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most exciting work published in the various research areas of the journal.
In this paper, we propose a method for efficient target classification based on the spatial features of the point cloud generated by using a high-resolution radar sensor. The frequency-modulated continuous wave radar sensor can estimate the distance and velocity of a target. In
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In this paper, we propose a method for efficient target classification based on the spatial features of the point cloud generated by using a high-resolution radar sensor. The frequency-modulated continuous wave radar sensor can estimate the distance and velocity of a target. In addition, the azimuth and elevation angle of the target can be estimated by using a multiple-input and multiple-output antenna system. Using the estimated distance, velocity, and angle, the 3D point cloud of target can be generated. From the generated point cloud, we extract the point cloud for each individual target using the density-based spatial clustering of application with noise method and a camera mounted on the radar sensor. Then, we define the convex hull boundaries that enclose these point clouds in both 3D and 2D spaces obtained by orthogonally projecting onto the , , and planes. Using the vertices of convex hull, we calculate the volume of the targets and the areas in 2D spaces. Several feature points, including the calculated spatial information, are numerized and configured into feature vectors. We design an uncomplicated deep neural network classifier based on minimal input information to achieve fast and efficient classification performance. As a result, the proposed method achieved an average accuracy of 97.1%, and the time required for training was reduced compared to the method using only point cloud data and the convolutional neural network-based method.
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Securing food, energy, and raw materials for a growing population is one of the most significant challenges of our century. Algae play a central role as an alternative to plants. Wastewater and flue gas can secure nutrients and CO2 for carbon fixation.
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Securing food, energy, and raw materials for a growing population is one of the most significant challenges of our century. Algae play a central role as an alternative to plants. Wastewater and flue gas can secure nutrients and CO2 for carbon fixation. Unfortunately, algae domestication is necessary to enhance biomass production and reduce cultivation costs. Nannochloropsis spp. have increased in popularity among microalgae due to their ability to accumulate high amounts of lipids, including PUFAs. Recently, the interest in the use of Nannochloropsis spp. as a green bio-factory for producing high-value products increased proportionally to the advances of synthetic biology and genetic tools in these species. In this review, we summarized the state of the art of current nuclear genetic manipulation techniques and a few examples of their application. The industrial use of Nannochloropsis spp. has not been feasible yet, but genetic tools can finally lead to exploiting this full-of-potential microalga.
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Recently, Milles and Hammami presented and studied the concept of a neutrosophic topology generated by a neutrosophic relation. As a continuation in the same direction, this paper studies the concepts of neutrosophic ideals and neutrosophic filters on that topology. More precisely, we offer
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Recently, Milles and Hammami presented and studied the concept of a neutrosophic topology generated by a neutrosophic relation. As a continuation in the same direction, this paper studies the concepts of neutrosophic ideals and neutrosophic filters on that topology. More precisely, we offer the lattice structure of neutrosophic open sets of a neutrosophic topology generated via a neutrosophic relation and examine its different characteristics. Furthermore, we enlarge to this lattice structure the notions of ideals (respectively, filters) and characterize them with regard to the lattice operations. We end this work by studying the prime neutrosophic ideal and prime neutrosophic filter as interesting types of neutrosophic ideals and neutrosophic filters.
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Intervention programs aimed at mitigating the effects of chronic noncommunicable disease (CNDs) focus on promoting healthy lifestyle habits (HLH), especially in the early stages of life. Because of this, different typologies of caregivers have been identified according to HLH during middle childhood and
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Intervention programs aimed at mitigating the effects of chronic noncommunicable disease (CNDs) focus on promoting healthy lifestyle habits (HLH), especially in the early stages of life. Because of this, different typologies of caregivers have been identified according to HLH during middle childhood and adolescence. However, the available studies have focused on aspects such as nutrition, physical activity, and rest, ignoring other HLHs that are equally important for children’s well-being. Likewise, few studies address HLH during the first five years of life and how caregivers affect children’s health. In a sample of 544 caregivers of children aged zero to five years from low-income Colombian communities, we established a typology of attitudes toward different HLHs. The results indicate the presence of three clusters that grouped caregivers with (1) positive attitudes toward all HLHs, (2) toward some HLHs, and (3) relatively low positive attitudes toward all HLHs. Membership in clusters with less positive attitudes toward HLHs was also found to be associated with low educational levels and living in rural areas. This study detected profiles of caregivers who may have unhealthy lifestyles, so the results would allow social workers to design differential interventions on HLHs in non-industrialized countries.
