Medical image diagnosis using deep learning has shown significant promise in clinical medicine. However, it often encounters two major difficulties in real-world applications: (1) domain shift, which invalidates the trained model on new datasets, and (2) class imbalance problems leading to model biases towards majority classes. To address these challenges, this paper proposes a transfer learning solution, named Dynamic Weighting Translation Transfer Learning (DTTL), for imbalanced medical image classification. The approach is grounded in information and entropy theory and comprises three modules: Cross-domain Discriminability Adaptation (CDA), Dynamic Domain Translation (DDT), and Balanced Target Learning (BTL). CDA connects discriminative feature learning between source and target domains using a synthetic discriminability loss and a domain-invariant feature learning loss. The DDT unit develops a dynamic translation process for imbalanced classes between two domains, utilizing a confidence-based selection approach to select the most useful synthesized images to create a pseudo-labeled balanced target domain. Finally, the BTL unit performs supervised learning on the reassembled target set to obtain the final diagnostic model. This paper delves into maximizing the entropy of class distributions, while simultaneously minimizing the cross-entropy between the source and target domains to reduce domain discrepancies. By incorporating entropy concepts into our framework, our method not only significantly enhances medical image classification in practical settings but also innovates the application of entropy and information theory within deep learning and medical image processing realms. Extensive experiments demonstrate that DTTL achieves the best performance compared to existing state-of-the-art methods for imbalanced medical image classification tasks. Full article

Colorimetric chemical sensing of target gases, such as hydrogen peroxide vapors, is an evolving area of research that implements responsive materials that undergo molecule-specific interaction, resulting in a visible color change. Due to the intuitive nature of an observable color change, such sensing systems are particularly desirable as they can be widely deployed at low cost and without the need for complex analytical instrumentation. In this work, we describe our development of a new spray-on sensing material that can provide a colorimetric response to the presence of a gas-phase target, specifically hydrogen peroxide vapor. By providing a cumulative response over time, we identified that part per million concentrations of hydrogen peroxide vapor can be detected. Specifically, we make use of iron chloride-containing formulations to enable the catalysis of hydrogen peroxide to hydroxyl radicals that serve to initiate polymerization of the diacetylene-containing amphiphile, resulting in a white to blue color transition. Due to the irreversible nature of the color change mechanism, the cumulative exposure to hydrogen peroxide over time is demonstrated, enabling longitudinal assessment of target exposure with the same coatings. The versatility of this approach in generating a colorimetric response to hydrogen peroxide vapor may find practical applications for environmental monitoring, diagnostics, or even industrial safety. Full article

Chile’s central-south region has experienced significant land use changes in the past fifty years, affecting native forests, agriculture, and urbanization. This article examines these changes and assesses their impact on native forest cover and agricultural land. Agricultural data for Chile (1980–2020) were obtained from public Chilean institutions (INE and ODEPA). Data on land use changes in central and south Chile (1975–2018), analysed from satellite images, were obtained from indexed papers. Urban area expansion in Chile between 1993 and 2020 was examined using publicly available data from MINVIU, Chile. Additionally, photovoltaic park data was sourced from SEA, Chile. Field crop coverage, primarily in central and southern Chile, decreased from 1,080,000 ha in 1980 to 667,000 ha in 2020, with notable decreases observed in cereal and legume crops. Conversely, the coverage of export-oriented orchards and vineyards increased from 194,947 ha to 492,587 ha. Forest plantations expanded significantly, ranging from 18% per decade in northern central Chile to 246% in the Maule and Biobío regions. This was accompanied by a 12.7–27.0% reduction per 10 years in native forest. Urban areas have experienced significant growth of 91% in the last 27 years, concentrated in the Mediterranean climate region. Solar photovoltaic parks have begun to increasingly replace thorn scrub (Espinal) and agricultural land, mirroring transformations seen in other Mediterranean nations like Spain and Portugal. Full article

