavitation is a disadvantageous phenomenon that occurs when fluid pressure drops below its vapor pressure. Under these conditions, bubbles form in the fluid. When these bubbles flow into a high-pressure area or tube, they erupt, causing harm to mechanical parts such as centrifugal pumps. The difference in pressure in a fluid is the result of varying temperatures. One way to eliminate cavitation is to reduce the radius of the bubbles to zero before they reach high-pressure areas, using a robust approach. In this paper, sliding mode control is used for this purpose due to its invariance property. To force the radius of the bubbles toward zero and prevent chattering, a new dynamic sliding mode control approach is used. In dynamic sliding mode control, chattering is removed by passing the input control through a low-pass filter, such as an integrator. A general model of the spherical bubble is used, transferred to the state space, and then a state proportional-integral feedback is applied to obtain a linear system with a new input control signal. A comparison is also made with traditional sliding mode control using state feedback, providing a trusted comparison. Full article

This paper presents the design of a robust speed controller for brushless DC motors (BLDCMs) under field-oriented control (FOC). The proposed robust controller integrates extension theory (ET) and sliding mode theory (SMT) to achieve robustness. First, the speed difference between the speed command and the actual speed of the BLDCM, along with the rate of change of the speed difference, are divided into 20 interval categories. Then, the feedback speed difference and the rate of change of the speed difference are calculated for their extension correlation with each of the 20 interval categories. The interval category with the highest correlation is used to determine the appropriate control gain for the sliding mode speed controller. This gain adjustment tunes the parameters of the sliding surface in the SMT, thereby suppressing the overshoot of the motor’s speed. Because a sliding surface reaching law of the sliding mode controller (SMC) adopts the exponential approach law (EAL), the system’s speed response can quickly follow the speed command in any state and exhibit an excellent load regulation response. The simplicity of this robust control method, which requires minimal training data, facilitates its easy implementation. Finally, the speed control of the BLDCM is simulated using Matlab/Simulink software (2023b version), and the results are compared with those of the SMC using the constant-speed approach law (CSAL). The simulation and experimental results demonstrate that the proposed robust controller exhibits superior speed command tracking and load regulation responses compared to the traditional SMC. Full article

The disturbance in river ecosystems caused by reservoirs and dams has become a critical topic, attracting increasing attention. However, the extent to which reservoir and dam construction and operation impact downstream river ecosystem health and ecosystem service functions is not fully understood. This research examines the Xiaolangdi Reservoir and the Lower Yellow River (LYR) ecosystem in China as a case study. We analyzed the complex material and energy flows in the LYR ecosystem using emergy theory and developed a set of emergy-based indicators for the quantitative assessment of river ecosystem health and services under reservoir operation interference. The results indicate that the total natural capital and environmental endowments of the LYR ecosystem have remained relatively stable after the operation of the Xiaolangdi Reservoir, with an increase in renewable emergy input. The ecosystem’s vigor decreased slightly, while the biomass emergy diversity index remained stable. However, the total emergy inputs increased significantly, with external feedback inputs becoming the most important emergy source for the LYR ecosystem. The resilience of the LYR ecosystem improved, with a significant increase in emergy density and a decrease in the emergy sustainability index. These findings suggest that although the river ecosystem continues to provide supporting services to human society, the extent of these services has diminished compared to pre-perturbation levels. In this research, a methodology for analyzing the impact of key reservoir operations on the ecosystem health and services of a large river is proposed to provide support for large river sustainable development studies. Full article

Background: Individuals with Autism Spectrum Disorder (ASD) frequently encounter increased levels of anxiety and display resistant behaviors during dental examinations, which negatively affects their oral care and maintenance. This study employed a cross-sectional design to evaluate the impact of virtual reality (VR) intervention on the anxiety and level of cooperation in children and adolescents with ASD during dental examinations. Methods: A total of 140 participants diagnosed with ASD, aged from 4- to 18-years-old, were selected from two specialized ASD management centers in Riyadh/Saudi Arabia. The participants were randomly allocated into either the control group or the VR group. Control group participants were subjected to a conventional dental examination, while the VR group utilized VR intervention to immerse themselves in a simulated natural and soothing environment. The Venham anxiety and behavior scale (VABS) was utilized to measure anxiety levels, while the Frankl behavior rating scale (FBRS) was employed to assess the level of cooperation. Data were analyzed using a Mann–Whitney U test with a significance level of p < 0.05. Results: The baseline anxiety and level of cooperation between the groups were comparable (p > 0.05). During the dental examination, the VR group had significantly reduced anxiety scores (2.48 ± 1.76) compared to the control group (1.50 ± 1.74) (p < 0.001). Regarding the level of cooperation, the VR group exhibited significantly greater levels of cooperation (3.41 ± 0.96) than the control group (2.86 ± 1.03) (p = 0.002). Conclusions: These findings suggest that VR intervention is a successful technique for decreasing anxiety and enhancing cooperation among children with ASD during dental examination. Integrating VR technology in dental environments can potentially improve the dental experience and results for children diagnosed with ASD. Full article