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After COVID-19, the dynamics of home office development slowed down. According to the experiences of major companies, the problem is “fluctuating”. Research from the pandemic era covers various aspects and fails to present the concept of synthetic developmental conditions. Therefore, the issue of
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After COVID-19, the dynamics of home office development slowed down. According to the experiences of major companies, the problem is “fluctuating”. Research from the pandemic era covers various aspects and fails to present the concept of synthetic developmental conditions. Therefore, the issue of extending the organisation to home spaces was undertaken, identifying the determinants of the sustainable development of workplaces and organisations. The key is to create sustainable work systems, i.e., adapted to the environment, while being creative, critical, and productive. This study aims to establish the cultural determinants of home office development based on empirical research from the perspective of neo-institutionalism. For this purpose, the institutional logics were subject to operationalisation and the co-dependencies of metalogics with the types of organisational cultures assumed in the Cameron–Quinn OCAI model were established. The information was collected in a CAWI survey. The presented research procedure constitutes a methodical innovation. The results demonstrate a trend of changes in the dominating types of organisational culture from market control to cooperation and creation with a stimulating role of professional logics (occupation, organisation) from the perspective of working from home which brings sustainable management and business models. There is a subtle role of home logic and low employee readiness level. The adapted cultural approach demonstrates that increasing effectiveness of home office solutions requires development of integrated practices, which consider this type of work as separate and specialised. The past corporate failures and spontaneous methods cannot serve as grounds for strategies (long-term solutions). However, the research demonstrates a low level and limited range of employee impact on the organisational culture. It also indicates the need for additional analyses to determine the concept of designing workplaces in the Sustainability–Harmonisation trajectory.
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In the quest to mitigate carbon dioxide emissions, it becomes essential to address the existing atmospheric CO2. Effective and economical methodologies, particularly those without additional energy consumption, are crucial. Currently, a leading method is the direct capture of CO2 using
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In the quest to mitigate carbon dioxide emissions, it becomes essential to address the existing atmospheric CO2. Effective and economical methodologies, particularly those without additional energy consumption, are crucial. Currently, a leading method is the direct capture of CO2 using ion exchange resins, which achieve the adsorption and desorption of carbon dioxide simply by using the humidity variations. This technology, though minimizing additional energy cost, still needs improvement in its efficiency in CO2 capture capacity and compared to other methods. In this work, we develop low-cost techniques to reduce the AmberLite™ IRA900 Cl (IRA-900) anion exchange resin to micro size, and observe significant performance enhancement on CO2 capture efficiency contingent on reducing the particle diameters. This performance disparity is attributed to the differential water adsorption capacities inherent in particles of diverse diameters. Our results reveal that smaller resin particles outperform their larger counterparts, exhibiting accelerated adsorption rates and expedited transitions from wet to dry states. Notably, these smaller particles display a quintupled enhancement in adsorption efficacy relative to non-treated particles and a marked increase in relative adsorption capacity. Upon treatment, IRA-900 demonstrates robust CO2 processing efficiency, achieving a peak adsorption rate of 1.28 g/mol·h and a maximum desorption rate of 1.18 g/mol·h. Also, the material is subjected to almost 100 cycles of testing, and even after 100 cycles, the resin particles maintain a capacity of 100%. Moreover, our material can be fully regenerated to 100% efficiency by simply immersing it in water. Simultaneously, storing it in water allows for the long-term maintenance of its performance without other treatment methods. A key observation is the resin’s sustained performance stability post extended exposure to humid conditions. These outcomes offer substantial practical implications, emphasizing the relevance of our study in practical environmental applications.
