Search Results (140)

Background: Digital transformation is reshaping healthcare operations, with loyalty programs increasingly used to strengthen patient engagement and streamline administrative workflows. However, fragmented information systems and manual verification routines continue to create bottlenecks, inconsistencies, and extended lead times. Methods: This study applies a mixed-methods approach within the Business Process Management (BPM) lifecycle to redesign the eligibility verification process for a loyalty program at Casa de Saúde São Mateus Hospital. Quantitative time measurements were collected during peak periods, while qualitative insights from staff observations and discussions supported process discovery and bottleneck identification. The proposed solution integrates a centralized SQL database, automated verification routines, and a dedicated administrative interface synchronized with the MedicineOne system. Results: The redesigned process reduced eligibility verification time by approximately 80% and improved Flow Efficiency by around 11.7%. Manual interventions, data fragmentation, and discount-application errors decreased substantially. The centralized database improved data reliability, while automated checks enhanced consistency and reduced staff workload. The system also enabled more accurate beneficiary management and improved coordination across administrative activities. Conclusions: Integrating Healthcare 4.0 principles with BPM enhances internal logistics, reduces lead times, and improves operational reliability. The proposed model offers a replicable framework for modernizing healthcare service delivery. Full article

Human Activity Recognition (HAR) has become crucial across various domains, including healthcare, smart homes, and security systems, owing to the proliferation of Internet of Things (IoT) devices. Several Machine Learning (ML) techniques, including Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM), have been proposed for HAR. However, they are still deficient in addressing the challenges of noisy features and insufficient data. This paper introduces a novel approach to tackle these two challenges, employing a Deep Learning (DL) Ensemble-Based Stacking Neural Network (SNN) combined with Generative Adversarial Networks (GANs) for HAR based on ambient sensors. Our proposed deep learning ensemble-based approach outperforms traditional ML techniques and enables robust and reliable recognition of activities in real-world scenarios. Comprehensive experiments conducted on six benchmark datasets from the CASAS smart home project demonstrate that the proposed stacking framework achieves superior accuracy on five out of six datasets when compared to literature-reported state-of-the-art baselines, with improvements ranging from 3.36 to 39.21 percentage points and an average gain of 13.28 percentage points. Although the baseline marginally outperforms the proposed models on one dataset (Aruba) in terms of accuracy, this exception does not alter the overall trend of consistent performance gains across diverse environments. Statistical significance of these improvements is further confirmed using the Wilcoxon signed-rank test. Moreover, the ASGAN-augmented models consistently improve macro-F1 performance over the corresponding baselines on five out of six datasets, while achieving comparable performance on the Milan dataset. The proposed GAN-based method further improves the activity recognition accuracy by a maximum of 4.77 percentage points, and an average of 1.28 percentage points compared to baseline models. By combining ensemble-based DL with GAN-generated synthetic data, a more robust and effective solution for ambient HAR addressing both accuracy and data imbalance challenges in real-world smart home settings is achieved. Full article

Practical training and recruitment strategies are critical for the sustainable implementation of psychosocial interventions. However, few studies have examined how to prepare community partners and doctoral students to support culturally adapted psycho-oncology interventions. This pre-pilot study aims first to evaluate two distinct training programs and recruitment procedures, and second to explore preliminary pre-post outcomes of the Caregiver-Patients Support to Cope with Advanced Cancer (CASA) intervention, using the Consolidated Framework for Implementation Research (CFIR). Three clinical psychology graduate students received CASA training, and two community partners completed Recruitment training. We present descriptive pre- and post-assessments, along with qualitative feedback, for both training and institutional (Puerto Rico Biobank) and community-based recruitment outcomes. A related-samples nonparametric analysis examined pre- and post-CASA intervention signals. Results indicated knowledge gains among doctoral students (pre-test M = 3.3; post-test M = 9.3) and community partners (pre-test M = 4.5; post-test M = 9.5). Preliminary outcomes revealed significant improvements in spiritual well-being (Z = −2.618, p = 0.009) and quality of life (Z = −2.957, p = 0.003) and a reduction in depressive (Z = −2.764, p = 0.006), anxiety (Z = −2.667, p = 0.008), and distress (Z = −2.195, p = 0.028) symptoms following CASA. Of 26 recruited dyads, institutional referrals enrolled 16 dyads (61.5%), while community partners referred 10 dyads with a 90.9% success rate. Findings support the feasibility of both training and CASA exploratory outcomes suggest meaningful psychosocial benefits for Latino dyads coping with advanced cancer. Combining institutional infrastructure with community engagement may enhance sustainability and equitable access to psycho-oncology care. Full article

