Search

This study explores the effect of steel ball size and proportion on mineral grinding characteristics using Discrete Element Method (DEM) simulations. Based on batch grinding kinetics, this paper analyzes the contact behavior during grinding, discussing particle breakage conditions and critical breakage energy. The results indicate that while increasing the size of the steel balls leads to higher collision energy, the collision probability decreases significantly; the opposite is true for smaller steel balls. Simulation results with different ball size combinations show that increasing the proportion of smaller balls does not significantly change the collision energy but greatly increases the collision probability, providing a basis for optimizing ball size distribution to improve grinding performance. Furthermore, appropriately increasing the proportion of smaller balls can reduce fluctuations in grinding energy consumption, thereby enhancing collision energy and collision probability while reducing energy costs. Liner wear results demonstrate that larger ball sizes increase liner wear, but different ball size combinations can effectively distribute the forces on the liner, reducing wear. [ABSTRACT FROM AUTHOR]

Light is a key environmental factor regulating reproduction in avians. However, the mechanism of light intensity regulating ovarian development is still unclear. In this study, 5-week-old (5 wk) partridge broiler breeders were randomly divided into a low-light-intensity group (LL group) and a natural-light-intensity group (NL group) (n = 100). In the rearing period (5 wk to 22 wk), the light intensity of the LL group and NL group were 0.41 ± 0.05 lux and 45.39 ± 1.09 lux, and in the laying period (23 wk to 32 wk) they were 23.92 ± 0.06 lux and 66.93 ± 0.76 lux, respectively. Samples were collected on 22 wk and 32 wk. The results showed that the LL group had a later age at first egg and a longer laying period than the NL group. Serum P4 and LH levels in the LL group were higher than in the NL group on 22 wk (p < 0.05). On 32 wk, P4, E2, LH and FSH levels in the LL group were lower than in the NL group (p < 0.05). Ovarian transcriptomics and metabolomics identified 128 differentially expressed genes (DEGs) and 467 differential metabolites (DMs) on 22 wk; 155 DEGs and 531 DMs on 32 wk between two groups. An enrichment analysis of these DEGs and DMs identified key signaling pathways, including steroid hormone biosynthesis, neuroactive ligand-receptor interaction. In these pathways, genes such as CYP21A1, SSTR2, and NPY may regulate the synthesis of metabolites, including tryptamine, triglycerides, and phenylalanine. These genes and metabolites may play a dominant role in the light-intensity regulation of ovarian development and laying performance in broiler breeders. [ABSTRACT FROM AUTHOR]

Collaborative distribution is the core of modern logistics, and the collaborative distribution centre is the physical location of distribution. This article aims to study the use of green computing energy management to promote a collaborative distribution optimization model and algorithm for an intelligent supply chain. A multiobjective genetic algorithm for energy management using green computing and a multiobjective hybrid genetic algorithm based on parallel selection methods are designed and implemented. A joint optimization model of VRP & VFP for logistics distribution is established. Collaborative system design and collaborative system operation inventory control issues are integrated. Considering uncertain demand, a multiobjective mixed-integer programming model of energy management using green computing is established to solve this problem. Experimental research shows that the optimal solution is found before the optimal operation of the 24th-generation collaborative system. The designed functional value of the collaborative system is 66109, and the optimal operating value of the collaborative system is 57348. [ABSTRACT FROM AUTHOR]

Myocardial infarction (MI) seriously threatens the health of elderly people, and reducing myocardial injury is of great significance for the treatment of MI. LncRNA-TTN-AS1 shows protective effects on cardiomyocyte injury, while the role of TTN-AS1 in MI remains unknown. CCK8, flow cytometry, and JC-1 staining assessed cell viability, apoptosis and mitochondrial membrane potential (MMP), respectively. Cellular reactive oxygen species (ROS) and secreted lactate dehydrogenase (LDH) levels were measured. The interactions between ELF5, TTN-AS1, PCBP2 and CDK6 were explored using ChIP, luciferase reporter assay, RIP, and pull-down. The severity of MI in mice was evaluated using TTC, H&E, and TUNEL staining. The data revealed that OGD/R significantly induced ROS, mitochondrial injury and apoptosis in AC16 cells, while overexpression of ELF5 or TTN-AS1 reversed these phenomena. ELF5 transcriptionally activated TTN-AS1 through binding with its promoter. TTN-AS1 increased CDK6 stability via recruiting PCBP2. CDK6 knockdown abolished the inhibitory effects of TTN-AS1 overexpression on OGD/R-induced myocardial injury. Furthermore, overexpression of TTN-AS1 or ELF5 alleviated MI progression in mice by upregulating CDK6. Collectively, TTN-AS1 transcriptionally regulated by ELF5 alleviated myocardial apoptosis and injury during MI via recruiting PCBP2 to increase CDK6 stability, which shed new lights on exploring new strategies against MI. [ABSTRACT FROM AUTHOR]