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Currently, the main solution for braking systems for underground electric trackless rubber-tired vehicles (UETRVs) is traditional hydraulic braking systems, which have the disadvantages of hydraulic pressure crawling, the risk of oil leakage and a high maintenance cost. An electro-mechanical-braking (EMB) system, as a
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Currently, the main solution for braking systems for underground electric trackless rubber-tired vehicles (UETRVs) is traditional hydraulic braking systems, which have the disadvantages of hydraulic pressure crawling, the risk of oil leakage and a high maintenance cost. An electro-mechanical-braking (EMB) system, as a type of novel brake-by-wire (BBW) system, can eliminate the above shortcomings and play a significant role in enhancing the intelligence level of the braking system in order to meet the motion control requirements of unmanned UETRVs. Among these requirements, the accurate control of clamping force is a key technology in controlling performance and the practical implementation of EMB systems. In order to achieve an adaptive clamping force control performance of an EMB system, an optimized fuzzy proportional-integral-differential (PID) controller is proposed, where the improved fuzzy algorithm is utilized to adaptively adjust the gain parameters of classic PID. In order to compensate for the deficiency of single-close-loop control and adjusting the brake gap automatically, a cascaded three-closed-loop control architecture with force/position switch technology is established, where a contact point detection method utilizing motor rotor angle displacement is proposed via experiments. The results of the simulation and experiments indicate that the clamping force response of the proposed multi-close-loop Variable Universe Fuzzy–PID (VUF-PID) controller is faster than the multi-closed-loop Fuzzy–PID and cascaded three-close-loop PID controllers. In addition, the chattering of braking force can be suppressed by 17%. This EMB system may rapidly and automatically finish the operation of the overall braking process, including gap elimination, clamping force tracking and gap recovery, which can obviously enhance the precision of the longitudinal motion control of UETRVs. It can thus serve as a BBW actuator of mine autonomous driving electric vehicles, especially in the stage of braking control.
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Standard beams are mainly used for the calibration of strain sensors using their load reconstruction models. However, as an ill-posed inverse problem, the solution to these models often fails to converge, especially when dealing with dynamic loads of different frequencies. To overcome this
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Standard beams are mainly used for the calibration of strain sensors using their load reconstruction models. However, as an ill-posed inverse problem, the solution to these models often fails to converge, especially when dealing with dynamic loads of different frequencies. To overcome this problem, a piecewise Tikhonov regularization method (PTR) is proposed to reconstruct dynamic loads. The transfer function matrix is built both using the denoised excitations and the corresponding responses. After singular value decomposition (SVD), the singular values are divided into submatrices of different sizes by utilizing a piecewise function. The regularization parameters are solved by optimizing the piecewise submatrices. The experimental result shows that the MREs of the PTR method are 6.20% at 70 Hz and 5.86% at 80 Hz. The traditional Tikhonov regularization method based on GCV exhibits MREs of 28.44% and 29.61% at frequencies of 70 Hz and 80 Hz, respectively, whereas the L-curve-based approach demonstrates MREs of 29.98% and 18.42% at the same frequencies. Furthermore, the PREs of the PTR method are 3.54% at 70 Hz and 3.73% at 80 Hz. The traditional Tikhonov regularization method based on GCV exhibits PREs of 27.01% and 26.88% at frequencies of 70 Hz and 80 Hz, respectively, whereas the L-curve-based approach demonstrates PREs of 29.50% and 15.56% at the same frequencies. All in all, the method proposed in this paper can be extensively applied to load reconstruction across different frequencies.
