Many physical factors influence post-stroke functional outcomes. However, few studies have examined the influence of height on these outcomes. Here, data from the Korean Stroke Cohort for Functioning and Rehabilitation were used and patients’ height was categorized into three groups: short (lower 25%), middle (middle 50%), and tall (upper 25%). Differences in the modified Rankin scale (mRS), functional ambulatory category (FAC), and Korean-translated version of the Modified Barthel Index (K-MBI) scores were analyzed for each group at 6 months post-stroke. A subgroup analysis was conducted based on the initial Fugl-Meyer Assessment (FMA) score. We analyzed functional outcomes in 5296 patients at 6 months post-stroke, adjusting for age and body mass index. The short-height group exhibited higher mRS scores (1.88 ± 0.043), lower FAC scores (3.74 ± 0.045), and lower K-MBI scores (82.83 ± 0.748) than the other height groups (p < 0.05). In the subgroup analysis, except for the very severe FMA group, the short-height group also exhibited worse outcomes in terms of mRS, FAC, and K-MBI scores (p < 0.05). Taken together, the short-height group exhibited worse outcomes related to disability, gait function, and ADLs at 6 months post-stroke. Full article

In humans, the transient receptor potential vanilloid 1 (TRPV1) gene is activated by exogenous (e.g., high temperatures, irritating compounds such as capsaicin) and endogenous (e.g., endocannabinoids, inflammatory factors, fatty acid metabolites, low pH) stimuli. It has been shown to be involved in several processes including nociception, thermosensation, and energy homeostasis. In this study, we investigated the association between TRPV1 gene variants, sensory perception (to capsaicin and PROP), and body composition (BMI and bioimpedance variables) in human populations. By comparing sequences deposited in worldwide databases, we identified two haplotype blocks (herein referred to as H1 and H2) that show strong stabilizing selection signals (MAF approaching 0.50, Tajima’s D > +4.5) only in individuals with sub-Saharan African ancestry. We therefore studied the genetic variants of these two regions in 46 volunteers of sub-Saharan descent and 45 Italian volunteers (both sexes). Linear regression analyses showed significant associations between TRPV1 diplotypes and body composition, but not with capsaicin perception. Specifically, in African women carrying the H1-b and H2-b haplotypes, a higher percentage of fat mass and lower extracellular fluid retention was observed, whereas no significant association was found in men. Our results suggest the possible action of sex-driven balancing selection at the non-coding sequences of the TRPV1 gene, with adaptive effects on water balance and lipid deposition. Full article

This epidemiological model forecasted reductions in recurrences and recurrence treatment cost savings with adjuvant atezolizumab vs best supportive care among Canadians with stage II-IIIA non-small cell lung cancer (NSCLC) at national and provincial levels. The population had resected, programmed cell death 1 ligand 1 (PD-L1)–high (≥50%), EGFR−, ALK−, stage II-IIIA NSCLC eligible for adjuvant treatment. Patients with recurrence or death and the costs of treating recurrences were estimated for those receiving adjuvant atezolizumab or best supportive care each year (2024–2034). Proportions of patients expected to be event free up to 10 years after treatment initiation were extrapolated with parametric survival analyses. In the base case analysis, 240 fewer recurrences were estimated to occur over 10 years (2024–2034) with adjuvant atezolizumab vs best supportive care across Canada, with 136 (57%) and 104 (43%) fewer locoregional and metastatic recurrences, respectively. Projected costs of treated recurrences were CAD 33.2 million less over 10 years with adjuvant atezolizumab at a national level (adjuvant atezolizumab, CAD 135.8 million; best supportive care, CAD 169.0 million). This model predicts a considerable long-term reduction in recurrences and substantial treatment cost savings with adjuvant atezolizumab vs best supportive care for patients with PD-L1–high early-stage NSCLC in Canada. Full article