Nature reserves serve as core spatial units for maintaining regional ecological security and biodiversity. Owing to their high ecosystem integrity, extensive vegetation cover, and low levels of disturbance, they play a crucial role in sustaining ecological processes and ensuring functional stability. Taking the Giant Panda National Park (GPNP), which spans the provinces of Gansu, Sichuan, and Shaanxi in China, as the study region, the vegetation net primary productivity (NPP) during 2001–2023 was simulated using the Carnegie–Ames–Stanford Approach (CASA) model. Spatial and temporal variations in NPP were examined using Moran’s I, Getis-Ord Gi* hotspot analysis, Theil–Sen trend estimation, and the Mann–Kendall test. In addition, the Optimal Parameters-based Geographical Detector (OPGD) model was applied to quantitatively assess the relative contributions of natural and anthropogenic factors to NPP dynamics. The results demonstrated that: (1) The mean annual NPP within the GPNP reached 646.90 gC·m⁻²·yr⁻¹, exhibiting a fluctuating yet generally upward trajectory, with an average growth rate of approximately 0.65 gC·m⁻²·yr⁻¹, reflecting the positive ecological outcomes of national park establishment and ecological restoration projects. (2) NPP exhibits significant spatial heterogeneity, with higher NPP values in the northern, while the central and western regions and some high-altitude areas remain at relatively low levels. Across the four major subregions of the GPNP, the Qinling has the highest mean annual NPP at 758.89 gC·m⁻²·yr⁻¹, whereas the Qionglai–Daxiaoxiangling subregion shows the lowest value at 616.27 gC·m⁻²·yr⁻¹. (3) Optimal NPP occurred under favorable temperature and precipitation conditions combined with relatively high solar radiation. Low elevations, gentle slopes, south facing aspects, and leached soils facilitated productivity accumulation, whereas areas with high elevation and steep slopes exhibited markedly lower productivity. Moderate human disturbance contributed to sustaining and enhancing NPP. (4) Factor detection results indicated that elevation, mean annual temperature, and land use were the dominant drivers of spatial heterogeneity when considering all natural and anthropogenic variables. Their interactions further enhanced explanatory power, particularly the interaction between elevation and climatic factors. Overall, these findings reveal the complex spatiotemporal characteristics and multi-factorial controls of vegetation productivity in the GPNP and provide scientific guidance for strengthening habitat conservation, improving ecological restoration planning, and supporting adaptive vegetation management within the national park systems. Full article

Rocky desertification severely restricts socio-economic development in the karst regions. However, assessments linking karst rocky desertification and NPP changes over the long term and at high resolution are limited. This study aims to reveal the spatiotemporal patterns and driving mechanisms of NPP changes in Wenshan Prefecture, addressing the scientific gap in quantitative process research and mechanism identification in karst desertification areas. We estimated vegetation NPP from 2000 to 2020 using remote sensing data and the CASA model. The Theil–Sen trend analysis and Mann–Kendall test were applied to assess temporal variation, while a Geographical Detector identified the dominant natural and human factors and their interactions shaping NPP spatial patterns. Our results showed that NPP increased overall by 4.07 gC m⁻² a⁻¹, alongside a general decline in rocky desertification. The most significant improvement occurred between 2010 and 2015, when rocky desertification shrank by 2224 km² and the dynamic rate reached 1.42%. Mean NPP reached 1057 gC m⁻² a⁻¹, with a “northwest high–southeast low” spatial pattern, and 77% of the region showed significant increases. Rocky desertification was most severe at elevations between 1000 and 2000 m. In the karst region, NPP is mainly controlled by natural factors, with soil depth and slope being the strongest influences. Human activity had the largest negative impact, and most factors interacted synergistically, where hydrothermal gradients and human disturbances more strongly suppressed NPP on steep, thin slopes than individually expected. These findings provide robust scientific evidence and practical decision-making support for ecological restoration, rocky desertification control and long-term sustainable development in Wenshan and other karst regions, highlighting the importance of continuous monitoring and adaptive management strategies to consolidate restoration achievements and guide future land-use planning and regional ecological policy. Full article

