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In the contemporary era of globalization and social diversity, diversity and inclusive culture have become key aspects of human resource management. This culture promotes the integration of different backgrounds and perspectives, which can effectively enhance employees’ creativity, the company’s innovation capabilities, and market competitiveness. This article explores the importance of diversity and inclusive culture in human resource management and analyzes how to promote and practice this culture in practical work. Firstly, the definitions of diversity and inclusivity and their potential benefits to the enterprise have been determined. Secondly, it analyzed how to embody diversity and inclusivity in employee recruitment, development, and retention. In addition, discussions were held on how to develop this culture through training and leadership, as well as how to improve the overall working environment of the enterprise by establishing and promoting diversity and inclusivity policies. This article emphasizes that the cultivation of diversity and inclusivity is not only a moral requirement but also an important component of corporate strategy, which is crucial for attracting and maintaining global talent and consumers.

Osteosarcoma (OS) is a common bone malignancy with poor prognosis. We aimed to investigate the relationship between cuproptosis-related lncRNAs (CRLncs) and the survival outcomes of patients with OS. Transcriptome and clinical data of 86 patients with OS were downloaded from The Cancer Genome Atlas (TCGA). The GSE16088 dataset was downloaded from the Gene Expression Omnibus (GEO) database. The 10 cuproptosis-related genes (CRGs) were obtained from a recently published article on cuproptosis in . Combined analysis of OS transcriptome data and the GSE16088 dataset identified differentially expressed CRGs related to OS. Next, pathway enrichment analysis was performed. Co-expression analysis obtained CRLncs related to OS. Univariate COX regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used to construct the risk prognostic model of CRLncs. The samples were divided evenly into training and test groups to verify the accuracy of the model. Risk curve, survival, receiver operating characteristic (ROC) curve, and independent prognostic analyses were performed. Next, principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) analysis were performed. Single-sample gene set enrichment analysis (ssGSEA) was used to explore the correlation between the risk prognostic models and OS immune microenvironment. Drug sensitivity analysis identified drugs with potential efficacy in OS. Real-time quantitative PCR, Western blotting, and immunohistochemistry analyses verified the expression of CRGs in OS. Real-time quantitative PCR was used to verify the expression of CRLncs in OS. Six CRLncs that can guide OS prognosis and immune microenvironment were obtained, including three high-risk CRLncs (AL645608.6, AL591767.1, and UNC5B-AS1) and three low-risk CRLncs (CARD8-AS1, AC098487.1, and AC005041.3). Immune cells such as B cells, macrophages, T-helper type 2 (Th2) cells, regulatory T cells (Treg), and immune functions such as APC co-inhibition, checkpoint, and T-cell co-inhibition were significantly downregulated in high-risk groups. In addition, we obtained four drugs with potential efficacy for OS: AUY922, bortezomib, lenalidomide, and Z.LLNle.CHO. The expression of LIPT1, DLAT, and FDX1 at both mRNA and protein levels was significantly elevated in OS cell lines compared with normal osteoblast hFOB1.19. The mRNA expression level of AL591767.1 was decreased in OS, and that of AL645608.6, CARD8-AS1, AC005041.3, AC098487.1, and UNC5B-AS1 was upregulated in OS. CRLncs that can guide OS prognosis and the immune microenvironment and drugs that may have a potential curative effect on OS obtained in this study provide a theoretical basis for OS survival research and clinical decision-making.

The water resource tax reform played an important role in promoting sustainable development in China. Subsequent to the seven-year reform, the effectiveness evaluation of the policy in each pilot area and the exploration of the optimization path directly affected the promotion of water resource tax policy and the improvement of water use efficiency. Therefore, the theoretical framework of the water resource tax policy field was constructed to examine the mechanism of the three subsystems of policy scenario, policy orientation, and policy effect; fuzzy-set qualitative comparative analysis (fsQCA) was then used to evaluate and quantitatively compare the policy implementation effect and policy path in each pilot area, with emphasis put on three policy orientations, i.e., the decision and decomposition effect of policy goals, the selection and im plementation effect of policy tools, and the policy supervision and security effect. As shown by the research results: ① the water resource tax reform had effectively improved the efficiency of water resource utilization in the pilot areas; ② three pilot models of water resource tax policy had been extracted, namely the policy goal and tool-driven model centering on a single dimension of the policy field, the implementation-supervision dual drive model emphasizing the supervision and security effect of the policy, and the three-dimensional policy orientation linkage model that focused on the synergistic effect of the policy field; ③ strong heterogeneity existed in water resource tax policy implementation paths and effects in each pilot area. Accordingly, regional heterogeneity could be considered in the process of reform to construct institutionalized, precise, and differentiated reform implementation methods from the perspective of the policy field.

