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AbstractThis paper provides a comprehensive analysis of the undrained failure envelope for embedded foundations in anisotropic clays. Using the AUS failure criterion as the soil strength model, the study examines how the anisotropic strength (re) and embedment depth (D/B) affect the behavior of the footing under combined loading conditions. Failure envelopes are assessed via two-dimensional finite element limit analysis (2D FELA) in both 2D and 3D spaces. This research highlights the failure mechanisms of embedded foundations, offering valuable insights into the engineering design of footings in anisotropic clays subjected to combined loads (V, H, M). Furthermore, this study introduces an advanced soft-computing approach by creating a machine learning model that leverages the adaptive neuro-fuzzy inference system (ANFIS) integrated with the particle swarm optimization (PSO) algorithm to predict the failure envelope of embedded footings, highlighting the novelty and original of this study. The optimised ANFIS model has been validated and demonstrates a strong correlation with the numerical FELA results, offering engineers a valuable tool for determining the failure envelope of embedded foundations in anisotropic clay under different loading scenarios (V, H, M). [ABSTRACT FROM AUTHOR]

The stress status of a soil pressure cell placed in soil is very different from its stress state in a uniform fluid medium. The use of the calibration coefficient provided by the soil pressure cell manufacturer will produce a large error. In order to improve the measurement accuracy of the interface-type earth pressure cell placed in soil, this paper focuses on a single-membrane resistive earth pressure cell installed on the surface of a structure, analyzing the influence of loading and unloading cycles, the thickness and particle size of the sand filling, and the depth of the earth pressure cell inserted in the structure on the calibration curve and matching error, which were analyzed through calibration tests. The results show that when the sand filling thickness is less than D (D is the diameter of the earth pressure cell), the calibration curve is unstable in relation to the increase in the number of loading and unloading cycles, which will cause the sand calibration coefficient used for stress conversion to not be used normally. When the sand filling thickness in the calibration bucket increases from 0.285D to 5D, the absolute value of the matching error first decreases and then increases, such that the optimal sand filling thickness is 3D. The output of the earth pressure cell increases with the decrease in sand particle size under the same load, and there is a significant difference between the theoretical calculation value and the experimental value of the matching error; aiming at this difference, an empirical formula is derived to reflect the ratio of the diameter of the induction diaphragm of the earth pressure cell to the maximum particle size of the sand filling. When the depth of the earth pressure cell inserted in the structure is "0", the sensing surface is flush with the structure and the absolute value of the matching error is the smallest. Changes in the horizontal placement of the soil pressure cell in the calibration bucket result in significant differences in both the output and hysteresis of the calibration curve. To improve the measurement accuracy of soil pressure cells in scaled tests for applications such as in the retaining walls of excavation pits, tunnel outer surfaces, pile tops, pile ends, and soil pressure measurements in soil, calibration of the soil pressure cells is required before testing. Due to the considerable difference in the stress states of the soil pressure cell between granular media and uniform fluid media, calibration in soil is essential. During in-soil calibration, factors such as cyclic loading and unloading, soil compression, sand thickness and particle size, and the placement of the soil pressure cell all affect the calibration results. This paper primarily investigates the influence of these factors on the calibration curve and matching error. This study found that, as the sand thickness increases, the matching error decreases initially and then increases. [ABSTRACT FROM AUTHOR]

Flexible sensor arrays have attracted extensive attention in human‐computer interaction. However, realizing high‐performance sensor units with programmable properties, and expanding them to multi‐pixel flexible arrays to maintain high sensing consistency is still struggling. Inspired by the contact behavior of octopus antenna, this paper proposes a programmable multistage dome structure‐based flexible sensing array with robust sensing stability and high array consistency. The biomimetic multistage dome structure is pressurized to gradually contact the electrode to achieve high sensitivity and a large pressure range. By adjusting the arrangement of the multistage dome structure, the pressure range and sensitivity can be customized. More importantly, this biomimetic structure can be expanded to a multi‐pixel sensor array at the wafer level with high consistency through scalable and high‐precision imprinting technologies. In the imprinting process, the conductive layer is conformally embedded into the multistage dome structure to improve the stability (maintain stability over 22 000 cycles). In addition, the braced isolation structure is designed to effectively improve the anti‐crosstalk performance of the sensor array (crosstalk coefficient: 26.62 dB). Benefitting from the programmable structural design and high‐precision manufacturing process, the sensor array can be customized and is demonstrated to detect human musculation in medical rehabilitation applications. [ABSTRACT FROM AUTHOR]