The paper considers an online scheduling problem with the effects of both learning and deterioration to minimize the total completion time. More specifically, we assume that the actual processing length of job Jj is p jr = p j r b + at , where pj is the initial processing time of Jj, t is the starting time of Jj, r is the seating arrangement position of Jj, b is the learning factor and a is the deterioration factor, respectively. For this problem, we show that the performance ratio of any deterministic online algorithm is not <2 and provide a best possible online algorithm DSBPT with a competitive ratio of 2. Furthermore, we also present a concise computational simulation study to verify the effectiveness and efficiency of the proposed algorithm DSBPT, as well as the management implications provided for decision-makers to production optimization. [ABSTRACT FROM AUTHOR]

Background: Previous studies have demonstrated the role of N6-methyladenosine (m6A) RNA methylation in various biological processes, our research is the first to elucidate its specific impact on LCAT mRNA stability and adipogenesis in poultry. Results: The 6 100-day-old female chickens were categorized into high (n = 3) and low-fat chickens (n = 3) based on their abdominal fat ratios, and their abdominal fat tissues were processed for MeRIP-seq and RNA-seq. An integrated analysis of MeRIP-seq and RNA-seq omics data revealed 16 differentially expressed genes associated with to differential m6A modifications. Among them, ELOVL fatty acid elongase 2 (ELOVL2), pyruvate dehydrogenase kinase 4 (PDK4), fatty acid binding protein 9 (PMP2), fatty acid binding protein 1 (FABP1), lysosomal associated membrane protein 3 (LAMP3), lecithin-cholesterol acyltransferase (LCAT) and solute carrier family 2 member 1 (SLC2A1) have ever been reported to be associated with adipogenesis. Interestingly, LCAT was down-regulated and expressed along with decreased levels of mRNA methylation methylation in the low-fat group. Mechanistically, the highly expressed ALKBH5 gene regulates LCAT RNA demethylation and affects LCAT mRNA stability. In addition, LCAT inhibits preadipocyte proliferation and promotes preadipocyte differentiation, and plays a key role in adipogenesis. Conclusions: In conclusion, ALKBH5 mediates RNA stability of LCAT through demethylation and affects chicken adipogenesis. This study provides a theoretical basis for further understanding of RNA methylation regulation in chicken adipogenesis. [ABSTRACT FROM AUTHOR]

The ideal and highly anticipated dressing for skin wounds should provide a moist environment, possess antibacterial properties, and ensure sustained drug release. In the present work, a hyaluronic acid‐based hydrogel was formed by cross‐linking crocetin and CaCO3@polyelectrolyte materials (CaCO3@PEM) microspheres with HA hydrogels via hydrogen bond and amido bonding (CaCO3@PEM@Cro@HA hydrogel, CPC@HA hydrogel). Moreover, the CPC@HA hydrogel had the capability of sustained, controlled release of calcium ions and crocetin via pH‐sensitive and accelerated skin wound healing. The experiment results showed that the CPC@HA hydrogel exhibited porous network structures, stable physical properties, and had antibacterial properties and biocompatibility in vitro. In addition, the CPC@HA hydrogel covering on the skin wound could reduce inflammation and promote wound healing. The high expression of angiogenic cytokines (CD31) and epidermal terminal differentiation markers (Loricrin) of wound healing tissue suggested the CPC@HA hydrogel also had the function of promoting the remodeling of regenerated skin. Overall, CPC@HA hydrogel has promising potential for clinical applications in accelerating skin wound repair. [ABSTRACT FROM AUTHOR]

This research explores the intricate-coupling relationship between typhoons and the ionosphere by the high-frequency surface wave radar's (HFSWR) over-the-horizon capabilities. This letter describes the gravity wave features in travelling ionospheric disturbances (TIDs) and ionospheric drift information. Further discussion is raised on the chaotic properties of gravity wave features using the Lyapunov exponents and chaotic attractors, particularly as they are influenced by typhoon. To predict these gravity wave features more accurately, a new model is developed by synergizing phase space reconstruction theory and statistical learning theory, a chaotic prediction model for gravity wave features constructed on a third-order Volterra filter. The experimental findings confirm that the gravity waves features detected via HFSWR present the hyperchaotic behaviour. More importantly, the innovative gravity wave prediction model based on chaotic attractor can capture the dynamics of the original chaotic system. Notably, the model's prediction accuracy has been improved by 98.6% after the introduction of phase space reconstruction modelling. [ABSTRACT FROM AUTHOR]