In the actual working environment, most equipment models present nonlinear characteristics. For nonlinear system filtering, filtering methods such as the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Cubature Kalman Filter (CKF) have been developed successively, all of which show good results. However, in the process of nonlinear system filtering, the performance of EKF decreases with an increase in the truncation error and even diverges. With improvement of the system dimension, the sampling points of UKF are relatively few and unrepresentative. In this paper, a novel high-order extended Unscented Kalman Filter (HUKF) based on an Unscented Kalman Filter is designed using the higher-order statistical properties of the approximate error. In addition, a method for calculating the approximate error of the multi-level approximation of the original function under the condition that the measurement is not rank-satisfied is proposed. The effectiveness of the filter is verified using digital simulation experiments. Full article

This study proposes a universal adaptive control algorithm for an unknown multi-input multi-output (MIMO) system using recursive least squares (RLS) and parameter self-tuning. The issue of adjusting the control and system parameters in response to changes in the platform was discussed. The development of a control algorithm that can consistently achieve reliable and robust control performance in various systems is important. This study aimed to develop a control algorithm that can track the reference value for any unknown MIMO system. For the controller design, an nth-order differential error dynamic model was designed, and an RLS with a scale factor was used to estimate the coefficients of the error dynamics. In the current scenario, the numbers of control inputs and error states in the error dynamics were assumed to be equal. It was designed such that the control input is derived based on the Lyapunov stability concept using the estimated coefficients. The scale factor in the RLS and injection term in the control input based on the sliding-mode approach were computed using a self-tuning methodology. The performance of the proposed universal adaptive control algorithm was evaluated using an actual DC motor and CarMaker (version 8.1.1) software tests under various scenarios. Full article

Calculating the service life of gears under variable loads requires a description of the load-carrying capacity. The current standard for this is the use of the S/N curve. International standards such as ISO 6336 stipulate the use of this approach for the calculation of the service of gears under variable loads. In this paper, five new approaches are developed and evaluated to describe the load-carrying capacity of gears in the load range of finite life. Four methods are based on machine learning, and one uses mathematical regression. To validate the new approaches, the results of an experimental study investigating the service life of gears under variable loads are presented. These results form the basis for the conducted study, which compares the five new methods with the existing approach. The comparison focuses on the ability of the load-carrying capacity descriptions to provide an accurate calculation of the service life and to reduce scattering as much as possible. The results of the study show significant potential for the new methods, especially the one based on a neural network. Full article

Singularities are configurations where the number of degrees of freedom of a robot changes instantaneously. In parallel manipulators, a singularity could reduce the mobility of the end-effector or produce uncontrolled motions of the mobile platform. Thus, a singularity is a critical problem for mechanical design and model-based control. This paper presents a general sensor-based method to identify singularities in the workspace of parallel manipulators with low computational cost. The proposed experimental method identifies a singularity by measuring sudden changes in the end-effector movements and huge increments in the forces applied by the actuators. This paper uses an inertial measurement unit and a 3D tracking system for measuring the end-effector movements, and current sensors for the forces exerted by the actuators. The proposed sensor-based identification of singularities is adjusted and implemented in three different robots to validate its effectiveness and feasibility for identifying singularities. The case studies are two prototypes for educational purposes—a five-bar mechanism and an L-CaPaMan parallel robot—and a four-degree-of-freedom robot for rehabilitation purposes. The tests showcase its potential as a practical solution for singularity identification in educational and industrial robots. Full article