In this article, we explore the connections between two distinct approaches: experiential learning (EL) and 4E cognition. EL emphasizes the role of concrete experiences as the building blocks of learning, whereas 4E cognition views cognition as arising from the interactions that an individual has with their physical and social environment. Despite their divergent theoretical frameworks, methodologies, and interests, we argue that both frameworks share a common vision of cognition and that their integration could mutually enhance their respective fields. This article outlines the historical origins and underlying assumptions of both frameworks, highlighting the potential links that can be established between them. Specifically, we explore the significance of embodiment, embeddedness, extended cognition, and enactive processes in learning and cognition. To bridge these frameworks, we propose employing the concept of "concrete experience" as an active engagement of individuals with their physical and social surroundings. By encompassing the essential aspects assigned to concrete experiences in EL, as well as the embodiment, situatedness, extended cognition, and enactive features of 4E cognition, this notion serves as a unifying element. Ultimately, the article suggests that combining the insights from EL and 4E cognition can offer a richer, more holistic understanding of representation. [ABSTRACT FROM AUTHOR]

This paper proposes an embedded Internet of Things (IoT) system for bioreactor sensor integration, aimed at optimizing temperature and turbidity control during cell cultivation. Utilizing an ESP32 development board, the system makes advances on previous iterations by incorporating superior analog-to-digital conversion capabilities, dual-core processing, and integrated Wi-Fi and Bluetooth connectivity. The key components include a DS18B20 digital temperature sensor, a TS-300B turbidity sensor, and a Peltier module for temperature regulation. Through real-time monitoring and data transmission to cloud platforms, the system facilitates advanced process control and optimization. The experimental results on yeast cultures demonstrate the system's effectiveness at maintaining optimal growth, highlighting its potential to enhance bioprocessing techniques. The proposed solution underscores the practical applications of the IoT in bioreactor environments, offering insights into the improved efficiency and reliability of culture cultivation processes. [ABSTRACT FROM AUTHOR]

A new architectural approach to real-time embedded programming is described. A bare-metal program is written in C/C++ and combines event-driven technique with concurrency based on co-routines. Events are processed by soft real-time core at the priority level of software generated interrupts. Event is first posted to input queue of the core and then processed by invocation of its event handler. A special case of event is co-routine, its resumable function being a co-routine event handler. The co-routine that either yielded or needs to be resumed is queued for event processing once again. As a result, it is processed multiple times until execution of resumable function comes to the end of its operator sequence. Different levels of processing priority may be assigned to an event. Soft real-time core could be further expanded to run on symmetrical multiprocessor hardware. A combination of co-routines and basic events could easily be used in fork/join model. Concurrency constructs resemble those of Go and occam languages. Virtually all classic types of synchronization primitives could be implemented. The new approach was implemented for various ARM and Blackfin processors in C++ language as portable DORSECC library. This library was further used to program real-time embedded systems for mass-produced banknote sorting machines. One type of systems was used to recognize and validate banknote images by the method of cascade of one-class classifiers. The other system worked as a motion controller and used finite automata to control sensors and actuators. The total number of systems in operation is currently over 20000. The event and co-routine core in these systems provides average event processing time in the range of dozens of microseconds with sub-microsecond overhead time per each event. [ABSTRACT FROM AUTHOR]

The rapid development of ISAs has brought the issue of software compatibility to the forefront in the embedded field. To address this challenge, one of the promising solutions is the adoption of a multiple-ISA processor that supports multiple different ISAs. However, due to constraints in cost and performance, the architecture of a multiple-ISA processor must be carefully optimized to meet the specific requirements of embedded systems. By exploring the RISC-V and ARM Thumb ISAs, this paper proposes RVAM16, which is an optimized multiple-ISA processor microarchitecture for embedded devices based on hardware binary translation technique. The results show that, when running non-native ARM Thumb programs, RVAM16 achieves a significant speedup of over 2.73× with less area and energy consumption compared to using hardware binary translation alone, reaching more than 70% of the performance of native RISC-V programs. [ABSTRACT FROM AUTHOR]

Copyright of Electric Drive for Locomotives is the property of Electric Drive for Locomotives Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the rapid development of computer technology and network communication technology, embedded micro control system has been widely used. It is crucial in the fields of large-scale chemical equipment, mechanized production base, transportation and future robots. Combined with the current Internet of Things technology, the equipment needs to be kept on the network during operation, real-time data comparison, data feedback, data reception and other network operations to provide strong help for human society. Focusing on the network communication level, due to the improvement of hardware and software technology, the basic link work has become the foundation part of realizing network communication, and the real problem is often the information transmission. For example, for wireless channel estimation and optimization based on embedded system, it is necessary to eliminate the interference of irresistible factors as far as possible, overview the defects in algorithm level and logic analysis level since the development of network communication technology, discuss the impact of network communication module of embedded monitoring system in practical application as far as possible, and make the error infinite to zero under the premise of unchanged hardware conditions. Based on the above conditions, the lightweight channel estimation method and the optimization under the condition of sparse matrix are proposed. This paper studies the network communication of embedded devices, especially the channel link in network communication, and focuses on the channel estimation algorithm. This paper proposes the advantages of LS and MMSE algorithms. According to the experimental results, although in terms of speed indicators, it still maintains better than the traditional algorithm in terms of average throughput, transmission delay, response time, transmission rate and so on in a static environment. [ABSTRACT FROM AUTHOR]