Quantifying carbon sequestration in cultivated land ecosystems is essential for achieving carbon neutrality and ensuring food security, yet current models often fail to capture the complex interactions between crop phenology and environmental factors at regional scales. This paper proposed an improved CASA-CGC model that couples crop phenological parameters with photosynthetic physiological processes, enabling precise carbon sink accounting at the growth cycle scale of cultivated land ecosystems. Results indicate that the carbon sequestration capacity of cultivated land in the province significantly increased from 2010 to 2022, with an average increase of 163.04 g C m⁻², and the spatial pattern showed a centralized evolution characteristic. Model validation showed that the accuracy of the CASA-CGC model is significantly better than traditional methods. Compared with remote sensing inversion products and 93 ground measurement point data, the improved CASA-CGC model increased the R² by 0.155 and reduced the RMSE by 4.19 compared with the tr-CASA model. The innovative introduction of the GeoDetector model reveals that the nonlinear interaction between natural and human factors dominates the carbon sequestration process (accounting for 60%), with the interaction effect between altitude and cropping system configuration being the strongest (q = 0.312), confirming that humans can significantly amplify the potential of natural carbon sinks by optimizing cropping systems. Full article

Cryopreservation of stallion spermatozoa remains a challenge in equine reproduction, as it induces mitochondrial dysfunction that cannot be fully captured by conventional sperm quality assessment and requires further investigation. This study provides a detailed bioenergetic evaluation of cryopreserved stallion sperm using Seahorse XFp technology to measure basal oxygen consumption rate (OCR) and to perform a MitoStress Test. Three ejaculates from 20 Warmblood stallions (licensed by the Holsteiner Verband, Elmshorn, Germany) were analyzed at 15 min intervals from 15 to 120 min after thawing. CASA and multiparametric flow cytometry were used to assess motility, sperm viability, reactive oxygen species (ROS) synthesis, lipid peroxidation (LPO), and DNA fragmentation index (%DFI). Seahorse analysis revealed marked intra- and inter-individual variability in basal OCR among frozen–thawed samples. Functional mitochondrial parameters showed only partial correlations with motility and viability results, underlining the added diagnostic value of combined metabolic profiling. Over the 2 h measurement, viability and motility displayed an increasingly negative correlation with ROS synthesis, while no significant relation was found between OCR and ROS synthesis or LPO. These findings demonstrate that stallion sperm mitochondria are highly sensitive organelles whose functional state cannot be fully assessed by routine motility or viability testing alone. Integrating Seahorse-based profiling with CASA and flow cytometry can improve sperm quality assessment. Moreover, this novel approach has been proven to be a valuable tool, offering broad opportunities for further research in stallion reproduction. Full article

