TSML: A New Pig Behavior Recognition Method Based on Two-Stream Mutual Learning Network

Changes in pig behavior are crucial information in the livestock breeding process, and automatic pig behavior recognition is a vital method for improving pig welfare. However, most methods for pig behavior recognition rely on human observation and deep learning. Human observation is often time-consuming and labor-intensive, while deep learning models with a large number of parameters can result in slow training times and low efficiency. To address these issues, this paper proposes a novel deep mutual learning enhanced two-stream pig behavior recognition approach. The proposed model consists of two mutual learning networks, which include the red-green-blue color model (RGB) and flow streams. Additionally, each branch contains two student networks that learn collaboratively to effectively achieve robust and rich appearance or motion features, ultimately leading to improved recognition performance of pig behaviors. Finally, the results of RGB and flow branches are weighted and fused to further improve the performance of pig behavior recognition. Experimental results demonstrate the effectiveness of the proposed model, which achieves state-of-the-art recognition performance with an accuracy of 96.52%, surpassing other models by 2.71%.

Non-linear association of liver enzymes with cognitive performance in the elderly: A cross-sectional study

BACKGROUND

Although liver metabolic dysfunction has been found to potentially elevate susceptibility to cognitive impairment and dementia, there is still insufficient evidence to explore the non-linear association of liver enzymes with cognitive performance. Therefore, we aimed to elucidate the non-linear relationship between liver enzymes and cognitive performance.

METHODS

In this cross-sectional study, 2764 individuals aged ≥ 60 who participated in the National Health and Nutrition Survey (NHANES) between 2011 and 2014 were included. The primary data comprised liver enzyme levels (alkaline phosphatase (ALP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), AST/ALT ratio, and gamma-glutamyl transferase (GGT)), and cognitive performance was the major measured outcome. The associations were analyzed using weighted multivariate logistic regression, subgroup analysis, a generalized additive model, smooth fitting curves, and threshold effects.

RESULTS

The results of the fully adjusted model indicated that ALP was negatively associated with the animal fluency test (AFT) score (OR = 1.48, 95% CI: 1.11-1.98), whereas ALT demonstrated a positive association with the consortium to establish a registry for Alzheimer's disease (CERAD) test score (OR = 0.72, 95% CI: 0.53-0.97). Additionally, the AST/ALT ratio was negatively associated with the global cognitive test (OR = 2.39, 95% CI: 1.53-3.73), CERAD (OR = 2.61, 95% CI: 1.77-3.84), and digit symbol substitution test (DSST) scores (OR = 2.51, 95% CI: 1.57-4.02). GGT was also negatively associated with the AFT score (OR = 1.16, 95% CI: 1.01-1.33) in unadjusted model. A non-linear relationship was observed between liver enzymes and the risk of cognitive impairment as assessed by the global cognitive test. Specifically, when ALP > 60 U/L, 0.77 < AST/ALT < 1.76, and 25 < GGT < 94 U/L, higher liver enzyme levels were significantly associated with an elevated cognitive impairment risk, while a lower cognitive impairment risk when ALT level was > 17 U/L.

CONCLUSIONS

There is a non-linear relationship between liver enzymes and cognitive performance, indicating that liver enzyme levels should be maintained within a certain level to mitigate the risk of cognitive impairment.

Exploring the Potential of Microbial Coalbed Methane for Sustainable Energy Development

By allowing coal to be converted by microorganisms into products like methane, hydrogen, methanol, ethanol, and other products, current coal deposits can be used effectively, cleanly, and sustainably. The intricacies of in situ microbial coal degradation must be understood in order to develop innovative energy production strategies and economically viable industrial microbial mining. This review covers various forms of conversion (such as the use of MECoM, which converts coal into hydrogen), stresses, and in situ use. There is ongoing discussion regarding the effectiveness of field-scale pilot testing when translated to commercial production. Assessing the applicability and long-term viability of MECoM technology will require addressing these knowledge gaps. Developing suitable nutrition plans and utilizing lab-generated data in the field are examples of this. Also, we recommend directions for future study to maximize methane production from coal. Microbial coal conversion technology needs to be successful in order to be resolved and to be a viable, sustainable energy source.