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This article explores the enhancement of material surface properties of Ti6Al4V, potentially applicable to dental implants, through ultra-short pulse laser systems. This study investigates potential connections between surface wettability and biocompatibility, addressing the challenge of improving variability in material properties with specific laser
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This article explores the enhancement of material surface properties of Ti6Al4V, potentially applicable to dental implants, through ultra-short pulse laser systems. This study investigates potential connections between surface wettability and biocompatibility, addressing the challenge of improving variability in material properties with specific laser treatment. Several designed microstructures were manufactured using a picosecond laser system. After that, the wettability of these structures was measured using the sessile drop method. The basic behavior and growth activity of biological cells (MG-63 cell line) on treated surfaces were also analyzed. While the conducted tests did not conclusively establish correlations between wettability and biocompatibility, the results indicated that laser treatment of Ti6Al4V could effectively enlarge the active surface to better biological cell colonization and adhesion and provide a focused moving orientation. This outcome suggests the potential application of laser treatment in producing special dental implants to mitigate the issues during and following implantation.
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Lucid dreaming (LD) is a physiological state of consciousness that occurs when dreamers become aware that they are dreaming, and may also control the oneiric content. In the general population, LD is spontaneously rare; thus, there is great interest in its induction. Here,
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Lucid dreaming (LD) is a physiological state of consciousness that occurs when dreamers become aware that they are dreaming, and may also control the oneiric content. In the general population, LD is spontaneously rare; thus, there is great interest in its induction. Here, we aim to review the literature on neuropsychopharmacological induction of LD. First, we describe the circadian and homeostatic processes of sleep regulation and the mechanisms that control REM sleep with a focus on neurotransmission systems. We then discuss the neurophysiology and phenomenology of LD to understand the main cortical oscillations and brain areas involved in the emergence of lucidity during REM sleep. Finally, we review possible exogenous substances—including natural plants and artificial drugs—that increase metacognition, REM sleep, and/or dream recall, thus with the potential to induce LD. We found that the main candidates are substances that increase cholinergic and/or dopaminergic transmission, such as galantamine. However, the main limitation of this technique is the complexity of these neurotransmitter systems, which challenges interpreting results in a simple way. We conclude that, despite these promising substances, more research is necessary to find a reliable way to pharmacologically induce LD.
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In addition to water repellency, superhydrophobic leaves of plants such as Salvinia molesta adsorb oil and separate it from water surfaces. This phenomenon has been the inspiration for a new method of oil–water separation, the bionic oil adsorber (BOA). In this paper, we
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In addition to water repellency, superhydrophobic leaves of plants such as Salvinia molesta adsorb oil and separate it from water surfaces. This phenomenon has been the inspiration for a new method of oil–water separation, the bionic oil adsorber (BOA). In this paper, we show how the biological effect can be abstracted and transferred to technical textiles, in this case knitted spacer textiles hydrophobized with a layered silicate, oriented at the biology push approach. Subsequently, the transport of the oil within the bio-inspired textile is analyzed by a three-dimensional fluid simulation. This fluid simulation shows that the textile can be optimized by reducing the pile yarn length, increasing the pile yarn spacing, and increasing the pile yarn diameter. For the first time, it has been possible with this simulation to optimize the bio-inspired textile with regard to oil transport with little effort and thus enable the successful implementation of a self-driven and sustainable oil removal method.
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Unmanned surface vehicle (USV)’s motion is represented by time-series data that exhibit highly nonlinear and non-stationary features, significantly influenced by environmental factors, such as wind speed and waves, when sailing on the sea. The accurate prediction of USV motion, particularly crucial parameters, such
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Unmanned surface vehicle (USV)’s motion is represented by time-series data that exhibit highly nonlinear and non-stationary features, significantly influenced by environmental factors, such as wind speed and waves, when sailing on the sea. The accurate prediction of USV motion, particularly crucial parameters, such as the roll angle and pitch angle, is imperative for ensuring safe navigation. However, traditional and single prediction models often struggle with low accuracy and fail to capture the intricate spatial–temporal dependencies among multiple input variables. To address these limitations, this paper proposes a prediction approach integrating temporal convolutional network (TCN) and bi-directional long short-term memory network (Bi-LSTM) models, augmented with a temporal pattern attention (TPA) mechanism, termed the TCN-Bi-LSTM-TPA (TBT) USV motion predictor. This hybrid model effectively combines the strengths of TCN and Bi-LSTM architectures to extract long-term temporal features and bi-directional dependencies. The introduction of the TPA mechanism enhances the model’s capability to extract spatial information, crucial for understanding the intricate interplay of various motion data. By integrating the features extracted by TCN with the output of the attention mechanism, the model incorporates additional contextual information, thereby improving prediction accuracy. To evaluate the performance of the proposed model, we conducted experiments using real USV motion data and calculated four evaluation metrics: mean square error (MSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and R-squared (R2). The results demonstrate the superior accuracy of the TCN-Bi-LSTM-TPA hybrid model in predicting USV roll angle and pitch angle, validating its effectiveness in addressing the challenges of multivariate USV motion prediction.