Despite significant advancements in total knee arthroplasty (TKA), managing postoperative pain remains a substantial clinical challenge. With advances in surgical techniques and pharmacology, TKA perioperative analgesic strategies continue to evolve, necessitating ongoing reassessment of current data. Multimodal analgesia has become the standard for perioperative pain management in TKA; however, variations in its specific components and applications across studies create challenges in selecting the optimal analgesic approach. Evaluating these pain management strategies is essential for understanding their benefits, limitations, and appropriate use, allowing the development of individualized perioperative analgesic plans. This review aims to summarize current research on perioperative pain control in TKA and assess the effectiveness of different analgesic interventions.

In view of the current debate about the relationship between lipids and deep venous thrombosis (DVT) in clinical studies, a two-sample Mendelian randomization (MR) study was conducted to clarify the effects of five circulating lipids (apolipoprotein A1, apolipoprotein B, low-density lipoprotein, high-density lipoprotein and triglycerides) on DVT from the perspective of genetic inheritance. Five lipids (exposure) were analysed by MR with DVT (outcome) from two different data sources. For the analysis, we used inverse variance weighting and a weighted mode, weighted median, simple mode and MR–Egger regression to analyse the effect of circulating lipids on DVT. In addition, we used the MR–Egger intercept test, Cochran’s Q test and “leave-one-out” sensitivity analysis to evaluate horizontal multiplicity, heterogeneity and stability, respectively, in the analysis. In the analysis, the two-sample Mendelian randomization analysis of five common circulating lipids and DVT showed that common circulating lipids had no causal effect on DVT, which is somewhat inconsistent with the findings of many published observational studies. Based on our results, our two-sample MR analysis failed to detect a statistically significant causal relationship between five common circulating lipids and DVT.

Background The incidence of pulmonary embolism complications in the literature ranges from 10 to 50%, with a 0.5–10% risk of fatal pulmonary embolism. However, the biological cause of pulmonary embolism is unknown. Methods This study used data from the Genome-Wide Association Study (GWAS) of Pulmonary Embolism and Human Blood Metabolites from the UK Biobank, and the data from subjects of European ancestry were analyzed. We explored the relationship between pulmonary embolism and blood metabolites in three ways. We first analyzed the genetic correlation between pulmonary embolism and human blood metabolites using the linkage disequilibrium score regression (LDSC) and then analyzed the causal relationship between pulmonary embolism and meaningful blood metabolites obtained from the LDSC, a procedure for which we used Mendelian randomization analysis. Finally, we obtained transcriptome sequencing data for patients with a pulmonary embolism from the GEO database, analyzed differentially expressed genes (DEGs) in patients with pulmonary embolism versus healthy populations, and compared the DEGs with the resulting blood metabolite genes to further validate the relationship between pulmonary embolism and blood metabolites. Result We found six human blood metabolites genetically associated with pulmonary embolism, stearic acid glycerol phosphate ethanolamine (correlation coefficient = 0.2582, P  = 0.0493), hydroxytryptophan (correlation coefficient = 0.2894, P  = 0.0435), and N1-methyladenosine (correlation coefficient = 0.0439, P  = 0.3728), and a significant causal relationship was discovered between hydroxytryptophan and pulmonary embolism. After screening microarray data from the GEO database, we performed differential gene analysis on the GSE19151 dataset and screened a total of 22,216 genes with P values less than 0.05, including 17,361 upregulated genes and 4854 downregulated genes. By comparing the resulting differentially expressed genes with six genes encoding blood metabolites, LIPC and NAT2 were found to be differentially expressed in association with pulmonary embolism.