The genus Cleopus Dejean, 1821 is herein revised for the first time. Based on adult morphological characteristics, 18 species are recognized as valid. Thirteen species, all distributed in the Eastern Palaearctis or Oriental region, are described as new: C. aduncirostris sp. n.; C. cognatus sp. n.; C. confusus sp. n.; C. dohertyi sp. n.; C. hajeki sp. n.; C. lirenae sp. n.; C. longitarsis sp. n.; C. minutus sp. n.; C. pallidisquamosus sp. n.; C. parvidentatus sp. n.; C. philippinensis sp. n.; C. simillimus sp. n.; and C. subaequalis sp. n. Lectotypes of following two valid species and three synonyms were designated: Curculio solani Fabricius, 1792; Curculio pulchellus Herbst, 1795; Cionus setiger Germar, 1821; Curculio immunis Marsham, 1802; and Cleopus pulchellus rigidus Stephens, 1831. Neotypes of Curculio perpensus Rossi, 1792 and Cleopus pulchellus flavus Stephens, 1832 were designated. The following new synonyms of Cleopus pulchellus (Herbst, 1795) were established: Cleopus pulchellus var. flavus Stephens, 1831 syn. n. and C. pulchellus var. rigidus Stephens, 1831 syn. n. Full article

Cold-mix asphalt is a greener alternative to pavement construction, processed at 10–40 °C, which is typically lower than other techniques like warm-mix asphalt and hot-mix asphalt. Huge amounts of construction and demolition waste, such as broken bricks, recycled concrete aggregates, reclaimed asphalt pavement, ceramic waste, etc., are generated every year due to the acceleration in infrastructure development. The production of such massive amounts causes landfilling issues, and their disposal is a serious issue nowadays. This study examines the effect of binary blended fillers on the performance of cold asphalt mixes using emulsified binders and 50% reclaimed asphalt pavement materials. Moreover, three types of binary blended fillers (BBFs), cement, fly ash, and Stabil Road, were used at different dosages. Overall, 500 samples were prepared for the mix design, and the optimum emulsion content was determined as 11% and 9% for the CM and 50R mixes, respectively, based on the Marshall stability peak value and volumetric properties such as voids in the mineral aggregates, total voids, and dry density. The moisture susceptibility of the recycled cold-mix asphalt (RCMA) mixture was evaluated using the tensile strength ratio. Cantabro abrasion loss was used to assess the cohesion resistance of the mixtures. The dynamic response of the mixes to the applied load was evaluated using the resilient modulus. The results of the present study reveal that using BBFs in the RCMA improved the inter-particle bonding and strength. Furthermore, BBF incorporation enhanced the performance of the recycled cold-mix asphalt. Full article

Octacalcium phosphate (OCP) is an attractive base material to combine into components developed for medical purposes, especially those used in bone replacement procedures, not only because of its excellent biocompatibility but also because of its ability to intercalate with multiple types of molecular layers such as silica, dicarboxylic acid, and various cations. On the other hand, there are no examples of simultaneous substituting for several different compounds on OCPs. Therefore, in this study, the physical and mechanical strength (DTS: diametral tensile strength) of OCPs substituted with both silica and dicarboxylic acids (thiomalate: SH-malate) were evaluated. By optimizing the amount of SH-malate, we were able to prepare a block consisting of OCPs with both silica and SH-malate supported in the interlayer. The composition of the OCP-based compound comprising this block was Ca₈Na_1.07H_6.33(PO₄)_4.44(SiO₄)_1.32(SH-malate)_2.40∙nH₂O. Interestingly, the low mechanical strength, a drawback of silica-substituted OCP blocks, could be improved by dicarboxylic acid substituting. The dicarboxylic acid addition increased the mechanical strength of silica-substituted OCP blocks, and the acid successfully incorporated into the interlayer, even with the presence of silica. These results are expected to advance the creation of better silica-substituted OCPs and improved bone replacement materials. Full article