In response to the problem of high energy consumption caused by inefficient temperature control of energy storage aggregates in traditional building envelope structures, this study developed a decanoic acid–stearic acid composite phase-change ceramsite aggregate to improve the thermal performance of buildings and promote the utilization of solid waste resources. Based on the theory of minimum melting, composite phase-change materials were screened through thermodynamic models. The capric acid–stearic acid (CA-SA) melt system, whose theoretical phase-transition temperature falls within the building indoor thermal environment control range (18–26 °C), was preferred as the experimental object of this study, and its characteristics were verified through step cooling curves and thermal property tests. Subsequently, the ceramsite adsorption process was optimized, and the encapsulation process was studied. Finally, the encapsulation performance was evaluated through thermal stability and stirring crushing rate tests. The results showed that the phase-transition temperature of the decanoic acid–stearic acid melt system was 24.83 °C, which accurately matched the indoor thermal environment control requirements. The ceramsite particles treated by a physical vibrating screen can reach equilibrium after 30 min of adsorption at room temperature and pressure, which is both efficient and economical. The encapsulation layer of sludge biochar cement slurry with a water–cement ratio of 0.5 and a biochar content of 3% has both thermal conductivity and encapsulation integrity. The thermal stability test showed that the percentage of leakage of sludge biochar cement slurry and epoxy resin encapsulated aggregates was 0%, and the thermal stability rating was “very stable”. However, the percentage of leakage of unencapsulated and spray-coated encapsulated aggregates was as high as 193% and 40%, respectively. The results of the mixing and crushing rate test show that although the mixing and crushing rate of sludge biochar cement slurry encapsulation is slightly higher, its production cost is much lower than that of epoxy resin, and it is also environmentally friendly. This study improves the thermal performance of buildings by using composite phase-change ceramsite aggregate, and simultaneously realizes the resource utilization of sludge biochar, providing a solution for building energy saving and efficiency that combines environmental and engineering value. Full article

The evaluation of sperm proteins has emerged as a promising approach to predicting semen quality across animal species. This study investigated the relationship between post-thaw concentrations of precursor A-kinase anchor protein 4 (proAKAP4) and objective sperm quality parameters in goats. Semen was collected from 16 adult goats (Boer, n = 8; Anglo-Nubian, n = 8) and frozen using a standardized protocol with OptiXcell (IMV Technologies, l′Aigle, France) extender (n = 5). After thawing, proAKAP4 concentrations were measured with an enzyme-linked immunosorbent assay (ELISA), while sperm motility and kinematics were assessed with computer-assisted analysis (CASA), and viability, plasma membrane integrity, acrosome integrity, and mitochondrial activity were evaluated using flow cytometry. Samples were grouped according to low, medium, or high proAKAP4 levels for comparison, and correlations with sperm parameters were examined. The results showed that semen with higher proAKAP4 concentrations had significantly greater total and progressive motility, more favorable kinematic values, and improved viability, plasma membrane integrity, and mitochondrial function (p < 0.05), whereas acrosome integrity was not influenced (p > 0.05). The average post-thaw proAKAP4 concentration was 38.66 ± 1.11 ng/10⁶ sperm, and no differences were observed between Boer and Anglo-Nubian breeds (p > 0.05). These findings indicate that proAKAP4 is strongly associated with multiple sperm functional traits and may serve as a reliable biomarker for assessing post-thaw semen quality in goats. Full article

HP, as an isotropic physical stress, has been widely applied in cell biology and reproductive research to simulate the effects of environmental pressure on cellular functions. In this study, the elastic silicone membrane of a novel bionic insemination catheter was employed as the pressure medium, with semen perfused into a sealed silicone chamber. As the silicone membrane underwent controlled deformation, the liquid inside the chamber generated a nearly uniform isotropic pressure, thereby maintaining spermatozoa in a stable HP environment. Boar sperm are susceptible to physiological and functional damage under HP stress, which can impair fertilization capacity. This study aimed to investigate the effects of TMAO, BET, or their combination on the quality of semen from eight Landrace boars under HP during storage at 17 °C (experiment repeated three times). Semen was collected using the manual collection method and treated with different concentrations of TMAO or BET. Sperm motility parameters were assessed using a CASA system to determine the optimal concentrations. Subsequently, experimental groups were established: the fresh group, HP control group, T group (optimal TMAO), B group (optimal BET), and H group (optimal TMAO + BET). The results showed that the optimal concentrations were 8 mmol/L for TMAO and 20 mmol/L for BET. Compared with the HP control group, the T, B, and H groups showed significantly improved sperm viability, mitochondrial membrane potential (MMP), and plasma membrane integrity (p < 0.05), and significantly reduced DFI, ROS, MDA, and NO contents (p < 0.05), while acrosome integrity showed no significant differences (p > 0.05). Additionally, the B group showed significantly increased T-AOC (p < 0.05). Non-targeted lipidomic analysis revealed 49 differential lipids in the T group, 262 in the B group, and 269 in the H group compared with the HP control. These differential lipids were mainly associated with PC, AcCa, and sphingolipid signaling pathways, with key sphingolipid pathway lipids including Cer, SM, and DG. These findings indicate that BET and TMAO + BET improve HP-induced sperm damage by modulating the sphingolipid signaling pathway and maintaining PC and AcCa levels, whereas TMAO alone may exert protective effects through additional mechanisms. In conclusion, TMAO, BET, or their combination effectively mitigates the detrimental effects of HP on boar sperm. Full article