Classification of Hyperspectral Images of Explosive Fragments Based on Spatial-Spectral Combination

The identification and recovery of explosive fragments can provide a reference for the evaluation of explosive power and the design of explosion-proof measures. At present, fragment detection usually uses a few bands in the visible light or infrared bands for imaging, without fully utilizing multi-band spectral information. Hyperspectral imaging has high spectral resolution and can provide multidimensional reference information for the fragments to be classified. Therefore, this article proposed a spatial-spectral joint method for explosive fragment classification by combining hyperspectral imaging technology. In a laboratory environment, this article collected hyperspectral images of explosion fragments scattered in simulated scenes. In order to extract effective features from redundant spectral information and improve classification accuracy, this paper adopted a classification framework based on deep learning. This framework used a convolutional neural network-bidirectional long short-term memory network (CNN-BiLSTM) as the spectral information classification model and a U-shaped network (U-Net) as the spatial segmentation model. The experimental results showed that the overall accuracy exceeds 95.2%. The analysis results indicated that the method of spatial-spectral combination can accurately identify explosive fragment targets. It validated the feasibility of using hyperspectral imaging for explosive fragment classification in laboratory environments. Due to the complex environment of the actual explosion site, this study still needs to be validated in outdoor environments. Our next step is to use airborne hyperspectral imaging to identify explosive fragments in outdoor environments.

Caregiver experiences of caring for family members with urostomy: a qualitative study

OBJECTIVE

In China, bladder tumors rank first for morbidity and mortality among urological and reproductive system tumors. Total radical cystectomy plus urinary flow conversion is the gold standard for the treatment of muscle-layer invasive bladder cancer. With an increasing number of radical cystectomies each year, the number of patients living with urostomy is growing. After discharge, primary care of urostomy patients is given at home, and high demands are placed on home caregivers due to issues of privacy and the complexity of replacing the urostomy device. This research explored the challenges faced by the family caregivers of urostomy patients.

METHODS

We used descriptive qualitative research methods to conduct interviews with twenty-five family caregivers of patients with urostomy. Survey subjects were from five general hospitals. All interviews were recorded, transcribed, and analyzed using thematic analysis.

RESULTS

Three critical challenges were identified-confusion, family crisis, and struggle psychology. Within these three themes, six sub-themes were constructed by coders. They were knowledge and skill deficiency, strong insecurities and uncertainties, role conflict, economic burden, emotional overwhelmed and calm acceptance.

CONCLUSION

Family caregivers play a critical role in patient care, and especially in urostomy care. Caregiving is associated with significant challenges that hinder the family caregiver's ability to effectively care for the patient, further diminishing the caregiver's quality of life. Therefore, healthcare professionals should consider the challenges faced by family caregivers and take measures to obviate them through education, preparation, and support.

Path Planning Algorithm for Manipulators in Complex Scenes Based on Improved RRT

Aiming at the problems of a six-degree-of-freedom robotic arm in a three-dimensional multi-obstacle space, such as low sampling efficiency and path search failure, an improved fast extended random tree (RRT*) algorithm for robotic arm path planning method (abbreviated as HP-APF-RRT*) is proposed. The algorithm generates multiple candidate points per iteration, selecting a sampling point probabilistically based on heuristic values, thereby optimizing sampling efficiency and reducing unnecessary nodes. To mitigate increased search times in obstacle-dense areas, an artificial potential field (APF) approach is integrated, establishing gravitational and repulsive fields to guide sampling points around obstacles toward the target. This method enhances path search in complex environments, yielding near-optimal paths. Furthermore, the path is simplified using the triangle inequality, and redundant intermediate nodes are utilized to further refine the path. Finally, the simulation experiment of the improved HP-APF-RRT* is executed on Matlab R2022b and ROS, and the physical experiment is performed on the NZ500-500 robotic arm. The effectiveness and superiority of the improved algorithm are determined by comparing it with the existing algorithms.

Insulin-Like Growth Factor Signaling in Alzheimer's Disease: Pathophysiology and Therapeutic Strategies

Alzheimer's disease (AD) is the leading cause of dementia among the elderly population, posing a significant public health challenge due to limited therapeutic options that merely delay cognitive decline. AD is associated with impaired energy metabolism and reduced neurotrophic signaling. The insulin-like growth factor (IGF) signaling pathway, crucial for central nervous system (CNS) development, metabolism, repair, cognition, and emotion regulation, includes IGF-1, IGF-2, IGF-1R, IGF-2R, insulin receptor (IR), and six insulin-like growth factor binding proteins (IGFBPs). Research has identified abnormalities in IGF signaling in individuals with AD and AD models. Dysregulated expression of IGFs, receptors, IGFBPs, and disruptions in downstream phosphoinositide 3-kinase-protein kinase B (PI3K/AKT) and mitogen-activated protein kinase (MAPK) pathways collectively increase AD susceptibility. Studies suggest modulating the IGF pathway may ameliorate AD pathology and cognitive decline. This review explores the CNS pathophysiology of IGF signaling in AD progression and assesses the potential of targeting the IGF system as a novel therapeutic strategy. Further research is essential to elucidate how aberrant IGF signaling contributes to AD development, understand underlying molecular mechanisms, and evaluate the safety and efficacy of IGF-based treatments.