The rapid and accurate estimation of leaf area index (LAI) through remote sensing holds significant importance for precise crop management. However, the direct construction of a vegetation index model based on multi-spectral data lacks robustness and spatiotemporal expansibility, making its direct application in practical production challenging. This study aimed to establish a simple and effective method for LAI estimation to address the issue of poor accuracy and stability that is encountered by vegetation index models under varying conditions. Based on seven years of field plot trials with different varieties and nitrogen fertilizer treatments, the Kalman filter (KF) fusion method was employed to integrate the estimated outcomes of multiple vegetation index models, and the fusion process was investigated by comparing and analyzing the relationship between fixed and dynamic variances alongside the fusion accuracy of optimal combinations during different growth stages. A novel multi-model integration fusion method, KF-DGDV (Kalman Filtering with Different Growth Periods and Different Vegetation Index Models), which combines the growth characteristics and uncertainty of LAI, was designed for the precise monitoring of LAI across various growth phases of rice. The results indicated that the KF-DGDV technique exhibits a superior accuracy in estimating LAI compared with statistical data fusion and the conventional vegetation index model method. Specifically, during the tillering to booting stage, a high R² value of 0.76 was achieved, while at the heading to maturity stage, it reached 0.66. In contrast, within the framework of the traditional vegetation index model, the red-edge difference vegetation index (DVIREP) model demonstrated a superior performance, with an R² value of 0.65, during tillering to booting stage, and 0.50 during the heading to maturity stage, respectively. The multi-model integration method (MME) yielded an R² value of 0.67 for LAI estimation during the tillering to booting stage, and 0.53 during the heading to maturity stage. Consequently, KF-DGDV presented an effective and stable real-time quantitative estimation method for LAI in rice. Full article

Among the world’s most important three chief black lands, China’s northeast region is a vital hub for the commercial extraction of grain, undertaking the task of grain reserves and special transfers. Utilizing the provincial data of the three northeastern provinces from 2010 to 2021, and using existing documents and records as essential elements, we structured a land security appraisal system with five criterion layers and 21 indicator layers of pressure, state, impact, response, and management. The three provinces in the northeast were evaluated for the security of their land resources using the entropy-dependent weight-TOPSIS pattern. The study findings indicate that: (1) In general, land resource security of the three northeastern provinces shows a pattern of decline followed by a gradual increase from 2012 to 2021, and there is a steady improvement in the level of land’s ecological stability; (2) There are differences in the ecological stability of the soil across cities and provinces, with Heilongjiang Province having the best land security status and Liaoning Province having the worst; (3) The amount of soil erosion in tiny watersheds is the indicator that has the biggest influence on land ecological stability in the three provinces in the northeast; (4) The response layer is the criterion layer that has the strongest correlation with land ecological safety. Full article

In the semiconductor manufacturing industry, achieving high yields constitutes one of the pivotal factors for sustaining market competitiveness. When confronting the substantial volume of high-dimensional, non-linear, and imbalanced data generated during semiconductor manufacturing processes, it becomes imperative to transcend traditional approaches and incorporate machine learning methodologies. By employing non-linear classification models, one can achieve more real-time anomaly detection, subsequently facilitating a deeper analysis of the fundamental causes behind anomalies. Given the considerable dimensionality of production line data in semiconductor manufacturing, there arises a necessity for dimensionality reduction to mitigate noise and reduce computational costs within the data. Feature selection stands out as one of the primary methodologies for achieving data dimensionality reduction. Utilizing wrapper-based heuristics algorithms, although characterized by high time complexity, often yields favorable performance in specific cases. If further combined into hybrid methodologies, they can concurrently satisfy data quality and computational cost considerations. Accordingly, this study proposes a two-stage feature selection model. Initially, redundant features are eliminated using mutual information to reduce the feature space. Subsequently, a Simplified Swarm Optimization algorithm is employed to design a unique fitness function aimed at selecting the optimal feature subset from candidate features. Finally, support vector machines are utilized as the classification model for validation purposes. For practical cases, it is evident that the feature selection method proposed in this study achieves superior classification accuracy with fewer features in the context of wafer anomaly classification problems. Furthermore, its performance on public datasets further substantiates the effectiveness and generalization capability of the proposed approach. Full article