Dietary fiber plays an important role in animal nutrition by influencing gut health, feed intake, and metabolism. In swine production, studies suggest that fibers may also affect reproductive traits, but findings remain inconsistent, especially in adult boars. This study evaluated the effects of partially fermentable insoluble fiber (PFIF) on semen quality, behavior, and general health of adult boars. Thirty animals were assigned to a completely randomized design with two treatments: (1) CON: no fiber supplementation, and (2) PFIF: fiber supplementation (35 g/animal/day). Fiber was provided once daily for 120 consecutive days. During the period, semen was collected weekly and analyzed macroscopically and microscopically using the Computer-Assisted Sperm Analysis (CASA) system. Behavior was recorded weekly, one and three hours after feeding, based on a pre-established ethogram. Feed intake, perineal, and fecal scores were also evaluated. Fiber supplementation did not affect total motility, progressive motility, sperm concentration, fecal or perineal scores, or behavior. However, improvements were observed in sperm kinematics, with higher straight-line distance (DSL), linearity (LIN), and straightness (STR), as well as a tendency for increased straight-line velocity (VSL) and wobble (WOB). Conversely, a higher incidence of proximal cytoplasmic droplets was recorded in the fiber group, indicating more sperm maturation defects. Supplemented animals also showed reduced feed intake compared with controls, suggesting a satiety effect of the fiber. In conclusion, PFIF supplementation (35 g/animal/day offered once daily) in adult boars produced mixed outcomes, with improved sperm kinematics but increased maturation defects and only minor changes in feeding behavior, indicating a limited and inconsistent physiological response. Full article

The Denoising Wavelet Transform Convolutional Long Short-Term Memory Network (DWTConvLSTM) is a novel ionospheric total electron content (TEC) spatiotemporal prediction model proposed in 2025 that can simultaneously consider high-frequency and low-frequency features while suppressing noise. However, it also has flaws as it only considers unidirectional temporal features in spatiotemporal prediction. To address this issue, this paper adopts a bidirectional structure and designs a bidirectional DWTConvLSTM model that can simultaneously extract bidirectional spatiotemporal features from TEC maps. Furthermore, we integrate a lightweight attention mechanism called Convolutional Additive Self-Attention (CASA) to enhance important features and attenuate unimportant ones. The final model was named CASA-BiDWTConvLSTM. We validated the effectiveness of each improvement through ablation experiments. Then, a comprehensive comparison was performed on the 11-year Global Ionospheric Maps (GIMs) dataset, involving the proposed CASA-BiDWTConvLSTM model and several other state-of-the-art models such as C1PG, ConvGRU, ConvLSTM, and PredRNN. In this experiment, the dataset was partitioned into 7 years for training, 2 years for validation, and the final 2 years for testing. The experimental results indicate that the RMSE of CASA-BiDWTConvLSTM is lower than those of C1PG, ConvGRU, ConvLSTM, and PredRNN. Specifically, the decreases in RMSE during high solar activity years are 24.84%, 16.57%, 13.50%, and 10.29%, respectively, while the decreases during low solar activity years are 26.11%, 16.83%, 11.68%, and 7.04%, respectively. In addition, this article also verified the effectiveness of CASA-BiDWTConvLSTM from spatial and temporal perspectives, as well as on four geomagnetic storms. Full article