Conventionally, the electromechanical system requires the installation of auxiliary displacement sensors and only the amount on the drive part and motion end, which increases volume, cost, and measurement error in the system. This paper presents an integrated measurement method with a sensing head, which takes the equal division characteristics of mechanical structures as part of the sensor, thus, the so-called self-sensing system. Moreover, the displacement is measured by counting the time pulses. The sensing head is integrated with the entire electromechanical system, including the driving, transmitting, and moving parts. Thus, the integration of the sensing part is greatly improved. Taking the rotary table as a special example, and the sensing head embedded into each part of the system, displacement information is obtained by the common processing system and fused by the adaptive weighted average method. The results of the experiment show that the fusion precision of each component is higher than only the motor position information as the feedback. The proposed method is a practical self-sensing technology with significant volume reduction and intelligent control benefits in the industry, especially suitable for extremely small and narrow spaces. [ABSTRACT FROM AUTHOR]

Hand gesture recognition using a camera provides an intuitive and promising means of human-computer interaction and allows operators to execute commands and control machines with simple gestures. Research in hand gesture recognition-based control systems has garnered significant attention, yet the deploying of microcontrollers into this domain remains relatively insignificant. In this study, we propose a novel approach utilizing micro-hand gesture recognition built on micro-bottleneck Residual and micro-bottleneck Conv blocks. Our proposed model, comprises only 42K parameters, is optimized for size to facilitate seamless operation on resource-constrained hardware. Benchmarking conducted on STM32 microcontrollers showcases remarkable efficiency, with the model achieving an average prediction time of just 269ms, marking a 7× faster over the state-of-art model. Notably, despite its compact size and enhanced speed, our model maintains competitive performance result, achieving an accuracy of 99.6% on the ASL dataset and 92% on OUHANDS dataset. These findings underscore the potential for deploying advanced control methods on compact, costeffective devices, presenting promising avenues for future research and industrial applications. [ABSTRACT FROM AUTHOR]

Abstract Flexible sensor arrays have attracted extensive attention in human‐computer interaction. However, realizing high‐performance sensor units with programmable properties, and expanding them to multi‐pixel flexible arrays to maintain high sensing consistency is still struggling. Inspired by the contact behavior of octopus antenna, this paper proposes a programmable multistage dome structure‐based flexible sensing array with robust sensing stability and high array consistency. The biomimetic multistage dome structure is pressurized to gradually contact the electrode to achieve high sensitivity and a large pressure range. By adjusting the arrangement of the multistage dome structure, the pressure range and sensitivity can be customized. More importantly, this biomimetic structure can be expanded to a multi‐pixel sensor array at the wafer level with high consistency through scalable and high‐precision imprinting technologies. In the imprinting process, the conductive layer is conformally embedded into the multistage dome structure to improve the stability (maintain stability over 22 000 cycles). In addition, the braced isolation structure is designed to effectively improve the anti‐crosstalk performance of the sensor array (crosstalk coefficient: 26.62 dB). Benefitting from the programmable structural design and high‐precision manufacturing process, the sensor array can be customized and is demonstrated to detect human musculation in medical rehabilitation applications.

Because of the availability of more than an actor and a wireless component in an e-health application, providing more security and safety to users of this type of applications is expected. Moreover, ensuring protection of data user available or shared within different services from any security attack becomes an important requirement. In this paper, we are interested essentially in the authentication process, and we propose an improved Landmarkbased algorithm as a tool to extract, firstly, key features from analysed faces, and hence to accelerate the authentication operation. The suggested approach beats other state-of-the-art works in terms of accuracy and speed-up attaining time execution constraint, according to experimental evaluations. [ABSTRACT FROM AUTHOR]

An ordered hypergroupoid is a hypergroupoid together with a partial order such that satisfies the monotone condition. In this paper, we introduce the notion of semihypergroup actions on ordered hypergroupoids. Some results in this respect are investigated. In particular, we prove that if S is a commutative semihypergroup acting on an ordered hypergroupoid H, then there exists a commutative semihypergroup S acting on the ordered hypergroupoid ... in such a way that $H$ is embedded in H. [ABSTRACT FROM AUTHOR]