Paclitaxel induces multipolar spindles at clinically relevant doses but does not substantially increase mitotic indices. Paclitaxel’s anti-cancer effects are hypothesized to occur by promoting chromosome mis-segregation on multipolar spindles leading to apoptosis, necrosis and cyclic-GMP-AMP Synthase–Stimulator of Interferon Genes (cGAS-STING) pathway activation in daughter cells, leading to secretion of type I interferon (IFN) and immunogenic cell death. Eribulin and vinorelbine have also been reported to cause increases in multipolar spindles in cancer cells. Recently, suppression of Anaphase-Promoting Complex/Cyclosome–Cell Division Cycle 20 (APC/C-CDC20) activity using CRISPR/Cas9 mutagenesis has been reported to increase sensitivity to Kinesin Family 18a (KIF18a) inhibition, which functions to suppress multipolar mitotic spindles in cancer cells. We propose that a way to enhance the effectiveness of anti-cancer agents that increase multipolar spindles is by suppressing the APC/C-CDC20 to delay, but not block, anaphase entry. Delaying anaphase entry in genomically unstable cells may enhance multipolar spindle-induced cell death. In genomically stable healthy human cells, delayed anaphase entry may suppress the level of multipolar spindles induced by anti-cancer drugs and lower mitotic cytotoxicity. We outline specific combinations of molecules to investigate that may achieve the goal of enhancing the effectiveness of anti-cancer agents. Full article

Liquefaction conversion technology has become one of the hottest biomass conversion methods due to its flexible material selection and extensive product applications. Exploring biomass liquefaction conversion focuses on catalysts, biomass/water ratio, and reaction temperature. However, it is found that solvents are crucial in the biomass liquefaction process and significantly impact the type of liquefied products and bio-oil yield. Given the current rapid development trend, timely sorting and summary of the solvent effect in the biomass liquefaction process can promote the subsequent development and industrialization of more efficient and cleaner biomass liquefaction technology. Therefore, this review first introduces the characteristics of water as the liquefaction solvent, then summarizes the effects of organic solvents on liquefaction, and finally elaborates on the synergistic effect of co-solvents, which provides a more systematic overview of solvent effects in the liquefaction process. Meanwhile, prospects are put forward for the future development of biomass liquefaction conversion. Full article

Industrialization has brought many environmental problems since its expansion, including heavy metal contamination in water used for agricultural irrigation. This research uses microbial fuel cell technology to generate bioelectricity and remove arsenic, copper, and iron, using contaminated agricultural water as a substrate and Bacillus marisflavi as a biocatalyst. The results obtained for electrical potential and current were 0.798 V and 3.519 mA, respectively, on the sixth day of operation and the pH value was 6.54 with an EC equal to 198.72 mS/cm, with a removal of 99.08, 56.08, and 91.39% of the concentrations of As, Cu, and Fe, respectively, obtained in 72 h. Likewise, total nitrogen concentrations, organic carbon, loss on ignition, dissolved organic carbon, and chemical oxygen demand were reduced by 69.047, 86.922, 85.378, 88.458, and 90.771%, respectively. At the same time, the PD_MAX shown was 376.20 ± 15.478 mW/cm², with a calculated internal resistance of 42.550 ± 12.353 Ω. This technique presents an essential advance in overcoming existing technical barriers because the engineered microbial fuel cells are accessible and scalable. It will generate important value by naturally reducing toxic metals and electrical energy, producing electric currents in a sustainable and affordable way. Full article

The continual expansion in the number of images poses a great challenge for the annotation of the data. Therefore, improving the model performance for image classification with limited labeled data has become an important problem to solve. To address the problem, we propose in this paper a simple and effective dual-training-based semi-supervised learning method for image classification. To enable the model to acquire more valuable information, we propose a dual training approach to enhance model training. Specifically, the model is trained with different augmented data at the same time with soft labels and hard labels, respectively. In addition, we propose a simple and effective weight generation method for generating the weight of samples during training to guide the model training. To further improve the model performance, we employ a projection layer at the end of the network to guide the self-learning of the model by minimizing the distance of features extracted from different layers. Finally, we evaluate the proposed approach on three benchmark image classification datasets. The experimental results demonstrate the effectiveness of our proposed approach. Full article