Carbon flow tracking and spatial pattern optimization at the scale of urban functional zones are key scientific challenges in achieving carbon neutrality. However, due to the complexity of carbon metabolism processes within urban functional zones, related studies remain limited. To address these scientific challenges, this study, based on the “source–sink–flow” ecosystem services framework, develops an integrated analytical approach at the scale of urban functional zones. The carbon balance is quantified using the CASA model in combination with multi-source data. A network model is employed to trace carbon flow pathways, identify critical nodes and interruption points, and optimize the urban spatial pattern through a low-carbon land use structure model. The research results indicate that the overall carbon balance in Hangzhou exhibits a spatial pattern of “deficit in the center and surplus in the periphery.” The main urban area shows a significant carbon deficit and relatively poor connectivity in the carbon flow network. Carbon sequestration services primarily flow from peripheral areas (such as Fuyang and Yuhang) with green spaces and agricultural functional zones toward high-emission residential–commercial and commercial–public functional zones in the central area. However, due to the interruption of multiple carbon flow paths, the overall carbon flow transmission capacity is significantly constrained. Through spatial optimization, some carbon deficit nodes were successfully converted into carbon surplus nodes, and disrupted carbon flow edges were repaired, particularly in the main urban area, where 369 carbon flow edges were restored, resulting in a significant improvement in the overall transmission efficiency of the carbon flow network. The carbon flow visualization and spatial optimization methods proposed in this paper provide a new perspective for urban carbon metabolism analysis and offer theoretical support for low-carbon city planning practices. Full article

Semen collection is an important component of conservation and animal husbandry. Semen quality is generally improved using voluntary collection methods, particularly artificial vaginas (AVs). Most commercially available AVs are tube-shaped with few species-specific design augmentations. As genitalia are highly variable across taxa, incorporating species-specific genital morphologies into AV designs may enhance collected semen quality. We compared dolphin semen quality using: (1) silicone bioinspired artificial vaginas (BAVs) that reflect the internal shape of dolphin vaginas, and (2) manual stimulation. Sperm motility and kinematic parameters of five bottlenose dolphins (Tursiops sp.) were assessed using computer-aided sperm analysis (CASA). Sperm collected using BAVs showed non-significant increases in median progressive and rapid motility, and increases in median and mean linear motility, supporting a sexual selection functional hypothesis for the biodiverse vaginal folds unique to whales, dolphins, and porpoises. Sperm concentration decreased with BAV collection, while no consistent trends were detected in volume, pH, velocity, or plasma membrane integrity. Modifications to AVs for other species that incorporate genital morphologies may also optimize collected semen quality for application to artificial insemination. Full article

Research on forest carbon sinks is crucial for mitigating global climate change and achieving carbon peaking and neutrality. However, studies at the county level remain relatively limited. This study utilized multi-source remote sensing data and the Carnegie–Ames-Stanford Approach (CASA) and soil respiration models to estimate the forest net ecosystem productivity (NEP) in Taoyuan County from 2000 to 2023. The spatiotemporal differentiation was analyzed using seasonal Mann–Kendall tests, Theil–Sen slope estimation, and standard deviation ellipses. The forest NEP for 2035 was predicted under multiple climate scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5) by applying a discrete coupling of the Patch-generating Land Use Simulation (PLUS) model, incorporating territorial spatial planning policy, and using the CASA model. The results indicated that the Taoyuan County forest NEP exhibited a fluctuating upward trend from 2000 to 2023, with higher (lower) values in the west/south (east/north). Under future warming and humidification, the overall forest NEP in Taoyuan County was projected to decrease by 2035, with predicted NEP values across scenarios ranking as SSP5-8.5 > SSP1-2.6 > SSP2-4.5. The findings offer practical insights for improving local forest management, optimizing forest configuration, and guiding county-level “dual-carbon” policies under future climate and land use change, thereby contributing to ecological sustainability. Full article