This review aims to present age-related changes in the neuroelectric responses of typically developing children (TDC) who are presumed to meet developmental stages appropriately. The review is based on findings from the frequently used neuropsychological tasks of active attention, where attention is deliberately focused versus passive attention where attention is drawn to a stimulus, facilitatory attention, which enhances the processing of a stimulus versus inhibitory attention, which suppresses the processing of a stimulus. The review discusses the early and late stages of attentional selectivity that correspond to early and late information processing. Age-related changes in early attentional selectivity were quantitatively represented in latencies of the event-related potential (ERP) components. Age-related changes in late attentional selectivity are also qualitatively represented by structural and functional reorganization of attentional processing and the brain areas involved. The purely bottom-up or top-down processing is challenged with age-related findings on difficult tasks that ensure a high cognitive load. TDC findings on brain oscillatory activity are enriched by findings from attention deficit hyperactivity disorder (ADHD). The transition from the low to fast oscillations in TDC and ADHD confirmed the maturational lag hypothesis. The deviant topographical localization of the oscillations confirmed the maturational deviance model. The gamma-based match and utilization model integrates all levels of attentional processing. According to these findings and theoretical formulations, brain oscillations can potentially display the human brain’s wholistic–integrative functions. Full article

An improved methodology for the condensation of Multi-Degree-Of-Freedom (MDOF) systems to equivalent Two-Degree-Of-Freedom (2EDOF) systems is presented. The methodology is applied to mid-rise buildings with Open Ground-Story and verified by means of Nonlinear Time History Analyses. The buildings studied are divided into two main segments: (a) ground story, whose stiffness and lateral strength are both provided only by reinforced concrete moment-resisting frames; and (b) from the second story to the roof, whose stiffness and lateral strength are provided by confined masonry walls. The proposed methodology allows us to do the following: (a) get the closest approximation to the real behavior of the MDOF system through the use of hysteresis rules with strength and stiffness degradation in the simplified system; (b) analyze the behavior of an OGS whose lateral stiffness is lower than the stiffness of the stories above; and (c) identify in which of the two subsystems (either the ground story with reinforced concrete frames or the second story with masonry) the maximum seismic demand of non-linear behavior occurs. For most of the cases studied and different scenarios of non-linear behavior, the 2EDOF simplified system reasonably approximates the MDOF system’s response; however, when a local failure in an upper story causes the collapse mechanism, the 2EDOF system does not adequately approximate the response of the MDOF system. Full article

A straightforward, fast and efficient analytical method was developed which utilizes a magnetic composite called three-dimensional graphene (3D-G@Fe₃O₄) as an adsorbent to recover nitrite ions (NO₂⁻) from environmental water samples. The investigation into the synthesized adsorbent contained an examination of its morphology, chemical composition, structural attributes, and magnetic properties. This comprehensive analysis was conducted using various instrumental techniques, including Fourier transform-infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), Raman spectroscopy, X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET), Barrett-Joyner-Halenda (BJH), and vibrating sample magnetometry (VSM). The adsorbent surface was activated by adding cetyltrimethylammonium bromide (CTAB) to the sample solution. To improve the selectivity and sensitivity of the method, nitrite ions were reacted with sulfanilic acid and chromotropic acid sequentially. An orange-red azo-dye complex was formed in the presence of nitrite ions with a clear absorbance peak at 514 nm. The effect of the main experimental parameters such as the pH of the sample solution, adsorbent dosage, and CTAB dosage was explored, and the optimization process was performed using a central composite design (CCD). The linear dynamic range (20–100 ng mL⁻¹) was determined under optimal experimental circumstances, yielding a reasonable determination coefficient (R2, 0.9993), a detection limit of 5.12 ng mL⁻¹, an enrichment factor of 167, and precision values of 1.0% intraday and 2.9% inter-day. The methodology successfully identified minute nitrite ions in environmental water samples with relative recoveries that varied between 96.05 and 101.6 ng mL⁻¹. Full article