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In order to detect abnormal heat generation in time, a reversible color-changing coating temperature measurement method is proposed for self-detection of temperature by power equipment, and its adhesion characteristics and aging performance were analyzed. The results showed that the reversible color-changing coating prepared
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In order to detect abnormal heat generation in time, a reversible color-changing coating temperature measurement method is proposed for self-detection of temperature by power equipment, and its adhesion characteristics and aging performance were analyzed. The results showed that the reversible color-changing coating prepared with crystalline violet lactone as the colorant, bisphenol A as the color developer, octadecanol as the solvent, and RTV-II as the base paint can meet the requirements of self-detection of temperature by power equipment with its adhesion performance. The accelerated aging tests using high temperature, light and humidity were carried out in the laboratory, and we concluded that the deterioration degree of the color-changing coating was positively correlated with the temperature. Light can accelerate the aging rate of reversible color-changing coatings, and the degradation process of the coating was significantly accelerated under UV light. The effect of humidity on the coating was not significant. The degradation of the coating after aging for 288 h under indoor conditions was small, while it was accelerated under outdoor natural conditions. This research can provide a reference for the on-site application of reversible color-changing coatings for self-detection of temperature by power equipment.
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“Paying it forward” is a behavior in which people help someone else because they were helped in the past. Although experimental evidence exists that indicates that real human beings often “pay-it-forward” even in the face of free-rider risks, the theoretical basis for the
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“Paying it forward” is a behavior in which people help someone else because they were helped in the past. Although experimental evidence exists that indicates that real human beings often “pay-it-forward” even in the face of free-rider risks, the theoretical basis for the evolution of this behavior remains unclear. In this paper, we propose a game-theoretical model that explains how pay-it-forward behavior can evolve despite the temptation to free-ride. By assuming that human beings exhibit cognitive distortions, as predicted by prospect theory, and that free-riding is punished with a tiny probability, we demonstrate that pay-it-forward, alongside unconditional altruistic behavior, can evolve and effectively deter free-riding behavior.
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UVB radiation is known to induce photodamage to the skin, disrupt the skin barrier, elicit cutaneous inflammation, and accelerate the aging process. Agaricus blazei Murill (ABM) is an edible medicinal and nutritional fungus. One of its constituents, Agaricus blazei Murill polysaccharide (ABP), has
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UVB radiation is known to induce photodamage to the skin, disrupt the skin barrier, elicit cutaneous inflammation, and accelerate the aging process. Agaricus blazei Murill (ABM) is an edible medicinal and nutritional fungus. One of its constituents, Agaricus blazei Murill polysaccharide (ABP), has been reported to exhibit antioxidant, anti-inflammatory, anti-tumor, and immunomodulatory effects, which suggests potential effects that protect against photodamage. In this study, a UVB-induced photodamage HaCaT model was established to investigate the potential reparative effects of ABP and its two constituents (A1 and A2). Firstly, two purified polysaccharides, A1 and A2, were obtained by DEAE-52 cellulose column chromatography, and their physical properties and chemical structures were studied. A1 and A2 exhibited a network-like microstructure, with molecular weights of 1.5 × 104 Da and 6.5 × 104 Da, respectively. The effects of A1 and A2 on cell proliferation, the mitochondrial membrane potential, and inflammatory factors were also explored. The results show that A1 and A2 significantly promoted cell proliferation, enhanced the mitochondrial membrane potential, suppressed the expression of inflammatory factors interleukin-1β (IL-1β), interleukin-8 (IL-8), interleukin-6 (IL-6), and tumor necrosis factor α (TNF-α), and increased the relative content of filaggrin (FLG) and aquaporin-3 (AQP3). The down-regulated JAK-STAT signaling pathway was found to play a role in the response to photodamage. These findings underscore the potential of ABP to ameliorate UVB-induced skin damage.