Existing test water lubrication bearing characteristics of the important characterisation parameter water film pressure of the many methods, because the sensor distance from the real measurement point is far away, or trauma to the shaft system is large and other reasons, the accurate water film pressure empirical data is difficult to obtain, restricting the bearings of further research and development. In response to these challenges, a new monitoring method is proposed in which thin-film sensors are embedded in bearing shingles, while pressure data are transmitted via wireless sensing. Firstly, the physical model of axial tile grooved bearing is established, and the location, structure and number of grooves are determined by finite element analysis of axial tile deformation near the grooves; A physical model of the bearing fluid domain and solid domain is established to simulate and analyse the water film pressure distribution; Then, a thin film sensor calibration method is proposed to calibrate it accurately; Finally, a multi-operating condition bearing water film pressure test experiment is carried out, it is compared and analysed with the simulation results and existing methods. The results of the study show that it is feasible to embed a thin film sensor in the groove of the bearing shaft tile and transmit the data wirelessly, and the measured data of water film pressure deviates less than 10% from the simulation results, which is more accurate than the measured data of existing methods. The water film pressure decreases along the axial direction, and there exists a part of lubrication film inside the bearing in a mixed lubrication state. [ABSTRACT FROM AUTHOR]

Learning new motor skills is often challenged by sensory mismatches. For reliable sensory information, people have actively employed sensory intervention methods. Visual assistance is the most popular method to provide sensory information, which is equivalent to the knowledge of performance (KP) in motor tasks. However, its efficacy is questionable because of visual-proprioceptive mismatch as well as heavy intrinsic visual and cognitive engagement in motor tasks. Electrotactile intervention is a promising technique to address the current limitations, as it provides KP using tactile feedback that has a close neurophysiological association with proprioception. To test its efficacy, we compared the effects of visual and electrotactile assistance on hitting point localization of the table-tennis racket during virtual-reality table-tennis game. Experimental results suggest that location-based electrotactile feedback outperforms visual assistance in localizing the hitting point on a table-tennis racket during virtual-reality table-tennis game. Our study showed the potential of electrotactile intervention for improving the efficacy of new motor skill training. [ABSTRACT FROM AUTHOR]

Copyright of Wool Textile Journal is the property of National Wool Textile Science & Technology Information Center and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

INTRODUCTION: With the development of digital technology and computer technology, the theory of digital economy has also had far-reaching development, but at present, the digital economy is still not able to clearly define whether the digital economy is good or bad for the high-quality development of China's economy. Therefore, it is necessary to research the spillover effect of the digital economy and the high-quality development of the economy with the help of embedded system technology. OBJECTIVES: To solve the issue of the poor coupling between the digital economy and high-quality development, to raise the degree of China's digital economic development, to improve the high energy consumption in the course of China's economic high-quality development, and to improve the application level of system technology in the study of China's economic development. METHODS: The digital economy model is established using the entropy weight method; its efficiency is evaluated using embedded system technology; the spillover effect analysis of high-quality development is then conducted using the digital economy index; and lastly, the overall assessment of the spillover effect is conducted using the comprehensive evaluation results of the entropy weight method. RESULTS: Embedded system technology has a noticeable promotion effect on the development of the digital economy; although the development of the digital economy and economic high-quality development are poorly coupled, their promotion effect is more significant; embedded system technology can indirectly promote the development of economic high-quality development through the digital economy. CONCLUSION: China should vigorously develop embedded system technology to promote the application of new technology in the economy and should further standardize the market economic order to maintain the orderly development of the digital economy. [ABSTRACT FROM AUTHOR]

In the current literature, there is no practical formula to calculate the horizontal displacement of cantilever walls. To fill this gap, in the present study, eight formulae for the estimation of wall displacement were developed based on 431 FE wall model configurations. Each formula considers factors such as the wall height, embedment depth, surcharge load, unit weight, internal friction angle, elastic modulus of the surrounding soil, and flexural rigidity of the wall. The FE model, which was used in the development of the formula, was also validated against a physical laboratory study. In addition, the outputs obtained from the formulae were compared with the results of two laboratory studies and a real site study. Finally, a parametric study was performed to estimate the influence of formula input parameters on wall displacement. [ABSTRACT FROM AUTHOR]

Hand gesture recognition using a camera provides an intuitive and promising means of human-computer interaction and allows operators to execute commands and control machines with simple gestures. Research in hand gesture recognition-based control systems has garnered significant attention, yet the deploying of microcontrollers into this domain remains relatively insignificant. In this study, we propose a novel approach utilizing micro-hand gesture recognition built on micro-bottleneck Residual and micro-bottleneck Conv blocks. Our proposed model, comprises only 42K parameters, is optimized for size to facilitate seamless operation on resource-constrained hardware. Benchmarking conducted on STM32 microcontrollers showcases remarkable efficiency, with the model achieving an average prediction time of just 269ms, marking a 7× faster over the state-of-art model. Notably, despite its compact size and enhanced speed, our model maintains competitive performance result, achieving an accuracy of 99.6% on the ASL dataset and 92% on OUHANDS dataset. These findings underscore the potential for deploying advanced control methods on compact, cost-effective devices, presenting promising avenues for future research and industrial applications.