In this study, the thickness of a thin film (t_c) at a low primary electron energy of less than or equal to 10 keV was calculated using electron energy-loss spectroscopy. This method uses the ratio of the intensity of the transmitted background spectrum to the intensity of the transmission electrons with zero-loss energy (elastic) in the presence of an accurate average inelastic free path length (λ). The Monte Carlo model was used to simulate the interaction between the electron beam and the tested thin films. The total background of the transmitted electrons is considered to be the electron transmitting the film with an energy above 50 eV to eliminate the effect of the secondary electrons. The method was used at low primary electron energy to measure the thickness (t) of C, Si, Cr, Cu, Ag, and Au films below 12 nm. For the C and Si films, the accuracy of the thickness calculation increased as the energy of the primary electrons and thickness of the film increased. However, for heavy elements, the accuracy of the film thickness calculations increased as the primary electron energy increased and the film thickness decreased. High accuracy (with 2% uncertainty) in the measurement of C and Si thin films was observed at large thicknesses and 10 keV, where . However, in the case of heavy-element films, the highest accuracy (with an uncertainty below 8%) was found for thin thicknesses and 10 keV, where . The present results show that an accurate film thickness measurement can be obtained at primary electron energy equal to or less than 10 keV and a ratio of . This method demonstrates the potential of low-loss electron energy-loss spectroscopy in transmission electron microscopy as a fast and straightforward method for determining the thin-film thickness of the material under investigation at low primary electron energies. Full article

Mediterranean grasslands provide different ecosystems and social and economic services to the Mediterranean basin. Specifically, in Spain, pastures occupy more than 55% of the Spanish surface. Farmers and policymakers need to estimate the Gross Primary Production (GPP) to make sustainable management of these ecosystems and to study the role of grasslands acting as sinks or sources of Carbon in the context of climate change. High-frequency satellites, such as Sentinel-2, have opened the door to study GPP with a higher spatial and lower revisit time (10 m and 5 days). Therefore, the overall objective of this research is to estimate an ecosystem light use efficiency (eLUE) GPP model for a Mediterranean grassland in central Spain using Sentinel-2 NDVI Normalized Difference Vegetation Index (NDVI), complemented with meteorological information at the field scale for a relatively long period (from January 2018 to July 2020). The GPP models studied in this research were the MODIS GPP product, as well as the four eLUE models built with MODIS or Sentinel-2 NDVI and complemented by the inclusion of minimum temperature (T_min) and soil water content (SWC). The models were validated through the GPP obtained from an eddy-covariance flux tower located in the study site (GPP_T). Results showed that the MODIS GPP product underestimated the GPP_T of the grassland ecosystem. Besides this, the approach of the eLUE concept was valid for estimating GPP in this Mediterranean grassland ecosystem. In addition, the models showed an improvement using Sentinel-2 NDVI compared to MODIS GPP product and compared to the models that used MODIS NDVI due to its higher spatial and temporal resolution. The inclusion of T_min and SWC was also a determinant in improving GPP models during winter and summer periods. This work also illustrates how the main wind directions of the study area must be considered to appropriately estimate the footprint of the eddy covariance flux tower. In conclusion, this study is the first step to efficiently estimating the GPP of Mediterranean grasslands using the Sentinel-2 NDVI with complementary meteorological field information to make the management of these ecosystems sustainable. Full article

Growing global concern over greenhouse gas emissions has led to a demand for understanding and addressing carbon emissions, with China being one of the main contributors to global carbon emissions, committed to reach the carbon peak by 2030. As a result, much previous research has delved into the drivers of carbon emissions in China; however, few studies have included new energy factors in the extended STIRPAT model when analysing the data, employed more advanced visualisation techniques such as force-directed diagrams, and explored factors outside of the industrial and energy sectors in determining China’s ability to reach their environmental goals. In this study, we use the extended STIRPAT model to analyse a more diverse range of drivers for carbon emissions in China and discuss methods to reach peak carbon emissions through the implementation of environmental policies. Using data from China’s 14th Five-Year Plan and Vision 2035 to set up two simulation scenarios, we predict China’s carbon emissions, introducing ridge regression to ensure validity, and employing big data and visualisation techniques to aid in interpreting results. Our findings suggest that China needs to implement more stringent environmental policies to meet its commitment to reach peak carbon emissions by 2030, revealing that factors such as per capita arable land area, per capita GDP, the proportion of people living in extreme poverty, the level of tourism development, the use of fossil fuels, and new energy technologies have a significant impact on China’s carbon emissions. As such, we can recommend more stringent policies relating to the agricultural, energy, and tourism sectors to help China achieve their goal of carbon peak by 2030. Full article