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Introduction: We applied a convergent mixed-methods research design, focusing on data from Swiss students to identify patterns of resilience development in high school. Method: The study consisted of an online longitudinal survey conducted in two waves, in autumn 2019 (n = 377 grade
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Introduction: We applied a convergent mixed-methods research design, focusing on data from Swiss students to identify patterns of resilience development in high school. Method: The study consisted of an online longitudinal survey conducted in two waves, in autumn 2019 (n = 377 grade seven) and spring 2021 (n = 257 grade eight). By combining latent transition analysis (LTA), a person-oriented quantitative method, and qualitative content analysis, we detected four resilience patterns. Results: The longitudinal survey revealed a decrease in the “blooming” pattern (students who displayed high levels of individual and social support indicators as well as satisfaction with their grades and academic success measures) over time and, on the other hand, an increase in the “challenged” pattern, suggesting larger numbers of students with low levels of social support and academic success. Additionally, qualitative interviews were conducted with four students from the sample. These interviews provided insights into the stressors; coping experiences, skills, processes, and resources; and outcomes related to resilience. Discussion: The analysis revealed key factors contributing to resilience, including empowering experiences, supportive individuals, self-help as a prioritized resource, and a positive school environment. Merging the data has elicited various claims such as improving both home and school environments, along with focusing on elaborating their interplay, is the most efficacious approach to bolstering resilience.
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In order to improve the control of a moving mirror control system and enhance the anti-interference ability of the system, active disturbance rejection control (ADRC) with parameter autotuning is proposed and applied to control a rotary voice coil motor (RVCM). Improved snake optimization
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In order to improve the control of a moving mirror control system and enhance the anti-interference ability of the system, active disturbance rejection control (ADRC) with parameter autotuning is proposed and applied to control a rotary voice coil motor (RVCM). Improved snake optimization (I-SO) was applied to tune and optimize ADRC’s key parameters. To obtain excellent parameters efficiently, in the population initialization phase of SO, the quality and diversity of initial solutions were improved through a chaotic elite opposition learning algorithm. In the local search phase, a sine and cosine (SC) search mode was introduced to enhance the local search ability of SO. The simulation results show that I-SO can effectively find the ideal parameters. I-SO has excellent search capability and stability. The experimental control system of a moving mirror was established, and the effectiveness of the parameters optimized by I-SO was verified. ADRC with parameter autotuning showed excellent control in the moving mirror control system, and the stability of the optical path scanning speed reached 99.2%.
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The Internet of Things (IoT) has become a transformative technological infrastructure, serving as a benchmark for automating and standardizing various activities across different domains to reduce human effort, especially in hazardous environments. In these networks, devices with embedded sensors capture valuable information about
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The Internet of Things (IoT) has become a transformative technological infrastructure, serving as a benchmark for automating and standardizing various activities across different domains to reduce human effort, especially in hazardous environments. In these networks, devices with embedded sensors capture valuable information about activities and report it to the nearest server. Although IoT networks are exceptionally useful in solving real-life problems, managing duplicate data values, often captured by neighboring devices, remains a challenging issue. Despite various methodologies reported in the literature to minimize the occurrence of duplicate data, it continues to be an open research problem. This paper presents a sophisticated data aggregation approach designed to minimize the ratio of duplicate data values in the refined set with the least possible information loss in IoT networks. First, at the device level, a local data aggregation process filters out outliers and duplicates data before transmission. Second, at the server level, a dynamic programming-based non-metric method identifies the longest common subsequence (LCS) among data from neighboring devices, which is then shared with the edge module. Simulation results confirm the approach’s exceptional performance in optimizing the bandwidth, energy consumption, and response time while maintaining high accuracy and precision, thus significantly reducing overall network congestion.