In order to improve the ability of bad data identification and fault location accuracy in power system risk control, a new risk control method for power systems using embedded technology was designed.S3C2440 chip was used as the central processing unit, the phasor measurement unit (PMU) technology was used to identify bad data in the power system, improving the efficiency of identification.Improved on the basis of traditional multiverse algorithms, fault localization was based on data collected by PMU, effectively improving the accuracy of fault localization.In the simulation experiment, the efficiency of identifying bad data by the proposed method has been improved by at least 33.76%, the accuracy of fault localization has been improved by 26.33%, and the efficiency has been improved by at least 43.4%.The proposed method has good risk control capabilities in the power system.

Zero-shot learning (ZSL) in a multi-model environment presents significant challenges and opportunities for improving cross-modal retrieval and object detection in unseen data. This study introduced a novel embedding approach of vector space clustering to address image-to-text and text-to-image retrieval problems effectively. We proposed an iterative training strategy; unlike the CLIP model, which directly compares visual and textual modalities, our model concatenates by clustering trained image and text features in common vector space. We use cross-modal contrastive and multi-stage contrast loss to improve the unsupervised learning of our model. This integration makes it possible to achieve proper clustering on embedding, which enhances the image-text matching problem in zero-shot learning tasks. We rigorously evaluate our model performance on standard benchmark datasets, including Flickr30K, Flickr8K, and MSCOCO 5K, achieving notable improvements with accuracies of 91.3%, 88.8%, and 90.3%, respectively. The results demonstrate the better performance of our model over existing methods but also show its effectiveness in enhancing cross-modal retrieval in zero-shot learning.

The fairness & bias of narrow coverage of AI becomes another challenge for AI researchers. If a commercial AI trains with a biased dataset, there will be severe gender or racial fairness and bias issues. Since the researchers use primary language datasets to train AI, the broad audience cannot be satisfied if a novel LLM (Large Language Model) AI shows a knowledge or creativity limitation on their specific spoken language. Narrow coverage of the LLMs can lead the audience to misinterpretation and confusion if the service involves STT (Speech-To-Text). In this paper, to overcome this issue of data diversity, we propose the idea that the embedded, extracted features have captured semantic proximity information that can be useful to mitigate diversity issues. This project focused on the Korean language food dataset for STT services, where a narrow-trained A.I. is prone to show its limitations, such as lifestyle-related elements. To present our proof of concept, we trained a baseline model, GPT2, with the Korean Wikipedia dataset in 2022. Then, we employed DistilBERT and KoBERT for comparison. The extracted hidden_state_output features from each model were utilized to build feature-extraction-based text search engines. We used the same idea of Local Sensitive Hashing (LSH) but effectively located a similar hash by applying transposed weights. We also present conventional classification benchmarks for performance comparison using top-k measurements, times for training and memory & disc consumptions. In the discussion, we proposed that our idea can mitigate the diversity problem without re-training the model and tokenizer.

This paper proposes a Design Space Exploration for Edge machine learning through the utilization of the novel MathWorks FPGA Deep Learning Processor IP, featured in the HDL Deep Learning toolbox. With the ever-increasing demand for real-time machine learning applications, there is a critical need for efficient and low-latency hardware solutions that can operate at the edge of the network, in close proximity to the data source. The HDL Deep Learning toolbox provides a flexible and customizable platform for deploying deep learning models on FPGAs, enabling effective inference acceleration for embedded IoT applications. In this study, our primary focus lies in investigating the impact of parallel processing elements on the performance and resource utilization of the FPGA-based processor. By analyzing the trade-offs between accuracy, speed, energy efficiency, and hardware resource utilization, we aim to gain valuable insights into making optimal design choices for FPGA-based implementations. Our evaluation is conducted on the AMD-Xilinx ZC706 development board, which serves as the target device for our experiments. We consider all the compatible Convolutional Neural Networks available within the HDL Deep Learning toolbox to comprehensively assess the performances.