In semiconductor manufacturing, multi-space process modules (PMs) are adopted in some cluster tools for wafer processing. With multi-space PMs, a PM can have multiple wafers concurrently. Also, the internal chamber in a PM should rotate to make the robot able to load/unload a wafer into/from a space in the PM. This means that the wafer staying time in PMs is affected by both the rotation operations of the internal chambers of PMs and the robot tasks. Thus, minimizing the wafer delay time is quite challenging. In this work, for cluster tools with single-arm robots and two-space PMs, efforts are made for wafer delay minimization in scheduling the tools. Specifically, a two-wafer backward strategy is presented to operate the tools in a steady state. Then, the workloads of each processing step and the robot are analyzed. Further, to find optimal schedules with the objective of minimizing the total wafer delay time, efficient algorithms are established. Finally, case studies show that the wafer delay time at some steps can be totally eliminated by the proposed method. In the meantime, in all cases, the proposed method can work well in reducing the total wafer delay time at all steps. Full article

Residential segregation refers to the phenomenon where people of different socioeconomic backgrounds live in spatially separated areas. It is essential to ensure equitable access to urban amenities for all residents in pursuit of the normative values in urban planning. To achieve this planning goal, the disparity in accessibility to urban amenities needs to be appropriately diagnosed. Private apartments and public rental apartments are representative types of residences where residential segregation is likely to occur in the context of South Korea, since these two types show considerable differences in education, income, and occupations. The objective of this study is to develop an analysis framework for diagnosing the difference in accessibility to urban amenities between the two residential types, and to empirically demonstrate their utility in the planning process. The most highlighted methodological novelty of the proposed analysis framework is that it includes not only global indicators for diagnosing the overall level of accessibility in the entire study area and assessing its statistical significance but also local indicators that represent local variations in accessibility. The empirical analysis conducted on Seoul revealed that not only were there significant local variations in accessibility between the two segregated residential areas, but the overall differences across the entire area were also pronounced. The proposed framework is useful in supporting decision-making processes for locating new public facilities or identifying regional priorities for guiding the placement of private amenities, with the aim of mitigating differences between segregated residential areas. Full article

Human beings have created numerous laws, sayings and proverbs that still influence behaviors and decision-making processes of people. Some of the laws, sayings or proverbs are used by people to understand the phenomena that may take place in daily life. For example, Murphy’s law states that “Anything that can go wrong will go wrong.” Murphy’s law is helpful for project planning with analysis and the consideration of risk. Similar to Murphy’s law, the old saying “Two heads are better than one” also influences the determination of the ways for people to get jobs done effectively. Although the old saying “Two heads are better than one” has been extensively discussed in different contexts, there is a lack of studies about whether this saying is valid and can be applied in evolutionary computation. Evolutionary computation is an important optimization approach in artificial intelligence. In this paper, we attempt to study the validity of this saying in the context of evolutionary computation approach to the decision making of ridesharing systems with trust constraints. We study the validity of the saying “Two heads are better than one” by developing a series of self-adaptive evolutionary algorithms for solving the optimization problem of ridesharing systems with trust constraints based on the saying, conducting several series of experiments and comparing the effectiveness of these self-adaptive evolutionary algorithms. The new finding is that the old saying “Two heads are better than one” is valid in most cases and hence can be applied to facilitate the development of effective self-adaptive evolutionary algorithms. Our new finding paves the way for developing a better evolutionary computation approach for ridesharing recommendation systems based on sayings created by human beings or human intelligence. Full article