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Thinopyrum intermedium (2n = 6x = 42, EeEeEbEbStSt or JJJsJsStSt) contains a large number of genes that are highly adaptable to the environment and immune to a variety of wheat diseases,
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Thinopyrum intermedium (2n = 6x = 42, EeEeEbEbStSt or JJJsJsStSt) contains a large number of genes that are highly adaptable to the environment and immune to a variety of wheat diseases, such as powdery mildew, rust, and yellow dwarf, making it an important gene source for the genetic improvement of common wheat. Currently, an important issue plaguing wheat production and breeding is the spread of pests and illnesses. Breeding disease-resistant wheat varieties using disease-resistant genes is currently the most effective measure to solve this problem. Moreover, alien resistance genes often have a stronger disease-resistant effect than the resistance genes found in common wheat. In this study, the wheat-Th. intermedium partial amphiploid line 92048 was developed through hybridization between Th. intermedium and common wheat. The chromosome structure and composition of 92048 were analyzed using ND-FISH and molecular marker analysis. The results showed that the chromosome composition of 92048 (Octoploid Trititrigia) was 56 = 42W + 6J + 4Js + 4St. In addition, we found that 92048 was highly resistant to a mixture of stripe rust races (CYR32, CYR33, and CYR34) during the seedling stage and fusarium head blight (FHB) in the field during the adult plant stage, suggesting that the alien or wheat chromosomes in 92048 had disease-resistant gene(s) to stripe rust and FHB. There is a high probability that the gene(s) for resistance to stripe rust and FHB are from the alien chromosomes. Therefore, 92048 shows promise as a bridge material for transferring superior genes from Th. intermedium to common wheat and improving disease resistance in common wheat.
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Recently, lumped Mach-Zehnder Modulators (MZMs) have received renewed attention due to their potential for low power consumption and compact size. However, the practicality of lumped MZMs with conventional lumped electrodes (C-LEs) is limited by their lower electro-optical (EO) bandwidth. The reduction in EO
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Recently, lumped Mach-Zehnder Modulators (MZMs) have received renewed attention due to their potential for low power consumption and compact size. However, the practicality of lumped MZMs with conventional lumped electrodes (C-LEs) is limited by their lower electro-optical (EO) bandwidth. The reduction in EO bandwidth results from the inherent trade-off between EO bandwidth and half-wave voltage length product () within the C-LE architecture. This paper proposes a thin-film lithium niobate (TFLN)-based lumped MZM with capacitively-loaded lumped electrodes (CL-LEs). The purely linear EO effect of the LN eliminates the parasitic capacitance in the doped PN junction and enhances the EO bandwidth. Furthermore, the CL-LE structure can break the limitation between EO bandwidth and inherent in the C-LE design. Simulations show the proposed device achieves a high EO bandwidth of 32.4 GHz and a low of 1.15 V·cm. Due to the reduced capacitance and lower , the power consumption of the device is as low as 0.1 pJ/bit. Simulation results indicate that the open-eye diagrams are achieved at 64 Gb/s for 1.5 mm TFLN lumped MZM, with an ER of 2.97 dB. Consequently, the proposed device architecture substantially enhances the performance of lumped MZMs, showing promise for application in short-reach optical interconnects within data centers.