[Evaluation of peripheral blood T-lymphocyte subpopulations features in patients with hepatitis B virus-related acute-on-chronic liver failure based on single-cell sequencing technology]

Objective: T lymphocyte exhaustion is an important component of immune dysfunction. Therefore, exploring peripheral blood-exhausted T lymphocyte features in patients with hepatitis B virus-related acute-on-chronic liver failure may provide potential therapeutic target molecules for ACLF immune dysfunction. Methods: Six cases with HBV-ACLF and three healthy controls were selected for T-cell heterogeneity detection using the single-cell RNA sequencing method. In addition, exhausted T lymphocyte subpopulations were screened to analyze their gene expression features, and their developmental trajectories quasi-timing. An independent sample t-test was used to compare the samples between the two groups. Results: Peripheral blood T lymphocytes in HBV-ACLF patients had different differentiation trajectories with different features distinct into eight subpopulations. Among them, the CD4(+)TIGIT(+) subsets (P = 0.007) and CD8(+)LAG3(+) (P = 0.010) subsets with highly exhausted genes were significantly higher than those in healthy controls. Quasi-time analysis showed that CD4(+)TIGIT(+) and CD8(+)LAG3(+) subsets appeared in the late stage of T lymphocyte differentiation, suggesting the transition of T lymphocyte from naïve-effector-exhausted during ACLF pathogenesis. Conclusion: There is heterogeneity in peripheral blood T lymphocyte differentiation in patients with HBV-ACLF, and the number of exhausted T cells featured by CD4(+)TIGIT(+)T cell and CD8(+)LAG3(+) T cell subsets increases significantly, suggesting that T lymphocyte immune exhaustion is involved in the immune dysfunction of HBV-ACLF, thereby identifying potential effective target molecules for improving ACLF patients' immune function.

Examining Carotenoid Metabolism Regulation and Its Role in Flower Color Variation in Brassica rapa L

Carotenoids are vital organic pigments that determine the color of flowers, roots, and fruits in plants, imparting them yellow, orange, and red hues. This study comprehensively analyzes carotenoid accumulation in different tissues of the Brassica rapa mutant "YB1", which exhibits altered flower and root colors. Integrating physiological and biochemical assessments, transcriptome profiling, and quantitative metabolomics, we examined carotenoid accumulation in the flowers, roots, stems, and seeds of YB1 throughout its growth and development. The results indicated that carotenoids continued to accumulate in the roots and stems of YBI, especially in its cortex, throughout plant growth and development; however, the carotenoid levels in the petals decreased with progression of the flowering stage. In total, 54 carotenoid compounds were identified across tissues, with 30 being unique metabolites. Their levels correlated with the expression pattern of 22 differentially expressed genes related to carotenoid biosynthesis and degradation. Tissue-specific genes, including CCD8 and NCED in flowers and ZEP in the roots and stems, were identified as key regulators of color variations in different plant parts. Additionally, we identified genes in the seeds that regulated the conversion of carotenoids to abscisic acid. In conclusion, this study offers valuable insights into the regulation of carotenoid metabolism in B. rapa, which can guide the selection and breeding of carotenoid-rich varieties.

Deficient gait function despite effect index of the Western Ontario and McMaster university osteoarthritis index score considered cured one year after bilateral total knee arthroplasty

BACKGROUND

To clarify the value of gait analysis and its consistency with traditional scoring scales for the evaluation of knee joint function after total knee arthroplasty (TKA).

METHODS

This study included 25 patients with knee osteoarthritis (KOA) who underwent bilateral TKA, and 25 conditionally matched healthy individuals, categorised into the experimental and control groups, respectively. Patients in the experimental group underwent gait analysis and Western Ontario and McMaster University Osteoarthritis Index (WOMAC) evaluation before and 1 year after TKA. Weight-bearing balance and walking stability were assessed using discrete trends of relevant gait indicators. Pearson's correlation analysis was performed on the gait and WOMAC score data of the experimental group before and after TKA.

RESULTS

One year after TKA, patients' gait indices (except gait cycle) were significantly better than before surgery, but significantly worse than that of the control group (P < 0.01). The shape of patients' plantar pressure curves did not return to normal. Additionally, the discrete trend of related gait indicators reflecting weight-bearing balance and walking stability were smaller than before TKA, but still greater than that of the control group. The WOMAC scores of patients 1 year after TKA were significantly lower than those before TKA (P < 0.001), and the efficacy index was > 80%. The WOMAC scores and gait analysis results were significantly correlated before TKA (P < 0.05).

CONCLUSIONS

Gait analysis should be used in conjunction with scoring scales to assess joint functions.