Arsenic (As) contamination of surface water has become a global concern, especially for the third world countries, and it is imperative to develop advanced materials and an effective treatment method to address the issue. In this paper, iron doped ZIF-8@MXene (Fe-ZIF-8@MXene) was prepared as a potential adsorbent to effectively and simultaneously remove As(III/V) from wastewater. To investigate this, Fe-ZIF-8@MXene was characterized before and after the removal of mixed As(III/V). The results of Fourier transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), specific surface area (BET) and point of zero charge (pHpzc) showed that Fe-ZIF-8@MXene was prepared successfully and kept a stable structure after As(III) and As(V) adsorption. The particle size of Fe-ZIF-8@MXene was in the range of 0.5 μm to 2.5 μm, where its BET was 531.7 m²/g. For both contaminants, adsorption was found to follow pseudo-second-order kinetics and was best-fitted by the Langmuir adsorption model with correlation coefficients (R²) of 0.998 and 0.997, for As(III) and As(V), respectively. The adsorbent was then applied to remove As from two actual water samples, giving maximum removal rates of 91.07% and 98.96% for As(III) and As(V), respectively. Finally, removal mechanisms for As(III/V) by Fe-ZIF-8@MXene were also explored. During the adsorption, multiple complexes were formed under the effect of its abundant surface functional groups involving multiple mechanisms, which included Van der Waals force, surface adsorption, chemical complexation and electrostatic interactions. In conclusion, this study demonstrated that Fe-ZIF-8@MXene was an advanced and reusable material for simultaneous removal of As(III/V) in wastewater. Full article

Introduction: Physical activity (PA) and exercise (EX) participation rates have not been increasing among older adults, with many not meeting recommended guidelines. This qualitative descriptive study examined factors influencing engagement in PA within and outside an older adult fitness club context, using self-determination theory (SDT). Methods: Thirty-seven community-dwelling adults 65 years and older participated in focus groups or telephone interviews. Two researchers independently coded and analyzed transcript data inductively and deductively using SDT. Results: Two broad themes, The Spectrum of Motivating Factors and Facilitators and Barriers, and nine sub-themes, Physical Activity and Exercise Brings Me Joy; Meaningful Personal Impetuses; I Get Active with a Little Help from my Spouse and Others; I See Changes and Improvements (Theme 1); I Can Do This; Connections and Sense of Belonging; I Cannot Do This; Setting, Environment, and People Supports; and Pragmatics (Theme 2), emerged from the data. All participants discussed several motivating factors: enjoyment, managing health conditions, being held ‘to account’ by others, opportunities for socialization, and seeing improvements in health and well-being. A lack of supportive environments, knowledgeable staff and suitable settings and programs were cited as barriers by participants who were not older adult fitness club members. Discussion: Factors along the extrinsic to intrinsic regulation continuum facilitated or hindered community-dwelling older adults to engage in and sustain PA within and outside an older adult fitness club context. The findings underscore the need for programs, settings, environments, and related components to be expressly older-adult-tailored to enhance motivation through competence, autonomy, and relatedness support for maximal engagement and participation in PA or EX. Full article

When there are dynamic obstacles in the environment, it is difficult for traditional path-generation algorithms to achieve desired obstacle-avoidance results. To solve this problem, we propose a robot navigation control method based on SAC (Soft Actor-Critic) Deep Reinforcement Learning. Firstly, we use a fast path-generation algorithm to control the robot to generate expert trajectories when the robot encounters danger as well as when it approaches a target, and we combine SAC reinforcement learning with imitation learning based on expert trajectories to improve the safety of training. Then, for the hybrid data consisting of agent data and expert data, we use an improved prioritized experience replay method to improve the learning efficiency of the policies. Finally, we introduce RNN (Recurrent Neural Network) units into the network structure of the SAC Deep Reinforcement-Learning navigation policy to improve the agent’s transfer inference ability in a new environment and obstacle-avoidance ability in dynamic environments. Through simulation and practical experiments, it is fully verified that our method has a higher training efficiency and navigation success rate compared to state-of-the-art reinforcement-learning algorithms, which further enhances the obstacle-avoidance capability of the robot system. Full article