Spam reviews pose a significant challenge to the integrity of online platforms, misleading consumers and undermining the credibility of genuine feedback. This paper introduces an innovative AI-generated spam review detection framework that leverages Deep Learning algorithms and Natural Language Processing (NLP) techniques to identify and mitigate spam reviews effectively. Our framework utilizes multiple Deep Learning models, including Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, Gated Recurrent Unit (GRU), and Bidirectional LSTM (BiLSTM), to capture intricate patterns in textual data. The system processes and analyzes large volumes of review content to detect deceptive patterns by utilizing advanced NLP and text embedding techniques such as One-Hot Encoding, Word2Vec, and Term Frequency-Inverse Document Frequency (TF-IDF). By combining three embedding techniques with four Deep Learning algorithms, a total of twelve exhaustive experiments were conducted to detect AI-generated spam reviews. The experimental results demonstrate that our approach outperforms the traditional machine learning models, offering a robust solution for ensuring the authenticity of online reviews. Among the models evaluated, those employing Word2Vec embeddings, particularly the BiLSTM_Word2Vec model, exhibited the strongest performance. The BiLSTM model with Word2Vec achieved the highest performance, with an exceptional accuracy of 98.46%, a precision of 0.98, a recall of 0.97, and an F1-score of 0.98, reflecting a near-perfect balance between precision and recall. Its high F2-score (0.9810) and F0.5-score (0.9857) further highlight its effectiveness in accurately detecting AI-generated spam while minimizing false positives, making it the most reliable option for this task. Similarly, the Word2Vec-based LSTM model also performed exceptionally well, with an accuracy of 97.58%, a precision of 0.97, a recall of 0.96, and an F1-score of 0.97. The CNN model with Word2Vec similarly delivered strong results, achieving an accuracy of 97.61%, a precision of 0.97, a recall of 0.96, and an F1-score of 0.97. This study is unique in its focus on detecting spam reviews specifically generated by AI-based tools rather than solely detecting spam reviews or AI-generated text. This research contributes to the field of spam detection by offering a scalable, efficient, and accurate framework that can be integrated into various online platforms, enhancing user trust and the decision-making processes. Full article

Manual ventilation, most commonly with a bag-valve mask, is a form of short-term ventilation used during resuscitative efforts in emergent and out-of-hospital scenarios. However, compared to mechanical ventilation, manual ventilation is an operator-dependent skill that is less well controlled and is highly subject to providing inappropriate ventilation to the patient. This article first reviews recent manual ventilation guidelines set forth by the American Heart Association and European Resuscitation Council for providing appropriate manual ventilation parameters (e.g., tidal volume and respiratory rate) in different patient populations in the setting of cardiopulmonary resuscitation. There is then a brief review of clinical and manikin-based studies that demonstrate healthcare providers routinely hyperventilate patients during manual ventilation, particularly in emergent scenarios. A discussion of the possible mechanisms of injury that can occur during inappropriate manual hyperventilation follows, including adverse hemodynamic alterations and lung injury such as acute barotrauma, gastric regurgitation and aspiration, and the possibility of a subacute, inflammatory-driven lung injury. Together, these injurious processes are described as manual-ventilation-induced lung injury (MVILI). This review concludes with a discussion that highlights recent progress in techniques and technologies for minimizing manual hyperventilation and MVILI, with a particular emphasis on tidal-volume feedback devices. Full article

When traditional grid-forming converters directly participate in the grid-connected operation of the power grid, due to the lack of a pre-synchronization control system, the voltage amplitude and initial phase on both sides of the grid-connected point will deviate, resulting in voltage and current distortion during grid-connected mode. An active support phase-locked loop free pre-synchronization control strategy based on the third-order model of a synchronous generator is proposed to address the grid-connected problem of the grid-forming converter mentioned above. First, a model of active support control with frequency integral feedback at small signal levels was constructed. The root locus method was employed to examine how system parameters affect the stability of the active support control system. Second, by adding phase pre-synchronization controllers and amplitude pre-synchronization controllers to the active frequency loop and excitation voltage loop of the third-order model, it was ensured that the frequency, phase, and voltage amplitude of the unit are consistent with the power grid, achieving a fast and smooth grid-connected mode of the unit. Finally, by using a DC source to simulate all types of new energy power generation equipment, the active support pre-synchronization control system based on the three-order model of synchronous generator is built in the MATLAB/Simulink simulation environment, and the accuracy and effectiveness of the control strategy in this paper is verified. Full article