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With the acceleration of urbanization, the increasing frequency of building fires has caused a large number of deaths and economic losses. In order to delve into the evacuation route selection behaviors seen in library fires and analyze the impacts of individual evacuation psychologies
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With the acceleration of urbanization, the increasing frequency of building fires has caused a large number of deaths and economic losses. In order to delve into the evacuation route selection behaviors seen in library fires and analyze the impacts of individual evacuation psychologies on route decisions during escaping, based on practical survey data from the library on the Boda campus of Xinjiang University, this study built a mixed Logit (ML) model irrespective of latent psychological variables and a hybrid choice model (HCM) considering the latent variables of adaptive evacuation psychologies to investigate the internal formation mechanism of evacuees’ route decisions. The results indicate that evacuees’ non-adaptive conformity psychology, adaptive altruism psychology, and environmental familiarity have significant impacts on their route decisions. The stronger the evacuees’ non-adaptive inertia psychology, the more they lean towards the shortest route. Meanwhile, altruistic adaptive evacuation psychology has a significant negative impact on the probability of choosing the longest route. The stronger the evacuees’ environmental familiarity, the more they tend to choose the evacuation route with good emergency lighting. Personal socio-economic attributes have varying impacts on peoples’ evacuation route decisions. The findings of our study provide theoretical support for sustainable planning, preparedness, and the design of fire evacuations. This contribution aids in advancing sustainable practices for emergency responses.
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Sleep bruxism (SB) can be determined with different diagnostic procedures. The relationship between psychometric variables and SB varies depending on the diagnostic method. The aim of the study was to compare the association between SB and oral health-related quality of life (OHRQoL; measured
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Sleep bruxism (SB) can be determined with different diagnostic procedures. The relationship between psychometric variables and SB varies depending on the diagnostic method. The aim of the study was to compare the association between SB and oral health-related quality of life (OHRQoL; measured by the Oral Health Impact Profile, OHIP), anxiety (measured by the State-Trait anxiety inventory, STAI), and stress (single scale variable) depending on the diagnostic method in the same sample. N = 45 participants were examined by non-instrumental (possible/probable SB) and instrumental methods (definite SB). The OHIP differed significantly between possible SB (median = 4) and non-SB (median = 0) with W = 115, p = 0.01, and probable SB (median = 6) and non-SB (median = 0) with W = 101, p = 0.01). There was no significant difference in the OHIP score between definite SB and non-SB. For the other psychometric variables, the analyses revealed no significant differences between SB and non-SB in all diagnostic procedures. The results suggest that there is a difference between possible/probable and definite SB with respect to the association with OHRQoL. Certain aspects of possible/probable SB might be responsible for the poor OHRQoL, which are not measured in definite SB.
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by
Maria del Carmen Herena-Funes, Caroline Correia de Alencar, Dara María Velázquez-Torres, Elisenda Marrero García, Yolanda Castellote-Caballero, Felipe León-Morillas, Aday Infante-Guedes and David Cruz-Díaz
Pelvic floor dysfunctions, associated with alterations in respiratory mechanics and, consequently, quality of life, are the cause of the most frequent gynecological problems. Pelvic floor muscle training emerges as a first-line treatment, with new approaches such as hypopressive exercises. The aim of this
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Pelvic floor dysfunctions, associated with alterations in respiratory mechanics and, consequently, quality of life, are the cause of the most frequent gynecological problems. Pelvic floor muscle training emerges as a first-line treatment, with new approaches such as hypopressive exercises. The aim of this study was to analyze the efficacy of an 8-week supervised training program of hypopressive exercises on the pelvic floor and its impact on improving the ventilatory mechanics and quality of life in women. Analysis of the spirometric parameters showed a significant main Group × Time effect for three parameters: the ratio of FEV1/FVC (p = 0.030), the forced expiratory flow at 75% of the expired vital capacity (p < 0.001), and the forced expiratory flow over the middle half of the forced vital capacity (p = 0.005). No statistical significance was found regarding the SF-12 questionnaire components; only differences were found over time in the physical role (p = 0.023), bodily pain (p = 0.001), and vitality (p < 0.010) domains and in the physical component summary score (p = 0.010). After an 8-week intervention of hypopressive exercises, an improvement in the ventilatory and pulmonary capacities can be observed.
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