In recent decades, population growth and economic development have greatly influenced the pattern of land use/land cover (LULC) in Rwanda. Nevertheless, LULC patterns and their underlying change mechanisms under future climate conditions are not well known. Therefore, it is particularly important to explore the direction of LULC transfer in the study area, identify the factors driving the transfer of different types of LULC and their changes, and simulate future LULC patterns under future climate conditions. Based on LULC analyses of Rwanda in 1990, 2000, 2010, and 2015, the LULC pattern of Rwanda in the next 30 years was simulated using an LULC transition matrix, random forest sampling, the Markov chain model, and the PLUS model. The results showed that LULC change in the study area primarily comprised a decrease in forest area and expansion of cropland area, accompanied by a small increase in grassland area and an annual increase in urban land area. Prior to 2000, the LULC in Rwanda was mainly converted from forest and grassland to cropland, with the ratio being 0.72:0.28. After 2010, the LULC was mainly converted from forest to grassland and cropland, with the ratio being 0.83:0.17. Changes in forests, grasslands, and cropland are driven by multiple factors, whereas changes in wetlands, water, urban land, and unused land are more likely to be driven by a single factor. The existing trend of LULC change will continue for the next 30 years, and the future LULC pattern will exhibit a trend in which cropland area will increase in the west and grassland area will decrease, whereas grassland area will increase in the east and cropland area will decrease.

Microencapsulation is a promising technique, which provides core materials with protective barrier, good stability, controlled release, and targeting delivery. Compared with the pharmaceutical, cosmetic, and textile industries, food processing has higher requirements for safety and hygiene and calls for quality and nutrition maintenance. This paper reviews the widely used polymers as microcapsule wall materials and the application in different food products, including plant-derived food, animal-derived food, and additives. Also, common preparation technologies (emphasizing advantages and disadvantages), including spray-drying, emulsification, freeze-drying, coacervation, layer-by-layer, extrusion, supercritical, fluidized bed coating, electrospray, solvent evaporation, nanocapsule preparation, and their correlation with selected wall materials in recent 10 years are presented. Personalized design and cheap, efficient, and eco-friendly preparation of microcapsules are urgently required to meet the needs of different processing or storage environments. Moreover, this review may provide a reference for the microencapsulation research interests and development on future exploration.

There is still some controversy about the relationship between lipids and venous thrombosis (VTE). A bidirectional Mendelian randomization (MR) study was conducted to clarify the causal relationship between three classical lipids (low-density lipoprotein (LDL), high-density lipoprotein (HDL) and triglycerides (TGs)) and venous thromboembolism (VTE) (deep venous thrombosis (DVT) and pulmonary embolism (PE)). Three classical lipids and VTE were analysed by bidirectional Mendelian randomization (MR). We used the random effect inverse variance weighted (IVW) model as the main analysis model and the weighted median method, simple mode method, weighted mode method and MR–Egger methods as supplementary methods. The leave-one-out test was used to determine the influence of outliers. The heterogeneity was calculated by using Cochran Q statistics in the MR–Egger and IVW methods. The intercept term in the MR‒Egger regression was used to indicate whether horizontal pleiotropy affected the results of the MR analysis. In addition, MR-PRESSO identified outlier single-nucleotide polymorphisms (SNPs) and obtained a stable result by removing outlier SNPs and then performing MR analysis. When we used three classical lipids (LDL, HDL and TGs) as exposure variables, no causal relationship between them and VTE (DVT and PE) was found. In addition, we did not find significant causal effects of VTE on the three classical lipids in reverse MR analysis. There is no significant causal relationship between three classical lipids (LDL, HDL and TGs) and VTE (DVT and PE) from a genetic point of view.

To deal with the highly nonlinear and time-varying characteristics of Batch Process, a model named adaptive stacking approximate kernel based broad learning system is proposed in this paper. This model innovatively introduces the approximate kernel based broad learning system (AKBLS) algorithm and the Adaptive Stacking framework, giving it strong nonlinear fitting ability, excellent generalization ability, and adaptive ability. The Broad Learning System (BLS) is known for its shorter training time for effective nonlinear processing, but the uncertainty brought by its double random mapping results in poor resistance to noisy data and unpredictable impact on performance. To address this issue, this paper proposes an AKBLS algorithm that reduces uncertainty, eliminates redundant features, and improves prediction accuracy by projecting feature nodes into the kernel space. It also significantly reduces the computation time of the kernel matrix by searching for approximate kernels to enhance its ability in industrial online applications. Extensive comparative experiments on various public datasets of different sizes validate this. The Adaptive Stacking framework utilizes the Stacking ensemble learning method, which integrates predictions from multiple AKBLS models using a meta-learner to improve generalization. Additionally, by employing the moving window method—where a fixed-length window slides through the database over time—the model gains adaptive ability, allowing it to better respond to gradual changes in industrial Batch Process. Experiments on a substantial dataset of penicillin simulations demonstrate that the proposed model significantly improves predictive accuracy compared to other common algorithms.