Cosmetic formulations with natural antioxidants can reduce the oxidative stress caused by solar radiation and pollution. In this context, the aim of this study was to develop and evaluate the clinical efficacy of cosmetic formulations containing olive extract (OE) and Spirulina sp. (SP). For this, rheological behavior, texture, and sensory properties were evaluated. In addition, 31 healthy women with an age of 39 to 60 years, with skin phototypes II and III, and the presence of signs of photoaging on the face were recruited and divided in Group 1 (vehicle formulation) and Group 2 (vehicle with active substances) for this clinical efficacy study. Both groups applied sunscreen daily during the day. The formulations showed non-Newtonian pseudoplastic behaviors and good sensory properties. The clinical evaluation using instrumental measurements showed an increase in skin hydration, an improvement of the skin barrier, and morphological characteristics of the epidermis after 12 weeks of application of the formulations. There was a significant increase in the brightness of the stratum corneum, which suggested a film-forming effect. In addition, both groups had an improvement in the dermis echogenicity, due to the use of sunscreens. Finally, the proposed formulation was effective in protecting the skin and reducing skin changes related to photoaging. Full article

This study investigated the effects of lithium slag and iron tailings on the hydration mechanism of Basic Oxygen Furnace (BOF) slag cement paste with the addition of 0.06% diethanol-isopropanolamine (DEIPA). This study examined the fluidity, compressive strength, pore solution pH, and hydration products of BOF slag-based composite cementitious materials. The results showed that DEIPA facilitated the conversion from ettringite (AFt) to monosulphate (AFm) and improved the early compressive strength of the BOF slag–cement mortar. Incorporating lithium slag into the DEIPA-containing BOF slag–cement system promoted AFt formation, increased calcium-silicate-hydrate production, and enhanced the microstructure. BOF slag, lithium slag, and iron tailings exhibit synergistic effects in cement pastes. BOF slag and lithium slag provided the reactive components SiO₂ and Al₂O₃. In the early hydration stages, the iron tailings primarily served as fillers, accelerating the system’s reactions. Full article

The three-axis parallel motion platform (TAPMP) with a common stator has low motion inertia, enabling highly precise and high-speed motion over a large range of strokes. The primary challenge faced by the TAPMP lies in the mutual pulling exerted between the common stator motors during motion. The driving forces generated by the motors are closely associated with their synchronization motion, a connection often overlooked in the design of existing controllers. To address this issue, this paper presents a novel synchronization controller with dynamics compensation (SC–DC) to achieve motion synchronization between the three motors, ultimately enhancing the platform’s tracking accuracy in task space. In this SC–DC method, the synchronization error of the common stator motors is introduced to represent the synchronized motion relationship between adjacent motors, and a dynamic feedforward control is adopted to compensate for the motor’s driving force. The stability of the proposed controller is analyzed using Lyapunov theory, demonstrating the convergence of both the tracking error and synchronization error. Trajectory tracking simulations and experimental studies are conducted on the TAPMP. The results show that, compared to the augmented proportional-derivative controller with dynamic compensation, the proposed controller significantly reduces both the MAE of the tracking error and synchronization error on the q₁ motor by 71.88% and 73.02%, respectively, demonstrating its performance advantages in trajectory tracking and synchronization. Full article

Overrunning spring clutches are widely used as essential transmission devices, and the occurrence of abnormal noise can lead to a decline in their performance. This study investigates the dynamic aspects of abnormal noise in engineering applications, including its causes, influencing factors, and suppression methods. Audio processing algorithms are employed to analyze the audio associated with abnormal noise, and the Fourier Motion Blur algorithm is applied to process video images of the springs. By combining the motion blur curve with the noise spectrum curve, the source of the abnormal noise is identified as friction-induced vibrations in the spring. Theoretical modeling and calculations are carried out from a dynamic perspective to validate that the phenomenon of abnormal noise in the clutch is a result of self-excited friction vibration caused by the stick–slip phenomenon. Based on theoretical analysis and practical engineering, surface texturing is added to the center shaft of the spring seat, optimizing the system as an overdamped system to suppress self-vibration. Utilizing CFD simulation analysis, the simulation results are used to improve the texturing parameters and further optimize the texturing shape, resulting in an optimal parallelogram surface texture structure. Experimental validation confirms that the improved overrunning spring clutch completely eliminates abnormal noise during overrunning operation. Therefore, this paper contributes to the understanding of the dynamic issues associated with abnormal noise in overrunning spring clutches, confirming that the mechanism for abnormal noise generation is friction-induced self-excitation vibration, and demonstrating that surface texture optimization methods effectively suppress the occurrence of abnormal noise. Full article