The stress status of a soil pressure cell placed in soil is very different from its stress state in a uniform fluid medium. The use of the calibration coefficient provided by the soil pressure cell manufacturer will produce a large error. In order to improve the measurement accuracy of the interface-type earth pressure cell placed in soil, this paper focuses on a single-membrane resistive earth pressure cell installed on the surface of a structure, analyzing the influence of loading and unloading cycles, the thickness and particle size of the sand filling, and the depth of the earth pressure cell inserted in the structure on the calibration curve and matching error, which were analyzed through calibration tests. The results show that when the sand filling thickness is less than D (D is the diameter of the earth pressure cell), the calibration curve is unstable in relation to the increase in the number of loading and unloading cycles, which will cause the sand calibration coefficient used for stress conversion to not be used normally. When the sand filling thickness in the calibration bucket increases from 0.285D to 5D, the absolute value of the matching error first decreases and then increases, such that the optimal sand filling thickness is 3D. The output of the earth pressure cell increases with the decrease in sand particle size under the same load, and there is a significant difference between the theoretical calculation value and the experimental value of the matching error; aiming at this difference, an empirical formula is derived to reflect the ratio of the diameter of the induction diaphragm of the earth pressure cell to the maximum particle size of the sand filling. When the depth of the earth pressure cell inserted in the structure is “0”, the sensing surface is flush with the structure and the absolute value of the matching error is the smallest. Changes in the horizontal placement of the soil pressure cell in the calibration bucket result in significant differences in both the output and hysteresis of the calibration curve. To improve the measurement accuracy of soil pressure cells in scaled tests for applications such as in the retaining walls of excavation pits, tunnel outer surfaces, pile tops, pile ends, and soil pressure measurements in soil, calibration of the soil pressure cells is required before testing. Due to the considerable difference in the stress states of the soil pressure cell between granular media and uniform fluid media, calibration in soil is essential. During in-soil calibration, factors such as cyclic loading and unloading, soil compression, sand thickness and particle size, and the placement of the soil pressure cell all affect the calibration results. This paper primarily investigates the influence of these factors on the calibration curve and matching error. This study found that, as the sand thickness increases, the matching error decreases initially and then increases.

This paper proposes an embedded Internet of Things (IoT) system for bioreactor sensor integration, aimed at optimizing temperature and turbidity control during cell cultivation. Utilizing an ESP32 development board, the system makes advances on previous iterations by incorporating superior analog-to-digital conversion capabilities, dual-core processing, and integrated Wi-Fi and Bluetooth connectivity. The key components include a DS18B20 digital temperature sensor, a TS-300B turbidity sensor, and a Peltier module for temperature regulation. Through real-time monitoring and data transmission to cloud platforms, the system facilitates advanced process control and optimization. The experimental results on yeast cultures demonstrate the system’s effectiveness at maintaining optimal growth, highlighting its potential to enhance bioprocessing techniques. The proposed solution underscores the practical applications of the IoT in bioreactor environments, offering insights into the improved efficiency and reliability of culture cultivation processes.

Despite calls for integration into routine heart failure (HF) care, optimal palliative care delivery for people living with HF remains unclear. Describe an innovative model of an embedded palliative care nurse practitioner (NP) within a HF team. Compare demographics and utilization among people hospitalized with HF receiving referral or embedded consultation. Using an electronic health record-based palliative care registry, we conducted descriptive analyses and t‐tests and χ2 tests, as appropriate, to examine bivariate associations between sociodemographic, clinical and utilization data of hospitalized people with HF receiving a traditional, referral-based palliative care consultation generated exclusively by the primary team vs. a novel, embedded-based consultation generated by collaboration between a palliative care NP and the advanced HF team at an urban, quaternary care academic medical center in New York City. During the study period from January 1, 2019–December 31, 2021, consultation volume nearly doubled with 363 consults from traditional referrals and an additional 317 consults from the newly embedded NP. People in the embedded group, as compared to referral, were younger (mean age: 60.1 vs. 71.9 years (2019); 59.2 vs. 70.4 (2020); 61.3 vs. 69.6 (2021), p -value < 0.001), more functional (median Karnofsky Performance Status: 40% vs. 30%, p -value = 0.01 (2019); 40% vs 20%, p- value < 0. 0001 (2020); 40% vs. 20%, p -value = 0.02 (2021)), more likely had capacity to designate a medical decision maker (56.4% vs. 20.6%, p -value < 0.001 (2020); 76.3% vs. 49.5%, p -value < 0.001 (2021)), received earlier consultation (median days before discharge: 9.5 vs. 4 (2019); 11 vs. 5 (2020); 7 vs. 3 (2021), p -value ≤ 0.001), and more likely to discharge home (60% vs. 26%, p -value ≤ 0.001 (2019); 62.7% vs 20.6%, p -value ≤ 0.001 (2020); 42.3% vs. 28%, p -value = 0.03 (2021)). Hospitalized people living with advanced HF who received an embedded palliative care consult were younger, had higher functional status and less illness severity compared to those served by a traditional, referral-based consult. [ABSTRACT FROM AUTHOR]