This paper presents tube-based Model Predictive Control (MPC) for the path and velocity tracking of an autonomous articulated vehicle. The target platform of this study is an autonomous articulated vehicle with a non-steerable axle. Consequently, the articulation angle and wheel torque input are determined by the tube-based MPC. The proposed MPC aims to achieve two objectives: minimizing path tracking error and enhancing robustness to disturbances. Furthermore, the lateral stability of the autonomous articulated vehicle is considered to reflect its dynamic characteristics. The vehicle model for the MPC is formulated using local linearization to minimize modeling errors. The reference state is determined using a virtual controller based on the linear quadratic regulator to provide the optimal reference for the MPC solver. The proposed algorithm was evaluated through a simulation study with base algorithms under noise injection into the sensor signal. Simulation results demonstrate that the proposed algorithm achieved the smallest path tracking error, compared to the base algorithms. Additionally, the proposed algorithm demonstrated robustness to external noise for multiple signals. Full article

Compliant physical interactions, interactive learning, and robust position control are crucial to improving the effectiveness and safety of rehabilitation robots. This paper proposes a human–robot cooperation control strategy (HRCCS) for lower limb rehabilitation robots. The high-level trajectory planner of the HRCCS consists of a trajectory generator, a trajectory learner, a desired trajectory predictor, and a soft saturation function. The trajectory planner can predict and generate a smooth desired trajectory through physical human–robot interaction (pHRI) in a restricted joint space and can learn the desired trajectory using the locally weighted regression method. Moreover, a triple-step controller was designed to be the low-level position controller of the HRCCS to ensure that each joint tracks the desired trajectory. A nonlinear disturbance observer is used to observe and compensate for total disturbances. The radial basis function neural networks (RBFNN) approximation law and robust term are adopted to compensate for observation errors. The simulation results indicate that the HRCCS is robust and can achieve compliant pHRI and interactive trajectory learning. Therefore, the HRCCS has the potential to be used in rehabilitation robots and other fields involving pHRI. Full article

The healthcare industry is confronted with the challenge to offer an increasing variety of healthcare services while in the meantime controlling rapidly increasing healthcare costs. Mass customization has been proven to be an effective strategy to fulfill customers’ individual specific needs with high efficiency and low cost in the manufacturing industry. This paper investigates the theoretical feasibility and practical applicability of adopting mass customization as a conceptual framework for designing a healthcare service delivery system. The nature of healthcare delivery systems and their evolution are discussed relative to those of manufacturing systems. Recent research in personalized medicine, consumer-driven healthcare, consumer healthcare informatics, and integrated healthcare delivery is reviewed as enabling technologies towards mass customization of healthcare services. By synthesizing these scattered efforts in different streams of literature, this paper concludes that mass customization can contribute to the redesign of healthcare service systems, and delineates a roadmap for future research. Full article

Processing ground motion signals at early stages can be advantageous for issuing public warnings, deploying first-responder teams, and other time-sensitive measures. Multiple Deep Learning (DL) models are presented herein, which can predict triaxial ground motion accelerations upon processing the first-arriving 0.5 s of recorded acceleration measurements. Principal Component Analysis (PCA) and the K-means clustering algorithm were utilized to cluster 17,602 accelerograms into 3 clusters using their metadata. The accelerograms were divided into 1 million input–output pairs for training, 100,000 for validation, and 420,000 for testing. Several non-overlapping forecast horizons were explored (1, 10, 50, 100, and 200 points). Various architectures of Artificial Neural Networks (ANNs) were trained and tested, such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM) networks, and CNN-LSTMs. The utilized training methodology applied different aspects of supervised and unsupervised learning. The LSTM model demonstrated superior performance in terms of short-term prediction. A prediction horizon of 10 timesteps in the future with a Root Mean Squared Error (RMSE) value of 8.43 × 10⁻⁶ g was achieved. In other words, the LSTM model exhibited a performance improvement of 95% compared to the baseline benchmark, i.e., ANN. It is worth noting that all the considered models exhibited acceptable real-time performance (0.01 s) when running in testing mode. The CNN model demonstrated the fastest computational performance among all models. It predicts ground accelerations under 0.5 ms on an Intel Core i9-10900X CPU (10 cores). The models allow for the implementation of real-time structural control responses via intelligent seismic protection systems (e.g., magneto-rheological (MR) dampers). Full article