Willmore defined embedded surfaces on f : S → E 3 , which is the embedding of S into Euclidean 3-space. He investigated the Euclidean metric of E 3 , inducing a Riemannian structure on f (S) . The expression analogous to the left-hand member of the curvature K is replaced by the mean curvature H 2 on f (S). Our aim is to observe the Gaussian and mean curvatures of curve–surface pairs using embedded surfaces in different curve–surface pairs and to define some developable operations on their curve–surface pairs. We also investigate the embedded surfaces using the Willmore method. We first recall the Darboux curve–surface and derive the new characterizations. This curve–surface pair is called the osculating Darboux curve–surface if its position vector always lies in the osculating Darboux plane spanned by a Darboux frame. Thus, we observed an osculating Darboux curve–surface pair. We also obtained the D ∼ -scroll of the curve–surface pair and involute D ∼ -scroll of the curve–surface pair with some differential geometric elements and found D ∼ (α , M) (s) and D ∗ ∼ (α , M) (s) -scrolls of the curve–surface pair (α , M) . [ABSTRACT FROM AUTHOR]

We prove that on a compact Riemannian manifold of dimension 3 or higher, with positive Ricci curvature, the Allen–Cahn min–max scheme in Bellettini and Wickramasekera (The Inhomogeneous Allen–Cahn Equation and the Existence of Prescribed-Mean-Curvature Hypersurfaces, 2020), with prescribing function taken to be a non-zero constant λ , produces an embedded hypersurface of constant mean curvature λ (λ -CMC). More precisely, we prove that the interface arising from said min–max contains no even-multiplicity minimal hypersurface and no quasi-embedded points (both of these occurrences are in principle possible in the conclusions of Bellettini and Wickramasekera, 2020). The immediate geometric corollary is the existence (in ambient manifolds as above) of embedded, closed λ -CMC hypersurfaces (with Morse index 1) for any prescribed non-zero constant λ , with the expected singular set when the ambient dimension is 8 or higher. [ABSTRACT FROM AUTHOR]

A prototype of a printed circuit board (PCB) with radio frequency electromagnetic compatibility specifications is designed using the top-down methodology for the two-layer Internet of Things with free open-source hardware and software, using the following techniques: requirements, analysis, modular design, schematics, manufacturing and functional testing. The study of the influence of the design parameters is carried out applying the standards of the Printed Circuit Institute and the characteristics of the technological production process for a free multiplatform for wireless networks. Finally, functional tests of the universal asynchronous transmit and receive (UART) communication with the microcontroller, the radio modules, the general-purpose input and output pins, and the over-the-air (OTA) configuration are performed to program the board wirelessly, without the need of a universal serial bus (USB) interface. [ABSTRACT FROM AUTHOR]

Negative features in microdevices find a wide range of applications. The process of 3D printing has revolutionized their fabrication due to the combination of good resolution and integration capability. Herein, we report on a systematic study of the effects of materials and print directions on the 3D printing of microfluidic channels as negative features under PolyJet technology. Specifically, the Statasys Objet500 printer was used for this study. We printed two sets of chips ( n = 10 each), each of which contains channel pairs of a high-contrast reference material and a sacrificial material, respectively. Both materials were embedded in a clear photopolymer resin. The channel pairs ranged in planned width from 64 to 992 μm. To explore the effect on print orientation, channels were printed either parallel or perpendicular with respect to the jetting head's movement. The width of each channel of a pair was compared for each planned width and each combination of materials. The effect of print orientation on channel morphology was also investigated. We found that reproducibility and accuracy were highest at a planned channel width of approximately ≥600 μm and that channel morphology was most suitable when the jetting head of the printer moved parallel to the channel's longitudinal axis. The results should be of interest to any users who wish to create negative features using PolyJet 3D technology. [ABSTRACT FROM AUTHOR]

On the basis of good governance, the new village sages play an important role in “three governance integration” to realize the connection between national rights and villagers. This paper analyzes the embedded logic of the new rural talents by case study and combining with Shangyu District of Shaoxing City, the birthplace of the real rural talents culture. From the angle of embedding: capital embedding, political embedding and cultural embedding to reflect the mechanism of the new rural sages, and from three aspects briefly summarized the role of the new rural sages in rural governance. By making good use of their own advantages, the new rural sages can better integrate into the rural construction, and act as a model to solve many contradictions that difficult to be reconciled by the grassroots government. [ABSTRACT FROM AUTHOR]

The concrete inside the embedded rock-socketed steel pipe pile is prefabricated on land. After embedding the steel pipe piles, grouting for pile's sidewalls is carried out, and the grout material generates buoyancy on pile, leading to a risk of floating during the grouting process. Existing preventive measures are high in risk and low in efficiency. To address the issue of grout-induced floating in embedded rock-socketed steel pipe piles, a solution is proposed. It involves analyzing the forces during the grouting process, adding a certain amount of quick-setting agent to the grout material, optimizing the layout of the prefabricated grout pipeline, altering the grouting construction process, and rigorously controlling the construction procedures. This approach enables continuous one-time grouting for the segments along the rock wall and steel casing of the embedded rock-socketed steel pipe piles. Through on-site comparisons and verification of grouting process, as well as engineering applications, this method effectively resolves the problem of floating during grouting for embedded rock-socketed steel pipe piles. It ensures construction quality and enhances construction efficiency. [ABSTRACT FROM AUTHOR]