A domain alignment-based hyperspectral image (HSI) classification method was designed to address the heterogeneity in resolution and band between the source domain and target domain datasets of cross-scene hyperspectral images, as well as the resulting reduction in common features. Firstly, after preliminary feature extraction, perform two domain alignment operations: image alignment and distribution alignment. Image alignment aims to align hyperspectral images of different bands or time points, ensuring that they are within the same spatial reference framework. Distribution alignment adjusts the distribution of features of samples of different categories in the feature space to reduce the distribution differences of the same type of features between two domains. Secondly, adjust the consistency of the two alignment methods to ensure that the features obtained through different alignment methods exhibit consistency in the feature space, thereby improving the comparability and reliability of the features. In addition, this method considers multiple losses in the model from different perspectives and makes comprehensive adjustments through a unified optimization process to more comprehensively capture and utilize the correlation information between data. Experimental results on Houston 2013 and Houston 2018 datasets can improve the hyperspectral prediction performance between datasets with different resolutions and bands, effectively solving the problems of high cost and limited training samples in HSI labeling and significantly improving cross-scene HSI classification performance. Full article

Activated carbon/BiOI nanocomposites were successfully synthesized through a simplistic method. The produced composites were then characterized using XRD, TEM, SEM-EDX, and XPS. The results showed that BiOI with a tetragonal crystal structure had been formed. The interaction between activated carbon and BiOI was confirmed via all the mentioned tools. The obtained nanocomposites’ electrical conductivity, dielectric properties, and Ac impedance were studied at 59 KHz−1.29 MHz. AC and dc conductivities were studied at temperatures between 303 and 573 K within the frequency range of 59 KHz–1.29 MHz. The 10% activated carbon/BiOI nanocomposite possessed dc and AC conductivity values of 5.56 × 10⁻⁴ and 2.86 × 10⁻⁴ Ω⁻¹.cm⁻¹, respectively, which were higher than BiOI and the other nanocomposites. Every sample exhibited increased electrical conductivity values as the temperature and frequency rose, suggesting that all samples had semiconducting behavior. The loss and dielectric constants (ε′ and ε″) also dropped as the frequency increased, leading to higher dielectric loss. The Nyquist plot unraveled single semicircle arcs and a decreased bulk resistance, indicating decreased grain boundary resistance. Consequently, the electrical characteristics of BiOI, 1C/BiOI, 5C/BiOI, and 10C/BiOI implied their applicability as dielectric absorbers, charge-stored capacitors, and high-frequency microwave devices. Full article

[Background] Intermediate care is a limited-time service founded on patient-centered care (PCC) that ensures continuity and quality of care during the transition between home and acute care services, promotes recovery, and restores independence and confidence. In Japan, systematic education on intermediate care for care providers is lacking. [Method] The present study explored the relationship between a Japanese scale used to evaluate individualized discharge support skills, a Japanese version of a tool for evaluating intermediate care based on PCC, and a tool that measures the shared decision making of care providers, which is the pinnacle of PCC. [Results] Clear correlations were found between the concepts evaluated using these three tools. Some concepts were not correlated between the Japanese scale that evaluated individualized discharge support skills and intermediate care based on PCC. [Conclusions] Elucidating the perspectives that help expand discharge care to intermediate care based on PCC will contribute to future education on intermediate care for Japanese care providers and to enriching patient-centered intermediate care. Full article