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The sector-wide challenge of student mental wellbeing within higher education (HE) requires universities to systematically and holistically enhance their practice and approaches. This paper recounts how an interdisciplinary team of academics, senior leaders, professional services and Students' Union representatives across seven institutions responded to this need by collaboratively identifying definitions, good-practice for replication, and benefits of activity to embed mental wellbeing in the curriculum. Considering and exploring definitions across HE, our study provides clarity and reference points for definitions, particularly around the nature of "embedding" in relation to mental wellbeing for students. Five core themes for mental wellbeing in HE were identified and defined through this study: flourishing or thriving, balance, community and belonging, dynamic, and inclusive. Furthermore, a five-point definition of embeddedness developed; it being modeled in practice, tailored to needs, inherent in values, ethos and culture, a holistic partnership approach, and represented in strategy supported by appropriate resource. These are represented as a MentalWellbeing Embeddedness Framework. The study sought good-practice examples from across seven HE providers, presented as example resources for replication by others in the sector seeking to address similar challenges within their institutions. Twenty-seven examples were developed into an online open educational resource toolkit, providing clear examples for use in a range of settings and responding to different needs around student mental wellbeing. Each example sharing its original rationale for development and clear list of benefits to be seen from replicating the initiative. Sector feedback to date indicates referencing the definitions activity and expanding this for use in other contexts, replication of good-practice examples in different settings, and support for identification of the benefits that can be achieved from embedding mental wellbeing in the curriculum. This paper is a call to action, shaping the future direction of student mental wellbeing, supported by policy, practice, and constant innovation. [ABSTRACT FROM AUTHOR]

The integration of rigid electronic components into stretchable materials is a complex challenge due to contrary material properties. This paper shows a novel approach for the embedding of electronic components into flexible and stretchable polymer substrates using a stereolithographic process that leads to stress reduction during stretching. The key factor is multimaterial printing with various elastic material properties. The paper shows a miniaturized packaged component (e.g., 0201 LED) in a flexible and stretchable substrate based on three different materials. The first material has rigid properties (stiffness 42.25 N/mm) and surrounds a small area of the LED with about 500 mm peripheral frame. The main purpose of this material is to round up the sharp edges of the LED to the next material. The second material is more elastic (stiffness 0.11 N/mm) and surrounds the first embedded LED. The purpose of the implementation of the second intermediate material is to spread the load between the LED and stretchable substrate caused by stretching. The third material has even higher elastic properties (stiffness 0.05 N/mm) and builds up the main part of the stretchable substrate (size of (4.5 3 34 3 0.27) mm3). After the fabrication of the multimaterial substrate with the embedded LED, horseshoe conductive traces are screen printed with conductive paste. Finally, the embedded LED substrate with the conductive traces is cured at 125°C. The final stretchable substrate with the embedded LED is able to stretch up to about 25% for 30 cycles without disturbing the electrical function. [ABSTRACT FROM AUTHOR]

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In order to actually test whether the onboard relay can meet the requirements of the service life and improve the stability and reliability of the onboard relay products, an embedded onboard relay life test system is designed to test the mechanical and electrical life of the on-board relay. In terms of system structure, it is divided into two parts: the lower computer and the upper computer. Based on the embedded system, the lower computer completes the drive of the onboard relay and the construction of the peripheral logic circuit by way of the main control module, collects the contact state of the relay to be measured in the process of action and codes the fault information, and transmits the coded fault information to the upper computer through RS-232 communication. The upper computer is designed with C# programming language, and has the functions of storing, analyzing and displaying the coded fault information. Finally, the feasibility and practicability of the system in information acquisition, data communication and fault diagnosis are verified through system joint debugging. [ABSTRACT FROM AUTHOR]

Abstract IoT and Embedded devices grow at an exponential rate, however, without adequate security mechanisms in place. One of the key challenges in the cyber world is the security of these devices. One of the main reasons that these devices are active targets for large-scale cyber-attacks is a lack of security standards and thorough testing by manufacturers. Manufacturer-specific operating systems or firmware of various architectures and characteristics are typically included with these devices. However, due to a lack of security testing and/or late patching, the underlying firmware or operating systems are vulnerable to numerous types of vulnerabilities. Reverse engineering and in-depth research of the firmware is required to detect the vulnerabilities. In this paper, we've delved into various aspects of IoT and embedded devices. This includes a comprehensive survey on the architecture of firmware, techniques for firmware extraction, and state-of-the-art vulnerability analysis frameworks for the detection of vulnerabilities using various approaches like static, dynamic, and hybrid approaches. Furthermore, we’ve scrutinized the challenges of existing vulnerability analysis frameworks and proposed a novel framework to address these issues.